第九章 心理健康问题 第十章 体育鍛炼与社会健康 第十一章 体育鍛炼与环境 第十二章 段炼与心血管疾病的防止 第十五章 运动损伤的预防和康复

6.1 核电装置的失效分析 6.2 火电装置的失效分析 6.3 风电设备的失效分析 6.4 石化装置的失效分析 6.5 化工设备的失效分析 6.6 冶金设备的失效分析 6.7 交通部件的失效分析 6.8 电子电路的失效分析 6.9 城市管网的失效分析

4.1 概述 4.2 磨粒磨损 4.3 粘着磨损 4.4 冲刷磨损 4.5 微动磨损 4.6 疲劳磨损 4.7 腐蚀磨损 4.8 气蚀 4.9 耐磨耐蚀复合管道的研发及应用

以人为中心的健康照顾是全科医学的基本特征，全科医生应当采用生物-心理-社会模式来开展全科的医疗、预防、保健、康复等卫生服务。全科医师在诊疗工作中首先要确认和解决病人的现患问题，同时管理病人连续性的健康照顾问题，并为病人及其家庭提供健康及预防疾病方面的建议，从而改变病人的求医遵医行为

糖尿病是一组由于胰岛素分泌缺陷及(或)其生物效应降低(胰岛素抵抗)引起的以高血糖为特征的慢性、全身性代谢疾病。 慢性高血糖将导致人体多组织、尤其是眼、肾、神经和心血管的长期损害、功能不全和衰竭，导致残废和早亡

第一节 肾的功能解剖和肾血流量 第二节 肾小球的滤过机能 第三节 肾小管与集合管的转运功能 第四节 尿液的浓缩和稀释

2.1 Understand the nature of data as it relates to business intelligence (BI) and analytics 2.2 Learn the methods used to make real-world data analytics ready 2.3 Describe statistical modeling and its relationship to business analytics 2.4 Learn about descriptive and inferential statistics 2.5 Define business reporting, and understand its historical evolution

3.1 Understand the basic definitions and concepts of data warehousing 3.2 Understand data warehousing architectures 3.3 Describe the processes used in developing and managing data warehouses 3.4 Explain data warehousing operations 3.5 Explain the role of data warehouses in decision support

4.1 Define data mining as an enabling technology for business analytics 4.2 Understand the objectives and benefits of data mining 4.3 Become familiar with the wide range of applications of data mining 4.4 Learn the standardized data mining processes 4.5 Learn different methods and algorithms of data mining 4.6 Build awareness of the existing data mining software tools 4.7 Understand the privacy issues, pitfalls, and myths of data mining

6.1 Understand the applications of prescriptive analytics techniques in combination with reporting and predictive analytics 6.2 Understand the basic concepts of analytical decision modeling 6.3 Understand the concepts of analytical models for selected decision problems, including linear programming and simulation models for decision support 6.4 Describe how spreadsheets can be used for analytical modeling and solutions 6.5 Explain the basic concepts of optimization and when to use them 6.6 Describe how to structure a linear programming model 6.7 Explain what is meant by sensitivity analysis, what-if analysis, and goal seeking 6.8 Understand the concepts and applications of different types of simulation 6.9 Understand potential applications of discrete event simulation