美国高等临床药学教育体系宏观结构变迁研究（1965年～2015年）

研究了1965年~2015年美国高等临床药学教育体系的层次结构、形式结构和分布结构等宏观结构的变迁情况。从临床药学实践、药师动态短缺、产业结构基础、办学经费来源、人口地理分布等方面,对半个世纪以来美国临床药学教育体系宏观结构变迁情况进行归因分析。在总结并肯定美国高等临床药学教育体系极高的市场敏感性和较强的结构优化灵活性的同时,探讨了美国高等临床药学教育体系宏观结构变迁过程中需要注意的问题。     

Empirical Priors in Polytomous Computerized Adaptive Tests: Risks and Rewards in Clinical Settings

The use of empirical prior information about participants has been shown to substantially improve the efficiency of computerized adaptive tests (CATs) in educational settings. However, it is unclear how these results translate to clinical settings, where small item banks with highly informative polytomous items often lead to very short CATs. We explored the risks and rewards of using prior information in CAT in two simulation studies, rooted in applied clinical examples. In the first simulation, prior precision and bias in the prior location were manipulated independently. Our results show that a precise personalized prior can meaningfully increase CAT efficiency. However, this reward comes with the potential risk of overconfidence in wrong empirical information (i.e., using a precise severely biased prior), which can lead to unnecessarily long tests, or severely biased estimates. The latter risk can be mitigated by setting a minimum number of items that are to be administered during the CAT, or by setting a less precise prior; be it at the expense of canceling out any efficiency gains. The second simulation, with more realistic bias and precision combinations in the empirical prior, places the prevalence of the potential risks in context. With similar estimation bias, an empirical prior reduced CAT test length, compared to a standard normal prior, in 68% of cases, by a median of 20%; while test length increased in only 3% of cases. The use of prior information in CAT seems to be a feasible and simple method to reduce test burden for patients and clinical practitioners alike.     

人体生物医学研究中受试者权益保护对策

在人体生物医学研究日益发达的今天,受试者权益保护问题逐渐浮出水面。目前我国对受试者的保护主要依赖于知情同意书和伦理委员会,关于受试者权益保护的规范性文件存在层级低、不系统和不完整等问题。建立专门的受试者保护法,完善受试者权益保护相关制度迫在眉睫。研究认为,制定专门的人体生物医学研究受试者权益保护法律,完善伦理委员会制度,推行强制保险以及救济金制度,建立严格的责任体系、开展积极的社会教育是受试者权益保护的基本对策。     

The Faulty Magnitude Detector: Why SNARC‐Like Tasks Cannot Support a Generalized Magnitude System

Do people represent space, time, number, and other conceptual domains using a generalized magnitude system (GMS)? To answer this question, numerous studies have used the spatial‐numerical association of response codes (SNARC) task and its variants. Yet, for a combination of reasons, SNARC‐like effects cannot provide evidence for a GMS, even in principle. Rather, these effects support a broader theory of how people use space metaphorically to scaffold their understanding of myriad non‐spatial domains, whether or not these domains exhibit variation in magnitude.     

Left caloric vestibular stimulation as a tool to reveal implicit and explicit parameters of body representation

Homeostatic parameters, such as temperature, are related to body representation. In this study, we measured whether caloric vestibular stimulation (CVS) alters body temperature and tactile processing, and if in the direction predicted by a holistic body matrix representation.Skin temperature and tactile two-point discrimination (TPD) acuity were measured for both arms before, immediately after and with a delay from CVS. Participants were also administered a personality questionnaire and an anxiety inventory to rule out confounding factors. Two control experiments were planned to exclude casual variations.Our results show that temperature drops significantly in both arms after CVS. CVS also induces a bilateral improvement in tactile acuity (even though not immediately after but in the delayed condition). Finally, these effects are not due to learning, as demonstrated by the control experiment.In summary, our results suggest that vestibular stimulation updates body representation, supporting the evidence in favor of a body matrix.     

中国颜色体系研究

概述了用颜色立体模型表示物体颜色,并做定量表示的颜色体系研究的理论意义及应用价值。介绍了国际上影响较大的颜色体系理论和编制原则的特点。中国颜色体系研究是在对国际上其它颜色体系的理论分析和对颜色样品测试的基础上,确立其理论依据和编制原则,开展了中国人眼对明度、色调、彩度等间距排列的视觉评价实验,建立了中国颜色体系理论模型。同时研制出《中国颜色体系样册》。该项研究于１９９３年７月通过了国家自然科学基金委员会和中国科学院联合召开的成果鉴定会,并得到良好的评价,又于１９９４年６月通过国家标准审查。该项研究的完成和推广,不仅能为我国国民经济各部门的颜色控制、标定和交流提供科学的颜色定量手段,同时也是对实用色度学的发展和颜色标准化工作做了有益的工作,产生了积极的经济效益和社会效益。     

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.     

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.