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2023

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Cianciosi, Danila and Alvarez-Suarez, José M. and Quiles, José L. and Forbes-Hernández, Tamara Y. and Navarro-Hortal, María D. and Machì, Michele and Pali-Casanova, Ramón and Martínez Espinosa, Julio César and Chen, Xiumin and Zhang, Di and Bai, Weibin and Lingmin, Tian and Mezzetti, Bruno and Battino, Maurizio and Diaz, Yasmany Armas mail francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, jose.quiles@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ramon.pali@unini.edu.mx, ulio.martinez@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED (2023) Anthocyanins: what do we know until now? Journal of Berry Research. pp. 1-6. ISSN 18785093

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Mazhar, Muhammad Fawad and Fatima, Anum and Álvarez, Roberto Marcelo and Miró Vera, Yini Airet and Martínez Espinosa, Julio César and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, roberto.alvarez@uneatlantico.es, yini.miro@uneatlantico.es, ulio.martinez@unini.edu.mx, UNSPECIFIED (2023) Deep Learning-Based Real Time Defect Detection for Optimization of Aircraft Manufacturing and Control Performance. Drones, 7 (1). p. 31. ISSN 2504-446X

Article Subjects > Teaching Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Álvarez, Roberto Marcelo and Brie, Santiago and Miró Vera, Yini Airet and 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

Article Subjects > Biomedicine
Subjects > Engineering
Subjects > Nutrition
Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Sumalla Cano, Sandra and Martínez-Licort, Rosmeri and Elío Pascual, Iñaki and Tutusaus, Kilian and Prola, Thomas and Vidal Mazón, Juan Luis and Sahelices, Benjamín and de la Torre Díez, Isabel mail UNSPECIFIED, sandra.sumalla@uneatlantico.es, UNSPECIFIED, inaki.elio@uneatlantico.es, kilian.tutusaus@uneatlantico.es, thomas.prola@uneatlantico.es, juanluis.vidal@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Systematic Review of Machine Learning applied to the Prediction of Obesity and Overweight. Journal of Medical Systems, 47 (1). ISSN 1573-689X

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Mallo, Javier and Cos, Francesc and Sampaio, Jaime and Jones, Margaret T. and Marqués-Jiménez, Diego and Mielgo-Ayuso, Juan and Freitas, Tomás T. and Alcaraz, Pedro E. and Vilamitjana, Javier and Ibañez, Sergio J. and Cuzzolin, Francesco and Terrados, Nicolás and Bird, Stephen P. and Zubillaga, Asier and Huyghe, Thomas and Jukic, Igor and Lorenzo, Alberto and Loturco, Irineu and Delextrat, Anne and Schelling, Xavi and Gómez-Ruano, Miguel and López-laval, Isaac and Vazquez, Jairo and Conte, Daniele and Velarde-Sotres, Álvaro and Bores Cerezal, Antonio and Ferioli, Davide and García, Franc and Peirau, Xavier and Martin-Acero, Rafael and Lago-Peñas, Carlos mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, alvaro.velarde@uneatlantico.es, antonio.bores@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (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

2022

Article Subjects > Biomedicine
Subjects > Nutrition
Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Elío Pascual, Iñaki and Alonso, Guzmán and Otero, Luis and Gutiérrez-Bardeci, Luis and Puente, Jesús and Muñoz-Cacho, Pedro mail UNSPECIFIED, inaki.elio@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (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

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Giampieri, Francesca and Quiles, José L. and Navarro-Hortal, María D. and Aparicio Obregón, Silvia and García Villena, Eduardo and Tutusaus, Kilian and De Giuseppe, Rachele and Grosso, Giuseppe and Cianciosi, Danila and Forbes-Hernández, Tamara Y. and Nabavi, Seyed M. and Battino, Maurizio mail UNSPECIFIED, francesca.giampieri@uneatlantico.es, jose.quiles@uneatlantico.es, UNSPECIFIED, silvia.aparicio@uneatlantico.es, eduardo.garcia@uneatlantico.es, kilian.tutusaus@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Biomedicine
Subjects > Engineering
Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Shafi, Imran and Afzal, Hammad and Díez, Isabel De La Torre and Lourdes, Del Rio-Solá M. and Breñosa, Jose and Martínez Espinosa, Julio César and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, UNSPECIFIED (2022) Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives. Healthcare, 10 (11). p. 2188. ISSN 2227-9032

Article Subjects > Biomedicine
Subjects > Nutrition
Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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. and Romero-Márquez, Jose M. and Muñoz-Ollero, Pedro and Jiménez-Trigo, Victoria and Esteban-Muñoz, Adelaida and Tutusaus, Kilian and Giampieri, Francesca and Battino, Maurizio and Sánchez-González, Cristina and Rivas-García, Lorenzo and Llopis, Juan and Forbes-Hernández, Tamara Y. and Quiles, José L. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, kilian.tutusaus@uneatlantico.es, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Kilby, Jeff and Breñosa, Jose and Martínez Espinosa, Julio César and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, UNSPECIFIED (2022) Analysis and Implementation of Human Mobility Behavior Using Similarity Analysis Based on Co-Occurrence Matrix. Sensors, 22 (24). p. 9898. ISSN 1424-8220

Article Subjects > Social Sciences
Subjects > Engineering
Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Shafi, Imran and Ahmad, Jamil and Álvarez, Roberto Marcelo and Miró Vera, Yini Airet and Soriano Flores, Emmanuel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, roberto.alvarez@uneatlantico.es, yini.miro@uneatlantico.es, emmanuel.soriano@uneatlantico.es, UNSPECIFIED (2022) An Analytical Framework for Innovation Determinants and Their Impact on Business Performance. Sustainability, 15 (1). p. 458. ISSN 2071-1050

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Ahmad, Ayaz and Rustam, Furqan and Saad, Eysha and Siddique, Muhammad Abubakar and Lee, Ernesto and Ortega-Mansilla, Arturo and Díez, Isabel de la Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, arturo.ortega@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Analyzing preventive precautions to limit spread of COVID-19. PLOS ONE, 17 (8). e0272350. ISSN 1932-6203

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Liaqat, Hannan Bin and Kiren, Tayybah and Sana, Muhammad Usman and Álvarez, Roberto Marcelo and Miró Vera, Yini Airet and Pascual Barrera, Alina Eugenia and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, roberto.alvarez@uneatlantico.es, yini.miro@uneatlantico.es, alina.pascual@unini.edu.mx, UNSPECIFIED (2022) Antifragile and Resilient Geographical Information System Service Delivery in Fog Computing. Sensors, 22 (22). p. 8778. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Mazzetto, Matías Ariel mail UNSPECIFIED (2022) Análisis y mejores prácticas proyectuales de una obra civil hidroeléctrica de Honduras. Project Design and Management, 4 (2). ISSN 2683-1597

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Sosa González, Wadi Elim and Pali-Casanova, Ramón and Yam Cervantes, Marcial Alfredo and Aguilar Vega, Manuel and Chacha Coto, Javier and Zavala Loría, José del Carmen and Dzul López, Luis Alonso and García Villena, Eduardo mail amanda@ugto.mx, UNSPECIFIED, ramon.pali@unini.edu.mx, marcial.yam@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Ishaq, Abid and Kokab, Sayyida Tabinda and de la Torre Diez, Isabel and Vidal Mazón, Juan Luis and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) An Artificial Neural Network Model for Water Quality and Water Consumption Prediction. Water, 14 (21). p. 3359. ISSN 2073-4441

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Abierto Inglés UNSPECIFIED metadata Kimothi, Sanjeev and Thapliyal, Asha and Akram, Shaik Vaseem and Singh, Rajesh and Gehlot, Anita and Mohamed, Heba G. and Anand, Divya and Ibrahim, Muhammad and Delgado Noya, Irene mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Rustam, Furqan and Daghriri, Talal and Díez, Isabel de la Torre and Vidal Mazón, Juan Luis and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) Building Heating and Cooling Load Prediction Using Ensemble Machine Learning Model. Sensors, 22 (19). p. 7692. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Rani, Shalli and Singh, Aman and Vidal Mazón, Juan Luis and Bhatia, Surbhi mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, juanluis.vidal@uneatlantico.es, UNSPECIFIED (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

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Forbes-Hernández, Tamara and Aparicio-Obregón, Silvia and Crespo-Álvarez, Jorge and Elexpuru Zabaleta, Maria and Gracia Villar, Mónica and Giampieri, Francesca and Elío Pascual, Iñaki mail sandra.sumalla@uneatlantico.es, UNSPECIFIED, 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

Article Subjects > Biomedicine
Subjects > Engineering
Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Suhail, Maryam and Qureshi, Junaid Nasir and Rustam, Furqan and de la Torre Díez, Isabel and Vidal Mazón, Juan Luis and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) Consortium Framework Using Blockchain for Asthma Healthcare in Pandemics. Sensors, 22 (21). p. 8582. ISSN 1424-8220

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Lafuente, Elena Presencio and Breñosa, Jose and Ortega-Mansilla, Arturo and Díez, Isabel de la Torre and Río-Solá, María Lourdes Del mail UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, arturo.ortega@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Correction to: Systematic Review of Telemedicine and eHealth Systems Applied to Vascular Surgery. Journal of Medical Systems, 47 (1). ISSN 1573-689X

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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. and Dumka, Ankur and Kumar, Manoj and Singh, Rajesh and Gehlot, Anita and Akram, Shaik Vaseem and Anand, Divya and Elkamchouchi, Dalia H. and Delgado Noya, Irene mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Pérez Pacho, Javier and Gracia Villar, Santos and Aparicio Obregón, Silvia and Breñosa, Jose and de la Torre Díez, Isabel mail UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, silvia.aparicio@uneatlantico.es, josemanuel.brenosa@uneatlantico.es, UNSPECIFIED (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

Article Subjects > Biomedicine
Subjects > Engineering
Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
Abierto Español Patient care and convenience remain the concern of medical professionals and caregivers alike. An unconscious patient confined to a bed may develop fluid accumulation and pressure sores due to inactivity and deficiency of oxygen flow. Moreover, weight monitoring is crucial for an effective treatment plan, which is difficult to measure for bedridden patients. This paper presents the design and development of a smart and cost-effective independent system for lateral rotation, movement, weight measurement, and transporting immobile patients. Optimal dimensions and practical design specifications are determined by a survey across various hospitals. Subsequently, the proposed hoist-based weighing and turning mechanism is CAD-modeled and simulated. Later, the structural analysis is carried out to select suitable metallurgy for various sub-assemblies to ensure design reliability. After fabrication, optimization, integration, and testing procedures, the base frame is designed to mount a hydraulic motor for the actuator, a DC power source for self-sustenance, and lockable wheels for portability. The installation of a weighing scale and a hydraulic actuator is ensured to lift the patient for weight measuring up to 600 pounds or lateral turning of 80 degrees both ways. The developed system offers simple operating characteristics, allows for keeping patient weight records, and assists nurses in changing patients’ lateral positions both ways, comfortably massage patients’ backs, and transport them from one bed to another. Additionally, being lightweight offers reduced contact with the patient to increase the healthcare staff’s safety in pandemics; it is also height adjustable and portable, allowing for use with multiple-sized beds and easy transportation across the medical facility. The feedback from paramedics is encouraging regarding reducing labor-intensive nursing tasks, alleviating the discomfort of long-term bed-ridden patients, and allowing medical practitioners to suggest better treatment plans metadata Shafi, Imran and Farooq, Muhammad Siddique and De La Torre Díez, Isabel and Breñosa, Jose and Martínez Espinosa, Julio César and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, UNSPECIFIED (2022) Design and Development of Smart Weight Measurement, Lateral Turning and Transfer Bedding for Unconscious Patients in Pandemics. Healthcare, 10 (11). p. 2174. ISSN 2227-9032

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Bores-Cerezal, Antonio and Mecías-Calvo, Marcos and Barcala Furelos, Martín and Aparicio Obregón, Silvia and Calleja-González, Julio mail alvaro.velarde@uneatlantico.es, antonio.bores@uneatlantico.es, marcos.mecias@uneatlantico.es, martin.barcala@uneatlantico.es, silvia.aparicio@uneatlantico.es, UNSPECIFIED (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

Article Subjects > Social Sciences Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Soriano Flores, Emmanuel and Rodríguez Velasco, Carmen Lilí and Silva Alvarado, Eduardo and Calderón Iglesias, Rubén and Álvarez, Roberto Marcelo and Gracia Villar, Santos mail silvana.marin@uneatlantico.es, emmanuel.soriano@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED, 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

Article Subjects > Teaching Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Azevedo-Gomes, Juliana and Ulloa-Guerra, Oscar and Ruiz Salces, Roberto and 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Viriyasitavat, Wattana and Juneja, Sapna and Alshahrani, Hani and Shaikh, Asadullah and Dhiman, Gaurav and Singh, Aman and Kaur, Amandeep mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED (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

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Abierto Español Introducción: Las caídas se consideran como uno de los síndromes geriátricos más importantes por su alta incidencia en los adultos mayores de 65 años. Las caídas pueden generar diversas e importantes consecuencias físicas y/o psicológicas, deterioro funcional, dependencia e incluso la muerte. Objetivo: Determinar la efectividad del entrenamiento propioceptivo para prevenir el riesgo de caídas en el adulto mayor de 65 años residente en un hogar de reposo en el km 1 vía a Dapa, Valle del Cauca. Metodología: Se realizó una investigación cuasiexperimental de corte transversal, con muestra no probabilística constituida por 12 mujeres y 3 hombres adultos mayores de 65 años residentes en un hogar de reposo, participando de manera voluntaria en un entrenamiento propioceptivo de 6 semanas, dos veces a la semana durante los meses de marzo y abril de 2021. La factibilidad de la propuesta de ejercicios propioceptivos se validó a partir de la técnica de investigación grupo nominal. Los resultados incluyeron las pruebas Short Physical Performance Battery (SPPB) y Timed up and go (TUG) evaluadas pre y post intervención. Resultados: Hubo diferencias significativas en el nivel de funcionalidad pre- post intervención, (p<0,05), las dos variables (nivel de riesgo de caída y nivel de funcionalidad) se correlacionan en sentido inverso (p<0,05). Conclusiones: El entrenamiento propioceptivo es efectivo para mejorar el equilibrio estático/dinámico, la velocidad de la marcha y fuerza de extremidades inferiores en los adultos mayores de 65 años que residen en un hogar de reposo. metadata Vélez Alape, Natalia and Hernández Cruz, Leonardo de Jesús and Velarde-Sotres, Álvaro mail UNSPECIFIED, eonardo.hernandez@unib.org, alvaro.velarde@uneatlantico.es (2022) Efecto de un entrenamiento propioceptivo para prevenir el riesgo de caída en adultos mayores. MLS Sport Research, 2 (2).

Article Subjects > Biomedicine
Subjects > Engineering
Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Din, Sadia and Khan, Asim and Díez, Isabel De La Torre and Pali-Casanova, Ramón and Tutusaus, Kilian and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ramon.pali@unini.edu.mx, kilian.tutusaus@uneatlantico.es, UNSPECIFIED (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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Farooq, Muhammad Shoaib and Rustam, Furqan and Gracia Villar, Mónica and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) Emotion Detection Using Facial Expression Involving Occlusions and Tilt. Applied Sciences, 12 (22). p. 11797. ISSN 2076-3417

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Gupta, Kamali and Qahtani, Abdulrahman M. and Gupta, Deepali and Alharithi, Fahd S. and Singh, Aman and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED (2022) Energy-Aware Live VM Migration Using Ballooning in Cloud Data Center. Electronics, 11 (23). p. 3932. ISSN 2079-9292

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Chithaluru, Premkumar and Singh, Aman and Joshi, Devendra and Elkamchouchi, Dalia H. and Mazas Pérez-Oleaga, Cristina and Anand, Divya mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Pascual Barrera, Alina Eugenia and Álvarez, Roberto Marcelo and Dzul López, Luis Alonso and Tutusaus, Kilian and Vidal Mazón, Juan Luis and Miró Vera, Yini Airet and Brie, Santiago and 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Wu, Jun and Bashir, Ali Kashif and Yang, Wu and Singh, Aman and AlZubi, Ahmad Ali mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED (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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Gupta, Deepali and Anand, Divya and S. Alharithi, Fahd and Almotiri, Jasem and Ortega-Mansilla, Arturo and Singh, Dinesh and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, arturo.ortega@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Fault Pattern Diagnosis and Classification in Sensor Nodes Using Fall Curve. Computers, Materials & Continua, 72 (1). pp. 1799-1814. ISSN 1546-2226

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Lázaro-Díez, María and Ramos Vivas, Jose mail UNSPECIFIED, UNSPECIFIED, jose.ramos@uneatlantico.es (2022) Genetic Resistance Determinants in Clinical Acinetobacter pittii Genomes. Antibiotics, 11 (5). p. 676. ISSN 2079-6382

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Jain, Anuj and Gehlot, Anita and Singh, Rajesh and Akram, Shaik Vaseem and Singh, Aman and Anand, Divya and Delgado Noya, Irene and Ahmad, Shafiq mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@unic.co.ao, divya.anand@uneatlantico.es, irene.delgado@uneatlantico.es, UNSPECIFIED (2022) Imperative Role of Automation and Wireless Technologies in Aquaponics Farming. Wireless Communications and Mobile Computing, 2022. pp. 1-13. ISSN 1530-8669

Article Subjects > Social Sciences
Subjects > Engineering
Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Singh, Rajesh and Gehlot, Anita and Akram, Shaik Vaseem and Singh, Aman and Caro Montero, Elisabeth and Priyadarshi, Neeraj and Twala, Bhekisipho mail UNSPECIFIED (2022) Imperative Role of Integrating Digitalization in the Firms Finance: A Technological Perspective. Electronics, 11 (19). p. 3252. ISSN 2079-9292

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Babbar, Himanshi and Shah, Syed Hassan Ahmed and Singh, Aman mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Social Sciences Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Garat de Marin, Mirtha Silvana and Soriano Flores, Emmanuel and Rojo Gutiérrez, Marco Antonio and Gracia Villar, Mónica and Durántez Prados, Frigdiano Álvaro mail UNSPECIFIED, 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Zhang, Mengjia and Nawaz, Muhammad and Ali, Muhammad and Singh, Aman mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es (2022) Information technology-based revolution in music education using AHP and TOPSIS. Soft Computing. ISSN 1432-7643

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Verma, Parag and Singh, Rajesh and Bhardwaj, Anuj and Alsubhi, Khalid and Anand, Divya and Delgado Noya, Irene and Aparicio Obregón, Silvia mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Gupta, Kamali and Gupta, Deepali and Singh, Aman and Ibrahim, Muhammad and Ortega-Mansilla, Arturo and Goyal, Nitin and Hamam, Habib mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, arturo.ortega@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Intelligent Load-Balancing Framework for Fog-Enabled Communication in Healthcare. Electronics, 11 (4). p. 566. ISSN 2079-9292

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Shafi, Imran and Khan, Harris and Díez, Isabel De La Torre and Breñosa, Jose and Martínez Espinosa, Julio César and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, UNSPECIFIED (2022) IoT Enabled Intelligent Stick for Visually Impaired People for Obstacle Recognition. Sensors, 22 (22). p. 8914. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Anand, Divya and Singh, Aman and Vij, Rishika and Alharbi, Abdullah and Alshammari, Majid and Ortega-Mansilla, Arturo mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Acosta Hernández, Begoña and Ramos Vivas, Jose and Déniz, Soraya and Rosario, Inmaculada and Martín Barrasa, José Luís and Henao, Andrés sánchez and Silva Sergent, Freddy and Ramos Sosa, María josé and García Álvarez, Natalia and Real, Fernando mail UNSPECIFIED, UNSPECIFIED, jose.ramos@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (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

Article Subjects > Engineering Ibero-american International University > Research > Scientific Production
Europe University of Atlantic > Research > Scientific Production
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 and Rani, Shalli and Singh, Aman and Elkamchouchi, Dalia H. and Delgado Noya, Irene mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Rani, Shalli and Faseeh Qureshi, Nawab Muhammad and Singh, Aman mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es (2022) Mitigating 5G security challenges for next-gen industry using quantum computing. Journal of King Saud University - Computer and Information Sciences. ISSN 13191578

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Ghosh, Debarshi and Taneja, Ashu and Saluja, Nitin and Rani, Shalli and Singh, Aman and Elkamchouchi, Dalia H. and Delgado Noya, Irene mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, 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

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Tapia Martínez, Olga and Elexpuru Zabaleta, Maria and Tutusaus, Kilian and Armas Diaz, Yasmany and Battino, Maurizio and Giampieri, Francesca mail jose.ramos@uneatlantico.es, olga.tapia@uneatlantico.es, maria.elexpuru@uneatlantico.es, kilian.tutusaus@uneatlantico.es, UNSPECIFIED, 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Gupta, Deepali and Gupta, Kamali and Anand, Divya and Elkamchouchi, Dalia H. and Mazas Pérez-Oleaga, Cristina and Ibrahim, Muhammad and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, cristina.mazas@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (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

Article Subjects > Biomedicine
Subjects > Engineering
Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Mehdi, Muhammad Mohsin and Jamal, M. Hasan and Raza, Imran and Hussain, Syed Asad and Breñosa, Jose and Martínez Espinosa, Julio César and Pascual Barrera, Alina Eugenia and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, alina.pascual@unini.edu.mx, UNSPECIFIED (2022) Multipath Routing in Wireless Body Area Sensor Network for Healthcare Monitoring. Healthcare, 10 (11). p. 2297. ISSN 2227-9032

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Alharithi, Fahd S. and Álvarez, Roberto Marcelo and Singh, Aman and Qahtani, Abdulrahman M. mail UNSPECIFIED, UNSPECIFIED, roberto.alvarez@uneatlantico.es, aman.singh@uneatlantico.es, UNSPECIFIED (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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Verma, Parag and Singh, Rajesh and Kumar Bisht, Anil and Anand, Divya and Moaiteq Aljahdali, Hani and Delgado Noya, Irene and Aparicio Obregón, Silvia mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Chithaluru, Premkumar and Singh, Aman and Yadav, Arvind and Elkamchouchi, Dalia H. and Mazas Pérez-Oleaga, Cristina and Anand, Divya mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Rustam, Furqan and Álvarez, Roberto Marcelo and Vidal Mazón, Juan Luis and Díez, Isabel de la Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, roberto.alvarez@uneatlantico.es, juanluis.vidal@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Pneumonia Classification from X-ray Images with Inception-V3 and Convolutional Neural Network. Diagnostics, 12 (5). p. 1280. ISSN 2075-4418

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Ashraf, Imran and Jabbar, Shehbaz and Tutusaus, Kilian and Mazas Pérez-Oleaga, Cristina and Pascual Barrera, Alina Eugenia and de la Torre Diez, Isabel mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, kilian.tutusaus@uneatlantico.es, cristina.mazas@uneatlantico.es, alina.pascual@unini.edu.mx, UNSPECIFIED (2022) Prediction β-Thalassemia carriers using complete blood count features. Scientific Reports, 12 (1). ISSN 2045-2322

Article Subjects > Biomedicine
Subjects > Nutrition
Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Machì, Michele and Salinari, Alessia and Mazas Pérez-Oleaga, Cristina and Martínez López, Nohora Milena and Briones Urbano, Mercedes and Cianciosi, Danila mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, cristina.mazas@uneatlantico.es, nohora.martinez@uneatlantico.es, mercedes.briones@uneatlantico.es, UNSPECIFIED (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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Singh, Rajesh and Siwach, Sweety and Vaseem Akram, Shaik and Alsubhi, Khalid and Singh, Aman and Delgado Noya, Irene and Choudhury, Sushabhan mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, irene.delgado@uneatlantico.es, UNSPECIFIED (2022) Real Time Monitoring of Muscle Fatigue with IoT and Wearable Devices. Computers, Materials & Continua, 72 (1). pp. 999-1015. ISSN 1546-2226

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Elío Pascual, Iñaki and Sumalla Cano, Sandra and Aparicio Obregón, Silvia and González-Antón, Carolina Teresa and Muñoz-Cacho, Pedro mail UNSPECIFIED, inaki.elio@uneatlantico.es, sandra.sumalla@uneatlantico.es, silvia.aparicio@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (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

Article Subjects > Engineering Universidad Internacional do Cuanza > Research > Scientific Production
Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Rustam, Furqan and Soriano Flores, Emmanuel and Vidal Mazón, Juan Luis and de la Torre Diez, Isabel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, emmanuel.soriano@uneatlantico.es, juanluis.vidal@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) A Review of Image Processing Techniques for Deepfakes. Sensors, 22 (12). p. 4556. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Gupta, Sheifali and Mohamed, Heba G. and Anand, Divya and Vidal Mazón, Juan Luis and Gupta, Deepali and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, juanluis.vidal@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Siamese Convolutional Neural Network-Based Twin Structure Model for Independent Offline Signature Verification. Sustainability, 14 (18). p. 11484. ISSN 2071-1050

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Singh, Aman and Alsubhi, Khalid and Goyal, Nitin and Abdrabou, Atef and Vidyarthi, Ankit and Rodrigues, Joel J. P. C. mail divya.anand@uneatlantico.es, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Stonier, Albert Alexander and Gupta, Punit and Gavilanes, Daniel and Masías Vergara, Manuel and Lung sin, Jong mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, daniel.gavilanes@uneatlantico.es, manuel.masias@uneatlantico.es, UNSPECIFIED (2022) Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoT. Energies, 15 (21). p. 8206. ISSN 1996-1073

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Chithaluru, Premkumar and Singh, Aman and Albahar, Marwan Ali and Jurcut, Anca and Álvarez, Roberto Marcelo and Mojjada, Ramesh Kumar and Joshi, Devendra mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, roberto.alvarez@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Suspended Sediment Yield Forecasting with Single and Multi-Objective Optimization Using Hybrid Artificial Intelligence Models. Mathematics, 10 (22). p. 4263. ISSN 2227-7390

Article Subjects > Biomedicine
Subjects > Engineering
Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Heyat, Md Belal Bin and Rahman, Khaleequr and Kunnavil, Radhika and Fazmiya, Mohamed Joonus Aynul and Akhtar, Faijan and Sumbul, X. and Vidal Mazón, Juan Luis and Rodríguez Velasco, Carmen Lilí and De La Torre Díez, Isabel mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (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

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Presencio Lafuente, Elena and Breñosa, Jose and Ortega-Mansilla, Arturo and Torre Díez, Isabel de la and Río-Solá, María Lourdes Del mail UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, arturo.ortega@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Systematic Review of Telemedicine and eHealth Systems Applied to Vascular Surgery. Journal of Medical Systems, 46 (12). ISSN 1573-689X

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Singh, Rajesh and Gehlot, Anita and Akram, Shaik Vaseem and Twala, Bhekisipho and Singh, Aman and Caro Montero, Elisabeth and Priyadarshi, Neeraj mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, elizabeth.caro@uneatlantico.es, UNSPECIFIED (2022) Technologies Empowered Environmental, Social, and Governance (ESG): An Industry 4.0 Landscape. Sustainability, 15 (1). p. 309. ISSN 2071-1050

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Farooq, Muhammad Shoaib and Naseem, Ansar and Rustam, Furqan and Gracia Villar, Mónica and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) Threatening URDU Language Detection from Tweets Using Machine Learning. Applied Sciences, 12 (20). p. 10342. ISSN 2076-3417

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Rustam, Furqan and De La Torre Díez, Isabel and Vidal Mazón, Juan Luis and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) Thyroid Disease Prediction Using Selective Features and Machine Learning Techniques. Cancers, 14 (16). p. 3914. ISSN 2072-6694

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Gupta, Deepali and Anand, Divya and Goyal, Nitin and Aljahdali, Hani Moaiteq and Ortega-Mansilla, Arturo and Kadry, Seifedine and Kumar, Arun mail UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, arturo.ortega@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Rani, Shalli and Singh, Aman and Vidal Mazón, Juan Luis and Wang, Han mail UNSPECIFIED, UNSPECIFIED, aman.singh@unic.co.ao, juanluis.vidal@uneatlantico.es, UNSPECIFIED (2022) Towards Security Mechanism in D2D Wireless Communication: A 5G Network Approach. Wireless Communications and Mobile Computing, 2022. pp. 1-9. ISSN 1530-8669

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Gupta, Sheifali and Garg, Meenu and Gupta, Deepali and Alharbi, Abdullah and Alyami, Hashem and Anand, Divya and Ortega-Mansilla, Arturo and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, arturo.ortega@uneatlantico.es, UNSPECIFIED (2022) Visualization of Customized Convolutional Neural Network for Natural Language Recognition. Sensors, 22 (8). p. 2881. ISSN 1424-8220

Article Subjects > Biomedicine
Subjects > Engineering
Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Aslam, Naila and De La Torre Díez, Isabel and Khan, Yaser Daanial and Vidal Mazón, Juan Luis and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) White Blood Cell Classification Using Texture and RGB Features of Oversampled Microscopic Images. Healthcare, 10 (11). p. 2230. ISSN 2227-9032

2021

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Jarrin, Sandra and Elexpuru Zabaleta, Maria and Crespo-Álvarez, Jorge and Dominguez Azpíroz, Irma and Tutusaus, Kilian and Ruiz Salces, Roberto and Calderón Iglesias, Rubén and 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Pérez Pacho, Javier and Gracia Villar, Santos and Aparicio Obregón, Silvia and Breñosa, Jose and de la Torre Díez, Isabel mail UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, silvia.aparicio@uneatlantico.es, josemanuel.brenosa@uneatlantico.es, UNSPECIFIED (2021) Analysis of mobile apps for information, prevention and monitoring of covid-19 and proposal of an innovative app in this field. JMIR Preprints. (Submitted)

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Lázaro-Díez, María and Redondo-Salvo, Santiago and Navas, Jesús and Ramos-Vivas, José mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Gracia Villar, Santos and Dzul López, Luis Alonso and Álvarez, Roberto Marcelo and Delgado Noya, Irene and 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Gupta, Deepali and Gupta, Sheifali and Singh, Aman and Aljahdali, Hani Moaiteq and Goyal, Nitin and Delgado Noya, Irene and Kadry, Seifedine mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, irene.delgado@uneatlantico.es, UNSPECIFIED (2021) Blockchain Enabled Transparent and Anti-Counterfeiting Supply of COVID-19 Vaccine Vials. Vaccines, 9 (11). p. 1239. ISSN 2076-393X

Article Subjects > Psychology Ibero-american International University > Research > Scientific Production
Europe University of Atlantic > Research > Scientific Production
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 and 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

Article Subjects > Psychology Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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. and Nogueira-López, Abel and Zangeneh, M. and López-Mora, C. mail UNSPECIFIED, abel.nogueira@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2021) Exercise Addiction and Perfectionism, Joint in the Same Path? A Systematic Review. International Journal of Mental Health and Addiction. ISSN 1557-1874

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Harnal, Shilpi and Tiwari, Rajeev and Alharithi, Fahd S. and Almulihi, Ahmed H. and Delgado Noya, Irene and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, irene.delgado@uneatlantico.es, UNSPECIFIED (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

Article Subjects > Teaching Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Pueyo Villa, Silvia and Delgado Noya, Irene and Tutusaus, Kilian and Ruiz Salces, Roberto and 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

Article Subjects > Teaching Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Abierto Español La formación pedagógica del docente debe partir de las competencias que el profesor debe desarrollar para aplicar a las TIC de manera educativa a lo largo de su vida docente. Este estudio, que es parte del Proyecto Europeo Lovedistance – Learning Optmization and Academic Inclusion Via Equitative Distance Teaching and Learning 609949-EPP-1-2019-1-PTEPPKA2-CBHE-JP, tiene como objetivo medir los niveles y dimensiones de las competencias determinadas por la UNESCO (2016) en cuanto a la acción docente frente a la utilización de las TIC en escenarios educativos. Se destacan las posibilidades de llevar a cabo una planificación basada en las TIC; el diseño o la capacidad de organización y construcción de escenarios de aprendizaje con las TIC; y la evaluación o la posibilidad de medida de la efectividad de las TIC para la educación a lo largo de la vida, en los espacios educativos que se desarrollan como docentes (Coll, 2008). El presente estudio se basa en el diseño de encuesta y utiliza como instrumento el cuestionario, aplicando una complementariedad metodológica con unos resultados que indican a través de un análisis descriptivo que la formación del profesorado, la coordinación y cooperación docente, y la profundización en el manejo de las tecnologías, son factores de gran importancia y favorecedores del uso de las TIC en la comunidad educativa. metadata Sartor-Harada, Andresa mail andresa.sartor@uneatlantico.es (2021) La comunidad docente y las competencias digitales: la formación a lo largo de la vida. Revista Conhecimento Online, 1. p. 177. ISSN 2176-8501

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Ansary, Johura and Forbes-Hernandez, Tamara Y. and Regolo, Lucia and Quinzi, Denise and Gracia Villar, Santos and Garcia Villena, Eduardo and Tutusaus Pifarre, Kilian and Alvarez-Suarez, José M. and Battino, Maurizio and Giampieri, Francesca mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, eduardo.garcia@uneatlantico.es, kilian.tutusaus@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (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

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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. and Varela-López, Alfonso and Navarro-Hortal, María D. and Badillo-Carrasco, Alberto and Forbes-Hernández, Tamara Y. and Giampieri, Francesca and Dominguez Azpíroz, Irma and Madrigal-Hoyos, Lorena and Battino, Maurizio and Quiles, José L. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Giampieri, Francesca and Forbes-Hernandez, Tamara Y. and Regolo, Lucia and Quinzi, Denise and Gracia Villar, Santos and Garcia Villena, Eduardo and Tutusaus, Kilian and Alvarez-Suarez, José M. and Battino, Maurizio and Cianciosi, Danila mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, eduardo.garcia@uneatlantico.es, kilian.tutusaus@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (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

Article Subjects > Psychology Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and López-Mora, Clara and Yüce, Arif and Nogueira-López, Abel and Tovar-Gálvez, Maria Isabel mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, abel.nogueira@uneatlantico.es, UNSPECIFIED (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

Article Subjects > Social Sciences Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Abierto Portugués Nas últimas décadas temos vivenciado a dificuldade em efetivar o uso da linguagem inclusiva ao tempo em que se evidencia a facilidade de implantação de uma neolíngua que provém do generismo queer. São tempos sombrios para a luta feminista, que sofre não só a difamação e deturpação da sua agenda e cânon, senão também a usurpação de conceitos e espaços. No ano 2021, que marca o centenário do pedagogo brasileiro Paulo Freire, estende-se sobre nós uma outra onda ameaçadora de irracionalismo, como aquela advertida por ele no século passado. O neoliberalismo mata, assim como mata o machismo; e as mulheres, a vida das mulheres, não vão além de uma objetificação para ambos. Nosso objetivo, com esse artigo, é dialogar desde e com a proposta pedagógica freiriana tomando como contraponto os conceitos ‘linguagem inclusiva’ e ‘neolíngua’ no intuito de denunciar e, principalmente, de enfatizar a necessidade permanente de uma educação emancipadora e libertadora para transformar os sistemas de opressão e morte. Uma teologia da vida não pode ficar em silêncio perante a ignomínia contemporânea metadata Ulrich, Claudete Beise and Ströher, Marga Janete and Núñez de la Paz, Nivia Ivette mail UNSPECIFIED (2021) Perseguindo o inédito viável: a pedagogia freiriana, a necesssidade da linguagem inclusiva e a denúncia à neolíngua do generismo queer. Revista Caminhos - Revista de Ciências da Religião, 19 (4). p. 228. ISSN 1678-3034

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Superio, Joshua and Galindo-Villegas, Jorge and Acosta, Félix mail jose.ramos@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2021) Phage Therapy as a Focused Management Strategy in Aquaculture. International Journal of Molecular Sciences, 22 (19). p. 10436. ISSN 1422-0067

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Elexpuru Zabaleta, Maria and Sámano Celorio, María Luisa and Pascual Barrera, Alina Eugenia and Forbes-Hernandez, Tamara Y. and Giampieri, Francesca and 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, UNSPECIFIED, UNSPECIFIED (2021) Phages and Enzybiotics in Food Biopreservation. Molecules, 26 (17). p. 5138. ISSN 1420-3049

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Sharma, Sharad and Singh, Aman and Alwadain, Ayed and Choi, Bong-Jun and Breñosa, Jose and Ortega-Mansilla, Arturo and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, arturo.ortega@uneatlantico.es, UNSPECIFIED (2021) Revolutionary Strategies Analysis and Proposed System for Future Infrastructure in Internet of Things. Sustainability, 14 (1). p. 71. ISSN 2071-1050

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Singh, Rajesh and Kuchhal, Piyush and Kumar, Adesh and Singh, Aman and Alsubhi, Khalid and Ibrahim, Muhammad and Gracia Villar, Santos and Breñosa, Jose mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

2020

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
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 and Forbes-Hernández, Tamara Y. and Calderón Iglesias, Rubén and Ruiz Salces, Roberto and Elexpuru Zabaleta, Maria and Dominguez Azpíroz, Irma and Cianciosi, Danila and Quiles, José L. and Giampieri, Francesca and Battino, Maurizio mail francesca.pistollato@uneatlantico.es, UNSPECIFIED, ruben.calderon@uneatlantico.es, roberto.ruiz@uneatlantico.es, maria.elexpuru@uneatlantico.es, irma.dominguez@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2020) Effects of caloric restriction on immunosurveillance, microbiota and cancer cell phenotype: Possible implications for cancer treatment. Seminars in Cancer Biology. ISSN 1044-579X

Article Subjects > Engineering Ibero-american International University > Research > Scientific Production
Europe University of Atlantic > Research > Scientific Production
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 and Fernandes, Roberto Fabiano mail UNSPECIFIED, 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

2019

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Afrin, Sadia and Forbes-Hernandez, Tamara Y. and Gasparrini, Massimiliano and Cianciosi, Danila and Reboredo-Rodriguez, Patricia and Varela-Lopez, Alfonso and Quiles, Jose L. and Battino, Maurizio mail UNSPECIFIED, UNSPECIFIED, tamara.forbes@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Yam Cervantes, Marcial Alfredo and Zavala-Loría, José and Loría-Bastarrachea, María and Aguilar-Vega, Manuel and Dzul Lopez, Luis Alonso and Sámano Celorio, María Luisa and Crespo-Álvarez, Jorge and García Villena, Eduardo and Agudo-Toyos, Pablo and Méndez-Martínez, Francisco mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, luis.dzul@unini.edu.mx, marialuisa.samano@uneatlantico.es, jorge.crespo@uneatlantico.es, eduardo.garcia@uneatlantico.es, pablo.agudo@uenatlantico.es, UNSPECIFIED (2019) Effect of Sulfonic Groups Concentration on IEC Properties in New Fluorinated Copolyamides. Polymers, 11 (7). p. 1169. ISSN 2073-4360

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Masías Vergara, Manuel and Agudo-Toyos, Pablo and Giampieri, Francesca and Battino, Maurizio mail francesca.pistollato@uneatlantico.es, manuel.masias@uneatlantico.es, pablo.agudo@uenatlantico.es, UNSPECIFIED, UNSPECIFIED (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

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Canedo-Lopez, Yunuen and Narvaez-Garcia, Asteria and Zavala Loría, José del Carmen and Dzul Lopez, Luis Alonso and Sámano Celorio, María Luisa and Crespo-Álvarez, Jorge and García Villena, Eduardo and Agudo-Toyos, Pablo mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

2018

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Quiles, José L. and Orantes-Bermejo, Francisco J. and Gasparrini, Massimiliano and Forbes-Hernandez, Tamara Y. and Sánchez-González, Cristina and Llopis, Juan and Rivas-García, Lorenzo and Afrin, Sadia and Varela-López, Alfonso and Cianciosi, Danila and Reboredo-Rodriguez, Patricia and Fernández-Piñar, Cristina Torres and Caderón Iglesia, Rubén and Ruiz Salces, Roberto and Aparicio Obregón, Silvia and Crespo-Álvarez, Jorge and Dzul Lopez, Luis and Xiao, Jianbo and Battino, Maurizio mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ruben.calderon@uneatlantico.es, roberto.ruiz@uneatlantico.es, silvia.aparicio@uneatlantico.es, jorge.crespo@uneatlantico.es, luis.dzul@unini.edu.mx, UNSPECIFIED, 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

Article Subjects > Biomedicine
Subjects > Nutrition
Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Calderón Iglesias, Rubén and Ruiz Salces, Roberto and Aparicio-Obregón, Silvia and Crespo-Álvarez, Jorge and Dzul Lopez, Luis Alonso and Manna, Piera Pia and Giampieri, Francesca and Battino, Maurizio mail francesca.pistollato@uneatlantico.es, ruben.calderon@uneatlantico.es, roberto.ruiz@uneatlantico.es, silvia.aparicio@uneatlantico.es, jorge.crespo@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (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

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Giampieri, Francesca and Forbes-Hernandez, Tamara Y. and Afrin, Sadia and Cianciosi, Danila and Reboredo-Rodriguez, Patricia and Varela-Lopez, Alfonso and Zhang, JiaoJiao and Quiles, Josè L. and Mezzetti, Bruno and Bompadre, Stefano and Battino, Maurizio mail UNSPECIFIED, UNSPECIFIED, tamara.forbes@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

2017

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Forbes-Hernandez, Tamara Y. and Giampieri, Francesca and Afrin, Sadia and Alvarez-Suarez, Josè M. and Mazzoni, Luca and Mezzetti, Bruno and Quiles, Josè L. and Battino, Maurizio mail UNSPECIFIED, tamara.forbes@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Psychology Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Martín Ayala, Juan Luis mail UNSPECIFIED (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

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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. and Giampieri, Francesca and Gasparrini, Massimiliano and Afrin, Sadia and Mazzoni, Luca and Cordero, Mario and Mezzetti, Bruno and Quiles, José L. and Battino, Maurizio mail tamara.forbes@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Forbes-Hernandez, Tamara Y. and Giampieri, Francesca and Afrin, Sadia and Mezzetti, Bruno and Quiles, José L. and Bompadre, Stefano and Battino, Maurizio mail UNSPECIFIED, tamara.forbes@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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. and Gasparrini, Massimiliano and Afrin, Sadia and Cianciosi, Danila and González-Paramás, Ana and Santos-Buelga, Celestino and Mezzetti, Bruno and Quiles, José L. and Battino, Maurizio and Giampieri, Francesca and Bompadre, Stefano mail tamara.forbes@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (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

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Alvarez-Suarez, Josè M. and Cordero, Mario D. and Gasparrini, Massimiliano and Forbes-Hernandez, Tamara Y. and Afrin, Sadia and Santos-Buelga, Celestino and González-Paramás, Ana M. and Astolfi, Paola and Rubini, Corrado and Zizzi, Antonio and Tulipani, Sara and Quiles, Josè L. and Mezzetti, Bruno and Battino, Maurizio mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, tamara.forbes@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Forbes-Hernandez, Tamara Y. and Afrin, Sadia and Reboredo-Rodriguez, Patricia and Cianciosi, Danila and Mezzetti, Bruno and Quiles, José L. and Bompadre, Stefano and Battino, Maurizio and Giampieri, Francesca mail UNSPECIFIED, tamara.forbes@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED (2017) Strawberry-Based Cosmetic Formulations Protect Human Dermal Fibroblasts against UVA-Induced Damage. Nutrients, 9 (6). p. 605. ISSN 2072-6643

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Forbes-Hernandez, Tamara Y. and Gasparrini, Massimiliano and Afrin, Sadia and Cianciosi, Danila and Reboredo-Rodriguez, Patricia and Varela-Lopez, Alfonso and Quiles, Jose L. and Mezzetti, Bruno and Battino, Maurizio mail UNSPECIFIED, tamara.forbes@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Calderón Iglesias, Rubén and Ruiz Salces, Roberto and Aparicio Obregón, Silvia and Crespo Alvare, Jorge and Dzul Lopez, Luis and Giampieri, Francesca and Battino, Maurizio mail UNSPECIFIED, ruben.calderon@uneatlantico.es, roberto.ruiz@uneatlantico.es, silvia.aparicio@uneatlantico.es, jorge.crespo@uneatlantico.es, luis.dzul@unini.edu.mx, UNSPECIFIED, 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

2016

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Sumalla Cano, Sandra and Elío Pascual, Iñaki and Masias Vergara, Manuel and Giampieri, Francesca and 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

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Mazzoni, Luca and Alvarez-Suarez, José M. and Giampieri, Francesca and Gasparrini, Massimiliano and Forbes-Hernandez, Tamara Y. and Afrin, Sadia and Errico Provenzano, Alfredo and Persico, Giuseppe and Mezzetti, Bruno and Amici, Augusto and Fanelli, Mirco and Battino, Maurizio mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, tamara.forbes@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Sumalla Cano, Sandra and Elío Pascual, Iñaki and Masias Vergara, Manuel and Giampieri, Francesca and Battino, Maurizio mail francesca.pitollato@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

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Alvarez-Suarez, Jose M. and Gasparrini, Massimiliano and Forbes- Hernandez, Tamara Y. and Afrin, Sadia and Bompadre, Stefano and Rubini, Corrado and Zizzi, Antonio and Astolfi, Paola and Santos-Buelga, Celestino and González-Paramás, Ana M. and Quiles, Josè L. and Mezzetti, Bruno and Battino, Maurizio mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, tamara.forbes@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Bremer-Hoffmann, Susanne and Basso, Giuseppe and Sumalla Cano, Sandra and Elío Pascual, Iñaki and Masías Vergara, Manuel and Giampieri, Francesca and Battino, Maurizio mail francesca.pistollato@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, 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

2015

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Román-Malo, Lourdes and Marín-Aguilar, Fabiola and Alvarez-Suarez, José Miguel and Giampieri, Francesca and Battino, Maurizio and Cordero, Mario D. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, josemanuel.alvarez@unini.edu.mx, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED (2015) Lipophilic antioxidants prevent lipopolysaccharide-induced mitochondrial dysfunction through mitochondrial biogenesis improvement. Pharmacological Research, 91. pp. 1-8. ISSN 10436618

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Sumalla Cano, Sandra and Elio Pascual, Iñaki and Masias Vergara, Manuel and Giampieri, Francesca and Battino, Maurizio mail francesca.pistollato@uneatlantico.es, sandra.sumalla@uneatlantico.es, inaki.elio@uneatlantico.es, manuel.masias@uneatlantico.es, UNSPECIFIED, 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

Article Subjects > Biomedicine
Subjects > Nutrition
Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Sumalla Cano, Sandra and Elío Pascual, Iñaki and Masías Vergara, Manuel and Giampieri, Francesca and 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

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Perez-Lopez, Patricia and Giampieri, Francesca and Alvarez-Suarez, José M. and Gasparrini, Massimiliano and Forbes-Hernandez, Tamara Y. and Quiles, José L. and Mezzetti, Bruno and Battino, Maurizio mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, tamara.forbes@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, 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

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Giampieri, Francesca and Battino, Maurizio mail francesa.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

2014

Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
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 and Alvarez-Suarez, José and Mazzoni, Luca and Forbes-Hernandez, Tamara Y. and Gasparrini, Massimiliano and Gonzàlez-Paramàs, Ana and Santos-Buelga, Celestino and Quiles, José and Bompadre, Stefano and Mezzetti, Bruno and Battino, Maurizio mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, tamara.forbes@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, 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

2013

Article Subjects > Social Sciences Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Abierto Español El objetivo de este estudio fue presentar cómo aplicar un modelo de ciclo de contra-inteligencia empresarial (CCIE) en la dirección estratégica, de forma que se puedan tomar medidas sobre la protección contra el espionaje cibernético en las tecnologías de la información y las comunicaciones (TICs) en las organizaciones. Los datos se obtuvieron de las recomendaciones de tres estudios relacionados con el espionaje cibernético en las TICS. El método de investigación se fundamentó en el análisis cualitativo de las recomendaciones de estos tres documentos y se clasificaron de acuerdo a las etapas del modelo CCIE recomendado por Lauria (2008). Los resultados demostraron que el 73% de las recomendaciones de los documentos analizados se relacionó con la definición de requisitos de protección, evaluación de vulnerabilidades, procesar, analizar y difundir los resultados. El 22% se relacionó con evaluar las amenazas de la competencia, desarrollar y utilizar protección. Estos resultados sugieren deficiencias en el desarrollo de contramedidas, lo cual afecta el ciclo completo. Se analizaron los documentos en el año 2013. metadata Valdés Ortíz, Francisco and Hidalgo González, Cristina and Gracia Villar, Santos and Domingo Soriano, Saúl mail UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, saul_domingo@funiber.org (2013) Aplicación de contra-inteligencia empresarial: análisis sobre la protección contra el espionaje cibernético en las organizaciones. Scientific International Journal, 10 (3). pp. 19-31. ISSN 1554-6349

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Deep Learning-Based Real Time Defect Detection for Optimization of Aircraft Manufacturing and Control Performance

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.

Producción Científica

Imran Shafi mail , Muhammad Fawad Mazhar mail , Anum Fatima mail , Roberto Marcelo Álvarez mail roberto.alvarez@uneatlantico.es, Yini Airet Miró Vera mail yini.miro@uneatlantico.es, Julio César Martínez Espinosa mail ulio.martinez@unini.edu.mx, Imran Ashraf mail ,

Shafi

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Systematic Review of Machine Learning applied to the Prediction of Obesity and Overweight

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.

Producción Científica

Antonio Ferreras mail , Sandra Sumalla Cano mail sandra.sumalla@uneatlantico.es, Rosmeri Martínez-Licort mail , Iñaki Elío Pascual mail inaki.elio@uneatlantico.es, Kilian Tutusaus mail kilian.tutusaus@uneatlantico.es, Thomas Prola mail thomas.prola@uneatlantico.es, Juan Luis Vidal Mazón mail juanluis.vidal@uneatlantico.es, Benjamín Sahelices mail , Isabel de la Torre Díez mail ,

Ferreras

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Integration of Sustainable Criteria in the Development of a Proposal for an Online Postgraduate Program in the Projects Area

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

Producción Científica

Mónica Gracia Villar mail monica.gracia@uneatlantico.es, Roberto Marcelo Álvarez mail roberto.alvarez@uneatlantico.es, Santiago Brie mail santiago.brie@uneatlantico.es, Yini Airet Miró Vera mail yini.miro@uneatlantico.es, Eduardo García Villena mail eduardo.garcia@uneatlantico.es,

Gracia Villar

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A commentary of factors related to player availability and its influence on performance in elite team sports

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.

Producción Científica

Julio Calleja-González mail , Javier Mallo mail , Francesc Cos mail , Jaime Sampaio mail , Margaret T. Jones mail , Diego Marqués-Jiménez mail , Juan Mielgo-Ayuso mail , Tomás T. Freitas mail , Pedro E. Alcaraz mail , Javier Vilamitjana mail , Sergio J. Ibañez mail , Francesco Cuzzolin mail , Nicolás Terrados mail , Stephen P. Bird mail , Asier Zubillaga mail , Thomas Huyghe mail , Igor Jukic mail , Alberto Lorenzo mail , Irineu Loturco mail , Anne Delextrat mail , Xavi Schelling mail , Miguel Gómez-Ruano mail , Isaac López-laval mail , Jairo Vazquez mail , Daniele Conte mail , Álvaro Velarde-Sotres mail alvaro.velarde@uneatlantico.es, Antonio Bores Cerezal mail antonio.bores@uneatlantico.es, Davide Ferioli mail , Franc García mail , Xavier Peirau mail , Rafael Martin-Acero mail , Carlos Lago-Peñas mail ,

Calleja-González

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Anthocyanins: what do we know until now?

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

Producción Científica

Francesca Giampieri mail francesca.giampieri@uneatlantico.es, Danila Cianciosi mail , José M. Alvarez-Suarez mail , José L. Quiles mail jose.quiles@uneatlantico.es, Tamara Y. Forbes-Hernández mail , María D. Navarro-Hortal mail , Michele Machì mail , Ramón Pali-Casanova mail ramon.pali@unini.edu.mx, Julio César Martínez Espinosa mail ulio.martinez@unini.edu.mx, Xiumin Chen mail , Di Zhang mail , Weibin Bai mail , Tian Lingmin mail , Bruno Mezzetti mail , Maurizio Battino mail maurizio.battino@uneatlantico.es, Yasmany Armas Diaz mail ,

Giampieri