Coleção de Artigos Acadêmicos
URI permanente para esta coleçãohttps://repositorio.insper.edu.br/handle/11224/3227
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63 resultados
Resultados da Pesquisa
Artigo Científico A Statistical Method to Distinguish Functional Brain Networks(2017) Fujita, André; MACIEL CALEBE VIDAL; Takahashi, Daniel Y.One major problem in neuroscience is the comparison of functional brain networks of different populations, e.g., distinguishing the networks of controls and patients. Traditional algorithms are based on search for isomorphism between networks, assuming that they are deterministic. However, biological networks present randomness that cannot be well modeled by those algorithms. For instance, functional brain networks of distinct subjects of the same population can be different due to individual characteristics. Moreover, networks of subjects from different populations can be generated through the same stochastic process. Thus, a better hypothesis is that networks are generated by random processes. In this case, subjects from the same group are samples from the same random process, whereas subjects from different groups are generated by distinct processes. Using this idea, we developed a statistical test called ANOGVA to test whether two or more populations of graphs are generated by the same random graph model. Our simulations' results demonstrate that we can precisely control the rate of false positives and that the test is powerful to discriminate random graphs generated by different models and parameters. The method also showed to be robust for unbalanced data. As an example, we applied ANOGVA to an fMRI dataset composed of controls and patients diagnosed with autism or Asperger. ANOGVA identified the cerebellar functional sub-network as statistically different between controls and autism (p < 0.001).Artigo Científico Correlation between graphs with an application to brain network analysis(2017) Fujita, André; Takahashi, Daniel Yasumasa; Balardin, Joana Bisol; MACIEL CALEBE VIDAL; Sato, João RicardoThe global functional brain network (graph) is more suitable for characterizing brain states than local analysis of the connectivity of brain regions. Therefore, graph-theoretic approaches are natural methods to use for studying the brain. However, conventional graph theoretical analyses are limited due to the lack of formal statistical methods of estimation and inference. For example, the concept of correlation between two vectors of graphs has not yet been defined. Thus, the introduction of a notion of correlation between graphs becomes necessary to better understand how brain sub-networks interact. To develop a framework to infer correlation between graphs, one may assume that they are generated by models and that the parameters of the models are the random variables. Then, it is possible to define that two graphs are independent when the random variables representing their parameters are independent. In the real world, however, the model is rarely known, and consequently, the parameters cannot be estimated. By analyzing the graph spectrum, it is shown that the spectral radius is highly associated with the parameters of the graph model. Based on this, a framework for correlation inference between graphs is constructed and the approach illustrated on functional magnetic resonance imaging data on 814 subjects comprising 529 controls and 285 individuals diagnosed with autism spectrum disorder (ASD). Results show that correlations between the default-mode and control, default-mode and somatomotor, and default-mode and visual sub-networks are higher in individuals with ASD than in the controls.Artigo Científico A Software to Compare Clusters between Groups and Its Application to the Study of Autism Spectrum Disorder(2017) MACIEL CALEBE VIDAL; Sato, João R.; Balardin, Joana B.; Takahashi, Daniel Y.; Fujita, AndréUnderstanding how brain activities cluster can help in the diagnosis of neuropsychological disorders. Thus, it is important to be able to identify alterations in the clustering structure of functional brain networks. Here, we provide an R implementation of Analysis of Cluster Variability (ANOCVA), which statistically tests (1) whether a set of brain regions of interest (ROI) are equally clustered between two or more populations and (2) whether the contribution of each ROI to the differences in clustering is significant. To illustrate the usefulness of our method and software, we apply the R package in a large functional magnetic resonance imaging (fMRI) dataset composed of 896 individuals (529 controls and 285 diagnosed with ASD—autism spectrum disorder) collected by the ABIDE (The Autism Brain Imaging Data Exchange) Consortium. Our analysis show that the clustering structure of controls and ASD subjects are different (p < 0.001) and that specific brain regions distributed in the frontotemporal, sensorimotor, visual, cerebellar, and brainstem systems significantly contributed (p < 0.05) to this differential clustering. These findings suggest an atypical organization of domain-specific functionbrain modules in ASD.Artigo Científico Information diffusion, cluster formation and entropy-based network dynamics in equity and commodity markets(2017) Bekiros, Stelios; Nguyen, Duc Khuong; Sandoval Junior, Leonidas; Uddin, Gazi SalahArtigo Científico Interest rates in trade credit markets(2017) Barbosa, Klenio de Souza; Moreira, Humberto; Novaes, WalterArtigo Científico Identifying Sales Performance Gaps with Internal Benchmarking(2017) DANNY PIMENTEL CLARO; Kamakura, Wagner A.Artigo Científico Using Group Drawings Activities to Facilitate the Understanding of the Systemic Aspects of Projects(2017) VINICIUS PICANÇO RODRIGUES; Amaral, João Alberto Arantes do; Hess, Aurélio; Gonçalves, PauloArtigo Científico The Impact of Daycare Attendance on Math Test Scores for a Cohort of Fourth Graders in Brazil(2017) CRISTINE CAMPOS DE XAVIER PINTO; Guimarães, Clarissa; Santos, DanielArtigo Científico Pedidos de vista no Tribunal Superior Eleitoral(2017) IVAR ALBERTO GLASHERSTER MARTINS LANGE HARTMANN; Correia Junior, Fernando; Araújo, Felipe; Appel, Osias; Craizer, Luis EduardoO artigo é o resultado de pesquisa quantitativa com objetivo de responder duas perguntas: 1) os pedidos de vista no TSE são comuns? 2) Os pedidos de vista no TSE são curtos? Foram capturados os dados básicos, incluindo informações de andamentos processuais, de 235.416 casos ingressados no tribunal entre janeiro de 2006 e maio de 2017. Os dados mostram que os pedidos de vista não são comuns no TSE. Apenas 1.17% dos processos no período tiveram um pedido de vista. Os dados também mostram que os pedidos de vista não são curtos. A média geral é de 66.97 dias, sendo que aproximadamente 1/5 dos pedidos ultrapassa 100 dias – 5 vezes o prazo mais alongado, pelo novo CPC.Artigo Científico Direito constitucional de recorrer e a judicialização da ineficiência empresarial(2017) IVAR ALBERTO GLASHERSTER MARTINS LANGE HARTMANN; Falcão, JoaquimA judicialização das questões consume ristas atinge o Supremo Tribunal Federal por via dos juizados especiais há vários anos. Recentemen te uma empresa do ramo de telefonia, a Oi, des tacou-se pelo volume desproporcional de processos que levou ao tribunal. Ao analisar o perfil da liti gância de direito do consumidor da Oi no Supremo, identificamos que a empresa envia o dobro de pro cessos do segundo colocado no ranking de maiores litigantes, apesar de ter taxa de sucesso menor do que 0,07%. No contexto da necessidade de adequa da proteção dos direitos do consumidor, esse com portamento pode ser caracterizado como bullying processual e demanda novas atitudes por parte dos órgãos reguladores e do próprio Supremo