Envejecimiento de la población, salud y ambiente urbano en América Latina. Retos del Urbanismo gerontológico.

El estudio reflexiona sobre los desafíos del envejecimiento de la población en las zonas urbanas de América Latina, destacando la importancia de la planificación gerontológica del entorno físico y social en la salud y calidad de vida de las personas mayores. La metodología consistió en una revisión de la literatura científica, principalmente revistas indexadas a Scopus y Thomson-Reuters. Los resultados indican que en la región el crecimiento urbano agrava las condiciones ambientales y los problemas de salud de la población de edad avanzada, una situación que se ve afectada por el contexto de vulnerabilidad social (pobreza, problemas de acceso a los servicios de salud). También, algunas de las claves se discuten en la comprensión de los desafíos de la planificación gerontológica de las ciudades de América Latina, y la participación activa de las personas mayores en el diseño de entornos construidos dinámicos y estimulantes, en especial, hogares y espacios públicos. Además, en la región el avance del envejecimiento de la población urbana va a generar una fuerte demanda de los gerontólogos ambientales, especialmente arquitectos, urbanistas y profesionales de la salud ambiental, con formación gerontológica en la sensibilidad de diseños favorables para envejecer en el lugar

Edge-superconnectivity of semiregular cages with odd girth

A graph is said to be edge-superconnected if each minimum edge-cut consists of all the edges incident with some vertex of minimum degree. A graph G is said to be a {d, d + 1}- semiregular graph if all its vertices have degree either d or d+1. A smallest {d,d+1}-semiregular graph G with girth g is said to be a ({d, d+1}; g)-cage.We show that every ({d, d+1}; g)-cage with odd girth g is edge-superconnected.Peer Reviewe

Los juegos tradicionales como propuesta pedagógica para cualificar el desarrollo motor en niños de 6 y 7 años del grado primero I.T.I Francisco José de Caldas.

Este proyecto se implementó en la Institución Educativa Distrital Francisco José de Caldas, donde se implementaron los juegos tradicionales como fuente o herramienta para contribuir al desarrollo motor de los niños de primer grado, los cuales tienen un rango de edad de 6 y 7 años de edad. Edad donde es fundamental el aprendizaje motor para un mejor desarrollo de su vida en general, ya que en estas etapas de desarrollo es de vital importancia el afianzamiento de sus funciones motoras. Por lo tanto, esta investigación se forjo bajo el objetivo principal de determinar la incidencia de la aplicación de los juegos tradicionales como propuesta pedagógica para cualificar el desarrollo motor en niños de 5 y 6 años del grado primero en el IED Francisco José de Caldas.Universidad Libre – Facultad de Ciencias de la Educación – Licenciatura en Educación Básica con énfasis en Educación Física, Recreación y Deporte

Envejecimiento de la población, salud y ambiente urbano en América Latina. Retos del Urbanismo gerontológico

El estudio reflexiona sobre los desafíos del envejecimiento de la población en las zonas urbanas de América Latina, destacando la importancia de la planificación gerontológica del entorno físico y social en la salud y calidad de vida de las personas mayores. La metodología consistió en una revisión de la literatura científica, principalmente revistas indexadas a Scopus y Thomson-Reuters. Los resultados indican que en la región el crecimiento urbano agrava las condiciones ambientales y los problemas de salud de la población de edad avanzada, una situación que se ve afectada por el contexto de vulnerabilidad social (pobreza, problemas de acceso a los servicios de salud). También, algunas de las claves se discuten en la comprensión de los desafíos de la planificación gerontológica de las ciudades de América Latina, y la participación activa de las personas mayores en el diseño de entornos construidos dinámicos y estimulantes, en especial, hogares y espacios públicos. Además, en la región el avance del envejecimiento de la población urbana va a generar una fuerte demanda de los gerontólogos ambientales, especialmente arquitectos, urbanistas y profesionales de la salud ambiental, con formación gerontológica en la sensibilidad de diseños favorables para envejecer en el lugar

2,9-Dimethyl-6H,13H-5:12,7:14-dimethano­dibenzo[d,i][1,3,6,8]tetraazecine

In the title structure, C18H20N4, the aromatic rings are almost orthogonal [81.6 (2)°]. The mol­ecule has symmetry 2 since it is situated on a crystallographic twofold axis. There are only weak inter­molecular inter­actions present in the structure, notably C—H⋯π-electron ring inter­actions. The 1H and 13C NMR spectra are in accordance with the X-ray structure analysis

Nonlinear Weighting Ensemble Learning Model to Diagnose Parkinson's Disease Using Multimodal Data

This work was supported by the FEDER/Junta deAndalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades/Proyecto (B-TIC-586-UGR20); the MCIN/AEI/10.13039/501100011033/ and FEDER \Una manerade hacer Europa" under the RTI2018-098913-B100 project, by the Consejeria de Economia, Innovacion,Ciencia y Empleo (Junta de Andalucia) and FEDER under CV20-45250, A-TIC-080-UGR18 and P20-00525 projects. Grant by F.J.M.M. RYC2021-030875-I funded by MCIN/AEI/10.13039/501100011033 and European Union NextGenerationEU/PRTR. Work by D.C.B. is supported by the MCIN/AEI/FJC2021-048082-I Juan de la Cierva Formacion'. Work by J.E.A. is supported by Next Generation EU Fund through a Margarita Salas Grant, and work by C.J.M. is supported by Ministerio de Universidades under the FPU18/04902 grant.Parkinson's Disease (PD) is the second most prevalent neurodegenerative disorder among adults. Although its triggers are still not clear, they may be due to a combination of different types of biomarkers measured through medical imaging, metabolomics, proteomics or genetics, among others. In this context, we have proposed a Computer-Aided Diagnosis (CAD) system that combines structural and functional imaging data from subjects in Parkinson's Progression Markers Initiative dataset by means of an Ensemble Learning methodology trained to identify and penalize input sources with low classification rates and/or high-variability. This proposal improves results published in recent years and provides an accurate solution not only from the point of view of image preprocessing (including a comparison between different intensity preservation techniques), but also in terms of dimensionality reduction methods (Isomap). In addition, we have also introduced a bagging classification schema for scenarios with unbalanced data.As shown by our results, the CAD proposal is able to detect PD with 96.48% of balanced accuracy, and opens up the possibility of combining any number of input data sources relevant for PD.FEDER/Junta deAndalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades/Proyecto B-TIC-586-UGR20MCIN/AEI P20-00525FEDER \Una manerade hacer Europa RYC2021-030875-IJunta de AndaluciaEuropean Union (EU) Spanish Government RTI2018-098913-B100, CV20-45250, A-TIC-080-UGR18European Union (EU)Juan de la Cierva FormacionNext Generation EU Fund through a Margarita Salas GrantMinisterio de Universidades FPU18/0490

Analysis of radiation parameters to control the effects of Nd: YAG laser surgery on gastric malignancies

Endoscopic laser surgery provides an advantageous alternative to Argon Plasma Coagulation, endoscopic tweezers or electro-ablation in gastroenterology that facilitates a selective ablation of stomach tumors with an additional hemostatic effect in the surrounding tissue. This coagulation effect can also be employed for the treatment of gastric ulcers. It is mandatory to control the laser parameters regardless of the desired effect, either cancerous tissue ablation or coagulation to prevent ulcerous bleeding, in order to avoid stomach wall perforation or an insufficient therapeutic outcome. Dosimetric models constitute an attractive tool to determine the proper light dose in order to offer a customized therapy planning that optimizes the treatment results. In this work, a model for Nd:YAG laser surgery is applied to predict both the coagulation zone in gastric ulcers and the removal in adenocarcinomas under different laser setups. Results show clear differences in the effective zone of the gastric malignancy affected by both coagulation and ablation. Therefore the current model could be employed in the clinical practice to plan the optimal laser beam parameters to treat a certain type of pathologic stomach tissue with variable morphology and without risk of perforation or undertreated parts.This work has been partially supported by the project MAT2012-38664-C02-01 of the Spanish Ministery of Economy and Competitiveness

Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares.

Background: Alzheimer’s disease (AD) is the most common cause of dementia in the elderly and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) is very frequently a prodromal phase of AD, and existing studies have suggested that people with MCI tend to progress to AD at a rate of about 10 % to 15 % per year. However, the ability of clinicians and machine learning systems to predict AD based on MRI biomarkers at an early stage is still a challenging problem that can have a great impact in improving treatments. Method: The proposed system, developed by the SiPBA-UGR team for this challenge, is based on feature standardization, ANOVA feature selection, partial least squares feature dimension reduction and an ensemble of one vs. rest random forest classifiers. With the aim of improving its performance when discriminating healthy controls (HC) from MCI, a second binary classification level was introduced that reconsiders the HC and MCI predictions of the first level. Results: The system was trained and evaluated on an ADNI datasets that consist of T1-weighted MRI morphological measurements from HC, stable MCI, converter MCI and AD subjects. The proposed system yields a 56.25 % classification score on the test subset which consists of 160 real subjects. Comparison with Existing Method(s): The classifier yielded the best performance when compared to: i) One vs. One (OvO), One vs. Rest (OvR) and error correcting output codes (ECOC) as strategies for reducing the multiclass classification task to multiple binary classification problems, ii) support vector machines, gradient boosting classifier and random forest as base binary classifiers, and iii) bagging ensemble learning. Conclusions: A robust method has been proposed for the international challenge on MCI prediction based on MRI data.This work was supported by the MINECO/FEDER under TEC2015-64718-R project, the Consejería de Economía, Innovacion, Ciencia, y Empleo of the Junta de Andalucía under the P11-TIC-7103 Excellence Project and the Salvador de Madariaga Mobility Grants 2017

Morphological Characterization of Functional Brain Imaging by Isosurface Analysis in Parkinson’s Disease.

Finding new biomarkers to model Parkinson’s Disease (PD) is a challenge not only to help discerning between Healthy Control (HC) subjects and patients with potential PD, but also as a way to measure quantitatively the loss of dopaminergic neurons mainly concentrated at substantia nigra. Within this context, the work presented here tries to provide a set of imaging features based on morphological characteristics extracted from I[123]-Ioflupane SPECT scans to discern between HC and PD participants in a balanced set of 386 scans from Parkinson’s Progression Markers Initiative (PPMI) database. These features, obtained from isosurfaces of each scan at different intensity levels, have been classified through the use of classical Machine Learning classifiers such as Support-Vector-Machines (SVM) or Na¨ıve Bayesian and compared with the results obtained using a Multi-Layer Perceptron (MLP). The proposed system, based on a Mann-Whitney-Wilcoxon U-Test for feature selection and the SVM approach, yielded a 97.04% balanced accuracy when the performance was evaluated using a 10-fold cross-validation. This proves the reliability of these biomarkers, especially those related to sphericity, center of mass, number of vertices, 2D-projected perimeter or the 2D-projected eccentricity; among others, but including both internal and external isosurfaces.This work was supported by the MINECO/FEDER under the RTI2018-098913-B-I00 and PGC2018- 098813-B-C32 projects and the General Secretariat of Universities, Research and Technology, Junta de Andalucía under the Excellence FEDER Project ATIC-117-UGR18

Connected system for monitoring electrical power transformers using thermal imaging

The stable supply of electricity is essential for the industrial activity and economic development as well as for human welfare. For this reason, electrical system devices are equipped with monitoring systems that facilitate their management and ensure an uninterrupted operation. This is the case of electrical power transformers, which usually have monitoring systems that allow early detection of anomalies in order to prevent potential malfunctions. These monitoring systems typically make use of sensors that are in physical contact with the transformer devices and can therefore be affected by transformer problems. In this work we demonstrate a monitoring system for electrical power transformers based on temperature measurements obtained by means of thermal cameras. Properly positioned, the cameras provide thermal data of the transformer, the incoming and outgoing lines and their surroundings. Subsequently, by appropriate image processing, it is possible to obtain temperature series to monitor the transformer operation. In addition, the system stores and processes thermal data in external equipment (placed in locations other than the transformers) and is equipped with a communications module that allows secure data transmission independent of the power grid. This aspect, along with the fact that there is no need to have physical contact with the transformer, make this approach safer and more reliable than standard approaches based on sensors. The proposed system has been evaluated in 14 stations belonging to the Spanish power grid, obtaining accurate and reliable temperature time seriesConsejería de Economía, Innovación, Ciencia y Empleo (Junta de Andalucía)FEDER under B-TIC-586-UGR20P20-00525 projects and by the University of GranadaEndesa Distribución under the PASTORA (ref. EXP – 00111351/ITC-20181102)RESISTO (ref. 2021/C005/00144188) contract