101 resultados para Information dispersal algorithm
Resumo:
A graph clustering algorithm constructs groups of closely related parts and machines separately. After they are matched for the least intercell moves, a refining process runs on the initial cell formation to decrease the number of intercell moves. A simple modification of this main approach can deal with some practical constraints, such as the popular constraint of bounding the maximum number of machines in a cell. Our approach makes a big improvement in the computational time. More importantly, improvement is seen in the number of intercell moves when the computational results were compared with best known solutions from the literature. (C) 2009 Elsevier Ltd. All rights reserved.
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The present study aimed to investigate the presence of corpus callosum (CC) volume deficits in a population-based recent-onset psychosis (ROP) sample, and whether CC volume relates to interhemispheric communication deficits. For this purpose, we used voxel-based morphometry comparisons of magnetic resonance imaging data between ROP (n = 122) and healthy control (n = 94) subjects. Subgroups (38 ROP and 39 controls) were investigated for correlations between CC volumes and performance on the Crossed Finger Localization Test (CFLT). Significant CC volume reductions in ROP subjects versus controls emerged after excluding substance misuse and non-right-handedness. CC reductions retained significance in the schizophrenia subgroup but not in affective psychoses subjects. There were significant positive correlations between CC volumes and CFLT scores in ROP subjects, specifically in subtasks involving interhemispheric communication. From these results, we can conclude that CC volume reductions are present in association with ROP. The relationship between such deficits and CFLT performance suggests that interhemispheric communication impairments are directly linked to CC abnormalities in ROP. (C) 2010 Elsevier Ireland Ltd. All rights reserved.
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The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.
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Background: Although various techniques have been used for breast conservation surgery reconstruction, there are few studies describing a logical approach to reconstruction of these defects. The objectives of this study were to establish a classification system for partial breast defects and to develop a reconstructive algorithm. Methods: The authors reviewed a 7-year experience with 209 immediate breast conservation surgery reconstructions. Mean follow-up was 31 months. Type I defects include tissue resection in smaller breasts (bra size A/B), including type IA, which involves minimal defects that do not cause distortion; type III, which involves moderate defects that cause moderate distortion; and type IC, which involves large defects that cause significant deformities. Type II includes tissue resection in medium-sized breasts with or without ptosis (bra size C), and type III includes tissue resection in large breasts with ptosis (bra size D). Results: Eighteen percent of patients presented type I, where a lateral thoracodorsal flap and a latissimus dorsi flap were performed in 68 percent. Forty-five percent presented type II defects, where bilateral mastopexy was performed in 52 percent. Thirty-seven percent of patients presented type III distortion, where bilateral reduction mammaplasty was performed in 67 percent. Thirty-five percent of patients presented complications, and most were minor. Conclusions: An algorithm based on breast size in relation to tumor location and extension of resection can be followed to determine the best approach to reconstruction. The authors` results have demonstrated that the complications were similar to those in other clinical series. Success depends on patient selection, coordinated planning with the oncologic surgeon, and careful intraoperative management.
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Objective: To determine the degree of knowledge that cardiologists from Sao Paulo, Brazil, have regarding a low-prevalent entity associated with a high rate of sudden death-Brugada syndrome. Methods: Two hundred forty-four cardiologists were interviewed by an instrument divided in two parts: in the first, we recorded gender, age, and data related to academic profile. The second-answered only by the professionals that manifested having some degree of knowledge on the syndrome-had 28 questions that evaluated their knowledge. The answers were spontaneous and they did not have a chance to consult. We used uni- and multivariate analysis on the average percentage of right and wrong answers, and the influence of the academic profile. Results: The predominant gender was the male gender (61.1%), the average age was 44.32 +/- 10.83 years, 40% with more than 20 years after obtaining their degree, 44% were educated in public institutions, 69% had a residency in cardiology, 20% had overseas practice, 12% had postdegree, 41% were linked to an educational institution, 24% with publication(s) in an indexed journal, 17.2% were authors of chapters in books, 2.5% had edited books, and 10% were linked to the Brazilian Society of Cardiac Arrhythmias. The average percentage of right answers was 45.7%. Conclusion: The sample studied revealed a little knowledge on the entity. A residency in cardiology was the factor of greater significance in the percentage of right answers. Other significant factors were the link of the interviewed person to an educational institution, or the Brazilian Society of Cardiac Arrhythmias, and having a specialist degree.
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Understanding the mating patterns of populations of tree species is a key component of ex situ genetic conservation. In this study, we analysed the genetic diversity, spatial genetic structure (SGS) and mating system at the hierarchical levels of fruits and individuals as well as pollen dispersal patterns in a continuous population of Theobroma cacao in Para State, Brazil. A total of 156 individuals in a 0.56 ha plot were mapped and genotyped for nine microsatellite loci. For the mating system analyses, 50 seeds were collected from nine seed trees by sampling five fruits per tree (10 seeds per fruit). Among the 156 individuals, 127 had unique multilocus genotypes, and the remaining were clones. The population was spatially aggregated; it demonstrated a significant SGS up to 15m that could be attributed primarily to the presence of clones. However, the short seed dispersal distance also contributed to this pattern. Population matings occurred mainly via outcrossing, but selfing was observed in some seed trees, which indicated the presence of individual variation for self-incompatibility. The matings were also correlated, especially within ((r) over cap (p(m)) = 0.607) rather than among the fruits ((r) over cap (p(m)) = 0.099), which suggested that a small number of pollen donors fertilised each fruit. The paternity analysis suggested a high proportion of pollen migration (61.3%), although within the plot, most of the pollen dispersal encompassed short distances (28m). The determination of these novel parameters provides the fundamental information required to establish long-term ex situ conservation strategies for this important tropical species. Heredity (2011) 106, 973-985; doi:10.1038/hdy.2010.145; published online 8 December 2010
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The purpose of this study was to investigate whether the additional sensory information could improve postural control in individuals with unilateral anterior cruciate ligament (ACL) injury. Twenty-eight individuals with unilateral ACL injury (mean age 23.6, 26 males, 2 females) and 28 healthy young control subjects (mean age 22.1 years, 26 males, 2 females) participated in this study. Postural control was evaluated with subjects single-leg standing on a force platform with eyes closed under two sensory conditions: normal sensory information and light touch to a stationary bar (applied force below 1 N). Three trials of 30 5 were performed in each single-leg stance and in each sensory condition. Mean sway amplitude and predominant frequency of center of pressure were calculated for both anterior-posterior and medial-lateral directions. Individuals with ACL injury showed greater mean sway amplitude than healthy control individuals even though the predominant frequency was similar for both groups. Additional sensory information improved postural control performance in individuals with ACL injury and healthy control, with a greater effect observed for the ACL group. Based on these results, we suggest that reduction in postural control performance in individuals with ACL injury would be due to the reduction of sensory information provided by the ACL, but when sensory information is enhanced, postural control performance improves. These results have implications for novel approaches to improve stability in individuals with ACL injury. (c) 2008 Elsevier Ireland Ltd. All rights reserved.
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The nutritional composition found in the laboratory and those present on labels of manufactured foods can differ significantly. The purpose of this study was to determine the nutritional composition of hamburgers and meatballs and compare them with your labels. The food analysis was performed following the Analytical Standards Institute`s Adolfo Lutz and energy content was determined by bomb calorimetry. Regarding the energy value, all the samples had values less than informed on the label. The content of lipids of hamburgers and meatballs ( except the beef) were lower than those reported on the label. The values of protein for the meatballs and chicken hamburger had lower values than those labels. Thus, the labels may overestimate as underestimate some nutritional values, leading to population erroneous information.
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In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.
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Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM), which is the most widely used method to analyze fMRI datasets.
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Plasmids are mobile genetic elements of bacteria that can impart important adaptive traits, such as increased virulence or antibiotic resistance. We report the existence of plasmids in Rickettsia (Rickettsiales; Rickettsiaceae) species, including Rickettsia akari, ""Candidatus Rickettsia amblyommii,"" R. bellii, R. rhipicephali, and REIS, the rickettsial endosymbiont of Ixodes scapularis. All of the rickettsiae were isolated from humans or North and South American ticks. R. parkeri isolates from both continents did not possess plasmids. We have now demonstrated plasmids in nearly all Rickettsia species that we have surveyed from three continents, which represent three of the four major proposed phylogenetic groups associated with blood-feeding arthropods. Gel-based evidence consistent with the existence of multiple plasmids in some species was confirmed by cloning plasmids with very different sequences from each of two ""Ca. Rickettsia amblyommii"" isolates. Phylogenetic analysis of rickettsial ParA plasmid partitioning proteins indicated multiple parA gene origins and plasmid incompatibility groups, consistent with possible multiple plasmid origins. Phylogenetic analysis of potentially host-adaptive rickettsial small heat shock proteins showed that hsp2 genes were plasmid specific and that hsp1 genes, found only on plasmids of ""Ca. Rickettsia amblyommii,"" R. felis, R. monacensis, and R. peacockii, were probably acquired independently of the hsp2 genes. Plasmid copy numbers in seven Rickettsia species ranged from 2.4 to 9.2 per chromosomal equivalent, as determined by real-time quantitative PCR. Plasmids may be of significance in rickettsial evolution and epidemiology by conferring genetic plasticity and host-adaptive traits via horizontal gene transfer that counteracts the reductive genome evolution typical of obligate intracellular bacteria.