Transportation dynamics on networks of mobile agents

Most existing works on transportation dynamics focus on networks of a fixed structure, but networks whose nodes are mobile have become widespread, such as cell-phone networks. We introduce a model to explore the basic physics of transportation on mobile networks. Of particular interest are the dependence of the throughput on the speed of agent movement and communication range. Our computations reveal a hierarchical dependence for the former while, for the latter, we find an algebraic power law between the throughput and the communication range with an exponent determined by the speed. We develop a physical theory based on the Fokker-Planck equation to explain these phenomena. Our findings provide insights into complex transportation dynamics arising commonly in natural and engineering systems

FPGA Deployment of LFADS for Real-time Neuroscience Experiments

Large-scale recordings of neural activity are providing new opportunities to study neural population dynamics. A powerful method for analyzing such high-dimensional measurements is to deploy an algorithm to learn the low-dimensional latent dynamics. LFADS (Latent Factor Analysis via Dynamical Systems) is a deep learning method for inferring latent dynamics from high-dimensional neural spiking data recorded simultaneously in single trials. This method has shown a remarkable performance in modeling complex brain signals with an average inference latency in milliseconds. As our capacity of simultaneously recording many neurons is increasing exponentially, it is becoming crucial to build capacity for deploying low-latency inference of the computing algorithms. To improve the real-time processing ability of LFADS, we introduce an efficient implementation of the LFADS models onto Field Programmable Gate Arrays (FPGA). Our implementation shows an inference latency of 41.97 $\mu$s for processing the data in a single trial on a Xilinx U55C.Comment: 6 pages, 8 figure

The Quark/Antiquark Asymmetry of the Nucleon Sea

Although the distributions of sea quarks and antiquarks generated by leading-twist QCD evolution through gluon splitting $g \rightarrow \bar q q$ are necessarily CP symmetric, the distributions of nonvalence quarks and antiquarks which are intrinsic to the nucleon's bound state wavefunction need not be identical. In this paper we investigate the sea quark/antiquark asymmetries in the nucleon wavefunction which are generated by a light-cone model of energetically-favored meson-baryon fluctuations. The model predicts striking quark/antiquark asymmetries in the momentum and helicity distributions for the down and strange contributions to the proton structure function: the intrinsic $d$ and $s$ quarks in the proton sea are predicted to be negatively polarized, whereas the intrinsic $\bar d$ and $\bar s$ antiquarks give zero contributions to the proton spin. Such a picture is supported by experimental phenomena related to the proton spin problem and the violation of the Ellis-Jaffe sum rule. The light-cone meson-baryon fluctuation model also suggests a structured momentum distribution asymmetry for strange quarks and antiquarks which could be relevant to an outstanding conflict between two different determinations of the strange quark sea in the nucleon. The model predicts an excess of intrinsic $d \bar d$ pairs over $u \bar u$ pairs, as supported by the Gottfried sum rule violation. We also predict that the intrinsic charm and anticharm helicity and momentum distributions are not identical.Comment: LaTex 18 pages, 4 figures. To obtain a copy, send e-mail to [email protected]

Flavor and Spin Structure of Octet Baryons at Large x

The quark flavor and spin distributions in octet baryons are calculated both in the SU(6) quark spectator diquark model and in a perturbative QCD (pQCD) based model. It is shown that the $\Lambda$ has the most significant difference in flavor structure at large $x$ between the two models, though the flavor and spin structure of other baryons can also provide tests of different models. The Drell-Yan process for $\Sigma^{\pm}$ beams on isoscalar targets can be used to test different predictions concerning the valence quark flavor structure of the $\Sigma^{\pm}$.Comment: 24 pages, 11 figures, version published in Nucl.Phys.B 574 (2000) 33

In vitro activities of antimicrobial combinations against planktonic and biofilm forms of Stenotrophomonas maltophilia

ObjectivesTo investigate the in vitro activity of antibiotic combinations against Stenotrophomonas maltophilia isolates and their associated biofilms.MethodsThirty-two S. maltophilia clinical isolates with at least twenty-five different pulsotypes were tested. The antibacterial activity of various antibiotic combinations against seven randomly selected planktonic and biofilm-embedded S. maltophilia strains with strong biofilm formation was assessed using broth methods. Extraction of bacterial genomic DNA and PCR detection of antibiotic resistance and biofilm-related genes were also performed.ResultsThe susceptibility rates of levofloxacin (LVX), fosfomycin (FOS), tigecycline (TGC) and sulfamethoxazole-trimethoprim (SXT) against 32 S. maltophilia isolates were 56.3, 71.9, 71.9 and 90.6%, respectively. Twenty-eight isolates were detected with strong biofilm formation. Antibiotic combinations, including aztreonam-clavulanic (ATM-CLA) with LVX, ceftazidime-avibactam (CZA) with LVX and SXT with TGC, exhibited potent inhibitory activity against these isolates with strong biofilm formation. The antibiotic resistance phenotype might not be fully caused by the common antibiotic-resistance or biofilm-formation gene.ConclusionS. maltophilia remained resistant to most antibiotics, including LVX and β-lactam/β-lactamases; however, TGC, FOS and SXT still exhibited potent activity. Although all tested S. maltophilia isolates exhibited moderate-to-strong biofilm formation, combination therapies, especially ATM-CLA with LVX, CZA with LVX and SXT with TGC, exhibited a higher inhibitory activity for these isolates