Gene Variants Related to Cardiovascular and Pulmonary Diseases May Correlate with Severe Outcome of COVID-19

Background: Severe outcomes of COVID-19 account for up to 15% of all cases. The study aims to check if any gene variants related to cardiovascular (CVD) and pulmonary diseases (PD) are correlated with a severe outcome of COVID-19 in a Polish cohort of COVID-19 patients. Methods: In this study, a subset of 747 samples from unrelated individuals collected across Poland in 2020 and 2021 was used and whole-genome sequencing was performed. Results: The GWAS analysis of SNPs and short indels located in genes related to CVD identified one variant significant in COVID-19 severe outcome in the HADHA gene, while for the PD gene panel, we found two significant variants in the DRC1 gene. In this study, both potentially protective and risk variants were identified, of which variants in the HADHA gene deserve the most attention. Conclusions: This is the first study reporting the association between the HADHA and DRC1 genetic variants and COVID-19 severe outcome based on the cohort WGS analysis. Although all the identified variants are localised in introns, they may be correlated and therefore inherited along with other risk variants, potentially causative to severe outcome of COVID-19 but not discovered yet.     

甲苯二异氰酸酯交联阳离子型丙烯酸酯树脂的制备及性能

用自由基聚合法制备了阳离子型羟基丙烯酸酯树脂,以甲苯-2,4-二异氰酸酯(TDI)和丁酮肟合成出半封端型TDI,将两种产物混合反应,制备出系列聚氨酯改性的丙烯酸酯树脂分散液.分散液成膜后,在高温(140 ℃)下解封的异氰酸酯官能团与丙烯酸酯树脂上的羟基反应得到异氰酸酯交联丙烯酸酯树脂膜.结果表明,随着交联度的提高,丙烯酸酯树脂的玻璃化转变温度升高,凝胶含量增加,拉伸性能、邵尔A硬度、耐腐蚀性及耐水性得以提高.     

支持基于内容检索的图像数据模型的设计

以面向对象的多媒体数据库系统Jasmine为平台,设计具有基于内容图像检索功能的面向对象数据模型,作为数据库的引擎,实现了一个支持基于内容检索技术的图像数据库系统。     

基于模拟谐振子的优化K-means聚类算法

针对K-means算法全局搜索能力的不足,提出了基于模拟谐振子的优化K-means聚类算法（SHO-KM）,该算法克服了K-means聚类算法对初始聚类中心选择敏感问题,能够获得全局最优的聚类划分。为了提高聚类划分质量,在聚类过程中采用基于Fisher分值的属性加权的实体之间距离计算方法,使用属性加权距离计算方法进行聚类划分时,无论是球形数据还是椭球形数据都能够获得较好的聚类划分结果。对KDD-99数据集的仿真实验结果表明,该算法在入侵检测中获得了理想的检测率和误报率。     

Robust fusion time‐varying Kalman estimators for multisensor networked systems with mixed uncertainties

This paper addresses the problem of designing robust fusion time‐varying Kalman estimators for a class of multisensor networked systems with mixed uncertainties including multiplicative noises, missing measurements, packet dropouts, and uncertain‐variance linearly correlated measurement and process white noises. By the augmented approach, the original system is converted into a stochastic parameter system with uncertain noise variances. Furthermore, applying the fictitious noise approach, the original system is converted into one with constant parameters and uncertain noise variances. According to the minimax robust estimation principle, based on the worst‐case system with the conservative upper bounds of the noise variances, the five robust fusion time‐varying Kalman estimators (predictor, filter, and smoother) are presented by using a unified design approach that the robust filter and smoother are designed based on the robust Kalman predictor, which include three robust weighted state fusion estimators with matrix weights, diagonal matrix weights, and scalar weights, a modified robust covariance intersection fusion estimator, and robust centralized fusion estimator. Their robustness is proved by using a combination method, which consists of Lyapunov equation approach, augmented noise approach, and decomposition approach of nonnegative definite matrix, such that their actual estimation error variances are guaranteed to have the corresponding minimal upper bounds for all admissible uncertainties. The accuracy relations among the robust local and fused time‐varying Kalman estimators are proved. A simulation example is shown with application to the continuous stirred tank reactor system to show the effectiveness and correctness of the proposed results.     

一种小波变换域的自适应视频水印算法

稳健性是数字水印算法的主要问题之一.根据视觉特点和信号特性实现水印分量的自适应嵌入是提高水印稳健性的有效途径.本文提出了一种基于小波变换域的自适应视频水印算法.水印根据2-D小波系数的特点嵌入在低频子带系数中,以获得较好的稳健性.为了在保证不可见性的前提下尽可能提高水印分量的强度,本文提出根据物体的运动和视频信号内容的纹理复杂度将低频子带中的系数进行分类,根据分类结果,自适应地调整嵌入水印的强度.实验结果表明:嵌入水印对多种攻击,如加性Gaussian噪声、高压缩比的MPEG-2压缩编码、时域抽样和丢帧、以及空域抽样等具有很好的稳健性.     

Web上分布式领域组件的框架表示

文章采用知识表示中的框架表示法,结合谓词产生式,语义网络等手段,提出了一个具有网络分布式及Ｗｅｂ化构造特性的领域构架及组件的表示方法ＦＲＤＤＣ。应用ＦＲＤＤＣ实现的ＡＮＤ－ＣＡＳＥ模型表现了ＦＲＤＤＣ的自然性,结构性,Ｗｅｂ可操作性,容纳柔性及知识表达能力。     

LD泵浦Nd:YVO_4/KTP激光器晶体长度对输出的影响

利用四能级激光系统的速率方程 ,对激光二极管 (LD)纵向泵浦Nd :YVO4 /KTP腔内倍频绿光激光器激活介质和倍频晶体的长度对输出激光功率的影响进行了理论计算 ,给出了参数优化结果 ,分析了它的工作特性 ,得到与理论计算符合较好的实验结果。     

一个快速的被动式传感器数据关联算法

本文针对仅能获得关于目标角度信息的被动式传感器、且允许传感器漏检、虚警、以及监视空域目标位置和数量未知的静态数据关联问题,提出了一个基于空间交点属性强度的快速数据关联算法.与现有算法相比,本方法较好地改进了数据关联算法的精度和运算速度.最后,通过仿真实验给以验证.     

基于综合仿真技术解决电力系统业务质量评价的方法

在实际工作中,业务系统运行质量及管理质量与网络质量的好坏密不可分,网络建设过程中对网络规模、建设需求与网络安全可靠性、资源使用情况等方面有着不同程度的要求,网络的升级改造、日常维护以及调度管理均对网络的质量有相应的评价标准和考核要求,为了提升电力运营管理、实现可靠性管理,需要结合相应业务管理指标需求,运用电力通信运行管理业务质量及应用模式仿真模型,对运行质量评价目标、动态风险评估管理、网络中故障和缺陷计分等进行业务质量评价.采用基于综合仿真技术解决业务质量评价的方法,实现业务质量评价管理及考核的结果验证,对于提升业务系统管理有重要的作用.