Night and crepuscular mosquitoes and risk of vector-borne diseases in areas of piassaba extraction in the middle Negro River basin, state of Amazonas, Brazil

A study of crepuscular and night-biting mosquitoes was conducted at remote settlements along the Padauiri River, middle Negro River, state of Amazonas, Brazil. Collections were performed with human bait and a CDC-light trap on three consecutive days per month from June 2003-May 2004. In total, 1,203 h of collection were performed, of which 384 were outside and 819 were inside houses. At total of 11,612 specimens were captured, and Anophelinae (6.01%) were much less frequent than Culicinae (93.94%). Anopheles darlingi was the most frequent Anophelinae collected. Among the culicines, 2,666 Culex (Ae.) clastrieri Casal & Garcia, 2,394 Culex. (Mel.) vomerifer Komp, and 1,252 Culex (Mel.) eastor Dyar were the most frequent species collected. The diversity of insects found reveals the receptivity of the area towards a variety of diseases facilitated by the presence of vectors involved in the transmission of Plasmodium, arboviruses and other infectious agents.

Proposta de criteris per la integració d¿alumnes amb NEE greus i permanents. Una distribució mes eficaç a les USEE com a eina d¿inclusió.

Les pràctiques desenvolupades a l¿EAP (Equip Assessorament Psicopedagògic) m¿han permès un apropament a les activitats que realitzen fora i dintre dels Centres Escolars i mes concretament la intervenció que es fa mitjançant les USEE (Unitats de Suport a l¿Educació Especial. Aquestes Unitats tenen com a finalitat afavorir la inclusió dels alumnes amb Necessitats Especials (NEE) amb dictamen. Mitjançant aquest treball podrem analitzar com la proposta de uns criteris clars i ben definits permet millorar la distribució d¿aquest alumnat i a la vegada aprofitar millor els recursos de suport dels Centres Educatius. De la mateixa manera aquesta proposta de criteris pot servir d¿oportunitat per establir nous escenaris de cooperació entre les unitats de suport i el sistema docent de l¿aula ordinària.

Perspectives for Forensic Intelligence in anti-doping: thinking outside the box

Today's approach to anti-doping is mostly centered on the judicial process, despite pursuing a further goal in the detection, reduction, solving and/or prevention of doping. Similarly to decision-making in the area of law enforcement feeding on Forensic Intelligence, anti-doping might significantly benefit from a more extensive gathering of knowledge. Forensic Intelligence might bring a broader logical dimension to the interpretation of data on doping activities for a more future-oriented and comprehensive approach instead of the traditional case-based and reactive process. Information coming from a variety of sources related to doping, whether directly or potentially, would feed an organized memory to provide real time intelligence on the size, seriousness and evolution of the phenomenon. Due to the complexity of doping, integrating analytical chemical results and longitudinal monitoring of biomarkers with physiological, epidemiological, sociological or circumstantial information might provide a logical framework enabling fit for purpose decision-making. Therefore, Anti-Doping Intelligence might prove efficient at providing a more proactive response to any potential or emerging doping phenomenon or to address existing problems with innovative actions or/and policies. This approach might prove useful to detect, neutralize, disrupt and/or prevent organized doping or the trafficking of doping agents, as well as helping to refine the targeting of athletes or teams. In addition, such an intelligence-led methodology would serve to address doping offenses in the absence of adverse analytical chemical evidence.

An iterative Multiscale Finite-Volume algorithm converging to the exact solution

The multiscale finite volume (MsFV) method has been developed to efficiently solve large heterogeneous problems (elliptic or parabolic); it is usually employed for pressure equations and delivers conservative flux fields to be used in transport problems. The method essentially relies on the hypothesis that the (fine-scale) problem can be reasonably described by a set of local solutions coupled by a conservative global (coarse-scale) problem. In most cases, the boundary conditions assigned for the local problems are satisfactory and the approximate conservative fluxes provided by the method are accurate. In numerically challenging cases, however, a more accurate localization is required to obtain a good approximation of the fine-scale solution. In this paper we develop a procedure to iteratively improve the boundary conditions of the local problems. The algorithm relies on the data structure of the MsFV method and employs a Krylov-subspace projection method to obtain an unconditionally stable scheme and accelerate convergence. Two variants are considered: in the first, only the MsFV operator is used; in the second, the MsFV operator is combined in a two-step method with an operator derived from the problem solved to construct the conservative flux field. The resulting iterative MsFV algorithms allow arbitrary reduction of the solution error without compromising the construction of a conservative flux field, which is guaranteed at any iteration. Since it converges to the exact solution, the method can be regarded as a linear solver. In this context, the schemes proposed here can be viewed as preconditioned versions of the Generalized Minimal Residual method (GMRES), with a very peculiar characteristic that the residual on the coarse grid is zero at any iteration (thus conservative fluxes can be obtained).

Proposal of a parallel architecture for a motion detection algorithm

This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed

Speculative parallelization of multipath radiosity algorithm

In computer graphics, global illumination algorithms take into account not only the light that comes directly from the sources, but also the light interreflections. This kind of algorithms produce very realistic images, but at a high computational cost, especially when dealing with complex environments. Parallel computation has been successfully applied to such algorithms in order to make it possible to compute highly-realistic images in a reasonable time. We introduce here a speculation-based parallel solution for a global illumination algorithm in the context of radiosity, in which we have taken advantage of the hierarchical nature of such an algorithm

A Monte Carlo-Based Fiber Tracking Algorithm using Diffusion Tensor MRI

Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach

Shape complexity based on mutual information

Shape complexity has recently received attention from different fields, such as computer vision and psychology. In this paper, integral geometry and information theory tools are applied to quantify the shape complexity from two different perspectives: from the inside of the object, we evaluate its degree of structure or correlation between its surfaces (inner complexity), and from the outside, we compute its degree of interaction with the circumscribing sphere (outer complexity). Our shape complexity measures are based on the following two facts: uniformly distributed global lines crossing an object define a continuous information channel and the continuous mutual information of this channel is independent of the object discretisation and invariant to translations, rotations, and changes of scale. The measures introduced in this paper can be potentially used as shape descriptors for object recognition, image retrieval, object localisation, tumour analysis, and protein docking, among others

Constraint algorithm for k-presymplectic Hamiltonian systems. Application to singular field theories

The k-symplectic formulation of field theories is especially simple, since only tangent and cotangent bundles are needed in its description. Its defining elements show a close relationship with those in the symplectic formulation of mechanics. It will be shown that this relationship also stands in the presymplectic case. In a natural way,one can mimick the presymplectic constraint algorithm to obtain a constraint algorithmthat can be applied to k-presymplectic field theory, and more particularly to the Lagrangian and Hamiltonian formulations offield theories defined by a singular Lagrangian, as well as to the unified Lagrangian-Hamiltonian formalism (Skinner--Rusk formalism) for k-presymplectic field theory. Two examples of application of the algorithm are also analyzed.

Leishmania aethiopica field isolates bearing an endosymbiontic dsRNA virus induce pro-inflammatory cytokine response.

BACKGROUND: Infection with Leishmania parasites causes mainly cutaneous lesions at the site of the sand fly bite. Inflammatory metastatic forms have been reported with Leishmania species such as L. braziliensis, guyanensis and aethiopica. Little is known about the factors underlying such exacerbated clinical presentations. Leishmania RNA virus (LRV) is mainly found within South American Leishmania braziliensis and guyanensis. In a mouse model of L. guyanensis infection, its presence is responsible for an hyper-inflammatory response driven by the recognition of the viral dsRNA genome by the host Toll-like Receptor 3 leading to an exacerbation of the disease. In one instance, LRV was reported outside of South America, namely in the L. major ASKH strain from Turkmenistan, suggesting that LRV appeared before the divergence of Leishmania subgenera. LRV presence inside Leishmania parasites could be one of the factors implicated in disease severity, providing rationale for LRV screening in L. aethiopica. METHODOLOGY/PRINCIPAL FINDINGS: A new LRV member was identified in four L. aethiopica strains (LRV-Lae). Three LRV-Lae genomes were sequenced and compared to L. guyanensis LRV1 and L. major LRV2. LRV-Lae more closely resembled LRV2. Despite their similar genomic organization, a notable difference was observed in the region where the capsid protein and viral polymerase open reading frames overlap, with a unique -1 situation in LRV-Lae. In vitro infection of murine macrophages showed that LRV-Lae induced a TLR3-dependent inflammatory response as previously observed for LRV1. CONCLUSIONS/SIGNIFICANCE: In this study, we report the presence of an immunogenic dsRNA virus in L. aethiopica human isolates. This is the first observation of LRV in Africa, and together with the unique description of LRV2 in Turkmenistan, it confirmed that LRV was present before the divergence of the L. (Leishmania) and (Viannia) subgenera. The potential implication of LRV-Lae on disease severity due to L. aethiopica infections is discussed.

Risk assessment of recurrence in sporadic retinoblastoma using a molecular-based algorithm

Le rétinoblastome (Rb) est une tumeur provenant des cellules rétiniennes progénitrices des photorécepteurs. C'est la tumeur pédiatrique maligne la plus fréquente avec une incidence par naissance évaluée entre 1/15Ό00 et 1/20Ό00. Les enfants atteints de Rb sont diagnostiqué dans leur grande majorité avant l'âge de 4 ans, soit le temps nécessaire à la différentiation et à la maturation des photorécepteurs et donc à la disparition de la cellule d'origine du Rb. La survie du patient, la sauvegarde oculaire et le pronostic visuel restent excellents pour autant que le traitement ne soit pas différé. Dans sa variante non héréditaire (60%) le Rb est toujours unilatéral et sporadique. Le Rb héréditaire de transmission dominante autosomique (40%), se décline sous toutes les formes, familiale (10%) ou sporadique (30%), que l'atteinte soit unilatérale ou bilatérale. La majorité des mutations causales sont uniques et distribuées de façon aléatoire sur la totalité du gène RB1 sans région prédisposante. La détection de ces mutations est couteuse et chronophage, tout en présentant un taux de détection relativement bas; surtout dans les cas de Rb sporadiques unilatéraux. Dans le but d'identifier les patients présentant un risque réel de développer un Rb, et de réduire le nombre d'examens sous narcose requis pour le dépistage de la maladie chez les sujets à risque, nous avons développé une stratégie sensible, rapide, efficace et peu couteuse basée sur une analyse de l'haplotype intragénique. Cet algorithme prend en compte a) la perte d'hétérozygotie intratumorale du gène RB1, b) l'origine paternelle préférentielle des nouvelles mutations germinales et c) un risque a priori dérivé des données empiriques de Vogel. Pendant la période allant de janvier 1994 à décembre 2006, nous avons comparé l'apparition de nouveau Rb parmi la fratrie et la descendance de patient atteints au nombre de nouveaux cas attendus calculé par notre algorithme. 134 familles ont été étudiées. L'analyse moléculaire a été effectuée chez 570 personnes dont 99 patients âgés de moins de 4 ans et donc à risque de développer un Rb. Parmi cette cohorte, nous avons observé l'apparition d'un cas de Rb, alors que les risques cumulés a posteriori calculé par notre algorithme prédisait l'apparition de 1.77 nouveau cas. Dans cette étude, nous avons pu valider notre algorithme prédisant la récurrence de Rb chez les parents de 1er degré de patients atteints. Cet outil devrait grandement faciliter le conseil génétique ainsi que le suivi des patients à risque de développer un Rb, surtout dans les cas ou le séquençage direct du gène RB1 n'est pas disponible ou est resté non informatif. - Purpose: Most RBI mutations are unique and distributed throughout the RBI gene. Their detection can be time-consuming and the yield especially low in cases of conservatively-treated sporadic unilateral retinoblas-toma (Rb) patients. In order to identify patients with true risk of developing Rb, and to reduce the number of unnecessary examinations under anesthesia in all other cases, we developed a universal sensitive, efficient and cost-effective strategy based on intragenic haplotype analysis. Methods: This algorithm allows the calculation of the a posteriori risk of developing Rb and takes into account (a) RBI loss of heterozygosity in tumors, (b) preferential paternal origin of new germline mutations, (c) a priori risk derived from empirical data by Vogel, and (d) disease penetrance of 90% in most cases. We report the occurrence of Rb in first degree relatives of patients with sporadic Rb who visited the Jules Gonin Eye Hospital, Lausanne, Switzerland, from January 1994 to December 2006 compared to expected new cases of Rb using our algorithm. Results: A total of 134 families with sporadic Rb were enrolled; testing was performed in 570 individuals and 99 patients younger than 4 years old were identified. We observed one new case of Rb. Using our algorithm, the cumulated total a posteriori risk of recurrence was 1.77. Conclusions: This is the first time that linkage analysis has been validated to monitor the risk of recurrence in sporadic Rb. This should be a useful tool in genetic counseling, especially when direct RBI screening for mutations leaves a negative result or is unavailable.

Experimental infection with the Toxoplasma gondii ME-49 strain in the Brazilian BR-1 mini pig is a suitable animal model for human toxoplasmosis

Toxoplasma gondii causes toxoplasmosis, a worldwide disease. Experimentation with pigs is necessary for the development of new therapeutic approaches to human diseases. BR-1 mini pigs were intramuscularly infected with T. gondii with tachyzoites (RH strain) or orally infected with cysts (ME-49 strain). Haematology and serum biochemistry were analysed and buffy coat cells were inoculated in mice to determine tachyzoite circulation. No alterations were observed in erythrocyte and platelet values; however, band neutrophils increased seven days after infection with ME-49. Serology of the mice inoculated with pig blood leucocytes revealed circulating ME-49 or RH strain tachyzoites in the pigs' peripheral blood at two and seven or nine days post-infection. The tachyzoites were also directly observed in blood smears from the infected pigs outside and inside leucocytes for longer periods. Alanine-aminotransferase was high at days 21 and 32 in the RH infected pigs. After 90 days, the pigs were euthanised and their tissue samples were processed and inoculated into mice. The mice serology revealed the presence of parasites in the hearts, ileums and mesenteric lymph nodes of the pigs. Additionally, cysts in the mice were only observed after pig heart tissue inoculation. The infected pigs presented similar human outcomes with relatively low pathogenicity and the BR-1 mini pig model infected with ME-49 is suitable to monitor experimental toxoplasmosis.

A Label space reduction algorithm for P2MP LSPs using asymmetric tunnels

The aim of traffic engineering is to optimise network resource utilization. Although several works on minimizing network resource utilization have been published, few works have focused on LSR label space. This paper proposes an algorithm that uses MPLS label stack features in order to reduce the number of labels used in LSPs forwarding. Some tunnelling methods and their MPLS implementation drawbacks are also discussed. The algorithm described sets up the NHLFE tables in each LSR, creating asymmetric tunnels when possible. Experimental results show that the algorithm achieves a large reduction factor in the label space. The work presented here applies for both types of connections: P2MP and P2P

Use of Hy's law and a new composite algorithm to predict acute liver failure in patients with drug-induced liver injury.

BACKGROUND & AIMS Hy's Law, which states that hepatocellular drug-induced liver injury (DILI) with jaundice indicates a serious reaction, is used widely to determine risk for acute liver failure (ALF). We aimed to optimize the definition of Hy's Law and to develop a model for predicting ALF in patients with DILI. METHODS We collected data from 771 patients with DILI (805 episodes) from the Spanish DILI registry, from April 1994 through August 2012. We analyzed data collected at DILI recognition and at the time of peak levels of alanine aminotransferase (ALT) and total bilirubin (TBL). RESULTS Of the 771 patients with DILI, 32 developed ALF. Hepatocellular injury, female sex, high levels of TBL, and a high ratio of aspartate aminotransferase (AST):ALT were independent risk factors for ALF. We compared 3 ways to use Hy's Law to predict which patients would develop ALF; all included TBL greater than 2-fold the upper limit of normal (×ULN) and either ALT level greater than 3 × ULN, a ratio (R) value (ALT × ULN/alkaline phosphatase × ULN) of 5 or greater, or a new ratio (nR) value (ALT or AST, whichever produced the highest ×ULN/ alkaline phosphatase × ULN value) of 5 or greater. At recognition of DILI, the R- and nR-based models identified patients who developed ALF with 67% and 63% specificity, respectively, whereas use of only ALT level identified them with 44% specificity. However, the level of ALT and the nR model each identified patients who developed ALF with 90% sensitivity, whereas the R criteria identified them with 83% sensitivity. An equal number of patients who did and did not develop ALF had alkaline phosphatase levels greater than 2 × ULN. An algorithm based on AST level greater than 17.3 × ULN, TBL greater than 6.6 × ULN, and AST:ALT greater than 1.5 identified patients who developed ALF with 82% specificity and 80% sensitivity. CONCLUSIONS When applied at DILI recognition, the nR criteria for Hy's Law provides the best balance of sensitivity and specificity whereas our new composite algorithm provides additional specificity in predicting the ultimate development of ALF.