Working memory training may help children with attention deficit hyperactivity disorder (ADHD), but robust evidence from systematic reviews is lacking. Children with poor Working memory ability struggle with academic and cognitive work compared to similar-aged peers without working memory deficits. Besides, working memory is correlated with inattention and disorganization in those with ADHD. The aim of this systematic review was to assess the effect of working memory training on symptoms and behaviors of children with ADHD. A search equation was proposed (ADHD OR attention deficit hyperactivity disorder AND working memory training), with twenty-four studies meeting the inclusion criteria in the Clarivate Analytics Web of Science Core Collection database. A bibliometric analysis was conducted to identify the importance of the research topic and a citation network was built to establish the lines of research. Finally, the citation network was exported to Gephi to visualize the research groups studying the topic. Findings suggest 3 lines of research: (a) Effects of working memory training on working memory, and academic performance in children with ADHD, (b) Effects of working memory training on executive functioning and child ADHD related symptoms, (c) Effects of working memory training on brain activity in child ADHD. Implications for clinical practice and school-based interventions are discussed

Este trabajo presenta una red neuronal artificial (RNA) para predecir el rendimiento académico estudiantil. Las RNAs emulan el funcionamiento fisiológico del cerebro humano, tienen la capacidad de procesar y abstraer información y son empleadas en investigaciones relacionadas con modelado predictivo debido a su capacidad para identificar relaciones no lineales entre variables. Se emplea una base de datos con información académica, demográfica, social e institucional de 395 estudiantes colombianos de media vocacional de la Institución Educativa Villa del Socorro, Medellín (Colombia). La base de datos es construida mediante la aplicación de encuestas e informes institucionales antes del inicio de la pandemia COVID-19. Los resultados muestran que la RNA desarrollada aquí clasifica adecuadamente el 73% de la muestra y que tiene un mejor desempeño en métricas (accuracy, recall, precision y F1-Score) que otras técnicas de aprendizaje supervisado. Se concluye que la predicción temprana del rendimiento académico permite formular estrategias didácticas y pedagógicas que hacen más eficiente el proceso de enseñanza y aprendizaje.

Anxiety affects men and women and have a negative impact on their lives. This paper presents two structural equation models (SEM) to evaluate the variables (physiological and cognitive), that most influenced the anxiety in men and women offenders of the law. Was used a representative sample of 60 offenders of the law (30 mens and 30 womens) of the Specialized Attention Center (SAC) “Carlos Lleras Restrepo” in Medellin, Colombia with diagnosis of Antisocial Personality Disorder (APD). The results of Bartlett's and KMO tests, indicated that the factorial analysis is adequate, all the constructs are statistically significant. The goodness-of-fit test indicated that the model fits well with the data. This paper concludes that, of the two constructs considered: physiological and cognition, in the men the construct that most influences the latent variable physiological are the “Palpitations or tachycardia”. The construct that most influences the latent variable cognitive is the “a feeling of instability”. In the women, the construct that most influences the latent variable physiological is the “dizziness or vertigo”. The construct that most influences the latent variable cognitive is “be afraid”.

Photovoltaic solar power referred to as solar power using photovoltaic cells, is a renewable energy source. The solar cells' electricity may be utilized to power buildings, neighborhoods, and even entire cities. A stable and low-maintenance technology, photovoltaic solar power is an appealing alternative for generating energy since it emits no greenhouse gases and has no moving components. This paper aimed to provide a photovoltaic solar power generation forecasting model developed with machine learning approaches and historical data. In conclusion, this type of predictive model enables the evaluation of additional non-traditional sources of renewable energy, in this case, photovoltaic solar power, which facilitates the planning process for the diversification of the energy matrix. Random Forests obtain the highest performance, with this knowledge power systems operators may forecast outcomes more precisely, this is the main contribution of this work.

Resumen. En Colombia, la papa es un producto básico cuyo precio depende principalmente de la oferta y la demanda locales. El sector papicultor colombiano presenta grandes incertidumbres sobre los benefi cios netos que se pueden generar en el corto, mediano y largo plazo, debido a la alta volatilidad de los precios del tubérculo. Este trabajo presenta un modelo de simulación de estrategias de inversión para papicultores colombianos desarrollado en la plataforma de simulación Vensim. El modelo consideró diferentes variables, entre las que se destacan el precio, el costo de la mano de obra, inversiones en nuevas tecnologías, entre otras. Con el desarrollo de este trabajo, se concluye que las utilidades de los productores son altamente sensibles a tres factores: precio, costos de producción e infl ación. Abstract. In Colombia, the potato is considered as a commodity whose price depends mainly on the local supply and demand. The Colombian potato's segment has large uncertainties on their benefi ts for either short, medium or long term. This is due to the high volatility of prices of the commodity. This paper shows a simulation model to guide investment strategies for different kinds of potato crops in Colombia, keeping in mind different variables such as price, cost and investment in new technologies. Hence, conclusions on potato crops' profi ts are then formulated as they are highly sensitive to three factors: price, production costs and infl ation.