Inelastic deformation micromechanism and modified fragmentation model for silicon carbide under dynamic compression

The underlying micromechanism remains to be clarified for the bulk inelastic behaviour of specific ceramics under impact loads. In this study, the silicon carbide materials were subjected to the split-Hopkinson pressure bar compression in which the strain rate was not constant but increased to the dynamic level at high stresses. The inelastic deformation occurs in the high strain rate stage in compression, followed by the final transgranular fracture. The post-test fragments were examined in both the SEM and high resolution TEM. It was found that macroscopic inelastic behaviour is dominated by the dislocation motion and the localised amorphisation that arise at high strain rates. The damage and thus the degraded modulus in the dynamic inelastic deformation were incorporated to modify a dynamic fragmentation model to evaluate the fragment size as a function of strain rates. The modified model more accurately predicts the size of fragments produced at high strain rates

SememeASR: Boosting Performance of End-to-End Speech Recognition against Domain and Long-Tailed Data Shift with Sememe Semantic Knowledge

Recently, excellent progress has been made in speech recognition. However, pure data-driven approaches have struggled to solve the problem in domain-mismatch and long-tailed data. Considering that knowledge-driven approaches can help data-driven approaches alleviate their flaws, we introduce sememe-based semantic knowledge information to speech recognition (SememeASR). Sememe, according to the linguistic definition, is the minimum semantic unit in a language and is able to represent the implicit semantic information behind each word very well. Our experiments show that the introduction of sememe information can improve the effectiveness of speech recognition. In addition, our further experiments show that sememe knowledge can improve the model's recognition of long-tailed data and enhance the model's domain generalization ability.Comment: Accepted by INTERSPEECH 202

Aquaporin-1 Deficiency Protects Against Myocardial Infarction by Reducing Both Edema and Apoptosis in Mice

Many studies have determined that AQP1 plays an important role in edema formation and resolution in various tissues via water transport across the cell membrane. The aim of this research was to determine both if and how AQP1 is associated with cardiac ischemic injury, particularly the development of edema following myocardial infarction (MI). AQP1+/+ and AQP1−/− mice were used to create the MI model. Under physiological conditions, AQP1−/− mice develop normally; however, in the setting of MI, they exhibit cardioprotective properties, as shown by reduced cardiac infarct size determined via NBT staining, improved cardiac function determined via left ventricular catheter measurements, decreased AQP1-dependent myocardial edema determined via water content assays and decreased apoptosis determined via TUNEL analysis. Cardiac ischemia caused by hypoxia secondary to AQP1 deficiency stabilized the expression of HIF-1α in endothelial cells and subsequently decreased microvascular permeability, resulting in the development of edema. The AQP1-dependent myocardial edema and apoptosis contributed to the development of MI. AQP1 deficiency protected cardiac function from ischemic injury following MI. Furthermore, AQP1 deficiency reduced microvascular permeability via the stabilization of HIF-1α levels in endothelial cells and decreased cellular apoptosis following MI

An alternating peak-optimization method for optimal trajectory generation of quadrotor drones

In this paper, we propose an alternating optimization method to address a time-optimal trajectory generation problem. Different from the existing solutions, our approach introduces a new formulation that minimizes the overall trajectory running time while maintaining the polynomial smoothness constraints and incorporating hard limits on motion derivatives to ensure feasibility. To address this problem, an alternating peak-optimization method is developed, which splits the optimization process into two sub-optimizations: the first sub-optimization optimizes polynomial coefficients for smoothness, and the second sub-optimization adjusts the time allocated to each trajectory segment. These are alternated until a feasible minimum-time solution is found. We offer a comprehensive set of simulations and experiments to showcase the superior performance of our approach in comparison to existing methods. A collection of demonstration videos with real drone flying experiments can be accessed at https://www.youtube.com/playlist?list=PLQGtPFK17zUYkwFT-fr0a8E49R8Uq712l

Ferroelectric-Domain-Patterning-Controlled Schottky Junction State in Monolayer MoS\u3csub\u3e2\u3c/sub\u3e

We exploit scanning-probe-controlled domain patterning in a ferroelectric top layer to induce nonvolatile modulation of the conduction characteristic of monolayer MoS2 between a transistor and a junction state. In the presence of a domain wall, MoS2 exhibits rectified I-V characteristics that are well described by the thermionic emission model. The induced Schottky barrier height ΦeffB varies from 0.38 to 0.57 eV and is tunable by a SiO2 global back gate, while the tuning range of ΦeffB depends sensitively on the conduction-band-tail trapping states. Our work points to a new route to achieving programmable functionalities in van der Waals materials and sheds light on the critical performance limiting factors in these hybrid systems