Facultad de Ingeniería - CampAGS

City

Aguascalientes

Country

Director

Claudia Nallely Sánchez Gómez

Parent Organisation

Campus Aguascalientes

OrgUnit's Publications

Now showing 1 - 10 of 450

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Effects of sourdough and yeast fermented breads consumption on glycaemia in healthy populations: a systematic review
(Frontiers Media SA, 2026-08-04)
Starowicz, Malgorzata
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Domínguez-Soberanes, Julieta
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Garcia-Gutierrez, Enriqueta
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Arslan-Tontul, Sultan
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Burton-Pimentel, Kathryn J.
Bread is a vital source of energy and is widely consumed in human diets. As a carbohydrate-rich food, it is often considered to impair glycaemic homeostasis; however, clinical and molecular evidence suggest that its effects may vary depending on the characteristics of bread consumed. In particular, sourdough-fermented bread has been proposed to exert potentially beneficial effects on glycaemia via shifts in metabolites in the food matrix, as well as chemical and physical changes that occur during fermentation. However, evidence from human interventional studies on this topic is inconsistent due to differing experimental designs, heterogeneous populations, or a focus on sourdough fermentation that does not consider the effects of yeast fermentation. Our objective was to evaluate the evidence for a positive effect of fermented bread consumption on glycaemia and insulinaemia in healthy adults. To this end, we conducted a systematic review to identify and analyze relevant human studies, complemented by a characterization of the breads investigated and a discussion of possible mechanisms of action, following the EFSA dossier framework. We identified 27 studies that met our inclusion criteria. Taking into account the risk of bias in these studies, the consistency of the reported effects, and the biological plausibility based on food characteristics and potential mechanisms of action, we conclude that the available evidence for a beneficial effect of sourdough compared to yeast-fermented bread on glycaemic and insulinaemic homeostasis in healthy individuals is neither sufficient nor convincing. For the general effect of fermentation on glycaemic and insulinaemic homeostasis in healthy individuals, evidence is considered very low. Copyright © 2026 Starowicz, Domínguez-Soberanes, Garcia-Gutierrez, Arslan-Tontul, Burton-Pimentel, Vidović, Moreno-Indias, Karagöz, Prvulović, Simeunovic, Ruiz-Limón, Gutiérrez-Repiso, Pajalic, Yerlikaya, Esatbeyoglu, Yilmaz, Mantzouridou, Chassard, Pracer, Vergères and Louis.
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A techno-biological framework for the optimization of utility-scale agrivoltaic systems using spatial yield constraints
(Elsevier BV, 2026-12)
Rodrigo, P. M.
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Gutiérrez, Sebastián
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Perez-Higueras, Pedro
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Islas-Pereda, Saul
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Escalante-Garcia, Nivia
The increasing competition for land between agricultural production and solar energy installation poses a major threat to global food and energy security. Agrivoltaic systems, which combine crop cultivation with photovoltaic arrays, help to alleviate this conflict. However, the diverse designs and complex interactions introduce substantial challenges for optimization. This study introduces a process-based biophysical framework for the optimization of utility-scale agrivoltaic systems under structural and spatial yield constraints. The framework includes fixed-tilt elevated, fixed vertical, and single-axis tracking systems, utilizing both monofacial and bifacial photovoltaic technologies. It integrates the physical layout geometries of photovoltaic arrays with dynamic microclimatic irradiance modeling and non-linear canopy photosynthetic saturation curves to evaluate the theoretical photosynthetic performance bounds and energy production metrics. In addition, a spatial optimization methodology governed by a strict ‘80/90 rule’ is presented. This methodology systematically identifies the maximum allowable array densities while ensuring agronomic performance is maintained. The assessment framework was applied across seven different geographic locations in the Americas and Europe, analyzing eleven unique plant species. Results reveal notable variations in optimal array densities, with capacities ranging from 18 to 88 W per square meter (Wp/m2). The proposed configurations can improve land-use efficiency, with land equivalent ratio values ranging from 1.05 to 1.90 as a function of latitude and crop-specific photosynthetic response. The proposed framework provides comprehensive guidelines that must be interpreted as an early-stage theoretical screening tool for comparing agrivoltaic layout performance bounds, rather than as a deployment-ready design or commercial optimization model. © 2026 The Authors.
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Hypnogram-Driven Automatic Sleep Staging and a Quality-Index Assessment Through a Two-Stage LSTM-DNN Ensemble Learning Approach Using Multi-Biosignal Features for Sleep Disorder Detection
(MDPI AG, 2026-06-27)
De Fazio, Roberto
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Paiano, Matteo
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Del-Valle-Soto, Carolina
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Al-Naami, Bassam
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Velázquez, Ramiro
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An Innovative Solution with Wearable and Aboard-the-Vehicle Sensors Integrated with Machine Learning Algorithms for Monitoring the Driver's Psycho-Physical Condition for Safety Purposes
(2024)
Roberto De Fazio
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Ilaria Cascella
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Paolo Visconti
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Velázquez, Ramiro
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Del-Valle-Soto, Carolina
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Rethinking Authenticity in Architecture: The Ethical Implications of AI-Generated Design
(Springer Nature Switzerland, 2025)
Colmenero Acevedo Ezequiel Alberto
17
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Data-Driven Based Control Applied to DC Network Converters for Voltage Bus Stabilization
(2020)
J. Loranca-Coutino
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C.V. Villarreal-Hernandez
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Ruiz-Martinez, O.F.
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Mayo Maldonado, Jonathan
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J.E. Valdez-Resendiz
1 11
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Predicting bitcoin price fluctuations using deep learning while leveraging the recurrent embedded topic model over text-based data
(C. Vargas F., 2024)
Vargas Fraga Carlos
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Ponce Espinosa, Hiram Eredín
En esta tesis se aborda el problema de predecir las fluctuaciones de precios de Bitcoin utilizando modelos de procesamiento de lenguaje natural mediante el uso de noticias de criptomonedas para garantizar predicciones de mayor calidad. Dado que las noticias sobre criptomonedas contienen vocabularios muy extensos y hablan sobre diferentes temas, los modelos de tópicos actuales son estrictos en la forma en que calculan las distribuciones de temas, por lo que no permiten flexibilidad según el conjunto de datos sobre el que se ajustan. Por lo tanto, cuando se aplican las distribuciones como conjunto de datos para entrenar un algoritmo de aprendizaje automático o de aprendizaje profundo, tiende a no ajustarse a las variaciones de precios de Bitcoin. Este trabajo investiga el fenómeno de manera estructurada a través de una metodología de investigación académica inspirada en CRISP-DM (Cross Industry Standard Process for Data Mining), aportando un nuevo modelo de tópicos de última generación llamado: Recurrent Embedded Topic Model(RETM), cuya novedad deriva de su capacidad para superar a los modelos de temas actuales al brindar flexibilidad al calcular las distribuciones de los tópicos. El RETM se comparó con otros modelos basados en precios, modelos de tópicos, análisis de sentimientos y modelos de encaje (embeddings) para integrarlos en varios modelos de aprendizaje automático y aprendizaje profundo para predecir las variaciones en precio de Bitcoin. Hubo una clara diferencia con un modelo basado en aprendizaje profundo (predictor binario) frente a todas las demás técnicas (con una exactitud del 73%, una precisión del 85% y un AUC (Area Under the Curve) del 79%), asegurando así predicciones de mayor calidad sobre las variaciones de precios de Bitcoin. Dentrode la tesis, existe una discusión sobre las complejidades de implementación para poner en prácticala metodología propuesta, así como, algunos análisis sobre la validez, confiabilidad, errores y limitaciones que surgieron de esta investigación. Se ha demostrado que este modelo proporciona mejores distribuciones de tópicos que se pueden aplicar a cualquier problema basado en el procesamiento del lenguaje natural que se puedan resolver utilizando distribuciones de tópicos o palabras, tanto problemas descriptivos o predictivos
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Introduction
(Springer Science and Business Media Deutschland GmbH, 2026)
Velázquez, Ramiro
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Pissaloux, Edwidge
8
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Switched Control Design for a Modified SEPIC Converter Applied to PEF Generation.
(IEEE, 2024-10-20)
Ruiz-Martinez, O.F.
29
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Color-aware Exposure Correction for Endoscopic Imaging using a Lightweight Vision Transformer
(2024)
Espinosa Loera, Ricardo Abel
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Eluney Hernández
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Gilberto Ochoa-Ruiz
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Christian Daul
13

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