Weighted-Sampling Audio Adversarial Example Attack

Recent studies have highlighted audio adversarial examples as a ubiquitous threat to state-of-the-art automatic speech recognition systems. Thorough studies on how to effectively generate adversarial examples are essential to prevent potential attacks. Despite many research on this, the efficiency and the robustness of existing works are not yet satisfactory. In this paper, we propose~\textit{weighted-sampling audio adversarial examples}, focusing on the numbers and the weights of distortion to reinforce the attack. Further, we apply a denoising method in the loss function to make the adversarial attack more imperceptible. Experiments show that our method is the first in the field to generate audio adversarial examples with low noise and high audio robustness at the minute time-consuming level.Comment: https://aaai.org/Papers/AAAI/2020GB/AAAI-LiuXL.9260.pd

The protective role of pregnane X receptor in lipopolysaccharide/D-galactosamine-induced acute liver injury.

The pregnane X receptor (PXR) is a nuclear receptor transcription factor regulating drug-metabolizing enzymes and transporters that facilitate xenobiotic and endobiotic detoxification. Recent studies show that PXR is important in abrogating intestinal tissue damage. This study examines the role of PXR in lipopolysaccharide (LPS)/D-galactosamine (GalN)-induced acute liver injury using wild-type and PXR-null mice. LPS/GalN-treated PXR-null mice had greater increases of alanine transaminase (ALT), hepatocyte apoptosis, necrosis, and hemorrhagic liver injury than wild-type mice. LPS/GalN-mediated phosphorylation of JNK1/2 and ERK1/2 was differentially regulated in wild-type and PXR-null mice. Importantly, LPS/GalN-induced hepatic Stat3 survival signaling was impaired and early activation of Jak2 was delayed in PXR-null mice. Expression levels of pro-survival proteins Bcl-xL and heme oxygenase-1 (HO-1), which are downstream of Stat3, were substantially lower in PXR-null than wild-type mouse livers after LPS/GalN treatment. Autophagy is also involved in LPS/GalN-induced liver injury. Lack of PXR resulted in a significant reduction of LC3B-I, -II as well as Beclin-1 protein levels after LPS/GalN treatment. In addition, PXR is implicated in hepatocytes homeostasis. Taken together, PXR is a critical hepatoprotective factor. Increases of LPS/GalN-induced hepatocyte apoptosis and liver injury in PXR-null mice are due to deregulated mitogen-activated protein (MAP) kinase activation as well as delayed Jak2/Stat3 activation, which lead to a compromise in defense mechanisms that involve Bcl-xL-, HO-1, and autophagy-mediated pathways

Edge Excitations and Non-Abelian Statistics in the Moore-Read State: A Numerical Study in the Presence of Coulomb Interaction and Edge Confinement

We study the ground state and low-energy excitations of fractional quantum Hall systems on a disk at filling fraction $\nu = 5/2$, with Coulomb interaction and background confining potential. We find the Moore-Read ground state is stable within a finite but narrow window in parameter space. The corresponding low-energy excitations contain a fermionic branch and a bosonic branch, with widely different velocities. A short-range repulsive potential can stabilize a charge $+e/4$ quasihole at the center, leading to a different edge excitation spectrum due to the change of boundary conditions for Majorana fermions, clearly indicating the non-Abelian nature of the quasihole.Comment: 4 pages, 3 figures. New version shortened for PRL. Corrected typo

Intelligent optical performance monitor using multi-task learning based artificial neural network

An intelligent optical performance monitor using multi-task learning based artificial neural network (MTL-ANN) is designed for simultaneous OSNR monitoring and modulation format identification (MFI). Signals' amplitude histograms (AHs) after constant module algorithm are selected as the input features for MTL-ANN. The experimental results of 20-Gbaud NRZ-OOK, PAM4 and PAM8 signals demonstrate that MTL-ANN could achieve OSNR monitoring and MFI simultaneously with higher accuracy and stability compared with single-task learning based ANNs (STL-ANNs). The results show an MFI accuracy of 100% and OSNR monitoring root-mean-square error of 0.63 dB for the three modulation formats under consideration. Furthermore, the number of neuron needed for the single MTL-ANN is almost the half of STL-ANN, which enables reduced-complexity optical performance monitoring devices for real-time performance monitoring