Modeling guided wave propagation with application to the long-range defect detection in railroad tracks

The aim of this work is to demonstrate the use of a commercial finite element package, ABAQUS EXPLICIT, to model ultrasonic guided waves in structural components. The particular application of interest is modeling the interaction of a broadband vertical bending mode with transverse-type defects in railroad tracks. This topic is part of a broader project on high-speed defect detection in rails by long-range ultrasonic inspections. Reflection coefficient spectra in the 20–45 kHz range are obtained for four different sizes and three different orientations of transverse head flaws. A preliminary study of Lamb waves in a free plate helps drawing modeling guidelines for the rail.     

Remanufacturability and Assessment Method

WITH the development of surface engineering andlaws on environment protect,lots of companies have toconsider reclaim of the used products.In practice,theyrealized if the products adopt design forremanufacturing,the benefit of remanufacturing wouldbe increased obviously'1'.Some researcher haveentered into remanufacturability field and built relativeevaluating methods'2'.Based on researching resultabout design for remanufacturing,some concepts,remanufacturability system and assessment method ar…     

Rational Design of CYP3A4 Inhibitors: A One-Atom Linker Elongation in Ritonavir-Like Compounds Leads to a Marked Improvement in the Binding Strength

Inhibition of the major human drug-metabolizing cytochrome P450 3A4 (CYP3A4) by pharmaceuticals and other xenobiotics could lead to toxicity, drug–drug interactions and other adverse effects, as well as pharmacoenhancement. Despite serious clinical implications, the structural basis and attributes required for the potent inhibition of CYP3A4 remain to be established. We utilized a rational inhibitor design to investigate the structure–activity relationships in the analogues of ritonavir, the most potent CYP3A4 inhibitor in clinical use. This study elucidated the optimal length of the head-group spacer using eleven (series V) analogues with the R₁/R₂ side-groups as phenyls or R₁–phenyl/R₂–indole/naphthalene in various stereo configurations. Spectral, functional and structural characterization of the inhibitory complexes showed that a one-atom head-group linker elongation, from pyridyl–ethyl to pyridyl–propyl, was beneficial and markedly improved K_s, IC₅₀ and thermostability of CYP3A4. In contrast, a two-atom linker extension led to a multi-fold decrease in the binding and inhibitory strength, possibly due to spatial and/or conformational constraints. The lead compound, 3h, was among the best inhibitors designed so far and overall, the strongest binder (K_s and IC₅₀ of 0.007 and 0.090 µM, respectively). 3h was the fourth structurally simpler inhibitor superior to ritonavir, which further demonstrates the power of our approach.     

A Holistic Evolutionary and 3D Pharmacophore Modelling Study Provides Insights into the Metabolism,Function, and Substrate Selectivity of the Human Monocarboxylate Transporter 4 (hMCT4)

Monocarboxylate transporters (MCTs) are of great research interest for their role in cancer cell metabolism and their potential ability to transport pharmacologically relevant compounds across the membrane. Each member of the MCT family could potentially provide novel therapeutic approaches to various diseases. The major differences among MCTs are related to each of their specific metabolic roles, their relative substrate and inhibitor affinities, the regulation of their expression, their intracellular localization, and their tissue distribution. MCT4 is the main mediator for the efflux of L-lactate produced in the cell. Thus, MCT4 maintains the glycolytic phenotype of the cancer cell by supplying the molecular resources for tumor cell proliferation and promotes the acidification of the extracellular microenvironment from the co-transport of protons. A promising therapeutic strategy in anti-cancer drug design is the selective inhibition of MCT4 for the glycolytic suppression of solid tumors. A small number of studies indicate molecules for dual inhibition of MCT1 and MCT4; however, no selective inhibitor with high-affinity for MCT4 has been identified. In this study, we attempt to approach the structural characteristics of MCT4 through an in silico pipeline for molecular modelling and pharmacophore elucidation towards the identification of specific inhibitors as a novel anti-cancer strategy.     

A Web Server for Designing Molecular Switches Composed of Two Interacting RNAs

The programmability of RNA–RNA interactions through intermolecular base-pairing has been successfully exploited to design a variety of RNA devices that artificially regulate gene expression. An in silico design for interacting structured RNA sequences that satisfies multiple design criteria becomes a complex multi-objective problem. Although multi-objective optimization is a powerful technique that explores a vast solution space without empirical weights between design objectives, to date, no web service for multi-objective design of RNA switches that utilizes RNA–RNA interaction has been proposed. We developed a web server, which is based on a multi-objective design algorithm called MODENA, to design two interacting RNAs that form a complex in silico. By predicting the secondary structures with RactIP during the design process, we can design RNAs that form a joint secondary structure with an external pseudoknot. The energy barrier upon the complex formation is modeled by an interaction seed that is optimized in the design algorithm. We benchmarked the RNA switch design approaches (MODENA+RactIP and MODENA+RNAcofold) for the target structures based on natural RNA-RNA interactions. As a result, MODENA+RactIP showed high design performance for the benchmark datasets.     

Reciprocal bi-directional generative adversarial network for cross-modal pedestrian re-identification

To improve the accuracy of cross-modal pedestrian re-identification,a reciprocal bi-directional generative adversarial network-based method is proposed.First,we build two generative adversarial networks to generate cross-modal heterogeneous images.Second,an associated loss is designed to pull close the distribution of features in latent space during the image translation between visible and infrared images so as to help the networks generate fake heterogeneous images that have high similarity with the real images.Finally,by concatenating the original and generated heterogeneous pedestrian images into the discriminative feature extraction network,images from different modalities can be unified into a common modality,thus suppressing the cross-modal gap.Representation learning and metric learning are utilized to achieve more discriminative pedestrian features.Comparative experiments are conducted on SYSU-MM01 and RegDB datasets to analyze the accuracy with different loss functions.Compared with other state-of-the-art cross-modal pedestrian re-identification methods,the proposed method achieves a higher accuracy and stronger robustness.     

Method for discrimination of false targets in multistation radar systems based on the deep neural network

For the existing jamming discrimination methods for multistation radar systems,only the single feature of target echo space correlation is utilized as the metric,which leads to insufficient comprehensiveness of feature extraction,so that effectiveness and universality are insufficient for the discrimination algorithm.In this paper,an identification method in multistatic radar systems based on the deep neural network is proposed.This method combines the characteristics of multistatic radar systems cooperative detection technology,which has many available resources and strong scheduling ability in space,time and frequency domain,with the strong model learning and feature representation ability in the process of information processing on the deep neural network,so that it can effectively apply to the field of anti-deception jamming.Full use is made of unknown information about echo data to obtain more multi-dimensional,more comprehensive,more complete and deeper feature differences besides correlation,so as to achieve a better jamming discrimination effect.Simulation results show that the proposed method can effectively reduce the influence of noise and pulse number on the jamming discrimination performance.At the same time,the limitation of the target echo correlation coefficient on anti-jamming technology under nonideal conditions is alleviated,which broadens the boundary conditions of the application process.     

《单片机原理及应用》课程思政的实践探索——以“单片机的存储器结构”知识点讲解为例

针对《单片机原理及应用》及其相关课程在课程思政建设中存在的问题,提出一种课程思政设计思路,即选取合适的授课内容与思政素材,从教学目标和教学设计出发,将思政素材自然融入到授课内容中。并以“单片机的存储器结构”知识点讲解为例,详细介绍了以上课程思政设计思路的具体设计与实施过程,具有较强的创新性与可操作性,对单片机类课程线上及线下教学的课程思政建设有一定的借鉴意义。     

工业设计决策网络构建及其动态演化仿真

针对工业设计过程多阶段方案决策的意见演化问题,融合复杂网络理论建立工业设计决策网络模型,通过意见动力学进行决策意见动态演化仿真.基于图论建立设计决策有权无向网络,以网络效率变化确定决策者权重,借助意见距离识别设计决策网络节点信任集合,利用加权平均意见驱动设计决策网络更新与演化. 提出工业设计决策网络的演化仿真流程,结合产品设计方案决策数据进行动态仿真分析,结果表明：信任阈值决定设计决策网络拓扑构成,随着网络演化的进行,决策个体间意见差异逐步缩小并最终达成共识;设计决策网络分析能够析出噪声节点及其意见变化,在实际产品设计决策中应重点关注;意见演化能够辅助确定工业设计方案决策轮次,明确方案在各指标上的表现并识别设计改进方向;仿真分析有助于发现设计决策中的关键因素和意见演化规律.     

银耳多糖超声波提取工艺优化及抗BV2细胞炎症的作用研究

以银耳为原料, 采用超声波辅助热水浸提法提取银耳多糖, 以多糖提取率为指标, 以超声波功率、提取料液比、提取温度和提取时间为影响因素, 设计单因素试验, 并通过正交试验得到较佳提取工艺。通过用TRPV1(Transient Receptor Potential Vanilloid1)试剂盒检测了小胶质细胞TRPV1的释放水平, 与脂多糖(Lipopolysaccharide, LPS)对照组相比, 不同质量浓度的银耳多糖组(62.5, 250, 1000 μg/mL)均能不同程度地抑制TRPV1的释放量。说明了银耳多糖对于BV2小胶质细胞炎症具有良好的抑制作用。