基于公用电话网实现发射机的远程控制

基于公用电话网络,利用个人通信终端实现对远程发射机的控制,主要介绍了系统的硬件组成及工作原理、软件的设计及实现方法.     

MLCC装配质量优化研究

针对本所产品中多层陶瓷电容器(MLCC)在经过环境试验后出现的失效问题,通过对失效原因进行分析,结合生产实际情况,进行了技术改进.制作了技术改进前后的试验板,经过环境试验后测试,结果表明,未改进前的试验板中的MLCC出现问题,而改进后的试验板没有发现问题.最后对故障MLCC进行了DPA检查,结果发现MLCC端头出现45°角裂纹.试验结果表明经过技术改进后有效地解决了MLCC装配质量问题,提高了产品装配合格率,达到了预期的效果.     

基于AT89S52的家庭智能浇花器的设计

设计了家庭智能浇花器,实现花卉的自动浇水.利用单片机实现自动浇花,根据不同的花种,设置了不同的控制方式,即定时定量浇花方式与根据湿度浇花.定时定量浇花是实现每天在规定的时间自动打开电磁阀浇花,根据不同的花卉所需水量不同,用一个按钮来设置浇花时间的长短,即电磁阀打开的时间,其余时间电磁阀闭合,水流不经过;根据湿度控制浇花...     

基于Labview的光纤光栅温度传感器实验研究

提出了一种基于Labview语言的实时数据采集及处理系统设计方案,介绍了光纤光栅温度传感波长解调原理,应用Labview语言编写了程序,实现对数据的处理和显示,试验结果表明:该系统能够有效利用计算机实现信号的处理,满足FBG传感器实时数据采集和处理的要求,获得了0.3℃温度测量精度和0.1 ℃分辨率.     

水下实验有线测量技术综述

水下实验是海洋工程、船舶工程、海洋资源开发、水下兵器研制等诸多领域的必要手段,有线测量是水下实验和水下测量的重要手段,它为水下实验提供数据支撑和评判依据,是一项基础性的工作.本文针对水下实验领域特点,详细阐述了有线测量水下实验技术的特点和着重点,综合介绍了水下实验测量技术.     

正交试验在软件测试用例设计中的应用

由于软件规模越来越大,软件测试要达到一定的测试覆盖率,生成的测试用例数目相当惊人。为了合理分配有限的测试资源,提出了一种基于正交试验的软件测试用例生成方法。简要介绍正交试验的基本概念,结合正交法的特点阐述其在设计软件测试用例方面的适用性及使用过程,最后给出实例。结果表明,生成测试用例数量较少,且测试效果能够得到保证。     

一种无人机扩频遥控系统的性能分析

在剖析无人机扩频遥控系统组成的基础上,对无人机扩频遥控系统的处理增益、抗干扰容限及保密性能做了具体的分析,对无人机扩频遥控系统的雷达截获概率做了深入的探讨。     

Identification of Human Dihydroorotate Dehydrogenase Inhibitor by a Pharmacophore-Based Virtual Screening Study

Human dihydroorotate dehydrogenase (hDHODH) is an enzyme belonging to a flavin mononucleotide (FMN)-dependent family involved in de novo pyrimidine biosynthesis, a key biological pathway for highly proliferating cancer cells and pathogens. In fact, hDHODH proved to be a promising therapeutic target for the treatment of acute myelogenous leukemia, multiple myeloma, and viral and bacterial infections; therefore, the identification of novel hDHODH ligands represents a hot topic in medicinal chemistry. In this work, we reported a virtual screening study for the identification of new promising hDHODH inhibitors. A pharmacophore-based approach combined with a consensus docking analysis and molecular dynamics simulations was applied to screen a large database of commercial compounds. The whole virtual screening protocol allowed for the identification of a novel compound that is endowed with promising inhibitory activity against hDHODH and is structurally different from known ligands. These results validated the reliability of the in silico workflow and provided a valuable starting point for hit-to-lead and future lead optimization studies aimed at the development of new potent hDHODH inhibitors.     

Harnessing Protein-Ligand Interaction Fingerprints to Predict New Scaffolds of RIPK1 Inhibitors

Necroptosis has emerged as an exciting target in oncological, inflammatory, neurodegenerative, and autoimmune diseases, in addition to acute ischemic injuries. It is known to play a role in innate immune response, as well as in antiviral cellular response. Here we devised a concerted in silico and experimental framework to identify novel RIPK1 inhibitors, a key necroptosis factor. We propose the first in silico model for the prediction of new RIPK1 inhibitor scaffolds by combining docking and machine learning methodologies. Through the data analysis of patterns in docking results, we derived two rules, where rule #1 consisted of a four-residue signature filter, and rule #2 consisted of a six-residue similarity filter based on docking calculations. These were used in consensus with a machine learning QSAR model from data collated from ChEMBL, the literature, in patents, and from PubChem data. The models allowed for good prediction of actives of >90, 92, and 96.4% precision, respectively. As a proof-of-concept, we selected 50 compounds from the ChemBridge database, using a consensus of both molecular docking and machine learning methods, and tested them in a phenotypic necroptosis assay and a biochemical RIPK1 inhibition assay. A total of 7 of the 47 tested compounds demonstrated around 20–25% inhibition of RIPK1’s kinase activity but, more importantly, these compounds were discovered to occupy new areas of chemical space. Although no strong actives were found, they could be candidates for further optimization, particularly because they have new scaffolds. In conclusion, this screening method may prove valuable for future screening efforts as it allows for the exploration of new areas of the chemical space in a very fast and inexpensive manner, therefore providing efficient starting points amenable to further hit-optimization campaigns.     

In Silico Drug Repurposing of FDA-Approved Drugs Highlighting Promacta as a Potential Inhibitor of H7N9 Influenza Virus

Influenza virus infections continue to be a significant and recurrent public health problem. Although vaccine efficacy varies, regular immunisation is the most effective method for suppressing the influenza virus. Antiviral drugs are available for influenza, although two of the four FDA-approved antiviral treatments have resulted in significant drug resistance. Therefore, new treatments are being sought to reduce the burden of flu-related illness. The time-consuming development of treatments for new and re-emerging diseases such as influenza and the high failure rate are increasing concerns. In this context, we used an in silico-based drug repurposing method to repurpose FDA-approved drugs as potential therapies against the H7N9 virus. To find potential inhibitors, a total of 2568 drugs were screened. Promacta, tucatinib, and lurasidone were identified as promising hits in the DrugBank database. According to the calculations of MM-GBSA, tucatinib (−54.11 kcal/mol) and Promacta (−56.20 kcal/mol) occupied the active site of neuraminidase with a higher binding affinity than the standard drug peramivir (−49.09 kcal/mol). Molecular dynamics (MD) simulation studies showed that the C-α atom backbones of the complexes of tucatinib and Promacta neuraminidase were stable throughout the simulation period. According to ADME analysis, the hit compounds have a high gastrointestinal absorption (GI) and do not exhibit properties that allow them to cross the blood–brain barrier (BBB). According to the in silico toxicity prediction, Promacta is not cardiotoxic, while lurasidone and tucatinib show only weak inhibition. Therefore, we propose to test these compounds experimentally against the influenza H7N9 virus. The investigation and validation of these potential H7N9 inhibitors would be beneficial in order to bring these compounds into clinical settings.