中医药学将走向何方

由于中医缺乏形态学,中医没有成熟的科学实验,中医的诊断很难标准化、客观化,理论逻辑的致命弱点,理论体系难以重构,所以中医药学在很长一段时间内将保留下来之后,随着中医药学的理论体系的缺陷无法克服,原有的中医药体系必然解体,其中有部分内容融入现代医学。中医药学的归宿就是逐渐融入现代医学。     

中国考试文化的古今嬗变与镜鉴

中国考试文化生态因社会环境、经济土壤、社会结构和国际环境影响而形成从保守封闭性向包容开放性转变的特征。本文从三个层面考察中国考试文化的当代嬗变： 考试观念文化从单一的政治情结向综合人文素质嬗变, 考试制度文化从僵化到创新嬗变, 考试行为文化则从场所、教学行为、主体、应试行为和实践行为考察。通过合理挖掘中国传统考试文化中的道德诉求与和谐理念, 力求凝练出一种具有深厚文化内涵和现代竞争意识的考试文化。     

工作记忆对时间加工的影响

非时间信息加工与时间加工的关系是复杂的, 存在双向干扰或单向干扰, 结果的不一致与任务所需的注意资源及工作记忆都有关。工作记忆的中央执行系统在时间加工中起主要作用, 同时进行的非时间任务对中央执行功能的需求越多, 两种任务之间的干扰程度越大。语言环和视空间模板对时间加工的影响与非时间信息的类型有关。工作记忆作为一个整体以工作记忆容量为指标, 计时成绩也表现出与工作记忆容量有关的年龄、智力等方面的差异。时间加工和工作记忆在额叶、顶叶、基底神经节等皮质存在共同的神经机制。未来应该丰富工作记忆的研究内容, 结合时间加工的分段性探讨工作记忆影响时间加工的具体进程及神经机制, 并力求在应用方面取得一定的成果。     

Changing the Criminal Justice System Response to Sexual Assault: An Empirical Study of a Participatory Action Research Project

In jurisdictions throughout the United States, thousands of sexual assault kits (SAKs; also known as a “rape kits”) have not been submitted by the police for forensic DNA testing. DNA evidence may be helpful to sexual assault investigations and prosecutions by identifying perpetrators, revealing serial offenders through DNA matches across cases, and exonerating those who have been wrongly accused. This paper describes a longitudinal action research project conducted in Detroit, Michigan after that city discovered approximately 11,000 untested sexual assault kits in a police department storage facility. We conducted a root cause analysis to examine individual, organizational, community, and societal factors that contributed to the development of the rape kit backlog in Detroit. Based on those findings, we implemented and evaluated structural changes to increase staffing, promote kit testing, and retrain police and prosecutors so that cases could be reopened for investigation and prosecution. As we conducted this work, we also studied how this action research project impacted the Detroit criminal justice system. Participating in this project changed stakeholders’ attitudes about the utility of research to address community problems, the usefulness of DNA evidence in sexual assault cases, and the impact of trauma on survivors. The results led to new protocols for SAK testing and police investigations, and new state legislation mandating SAK forensic DNA testing.     

Computer‐based training to teach observers to accurately score problem behavior using fast forwarding at 5x normal speed

The current study evaluated whether a computer‐based training program could improve observers' accuracy in scoring discrete instances of problem behavior at 5x normal speed using a multiple‐baseline design across subjects. During pretraining and posttraining, observers attempted to score multiple examples of problem behavior at 5.0x without feedback. During training, participants scored multiple examples of problem behavior at 5.0x with automated feedback. Researchers measured omission (missing problem behavior) and commission (scoring other behavior as problem behavior) errors and the total duration of scoring time to determine the observers' accuracy and efficiency, respectively. After training, all participants scored instances of problem behavior with less than 11% error using 5.0x. The time required to score the videos across 90‐min observations was reduced by 66%. Results extend previous evaluations of fast forwarding by demonstrating that the training program could be used to teach observers to accurately score problem behavior using a speed faster than 3.5x.     

Cogmic space for narrative-based world representation

Representing a world or a physical/social environment in an agent’s cognitive system is essential for creating human-like artificial intelligence. This study takes a story-centered approach to this issue. In this context, a story refers to an internal representation involving a narrative structure, which is assumed to be a common form of organizing past, present, future, and fictional events and situations. In the artificial intelligence field, a story or narrative is traditionally treated as a symbolic representation. However, a symbolic story representation is limited in its representational power to construct a rich world. For example, a symbolic story representation is unfit to handle the sensory/bodily dimension of a world. In search of a computational theory for narrative-based world representation, this study proposes the conceptual framework of a Cogmic Space for a comic strip-like representation of a world. In the proposed framework, a story is positioned as a mid-level representation, in which the conceptual and sensory/bodily dimensions of a world are unified. The events and their background situations that constitute a story are unified into a sequence of panels. Based on this structure, a representation (i.e., a story) and the represented environment are connected via an isomorphism of their temporal, spatial, and relational structures. Furthermore, the framework of a Cogmic Space is associated with the generative aspect of representations, which is conceptualized in terms of unconscious- and conscious-level processes/representations. Finally, a proof-of-concept implementation is presented to provide a concrete account of the proposed framework.     

Cognitive computing models for estimation of reference evapotranspiration: A review

Irrigation practices can be advanced by the aid of cognitive computing models. Repeated droughts, population expansion and the impact of global warming collectively impose rigorous restrictions over irrigation practices. Reference evapotranspiration (ET₀) is a vital factor to predict the crop water requirements based on climate data. There are many techniques available for the prediction of ET₀. An efficient ET₀ prediction model plays an important role in irrigation system to increase water productivity. In the present study, a review has been carried out over cognitive computing models used for the estimation of ET₀. Review exhibits that artificial neural network (ANN) approach outperforms support vector machine (SVM) and genetic programming (GP). Second order neural network (SONN) is the most promising approach among ANN models.     

基于网络理论的物质成瘾新视角

物质成瘾是一种涉及生理、心理和环境等多因素的复杂现象, 但是当前基于生物还原论的解释对物质成瘾现象整体性的理解和康复研究造成了阻碍。网络理论聚焦于心理障碍变量之间相互作用形成的反馈环路, 从整体视角为研究物质成瘾提供了新的理论框架。将网络理论应用于物质成瘾的研究中将有利于:(1)理解症状之间的相互关系和影响; (2)理解症状网络的整体性和系统性动态变化过程; 以及(3)将多层次和多水平因素整合到统一的理论框架中。从网络理论视角来理解物质成瘾, 也将对未来的干预和治疗提供了理论支持。目前, 网络理论仍处于言语模型阶段, 未来需要进一步提出更具体、可验证的统计模型, 以完善对于物质成瘾机制的了解, 更加有效地推进物质成瘾的治疗与恢复。     

自恋与行为抑制/激活系统的关系：元分析

运用元分析方法探讨自恋与行为抑制/激活系统的关系。经过文献检索和筛选, 纳入原始文献19篇, 包含25个独立样本, 共7702名被试。根据同质性检验结果, 选用随机效应模型。结果发现, 自恋与行为抑制系统存在中度负相关(r = -0.27, 95% CI为[-0.34, -0.21]), 自恋测量工具在两者间起显著的调节作用; 自恋与行为激活系统存在高度正相关(r = 0.46, 95% CI为[0.40, 0.52]), 被试类型在两者间起显著的调节作用。自恋与行为抑制/激活系统的密切关系支持了自恋的主体性理论和人格强化敏感性理论。     

非符号数量表征和符号分数表征的关系

个体学习符号分数的一个关键是能对其数值形成准确表征。现有研究假设符号分数表征的认知基础是人类自婴幼儿期就具有的非符号数量表征(如表征两个集合各自的数量, 或两个数量的比例)。其证据包括表征非符号数量(尤其是非符号数量比例关系)和表征符号分数在行为和大脑神经活动层面上都表现出相关性。然而要说明非符号数量表征是符号分数表征的认知基础, 还需更多研究表明两者在数量概念上的独特相关和因果联系, 并阐明符号分数表征形成的认知机制。