Key Technologies for Decentralized Control Platform with Dynamic Evolution for Railway Transportation System

Key technologies as well as their principles were discussed for a decentralized control platform capable of dynamic evolution. The primary content includes the automatic decision-making mechanism and the algorithm of the control center migration, the principle and technology of system self-monitoring, the principle and technology of the switch-mode of remote control station, the information transmission technology, and the data consistency technology. These key technologies have shown a series of advanced characteristics for decentralized control platform.

A Machine Learning-Based Web Application for Heart Disease Prediction

This work leveraged predictive modeling techniques in machine learning (ML) to predict heart disease using a dataset sourced from the Center for Disease Control and Prevention in the US. The dataset was preprocessed and used to train five machine learning models: random forest, support vector machine, logistic regression, extreme gradient boosting and light gradient boosting. The goal was to use the best performing model to develop a web application capable of reliably predicting heart disease based on user-provided data. The extreme gradient boosting classifier provided the most reliable results with precision, recall and F1-score of 97%, 72%, and 83% respectively for Class 0 (no heart disease) and 21% (precision), 81% (recall) and 34% (F1-score) for Class 1 (heart disease). The model was further deployed as a web application.

A Novel Design Framework for Smart Operating Robot in Power System

This paper proposes the concept and framework of smart operating system based on the artificial intelligence(AI)techniques. The demands and the potential applications of AI technologies in power system control centers is discussed in the beginning of the paper. The discussion is based on the results of a field study in the Tianjin Power System Control Center in China. According to the study, one problem in power systems is that the power system analysis system in the control center is not fast and powerful enough to help the operators in time to deal with the incidents in the power system. Another issue in current power system control center is that the operation tickets are compiled manually by the operators, so that it is less efficient and human errors cannot be avoided. Based on these problems, a framework of the smart operating robot is proposed in this paper, which includes an intelligent power system analysis system and a smart operation ticket compiling system to solve the two problems in power system control centers. The proposed framework is mainly based on the AI techniques, especially the neural network with deep learning, since it is faster and more capable of dealing with the highly nonlinear and complex power system.

Thruster direction controlling of assembled spacecraft based on gimbal suspension

The attitude control system design and its control effect are affected considerably by the mass-property parameters of the spacecraft. In the mission of on-orbit servicing, as fuel is expended, or the payloads are added or removed, the center of mass will be changed in certain axe; consequently, some thrusters＇ directions are deviated from the center of mass（CM） in certain plane. The CM of assembled spacecraft estimation and thruster direction control are studied. Firstly, the attitude dynamics of the assembled spacecraft is established based on the Newton-Euler method. Secondly, the estimation can be identified by the least recursive squares algorithm. Then, a scheme to control the thrusters＇ directions is proposed. By using the gimbal installed at the end of the boom, the angle of the thruster is controlled by driving the gimbal; therefore, thrusters can be directed to the CM again. Finally, numerical simulations are used to verify this scheme. Results of the numerical simulations clearly show that this control scheme is rational and feasible.

省级疾病预防控制机构青年人才培养模式探究:以“青耕计划”为例

目的分析上海市疾病预防控制中心青年人才培养项目的实施现状与成效,提出切实可行的人才培养优化策略,以期进一步提升疾病预防控制人才培养能力,构建合理的人才梯队,激发科研活力。方法对上海市疾病预防控制中心获“青耕计划”资助的2批次共67名培养对象进行问卷调查,分析相关投入、产出情况及培养对象对该培养项目的意见建议等。结果“青耕计划”培养对象所在部门对其项目实施提供的支持和帮助很大。67名培养对象在培养期间共撰写中文论文74篇,中位数为1篇,共撰写英文论文14篇。共申报课题45次,获批课题共9项。共参加科普宣讲93次,撰写科普文章67篇,中位数为1篇。53.85%的培养对象确立了今后的研究方向,44.62%的培养对象明确了自己的职业规划,培养对象认为其业务能力和科研能力均有较大提升。结论作为青年人才的“第一桶金”,“青耕计划”对提升科研素养、熟悉科研流程、助力业务工作等方面均起到了很好的效果,建议从培养周期、支持力度、培训交流、导师遴选、资源共享、考核激励机制等方面对该人才培养计划进一步优化。

上海市疾病预防控制中心就业见习基地运行效果评估:基于结果链模型

目的 对上海市疾病预防控制中心针对高校毕业学年学生开展的就业见习基地运行效果进行评估,并就提升就业见习工作的效果提出政策建议。方法 构建基于结果链模型的评估指标体系,通过客观资料收集,并对2018—2022年的往届见习学员和带教老师,以及2022年末的在岗见习学员,开展满意度调查,分析和评估上海市疾病预防控制中心就业见习基地运行效果。在此基础上,提出改进就业见习工作的建议与措施。结果 基于结果链模型构建包括5个一级指标、14个二级指标、32个三级指标的评估指标体系,并对2018—2022年上海市疾病预防控制中心就业见习基地的运行效果进行评分,得分84.8分。其中,与上海市疾病预防控制中心就业见习基地相关的未得满分指标有:投入环节,管理体系中的组织架构;产出环节,基地产出中的见习岗位类别;结果环节,见习学员和带教老师的政策认知情况。结论 2018—2022年,上海市疾病预防控制中心就业见习基地运行情况良好,取得了一定的成效,但是仍存在不足。建议通过重视政策宣传,多渠道宣传上海市就业见习政策;完善组织架构,落实事前、事中、事后管理;拓展岗位类别,培养多类型公共卫生人才;延长见习期限,重视实践能力培养等措施加以改进。

Analysis of CDC’s Role in Public Health Emergencies

Objective:To explore the role of the Centers for Disease Control and Prevention(CDC)in public health emergencies.Methods:The details of 12 public health events that occurred between January 2021 to December 2022 were analyzed to explore the roles of the CDC.Results:There were 160 patients involved in 10 public health events in 2021 and 48 patients involved in 2 public health events in 2022.Besides,the proportion of school public health events in 2022 was 0%,which was lower than in 2021,which was 80%(P<0.05).99.38%of patients during public health events were sent to the hospital promptly in 2022,which was higher than that in 2021,which was 81.25%(P<0.05).Furthermore,the average time taken for the CDC to control public health events in 2022 was 20.11±1.62 hours,and the average time taken to send inspection reports was shorter than that in 2021.The public satisfaction score was also higher in 2022 compared to 2021(P<0.05).Conclusion:The role of the CDC is to control infectious diseases.Therefore,it is important to pinpoint the existing problems in the strategies implemented by the CDC so that more improvements can be made to better prevent infectious diseases.

北京市区级疾病预防控制中心机构设置和人员配置现状

目的了解北京市区级疾病预防控制中心(以下简称“疾控中心”)机构设置和人员配置现状。方法2020年4月,对北京市16家区级疾控中心进行调查,按照国家相关规范性文件要求,评价机构设置和人员配置的合理性。结果16家区级疾控中心在编总人数2196人,在编人数与辖区内常住人口的比例为(0.57~2.54)/万,业务科室数量占所有内设科室数量的比例为56%~81%,专业技术岗位在编人员比例为67%~94%,其中,12家区级疾控中心的在编人数与辖区内常住人口的比例未达到不低于1.75/万的要求,7家区级疾控中心的业务科室所占比例未达到不低于70%的要求,5家区级疾控中心专业技术岗位在编人员比例未达到不低于85%的要求。在编人员组成情况:男女比为1.0:1.8;30~<50岁人群比例占71%;文化程度以本科和硕士为主,占81%;专业以公共卫生和检验专业为主,占72%;职称以中级和初级为主,占73%。2017—2019年16家区级疾控中心共144人离职,以文化程度较高的初级和中级专业技术人员为主。结论北京市部分区级疾控中心机构设置、人员编制和专业技术人员构成未达到国家相关核定标准。部分区级疾控中心缺乏有较高文化程度的专业技术人才,人员结构不合理,同时存在人才引不来和留不住的双重问题。在疾病预防控制机构(以下简称“疾控机构”)改革中,应加强对全市区级疾控机构的统筹管理,统一机构设置,增加人员编制,优化人员结构,改革激励机制,确保薪酬水平,实现人才总量合理增长、队伍素质大幅提升、队伍结构更加优化的目标。

实现船舶稳性的多油舱自适应调度算法及仿真

针对油舱对船舶浮态与稳性的影响,研究了保持船舶稳性的多油舱自适应调度控制算法,并用WinCC(WindowsControlCenter)组态软件编写了船舶自动浮态调整仿真系统。在系统架构上,采用布尔逻辑表构建了油舱、泵、管路之间的连通关系,并根据浮态方程计算出舱群之间的调驳油量,再根据多变量多约束的自适应优化调度算法实现了油舱驳油过程中浮态的平衡。仿真结果表明调度算法可以对船舶的浮态进行有效调整,并保持船舶稳性,避免了由油舱油量分布不均给船舶带来的不利影响,保障了航行安全。

One disease, many faces-typical and atypical presentations of SARS-CoV-2 infection-related COVID-19 disease

Since the appearance of the novel coronavirus(severe acute respiratory syndrome-coronavirus-2)and related coronavirus disease 2019(COVID-19)in China in December 2019,a very high number of small and large patient series have been published in literature from around the world.Even though the classical presentation of COVID-19 is one with respiratory symptoms with or without pneumonia that can be self-limiting or evolve into severe respiratory distress syndrome with multiple organ failure,and secondary bacterial sepsis,a large body of evidence suggests a plethora of other types of clinical presentation.In this exhaustive review,we reviewed all of the published literature on COVID-19 to identify different types of clinical presentations affecting various organ systems,to provide an in-depth analysis that may prove useful for clinicians and health-workers on the frontline,battling the severe pandemic.

THE STRATEGY OF RESOURCE MANAGEMENT BASED ON GRID COMPUTING

This paper analyzes the defaults of traditional method according to the resource management method of grid computing based on virtual organization. It supports the concept to ameliorate the resource management with mobile agent and gives the ameliorated resource management model. Also pointed out is the methodology of ameliorating resource management and the way to realize in reality.

Opioid Prescriptions in Women: Is the Data Accurate?

Background: In 2012, U.S. health care providers wrote more than 259 million opioid prescriptions, which is twice as many as in 1998. Approximately 1 in 10 women report the use of opioids for pain management during pregnancy. The Centers for Disease Control and Prevention (CDC) estimated that between 2008 and 2012, 39% of reproductive-aged women on Medicaid had filled a prescription for opioid medication each year, as did 28% of women with private insurance. The opioid epidemic extends to the state of New Jersey (NJ);however, limited data is available regarding opioid prescriptions among Medicaid and private insurance patients within the state. Objective: Evaluate opioid prescriptions filled in reproductive-aged women presenting in labor at a community teaching hospital in suburban New Jersey. Methods: We performed a retrospective cohort study using data obtained from patient records and the New Jersey Prescription Monitoring Program (NJPMP) database. We enrolled 200 patients that were admitted in labor between May 2015 and May 2016. Data was collected from reproductive-aged women during the one year preceding labor admission. We compared our findings to national data reported by the CDC using Chi-square analysis. Maternal demographic data were extracted from patient records and included age, insurance status (private insurance, Medicaid, and no insurance), race, and ethnicity. The primary outcome was opioid prescriptions filled. Results: Of the 200 women admitted in labor, 129 had private insurance, 63 had Medicaid, and 8 had no insurance. We found that 5.4% (7/129) of patients with private insurance, 4.8% (3/63) of patients with Medicaid, and 12.5% (1/8) of patients with no insurance filled opioid prescriptions. Overall, 5.5% (11/200) of women filled opioid prescriptions during the study period. Opioid prescriptions confirmed via NJPMP were significantly lower than rates reported by the CDC in Medicaid (4.8% vs. 41.4%, p-value 0.001) and private insurance (5.4% vs. 29.1%, p-value < 0.001) patients, respectively. Conclusion: Rates of opioid prescriptions filled were lower among our suburban cohort of women in New Jersey than national rates reported by the CDC. We did not confirm that patients with Medicaid filled more prescriptions than patients with private insurance. These discrepancies raise the question of whether a federal prescription monitoring program would better capture data than state-wide programs. Further research is needed to ensure that prescription monitoring programs are actually capturing accurate data.

Exploration and practice of general practitioner responsibility system in an urban community of Shanghai

Objective:The Minhang district of Shanghai was selected as the subject and its public health management model was investigated.Methods:Minhang became a pilot location for the implementation of the general practitioner responsibility system(GPRS)in 2011.Since then,the management model of public health services in the district has gradually merged with the GPRS through a series of actions:the adjustment of organizations and the coordination mechanism in community public health services,the integration of basic public health services and clinic practice,the establishment of an informationized Internet service platform,comprehensive budgeting management of public health service programs,and performance assessment management of health workers.Results:By the end of 2014,the number of residents who had a contractual relationship with a general practitioner(GP)in Minhang had reached 1.4367 million and all of them had family health records.Compared with 2010,both the rate of maternal management and the rate of children management stayed at high level(≥96%),the rate of hypertension management increased(40.73%vs.28.70%),the rate of blood pressure control increased(82.13%vs.77.51%),the incidence of diabetes decreased(21.93%vs.37.85%),the rate of effective control of blood glucose for dia-betic patients increased(82.43%vs.62.77%),and the rate of child health management increased(99.79%vs.91.54%).Conclusion:The GPRS has helped to create a better community health environment.How-ever,the development of this system is limited by several factors,including the following:the shortage of GPs,most GPs do not have good public health service skills and a correct public health concept,unclear division of different services,and imperfect department coordination.

Optimal Threshold Policies for Robust Data Center Control

With the simultaneous rise of energy costs and demand for cloud computing, efficient control of data centers becomes crucial. In the data center control problem, one needs to plan at every time step how many servers to switch on or off in order to meet stochastic job arrivals while trying to minimize electricity consumption. This problem becomes particularly challenging when servers can be of various types and jobs from different classes can only be served by certain types of server, as it is often the case in real data centers. We model this problem as a robust Markov decision process(i.e., the transition function is not assumed to be known precisely). We give sufficient conditions(which seem to be reasonable and satisfied in practice) guaranteeing that an optimal threshold policy exists. This property can then be exploited in the design of an efficient solving method, which we provide.Finally, we present some experimental results demonstrating the practicability of our approach and compare with a previous related approach based on model predictive control.

Investigation and analysis of the biosafety awareness of laboratory staff involved in the detection of pathogens in seven provincial Centers for Disease Control and Prevention in China

This study aims to evaluate the biosafety awareness of laboratory staff working on pathogens detection in seven Centers for Disease Control and Prevention and support these staff's biosafety management and training.A total of 208 laboratory staff from seven provincial CDCs were chosen by stratified random sampling to undergo a self-administered questionnaire survey.The collected data were analyzed using SPSS 22.0.The overall average biosafety awareness of the CDC laboratory staff involved in pathogen detection was 82.5 points.The average biosafety awareness score was the highest in health monitoring(92.63 points)and the lowest in risk assessment and control(41.6 points).Among the seven provincial CDCs,the Guizhou Provincial Center for Disease Control and Prevention laboratory staff showed the lowest average biosafety awareness score(74.3 points).The team who worked for 5–14 years were more likely to score above the passing score(≥88 points;corrected OR 0.400,95%CI:0.168–0.951)than the staff with less than five years of work experience.In addition,the mid-level and junior-level staff,as well as the lower position ones were more likely to score below the passing score(<88 points;junior level and lower:corrected OR 3.473,95%CI:1.028–11.737;mid-level:corrected OR 2.797,95%CI:1.027–7.618)compared with the senior-level staff.Among the surveyed team,66.3%identified a lack of specific funds related to work,61.5%identified a lack of designated personnel for the laboratory biosafety management.The biosafety awareness in CDC laboratory staff involved in pathogen detection is low,especially regarding risk assessment and control.The biosafety awareness in Guizhou and Guangxi Provincial CDC laboratory staff is also low.Laboratory funding,job title,and years of experience in a laboratory influence biosafety awareness in CDC laboratory staff.The biosafety knowledge,education,and training of CDC laboratory staff involved in pathogen detection need to improve by paying attention to the content and coverage of biosafety training,exploring new training modalities,and increasing funding for activities related to biosafety in CDC.

Control Model of Bloom Dynamic Soft Reduction

There are significant effects of process parameters on internal qualities of bloom, and these process parameters are as follows. position and reduction amount, reduction distribution, reduction rate, and so on. Developing a control model is the key to apply soft reduction technology successfully. As the research object, 360 mm ×450 mm bloom caster in PISCO （Panzhihua Iron and Steel Co. ） has been studied, and the research method for control model of dynamic soft reduction has been proposed. On the basis of solidification and heat transfer model, the position of soft reduction and reduction distribution of each frame are determined according to the bloom temperature distribution and solid fraction in bloom center calculated. Production practice shows that the ratio of center porosity which is less than or equal to 1.0, increased to 97.27%, ratio of central segregation which is less than or equal to 0.5, increased to 80.91%, and ratio of central carbon segregation index which is more than or equal to 1.10, decreased to 4% with the applying model of dynamic soft reduction.

Distribution Control Centers in the US and Europe:Commonalities,Differences,and Lessons

The distribution control center(DCC)has evolved from a sideshow in the traditional distribution service center to a major centerpiece of the utility moving into the decentralized world.Mostly,this is the place where much of the action is happening due to new forms of energy that are coining into the distribution system.This creates the flexibility of operation and in-creased complexity due to the need for increased coordination between the transmission control center and DCC.However,the US and European utilities have adapted to this change in very different ways.Firstly,we describe the research works done in a DCC and their evolutions from the perspectives of major US utilities,and those enhanced by the European perspective focusing on the coordination of distribution system operator and transmission system operator(DSO-TSO).We pres-ent the insights into the systems used in these control centers and the role of vendors in their evolution.Throughout this paper,we present the perspectives of challenges,operational capabilities,and the involvement of various parties who will be re-sponsible to make the transition successful.Key differences are pointed out on how distribution operations are conducted between the US and Europe.