181 resultados para Circle K Club


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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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Using hydrodynamic simulations, we study the mass-loss due to supernova-driven outflows from Milky Way type disc galaxies, paying particular attention to the effect of the extended hot halo gas. We find that the total mass-loss at inner radii scales roughly linearly with total mass of stars formed, and that the mass loading factor at the virial radius can be several times its value at inner radii because of the swept up hot halo gas. The temperature distribution of the outflowing material in the inner region (similar to 10 kpc) is bimodal in nature, peaking at 10(5) K and 10(6.5) K, responsible for optical and X-ray emission, respectively. The contribution of cold/warm gas with temperature <= 10(5.5) K to the outflow rate within 10 kpc is approximate to 0.3-0.5. The warm mass loading factor, eta(3e5) (T <= 3 x 10(5) K) is related to the mass loading factor at the virial radius (eta(v)) as eta(v) approximate to 25 eta(3e5) (SFR/M-circle dot yr(-1))(-0.15) for a baryon fraction of 0.1 and a starburst period of 50 Myr. We also discuss the effect of multiple bursts that are separated by both short and long periods. The outflow speed at the virial radius is close to the sound speed in the hot halo, less than or similar to 200 km s(-1). We identify two `sequences' of outflowing cold gas at small scales: a fast (approximate to 500 km s(-1)) sequence, driven by the unshocked free-wind; and a slow sequence (approximate to +/- 100 km s(-1)) at the conical interface of the superwind and the hot halo.

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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 boxicity (cubicity) of a graph G is the minimum natural number k such that G can be represented as an intersection graph of axis-parallel rectangular boxes (axis-parallel unit cubes) in R-k. In this article, we give estimates on the boxicity and the cubicity of Cartesian, strong and direct products of graphs in terms of invariants of the component graphs. In particular, we study the growth, as a function of d, of the boxicity and the cubicity of the dth power of a graph with respect to the three products. Among others, we show a surprising result that the boxicity and the cubicity of the dth Cartesian power of any given finite graph is, respectively, in O(log d/ log log d) and circle dot(d/ log d). On the other hand, we show that there cannot exist any sublinear bound on the growth of the boxicity of powers of a general graph with respect to strong and direct products. (C) 2015 Elsevier Ltd. All rights reserved.

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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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Using high-resolution 3D and 2D (axisymmetric) hydrodynamic simulations in spherical geometry, we study the evolution of cool cluster cores heated by feedback-driven bipolar active galactic nuclei (AGNs) jets. Condensation of cold gas, and the consequent enhanced accretion, is required for AGN feedback to balance radiative cooling with reasonable efficiencies, and to match the observed cool core properties. A feedback efficiency (mechanical luminosity approximate to epsilon(M) over dot(acc)c(2); where (M) over dot(acc). is the mass accretion rate at 1 kpc) as small as 6 x 10(-5) is sufficient to reduce the cooling/accretion rate by similar to 10 compared to a pure cooling flow in clusters (with M-200 less than or similar to 7 x 10(14) M-circle dot). This value is much smaller compared to the ones considered earlier, and is consistent with the jet efficiency and the fact that only a small fraction of gas at 1 kpc is accreted onto the supermassive black hole (SMBH). The feedback efficiency in earlier works was so high that the cluster core reached equilibrium in a hot state without much precipitation, unlike what is observed in cool-core clusters. We find hysteresis cycles in all our simulations with cold mode feedback: condensation of cold gas when the ratio of the cooling-time to the free-fall time (t(cool)/t(ff)) is less than or similar to 10 leads to a sudden enhancement in the accretion rate; a large accretion rate causes strong jets and overheating of the hot intracluster medium such that t(cool)/t(ff) > 10; further condensation of cold gas is suppressed and the accretion rate falls, leading to slow cooling of the core and condensation of cold gas, restarting the cycle. Therefore, there is a spread in core properties, such as the jet power, accretion rate, for the same value of core entropy t(cool)/t(ff). A smaller number of cycles is observed for higher efficiencies and for lower mass halos because the core is overheated to a longer cooling time. The 3D simulations show the formation of a few-kpc scale, rotationally supported, massive (similar to 10(11) M-circle dot) cold gas torus. Since the torus gas is not accreted onto the SMBH, it is largely decoupled from the feedback cycle. The radially dominant cold gas (T < 5 x 10(4) K; vertical bar v(r)vertical bar >vertical bar v(phi vertical bar)) consists of fast cold gas uplifted by AGN jets and freely infalling cold gas condensing out of the core. The radially dominant cold gas extends out to 25 kpc for the fiducial run (halo mass 7 x 10(14) M-circle dot and feedback efficiency 6 x 10(-5)), with the average mass inflow rate dominating the outflow rate by a factor of approximate to 2. We compare our simulation results with recent observations.

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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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This paper proposes a design methodology to stabilize collective circular motion of a group of N-identical agents moving at unit speed around individual circles of different radii and different centers. The collective circular motion studied in this paper is characterized by the clockwise rotation of all agents around a common circle of desired radius as well as center, which is fixed. Our interest is to achieve those collective circular motions in which the phases of the agents are arranged either in synchronized, in balanced or in splay formation. In synchronized formation, the agents and their centroid move in a common direction while in balanced formation, the movement of the agents ensures a fixed location of the centroid. The splay state is a special case of balanced formation, in which the phases are separated by multiples of 2 pi/N. We derive the feedback controls and prove the asymptotic stability of the desired collective circular motion by using Lyapunov theory and the LaSalle's Invariance principle.

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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.