34 resultados para New Space Vector Modulation

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Several extensions of the standard model predict the existence of new neutral spin-1 resonances associated with the electroweak symmetry breaking sector. Using the data from ATLAS (with integrated luminosity of L = 1.02 fb(-1)) and CMS (with integrated luminosity of L = 1.55 fb(-1)) on the production of W+W- pairs through the process pp --> l(+)l(-)' is not an element of(T), we place model independent bounds on these new vector resonances masses, couplings, and widths. Our analyses show that the present data exclude new neutral vector resonances with masses up to 1-2.3 TeV depending on their couplings and widths. We also demonstrate how to extend our analysis framework to different models with a specific example.

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In this work, a new enrichment space to accommodate jumps in the pressure field at immersed interfaces in finite element formulations, is proposed. The new enrichment adds two degrees of freedom per element that can be eliminated by means of static condensation. The new space is tested and compared with the classical P1 space and to the space proposed by Ausas et al (Comp. Meth. Appl. Mech. Eng., Vol. 199, 10191031, 2010) in several problems involving jumps in the viscosity and/or the presence of singular forces at interfaces not conforming with the element edges. The combination of this enrichment space with another enrichment that accommodates discontinuities in the pressure gradient has also been explored, exhibiting excellent results in problems involving jumps in the density or the volume forces. Copyright (c) 2011 John Wiley & Sons, Ltd.

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We consider a recently proposed finite-element space that consists of piecewise affine functions with discontinuities across a smooth given interface Γ (a curve in two dimensions, a surface in three dimensions). Contrary to existing extended finite element methodologies, the space is a variant of the standard conforming Formula space that can be implemented element by element. Further, it neither introduces new unknowns nor deteriorates the sparsity structure. It is proved that, for u arbitrary in Formula, the interpolant Formula defined by this new space satisfies Graphic where h is the mesh size, Formula is the domain, Formula, Formula, Formula and standard notation has been adopted for the function spaces. This result proves the good approximation properties of the finite-element space as compared to any space consisting of functions that are continuous across Γ, which would yield an error in the Formula-norm of order Graphic. These properties make this space especially attractive for approximating the pressure in problems with surface tension or other immersed interfaces that lead to discontinuities in the pressure field. Furthermore, the result still holds for interfaces that end within the domain, as happens for example in cracked domains.

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Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

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Oriocrassatella Etheridge Jr., 1907 is a long range crassatellid bivalve genus well recognized in shallow waters of epeiric seas throughout the upper part of Paleozoic. The first occurrences of this genus are recorded in the sedimentary successions of the Gondwana, both in Australia and South America. However, the geographic and age distribution of Oriocrassatella in Late Mississippian deposits of Australia and Argentina may indicate an earliest Visean or even a pre-Visean origin for the genus. Following its origin in Early Carboniferous a complex paleobiogeographic history from Southern to Northern Hemisphere took place in the Permian. During its initial dispersal phase from Late Carboniferous to the Early Permian the genus thrived in cold water environments associated to the Late Paleozoic Gondwana glaciation. Shallow-water bottoms of the warm waters of the central Gondwana fringe and Laurussia were colonized by Oriocrassatella only during Early Permian times when the genus became cosmopolitan. A new species of this genus is described herein, Oriocrassatella piauiensis n. sp., recorded from the Piaui Formation, Pennsylvanian of the Parnaiba Basin. This new species may represent an early adaptation to warm waters. However, based on available data, species of this genus seem to have adapted definitely to warm water environments probably related the Late Pennsylvanian interglacial phases. In these phases, climatic barrier were interrupted allowing the faunal interchange and larval dispersion following a South to North migration route through the eastern margins of Gondwana and the eastern Paleotethys.

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Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that, on average, the proposed hybrid methods obtained lower error rates when compared to their components applied in isolation.

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Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.

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PURPOSE: To determine whether the improvement in intermediate vision after bilateral implantation of an aspheric multifocal intraocular lens (IOL) with a +3.00 diopter (D) addition (add) occurs at the expense of optical quality compared with the previous model with a +4.00 D add. SETTING: Department of Ophthalmology, University of Sao Paulo, Sao Paulo, Brazil. DESIGN: Prospective randomized double-masked comparative clinical trial. METHODS: One year after bilateral implantation of Acrysof Restor SN6AD1 +3.00 D IOLs or Acrysof Restor SN6AD3 +4.00 D IOLs, optical quality was evaluated by analyzing the in vivo modulation transfer function (MTF) and point-spread function (expressed as Strehl ratio). The Strehl ratio and MTF curve with a 4.0 pupil and a 6.0 mm pupil were measured by dynamic retinoscopy aberrometry. The uncorrected and corrected distance visual acuities at 4 m, uncorrected and distance-corrected near visual acuities at 40 cm, and uncorrected and distance-corrected intermediate visual acuities at 50 cm, 60 cm, and 70 cm were measured. RESULTS: Both IOL groups comprised 40 eyes of 20 patients. One year postoperatively, there were no statistically significant between-group differences in the MTF or Strehl ratio with either pupil size. There were no statistically significant between-group differences in distance or near visual acuity. Intermediate visual acuity was significantly better in the +3.00 D IOL group. CONCLUSION: Results indicate that the improvement in intermediate vision in eyes with the aspheric multifocal +3.00 D add IOL occurred without decreasing optical quality over that with the previous version IOL with a +4.00 D add.

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There is a molecular crosstalk between the trophoblast and maternal immune cells of bovine endometrium. The uterine cells are able to secrete cytokine/chemokines to either induce a suppressive environment for establishment of the pregnancy or to recruit immune cells to the endometrium to fight infections. Despite morphological differences between women and cows, mechanisms for immune tolerance during pregnancy seem to be conserved. Mechanisms for uterine immunesuppression in the cow include: reduced expression of major histocompatability proteins by the trophoblast; recruitment of macrophages to the pregnant endometrium; and modulation of immune-related genes in response to the presence of the conceptus. Recently, an eGFP transgenic cloned embryo model developed by our group showed that there is modulation of foetal proteins expressed at the site of syncytium formation, suggesting that foetal cell can regulate not only by the secretion of specific factors such as interferon-tau, but also by regulating their own protein expression to avoid excessive maternal recognition by the local immune system. Furthermore, foetal DNA can be detected in the maternal circulation; this may reflect the occurrence of an invasion of trophoblast cells and/or their fragment beyond the uterine basement membrane in the cow. In fact, the newly description of exosome release by the trophoblast cell suggests that could be a new fashion of maternal-foetal communication at the placental barrier. Additionally, recent global transcriptome studies on bovine endometrium suggested that the immune system is aware, from an immunological point of view, of the presence of the foetus in the cow during early pregnancy.

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Bol algebras appear as the tangent algebra of Bol loops. A (left) Bol algebra is a vector space equipped with a binary operation [a, b] and a ternary operation {a, b, c} that satisfy five defining identities. If A is a left or right alternative algebra then A(b) is a Bol algebra, where [a, b] := ab - ba is the commutator and {a, b, c} := < b, c, a > is the Jordan associator. A special identity is an identity satisfied by Ab for all right alternative algebras A, but not satisfied by the free Bol algebra. We show that there are no special identities of degree <= 7, but there are special identities of degree 8. We obtain all the special identities of degree 8 in partition six-two. (C) 2011 Elsevier Inc. All rights reserved.

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Chemosensitive neurons in the retrotrapezoid nucleus (RTN) regulate breathing in response to CO2/H+ changes. Their activity is also sensitive to neuromodulatory inputs from multiple respiratory centers, and thus they serve as a key nexus of respiratory control. However, molecular mechanisms that control their activity and susceptibility to neuromodulation are unknown. Here, we show in vitro and in vivo that KCNQ channels are critical determinants of RTN neural activity. In particular, we find that pharmacological block of KCNQ channels (XE991, 10 mu M) increased basal activity and CO2 responsiveness of RTN neurons in rat brain slices, whereas KCNQ channel activation (retigabine, 2-40 mu M) silenced these neurons. Interestingly, we also find that KCNQ and apamin-sensitive SK channels act synergistically to regulate firing rate of RTN chemoreceptors; simultaneous blockade of both channels led to a increase in CO2 responsiveness. Furthermore, we also show that KCNQ channels but not SK channels are downstream effectors of serotonin modulation of RTN activity in vitro. In contrast, inhibition of KCNQ channel did not prevent modulation of RTN activity by Substance P or thyrotropin-releasing hormone, previously identified neuromodulators of RTN chemoreception. Importantly, we also show that KCNQ channels are critical for RTN activity in vivo. Inhibition of KCNQ channels lowered the CO2 threshold for phrenic nerve discharge in anesthetized rats and decreased the ventilatory response to serotonin in awake and anesthetized animals. Given that serotonergic dysfunction may contribute to respiratory failure, our findings suggest KCNQ channels as a new therapeutic avenue for respiratory complications associated with multiple neurological disorders.

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We consider a class of involutive systems of n smooth vector fields on the n + 1 dimensional torus. We obtain a complete characterization for the global solvability of this class in terms of Liouville forms and of the connectedness of all sublevel and superlevel sets of the primitive of a certain 1-form in the minimal covering space.

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The silverleaf whitefly (Bemisia tabaci) is actually a complex of morphologically indistinct species that vary in their capacity to transmit plant viruses and to induce physiological disorders in plants of economic importance. The worldwide impact of this whitefly has increased greatly, as it is a vector of various types of phytovirus, especially geminiviruses, in plants of economic importance. The adaptability of B. tabaci to many regions of the world has fostered the appearance of various biotypes that attack a broad spectrum of host plants. We developed microsatellite markers to study genetic variability and population structure of this whitefly in Brazil. Thirteen polymorphic microsatellite markers were isolated and characterized in 20 individuals from a natural population that were collected in soybean in Campinas (SP). The number of alleles per locus ranged from one to two, and the expected heterozygosity ranged from 0.000 to 0.505. These microsatellite markers will be useful for studies and management of B. tabaci. The low polymorphism found in these molecular markers is probably associated with homology of genes expressed in these markers.

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We present a new method to quantify substructures in clusters of galaxies, based on the analysis of the intensity of structures. This analysis is done in a residual image that is the result of the subtraction of a surface brightness model, obtained by fitting a two-dimensional analytical model (beta-model or Sersic profile) with elliptical symmetry, from the X-ray image. Our method is applied to 34 clusters observed by the Chandra Space Telescope that are in the redshift range z is an element of [0.02, 0.2] and have a signal-to-noise ratio (S/N) greater than 100. We present the calibration of the method and the relations between the substructure level with physical quantities, such as the mass, X-ray luminosity, temperature, and cluster redshift. We use our method to separate the clusters in two sub-samples of high-and low-substructure levels. We conclude, using Monte Carlo simulations, that the method recuperates very well the true amount of substructure for small angular core radii clusters (with respect to the whole image size) and good S/N observations. We find no evidence of correlation between the substructure level and physical properties of the clusters such as gas temperature, X-ray luminosity, and redshift; however, analysis suggest a trend between the substructure level and cluster mass. The scaling relations for the two sub-samples (high-and low-substructure level clusters) are different (they present an offset, i. e., given a fixed mass or temperature, low-substructure clusters tend to be more X-ray luminous), which is an important result for cosmological tests using the mass-luminosity relation to obtain the cluster mass function, since they rely on the assumption that clusters do not present different scaling relations according to their dynamical state.

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Ischemia/reperfusion injury (IRI) is a leading cause of acute renal failure. The definition of the molecular mechanisms involved in renal IRI and counter protection promoted by ischemic pre-conditioning (IPC) or Hemin treatment is an important milestone that needs to be accomplished in this research area. We examined, through an oligonucleotide microarray protocol, the renal differential transcriptome profiles of mice submitted to IRI, IPC and Hemin treatment. After identifying the profiles of differentially expressed genes observed for each comparison, we carried out functional enrichment analysis to reveal transcripts putatively involved in potential relevant biological processes and signaling pathways. The most relevant processes found in these comparisons were stress, apoptosis, cell differentiation, angiogenesis, focal adhesion, ECM-receptor interaction, ion transport, angiogenesis, mitosis and cell cycle, inflammatory response, olfactory transduction and regulation of actin cytoskeleton. In addition, the most important overrepresented pathways were MAPK, ErbB, JAK/STAT, Toll and Nod like receptors, Angiotensin II, Arachidonic acid metabolism, Wnt and coagulation cascade. Also, new insights were gained about the underlying protection mechanisms against renal IRI promoted by IPC and Hemin treatment. Venn diagram analysis allowed us to uncover common and exclusively differentially expressed genes between these two protective maneuvers, underscoring potential common and exclusive biological functions regulated in each case. In summary, IPC exclusively regulated the expression of genes belonging to stress, protein modification and apoptosis, highlighting the role of IPC in controlling exacerbated stress response. Treatment with the Hmox1 inducer Hemin, in turn, exclusively regulated the expression of genes associated with cell differentiation, metabolic pathways, cell cycle, mitosis, development, regulation of actin cytoskeleton and arachidonic acid metabolism, suggesting a pleiotropic effect for Hemin. These findings improve the biological understanding of how the kidney behaves after IRI. They also illustrate some possible underlying molecular mechanisms involved in kidney protection observed with IPC or Hemin treatment maneuvers.