Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

Probabilistic consensus clustering using evidence accumulation

Clustering ensemble methods produce a consensus partition of a set of data points by combining the results of a collection of base clustering algorithms. In the evidence accumulation clustering (EAC) paradigm, the clustering ensemble is transformed into a pairwise co-association matrix, thus avoiding the label correspondence problem, which is intrinsic to other clustering ensemble schemes. In this paper, we propose a consensus clustering approach based on the EAC paradigm, which is not limited to crisp partitions and fully exploits the nature of the co-association matrix. Our solution determines probabilistic assignments of data points to clusters by minimizing a Bregman divergence between the observed co-association frequencies and the corresponding co-occurrence probabilities expressed as functions of the unknown assignments. We additionally propose an optimization algorithm to find a solution under any double-convex Bregman divergence. Experiments on both synthetic and real benchmark data show the effectiveness of the proposed approach.

A MAP approach to evidence accumulation clustering

The Evidence Accumulation Clustering (EAC) paradigm is a clustering ensemble method which derives a consensus partition from a collection of base clusterings obtained using different algorithms. It collects from the partitions in the ensemble a set of pairwise observations about the co-occurrence of objects in a same cluster and it uses these co-occurrence statistics to derive a similarity matrix, referred to as co-association matrix. The Probabilistic Evidence Accumulation for Clustering Ensembles (PEACE) algorithm is a principled approach for the extraction of a consensus clustering from the observations encoded in the co-association matrix based on a probabilistic model for the co-association matrix parameterized by the unknown assignments of objects to clusters. In this paper we extend the PEACE algorithm by deriving a consensus solution according to a MAP approach with Dirichlet priors defined for the unknown probabilistic cluster assignments. In particular, we study the positive regularization effect of Dirichlet priors on the final consensus solution with both synthetic and real benchmark data.

ECG Analysis Using Consensus Clustering

Biosignals analysis has become widespread, upstaging their typical use in clinical settings. Electrocardiography (ECG) plays a central role in patient monitoring as a diagnosis tool in today's medicine and as an emerging biometric trait. In this paper we adopt a consensus clustering approach for the unsupervised analysis of an ECG-based biometric records. This type of analysis highlights natural groups within the population under investigation, which can be correlated with ground truth information in order to gain more insights about the data. Preliminary results are promising, for meaningful clusters are extracted from the population under analysis. © 2014 EURASIP.

Quantifying the time for accurate EEG decoding of single value-based decisions.

BACKGROUND: Recent neuroimaging studies suggest that value-based decision-making may rely on mechanisms of evidence accumulation. However no studies have explicitly investigated the time when single decisions are taken based on such an accumulation process. NEW METHOD: Here, we outline a novel electroencephalography (EEG) decoding technique which is based on accumulating the probability of appearance of prototypical voltage topographies and can be used for predicting subjects' decisions. We use this approach for studying the time-course of single decisions, during a task where subjects were asked to compare reward vs. loss points for accepting or rejecting offers. RESULTS: We show that based on this new method, we can accurately decode decisions for the majority of the subjects. The typical time-period for accurate decoding was modulated by task difficulty on a trial-by-trial basis. Typical latencies of when decisions are made were detected at ∼500ms for 'easy' vs. ∼700ms for 'hard' decisions, well before subjects' response (∼340ms). Importantly, this decision time correlated with the drift rates of a diffusion model, evaluated independently at the behavioral level. COMPARISON WITH EXISTING METHOD(S): We compare the performance of our algorithm with logistic regression and support vector machine and show that we obtain significant results for a higher number of subjects than with these two approaches. We also carry out analyses at the average event-related potential level, for comparison with previous studies on decision-making. CONCLUSIONS: We present a novel approach for studying the timing of value-based decision-making, by accumulating patterns of topographic EEG activity at single-trial level.

Étude du cortex prémoteur et préfrontal lors de la prise de décision pendant l'intégration temporelle des informations

Une variété de modèles sur le processus de prise de décision dans divers contextes présume que les sujets accumulent les évidences sensorielles, échantillonnent et intègrent constamment les signaux pour et contre des hypothèses alternatives. L'intégration continue jusqu'à ce que les évidences en faveur de l'une des hypothèses dépassent un seuil de critère de décision (niveau de preuve exigé pour prendre une décision). De nouveaux modèles suggèrent que ce processus de décision est plutôt dynamique; les différents paramètres peuvent varier entre les essais et même pendant l’essai plutôt que d’être un processus statique avec des paramètres qui ne changent qu’entre les blocs d’essais. Ce projet de doctorat a pour but de démontrer que les décisions concernant les mouvements d’atteinte impliquent un mécanisme d’accumulation temporelle des informations sensorielles menant à un seuil de décision. Pour ce faire, nous avons élaboré un paradigme de prise de décision basée sur un stimulus ambigu afin de voir si les neurones du cortex moteur primaire (M1), prémoteur dorsal (PMd) et préfrontal (DLPFc) démontrent des corrélats neuronaux de ce processus d’accumulation temporelle. Nous avons tout d’abord testé différentes versions de la tâche avec l’aide de sujets humains afin de développer une tâche où l’on observe le comportement idéal des sujets pour nous permettre de vérifier l’hypothèse de travail. Les données comportementales chez l’humain et les singes des temps de réaction et du pourcentage d'erreurs montrent une augmentation systématique avec l'augmentation de l'ambigüité du stimulus. Ces résultats sont cohérents avec les prédictions des modèles de diffusion, tel que confirmé par une modélisation computationnelle des données. Nous avons, par la suite, enregistré des cellules dans M1, PMd et DLPFc de 2 singes pendant qu'ils s'exécutaient à la tâche. Les neurones de M1 ne semblent pas être influencés par l'ambiguïté des stimuli mais déchargent plutôt en corrélation avec le mouvement exécuté. Les neurones du PMd codent la direction du mouvement choisi par les singes, assez rapidement après la présentation du stimulus. De plus, l’activation de plusieurs cellules du PMd est plus lente lorsque l'ambiguïté du stimulus augmente et prend plus de temps à signaler la direction de mouvement. L’activité des neurones du PMd reflète le choix de l’animal, peu importe si c’est une bonne réponse ou une erreur. Ceci supporte un rôle du PMd dans la prise de décision concernant les mouvements d’atteinte. Finalement, nous avons débuté des enregistrements dans le cortex préfrontal et les résultats présentés sont préliminaires. Les neurones du DLPFc semblent beaucoup plus influencés par les combinaisons des facteurs de couleur et de position spatiale que les neurones du PMd. Notre conclusion est que le cortex PMd est impliqué dans l'évaluation des évidences pour ou contre la position spatiale de différentes cibles potentielles mais assez indépendamment de la couleur de celles-ci. Le cortex DLPFc serait plutôt responsable du traitement des informations pour la combinaison de la couleur et de la position des cibles spatiales et du stimulus ambigu nécessaire pour faire le lien entre le stimulus ambigu et la cible correspondante.

Analysis of hand kinematics reveals inter-individual differences in intertemporal decision dynamics

During intertemporal decisions, the preference for smaller, sooner reward over larger-delayed rewards (temporal discounting, TD) exhibits substantial inter-subject variability; however, it is currently unclear what are the mechanisms underlying this apparently idiosyncratic behavior. To answer this question, here we recorded and analyzed mouse movement kinematics during intertemporal choices in a large sample of participants (N = 86). Results revealed a specific pattern of decision dynamics associated with the selection of “immediate” versus “delayed” response alternatives, which well discriminated between a “discounter” versus a “farsighted” behavior—thus representing a reliable behavioral marker of TD preferences. By fitting the Drift Diffusion Model to the data, we showed that differences between discounter and farsighted subjects could be explained in terms of different model parameterizations, corresponding to the use of different choice mechanisms in the two groups. While farsighted subjects were biased toward the “delayed” option, discounter subjects were not correspondingly biased toward the “immediate” option. Rather, as shown by the dynamics of evidence accumulation over time, their behavior was characterized by high choice uncertainty.

Activity in inferior parietal and medial prefrontal cortex signals the accumulation of evidence in a probability learning task.

In an uncertain environment, probabilities are key to predicting future events and making adaptive choices. However, little is known about how humans learn such probabilities and where and how they are encoded in the brain, especially when they concern more than two outcomes. During functional magnetic resonance imaging (fMRI), young adults learned the probabilities of uncertain stimuli through repetitive sampling. Stimuli represented payoffs and participants had to predict their occurrence to maximize their earnings. Choices indicated loss and risk aversion but unbiased estimation of probabilities. BOLD response in medial prefrontal cortex and angular gyri increased linearly with the probability of the currently observed stimulus, untainted by its value. Connectivity analyses during rest and task revealed that these regions belonged to the default mode network. The activation of past outcomes in memory is evoked as a possible mechanism to explain the engagement of the default mode network in probability learning. A BOLD response relating to value was detected only at decision time, mainly in striatum. It is concluded that activity in inferior parietal and medial prefrontal cortex reflects the amount of evidence accumulated in favor of competing and uncertain outcomes.

Identification and quantification of phytochelatins in roots of rice to long-term exposure: evidence of individual role on arsenic accumulation and translocation

Rice has the predilection to take up arsenic in the form of methylated arsenic (o-As) and inorganic arsenic species (i-As). Plants defend themselves using i-As efflux systems and the production of phytochelatins (PCs) to complex i-As. Our study focused on the identification and quantification of phytochelatins by HPLC-ICP-MS/ESI-MS, relating them to the several variables linked to As exposure. GSH, 11 PCs, and As–PC complexes from the roots of six rice cultivars (Italica Carolina, Dom Sofid, 9524, Kitrana 508, YRL-1, and Lemont) exposed to low and high levels of i-As were compared with total, i-As, and o-As in roots, shoots, and grains. Only Dom Sofid, Kitrana 508, and 9524 were found to produce higher levels of PCs even when exposed to low levels of As. PCs were only correlated to i-As in the roots (r=0.884, P <0.001). However, significant negative correlations to As transfer factors (TF) roots–grains (r= –0.739, P <0.05) and shoots–grains (r= –0.541, P <0.05), suggested that these peptides help in trapping i-As but not o-As in the roots, reducing grains’ i-As. Italica Carolina reduced i-As in grains after high exposure, where some specific PCs had a special role in this reduction. In Lemont, exposure to elevated levels of i-As did not result in higher i-As levels in the grains and there were no significant increases in PCs or thiols. Finally, the high production of PCs in Kitrana 508 and Dom Sofid in response to high As treatment did not relate to a reduction of i-As in grains, suggesting that other mechanisms such as As–PC release and transport seems to be important in determining grain As in these cultivars.

Tumor necrosis factors alpha and beta protect neurons against amyloid beta-peptide toxicity: evidence for involvement of a kappa B-binding factor and attenuation of peroxide and Ca2+ accumulation.

In Alzheimer disease (AD) the amyloid beta-peptide (A beta) accumulates in plaques in the brain. A beta can be neurotoxic by a mechanism involving induction of reactive oxygen species (ROS) and elevation of intracellular free calcium levels ([Ca2+]i). In light of evidence for an inflammatory response in the brain in AD and reports of increased levels of tumor necrosis factor (TNF) in AD brain we tested the hypothesis that TNFs affect neuronal vulnerability to A beta. A beta-(25-35) and A beta-(1-40) induced neuronal degeneration in a concentration- and time-dependent manner. Pretreatment of cultures for 24 hr with TNF-beta or TNF-alpha resulted in significant attenuation of A beta-induced neuronal degeneration. Accumulation of peroxides induced in neurons by A beta was significantly attenuated in TNF-pretreated cultures, and TNFs protected neurons against iron toxicity, suggesting that TNFs induce antioxidant pathways. The [Ca2+]i response to glutamate (quantified by fura-2 imaging) was markedly potentiated in neurons exposed to A beta, and this action of A beta was suppressed in cultures pretreated with TNFs. Electrophoretic mobility-shift assays demonstrated an induction of a kappa beta-binding activity in hippocampal cells exposed to TNFs. Exposure of cultures to I kappa B (MAD3) antisense oligonucleotides, a manipulation designed to induce NF-kappa B, mimicked the protection by TNFs. These data suggest that TNFs protect hippocampal neurons against A beta toxicity by suppressing accumulation of ROS and Ca2+ and that kappa B-dependent transcription is sufficient to mediate these effects. A modulatory role for TNF in the neurodegenerative process in AD is proposed.

Characterization of Yeast Extracellular Vesicles: Evidence for the Participation of Different Pathways of Cellular Traffic in Vesicle Biogenesis

Background: Extracellular vesicles in yeast cells are involved in the molecular traffic across the cell wall. In yeast pathogens, these vesicles have been implicated in the transport of proteins, lipids, polysaccharide and pigments to the extracellular space. Cellular pathways required for the biogenesis of yeast extracellular vesicles are largely unknown. Methodology/Principal Findings: We characterized extracellular vesicle production in wild type (WT) and mutant strains of the model yeast Saccharomyces cerevisiae using transmission electron microscopy in combination with light scattering analysis, lipid extraction and proteomics. WT cells and mutants with defective expression of Sec4p, a secretory vesicle-associated Rab GTPase essential for Golgi-derived exocytosis, or Snf7p, which is involved in multivesicular body (MVB) formation, were analyzed in parallel. Bilayered vesicles with diameters at the 100-300 nm range were found in extracellular fractions from yeast cultures. Proteomic analysis of vesicular fractions from the cells aforementioned and additional mutants with defects in conventional secretion pathways (sec1-1, fusion of Golgi-derived exocytic vesicles with the plasma membrane; bos1-1, vesicle targeting to the Golgi complex) or MVB functionality (vps23, late endosomal trafficking) revealed a complex and interrelated protein collection. Semi-quantitative analysis of protein abundance revealed that mutations in both MVB- and Golgi-derived pathways affected the composition of yeast extracellular vesicles, but none abrogated vesicle production. Lipid analysis revealed that mutants with defects in Golgi-related components of the secretory pathway had slower vesicle release kinetics, as inferred from intracellular accumulation of sterols and reduced detection of these lipids in vesicle fractions in comparison with WT cells. Conclusions/Significance: Our results suggest that both conventional and unconventional pathways of secretion are required for biogenesis of extracellular vesicles, which demonstrate the complexity of this process in the biology of yeast cells.

Cell cycle arrest evidence, parasiticidal and bactericidal properties induced by L-amino acid oxidase from Bothrops atrox snake venom

The present article describes an L-amino acid oxidase from Bothrops atrox snake venom as with antiprotozoal activities in Trypanosoma cruzi and in different species of Leishmania (Leishmania braziliensis, Leishmania donovani and Leishmania major). Leishmanicidal effects were inhibited by catalase, suggesting that they are mediated by H(2)O(2) production. Leishmania spp. cause a spectrum of diseases, ranging from self-healing ulcers to disseminated and often fatal infections, depending on the species involved and the host`s immune response. BatroxLAAO also displays bactericidal activity against both Gram-positive and Gram-negative bacteria. The apoptosis induced by BatroxLAAO on HL-60 cell lines and PBMC cells was determined by morphological cell evaluation using a mix of fluorescent dyes. As revealed by flow cytometry analysis, suppression of cell proliferation with BatroxLAAO was accompanied by the significant accumulation of cells in the G0/G1 phase boundary in HL-60 cells. BatroxLAAO at 25 mu g/mL and 50 mu g/mL blocked G0-G1 transition, resulting in G0/G1 phase cell cycle arrest, thereby delaying the progression of cells through S and G2/M phase in HL-60 cells. This was shown by an accentuated decrease in the proportion of cells in S phase, and the almost absence of G2/M phase cell population. BatroxLAAO is an interesting enzyme that provides a better understanding of the ophidian envenomation mechanism, and has biotechnological potential as a model for therapeutic agents. (C) 2011 Elsevier Masson SAS. All rights reserved.

Do migrants' remittances decline over time? Evidence from Tongans and Western Samoans in Australia

There is concern that Pacific Island economies dependent on remittances of migrants will endure foreign exchange shortages and falling living standards as remittance levels fall because of lower migration rates and the belief that migrants' willingness to remit declines over time. The empirical validity of the remittance-decay hypothesis has never been tested. From survey data on Tongan and Western Samoan migrants in Sydney, this paper estimates remittance functions using multivariate regression analysis. It is found that the remittance-decay hypothesis has no empirical validity, and migrants are motivated by factors other than altruistic family support, including asset accumulation and investment back home.