Physiological and molecular aspects of seed longevity: exploring intra-species variation in eight Pisum sativum L. accessions

Maraeva Gianella Daniele Dondi Andreas Börner Anca Macovei Andrea Pagano Filippo Guzzon Alma Balestrazzi (2022, [Artículo])

Thermogravimetry CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CARBOHYDRATES PROLINE TOCOPHEROLS GENETICS PHYSIOLOGY PEAS SEEDS SUGARS DIFFERENTIAL SCANNING CALORIMETRY SEED LONGEVITY THERMOGRAVIMETRIC ANALYSIS

Leveraging the self-heating effect of ntc thermistor to detect its minimum coverage by a dispensed paste in the mass production process of temperature sensors

Saúl Alejandro Rodríguez Jiménez LEONOR ADRIANA CARDENAS ROBLEDO (2023, [Artículo])

This paper develops a device capable of confirming the minimum coverage area on a thermistor by a thermal paste dispensed and cured in the manufacturing process of Exhaust Gas Recirculation (EGR) temperature sensors to provide the required fixation in the presence of mechanical shock conditions. Such a device leverages the thermistor’s self-heating effect and the thermal conductivity of the paste to read the voltage drop from the sensor, which translates into paste coverage area. The methodology follows a synthesized procedure to develop equipment and processes, considering an early phase for concept confirmation to demonstrate the feasibility of the device development. In a later phase, the optimal parameters are calculated and set to the device for delivering the corresponding classification of the sensors during the test. Once launched in production, the device demonstrates high effectiveness in screening out the sensors with rejectable paste coverage area on the thermistor.

Self-heating effect Thermistor Paste Temperature sensor Heat dissipation INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS

Biodiversity conservation in an anthropized landscape: Trees, not patch size drive, bird community composition in a low-input agroecosystem

ERIC MELLINK BIJTEL (2017, [Artículo])

One of the most typical agro-ecosystems in the Llanos de Ojuelos, a semi-arid region of central Mexico, is that of fruit-production orchards of nopales (prickly pear cacti). This perennial habitat with complex vertical structure provides refuge and food for at least 112 species of birds throughout the year. Nopal orchards vary in their internal structure, size and shrub/ tree composition, yet these factors have unknown effects on the animals that use them. To further understand the conservation potential of this agro-ecosystem, we evaluated the effects of patch-size and the presence of trees on bird community composition, as well as several habitat variables, through an information-theoretical modelling approach. Community composition was obtained through a year of census transects in 12 orchards. The presence of trees in the orchards was the major driver of bird communities followed by seasonality; bird communities are independent of patch size, except for small orchard patches that benefit black-chin sparrows, which are considered a sensitive species. At least 55 species of six trophic guilds (insectivores, granivores, carnivores, nectivores, omnivores, and frugivores) used the orchards. Orchards provide adequate habitat and food resources for several sensitive species of resident and migratory sparrows. The attributes that make orchards important for birds: trees, shrubs, herb seeds, and open patches can be managed to maintain native biodiversity in highly anthropized regions with an urgent need to find convergence between production and biological conservation. © 2017 Mellink et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

agroecosystem, carnivore, chin, conservation biology, driver, frugivore, granivore, habitat, human, insectivore, landscape, nonhuman, omnivore, orchard, resident, seasonal variation, shrub, sparrow, theoretical model, agriculture, animal, biodiversit CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Teacher training in the state of Chihuahua: Between the health challenge and teacher resilience

Evangelina Cervantes Holguín Pavel Roel Gutiérrez Sandoval Cely Celene Ronquillo Chávez (2023, [Artículo, Artículo])

The article proposes to recover the response of the Teacher Training and Updating Institutions in the state of Chihuahua regarding the various challenges imposed by the Coronavirus Disease (COVID-19). The qualitative exercise analyzes the experience of 10 institutions based on the voice of their students, teachers, and principals regarding changes in academic, administrative, and organizational processes. It is concluded that the pandemic has affected each institution in different ways and with diverse intensity. Despite the achievements, the experience analyzed reveals the relative success of the using virtual platforms in the face of three basic conditions: connectivity, technological competencies, and socio-emotional skills of the teaching staff. It highlights the importance of implementing tutoring, resilience, or awareness actions of teachers and students' needs, feelings, and sufferings. It is opportune to recover the experiences of other institutions and to question especially students, thesis students and graduates.

Acceso a la educación Aprendizaje en línea Educación a distancia Formación de docentes Tecnología educacional HUMANIDADES Y CIENCIAS DE LA CONDUCTA HUMANIDADES Y CIENCIAS DE LA CONDUCTA Access to education online learning distance education teacher education educational technology

Calibrated multi-model ensemble seasonal prediction of Bangladesh summer monsoon rainfall

Nachiketa Acharya Carlo Montes Timothy Joseph Krupnik (2023, [Artículo])

Bangladesh summer monsoon rainfall (BSMR), typically from June through September (JJAS), represents the main source of water for multiple sectors. However, its high spatial and interannual variability makes the seasonal prediction of BSMR crucial for building resilience to natural disasters and for food security in a climate-risk-prone country. This study describes the development and implementation of an objective system for the seasonal forecasting of BSMR, recently adopted by the Bangladesh Meteorological Department (BMD). The approach is based on the use of a calibrated multi-model ensemble (CMME) of seven state-of-the-art general circulation models (GCMs) from the North American Multi-Model Ensemble project. The lead-1 (initial conditions of May for forecasting JJAS total rainfall) hindcasts (spanning 1982–2010) and forecasts (spanning 2011–2018) of seasonal total rainfall for the JJAS season from these seven GCMs were used. A canonical correlation analysis (CCA) regression is used to calibrate the raw GCMs outputs against observations, which are then combined with equal weight to generate final CMME predictions. Results show, compared to individual calibrated GCMs and uncalibrated MME, that the CCA-based calibration generates significant improvements over individual raw GCM in terms of the magnitude of systematic errors, Spearman's correlation coefficients, and generalised discrimination scores over most of Bangladesh areas, especially in the northern part of the country. Since October 2019, the BMD has been issuing real-time seasonal rainfall forecasts using this new forecast system.

Multi-Model Ensemble Seasonal Forecasting CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE SERVICES FORECASTING MONSOONS

Genetic effects of Rht-B1b and Rht-D1b dwarfing alleles on plant height and agronomic traits of bread wheat (Triticum aestivum L.) breeding lines

Zine El Abidine Fellahi Abderrahmane Hannachi Susanne Dreisigacker deepmala sehgal Hamenna Bouzerzour (2023, [Artículo])

Pleiotropic Effects Reduced Height Genes CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA PLANT HEIGHT TRITICUM AESTIVUM YIELD COMPONENTS ALLELES BREEDING LINES

Reconocimiento continuo de la Lengua de Señas Mexicana

Continuous recognition of Mexican Sign Language

Ricardo Fernando Morfín Chávez (2023, [Tesis de maestría])

La Lengua de Señas Mexicana (LSM) es la lengua utilizada por la comunidad Sorda en México, y, a menudo, subestimada y pasada por alto por la comunidad oyente, lo que resulta en la exclusión sistemática de las personas Sordas en diversos aspectos de la vida. Sin embargo, la tecnología puede desempeñar un papel fundamental en acercar a la comunidad Sorda con la comunidad oyente, promoviendo una mayor inclusión y comprensión entre ambas. El objetivo principal de este trabajo es diseñar, implementar y evaluar un sistema de reconocimiento continuo de señas estáticas en LSM mediante, visión por computadora y técnicas de aprendizaje máquina. Se establecieron objetivos específicos, que incluyen la generación de un conjunto de datos de señas estáticas, pertenecientes al alfabeto manual de la LSM, el diseño de un modelo de reconocimiento, y la evaluación del sistema, tanto en la modalidad aislada como en la continua. La metodología involucra dos evaluaciones distintas. La primera se enfoca en el reconocimiento de señas estáticas en el dominio aislado, para ello se capturaron datos de 20 participantes realizando movimientos de la mano en múltiples ángulos. Se evaluaron diversas técnicas de aprendizaje automático, destacando que el enfoque basado en Máquinas de Soporte Vectorial (SVM) obtuvo los mejores resultados (F1-Score promedio del 0.91). La segunda evaluación se concentra en el reconocimiento continuo de señas estáticas, con datos recopilados de seis participantes con diferentes niveles de competencia en LSM, logrando un rendimiento sólido con errores cercanos al 7 %. Además, se evaluó la viabilidad del sistema en aplicaciones de tiempo real, demostrando un excelente desempeño (velocidad promedio de procesamiento de 45 cuadros por segundo). A pesar de los logros alcanzados, es importante reconocer que este proyecto se centró en el reconocimiento continuo de señas estáticas en LSM. Queda pendiente, como un desafío interesante, la exploración del reconocimiento continuo de señas dinámicas en LSM para futuras investigaciones. Se considera esencial explorar enfoques orientados a la escalabilidad y aplicaciones en tiempo real en investigaciones posteriores.

This study focuses on the continuous recognition of static signs in Mexican Sign Language (Lengua de Señas Mexicana (LSM)), the language used by the Deaf community in Mexico. Despite its significance, LSM is often underestimated and overlooked, leading to the systematic exclusion of Deaf individuals in various aspects of life. The primary objective of this work is to design, implement, and evaluate a continuous static sign recognition system in LSM using computer vision and machine learning techniques. Specific goals were established, including the creation of a dataset of static signs belonging to the manual alphabet of LSM, the design of a recognition model, and the evaluation of the system in both isolated and continuous modes. The methodology involves two distinct evaluations. The first one focuses on the recognition of static signs in the isolated domain, for which data from 20 participants performing hand movements at various angles were collected. Various machine learning techniques were evaluated, with the Máquinas de Soporte Vectorial (SVM)-based approach achieving the best results (average F1-Score of 0.91). The second evaluation centers on the continuous recognition of static signs, using data collected from six participants with varying levels of competence in LSM, achieving robust performance with errors close to 7 %. Furthermore, the feasibility of the system in real-time applications was assessed, demonstrating excellent performance (average processing speed of 45 frames per second). Despite the achievements, it is important to recognize that this project focused on continuous recognition of static signs in LSM. It remains an interesting challenge to explore the continuous recognition of dynamic signs in LSM for future research. It is considered essential to explore scalability-oriented approaches and real-time applications in subsequent investigations.

Lengua de Señas Mexicana (LSM), visión por computadora, aprendizaje automático, alfabeto manual de la LSM, reconocimiento automático de señas estáticas, reconocimiento aislado de señas, reconocimiento continuo de señas, aplicacion Mexican Sign Language (LSM), computer vision, machine learning, LSM manual alpahbet, automatic recognition of static signs, isolated sign recognition, continuous sign recognition, real-time aplications INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES ENSEÑANZA CON AYUDA DE ORDENADOR ENSEÑANZA CON AYUDA DE ORDENADOR

Epistasis activation contributes substantially to heterosis in temperate by tropical maize hybrids

Liu Xiaogang Yunbi Xu (2022, [Artículo])

Genome-Wide Association Study Epistatic Effects Protein Interaction Multiple-Hybrid Population CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA HETEROSIS MAIZE PROTEINS HYBRIDS

The impact of 1.5 °C and 2.0 °C global warming on global maize production and trade

Wei Xiong Tariq Ali (2022, [Artículo])

Future Climate Scenario Data Yield Reduction Risk CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE GREENHOUSE EFFECT MAIZE MITIGATION SIMULATION ACCLIMATIZATION ADAPTATION GLOBAL WARMING

Genomic prediction of yield performance among single-cross maize hybrids using a partial diallel cross design

Junjie Fu XUECAI ZHANG (2023, [Artículo])

Genomic Prediction Prediction Model Genetic Effects Hybrid Performance CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE GENETICS HYBRIDS PERFORMANCE ASSESSMENT