Dropout and Engineering undergraduate programs at the Universidad Nacional de Colombia between 2012-2019

Dropout is a topic of significant concern to Higher Education Institutions, especially in Colombia it is considered one of the most important indicators to define higher education quality. Nevertheless, in Colombia, and particularly at the Universidad Nacional de Colombia, it has been generally assessed only academic dropout. This decision has prevented understanding other types of dropouts that also occur in the university. The research group performed Multiple Correspondence Analysis to assess the relationship between dropout types (academic, dropout on request, and expiry of time limits) and variables such as sex, socioeconomic stratum, type of admission, and semester of dropout. In the results, we found a disparity between types of dropout concerning the type of university admission, sex, socio-economic stratum, and the semester in which dropout occurs. Women are related to the dropout request while men are associated with the academic dropout. Additionally, the academic dropout occurs in the first 4 semesters, and the expiry of time limits occurs in the last ones.

Dynamics of Dispersed-Nesting Black Brant on the Yukon-Kuskokwim Delta

The number of black brant Branta bernicla nigricans nests within major breeding colonies on the Yukon-Kuskowkim Delta has declined since 1992. It has been hypothesized that these declines are partially explained by increased numbers of black brant breeding outside of these colonies. To assess this hypothesis, we analyzed spatiotemporal patterns in numbers of black brant nests occurring outside major colonies. Nesting densities of black brant vary among three strata: 1) peripheral to major colonies, 2) other coastal habitats, and 3) inland habitats. We sampled some substrata within each stratum type only between 1986 and 1999 (historical strata), whereas we sampled others over the period 1986–2016 (long-term strata). We fit regression models with number of nests on a plot as a response variable, a log link, and year as the explanatory variable. We allowed each stratum (e.g., historical peripheral) to have its own intercept to account for variation in mean nest density but constrained linear and quadratic regression coefficients to be the same for strata in similar habitats (e.g., historical and long-term peripheral). We used a negative binomial distribution for nests to allow for substantial variation in nests per plot. We fit models using Markov Chain Monte Carlo methods in JAGS. Ninety-five percent credible intervals for both linear and quadratic coefficients for the peripheral and coastal strata, where most nests occurred, broadly overlapped zero, indicating modest trends in numbers of nests in these strata. We estimated there were 6,584 (95% credible interval: 4,221−11,269) dispersed nests in 1986, increasing to 11,051 (95% credible interval: 7,450−17,460) in 2016. Our results indicated that increases in dispersed nests were unable to replace declines in colony nests. Furthermore, quadratic trends indicated that potential earlier annual increases in dispersed nests have declined to zero. We conclude that total numbers of black brant nests on the Yukon-Kuskokwim Delta are likely declining, consistent with the trend in fall age ratios over the same period. Uncertainty about trends in areas not sampled since 1994 adds to the uncertainty about the precise magnitude of the decline. We recommend that the area sampled by the random plot program be expanded to include strata sampled only before 1995.

A Stratigraphic Prediction Method Based on Machine Learning

Simulation of a geostratigraphic unit is of vital importance for the study of geoinformatics, as well as geoengineering planning and design. A traditional method depends on the guidance of expert experience, which is subjective and limited, thereby making the effective evaluation of a stratum simulation quite impossible. To solve this problem, this study proposes a machine learning method for a geostratigraphic series simulation. On the basis of a recurrent neural network, a sequence model of the stratum type and a sequence model of the stratum thickness is successively established. The performance of the model is improved in combination with expert-driven learning. Finally, a machine learning model is established for a geostratigraphic series simulation, and a three-dimensional (3D) geological modeling evaluation method is proposed which considers the stratum type and thickness. The results show that we can use machine learning in the simulation of a series. The series model based on machine learning can describe the real situation at wells, and it is a complimentary tool to the traditional 3D geological model. The prediction ability of the model is improved to a certain extent by including expert-driven learning. This study provides a novel approach for the simulation and prediction of a series by 3D geological modeling.

Research in motor behavior in the year 2018

The Motor Behavior (MB) area investigates the neuropsychological processes of the organization of the motor response in terms of learning, control and motor development from which three research sub-areas emerged called Motor Learning (ML), Motor Control (MC) and Motor Development (MD). This study aimed to describe the intellectual production in the sub-areas ML, MC and MD in 2018 and to identify the current profile of the MB area. The intellectual production in the sub-areas of the MB was organized, by stratum, type of task and adherence with the CAPES area 21 journals. There were 53 articles published by 51 researchers in the MB area linked to Postgraduate programs in Physical Education in 2018. The distribution of articles by sub-areas was represented by 30.18% ML, 54.72% MC and 15.10% MD. The MC sub-area presented 86% of articles published in the upper stratum, the ML sub-area with 37%, followed by the MD sub-area with 13%. The average of the three sub-areas resulted in 83.02% of studies with a simple task and only 16.98% with a complex task. The greater number of publications with low adherence combined with the greater number of researches with simple tasks seems to demonstrate the researchers' difficulty in approaching the knowledge produced in the area of MB for undergraduate students in Physical Education.