412 research outputs found
Disentangled Text Representation Learning with Information-Theoretic Perspective for Adversarial Robustness
Adversarial vulnerability remains a major obstacle to constructing reliable
NLP systems. When imperceptible perturbations are added to raw input text, the
performance of a deep learning model may drop dramatically under attacks.
Recent work argues the adversarial vulnerability of the model is caused by the
non-robust features in supervised training. Thus in this paper, we tackle the
adversarial robustness challenge from the view of disentangled representation
learning, which is able to explicitly disentangle robust and non-robust
features in text. Specifically, inspired by the variation of information (VI)
in information theory, we derive a disentangled learning objective composed of
mutual information to represent both the semantic representativeness of latent
embeddings and differentiation of robust and non-robust features. On the basis
of this, we design a disentangled learning network to estimate these mutual
information. Experiments on text classification and entailment tasks show that
our method significantly outperforms the representative methods under
adversarial attacks, indicating that discarding non-robust features is critical
for improving adversarial robustness
Investigation of the Frequency Shift of a SAD Circuit Loop and the Internal Micro-Cantilever in a Gas Sensor
Micro-cantilever sensors for mass detection using resonance frequency have attracted considerable attention over the last decade in the field of gas sensing. For such a sensing system, an oscillator circuit loop is conventionally used to actuate the micro-cantilever, and trace the frequency shifts. In this paper, gas experiments are introduced to investigate the mechanical resonance frequency shifts of the micro-cantilever within the circuit loop(mechanical resonance frequency, MRF) and resonating frequency shifts of the electric signal in the oscillator circuit (system working frequency, SWF). A silicon beam with a piezoelectric zinc oxide layer is employed in the experiment, and a Self-Actuating-Detecting (SAD) circuit loop is built to drive the micro-cantilever and to follow the frequency shifts. The differences between the two resonating frequencies and their shifts are discussed and analyzed, and a coefficient α related to the two frequency shifts is confirmed
Random vibration analysis for coupled vehicle-track systems with uncertain parameters
Purpose
– The purpose of this paper is to present a new random vibration-based assessment method for coupled vehicle-track systems with uncertain parameters when subjected to random track irregularity.
Design/methodology/approach
– The uncertain parameters of vehicle are described as bounded random variables. The track is regarded as an infinite periodic structure, and the dynamic equations of the coupled vehicle-track system, under mixed physical coordinates and symplectic dual coordinates, are established through wheel-rail coupling relationships. The random track irregularities at the wheel-rail contact points are converted to a series of deterministic harmonic excitations with phase lag by using the pseudo excitation method. Based on the polynomial chaos expansion of the pseudo response, a chaos expanded pseudo equation is derived, leading to the combined hybrid pseudo excitation method-polynomial chaos expansion method.
Findings
– The impact of uncertainty propagation on the random vibration analysis is assessed efficiently. According to GB5599-85, the reliability analysis for the stability index is implemented, which can grade the comfort level by the probability. Comparing to the deterministic analysis, it turns out that neglect of the parameter uncertainty will lead to potentially risky analysis results.
Originality/value
– The proposed method is compared with Monte Carlo simulations, achieving good agreement. It is an effective means for random vibration analysis of uncertain coupled vehicle-track systems and has good engineering practicality
The role of mitochondria-associated membranes mediated ROS on NLRP3 inflammasome in cardiovascular diseases
Reactive oxygen species (ROS) metabolism is essential for the homeostasis of cells. Appropriate production of ROS is an important signaling molecule, but excessive ROS production can damage cells. ROS and ROS-associated proteins can act as damage associated molecular pattern molecules (DAMPs) to activate the NACHT, LRR, and PYD domains-containing protein 3 (NLRP3) inflammasome in cardiovascular diseases. Previous studies have shown that there are connected sites, termed mitochondria-associated membranes (MAMs), between mitochondria and the endoplasmic reticulum. In cardiovascular disease progression, MAMs play multiple roles, the most important of which is the ability to mediate ROS generation, which further activates the NLPR3 inflammasome, exacerbating the progression of disease. In this review, the following topics will be covered: 1. Molecular structures on MAMs that can mediate ROS generation; 2. Specific mechanisms of molecule-mediated ROS generation and the molecules' roles in cardiovascular disease, 3. The effects of MAMs-mediated ROS on the NLRP3 inflammasome in cardiovascular disease. The purpose of this review is to provide a basis for subsequent clinical treatment development
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