El tridimensionalismo jurídico en el sistema penitenciario: interpretación de las obligaciones garantes normativas en el estado de Campeche, México.
Thesis Subjects > Social Sciences Ibero-american International University > Research > Doctoral Thesis Cerrado Español Los derechos humanos a partir de la reforma constitucional de 2011 fueron revestidos de obligaciones estatales a nivel internacional, nacional y local. Estas obligaciones permiten a sus titulares gozar y exigir el cúmulo de derechos humanos que garantizan su dignidad humana y, por ende, su autodeterminación. Cuando estos titulares pertenecen a grupos vulnerables dependientes en su totalidad del Estado, la evaluación de los compromisos jurídicos debe ser analizado aún más estrictamente, si lo es posible. Los sujetos privados de la libertad en cumplimiento de las sanciones del Estado, son titulares de derechos dependientes de la materialización de los mismos del propio Estado. De ahí que surja la motivación del presente estudio para conocer e interpretar los alcances de la garantía jurídica en materia de derechos humanos del Estado de Campeche, en grupos vulnerables privados de la libertad.El estudio tiene como metodología el tridimensionalismo jurídico, propuesto por Miguel Reale. En la presente tesis se analizan los hechos, el valor y la norma acorde a cada grupo poblacional vulnerable, de cada estadio evolutivo de la persona; para dar respuesta a través de la construcción de una serie de directrices y principios interpretativos que permiten conocer si se cumplimenta o no con lo establecido por la Constitución Política de los Estados Unidos Mexicanos, legislaciones internacionales, criterios y recomendaciones internacionales, entre otros elementos valiosos para el análisis en comento. Concluyendo con una serie de recomendaciones que permitan discernir directrices suficientes que aporten un valor teórico jurídico a la omni-comprensión del tratamiento de los derechos humanos. metadata Barony Vera, Erika mail erika.barony@doctorado.unini.edu.mx (2023) El tridimensionalismo jurídico en el sistema penitenciario: interpretación de las obligaciones garantes normativas en el estado de Campeche, México. Doctoral thesis, Universidad Internacional Iberoamericana México.
Full text not available from this repository.Abstract
Los derechos humanos a partir de la reforma constitucional de 2011 fueron revestidos de obligaciones estatales a nivel internacional, nacional y local. Estas obligaciones permiten a sus titulares gozar y exigir el cúmulo de derechos humanos que garantizan su dignidad humana y, por ende, su autodeterminación. Cuando estos titulares pertenecen a grupos vulnerables dependientes en su totalidad del Estado, la evaluación de los compromisos jurídicos debe ser analizado aún más estrictamente, si lo es posible. Los sujetos privados de la libertad en cumplimiento de las sanciones del Estado, son titulares de derechos dependientes de la materialización de los mismos del propio Estado. De ahí que surja la motivación del presente estudio para conocer e interpretar los alcances de la garantía jurídica en materia de derechos humanos del Estado de Campeche, en grupos vulnerables privados de la libertad.El estudio tiene como metodología el tridimensionalismo jurídico, propuesto por Miguel Reale. En la presente tesis se analizan los hechos, el valor y la norma acorde a cada grupo poblacional vulnerable, de cada estadio evolutivo de la persona; para dar respuesta a través de la construcción de una serie de directrices y principios interpretativos que permiten conocer si se cumplimenta o no con lo establecido por la Constitución Política de los Estados Unidos Mexicanos, legislaciones internacionales, criterios y recomendaciones internacionales, entre otros elementos valiosos para el análisis en comento. Concluyendo con una serie de recomendaciones que permitan discernir directrices suficientes que aporten un valor teórico jurídico a la omni-comprensión del tratamiento de los derechos humanos.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | Derechos humanos, derechos fundamentales, centros penitenciarios, grupos vulnerables. |
| Subjects: | Subjects > Social Sciences |
| Divisions: | Ibero-american International University > Research > Doctoral Thesis |
| Date Deposited: | 28 Sep 2023 23:30 |
| Last Modified: | 28 Sep 2023 23:30 |
| URI: | https://repositorio.unini.edu.mx/id/eprint/6893 |
Actions (login required)
 |
View Item |
en
close
Single-cell omics for nutrition research: an emerging opportunity for human-centric investigations
Understanding how dietary compounds affect human health is challenged by their molecular complexity and cell-type–specific effects. Conventional multi-cell type (bulk) analyses obscure cellular heterogeneity, while animal and standard in vitro models often fail to replicate human physiology. Single-cell omics technologies—such as single-cell RNA sequencing, as well as single-cell–resolved proteomic and metabolomic approaches—enable high-resolution investigation of nutrient–cell interactions and reveal mechanisms at a single-cell resolution. When combined with advanced human-derived in vitro systems like organoids and organ-on-chip platforms, they support mechanistic studies in physiologically relevant contexts. This review outlines emerging applications of single-cell omics in nutrition research, emphasizing their potential to uncover cell-specific dietary responses, identify nutrient-sensitive pathways, and capture interindividual variability. It also discusses key challenges—including technical limitations, model selection, and institutional biases—and identifies strategic directions to facilitate broader adoption in the field. Collectively, single-cell omics offer a transformative framework to advance human-centric nutrition research.
Manuela Cassotta mail manucassotta@gmail.com, Yasmany Armas Diaz mail , Danila Cianciosi mail , Bei Yang mail , Zexiu Qi mail , Ge Chen mail , Santos Gracia Villar mail santos.gracia@uneatlantico.es, Luis Alonso Dzul López mail luis.dzul@uneatlantico.es, Giuseppe Grosso mail , José L. Quiles mail , Jianbo Xiao mail , Maurizio Battino mail maurizio.battino@uneatlantico.es, Francesca Giampieri mail francesca.giampieri@uneatlantico.es,
Cassotta
<a href="/17862/1/sensors-25-06419.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
en
open
Edge-Based Autonomous Fire and Smoke Detection Using MobileNetV2
Forest fires pose significant threats to ecosystems, human life, and the global climate, necessitating rapid and reliable detection systems. Traditional fire detection approaches, including sensor networks, satellite monitoring, and centralized image analysis, often suffer from delayed response, high false positives, and limited deployment in remote areas. Recent deep learning-based methods offer high classification accuracy but are typically computationally intensive and unsuitable for low-power, real-time edge devices. This study presents an autonomous, edge-based forest fire and smoke detection system using a lightweight MobileNetV2 convolutional neural network. The model is trained on a balanced dataset of fire, smoke, and non-fire images and optimized for deployment on resource-constrained edge devices. The system performs near real-time inference, achieving a test accuracy of 97.98% with an average end-to-end prediction latency of 0.77 s per frame (approximately 1.3 FPS) on the Raspberry Pi 5 edge device. Predictions include the class label, confidence score, and timestamp, all generated locally without reliance on cloud connectivity, thereby enhancing security and robustness against potential cyber threats. Experimental results demonstrate that the proposed solution maintains high predictive performance comparable to state-of-the-art methods while providing efficient, offline operation suitable for real-world environmental monitoring and early wildfire mitigation. This approach enables cost-effective, scalable deployment in remote forest regions, combining accuracy, speed, and autonomous edge processing for timely fire and smoke detection.
Dilshod Sharobiddinov mail , Hafeez Ur Rehman Siddiqui mail , Adil Ali Saleem mail , Gerardo Méndez Mezquita mail , Debora L. Ramírez-Vargas mail debora.ramirez@unini.edu.mx, Isabel de la Torre Díez mail ,
Sharobiddinov
<a href="/17863/1/v16p4316.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
en
open
Breast cancer is a lethal carcinoma impacting a considerable number of women across the globe. While preventive measures are limited, early detection remains the most effective strategy. Accurate classification of breast tumors into benign and malignant categories is important which may help physicians in diagnosing the disease faster. This survey investigates the emerging inclination and approaches in the area of machine learning (ML) for the diagnosis of breast cancer, pointing out the classification techniques based on both segmentation and feature selection. Certain datasets such as the Wisconsin Diagnostic Breast Cancer Dataset (WDBC), Wisconsin Breast Cancer Dataset Original (WBCD), Wisconsin Prognostic Breast Cancer Dataset (WPBC), BreakHis, and others are being evaluated in this study for the demonstration of their influence on the performance of the diagnostic tools and the accuracy of the models such as Support vector machine, Convolutional Neural Networks (CNNs) and ensemble approaches. The main shortcomings or research gaps such as prejudice of datasets, scarcity of generalizability, and interpretation challenges are highlighted. This research emphasizes the importance of the hybrid methodologies, cross-dataset validation, and the engineering of explainable AI to narrow these gaps and enhance the overall clinical acceptance of ML-based detection tools.
Alveena Saleem mail , Muhammad Umair mail , Muhammad Tahir Naseem mail , Muhammad Zubair mail , Silvia Aparicio Obregón mail silvia.aparicio@uneatlantico.es, Rubén Calderón Iglesias mail ruben.calderon@uneatlantico.es, Shoaib Hassan mail , Imran Ashraf mail ,
Saleem
<a class="ep_document_link" href="/17849/1/1-s2.0-S2590005625001043-main.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
en
open
Ultra Wideband radar-based gait analysis for gender classification using artificial intelligence
Gender classification plays a vital role in various applications, particularly in security and healthcare. While several biometric methods such as facial recognition, voice analysis, activity monitoring, and gait recognition are commonly used, their accuracy and reliability often suffer due to challenges like body part occlusion, high computational costs, and recognition errors. This study investigates gender classification using gait data captured by Ultra-Wideband radar, offering a non-intrusive and occlusion-resilient alternative to traditional biometric methods. A dataset comprising 163 participants was collected, and the radar signals underwent preprocessing, including clutter suppression and peak detection, to isolate meaningful gait cycles. Spectral features extracted from these cycles were transformed using a novel integration of Feedforward Artificial Neural Networks and Random Forests , enhancing discriminative power. Among the models evaluated, the Random Forest classifier demonstrated superior performance, achieving 94.68% accuracy and a cross-validation score of 0.93. The study highlights the effectiveness of Ultra-wideband radar and the proposed transformation framework in advancing robust gender classification.
Adil Ali Saleem mail , Hafeez Ur Rehman Siddiqui mail , Muhammad Amjad Raza mail , Sandra Dudley mail , Julio César Martínez Espinosa mail ulio.martinez@unini.edu.mx, Luis Alonso Dzul López mail luis.dzul@uneatlantico.es, Isabel de la Torre Díez mail ,
Saleem
<a href="/17856/1/fpubh-13-1654645.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
en
open
Background: Physical activity in children and adolescents represents one of the most important lifestyle factors to determine current and future health. Aim: The aim of the study is to assess the lifestyle and dietary factors linked to physical activity in younger populations across five countries in the Mediterranean region. Design: A total of 2,011 parents of children and adolescents (age range 6–17 years) participating to a preliminary survey of the DELICIOUS project were investigated to determine children's adequate physical activity level (identified using the short form of the international physical activity questionnaire) as well as diet quality parameters [measured as Youth-Healthy Eating Index (Y-HEI)] and eating and lifestyle factors (i.e., meal habits, sleep duration, screen time, etc.). Logistic regression analyses were performed to assess the odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between variables of interest. Results: Younger children of younger parents currently working had higher rates and probability to have adequate physical activity. Multivariate analysis showed that children and adolescents who had breakfast (OR = 1.88, 95% CI: 1.38, 2.56) and often ate with their family (OR = 1.80, 95% CI: 0.90, 3.61) were more likely to have an adequate level of physical activity. Children and adolescents who reported a sleep duration (8–10 h) closest to the recommended one were significantly more likely to achieve adequate levels of physical activity (OR = 1.88, 95% CI: 1.38, 2.56). Conversely, those with more than 4 h of daily screen time were less likely to engage in adequate physical activity (OR = 0.77, 95% CI: 0.54, 1.10). Furthermore, children and adolescents in the highest tertile of YEHI scores showed a 60% greater likelihood of engaging in adequate physical activity (OR = 1.60, 95% CI: 1.27, 2.01). Conclusion: These results emphasize the importance of promoting healthy diet and lifestyle habits, including structured and high quality shared meals, sufficient sleep, and screen time moderation, as key strategies to support active behaviors in younger populations. Future interventions should focus on reinforcing these behaviors through parental guidance and community-based initiatives to foster lifelong healthy habits.
Alice Rosi mail , Francesca Scazzina mail , Maria Antonieta Touriz Bonifaz mail , Francesca Giampieri mail francesca.giampieri@uneatlantico.es, Achraf Ammar mail , Khaled Trabelsi mail , Osama Abdelkarim mail , Mohamed Aly mail , Evelyn Frias-Toral mail , Juancho Pons mail , Laura Vázquez-Araújo mail , Josep Alemany Iturriaga mail josep.alemany@uneatlantico.es, Lorenzo Monasta mail , Nunzia Decembrino mail , Ana Mata mail , Adrián Chacón mail , Pablo Busó mail , Giuseppe Grosso mail ,
Rosi