Execução Orçamentária da União em Ações e Serviços Públicos de Saúde entre 2012 e 2015 e Apuração dos Recursos Mínimos a Serem Aplicados no Referido Período

Breve histórico do Sistema Nacional de Saúde e do respectivo financiamento a partir da Emenda Constitucional da Saúde até 2015, apresenta dados afetos à execução orçamentária da União em Ações e Serviços Públicos de Saúde (ASPS) a partir da vigência da Lei Complementar nº 141, de 2012, e estima o mínimo constitucional a ser aplicado frente à legislação e às revisões do PIB pelo IBGE.

Parcellation of fMRI datasets with ICA and PLS: a data driven approach

Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM) and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of Hemodynamic Response Function (HRF) and task-related signal changes, or about the subject behaviour during the task. In this paper, we introduce a data-driven version of the spectral clustering parcellation, based on Independent Component Analysis (ICA) and Partial Least Squares (PLS) instead of the GLM. First, a number of independent components are automatically selected. Seed voxels are then obtained from the associated ICA maps and we compute the PLS latent variables between the fMRI signal of the seed voxels (which covers regional variations of the HRF) and the principal components of the signal across all voxels. Finally, we parcellate all subjects data with a spectral clustering of the PLS latent variables. We present results of the application of the proposed method on both single-subject and multi-subject fMRI datasets. Preliminary experimental results, evaluated with intra-parcel variance of GLM t-values and PLS derived t-values, indicate that this data-driven approach offers improvement in terms of parcellation accuracy over GLM based techniques.

MICROECONOMÍA POLÍTICA DE LOS PRECIOS MÍNIMOS Y MÁXIMOS: EL CASO DEL SUBSECTOR ARROCERO COSTARRICENSE

El artículo logra sistematizar y analizar con un enfoque económico diferente a los tradicionales, la problemática introducida por las políticas de precios mínimos y máximos. El estudio del sector arrocero costarricense para tal propósito, busca evidenciar la solvencia teórica para casos concretos. El modelo aplicado en tal caso, demuestra su capacidad para generar elementos adecuados a una cierta estrategia planeada a nivel de las esferas de la producción y de la circulación propias de la cadena agroalimentaria del arroz.

Programa SAS® para ajuste de curvas de retenção.

Neste trabalho apresentamos um programa SAS para ajuste de curvas de retenção,informação essencial para simulações da dinâmica da água no solo e seus impacto no rendimento agrícola de culturas. Os parâmetros são estimados utilizando métodos de quadrados mínimos não lineares, via processos iterativos implementados no procedimento NLIN (Proc NLIN) do software estatístico SAS/STAT® do SAS System. Uma das vantagens do uso desse programa, é a possibilidade de quantificar incertezas associadas às estimativas dos parâmetros da curva de retenção e aos valores preditos da umidade volumétrica para cada nível específico de tensão da água no solo. Podem ser ajustadas curvas para um grande número de estratos (ex. classes de solo, profundidades) com geração de arquivos em diversos formatos (ex. planilha Excel), contendo as informações sobre qualidade de ajuste dos modelos, estimativas de parâmetros e suas incertezas para cada estrato.

Reputational risk of banks : a study on the effects of regulatory sanctions for major european banks

Mestrado em Finanças

Resistência antimicrobiana em salmonella spp. isoladas de aviários de frangos de corte: dados parciais.

2016

Lei Complementar 141/2012 [Punições pela não aplicação dos recursos mínimos em saúde]

Trata sobre a necessidade de se aplicar, pelo gestor responsável, toda a verba destinada à saúde, sob risco de sofrer as punições cabíveis à luz da Lei Complementar 141/2012. Material produzido para utilização no curso "Responsabilidades gestoras no último ano de mandato" fornecido pela Universidade Aberta do SUS (UNA-SUS).

Aplicação dos Recursos Mínimos (15%) em Ações e Serviços Públicos em Saúde - ASPS: como cumprir o compromisso e em qual prazo? [Responsabilidades Orçamentárias e Fiscais]

Trata do prazo que o gestor público de saúde tem para realizar a aplicação mínima das verbas municipais destinadas à saúde pública. Material produzido para utilização no curso "Responsabilidades gestoras no último ano de mandato" fornecido pela Universidade Aberta do SUS (UNA-SUS).

Responsabilidades orçamentárias e fiscais: aplicação dos recursos mínimos (15%) em Ações e Serviços Públicos em Saúde - ASPS

Aborda a exigência mínima de aplicação de 15% das receitas e transferências correntes nas Ações e Serviços Públicos de Saúde (ASPS) que promovem, protegem e recuperam a saúde. Para isso são consideradas as receitas: pagas, as liquidadas e inscritas em Restos a Pagar; e as empenhadas e não liquidadas inscritas em Restos a Pagar até o limite da disponibilidade de caixa do exercício. Aborda também as penalidades pelo não cumprimento das ASPS.

Ihwg-μnir: A Miniaturised Near-infrared Gas Sensor Based On Substrate-integrated Hollow Waveguides Coupled To A Micro-nir-spectrophotometer.

A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.

Study Of The Homogeneity Of Drug Loaded In Polymeric Films Using Near-infrared Chemical Imaging And Split-plot Design.

Split-plot design (SPD) and near-infrared chemical imaging were used to study the homogeneity of the drug paracetamol loaded in films and prepared from mixtures of the biocompatible polymers hydroxypropyl methylcellulose, polyvinylpyrrolidone, and polyethyleneglycol. The study was split into two parts: a partial least-squares (PLS) model was developed for a pixel-to-pixel quantification of the drug loaded into films. Afterwards, a SPD was developed to study the influence of the polymeric composition of films and the two process conditions related to their preparation (percentage of the drug in the formulations and curing temperature) on the homogeneity of the drug dispersed in the polymeric matrix. Chemical images of each formulation of the SPD were obtained by pixel-to-pixel predictions of the drug using the PLS model of the first part, and macropixel analyses were performed for each image to obtain the y-responses (homogeneity parameter). The design was modeled using PLS regression, allowing only the most relevant factors to remain in the final model. The interpretation of the SPD was enhanced by utilizing the orthogonal PLS algorithm, where the y-orthogonal variations in the design were separated from the y-correlated variation.

Petroleomics By Electrospray Ionization Ft-icr Mass Spectrometry Coupled To Partial Least Squares With Variable Selection Methods: Prediction Of The Total Acid Number Of Crude Oils.

Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.

Classification Of Frankfurters By Ft-raman Spectroscopy And Chemometric Methods.

Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.

Fast And Direct Na And K Determination In Table, Marine, And Low-sodium Salts By X-ray Fluorescence And Chemometrics.

X-ray fluorescence (XRF) is a fast, low-cost, nondestructive, and truly multielement analytical technique. The objectives of this study are to quantify the amount of Na(+) and K(+) in samples of table salt (refined, marine, and light) and to compare three different methodologies of quantification using XRF. A fundamental parameter method revealed difficulties in quantifying accurately lighter elements (Z < 22). A univariate methodology based on peak area calibration is an attractive alternative, even though additional steps of data manipulation might consume some time. Quantifications were performed with good correlations for both Na (r = 0.974) and K (r = 0.992). A partial least-squares (PLS) regression method with five latent variables was very fast. Na(+) quantifications provided calibration errors lower than 16% and a correlation of 0.995. Of great concern was the observation of high Na(+) levels in low-sodium salts. The presented application may be performed in a fast and multielement fashion, in accordance with Green Chemistry specifications.

Determination Of Detergent And Dispensant Additives In Gasoline By Ring-oven And Near Infrared Hypespectral Imaging.

A method using the ring-oven technique for pre-concentration in filter paper discs and near infrared hyperspectral imaging is proposed to identify four detergent and dispersant additives, and to determine their concentration in gasoline. Different approaches were used to select the best image data processing in order to gather the relevant spectral information. This was attained by selecting the pixels of the region of interest (ROI), using a pre-calculated threshold value of the PCA scores arranged as histograms, to select the spectra set; summing up the selected spectra to achieve representativeness; and compensating for the superimposed filter paper spectral information, also supported by scores histograms for each individual sample. The best classification model was achieved using linear discriminant analysis and genetic algorithm (LDA/GA), whose correct classification rate in the external validation set was 92%. Previous classification of the type of additive present in the gasoline is necessary to define the PLS model required for its quantitative determination. Considering that two of the additives studied present high spectral similarity, a PLS regression model was constructed to predict their content in gasoline, while two additional models were used for the remaining additives. The results for the external validation of these regression models showed a mean percentage error of prediction varying from 5 to 15%.