Dynamic texture segmentation based on deterministic partially self-avoiding walks

Recently there has been a considerable interest in dynamic textures due to the explosive growth of multimedia databases. In addition, dynamic texture appears in a wide range of videos, which makes it very important in applications concerning to model physical phenomena. Thus, dynamic textures have emerged as a new field of investigation that extends the static or spatial textures to the spatio-temporal domain. In this paper, we propose a novel approach for dynamic texture segmentation based on automata theory and k-means algorithm. In this approach, a feature vector is extracted for each pixel by applying deterministic partially self-avoiding walks on three orthogonal planes of the video. Then, these feature vectors are clustered by the well-known k-means algorithm. Although the k-means algorithm has shown interesting results, it only ensures its convergence to a local minimum, which affects the final result of segmentation. In order to overcome this drawback, we compare six methods of initialization of the k-means. The experimental results have demonstrated the effectiveness of our proposed approach compared to the state-of-the-art segmentation methods.

Role of Two Clusters of Male Alcoholics in Treatment Retention

Aims: This study aimed to classify alcohol-dependent outpatients on the basis of clinical factors and to verify if the resulting types show different treatment retention. Methods: The sample comprised 332 alcoholics that were enrolled in three different pharmacological trials carried out at Sao Paulo University, Brazil. Based on four clinical factors problem drinking onset age, familial alcoholism, alcohol dependence severity, and depression - K-means cluster analysis was performed by using the average silhouette width to determine the number of clusters. A direct logistic regression was performed to analyze the influence of clusters, medication groups, and Alcoholics Anonymous ( AA) attendance in treatment retention. Results: Two clusters were delineated. The cluster characterized by earlier onset age, more familial alcoholism, higher alcoholism severity, and less depression symptoms showed a higher chance of discontinuing the treatment, independently of medications used and AA attendance. Participation in AA was significantly related to treatment retention. Discussion: Health services should broaden the scope of services offered to meet heterogeneous needs of clients, and identify treatment practices and therapists which improve retention. Information about patients' characteristics linked to dropout should be used to make treatment programs more responsive and attractive, combining pharmacological agents with more intensive and diversified psychosocial interventions. Copyright (C) 2012 S. Karger AG, Basel

Multivariate analysis in the maximum strength performance

This study performed an exploratory analysis of the anthropometrical and morphological muscle variables related to the one-repetition maximum (1RM) performance. In addition, the capacity of these variables to predict the force production was analyzed. 50 active males were submitted to the experimental procedures: vastus lateralis muscle biopsy, quadriceps magnetic resonance imaging, body mass assessment and 1RM test in the leg-press exercise. K-means cluster analysis was performed after obtaining the body mass, sum of the left and right quadriceps muscle cross-sectional area (Sigma CSA), percentage of the type II fibers and the 1RM performance. The number of clusters was defined a priori and then were labeled as high strength performance (HSP1RM) group and low strength performance (LSP1RM) group. Stepwise multiple regressions were performed by means of body mass, Sigma CSA, percentage of the type II fibers and clusters as predictors' variables and 1RM performance as response variable. The clusters mean +/- SD were: 292.8 +/- 52.1 kg, 84.7 +/- 17.9 kg, 19249.7 +/- 1645.5 mm(2) and 50.8 +/- 7.2% for the HSP1RM and 254.0 +/- 51.1 kg, 69.2 +/- 8.1 kg, 15483.1 +/- 1 104.8 mm(2) and 51.7 +/- 6.2 %, for the LSP1RM in the 1RM, body mass, Sigma CSA and muscle fiber type II percentage, respectively. The most important variable in the clusters division was the Sigma CSA. In addition, the Sigma CSA and muscle fiber type II percentage explained the variance in the 1RM performance (Adj R-2 = 0.35, p = 0.0001) for all participants and for the LSP1RM (Adj R-2 = 0.25, p = 0.002). For the HSP1RM, only the Sigma CSA was entered in the model and showed the highest capacity to explain the variance in the 1RM performance (Adj R-2 = 0.38, p = 0.01). As a conclusion, the muscle CSA was the most relevant variable to predict force production in individuals with no strength training background.

Speech perception and cortical auditory evoked potentials in cochlear implant users with auditory neuropathy spectrum disorders

Objective: To characterize the PI component of long latency auditory evoked potentials (LLAEPs) in cochlear implant users with auditory neuropathy spectrum disorder (ANSD) and determine firstly whether they correlate with speech perception performance and secondly whether they correlate with other variables related to cochlear implant use. Methods: This study was conducted at the Center for Audiological Research at the University of Sao Paulo. The sample included 14 pediatric (4-11 years of age) cochlear implant users with ANSD, of both sexes, with profound prelingual hearing loss. Patients with hypoplasia or agenesis of the auditory nerve were excluded from the study. LLAEPs produced in response to speech stimuli were recorded using a Smart EP USB Jr. system. The subjects' speech perception was evaluated using tests 5 and 6 of the Glendonald Auditory Screening Procedure (GASP). Results: The P-1 component was detected in 12/14 (85.7%) children with ANSD. Latency of the P-1 component correlated with duration of sensorial hearing deprivation (*p = 0.007, r = 0.7278), but not with duration of cochlear implant use. An analysis of groups assigned according to GASP performance (k-means clustering) revealed that aspects of prior central auditory system development reflected in the P-1 component are related to behavioral auditory skills. Conclusions: In children with ANSD using cochlear implants, the P-1 component can serve as a marker of central auditory cortical development and a predictor of the implanted child's speech perception performance. (c) 2012 Elsevier Ireland Ltd. All rights reserved.

Heuristics for minimizing the maximum within-clusters distance

The clustering problem consists in finding patterns in a data set in order to divide it into clusters with high within-cluster similarity. This paper presents the study of a problem, here called MMD problem, which aims at finding a clustering with a predefined number of clusters that minimizes the largest within-cluster distance (diameter) among all clusters. There are two main objectives in this paper: to propose heuristics for the MMD and to evaluate the suitability of the best proposed heuristic results according to the real classification of some data sets. Regarding the first objective, the results obtained in the experiments indicate a good performance of the best proposed heuristic that outperformed the Complete Linkage algorithm (the most used method from the literature for this problem). Nevertheless, regarding the suitability of the results according to the real classification of the data sets, the proposed heuristic achieved better quality results than C-Means algorithm, but worse than Complete Linkage.

Localising and quantifying damage by means of a multi-chromosome genetic algorithm

This paper presents a structural damage detection methodology based on genetic algorithms and dynamic parameters. Three chromosomes are used to codify an individual in the population. The first and second chromosomes locate and quantify damage, respectively. The third permits the self-adaptation of the genetic parameters. The natural frequencies and mode shapes are used to formulate the objective function. A numerical analysis was performed for several truss structures under different damage scenarios. The results have shown that the methodology can reliably identify damage scenarios using noisy measurements and that it results in only a few misidentified elements. (C) 2012 Civil-Comp Ltd and Elsevier Ltd. All rights reserved.

Kinetic Analysis of Gill (Na+,K+)-ATPase Activity in Selected Ontogenetic Stages of the Amazon River Shrimp, (Decapoda, Palaemonidae): Interactions at ATP- and Cation-Binding Sites

We investigated modulation by ATP, Mg2+, Na+, K+ and NH4 (+) and inhibition by ouabain of (Na+,K+)-ATPase activity in microsomal homogenates of whole zoeae I and decapodid III (formerly zoea IX) and whole-body and gill homogenates of juvenile and adult Amazon River shrimps, . (Na+,K+)-ATPase-specific activity was increased twofold in decapodid III compared to zoea I, juveniles and adults, suggesting an important role in this ontogenetic stage. The apparent affinity for ATP ( (M) = 0.09 +/- A 0.01 mmol L-1) of the decapodid III (Na+,K+)-ATPase, about twofold greater than the other stages, further highlights this relevance. Modulation of (Na+,K+)-ATPase activity by K+ also revealed a threefold greater affinity for K+ ( (0.5) = 0.91 +/- A 0.04 mmol L-1) in decapodid III than in other stages; NH4 (+) had no modulatory effect. The affinity for Na+ ( (0.5) = 13.2 +/- A 0.6 mmol L-1) of zoea I (Na+,K+)-ATPase was fourfold less than other stages. Modulation by Na+, Mg2+ and NH4 (+) obeyed cooperative kinetics, while K+ modulation exhibited Michaelis-Menten behavior. Rates of maximal Mg2+ stimulation of ouabain-insensitive ATPase activity differed in each ontogenetic stage, suggesting that Mg2+-stimulated ATPases other than (Na+,K+)-ATPase are present. Ouabain inhibition suggests that, among the various ATPase activities present in the different stages, Na+-ATPase may be involved in the ontogeny of osmoregulation in larval The NH4 (+)-stimulated, ouabain-insensitive ATPase activity seen in zoea I and decapodid III may reflect a stage-specific means of ammonia excretion since functional gills are absent in the early larval stages.

Fuzzy Connectedness Image Segmentation in Graph Cut Formulation: A Linear-Time Algorithm and a Comparative Analysis

A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.

Unraveling the Mysterious Role of Palladium in Feigl bis(dimethylglyoximate)nickel(II) Spot Tests by Means of Confocal Raman Microscopy

The add protection effect promoted by traces of PdCl2 in [Ni(dmgH)(2)] spot tests was elucidated from confocal Raman microscopy imaging, which revealed the formation of protecting layers of [Pd(dmgH)(2)] closing the extremities of the [Ni(dmgH)(2)] filaments.

Looking over Toxin-K+ Channel Interactions. Clues from the Structural and Functional Characterization of alpha-KTx Toxin Tc32, a Kv1.3 Channel Blocker

alpha-KTx toxin Tc32, from the Amazonian scorpion Tityus cambridgei, lacks the dyad motif; including Lys27, characteristic of the family and generally associated with channel blockage. The toxin has been cloned and expressed for the first time. Electrophysiological experiments, by showing that the recombinant form blocks Kv1.3 channels of olfactory bulb periglomerular cells like the natural Tc32 toxin, when tested on the Kv1.3 channel of human T lymphocytes, confirmed it is in an active fold. The nuclear magnetic resonance-derived structure revealed it exhibits an alpha/beta scaffold typical of the members of the alpha-KTx family. TdK2 and TdK3, all belonging to the same alpha-KTx 18 subfamily, share significant sequence identity with Tc32 but diverse selectivity and affinity for Kv1.3 and Kv1.1 channels. To gain insight into the structural features that may justify those differences, we used the recombinant Tc32 nuclear magnetic resonance-derived structure to model the other two toxins, for which no experimental structure is available. Their interaction with Kv1.3 and Kv1.1 has been investigated by means of docking simulations. The results suggest that differences in the electrostatic features of the toxins and channels, in their contact surfaces, and in their total dipole moment orientations govern the affinity and selectivity of toxins. In addition, we found that, regardless of whether the dyad motif is present, it is always a Lys side chain that physically blocks the channels, irrespective of its position in the toxin sequence.

Parallel Layout Construction Algorithm for Irregular Shape Packing Problems

Cutting and packing problems arise in a variety of industries, including garment, wood and shipbuilding. Irregular shape packing is a special case which admits irregular items and is much more complex due to the geometry of items. In order to ensure that items do not overlap and no item from the layout protrudes from the container, the collision free region concept was adopted. It represents all possible translations for a new item to be inserted into a container with already placed items. To construct a feasible layout, collision free region for each item is determined through a sequence of Boolean operations over polygons. In order to improve the speed of the algorithm, a parallel version of the layout construction was proposed and it was applied to a simulated annealing algorithm used to solve bin packing problems. Tests were performed in order to determine the speed improvement of the parallel version over the serial algorithm