998 resultados para temporal chains


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We study here different regions in phase diagrams of the spin-1/2, spin-1 and spin-3/2 one-dimensional antiferromagnetic Heisenberg systems with frustration (next-nearest-neighbor interaction J(2)) and dimerization (delta). In particular, we analyze the behaviors of the bipartite entanglement entropy and fidelity at the gapless to gapped phase transitions and across the lines separating different phases in the J(2)-delta plane. All the calculations in this work are based on numerical exact diagonalizations of finite systems.

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The potential merit of laser-induced breakdown spectroscopy (LIBS) has been demonstrated for detection and quantification of trace pollutants trapped in snow/ice samples. In this technique, a high-power pulsed laser beam from Nd:YAG Laser (Model no. Surelite III-10, Continuum, Santa Clara, CA, USA) is focused on the surface of the target to generate plasma. The characteristic emissions from laser-generated plasma are collected and recorded by a fiber-coupled LIBS 2000+ (Ocean Optics, Santa Clara, CA, USA) spectrometer. The fingerprint of the constituents present in the sample is obtained by analyzing the spectral lines by using OOI LIBS software. Reliable detection of several elements like Zn, Al, Mg, Fe, Ca, C, N, H, and O in snow/ice samples collected from different locations (elevation) of Manali and several snow samples collected from the Greater Himalayan region (from a cold lab in Manali, India) in different months has been demonstrated. The calibration curve approach has been adopted for the quantitative analysis of these elements like Zn, Al, Fe, and Mg. Our results clearly demonstrate that the level of contamination is higher in those samples that were collected in the month of January in comparison to those collected in February and March.

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Intraspecific competition is a key factor shaping space-use strategies and movement decisions in many species, yet how and when neighbors utilize shared areas while exhibiting active avoidance of one another is largely unknown. Here, we investigated temporal landscape partitioning in a population of wild baboons (Papio cynocephalus). We used global positioning system (GPS) collars to synchronously record the hourly locations of five baboon social groups for similar to 900 days, and we used behavioral, demographic, and life history data to measure factors affecting use of overlap areas. Annual home ranges of neighboring groups overlapped substantially, as predicted (baboons are considered non-territorial), but home ranges overlapped less when space use was assessed over shorter time scales. Moreover, neighboring groups were in close spatial proximity to one another on fewer days than predicted by a null model, suggesting an avoidance-based spacing pattern. At all time scales examined (monthly, biweekly, and weekly), time spent in overlap areas was greater during time periods when groups fed on evenly dispersed, low-quality foods. The percent of fertile females in social groups was negatively correlated with time spent in overlap areas only during weekly time intervals. This suggests that broad temporal changes in ecological resources are a major predictor of how intensively overlap areas are used, and groups modify these ecologically driven spacing patterns at short time scales based on female reproductive status. Together, these findings offer insight into the economics of territoriality by highlighting the dynamics of spacing patterns at differing time scales.

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We review the spatio-temporal dynamical features of the Ananthakrishna model for the Portevin-Le Chatelier effect, a kind of plastic instability observed under constant strain rate deformation conditions. We then establish a qualitative correspondence between the spatio-temporal structures that evolve continuously in the instability domain and the nature of the irregularity of the scalar stress signal. Rest of the study is on quantifying the dynamical information contained in the stress signals about the spatio-temporal dynamics of the model. We show that at low applied strain rates, there is a one-to-one correspondence with the randomly nucleated isolated bursts of mobile dislocation density and the stress drops. We then show that the model equations are spatio-temporally chaotic by demonstrating the number of positive Lyapunov exponents and Lyapunov dimension scale with the system size at low and high strain rates. Using a modified algorithm for calculating correlation dimension density, we show that the stress-strain signals at low applied strain rates corresponding to spatially uncorrelated dislocation bands exhibit features of low dimensional chaos. This is made quantitative by demonstrating that the model equations can be approximately reduced to space independent model equations for the average dislocation densities, which is known to be low-dimensionally chaotic. However, the scaling regime for the correlation dimension shrinks with increasing applied strain rate due to increasing propensity for propagation of the dislocation bands. The stress signals in the partially propagating to fully propagating bands turn to have features of extensive chaos.

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The confinement of a polymer to volumes whose characteristic linear dimensions are comparable to or smaller than its bulk radius of gyration R-G,R-bulk can produce significant changes in its static and dynamic properties, with important implications for the understanding of single-molecule processes in biology and chemistry. In this paper, we present calculations of the effects of a narrow rectangular slit of thickness d on the scaling behavior of the diffusivity D and relaxation time tau(r) of a Gaussian chain of polymerization index N and persistence length l(0). The calculations are based on the Rouse-Zimm model of chain dynamics, with the pre-averaged hydrodynamic interaction being obtained from the solutions to Stokes equations for an incompressible fluid in a parallel plate geometry in the limit of small d. They go beyond de Gennes' purely phenomenological analysis of the problem based on blobs, which has so far been the only analytical route to the determination of chain scaling behavior for this particular geometry. The present model predicts that D similar to dN(-1) ln(N/d(2)) and tau(r) similar to N(2)d(-1) ln(N/d(2))(-1) in the regime of moderate confinement, where l(0) << d < R-G,R-bulk. The corresponding results for the blob model have exactly the same power law behavior, but contain no logarithmic corrections; the difference suggests that segments within a blob may actually be partially draining and not non-draining as generally assumed.

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The confinement of a polymer to volumes whose characteristic linear dimensions are comparable to or smaller than its bulk radius of gyration R-G,R-bulk can produce significant changes in its static and dynamic properties, with important implications for the understanding of single-molecule processes in biology and chemistry. In this paper, we present calculations of the effects of a narrow rectangular slit of thickness d on the scaling behavior of the diffusivity D and relaxation time tau(r) of a Gaussian chain of polymerization index N and persistence length l(0). The calculations are based on the Rouse-Zimm model of chain dynamics, with the pre-averaged hydrodynamic interaction being obtained from the solutions to Stokes equations for an incompressible fluid in a parallel plate geometry in the limit of small d. They go beyond de Gennes' purely phenomenological analysis of the problem based on blobs, which has so far been the only analytical route to the determination of chain scaling behavior for this particular geometry. The present model predicts that D similar to dN(-1) ln(N/d(2)) and tau(r) similar to N(2)d(-1) ln(N/d(2))(-1) in the regime of moderate confinement, where l(0) << d < R-G,R-bulk. The corresponding results for the blob model have exactly the same power law behavior, but contain no logarithmic corrections; the difference suggests that segments within a blob may actually be partially draining and not non-draining as generally assumed. (C) 2013 AIP Publishing LLC.

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Synfire waves are propagating spike packets in synfire chains, which are feedforward chains embedded in random networks. Although synfire waves have proved to be effective quantification for network activity with clear relations to network structure, their utilities are largely limited to feedforward networks with low background activity. To overcome these shortcomings, we describe a novel generalisation of synfire waves, and define `synconset wave' as a cascade of first spikes within a synchronisation event. Synconset waves would occur in `synconset chains', which are feedforward chains embedded in possibly heavily recurrent networks with heavy background activity. We probed the utility of synconset waves using simulation of single compartment neuron network models with biophysically realistic conductances, and demonstrated that the spread of synconset waves directly follows from the network connectivity matrix and is modulated by top-down inputs and the resultant oscillations. Such synconset profiles lend intuitive insights into network organisation in terms of connection probabilities between various network regions rather than an adjacency matrix. To test this intuition, we develop a Bayesian likelihood function that quantifies the probability that an observed synfire wave was caused by a given network. Further, we demonstrate it's utility in the inverse problem of identifying the network that caused a given synfire wave. This method was effective even in highly subsampled networks where only a small subset of neurons were accessible, thus showing it's utility in experimental estimation of connectomes in real neuronal-networks. Together, we propose synconset chains/waves as an effective framework for understanding the impact of network structure on function, and as a step towards developing physiology-driven network identification methods. Finally, as synconset chains extend the utilities of synfire chains to arbitrary networks, we suggest utilities of our framework to several aspects of network physiology including cell assemblies, population codes, and oscillatory synchrony.

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We address the problem of temporal envelope modeling for transient audio signals. We propose the Gamma distribution function (GDF) as a suitable candidate for modeling the envelope keeping in view some of its interesting properties such as asymmetry, causality, near-optimal time-bandwidth product, controllability of rise and decay, etc. The problem of finding the parameters of the GDF becomes a nonlinear regression problem. We overcome the hurdle by using a logarithmic envelope fit, which reduces the problem to one of linear regression. The logarithmic transformation also has the feature of dynamic range compression. Since temporal envelopes of audio signals are not uniformly distributed, in order to compute the amplitude, we investigate the importance of various loss functions for regression. Based on synthesized data experiments, wherein we have a ground truth, and real-world signals, we observe that the least-squares technique gives reasonably accurate amplitude estimates compared with other loss functions.

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We propose a novel space-time descriptor for region-based tracking which is very concise and efficient. The regions represented by covariance matrices within a temporal fragment, are used to estimate this space-time descriptor which we call the Eigenprofiles(EP). EP so obtained is used in estimating the Covariance Matrix of features over spatio-temporal fragments. The Second Order Statistics of spatio-temporal fragments form our target model which can be adapted for variations across the video. The model being concise also allows the use of multiple spatially overlapping fragments to represent the target. We demonstrate good tracking results on very challenging datasets, shot under insufficient illumination conditions.

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Single-molecule force spectroscopy has proven to be an efficient tool for the quantitative characterization of flexible foldamers on the single-molecule level in this study. The extent of folding has been estimated quantitatively for the first time to the best of our knowledge, which is crucial for a better understanding of the ``folding-process'' on single-molecule level. Therefore, this study may provide a guidance to regulate folding for realizing rational control over the functions of bulk materials.

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Land use (LU) land cover (LC) information at a temporal scale illustrates the physical coverage of the Earth's terrestrial surface according to its use and provides the intricate information for effective planning and management activities. LULC changes are stated as local and location specific, collectively they act as drivers of global environmental changes. Understanding and predicting the impact of LULC change processes requires long term historical restorations and projecting into the future of land cover changes at regional to global scales. The present study aims at quantifying spatio temporal landscape dynamics along the gradient of varying terrains presented in the landscape by multi-data approach (MDA). MDA incorporates multi temporal satellite imagery with demographic data and other additional relevant data sets. The gradient covers three different types of topographic features, planes; hilly terrain and coastal region to account the significant role of elevation in land cover change. The seasonality is another aspect to be considered in the vegetation dominated landscapes; variations are accounted using multi seasonal data. Spatial patterns of the various patches are identified and analysed using landscape metrics to understand the forest fragmentation. The prediction of likely changes in 2020 through scenario analysis has been done to account for the changes, considering the present growth rates and due to the proposed developmental projects. This work summarizes recent estimates on changes in cropland, agricultural intensification, deforestation, pasture expansion, and urbanization as the causal factors for LULC change.

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Unconstrained gamma(4) amino acid residues derived by homologation of proteinogenic amino acids facilitate helical folding in hybrid (alpha gamma)(n) sequences. The C-12 helical conformation for the decapeptide, Boc-Leu-gamma(4)(R)Val](5)-OMe, is established in crystals by X-ray diffraction. A regular C-12 helix is demonstrated by NMR studies of the 18 residue peptide, Boc-Leu-gamma(4)(AR)Val](9)-OMe, and a designed 16 residue (alpha gamma)(n) peptide, incorporating variable side chains. Unconstrained (alpha gamma)(n) peptides show an unexpectedly high propensity for helical folding in long polypeptide sequences.

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In the self-organized public key management approaches, public key verification is achieved through verification routes constituted by the transitive trust relationships among the network principals. Most of the existing approaches do not distinguish among different available verification routes. Moreover, to ensure stronger security, it is important to choose an appropriate metric to evaluate the strength of a route. Besides, all of the existing self-organized approaches use certificate-chains for achieving authentication, which are highly resource consuming. In this paper, we present a self-organized certificate-less on-demand public key management (CLPKM) protocol, which aims at providing the strongest verification routes for authentication purposes. It restricts the compromise probability for a verification route by restricting its length. Besides, we evaluate the strength of a verification route using its end-to-end trust value. The other important aspect of the protocol is that it uses a MAC function instead of RSA certificates to perform public key verifications. By doing this, the protocol saves considerable computation power, bandwidth and storage space. We have used an extended strand space model to analyze the correctness of the protocol. The analytical, simulation, and the testbed implementation results confirm the effectiveness of the proposed protocol. (c) 2014 Elsevier B.V. All rights reserved.

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Long-term surveys of entire communities of species are needed to measure fluctuations in natural populations and elucidate the mechanisms driving population dynamics and community assembly. We analysed changes in abundance of over 4000 tree species in 12 forests across the world over periods of 6-28years. Abundance fluctuations in all forests are large and consistent with population dynamics models in which temporal environmental variance plays a central role. At some sites we identify clear environmental drivers, such as fire and drought, that could underlie these patterns, but at other sites there is a need for further research to identify drivers. In addition, cross-site comparisons showed that abundance fluctuations were smaller at species-rich sites, consistent with the idea that stable environmental conditions promote higher diversity. Much community ecology theory emphasises demographic variance and niche stabilisation; we encourage the development of theory in which temporal environmental variance plays a central role.