971 resultados para canonical matrices
Resumo:
Matrix population models, elasticity analysis and loop analysis can potentially provide powerful techniques for the analysis of life histories. Data from a capture-recapture study on a population of southern highland water skinks (Eulamprus tympanum) were used to construct a matrix population model. Errors in elasticities were calculated by using the parametric bootstrap technique. Elasticity and loop analyses were then conducted to identify the life history stages most important to fitness. The same techniques were used to investigate the relative importance of fast versus slow growth, and rapid versus delayed reproduction. Mature water skinks were long-lived, but there was high immature mortality. The most sensitive life history stage was the subadult stage. It is suggested that life history evolution in E. tympanum may be strongly affected by predation, particularly by birds. Because our population declined over the study, slow growth and delayed reproduction were the optimal life history strategies over this period. Although the techniques of evolutionary demography provide a powerful approach for the analysis of life histories, there are formidable logistical obstacles in gathering enough high-quality data for robust estimates of the critical parameters.
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Integrable Kondo impurities in two cases of one-dimensional q-deformed t-J models are studied by means of the boundary Z(2)-graded quantum inverse scattering method. The boundary K matrices depending on the local magnetic moments of the impurities are presented as nontrivial realizations of the reflection equation algebras in an impurity Hilbert space. Furthermore, these models are solved by using the algebraic Bethe ansatz method and the Bethe ansatz equations are obtained.
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Promiscuous T-cell epitopes make ideal targets for vaccine development. We report here a computational system, multipred, for the prediction of peptide binding to the HLA-A2 supertype. It combines a novel representation of peptide/MHC interactions with a hidden Markov model as the prediction algorithm. multipred is both sensitive and specific, and demonstrates high accuracy of peptide-binding predictions for HLA-A*0201, *0204, and *0205 alleles, good accuracy for *0206 allele, and marginal accuracy for *0203 allele. multipred replaces earlier requirements for individual prediction models for each HLA allelic variant and simplifies computational aspects of peptide-binding prediction. Preliminary testing indicates that multipred can predict peptide binding to HLA-A2 supertype molecules with high accuracy, including those allelic variants for which no experimental binding data are currently available.
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Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.
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We study the transformation of maximally entangled states under the action of Lorentz transformations in a fully relativistic setting. By explicit calculation of the Wigner rotation, we describe the relativistic analog of the Bell states as viewed from two inertial frames moving with constant velocity with respect to each other. Though the finite dimensional matrices describing the Lorentz transformations are non-unitary, each single particle state of the entangled pair undergoes an effective, momentum dependent, local unitary rotation, thereby preserving the entanglement fidelity of the bipartite state. The details of how these unitary transformations are manifested are explicitly worked out for the Bell states comprised of massive spin 1/2 particles and massless photon polarizations. The relevance of this work to non-inertial frames is briefly discussed.
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Activity within motor areas of the cortex begins to increase 1 to 2 s prior to voluntary self-initiated movement (termed the Bereitschaftspotential or readiness potential). There has been much speculation and debate over the precise source of this early premovement activity as it is important for understanding the roles of higher order motor areas in the preparation and readiness for voluntary movement. In this study, we use high-field (3-T) event-related fMRI with high temporal sampling (partial brain volumes every 250 ms) to specifically examine hemodynamic response time courses during the preparation, readiness, and execution of purely self-initiated voluntary movement. Five right-handed healthy volunteers performed a rapid sequential finger-to-thumb movement performed at self-determined times (12-15 trials). Functional images for each trial were temporally aligned and the averaged time series for each subject was iteratively correlated with a canonical hemodynamic response function progressively shifted in time. This analysis method identified areas of activation without constraining hemodynamic response timing. All subjects showed activation within frontal mesial areas, including supplementary motor area (SMA) and cingulate motor areas, as well as activation in left primary sensorimotor areas. The time courses of hemodynamic responses showed a great deal of variability in shape and timing between subjects; however, four subjects clearly showed earlier relative hemodynamic responses within SMA/cingulate motor areas compared with left primary motor areas. These results provide further evidence that the SMA and cingulate motor areas are major contributors to early stage premovement activity and play an important role in the preparation and readiness for voluntary movement. (C) 2003 Elsevier Inc. All rights reserved.
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This paper analyzes the geography of regional competitiveness in manufacturing in Brazil. The authors estimate stochastic frontiers to calculate regional efficiency of representative firms in 137 regions in the period 2000-2006, in four sectors defined by technological intensity. The efficiency results are analyzed using Markov Spatial Transition Matrices to provide insights into the transition of regions between efficiency levels, considering their local spatial context. The results indicate that geography plays an important role in manufacturing competitiveness. In particular, regions with more competitive neighbors are more likely to improve their relative efficiency (pull effect) over time, and regions with less competitive neighbors are more likely to lose relative efficiency (drag effect). The authors find that the pull effect is stronger than the drag effect.
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We introduced a spectral clustering algorithm based on the bipartite graph model for the Manufacturing Cell Formation problem in [Oliveira S, Ribeiro JFF, Seok SC. A spectral clustering algorithm for manufacturing cell formation. Computers and Industrial Engineering. 2007 [submitted for publication]]. It constructs two similarity matrices; one for parts and one for machines. The algorithm executes a spectral clustering algorithm on each separately to find families of parts and cells of machines. The similarity measure in the approach utilized limited information between parts and between machines. This paper reviews several well-known similarity measures which have been used for Group Technology. Computational clustering results are compared by various performance measures. (C) 2008 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
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A graph clustering algorithm constructs groups of closely related parts and machines separately. After they are matched for the least intercell moves, a refining process runs on the initial cell formation to decrease the number of intercell moves. A simple modification of this main approach can deal with some practical constraints, such as the popular constraint of bounding the maximum number of machines in a cell. Our approach makes a big improvement in the computational time. More importantly, improvement is seen in the number of intercell moves when the computational results were compared with best known solutions from the literature. (C) 2009 Elsevier Ltd. All rights reserved.
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Loss of connectivity in impounded rivers is among the impacts imposed by dams, and mitigation measures such as fish passages might not accomplish their purpose of reestablishing an efficient bi-directional gene flow in the fish populations affected. As a consequence, fish populations remain fragmented, and a new interpopulational structure may develop, with increased risk of reduced genetic diversity and stochastic extinction. In order to evaluate the effects of the Gavio Peixoto Dam, which was constructed almost a century ago on the Jacar,-Gua double dagger u River in the Upper Parana River basin, Brazil, a comparative morphometric study was undertaken on the populations of the Neotropical migratory characid fish Salminus hilarii living up- and downstream of this dam. Population dynamics, spatial segregation, and habitat use by different age classes were monitored for 2 years. We found that segregation caused by the dam and long periods with no efficient connection by fish passages have led to fragmentation and interpopulational structuring of S. hilarii, as revealed by canonical variable analysis of morphometric features. The fish populations occupying the up- and downstream sections have succeeded in performing short-distance reproductive migrations in the main river and tributaries, have found suitable habitats for completing their life cycle, and have been able to maintain distinct small-sized populations so far.
Calcium Carbonate Particle Growth Depending on Coupling among Adjacent Layers in Hybrid LB/LbL Films
Resumo:
There are practical and academic situations that justify the study of calcium carbonate crystallization and especially of systems that are associated with organic matrices and a confined medium. Despite the fact that many different matrices have been studied, the use of well-behaved, thin organic films may provide new knowledge about this system. In this work, we have studied the growth of calcium carbonate particles on well-defined organic matrices that were formed by layer-by-layer (LbL) polyelectrolyte films deposited on phospholipid Langmuir-Blodgett films (LB). We were able to change the surface electrical charge density of the LB films by changing the proportions of a negatively charged lipid, the sodium salt of dimyristoyl-sn-glycero-phosphatidyl acid (DMPA), and a zwitterionic lipid. dimyristoyl-sn-glycero-phosphatidylethanolamine (DMPE). This affects the subsequent polyelectrolyte LbL film deposition, which also changes the the nature of the bonding (electrostatic interaction or hydrogen bonding). This approach allowed for the formation of calcium carbonate particles of different final shapes, roughnesses, and sizes. The masses of deposited lipids, polyelectrolytes, and calcium cabonate were quantified by the quartz crystal microbalance technique. The structures of obtained particles were analyzed by scanning electron microscopy.
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Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.
Resumo:
WO(3)/chitosan and WO(3)/chitosan/poly(ethylene oxide) (PEO) films were prepared by the layer-by-layer method. The presence of chitosan enabled PEO to be carried into the self-assembled structure, contributing to an increase in the Li(+) diffusion rate. On the basis of the galvanostatic intermittent titration technique (GITT) and the quadratic logistic equation (QLE), a spectroelectrochemical method was used for determination of the ""optical"" diffusion coefficient (D(op)), enabling analysis of the Li(+) diffusion rate and, consequently, the coloration front rate in these host matrices. The D(op) values within the WO(3)/chitosan/PEO film were significantly higher than those within the WO(3)/chitosan film, mainly for higher values of injected charge. The presence of PEO also ensured larger accessibility to the electroactive sites, in accordance with the method employed here. Hence, this spectroelectrochemical method allowed us to separate the contribution of the diffusion process from the number of accessible electroactive sites in the materials, thereby aiding a better understanding of the useful electrochemical and electrochromic properties of these films for use in electrochromic devices. (C) 2010 Elsevier B.V. All rights reserved.
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A sensitive and reproducible stir bar-sorptive extraction and high performance liquid chromatography-UV detection (SBSE/HPLC-UV) method for therapeutic drug monitoring of rifampicin in plasma samples is described and compared with a liquid:liquid extraction (LLE/HPLC-UV) method. This miniaturized method can result in faster analysis, higher sample throughput, lower solvent consumption and less workload per sample while maintaining or even improving sensitivity. Important factors in the optimization of SBSE efficiency such as pH, temperature, extraction time and desorption conditions (solvents, mode magnetic stir, mode ultrasonic stir, time and number of steps) were optimized recoveries ranging from 75 to 80%. Separation was obtained using a reverse phase C(8) column with UV detection (254 nm). The mobile phase consisted of methanol:0.25 N sodium acetate buffer, pH 5.0 (58:42, v/v). The SBSE/HPLC-UV method was linear over a working range of 0.125-50.0 mu g mL(-1). The intra-assay and inter-assay precision and accuracy were studied at three concentrations (1.25, 6.25 and 25.0 mu g mL(-1)). The intra-assay coefficients of variation (CVs) for all compounds were less than 10% and all inter-CVs were less than 10%. Limits of quantification were 0.125 mu g mL(-1). Stability studies showed rifampicin was stable in plasma for 12 h after thawing; the samples were also stable for 24 h after preparation. Based on the figures of merit results, the SBSE/HPLC-UV proved to be adequate to the rifampicin analyses from therapeutic to toxic levels. This method was successfully applied to the analysis of real samples and was as effective as the LLE/HPLC-UV method. (C) 2009 Elsevier B.V. All rights reserved.
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The effect of pore structure on the behavior of lithium intercalation into an electrode containing porous V(2)O(5) film has been investigated and compared with the electrode containing a non-porous V(2)O(5) film. X-ray diffraction patterns indicate a lamellar structure for both materials. Nitrogen adsorption isotherms, t-plot method, and Scanning Electronic Microscopy show that the route employed for the preparation of mesoporous V(2)O(5) was successful. The electrochemical performance of these matrices as lithium intercalation cathode materials was evaluated. The porous material reaches stability after several cycles more easily compared with the V(2)O(5) xerogel. Lithium intercalation into the porous V(2)O(5) film electrode is crucially influenced by pore surface and film surface irregularity, in contrast with the non-porous surface of the V(2)O(5) xerogel.