Repositorio Universidad Europea del Atlántico
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The VegPlate for Sports: A Plant-Based Food Guide for Athletes
Get PDFBackground: Nutrition strategies improve physiological and biochemical adaptation to training, facilitate more intense workouts, promote faster recoveries after a workout in anticipation of the next, and help to prepare for a race and maintain the body’s hydration status. Although vegetarianism (i.e., lacto-ovo and veganism) has become increasingly popular in recent years, the number of vegetarian athletes is not known, and no specific recommendations have been made for vegetarian dietary planning in sports. Well-planned diets are mandatory to obtain the best performance, and the available literature reports that those excluding all types of flesh foods (meat, poultry, game, and seafood) neither find advantages nor suffer from disadvantages, compared to omnivorous diets, for strength, anaerobic, or aerobic exercise performance; additionally, some benefits can be derived for general health. Methods: We conceived the VegPlate for Sports, a vegetarian food guide (VFG) based on the already-validated VegPlate facilitating method, designed according to the Italian dietary reference intakes (DRIs). Results: The VegPlate for Sports is suitable for men and women who are active in sports and adhere to a vegetarian (i.e., lacto-ovo and vegan) diet, and provides weight-based, adequate dietary planning. Conclusions: The VegPlate for Sports represents a practical tool for nutrition professionals and gives the possibility to plan diets based on energy, carbohydrate (CHO), and protein (PRO) necessities, from 50 to 90 Kg body weight (BW)
La adopción en el Código Civil: evolución normativa, doctrinal y sociojurídica desde 1889 hasta la actualidad
No full textEl objeto de esta monografía es el estudio diacrónico y pormenorizado de la adopción, tomando como referencia el texto originario del Código Civil de 1889 y el análisis doctrinal que hicieron los principales civilistas y jurisconsultos de la época. Con una visión práctica y una fuerte base teórica, tanto en el ámbito del Derecho civil como de la Sociología jurídica, este libro pretende llenar un vacío derivado de la falta de un análisis específico, compilatorio, doctrinal y monográfico, respecto a como ha ido evolucionando la adopción en cada una de las reformas que se han sucedido (dieciséis) desde el año 1889 hasta la actualidad. Asimismo y con un enorme rigor académico, Manuel Baelo Álvarez escudriña la exégesis de cada uno de los artículos del vigente Código Civil, su normatividad, el significado y la utilidad sociojurídica de la adopción, no solo en España, sino también en aquellos territorios en los que nuestro Código Civil estuvo presente, como Filipinas, Puerto Rico, Cuba y el Golfo de Guinea (Guinea Ecuatorial)
Resilience Optimization of Post-Quantum Cryptography Key Encapsulation Algorithms
Get PDFRecent developments in quantum computing have shed light on the shortcomings of the conventional public cryptosystem. Even while Shor’s algorithm cannot yet be implemented on quantum computers, it indicates that asymmetric key encryption will not be practicable or secure in the near future. The National Institute of Standards and Technology (NIST) has started looking for a post-quantum encryption algorithm that is resistant to the development of future quantum computers as a response to this security concern. The current focus is on standardizing asymmetric cryptography that should be impenetrable by a quantum computer. This has become increasingly important in recent years. Currently, the process of standardizing asymmetric cryptography is coming very close to being finished. This study evaluated the performance of two post-quantum cryptography (PQC) algorithms, both of which were selected as NIST fourth-round finalists. The research assessed the key generation, encapsulation, and decapsulation operations, providing insights into their efficiency and suitability for real-world applications. Further research and standardization efforts are required to enable secure and efficient post-quantum encryption. When selecting appropriate post-quantum encryption algorithms for specific applications, factors such as security levels, performance requirements, key sizes, and platform compatibility should be taken into account. This paper provides helpful insight for post-quantum cryptography researchers and practitioners, assisting in the decision-making process for selecting appropriate algorithms to protect confidential data in the age of quantum computing
Implementação da vacinação contra covid-19 no Brasil: uma análise da comunicação de saúde através de notícias no portal do Ministério da Saúde
No full textA pandemia da Covid-19 trouxe consigo um intenso debate sobre a vacinação contra a doença, bem como sobre as informações oficiais relacionadas a ela. O Ministério da Saúde do Brasil tem sido o principal responsável por fornecer informações confiáveis e precisas sobre a vacinação. O objetivo desta pesquisa é analisar a comunicação de saúde do Ministério da Saúde do Brasil a respeito da vacinação contra a Covid-19. Trata-se de uma pesquisa qualitativa com método discursivo de análise de conteúdo das informações de vacinação contra a covid-19 no portal do ministério da saúde. A amostra deste estudo são matérias do portal oficial do ministério da saúde (gov.br/saude) selecionadas usando os critérios de título como: “vacinação covid-19”; e delimitando o tempo de 15 a 30 de novembro de 2022, por ser demarcado um período de nova onda da covid no Brasil e o alerta da OMS de “tríplice ameaça”. A comunicação informativa em saúde é essencial para uma boa prática e aceitação da vacinação por parte da população, pois fornece ao leitor informações úteis e relevantes sobre a campanha de vacinação contra a covid-19 e grupos de risco. Os resultados mostraram que a vacina da CoronaVac foi a disponibilizada para as crianças. As categorizações foram: tipo de vacina, importância, público-alvo e transparência. Houveram algumas limitações quanto ao nível de detalhamento e atualizações nessas matérias. Contudo, é possível obter um melhor entendimento das estratégias de comunicação do governo brasileiro para a campanha de vacinação através de análise das notícias veiculadas no portal do Ministério da Saúde. A estratégia usada no portal é eficaz e promove a cultura de vacinação contra o covid-19. O portal oferece informações relevantes e confiáveis sobre a vacinação, incluindo dados científicos para auxiliar nas decisões sobre a vacinação
Worry, rumination and negative metacognitive beliefs as moderators of outcomes of Transdiagnostic group cognitive-behavioural therapy in emotional disorders
Get PDFBackground
Despite the relevance of cognitive processes such as rumination, worry, negative metacognitive beliefs in emotional disorders, the existing literature about how these cognitive processes moderate the effect of treatment in treatment outcomes is limited. The aim of the present study was to explore the potential moderator effect of baseline cognitive processes—worry, rumination and negative metacognitive beliefs—on the relationship between treatment allocation (transdiagnostic cognitive-behavioural therapy —TD-CBT plus treatment as usual—TAU vs. TAU alone) and treatment outcomes (anxiety and depressive symptoms, quality of life [QoL], and functioning) in primary care patients with emotional disorders.
Methods
A total of 631 participants completed scales to evaluate worry, rumination, negative metacognitive beliefs, QoL, functioning, and anxiety and depressive symptoms.
Results
Worry and rumination acted as moderators on the effect of treatment for anxiety (b = −1.25, p = .003; b = −0.98, p = .048 respectively) and depressive symptoms (b = −1.21, p = .017; b = −1.34, p = .024 respectively). Individuals with higher baseline levels of worry and rumination obtained a greater reduction in emotional symptoms from the addition TD-CBT to TAU. Negative metacognitive beliefs were not a significant moderator of any treatment outcome.
Limitations
The study assesses cognitive processes over a relatively short period of time and uses self-reported instruments. In addition, it only includes individuals with mild or moderate anxiety or depressive disorders, which limits generalization to other populations.
Conclusions
These results underscore the generalization of the TD-CBT to individuals with emotional disorders in primary care with different cognitive profiles, especially those with high levels of worry and rumination
FMDNet: An Efficient System for Face Mask Detection Based on Lightweight Model during COVID-19 Pandemic in Public Areas
Get PDFA new artificial intelligence-based approach is proposed by developing a deep learning (DL) model for identifying the people who violate the face mask protocol in public places. To achieve this goal, a private dataset was created, including different face images with and without masks. The proposed model was trained to detect face masks from real-time surveillance videos. The proposed face mask detection (FMDNet) model achieved a promising detection of 99.0% in terms of accuracy for identifying violations (no face mask) in public places. The model presented a better detection capability compared to other recent DL models such as FSA-Net, MobileNet V2, and ResNet by 24.03%, 5.0%, and 24.10%, respectively. Meanwhile, the model is lightweight and had a confidence score of 99.0% in a resource-constrained environment. The model can perform the detection task in real-time environments at 41.72 frames per second (FPS). Thus, the developed model can be applicable and useful for governments to maintain the rules of the SOP protocol
A Systematic Review of Disaster Management Systems: Approaches, Challenges, and Future Directions
No full textDisaster management is a critical area that requires efficient methods and techniques to address various challenges. This comprehensive assessment offers an in-depth overview of disaster management systems, methods, obstacles, and potential future paths. Specifically, it focuses on flood control, a significant and recurrent category of natural disasters. The analysis begins by exploring various types of natural catastrophes, including earthquakes, wildfires, and floods. It then delves into the different domains that collectively contribute to effective flood management. These domains encompass cutting-edge technologies such as big data analysis and cloud computing, providing scalable and reliable infrastructure for data storage, processing, and analysis. The study investigates the potential of the Internet of Things and sensor networks to gather real-time data from flood-prone areas, enhancing situational awareness and enabling prompt actions. Model-driven engineering is examined for its utility in developing and modeling flood scenarios, aiding in preparation and response planning. This study includes the Google Earth engine (GEE) and examines previous studies involving GEE. Moreover, we discuss remote sensing; remote sensing is undoubtedly a valuable tool for disaster management, and offers geographical data in various situations. We explore the application of Geographical Information System (GIS) and Spatial Data Management for visualizing and analyzing spatial data and facilitating informed decision-making and resource allocation during floods. In the final section, the focus shifts to the utilization of machine learning and data analytics in flood management. These methodologies offer predictive models and data-driven insights, enhancing early warning systems, risk assessment, and mitigation strategies. Through this in-depth analysis, the significance of incorporating these spheres into flood control procedures is highlighted, with the aim of improving disaster management techniques and enhancing resilience in flood-prone regions. The paper addresses existing challenges and provides future research directions, ultimately striving for a clearer and more coherent representation of disaster management techniques
Diferencia del perfil de los estados de ánimo en jóvenes escolares que practican deporte extraescolar federado vs no federados (Difference in the profile of moods in young schoolchildren who practice federated extracurricular sports vs. schoolchildren)
No full textEl objetivo del presente estudio es comparar el perfil de los estados de ánimo (EA) en jóvenes escolares que practican diferentes deportes extraescolares de manera federada respecto a escolares de Educación Primaria y Secundaria que no están federados. Seleccionándose un total de 329 sujetos (141 deportistas y 188 escolares no practicantes). Los EA se evaluaron mediante el cuestionario Profile of Moods States (POMS). La comparación se realizó en base al deporte practicado y en función de si eran deportistas federados o no federados. Los resultados muestran valores más elevados en la escala del vigor, así como diferencias significativas en las escalas depresión y fatiga entre los deportistas. Además, se observan diferencias entre no federados escolares para la depresión, hostilidad y tensión. Se concluye que los deportistas muestran valores que se asocian con el denominado perfil iceberg
Forecasting of Post-Graduate Students’ Late Dropout Based on the Optimal Probability Threshold Adjustment Technique for Imbalanced Data
Get PDFThe purpose of this research article was to contrast the benefits of the optimal probability threshold adjustment technique with other imbalanced data processing techniques, in its application to the prediction of post-graduate students’ late dropout from distance learning courses in two universities in the Ibero-American space. In this context, the optimization of the Logistic Regression, Random Forest, and Neural Network classifiers, together with different techniques, attributes, and algorithms (Hyperparameters, SMOTE, SMOTE_SVM, and ADASYN) resulted in a set of metrics for decision-making, prioritizing the reduction of false negatives. The best model was the Neural Network model in combination with SMOTE_SVM, obtaining a recall index of 0.75 and an f1-Score of 0.60. Likewise, the robustness of the Random Forest classifier for imbalanced data was demonstrated by achieving, with an optimal threshold of 0.427, very similar metrics to those obtained by the consensus of the three best models found. This demonstrates that, for Random Forest, the optimal prediction probability threshold is an excellent alternative to resampling techniques with different optimal thresholds. Finally, it is hoped that this research paper will contribute to boost the application of this simple but powerful technique, which is highly underrated with respect to data resampling techniques for imbalanced data
SARSMutOnto: An Ontology for SARS-CoV-2 Lineages and Mutations
Get PDFMutations allow viruses to continuously evolve by changing their genetic code to adapt to the hosts they infect. It is an adaptive and evolutionary mechanism that helps viruses acquire characteristics favoring their survival and propagation. The COVID-19 pandemic declared by the WHO in March 2020 is caused by the SARS-CoV-2 virus. The non-stop adaptive mutations of this virus and the emergence of several variants over time with characteristics favoring their spread constitute one of the biggest obstacles that researchers face in controlling this pandemic. Understanding the mutation mechanism allows for the adoption of anticipatory measures and the proposal of strategies to control its propagation. In this study, we focus on the mutations of this virus, and we propose the SARSMutOnto ontology to model SARS-CoV-2 mutations reported by Pango researchers. A detailed description is given for each mutation. The genes where the mutations occur and the genomic structure of this virus are also included. The sub-lineages and the recombinant sub-lineages resulting from these mutations are additionally represented while maintaining their hierarchy. We developed a Python-based tool to automatically generate this ontology from various published Pango source files. At the end of this paper, we provide some examples of SPARQL queries that can be used to exploit this ontology. SARSMutOnto might become a ‘wet bench’ machine learning tool for predicting likely future mutations based on previous mutations