研究性学习中的心理学思想探析

研究性学习视学生为一个完整的人，注重学生个性的培养，重视学生潜能的开发以及整体素质的协调，这其中渗透着激发学生学习动机、使学生达到自我实现等心理学思想．该文对研究性学习的几个特点的心理学思想进行了分析。     

对体育教育专业篮球普修课教学现状的思考

通过对体育教育专业篮球普修课教学目标、教学内容、教学模式以及对学生的成绩评价进行思考和令尊，结合《全国普通高校学校体育教育本科专业课程方案》对培养目标的规定，提出了对体育教育专业篮球普修课的培养目标进行重新定位，优化教学内容、优化教学模式、优化教学手段、优化评价体系，培养出合格的21世纪体育教师。     

人性·人本·人化--人本管理的实质及其管理实现

管理理论的建构常常以某种人性假设为前提.对复杂人性本质的不同推定,决定着管理科学理论的不同走向.人本管理是一种有别于其他诸如"物本管理"、"资本管理"、"能本管理"等的管理理论,其不同之处或者说其进步性就在于它谋求对人的理解,即试图在对人性的种种假设中探寻"人"与人之"本"的内在逻辑,以建立一种"人为"与"为人"的柔性的管理规约.在我国特有的管理语境中,人本管理的本质与实现的理解是有其独特性的.在管理实践中,人不仅仅是手段,人本身也是目的.     

浅析法律文书语言的精确性与模糊性

法律文书由于具有很强的专业性,因而也就具有应用文书的一般写作特点,尤其在语言的精确性方面要求甚严,但模糊语言的恰当运用,同样能不偏不倚地准确表意,使文书能达到其基本地的使用目的。     

大学生学习焦虑心理研究

通过分析大学生学习焦虑心理的成因以及学习焦虑控制问题。论述了大学生学习焦虑心理与学习成绩的关系。     

基于语言偏好的群体决策的软解法

群体决策模型用于支持系统或专家系统，面临的两个问题是：自然语言与机器语言的匹配以及模型解与决策者意向交融．本文在许多学者大量工作的基础上，试图提出群决策的软化求解模型．主要提出两方面的结果：一是多准则语言偏好的综合；二是采用模糊匹配方法和语言变量的软算法将个人语言偏好聚集为群体可接受决策解．最后给出实例计算以说明操作步骤．该模型可用于人－机交流式ＧＤＳＳ或小群（７～１２人）会议支持系统的软件设计     

铜发光中心的分布和位错显微结构的关系

本文作者根据显著观测和发光光谱的测试结果表证实了在ＺｎＳ：Ｃｕ单晶中，蓝色铜发光中心及绿色铜发光中心的分布和位错线区域的横向与纵向的显著与纵向的显著结构有着固定的对应关系。     

Using genetically-defined rodent strains for the identification of hippocampal traits relevant for two-way avoidance behavior: a non-invasive approach

Summary Genetically-defined rodent strains permit the identification of hippocampal traits which are of functional relevance for the performance of two-way avoidance behavior. This is exemplified here by analyzing the relationship between infrapyramidal mossy fibers (a tiny projection terminating upon the basal dendrites of hippocampal pyramidal neurons) and two-way avoidance learning in about 800 animals. The necessary steps include 1) identification of structural traits sensitive to selective breeding for extremes in two-way avoidance, 2) testing the robustness of the associations found by studying individual and genetical correlations between hippocampal traits and behavior, 3) establishing causal relationships by Mendelian crossing of strains with extreme structural traits and studying the behavioral consequences of such structural randomization, 4) confirming causal relationships by manipulating the structural variable in inbred (isogenic) strains, thereby eliminating the possibility of genetic linkage, and 5) ruling out the possibility of spurious associations by studying the correlations between the hippocampal trait and other behaviors known to depend on hippocampal functioning.In comparison with the classical lesion approach for identifying relationships between brain and behavior, the present procedure appears to be superior in two aspects: it is non-invasive, and it focuses automatically on those brain traits which are used by natural selection to shape behaviorally-defined animal populations, i.e., it reveals the natural regulators of behavior.     

Biological role of major transplantation antigens in T cell self-recognition

Summary The proposal is made, illustrated and supported by experimental evidence that T cell-mediated immunopathology triggered initially by low- or non-cytopathic infectious agents may cause diseases, susceptibility to which is linked to the major histocompatibility gene complex.This summary is an updated version of the paper given on the occasion of the Paul Ehrlich Prize ceremonies in 1983; it was also presented at the meeting New Trends in Allergy II in München 1985, and is reproduced here with the permission of Springer Verlag, Heidelberg.     

Learning attention-based strategies to cooperate for multi-agent path finding

Multi-agent path finding (MAPF) is a challenging multi-agent systems problem where all agents are required to effectively reach their goals concurrently with not colliding with each other and avoiding obstacles. In MAPF, it is a challenge to effectively express the observation of agents, utilize historical information, and effectively communicate with neighbor agents. To tackle these issues, in this work, we proposed a well-designed model that utilizes the local states of nearby agents and outputs an optimal action for each agent to execute. We build the local observation encoder by using residual attention CNN to extract local observations and use the Transformer architecture to build an interaction layer to combine local observations of agents. With the purpose of overcoming the deficiency of success rate, we also designed a new evaluation index, namely extra time rate (ETR). The experimental results show that our model is superior to most previous models in terms of success rate and ETR. In addition, we also completed the ablation study on the model, and the effectiveness of each component of the model was proved.