增进学生身心健康是我国学校体育发展的根本和方向——学习贯彻习近平总书记在全国教育大会上的重要讲话精神

2018年9月10日，习近平总书记在全国教育大会上强调：“要树立健康第一的教育理念，开齐开足体育课，帮助学生在体育锻炼中享受乐趣、增强体质、健全人格、锤炼意志。”这为我国未来学校体育的发展指明了方向。学校体育要认真贯彻落实习近平总书记的重要讲话精神，把增进学生的身心健康作为学校体育工作的出发点和落脚点，切实提高学生的身心健康水平，促进学生全面发展。本文首先阐述了习近平总书记重要讲话精神的核心要义，以及所体现的以人为本的思想、高度重视把学生的健康放在首位、非常关注学生的身心协调发展等。其次，就如何落实习近平总书记的重要讲话精神提出了建设性意见：必须开齐开足体育课，保证校内外锻炼时间；提高体育课和课外体育活动的教育教学质量，加强学生的运动效果；“五育”并重，将学校体育纳入学校教育质量评价的重要组成部分；体育教师应树立强烈的社会责任感和使命感等措施和建议。     

泌阳凹陷泌301 井区不同流动单元产能分析

在沉积微相、储层物性特征分析的基础上，选取孔隙度、渗透率、流动带指数等参数，对泌阳凹陷赵凹油田泌301 井区核三段油层组进行流动单元划分。依据流动带指数的大小，将研究区目的层段划分为A、B、C、D 和E 等5 类流动单元。通过研究发现，各类流动单元与物性、岩性、沉积微相之间具有较好的对应关系，同时对不同流动单元产能进行了分析。研究结果表明，流动单元的划分能够真实客观地反映储层物性差、非均质性强的地质特点，单井产能与流动带指数有较好的乘幂关系，不同流动单元产能差异较为明显，物性最好的A 类流动单元产能最高，物性最差的E类流动单元产能最低。     

Multivariate Return Decomposition: Theory and Implications

In this paper, we propose a model based on multivariate decomposition of multiplicative – absolute values and signs – components of asset returns. In the m-variate case, the marginals for the m absolute values and the binary marginals for the m directions are linked through a 2m-dimensional copula. The approach is detailed in the case of a bivariate decomposition. We outline the construction of the likelihood function and the computation of different conditional measures. The finite-sample properties of the maximum likelihood estimator are assessed by simulation. An application to predicting bond returns illustrates the usefulness of the proposed method.     

儿童编程工具发展历程、特征及对未来教育路向的影响

摘 要：从1960年代LOGO的诞生开始,儿童编程经历了准备期、发展期、实施期、停滞期、复兴期五个时期的发展。总体特征是从复杂语法到简单语法、从抽象系统到可视化系统、从文本编程到非文本编程、从软件编程到物理编程。编程工具的不断发展和完善,让儿童学习编程成为可能。随着数字化社会的到来,编程教育将逐渐成为儿童教育中不可或缺的一部分,并将向下延伸到小学和幼儿园,其教育路向很可能朝学校化、普及化、低龄化发展。     

会计稳健性与自由现金流的代理成本:基于公司投资行为的考察

会计稳健性要求及时确认损失的发生、延时确认收益的发生.一般认为会计稳健性较高的公司,信息不对称程度低,具有较高的公司治理水平.本文从公司投资行为视角考察会计稳健性对自由现金流代理成本的影响.通过研究发现:非效率投资在我国企业普遍存在;高的会计稳健性具有抑制非效率投资的作用,并在一定程度上降低了自由现金流的代理成本.但要彻底解决非效率投资问题,仍需进一步规范公司的现金持有政策,并完善公司治理结构.本文的研究也为控制自由现金流的代理成本提供了一种可行性的解决方案.     

现金流不确定状态下财务指标IRR的应用探析

内含报酬率是目前评价项目可行性的主要指标之一,在应用时都是建立在对现金净流量值给出确切估计的基础上,但在实际经营活动中现金净流量存在着很多不确定性,往往是不能确切地估计出来。在此基础上考虑了各期现金流是概率排序型、各期现金净流量值是一个区间数以及各期现金净流量满足特定的概率分布这三种不确定状态下的IRR应用情形,使其能够更加贴近现实,提高项目评估的准确性。     

电子商务网站特征对心流体验的影响研究

文章基于文献回顾与深度访谈,提出了电子商务环境下网站特征对心流体验影响的研究模型.该模型聚焦于网站的互动性与生动性这两个主要特征对心流体验的影响作用.并通过问卷调查收集数据,运用层级回归分析法进行假设检验.研究发现:网站互动性与生动性对心流体验均有显著正向影响;网站互动性显著正向影响心流体验的控制、专注与好奇维度,而对愉悦维度没有显著影响;网站生动性对心流体验的控制、专注、好奇与愉悦四个维度均有显著正向影响.研究结果不仅丰富了在线心流体验理论,而且为电子商务企业提供了有益的借鉴.     

除尘器区低温省煤器烟道数值模拟

为实现除尘器区低温省煤器的节能改造,基于FLUENT6.3软件,对除尘器区低温省煤器烟道的流场进行数值模拟研究。研究结果表明:除尘器前烟道内流场严重不均,转弯处有明显的高速区与漩涡区,局部速度高达32 m/s;加装低温省煤器后,两低温省煤器内流场不均,最大速度偏差系数达79.3%,严重影响低温省煤器的换热效果,同时会磨损、冲刷低温省煤器管路,危及低温省煤器的安全;除尘器入口处出现大面积的低速区域,导致进入除尘器后流场紊乱、除尘器电耗高、除尘效率低等现象,除尘器前烟道内整流消涡可以根治除尘器工作效率的问题。     

Topological Performance Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems

Critical infrastructure systems must be both robust and resilient in order to ensure the functioning of society. To improve the performance of such systems, we often use risk and vulnerability analysis to find and address system weaknesses. A critical component of such analyses is the ability to accurately determine the negative consequences of various types of failures in the system. Numerous mathematical and simulation models exist that can be used to this end. However, there are relatively few studies comparing the implications of using different modeling approaches in the context of comprehensive risk analysis of critical infrastructures. In this article, we suggest a classification of these models, which span from simple topologically‐oriented models to advanced physical‐flow‐based models. Here, we focus on electric power systems and present a study aimed at understanding the tradeoffs between simplicity and fidelity in models used in the context of risk analysis. Specifically, the purpose of this article is to compare performance estimates achieved with a spectrum of approaches typically used for risk and vulnerability analysis of electric power systems and evaluate if more simplified topological measures can be combined using statistical methods to be used as a surrogate for physical flow models. The results of our work provide guidance as to appropriate models or combinations of models to use when analyzing large‐scale critical infrastructure systems, where simulation times quickly become insurmountable when using more advanced models, severely limiting the extent of analyses that can be performed.     

Optimization of Cascade‐Resilient Electrical Infrastructures and its Validation by Power Flow Modeling

Large‐scale outages on real‐world critical infrastructures, although infrequent, are increasingly disastrous to our society. In this article, we are primarily concerned with power transmission networks and we consider the problem of allocation of generation to distributors by rewiring links under the objectives of maximizing network resilience to cascading failure and minimizing investment costs. The combinatorial multiobjective optimization is carried out by a nondominated sorting binary differential evolution (NSBDE) algorithm. For each generators–distributors connection pattern considered in the NSBDE search, a computationally cheap, topological model of failure cascading in a complex network (named the Motter‐Lai [ML] model) is used to simulate and quantify network resilience to cascading failures initiated by targeted attacks. The results on the 400 kV French power transmission network case study show that the proposed method allows us to identify optimal patterns of generators–distributors connection that improve cascading resilience at an acceptable cost. To verify the realistic character of the results obtained by the NSBDE with the embedded ML topological model, a more realistic but also more computationally expensive model of cascading failures is adopted, based on optimal power flow (namely, the ORNL‐Pserc‐Alaska) model). The consistent results between the two models provide impetus for the use of topological, complex network theory models for analysis and optimization of large infrastructures against cascading failure with the advantages of simplicity, scalability, and low computational cost.