Implantação de CGH's na Amazônia: uma visão global com ênfase nos aspectos hidrológicos, tecnológicos, ambientais e financeiros

Um problema de grande relevância social na Amazônia é o fato das pequenas comunidades isoladas não serem contempladas pelos benefícios dos grandes empreendimentos hidrelétricos instalados na região. Uma solução alternativa a para este problema, é o aproveitamento da grande malha de pequenos rios e igarapés da região a partir da implantação de Centrais Geradoras Hidrelétricas – CGH’s (antigas mini e microcentrais).. Dentro deste contexto, o presente trabalho analisa e discute certos aspectos gerais inerentes à implantação das CGH’s, e principalmente, trazendo-os à realidade das pequenas bacias Amazônicas. Os aspectos a serem abordados neste trabalho dizem respeito às avaliações preliminares de terreno, aspectos hidrológicos, tecnológicos, ambientais e financeiros. Os aspectos são analisados de forma global para implantação de CGH’s e suas etapas, também analisados e aplicados a um estudo de caso – implantação da CGH irmã Dorothy na pequena bacia hidrográfica do Igarapé são João em Anapú-pa, onde foi possível a utilização de metodologia existente para um estudo aprimorado de implantação de CGH’s na Amazônia. No âmbito hidrológico, utilizou-se um modelo chuva-vazão desenvolvido por Blanco 2005 e aplicou a pequenas bacias da Amazônia que não possuem registros de vazão. Nos aspectos tecnológicos utilizou ferramentas computacionais para predição de desempenho de turbinas axiais de baixa queda adaptas ao relevo da região, e simulados para a turbina axial a ser implantada na CGH irmã Dorothy. No contexto ambiental atualmente há forte cobrança pelas autoridades competentes locais para realização do estudo ambiental inerente ao aproveitamento, e se tratando da região Amazônica, ambientalmente muita agredida pela ação do homem, os estudos devem ser bem definidos, apontando os possíveis impactos que podem ser causados pela CGH, descritos no RAS (Relatório Ambiental Simplificado) anexo deste trabalho. Desta forma foi desenvolvido um método para cálculo e simulação da área inundada para implantação de CGH’s na Amazônia, aplicado à CGH irmã Dorothy. No âmbito financeiro, são raras as informações referentes aos custos de implantação de CGH’s na Amazônia. Assim, foram levantados os custos referentes à implantação da CGH irmã Dorothy e comparados a custos de CGH’s e de geradores a diesel disponíveis na literatura.

Waist circumference in predicting gestational diabetes mellitus

Background: To evaluate waist circumference (WC) measured at 20-24 weeks of gestation as a predictor of gestational diabetes mellitus (GDM).Methods: This cross-sectional study included 240 women at 20-24 weeks of gestation. At enrollment, WC was measured, and both prepregnancy and gestational body mass index (BMI) were estimated. According to the results of 75-g oral glucose tolerance test (OGTT) performed at 24-28 weeks, subjects were allocated into two groups, non-GDM and GDM. WC sensitivity and specificity, and odds ratios (OR) and 95% confidence intervals for BMI and WC were estimated, and a receiver operating characteristics curve was generated.Results: Of the 240 pregnant women enrolled, 31 (13%) had GDM. Prepregnancy BMI (OR = 4.21), gestational BMI (OR = 3.17) and WC at 20-24 weeks (OR = 4.02) correlated with GDM risk. At 20-24 weeks, a WC of 85.5-88.5 cm was the optimal cutoff point for predicting GDM (Sens/Spec balance between 87.1/41.1% and 77.4/56.9%).Conclusion: At 20-24 weeks of gestation, WC values in the range of 86-88 cm showed to be a good performance in predicting GDM.

Analysis of localized muscle fatigue in elderly women with and without a history of falls using electromyographic signal frequency parameters

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Predicting soluble solid content in intact jaboticaba [Myrciaria jaboticaba (Vell.) O. Berg] fruit using near-infrared spectroscopy and chemometrics

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Predicting breeding values for milk yield of Guzera (Bos indicus) cows using random regression models

Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.

Ultrasonographic measurements of kidney fat thickness and Longissimus muscle area in predicting body composition of pregnant goats

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

MetaPPase by in silico analyses predicting the novel gene operate as H+ pumps.

The lastyears declined the discovery of compounds to use in industrial and naturaldiversity has been the best supplier for novel genes, enzymes and compounds inhigh demand by the biotechnology industry. We know immense diversity of microorganisms,yet most remains unexplored. For these reason we use the metagenômica approach toinvestigate the potential of uncultured microorganisms. With this purpose weused the metagenomic library of from Eucalyptus spp. arboretum (EAA), wedid screening to found positive clone and them was submitted to the process of shotgun,the data obtained was submitted a bioinformatics analyses. Our results showsthe hypothesis of high unexplored microbial diversity of soil are able to foundnovel genes and metagenomic approach is and allowed to isolate novel genes and insilico analyses are essential part to identify a novel Inorganicpyrophosphatase (PPase) prediction indicated the novel gene operate as H+ pumps. Thissuggests that a special feature, our work in situ will be cloning thegene expression vector for subsequent kinetic characterization and crystallization.

Aspects correlates with Scandinavian Stroke Scale for predicting early neurological impairment

Objective: To investigate the correlation between the Alberta Program Early CT Score (ASPECTS) and the Scandinavian Stroke Scale (SSS) for the evaluation of neurological impairment in patients with acute stroke. Method: 59 patients with a first acute ischemic stroke were evaluated. The ASPECTS were evaluated by 2 neurologists at admission and by another neurologist after 48 hours. The NIHSS and SSS was applied to determinate stroke severity. Correlations and agreements were analysed statistically by Spearman and Kappa tests. Results: ASPECTS was correlated with National Institute of Health Stroke Scale (NIHSS) at admission (r = -0.52; p < 0.001) and SSS (r = 0.50; p < 0.001). The ASPECTS and SSS items were most correlated with arm (r = 0.52; p < 0.001) and hand (r = 0.49; p < 0.001) motor power, and speech (r = 0.51; p < 0.001). The SSS of 25.5 shows sensitivity (68%) and specificity (72%) when associated with ASPECTS <= 7. Conclusion: The SSS can predict worst neurological impairment when associated with lower values of ASPECTS.

NIRS and iSPA-PLS for predicting total anthocyanin content in jaboticaba fruit

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Predicting embryo presence and viability

Pregnancy establishment, followed by birth of live offspring, is essential to all mammals. The biological processes leading up to pregnancy establishment, maintenance, and birth are complex and dependent on the coordinated timing of a series of events at the molecular, cellular, and physiological level. The ability to ovulate a competent oocyte, which is capable of undergoing fertilization, is only the initial step in achieving a successful pregnancy. Once fertilization has occurred and early embryonic development is initiated, early pregnancy detection is critical to provide proper prenatal care (humans) or appropriate management (domestic livestock). However, the simple presence of an embryo, early in gestation, does not guarantee the birth of a live offspring. Pregnancy loss (embryonic mortality, spontaneous abortions, etc.) has been well documented in all mammals, especially in humans and domestic livestock species, and is a major cause of reproductive loss. It has been estimated that only about 25-30 % of all fertilized oocytes in humans result in birth of a live offspring; however, identifying the embryos that will not survive to parturition has not been an easy task. Therefore, investigators have focused the identification of products in maternal circulation that permit the detection of an embryo and assessment of its well-being. This review will focus on the advances in predicting embryonic presence and viability, in vivo.

Neural models for predicting hole diameters in drilling processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Neural models for predicting hole diameters in drilling processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)