997 resultados para Wave Prediction
Resumo:
The spectrum of short-closed chains up to N=12 are studied by exact diagonalization to obtain the spin-wave spectrum of the Hamiltonian H=2J Sigma i=1Nsi.si+1+2J alpha Sigma i=1Nsi.si+2, -1.0
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Further improvement in performance, to achieve near transparent quality LSF quantization, is shown to be possible by using a higher order two dimensional (2-D) prediction in the coefficient domain. The prediction is performed in a closed-loop manner so that the LSF reconstruction error is the same as the quantization error of the prediction residual. We show that an optimum 2-D predictor, exploiting both inter-frame and intra-frame correlations, performs better than existing predictive methods. Computationally efficient split vector quantization technique is used to implement the proposed 2-D prediction based method. We show further improvement in performance by using weighted Euclidean distance.
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The skin cancer incidence has increased substantially over the past decades and the role of ultraviolet (UV) radiation in the etiology of skin cancer is well established. Ultraviolet B radiation (280-320 nm) is commonly considered as the more harmful part of the UV-spectrum due to its DNA-damaging potential and well-known carcinogenic effects. Ultraviolet A radiation (320-400 nm) is still regarded as a relatively low health hazard. However, UVA radiation is the predominant component in sunlight, constituting more than 90% of the environmentally relevant solar ultraviolet radiation. In the light of the recent scientific evidence, UVA has been shown to have genotoxic and immunologic effects, and it has been proposed that UVA plays a significant role in the development of skin cancer. Due to the popularity of skin tanning lamps, which emit high intensity UVA radiation and because of the prolonged sun tanning periods with the help of effective UVB blockers, the potential deleterious effects of UVA has emerged as a source of concern for public health. The possibility that UV radiation may affect melanoma metastasis has not been addressed before. UVA radiation can modulate various cellular processes, some of which might affect the metastatic potential of melanoma cells. The aim of the present study was to investigate the possible role of UVA irradiation on the metastatic capacity of mouse melanoma both in vitro and in vivo. The in vitro part of the study dealt with the enhancement of the intercellular interactions occurring either between tumor cells or between tumor cells and endothelial cells after UVA irradiation. The use of the mouse melanoma/endothelium in vitro model showed that a single-dose of UVA to melanoma cells causes an increase in melanoma cell adhesiveness to non-irradiated endothelium after 24-h irradiation. Multiple-dose irradiation of melanoma cells already increased adhesion at a 1-h time-point, which suggests the possible cumulative effect of multiple doses of UVA irradiation. This enhancement of adhesiveness might lead to an increase in binding tumor cells to the endothelial lining of vasculature in various internal organs if occurring also in vivo. A further novel observation is that UVA induced both decline in the expression of E-cadherin adhesion molecule and increase in the expression of the N-cadherin adhesion molecule. In addition, a significant decline in homotypic melanoma-melanoma adhesion (clustering) was observed, which might result in the reduction of E-cadherin expression. The aim of the in vivo animal study was to confirm the physiological significance of previously obtained in vitro results and to determine whether UVA radiation might increase melanoma metastasis in vivo. The use of C57BL/6 mice and syngeneic melanoma cell lines B16-F1 and B16-F10 showed that mice, which were i.v. injected with B16-F1 melanoma cells and thereafter exposed to UVA developed significantly more lung metastases when compared with the non-UVA-exposed group. To study the mechanism behind this phenomenon, the direct effect of UVA-induced lung colonization capacity was examined by the in vitro exposure of B16-F1 cells. Alternatively, the UVA-induced immunosuppression, which might be involved in increased melanoma metastasis, was measured by standard contact hypersensitivity assay (CHS). It appears that the UVA-induced increase of metastasis in vivo might be caused by a combination of UVA-induced systemic immunosuppression, and to the lesser extent, it might be caused by the increased adhesiveness of UVA irradiated melanoma cells. Finally, the UVA effect on gene expression in mouse melanoma was determined by a cDNA array, which revealed UVA-induced changes in the 9 differentially expressed genes that are involved in angiogenesis, cell cycle, stress-response, and cell motility. These results suggest that observed genes might be involved in cellular response to UVA and a physiologically relevant UVA dose have previously unknown cellular implications. The novel results presented in this thesis offer evidence that UVA exposure might increase the metastatic potential of the melanoma cells present in blood circulation. Considering the wellknown UVA-induced deleterious effects on cellular level, this study further supports the notion that UVA radiation might have more potential impact on health than previously suggested. The possibility of the pro-metastatic effects of UVA exposure might not be of very high significance for daily exposures. However, UVA effects might gain physiological significance following extensive sunbathing or solaria tanning periods. Whether similar UVA-induced pro-metastatic effects occur in people sunbathing or using solaria remains to be determined. In the light of the results presented in this thesis, the avoidance of solaria use could be well justified.
Resumo:
The special class of quasi-simple wave solutions is studied for the system of partial differential equations governing inviscid acoustic gravity waves. It is shown that these traveling wave solutions do not admit shocks. Periodic solutions are found to exist when there is no propagation in the vertical direction. The solutions for some particular cases are depicted graphically. Physics of Fluids is copyrighted by The American Institute of Physics.
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A theoretical study on the propagation of plane waves in the presence of a hot mean flow in a uniform pipe is presented. The temperature variation in the pipe is taken to be a linear temperature gradient along the axis. The theoretical studies include the formulation of a wave equation based on continuity, momentum, and state equation, and derivation of a general four-pole matrix, which is shown to yield the well-known transfer matrices for several other simpler cases.
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The problem of excitation of 11zultilayercd-graded-dielectric-coatedc onductor by a magnetic ring source is fornzulated in the ,form of a contour integrul which is rolved by using the method of steepest descent. Numerical evaluation of launching efiiency shows that high value of about 90 percent can be attained by choosing proper dimensions of the launcher with respect to the dimension of the surface wave line.
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The past several years have seen significant advances in the development of computational methods for the prediction of the structure and interactions of coiled-coil peptides. These methods are generally based on pairwise correlations of amino acids, helical propensity, thermal melts and the energetics of sidechain interactions, as well as statistical patterns based on Hidden Markov Model (HMM) and Support Vector Machine (SVM) techniques. These methods are complemented by a number of public databases that contain sequences, motifs, domains and other details of coiled-coil structures identified by various algorithms. Some of these computational methods have been developed to make predictions of coiled-coil structure on the basis of sequence information; however, structural predictions of the oligomerisation state of these peptides still remains largely an open question due to the dynamic behaviour of these molecules. This review focuses on existing in silico methods for the prediction of coiled-coil peptides of functional importance using sequence and/or three-dimensional structural data.
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Heparin is a glycosaminoglycan known to bind bone morphogenetic proteins (BMPs) and the growth and differentiation factors (GDFs) and has strong and variable effects on BMP osteogenic activity. In this paper we report our predictions of the likely heparin binding sites for BMP-2 and 14. The N-terminal sequences upstream of TGF-β-type cysteine-knot domains in BMP-2, 7 and 14 contain the basic residues arginine and lysine, which are key components of the heparin/HS-binding sites, with these residues being highly non-conserved. Importantly, evolutionary conserved surfaces on the beta sheets are required for interactions with receptors and antagonists. Furthermore, BMP-2 has electropositive surfaces on two sides compared to BMP-7 and BMP-14. Molecular docking simulations suggest the presence of high and low affinity binding sites in dimeric BMP-2. Histidines were found to play a role in the interactions of BMP-2 with heparin; however, a pKa analysis suggests that histidines are likely not protonated. This is indicative that interactions of BMP-2 with heparin do not require acidic pH. Taken together, non-conserved amino acid residues in the N-terminus and residues protruding from the beta sheet (not overlapping with the receptor binding sites and the dimeric interface) and not C-terminal are found to be important for heparin–BMP interactions.
Resumo:
Speed control of ac motors requires variable frequency, variable current, or variable voltage supply. Variable frequency supply can be obtained directly from a fixed frequency supply by using a frequency converter or from a dc source using inverters. In this paper a control technique for reference wave adaptive-current generation by modulating the inverter voltage is explained. Extension of this technique for three-phase induction-motor speed control is briefly explained. The oscillograms of the current waveforms obtained from the experimental setup are also shown.
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In this paper, we consider a more realistic model of a spherical blast wave of moderate strength. An arbitrary number of terms for the series solution in each of the regions behind the main shock - the expansion region, the nearly uniform region outside the main expansion and the region between the contact surface and the main shock, have been generated and matched across the boundaries. We then study the convergence of the solution by using Pade approximation. It constitutes a genuine analytic solution for a moderately strong explosion, which, however, does not involve a secondary shock. The pressure distribution behind the shock however shows some significant changes in the location of the tail of the rarefaction and the interface, in comparison to the planar problem. The theory developed for the spherical blasts is also extended to cylindrical blasts. The results are compared with the numerical solution.
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A lack of information on protein-protein interactions at the host-pathogen interface is impeding the understanding of the pathogenesis process. A recently developed, homology search-based method to predict protein-protein interactions is applied to the gastric pathogen, Helicobacter pylori to predict the interactions between proteins of H. pylori and human proteins in vitro. Many of the predicted interactions could potentially occur between the pathogen and its human host during pathogenesis as we focused mainly on the H. pylori proteins that have a transmembrane region or are encoded in the pathogenic island and those which are known to be secreted into the human host. By applying the homology search approach to protein-protein interaction databases DIP and iPfam, we could predict in vitro interactions for a total of 623 H. pylori proteins with 6559 human proteins. The predicted interactions include 549 hypothetical proteins of as yet unknown function encoded in the H. pylori genome and 13 experimentally verified secreted proteins. We have recognized 833 interactions involving the extracellular domains of transmembrane proteins of H. pylori. Structural analysis of some of the examples reveals that the interaction predicted by us is consistent with the structural compatibility of binding partners. Examples of interactions with discernible biological relevance are discussed.
Resumo:
The rapid increase in genome sequence information has necessitated the annotation of their functional elements, particularly those occurring in the non-coding regions, in the genomic context. Promoter region is the key regulatory region, which enables the gene to be transcribed or repressed, but it is difficult to determine experimentally. Hence an in silico identification of promoters is crucial in order to guide experimental work and to pin point the key region that controls the transcription initiation of a gene. In this analysis, we demonstrate that while the promoter regions are in general less stable than the flanking regions, their average free energy varies depending on the GC composition of the flanking genomic sequence. We have therefore obtained a set of free energy threshold values, for genomic DNA with varying GC content and used them as generic criteria for predicting promoter regions in several microbial genomes, using an in-house developed tool `PromPredict'. On applying it to predict promoter regions corresponding to the 1144 and 612 experimentally validated TSSs in E. coli (50.8% GC) and B. subtilis (43.5% GC) sensitivity of 99% and 95% and precision values of 58% and 60%, respectively, were achieved. For the limited data set of 81 TSSs available for M. tuberculosis (65.6% GC) a sensitivity of 100% and precision of 49% was obtained.
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Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.