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This work proposes a new procedure for estimating the non-stationary spatial covariance function for Spatial-Temporal Deformation. The proposed procedure is based on a monotonic function approach. The deformation functions are expanded as a linear combination of the wavelet basis. The estimate of the deformation guarantees an injective transformation. Such that two distinct locations in the geographic plane are not mapped into the same point in the deformation plane. Simulation studies have shown the effectiveness of this procedure. An application to historical daily maximum temperature records exemplifies the flexibility of the proposed methodology when dealing with real datasets.

Considering the field of functional data analysis, we developed a new Bayesian method for variable selection in function-on-scalar regression (FOSR). Our approach uses latent variables, allowing an adaptive selection since it can determine the number of variables and which ones should be selected for a function-on-scalar regression model. Simulation studies show the proposed method's main properties, such as its accuracy in estimating the coefficients and high capacity to select variables correctly. Furthermore, we conducted comparative studies with the main competing methods, such as the BGLSS method as well as the group LASSO, the group MCP and the group SCAD. We also used a COVID-19 dataset and some socioeconomic data from Brazil for real data application. In short, the proposed Bayesian variable selection model is extremely competitive, showing significant predictive and selective quality.

With the vast popularity of the deep learning models in the engineering and mathematical fields, Artificial Neural Networks (ANN) have recently attracted significant research applications in agriculture, economics, informatics and finance. In this paper, we use a deep learning method to capture and predict the unknown complex nonlinear characteristics of agricultural output based on autoregressive artificial neural network, using Nigeria as a case study. Using the proposed model, shocks in agricultural output is analyzed and modeled using data obtained for a period of forty years (1980-2019), and compared with analyses obtained from the autoregressive integrated moving average model (ARIMA). This result is significant because it justifies the superiority of the hybrid ANN model over the traditional Box-Jenkins methodology for forecasting non-stationary time series. The empirical results show that the proposed autoregressive ANN model achieves an improved forecasting accuracy over the traditional Box-Jenkins ARIMA method. It is further proposed that various types of artificial neural networks would be useful in forecasting and solving relevant tasks and problems widely defined in global agricultural production.

Made available in DSpace on 2022-04-29T08:46:09Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-11-01 The Scientific Department of Neuroimmunology of the Brazilian Academy of Neurology (DCNI/ABN) and Brazilian Committee for Treatment and Research in Multiple Sclerosis and Neuroimmunological Diseases (BCTRIMS) provide recommendations in this document for vaccination of the population with demyelinating diseases of the central nervous system (CNS) against infections in general and against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. We emphasize the seriousness of the current situation in view of the spread of COVID-19 in our country. Therefore, reference guides on vaccination for clinicians, patients, and public health authorities are particularly important to prevent some infectious diseases. The DCNI/ABN and BCTRIMS recommend that patients with CNS demyelinating diseases (e.g., MS and NMOSD) be continually monitored for updates to their vaccination schedule, especially at the beginning or before a change in treatment with a disease modifying drug (DMD). It is also important to note that vaccines are safe, and physicians should encourage their use in all patients. Clearly, special care should be taken when live attenuated viruses are involved. Finally, it is important for physicians to verify which DMD the patient is receiving and when the last dose was taken, as each drug may affect the induction of immune response differently. Pontifícia Universidade Católica Do Rio Grande Do Sul, RS Universidade Federal de Sergipe, SE Universidade Tiradentes, SE Universidade de Campinas Faculdade de Ciências Médicas, SP Universidade Federal de São Paulo Escola Paulista de Medicina, SP Universidade Federal de Minas Gerais, MG Universidade de São Paulo Faculdade de Medicina Hospital das Clínicas, SP Universidade Federal Do Amazonas, AM Universidade Federal Do Paraná, PR Hospital Sírio Libanês, SP Escola Bahiana de Medicina e Saúde Pública, BA Hospital Geral de Fortaleza, CE Clínica Nossa Senhora das Graças, MS Hospital Santa Marcelina, SP Santa Casa, MG Instituto de Infectologia Emílio Ribas, SP Fundação Centro Integrado de Apoio Ao Portador de Deficiência, PB Secretaria de Estado da Saúde, DF Universidade Federal Do Rio de Janeiro, RJ Santa Casa, PR Hospital de Clínicas de Passo Fundo, RS Universidade Federal de Goiás, GO Universidade Estácio de Sá, RJ Hospital São Francisco Na Providência de Deus, RJ Universidade Federal Do Ceará, CE Associação Brasileira de Esclerose Múltipla, SP Santa Casa, SP Universidade Federal Fluminense, RJ Pontifícia Universidade Católica, SP Instituto de Neurologia de Curitiba, PR IAMSPE, SP Private Service, SP Universidade da Região de Joinville, SC Hospital Moinhos de Vento, RS Santa Casa, RJ Universidade Federal Ciências da Saúde de Porto Alegre, RS Faculdade de Medicina de Jundiaí, SP Hospital Israelita Albert Einstein, SP Hospital de Base Do Distrito Federal, DF Hospital Beneficiência Portuguesa, SP Hospital Regional de Vilhena, RO Universidade Federal Do Estado Do Rio de Janeiro, RJ Hospital Universitário Prof. Edgar Santos, BA Universidade Metropolitana de Santos, SP Hospital da Restauração, PE Universidade Estadual Paulista Faculdade de Medicina de Botucatu, SP Universidade de Brasília Faculdade de Medicina, DF Universidade Estadual Paulista Faculdade de Medicina de Botucatu, SP

In this paper, we apply statistical methods for functional data to explain the heterogeneity in the evolution of number of deaths of Covid-19 over different regions. We treat the cumulative daily number of deaths in a specific region as a curve (functional data) such that the data comprise of a set of curves over a cross-section of locations. We start by using clustering methods for functional data to identify potential heterogeneity in the curves and their functional derivatives. This first stage is an unconditional descriptive analysis, as we do not use any covariate to estimate the clusters. The estimated clusters are analyzed as "levels of alert" to identify cities in a possible critical situation. In the second and final stage, we propose a functional quantile regression model of the death curves on a number of scalar socioeconomic and demographic indicators in order to investigate their functional effects at different levels of the cumulative number of deaths over time. The proposed model showed a superior predictive capacity by providing better curve fit at different levels of the cumulative number of deaths compared to the functional regression model based on ordinary least squares., 22 pages, 15 figures

This paper presents a novel method for clustering surfaces. The proposal involves first using natural splines basis functions in a tensor product to smooth the data and thus reduce the dimension to a finite number of coefficients, and then using these estimated coefficients to cluster the surfaces via k-means or spectral clustering. An extension of the algorithm to clustering higher-dimensional tensors is also discussed. We show that the proposed algorithm exhibits the property of strong consistency, with or without measurement errors, in correctly clustering the data as the sample size increases. Simulation studies suggest that the proposed method outperforms the benchmark k-means and spectral algorithm which use the original data. In addition, an EGG real data example is considered to illustrate the practical application of the proposal.

We propose a method for nonstationary covariance function modeling, based on the spatial deformation method of Sampson and Guttorp [1992], but using a low-rank, scalable deformation function written as a linear combination of the tensor product of B-spline basis. This approach addresses two important weaknesses in current computational aspects. First, it allows one to constrain estimated 2D deformations to be non-folding (bijective) in 2D. This requirement of the model has, up to now,been addressed only by arbitrary levels of spatial smoothing. Second, basis functions with compact support enable the application to large datasets of spatial monitoring sites of environmental data. An application to rainfall data in southeastern Brazil illustrates the method

The expanding therapeutic arsenal in multiple sclerosis (MS) has allowed for more effective and personalized treatment, but the choice and management of disease-modifying therapies (DMTs) is becoming increasingly complex. In this context, experts from the Brazilian Committee on Treatment and Research in Multiple Sclerosis and the Neuroimmunology Scientific Department of the Brazilian Academy of Neurology have convened to establish this Brazilian Consensus for the Treatment of MS, based on their understanding that neurologists should be able to prescribe MS DMTs according to what is better for each patient, based on up-to-date evidence and practice. We herein propose practical recommendations for the treatment of MS, with the main focus on the choice and management of DMTs, as well as present a review of the scientific rationale supporting therapeutic strategies in MS. RESUMO O crescent arsenal terapêutico na esclerose múltipla (EM) tem permitido tratamentos mais efetivos e personalizados, mas a escolha e o manejo das terapias modificadoras da doença (TMDs) tem se tornado cada vez mais complexos. Neste contexto, especialistas do Comitê Brasileiro de Tratamento e Pesquisa em Esclerose Múltipla e do Departamento Científico de Neuroimunologia da Academia Brasileira de Neurologia reuniram-se para estabelecer este Consenso Brasileiro para o Tratamento da EM, baseados no entendimento de que neurologistas devem ter a possibilidade de prescrever TMDs para EM de acordo com o que é melhor para cada paciente, com base em evidências e práticas atualizadas. Por meio deste documento, propomos recomendações práticas para o tratamento da EM, com foco principal na escolha e no manejo das TMDs, e revisamos os argumentos que embasam as estratégias de tratamento na EM.

Caprine arthritis encephalitis causes considerable losses in goat production. The main form of the caprine arthritis encephalitis virus transmission is through the ingestion of colostrum or milk from infected females. However, some transmissions cannot be explained in this manner. Therefore, this study aimed to evaluate transplacental transmission of caprine arthritis encephalitis virus. Blood samples were collected from 283 newborn kids of Anglo-Nubian and Saanen breeds born from seropositive and seronegative goats. Samples were collected immediately after birth and analyzed with agarose gel immunodiffusion and western blot. All samples were negative in the agarose gel immunodiffusion. However, the western blot test demonstrated that four kids were born positive for caprine arthritis encephalitis virus. This result indicates that although in a low frequency (1.4%), there is a possibility of transplacental transmission of small ruminant lentivirus. RESUMO: A artrite encefalite caprina causa perdas consideráveis para a produção caprina. A principal forma de transmissão do vírus da artrite encefalite caprina é a ingestão de colostro ou leite de fêmeas infectadas. No entanto, algumas transmissões não podem ser explicadas por esta via. Dessa forma, este estudo teve como objetivo avaliar a transmissão do vírus da artrite encefalite caprina por via transplacentária (vertical). Foram realizadas coletas de sangue em 283 crias recém-nascidas das raças Anglo-Nubiana e Saanen, provenientes de progenitores soropositivos e soronegativos. As amostras foram coletadas logo após o nascimento e analisadas pelas técnicas de imunodifusão em gel de agarose e western blot. No teste de imunodifusão em gel de agarose, nenhum cabrito foi detectado reagente. Porém, no teste de western blot, quatro cabritos nasceram soropositivos. Esse resultado indica que, apesar de baixa frequência (1,4%), existe a possibilidade de transmissão via transplacentária do lentivírus de pequenos ruminantes.

Submitted by Tauane Esteves (tauanefe@stj.jus.br) on 2018-09-03T18:36:33Z No. of bitstreams: 2 constitutional_process_construction_dias.pdf: 584151 bytes, checksum: f5f3d676bdf382fca77c14398845c89c (MD5) license.txt: 1239 bytes, checksum: c9b4c351324448672315a00808efb725 (MD5) Approved for entry into archive by betanial@stj.jus.br (betanial@stj.jus.br) on 2018-09-04T19:16:37Z (GMT) No. of bitstreams: 2 constitutional_process_construction_dias.pdf: 584151 bytes, checksum: f5f3d676bdf382fca77c14398845c89c (MD5) license.txt: 1239 bytes, checksum: c9b4c351324448672315a00808efb725 (MD5) Made available in DSpace on 2018-09-04T19:16:37Z (GMT). No. of bitstreams: 2 constitutional_process_construction_dias.pdf: 584151 bytes, checksum: f5f3d676bdf382fca77c14398845c89c (MD5) license.txt: 1239 bytes, checksum: c9b4c351324448672315a00808efb725 (MD5) Previous issue date: 2018 Demonstra que o processo constitucional contribui para fortalecer a legitimidade democrática do Estado, tanto para o processo constitucional legislativo quanto para o processo constitucional jurisdicional.

Understanding the energy consumption patterns of different types of consumers is essential in any planning of energy distribution. However, obtaining consumption information for single individuals is often either not possible or too expensive. Therefore, we consider data from aggregations of energy use, that is, from sums of individuals' energy use, where each individual falls into one of C consumer classes. Unfortunately, the exact number of individuals of each class may be unknown: consumers do not always report the appropriate class, due to various factors including differential energy rates for different consumer classes. We develop a methodology to estimate the expected energy use of each class as a function of time and the true number of consumers in each class. We also provide some measure of uncertainty of the resulting estimates. To accomplish this, we assume that the expected consumption is a function of time that can be well approximated by a linear combination of B-splines. Individual consumer perturbations from this baseline are modeled as B-splines with random coefficients. We treat the reported numbers of consumers in each category as random variables with distribution depending on the true number of consumers in each class and on the probabilities of a consumer in one class reporting as another class. We obtain maximum likelihood estimates of all parameters via a maximization algorithm. We introduce a special numerical trick for calculating the maximum likelihood estimates of the true number of consumers in each class. We apply our method to a data set and study our method via simulation., 31 pages, 9 figures and 5 tables

Nonparametric density estimation is of great importance when econometricians want to model the probabilistic or stochastic structure of a data set. This comprehensive review summarizes the most important theoretical aspects of kernel density estimation and provides an extensive description of classical and modern data analytic methods to compute the smoothing parameter. Throughout the text, several references can be found to the most up-to-date and cut point research approaches in this area, while econometric data sets are analyzed as examples. Lastly, we present SIZer, a new approach introduced by Chaudhuri and Marron (2000), whose objective is to analyze the visible features representing important underlying structures for different bandwidths.

Nonparametric density estimation is of great importance when econometricians want to model the probabilistic or stochastic structure of a data set. This comprehensive review summarizes the most important theoretical aspects of kernel density estimation and provides an extensive description of classical and modern data analytic methods to compute the smoothing parameter. Throughout the text, several references can be found to the most up-to-date and cut point research approaches in this area, while econometric data sets are analyzed as examples. Lastly, we present SIZer, a new approach introduced by Chaudhuri and Marron (2000), whose objective is to analyze the visible features representing important underlying structures for different bandwidths.

Submitted by Regina Mello (mrmello@inmetro.gov.br) on 2011-02-11T11:18:12Z No. of bitstreams: 1 2006_RipperGarciaDiasInternoise 02.pdf: 956960 bytes, checksum: 016b8abbad23513e9be59603695ef04c (MD5) Approved for entry into archive by Claudia Araujo(caraujo@inmetro.gov.br) on 2011-02-28T17:05:02Z (GMT) No. of bitstreams: 1 2006_RipperGarciaDiasInternoise 02.pdf: 956960 bytes, checksum: 016b8abbad23513e9be59603695ef04c (MD5) Made available in DSpace on 2011-02-28T17:11:24Z (GMT). No. of bitstreams: 1 2006_RipperGarciaDiasInternoise 02.pdf: 956960 bytes, checksum: 016b8abbad23513e9be59603695ef04c (MD5) Previous issue date: 2006 ABSTRACT: This paper presents an interferometric system built in the Brazilian National Institute of Metrology for the primary calibration of accelerometers. The theory of the calibration method is reviewed, the experimental set-up is described and some results are presented. 9 p.: il.

Submitted by Regina Mello (mrmello@inmetro.gov.br) on 2011-02-11T11:10:38Z No. of bitstreams: 1 2006_RipperGarciaDiasAIVELA.pdf: 482446 bytes, checksum: 564090d53db15f3be06a9e19265b691a (MD5) Approved for entry into archive by Claudia Araujo(caraujo@inmetro.gov.br) on 2011-02-28T16:36:43Z (GMT) No. of bitstreams: 1 2006_RipperGarciaDiasAIVELA.pdf: 482446 bytes, checksum: 564090d53db15f3be06a9e19265b691a (MD5) Made available in DSpace on 2011-02-28T17:07:01Z (GMT). No. of bitstreams: 1 2006_RipperGarciaDiasAIVELA.pdf: 482446 bytes, checksum: 564090d53db15f3be06a9e19265b691a (MD5) Previous issue date: 2006 ABSTRACT: This paper presents an automated accelerometer calibration system based on an homodyne quadrature interferometer. The vibration exciter and the interferometer are mounted on separate seismic blocks. To minimize the influence of low frequency noise due to the relative movement between the blocks, a high-pass recursive moving average filtering algorithm is implemented. The vibration and the measuring system are fully synchronized. A flexible setting of the acquisition rate is used to improve the computational efficiency and allow the calibration at any desired frequency within the frequency range from 10 Hz to 10 kHz. The theory of the method is briefly described. The experimental set-up is presented and some results are given. 10 p. : il.