Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

Introducción: La evaluación de la competencia laboral promoción de la salud ante la COVID-19 que demuestran los estudiantes Enfermería durante la educación en el trabajo, constituye una prioridad actual del sistema de salud en el Ecuador.Objetivo: Evaluar la competencia laboral promoción de la salud ante la COVID-19 que demuestran los estudiantes de Enfermería durante la educación en el trabajo, que contribuya a la mejora de sus desempeños como Enfermeros (as).Métodos: Se realizó una investigación cuantitativa de tipo pre-experimental, a partir de una muestra de 100 estudiantes de Enfermería de la Universidad Técnica de Babahoyo en el Ecuador escogidos por selección aleatoria, asumiendo el 15% del volumen de la población. Se emplearon los métodos de la observación y los exámenes de actuación de los estudiantes durante la educación en el trabajo y el enfoque de sistema.Resultados: Se aportan los principales logros y deficiencias que demuestran los estudiantes de Enfermería en la promoción de la salud ante la COVID-19 durante la educación en el trabajo. Se hace la propuesta de la competencia de promoción de la salud ante la COVID-19 y la metodología a seguir para su evaluación desde la integración entre la academia universitaria con la educación en el trabajo.Conclusiones: La competencia promoción de la salud ante la COVID-19 debe ser una competencia genérica que caracteriza al perfil del egresado de la carrera de Enfermería, debe ser evaluada en todos los años de estudios, a partir de la integración de la docencia universitaria con la educación en el trabajo, que permita la toma de decisiones para la mejora de los desempeños de los estudiantes de Enfermería en el área de promoción de la salud.Palabras clave: Competencia laboral, evaluación, promoción, COVID-19

Introducción: La lactancia materna es un acto fisiológico e instintivo. En Cuba, debe ser un elemento de extraordinaria importancia para mantener la tendencia descendente de la mortalidad y la morbilidad en el niño menor de cinco años.Objetivo: Elevar el nivel de conocimientos sobre lactancia materna exclusiva en las embarazadas pertenecientes a los consultorios 1 al 5 del policlínico Docente Frank País en el período comprendido de mayo a diciembre 2021.Método: Se realizó un estudio cuasi experimental de intervención educativa en 38 gestantes escogidas al azar a través de un muestreo aleatorio simple. Se aplicó un cuestionario para diagnosticar el conocimiento antes y después de la intervención educativa. Se aplicó un cuestionario para diagnosticar el conocimiento antes y después de la intervención educativa.Se utilizó como prueba estadística la prueba de suma de rangos con signos de Wilcoxon, para evaluar la significación del cambio, antes y después de la intervención y la prueba exacta de Fisher Irwin para determinar la posible relación entre el conocimiento de las madres sobre lactancia materna y el mantenimiento exclusivo de esta hasta los seis meses.Resultados: El rango de edad de mayor incidencia fue de 20 a 24 años con 12, para un 31,6%. El nivel escolar que predominó fue el preuniversitario, con 22 pacientes para un 57,9%. En referencia al estado civil predominó la unión consensual con 28 para 73,7%. Con respecto al nivel de conocimiento por temas fue el de las posiciones adecuadas para lactar el de mayor resultado con 38, para 100%, y en el nivel de conocimiento general predomina el nivel alto con 29, para 76,3% del total al final de la intervención educativa.Conclusiones: Con la aplicación de la estrategia educativa se logró elevar el nivel de conocimientos generales sobre la lactancia materna.Palabras clave: lactancia materna, exclusiva, embarazadas

Introducción: La hemorragia por várices esofágicas constituye la principal complicación de la hipertensión portal, siendo la causa más prevalente de muerte o de trasplante hepático en los pacientes con cirrosis hepática.Objetivo: Determinar la utilidad del tratamiento endoscópico con bandas elásticas de várices esofágicas en pacientes con cirrosis hepática.Método: Se realizó un estudio cuasiexperimental en su variante antes y después (pretest-postest), sin grupo control, en pacientes con cirrosis hepática y várices esofágicas, en el período de octubre -2017 a mayo - 2021 en el Hospital “Lucía Íñiguez Landín” de la provincia Holguín.El universo estuvo constituido por 41 pacientes con diagnóstico endoscópico de várices esofágicas, atendidos de forma electiva en la consulta externa especializada en cirrosis hepática. La muestra se conformó con 30 pacientes que cumplieron con los criterios de inclusión y exclusión. Fueron empleados métodos teóricos y empíricos para el análisis, interpretación y procesamiento de los datos obtenidos.Resultados: La hepatitis por virus C fue la principal causa de cirrosis hepática con hipertensión portal. Los pacientes con Child-Pugh C necesitaron mayor número de sesiones de tratamiento y de bandas elásticas.Conclusiones: El tratamiento endoscópico de várices esofágicas causadas por hipertensión portal con bandas elásticas resultó efectivo en todos los pacientes, puesto que disminuyó la frecuencia y severidad de las hemorragias digestivas.El tratamiento utilizado disminuyó en todos los pacientes el grado de las várices esofágicas, aunque en diferente medida con respecto a la severidad.Palabras clave: cirrosis hepática, varices esofágicas, bandas elásticas

Due to their asynchronous interactions, testing reactive systems is a  laborious activity present in any software development project. In this setting, the finite memory formalism of Labeled Transition Systems has been used to generate test suites that can be applied to check ioco conformance of implementations to a given specification. In this work we turn to a more complex scenario where a stronger formalism is considered, the Visibly Pushdown Labeled Transition System (VPTS), which allows access to a potentially infinite pushdown memory. We study an extension of the ioco conformance relation to VPTS models and develop polynomial time algorithms to verify conformance for VPTS models in a white-box testing scenario.

Blockchain technology supports building transparent and decentralized systems in which the executed transactions can be easily traceable. Suppose one such system is intended to manage and process personal data. In that case, complementary mechanisms are required that make it possible for the system to comply, for instance, with data protection regulations. This work studies the integration of off-chain capabilities in blockchain-based solutions. In particular, we have focused on mechanisms that support safely moving data or computational operations outside the core blockchain network. We have carried out a thorough analysis of the European data protection regulation and discussed the weaknesses and strengths regarding the security and privacy requirements established by that regulation of solutions built using traditional blockchain technology.As a direct consequence of this study, we have conceived, and present in this paper, a system architecture for the design of privacy-aware solutions that use that kind of technology and put forward a systematic approach for performing a security and privacy threat analysis of one such solution. We illustrate the use of the proposed methodological tools, presenting and discussing the high-level design and security and privacy assessment of a system that provides services to handle, store, and validate digital academic certificates.

Public health problems such as dengue fever need accurate forecasts so governments can take effective preventive measures. Deep learning (DL) and machine learning have become increasingly popular as the volume of data increases continuously. Nevertheless, performing accurate predictions in areas with fewer cases can be challenging. When we apply DL models using long short-term memory (LSTM) in different cities considering weekly dengue incidence and climate, some models may present heterogeneous behaviours and poor accuracy because of the need for more data. To mitigate this problem, clustering analysis across time series is performed based on scores to measure the clustering quality in 217 Paraguayan cities. First, we compare the raw and feature-based clustering techniques considering several metrics.Our results indicate that hierarchical clustering combined with Spearman correlation is the most appropriate approach. Finally, several LSTM models built using clustering results were compared. The main contribution of this work is a technique that can improve the performance of time series models that combine information from similar time series and weather data.

Blockchain is one of the most recent disrupting technologies. Since Bitcoin emerged as its initial application, many blockchain projects arose offering different features for general and domain specific scenarios. In turn, Blockchain platforms were designed as isolated environments where interoperability was not a native feature. During the last years,academic and industry efforts worked to improve interoperability between blockchain platforms and provided many solutions to solve this problem. However, there is not consensus in the literature on how to classify certain type of solutions and the classification of some of them is not straightforward, which hinders the understanding of the work in the area. In order to organize existing work, this paper provides a feature-based classification framework based on fourteen key interoperability features, that enabled the classification of sixty-two academic papers in three categories and six subcategories. The results show that nowadays research is focused on public interoperability, while private and public-to-private interoperability are still on their first steps. Based on these results, this work also discusses nowadays blockchain interoperability landscape, identifies challenges, and suggests future research directions.

Wildfires are a problem of great interest in the world because of the damage they cause every year to forest, wild fauna and flora, an also threatening human lives, among others. There are some computational models for numerical simulations to address this phenomena, and a few of them have an open-source implementation. The goal of this work is to extend a CPU Python’s implementation of wildfire open-source framework developed in NumPy, to a GPU improved version using CuPy. The algorithm used is based on a numerical discretization of a wildfire spreading mathematical model described by a system of partial differential equations. Computational and mathematical components, numerical simulations and applications are described in details in the document. In addition, this work includes includes a brief performance comparison between both implementations, pointing out that we can achieve good execution times using the CuPy GPU implementation without spending enough programming effort.

Physical limitations in processor design have made computer industry shift from improving the speed of a single processor to increasing the number of processing core units. But the design of software to exploit parallel processing power in a correct and cost-effective way is a challenging task requiring a high degree of expertise. In 2017, Pérez and Yovineproposed a platform-agnostic parallel programming pattern called PCR, that eases writing parallel code. In this thesis, we formalize the PCR pattern in terms of TLA+ —a formal specification language for concurrent systems that is being used at places suchas Intel, Amazon and Microsoft. We seek to provide a formal framework mainly for (1) expressing high level PCR designs and prove their functional correctness in the sense that their parallel computation computes a given mathematical function, and (2) being able to formally relate different PCR designs. In this way, we contribute to the state of the art in formal verification of parallel programs by leveraging TLA+-related tools to proving properties about high-level PCR-based algorithms such as their functional correctness and refinement.

The problem of conceptual comparison of names plays an important role in the field of natural language processing. In this task, the goal is to choose, among a set of names, which one refers to the same concept or object as a given input name. In this paper, we propose an algorithm for comparing names of products and services in Portuguese that takes account of the semantic information contained in the names. The semantic similarity between two names is calculated using information from Onto.PT, the largest public lexical ontology for the Portuguese language. Experiments were conducted on a dataset composed of 5,000 pairs of names of products and services in Portuguese. Our experimental results show that the algorithm based on Onto.PT is more effective than other well-known algorithms for name comparison, producing the highest recall and precision. Moreover, results also provide interesting insights into the advantages and disadvantages of using Onto.PT for assessing the semantic similarity of names and other kinds of short texts.