Predicting the geographic distribution of Lutzomyia longipalpis (Diptera: Psychodidae) and visceral leishmaniasis in the state of Mato Grosso do Sul, Brazil

To understand the geographic distribution of visceral leishmaniasis (VL) in the state of Mato Grosso do Sul (MS), Brazil, both the climatic niches of Lutzomyia longipalpis and VL cases were analysed. Distributional data were obtained from 55 of the 79 counties of MS between 2003-2012. Ecological niche models (ENM) of Lu. longipalpis and VL cases were produced using the maximum entropy algorithm based on eight climatic variables. Lu. longipalpis showed a wide distribution in MS. The highest climatic suitability for Lu. longipalpis was observed in southern MS. Temperature seasonality and annual mean precipitation were the variables that most influenced these models. Two areas of high climatic suitability for the occurrence of VL cases were predicted: one near Aquidauana and another encompassing several municipalities in the southeast region of MS. As expected, a large overlap between the models for Lu. longipalpis and VL cases was detected. Northern and northwestern areas of MS were suitable for the occurrence of cases, but did not show high climatic suitability for Lu. longipalpis . ENM of vectors and human cases provided a greater understanding of the geographic distribution of VL in MS, which can be applied to the development of future surveillance strategies.

Visualització de volums usant miralls màgics

En el marc del conveni de col·laboració entre el Grup de Gràfics de Girona de la Universitat de Girona i el Grup de Neuroradiologia de l’Institut de Diagnòstic per la Imatge de l’Hospital Universitari Dr. Josep Trueta de Girona, es planteja desenvolupar la plataforma StarViewer, una plataforma que incorpori les tècniques bàsiques de visualització científica complementant la visualització 2D tradicional amb una visualització 3D que permeti inspeccionar la informació del pacient de forma més eficient i facilitant-ne el seu diagnòstic. En aquest projecte s’implementen dos tècniques que formaran part de la plataforma StarViewer. El primer objectiu és implementar un mètode per facilitar la visualització i la interpretació de models de vòxels simples i models de vòxels fusionats, i el segon és implementar un mètode basat en mesures de la Teoria de la Informació per ajudar l’usuari a trobar el punt de vista òptim per a un model donat. Per assolir el primer objectiu ens centrarem en la tècnica dels Miralls màgics o Magic Mirrors, que permeten la visualització simultània del model de vòxels des de diferents punts de vista, i per al segon objectiu, en el concepte d’excess entropy, que és una mesura de la informació, per determinar quin punt de vista aporta més informació a l’usuari

Calorimetry of dehydrogenation and dangling-bond recombination in several hydrogenated amorphous silicon materials

Differential scanning calorimetry (DSC) was used to study the dehydrogenation processes that take place in three hydrogenated amorphous silicon materials: nanoparticles, polymorphous silicon, and conventional device-quality amorphous silicon. Comparison of DSC thermograms with evolved gas analysis (EGA) has led to the identification of four dehydrogenation processes arising from polymeric chains (A), SiH groups at the surfaces of internal voids (A'), SiH groups at interfaces (B), and in the bulk (C). All of them are slightly exothermic with enthalpies below 50 meV/H atoms , indicating that, after dissociation of any SiH group, most dangling bonds recombine. The kinetics of the three low-temperature processes [with DSC peak temperatures at around 320 (A),360 (A'), and 430°C (B)] exhibit a kinetic-compensation effect characterized by a linea relationship between the activation entropy and enthalpy, which constitutes their signature. Their Si-H bond-dissociation energies have been determined to be E (Si-H)0=3.14 (A), 3.19 (A'), and 3.28 eV (B). In these cases it was possible to extract the formation energy E(DB) of the dangling bonds that recombine after Si-H bond breaking [0.97 (A), 1.05 (A'), and 1.12 (B)]. It is concluded that E(DB) increases with the degree of confinement and that E(DB)>1.10 eV for the isolated dangling bond in the bulk. After Si-H dissociation and for the low-temperature processes, hydrogen is transported in molecular form and a low relaxation of the silicon network is promoted. This is in contrast to the high-temperature process for which the diffusion of H in atomic form induces a substantial lattice relaxation that, for the conventional amorphous sample, releases energy of around 600 meV per H atom. It is argued that the density of sites in the Si network for H trapping diminishes during atomic diffusion

Critical analysis and extension of the Hirshfeld atoms in molecules

The computational approach to the Hirshfeld [Theor. Chim. Acta 44, 129 (1977)] atom in a molecule is critically investigated, and several difficulties are highlighted. It is shown that these difficulties are mitigated by an alternative, iterative version, of the Hirshfeld partitioning procedure. The iterative scheme ensures that the Hirshfeld definition represents a mathematically proper information entropy, allows the Hirshfeld approach to be used for charged molecules, eliminates arbitrariness in the choice of the promolecule, and increases the magnitudes of the charges. The resulting "Hirshfeld-I charges" correlate well with electrostatic potential derived atomic charges

Informed Control Over Inputs and Extent of Industrial Processing, June 2005

Stylized facts regarding the industrial process include emphases on obtaining information about and control over the quality of raw materials. We provide a model that establishes conditions under which informed control involves ensuring uniformity in inputs and increased uniformity encourages more extensive processing. We show when the Boltzmann-Shannon entropy statistic is an appropriate measure of uniformity.

Applause identification and its relevance to archival of Carnatic music

A Carnatic music concert is made up of a sequence of pieces, where each piece corresponds to a particular genre and ra¯aga (melody). Unlike a western music concert, the artist may be applauded intra-performance inter-performance. Most Carnatic music that is archived today correspond to a single audio recordings of entire concerts.The purpose of this paper is to segment single audio recordings into a sequence of pieces using thecharacteristic features of applause and music. Spectral flux, spectral entropy change quite significantly from music to applause and vice-versa. The characteristics of these features for a subset of concerts was studied. A threshold based approach was used to segment the pieces into music fragments and applauses. Preliminary resultson recordings 19 concerts from matched microphones show that the EER is about 17% for a resolution of 0.25 seconds. Further, a parameter called CUSUM is estimatedfor the applause regions. The CUSUM values determine the strength of the applause. The CUSUM is used to characterise the highlights of a concert.

Shifts in species and phylogenetic diversity between sapling and tree communities indicate negative density dependence in a lowland rain forest

1. As trees in a given cohort progress through ontogeny, many individuals die. This risk of mortality is unevenly distributed across species because of many processes such as habitat filtering, interspecific competition and negative density dependence. Here, we predict and test the patterns that such ecological processes should inscribe on both species and phylogenetic diversity as plants recruit from saplings to the canopy. 2. We compared species and phylogenetic diversity of sapling and tree communities at two sites in French Guiana. We surveyed 2084 adult trees in four 1-ha tree plots and 943 saplings in sixteen 16-m2 subplots nested within the tree plots. Species diversity was measured using Fisher's alpha (species richness) and Simpson's index (species evenness). Phylogenetic diversity was measured using Faith's phylogenetic diversity (phylogenetic richness) and Rao's quadratic entropy index (phylogenetic evenness). The phylogenetic diversity indices were inferred using four phylogenetic hypotheses: two based on rbcLa plastid DNA sequences obtained from the inventoried individuals with different branch lengths, a global phylogeny available from the Angiosperm Phylogeny Group, and a combination of both. 3. Taxonomic identification of the saplings was performed by combining morphological and DNA barcoding techniques using three plant DNA barcodes (psbA-trnH, rpoC1 and rbcLa). DNA barcoding enabled us to increase species assignment and to assign unidentified saplings to molecular operational taxonomic units. 4. Species richness was similar between saplings and trees, but in about half of our comparisons, species evenness was higher in trees than in saplings. This suggests that negative density dependence plays an important role during the sapling-to-tree transition. 5. Phylogenetic richness increased between saplings and trees in about half of the comparisons. Phylogenetic evenness increased significantly between saplings and trees in a few cases (4 out of 16) and only with the most resolved phylogeny. These results suggest that negative density dependence operates largely independently of the phylogenetic structure of communities. 6. Synthesis. By contrasting species richness and evenness across size classes, we suggest that negative density dependence drives shifts in composition during the sapling-to-tree transition. In addition, we found little evidence for a change in phylogenetic diversity across age classes, suggesting that the observed patterns are not phylogenetically constrained.

On the Properties and Cosmology of Q-balls

The properties and cosmological importance of a class of non-topological solitons, Q-balls, are studied. Aspects of Q-ball solutions and Q-ball cosmology discussed in the literature are reviewed. Q-balls are particularly considered in the Minimal Supersymmetric Standard Model with supersymmetry broken by a hidden sector mechanism mediated by either gravity or gauge interactions. Q-ball profiles, charge-energy relations and evaporation rates for realistic Q-ball profiles are calculated for general polynomial potentials and for the gravity mediated scenario. In all of the cases, the evaporation rates are found to increase with decreasing charge. Q-ball collisions are studied by numerical means in the two supersymmetry breaking scenarios. It is noted that the collision processes can be divided into three types: fusion, charge transfer and elastic scattering. Cross-sections are calculated for the different types of processes in the different scenarios. The formation of Q-balls from the fragmentation of the Aflieck-Dine -condensate is studied by numerical and analytical means. The charge distribution is found to depend strongly on the initial energy-charge ratio of the condensate. The final state is typically noted to consist of Q- and anti-Q-balls in a state of maximum entropy. By studying the relaxation of excited Q-balls the rate at which excess energy can be emitted is calculated in the gravity mediated scenario. The Q-ball is also found to withstand excess energy well without significant charge loss. The possible cosmological consequences of these Q-ball properties are discussed.

BME-based uncertainty assessment of the Chernobyl fallout

The vast territories that have been radioactively contaminated during the 1986 Chernobyl accident provide a substantial data set of radioactive monitoring data, which can be used for the verification and testing of the different spatial estimation (prediction) methods involved in risk assessment studies. Using the Chernobyl data set for such a purpose is motivated by its heterogeneous spatial structure (the data are characterized by large-scale correlations, short-scale variability, spotty features, etc.). The present work is concerned with the application of the Bayesian Maximum Entropy (BME) method to estimate the extent and the magnitude of the radioactive soil contamination by 137Cs due to the Chernobyl fallout. The powerful BME method allows rigorous incorporation of a wide variety of knowledge bases into the spatial estimation procedure leading to informative contamination maps. Exact measurements (?hard? data) are combined with secondary information on local uncertainties (treated as ?soft? data) to generate science-based uncertainty assessment of soil contamination estimates at unsampled locations. BME describes uncertainty in terms of the posterior probability distributions generated across space, whereas no assumption about the underlying distribution is made and non-linear estimators are automatically incorporated. Traditional estimation variances based on the assumption of an underlying Gaussian distribution (analogous, e.g., to the kriging variance) can be derived as a special case of the BME uncertainty analysis. The BME estimates obtained using hard and soft data are compared with the BME estimates obtained using only hard data. The comparison involves both the accuracy of the estimation maps using the exact data and the assessment of the associated uncertainty using repeated measurements. Furthermore, a comparison of the spatial estimation accuracy obtained by the two methods was carried out using a validation data set of hard data. Finally, a separate uncertainty analysis was conducted that evaluated the ability of the posterior probabilities to reproduce the distribution of the raw repeated measurements available in certain populated sites. The analysis provides an illustration of the improvement in mapping accuracy obtained by adding soft data to the existing hard data and, in general, demonstrates that the BME method performs well both in terms of estimation accuracy as well as in terms estimation error assessment, which are both useful features for the Chernobyl fallout study.

Caracterização das Comunidades Subtidais de Macroinvertebrados Bentónicos de Substrato Rochoso da Ilha de São Vicente, Cabo Verde

The Cape Verde Archipelago location and its biogeographical features are of special interest for Marine Ecology. However, there’s a lack of knowledge regarding the composition of the coastal ecosystems in this region, especially about benthic macroinvertebrates subtidal communities. Between August and October of 2007, eight locations around the island of São Vicente were sampled. Within each of those spots, fragments of substratum were collected and throughout the processing of the collected data, a total of 4032 individuals were counted, which belong to 81 different species. Shannon’s Entropy and Gini-Simpson’s diversity index were calculated, as the real number of species each one represented. By comparing the results, differences between sampling stations and between indices within the same sampling station were found. With the purpose of clustering the sampled locations according to the number of collected organisms by species, a dendrogram was elaborated and a principal component analysis was carried out. The considered sampling stations didn’t reveal significant differences according to the composition of their benthic macroinvertebrates subtidal communities in terms of great taxonomic groups or functional groups. It’s assumed that they differ only by minute traits.

Adult sex ratio effects on male survivorship of Drosophila melanogaster Meigen (Diptera, Drosophilidae)

The behavioral biology has a central role in evolutionary biology mainly because the antagonistic relations that occur in the sexual reproduction. One involves the effect of reproduction on the future life expectation. In this scenario, changes in male operational sex ratio could lead to an increase in mortality due to costs associated with excessive courtship and mating displays. Thus, this work experimentally altered the male sex ratio of Drosophila melanogaster Meigen, 1830, to determine its impact on mortality. The results indicated that mortality increases as the sex ratio changes, including modifications in the survivorship curve type and in the curve concavity, measured by entropy.

Worst-case bounds for the logarithmic loss of predictors

We investigate on-line prediction of individual sequences. Given a class of predictors, the goal is to predict as well as the best predictor in the class, where the loss is measured by the self information (logarithmic) loss function. The excess loss (regret) is closely related to the redundancy of the associated lossless universal code. Using Shtarkov's theorem and tools from empirical process theory, we prove a general upper bound on the best possible (minimax) regret. The bound depends on certain metric properties of the class of predictors. We apply the bound to both parametric and nonparametric classes ofpredictors. Finally, we point out a suboptimal behavior of the popular Bayesian weighted average algorithm.

Model selection and error estimation

We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of the error estimate. We consider several penalty functions, involving error estimates on independent test data, empirical {\sc vc} dimension, empirical {\sc vc} entropy, andmargin-based quantities. We also consider the maximal difference between the error on the first half of the training data and the second half, and the expected maximal discrepancy, a closely related capacity estimate that can be calculated by Monte Carlo integration. Maximal discrepancy penalty functions are appealing for pattern classification problems, since their computation is equivalent to empirical risk minimization over the training data with some labels flipped.

Characterization of a major V3 duplication in the NS5A region of genotype 1b HCV by quasispecies analysis in a French multicenter study

Background and Aims: The NS5A protein of the HCV is known tobe involved in viral replication and assembly and probably in theresistance to Interferon based-therapy. Previous studies identifiedinsertions or deletions from 1 to 12 nucleotides in several genomicregions. In a multicenter study (17 French and 1 Swiss laboratoriesof virology), we identified for the first time a 31 amino acidsinsertion leading to a duplication of the V3 domain in the NS5Aregion with a high prevalence. Quasispecies of each strain withduplication were characterized and the inserted V3 domain wasidentified.Methods: Between 2006 and 2008, 1067 patients chronicallyinfected with a 1b HCV were consecutively included in the study.We first amplified the V3 region by RT-PCR to detect duplication(919 samples successfully amplified). The entire NS5A region wasthen amplified, cloned and sequenced in strains bearing theduplication. V3 sequences (called R1 and R2) from each clonewere analyzed with BioEdit and compared to a V3 consensussequence (C) built from the Database Los Alamos Hepatitis C.Entropy was determined at each position.Results: V3 duplications were identified in 25 patients representinga prevalence of 2.72%. We sequenced 2043 clones from which776 had a complete coding NS5A sequence (corresponding toa mean of 30 clones per patient). At the intra-individual level,6 to 17 variants were identified per V3 region, with a maximum of3 different amino acids. At the inter-individual level, a differenceof 7 and 2 amino acids was observed between C and R1 and R2sequences, respectively. Moreover few positions presented entropyhigher than 1 (4 for the R1, 2 for the R2 and 2 for the C). Among allthe sequenced clones, more than 60% were defective virus (partialfragment of NS5A or stop codon).Conclusions: We identified a duplication of the V3 domain ingenotype 1b HCV with a high prevalence. The R2 domain, which wasthe most similar to the C region, might probably be the "original"domain, whereas R1 should be the inserted domain. Phylogeneticanalyses are under process to confirm this hypothesis.

Active learning methods for remote sensing image classification

In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.