Historical use of water resources. Civil works evolution in Zacatecas state

Carlos Bautista-Capetillo Georgia González-Pérez Hiram Badillo-Almaraz (2021, [Artículo, Artículo])

Availability and demand are essential aspects for the human being when planning is made to provide water to the different sectors that may have need of it; still, the demand of suitable volume of water increases day by day, while the supply decreases gradually. In this inverse relationship, anthropogenic and environmental dynamics are decisive to guarantee the needs of the population, specifically due to the climatic transformations evidenced in recent decades. Throughout history, the state of Zacatecas has suffered the ravages of extreme environmental events, mainly those related to drought. Likewise, but on a lesser extent, severe floods have occurred that have caused socioeconomic damage. In this work, the climatic variations of temperature and precipitation and their influence on the evolution of hydraulic systems for the supply of drinking water in the municipality of Nochistlán de Mejía, Zacatecas are analyzed during the period 1930-2015.

drinking water supply historical development of waterworks climate and its transformations Abasto de agua potable desarrollo histórico de obras hidráulicas clima y sus transformaciones CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA

Colaboración y co-creación de conocimiento para una agricultura sostenible

Jelle Van Loon (2021, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SUSTAINABLE AGRICULTURE AGRIFOOD SYSTEMS FOOD SECURITY CLIMATE CHANGE ADAPTATION

Dormitator latifrons (Richardson, 1844) a Pacific fat sleeper, but skinny in research: a scientometric study

MARTIN ALONSO ARECHIGA PALOMERA KAREN NOEMI NIEVES RODRIGUEZ OLIMPIA CHONG CARRILLO Héctor Gerardo Nolasco Soria Emyr Saúl Peña Marín Carlos Alfonso Alvarez_González DAVID JULIAN PALMA CANCINO RAFAEL MARTINEZ GARCIA DANIEL BADILLO ZAPATA FERNANDO VEGA VILLASANTE (2022, [Artículo])

"In order to provide information on the current knowledge about the native fish Dormitator latifrons and identify the gaps that must be filled to achieve correct resource management, a scientometric study was carried out using different scientific databases. A total of 103 publications were registered between the years 1972 and 2021. Results indicate that the species has been addressed since 2001 with less than one publication per year, with 2008 being the year with the highest number of publications (10). The main topics addressed were ecology, physiology, and parasitology of fish. The available knowledge generated about the species is concentrated in 68 journals, with Mexico as the most productive country, followed by USA and Ecuador, and the most productive research centers about this fish were Mexico’s Instituto Politécnico Nacional and Universidad de Guadalajara. A total of 285 authors were detected contributing knowledge to the species, with Violante-González in the top with ten publications. The co-authorship co-occurrence maps suggest there is no solid collaborative relationship between the scientific community and that the information generated is insufficient for conserving and exploiting this fish. It is essential to increase the study of thematic areas that allow their comprehensive management in the medium term; topics like reproduction in captivity, aquaculture, and nutrition must be addressed in the future to assure a sustainable use of this resource."

Dormitator latifrons, native fish, amphidromous, worldwide database, regional database, cooccurrence map CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CIENCIAS AGRARIAS PECES Y FAUNA SILVESTRE DINÁMICA DE LAS POBLACIONES DINÁMICA DE LAS POBLACIONES

Transición de leña a gas licuado a presión (GLP) en el sur de México, oportunidad para la mitigación del cambio climático en la región menos desarrollada del país

Transition from biomass to LP gas in southern Mexico, an opportunity for climate change mitigation in the least developed region in the country

Elio Guarionex Lagunes Díaz María Eugenia González Rosende Alfredo Ortega Rubio (2015, [Artículo])

"En los estados del sur de México, entre un 25% y un 55% de los hogares dependen de la leña para cocinar, lo cual trae consecuencias en el ambiente, el desarrollo y la salud. No obstante, el conocimiento de estas consecuencias y la migración hacia combustibles modernos ha permanecido relegada de las políticas de desarrollo. En este trabajo, partiendo de una descripción del panorama de uso de leña en el país y su importancia como fuente de energía, se presenta una aproximación para estimar ahorros en emisiones de CO2 logrables por la transición a gas licuado a presión (GLP), los cuales pueden alcanzar 3.14 Mt CO2e, 26% menos que el escenario base. Se finaliza con una discusión de la transición hacia combustibles modernos, las barreras que la impiden y los logros y fallos de la distribución de estufas ahorradoras de leña, la principal iniciativa gubernamental para aliviar el consumo de leña en el país."

"Between 25% and 55% of households in southern Mexico depend on biomass for cooking, which carries serious consequences on the environment, development and health. In spite of the knowledge of these consequences, transition from biomass to modern fuels has remained outside energy and development policies. In the present work, after describing the panorama of fuelwood use in the country and its importance as an energy source, an approach is presented for estimating CO2 savings achievable by transition to pressurized liquefied gas (LP). These savings can reach 3.14 Mt CO2e, 26% less than the baseline scenario. At the end we discuss on the transition to modern fuels in Mexico, the barriers that hinder it and the achievements and failures of the distribution of fuelwood saving cookstoves, as the only and most important governmental initiative to alleviate biomass use, comparing it with other priorities in the government's agenda."

Transición energética, cambio climático, política energética. Energy transition, climate change, energy policy. CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA CIENCIAS DE LA TIERRA Y DEL ESPACIO METEOROLOGÍA CONTAMINACIÓN ATMOSFÉRICA CONTAMINACIÓN ATMOSFÉRICA

Agricultura, agua y cambio climático en zonas áridas de México

SALVADOR EMILIO LLUCH COTA JUAN ALBERTO VELAZQUEZ ZAPATA César Nieto Delgado (2022, [Artículo])

"En este artículo se expone cómo a pesar de que la ciencia y la tecnología han permitido aumentar históricamente la productividad agrícola, hoy día existen grandes retos derivados del cambio climático y la crisis global de abastecimiento de agua. Se comentan algunas medidas de adaptación y manejo del recurso agua, con algunas referencias a nuestra realidad nacional, y se argumenta cómo el enfoque de Nexo, que implica la toma de decisiones sobre el uso del recurso agua de forma transectorial, representa una alternativa de adaptación al cambio climático."

Cambio climático, agricultura, agua, Nexo, adaptación Climate change, agriculture, water, nexus, adaptation CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA CIENCIAS DE LA TIERRA Y DEL ESPACIO CLIMATOLOGÍA CLIMATOLOGÍA REGIONAL CLIMATOLOGÍA REGIONAL

Offshore wind energy climate projection using UPSCALE climate data under the RCP8.5 emission scenario

MARKUS SEBASTIAN GROSS (2016, [Artículo])

In previous work, the authors demonstrated how data from climate simulations can be utilized to estimate regional wind power densities. In particular, it was shown that the quality of wind power densities, estimated from the UPSCALE global dataset in offshore regions of Mexico, compared well with regional high resolution studies. Additionally, a link between surface temperature and moist air density in the estimates was presented. UPSCALE is an acronym for UK on PRACE (the Partnership for Advanced Computing in Europe)-weather-resolving Simulations of Climate for globAL Environmental risk. The UPSCALE experiment was performed in 2012 by NCAS (National Centre for Atmospheric Science)- Climate, at the University of Reading and the UK Met Office Hadley Centre. The study included a 25.6-year, five-member ensemble simulation of the HadGEM3 global atmosphere, at 25km resolution for present climate conditions. The initial conditions for the ensemble runs were taken from consecutive days of a test configuration. In the present paper, the emphasis is placed on the single climate run for a potential future climate scenario in the UPSCALE experiment dataset, using the Representation Concentrations Pathways (RCP) 8.5 climate change scenario. Firstly, some tests were performed to ensure that the results using only one instantiation of the current climate dataset are as robust as possible within the constraints of the available data. In order to achieve this, an artificial time series over a longer sampling period was created. Then, it was shown that these longer time series provided almost the same results than the short ones, thus leading to the argument that the short time series is sufficient to capture the climate. Finally, with the confidence that one instantiation is sufficient, the future climate dataset was analysed to provide, for the first time, a projection of future changes in wind power resources using the UPSCALE dataset. It is hoped that this, in turn, will provide some guidance for wind power developers and policy makers to prepare and adapt for climate change impacts on wind energy production. Although offshore locations around Mexico were used as a case study, the dataset is global and hence the methodology presented can be readily applied at any desired location. © Copyright 2016 Gross, Magar. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reprod

atmosphere, climate change, Europe, Mexico, sampling, time series analysis, university, weather, wind power, climate, risk, theoretical model, wind, Climate, Models, Theoretical, Risk, Wind CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA CIENCIAS DE LA TIERRA Y DEL ESPACIO OCEANOGRAFÍA OCEANOGRAFÍA

Contratos inteligentes para la gestión de datos de sensado móvil y vestible para aplicaciones en salud

Smart contracts for mobile and wearable sensing data management for health applications

José Ricardo Cedeño García (2023, [Tesis de maestría])

El aumento en la producción de datos derivado de la adopción de tecnologías móviles y de IoT está revolucionando la salud, pero también plantea importantes retos éticos y de privacidad. Los recientes avances en el aprendizaje automático han resaltado la importancia de recopilar y etiquetar datos correctamente, en especial para fines críticos, como el desarrollo de aplicaciones para cuidados médicos. La recopilación de datos médicos para tareas de aprendizaje automático presenta limitaciones en cuanto a la cantidad, variedad y calidad de las fuentes disponibles. Una forma de abordar este dilema es el uso de Blockchain para la recopilación y el uso de datos de pacientes. El anonimato de una red centralizada permite proteger la identidad del paciente. La estructura formada por nodos permite que la información esté siempre disponible y no dependa de un servidor principal. La inmutabilidad de los registros en la cadena garantiza la trazabilidad inequívoca del flujo de los datos del paciente. Por último, los mecanismos de consenso y recompensa de la red podrían motivar a nuevos usuarios a participar del sensado activo. Presentamos TRHEAD, una arquitectura de referencia basada en la Blockchain para recopilar datos sanitarios, firmar consentimientos, anotar datos y obtener crédito por los mismos, permitiendo a los usuarios rastrear el uso de sus datos, a los científicos rastrear su procedencia y proteger al mismo tiempo la privacidad de los pacientes. Exponemos dos implementaciones de nuestra arquitectura aplicadas a distintas campañas de sensado para comprobar su viabilidad, así como los resultados de su aplicación en estos escenarios y las conclusiones que desprendieron de su análisis. Dado que uno de los objetivos principales de TRHEAD es la recopilación de datos mediante sensado activo para el entrenamiento legal/consciente de modelos de aprendizaje automático, se realizó el entrenamiento de un modelo con los datos obtenidos de la campaña de sensado correspondiente a imágenes de rostros humanos, con el fin de detectar estados de ánimo. Finalmente se discute el papel de TRHEAD en el aseguramiento del trato justo y consciente de la información de los pacientes y el camino por recorrer en el perfeccionamiento de la arquitectura.

The increase in data production resulting from the adoption of mobile and IoT technologies is revolutionizing healthcare, but it also poses significant ethical and privacy challenges. Recent advances in machine learning have highlighted the importance of collecting and labeling data correctly, especially for critical purposes such as deploying healthcare software. Collecting medical data for machine learning tasks presents limitations in terms of the quantity, variety, and quality of available sources. One way to address this dilemma is the use of Blockchain for the collection and use of patient data. The anonymity of a centralized network allows the patient’s identity to be protected. The structure formed by nodes allows information to be always available and not dependent on a main server. The immutability of the records in the chain guarantees the unequivocal traceability of the flow of patient data. Finally, the network’s consensus and reward mechanisms could motivate new users to participate in active sensing. We present TRHEAD, a Blockchain-based reference architecture for collecting healthcare data, signing consents, annotating data and getting credit for it, allowing users to track the use of their data, scientists to track its provenance while protecting patients privacy. We present two implementations of our architecture applied to different sensing campaigns to test their feasibility, as well as the results of their application in these scenarios and the conclusions drawn from those results. Since one of the main objectives of TRHEAD is the collection of data through active sensing for the legal/conscious training of machine learning models, a model was trained with the data obtained from the sensing campaign corresponding to images of human faces, in order to detect moods. Finally, the role of TRHEAD in ensuring the fair and conscientious treatment of patient information and the road ahead in refining the architecture is discussed.

Contratos Inteligentes, Blockchain, Privacidad, Aprendizaje de Máquina Etico, Recopilación Consciente de Datos, Consentimiento, Arquitectura de Referencia Smart Contracts, Blockchain, Privacy, Ethical Machine Learning, Conscious Data Collection, Consent, Reference Architecture INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES INTELIGENCIA ARTIFICIAL INTELIGENCIA ARTIFICIAL

OPTIMIZING THE TRANSFER OF ENERGY IN A HEAT EXCHANGER MINIMIZING THE CORROSION PROBLEMS IN PIPES IN A HYDROELECTRIC POWER STATION USING DATA MINING AND SUPPORT VECTOR MACHINE

VICTOR MANUEL ZEZATTI FLORES GUSTAVO URQUIZA BELTRAN MIGUEL ANGEL BASURTO PENSADO LAURA LILIA CASTRO GOMEZ (2019, [Artículo])

This research is based on the operation tube heat exchangers, their use and problematic on hydroelectric power plants. It is based on the design heat exchanger tubes for industrial use, which took the parameters of operation, design, working fluids (air and water) and conditions to assemble a monitoring equipment at appropriate scale for the laboratory, with the necessary measurement instruments to analyze the behavior of heat energy transfer by means of thermocouples, the velocity of the air with a hot wire anemometer and the flow of water with a turbine flow meter, in pipes of different materials: copper, steel 1018 and stainless steel 316L, all in ideal conditions, and with this to found a comparative parameter with pipes of the same materials but under conditions of deterioration with the presence of forced oxidation and with the data mining and support vector machine can be minimized the corrosion problems in pipes.

INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS Data Mining, Support Vector Machine, Pattern Recognition and Decision Support System, heat exchangers.

Implementation of a Nickel-Electroless Coating in Heat Exchanger Pipes Considering the Problem of the Environmental Conditions ofthe Cooling Water Without Recirculation to Increase the Effectiveness Under Uncertainty

VICTOR MANUEL ZEZATTI FLORES GUSTAVO URQUIZA BELTRAN MIGUEL ANGEL BASURTO PENSADO LAURA LILIA CASTRO GOMEZ JUAN CARLOS GARCIA CASTREJON (2022, [Artículo])

This research is based on the operation tube heat exchangers, their use and problematic on hydroelectric power plants. It is based on the design heat exchanger tubes for industrial use, which took the parameters of operation, design, working fluids (air and water) and conditions to assemble a monitoring equipment at appropriate scale for the laboratory, with the necessary measurement instruments to analyze the behavior of heat energy transfer by means of thermocouples, the velocity of the air with a hot wire anemometer and the flow of water with a turbine flow meter, in pipes of different materials: copper, steel 1018 and stainless steel 316L, all in ideal conditions, and with this to found a comparative parameter with pipes of the same materials but under conditions of deterioration with the presence of forced oxidation and with the data mining and support vector machine can be minimized the corrosion problems in pipes.

INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS Data mining, Support Vector Machine, Pattern Recognition and Decision Support System, Heat exchangers

Detección de eventos violentos en publicaciones de redes sociales

Detection of violent events in social media publications

Esteban Ponce León (2023, [Tesis de maestría])

En los últimos años, ha habido un interés creciente en el monitoreo de redes sociales para recopilar información y, en algunos casos, para examinar la ocurrencia de delitos. Sin embargo, gran parte de las investigaciones hasta ahora solo se han centrado en ciudades de EE. UU. o extranjeras, y por ende, en publicaciones y conjuntos de datos en inglés El objetivo principal de esta tesis es diseñar un método que permita la identificación de publicaciones de eventos violentos en español y en Twitter, utilizando información multimodal y técnicas de aumento de datos que mejoren el rendimiento de los modelos. Para esto, el trabajo de investigación se dividió en dos fases experimentales. La primera orientada a identificar publicaciones a partir de solo texto, explorando diferentes técnicas de aumento de datos para texto y modelos de aprendizaje máquina y profundo. En la segunda fase, se extendió el método propuesto para abordar la identificación en un contexto multimodal, es decir, considerando tanto los textos de los tweets como las imágenes compartidas que los acompañan. En este caso el método propuesto consideró utilizar descripciones textuales de las imágenes y abordar la problemática desde el dominio textual, además se hicieron 2 tipos de aumento de datos para cada tipo de información. La evaluación de los métodos se hizo utilizando las colecciones de la tarea de evaluación DA-VINCIS 2022 y 2023. Los resultados demostraron una mejora en el rendimiento de los modelos al considerar el uso de información multimodal y el uso de aumento de datos.

In recent years, there has been a growing interest in monitoring social networks to gather information and, in some cases, to examine the occurrence of crime. However, much of the research so far has only focused on US or foreign cities, and thus on English-language publications and data sets. The main objective of this thesis is to design a method that allows the identification of publications of violent events in Spanish and on Twitter, using multimodal information and data augmentation techniques that improve the performance of the models. For this, the research work was divided into two experimental phases. The first aimed at identifying publications from only text, exploring different data augmentation techniques for text and machine and deep learning models. In the second phase, the proposed method was extended to address identification in a multimodal context, that is, considering both the texts of the tweets and the shared images that accompany them. In this case, the proposed method considered using textual descriptions of the images and addressing the problem from the textual domain, in addition, 2 types of data augmentation were made for each type of information. The evaluation of the methods was done using the collections of the DA-VINCIS 2022 and 2023 evaluation task. The results demonstrated an improvement in the performance of the models when considering the use of multimodal information and the use of data augmentation.

Detección de Violencia, Redes Sociales, Aumento de Datos, Procesamiento del Lenguaje Natural, BERT, BETO, Descripción de Imágenes Violence Detection, Social Networks, Data Augmentation, Natural Language Processing, BERT, BETO, Image Captioning INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES MODELOS CAUSALES MODELOS CAUSALES