995 resultados para vector flow


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Comparision by scanning electron microscopy (SEM) of Trypanosoma cruzi flagellates attached to the cuticle of the rectal gland of infected Dipetalogaster maxima nymphs, showed marked differences before amd after feeding. Before feeding numerous metacyclic trypomastigotes were observed among the abundant epimastigotes that formed the carpet of flagellates. On the other hand, in insects that were allowed to urinate for 24 hours after a meal, the metacyclics were scarce,indicating that they had been detached by the urine flow. An asymetric type of cell division, probably originating both an epi-and a trypomastigote, was occasionally observed. The occurrence of swellings at different levels of the flagella of epimastigotes suggests that secondary sites of attachment may be common.

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In this paper we present a prototype of a control flow for an a posteriori drug dose adaptation for Chronic Myelogenous Leukemia (CML) patients. The control flow is modeled using Timed Automata extended with Tasks (TAT) model. The feedback loop of the control flow includes the decision-making process for drug dose adaptation. This is based on the outputs of the body response model represented by the Support Vector Machine (SVM) algorithm for drug concentration prediction. The decision is further checked for conformity with the dose level rules of a medical guideline. We also have developed an automatic code synthesizer for the icycom platform as an extension of the TIMES tool.

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The population genetic structure of Anopheles darlingi, the major human malaria vector in the Neotropics, was examined using seven microsatellite loci from nine localities in central and western Amazonian Brazil. High levels of genetic variability were detected (5-25 alleles per locus; H E = 0.519-0.949). There was deviation from Hardy-Weinberg Equilibrium for 59.79% of the tests due to heterozygote deficits, while the analysis of linkage disequilibrium was significant for only two of 189 (1.05%) tests, most likely caused by null alleles. Genetic differentiation (F ST = 0.001-0.095; Nm = 4.7-363.8) indicates that gene flow is extensive among locations < 152 km apart (with two exceptions) and reduced, but not absent, at a larger geographic scale. Genetic and geographic distances were significantly correlated (R² = 0.893, P < 0.0002), supporting the isolation by distance (IBD) model. The overall estimate of Ne was 202.4 individuals under the linkage disequilibrium model, and 8 under the heterozygote excess model. Analysis of molecular variance showed that nearly all variation (~ 94%) was within sample locations. The UPGMA phenogram clustered the samples geographically, with one branch including 5/6 of the state of Amazonas localities and the other branch the Acre, Rondônia, and remaining Amazonas localities. Taken together, these data suggest little genetic structure for An. darlingi from central and western Amazonian Brazil. These findings also imply that the IBD model explains nearly all of the differentiation detected. In practical terms, populations of An. darlingi at distances < 152 km should respond similarly to vector control measures, because of high gene flow.

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Anopheles darlingi is the most important Brazilian malaria vector, with a widespread distribution in the Amazon forest. Effective strategies for vector control could be better developed through knowledge of its genetic structure and gene flow among populations, to assess the vector diversity and competence in transmitting Plasmodium. The aim of this study was to assess the genetic diversity of An. darlingi collected at four locations in Porto Velho, by sequencing a fragment of the ND4 mitochondrial gene. From 218 individual mosquitoes, we obtained 20 different haplotypes with a diversity index of 0.756, equivalent to that found in other neotropical anophelines. The analysis did not demonstrate significant population structure. However, haplotype diversity within some populations seems to be over-represented, suggesting the presence of sub-populations, but the presence of highly represented haplotypes complicates this analysis. There was no clear correlation among genetic and geographical distance and there were differences in relation to seasonality, which is important for malarial epidemiology.

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The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

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A procedure is described that allows the simple identification and sorting of live human cells that transcribe actively the HIV virus, based on the detection of GFP fluorescence in cells. Using adenoviral vectors for gene transfer, an expression cassette including the HIV-1 LTR driving the reporter gene GFP was introduced into cells that expressed stably either the Tat transcriptional activator, or an inactive mutant of Tat. Both northern and fluorescence-activated cell sorting (FACS) analysis indicate that cells containing the functional Tat protein presented levels of GFP mRNA and GFP fluorescence several orders of magnitude higher than control cells. Correspondingly, cells infected with HIV-1 showed similar enhanced reporter gene activation. HIV-1-infected cells of the lymphocytic line Jurkat were easily identified by fluorescence-activated cell sorting (FACS) as they displayed a much higher green fluorescence after transduction with the reporter adenoviral vector. This procedure could also be applied on primary human cells as blood monocyte-derived macrophages exposed to the adenoviral LTR-GFP reporter presented a much higher fluorescence when infected with HIV-1 compared with HIV-uninfected cells. The vector described has the advantages of labelling cells independently of their proliferation status and that analysis can be carried on intact cells which can be isolated subsequently by fluorescence-activated cell sorting (FACS) for further culture. This work suggests that adenoviral vectors carrying a virus-specific transcriptional control element controlling the expressions of a fluorescent protein will be useful in the identification and isolation of cells transcribing actively the viral template, and to be of use for drug screening and susceptibility assays.

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Fluvial deposits are a challenge for modelling flow in sub-surface reservoirs. Connectivity and continuity of permeable bodies have a major impact on fluid flow in porous media. Contemporary object-based and multipoint statistics methods face a problem of robust representation of connected structures. An alternative approach to model petrophysical properties is based on machine learning algorithm ? Support Vector Regression (SVR). Semi-supervised SVR is able to establish spatial connectivity taking into account the prior knowledge on natural similarities. SVR as a learning algorithm is robust to noise and captures dependencies from all available data. Semi-supervised SVR applied to a synthetic fluvial reservoir demonstrated robust results, which are well matched to the flow performance

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Parasite population structure is often thought to be largely shaped by that of its host. In the case of a parasite with a complex life cycle, two host species, each with their own patterns of demography and migration, spread the parasite. However, the population structure of the parasite is predicted to resemble only that of the most vagile host species. In this study, we tested this prediction in the context of a vector-transmitted parasite. We sampled the haemosporidian parasite Polychromophilus melanipherus across its European range, together with its bat fly vector Nycteribia schmidlii and its host, the bent-winged bat Miniopterus schreibersii. Based on microsatellite analyses, the wingless vector, and not the bat host, was identified as the least structured population and should therefore be considered the most vagile host. Genetic distance matrices were compared for all three species based on a mitochondrial DNA fragment. Both host and vector populations followed an isolation-by-distance pattern across the Mediterranean, but not the parasite. Mantel tests found no correlation between the parasite and either the host or vector populations. We therefore found no support for our hypothesis; the parasite population structure matched neither vector nor host. Instead, we propose a model where the parasite's gene flow is represented by the added effects of host and vector dispersal patterns.

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The self-assembly into wormlike micelles of a poly(ethylene oxide)-b-poly(propylene oxide)-b-poly(ethylene oxide) triblock copolymer Pluronic P84 in aqueous salt solution (2 M NaCl) has been studied by rheology, small-angle X-ray and neutron scattering (SAXS/SANS), and light scattering. Measurements of the flow curves by controlled stress rheometry indicated phase separation under flow. SAXS on solutions subjected to capillary flow showed alignment of micelles at intermediate shear rates, although loss of alignment was observed for high shear rates. For dilute solutions, SAXS and static light scattering data on unaligned samples could be superposed over three decades in scattering vector, providing unique information on the wormlike micelle structure over several length scales. SANS data provided information on even shorter length scales, in particular, concerning "blob" scattering from the micelle corona. The data could be modeled based on a system of semiflexible self-avoiding cylinders with a circular cross-section, as described by the wormlike chain model with excluded volume interactions. The micelle structure was compared at two temperatures close to the cloud point (47 degrees C). The micellar radius was found not to vary with temperature in this region, although the contour length increased with increasing temperature, whereas the Kuhn length decreased. These variations result in an increase of the low-concentration radius of gyration with increasing temperature. This was consistent with dynamic light scattering results, and, applying theoretical results from the literature, this is in agreement with an increase in endcap energy due to changes in hydration of the poly(ethylene oxide) blocks as the temperature is increased.

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This paper presents novel observer-based techniques for the estimation of flow demands in gas networks, from sparse pressure telemetry. A completely observable model is explored, constructed by incorporating difference equations that assume the flow demands are steady. Since the flow demands usually vary slowly with time, this is a reasonable approximation. Two techniques for constructing robust observers are employed: robust eigenstructure assignment and singular value assignment. These techniques help to reduce the effects of the system approximation. Modelling error may be further reduced by making use of known profiles for the flow demands. The theory is extended to deal successfully with the problem of measurement bias. The pressure measurements available are subject to constant biases which degrade the flow demand estimates, and such biases need to be estimated. This is achieved by constructing a further model variation that incorporates the biases into an augmented state vector, but now includes information about the flow demand profiles in a new form.

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We present a first overview of flows in the high latitude ionosphere observed at 15 s resolution using the U.K.-Polar EISCAT experiment. Data are described from experiments conducted on two days, 27 October 1984 and 29 August 1985, which together span the local times between about 0200 and 2130MLT and cover five different regions of ionospheric flow. With increasing local time, these are: the dawn auroral zone flow cell, the dayside region of low background flows equatorward of the flow cells, the dusk auroral zone flow cell, the boundary region between the dusk auroral zone and the polar cap, and the evening polar cap. Flows in both the equatorward and poleward portions of the auroral zone cells appear to be relatively smooth, while in the central region of high speed flow considerable variations are generally present. These have the form of irregular fluctuations on a wide range of time scales in the early morning dawn cell, and impulsive wave-like variations with periods of a few minutes in the afternoon dusk cell. In the dayside region between the flow cells, the ionosphere is often essentially stagnant for long intervals, but low amplitude ULF waves with a period of about 5 min can also occur and persist for many cycles. These conditions are punctuated at one to two hour intervals by sudden ‘flow burst’ events with impulsively generated damped wave trains. Initial burst flows are generally directed poleward and can peak at line-of-sight speeds in excess of 1 km s^{−1} after perhaps 45 s. Flows in the polar cap are reasonably smooth on time scales of a few minutes and show no evidence for the presence of ULF waves. Under most, but not all, of the above conditions, the beam-swinging algorithm used to determine background vector flows should produce meaningful results. Comparison of these flow data with simultaneous plasma and magnetic field measurements in the solar wind, made by the AMPTE IRM and UKS spacecraft, emphasizes the strong control exerted on high latitude flows by the north-south component of the IMF.

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Extensive population structuring is known to occur in Anopheles darlingi, the primary malaria vector of the Neotropics. We analysed the phylogeographic structure of the species using the mitochondrial cytochrome oxidase I marker. Diversity is divided into six main population groups in South America: Colombia, central Amazonia, southern Brazil, south-eastern Brazil, and two groups in north-east Brazil. The ancestral distribution of the taxon is hypothesized to be central Amazonia, and there is evidence of expansion from this region during the late Pleistocene. The expansion was not a homogeneous front, however, with at least four subgroups being formed due to geographic barriers. As the species spread, populations became isolated from each other by the Amazon River and the coastal mountain ranges of south-eastern Brazil and the Andes. Analyses incorporating distances around these barriers suggest that the entire South American range of An. darlingi is at mutation-dispersal-drift equilibrium. Because the species is distributed throughout such a broad area, the limited dispersal across some landscape types promotes differentiation between otherwise proximate populations. Moreover, samples from the An. darlingi holotype location in Rio de Janeiro State are substantially derived from all other populations, implying that there may be additional genetic differences of epidemiological relevance. The results obtained contribute to our understanding of gene flow in this species and allow the formulation of human mosquito health protocols in light of the potential population differences in vector capacity or tolerance to control strategies. (C) 2009 The Linnean Society of London, Biological Journal of the Linnean Society, 2009, 97, 854-866.

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We introduce a flexible technique for interactive exploration of vector field data through classification derived from user-specified feature templates. Our method is founded on the observation that, while similar features within the vector field may be spatially disparate, they share similar neighborhood characteristics. Users generate feature-based visualizations by interactively highlighting well-accepted and domain specific representative feature points. Feature exploration begins with the computation of attributes that describe the neighborhood of each sample within the input vector field. Compilation of these attributes forms a representation of the vector field samples in the attribute space. We project the attribute points onto the canonical 2D plane to enable interactive exploration of the vector field using a painting interface. The projection encodes the similarities between vector field points within the distances computed between their associated attribute points. The proposed method is performed at interactive rates for enhanced user experience and is completely flexible as showcased by the simultaneous identification of diverse feature types.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Anopheles darlingi is the most important Brazilian malaria vector, with a widespread distribution in the Amazon forest. Effective strategies for vector control could be better developed through knowledge of its genetic structure and gene flow among populations, to assess the vector diversity and competence in transmitting Plasmodium. The aim of this study was to assess the genetic diversity of An. darlingi collected at four locations in Porto Velho, by sequencing a fragment of the ND4 mitochondrial gene. From 218 individual mosquitoes, we obtained 20 different haplotypes with a diversity index of 0.756, equivalent to that found in other neotropical anophelines. The analysis did not demonstrate significant population structure. However, haplotype diversity within some populations seems to be over-represented, suggesting the presence of sub-populations, but the presence of highly represented haplotypes complicates this analysis. There was no clear correlation among genetic and geographical distance and there were differences in relation to seasonality, which is important for malarial epidemiology.