Non-Linear Unsteady Aerodynamic Response Approximation Using Multi-Layer Functionals

Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.

Dynamic network data envelopment analysis for university hospitals evaluation

ABSTRACT OBJECTIVE To develop an assessment tool to evaluate the efficiency of federal university general hospitals. METHODS Data envelopment analysis, a linear programming technique, creates a best practice frontier by comparing observed production given the amount of resources used. The model is output-oriented and considers variable returns to scale. Network data envelopment analysis considers link variables belonging to more than one dimension (in the model, medical residents, adjusted admissions, and research projects). Dynamic network data envelopment analysis uses carry-over variables (in the model, financing budget) to analyze frontier shift in subsequent years. Data were gathered from the information system of the Brazilian Ministry of Education (MEC), 2010-2013. RESULTS The mean scores for health care, teaching and research over the period were 58.0%, 86.0%, and 61.0%, respectively. In 2012, the best performance year, for all units to reach the frontier it would be necessary to have a mean increase of 65.0% in outpatient visits; 34.0% in admissions; 12.0% in undergraduate students; 13.0% in multi-professional residents; 48.0% in graduate students; 7.0% in research projects; besides a decrease of 9.0% in medical residents. In the same year, an increase of 0.9% in financing budget would be necessary to improve the care output frontier. In the dynamic evaluation, there was progress in teaching efficiency, oscillation in medical care and no variation in research. CONCLUSIONS The proposed model generates public health planning and programming parameters by estimating efficiency scores and making projections to reach the best practice frontier.

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS

ABSTRACT The present study aimed at evaluating the heterotic group formation in guava based on quantitative descriptors and using artificial neural network (ANN). For such, we evaluated eight quantitative descriptors. Large genetic variability was found for the eight quantitative traits in the 138 genotypes of guava. The artificial neural network technique determined that the optimal number of groups was three. The grouping consistency was determined by linear discriminant analysis, which obtained classification percentage of the groups, with a value of 86 %. It was concluded that the artificial neural network method is effective to detect genetic divergence and heterotic group formation.

Rainfall erosivity for the State of Rio de Janeiro estimated by artificial neural network

The Artificial Neural Networks (ANNs) are mathematical models method capable of estimating non-linear response plans. The advantage of these models is to present different responses of the statistical models. Thus, the objective of this study was to develop and to test ANNs for estimating rainfall erosivity index (EI30) as a function of the geographical location for the state of Rio de Janeiro, Brazil and generating a thematic visualization map. The characteristics of latitude, longitude e altitude using ANNs were acceptable to estimating EI30 and allowing visualization of the space variability of EI30. Thus, ANN is a potential option for the estimate of climatic variables in substitution to the traditional methods of interpolation.

Determination of the influence of the variation of reducing and non-reducing sugars on coffee quality with use of artificial neural network

The present study aimed at evaluating the use of Artificial Neural Network to correlate the values resulting from chemical analyses of samples of coffee with the values of their sensory analyses. The coffee samples used were from the Coffea arabica L., cultivars Acaiá do Cerrado, Topázio, Acaiá 474-19 and Bourbon, collected in the southern region of the state of Minas Gerais. The chemical analyses were carried out for reducing and non-reducing sugars. The quality of the beverage was evaluated by sensory analysis. The Artificial Neural Network method used values from chemical analyses as input variables and values from sensory analysis as output values. The multiple linear regression of sensory analysis values, according to the values from chemical analyses, presented a determination coefficient of 0.3106, while the Artificial Neural Network achieved a level of 80.00% of success in the classification of values from the sensory analysis.

Cloning, sequence analysis, and expression of cDNA coding for the major house dust mite allergen, Der f 1, in Escherichia coli

Our objective was to clone, express and characterize adult Dermatophagoides farinae group 1 (Der f 1) allergens to further produce recombinant allergens for future clinical applications in order to eliminate side reactions from crude extracts of mites. Based on GenBank data, we designed primers and amplified the cDNA fragment coding for Der f 1 by nested-PCR. After purification and recovery, the cDNA fragment was cloned into the pMD19-T vector. The fragment was then sequenced, subcloned into the plasmid pET28a(+), expressed in Escherichia coli BL21 and identified by Western blotting. The cDNA coding for Der f 1 was cloned, sequenced and expressed successfully. Sequence analysis showed the presence of an open reading frame containing 966 bp that encodes a protein of 321 amino acids. Interestingly, homology analysis showed that the Der p 1 shared more than 87% identity in amino acid sequence with Eur m 1 but only 80% with Der f 1. Furthermore, phylogenetic analyses suggested that D. pteronyssinus was evolutionarily closer to Euroglyphus maynei than to D. farinae, even though D. pteronyssinus and D. farinae belong to the same Dermatophagoides genus. A total of three cysteine peptidase active sites were found in the predicted amino acid sequence, including 127-138 (QGGCGSCWAFSG), 267-277 (NYHAVNIVGYG) and 284-303 (YWIVRNSWDTTWGDSGYGYF). Moreover, secondary structure analysis revealed that Der f 1 contained an a helix (33.96%), an extended strand (17.13%), a ß turn (5.61%), and a random coil (43.30%). A simple three-dimensional model of this protein was constructed using a Swiss-model server. The cDNA coding for Der f 1 was cloned, sequenced and expressed successfully. Alignment and phylogenetic analysis suggests that D. pteronyssinus is evolutionarily more similar to E. maynei than to D. farinae.

A network society communicative model for optimizing the Refugee Status Determination (RSD) procedures

This article recommends a new way to improve Refugee Status Determination (RSD) procedures by proposing a network society communicative model based on active involvement and dialogue among all implementing partners. This model, named after proposals from Castells, Habermas, Apel, Chimni, and Betts, would be mediated by the United Nations High Commissioner for Refugees (UNHCR), whose role would be modeled after that of the International Committee of the Red Cross (ICRC) practice.

The international implications of the Chinese model of development in the Global South: Asian Consensus as a network power

This paper analyzes People's Republic of China (PRC) economic and political ascendance in the 21st century focusing on the evolution of the sui generis economic development model and its significances of the evolution of relationship between China and the developing countries in the peripheral "Global South." The objective of this article is to analyze the relationship between China and the Global South (Africa and South America) in the 21st century, characterized as a new Center-periphery global network power based on trade and investment that we call as "Asian Consensus."

Testes para verificar a igualdade de parâmetros e a identidade de modelos de regressão não-linear em dados de experimento com delineamento em blocos casualizados

Considerou-se o ajustamento de equações de regressão não-linear e o teste da razão de verossimilhança, com aproximações pelas estatísticas qui-quadrado e F, para testar as hipóteses de igualdade de qualquer subconjunto de parâmetros e de identidade dos modelos para dados com repetições provenientes de experimento com delineamento em blocos completos casualizados. Concluiu-se que as duas aproximações podem ser utilizadas, mas a aproximação pela estatística F deve ser preferida, principalmente para pequenas amostras.

Atributos físicos de um Latossolo Vermelho correlacionados linear e espacialmente com a consorciação de guandu com milheto

O sistema cultivo mínimo, por possibilitar pouca movimentação de solo, menor número de operações agrícolas sem incorporação dos resíduos vegetais, apresenta vantagens em razão do menor custo de preparo e da redução das perdas de solo e água. No ano agrícola de 2006/2007, na Fazenda de Ensino e Pesquisa da Faculdade de Engenharia de Ilha Solteira, SP, Brasil - FEIS/UNESP, situada nas condições do Cerrado Brasileiro, objetivou-se analisar a produtividade de massa de matéria seca da consorciação de forragem (guandu+milheto) (MSF), em função de atributos físicos do solo, tais como resistência à penetração (RP), umidade gravimétrica (UG), umidade volumétrica (UV) e densidade do solo (DS) nas profundidades de 0,0-0,10 m; 0,10-0,20 m e 0,20-0,30 m. Para tanto, foi instalado um ensaio, contendo 117 pontos amostrais, em um Latossolo Vermelho distroférrico, sob pivô central, numa área experimental de 1600 m² sob cultivo mínimo. A análise estatística constou de análise descritiva inicial dos atributos e análise das correlações lineares simples entre eles, e, finalmente, de análise geoestatística. Do ponto de vista da correlação espacial, o atributo que mais bem explica a produtividade de massa de matéria seca da consorciação é a densidade do solo na camada de 0,20-0,30 m, com uma correlação inversa, indicando que as espécies se desenvolvem bem em solos adensados.

Network dynamics in scientific knowledge acquisition: an analysis in three public universities in the state of Bahia

This paper aims to cast some light on the dynamics of knowledge networks in developing countries by analyzing the scientific production of the largest university in the Northeast of Brazil and its influence on some of the remaining regional research institutions in the state of Bahia. Using a methodology test to be employed in a larger project, the Universidade Federal da Bahia (UFBA) (Federal University of Bahia), the Universidade do Estado da Bahia (Uneb) (State of Bahia University) and the Universidade Estadual de Santa Cruz (Uesc)'s (Santa Cruz State University) scientific productions are discussed in one of their most traditionally expressive sectors in academic production - namely, the field of chemistry, using social network analysis of co-authorship networks to investigate the existence of small world phenomena and the importance of these phenomena in research performance in these three universities. The results already obtained through this research bring to light data of considerable interest concerning the scientific production in unconsolidated research universities. It shows the important participation of the UFBA network in the composition of the other two public universities research networks, indicating a possible occurrence of small world phenomena in the UFBA and Uesc networks, as well as the importance of individual researchers in consolidating research networks in peripheral universities. The article also hints that the methodology employed appears to be adequate insofar as scientific production may be used as a proxy for scientific knowledge.

Ensuring dynamic strategic fit of firms that compete globally in alliances and networks: proposing the Global SNA - Strategic Network Analysis - framework

In order to sustain their competitive advantage in the current increasingly globalized and turbulent context, more and more firms are competing globally in alliances and networks that oblige them to adopt new managerial paradigms and tools. However, their strategic analyses rarely take into account the strategic implications of these alliances and networks, considering their global relational characteristics, admittedly because of a lack of adequate tools to do so. This paper contributes to research that seeks to fill this gap by proposing the Global Strategic Network Analysis - SNA - framework. Its purpose is to help firms that compete globally in alliances and networks to carry out their strategic assessments and decision-making with a view to ensuring dynamic strategic fit from both a global and relational perspective.

Regressão linear com duplo truncamento na distribuição da variável dependente

Do problema do ajuste de uma regressão linear, quando a distribuição da variável dependente tem duplo truncamento, utilizando a função de máxima verossimilhança e um processo iterativo.