162 resultados para Caminhos k-críticos


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In this paper, we present a novel algorithm for piecewise linear regression which can learn continuous as well as discontinuous piecewise linear functions. The main idea is to repeatedly partition the data and learn a linear model in each partition. The proposed algorithm is similar in spirit to k-means clustering algorithm. We show that our algorithm can also be viewed as a special case of an EM algorithm for maximum likelihood estimation under a reasonable probability model. We empirically demonstrate the effectiveness of our approach by comparing its performance with that of the state of art algorithms on various datasets. (C) 2014 Elsevier Inc. All rights reserved.

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An increase in the hyperpolarization-activated cyclic nucleotide-gated (HCN) channel conductance reduces input resistance, whereas the consequent increase in the inward h current depolarizes the membrane. This results in a delicate and unique conductance-current balance triggered by the expression of HCN channels. In this study, we employ experimentally constrained, morphologically realistic, conductance-based models of hippocampal neurons to explore certain aspects of this conductance-current balance. First, we found that the inclusion of an experimentally determined gradient in A-type K+ conductance, but not in M-type K+ conductance, tilts the HCN conductance-current balance heavily in favor of conductance, thereby exerting an overall restorative influence on neural excitability. Next, motivated by the well-established modulation of neuronal excitability by synaptically driven high-conductance states observed under in vivo conditions, we inserted thousands of excitatory and inhibitory synapses with different somatodendritic distributions. We measured the efficacy of HCN channels, independently and in conjunction with other channels, in altering resting membrane potential (RMP) and input resistance (R-in) when the neuron received randomized or rhythmic synaptic bombardments through variable numbers of synaptic inputs. We found that the impact of HCN channels on average RMP, R in, firing frequency, and peak-to-peak voltage response was severely weakened under high-conductance states, with the impinging synaptic drive playing a dominant role in regulating these measurements. Our results suggest that the debate on the role of HCN channels in altering excitability should encompass physiological and pathophysiological neuronal states under in vivo conditions and the spatiotemporal interactions of HCN channels with other channels.

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Iron-based layered chalcogenides are interesting because of their structural magnetic and superconducting properties. Single crystals of the parent binary chalcogenides, Fe1+y Te, and intercalated ternary chalcogenides, K0.8Fe2Se2, are grown and investigated in detail. Single crystals are grown by modified horizontal Bridgman method. Fe1+y Te demonstrates an antiferromagnetic (AFM) transition at T (N) =67 K which is identified as a magnetostructural transition. By varying the concentration of excess Fe, we have tuned T (N) over a range of temperature from 67 to 57 K. The superconducting properties of K0.8Fe2Se2 crystals are explored by magnetization measurements. A superconducting transition is observed at T (C) =31 K. The lower critical field of K0.8Fe2Se2 is estimated from field variation of magnetization measurements.

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This work reports a detailed temperature dependent Raman study on the mixed crystals of K-0.9(NH4)(0.1)H2AsO4 (KADA) from 5K to 300K in the spectral range of 60-1200cm(-1), covering tetragonal to orthorhombic structural phase transition accompanied by paraelectric to ferroelectric transition at T-c* similar to 60K. Multiple phase transitions below transition temperature (Tc* similar to 60K) are marked by the appearance of new modes, splitting of existing ones as well as anomalies in the self-energy parameters (i.e. mode frequencies and damping coefficient) of the phonon modes. Temperature independent behaviour of damping coefficient and abrupt jump in the mode frequency of some of the internal vibrations of AsO4 tetrahedra as well as external vibrations clearly signal long range ferroelectric ordering and proton ordering below T-c*. In addition, we observed that temperature dependence of many prominent phonon modes diverges significantly from their normal anharmonic behaviour below T-c* suggesting potential coupling between pseudospins and phonons. (C) 2015 Author(s).

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The issue of growth rate reduction of high speed mixing layer with convective Mach number is examined for similar and dissimilar gases using Reynolds averaged Navier-Stokes (RANS) methodology with k- turbulence model. It is observed that the growth rate predicted using RANS simulations closely matches with that predicted using model free simulations. Velocity profiles do not depend on the modelled value of Pr-t and Sc-t; while the temperature and species mass fraction distributions depend heavily on them. Although basic k- turbulence model could not capture the reduced growth rate for the mixing layer formed between similar gases, it predicts very well the reduced growth rate for the mixing layer for the dissimilar gases. It appears that density ratio changes caused by temperature changes for the dissimilar gases have profound effect on the growth rate reduction.

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The K-user multiple input multiple output (MIMO) Gaussian symmetric interference channel where each transmitter has M antennas and each receiver has N antennas is studied from a generalized degrees of freedom (GDOF) perspective. An inner bound on the GDOF is derived using a combination of techniques such as treating interference as noise, zero forcing (ZF) at the receivers, interference alignment (IA), and extending the Han-Kobayashi (HK) scheme to K users, as a function of the number of antennas and the log INR/log SNR level. Several interesting conclusions are drawn from the derived bounds. It is shown that when K > N/M + 1, a combination of the HK and IA schemes performs the best among the schemes considered. When N/M < K <= N/M + 1, the HK-scheme outperforms other schemes and is found to be GDOF optimal in many cases. In addition, when the SNR and INR are at the same level, ZF-receiving and the HK-scheme have the same GDOF performance.

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This paper derives outer bounds on the sum rate of the K-user MIMO Gaussian interference channel (GIC). Three outer bounds are derived, under different assumptions of cooperation and providing side information to receivers. The novelty in the derivation lies in the careful selection of side information, which results in the cancellation of the negative differential entropy terms containing signal components, leading to a tractable outer bound. The overall outer bound is obtained by taking the minimum of the three outer bounds. The derived bounds are simplified for the MIMO Gaussian symmetric IC to obtain outer bounds on the generalized degrees of freedom (GDOF). The relative performance of the bounds yields insight into the performance limits of multiuser MIMO GICs and the relative merits of different schemes for interference management. These insights are confirmed by establishing the optimality of the bounds in specific cases using an inner bound on the GDOF derived by the authors in a previous work. It is also shown that many of the existing results on the GDOF of the GIC can be obtained as special cases of the bounds, e. g., by setting K = 2 or the number of antennas at each user to 1.

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We report on the first dielectric investigation of high-k yttrium copper titanate thin films, which were demonstrated to be very promising for nanoelectronics applications. The dielectric constant of these films is found to vary from 100 down to 24 (at 100 kHz) as a function of deposition conditions, namely oxygen pressure and film thickness. The physical origin of such variation was investigated in the framework of universal dielectric response and Cole-Cole relations and by means of voltage dependence studies of the dielectric constant. Surface-related effects and charge hopping polarization processes, strictly dependent on the film microstructure, are suggested to be mainly responsible for the observed dielectric response. In particular, the bulky behaviour of thick films deposited at lower oxygen pressure evolves towards a more complex and electrically heterogeneous structure when either the thickness decreases down to 50 nm or the films are grown under high oxygen pressure.

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We report on the first dielectric investigation of high-k yttrium copper titanate thin films, which were demonstrated to be very promising for nanoelectronics applications. The dielectric constant of these films is found to vary from 100 down to 24 (at 100 kHz) as a function of deposition conditions, namely oxygen pressure and film thickness. The physical origin of such variation was investigated in the framework of universal dielectric response and Cole-Cole relations and by means of voltage dependence studies of the dielectric constant. Surface-related effects and charge hopping polarization processes, strictly dependent on the film microstructure, are suggested to be mainly responsible for the observed dielectric response. In particular, the bulky behaviour of thick films deposited at lower oxygen pressure evolves towards a more complex and electrically heterogeneous structure when either the thickness decreases down to 50 nm or the films are grown under high oxygen pressure.

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We develop a new dictionary learning algorithm called the l(1)-K-svp, by minimizing the l(1) distortion on the data term. The proposed formulation corresponds to maximum a posteriori estimation assuming a Laplacian prior on the coefficient matrix and additive noise, and is, in general, robust to non-Gaussian noise. The l(1) distortion is minimized by employing the iteratively reweighted least-squares algorithm. The dictionary atoms and the corresponding sparse coefficients are simultaneously estimated in the dictionary update step. Experimental results show that l(1)-K-SVD results in noise-robustness, faster convergence, and higher atom recovery rate than the method of optimal directions, K-SVD, and the robust dictionary learning algorithm (RDL), in Gaussian as well as non-Gaussian noise. For a fixed value of sparsity, number of dictionary atoms, and data dimension, l(1)-K-SVD outperforms K-SVD and RDL on small training sets. We also consider the generalized l(p), 0 < p < 1, data metric to tackle heavy-tailed/impulsive noise. In an image denoising application, l(1)-K-SVD was found to result in higher peak signal-to-noise ratio (PSNR) over K-SVD for Laplacian noise. The structural similarity index increases by 0.1 for low input PSNR, which is significant and demonstrates the efficacy of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.

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In this letter, we submit our comment on the following recently published papers by Kalidas Das: (1) ``Influence of chemical reaction and viscous dissipation on MHD mixed convection flow,'' Journal of Mechanical Science and Technology 28 (5) (2014) 1881-1885; and (2) ``Cu-water nanofluid flow and heat transfer over a shrinking sheet,'' Journal of Mechanical Science and Technology 28 (12) (2014) 5089-5094. The authors attempt to present the similarity solutions in both papers. We comment that the similarity transformations considered in Refs. 1, 2] are incorrect. Thus, the results presented by Kalidas Das lead to invalid conclusions.