966 resultados para Critical Levels
Resumo:
We report accurate magnetization measurements on the spin-gap compound NiCl(2)-4SC (NH(2))(2) around the low portion of the magnetic induced phase ordering. The critical density of the magnetization at the phase boundary is analyzed in terms of a Bose-Einstein condensation (BEC) of bosonic particles, and the boson interaction strength is obtained as upsilon(0)=0.61 meV. The detailed analysis of the magnetization data across the transition leads to the conclusion for the preservation of the U(1) symmetry, as required for BEC. (c) 2009 American Institute of Physics. [DOI: 10.1063/1.3055265]
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We report new magnetization measurements on the spin-gap compound NiCl(2)-4SC(NH(2))(2) at the low-field boundary of the magnetic field-induced ordering. The critical density of the magnetization is analyzed in terms of a Bose-Einstein condensation of bosonic quasiparticles. The analysis of the magnetization at the transition leads to the conclusion for the preservation of the U(1) symmetry, as required for Bose-Einstein condensation. The experimental data are well described by quantum Monte Carlo simulations.
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We report results of magnetoacoustic studies in the quantum spin-chain magnet NiCl(2)-4SC(NH(2))(2) (DTN) having a field-induced ordered antiferromagnetic (AF) phase. In the vicinity of the quantum critical points (QCPs) the acoustic c(33) mode manifests a pronounced softening accompanied by energy dissipation of the sound wave. The acoustic anomalies are traced up to T > T(N), where the thermodynamic properties are determined by fermionic magnetic excitations, the ""hallmark"" of one-dimensional (1D) spin chains. On the other hand, as established in earlier studies, the AF phase in DTN is governed by bosonic magnetic excitations. Our results suggest the presence of a crossover from a 1D fermionic to a three-dimensional bosonic character of the magnetic excitations in DTN in the vicinity of the QCPs.
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We studied the effect of quantum confinement in Mn-doped InAs nanocrystals using theoretical methods. We observe that the stability of the impurities decreases with the size of the nanocrystals, making doping more difficult in small nanoparticles. Substitutional impurities are always more stable than interstitial ones, independent of the size of the nanocrystal. There is also a decrease in the energy difference between the high and low spin configurations, indicating that the critical temperature should decrease with the size of the nanoparticles, in agreement with experimental observations and in detriment to the development of functional spintronic devices with doped nanocrystals. Codoping with acceptors or saturating the nanocrystals with molecules that insert partially empty levels in the energy gap should be an efficient way to increase T(C).
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Stavskaya's model is a one-dimensional probabilistic cellular automaton (PCA) introduced in the end of the 1960s as an example of a model displaying a nonequilibrium phase transition. Although its absorbing state phase transition is well understood nowadays, the model never received a full numerical treatment to investigate its critical behavior. In this Brief Report we characterize the critical behavior of Stavskaya's PCA by means of Monte Carlo simulations and finite-size scaling analysis. The critical exponents of the model are calculated and indicate that its phase transition belongs to the directed percolation universality class of critical behavior, as would be expected on the basis of the directed percolation conjecture. We also explicitly establish the relationship of the model with the Domany-Kinzel PCA on its directed site percolation line, a connection that seems to have gone unnoticed in the literature so far.
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Finite-size scaling analysis turns out to be a powerful tool to calculate the phase diagram as well as the critical properties of two-dimensional classical statistical mechanics models and quantum Hamiltonians in one dimension. The most used method to locate quantum critical points is the so-called crossing method, where the estimates are obtained by comparing the mass gaps of two distinct lattice sizes. The success of this method is due to its simplicity and the ability to provide accurate results even considering relatively small lattice sizes. In this paper, we introduce an estimator that locates quantum critical points by exploring the known distinct behavior of the entanglement entropy in critical and noncritical systems. As a benchmark test, we use this new estimator to locate the critical point of the quantum Ising chain and the critical line of the spin-1 Blume-Capel quantum chain. The tricritical point of this last model is also obtained. Comparison with the standard crossing method is also presented. The method we propose is simple to implement in practice, particularly in density matrix renormalization group calculations, and provides us, like the crossing method, amazingly accurate results for quite small lattice sizes. Our applications show that the proposed method has several advantages, as compared with the standard crossing method, and we believe it will become popular in future numerical studies.
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The longitudinal resistivity rho(xx) of two-dimensional electron gases formed in wells with two subbands displays ringlike structures when plotted in a density-magnetic-field diagram, due to the crossings of spin-split Landau levels (LLs) from distinct subbands. Using spin density functional theory and linear response, we investigate the shape and spin polarization of these structures as a function of temperature and magnetic-field tilt angle. We find that (i) some of the rings ""break'' at sufficiently low temperatures due to a quantum Hall ferromagnetic phase transition, thus exhibiting a high degree of spin polarization (similar to 50%) within, consistent with the NMR data of Zhang et al. [Phys. Rev. Lett. 98, 246802 (2007)], and (ii) for increasing tilting angles the interplay between the anticrossings due to inter-LL couplings and the exchange-correlation effects leads to a collapse of the rings at some critical angle theta(c), in agreement with the data of Guo et al. [Phys. Rev. B 78, 233305 (2008)].
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We analyze the finite-size corrections to entanglement in quantum critical systems. By using conformal symmetry and density functional theory, we discuss the structure of the finite-size contributions to a general measure of ground state entanglement, which are ruled by the central charge of the underlying conformal field theory. More generally, we show that all conformal towers formed by an infinite number of excited states (as the size of the system L -> infinity) exhibit a unique pattern of entanglement, which differ only at leading order (1/L)(2). In this case, entanglement is also shown to obey a universal structure, given by the anomalous dimensions of the primary operators of the theory. As an illustration, we discuss the behavior of pairwise entanglement for the eigenspectrum of the spin-1/2 XXZ chain with an arbitrary length L for both periodic and twisted boundary conditions.
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Liquid-core waveguides (LCWs), devices that constrain the emitted radiation minimizing losses during the transport, are an alternative to maximize the amount of detected radiation in luminescence. In this work, the performance of a LCW flow-cell was critically evaluated for chemiluminescence measurements, by using as model the oxidation of luminol by hydrogen peroxide or hypochlorite. An analytical procedure for hypochlorite determination was also developed, with linear response in the range 0.2-3.8 mg/L (2.7-51 mu mol/L), a detection limit estimated as 8 mu g/L (0.64 mu mol/L) at the 99.7% confidence level and luminol consumption of 50 mu g/determination. The coefficients of variation were 3.3% and 1.6% for 0.4 and 1.9 mg/L CIO(-), respectively, with a sampling rate of 164 determinations/h. The procedure was applied to the analysis of Dakin`s solution samples, yielding results in agreement with those obtained by iodometric titration at the 95% confidence level. Copyright (c) 2008 John Wiley & Sons, Ltd.
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Coupling of a flow cell based on a liquid core waveguide (LCW) to flow systems for spectro photometric measurements was critically evaluated. Flow-based systems with and without chemical reactions were exploited to estimate the increase in analytical signal in comparison to those obtained with a conventional I cm cell under different experimental conditions. The Schlieren effect associated to intense concentration gradients in the sample zone was investigated with model solutions that do not absorb visible electromagnetic radiation. The effect of radiation scattering was lower than the expected by considering the increase in the optical path, being the magnitude of the perturbation up to 40% higher for the 100-cm LCW cell. Several alternatives for compensation of the Schlieren effect were experimentally investigated. The potentiality of the LCW for turbidimetric measurements and coupling to monosegmented flow analysis was also evaluated. (C) 2008 Elsevier B.V. All rights reserved.
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Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.
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In this work we study an agent based model to investigate the role of asymmetric information degrees for market evolution. This model is quite simple and may be treated analytically since the consumers evaluate the quality of a certain good taking into account only the quality of the last good purchased plus her perceptive capacity beta. As a consequence, the system evolves according to a stationary Markov chain. The value of a good offered by the firms increases along with quality according to an exponent alpha, which is a measure of the technology. It incorporates all the technological capacity of the production systems such as education, scientific development and techniques that change the productivity rates. The technological level plays an important role to explain how the asymmetry of information may affect the market evolution in this model. We observe that, for high technological levels, the market can detect adverse selection. The model allows us to compute the maximum asymmetric information degree before the market collapses. Below this critical point the market evolves during a limited period of time and then dies out completely. When beta is closer to 1 (symmetric information), the market becomes more profitable for high quality goods, although high and low quality markets coexist. The maximum asymmetric information level is a consequence of an ergodicity breakdown in the process of quality evaluation. (C) 2011 Elsevier B.V. All rights reserved.
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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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Background: Continuing education courses related to critical thinking and clinical reasoning are needed to improve the accuracy of diagnosis. Method: This study evaluated a 4-day, 16-hour continuing education course conducted in Brazil. Thirty-nine nurses completed a pretest and a posttest consisting of two written case studies designed to measure the accuracy of nurses` diagnoses. Results: There were significant differences in accuracy from pretest to posttest for case 1 (p = .008) and case 2 (p = .042) and overall (p = .001). Conclusion: Continuing education courses should be implemented to improve the accuracy of nurses` diagnoses. J Contin Educ Nurs 2009;40(3):121-127.
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Background/Aims: To investigate the association between cortisol levels, chronic stress and coping in subjects with amnestic-type mild cognitive impairment (aMCI). Methods: Cortisol levels were measured using morning saliva samples from 33 individuals with aMCI and from 41 healthy elderly. Chronic stress was evaluated with the Stress Symptoms List (SSL), whereas coping strategies were assessed using the Jalowiec Coping Scale. Results: aMCI subjects with high SSL scores presented higher cortisol levels (p = 0.045). Furthermore, aMCI subjects who employed emotion-focused coping had higher SSL scores (p = 0.023). Conclusion: The association between increased cortisol secretion, chronic stress and coping strategies may be modulated by the presence or absence of cognitive impairment, where memory deficit awareness constitutes an additional potential factor involved in high stress severity. Copyright (C) 2009 S. Karger AG, Basel