99 resultados para Interaction Man-Computer


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Recently, we have found an additional spin-orbit (SO) interaction in quantum wells with two subbands [Bernardes , Phys. Rev. Lett. 99, 076603 (2007)]. This new SO term is nonzero even in symmetric geometries, as it arises from the intersubband coupling between confined states of distinct parities, and its strength is comparable to that of the ordinary Rashba. Starting from the 8x8 Kane model, here we present a detailed derivation of this new SO Hamiltonian and the corresponding SO coupling. In addition, within the self-consistent Hartree approximation, we calculate the strength of this new SO coupling for realistic symmetric modulation-doped wells with two subbands. We consider gated structures with either a constant areal electron density or a constant chemical potential. In the parameter range studied, both models give similar results. By considering the effects of an external applied bias, which breaks the structural inversion symmetry of the wells, we also calculate the strength of the resulting induced Rashba couplings within each subband. Interestingly, we find that for double wells the Rashba couplings for the first and second subbands interchange signs abruptly across the zero bias, while the intersubband SO coupling exhibits a resonant behavior near this symmetric configuration. For completeness we also determine the strength of the Dresselhaus couplings and find them essentially constant as function of the applied bias.

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We theoretically investigate the Rashba spin-orbit interaction in InAs/GaSb quantum wells (QWs). We find that the Rashba spin-splitting (RSS) sensitively depends on the thickness of the InAs layer. The RSS exhibits nonlinear behavior for narrow InAs/GaSb QWs and the oscillating feature for wide InAs/GaSb QWs. The nonlinear and oscillating behaviors arise from the weakened and enhanced interband coupling. The RSS also show asymmetric features respect to the direction of the external electric field. (C) 2008 American Institute of Physics.

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We investigate the performance of a variant of Axelrod's model for dissemination of culture-the Adaptive Culture Heuristic (ACH)-on solving an NP-Complete optimization problem, namely, the classification of binary input patterns of size F by a Boolean Binary Perceptron. In this heuristic, N agents, characterized by binary strings of length F which represent possible solutions to the optimization problem, are fixed at the sites of a square lattice and interact with their nearest neighbors only. The interactions are such that the agents' strings (or cultures) become more similar to the low-cost strings of their neighbors resulting in the dissemination of these strings across the lattice. Eventually the dynamics freezes into a homogeneous absorbing configuration in which all agents exhibit identical solutions to the optimization problem. We find through extensive simulations that the probability of finding the optimal solution is a function of the reduced variable F/N(1/4) so that the number of agents must increase with the fourth power of the problem size, N proportional to F(4), to guarantee a fixed probability of success. In this case, we find that the relaxation time to reach an absorbing configuration scales with F(6) which can be interpreted as the overall computational cost of the ACH to find an optimal set of weights for a Boolean binary perceptron, given a fixed probability of success.

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Ultra-high-energy cosmic rays (UHECRs), with energies above similar to 6 x 10(19) eV, seem to show a weak correlation with the distribution of matter relatively near to us in the universe. It has earlier been proposed that UHECRs could be accelerated in either the nucleus or the outer lobes of the nearby radio galaxy Cen A. We show that UHECR production at a spatially intermediate location about 15 kpc northeast from the nucleus, where the jet emerging from the nucleus is observed to strike a large star-forming shell of gas, is a plausible alternative. A relativistic jet is capable of accelerating lower energy heavy seed cosmic rays (CRs) to UHECRs on timescales comparable to the time it takes the jet to pierce the large gaseous cloud. In this model, many CRs arising from a starburst, with a composition enhanced in heavy elements near the knee region around PeV, are boosted to ultra-high energies by the relativistic shock of a newly oriented jet. This model matches the overall spectrum shown by the Auger data and also makes a prediction for the chemical composition as a function of particle energy. We thus predict an observable anisotropy in the composition at high energy in the sense that lighter nuclei should preferentially be seen toward the general direction of Cen A. Taking into consideration the magnetic field models for the Galactic disk and a Galactic magnetic wind, this scenario may resolve the discrepancy between HiRes and Auger results concerning the chemical composition of UHECRs.

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The concept of constitutional dynamic chemistry (CDC) based on the control of non-covalent interactions in supramolecular structures is promising for having a large impact on nanoscience and nanotechnology if adequate nanoscale manipulation methods are used. In this study, we demonstrate that the layer-by-layer (LbL) technique may be used to produce electroactive electrodes with ITO coated by tetrasulfonated nickel phthalocyanine (NiTsPc) alternated with poly(allylamine hydrochloride) (PAH) incorporating gold nanoparticles (AuNP), in which synergy has been achieved in the interaction between the nanoparticles and NiTsPc. The catalytic activity toward hydrogen peroxide (H(2)O(2)) in multilayer films was investigated using cyclic voltammetry, where oxidation of H(2)O(2) led to increased currents in the PAH-AuNP/NiTsPc films for the electrochemical processes associated with the phthalocyanine ring and nickel at 0.52 and 0.81 V vs. SCE, respectively, while for PAH/NiTsPc films (without AuNP) only the first redox process was affected. In control experiments we found out that the catalytic activity was not solely due to the presence of AuNP, but rather to the nanoparticles inducing NiTsPc supramolecular structures that favored access to their redox sites, thus yielding strong charge transfer. The combined effects of NiTsPc and AuNP, which could only be observed in nanostructured LbL films, point to another avenue to pursue within the CDC paradigm.

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Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

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We consider the problem of interaction neighborhood estimation from the partial observation of a finite number of realizations of a random field. We introduce a model selection rule to choose estimators of conditional probabilities among natural candidates. Our main result is an oracle inequality satisfied by the resulting estimator. We use then this selection rule in a two-step procedure to evaluate the interacting neighborhoods. The selection rule selects a small prior set of possible interacting points and a cutting step remove from this prior set the irrelevant points. We also prove that the Ising models satisfy the assumptions of the main theorems, without restrictions on the temperature, on the structure of the interacting graph or on the range of the interactions. It provides therefore a large class of applications for our results. We give a computationally efficient procedure in these models. We finally show the practical efficiency of our approach in a simulation study.

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Bacterial type III secretion systems deliver protein virulence factors to host cells. Here we characterize the interaction between HrpB2, a small protein secreted by the Xanthomonas citri subsp. citri type III secretion system, and the cytosolic domain of the inner membrane protein HrcU, a paralog of the flagellar protein FlhB. We show that a recombinant fragment corresponding to the C-terminal cytosolic domain of HrcU produced in E. coli suffers cleavage within a conserved Asn264-Pro265-Thr266-His267 (NPTH) sequence. A recombinant HrcU cytosolic domain with N264A, P265A, T266A mutations at the cleavage site (HrcU(AAAH)) was not cleaved and interacted with HrpB2. Furthermore, a polypeptide corresponding to the sequence following the NPTH cleavage site also interacted with HrpB2 indicating that the site for interaction is located after the NPTH site. Non-polar deletion mutants of the hrcU and hrpB2 genes resulted in a total loss of pathogenicity in susceptible citrus plants and disease symptoms could be recovered by expression of HrpB2 and HrcU from extrachromossomal plasmids. Complementation of the Delta hrcU mutant with HrcU(AAAH) produced canker lesions similar to those observed when complemented with wild-type HrcU. HrpB2 secretion however, was significantly reduced in the Delta hrcU mutant complemented with HrcU(AAAH), suggesting that an intact and cleavable NPTH site in HrcU is necessary for total functionally of T3SS in X. citri subsp. citri. Complementation of the Delta hrpB2 X. citri subsp. citri strain with a series of hrpB2 gene mutants revealed that the highly conserved HrpB2 C-terminus is essential for T3SS-dependent development of citrus canker symptoms in planta.

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Background: Persistent infection with oncogenic types of human papillomavirus (HPV) is the major risk factor for invasive cervical cancer (ICC), and non-European variants of HPV-16 are associated with an increased risk of persistence and ICC. HLA class II polymorphisms are also associated with genetic susceptibility to ICC. Our aim is to verify if these associations are influenced by HPV-16 variability. Methods: We characterized HPV-16 variants by PCR in 107 ICC cases, which were typed for HLA-DQA1, DRB1 and DQB1 genes and compared to 257 controls. We measured the magnitude of associations by logistic regression analysis. Results: European ( E), Asian-American ( AA) and African (Af) variants were identified. Here we show that inverse association between DQB1*05 ( adjusted odds ratio [ OR] = 0.66; 95% confidence interval [CI]: 0.39-1.12]) and HPV-16 positive ICC in our previous report was mostly attributable to AA variant carriers ( OR = 0.27; 95% CI: 0.10-0.75). We observed similar proportions of HLA DRB1*1302 carriers in E-P positive cases and controls, but interestingly, this allele was not found in AA cases ( p = 0.03, Fisher exact test). A positive association with DRB1*15 was observed in both groups of women harboring either E ( OR = 2.99; 95% CI: 1.13-7.86) or AA variants ( OR = 2.34; 95% CI: 1.00-5.46). There was an inverse association between DRB1*04 and ICC among women with HPV-16 carrying the 350T [83L] single nucleotide polymorphism in the E6 gene ( OR = 0.27; 95% CI: 0.08-0.96). An inverse association between DQB1*05 and cases carrying 350G (83V) variants was also found ( OR = 0.37; 95% CI: 0.15-0.89). Conclusion: Our results suggest that the association between HLA polymorphism and risk of ICC might be influenced by the distribution of HPV-16 variants.

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Background: Physical protein-protein interaction (PPI) is a critical phenomenon for the function of most proteins in living organisms and a significant fraction of PPIs are the result of domain-domain interactions. Exon shuffling, intron-mediated recombination of exons from existing genes, is known to have been a major mechanism of domain shuffling in metazoans. Thus, we hypothesized that exon shuffling could have a significant influence in shaping the topology of PPI networks. Results: We tested our hypothesis by compiling exon shuffling and PPI data from six eukaryotic species: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Cryptococcus neoformans and Arabidopsis thaliana. For all four metazoan species, genes enriched in exon shuffling events presented on average higher vertex degree (number of interacting partners) in PPI networks. Furthermore, we verified that a set of protein domains that are simultaneously promiscuous (known to interact to multiple types of other domains), self-interacting (able to interact with another copy of themselves) and abundant in the genomes presents a stronger signal for exon shuffling. Conclusions: Exon shuffling appears to have been a recurrent mechanism for the emergence of new PPIs along metazoan evolution. In metazoan genomes, exon shuffling also promoted the expansion of some protein domains. We speculate that their promiscuous and self-interacting properties may have been decisive for that expansion.

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We studied the open circuit interaction of methanol and ethanol with oxidized platinum electrodes using in situ infrared spectroscopy. For methanol, it was found that formic acid is the main species formed in the initial region of the transient and that the steep decrease of the open circuit potential coincides with an explosive increase in the CO(2) production, which is followed by an increase in the coverage of adsorbed CO. For ethanol, acetaldehyde was the main product detected and only traces of dissolved CO(2) and adsorbed CO were found after the steep potential decay. In both cases, the transients were interpreted in terms of (a) the emergence of sub-surface oxygen in the beginning of the transient, where the oxide content is high, and (b) the autocatalytic production of free platinum sites for lower oxide content during the steep decay of the open circuit potential.

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A model where agents show discrete behavior regarding their actions, but have continuous opinions that are updated by interacting with other agents is presented. This new updating rule is applied to both the voter and Sznajd models for interaction between neighbors, and its consequences are discussed. The appearance of extremists is naturally observed and it seems to be a characteristic of this model.

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This paper presents a framework to build medical training applications by using virtual reality and a tool that helps the class instantiation of this framework. The main purpose is to make easier the building of virtual reality applications in the medical training area, considering systems to simulate biopsy exams and make available deformation, collision detection, and stereoscopy functionalities. The instantiation of the classes allows quick implementation of the tools for such a purpose, thus reducing errors and offering low cost due to the use of open source tools. Using the instantiation tool, the process of building applications is fast and easy. Therefore, computer programmers can obtain an initial application and adapt it to their needs. This tool allows the user to include, delete, and edit parameters in the functionalities chosen as well as storing these parameters for future use. In order to verify the efficiency of the framework, some case studies are presented.

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In the plasma kallikrein-kinin system, it has been shown that when plasma prekallikrein (PM) and high molecular weight kininogen (HK) assemble on endothelial cells, plasma kallikrein (huPK) becomes available to cleave HK, releasing bradykinin, a potent mediator of the inflammatory response. Because the formation of soluble glycosaminoglycans occurs concomitantly during the inflammatory processes, the effect of these polysaccharides on the interaction of HK on the cell surface or extracellular matrix (ECM) of two endothelial cell lines (ECV304 and RAEC) was investigated. In the presence of Zn(+2), HK binding to the surface or ECM of RAEC was abolished by heparin; reduced by heparan sulfate, keratan sulfate, chondroitin 4-sulfate or dermatan sulfate; and not affected by chondroitin 6-sulfate. By contrast, only heparin reduced HK binding to the ECV304 cell surface or ECM. Using heparin-correlated molecules such as low molecular weight dextran sulfate, low molecular weight heparin and N-desulfated heparin, we suggest that these effects were mainly dependent on the charge density and on the N-sulfated glucosamine present in heparin. Surprisingly, PM binding to cell- or ECM-bound-HK and PM activation was not modified by heparin. However, the hydrolysis of HK by huPK, releasing BK in the fluid phase, was augmented by this glycosaminoglycan in the presence of Zn(2+). Thus, a functional dichotomy exists in which soluble glycosaminoglycans may possibly either increase or decrease the formation of BK. In conclusion, glycosaminoglycans that accumulated in inflammatory fluids or used as a therapeutic drug (e.g., heparin) could act as pro- or anti-inflammatory mediators depending on different factors within the cell environment. (C) 2011 Elsevier Masson SAS. All rights reserved.