Gap Junctional Communication via Connexin43 between Purkinje Fibers and Working Myocytes Explains the Epicardial Activation Pattern in the Postnatal Mouse Left Ventricle

The mammalian ventricular myocardium forms a functional syncytium due to flow of electrical current mediated in part by gap junctions localized within intercalated disks. The connexin (Cx) subunit of gap junctions have direct and indirect roles in conduction of electrical impulse from the cardiac pacemaker via the cardiac conduction system (CCS) to working myocytes. Cx43 is the dominant isoform in these channels. We have studied the distribution of Cx43 junctions between the CCS and working myocytes in a transgenic mouse model, which had the His-Purkinje portion of the CCS labeled with green fluorescence protein. The highest number of such connections was found in a region about one-third of ventricular length above the apex, and it correlated with the peak proportion of Purkinje fibers (PFs) to the ventricular myocardium. At this location, on the septal surface of the left ventricle, the insulated left bundle branch split into the uninsulated network of PFs that continued to the free wall anteriorly and posteriorly. The second peak of PF abundance was present in the ventricular apex. Epicardial activation maps correspondingly placed the site of the first activation in the apical region, while some hearts presented more highly located breakthrough sites. Taken together, these results increase our understanding of the physiological pattern of ventricular activation and its morphological underpinning through detailed CCS anatomy and distribution of its gap junctional coupling to the working myocardium.     

基于自动机理论的密码匹配方法

针对用户安全登录问题,提出了一种基于自动机的密码匹配模型.首先,对于用户任意输入的密码进行同态映射加密; 其次,构造出可接受加密密码的自动机——状态数目可变自动机(VNS - DFA),该自动机不仅能够匹配加密密码,同时还可以输出加密密码的同态原像以及匹配成功的次数; 最后,在状态数目可变的自动机上对用户输入的密码进行实验验证表明,用户建立的密码经过同态映射后可全部被该自动机接受,且该自动机的时间复杂度优于传统的DFA以及改进的DFA.     

基于数字孪生的飞机总装生产线建模

为了实现飞机制造企业总装生产线车间物理空间与信息空间的实时交互与深度融合,通过分析飞机总装生产线组成单元与生产业务逻辑,提出基于数字孪生的飞机总装生产线车间建模框架. 从“人、机、料、法、环、测”六维视角出发,阐述生产线关键要素建模与实现,并提出飞机总装生产线三维可视化及信息集成平台实现技术流程. 在CATIA中建立车间三维数字模型,基于浏览器和WebGL技术建立虚拟空间,通过采集生产现场过程数据实现物理实体向虚拟空间的实时映射. 以某型飞机总装生产线车间为例,实现总装现场与虚拟可视化的同步映射、WebServices服务、信息查询服务及装配工艺过程查询服务,有效提高作业效率并为工作人员决策提供科学参考.     

基于双目强约束的直接稀疏视觉里程计

为了提高双目直接稀疏里程计(Stereo Direct Sparse Odometry, Stereo DSO)的定位速度和精度, 使得移动机器人可以更有效地执行任务, 提出了一种基于双目强约束的直接稀疏视觉里程计系统。基于直接法的即时定位与地图构建(Simultaneous Localization and Mapping, SLAM)系统直接对图像像素构建光度误差优化函数, 无需提取特征点, 克服了基于特征点法的SLAM系统在弱纹理场景下不鲁棒的缺陷, 并且在前端跟踪阶段效率更高。提出一种快速、准确的双目初始化方法, 结合三角化不确定性为不同类型的点赋予不同的深度范围, 加速深度滤波器的收敛。同时, 在运动估计阶段引入双目约束, 使得该系统在绝对尺度上的定位更加准确。通过在公开的KITTI数据集11个序列上进行实验, 实验结果表明所提出的算法在定位精度上明显优于同样采用直接法的Stereo Large Scale Direct SLAM(LSD-SLAM2)和Stereo DSO, 并达到与基于特征点法的ORB-SLAM3相近的水平, 为直接法SLAM提供一种更优的定位方案。     

基于XML异构数据库集成中间件的设计与实现

为了解决网络环境中异构数据库数据共享和协作问题,提出了基于XML中间件技术实现异构数据库之间信息交换模型.在此模型中对虚拟法或中介法模型进行改进设计了翻译器、集成器和转换器,分别用于数据获取、合并和格式转换.为了更精确地描述XML文件自身结构信息,实现了从DTD到XML Schema的转换.     

一种高动态范围图像可视化算法*

提出的自适应HDR图像可视化算法中,输入图像被分解为基本层和细节层.该算法将整体明暗效果的显示看做整体问题,对表示亮度的基本层采用基于整体统计信息的直方图调整算法处理;可视细节信息的保持作为局部问题,算法采用自适应细节增强算法处理细节层.通过定义映射图对细节增强后的图像进行最终映射,将两方面结合起来得到最终结果.实验结果表明,该算法能对HDR图像进行较高视觉质量的显示.     

多信息源下本体自动抽取的实现*

以关系型数据库、XML文件、HTML文件、一般文档为信息源,运用不同的方法分别将多信息源映射为概念图,并按照拟定的概念逻辑结构进行统一存储,最后运用抽取算法实现本体的自动抽取.     

面向等价性验证的锁存器匹配算法

为了克服现有等价性验证技术中难以精确匹配锁存器的局限性,提出了一种结合多种方法的新型锁存器匹配算法.该算法结合任意模拟、局部二叉判决图、目标模拟3种方法来匹配锁存器,并使用了类似滤波器的思想,任意模拟对锁存器作初步快速匹配,提出的局部二叉判决图技术降低了发生内存爆炸的可能性,目标模拟则针对性地对锁存器作进一步的划分. ISCAS89电路实验结果表明,该算法与模拟和自动测试矢量生成等方法相比,在运行时间、占用内存和匹配精度等方面均体现出有效性,可用于处理较大规模的时序电路验证问题.     

弹性半无限空间中矩形孔收缩的复变函数解答

随着城市建设的发展,矩形隧道的应用越来越多,但针对矩形隧道的理论研究却鲜有见闻。针对矩形隧道,建立了半无限空间矩形隧道的弹性理论计算模型,采用最小二乘迭代方法确定共形映射函数的各项系数,并将计算区域映射为复平面上的一个同心圆环;运用Muskhelishvili复变函数方法,将计算区域内的应力函数展开成为Laurant级数的形式,给定了地表零应力边界和矩形孔口径向位移边界,求得了半无限空间矩形隧道在给定位移条件下的应力场和位移场。分析了不同高宽比、不同泊松比、不同埋深对位移场和应力场的影响,总结了矩形隧道位移场和应力场的一般规律。结果表明：高宽比偏小、泊松比偏大、埋深偏小都会使得沉降槽不再是类高斯曲线的形状,这些参数的变化也会在不同程度上影响应力场和位移场的大小和分布。     

AKT Inhibitors: The Road Ahead to Computational Modeling-Guided Discovery

AKT, is a serine/threonine protein kinase comprising three isoforms—namely: AKT1, AKT2 and AKT3, whose inhibitors have been recognized as promising therapeutic targets for various human disorders, especially cancer. In this work, we report a systematic evaluation of multi-target Quantitative Structure-Activity Relationship (mt-QSAR) models to probe AKT’ inhibitory activity, based on different feature selection algorithms and machine learning tools. The best predictive linear and non-linear mt-QSAR models were found by the genetic algorithm-based linear discriminant analysis (GA-LDA) and gradient boosting (Xgboost) techniques, respectively, using a dataset containing 5523 inhibitors of the AKT isoforms assayed under various experimental conditions. The linear model highlighted the key structural attributes responsible for higher inhibitory activity whereas the non-linear model displayed an overall accuracy higher than 90%. Both these predictive models, generated through internal and external validation methods, were then used for screening the Asinex kinase inhibitor library to identify the most potential virtual hits as pan-AKT inhibitors. The virtual hits identified were then filtered by stepwise analyses based on reverse pharmacophore-mapping based prediction. Finally, results of molecular dynamics simulations were used to estimate the theoretical binding affinity of the selected virtual hits towards the three isoforms of enzyme AKT. Our computational findings thus provide important guidelines to facilitate the discovery of novel AKT inhibitors.