LEARNING A COMPLEX MOTOR SKILL FROM VIDEO AND POINT-LIGHT DEMONSTRATIONS

The aim of this Study was to compare the learning process of a highly complex ballet skill following demonstrations of point light and video models 16 participants divided into point light and video groups (ns = 8) performed 160 trials of a pirouette equally distributed in blocks of 20 trials alternating periods of demonstration and practice with a retention test a day later Measures of head and trunk oscillation coordination d1 parity from the model and movement time difference showed similarities between video and point light groups ballet experts evaluations indicated superiority of performance in the video over the point light group Results are discussed in terms of the task requirements of dissociation between head and trunk rotations focusing on the hypothesis of sufficiency and higher relevance of information contained in biological motion models applied to learning of complex motor skills

Relevance of leaf surface contamination for assessing chemical composition of bromeliads in a restinga forest

Resuspended soil and other airborne particles adhered to the leaf surface affect the chemical composition of the plant. A well-defined cleaning procedure is necessary to avoid this problem, providing a correct assessment of the inherent chemical composition of bromeliads. To evaluate the influence of a washing procedure, INAA was applied for determining chemical elements in the leaves of bromeliads from Vriesea carinata species, both non-washed and washed with Alconox, EDTA and bi-distilled water. Br, Ce, Hg, La, Sc, Se, Sm and Th showed higher mass fractions in non-washed leaves. The washing procedure removed the exogenous material without leaching chemical elements from inside the tissues.

Laser-induced breakdown spectroscopy and chemometrics for classification of toys relying on toxic elements

Quality control of toys for avoiding children exposure to potentially toxic elements is of utmost relevance and it is a common requirement in national and/or international norms for health and safety reasons. Laser-induced breakdown spectroscopy (LIBS) was recently evaluated at authors` laboratory for direct analysis of plastic toys and one of the main difficulties for the determination of Cd. Cr and Pb was the variety of mixtures and types of polymers. As most norms rely on migration (lixiviation) protocols, chemometric classification models from LIBS spectra were tested for sampling toys that present potential risk of Cd, Cr and Pb contamination. The classification models were generated from the emission spectra of 51 polymeric toys and by using Partial Least Squares - Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogy (SIMCA) and K-Nearest Neighbor (KNN). The classification models and validations were carried out with 40 and 11 test samples, respectively. Best results were obtained when KNN was used, with corrected predictions varying from 95% for Cd to 100% for Cr and Pb. (C) 2011 Elsevier B.V. All rights reserved.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

Bayesian updating rules in continuous opinion dynamics models

Here, I investigate the use of Bayesian updating rules applied to modeling how social agents change their minds in the case of continuous opinion models. Given another agent statement about the continuous value of a variable, we will see that interesting dynamics emerge when an agent assigns a likelihood to that value that is a mixture of a Gaussian and a uniform distribution. This represents the idea that the other agent might have no idea about what is being talked about. The effect of updating only the first moments of the distribution will be studied, and we will see that this generates results similar to those of the bounded confidence models. On also updating the second moment, several different opinions always survive in the long run, as agents become more stubborn with time. However, depending on the probability of error and initial uncertainty, those opinions might be clustered around a central value.

Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

Treatment of Obese Adolescents: The Influence of Periodization Models and ACE Genotype

The aims of the present study were to compare the effects of two periodization models on metabolic syndrome risk factors in obese adolescents and verify whether the angiotensin-converting enzyme (ACE) genotype is important in establishing these effects. A total of 32 postpuberty obese adolescents were submitted to aerobic training (AT) and resistance training (RT) for 14 weeks. The subjects were divided into linear periodization (LP, n = 16) or daily undulating periodization (DUP, n = 16). Body composition, visceral and subcutaneous fat, glycemia, insulinemia, homeostasis model assessment of insulin resistance (HOMA-IR), lipid profiles, blood pressure, maximal oxygen consumption (VO(2max)), resting metabolic rate (RMR), muscular endurance were analyzed at baseline and after intervention. Both groups demonstrated a significant reduction in body mass, BMI, body fat, visceral and subcutaneous fat, total and low-density lipoprotein cholesterol, blood pressure and an increase in fat-free mass, VO(2max), and muscular endurance. However, only DUP promoted a reduction in insulin concentrations and HOMA-IR. It is important to emphasize that there was no statics difference between LP and DUP groups; however, it appears that there may be bigger changes in the DUP than LP group in some of the metabolic syndrome risk factors in obese adolescents with regard to the effect size (ES). Both periodization models presented a large effect on muscular endurance. Despite the limitation of sample size, our results suggested that the ACE genotype may influence the functional and metabolic characteristics of obese adolescents and may be considered in the future strategies for massive obesity control.

Efficient method for obtaining Lep(ob)/Lep(ob)-derived animal models using adipose tissue transplantations

Background: Leptin-deficient mice (Lep(ob)/Lep(ob), also known as ob/ob) are of great importance for studies of obesity, diabetes and other correlated pathologies. Thus, generation of animals carrying the Lep(ob) gene mutation as well as additional genomic modifications has been used to associate genes with metabolic diseases. However, the infertility of Lep(ob)/Lep(ob) mice impairs this kind of breeding experiment. Objective: To propose a new method for production of Lep(ob)/Lep(ob) animals and Lep(ob)/Lep(ob)-derived animal models by restoring the fertility of Lep(ob)/Lep(ob) mice in a stable way through white adipose tissue transplantations. Methods: For this purpose, 1 g of peri-gonadal adipose tissue from lean donors was used in subcutaneous transplantations of Lep(ob)/Lep(ob) animals and a crossing strategy was established to generate Lep(ob)/Lep(ob)-derived mice. Results: The presented method reduced by four times the number of animals used to generate double transgenic models (from about 20 to 5 animals per double mutant produced) and minimized the number of genotyping steps (from 3 to 1 genotyping step, reducing the number of Lep gene genotyping assays from 83 to 6). Conclusion: The application of the adipose transplantation technique drastically improves both the production of Lep(ob)/Lep(ob) animals and the generation of Lep(ob)/Lep(ob)-derived animal models. International Journal of Obesity (2009) 33, 938-944; doi: 10.1038/ijo.2009.95; published online 16 June 2009

Relevance of extractives and wood transformation products on the biodegradation of Pinus taeda by Ceriporiopsis subvermispora

Ceriporiopsis subvermispora is a promising white-rot fungus for biopulping. However, the underlying biochemistry involved in lignin removal and insignificant cellulose degradation by this species is not completely understood. This paper addresses this topic focusing on the involvement of ethanol-soluble extractives and wood transformation products in the biodegradation process. Cultures containing ethanol-extracted or in natura wood chips presented similar levels of extracellular enzymes and degradation of wood components. Fe3+-reducing compounds present in undecayed Pinus taeda were rapidly diminished by fungal degradation. Lignin-degradation products released during biodegradation restored part of the Fe3+-reducing activity. However, Fe3+ reduction was ineffective in presence of 0.5 mM oxalate at pH 4.5. Fungal consumption of Fe3+-reducing compounds and secretion of oxalic acid minimized the significance of Fenton`s reaction in the initial stages of wood biotreatment. This would explain limited polysaccharide degradation by the fungus that also lacks a complete set of hydrolytic enzymes. Scientific relevance of the paper: Ceriporiopsis subvermispora is a white-rot fungus suitable for biopulping processes because it degrades lignin selectively and causes significant structural changes on the wood components during the earlier decay stages. However, the intricate mechanism to explain lignin transformation and insignificant cellulose degradation by this species remains poorly understood. Some recent evidences pointed out for lipid peroxidation reactions as all initiating process explaining lignin degradation. On the other hand, alkylitaconic acids produced by the fungus via transformations of fatty acids occurring in wood showed to prevent polysaccharide degradation in Fenton reactions. In this context, one may conclude that the involvement of native wood substances or their transformation products in the overall wood biodegradation process induced by C subvermispora is still a matter of discussion. While free and esterified fatty acids present in wood extractives may be involved in the biosynthesis of alkylitaconic acids and in lipid peroxidation reactions, some extractives and lignin degradation products can reduce Fe3+, providing Fe2+ species needed to form OH radical via Fenton`s reaction. The present study focuses on this topic by evaluating the relevance of ethanol-soluble extractives and wood transformation products on the biodegradation of P. taeda by C subvermispora. For this, solid-state cultures containing ethanol-extracted and in natura wood chips were evaluated in details for up to 4 weeks. (C) 2007 Elsevier Ltd. All rights reserved.

Lignocellulosic polysaccharides and lignin degradation by wood decay fungi: the relevance of nonenzymatic Fenton-based reactions

The brown rot fungus Wolfiporia cocos and the selective white rot fungus Perenniporia medulla-panis produce peptides and phenolate-derivative compounds as low molecular weight Fe(3+)-reductants. Phenolates were the major compounds with Fe(3+)-reducing activity in both fungi and displayed Fe(3+)-reducing activity at pH 2.0 and 4.5 in the absence and presence of oxalic acid. The chemical structures of these compounds were identified. Together with Fe(3+) and H(2)O(2) (mediated Fenton reaction) they produced oxygen radicals that oxidized lignocellulosic polysaccharides and lignin extensively in vitro under conditions similar to those found in vivo. These results indicate that, in addition to the extensively studied Gloeophyllum trabeum-a model brown rot fungus-other brown rot fungi as well as selective white rot fungi, possess the means to promote Fenton chemistry to degrade cellulose and hemicellulose, and to modify lignin. Moreover, new information is provided, particularly regarding how lignin is attacked, and either repolymerized or solubilized depending on the type of fungal attack, and suggests a new pathway for selective white rot degradation of wood. The importance of Fenton reactions mediated by phenolates operating separately or synergistically with carbohydrate-degrading enzymes in brown rot fungi, and lignin-modifying enzymes in white rot fungi is discussed. This research improves our understanding of natural processes in carbon cycling in the environment, which may enable the exploration of novel methods for bioconversion of lignocellulose in the production of biofuels or polymers, in addition to the development of new and better ways to protect wood from degradation by microorganisms.

Low-intensity Ultrasound Increases FAK, ERK-1/2, and IRS-1 Expression of Intact Rat Bones in a Noncumulative Manner

Background Low-intensity pulsed ultrasound stimulation (LIPUS) reportedly increases osteogenesis in fracture models but fails in intact bone, suggesting LIPUS does not act on mechanotransduction and growth factor pathways of intact bone. Questions/Purposes We asked whether daily 20-minute LIPUS applied to intact tibias would act on bone proteins involved in mechanotransduction (focal adhesion kinase [FAK], and extracellular signal-regulated kinase-1/2 [ERK-1/2]), and growth factor signaling (insulin receptor substrate-1 [IRS-1]) pathways at 7, 14, and 21 days of treatment. Methods Immunoblotting was performed to detect FAK, ERK-1/2, and IRS-1 expression and activation from the stimulated intact tibias at 7, 14, and 21 days of daily 20-minute LIPUS. Results LIPUS increased FAK expression (at 7 days), ERK-1/2 (at 14 days), and IRS-1 (at 7 days), but expression decreased 7 days later, indicating a noncumulative effect of LIPUS. As only FAK expression was detected at 21 days, these observations suggest LIPUS influences nuclear reactions that may be modulated by a major cellular mechanism preferentially inhibiting IRS-1 expression and not FAK expression. Increased ERK-1/2 expression at 14 days suggests the differing mechanisms for promoting ERK-1/2, FAK, and IRS-1 syntheses. IRS-1 expression behaved similarly to FAK expression; therefore, LIPUS may modulate growth factor pathways. LIPUS increased sustained FAK and ERK-1/2 activation, but not IRS-1, suggesting sustained ERK-1/2 activation is not the result of mechanically induced growth factor activation. Conclusions LIPUS acts on mechanotransduction and growth factor pathways in intact bone in a noncumulative manner. Clinical relevance These data suggest LIPUS applied to intact bone acts on proteins involved in osteogenesis.

Aerodynamic study of three-dimensional larynx models using finite element methods

The airflow velocities and pressures are calculated from a three-dimensional model of the human larynx by using the finite element method. The laryngeal airflow is assumed to be incompressible, isothermal, steady, and created by fixed pressure drops. The influence of different laryngeal profiles (convergent, parallel, and divergent), glottal area, and dimensions of false vocal folds in the airflow are investigated. The results indicate that vertical and horizontal phase differences in the laryngeal tissue movements are influenced by the nonlinear pressure distribution across the glottal channel, and the glottal entrance shape influences the air pressure distribution inside the glottis. Additionally, the false vocal folds increase the glottal duct pressure drop by creating a new constricted channel in the larynx, and alter the airflow vortexes formed after the true vocal folds. (C) 2007 Elsevier Ltd. All rights reserved.

Simplified models for cross-section stress demands on C-section purlins in uplift

The objective of this paper is to provide and verify simplified models that predict the longitudinal stresses that develop in C-section purlins in uplift. The paper begins with the simple case of flexural stress: where the force has to be applied at the shear center, or the section braced in both flanges. Restrictions on load application point and restraint of the flanges are removed until arriving at the more complex problem of bending when movement of the tension flange alone is restricted, as commonly found in purlin-sheeting systems. Winter`s model for predicting the longitudinal stresses developed due to direct torsion is reviewed, verified, and then extended to cover the case of a bending member with tension flange restraint. The developed longitudinal stresses from flexure and restrained torsion are used to assess the elastic stability behavior of typical purlin-sheeting systems. Finally, strength predictions of typical C-section purlins are provided for existing AISI methods and a newly proposed extension to the direct strength method that employs the predicted longitudinal stress distributions within the strength prediction. (C) 2009 Elsevier Ltd. All rights reserved.

A simple way to introduce fibers into FEM models

This communication proposes a simple way to introduce fibers into finite element modelling. This is a promising formulation to deal with fiber-reinforced composites by the finite element method (FEM), as it allows the consideration of short or long fibers placed arbitrarily inside a continuum domain (matrix). The most important feature of the formulation is that no additional degree of freedom is introduced into the pre-existent finite element numerical system to consider any distribution of fiber inclusions. In other words, the size of the system of equations used to solve a non-reinforced medium is the same as the one used to solve the reinforced counterpart. Another important characteristic is the reduced work required by the user to introduce fibers, avoiding `rebar` elements, node-by-node geometrical definitions or even complex mesh generation. An additional characteristic of the technique is the possibility of representing unbounded stresses at the end of fibers using a finite number of degrees of freedom. Further studies are required for non-linear applications in which localization may occur. Along the text the linear formulation is presented and the bounded connection between fibers and continuum is considered. Four examples are presented, including non-linear analysis, to validate and show the capabilities of the formulation. Copyright (c) 2007 John Wiley & Sons, Ltd.

2D evaluation of crack openings using smeared and embedded crack models

This work deals with the determination of crack openings in 2D reinforced concrete structures using the Finite Element Method with a smeared rotating crack model or an embedded crack model In the smeared crack model, the strong discontinuity associated with the crack is spread throughout the finite element As is well known, the continuity of the displacement field assumed for these models is incompatible with the actual discontinuity However, this type of model has been used extensively due to the relative computational simplicity it provides by treating cracks in a continuum framework, as well as the reportedly good predictions of reinforced concrete members` structural behavior On the other hand, by enriching the displacement field within each finite element crossed by the crack path, the embedded crack model is able to describe the effects of actual discontinuities (cracks) This paper presents a comparative study of the abilities of these 2D models in predicting the mechanical behavior of reinforced concrete structures Structural responses are compared with experimental results from the literature, including crack patterns, crack openings and rebar stresses predicted by both models