Planning hierarchical hospital service areas for maternal care using a network optimization approach: A case study in Hubei,China

Improving maternal health is one of the Sustainable Development Goals. Hospital service areas (HSAs), which contain most hospitalization behaviors at the local scale, are crucial for health care planning. However, little attention has been given to HSAs for maternal care and the hierarchy structure. Considering Hubei, central China, as a case study, this study aims to fill these gaps by developing a method for delineating hierarchical HSAs for maternal care using a network optimization approach. The approach is driven by actual patient flow data and has an explicit objective to maximize the modularity. It also establishes the hierarchical structure of maternal care HSAs, which is fundamental for the planning of hierarchical maternal care and referral systems. In our case study, 45 secondary HSAs and 22 tertiary HSAs are delineated to achieve maximal modularity. The HSAs perform well in terms of indices such as the Localization Index and Market Share Index. Furthermore, there is a complementary relationship between secondary and tertiary hospitals, which suggests the need for referral system planning. This study can provide evidence for the validity of the HSA and the planning of maternal care HSAs in China. It also provides transferable methods for planning hierarchical HSAs in other developing countries.     

A Community Resilience Evaluation and Optimization Strategy based on Stormwater Management

In the context of disaster normalization, the concept of “resilience” has been gradually introduced into the field of disaster prevention and mitigation in urban communities. In order to resist the increasingly frequent disasters caused by extreme weather, it is necessary to shift the focus of building resilient urban communities to the level of stormwater management. Community resilience is a disaster prevention and mitigation capability based on community resources. In order to solve the deficiency of storm and flood management in the current construction of resilient communities in China, it is necessary to establish a quantitative evaluation system to evaluate it. This paper uses the analytic hierarchy process and Delphi method to establish a community resilience evaluation system from the perspectives of community material space level, community management level and individual level. Then three communities in Hefei City, Anhui Province are selected for practical application of the system, and corresponding optimization and transformation strategies are proposed. The results show that: (1) The resilience of community stormwater management is closely related to the integrated environment of the community, the allocation of flood control facilities and the daily disaster prevention and mitigation management; (2) The ability of disaster prevention and mitigation and the awareness of public participation of the residents in all communities are relatively weak, and the communities invest less in the popularization of stormwater management wisdom; and (3) Resilient communities should not only pay attention to the construction of non-engineering disaster prevention measures, but also to the application of small-scale green infrastructure oriented toward stormwater management.     

择优法降水集合预报试验的研究

基于集合平均预报方法的基础上，提出了择优法降水集合预报方法，以多物理过程集合预报系统为例，对该方法进行阐述和试验。利用集合预报系统各成员过去24 h预报的500 hPa和700 hPa温度差（T500-700）与实况温度差的相关系数作为集合预报成员的筛选因子，选择相关系数较大的成员作为集合成员进行降水集合预报试验。初步试验结果表明，择优法降水集合预报要略优于集合平均法的预报，24 h降水集合预报有所改善。择优法降水集合预报简单易行，在计算资源有限的情况下，可优先计算择优的成员，因此比集合平均法节约计算时间，提高集合预报时效，具有一定的业务应用价值。     

溶藻弧菌HY9901血红素结合蛋白HutB的原核表达及纯化

为探究溶藻弧菌(Vibrio alginolyticus)HY9901血红素结合蛋白HutB作为疫苗候选抗原的可能性,采用PCR方法扩增V.alginolyticus HY9901 hutB基因全长序列,克隆到pMD18-T载体,经双酶切、连接后,定向插入到pET-28a(+)中,构建原核表达载体pET-HutB,转入大肠杆菌BL21(DE3)中进行IPTG诱导表达。SDS-PAGE验证后,优化诱导表达条件和纯化条件,并进行Western-blot分析。结果表明,HutB蛋白在E.coli中诱导表达的最优条件:0.4 mmol/L IPTG,37℃诱导4h,表达的蛋白分子量与预期大小相符,主要以包涵体的形式存在,300 mmol/L咪唑洗脱时效果最佳,能与鼠抗His-tag单抗特异性结合。     

利用Vicon系统进行IMU标定

针对传统IMU标定方法操作复杂、过于依赖转台的问题,本文提出了一种利用Vicon系统进行IMU标定的方法。首先,利用预积分技术将IMU数据与Vicon数据融合,得到IMU残差;然后,将Vicon相邻帧间的状态量相减,得到Vicon残差;最后,将IMU残差和Vicon残差放到同一个状态向量中,并引入边缘化先验信息,建立非线性优化函数,求解得到陀螺仪和加速度计的零偏估计参数。同时本文设计EuRoc数据集测试试验和室内定位对比试验,结果表明,该方法对IMU的标定结果优于传统方法的标定结果,具有更高的精度。     

小波去噪的灰色最小二乘支持向量机变形预测

针对变形监测数据的随机性和非平稳性,以及单一预测模型的不足,该文提出了基于小波去噪的灰色最小二乘支持向量机变形预测模型。采用小波去噪对原始数据进行降噪处理,减弱数据随机扰动的影响,建立灰色最小二乘支持向量机模型,并采用粒子群算法寻找最优参数。通过大坝位移监测数据实例对模型进行验证,并与灰色模型、最小二乘支持向量机以及灰色最小二乘支持向量机进行对比分析。实验结果证明,该模型预测精度更高、稳定性更强。     

混沌蜂群优化的NSST域多光谱与全色图像融合

为有效融合多光谱图像的光谱信息和全色图像的空间细节信息,提出了一种基于混沌蜂群优化和改进脉冲耦合神经网络(PCNN)的非下采样Shearlet变换(NSST)域图像融合方法。首先对多光谱图像进行Intensity-HueSaturation(IHS)变换,全色图像的直方图按照多光谱图像亮度分量的直方图进行匹配;然后分别对多光谱图像的亮度分量和新全色图像进行NSST变换,对低频分量使用改进加权融合算法进行融合,以互信息作为适应度函数,利用混沌蜂群算法找到最优加权系数。对高频分量采用改进脉冲耦合神经网络(PCNN)方法进行融合,再经NSST逆变换和IHS逆变换得到融合图像。本文方法在主观视觉效果和信息熵、光谱扭曲度等客观定量评价指标上优于基于IHS变换、基于非下采样Contourlet变换(NSCT)和非负矩阵分解(NMF)、基于NSCT和PCNN等5种融合方法。本文方法在提升图像空间分辨率的同时,有效地保留了光谱信息。     

日本熊本地区高频衰减参数κ与Vs30统计研究

地震工程学中高频衰减参数κ是一个重要的参数。距离为0 km处的参数κ₀在地震动模拟中最常用,其主要控制傅里叶谱在高频部分的衰减特征。计算了日本熊本地区矩震级M_w为5.0~7.1级且震中距小于250 km的81个台站水平方向的κ和V_s30（距离地表30 m深度的平均剪切波速）。在不同矩震级和不同场地距离下,用线性拟合和二次拟合统计了κ与V_s30的关系,并与全球平均水平进行了比较。结果表明:κ与V_s30呈很强的负相关性,相关性随矩震级的增大而增大,且熊本地区的κ要高于全球平均水平。矩震级较小时,二次拟合的效果好于线性拟合,建议用二次拟合的经验关系式进行κ或V_s30的估计。近场情况下,κ总体要小于远场,线性拟合与二次拟合的效果差异不大。对C类场地,拟合的κ与全球平均水平较接近。对B类场地,拟合的κ高于全球平均水平。远场情况下,二次拟合的效果好于线性拟合,但对B类和C类场地,κ均小于全球平均水平。本文的研究结果既能在随机模拟方法中结合场地的地壳放大使用来达到提高模拟精度的目的,又能为只有钻孔信息的地区提供κ的估计。     

基于支持向量机的2021年2月13日日本福岛近海Mj7.3级地震震级估算

2021年2月13日日本福岛县近海发生M_j7.3级地震,触发了日本气象厅地震预警系统,系统在首台触发后5.6s发出震级为M_j6.3级的预警第1报,首台触发后10s对公众发布警报、预警震级为M_j6.4级。基于多类型特征参数输入的机器学习支持向量机震级估算模型（SVM-M）,利用2021年2月13日日本福岛县近海M_j7.3级地震获取的日本K-net强震动观测数据,分析SVM-M模型在该次地震中首台触发初期（首台触发后1~10s）的震级估算效能。结果表明:SVM-M震级估算模型,在首台触发后1s即可给出M_j6.3级的震级估算结果,与日本气象厅在首台触发后5.6s发布的预警第1报震级相同;随着时间窗的增加,首台触发后5s和10s,SVM-M模型的震级估算结果分别是M_j6.7级和M_j6.6级,均大于日本气象厅首台触发后10s对公众发布警报的预警震级。该次地震的离线模拟结果表明:SVM-M模型可在地震发生初期有效提高地震预警震级确定的准确性和时效性。     

多数据源三维量测技术在输电线路勘测设计中的应用

本文介绍构建以全数字摄影测量、高分辨率遥感卫星影像、地形图等多数据源为基础,通过立体匹配技术生成大场景三维立体量测平台,为输电线路优化选线提供强大的技术支撑,实现输电线路勘测设计作业流程的创新.