Regular (2+1)-dimensional black holes within non-linear Electrodynamics

(2+1)-regular static black hole solutions with a nonlinear electric field are derived. The source to the Einstein equations is an energy momentum tensor of nonlinear electrodynamics, which satisfies the weak energy conditions and in the weak field limit becomes the (2+1)-Maxwell field tensor. The derived class of solutions is regular; the metric, curvature invariants and electric field are regular everywhere. The metric becomes, for a vanishing parameter, the (2+1)-static charged BTZ solution. A general procedure to derive solutions for the static BTZ (2+1)-spacetime, for any nonlinear Lagrangian depending on the electric field is formulated; for relevant electric fields one requires the fulfillment of the weak energy conditions.Comment: 5 pages, Latex, 2 figure

The multi-depot k-traveling repairman problem

In this paper, we study the multi-depot k-traveling repairman problem. This problem extends the traditional traveling repairman problem to the multi-depot case. Its objective, similar to the single depot variant, is the minimization of the sum of the arrival times to customers. We propose two distinct formulations to model the problem, obtained on layered graphs. In order to find feasible solutions for the largest instances, we propose a hybrid genetic algorithm where initial solutions are built using a splitting heuristic and a local search is embedded into the genetic algorithm. The efficiency of the mathematical formulations and of the solution approach are investigated through computational experiments. The proposed models are scalable enough to solve instances up to 240 customers

Inferring Latent Structure From Mixed Real and Categorical Relational Data

We consider analysis of relational data (a matrix), in which the rows correspond to subjects (e.g., people) and the columns correspond to attributes. The elements of the matrix may be a mix of real and categorical. Each subject and attribute is characterized by a latent binary feature vector, and an inferred matrix maps each row-column pair of binary feature vectors to an observed matrix element. The latent binary features of the rows are modeled via a multivariate Gaussian distribution with low-rank covariance matrix, and the Gaussian random variables are mapped to latent binary features via a probit link. The same type construction is applied jointly to the columns. The model infers latent, low-dimensional binary features associated with each row and each column, as well correlation structure between all rows and between all columns

UOLO - automatic object detection and segmentation in biomedical images

We propose UOLO, a novel framework for the simultaneous detection and segmentation of structures of interest in medical images. UOLO consists of an object segmentation module which intermediate abstract representations are processed and used as input for object detection. The resulting system is optimized simultaneously for detecting a class of objects and segmenting an optionally different class of structures. UOLO is trained on a set of bounding boxes enclosing the objects to detect, as well as pixel-wise segmentation information, when available. A new loss function is devised, taking into account whether a reference segmentation is accessible for each training image, in order to suitably backpropagate the error. We validate UOLO on the task of simultaneous optic disc (OD) detection, fovea detection, and OD segmentation from retinal images, achieving state-of-the-art performance on public datasets.Comment: Publised on DLMIA 2018. Licensed under the Creative Commons CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0

GeoGebra as learning tool for the search of the roots of functions in numerical methods

Physics is capable of describing, through equations, phenomena on a micro and macroscopic scale. However, most of these equations are non-linear and the identification of their roots requires the use of approximation methods, with numerical methods being a proposal based on a systematic and iterative process, that conclude only when a pre-established tolerance is satisfied. Traditional teaching of numerical methods involves the memorization of algorithms. However, this hinders student’s ability to understand the important aspects and then apply them for solving applied problems in subjects such as kinematics, dynamics, electromagnetism, etc. Therefore, this work proposes the use of GeoGebra, as a didactic tool to illustrate the functioning of single root searching algorithms. By using the dynamical graphic’s view of GeoGebra, a series of abstract and applied problems where solved by engineering students taking a numerical methods course. The scores of this test group was then compared to a test group, taught trough algorithm memorization. Results show can improve their understanding of how the bisection, false position, secant, and Newton-Raphson methods are able to find approximated solutions to polynomial and trigonometric equations. The results are compared against traditional learning, based on memorizing the steps of the algorithm for each method and the representation of the convergence of successive roots by numerical tables

Chemoprevention agents to reduce mammographic breast density in premenopausal women: A systematic review of clinical trials

Background: Higher mammographic breast density (MBD) is associated with an increased risk of breast cancer when compared with lower MBD, especially in premenopausal women. However, little is known about the effectiveness of chemoprevention agents in reducing MBD in premenopausal women without a history of breast cancer. Findings from this review should provide insight on how to target MBD in breast cancer prevention in premenopausal women with dense breasts. Methods: We searched 9 electronic databases for clinical trials in English, Spanish, French, or German published until January 2020. Articles evaluating the association of pharmacological agents and MBD were included. Data were extracted on methods, type and dose of intervention, outcomes, side effects, and follow up. Quality of the studies was assessed using the US Preventive Services Task Force criteria. Results: We identified 7 clinical trials evaluating the associations of 6 chemoprevention agents with changes in MBD in premenopausal women without history of breast cancer. The studies evaluated selective estrogen-receptor modulators (n = 1); gonadotropin-releasing hormone agonists (n = 2); isoflavones (n = 1); vitamin D (n = 1); and Boswellia, betaine, and mayo-inositol compound (n = 1). Hormonal interventions were associated with net reductions in percent density (tamoxifen [13.4%], leuprolide acetate [8.9%], and goserelin [2.7%]), whereas nonhormonal (vitamin D and isoflavone) interventions were not. However, MBD returned to preintervention baseline levels after cessation of gonadotropin-releasing hormone agonists. Conclusions: A limited number of chemoprevention agents have been shown to reduce MBD in premenopausal women. Identification of new and well-tolerated chemoprevention agents targeting MBD and larger studies to confirm agents that have been studied in small trials are urgent priorities for primary breast cancer prevention in premenopausal women with dense breasts

Impacto de la convivencia escolar sobre el rendimiento académico, desde la percepción de estudiantes con desarrollo típico y necesidades educativas especiales

This descriptive correlational study aims to compare the perception about eight dimensions of school coexistence of typically developing high school students (n = 545) and students with special educational needs (n = 75) from Chile and their relationship with the general academic performance.  Based on the analysis of hierarchical and non-hierarchical clusters, multiple regression and logistic regression, it was found that students with special educational needs have a less favorable perception in almost every dimension analyzed; especially, in those aspects related to school victimization, aggression, and indiscipline. Likewise, they perceive that they have a limited peer social network, as well as limited normative adjustment and a lower perception about their own positive interpersonal skills. The multiple regression and logistic regression models allow confirming that the dimensions of school coexistence account for between 20% and 27% of the academic performance variability. The aforementioned models highlight the role and negative effect of the level of victimization perceived by students, as well as the perception about the occurrence of indiscipline situations in the classroom, and the fact of belonging to the group of students with special educational needs, and to the group of male students. The findings are analyzed and discussed in light of the implications for high social vulnerability educational contexts.This descriptive correlational study aims to compare the perception about eight dimensions of school coexistence of typically developing high school students (n = 545) and students with special educational needs (n = 75) from Chile and their relationship with the general academic performance.  Based on the analysis of hierarchical and non-hierarchical clusters, multiple regression and logistic regression, it was found that students with special educational needs have a less favorable perception in almost every dimension analyzed; especially, in those aspects related to school victimization, aggression, and indiscipline. Likewise, they perceive that they have a limited peer social network, as well as limited normative adjustment and a lower perception about their own positive interpersonal skills. The multiple regression and logistic regression models allow confirming that the dimensions of school coexistence account for between 20% and 27% of the academic performance variability. The aforementioned models highlight the role and negative effect of the level of victimization perceived by students, as well as the perception about the occurrence of indiscipline situations in the classroom, and the fact of belonging to the group of students with special educational needs, and to the group of male students. The findings are analyzed and discussed in light of the implications for high social vulnerability educational contexts.Estudio descriptivo-correlacional que busca comparar la percepción acerca de ocho dimensiones de la convivencia escolar de estudiantes chilenos de educación media con desarrollo típico (n=545) y con necesidades educativas especiales (n=75), y su relación con el rendimiento académico general. A partir de los análisis de conglomerados jerárquico y no jerárquico, regresión múltiple y regresión logística, se constata que los estudiantes con necesidades educativas especiales tienen una percepción más desfavorable en casi todas las dimensiones analizadas, especialmente en aquellos aspectos asociados a la victimización escolar y agresión e indisciplina, de igual forma, perciben tener una menor red social de iguales, menor ajuste normativo y una más baja percepción respecto de la gestión interpersonal positiva. Los modelos de regresión múltiple y regresión logística, permiten constatar que las dimensiones de la convivencia escolar explican entre el 20% y el 27% de la variabilidad del rendimiento académico. En dichos modelos destaca el papel y efecto negativo que tiene la el grado de victimización que perciben los estudiantes, como también la percepción respecto de la ocurrencia o presencia de situaciones de indisciplina al interior del aula, como también el hecho de pertenecer al grupo de estudiantes con necesidades educativas especiales, y el pertenecer al grupo de estudiantes hombres. Se analizan y discuten los hallazgos a la luz de las implicaciones para contextos educativos de alta vulnerabilidad social