Electromagnetic Form Factors of Nucleons in a Light-cone Diquark Model

We investigate the electromagnetic form factors of nucleons within a simple relativistic quark spectator-diquark model using the light-cone formalism. Melosh rotations are applied to both quark and vector diquark. It is shown that the difference between vector and scalar spectator diquarks reproduces the right electric form factor of neutrons, and both the form factors $G_E(Q^2)$ and $G_M(Q^2)$ of the proton and neutron agree with experimental data well up to $Q^2=2 ~\rm{GeV}^2$ in this simple model.Comment: 16 pages, Revtex4, minor changes, to appear in Phys. Rev.

Studies on Effects of Aircraft Noise on Behavior of Rats, Their Plasma Norepinephrine Levels and Cell Morphology of the Temporal Lobe

To study the physiological effects of airport noise exposure on organisms, Sprague-Dawley (SD) rats were exposed in soundproof chambers to previously recorded aircraft-related noise for 65 d. As a comparison, unexposed control rats were also used. According to aircraft flight schedules, aircraft noise was replayed and its weighted equivalent continuous perceived noise levels (LWECPN) were adjusted to 75 and 80 dB for the two experimental groups. Rat behaviors were observed through an open field test and the concentrations of plasma norepinephrine (NE) were tested by high-performance liquid chromatography-fluorimetric detection (HPLC-FLD). The morphologies of neurons and synapses in the temporal lobe were also examined by transmission electron microscopy (TEM). Our results indicated that SD rats of experiment group exposed to airport noise of 80 dB had significantly lower line crossing number (P < 0.05) and significantly longer center area duration (P < 0.05) compared with that of control group. After 29 d of airport noise exposure, the concentrations of plasma NE of experiment group were significantly higher than that of control group (P < 0.05). It was determined that the neuron and synapsis of the temporal lobe of experiment group exposed to 80 dB for 65 d showed signs of damage. In conclusion, exposing rats to long-term aircraft noise affects their behaviors, plasma NE levels, and cell morphology of the temporal lobe. Of course, the differences in the hearing sensitivity to different sound frequencies and circadian rhythms between rats and humans can bring variances in physiological effects under the same noise exposure. Therefore, if this study results are applied into humans, it should be further confirmed

Intervalley Scattering and Localization Behaviors of Spin-Valley Coupled Dirac Fermions

We study the quantum diffusive transport of multivalley massive Dirac cones, where time-reversal symmetry requires opposite spin orientations in inequivalent valleys. We show that the intervalley scattering and intravalley scattering can be distinguished from the quantum conductivity that corrects the semiclassical Drude conductivity, due to their distinct symmetries and localization trends. In immediate practice, it allows transport measurements to estimate the intervalley scattering rate in hole-doped monolayers of group-VI transition metal dichalcogenides (e.g., molybdenum dichalcogenides and tungsten dichalcogenides), an ideal class of materials for valleytronics applications. The results can be generalized to a large class of multivalley massive Dirac systems with spin-valley coupling and time-reversal symmetry.Comment: 5 pages+4 pages of supplemental materials, 4 figure

Learning-Based Distributed Detection-Estimation in Sensor Networks with Unknown Sensor Defects

We consider the problem of distributed estimation of an unknown deterministic scalar parameter (the target signal) in a wireless sensor network (WSN), where each sensor receives a single snapshot of the field. We assume that the observation at each node randomly falls into one of two modes: a valid or an invalid observation mode. Specifically, mode one corresponds to the desired signal plus noise observation mode (\emph{valid}), and mode two corresponds to the pure noise mode (\emph{invalid}) due to node defect or damage. With no prior information on such local sensing modes, we introduce a learning-based distributed procedure, called the mixed detection-estimation (MDE) algorithm, based on iterative closed-loop interactions between mode learning (detection) and target estimation. The online learning step re-assesses the validity of the local observations at each iteration, thus refining the ongoing estimation update process. The convergence of the MDE algorithm is established analytically. Asymptotic analysis shows that, in the high signal-to-noise ratio (SNR) regime, the MDE estimation error converges to that of an ideal (centralized) estimator with perfect information about the node sensing modes. This is in contrast to the estimation performance of a naive average consensus based distributed estimator (without mode learning), whose estimation error blows up with an increasing SNR.Comment: 15 pages, 2 figures, submitted to TS