920 resultados para Fourier coefficients vector


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Triatoma sordida is a species that transmits Trypanosoma cruzi to humans. In Brazil, T. sordida currently deserves special attention because of its wide distribution, tendency to invade domestic environments and vectorial competence. For the planning and execution of control protocols to be effective against Triatominae, they must consider its population structure. In this context, this study aimed to characterise the genetic variability of T. sordida populations collected in areas with persistent infestations from Minas Gerais, Brazil. Levels of genetic variation and population structure were determined in peridomestic T. sordida by sequencing a polymorphic region of the mitochondrial cytochrome b gene. Low nucleotide and haplotype diversity were observed for all 14 sampled areas; π values ranged from 0.002-0.006. Most obtained haplotypes occurred at low frequencies, and some were exclusive to only one of the studied populations. Interpopulation genetic diversity analysis revealed strong genetic structuring. Furthermore, the genetic variability of Brazilian populations is small compared to that of Argentinean and Bolivian specimens. The possible factors related to the reduced genetic variability and strong genetic structuring obtained for studied populations are discussed in this paper.

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A new quantitative approach of the mandibular sexual dimorphism, based on computer-aided image analysis and elliptical Fourier analysis of the mandibular outline in lateral view is presented. This method was applied to a series of 117 dentulous mandibles from 69 male and 48 female individuals native of Rhenish countries. Statistical discriminant analysis of the elliptical Fourier harmonics allowed the demonstration of a significant sexual dimorphism in 97.1% of males and 91.7% of females, i.e. in a higher proportion than in previous studies using classical metrical approaches. This original method opens interesting perspectives for increasing the accuracy of sex identification in current anthropological practice and in forensic procedures.

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Background: Adenovirus serotype 5 (Ad5) phase IIb vaccine trial (STEP) was prematurely stopped due to a lack of efficacy and two-fold higher incidence of HIV infection among Ad5 seropositive vaccine recipients. We have recently demonstrated that Ad5 immune complexes (Ad5 ICs)-mediated activation of the dendritic cell (DC)-T cell axis was associated with the enhancement of HIV infection in vitro. Although the direct role of Ad5 neutralizing antibodies (NAbs) in the increase of HIV susceptibility during the STEP trial is still under debate, vector-specific NAbs remain a major hurdle for vector-based gene therapies or vaccine strategies. To surmount this obstacle, vectors based on ''rare'' Ad serotypes including Ad6, Ad26, Ad36 and Ad41 were engineered.Methods: The present study aimed to determine whether Ad ICmediated DC maturation could be circumvented using these Advector candidates.Results: We found that all Ad vectors tested forming ICs with plasma containing serotype-specific NAbs had the capacity to 1) mature human DCs as monitored by the up-regulation of costimulatory molecules and the release of pro-inflammatory cytokines (TNF-a), via the stabilization of Ad capsid at endosomal but not lysosomal pH rendering Ad DNA/TLR9 interactions possible and 2) potentiate Ad-specific CD4 and CD8 T cell responses.Conclusion: In conclusion, despite a conserved DC maturation potential, the low prevalence of serotype-specific NAbs renders rare Ad vectors attractive for vaccine strategies.

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We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.

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The joint angles of multi-segment foot models have been primarily described using two mathematical methods: the joint coordinate system and the attitude vector. This study aimed to determine whether the angles obtained through these two descriptors are comparable, and whether these descriptors have similar sensitivity to experimental errors. Six subjects walked eight times on an instrumented walkway while the joint angles among shank, hindfoot, medial forefoot, and lateral forefoot were measured. The angles obtained using both descriptors and their sensitivity to experimental errors were compared. There was no overall significant difference between the ranges of motion obtained using both descriptors. However, median differences of more than 6° were noticed for the medial-lateral forefoot joint. For all joints and rotation planes, both descriptors provided highly similar angle patterns (median correlation coefficient: R>0.90), except for the medial-lateral forefoot angle in the transverse plane (median R=0.77). The joint coordinate system was significantly more sensitive to anatomical landmarks misplacement errors. However, the absolute differences of sensitivity were small relative to the joints ranges of motion. In conclusion, the angles obtained using these two descriptors were not identical, but were similar for at least the shank-hindfoot and hindfoot-medial forefoot joints. Therefore, the angle comparison across descriptors is possible for these two joints. Comparison should be done more carefully for the medial-lateral forefoot joint. Moreover, despite different sensitivities to experimental errors, the effects of the experimental errors on the angles were small for both descriptors suggesting that both descriptors can be considered for multi-segment foot models.

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Standard practice in Bayesian VARs is to formulate priors on the autoregressive parameters, but economists and policy makers actually have priors about the behavior of observable variables. We show how this kind of prior can be used in a VAR under strict probability theory principles. We state the inverse problem to be solved and we propose a numerical algorithm that works well in practical situations with a very large number of parameters. We prove various convergence theorems for the algorithm. As an application, we first show that the results in Christiano et al. (1999) are very sensitive to the introduction of various priors that are widely used. These priors turn out to be associated with undesirable priors on observables. But an empirical prior on observables helps clarify the relevance of these estimates: we find much higher persistence of output responses to monetary policy shocks than the one reported in Christiano et al. (1999) and a significantly larger total effect.

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Estudi realitzat a partir d’una estada al Institut de Génétique Moléculaire de Montpellier, França, entre 2010 i 2012. En aquest projecte s’ha avaluat les avantatges dels vectors adenovirals canins tipus 2 (CAV2) com a vectors de transferència gènica al sistema nerviós central (SNC) en un model primat no-humà i en un model caní del síndrome de Sly (mucopolisacaridosis tipus 7, MPS VII), malaltia monogènica que cursa amb neurodegeneració. En una primera part del projecte s’ha avaluat la biodistribució, l’eficàcia i la durada de l’expressió del transgen en un model primat no humà, (Microcebus murinus). Com ha vector s’ha utilitzat un CAV2 de primera generació que expressa la proteïna verda fluorescent (CAVGFP). Els resultats aportats en aquesta memòria demostren que en primats no humans, com en d’altres espècies testades anteriorment per l’equip de l’EJ Kremer, la injecció intracerebral de CAV2 resulta en una extensa transducció del SNC, siguent les neurones i els precursors neuronals les cèl•lules preferencialment transduïdes. Els vectors canins, servint-se de vesícules intracel•lulars són transportats, majoritàriament, des de les sinapsis cap al soma neuronal, aquest transport intracel•lular permet una extensa transducció del SNC a partir d’una única injecció intracerebral dels vectors virals. En una segona part d’aquest projecte s’ha avaluat l’ús terapèutic dels CAV2. S’ha injectat un vector helper-dependent que expressa el gen la b-glucuronidasa i el gen de la proteïna verda fluorescent (HD-RIGIE), en el SNC del model caní del síndrome de Sly (MPS VII). La biodistribució i la eficàcia terapèutica han estat avaluades. Els nivells d’activitat enzimàtica en animals malalts injectats amb el vector terapèutic va arribar a valors similars als dels animals no afectes. A més a més s’ha observat una reducció en la quantitat dels GAGs acumulats en les cèl•lules dels animals malalts tractats amb el vector terapèutic, demostrant la potencialitat terapèutica dels CAV2 per a malalties que afecten al SNC. Els resultats aportats en aquest treball ens permeten dir que els CAV2 són unes bones eines terapèutiques per al tractament de malalties que afecten al SNC.

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Induced pluripotent stem (iPS) cells have generated keen interestdue to their potential use in regenerative medicine. They havebeen obtained from various cell types of both mice and humans byexogenous delivery of different combinations of Oct4, Sox2, Klf4,c-Myc, Nanog, and Lin28. The delivery of these transcription factorshas mostly entailed the use of integrating viral vectors (retrovirusesor lentiviruses), carrying the risk of both insertional mutagenesisand oncogenesis due to misexpression of these exogenousfactors. Therefore, obtaining iPS cells that do not carry integratedtransgene sequences is an important prerequisite for their eventualtherapeutic use. Here we report the generation of iPS cell linesfrom mouse embryonic fibroblasts with no evidence of integrationof the reprogramming vector in their genome, achieved by nucleofectionof a polycistronic construct coexpressing Oct4, Sox2, Klf4,and c-Myc

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Building a personalized model to describe the drug concentration inside the human body for each patient is highly important to the clinical practice and demanding to the modeling tools. Instead of using traditional explicit methods, in this paper we propose a machine learning approach to describe the relation between the drug concentration and patients' features. Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. We focus mainly on the prediction of the drug concentrations as well as the analysis of different features' influence. Models are built based on Support Vector Machine and the prediction results are compared with the traditional analytical models.

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In this article we present a hybrid approach for automatic summarization of Spanish medical texts. There are a lot of systems for automatic summarization using statistics or linguistics, but only a few of them combining both techniques. Our idea is that to reach a good summary we need to use linguistic aspects of texts, but as well we should benefit of the advantages of statistical techniques. We have integrated the Cortex (Vector Space Model) and Enertex (statistical physics) systems coupled with the Yate term extractor, and the Disicosum system (linguistics). We have compared these systems and afterwards we have integrated them in a hybrid approach. Finally, we have applied this hybrid system over a corpora of medical articles and we have evaluated their performances obtaining good results.

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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 for the simultaneous analysis of cell-wall polysaccharides, amides and aliphatic polyesters by transmission Fourier transform infrared microspectroscopy (FTIR) has been established for Arabidopsis petals. The combination of FTIR imaging with spectra derivatization revealed that petals, in contrast to other organs, have a characteristic chemical zoning with high amount of aliphatic compounds and esters in the lamina and of polysaccharides in the stalk of the petal. The hinge region of petals was particular rich in amides as well as in vibrations potentially associated with hemicellulose. In addition, a number of other distribution patterns have been identified. Analyses of mutants in cutin deposition confirmed that vibrations of aliphatic compounds and esters present in the lamina were largely associated with the cuticular polyester. Calculation of spectrotypes, including the standard deviation of intensities, allowed detailed comparison of the spectral features of various mutants. The spectrotypes not only revealed differences in the amount of polyesters in cutin mutants, but also changes in other compound classes. For example, in addition to the expected strong deficiencies in polyester content, the long-chain acyl CoA synthase 2 mutant showed increased intensities of vibrations in a wavelength range that is typical for polysaccharides. Identical spectral features were observed in quasimodo2, a cell-wall mutant of Arabidopsis with a defect in pectin formation that exhibits increased cellulose synthase activity. FTIR thus proved to be a convenient method for the identification and characterization of mutants affected in the deposition of cutin in petals.