Minimum MSE Weights of Adjusted Summary Estimator of Risk Difference in Multi-Center Studies

The simple adjusted estimator of risk difference in each center is easy constructed by adding a value c on the number of successes and on the number of failures in each arm of the proportion estimator. Assessing a treatment effect in multi-center studies, we propose minimum MSE (mean square error) weights of an adjusted summary estimate of risk difference under the assumption of a constant of common risk difference over all centers. To evaluate the performance of the proposed weights, we compare not only in terms of estimation based on bias, variance, and MSE with two other conventional weights, such as the Cochran-Mantel-Haenszel weights and the inverse variance (weighted least square) weights, but also we compare the potential tests based on the type I error probability and the power of test in a variety of situations. The results illustrate that the proposed weights in terms of point estimation and hypothesis testing perform well and should be recommended to use as an alternative choice. Finally, two applications are illustrated for the practical use.

Cost-Aware Multi-Domain Virtual Data Center Embedding

Virtual data center is a new form of cloud computing concept applied to data center. As one of the most important challenges, virtual data center embedding problem has attracted much attention from researchers. In data centers, energy issue is very important for the reality that data center energy consumption has increased by dozens of times in the last decade. In this paper, we are concerned about the cost-aware multi-domain virtual data center embedding problem. In order to solve this problem, this paper first addresses the energy consumption model. The model includes the energy consumption model of the virtual machine node and the virtual switch node, to quantify the energy consumption in the virtual data center embedding process. Based on the energy consumption model above, this paper presents a heuristic algorithm for cost-aware multi-domain virtual data center embedding. The algorithm consists of two steps: inter-domain embedding and intra-domain embedding. Inter-domain virtual data center embedding refers to dividing virtual data center requests into several slices to select the appropriate single data center. Intra-domain virtual data center refers to embedding virtual data center requests in each data center. We first propose an inter-domain virtual data center embedding algorithm based on label propagation to select the appropriate single data center. We then propose a cost-aware virtual data center embedding algorithm to perform the intra-domain data center embedding. Extensive simulation results show that our proposed algorithm in this paper can effectively reduce the energy consumption while ensuring the success ratio of embedding.

Multi-Order and Multi-Center Metallogenic Zoning of Yinshan Cu-Au Polymetallic Ore Deposit,Jiangxi Province,China

Yinshan anticline is the product of tectono-dynamic deformation - metamorphism .Along the axis of the anticline exists a brittle-ductile shearing zone which obviously controls the ore-formation . Mineralization occurs along the axis of the anticline in a width of about 1000m .In the mining area .volcano- subvolcanic rocks of Early Yanshan period are divided into three cycles :Ⅰ intermediate acidic dacite lava and dacite porphyry ;Ⅱ acidic amphibole liparite and quartz porphyry;Ⅲ intermediate andesite porphyrite . Among them activities of ⅠandⅡ cycles are more intensive and are intimately related to the mineralization . Yinshan ore deposit is the result of combinative processes of tectono -dynamic and volcano -magmatic hydrothermal fluids, so that mere are two centers of metallogenic zoning, one being the axial strain zone of Yinshan anticline which is the center of first order, and the other being porphyry stock , 2nd order.

The Volume Effect and Safety of 6% Hydroxyethyl Starch 130/0.4 in Patients Undergoing Major Elective Surgery: An Uncontrolled, Open-Labeled, Multi-Center Study

Purpose: The primary aim of this study was to investigate volume effect and safety of up to 50 mL/kg BW 6% hydroxyethyl starch (HES) 130/0.4 in adult and pediatric patients undergoing major elective surgery. The need to infuse human albumin may be reduced or avoided in Japan if these large doses 6% HES 130/0.4 can be infused. Methods: The study was an uncontrolled, open-labeled, multi-center trial. Fifteen adult and 5 pediatric patients undergoing major elective surgery received 6% HES 130/0.4 (Voluven&#174) with a maximum dose of 50 mL/kg from the start of surgery until 2 hours after the end of surgery according to a treatment algorithm. The primary efficacy endpoint was the volume effect of 6% HES 130/0.4 determined by the volume of saved albumin during the investigational period and the time course of hemodynamic stability in adult and pediatric patients. Safety parameters were fluid balance, hemodynamic and laboratory parameters ECG, local and systemic tolerance and adverse events. Results: Adult patients received a mean of 32.0 mL/kg of 6% HES 130/0.4. For 12 out of 15 adult patients an average amount of 1033.8 mL (18.6 mL/kg) albumin could be saved. The other 3 adult patients did not receive more than 1000 mL of HES 130/0.4. All pediatric patients received approximately 50 mL/kg of HES 130/0.4;for these patients an average amount of 39.9 mL/kg body weight albumin could be saved. The majority of adult patients, and all pediatric patients were hemodynamically stable at all 3 time points. The observed changes of the assessed laboratory parameters including hematological and coagulation parameters or in any other safety parameter determined did not reveal any safety concern related to the administration of 6% HES 130/0.4 up to doses of 50 mL/kg body weight. Conclusion: The study results indicate that 6% HES 130/0.4 has a reliable volume effect, could contribute to significant human albumin savings and was safe and well tolerated up to a maximum dose of 50 mL/kg body weight in adult and pediatric patients undergoing major elective surgery.

METHOD OF CENTERS ALGORITHM FORMULTI-OBJECTIVE PROGRAMMING PROBLEMS

In this paper, we consider a method of centers for solving multi-objective programming problems, where the objective functions involved are concave functions and the set of feasible points is convex. The algorithm is defined so that the sub-problems that must be solved during its execution may be solved by finite-step procedures. Conditions are given under which the algorithm generates sequences of feasible points and constraint multiplier vectors that have accumulation points satisfying the KKT conditions. Finally, we establish convergence of the proposed method of centers algorithm for solving multiobjective programming problems.

SOPA:Source Routing Based Packet-Level Multi-Path Routing in Data Center Networks

Many ＂rich - connected＂ topologies with multiple parallel paths between smwers have been proposed for data center networks recently to provide high bisection bandwidth, but it re mains challenging to fully utilize the high network capacity by appropriate multi- path routing algorithms. As flow-level path splitting may lead to trafl＇ic imbalance between paths due to flow- size difference, packet-level path splitting attracts more attention lately, which spreads packets from flows into multiple available paths and significantly improves link utilizations. However, it may cause packet reordering, confusing the TCP congestion control algorithm and lowering the throughput of flows. In this paper, we design a novel packetlevel multi-path routing scheme called SOPA, which leverag- es OpenFlow to perform packet-level path splitting in a round- robin fashion, and hence significantly mitigates the packet reordering problem and improves the network throughput. Moreover, SOPA leverages the topological feature of data center networks to encode a very small number of switches along the path into the packet header, resulting in very light overhead. Compared with random packet spraying （RPS）, Hedera and equal-cost multi-path routing （ECMP）, our simulations demonstrate that SOPA achieves 29.87%, 50.41% and 77.74% higher network throughput respectively under permutation workload, and reduces average data transfer completion time by 53.65%, 343.31% and 348.25% respectively under production workload.

多中心协同治理:何以可能,何以可为?——基于江苏C县农村人居环境治理的经验诠释

从多中心协同治理的理论逻辑出发,构建“政府、企业、村民、社会组织”多中心主体下的协同治理机制,聚焦主体之间互动关系的生成机制和运行逻辑,并以江苏省C县农村人居环境的治理实践作为典型案例进行解析。研究表明,多中心协同治理是一种节本增效且具备操作性的治理方案,具备中国乡村场域的现实支撑,即主要通过沟通协作、资源整合、目标耦合以及利益联结,明确治理体系中各主体的功能定位,进而对行政规制、市场经济、村民自治、社会参与等进行界定分工,由此有效调动各方的积极性和能动性,实现激励相容与优势互补,最终形成治理合力。

“里和”与“外应”:气候变化下环湖地区的适应性治理

气候变化给青藏高原带来显著影响,更是对当地农牧民的生计造成冲击,研究当地气候变化影响及牧民应对策略,不仅是提高气候变化适应能力的起点,也是建立适应气候变化区域格局的重要支撑。基于2020和2023年对案例地Z村的两次实地调研,通过牧户问卷调查和深度访谈,按照适应性治理的三层特征,分析当地气候变化适应的成效与挑战。研究发现:面对降水和气温的变化、湖面扩大、植被变化和灾害影响,牧民积极采取多种办法来减少气候变化的影响,呈现较高的适应性与恢复力。这些适应行动的成功经验源于“里和”,包括人与人之间的合作以及人与自然间的和谐律动。但是“外应”不足仍是挑战,即案例地缺少必要的外部支持,不仅包括直接灾害救助,还包括对其适应能力可持续性的保护和应对潜在的草原生态变化。如果“外应”持续低迷,现有的适应能力终会耗尽。提出建立适应气候变化区域格局应遵循多中心治理的思路,将多个利益相关者联合起来,汇总不同地区气候变化应对的成功经验,形成多种知识的融合,才能形成对地方的有效“外应”,提高中国气候变化适应能力。

多中心产业共治的区域现代产业集群建设策略——以广东省精密仪器设备产业集群为例

在国际高端技术封锁日益严峻的新形势下,从任务解构的角度将区域现代产业集群建设进行分层任务细化尤为重要,且需要从目标需求导向的角度出发,针对具体分层任务明确多元治理主体的结构关系及对应主体的治理举措。基于现代产业体系的内涵特征提出区域现代产业集群建设逻辑,并基于多中心治理理论构建多中心产业共治建设区域现代产业集群的理论框架。研究认为,面向区域现代产业集群建设的战略层、发展层、支撑层等五大分层建设任务,政府部门、企业、科研机构、行业协会与服务机构等多元主体通过自发互动博弈,形成分类主导的多中心产业共治模式。为进一步阐述及试验理论,以广东省精密仪器设备产业集群主导咨询机构的集群治理为实践案例,认为其存在多中心联动的积极性和共治模式均有待加强的问题,且关键核心技术短缺问题较为突出。针对此,提出健全多中心联动协调工作机制、政企双中心共治提升产业安全度、多维支撑中心有序推进关键核心技术攻关、政府牵引多中心集聚融通、数字治理创新助推区域产业集群智慧建设等共治效能提升的建议。

基于云数据中心的多源异构数据治理技术研究

目前常规的多源异构数据治理方法主要通过对数据属性进行判断,从而实现分区域数据清洗,由于缺乏对非线性数据的分析,导致治理性能不佳;对此,提出基于云数据中心的多源异构数据治理技术;采用关系型数据库中的ETL功能对数据进行清洗,对数据转换模式以及数据清洗规则进行定义;引入互信息系数对数据相关程度进行判定,并进行非线性数据相关性分析;以云数据中心作为载体,对多源异构数据治理体系进行构建;在实验中,对提出的数据治理技术进行了治理性能的检验;最终的实验结果表明,提出的数据治理技术具备较高的查准率,对云数据中心多源异构数据具备较为理想的数据治理效果。

基于Isight的可变角度主轴刀柄机构设计与优化

为实现基于三轴数控加工中心的四轴数控加工功能,文中提出了一种可变角度主轴刀柄机构,其具有低成本的多轴化数控功能升级技术优势。首先,完成可变角度主轴刀柄机构的结构设计,并建立该机构的运动学模型;其次,基于ADAMS∕View建立可变角度主轴刀柄机构的参数化模型,并通过Isight平台搭建多目标优化设计流程,以主动臂平均扭矩、主动臂转角及连杆总长度为优化目标,采用NSGA-Ⅱ算法进行多目标优化设计。数值算例的结果表明:相较于原始方案,优化后主动臂平均扭矩减小了15.5%,连杆总长度减小了11.3%,且机构内各部件在运动中不发生结构干涉。因此,基于Isight平台对可变角度主轴刀柄机构进行多目标优化设计的方法是可行的,优化后的机构具有更加合理的尺寸参数,可最大限度地发挥可变角度主轴刀柄机构的动力性和经济性。

Multi-Hazard Evaluation Using Cluster Analysis—For Designated Evacuation Centers of Yokohama

Hazard maps are usually prepared for each disaster, including seismic hazard maps, flood hazard maps, and landslide hazard maps. However, when the general public attempts to check their own disaster risk, most are likely not aware of the specific types of disaster. So, first of all, we need to know what kinds of hazards are important. However, the information that integrates multiple hazards is not well maintained, and there are few such studies. On the other hand, in Japan, a lot of hazard information is being released on the Internet. So, we summarized and assessed hazard data that can be accessed online regarding shelters (where evacuees live during disasters) and their catchments (areas assigned to each shelter) in Yokohama City, Kanagawa Prefecture. Based on the results, we investigated whether a grouping by cluster analysis would allow for multi-hazard assessment. We used four natural disasters (seismic, flood, tsunami, sediment disaster) and six parameters of other population and senior population. However, since the characteristics of the population and the senior population were almost the same, only population data was used in the final examination. From the cluster analysis, it was found that it is appropriate to group the designated evacuation centers in Yokohama City into six groups. In addition, each of the six groups was found to have explainable characteristics, confirming the effectiveness of multi-hazard creation using cluster analysis. For example, we divided, all hazards are low, both flood and Seismic hazards are high, sediment hazards are high, etc. In many Japanese cities, disaster prevention measures have been constructed in consideration of ground hazards, mainly for earthquake disasters. In this paper, we confirmed the consistency between the evaluation results of the multi-hazard evaluated here and the existing ground hazard map and examined the usefulness of the designated evacuation center. Finally, the validity was confirmed by comparing this result with the ground hazard based on the actual measurement by the past research. In places where the seismic hazard is large, the two are consistent with the fact that the easiness of shaking by actual measurement is also large.

多元主体参与高职院校创新创业教育的行动路径

随着“大众创业,万众创新”国家战略的实施,高职院校创新创业教育已成为推动经济社会发展的新引擎。在高职院校创新创业教育中,政府、社会力量和高职院校等参与主体围绕公共利益最大化的共同目标履行各自职能。各参与主体都有自身的利益诉求,当以自身利益最大化思维参与创新创业教育时,会出现局部利益凌驾于整体利益之上的问题,使创新创业教育出现主体不在场或缺位现象。为了实现高职院校创新创业教育良性发展,应建立多中心治理架构下的创新创业教育参与模式,从强化政府引领与支持、推动校企融合与共振、提升学校教育水平与培养能力等方面构建创新创业教育路径。

临床研究中心价值共创模式与运行机制研究

通过对从事临床研究相关人员的半结构访谈和二手数据以及案例研究,构建临床研究中心多主体价值共创模式;基于英美两国临床研究机构的案例研究建立临床研究中心价值共创运行机制,为中国推进临床研究中心体系建设提供理论指导和实践启示。研究发现,我国在国家重大专项支持和引导下,在资源共享、利益共享的原则下,建构以学科交叉和社会合作为内涵的多主体价值共创模式,建立决策、协同、评审和转化的运行机制,是实现我国临床研究能力和诊疗水平提升的关键。

基于多视数据重构损失标定的叶片型面光学检测

航发叶片型面检测是保证叶片加工质量、工作性能和使用寿命的关键环节。对此,该文开发一套基于线激光器的叶片型面检测平台;在完成线激光器与叶片相对位姿校准及Z向测量基准建立基础上,实现叶片型面特定截面处型线数据的多视采集;提出一种基于多视数据重构损失标定回转中心的型线重构方法。以两种典型燃气轮机导向叶片为检测对象,所提出方法获取的检测数据与三坐标测量机检测数据的对比结果表明,轮廓度检测平均绝对偏差在0.022 mm以内,最大标准偏差为0.0186 mm,最大RMS估计为0.0251 mm;特征参数检测最大偏差为0.0401mm。实验结果验证了所提出方法面向叶片型面检测的可行性。

含共享储能的数据中心微网群分布式优化调度

多个数据中心微网可联合成微网群以实现不同数据中心微网的资源联动和能量互补。首先,建立了含共享储能的数据中心微网群运行模型,考虑了不同数据中心微网间的功率交互、数据负载交互、碳配额交互及共享储能容量使用权分配等耦合约束。其次,提出了考虑时变容量使用权和旋转备用服务的共享储能容量分配与运行策略,以进一步提高共享储能的效能。然后,采用高斯混合模型对数据中心微网内可再生发电的预测误差概率分布进行精确拟合,并结合机会约束处理预测误差的不确定性。最后,通过交替方向乘子法实现各个数据中心微网的独立求解,并引入动态乘子更新策略和预测-矫正因子以提高算法的收敛性。所提模型与方法的有效性在仿真中得到验证。

“无线组网与性能测试”综合教学实验设计

针对综合实验中知识点融会贯通不够,工程性不强等问题,设计了“无线组网与性能测试”综合实验。以应急通信、军事演习为背景,涵盖环境勘察、链路预算、组网设计、性能测试、技术优化等环节,设置多层任务,逐步提升学生解决复杂问题的综合能力,培养学生不断探索的科学精神。紧跟通信行业发展,提出以“学生为中心”,采用“组内协作、组间较量”机制,创新任务驱动的PBL教学,构建“多维度、全方位”的评价机制。有助于学生专业知识的综合运用和工程素养与科学思维的培养,最终形成学生自身的知识架构,实现实验教学的“铸魂性、创新性、高阶性、挑战度”。

考虑速度时变的多配送中心医药冷链配送路径优化

随着医药冷链市场需求的迅速增长,越来越多的城市、企业采用多配送中心模式,因此研究多配送中心模式下的医药冷链路径优化以减少配送成本尤为重要。在实际配送过程中,由于交通拥堵问题,配送车辆无法保持恒定的速度,进而可能导致配送成本的增加。基于此,构建考虑时变速度的多配送中心医药冷链物流路径优化模型,并结合遗传算法与粒子群算法对模型进行求解。通过数值算例的结果表明了模型的合理性和算法的有效性。

设备故障下的零空闲多设备工作中心调度

设备故障是车间调度中最为常见的动态事件,易对原生产调度计划造成影响。为保证加工生产在遇到设备故障后能够快速地对原调度方案做出调整,降低设备故障所带来的负面影响,对设备故障下的零空闲多设备工作中心调度问题进行研究。建立了设备故障下考虑调整时间和搬运时间的零空闲多设备工作中心调度模型,优化目标为最小化最大完工时间、搬运次数和系统稳定性;设计NSGA-Ⅱ-V算法用于原调度和重调度的求解;基于NSGA-Ⅱ-V获得的静态调度结果与部分重调度策略的思想,进行设备故障算例测试。测试结果表明,所提模型和算法可较好地处理动态事件为设备故障的零空闲多设备工作中心调度问题。

维持性血液透析患者发生无症状脑梗死风险预测模型的建立及验证:一项多中心研究

背景维持性血液透析(MHD)患者具有较高无症状脑梗死(SBI)发病率,且是症状性脑梗死和血管性痴呆的临床前阶段。因此非常有必要探讨MHD患者SBI风险,以早期识别并减少不良预后。目的探讨MHD患者发生SBI的危险因素,构建预测模型并评价其效能。方法纳入2017年1月—2022年10月4个中心(川北医学院附属南充市中心医院、广元市中心医院、遂宁市中心医院、蓬安县人民医院)的486例MHD患者。以MHD患者是否发生SBI为结局事件,分为SBI组(n=102)和非SBI组(n=384),比较两组研究对象的基线特征。按照7∶3的比例将患者随机分为建模集(n=340)和验证集(n=146)。通过LASSO回归和多因素Logistic回归分析确定预测变量,构建MHD患者发生SBI的风险预测模型并绘制列线图;采用受试者工作特征(ROC)曲线下面积、校准曲线和决策曲线分析评估模型的预测性能、准确性和临床应用价值。结果建模集70例(20.6%)MHD患者发生SBI,验证集32例(21.9%)患者发生SBI。LASSO回归结合多因素Logistic回归分析结果显示,年龄(OR=1.027,95%CI=1.005~1.050)、饮酒史(OR=4.487,95%CI=2.075~9.706)、BMI(OR=1.082,95%CI=1.011~1.156)、睡眠时间<5 h/d或>9 h/d(OR=6.286,95%CI=3.560~11.282)、慢性病史(慢性阻塞性肺疾病、糖尿病、慢性乙肝)(OR=1.873,95%CI=1.067~3.347)、血清乳酸水平(OR=1.452,95%CI=1.152~1.897)、尿素清除率(URR)(OR=0.922,95%CI=0.875~0.970)和抗血小板药用药史(OR=0.149,95%CI=0.030~0.490)是MHD患者发生SBI的独立影响因素(P<0.05)。构建包含上述8个影响因素的预测模型并绘制列线图。该预测模型在建模集和验证集的ROC曲线下面积分别为0.816(95%CI=0.759~0.873)和0.808(95%CI=0.723~0.893),校准曲线表现出良好的一致性。DCA曲线提示该模型可使患者获得最大临床收益。结论基于年龄、饮酒史、BMI、睡眠不足或睡眠过长、慢性病史(慢性阻塞性肺疾病、糖尿病、慢性乙肝)、血清乳酸水平、URR和抗血小板药用药史建立的MHD患者发生SBI风险预测模型有较好的预测效能和临床实用性,有望对MHD患者发生SBI风险进行准确、个性化的评估并实施早期干预以降低发病率。