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Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Tuberculosis (TB) is an airborne disease caused by Mycobacterium tuberculosis. It is imperative to detect cases of TB as early as possible because if left untreated, there is a 70% chance of a patient dying within 10 years. The necessity for supplementary tools has increased in mid to low-income countries due to the rise of automation in healthcare sectors. The already limited resources are being heavily allocated towards controlling other dangerous diseases. Modern digital radiography (DR) machines, used for screening chest X-rays of potential TB victims are very practical. Coupled with computer-aided detection (CAD) with the aid of artificial intelligence, radiologists working in this field can really help potential patients. In this study, progressive resizing is introduced for training models to perform automatic inference of TB using chest X-ray images. ImageNet fine-tuned Normalization-Free Networks (NFNets) are trained for classification and the Score-Cam algorithm is utilized to highlight the regions in the chest X-Rays for detailed inference on the diagnosis. The proposed method is engineered to provide accurate diagnostics for both binary and multiclass classification. The models trained with this method have achieved 96.91% accuracy, 99.38% AUC, 91.81% sensitivity, and 98.42% specificity on a multiclass classification dataset. Moreover, models have also achieved top-1 inference metrics of 96% accuracy and 98% AUC for binary classification. The results obtained demonstrate that the proposed method can be used as a secondary decision tool in a clinical setting for assisting radiologists. metadata Acharya, Vasundhara; Dhiman, Gaurav; Prakasha, Krishna; Bahadur, Pranshu; Choraria, Ankit; M, Sushobhitha; J, Sowjanya; Prabhu, Srikanth; Chadaga, Krishnaraj; Viriyasitavat, Wattana; Kautish, Sandeep y Haldorai, Anandakumar mail SIN ESPECIFICAR (2022) AI-Assisted Tuberculosis Detection and Classification from Chest X-Rays Using a Deep Learning Normalization-Free Network Model. Computational Intelligence and Neuroscience, 2022. pp. 1-19. ISSN 1687-5265
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
This project encompasses a current topic which has influence in the whole humanity. This is related to the importance of caring for the environment. Taking as reference this topic, the project is intended to provoke a positive impact in a group of learners in terms of improving English learning skills. In order to achieve the goals stated in this project, it was focused on the CLIL methodology. Besides, it took place in Leiva, Nariño. This is a small town located in the south of Colombia in the middle of the mountain chain. The place is rich in nature but it does not have a treatment of waste in terms of recycling. For this reason, It is considered important to take into consideration this issue and raise consciousness with the students of ninth grade of San Gerardo school through the learning of English. Besides, it is significant because learners could be the pioneers of implementing alternatives to the lack of treatment of waste in the town.
metadata
Argote Ibarra, Angiee Julieth
mail
anjuli8@yahoo.es
(2022)
Action Research for Designing an EFL CLIL, Communicative and Task-Based Material Integrating Environmental Contents for ninth grade in students at I.E. San Gerardo of A1 Level.
Masters thesis, SIN ESPECIFICAR.
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
The use of strategies in the classroom plays an important role in the student/teacher process, so the skills provided by the teacher are an integral part of this process. For this reason, the qualities that the teacher develops through experience and professional development are often defined as important characteristics for the final outcomes of each student. In the development of a new language, the use of viable and focused strategies helps to have a process rich in results, especially in the development of communication skills, where students can express each of their ideas in a real context.
metadata
Angulo Luna, Lina Marcela
mail
linamar2888@hotmail.com
(2022)
An Action Research for Implementing Didactic Strategies Increasing EFL Teachers' Agency and Improving the EFL Learning Process in a Study Group in a School in Monteria, Colombia.
Masters thesis, SIN ESPECIFICAR.
Artículo
Materias > Ciencias Sociales
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Innovation plays a pivotal role in the progress and goodwill of an organization, and its ability to thrive. Consequently, the impact analysis of innovation on the performance of an organization holds great importance. This paper presents a two-stage analytical framework to examine the impact of business innovation on a firm’s performance, especially firms from the manufacturing sector. The prime objective is to identify the factors that have an impact on firm-level innovation, and to examine the impact of firm-level innovation on business performance. The framework and its analysis are based on the latest World Bank enterprise survey, with a sample size of 696 manufacturing firms. The first stage of the proposed framework establishes the analytical results through Bivariate Probit, which indicates that research and development (R&D) has a significantly positive impact on the product, process, marketing, and organizational innovations. It thus highlights the important role of the allocation of lump-sum amounts for R&D activities. The statistical analysis shows that innovation does not depend on the size of the firms. Moreover, the older firms are found to be wiser at conducting R&D than newer firms that are reluctant to take risks. The second stage of the proposed framework separately analyzes the impacts of the product and organizational innovation, and the process and marketing innovation on the firm performance, and finds them to be statistically significant and insignificant, respectively.
metadata
Aslam, Mahrukh; Shafi, Imran; Ahmad, Jamil; Álvarez, Roberto Marcelo; Miró Vera, Yini Airet; Soriano Flores, Emmanuel y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, roberto.alvarez@uneatlantico.es, yini.miro@uneatlantico.es, emmanuel.soriano@uneatlantico.es, SIN ESPECIFICAR
(2022)
An Analytical Framework for Innovation Determinants and Their Impact on Business Performance.
Sustainability, 15 (1).
p. 458.
ISSN 2071-1050
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Behavioral economics and artificial intelligence (AI) have been two rapidly growing fields of research over the past few years. While behavioral economics aims to combine concepts from psychology, sociology, and neuroscience with classical economic thoughts to understand human decision-making processes in the complex economic environment, AI on the other hand, focuses on creating intelligent machines that can mimic human cognitive abilities such as learning, problem-solving, decision-making, and language understanding. The intersection of these two fields has led to thrilling research theories and practical applications. This study provides a bibliometric analysis of the literature on AI and behavioral economics to gain insight into research trends in this field. We conducted this bibliometric analysis using the Web of Science database on articles published between 2012 and 2022 that were related to AI and behavioral economics. VOSviewer and Bibliometrix R package were utilized to identify influential authors, journals, institutions, and countries in the field. Network analysis was also performed to identify the main research themes and their interrelationships. The analysis revealed that the number of publications on AI and behavioral economics has been increasing steadily over the past decade. We found that most studies focused on customer and consumer behavior, including topics such as decision-making under uncertainty, neuroeconomics, and behavioral game theory, combined mainly with machine learning and deep learning techniques. We also identified several emerging themes, including the use of AI in nudging and prospect theory in behavioral finance, as well as undeveloped themes such as AI-driven behavioral macroeconomics. The findings suggests that there is a need for more interdisciplinary collaboration between researchers in behavioral economics and AI. We also suggest that future research on AI and behavioral economics further consider the ethical implications of using AI and behavioral insights in decision-making. This study can serve as a valuable resource for researchers interested in AI and behavioral economics.
metadata
Aoujil, Zakaria; Hanine, Mohamed; Soriano Flores, Emmanuel; Samad, Md Abdu y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, emmanuel.soriano@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Artificial Intelligence and Behavioral Economics: A Bibliographic Analysis of Research Field.
IEEE Access.
p. 1.
ISSN 2169-3536
(En Prensa)
Artículo Materias > Biomedicina Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Objective: Women with gynecologic cancer may sufer from pelvic foor dysfunction (PFD). Before radiotherapy, prehabilitation with pelvic foor muscle exercises (PFME) and vaginal dilator (VD) might prevent it and foster sexual life. This study aims to explore the experience of gynecologic cancer patients getting external beam radiation treatments regarding barriers to and facilitators of adherence to a prehabilitation program to prevent PFD. Methods: This qualitative research with thematic content analysis included 11 women with gynecologic cancer and diferent levels of adherence to PFME and VD. Participants were interviewed based on a semi-structured script. The information was analyzed manually, assisted with Nvivo12® software, and triangulated with open coding. Results: High self-motivation, desire to improve their health, symptoms of improvement, availability of time, the desire to resume sexual life, and the support of the partner were facilitators of adherence. The instructional exercise audio, clarity of the information, and closer communication with the physical therapist were also valued. The main barriers were general malaise secondary to oncological treatments, forgetfulness, lack of time, misinformation, lack of coordination with the treatment team, discomfort with the VD, and a feeling of shame. Feedback from the attending physician was a facilitator when present or a barrier when absent. Conclusion: These barriers and facilitators should be considered when designing and implementing preventive programs with PFME and VD. Behavioral counselling should consider the desire to remain sexually active; in such cases, including the partner in the therapeutic process is appraised. Otherwise, the focus should be on benefts for maintenance of pelvic foor function. metadata Araya, Paulina; Roa-Alcaino, Sonia; Celedón, Claudia; Cuevas-Said, Mónica; de Sousa Dantas, Diego y Sacomori, Cinara mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, csacomori@yahoo.com.br (2022) Barriers to and facilitators of adherence to pelvic floor muscle exercises and vaginal dilator use among gynecologic cancer patients: a qualitative study. Supportive Care in Cancer. ISSN 0941-4355
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Cerrado
Inglés
Betalains are water-soluble, nitrogen-containing vacuolar pigment and can be divided into two subclasses: the yellow – orange betaxanthins and the red – violet betacyanin. These pigments can be found mainly in Latin America, but also in some parts of Asia, Africa, Australia and in the Mediterranean area. In this work an overview related with the status of research about betalains extracted from Opuntia spp and the enforces made to evaluate their positive incidence in the human body is provided. Several studies enhance their anticancer, anti-inflammatory and antioxidant properties. They also exhibit antimicrobial and antidiabetic effect. Taking into account these properties, betalains seem to be a promising natural alternative as a colorant to replace the synthetic ones in the food additive industry. In addition, the use of Opuntia spp fruits as possible colorant sources in the Food Industry, may contribute positively to the sustainable development in semi-arid regions.
metadata
Armas Diaz, Yasmany; Qi, Zexiu; Yang, Bei; Martínez López, Nohora Milena; Briones Urbano, Mercedes y Cianciosi, Danila
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, nohora.martinez@uneatlantico.es, mercedes.briones@uneatlantico.es, SIN ESPECIFICAR
(2023)
Betalains: The main bioactive compounds of Opuntia spp and their possible health benefits in the Mediterranean diet.
Mediterranean Journal of Nutrition and Metabolism, 16 (3).
pp. 181-190.
ISSN 1973798X
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The wheat crop that fulfills 35% of human food demand is facing several problems due to a lack of transparency, security, reliability, and traceability in the existing agriculture supply chain. Many systems have been developed for the agriculture supply chain to overcome such issues, however, monopolistic centralized control is the biggest hurdle to realizing the use of such systems. It has eventually gained consumers’ trust in branded products and rejected other products due to the lack of traceable supply chain information. This study proposes a blockchain-based framework for supply chain traceability which provides trustable, transparent, secure, and reliable services for the wheat crop. A crypto token called wheat coin (WC) has been introduced to keep track of transactions among the stakeholders of the wheat supply chain. Moreover, an initial coin offering (ICO) of WC, crypto wallets, and an economic model are proposed. Furthermore, a smart contract-based transaction system has been devised for the transparency of wheat crop transactions and conversion of WC to fiat and vice versa. We have developed the interplanetary file system (IPFS) to improve data availability, security, and transparency which stores encrypted private data of farmers, businesses, and merchants. Lastly, the results of the experiments show that the proposed framework shows better performance as compared to previous crop supply chain solutions in terms of latency to add-blocks, per-minute transactions, average gas charge for the transaction, and transaction verification time. Performance analysis with Bitcoin and Ethereum shows the superior performance of the proposed system.
metadata
Alam, Shadab; Farooq, Muhammad Shoaib; Ansari, Zain Khalid; Alvi, Atif; Rustam, Furqan; Díez, Isabel De La Torre; Vidal Mazón, Juan Luis; Rodríguez Velasco, Carmen Lilí y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR
(2024)
Blockchain based transparent and reliable framework for wheat crop supply chain.
PLOS ONE, 19 (1).
e0295036.
ISSN 1932-6203
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
SIN ESPECIFICAR
metadata
Ali, Omer; Abbas, Qamar; Mahmood, Khalid; Bautista Thompson, Ernesto; Arambarri, Jon y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, ernesto.bautista@unini.edu.mx, jon.arambarri@uneatlantico.es, SIN ESPECIFICAR
(2023)
Competitive Coevolution-Based Improved Phasor Particle Swarm Optimization Algorithm for Solving Continuous Problems.
Mathematics, 11 (21).
p. 4406.
ISSN 2227-7390
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Renewable energy solutions are appropriate for on-grid and off-grid applications, acting as a supporter for the utility network or rural locations without the need to develop or extend costly and difficult grid infrastructure. As a result, hybrid renewable energy sources have become a popular option for grid-connected or standalone systems. This paper examines hybrid renewable energy power production systems with a focus on energy sustainability, reliability due to irregularities, techno-economic feasibility, and being environmentally friendly. In attaining a reliable, clean, and cost-effective system, sizing optimal hybrid renewable energy sources (HRES) is a crucial challenge. The presenters went further to outline the best sizing approach that can be used in HRES, taking into consideration the key components, parameters, methods, and data. Moreover, the goal functions, constraints from design, system components, optimization software tools, and meta-heuristic algorithm methodologies were highlighted for the available studies in this timely synopsis of the state of the art. Additionally, current issues resulting from scaling HRES were also identified and discussed. The latest trends and advances in planning problems were thoroughly addressed. Finally, this paper provides suggestions for further research into the appropriate component sizing in HRES.
metadata
Agajie, Takele Ferede; Ali, Ahmed; Fopah-Lele, Armand; Amoussou, Isaac; Khan, Baseem; Rodríguez Velasco, Carmen Lilí y Tanyi, Emmanuel
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR
(2023)
A Comprehensive Review on Techno-Economic Analysis and Optimal Sizing of Hybrid Renewable Energy Sources with Energy Storage Systems.
Energies, 16 (2).
p. 642.
ISSN 1996-1073
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
Designing a course is paramount for English language teachers and teachers in general, as learning how to do this is connected to real situations such as, the context in which learners are immersed and with their needs to successfully enhance their communicative competence. Thus, this project consists of the design of a course to improve the learners' writing skill at tertiary level from a university located in the central region of Chile. This projects guides teachers on the different stages to design a course as well as the writing course designed for the learners, following the principles of TBLT.
metadata
Ayala Ayala, Alejandro Alfredo
mail
ar04912@gmail.com
(2022)
Design of a EFL Task-based Course to Enhance the Linguistic Writing Skill of Learners in a General English Program at O’Higgins University.
Masters thesis, SIN ESPECIFICAR.
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Requirements specifications written in natural language enable us to understand a program’s intended functionality, which we can then translate into operational software. At varying stages of requirement specification, multiple ambiguities emerge. Ambiguities may appear at several levels including the syntactic, semantic, domain, lexical, and pragmatic levels. The primary objective of this study is to identify requirements’ pragmatic ambiguity. Pragmatic ambiguity occurs when the same set of circumstances can be interpreted in multiple ways. It requires consideration of the context statement of the requirements. Prior research has developed methods for obtaining concepts based on individual nodes, so there is room for improvement in the requirements interpretation procedure. This research aims to develop a more effective model for identifying pragmatic ambiguity in requirement definition. To better interpret requirements, we introduced the Concept Maximum Matching (CMM) technique, which extracts concepts based on edges. The CMM technique significantly improves precision because it permits a more accurate interpretation of requirements based on the relative weight of their edges. Obtaining an F-measure score of 0.754 as opposed to 0.563 in existing models, the evaluation results demonstrate that CMM is a substantial improvement over the previous method.
metadata
Aslam, Khadija; Iqbal, Faiza; Altaf, Ayesha; Hussain, Naveed; Gracia Villar, Mónica; Soriano Flores, Emmanuel; Diez, Isabel De La Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, monica.gracia@uneatlantico.es, emmanuel.soriano@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Detecting Pragmatic Ambiguity in Requirement Specification Using Novel Concept Maximum Matching Approach Based on Graph Network.
IEEE Access.
p. 1.
ISSN 2169-3536
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Non-Insulin-Dependent Diabetes Mellitus (NIDDM) is a chronic health condition caused by high blood sugar levels, and if not treated early, it can lead to serious complications i.e. blindness. Human Activity Recognition (HAR) offers potential for early NIDDM diagnosis, emerging as a key application for HAR technology. This research introduces DiabSense, a state-of-the-art smartphone-dependent system for early staging of NIDDM. DiabSense incorporates HAR and Diabetic Retinopathy (DR) upon leveraging the power of two different Graph Neural Networks (GNN). HAR uses a comprehensive array of 23 human activities resembling Diabetes symptoms, and DR is a prevalent complication of NIDDM. Graph Attention Network (GAT) in HAR achieved 98.32% accuracy on sensor data, while Graph Convolutional Network (GCN) in the Aptos 2019 dataset scored 84.48%, surpassing other state-of-the-art models. The trained GCN analyzed retinal images of four experimental human subjects for DR report generation, and GAT generated their average duration of daily activities over 30 days. The daily activities in non-diabetic periods of diabetic patients were measured and compared with the daily activities of the experimental subjects, which helped generate risk factors. Fusing risk factors with DR conditions enabled early diagnosis recommendations for the experimental subjects despite the absence of any apparent symptoms. The comparison of DiabSense system outcome with clinical diagnosis reports in the experimental subjects was conducted using the A1C test. The test results confirmed the accurate assessment of early diagnosis requirements for experimental subjects by the system. Overall, DiabSense exhibits significant potential for ensuring early NIDDM treatment, improving millions of lives worldwide.
metadata
Alam, Md Nuho Ul; Hasnine, Ibrahim; Bahadur, Erfanul Hoque; Masum, Abdul Kadar Muhammad; Briones Urbano, Mercedes; Masías Vergara, Manuel; Uddin, Jia; Ashraf, Imran y Samad, Md. Abdus
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, mercedes.briones@uneatlantico.es, manuel.masias@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
DiabSense: early diagnosis of non-insulin-dependent diabetes mellitus using smartphone-based human activity recognition and diabetic retinopathy analysis with Graph Neural Network.
Journal of Big Data, 11 (1).
ISSN 2196-1115
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Ubiquitous data monitoring and processing with minimal latency is one of the crucial challenges in real-time and scalable applications. Internet of Things (IoT), fog computing, edge computing, cloud computing, and the edge of things are the spine of all real-time and scalable applications. Conspicuously, this study proposed a novel framework for a real-time and scalable application that changes dynamically with time. In this study, IoT deployment is recommended for data acquisition. The Pre-Processing of data with local edge and fog nodes is implemented in this study. The threshold-oriented data classification method is deployed to improve the intrusion detection mechanism’s performance. The employment of machine learning-empowered intelligent algorithms in a distributed manner is implemented to enhance the overall response rate of the layered framework. The placement of respondent nodes near the framework’s IoT layer minimizes the network’s latency. For economic evaluation of the proposed framework with minimal efforts, EdgeCloudSim and FogNetSim++ simulation environments are deployed in this study. The experimental results confirm the robustness of the proposed system by its improvised threshold-oriented data classification and intrusion detection approach, improved response rate, and prediction mechanism. Moreover, the proposed layered framework provides a robust solution for real-time and scalable applications that changes dynamically with time.
metadata
Aldribi, Abdulaziz; Singh, Aman y Breñosa, Jose
mail
SIN ESPECIFICAR, aman.singh@uneatlantico.es, josemanuel.brenosa@uneatlantico.es
(2023)
Edge of Things Inspired Robust Intrusion Detection Framework for Scalable and Decentralized Applications.
Computer Systems Science and Engineering, 46 (3).
pp. 3865-3881.
ISSN 0267-6192
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español La proliferación de proyectos de desarrollo en África en general y en Camerún en particular durante la última década contrasta con sus resultados que en la mayoría de los casos son ambiguos. Estas actuaciones dependen en gran medida de las estrategias y decisiones adoptadas por los actores que interactúan. El análisis estratégico es, por tanto, un enfoque fundamental para comprender mejor los resultados de los programas de desarrollo. En este marco encaja el método MACTOR (Godet, 2007), una aplicación de la racionalidad actancial en el análisis de las interacciones humanas. Permite identificar a todos los actores activos y pasivos que intervienen en un proyecto y definir la matriz de alianzas, conflictos, estrategias, tácticas y objetivos que persiguen estos actores. Este método abre la vía a un análisis activo de la gestión de los proyectos de desarrollo para identificar mejor sus puntos fuertes y débiles. Este artículo es una revisión sistemática de las cuestiones en juego en este método y su aplicación en el contexto camerunés. Destaca los determinantes teóricos del método y su relevancia en el análisis de gestión de proyectos bajo una racionalidad actancial. metadata Assontia Djoudji, Gaston; en Bediang, Roger Kolokosso y Begnikin, Jean Joël mail gaston.assontia@doctorado.unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR (2022) El método MACTOR para analizar los procesos de gestión de los proyectos y programas de desarrollo en África. Project Design and Management, 4 (1). pp. 1-14. ISSN 2683-1597
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Humans can carry various diseases, some of which are poorly understood and lack comprehensive solutions. Such a disease can exists in human eye that can affect one or both eyes is diabetic retinopathy (DR) which can impair function, vision, and eventually result in permanent blindness. It is one of those complex complexities. Therefore, early detection of DR can significantly reduce the risk of vision impairment by appropriate treatment and necessary precautions. The primary aim of this study is to leverage cutting-edge models trained on diverse image datasets and propose a CNN model that demonstrates comparable performance. Specifically, we employ transfer learning models such as DenseNet121, Xception, Resnet50, VGG16, VGG19, and InceptionV3, and machine learning models such as SVM, and neural network models like (RNN) for binary and multi-class classification. It has been shown that the proposed approach of multi-label classification with softmax functions and categorical cross-entropy works more effectively, yielding perfect accuracy, precision, and recall values. In particular, Xception achieved an impressive 82% accuracy among all the transfer learning models, setting a new benchmark for the dataset used. However, our proposed CNN model shows superior performance, achieving an accuracy of 95.27% on this dataset, surpassing the state-of-the-art Xception model. Moreover, for single-label (binary classifications), our proposed model achieved perfect accuracy as well. Through exploration of these advances, our objective is to provide a comprehensive overview of the leading methods for the early detection of DR. The aim is to discuss the challenges associated with these methods and highlight potential enhancements. In essence, this paper provides a high-level perspective on the integration of deep learning techniques and machine learning models, coupled with explainable artificial intelligence (XAI) and gradient-weighted class activation mapping (Grad-CAM). We prese...
metadata
Ahnaf Alavee, Kazi; Hasan, Mehedi; Hasnayen Zillanee, Abu; Mostakim, Moin; Uddin, Jia; Silva Alvarado, Eduardo René; de la Torre Diez, Isabel; Ashraf, Imran y Abdus Samad, Md
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, eduardo.silva@funiber.org, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Enhancing Early Detection of Diabetic Retinopathy Through the Integration of Deep Learning Models and Explainable Artificial Intelligence.
IEEE Access, 12.
pp. 73950-73969.
ISSN 2169-3536
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
E-Vehicles are used for transportation and, with a vehicle-to-grid optimization approach, they may be used for supplying a backup source of energy for renewable energy sources. Renewable energy sources are integrated to maintain the demand of consumers, mitigate the active and reactive power losses, and maintain the voltage profile. Renewable energy sources are not supplied all day and, to meet the peak demand, extra electricity may be supplied through e-Vehicles. E-Vehicles with random integration may cause system unbalancing problems and need a solution. The objective of this paper is to integrate e-Vehicles with the grid as a backup source of energy through the grid-to-vehicle optimization approach by reducing active and reactive power losses and maintaining voltage profile. In this paper, three case studies are discussed: (i) integration of renewable energy sources alone; (ii) integration of e-Vehicles alone; (iii) integration of renewable energy sources and e-Vehicles in hybrid mode. The simulation results show the effectiveness of the integration and the active and reactive power losses are minimum when we used the third case.
metadata
Agrawal, Himanshi; Talwariya, Akash; Gill, Amandeep; Singh, Aman; Alyami, Hashem; Alosaimi, Wael y Ortega-Mansilla, Arturo
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, arturo.ortega@uneatlantico.es
(2022)
A Fuzzy-Genetic-Based Integration of Renewable Energy Sources and E-Vehicles.
Energies, 15 (9).
p. 3300.
ISSN 1996-1073
Artículo
Materias > Ingeniería
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
This research paper aims to examine the impact of innovative HRM practices, including employee participation, performance appraisal, reward and compensation, recruitment and selection, and redeployment–retraining on firm performance. For this purpose, four different models are utilized to examine the impact of innovative HRM department practices on the performance of small and medium enterprises (SMEs) in a country. The dependent variable, firm performance, is proxified by different variables such as labor productivity, product innovation, process innovation, and marketing innovation. For empirical analysis, primary data are collected using a questionnaire. Estimation is conducted using ordinary least squares (OLS) and logit regression techniques. The estimated results indicate that most innovative HRM practices have a statistically significant impact on firm performance in terms of labor productivity, product, process, and marketing innovations. These results imply that SMEs in a country may observe the benefits of devoting greater attention to innovative HRM practices to achieve their future growth potential.
metadata
Aslam, Mahvish; Shafi, Imran; Ahmed, Jamil; Garat de Marin, Mirtha Silvana; Soriano Flores, Emmanuel; Rojo Gutiérrez, Marco Antonio y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, silvana.marin@uneatlantico.es, emmanuel.soriano@uneatlantico.es, marco.rojo@unini.edu.mx, SIN ESPECIFICAR
(2023)
Impact of Innovation-Oriented Human Resource on Small and Medium Enterprises’ Performance.
Sustainability, 15 (7).
p. 6273.
ISSN 2071-1050
Artículo
Materias > Educación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The main aim of this study was to analyse the influence of e-learning training on the acquisition of competences in basketball coaches in Cantabria. The current landscape of basketball coach training shows an increasing demand for innovative training models and emerging pedagogies, including e-learning-based methodologies. The study sample consisted of fifty students from these courses, all above 16 years of age (36 males, 14 females). Among them, 16% resided outside the autonomous community of Cantabria, 10% resided more than 50 km from the city of Santander, 36% between 10 and 50 km, 14% less than 10 km, and 24% resided within Santander city. Data were collected through a Google Forms survey distributed by the Cantabrian Basketball Federation to training course students. Participation was voluntary and anonymous. The survey, consisting of 56 questions, was validated by two sports and health doctors and two senior basketball coaches. The collected data were processed and analysed using Microsoft® Excel version 16.74, and the results were expressed in percentages. The analysis revealed that 24.60% of the students trained through the e-learning methodology considered themselves fully qualified as basketball coaches, contrasting with 10.98% of those trained via traditional face-to-face methodology. The results of the study provide insights into important characteristics that can be adjusted and improved within the investigated educational process. Moreover, the study concludes that e-learning training effectively qualifies basketball coaches in Cantabria.
metadata
Alemany Iturriaga, Josep; Velarde-Sotres, Álvaro; Jorge, Javier y Giglio, Kamil
mail
josep.alemany@uneatlantico.es, alvaro.velarde@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Influence of E-learning training on the acquisition of competences in basketball coaches in Cantabria.
Cogent Education, 11 (1).
ISSN 2331-186X
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Mold breakout is one of the significant problems in a continuous casting machine (caster). It represents one of the key areas within the steel production facilities of a steel plant. A breakout event on a caster will always cause safety hazards, high repair costs, loss of production, and shutdown of the caster for a short while. In this paper, a logic-judgment-based mold breakout prediction system has been developed for a continuous casting machine. This system developed new algorithms to detect the different sticker behaviors. With more algorithms running, each algorithm is more specialized in the other behaviors of stickers. This new logic-based breakout prediction system (BOPS) not only detects sticker breakouts but also detects breakouts that takes place due to variations in casting speed, mold level fluctuation, and taper/mold problems. This system also finds the exact location of the breakout in the mold and reduces the number of false alarms. The task of the system is to recognize a sticker and prevent a breakout. Moreover, the breakout prediction system uses an online thermal map of the mold for process visualization and assisting breakout prediction. This is done by alerting the operating staff or automatically reducing the cast speed according to the location of alarmed thermocouples, the type of steel, the tundish temperature, and the size of the cold slab width. By applying the proposed model in an actual steel plant, field application results show that it could timely detect all 13 breakouts with a detection ratio of 100%, and the frequency of false alarms was less than 0.056% times/heat. It has the additional advantage of not needing a lot of learning data, as most neural networks do. Thus, this new logical BOPS system should not only detect the sticker breakouts but also detect breakouts taking place due to variations in casting speed and mold level fluctuation. metadata Ansari, Md Obaidullah; Ghose, Joyjeet; Chattopadhyaya, Somnath; Ghosh, Debasree; Sharma, Shubham; Sharma, Prashant; Kumar, Abhinav; Li, Changhe; Singh, Rajesh y Eldin, Sayed M. mail SIN ESPECIFICAR (2022) An Intelligent Logic-Based Mold Breakout Prediction System Algorithm for the Continuous Casting Process of Steel: A Novel Study. Micromachines, 13 (12). p. 2148. ISSN 2072-666X
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
An Internet of Things (IoT) network is prone to many ways of threatening individuals. IoT sensors are lightweight, lack complicated security protocols, and face threats to privacy and confidentiality. Hackers can attack the IoT network and access personal information and confidential data for blackmailing, and negatively manipulate data. This study aims to propose an IoT threat protection system (IoTTPS) to protect the IoT network from threats using an ensemble model RKSVM, comprising a random forest (RF), K nearest neighbor (KNN), and support vector machine (SVM) model. The software-defined networks (SDN)-based IoT network datasets such as KDD cup 99, NSL-KDD, and CICIDS are used for threat detection based on machine learning. The experimental phase is conducted by using a decision tree (DT), logistic regression (LR), Naive Bayes (NB), RF, SVM, gradient boosting machine (GBM), KNN, and the proposed ensemble RKSVM model. Furthermore, performance is optimized by adding a grid search hyperparameter optimization technique with K-Fold cross-validation. As well as the NSL-KDD dataset, two other datasets, KDD and CIC-IDS 2017, are used to validate the performance. Classification accuracies of 99.7%, 99.3%, 99.7%, and 97.8% are obtained for DoS, Probe, U2R, and R2L attacks using the proposed ensemble RKSVM model using grid search and cross-fold validation. Experimental results demonstrate the superior performance of the proposed model for IoT threat detection.
metadata
Akram, Urooj; Sharif, Wareesa; Shahroz, Mobeen; Mushtaq, Muhammad Faheem; Gavilanes Aray, Daniel; Bautista Thompson, Ernesto; Diez, Isabel de la Torre; Djuraev, Sirojiddin y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, daniel.gavilanes@uneatlantico.es, ernesto.bautista@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
IoTTPS: Ensemble RKSVM Model-Based Internet of Things Threat Protection System.
Sensors, 23 (14).
p. 6379.
ISSN 1424-8220
Artículo Materias > Educación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Este artículo recoge los datos de la investigación hecha en la ciudad de Soacha, Colombia, sobre las competencias que adquirieron los docentes en su formación de pregrado y que laboran en el nivel de educación básica. Pretende indicar en un análisis de tipo mixto, las fortalezas y oportunidades, así como las debilidades y amenazas, en referencia a: las competencias adquiridas, en un grupo muestra de 50 docentes a través de instrumentos como la encuesta y la entrevista, competencias que son necesarias en el perfil profesional que propone las políticas educativas nacionales. Los datos, nos dejará ver, un diagnóstico sobre el porcentaje de competitividad frente a los requerimientos del estado colombiano, el cual pretende para el año 2025 alcanzar una excelencia educativa, como mejor país en los procesos de educación en Latinoamérica. El estudio nos muestra el perfil real del docente, en el nivel educativo de pregrado y sus fortalezas y falencias a la hora de las prácticas como profesional, así como el acercamiento a los perfiles que solicita el estado. De igual modo, dará pautas para que las instituciones que apliquen la metodología, puedan desde la implementación y el análisis de la propuesta, proyectar planes de mejora en la formación del recurso humano que participa en el desarrollo del Proyecto Educativo Institucional con el cual se pretende alcanzar mayor calidad educativa, como también el proponer articulaciones formativas y de mejora, con las universidades de las cuales han egresado los docentes y que incursionan en el ambiente educativo de la ciudad de Soacha. metadata Acuña Gamboa, Luis Alan y Suárez Ramírez, Marco Aurelio mail SIN ESPECIFICAR, marco.suarez@doctorado.unini.edu.mx (2022) Las competencias docentes en su formación de pregrado: un estudio del perfil profesional para la acción pedagógica en educación básica en la ciudad de Soacha-Colombia. MLS Educational Research, 6 (1). ISSN 2603-5820
Artículo Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Habiéndose desatado la pandemia del COVID-19 a nivel internacional, se tiene que la respuesta del Estado Peruano es la de promulgar el Decreto Supremo N° 0400-2020-PCM donde se declara el Estado de Emergencia Nacional en Perú por el brote del COVID-19. Dado lo anterior es menester tener conocimiento del impacto del COVID-19, en particular, en lo referido a las relaciones de género y trabajo de mujeres en el Perú. La investigación propuesta constituye una instancia donde se han generado ciertos dispositivos estadísticos a partir de un análisis descriptivo que permite medir el impacto del COVID-19 en las relaciones de género y trabajo de mujeres. Los dispositivos estadísticos resultan de la operacionalización de las relaciones de género y trabajo de mujeres como factores de riesgo demográficos. En la operacionalización se mide: (1) el avance de la pandemia mediante la cantidad de casos positivos por COVID-19; (2) la desaceleración económica mediante el número de puestos de mujeres; (3) el avance del confinamiento social mediante el número de actividades desempeñados en el hogar o fuera de él para obtener un ingreso. Los dispositivos estadísticos abordados tienen su alcance para con la nación peruana durante los trimestres IV de 2020 y I de 2021. La investigación propuesta resulta de interés para observar el comportamiento de las relaciones de género y trabajo de mujeres respecto del impacto de la pandemia COVID-19. metadata Azálgara Bedoya, Mauricio mail mazalgarab@gmail.com (2021) Las relaciones de género y el trabajo de mujeres como factores de riesgo demográficos por la pandemia del COVID-19. Project Design and Management, 3 (2). pp. 55-74. ISSN 2683-1597
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Remarkable progress in the Internet of Things (IoT) and the requirements in the Industrial era have raised new constraints of industrial data where huge data are gathered by heterogeneous devices. Recently, Industry 4.0 has attracted attention in various fields of industries such as medicines, automobiles, logistics, etc. However, every field is suffering from some threats and vulnerabilities. In this paper, a new model is proposed for detecting different types of attacks and it is analyzed with a deep learning technique, i.e., classifier-Convolution Neural Network and Long Short-Term Memory. The UNSW NB 15 dataset is used for the classification of various attacks in the field of Industry 4.0 for providing security and protection to the different types of sensors used for heterogeneous data. The proposed model achieves the results using Cortex processors, a 1.2 GHz processor, and four gigabytes of RAM. The attack detection model is written in Python 3.8.8 and Keras. Keras constructs the model using layers of Convolutional, Max Pooling, and Dense Layers. The model is trained using 250 batch size, 60 epochs, 10 classes. For this model, the activation functions are Relu and softmax pooling.
metadata
Anand, Ankita; Rani, Shalli; Singh, Aman; Elkamchouchi, Dalia H. y Delgado Noya, Irene
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, irene.delgado@uneatlantico.es
(2022)
Lightweight Hybrid Deep Learning Architecture and Model for Security in IIOT.
Applied Sciences, 12 (13).
p. 6442.
ISSN 2076-3417
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
This action research intended to analyze how the implementation of the CLIL Approach as the integration of EFL and Social Studies contents could increase the motivation in a 2nd grade class at San Ignacio School, which is located in Medellín, Colombia. Likewise, it also aimed to study the improvements that students could attain in their English proficiency after being immersed in the language through the learning of a specific subject.
metadata
Acosta Lafont, Yaneth
mail
jeyakama@hotmail.com
(2022)
Master in Teaching English as a Foreign Language.
Masters thesis, SIN ESPECIFICAR.
Artículo Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español La Industria 4.0 llegó con la tecnología digital y la promesa de un incremento de la productividad sobre la base de dato. El escenario es útil al stakeholder de la empresa exportadora sostenible, porque le permite crear valor a los bienes que exporta. Pero se requiere un modelo que acepte la incertidumbre para relacionar las variables de entrada: tecnología digital y estrategia 4.0 con la variable de salida: sostenibilidad. Un problema que se resuelve bajo un enfoque de la lógica difusa y el sistema de inferencia difusa el cual genera el conjunto de datos para entrenar, controlar y validar la red adaptativa del sistema de inferencia difusa (ANFIS). Lo que permite construir el algoritmo del modelo de valuación de sostenibilidad (MVS) y así se completa el objetivo general. Luego, el modelo se utiliza en cinco empresas exportadoras con el propósito de supervisar, controlar y calibrar el resultado de la variable de salida, el cual puede ser un valor, entre cero y uno, donde cero significa una baja sostenibilidad y uno refleja una alta sostenibilidad. Dato y conocimiento que le permite al stakeholder tomar decisiones estratégicas sobre las habilidades y competencias digitales avanzadas en el puesto de trabajo, lo cual es toda una innovación en el contexto de la Industria 4.0 que permite una contribución de conocimiento a la literatura económica y gestión de empresa. El MVS continuara su proceso de entrenamiento con nuevos ecosistemas exportadores, entrevistas presenciales y adaptar su contenido a otro idioma. metadata Alegre Poma, Napoleon Brito y Trigueros Pina, José Antonio mail SIN ESPECIFICAR (2021) Modelo de valuación de sostenibilidad para una empresa exportadora 4.0. Project Design and Management, 3 (1). pp. 7-28. ISSN 2683-1597
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Mobility and low energy consumption are considered the main requirements for wireless body area sensor networks (WBASN) used in healthcare monitoring systems (HMS). In HMS, battery-powered sensor nodes with limited energy are used to obtain vital statistics about the body. Hence, energy-efficient schemes are desired to maintain long-term and steady connectivity of the sensor nodes. A sheer amount of energy is consumed in activities such as idle listening, excessive transmission and reception of control messages, packet collisions and retransmission of packets, and poor path selection, that may lead to more energy consumption. A combination of adaptive scheduling with an energy-efficient protocol can help select an appropriate path at a suitable time to minimize the control overhead, energy consumption, packet collision, and excessive idle listening. This paper proposes a region-based energy-efficient multipath routing (REMR) approach that divides the entire sensor network into clusters with preferably multiple candidates to represent each cluster. The cluster representatives (CRs) route packets through various clusters. For routing, the energy requirement of each route is considered, and the path with minimum energy requirements is selected. Similarly, end-to-end delay, higher throughput, and packet-delivery ratio are considered for packet routing.
metadata
Akbar, Shuja; Mehdi, Muhammad Mohsin; Jamal, M. Hasan; Raza, Imran; Hussain, Syed Asad; Breñosa, Jose; Martínez Espinosa, Julio César; Pascual Barrera, Alina Eugenia y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, alina.pascual@unini.edu.mx, SIN ESPECIFICAR
(2022)
Multipath Routing in Wireless Body Area Sensor Network for Healthcare Monitoring.
Healthcare, 10 (11).
p. 2297.
ISSN 2227-9032
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
Fog-assisted and IoT-enabled smart healthcare system with rapid response rates is the major area of concern now a days. Dynamic and heterogeneous fog networks are difficult to manage and a considerable amount of overhead could be realized while managing ever increasing load on foglets. Fog computing plays a vital role in managing ever increasing processing demands from diverse IoT-based applications. Smart healthcare systems work with the assistance of sensor-based devices and automatic data collection and processing can speed up overall system functionality. In the proposed work, a novel framework for smart health care is presented where a series of activities are performed with prime objective of reducing latency and execution time. Principal component analysis is used for feature reduction and support vector machines with radial basis function kernel is used for classification purpose. Workload optimization on the fog nodes is implemented using genetic algorithm. Data collection process also involves preprocessing as a leading step for generating cleaner data. Amalgamation of intelligent and optimization techniques in the presented framework certainly improves the efficiency of the overall system. Experimental results reveal that proposed work outperforms the existing fog-assisted smart healthcare systems in terms of latency, execution time, overall system accuracy, and system stability.
metadata
Abdellatif, Ahmed A. H.; Singh, Aman; Aldribi, Abdulaziz; Ortega-Mansilla, Arturo; Ibrahim, Muhammad y Rehman, Ateeq Ur
mail
SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, arturo.ortega@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
A Novel Framework for Fog-Assisted Smart Healthcare System with Workload Optimization.
Computational Intelligence and Neuroscience, 2022.
pp. 1-12.
ISSN 1687-5265
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The IoT (Internet of Things) has played a promising role in e-healthcare applications during the last decade. Medical sensors record a variety of data and transmit them over the IoT network to facilitate remote patient monitoring. When a patient visits a hospital he may need to connect or disconnect medical devices from the medical healthcare system frequently. Also, multiple entities (e.g., doctors, medical staff, etc.) need access to patient data and require distinct sets of patient data. As a result of the dynamic nature of medical devices, medical users require frequent access to data, which raises complex security concerns. Granting access to a whole set of data creates privacy issues. Also, each of these medical user need to grant access rights to a specific set of medical data, which is quite a tedious task. In order to provide role-based access to medical users, this study proposes a blockchain-based framework for authenticating multiple entities based on the trust domain to reduce the administrative burden. This study is further validated by simulation on the infura blockchain using solidity and Python. The results demonstrate that role-based authorization and multi-entities authentication have been implemented and the owner of medical data can control access rights at any time and grant medical users easy access to a set of data in a healthcare system. The system has minimal latency compared to existing blockchain systems that lack multi-entity authentication and role-based authorization.
metadata
Alam, Shadab; Aslam, Muhammad Shehzad; Altaf, Ayesha; Iqbal, Faiza; Nigar, Natasha; Castanedo Galán, Juan; Gavilanes Aray, Daniel; Díez, Isabel de la Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, juan.castanedo@uneatlantico.es, daniel.gavilanes@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Novel model to authenticate role-based medical users for blockchain-based IoMT devices.
PLOS ONE, 19 (7).
e0304774.
ISSN 1932-6203
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
In recent times, scientific attention has been paid to different foods and their bioactive components for the ability to inhibit the onset and progress of different types of cancer. Nigella sativa extract, powder and seed oil and its main components, thymoquinone and α-hederin, have showed potent anticancer and chemosensitizing effects against various types of cancer, such as liver, colon, breast, renal, cervical, lung, ovarian, pancreatic, prostate and skin tumors, through the modulation of various molecular signaling pathways. Herein, the purpose of this review was to highlight the anticancer activity of Nigella sativa and it constitutes, focusing on different in vitro, in vivo and clinical studies and projects, in order to underline their antiproliferative, proapoptotic, cytotoxic and antimetastatic effects. Particular attention has been also given to the synergistic effect of Nigella sativa and it constitutes with chemotherapeutic drugs, and to the synthesized analogs of thymoquinone that seem to enhance the chemo-sensitizing potential. This review could be a useful step towards new research on N. sativa and cancer, to include this plant in the dietary treatments in support to conventional therapies, for the best achievement of therapeutic goals.
metadata
Ansary, Johura; Giampieri, Francesca; Forbes-Hernandez, Tamara Y.; Regolo, Lucia; Quinzi, Denise; Gracia Villar, Santos; Garcia Villena, Eduardo; Tutusaus, Kilian; Alvarez-Suarez, José M.; Battino, Maurizio y Cianciosi, Danila
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, eduardo.garcia@uneatlantico.es, kilian.tutusaus@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2021)
Nutritional Value and Preventive Role of Nigella sativa L. and Its Main Component Thymoquinone in Cancer: An Evidenced-Based Review of Preclinical and Clinical Studies.
Molecules, 26 (8).
p. 2108.
ISSN 1420-3049
Artículo Materias > Educación física y el deporte Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Objectives: This study aimed to map the characteristics and the predominant components of clinical physical activity (PA) counseling in Saudi Arabia for adult patients and outline evidence of outcomes and prevalent barriers to its implementation. Methods: We conducted a systematic literature search of four online databases: Web of Science, PubMed, ScienceDirect, and The Cochrane Library. Each study was assessed and evaluated using the Mixed Methods Appraisal Tool (MMAT) for methodological quality. Results: A total of 120 studies were screened, and 47 studies were sought for retrieval. In total, 25 articles were eligible and were subjected to extensive review. After a detailed evaluation, only nine studies met the inclusion criteria. All included were quantitative studies that compiled descriptive and numerical data on physical activity counseling. Four studies described PA counseling information in Saudi Arabia or prescription as lifestyle modification and program structure. The programs used various techniques to motivate patients to adhere to PA protocols. In general, practitioners indicated a high perceived competence in helping patients meet PA guidelines. The most frequently stated barrier was a lack of time for PA discussions with patients, followed by a lack of training in PA counseling, and a lack of patient compliance. Significant improvements in clinical parameters and smoking, food, and exercise habits were detected in experimental trials with respective intervention programs. Conclusion: This review provides preliminary insights into the delivered intervention and standard care content, its outcomes, and clinicians’ perceived competence and barriers regarding current PA counseling approaches in Saudi Arabia. Despite the small number of studies included, this review contributes to the limited understanding of current PA counseling practices in Saudi Arabia and serves as an informational source for clinicians and policymakers and a starting point for further research. metadata AlMarzooqi, Mezna A. y Saller, Franziska V. I. mail SIN ESPECIFICAR (2022) Physical Activity Counseling in Saudi Arabia: A Systematic Review of Content, Outcomes, and Barriers. International Journal of Environmental Research and Public Health, 19 (23). p. 16350. ISSN 1660-4601
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Pneumonia is a potentially life-threatening infectious disease that is typically diagnosed through physical examinations and diagnostic imaging techniques such as chest X-rays, ultrasounds or lung biopsies. Accurate diagnosis is crucial as wrong diagnosis, inadequate treatment or lack of treatment can cause serious consequences for patients and may become fatal. The advancements in deep learning have significantly contributed to aiding medical experts in diagnosing pneumonia by assisting in their decision-making process. By leveraging deep learning models, healthcare professionals can enhance diagnostic accuracy and make informed treatment decisions for patients suspected of having pneumonia. In this study, six deep learning models including CNN, InceptionResNetV2, Xception, VGG16, ResNet50 and EfficientNetV2L are implemented and evaluated. The study also incorporates the Adam optimizer, which effectively adjusts the epoch for all the models. The models are trained on a dataset of 5856 chest X-ray images and show 87.78%, 88.94%, 90.7%, 91.66%, 87.98% and 94.02% accuracy for CNN, InceptionResNetV2, Xception, VGG16, ResNet50 and EfficientNetV2L, respectively. Notably, EfficientNetV2L demonstrates the highest accuracy and proves its robustness for pneumonia detection. These findings highlight the potential of deep learning models in accurately detecting and predicting pneumonia based on chest X-ray images, providing valuable support in clinical decision-making and improving patient treatment.
metadata
Ali, Mudasir; Shahroz, Mobeen; Akram, Urooj; Mushtaq, Muhammad Faheem; Carvajal-Altamiranda, Stefanía; Aparicio Obregón, Silvia; Díez, Isabel De La Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, stefania.carvajal@uneatlantico.es, silvia.aparicio@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Pneumonia Detection Using Chest Radiographs With Novel EfficientNetV2L Model.
IEEE Access, 12.
pp. 34691-34707.
ISSN 2169-3536
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
We describe the biological effects of a polyphenol-rich strawberry extract (PRSE), obtained from the “Alba” variety, on the highly aggressive and invasive basal-like breast cancer cell line A17. Dose-response and time-course experiments showed that PRSE is able to decrease the cellular viability of A17 cells in a time- and dose-dependent manner. PRSE effect on cell survival was investigated in other tumor and normal cell lines of both mouse and human origin, demonstrating that PRSE is more active against breast cancer cells. Cytofluorimetric analysis of A17 cells demonstrated that sub-lethal doses of PRSE reduce the number of cells in S phase, inducing the accumulation of cells in G1 phase of cell cycle. In addition, the migration of A17 cells was studied monitoring the ability of PRSE to inhibit cellular mobility. Gene expression analysis revealed the modulation of 12 genes playing different roles in the cellular migration, adhesion and invasion processes. Finally, in vivo experiments showed the growth inhibition of A17 cells orthotopically transplanted into FVB syngeneic mice fed with PRSE. Overall, we demonstrated that PRSE exerts important biological activities against a highly invasive breast cancer cell line both in vitro and in vivo suggesting the strawberry extracts as preventive/curative food strategy.
metadata
Amatori, Stefano; Mazzoni, Luca; Alvarez-Suarez, José M.; Giampieri, Francesca; Gasparrini, Massimiliano; Forbes-Hernandez, Tamara Y.; Afrin, Sadia; Errico Provenzano, Alfredo; Persico, Giuseppe; Mezzetti, Bruno; Amici, Augusto; Fanelli, Mirco y Battino, Maurizio
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2016)
Polyphenol-rich strawberry extract (PRSE) shows in vitro and in vivo biological activity against invasive breast cancer cells.
Scientific Reports, 6 (1).
ISSN 2045-2322
Artículo
Materias > Biomedicina
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Cerrado
Inglés
Cactus has been used in traditional folk medicine because of its role in treating a number of diseases and conditions. Prickly pear fruit is an excellent source of secondary metabolites (i.e., betalains, flavonoids, and ascorbic acid) with health-promoting properties against many common human diseases, including diabetes, hypertension, hypercholesterolemia, rheumatic pain, gastric mucosa diseases and asthma. In addition, prickly pears are potential candidates for the development of low-cost functional foods because they grow with low water requirements in arid regions of the world. This review describes the main bioactive compounds found in this fruit and shows the in vitro and some clinical studies about the fruit of most important cactus (Opuntia ficus-indica) and its relationship with some chronic diseases. Even though a lot of effort have been done to study the relationship between this fruit and the human health, more studies on Opuntia ficus-indica could help better understand its pharmacological mechanism of action to provide clear scientific evidence to explain its traditional uses, and to identify its therapeutic potential in other diseases.
metadata
Armas Diaz, Yasmany; Machì, Michele; Salinari, Alessia; Mazas Pérez-Oleaga, Cristina; Martínez López, Nohora Milena; Briones Urbano, Mercedes y Cianciosi, Danila
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, cristina.mazas@uneatlantico.es, nohora.martinez@uneatlantico.es, mercedes.briones@uneatlantico.es, SIN ESPECIFICAR
(2022)
Prickly pear fruits from "Opuntia ficus-indica" varieties as a source of potential bioactive compounds in the Mediterranean diet.
Mediterranean Journal of Nutrition and Metabolism, 15 (4).
pp. 581-592.
ISSN 1973798X
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Correct identification of tumor in brain images is critical for treatment. In the medical domain, class distributions of recorded data could differ with locations and require high levels of privacy while collaboratively training the deep learning (DL) models for classifications. The main aim of this paper is to propose a privacy-preserving collaborative model for the classification of brain tumor in heterogeneously distributed magnetic resonance imaging (MRI) images. In this paper, initially, an open-source dataset has been acquired and analyzed as per the required competencies. The acquired dataset has four types of MRI images: pituitary tumor, meningioma tumor, glioma tumor, and no tumor. First, the acquired dataset was analyzed using DL and transfer learning algorithms. By applying implementations of basic algorithms, better algorithms were identified for further implementations in a federated learning ecosystem. DenseNet201-based transfer learning was identified as a better neural network and further utilized for collaborative transfer learning implementations. Here, the paper also focused on developing a suitable system for a heterogeneous distributed tumor database. Heterogeneous data were converted from the available data by applying nonidentical data distribution. The study discovered that the federated DL models, involving multiple clients, exhibited superior performance compared to conventional pretrained models. The proposed framework possesses distinctive characteristics that distinguish it from existing classification methods for brain tumor identification, particularly in terms of ensuring data privacy for edge devices with limited resources. Due to these additional features, the framework stands as the optimal alternative solution for early diagnosis of brain tumor.
metadata
Aggarwal, Meenakshi; Khullar, Vikas; Goyal, Nitin; Rastogi, Rashi; Singh, Aman; Yélamos Torres, Vanessa y Albahar, Marwan Ali
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, vanessa.yelamos@funiber.org, SIN ESPECIFICAR
(2023)
Privacy preserved collaborative transfer learning model with heterogeneous distributed data for brain tumor classification.
International Journal of Imaging Systems and Technology, 34 (2).
ISSN 0899-9457
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Non-word and real-word errors are generally two types of spelling errors. Non-word errors are misspelled words that are nonexistent in the lexicon while real-word errors are misspelled words that exist in the lexicon but are used out of context in a sentence. Lexicon-based lookup approach is widely used for non-word errors but it is incapable of handling real-word errors as they require contextual information. Contrary to the English language, real-word error detection and correction for low-resourced languages like Urdu is an unexplored area. This paper presents a real-word spelling error detection and correction approach for the Urdu language. We develop an extensive lexicon of 593,738 words and use this lexicon to develop a dataset for real-word errors comprising 125562 sentences and 2,552,735 words. Based on the developed lexicon and dataset, we then develop a contextual spell checker that detects and corrects real-word errors. For the real-word error detection phase, word-gram features are used along with five machine learning classifiers, achieving a precision, recall, and F1-score of 0.84,0.79, and 0.81 respectively. We also test the proposed approach with a 40% error density. For real-word error correction, the Damerau-Levenshtein distance is used along with the n-gram model for further ranking of the suggested candidate words, achieving an accuracy of up to 83.67%.
metadata
Aziz, Romila; Anwar, Muhammad Waqas; Jamal, Muhammad Hasan; Bajwa, Usama Ijaz; Kuc Castilla, Ángel Gabriel; Uc-Rios, Carlos; Bautista Thompson, Ernesto y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, carlos.uc@unini.edu.mx, ernesto.bautista@unini.edu.mx, SIN ESPECIFICAR
(2023)
Real Word Spelling Error Detection and Correction for Urdu Language.
IEEE Access.
p. 1.
ISSN 2169-3536
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
With the rapid increase of users over social media, cyberbullying, and hate speech problems have arisen over the past years. Automatic hate speech detection (HSD) from text is an emerging research problem in natural language processing (NLP). Researchers developed various approaches to solve the automatic hate speech detection problem using different corpora in various languages, however, research on the Urdu language is rather scarce. This study aims to address the HSD task on Twitter using Roman Urdu text. The contribution of this research is the development of a hybrid model for Roman Urdu HSD, which has not been previously explored. The novel hybrid model integrates deep learning (DL) and transformer models for automatic feature extraction, combined with machine learning algorithms (MLAs) for classification. To further enhance model performance, we employ several hyperparameter optimization (HPO) techniques, including Grid Search (GS), Randomized Search (RS), and Bayesian Optimization with Gaussian Processes (BOGP). Evaluation is carried out on two publicly available benchmarks Roman Urdu corpora comprising HS-RU-20 corpus and RUHSOLD hate speech corpus. Results demonstrate that the Multilingual BERT (MBERT) feature learner, paired with a Support Vector Machine (SVM) classifier and optimized using RS, achieves state-of-the-art performance. On the HS-RU-20 corpus, this model attained an accuracy of 0.93 and an F1 score of 0.95 for the Neutral-Hostile classification task, and an accuracy of 0.89 with an F1 score of 0.88 for the Hate Speech-Offensive task. On the RUHSOLD corpus, the same model achieved an accuracy of 0.95 and an F1 score of 0.94 for the Coarse-grained task, alongside an accuracy of 0.87 and an F1 score of 0.84 for the Fine-grained task. These results demonstrate the effectiveness of our hybrid approach for Roman Urdu hate speech detection.
metadata
Ashiq, Waqar; Kanwal, Samra; Rafique, Adnan; Waqas, Muhammad; Khurshaid, Tahir; Caro Montero, Elizabeth; Bustamante Alonso, Alicia y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, elizabeth.caro@uneatlantico.es, alicia.bustamante@uneatlantico.es, SIN ESPECIFICAR
(2024)
Roman urdu hate speech detection using hybrid machine learning models and hyperparameter optimization.
Scientific Reports, 14 (1).
ISSN 2045-2322
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Cerrado
Inglés
Smart vehicle parking is a collaborative effort of technology and human innovation where the efforts are to be minimized to save time and efforts. In smart cities it is one of the common challenges to introduce smart parking to increase parking efficiency and combat numerous issues like identification of free parking slot and real-time dynamic updation on traffic to save fuel and energy. In this work, a new cloud-based smart parking architecture is proposed that can help in predicting the available free parking slots in smart cities. Initially, the methodology collects the car count at any near by parking using Internet of Things (IoT) and Cloud-based approach. Later, the approach uses the Kernel Least Mean Square algorithm to make heuristic predictions about future vacancy using auto-regression. The proposed approach thus utilizes the online learning or model training. To validate the efficacy of the proposed work, the testing is done on the real-time dataset. The extensive numerical investigation is performed on parking lots of four international airports of a smart city in actual deployment scenarios. The experimentation has revealed superior performance of the method in terms of vacancy prediction.
metadata
Anand, Divya; Singh, Aman; Alsubhi, Khalid; Goyal, Nitin; Abdrabou, Atef; Vidyarthi, Ankit y Rodrigues, Joel J. P. C.
mail
divya.anand@uneatlantico.es, aman.singh@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
A Smart Cloud and IoVT-Based Kernel Adaptive Filtering Framework for Parking Prediction.
IEEE Transactions on Intelligent Transportation Systems.
pp. 1-9.
ISSN 1524-9050
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Plant stress reduction research has advanced significantly with the use of Artificial Intelligence (AI) techniques, such as machine learning and deep learning. This is a significant step toward sustainable agriculture. Innovative insights into the physiological responses of plants mostly crops to drought stress have been revealed through the use of complex algorithms like gradient boosting, support vector machines (SVM), recurrent neural network (RNN), and long short-term memory (LSTM), combined with a thorough examination of the TYRKC and RBR-E3 domains in stress-associated signaling proteins across a range of crop species. Modern resources were used in this study, including the UniProt protein database for crop physiochemical properties associated with specific signaling domains and the SMART database for signaling protein domains. These insights were then applied to deep learning and machine learning techniques after careful data processing. The rigorous metric evaluations and ablation analysis that typified the study’s approach highlighted the algorithms’ effectiveness and dependability in recognizing and classifying stress events. Notably, the accuracy of SVM was 82%, while gradient boosting and RNN showed 96%, and 94%, respectively and LSTM obtained an astounding 97% accuracy. The study observed these successes but also highlights the ongoing obstacles to AI adoption in agriculture, emphasizing the need for creative thinking and interdisciplinary cooperation. In addition to its scholarly value, the collected data has significant implications for improving resource efficiency, directing precision agricultural methods, and supporting global food security programs. Notably, the gradient boosting and LSTM algorithm outperformed the others with an exceptional accuracy of 96% and 97%, demonstrating their potential for accurate stress categorization. This work highlights the revolutionary potential of AI to completely disrupt the agricultural industry while simultaneously advancing our understanding of plant stress responses.
metadata
Ali, Tariq; Rehman, Saif Ur; Ali, Shamshair; Mahmood, Khalid; Aparicio Obregón, Silvia; Calderón Iglesias, Rubén; Khurshaid, Tahir y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, silvia.aparicio@uneatlantico.es, ruben.calderon@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Smart agriculture: utilizing machine learning and deep learning for drought stress identification in crops.
Scientific Reports, 14 (1).
ISSN 2045-2322
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Many problems in nature can be solved by resorting to numbers in a particular sequence. For example, the numbers in the so called Fibonacci sequence have been successfully applied in computer science, mathematics and game theory. Another example is the triangular number sequence, which has two main applications: the handshake problem and the round-robin tournament. These two sequences can be found in the Pascal's triangle. With the aim of enhancing the waveform quality at the output of a multilevel inverter, this paper explores the suitability of the triangular number sequence to compute the commutation angles in Pulse Width Modulation switching pattern. It has been found that this approach provides a harmonic performance comparable to the results obtained with other calculation techniques such as the Newton Raphson method or Genetic Algorithm, but without the difficulty of solving the complex non-linear equation. metadata Aguayo-Alquicira, Jesus; De León Aldaco, Susana Estefany; Calleja-Gjumlich, Jorge Hugo y Claudio-Sánchez, Abraham mail SIN ESPECIFICAR (2020) Switching Angles Calculation in Multilevel Inverters Using Triangular Number Sequence –A THD Minimization Approach. European Journal of Electrical Engineering, 22 (1). pp. 49-55. ISSN 21033641
Ponencia/Presentación en Jornada, Congreso Materias > Educación Universidad Internacional Iberoamericana México > Investigación > Congresos Cerrado Inglés According to Unicef, in 2019, 33 million children were international migrants. This situation has been intensified due to Covid-19 pandemic. Among the reasons to leave a country, we can find poverty, climate change, economic reasons or the hope of having a better life. Migrant children in school age can face many challenges: language barriers, lack of understanding of social norms, limited resources from the school, and psychosocial issues. These challenges can produce long-lasting psychological and physical effects leading to a halt on the developing of their full potential along their life. So, an early intervention is crucial to boost migrant children’s educational language acquisition and understanding of culture and social norms to their educational achievement. This paper discusses the advantages of mlearning to foster language learning and facilitate a cultural integration by migrant children with the support of translanguaging strategies and intercultural approach. The role of mlearning to foster language learning has been discussed by Azevedo-Gomes & Sartor-Harada (2020) with a mlearning model with four guidelines: the construction of meaning, the interaction between peers, a focus on previous experiences, and formative feedback. Mlearning seeks to integrate learning theories, especially constructivist and behavioral theories to also create collaborative working environments (Crompton, Burke & Gregory, 2017). Despite the fact the design is focused to improve a minority language, the concepts about psycholinguistic factors are similar to migrant children's needs. Furthermore, mlearning allows to involve parents in language instruction and provide flexible education pathways, both considered good policy practices by OECD (2021) to support the lifelong integration of immigrant children. The report examines the role of an intercultural approach with the support of translanguaging strategies. The first one considers the child’s heritage and could help to expand awareness towards both cultures in gamified activities. Plus, translanguaging strategies “leverages the fluid language of learners in ways that deepen their engagement and comprehension of complex content and texts” (García & Vogel, 2017, p.2) and could help children to transfer language competencies to a new language, speeding up their target language learning and fostering their self-esteem by valuing their previous knowledge. The authors base their assumptions on the thesis that the formula translanguaging and intercultural approach can contribute to a positive mixed identity construction. Finally, the authors present their strategy for gamified activities with mlearning support including translanguaging strategies and intercultural approach in order to ease integration and a full educational achievement of migrant children. metadata Azevedo-Gomes, Juliana; Sartor-Harada, Andresa; Cordovés Santiesteban, Alexander Armando y Cordero Gómez, Yoanky mail SIN ESPECIFICAR, SIN ESPECIFICAR, alexander.cordoves@unini.edu.mx, SIN ESPECIFICAR (2021) Translanguaging and intercultural approach: a mlearning proposal to ease inmigrant children's integration. In: 14th annual International Conference of Education, Research and Innovation.
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Blockchain and machine learning (ML) has garnered growing interest as cutting-edge technologies that have witnessed tremendous strides in their respective domains. Blockchain technology provides a decentralized and immutable ledger, enabling secure and transparent transactions without intermediaries. Alternatively, ML is a sub-field of artificial intelligence (AI) that empowers systems to enhance their performance by learning from data. The integration of these data-driven paradigms holds the potential to reinforce data privacy and security, improve data analysis accuracy, and automate complex processes. The confluence of blockchain and ML has sparked increasing interest among scholars and researchers. Therefore, a bibliometric analysis is carried out to investigate the key focus areas, hotspots, potential prospects, and dynamical aspects of the field. This paper evaluates 700 manuscripts drawn from the Web of Science (WoS) core collection database, spanning from 2017 to 2022. The analysis is conducted using advanced bibliometric tools (e.g., Bibliometrix R, VOSviewer, and CiteSpace) to assess various aspects of the research area regarding publication productivity, influential articles, prolific authors, the productivity of academic countries and institutions, as well as the intellectual structure in terms of hot topics and emerging trends. The findings suggest that upcoming research should focus on blockchain technology, AI-powered 5G networks, industrial cyber-physical systems, IoT environments, and autonomous vehicles. This paper provides a valuable foundation for both academic scholars and practitioners as they contemplate future projects on the integration of blockchain and ML.
metadata
Akrami, Nouhaila El; Hanine, Mohamed; Flores, Emmanuel Soriano; Aray, Daniel Gavilanes y Ashraf, Imran
mail
SIN ESPECIFICAR
(2023)
Unleashing the Potential of Blockchain and Machine Learning: Insights and Emerging Trends From Bibliometric Analysis.
IEEE Access, 11.
pp. 78879-78903.
ISSN 2169-3536
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Objective
This study aims to develop a lightweight convolutional neural network-based edge federated learning architecture for COVID-19 detection using X-ray images, aiming to minimize computational cost, latency, and bandwidth requirements while preserving patient privacy.
Method
The proposed method uses an edge federated learning architecture to optimize task allocation and execution. Unlike in traditional edge networks where requests from fixed nodes are handled by nearby edge devices or remote clouds, the proposed model uses an intelligent broker within the federation to assess member edge cloudlets' parameters, such as resources and hop count, to make optimal decisions for task offloading. This approach enhances performance and privacy by placing tasks in closer proximity to the user. DenseNet is used for model training, with a depth of 60 and 357,482 parameters. This resource-aware distributed approach optimizes computing resource utilization within the edge-federated learning architecture.
Results
The experimental results demonstrate significant improvements in various performance metrics. The proposed method reduces training time by 53.1%, optimizes CPU and memory utilization by 17.5% and 33.6%, and maintains accurate COVID-19 detection capabilities without compromising the F1 score, demonstrating the efficiency and effectiveness of the lightweight convolutional neural network-based edge federated learning architecture.
Conclusion
Existing studies predominantly concentrate on either privacy and accuracy or load balancing and energy optimization, with limited emphasis on training time. The proposed approach offers a comprehensive performance-centric solution that simultaneously addresses privacy, load balancing, and energy optimization while reducing training time, providing a more holistic and balanced solution for optimal system performance.
metadata
Alvi, Sohaib Bin Khalid; Nayyer, Muhammad Ziad; Jamal, Muhammad Hasan; Raza, Imran; de la Torre Diez, Isabel; Rodríguez Velasco, Carmen Lilí; Breñosa, Jose y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, carmen.rodriguez@uneatlantico.es, josemanuel.brenosa@uneatlantico.es, SIN ESPECIFICAR
(2023)
A lightweight deep learning approach for COVID-19 detection using X-ray images with edge federation.
DIGITAL HEALTH, 9.
ISSN 2055-2076
B
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Project-based organizations need to procure different commodities, and the failure/success of a project depends heavily on procurement management. Companies must refine and develop methods to simplify and optimize the procurement process in a highly competitive environment. This paper presents a methodology to help managers of project-based organizations analyze procurement processes to determine the optimal framework for simultaneously addressing multiple objectives. These goals include minimizing the time between the generation and required approval for a purchase, identifying unnamed activities, and allocating the budget efficiently. In this paper, we apply process mining algorithms to a dataset consisting of event logs on Oracle Financials-based enterprise resource planning (ERP) procurement processes in ERP systems and demonstrate interesting results leading to project procurement intelligence (PPI). The provided log data is the real-life data consisting of 180,462 events referring to seven activities within 43,101 cases. The logged procurement processes are filtered and analyzed using the open-source process mining frameworks PrOM and Disco. As a result of the process mining activities, a simulation of the discovered process model derived from the event log of the entire procurement process is presented, and the most frequent potential behaviors are identified. This analysis and extraction of frequent processes from corporate event logs help organizations understand, adapt, and redesign procurement operations and, most importantly, make them more efficient and of higher quality. This study shows that after the successful formulation of guiding principles, data refinement, and process structure optimization, the case study results are considered significant by the organization’s management.
metadata
Butt, Naveed Anwer; Mahmood, Zafar; Sana, Muhammad Usman; Díez, Isabel de la Torre; Castanedo Galán, Juan; Brie, Santiago y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, juan.castanedo@uneatlantico.es, santiago.brie@uneatlantico.es, SIN ESPECIFICAR
(2023)
Behavioral and Performance Analysis of a Real-Time Case Study Event Log: A Process Mining Approach.
Applied Sciences, 13 (7).
p. 4145.
ISSN 2076-3417
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español El objetivo de esta investigación es conocer las estructuras básicas que contienen las metodologías de proyectos y lograr una tipificación que nos permita analizar las posibilidades de complementariedad y articulación de las mismas. Metodología: A partir de la identificación de las principales metodologías de proyectos, se reconocieron tipologías según las organizaciones que las promueven; luego se seleccionaron las más representativas de cada tipo y se realizó una comparación entre los ciclos de vida y los procesos básicos de cada fase dentro del grupo tipificado; posteriormente se desarrollaron tablas síntesis que representan a cada grupo de metodologías y que reflejan el contenido común de cada fase; por último se desarrollan tablas que mostraran los contenidos en cuanto a procesos, componentes e instrumentos. Este proceso permitió una comparación a nivel grupo de metodologías, lo cual hizo posible acceder a conclusiones sobre las posibilidades de complementariedad y articulación. Resultados: el análisis comparativo develó que el grupo de metodologías asociadas a las Agencias de Cooperación cuentan con unas instancias preliminares no presentes en las metodologías propuestas por las asociaciones profesionales; por otro lado, se pudo determinar que las metodologías de las asociaciones profesionales son mucho más complejas y completas en los procesos e instrumental propuesto para las fases de implementación. Discusión: Las metodologías son en muchos aspectos complementarias, una articulación entre ellas permitirá que los profesionales que se desarrollan en la disciplina capitalicen las virtudes y potencialidades de las metodologías que no les son propias, propendiendo a una práctica profesional integral y superadora. metadata Brie, Santiago mail SIN ESPECIFICAR (2020) Complementariedad y articulación de las metodologías de planificación y gestión de proyectos. Project, Design and Management, 2 (1). pp. 7-26. ISSN 26831597
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés Ionizing and non-ionizing radiations are part of our daily life, and when organisms are exposed to them for a long time, they may experience their lethal or sublethal effects. For this reason, technologies have been created to quantify them. In this study, Internet of Things (IoT) was used through connecting gamma meters and a low-cost UV radiation device. The validation of this structure was performed with meters calibrated in certified laboratories. The validation results matched those obtained by the other devices, with an error of 2%. metadata Baena Navarro, Ruben Enrique; Torres-Hoyos, F.; Uc-Rios, Carlos y Colmenares-Quintero, R.F. mail ruben.baena@campusucc.edu.co, SIN ESPECIFICAR, carlos.uc@unini.edu.mx, SIN ESPECIFICAR (2020) Design and assembly of an IoT-based device to determine the absorbed dose of gamma and UV radiation. Applied Radiation and Isotopes, 166. p. 109359. ISSN 09698043
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Cerrado
Inglés
Federated learning is a distributed machine-learning technique that enables multiple devices to learn a shared model while keeping their local data private. The approach poses security challenges, such as model integrity, that must be addressed to ensure the reliability of the learned models. In this context, software-defined networking (SDN) can play a crucial role in improving the security of federated learning systems; indeed, it can provide centralized control and management of network resources, enforcement of security policies, and detection and mitigation of network-level threats. The integration of SDN with federated learning can help achieve a secure and efficient distributed learning environment. In this paper, an architecture is proposed to detect attacks on Federated Learning using SDN; furthermore, the machine learning model is deployed on a number of devices for training. The simulation results are carried out using the N-BaIoT dataset and training models such as Random Forest achieves 99.6%, Decision Tree achieves 99.8%, and K-Nearest Neighbor achieves 99.3% with 20 features.
metadata
Babbar, Himanshi; Rani, Shalli; Singh, Aman y Gianini, Gabriele
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR
(2024)
Detecting Cyberattacks to Federated Learning on Software-Defined Networks.
Communications in Computer and Information Science, 2022.
pp. 120-132.
ISSN 1865-0929
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
A new artificial intelligence-based approach is proposed by developing a deep learning (DL) model for identifying the people who violate the face mask protocol in public places. To achieve this goal, a private dataset was created, including different face images with and without masks. The proposed model was trained to detect face masks from real-time surveillance videos. The proposed face mask detection (FMDNet) model achieved a promising detection of 99.0% in terms of accuracy for identifying violations (no face mask) in public places. The model presented a better detection capability compared to other recent DL models such as FSA-Net, MobileNet V2, and ResNet by 24.03%, 5.0%, and 24.10%, respectively. Meanwhile, the model is lightweight and had a confidence score of 99.0% in a resource-constrained environment. The model can perform the detection task in real-time environments at 41.72 frames per second (FPS). Thus, the developed model can be applicable and useful for governments to maintain the rules of the SOP protocol.
metadata
Benifa, J. V. Bibal; Chola, Channabasava; Muaad, Abdullah Y.; Hayat, Mohd Ammar Bin; Bin Heyat, Md Belal; Mehrotra, Rajat; Akhtar, Faijan; Hussein, Hany S.; Ramírez-Vargas, Debora L.; Kuc Castilla, Ángel Gabriel; Díez, Isabel de la Torre y Khan, Salabat
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, debora.ramirez@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
FMDNet: An Efficient System for Face Mask Detection Based on Lightweight Model during COVID-19 Pandemic in Public Areas.
Sensors, 23 (13).
p. 6090.
ISSN 1424-8220
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
In the Internet of things (IoT), data packets are accumulated and disseminated across IoT devices without human intervention, therefore the privacy and security of sensitive data during transmission are crucial. For this purpose, multiple routing techniques exist to ensure security and privacy in IoT Systems. One such technique is the routing protocol for low power and lossy networks (RPL) which is an IPv6 protocol commonly used for routing in IoT systems. Formal modeling of an IoT system can validate the reliability, accuracy, and consistency of the system. This paper presents the formal modeling of RPL protocol and the analysis of its security schemes using colored Petri nets that applies formal validation and verification for both the secure and non-secure modes of RPL protocol. The proposed approach can also be useful for formal modeling-based verification of the security of the other communication protocols.
metadata
Balfaqih, Mohammed; Ahmad, Farooq; Chaudhry, Muhammad Tayyab; Jamal, Muhammad Hasan; Sohail, Muhammad Amar; Gavilanes Aray, Daniel; Masías Vergara, Manuel y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, daniel.gavilanes@uneatlantico.es, manuel.masias@uneatlantico.es, SIN ESPECIFICAR
(2023)
Formal modeling and analysis of security schemes of RPL protocol using colored Petri nets.
PLOS ONE, 18 (8).
e0285700.
ISSN 1932-6203
Artículo
Materias > Ciencias Sociales
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Financial management is a critical aspect of firms, and entails the strategic planning, direction, and control of financial endeavors. Risk assessment, fraud detection, wealth management, online transactions, customized bond scheme, customer retention, virtual assistant and so on, are a few of the critical areas where Industry 4.0 technologies intervention are highly required for managing firms' finance. It has been identified from the previous studies that they are limited studies that have addressed the significance and application of integrating of Industry 4.0 technologies such as Internet of Things (IoT), cloud computing, big data, robotic process automation (RPA), artificial intelligence (AI), Blockchain, Digital twin, and Metaverse. With the motivation from the above aspects, this study aims to discuss the role of these technologies in the area of financial management of a firm. Based up on the analysis, it has been concluded that these technologies assist to credit risk management based on real-time data; financial data analytics of risk assessment, digital finance, digital auditing, fraud detection, and AI- and IoT- based virtual assistants. This study recommended that digital technologies be deeply integrated into the financial sector to improve service quality and accessibility, as well as the creation of innovative rules that allow for healthy competition among market participants.
metadata
Bisht, Deepa; Singh, Rajesh; Gehlot, Anita; Akram, Shaik Vaseem; Singh, Aman; Caro Montero, Elisabeth; Priyadarshi, Neeraj y Twala, Bhekisipho
mail
SIN ESPECIFICAR
(2022)
Imperative Role of Integrating Digitalization in the Firms Finance: A Technological Perspective.
Electronics, 11 (19).
p. 3252.
ISSN 2079-9292
Artículo Materias > Educación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español La calidad de un trabajo académico está asociado al rigor científico empleado en su elaboración, especialmente en lo relativo a la redacción de las citas y referencias. El artículo que presentamos tiene como objetivo general analizar el nivel de aplicación de las normas de la Asociación de Psicólogos Americanos (APA) en la elaboración de las citas y referencias en los Proyectos de Grado de los estudiantes de la carrera de educación de la Universidad Tecnológica de Santiago (UTESA), recinto Gaspar Hernández. La población bajo estudio está representada por 334 estudiantes, 34 docentes y los 83 Proyectos de Grado que representan los documentos académicos elaborados por los alumnos, desde el cuatrimestre 3/2016/ hasta el 3/2019. Estos incluyen 7,298 citas y 6,038 referencias. La metodología se sustenta en un enfoque mixto, al incluir elementos cuantitativos y técnicas cualitativas. En la recopilación de los datos se utilizaron dos cuestionarios elaborados ad hoc, con la escala tipo Likert y una Matriz de Análisis de Datos. En el análisis de los datos se empleó la estadística descriptiva. Los resultados del estudio identificaron errores en las citas elaboradas, tales como, el uso incorrecto de los signos de puntuación, ordenamiento erróneo de los elementos, omisión o cambio en los datos, ausencia del año de publicación de la fuente. En las referencias, se observa combinación de formatos, invertir el orden de los componentes, y otros más graves, como URL incompletos u omisión de información de la fuente. metadata Bernardo Jiménez, Aranzazu y Liriano Pérez, Daniel José mail SIN ESPECIFICAR (2022) La redacción de las citas y referencias en los Proyectos de Grado: caso República Dominicana. MLS Educational Research, 6 (2). ISSN 2603-5820
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Oxidative stress is implicated in several infectious diseases. In this regard, lipopolysaccharide (LPS), an endotoxic component, induces mitochondrial dysfunction and oxidative stress in several pathological events such as periodontal disease or sepsis. In our experiments, LPS-treated fibroblasts provoked increased oxidative stress, mitochondrial dysfunction, reduced oxygen consumption and mitochondrial biogenesis. After comparing coenzyme Q10 (CoQ10) and N-acetylcysteine (NAC), we observed a more significant protection of CoQ10 than of NAC, which was comparable with other lipophilic and hydrophilic antioxidants such as vitamin E or BHA respectively. CoQ10 improved mitochondrial biogenesis by activating PGC-1α and TFAM. This lipophilic antioxidant protection was observed in mice after LPS injection. These results show that mitochondria-targeted lipophilic antioxidants could be a possible specific therapeutic strategy in pharmacology in the treatment of infectious diseases and their complications.
metadata
Bullón, Pedro; Román-Malo, Lourdes; Marín-Aguilar, Fabiola; Alvarez-Suarez, José Miguel; Giampieri, Francesca; Battino, Maurizio y Cordero, Mario D.
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, josemanuel.alvarez@unini.edu.mx, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR
(2015)
Lipophilic antioxidants prevent lipopolysaccharide-induced mitochondrial dysfunction through mitochondrial biogenesis improvement.
Pharmacological Research, 91.
pp. 1-8.
ISSN 10436618
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés In Wireless Sensor Networks (WSNs), routing algorithms can provide energy efficiency. However, due to unbalanced energy consumption for all nodes, the network lifetime is still prone to degradation. Hence, energy efficient routing was developed in this article by selecting cluster heads (CH) with the help of adaptive whale optimization (AWOA) which was used to reduce time-consumption delays. The multi-objective function was developed for CH selection. The clusters were then created using the distance function. After establishing groupings, the supercluster head (SCH) was selected using the benefit of a fuzzy inference system (FIS) which was used to collect data for all CHs and send them to the base station (BS). Finally, for the data-transfer procedure, hop count routing was used. An Oppositional-based Whale optimization algorithm (OWOA) was developed for multi-constrained QoS routing with the help of AWOA. The performance of the proposed OWOA methodology was analyzed according to the following metrics: delay, delivery ratio, energy, NLT, and throughput and compared with conventional techniques such as particle swarm optimization, genetic algorithm, and Whale optimization algorithm metadata Bali, Himani; Gill, Amandeep; Choudhary, Abhilasha; Anand, Divya; Alharithi, Fahd S.; Aldossary, Sultan M. y Vidal Mazón, Juan Luis mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, juanluis.vidal@uneatlantico.es (2022) Multi-Objective Energy Efficient Adaptive Whale Optimization Based Routing for Wireless Sensor Network. Energies, 15 (14). p. 5237. ISSN 1996-1073
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
New approaches to software testing are required due to the rising complexity of today’s software applications and the rapid growth of software engineering practices. Among these methods, one that has shown promise is the introduction of Natural Language Processing (NLP) tools to software testing practices. NLP has witnessed a rise in popularity within all IT fields, especially in software engineering, where its use has improved the way we extract information from textual data. The goal of this systematic literature review (SLR) is to provide an in-depth analysis of the present body of the literature on the expanding subject of NLP-based software testing. Through a repeatable process, that takes into account the quality of the research, we examined 24 papers extracted from Web of Science and Scopus databases to extract insights about the usage of NLP techniques in the field of software testing. Requirements analysis and test case generation popped up as the most hot topics in the field. We also explored NLP techniques, software testing types, machine/deep learning algorithms, and NLP tools and frameworks used in the studied body of literature. This study also stressed some recurrent open challenges that need further work in future research such as the generalization of the NLP algorithm across domains and languages and the ambiguity in the natural language requirements. Software testing professionals and researchers can get important insights from the findings of this SLR, which will help them comprehend the advantages and challenges of using NLP in software testing.
metadata
Boukhlif, Mohamed; Hanine, Mohamed; Kharmoum, Nassim; Ruigómez Noriega, Atenea; García Obeso, David y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, atenea.ruigomez@uneatlantico.es, david.garcia@uneatlantico.es, SIN ESPECIFICAR
(2024)
Natural Language Processing-Based Software Testing: A Systematic Literature Review.
IEEE Access, 12.
pp. 79383-79400.
ISSN 2169-3536
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Mutations allow viruses to continuously evolve by changing their genetic code to adapt to the hosts they infect. It is an adaptive and evolutionary mechanism that helps viruses acquire characteristics favoring their survival and propagation. The COVID-19 pandemic declared by the WHO in March 2020 is caused by the SARS-CoV-2 virus. The non-stop adaptive mutations of this virus and the emergence of several variants over time with characteristics favoring their spread constitute one of the biggest obstacles that researchers face in controlling this pandemic. Understanding the mutation mechanism allows for the adoption of anticipatory measures and the proposal of strategies to control its propagation. In this study, we focus on the mutations of this virus, and we propose the SARSMutOnto ontology to model SARS-CoV-2 mutations reported by Pango researchers. A detailed description is given for each mutation. The genes where the mutations occur and the genomic structure of this virus are also included. The sub-lineages and the recombinant sub-lineages resulting from these mutations are additionally represented while maintaining their hierarchy. We developed a Python-based tool to automatically generate this ontology from various published Pango source files. At the end of this paper, we provide some examples of SPARQL queries that can be used to exploit this ontology. SARSMutOnto might become a ‘wet bench’ machine learning tool for predicting likely future mutations based on previous mutations.
metadata
Bakkas, Jamal; Hanine, Mohamed; Chekry, Abderrahman; Gounane, Said; de la Torre Díez, Isabel; Lipari, Vivian; Martínez López, Nohora Milena y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, vivian.lipari@uneatlantico.es, nohora.martinez@uneatlantico.es, SIN ESPECIFICAR
(2023)
SARSMutOnto: An Ontology for SARS-CoV-2 Lineages and Mutations.
Viruses, 15 (2).
p. 505.
ISSN 1999-4915
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés The high level of electrical energy consumption of induction motors widely used in the industrial sector has increased interest in this sector to search for strategies to improve energy efficiency in order to save energy. During the last decade, the use of power inverters for speed control system applications in induction motors has increased considerably. Its main advantage is its capacity to improve energy efficiency, which depends mainly on the modulation technique used. In this paper, a comparative analysis of the output voltage behaviour of a three-phase dual inverter using an open-end winding induction motor was performed. For the comparative analysis, four modulation techniques: 1. Sinusoidal Pulse Width Modulation (SPWM), 2. Alternative Phase Opposite Disposition Pulse Width Modulation (APOD-PWM), 3. Third Harmonic Injection Pulse Width Modulation (THI-PWM), and 4. Carrier Based Space Vector Pulse Width Modulation (CB-SVPWM), were applied. The comparison of the simulation results was carried out using the PSim software. metadata Bahena, Adolfo; De León Aldaco, Susana Estefany y Alquicira, Jesus mail SIN ESPECIFICAR (2020) Simulation for a Dual Inverter Feeding a Three-Phase Open-End Winding Induction Motor: A Comparative Study of PWM Techniques. European Journal of Electrical Engineering, 22 (1). pp. 13-21. ISSN 21033641
Artículo
Materias > Ciencias Sociales
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The primary objectives of this research article were twofold. Firstly, to categorise a total of 294 individuals who aspired to three distinct competency profiles associated with the supervision of international car sales (SPV). Secondly, to prioritise the criteria used for measurement and assess the level of satisfaction attained following the provision of targeted online training for each respective position. Segmentation was performed using the K-Means algorithm on a Likert scale importance questionnaire. Satisfaction indicators were derived by applying fuzzy set methods to the results of a satisfaction questionnaire, also using a Likert scale. The measurement criteria did not show any clear negative perceptions. The overall satisfaction index was 0.7, which was supported by classic statistics and placed in a high category. Additionally, a variable analysis revealed that candidates from the Euro-Asian region exhibited significantly low levels of satisfaction. However, no significant associations were observed between satisfaction levels and gender, income profile, completed training action, or age groups. The researchers rigorously employed a methodology that included assessing the validity and reliability of the instrument. A review of relevant literature also supported the analysis of the results. These findings suggest that the method could be applied to other multidisciplinary programmes to make informed decisions in the field of training.
metadata
Brito Ballester, Julién; Gracia Villar, Mónica; Soriano Flores, Emmanuel y García Villena, Eduardo
mail
julien.brito@uneatlantico.es, monica.gracia@uneatlantico.es, emmanuel.soriano@uneatlantico.es, eduardo.garcia@uneatlantico.es
(2023)
Use of Fuzzy Approach Methodology and Consensus in Creating a Hierarchy of Satisfaction for Measurement Criteria: Application to Online Training Actions Directed at Classification by Key Competency Profiles in Sales Supervision (SPV) within the Automotive.
International Journal of Operations and Quantitative Management, 29 (2).
pp. 223-251.
C
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
The current globalization along with the difficult pandemic situation we are living in has resulted in the need for more and better ways of improving the education in English as a Foreign Language and the development of different places that generate opportunities where the students feel motivated, despite of the difficult conditions they are going through not only as students but as humans as well. Also, along with the different courses offered by different institutions around the world, the need of a space for the students to practice autonomously the English Language, a space to complement their learning process with extra-curricular hours as students used to do before this health emergency context, has been demonstrated.In response to the before described, this project, which aimed to develop an action research to boost the motivation of EFL students at Universidad Santiago de Cali, successfully designed and carried out a Task-Based extracurricular material for English practice in a virtual space with a group of 52 individuals studying English (A2) in the language institute of this same establishment.The methodological part of this research followed a very qualitative, descriptive approach that also involved a lot of participation of the different members of the study, hence during three weeks of intervention the different contributions, feedback and theories resulted in the development of a virtual space where the students could practice English autonomously.The material presented in this study was built under task-based, CLT, active learning approaches and also included meaningful learning, multiple intelligences among other theories that were able to characterize the group with the help of a questionnaire, hence making the virtual space fit to the specific context. Along with the before described, this study used different tools that helped in the improvement of the material and the activities presented during the intervention process where new data, motivations and ideas were discovered through observation and leaning diaries.The results found were that the motivation can be indeed boosted by considering the student’s participation, opinions, likes and needs to learn the language and that using different and new technologies as a way to innovate in the classes and the learning process can result in very positive outcomes in the motivation. This study also shows that there are difficulties that the current teachers are facing nowadays, for example, students’ lack of autonomy and collaborative work, which presence needs to be considered by all the members in order to progress in their learning of the foreign language at a higher pace.In addition, the general conclusions of this project led to considering the involvement of new technologies as the education is reinvented in the times of the pandemic to keep the students’ motivation in their learning, and also calls to concepts as the students’ learning autonomy and cooperative learning that are key to learn English as a foreign language as a possibility to deepen in future research lines.
metadata
Cortés Escobar, Victor Hugo
mail
victor.cortes00@usc.edu.co
(2022)
An Action Research to Boost the Motivation of EFL students at Universidad Santiago de Cali through the Implementation of a Task Based extracurricular material for a virtual space for English practice.
Masters thesis, SIN ESPECIFICAR.
Artículo
Materias > Biomedicina
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Background: The aim of this study was to relate adherence to the Mediterranean diet (MedDiet) to the prevalence of metabolic syndrome (MetS) in an elderly population from the north of Spain. Methods: We carried out an observational, descriptive, cross-sectional, and correlational study involving 556 non-institutionalised individuals aged 65 to 79 years. The MEDAS-14 questionnaire score was used to define the degree of adherence to the Mediterranean diet. The diagnosis of MetS was conducted using the International Diabetes Federation (IDF) criteria. Results: In 264 subjects with an average age of 71.9 (SD: ±4.2), 39% of whom were men, 36.4% had good adherence (score ≥ 9 in MEDAS-14), with no differences by gender or age. The prevalence of MetS was 40.2%, with 47.6% in men and 35.4% in women (p < 0.05). The prevalence of MetS was 2.4 times more frequent among individuals who consumed less than two servings (200 g) of vegetables daily compared with those who consumed two or more servings of vegetables daily (OR: 2.368, 95%CI: 1.141–4.916, p = 0.021). Low adherence to the MedDiet (MEDAS-14 score ≤ 8) was associated with an 82% higher prevalence of MetS (OR: 1.817, 95%CI: 1.072–3.081, p = 0.027). Conclusion: An inverse relationship was established between adherence to the MedDiet and the prevalence of MetS
metadata
Cubas-Basterrechea, Gloria; Elío Pascual, Iñaki; Alonso, Guzmán; Otero, Luis; Gutiérrez-Bardeci, Luis; Puente, Jesús y Muñoz-Cacho, Pedro
mail
SIN ESPECIFICAR, inaki.elio@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Adherence to the Mediterranean Diet Is Inversely Associated with the Prevalence of Metabolic Syndrome in Older People from the North of Spain.
Nutrients, 14 (21).
p. 4536.
ISSN 2072-6643
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Acinetobacter baumannii is a Gram-negative coccoid rod species, clinically relevant as a human pathogen, included in the ESKAPE group. Carbapenem-resistant A. baumannii (CRAB) are considered by the World Health Organization (WHO) as a critical priority pathogen for the research and development of new antibiotics. Some of the most relevant features of this pathogen are its intrinsic multidrug resistance and its ability to acquire rapid and effective new resistant determinants against last-resort clinical antibiotics, mostly from other ESKAPE species. The presence of plasmids and mobile genetic elements in their genomes contributes to the acquisition of new antimicrobial resistance determinants. However, although A. baumannii has arisen as an important human pathogen, information about these elements is still not well understood. Current genomic analysis availability has increased our ability to understand the microevolution of bacterial pathogens, including point mutations, genetic dissemination, genomic stability, and pan- and core-genome compositions. In this work, we deeply studied the genomes of four clinical strains from our hospital, and the reference strain ATCC®19606TM, which have shown a remarkable ability to survive and maintain their effective capacity when subjected to long-term stress conditions. With that, our aim was presenting a detailed analysis of their genomes, including antibiotic resistance determinants and plasmid composition.
metadata
Chapartegui-González, Itziar; Lázaro-Díez, María; Redondo-Salvo, Santiago; Navas, Jesús y Ramos-Vivas, José
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, jose.ramos@uneatlantico.es
(2021)
Antimicrobial Resistance Determinants in Genomes and Plasmids from Acinetobacter baumannii Clinical Isolates.
Antibiotics, 10 (7).
p. 753.
ISSN 2079-6382
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The COVID-19 pandemic has profoundly affected almost all facets of peoples’ lives, various economic areas and regions of the world. In such a situation implementation of a vaccination can be viewed as essential but its success will be dependent on availability and transparency in the distribution process that will be shared among the stakeholders. Various distributed ledgers (DLTs) such as blockchain provide an open, public, immutable system that has numerous applications due the mentioned abilities. In this paper the authors have proposed a solution based on blockchain to increase the security and transparency in the tracing of COVID-19 vaccination vials. Smart contracts have been developed to monitor the supply, distribution of vaccination vials. The proposed solution will help to generate a tamper-proof and secure environment for the distribution of COVID-19 vaccination vials. Proof of delivery is used as a consensus mechanism for the proposed solution. A feedback feature is also implemented in order to track the vials lot in case of any side effect cause to the patient. The authors have implemented and tested the proposed solution using Ethereum test network, RinkeyBy, MetaMask, one clicks DApp. The proposed solution shows promising results in terms of throughput and scalability.
metadata
Chauhan, Harsha; Gupta, Deepali; Gupta, Sheifali; Singh, Aman; Aljahdali, Hani Moaiteq; Goyal, Nitin; Delgado Noya, Irene y Kadry, Seifedine
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, irene.delgado@uneatlantico.es, SIN ESPECIFICAR
(2021)
Blockchain Enabled Transparent and Anti-Counterfeiting Supply of COVID-19 Vaccine Vials.
Vaccines, 9 (11).
p. 1239.
ISSN 2076-393X
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Building energy consumption prediction has become an important research problem within the context of sustainable homes and smart cities. Data-driven approaches have been regarded as the most suitable for integration into smart houses. With the wide deployment of IoT sensors, the data generated from these sensors can be used for modeling and forecasting energy consumption patterns. Existing studies lag in prediction accuracy and various attributes of buildings are not very well studied. This study follows a data-driven approach in this regard. The novelty of the paper lies in the fact that an ensemble model is proposed, which provides higher performance regarding cooling and heating load prediction. Moreover, the influence of different features on heating and cooling load is investigated. Experiments are performed by considering different features such as glazing area, orientation, height, relative compactness, roof area, surface area, and wall area. Results indicate that relative compactness, surface area, and wall area play a significant role in selecting the appropriate cooling and heating load for a building. The proposed model achieves 0.999 R2 for heating load prediction and 0.997 R2 for cooling load prediction, which is superior to existing state-of-the-art models. The precise prediction of heating and cooling load, can help engineers design energy-efficient buildings, especially in the context of future smart homes
metadata
Chaganti, Rajasekhar; Rustam, Furqan; Daghriri, Talal; Díez, Isabel de la Torre; Vidal Mazón, Juan Luis; Rodríguez Velasco, Carmen Lilí y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR
(2022)
Building Heating and Cooling Load Prediction Using Ensemble Machine Learning Model.
Sensors, 22 (19).
p. 7692.
ISSN 1424-8220
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
Alpha-linolenic acid (ALA) is a long-chain polyunsaturated essential fatty acid of the Ω3 series found mainly in vegetables, especially in the fatty part of oilseeds, dried fruit, berries, and legumes. It is very popular for its preventive use in several diseases: It seems to reduce the risk of the onset or decrease some phenomena related to inflammation, oxidative stress, and conditions of dysregulation of the immune response. Recent studies have confirmed these unhealthy situations also in patients with severe coronavirus disease 2019 (COVID-19). Different findings (in vitro, in vivo, and clinical ones), summarized and analyzed in this review, have showed an important role of ALA in other various non-COVID physiological and pathological situations against “cytokines storm,” chemokines secretion, oxidative stress, and dysregulation of immune cells that are also involved in the infection of the 2019 novel coronavirus. According to the effects of ALA against all the aforementioned situations (also present in patients with a severe clinical picture of severe acute respiratory syndrome-(CoV-2) infection), there may be the biologic plausibility of a prophylactic effect of this compound against COVID-19 symptoms and fatality.
metadata
Cianciosi, Danila; Diaz, Yasmany Armas; Gaddi, Antonio Vittorino; Capello, Fabio; Savo, Maria Teresa; Pali-Casanova, Ramón; Martínez Espinosa, Julio César; Pascual Barrera, Alina Eugenia; Navarro‐Hortal, Maria‐Dolores; Tian, Lingmin; Bai, Weibin; Giampieri, Francesca y Battino, Maurizio
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, ramon.pali@unini.edu.mx, ulio.martinez@unini.edu.mx, alina.pascual@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, francesca.giampieri@uneatlantico.es, SIN ESPECIFICAR
(2023)
Can alpha‐linolenic acid be a modulator of “cytokine storm,” oxidative stress and immune response in SARS‐CoV‐2 infection?
Food Frontiers.
ISSN 2643-8429
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Cerrado
Inglés
Manuka honey, which is rich in pinocembrin, quercetin, naringenin, salicylic, p-coumaric, ferulic, syringic and 3,4-dihydroxybenzoic acids, has been shown to have pleiotropic effects against colon cancer cells. In this study, potential chemosensitizing effects of Manuka honey against 5-Fluorouracil were investigated in colonspheres enriched with cancer stem cells (CSCs), which are responsible for chemoresistance. Results showed that 5-Fluorouracil increased when it was combined with Manuka honey by downregulating the gene expression of both ATP-binding cassette sub-family G member 2, an efflux pump and thymidylate synthase, the main target of 5-Fluorouracil which regulates the ex novo DNA synthesis. Manuka honey was associated with decreased self-renewal ability by CSCs, regulating expression of several genes in Wnt/β-catenin, Hedgehog and Notch pathways. This preliminary study opens new areas of research into the effects of natural compounds in combination with pharmaceuticals and, potentially, increase efficacy or reduce adverse effects.
metadata
Cianciosi, Danila; Armas Diaz, Yasmany; Alvarez-Suarez, José M.; Chen, Xiumin; Zhang, Di; Martínez López, Nohora Milena; Briones Urbano, Mercedes; Quiles, José L.; Amici, Adolfo; Battino, Maurizio y Giampieri, Francesca
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, nohora.martinez@uneatlantico.es, mercedes.briones@uneatlantico.es, jose.quiles@uneatlantico.es, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es, francesca.giampieri@uneatlantico.es
(2023)
Can the phenolic compounds of Manuka honey chemosensitize colon cancer stem cells? A deep insight into the effect on chemoresistance and self-renewal.
Food Chemistry, 427.
p. 136684.
ISSN 03088146
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Objectives: We sought to examine the correlation between the recommended consumption of at least two servings (400 g) of vegetables per day and the prevalence of metabolic syndrome (MetS) in an elderly population. Methods: This observational, cross-sectional, and descriptive study was conducted with 264 non-institutionalized people aged 65 to 79 years old. We adhered to the recommended guidelines for vegetable intake from the MEDAS-14 questionnaire, which has been validated for elderly populations at high cardiovascular risk. Diagnoses of MetS were made based on the criteria set forth by the International Diabetes Federation (IDF). Results: Among 264 individuals, who had a mean age of 71.9 (SD: 4.2) and comprised 39% men, the prevalence of MetS was 40.2%. A total of 17% of the participants adhered to the recommended vegetable consumption. Consuming the recommended amount of vegetables was correlated with a 19% reduction in the prevalence of MetS, to 24.4% from 43.4% among those with low vegetable consumption (p < 0.05). A main finding was that inadequate vegetable consumption was significantly associated with a higher prevalence of MetS (OR: 2.21; 95% CI: 1.06–4.63; p = 0.035), considering potential influences by nutritional (consumption of fruit and nuts) and socio-demographic (sex, age, and level of education) covariates. Conclusions: A beneficial inverse correlation was identified between the recommended vegetable intake and the prevalence of MetS. In contrast, inadequate vegetable consumption was revealed as an independent variable associated with the prevalence of MetS. Considering the very low adherence to the recommended vegetable intake we observed, encouraging increased vegetable consumption among older individuals, who have a high prevalence of MetS, is advisable.
metadata
Cubas-Basterrechea, Gloria; Elío Pascual, Iñaki; González Antón, Carolina y Muñoz Cacho, Pedro
mail
SIN ESPECIFICAR, inaki.elio@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Daily Intake of Two or More Servings of Vegetables Is Associated with a Lower Prevalence of Metabolic Syndrome in Older People.
Nutrients, 16 (23).
p. 4101.
ISSN 2072-6643
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Antimicrobial-resistant pathogenic bacteria are an increasing problem in public health, especially in the healthcare environment, where nosocomial infection microorganisms find their niche. Among these bacteria, the genus Acinetobacter which belongs to the ESKAPE pathogenic group harbors different multi-drug resistant (MDR) species that cause human nosocomial infections. Although A. baumannii has always attracted more interest, the close-related species A. pittii is the object of more study due to the increase in its isolation and MDR strains. In this work, we present the genomic analysis of five clinically isolated A. pittii strains from a Spanish hospital, with special attention to their genetic resistance determinants and plasmid structures. All the strains harbored different genes related to β-lactam resistance, as well as different MDR efflux pumps. We also found and described, for the first time in this species, point mutations that seem linked with colistin resistance, which highlights the relevance of this comparative analysis among the pathogenic species isolates.
metadata
Chapartegui-González, Itziar; Lázaro-Díez, María y Ramos Vivas, Jose
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, jose.ramos@uneatlantico.es
(2022)
Genetic Resistance Determinants in Clinical Acinetobacter pittii Genomes.
Antibiotics, 11 (5).
p. 676.
ISSN 2079-6382
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Much of nutrition research has been conventionally based on the use of simplistic in vitro systems or animal models, which have been extensively employed in an effort to better understand the relationships between diet and complex diseases as well as to evaluate food safety. Although these models have undeniably contributed to increase our mechanistic understanding of basic biological processes, they do not adequately model complex human physiopathological phenomena, creating concerns about the translatability to humans. During the last decade, extraordinary advancement in stem cell culturing, three-dimensional cell cultures, sequencing technologies, and computer science has occurred, which has originated a wealth of novel human-based and more physiologically relevant tools. These tools, also known as “new approach methodologies,” which comprise patient-derived organoids, organs-on-chip, multi-omics approach, along with computational models and analysis, represent innovative and exciting tools to forward nutrition research from a human-biology-oriented perspective. After considering some shortcomings of conventional in vitro and vivo approaches, here we describe the main novel available and emerging tools that are appropriate for designing a more human-relevant nutrition research. Our aim is to encourage discussion on the opportunity to explore innovative paths in nutrition research and to promote a paradigm-change toward a more human biology-focused approach to better understand human nutritional pathophysiology, to evaluate novel food products, and to develop more effective targeted preventive or therapeutic strategies while helping in reducing the number and replacing animals employed in nutrition research.
metadata
Cassotta, Manuela; Cianciosi, Danila; Elexpuru Zabaleta, Maria; Elío Pascual, Iñaki; Sumalla Cano, Sandra; Giampieri, Francesca y Battino, Maurizio
mail
manucassotta@gmail.com, SIN ESPECIFICAR, maria.elexpuru@uneatlantico.es, inaki.elio@uneatlantico.es, sandra.sumalla@uneatlantico.es, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es
(2024)
Human‐based new approach methodologies to accelerate advances in nutrition research.
Food Frontiers.
pp. 1-32.
ISSN 2643-8429
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
This paper focuses on retrieving plant leaf images based on different features that can be useful in the plant industry. Various images and their features can be used to identify the type of leaf and its disease. For this purpose, a well-organized computer-assisted plant image retrieval approach is required that can use a hybrid combination of the color and shape attributes of leaf images for plant disease identification and botanical gardening in the agriculture sector. In this research work, an innovative framework is proposed for the retrieval of leaf images that uses a hybrid combination of color and shape features to improve retrieval accuracy. For the color features, the Color Difference Histograms (CDH) descriptor is used while shape features are determined using the Saliency Structure Histogram (SSH) descriptor. To extract the various properties of leaves, Hue and Saturation Value (HSV) color space features and First Order Statistical Features (FOSF) features are computed in CDH and SSH descriptors, respectively. After that, the HSV and FOSF features of leaf images are concatenated. The concatenated features of database images are compared with the query image in terms of the Euclidean distance and a threshold value of Euclidean distance is taken for retrieval of images. The best results are obtained at the threshold value of 80% of the maximum Euclidean distance. The system’s effectiveness is also evaluated with different performance metrics like precision, recall, and F-measure, and their values come out to be respectively 1.00, 0.96, and 0.97, which is better than individual feature descriptors.
metadata
Chugh, Himani; Gupta, Sheifali; Garg, Meenu; Gupta, Deepali; Mohamed, Heba G.; Delgado Noya, Irene; Singh, Aman y Goyal, Nitin
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, irene.delgado@uneatlantico.es, aman.singh@uneatlantico.es, SIN ESPECIFICAR
(2022)
An Image Retrieval Framework Design Analysis Using Saliency Structure and Color Difference Histogram.
Sustainability, 14 (16).
p. 10357.
ISSN 2071-1050
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés, Español, Portugués
La importancia de la seguridad de la información en las empresas corporativas de tecnología de la información tiene el objetivo principal de proponer medidas de seguridad para proteger la información en las empresas corporativas de tecnología de la información. En este sentido, la investigación es una investigación cualitativa, exploratoria y descriptiva, ya que se basa en la búsqueda de material bibliográfico que permita sugerir medidas de seguridad para la protección de la información. Los datos secundarios se recopilaron sistemáticamente, buscando la palabra clave: medidas de seguridad y sus sinónimos. La búsqueda se realizó en bases de datos computarizadas, como Google Acadêmico® y el Portal de Periódicos Capes. Se ha identificado un conjunto de sugerencias para medidas de seguridad que permiten a las empresas corporativas en el campo de la tecnología de la información aprovechar. Se destaca como conclusión que las medidas preventivas, de detección y correctivas propuestas deben estar involucradas en un plan de seguridad y contingencia difundido en toda la organización..
metadata
Cassinda Quissanga, Fernando y Fernandes, Roberto Fabiano
mail
SIN ESPECIFICAR, roberto.fabiano@funiber.org
(2020)
Importancia de la seguridad de la información en las empresas de tecnología de información corporativa.
Project, Design and Management, 2 (1).
pp. 87-102.
ISSN 26831597
Artículo
Materias > Ciencias Sociales
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Angola, as with many countries on the African continent, has great inequalities or asymmetries between its provinces. At the economic, financial, and technological level, there is a great disparity between them, where it is observed that the province of Luanda is the largest financial business center to the detriment of others, such as Moxico, Zaire, and Cabinda. In the latter, despite the advantages of high oil production, from a regional point of view, they remain almost stagnant in time, in a social dysfunction where the population lives on extractivism and artisanal fishing. This article analyzes the most important events in contemporary regional history, the Portuguese occupation that was the Portuguese colonial rule over Angola (1890–1930) and the civil war that was a struggle between Angolans for control of the country (1975–2002), in the consolidation of the asymmetries between provinces. For this work, a theoretical-reflective study was conducted based on the reading of books, articles, and previous investigations on the phenomenon studied. Considering the interpretation and analysis of the theoretical content obtained through the bibliographic research conducted, this theoretical construction approaches the qualitative approach. We conclude that the deep inequalities between regions and within them, between the provinces studied, originated historically in the form of exploitation of the regions and from the consequences of the war. The asymmetries, observed through the variables studied show that the provinces historically explored and considered object regions present a lower growth compared to those that were considered subject regions in which the applied geopolitical strategy, as they are centers of primary production flows, was different. We also observe that, due to the conflicts of the civil war in the less developed regions, the inequalities have deepened, contributing seriously to a higher level of poverty and a lower development of the provinces where these conflicts took place.
metadata
Catoto Capitango, João Adolfo; Garat de Marin, Mirtha Silvana; Soriano Flores, Emmanuel; Rojo Gutiérrez, Marco Antonio; Gracia Villar, Mónica y Durántez Prados, Frigdiano Álvaro
mail
SIN ESPECIFICAR, silvana.marin@uneatlantico.es, emmanuel.soriano@uneatlantico.es, marco.rojo@unini.edu.mx, monica.gracia@uneatlantico.es, durantez@uneatlantico.es
(2022)
Inequalities and Asymmetries in the Development of Angola’s Provinces: The Impact of Colonialism and Civil War.
Social Sciences, 11 (8).
p. 334.
ISSN 2076-0760
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Cancer stem cells (CSCs) are a rare tumor subpopulation with high differentiation, proliferative and tumorigenic potential compared to the remaining tumor population. CSCs were first discovered by Bonnet and Dick in 1997 in acute myeloid leukemia. The identification and isolation of these cells in this pioneering study were carried out through the flow cytometry, exploiting the presence of specific cell surface molecular markers (CD34+/CD38−). In the following years, different strategies and projects have been developed for the study of CSCs, which are basically divided into surface markers assays and functional assays; some of these techniques also allow working with a cellular model that better mimics the tumor architecture. The purpose of this mini review is to summarize and briefly describe all the current methods used for the identification, isolation and enrichment of CSCs, describing, where possible, the molecular basis, the advantages and disadvantages of each technique with a particular focus on those that offer a three-dimensional culture.
metadata
Cianciosi, Danila; Ansary, Johura; Forbes-Hernandez, Tamara Y.; Regolo, Lucia; Quinzi, Denise; Gracia Villar, Santos; Garcia Villena, Eduardo; Tutusaus Pifarre, Kilian; Alvarez-Suarez, José M.; Battino, Maurizio y Giampieri, Francesca
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, eduardo.garcia@uneatlantico.es, kilian.tutusaus@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2021)
The Molecular Basis of Different Approaches for the Study of Cancer Stem Cells and the Advantages and Disadvantages of a Three-Dimensional Culture.
Molecules, 26 (9).
p. 2615.
ISSN 1420-3049
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
COVID-19 is an infectious disease caused by the deadly virus SARS-CoV-2 that affects the lung of the patient. Different symptoms, including fever, muscle pain and respiratory syndrome, can be identified in COVID-19-affected patients. The disease needs to be diagnosed in a timely manner, otherwise the lung infection can turn into a severe form and the patient’s life may be in danger. In this work, an ensemble deep learning-based technique is proposed for COVID-19 detection that can classify the disease with high accuracy, efficiency, and reliability. A weighted average ensemble (WAE) prediction was performed by combining three CNN models, namely Xception, VGG19 and ResNet50V2, where 97.25% and 94.10% accuracy was achieved for binary and multiclass classification, respectively. To accurately detect the disease, different test methods have been proposed and developed, some of which are even being used in real-time situations. RT-PCR is one of the most successful COVID-19 detection methods, and is being used worldwide with high accuracy and sensitivity. However, complexity and time-consuming manual processes are limitations of this method. To make the detection process automated, researchers across the world have started to use deep learning to detect COVID-19 applied on medical imaging. Although most of the existing systems offer high accuracy, different limitations, including high variance, overfitting and generalization errors, can be found that can degrade the system performance. Some of the reasons behind those limitations are a lack of reliable data resources, missing preprocessing techniques, a lack of proper model selection, etc., which eventually create reliability issues. Reliability is an important factor for any healthcare system. Here, transfer learning with better preprocessing techniques applied on two benchmark datasets makes the work more reliable. The weighted average ensemble technique with hyperparameter tuning ensures better accuracy than using a randomly selected single CNN model.
metadata
Chakraborty, Gouri Shankar; Batra, Salil; Singh, Aman; Muhammad, Ghulam; Yélamos Torres, Vanessa y Mahajan, Makul
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, vanessa.yelamos@funiber.org, SIN ESPECIFICAR
(2023)
A Novel Deep Learning-Based Classification Framework for COVID-19 Assisted with Weighted Average Ensemble Modeling.
Diagnostics, 13 (10).
p. 1806.
ISSN 2075-4418
Artículo Materias > Psicología Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español, Portugués Para viabilizar las condiciones de vida, propietarios de las pequeñas y medianas explotaciones agrarias participan en actividades no agrícolas, como trabajo remunerado, reduciendo así el tiempo dedicado a la agricultura, situación que provoca inseguridad alimentaria, pero en otros casos aumenta su productividad agrícola y bienestar. Este artículo evalúa la importancia y los determinantes del trabajo remunerado no agrícola (TRNA) en la productividad agrícola y el bienestar de los agricultores familiares de Gaza y Maputo, sur de Mozambique, basado en los resultados de la encuesta agraria integrada 2015, realizado por el Ministerio de Agricultura y Seguridad Alimentaria. Para ello, fueron estimadas las familias participantes del TRNA, segmentado por los indicadores socio-demográficos, proceso productivo y bienestar por provincia. Los resultados revelan que el 55,4% de las explotaciones se ocuparon en 2015 del TRNA, una gran contribución al empleo. Los factores asociados a esa participación fueron la edad relativamente baja, tamaño numeroso de la familia, responsable familiar del sexo masculino, no casado, escolaridad relativamente alta, pequeña extensión de la tierra cultivada y baja reserva alimentaria. Esta situación contribuiu para una mayor productividad agrícola, así como a mejorar el bienestar familiar entre los participantes del TRNA, en términos de acceso a agua potable, animales domésticos, teléfono móvil y bicicleta. Este hecho propició una autoevaluación favorable de la situación económica del hogar en comparación con los tres años anteriores, lo que sugiere que el trabajo remunerado no agrícola combinado con agricultura puede constituir una estrategia política sostenible del desarrollo rural. metadata Cossa, Alberto Francisco mail SIN ESPECIFICAR (2019) Papel del trabajo remunerado no agrícola en la productividad agrícola y bienestar. Evidencias de las provincias de Gaza y Maputo, al sur de Mozambique en 2015. MLS Psychology Research, 2 (1). pp. 45-64. ISSN 26055295
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español El consumo de energía a nivel mundial continúa incrementándose debido al aumento demográfico y desarrollo tecnológico, sin embargo, el 73 % de la energía utilizada proviene de fuentes fósiles altamente contaminantes para el planeta y cuyas reservas mundiales se reducen aceleradamente, utilizando únicamente un porcentaje menor de energías limpias o renovables que mitiguen el calentamiento global, el cambio climático y aseguren la sustentabilidad energética mundial. Conscientes de esta problemática nacional y mundial, se propone un modelo energético descriptivo que incluya metodológicamente los pasos a seguir para determinar la viabilidad de instalar sistemas solares fotovoltaicos en cualquier región del mundo, mediante el análisis del recurso energético renovable disponible, de las variables medioambientales y eléctricas y, de los recursos humanos, materiales y financieros. El modelo propuesto se desarrolla y diseña mediante la recopilación, integración y análisis de diversas fuentes y trabajos de investigación relacionados al tema, conjuntado como un sistema integral que muestra gráficamente y describe los bloques de información que deben considerarse. Como un caso particular de estudio el modelo se aplica en Nuevo Laredo, para demostrar que existen las condiciones necesarias para instalar sistemas fotovoltaicos. Se considera la medición de variables in situ mediante instrumentos especiales y las obtenidas de bases de datos o software especial, se analizan y se comparan con normas, especificaciones de fabricantes, regulaciones y parámetros de referencia, lo que permite determinar la viabilidad de la región para instalar sistemas solares fotovoltaicos. Finalmente, la aplicación del modelo requiere elaborar un reporte técnico de los resultados obtenidos. metadata Cruz Arellano, Martin y Castillo Tellez, Margarita mail SIN ESPECIFICAR (2021) Planteamiento de un modelo energético descriptivo aplicable a la instalación de sistemas solares fotovoltaicos interconectados a la red mediante generación distribuida: caso de estudio en Nuevo Laredo. Project Design and Management, 3 (1). pp. 112-137. ISSN 2683-1597
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Cerrado
Inglés
Inflammatory bowel disease (IBD) patients are at substantially higher risk of colorectal cancer (CRC) and IBD-associated CRC accounts for roughly 10-15% of the annual mortality in IBD patients. IBD-related CRC also affects younger patients if compared with sporadic CRC, with a 5-year survival rate of 50%. Regardless of medical therapies, the persistent inflammation state characterizing IBD raises the risk for precancerous changes and CRC, with additional input from several elements including genetic and environmental risk factors, IBD-associated comorbidities, intestinal barrier disfunction, and gut microbiota modifications. It is well known that nutritional habits and dietary bioactive compounds can influence IBD-associated inflammation, microbiome abundance and composition, oxidative stress balance, and gut permeability. In addition, in the last years, results from broad epidemiological and experimental studies have associated certain foods or nutritional patterns with the risk of colorectal neoplasia. Here we review the possible role of nutrition in the prevention of IBD-related CRC, focusing specifically on human studies. In conclusion it emerges that nutritional interventions based on healthy, nutrient-dense dietary patterns characterized by a high intake of fiber, vegetables, fruit, Omega-3 PUFAs, and low amount of animal proteins, processed foods and alcohol, combined with probiotic supplementation have the potential of reducing IBD-activity and preventing the risk of IBD-related CRC through different mechanisms, suggesting that targeted nutritional interventions may represent a novel promising approach for the prevention and management of IBD-associated CRC.
metadata
Cassotta, Manuela; Cianciosi, Danila; De Giuseppe, Rachele; Navarro-Hortal, Maria Dolores; Diaz, Yasmany Armas; Forbes-Hernández, Tamara Yuliett; Tutusaus, Kilian; Pascual Barrera, Alina Eugenia; Grosso, Giuseppe; Xiao, Jianbo; Battino, Maurizio y Giampieri, Francesca
mail
manucassotta@gmail.com, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, kilian.tutusaus@uneatlantico.es, alina.pascual@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es, francesca.giampieri@uneatlantico.es
(2023)
Possible role of nutrition in the prevention of Inflammatory Bowel Disease-related colorectal cancer: a focus on human studies.
Nutrition.
p. 111980.
ISSN 08999007
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Background: The aim of this study was to relate the adherence to nut consumption (30 g) three or more days per week to the prevalence of abdominal obesity and metabolic syndrome (MetS) in an elderly population from the north of Spain. Methods: The study consists of an observational, descriptive, cross-sectional, and correlational study conducted in 556 non-institutionalised individuals between 65 and 79 years of age. To define the consumption recommendation of nuts the indication of the questionnaire MEDAS-14 was followed. The diagnosis of MetS was conducted using the International Diabetes Federation (IDF) criteria. Results: In 264 subjects aged 71.9 (SD: ±4.2) years old, 39% of whom were men, the adherence to nut consumption recommendations was 40.2%. Of these individuals, 79.5% had abdominal obesity. The prevalence of MetS was 40.2%, being 47.6% in men and 35.4% in women (p < 0.05). A nut consumption lower than recommended was associated with a 19% higher prevalence of abdominal obesity (Prevalence Ratio: 1.19; 95% CI: 1.03−1.37; p < 0.05) and a 61% higher prevalence of MetS (Prevalence Ratio: 1.61; 95% CI: 1.16−2.25; p = 0.005) compared to a consumption of ≥3 servings per week. Conclusion: An inverse relationship was established between nut consumption and the prevalence of abdominal obesity and metabolic syndrome.
metadata
Cubas-Basterrechea, Gloria; Elío Pascual, Iñaki; Sumalla Cano, Sandra; Aparicio Obregón, Silvia; González-Antón, Carolina Teresa y Muñoz-Cacho, Pedro
mail
SIN ESPECIFICAR, inaki.elio@uneatlantico.es, sandra.sumalla@uneatlantico.es, silvia.aparicio@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
The Regular Consumption of Nuts Is Associated with a Lower Prevalence of Abdominal Obesity and Metabolic Syndrome in Older People from the North of Spain.
International Journal of Environmental Research and Public Health, 19 (3).
p. 1256.
ISSN 1660-4601
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés Chemical modification of guar gum was done by graft copolymerization of monomer hydroxyethyl methacrylate (HEMA) using azobisisobutyronitrile (AIBN) as initiator. Optimal reaction parameters were settled by varying one reaction condition and keeping the other constant. The optimum reaction conditions worked out were solvent system: binary, [H2O] = 15.00 mL, [acetone] = 5.00 mL, [HEMA] = 82.217× 10−2 mol/L, [AIBN] = 3.333 × 10−2 mol/L, reaction time = 3 h, reaction temperature = 60 °C on to 1.00 g guar gum with Pg = 1694.6 and %GE = 68,704.152. Pure guar gum polymer and grafts were analyzed by several physicochemical investigation techniques like FTIR, SEM, XRD, EDX, and swelling studies. Percent swelling of the guar gum polymer and grafts was investigated at pH 2.2, 7.0, 7.4 and 9.4 concerning time. The finest yield of Ps was recorded at pH 9.4 with time 24 h for graft copolymer. Guar gum and grafted samples were explored for the sorption of toxic dye Bismarck brown Y from the aqueous solution with respect to variable contact time, pH, temperature and dye concentration so as to investigate the stimuli responsive sorption behaviour. Graft copolymers showed better results than guar gum with percent dye uptake (Du) of 97.588 % in 24 h contact time, 35 °C temperature, 9.4 pH at 150.00 ppm dye feed concentration as compared to Guar gum which only showed 85.260 % dye uptake at alike dye fed concentration. The kinetic behaviour of the polymeric samples was evaluated by applying many adsorption isotherms and kinetic models. The value of 1/n was between 0 → 1 showing that there was physisorption of the BB dye that took place on the surface of the polymers. Thermodynamics of BB Y adsorption onto hydrogels was investigated concerning the Van't Hoff equation. -∆G° values obtained from the curve proved the spontanity of the process. Within the context of adsorption efficiency, an investigation was conducted to examine the process of sorption of Bismarck brown Y dye from aqueous solutions. The graft copolymers demonstrated remarkable adsorption abilities, achieving a dye uptake (Du) of 97.588 % over a 24-h period at a temperature of 35 °C, pH level of 9.4, and a dye concentration of 150.00 ppm. The raised adsorption capacity was additionally corroborated by the application of several adsorption isotherms and kinetic models, which indicated that physisorption is the prevailing process/mechanism. Additionally, the thermodynamic research, utilising the Van't Hoff equation, validated the spontaneity of the adsorption phenomenon, as evidenced by the presence of a negative ∆G° values. The thermodynamic analysis revealed herein establishes a strong scientific foundation for the effectiveness of adsorbent composed of graft copolymers based on guar gum. The research conclude the efficiency of the guar gum based grafted copolymers for the water remediation as efficient adsorbents. The captured dye can be re-utilised and the hydrogels can be used for the same purpose in number of cycles. metadata Chopra, Lalita; Sharma, Anika; Chohan, Jasgurpreet Singh; Upadhyay, Viyat Varun; Singh, Rajesh; Sharma, Shubham; Dwivedi, Shashi Prakash; Kumar, Abhinav y Tag-Eldin, Elsayed M. mail SIN ESPECIFICAR (2024) Synthesis and characterizations of super adsorbent hydrogel based on biopolymer, Guar Gum-grafted-Poly (hydroxyethyl methacrylate) (Gg-g-Poly (HEMA)) for the removal of Bismarck brown Y dye from aqueous solution. International Journal of Biological Macromolecules, 256. p. 128518. ISSN 01418130
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Data mining is an analytical approach that contributes to achieving a solution to many problems by extracting previously unknown, fascinating, nontrivial, and potentially valuable information from massive datasets. Clustering in data mining is used for splitting or segmenting data items/points into meaningful groups and clusters by grouping the items that are near to each other based on certain statistics. This paper covers various elements of clustering, such as algorithmic methodologies, applications, clustering assessment measurement, and researcher-proposed enhancements with their impact on data mining thorough grasp of clustering algorithms, its applications, and the advances achieved in the existing literature. This study includes a literature search for papers published between 1995 and 2023, including conference and journal publications. The study begins by outlining fundamental clustering techniques along with algorithm improvements and emphasizing their advantages and limitations in comparison to other clustering algorithms. It investigates the evolution measures for clustering algorithms with an emphasis on metrics used to gauge clustering quality, such as the F-measure and the Rand Index. This study includes a variety of clustering-related topics, such as algorithmic approaches, practical applications, metrics for clustering evaluation, and researcher-proposed improvements. It addresses numerous methodologies offered to increase the convergence speed, resilience, and accuracy of clustering, such as initialization procedures, distance measures, and optimization strategies. The work concludes by emphasizing clustering as an active research area driven by the need to identify significant patterns and structures in data, enhance knowledge acquisition, and improve decision making across different domains. This study aims to contribute to the broader knowledge base of data mining practitioners and researchers, facilitating informed decision making and fostering advancements in the field through a thorough analysis of algorithmic enhancements, clustering assessment metrics, and optimization strategies.
metadata
Chaudhry, Mahnoor; Shafi, Imran; Mahnoor, Mahnoor; Ramírez-Vargas, Debora L.; Bautista Thompson, Ernesto y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, debora.ramirez@unini.edu.mx, ernesto.bautista@unini.edu.mx, SIN ESPECIFICAR
(2023)
A Systematic Literature Review on Identifying Patterns Using Unsupervised Clustering Algorithms: A Data Mining Perspective.
Symmetry, 15 (9).
p. 1679.
ISSN 2073-8994
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
This study is based on real teaching conditions due to the outbreak of COVID 19 in 2020.
metadata
Carrero Mercado, Carla Rosario
mail
carrerocarla@gmail.com
(2022)
Teaching strategies and e-learning using Google for Education tools in school students of IV secondary from Colegio Peruano Aleman Beata Imelda.
Masters thesis, SIN ESPECIFICAR.
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Thyroid disease prediction has emerged as an important task recently. Despite existing approaches for its diagnosis, often the target is binary classification, the used datasets are small-sized and results are not validated either. Predominantly, existing approaches focus on model optimization and the feature engineering part is less investigated. To overcome these limitations, this study presents an approach that investigates feature engineering for machine learning and deep learning models. Forward feature selection, backward feature elimination, bidirectional feature elimination, and machine learning-based feature selection using extra tree classifiers are adopted. The proposed approach can predict Hashimoto’s thyroiditis (primary hypothyroid), binding protein (increased binding protein), autoimmune thyroiditis (compensated hypothyroid), and non-thyroidal syndrome (NTIS) (concurrent non-thyroidal illness). Extensive experiments show that the extra tree classifier-based selected feature yields the best results with 0.99 accuracy and an F1 score when used with the random forest classifier. Results suggest that the machine learning models are a better choice for thyroid disease detection regarding the provided accuracy and the computational complexity. K-fold cross-validation and performance comparison with existing studies corroborate the superior performance of the proposed approach.
metadata
Chaganti, Rajasekhar; Rustam, Furqan; De La Torre Díez, Isabel; Vidal Mazón, Juan Luis; Rodríguez Velasco, Carmen Lilí y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR
(2022)
Thyroid Disease Prediction Using Selective Features and Machine Learning Techniques.
Cancers, 14 (16).
p. 3914.
ISSN 2072-6694
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Cerrado
Inglés
The development of underwater wireless sensor networks (UWSNs) has attracted great interest from many researchers and scientists to detect and monitor unfamiliar underwater domains. To achieve this goal, collecting data with an underwater network of sensors is primordial. Moreover, real-time information transmission needs to be achieved through efficient and enabling technologies for node deployment and data collection in UWSN. The Internet of Things (IoT) helps in real time data transmission, and it has great potential in UWSN, i.e., the Internet of Underwater Things (IoUT). The Internet of Underwater Things (IoUT) is a modern communication ecosystem for undersea things in marine and underwater environments. Intelligent boats and ships, automatic maritime transportation, location and navigation, undersea discovery, catastrophe forecasting and avoidance, as well as intelligent monitoring and security are all intertwined with IoUT technology. In this paper, the enabling technologies of UWSN along with several fundamental key aspects are scrupulously explained. The study aims to inquire about node deployment and data collection strategies, and then encourages researchers to lay the groundwork for new node deployment and advanced data collection techniques that enable effective underwater communication techniques. Besides different types of communication media, applications of UWSNs are also part of this paper. Various existing data collection protocols based on the deployment models are simulated using Network Simulator (NS 2.30) to analyse and compare the performance of state-of-the-art techniques.
metadata
Chaudhary, Monika; Goyal, Nitin; Benslimane, Abderrahim; Awasthi, Lalit Kumar; Alwadain, Ayed y Singh, Aman
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es
(2022)
Underwater Wireless Sensor Networks: Enabling Technologies for Node Deployment and Data Collection Challenges.
IEEE Internet of Things Journal.
p. 1.
ISSN 2372-2541
Artículo
Materias > Educación física y el deporte
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Elite performance and sporting success are often the result of optimal integration and synergy of all components of sports preparedness (i.e., health, technical and tactical skills, bioenergetic and neuromuscular abilities and capacities, anthropometric characteristics, cognition, emotions, creativity, or personality), which evolve because of systematic long-term sports preparation. However, the relative importance of these characteristics varies between individual and team sports. While some individual sports require a high standard of bioenergetic and neuromuscular abilities and capacities, team sports performance is closely related to technical and tactical skills, which may compensate for weakness within the fitness level (1). Nonetheless, successful team sport performances seem to be much more dependent on the interaction among a wide range of factors than on the maximum development of one or two factors in isolation. In team sports, elite performance emerges from the interaction among the individual parts (2) to overcome the opponent during competition.
Sports may be categorized according to the degree of predictability of the environment that they are played in (3). Team sports occur in highly unpredictable environments due to the interactions with both teammates and opponents, with performance dealing with this unpredictability. Thus, it is important to have a clear understanding of the integrative systems and the principles that rule their interactions with the environment, keeping in mind the main aim of the process: developing the diversity/unpredictability potential of athletes/teams (4) to afford the emergence of rich patterns of behavior from players to adapt quickly and effectively in dynamically changing and unpredictable environments (5).
Performance in team sports is affected by several factors that affect the organization of training and competitions. These include, for example, COVID-19 cases (6), PCR tests (7), air flights and their effects prior to competition (8), injuries (9), or match-congested schedules (10). The interaction among these factors may also influence player availability. The concept of player availability is a common one in elite team sports. Available players can be considered the ones who are injury-free and ready to compete whether the head coach chooses to put them on the lineup. Thus, an available state would be when a player is fit and recovered enough to compete. On the other hand, player unavailability would be considered a state which includes injury, sanction or suspension, or other reasons that would keep a player out of match. However, this topic needs to be explored more in elite team sport environments. Considering previous enriching work, it remains important to further progress and provide academic knowledge in order to support coaches/managers, strength and conditioning coaches, sport scientists, and medical team members (e.g., doctors, physicians, and physiotherapists) in their working environments. While widely-advocated scientific groundwork is considered throughout this manuscript, the main aim of this opinion article is to provide a review of factors related to player availability and its influence on performance in elite team sports (Figure 1). Finally, some practical suggestions and recommendations are provided to deal with constant alterations in player's availability and performance fluctuations.
metadata
Calleja-González, Julio; Mallo, Javier; Cos, Francesc; Sampaio, Jaime; Jones, Margaret T.; Marqués-Jiménez, Diego; Mielgo-Ayuso, Juan; Freitas, Tomás T.; Alcaraz, Pedro E.; Vilamitjana, Javier; Ibañez, Sergio J.; Cuzzolin, Francesco; Terrados, Nicolás; Bird, Stephen P.; Zubillaga, Asier; Huyghe, Thomas; Jukic, Igor; Lorenzo, Alberto; Loturco, Irineu; Delextrat, Anne; Schelling, Xavi; Gómez-Ruano, Miguel; López-laval, Isaac; Vazquez, Jairo; Conte, Daniele; Velarde-Sotres, Álvaro; Bores Cerezal, Antonio; Ferioli, Davide; García, Franc; Peirau, Xavier; Martin-Acero, Rafael y Lago-Peñas, Carlos
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, alvaro.velarde@uneatlantico.es, antonio.bores@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
A commentary of factors related to player availability and its influence on performance in elite team sports.
Frontiers in Sports and Active Living, 4.
ISSN 2624-9367
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Cerrado
Inglés
The Internet of Things (IoT) is a network of interconnected devices that includes low-end devices (sensors) and high-end devices (servers). The routing protocol used the Low-Power and Lossy Networks (RPL) protocol, which was designed to collect data in Low-Power and Lossy Networks (LLN) efficiently and reliably. The RPL rank property specifies how sensor nodes are placed in Destination Oriented Directed Acyclic Graphs (DODAG) based on an Objective Function (OF). The OF includes information such as the Expected Transmission Count (ETX) and packet delivery rate. The rank property aids in routing path optimization, reducing control overhead, and maintaining a loop-free topology by using rank-based data path validation. However, it causes many issues, such as optimal parent selection, next-hop node selection, and network instability. We proposed an Enhanced Opportunistic Rank-based Parent Node Selection for Sustainable and Smart IoT Networks to address these issues. The optimal parent node is determined by forecasting the expected energy of each node using Received Signal Strength (RSS) and an enhanced reinforcement learning algorithm. The proposed method addresses the issue of selecting the next-hop neighbor node and improves routing stability. Furthermore, when a large number of new nodes try to join the sustainable IoT-based smart cities, the proposed technique provides optimal load balance
metadata
Chithaluru, Premkumar; Singh, Aman; Mahmoud, Mahmoud Shuker; Kumar, Sunil; Vidal Mazón, Juan Luis; Alkhayyat, Ahmed y Anand, Divya
mail
SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, juanluis.vidal@uneatlantico.es, SIN ESPECIFICAR, divya.anand@uneatlantico.es
(2023)
An enhanced opportunistic rank-based parent node selection for sustainable & smart IoT networks.
Sustainable Energy Technologies and Assessments, 56.
p. 103079.
ISSN 22131388
D
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Cerrado
Inglés
Given that it provides nourishment for more than half of humanity, rice is regarded as one of the most significant plants in the world in agriculture. The quantity and quality of the product may be impacted by diseases that can damage rice plants which can occasionally cause crop losses ranging from 30 to 60%. This manuscript proposed a Convolutional Neural Network (CNN) and Visual Geometry Group (VGG)19 i.e. CNN-VGG19 model with a transfer learning-based method for the precise identification and classification of rice leaf diseases. This scheme employs a transfer learning technique based on the VGG19 which can identify the brown spot class. The accuracy is 93.0% in the deployment of the dataset of rice leaf disease. The other parameters are sensitivity, specificity, precision and F1-score with 89.9%, 94.7%, 92.4% and 90.5% respectively. The developed technique obtained better results as compared to the existing baseline models.
metadata
Dogra, Roopali; Rani, Shalli; Singh, Aman; Albahar, Marwan Ali; Pascual Barrera, Alina Eugenia y Alkhayyat, Ahmed
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, alina.pascual@unini.edu.mx, SIN ESPECIFICAR
(2023)
Deep learning model for detection of brown spot rice leaf disease with smart agriculture.
Computers and Electrical Engineering, 109.
p. 108659.
ISSN 00457906
Artículo Materias > Biomedicina Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Breast cancer (BC) is one of the most common diseases in the global population. It most commonly presents in women; however, there has been an increase in the number of men diagnosed with the disease, although at a lower rate. Its specific characteristics and associated risk factors mean that preventative measures are considered to be one of the most important methods of avoiding BC. Therefore, education is a fundamental part of this process. The objective of this study is to report on the educational interventions on BC carried out in healthcare between 2016 and 2021. To this end, an integrative review was carried out using the following databases: PubMed (NCBI), Science Direct, Scopus, SciELO and Google Scholar, using the keywords ‘breast cancer’, ‘intervention education’, ‘prevention’ and the Boolean operator ‘AND’. Quantitative, full-text articles in English, Spanish or Portuguese were included. Finally, 19 articles were selected for analysis and it was found that, with regard to educational interventions on BC carried out in healthcare, one article included men and women and the remaining 18 included only women, with interventions carried out in sessions, workshops, in stages and using dynamic techniques. Therefore, there is a pressing need for educational interventions on BC for men and women at all stages of life; however, priority should be given to the young population in order to allow for early prevention. These interventions do not generate costs for the health sector, but they have a positive effect by increasing knowledge and promoting self-care. metadata de Carmen Ortega Jiménez, Mayra; García Rodríguez, Deysi Emilia; Hidalgo Mares, Brenda y Ortega Jiménez, Marcela mail SIN ESPECIFICAR (2021) Educational interventions on breast cancer in men and women: a necessity in primary healthcare. ecancermedicalscience, 15. ISSN 17546605
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Efficient traffic management has become a major concern within the framework of smart city projects. However, the increasing complexity of data exchanges and the growing importance of big data makes this task more challenging. Vehicular ad hoc networks (VANETs) face various challenges, including the management of massive data generated by different entities in their environment. In this context, a proposal is put forth for a real-time anomaly detection system with parallel data processing, thereby speeding up data processing. This approach accurately computes vehicle density for each section at any given time, enabling precise traffic management and the provision of information to vehicles regarding traffic density and the safest route to their destination. Furthermore, a machine learning-based prediction system has been developed to mitigate congestion problems and reduce accident risks. Simulations demonstrate that the proposed solution effectively addresses transportation issues while maintaining low latency and high precision.
metadata
Driss Laanaoui, My; Lachgar, Mohamed; Mohamed, Hanine; Hamid, Hrimech; Gracia Villar, Santos y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, SIN ESPECIFICAR
(2024)
Enhancing Urban Traffic Management Through Real-Time Anomaly Detection and Load Balancing.
IEEE Access, 12.
pp. 63683-63700.
ISSN 2169-3536
Artículo Materias > Biomedicina Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Low energy pulsed electromagnetic signals (PEMS) therapy, in the field of bioelectronics, has been suggested as a promising analgesic therapy with special interest in treating conditions with poor response to pharmacotherapy. This study evaluated the effectiveness of PEMS therapy on the treatment of chronic low back pain patients with a neuropathic component. A group of 64 individuals with such condition was allocated to a 2-week treatment period (10 twenty-minute sessions on consecutive days) with an active PEMS therapy device or an inactive device in random order. The pain was assessed on a visual analog scale, and the functional status was assessed using the SF-12 questionnaire. The visual analog scale scores were lower after treatment than at baseline but only in the group treated with the active device. According to the DN4 score, neuropathic pain decreased in both experimental groups with respect to baseline, but this was only significant for the group treated with the active device. Similarly, an improvement in the SF-12 and Medical Outcomes Study (MOS) sleep scale components was reported. The study demonstrated that low-energy PEMS therapy was efficient in reducing pain and improving function in chronic low back pain patients with a neuropathic component. metadata de Teresa, Carlos; Varela-López, Alfonso; Rios-Álvarez, Susana; Gálvez, Rafael; Maire, Coralie; Gracia Villar, Santos; Battino, Maurizio y Quiles, José L. mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, maurizio.battino@uneatlantico.es, jose.quiles@uneatlantico.es (2021) Evaluation of the Analgesic Efficacy of a Bioelectronic Device in Non-Specific Chronic Low Back Pain with Neuropathic Component. A Randomized Trial. Journal of Clinical Medicine, 10 (8). p. 1781. ISSN 2077-0383
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés This study explored the impact of varying weight percentages of TiMoVWCr high-entropy alloy (HEA) powder addition on A356 composites produced using friction stir processing (FSP). Unlike previous research that often focused on singular aspects, such as mechanical properties, or microstructural analysis, this investigation systematically examined the multifaceted performance of A356 composites by comprehensively assessing the microstructure, interfacial bonding strength, mechanical properties, and wear behavior. The study identified a uniform distribution of TiMoVWCr HEA powder in the composition A356/2%Ti2%Mo2%V2%W2%Cr, highlighting the effectiveness of the FSP technique in achieving homogeneous dispersion. Strong bonding between the reinforcement and matrix material was observed in the same composition, indicating favorable interfacial characteristics. Mechanical properties, including tensile strength and hardness, were evaluated for various compositions, demonstrating significant improvements across the board. The addition of 2%Ti2%Mo2%V2%W2%Cr powder enhanced the tensile strength by 36.39%, while hardness improved by 62.71%. Similarly, wear resistance showed notable enhancements ranging from 35.56 to 48.89% for different compositions. Microstructural analysis revealed approximately 1640.59 grains per square inch for the A356/2%Ti2%Mo2%V2%W2%Cr processed composite at 500 magnifications. In reinforcing Al composites with Ti, Mo, V, W, and Cr high-entropy alloy (HEA) particles, each element imparted distinct benefits. Titanium (Ti) enhanced strength and wear resistance, molybdenum (Mo) contributed to improved hardness, vanadium (V) promoted hardenability, tungsten (W) enhanced wear resistance, and chromium (Cr) provided wear resistance and hardness. Anticipating the potential applications of the developed composite, the study suggests its suitability for the aerospace sector, particularly in casting lightweight yet high-strength parts such as aircraft components, engine components, and structural components, underlining the significance of the investigated TiMoVWCr HEA powder-modified A356 composites. metadata Dwivedi, Shashi Prakash; Sharma, Shubham; Li, Changhe; Zhang, Yanbin; Singh, Rajesh; Kumar, Abhinav; Awwad, Fuad A.; Khan, M. Ijaz y Ismail, Emad A. A. mail SIN ESPECIFICAR (2024) Exploring Microstructural, Interfacial, Mechanical, and Wear Properties of AlSi7Mg0.3 Composites with TiMOVWCr High-Entropy Alloy Powder. ACS Omega, 9 (17). pp. 18813-18826. ISSN 2470-1343
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
In December 2019, a group of people in Wuhan city of Hubei province of China were found to be affected by an infection called dark etiology pneumonia. The outbreak of this pneumonia infection was declared a deadly disease by the China Center for Disease Control and Prevention on January 9, 2020, named Novel Coronavirus 2019 (nCoV-2019). This nCoV-2019 is now known as COVID-19. There is a big list of infections of this coronavirus which is present in the form of a big family. This virus can cause several diseases that usually develop with a serious problem. According to the World Health Organization (WHO), 2019-nCoV has been placed as the modern generation of Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) coronaviruses, so COVID-19 can repeatedly change its internal genome structure to extend its existence. Understanding and accurately predicting the mutational properties of the genome structure of COVID-19 can form a good leadership role in preventing and fighting against coronavirus. In this research paper, an analytical approach has been presented which is based on the k-means cluster technique of machine learning to find the clusters over the mutational properties of the COVID-19 viruses’ complete genome. This method would be able to act as a promising tool to monitor and track pathogenic infections in their stable and local genetics/hereditary varieties. This paper identifies five main clusters of mutations with as best in most cases in the coronavirus that could help scientists and researchers develop disease control vaccines for the transformation of coronaviruses.
metadata
Dumka, Ankur; Verma, Parag; Singh, Rajesh; Bhardwaj, Anuj; Alsubhi, Khalid; Anand, Divya; Delgado Noya, Irene y Aparicio Obregón, Silvia
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, irene.delgado@uneatlantico.es, silvia.aparicio@uneatlantico.es
(2022)
Intelligent Approach for Clustering Mutations’ Nature of COVID-19 Genome.
Computers, Materials & Continua, 72 (3).
pp. 4453-4466.
ISSN 1546-2226
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés Reliability predictions are routinely performed according to mission profiles, in photovoltaic applications including at least irradiance and temperature. This paper is aimed at assessing the necessity of including humidity meteorological data in the mission profile. A DC/DC soft-switching converter rated at 1 kW, and aimed at PV applications is selected as case study. Its reliability is predicted using FIDES guide, using seasonal mission profiles for eight different sites with climates ranging from tropical-humid to hot and dry. The prediction results are contrasted, assuming that the most failure-prone converters are those at the highest temperature. The results corroborate that the thermal stress factor has a large impact on the increase in the failure rate of semiconductor devices. Nevertheless, humidity also has a noticeable impact on the failure rate, contributing with 30% in the transistors, with 6% in the diodes, and in minor proportion in the passive devices. The impact of humidity is larger when it occurs simultaneously with sustained, high temperatures, and it was found that neglecting humidity might underestimate the failure rate by as much as 35% in hot, humid sites. Therefore, detailed humidity meteorological data should be included in the mission profile. metadata De León Aldaco, Susana Estefany; Calleja, Hugo y Aguayo Alquicira, Jesus mail SIN ESPECIFICAR (2020) Mission profiles and hygrothermal conditions: Its effects on the reliability of a soft switching converter. Microelectronics Reliability, 111. p. 113707. ISSN 00262714
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
This is an effort to analyze the reaction of stock prices of Indian public and private banks listed in NSE and BSE to the announcement of seven best case news events. Several recent studies have analyzed the correlation between stock prices and news announcements; however, there is no evidence on how private and public sector Indian bank stocks react to important news events independently. We examine these features by concentrating on a sample of banking and government news events. We classify these news events to create a group of negative and a group of positive tone of announcements (sentiments). The statistical results show that the negative banking news announcements had a one-month impact on private banks, with statistically significant negative mean CARs. However, with highly statistically substantial negative mean CARs, the influence of the negative banking news announcements on public banks was observed for two months after the news was published. Furthermore, the influence of the positive banking news on private banks persisted a month after the news was published. Positive banking news events had an influence on public banks for five days after they were published. The study concludes that public bank stocks react more to negative news announcements than positive news announcements in the same manner as the sentimental polarity of the news announcements as compared to private bank stocks. First, we retrieved the news articles published in prominent online financial news portals between 2017 and 2020, and the seven major news events were extracted and classified using multi-class text classification. The Random Forest classifier produced a significant accuracy of 94% with pre-trained embeddings of DistilBERT, a neural network model, which outperformed the traditional feature representation technique, TF-IDF. The training data for the classifier were balanced using the SMOTE sampling technique
metadata
Dogra, Varun; Alharithi, Fahd S.; Álvarez, Roberto Marcelo; Singh, Aman y Qahtani, Abdulrahman M.
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, roberto.alvarez@uneatlantico.es, aman.singh@uneatlantico.es, SIN ESPECIFICAR
(2022)
NLP-Based Application for Analyzing Private and Public Banks Stocks Reaction to News Events in the Indian Stock Exchange.
Systems, 10 (6).
p. 233.
ISSN 2079-8954
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Coronavirus (COVID-19) has impacted nearly every person across the globe either in terms of losses of life or as of lockdown. The current coronavirus (COVID-19) pandemic is a rare/special situation where people can express their feelings on Internet-based social networks. Social media is emerging as the biggest platform in recent years where people spend most of their time expressing themselves and their emotions. This research is based on gathering data from Twitter and analyzing the behavior of the people during the COVID-19 lockdown. The research is based on the logic expressed by people in this perspective and emotions for the suffering of COVID-19 and lockdown. In this research, we have used a Long Short-Term Memory (LSTM) network model with Convolutional Neural Network using Keras python deep-learning library to determine whether social media platform users are depressed in terms of positive, negative, or neutral emotional out bust based on their Twitter posts. The results showed that the model has 88.14% accuracy (representation of the correct prediction over the test dataset) after 10 epochs which most tweets showed had neutral polarity. The evaluation shows interesting results in positive (1), negative (–1), and neutral (0) emotions through different visualization.
metadata
Dumka, Ankur; Verma, Parag; Singh, Rajesh; Kumar Bisht, Anil; Anand, Divya; Moaiteq Aljahdali, Hani; Delgado Noya, Irene y Aparicio Obregón, Silvia
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, SIN ESPECIFICAR, irene.delgado@uneatlantico.es, silvia.aparicio@uneatlantico.es
(2022)
A Novel Deep Learning Based Healthcare Model for COVID-19 Pandemic Stress Analysis.
Computers, Materials & Continua, 72 (3).
pp. 6029-6044.
ISSN 1546-2226
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
The evolution of the COVID-19 pandemic has been associated with variations in clinical presentation and severity. Similarly, prediction scores may suffer changes in their diagnostic accuracy. The aim of this study was to test the 30-day mortality predictive validity of the 4C and SEIMC scores during the sixth wave of the pandemic and to compare them with those of validation studies. This was a longitudinal retrospective observational study. COVID-19 patients who were admitted to the Emergency Department of a Spanish hospital from December 15, 2021, to January 31, 2022, were selected. A side-by-side comparison with the pivotal validation studies was subsequently performed. The main measures were 30-day mortality and the 4C and SEIMC scores. A total of 27,614 patients were considered in the study, including 22,361 from the 4C, 4,627 from the SEIMC and 626 from our hospital. The 30-day mortality rate was significantly lower than that reported in the validation studies. The AUCs were 0.931 (95% CI: 0.90–0.95) for 4C and 0.903 (95% CI: 086–0.93) for SEIMC, which were significantly greater than those obtained in the first wave. Despite the changes that have occurred during the coronavirus disease 2019 (COVID-19) pandemic, with a reduction in lethality, scorecard systems are currently still useful tools for detecting patients with poor disease risk, with better prognostic capacity.
metadata
de Santos Castro, Pedro Ángel; del Pozo Vegas, Carlos; Pinilla Arribas, Leyre Teresa; Zalama Sánchez, Daniel; Sanz-García, Ancor; Vásquez del Águila, Tony Giancarlo; González Izquierdo, Pablo; de Santos Sánchez, Sara; Mazas Pérez-Oleaga, Cristina; Dominguez Azpíroz, Irma; Elío Pascual, Iñaki y Martín-Rodríguez, Francisco
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, cristina.mazas@uneatlantico.es, irma.dominguez@unini.edu.mx, inaki.elio@uneatlantico.es, SIN ESPECIFICAR
(2024)
Performance of the 4C and SEIMC scoring systems in predicting mortality from onset to current COVID-19 pandemic in emergency departments.
Scientific Reports, 14 (1).
ISSN 2045-2322
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
The evolution of the COVID-19 pandemic has been associated with variations in clinical presentation and severity. Similarly, prediction scores may suffer changes in their diagnostic accuracy. The aim of this study was to test the 30-day mortality predictive validity of the 4C and SEIMC scores during the sixth wave of the pandemic and to compare them with those of validation studies. This was a longitudinal retrospective observational study. COVID-19 patients who were admitted to the Emergency Department of a Spanish hospital from December 15, 2021, to January 31, 2022, were selected. A side-by-side comparison with the pivotal validation studies was subsequently performed. The main measures were 30-day mortality and the 4C and SEIMC scores. A total of 27,614 patients were considered in the study, including 22,361 from the 4C, 4,627 from the SEIMC and 626 from our hospital. The 30-day mortality rate was significantly lower than that reported in the validation studies. The AUCs were 0.931 (95% CI: 0.90–0.95) for 4C and 0.903 (95% CI: 086–0.93) for SEIMC, which were significantly greater than those obtained in the first wave. Despite the changes that have occurred during the coronavirus disease 2019 (COVID-19) pandemic, with a reduction in lethality, scorecard systems are currently still useful tools for detecting patients with poor disease risk, with better prognostic capacity.
metadata
de Santos Castro, Pedro Ángel; del Pozo Vegas, Carlos; Pinilla Arribas, Leyre Teresa; Zalama Sánchez, Daniel; Sanz-García, Ancor; Vásquez del Águila, Tony Giancarlo; González Izquierdo, Pablo; de Santos Sánchez, Sara; Mazas Pérez-Oleaga, Cristina; Dominguez Azpíroz, Irma; Elío Pascual, Iñaki y Martín-Rodríguez, Francisco
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, cristina.mazas@uneatlantico.es, irma.dominguez@unini.edu.mx, inaki.elio@uneatlantico.es, SIN ESPECIFICAR
(2024)
Performance of the 4C and SEIMC scoring systems in predicting mortality from onset to current COVID-19 pandemic in emergency departments.
Scientific Reports, 14 (1).
ISSN 2045-2322
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Objective The aim was to explore the association of demographic and prehospital parameters with short-term and long-term mortality in acute life-threatening cardiovascular disease by using a hazard model, focusing on elderly individuals, by comparing patients under 75 years versus patients over 75 years of age.
Design Prospective, multicentre, observational study.
Setting Emergency medical services (EMS) delivery study gathering data from two back-to-back studies between 1 October 2019 and 30 November 2021. Six advanced life support (ALS), 43 basic life support and five hospitals in Spain were considered.
Participants Adult patients suffering from acute life-threatening cardiovascular disease attended by the EMS.
Primary and secondary outcome measures The primary outcome was in-hospital mortality from any cause within the first to the 365 days following EMS attendance. The main measures included prehospital demographics, biochemical variables, prehospital ALS techniques used and syndromic suspected conditions.
Results A total of 1744 patients fulfilled the inclusion criteria. The 365-day cumulative mortality in the elderly amounted to 26.1% (229 cases) versus 11.6% (11.6%) in patients under 75 years old. Elderly patients (≥75 years) presented a twofold risk of mortality compared with patients ≤74 years. Life-threatening interventions (mechanical ventilation, cardioversion and defibrillation) were also related to a twofold increased risk of mortality. Importantly, patients suffering from acute heart failure presented a more than twofold increased risk of mortality.
Conclusions This study revealed the prehospital variables associated with the long-term mortality of patients suffering from acute cardiovascular disease. Our results provide important insights for the development of specific codes or scores for cardiovascular diseases to facilitate the risk of mortality characterisation.
metadata
del Pozo Vegas, Carlos; Zalama-Sánchez, Daniel; Sanz-Garcia, Ancor; López-Izquierdo, Raúl; Sáez-Belloso, Silvia; Mazas Pérez-Oleaga, Cristina; Dominguez Azpíroz, Irma; Elío Pascual, Iñaki y Martín-Rodríguez, Francisco
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, cristina.mazas@uneatlantico.es, irma.dominguez@unini.edu.mx, inaki.elio@uneatlantico.es, SIN ESPECIFICAR
(2023)
Prehospital acute life-threatening cardiovascular disease in elderly: an observational, prospective, multicentre, ambulance-based cohort study.
BMJ Open, 13 (11).
e078815.
ISSN 2044-6055
Artículo Materias > Psicología Universidad Internacional Iberoamericana México > Investigación > Congresos Abierto Inglés SIN ESPECIFICAR metadata Duñabeitia, Jon A.; Griffin, Kim L.; Martín, Juan L.; Oliva, Mireia; Sámano, María L. y Ivaz, Lela mail SIN ESPECIFICAR, kim.griffin@uneatlantico.es, juan.martin@uneatlantico.es, mireia.oliva@uneatlantico.es, marialuisa.samano@uneatlantico.es, SIN ESPECIFICAR (2016) The Spanish General Knowledge Norms. Front. Psychol., 7. p. 1888. ISSN 1664-1078
E
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
BACKGROUND:In Spain, there are several studies published on the relationship between eating habits and lifestyle among university students; but only a few of them are focused on online postgraduate students. OBJECTIVE:Herein we aimed to evaluate the degree of adherence to the Mediterranean diet pyramid (2010 edition), non-communicable diseases (NCDs), and lifestyle in online postgraduate students aged 20–65 years belonging to the food area of the Fundación Universitaria Iberoamericana (FUNIBER). METHODS:We performed a descriptive cross-sectional study including 100 online post-graduate students aged 20–65 years who were recruited by an accidental non-probabilistic sampling method consisting of a questionnaire on their sociodemographic characteristics, NCDs, lifestyle, and a 3-day food intake record (3-d). RESULTS:The profile of the students was 74% women, with a mean age of 36.6 (±10.5) years and body mass index (BMI) of 22.6 kg / m2 (±3.3). 71% of the volunteers presented normal weight, while 20% were overweight. Indeed, only a low percentage of the volunteers presented hypertension (1%), cardiovascular disease (0%), diabetes mellitus 1 (2%), diabetes mellitus 2 (3%), hypercholesterolemia (9%), and hyperuricemia (2%). Concerning lifestyle, (77%) of students were non-smokers, (78%) consumed beverages with caffeine, (51%) did not consume alcoholic beverages, and nearly all of them (84%) frequently (3 times /week) practiced physical activity. 68% of the recruited students exhibited adherence to “Medium diet quality diet (4–7)” followed by (26%) with a “Poor diet quality (<3)” and “Optimal diet quality” (6%). CONCLUSIONS:Spanish postgraduate students of the nutritional area, have good health and a healthy lifestyle but are moving away from the MD model, should be established campaigns for the improvement of eating habits of the postgraduate university population.
metadata
Elío Pascual, Iñaki; Jarrin, Sandra; Elexpuru Zabaleta, Maria; Crespo-Álvarez, Jorge; Dominguez Azpíroz, Irma; Tutusaus, Kilian; Ruiz Salces, Roberto; Calderón Iglesias, Rubén y Sumalla Cano, Sandra
mail
inaki.elio@uneatlantico.es, sandra.jarrin@uneatlantico.es, maria.elexpuru@uneatlantico.es, jorge.crespo@uneatlantico.es, irma.dominguez@uneatlantico.es, kilian.tutusaus@uneatlantico.es, roberto.ruiz@uneatlantico.es, ruben.calderon@uneatlantico.es, sandra.sumalla@uneatlantico.es
(2021)
Adherence to the pyramid of the Mediterranean diet (2010), non-communicable diseases and lifestyle in online postgraduate Spanish students in the food area.
Mediterranean Journal of Nutrition and Metabolism, 14 (2).
pp. 191-205.
ISSN 1973798X
Artículo Materias > Alimentación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés The shells of cocoa beans are considered as unused agro-industrial waste. In Ecuador there are several cocoa industries, which generate significant amounts of this waste. In this research, the shells were coming from the National Arriba cocoa almonds were used for the production of flour in order to analyze its nutritional characteristics, where the important nutritional value of the same was confirmed, for its use in the bakery industry, as a food supplement or for other uses for human consumption in baked products. metadata El-Salous, Ahmed y Pascual Barrera, Alina Eugenia mail SIN ESPECIFICAR, alina.pascual@unini.edu.mx (2022) Cocoa Shells Flour for Human Consumption. Current Perspectives in Agriculture and Food Science Vol. 1, 1. pp. 39-46.
Artículo
Materias > Biomedicina
Materias > Ciencias Sociales
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Aim: The development of predictive models for patients treated by emergency medical services (EMS) is on the rise in the emergency field. However, how these models evolve over time has not been studied. The objective of the present work is to compare the characteristics of patients who present mortality in the short, medium and long term, and to derive and validate a predictive model for each mortality time. Methods: A prospective multicenter study was conducted, which included adult patients with unselected acute illness who were treated by EMS. The primary outcome was noncumulative mortality from all causes by time windows including 30-day mortality, 31- to 180-day mortality, and 181- to 365-day mortality. Prehospital predictors included demographic variables, standard vital signs, prehospital laboratory tests, and comorbidities. Results: A total of 4830 patients were enrolled. The noncumulative mortalities at 30, 180, and 365 days were 10.8%, 6.6%, and 3.5%, respectively. The best predictive value was shown for 30-day mortality (AUC = 0.930; 95% CI: 0.919–0.940), followed by 180-day (AUC = 0.852; 95% CI: 0.832–0.871) and 365-day (AUC = 0.806; 95% CI: 0.778–0.833) mortality. Discussion: Rapid characterization of patients at risk of short-, medium-, or long-term mortality could help EMS to improve the treatment of patients suffering from acute illnesses.
metadata
Enriquez de Salamanca Gambara, Rodrigo; Sanz-García, Ancor; del Pozo Vegas, Carlos; López-Izquierdo, Raúl; Sánchez Soberón, Irene; Delgado Benito, Juan F.; Martínez Díaz, Raquel; Mazas Pérez-Oleaga, Cristina; Martínez López, Nohora Milena; Dominguez Azpíroz, Irma y Martín-Rodríguez, Francisco
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, raquel.martinez@uneatlantico.es, cristina.mazas@uneatlantico.es, nohora.martinez@uneatlantico.es, irma.dominguez@unini.edu.mx, SIN ESPECIFICAR
(2024)
A Comparison of the Clinical Characteristics of Short-, Mid-, and Long-Term Mortality in Patients Attended by the Emergency Medical Services: An Observational Study.
Diagnostics, 14 (12).
p. 1292.
ISSN 2075-4418
Artículo
Materias > Educación
Materias > Comunicación
Materias > Psicología
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Communication professionals are experiencing a growing level of exposure to traumatic events as a result of their involvement in the coverage of various tragedies, including accidents, climatic disasters, rights violations, and acts of terrorism. However, it is worth noting that journalism and communication university courses often lack comprehensive instruction on effectively managing emotional challenges, anxiety, trauma, self-care, and the prevention of vicarious trauma. The objective of this study is to assess the inclusion of emotional management within the curricula of Journalism and Communication programmes offered by two universities in Catalonia, namely the University of Barcelona and the Autonomous University of Barcelona. In order to accomplish this objective, a series of semi-structured interviews were carried out with a total of twelve (12) professors who specialise in the fields of Journalism and Communication. Additionally, a thorough analysis was conducted on a set of 97 study plan guides. The results indicate that none of the participants in the interviews possess knowledge regarding any existing training programmes focused on emotional management. Furthermore, they unanimously agree on the importance of implementing such courses. The study plans did not include any subjects that were specifically dedicated to the topic of emotional management. This study presents a set of strategies aimed at creating a cross-disciplinary teaching-learning model that offers a comprehensive educational experience for students. This entails integrating precise subject matter on the previously mentioned topics, fostering critical contemplation and discourse regarding emotions within the educational setting, and advocating for ethical and sound professional behaviours.
metadata
Escudero, Carolina; Prola, Thomas; Fraga, Leticia y Soriano Flores, Emmanuel
mail
SIN ESPECIFICAR, thomas.prola@uneatlantico.es, leticia.fraga@uneatlantico.es, emmanuel.soriano@uneatlantico.es
(2023)
Emotional Management in Journalism and Communication Studies.
Social Space, 23 (2).
pp. 507-534.
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
With the rapid growth of Internet of Things (IoT) systems, ensuring robust security measures has become paramount. Microservices Architecture (MSA) has emerged as a promising approach for enhancing IoT systems security, yet its adoption in this context lacks comprehensive analysis. This systematic review addresses this research gap by examining the incorporation of MSA in IoT systems from 2010 to 2024. From an initial pool of 4388 studies, selected articles underwent thorough quality assessment with weighted critical appraisal questions and a defined inclusion threshold. This study represents the first comprehensive systematic review to investigate the potential of microservices in IoT, with a particular focus on security aspects. The review explores the merits of MSA, highlighting twelve benefits, eight key challenges, and eight security risks. Additionally, the eight best practices for implementing MSA in IoT systems are extracted. The findings underscore MSA’s utility in fortifying IoT security while also acknowledging complexities and potential vulnerabilities. Moreover, the study calls attention to the importance of incorporating complementary technologies including blockchain and machine learning to address identified gaps effectively. Finally, we propose a taxonomic classification for Microservice-based IoT security patterns, facilitating the categorization and organization of security measures in this context. Such a review can help researchers and practitioners identify existing gaps, highlight potential research directions, and provide guidelines for designing secure and efficient microservice-based IoT systems.
metadata
El Akhdar, Abir; Baidada, Chafik; Kartit, Ali; Hanine, Mohamed; Osorio García, Carlos Manuel; García Lara, Roberto y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, carlos.osorio@uneatlantico.es, roberto.garcia@unini.edu.mx, SIN ESPECIFICAR
(2024)
Exploring the Potential of Microservices in Internet of Things: A Systematic Review of Security and Prospects.
Sensors, 24 (20).
p. 6771.
ISSN 1424-8220
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
The use of social networks is part of the daily life of adolescents. Through them, they communicate with their friends and family, have fun and explore different topics. On the other hand, reading comprehension in English is one of the skills that is most worked on with students about to finish their high school studies and start university life. This degree work seeks to integrate social networks such as Instagram and WhatsApp with the development of reading comprehension in English of tenth-grade students of a public institution through a didactic proposal that includes topics of interest to students that are usually published and shared on social networks. The proposal is developed in several stages and moments as different aspects of reading comprehension are worked on, such as the speed of comprehension, the level of comprehension, and the recognition of vocabulary in the texts.In this action research, a mixed methodology was used, including aspects of the case study. For the first objective, where a diagnosis of the level of English of the students was necessary, an instrument taken from an English teaching text was applied. For the following objective, the literature on successful educational experiences in the use of social networks worldwide was reviewed. Combining the findings of the diagnosis and the literature, a didactic proposal carried out for several weeks was created. At the end of the proposal, the instrument used as a diagnosis was applied again and the new results were analyzed.Some results of this research were the low level of reading comprehension of the students evidenced in the initial diagnosis and their improvement after the implementation of the didactic proposal. It can be also deduced the need to encourage the use of ICT both in students and teachers in the development of skills in English, which has to work with the scarcity of technological resources such as computers and internet connections in the educational institution. Other aspects such as the connection of topics to the interests and likes of the students, and the need to expand the didactic proposal in other groups and for a longer time were shown in the results and conclusions of this research.
metadata
Echavarria Cifuentes, Claudia Yanet
mail
claudia.echavarria@udea.edu.co
(2022)
Proposal for the improvement of reading comprehension of English as a foreign language based on social networks for tenth grade students.
Masters thesis, SIN ESPECIFICAR.
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
The purpose of the study is to assess the risk of developing general eating disorders (ED), anorexia nervosa (AN), and bulimia nervosa (BN), as well as to examine the effects of gender, academic year, place of residence, faculty, and diet quality on that risk. Over two academic years, 129 first- and fourth-year Uneatlántico students were included in an observational descriptive study. The self-administered tests SCOFF, EAT-26, and BITE were used to determine the participants’ risk of developing ED. The degree of adherence to the Mediterranean diet (MD) was used to evaluate the quality of the diet. Data were collected at the beginning (T1) and at the end (T2) of the academic year. The main results were that at T1, 34.9% of participants were at risk of developing general ED, AN 3.9%, and BN 16.3%. At T2, these percentages were 37.2%, 14.7%, and 8.5%, respectively. At T2, the frequency of general ED in the female group was 2.5 times higher (OR: 2.55, 95% CI: 1.22–5.32, p = 0.012). The low-moderate adherence to the MD students’ group was 0.92 times less frequent than general ED at T2 (OR: 0.921, 95%CI: 0.385–2.20, p < 0.001). The most significant risk factor for developing ED is being a female in the first year of university. Moreover, it appears that the likelihood of developing ED generally increases during the academic year.
metadata
Eguren García, Imanol; Sumalla Cano, Sandra; Conde González, Sandra; Vila-Martí, Anna; Briones Urbano, Mercedes; Martínez Díaz, Raquel y Elío Pascual, Iñaki
mail
imanol.eguren@uneatlantico.es, sandra.sumalla@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, mercedes.briones@uneatlantico.es, raquel.martinez@uneatlantico.es, inaki.elio@uneatlantico.es
(2024)
Risk Factors for Eating Disorders in University Students: The RUNEAT Study.
Healthcare, 12 (9).
p. 942.
ISSN 2227-9032
Artículo
Materias > Ciencias Sociales
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
In the last two decades, there is an increasingly broad line of studies that warn about the emotional health of journalists and the challenges that it poses for communication professionals to be able to separate work issues from their personal lives. The coverage of COVID-19 exposed many journalists to situations of frustration, discomfort and stress for various reasons: long working hours, not having the appropriate technological material, added to an environment of uncertainty caused by the pandemic. This study aims to examine the possible scope of technostress –in some cases associated to digital divide– in journalists and analyze if they are aware of the uses of care of the self as a way to deal with stressful situations. For this, our research is based on documentary analysis, a survey answered by (50) fifty Argentinean journalists, and twelve (12) in-depth interviews to experienced journalists. Our findings suggest that constant exposure to computers and smartphones during the lockdown together with difficulties to connect to Internet or to have the adequate materials and the lack of coping strategies –as the care of the self– confirms the presence of technostress. Another result that emerges from this research, it should be addressed in future studies, is that some journalists’ reactions about care of the self could respond to the third person effect theory to maintain high self-esteem and not demonstrate vulnerability.
metadata
Escudero, Carolina; Prola, Thomas; Soriano Flores, Emmanuel y Silva Alvarado, Eduardo René
mail
SIN ESPECIFICAR, thomas.prola@uneatlantico.es, emmanuel.soriano@uneatlantico.es, eduardo.silva@funiber.org
(2023)
The Scope of Technostress and Care of The Self on Journalists During the Pandemic.
Przestrzeń Społeczna (Social Space), 23 (4).
pp. 20-43.
ISSN 20841558
Artículo Materias > Alimentación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés This research is carried out as an alternative for the bakery industry when looking for new sources of vegetable flour to be used in the preparation of breads and cookies, because the wheat production in Ecuador is not enough. On the other hand, the cocoa industries in the country produce a high quantity of cocoa shells that are considered as agroindustrial waste, which come from the two main varieties of cocoa, Nacional Arriba and CCN51. That is why, as a product of the grinding of these husks, flour was obtained that was used for the production of breads and biscuits with different dosage percentages based on various bibliographical sources and the authors' own experiences. In the case of the breads, the dosage used was 10% and 20%, while for the cookies a dosage of 70% and 80% was applied. Both the breads and the cookies were evaluated fortheir sensorial quality, by means of untrained judges using a hedonic scale from 1 to 5. The results confirm a high sensory quality in the cookies compared with the sensory quality obtained in the breads. metadata El Salous, A y Pascual Barrera, Alina Eugenia mail SIN ESPECIFICAR, alina.pascual@unini.edu.mx (2018) Sensorial Quality ofBreads and Cookies Prepared with Flour from The Shells of Two Varieties of Cocoain Ecuador. Italian Journal of Food Science. pp. 1-10.
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
In this paper, a novel ultra-wideband UWB antenna element with triple-band notches is proposed. The proposed UWB radiator element operates from 2.03 GHz up to 15.04 GHz with triple rejected bands at the WiMAX band (3.28–3.8 GHz), WLAN band (5.05–5.9 GHz), and X-band (7.78–8.51 GHz). In addition, the radiator supports the Bluetooth band (2.4–2.483 GHz). Three different techniques were utilized to obtain the triple-band notches. An alpha-shaped coupled line with a stub-loaded resonator (SLR) band stop filter was inserted along the main feeding line before the radiator to obtain a WiMAX band notch characteristic. Two identical U-shaped slots were etched on the proposed UWB radiator to achieve WLAN band notch characteristics with a very high degree of selectivity. Two identical metallic frames of an octagon-shaped electromagnetic band gap structure (EBG) were placed along the main feeding line to achieve the notch characteristic with X-band satellite communication with high sharpness edges. A novel UWB multiple-input multiple-output (MIMO) radiator is proposed. The proposed UWB-MIMO radiator was fabricated on FR-4 substrate material and measured. The isolation between every two adjacent ports was below −20 dB over the FCC-UWB spectrum and the Bluetooth band for the four MIMO antennas. The envelope correlation coefficient (ECC) between the proposed antennas in MIMO does not exceed 0.05. The diversity gains (DG) for all the radiators are greater than 9.98 dB.
metadata
El-Gendy, Mohamed S.; Ali, Mohamed Mamdouh M.; Bautista Thompson, Ernesto y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, ernesto.bautista@unini.edu.mx, SIN ESPECIFICAR
(2023)
Triple-Band Notched Ultra-Wideband Microstrip MIMO Antenna with Bluetooth Band.
Sensors, 23 (9).
p. 4475.
ISSN 1424-8220
F
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Artificial intelligence has been widely used in the field of dentistry in recent years. The present study highlights current advances and limitations in integrating artificial intelligence, machine learning, and deep learning in subfields of dentistry including periodontology, endodontics, orthodontics, restorative dentistry, and oral pathology. This article aims to provide a systematic review of current clinical applications of artificial intelligence within different fields of dentistry. The preferred reporting items for systematic reviews (PRISMA) statement was used as a formal guideline for data collection. Data was obtained from research studies for 2009–2022. The analysis included a total of 55 papers from Google Scholar, IEEE, PubMed, and Scopus databases. Results show that artificial intelligence has the potential to improve dental care, disease diagnosis and prognosis, treatment planning, and risk assessment. Finally, this study highlights the limitations of the analyzed studies and provides future directions to improve dental care
metadata
Fatima, Anum; Shafi, Imran; Afzal, Hammad; Díez, Isabel De La Torre; Lourdes, Del Rio-Solá M.; Breñosa, Jose; Martínez Espinosa, Julio César y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, SIN ESPECIFICAR
(2022)
Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives.
Healthcare, 10 (11).
p. 2188.
ISSN 2227-9032
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Asthma is a deadly disease that affects the lungs and air supply of the human body. Coronavirus and its variants also affect the airways of the lungs. Asthma patients approach hospitals mostly in a critical condition and require emergency treatment, which creates a burden on health institutions during pandemics. The similar symptoms of asthma and coronavirus create confusion for health workers during patient handling and treatment of disease. The unavailability of patient history to physicians causes complications in proper diagnostics and treatments. Many asthma patient deaths have been reported especially during pandemics, which necessitates an efficient framework for asthma patients. In this article, we have proposed a blockchain consortium healthcare framework for asthma patients. The proposed framework helps in managing asthma healthcare units, coronavirus patient records and vaccination centers, insurance companies, and government agencies, which are connected through the secure blockchain network. The proposed framework increases data security and scalability as it stores encrypted patient data on the Interplanetary File System (IPFS) and keeps data hash values on the blockchain. The patient data are traceable and accessible to physicians and stakeholders, which helps in accurate diagnostics, timely treatment, and the management of patients. The smart contract ensures the execution of all business rules. The patient profile generation mechanism is also discussed. The experiment results revealed that the proposed framework has better transaction throughput, query delay, and security than existing solutions
metadata
Farooq, Muhammad Shoaib; Suhail, Maryam; Qureshi, Junaid Nasir; Rustam, Furqan; de la Torre Díez, Isabel; Vidal Mazón, Juan Luis; Rodríguez Velasco, Carmen Lilí y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR
(2022)
Consortium Framework Using Blockchain for Asthma Healthcare in Pandemics.
Sensors, 22 (21).
p. 8582.
ISSN 1424-8220
Artículo
Materias > Psicología
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés, Español
Este artículo se deriva de la investigación de Tesis Doctoral sobre resiliencia, discapacidad y educación superior. El diseño del estudio es mixto, de tipo explicativo secuencial con una estrategia de investigación que integra el enfoque investigativo cuantitativo y cualitativo. El propósito de la investigación es caracterizar la resiliencia del estudiantado con discapacidad que le permite enfrentar las barreras en la educación superior con el fin de establecer los factores de enclave para el diseño de una ruta de acompañamiento resiliente. Se emplearon distintas técnicas de indagación tales como la escala de resiliencia SV-RES60, un cuestionario y una entrevista. Se contó con la participación de 110 estudiantes (55 regulares y 55 egresados) que cursan o han cursado una carrera en la UNA del año 2000 al 2020. Se realiza un análisis descriptivo y comparativo mediante herramientas básicas de estadística y con apoyo del programa SPSS permitió cuantificar y caracterizar la información recabada; asimismo establecer patrones de relación por grupos de estudio complementando con argumentación, testimonios y teoría indagada. Se concluye que el estudiantado con discapacidad presenta un estado resiliente durante su formación universitaria ante la presencia de las barreras estructurales que obstaculiza su desarrollo personal, académico y social. A partir de los resultados se justifica la actualización del personal docente y los servicios de apoyo sobre los modelos de promoción de la resiliencia y la implementación de una ruta de acompañamiento resiliente que se deriva de este estudio.
metadata
Fontana Hernández, Angélica del Socorro y Martín Ayala, Juan Luis
mail
angelica.fontana@doctorado.unini.educ.mx, juan.martin@uneatlantico.es
(2021)
Creciendo en la adversidad: la resiliencia del estudiantado con discapacidad en la Universidad Nacional, Costa Rica.
MLS Psychology Research, 4 (1).
pp. 39-58.
ISSN 26055295
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Automated dental imaging interpretation is one of the most prolific areas of research using artificial intelligence. X-ray imaging systems have enabled dental clinicians to identify dental diseases. However, the manual process of dental disease assessment is tedious and error-prone when diagnosed by inexperienced dentists. Thus, researchers have employed different advanced computer vision techniques, as well as machine and deep learning models for dental disease diagnoses using X-ray imagery. In this regard, a lightweight Mask-RCNN model is proposed for periapical disease detection. The proposed model is constructed in two parts: a lightweight modified MobileNet-v2 backbone and region-based network (RPN) are proposed for periapical disease localization on a small dataset. To measure the effectiveness of the proposed model, the lightweight Mask-RCNN is evaluated on a custom annotated dataset comprising images of five different types of periapical lesions. The results reveal that the model can detect and localize periapical lesions with an overall accuracy of 94%, a mean average precision of 85%, and a mean insection over a union of 71.0%. The proposed model improves the detection, classification, and localization accuracy significantly using a smaller number of images compared to existing methods and outperforms state-of-the-art approaches
metadata
Fatima, Anum; Shafi, Imran; Afzal, Hammad; Mahmood, Khawar; Díez, Isabel de la Torre; Lipari, Vivian; Brito Ballester, Julién y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, vivian.lipari@uneatlantico.es, julien.brito@uneatlantico.es, SIN ESPECIFICAR
(2023)
Deep Learning-Based Multiclass Instance Segmentation for Dental Lesion Detection.
Healthcare, 11 (3).
p. 347.
ISSN 2227-9032
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Traffic accidents present significant risks to human life, leading to a high number of fatalities and injuries. According to the World Health Organization’s 2022 worldwide status report on road safety, there were 27,582 deaths linked to traffic-related events, including 4448 fatalities at the collision scenes. Drunk driving is one of the leading causes contributing to the rising count of deadly accidents. Current methods to assess driver alcohol consumption are vulnerable to network risks, such as data corruption, identity theft, and man-in-the-middle attacks. In addition, these systems are subject to security restrictions that have been largely overlooked in earlier research focused on driver information. This study intends to develop a platform that combines the Internet of Things (IoT) with blockchain technology in order to address these concerns and improve the security of user data. In this work, we present a device- and blockchain-based dashboard solution for a centralized police monitoring account. The equipment is responsible for determining the driver’s impairment level by monitoring the driver’s blood alcohol concentration (BAC) and the stability of the vehicle. At predetermined times, integrated blockchain transactions are executed, transmitting data straight to the central police account. This eliminates the need for a central server, ensuring the immutability of data and the existence of blockchain transactions that are independent of any central authority. Our system delivers scalability, compatibility, and faster execution times by adopting this approach. Through comparative research, we have identified a significant increase in the need for security measures in relevant scenarios, highlighting the importance of our suggested model.
metadata
Farooq, Hamza; Altaf, Ayesha; Iqbal, Faiza; Castanedo Galán, Juan; Gavilanes Aray, Daniel y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, juan.castanedo@uneatlantico.es, daniel.gavilanes@uneatlantico.es, SIN ESPECIFICAR
(2023)
DrunkChain: Blockchain-Based IoT System for Preventing Drunk Driving-Related Traffic Accidents.
Sensors, 23 (12).
p. 5388.
ISSN 1424-8220
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Current evidence indicates that the consumption of strawberries, a natural source of a wide range of nutritive and bioactive compounds, is associated with the prevention and improvement of chronic-degenerative diseases.. Studies involving cells and animals provide evidence on the anti-inflammatory, anticarcinogenic and antiproliferative activity of the strawberry. Epidemiological and clinical studies demonstrate that its acute consumption increases plasma antioxidant capacity, improves circulating inflammatory markers and ameliorates postprandial glycemic response. At the same time, a protracted intake reduces chronic inflammation and improves plasma lipid profile, supporting cardiovascular health, especially in individuals with increased risk for metabolic syndrome. To explain these beneficial effects, much attention has been paid in the past to the antioxidant properties of strawberry polyphenols. However, recent research has shown that their biological and functional activities are related not only to the antioxidant capacity but also to the modulation of many cellular pathways involved in metabolism, survival, proliferation, and antioxidant defenses. The aim of this review is to update and discuss the molecular and cellular mechanisms proposed in recent studies to elucidate the healthy effects of strawberry polyphenols against the most common chronic diseases, such as cancer, cardiovascular diseases, metabolic syndrome, and inflammation.
metadata
Forbes-Hernandez, Tamara Y.; Gasparrini, Massimiliano; Afrin, Sadia; Bompadre, Stefano; Mezzetti, Bruno; Quiles, Josè L.; Giampieri, Francesca y Battino, Maurizio
mail
tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es
(2016)
The Healthy Effects of Strawberry Polyphenols: Which Strategy behind Antioxidant Capacity?
Critical Reviews in Food Science and Nutrition, 56 (sup1).
S46-S59.
ISSN 1040-8398
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
With the advancement in information technology, digital data stealing and duplication have become easier. Over a trillion bytes of data are generated and shared on social media through the internet in a single day, and the authenticity of digital data is currently a major problem. Cryptography and image watermarking are domains that provide multiple security services, such as authenticity, integrity, and privacy. In this paper, a digital image watermarking technique is proposed that employs the least significant bit (LSB) and canny edge detection method. The proposed method provides better security services and it is computationally less expensive, which is the demand of today’s world. The major contribution of this method is to find suitable places for watermarking embedding and provides additional watermark security by scrambling the watermark image. A digital image is divided into non-overlapping blocks, and the gradient is calculated for each block. Then convolution masks are applied to find the gradient direction and magnitude, and non-maximum suppression is applied. Finally, LSB is used to embed the watermark in the hysteresis step. Furthermore, additional security is provided by scrambling the watermark signal using our chaotic substitution box. The proposed technique is more secure because of LSB’s high payload and watermark embedding feature after a canny edge detection filter. The canny edge gradient direction and magnitude find how many bits will be embedded. To test the performance of the proposed technique, several image processing, and geometrical attacks are performed. The proposed method shows high robustness to image processing and geometrical attacks
metadata
Faheem, Zaid Bin; Ishaq, Abid; Rustam, Furqan; de la Torre Díez, Isabel; Gavilanes, Daniel; Masías Vergara, Manuel y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, daniel.gavilanes@uneatlantico.es, manuel.masias@uneatlantico.es, SIN ESPECIFICAR
(2023)
Image Watermarking Using Least Significant Bit and Canny Edge Detection.
Sensors, 23 (3).
p. 1210.
ISSN 1424-8220
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés Global climate change has generated several adverse effects, such as loss of sea ice, earlier breakup of ice on rivers and lakes, more intense heat waves and accelerated sea level rise. Of all the aforementioned effects, sea level rise is an unequivocal and forthcoming effect that has generated great interest. metadata Fernández-Díaz, Violeta Zetzangari; Canul Turriza, Roman; Kuc Castilla, Ángel Gabriel; Arreguín-Rodríguez, Gabriela J. y Mejía-Piña, Karla Gabriela mail SIN ESPECIFICAR (2022) Impact of Sea Level Rise and Flooding in Two Key Mexican Coastal Cities. Ocean Yearbook Online, 36 (1). pp. 139-157. ISSN 2211-6001
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
In today’s modern world, information and communication technologies are playing an active role in increasing the standards and quality of life for the betterment of human beings. Due to these technologies, people are now learning and experiencing new things very effectively and efficiently. With the implementation of information technology (IT)-based smart technologies in music education, learners can learn and create quality music. There is a need for the employment of information technology in music classrooms. Governments and institutions need to provide adequate resources to achieve its implementation. The traditional methods of learning are not capable of providing enough quality education to students. The present study focuses on the crucial role of information technology in the enhancement of music education. The advancements in modern technologies are expanding music education very rapidly and productively. To help learners with the use of an accurate technological method for learning purposes, various features have been identified from the existing literature. Based on these identified features, different IT-based procedures are ranked by the employment of analytic hierarchy process (AHP) and TOPSIS. The outcomes of the study demonstrated the efficacy of the approachesCorr.
metadata
Fu, Yi; Zhang, Mengjia; Nawaz, Muhammad; Ali, Muhammad y Singh, Aman
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es
(2022)
Information technology-based revolution in music education using AHP and TOPSIS.
Soft Computing.
ISSN 1432-7643
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
This paper presents the design, development, and testing of an IoT-enabled smart stick for visually impaired people to navigate the outside environment with the ability to detect and warn about obstacles. The proposed design employs ultrasonic sensors for obstacle detection, a water sensor for sensing the puddles and wet surfaces in the user’s path, and a high-definition video camera integrated with object recognition. Furthermore, the user is signaled about various hindrances and objects using voice feedback through earphones after accurately detecting and identifying objects. The proposed smart stick has two modes; one uses ultrasonic sensors for detection and feedback through vibration motors to inform about the direction of the obstacle, and the second mode is the detection and recognition of obstacles and providing voice feedback. The proposed system allows for switching between the two modes depending on the environment and personal preference. Moreover, the latitude/longitude values of the user are captured and uploaded to the IoT platform for effective tracking via global positioning system (GPS)/global system for mobile communication (GSM) modules, which enable the live location of the user/stick to be monitored on the IoT dashboard. A panic button is also provided for emergency assistance by generating a request signal in the form of an SMS containing a Google maps link generated with latitude and longitude coordinates and sent through an IoT-enabled environment. The smart stick has been designed to be lightweight, waterproof, size adjustable, and has long battery life. The overall design ensures energy efficiency, portability, stability, ease of access, and robust features.
metadata
Farooq, Muhammad Siddique; Shafi, Imran; Khan, Harris; Díez, Isabel De La Torre; Breñosa, Jose; Martínez Espinosa, Julio César y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, SIN ESPECIFICAR
(2022)
IoT Enabled Intelligent Stick for Visually Impaired People for Obstacle Recognition.
Sensors, 22 (22).
p. 8914.
ISSN 1424-8220
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Regulation of lipid metabolism is essential for treatment and prevention of several chronic diseases such as obesity, diabetes, and cardiovascular diseases, which are responsible for most deaths worldwide. It has been demonstrated that the AMP-activated protein kinase (AMPK) has a direct impact on lipid metabolism by modulating several downstream-signaling components. The main objective of the present work was to evaluate the in vitro effect of a methanolic strawberry extract on AMPK and its possible repercussion on lipid metabolism in human hepatocellular carcinoma cells (HepG2). For such purpose, the lipid profile and the expression of proteins metabolically related to AMPK were determined on cells lysates. The results demonstrated that strawberry methanolic extract decreased total cholesterol, low-density lipoprotein (LDL)-cholesterol, and triglycerides levels (up to 0.50-, 0.30-, and 0.40-fold, respectively) while it stimulated the p-AMPK/AMPK expression (up to 3.06-fold), compared to the control. AMPK stimulation led to the phosphorylation and consequent inactivation of acetyl coenzyme A carboxylase (ACC) and inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the major regulators of fatty acids and cholesterol synthesis, respectively. Strawberry treatment also entailed a 4.34-, 2.37-, and 2.47-fold overexpression of LDL receptor, sirtuin 1 (Sirt1), and the peroxisome proliferator activated receptor gamma coactivator 1-alpha (PGC-1α), respectively, compared to control. The observed results were counteracted by treatment with compound C, an AMPK pharmacological inhibitor, confirming that multiple effects of strawberries on lipid metabolism are mediated by the activation of this protein.
metadata
Forbes-Hernandez, Tamara Y.; Giampieri, Francesca; Gasparrini, Massimiliano; Afrin, Sadia; Mazzoni, Luca; Cordero, Mario; Mezzetti, Bruno; Quiles, José L. y Battino, Maurizio
mail
tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2017)
Lipid Accumulation in HepG2 Cells Is Attenuated by Strawberry Extract through AMPK Activation.
Nutrients, 9 (6).
p. 621.
ISSN 2072-6643
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés The economic valuation of coastal ecosystem services is a critical step for the design of sound public policies that support the preservation of the services that nature provides to society in the context of climate change. Using the value transfer method, we obtained the economic valuation that represents the loss of coastal ecosystem services caused by sea level rise in Mexico. Using the Bathtub method, digital elevation models and sea level data, we identified the areas in the country prone to flooding and the associated ecosystem impacts. In Mexico, the annual economic loss caused by the disappearance of coastal ecosystem services is estimated at $6,476,402,405 USD, where wetlands represent the greatest economic losses, since they represent the largest affected ecosystem by area. However, beaches and dunes are the most valued ecosystem due to the economic activities that occur in these areas. In the mangroves, the service as habitat, refuge and nursery is the most valued for its positive relationship with fisheries. The states with the most economic losses are Baja California Sur, Sinaloa and Campeche. The protection of the coastal zone in Mexico should be a priority in the development strategies in the country because its loss and/or rehabilitation imply high economic costs and compromises the wellbeing of society. metadata Fernández-Díaz, Violeta Z.; Canul Turriza, Román A.; Kuc Castilla, Ángel Gabriel y Hinojosa-Huerta, Osvel mail SIN ESPECIFICAR (2022) Loss of coastal ecosystem services in Mexico: An approach to economic valuation in the face of sea level rise. Frontiers in Marine Science, 9. ISSN 2296-7745
Artículo Materias > Educación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Este trabajo presenta los desafíos a que se enfrentan los docentes de los Institutos Privados de Educación Superior (IPES) en sus prácticas docente con las TIC y asimismo propone algunas propuestas de mejora. Con base en el método mixto (Lynd & Lynd, 1929/1959), se ha realizado una observación participativa a fin de presentar al docente de los IPES. La recogida de datos nos permite destacar datos cuantitativos y las opiniones de los docentes respecto a su práctica docente. En cuanto a su calificación docente, se desprende del análisis de los resultados que el cuerpo docente de los IPES es heterogéneo. En este campo, encontramos profesionales de la docencia, profesionales de otros dominios, estudiantes con Máster, ingenieros o con grados equivalentes que, en espera de tener un empleo en una empresa, se improvisan docentes. La mayoría de los docentes parece tener habilidades básicas en TIC, es consciente de su importancia en su práctica docente, pero no tiene suficiente acompañamiento en este proceso de cambio. El análisis muestra la necesidad de reestructurar el funcionamiento de los IPES. Dicha reestructuración debería consistir en la redefinición del marco estratégico de los IPES y de los diferentes actores, así como la formación de los mismos en el uso adecuado de las TIC en su práctica pedagógica, facilitando así su acceso a las herramientas de las TIC. Para facilitar una práctica pedagógica efectiva de los docentes de los IPES con las TIC, es importante asegurar que estén capacitados, equipados y motivados para tal fin. metadata Fodjo Djeche, Carole y Eyeang, Eugénie mail carole.fodjo@doctorado.unini.edu.mx, eugenie.eyeang@unini.edu.mx (2022) Práctica pedagógica con las TIC: casos de los docentes de los IPES en Camerún. MLS Inclusion and Society Journal, 2 (2).
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Recent developments in quantum computing have shed light on the shortcomings of the conventional public cryptosystem. Even while Shor’s algorithm cannot yet be implemented on quantum computers, it indicates that asymmetric key encryption will not be practicable or secure in the near future. The National Institute of Standards and Technology (NIST) has started looking for a post-quantum encryption algorithm that is resistant to the development of future quantum computers as a response to this security concern. The current focus is on standardizing asymmetric cryptography that should be impenetrable by a quantum computer. This has become increasingly important in recent years. Currently, the process of standardizing asymmetric cryptography is coming very close to being finished. This study evaluated the performance of two post-quantum cryptography (PQC) algorithms, both of which were selected as NIST fourth-round finalists. The research assessed the key generation, encapsulation, and decapsulation operations, providing insights into their efficiency and suitability for real-world applications. Further research and standardization efforts are required to enable secure and efficient post-quantum encryption. When selecting appropriate post-quantum encryption algorithms for specific applications, factors such as security levels, performance requirements, key sizes, and platform compatibility should be taken into account. This paper provides helpful insight for post-quantum cryptography researchers and practitioners, assisting in the decision-making process for selecting appropriate algorithms to protect confidential data in the age of quantum computing.
metadata
Farooq, Sana; Altaf, Ayesha; Iqbal, Faiza; Bautista Thompson, Ernesto; Ramírez-Vargas, Debora L.; Díez, Isabel de la Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, ernesto.bautista@unini.edu.mx, debora.ramirez@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Resilience Optimization of Post-Quantum Cryptography Key Encapsulation Algorithms.
Sensors, 23 (12).
p. 5379.
ISSN 1424-8220
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
Research findings in the area of teaching-and-learning a foreign language have suggested new ways to teach L2 vocabulary. In this thesis, we define the Involvement Load Hypothesis. Then, we describe a research study that we conducted, report the results and discuss the evidence that indicates that, to consider the tenets of the ILH when teaching new English words to secondary school students with low proficiency may help them improve their vocabulary.
metadata
Fabrini Ramos, Rosario del Valle
mail
rfabrini19.ffha@gmail.com
(2022)
Second Incidental Vocabulary Acquisition in an EFL setting: testing the Involvement Load Hypothesis in secondary school.
Masters thesis, SIN ESPECIFICAR.
Artículo
Materias > Educación
Materias > Psicología
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The research will identify the role of soft powers, architecture, heritage, and culture, as building structures of cultural development and identity of Chilean society. A trilogy that contributes to a potential socio-cultural improvement, as integration platforms, applying a management model with new educational and cultural strategies, promoting the recovery of municipal infrastructure for cultural use in the neighborhoods, which favor and facilitate the interrelation of audiences at the communal level, considering in it relevance of the own, generating a greater identity thickness that allows an improvement in the quality of life of the society. Chilean society, neoliberal, considers urban spaces of mass consumption, shopping centers, and galleries, as its entertainment and “cultural” action par excellence, replacing and displacing the socio-cultural action of meeting and developing creative and cultural activities, around squares, parks, and spaces of citizen cultural infrastructure, showing a loss of cultural and identity values. Chile presents today a certain weakening in behaviors referred to as cultural attendance and consumption (low audience in theaters, libraries, museums, and art galleries), which does not mean that no time is devoted to leisure recreation, but shows deterioration and lack of massive interest in the attendance and use of spaces traditionally used as platforms for cultural expression and development, denoting, also, a growing phenomenon of fragmentation and socio-cultural stratification. As a scientific product, a typology of the project is developed, as a model of cultural management, with the recovery of existing infrastructure, which will expose a result that the soft powers are facilitators of building axes to strengthen the culture and identity of the society. As a research methodology, it is a non-experimental, interpretative and exploratory, theoretical structure with a qualitative approach. In conclusion, the constructive role achieved by soft powers, improving spaces for pa
metadata
Frutos Lázaro, María Macarena y Anaya Hernández, Armando
mail
SIN ESPECIFICAR, armando.anaya@unini.edu.mx
(2022)
Soft Powers and their application as potential and conditioning structures in the development and strengthening of education, culture and identity in Chile.
Journal of Positive School Psychology.
pp. 9115-9125.
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Dyslipidemia and oxidation of low density lipoproteins (LDL) are recognized as critical factors in the development of atherosclerosis. Healthy dietary patterns, with abundant fruit and vegetable consumption, may prevent the onset of these risk factors due to the presence of phytochemical compounds. Strawberries are known for their high content of polyphenols; among them, flavonoids are the major constituents, and it is presumed that they are responsible for the biological activity of the fruit. Nevertheless, there are only a few studies that actually evaluate the effects of different fractions isolated from strawberries. In order to assess the effects of two different strawberry extracts (whole methanolic extract/anthocyanin-enriched fraction) on the lipid profile and antioxidant status in human hepatocellular carcinoma (HepG2) cells, the triglycerides and LDL-cholesterol content, lipid peroxidation, intracellular reactive oxygen species (ROS) content and antioxidant enzymes’ activity on cell lysates were determined. Results demonstrated that both strawberry extracts not only improved the lipid metabolism by decreasing triglycerides and LDL-cholesterol contents, but also improved the redox state of HepG2 cells by modulating thiobarbituric acid-reactive substances production, antioxidant enzyme activity and ROS generation. The observed effects were more pronounced for the anthocyanin-enriched fraction.
metadata
Forbes-Hernandez, Tamara Y.; Gasparrini, Massimiliano; Afrin, Sadia; Cianciosi, Danila; González-Paramás, Ana; Santos-Buelga, Celestino; Mezzetti, Bruno; Quiles, José L.; Battino, Maurizio; Giampieri, Francesca y Bompadre, Stefano
mail
tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2017)
Strawberry (cv. Romina) Methanolic Extract and Anthocyanin-Enriched Fraction Improve Lipid Profile and Antioxidant Status in HepG2 Cells.
International Journal of Molecular Sciences, 18 (6).
p. 1149.
ISSN 1422-0067
Artículo
Materias > Biomedicina
Materias > Ingeniería
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Cerrado
Inglés
Obesity and overweight has increased in the last year and has become a pandemic disease, the result of sedentary lifestyles and unhealthy diets rich in sugars, refined starches, fats and calories. Machine learning (ML) has proven to be very useful in the scientific community, especially in the health sector. With the aim of providing useful tools to help nutritionists and dieticians, research focused on the development of ML and Deep Learning (DL) algorithms and models is searched in the literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol has been used, a very common technique applied to carry out revisions. In our proposal, 17 articles have been filtered in which ML and DL are applied in the prediction of diseases, in the delineation of treatment strategies, in the improvement of personalized nutrition and more. Despite expecting better results with the use of DL, according to the selected investigations, the traditional methods are still the most used and the yields in both cases fluctuate around positive values, conditioned by the databases (transformed in each case) to a greater extent than by the artificial intelligence paradigm used. Conclusions: An important compilation is provided for the literature in this area. ML models are time-consuming to clean data, but (like DL) they allow automatic modeling of large volumes of data which makes them superior to traditional statistics.
metadata
Ferreras, Antonio; Sumalla Cano, Sandra; Martínez-Licort, Rosmeri; Elío Pascual, Iñaki; Tutusaus, Kilian; Prola, Thomas; Vidal Mazón, Juan Luis; Sahelices, Benjamín y de la Torre Díez, Isabel
mail
SIN ESPECIFICAR, sandra.sumalla@uneatlantico.es, SIN ESPECIFICAR, inaki.elio@uneatlantico.es, kilian.tutusaus@uneatlantico.es, thomas.prola@uneatlantico.es, juanluis.vidal@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Systematic Review of Machine Learning applied to the Prediction of Obesity and Overweight.
Journal of Medical Systems, 47 (1).
ISSN 1573-689X
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The essence of quantum machine learning is to optimize problem-solving by executing machine learning algorithms on quantum computers and exploiting potent laws such as superposition and entanglement. Support vector machine (SVM) is widely recognized as one of the most effective classification machine learning techniques currently available. Since, in conventional systems, the SVM kernel technique tends to sluggish down and even fail as datasets become increasingly complex or jumbled. To compare the execution time and accuracy of conventional SVM classification to that of quantum SVM classification, the appropriate quantum features for mapping need to be selected. As the dataset grows complex, the importance of selecting an appropriate feature map that outperforms or performs as well as the classification grows. This paper utilizes conventional SVM to select an optimal feature map and benchmark dataset for predicting air quality. Experimental evidence demonstrates that the precision of quantum SVM surpasses that of classical SVM for air quality assessment. Using quantum labs from IBM’s quantum computer cloud, conventional and quantum computing have been compared. When applied to the same dataset, the conventional SVM achieved an accuracy of 91% and 87% respectively, whereas the quantum SVM demonstrated an accuracy of 97% and 94% respectively for air quality prediction. The study introduces the use of quantum Support Vector Machines (SVM) for predicting air quality. It emphasizes the novel method of choosing the best quantum feature maps. Through the utilization of quantum-enhanced feature mapping, our objective is to exceed the constraints of classical SVM and achieve unparalleled levels of precision and effectiveness. We conduct precise experiments utilizing IBM’s state-of-the-art quantum computer cloud to compare the performance of conventional and quantum SVM algorithms on a shared dataset.
metadata
Farooq, Omer; Shahid, Maida; Arshad, Shazia; Altaf, Ayesha; Iqbal, Faiza; Vera, Yini Airet Miro; Flores, Miguel Angel Lopez y Ashraf, Imran
mail
SIN ESPECIFICAR
(2024)
An enhanced approach for predicting air pollution using quantum support vector machine.
Scientific Reports, 14 (1).
ISSN 2045-2322
Artículo Materias > Biomedicina Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Background: The COVID-19 pandemic has been deadly globally; however, the most lethal outbreak worldwide occurred in Ecuador. Our work aims to highlight the pandemic's impact on the most affected countries worldwide due to the pandemic in terms of excess deaths per capita and per day. Methodology: An ecological study of all-cause mortality recorded in Ecuador during the year 2020. To calculate the total excess death relative to the historical average for the same dates in 2017, 2018 and 2019. A Poisson fitting analysis was used to identify trends on officially recorded all-caused deaths and those attributed to COVID-19. A bootstrapping technique based on central tendency measures was used to emulate the sampling distribution of our expected deaths estimator by simulating the data generation and model fitting processes on a daily basis since the first confirmed case was reported worldwide. Results: In Ecuador, during 2020, 115,070 deaths were totally reported and 42,453 were catalogued as excessive mortality when comparing with the last 3-years average (2017-2019). Ecuador is the country with the highest recorded excess mortality in the world within the shortest timespan. In one single day, Ecuador recorded 1,120 deaths (6/100,000), while Peru had 740 deaths (2/100,000) and Brazil 4,249 deaths (2/100,000). This value represents an additional 408% of the expected fatalities. The province with the highest number of excess deaths was Santa Elena on Ecuador's coast, with more than 154% increment versus previous years. Conclusions: Adjusting for population size and time, the hardest-hit country due to the COVID-19 pandemic was Ecuador. The mortality excess rate shows that the SARS-CoV-2 virus spread rapidly in the country, especially in the coastal province of Santa Elena and Guayas. Our results and the new proposed methodology could help to address the actual death toll situation during the early phase of the pandemic in Ecuador. metadata Fernández, Raúl; Vásconez-González, Jorge; Simbaña-Rivera, Katherine; Lister, Alex; Landazuri, Samanta; Castillo, Diana; Izquierdo Condoy, Juan Sebastian y Ortiz-Prado, Esteban mail SIN ESPECIFICAR (2022) The world’s deadliest outbreak during the COVID-19 Pandemic: A proposed analytical approach to estimate Daily Excess mortality rates in Ecuador. SSRN Electronic Journal. ISSN 1556-5068
G
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
The objective of this work is to develop an action research for the implementation of Communicative Tasks Based on Films (Didactic Unit of Communicative Tasks) DUCT to improve oral skills in an EFL B1 class of 11th grade at Claretiano school in Colombia, taking into account that oral skills (listening / speaking) are the greatest importance in the proccess of learning a second language in any context of the world. The research is based on the qualitative approach, and corresponds to the design of action research, which was carried out with a population of fifteen students of the 11th grade of the Claretian school of the city of Neiva Colombia. Observation, survey and interview were used as the main data collection technique, and as instruments Anecdotal record, Diagnostic test, Questionnaire (Pre-test) Interview, Didactic Unit of the Communicative Task and Questionnaire (post-test), with the use of these instruments it was possible to make the diagnosis of the students of grade 11, demonstrate the level of comprehension and oral production of English before and after the use of films. Visualize the progress of students with the implementation of films for the teaching of English according to the perception of the teacher and the general assessment of the application of films in the teaching of English. After evaluating the results of this research proposal we can conclude that the use of films in the teaching of a second language should be considered as an excellent audiovisual technological tool that strengthens the ability of listening and oral production taking into account that they are used properly, and contextualized around the aspects of the language in order to strengthen and optimize it; The use of this resource showed that it can not only contribute to the improvement of listening and speech comprehension, but also of all language skills, expanding its vocabulary and gaining some fluency in oral expression.With the use of films in the teaching of English it was shown that it not only contributes to the development of listening and oral comprehension, but also of all linguistic skills, taking into account that it helps us to expand vocabulary and gain some fluency in oral expression.
metadata
Guzmán Murcia, Maricela
mail
mariguz75@hotmail.com
(2022)
Action Research for Implementing Movie-Based Communicative Tasks for Improving the Speaking Skills in an 11th Grade High School B1 EFL Class in Colombia.
Masters thesis, SIN ESPECIFICAR.
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
This action research and material design project consists of the elaboration of a teaching tool to supply a real need and address a real problem that a certain population in the city of Buenaventura located in Colombia has which is in this case, the lack of resources or a textbook to impart English classes.This study uses action research to identify a dilema and uses a series of tools such as observation, interviews and text to collect data that was deeply analysed with the intention of seeking for the greatest strategy to overcome this need aforementioned.
metadata
Guerrero Salazar, Jhony Fernando
mail
jhonny139316@hotmail.com
(2022)
An Action Research to Design, Implement and Evaluate a CLIL Communicative and Task-Based Approach Material for a 11th Grade Students with A1 Level of English from a Foundation in Buenaventura, Colombia.
Masters thesis, SIN ESPECIFICAR.
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Age-related macular degeneration (AMD) is a serious degenerative disease affecting the eyes, and is the main cause of severe vision loss among people >55 years of age in developed countries. Its onset and progression have been associated with several genetic and lifestyle factors, with diet appearing to play a pivotal role in the latter. In particular, dietary eating patterns rich in plant foods have been shown to lower the risk of developing the disease, and to decrease the odds of progressing to more advanced stages in individuals already burdened with early AMD. We systematically reviewed the literature to analyse the relationship between the adherence to a Mediterranean diet, a mainly plant-based dietary pattern, and the onset/progression of AMD. Eight human observational studies were analysed. Despite some differences, they consistently indicate that higher adherence to a Mediterranean eating pattern lowers the odds of developing AMD and decreases the risk of progression to more advanced stages of the disease, establishing the way for preventative measures emphasizing dietary patterns rich in plant-foods
metadata
Gastaldello, Annalisa; Giampieri, Francesca; Quiles, José L.; Navarro-Hortal, María D.; Aparicio Obregón, Silvia; García Villena, Eduardo; Tutusaus, Kilian; De Giuseppe, Rachele; Grosso, Giuseppe; Cianciosi, Danila; Forbes-Hernández, Tamara Y.; Nabavi, Seyed M. y Battino, Maurizio
mail
SIN ESPECIFICAR, francesca.giampieri@uneatlantico.es, jose.quiles@uneatlantico.es, SIN ESPECIFICAR, silvia.aparicio@uneatlantico.es, eduardo.garcia@uneatlantico.es, kilian.tutusaus@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2022)
Adherence to the Mediterranean-Style Eating Pattern and Macular Degeneration: A Systematic Review of Observational Studies.
Nutrients, 14 (10).
p. 2028.
ISSN 2072-6643
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
Industries need solutions that can automatically monitor oil leakage from deployed underwater pipelines and to rapidly report any damage. The location prediction of mineral reservoirs like oil, gas, or metals in deep water is a challenge during the extraction of these resources. Moreover, the problem of ores and mineral deposits on the seafloor comes into play. The abovementioned challenges necessitate for the deployment of underwater wireless sensor networks (UWSNs). Anchor-based localization techniques are segregated into range-free and range-based processes. Range-based schemes depend on various techniques like angle of arrival (AoA), time of arrival (ToA), time difference of arrival (TDoA), and received signal strength indicator (RSSI). In this article, the localization of these leakages is performed by using range-based metrics for calculating the distance among anchor nodes (ANs) and target nodes (TNs). This estimated distance is further optimized to minimize the estimation error. A multilateralism procedure is used to estimate the optimal position of each TN. The results exhibit that the proposed algorithm shows a high performance when compared to previous works, in terms of minimum energy consumption, lower packet loss, rapid location estimation, and lowest localization error. The benefit of using the proposed methodology greatly impacts on identifying the leakage area in mobility-assisted UWSN, where rapid reporting helps to lower the loss of resources.
metadata
Goyal, Nitin; Nain, Mamta; Singh, Aman; Abualsaud, Khalid; Alsubhi, Khalid; Ortega-Mansilla, Arturo y Zorba, Nizar
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, arturo.ortega@uneatlantico.es, SIN ESPECIFICAR
(2022)
An Anchor-Based Localization in Underwater Wireless Sensor Networks for Industrial Oil Pipeline Monitoring.
IEEE Canadian Journal of Electrical and Computer Engineering, 45 (4).
pp. 466-474.
ISSN 2694-1783
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Cerrado
Inglés
Diets enriched in plant-based foods are associated with the maintenance of a good well-being and with the prevention of many non-communicable diseases. The health effects of fruits and vegetables consumption are mainly due to the presence of micronutrients, including vitamins and minerals, and polyphenols, plant secondary metabolites. One of the most important classes of phenolic compounds are anthocyanins, that confer the typical purple-red color to many foods, such as berries, peaches, plums, red onions, purple corn, eggplants, as well as purple carrots, sweet potatoes and red cabbages, among others. This commentary aims to briefly highlight the progress made by science in the last years, focusing on some unexpected aspects related with anthocyanins, such as their bioavailability, their health effects and their relationship with gut microbiota
metadata
Giampieri, Francesca; Cianciosi, Danila; Alvarez-Suarez, José M.; Quiles, José L.; Forbes-Hernández, Tamara Y.; Navarro-Hortal, María D.; Machì, Michele; Pali-Casanova, Ramón; Martínez Espinosa, Julio César; Chen, Xiumin; Zhang, Di; Bai, Weibin; Lingmin, Tian; Mezzetti, Bruno; Battino, Maurizio y Diaz, Yasmany Armas
mail
francesca.giampieri@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, jose.quiles@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, ramon.pali@unini.edu.mx, ulio.martinez@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR
(2023)
Anthocyanins: what do we know until now?
Journal of Berry Research.
pp. 1-6.
ISSN 18785093
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
A common denominator in the pathogenesis of most chronic inflammatory diseases is the involvement of oxidative stress, related to ROS production by all aerobic organisms. Dietary antioxidants from plant foods represent an efficient strategy to counteract this condition. The aim of the present study was to evaluate the protective effects of strawberry extracts on inflammatory status induced by E. Coli LPS on RAW 264.7 macrophages by measuring the main oxidative and inflammatory biomarkers and investigating the molecular pathways involved. Strawberry pre-treatment efficiently counteracted LPS-induced oxidative stress reducing the amount of ROS and nitrite production, stimulating endogenous antioxidant enzyme activities and enhancing protection against lipid, protein and DNA damage (P < 0.05). Strawberry pre-treatment exerted these protective effects primarily through the activation of the Nrf2 pathway, which is markedly AMPK-dependent and also by the modulation of the NF-kB signalling pathway. Finally, an improvement in mitochondria functionality was also detected. The results obtained in this work highlight the health benefit of strawberries against inflammatory and oxidative stress in LPS-stimulated RAW 264.7 macrophages, investigating for the first time the possible involved molecular mechanisms.
metadata
Gasparrini, Massimiliano; Forbes-Hernandez, Tamara Y.; Giampieri, Francesca; Afrin, Sadia; Alvarez-Suarez, Josè M.; Mazzoni, Luca; Mezzetti, Bruno; Quiles, Josè L. y Battino, Maurizio
mail
SIN ESPECIFICAR, tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2017)
Anti-inflammatory effect of strawberry extract against LPS-induced stress in RAW 264.7 macrophages.
Food and Chemical Toxicology, 102.
pp. 1-10.
ISSN 0278-6915
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The purpose of this research was to plan an approach to a project framework that integrated a model for sustainability and CSR, with the process groups of the Project Management Body of Knowledge (PMBOK®) standard, in its application to the training of a group of students in Project Design, Management, and Evaluation. The integration was justified by the scarce explicit references to sustainability and CSR found in traditional project management guidelines, norms, and standards. The new framework was used to structure a Sustainability Management Plan, which made it possible to incorporate sustainability criteria throughout the life cycle of the training project. The training proposal in Project Design, Management, and Evaluation was chosen, among several alternatives, by a multi-criteria selection process (fuzzy AHP) in the context of project scope management. The results reveal a great heterogeneity among the models and the lack of a base of key indicators in sustainability and CSR measurement tools as well as of explicit references to sustainability in project management standards. It is therefore necessary to develop a Sustainability Management Plan that can be introduced in the Project Management Plan and thus influence the strategic and operational guidelines of the Institution.
metadata
García Villena, Eduardo; Gracia Villar, Santos; Dzul López, Luis Alonso; Álvarez, Roberto Marcelo; Delgado Noya, Irene y Vidal Mazón, Juan Luis
mail
eduardo.garcia@uneatlantico.es, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, roberto.alvarez@uneatlantico.es, irene.delgado@uneatlantico.es, juanluis.vidal@uneatlantico.es
(2021)
Approach to a Project Framework in the Environment of Sustainability and Corporate Social Responsibility (CSR): Case Study of a Training Proposal to a Group of Students in a Higher Education Institution.
Sustainability, 13 (19).
p. 10880.
ISSN 2071-1050
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
During the process of beeswax recycling, many industrial derivatives are obtained. These matrices may have an interesting healthy and commercial potential but to date they have not been properly studied. The aim of the present work was to evaluate the proximal and phytochemical composition, the antioxidant capacity and cytotoxic effects of two by-products from beeswax recycling process named MUD 1 and MUD 2 on liver hepatocellular carcinoma. Our results showed that MUD 1 presented the highest (P < .05) fiber, protein, carbohydrate, polyphenol and flavonoid concentration, as well as the highest (P < .05) total antioxidant capacity than the MUD 2 samples. MUD1 exerted also anticancer activity on HepG2 cells, by reducing cellular viability, increasing intracellular ROS levels and affecting mitochondrial functionality in a dose-dependent manner. We showed for the first time that by-products from beeswax recycling process can represent a rich source of phytochemicals with high total antioxidant capacity and anticancer activity; however, further researches are necessary to evaluate their potentiality for human health by in vivo studies.
metadata
Giampieri, Francesca; Quiles, José L.; Orantes-Bermejo, Francisco J.; Gasparrini, Massimiliano; Forbes-Hernandez, Tamara Y.; Sánchez-González, Cristina; Llopis, Juan; Rivas-García, Lorenzo; Afrin, Sadia; Varela-López, Alfonso; Cianciosi, Danila; Reboredo-Rodriguez, Patricia; Fernández-Piñar, Cristina Torres; Caderón Iglesia, Rubén; Ruiz Salces, Roberto; Aparicio Obregón, Silvia; Crespo-Álvarez, Jorge; Dzul Lopez, Luis; Xiao, Jianbo y Battino, Maurizio
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, ruben.calderon@uneatlantico.es, roberto.ruiz@uneatlantico.es, silvia.aparicio@uneatlantico.es, jorge.crespo@uneatlantico.es, luis.dzul@unini.edu.mx, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2018)
Are by-products from beeswax recycling process a new promising source of bioactive compounds with biomedical properties?
Food and Chemical Toxicology, 112.
pp. 126-133.
ISSN 0278-6915
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Significance: In eukaryotes, autophagy represents a highly evolutionary conserved process, through which macromolecules and cytoplasmic material are degraded into lysosomes and recycled for biosynthetic or energetic purposes. Dysfunction of the autophagic process has been associated with the onset and development of many human chronic pathologies, such as cardiovascular, metabolic, and neurodegenerative diseases as well as cancer.
Recent Advances: Currently, comprehensive research is being carried out to discover new therapeutic agents that are able to modulate the autophagic process in vivo. Recent evidence has shown that a large number of natural bioactive compounds are involved in the regulation of autophagy by modulating several transcriptional factors and signaling pathways.
Critical Issues: Critical issues that deserve particular attention are the inadequate understanding of the complex role of autophagy in disease pathogenesis, the limited availability of therapeutic drugs, and the lack of clinical trials. In this context, the effects that natural bioactive compounds exert on autophagic modulation should be clearly highlighted, since they depend on the type and stage of the pathological conditions of diseases.
Future Directions: Research efforts should now focus on understanding the survival-supporting and death-promoting roles of autophagy, how natural compounds interact exactly with the autophagic targets so as to induce or inhibit autophagy and on the evaluation of their pharmacological effects in a more in-depth and mechanistic way. In addition, clinical studies on autophagy-inducing natural products are strongly encouraged, also to highlight some fundamental aspects, such as the dose, the duration, and the possible synergistic action of these compounds with conventional therapy.
metadata
Giampieri, Francesca; Afrin, Sadia; Forbes-Hernandez, Tamara Y.; Gasparrini, Massimiliano; Cianciosi, Danila; Reboredo-Rodriguez, Patricia; Varela-Lopez, Alfonso; Quiles, Jose L. y Battino, Maurizio
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, tamara.forbes@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2019)
Autophagy in Human Health and Disease: Novel Therapeutic Opportunities.
Antioxidants & Redox Signaling, 30 (4).
pp. 577-634.
ISSN 1523-0864
Artículo
Materias > Ciencias Sociales
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
This article proposes a discussion on the form of coexistence of local Development Agencies in Uruguay, with local governments in the face of the new scenarios marked by the decentralization process, initiated in the country with the Constitutional Reform of 1996 and culminating in February 2009, with the Law of Political Decentralization and Citizen Participation. The discussion applies in particular to the local development agency of the city of Rivera (ADR), located in the northeast of the country. A descriptive, mixed, bibliographic, documentary investigation was carried out with primary data collection to internal and external references to ADR. The results show that the coexistence of both institutions has been difficult, without defining clear roles. Promoting dialogue to define the role of each seems to be the great challenge facing the sustainability of the agency
metadata
Garat de Marin, Mirtha Silvana; Soriano Flores, Emmanuel; Rodríguez Velasco, Carmen Lilí; Silva Alvarado, Eduardo; Calderón Iglesias, Rubén; Álvarez, Roberto Marcelo y Gracia Villar, Santos
mail
silvana.marin@uneatlantico.es, emmanuel.soriano@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR, ruben.calderon@uneatlantico.es, roberto.alvarez@uneatlantico.es, santos.gracia@uneatlantico.es
(2022)
Development Agencies and Local Governments—Coexistence within the Same Territory.
Social Sciences, 11 (9).
p. 398.
ISSN 2076-0760
Artículo
Materias > Biomedicina
Materias > Alimentación
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Background
Aim to this study is to investigate the association of Dietary Counseling, Meal Patterns, and Diet Quality (DietQ) in Patients with Type 2 Diabetes Mellitus (T2DM) with/without chronic kidney disease (CKD) in primary healthcare.
Methods
Cross-sectional study acquired data on dietary counseling and meal patterns by direct interview with a food-frequency questionnaire and one 24-h food-recall. The Healthy Eating Index (HEI) was used to classify DietQ [“good” DietQ (GDietQ, score ≥ 80) and “poor” DietQ (PDietQ, score < 80)].
Participants/setting
This study included 705 patients with T2DM: 306 with normal kidney function; 236 with early nephropathy, and 163 with overt nephropathy (ON).
Statistical analyses performed
Multivariate linear-regression models for predicting HEI and χ2 tests for qualitative variables and one-way ANOVA for quantitative variables were employed. Mann-Whitney U and independent Student t were performed for comparisons between GDietQ and PDietQ.
Results
Only 18 % of the population was classified as GDietQ. Patients with ON and PDietQ vs. with GDietQ received significantly less dietary counseling from any health professional in general (45 % vs 72 %, respectively), or from any nutrition professional (36 % vs. 61 %, respectively). A better HEI was significantly predicted (F = 42.01; p = 0.0001) by lower HbA1C (β −0.53, p = 0.0007) and better diet diversity (β 8.09, p = 0.0001).
Conclusions
Patients with more advanced stages of CKD had less nutritional counseling and worse dietary patterns, as well as more frequent PDietQ. Our findings reinforce the need for dietitians and nutritionists in primary healthcare to provide timely nutritional counseling.
metadata
Gómez-García, Erika F.; Cueto-Manzano, Alfonso M.; Martínez-Ramírez, Héctor R.; Cortés-Sanabria, Laura; Avesani, Carla M.; Orozco-González, Claudia N. y Rojas-Campos, Enrique
mail
SIN ESPECIFICAR
(2024)
Dietary counseling, meal patterns, and diet quality in patients with type 2 diabetes mellitus with/without chronic kidney disease.
Journal of Diabetes and its Complications, 38 (10).
p. 108853.
ISSN 10568727
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
The demand for digitization has inspired organizations to move towards cloud computing, which has increased the challenge for cloud service providers to provide quality service. One of the challenges is energy consumption, which can shoot up the cost of using computing resources and has raised the carbon footprint in the atmosphere; therefore, it is an issue that it is imperative to address. Virtualization, bin-packing, and live VM migration techniques are the key resolvers that have been found to be efficacious in presenting sound solutions. Thus, in this paper, a new live VM migration algorithm, live migration with efficient ballooning (LMEB), is proposed; LMEB focuses on decreasing the size of the data that need to be shifted from the source to the destination server so that the total energy consumption of migration can be reduced. A simulation was performed with a specific configuration of virtual machines and servers, and the results proved that the proposed algorithm could trim down energy usage by 18%, migration time by 20%, and downtime by 20% in comparison with the existing approach of live migration with ballooning (LMB)
metadata
Gupta, Neha; Gupta, Kamali; Qahtani, Abdulrahman M.; Gupta, Deepali; Alharithi, Fahd S.; Singh, Aman y Goyal, Nitin
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR
(2022)
Energy-Aware Live VM Migration Using Ballooning in Cloud Data Center.
Electronics, 11 (23).
p. 3932.
ISSN 2079-9292
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The purpose of this article is to help to bridge the gap between sustainability and its application to project management by developing a methodology based on artificial intelligence to diagnose, classify, and forecast the level of sustainability of a sample of 186 projects aimed at local communities in Latin American and Caribbean countries. First, the compliance evaluation with the Sustainable Development Goals (SDGs) within the framework of the 2030 Agenda served to diagnose and determine, through fuzzy sets, a global sustainability index for the sample, resulting in a value of 0.638, in accordance with the overall average for the region. Probabilistic predictions were then made on the sustainability of the projects using a series of supervised learning classifiers (SVM, Random Forest, AdaBoost, KNN, etc.), with the SMOTE resampling technique, which provided a significant improvement toward the results of the different metrics of the base models. In this context, the Support Vector Machine (SVM) + SMOTE was the best classification algorithm, with accuracy of 0.92. Lastly, the extrapolation of this methodology is to be expected toward other realities and local circumstances, contributing to the fulfillment of the SDGs and the development of individual and collective capacities through the management and direction of projects.
metadata
García Villena, Eduardo; Pascual Barrera, Alina Eugenia; Álvarez, Roberto Marcelo; Dzul López, Luis Alonso; Tutusaus, Kilian; Vidal Mazón, Juan Luis; Miró Vera, Yini Airet; Brie, Santiago y López Flores, Miguel A.
mail
eduardo.garcia@uneatlantico.es, alina.pascual@unini.edu.mx, roberto.alvarez@uneatlantico.es, luis.dzul@uneatlantico.es, kilian.tutusaus@uneatlantico.es, juanluis.vidal@uneatlantico.es, yini.miro@uneatlantico.es, santiago.brie@uneatlantico.es, miguelangel.lopez@uneatlantico.es
(2022)
Evaluation of the Sustainable Development Goals in the Diagnosis and Prediction of the Sustainability of Projects Aimed at Local Communities in Latin America and the Caribbean.
Applied Sciences, 12 (21).
p. 11188.
ISSN 2076-3417
Artículo
Materias > Psicología
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Cerrado
Inglés
In recent decades, perfectionism has generated growing interest from the scientific community in understanding exercise addiction, due to the explicative contributions offered its characteristics that can make individuals more susceptible to unhealthy and compulsive exercise. There have been limited studies of such constructions in sports contexts. With the purpose of identifying the most relevant evidence on the constructs in sports contexts, the main links between perfectionism and exercise addiction in athletes were described. Taking into account the principles established by the PRISMA and AMSTAR statements for the qualitative and quantitative description of findings in systematic reviews, a compendium of original articles in English, French and Spanish published on the Web of Science electronic platforms and databases is presented, Scopus, ProQuest, MEDLINE and EBSCO-HOST, and included major resources such as PSY Articles, PsycINFO, LWW, ERIC, SportDISCUS, PubMed, ERIC, Dialnet, PubMed, ISOC, the Cochrane Library and Google Scholar. Of the 754 articles identified, only 22 met the established inclusion criteria. Finally, the relationship between exercise addiction and perfectionism, and the risk function of certain personality traits, such as narcissism, in this association is confirmed.
metadata
González-Hernández, J.; Nogueira-López, Abel; Zangeneh, M. y López-Mora, C.
mail
SIN ESPECIFICAR, abel.nogueira@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2021)
Exercise Addiction and Perfectionism, Joint in the Same Path? A Systematic Review.
International Journal of Mental Health and Addiction.
ISSN 1557-1874
Artículo
Materias > Biomedicina
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Cardiovascular diseases (CVDs) are one of the main causes of mortality and morbidity worldwide. A healthy diet rich in plant-derived compounds such as (poly)phenols appears to have a key role in improving cardiovascular health. Flavan-3-ols represent a subclass of (poly)phenols of great interest for their possible health benefits. In this review, we summarized the results of clinical studies on vascular outcomes of flavan-3-ol supplementation and we focused on the role of the microbiota in CVD. Clinical trials included in this review showed that supplementation with flavan-3-ols mostly derived from cocoa products significantly reduces blood pressure and improves endothelial function. Studies on catechins from green tea demonstrated better results when involving healthy individuals. From a mechanistic point of view, emerging evidence suggests that microbial metabolites may play a role in the observed effects. Their function extends beyond the previous belief of ROS scavenging activity and encompasses a direct impact on gene expression and protein function. Although flavan-3-ols appear to have effects on cardiovascular health, further studies are needed to clarify and confirm these potential benefits and the rising evidence of the potential involvement of the microbiota.
metadata
Godos, Justyna; Romano, Giovanni Luca; Laudani, Samuele; Gozzo, Lucia; Guerrera, Ida; Dominguez Azpíroz, Irma; Martínez Díaz, Raquel; Quiles, José L.; Battino, Maurizio; Drago, Filippo; Giampieri, Francesca; Galvano, Fabio y Grosso, Giuseppe
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, irma.dominguez@unini.edu.mx, raquel.martinez@uneatlantico.es, jose.quiles@uneatlantico.es, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR, francesca.giampieri@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Flavan-3-ols and Vascular Health: Clinical Evidence and Mechanisms of Action.
Nutrients, 16 (15).
p. 2471.
ISSN 2072-6643
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Food and agriculture are significant aspects that can meet the food demand estimated by the Food Agriculture Organization (FAO) by 2050. In addition to this, the United Nations sustainable development goals recommended implementing sustainable practices to meet food demand to achieve sustainability. Currently, aquaponics is one of the sustainable practices that require less land and water and has a low environmental impact. Aquaponics is a closed-loop and soil-less method of farming, where it requires intensive monitoring, control, and management. The advancement of wireless sensors and communication protocols empowered to implementation of an Internet of Things- (IoT-) based system for real-time monitoring, control, and management in aquaponics. This study presents a review of the wireless technology implementation and progress in aquaponics. Based on the review, the study discusses the significant water and environmental parameters of aquaponics. Followed by this, the study presents the implementation of remote, IoT, and ML-based monitoring of aquaponics. Finally, the review presents the recommendations such as edge and fog-based vision nodes, machine learning models for prediction, LoRa-based sensor nodes, and gateway-based architecture that are beneficial for the enhancement of wireless aquaponics and also for real-time prediction in the future.
metadata
Gayam, Kiran Kumari; Jain, Anuj; Gehlot, Anita; Singh, Rajesh; Akram, Shaik Vaseem; Singh, Aman; Anand, Divya; Delgado Noya, Irene y Ahmad, Shafiq
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@unic.co.ao, divya.anand@uneatlantico.es, irene.delgado@uneatlantico.es, SIN ESPECIFICAR
(2022)
Imperative Role of Automation and Wireless Technologies in Aquaponics Farming.
Wireless Communications and Mobile Computing, 2022.
pp. 1-13.
ISSN 1530-8669
Artículo
Materias > Educación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The purpose of this article was to evaluate the level of satisfaction of a sample of graduates in relation to different online postgraduate programs in the environmental area, as part of the process of continuous improvement in which the educational institution was immersed for the renewal of its accreditation before the corresponding official bodies. Based on the bibliographic review of a series of models and tools, a Likert scale measurement instrument was developed. This instrument, once applied and validated, showed a good level of reliability, with more than three quarters of the participants having a positive evaluation of satisfaction. Likewise, to facilitate the relational study, and after confirming the suitability of performing a factor analysis, four variable grouping factors were determined, which explained a good part of the variability of the instrument’s items. As a result of the analysis, it was found that there were significant values of low satisfaction in graduates from the Eurasian area, mainly in terms of organizational issues and academic expectations. On the other hand, it was observed that the methodological aspects of the “Auditing” and “Biodiversity” programs showed higher levels of dissatisfaction than the rest, with no statistically significant relationships between gender, entry profile or age groups. The methodology followed and the rigor in determining the validity and reliability of the instrument, as well as the subsequent analysis of the results, endorsed by the review of the documented information, suggest that the instrument can be applied to other multidisciplinary programs for decision making with guarantees in the educational field
metadata
García Villena, Eduardo; Pueyo Villa, Silvia; Delgado Noya, Irene; Tutusaus, Kilian; Ruiz Salces, Roberto y Pascual Barrera, Alina Eugenia
mail
eduardo.garcia@uneatlantico.es, silvia.pueyo@uneatlantico.es, irene.delgado@uneatlantico.es, kilian.tutusaus@uneatlantico.es, roberto.ruiz@uneatlantico.es, alina.pascual@unini.edu.mx
(2021)
Instrumentalization of a Model for the Evaluation of the Level of Satisfaction of Graduates under an E-Learning Methodology: A Case Analysis Oriented to Postgraduate Studies in the Environmental Field.
Sustainability, 13 (9).
p. 5112.
ISSN 2071-1050
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Historical centers (HC) are confronted with a diverse functional reality where different environmental factors or variables could break precarious equilibriums becoming complex spaces of indefinite limits which result from urbanizing processes imposed city model by official planning. Through a research documentary, it´s been tried to synthesize art´s state in the subject of resilience of HC in coastal cities with functional problems, to establish a whole designed model of resilience, which regards as a system, the various subsystems in balance with all environmental factors, which guarantees urban sustainability. To have a whole plan for it´s resilience will allow institutions involved in urban development to create effective programs, contributing to sustainable development of the city. metadata González Ballesteros, Cristóbal mail SIN ESPECIFICAR (2020) Integral model for the resilience of historic centers in coastal cities. International Journal of Current Research, 12 (10). pp. 14299-14308. ISSN 0975-833X
Artículo
Materias > Educación
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Regulatory dispersion and a utilitarian use of sustainability deepen the gap within the teaching–learning process and limit the introduction of sustainable criteria in organizations through projects. The objective of this research consisted in developing a sustainable and holistic educational proposal for an online postgraduate program belonging to the Universidad Europea del Atlántico (UNEATLANTICO) within the field of projects. The proposal was based on the instrumentalization of a model comprised of national and international bibliographic references, resulting in a sustainability guide with significant improvements in relation to the reference standard par excellence: ISO 26000:2010. This guide formed the basis of a sustainability management plan, which was key in the project methodology and during the development of sustainable objectives and descriptors for each of the subjects. Lastly, the entities, attributes, and cardinal relationships were established for the development of a physical model used to facilitate the management of all this information within a SQL database. The rigor when determining the educational program, as well as the subsequent analysis of results as supported by the literature review, presupposes the application of this methodology toward other multidisciplinary programs contributing to the adoption of good sustainability practices within the educational field
metadata
Gracia Villar, Mónica; Álvarez, Roberto Marcelo; Brie, Santiago; Miró Vera, Yini Airet y García Villena, Eduardo
mail
monica.gracia@uneatlantico.es, roberto.alvarez@uneatlantico.es, santiago.brie@uneatlantico.es, yini.miro@uneatlantico.es, eduardo.garcia@uneatlantico.es
(2023)
Integration of Sustainable Criteria in the Development of a Proposal for an Online Postgraduate Program in the Projects Area.
Education Sciences, 13 (1).
p. 97.
ISSN 2227-7102
Artículo Materias > Alimentación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Currently, food access has worsened during the COVID-19 pandemic. For this reason, various alternatives are required to improve the population’s diet. Among the many alternatives is the use of 3D printing technology to reproduce food that can reach the most vulnerable population. This remarkable study shows future generations the importance of seeking innovative food that guarantees a nutritious and accessible diet. The study focuses on the Panamanian population to determine which variables influence the decision to consume innovative foods. The innovative product to be tested is based on insects, arachnids, and arthropods, which may be difficult for the population to consume, but thanks to 3D printing technologies, it is possible to generate foods based on these raw materials that look like traditional foods. Likewise, processing these foods generates less water consumption, giving them an ecological attribute. The present study seeks to know the variables that determine the purchase intention of consumers in Panama regarding the food supply based on insects, arachnids, and arthropods that are transformed into traditional food formats using 3D printers. This information can help companies prepare food offers to consumers in Panama. metadata González-Guzmán, Marcos Enrique; Del-Aguila-Arcentales, Shyla; Alvarez-Risco, Aldo; Rojas-Osorio, Mercedes; Yáñez, Jaime A. y Pandiselvam, Ravi mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, jaime.yanez@unini.edu.mx, SIN ESPECIFICAR (2024) Intention to Purchase Foods Based on Insects, Arachnids, and Arthropods, Processed by 3D Printing in Panama Consumers. International Journal of Food Science, 2024 (1). ISSN 2356-7015
Artículo Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español La crisis económica provocada por la pandemia del COVID-19 y el actual anuncio de la Reserva Federal de una posible recesión frente a la inflación que se ha presentado en el último trimestre hace necesaria la discusión de la naturaleza de las crisis en términos de los ciclos de corto y largo plazo en la economía, sus características y principales consecuencias. La caracterización de la crisis de 2007 como una crisis de rentabilidad y como el fin de un ciclo de crecimiento económico de largo plazo, así como las particularidades socio-económicas que presenta abre paso a la posibilidad de formular políticas más eficientes y efectivas para enfrentar las crisis coyunturales ante las dificultades que presenta el agotamiento de un modelo de acumulación ligado a la globalización neoliberal. Por esta razón, el objetivo de esta investigación es encontrar las principales características de la crisis antes citada por medio de un estudio socio-histórico de corte descriptivo para el caso de Estados Unidos como principal centro económico mundial, y así, caracterizar el último ciclo de largo plazo del capitalismo. El planteamiento pretende ser integral por lo que se analiza el fenómeno desde las principales escuelas económicas, la neoclásica, neokeynesiana, keynesiana y marxista. El documento concluye con una serie de propuestas de política económica entorno a las características de la crisis y del modelo de acumulación del ciclo de crecimiento de largo plazo que comenzó a partir del establecimiento de las políticas neoliberales en detrimento de las políticas de corte keynesiano de la posguerra. metadata García Ramírez, Roberto Fernando y Rojo Gutiérrez, Marco Antonio mail roberto.ramirez@unini.edu.mx, marco.rojo@unini.edu.mx (2022) La crisis de 2007 en Estados Unidos ¿Desequilibrio entre oferta y demanda o crisis de rentabilidad? MLS Law and International Politics, 1 (2).
Sección/Capítulo de Libro Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés The last fifty years have seen an environmental crisis caused by absurd political, economic and technological models which slowly bring ruin to society and the environment. The United Nations Organization (UN), as part of its United Nation Development Program (UNDP), fosters global sustainable development, specifically focusing on the need to address climate change. Additionally, international agreements and congresses have been trying to offer compensation alternatives for environmental protection. These efforts, however, have not been effective. Recent generations have caused mayor environmental impact, and we are now left with a huge rupture between governments, businesses and consumers who pass responsibility among each other. The global population generates with everything from everyday habits to complex production processes. Even though some people accept social and environmental responsibilities, this does not lead to any environmental recovery. This paper offers strategies for environmental recovery. Firstly, through strong public policy, secondly through accounting regulation obliging companies to take into account environmental impact and finally through education and the creation of curriculums that will promote more responsibility. metadata González Cortés, Luz Dary mail SIN ESPECIFICAR (2019) Leadership for Achieving Sustainable Development: Social and Environmental Concerns. In: Sustainable Leadership for Entrepreneurs and Academics. Springer, pp. 399-407. ISBN 978-3-030-15495-0
Artículo
Materias > Psicología
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Currently, high hospital readmission rates have become a problem for mental health services, because it is directly associated with the quality of patient care. The development of predictive models with machine learning algorithms allows the assessment of readmission risk in hospitals. The main objective of this paper is to predict the readmission risk of patients with schizophrenia in a region of Spain, using machine learning algorithms. In this study, we used a dataset with 6089 electronic admission records corresponding to 3065 patients with schizophrenia disorders. Data were collected in the period 2005–2015 from acute units of 11 public hospitals in a Spain region. The Random Forest classifier obtained the best results in predicting the readmission risk, in the metrics accuracy = 0.817, recall = 0.887, F1-score = 0.877, and AUC = 0.879. This paper shows the algorithm with highest accuracy value and determines the factors associated with readmission risk of patients with schizophrenia in this population. It also shows that the development of predictive models with a machine learning approach can help improve patient care quality and develop preventive treatments.
metadata
Góngora Alonso, Susel; Herrera Montano, Isabel; Martín Ayala, Juan Luis; Rodrigues, Joel J. P. C.; Franco-Martín, Manuel y de la Torre Díez, Isabel
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, juan.martin@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Machine Learning Models to Predict Readmission Risk of Patients with Schizophrenia in a Spanish Region.
International Journal of Mental Health and Addiction.
ISSN 1557-1874
Artículo Materias > Alimentación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Background: DNA methylation is the best epigenetic mechanism for explaining the interactions between nutrients and genes involved in intrauterine growth and development programming. A possible contributor of methylation abnormalities to congenital heart disease is the folate methylation regulatory pathway; however, the mechanisms and methylation patterns of VSD-associated genes are not fully understood. Objective: To determine if maternal dietary intake of folic acid (FA) is related to the methylation status (MS) of VSD-associated genes (AXIN1, MTHFR, TBX1, and TBX20). Methods: Prospective case–control study; 48 mothers and their children were evaluated. The mothers’ dietary variables were collected through a food frequency questionnaire focusing on FA and the consumption of supplements with FA. The MS of promoters of genes was determined in the children. Results: The intake of FA supplements was significantly higher in the control mothers. In terms of maternal folic acid consumption, significant differences were found in the first trimester of pregnancy. Significant differences were observed in the MS of MTHFR and AXIN1 genes in VSD and control children. A correlation between maternal FA supplementation and MS of AXIN1 and TBX20 genes was found in control and VSD children, respectively. Conclusions: A lower MS of AXIN1 genes and a higher MS of TBX20 genes is associated with FA maternal supplementation. metadata González-Peña, Sandra M.; Calvo-Anguiano, Geovana; Martínez-de-Villarreal, Laura E.; Ancer-Rodríguez, Patricia R.; Lugo-Trampe, José J.; Saldivar-Rodríguez, Donato; Hernández-Almaguer, María D.; Calzada-Dávila, Melissa; Guerrero-Orjuela, Ligia S. y Campos-Acevedo, Luis D. mail SIN ESPECIFICAR (2021) Maternal Folic Acid Intake and Methylation Status of Genes Associated with Ventricular Septal Defects in Children: Case–Control Study. Nutrients, 13 (6). p. 2071. ISSN 2072-6643
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
The prevalence of sleep disorders, characterized by issues with quality, timing, and sleep duration is increasing globally. Among modifiable risk factors, diet quality has been suggested to influence sleep features. The Mediterranean diet is considered a landmark dietary pattern in terms of quality and effects on human health. However, dietary habits characterized by this cultural heritage should also be considered in the context of overall lifestyle behaviors, including sleep habits. This study aimed to systematically revise the literature relating to adherence to the Mediterranean diet and sleep features in observational studies. The systematic review comprised 23 reports describing the relation between adherence to the Mediterranean diet and different sleep features, including sleep quality, sleep duration, daytime sleepiness, and insomnia symptoms. The majority of the included studies were conducted in the Mediterranean basin and reported a significant association between a higher adherence to the Mediterranean diet and a lower likelihood of having poor sleep quality, inadequate sleep duration, excessive daytime sleepiness or symptoms of insomnia. Interestingly, additional studies conducted outside the Mediterranean basin showed a relationship between the adoption of a Mediterranean-type diet and sleep quality, suggesting that biological mechanisms sustaining such an association may exist. In conclusion, current evidence suggests a relationship between adhering to the Mediterranean diet and overall sleep quality and different sleep parameters. The plausible bidirectional association should be further investigated to understand whether the promotion of a healthy diet could be used as a tool to improve sleep quality.
metadata
Godos, Justyna; Ferri, Raffaele; Lanza, Giuseppe; Caraci, Filippo; Rojas Vistorte, Angel Olider; Yélamos Torres, Vanessa; Grosso, Giuseppe y Castellano, Sabrina
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, angel.rojas@uneatlantico.es, vanessa.yelamos@funiber.org, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Mediterranean Diet and Sleep Features: A Systematic Review of Current Evidence.
Nutrients, 16 (2).
p. 282.
ISSN 2072-6643
Artículo
Materias > Comunicación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés, Español
Esta investigación ha sido desarrollada con el objetivo general de determinar un modelo de comunicación efectiva para la difusión de los Programas y Proyectos de Inversión Pública (PIP) del Departamento de Loreto, que ocupa la tercera parte del territorio del Perú, y, dadas sus características geográficas, existe mucha influencia cultural de Colombia y Brasil. Desde la perspectiva metodológica, se basó en un enfoque cuantitativo, de nivel descriptivo, con un diseño de campo, no experimental, transversal, que se apoyó en encuestas aplicadas a los tenientes gobernadores de los poblados ubicados en las fronteras con Colombia y Brasil. Una vez desarrollado el trabajo de campo, se realizó el procesamiento de la información, generando así el análisis descriptivo, la discusión de los resultados y la propuesta de modelo. En esencia, se llegó a la conclusión de que existen importantes limitaciones en el modelo actual de difusión de los PIP en el Departamento de Loreto, debilidades concernientes a todos los elementos de la comunicación: emisores dispersos y no preparados, receptores no caracterizados, canales desaprovechados, mensajes no codificados ni contextualizados, retroalimentación no estimulada. En vista de lo cual se diseña un Modelo de Comunicación Efectiva para la Difusión de los PIP (MCE-D-PIP) que plantea el desarrollo de una Sala Situacional de Comunicación Efectiva (SSCE– PIP), que permita potenciar los roles de productores, consumidores y prosumidores de la información, mediante la diversificación de los canales y una especializada codificación del mensaje, en función del contexto: diversidad cultural, condiciones educativas, factores tecnológicos, entre otros.
metadata
Gallo Infantes, Francisco Antonio; Arambarri, Jon; Lloret Romero, Nuria y Cadillo López, Claudet
mail
SIN ESPECIFICAR, jon.arambarri@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Modelo de comunicación efectiva para la difusión de los programas y proyectos de inversión pública del Departamento de Loreto, Perú.
MLS Educational Research, 7 (1).
ISSN 2792-9280
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Electroporation is a next generation bioelectronics device. The emerging application of electroporation requires high voltage pulses having a pulse-width in the nanosecond range. The essential use of a capacitor results in an increase in the size of the electroporator circuit. This paper discusses the modification of a conventional Marx generator circuit to achieve the high voltage electroporation pulses with a minimal chip size of the circuit. The reduced capacitors are attributed to a reduction in the number of stages used to achieve the required voltage boost. The paper proposes the improved isolation between two capacitors with the usage of optocouplers. Parametric analysis is presented to define the tuneable range of the electroporator circuit. The output voltage of 49.4 V is achieved using the proposed 5-stage MOSFET circuit with an input voltage of 12 V.
metadata
Ganesan, Selvakumar; Ghosh, Debarshi; Taneja, Ashu; Saluja, Nitin; Rani, Shalli; Singh, Aman; Elkamchouchi, Dalia H. y Delgado Noya, Irene
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, irene.delgado@uneatlantico.es
(2022)
A Modified Marx Generator Circuit with Enhanced Tradeoff between Voltage and Pulse Width for Electroporation Applications.
Electronics, 11 (13).
p. 2013.
ISSN 2079-9292
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Los cambios provocados por la globalización han construido una nueva realidad para los medios de producción y comunicación, la calidad de vida y el comportamiento, favoreciendo el surgimiento de proyectos en todo el mundo. Durante el gobierno del Partido de los Trabajadores (2003-2016), Brasil siguió esta tendencia, transformándose en un gran sitio de construcción, donde la ingeniería de exploración de petróleo y gas asumió un papel importante para la economía nacional. La alta demanda mundial de energía y el descubrimiento de la provincia del presal permitirían al país convertirse en exportador de energía y superpotencia para el año 2030, definiendo el carácter estratégico de los megaproyectos de exploración de petróleo y gas en la Cuenca de Santos, São Paulo. El programa de gobierno en la era del PT ofreció a Brasil un terreno fértil para el desarrollo económico, pero también para la ilegalidad, cuando una nueva realidad sacada a la luz en 2014 por la Operación Lava Jato desencadenó el mayor escándalo de corrupción en la historia de Brasil. La combinación de complejidad y corrupción provocó retrasos en la entrega de petróleo al mercado de consumo y enormes pérdidas financieras. La situación exigía iniciativas de apoyo a la gestión de horarios que estén a la altura del desafío, donde la respuesta esperada es la aplicación de un método de análisis de horarios – el Método FORTE v. 1.0 – responsable de la primera iniciativa integrada dirigida al cumplimiento, gestión de proyectos y conocimiento corporativo, ajustada a la realidad de los grandes proyectos de ingeniería en Brasil. La situación requería una solución de TI con diferentes características – Oracle Primavera P6 – y el resultado de la iniciativa es un conjunto de logros más allá de la gestión de proyectos, permeando todo el tejido organizacional. metadata Garat de Marin, Mirtha Silvana y Forte Silva, Marcus Vinícius mail silvana.marin@uneatlantico.es, SIN ESPECIFICAR (2023) Método FORTE v. 1.0: una contribución a la gestión de megaproyectos de ingeniería en Brasil. Project Design and Management. ISSN 2683-1597
Artículo
Materias > Psicología
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Background: In an unprecedented situation of interruption of the sporting dynamics, the world of sport is going through a series of adaptations necessary to continue functioning despite coronavirus disease 2019 (COVID-19). More than ever, athletes are facing a different challenge, a source of discomfort and uncertainty, and one that absolutely alters not only sports calendars, but also trajectories, progressions, and approaches to sports life. Therefore, it is necessary to identify the levels of psychological vulnerability that may have been generated in the athletes, because of the coexistence with dysfunctional responses during the COVID-19 experience, and which directly influence the decrease of their mental health.
Methods: With a descriptive and transversal design, the study aims to identify the state of the dysfunctional psychological response of a sample of Spanish athletes (N = 284). The DASS-21 (Depression, Anxiety, and Stress Scale), Toronto-20 (alexithymia), and Distress Tolerance Scale questionnaires were administered to a sample of high-level Spanish athletes in Olympic programs.
Results: The results suggest that the analyzed athletes indicate high levels of dysfunctional response (e.g., anxiety, stress, depression, and alexithymia) when their tolerance is low. In addition, the variables show less relational strength, when the capacity of tolerance to distress is worse and age is lower. At the same time, the greater the anxiety and uncertainty are, leading to more catastrophic and negative thoughts, the younger the athletes are.
Conclusions: It is clear that both age and tolerance to distress are considered adequate protective factors for psychological vulnerability in general and for associated dysfunctional responses in particular. Moreover, the psychological resources offered by more experienced athletes are also a guarantee of protection against negativity and catastrophism.
metadata
González-Hernández, Juan; López-Mora, Clara; Yüce, Arif; Nogueira-López, Abel y Tovar-Gálvez, Maria Isabel
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, abel.nogueira@uneatlantico.es, SIN ESPECIFICAR
(2021)
“Oh, My God! My Season Is Over!” COVID-19 and Regulation of the Psychological Response in Spanish High-Performance Athletes.
Frontiers in Psychology, 12.
ISSN 1664-1078
Artículo Materias > Biomedicina Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Strawberry polyphenols have been extensively studied over the last two decades for their beneficial properties. Recently, their possible use in ameliorating skin conditions has also been proposed; however, their role in preventing UVA-induced damage in cosmetic formulation has not yet been investigated. Skin is constantly exposed to several environmental stressors, such as UVA radiation, that induce oxidative stress, inflammation and cell death via the production of reactive oxygen species (ROS). In the present study, we assessed the potential photoprotective capacity of different strawberry-based formulations, enriched with nanoparticles of Coenzyme Q10 and with sun protection factor 10 (SPF10), in human dermal fibroblasts (HuDe) exposed to UVA radiation. We confirmed that strawberries are a very rich source of polyphenols, anthocyanins and vitamins, and possess high total antioxidant capacity. We also showed that strawberry extracts (25 μg/mL–1 mg/mL) exert a noticeable photoprotection in HuDe, increasing cell viability in a dose-dependent way, and that these effects are potentiated by the presence of CoQ10red (100 μg/mL). We have demonstrated for the first time that the topical use of strawberry extract may provide good photoprotection, even if more in-depth studies are strongly encouraged in order to evaluate the cellular and molecular effects of strawberry protection. metadata Gasparrini, Massimiliano; Forbes-Hernandez, Tamara Y.; Afrin, Sadia; Alvarez-Suarez, José; Gonzàlez-Paramàs, Ana; Santos-Buelga, Celestino; Bompadre, Stefano; Quiles, José; Mezzetti, Bruno y Giampieri, Francesca mail SIN ESPECIFICAR, tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2015) A Pilot Study of the Photoprotective Effects of Strawberry-Based Cosmetic Formulations on Human Dermal Fibroblasts. International Journal of Molecular Sciences, 16 (8). pp. 17870-17884. ISSN 1422-0067
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Strawberry bioactive compounds are widely known to be powerful antioxidants. In this study, the antioxidant and anti-aging activities of a polyphenol-rich strawberry extract were evaluated using human dermal fibroblasts exposed to H2O2. Firstly, the phenol and flavonoid contents of strawberry extract were studied, as well as the antioxidant capacity. HPLC-DAD analysis was performed to determine the vitamin C and β-carotene concentration, while HPLC-DAD/ESI-MS analysis was used for anthocyanin identification. Strawberry extract presented a high antioxidant capacity, and a relevant concentration of vitamins and phenolics. Pelargonidin- and cyanidin-glycosides were the most representative anthocyanin components of the fruits. Fibroblasts incubated with strawberry extract and stressed with H2O2 showed an increase in cell viability, a smaller intracellular amount of ROS, and a reduction of membrane lipid peroxidation and DNA damage. Strawberry extract was also able to improve mitochondrial functionality, increasing the basal respiration of mitochondria and to promote a regenerative capacity of cells after exposure to pro-oxidant stimuli. These findings confirm that strawberries possess antioxidant properties and provide new insights into the beneficial role of strawberry bioactive compounds on protecting skin from oxidative stress and aging.
metadata
Giampieri, Francesca; Alvarez-Suarez, José; Mazzoni, Luca; Forbes-Hernandez, Tamara Y.; Gasparrini, Massimiliano; Gonzàlez-Paramàs, Ana; Santos-Buelga, Celestino; Quiles, José; Bompadre, Stefano; Mezzetti, Bruno y Battino, Maurizio
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2014)
Polyphenol-Rich Strawberry Extract Protects Human Dermal Fibroblasts against Hydrogen Peroxide Oxidative Damage and Improves Mitochondrial Functionality.
Molecules, 19 (6).
pp. 7798-7816.
ISSN 1420-3049
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
A protracted pro-inflammatory state is a major contributing factor in the development, progression and complication of the most common chronic pathologies. Fruit and vegetables represent the main sources of dietary antioxidants and their consumption can be considered an efficient tool to counteract inflammatory states. In this context an evaluation of the protective effects of strawberry extracts on inflammatory stress induced by E. coli LPS on human dermal fibroblast cells was performed in terms of viability assays, ROS and nitrite production and biomarkers of oxidative damage of the main biological macromolecules. The results demonstrated that strawberry extracts exerted an anti-inflammatory effect on LPS-treated cells, through an increase in cell viability, and the reduction of ROS and nitrite levels, and lipid, protein and DNA damage. This work showed for the first time the potential health benefits of strawberry extract against inflammatory and oxidative stress in LPS-treated human dermal fibroblast cells.
metadata
Gasparrini, Massimiliano; Forbes-Hernandez, Tamara Y.; Giampieri, Francesca; Afrin, Sadia; Mezzetti, Bruno; Quiles, José L.; Bompadre, Stefano y Battino, Maurizio
mail
SIN ESPECIFICAR, tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2017)
Protective Effect of Strawberry Extract against Inflammatory Stress Induced in Human Dermal Fibroblasts.
Molecules, 22 (1).
p. 164.
ISSN 1420-3049
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Wearable monitoring devices are in demand in recent times for monitoring daily activities including exercise. Moreover, it is widely utilizing for preventing injuries of athletes during a practice session and in few cases, it leads to muscle fatigue. At present, emerging technology like the internet of things (IoT) and sensors is empowering to monitor and visualize the physical data from any remote location through internet connectivity. In this study, an IoT-enabled wearable device is proposing for monitoring and identifying the muscle fatigue condition using a surface electromyogram (sEMG) sensor. Normally, the EMG signal is utilized to display muscle activity. Arduino controller, Wi-Fi module, and EMG sensor are utilized in developing the wearable device. The Time-frequency domain spectrum technique is employed for classifying the three muscle fatigue conditions including mean RMS, mean frequency, etc. A real-time experiment is realized on six different individuals with developed wearable devices and the average RMS value assists to determine the average threshold of recorded data. The threshold level is analyzed by calculating the mean RMS value and concluded three fatigue conditions as >2 V: Extensive); 1–2 V: Moderate, and <1 V: relaxed. The warning alarm system was designed in LabVIEW with three color LEDs to indicate the different states of muscle fatigue. Moreover, the device is interfaced with the cloud through the internet provided with a Wi-Fi module embedded in wearable devices. The data available in the cloud server can be utilized for forecasting the frequency of an individual to muscle fatigue.
metadata
Gehlot, Anita; Singh, Rajesh; Siwach, Sweety; Vaseem Akram, Shaik; Alsubhi, Khalid; Singh, Aman; Delgado Noya, Irene y Choudhury, Sushabhan
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, irene.delgado@uneatlantico.es, SIN ESPECIFICAR
(2022)
Real Time Monitoring of Muscle Fatigue with IoT and Wearable Devices.
Computers, Materials & Continua, 72 (1).
pp. 999-1015.
ISSN 1546-2226
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Cardiovascular diseases are among the leading causes of mortality worldwide, with dietary factors being the main risk contributors. Diets rich in bioactive compounds, such as (poly)phenols, have been shown to potentially exert positive effects on vascular health. Among them, resveratrol has gained particular attention due to its potential antioxidant and anti-inflammatory action. Nevertheless, the results in humans are conflicting possibly due to interindividual different responses. The gut microbiota, a complex microbial community that inhabits the gastrointestinal tract, has been called out as potentially responsible for modulating the biological activities of phenolic metabolites in humans. The present review aims to summarize the main findings from clinical trials on the effects of resveratrol interventions on endothelial and vascular outcomes and review potential mechanisms interesting the role of gut microbiota on the metabolism of this molecule and its cardioprotective metabolites. The findings from randomized controlled trials show contrasting results on the effects of resveratrol supplementation and vascular biomarkers without dose-dependent effect. In particular, studies in which resveratrol was integrated using food sources, i.e., red wine, reported significant effects although the resveratrol content was, on average, much lower compared to tablet supplementation, while other studies with often extreme resveratrol supplementation resulted in null findings. The results from experimental studies suggest that resveratrol exerts cardioprotective effects through the modulation of various antioxidant, anti-inflammatory, and anti-hypertensive pathways, and microbiota composition. Recent studies on resveratrol-derived metabolites, such as piceatannol, have demonstrated its effects on biomarkers of vascular health. Moreover, resveratrol itself has been shown to improve the gut microbiota composition toward an anti-inflammatory profile. Considering the contrasting findings from clinical studies, future research exploring the bidirectional link between resveratrol metabolism and gut microbiota as well as the mediating effect of gut microbiota in resveratrol effect on cardiovascular health is warranted.
metadata
Godos, Justyna; Romano, Giovanni Luca; Gozzo, Lucia; Laudani, Samuele; Paladino, Nadia; Dominguez Azpíroz, Irma; Martínez López, Nohora Milena; Giampieri, Francesca; Quiles, José L.; Battino, Maurizio; Galvano, Fabio; Drago, Filippo y Grosso, Giuseppe
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, irma.dominguez@unini.edu.mx, nohora.martinez@uneatlantico.es, francesca.giampieri@uneatlantico.es, jose.quiles@uneatlantico.es, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Resveratrol and vascular health: evidence from clinical studies and mechanisms of actions related to its metabolites produced by gut microbiota.
Frontiers in Pharmacology, 15.
ISSN 1663-9812
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés Silicon photonics is rapidly evolving as an advanced chip framework for implementing quantum technologies. With the help of silicon photonics, general-purpose programmable networks with hundreds of discrete components have been developed. These networks can compute quantum states generated on-chip as well as more extraordinary functions like quantum transmission and random number generation. In particular, the interfacing of silicon photonics with complementary metal oxide semiconductor (CMOS) microelectronics enables us to build miniaturized quantum devices for next-generation sensing, communication, and generating randomness for assembling quantum computers. In this review, we assess the significance of silicon photonics and its interfacing with microelectronics for achieving the technology milestones in the next generation of quantum computers and quantum communication. To this end, especially, we have provided an overview of the mechanism of a homodyne detector and the latest state-of-the-art of measuring squeezed light along with its integration on a photonic chip. Finally, we present an outlook on future studies that are considered beneficial for the wide implementation of silicon photonics for distinct data-driven applications with maximum throughput. metadata Gupta, Rajeev; Singh, Rajesh; Gehlot, Anita; Akram, Shaik Vaseem; Yadav, Neha; Brajpuriya, Ranjeet; Yadav, Ashish; Wu, Yongling; Zheng, Hongyu; Biswas, Abhijit; Suhir, Ephraim; Yadav, Vikram Singh; Kumar, Tanuj y Verma, Ajay Singh mail SIN ESPECIFICAR (2023) Silicon photonics interfaced with microelectronics for integrated photonic quantum technologies: a new era in advanced quantum computers and quantum communications? Nanoscale. ISSN 2040-3364
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Doxorubicin (Dox), one of the most used chemotherapeutic agents, is known to generate oxidative stress and block DNA synthesis, which result in severe dose-limiting toxicity. A strategy to protect against Dox toxic effects could be to use dietary antioxidants of which fruits and vegetable are a rich source. In this context, strawberry consumption is associated with the maintenance of good health and the prevention of several diseases, thanks to the antioxidant capacities of its bioactive compounds. The aim of the present study was to evaluate the protective effects of strawberry consumption against oxidative stress induced by Dox in rats. Animals were fed with strawberry enriched diet (15% of the total calories) for two months and Dox (10 mg/kg; i.p.) was injected at the end of the experimental period. Strawberry consumption significantly inhibited ROS production and oxidative damage biomarkers accumulation in plasma and liver tissue and alleviated histopathological changes in rat livers treated with Dox. The reduction of antioxidant enzyme activities was significantly mitigated after strawberry consumption. In addition, strawberry enriched diet ameliorated liver mitochondrial antioxidant levels and functionality. In conclusion, strawberry intake protects against Dox-induced toxicity, at plasma, liver and mitochondrial levels thanks to its high contents of bioactive compounds.
metadata
Giampieri, Francesca; Alvarez-Suarez, Jose M.; Gasparrini, Massimiliano; Forbes- Hernandez, Tamara Y.; Afrin, Sadia; Bompadre, Stefano; Rubini, Corrado; Zizzi, Antonio; Astolfi, Paola; Santos-Buelga, Celestino; González-Paramás, Ana M.; Quiles, Josè L.; Mezzetti, Bruno y Battino, Maurizio
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2016)
Strawberry consumption alleviates doxorubicin-induced toxicity by suppressing oxidative stress.
Food and Chemical Toxicology, 94.
pp. 128-137.
ISSN 0278-6915
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Dietary polyphenols have been recently proposed as activators of the AMP-activated protein kinase (AMPK) signaling pathway and this fact might explain the relationship between the consumption of polyphenol-rich foods and the slowdown of the progression of aging. In the present work, the effects of strawberry consumption were evaluated on biomarkers of oxidative damage and on aging-associated reductions in mitochondrial function and biogenesis for 8weeks in old rats. Strawberry supplementation increased antioxidant enzyme activities, mitochondrial biomass and functionality, and decreased intracellular ROS levels and biomarkers of protein, lipid and DNA damage (P<0.05). Furthermore, a significant (P<0.05) increase in the expression of the AMPK cascade genes, involved in mitochondrial biogenesis and antioxidant defences, was also detected after strawberry intake. These in vivo results were then verified in vitro on HepG2 cells, confirming the involvement of AMPK in the beneficial effects exerted by strawberry against aging progression.
metadata
Giampieri, Francesca; Alvarez-Suarez, Josè M.; Cordero, Mario D.; Gasparrini, Massimiliano; Forbes-Hernandez, Tamara Y.; Afrin, Sadia; Santos-Buelga, Celestino; González-Paramás, Ana M.; Astolfi, Paola; Rubini, Corrado; Zizzi, Antonio; Tulipani, Sara; Quiles, Josè L.; Mezzetti, Bruno y Battino, Maurizio
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2017)
Strawberry consumption improves aging-associated impairments, mitochondrial biogenesis and functionality through the AMP-activated protein kinase signaling cascade.
Food Chemistry, 234.
pp. 464-471.
ISSN 03088146
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
A protracted pro-inflammatory state is the common denominator in the development, progression and complication of the common chronic diseases. Dietary antioxidants represent an efficient tool to counteract this inflammatory state. The aim of the present work was to evaluate the effects of strawberry extracts on inflammation evoked by E. Coli lipopolysaccharide in Human Dermal Fibroblast, by measuring reactive oxygen species production, apoptosis rate, antioxidant enzymes activity, mitochondria functionality and also investigating the molecular pathway involved in inflammatory and antioxidant response. The results demonstrated that strawberry pre-treatment reduced intracellular reactive oxygen species levels, apoptotic rate, improved antioxidant defences and mitochondria functionality in lipopolysaccharide -treated cells. Strawberry exerted these protective activities through the inhibition of the NF-kB signalling pathway and the stimulation of the Nrf2 pathway, with a mechanism AMPK-dependent. These results confirm the health benefits of strawberry in the prevention of inflammation and oxidative stress condition in lipopolysaccharide-treated cells.
metadata
Gasparrini, Massimiliano; Giampieri, Francesca; Forbes-Hernandez, Tamara Y.; Afrin, Sadia; Cianciosi, Danila; Reboredo-Rodriguez, Patricia; Varela-Lopez, Alfonso; Zhang, JiaoJiao; Quiles, Josè L.; Mezzetti, Bruno; Bompadre, Stefano y Battino, Maurizio
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2018)
Strawberry extracts efficiently counteract inflammatory stress induced by the endotoxin lipopolysaccharide in Human Dermal Fibroblast.
Food and Chemical Toxicology, 114.
pp. 128-140.
ISSN 0278-6915
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Extreme exposure of skin to Ultraviolet A (UVA)-radiation may induce a dysregulated production of reactive oxygen species (ROS) which can interact with cellular biomolecules leading to oxidative stress, inflammation, DNA damage, and alteration of cellular molecular pathways, responsible for skin photoaging, hyperplasia, erythema, and cancer. For these reasons, the use of dietary natural bioactive compounds with remarkable antioxidant activity could be a strategic tool to counteract these UVA-radiation-caused deleterious effects. Thus, the purpose of the present work was to test the efficacy of strawberry (50 μg/mL)-based formulations supplemented with Coenzyme Q10 (100 μg/mL) and sun protection factor 10 in human dermal fibroblasts irradiated with UVA-radiation. The apoptosis rate, the amount of intracellular reactive oxygen species (ROS) production, the expression of proteins involved in antioxidant and inflammatory response, and mitochondrial functionality were evaluated. The results showed that the synergic topical use of strawberry and Coenzyme Q10 provided a significant (p < 0.05) photoprotective effect, reducing cell death and ROS, increasing antioxidant defense, lowering inflammatory markers, and improving mitochondrial functionality. The obtained results suggest the use of strawberry-based formulations as an innovative, natural, and useful tool for the prevention of UVA exposure-induced skin diseases in order to decrease or substitute the amount of synthetic sunscreen agents.
metadata
Gasparrini, Massimiliano; Forbes-Hernandez, Tamara Y.; Afrin, Sadia; Reboredo-Rodriguez, Patricia; Cianciosi, Danila; Mezzetti, Bruno; Quiles, José L.; Bompadre, Stefano; Battino, Maurizio y Giampieri, Francesca
mail
SIN ESPECIFICAR, tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR
(2017)
Strawberry-Based Cosmetic Formulations Protect Human Dermal Fibroblasts against UVA-Induced Damage.
Nutrients, 9 (6).
p. 605.
ISSN 2072-6643
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Device-to-device (D2D) communication has attracted many researchers, cellular operators, and equipment makers as mobile traffic and bandwidth demands have increased. It supports direct communication within devices with no need for any intermediate node and, therefore, offers advantage in 5G network while providing wide cell coverage range and frequency reuse. However, establishing acceptable and secure mechanism for D2D communication which ensures confidentiality, integrity, and availability is an issue encountered in this situation. Furthermore, in a resource-constrained IoT environment, these security challenges are more critical and difficult to mitigate, especially during emergence of IoT with 5G network application scenarios. To address these issues, this paper proposed a security mechanism in 5G network for D2D wireless communication dependent on lightweight modified elliptic curve cryptography (LMECC). The proposed scheme follows a proactive routing protocol to discover services, managing link setup, and for data transfer with the aim to reduce communication overhead during user authentication. The proposed approach has been compared against Diffie–Hellman (DH) and ElGamal (ELG) schemes to evaluate the protocol overhead and security enhancement at network edge. Results proved the outstanding performance of the proposed LMECC for strengthening data secrecy with approximate 13% and 22.5% lower overhead than DH and ELG schemes.
metadata
Gupta, Divya; Rani, Shalli; Singh, Aman; Vidal Mazón, Juan Luis y Wang, Han
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@unic.co.ao, juanluis.vidal@uneatlantico.es, SIN ESPECIFICAR
(2022)
Towards Security Mechanism in D2D Wireless Communication: A 5G Network Approach.
Wireless Communications and Mobile Computing, 2022.
pp. 1-9.
ISSN 1530-8669
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The paddy crop is the most essential and consumable agricultural produce. Leaf disease impacts the quality and productivity of paddy crops. Therefore, tackling this issue as early as possible is mandatory to reduce its impact. Consequently, in recent years, deep learning methods have been essential in identifying and classifying leaf disease. Deep learning is used to observe patterns in disease in crop leaves. For instance, organizing a crop’s leaf according to its shape, size, and color is significant. To facilitate farmers, this study proposed a Convolutional Neural Networks-based Deep Learning (CNN-based DL) architecture, including transfer learning (TL) for agricultural research. In this study, different TL architectures, viz. InceptionV3, VGG16, ResNet, SqueezeNet, and VGG19, were considered to carry out disease detection in paddy plants. The approach started with preprocessing the leaf image; afterward, semantic segmentation was used to extract a region of interest. Consequently, TL architectures were tuned with segmented images. Finally, the extra, fully connected layers of the Deep Neural Network (DNN) are used to classify and identify leaf disease. The proposed model was concerned with the biotic diseases of paddy leaves due to fungi and bacteria. The proposed model showed an accuracy rate of 96.4%, better than state-of-the-art models with different variants of TL architectures. After analysis of the outcomes, the study concluded that the anticipated model outperforms other existing models
metadata
Gautam, Vinay; Trivedi, Naresh K.; Singh, Aman; Mohamed, Heba G.; Delgado Noya, Irene; Kaur, Preet y Goyal, Nitin
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, irene.delgado@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
A Transfer Learning-Based Artificial Intelligence Model for Leaf Disease Assessment.
Sustainability, 14 (20).
p. 13610.
ISSN 2071-1050
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
Over the last decades, the Mediterranean diet gained enormous scientific, social, and commercial attention due to proven positive effects on health and undeniable taste that facilitated a widespread popularity. Researchers have investigated the role of Mediterranean-type dietary patterns on human health all around the world, reporting consistent findings concerning its benefits. However, what does truly define the Mediterranean diet? The myriad of dietary scores synthesizes the nutritional content of a Mediterranean-type diet, but a variety of aspects are generally unexplored when studying the adherence to this dietary pattern. Among dietary factors, the main characteristics of the Mediterranean diet, such as consumption of fruit and vegetables, olive oil, and cereals should be accompanied by other underrated features, such as the following: (i) specific reference to whole-grain consumption; (ii) considering the consumption of legumes, nuts, seeds, herbs and spices often untested when exploring the adherence to the Mediterranean diet; (iii) consumption of eggs and dairy products as common foods consumed in the Mediterranean region (irrespectively of the modern demonization of dietary fat intake). Another main feature of the Mediterranean diet includes (red) wine consumption, but more general patterns of alcohol intake are generally unmeasured, lacking specificity concerning the drinking occasion and intensity (i.e., alcohol drinking during meals). Among other underrated aspects, cooking methods are rather simple and yet extremely varied. Several underrated aspects are related to the quality of food consumed when the Mediterranean diet was first investigated: foods are locally produced, minimally processed, and preserved with more natural methods (i.e., fermentation), strongly connected with the territory with limited and controlled impact on the environment. Dietary habits are also associated with lifestyle behaviors, such as sleeping patterns, and social and cultural values, favoring commensality and frugality. In conclusion, it is rather reductive to consider the Mediterranean diet as just a pattern of food groups to be consumed decontextualized from the social and geographical background of Mediterranean culture. While the methodologies to study the Mediterranean diet have demonstrated to be useful up to date, a more holistic approach should be considered in future studies by considering the aforementioned underrated features and values to be potentially applied globally through the concept of a “Planeterranean” diet.
metadata
Godos, Justyna; Scazzina, Francesca; Paternò Castello, Corrado; Giampieri, Francesca; Quiles, José L.; Briones Urbano, Mercedes; Battino, Maurizio; Galvano, Fabio; Iacoviello, Licia; de Gaetano, Giovanni; Bonaccio, Marialaura y Grosso, Giuseppe
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, francesca.giampieri@uneatlantico.es, jose.quiles@uneatlantico.es, mercedes.briones@uneatlantico.es, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Underrated aspects of a true Mediterranean diet: understanding traditional features for worldwide application of a “Planeterranean” diet.
Journal of Translational Medicine, 22 (1).
ISSN 1479-5876
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Currently, two-wheelers are the most popular mode of transportation, driven by the majority the people. Research by the World Health Organization (WHO) identifies that most two-wheeler deaths are caused due to not wearing a helmet. However, the advancement in sensors and wireless communication technology empowers one to monitor physical things such as helmets through wireless technology. Motivated by these aspects, this article proposes a wireless personal network and an Internet of Things assisted system for automating the ignition of two-wheelers with authorization and authentication through the helmet. The authentication and authorization are realized with the assistance of a helmet node and a two-wheeler node based on 2.4 GHz RF communication. The helmet node is embedded with three flex sensors utilized to experiment with different age groups and under different temperature conditions. The statistical data collected during the experiment are utilized to identify the appropriate threshold value through a t-test hypothesis for igniting the two-wheelers. The threshold value obtained after the t-test is logged in the helmet node for initiating the communication with the two-wheeler node. The pairing of the helmet node along with the RFID key is achieved through 2.4 GHZ RF communication. During real-time implementation, the helmet node updates the status to the server and LABVIEW data logger, after wearing the helmet. Along with the customization of hardware, a LABVIEW data logger is designed to visualize the data on the server side.
metadata
Gehlot, Anita; Singh, Rajesh; Kuchhal, Piyush; Kumar, Adesh; Singh, Aman; Alsubhi, Khalid; Ibrahim, Muhammad; Gracia Villar, Santos y Breñosa, Jose
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, josemanuel.brenosa@uneatlantico.es
(2021)
WPAN and IoT Enabled Automation to Authenticate Ignition of Vehicle in Perspective of Smart Cities.
Sensors, 21 (21).
p. 7031.
ISSN 1424-8220
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Background/Objectives: The diet quality of younger individuals is decreasing globally, with alarming trends also in the Mediterranean region. The aim of this study was to assess diet quality and adequacy in relation to country-specific dietary recommendations for children and adolescents living in the Mediterranean area. Methods: A cross-sectional survey was conducted of 2011 parents of the target population participating in the DELICIOUS EU-PRIMA project. Dietary data and cross-references with food-based recommendations and the application of the youth healthy eating index (YHEI) was assessed through 24 h recalls and food frequency questionnaires. Results: Adherence to recommendations on plant-based foods was low (less than ∼20%), including fruit and vegetables adequacy in all countries, legume adequacy in all countries except for Italy, and cereal adequacy in all countries except for Portugal. For animal products and dietary fats, the adequacy in relation to the national food-based dietary recommendations was slightly better (∼40% on average) in most countries, although the Eastern countries reported worse rates. Higher scores on the YHEI predicted adequacy in relation to vegetables (except Egypt), fruit (except Lebanon), cereals (except Spain), and legumes (except Spain) in most countries. Younger children (p < 0.005) reporting having 8–10 h adequate sleep duration (p < 0.001), <2 h/day screen time (p < 0.001), and a medium/high physical activity level (p < 0.001) displayed a better diet quality. Moreover, older respondents (p < 0.001) with a medium/high educational level (p = 0.001) and living with a partner (p = 0.003) reported that their children had a better diet quality. Conclusions: Plant-based food groups, including fruit, vegetables, legumes, and even (whole-grain) cereals are underrepresented in the diets of Mediterranean children and adolescents. Moreover, the adequate consumption of other important dietary components, such as milk and dairy products, is rather disregarded, leading to substantially suboptimal diets and poor adequacy in relation to dietary guidelines.
metadata
Giampieri, Francesca; Rosi, Alice; Scazzina, Francesca; Frias-Toral, Evelyn; Abdelkarim, Osama; Aly, Mohamed; Zambrano-Villacres, Raynier; Pons, Juancho; Vázquez-Araújo, Laura; Sumalla Cano, Sandra; Elío Pascual, Iñaki; Monasta, Lorenzo; Mata, Ana; Pardo, María Isabel; Busó, Pablo y Grosso, Giuseppe
mail
francesca.giampieri@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, sandra.sumalla@uneatlantico.es, inaki.elio@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Youth Healthy Eating Index (YHEI) and Diet Adequacy in Relation to Country-Specific National Dietary Recommendations in Children and Adolescents in Five Mediterranean Countries from the DELICIOUS Project.
Nutrients, 16 (22).
p. 3907.
ISSN 2072-6643
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
It is generally accepted that a fruit and vegetable–enriched diet is favorable for human health. The consumption of strawberries, in particular, has been related to the maintenance of well-being and the prevention of several chronic diseases, owing to the high contents of antioxidants and phytochemicals present in the fruit. Several biological effects have been explained through the total antioxidant capacity exerted by these bioactive compounds, but recently more intricate mechanisms have begun to be examined. In this context, it has been reported that strawberry phenolics are able to exert anti-inflammatory, anticarcinogenic, antiproliferative, and antiatherosclerotic activities, acting on specific molecular pathways related to antioxidant defenses, metabolism, survival, and proliferation. The overall aim of this work is to discuss and update the cellular and molecular mechanisms recently proposed to clarify the effects of strawberry phenolics on human health, with particular attention to the most common chronic diseases, such as metabolic syndrome, cardiovascular disease, and cancer.
metadata
Giampieri, Francesca; Forbes-Hernandez, Tamara Y.; Gasparrini, Massimiliano; Afrin, Sadia; Cianciosi, Danila; Reboredo-Rodriguez, Patricia; Varela-Lopez, Alfonso; Quiles, Jose L.; Mezzetti, Bruno y Battino, Maurizio
mail
SIN ESPECIFICAR, tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2017)
The healthy effects of strawberry bioactive compounds on molecular pathways related to chronic diseases.
Annals of the New York Academy of Sciences, 1398 (1).
pp. 62-71.
ISSN 0077-8923
H
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Background: To address the current pandemic, multiple studies have focused on the development of new mHealth applications to help curb the number of infections, these applications aim to accelerate the identification and self-isolation of people exposed to SARS-CoV- 2, the coronavirus known to cause COVID-19, by being in close contact with infected individuals. Objective: The main objectives of this paper are: 1)To analyze the current status of COVID-19 apps available the main virtual stores: Google Play Store and App Store, and 2)To propose a novel mobile application based on the limitations of the analyzed apps. Methods: The search for apps in this research was carried out in the main virtual stores: Google Play Store and App Store, until May 2021. After the analysis of the selected apps, a novel app is proposed whose main function will be the multiple transmission of information about the patient's symptoms from the application, without the need for phone calls or chat in real time. For its development, the flowchart shown in this session is followed. Results: The search yielded a total of 50 apps, of which 24 were relevant to this study. It is important to note that 23 of the apps analyzed are free. Of the total number of apps, 54% are available for Android and iOS operating systems. 50% of the apps have more than 5 thousand downloads. This means that Covid-19 related apps are in high demand among mobile device users today. The developed app is called COVINFO and its name comes from the union of the words COVID-19 and information, inserted in such a way that the user can get an idea of the app's functionality just by listening or reading the resulting name. The application has been created for mobile devices with Android operating system, being compatible with Android 4.4 and higher. Conclusions: Of the apps found, 37.5% only offer information about the virus and the necessary measures to avoid infection. During the analysis it was detected that 12.5% of the apps are focused on locating outbreaks and that none of them have been successful for the following reasons: not being interconnected to share data; and the request for access to the user's geolocation, generating distrust on the part of the user who, consequently, rejects them. This work addresses the development of an application for the transmission of the user's symptoms to his regular doctor, based on the fact that only 16.6% of the existing applications have this functionality. The COVINFO app offers a service that no other application on the market has: doctor-patient interaction without the need for calls or chat in real time for constant monitoring by the doctor of the patient's condition and evolution.
metadata
Herrera Montano, Isabel; Pérez Pacho, Javier; Gracia Villar, Santos; Aparicio Obregón, Silvia; Breñosa, Jose y de la Torre Díez, Isabel
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, silvia.aparicio@uneatlantico.es, josemanuel.brenosa@uneatlantico.es, SIN ESPECIFICAR
(2021)
Analysis of mobile apps for information, prevention and monitoring of covid-19 and proposal of an innovative app in this field.
JMIR Preprints.
(En Evaluación)
Ponencia/Presentación en Jornada, Congreso Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Congresos Cerrado Inglés Conventional IP networks connect places at great distances and meet the connectivity needs of their users. To perform each of these operations, each packet must pass through various network devices, which make individual routing decisions that make centralized network management difficult. These networks have been growing both in size and complexity, each day at a higher rate, which has generated a series of difficulties in personalization, integration, security, and optimization of these. As a solution, the Software-Defined Networking (SDN) architecture [1] was created, which promises to be a dynamic, manageable, profitable and adaptable architecture, thus becoming an ideal tool to handle large bandwidths and the development and implementation of customized applications, for different types of needs on communication networks. This document shows a performance analysis between SDN and a conventional IP network configured with the EIGRP and BGP routing protocols, establishing a configuration scenario with physical network equipment and with an SDN emulator called Mininet. The research methodology is based on the guidelines of the Cisco PPDIOO methodology and is developed in the following phases: 1. Elaboration of physical network topology with Cisco equipment, performing experiments with IPv4 and IPv6, measuring variables such as Jitter, Delay and Throughput. 2. Carrying out the same experiments and tests with SDN, in a network topology with similar characteristics to those already mentioned, but with OpenFlow switches. 3. Analysis of results, for which the behavior of jitter, delay and throughput variations of both scenarios is examined to make a series of comparisons (made with statistical analysis) concerning protocol, addressing, packet size among others. Finally, it was obtained as a result that SDN has a lower delay and jitter than the conventional IP network in some cases, as well as a more favorable throughput. metadata Hernandez, Leonel; Jimenez, Genett; Pranolo, Andri y Uc-Rios, Carlos mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, carlos.uc@unini.edu.mx (2019) Comparative Performance Analysis Between Software-Defined Networks and Conventional IP Networks. In: 2019 5th International Conference on Science in Information Technology (ICSITech), 24-24 otubre de 2019, Yogyakarta, Indonesia.
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
In the field of natural language processing, machine translation is a colossally developing research area that helps humans communicate more effectively by bridging the linguistic gap. In machine translation, normalization and morphological analyses are the first and perhaps the most important modules for information retrieval (IR). To build a morphological analyzer, or to complete the normalization process, it is important to extract the correct root out of different words. Stemming and lemmatization are techniques commonly used to find the correct root words in a language. However, a few studies on IR systems for the Urdu language have shown that lemmatization is more effective than stemming due to infixes found in Urdu words. This paper presents a lemmatization algorithm based on recurrent neural network models for the Urdu language. However, lemmatization techniques for resource-scarce languages such as Urdu are not very common. The proposed model is trained and tested on two datasets, namely, the Urdu Monolingual Corpus (UMC) and the Universal Dependencies Corpus of Urdu (UDU). The datasets are lemmatized with the help of recurrent neural network models. The Word2Vec model and edit trees are used to generate semantic and syntactic embedding. Bidirectional long short-term memory (BiLSTM), bidirectional gated recurrent unit (BiGRU), bidirectional gated recurrent neural network (BiGRNN), and attention-free encoder–decoder (AFED) models are trained under defined hyperparameters. Experimental results show that the attention-free encoder-decoder model achieves an accuracy, precision, recall, and F-score of 0.96, 0.95, 0.95, and 0.95, respectively, and outperforms existing models
metadata
Hafeez, Rabab; Anwar, Muhammad Waqas; Jamal, Muhammad Hasan; Fatima, Tayyaba; Martínez Espinosa, Julio César; Dzul López, Luis Alonso; Bautista Thompson, Ernesto y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, ulio.martinez@unini.edu.mx, luis.dzul@uneatlantico.es, ernesto.bautista@unini.edu.mx, SIN ESPECIFICAR
(2023)
Contextual Urdu Lemmatization Using Recurrent Neural Network Models.
Mathematics, 11 (2).
p. 435.
ISSN 2227-7390
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
To address the current pandemic, multiple studies have focused on the development of new mHealth apps to help in curbing the number of infections, these applications aim to accelerate the identification and self-isolation of people exposed to SARS-CoV-2, the coronavirus known to cause COVID-19, by being in close contact with infected individuals. The main objectives of this paper are: (1) Analyze the current status of COVID-19 apps available on the main virtual stores: Google Play Store and App Store for Spain, and (2) Propose a novel mobile application that allows interaction and doctor-patient follow-up without the need for real-time consultations (face-to-face or telephone). In this research, a search for eHealth and telemedicine apps related to Covid-19 was performed in the main online stores: Google Play Store and App Store, until May 2021. Keywords were entered into the search engines of the online stores and relevant apps were selected for study using a PRISMA methodology. For the design and implementation of the proposed app named COVINFO, the main weaknesses of the apps studied were taken into account in order to propose a novel and useful app for healthcare systems. The search yielded a total of 50 apps, of which 24 were relevant to this study, of which 23 are free and 54% are available for Android and iOS operating systems (OS). The proposed app has been developed for mobile devices with Android OS being compatible with Android 4.4 and higher. This app enables doctor-patient interaction and constant monitoring of the patient's progress without the need for calls, chats or face-to-face consultation in real time. This work addresses design and development of an application for the transmission of the user's symptoms to his regular doctor, based on the fact that only 16.6% of existing applications have this functionality. The COVINFO app offers a novel service: asynchronous doctor-patient communication, as well as constant monitoring of the patient’s condition and evolution. This app makes it possible to better manage the time of healthcare personnel and avoid overcrowding in hospitals, with the aim of preventing the collapse of healthcare systems and the spread of the coronavirus.
metadata
Herrera Montano, Isabel; Pérez Pacho, Javier; Gracia Villar, Santos; Aparicio Obregón, Silvia; Breñosa, Jose y de la Torre Díez, Isabel
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, silvia.aparicio@uneatlantico.es, josemanuel.brenosa@uneatlantico.es, SIN ESPECIFICAR
(2022)
Descriptive Analysis of Mobile Apps for Management of COVID-19 in Spain and Development of an Innovate App in that field.
Scientific Reports, 12 (1).
ISSN 2045-2322
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Higher education institutions' wireless networks have different roles and network requirements, ranging from educational platforms and informative consultations. Currently, the inefficient use of network resources, poor wireless planning, and other factors, affect having a robust and stable network platform. Different authors have investigated the various strategies for the optimization of wireless infrastructures. Still, most of the cases studied aim to improve traditional performance variables without considering maximizing the level of user satisfaction, which represents a flaw that this research paper hopes to solve through SDWN and a predictive model. The authors will determine an appropriate methodology to estimate the user's level of satisfaction through an algorithm or predictive model based on nonlinear multiple regression supported on network performance variables, making a characterization of the project's environment analyzing the wireless conditions. The investigation phases will follow the life cycle guidelines defined by the Cisco PPDIOO methodology (Prepare, Plan, Design, Implement, Operate, Optimize). As a result, it is expected that the project will be the beginning of academic research that will help create strategies to optimize the WiFi network of any educational institution to maximize user satisfaction. In short, the optimization process provides the network with differentiating factors through a modular design with variable modification of parameters according to the users' requirements and needs. metadata Hernandez, Leonel; Uc Ríos, Carlos Eduardo y Pranolo, Andri mail SIN ESPECIFICAR, carlos.uc@unini.edu.mx, SIN ESPECIFICAR (2021) Design a Model-Based on Nonlinear Multiple Regression to Predict the Level of User Satisfaction when Optimizing a Traditional WLAN Using SDWN. International Journal on Advanced Science, Engineering and Information Technology, 11 (4). p. 1487. ISSN 2088-5334
Artículo
Materias > Psicología
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Aggressive behaviour is a common response in different contexts all around the world. General aggression theories, such as the frustration-aggression theory, try to explain this behaviour in any context. However, situational specificity could play a relevant role in this issue, so proneness to behave aggressively may depend more on the context than on a general root or personality trait. With the aim of shedding light in this field, the current research aimed to analyse the relationship between aggressive behaviour on the road and intimate relationships. A sample composed of 275 participants who had a driving license and lived with an intimate partner completed a set of self-reports regarding aggressive behaviour in both contexts. The results suggested a convergence in the way of expressing anger, except in the case of adaptive aggression. A SEM-based approach indicated that the measured aggressive variables fitted better in two highly correlated factors rather than a single one, suggesting the relevance of the situational specificity in the prediction of aggressive behaviour in both contexts. Practical implications regarding evaluation and intervention for aggression reduction are discussed, as well as the limitations of the current research.
metadata
Herrero-Fernández, David; Parada-Fernández, Pamela; Rodríguez-Arcos, Irene; Martín Ayala, Juan Luis y Castaño Castaño, Sergio
mail
david.herrero@uneatlantico.es, pamela.parada@uneatlantico.es, SIN ESPECIFICAR, juan.martin@uneatlantico.es, sergio.castano@uneatlantico.es
(2023)
Do people drive as they live together? Associations between aggressive behaviour on the road and intimate relationships.
Transportation Research Part F: Traffic Psychology and Behaviour, 95.
pp. 251-260.
ISSN 13698478
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The Internet of Things (IoT) has positioned itself globally as a dominant force in the technology sector. IoT, a technology based on interconnected devices, has found applications in various research areas, including healthcare. Embedded devices and wearable technologies powered by IoT have been shown to be effective in patient monitoring and management systems, with a particular focus on pregnant women. This study provides a comprehensive systematic review of the literature on IoT architectures, systems, models and devices used to monitor and manage complications during pregnancy, postpartum and neonatal care. The study identifies emerging research trends and highlights existing research challenges and gaps, offering insights to improve the well-being of pregnant women at a critical moment in their lives. The literature review and discussions presented here serve as valuable resources for stakeholders in this field and pave the way for new and effective paradigms. Additionally, we outline a future research scope discussion for the benefit of researchers and healthcare professionals.
metadata
Hossain, Mohammad Mobarak; Kashem, Mohammod Abul; Islam, Md. Monirul; Sahidullah, Md.; Mumu, Sumona Hoque; Uddin, Jia; Gavilanes Aray, Daniel; de la Torre Diez, Isabel; Ashraf, Imran y Samad, Md Abdus
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, daniel.gavilanes@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Internet of Things in Pregnancy Care Coordination and Management: A Systematic Review.
Sensors, 23 (23).
p. 9367.
ISSN 1424-8220
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés The campus wireless networks have many users, who have different roles and network requirements, ranging from the use of educational platforms, informative consultations, emails, among others. Currently due to the inefficient use of network resources and little wireless planning, caused by the growth of the technological infrastructure (which is often due to daily worries, rather than to a lack of preparation by those in charge of managing the network), There are two essential factors that truncate the requirement of having a stable and robust network platform. First, the degradation of the quality of services perceived by users, and second, the congestion caused by the high demand for convergent traffic (video, voice, and data). Both factors imply great challenges on the part of the administrators of the network, which in many occasions are overwhelmed by permanent incidences of instability, coverage, and congestion, as well as the difficulty of maintaining it economically. The present investigation seeks to propose a process of optimization of the infrastructure and parameters of the configuration of a wireless network, that allows maximizing the level of satisfaction of the users in Higher Education Institutions. In the first place, it is expected to determine an adequate methodology to estimate the level of satisfaction of the users (defining a mathematical criterion or algorithm based on the study variables [1], characterize the environment in which the project will be developed, making a complete study of the wireless conditions and implement optimization strategies with software-defined networks (SDN). SDN is a concept in computer networks that allows network management to be carried out efficiently and flexibly, separating the control plane from the data plane into network devices. SDN architecture consists of an infrastructure layer which is a collection of network devices connected to the SDN Controller using protocol (OpenFlow) as a protocol [2]. Also, SDN will study traffic patterns on the network as a basis for optimizing network device usage [3]. The phases of the research will be carried out following the life cycle defined by the Cisco PPDIOO methodology (Prepare, Plan, Design, Implement, Operate, Optimize) metadata Hernandez, Leonel; Balmaceda, Nidia; Hernandez, Hugo; Vargas, Carlos; De La Hoz, Emiro; Orellano, Nataly; Vasquez, Emilse y Uc-Rios, Carlos mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, carlos.uc@unini.edu.mx (2019) Optimization of a WiFi Wireless Network that Maximizes the Level of Satisfaction of Users and Allows the Use of New Technological Trends in Higher Education Institutions. Lecture notes in computer science, 11587. pp. 144-160. ISSN 0302-9743
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The rising popularity of online shopping has led to a steady stream of new product evaluations. Consumers benefit from these evaluations as they make purchasing decisions. Many research projects rank products using these reviews, however, most of these methodologies have ignored negative polarity while evaluating products for client needs. The main contribution of this research is the inclusion of negative polarity in the analysis of product rankings alongside positive polarity. To account for reviews that contain many sentiments and different elements, the suggested method first breaks them down into sentences. This process aids in determining the polarity of products at the phrase level by extracting elements from product evaluations. The next step is to link the polarity to the review’s sentence-level features. Products are prioritized following user needs by assigning relative importance to each of the polarities. The Amazon review dataset has been used in the experimental assessments so that the efficacy of the suggested approach can be estimated. Experimental evaluation of PRUS utilizes rank score ( RS ) and normalized discounted cumulative gain ( nDCG ) score. Results indicate that PRUS gives independence to the user to select recommended list based on specific features with respect to positive or negative aspects of the products.
metadata
Hussain, Naveed; Mirza, Hamid Turab; Iqbal, Faiza; Altaf, Ayesha; Shoukat, Ahtsham; Gracia Villar, Mónica; Soriano Flores, Emmanuel; Rojo Gutiérrez, Marco Antonio y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, monica.gracia@uneatlantico.es, emmanuel.soriano@uneatlantico.es, marco.rojo@unini.edu.mx, SIN ESPECIFICAR
(2023)
PRUS: Product Recommender System Based on User Specifications and Customers Reviews.
IEEE Access, 11.
pp. 81289-81297.
ISSN 2169-3536
Artículo Materias > Educación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Este trabalho tenta analisar a relação entre treinamento de professores (TP), treinamento de professores em educação inclusiva (TPEI), treinamento de professores em tecnologias (TPT), treinamento de professores em ecologia (TPE) e treinamento de professores em tempo do pandemia (TPP), através de uma análise de fator de confirmação (AFC) com modelo de equação estrutural (SEM) de uma escala Likert criada ad hoc, validada e confirmada. Para a busca de respostas, foi realizado um processo de pesquisa não-experimental, descritivo, explicativo e correlacional. O instrumento utilizado para coletar os dados foi uma escala, validada em conteúdo e com um excelente alfa Cronbach (.902). A validade da construção foi realizada com uma análise fatorial exploratória (AFE). A amostra foi de 598 alunos de Mestrado em Formação de Professores e o último ano (4º) do Ensino Primário da Universidade de Jaen (Espanha). Pode-se concluir que existe uma relação entre as diferentes formas de formação de professores. A partir da análise correlacional, o maior coeficiente é entre formação de professores em ecologia e formação de professores em educação inclusiva. A partir da AFC confirma-se que essa correlação é uma relação muito forte, de modo que a inclusão e a ecologia devem ser eixos centrais em toda a formação de professores; por outro lado, conclui-se a baixa relação entre formação de professores e formação de professores em tempos de pandemia, de modo que, pelo menos em teoria, a Covid-19 não deve afetar a formação de professores. metadata Hernández Fernández, Antonio y de Barros Camargo, Claudia mail SIN ESPECIFICAR (2021) SEM model for technological, ecological and inclusive teacher training in times of pandemic. Texto Livre: Linguagem e Tecnologia, 14 (2). e33640. ISSN 1983-3652
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Telephysiotherapy has emerged as a vital solution for delivering remote healthcare, particularly in response to global challenges such as the COVID-19 pandemic. This study seeks to enhance telephysiotherapy by developing a system capable of accurately classifying physiotherapeutic exercises using PoseNet, a state-of-the-art pose estimation model. A dataset was collected from 49 participants (35 males, 14 females) performing seven distinct exercises, with twelve anatomical landmarks then extracted using the Google MediaPipe library. Each landmark was represented by four features, which were used for classification. The core challenge addressed in this research involves ensuring accurate and real-time exercise classification across diverse body morphologies and exercise types. Several tree-based classifiers, including Random Forest, Extra Tree Classifier, XGBoost, LightGBM, and Hist Gradient Boosting, were employed. Furthermore, two novel ensemble models called RandomLightHist Fusion and StackedXLightRF are proposed to enhance classification accuracy. The RandomLightHist Fusion model achieved superior accuracy of 99.6%, demonstrating the system’s robustness and effectiveness. This innovation offers a practical solution for providing real-time feedback in telephysiotherapy, with potential to improve patient outcomes through accurate monitoring and assessment of exercise performance.
metadata
Hussain, Shahzad; Siddiqui, Hafeez Ur Rehman; Saleem, Adil Ali; Raza, Muhammad Amjad; Alemany Iturriaga, Josep; Velarde-Sotres, Álvaro; Díez, Isabel De la Torre y Dudley, Sandra
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, josep.alemany@uneatlantico.es, alvaro.velarde@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Smart Physiotherapy: Advancing Arm-Based Exercise Classification with PoseNet and Ensemble Models.
Sensors, 24 (19).
p. 6325.
ISSN 1424-8220
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Objective: The objective of this paper is to review and analyze the current state of telemedicine and ehealth in the field of vascular surgery. Methods: This paper collects the relevant information obtained after reviewing the articles related to telemedicine in vascular surgery, published from 2012 to 2022 contained in scientific databases. In addition, the results obtained are statistically studied based on various factors, such as the year of publication or the search engine. In this way, we obtain a complete vision of the current state of telemedicine in the field of vascular surgery. Results: After performing this search and applying selection criteria, 29 articles were obtained for subsequent study and discussion, of which 20 were published in the second half of the decade, representing 70% of the results. In the analysis carried out according to the search criteria used, it can be seen that using the word telemedicine we obtained 69% of the articles while with the criteria mHealth and eHealth we only obtained 22% and 9% of the results, respectively. It can be seen that the filter with the most potential content articles was “vascular surgery AND telemedicine”. In the analysis performed according to the search engine, it was observed that the Google Scholar database contains 93% of the articles found in the massive search and the relevant articles contained therein represent 52% of the total. Conclusion: An upward trend has been observed in recent years, with a clear increase in the number of publications and much lower figures in the first years. One aspect to highlight is that 47.8% of the articles analyzed focus only on postoperative treatment, which may be due to the help provided by telemedicine in detecting surgical site infections by sending images and videos, this being one of the most common postoperative complications. The analyzed works show the importance of telemedicine in vascular surgery and identify possible future lines of research. In the analysis carried out on the origin of the selected relevant papers, an important interest of the US in this topic is demonstrated since more than 50% of the research contains authors from this country, it is also observed that there is no research from Spain, so this research would be an initial step to determine the weaknesses of telemedicine in this field of medicine and a good opportunity to open a research gap in this branch.
metadata
Herrera Montano, Isabel; Presencio Lafuente, Elena; Breñosa, Jose; Ortega-Mansilla, Arturo; Torre Díez, Isabel de la y Río-Solá, María Lourdes Del
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, josemanuel.brenosa@uneatlantico.es, arturo.ortega@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Systematic Review of Telemedicine and eHealth Systems Applied to Vascular Surgery.
Journal of Medical Systems, 46 (12).
ISSN 1573-689X
Artículo
Materias > Psicología
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Introduction: Trait driving anger is a widely studied personality variable in the field of road safety, due to its strong relationship with both risky behavior on the road and crash-related events. The Deffenbacher’s Driving Anger Scale theoretical approach has underlined different situations that could provoke anger in drivers, although trait driving anger is usually analyzed as a whole. Trait general anger has been proposed as one of the most relevant predictors of trait driving anger, showing moderate relationships with it. Method: The current research aimed to analyze the relationship between trait general anger and each one of the situations provoking anger, as well as to search for personality variables that could moderate these relationships. Based on literature review, it was expected that self-esteem would moderate both Discourtesy and Hostile gestures, Type-A behavior pattern would moderate both Slow driving and Traffic obstructions, and conscientiousness would moderate both Police presence and Illegal driving. A sample of 417 drivers (Mage = 31.24, SDage = 13.59, 64.5% females) taken from the Spanish general population completed a set of self-reports. Results: The results showed significant moderation effects in the case of Hostile gestures, Discourtesy, Illegal driving, and Slow driving. Conditional processes of these moderations were analyzed. Lastly, practical implications are discussed, allowing for tailored interventions to be implemented based on individual drivers' tendencies. Therefore, interventions should address different triggers of driving anger: boosting self-esteem for those angered by disrespect, targeting Type-A behavior reduction for those angered by traffic slowdowns, and promoting conscientiousness enhancement for those angered by others' risky driving.
metadata
Herrero-Fernández, David; Bogdan-Ganea, Smaranda R.; Álvarez Ferradas, Carla y Martín Ayala, Juan Luis
mail
david.herrero@uneatlantico.es, SIN ESPECIFICAR, carla.alvarez@uneatlantico.es, juan.martin@uneatlantico.es
(2024)
Which drivers drive as they live and who are transformed while driving? Analysis of moderators in the relationship between general anger and driving anger.
Journal of Safety Research, 90.
pp. 295-305.
ISSN 00224375
Artículo
Materias > Psicología
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Introduction: Road crashes are still one of the main causes of death around the world. Risky behavior has been proposed as one of the foremost predictors, with the theoretical framework of aberrant behavior emerging as a predominant approach for its examination. Sensation seeking has been pointed out as one of the main personality predictors of aberrant behavior. The current research aimed to investigate the moderated-moderation effect of both risk perception and self-esteem in the relationship between sensation seeking and aberrant behavior. Method: Two studies were conducted. The first study aimed to analyze the psychometric properties of the Spanish version of the Risk Perception Scale (RPS), a 10-item self-report to assess risk perception. A sample composed of 471 Spanish drivers (319 female, Mage = 29.75) completed the RPS. In the second study, a different sample of 236 Spanish drivers (129 female, Mage = 38.49) completed a set of self-reports aiming both to analyze the concurrent and divergent validity of the RPS, and to test the main moderated-moderation hypothesis. Results: With respect to the first study, the confirmatory factor analysis (CFA) supported a 7-item version which fitted in a single reliable factor (α = .74). Regarding the second study, the results supported both the concurrent and divergent validity of the RPS. Likewise, it was verified the moderated-moderation effect in the case of ordinary violations (R2 = .34), aggressive violations (R2 = .20), and lapses (R2 = .12). Conclusions: The RPS is a useful self-report to assess subjective risk perception in Spanish drivers. Both self-esteem and risk perception affect the relationship between sensation seeking and aberrant driving behavior. Practical implications: Intervention programs aiming to reduce aberrant driving behavior should be focused on reducing sensation seeking tendencies while simultaneously enhancing both risk perception skills and self-esteem.
metadata
Herrero-Fernández, David; Bogdan-Ganea, Smaranda R.; Setién-Suero, Esther y Martín Ayala, Juan Luis
mail
david.herrero@uneatlantico.es, SIN ESPECIFICAR, esther.setien@uneatlantico.es, juan.martin@uneatlantico.es
(2024)
The role of subjective risk perception and self-esteem in the relationship between sensation seeking and aberrant behaviors on the road: A moderated-moderation model.
Journal of Safety Research, 90.
pp. 31-42.
ISSN 00224375
I
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Internet of Things (IoT) has made significant strides in energy management systems recently. Due to the continually increasing cost of energy, supply–demand disparities, and rising carbon footprints, the need for smart homes for monitoring, managing, and conserving energy has increased. In IoT-based systems, device data are delivered to the network edge before being stored in the fog or cloud for further transactions. This raises worries about the data’s security, privacy, and veracity. It is vital to monitor who accesses and updates this information to protect IoT end-users linked to IoT devices. Smart meters are installed in smart homes and are susceptible to numerous cyber attacks. Access to IoT devices and related data must be secured to prevent misuse and protect IoT users’ privacy. The purpose of this research was to design a blockchain-based edge computing method for securing the smart home system, in conjunction with machine learning techniques, in order to construct a secure smart home system with energy usage prediction and user profiling. The research proposes a blockchain-based smart home system that can continuously monitor IoT-enabled smart home appliances such as smart microwaves, dishwashers, furnaces, and refrigerators, among others. An approach based on machine learning was utilized to train the auto-regressive integrated moving average (ARIMA) model for energy usage prediction, which is provided in the user’s wallet, to estimate energy consumption and maintain user profiles. The model was tested using the moving average statistical model, the ARIMA model, and the deep-learning-based long short-term memory (LSTM) model on a dataset of smart-home-based energy usage under changing weather conditions. The findings of the analysis reveal that the LSTM model accurately forecasts the energy usage of smart homes.
metadata
Iqbal, Faiza; Altaf, Ayesha; Waris, Zeest; Gavilanes Aray, Daniel; López Flores, Miguel Ángel; Díez, Isabel de la Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, daniel.gavilanes@uneatlantico.es, miguelangel.lopez@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Blockchain-Modeled Edge-Computing-Based Smart Home Monitoring System with Energy Usage Prediction.
Sensors, 23 (11).
p. 5263.
ISSN 1424-8220
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
With the outbreak of the COVID-19 pandemic, social isolation and quarantine have become commonplace across the world. IoT health monitoring solutions eliminate the need for regular doctor visits and interactions among patients and medical personnel. Many patients in wards or intensive care units require continuous monitoring of their health. Continuous patient monitoring is a hectic practice in hospitals with limited staff; in a pandemic situation like COVID-19, it becomes much more difficult practice when hospitals are working at full capacity and there is still a risk of medical workers being infected. In this study, we propose an Internet of Things (IoT)-based patient health monitoring system that collects real-time data on important health indicators such as pulse rate, blood oxygen saturation, and body temperature but can be expanded to include more parameters. Our system is comprised of a hardware component that collects and transmits data from sensors to a cloud-based storage system, where it can be accessed and analyzed by healthcare specialists. The ESP-32 microcontroller interfaces with the multiple sensors and wirelessly transmits the collected data to the cloud storage system. A pulse oximeter is utilized in our system to measure blood oxygen saturation and body temperature, as well as a heart rate monitor to measure pulse rate. A web-based interface is also implemented, allowing healthcare practitioners to access and visualize the collected data in real-time, making remote patient monitoring easier. Overall, our IoT-based patient health monitoring system represents a significant advancement in remote patient monitoring, allowing healthcare practitioners to access real-time data on important health metrics and detect potential health issues before they escalate.
metadata
Islam, Md. Milon; Shafi, Imran; Din, Sadia; Farooq, Siddique; Díez, Isabel de la Torre; Breñosa, Jose; Martínez Espinosa, Julio César y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, SIN ESPECIFICAR
(2024)
Design and development of patient health tracking, monitoring and big data storage using Internet of Things and real time cloud computing.
PLOS ONE, 19 (3).
e0298582.
ISSN 1932-6203
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Nanotechnology has opened new avenues for advanced research in various fields of soft materials. Materials scientists, chemists, physicists, and computational mathematicians have begun to take a keen interest in soft materials due to their potential applications in nanopatterning, membrane separation, drug delivery, nanolithography, advanced storage media, and nanorobotics. The unique properties of soft materials, particularly self-assembly, have made them useful in fields ranging from nanotechnology to biomedicine. The discovery of new morphologies in the diblock copolymer system in curved geometries is a challenging problem for mathematicians and theoretical scientists. Structural frustration under the effects of confinement in the system helps predict new structures. This mathematical study evaluates the effects of confinement and curvature on symmetric diblock copolymer melt using a cell dynamic simulation model. New patterns in lamella morphologies are predicted. The Laplacian involved in the cell dynamic simulation model is approximated by generating a 17-point stencil discretized to a polar grid by the finite difference method. Codes are programmed in FORTRAN to run the simulation, and IBM open DX is used to visualize the results. Comparison of computational results with existing studies validates this study and identifies defects and new patterns.
metadata
Iqbal, Muhammad Javed; Soomro, Inayatullah; Razzaq, Mirza Abdur; Omar-Martinez, Erislandy; Velázquez Martínez, Zaily Leticia y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, zaily.velazquez@unini.edu.mx, SIN ESPECIFICAR
(2024)
Investigation of structural frustration in symmetric diblock copolymers confined in polar discs through cell dynamic simulation.
Scientific Reports, 14 (1).
ISSN 2045-2322
Artículo Materias > Educación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Evaluating the quality of education contributes to the detection, as well as to the improvement or solution of failures in the educational system of schools. Likewise, teacher training is one of the main axes of educational quality. Objective: To evaluate educational quality through the degree of satisfaction of students and teachers. Methodology: An instrument based on a Likert scale was applied to 304 students and 198 teachers of the 18 largest private universities located in the city of Culiacán, Sinaloa. The research was carried out from the observational analytical method, including a cross-sectional and quantitative study of descriptive scope. Results: The results show that in the classrooms there is a heterogeneity of students with very particular interests and needs, while on the side of the educational institutions the interests do not always agree with these needs and interests, and even less with the formative education of the teachers. Conclusions: the crucial role of teachers and educational institutions in meeting the goals set for undergraduate students is recognized; at the same time, a permanent evaluation of educational quality and teacher training is required. metadata Ibarra-Sánchez, Alfredo y Acuña Gamboa, Luis Alan mail SIN ESPECIFICAR (2022) The Quality of Private Higher Education in Mexico: The Case of Culiacán, Sinaloa. Sinergias Educativas, 7 (1).
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Virtual histopathology is an emerging technology in medical imaging that utilizes advanced computational methods to analyze tissue images for more precise disease diagnosis. Traditionally, histopathology relies on manual techniques and expertise, often resulting in time-consuming processes and variability in diagnoses. Virtual histopathology offers a more consistent, and automated approach, employing techniques like machine learning, deep learning, and image processing to simulate staining and enhance tissue analysis. This review explores the strengths, limitations, and clinical applications of these methods, highlighting recent advancements in virtual histopathological approaches. In addition, important areas are identified for future research to improve diagnostic accuracy and efficiency in clinical settings.
metadata
Imran, Muhammad Talha; Shafi, Imran; Ahmad, Jamil; Butt, Muhammad Fasih Uddin; Gracia Villar, Santos; García Villena, Eduardo; Khurshaid, Tahir y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, eduardo.garcia@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Virtual histopathology methods in medical imaging - a systematic review.
BMC Medical Imaging, 24 (1).
ISSN 1471-2342
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Accurately predicting the remaining useful life (RUL) of lithium-ion (Li-ion) batteries is vital for improving battery performance and safety in applications such as consumer electronics and electric vehicles. While the prediction of RUL for these batteries is a well-established field, the current research refines RUL prediction methodologies by leveraging deep learning techniques, advancing prediction accuracy. This study proposes AccuCell Prodigy, a deep learning model that integrates auto-encoders and long short-term memory (LSTM) layers to enhance RUL prediction accuracy and efficiency. The model’s name reflects its precision (“AccuCell”) and predictive strength (“Prodigy”). The proposed methodology involves preparing a dataset of battery operational features, split using an 80–20 ratio for training and testing. Leveraging 22 variations of current (critical parameter) across three Li-ion cells, AccuCell Prodigy significantly reduces prediction errors, achieving a mean square error of 0.1305%, mean absolute error of 2.484%, and root mean square error of 3.613%, with a high R-squared value of 0.9849. These results highlight its robustness and potential for advancing battery health management.
metadata
Iftikhar, Mahrukh; Shoaib, Muhammad; Altaf, Ayesha; Iqbal, Faiza; Gracia Villar, Santos; Dzul López, Luis Alonso y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, SIN ESPECIFICAR
(2024)
A deep learning approach to optimize remaining useful life prediction for Li-ion batteries.
Scientific Reports, 14 (1).
ISSN 2045-2322
J
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Generative intelligence relies heavily on the integration of vision and language. Much of the research has focused on image captioning, which involves describing images with meaningful sentences. Typically, when generating sentences that describe the visual content, a language model and a vision encoder are commonly employed. Because of the incorporation of object areas, properties, multi-modal connections, attentive techniques, and early fusion approaches like bidirectional encoder representations from transformers (BERT), these components have experienced substantial advancements over the years. This research offers a reference to the body of literature, identifies emerging trends in an area that blends computer vision as well as natural language processing in order to maximize their complementary effects, and identifies the most significant technological improvements in architectures employed for image captioning. It also discusses various problem variants and open challenges. This comparison allows for an objective assessment of different techniques, architectures, and training strategies by identifying the most significant technical innovations, and offers valuable insights into the current landscape of image captioning research.
metadata
Jamil, Azhar; Rehman, Saif Ur; Mahmood, Khalid; Gracia Villar, Mónica; Prola, Thomas; Diez, Isabel De La Torre; Samad, Md Abdus y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, monica.gracia@uneatlantico.es, thomas.prola@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Deep Learning Approaches for Image Captioning: Opportunities, Challenges and Future Potential.
IEEE Access.
p. 1.
ISSN 2169-3536
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español, Portugués Existe en el país el escenario de mercado lleno de este producto, con varias marcas y jugadores fruto de la dependencia al 90% de las importaciones y se han registrado muchos inconvenientes en su proceso de comercialización y ventas. Tras un cuidadoso análisis, se identificó que este problema se debe a la falta de un programa adecuado de control de calidad de estos productos. En términos generales, el presente estudio tenía como objetivo desarrollar un sistema de gestión y seguimiento de la calidad de los aceites lubricantes para automóviles aplicable al contexto angoleño. A través de una investigación cualitativa y como resultado de un estudio exploratorio, que incluyó entrevistas y estudios de campo, a las partes interesadas en las áreas de producción, importación, inspección, comercialización y fiscalización de combustibles y lubricantes, este estudio presenta una propuesta de programa de monitoreo de aceites lubricantes automotrices con el fin de garantizar la calidad del producto. Una vez hecho esto, los resultados permitieron identificar los inconvenientes del modelo actual de gestión de la calidad de los combustibles y lubricantes y, en consecuencia, sistematizar una propuesta de modelo para un "Sistema Integrado de Monitorización de la Calidad de los Lubricantes" con el potencial de ser extendido también a la monitorización y gestión de la calidad de otras clases de aceites lubricantes y combustibles. Tras describir su funcionalidad, sus principios y las condiciones de estructuración para el funcionamiento de la respectiva propuesta, el estudio recomienda al Ministerio de Recursos Minerales, Petróleo y Gas de la República de Angola que haga suya la idea de crear e implementar el sistema aquí propuesto metadata Jacob Kurtz, Diego y Morais, Pedro Gelson mail 0000-0002-5483-2211, SIN ESPECIFICAR (2021) Desarrollo de un sistema de gestión y control de la calidad de los aceites lubricantes para automóviles aplicable al contexto angoleño. Project Design and Management, 3 (2). pp. 99-116. ISSN 2683-1597
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Classification is a commonly used technique in data mining and is applied in various fields such as sentiment analysis, fraud detection, and fault diagnosis. Multiclass classification, which involves more than two classes, is more complex than binary classification. There are mainly two ways to approach multiclass classification, one is to expand the binary classifier into a multiclass classifier through various strategies and the other is to divide the multiclass classification problem into multiple binary problems (binarization). Two popular approaches for binarization are One vs One (OvO) and One vs All (OvA). It is simpler to aggregate the outputs of all binary classifiers as the number of classifiers decreases. However, it causes an imbalance of positive and negative sample numbers, which affects the classification effect of each binary classifier. In this article, we contribute to the field of ensemble learning and multi-class classification by proposing a new method called Ensemble Partition Sampling (EPS). This article presents a new approach to multiclass classification using an "Ensemble Partition Sampling" method within the "one-vs-all" (OvA) framework. The primary goal of this method is to tackle the problem of data imbalance by incorporating ensemble learning and preprocessing techniques into each binary dataset. The study found that Ensemble Partition Sampling (EPS) is the most effective method for imbalanced and multiclass imbalanced classification, outperforming other methods including OvA, SMOTE, k-means-SMOTE, Bagging-RB, DES-MI, OvO-EASY, and OvO-SMB. The study used CART, Random Forest, and SVM as classifiers, and the results consistently showed that EPS outperformed all other algorithms. The findings suggest that EPS is a highly effective method for improving classification performance in imbalanced and multiclass imbalanced datasets.
metadata
Jabir, Brahim; Díez, Isabel De la Torre; Bautista Thompson, Ernesto; Ramírez-Vargas, Debora L. y Kuc Castilla, Ángel Gabriel
mail
SIN ESPECIFICAR
(2023)
Ensemble Partition Sampling (EPS) for Improved Multi-Class Classification.
IEEE Access.
p. 1.
ISSN 2169-3536
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés The organic polymer known as Polypyrrole (Ppy) is synthesized when pyrrole monomers are polymerized. Excellent thermal stability, superior electrical conductivity, and environmental stability are all characteristics of Polypyrrole. Chemical oxidative polymerization was used to synthesize Ppy using Ferric chloride (FeCl3) as an oxidizing agent and surfactant CTAB in aqueous solution. Oxidant (FeCl3) to pyrrole varied in different molar ratios (2, 3, 4 and 5). It was found that increasing this ratio up to 4 increases PPy's conductivity. XRD, FTIR, and SEM were used to characterize Ppy. The conductive nature of Ppy was studied by I–V characteristics. The best conductive polymer is studied for the NH3 gas response. metadata Jain, Alok; Nabeel, Ansari Novman; Bhagwat, Sunita; Kumar, Rajeev; Sharma, Shubham; Kozak, Drazan; Hunjet, Anica; Kumar, Abhinav y Singh, Rajesh mail SIN ESPECIFICAR (2023) Fabrication of polypyrrole gas sensor for detection of NH3 using an oxidizing agent and pyrrole combinations: Studies and characterizations. Heliyon, 9 (7). e17611. ISSN 24058440
Artículo Materias > Educación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés The information and communication technologies-ICT, have more use with the implementation of Learning Management System-LMS; The present study was carried out to evaluate the use of four LMS in a university, to identify acceptance and performance, through the student's inputs, the LMS used: Edmodo, Classroom, Schoology and Moodle, the methodology consisted of 4 stages; 1) LMS selection, 2) conFiguretion LMS, 3) evaluation of acceptance factors and 4) calculation of statistical coefficients. The results obtained from the four LMS, Google Classroom in its conFiguretion has the highest level of performance, with an average of 73%; while for the statistical coefficients; Of seven factors evaluated for the level of acceptance, those with the greatest preference for the learners were System Factors FS (82%), Anxiety and innovationAI (80%) and Virtual Library BV (43%). metadata Juarez Santiago, Brenda; Olivares Ramírez, Juan Manuel; Ferriol Sánchez, Fermín y Ledesma Uribe, Norma Alejandra mail SIN ESPECIFICAR, SIN ESPECIFICAR, fermin.ferriol@unini.edu.mx, SIN ESPECIFICAR (2020) New model, to evaluate the implementation of LMS in institutions at a higher level, through the supplies of the student. Journal of Systems and Educational Management. pp. 7-16. ISSN 2410-3977
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
The standard optimization of open-pit mine design and production scheduling, which is impacted by a variety of factors, is an essential part of mining activities. The metal uncertainty, which is connected to supply uncertainty, is a crucial component in optimization. To address uncertainties regarding the economic value of mining blocks and the general problem of mine design optimization, a minimum-cut network flow algorithm is employed to give the optimal ultimate pit limits and pushback designs under uncertainty. A structure that is computationally effective and can manage the joint presentation and treatment of the economic values of mining blocks under various circumstances is created by the push re-label minimum-cut technique. In this study, the algorithm is put to the test using a copper deposit and shows similarities to other stochastic optimizers for mine planning that have already been created. Higher possibilities of reaching predicted production targets are created by the algorithm’s earlier selection of more certain blocks with blocks of high value. Results show that, in comparison to a conventional approach using the same algorithm, the cumulative metal output is larger when the uncertainty in the metal content is taken into consideration. There is also an additional 10% gain in net present value.
metadata
Joshi, Devendra; Ali Albahar, Marwan; Chithaluru, Premkumar; Singh, Aman; Yadav, Arvind y Miró Vera, Yini Airet
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, yini.miro@uneatlantico.es
(2022)
A Novel Approach to Integrating Uncertainty into a Push Re-Label Network Flow Algorithm for Pit Optimization.
Mathematics, 10 (24).
p. 4803.
ISSN 2227-7390
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Traditional optimization of open pit mine design is a crucial component of mining endeavors and is influenced by many variables. The critical factor in optimization is the geological uncertainty, which relates to the ore grade. To deal with uncertainties related to the block economic values of mining blocks and the general problem of mine design optimization, under unknown conditions, the best ultimate pit limits and pushback designs are produced by a minimum cut algorithm. The push–relabel minimal cut algorithm provides a framework for computationally efficient representation and processing of the economic values of mining blocks under multiple scenarios. A sequential Gaussian simulation-based smoothing spline technique was created. To produce pushbacks, an efficient parameterized minimum cut algorithm is suggested. An analysis of Indian iron ore mining was performed. The developed mine scheduling algorithm was compared with the conventional algorithm, and the results show that when uncertainty is considered, the cumulative metal production is higher and there is an additional increase of about 5% in net present value. The results of this work help the mining industry to plan mines in such a way that can generate maximum profit from the deposits.
metadata
Joshi, Devendra; Chithaluru, Premkumar; Singh, Aman; Yadav, Arvind; Elkamchouchi, Dalia H.; Mazas Pérez-Oleaga, Cristina y Anand, Divya
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, cristina.mazas@uneatlantico.es, divya.anand@uneatlantico.es
(2022)
A Novel Large-Scale Stochastic Pushback Design Merged with a Minimum Cut Algorithm for Open Pit Mine Production Scheduling.
Systems, 10 (5).
p. 159.
ISSN 2079-8954
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
This study involves a working limestone mine that supplies limestone to the cement factory. The two main goals of this paper are to (a) determine how long an operating mine can continue to provide the cement plant with the quality and quantity of materials it needs, and (b) explore the viability of combining some limestone from a nearby mine with the study mine limestone to meet the cement plant’s quality and quantity goals. These objectives are accomplished by figuring out the maximum net profit for the ultimate pit limit and production sequencing of the mining blocks. The issues were resolved using a branch-and-cut based sequential integer and mixed integer programming problem. The study mine can exclusively feed the cement plant for up to 15 years, according to the data. However, it was also noted that the addition of the limestone from the neighboring mine substantially increased the mine’s life (85 years). The findings also showed that, when compared with the production planning formulation that the company is now using, the proposed approach creates 10% more profit. The suggested method also aids in determining the desired desirable quality of the limestone that will be transported from the nearby mine throughout each production stage.
metadata
Joshi, Devendra; Chithaluru, Premkumar; Singh, Aman; Yadav, Arvind; Elkamchouchi, Dalia H.; Breñosa, Jose y Anand, Divya
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, josemanuel.brenosa@uneatlantico.es, divya.anand@uneatlantico.es
(2022)
An Optimized Open Pit Mine Application for Limestone Quarry Production Scheduling to Maximize Net Present Value.
Mathematics, 10 (21).
p. 4140.
ISSN 2227-7390
K
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Adaptive equalization is crucial in mitigating distortions and compensating for frequency response variations in communication systems. It aims to enhance signal quality by adjusting the characteristics of the received signal. Particle swarm optimization (PSO) algorithms have shown promise in optimizing the tap weights of the equalizer. However, there is a need to enhance the optimization capabilities of PSO further to improve the equalization performance. This paper provides a comprehensive study of the issues and challenges of adaptive filtering by comparing different variants of PSO and analyzing the performance by combining PSO with other optimization algorithms to achieve better convergence, accuracy, and adaptability. Traditional PSO algorithms often suffer from high computational complexity and slow convergence rates, limiting their effectiveness in solving complex optimization problems. To address these limitations, this paper proposes a set of techniques aimed at reducing the complexity and accelerating the convergence of PSO.
metadata
Khan, Arooj; Shafi, Imran; Khawaja, Sajid Gul; de la Torre Díez, Isabel; López Flores, Miguel Ángel; Castanedo Galán, Juan y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, miguelangel.lopez@uneatlantico.es, juan.castanedo@uneatlantico.es, SIN ESPECIFICAR
(2023)
Adaptive Filtering: Issues, Challenges, and Best-Fit Solutions Using Particle Swarm Optimization Variants.
Sensors, 23 (18).
p. 7710.
ISSN 1424-8220
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
The provision of Wireless Fidelity (Wi-Fi) service in an indoor environment is a crucial task and the decay in signal strength issues arises especially in indoor environments. The Line-of-Sight (LOS) is a path for signal propagation that commonly impedes innumerable indoor objects damage signals and also causes signal fading. In addition, the Signal decay (signal penetration), signal reflection, and long transmission distance between transceivers are the key concerns. The signals lose their power due to the existence of obstacles (path of signals) and hence destroy received signal strength (RSS) between different communicating nodes and ultimately cause loss of the packet. Thus, to solve this issue, herein we propose an advanced model to maximize the LOS in communicating nodes using a modern indoor environment. Our proposal comprised various components for instance signal enhancers, repeaters, reflectors,. these components are connected. The signal attenuation and calculation model comprises of power algorithm and hence it can quickly and efficiently find the walls and corridors as obstacles in an indoor environment. We compared our proposed model with state of the art model using Received Signal Strength (RSS) and Packet Delivery Ratio (PDR) (different scenario) and found that our proposed model is efficient. Our proposed model achieved high network throughput as compared to the state-of-the-art models.
metadata
Khan, Muhammad Nasir; Waqas, Muhammad; Abbas, Qamar; Qureshi, Ahsan; Amin, Farhan; de la Torre Díez, Isabel; Uc Ríos, Carlos Eduardo y Fabian Gongora, Henry
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, carlos.uc@unini.edu.mx, henry.gongora@uneatlantico.es
(2024)
Advanced Line-of-Sight (LOS) model for communicating devices in modern indoor environment.
PLOS ONE, 19 (7).
e0305039.
ISSN 1932-6203
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
SIN ESPECIFICAR
metadata
Kimothi, Sanjeev; Thapliyal, Asha; Akram, Shaik Vaseem; Singh, Rajesh; Gehlot, Anita; Mohamed, Heba G.; Anand, Divya; Ibrahim, Muhammad y Delgado Noya, Irene
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, SIN ESPECIFICAR, irene.delgado@uneatlantico.es
(2022)
Big Data Analysis Framework for Water Quality Indicators with Assimilation of IoT and ML.
Electronics, 11 (13).
p. 1927.
ISSN 2079-9292
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
SIN ESPECIFICAR
metadata
Khawaja, Seher Ansar; Farooq, Muhammad Shoaib; Ishaq, Kashif; Alsubaie, Najah; Karamti, Hanen; Caro Montero, Elizabeth; Silva Alvarado, Eduardo René y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, elizabeth.caro@uneatlantico.es, eduardo.silva@funiber.org, SIN ESPECIFICAR
(2024)
Correction: Prediction of leukemia peptides using convolutional neural network and protein compositions.
BMC Cancer, 24 (1).
ISSN 1471-2407
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Objective Epileptic seizures are neurological events that pose significant risks of physical injuries characterized by sudden, abnormal bursts of electrical activity in the brain, often leading to loss of consciousness and uncontrolled movements. Early seizure detection is essential for timely treatments and better patient outcomes. To address this critical issue, there is a need for an advanced artificial intelligence approach for the early detection of epileptic seizure disorder. Methods This study primarily focuses on designing a novel ensemble approach to perform early detection of epileptic seizure disease with high performance. A novel ensemble approach consisting of a fast, independent component analysis random forest (FIR) and prediction probability is proposed, which uses electroencephalography (EEG) data to investigate the efficacy of the proposed approach for early detection of epileptic seizures. The FIR model extracts independent components and class prediction probability features, creating a new feature set. The proposed model combined integrated component analysis (ICA) with predicting probability to enhance seizure recognition accuracy scores. Extensive experimental evaluations demonstrate that FIR assists machine learning models to obtain superior results compared to original features. Results The research gap is addressed using combined features to improve the performance of epileptic seizure detection compared to a single feature set. In particular, the ensemble model FIR with support vector machine (FIR + SVM) outperforms other methods, achieving an accuracy of 98.4% for epileptic seizure detection. Conclusions The proposed FIR has the potential for early diagnosis of epileptic seizures and can significantly help the medical industry with enhanced detection and timely interventions.
metadata
Khalid, Madiha; Raza, Ali; Akhtar, Adnan; Rustam, Furqan; Brito Ballester, Julién; Rodríguez Velasco, Carmen Lilí; Díez, Isabel de la Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, julien.brito@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Diagnosing epileptic seizures using combined features from independent components and prediction probability from EEG data.
DIGITAL HEALTH, 10.
ISSN 2055-2076
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español, Portugués Esta investigación se derivó de una parte de la base teórica de la tesis de maestría del autor, desarrollada en conjunto con el Programa de Maestría en Diseño, Gestión y Gestión de Proyectos, en la Universidad Internacional Iberoamericana, UNINI-México (UNINI-MX). El autor tiene experiencia en proyectos en el sector de la construcción, su compatibilidad y enseñanza del software específico utilizado en este segmento, y se motivó al observar el contexto en la práctica y la vergüenza personal. En otros países, es una realidad, y no una novedad, aprobar los puntajes de los proyectos de construcción, en relación con sus criterios de construcción, antes de proceder a su logro. También es digno de mención que los proyectos que resultan del modelado de la información de construcción (proyectos BIM), entre otros avances tecnometodológicos entrantes de manera exponencialmente creciente en la velocidad de ocurrencia, calidad y cantidad de colaboraciones, exigen cada vez más cambios en los paradigmas en la construcción civil, pero facilitan la extracción de datos que pueden evaluarse, en relación con su capacidad de construcción, de forma automatizada. El propósito de BIM no debe ser solo la automatización de los resultados gráficos-textuales. Este trabajo buscó conceptualizar, con base en la literatura y las experiencias, cómo y cuándo extraer información de proyectos BIM que buscan automatizar la Evaluación de la Constructibilidad del Edificio. metadata Kotaira, Keila mail SIN ESPECIFICAR (2020) Evaluación de constructividad en Proyectos BIM en Brasil. Project Design and Management, 2 (2). pp. 7-23. ISSN 2683-1597
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
COVID-19 declared as a pandemic that has a faster rate of infection and has impacted the lives and the country’s economy due to forced lockdowns. Its detection using RT-PCR is required long time and due to which its infection has grown exponentially. This creates havoc for the shortage of testing kits in many countries. This work has proposed a new image processing-based technique for the health care systems named “C19D-Net”, to detect “COVID-19” infection from “Chest X-Ray” (XR) images, which can help radiologists to improve their accuracy of detection COVID-19. The proposed system extracts deep learning (DL) features by applying the InceptionV4 architecture and Multiclass SVM classifier to classify and detect COVID-19 infection into four different classes. The dataset of 1900 Chest XR images has been collected from two publicly accessible databases. Images are pre-processed with proper scaling and regular feeding to the proposed model for accuracy attainments. Extensive tests are conducted with the proposed model (“C19D-Net”) and it has succeeded to achieve the highest COVID-19 detection accuracy as 96.24% for 4-classes, 95.51% for three-classes, and 98.1% for two-classes. The proposed method has outperformed well in expressions of “precision”, “accuracy”, “F1-score” and “recall” in comparison with most of the recent previously published methods. As a result, for the present situation of COVID-19, the proposed “C19D-Net” can be employed in places where test kits are in short supply, to help the radiologists to improve their accuracy of detection of COVID-19 patients through XR-Images.
metadata
Kaur, Prabhjot; Harnal, Shilpi; Tiwari, Rajeev; Alharithi, Fahd S.; Almulihi, Ahmed H.; Delgado Noya, Irene y Goyal, Nitin
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, irene.delgado@uneatlantico.es, SIN ESPECIFICAR
(2021)
A Hybrid Convolutional Neural Network Model for Diagnosis of COVID-19 Using Chest X-ray Images.
International Journal of Environmental Research and Public Health, 18 (22).
p. 12191.
ISSN 1660-4601
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Agriculture is a critical domain, where technology can have a significant impact on increasing yields, improving crop quality, and reducing environmental impact. The use of renewable energy sources such as solar power in agriculture has gained momentum in recent years due to the potential to reduce the carbon footprint of farming operations. In addition to providing a source of clean energy, solar tracking systems can also be used for remote weather monitoring in the agricultural field. The ability to collect real-time data on weather parameters such as temperature, humidity, and rainfall can help farmers make informed decisions on irrigation, pest control, and other crop management practices. The main idea of this study is to present a system that can improve the efficiency of solar panels to provide constant power to the sensor in the agricultural field and transfer real-time data to the app. This research presents a mechanism to improve the arrangement of a photovoltaic (PV) array with solar power and to produce maximum energy. The proposed system changes its direction in two axes (azimuth and elevation) by detecting the difference between the position of the sun and the panel to track the sun using a light-dependent resistor. A testbed with a hardware experimental setup is designed to test the system’s capability to track according to the position of the sun effectively. In the end, real-time data are displayed using the Android app, and the weather data are transferred to the app using a GSM/WiFi module. This research improves the existing system, and results showed that the relative increase in power generation was up to 52%. Using intelligent artificial intelligence techniques with the QoS algorithm, the quality of service produced by the existing system is improved.
metadata
Kanwal, Tabassum; Rehman, Saif Ur; Ali, Tariq; Mahmood, Khalid; Gracia Villar, Santos; Dzul Lopez, Luis y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, luis.dzul@unini.edu.mx, SIN ESPECIFICAR
(2023)
An Intelligent Dual-Axis Solar Tracking System for Remote Weather Monitoring in the Agricultural Field.
Agriculture, 13 (8).
p. 1600.
ISSN 2077-0472
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
In today’s technological and stressful world, when everyone is busy in their daily routines and places blind faith in pharmaceutical advancements to protect their health, the sudden, horrifying effects of the COVID-19 pandemic have resulted in serious emotional and psychological impacts in the general population. In spite of advanced vaccination campaigns, fear and hesitation have become a part of human life since there are a number of people who do not want to take these immunity boosting vaccinations. Such people may become carriers of infectious viruses, leading to a more rapid rate of spread; therefore, this class of spreaders needs to be screened at the earliest opportunity. In this context, there is a need for advanced health monitoring systems which can assist the pharmaceutical industry to monitor and record the health status of people. To address this need and reduce the uncertainty of the situation, this study has designed and tested an Internet of Things (IoT) and Fog computing-based multi-node architecture was for real-time initial screening and recording of such subjects. The proposed system was able to record current body temperature and location coordinates along with the facial images. Further, the proposed system was able to transmit data to a cloud database using internet-connected services. An implementation and reviews-based working environment analysis was conducted to determine the efficacy of the proposed system. It was observed from the statistical analysis that the proposed IoT Fog-enabled ecosystem could be utilized efficiently.
metadata
Khullar, Vikas; Singh, Harjit Pal; Miró Vera, Yini Airet; Anand, Divya; Mohamed, Heba G.; Gupta, Deepali; Kumar, Navdeep y Goyal, Nitin
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, yini.miro@uneatlantico.es, divya.anand@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
IoT Fog-Enabled Multi-Node Centralized Ecosystem for Real Time Screening and Monitoring of Health Information.
Applied Sciences, 12 (19).
p. 9845.
ISSN 2076-3417
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Society and the environment are severely impacted by catastrophic events, specifically floods. Inadequate emergency preparedness and response are frequently the result of the absence of a comprehensive plan for flood management. This article proposes a novel flood disaster management (FDM) system using the full lifecycle disaster event model (FLCNDEM), an abstract model based on the function super object. The proposed FDM system integrates data from existing flood protocols, languages, and patterns and analyzes viewing requests at various phases of an event to enhance preparedness and response. The construction of a task library and knowledge base to initialize FLCNDEM results in FLCDEM flooding response. The proposed FDM system improves the emergency response by offering a comprehensive framework for flood management, including pre-disaster planning, real-time monitoring, and post-disaster evaluation. The proposed system can be modified to accommodate various flood scenarios and enhance global flood management.
metadata
Khan, Saad Mazhar; Shafi, Imran; Butt, Wasi Haider; Díez, Isabel de la Torre; López Flores, Miguel Ángel; Castanedo Galán, Juan y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, miguelangel.lopez@uneatlantico.es, juan.castanedo@uneatlantico.es, SIN ESPECIFICAR
(2023)
Model Driven Approach for Efficient Flood Disaster Management with Meta Model Support.
Land, 12 (8).
p. 1538.
ISSN 2073-445X
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The world population is on the rise, which demands higher food production. The reduction in the amount of land under cultivation due to urbanization makes this more challenging. The solution to this problem lies in the artificial cultivation of crops. IoT and sensors play an important role in optimizing the artificial cultivation of crops. The selection of sensors is important in order to ensure a better quality and yield in an automated artificial environment. There are many challenges involved in selecting sensors due to the highly competitive market. This paper provides a novel approach to sensor selection for saffron cultivation in an IoT-based environment. The crop used in this study is saffron due to the reason that much less research has been conducted on its hydroponic cultivation using sensors and its huge economic impact. A detailed hardware-based framework, the growth cycle of the crop, along with all the sensors, and the block layout used for saffron cultivation in a hydroponic medium are provided. The important parameters for a hydroponic medium, such as the concentration of nutrients and flow rate required, are discussed in detail. This paper is the first of its kind to explain the sensor configurations, performance metrics, and sensor-based saffron cultivation model. The paper discusses different metrics related to the selection, use and role of sensors in different IoT-based saffron cultivation practices. A smart hydroponic setup for saffron cultivation is proposed. The results of the model are evaluated using the AquaCrop simulator. The simulator is used to evaluate the value of performance metrics such as the yield, harvest index, water productivity, and biomass. The values obtained provide better results as compared to natural cultivation.
metadata
Kour, Kanwalpreet; Gupta, Deepali; Gupta, Kamali; Anand, Divya; Elkamchouchi, Dalia H.; Mazas Pérez-Oleaga, Cristina; Ibrahim, Muhammad y Goyal, Nitin
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, SIN ESPECIFICAR, cristina.mazas@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Monitoring Ambient Parameters in the IoT Precision Agriculture Scenario: An Approach to Sensor Selection and Hydroponic Saffron Cultivation.
Sensors, 22 (22).
p. 8905.
ISSN 1424-8220
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Cerrado
Inglés
Blockchain technology may provide a potential solution to the Internet of Things (IoT) security challenges by providing a decentralized and secure method for storing, managing, and sharing data. The Secure Hash Algorithm (SHA-256) hashed value of preliminary data (block) is retained in one block along with transaction data in tree form and timestamp in a chain of blocks. However, there are observations about blockchain limitations such as higher energy consumption, secure data, self-maintenance reliance, and higher cost. These constraints can be overcome by incorporating encryption algorithms into accepting blocks of data. In this paper, we propose a secure intelligent computational model for a large-scale interconnected IoT environment; an analytical modeling technique is considered for the proposed system. The proposed system takes advantage of the potential security feature of blockchain, which is considered the most appropriate secure communication system in an IoT. A computational model is built using the proposed blockchain technology to incorporate a secure and intelligent communication system. The proposed system uses the enhanced McEliece encryption approach’s potential to link the blockchain due to the faster mode of encryption and decryption process with a highly reduced number of steps.
metadata
Kumar, Sunil; Singh, Aman; Benslimane, Abderrahim; Chithaluru, Premkumar; Albahar, Marwan Ali; Rathore, Rajkumar Singh y Álvarez, Roberto Marcelo
mail
SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, roberto.alvarez@uneatlantico.es
(2023)
An Optimized Intelligent Computational Security Model for Interconnected Blockchain-IoT System & Cities.
Ad Hoc Networks, 151.
p. 103299.
ISSN 15708705
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Cerrado
Inglés
Leukemia is a type of blood cell cancer that is in the bone marrow’s blood-forming cells. Two types of Leukemia are acute and chronic; acute enhances fast and chronic growth gradually which are further classified into lymphocytic and myeloid leukemias. This work evaluates a unique deep convolutional neural network (CNN) classifier that improves identification precision by carefully examining concatenated peptide patterns. The study uses leukemia protein expression for experiments supporting two different techniques including independence and applied cross-validation. In addition to CNN, multilayer perceptron (MLP), gated recurrent unit (GRU), and recurrent neural network (RNN) are applied. The experimental results show that the CNN model surpasses competitors with its outstanding predictability in independent and cross-validation testing applied on different features extracted from protein expressions such as amino acid composition (AAC) with a group of AAC (GAAC), tripeptide composition (TPC) with a group of TPC (GTPC), and dipeptide composition (DPC) for calculating its accuracies with their receiver operating characteristic (ROC) curve. In independence testing, a feature expression of AAC and a group of GAAC are applied using MLP and CNN modules, and ROC curves are achieved with overall 100% accuracy for the detection of protein patterns. In cross-validation testing, a feature expression on a group of AAC and GAAC patterns achieved 98.33% accuracy which is the highest for the CNN module. Furthermore, ROC curves show a 0.965% extraordinary result for the GRU module. The findings show that the CNN model is excellent at figuring out leukemia illnesses from protein expressions with higher accuracy.
metadata
Khawaja, Seher Ansar; Farooq, Muhammad Shoaib; Ishaq, Kashif; Alsubaie, Najah; Karamti, Hanen; Caro Montero, Elizabeth; Silva Alvarado, Eduardo René y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, elizabeth.caro@uneatlantico.es, eduardo.silva@funiber.org, SIN ESPECIFICAR
(2024)
Prediction of leukemia peptides using convolutional neural network and protein compositions.
BMC Cancer, 24 (1).
ISSN 1471-2407
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The Internet of Things (IoT) has changed the worldwide network of people, smart devices, intelligent things, data, and information as an emergent technology. IoT development is still in its early stages, and numerous interrelated challenges must be addressed. IoT is the unifying idea of embedding everything. The Internet of Things offers a huge opportunity to improve the world’s accessibility, integrity, availability, scalability, confidentiality, and interoperability. However, securing the Internet of Things is a difficult issue. The IoT aims to connect almost everything within the framework of a common infrastructure. This helps in controlling devices and, will allow device status to be updated everywhere and at any time. To develop technology via IoT, several critical scientific studies and inquiries have been carried out. However, many obstacles and problems remain to be tackled in order to reach IoT’s maximum potential. These problems and concerns must be taken into consideration in different areas of the IoT, such as implementation in remote areas, threats to the system, development support, social and environmental impacts, etc. This paper reviews the current state of the art in different IoT architectures, with a focus on current technologies, applications, challenges, IoT protocols, and opportunities. As a result, a detailed taxonomy of IoT is presented here which includes interoperability, scalability, security and energy efficiency, among other things. Moreover, the significance of blockchains and big data as well as their analysis in relation to IoT, is discussed. This article aims to help readers and researchers understand the IoT and its applicability to the real world.
metadata
Kumar, Arun; Sharma, Sharad; Singh, Aman; Alwadain, Ayed; Choi, Bong-Jun; Breñosa, Jose; Ortega-Mansilla, Arturo y Goyal, Nitin
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, josemanuel.brenosa@uneatlantico.es, arturo.ortega@uneatlantico.es, SIN ESPECIFICAR
(2021)
Revolutionary Strategies Analysis and Proposed System for Future Infrastructure in Internet of Things.
Sustainability, 14 (1).
p. 71.
ISSN 2071-1050
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
To provide faster access to the treatment of patients, healthcare system can be integrated with Internet of Things to provide prior and timely health services to the patient. There is a huge limitation in the sensing layer as the IoT devices here have low computational power, limited storage and less battery life. So, this huge amount of data needs to be stored on the cloud. The information and the data sensed by these devices is made accessible on the internet from where medical staff, doctors, relatives and family members can access this information. This helps in improving the treatment as well as getting faster medical assistance, tracking of routine activities and health focus of elderly people on frequent basis. However, the data transmission from IoT devices to the cloud faces many security challenges and is vulnerable to different security and privacy threats during the transmission path. The purpose of this research is to design a Certificateless Secured Signature Scheme that will provide a magnificent amount of security during the transmission of data. Certificateless signature, that removes the intricate certificate management and key escrow problem, is one of the practical methods to provide data integrity and identity authentication for the IoT. Experimental result shows that the proposed scheme performs better than the existing certificateless signature schemes in terms of computational cost, encryption and decryption time. This scheme is the best combination of high security and cost efficiency and is further suitable for the resource constrained IoT environment.
metadata
Kakkar, Latika; Gupta, Deepali; Tanwar, Sarvesh; Saxena, Sapna; Alsubhi, Khalid; Anand, Divya; Delgado Noya, Irene y Goyal, Nitin
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, irene.delgado@uneatlantico.es, SIN ESPECIFICAR
(2022)
A Secure and Efficient Signature Scheme for IoT in Healthcare.
Computers, Materials & Continua, 73 (3).
pp. 6151-6168.
ISSN 1546-2226
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Disaster management is a critical area that requires efficient methods and techniques to address various challenges. This comprehensive assessment offers an in-depth overview of disaster management systems, methods, obstacles, and potential future paths. Specifically, it focuses on flood control, a significant and recurrent category of natural disasters. The analysis begins by exploring various types of natural catastrophes, including earthquakes, wildfires, and floods. It then delves into the different domains that collectively contribute to effective flood management. These domains encompass cutting-edge technologies such as big data analysis and cloud computing, providing scalable and reliable infrastructure for data storage, processing, and analysis. The study investigates the potential of the Internet of Things and sensor networks to gather real-time data from flood-prone areas, enhancing situational awareness and enabling prompt actions. Model-driven engineering is examined for its utility in developing and modeling flood scenarios, aiding in preparation and response planning. This study includes the Google Earth engine (GEE) and examines previous studies involving GEE. Moreover, we discuss remote sensing; remote sensing is undoubtedly a valuable tool for disaster management, and offers geographical data in various situations. We explore the application of Geographical Information System (GIS) and Spatial Data Management for visualizing and analyzing spatial data and facilitating informed decision-making and resource allocation during floods. In the final section, the focus shifts to the utilization of machine learning and data analytics in flood management. These methodologies offer predictive models and data-driven insights, enhancing early warning systems, risk assessment, and mitigation strategies. Through this in-depth analysis, the significance of incorporating these spheres into flood control procedures is highlighted, with the aim of improving disaster management techniques and enhancing resilience in flood-prone regions. The paper addresses existing challenges and provides future research directions, ultimately striving for a clearer and more coherent representation of disaster management techniques.
metadata
Khan, Saad Mazhar; Shafi, Imran; Butt, Wasi Haider; Diez, Isabel de la Torre; López Flores, Miguel Ángel; Castanedo Galán, Juan y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, miguelangel.lopez@uneatlantico.es, juan.castanedo@uneatlantico.es, SIN ESPECIFICAR
(2023)
A Systematic Review of Disaster Management Systems: Approaches, Challenges, and Future Directions.
Land, 12 (8).
p. 1514.
ISSN 2073-445X
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Artificial intelligence (AI)-based models have emerged as powerful tools in financial markets, capable of reducing investment risks and aiding in selecting highly profitable stocks by achieving precise predictions. This holds immense value for investors, as it empowers them to make data-driven decisions. Identifying current and future trends in multi-class forecasting techniques employed within financial markets, particularly profitability analysis as an evaluation metric is important. The review focuses on examining stud-ies conducted between 2018 and 2023, sourced from three prominent academic databases. A meticulous three-stage approach was employed, encompassing the systematic planning, conduct, and analysis of the se-lected studies. Specifically, the analysis emphasizes technical assessment, profitability analysis, hybrid mod-eling, and the type of results generated by models. Articles were shortlisted based on inclusion and exclusion criteria, while a rigorous quality assessment through ten quality criteria questions, utilizing a Likert-type scale was employed to ensure methodological robustness. We observed that ensemble and hybrid models with long short-term memory (LSTM) and support vector machines (SVM) are being more adopted for financial trends and price prediction. Moreover, hybrid models employing AI algorithms for feature engineering have great potential at par with ensemble techniques. Most studies only employ performance metrics and lack utilization of profitability metrics or investment or trading strategy (simulated or real-time). Similarly, research on multi-class or output is severely lacking in financial forecasting and can be a good avenue for future research.
metadata
Khattak, Bilal Hassan Ahmed; Shafi, Imran; Khan, Abdul Saboor; Soriano Flores, Emmanuel; García Lara, Roberto; Samad, Md. Abdus y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, emmanuel.soriano@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
A Systematic Survey of AI Models in Financial Market Forecasting for Profitability Analysis.
IEEE Access, 11.
pp. 125359-125380.
ISSN 2169-3536
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The probability of medical staff to get affected from COVID19 is much higher due to their working environment which is more exposed to infectious diseases. So, as a preventive measure the body temperature monitoring of medical staff at regular intervals is highly recommended. Infrared temperature sensing guns have proved its effectiveness and therefore such devices are used to monitor the body temperature. These devices are either used on hands or forehead. As a result, there are many issues in monitoring the temperature of frontline healthcare professionals. Firstly, these healthcare professionals keep wearing PPE (Personal Protective Equipment) kits during working hours and as a result it would be very difficult to monitor their body temperature. Secondly, these healthcare professionals also wear face shields and in such cases monitoring temperature by exposing forehead needs removal of face shield. Doing so after regular intervals is surely uncomfortable for healthcare professionals. To avoid such issues, this paper is disclosing a technologically advanced face shield equipped with sensors capable of monitoring body temperature instantly without the hassle of removing the face shield. This face shield is integrated with a built-in infrared temperature sensor. A total of 10 such face shields were printed and assembled within the university lab and then handed over to a group of ten members including faculty and students of nursing and health science department. This sequence was repeated four times and as a result 40 healthcare workers participated in the study. Thereafter, feedback analysis was conducted on questionnaire data and found a significant overall mean score of 4.59 out of 5 which indicates that the product is effective and worthy in every facet. Stress analysis is also performed in the simulated environment and found that the device can easily withstand the typically applied forces. The limitations of this product are difficulty in cleaning the product and comparatively high cost due to the deployment of electronic equipment
metadata
Kumar Kaushal, Rajesh; Kumar, Naveen; Kukreja, Vinay; S. Alharithi, Fahd; H. Almulihi, Ahmed; Ortega-Mansilla, Arturo y Rani, Shikha
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, arturo.ortega@uneatlantico.es, SIN ESPECIFICAR
(2022)
Technologically Advanced Reusable 3D Face Shield for Health Workers Confronting COVID19.
Computers, Materials & Continua, 72 (2).
pp. 2565-2579.
ISSN 1546-2226
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
This paper introduced a method using hybrid combination of network restructuring and optimal placement of optimally sized distributed generators (DG) to reduce loss and improve voltage profile in a practical transmission network for scenario of high load demand for a period of ten years. A study is performed for four study cases which includes the test transmission network without considering optimal DG placement and network restructuring, considering network restructuring, optimal placement of DG units using proposed grid parameter oriented harmony search algorithm (GPOHSA) and considering hybrid combination of network restructuring and DG placement using GPOHSA. Network restructuring is achieved by addition of a new 400 kV Grid-substation (GSS) and a 220 kV GSS along with associated transmission system. GPOHSA is obtained by a modification in the conventional harmony search algorithm (HSA) where grid coordinates are used for locating the individuals in an objective space. Performance Improvement Indicators such as real power loss reduction indicator (SPLRI), reactive power loss reduction indicator (SQLRI) and summation of node voltage deviation reduction indicator (SNVDRI) are proposed to evaluate performance of each case of study. The period of investment return is assessed to evaluate the pay back period of the investments incurred in network restructuring and DG units. It is established that hybrid combination of network restructuring and DG units placement using GPOHSA is effective to meet the increased load demand for time period of ten years with reduced losses and improved voltage profile. Investment incurred on the network restructuring and DG units placement will be recovered in a time period of 4 years. Effectiveness of the GPOHSA is better relative to the conventional genetic algorithm (GA) for DG unit placement. The study is performed using the MATLAB software on a practical transmission network in India.
metadata
Kumar, Pramod; Swarnkar, Nagendra Kumar; Ali, Ahmed; Mahela, Om Prakash; Khan, Baseem; Anand, Divya y Brito Ballester, Julién
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, julien.brito@uneatlantico.es
(2023)
Transmission Network Loss Reduction and Voltage Profile Improvement Using Network Restructuring and Optimal DG Placement.
Sustainability, 15 (2).
p. 976.
ISSN 2071-1050
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Revistas Científicas
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Named Entity Recognition (NER) is a natural language processing task that has been widely explored for different languages in the recent decade but is still an under-researched area for the Urdu language due to its rich morphology and language complexities. Existing state-of-the-art studies on Urdu NER use various deep-learning approaches through automatic feature selection using word embeddings. This paper presents a deep learning approach for Urdu NER that harnesses FastText and Floret word embeddings to capture the contextual information of words by considering the surrounding context of words for improved feature extraction. The pre-trained FastText and Floret word embeddings are publicly available for Urdu language which are utilized to generate feature vectors of four benchmark Urdu language datasets. These features are then used as input to train various combinations of Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), Gated Recurrent Unit (GRU), CRF, and deep learning models. The results show that our proposed approach significantly outperforms existing state-of-the-art studies on Urdu NER, achieving an F-score of up to 0.98 when using BiLSTM+GRU with Floret embeddings. Error analysis shows a low classification error rate ranging from 1.24% to 3.63% across various datasets showing the robustness of the proposed approach. The performance comparison shows that the proposed approach significantly outperforms similar existing studies.
metadata
Khan, Hikmat Ullah; Anam, Rimsha; Anwar, Muhammad Waqas; Jamal, Muhammad Hasan; Bajwa, Usama Ijaz; Diez, Isabel de la Torre; Silva Alvarado, Eduardo René; Soriano Flores, Emmanuel y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, eduardo.silva@funiber.org, emmanuel.soriano@uneatlantico.es, SIN ESPECIFICAR
(2024)
A deep learning approach for Named Entity Recognition in Urdu language.
PLOS ONE, 19 (3).
e0300725.
ISSN 1932-6203
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
Air-writing is a widely used technique for writing arbitrary characters or numbers in the air. In this study, a data collection technique was developed to collect hand motion data for Bengali air-writing, and a motion sensor-based data set was prepared. The feature set as then utilized to determine the most effective machine learning (ML) model among the existing well-known supervised machine learning models to classify Bengali characters from air-written data. Our results showed that medium Gaussian SVM had the highest accuracy (96.5%) in the classification of Bengali character from air writing data. In addition, the proposed system achieved over 81% accuracy in real-time classification. The comparison with other studies showed that the existing supervised ML models predicted the created data set more accurately than many other models that have been suggested for other languages.
metadata
Kader, Mohammed Abdul; Ullah, Muhammad Ahsan; Islam, Md Saiful; Ferriol Sánchez, Fermín; Samad, Md Abdus y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, fermin.ferriol@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
A real-time air-writing model to recognize Bengali characters.
AIMS Mathematics, 9 (3).
pp. 6668-6698.
ISSN 2473-6988
L
Tesis
Materias > Educación
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster
Cerrado
Inglés
Teaching listening comprehension is one of the most difficult tasks for English teachers and for students, because there are no rules as in grammar teaching. This study explored to what extent students enhance listening comprehension through movie segments and what their attitudes are towards this teaching tool. A total of 64 students and two English teachers were surveyed. Interviews were used to know student's positive and negative opinions towards the strategy. Clearly, using movies proved to be an effective way for students to improve their listening ability. Most learners improved listening skills and gained more than vocabulary, understood more foreign culture, felt relaxed and had fun while learning in class.
metadata
Lara Ramirez, Juan Pablo
mail
juanlararamirez04@gmail.com
(2022)
An Action Research for improving listening skills by implementing the use of movie segments in a 2nd EFL Class with BGU students at “Réplica Guayaquil” high school.
Masters thesis, SIN ESPECIFICAR.
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español La delegación es una forma legítima que tienen los Estados centralizados o seccionales de transferir capacidades jurídicas, administrativas, operacionales y de gestión en general a entidades descentralizadas del propio Estado o entes del sector privado. En el Ecuador existen varias formas de delegar competencias y gestiones financieras, administrativas y operativas a cargo de empresas estatales extranjeras, privadas nacionales o extranjeras e incluso por medio de alianzas público-privadas. Los puertos marítimos del Ecuador forman parte de los sectores estratégicos del Estado por sus condiciones de infraestructura, ubicación geopolítica y facilidades de conectividad, elementos que los hacen atractivos para los inversionistas nacionales e internacionales especializados en los negocios marítimos, situación que los transforma en aliados valiosos para el comercio internacional y el tránsito de pasajeros turísticos. La estructura jurídica fundamental que soporta la acción de concesionar o delegar áreas de sectores estratégicos del Estado ecuatoriano —en este caso los puertos marítimos— tiene sustento legal en la Constitución de la República, el Código Orgánico de la Producción Comercio e Inversiones, la Ley Orgánica de Incentivos Para Asociaciones Público Privadas, el Código Orgánico Administrativo y Ley Orgánica de la Contraloría General del Estado, entre otros cuerpos legales. El objetivo fundamental para la delegación e incluso la concesión de los puertos marítimos en el Ecuador obedece a la búsqueda de una gestión eficiente y eficaz para crear un entorno competitivo, sostenido en un ordenamiento jurídico que le permite lograr una dinámica efectiva que incentiva el comercio multilateral. El Estado ecuatoriano pretende que las ventajas comparativas y competitivas de infraestructuras y posicionamiento estratégico sirvan para generar un desarrollo sostenido basado en la capacidad de brindar servicios portuarios ágiles, seguros y con costes competitivos. metadata Loor Zambrano, Angela Annabella y Pahul Robredo, María Graciela mail SIN ESPECIFICAR (2022) Análisis del marco constitucional y normativo para la delegación de puertos marítimos en el Ecuador. MLS Law and International Politics, 1 (2).
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Emergency medical services (EMSs) face critical situations that require patient risk classification based on analytical and vital signs. We aimed to establish clustering-derived phenotypes based on prehospital analytical and vital signs that allow risk stratification. This was a prospective, multicenter, EMS-delivered, ambulance-based cohort study considering six advanced life support units, 38 basic life support units, and four tertiary hospitals in Spain. Adults with unselected acute diseases managed by the EMS and evacuated with discharge priority to emergency departments were considered between January 1, 2020, and June 30, 2023. Prehospital point-of-care testing and on-scene vital signs were used for the unsupervised machine learning method (clustering) to determine the phenotypes. Then phenotypes were compared with the primary outcome (cumulative mortality (all-cause) at 2, 7, and 30 days). A total of 7909 patients were included. The median (IQR) age was 64 (51–80) years, 41% were women, and 26% were living in rural areas. Three clusters were identified: alpha 16.2% (1281 patients), beta 28.8% (2279), and gamma 55% (4349). The mortality rates for alpha, beta and gamma at 2 days were 18.6%, 4.1%, and 0.8%, respectively; at 7 days, were 24.7%, 6.2%, and 1.7%; and at 30 days, were 33%, 10.2%, and 3.2%, respectively. Based on standard vital signs and blood test biomarkers in the prehospital scenario, three clusters were identified: alpha (high-risk), beta and gamma (medium- and low-risk, respectively). This permits the EMS system to quickly identify patients who are potentially compromised and to proactively implement the necessary interventions.
metadata
López-Izquierdo, Raúl; del Pozo Vegas, Carlos; Sanz-García, Ancor; Mayo Íscar, Agustín; Castro Villamor, Miguel A.; Silva Alvarado, Eduardo René; Gracia Villar, Santos; Dzul López, Luis Alonso; Aparicio Obregón, Silvia; Calderón Iglesias, Rubén; Soriano, Joan B. y Martín-Rodríguez, Francisco
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, eduardo.silva@funiber.org, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, silvia.aparicio@uneatlantico.es, ruben.calderon@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Clinical phenotypes and short-term outcomes based on prehospital point-of-care testing and on-scene vital signs.
npj Digital Medicine, 7 (1).
ISSN 2398-6352
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Emergency medical services (EMSs) face critical situations that require patient risk classification based on analytical and vital signs. We aimed to establish clustering-derived phenotypes based on prehospital analytical and vital signs that allow risk stratification. This was a prospective, multicenter, EMS-delivered, ambulance-based cohort study considering six advanced life support units, 38 basic life support units, and four tertiary hospitals in Spain. Adults with unselected acute diseases managed by the EMS and evacuated with discharge priority to emergency departments were considered between January 1, 2020, and June 30, 2023. Prehospital point-of-care testing and on-scene vital signs were used for the unsupervised machine learning method (clustering) to determine the phenotypes. Then phenotypes were compared with the primary outcome (cumulative mortality (all-cause) at 2, 7, and 30 days). A total of 7909 patients were included. The median (IQR) age was 64 (51–80) years, 41% were women, and 26% were living in rural areas. Three clusters were identified: alpha 16.2% (1281 patients), beta 28.8% (2279), and gamma 55% (4349). The mortality rates for alpha, beta and gamma at 2 days were 18.6%, 4.1%, and 0.8%, respectively; at 7 days, were 24.7%, 6.2%, and 1.7%; and at 30 days, were 33%, 10.2%, and 3.2%, respectively. Based on standard vital signs and blood test biomarkers in the prehospital scenario, three clusters were identified: alpha (high-risk), beta and gamma (medium- and low-risk, respectively). This permits the EMS system to quickly identify patients who are potentially compromised and to proactively implement the necessary interventions.
metadata
López-Izquierdo, Raúl; del Pozo Vegas, Carlos; Sanz-García, Ancor; Mayo Íscar, Agustín; Castro Villamor, Miguel A.; Silva Alvarado, Eduardo René; Gracia Villar, Santos; Dzul López, Luis Alonso; Aparicio Obregón, Silvia; Calderón Iglesias, Rubén; Soriano, Joan B. y Martín-Rodríguez, Francisco
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, eduardo.silva@funiber.org, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, silvia.aparicio@uneatlantico.es, ruben.calderon@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Clinical phenotypes and short-term outcomes based on prehospital point-of-care testing and on-scene vital signs.
npj Digital Medicine, 7 (1).
ISSN 2398-6352
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español El presente artículo expone parte de los hallazgos de una investigación destinada a diseñar una metodología para la elaboración de un modelo de gestión (MdG), como componente básico en la preparación y evaluación de proyectos en el ámbito del Sistema Nacional de Inversiones de Chile (SNI). La metodología utilizada fue de tipo cualitativa cuantificable. La investigación consideró el análisis de metodologías y requisitos de información para la preparación y evaluación de proyectos ex ante, la revisión de modelos en proyectos ex post, el diseño de una metodología para la elaboración de un modelo y la aplicación en un proyecto (caso), lo cual se realizó a través de entrevistas, observaciones y análisis de documentos. Los resultados obtenidos dan cuenta que las metodologías para la preparación y evaluación de proyectos de inversión pública (sociales), a diferencia de los proyectos privados, no consideran un módulo de información sobre la organización para la operación, así como tampoco los requisitos de información sectoriales. Sin embargo, los proyectos evaluados ex post revelan la importancia y utilidad de contar con un modelo ex ante para su puesta en marcha y operación ex post. Y a partir de una definición de contenidos, se diseñó una metodología para la elaboración de un modelo que permita la planificación, el seguimiento y la evaluación de un proyecto de inversión. metadata Latorre, Alex mail SIN ESPECIFICAR (2020) Diseño de un modelo de gestión en la preparación y evaluación de proyectos. Project, Design and Management, 2 (1). pp. 51-70. ISSN 26831597
Tesis Materias > Educación Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster Cerrado Inglés The present materials design project as a final product of the master’s in applied Linguistics to the Teaching of English as a Foreign Language of the UNINI-MX by the Iberoamerica Foundation (FUNIBER); It is focused on Enhancement of The Four Academic Skills on Students from English of the Centro Universitario del Litoral Pacifico during the III PAC 2021.Such project initiative arises from the interest of solving a problem of a pedagogical-didactic nature concerning the teaching-learning processes, on the part of the teachers of the area of English in its virtual mode, synthesizing this difficulty in the following question: What are the relevant didactic activities, from a qualitative approach, in the language learning processes, in the virtual mode, that English teachers should use? Likewise, it is necessary to mention that the confinement caused by the Covid-19 crisis has suddenly pushed us to move from the face-to-face to the virtual. Therefore, it is necessary to prepare to design effective activities to improve the English level of the students and at the end of the class they can reach an A2 level.The aspects contemplated in this subject design project are described below: Chapter 2 contemplates justification of academic and personal interest, which includes why this project was chosen. Chapter 3 contemplates the general and specific objectives that explain what is intended to be achieved with the design of activities or materials based on their novelty, relevance, relevance, theoretical contributions. Chapter 4 contemplates the theoretical background of the research, where the theoretical framework is visualized, that is, the set of existing theories about the advances concerning the subject under investigation (state of the art), the historical and contextual framework and among others. Chapter 5: in its Methodology of the project, where it is detailed how each of the activities were planned and the process that should have been followed. Chapter 6 Result and Discussions considers the results obtained once each activity was applied and the percentage of effectiveness in student learning; and to finish in this section of this chapter are the bibliographic references used in the preparation of the project, they can be books, magazines, articles, and other documents that were relevant to write the document; and the section of the appendixes such as: copies of activities. metadata Lopez Fuentes, Eimy Vanessa mail eimylopez11@hotmail.com (2022) Enhancement of the four academic skills on students from english class at Centro Regional Del Litoral Pacifico. Masters thesis, SIN ESPECIFICAR.
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Cerrado
Inglés
Recently, the Internet of Medical Things (IoMT) could offload healthcare services to 5 G edge computing for low latency. However, some existing works assumed altruistic patients will sacrifice Quality of Service (QoS) for the global optimum. For priority-aware and deadline-sensitive healthcare, this sufficient and simplified assumption will undermine the engagement enthusiasm, i.e., unfairness. To address this issue, we propose a long-term proportional fairness-driven 5 G edge healthcare, i.e., FairHealth. First, we establish a long-term Nash bargaining game to model the service offloading, considering the stochastic demand and dynamic environment. We then design a Lyapunov-based proportional-fairness resource scheduling algorithm, which decouples the long-term fairness problem into single-slot sub-problems, realizing a trade-off between service stability and fairness. Moreover, we propose a block-coordinate descent method to iteratively solve non-convex fair sub-problems. Simulation results show that our scheme can improve 74.44% of the fairness index (i.e., Nash product), compared with the classic global time-optimal scheme.
metadata
Lin, Xi; Wu, Jun; Bashir, Ali Kashif; Yang, Wu; Singh, Aman y AlZubi, Ahmad Ali
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR
(2022)
FairHealth: Long-Term Proportional Fairness-Driven 5G Edge Healthcare in Internet of Medical Things.
IEEE Transactions on Industrial Informatics.
pp. 1-10.
ISSN 1551-3203
Artículo
Materias > Biomedicina
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Isoflavones are a group of (poly)phenols, also defined as phytoestrogens, with chemical structures comparable with estrogen, that exert weak estrogenic effects. These phytochemical compounds have been targeted for their proven antioxidant and protective effects. Recognizing the increasing prevalence of cardiovascular diseases (CVD), there is a growing interest in understanding the potential cardiovascular benefits associated with these phytochemical compounds. Gut microbiota may play a key role in mediating the effects of isoflavones on vascular and endothelial functions, as it is directly implicated in isoflavones metabolism. The findings from randomized clinical trials indicate that isoflavone supplementation may exert putative effects on vascular biomarkers among healthy individuals, but not among patients affected by cardiometabolic disorders. These results might be explained by the enzymatic transformation to which isoflavones are subjected by the gut microbiota, suggesting that a diverse composition of the microbiota may determine the diverse bioavailability of these compounds. Specifically, the conversion of isoflavones in equol—a microbiota-derived metabolite—seems to differ between individuals. Further studies are needed to clarify the intricate molecular mechanisms behind these contrasting results.
metadata
Laudani, Samuele; Godos, Justyna; Romano, Giovanni Luca; Gozzo, Lucia; Di Domenico, Federica Martina; Dominguez Azpíroz, Irma; Martínez Díaz, Raquel; Giampieri, Francesca; Quiles, José L.; Battino, Maurizio; Drago, Filippo; Galvano, Fabio y Grosso, Giuseppe
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, irma.dominguez@unini.edu.mx, raquel.martinez@uneatlantico.es, francesca.giampieri@uneatlantico.es, jose.quiles@uneatlantico.es, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Isoflavones Effects on Vascular and Endothelial Outcomes: How Is the Gut Microbiota Involved?
Pharmaceuticals, 17 (2).
p. 236.
ISSN 1424-8247
Artículo Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español El menoscabo al derecho de trabajo ha sido un problema social en Guatemala, que ha afectado a trabajadores desde siglos pasados, fueron objeto de torturas y esclavitud, en el presente siglo la esclavitud ya no es muy notoria, gracias a la protección de derechos humanos; aun así existe abuso de patrono hacía el trabajador, no paga un salario justo, no pagar la indemnización es otro factor para demandar al patrono ante Juzgado de Trabajo, agotada la vía administrativa entra en conflicto laboral con el patrono ante un Juzgado jurisdiccional, que conoce y resuelve, basado en ley vigente, con la protección jurídica preferente, ello despierta el interés de analizar profundamente los derechos humanos, principios del derecho, que no se viole el debido proceso; las normas vigentes en materia laboral aportan elementos para el bien común de las partes, tomando el Principio de tutelaridad que asiste a todos los trabajadores basado en la C.P.R.G, 4, 44, 46, 101-117, leyes locales e internacionales, si no se aplica la justicia se ve afectada la esfera jurídica en el presente estudio se analizó al derecho comparado como instrumento legal que compara características de diferentes sistemas jurídicos que se aplican para solucionar de forma justa los problemas laborales, normas que favorecen a Guatemala: convención sobre derechos del niño, Pacto San José, convención de viena, la OIT, DUDH con similitud a derechos civiles en materia jurídica internacional para propiciar un trabajo digno, para el bien común, la armonía y la paz de la sociedad. metadata López Herrera, Josefa Eufemia mail SIN ESPECIFICAR (2023) Principio de tutelaridad protección jurídica preferente ante el menoscabo al derecho del trabajo. MLS Law and International Politics, 2 (1). ISSN 2952-248X
Artículo Materias > Psicología Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés The current study aimed to determine how attitudes towards research are related to epistemic orientation, critical thinking, and satisfaction with research courses in psychology university students. Control variables included respondents' gender, current academic degree (undergraduate or postgraduate), number of research methods courses completed, number of research projects completed, and academic score. A quantitative, cross-sectional design was used, with a non-probabilistic sample size of 137 students. Correlational findings suggest that students with high scores in critical thinking domains and empiric and rational dispositions, tend to achieve higher academic grades. Rationality and reflexive skepticism were related to the number of research projects completed by the student. While an intuitive disposition is inversely related to academic scores and the number of research courses completed. Results from a hierarchical linear regression model suggest that attitudes towards research are significantly and positively affected by students' satisfaction with research courses, empiric epistemic orientation, and critical openness. On the other hand, an intuitive epistemic orientation has significant detrimental effects on attitudes towards research. Rational epistemic orientation and skeptic reflexiveness yielded non-significant coefficients. Overall, the model containing all independent variables accounted for 47.4% of the variance in attitudinal scores; this constitutes a large effect size. Results are discussed in light of previous research and their implications for the teaching of psychology in higher education. metadata Landa-Blanco, Miguel y Cortés-Ramos, Antonio mail SIN ESPECIFICAR (2021) Psychology students' attitudes towards research: the role of critical thinking, epistemic orientation, and satisfaction with research courses. Heliyon, 7 (12). e08504. ISSN 24058440
M
Tesis
Materias > Educación
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster
Cerrado
Inglés
This Action Research Project is aimed to contribute to the production of English Speaking and Writing skills in a group of six-grade students by employing CLIL and Task-Based Science activities to catch children's interes to learn and produce the second language in an autonomous and meaningful way.This project shows four stages: 1) Diagnostic of learning needs and motivations for productive skills, 2) Designing of CLIL and task-based Science activities to reach productive skills, 3) Implementation of CLIL and task-based Science activities for online, face-to-face and hybrid classes, and 4) Evaluation of the impact and meaningful outcomes.For this Action-Research project, explanatory and exploratory methodologies were applied. The instruments to collect quantitative and qualitative informaction were designed with online applications to receive the answers of all the educative community, face-to-face, online and hybrid modalities.Furthermore, a proved compilation of Science lessons used with six-grders to improve the mentioned skills is going to be shared, rubrics and gamification for assessment samples tht have motivated students to learn and produce a second language while they are exploring their world.
metadata
Méndez Guevara, Verónica Del Carmen
mail
vero_anahi2000@yahoo.com
(2022)
An Action Reseach for Implementing CLIL and Task-Based Science Activities for Promoting the Englsih Productive Skills in a Group of Six-Grade Students at a Private International Bilingual School in Cumbayá, Ecuador.
Masters thesis, SIN ESPECIFICAR.
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
The main aim of this research is to develop an action research for designing and implementing an EFL B1 communicative and task-based material design and analyzing its impact on a group of 17-25-year-old students. Throughout the theoretical framework in the paper, you will be able to understand what Task Based Approach is. Besides, we will review the different principles of this approach, its type of materials and the specific sequence of activities it requires. Also, we will understand why it is important and what kind of advantages and disadvantages we can encounter.This project was applied in Universidad Técnica Nacional (UTN) in Costa Rica with a group of youngsters to establish how new and innovative creative activities and materials could interact with this target group and what kind of effects and data we could gather from their experience. This project used a mixed method approach. Due to the pandemic, the research was carried out virtually. Besides, questionnaires and direct observation were applied to collect information, these helped to obtain available data to explain in the results section that these materials and activities were very effective despite of working virtually. The project includes a booklet guide with innovative materials and alternative activities with their specific instructions on how to use them. This includes the plan carried out and the activities used in the research to obtain the data. Thanks to this class done useful results were gathered. In this section, we can realize that the project was effective, the materials and the activities used worked properly within the students' interaction.Communication was successful despite of the circumstances. However, it also shows that there is always room for improvement. Therefore, a series of conclusions and recommendations are stated at the end of the research. Basically, they describe that Task Based is highly effective for communication, although it requires autonomy and responsibility from students. Careful planning is a must. Materials need to be related to real life experiences. Teachers need to promote interaction and be facilitators in the process while including the four skills and making learners take risks with motivation. This is just a short summary of the project, yet you are invited to review it closely through the paper.
metadata
Madrigal Rodriguez, Steven Gerardo
mail
stevengmr11@gmail.com
(2022)
An Action Research for Designing and Implementing an EFL Communicative and Task Based -gn in a Group of 17-25-year-old Students.
Masters thesis, SIN ESPECIFICAR.
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
This action research analyses the impact of web-based individual and collaborative writing tasks in English online lessons and collects students’ perceptions about their own writing development after performing those tasks. The participants of this research are university students, who are studying and training to become school teachers, in this sense, they evaluated these types of web-based writing tasks from both perspectives, as pupils and as student teachers. The study begins with a preliminary diagnosis to develop students' language profiles and their perceptions of writing, later on, some collaborative and individual web tasks were designed and implemented during the 4-week online instruction. After this phase, qualitative and quantitative data corpus was collected to evaluate the effect of the task on students writing development. The findings will serve as a starting point for further investigations about EFL online writing.
metadata
Morales Jácome, Carmen Elena
mail
carmitamoralesj@gmail.com
(2022)
An Action Research for increasing students' engagement while implementing collaborative and individual web-based writing tasks in A2-level students (Pre-intermediate) learning EFL online.
Masters thesis, SIN ESPECIFICAR.
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The fast expansion of ICT (information and communications technology) has provided rich sources of data for the analysis, modeling, and interpretation of human mobility patterns. Many researchers have already introduced behavior-aware protocols for a better understanding of architecture and realistic modeling of behavioral characteristics, similarities, and aggregation of mobile users. We are introducing the similarity analytical framework for the mobile encountering analysis to allow for more direct integration between the physical world and cyber-based systems. In this research, we propose a method for finding the similarity behavior of users’ mobility patterns based on location and time. This research was conducted to develop a technique for producing co-occurrence matrices of users based on their similar behaviors to determine their encounters. Our approach, named SAA (similarity analysis approach), makes use of the device info i.e., IP (internet protocol) and MAC (media access control) address, providing an in-depth analysis of similarity behaviors on a daily basis. We analyzed the similarity distributions of users on different days of the week for different locations based on their real movements. The results show similar characteristics of users with common mobility behaviors based on location and time to showcase the efficacy. The results show that the proposed SAA approach is 33% more accurate in terms of recognizing the user’s similarity as compared to the existing similarity approach.
metadata
Memon, Ambreen; Kilby, Jeff; Breñosa, Jose; Martínez Espinosa, Julio César y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, SIN ESPECIFICAR
(2022)
Analysis and Implementation of Human Mobility Behavior Using Similarity Analysis Based on Co-Occurrence Matrix.
Sensors, 22 (24).
p. 9898.
ISSN 1424-8220
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The demand for cloud computing has drastically increased recently, but this paradigm has several issues due to its inherent complications, such as non-reliability, latency, lesser mobility support, and location-aware services. Fog computing can resolve these issues to some extent, yet it is still in its infancy. Despite several existing works, these works lack fault-tolerant fog computing, which necessitates further research. Fault tolerance enables the performing and provisioning of services despite failures and maintains anti-fragility and resiliency. Fog computing is highly diverse in terms of failures as compared to cloud computing and requires wide research and investigation. From this perspective, this study primarily focuses on the provision of uninterrupted services through fog computing. A framework has been designed to provide uninterrupted services while maintaining resiliency. The geographical information system (GIS) services have been deployed as a test bed which requires high computation, requires intensive resources in terms of CPU and memory, and requires low latency. Keeping different types of failures at different levels and their impacts on service failure and greater response time in mind, the framework was made anti-fragile and resilient at different levels. Experimental results indicate that during service interruption, the user state remains unaffected.
metadata
Mir, Tahira Sarwar; Liaqat, Hannan Bin; Kiren, Tayybah; Sana, Muhammad Usman; Álvarez, Roberto Marcelo; Miró Vera, Yini Airet; Pascual Barrera, Alina Eugenia y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, roberto.alvarez@uneatlantico.es, yini.miro@uneatlantico.es, alina.pascual@unini.edu.mx, SIN ESPECIFICAR
(2022)
Antifragile and Resilient Geographical Information System Service Delivery in Fog Computing.
Sensors, 22 (22).
p. 8778.
ISSN 1424-8220
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español El objetivo de esta investigación es analizar el uso de las TIC que favorecen la innovación de los procesos y los factores que inciden en la productividad de las empresas panificadoras del Municipio de Campeche, es una investigación de tipo no experimental, se corresponde con un diseño transversal y un enfoque cuantitativo, cuya población es de 135 empresas y una muestra de veinte (20); se realizó un muestreo por conveniencia toda vez que las unidades a estudiar se eligen de acuerdo a su fácil disponibilidad, esto motivado a las implicaciones existentes generadas por la pandemia del COVID-19; se elaboró un instrumento que fue validado en su contenido por expertos en gerencia y calculada su fiabilidad, fue aplicado a los dueños o gerentes de las citadas empresas. Entre las conclusiones se destacan: es necesaria la incorporación y uso de las TIC debido a que se requiere la modificación y adaptación a las nuevas tecnologías y cambios presentes en el mercado tan necesarios para la subsistencia. Los motivos que impiden la innovación están sustentados en: no tener información suficiente sobre los elementos que las conforman, costos elevados para innovar, falta de financiamiento por parte del estado y sector privado, no disponer de capital suficiente. Finalmente se evidencia una marcada influencia de los factores internos y externos que inciden en la productividad, por lo que es importante que en el futuro se estudien y analicen a profundidad. metadata Moreno Briceño, Fidel y Medina Minaya, Alberto Eliceo mail SIN ESPECIFICAR, alberto.medina@doctorado.unini.edu.mx (2023) Análisis de la innovación en los procesos y la productividad respecto al uso de TIC en las empresas panificadoras del Municipio de Campeche, México. Project Design and Management, 5 (1). ISSN 2683-1597
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Currently, multilevel inverters have been increased the number of applications in the industrial sector and renewable energy sources. Among its characteristics, the most remarkable are modular design, high performance, and low harmonic distortion in the output voltage waveform. For this paper, a single-phase Cascade H-Bridge Multilevel Inverters (CHB-MLI or CMLI) topology with independent DC sources, has been selected for the case study. Analyzing three scenarios: 5-level, 7-level, and 9-level applying the concept of the Optimized Harmonic Stepped-Waveform (OHSW) and comparing the results between the Selective Harmonic Eliminated-Pulse Width Modulation (SHE-PWM) and the Optimal Minimization of the Total Harmonic Distortion (OMTHD) are also presented. To compare the results obtained with classical and nature-inspired optimization methods, three techniques are used to solve transcendental nonlinear equations for the problem of Total Harmonic Distortion (THD) minimization: Newton Raphson (NR), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), which have been widely used for the problems of THD minimization in multilevel inverters. metadata Marín-Reyes, Manuel; Aguayo-Alquicira, Jesus y De León Aldaco, Susana Estefany mail SIN ESPECIFICAR (2020) Calculation of Optimal Switching Angles for a Multilevel Inverter Using NR, PSO, and GA- a Comparison. European Journal of Electrical Engineering, 22 (4-5). pp. 349-355. ISSN 21033641
Artículo
Materias > Biomedicina
Materias > Alimentación
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Objective: The aim of this study was to validate a direct taste perception test (TPT) and evaluate its performance in patients on dialysis.
Methods: This cross-sectional study was carried out in a tertiary-care hospital. A TPT was validated on 112 healthy subjects and applied on 43 patients on hemodialysis and 32 patients on peritoneal dialysis. All participants were presented a 10-mL sample to identify and rate intensity of primary tastes: sweet (sucrose 2%), sour (citric acid 0.1%), bitter (caffeine 0.06%), salty (sodium chloride 0.5%), and umami (sodium glutamate 0.25%). The internal consistency and repeatability of TPT was assessed by Cronbach's alpha and intraclass correlation coefficient. Chi-square and Mann-Whitney U tests were used to compare groups.
Results: TPT had Cronbach's alpha of 0.77. Intraclass correlation coefficient was 0.74 for sweet, P < .0001; 0.57 for salty, P = .001; 0.62 for sour, P < .0001; 0.78 for bitter, P < .0001; and 0.76 for umami, P < .0001. Compared with controls, patients on peritoneal dialysis were less able to identify sweet and umami tastes (P < .05) and marginally (P = .06) sour taste, whereas patients on hemodialysis were marginally (P = .06) less able to identify sweet and salty tastes. Bitter was not differently identified between groups. According to the visual analog scale (0-10), all patients on dialysis perceived sour taste less intensely than control subjects (P < .05).
Conclusions: This TPT for patients on dialysis had adequate reliability to identify five primary tastes in a clinical setting. Except for bitter taste, perception of all the primary tastes was altered in patients on dialysis compared with control subjects. A broader use of this test would help identify taste alterations and implement strategies for malnutrition.
metadata
Márquez-Herrera, Roxana M.; Núñez-Murillo, Gabriela K.; Ruíz-Gurrola, Claudia G.; Gómez-García, Erika F.; Orozco-González, Claudia N.; Cortes-Sanabria, Laura; Cueto-Manzano, Alfonso M. y Rojas-Campos, Enrique
mail
SIN ESPECIFICAR
(2020)
Clinical Taste Perception Test for Patients With End-Stage Kidney Disease on Dialysis.
Journal of Renal Nutrition, 30 (1).
pp. 79-84.
ISSN 10512276
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The authors have requested to update the original publication of this article.
Duplicate text in the second and third paragraphs of page 5 should be deleted.
Acknowledgments section should be removed.
The original article has been corrected.
metadata
Montano, Isabel Herrera; Lafuente, Elena Presencio; Breñosa, Jose; Ortega-Mansilla, Arturo; Díez, Isabel de la Torre y Río-Solá, María Lourdes Del
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, josemanuel.brenosa@uneatlantico.es, arturo.ortega@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Correction to: Systematic Review of Telemedicine and eHealth Systems Applied to Vascular Surgery.
Journal of Medical Systems, 47 (1).
ISSN 1573-689X
Artículo
Materias > Biomedicina
Materias > Alimentación
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The authors regret the incorrect publication of the actual affiliation for the author José Ramos-Vivas in the original article. The corrected affiliation is provided below:
Luis Monzón-Atienzaa, Jimena Bravoa, Álvaro Fernández-Monteroa, Ives Charlie-Silvab, Daniel Monteroa, José Ramos-Vivasa,d,e, Jorge Galindo-Villegasc,*, Félix Acostaa
aGrupo de Investigaci'on en Acuicultura (GIA), Instituto Ecoaqua, Universidad de Las Palmas de Gran Canaria, Spain
bDepartment of Pharmacology, Institute of Biomedical Sciences, University of Sao Paulo, SP, Brazil
cFaculty of Biosciences and Aquaculture, Nord University, Bodø, Norway
dResearch Group on Foods, Nutritional Biochemistry and Health, Universidad Europea del Atlántico, 39011 Santander, Spain
eDepartment of Project Management, Universidad Internacional Iberoamericana, Campeche 24560, Mexico
The authors would like to apologise for any inconvenience caused.
metadata
Monzón-Atienza, Luis; Bravo, Jimena; Fernández-Montero, Álvaro; Charlie-Silva, Ives; Montero, Daniel; Ramos Vivas, Jose; Galindo-Villegas, Jorge y Acosta, Félix
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, jose.ramos@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Corrigendum to “Dietary supplementation of Bacillus velezensis improves Vibrio anguillarum clearance in European sea bass by activating essential innate immune mechanisms” [Fish Shellfish Immunol. 124 (2022) 244–253].
Fish & Shellfish Immunology.
ISSN 10504648
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Malaria is an extremely malignant disease and is caused by the bites of infected female mosquitoes. This disease is not only infectious among humans, but among animals as well. Malaria causes mild symptoms like fever, headache, sweating and vomiting, and muscle discomfort; severe symptoms include coma, seizures, and kidney failure. The timely identification of malaria parasites is a challenging and chaotic endeavor for health staff. An expert technician examines the schematic blood smears of infected red blood cells through a microscope. The conventional methods for identifying malaria are not efficient. Machine learning approaches are effective for simple classification challenges but not for complex tasks. Furthermore, machine learning involves rigorous feature engineering to train the model and detect patterns in the features. On the other hand, deep learning works well with complex tasks and automatically extracts low and high-level features from the images to detect disease. In this paper, EfficientNet, a deep learning-based approach for detecting Malaria, is proposed that uses red blood cell images. Experiments are carried out and performance comparison is made with pre-trained deep learning models. In addition, k-fold cross-validation is also used to substantiate the results of the proposed approach. Experiments show that the proposed approach is 97.57% accurate in detecting Malaria from red blood cell images and can be beneficial practically for medical healthcare staff.
metadata
Mujahid, Muhammad; Rustam, Furqan; Shafique, Rahman; Caro Montero, Elizabeth; Silva Alvarado, Eduardo René; de la Torre Diez, Isabel y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, elizabeth.caro@uneatlantico.es, eduardo.silva@funiber.org, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Efficient deep learning-based approach for malaria detection using red blood cell smears.
Scientific Reports, 14 (1).
ISSN 2045-2322
Artículo Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Introduction Resentment towards the Chinese population was perceived during the first months of the pandemic because the pandemic/disease started in that country. Objective To determine the factors associated with the perception of resentment towards the Chinese in Latin America during the first wave of the COVID-19 pandemic. Methodology Analytical cross-sectional study conducted during the second semester of the pandemic in more than a dozen countries. Four questions were asked about the perception of resentment towards the Chinese (Cronbach's Alpha: 0.88); those with the highest scores on the sum of the four questions were considered to have "more resentment towards the Chinese," and descriptive and analytical statistics were obtained. Results Of the 7721 respondents, in the multivariate analysis, it was found that there was a difference according to the country; compared to Peru, those who had more resentment towards the Chinese were those residing in Paraguay (aPR: 1.29; 95%CI: 1.17–1.42; p-value < 0.001) and Bolivia (aPR: 1.52; 95%CI: 1.37–1.68; p-value < 0.001), while Chile (aPR: 0.78; 95%CI: 0.69–0.88; p-value < 0.001) had less resentment: 0.69–0.88; p-value < 0.001), Mexico (aPR: 0.68; 95%CI: 0.57–0.80; p-value < 0.001), Panama (aPR: 0.71; 95%CI: 0.59–0.86; p-value < 0.001) and Costa Rica (aPR: 0.64; 95%CI: 0.49–0.85; p-value = 0.002). Discussion There was a significant difference in resentment for each country. metadata Mejia, Christian R.; Ascarza, Gianpool; Alvarez-Risco, Aldo; Misayauri, Jean; Arias-Chavez, Dennis; Vilela-Estrada, Martin A.; Serna-Alarcón, Victor; Requena, Tatiana; Ubillus, Milward; Del-Aguila-Arcentales, Shyla; Davies, Neal M. y Yáñez, Jaime A. mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, jaime.yanez@unini.edu.mx (2024) Factors associated with the perception of resentment towards the Chinese in Latin America during the first wave of the COVID-19 pandemic. BMC Public Health, 24 (1). ISSN 1471-2458
Artículo Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Esta investigación describe la gestión de herramientas de Inteligencia de Negocios para evaluar el entorno productivo de una empresa comercializadora industrial de Ecuador, en específico, dentro de la categoría comercial de inocuidad. El estudio fue de tipo descriptivo y evaluativo con la presentación de un diseño no-experimental y de corte longitudinal. De una muestra censal de 24 individuos (asesores comerciales, técnicos y directivos), se obtuvo una data mediante la observación directa y la aplicación de una encuesta de preguntas cerradas tipo dicotómicas, con validez de contenido mediante juicio de expertos y registro de buen nivel de confiabilidad (α = 0,91; p < 0,05), cuyo análisis general se ejecutó mediante el método hipotético-deductivo. Los resultados reflejaron que solo el 58% de las intenciones comerciales se concretaron en ventas exitosas y, de estas últimas, el 70% precisó al menos de dos visitas a las instalaciones de clientes. Adicionalmente, solo el 11% de los reclamos correspondieron a las áreas evaluadas (logística). Por la Inteligencia de Negocios pudo diagnosticarse que las no conformidades principales denotaron interrupciones en las actividades transversales de la compañía, producto de la falta de procesos establecidos, indicadores de gestión y desempeño, igualmente por la carencia de herramientas tecnológicas adecuadas. Se concluyó que la empresa amerita de un sistema orientado hacia la optimización de la categoría comercial de inocuidad, los procesos administrativos, operacionales y de mejora continua, con el fin de garantizar una mayor sostenibilidad económica. metadata Malavé-Figueroa, Adelso Nikolai y Arízaga Collantes, Ligia Estefanía mail Adelso.malave@unini.edu.mx, SIN ESPECIFICAR (2022) Gestión de herramientas de inteligencia de negocios para el diagnóstico de la categoría comercial de inocuidad en un entorno empresarial ecuatoriano. Project Design and Management, 4 (2). ISSN 2683-1597
Artículo Materias > Psicología Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Las intervenciones basadas en Mindfulness cada vez son más utilizadas para intervenir en estrés, ansiedad o depresión; sin embargo, para trastorno mental grave aún se requiere de más investigación. El objetivo de este estudio es comprobar la eficacia de un programa de Mindfulness adaptado para enfermedad mental, sobre la ansiedad, depresión y calidad de vida de personas diagnosticadas de trastorno mental grave. Para comprobar su eficacia, se reclutó una muestra de 26 usuarios del Centro de Rehabilitación Psicosocial Padre Menni de Torrelavega, divididos en 2 grupos, 13 en grupo control, y 13 en grupo experimental. Se procedió al estudio recogiendo medidas en dos momentos diferentes, pretest y postest, a través de los instrumentos STAI, BDI y WHOQOL-BREF para medir ansiedad, depresión y calidad de vida, respectivamente. Se comprobó que la muestra de ambos grupos pertenecía a la misma población, y a través del análisis de varianza con medidas repetidas ANOVA, los resultados demostraron pequeñas diferencias estadísticamente significativas en ansiedad/rasgo y depresión, que sin embargo no fue así en la medición pre y post de las variables ansiedad/estado y calidad de vida, concluyendo finalmente que el programa de intervención atendió de manera parcial al objetivo de reducir la sintomatología más común de la enfermedad mental grave metadata Martino Becerril, Iciar mail SIN ESPECIFICAR (2020) Implementación de programas basados en Mindfulness con pacientes con enfermedad mental del centro de rehabilitación psicosocial Padre Menni de Torrelavega. MLS Psychology Research, 3 (2). pp. 57-72. ISSN 26055295
Artículo
Materias > Ciencias Sociales
Materias > Ingeniería
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
Energy is a crucial element for human needs today. Traditional systems of energy generation have represented a problem in terms of their costs, their impact on the environment, and their impact on community life. Therefore, the search for clean and renewable energy sources that meet the needs of contemporary society becomes increasingly essential in the search for alternatives related to energy sources. The photovoltaic energy generation system explores the solar irradiation, making it possible to generate and store energy. This system finds good conditions for implementation in Brazil in terms of climatic characteristics, but investments and public policies that encourage and favor this process are still needed. This study aimed to identify how the deployment of photovoltaic mini-generation power plant in a federal university, the Federal University of Paraná (UFPR), can contribute to the university community in relation to cost reduction and environmental preservation. The methodology used was descriptive-exploratory, qualitative, through which an open questionnaire and a semi-structured interview were carried out, guided by the theme. After analyzing the data, the conclusion was that the system can bring benefits in the long term and that most of the interviewees consider Brazil's great potential in expanding the exploration of other sources of energy, besides hydroelectric, which, besides being costly, brings fewer advantages related to the environmental and social contexts.
metadata
Miura, Augusto Takashi; Pereira, Vilmar Alves y Florencio da Silva, Rodrigo
mail
SIN ESPECIFICAR, vilmar.alves@unini.edu.mx, SIN ESPECIFICAR
(2022)
Implementation of photovoltaic energy, sustainability, economic and social development in a Higher Education Institution in Brazil.
Latin American Journal of Development, 4 (4).
pp. 1514-1532.
ISSN 2674-9297
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The present technological era significantly makes use of Internet-of-Things (IoT) devices for offering and implementing healthcare services. Post COVID-19, the future of the healthcare system is highly reliant upon the inculcation of Artificial-Intelligence (AI) mechanisms in its day-to-day procedures, and this is realized in its implementation using sensor-enabled smart and intelligent IoT devices for providing extensive care to patients relative to the symmetric concept. The offerings of such AI-enabled services include handling the huge amount of data processed and sensed by smart medical sensors without compromising the performance parameters, such as the response time, latency, availability, cost and processing time. This has resulted in a need to balance the load of the smart operational devices to avoid any failure of responsiveness. Thus, in this paper, a fog-based framework is proposed that can balance the load among fog nodes for handling the challenging communication and processing requirements of intelligent real-time applications.
metadata
Malik, Swati; Gupta, Kamali; Gupta, Deepali; Singh, Aman; Ibrahim, Muhammad; Ortega-Mansilla, Arturo; Goyal, Nitin y Hamam, Habib
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, arturo.ortega@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Intelligent Load-Balancing Framework for Fog-Enabled Communication in Healthcare.
Electronics, 11 (4).
p. 566.
ISSN 2079-9292
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
5G has been launched in a few countries of the world, so now all focus shifted towards the development of future 6G networks. 5G has connected all aspects of society. Ubiquitous connectivity has opened the doors for more data sharing. Although 5G is providing low latency, higher data rates, and high-speed yet there are some security-related vulnerabilities. Those security issues need to be mitigated for securing 6G networks from existing challenges. Classical cryptography will not remain enough for securing the 6G network. As all classical cryptography can be disabled with the help of quantum mechanics. Therefore, in the place of traditional security solutions, in this article, we have reviewed all the existing quantum solutions of 5G existing security issues to mitigate them and secure 6G in a Future Quantum World.
metadata
Mangla, Cherry; Rani, Shalli; Faseeh Qureshi, Nawab Muhammad y Singh, Aman
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es
(2023)
Mitigating 5G security challenges for next-gen industry using quantum computing.
Journal of King Saud University - Computer and Information Sciences.
ISSN 13191578
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Pneumonia is one of the leading causes of death in both infants and elderly people, with approximately 4 million deaths each year. It may be a virus, bacterial, or fungal, depending on the contagious pathogen that damages the lung’s tiny air sacs (alveoli). Patients with underlying disorders such as asthma, a weakened immune system, hospitalized babies, and older persons on ventilators are all at risk, particularly if pneumonia is not detected early. Despite the existing approaches for its diagnosis, low accuracy and efficiency require further research for more accurate systems. This study is a similar endeavor for the detection of pneumonia by the use of X-ray images. The dataset is preprocessed to make it suitable for transfer learning tasks. Different pre-trained convolutional neural network (CNN) variants are utilized, including VGG16, Inception-v3, and ResNet50. Ensembles are made by incorporating CNN with Inception-V3, VGG-16, and ResNet50. Besides the common evaluation metrics, the performance of the pre-trained and ensemble deep learning models is measured with Cohen’s kappa as well as the area under the curve (AUC). Experimental results show that Inception-V3 with CNN attained the highest accuracy and recall score of 99.29% and 99.73%, respectively
metadata
Mujahid, Muhammad; Rustam, Furqan; Álvarez, Roberto Marcelo; Vidal Mazón, Juan Luis; Díez, Isabel de la Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, roberto.alvarez@uneatlantico.es, juanluis.vidal@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Pneumonia Classification from X-ray Images with Inception-V3 and Convolutional Neural Network.
Diagnostics, 12 (5).
p. 1280.
ISSN 2075-4418
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Background: Nowadays, there is no gold standard score for prehospital sepsis and sepsis-related mortality identification. The aim of the present study was to analyze the performance of qSOFA, NEWS2 and mSOFA as sepsis predictors in patients with infection-suspected in prehospital care. The second objective is to study the predictive ability of the aforementioned scores in septic-shock and in-hospital mortality.
Methods: Prospective, ambulance-based, and multicenter cohort study, developed by the emergency medical services, among patients (n = 535) with suspected infection transferred by ambulance with high-priority to the emergency department (ED). The study enrolled 40 ambulances and 4 ED in Spain between 1 January 2020, and 30 September 2021. All the variables used in the scores, in addition to socio-demographic data, standard vital signs, prehospital analytical parameters (glucose, lactate, and creatinine) were collected. For the evaluation of the scores, the discriminative power, calibration curve and decision curve analysis (DCA) were used.
Results: The mSOFA outperformed the other two scores for mortality, presenting the following AUCs: 0.877 (95%CI 0.841–0.913), 0.761 (95%CI 0.706–0.816), 0.731 (95%CI 0.674–0.788), for mSOFA, NEWS, and qSOFA, respectively. No differences were found for sepsis nor septic shock, but mSOFA’s AUCs was higher than the one of the other two scores. The calibration curve and DCA presented similar results.
Conclusion: The use of mSOFA could provide and extra insight regarding the short-term mortality and sepsis diagnostic, backing its recommendation in the prehospital scenario.
metadata
Melero-Guijarro, Laura; Sanz-García, Ancor; Martín-Rodríguez, Francisco; Lipari, Vivian; Mazas Pérez-Oleaga, Cristina; Carvajal-Altamiranda, Stefanía; Martínez López, Nohora Milena; Dominguez Azpíroz, Irma; Castro Villamor, Miguel A.; Sánchez Soberón, Irene y López-Izquierdo, Raúl
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, vivian.lipari@uneatlantico.es, cristina.mazas@uneatlantico.es, stefania.carvajal@uneatlantico.es, nohora.martinez@uneatlantico.es, irma.dominguez@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Prehospital qSOFA, mSOFA, and NEWS2 performance for sepsis prediction: A prospective, multi-center, cohort study.
Frontiers in Medicine, 10.
ISSN 2296-858X
Artículo
Materias > Educación física y el deporte
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
(1) Background: The increasing life expectancy brings an increase in geriatric syndromes, specifically frailty. The literature shows that exercise is a key to preventing, or even reversing, frailty in community-dwelling populations. The main objective is to demonstrate how an intervention based on multicomponent exercise produces an improvement in frailty and pre-frailty in a community-dwelling population. (2) Methods: a prospective observational study of a multicomponent exercise program for geriatric revitalization with people aged over 65 holding Barthel Index scores equal to, or beyond, 90. The program was developed over 30 weeks, three times a week, in sessions lasting 45–50 min each. Frailty levels were registered by the Short Physical Performance Battery, FRAIL Questionnaire Screening Tool, and Timed “Up & Go” at the beginning of the program, 30 weeks later (at the end of the program), and following 13 weeks without training; (3) Results: 360 participants completed the program; a greater risk of frailty was found before the program started among older women living in urban areas, with a more elevated fat percentage, more baseline pathologies, and wider baseline medication use. Furthermore, heterogeneous results were observed both in training periods and in periods without physical activity. However, they are consistent over time and show improvement after training. They show a good correlation between TUG and SPPB; (4) Conclusions: A thirty-week multicomponent exercise program improves frailty and pre-frailty status in a community-dwelling population with no functional decline. Nevertheless, a lack of homogeneity is evident among the various tools used for measuring frailty over training periods and inactivity periods.
metadata
Morales-Sánchez, Almudena; Calvo Arenillas, José Ignacio; Gutiérrez Palmero, María José; Martín-Conty, José L.; Polonio-López, Begoña; Dzul Lopez, Luis Alonso; Mordillo-Mateos, Laura; Bernal-Jiménez, Juan José; Conty-Serrano, Rosa; Torres-Falguera, Francisca; Martínez Cano, Alfonso y Durantez-Fernández, Carlos
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, luis.dzul@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
A Prospective Observational Study of Frailty in Geriatric Revitalization Aimed at Community-Dwelling Elderly.
Journal of Clinical Medicine, 13 (9).
p. 2514.
ISSN 2077-0383
Artículo Materias > Psicología Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés The main objective of this study was to estimate the psychometric properties of the Emotional Fatigue Scale (ECE) in a sample of 1308 Chilean university students and confirm the unifactorial structure of the scale. Exploratory and confirmatory factor analyses were carried out. The ECE assessment had an internal consistency of 0.893 (Cronbach’s Alpha). An exploratory factor analysis with Varimax rotation and a confirmatory analysis were performed, obtaining the factor that explains 52.3% of the variance. The results indicated that the ECE has adequate psychometric properties for use with higher education students in Chile. The ECE scale has good psychometric properties to be applied in the Chilean university context. Its usage may be very relevant to contribute to higher education institutions to emphasize students’ mental health and prevent possible severe pathologies in future professionals. It is suggested to use the ECE scale together with the EES-Int, which is the only interpretation table for this instrument. metadata Martínez-Líbano, Jonathan; Yeomans, María-Mercedes y Oyanedel, Juan-Carlos mail SIN ESPECIFICAR (2022) Psychometric Properties of the Emotional Exhaustion Scale (ECE) in Chilean Higher Education Students. European Journal of Investigation in Health, Psychology and Education, 12 (1). pp. 50-60. ISSN 2254-9625
Artículo Materias > Alimentación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés The aim of the present study was to develop and validate a test to evaluate dietitian's clinical competence (CC) about nutritional care in patients with early chronic kidney disease (CKD). The study was conducted through five steps: (1) CC and its dimensions were defined; (2) test items were elaborated, and choice of response format and scoring system was selected; (3) content and face validity were established; (4) test was subjected to a pilot test and those items with inadequate performance were removed; (5) criterion validity and internal consistency for final validation were established. A 120-items test was developed and applied to 207 dietitians for validation. Dietitians with previous CKD training obtained higher scores than those with no training, confirming the test validity criterion. According to item analysis, Cronbach's α was 0⋅85, difficulty index 0⋅61 ± 0⋅22, discrimination index 0⋅26 ± 0⋅15 and inter-item correlation 0⋅19 ± 0⋅11, displaying adequate internal consistency. metadata Márquez-Herrera, Roxana M.; Cortés-Sanabria, Laura; Cueto-Manzano, Alfonso M.; Martínez-Ramírez, Héctor R.; Rojas-Campos, Enrique; Orozco González, Nelly y González-Palacios, Aaron mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, nelly.orozco@unini.edu.mx, SIN ESPECIFICAR (2022) Reliability and validity of a clinical competence test for dietitians caring patients with early chronic kidney disease. Journal of Nutritional Science, 11. ISSN 2048-6790
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Technology’s expansion has contributed to the rise in popularity of social media platforms. Twitter is one of the leading social media platforms that people use to share their opinions. Such opinions, sometimes, may contain threatening text, deliberately or non-deliberately, which can be disturbing for other users. Consequently, the detection of threatening content on social media is an important task. Contrary to high-resource languages like English, Dutch, and others that have several such approaches, the low-resource Urdu language does not have such a luxury. Therefore, this study presents an intelligent threatening language detection for the Urdu language. A stacking model is proposed that uses an extra tree (ET) classifier and Bayes theorem-based Bernoulli Naive Bayes (BNB) as the based learners while logistic regression (LR) is employed as the meta learner. A performance analysis is carried out by deploying a support vector classifier, ET, LR, BNB, fully connected network, convolutional neural network, long short-term memory, and gated recurrent unit. Experimental results indicate that the stacked model performs better than both machine learning and deep learning models. With 74.01% accuracy, 70.84% precision, 75.65% recall, and 73.99% F1 score, the model outperforms the existing benchmark study.
metadata
Mehmood, Aneela; Farooq, Muhammad Shoaib; Naseem, Ansar; Rustam, Furqan; Gracia Villar, Mónica; Rodríguez Velasco, Carmen Lilí y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, monica.gracia@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR
(2022)
Threatening URDU Language Detection from Tweets Using Machine Learning.
Applied Sciences, 12 (20).
p. 10342.
ISSN 2076-3417
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español El articulo describe los resultados de la transferencia de conocimiento del Grupo Suez, a partir de las soluciones de mejoramiento para eliminar o mitigar las situaciones conflictivas o problemáticas, los riesgos u oportunidades en los procesos e indicadores estratégicos de Aguas de Cartagena S.A. E.S.P. – Acuacar, pero a su vez revisa el estado del arte en conexión a la cesión del discernimiento corporativo en los últimos 10 años, lo que permite configurar la hipótesis: la transferencia de conocimiento mejora el rendimiento corporativo. Él análisis se realizó desde un enfoque cualicuantitativo sustentado en el análisis documental y el paradigma positivista. Se revisó también la metodología propia de registro de entrega del conocimiento de ACUACAR con lo que se pudo construir su síntesis en el periodo 2019 al igual que se utilizó la técnica de análisis de la varianza para demostrar el supuesto señalado. El diseño exploratorio, descriptivo y longitudinal ad hoc se fundamentó en la revisión documental, la observación, la aplicación de instrumentos de recogida de datos y entrevistas al equipo directivo de Aguas de Cartagena S.A. Se encontró que el conocimiento transmitido a través de métodos, procedimientos y tecnologías ejerce influencia positiva en el rendimiento corporativo de ACUACAR. En conclusión, se corrobora la tesis sobre que la cesión de conocimientos despliega influencia determinante en la mejora del rendimiento empresarial de ACUACAR. metadata Mendoza Betin, Javier Alfonso mail SIN ESPECIFICAR (2021) Transferencia de conocimiento: el caso del grupo Suez y Aguas de Cartagena SAESP “Acuacar”. Project Design and Management, 3 (2). pp. 75-98. ISSN 2683-1597
Artículo
Materias > Ingeniería
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Docencia > Trabajos finales de grado
Abierto
Inglés
Power Quality (PQ) has become a significant issue in power networks. Power quality disturbances must be precisely and appropriately identified. This activity involves identifying, classifying, and mitigating power quality problems. A case study of the Awada industrial zone in Ethiopia is taken into consideration to show the practical applicability of the proposed work. It is found that the current harmonic distortion levels exceed the restrictions with a maximum percentage Total Harmonic Distortion of Current (THDI) value of up to 23.09%. The signal processing technique, i.e., Stockwell Transform (ST) is utilized for the identification of power quality issues, and it covers the most important and common power quality issues. The Support Vector Machine (SVM) method is used to categorize power quality issues, which enhances the classification procedure. The ST scored better in terms of accuracy than the Wavelet Transform (WT), Fourier Transform (FT), and Hilbert Transform (HT), obtaining 97.1%, as compared to 91.08%, 88.91%, and 86.8%, respectively. The maximum classification accuracy of SVM was 98.3%. To lower the current level of harmonic distortion in the industrial sector, a Distribution Static Compensator (D-STATCOM) is developed in the current control mode. To evaluate the performance of the D-STATCOM, the performance of the distribution network with and without D-STATCOM is simulated. The simulation results show that THDI is reduced to 4.36% when the suggested D-STATCOM is applied in the system.
metadata
Mengistu, Epaphros; Khan, Baseem; Qasaymeh, Yazeed; Alghamdi, Ali S.; Zubair, Muhammad; Awan, Ahmed Bilal; Ashiq, Muhammad Gul Bahar; Ali, Samia Gharib y Mazas Pérez-Oleaga, Cristina
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, cristina.mazas@uneatlantico.es
(2023)
Utilization of Stockwell Transform, Support Vector Machine and D-STATCOM for the Identification, Classification and Mitigation of Power Quality Problems.
Sustainability, 15 (7).
p. 6007.
ISSN 2071-1050
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Berries are a relevant source of micronutrients and nonessential phytochemicals, such as polyphenol compounds, that play a synergistic and cumulative role in human health promotion. Several systematic analyses showed that berry phenolics are able to detoxify reactive oxygen and nitrogen species, blocking their production, to intervene in the cell cycle, participating in the transduction and expression of genes involved in apoptosis, and to repair oxidative DNA damage. As a consequence, the improvement of the nutritional quality of berries has become a new quality target of breeding and biotechnological strategies, to control or to increase the content of specific health-related compounds in fruits. This work reviews, on the basis of the in vitro and in vivo evidence, the main berries' phytochemical compounds and their possible mechanisms of action on pathways involved in several type of diseases, with particular attention to cancer, inflammation, neurodegeneration, diabetes and cardiovascular diseases. © 2015 Society of Chemical Industry
metadata
Mazzoni, Luca; Perez-Lopez, Patricia; Giampieri, Francesca; Alvarez-Suarez, José M.; Gasparrini, Massimiliano; Forbes-Hernandez, Tamara Y.; Quiles, José L.; Mezzetti, Bruno y Battino, Maurizio
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2015)
The genetic aspects of berries: from field to health.
Journal of the Science of Food and Agriculture, 96 (2).
pp. 365-371.
ISSN 00225142
N
Artículo
Materias > Biomedicina
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Alzheimer's is a chronic degenerative disease of the central nervous system considered the leading cause of dementia in the world. It is characterized by two etiopathological events related to oxidative stress: the aggregation of β-amyloid peptide and the formation of neurofibrillary tangles of hyperphosphorylated Tau protein in the brain. The incidence of this disease increases with age and has been associated with inadequate lifestyles. Some natural compounds have been shown to improve the hallmarks of the disease. However, despite its potential, there is no scientific evidence about Manuka honey (MH) in this regard. In the present work we evaluated the effect of MH on the toxicity induced by Aβ aggregation and Tau in a Caenorhabditis elegans model. Our results demonstrated that MH was able to improve indicators of oxidative stress and delayed Aβ-induced paralysis in the AD model CL4176 through HSP-16.2 and SKN-1/NRF2 pathways. Nevertheless, its sugar content impaired the indicators of locomotion (an indicator of tau neurotoxicity) in both the transgenic strain BR5706 and in the wild-type N2 worms.
metadata
Navarro-Hortal, María D.; Romero-Márquez, Jose M.; Muñoz-Ollero, Pedro; Jiménez-Trigo, Victoria; Esteban-Muñoz, Adelaida; Tutusaus, Kilian; Giampieri, Francesca; Battino, Maurizio; Sánchez-González, Cristina; Rivas-García, Lorenzo; Llopis, Juan; Forbes-Hernández, Tamara Y. y Quiles, José L.
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, kilian.tutusaus@uneatlantico.es, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, jose.quiles@uneatlantico.es
(2022)
Amyloid β-but not Tau-induced neurotoxicity is suppressed by Manuka honey via HSP-16.2 and SKN-1/Nrf2 pathways in an in vivo model of Alzheimer's disease.
Food & Function.
ISSN 2042-6496
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Broccoli has gained popularity as a highly consumed vegetable due to its nutritional and health properties. This study aimed to evaluate the composition profile and the antioxidant capacity of a hydrophilic extract derived from broccoli byproducts, as well as its influence on redox biology, Alzheimer’s disease markers, and aging in the Caenorhabditis elegans model. The presence of glucosinolate was observed and antioxidant capacity was demonstrated both in vitro and in vivo. The in vitro acetylcholinesterase inhibitory capacity was quantified, and the treatment ameliorated the amyloid-β- and tau-induced proteotoxicity in transgenic strains via SOD-3 and SKN-1, respectively, and HSP-16.2 for both parameters. Furthermore, a preliminary study on aging indicated that the extract effectively reduced reactive oxygen species levels in aged worms and extended their lifespan. Utilizing broccoli byproducts for nutraceutical or functional foods could manage vegetable processing waste, enhancing productivity and sustainability while providing significant health benefits.
metadata
Navarro-Hortal, María D.; Romero-Márquez, Jose M.; López-Bascón, M. Asunción; Sánchez-González, Cristina; Xiao, Jianbo; Sumalla Cano, Sandra; Battino, Maurizio; Forbes-Hernande, Tamara Y. y Quiles, José L.
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, sandra.sumalla@uneatlantico.es, maurizio.battino@uneatlantico.es, tamara.forbes@unini.edu.mx, jose.quiles@uneatlantico.es
(2024)
In Vitro and In Vivo Insights into a Broccoli Byproduct as a Healthy Ingredient for the Management of Alzheimer’s Disease and Aging through Redox Biology.
Journal of Agricultural and Food Chemistry, 72 (10).
pp. 5197-5211.
ISSN 0021-8561
Tesis
Materias > Educación
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster
Cerrado
Inglés
The problematic generated by the overuse of Spanish in the English as a Foreign Language classroom focused on English as a Foreign Language students at superior sublevel from public schools in Ecuador is reviewed in this research. This work was developed by providing writing and speaking assignments to selected participants as well as by conducting surveys to students and to all English teachers from this sublevel. The present investigation process was done in order to find the causes of the overuse of Spanish by means of a correlation between a bibliographic and camp work. Thus, a better English fluency is intended to be reached by avoiding practices such as using Spanish or thinking in Spanish first instead of using English within the learning context.
metadata
Núñez Pesantez, Milton Armando
mail
armando-tom@hotmail.com
(2022)
A research on the overuse of Spanish in the EFL classroom focused on EFL students at superior sublevel From Humberto Vacas Gómez school in Ecuador.
Masters thesis, SIN ESPECIFICAR.
O
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
In this master’s final project are presented the research-action project results in which it has been tried to implement “An Action Research for implementing reading activities and strategies in the 1101 class at Nuestra Señora de Los Dolores School, in Manare Villanueva, Casanare, Colombia”. It starts with the identification of the student’s reading needs I order to propose a variety of activities and strategies that help them to acquire a better comprehension and increasing their vocabulary as well as getting good marks in the application of the institutional and external tests. To achieve this objective, it was essential to take in consideration the theoretical contributions of studies by important authors and its respective analysis on it for the development of an investigation with qualitative methodology. Data collection was done through several qualitative techniques for the students such as: a survey, application of a pre-test and a post-test, an interview and the observation in each class. The more relevant results show that the applied activities and strategies were useful and in someway, was given the improvement of the reading skills in the students of eleventh grade and the marks they got as in the internal as external tests, however as teachers must continue motivating and advising our students about the importance of the knowledge and the study of this interesting subject as is English language.
metadata
Oliveros Quintana, Yury Paola
mail
teacheryurypao@hotmail.com
(2022)
An Action Research for implementing reading activities and strategies in the 1101 class at Nuestra Señora de Los Dolores School, in Manare Villanueva, Casanare, Colombia.
Masters thesis, SIN ESPECIFICAR.
Artículo
Materias > Educación
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés, Español
Los programas educativos cada vez más se inclinan a la potenciación de valores que favorezcan el desarrollo integral de los educandos, para ello se implementan diversas fórmulas que pretenden desde lo metodológico ajustarse a las exigencias sociales, educativas y curriculares. En este acercamiento a la formación del Bachiller Ecuatoriano, se analizan sus principios legales, lineamientos curriculares y estándares de calidad educativa enfocado al cumplimiento del perfil de salida del bachillerato, así como la percepción de estos por parte de estudiantes y docentes de la Unidad Educativa del Milenio Manuel J. Calle de la ciudad de Cuenca, a partir de aquí se propone una estrategia de mejora con el uso del Método de Aprendizaje Basado en Proyectos (ABP), aplicada en una muestra de 92 estudiantes del 2do año del Bachillerato General Unificado (BGU), quienes cursaron el Programa de Participación Estudiantil (PPE), específicamente el PPE (2017-2018), cuyos resultados evidencian que el Método ABP empleado en el PPE caso de estudio contribuye significativamente a elevar la calidad del Perfil de Salida del Bachiller (PSB) por medio del desarrollo de habilidades para la vida. El Método de Aprendizaje Basado en Proyectos ABP es una alternativa adecuada para elevar el proceso formativo del país, a la vez facilita la convivencia armónica en el marco escolar para quienes la utilizan directa e indirectamente.
metadata
Orúe López, Amalia Beatriz; Martínez Sierra, Ricel y Jara Quito, Daysi Margoth
mail
SIN ESPECIFICAR, ricel.martinez@unini.org, daysi.jara@doctorado.unini.edu.mx
(2023)
Análisis crítico sobre el perfil de salida del bachillerato ecuatoriano. Una mirada desde el método de aprendizaje basado en proyectos.
MLS Educational Research, 7 (1).
ISSN 2603-5820
Artículo
Materias > Educación física y el deporte
Materias > Educación
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés, Español
La educación física, como cultura del movimiento, es una práctica compleja de enseñanza e investigación que se desarrolla históricamente y por tanto hay que analizar como práctica situada que ocurre entre sujetos que también tienen su propio sentido histórico, social y político. La educación en la escuela es el espacio privilegiado de enseñanza de la educación física para la transformación social, es decir, para la praxis. A partir de estas consideraciones en este artículo propongo algunas reflexiones sobre la importancia del estudio de la praxis docente en sentido amplio, así como el lugar del profesor de educación física en tanto sujeto involucrado con la educación de las nuevas generaciones y por tanto responsable de, no solo generar espacios que circulen los saberes propios de la educación física, sino también de habilitar la reflexión colectiva en un intento por superar la perspectiva técnica de la enseñanza. Primero se presenta el concepto de educación y escuela y los sentidos que han asumido históricamente, luego se presentan las prácticas de enseñanza institucionalizas, y por último se presentan algunos aspectos de la situación actual de la educación física en relación con la temática, es decir las relaciones entre educación, escuela y educación física escolar.
metadata
Oroño Lugano, Marcela y Azaustre Lorenzo, María Carmen
mail
SIN ESPECIFICAR
(2022)
Educación, enseñanza, escuela y educación física: sentidos, relaciones y puntos de encuentros a la luz de la praxis docente.
MLS Educational Research, 6 (2).
ISSN 2603-5820
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Resumen. El estudio consistió en determinar el efecto del compost de E. crassipes en la calidad de las plantas en vivero de T. cacao, conocer los porcentajes de compost apropiados para su implementación y determinar niveles de plomo (Pb), arsénico (As) y mercurio (Hg) en plantas de E. crassipes, compost y plantas de T. cacao. Se utilizó un diseño completamente al azar, con 5 tratamientos, 5 repeticiones con 48 plantas cada uno. Se usó compost de E. crassipes en porcentajes de 10%, 20% y 40% mezclados con tierra en 90%, 80% y 60%. Los tratamientos se identificaron como: T1 (T10:90), T2 (T20:80), T3 (T40:60), un tratamiento relativo T4 (TR, 100% tierra y fertilización química) y un tratamiento testigo T5 (TT, 100% tierra). Los resultados del ANOVA demuestran que existe diferencia estadística significativa de los tratamientos en la calidad de las plantas de T. cacao para el diámetro, Índice de Calidad de Dickson (ICD) y peso seco total. Los T1, T2, T3 y T4, fueron estadísticamente superiores al tratamiento testigo T5 (TT) en esas variables. La altura de planta, índice de esbeltez, y relación peso seco aéreo-peso seco radicular, no presentaron diferencia estadística a un nivel de significancia de 0.05. La traslocación de Pb a plantas de T. cacao fue inexistente. Las plantas del T3 (T40:60), mostraron amarillamiento clorótico y síntomas de enfermedades en los 45 a los 90 días de germinadas. Se recomienda usar porcentajes de compost de E. crassipes no mayores al 20%, para plantas de T. cacao en vivero. metadata Orellana Tobar, Samuel Alfredo y Hernández, Armando Anaya mail SIN ESPECIFICAR, armando.anaya@unini.edu.mx (2021) Efecto del compost de Eichhornia crassipes en la calidad de plantas en vivero de Theobroma cacao. Project Design and Management, 3 (1). pp. 73-88. ISSN 2683-1597
Artículo
Materias > Biomedicina
Materias > Alimentación
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Protein-energy wasting (PEW) and poor health-related quality of life (HRQoL) are independently associated with morbi-mortality in continuous ambulatory peritoneal dialysis (CAPD). PEW may reduce HRQoL; however, we hypothesized HRQoL is affected differentially by PEW degrees or by individual criteria of nutritional status.
Aim
To evaluate HRQoL according to PEW severity and nutritional status indicators in CAPD.
This is a cross-sectional study in 151 patients. Subjective global assessment (SGA) was employed, and nutritional status classified as normal, mild-moderate PEW, and severe PEW. HRQoL was evaluated using Kidney Disease Quality of Life Short Form™, including physical (PCS), mental (MCS) and kidney disease (KDCS) components, and their subscales. Dietary intake, anthropometric and biochemical variables were measured.
Forty-six percent of patients were well-nourished, 44% had mild-moderate PEW, and 10% severe PEW. Compared with well-nourished patients, those with mild-moderate (p = 0.06) and severe (p = 0.005) PEW had lower HRQoL score [68 (52–75), 55 (45–72), 46 (43–58), respectively]. PCS, MCS, and KDCS and their subscales had lower values as PEW was more severe. Patients with obesity and hypoalbuminemia had significantly lower HRQoL overall and component scores than their counterparts. Dietary intake was not associated with quality of life. In multivariate analysis obesity, PEW (by SGA), hypoalbuminemia, and low educational level predicted poor HRQoL (χ2 58.2, p < 0.0001).
As conclusion, PEW severity was related with worse HRQoL, either as overall score or in every component or subscale in CAPD patients. Poor HRQoL was predicted independently by PEW severity and obesity; additional predictors were hypoalbuminemia and low education.
metadata
Orozco González, Nelly; Márquez-Herrera, Roxana M.; Cortés-Sanabria, Laura; Cueto-Manzano, Alfonso M.; Gutiérrez-Medina, Margarita; Gómez-García, Erika F.; Rojas-Campos, Enrique; Paniagua-Sierra, José R. y Martín del Campo, Fabiola
mail
nelly.orozco@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2021)
Severity of protein-energy wasting and obesity are independently related with poor quality of life in peritoneal dialysis patients.
Nefrología.
ISSN 02116995
Artículo Materias > Biomedicina Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Protein-energy wasting (PEW) and poor health-related quality of life (HRQoL) are independently associated with morbi-mortality in continuous ambulatory peritoneal dialysis (CAPD). PEW may reduce HRQoL; however, we hypothesized HRQoL is affected differentially by PEW degrees or by individual criteria of nutritional status. Aim To evaluate HRQoL according to PEW severity and nutritional status indicators in CAPD. This is a cross-sectional study in 151 patients. Subjective global assessment (SGA) was employed, and nutritional status classified as normal, mild-moderate PEW, and severe PEW. HRQoL was evaluated using Kidney Disease Quality of Life Short Form™, including physical (PCS), mental (MCS) and kidney disease (KDCS) components, and their subscales. Dietary intake, anthropometric and biochemical variables were measured. Forty-six percent of patients were well-nourished, 44% had mild-moderate PEW, and 10% severe PEW. Compared with well-nourished patients, those with mild-moderate (p = 0.06) and severe (p = 0.005) PEW had lower HRQoL score [68 (52–75), 55 (45–72), 46 (43–58), respectively]. PCS, MCS, and KDCS and their subscales had lower values as PEW was more severe. Patients with obesity and hypoalbuminemia had significantly lower HRQoL overall and component scores than their counterparts. Dietary intake was not associated with quality of life. In multivariate analysis obesity, PEW (by SGA), hypoalbuminemia, and low educational level predicted poor HRQoL (χ2 58.2, p < 0.0001). As conclusion, PEW severity was related with worse HRQoL, either as overall score or in every component or subscale in CAPD patients. Poor HRQoL was predicted independently by PEW severity and obesity; additional predictors were hypoalbuminemia and low education. metadata Orozco González, Nelly; Márquez-Herrera, Roxana M.; Cortés-Sanabria, Laura; Cueto-Manzano, Alfonso M.; Gutiérrez-Medina, Margarita; Gómez-García, Erika F.; Rojas-Campos, Enrique; Paniagua-Sierra, José R. y Martín del Campo, Fabiola mail nelly.orozco@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2022) Severity of protein-energy wasting and obesity are independently related with poor quality of life in peritoneal dialysis patients. Nefrología (English Edition), 42 (2). pp. 186-195. ISSN 20132514
Artículo Materias > Psicología Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Los métodos restaurativos de resolución de conflictos son herramientas de pleno uso en la Justicia y en los diferentes ámbitos de actuación de la sociedad en la que vivimos. En este artículo se aborda su uso específico para el manejo de conflictos intrafamiliares en casos de Alienación Parental, sacando a la luz el Síndrome de Alienación Parental. La línea teórica adoptada está en línea con la corriente que asume la existencia tanto de la Alienación, como del Síndrome, pero respetando opiniones contrarias, seleccionándose los siguientes métodos: Arbitraje, Círculos Restaurativos, Conciliación, Conferencias Restaurativas, Constelación Sistémica, Mediación, Negociación y Transacción. Se realizó una revisión sistemática de la literatura en artículos científicos en bases de datos electrónicas de investigación científica en Internet a través de Google Scholar. Se seleccionaron sesenta y un (61) trabajos académicos en los últimos 3 (tres) años, cuya lectura dilucida las recomendaciones del Autor (es) en cuanto a la recomendación específica de los métodos en casos de Alienación Parental en Brasil. Se encontró que más del 60% de los trabajos recomiendan la Mediación como camino a seguir, lo que sugiere un condicionamiento de los profesionales en el campo de la Alienación Parental, al señalar, en la mayoría, la Mediación. Muy probablemente, influenciado por la legislación vigente, dejando de lado los otros métodos, que pueden configurarse como excelentes opciones, dependiendo de la etapa de la Alienación. Estas posibilidades de aplicación de los Métodos Restaurativos de Resolución de Conflictos basados en estas etapas se presentan, con la ayuda de una tipología identificada en la Literatura, para brindar nuevas opciones para un apoyo efectivo y eficiente a los conflictos intrafamiliares en casos de Alienación Parental. metadata Oliveira, Sueli Santos y Maciel Pereira, Jose Antonio mail 0000-0001-7881-5371, 0000-0002-2364-4322 (2022) Una reflexión sobre la aplicación de métodos restaurativos de resolución de conflictos en la alienación parental. MLS Psychology Research, 5 (1). pp. 101-116. ISSN 2605-5295
Artículo Materias > Alimentación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Background & aims Evidence suggests that multiple-behavior interventions (with a specialist) have a greater impact on public health than single-behavior interventions, particularly in a chronic patient. However, there is little understanding of some very basic principles concerning multiple health behavior change, especially in situations such as kidney transplantation, which requires a great willingness to change negative lifestyle behaviors to achieve intermediate and long-term success. We compared healthy lifestyles and nutritional status according to the willingness to change dietary and exercise behavior in dialysis patients from a living donor kidney transplant program. Methods 400 dialysis patients had a dietetic, anthropometric, protein-energy wasting [subjective global assessment (SGA)] and biochemical evaluation. Lifestyle was evaluated with an adapted instrument to measure lifestyle in chronic disease. Willingness to change behaviors was evaluated by the trans-theoretical model; 2 groups were formed: willingness to change dietary and exercise behaviors and unwillingness to change. Results Willingness to change dietary behavior was 50% and exercise 25%. Patients with willingness to change dietary and exercise behaviors had better healthy lifestyle scores, and higher frequency of healthy food consumption. Healthy lifestyle score (R2 = 0.37, p < 0.0001) was predicted by older age, higher educational degree, shorter time on dialysis, and the highest willingness to change dietary and exercise behaviors. Conclusions Willingness to change dietary and exercise behaviors was associated with healthy lifestyle, as well as with higher frequency of healthy food consumption and with lower frequency of unhealthy food consumption. metadata Orozco González, Nelly; Cortés-Sanabria, Laura; Márquez-Herrera, Roxana M.; Martín-del-Campo-López, Fabiola; Gómez-García, Erika F.; Rojas-Campos, Enrique; Gómez-Navarro, Benjamín y Cueto-Manzano, Alfonso M. mail nelly.orozco@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2022) Willingness to change diet and exercise behavior is associated with better lifestyle in dialysis patients close to a kidney transplant. Clinical Nutrition ESPEN, 47. pp. 277-282. ISSN 24054577
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Artículo Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español El objeto del presente trabajo es analizar la figura jurídica del fideicomiso como medio de afectación de las participaciones federales como fuente de pago y garantía de créditos de las entidades federativas. Analizaremos el caso particular del estado de Colima y de las particularidades respectivas a su contrato de fideicomiso de afectación de participaciones federales, para estar en aptitud de determinar, además de su incompatibilidad para lograr la afectación de participaciones federales a través de dicha figura jurídica, los abusos que ello implica como la falta de respeto a los derechos de audiencia y defensa del estado de Colima, en la ejecución de dichas participaciones federales, mediante procedimientos que no le garantizan las formalidades esenciales del procedimiento. De igual forma analizaremos la incompatibilidad de las entidades federativas de legislar en relación a la factibilidad de utilizar al fideicomiso, como mecanismo de afectación de las participaciones federales como fuente de pago y garantía de los créditos asumidos por las entidades federativas, por ser el fideicomiso una materia de reservada adecuación legislativa para el Congreso de la Unión. El método utilizado en este trabajo es el inductivo-deductivo con enfoque cualitativo, utilizándose como instrumentos de investigación los documentales, a través del análisis cualitativo de la legislación, jurisprudencia y doctrina relacionada con la materia del presente trabajo. metadata Pérez Moreno, Arturo Javier mail SIN ESPECIFICAR (2022) Abuso de la figura del fideicomiso como fuente de pago o garantía con cargo a participaciones federales. Caso del estado de Colima. MLS Law and International Politics, 1 (2).
Artículo
Materias > Educación física y el deporte
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés, Español
Este estudio pretendía conocer cómo incide la aplicación del método continuo variable en la mejora de la resistencia de las participantes en las clases de bailoterapia. El objetivo general de este proyecto fue diseñar una propuesta de aplicación del método continuo variable en las clases de bailoterapia para lograr el mejoramiento de la resistencia. Se realizó un estudio de tipo cuantitativo, experimental de corte transversal y de campo, participaron un total de 20 mujeres adultas, con edades entre 20 y 59 años. Para saber el estado inicial de resistencia se llevó a cabo una evaluación pre intervención registrando los resultados en fichas de observación. Se utilizó la estadística t de Student para muestras relacionadas por tratarse del mismo grupo evaluado en una pre y post evaluación para comparar las medias en relación a los objetivos de la investigación. De los resultados obtenidos, se aprecia que existe un incremento significativo de la resistencia observada en la pre evaluación de cansancio parcial con una media de 12,95 minutos y la post evaluación de cansancio parcial con una media de 22,75 minutos, con un nivel de confianza de 0,05, observando un valor de p =,000. Así mismo, se aprecia que existe un incremento de la resistencia observada en la pre evaluación de cansancio total con una media de 19,80 minutos y en la post evaluación de cansancio total con 30,40 minutos, con un nivel de confianza de 0,05, observando un valor de p =,000.
metadata
Puebla, Zandy Alexandra y Hernández Cruz, Leonardo de Jesús
mail
SIN ESPECIFICAR, leonardo.hernandez@unib.org
(2022)
Aplicación del método continuo variable en la planificación de las clases de bailoterapia para el mejoramiento de la resistencia de las participantes de la parroquia "grl. Pedro J. Montero" del cantón Yaguachi, Ecuador.
MLS Sport Research, 2 (2).
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Accumulation of proteinaceous amyloid β plaques and tau oligomers may occur several years before the onset of Alzheimer disease (AD). Under normal circumstances, misfolded proteins get cleared by proteasome degradation, autophagy, and the recently discovered brain glymphatic system, an astroglial-mediated interstitial fluid bulk flow. It has been shown that the activity of the glymphatic system is higher during sleep and disengaged or low during wakefulness. As a consequence, poor sleep quality, which is associated with dementia, might negatively affect glymphatic system activity, thus contributing to amyloid accumulation. The diet is another important factor to consider in the regulation of this complex network. Diets characterized by high intakes of refined sugars, salt, animal-derived proteins and fats and by low intakes of fruit and vegetables are associated with a higher risk of AD and can perturb the circadian modulation of cortisol secretion, which is associated with poor sleep quality. For this reason, diets and nutritional interventions aimed at restoring cortisol concentrations may ease sleep disorders and may facilitate brain clearance, consequentially reducing the risk of cognitive impairment and dementia. Here, we describe the associations that exist between sleep, cortisol regulation, and diet and their possible implications for the risk of cognitive impairment and AD.
metadata
Pistollato, Francesca; Sumalla Cano, Sandra; Elío Pascual, Iñaki; Masias Vergara, Manuel; Giampieri, Francesca y Battino, Maurizio
mail
francesca.pistollato@uneatlantico.es, sandra.sumalla@uneatlantico.es, inaki.elio@uneatlantico.es, manuel.masias@uneatlantico.es, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es
(2016)
Associations between Sleep, Cortisol Regulation, and Diet: Possible Implications for the Risk of Alzheimer Disease.
Advances in Nutrition: An International Review Journal, 7 (4).
pp. 679-689.
ISSN 2156-5376
Artículo
Materias > Educación física y el deporte
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The aim of the present study was to understand the effect of a multicomponent physical exercise program on the functional physical fitness of older people with overweight or obesity in Chile, and whether these effects were similar in women and men. For this purpose, a quasi-experimental study was designed with a control group to evaluate the functional physical fitness through the Senior Fitness Test battery for older people [SFT; aerobic endurance (AE), lower body strength (LBS), upper body strength (UBS), upper body flexibility (UBF), lower body flexibility (LBF), dynamic balance (DB), and hand pressure strength right (HPSR) and left (HPSL)]. Seventy older people with overweight or obesity aged between 60 and 86 years participated (M = 73.15; SD = 5.94), and were randomized into a control group (CG, n = 35) and an experimental group (EG, n = 35). The results after the intervention between the CG and EG indicated that there were statistically significant differences in the AE (p = 0.036), in the LBS (p = 0.031), and in the LBF (p = 0.017), which did not exist before the intervention (p > 0.050), except in the HPSR (0.029). Regarding the results of the EG (pre vs. post-intervention), statistically significant differences were found in all of the variables studied: AE (p < 0.001), LBS (p < 0.001), UBS (p < 0.001), LBF (p = 0.017), UBF (p < 0.001), DB (p = 0.002), HPSR (p < 0.001), and HPSL (p = 0.012) in both men and women. These improvements did not exist in any of the CG variables (p > 0.05). Based on the results obtained, we can say that a multicomponent physical exercise program applied for 6 months in older people with overweight or obesity produces improvements in functional physical fitness regardless of sex, except in lower body flexibility and left-hand dynamometry.
metadata
Pleticosic-Ramírez, Yazmina; Velarde-Sotres, Álvaro; Mecías-Calvo, Marcos y Navarro-Patón, Rubén
mail
yazmina.pleticosic@doctorado.unini.edu.mx, alvaro.velarde@uneatlantico.es, marcos.mecias@uneatlantico.es, SIN ESPECIFICAR
(2024)
Can the Functional Physical Fitness of Older People with Overweight or Obesity Be Improved through a Multicomponent Physical Exercise Program? A Chilean Population Study.
Applied Sciences, 14 (15).
p. 6502.
ISSN 2076-3417
Artículo
Materias > Psicología
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Este artículo parte de la reflexión acerca de la vulneración de derechos de las personas con discapacidad, al desconocer que la sexualidad y afectividad también son fundamentales en sus vidas y configuran el ejercicio de los derechos sexuales y reproductivos; sin embargo, se han logrado importantes avances para su reconocimiento como sujetos titulares de derechos y generado múltiples normas que reivindican su titularidad y garantía; no obstante, estudios adelantados en Colombia y en el mundo, evidencian la persistencia de barreras fundamentadas en el desconocimiento, discriminación y falsas creencias sobre dichos aspectos de las personas con discapacidad.
El interés del estudio fue indagar mediante una encuesta, los conocimientos, actitudes y prácticas de padres, madres y cuidadores de adolescentes con discapacidad cognitiva de una institución educativa especializada de Bogotá, para que los resultados contribuyan a fortalecer capacidades de las familias y de instituciones con acciones pedagógicas que fomenten la garantía de derechos y el mejoramiento de la calidad de vida de esta población.
metadata
Polanco Valenzuela, Mauricio y Martín Ayala, Juan Luis
mail
SIN ESPECIFICAR
(2017)
Conocimientos, actitudes y prácticas de familias de adolescentes con discapacidad cognitiva en sexualidad y afectividad.
Diversitas, 13 (2).
pp. 187-199.
ISSN 1794-9998
Artículo
Materias > Biomedicina
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The genus Aeromonas has received constant attention in different areas, from aquaculture and veterinary medicine to food safety, where more and more frequent isolates are occurring with increased resistance to antibiotics. The present paper studied the interaction of Aeromonas strains isolated from fresh produce and water with different eukaryotic cell types with the aim of better understanding the cytotoxic capacity of these strains. To study host-cell pathogen interactions in Aeromonas, we used HT-29, Vero, J774A.1, and primary mouse embryonic fibroblasts. These interactions were analyzed by confocal microscopy to determine the cytotoxicity of the strains. We also used Galleria mellonella larvae to test their pathogenicity in this experimental model. Our results demonstrated that two strains showed high cytotoxicity in epithelial cells, fibroblasts, and macrophages. Furthermore, these strains showed high virulence using the G. mellonella model. All strains used in this paper generally showed low levels of resistance to the different families of the antibiotics being tested. These results indicated that some strains of Aeromonas present in vegetables and water pose a potential health hazard, displaying very high in vitro and in vivo virulence. This pathogenic potential, and some recent concerning findings on antimicrobial resistance in Aeromonas, encourage further efforts in examining the precise significance of Aeromonas strains isolated from foods for human consumption.
metadata
Pintor-Cora, Alberto; Tapia Martínez, Olga; Elexpuru Zabaleta, Maria; Ruiz de Alegría, Carlos; Rodríguez-Calleja, Jose M.; Santos, Jesús A. y Ramos Vivas, Jose
mail
SIN ESPECIFICAR, olga.tapia@uneatlantico.es, maria.elexpuru@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, jose.ramos@uneatlantico.es
(2023)
Cytotoxicity and Antimicrobial Resistance of Aeromonas Strains Isolated from Fresh Produce and Irrigation Water.
Antibiotics, 12 (3).
p. 511.
ISSN 2079-6382
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Seven aromatic polyamides and copolyamides were synthesized from two different aromatic diamines: 4,4′-(Hexafluoroisopropylidene)bis(p-phenyleneoxy)dianiline (HFDA) and 2,4-Aminobenzenesulfonic acid (DABS). The synthesis was carried out by polycondensation using isophthaloyl dichloride (1SO). The effect of an increasing molar concentration of the sulfonated groups, from DABS, in the copolymer properties was evaluated. Inherent viscosity tests were carried out to estimate molecular weights. Mechanical tests were carried out under tension, maximum strength ( σ max), Young’s modulus (E), and elongation at break (εmax) to determine their mechanical properties. Tests for water sorption and ion exchange capacity (IEC) were carried out. Proton conductivity was measured using electrochemical impedance spectroscopy (EIS). The results indicate that as the degree of sulfonation increase, the greater the proton conductivity. The results obtained showed conductivity values lower than the commercial membrane Nafion 115 of 0.0065 S cm−1. The membrane from copolyamide HFDA/DABS/1S0-70/30 with 30 mol DABS obtained the best IEC, with a value of 0.747 mmol g−1 that resulted in a conductivity of 2.7018 × 10−4 S cm−1, lower than the data reported for the commercial membrane Nafion 115. According to the results obtained, we can suggest that further developments increasing IEC will render membranes based on aromatic polyamides that are suitable for their use in PEM fuel cells.
metadata
Pali-Casanova, Ramón; Yam Cervantes, Marcial Alfredo; Zavala-Loría, José; Loría-Bastarrachea, María; Aguilar-Vega, Manuel; Dzul Lopez, Luis Alonso; Sámano Celorio, María Luisa; Crespo-Álvarez, Jorge; García Villena, Eduardo; Agudo-Toyos, Pablo y Méndez-Martínez, Francisco
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, luis.dzul@unini.edu.mx, marialuisa.samano@uneatlantico.es, jorge.crespo@uneatlantico.es, eduardo.garcia@uneatlantico.es, pablo.agudo@uenatlantico.es, SIN ESPECIFICAR
(2019)
Effect of Sulfonic Groups Concentration on IEC Properties in New Fluorinated Copolyamides.
Polymers, 11 (7).
p. 1169.
ISSN 2073-4360
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Cerrado
Inglés
Fasting, caloric restriction and foods or compounds mimicking the biological effects of caloric restriction, known as caloric restriction mimetics, have been associated with a lower risk of age-related diseases, including cardiovascular diseases, cancer and cognitive decline, and a longer lifespan. Reduced calorie intake has been shown to stimulate cancer immunosurveillance, reducing the migration of immunosuppressive regulatory T cells towards the tumor bulk. Autophagy stimulation via reduction of lysine acetylation, increased sensitivity to chemo- and immunotherapy, along with a reduction of insulin-like growth factor 1 and reactive oxygen species have been described as some of the major effects triggered by caloric restriction. Fasting and caloric restriction have also been shown to beneficially influence gut microbiota composition, modify host metabolism, reduce total cholesterol and triglyceride levels, lower diastolic blood pressure and elevate morning cortisol level, with beneficial modulatory effects on cardiopulmonary fitness, body fat and weight, fatigue and weakness, and general quality of life. Moreover, caloric restriction may reduce the carcinogenic and metastatic potential of cancer stem cells, which are generally considered responsible of tumor formation and relapse. Here, we reviewed in vitro and in vivo studies describing the effects of fasting, caloric restriction and some caloric restriction mimetics on immunosurveillance, gut microbiota, metabolism, and cancer stem cell growth, highlighting the molecular and cellular mechanisms underlying these effects. Additionally, studies on caloric restriction interventions in cancer patients or cancer risk subjects are discussed. Considering the promising effects associated with caloric restriction and caloric restriction mimetics, we think that controlled-randomized large clinical trials are warranted to evaluate the inclusion of these non-pharmacological approaches in clinical practice.
metadata
Pistollato, Francesca; Forbes-Hernández, Tamara Y.; Calderón Iglesias, Rubén; Ruiz Salces, Roberto; Elexpuru Zabaleta, Maria; Dominguez Azpíroz, Irma; Cianciosi, Danila; Quiles, José L.; Giampieri, Francesca y Battino, Maurizio
mail
francesca.pistollato@uneatlantico.es, SIN ESPECIFICAR, ruben.calderon@uneatlantico.es, roberto.ruiz@uneatlantico.es, maria.elexpuru@uneatlantico.es, irma.dominguez@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2021)
Effects of caloric restriction on immunosurveillance, microbiota and cancer cell phenotype: Possible implications for cancer treatment.
Seminars in Cancer Biology.
pp. 45-57.
ISSN 1044-579X
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
About 1 of 10 women, particularly those older than 60 years of age, shows some degree of thyroid hormone deficiency. Thyroid diseases are generally characterized by perturbations of thyroid signaling homeostasis. The most common examples of thyroid diseases include hypothyroidism, hyperthyroidism, and several types of thyroid cancers. Phytochemicals have been shown to have either beneficial or detrimental effects on thyroid function. Some flavonoids have been reported to affect the expression and the activity of several thyroid-related enzymes and proteins, and for this reason some concerns have been raised about the possible thyroid-disruptive properties of foods enriched in these substances. On the other hand, the beneficial effects of some plant-derived compounds, such as myricetin, quercetin, apigenin, rutin, genistein, and curcumin, and their possible role as adjuvants for the treatment of thyroid cancers have been described. Here, the role of phytochemicals in thyroid signaling modulation and their possible beneficial or detrimental effects on thyroid disease risk are discussed.
metadata
Pistollato, Francesca; Masías Vergara, Manuel; Agudo-Toyos, Pablo; Giampieri, Francesca y Battino, Maurizio
mail
francesca.pistollato@uneatlantico.es, manuel.masias@uneatlantico.es, pablo.agudo@uenatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2019)
Effects of phytochemicals on thyroid function and their possible role in thyroid disease.
Annals of the New York Academy of Sciences, 1443 (1).
pp. 3-19.
ISSN 0077-8923
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Hybrid membranes with three different thicknesses, PMDS_C1, PMDS_C2, and PMDS_C3 (0.21 ± 0.03 mm, 0.31 ± 0.05 mm, and 0.48 ± 0.07 mm), were synthesized by the sol–gel method using polydimethylsiloxane, hydroxy-terminated, and cyanopropyltriethoxysilane. The presence of cyano, methyl, and silicon-methyl groups was confirmed by FTIR analysis. Contact angle analysis revealed the membranes’ hydrophilic nature. Solvent resistance tests conducted under vortex and ultrasonic treatments (45 and 60 min) demonstrated a preference order of acetonitrile > methanol > water. Furthermore, the membranes exhibited stability over 48 h when exposed to different pH conditions (1, 3, 6, and 9), with negligible mass losses below 1%. The thermogravimetric analysis showed that the material was stable until 400 °C. Finally, the sorption analysis showed its capacity to detect furfural, 2-furylmethylketone, 5-methylfurfural, and 2-methyl 2-furoate. The thicker membrane was able to adsorb and slightly desorb a higher concentration of furanic compounds due to its high polarity provided by the addition of the cyano groups. The results indicated that the membranes may be suitable for sorbent materials in extracting and enriching organic compounds. metadata Pérez-Padilla, Yamile; Aguilar-Vega, Manuel; Uc-Cayetano, Erbin Guillermo; Esparza-Ruiz, Adriana; Yam Cervantes, Marcial Alfredo y Muñoz-Rodríguez, David mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, marcial.yam@unini.edu.mx, SIN ESPECIFICAR (2023) Evaluation of Organofunctionalized Polydimethylsiloxane Films for the Extraction of Furanic Compounds. Polymers, 15 (13). p. 2851. ISSN 2073-4360
Artículo Materias > Educación física y el deporte Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés This research aimed to explore the changes produced in body mass index (BMI), fat mass percentage (FMP), muscle mass percentage (MMP), and visceral fat percentage (VFP) in 60-year-old or over overweight or obese people after a multicomponent exercise program. This quasi-experimental study involved 70 overweight or obese older people between 60 and 86 years old (M = 73.15; SD = 5.94) who were randomly assigned to a control group (CG, n = 35) and an experimental group (EG, n = 35). At the beginning and at the end of the intervention program, anthropometric and body composition data were collected. The results showed an increase in BMI after the intervention in the CG (p = 0.010) and a decrease in the EG (p < 0.001). The results regarding the FMP indicate a significant decrease in the EG (p < 0.001) after the intervention, as occurs with the VFP (p = 0.003). The MMP increased in the EG (p < 0.001) after the intervention program. Regarding gender, statistically significant differences were found in the MMP after the intervention (p = 0.025), with higher percentages in men in the EG. VFP decreased in both men (p = 0.005) and women (p = 0.019) in the EG. From the results obtained, we can say that a 6-month multicomponent program produces a decrease in BMI, FMP, and VFP and an increase in MMP in its participants. This type of intervention seems to produce a greater increase in muscle mass in men than in women and a decrease in VFP in both genders. metadata Pleticosic-Ramírez, Yazmina; Mecías-Calvo, Marcos; Arufe-Giráldez, Víctor y Navarro-Patón, Rubén mail yazmina.pleticosic@doctorado.unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Incidence of a Multicomponent Physical Exercise Program on Body Composition in Overweight or Obese People Aged 60 Years or Older from Chile. Journal of Functional Morphology and Kinesiology, 9 (2). p. 81. ISSN 2411-5142
Artículo Materias > Educación física y el deporte Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Multicomponent exercise is a physical exercise modality in which various physical qualities (strength, cardiorespiratory endurance, flexibility, and balance) are developed with an equal distribution of volume in the same session (approximately 60 min) and that has been little explored in improving the quality of life of older adults. The aim of this study was to verify the effect of multicomponent training on self-perceived quality of life in Chilean overweight or obese older people. To this end, a quasi-experimental study with a control group was designed to evaluate self-perceived Quality of Life using the World Health Organization Quality of Life, brief version [Overall Quality of Life (OQOL); Overall Health (OH); Physical Health (PH); Psychological Health (PsH); Social Relations (SR); Environment (E)]. Seventy overweight or obese people aged between 60 and 86 years participated (M = 73.15; SD = 5.94) and were randomized into a control group (CG, n = 35) and an experimental group (EG, n = 35). The results in the EG (pre vs. post-intervention) indicated that there were statistically significant differences in OQOL (p = 0.005), OH (p = 0.014), PH (p < 0.001), PsH (p < 0.001), E (p = 0.015), and SR (p < 0.001) which were not found in the CG in any of the variables (p > 0.050) except in SR (p < 0.001). Regarding sex, post-intervention differences were only found between CG and EG in women in OQOL (p = 0.002), PH (p < 0.001), PsH (p = 0.003), and SR (p < 0.001), but not in OH or E (p > 0.050). These differences were not found among men in any of the variables (p > 0.050). As a conclusion, we can say that a multicomponent physical exercise program applied for 6 months significantly improves the perception of OQOL, OH, PH, PsH, SR, and E in overweight or obese older people. This perception is greater in men than in women. metadata Pleticosic-Ramírez, Yazmina; Arufe-Giráldez, Víctor; Rodríguez-Negro, Josune; Mecías-Calvo, Marcos y Navarro-Patón, Rubén mail yazmina.pleticosic@doctorado.unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Is It Possible to Improve the Perceived Quality of Life of Overweight or Obese Older People through a Multicomponent Physical Exercise Program? Behavioral Sciences, 14 (7). p. 618. ISSN 2076-328X
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Yersiniosis, caused by the fish pathogen Yersinia ruckeri, is a serious bacterial septicaemia affecting mainly salmonids worldwide. The acute infection may result in high mortality without apparent external disease signs, while the chronic one causes moderate to considerable mortality. Survivors of yersiniosis outbreaks become carriers. Y. ruckeri is able to adhere to, and to invade, phagocytic and non-phagocytic fish cells by using unknown molecular mechanisms. The aim of this study was to describe the kinetics of cell invasion by Y. ruckeri serotype O1 biotype 1 in a fish cell line (RTG-2) originating from rainbow trout gonads. The efficiency of invasion by Y. ruckeri was found to be temperature dependent, having a maximum at 20 °C. The bacterium was able to survive up to 96 h postinfection. The incubation of the cells at 4 °C and the pre-incubation of the bacteria with sugars or heat-inactivated antiserum significantly decreased the efficiency of invasion or even completely prevented the invasion of RTG-2 cells. These findings indicate that Y. ruckeri is capable of adhering to, entering and surviving within non-phagocytic cells, and that the intracellular environment may constitute a suitable niche for this pathogen that can favour the spread of infection and/or the maintenance of a carrier state of fish.
metadata
Padilla, Daniel; Acosta Hernández, Begoña; Ramos Vivas, Jose; Déniz, Soraya; Rosario, Inmaculada; Martín Barrasa, José Luís; Henao, Andrés sánchez; Silva Sergent, Freddy; Ramos Sosa, María josé; García Álvarez, Natalia y Real, Fernando
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, jose.ramos@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Kinetics of the invasion of a non-phagocytic fish cell line, RTG-2 by Yersinia ruckeri serotype O1 biotype 1.
Acta Veterinaria Hungarica.
ISSN 0236-6290
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español En el presente estudio se investigan la evolución de la generación de energía eléctrica del sector público y del sector privado por el cambio en la legislación eléctrica en 1996, por medio de la Ley General de Electricidad, para el efecto se utilizó el método analítico sintético, el estudio se realiza desde el enfoque cualitativo, con metodología mixta, la información se obtiene de fuentes secundarias, que corresponden a publicaciones de entidades del sector eléctrico efectuadas por la red internacional, o por información proporcionada, para los años en estudio y las variables definidas, el análisis de los artículos de la ley que regula la generación de energía eléctrica y la selección de los expertos entrevistados para la pregunta planteada, se realizó de acuerdo al criterio del investigador; con la información conseguida, se encontró el incremento de la generación de energía eléctrica del sector privado, debido a la apertura a la inversión de capitales privados en los proyectos eléctricos y a la posibilidad de entrar al mercado, el cambio en la legislación causa el incremento de los participantes en el subsector privado, registrados como agentes de mercado, entre los cuales se encuentran los agentes generadores, la generación de energía eléctrica disponible en el año 2017 es adecuada para lograr la satisfacción del servicio de energía eléctrica a los usuarios, en horas pico metadata Pérez Barrios, Edgar Estuardo y Silva Alvarado, Eduardo René mail estuardo.perez@unini.org, eduardo.silva@funiber.org (2022) La generación de energía eléctrica de 1996 al 2017 en Guatemala. MLS Law and International Politics, 1 (2).
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Un Modelo de Madurez de la Gestión de Proyectos contribuye a que las organizaciones midan y maduren sus prácticas en gestión de proyectos, programas y portafolios, a través de la definición de conocimientos mejoras en sus procesos. En México, existen estados con mayor crecimiento en el desarrollo de nuevos proyectos, como se ha visto en los últimos 20 años en el estado de Baja California Norte. El observatorio nacional reportó que la población de profesionistas en el estado alcanzó 305,374 de personas (SNE, 2020). Por consiguiente, se pretende conocer si este sector de la población conoce o aplica algún modelo de madurez en su trabajo. Por lo anterior, se propone un nuevo modelo de madurez que combina las fortalezas de los modelos más conocidos en la literatura y propone un plan de acciones estratégicas encaminadas hacia la madurez. Se analizó el nivel de madurez de la gestión de proyectos y de las competencias individuales, grupales e institucionales de esta población en el estado por medio de una encuesta multidimensional. Para comprobar su validez, se aplicó el análisis factorial exploratorio. Se encontró que los conocimientos en los procesos de la gestión de proyectos cuentan con un nivel 3 de madurez. Sin embargo, la misión, visión y las competencias institucionales apenas lograron un nivel 2. Lo que sugiere que las gerencias bajacalifornianas deben trabajar en esos aspectos. La nueva cultura propone un plan de acciones que se alinee con las estrategias y fomente la madurez en cualquier organización. metadata Pelayo Ramos, Octavio; Bravo Diaz, Brenda y Bazurto Roldán, José Antonio mail SIN ESPECIFICAR (2020) La nueva cultura de la madurez mexicana: un plan de desarrollo profesional y acciones estratégicas encaminadas a mejorar el nivel de madurez sobre los profesionistas baja californianos. Project, Design and Management, 3 (2). pp. 7-36. ISSN 26831597
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español En este trabajo fueron identificados los instrumentos dentro de los procesos utilizados para la planeación de la ejecución de proyectos de las organizaciones sin fines de lucro, ENL: el Alcance, Tiempo y Costos, así como su impacto en el desempeño de los proyectos y su mejora a través del modelo propuesto, que rescata las mejores prácticas del mundo de las mismas entidades, al mismo tiempo fueron identificadas cuales fueron las prácticas del mundo empresarial que pueden ser adaptadas en mayor o menor grado. Para la gestión de la implementación se encontraron 18 instrumentos en su mayoría propuestos y rescatados del mundo empresarial entre ellos; 10 de ellos fueron adaptados para las ENL sin problemas en un 100%; 4 de ellos para el 36% de las ENL; mientras que de los instrumentos propios del mundo empresarial sólo un 28% pudieron ser adaptados para la ENL. En general, se pudo identificar a partir de los resultados que la ENLs no cuentan con una estructura funcional que facilite la formulación y ejecución de proyectos, ya que las decisiones se toman en altos niveles empresariales, lo que a veces unido a la falta de experiencia dificulta la aplicación del uso de las herramientas, y retrasa la consecución y captación de recursos a través de los proyectos. Finalmente, el modelo representa una propuesta inicial que puede ser analizada, modificada y está sujeto a la mejora continua. metadata Prieto Mérida, Marco Antonio y Yam Cervantes, Marcial Alfredo mail SIN ESPECIFICAR, marcial.yam@unini.edu.mx (2022) Modelo estandarizado para la planificación en la ejecución de proyectos que permita mejorar el desempeño de las entidades no lucrativas. Project Design and Management, 4 (2). ISSN 2683-1597
Artículo
Materias > Biomedicina
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Ample epidemiological evidence suggests a strong correlation among diet, lifestyle factors and the onset and consolidation of dementia and Alzheimer’s disease (AD). It has been demonstrated that AD, diabetes, obesity, insulin resistance, and cardiovascular disease are strongly interconnected pathologies. Preventive strategies and nutritional interventions seem to be promising approaches to delay neurocognitive decline and reduce the risk of AD and other non-psychiatric co-morbidities. In this regard, healthy dietary patterns, characterized by high intake of plant-based foods, probiotics, antioxidants, soy beans, nuts, and omega-3 polyunsaturated fatty acids, and a low intake of saturated fats, animal-derived proteins, and refined sugars, have been shown to decrease the risk of neurocognitive impairments and eventually the onset of AD. Here we review the role of some nutrients and, in particular, of healthy dietary patterns, such as the Mediterranean diet and other emerging healthy diets, DASH (Dietary Approach to Stop Hypertension) and MIND (Mediterranean-DASH dietIntervention for Neurodegenerative Delay), for the maintenance of cognitive performance, focusing specifically on human studies. The beneficial effects associated with overall diet composition, rather than single nutrient supplementations, for the prevention or the delay of AD and dementia are discussed.
metadata
Pistollato, Francesca; Calderón Iglesias, Rubén; Ruiz Salces, Roberto; Aparicio-Obregón, Silvia; Crespo-Álvarez, Jorge; Dzul Lopez, Luis Alonso; Manna, Piera Pia; Giampieri, Francesca y Battino, Maurizio
mail
francesca.pistollato@uneatlantico.es, ruben.calderon@uneatlantico.es, roberto.ruiz@uneatlantico.es, silvia.aparicio@uneatlantico.es, jorge.crespo@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2018)
Nutritional patterns associated with the maintenance of neurocognitive functions and the risk of dementia and Alzheimer’s disease: A focus on human studies.
Pharmacological Research, 131.
pp. 32-43.
ISSN 10436618
Artículo Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés The math faculty experiences high drop-out, failing and withdrawal rates in the subject of university algebra. The findings show that higher education institutions can provide better service to students and can maximize their funding to increase graduation rates by eliminating withdrawal and failure rates. In this qualitative research, the faculty of mathematics at a university in southern Texas was asked to share their experiences and perceptions about the factors that contribute to the rates of withdrawal, failure and withdrawal in university algebra courses. This research provides information for a variety of stakeholders, as it shares the poorly understood perceptions of members of the mathematics faculty regarding how their experience in teaching university algebra influences teacher participation and student support. This research suggests implementing interventions for better teaching and provides strategies to increase approval and retention rates by finding best practices to teach university algebra, as well as serving as a reference for reducing failure and withdrawal rates due to expert recommendation. metadata Padilla-Oviedo, Andrés y Rojo Gutiérrez, Marco Antonio mail SIN ESPECIFICAR, marco.rojo@unini.edu.mx (2021) Perceptions from mathematics leaders' faculty at a South Texas University in factors that contribute with drop, fail and withdraw rates in college algebra. Veritas & Research, 3 (2). pp. 101-110.
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Environmental and lifestyle factors are known to play an important role during gestation, determining newborns' health status and influencing their risk of being subject to certain noncommunicable diseases later in life. In particular, maternal nutritional patterns characterized by a low intake of plant-derived foods could increase the risk of gestation-related issues, such as preeclampsia and pregravid obesity, increase genotoxicant susceptibility, and contribute to the onset of pediatric diseases. In particular, the risk of pediatric wheeze, diabetes, neural tube defects, orofacial clefts, and some pediatric tumors seems to be reduced by maternal intake of adequate amounts of vegetables, fruits, and selected antioxidants. Nevertheless, plant-based diets, like any other diet, if improperly balanced, could be deficient in some specific nutrients that are particularly relevant during gestation, such as n–3 (ω-3) fatty acids, vitamin B-12, iron, zinc, and iodine, possibly affecting the offspring's health state. Here we review the scientific literature in this field, focusing specifically on observational studies in humans, and highlight protective effects elicited by maternal diets enriched in plant-derived foods and possible issues related to maternal plant-based diets.
metadata
Pistollato, Francesca; Sumalla Cano, Sandra; Elio Pascual, Iñaki; Masias Vergara, Manuel; Giampieri, Francesca y Battino, Maurizio
mail
francesca.pistollato@uneatlantico.es, sandra.sumalla@uneatlantico.es, inaki.elio@uneatlantico.es, manuel.masias@uneatlantico.es, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2015)
Plant-Based and Plant-Rich Diet Patterns during Gestation: Beneficial Effects and Possible Shortcomings.
Advances in Nutrition, 6 (5).
pp. 581-591.
ISSN 2161-8313
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
It has been hypothesized that alterations in the composition of the gut microbiota might be associated with the onset of certain human pathologies, such as Alzheimer disease, a neurodegenerative syndrome associated with cerebral accumulation of amyloid-β fibrils. It has been shown that bacteria populating the gut microbiota can release significant amounts of amyloids and lipopolysaccharides, which might play a role in the modulation of signaling pathways and the production of proinflammatory cytokines related to the pathogenesis of Alzheimer disease. Additionally, nutrients have been shown to affect the composition of the gut microbiota as well as the formation and aggregation of cerebral amyloid-β. This suggests that modulating the gut microbiome and amyloidogenesis through specific nutritional interventions might prove to be an effective strategy to prevent or reduce the risk of Alzheimer disease. This review examines the possible role of the gut in the dissemination of amyloids, the role of the gut microbiota in the regulation of the gut–brain axis, the potential amyloidogenic properties of gut bacteria, and the possible impact of nutrients on modulation of microbiota composition and amyloid formation in relation to the pathogenesis of Alzheimer disease.
metadata
Pistollato, Francesca; Sumalla Cano, Sandra; Elío Pascual, Iñaki; Masias Vergara, Manuel; Giampieri, Francesca y Battino, Maurizio
mail
francesca.pistollato@uneatlantico.es, sandra.sumalla@uneatlantico.es, inaki.elio@uneatlantico.es, manuel.masias@uneatlantico.es, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es
(2016)
Role of gut microbiota and nutrients in amyloid formation and pathogenesis of Alzheimer disease.
Nutrition Reviews, 74 (10).
pp. 624-634.
ISSN 0029-6643
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Conventional outage management practices in distribution systems are tedious and complex due to the long time taken to locate the fault. Emerging smart technologies and various cloud services offered could be utilized and integrated into the power industry to enhance the overall process, especially in the fault monitoring and normalizing fields in distribution systems. This paper introduces smart fault monitoring and normalizing technologies in distribution systems by using one of the most popular cloud service platforms, the Microsoft Azure Internet of Things (IoT) Hub, together with some of the related services. A hardware prototype was constructed based on part of a real underground distribution system network, and the fault monitoring and normalizing techniques were integrated to form a system. Such a system with IoT integration effectively reduces the power outage experienced by customers in the healthy section of the faulted feeder from approximately 1 h to less than 5 min and is able to improve the System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) in electric utility companies significantly
metadata
Peter, Geno; Stonier, Albert Alexander; Gupta, Punit; Gavilanes, Daniel; Masías Vergara, Manuel y Lung sin, Jong
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, daniel.gavilanes@uneatlantico.es, manuel.masias@uneatlantico.es, SIN ESPECIFICAR
(2022)
Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoT.
Energies, 15 (21).
p. 8206.
ISSN 1996-1073
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés Kinetic rigidity of several polymers such as 2,6-bis(3-aminophenoxy)benzonitrile/4,4′oxydiphthalic anhydride (β-CN)APB/ODPA, poly[(2,2-dimethyl-1,3-dioxolan-4-yl)methyl acrylate)] (PACGA), and diglycidyl ether of bisphenol A (DEGEBA) was studied. Rigidity parameter D, Vogel’s temperature T0, and the activation energy Uα (Tg) for the glass transition were evaluated through Vogel’s model along with relaxation data using “nonlinear” regression of Arrhenius function. The existence of certain functional groups within the structure, such as the aromatic rings, gives high level of kinetic rigidity to the structure as is the case of (β-CN)APB/ODPA and DEGEBA, while the aliphatic groups confer flexibility, as in PACGA. metadata Pali-Casanova, Ramón; González, Wadi Elim Sosa; Zavala Loría, José del Carmen; García, Asteria Narváez; Yam Cervantes, Marcial Alfredo; Vega, Manuel de Jesús Aguilar y Dzul Lopez, Luis mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, luis.dzul@unini.edu.mx (2021) Structure and kinetic rigidity of polymers as related to chain relaxations. Journal of Thermoplastic Composite Materials, 34 (5). pp. 596-613. ISSN 0892-7057
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés Six aromatic copolyamides contanining phenyl groups were synthesized and characterized. The concentrations of the para-linked phenyl groups and meta-linked phenyl groups were varied systematically on the copolymers general structure to obtain a set of random copolyamides. Effect of copolymerization on glass transition temperature (Tg), tensile modulus (E), Tensile strength (σ) were measured. Changes in density were determined to estimate the effect on Fractional Free Volume (FFV). Results indicate that the substitution of para-linked phenyl group by meta-linked phenyl group causes an increase in tensile modulus E and tensile strength a decrease in Tg. The observed results are attributed to the asymmetric position of the linkages in the TERE and ISO isomers, because symmetric linkages, such as TERE, induces a higher packing of the polyamide chains while the asymmetry of ISO isomer inhibits packing causing an expansion in the FFV. metadata Pali-Casanova, Ramón; Loría-Bastarrachea, María; Aguilar-Vega, M. J.; Zavala-Loría, José; Dzul Lopez, Luis y Yam Cervantes, Marcial Alfredo mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, luis.dzul@unini.edu.mx, SIN ESPECIFICAR (2019) Structure effect on mechanical and thermal properties in aromatic copolyamides with phenyl substituents. Journal of Polymer Research, 26 (10). ISSN 1022-9760
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Glioblastoma multiforme (GBM) are extremely lethal and still poorly treated primary brain tumors, characterized by the presence of highly tumorigenic cancer stem cell (CSC) subpopulations, considered responsible for tumor relapse. In order to successfully eradicate GBM growth and recurrence, new anti-cancer strategies selectively targeting CSCs should be designed. CSCs might be eradicated by targeting some of their cell surface markers and transporters, inducing their differentiation, impacting their hyper-glycolytic metabolism, inhibiting CSC-related signaling pathways and/or by targeting their microenvironmental niche. In this regard, phytocompounds such as curcumin, isothiocyanates, resveratrol and epigallocatechin-3-gallate have been shown to prevent or reverse cancer-related epigenetic dysfunctions, reducing tumorigenesis, preventing metastasis and/or increasing chemotherapy and radiotherapy efficacy. However, the actual bioavailability and metabolic processing of phytocompounds is generally unknown, and the presence of the blood brain barrier often represents a limitation to glioma treatments. Nowadays, nanoparticles (NPs) can be loaded with therapeutic compounds such as phytochemicals, improving their bioavailability and their targeted delivery within the GBM tumor bulk. Moreover, NPs can be designed to increase their tropism and specificity toward CSCs by conjugating their surface with antibodies specific for CSC antigens, with ligands or with glucose analogues. Here we discuss the use of phytochemicals as anti-glioma agents and the applicability of phytochemical-loaded NPs as drug delivery systems to target GBM. Additionally, we provide some examples on how NPs can be specifically formulated to improve CSC targeting.
metadata
Pistollato, Francesca; Bremer-Hoffmann, Susanne; Basso, Giuseppe; Sumalla Cano, Sandra; Elío Pascual, Iñaki; Masías Vergara, Manuel; Giampieri, Francesca y Battino, Maurizio
mail
francesca.pistollato@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, sandra.sumalla@uneatlantico.es, inaki.elio@uneatlantico.es, manuel.masias@uneatlantico.es, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es
(2016)
Targeting Glioblastoma with the Use of Phytocompounds and Nanoparticles.
Targeted Oncology, 11 (1).
pp. 1-16.
ISSN 1776-2596
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Using artificial intelligence (AI) based software defect prediction (SDP) techniques in the software development process helps isolate defective software modules, count the number of software defects, and identify risky code changes. However, software development teams are unaware of SDP and do not have easy access to relevant models and techniques. The major reason for this problem seems to be the fragmentation of SDP research and SDP practice. To unify SDP research and practice this article introduces a cloud-based, global, unified AI framework for SDP called DePaaS—Defects Prediction as a Service. The article describes the usage context, use cases and detailed architecture of DePaaS and presents the first response of the industry practitioners to DePaaS. In a first of its kind survey, the article captures practitioner’s belief into SDP and ability of DePaaS to solve some of the known challenges of the field of software defect prediction. This article also provides a novel process for SDP, detailed description of the structure and behaviour of DePaaS architecture components, six best SDP models offered by DePaaS, a description of algorithms that recommend SDP models, feature sets and tunable parameters, and a rich set of challenges to build, use and sustain DePaaS. With the contributions of this article, SDP research and practice could be unified enabling building and using more pragmatic defect prediction models leading to increase in the efficiency of software testing
metadata
Pandit, Mahesha; Gupta, Deepali; Anand, Divya; Goyal, Nitin; Aljahdali, Hani Moaiteq; Ortega-Mansilla, Arturo; Kadry, Seifedine y Kumar, Arun
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, arturo.ortega@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Towards Design and Feasibility Analysis of DePaaS: AI Based Global Unified Software Defect Prediction Framework.
Applied Sciences, 12 (1).
p. 493.
ISSN 2076-3417
Artículo
Materias > Biomedicina
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Cerrado
Inglés
In the last decade, specific dietary patterns, mainly characterized by high consumption of vegetables and fruits, have been proven beneficial for the prevention of both metabolic syndrome (MetS)-related dysfunctions and neurodegenerative disorders, such as Alzheimer’s disease (AD). Nowadays, neuroimaging readouts can be used to diagnose AD, investigate MetS effects on brain functionality and anatomy, and assess the effects of dietary supplementations and nutritional patterns in relation to neurodegeneration and AD-related features. Here we review scientific literature describing the use of the most recent neuroimaging techniques to detect AD- and MetS-related brain features, and also to investigate associations between consolidated dietary patterns or nutritional interventions and AD, specifically focusing on observational and intervention studies in humans.
metadata
Pistollato, Francesca; Sumalla Cano, Sandra; Elío Pascual, Iñaki; Masías Vergara, Manuel; Giampieri, Francesca y Battino, Maurizio
mail
francesca.pistollato@uneatlantico.es, sandra.sumalla@uneatlantico.es, inaki.elio@uneatlantico.es, manuel.masias@uneatlantico.es, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es
(2015)
The Use of Neuroimaging to Assess Associations Among Diet, Nutrients, Metabolic Syndrome, and Alzheimer’s Disease.
Journal of Alzheimer's Disease, 48 (2).
pp. 303-318.
ISSN 13872877
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
At this time, efforts are being made on a worldwide scale to accomplish sustainable development objectives. It has, thus, now become essential to investigate the part of technology in the accomplishment of these Sustainable Development Goals (SDGs), as this will enable us to circumvent any potential conflicts that may arise. The importance of wastewater management in the accomplishment of these goals has been highlighted in the study. The research focuses on the role of fourth industrial revolution in meeting the Sustainable Goals for 2030. Given that water is the most important resource on the planet and since 11 of the 17 Sustainable Goals are directly related to having access to clean water, effective water management is the most fundamental need for achieving these goals. The age of Industry 4.0 has ushered in a variety of new solutions in many industrial sectors, including manufacturing, water, energy, healthcare, and electronics. This paper examines the present creative solutions in water treatment from an Industry-4.0 viewpoint, focusing on big data, the Internet of Things, artificial intelligence, and several other technologies. The study has correlated the various concepts of Industry 4.0 along with water and wastewater management and also discusses the prior work carried out in this field with help of different technologies. In addition to proposing a way for explaining the operation of I4.0 in water treatment through a systematic diagram, the paper makes suggestions for further research as well.
metadata
Pandey, Shivam; Twala, Bhekisipho; Singh, Rajesh; Gehlot, Anita; Singh, Aman; Caro Montero, Elisabeth y Priyadarshi, Neeraj
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, elizabeth.caro@uneatlantico.es, SIN ESPECIFICAR
(2022)
Wastewater Treatment with Technical Intervention Inclination towards Smart Cities.
Sustainability, 14 (18).
p. 11563.
ISSN 2071-1050
Artículo
Materias > Educación
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés, Español, Portugués
Este estudo tem por objetivo apresentar reflexões a partir da experiência de estudantes em nível de doutorado sobre a modalidade da Internacionalização em Casa no contexto da Pós-graduação, através da Educação a Distância. Pesquisa de horizonte qualitativo com abordagem da Hermenêutica Filosófica, num primeiro momento, apresenta demarcações conceituais sobre a necessidade da internacionalização, suas formas e desafios no contexto da região da América Latina e Caribe. Num segundo, apresenta resultados de uma experiência com estudantes que vivenciam esta modalidade no Chile, Colômbia e Brasil. Os resultados expressam as motivações, avaliações, aprendizagens e desafios em cursar um doutorado nessa modalidade. A internacionalização em casa na Pós-graduação propicia a emergência de uma nova relação entre uma instituição internacional diretamente com o estudante. Para os estudantes, a satisfação está na realização de um curso que em outros moldes não seria possível sem perder os vínculos pessoais e profissionais. O maior desafio passa pela disciplina e gestão de espaços e tempos de estudo.
metadata
Pereira, Vilmar Alves
mail
vilmar.alves@unini.edu.mx
(2022)
A internacionalização em casa na pós-graduação na América Latina e Caribe na modalidade a distância.
Revista Ibero-Americana de Estudos em Educação.
pp. 2476-2493.
ISSN 2446-8606
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
Among gynaecological cancers, ovarian cancer represents the leading cause of death in women. Current treatment for ovarian cancer entails surgery followed by combined chemotherapy with platinum and taxane, which are associated, particularly cisplatin, with severe side effects. While this treatment approach appears to be initially effective in a high number of patients, nearly 70% of them suffer a relapse within a few months after initial treatment. Therefore, more effective and better-tolerated treatment options are clearly needed. In recent years, several natural compounds (such as curcumin, epigallocatechin 3-gallate (EGCG), resveratrol, sulforaphane and Withaferin-A), characterized by long-term safety and negligible and/or inexistent side effects, have been proposed as possible adjuvants of traditional chemotherapy. Indeed, several in vitro and in vivo studies have shown that phytocompounds can effectively inhibit tumor cell proliferation, stimulate autophagy, induce apoptosis, and specifically target ovarian cancer stem cells (CSCs), which are generally considered to be responsible for tumor recurrence in several types of cancer. Here we review current literature on the role of natural products in ovarian cancer chemoprevention, highlighting their effects particularly on the regulation of inflammation, autophagy, proliferation and apoptosis, chemotherapy resistance, and ovarian CSC growth.
metadata
Pistollato, Francesca; Calderón Iglesias, Rubén; Ruiz Salces, Roberto; Aparicio Obregón, Silvia; Crespo Alvare, Jorge; Dzul Lopez, Luis; Giampieri, Francesca y Battino, Maurizio
mail
SIN ESPECIFICAR, ruben.calderon@uneatlantico.es, roberto.ruiz@uneatlantico.es, silvia.aparicio@uneatlantico.es, jorge.crespo@uneatlantico.es, luis.dzul@unini.edu.mx, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es
(2017)
The use of natural compounds for the targeting and chemoprevention of ovarian cancer.
Cancer Letters, 411.
pp. 191-200.
ISSN 0304-3835
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
In the last decades cancer has been considered as an epigenetic dysfunction, given the profound role of diet and lifestyle in cancer prevention and the determination of cancer risk. A plethora of recent publications have addressed the specific role of several environmental factors, such as nutritional habits, behavior, stress and toxins in the regulation of the physiological and cancer epigenome. In particular, plant-derived bioactive nutrients have been seen to positively affect normal cell growth, proliferation and differentiation and also to revert cancer related epigenetic dysfunctions, reducing tumorigenesis, preventing metastasis and/or increasing chemo and radiotherapy efficacy. Moreover, virtually all cancer types are characterized by the presence of cancer stem cell (CSC) subpopulations, residing in specific hypoxic and acidic microenvironments, or niches, and these cells are currently considered responsible for tumor resistance to therapy and tumor relapse. Modern anti-cancer strategies should be designed to selectively target CSCs and modulate the hypoxic and acidic tumor microenvironment, and, to this end, natural bioactive components seem to play a role. This review aims to discuss the effects elicited by plant-derived bioactive nutrients in the regulation of CSC self-renewal, cancer metabolism and tumor microenvironment.
metadata
Pistollato, Francesca; Giampieri, Francesca y Battino, Maurizio
mail
francesca.pistollato@uneatlantico.es, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es
(2015)
The use of plant-derived bioactive compounds to target cancer stem cells and modulate tumor microenvironment.
Food and Chemical Toxicology, 75.
pp. 58-70.
ISSN 02786915
Q
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
With the global spread of COVID-19, the governments advised the public for adopting safety precautions to limit its spread. The virus spreads from people, contaminated places, and nozzle droplets that necessitate strict precautionary measures. Consequently, different safety precautions have been implemented to fight COVID-19 such as wearing a facemask, restriction of social gatherings, keeping 6 feet distance, etc. Despite the warnings, highlighted need for such measures, and the increasing severity of the pandemic situation, the expected number of people adopting these precautions is low. This study aims at assessing and understanding the public perception of COVID-19 safety precautions, especially the use of facemask. A unified framework of sentiment lexicon with the proposed ensemble EB-DT is devised to analyze sentiments regarding safety precautions. Extensive experiments are performed with a large dataset collected from Twitter. In addition, the factors leading to a negative perception of safety precautions are analyzed by performing topic analysis using the Latent Dirichlet allocation algorithm. The experimental results reveal that 12% of the tweets correspond to negative sentiments towards facemask precaution mainly by its discomfort. Analysis of change in peoples’ sentiment over time indicates a gradual increase in the positive sentiments regarding COVID-19 restrictions.
metadata
Qamar, Usman; Ahmad, Ayaz; Rustam, Furqan; Saad, Eysha; Siddique, Muhammad Abubakar; Lee, Ernesto; Ortega-Mansilla, Arturo; Díez, Isabel de la Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, arturo.ortega@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Analyzing preventive precautions to limit spread of COVID-19.
PLOS ONE, 17 (8).
e0272350.
ISSN 1932-6203
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Facial emotion recognition (FER) is an important and developing topic of research in the field of pattern recognition. The effective application of facial emotion analysis is gaining popularity in surveillance footage, expression analysis, activity recognition, home automation, computer games, stress treatment, patient observation, depression, psychoanalysis, and robotics. Robot interfaces, emotion-aware smart agent systems, and efficient human–computer interaction all benefit greatly from facial expression recognition. This has garnered attention as a key prospect in recent years. However, due to shortcomings in the presence of occlusions, fluctuations in lighting, and changes in physical appearance, research on emotion recognition has to be improved. This paper proposes a new architecture design of a convolutional neural network (CNN) for the FER system and contains five convolution layers, one fully connected layer with rectified linear unit activation function, and a SoftMax layer. Additionally, the feature map enhancement is applied to accomplish a higher detection rate and higher precision. Lastly, an application is developed that mitigates the effects of the aforementioned problems and can identify the basic expressions of human emotions, such as joy, grief, surprise, fear, contempt, anger, etc. Results indicate that the proposed CNN achieves 92.66% accuracy with mixed datasets, while the accuracy for the cross dataset is 94.94%.
metadata
Qazi, Awais Salman; Farooq, Muhammad Shoaib; Rustam, Furqan; Gracia Villar, Mónica; Rodríguez Velasco, Carmen Lilí y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, monica.gracia@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR
(2022)
Emotion Detection Using Facial Expression Involving Occlusions and Tilt.
Applied Sciences, 12 (22).
p. 11797.
ISSN 2076-3417
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español El Sistema de Investigación de la Universidad Estatal a Distancia (UNED) ha buscado, desde su creación, propiciar una dinámica sistémica para la gestión de sus proyectos, apoyada en herramientas tecnológicas diseñadas a la medida. Esta perspectiva reta la visión tradicional de gestión de proyectos de investigación y abre posibilidades de innovación en este ámbito. Así, surge Gestiona, un software en línea para la captura de la información producida por los proyectos pertenecientes a dicho sistema de investigación. Como objetivo se ha buscado la mejora continua de Gestiona y su adaptación a los cambios del sistema de investigación de la UNED, considerando como criterio de efectividad la mínima pérdida de información posible a partir de los datos generados por los proyectos. El presente trabajo muestra cómo, una indagación sistémica del comportamiento de los actores que intervienen en los proyectos, ha permitido la mejora continua de la herramienta y la captura de datos relevantes en Gestiona, para la toma de decisiones por parte de las personas gestoras de los proyectos de investigación. Los resultados obtenidos muestran la efectividad de la indagación sistémica como una alternativa para la mejora continua de la gestión de proyectos. Asimismo, se presentan oportunidades de mejora emergentes como una característica valiosa propia del proceso de indagación sistémica. metadata Quesada Brenes, Esterlyn Mauricio y Segura Castillo, Andrés mail SIN ESPECIFICAR (2023) Indagación sistémica para la mejora continua de las herramientas de gestión de proyectos: el caso Gestiona de la Universidad Estatal a Distancia. Project Design and Management. ISSN 2683-1597
R
Tesis Materias > Educación Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster Cerrado Inglés This research focuses implementing communicative and task-based activities integrating information and communication technologies and online tools in a group of EFL B1-level students enrolled in distance learning courses in a Language Institute in Mexico, through observation, interviews, and surveys, data was gathered. This information helped design a lesson plan which would help improve learners' engagement and participation. metadata Ramírez Angmen, Andrea Carolina mail carorang14@gmail.com (2022) An Action Research for Implementing Communicative and Task-Based Activities Integrating ICTs and Online Tools in a Group of EFL B1-level Mexican students. Masters thesis, SIN ESPECIFICAR.
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Extracting knowledge from hybrid data, comprising both categorical and numerical data, poses significant challenges due to the inherent difficulty in preserving information and practical meanings during the conversion process. To address this challenge, hybrid data processing methods, combining complementary rough sets, have emerged as a promising approach for handling uncertainty. However, selecting an appropriate model and effectively utilizing it in data mining requires a thorough qualitative and quantitative comparison of existing hybrid data processing models. This research aims to contribute to the analysis of hybrid data processing models based on neighborhood rough sets by investigating the inherent relationships among these models. We propose a generic neighborhood rough set-based hybrid model specifically designed for processing hybrid data, thereby enhancing the efficacy of the data mining process without resorting to discretization and avoiding information loss or practical meaning degradation in datasets. The proposed scheme dynamically adapts the threshold value for the neighborhood approximation space according to the characteristics of the given datasets, ensuring optimal performance without sacrificing accuracy. To evaluate the effectiveness of the proposed scheme, we develop a testbed tailored for Parkinson’s patients, a domain where hybrid data processing is particularly relevant. The experimental results demonstrate that the proposed scheme consistently outperforms existing schemes in adaptively handling both numerical and categorical data, achieving an impressive accuracy of 95% on the Parkinson’s dataset. Overall, this research contributes to advancing hybrid data processing techniques by providing a robust and adaptive solution that addresses the challenges associated with handling hybrid data, particularly in the context of Parkinson’s disease analysis.
metadata
Raza, Imran; Jamal, Muhammad Hasan; Qureshi, Rizwan; Shahid, Abdul Karim; Rojas Vistorte, Angel Olider; Samad, Md Abdus y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, angel.rojas@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Adaptive neighborhood rough set model for hybrid data processing: a case study on Parkinson’s disease behavioral analysis.
Scientific Reports, 14 (1).
ISSN 2045-2322
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Ensuring the supply of electricity in a reliable and safe way is not an easy task, especially when considering renewable and clean energy generated with wind turbines given the intermittency or variability of the wind; also considering different time horizons increases complexity. Mexico has great potential for wind energy in the Eastern region and, to meet this challenge, a platform capable of generating forecast models automatically through mathematical techniques and artificial intelligence and managing them is proposed aimed at providing support based on knowledge and presenting the information graphically through a flexible dashboard, which is customizable and accessible when and where required. In this investigation, components related to the generation of electrical energy in this area are identified and a centralized system is proposed, with information segmentation, management of 3 user profiles, 6 KPIs, 5 configurable parameters, 7 different forecast models using statistical techniques, support vector machines, and automatic and deep learning, with 2 ways of visualization, to carry out analyses at 3 different time horizons. It is built in a modular way with free and open-source software. The results in the energy sector show that it allows focusing on priority activities avoiding rework, ensures reliability and completeness, is scalable, avoids duplication, allows resources to be shared, responds quickly to hypotheses, and has a global and summarized view of relevant data according to the interested party for different periods of time in an agile way, reducing times and offering support to the decision maker. metadata Romero, Inés y Ochoa-Zezzati, Alberto mail SIN ESPECIFICAR (2022) Analytical, Dynamic, and Interactive Platform for Generation and Managing Predictive Models Focused on Energy Sector. Journal of Electrical and Computer Engineering, 2022. pp. 1-12. ISSN 2090-0147
Artículo
Materias > Ingeniería
Materias > Comunicación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Chatbots are AI-powered programs designed to replicate human conversation. They are capable of performing a wide range of tasks, including answering questions, offering directions, controlling smart home thermostats, and playing music, among other functions. ChatGPT is a popular AI-based chatbot that generates meaningful responses to queries, aiding people in learning. While some individuals support ChatGPT, others view it as a disruptive tool in the field of education. Discussions about this tool can be found across different social media platforms. Analyzing the sentiment of such social media data, which comprises people’s opinions, is crucial for assessing public sentiment regarding the success and shortcomings of such tools. This study performs a sentiment analysis and topic modeling on ChatGPT-based tweets. ChatGPT-based tweets are the author’s extracted tweets from Twitter using ChatGPT hashtags, where users share their reviews and opinions about ChatGPT, providing a reference to the thoughts expressed by users in their tweets. The Latent Dirichlet Allocation (LDA) approach is employed to identify the most frequently discussed topics in relation to ChatGPT tweets. For the sentiment analysis, a deep transformer-based Bidirectional Encoder Representations from Transformers (BERT) model with three dense layers of neural networks is proposed. Additionally, machine and deep learning models with fine-tuned parameters are utilized for a comparative analysis. Experimental results demonstrate the superior performance of the proposed BERT model, achieving an accuracy of 96.49%.
metadata
R, Sudheesh; Mujahid, Muhammad; Rustam, Furqan; Shafique, Rahman; Chunduri, Venkata; Gracia Villar, Mónica; Brito Ballester, Julién; Diez, Isabel de la Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, monica.gracia@uneatlantico.es, julien.brito@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Analyzing Sentiments Regarding ChatGPT Using Novel BERT: A Machine Learning Approach.
Information, 14 (9).
p. 474.
ISSN 2078-2489
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés, Español
Actualmente la gestión de proyectos cuenta con muchas herramientas y metodologías que buscan desarrollar proyectos exitosos, no siempre es posible cumplir con los objetivos fijados desde su concepción. Una gran parte de los proyectos de construcción son ejecutados sin ser evaluados y documentados adecuadamente a lo largo de su ciclo de vida, aumentando las probabilidades de ser un proyecto fallido y de no cumplir con la rentabilidad o uso esperado. El caso de estudio es sobre un proyecto hidroeléctrico que fue iniciado con personal propio de una empresa privada hondureña (EPH)[1], que al poco tiempo empezó a presentar una serie de inconvenientes que generaron desfases en costos y en tiempo. Cuando se había utilizado el 85% del presupuesto original estimado y se observa un avance de obra menor al 50%, la EPH decidió contratar a una empresa supervisora externa (ESE) para darle seguimiento al proyecto, revisar el diseño del mismo y que se asegurara que el proyecto fuera culminado. El proyecto fue culminado con un año y ocho meses adicionales de construcción y el costo del total final superó en 7.5 millones de dólares americanos del presupuesto original. El objetivo principal de esta investigación es la de analizar la eficiencia y sostenibilidad del proyecto para obtener lecciones que posibiliten la identificación de las fallas y aciertos en los desvíos alcanzados a lo largo del mismo y, a partir de ellos, generar recomendaciones que le permitan a la organización corregir y mejorar su actual metodología para sus futuros proyectos.
metadata
Ramírez López, Ana Mellissa y Mazzetto, Matías Ariel
mail
SIN ESPECIFICAR
(2022)
Análisis y mejores prácticas proyectuales de una obra civil hidroeléctrica de Honduras.
Project Design and Management, 4 (2).
ISSN 2683-1597
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
With rapid urbanization, high rates of industrialization, and inappropriate waste disposal, water quality has been substantially degraded during the past decade. So, water quality prediction, an essential element for a healthy society, has become a task of great significance to protecting the water environment. Existing approaches focus predominantly on either water quality or water consumption prediction, utilizing complex algorithms that reduce the accuracy of imbalanced datasets and increase computational complexity. This study proposes a simple architecture of neural networks which is more efficient and accurate and can work for predicting both water quality and water consumption. An artificial neural network (ANN) consisting of one hidden layer and a couple of dropout and activation layers is utilized in this regard. The approach is tested using two datasets for predicting water quality and water consumption. Results show a 0.96 accuracy for water quality prediction which is better than existing studies. A 0.99 R2 score is obtained for water consumption prediction which is superior to existing state-of-the-art approaches.
metadata
Rustam, Furqan; Ishaq, Abid; Kokab, Sayyida Tabinda; de la Torre Diez, Isabel; Vidal Mazón, Juan Luis; Rodríguez Velasco, Carmen Lilí y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR
(2022)
An Artificial Neural Network Model for Water Quality and Water Consumption Prediction.
Water, 14 (21).
p. 3359.
ISSN 2073-4441
Artículo
Materias > Educación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
It is recommended to implement the teaching of Basic Life Support (BLS) in schools; however, studies on the best training method are limited and have been a priority in recent years. The objective of this study was to analyze the attitudes and practical skills learned during BLS training using a gamified proposal. A comparative study was carried out, consisting of Compulsory Secondary Education students [control group (CG; classical teaching) and experimental group (EG; gamified proposal)]. The instruments used were the CPR and AED action sequence observation sheet, data from the Laerdal Resusci Anne manikin and AED and Attitude Questionnaire towards Basic Life Support and the Use of the Automated External Defibrillator. Sixty-eight students (33 girls) with a mean age of 13.91 ± 0.70 years were recruited. Results were significantly better in the EG (n = 37) [i.e., breathing control (p = 0.037); call to emergency services (p = 0.049); mean compression depth (p = 0.001); self-confidence (p = 0.006); intention to perform BLS and AED (p = 0.002)]; and significantly better in the CG (n = 31) [Total percentage of CPR (p < 0.001); percentage of correct compression (p < 0.001); time to apply effective shock with AED (p < 0.001); demotivation (p = 0.005). We can conclude that the group that was trained with the training method through the gamified proposal presents better intentions and attitudes to act in the event of cardiac arrest than those of the classic method. This training method allows for similar results in terms of CPR and AED skills to classical teaching, so it should be taken into account as a method for teaching BLS to secondary education students.
metadata
Rodríguez-García, Adrián; Ruiz-García, Giovanna; Navarro-Patón, Rubén y Mecías-Calvo, Marcos
mail
adrian.rodriguez@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, marcos.mecias@uneatlantico.es
(2024)
Attitudes and Skills in Basic Life Support after Two Types of Training: Traditional vs. Gamification, of Compulsory Secondary Education Students: A Simulation Study.
Pediatric Reports, 16 (3).
pp. 631-643.
ISSN 2036-7503
Artículo Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Entrepreneurship is one of the factors that contribute to economic growth. The present study compares the entrepreneurship between South Korea and Colombia; it identifies best practices that increase entrepreneurship as an ecosystem conditions for both countries. Also, this study provides evidence on how implementing reforms improve entrepreneurship by reducing the processes and number of days required to attain goals. The use of new technologies and organizational innovation allowed improving the processes. Furthermore, creating universal formats reduced the costs throughout the new production unit was established. In addition, transparency, access to information, work regulation, and the government role in creating new companies in respect to demand are topics of a pending agenda in favor of entrepreneurship for both countries. metadata Rojo Gutiérrez, Marco Antonio; Olaya Molano, Juan Carlos; Padilla Oviedo, Andrés y Ramon Ramirez, Juan mail marco.rojo@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2017) A Comparative Study in Entrepreneurship Between South Korea and Colombia. IJRDO - Journal of Social Science and Humanities Research, 2 (9). pp. 69-81.
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Currently, induction motors are widely used in industry because have a high potential for efficiency improvement. Therefore, a topic of interest to the industry is to reduce the energy consumption of induction motors, as they represent almost half of the total electrical energy consumption in the world. The energy consumption of electric motors can be reduced by using motors that are more efficient and by using power converters to feed the motors, thereby enabling accurate control according to the load. The function of the power converter is to modify the intrinsic characteristics of the induction motor (speed and torque). There are different topologies of the power converter commonly called inverter for induction motors. An inverter requires a modulation strategy for its operation, there are several modulation strategies that are used in the induction converter-motor assembly. This paper presents the comparative analysis of the influence of the phase disposition modulation (PD-PWM) strategy with different modulation indices, on parameters related to the output signal of a cascaded multilevel inverter (seven-levels) as well as on the nominal working conditions of a three-phase induction motor metadata Reyes Severiano, Yesenia; Aguayo Alquicira, Jesús; De León Aldaco, Susana Estefany y Carrillo Santos, Luis Mauricio mail SIN ESPECIFICAR (2020) Comparative analysis of PD-PWM technique in the set: Multilevel Inverter-Induction motor. Ingeniería Investigación y Tecnología, 21 (1). pp. 1-8. ISSN 14057743
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
According to the World Health Organization (WHO), Parkinson’s disease (PD) is a neurodegenerative disease of the brain that causes motor symptoms including slower movement, rigidity, tremor, and imbalance in addition to other problems like Alzheimer’s disease (AD), psychiatric problems, insomnia, anxiety, and sensory abnormalities. Techniques including artificial intelligence (AI), machine learning (ML), and deep learning (DL) have been established for the classification of PD and normal controls (NC) with similar therapeutic appearances in order to address these problems and improve the diagnostic procedure for PD. In this article, we examine a literature survey of research articles published up to September 2022 in order to present an in-depth analysis of the use of datasets, various modalities, experimental setups, and architectures that have been applied in the diagnosis of subjective disease. This analysis includes a total of 217 research publications with a list of the various datasets, methodologies, and features. These findings suggest that ML/DL methods and novel biomarkers hold promising results for application in medical decision-making, leading to a more methodical and thorough detection of PD. Finally, we highlight the challenges and provide appropriate recommendations on selecting approaches that might be used for subgrouping and connection analysis with structural magnetic resonance imaging (sMRI), DaTSCAN, and single-photon emission computerized tomography (SPECT) data for future Parkinson’s research.
metadata
Rana, Arti; Dumka, Ankur; Singh, Rajesh; Panda, Manoj Kumar y Priyadarshi, Neeraj
mail
SIN ESPECIFICAR
(2022)
A Computerized Analysis with Machine Learning Techniques for the Diagnosis of Parkinson’s Disease: Past Studies and Future Perspectives.
Diagnostics, 12 (11).
p. 2708.
ISSN 2075-4418
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Large-scale distributed systems have the advantages of high processing speeds and large communication bandwidths over the network. The processing of huge real-world data within a time constraint becomes tricky, due to the complexity of data parallel task scheduling in a time constrained environment. This paper proposes data parallel task scheduling in cloud to address the minimization of cost and time constraints. By running concurrent executions of tasks on multi-core cloud resources, the number of parallel executions could be increased correspondingly, thereby, finishing the task within the deadline is possible. A mathematical model is developed here to minimize the operational cost of data parallel tasks by feasibly assigning a load to each virtual machine in the cloud data center. This work experiments with a machine learning model that is replicated on the multi-core cloud heterogeneous resources to execute different input data concurrently to accomplish distributive learning. The outcome of concurrent execution of data-intensive tasks on different parts of the input dataset gives better solutions in terms of processing the task by the deadline at optimized cost.
metadata
Rajalakshmi, N. R.; Dumka, Ankur; Kumar, Manoj; Singh, Rajesh; Gehlot, Anita; Akram, Shaik Vaseem; Anand, Divya; Elkamchouchi, Dalia H. y Delgado Noya, Irene
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, SIN ESPECIFICAR, irene.delgado@uneatlantico.es
(2022)
A Cost-Optimized Data Parallel Task Scheduling with Deadline Constraints in Cloud.
Electronics, 11 (13).
p. 2022.
ISSN 2079-9292
Artículo Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español La presente investigación está orientada a verificar la viabilidad de aplicar el Cuadro de Mando Integral (CMI) a la gestión de los recursos en la Gendarmería Nacional Argentina (GNA), como herramienta capaz de convertir la visión y las estrategias a la organización, comunicar y relacionar objetivos e indicadores con el propósito de alcanzar la eficiencia administrativa. Para lograrlo se recurrió a la metodología mixta (cualitativa, cuantitativa y descriptiva), en función a las referencias teóricas vinculadas al CMI, el análisis de la administración de la Fuerza, el presupuesto, el clima organizacional y el concepto de los ciudadanos sobre la GNA. Las muestras fueron colectadas en tres fases: en la primera se realizó el análisis documental vinculado a la gestión y la bibliografía disponible; en la segunda, entrevistas a los oficiales superiores, sobre el conocimiento sobre el instrumento; encuesta al personal para indagar sobre el clima organizacional y, por último, una encuesta de opinión a los ciudadanos beneficiarios del servicio de la GNA; la tercera fase se diseñó del prototipo de CMI aplicado a la Institución. La validación de los instrumentos se realizó a través del Coeficiente de Alfa de Cronbach. Se aprecia que es viable la aplicación de esta herramienta y que puede aportar información en tiempo y oportunidad para monitorear las actividades, priorizar los proyectos, medir la trayectoria del uso de los recursos, alinear el trabajo, facilitar las comunicaciones internas y tomar adecuadas decisiones en búsqueda de la eficiencia en la utilización de los recursos. metadata Rojo Gutiérrez, Marco Antonio y Zampedri, Óscar Alcides mail marco.rojo@unini.edu.mx, SIN ESPECIFICAR (2022) Cuadro de mando integral en el sector público: caso de estudio la Gendarmería Nacional Argentina. MLS Law and International Politics, 2 (1). ISSN 2952-248X
Artículo
Materias > Ingeniería
Materias > Psicología
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Predicting depression intensity from microblogs and social media posts has numerous benefits and applications, including predicting early psychological disorders and stress in individuals or the general public. A major challenge in predicting depression using social media posts is that the existing studies do not focus on predicting the intensity of depression in social media texts but rather only perform the binary classification of depression and moreover noisy data makes it difficult to predict the true depression in the social media text. This study intends to begin by collecting relevant Tweets and generating a corpus of 210000 public tweets using Twitter public application programming interfaces (APIs). A strategy is devised to filter out only depression-related tweets by creating a list of relevant hashtags to reduce noise in the corpus. Furthermore, an algorithm is developed to annotate the data into three depression classes: ‘Mild,’ ‘Moderate,’ and ‘Severe,’ based on International Classification of Diseases-10 (ICD-10) depression diagnostic criteria. Different baseline classifiers are applied to the annotated dataset to get a preliminary idea of classification performance on the corpus. Further FastText-based model is applied and fine-tuned with different preprocessing techniques and hyperparameter tuning to produce the tuned model, which significantly increases the depression classification performance to an 84% F1 score and 90% accuracy compared to baselines. Finally, a FastText-based weighted soft voting ensemble (WSVE) is proposed to boost the model’s performance by combining several other classifiers and assigning weights to individual models according to their individual performances. The proposed WSVE outperformed all baselines as well as FastText alone, with an F1 of 89%, 5% higher than FastText alone, and an accuracy of 93%, 3% higher than FastText alone. The proposed model better captures the contextual features of the relatively small sample class and aids in the detection of early depression intensity prediction from tweets with impactful performances.
metadata
Rizwan, Muhammad; Mushtaq, Muhammad Faheem; Rafiq, Maryam; Mehmood, Arif; Diez, Isabel de la Torre; Gracia Villar, Mónica; Garay, Helena y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, monica.gracia@uneatlantico.es, helena.garay@uneatlantico.es, SIN ESPECIFICAR
(2024)
Depression Intensity Classification from Tweets Using FastText Based Weighted Soft Voting Ensemble.
Computers, Materials & Continua, 78 (2).
pp. 2047-2066.
ISSN 1546-2226
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
Retinitis pigmentosa (RP) is a group of genetic retinal disorders characterized by progressive vision loss, culminating in blindness. Identifying pigment signs (PS) linked with RP is crucial for monitoring and possibly slowing the disease’s degenerative course. However, the segmentation and detection of PS are challenging due to the difficulty of distinguishing between PS and blood vessels and the variability in size, shape, and color of PS. Recently, advances in deep learning techniques have shown impressive results in medical image analysis, especially in ophthalmology. This study presents an approach for classifying pigment marks in color fundus images of RP using a modified squeeze-and-excitation ResNet (SE-ResNet) architecture. This variant synergizes the efficiency of residual skip connections with the robust attention mechanism of the SE block to amplify feature representation. The SE-ResNet model was fine-tuned to determine the optimal layer configuration that balances performance metrics and computational costs. We trained the proposed model on the RIPS dataset, which comprises images from patients diagnosed at various RP stages. Experimental results confirm the efficacy of the proposed model in classifying different types of pigment signs associated with RP. The model yielded performance metrics, such as accuracy, sensitivity, specificity, and f-measure of 99.16%, 97.70%, 96.93%, 90.47%, 99.37%, 97.80%, 97.44%, and 90.60% on the testing set, based on GT1 & GT2 respectively. Given its performance, this model is an excellent candidate for integration into computer-aided diagnostic systems for RP, aiming to enhance patient care and vision-related healthcare services.
metadata
Rashid, Rubina; Aslam, Waqar; Mehmood, Arif; Ramírez-Vargas, Debora L.; Diez, Isabel De La Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, debora.ramirez@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
A Detectability Analysis of Retinitis Pigmetosa Using Novel SE-ResNet Based Deep Learning Model and Color Fundus Images.
IEEE Access, 12.
pp. 28297-28309.
ISSN 2169-3536
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
Internet security is a major concern these days due to the increasing demand for information technology (IT)-based platforms and cloud computing. With its expansion, the Internet has been facing various types of attacks. Viruses, denial of service (DoS) attacks, distributed DoS (DDoS) attacks, code injection attacks, and spoofing are the most common types of attacks in the modern era. Due to the expansion of IT, the volume and severity of network attacks have been increasing lately. DoS and DDoS are the most frequently reported network traffic attacks. Traditional solutions such as intrusion detection systems and firewalls cannot detect complex DDoS and DoS attacks. With the integration of artificial intelligence-based machine learning and deep learning methods, several novel approaches have been presented for DoS and DDoS detection. In particular, deep learning models have played a crucial role in detecting DDoS attacks due to their exceptional performance. This study adopts deep learning models including recurrent neural network (RNN), long short-term memory (LSTM), and gradient recurrent unit (GRU) to detect DDoS attacks on the most recent dataset, CICDDoS2019, and a comparative analysis is conducted with the CICIDS2017 dataset. The comparative analysis contributes to the development of a competent and accurate method for detecting DDoS attacks with reduced execution time and complexity. The experimental results demonstrate that models perform equally well on the CICDDoS2019 dataset with an accuracy score of 0.99, but there is a difference in execution time, with GRU showing less execution time than those of RNN and LSTM.
metadata
Ramzan, Mahrukh; Shoaib, Muhammad; Altaf, Ayesha; Arshad, Shazia; Iqbal, Faiza; Kuc Castilla, Ángel Gabriel y Ashraf, Imran
mail
SIN ESPECIFICAR
(2023)
Distributed Denial of Service Attack Detection in Network Traffic Using Deep Learning Algorithm.
Sensors, 23 (20).
p. 8642.
ISSN 1424-8220
Artículo
Materias > Biomedicina
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
In order to promote the sustainable development of aquaculture, it is of great importance to better understand fish diseases caused by classic and emerging bacterial pathogens. Strains of classic fish pathogens such as Aeromonas, Vibrio, Photobacterium, Edwardsiella, Yersinia, Flavobacterium, or Piscirickettsia.
metadata
Ramos-Vivas, José y Acosta, Félix
mail
jose.ramos@uneatlantico.es, SIN ESPECIFICAR
(2024)
Editorial: Host-bacteria interactions in fish pathogens.
Frontiers in Cellular and Infection Microbiology, 14.
ISSN 2235-2988
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Cerrado
Inglés
In this study, the phytochemical profile of fifty olive leaves (OL) extracts from Spain, Italy, Greece, Portugal, and Morocco was characterized and their anti-cholinergic, anti-inflammatory, and antioxidant activities were evaluated. Luteolin-7-O-glucoside, isoharmnentin, and apigenin were involved in the acetylcholinesterase (AChE) inhibitory activity, while oleuropein and hydroxytyrosol showed noteworthy potential. Secoiridoids contributed to the cyclooxygenase-2 inhibitory activity and antioxidant capacity. Compounds such as oleuropein, ligstroside and luteolin-7-O-glucoside, may exert an important role in the ferric reducing antioxidant capacity. It should be also highlighted the role of hydroxytyrosol, hydroxycoumarins, and verbascoside concerning the antioxidant activity. This research provides valuable insights and confirms that specific compounds within OL extracts contribute to distinct anti-cholinergic, anti-inflammatory, and anti-oxidative effects.
metadata
Romero-Márquez, Jose M.; Navarro-Hortal, María D.; Forbes-Hernández, Tamara Y.; Varela-López, Alfonso; Puentes, Juan G.; Sánchez-González, Cristina; Sumalla Cano, Sandra; Battino, Maurizio; García-Ruiz, Roberto; Sánchez, Sebastián y Quiles, José L.
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, sandra.sumalla@uneatlantico.es, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, jose.quiles@uneatlantico.es
(2024)
Effect of olive leaf phytochemicals on the anti-acetylcholinesterase, anti-cyclooxygenase-2 and ferric reducing antioxidant capacity.
Food Chemistry, 444.
p. 138516.
ISSN 03088146
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Diabetes is a persistent health condition led by insufficient use or inappropriate use of insulin in the body. If left undetected, it can lead to further complications involving organ damage such as heart, lungs, and eyes. Timely detection of diabetes helps obtain the right medication, diet, and exercise plan to lead a healthy life. ML approach has been utilized to obtain rapid and reliable diabetes detection, however, existing approaches suffer from the use of limited datasets, lack of generalizability, and lower accuracy. This study proposes a novel feature extraction approach to overcome these limitations by using an ensemble of convolutional neural network (CNN) and long short-term memory (LSTM) models. Multiple datasets are combined to make a larger dataset for experiments and multiple features are utilized for investigating the efficacy of the proposed approach. Features from the extra tree classifier, CNN, and LSTM are also considered for comparison. Experimental results reveal the superb performance of CNN-LSTM-based features with random forest model obtaining a 0.99 accuracy score. This performance is further validated by comparison with existing approaches and k-fold cross-validation which shows the proposed approach provides robust results.
metadata
Rustam, Furqan; Al-Shamayleh, Ahmad Sami; Shafique, Rahman; Aparicio Obregón, Silvia; Calderón Iglesias, Rubén; Gonzalez, J. Pablo Miramontes y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, silvia.aparicio@uneatlantico.es, ruben.calderon@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Enhanced detection of diabetes mellitus using novel ensemble feature engineering approach and machine learning model.
Scientific Reports, 14 (1).
ISSN 2045-2322
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Thyroid illness encompasses a range of disorders affecting the thyroid gland, leading to either hyperthyroidism or hypothyroidism, which can significantly impact metabolism and overall health. Hypothyroidism can cause a slowdown in bodily processes, leading to symptoms such as fatigue, weight gain, depression, and cold sensitivity. Hyperthyroidism can lead to increased metabolism, causing symptoms like rapid weight loss, anxiety, irritability, and heart palpitations. Prompt diagnosis and appropriate treatment are crucial in managing thyroid disorders and improving patients’ quality of life. Thyroid illness affects millions worldwide and can significantly impact their quality of life if left untreated. This research aims to propose an effective artificial intelligence-based approach for the early diagnosis of thyroid illness. An open-access thyroid disease dataset based on 3,772 male and female patient observations is used for this research experiment. This study uses the nominal continuous synthetic minority oversampling technique (SMOTE-NC) for data balancing and a fine-tuned light gradient booster machine (LGBM) technique to diagnose thyroid illness and handle class imbalance problems. The proposed SNL (SMOTE-NC-LGBM) approach outperformed the state-of-the-art approach with high-accuracy performance scores of 0.96. We have also applied advanced machine learning and deep learning methods for comparison to evaluate performance. Hyperparameter optimizations are also conducted to enhance thyroid diagnosis performance. In addition, we have applied the explainable Artificial Intelligence (XAI) mechanism based on Shapley Additive exPlanations (SHAP) to enhance the transparency and interpretability of the proposed method by analyzing the decision-making processes. The proposed research revolutionizes the diagnosis of thyroid disorders efficiently and helps specialties overcome thyroid disorders early.
metadata
Raza, Ali; Eid, Fatma; Caro Montero, Elisabeth; Delgado Noya, Irene y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, elizabeth.caro@uneatlantico.es, irene.delgado@uneatlantico.es, SIN ESPECIFICAR
(2024)
Enhanced interpretable thyroid disease diagnosis by leveraging synthetic oversampling and machine learning models.
BMC Medical Informatics and Decision Making, 24 (1).
ISSN 1472-6947
Artículo Materias > Alimentación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Introduction: during the pandemic, an increase in symptoms of depression and anxiety, as well as lifestyle changes in adolescents has been reported. Objectives: to evaluate anxiety and depression symptoms, risky eating behaviors (REB), eating habits and physical activity after the COVID-19 pandemic in Mexican adolescents; to associate the study variables with the development of REB. Methods: a study was performed with a sample of 2,710 adolescents. The Hospital Anxiety and Depression Scale (HADS) and the Questionnaire to measure Risky Eating Behaviors were applied; eating habits and physical activity were evaluated. A Multivariate Logistic Regression analysis was performed to evaluate an association between study variables and REB. Results: it was found that 34.4 % and 47.2 % of the adolescents presented symptoms of depression and anxiety, respectively. Furthermore, 10.6 % had REB and 18.1 % were at risk of REB. The combined prevalence of overweight and obesity was 46.5 %; only 13.1 % of the participants had healthy eating habits and 18.2 % adequate physical activity. Symptoms of depression (p < 0.0001), anxiety (p < 0.0001), higher BMI (p < 0.0001), female sex, excessive consumption of sugary drinks, eating outside the home (p < 0.0001), and lifestyle (p = 0.001) were associated with REB. Conclusions: confinement caused chaos on the lifestyle of adolescents as well as their psychological health. It is essential to develop educational programs that involve government authorities, parents and health agencies to reinforce the topics of healthy eating, physical activity and mental health in the country's secondary schools. metadata Radilla Vázquez, Claudia Cecilia; Sotomayor Terán, Diva Guadalupe; Lazarevich, Irina; Gutiérrez Tolentino, Rey; Leija Alva, Gerardo y Barriguete Meléndez, Jorge Armando mail SIN ESPECIFICAR (2024) Evaluation of depression, anxiety, risky eating behaviors, eating habits and physical activity after the COVID-19 pandemic among adolescents in Mexico City. Nutrición Hospitalaria. ISSN 0212-1611
Artículo
Materias > Ingeniería
Materias > Educación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The purpose of this research article was to contrast the benefits of the optimal probability threshold adjustment technique with other imbalanced data processing techniques, in its application to the prediction of post-graduate students’ late dropout from distance learning courses in two universities in the Ibero-American space. In this context, the optimization of the Logistic Regression, Random Forest, and Neural Network classifiers, together with different techniques, attributes, and algorithms (Hyperparameters, SMOTE, SMOTE_SVM, and ADASYN) resulted in a set of metrics for decision-making, prioritizing the reduction of false negatives. The best model was the Neural Network model in combination with SMOTE_SVM, obtaining a recall index of 0.75 and an f1-Score of 0.60. Likewise, the robustness of the Random Forest classifier for imbalanced data was demonstrated by achieving, with an optimal threshold of 0.427, very similar metrics to those obtained by the consensus of the three best models found. This demonstrates that, for Random Forest, the optimal prediction probability threshold is an excellent alternative to resampling techniques with different optimal thresholds. Finally, it is hoped that this research paper will contribute to boost the application of this simple but powerful technique, which is highly underrated with respect to data resampling techniques for imbalanced data.
metadata
Rodríguez Velasco, Carmen Lilí; García Villena, Eduardo; Brito Ballester, Julién; Durántez Prados, Frigdiano Álvaro; Silva Alvarado, Eduardo René y Crespo Álvarez, Jorge
mail
carmen.rodriguez@uneatlantico.es, eduardo.garcia@uneatlantico.es, julien.brito@uneatlantico.es, durantez@uneatlantico.es, eduardo.silva@funiber.org, jorge.crespo@uneatlantico.es
(2023)
Forecasting of Post-Graduate Students’ Late Dropout Based on the Optimal Probability Threshold Adjustment Technique for Imbalanced Data.
International Journal of Emerging Technologies in Learning (iJET), 18 (04).
pp. 120-155.
ISSN 1863-0383
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
In the last decades, the world population and demand for any kind of product have grown exponentially. The rhythm of production to satisfy the request of the population has become unsustainable and the concept of the linear economy, introduced after the Industrial Revolution, has been replaced by a new economic approach, the circular economy. In this new economic model, the concept of “the end of life” is substituted by the concept of restoration, providing a new life to many industrial wastes. Leaves are a by-product of several agricultural cultivations. In recent years, the scientific interest regarding leaf biochemical composition grew, recording that plant leaves may be considered an alternative source of bioactive substances. Plant leaves’ main bioactive compounds are similar to those in fruits, i.e., phenolic acids and esters, flavonols, anthocyanins, and procyanidins. Bioactive compounds can positively influence human health; in fact, it is no coincidence that the leaves were used by our ancestors as a natural remedy for various pathological conditions. Therefore, leaves can be exploited to manufacture many products in food (e.g., being incorporated in food formulations as natural antioxidants, or used to create edible coatings or films for food packaging), cosmetic and pharmaceutical industries (e.g., promising ingredients in anti-aging cosmetics such as oils, serums, dermatological creams, bath gels, and other products). This review focuses on the leaves’ main bioactive compounds and their beneficial health effects, indicating their applications until today to enhance them as a harvesting by-product and highlight their possible reuse for new potential healthy products.
metadata
Regolo, Lucia; Giampieri, Francesca; Battino, Maurizio; Armas Diaz, Yasmany; Mezzetti, Bruno; Elexpuru Zabaleta, Maria; Mazas Pérez-Oleaga, Cristina; Tutusaus, Kilian y Mazzoni, Luca
mail
SIN ESPECIFICAR, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, maria.elexpuru@uneatlantico.es, cristina.mazas@uneatlantico.es, kilian.tutusaus@uneatlantico.es, SIN ESPECIFICAR
(2024)
From by-products to new application opportunities: the enhancement of the leaves deriving from the fruit plants for new potential healthy products.
Frontiers in Nutrition, 11.
ISSN 2296-861X
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The objectives this study were to examine the integrated use of oil–coagulant for the direct extraction of coagulant from Moringa oleifera (MO) with 5% and 10% (NH4)2SO4 extractor solution to harvest Scenedesmus obliquus cultivated in urban wastewater and to analyze the oil extracted from MO and S. obliquus. An average content of 0.47 g of coagulant and 0.5 g of oil per gram of MO was obtained. Highly efficient algal harvest, 80.33% and 72.13%, was achieved at a dose of 0.38 g L−1 and pH 8–9 for 5% and 10% extractor solutions, respectively. For values above pH 9, the harvest efficiency decreases, producing a whitish water with 10% (NH4)2SO4 solution. The oil profile (MO and S. obliquus) showed contents of SFA of 36.24–36.54%, monounsaturated fatty acids of 32.78–36.13%, and polyunsaturated fatty acids of 27.63–30.67%. The biodiesel obtained by S. obliquus and MO has poor cold flow properties, indicating possible applications limited to warm climates. For both biodiesels, good fuel ignition was observed according to the high cetane number and positive correlation with SFA and negative correlation with the degree of saturation. This supports the use of MO as a potentially harmless bioflocculant for microalgal harvest in wastewater, contributing to its treatment, and a possible source of low-cost biodiesel.
metadata
Ruiz-Marin, Alejandro; Canedo-Lopez, Yunuen; Narvaez-Garcia, Asteria; Zavala Loría, José del Carmen; Dzul Lopez, Luis Alonso; Sámano Celorio, María Luisa; Crespo-Álvarez, Jorge; García Villena, Eduardo y Agudo-Toyos, Pablo
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, jose.zavala@unini.edu.mx, luis.dzul@unini.edu.mx, marialuisa.samano@uneatlantico.es, jorge.crespo@uneatlantico.es, eduardo.garcia@uneatlantico.es, pablo.agudo@uenatlantico.es
(2019)
Harvesting Scenedesmus obliquus via Flocculation of Moringa oleifera Seed Extract from Urban Wastewater: Proposal for the Integrated Use of Oil and Flocculant.
Energies, 12 (20).
p. 3996.
ISSN 1996-1073
Artículo Materias > Educación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español El concepto de gamificación aplicado en el ámbito educativo, incide positivamente en la motivación y compromiso de los estudiantes en los procesos de aprendizaje. El propósito de este artículo consiste en analizar cuál fue el impacto de la gamificación con TIC en el desempeño académico en el área de ciencias sociales por parte de los estudiantes de cuarto grado de primaria de la institución educativa técnica Antonio Nariño de Moniquirá - Colombia. Metodológicamente se realizó un estudio de tipo mixto secuencial explicativo CUAN CUAL CUAN donde intervienen instrumentos cuantitativos y cualitativos, que cuentan con los respectivos criterios de validez y fiabilidad. La muestra quedó compuesta tanto por docentes, que participaron a través de la entrevista etnográfica y el cuestionario y facilitaron la observación del desarrollo de la propuesta de gamificación, como por estudiantes, que fueron organizados en dos grupos: experimental y control, para confrontar los resultados obtenidos en el pretest y postest. En el análisis de los datos cuantitativos se utilizó el software SPSS 11.0 y para el análisis de los datos cualitativos se implementó la herramienta Atlas.ti. Dentro de los resultados obtenidos se destaca que sí existió diferencia significativa entre las medias de los puntajes obtenidos en el pretest y el postest, tras la implementación de la propuesta gamificada, a la vez que se evidencia mejoramiento del clima en el aula, mayor motivación y participación de los estudiantes en clase. Resalta la propuesta de los docentes en relación al uso de herramientas TIC gamificadoras para planear, motivar, aprender y evaluar, junto al intercambio de experiencias exitosas de gamificación en otras áreas del conocimiento. Se concluye que el uso de estrategias gamificadas supone un aporte positivo a las dinámicas docentes, útil para la mejora de los resultados académicos en ciencias sociales. metadata Rojas Soler, Luz Erminda y Amber, Diana mail lerojass@misena.edu.co, SIN ESPECIFICAR (2022) Impacto de la gamificación con TIC en la enseñanza de las ciencias sociales en estudiantes de cuarto grado de primaria. MLS Educational Research, 6 (2). ISSN 2603-5820
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Parkinson’s disease (PD) is a neurodegenerative disease that affects the neural, behavioral, and physiological systems of the brain. This disease is also known as tremor. The common symptoms of this disease are a slowness of movement known as ‘bradykinesia’, loss of automatic movements, speech/writing changes, and difficulty with walking at early stages. To solve these issues and to enhance the diagnostic process of PD, machine learning (ML) algorithms have been implemented for the categorization of subjective disease and healthy controls (HC) with comparable medical appearances. To provide a far-reaching outline of data modalities and artificial intelligence techniques that have been utilized in the analysis and diagnosis of PD, we conducted a literature analysis of research papers published up until 2022. A total of 112 research papers were included in this study, with an examination of their targets, data sources and different types of datasets, ML algorithms, and associated outcomes. The results showed that ML approaches and new biomarkers have a lot of promise for being used in clinical decision-making, resulting in a more systematic and informed diagnosis of PD. In this study, some major challenges were addressed along with a future recommendation metadata Rana, Arti; Dumka, Ankur; Singh, Rajesh; Panda, Manoj Kumar; Priyadarshi, Neeraj y Twala, Bhekisipho mail SIN ESPECIFICAR (2022) Imperative Role of Machine Learning Algorithm for Detection of Parkinson’s Disease: Review, Challenges and Recommendations. Diagnostics, 12 (8). p. 2003. ISSN 2075-4418
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
In Smart Cities’ applications, Multi-node cooperative spectrum sensing (CSS) can boost spectrum sensing efficiency in cognitive wireless networks (CWN), although there is a non-linear interaction among number of nodes and sensing efficiency. Cooperative sensing by nodes with low computational cost is not favorable to improving sensing reliability and diminishes spectrum sensing energy efficiency, which poses obstacles to the regular operation of CWN. To enhance the evaluation and interpretation of nodes and resolves the difficulty of sensor selection in cognitive sensor networks for energy-efficient spectrum sensing. We examined reducing energy usage in smart cities while substantially boosting spectrum detecting accuracy. In optimizing energy effectiveness in spectrum sensing while minimizing complexity, we use the energy detection for spectrum sensing and describe the challenge of sensor selection. This article proposed the algorithm for choosing the sensing nodes while reducing the energy utilization and improving the sensing efficiency. All the information regarding nodes is saved in the fusion center (FC) through which blockchain encrypts the information of nodes ensuring that a node’s trust value conforms to its own without any ambiguity, CWN-FC pick high-performance nodes to engage in CSS. The performance evaluation and computation results shows the comparison between various algorithms with the proposed approach which achieves 10% sensing efficiency in finding the solution for identification and triggering possibilities with the value of α=1.5 and γ=2.5 with the varying number of nodes.
metadata
Rani, Shalli; Babbar, Himanshi; Shah, Syed Hassan Ahmed y Singh, Aman
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es
(2022)
Improvement of energy conservation using blockchain-enabled cognitive wireless networks for smart cities.
Scientific Reports, 12 (1).
ISSN 2045-2322
Artículo Materias > Psicología Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Introduction: Artificial Intelligence (AI) is transforming multiple sectors within our society, including education. In this context, emotions play a fundamental role in the teaching-learning process given that they influence academic performance, motivation, information retention, and student well-being. Thus, the integration of AI in emotional assessment within educational environments offers several advantages that can transform how we understand and address the socio-emotional development of students. However, there remains a lack of comprehensive approach that systematizes advancements, challenges, and opportunities in this field. Aim: This systematic literature review aims to explore how artificial intelligence (AI) is used to evaluate emotions within educational settings. We provide a comprehensive overview of the current state of research, focusing on advancements, challenges, and opportunities in the domain of AI-driven emotional assessment within educational settings. Method: The review involved a search across the following academic databases: Pubmed, Web of Science, PsycINFO and Scopus. Forty-one articles were selected that meet the established inclusion criteria. These articles were analyzed to extract key insights related to the integration of AI and emotional assessment within educational environments. Results: The findings reveal a variety of AI-driven approaches that were developed to capture and analyze students’ emotional states during learning activities. The findings are summarized in four fundamental topics: (1) emotion recognition in education, (2) technology integration and learning outcomes, (3) special education and assistive technology, (4) affective computing. Among the key AI techniques employed are machine learning and facial recognition, which are used to assess emotions. These approaches demonstrate promising potential in enhancing pedagogical strategies and creating adaptive learning environments that cater to individual emotional needs. The review identified emerging factors that, while important, require further investigation to understand their relationships and implications fully. These elements could significantly enhance the use of AI in assessing emotions within educational settings. Specifically, we are referring to: (1) federated learning, (2) convolutional neural network (CNN), (3) recurrent neural network (RNN), (4) facial expression databases, and (5) ethics in the development of intelligent systems. Conclusion: This systematic literature review showcases the significance of AI in revolutionizing educational practices through emotion assessment. While advancements are evident, challenges related to accuracy, privacy, and cross-cultural validity were also identified. The synthesis of existing research highlights the need for further research into refining AI models for emotion recognition and emphasizes the importance of ethical considerations in implementing AI technologies within educational contexts. metadata Rojas Vistorte, Angel Olider; Deroncele-Acosta, Angel; Martín Ayala, Juan Luis; Barrasa, Angel; López-Granero, Caridad y Martí-González, Mariacarla mail angel.rojas@uneatlantico.es, SIN ESPECIFICAR, juan.martin@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Integrating artificial intelligence to assess emotions in learning environments: a systematic literature review. Frontiers in Psychology, 15. ISSN 1664-1078
Artículo Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español En esta investigación se identifica el desempeño y la gestión de la innovación en las empresas industriales micro, pequeñas y medianas (mipymes) de Córdoba, Argentina durante el periodo 2015-2020. La información se toma a partir de un cuestionario aplicado a 90 empresas de la región. Se crean dos índices, uno que refleja las actividades de gestión de la innovación y otro que refleja el desempeño innovador. Un relevante número de empresas asume resultados positivos en su desempeño innovador, siendo la innovación en productos y la innovación en procesos las más significativas, seguidas por la innovación organizativa y la innovación comercial. Entre las actividades de gestión de la innovación más importantes y que muestran un impacto positivo en el desempeño innovador, se destacan el fomento a la creatividad; la priorización de la innovación en la estrategia empresarial; el diseño de una estrategia de marketing y las actividades relacionadas con la internacionalización. Un análisis que subyace de lo anterior, se basa en considerar los múltiples factores que afectan a los índices tanto de desempeño como de gestión de la innovación y que forman parte de un proceso mucho más complejo y fuertemente condicionado por el contexto externo e intrínseco a las firmas. metadata Rojo Gutiérrez, Marco Antonio y Beladelli, Luciana María mail marco.rojo@unini.edu.mx, SIN ESPECIFICAR (2022) Las Actividades de gestión de la innovación como determinantes explicativas del desempeño innovador de las mipymes industriales en Córdoba, Argentina. Estudio de caso 2015-2020. Project Design and Management, 4 (2).
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés Today’s processes are dynamic, in particular how customers purchase products and/or services from financial institutions. Therefore, organizations face the challenge of establishing business strategies focused on the customer and building long-lasting relationships. This implies accelerating the needs of a digital transformation both toward the customer and in internal processes. A framework for risk management, applicable to digital transformation projects, is presented under an agile approach to manage and manage operational risks. Thus, through a methodology based on the application of a set of Scrum best practices, it is integrated into the current risk management tools of a banking institution. The results are scalable and extensible to Financial and Governmental Institutions. metadata Recabarren-Domínguez, Eduardo; López, Felipe A.; Ferriol Sánchez, Fermín y Gatica, Gustavo mail SIN ESPECIFICAR, SIN ESPECIFICAR, fermin.ferriol@unini.edu.mx, SIN ESPECIFICAR (2021) A Methodological Proposal for Managing Operational Risk by Integrating Agility. Developments and Advances in Defense and Security, 255. pp. 319-325. ISSN 2190-3018
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Age-related bone disorders such as osteoporosis or osteoarthritis are a major public health problem due to the functional disability for millions of people worldwide. Furthermore, fractures are associated with a higher degree of morbidity and mortality in the long term, which generates greater financial and health costs. As the world population becomes older, the incidence of this type of disease increases and this effect seems notably greater in those countries that present a more westernized lifestyle. Thus, increased efforts are directed toward reducing risks that need to focus not only on the prevention of bone diseases, but also on the treatment of persons already afflicted. Evidence is accumulating that dietary lipids play an important role in bone health which results relevant to develop effective interventions for prevent bone diseases or alterations, especially in the elderly segment of the population. This review focuses on evidence about the effects of dietary lipids on bone health and describes possible mechanisms to explain how lipids act on bone metabolism during aging. Little work, however, has been accomplished in humans, so this is a challenge for future research.
metadata
Romero-Márquez, Jose M.; Varela-López, Alfonso; Navarro-Hortal, María D.; Badillo-Carrasco, Alberto; Forbes-Hernández, Tamara Y.; Giampieri, Francesca; Dominguez Azpíroz, Irma; Madrigal-Hoyos, Lorena; Battino, Maurizio y Quiles, José L.
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, irma.dominguez@uneatlantico.es, lorena.madrigal@uneatlantico.es, maurizio.battino@uneatlantico.es, jose.quiles@uneatlantico.es
(2021)
Molecular Interactions between Dietary Lipids and Bone Tissue during Aging.
International Journal of Molecular Sciences, 22 (12).
p. 6473.
ISSN 1422-0067
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Alzheimer’s Disease (AD) is the cause of around 60–70% of global cases of dementia and approximately 50 million people have been reported to suffer this disease worldwide. The leaves of olive trees (Olea europaea) are the most abundant by-products of the olive grove industry. These by-products have been highlighted due to the wide variety of bioactive compounds such as oleuropein (OLE) and hydroxytyrosol (HT) with demonstrated medicinal properties to fight AD. In particular, the olive leaf (OL), OLE, and HT reduced not only amyloid-β formation but also neurofibrillary tangles formation through amyloid protein precursor processing modulation. Although the isolated olive phytochemicals exerted lower cholinesterase inhibitory activity, OL demonstrated high inhibitory activity in the cholinergic tests evaluated. The mechanisms underlying these protective effects may be associated with decreased neuroinflammation and oxidative stress via NF-κB and Nrf2 modulation, respectively. Despite the limited research, evidence indicates that OL consumption promotes autophagy and restores loss of proteostasis, which was reflected in lower toxic protein aggregation in AD models. Therefore, olive phytochemicals may be a promising tool as an adjuvant in the treatment of AD.
metadata
Romero-Márquez, Jose M.; Forbes-Hernández, Tamara Y.; Navarro-Hortal, María D.; Quirantes-Piné, Rosa; Grosso, Giuseppe; Giampieri, Francesca; Lipari, Vivian; Sánchez-González, Cristina; Battino, Maurizio y Quiles, José L.
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, francesca.giampieri@uneatlantico.es, vivian.lipari@uneatlantico.es, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es, jose.quiles@uneatlantico.es
(2023)
Molecular Mechanisms of the Protective Effects of Olive Leaf Polyphenols against Alzheimer’s Disease.
International Journal of Molecular Sciences, 24 (5).
p. 4353.
ISSN 1422-0067
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Hafnia alvei is receiving increasing attention from both a medical and veterinary point of view, but the diversity of molecules it produces has made the interest in this bacterium extend to the field of probiotics, the microbiota, and above all, to its presence and action on consumer foods. The production of Acyl Homoserine Lactones (AHLs), a type of quorum-sensing (QS) signaling molecule, is the most often-studied chemical signaling molecule in Gram-negative bacteria. H. alvei can use this communication mechanism to promote the expression of certain enzymatic activities in fermented foods, where this bacterium is frequently present. H. alvei also produces a series of molecules involved in the modification of the organoleptic properties of different products, especially cheeses, where it shares space with other microorganisms. Although some strains of this species are implicated in infections in humans, many produce antibacterial compounds, such as bacteriocins, that inhibit the growth of true pathogens, so the characterization of these molecules could be very interesting from the point of view of clinical medicine and the food industry. Lastly, in some cases, H. alvei is responsible for the production of biogenic amines or other compounds of special interest in food health. In this article, we will review the most interesting molecules that produce the H. alvei strains and will discuss some of their properties, both from the point of view of their biological activity on other microorganisms and the properties of different food matrices in which this bacterium usually thrives.
metadata
Ramos Vivas, Jose; Tapia Martínez, Olga; Elexpuru Zabaleta, Maria; Tutusaus, Kilian; Armas Diaz, Yasmany; Battino, Maurizio y Giampieri, Francesca
mail
jose.ramos@uneatlantico.es, olga.tapia@uneatlantico.es, maria.elexpuru@uneatlantico.es, kilian.tutusaus@uneatlantico.es, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es, francesca.giampieri@uneatlantico.es
(2022)
The Molecular Weaponry Produced by the Bacterium Hafnia alvei in Foods.
Molecules, 27 (17).
p. 5585.
ISSN 1420-3049
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Therapeutic bacteriophages, commonly called as phages, are a promising potential alternative to antibiotics in the management of bacterial infections of a wide range of organisms including cultured fish. Their natural immunogenicity often induces the modulation of a variated collection of immune responses within several types of immunocytes while promoting specific mechanisms of bacterial clearance. However, to achieve standardized treatments at the practical level and avoid possible side effects in cultivated fish, several improvements in the understanding of their biology and the associated genomes are required. Interestingly, a particular feature with therapeutic potential among all phages is the production of lytic enzymes. The use of such enzymes against human and livestock pathogens has already provided in vitro and in vivo promissory results. So far, the best-understood phages utilized to fight against either Gram-negative or Gram-positive bacterial species in fish culture are mainly restricted to the Myoviridae and Podoviridae, and the Siphoviridae, respectively. However, the current functional use of phages against bacterial pathogens of cultured fish is still in its infancy. Based on the available data, in this review, we summarize the current knowledge about phage, identify gaps, and provide insights into the possible bacterial control strategies they might represent for managing aquaculture-related bacterial diseases.
metadata
Ramos-Vivas, José; Superio, Joshua; Galindo-Villegas, Jorge y Acosta, Félix
mail
jose.ramos@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2021)
Phage Therapy as a Focused Management Strategy in Aquaculture.
International Journal of Molecular Sciences, 22 (19).
p. 10436.
ISSN 1422-0067
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Presently, biopreservation through protective bacterial cultures and their antimicrobial products or using antibacterial compounds derived from plants are proposed as feasible strategies to maintain the long shelf-life of products. Another emerging category of food biopreservatives are bacteriophages or their antibacterial enzymes called “phage lysins” or “enzybiotics”, which can be used directly as antibacterial agents due to their ability to act on the membranes of bacteria and destroy them. Bacteriophages are an alternative to antimicrobials in the fight against bacteria, mainly because they have a practically unique host range that gives them great specificity. In addition to their potential ability to specifically control strains of pathogenic bacteria, their use does not generate a negative environmental impact as in the case of antibiotics. Both phages and their enzymes can favor a reduction in antibiotic use, which is desirable given the alarming increase in resistance to antibiotics used not only in human medicine but also in veterinary medicine, agriculture, and in general all processes of manufacturing, preservation, and distribution of food. We present here an overview of the scientific background of phages and enzybiotics in the food industry, as well as food applications of these biopreservatives.
metadata
Ramos Vivas, Jose; Elexpuru Zabaleta, Maria; Sámano Celorio, María Luisa; Pascual Barrera, Alina Eugenia; Forbes-Hernandez, Tamara Y.; Giampieri, Francesca y Battino, Maurizio
mail
jose.ramos@uneatlantico.es, maria.elexpuru@uneatlantico.es, marialuisa.samano@uneatlantico.es, alina.pascual@unini.edu.mx, tamara.forbes@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR
(2021)
Phages and Enzybiotics in Food Biopreservation.
Molecules, 26 (17).
p. 5138.
ISSN 1420-3049
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
β-Thalassemia is one of the dangerous causes of the high mortality rate in the Mediterranean countries. Substantial resources are required to save a β-Thalassemia carriers’ life and early detection of thalassemia patients can help appropriate treatment to increase the carrier’s life expectancy. Being a genetic disease, it can not be prevented however the analysis of several indicators in parents’ blood can be used to detect disorders causing Thalassemia. Laboratory tests for Thalassemia are time-consuming and expensive like high-performance liquid chromatography, Complete Blood Count (CBC) with peripheral smear, genetic test, etc. Red blood indices from CBC can be used with machine learning models for the same task. Despite the available approaches for Thalassemia carriers from CBC data, gaps exist between the desired and achieved accuracy. Moreover, the data imbalance problem is studied well which makes the models less generalizable. This study proposes a highly accurate approach for β-Thalassemia detection using red blood indices from CBC augmented by supervised machine learning. In view of the fact that all the features do not carry predictive information regarding the target variable, this study employs a unified framework of two features selection techniques including Principal Component Analysis (PCA) and Singular Vector Decomposition (SVD). The data imbalance between β-Thalassemia carrier and non-carriers is handled by Synthetic Minority Oversampling Technique (SMOTE) and Adaptive Synthetic (ADASYN). Extensive experiments are performed using many state-of-the-art machine learning models and deep learning models. Experimental results indicate the superiority of the proposed approach over existing approaches with an accuracy score of 0.96.
metadata
Rustam, Furqan; Ashraf, Imran; Jabbar, Shehbaz; Tutusaus, Kilian; Mazas Pérez-Oleaga, Cristina; Pascual Barrera, Alina Eugenia y de la Torre Diez, Isabel
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, kilian.tutusaus@uneatlantico.es, cristina.mazas@uneatlantico.es, alina.pascual@unini.edu.mx, SIN ESPECIFICAR
(2022)
Prediction β-Thalassemia carriers using complete blood count features.
Scientific Reports, 12 (1).
ISSN 2045-2322
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Background: Microalgae remove nutrients from wastewater with the possibility of grow in mixotrophic and heterotrophic cultures. However, the effluent quality can modify the profile of fatty acids and biodiesel quality. Methods: Phototrophic and mixotrophic (light / dark; 12/12 h) cultures of Scenedesmus obliquus on domestic wastewater (WW) and Artificial Wastewater (AW) was carried out to evaluate the lipid accumulation and fatty acid methyl esters profile. The microalgae was first cultivated in an enriched medium (90 mg N-NH4 L-1) and subsequently under nitrogen limitation (30, 20 and 10 mg N L-1) using a two-stage process for both culture media. Results: A higher cell density in enriched AW medium was obtained in phototrophic and mixotrophic culture of 19 x 106 cell mL-1 and 20 x 106 cell mL-1, respectively; than for WW (13 x 106 cell mL-1 and 14 x 106 cell mL-1, respectively). The nitrogen limitation (from 90 to 20 mg N L-1) for AW increased the lipid content by 5.0% and 17.28% under phototrophic and mixotrophic conditions, respectively and only 5% for WW in mixotrophic culture. Conclusion: The high Cetane Number (CN) show a positive correlation with high Saturated Fatty Acids (SFA) content and negative correlation with the Degree of Saturation (DU), suggesting a good ignition of fuel. The Cold Filter Plugging Point (CFPP) (-6.02 to -8.45 °C) and Oxidative Stability (OS) (3.53 - 6.6 h) propose to Scenedesmus obliquus as a candidate in the production of biodiesel and potential application for an integral urban wastewater treatment system. metadata Ruiz-Marin, Alejandro; Canedo-López, Yunuen; Narvaez-García, Asteria; Robles-Heredia, Juan Carlos y Zavala Loría, José del Carmen mail SIN ESPECIFICAR (2018) Productivity and Biodiesel Quality of Fatty Acids Contents from Scenedesmus obliquus in Domestic Wastewater Using Phototrophic and Mixotrophic Cultivation Systems. The Open Biotechnology Journal, 12 (1). pp. 229-240. ISSN 1874-0707
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Railway track faults may lead to railway accidents and cause human and financial loss. Spatial, temporal, and weather elements, and wear and tear, lead to ballast, loose nuts, misalignment, and cracks leading to accidents. Manual inspection of such defects is time-consuming and prone to errors. Automatic inspection provides a fast, reliable, and unbiased solution. However, highly accurate fault detection is challenging due to the lack of public datasets, noisy data, inefficient models, etc. To obtain better performance, this study presents a novel approach that relies on mel frequency cepstral coefficient features from acoustic data. The primary objective of this study is to increase fault detection performance. As well as designing an ensemble model, we utilize selective features using chi-square(chi2) that have high importance with respect to the target class. Extensive experiments were carried out to analyze the efficiency of the proposed approach. The experimental results suggest that using 60 features, 40 original features, and 20 chi2 features produces optimal results both regarding accuracy and computational complexity. A mean accuracy score of 0.99 was obtained using the proposed approach with machine learning models using the collected data. Moreover, this performance was significantly better than that of existing approaches; however, the performance of models may vary in real-world settings.
metadata
Rustam, Furqan; Ishaq, Abid; Hashmi, Muhammad Shadab Alam; Siddiqui, Hafeez Ur Rehman; Dzul Lopez, Luis; Castanedo Galán, Juan y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, luis.dzul@unini.edu.mx, juan.castanedo@uneatlantico.es, SIN ESPECIFICAR
(2023)
Railway Track Fault Detection Using Selective MFCC Features from Acoustic Data.
Sensors, 23 (16).
p. 7018.
ISSN 1424-8220
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
MANET is a mobile ad hoc network with many mobile nodes communicating without a centralized module. Infrastructure-less networks make it desirable for many researchers to publish and bind multimedia services. Each node in this infrastructure-less network acts as self-organizing and re-configurable. It allows services to deploy and attain from another node over the ad hoc network. The service composition aims to provide a user’s requirement by combining different atomic services based on non-functional QoS parameters such as reliability, availability, scalability, etc. To provide service composition in MANET is challenging because of the node mobility, link failure, and topology changes, so a traditional protocol will be sufficient to obtain real-time services from mobile nodes. In this paper, the ad hoc on-demand distance vector protocol (AODV) is used and analyzed based on MANET’s QoS (Quality of Service) metrics. The QoS metrics for MANET depends on delay, bandwidth, memory capacity, network load, and packet drop. The requester node and provider node broker acts as a composer for this MANET network. The authors propose a QoS-based Dynamic Secured Broker Selection architecture (QoSDSBS) for service composition in MANET, which uses a dynamic broker and provides a secure path selection based on QoS metrics. The proposed algorithm is simulated using Network Simulator (NS2) with 53 intermediate nodes and 35 mobile nodes of area 1000 m × 1000 m. The comparative results show that the proposed architecture outperforms, with standards, the AODV protocol and affords higher scalability and a reduced network load
metadata
Ramalingam, Rajakumar; Muniyan, Rajeswari; Dumka, Ankur; Singh, Devesh Pratap; Mohamed, Heba G.; Singh, Rajesh; Anand, Divya y Delgado Noya, Irene
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, irene.delgado@uneatlantico.es
(2022)
Routing Protocol for MANET Based on QoS-Aware Service Composition with Dynamic Secured Broker Selection.
Electronics, 11 (17).
p. 2637.
ISSN 2079-9292
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Software cost and effort estimation is one of the most significant tasks in the area of software engineering. Research conducted in this field has been evolving with new techniques that necessitate periodic comparative analyses. Software project success largely depends on accurate software cost estimation as it gives an idea of the challenges and risks involved in the development. The great diversity of ML and Non-ML techniques has generated a comparison and progressed into the integration of these techniques. Based on varying advantages it has become imperative to work out preferred estimation techniques to improve the project development process. This study aims to present a systematic literature review (SLR) to investigate the trends of the articles published in the recent one and a half decades and to propose a way forward. This systematic literature review has proposed a three-stage approach to plan (Tollgate approach), conduct (Likert type scale), and report the results from five renowned digital libraries. For the selected 52 articles, artificial neural network model (ANN) and constructive cost model (COCOMO) based approaches have been the favored techniques. The mean magnitude of relative error (MMRE) has been the preferred accuracy metric, software engineering, and project management are the most relevant fields, and the promise repository has been identified as the widely accessed database. This review is likely to be of value for the development, cost, and effort estimations.
metadata
Rashid, Chaudhary Hamza; Shafi, Imran; Ahmad, Jamil; Bautista Thompson, Ernesto; Masías Vergara, Manuel; Diez, Isabel De La Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, ernesto.bautista@unini.edu.mx, manuel.masias@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Software Cost and Effort Estimation: Current Approaches and Future Trends.
IEEE Access.
p. 1.
ISSN 2169-3536
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Guayaquil, Ecuador, is in a tropical area on the equatorial Pacific Ocean coast of South America. Since 2008 the city has been increasing its population, vehicle fleet and manufacturing industries. Within the city there are various industrial and urban land uses sharing the same space. With regard to air quality there is a lack of government information on it. Therefore, the research’s aim was to investigate the spatio-temporal characteristics of PM1 and PM2.5 concentrations and their main influencing factors. For this, both PM fractions were sampled and a bivariate analysis (cross-correlation and Pearson's correlation), multivariate linear and logistic regression analysis was applied. Hourly and daily PM1 and PM2.5 were the dependent variables, and meteorological variables, occurrence of events and characteristics of land use were the independent variables. We found 48% exceedances of the PM2.5-24 h World Health Organization 2021 threshold’s, which questions the city’s air quality. The cross-correlation function and Pearson’s correlation analysis indicate that hourly and daily temperature, relative humidity, and wind speed have a complex nonlinear relationship with PM concentrations. Multivariate linear and logistic regression models for PM1-24 h showed that rain and the flat orography of cement plant sector decrease concentrations; while unusual PM emission events (traffic jams and vegetation-fires) increase them. The same models for PM2.5-24 h show that the dry season and the industrial sector (strong activity) increase the concentration of PM2.5-24 h, and the cement plant decrease them. Public policies and interventions should aim to regulate land uses while continuously monitoring emission sources, both regular and unusual. metadata Rincon Polo, Gladys; Morantes, Giobertti; Roa-López, Heydi; Cornejo-Rodriguez, Maria del Pilar; Jones, Benjamin y Cremades, Lázaro V. mail SIN ESPECIFICAR (2022) Spatio-temporal statistical analysis of PM1 and PM2.5 concentrations and their key influencing factors at Guayaquil city, Ecuador. Stochastic Environmental Research and Risk Assessment. ISSN 1436-3240
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Se propone el diseño de una estrategia metodológica compuesta por modelos computacionales, tecnología musical y reglas básicas de composición armónica. La estrategia integra diferentes herramientas como lenguajes de programación, diseño y reutilización de algoritmos y librerías para la extracción de características fuertes a las muestras producidas por un intérprete, así como la ejecución de procesos estocásticos discretos que generan melodías acotadas por reglas básicas de composición de música Pop. Los fragmentos generados son convertidos en series que posteriormente son reproducidos de forma controlada, por un dispositivo MIDI (Musical Instrument Digital Interface). Para garantizar la integración de todos los elementos como un sistema que genera iteraciones, se utilizan protocolos de control abierto entre lenguajes de programación y herramientas que permiten la interconexión y comunicación entre los diferentes componentes tecnológicos que conforman la estrategia. Una vez concluido el proceso de generación de fragmentos melódicos, estos son transmitidos a un gestor de audio y copiados en cada canal del gestor en un formato de tipo estándar MIDI. metadata Rodriguez, Carlos Alberto; López-Pelaez, Maria Paz y Arambarri, Jon mail SIN ESPECIFICAR, SIN ESPECIFICAR, jon.arambarri@uneatlantico.es (2020) Una estrategia metodológica para la optimización de procesos de producción de música POP, basada en modelos computacionales. Project Design and Management, 2 (2). pp. 23-42. ISSN 2603-5820
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
White blood cell (WBC) type classification is a task of significant importance for diagnosis using microscopic images of WBC, which develop immunity to fight against infections and foreign substances. WBCs consist of different types, and abnormalities in a type of WBC may potentially represent a disease such as leukemia. Existing studies are limited by low accuracy and overrated performance, often caused by model overfit due to an imbalanced dataset. Additionally, many studies consider a lower number of WBC types, and the accuracy is exaggerated. This study presents a hybrid feature set of selective features and synthetic minority oversampling technique-based resampling to mitigate the influence of the above-mentioned problems. Furthermore, machine learning models are adopted for being less computationally complex, requiring less data for training, and providing robust results. Experiments are performed using both machine- and deep learning models for performance comparison using the original dataset, augmented dataset, and oversampled dataset to analyze the performances of the models. The results suggest that a hybrid feature set of both texture and RGB features from microscopic images, selected using Chi2, produces a high accuracy of 0.97 with random forest. Performance appraisal using k-fold cross-validation and comparison with existing state-of-the-art studies shows that the proposed approach outperforms existing studies regarding the obtained accuracy and computational complexity.
metadata
Rustam, Furqan; Aslam, Naila; De La Torre Díez, Isabel; Khan, Yaser Daanial; Vidal Mazón, Juan Luis; Rodríguez Velasco, Carmen Lilí y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR
(2022)
White Blood Cell Classification Using Texture and RGB Features of Oversampled Microscopic Images.
Healthcare, 10 (11).
p. 2230.
ISSN 2227-9032
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Video content on the web platform has increased explosively during the past decade, thanks to the open access to Facebook, YouTube, etc. YouTube is the second-largest social media platform nowadays containing more than 37 million YouTube channels. YouTube revealed at a recent press event that 30,000 new content videos per hour and 720,000 per day are posted. There is a need for an advanced deep learning-based approach to categorize the huge database of YouTube videos. This study aims to develop an artificial intelligence-based approach to categorize YouTube videos. This study analyzes the textual information related to videos like titles, descriptions, user tags, etc. using YouTube exploratory data analysis (YEDA) and shows that such information can be potentially used to categorize videos. A deep convolutional neural network (DCNN) is designed to categorize YouTube videos with efficiency and high accuracy. In addition, recurrent neural network (RNN), and gated recurrent unit (GRU) are also employed for performance comparison. Moreover, logistic regression, support vector machines, decision trees, and random forest models are also used. A large dataset with 9 classes is used for experiments. Experimental findings indicate that the proposed DCNN achieves the highest receiver operating characteristics (ROC) area under the curve (AUC) score of 99% in the context of YouTube video categorization and 96% accuracy which is better than existing approaches. The proposed approach can be used to help YouTube users suggest relevant videos and sort them by video category.
metadata
Raza, Ali; Younas, Faizan; Siddiqui, Hafeez Ur Rehman; Rustam, Furqan; Gracia Villar, Mónica; Silva Alvarado, Eduardo René y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, monica.gracia@uneatlantico.es, eduardo.silva@funiber.org, SIN ESPECIFICAR
(2024)
An improved deep convolutional neural network-based YouTube video classification using textual features.
Heliyon, 10 (16).
e35812.
ISSN 24058440
Tesis
Materias > Educación
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster
Cerrado
Inglés
Teaching pronunciation is a very difficult task within the public schooling system in Ecuador, because Pronunciation alone has not been taken into consideration in many ways. Learners are memorizing words and phrases and teachers do not feel comfortable teaching pronunciation because they have no preparation in the field.We need to change the teaching-learning process in order to provide better opportunities to our students.
metadata
Rosales Villalva, Karem Victoria
mail
kvr9918@hotmail.com
(2022)
A research on Teaching Pronunciation and Evaluation in the Public Education System in Ecuador.
Masters thesis, Universidad Internacional Iberoamericana México.
S
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Varias organizaciones y profesionales de la gestión de proyectos centran su atención en el desempeño en la realización de proyectos. Durante varios años, Camerún se ha dedicado a la realización de grandes proyectos de construcción potencialmente comparables a megaproyectos, como el proyecto de construcción del segundo puente sobre el Wouri. El objetivo general de este estudio fue analizar el nivel de desempeño del proyecto para construir el segundo puente sobre el Wouri. Esta investigación se desarrolló a partir de un enfoque cualitativo por un lado y un enfoque cuantitativo por el otro. Esta investigación eligió la entrevista semiestructurada a través de un cuestionario y la investigación documental como instrumentos de recolección de datos. Los participantes estaban compuestos por un representante de la autoridad contratante, un representante del propietario del proyecto, un representante del jefe del servicio contratado, un representante del ingeniero contratado, un representante del asistente del propietario del proyecto y dos representantes de la empresa que realiza el trabajo. Los datos recopilados se analizaron utilizando el software de análisis de datos Statistical Package for the Social Sciences (SPSS) y el software EXCEL. Parece que no se cumplieron los plazos y costes de ejecución, pero se cumplió el nivel de calidad inicialmente previsto. Los resultados de esta investigación son similares a los hallazgos de OPS (2011), Standish group (2018) y PMI (2015) en cuanto a investigaciones sobre el desempeño de proyectos con alto porcentaje de fallas en megaproyectos. metadata Song, Antoinette y Momo Kountchou, Arthur mail SIN ESPECIFICAR (2022) Análisis del nivel de rendimiento de megaprojets en Camerún: caso del proyecto de construcción del segundo puente sobre el Wouri = Analysis of the performance level of megaprojects in Cameroon: the case of the second wouri bridge construction project. Project Design and Management, 4 (2). ISSN 2683-1597
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
In the last decade, artificial intelligence (AI) and AI-mediated technologies have undergone rapid evolution in healthcare and medicine, from apps to computer software able to analyze medical images, robotic surgery and advanced data storage system. The main aim of the present commentary is to briefly describe the evolution of AI and its applications in healthcare, particularly in nutrition and clinical biochemistry. Indeed, AI is revealing itself to be an important tool in clinical nutrition by using telematic means to self-monitor various health metrics, including blood glucose levels, body weight, heart rate, fat percentage, blood pressure, activity tracking and calorie intake trackers. In particular, the application of the most common digital technologies used in the field of nutrition as well as the employment of AI in the management of diabetes and obesity, two of the most common nutrition-related pathologies worldwide, will be presented.
metadata
Salinari, Alessia; Machì, Michele; Armas Diaz, Yasmany; Cianciosi, Danila; Qi, Zexiu; Yang, Bei; Ferreiro Cotorruelo, Maria Soledad; Gracia Villar, Santos; Dzul López, Luis Alonso; Battino, Maurizio y Giampieri, Francesca
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, maurizio.battino@uneatlantico.es, francesca.giampieri@uneatlantico.es
(2023)
The Application of Digital Technologies and Artificial Intelligence in Healthcare: An Overview on Nutrition Assessment.
Diseases, 11 (3).
p. 97.
ISSN 2079-9721
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Chronic obstructive pulmonary disease (COPD) is a severe and chronic ailment that is currently ranked as the third most common cause of mortality across the globe. COPD patients often experience debilitating symptoms such as chronic coughing, shortness of breath, and fatigue. Sadly, the disease frequently goes undiagnosed until it is too late, leaving patients without the care they desperately need. So, COPD detection at an early stage is crucial to prevent further damage to the lungs and improve quality of life. Traditional COPD detection methods often rely on physical examinations and tests such as spirometry, chest radiography, blood gas tests, and genetic tests. However, these methods may not always be accurate or accessible. One of the key vital signs for detecting COPD is the patient’s respiration rate. However, it is crucial to consider a patient’s medical and demographic characteristics simultaneously for better detection results. To address this issue, this study aims to detect COPD patients using artificial intelligence techniques. To achieve this goal, a novel framework is proposed that utilizes ultra-wideband (UWB) radar-based temporal and spectral features to build machine learning and deep learning models. This new set of temporal and spectral features is extracted from respiration data collected non-invasively from 1.5 m distance using UWB radar. Different machine learning and deep learning models are trained and tested on the collected dataset. The findings are promising, with a high accuracy score of 100% for COPD detection. This means that the proposed framework could potentially save lives by identifying COPD patients at an early stage. The k-fold cross-validation technique and performance comparison with the state-of-the-art studies are applied to validate its performance, ensuring that the results are robust and reliable. The high accuracy score achieved in the study implies that the proposed framework has the potential for the efficient detection of COPD at an early stage.
metadata
Siddiqui, Hafeez-Ur-Rehman; Raza, Ali; Saleem, Adil Ali; Rustam, Furqan; Díez, Isabel de la Torre; Gavilanes Aray, Daniel; Lipari, Vivian; Ashraf, Imran y Dudley, Sandra
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, daniel.gavilanes@uneatlantico.es, vivian.lipari@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
An Approach to Detect Chronic Obstructive Pulmonary Disease Using UWB Radar-Based Temporal and Spectral Features.
Diagnostics, 13 (6).
p. 1096.
ISSN 2075-4418
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The precise prediction of power estimates of wind–solar renewable energy sources becomes challenging due to their intermittent nature and difference in intensity between day and night. Machine-learning algorithms are non-linear mapping functions to approximate any given function from known input–output pairs and can be used for this purpose. This paper presents an artificial neural network (ANN)-based method to predict hybrid wind–solar resources and estimate power generation by correlating wind speed and solar radiation for real-time data. The proposed ANN allows optimization of the hybrid system’s operation by efficient wind and solar energy production estimation for a given set of weather conditions. The proposed model uses temperature, humidity, air pressure, solar radiation, optimum angle, and target values of known wind speeds, solar radiation, and optimum angle. A normalization function to narrow the error distribution and an iterative method with the Levenberg–Marquardt training function is used to reduce error. The experimental results show the effectiveness of the proposed approach against the existing wind, solar, or wind–solar estimation methods. It is envisaged that such an intelligent yet simplified method for predicting wind speed, solar radiation, and optimum angle, and designing wind–solar hybrid systems can improve the accuracy and efficiency of renewable energy generation.
metadata
Shafi, Imran; Khan, Harris; Farooq, Muhammad Siddique; Diez, Isabel de la Torre; Miró Vera, Yini Airet; Castanedo Galán, Juan y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, yini.miro@uneatlantico.es, juan.castanedo@uneatlantico.es, SIN ESPECIFICAR
(2023)
An Artificial Neural Network-Based Approach for Real-Time Hybrid Wind–Solar Resource Assessment and Power Estimation.
Energies, 16 (10).
p. 4171.
ISSN 1996-1073
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Breast cancer is prevalent in women and the second leading cause of death. Conventional breast cancer detection methods require several laboratory tests and medical experts. Automated breast cancer detection is thus very important for timely treatment. This study explores the influence of various feature selection technique to increase the performance of machine learning methods for breast cancer detection. Experimental results shows that use of appropriate features tend to show highly accurate prediction
metadata
Shafique, Rahman; Rustam, Furqan; Choi, Gyu Sang; Díez, Isabel de la Torre; Mahmood, Arif; Lipari, Vivian; Rodríguez Velasco, Carmen Lilí y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, vivian.lipari@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR
(2023)
Breast Cancer Prediction Using Fine Needle Aspiration Features and Upsampling with Supervised Machine Learning.
Cancers, 15 (3).
p. 681.
ISSN 2072-6694
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Developments in medical care have inspired wide interest in the current decade, especially to their services to individuals living prolonged and healthier lives. Alzheimer’s disease (AD) is the most chronic neurodegeneration and dementia-causing disorder. Economic expense of treating AD patients is expected to grow. The requirement of developing a computer-aided technique for early AD categorization becomes even more essential. Deep learning (DL) models offer numerous benefits against machine learning tools. Several latest experiments that exploited brain magnetic resonance imaging (MRI) scans and convolutional neural networks (CNN) for AD classification showed promising conclusions. CNN’s receptive field aids in the extraction of main recognizable features from these MRI scans. In order to increase classification accuracy, a new adaptive model based on CNN and support vector machines (SVM) is presented in the research, combining both the CNN’s capabilities in feature extraction and SVM in classification. The objective of this research is to build a hybrid CNN-SVM model for classifying AD using the MRI ADNI dataset. Experimental results reveal that the hybrid CNN-SVM model outperforms the CNN model alone, with relative improvements of 3.4%, 1.09%, 0.85%, and 2.82% on the testing dataset for AD vs. cognitive normal (CN), CN vs. mild cognitive impairment (MCI), AD vs. MCI, and CN vs. MCI vs. AD, respectively. Finally, the proposed approach has been further experimented on OASIS dataset leading to accuracy of 86.2%.
metadata
Sethi, Monika; Rani, Shalli; Singh, Aman; Vidal Mazón, Juan Luis y Bhatia, Surbhi
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, juanluis.vidal@uneatlantico.es, SIN ESPECIFICAR
(2022)
A CAD System for Alzheimer’s Disease Classification Using Neuroimaging MRI 2D Slices.
Computational and Mathematical Methods in Medicine, 2022.
pp. 1-11.
ISSN 1748-670X
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Background: Cardiovascular diseases (CVDs) encompass a variety of conditions that affect the heart and blood vessels. Carotenoids, a group of fat-soluble organic pigments synthesized by plants, fungi, algae, and some bacteria, may have a beneficial effect in reducing cardiovascular disease (CVD) risk. This study aims to examine and synthesize current research on the relationship between carotenoids and CVDs. Methods: A systematic review was conducted using MEDLINE and the Cochrane Library to identify relevant studies on the efficacy of carotenoid supplementation for CVD prevention. Interventional analytical studies (randomized and non-randomized clinical trials) published in English from January 2011 to February 2024 were included. Results: A total of 38 studies were included in the qualitative analysis. Of these, 17 epidemiological studies assessed the relationship between carotenoids and CVDs, 9 examined the effect of carotenoid supplementation, and 12 evaluated dietary interventions. Conclusions: Elevated serum carotenoid levels are associated with reduced CVD risk factors and inflammatory markers. Increasing the consumption of carotenoid-rich foods appears to be more effective than supplementation, though the specific effects of individual carotenoids on CVD risk remain uncertain.
metadata
Sumalla Cano, Sandra; Eguren García, Imanol; Lasarte García, Álvaro; Prola, Thomas; Martínez Díaz, Raquel y Elío Pascual, Iñaki
mail
sandra.sumalla@uneatlantico.es, imanol.eguren@uneatlantico.es, SIN ESPECIFICAR, thomas.prola@uneatlantico.es, raquel.martinez@uneatlantico.es, inaki.elio@uneatlantico.es
(2024)
Carotenoids Intake and Cardiovascular Prevention: A Systematic Review.
Nutrients, 16 (22).
p. 3859.
ISSN 2072-6643
Artículo Materias > Psicología Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español, Portugués Las relaciones de trabajo marítimo en un entorno de la industria petrolera en alta mar han sido estudiadas recientemente, pero las organizaciones de embarcaciones de apoyo marítimo no tienen ningún destaque. Estas cumplen con una misión de soporte en esta industria, teniendo sus tripulantes en confinamiento y bajo otras situaciones desgastantes. Esto se presenta como un escenario, donde se presume que existen muchos conflictos organizacionales. Metodología. En un estudio de caso, que tendrán sus relaciones de trabajo en las embarcaciones colocadas a la luz de la "Taxonomía de Conflictos Organizacionales según su Ámbito de actuación" desarrollada por Armadans, Vega y Sacristán (2016). Se utilizó el análisis contenido para identificación de evidencias empíricas, dentro de un aporte bibliográfico pautado por revisión bibliográfica digital, en fuentes primarias para la selección de los textos científicos que pudieran describir las situaciones y rutinas de trabajo a bordo. Recopilada en 07/07/2018, la base de datos de Google Académico escrito en portugués, la sintaxis de búsqueda de "conflictos de organización" en el período 2017 y 2018, y "apoyo marítimo" en el período de 2014 a 2018. Resultados. Con las evidencias empíricas fue posible la categorización de los conflictos organizacionales. Los dos más destacados conflictos organizacionales presentes son los vinculados a la estructura organizacional y los por competición individual por recursos escasos. Discusión. Se comprueba la necesidad del compromiso de la Alta Dirección para una mejor gestión de conflictos a bordo de embarcaciones, con aplicación de métodos de resolución de conflictos. Se presentan sugerencias de mitigación y aprovechamiento de los conflictos, así como las limitaciones del estudio. metadata Sant´Anna Maciel, Monica Pires y Maciel Pereira, Jose Antonio mail SIN ESPECIFICAR (2019) Categorización de los conflictos organizacionales en embarcaciones de apoyo marítimo brasileñas. MLS Psychology Research, 2 (1). pp. 27-44. ISSN 26055295
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés In recent years, nanotechnology and materials science have evolved and matured, making it increasingly easier to design and fabricate next-generation 3D microelectronics. The process has changed drastically from traditional 2D microelectronics, resulting in improved performance, higher integration density, and new functionalities. As applications become more complex and power-intensive, this technology can address the demands of high-performance computing, advanced sensors, and cutting-edge communication systems via wearable, flexible devices, etc. To manufacture higher-density microelectronics, recent advances in the fabrication of such 3D devices are discussed. Furthermore, the paper stresses the importance of novel materials and architectures, such as monolithic 3D integration and heterogeneous integration, in overcoming these challenges. We emphasize the importance of addressing complex issues to achieve better performance and higher integration density, which will play an important role in shaping the next generation of microelectronic devices. The multifaceted challenges involved in developing next-generation 3D microelectronic devices are also highlighted. metadata Singh, Niharika; Srivastava, Kingshuk; Kumar, Ajay; Yadav, Neha; Yadav, Ashish; Dubey, Santosh; Singh, Rajesh; Gehlot, Anita; Verma, Ajay Singh; Gupta, Neha; Kumar, Tanuj; Wu, Yongling; Hongyu, Zheng; Mondal, Aniruddha; Pandey, Kailash; Brajpuriya, Ranjeet; Kumar, Shalendra y Gupta, Rajeev mail SIN ESPECIFICAR (2024) Challenges and opportunities in engineering next-generation 3D microelectronic devices: improved performance and higher integration density. Nanoscale Advances, 6 (24). pp. 6044-6060. ISSN 2516-0230
Artículo
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The aim of this study was to evaluate the influence of the lockdown due to the COVID-19 pandemic, on eating and physical activity behavior, in a university population. A healthy diet such as the Mediterranean Diet (MD) pattern, rich in fruit and vegetables, can prevent degenerative diseases such as obesity, diabetes, cardiovascular diseases, etc. We conducted a cross-sectional study and data were collected by an anonymous online questionnaire. Participants completed a survey consisting of 3 sections: sociodemographic data; dietary behavior and physical activity; the Mediterranean Diet questionnaire (MEDAS-14) and the Emotional Eater Questionnaire (EEQ). A total of 168 participants completed the questionnaire: 66.7% were women, 79.2% were from Spain, 76.8% were students, 76.2% lived in their family home and 66.1% were of normal weight. During lockdown our population shopped for groceries 1 time or less per week (76.8%); maintained the same consumption of fruits (45.2%), vegetables (50.6%), dairy products (61.9%), pulses (64.9%), fish/seafood (57.7%), white meat (77.4%), red and processed meat (71.4%), pastries and snacks (48.2%), rice/pasta/potatoes (70.2%) and nuts (62.5%), spirits (98.8%) and sugary drinks (91.7%). Cooking time increased (73.2%) and the consumption decreased of low alcohol drinks (60.1%), spirits (75%) and sugary drinks (57.1%), and physical activity also diminished (49.4%). University Employees (UE) gained more weight (1.01 ± 0.02) than students (0.99 ± 0.03) (p < 0.05) during the confinement period. A total of 79.8% of the participants obtained a Medium/High Adherence to the MD during lockdown. Emotional and very emotional eaters were higher in the female group (p < 0.01). In the event of further confinement, strategies should be implemented to promote a balanced and healthy diet together with the practice of physical activity, taking special care of the female and UE groups.
metadata
Sumalla Cano, Sandra; Forbes-Hernández, Tamara; Aparicio-Obregón, Silvia; Crespo-Álvarez, Jorge; Elexpuru Zabaleta, Maria; Gracia Villar, Mónica; Giampieri, Francesca y Elío Pascual, Iñaki
mail
sandra.sumalla@uneatlantico.es, SIN ESPECIFICAR, silvia.aparicio@uneatlantico.es, jorge.crespo@uneatlantico.es, maria.elexpuru@uneatlantico.es, monica.gracia@uneatlantico.es, francesca.giampieri@uneatlantico.es, inaki.elio@uneatlantico.es
(2022)
Changes in the Lifestyle of the Spanish University Population during Confinement for COVID-19.
International Journal of Environmental Research and Public Health, 19 (4).
p. 2210.
ISSN 1660-4601
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Currently, multilevel inverters with an induction motor as a load are widely used in the industry. Therefore, there has been an increase in the number of studies related to the analysis of the advantages and disadvantages that are presented in the set: multilevel inverter + induction motor (MLI+IM). Exist several multilevel inverter topologies and different modulation techniques for these inverters, so it is very difficult to select the most suitable combination to improve the operating conditions of the set. This paper presents a comparative analysis of the behavior of the electrical and mechanical parameters in the set: multilevel inverter + induction motor, using four different pulse width modulation techniques to generate the switching states for the power semiconductor devices in a three-phase, seven-level cascade multilevel inverter. The objective of the comparison is to identify the modulation strategy with the best performance for the conditions established in this study. metadata Severiano, Yesenia; Alquicira, Jesús; De León Aldaco, Susana Estefany y Santos, Luis mail SIN ESPECIFICAR (2020) Comparative Analysis of PWM Techniques in the Set: Multilevel Inverter + Induction Motor. European Journal of Electrical Engineering, 22 (2). pp. 111-117. ISSN 21033641
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Artificial intelligence has made substantial progress in medicine. Automated dental imaging interpretation is one of the most prolific areas of research using AI. X-ray and infrared imaging systems have enabled dental clinicians to identify dental diseases since the 1950s. However, the manual process of dental disease assessment is tedious and error-prone when diagnosed by inexperienced dentists. Thus, researchers have employed different advanced computer vision techniques, and machine- and deep-learning models for dental disease diagnoses using X-ray and near-infrared imagery. Despite the notable development of AI in dentistry, certain factors affect the performance of the proposed approaches, including limited data availability, imbalanced classes, and lack of transparency and interpretability. Hence, it is of utmost importance for the research community to formulate suitable approaches, considering the existing challenges and leveraging findings from the existing studies. Based on an extensive literature review, this survey provides a brief overview of X-ray and near-infrared imaging systems. Additionally, a comprehensive insight into challenges faced by researchers in the dental domain has been brought forth in this survey. The article further offers an amalgamative assessment of both performances and methods evaluated on public benchmarks and concludes with ethical considerations and future research avenues.
metadata
Shafi, Imran; Fatima, Anum; Afzal, Hammad; Díez, Isabel de la Torre; Lipari, Vivian; Breñosa, Jose y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, vivian.lipari@uneatlantico.es, josemanuel.brenosa@uneatlantico.es, SIN ESPECIFICAR
(2023)
A Comprehensive Review of Recent Advances in Artificial Intelligence for Dentistry E-Health.
Diagnostics, 13 (13).
p. 2196.
ISSN 2075-4418
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Monitoring tool conditions and sub-assemblies before final integration is essential to reducing processing failures and improving production quality for manufacturing setups. This research study proposes a real-time deep learning-based framework for identifying faulty components due to malfunctioning at different manufacturing stages in the aerospace industry. It uses a convolutional neural network (CNN) to recognize and classify intermediate abnormal states in a single manufacturing process. The manufacturing process for aircraft factory products comprises different phases; analyzing the components after the integration is labor-intensive and time-consuming, which often puts the company’s stake at high risk. To overcome these challenges, the proposed AI-based system can perform inspection and defect detection and alleviate the probability of components’ needing to be re-manufacturing after being assembled. In addition, it analyses the impact value, i.e., rework delays and costs, of manufacturing processes using a statistical process control tool on real-time data for various manufactured components. Defects are detected and classified using the CNN and teachable machine in the single manufacturing process during the initial stage prior to assembling the components. The results show the significance of the proposed approach in improving operational cost management and reducing rework-induced delays. Ground tests are conducted to calculate the impact value followed by the air tests of the final assembled aircraft. The statistical results indicate a 52.88% and 34.32% reduction in time delays and total cost, respectively.
metadata
Shafi, Imran; Mazhar, Muhammad Fawad; Fatima, Anum; Álvarez, Roberto Marcelo; Miró Vera, Yini Airet; Martínez Espinosa, Julio César y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, roberto.alvarez@uneatlantico.es, yini.miro@uneatlantico.es, ulio.martinez@unini.edu.mx, SIN ESPECIFICAR
(2023)
Deep Learning-Based Real Time Defect Detection for Optimization of Aircraft Manufacturing and Control Performance.
Drones, 7 (1).
p. 31.
ISSN 2504-446X
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
The classification of bird species is of significant importance in the field of ornithology, as it plays an important role in assessing and monitoring environmental dynamics, including habitat modifications, migratory behaviors, levels of pollution, and disease occurrences. Traditional methods of bird classification, such as visual identification, were time-intensive and required a high level of expertise. However, audio-based bird species classification is a promising approach that can be used to automate bird species identification. This study aims to establish an audio-based bird species classification system for 264 Eastern African bird species employing modified deep transfer learning. In particular, the pre-trained EfficientNet technique was utilized for the investigation. The study adapts the fine-tune model to learn the pertinent patterns from mel spectrogram images specific to this bird species classification task. The fine-tuned EfficientNet model combined with a type of Recurrent Neural Networks (RNNs) namely Gated Recurrent Unit (GRU) and Long short-term memory (LSTM). RNNs are employed to capture the temporal dependencies in audio signals, thereby enhancing bird species classification accuracy. The dataset utilized in this work contains nearly 17,000 bird sound recordings across a diverse range of species. The experiment was conducted with several combinations of EfficientNet and RNNs, and EfficientNet-B7 with GRU surpasses other experimental models with an accuracy of 84.03% and a macro-average precision score of 0.8342.
metadata
Shaikh, Asadullah; Baowaly, Mrinal Kanti; Sarkar, Bisnu Chandra; Walid, Md. Abul Ala; Ahamad, Md. Martuza; Singh, Bikash Chandra; Silva Alvarado, Eduardo René; Ashraf, Imran y Samad, Md. Abdus
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, eduardo.silva@funiber.org, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Deep transfer learning-based bird species classification using mel spectrogram images.
PLOS ONE, 19 (8).
e0305708.
ISSN 1932-6203
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés The collection of water is proposed from the design of contour borders and half moons, green infrastructure measures, to reduce surface runoff and increase the availability of water for vegetation. The contour and crescent ridges have land ridges with a trapezoidal section, which follow the contour lines, to compartmentalize the slope into smaller hydrological units, the ends of which are located on contour lines. With the data of maximum rainfall every 24 hours and parameters of Gumbel's Law modified, the equations of maximum daily rainfall height (hdT), rainfall height for a duration ´´t´´ (htT), and the Intensity Duration Frequency curve (ItT), for a duration of t <2h. Then considering the values of basic infiltration, vegetation cover, soil type and hydrological condition, the curve numbers were determined for different soil moisture conditions, later the separation length (L) between the Half Moons, and the borders was calculated. in contour, which were designed by means of 10 configurations between diameter and height, for the two infrastructures, being in Copacabana Valle, the greatest separation distance. metadata Schmidt-Gomez, Armando; Olivares-Ramírez, Juan Manuel; Ferriol-Sánchez, Fermín y Marroquín-De Jesús, Ángel mail SIN ESPECIFICAR (2021) Design of edges in contour and half moons from edaphoclimatic parameters, for the endorrheic basin of lagunas de tajzara - ramsar site 1030. Journal of Research and Development, 7 (19). pp. 1-8. ISSN 2444-4987
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Esta investigación pretende determinar la existencia o no de componentes orgánicos a partir del análisis en fragmentos de morteros del convento de San Diego localizado en el centro histórico de la ciudad de Quito - Ecuador; se realizó la investigación de nueve (9) muestras de morteros tomadas de la edificación que corresponde a la época colonial, las muestras son: de adobe, mortero de pisos y enlucidos, estos fragmentos corresponden a diferentes periodos de construcción que van desde: 1597 a 1700; la presente investigación determinó que en los morteros analizados hay la presencia del mucílago de nopal. Para realizar una valoración se obtuvieron patrones del mucilago, para esto se tomaron dos muestras de la baba de nopal: la primera muestra fue obtenida a temperatura ambiente, la misma que al tacto es ligera y pegajosa, y la segunda muestra fue extraída por medio de cocción a una temperatura de entre 90 a 100 C°, esta al tacto es mucho más densa y adherente. Así mismo, el uso de la cal fue añadido comparando la acción de la cal viva, respecto a la cal apagada (ahogada) lo que genera plasticidad adicional en el material. Con estos patrones se realizó la comparación del patrón obtenido de los morteros antiguos, como resultado se obtuvo que los patrones que coinciden entre sí son los espectros obtenido por cocción con el obtenido de los morteros antiguos, lo que determina que se utilizó el mucilago de nopal en la construcción en la época colonial. metadata Silva Cascante, Angel Vicente; Uría Cevallos, Guadalupe Del Rosario y Vásquez Mora, Carlos Andrés mail SIN ESPECIFICAR (2020) Determinación del uso del mucilago de nopal en la construcción de la época colonial (caso Convento de San Diego). Project Design and Management, 2 (2). pp. 95-118. ISSN 2683-1597
Artículo
Materias > Ciencias Sociales
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
This research aims to gather opinions from experts in the European tourism sector regarding training needs to address severe crises, such as Covid, in Small and Medium-Sized Enterprises (SMEs) across five countries: Spain, Iceland, Ireland, Scotland, and Germany. This study was conducted within the scope of the European TC-NAV project, which is funded by the European Union. The ultimate goal of this project is to develop training solutions for European SMEs Most existing literature on tourism crises primarily examines the impact on destinations as a whole rather than on individual tourism enterprises. Thus, this research is both relevant and timely The methodology employed was qualitative, and data being collected using a 9-question interview guide. This guide underwent validation by experts, achieving a Cronbach's Alpha value of 0.7. In total, 30 individuals were interviewed: 5 civil servants, 9 company directors, 5 university professors, 6 researchers, and 5 entrepreneurs. Some notable findings include the importance of innovation for change, promoting sustainable tourism, fostering informal partnerships among regional companies, the essential role of government support, the benefits of flexible planning and service digitisation, and the ongoing need for training and upskilling.
metadata
Soriano Flores, Emmanuel; Prola, Thomas; Halldórsdóttir, Íris Hrund Halldórsdóttir y Taylor, Steve
mail
emmanuel.soriano@uneatlantico.es, thomas.prola@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Diagnosing Training Needs in European Tourism SMEs: The TC-NAV Project for Managing and Overcoming Virulent Crises.
Kurdish Studies, 11 (2).
pp. 2011-2022.
ISSN 2051-4883
Artículo
Materias > Educación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The United Nations Educational, Scientific, and Cultural Organization (UNESCO) highlights the relevance of using information and communications technology (ICT) in education for improving the quality of education. To achieve this goal, it is necessary to extend research on digital competences in education. To advance the development of digital competencies it is necessary to take account of how teachers perceive these. In addition, systematic reviews of the literature on ICT and education show an imbalance regarding the amount of research from Africa compared to other regions of the world. In this sense, the objective of this study carried out between March 2019 and April 2020 was to analyse the perceptions of primary school teachers from 8 African countries about their digital competences. The teachers were master’s students in teacher training on virtual platforms. A mixed methodological perspective (quantitative-qualitative) was adopted and a questionnaire with closed and open-ended questions was applied. The quantitative and qualitative analyses show that the teachers recognised their digital competence at all 3 levels. The needs highlighted by teachers were in developing their knowledge of how to create content with the support of technology. However, the available resources, which differed in the participants’ work contexts and did not enable the equal use of ICT in all African countries, was an important issue highlighted by the participants. It is recommended that teacher training in digital competence is prepared using instructional design that promotes innovation and contact with real teaching-learning situations.
metadata
Sartor-Harada, Andresa; Azevedo-Gomes, Juliana; Ulloa-Guerra, Oscar; Ruiz Salces, Roberto y Calderón Iglesias, Rubén
mail
andresa.sartor@uneatlantico.es, juliana.azevedo@uneatlantico.es, oscar.ulloa@uneatlantico.es, roberto.ruiz@uneatlantico.es, ruben.calderon@uneatlantico.es
(2022)
Digital competencies: perceptions of primary school teachers pursuing master’s degrees from eight African countries.
SA Journal of Education, 42 (3).
ISSN 2076-3433
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Cerrado
Inglés
The Internet of Things (IoT) is a revolutionary technique of sharing data for smart devices that generates huge amounts of data from smart healthcare systems. Therefore, healthcare systems utilize the convergence power and traffic analysis of sensors that cannot be satisfactorily handled by the IoT. In this article, a novel mutation operator is devised and incorporated with the differential evolution (DE) algorithm. Two tests have been conducted in the validation process. Firstly, the newly dual adaption-based operators incorporated with the differential evolution algorithm are being proposed. The proposed approach provides sufficient diversity and enhances the search speed of nature’s local and global search environments in the problem. The proposed method incorporates the application of IoT-based smart healthcare. Second, an application-based test has been conducted, in which the proposed approach is applied to the application in the smart healthcare system. Therefore, IoT sensor deployment is an optimization problem to minimize service time, delay, and energy loss by considering the communication constraint between sensors(objects). The proposed algorithm is applied in this article to solve this optimization problem. Further, in the experimentation and comparative study, the proposed method is superior to the standard evolutionary algorithms in IoT applications concerning the minimum number of function evaluations and minimization of traffic services. The proposed approach also achieves efficiency in the minimum loss of energy in each service and reduces load and delay
metadata
Singh, Shailendra Pratap; Viriyasitavat, Wattana; Juneja, Sapna; Alshahrani, Hani; Shaikh, Asadullah; Dhiman, Gaurav; Singh, Aman y Kaur, Amandeep
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR
(2022)
Dual adaption based evolutionary algorithm for optimized the smart healthcare communication service of the Internet of Things in smart city.
Physical Communication, 55.
p. 101893.
ISSN 18744907
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The diagnosis of early-stage lung cancer is challenging due to its asymptomatic nature, especially given the repeated radiation exposure and high cost of computed tomography(CT). Examining the lung CT images to detect pulmonary nodules, especially the cell lung cancer lesions, is also tedious and prone to errors even by a specialist. This study proposes a cancer diagnostic model based on a deep learning-enabled support vector machine (SVM). The proposed computer-aided design (CAD) model identifies the physiological and pathological changes in the soft tissues of the cross-section in lung cancer lesions. The model is first trained to recognize lung cancer by measuring and comparing the selected profile values in CT images obtained from patients and control patients at their diagnosis. Then, the model is tested and validated using the CT scans of both patients and control patients that are not shown in the training phase. The study investigates 888 annotated CT scans from the publicly available LIDC/IDRI database. The proposed deep learning-assisted SVM-based model yields 94% accuracy for pulmonary nodule detection representing early-stage lung cancer. It is found superior to other existing methods including complex deep learning, simple machine learning, and the hybrid techniques used on lung CT images for nodule detection. Experimental results demonstrate that the proposed approach can greatly assist radiologists in detecting early lung cancer and facilitating the timely management of patients.
metadata
Shafi, Imran; Din, Sadia; Khan, Asim; Díez, Isabel De La Torre; Pali-Casanova, Ramón; Tutusaus, Kilian y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, ramon.pali@unini.edu.mx, kilian.tutusaus@uneatlantico.es, SIN ESPECIFICAR
(2022)
An Effective Method for Lung Cancer Diagnosis from CT Scan Using Deep Learning-Based Support Vector Network.
Cancers, 14 (21).
p. 5457.
ISSN 2072-6694
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
A novel approach is presented in this study for the classification of lower limb disorders, with a specific emphasis on the knee, hip, and ankle. The research employs gait analysis and the extraction of PoseNet features from video data in order to effectively identify and categorize these disorders. The PoseNet algorithm facilitates the extraction of key body joint movements and positions from videos in a non-invasive and user-friendly manner, thereby offering a comprehensive representation of lower limb movements. The features that are extracted are subsequently standardized and employed as inputs for a range of machine learning algorithms, such as Random Forest, Extra Tree Classifier, Multilayer Perceptron, Artificial Neural Networks, and Convolutional Neural Networks. The models undergo training and testing processes using a dataset consisting of 174 real patients and normal individuals collected at the Tehsil Headquarter Hospital Sadiq Abad. The evaluation of their performance is conducted through the utilization of K-fold cross-validation. The findings exhibit a notable level of accuracy and precision in the classification of various lower limb disorders. Notably, the Artificial Neural Networks model achieves the highest accuracy rate of 98.84%. The proposed methodology exhibits potential in enhancing the diagnosis and treatment planning of lower limb disorders. It presents a non-invasive and efficient method of analyzing gait patterns and identifying particular conditions.
metadata
Siddiqui, Hafeez Ur Rehman; Saleem, Adil Ali; Raza, Muhammad Amjad; Gracia Villar, Santos; Dzul Lopez, Luis; Diez, Isabel de la Torre; Rustam, Furqan y Dudley, Sandra
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, luis.dzul@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Empowering Lower Limb Disorder Identification through PoseNet and Artificial Intelligence.
Diagnostics, 13 (18).
p. 2881.
ISSN 2075-4418
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Cricket has a massive global following and is ranked as the second most popular sport globally, with an estimated 2.5 billion fans. Batting requires quick decisions based on ball speed, trajectory, fielder positions, etc. Recently, computer vision and machine learning techniques have gained attention as potential tools to predict cricket strokes played by batters. This study presents a cutting-edge approach to predicting batsman strokes using computer vision and machine learning. The study analyzes eight strokes: pull, cut, cover drive, straight drive, backfoot punch, on drive, flick, and sweep. The study uses the MediaPipe library to extract features from videos and several machine learning and deep learning algorithms, including random forest (RF), support vector machine, k-nearest neighbors, decision tree, linear regression, and long short-term memory to predict the strokes. The study achieves an outstanding accuracy of 99.77% using the RF algorithm, outperforming the other algorithms used in the study. The k-fold validation of the RF model is 95.0% with a standard deviation of 0.07, highlighting the potential of computer vision and machine learning techniques for predicting batsman strokes in cricket. The study’s results could help improve coaching techniques and enhance batsmen’s performance in cricket, ultimately improving the game’s overall quality.
metadata
Siddiqui, Hafeez Ur Rehman; Younas, Faizan; Rustam, Furqan; Soriano Flores, Emmanuel; Brito Ballester, Julién; Diez, Isabel de la Torre; Dudley, Sandra y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, emmanuel.soriano@uneatlantico.es, julien.brito@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Enhancing Cricket Performance Analysis with Human Pose Estimation and Machine Learning.
Sensors, 23 (15).
p. 6839.
ISSN 1424-8220
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés The development of biodegradable materials arises as an alternative to reduce the pollution caused by plastic waste to the environment, with this premise this study was proposed to develop plastic biopolymers from bioactive compounds with different matrices modified cassava starch (5 – 12 %), fish scale collagen (10 – 40 %), lemon essential oil (0,5 - 1,5 %) and gelatinization temperature (70 – 80 °C); A Box Behnken response surface experimental design was used; with the determination of their mechanical properties (maximum stress, Young's modulus, shear strength, stress at break and percentage elongation at break). According to the results found, it was determined that the modified cassava starch had the greatest influence on the mechanical properties, taking into account its importance to create more resistant materials, but it evidences plasticizing difficulties, where the fish scale collagen has a significant influence. In addition, it is evidenced that lemon essential oil had a great influence on Young's modulus (46,28 ± 2,31 MPa) and the percentage of elongation (69,69 ± 2,16 %); while the gelatinization temperature of 80 °C is not recommended for this type of starch-protein matrices due to damage of the structure; determining a better mechanical resistance and a great increase of Young's modulus. In conclusion, the characteristics and performance of the film based on cassava starch, collagen flakes and lemon essential oil have a positive impact on the maximum level of mechanical efficiency of the biodegradable films, achieving a better performance in their mechanical properties. metadata Sánchez Soto, Juan Manuel; López-Alcántara, Ruth; Sánchez-González, Andrea del Pilar y Torres-Mendoza, Eyleen Jeniffer mail juan.sanchez@doctorado.unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2022) Evaluation of mechanical properties of matrices derived from fish scale collagen. Revista Colombiana de Investigaciones Agroindustriales, 9 (2). pp. 119-129. ISSN 2422-4456
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Background: The 2023 dengue outbreak has proven that dengue is not only an endemic disease but also an emerging health threat in Bangladesh. Integrated studies on the epidemiology, clinical characteristics, seasonality, and genotype of dengue are limited. This study was conducted to determine recent trends in the molecular epidemiology, clinical features, and seasonality of dengue outbreaks.
Methods: We analyzed data from 41 original studies, extracting epidemiological information from all 41 articles, clinical symptoms from 30 articles, and genotypic diversity from 11 articles. The study adhered to the standards of the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) Statement and Cochrane Collaboration guidelines.
Conclusion: This study provides integrated insights into the molecular epidemiology, clinical features, seasonality, and transmission of dengue in Bangladesh and highlights research gaps for future studies.
metadata
Sharif, Nadim; Opu, Rubayet Rayhan; Saha, Tama; Masud, Abdullah Ibna; Naim, Jannatin; Alsharif, Khalaf F.; Alzahrani, Khalid J.; Silva Alvarado, Eduardo René; Delgado Noya, Irene; De la Torre Díez, Isabel y Dey, Shuvra Kanti
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, eduardo.silva@funiber.org, irene.delgado@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Evolving epidemiology, clinical features, and genotyping of dengue outbreaks in Bangladesh, 2000–2024: a systematic review.
Frontiers in Microbiology, 15.
ISSN 1664-302X
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
In contemporary society, depression has emerged as a prominent mental disorder that exhibits exponential growth and exerts a substantial influence on premature mortality. Although numerous research applied machine learning methods to forecast signs of depression. Nevertheless, only a limited number of research have taken into account the severity level as a multiclass variable. Besides, maintaining the equality of data distribution among all the classes rarely happens in practical communities. So, the inevitable class imbalance for multiple variables is considered a substantial challenge in this domain. Furthermore, this research emphasizes the significance of addressing class imbalance issues in the context of multiple classes. We introduced a new approach Feature group partitioning (FGP) in the data preprocessing phase which effectively reduces the dimensionality of features to a minimum. This study utilized synthetic oversampling techniques, specifically Synthetic Minority Over-sampling Technique (SMOTE) and Adaptive Synthetic (ADASYN), for class balancing. The dataset used in this research was collected from university students by administering the Burn Depression Checklist (BDC). For methodological modifications, we implemented heterogeneous ensemble learning stacking, homogeneous ensemble bagging, and five distinct supervised machine learning algorithms. The issue of overfitting was mitigated by evaluating the accuracy of the training, validation, and testing datasets. To justify the effectiveness of the prediction models, balanced accuracy, sensitivity, specificity, precision, and f1-score indices are used. Overall, comprehensive analysis demonstrates the discrimination between the Conventional Depression Screening (CDS) and FGP approach. In summary, the results show that the stacking classifier for FGP with SMOTE approach yields the highest balanced accuracy, with a rate of 92.81%. The empirical evidence has demonstrated that the FGP approach, when combined with the SMOTE, able to produce better performance in predicting the severity of depression. Most importantly the optimization of the training time of the FGP approach for all of the classifiers is a significant achievement of this research.
metadata
Shaha, Tumpa Rani; Begum, Momotaz; Uddin, Jia; Yélamos Torres, Vanessa; Alemany Iturriaga, Josep; Ashraf, Imran y Samad, Md. Abdus
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, vanessa.yelamos@funiber.org, josep.alemany@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Feature group partitioning: an approach for depression severity prediction with class balancing using machine learning algorithms.
BMC Medical Research Methodology, 24 (1).
ISSN 1471-2288
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Wafer mappings (WM) help diagnose low-yield issues in semiconductor production by offering vital information about process anomalies. As integrated circuits continue to grow in complexity, doing efficient yield analyses is becoming more essential but also more difficult. Semiconductor manufacturers require constant attention to reliability and efficiency. Using the capabilities of convolutional neural network (CNN) models improved by hierarchical attention module (HAM), wafer hotspot detection is achieved throughout the fabrication process. In an effort to achieve accurate hotspot detection, this study examines a variety of model combinations, including CNN, CNN+long short-term memory (LSTM) LSTM, CNN+Autoencoder, CNN+artificial neural network (ANN), LSTM+HAM, Autoencoder+HAM, ANN+HAM, and CNN+HAM. Data augmentation strategies are utilized to enhance the model’s resilience by optimizing its performance on a variety of datasets. Experimental results indicate a superior performance of 94.58% accuracy using the CNN+HAM model. K-fold cross-validation results using 3, 5, 7, and 10 folds indicate mean accuracy of 94.66%, 94.67%, 94.66%, and 94.66%, for the proposed approach, respectively. The proposed model performs better than recent existing works on wafer hotspot detection. Performance comparison with existing models further validates its robustness and performance.
metadata
Shahroz, Mobeen; Ali, Mudasir; Tahir, Alishba; Fabian Gongora, Henry; Uc Ríos, Carlos Eduardo; Abdus Samad, Md y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, henry.gongora@uneatlantico.es, carlos.uc@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Hierarchical Attention Module-Based Hotspot Detection in Wafer Fabrication Using Convolutional Neural Network Model.
IEEE Access, 12.
pp. 92840-92855.
ISSN 2169-3536
Artículo Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español El cumplimiento normativo, también conocido como compliance, se ha convertido en tema importante y de preocupación para las empresas en todo el mundo. En México, el cumplimiento jurídico ha adquirido cada vez más importancia debido a la creciente complejidad del marco regulatorio y a las sanciones más severas impuestas por las autoridades en caso de incumplimiento. Los sistemas de cumplimiento normativo o compliance se establecen en la legislación mexicana como atenuantes y/o excluyentes de la responsabilidad jurídica en cualquiera de las ramificaciones que a través del derecho establecen bases de sanciones para lograr un cumplimiento al que deben acceder las personas jurídicas sin proporcionar estándares mínimos de aplicación sin unificar criterios, normativos y procedimientos. Este artículo se propone ubicar las acciones normativas con las que dispone el Estado de Derecho mexicano, su marco legal y las implicaciones para las empresas que operan en el país. metadata Solis Gutierrez, Daniela Cecilia mail SIN ESPECIFICAR (2023) Importancia del cumplimiento normativo en México. Implementación del compliance en las empresas mexicanas. MLS Law and International Politics, 2 (1). ISSN 2952-248X
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The integration of a flexible alternating current transmission system (FACTS) and a power system stabilizer (PSS) can increase dynamic stability. This paper presents the enhancement of power system dynamic stability through the optimal design of a power system stabilizer and UPFC using an ant lion optimization (ALO) technique to enhance transmission line capacity. The gained damping ratio, eigenvalue and time domain results of the suggested ALO technique were compared with a base case system, ALO-based PSS and ALO-based PSS-UPFC to test the effectiveness of the proposed system in different loading cases. Eigenvalues gained from an ant lion approach-based UPFC with a PSS and a base case system are compared to examine the robustness of the ALO method for various loading conditions. Thus, this paper addresses the mechanism regarding the power system dynamic stability of transmission lines by integrating the optimal size of a PSS and UPFC into the power system. Therefore, the main contribution of this manuscript is the optimal coordination of a power system stabilizer, power oscillation damper and unified power flow using ant lion optimization for the mitigation of low-frequency oscillation.
metadata
Solomon, Endeshaw; Khan, Baseem; Boulkaibet, Ilyes; Neji, Bilel; Khezami, Nadhira; Ali, Ahmed; Mahela, Om Prakash y Pascual Barrera, Alina Eugenia
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, alina.pascual@unini.edu.mx
(2023)
Mitigating Low-Frequency Oscillations and Enhancing the Dynamic Stability of Power System Using Optimal Coordination of Power System Stabilizer and Unified Power Flow Controller.
Sustainability, 15 (8).
p. 6980.
ISSN 2071-1050
Artículo Materias > Psicología Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español La población con necesidades educativas especiales ha enfrentado a lo largo de la historia dificultades en la inclusión social, cultural y también educativa. Guatemala no es la excepción por ser un país en vías de desarrollo y con grandes deficiencias de atención en el sistema educativo. Actualmente se carece de una pedagogía y didáctica que solucione esta problemática para los docentes que trabajan con alumnos con necesidades educativas especiales, como a la vez los centros educativos carecen de un adiestramiento en relación con educación especial junto a programas terapéuticos que brinden resultados para las personas con discapacidad. En esta investigación se analizó la validez del modelo pedagógico-terapéutico “Cetumismo” contra el programa “Aula Recurso” del Ministerio de Educación de Guatemala. Esto se efectuó en una muestra seleccionada de docentes que laboran en centros educativos, luego de responder un Cuestionario estandarizado para valorar la calidad de la Educación Especial en los centros educativos por medio del proceso estadístico prueba t de student, en donde se compararon las medias obtenidas en los dos momentos de evaluación, obteniendo la varianza. Los resultados obtenidos establecen que con un nivel de significancia de 0.05 se rechaza la hipótesis nula y se acepta la hipótesis alternativa; por lo que la comparación de las medias en el proceso estadístico realizado determina que, entre ambos programas, el programa que resuelve las necesidades educativas especiales en relación con la educación especial es Modelo Pedagógico Terapéutico “Cetumismo”. Los docentes evaluados a pesar de pertenecer a una escuela que utiliza el programa “Aula Recurso” impuesto por el Ministerio de Educación de Guatemala, consideran que un modelo pedagógico-terapéutico como “Cetumismo” traería mayores beneficios en las necesidades de educación especial de personas con discapacidad, con adecuaciones curriculares específicas para cada alumno, capacitaciones constantes y actualizadas para docentes, pensum diferenciado, proceso educativo inclusivo luego del alcance de las competencias propuestas por caso metadata Soto Genovese, Eimy Ann mail SIN ESPECIFICAR (2020) Modelo Pedagógico-terapéutica para atención a la educación especial en Guatemala. MLS Psychology Research, 3 (1). pp. 39-64. ISSN 26055295
Artículo Materias > Psicología Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Este artículo es un primer paso hacia la construcción de un modelo teórico personalizado que se aplica en la industria marítima para la solución de los conflictos organizativos de una empresa de servicios de apoyo marítimo a través de una herramienta sistémica. Este modelo se deriva de la técnica de resolución de conflictos autocomputada llamada Constelación Organizacional Sistémica desarrollada inicialmente por Bert Hellinger. Su redacción se apoyó en una bibliografía teórica sobre el uso de esta técnica, compilada entre 2014 y 2020 a partir del banco electrónico existente de literatura científica Google Scholar con el uso de sintaxis específica. Se utilizó el método de análisis de contenido, basado en una matriz de Constelaciones Familiares, para la intersección de trabajos académicos teóricos sobre tipos de Constelaciones y sobre Empresas de Apoyo Marítimo para identificar las características funcionales necesarias en una empresa del sector y su idoneidad para los roles existentes. de los participantes involucrados directa o indirectamente en el proceso de una Constelación Organizacional. Como resultado, la construcción del modelo sigue siendo totalmente empírica, y su validez se discute con el uso de grupos de discusión y su empleabilidad en la empresa en esta área. En conclusión, se entiende que se trata de un modelo pionero, robusto y personalizado, y que está listo para ser probado en alguna empresa de apoyo marítimo para la evaluación y verificación de los ajustes necesarios metadata Sant´Anna Maciel, Monica Pires y Maciel Pereira, Jose Antonio mail SIN ESPECIFICAR (2020) Modelo Teórico para la resolución de conflictos en las compañías navieras brasileñas a través de una constelación organizacional sistémica - una propuesta. MLS psychology research, 3 (2). pp. 7-26. ISSN 2605-5295
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Portugués O uso de padrões ou modelos para gerenciamento de serviços de TIC não é uma novidade no Brasil, no entanto é notória a falta de informações sobre a aplicabilidade desses modelos. O objetivo principal do estudo foi realizar um levantamento dos modelos de gerenciamento de serviços de TIC praticados nas escolas particulares da cidade de São Paulo e após a coleta dos dados efetuar um cruzamento das info rmações com os níveis de satisfação dos clientes internos (em específico, os coordenadores pedagógicos) de cada instituição para que seja possível entender a relação entre os altos nívei s de qualidade das escolas e os modelos de gerenciamento de serviços de TIC aplicados nessas instituições. Para levantamento dos dados foi aplicado a cada perfil de profissional, o gerente de TIC e o coordenador pedagógico, um questionário com a intenção de aprofundar o conhecimento sob re o setor. A amostra selecionada foi de 67 gerentes de TIC e 69 coordenadores pedagógicos. Através da apuração dos dados foi possível entender parte da relação entre a oferta de equipamentos, redes sem fio e serviços de suporte de tecnologia, com a percepção de qualidade do profissional de pedagogia em uma mesma instituição de ensino básico. Como resultado das duas pesquisas, foi possível entender a relação direta entre uma escola bem aparelhada e com profissionais treinados em atendimento no cotidiano do professor. metadata Serapiao, Christian mail SIN ESPECIFICAR (2020) Modelos de gerenciamento de serviços de TIC em escolas particulares na cidade de São Paulo. Project, Design and Management, 2 (1). pp. 103-119. ISSN 26831597
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Background and Aims
The 2022-mpox outbreak has spread worldwide in a short time. Integrated knowledge of the epidemiology, clinical characteristics, and transmission of mpox are limited. This systematic review of peer-reviewed articles and gray literature was conducted to shed light on the epidemiology, clinical features, and transmission of 2022-mpox outbreak.
Methods
We identified 45 peer-reviewed manuscripts for data analysis. The standards of the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) Statement and Cochrane Collaboration were followed for conducting the study.
Results
The case number of mpox has increased about 100 times worldwide. About 99% of the cases in 2022 outbreak was from non-endemic regions. Men (70%–98% cases) were mostly infected with homosexual and bisexual behavior (30%–60%). The ages of the infected people ranged between 30 and 40 years. The presence of HIV and sexually transmitted infections among 30%–60% of cases were reported. Human-to-human transmission via direct contact and different body fluids were involved in the majority of the cases (90%–100%). Lesions in genitals, perianal, and anogenital areas were more prevalent. Unusually, pharyngitis (15%–40%) and proctitis (20%–40%) were more common during 2022 outbreak than pre-2022 outbreaks. Brincidofovir is approved for the treatment of smallpox by FDA (USA). Two vaccines, including JYNNEOSTM and ACAM2000®, are approved and used for pre- and post-prophylaxis in cases. About 100% of the cases in non-endemic regions were associated with isolates of IIb clade with a divergence of 0.0018–0.0035. Isolates from B.1 lineage were the most predominant followed by B.1.2 and B.1.10.
Conclusion
This study will add integrated knowledge of the epidemiology, clinical features, and transmission of mpox.
metadata
Sharif, Nadim; Sharif, Nazmul; Alzahrani, Khalid J.; Halawani, Ibrahim F.; Alzahrani, Fuad M.; Díez, Isabel De la Torre; Lipari, Vivian; López Flores, Miguel Ángel; Parvez, Anowar K. y Dey, Shuvra K.
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, vivian.lipari@uneatlantico.es, miguelangel.lopez@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Molecular epidemiology, transmission and clinical features of 2022‐mpox outbreak: A systematic review.
Health Science Reports, 6 (10).
ISSN 2398-8835
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Antimicrobial and multidrug resistance (MDR) pathogens are becoming one of the major health threats among children. Integrated studies on the molecular epidemiology and prevalence of AMR and MDR diarrheal pathogens are lacking. A total of 404 fecal specimens were collected from children with diarrhea in Bangladesh from January 2019 to December 2021. We used conventional bacteriologic and molecular sequence analysis methods. Phenotypic and genotypic resistance were determined by disk diffusion and molecular sequencing methods. Fisher’s exact tests with 95% confidence intervals (CIs) was performed. Prevalence of bacterial infection was 63% (251 of 404) among children with diarrhea. E. coli (29%) was the most prevalent. E. coli, Shigella spp., V. cholerae, and Salmonella spp., showed the highest frequency of resistance against ceftriaxone (75–85%), and erythromycin (70–75%%). About 10–20% isolates of E. coli, V. cholerae and Shigella spp. showed MDR against cephem, macrolides, and quinolones. Significant association (p value < 0.05) was found between the phenotypic and genotypic resistance. The risk of diarrhea was the highest among the patients co-infected with E. coli and rotavirus [OR 3.6 (95% CI 1.1–5.4) (p = 0.001)] followed by Shigella spp. and rotavirus [OR 3.5 (95% CI 0.5–5.3) (p = 0.001)]. This study will provide an integrated insight of molecular epidemiology and antimicrobial resistance profiling of bacterial pathogens among children with diarrhea in Bangladesh.
metadata
Sharif, Nadim; Ahmed, Shamsun Nahar; Khandaker, Shamim; Monifa, Nuzhat Haque; Abusharha, Ali; Ramírez-Vargas, Debora L.; Díez, Isabel De la Torre; Kuc Castilla, Ángel Gabriel; Talukder, Ali Azam; Parvez, Anowar Khasru y Dey, Shuvra Kanti
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, debora.ramirez@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Multidrug resistance pattern and molecular epidemiology of pathogens among children with diarrhea in Bangladesh, 2019–2021.
Scientific Reports, 13 (1).
ISSN 2045-2322
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Lumbar spine stenosis (LSS) is caused by low back pain that exerts pressure on the nerves in the spine. Detecting LSS is a significantly important yet difficult task. It is detected by analyzing the area of the anteroposterior diameter of the patient’s lumbar spine. Currently, the versatility and accuracy of LSS segmentation algorithms are limited. The objective of this research is to use magnetic resonance imaging (MRI) to automatically categorize LSS. This study presents a convolutional neural network (CNN)-based method to detect LSS using MRI images. Radiological grading is performed on a publicly available dataset. Four regions of interest (ROIs) are determined to diagnose LSS with normal, mild, moderate, and severe gradings. The experiments are performed on 1545 axial-view MRI images. Furthermore, two datasets—multi-ROI and single-ROI—are created. For training and testing, an 80:20 ratio of randomly selected labeled datasets is used, with fivefold cross-validation. The results of the proposed model reveal a 97.01% accuracy for multi-ROI and 97.71% accuracy for single-ROI. The proposed computer-aided diagnosis approach can significantly improve diagnostic accuracy in everyday clinical workflows to assist medical experts in decision making. The proposed CNN-based MRI image segmentation approach shows its efficacy on a variety of datasets. Results are compared to existing state-of-the-art studies, indicating the superior performance of the proposed approach.
metadata
Shahzadi, Turrnum; Ali, Muhammad Usman; Majeed, Fiaz; Sana, Muhammad Usman; Martínez Díaz, Raquel; Samad, Md Abdus y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, raquel.martinez@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Nerve Root Compression Analysis to Find Lumbar Spine Stenosis on MRI Using CNN.
Diagnostics, 13 (18).
p. 2975.
ISSN 2075-4418
Artículo Materias > Psicología Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Esta publicación describe el desarrollo de 33 reactivos de escala para evaluar las percepciones de mentalidad fija y aprendiente de las personas. El concepto de mentalidad fija y aprendiente surge de la teoría de Carol S. Dweck que ha sido discutida por años en diversas investigaciones en el ámbito escolar, sin embargo aún no se ha desarrollado una escala de medición en adultos particularmente en trabajadores para la productividad, se diseñó una escala de medición con tres secciones con 70 reactivos de mentalidad fija y aprendiente, tomando la referencia la medición de inteligencia de Dweck, Chiu y Hong (1995), Dweck et al. (1999) y Buchanan y Kern (2017). En el estudio participaron 97 supervisores de la industria maquiladora de Reynosa Tamaulipas, se aplicaron encuestas a tres grupos de participantes para realizar el proceso de análisis de reducción factorial para comprobar el nivel de significancia y validación de reactivos. Como resultado se obtuvieron 15 reactivos de mentalidad fija y 18 reactivos de mentalidad aprendiente, los cuales corroboran las teorías referidas de la medición de las dos dimensiones de mentalidad fija y aprendiente. El uso de esta escala puede servir como referente para futuras investigaciones en adultos para demostrar su competencia en la productividad. metadata Sahagun, Miguel y López Vázquez, Francisco mail SIN ESPECIFICAR (2021) Nueva escala de medición de mentalidad fija y aprendiente: desarrollo y validación. Project Design and Management, 3 (2). pp. 37-54. ISSN 2683-1597
Artículo Materias > Alimentación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés A procedure easy to upscale industrially aimed at obtaining resistant starch (RS) type III (RS-III) was optimized, using a native faba bean from Mexico (Vicia faba L. creole) as RS source for the first time. Pullulanase debranching treatment (6–18 enzyme units (U)/g starch; 0–27 h) and retrogradation process (−30 °C, 2 °C or 20 °C; 1–6 days) was optimized for faba beans. Optimal conditions were determined at 18 U/g for 27 h and a retrogradation process at 20 °C for 6 days. Obtained faba bean RS was also compared with RS obtained from conventional sources, beans (Phaseolus vulgaris L. Jamapa) and maize, under these optimal conditions. Beans (faba beans, 64.88%; beans, 64.84%) yielded greater RS-III than maize (58.44%). The retrogradation process increased the crystallinity structure of the RS samples compared to their respective NS. Typical legume C pattern (faba bean and beans) and cereal A pattern (maize) of samples changed to an irregular polymorphic morphology type B + V, caused by retrogradation, and increasing RS content. As consequence, the digestibility of the retrograded samples was significantly reduced (approximately 50%) and increasing the amount of slow digestible starch fraction (SDS). metadata Suárez-Diéguez, Teodoro; Pérez-Moreno, Fidel; Ariza-Ortega, José Alberto; López-Rodríguez, Guadalupe y Nieto, Juan Antonio mail SIN ESPECIFICAR (2021) Obtention and characterization of resistant starch from creole faba bean (Vicia faba L. creole) as a promising functional ingredient. LWT, 145. p. 111247. ISSN 00236438
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
This paper introduces a power quality (PQ) detection and categorization algorithm actuated by multiple signal processing techniques and rule-based decision tree (RBDT). This is aimed to recognize PQ events of simple nature and higher order multiplicity with less computational time using hybridization of the signal processing techniques. A voltage waveform with a PQ event (PQE) is processed using the Stockwell transform (ST) to compute the Stockwell PQ detection index (SPDI). The voltage waveform is also processed using the Hilbert transform (HT) to compute the Hilbert PQ detection index (HPDI). A voltage waveform is also decomposed using the Discrete Wavelet transform (DWT) to compute the classification feature index (CFI) [CFI1 to CFI4]. A combined PQ detection index (CPDI) is computed by multiplication of the SPDI, the HPDI and CFI1 to CFI4. Incidence of a PQE on a voltage signal is located with the help of a location PQ disturbance index (LPDI) which is computed by differentiating the CPDI with respect to time. CFI5, CFI6 and CFI7 are computed from the SPDI, the HPDI and the CPDI, respectively. Categorization of PQ events is performed using CFI1 to CFI7 by the rule-based decision tree (RBDT) with the help of simple decision rules. We conclude that the proposed algorithm is effective to identify the PQE with an accuracy of 98.58% in a noise-free environment and 97.62% in the presence of 20 dB SNR (signal-to-noise ratio) noise. Ten simple nature PQEs and eight combined PQ events (CPQEs) with multiplicity of two, three and four are effectively detected and categorized using the algorithm. The algorithm is also tested to detect a sag PQ event due to a line-to-ground (LG) fault incident on a practical distribution utility network. The performance of the investigated method is compared with a DWT-based technique in terms of accuracy of classification with and without noise, maximum computational time of PQ detection and multiplicity of PQE which can be effectively detected. A simulation is performed using the MATLAB software. MATLAB codes are used for modelling the PQE disturbances and the proposed algorithm using mathematical formulations.
metadata
Singh, Surendra; Sharma, Avdhesh; Garg, Akhil Ranjan; Mahela, Om Prakash; Khan, Baseem; Boulkaibet, Ilyes; Neji, Bilel; Ali, Ahmed y Brito Ballester, Julién
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, julien.brito@uneatlantico.es
(2023)
Power Quality Detection and Categorization Algorithm Actuated by Multiple Signal Processing Techniques and Rule-Based Decision Tree.
Sustainability, 15 (5).
p. 4317.
ISSN 2071-1050
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Introduction: Rotavirus infection is a major cause of mortality among children under 5 years in Bangladesh. There is lack of integrated studies on rotavirus prevalence and genetic diversity during 1973 to 2023 in Bangladesh.
Methods: This meta-analysis was conducted to determine the prevalence, genotypic diversity and seasonal distribution of rotavirus during pre-vaccination period in Bangladesh. This study included published articles on rotavirus A, rotavirus B and rotavirus C. We used Medline, Scopus and Google Scholar for published articles. Selected literatures were published between 1973 to 2023.
Results: This study detected 12431 research articles published on rotavirus. Based on the inclusion criteria, 29 of 75 (30.2%) studies were selected. Molecular epidemiological data was taken from 29 articles, prevalence data from 29 articles, and clinical symptoms from 19 articles. The pooled prevalence of rotavirus was 30.1% (95% CI: 22%-45%, p = 0.005). Rotavirus G1 (27.1%, 2228 of 8219) was the most prevalent followed by G2 (21.09%, 1733 of 8219), G4 (11.58%, 952 of 8219), G9 (9.37%, 770 of 8219), G12 (8.48%, 697 of 8219), and G3 (2.79%, 229 of 8219), respectively. Genotype P[8] (40.6%, 2548 of 6274) was the most prevalent followed by P[4] (12.4%, 777 of 6274) and P[6] (6.4%, 400 of 6274), respectively. Rotavirus G1P[8] (19%) was the most frequent followed by G2P [4] (9.4%), G12P[8] (7.2%), and G9P[8], respectively. Rotavirus infection had higher odds of occurrence during December and February (aOR: 2.86, 95% CI: 2.43-3.6, p = 0.001).
Discussion: This is the first meta-analysis including all the studies on prevalence, molecular epidemiology, and genetic diversity of rotavirus from 1973 to 2023, pre-vaccination period in Bangladesh. This study will provide overall scenario of rotavirus genetic diversity and seasonality during pre-vaccination period and aids in policy making for rotavirus vaccination program in Bangladesh. This work will add valuable knowledge for vaccination against rotavirus and compare the data after starting vaccination in Bangladesh.
metadata
Sharif, Nadim; Sharif, Nazmul; Khan, Afsana; Dominguez Azpíroz, Irma; Martínez Díaz, Raquel; Díez, Isabel De la Torre; Parvez, Anowar Khasru y Dey, Shuvra Kanti
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, irma.dominguez@unini.edu.mx, raquel.martinez@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Prevalence and genetic diversity of rotavirus in Bangladesh during pre-vaccination period, 1973-2023: a meta-analysis.
Frontiers in Immunology, 14.
ISSN 1664-3224
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Introduction: Co-prevalence of long-COVID-19, cardiovascular diseases and diabetes is one of the major health challenges of the pandemic worldwide. Studies on long-COVID-19 and associated health outcomes are absent in Bangladesh. The main aim of this study was to determine the prevalence and impact of long-COVID-19 on preexisting diabetes and cardiovascular diseases (CVD) on health outcomes among patients in Bangladesh.
Methods: We collected data from 3,250 participants in Bangladesh, retrospectively. Multivariable logistic regression model was used to determine the odds ratio between independent and dependent variables. Kaplan-Meier survival curve was used to determine the cumulative survival.
Results: COVID-19 was detected among 73.4% (2,385 of 3,250) participants. Acute long-COVID-19 was detected among 28.4% (678 of 2,385) and chronic long-COVID-19 among 71.6% (1,707 of 2,385) patients. CVD and diabetes were found among 32%, and 24% patients, respectively. Mortality rate was 18% (585 of 3,250) among the participants. Co-prevalence of CVD, diabetes and COVID-19 was involved in majority of fatality (95%). Fever (97%), dry cough (87%) and loss of taste and smell (85%) were the most prevalent symptoms. Patients with co-prevalence of CVD, diabetes and COVID-19 had higher risk of fatality (OR: 3.65, 95% CI, 2.79–4.24). Co-prevalence of CVD, diabetes and chronic long-COVID-19 were detected among 11.9% patients.
Discussion: Risk of hospitalization and fatality reduced significantly among the vaccinated. This is one of the early studies on long-COVID-19 in Bangladesh.
metadata
Sharif, Nadim; Sharif, Nazmul; Khan, Afsana; Halawani, Ibrahim F.; Alzahrani, Fuad M.; Alzahrani, Khalid J.; Díez, Isabel De la Torre; Ramírez-Vargas, Debora L.; Kuc Castilla, Ángel Gabriel; Parvez, Anowar Khasru y Dey, Shuvra Kanti
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, debora.ramirez@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Prevalence and impact of long COVID-19 among patients with diabetes and cardiovascular diseases in Bangladesh.
Frontiers in Public Health, 11.
ISSN 2296-2565
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Deep learning is used to address a wide range of challenging issues including large data analysis, image processing, object detection, and autonomous control. In the same way, deep learning techniques are also used to develop software and techniques that pose a danger to privacy, democracy, and national security. Fake content in the form of images and videos using digital manipulation with artificial intelligence (AI) approaches has become widespread during the past few years. Deepfakes, in the form of audio, images, and videos, have become a major concern during the past few years. Complemented by artificial intelligence, deepfakes swap the face of one person with the other and generate hyper-realistic videos. Accompanying the speed of social media, deepfakes can immediately reach millions of people and can be very dangerous to make fake news, hoaxes, and fraud. Besides the well-known movie stars, politicians have been victims of deepfakes in the past, especially US presidents Barak Obama and Donald Trump, however, the public at large can be the target of deepfakes. To overcome the challenge of deepfake identification and mitigate its impact, large efforts have been carried out to devise novel methods to detect face manipulation. This study also discusses how to counter the threats from deepfake technology and alleviate its impact. The outcomes recommend that despite a serious threat to society, business, and political institutions, they can be combated through appropriate policies, regulation, individual actions, training, and education. In addition, the evolution of technology is desired for deepfake identification, content authentication, and deepfake prevention. Different studies have performed deepfake detection using machine learning and deep learning techniques such as support vector machine, random forest, multilayer perceptron, k-nearest neighbors, convolutional neural networks with and without long short-term memory, and other similar models. This study aims to highlight the recent research in deepfake images and video detection, such as deepfake creation, various detection algorithms on self-made datasets, and existing benchmark datasets.
metadata
Shahzad, Hina Fatima; Rustam, Furqan; Soriano Flores, Emmanuel; Vidal Mazón, Juan Luis; de la Torre Diez, Isabel y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, emmanuel.soriano@uneatlantico.es, juanluis.vidal@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
A Review of Image Processing Techniques for Deepfakes.
Sensors, 22 (12).
p. 4556.
ISSN 1424-8220
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés The proper verification of users plays a vital role during communication over a social network to protect the personal data of users. Multifarious protocols have been implemented to secure the confidential data of the users, but these protocols have various limitations and are incapable of providing secrecy of data against various attacks, such as replay and cryptanalysis attacks. In this article, the authors proposed a novel method for security verification of the social network model using an improved three-party authenticated key exchange (3PAKE) protocol based on symmetric encryption and (ECC) elliptic curve cryptography. The outcome of the paper demonstrates that our proposed algorithm provides the desired secrecy to the confidential data exchange over social networks in real-time and consumes less time in comparison to existing protocols. Our protocol consumes a search time of 0.09 s, overall communication steps took 2 during the verification, and depth plies was 3 along with 20 visited nodes. The 3PAKE protocol has been considered a suitable approach for social network secrecy during information exchange between user and server, thereby providing greater secrecy to the user in data exchange over social networks and more robustness against multifarious known attacks, such as cryptanalysis and replay attacks in real-time metadata Sinha, Vivek Kumar; Anand, Divya; Kaur, Sandeep; Singh, Pankaj y Delgado Noya, Irene mail SIN ESPECIFICAR, divya.anand@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, irene.delgado@uneatlantico.es (2022) Security Verification of Social Network Model Using Improved Three-Party Authenticated Key Exchange Protocol. Symmetry, 14 (8). p. 1567. ISSN 2073-8994
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
One of the toughest biometrics and document forensics problems is confirming a signature’s authenticity and legal identity. A forgery may vary from a genuine signature by specific distortions. Therefore, it is necessary to continuously monitor crucial distinctions between real and forged signatures for secure work and economic growth, but this is particularly difficult in writer-independent tasks. We thus propose an innovative and sustainable writer-independent approach based on a Siamese neural network for offline signature verification. The Siamese network is a twin-like structure with shared weights and parameters. Similar and dissimilar images are exposed to this network, and the Euclidean distances between them are calculated. The distance is reduced for identical signatures, and the distance is increased for different signatures. Three datasets, namely GPDS, BHsig260 Hindi, and BHsig260 Bengali datasets, were tested in this work. The proposed model was analyzed by comparing the results of different parameters such as optimizers, batch size, and the number of epochs on all three datasets. The proposed Siamese neural network outperforms the GPDS synthetic dataset in the English language, with an accuracy of 92%. It also performs well for the Hindi and Bengali datasets while considering skilled forgeries
metadata
Sharma, Neha; Gupta, Sheifali; Mohamed, Heba G.; Anand, Divya; Vidal Mazón, Juan Luis; Gupta, Deepali y Goyal, Nitin
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, juanluis.vidal@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Siamese Convolutional Neural Network-Based Twin Structure Model for Independent Offline Signature Verification.
Sustainability, 14 (18).
p. 11484.
ISSN 2071-1050
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Assessment of side effects associated with COVID-19 vaccination is required to monitor safety issues and acceptance of vaccines in the long term. We found a significant knowledge gap in the safety profile of COVID-19 vaccines in Bangladesh. We enrolled 1805 vaccine recipients from May 5, 2021, to April 4, 2023. Kruskal-Wallis test and χ2 test were performed. Multivariable logistic regression was also performed. First, second and third doses were administered among 1805, 1341, and 923 participants, respectively. Oxford–AstraZeneca (2946 doses) was the highest administered followed by Sinopharm BIBP (551 doses), Sinovac (214 doses), Pfizer-BioNTech (198 doses), and Moderna (160 doses), respectively. Pain at the injection site (80-90%, 3200–3600), swelling (85%, 3458), redness (78%, 3168), and heaviness in hand (65%, 2645) were the most common local effects, and fever (85%, 3458), headache (82%, 3336), myalgia (70%, 2848), chills (67%, 2726), muscle pain (60%, 2441) were the most prevalent systemic side effects reported within 48 h of vaccination. Thrombosis was only reported among the Oxford–AstraZeneca recipients (3.5-5.7%). Both local and systemic effects were significantly associated with the Oxford–AstraZeneca (p-value < 0.05), Pfizer–BioNTech (p-value < 0.05), and Moderna (p-value < 0.05) vaccination. Chronic urticaria and psoriasis were reported by 55-60% of the recipients after six months or later. The highest percentage of local and systemic effects after 2nd and 3rd dose were found among recipients of Moderna followed by Pfizer-BioNTech and Oxford–AstraZeneca. Homogenous doses of Oxford–AstraZeneca and heterogenous doses of Moderna and Pfizer-BioNTech were significantly associated with elevated adverse effects. Females, aged above 60 years with preexisting health conditions had higher risks. Vaccination with Pfizer-BioNTech (OR 4.34, 95% CI 3.95–4.58) had the highest odds of severe and long-term effects followed by Moderna (OR 4.15, 95% CI 3.92–4.69) and Oxford–AstraZeneca (OR 3.89, 95% CI 3.45–4.06), respectively. This study will provide an integrated insight into the safety profile of COVID-19 vaccines.
metadata
Sharif, Nadim; Opu, Rubayet Rayhan; Saha, Tama; Khan, Afsana; Aljohani, Abrar; Alsuwat, Meshari A.; García, Carlos O.; Vázquez, Annia A.; Alzahrani, Khalid J.; Miramontes-González, J. Pablo y Dey, Shuvra Kanti
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, annia.almeyda@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Side effects associated with homogenous and heterogenous doses of Oxford–AstraZeneca vaccine among adults in Bangladesh: an observational study.
Scientific Reports, 14 (1).
ISSN 2045-2322
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Assessment of side effects associated with COVID-19 vaccination is required to monitor safety issues and acceptance of vaccines in the long term. We found a significant knowledge gap in the safety profile of COVID-19 vaccines in Bangladesh. We enrolled 1805 vaccine recipients from May 5, 2021, to April 4, 2023. Kruskal-Wallis test and χ2 test were performed. Multivariable logistic regression was also performed. First, second and third doses were administered among 1805, 1341, and 923 participants, respectively. Oxford–AstraZeneca (2946 doses) was the highest administered followed by Sinopharm BIBP (551 doses), Sinovac (214 doses), Pfizer-BioNTech (198 doses), and Moderna (160 doses), respectively. Pain at the injection site (80-90%, 3200–3600), swelling (85%, 3458), redness (78%, 3168), and heaviness in hand (65%, 2645) were the most common local effects, and fever (85%, 3458), headache (82%, 3336), myalgia (70%, 2848), chills (67%, 2726), muscle pain (60%, 2441) were the most prevalent systemic side effects reported within 48 h of vaccination. Thrombosis was only reported among the Oxford–AstraZeneca recipients (3.5-5.7%). Both local and systemic effects were significantly associated with the Oxford–AstraZeneca (p-value < 0.05), Pfizer–BioNTech (p-value < 0.05), and Moderna (p-value < 0.05) vaccination. Chronic urticaria and psoriasis were reported by 55-60% of the recipients after six months or later. The highest percentage of local and systemic effects after 2nd and 3rd dose were found among recipients of Moderna followed by Pfizer-BioNTech and Oxford–AstraZeneca. Homogenous doses of Oxford–AstraZeneca and heterogenous doses of Moderna and Pfizer-BioNTech were significantly associated with elevated adverse effects. Females, aged above 60 years with preexisting health conditions had higher risks. Vaccination with Pfizer-BioNTech (OR 4.34, 95% CI 3.95–4.58) had the highest odds of severe and long-term effects followed by Moderna (OR 4.15, 95% CI 3.92–4.69) and Oxford–AstraZeneca (OR 3.89, 95% CI 3.45–4.06), respectively. This study will provide an integrated insight into the safety profile of COVID-19 vaccines.
metadata
Sharif, Nadim; Opu, Rubayet Rayhan; Saha, Tama; Khan, Afsana; Aljohani, Abrar; Alsuwat, Meshari A.; García, Carlos O.; Vázquez, Annia A.; Alzahrani, Khalid J.; Miramontes-González, J. Pablo y Dey, Shuvra Kanti
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, annia.almeyda@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Side effects associated with homogenous and heterogenous doses of Oxford–AstraZeneca vaccine among adults in Bangladesh: an observational study.
Scientific Reports, 14 (1).
ISSN 2045-2322
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Safety critical spare parts hold special importance for aviation organizations. However, accurate forecasting of such parts becomes challenging when the data are lumpy or intermittent. This research paper proposes an artificial neural network (ANN) model that is able to observe the recent trends of error surface and responds efficiently to the local gradient for precise spare prediction results marked by lumpiness. Introduction of the momentum term allows the proposed ANN model to ignore small variations in the error surface and to behave like a low-pass filter and thus to avoid local minima. Using the whole collection of aviation spare parts having the highest demand activity, an ANN model is built to predict the failure of aircraft installed parts. The proposed model is first optimized for its topology and is later trained and validated with known historical demand datasets. The testing phase includes introducing input vector comprising influential factors that dictate sporadic demand. The proposed approach is found to provide superior results due to its simple architecture and fast converging training algorithm once evaluated against some other state-of-the-art models from the literature using related benchmark performance criteria. The experimental results demonstrate the effectiveness of the proposed approach. The accurate prediction of the cost-heavy and critical spare parts is expected to result in huge cost savings, reduce downtime, and improve the operational readiness of drones, fixed wing aircraft and helicopters. This also resolves the dead inventory issue as a result of wrong demands of fast moving spares due to human error.
metadata
Shafi, Imran; Sohail, Amir; Ahmad, Jamil; Martínez Espinosa, Julio César; Dzul Lopez, Luis Alonso; Bautista Thompson, Ernesto y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, luis.dzul@unini.edu.mx, ernesto.bautista@unini.edu.mx, SIN ESPECIFICAR
(2023)
Spare Parts Forecasting and Lumpiness Classification Using Neural Network Model and Its Impact on Aviation Safety.
Applied Sciences, 13 (9).
p. 5475.
ISSN 2076-3417
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
Stress is now a serious disease that exists due to changes in working life and food ecosystems around the world. In general, it is difficult for a person to know if they are under stress. According to previous research, temperature, heart rate variability (HRV), humidity, and blood pressure are used to assess stress levels with the use of instruments. With the development of sensor technology and wireless connectivity, people around the world are adopting and using smart devices. In this study, a bio signal detection device with Internet of Things (IoT) capability with a galvanic skin reaction (GSR) sensor is proposed and built for real-time stress monitoring. The proposed device is based on an Arduino controller and Bluetooth communication. To evaluate the performance of the system, physical stress is created on 10 different participants with three distinct tasks namely reading, visualizing the timer clock, and watching videos. MATLAB analysis is performed for identifying the three different levels of stress and obtaining the threshold values as if the person GSR voltage i.e., relaxed for <1.75 volts; Normal: between 1.75 and 1.44 volts and stressed: >1.44 volts. In addition, LabVIEW is used as a data acquisition system, and a Blueterm mobile application is also used to view the sensor reading received from the device through Bluetooth communication.
metadata
Singh, Rajesh; Gehlot, Anita; Saxena, Ritika; Alsubhi, Khalid; Anand, Divya; Delgado Noya, Irene; Vaseem Akram, Shaik y Choudhury, Sushabhan
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, irene.delgado@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Stress Detector Supported Galvanic Skin Response System with IoT and LabVIEW GUI.
Computers, Materials & Continua, 74 (1).
pp. 1217-1233.
ISSN 1546-2226
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Herbal medicine and nutritional supplements are suggested to treat premenstrual somatic and psycho-behavioural symptoms in clinical guidelines; nonetheless, this is at present based on poor-quality trial evidence. Hence, we aimed to design a systematic review and meta-analysis for their effectiveness in alleviating premenstrual symptoms. The published randomized controlled trials (RCTs) were extracted from Google scholar, PubMed, Scopus and PROSPERO databases. The risk of bias in randomized trials was assessed by Cochrane risk-of-bias tool. The main outcome parameters were analysed separately based on the Premenstrual Symptom Screening Tool and PMTS and DRSP scores. Secondary parameters of somatic, psychological, and behavioural subscale symptoms of PSST were also analysed. Data synthesis was performed assuming a random-effects model, and standardized mean difference (SMDs) was analysed using SPSS version 28.0.0 (IBM, Armonk, NY, USA). A total of 754 articles were screened, and 15 RCTs were included (n = 1211 patients). Primary results for participants randomized to an intervention reported reduced PSST (n = 9), PMTS (n = 2), and DSR (n = 4) scores with (SMD = −1.44; 95% CI: −1.72 to −1.17), (SMD = −1.69; 95% CI: −3.80 to 0.42) and (SMD = 2.86; 95% CI: 1.02 to 4.69) verses comparator with substantial heterogeneity. Physical (SMD = −1.61; 95% CI = −2.56 to −0.66), behavioural (SMD = −0.60; 95% CI = −1.55 to0.35) and mood (SMD = 0.57; 95% CI = −0.96 to 2.11) subscale symptom groupings of PSST displayed similar findings. Fifty-three studies (n = 8) were considered at low risk of bias with high quality. Mild adverse events were reported by four RCTs. Based on the existing evidence, herbal medicine and nutritional supplements may be effective and safe for PMS
metadata
Sultana, Arshiya; Heyat, Md Belal Bin; Rahman, Khaleequr; Kunnavil, Radhika; Fazmiya, Mohamed Joonus Aynul; Akhtar, Faijan; Sumbul, X.; Vidal Mazón, Juan Luis; Rodríguez Velasco, Carmen Lilí y De La Torre Díez, Isabel
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR
(2022)
A Systematic Review and Meta-Analysis of Premenstrual Syndrome with Special Emphasis on Herbal Medicine and Nutritional Supplements.
Pharmaceuticals, 15 (11).
p. 1371.
ISSN 1424-8247
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Currently, sustainability is a vital aspect for every nation and organization to accomplish Sustainable Development Goals (SDGs) by 2030. Environmental, social, and governance (ESG) metrics are used to evaluate the sustainability level of an organization. According to the statistics, 53% of respondents in the BlackRock survey are concerned about the availability of low ESG data, which is critical for determining the organization’s sustainability level. This obstacle can be overcome by implementing Industry 4.0 technologies, which enable real-time data, data authentication, prediction, transparency, authentication, and structured data. Based on the review of previous studies, it was determined that only a few studies discussed the implementation of Industry 4.0 technologies for ESG data and evaluation. The objective of the study is to discuss the significance of ESG data and report, which is used for the evaluation of the sustainability of an organization. In this regard, the assimilation of Industry 4.0 technologies (Internet of Things (IoT), artificial intelligence (AI), blockchain, and big data for obtaining ESG data by an organization is detailed presented to study the progress of advancement of these technologies for ESG. On the basis of analysis, this study concludes that consumers are concerned about the ESG data, as most organizations develop inaccurate ESG data and suggest that these digital technologies have a crucial role in framing an accurate ESG report. After analysis a few vital conclusions are drawn such as ESG investment has benefited from AI capabilities, which previously relied on self-disclosed, annualized company information that was susceptible to inherent data issues and biases. Finally, the article discusses the vital recommendations that can be implemented for future work
metadata
Saxena, Archana; Singh, Rajesh; Gehlot, Anita; Akram, Shaik Vaseem; Twala, Bhekisipho; Singh, Aman; Caro Montero, Elisabeth y Priyadarshi, Neeraj
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, elizabeth.caro@uneatlantico.es, SIN ESPECIFICAR
(2022)
Technologies Empowered Environmental, Social, and Governance (ESG): An Industry 4.0 Landscape.
Sustainability, 15 (1).
p. 309.
ISSN 2071-1050
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
With a view of the post-COVID-19 world and probable future pandemics, this paper presents an Internet of Things (IoT)-based automated healthcare diagnosis model that employs a mixed approach using data augmentation, transfer learning, and deep learning techniques and does not require physical interaction between the patient and physician. Through a user-friendly graphic user interface and availability of suitable computing power on smart devices, the embedded artificial intelligence allows the proposed model to be effectively used by a layperson without the need for a dental expert by indicating any issues with the teeth and subsequent treatment options. The proposed method involves multiple processes, including data acquisition using IoT devices, data preprocessing, deep learning-based feature extraction, and classification through an unsupervised neural network. The dataset contains multiple periapical X-rays of five different types of lesions obtained through an IoT device mounted within the mouth guard. A pretrained AlexNet, a fast GPU implementation of a convolutional neural network (CNN), is fine-tuned using data augmentation and transfer learning and employed to extract the suitable feature set. The data augmentation avoids overtraining, whereas accuracy is improved by transfer learning. Later, support vector machine (SVM) and the K-nearest neighbors (KNN) classifiers are trained for lesion classification. It was found that the proposed automated model based on the AlexNet extraction mechanism followed by the SVM classifier achieved an accuracy of 98%, showing the effectiveness of the presented approach.
metadata
Shafi, Imran; Sajad, Muhammad; Fatima, Anum; Gavilanes Aray, Daniel; Lipari, Vivian; Diez, Isabel de la Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, daniel.gavilanes@uneatlantico.es, vivian.lipari@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Teeth Lesion Detection Using Deep Learning and the Internet of Things Post-COVID-19.
Sensors, 23 (15).
p. 6837.
ISSN 1424-8220
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Driving while drowsy poses significant risks, including reduced cognitive function and the potential for accidents, which can lead to severe consequences such as trauma, economic losses, injuries, or death. The use of artificial intelligence can enable effective detection of driver drowsiness, helping to prevent accidents and enhance driver performance. This research aims to address the crucial need for real-time and accurate drowsiness detection to mitigate the impact of fatigue-related accidents. Leveraging ultra-wideband radar data collected over five minutes, the dataset was segmented into one-minute chunks and transformed into grayscale images. Spatial features are retrieved from the images using a two-dimensional Convolutional Neural Network. Following that, these features were used to train and test multiple machine learning classifiers. The ensemble classifier RF-XGB-SVM, which combines Random Forest, XGBoost, and Support Vector Machine using a hard voting criterion, performed admirably with an accuracy of 96.6%. Additionally, the proposed approach was validated with a robust k-fold score of 97% and a standard deviation of 0.018, demonstrating significant results. The dataset is augmented using Generative Adversarial Networks, resulting in improved accuracies for all models. Among them, the RF-XGB-SVM model outperformed the rest with an accuracy score of 99.58%.
metadata
Siddiqui, Hafeez Ur Rehman; Akmal, Ambreen; Iqbal, Muhammad; Saleem, Adil Ali; Raza, Muhammad Amjad; Zafar, Kainat; Zaib, Aqsa; Dudley, Sandra; Arambarri, Jon; Kuc Castilla, Ángel Gabriel y Rustam, Furqan
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, jon.arambarri@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Ultra-Wide Band Radar Empowered Driver Drowsiness Detection with Convolutional Spatial Feature Engineering and Artificial Intelligence.
Sensors, 24 (12).
p. 3754.
ISSN 1424-8220
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés This paper reports the behaviour of solid urban waste generation in the Metropolitan Area of Misiones, during a period of seven days. The waste analysed came from collection routes by household sampling points determined according to the land use and socioeconomic level of the population in the study area. The methodology consisted of visualising the sample universe, selecting the household waste collection routes and then classifying and analysing their composition according to ASTM D5231-92 (2016). This strategy was considered valid, given that the habits and customs of the population are closely related to the socioeconomic levels that directly affect consumption and consequently the quality of waste. Organic matter (51.80%) was the most representative, followed by materials with recycling potential, such as plastic (13.90%), glass (7.90%), paper and cardboard (7.80%), metals/aluminium (2.20%) and tetrabrik (2.60%). The quality of MSW was not uniform between cities, with Garupá (61.50%) being the city that generated the most organic waste, followed by Posadas (57.50%) and ending with Candelaria (29.00%) with a marked decrease. As a limitation of the method, it was determined that the results are representative of each city and of the winter season. metadata Sambiasi, Cesar G.; Pascual Barrera, Alina Eugenia y Sambiasi, Maria A. mail SIN ESPECIFICAR, alina.pascual@unini.edu.mx, SIN ESPECIFICAR (2022) Urban Solid Waste Characterization of the Misiones Metropolitan Area. Revista de Ciencia y Tecnología (38). pp. 36-41. ISSN 03298922
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Unfired admixed soil blocks are made up of soil plus stabilizers such as binders, fibers, or a combination of both. Soil is abundant on Earth, and it has been used to provide shelter to millions of people. The manufacturing and usage of cement and cement blocks raise several environmental and economic challenges. Due to disposal issues, agricultural and industrial waste is currently the biggest hazard to the environment and humanity in the world. Consequently, environmental degradation brought on by agricultural waste harms the ecology. As a result, researchers are attempting to develop an alternative to cement blocks, and various tests on unfired admixed soil blocks have been done. This investigation uses agricultural waste (i.e., paddy straw fiber and sugarcane bagasse ash) and industrial waste (i.e., marble dust) in manufacturing unfired admixed soil blocks. Under this investigation, the applicability of unfired soil blocks admixed with marble dust, paddy straw fiber, and bagasse ash was studied. The marble dust level ranged from 25% to 35%, bagasse ash content ranged from 7.5% to 12.5%, and the content of paddy straw fiber ranged from 0.8% to 1.2% by soil dry weight. Various tests were conducted on the 81 mix designs of the prepared unfired admixed soil blocks to find out the physical properties of the block followed by modeling and optimization. The findings demonstrate that the suggested method is a superior alternative to burned bricks for improving the physical properties of admixed soil blocks without firing metadata Sharma, Tarun; Singh, Sandeep; Sharma, Shubham; Sharma, Prashant; Gehlot, Anita; Shukla, Anand Kumar y Eldin, Sayed M. mail SIN ESPECIFICAR (2022) The Use of Marble Dust, Bagasse Ash, and Paddy Straw to Improve the Water Absorption and Linear Shrinkage of Unfired Soil Block for Structure Applications. Materials, 15 (21). p. 7786. ISSN 1996-1944
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
For analytical approach-based word recognition techniques, the task of segmenting the word into individual characters is a big challenge, specifically for cursive handwriting. For this, a holistic approach can be a better option, wherein the entire word is passed to an appropriate recognizer. Gurumukhi script is a complex script for which a holistic approach can be proposed for offline handwritten word recognition. In this paper, the authors propose a Convolutional Neural Network-based architecture for recognition of the Gurumukhi month names. The architecture is designed with five convolutional layers and three pooling layers. The authors also prepared a dataset of 24,000 images, each with a size of 50 × 50. The dataset was collected from 500 distinct writers of different age groups and professions. The proposed method achieved training and validation accuracies of about 97.03% and 99.50%, respectively for the proposed dataset.
metadata
Singh, Tajinder Pal; Gupta, Sheifali; Garg, Meenu; Gupta, Deepali; Alharbi, Abdullah; Alyami, Hashem; Anand, Divya; Ortega-Mansilla, Arturo y Goyal, Nitin
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, arturo.ortega@uneatlantico.es, SIN ESPECIFICAR
(2022)
Visualization of Customized Convolutional Neural Network for Natural Language Recognition.
Sensors, 22 (8).
p. 2881.
ISSN 1424-8220
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
This study sought to investigate how different brain regions are affected by Alzheimer’s disease (AD) at various phases of the disease, using independent component analysis (ICA). The study examines six regions in the mild cognitive impairment (MCI) stage, four in the early stage of Alzheimer’s disease (AD), six in the moderate stage, and six in the severe stage. The precuneus, cuneus, middle frontal gyri, calcarine cortex, superior medial frontal gyri, and superior frontal gyri were the areas impacted at all phases. A general linear model (GLM) is used to extract the voxels of the previously mentioned regions. The resting fMRI data for 18 AD patients who had advanced from MCI to stage 3 of the disease were obtained from the ADNI public source database. The subjects include eight women and ten men. The voxel dataset is used to train and test ten machine learning algorithms to categorize the MCI, mild, moderate, and severe stages of Alzheimer’s disease. The accuracy, recall, precision, and F1 score were used as conventional scoring measures to evaluate the classification outcomes. AdaBoost fared better than the other algorithms and obtained a phenomenal accuracy of 98.61%, precision of 99.00%, and recall and F1 scores of 98.00% each.
metadata
Shahzadi, Samra; Butt, Naveed Anwer; Sana, Muhammad Usman; Elío Pascual, Iñaki; Briones Urbano, Mercedes; Díez, Isabel de la Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, inaki.elio@uneatlantico.es, mercedes.briones@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Voxel Extraction and Multiclass Classification of Identified Brain Regions across Various Stages of Alzheimer’s Disease Using Machine Learning Approaches.
Diagnostics, 13 (18).
p. 2871.
ISSN 2075-4418
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The most important and emerging characteristic of Wireless Body Area Networks (WBANs), which differentiates them from other wired and wireless area networks, is mobility. Therefore, the routing protocols for WBAN are designed in such a way that they can deal with dynamic changes in topology and provide maximum throughput, packet delivery ratio, average end-to-end delay, and minimum energy consumption. Thus, achieving optimal values for every performance parameter becomes a big challenge. This work investigates the performance of three separate path discovery protocols, such as Destination-Sequenced Distance-Vector Routing (DSDV), Ad Hoc On-demand Distance Vector (AODV), and Ad Hoc On-demand Multipath Distance Vector Routing protocol (AOMDV), for two different mobility models with a fixed-positioned sink. During experimentation, the AOMDV routing protocol achieves a high packet delivery ratio (PDR), average end-to-end delay, and throughput as compared to other routing protocols.
metadata
Singh, Sunny; Prasad, Devendra; Rani, Shalli; Singh, Aman; Alharithi, Fahd S. y Almotiri, Jasem
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Wireless Body Area Routing Protocols Impact Analysis on Entity Mobility Models with Static Sink Node.
Applied Sciences, 12 (11).
p. 5655.
ISSN 2076-3417
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
This research intent for enhancing creative writing skills in eleventh EFL learners through the implementation of TBLT, by different kinds of activities to carry out into the classroom to develop students' imagination and encourage them to learn English in a way they can profit it. The reason of choosing TBLT to enhance creative writing is because during the learning/teaching process it is noticed that students have difficulties to write texts or short coherent. This problem is presented because of the lack of vocabulary, knowledge, and grammar structures. So, considering that it is relevant to work on creative writing skill and at least achieved an improvement in matter of producing some phrases and short texts. That is why, vocabulary and grammar would play important role in the learning process given that it is easier to use creative writing activities in a second language knowing a lot of vocabulary and the rules of grammar but using strategies that can boost the learning process. Teaching writing in foreign language learners brings challenges and efforts to promote linguistic competences as grammar, vocabulary, writing mechanics, and process and text structures, which means not only words but communication and meaning. In this way, creative writing looks for stimulating students to learn English in creative situations letting them communicate and interact with the L2 in a meaningful and fruitful method, exchanging information, improving their imagination, supporting ideas, gain vocabulary, to motivate them to see the foreign language as a vehicle for social interaction and show them it is possible to learn English doing what they like, and one of the language teaching approaches which focuses on learning to communicate through interaction is TBLT. This project can benefit teachers and students since they can use task-based creative writing activities to contribute in the improvement of writing skill.
metadata
Suarez Carvajal, Jeniffer Elizabeth
mail
jeniffersuarez.0206@gmail.com
(2022)
An action research for implementing task-based creative writing activities in an EFL 11th grade class at Colegio Antonio Nariño, in Colombia.
Masters thesis, SIN ESPECIFICAR.
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés In present investigation, the impact of nanoparticle concentration on the machining accomplishment of Hastelloy C-276 has been examined in turning operation. The outputs like temperature, surface roughness, chip reduction coefficient (CRC), tool wear, and friction coefficient along with angle of shear have been estimated. The graphene nanoparticles (GnP) have been blended into soybean oil in distinct weight/volume ratio of 0.5, 1 and 1.5%. The experimental observations revealed that higher concentration of nanoparticles has enhanced the heat carrying capacity of amalgamation by 12.28%, surface roughness (27.88%), Temperature (16.8%), tool wear (22.5%), CRC (17.5%), coefficient of friction (46.36%) and shear angle (15%). Scanning electron microscopy identified nose wear, abrasion, adhesion and loss of tool coating. Further, lower tool wear has been noticed at 1.5% concentration, while the complete failure of insert has been reported during 116 m/min, 0.246 mm/rev having 0.5% concentration. ANOVA results exhibited that surface roughness is highly influenced by speed rate (41.66%) trailed by feed rate (28.16%) and then after concentration (13.68%). Temperature is dominated by cutting speed (69.31%), concentration (14.53%) and feed rate (13.25%). Likewise, tool wear was majorly altered by cutting speed (67.2%) accompanied by feed rate (23.90%) and thirdly concentration of GnP (5.03%). metadata Singh, Gurpreet; Sharma, Shubham; Seikh, A.H.; Li, Changhe; Zhang, Yanbin; Rajkumar, S.; Kumar, Abhinav; Singh, Rajesh y Eldin, Sayed M. mail SIN ESPECIFICAR (2023) A novel study on the influence of graphene-based nanofluid concentrations on the response characteristics and surface-integrity of Hastelloy C-276 during minimum quantity lubrication. Heliyon, 9 (9). e19175. ISSN 24058440
T
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
This paper presents a current- and voltage-driven protection scheme for transmission lines based on a hybrid mix of Stockwell transform (ST) and Hilbert transform (HT). Use of both current and voltage waveforms to detect and categorize faults, improves the reliability of this protection scheme and avoids false tripping. Current and voltage waveforms captured during a period of fault are analyzed using ST to compute a median intermediate fault index (MIFI), a maximum value intermediate fault index (MVFI), and a summation intermediate fault index (SIFI). Current and voltage signals are analyzed via applying HT to compute a Hilbert fault index (HFI). The proposed hybrid current and voltage fault index (HCVFI) is obtained from the MIFI, MVFI, SIFI, and HFI. A threshold magnitude for this hybrid current and voltage fault index (HCVFITH) is set to 500 to identify the faulty phase. The HCVFIT is selected after testing the method for various conditions of different fault locations, different fault impedances, different fault occurrence angles, and reverse flows of power. Fault classification is performed using the number of faulty phases and an index for ground detection (IGD). The ground involved in a fault is detected by comparison of peak IGD magnitude with a threshold for ground detection (THGD). THGD is considered equal to 1000 in this study. The study is carried out using a two-terminal transmission line modeled in MATLAB software. The performance of the proposed technique is better compared to a discrete wavelet transform (DWT)-based technique, a time–frequency approach, and an alienation method. Our algorithm effectively detected an AG fault, observed on a practical transmission line.
metadata
Tang, Ligang; Mahela, Om Prakash; Khan, Baseem y Miró Vera, Yini Airet
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, yini.miro@uneatlantico.es
(2023)
Current- and Voltage-Actuated Transmission Line Protection Scheme Using a Hybrid Combination of Signal Processing Techniques.
Sustainability, 15 (7).
p. 5715.
ISSN 2071-1050
Artículo
Materias > Biomedicina
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Pregnancy-associated anemia is a significant health issue that poses negative consequences for both the mother and the developing fetus. This study explores the triggering factors of anemia among pregnant females in India, utilizing data from the Demographic and Health Survey 2019–21. Chi-squared and gamma tests were conducted to find out the relationship between anemia and various socioeconomic and sociodemographic elements. Furthermore, ordinal logistic regression and multinomial logistic regression were used to gain deeper insight into the factors that affect anemia among pregnant women in India. According to these findings, anemia affects about 50% of pregnant women in India. Anemia is significantly associated with various factors such as geographical location, level of education, and wealth index. The results of our study indicate that enhancing education and socioeconomic status may serve as viable approaches for mitigating the prevalence of anemia disease developed in pregnant females in India. Employing both Ordinal and Multinominal logistic regression provides a more comprehensive understanding of the risk factors associated with anemia, enabling the development of targeted interventions to prevent and manage this health condition. This paper aims to enhance the efficacy of anemia prevention and management strategies for pregnant women in India by offering an in-depth understanding of the causative factors of anemia.
metadata
Talin, Iffat Ara; Abid, Mahmudul Hasan; Samad, Md Abdus; Dominguez Azpíroz, Irma; de la Torre Diez, Isabel; Ashraf, Imran y Nahid, Abdullah-Al
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, irma.dominguez@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2023)
Exploring factors influencing the severity of pregnancy anemia in India: a study using proportional odds model.
Scientific Reports, 13 (1).
ISSN 2045-2322
Artículo Materias > Educación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Portugués O estudo aqui apresentado tem como objetivo apresentar sobre o acesso à primeira etapa daEducação básica, Educação Infantil, de 0 a 5 anos no Estado de Mato Grosso, Brasil. A contribuição doestudo, se manifesta por entender sobre a importância do trabalho realizado no âmbito educacional pordireito da criança. A infância é o período que se alicerça toda a estrutura de um indivíduo, em todas asdimensões. Oportunamente, a relevância do desenvolvimento desta pesquisa vem investigar sobre: comoestá o acesso à Educação Infantil no Estado de Mato Grosso, estando ao final do Plano Nacional deEducação?O método de pesquisa foi realizado através de pesquisa quantitativa, a partir do Censo escolar,Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira (INEP) e Instituto Brasileiro deGeografia e Estatística (IBGE) dos últimos anos (2010 a 2021).A análise ocorreu de natureza básica, a partir dos dados numéricos e estatísticos por meio detabelas, gráficos e descrição dos dados. metadata Tadeu Queiroz de Moraes, Carlos y Cadidé Vilela, Maria Cristiana mail SIN ESPECIFICAR (2023) O acesso à educação infantil no estado de Mato Grosso–Brasil: ao final do Plano Nacional de Educação (2014-2024). Project Design and Management. ISSN 2683-1597
U
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Public concern regarding health systems has experienced a rapid surge during the last two years due to the COVID-19 outbreak. Accordingly, medical professionals and health-related institutions reach out to patients and seek feedback to analyze, monitor, and uplift medical services. Such views and perceptions are often shared on social media platforms like Facebook, Instagram, Twitter, etc. Twitter is the most popular and commonly used by the researcher as an online platform for instant access to real-time news, opinions, and discussion. Its trending hashtags (#) and viral content make it an ideal hub for monitoring public opinion on a variety of topics. The tweets are extracted using three hashtags #healthcare, #healthcare services, and #medical facilities. Also, location and tweet sentiment analysis are considered in this study. Several recent studies deployed Twitter datasets using ML and DL models, but the results show lower accuracy. In addition, the studies did not perform extensive comparative analysis and lack validation. This study addresses two research questions: first, what are the sentiments of people toward medical services worldwide? and second, how effective are the machine learning and deep learning approaches for the classification of sentiment on healthcare tweets? Experiments are performed using several well-known machine learning models including support vector machine, logistic regression, Gaussian naive Bayes, extra tree classifier, k nearest neighbor, random forest, decision tree, and AdaBoost. In addition, this study proposes a transfer learning-based LSTM-ETC model that effectively predicts the customer’s satisfaction level from the healthcare dataset. Results indicate that despite the best performance by the ETC model with an 0.88 accuracy score, the proposed model outperforms with a 0.95 accuracy score. Predominantly, the people are happy about the provided medical services as the ratio of the positive sentiments is substantially higher than the negative sentiments. The sentiments, either positive or negative, play a crucial role in making important decisions through customer feedback and enhancing quality.
metadata
Usman, Muhammad; Mujahid, Muhammad; Rustam, Furqan; Soriano Flores, Emmanuel; Vidal Mazón, Juan Luis; Díez, Isabel de la Torre y Ashraf, Imran
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, emmanuel.soriano@uneatlantico.es, juanluis.vidal@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Analyzing patients satisfaction level for medical services using twitter data.
PeerJ Computer Science, 10.
e1697.
ISSN 2376-5992
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Abierto
Inglés
The rapid expansion of Internet of Things (IoT) devices deploys various sensors in different applications like homes, cities and offices. IoT applications depend upon the accuracy of sensor data. So, it is necessary to predict faults in the sensor and isolate their cause. A novel primitive technique named fall curve is presented in this paper which characterizes sensor faults. This technique identifies the faulty sensor and determines the correct working of the sensor. Different sources of sensor faults are explained in detail whereas various faults that occurred in sensor nodes available in IoT devices are also presented in tabular form. Fault prediction in digital and analog sensors along with methods of sensor fault prediction are described. There are several advantages and disadvantages of sensor fault prediction methods and the fall curve technique. So, some solutions are provided to overcome the limitations of the fall curve technique. In this paper, a bibliometric analysis is carried out to visually analyze 63 papers fetched from the Scopus database for the past five years. Its novelty is to predict a fault before its occurrence by looking at the fall curve. The sensing of current flow in devices is important to prevent a major loss. So, the fall curves of ACS712 current sensors configured on different devices are drawn for predicting faulty or non-faulty devices. The analysis result proved that if any of the current sensors gets faulty, then the fall curve will differ and the value will immediately drop to zero. Various evaluation metrics for fault prediction are also described in this paper. At last, this paper also addresses some possible open research issues which are important to deal with false IoT sensor data.
metadata
Uppal, Mudita; Gupta, Deepali; Anand, Divya; S. Alharithi, Fahd; Almotiri, Jasem; Ortega-Mansilla, Arturo; Singh, Dinesh y Goyal, Nitin
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, arturo.ortega@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Fault Pattern Diagnosis and Classification in Sensor Nodes Using Fall Curve.
Computers, Materials & Continua, 72 (1).
pp. 1799-1814.
ISSN 1546-2226
Artículo
Materias > Biomedicina
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto
Inglés
Interleukin-10, a highly effective cytokine recognized for its anti-inflammatory properties, plays a critical role in the immune system. In addition to its well-documented capacity to mitigate inflammation, IL-10 can unexpectedly demonstrate pro-inflammatory characteristics under specific circumstances. The presence of both aspects emphasizes the vital need to identify the IL-10-induced peptide. To mitigate the drawbacks of manual identification, which include its high cost, this study introduces StackIL10, an ensemble learning model based on stacking, to identify IL-10-inducing peptides in a precise and efficient manner. Ten Amino-acid-composition-based Feature Extraction approaches are considered. The StackIL10, stacking ensemble, the model with five optimized Machine Learning Algorithm (specifically LGBM, RF, SVM, Decision Tree, KNN) as the base learners and a Logistic Regression as the meta learner was constructed, and the identification rate reached 91.7%, MCC of 0.833 with 0.9078 Specificity. Experiments were conducted to examine the impact of various enhancement techniques on the correctness of IL-10 Prediction. These experiments included comparisons between single models and various combinations of stacking-based ensemble models. It was demonstrated that the model proposed in this study was more effective than singular models and produced satisfactory results, thereby improving the identification of peptides that induce IL-10.
metadata
Usmani, Salman Sadullah; Tuhin, Izaz Ahmmed; Mia, Md. Rajib; Islam, Md. Monirul; Islam, Md. Monirul; Mahmud, Imran; Uc Ríos, Carlos Eduardo; Fabian Gongora, Henry; Ashraf, Imran y Samad, Md. Abdus
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, carlos.uc@unini.edu.mx, henry.gongora@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
StackIL10: A stacking ensemble model for the improved prediction of IL-10 inducing peptides.
PLOS ONE, 19 (11).
e0313835.
ISSN 1932-6203
V
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Population and industrial growth in Mexico’s Bajío region demand greater electricity consumption. The production of electricity from fuel oil has severe implications on climate change and people’s health due to SO2 emissions. This study describes the simulation of eight different scenarios for SO2 pollutant dispersion. It takes into account distance, geoenvironmental parameters, wind, terrain roughness, and Pasquill–Gifford–Turner atmospheric stability and categories of dispersion based on technical information about SO2 concentration from stacks and from one of the atmospheric monitoring stations in Salamanca city. Its transverse character, its usefulness for modeling, and epidemiological, meteorological, and fluid dynamics studies, as suggested by the models approved by the Environmental Protection Agency (EPA), show a maximum average concentration of 399 µg/m3, at an average distance of 1800 m. The best result comparison in the scenarios was scenery 8. Maximum nocturnal dispersion was shown at a wind speed of 8.4 m/s, and an SO2 concentration of 280 µg/m3 for stack 4, an atypical situation due to the geography of the city. From the validation process, a relative error of 14.7 % was obtained, which indicates the reliability of the applied Gaussian model. Regarding the mathematical solution of the model, this represents a reliable and low-cost tool that can help improve air quality management, the location or relocation of atmospheric monitoring stations, and migration from the use of fossil fuels to environmentally friendly fuels.
metadata
Violante Gavira, Amanda Enrriqueta; Sosa González, Wadi Elim; Pali-Casanova, Ramón; Yam Cervantes, Marcial Alfredo; Aguilar Vega, Manuel; Chacha Coto, Javier; Zavala Loría, José del Carmen; Dzul López, Luis Alonso y García Villena, Eduardo
mail
amanda@ugto.mx, SIN ESPECIFICAR, ramon.pali@unini.edu.mx, marcial.yam@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, jose.zavala@unini.edu.mx, luis.dzul@uneatlantico.es, eduardo.garcia@uneatlantico.es
(2022)
Application of the Gaussian Model for Monitoring Scenarios and Estimation of SO2 Atmospheric Emissions in the Salamanca Area, Bajío, Mexico.
Atmosphere, 13 (6).
p. 874.
ISSN 2073-4433
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés A population explosion has resulted in garbage generation on a large scale. The process of proper and automatic garbage collection is a challenging and tedious task for developing countries. This paper proposes a deep learning-based intelligent garbage detection system using an Unmanned Aerial Vehicle (UAV). The main aim of this paper is to provide a low-cost, accurate and easy-to-use solution for handling the garbage effectively. It also helps municipal corporations to detect the garbage areas in remote locations automatically. This automation was derived using two Convolutional Neural Network (CNN) models and images of solid waste were captured by the drone. Both models were trained on the collected image dataset at different learning rates, optimizers and epochs. This research uses symmetry during the sampling of garbage images. Homogeneity regarding resizing of images is generated due to the application of symmetry to extract their characteristics. The performance of two CNN models was evaluated with the state-of-the-art models using different performance evaluation metrics such as precision, recall, F1-score, and accuracy. The CNN1 model achieved better performance for automatic solid waste detection with 94% accuracy metadata Verma, Vishal; Gupta, Deepali; Gupta, Sheifali; Uppal, Mudita; Anand, Divya; Ortega-Mansilla, Arturo; Alharithi, Fahd S.; Almotiri, Jasem y Goyal, Nitin mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, arturo.ortega@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2022) A Deep Learning-Based Intelligent Garbage Detection System Using an Unmanned Aerial Vehicle. Symmetry, 14 (5). p. 960. ISSN 2073-8994
Artículo
Materias > Educación física y el deporte
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Abstract: Sports injuries can affect the performance of athletes. For this reason, functional tests are used for injury assessment and prevention, analyzing physical or physiological imbalances and detecting asymmetries. The main aim of this study was to detect the asymmetries in the upper limbs (right and left arms) in athletes, using the OctoBalance Test (OB), depending on the stage of the season. Two hundred and fifty-two participants (age: 23.33 ± 8.96 years old; height: 178.63 ± 11.12 cm; body mass: 80.28 ± 17.61 kg; body mass index: 24.88 ± 4.58; sports experience: 12.52 ± 6.28 years), practicing different sports (rugby, athletics, football, swimming, handball, triathlon, basketball, hockey, badminton and volleyball), assessed with the OB in medial, superolateral, and inferolateral directions in both arms, in four moments of the season (May 2017, September 2017, February 2018 and May 2018). ANOVA test was used with repeated measures with a p ≤ 0.05, for the analysis of the different studied variances. Significant differences were found (p = 0.021) in the medial direction of the left arm, between the first (May 2017) and fourth stages (May 2018), with values of 71.02 ± 7.15 cm and 65.03 ± 7.66 cm. From the detection of asymmetries, using the OB to measure, in the medial, superolateral and inferolateral directions, mobility and balance can be assessed. In addition, it is possible to observe functional imbalances, as a risk factor for injury, in each of the stages into which the season is divided, which will help in the prevention of injuries and in the individualization of training.
metadata
Velarde-Sotres, Álvaro; Bores-Cerezal, Antonio; Mecías-Calvo, Marcos; Barcala Furelos, Martín; Aparicio Obregón, Silvia y Calleja-González, Julio
mail
alvaro.velarde@uneatlantico.es, antonio.bores@uneatlantico.es, marcos.mecias@uneatlantico.es, martin.barcala@uneatlantico.es, silvia.aparicio@uneatlantico.es, SIN ESPECIFICAR
(2022)
Detection of Upper Limb Asymmetries in Athletes According to
the Stage of the Season—A Longitudinal Study.
International Journal of Environmental Research and Public Health, 19 (2).
p. 849.
ISSN 1660-4601
Artículo Materias > Educación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Una educación universitaria de calidad, coherente con las normas del sistema educativo, sustentado por una gestión docente flexible enfocada en el aprendizaje y buenos resultados académicos, se esmera en constantemente actualizar e innovar sus clases con mejores estrategias que motiven un desarrollo significativo en sus estudiantes. El modelo de los estilos de aprendizaje de Honey - Alonso (1992), se consolida en el contexto universitario como un instrumento validado que reconoce el perfil de cada alumno para mejorar su experiencia, haciéndola más sencilla y satisfactoria, para lograr ser mejor aprendiz en diferentes contextos. El presente estudio tiene como objetivo identificar los estilos de aprendizaje en los estudiantes de la carrera de Administración y Negocios Internacionales de la Universidad La Salle (2021), y determinar la posible correlación entre los estilos con respecto del rendimiento académico, sexo y ciclo de estudio. La investigación es de naturaleza cuantitativa de alcance descriptivo – correlacional, se utilizó el Cuestionario Honey – Alonso de Estilos de Aprendizaje (CHAEA) y el registro de las notas del ciclo anterior de los estudiantes de la carrera profesional seleccionada. Los resultados indican que el estilo Teórico es el de mayor preferencia entre los alumnos universitarios de esta carrera, además no hay relación entre el estilo de aprendizaje con el sexo o el ciclo de estudio, y se puede afirmar que existe relación entre los estilos de aprendizaje con el rendimiento académico. metadata Valdivia Rodríguez, Paola Verónica y Tamayo Ancona, Martín Eliseo mail paola.valdivia@doctorado.unini.edu.mx, martin.ancona@unini.edu.mx (2023) Función del estilo de aprendizaje en el rendimiento académico de los estudiantes de Administración y Negocios Internacionales en una institución universitaria en Perú. MLS Educational Research, 7 (1). ISSN 2603-5820
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Education 4.0 imitates Industry 4.0 in many aspects such as technology, customs, challenges, and benefits. The remarkable advancement in embryonic technologies, including IoT (Internet of Things), Fog Computing, Cloud Computing, and Augmented and Virtual Reality (AR/VR), polishes every dimension of Industry 4.0. The constructive impacts of Industry 4.0 are also replicated in Education 4.0. Real-time assessment, irregularity detection, and alert generation are some of the leading necessities of Education 4.0. Conspicuously, this study proposes a reliable assessment, irregularity detection, and alert generation framework for Education 4.0. The proposed framework correspondingly addresses the comparable issues of Industry 4.0. The proposed study (1) recommends the use of IoT, Fog, and Cloud Computing, i.e., IFC technological integration for the implementation of Education 4.0. Subsequently, (2) the Symbolic Aggregation Approximation (SAX), Kalman Filter, and Learning Bayesian Network (LBN) are deployed for data pre-processing and classification. Further, (3) the assessment, irregularity detection, and alert generation are accomplished over SoTL (the set of threshold limits) and the Multi-Layered Bi-Directional Long Short-Term Memory (M-Bi-LSTM)-based predictive model. To substantiate the proposed framework, experimental simulations are implemented. The experimental outcomes substantiate the better performance of the proposed framework, in contrast to the other contemporary technologies deployed for the enactment of Education 4.0
metadata
Verma, Anil; Anand, Divya; Singh, Aman; Vij, Rishika; Alharbi, Abdullah; Alshammari, Majid y Ortega-Mansilla, Arturo
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, arturo.ortega@uneatlantico.es
(2022)
IoT-Inspired Reliable Irregularity-Detection Framework for Education 4.0 and Industry 4.0.
Electronics, 11 (9).
p. 1436.
ISSN 2079-9292
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Ante la adopción creciente del modelo ISO 9000 por las Empresas Industriales de Productos Algodoneros Textiles en Bolivia (EIPAT), para abordar eficazmente un contexto dinámico y, al no poder visibilizar cambios representativos en su desempeño; además, considerando el impacto de un Liderazgo sólido en los colaboradores y su repercusión en los procesos y la organización, y por último, siendo uno de los principios de gestión de la calidad el Liderazgo; se buscó establecer la relación entre éste y el Éxito Organizacional (EO). Se establecieron 2 objetivos: (1) Determinar si los niveles de dirección ejercen las acciones de Liderazgo recomendadas por el modelo ISO 9000 y, (2) Determinar la relación que existe entre el Liderazgo que se ejerce en cada uno de los niveles de dirección y el EO. La hipótesis alterna fue “Las acciones para ejercer Liderazgo influyen positivamente en el Éxito de las organizaciones con certificación ISO 9001”; y la nula “Las acciones para ejercer Liderazgo no influyen positivamente en el Éxito de las organizaciones con certificación ISO 9001”. El instrumento de recolección de información fue validado por expertos en metodología de la investigación y el estadístico Alfa de Cronbach. En el análisis de los datos se utilizó las medidas de tendencia central y variabilidad para lo descriptivo y el coeficiente de correlación de Spearman para lo correlacional; lo cual permitió determinar que existe una relación positiva fuerte y moderada entre las variables de estudio; así como, que los niveles de dirección medios ejercen con mayor frecuencia dichas prácticas. metadata Vasquez Lema, Marcelo Rodrigo y Vázquez Loayza, Juan Pablo mail SIN ESPECIFICAR (2021) Liderazgo y éxito organizacional con el modelo ISO 9001. Project Design and Management, 3 (1). pp. 89-112. ISSN 2683-1597
Tesis
Materias > Educación
Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Cerrado
Inglés
Most students find reading in a foreign language a difficult task, mainly due to the high number of unknown words they can locate when reading a text. They consider reading activities boring. Thus, as a result of it, students get low level of reading comprehension. Concerned with this situation. This action research project considered the great importance of boosting reading comprehension skills by using technology in a EFL classroom. It is important to highlight that this project constitutes a contribution to the field of Call Computer Assisted Language Learning (CALL) which nowadays catches the students ‘attention and motivation to learn English by using the internet. In that sense, this study concluded that WebQuests are considered as one of the important ways to join technology with learning.
metadata
Vargas Peña, Yirly Tatiana
mail
tatianavargas20@hotmail.com
(2022)
The effects of WebQuests in a EFL remote classroom: a Learning Constructivist strategy.
Masters thesis, SIN ESPECIFICAR.
Y
Artículo Materias > Educación Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español La expansión del internet y de los celulares inteligentes impactan hoy con fuerza en la democratización del conocimiento en el mundo. Y este conocimiento, a su vez, impacta en todas las actividades humanas, como el aprendizaje. El uso de las plataformas tecnológicas que soportan el aprendizaje electrónico, conocido por su nombre en inglés e-learning por parte de los alumnos, los profesores y la dirección académica, se encuentra en plena transformación. Por un lado, el dinamismo tecnológico al desarrollar nuevas funcionalidades no siempre bien adaptadas a la pedagogía. Y, por otro, la necesidad de encontrar un lenguaje de medios apropiado para el aprendizaje digital. El objetivo de esta investigación es analizar las brechas y oportunidades en el uso del foro en el entorno del aprendizaje virtual de los estudiantes de maestría de la Escuela de Posgrado de la Universidad Tecnológica del Perú (UTP). Se detectó la oportunidad para contribuir en la adaptación del docente a las nuevas competencias que exigen las tecnologías de la información y de la comunicación (TIC). La metodología empleada fue mixta cuantitativa y cualitativa con dos instrumentos de evaluación. El estudio permitió identificar oportunidades de mejora en el uso del foro virtual como impulsor de la experiencia de aprendizaje y valorar su impacto en la interacción social educativa. metadata Yamagoshi Wang, José Carlos y Darahuge, María Elena mail SIN ESPECIFICAR (2023) El foro virtual como impulsor de la experiencia de aprendizaje. MLS Educational Research, 7 (1). ISSN 2603-5820
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
Rivers are dynamic geological agents on the earth which transport the weathered materials of the continent to the sea. Estimation of suspended sediment yield (SSY) is essential for management, planning, and designing in any river basin system. Estimation of SSY is critical due to its complex nonlinear processes, which are not captured by conventional regression methods. Rainfall, temperature, water discharge, SSY, rock type, relief, and catchment area data of 11 gauging stations were utilized to develop robust artificial intelligence (AI), similar to an artificial-neural-network (ANN)-based model for SSY prediction. The developed highly generalized global single ANN model using a large amount of data was applied at individual gauging stations for SSY prediction in the Mahanadi River basin, which is one of India’s largest peninsular rivers. It appeared that the proposed ANN model had the lowest root-mean-squared error (0.0089) and mean absolute error (0.0029) along with the highest coefficient of correlation (0.867) values among all comparative models (sediment rating curve and multiple linear regression). The ANN provided the best accuracy at Tikarapara among all stations. The ANN model was the most suitable substitute over other comparative models for SSY prediction. It was also noticed that the developed ANN model using the combined data of eleven stations performed better at Tikarapara than the other ANN which was developed using data from Tikarapara only. These approaches are suggested for SSY prediction in river basin systems due to their ease of implementation and better performance.
metadata
Yadav, Arvind; Chithaluru, Premkumar; Singh, Aman; Joshi, Devendra; Elkamchouchi, Dalia H.; Mazas Pérez-Oleaga, Cristina y Anand, Divya
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, cristina.mazas@uneatlantico.es, divya.anand@uneatlantico.es
(2022)
An Enhanced Feed-Forward Back Propagation Levenberg–Marquardt Algorithm for Suspended Sediment Yield Modeling.
Water, 14 (22).
p. 3714.
ISSN 2073-4441
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español Dado que la gestión de proyectos es generalmente estresante debido a sus innumerables actividades, una gestión de recursos humanos subjetiva de los proyectos conduce a grandes conflictos y tensiones. El trabajo científico anterior se ha centrado más en la gestión de proyectos para grandes empresas. Las opiniones de los expertos en gestión de proyectos son divergentes entre quienes se muestran escépticos sobre su vínculo con HRM y quienes sostienen que HRM es una palanca global para el éxito del proyecto. Este estudio tiene como objetivo enriquecer este debate centrándose en la existencia de un vínculo entre la gestión de recursos humanos y la gestión de proyectos PYME. La hipótesis general del estudio se basa en el principio de que las prácticas de GRH de las PYMES pueden traducirse en objetividad en los procedimientos de contratación, la relevancia de los sistemas retributivos, los rigores en las acciones formativas y el desarrollo de habilidades determinan los niveles de productividad organizacional. El diseño metodológico adoptado es la técnica de muestreo basada en deseos de administrar un cuestionario a una muestra de 87 partes interesadas en el estudio. Los resultados revelan que las prácticas de gestión de recursos humanos tienen vínculos significativos con la productividad de las pymes. Estos resultados podrían explicarse por las características específicas de la gestión de recursos humanos en las pymes. A modo de discusión, dado que se realizan pocos estudios sobre la gestión de proyectos PYME, ¿no deberían los futuros metodólogos dar protagonismo a la exploración de esta perspectiva de investigación? metadata Youmbi, Djiowou y Antoinette, Song mail herve.djiowou@doctorado.unini.edu.mx, SIN ESPECIFICAR (2022) Gestión de proyectos empresariales en el eje de gestión de recursos humanos: impacto de las prácticas de gestión de recursos humanos en la productividad de las pymes agroalimentarias camerunesas. Project Design and Management, 4 (1). pp. 36-51. ISSN 2683-1597
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
Forecasting of sediment load (SL) is essential for reservoir operations, design of water resource structures, risk management, water resource planning and for preventing natural disasters in the river basin systems. Direct measurement of SL is difficult, labour intensive, and expensive. The development of an accurate and reliable model for forecasting the SL is required. Sediment transport is highly non-linear and is influenced by a variety of factors. Forecasting of the SL using various conventional methods is not highly accurate because of the association of various complex phenomena. In this study, major key factors such as rock type (RT), relief (R), rainfall (RF), water discharge (WD), temperature (T), catchment area (CA), and SL are recognized in developing the one-step-ahead SL forecasting model in the Mahanadi River (MR), which is among India’s largest rivers. Artificial neural networks (ANN) in conjunction with multi-objective genetic algorithm (ANN-MOGA)-based forecasting models were developed for forecasting the SL in the MR. The ANN-MOGA model was employed to optimize the two competing objective functions (bias and error variance) with simultaneous optimization of all associated ANN parameters. The performances of the proposed novel model were finally compared to other existing methods to verify the forecasting capability of the model. The ANN-MOGA model improved the performance by 12.81% and 10.19% compared to traditional AR and MAR regression models, respectively. The results suggested that hybrid ANN-MOGA models outperform traditional autoregressive and multivariate autoregressive forecasting models. Overall, hybrid ANN-MOGA intelligent techniques are recommended for the forecasting of SL in rivers
metadata
Yadav, Arvind; Ali Albahar, Marwan; Chithaluru, Premkumar; Singh, Aman; Alammari, Abdullah; Kumar, Gogulamudi Vijay y Miró Vera, Yini Airet
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, yini.miro@uneatlantico.es
(2023)
Hybridizing Artificial Intelligence Algorithms for Forecasting of Sediment Load with Multi-Objective Optimization.
Water, 15 (3).
p. 522.
ISSN 2073-4441
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Abierto
Inglés
Rivers play a major role within ecosystems and society, including for domestic, industrial, and agricultural uses, and in power generation. Forecasting of suspended sediment yield (SSY) is critical for design, management, planning, and disaster prevention in river basin systems. It is difficult to forecast the SSY using conventional methods because these approaches cannot handle complicated non-stationarity and non-linearity. Artificial intelligence techniques have gained popularity in water resources due to handling complex problems of SSY. In this study, a fully automated generalized single hybrid intelligent artificial neural network (ANN)-based genetic algorithm (GA) forecasting model was developed using water discharge, temperature, rainfall, SSY, rock type, relief, and catchment area data of eleven gauging stations for forecasting the SSY. It is applied at individual gauging stations for SSY forecasting in the Mahanadi River which is one of India’s largest peninsular rivers. All parameters of the ANN are optimized automatically and simultaneously using the GA. The multi-objective algorithm was applied to optimize the two conflicting objective functions (error variance and bias). The mean square error objective function was considered for the single-objective optimization model. Single and multi-objective GA-based ANN, autoregressive and multivariate autoregressive models were compared to each other. It was found that the single-objective GA-based ANN model provided the best accuracy among all comparative models, and it is the most suitable substitute for forecasting SSY. If the measurement of SSY is unavailable, then single-objective GA-based ANN modeling approaches can be recommended for forecasting SSY due to comparatively superior performance and simplicity of implementation
metadata
Yadav, Arvind; Chithaluru, Premkumar; Singh, Aman; Albahar, Marwan Ali; Jurcut, Anca; Álvarez, Roberto Marcelo; Mojjada, Ramesh Kumar y Joshi, Devendra
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, roberto.alvarez@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR
(2022)
Suspended Sediment Yield Forecasting with Single and Multi-Objective Optimization Using Hybrid Artificial Intelligence Models.
Mathematics, 10 (22).
p. 4263.
ISSN 2227-7390
Artículo Materias > Biomedicina Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés The law of superposition underpins first-order linear pharmacokinetic relationships. Most drugs, therefore, after a single dose can be described by first-order or linear processes, which can be superposed to understand multiple-dose regimen behavior. However, there are a number of situations where drugs could display behaviors after multiple dosing that leads to capacity-limited or saturation non-linear kinetics and the law of superposition is overruled. This review presents a practical guide to understand the equations and calculations for single and multiple-dosing regimens after intravenous and oral administration. It also provides the pharmaceutical basis for saturation in ADME processes and the consequent changes in the area under the concentration–time curve, which represents drug exposure that can lead to the modulation of efficacy and/or toxic effects. The pharmacokineticist must implicitly understand the principles of superposition, which are a central tenet of drug behavior and disposition during drug development. metadata Yousef, Malaz; Yáñez, Jaime A.; Löbenberg, Raimar y Davies, Neal M. mail SIN ESPECIFICAR, jaime.yanez@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Upholding or Breaking the Law of Superposition in Pharmacokinetics. Biomedicines, 12 (8). p. 1843. ISSN 2227-9059
Z
Tesis
Materias > Educación
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster
Cerrado
Inglés
This article discusses the importance of including English instruction in the curricular contents of learning institutions in Ecuador. Of particular interest for this study is how beginner-level English language learners at a public university in Guayaquil - Ecuador perform when exposed to lessons taught using two different methods – the TPRS method versus the traditional teaching method (using textbooks, workbooks and audio recordings).
metadata
Zea Vallejo, Daniel Arturo
mail
dzea2012@hotmail.com
(2022)
An Action Research for Implementing Teaching Proficiency through Reading and Storytelling (TPRS) for developing vocabulary in a group of EFL students from the Faculty of Chemistry at University of Guayaquil.
Masters thesis, SIN ESPECIFICAR.
Artículo
Materias > Educación física y el deporte
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
OBJECTIVE:
This study aimed to analyze the body composition and somatotype of professional soccer players, investigating variations across categories and playing positions.
METHODS:
An observational, cross-sectional, and analytical study was conducted with 51 male professional soccer players in the U-19 and U-20 categories. Data about sex, age, height, and weight were collected between March and May 2023. Body composition analysis utilized the ISAK protocol for the restricted profile, while somatotype categorization employed the Heath and Carter formula. Statistical analysis was performed using IBM SPSS Statistics V.26, which involved the application of Mann-Whitney and Kruskal-Wallis tests to discern differences in body composition variables and proportionality based on categories and playing positions. The Dunn test further identified specific positions exhibiting significant differences.
RESULTS:
The study encompassed 51 players, highlighting meaningful differences in body composition. The average body mass in kg was 75.8 (±6.9) for U-20 players and 70.5 (±6.1) for U-19 players. The somatotype values were 2.6-4.6-2.3 for U-20 players and 2.5-4.3-2.8 for U-19 players, with a predominance of muscle mass in all categories, characterizing them as balanced mesomorphs.
CONCLUSIONS:
Body composition and somatotype findings underscore distinctions in body mass across categories and playing positions, with notably higher body mass and muscle mass predominance in elevated categories. However, the prevailing skeletal muscle development establishes a significant semblance with the recognized somatotype standard for soccer.
metadata
Zambrano-Villacres, Raynier; Frias-Toral, Evelyn; Maldonado-Ponce, Emily; Poveda-Loor, Carlos; Leal, Paola; Velarde-Sotres, Álvaro; Leonardi, Alice; Trovato, Bruno; Roggio, Federico; Castorina, Alessandro; Wenxin, Xu y Musumeci, Giuseppe
mail
SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, alvaro.velarde@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR
(2024)
Exploring body composition and somatotype profiles among youth professional soccer players.
Mediterranean Journal of Nutrition and Metabolism, 17 (3).
pp. 241-254.
ISSN 1973798X
Artículo
Materias > Ingeniería
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto
Inglés
The rapid generation of data from various sources by the public sector, private corporations, business associations, and local communities is referred to as big data. This large and complex dataset is often regarded as the ‘new oil’ by public administrations (PAs), and data-driven approaches are employed to transform it into valuable insights that can improve governance, transparency, digital services, and public engagement. The government’s big-data ecosystem (GBDE) is a result of this initiative. Effective data management is the first step towards large-scale data analysis, which yields insights that benefit your work and your customers. However, managing big data throughout its life cycle is a daunting challenge for public agencies. Despite its widespread use, big data management is still a significant obstacle. To address this issue, this study proposes a hybrid approach to secure the data management life cycle for GBDE. Specifically, we use a combination of the ECC algorithm with AES 128 BITS encryption to ensure that the data remain confidential and secure. We identified and analyzed various data life cycle models through a systematic literature review to create a data management life cycle for data-driven governments. This approach enhances the security and privacy of data management and addresses the challenges faced by public agencies.
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Zahid, Reeba; Altaf, Ayesha; Ahmad, Tauqir; Iqbal, Faiza; Miró Vera, Yini Airet; López Flores, Miguel Ángel y Ashraf, Imran
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SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, yini.miro@uneatlantico.es, miguelangel.lopez@uneatlantico.es, SIN ESPECIFICAR
(2023)
Secure Data Management Life Cycle for Government Big-Data Ecosystem: Design and Development Perspective.
Systems, 11 (8).
p. 380.
ISSN 2079-8954
Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español El presente trabajo de investigación muestra una línea de acción para la solución de un procedimiento de cálculo dentro del contrato de compra de energía para el suministro de una Distribuidora Eléctrica en Guatemala. Se explica la dificultad de trabajar con una indexación incierta, la cual provoca diversas interpretaciones, acarreando un problema de decisión por las partes, debido a que no está explicito el procedimiento correcto a tomar, dado que lo que existe por escrito es ambiguo. Se analiza la Teoría Económica de los Contratos junto con los aspectos más relevantes son: analizar el contexto internacional de los contratos de largo plazo y las dificultades que se presentan en la forma de aplicación de la indexación. Contrastarlos con los acontecimientos presentados en la práctica guatemalteca y la problemática que se ha generado. Mostrar un método de resolución que evite a extender las diferencias entre las partes. La Metodología utilizada es la de análisis de contenido, la cual es una de las metodologías de la investigación jurídica, debido a que se realiza una investigación cualitativa dado que se realiza una investigación bibliográfica la cual revisa documentación concerniente al tema. Los resultados esperados son: obtener un fundamento para demostrar que el procedimiento de cálculo de indexación se ajusta a lo escrito en los contratos de compra de energía entre la distribuidora de energía y el proveedor de energía. Con esto se tendrá el mecanismo a seguir para resolver futuros conflictos que se puedan dar ante la presencia de una interpretación de cálculo. metadata Zea Castañeda, Kevin mail kevin.zeacastaneda@doctorado.unini.edu.mx (2023) Un problema en los PPA de contratos de suministro de energía eléctrica, la indexación. MLS Law and International Politics, 2 (1). ISSN 2952-248X
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Artículo Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés, Español El concepto sobre éxito empresarial es amplio y no existe consenso sobre su medición. La tendencia más extendida es utilizar indicadores de tipo financiero como la rentabilidad, productividad y crecimiento de ventas. En la ciudad de Huancayo, Perú, a inicios de 2020, existen 381 Mipyme’s (micro, pequeñas y medianas empresas) del sector salud. El objetivo de la investigación fue determinar los factores para el éxito de las Mipyme’s del Sector Salud de la ciudad de Huancayo, usando un modelo econométrico. Las hipótesis a demostrar fue que la fuente de financiamiento, la planificación estratégica y el uso de TIC´s, la formación gerencial, la innovación, la aplicación de un programa de calidad, la dedicación al negocio y la publicidad en redes sociales tienen un efecto significativo en el éxito de estas empresas. La investigación fue explicativa no experimental, desarrollándose un modelo econométrico mediante el método de regresión lineal múltiple. La variable dependiente fue numérica, las variables independientes cualitativas dicotómicas (dummies). Para el estudio se consideró al universo (censo). El modelo econométrico obtuvo un R2 = 0.463 (se acerca a un valor estadísticamente bueno) y un F significativo, cumplió además con los supuestos de regresión lineal, siendo así validado. Para este modelo, la fuente de financiamiento, la planificación estratégica y el uso de TIC´s, la formación gerencial, la innovación, la dedicación al negocio y la publicidad en redes sociales, resultaron significativas para el modelo. Sin embargo, la aplicación de un programa de calidad no resultó estadísticamente significativa, por tanto, fue descartada del modelo. metadata Álvarez Risco, Aldo y Vílchez Gutiérrez, Joel Benedicto mail SIN ESPECIFICAR (2020) Factores de éxito de MIPYMES del sector salud, ciudad de Huancayo--Perú, 2020. Project Design and Management, 2 (2). pp. 59-78. ISSN 2683-1597
<a class="ep_document_link" href="/10290/1/Influence%20of%20E-learning%20training%20on%20the%20acquisition%20of%20competences%20in%20basketball%20coaches%20in%20Cantabria.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
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The main aim of this study was to analyse the influence of e-learning training on the acquisition of competences in basketball coaches in Cantabria. The current landscape of basketball coach training shows an increasing demand for innovative training models and emerging pedagogies, including e-learning-based methodologies. The study sample consisted of fifty students from these courses, all above 16 years of age (36 males, 14 females). Among them, 16% resided outside the autonomous community of Cantabria, 10% resided more than 50 km from the city of Santander, 36% between 10 and 50 km, 14% less than 10 km, and 24% resided within Santander city. Data were collected through a Google Forms survey distributed by the Cantabrian Basketball Federation to training course students. Participation was voluntary and anonymous. The survey, consisting of 56 questions, was validated by two sports and health doctors and two senior basketball coaches. The collected data were processed and analysed using Microsoft® Excel version 16.74, and the results were expressed in percentages. The analysis revealed that 24.60% of the students trained through the e-learning methodology considered themselves fully qualified as basketball coaches, contrasting with 10.98% of those trained via traditional face-to-face methodology. The results of the study provide insights into important characteristics that can be adjusted and improved within the investigated educational process. Moreover, the study concludes that e-learning training effectively qualifies basketball coaches in Cantabria.
Josep Alemany Iturriaga mail josep.alemany@uneatlantico.es, Álvaro Velarde-Sotres mail alvaro.velarde@uneatlantico.es, Javier Jorge mail , Kamil Giglio mail ,
Alemany Iturriaga
<a href="/15625/1/s41598-024-74127-8.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
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Plant stress reduction research has advanced significantly with the use of Artificial Intelligence (AI) techniques, such as machine learning and deep learning. This is a significant step toward sustainable agriculture. Innovative insights into the physiological responses of plants mostly crops to drought stress have been revealed through the use of complex algorithms like gradient boosting, support vector machines (SVM), recurrent neural network (RNN), and long short-term memory (LSTM), combined with a thorough examination of the TYRKC and RBR-E3 domains in stress-associated signaling proteins across a range of crop species. Modern resources were used in this study, including the UniProt protein database for crop physiochemical properties associated with specific signaling domains and the SMART database for signaling protein domains. These insights were then applied to deep learning and machine learning techniques after careful data processing. The rigorous metric evaluations and ablation analysis that typified the study’s approach highlighted the algorithms’ effectiveness and dependability in recognizing and classifying stress events. Notably, the accuracy of SVM was 82%, while gradient boosting and RNN showed 96%, and 94%, respectively and LSTM obtained an astounding 97% accuracy. The study observed these successes but also highlights the ongoing obstacles to AI adoption in agriculture, emphasizing the need for creative thinking and interdisciplinary cooperation. In addition to its scholarly value, the collected data has significant implications for improving resource efficiency, directing precision agricultural methods, and supporting global food security programs. Notably, the gradient boosting and LSTM algorithm outperformed the others with an exceptional accuracy of 96% and 97%, demonstrating their potential for accurate stress categorization. This work highlights the revolutionary potential of AI to completely disrupt the agricultural industry while simultaneously advancing our understanding of plant stress responses.
Tariq Ali mail , Saif Ur Rehman mail , Shamshair Ali mail , Khalid Mahmood mail , Silvia Aparicio Obregón mail silvia.aparicio@uneatlantico.es, Rubén Calderón Iglesias mail ruben.calderon@uneatlantico.es, Tahir Khurshaid mail , Imran Ashraf mail ,
Ali
<a class="ep_document_link" href="/15198/1/nutrients-16-03859.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
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Carotenoids Intake and Cardiovascular Prevention: A Systematic Review
Background: Cardiovascular diseases (CVDs) encompass a variety of conditions that affect the heart and blood vessels. Carotenoids, a group of fat-soluble organic pigments synthesized by plants, fungi, algae, and some bacteria, may have a beneficial effect in reducing cardiovascular disease (CVD) risk. This study aims to examine and synthesize current research on the relationship between carotenoids and CVDs. Methods: A systematic review was conducted using MEDLINE and the Cochrane Library to identify relevant studies on the efficacy of carotenoid supplementation for CVD prevention. Interventional analytical studies (randomized and non-randomized clinical trials) published in English from January 2011 to February 2024 were included. Results: A total of 38 studies were included in the qualitative analysis. Of these, 17 epidemiological studies assessed the relationship between carotenoids and CVDs, 9 examined the effect of carotenoid supplementation, and 12 evaluated dietary interventions. Conclusions: Elevated serum carotenoid levels are associated with reduced CVD risk factors and inflammatory markers. Increasing the consumption of carotenoid-rich foods appears to be more effective than supplementation, though the specific effects of individual carotenoids on CVD risk remain uncertain.
Sandra Sumalla Cano mail sandra.sumalla@uneatlantico.es, Imanol Eguren García mail imanol.eguren@uneatlantico.es, Álvaro Lasarte García mail , Thomas Prola mail thomas.prola@uneatlantico.es, Raquel Martínez Díaz mail raquel.martinez@uneatlantico.es, Iñaki Elío Pascual mail inaki.elio@uneatlantico.es,
Sumalla Cano
<a class="ep_document_link" href="/15333/1/nutrients-16-03907.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
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Background/Objectives: The diet quality of younger individuals is decreasing globally, with alarming trends also in the Mediterranean region. The aim of this study was to assess diet quality and adequacy in relation to country-specific dietary recommendations for children and adolescents living in the Mediterranean area. Methods: A cross-sectional survey was conducted of 2011 parents of the target population participating in the DELICIOUS EU-PRIMA project. Dietary data and cross-references with food-based recommendations and the application of the youth healthy eating index (YHEI) was assessed through 24 h recalls and food frequency questionnaires. Results: Adherence to recommendations on plant-based foods was low (less than ∼20%), including fruit and vegetables adequacy in all countries, legume adequacy in all countries except for Italy, and cereal adequacy in all countries except for Portugal. For animal products and dietary fats, the adequacy in relation to the national food-based dietary recommendations was slightly better (∼40% on average) in most countries, although the Eastern countries reported worse rates. Higher scores on the YHEI predicted adequacy in relation to vegetables (except Egypt), fruit (except Lebanon), cereals (except Spain), and legumes (except Spain) in most countries. Younger children (p < 0.005) reporting having 8–10 h adequate sleep duration (p < 0.001), <2 h/day screen time (p < 0.001), and a medium/high physical activity level (p < 0.001) displayed a better diet quality. Moreover, older respondents (p < 0.001) with a medium/high educational level (p = 0.001) and living with a partner (p = 0.003) reported that their children had a better diet quality. Conclusions: Plant-based food groups, including fruit, vegetables, legumes, and even (whole-grain) cereals are underrepresented in the diets of Mediterranean children and adolescents. Moreover, the adequate consumption of other important dietary components, such as milk and dairy products, is rather disregarded, leading to substantially suboptimal diets and poor adequacy in relation to dietary guidelines.
Francesca Giampieri mail francesca.giampieri@uneatlantico.es, Alice Rosi mail , Francesca Scazzina mail , Evelyn Frias-Toral mail , Osama Abdelkarim mail , Mohamed Aly mail , Raynier Zambrano-Villacres mail , Juancho Pons mail , Laura Vázquez-Araújo mail , Sandra Sumalla Cano mail sandra.sumalla@uneatlantico.es, Iñaki Elío Pascual mail inaki.elio@uneatlantico.es, Lorenzo Monasta mail , Ana Mata mail , María Isabel Pardo mail , Pablo Busó mail , Giuseppe Grosso mail ,
Giampieri
<a href="/15440/1/fcimb-1-1515641.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
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Editorial: Host-bacteria interactions in fish pathogens
In order to promote the sustainable development of aquaculture, it is of great importance to better understand fish diseases caused by classic and emerging bacterial pathogens. Strains of classic fish pathogens such as Aeromonas, Vibrio, Photobacterium, Edwardsiella, Yersinia, Flavobacterium, or Piscirickettsia.
José Ramos-Vivas mail jose.ramos@uneatlantico.es, Félix Acosta mail ,
Ramos-Vivas