946 resultados para Theoretical approach
Resumo:
In this paper, we estimate the losses during teleportation processes requiring either two high-Q cavities or a single bimodal cavity. The estimates were carried out using the phenomenological operator approach introduced by de Almeida et al. [Phys. Rev. A 62, 033815 (2000)].
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The parallel mutation-selection evolutionary dynamics, in which mutation and replication are independent events, is solved exactly in the case that the Malthusian fitnesses associated to the genomes are described by the random energy model (REM) and by a ferromagnetic version of the REM. The solution method uses the mapping of the evolutionary dynamics into a quantum Ising chain in a transverse field and the Suzuki-Trotter formalism to calculate the transition probabilities between configurations at different times. We find that in the case of the REM landscape the dynamics can exhibit three distinct regimes: pure diffusion or stasis for short times, depending on the fitness of the initial configuration, and a spin-glass regime for large times. The dynamic transition between these dynamical regimes is marked by discontinuities in the mean-fitness as well as in the overlap with the initial reference sequence. The relaxation to equilibrium is described by an inverse time decay. In the ferromagnetic REM, we find in addition to these three regimes, a ferromagnetic regime where the overlap and the mean-fitness are frozen. In this case, the system relaxes to equilibrium in a finite time. The relevance of our results to information processing aspects of evolution is discussed.
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We present parameter-free calculations of electronic properties of InGaN, InAlN, and AlGaN alloys. The calculations are based on a generalized quasichemical approach, to account for disorder and composition effects, and first-principles calculations within the density functional theory with the LDA-1/2 approach, to accurately determine the band gaps. We provide precise results for AlGaN, InGaN, and AlInN band gaps for the entire range of compositions, and their respective bowing parameters. (C) 2011 American Institute of Physics. [doi:10.1063/1.3576570]
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Transparent conducting oxides (TCO) are widely used in technological applications ranging from photovoltaics to thin-film transparent field-effect transistors. In this work we report a first-principles investigation, based on density-functional theory, of the atomic and electronic properties of Ga(2)O(3)(ZnO)(6) (GZO(6)), which is a promising candidate to be used as host oxide for wide band gap TCO applications. We identify a low-energy configuration for the coherent distribution of the Ga and Zn atoms in the cation positions within the experimentally reported orthorhombic GZO(6) structure. Four Ga atoms are located in four-fold sites, while the remaining 12 Ga atoms in the unit cell form four shared Ga agglomerates (a motif of four atoms). The Zn atoms are distributed in the remaining cation sites with effective coordination numbers from 3.90 to 4.50. Furthermore, we identify the natural formation of twin-boundaries in GZO(6), which can explain the zigzag modulations observed experimentally by high-resolution transmission electron microscopy in GZO(n) (n=9). Due to the intrinsic twin-boundary formation, polarity inversion in the ZnO tetrahedrons is present which is facilitated by the formation of the Ga agglomerates. Our analysis shows that the formation of fourfold Ga sites and Ga agglomerates are stabilized by the electronic octet rule, while the distribution of Ga atoms and the formation of the twin-boundary help alleviate excess strain. Finally we identify that the electronic properties of GZO(6) are essentially determined by the electronic properties of ZnO, i.e., there are slight changes in the band gap and optical absorption properties.
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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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Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.
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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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Obesity has been recognized as a worldwide public health problem. It significantly increases the chances of developing several diseases, including Type II diabetes. The roles of insulin and leptin in obesity involve reactions that can be better understood when they are presented step by step. The aim of this work was to design software with data from some of the most recent publications on obesity, especially those concerning the roles of insulin and leptin in this metabolic disturbance. The most notable characteristic of this software is the use of animations representing the cellular response together with the presentation of recently discovered mechanisms on the participation of insulin and leptin in processes leading to obesity. The software was field tested in the Biochemistry of Nutrition web-based course. After using the software and discussing its contents in chatrooms, students were asked to answer an evaluation survey about the whole activity and the usefulness of the software within the learning process. The teaching assistants (TA) evaluated the software as a tool to help in the teaching process. The students' and TAs' satisfaction was very evident and encouraged us to move forward with the software development and to improve the use of this kind of educational tool in biochemistry classes.
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A simple and easy approach to produce polymeric microchips with integrated copper electrodes for capacitively coupled contactless conductivity detection (CD) is described. Copper electrodes were fabricated using a printed circuit board (PCB) as an inexpensive thin-layer of metal. The electrode layout was first drawn and laser printed on a wax paper sheet. The toner layer deposited on the paper sheet was thermally transferred to the PCB surface working as a mask for wet chemical etching of the copper layer. After the etching step, the toner was removed with an acetonitrile-dampened cotton. A poly(ethylene terephthalate) (PET) film coated with a thin thermo-sensitive adhesive layer was used to laminate the PCB plate providing an insulator layer of the electrodes to perform CID measurements. Electrophoresis microchannels were fabricated in poly(dimethylsiloxane) (PDMS) by soft lithography and reversibly sealed against the PET film. These hybrid PDMS/PET chips exhibited a stable electroosmotic mobility of 4.25 +/- 0.04 x 10(-4) V cm(-2) s(-1), at pH 6.1, over fifty runs. Efficiencies ranging from 1127 to 1690 theoretical plates were obtained for inorganic cations.
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The aim of this paper was to study a method based on gas production technique to measure the biological effects of tannins on rumen fermentation. Six feeds were used as fermentation substrates in a semi-automated gas method: feed A - aroeira (Astronium urundeuva); feed B - jurema preta (Mimosa hostilis), feed C - sorghum grains (Sorghum bicolor); feed D - Tifton-85 (Cynodon sp.); and two others prepared mixing 450 g sorghum leaves, 450 g concentrate (maize and soybean meal) and 100 g either of acacia (Acacia mearnsii) tannin extract (feed E) or quebracho (Schinopsis lorentzii) tannin extract (feed F) per kg (w:w). Three assays were carried out to standardize the bioassay for tannins. The first assay compared two binding agents (polyethylene glycol - PEG - and polyvinyl polypirrolidone - PVPP) to attenuate the tannin effects. The complex formed by PEG and tannins showed to be more stable than PVPP and tannins. Then, in the second assay, PEG was used as binding agent, and this assay was done to evaluate levels of PEG (0, 500, 750, 1000 and 1250 mg/g DM) to minimize the tannin effect. All the tested levels of PEG produced a response to evaluate tannin effects but the best response was for dose of 1000 mg/g DM. Using this dose of PEG, the final assay was carried out to test three compounds (tannic acid, quebracho extract and acacia extract) to establish a curve of biological equivalent effect of tannins. For this, five levels of each compound were added to I g of a standard feed (Lucerne hay). The equivalent effect showed not to be directly related to the chemical analysis for tannins. It was shown that different sources of tannins had different activities or reactivities. The curves of biological equivalence can provide information about tannin reactivity and its use seems to be important as an additional factor for chemical analysis. (C) 2007 Elsevier B.V. All rights reserved.
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A simultaneous optimization strategy based on a neuro-genetic approach is proposed for selection of laser induced breakdown spectroscopy operational conditions for the simultaneous determination of macronutrients (Ca, Mg and P), micro-nutrients (B, Cu, Fe, Mn and Zn), Al and Si in plant samples. A laser induced breakdown spectroscopy system equipped with a 10 Hz Q-switched Nd:YAG laser (12 ns, 532 nm, 140 mJ) and an Echelle spectrometer with intensified coupled-charge device was used. Integration time gate, delay time, amplification gain and number of pulses were optimized. Pellets of spinach leaves (NIST 1570a) were employed as laboratory samples. In order to find a model that could correlate laser induced breakdown spectroscopy operational conditions with compromised high peak areas of all elements simultaneously, a Bayesian Regularized Artificial Neural Network approach was employed. Subsequently, a genetic algorithm was applied to find optimal conditions for the neural network model, in an approach called neuro-genetic, A single laser induced breakdown spectroscopy working condition that maximizes peak areas of all elements simultaneously, was obtained with the following optimized parameters: 9.0 mu s integration time gate, 1.1 mu s delay time, 225 (a.u.) amplification gain and 30 accumulated laser pulses. The proposed approach is a useful and a suitable tool for the optimization process of such a complex analytical problem. (C) 2009 Elsevier B.V. All rights reserved.
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A novel strategy for accomplishing zone trapping in flow analysis is proposed. The sample and the reagent solutions are simultaneously inserted into convergent carrier streams and the established zones merge together before reaching the detector, where the most concentrated portion of the entire sample zone is trapped. The main characteristics, potentialities and limitations of the strategy were critically evaluated in relation to an analogous flow system with zone stopping. When applied to the spectrophotometric determination of nitrite in river waters, the main figures of merit were maintained, exception made for the sampling frequency which was calculated as 189h(-1), about 32% higher relatively to the analogous system with zone stopping. The sample inserted volume can be increased up to 1.0 mL without affecting sampling frequency and no problems with pump heating or malfunctions were noted after 8-h operation of the system. In contrast to zone stopping, only a small portion of the sample zone is halted with zone trapping, leading to these beneficial effects. (C) 2011 Elsevier B.V. All rights reserved.
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Diabetes mellitus (DM) is a disease that affects a large number of people, and the number of problems associated with the disease has been increasing in the past few decades. These problems include cardiovascular disorders, blindness and the eventual need to amputate limbs. Therefore, the quality of life for people living with DM is less than it is for healthy people. In several cases, metabolic syndrome (MS), which can be considered a disturbance of the lipid metabolism, is associated with DM. In this work, two drugs used to treat DM, pioglitazone and rosiglitazone, were studied using theoretical methods, and their molecular properties were related to the biological activity of these drugs. From the results, it was possible to correlate the properties of each substance-particularly electronic properties-with the biological interactions that are linked to their pharmacological effects. These results suggest that there are future prospects for designing or developing new drugs based on the correlation between theoretical and experimental properties.
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This article intends to contribute to the reflection on the Educational Statistics as being source for the researches on History of Education. The main concern was to reveal the way Educational Statistics related to the period from 1871 to 1931 were produced, in central government. Official reports - from the General Statistics Directory - and Statistics yearbooks released by that department were analyzed and, on this analysis, recommendations and definitions to perform the works were sought. By rending problematic to the documental issues on Educational Statistics and their usual interpretations, the intention was to reduce the ignorance about the origin of the school numbers, which are occasionally used in current researches without the convenient critical exam.
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Electrodeposition of thin copper layer was carried out on titanium wires in acidic sulphate bath. The influence of titanium surface preparation, cathodic current density, copper sulphate and sulphuric acid concentrations, electrical charge density and stirring of the solution on the adhesion of the electrodeposits was studied using the Taguchi statistical method. A L(16) orthogonal array with the six factors of control at two levels each and three interactions was employed. The analysis of variance of the mean adhesion response and signal-to-noise ratio showed the great influence of cathodic current density on adhesion. on the contrary, the other factors as well as the three investigated interactions revealed low or no significant effect. From this study optimized electrolysis conditions were defined. The copper electrocoating improved the electrical conductivity of the titanium wire. This shows that copper electrocoated titanium wires could be employed for both electrical purpose and mechanical reinforcement in superconducting magnets. (C) 2008 Elsevier B.V. All rights reserved.