Psychometric evaluation of the Disordered Eating Attitude Scale (DEAS). English version

Eating attitudes are defined as beliefs, thoughts, feelings, behaviors and relationship with food They could influence people`s food choices and their health status Objective This study aimed to adapt from Portuguese to English the Disordered Eating Attitude Scale (DEAS) and evaluate its validity and reliability. The original scale in Portuguese was translated and adapted into English and was applied to female university students of University of Minnesota USA (n = 224). Internal consistency was determined (Cronbach`s Alpha). Convergent validity was assessed by correlations between Eating Attitude Test-26 (EAT-26) and Restrain Scale (RS). Reliability was evaluated applying twice the scale to a sub-sample (n = 30). The scale was back translated into Portuguese and compared with the original version and discrepancies were not found. The internal consistency was .76 The DEAS total score was significantly associated with EAT-26 (r = 0.65) and RS (r = 0 69) scores The correlation between test-retest was r = 09 The English version of DEAS showed appropriate internal consistency, convergent validity and test-retest reliability and will be useful to assess eating attitudes in different population groups in English spoken countries. (C) 2010 Elsevier Ltd. All rights reserved

DEVELOPMENT AND VALIDITY OF THE DISORDERED EATING ATTITUDE SCALE (DEAS)

The aim of this study was to develop and validate the Disordered Eating Attitude Scale to measure disordered eating attitudes, defined as abnormal beliefs, thoughts, feelings, behaviors, and relationship regarding food. Exploratory factor analysis was performed and internal consistency assessed in a sample of female university students (N=196). Convergent validity was acceptable based on statistically significant correlations with the Eating Attitude Test-26 and Restraint Scale. Known-groups validity was determined by comparing the student sample`s mean scores against scores of an eating disorder group (N=51). The Disordered Eating Attitude Scale comprises 25 questions and five subscales explaining 54.3% of total variance. The total scores differentiated student, bulimia, and anorexia groups. The scale should prove useful for evaluating eating attitudes in various population groups and eating disordered patients.

A comparison of two bench-scale anaerobic systems used for the treatment of dairy effluents

The objective of this work was to compare two anaerobic reactor conflgurations, a hybrid upflow anaerobic sludge blanket (UASBh) reactor and an anaerobic sequencing batch reactor with immobilised biomass (ASBBR) treating dairy effluents. The reactors were fed with effluent from the milk pasteurisation process (effluent 1-E1) and later with effluent from the same process combined with the one from the cheese manufacturing (effluent 2-E2). The ASBBR reactor showed average organic matter removal efficiency of 95.2% for E1 and 93.5% for E2, while the hybrid UASB reactor showed removal efficiencies of 90.3% and 80.1% respectively.

Climate perspective on the large-scale circulation associated with the transition of the first South Atlantic hurricane

The landfall of Cyclone Catarina on the Brazilian coast in March 2004 became known as the first documented hurricane in the South Atlantic Ocean, promoting a new view oil how large-scale features can contribute to tropical transition. The aim of this paper is to put the large-scale circulation associated with Catarina`s transition in climate perspective. This is discussed in the light of a robust pattern of spatial correlations between thermodynamic and dynamic variables of importance for hurricane formation. A discussion on how transition mechanisms respond to the present-day circulation is presented. These associations help in understanding why Catarina was formed in a region previously thought to be hurricane-free. Catarina developed over a large-scale area of thermodynamically favourable air/sea temperature contrast. This aspect explains the paradox that such a rare system developed when the sea surface temperature was slightly below average. But, although thermodynamics played an important role, it is apparent that Catarina would not have formed without the key dynamic interplay triggered by a high latitude blocking. The blocking was associated with an extreme positive phase of the Southern Annular Mode (SAM) both hemispherically and locally, and the nearby area where Catarina developed is found to be more cyclonic during the positive phase of the SAM. A conceptual model is developed and a `South Atlantic index` is introduced as a useful diagnostic of potential conditions leading to tropical transition in the area, where large-scale indices indicate trends towards more favourable atmospheric conditions for tropical cyclone formation. Copyright (c) 2008 Royal Meteorological Society

Scale architecture of the palmar and plantar epidermis of Polychrus acutirostris Spix, 1825 (Iguania, Polychrotidae) and its relationship to arboreal locomotion

In tetrapod squamates, the diversity of micro-ornamentations of the epidermis of the contact areas of hands and feet is generally associated with constraints and modalities related to locomotion. Polychrus acutirostris is a medium-sized lizard that occurs in open heterogeneous habitats in South America, such as the cerrados, caatingas, and fallow lands. It progresses slowly on branches of various diameters in its arboreal environment. It can also move more rapidly on the ground. The hands and feet are prehensile and may be considered an adaptation for grasping and climbing. Epidermal surfaces from the palmar and plantar areas of the hands and feet of P. acutirostris were prepared for SEM examination, and studied at various magnifications. They show three major levels of complexity: (1) scale types, organized in gradients of size and imbrication, (2) scalar ornamentations, organized by increasing complexity and polarity, and (3) presence of Oberhautchen showing typically iguanian honeycomb micro-ornamentations. The shape and surface structure of the scales with their pattern of micro-ornamental peaks, which improve grip, and the grasping hands and feet indicate that P. acutirostris is morpho-functionally specialized for arboreality. (C) 2009 Elsevier GmbH. All rights reserved.

Landscape and farm scale management to enhance biodiversity conservation in the cocoa producing region of southern Bahia, Brazil

In southern Bahia, Brazil, large land areas are used for the production of cocoa (Theobroma cacao), which is predominantly grown under the shade of native trees in an agroforestry system locally known as cabruca. As a dominant forest-like landscape element of the cocoa region, the cabrucas play an important role in the conservation of the region`s biodiversity. The purpose of this review is to provide the scientific basis for an action plan to reconcile cocoa production and biodiversity conservation in southern Bahia. The available research collectively highlights the diversity of responses of different species and biological groups to both the habitat quality of the cabrucas themselves and to the general characteristics of the landscape, such as the relative extent and spatial configuration of different vegetation types within the landscape mosaic. We identify factors that influence directly or indirectly the occurrence of native species in the cabrucas and the wider landscape of the cocoa region and develop recommendations for their conservation management. We show that the current scientific knowledge already provides a good basis for a biodiversity friendly management of the cocoa region of southern Bahia, although more work is needed to refine some management recommendations, especially on shade canopy composition and density, and verify their economic viability. The implementation of our recommendations should be accompanied by appropriate biological and socioeconomic monitoring and the findings should inform a broad program of adaptive management of the cabrucas and the wider cocoa landscape.

Influence of multi-scale landscape structure on the occurrence of carnivorous mammals in a human-modified savanna, Brazil

So Paulo is the most developed state in Brazil and contains few fragments of native ecosystems, generally surrounded by intensive agriculture lands. Despite this, some areas still shelter large native animals. We aimed at understanding how medium and large carnivores use a mosaic landscape of forest/savanna and agroecosystems, and how the species respond to different landscape parameters (percentage of landcover and edge density), in a multi-scale perspective. The response variables were: species richness, carnivore frequency and frequency for the three most recorded species (Puma concolor, Chrysocyon brachyurus and Leopardus pardalis). We compared 11 competing models using Akaike`s information criterion (AIC) and assessed model support using weight of AIC. Concurrent models were combinations of landcover types (native vegetation, ""cerrado"" formations, ""cerrado"" and eucalypt plantation), landscape feature (percentage of landcover and edge density) and spatial scale. Herein, spatial scale refers to the radius around a sampling point defining a circular landscape. The scales analyzed were 250 (fine), 1,000 (medium) and 2,000 m (coarse). The shape of curves for response variables (linear, exponential and power) was also assessed. Our results indicate that species with high mobility, P. concolor and C. brachyurus, were best explained by edge density of the native vegetation at a coarse scale (2,000 m). The relationship between P. concolor and C. brachyurus frequency had a negative power-shaped response to explanatory variables. This general trend was also observed for species richness and carnivore frequency. Species richness and P. concolor frequency were also well explained by a second concurrent model: edge density of cerrado at the fine (250 m) scale. A different response was recorded for L. pardalis, as the frequency was best explained for the amount of cerrado at the fine (250 m) scale. The curve of response was linearly positive. The contrasting results (P. concolor and C. brachyurus vs L. pardalis) may be due to the much higher mobility of the two first species, in comparison with the third. Still, L. pardalis requires habitat with higher quality when compared with other two species. This study highlights the importance of considering multiple spatial scales when evaluating species responses to different habitats. An important and new finding was the prevalence of edge density over the habitat extension to explain overall carnivore distribution, a key information for planning and management of protected areas.

Screening of ARHSP-TCC Patients Expands the Spectrum of SPG11 Mutations and Includes a Large Scale Gene Deletion

Autosomal recessive spastic paraplegia with thinning of corpus callosum (ARHSP-TCC) is a complex form of HSP initially described in Japan but subsequently reported to have a worldwide distribution with a particular high frequency in multiple families from the Mediterranean basin. We recently showed that ARHSP-TCC is commonly associated with mutations in SPG11/KIAA1840 on chromosome 15q. We have now screened a collection of new patients mainly originating from Italy and Brazil, in order to further ascertain the spectrum of mutations in SPG11, enlarge the ethnic origin of SPG11 patients, determine the relative frequency at the level of single Countries (i.e., Italy), and establish whether there is one or more common mutation. In 25 index cases we identified 32 mutations; 22 are novel, including 9 nonsense, 3 small deletions, 4 insertions, 1 in/del, 1 small duplication, 1 missense, 2 splice-site, and for the first time a large genomic rearrangement. This brings the total number of SPG11 mutated patients in the SPATAX collection to 111 cases in 44 families and in 17 isolated cases, from 16 Countries, all assessed using homogeneous clinical criteria. While expanding the spectrum of mutations in SPG11, this larger series also corroborated the notion that even within apparently homogeneous population a molecular diagnosis cannot be achieved without full gene sequencing. (C) 2008 Wiley-Liss, Inc.

Bayesian nonlinear regression models with scale mixtures of skew-normal distributions: Estimation and case influence diagnostics

The purpose of this paper is to develop a Bayesian analysis for nonlinear regression models under scale mixtures of skew-normal distributions. This novel class of models provides a useful generalization of the symmetrical nonlinear regression models since the error distributions cover both skewness and heavy-tailed distributions such as the skew-t, skew-slash and the skew-contaminated normal distributions. The main advantage of these class of distributions is that they have a nice hierarchical representation that allows the implementation of Markov chain Monte Carlo (MCMC) methods to simulate samples from the joint posterior distribution. In order to examine the robust aspects of this flexible class, against outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. Further, some discussions on the model selection criteria are given. The newly developed procedures are illustrated considering two simulations study, and a real data previously analyzed under normal and skew-normal nonlinear regression models. (C) 2010 Elsevier B.V. All rights reserved.

A Parallel Hardware Architecture for Scale and Rotation Invariant Feature Detection

This paper proposes a parallel hardware architecture for image feature detection based on the Scale Invariant Feature Transform algorithm and applied to the Simultaneous Localization And Mapping problem. The work also proposes specific hardware optimizations considered fundamental to embed such a robotic control system on-a-chip. The proposed architecture is completely stand-alone; it reads the input data directly from a CMOS image sensor and provides the results via a field-programmable gate array coupled to an embedded processor. The results may either be used directly in an on-chip application or accessed through an Ethernet connection. The system is able to detect features up to 30 frames per second (320 x 240 pixels) and has accuracy similar to a PC-based implementation. The achieved system performance is at least one order of magnitude better than a PC-based solution, a result achieved by investigating the impact of several hardware-orientated optimizations oil performance, area and accuracy.

A new scale-invariant ratio and finite-size scaling for the stochastic susceptible-infected-recovered model

The critical behavior of the stochastic susceptible-infected-recovered model on a square lattice is obtained by numerical simulations and finite-size scaling. The order parameter as well as the distribution in the number of recovered individuals is determined as a function of the infection rate for several values of the system size. The analysis around criticality is obtained by exploring the close relationship between the present model and standard percolation theory. The quantity UP, equal to the ratio U between the second moment and the squared first moment of the size distribution multiplied by the order parameter P, is shown to have, for a square system, a universal value 1.0167(1) that is the same for site and bond percolation, confirming further that the SIR model is also in the percolation class.

Shape classification using complex network and Multi-scale Fractal Dimension

Shape provides one of the most relevant information about an object. This makes shape one of the most important visual attributes used to characterize objects. This paper introduces a novel approach for shape characterization, which combines modeling shape into a complex network and the analysis of its complexity in a dynamic evolution context. Descriptors computed through this approach show to be efficient in shape characterization, incorporating many characteristics, such as scale and rotation invariant. Experiments using two different shape databases (an artificial shapes database and a leaf shape database) are presented in order to evaluate the method. and its results are compared to traditional shape analysis methods found in literature. (C) 2009 Published by Elsevier B.V.

Resilience of protein-protein interaction networks as determined by their large-scale topological features

The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.

A multi-GPU algorithm for large-scale neuronal networks

Large-scale simulations of parts of the brain using detailed neuronal models to improve our understanding of brain functions are becoming a reality with the usage of supercomputers and large clusters. However, the high acquisition and maintenance cost of these computers, including the physical space, air conditioning, and electrical power, limits the number of simulations of this kind that scientists can perform. Modern commodity graphical cards, based on the CUDA platform, contain graphical processing units (GPUs) composed of hundreds of processors that can simultaneously execute thousands of threads and thus constitute a low-cost solution for many high-performance computing applications. In this work, we present a CUDA algorithm that enables the execution, on multiple GPUs, of simulations of large-scale networks composed of biologically realistic Hodgkin-Huxley neurons. The algorithm represents each neuron as a CUDA thread, which solves the set of coupled differential equations that model each neuron. Communication among neurons located in different GPUs is coordinated by the CPU. We obtained speedups of 40 for the simulation of 200k neurons that received random external input and speedups of 9 for a network with 200k neurons and 20M neuronal connections, in a single computer with two graphic boards with two GPUs each, when compared with a modern quad-core CPU. Copyright (C) 2010 John Wiley & Sons, Ltd.

Multivariate measurement error models based on scale mixtures of the skew-normal distribution

Scale mixtures of the skew-normal (SMSN) distribution is a class of asymmetric thick-tailed distributions that includes the skew-normal (SN) distribution as a special case. The main advantage of these classes of distributions is that they are easy to simulate and have a nice hierarchical representation facilitating easy implementation of the expectation-maximization algorithm for the maximum-likelihood estimation. In this paper, we assume an SMSN distribution for the unobserved value of the covariates and a symmetric scale mixtures of the normal distribution for the error term of the model. This provides a robust alternative to parameter estimation in multivariate measurement error models. Specific distributions examined include univariate and multivariate versions of the SN, skew-t, skew-slash and skew-contaminated normal distributions. The results and methods are applied to a real data set.