Interindividual Differences in Leg Muscle Mass and Pyruvate Kinase Activity Correlate with Interindividual Differences in Jumping Performance of Hyla multilineata

Frog jumping is an excellent model system for examining the structural basis of interindividual variation in burst locomotor performance. Some possible factors that affect jump performance, such as total body size, hindlimb length, muscle mass, and muscle mechanical and biochemical properties, were analysed at the interindividual (intraspecies) level in the tree frog Hyla multilineata. The aim of this study was to determine which of these physiological and anatomical variables both vary between individuals and are correlated with interindividual variation in jump performance. The model produced via stepwise linear regression analysis of absolute data suggested that 62% of the interindividual variation in maximum jump distance could be explained by a combination of interindividual variation in absolute plantaris muscle mass, total hindlimb muscle mass ( excluding plantaris muscle), and pyruvate kinase activity. When body length effects were removed, multiple regression indicated that the same independent variables explained 43% of the residual interindividual variation in jump distance. This suggests that individuals with relatively large jumping muscles and high pyruvate kinase activity for their body size achieved comparatively large maximal jump distances for their body size.

Water quality condition and trend in North Queensland waterways

The Queensland Environmental Protection Agency monitored water quality at 133 sites in North Queensland waterways between Cooktown and Bundaburg from 1992 to 2001. Condition of the waterways was rated by comparing recent data with the Queensland Water Quality Guidelines. Long-term trends were analysed using a censored regression technique that incorporates the effects of flow, temperature, seasonality and allows for long-term non-linear trends. Many sites were in good condition; those in poor condition were usually impacted by point source discharges; those in moderate condition were usually impacted by agricultural land use. There were no consistent long-term trends across the whole region. Recommendations for future programs include incorporating pressure indicators, ensuring high standards of quality assurance, including covariates such as rainfall in trend assessment and continuing programs over more than 10 years to allow detection of trends due to changes in land-use. (c) 2004 Elsevier Ltd. All rights reserved.

Analytical solutions of linear finite- and small-strain one-dimensional consolidation

Analytical solutions are presented for linear finite-strain one-dimensional consolidation of initially unconsolidated soil layers with surcharge loading for both one- and two-way drainage. These solutions complement earlier solutions for initially unconsolidated soil layers without surcharge and initially normally consolidated soil layers with surcharge. Small-strain solutions for the consolidation of initially unconsolidated soil layers with surcharge loading are also presented, and the relationship between the earlier solutions for initially unconsolidated soil without surcharge and the corresponding small-strain solutions, which was not addressed in the earlier work, is clarified. The new solutions for initially unconsolidated soil with surcharge loading can be applied to the analysis of low stress consolidation tests and to the partial validation of numerical solutions of non-linear finite-strain consolidation. They also clarify a formerly perplexing aspect of finite-strain solution charts first noted in numerical solutions. Copyright (C) 2004 John Wiley Sons, Ltd.

Genetic and environmental influences on extreme personality dispositions in adolescent female twins

Background: The objective was to determine whether the pattern of environmental and genetic influences on deviant personality scores differs from that observed for the normative range of personality, comparing results in adolescent and adult female twins. Methods: A sample of 2,796 female adolescent twins ascertained from birth records provided Junior Eysenck Personality Questionnaire data. The average age of the sample was 17.0 years ( S. D. 2.3). Genetic analyses of continuous and extreme personality scores were conducted. Results were compared for 3,178 adult female twins. Results: Genetic analysis of continuous traits in adolescent female twins were similar to findings in adult female twins, with genetic influences accounting for between 37% and 44% of the variance in Extraversion (Ex), Neuroticism (N), and Social Non-Conformity (SNC), with significant evidence of shared environmental influences (19%) found only for SNC in the adult female twins. Analyses of extreme personality characteristics, defined categorically, in the adolescent data and replicated in the adult female data, yielded estimates for high N and high SNC that deviated substantially (p < .05) from those obtained in the continuous trait analyses, and provided suggestive evidence that shared family environment may play a more important role in determining personality deviance than has been previously found when personality is viewed continuously. However, multiple-threshold models that assumed the same genetic and environmental determinants of both normative range variation and extreme scores gave acceptable fits for each personality dimension. Conclusions: The hypothesis of differences in genetic or environmental factors responsible for N and SNC among female twins with scores in the extreme versus normative ranges was partially supported, but not for Ex.

Elasticity, yielding and episodicity in simple models of mantle convection

We explore the implications of refinements in the mechanical description of planetary constituents on the convection modes predicted by finite-element simulations. The refinements consist in the inclusion of incremental elasticity, plasticity (yielding) and multiple simultaneous creep mechanisms in addition to the usual visco-plastic models employed in the context of unified plate-mantle models. The main emphasis of this paper rests on the constitutive and computational formulation of the model. We apply a consistent incremental formulation of the non-linear governing equations avoiding the computationally expensive iterations that are otherwise necessary to handle the onset of plastic yield. In connection with episodic convection simulations, we point out the strong dependency of the results on the choice of the initial temperature distribution. Our results also indicate that the inclusion of elasticity in the constitutive relationships lowers the mechanical energy associated with subduction events.

Bifurcations in the non-dissipative dynamics of ultra cold atoms

We present the first experimental observation of several bifurcations in a controllable non-linear Hamiltonian system. Dynamics of cold atoms are used to test predictions of non-linear, non-dissipative Hamiltonian dynamics.

EXPERIÊNCIAS AFETIVAS NO CONTEXTO ORGANIZACIONAL E SEU IMPACTO SOBRE O BEM-ESTAR NO TRABALHO

Em ambiente de elevada pressão, competição e necessidade de criação de diferenciais consistentes que venham contribuir com a longevidade das organizações, nota-se a busca e, às vezes, radicais transformações nos modelos de gestão de negócios e gestão do ser humano no meio empresarial. No campo central dos estudos atuais acerca do comportamento humano e de suas relações com as diversas instituições em que o homem se vê inserido, figuram os esforços voltados à compreensão do papel e valor da contribuição do ser humano ao ambiente de trabalho e fortalecimento das organizações. Crescentes se mostram a preocupação e o entendimento sobre os fatores que impactam o bem-estar geral, o bem-estar no trabalho, a saúde dos trabalhadores e as variáveis emocionais oriundas das relações interpessoais comuns a todo organismo social. A combinação de temas emergentes e ricos em significância como bem-estar no trabalho, satisfação e envolvimento com o trabalho, comprometimento organizacional afetivo, emoções, afetos e sentimentos, caracterizam-se como um vasto e instigante campo de pesquisa para uma adaptação mais ampla do ser humano ao ambiente organizacional. O presente estudo teve como objetivo submeter ao teste empírico as relações entre experiências afetivas no contexto organizacional e três dimensões de bem-estar no trabalho - satisfação no trabalho, envolvimento com o trabalho e comprometimento organizacional afetivo. A amostra foi composta por 253 profissionais de uma indústria metalúrgica de autopeças na grande São Paulo, sendo 213 do sexo masculino e 29 do sexo feminino, com maior freqüência na faixa etária compreendida entre 26 a 30 anos, distribuída entre solteiros e casados. Para a coleta de dados foi utilizado um questionário de auto-preenchimento com quatro escalas que avaliaram afetos positivos e negativos, satisfação no trabalho, envolvimento com o trabalho e comprometimento organizacional afetivo. A análise dos dados foi feita por meio do SPSS, versão 16.0 e diversos sub-programas permitiram realizar análises descritivas bem como calcular modelos de regressão linear para verificar o impacto de afetos positivos e negativos sobre bem-estar no trabalho. Os resultados deste estudo revelaram que o principal preditor das dimensões de bem-estar no trabalho foram os afetos positivos. Assim, parece ser adequado afirmar que bem-estar no trabalho seja um estado psicológico sustentado, em especial, pela vivência de emoções positivas no contexto organizacional. Sugere-se que a promoção da saúde e do bem-estar dentro das organizações sejam focos de estudos futuros, representando valiosa contribuição aos campos de conhecimento da psicologia da saúde e da psicologia organizacional, bem como ao conseqüente fortalecimento dos vínculos entre empresa e trabalhadores.(AU)

Efficient training of RBF networks for classification.

Radial Basis Function networks with linear outputs are often used in regression problems because they can be substantially faster to train than Multi-layer Perceptrons. For classification problems, the use of linear outputs is less appropriate as the outputs are not guaranteed to represent probabilities. We show how RBFs with logistic and softmax outputs can be trained efficiently using the Fisher scoring algorithm. This approach can be used with any model which consists of a generalised linear output function applied to a model which is linear in its parameters. We compare this approach with standard non-linear optimisation algorithms on a number of datasets.

Efficient training of RBF networks for classification

Radial Basis Function networks with linear outputs are often used in regression problems because they can be substantially faster to train than Multi-layer Perceptrons. For classification problems, the use of linear outputs is less appropriate as the outputs are not guaranteed to represent probabilities. In this paper we show how RBFs with logistic and softmax outputs can be trained efficiently using algorithms derived from Generalised Linear Models. This approach is compared with standard non-linear optimisation algorithms on a number of datasets.

A comparison of linear forecasting models and neural networks:an application to Euro inflation and Euro Divisia

Linear models reach their limitations in applications with nonlinearities in the data. In this paper new empirical evidence is provided on the relative Euro inflation forecasting performance of linear and non-linear models. The well established and widely used univariate ARIMA and multivariate VAR models are used as linear forecasting models whereas neural networks (NN) are used as non-linear forecasting models. It is endeavoured to keep the level of subjectivity in the NN building process to a minimum in an attempt to exploit the full potentials of the NN. It is also investigated whether the historically poor performance of the theoretically superior measure of the monetary services flow, Divisia, relative to the traditional Simple Sum measure could be attributed to a certain extent to the evaluation of these indices within a linear framework. Results obtained suggest that non-linear models provide better within-sample and out-of-sample forecasts and linear models are simply a subset of them. The Divisia index also outperforms the Simple Sum index when evaluated in a non-linear framework. © 2005 Taylor & Francis Group Ltd.

Motion sharpening and contrast:Gain control precedes compressive non-linearity?

Blurred edges appear sharper in motion than when they are stationary. We (Vision Research 38 (1998) 2108) have previously shown how such distortions in perceived edge blur may be accounted for by a model which assumes that luminance contrast is encoded by a local contrast transducer whose response becomes progressively more compressive as speed increases. If the form of the transducer is fixed (independent of contrast) for a given speed, then a strong prediction of the model is that motion sharpening should increase with increasing contrast. We measured the sharpening of periodic patterns over a large range of contrasts, blur widths and speeds. The results indicate that whilst sharpening increases with speed it is practically invariant with contrast. The contrast invariance of motion sharpening is not explained by an early, static compressive non-linearity alone. However, several alternative explanations are also inconsistent with these results. We show that if a dynamic contrast gain control precedes the static non-linear transducer then motion sharpening, its speed dependence, and its invariance with contrast, can be predicted with reasonable accuracy. © 2003 Elsevier Science Ltd. All rights reserved.

Role of β3-adrenergic receptors in the action of a tumour lipid mobilizing factor

Induction of lipolysis in murine white adipocytes, and stimulation of adenylate cyclase in adipocyte plasma membranes, by a tumour-produced lipid mobilizing factor, was attenuated by low concentrations (10-7-10-5M) of the specific β3-adrenoceptor antagonist SR59230A. Lipid mobilizing factor (250 nM) produced comparable increases in intracellular cyclic AMP in CHOKI cells transfected with the human β3-adrenoceptor to that obtained with isoprenaline (1 nM). In both cases cyclic AMP production was attenuated by SR59230A confirming that the effect is mediated through a β3-adrenoceptor. A non-linear regression analysis of binding of lipid mobilizing factor to the β3-adrenoceptor showed a high affinity binding site with a Kd value 78±45 nM and a Bmax value (282±1 fmole mg protein-1) comparable with that of other β3-adrenoceptor agonists. These results suggest that lipid mobilizing factor induces lipolysis through binding to a β3-adrenoceptor. © 2002 The Cancer Research Campaign.

Statnote 27: Principal components analysis (PCA)

In Statnotes 24 and 25, multiple linear regression, a statistical method that examines the relationship between a single dependent variable (Y) and two or more independent variables (X), was described. The principle objective of such an analysis was to determine which of the X variables had a significant influence on Y and to construct an equation that predicts Y from the X variables. ‘Principal components analysis’ (PCA) and ‘factor analysis’ (FA) are also methods of examining the relationships between different variables but they differ from multiple regression in that no distinction is made between the dependent and independent variables, all variables being essentially treated the same. Originally, PCA and FA were regarded as distinct methods but in recent times they have been combined into a single analysis, PCA often being the first stage of a FA. The basic objective of a PCA/FA is to examine the relationships between the variables or the ‘structure’ of the variables and to determine whether these relationships can be explained by a smaller number of ‘factors’. This statnote describes the use of PCA/FA in the analysis of the differences between the DNA profiles of different MRSA strains introduced in Statnote 26.

Neural network control of a gas turbine

In this paper we explore the practical use of neural networks for controlling complex non-linear systems. The system used to demonstrate this approach is a simulation of a gas turbine engine typical of those used to power commercial aircraft. The novelty of the work lies in the requirement for multiple controllers which are used to maintain system variables in safe operating regions as well as governing the engine thrust.

Techniques to improve forecasting models: applications to energy demand and price

This thesis is a study of three techniques to improve performance of some standard fore-casting models, application to the energy demand and prices. We focus on forecasting demand and price one-day ahead. First, the wavelet transform was used as a pre-processing procedure with two approaches: multicomponent-forecasts and direct-forecasts. We have empirically compared these approaches and found that the former consistently outperformed the latter. Second, adaptive models were introduced to continuously update model parameters in the testing period by combining ?lters with standard forecasting methods. Among these adaptive models, the adaptive LR-GARCH model was proposed for the fi?rst time in the thesis. Third, with regard to noise distributions of the dependent variables in the forecasting models, we used either Gaussian or Student-t distributions. This thesis proposed a novel algorithm to infer parameters of Student-t noise models. The method is an extension of earlier work for models that are linear in parameters to the non-linear multilayer perceptron. Therefore, the proposed method broadens the range of models that can use a Student-t noise distribution. Because these techniques cannot stand alone, they must be combined with prediction models to improve their performance. We combined these techniques with some standard forecasting models: multilayer perceptron, radial basis functions, linear regression, and linear regression with GARCH. These techniques and forecasting models were applied to two datasets from the UK energy markets: daily electricity demand (which is stationary) and gas forward prices (non-stationary). The results showed that these techniques provided good improvement to prediction performance.