Arboles de Decisión como Metodología para Determinar el Rendimiento Académico en Educación Superior / Decision Trees as a Methodology to Determine Academic Performance in Higher Education / Árvores de Decisão como Metodologia para Determinar o Desempenho Acadêmico no Ensino Superior

Resumen Introducción. En este artículo se presentan los resultados finales de la investigación Árboles de decisión como metodología para determinar el rendimiento académico en educación superior. Objetivo. Explicar el rendimiento académico de los alumnos que cursan asignaturas relacionadas con la programación en una institución de nivel superior ubicada en la zona urbana de Pánuco, Veracruz, México. El rendimiento académico presenta una situación que no solamente preocupa a las instituciones educativas, sino también a los estudiantes, padres de familia, profesores y directores. Puede mencionarse que este presenta también una situación mundial y que es investigado en diferentes áreas de conocimiento. Materiales y Métodos. Se aplicó un cuestionario a 341 estudiantes repartidos en el segundo, cuarto y sexto semestre. Se utilizaron dos técnicas de modelado estadístico: árbol de decisión y regresión lineal múltiple, para definir qué variables independientes están asociadas al rendimiento académico. Resultados. Se ubica que las variables de aprendizaje en el aula y las tutorías externas están relacionadas con la variable de rendimiento académico y que el 48.1 % de los alumnos necesitan algún apoyo académico o capacitación externa para el reforzamiento de la programación. Conclusiones. Se recomienda implementar estrategias de mejora para reducir la sobrecarga de trabajo de los alumnos. También realizar una sensibilización antes de aplicar la encuesta y que los cuestionarios sean aplicados en fechas de exámenes ya que los alumnos se encuentran en niveles altos de estrés. En trabajos posteriores se tiene contemplado poder evaluar los efectos sobre el rendimiento académico, económico, social y cultural.

Abstract Introduction. This article presents the results of the Decision Trees research as a methodology to determine academic performance in higher education. Objective. Explain the academic performance of students taking subjects related to programming at a higher-level institution located in the urban area of Pánuco, Veracruz, Mexico. Academic performance presents a situation that not only concerns educational institutions, but also students, parents, teachers, and principals. It can be mentioned that this also presents a world situation and that it is investigated in different areas of knowledge. Materials and methods. A questionnaire was applied to 341 students distributed in the second, fourth and sixth semester. Two statistical modeling techniques were used: decision tree and multiple linear regression, to define which independent variables are associated with academic performance. Results. It is located that the learning variables in the classroom and the external tutorials are related to the academic performance variable and that 48.1 % of the students need some academic support or external training to reinforce the programming. Conclusions. It is recommended to implement improvement strategies to reduce the work overload of the students. Also make an awareness before applying the survey and that the questionnaires are applied on test dates since the students are at high levels of stress. Future research could evaluate the effect on academic, economic and cultural performance.

Resumo Introdução. Este artigo apresenta os resultados da pesquisa Árvores de Decisão como uma metodologia para determinar o desempenho acadêmico no ensino superior. Objetivo. Explique o desempenho acadêmico dos estudantes que cursam matérias relacionadas à programação em uma instituição de nível superior localizada na área urbana de Pánuco, Veracruz, México. O desempenho acadêmico apresenta uma situação que diz respeito não apenas às instituições de ensino, mas também a estudantes, pais, professores e diretores. Pode-se mencionar que isso também apresenta uma situação mundial e é investigada em diferentes áreas do conhecimento. Materiais e métodos. Foi aplicado um questionário a 341 alunos distribuídos no segundo, quarto e sexto semestre. Foram utilizadas duas técnicas de modelagem estatística: árvore de decisão e regressão linear múltipla, para definir quais variáveis independentes estão associadas ao desempenho acadêmico. Resultados. Fica localizado que as variáveis de aprendizagem em sala de aula e os tutoriais externos estão relacionados à variável desempenho acadêmico e que 48,1 % dos alunos precisam de algum apoio acadêmico ou treinamento externo para reforçar a programação. Conclusões. Recomenda-se implementar estratégias de melhoria para reduzir a sobrecarga de trabalho dos alunos. Lembre-se também antes de aplicar a pesquisa e que os questionários sejam aplicados nas datas dos testes, uma vez que os alunos estão em altos níveis de estresse.

Analysis of a dose-response assay in Scaptotrigona bipunctatabees, Lepeletier, 1836 (Hymenoptera: Apidae) using the logistic regression model under the Bayesian approach

This paper shows the results of a dose-response study in Scaptotrigona bipunctatabees, Lepeletier, 1836 (Hymenoptera: Apidae) exposed to the insecticide Fastac Duo. The aim was to evaluate the lethal concentration that causes the death of 50% of bees (LC50) and investigate the odd of mortality after exposure to different concentrations, using the logistic regression model under the Bayesian approach. In this approach, it is possible to incorporate a prior information and gives more accurate inferential results. Three independent dose-response experiments were analyzed, dissimilar in their lead time according to guidelines from the Organisation for Economic Co-operation and Development (OECD), in which each assay contained four replicates at the concentration levels investigated, including control. Observing exposure to the agrochemical, it was identified that the higher the concentration, the greater the odd of mortality. Regarding the estimated lethal concentrations for each experiment, the following values were found, 0.03 g a.i. L-1, for 24hours, 0.04 g a.i. L-1, for 48hoursand 0.06 g a.i. L-1for 72hours, showing that in experiments with longer exposure times there was an increase in LC50. Concluding, the study showed an alternative approach to classical methods for dose-response studies in Scaptotrigona bipunctatabees exposed to the insecticide Fastac Duo.

Improvement of antimicrobial metabolites by Saccharothrix flava VSM-3 using full factorial design and chemotype analysis

Bioactive metabolite production by marine Saccharothrix flava VSM-3was modeled by response surface methodology(RSM) statistical optimization, and kinetic parameter estimation was executed using unstructured models to depict theimportance of growth-associated metabolite production. RSM-based optimization of the variables and their interactionswas analyzed where the modeled data and experimental data are in concurrence and better responses were yieldedin terms of inhibition zones for active metabolite with good regression coefficients. The regression model developedthe significance of five variables and their influence on the bioactive metabolite production and its effect against theresponses. Logistic, Luedeking–Piret equations were used for batch fermentation to produce bioactive metabolites byS. flava VSM-3, where the anticipated parameter data followed experimental data. Chemotype (using ethyl acetateextract) analysis of actinobacterial isolate S. flava was elucidated for the first time by liquid chromatography quadrupoletime-of-flight mass spectrometry (LC-QTOF-MS) analysis. The main compounds identified in the positive ion modewere 7-Deazaadenosine, 5-Hydroxy-9-Methylstreptimidone, Amiclenomycin, Dihydroabikoviromycin, EpopromycinA, OAP Silane 55 and MKN-003B. In the present study, maritime silt specimen of Bay of Bengal comprising S. flavaVSM-3 recorded prominent broad-spectrum activity against various plant pathogens and LC-QTOF-MS data alsosupported VSM-3 was the most active strain. This study also reveals that under-explored Bay of Bengal of northcoastal Andhra Pradesh should be continuously explored for extracting bioactive compounds from diverse strains.

Power-law Behavior of the Alternative Splicing of Exons in Human Transcriptome

Aims: To establish the common rules of exon combinatorics during RNA splicing. Study Design: Inferring a plausible statistical model of exon combinatorics from the annotated models of human genes during RNA splicing. Place and Duration of Study: Department of Genetics (Belarusian State University), Proteome and Genome Research Unit (Luxembourg Institute of Health), Department of Genetics (Lomonosov Moscow State University) and Moscow Center of Experimental Embryology and Reproductive Biotechnologies, between January 2017 and July 2019. Methodology: We used human mRNA and EST sequences from GenBank (1093522 unique records in total) and linear models of the human genes from Ensembl (58051 genes), AceView (72384 genes), ECgene (57172 genes), NCBI RefSeq (54262 genes), UCSC Genome Browser (58037 genes) and VEGA (54950 genes) to calculate a combinatorial index of human exons. We inferred the most plausible statistical model describing the distribution of combinatorial index of human exons using Clauset’s mathematical formalism. Predictors of the combinatorial index values and functional outcomes of the predefined behavior of exons during splicing were also determined. Results: Power-law is the most plausible statistical model describing the combinatorics of exons during RNA splicing. The combinatorial index of human exons is defined by more than 90% by the 138 features that have different importance. The most important of these features are the abundance of exon in transcripts, the strength of splice sites, the rank of exon in transcripts and the type of exon. Analysis of the marginal effects shows that different values of the same feature have unequal influence on the combinatorial index of human exons. Power-law behavior of exons during RNA splicing pre-determines structural diversity of transcripts, low sensitivity of splicing process to random perturbations and its high vulnerability to manipulation with highly combinative exons. Conclusion: Exons widely involved in alternative splicing are a part of the common power-law phenomenon in human cells. The power-law behavior of exons during RNA splicing gives the unique characteristics to human genes.

Análise dos fatores associados aos acidentes de trânsito envolvendo ciclistas atendidos nas capitais brasileiras / Analysis of factors associated with traffic accidents of cyclists attended in Brazilian state capitals

Resumo O Brasil possui a sexta maior frota de bicicletas do mundo, sendo esta o veículo de transporte individual mais utilizado no país. Porém, poucos estudos abordam a temática envolvendo os acidentes com ciclistas, bem como os fatores que colaboram ou evitam essa ocorrência. Utilizou-se amostragem complexa e posterior análise de dados por regressão logística multivariada e cálculo das respectivas razões de chance para estudar o Inquérito de delineamento transversal (VIVA), o qual compõe o Sistema de Vigilância de Violências e Acidentes do Ministério da Saúde. As razões de chance apontaram maiores chances de ocorrência de acidentes envolvendo ciclistas em indivíduos do sexo masculino, de menor escolaridade e que residem em área urbana e periurbana. Pessoas que não estavam utilizando a bicicleta para ir ao trabalho apresentaram maior chance de acidente. O perfil encontrado no presente estudo corrobora os achados de outros estudos, os quais consideram que a coexistência de ciclistas com os demais meios de transporte, no mesmo espaço urbano, acarreta em maior chance de acidentes. A construção de espaços exclusivos à circulação de bicicletas e a realização de campanhas educativas são preconizadas.

Abstract Introduction: Brazil has the sixth largest bicycles fleet in the world and bicycle is the most used individual transport vehicle in the country. Few studies address the issue of cyclists' accidents and factors that contribute to or prevent this event. Methodology: VIVA is a cross-sectional survey and is part of the Violence and Accidents Surveillance System, Brazilian Ministry of Health. We used complex sampling and subsequent data review through multivariate logistic regression and calculation of the respective odds ratios. Results: Odds ratios showed greater likelihood of cyclists' accidents in males, people with less schooling and living in urban and periurban areas. People who were not using the bike to go to work were more likely to suffer an accident. Discussion: The profile found in this study corroborates findings of other studies. They claim that the coexistence of cyclists and other means of transportation in the same urban space increases the likelihood of accidents. Conclusion: The construction of bicycle-exclusive spaces and educational campaigns are required.