Characterization Of Multiscroll Attractors Using Lyapunov Exponents And Lagrangian Coherent Structures.

The present work aims to apply a recently proposed method for estimating Lyapunov exponents to characterize-with the aid of the metric entropy and the fractal dimension-the degree of information and the topological structure associated with multiscroll attractors. In particular, the employed methodology offers the possibility of obtaining the whole Lyapunov spectrum directly from the state equations without employing any linearization procedure or time series-based analysis. As a main result, the predictability and the complexity associated with the phase trajectory were quantified as the number of scrolls are progressively increased for a particular piecewise linear model. In general, it is shown here that the trajectory tends to increase its complexity and unpredictability following an exponential behaviour with the addition of scrolls towards to an upper bound limit, except for some degenerated situations where a non-uniform grid of scrolls is attained. Moreover, the approach employed here also provides an easy way for estimating the finite time Lyapunov exponents of the dynamics and, consequently, the Lagrangian coherent structures for the vector field. These structures are particularly important to understand the stretching/folding behaviour underlying the chaotic multiscroll structure and can provide a better insight of phase space partition and exploration as new scrolls are progressively added to the attractor.2302310

Schizophrenia and work: aspects related to job acquisition in a follow-up study

Objective: Work is considered one of the main forms of social organizationhowever, few individuals with schizophrenia find work opportunities. The purpose of this study was to evaluate the relationship between schizophrenia symptoms and job acquisition. Method: Fifty-three individuals diagnosed with schizophrenia from an outpatient treatment facility were included in an 18-month follow-up study. After enrollment, they participated in a prevocational training group. At the end of training (baseline) and 18 months later, sociodemographic, clinical data and occupational history were collected. Positive and negative symptoms (Positive and Negative Syndrome Scale - PANSS), depression (Calgary Depression Scale), disease severity (Clinical Global Impression - CGI), functionality (Global Assessment of Functioning - GAF), personal and social performance (Personal and Social Performance - PSP) and cognitive functions (Measurement and Treatment Research to Improve Cognition in Schizophrenia - MATRICS battery) were applied at baseline and at the end of the study. Results: Those with some previous work experience (n = 19) presented lower scores on the PANSS, Calgary, GAF, CGI and PSP scales (p < 0.05) than those who did not work. Among those who worked, there was a slight worsening in positive symptoms (positive PANSS). Conclusions: Individuals with less severe symptoms were more able to find employment. Positive symptom changes do not seem to affect participation at workhowever, this calls for discussion about the importance of employment support.Programa de Esquizofrenia (PROESQ)Centro de Atencao Integrada a Saude Mental (CAISM)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [2011/50740-5]Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)FAPESPConselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)CAPESUniv Fed Sao Paulo UNIFESP, Dept Psiquiatria, Sao Paulo, SP, BrazilUniv Fed Sao Carlos UFSCar, Dept Med, Sao Carlos, SP, BrazilUniv Fed Sao Carlos, Dept Terapia Ocupac, Sao Carlos, SP, BrazilFac Ciencias Med Santa Casa Sao Paulo, Dept Psiquiatria, Sao Paulo, SP, BrazilUniv Fed Sao Paulo UNIFESP, Dept Psiquiatria, Sao Paulo, SP, BrazilFAPESP [2011/50740-5]Web of Scienc

A core outcome set for evaluating self-management interventions in people with comorbid diabetes and severe mental illness : study protocol for a modified Delphi study and systematic review

BACKGROUND: People with diabetes and comorbid severe mental illness (SMI) form a growing population at risk of increased mortality and morbidity compared to those with diabetes or SMI alone. There is increasing interest in interventions that target diabetes in SMI in order to help to improve physical health and reduce the associated health inequalities. However, there is a lack of consensus about which outcomes are important for this comorbid population, with trials differing in their focus on physical and mental health. A core outcome set, which includes outcomes across both conditions that are relevant to patients and other key stakeholders, is needed. METHODS: This study protocol describes methods to develop a core outcome set for use in effectiveness trials of self-management interventions for adults with comorbid type-2 diabetes and SMI. We will use a modified Delphi method to identify, rank, and agree core outcomes. This will comprise a two-round online survey and multistakeholder workshops involving patients and carers, health and social care professionals, health care commissioners, and other experts (e.g. academic researchers and third sector organisations). We will also select appropriate measurement tools for each outcome in the proposed core set and identify gaps in measures, where these exist. DISCUSSION: The proposed core outcome set will provide clear guidance about what outcomes should be measured, as a minimum, in trials of interventions for people with coexisting type-2 diabetes and SMI, and improve future synthesis of trial evidence in this area. We will also explore the challenges of using online Delphi methods for this hard-to-reach population, and examine differences in opinion about which outcomes matter to diverse stakeholder groups. TRIAL REGISTRATION: COMET registration: http://www.comet-initiative.org/studies/details/911 . Registered on 1 July 2016

The Effectiveness of Pharmacological and Non-Pharmacological Interventions for Improving Glycaemic Control in Adults with Severe Mental Illness: A Systematic Review and Meta-Analysis

People with severe mental illness (SMI) have reduced life expectancy compared with the general population, which can be explained partly by their increased risk of diabetes. We conducted a meta-analysis to determine the clinical effectiveness of pharmacological and non-pharmacological interventions for improving glycaemic control in people with SMI (PROSPERO registration: CRD42015015558). A systematic literature search was performed on 30/10/2015 to identify randomised controlled trials (RCTs) in adults with SMI, with or without a diagnosis of diabetes that measured fasting blood glucose or glycated haemoglobin (HbA1c). Screening and data extraction were carried out independently by two reviewers. We used random effects meta-analysis to estimate effectiveness, and subgroup analysis and univariate meta-regression to explore heterogeneity. The Cochrane Collaboration’s tool was used to assess risk of bias. We found 54 eligible RCTs in 4,392 adults (40 pharmacological, 13 behavioural, one mixed intervention). Data for meta-analysis were available from 48 RCTs (n = 4052). Both pharmacological (mean difference (MD), -0.11mmol/L; 95% confidence interval (CI), [-0.19, -0.02], p = 0.02, n = 2536) and behavioural interventions (MD, -0.28mmol//L; 95% CI, [-0.43, -0.12], p<0.001, n = 956) were effective in lowering fasting glucose, but not HbA1c (pharmacological MD, -0.03%; 95% CI, [-0.12, 0.06], p = 0.52, n = 1515; behavioural MD, 0.18%; 95% CI, [-0.07, 0.42], p = 0.16, n = 140) compared with usual care or placebo. In subgroup analysis of pharmacological interventions, metformin and antipsychotic switching strategies improved HbA1c. Behavioural interventions of longer duration and those including repeated physical activity had greater effects on fasting glucose than those without these characteristics. Baseline levels of fasting glucose explained some of the heterogeneity in behavioural interventions but not in pharmacological interventions. Although the strength of the evidence is limited by inadequate trial design and reporting and significant heterogeneity, there is some evidence that behavioural interventions, antipsychotic switching, and metformin can lead to clinically important improvements in glycaemic measurements in adults with SMI

The effects of lifestyle interventions on (long-term) weight management, cardiometabolic risk and depressive symptoms in people with psychotic disorders:A meta-analysis

AIMS: The aim of this study was to estimate the effects of lifestyle interventions on bodyweight and other cardiometabolic risk factors in people with psychotic disorders. Additionally, the long-term effects on body weight and the effects on depressive symptoms were examined. MATERIAL AND METHODS: We searched four databases for randomized controlled trials (RCTs) that compared lifestyle interventions to control conditions in patients with psychotic disorders. Lifestyle interventions were aimed at weight loss or weight gain prevention, and the study outcomes included bodyweight or metabolic parameters. RESULTS: The search resulted in 25 RCTs -only 4 were considered high quality- showing an overall effect of lifestyle interventions on bodyweight (effect size (ES)  =  -0.63, p<0.0001). Lifestyle interventions were effective in both weight loss (ES =  -0.52, p<0.0001) and weight-gain-prevention (ES =  -0.84, p = 0.0002). There were significant long-term effects, two to six months post-intervention, for both weight-gain-prevention interventions (ES =  -0.85, p = 0.0002) and weight loss studies (ES =  -0.46, p = 0.02). Up to ten studies reported on cardiometabolic risk factors and showed that lifestyle interventions led to significant improvements in waist circumference, triglycerides, fasting glucose and insulin. No significant effects were found for blood pressure and cholesterol levels. Four studies reported on depressive symptoms and showed a significant effect (ES =  -0.95, p = 0.05). CONCLUSION: Lifestyle interventions are effective in treating and preventing obesity, and in reducing cardiometabolic risk factors. However, the quality of the studies leaves much to be desired

Can graph metrics be used for EEG-BCIs based on hand motor imagery?

FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFINEP - FINANCIADORA DE ESTUDOS E PROJETOSCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORThe study of motor imagery (MI) has been a subject of great interest within the brain-computer interface (BCI) community. Several approaches have been proposed to solve the problem of classifying cerebral responses due to MI, mostly based on the power spectral density of the mu and beta bands; however, no optimum manner of proceeding through the fundamental steps of a MI-BCI has yet been established. In this work, we explored a relatively novel approach regarding feature generation for a MI-BCI by assuming that functional connectivity patterns of the brain are altered during hand MI. We modelled interactions among EEG electrodes by a graph, extracted metrics from it during left and right hand MI from eight subjects and classified the signals using commonly employed techniques in the BCI community (LDA and SVM). We also compared this approach to the more established method of using the signal power spectral density as the classifier features. With the graph method, we confirmed that only specific electrodes provide relevant information for data classification. A first approach provided maximum average classification rates across all subjects for the graph method of 86% for the mu band and 87% for the beta band. For the PSD method, average rates were of 98% and 99% for the mu and beta bands, respectively. However, a much larger number of features was needed: (130 44) and (273 89) for the mu and beta bands, respectively. Aiming to reproduce these rates using the graph method, pairwise inputs combinations of graph metrics were tested. They proved to be sufficient to obtain essentially the same classification accuracy rates, but with a considerably smaller number of features - about 60 features, for both bands. We thus conclude that the graph method is a feasible option for classification of hand MI signals.40359365FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFINEP - FINANCIADORA DE ESTUDOS E PROJETOSCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFINEP - FINANCIADORA DE ESTUDOS E PROJETOSCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIOR2013/07559-3Sem informaçãoSem informaçãoSem informaçã

Análise Comparativa de Metodologias de Inteligência Computacional para Identificação do Sistema Misturador em Análise de Componentes Esparsos

Sem resumo

Unorganized machines for seasonal streamflow series forecasting

Modern unorganized machines - extreme learning machines and echo state networks - provide an elegant balance between processing capability and mathematical simplicity, circumventing the difficulties associated with the conventional training approaches of feedforward/recurrent neural networks (FNNs/RNNs). This work performs a detailed investigation of the applicability of unorganized architectures to the problem of seasonal streamflow series forecasting, considering scenarios associated with four Brazilian hydroelectric plants and four distinct prediction horizons. Experimental results indicate the pertinence of these models to the focused task243CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPnão temnão temnão te

Blind Extraction Of Sparse Components Based On L0-norm Minimization

We investigate the application of cost functions based on the 0-norm to the problem of blind source extraction (BSE). We show that if the sources have different levels of sparsity, then the minimization of the 0-norm leads to the extraction of the sparsest component even when the sources are statistically dependent. We also study the conditions guaranteeing BSE when an approximation of the 0-norm is considered. Finally, we provide a numerical example to illustrate the applicability of our proposal. © 2011 IEEE.617620Comon, P., Jutten, C., (2010) Handbook of Blind Source Separation: Independent Component Analysis and Applications, , Academic PressDelfosse, N., Loubaton, P., Adaptive blind separation of independent sources: A deflation approach (1995) Signal Processing, 45, pp. 59-83Hyvärinen, A., Karhunen, J., Oja, E., (2001) Independent Component Analysis, , John Wiley & SonsMourad, N., Reilly, J.P., Blind extraction of sparse sources (2010) Proc. of IEEE ICASSP, pp. 2666-2669Nadalin, E.Z., Takahata, A.K., Duarte, L.T., Suyama, R., Attux, R., Blind extraction of the sparsest component (2010) LNCS, 6365, pp. 263-270Elad, M., (2010) Sparse and Redundant Representations from Theory to Applications in Signal and Image Processing, , SpringerBabaie-Zadeh, H., Mohimani, M., Jutten, C., A fast approach for overcomplete sparse decomposition based on smoothed l0 norm (2009) IEEE Trans. on Sig. Proc., 57, pp. 289-301Weston, J., Elisseeff, A., Schölkopf, B., Use of the zeronorm with linear models and kernel methods (2003) Jour. of Machine Lear. Res., 3, pp. 1439-146