Navigation in a small world with local information

It is commonly known that there exist short paths between vertices in a network showing the small-world effect. Yet vertices, for example, the individuals living in society, usually are not able to find the shortest paths, due to the very serious limit of information. To theoretically study this issue, here the navigation process of launching messages toward designated targets is investigated on a variant of the one-dimensional small-world network (SWN). In the network structure considered, the probability of a shortcut falling between a pair of nodes is proportional to $r^{-\alpha}$, where $r$ is the lattice distance between the nodes. When $\alpha =0$, it reduces to the SWN model with random shortcuts. The system shows the dynamic small-world (SW) effect, which is different from the well-studied static SW effect. We study the effective network diameter, the path length as a function of the lattice distance, and the dynamics. They are controlled by multiple parameters, and we use data collapse to show that the parameters are correlated. The central finding is that, in the one-dimensional network studied, the dynamic SW effect exists for $0\leq \alpha \leq 2$. For each given value of $\alpha$ in this region, the point that the dynamic SW effect arises is $ML^{\prime}\sim 1$, where $M$ is the number of useful shortcuts and $L^{\prime}$ is the average reduced (effective) length of them.Comment: 10 pages, 5 figures, accepted for publication in Physical Review

Anomalous particle-number fluctuations in a three-dimensional interacting Bose-Einstein condensate

The particle-number fluctuations originated from collective excitations are investigated for a three-dimensional, repulsively interacting Bose-Einstein condensate (BEC) confined in a harmonic trap. The contribution due to the quantum depletion of the condensate is calculated and the explicit expression of the coefficient in the formulas denoting the particle-number fluctuations is given. The results show that the particle-number fluctuations of the condensate follow the law $\sim N^{22/15}$ and the fluctuations vanish when temperature approaches to the BEC critical temperature.Comment: RevTex, 4 page

Combination strategy based on relative performance monitoring for multi-stream reverberant speech recognition

A multi-stream framework with deep neural network (DNN) classifiers is applied to improve automatic speech recognition (ASR) in environments with different reverberation characteristics. We propose a room parameter estimation model to establish a reliable combination strategy which performs on either DNN posterior probabilities or word lattices. The model is implemented by training a multilayer perceptron incorporating auditory-inspired features in order to distinguish between and generalize to various reverberant conditions, and the model output is shown to be highly correlated to ASR performances between multiple streams, i.e., relative performance monitoring, in contrast to conventional mean temporal distance based performance monitoring for a single stream. Compared to traditional multi-condition training, average relative word error rate improvements of 7.7% and 9.4% have been achieved by the proposed combination strategies performing on posteriors and lattices, respectively, when the multi-stream ASR is tested in known and unknown simulated reverberant environments as well as realistically recorded conditions taken from REVERB Challenge evaluation set

Entropy, Dynamics and Instantaneous Normal Modes in a Random Energy Model

It is shown that the fraction f of imaginary frequency instantaneous normal modes (INM) may be defined and calculated in a random energy model(REM) of liquids. The configurational entropy S and the averaged hopping rate among the states R are also obtained and related to f, with the results R~f and S=a+b*ln(f). The proportionality between R and f is the basis of existing INM theories of diffusion, so the REM further confirms their validity. A link to S opens new avenues for introducing INM into dynamical theories. Liquid 'states' are usually defined by assigning a configuration to the minimum to which it will drain, but the REM naturally treats saddle-barriers on the same footing as minima, which may be a better mapping of the continuum of configurations to discrete states. Requirements of a detailed REM description of liquids are discussed

Bicarbonate Resensitization of Methicillin-Resistant Staphylococcus aureus to β-Lactam Antibiotics.

Endovascular infections caused by methicillin-resistant Staphylococcus aureus (MRSA) are a major health care concern, especially infective endocarditis (IE). Standard antimicrobial susceptibility testing (AST) defines most MRSA strains as "resistant" to β-lactams, often leading to the use of costly and/or toxic treatment regimens. In this investigation, five prototype MRSA strains, representing the range of genotypes in current clinical circulation, were studied. We identified two distinct MRSA phenotypes upon AST using standard media, with or without sodium bicarbonate (NaHCO3) supplementation: one highly susceptible to the antistaphylococcal β-lactams oxacillin and cefazolin (NaHCO3 responsive) and one resistant to such agents (NaHCO3 nonresponsive). These phenotypes accurately predicted clearance profiles of MRSA from target tissues in experimental MRSA IE treated with each β-lactam. Mechanistically, NaHCO3 reduced the expression of two key genes involved in the MRSA phenotype, mecA and sarA, leading to decreased production of penicillin-binding protein 2a (that mediates methicillin resistance), in NaHCO3-responsive (but not in NaHCO3-nonresponsive) strains. Moreover, both cefazolin and oxacillin synergistically killed NaHCO3-responsive strains in the presence of the host defense antimicrobial peptide (LL-37) in NaHCO3-supplemented media. These findings suggest that AST of MRSA strains in NaHCO3-containing media may potentially identify infections caused by NaHCO3-responsive strains that are appropriate for β-lactam therapy

Deep Attributes Driven Multi-Camera Person Re-identification

The visual appearance of a person is easily affected by many factors like pose variations, viewpoint changes and camera parameter differences. This makes person Re-Identification (ReID) among multiple cameras a very challenging task. This work is motivated to learn mid-level human attributes which are robust to such visual appearance variations. And we propose a semi-supervised attribute learning framework which progressively boosts the accuracy of attributes only using a limited number of labeled data. Specifically, this framework involves a three-stage training. A deep Convolutional Neural Network (dCNN) is first trained on an independent dataset labeled with attributes. Then it is fine-tuned on another dataset only labeled with person IDs using our defined triplet loss. Finally, the updated dCNN predicts attribute labels for the target dataset, which is combined with the independent dataset for the final round of fine-tuning. The predicted attributes, namely \emph{deep attributes} exhibit superior generalization ability across different datasets. By directly using the deep attributes with simple Cosine distance, we have obtained surprisingly good accuracy on four person ReID datasets. Experiments also show that a simple metric learning modular further boosts our method, making it significantly outperform many recent works.Comment: Person Re-identification; 17 pages; 5 figures; In IEEE ECCV 201

Lattice Boltzmann Approach to High-Speed Compressible Flows

We present an improved lattice Boltzmann model for high-speed compressible flows. The model is composed of a discrete-velocity model by Kataoka and Tsutahara [Phys. Rev. E \textbf{69}, 056702 (2004)] and an appropriate finite-difference scheme combined with an additional dissipation term. With the dissipation term parameters in the model can be flexibly chosen so that the von Neumann stability condition is satisfied. The influence of the various model parameters on the numerical stability is analyzed and some reference values of parameter are suggested. The new scheme works for both subsonic and supersonic flows with a Mach number up to 30 (or higher), which is validated by well-known benchmark tests. Simulations on Riemann problems with very high ratios ($1000:1$) of pressure and density also show good accuracy and stability. Successful recovering of regular and double Mach shock reflections shows the potential application of the lattice Boltzmann model to fluid systems where non-equilibrium processes are intrinsic. The new scheme for stability can be easily extended to other lattice Boltzmann models.Comment: Figs.11 and 12 in JPEG format. Int. J. Mod. Phys. C (to appear

Evidence for a Photospheric Component in the Prompt Emission of the Short GRB120323A and its Effects on the GRB Hardness-Luminosity Relation

The short GRB 120323A had the highest flux ever detected with the Fermi/GBM. Here we study its remarkable spectral properties and their evolution using two spectral models: (i) a single emission component scenario, where the spectrum is modeled by the empirical Band function, and (ii) a two component scenario, where thermal (Planck-like) emission is observed simultaneously with a non-thermal component (a Band function). We find that the latter model fits the integrated burst spectrum significantly better than the former, and that their respective spectral parameters are dramatically different: when fit with a Band function only, the Epeak of the event is unusually soft for a short GRB, while adding a thermal component leads to more typical short GRB values. Our time-resolved spectral analysis produces similar results. We argue here that the two-component model is the preferred interpretation for GRB 120323A, based on: (i) the values and evolution of the Band function parameters of the two component scenario, which are more typical for a short GRB, and (ii) the appearance in the data of a significant hardness-intensity correlation, commonly found in GRBs, when we employee two-component model fits; the correlation is non-existent in the Band-only fits. GRB 110721A, a long burst with an intense photospheric emission, exhibits the exact same behavior. We conclude that GRB 120323A has a strong photospheric emission contribution, first time observed in a short GRB. Magnetic dissipation models are difficult to reconcile with these results, which instead favor photospheric thermal emission and fast cooling synchrotron radiation from internal shocks. Finally, we derive a possibly universal hardness-luminosity relation in the source frame using a larger set of GRBs L,i=(1.59+/-0.84).10^50 (Epeak,i)^(1.33+/-0.07) erg/s), which could be used as a possible redshift estimator for cosmology.Comment: 27 pages, 13 figures, Accepted by ApJ (April, 7th 2013