Evaluación de la producción de biogás y el poder calorífico con la utilización de tres sustratos (estiércol de ganado bovino y porcino, y la pulpa de café)

Las áreas de bosque han sido taladas, debido al aprovechamiento del suelo para trabajar la tierra y así procurándose su alimentación y la construcción de vivienda. La población mundial ha aumentado aceleradamente aprovechando los recursos naturales. La leña ha sido la fuente de energía principal para la cocción de alimentos en los hogares. Como prácticas culturales, dentro de las que están, la agricultura y la ganadería, aprovecha el suelo, dando la tala de los bosques y la baja escala de reforestación están afectando esta fuente energética de la cual depende más de una tercera parte de la población rural de bajos ingresos del mundo. Los altos costos de los fertilizantes químicos hacen necesario desarrollar métodos más eficaces y de bajo costo para el reciclaje de los estiércoles bovinas y porcinas así como de los subproductos del manejo de la pulpa de café para la producción de biogás

Problem-Based Teaching through Video Podcasts for Coding and Cryptography

In this work we present the development and preliminary evaluation of several problem-based video podcasts addressed to students of the subject “Coding and Cryptography”. Specifically, this experiment has been carried out with the students of both the Bachelor’s degree in Mathematics and the Master’s degree of Mathematical Research and Modelling, Statistics and Computation, at the University of the Basque Country (UPV/EHU). Our results suggest that students found these complementary videos helpful for their learning process, indicating that this methodology could be appropriate for subjects treating complex concepts, such as those in the last years of degree or in master courses.The authors are supported by the University of the Basque Country, UPV/EHU (Convocatoria de Ayudas para Proyecto de Innovación Educativa, PIE-2018, Código 2), and also by the Basque Government grant IT974-16

Guiding the retraining of convolutional neural networks against adversarial inputs

Background: When using deep learning models, one of the most critical vulnerabilities is their exposure to adversarial inputs, which can cause wrong decisions (e.g., incorrect classification of an image) with minor perturbations. To address this vulnerability, it becomes necessary to retrain the affected model against adversarial inputs as part of the software testing process. In order to make this process energy efficient, data scientists need support on which are the best guidance metrics for reducing the adversarial inputs to create and use during testing, as well as optimal dataset configurations. Aim: We examined six guidance metrics for retraining deep learning models, specifically with convolutional neural network architecture, and three retraining configurations. Our goal is to improve the convolutional neural networks against the attack of adversarial inputs with regard to the accuracy, resource utilization and execution time from the point of view of a data scientist in the context of image classification. Method: We conducted an empirical study using five datasets for image classification. We explore: (a) the accuracy, resource utilization, and execution time of retraining convolutional neural networks with the guidance of six different guidance metrics (neuron coverage, likelihood-based surprise adequacy, distance-based surprise adequacy, DeepGini, softmax entropy and random), (b) the accuracy and resource utilization of retraining convolutional neural networks with three different configurations (one-step adversarial retraining, adversarial retraining and adversarial fine-tuning). Results: We reveal that adversarial retraining from original model weights, and by ordering with uncertainty metrics, gives the best model w.r.t. accuracy, resource utilization, and execution time. Conclusions: Although more studies are necessary, we recommend data scientists use the above configuration and metrics to deal with the vulnerability to adversarial inputs of deep learning models, as they can improve their models against adversarial inputs without using many inputs and without creating numerous adversarial inputs. We also show that dataset size has an important impact on the results.This work was supported by the GAISSA Spanish research project (ref. TED2021-130923B-I00; MCIN/AEI/10.13039/501100011033), the “UNAM-DGECI: Iniciación a la Investigación (verano otoño 2021)” scholarship provided by Universidad Nacional Autónoma de México (UNAM), the “Beatriz Galindo” Spanish Program BEAGAL18/00064, the Austrian Science Fund (FWF): I 4701-N and the project Continuous Testing in Production (ConTest) funded by the Austrian Research Promotion Agency (FFG): 888127.Peer ReviewedObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantObjectius de Desenvolupament Sostenible::13 - Acció per al ClimaPostprint (published version

Humoral response (IgG) of goats experimentally infected with Fasciola hepatica against cysteine proteinases of adult fluke

The use of cysteine proteinases from Fasciola hepatica adult flukes for the serodiagnosis of caprine fasciolosis by means of an indirect ELISA test was studied. Two proteolytic fractions from adult fluke homogenates, with apparent molecular weights of 28 and 34 kDa (P28 and P34 respectively), were characterised as cysteine proteinases using azocasein assays and gelatin gel analysis. Both P28 and P34 fractions were electroluted and used as antigens in two different indirect ELISA tests. Serum IgG levels against P28 and P34 in goats given an experimental primary infection with 200 metacercariae or in goats given two experimental infections with 200 metacercariae were determined and compared with those observed in an uninfected control group. ELISA tests using both cysteine proteases showed a rapid and consistent detection of specific IgG in all experimentally infected goats. The IgG response to P28 was the first to be detected as early as 2–3 weeks post-infection and remained elevated throughout the experiment. The response to P34 was detected later (4–6 wpi) and disappeared in some animals at 18 wpi, while flukes were still present in the bile ducts. No significant differences were observed between the anti-P28 and anti-P34 IgG responses between animals receiving a primary or a challenge infection. The results of our study, although preliminary, are promising since the P28 ELISA described here may be a reliable method for the immunodiagnosis of F. hepatica infection in goats

Variability of the temporary sequence of the kinetic chain of the handball throw

Se pretende analizar la variabilidad intraindividual de los lanzamientos en apoyo desde nueve metros y en presencia de un portero. La muestra se compone de cuatro lanzadores y siete porteros de la primera división española. A partir de las fuerzas de reacción se registró el movimiento de los porteros, y los lanzamientos mediante técnicas de vídeo 3D. La variabilidad en los patrones de movimiento engaña al portero y reducen el tiempo de movimiento. La cadena cinética utilizada responde a una secuencia temporal P-D, orientada a reducir el estrés excesivo en la articulación del hombro. La inercia del tronco permite reducir el tiempo de ejecución y elegir el instante de inicio de lanzamiento según las acciones del portero.The aim is to analyze the intraindividual variability of the throw in support realized from nine meters and in presence of a goalkeeper. Four throwers and seven goalkeepers from first Spanish division took part. From the forces of reaction proceeding from the platform, was registered the beginning of the movement of the goalkeeper, whereas the model of the throwing was using video 3D. The variability in the movement pattern faked the goalkeepers and reduced the time of movement. The kinetic chain is a temporary sequence P-D orientated to reducing the excessive stress in the joint of the shoulder. The inertia of the trunk reduced the time of execution and choose the instant of throwing depending on the goalkeeper

On Curriculum Greening, Environmental Training, Sensitization & Professional Development: a contemporary readings selection to know more

Una selección de lecturas contemporáneas para saber más sobre ambientalización curricular, formación ambiental, sensibilización y desarrollo profesional.Grupo FORCE (HUM-386). Departamento de Didáctica y Organización escolar de la Universidad de Granad

How Do We Create Experiences for Students That Connect with What They Care About?

The main aim of this work is to describe the process by which some students, participating in a teaching experiment, recreate with guidance material and personal attendance some advanced concepts at the doctoral level. More precisely, the students deal with concepts related to pure abstract algebra, beginning with an exploration of the well known mathematical game of the Hanoi Towers on the three rods.The authors are supported by the University of the Basque Country, UPV/EHU (Convocatoria de Ayudas para Proyecto de Innovación Educativa, PIE-2018, Código 2)

CALE: Learning by Example in Mathematics with Applets in Mathematical Computational Packages

In this work we present a methodology of “learning by example” assisted by computers in the study of mathematics. We propose the use of mathematical computational packages to program applets aimed to solve mathematical problems. Each time the student runs the applet, a new random instance of the problem is generated, and he is guided, step by step to solve it. The student can repeat the process as many times as necessary until his knowledge is consolidated, by taking a more active role in the process after the first repetitions of several instances.The authors are supported by the University of the Basque Country, UPV/EHU (PIE-2018, Código 2) and by the Basque Government, grant IT974-16

Sobre ambientalización curricular, formación ambiental, sensibilización y desarrollo profesional: una selección de lecturas contemporáneas para saber más

Sobre ambientalización curricular, formación ambiental, sensibilización y desarrollo profesional: una selección de lecturas contemporáneas para saber má

Detección de comunidades científicas en los tribunales de tesis en el área de marketing

En esta contribución se presenta un análisis de los tribunales de defensa de las tesis doctorales españolas leídas en el área de marketing, basado en redes bibliográficas y detección de comunidades. Los datos fueron descargados de la base de datos TESEO, seguido de un proceso de filtrado en el que se seleccionaron sólo aquellas tesis en las que la palabra “marketing” aparecía en el título, en el nombre del programa de doctorado o en los descriptores. Mediante técnicas bibliométricas, se construyó una red basada en la relación de co-ocurrencia de los miembros del tribunal de defensa. Finalmente, mediante algoritmos de detección de comunidades, se detectan los distintos grupos de miembros que suelen pertenecer de manera conjunta a los tribunales de defensa.In this contribution, an analysis of the marketing theses defended in Spain is carried out based on bibliographic networks and communities detection. Data was retrieved from TESEO database. Then, a filtering process was applied in order to get only theses data in which doctoral programs, thesis title or keywords match with terms related with Marketing. Then, we build a network with theses defense committee members from the data extracted and we apply fundamentals of social network analysis and community detection techniques to analyze data and uncover novel characteristics from network structure