Interactive Correlation Environment (ICE) - A Statistical Web Tool for Data Collinearity Analysis

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

Validation of analytical methodology for quantification of cefazolin sodium pharmaceutical dosage form by high performance liquid chromatography to be applied for quality control in pharmaceutical industry

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

Predição da performance de corredores de endurance por meio de testes de laboratório e pista

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

Respostas da frequência de braçada e do comprimento de braçada na e acima da intensidade correspondente à máxima fase estável de lactato sanguíneo em indivíduos com diferentes níveis de performance

The main objective of this study was to analyze the behavior of variables related to swim ability at and above maximal lactate steady state (MLSS), performed at continuous and intermittent conditions in individuals with different aerobic performance levels. Participated of this study male swimmers with ages between 20 to 25 years, specialists in events of 400 m, 800 m and 1500 m and open water swims, with at least 3 years of experience in the modality. The individuals performed a maximal 400-m swim test. After this test, they were divided into two groups, in accordance with the speed attained during 400-m swim test: G1 (higher performance) and G2 (lower performance). For the determination of continuous MLSS (MLSSc), 2 to 4 trials of 30-min were performed. For the determination of the intermittent MLSS (MLSSi) 2 to 4 trials of 30-min (12 repetitions of 2 min 30 s, with 30 s of rest) were performed, in constant speed, with the first trial performed at 102.5% MLSSc. Th technical indexes, stroke rate (FB) and stroke length (CB) were determined in all tests. The SR was calculated trough recordings using the time needed to perform five stroke cycles. The SL was calculated dividing the speed by the SR. There was no significant difference on the antropometric characteristics between groups. The speed at and above MLSSc were significantly higher at G1 (1,23±0,05 e 1,27±0,06, respectively) than G2 (1,10±0,06 e 1,13±0,06, respectively). There was significant change in SL and SR in G2. In the same way, there was significant change in SL and SR only in G2, above MLSSc. Similar to continuous condition, the speeds at and above MLSSi were significantly higher in G1 (1,27±0,05 e 1,30±0,05, respectively) do que no G2 (1,14±0,07 e 1,16±0,07, respectively). There was significant change in SL and SR only in G2. There was significant change in SR and SL in both groups above MLSSi. Thus,...(Complete abstract click electronic access below)

Qualidade da semeadura e do arranquio mecanizado do amendoim

Pós-graduação em Agronomia (Ciência do Solo) - FCAV

Green Manufacturing: Relationship between Adoption of Green Operational Practices and Green Performance of Brazilian ISO 9001-Certified Firms

The present work aims at analyzing how the adoption of a proactive environmental management via green operational practices (GOPs) correlates to the Green Performance (GrP) of a given set of ISO 9001-certified firms in Brazil. To this end, we elaborated a conceptual framework about environmental management, GOPs, and GrP Such theoretical foundation supported the development of empirical research through quantitative analysis. For the analysis, 75 questionnaires were collected from ISO 9001 certified companies. Data was analyzed by with statistical tools such as descriptive analysis, correlation analysis, and Structural Equation Modeling (SEM). The results demonstrate that the adoption of GOPs, in fact, exerts a positive impact on the GrP of the firms. This work contributes to a better understanding of green manufacturing in Brazil's industrial sector

Sociocognitive performance in autism spectrum disorders and interference of the therapeutic environment

To analyze the sociocognitive performance of children and adolescents with autism spectrum disorders in two environments of language therapy, which differ as to the physical structure. Ten children and adolescents with ages between 4 and 13 years, of both genders, diagnosed with autism spectrum disorders took part in the study. For data collection, eight filming sessions were performed during individual language therapy lasting 30 minutes, being four in a room with conventional environmental organization (common room) and four in a room with specific ambiance [children's interaction core (CIC) room], interspersed during a month. For the analysis of filmed situations, the Sociocognitive Performance Protocol was used and obtained data were subjected to statistical analysis. No statistical significance was found in sociocognitive performance of 10 subjects in the common and CIC rooms, although specific differences were observed in some cases. The creation of preestablished physical environments or specific materials is not and should not be considered essential for language therapy. It is noteworthy, however, that the absence of a large volume of statistically significant data does not indicate that the results are not expressive, reiterating the need for further research in the area.

Validation of a stability-indicating HPLC method with diode array detection for the determination of beclomethasone dipropionate in aqueous suspension for nebulizer

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.