基于泰勒级数展开法的船舶水动力数值预报

为减小由大、小时间参数区域划分不明确所导致的三维时域Green函数的数值误差,在大、小时间区域交界处采用泰勒级数展开法对三维时域Green函数进行计算.基于线性叠加原理,采用脉冲响应函数法对船舶辐射问题与绕射问题进行求解.将Wigley Ⅰ型船作为研究算例,数值计算结果表明:本文计算的三维时域Green函数数值精度在大、小时间参数过渡区域内提高了四个数量级,水动力数值计算结果与其他文献结果及试验结果吻合较好,证明了本文所建立的水动力分析模型的可靠性.     

共享自动驾驶汽车使用意愿模型及其影响因素

为了构建共享自动驾驶汽车(shared autonomous vehicles，SAV) 的使用意愿模型并分析其影响因素，通过使用时机和使用频率来体现公众对SAV的使用意愿；采用验证性因子分析将态度潜变量转化为潜变量得分，以此将态度潜变量引入传统的有序Logit模型；提出SAV使用意愿的有序Logit模型构建方法，并建立基于个人属性、通勤特征、态度潜变量的SAV使用意愿模型.研究发现:是否使用过滴滴拼车、工作单位停车费、自动驾驶态度对使用时机和3种价格(1，2，3元/km) 下的使用频率有显著影响；使用过滴滴拼车、工作单位收取停车费、支持自动驾驶的群体倾向于频繁地、更早地使用SAV出行；公众期望以1元/km或 2元/km即不超过目前滴滴拼车的价格使用SAV.     

产后早期肛提肌裂孔扩张程度及相关因素分析

目的 分析产后早期肛提肌裂孔扩张的影响因素.方法 盆底超声测量产后早期女性肛提肌裂孔面积,其中研究组为105名肛提肌裂孔扩张者,对照组为145名肛提肌裂孔正常者,对肛提肌裂孔扩张的相关因素进行二元Logistic回归分析.结果 研究组中盆底疾病的发生率高于对照组(P＜0.05),Logistic回归分析显示第二产程时间、胎儿体重、催产素使用和盆腔器官脱垂与肛提肌裂孔扩张显著相关(P＜0.05).结论 第二产程时间延长、催产素增加和胎儿体重增加是肛提肌裂孔扩张的影响因素,对预测和精确诊断盆底疾病有临床意义.     

Blockage of the NLRP3 inflammasome by MCC950 improves anti-tumor immune responses in head and neck squamous cell carcinoma

The NLRP3 inflammasome is a critical innate immune pathway responsible for producing active interleukin (IL)-1β, which is associated with tumor development and immunity. However, the mechanisms regulating the inflammatory microenvironment, tumorigenesis and tumor immunity are unclear. Herein, we show that the NLRP3 inflammasome was over-expressed in human HNSCC tissues and that the IL-1β concentration was increased in the peripheral blood of HNSCC patients. Additionally, elevated NLRP3 inflammasome levels were detected in tumor tissues of Tgfbr1/Pten 2cKO HNSCC mice, and elevated IL-1β levels were detected in the peripheral blood serum, spleen, draining lymph nodes and tumor tissues. Blocking NLRP3 inflammasome activation using MCC950 remarkably reduced IL-1β production in an HNSCC mouse model and reduced the numbers of myeloid-derived suppressor cells (MDSCs), regulatory T cells (Tregs) and tumor-associated macrophages (TAMs). Moreover, inhibiting NLRP3 inflammasome activation increased the numbers of CD4⁺ and CD8⁺ T cells in HNSCC mice. Notably, the numbers of exhausted PD-1⁺ and Tim3⁺ T cells were significantly reduced. A human HNSCC tissue microarray showed that NLRP3 inflammasome expression was correlated with the expression of CD8 and CD4, the Treg marker Foxp3, the MDSC markers CD11b and CD33, and the TAM markers CD68 and CD163, PD-1 and Tim3. Overall, our results demonstrate that the NLRP3 inflammasome/IL-1β pathway promotes tumorigenesis in HNSCC and inactivation of this pathway delays tumor growth, accompanied by decreased immunosuppressive cell accumulation and an increased number of effector T cells. Thus, inhibition of the tumor microenvironment through the NLRP3 inflammasome/IL-1β pathway may provide a novel approach for HNSCC therapy.     

砂岩在西湖凹陷花港组交互式盖层中的作用初探

西湖凹陷花港组盖层具有砂泥岩交互式发育特征，而与泥岩伴生的砂岩类盖层的油气封闭作用研究较少。采用岩芯、镜下观察及压汞等分析方法，对砂泥岩交互式盖层中的砂岩特征进行了分析。结果表明，盖层中的砂岩可作为有效盖层，砂岩类盖层早期受沉积环境控制，含有较多的泥质而导致早期压实作用较强，加之晚期的黏土矿物转换及胶结物的发育，具备形成良好盖层的条件。在不同地区进行砂岩盖层有效性研究时应以沉积环境为基础，针对不同类型的砂岩进行成岩作用研究，并针对不同类型的砂岩样品进行实验分析以明确砂岩盖层的有效性。     

利用SRTM数据修测高山区地貌的探讨

在高海拔区域测制地形图,如青藏高原地区,所获取的遥感影像局部存在着大范围的高山阴影或云雪覆盖,造成立体观测地貌困难的现象,探讨应用SRTM数据对这类特殊区域地貌进行修测补绘。介绍了数据处理的作业过程,并对实验区SRTM与SPOT5影像立体测图成果进行实验对比分析,成果符合要求。     

基于极化单脉冲雷达扩展目标角度估计方法

当单脉冲雷达受到箔条质心干扰时, 将视为波束内存在两个不可分辨的目标, 由于目标和箔条干扰回波混叠耦合, 导致单脉冲测角偏差, 最终致使目标跟踪丢失。对此, 利用宽带单脉冲雷达测角精度高的优点和极化信息, 提出一种基于极化单脉冲雷达的扩展目标角度估计方法。首先，分析宽带单脉冲雷达体制下箔条质心干扰的特点, 给出扩展目标双极化和差信号模型。然后, 根据和、差通道极化回波信号, 通过联立方程组, 估计出目标和箔条干扰的到达角(angle of arrival, AOA), 为后续利用目标角度信息跟踪目标提供条件。最后，通过蒙特卡罗仿真实验分析关键参数对目标角度估计性能的影响, 并与传统单脉冲雷达体制的测角方法进行比较。理论分析和仿真实验表明, 在质心干扰条件下, 宽带单脉冲雷达估计目标AOA的性能要优于传统单脉冲雷达。     

迹为整数的3×3阶正交矩阵的谱

讨论了3×3阶正交矩阵的特征值和迹的关系,证明了迹为整数的3×3阶正交矩阵的谱可由迹确定,为应用广泛的3×3阶正交矩阵的谱的计算提供了简单实用的方法.     

基于高斯字典原子稀疏表示的高精度宽角SAR成像方法

为了提高从宽角合成孔径雷达(synthetic aperture radar, SAR)图像中提取目标后向散射各向异性特性的性能,在宽角SAR字典稀疏表示模型的基础上,提出一种基于高斯字典原子的高精度宽角SAR成像方法。在字典构造上,采用不同中心位置、相同方差的高斯函数。在求解稀疏表示系数上,采用广义最小最大凹惩罚稀疏重构算法求解。最后，根据稀疏表示系数的重构结果以及构造的字典得到目标的后向散射各向异性特性。通过仿真实验和Backhoe数据对算法进行验证,结果表明,该方法能够高精度地提取目标的后向散射各向异性特性。     

Hierarchical Community Detection Based on Partial Matrix Convergence Using Random Walks

Random walks are a standard tool for modeling the spreading process in social and biological systems.But in the face of large-scale networks,to achieve convergence,iterative calculation of the transition matrix in random walk methods consumes a lot of time.In this paper,we propose a three-stage hierarchical community detection algorithm based on Partial Matrix Approximation Convergence(PMAC) using random walks.First,this algorithm identifies the initial core nodes in a network by classical measurement and then utilizes the error function of the partial transition matrix convergence of the core nodes to determine the number of random walks steps.As such,the PMAC of the core nodes replaces the final convergence of all the nodes in the whole matrix.Finally,based on the approximation convergence transition matrix,we cluster the communities around core nodes and use a closeness index to merge two communities.By recursively repeating the process,a dendrogram of the communities is eventually constructed.We validated the performance of the PMAC by comparing its results with those of two representative methods for three real-world networks with different scales.