Integrable Kondo impurity in one-dimensional q-deformed t-J models

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.

Prediction of promiscuous peptides that bind HLA class I molecules

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.

Methods for prediction of peptide binding to MHC molecules: A comparative study

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.

On entanglement and Lorentz transformations

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.

Neighborhood and Efficiency in Manufacturing in Brazilian Regions: A Spatial Markov Chain Analysis

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.

A comparative study of similarity measures for manufacturing cell formation

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.

A spectral clustering algorithm for manufacturing cell formation

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.

Valuing water resources in developing countries: A semiparametric approach to valuation models

Valuation of projects for the preservation of water resources provides important information to policy makers and funding institutions. Standard contingent valuation models rely on distributional assumptions to provide welfare measures. Deviations from assumed and actual distribution of benefits are important when designing policies in developing countries, where inequality is a concern. This article applies semiparametric methods to obtain estimates of the benefit from a project for the preservation of an important Brazilian river basin. These estimates lead to significant differences from those obtained using the standard parametric approach.

Synthesis and characterization of ternary hybrid material based on poly-o-methoxyaniline and poly(ethylene oxide) in mesostructured V(2)O(5)

New hybrid composites based on mesostructured V(2)O(5) containing intercalated poly(ethylene oxide), poly-o-methoxyaniline and poly(ethylene oxide)/poly-o-methoxyaniline were prepared. The results suggest that the polymers were intercalated into the layers of the mesostructured V(2)O(5). Electrochemical studies showed that the presence of both polymers in the mesostructured V(2)O(5) (ternary hybrid) leads to an increase in total charge and stability after several cycles compared with binary hybrid composites. This fact makes this material a potential component as cathode for lithium ion intercalation and further, a promising candidate for applications in batteries.

Calcium Carbonate Particle Growth Depending on Coupling among Adjacent Layers in Hybrid LB/LbL Films

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.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

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.

Morphological and electrochemical investigation of RuO(2)-Ta(2)O(5) oxide films prepared by the Pechini-Adams method

Preparation methods can profoundly affect the structural and electrochemical properties of electrocatalytic coatings. In this investigation, RuO(2)-Ta(2)O(5) thin films containing between 10 and 90 at.% Ru were prepared by the Pechini-Adams method. These coatings were electrochemically and physically characterized by cyclic voltammetry, scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD). The composition and morphology of the oxide were investigated before and after accelerated life tests (ALT) by EDX and SEM. SEM results indicate typical mud-flat-cracking morphology for the majority of the films. High resolution SEMs reveal that pure oxide phases exhibit nanoporosity while binary compositions display a very compact structure. EDX analyses reveal considerable amounts of Ru in the coating even after total deactivation. XRD indicated a rutile-type structure for RuO(2) and orthorhombic structure for Ta(2)O(5). XPS data demonstrate that the binding energy of Ta is affected by Ru addition in the thin films, but the binding energy of Ru is not likewise influenced by Ta. The stability of the electrodes was evaluated by ALT performed at 750 mA cm(-2) in 80 degrees C 0.5 mol dm(-3) H(2)SO(4). The performance of electrodes prepared by the Pechini-Adams method is 100% better than that of electrodes prepared by standard thermal decomposition.

Effect of W on PtSn/C catalysts for ethanol electrooxidation

Binary and ternary Pt-based catalysts were prepared by the Pechini-Adams modified method on carbon Vulcan XC-72, and different nominal compositions were characterized by TEM and XRD. XRD showed that the electrocatalysts consisted of the Pt displaced phase, suggesting the formation of a solid solution between the metals Pt/W and Pt/Sn. Electrochemical investigations on these different electrode materials were carried out as a function of the electrocatalyst composition, in acid medium (0.5 mol dm(-3) H2SO4) and in the presence of ethanol. The results obtained at room temperature showed that the PtSnW/C catalyst display better catalytic activity for ethanol oxidation compared to PtW/C catalyst. The reaction products (acetaldehyde, acetic acid and carbon dioxide) were analyzed by HPLC and identified by in situ infrared reflectance spectroscopy. The latter technique also allowed identification of the intermediate and adsorbed species. The presence of linearly adsorbed CO and CO2 indicated that the cleavage of the C-C bond in the ethanol substrate occurred during the oxidation process. At 90 degrees C, the Pt85Sn8W7/C catalyst gave higher current and power performances as anode material in a direct ethanol fuel cell (DEFC).

Self-assembled films from WO(3): Electrochromism and lithium ion diffusion

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.

Rifampicin determination in plasma by stir bar-sorptive extraction and liquid chromatography

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.