Consultório na Rua em uma capital do Nordeste brasileiro: o olhar de pessoas em situação de vulnerabilidade social

Resumo: O objetivo deste estudo foi avaliar a estratégia do Consultório na Rua em Maceió, Alagoas, Brasil, com base na perspectiva de seus usuários. Pesquisa de abordagem qualitativa, cujo cenário foram os campos de atuação da estratégia Consultório na Rua em Maceió, Alagoas. Os sujeitos da pesquisa foram 18 pessoas em situação de rua atendidas pela estratégia, sendo dez homens e oito mulheres, com idades entre 20 e 40 anos. A coleta de dados se deu entre setembro de 2014 e fevereiro de 2015, sendo empregada a técnica de entrevista semiestruturada. Os dados foram analisados por meio da técnica de análise de conteúdo e apontaram duas categorias: a primeira, Consultório na Rua como ele é, revelou os nós críticos, desafios e potencialidades dessa estratégia; a segunda, Consultório na Rua: suporte social, afeto e perspectiva de mudança, para quem se encontra em situação de rua. Os resultados demonstraram que a estratégia é avaliada positivamente e que se constitui como suporte social não apenas em questões relativas à saúde-doença, mas também em aspectos da vida cotidiana

Anger and disgust shape judgments of social sanctions across cultures, especially in high individual autonomy societies

Data availability; The datasets analyzed during the current study are available in the Center for Open Science repository, https://osf.io/djnfg/.Supplementary Information is available online at: https://link.springer.com/article/10.1038/s41598-024-55815-x#Sec17 .When someone violates a social norm, others may think that some sanction would be appropriate. We examine how the experience of emotions like anger and disgust relate to the judged appropriateness of sanctions, in a pre-registered analysis of data from a large-scale study in 56 societies. Across the world, we find that individuals who experience anger and disgust over a norm violation are more likely to endorse confrontation, ostracism and, to a smaller extent, gossip. Moreover, we find that the experience of anger is consistently the strongest predictor of judgments of confrontation, compared to other emotions. Although the link between state-based emotions and judgments may seem universal, its strength varies across countries. Aligned with theoretical predictions, this link is stronger in societies, and among individuals, that place higher value on individual autonomy. Thus, autonomy values may increase the role that emotions play in guiding judgments of social sanctions.This research was funded by the Swedish Foundation for Humanities and Social Sciences (Riksbankens Jubileumsfond) [P17-0030:1]. The contribution of J.W was supported by CAS Youth Innovation Promotion Association and fundings from the Institute of Psychology, Chinese Academy of Sciences (Y5CX052003 and E2CX3315CX). The contributions of M.H and S.G. for the Czech part of research was supported by a Grant 23-061770S of the Czech Science Foundation and by RVO: 68081740 of the Institute of Psychology, Czech Academy of Sciences. Open access funding provided by Linköping University

Electrical load forecasting formulation by a fast neural network

The objective of this work is to develop a methodology for electric load forecasting based on a neural network. Here, backpropagation algorithm is used with an adaptive process that based on fuzzy logic and using a decaying exponential function to avoid instability in the convergence process. This methodology results in fast training, when compared to the conventional formulation of backpropagation algorithm. The results are presented using data from a Brazilian Electric Company, and shows a very good performance for the proposal objective.Univ Estadual Paulista, Dept Engn Eletr, Ilha Solteira, SP, BrazilUniv Estadual Paulista, Dept Engn Eletr, Ilha Solteira, SP, Brazi

Electric load forecasting using a fuzzy ART&ARTMAP neural network

This work presents a neural network based on the ART architecture ( adaptive resonance theory), named fuzzy ART& ARTMAP neural network, applied to the electric load-forecasting problem. The neural networks based on the ARTarchitecture have two fundamental characteristics that are extremely important for the network performance ( stability and plasticity), which allow the implementation of continuous training. The fuzzy ART& ARTMAP neural network aims to reduce the imprecision of the forecasting results by a mechanism that separate the analog and binary data, processing them separately. Therefore, this represents a reduction on the processing time and improved quality of the results, when compared to the Back-Propagation neural network, and better to the classical forecasting techniques (ARIMA of Box and Jenkins methods). Finished the training, the fuzzy ART& ARTMAP neural network is capable to forecast electrical loads 24 h in advance. To validate the methodology, data from a Brazilian electric company is used. (C) 2004 Elsevier B.V. All rights reserved

Electrical load forecasting formulation by a fast neural network

The objective of this work is to develop a methodology for electric load forecasting based on a neural network. Here, backpropagation algorithm is used with an adaptive process that based on fuzzy logic and using a decaying exponential function to avoid instability in the convergence process. This methodology results in fast training, when compared to the conventional formulation of backpropagation algorithm. The results are presented using data from a Brazilian Electric Company, and shows a very good performance for the proposal objective

Electrical load forecasting formulation by a fast neural network

The objective of this work is to develop a methodology for electric load forecasting based on a neural network. Here, backpropagation algorithm is used with an adaptive process that based on fuzzy logic and using a decaying exponential function to avoid instability in the convergence process. This methodology results in fast training, when compared to the conventional formulation of backpropagation algorithm. The results are presented using data from a Brazilian Electric Company, and shows a very good performance for the proposal objective