Identification of Host Cellular Protein Substrates of SARS-COV-2 Main Protease

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease-19 (COVID-19) being associated with severe pneumonia. Like with other viruses, the interaction of SARS-CoV-2 with host cell proteins is necessary for successful replication, and cleavage of cellular targets by the viral protease also may contribute to the pathogenesis, but knowledge about the human proteins that are processed by the main protease (3CLpro) of SARS-CoV-2 is still limited. We tested the prediction potentials of two different in silico methods for the identification of SARS-CoV-2 3CLpro cleavage sites in human proteins. Short stretches of homologous host-pathogen protein sequences (SSHHPS) that are present in SARS-CoV-2 polyprotein and human proteins were identified using BLAST analysis, and the NetCorona 1.0 webserver was used to successfully predict cleavage sites, although this method was primarily developed for SARS-CoV. Human C-terminal-binding protein 1 (CTBP1) was found to be cleaved in vitro by SARS-CoV-2 3CLpro, the existence of the cleavage site was proved experimentally by using a His₆-MBP-mEYFP recombinant substrate containing the predicted target sequence. Our results highlight both potentials and limitations of the tested algorithms. The identification of candidate host substrates of 3CLpro may help better develop an understanding of the molecular mechanisms behind the replication and pathogenesis of SARS-CoV-2.     

Application of the novel Droplet digital PCR technology for identification of meat species

The authenticity and traceability of meat products are issues of primary importance to ensure food safety. Unfortunately, food adulteration (e.g. the addition of inexpensive cuts to minced meat products) and mislabelling (e.g. the inclusion of meat from species other than those declared) happens frequently worldwide. The aim of this study was to apply a droplet digital PCR assay for the detection and quantification (copies μL⁻¹) of the beef, pork, horse, sheep, chicken and turkey in meat products. The analysis conducted on commercial meat showed the presence of traces of DNA from other animal species than those declared. We show that the method is highly sensitive, specific and accurate (accuracy = 100%). This method could be adopted by competent food safety authorities to verify compliance with the labelling of meat products and to ensure quality and safety throughout the meat supply chain, from primary production to consumption.     

风速时间序列混沌判定方法比较研究

混沌识别是对非线性时间序列进行混沌预测的前提。针对时间序列风速确定性与随机性相结合的复杂非线性特征,研究了不同的混沌识别方法,并对风速时间序列进行混沌特征识别。应用随机噪声、周期运动及经典混沌系统的时间序列对所选方法进行可靠性验证。对美国国家风能研究中心M2测风塔实测时间序列风速数据进行非线性混沌特征识别。结果表明:风速时间序列具有明显的混沌特征;各风速时间序列表现出不同程度的混沌特征;各混沌识别方法对风速时间序列混沌特征的表达形式不同,互为补充,相互验证。     

船体结构冰载荷反演方法及试验验证

冰载荷是影响船舶冰区航行期间结构安全的重要环境载荷。船舶的冰压监测通常采用应变传感器，合理地布放传感器是识别冰载荷的基础。通过对比船体外板结构试验中的冲击载荷和不同测试方案下的应变信号，确定了最佳应变传感器布放方案；采用Green核函数方法建立了船体外板结构应变冲击载荷间的响应关系，并对采集信号在噪声影响下反演的不适定性进行了分析；采用Tikhonov正则化方法克服了载荷反演过程中出现的数值不稳定问题；最后将试验中的响应用到载荷识别分析中，反演的载荷可以较为准确地反映冲击载荷的时域特征并且载荷识别精度良好。     

双馈风机风电场联络线出口故障方向判别

由于双馈风机风电场故障特性与传统同步机存在较大差别,因此传统方向元件应用于双馈风机风电场时存在适应性问题。针对双馈风机风电场存在的频率偏移、等值内阻抗不稳定和弱馈等特点,提出一种基于时域波形相似度的故障方向元件。根据推算的联络线对侧电压与保护安装处记忆电压波形的余弦相似度判断故障方向,能够有效解决双馈风机风电场出口故障方向判别存在的问题。在PSCAD/EMTDC中搭建典型的双馈风机接入系统,仿真结果表明,所提故障方向元件针对不同的故障类型均能有效判断故障方向。     

基于关键拓扑变动项辨识的调度操作潮流校核方法

为解决传统调度操作潮流校核中的有效性问题，定义了一种面向调度操作的关键拓扑变动概念，提出并实现了基于关键拓扑变动辨识的调度操作潮流校核方法。首先，剖析了调度操作安全校核的实施目的，围绕其运行断面潮流校验的校核目的，定义了面向调度操作的关键拓扑变动概念，并基于网络拓扑连接关系设计了其辨识方法。在此基础上，提出了基于关键拓扑变动项辨识的调度操作潮流校核方法，明确了其实施流程和要点。最后基于当前电网调度自动化系统实际，构建了其实施框架，并介绍了其在某电网的实施效益。     

利用非糖物质快速鉴别单花蜂蜜

本文利用非糖物质快速鉴别四种常见的单花蜂蜜(枸杞蜂蜜、荆条蜂蜜、枣花蜂蜜和洋槐蜂蜜)。利用固相萃取除糖提取蜂蜜非糖物质,并用高效液相色谱(HPLC)结合化学计量学进行蜂蜜花源的判定。发现了四种单花蜂蜜的非糖特征标志物。芦丁、丁香酸甲酯、阿魏酸的含量在四种蜂蜜中差异最大。对羟基苯甲酸和脱落酸在枸杞蜂蜜中平均含量分别为0.59μg/g和0.42μg/g,可作为枸杞蜂蜜的花源标志物;对香豆酸和肉桂酸在荆条蜂蜜中平均含量为0.08μg/g和0.05μg/g,可作为荆条蜂蜜的潜在花源标志物;阿魏酸、异阿魏酸是枣花蜂蜜的特征标志物,平均含量分别为0.40μg/g和0.76μg/g;洋槐蜂蜜的特征标志物是芦丁和丁香酸甲酯,平均含量为0.08μg/g和0.14μg/g。利用高效液相色谱指纹图谱结合化学计量学方法(主成分分析和判别分析),四种单花蜂蜜依据其花源被成功区分。本研究对蜂蜜真实性判定有重要参考价值,为后续蜂蜜真伪鉴别奠定基础。     

Efficient model selection for real-time adaptive cold start strategy of a fuel cell system on vehicular applications

The PEMFC maximum power is greatly influenced by subfreezing temperature and degradation phenomena. Therefore, a dependable model is required to estimate the power with respect to the variation of the operating conditions and state of health. Semi-empirical models are potent tools in this regard. Nonetheless, there is not much information about their cold environment reliability. This paper comprehensively compares the performance of some models (already tested in normal ambient temperature) in subfreezing condition to introduce the most reliable one for PEMFC cold start-up application. Firstly, seven models are compared regarding voltage losses and precision. Subsequently, the three most dependable ones are selected and experimentally compared at sub-zero temperature in terms of polarization curve estimation for three PEMFCs with different degradation levels. The results of this study indicate that the model introduced by Amphlett et al. has a superior performance compared to other ones regarding the characteristic's estimation in below-zero temperature.     

灭火器的定位和有效性辨识研究

智慧消防是智慧城市建设的重要组成部分，在消防工作创新发展中发挥重要作用。灭火器作为扑救初期火灾的最普遍、最便捷和最广泛使用的灭火设施，在初期火灾的扑救和火灾防控中发挥重要的作用，其有效性和完好性是扑救初期火灾的必要条件。基于物联网及大数据的优势，建立消防灭火设施的定位与有效性辨识系统，并介绍系统的关键技术、网络架构、技术特征。此系统可对灭火器等消防灭火设施的伺应状态、完好性、有效性等功能特性进行跟踪巡检和辨识，以实现对灭火器的实时监控和智能化管理，促进消防设施建设的完善和优化，增强灭火系统的可靠性，充分发挥智慧消防技术在智慧城市建设中的优势。