正确认识免疫抑制剂治疗风湿病的双刃剑作用

免疫抑制剂治疗风湿病疗效显著,但由于其免疫抑制的作用机理,临床应用会引起很多的副作用。由于患者的个体差异,治疗作用与副反应不尽相同。所以,在治疗的时候应该尽量扩大治疗作用减少副作用,并向患者阐明药物的双重性。     

Fairweather and ESID: Contemporary Impact and a Legacy for the Twenty-First Century

This paper illustrates how the articles in this special issue demonstrate the central values, research, and action principles inherent in Fairweather's ESID model. The programs described in these articles address earlier social problems in new forms (e.g., previously, institutionalized mentally ill patients and now, the homeless mentally ill) and new issues (e.g., HIV prevention). Dissemination of innovative programs is abundant, but only recently has research begun in earnest to study the critical processes of dissemination. Moreover, Fairweather has pointed us in important, but yet unrealized directions for how to pursue a theory of social change on the basis of ecological concepts, innovative research methods and data analytic techniques, and salient change agent behaviors and principles.     

对我国儿童肾移植发展的思考与建议

肾移植是儿童终末期肾衰最重要的替代治疗手段。国内数家大的移植中心儿童肾移植长期存活率已接近国外先进水平,但我国肾移植患儿总数较少,主要原因是经费不足和供体缺乏。为推动儿童肾移植的发展,建议建立国家医疗救助制度,鼓励亲属活体肾脏捐献,严格掌握适应证,合理使用免疫抑制剂,加强多中心协作,建立移植随访网络。     

Listenmee® and Listenmee® smartphone application: Synchronizing walking to rhythmic auditory cues to improve gait in Parkinson’s disease

Evidence supports the use of rhythmic external auditory signals to improve gait in PD patients (Arias & Cudeiro, 2008; Kenyon & Thaut, 2000; McIntosh, Rice & Thaut, 1994; McIntosh et al., 1997; Morris, Iansek, & Matyas, 1994; Thaut, McIntosh, & Rice, 1997; Suteerawattananon, Morris, Etnyre, Jankovic, & Protas , 2004; Willems, Nieuwboer, Chavert, & Desloovere, 2006). However, few prototypes are available for daily use, and to our knowledge, none utilize a smartphone application allowing individualized sounds and cadence. Therefore, we analyzed the effects on gait of Listenmee®, an intelligent glasses system with a portable auditory device, and present its smartphone application, the Listenmee app®, offering over 100 different sounds and an adjustable metronome to individualize the cueing rate as well as its smartwatch with accelerometer to detect magnitude and direction of the proper acceleration, track calorie count, sleep patterns, steps count and daily distances. The present study included patients with idiopathic PD presented gait disturbances including freezing. Auditory rhythmic cues were delivered through Listenmee®. Performance was analyzed in a motion and gait analysis laboratory. The results revealed significant improvements in gait performance over three major dependent variables: walking speed in 38.1%, cadence in 28.1% and stride length in 44.5%. Our findings suggest that auditory cueing through Listenmee® may significantly enhance gait performance. Further studies are needed to elucidate the potential role and maximize the benefits of these portable devices.     

Reasoning about conscious experience with axiomatic and graphical mathematics

We cast aspects of consciousness in axiomatic mathematical terms, using the graphical calculus of general process theories (a.k.a symmetric monoidal categories and Frobenius algebras therein). This calculus exploits the ontological neutrality of process theories. A toy example using the axiomatic calculus is given to show the power of this approach, recovering other aspects of conscious experience, such as external and internal subjective distinction, privacy or unreadability of personal subjective experience, and phenomenal unity, one of the main issues for scientific studies of consciousness. In fact, these features naturally arise from the compositional nature of axiomatic calculus.     

When to (or not to) trust intelligent machines: Insights from an evolutionary game theory analysis of trust in repeated games

The actions of intelligent agents, such as chatbots, recommender systems, and virtual assistants are typically not fully transparent to the user. Consequently, users take the risk that such agents act in ways opposed to the users’ preferences or goals. It is often argued that people use trust as a cognitive shortcut to reduce the complexity of such interactions. Here we formalise this by using the methods of evolutionary game theory to study the viability of trust-based strategies in repeated games. These are reciprocal strategies that cooperate as long as the other player is observed to be cooperating. Unlike classic reciprocal strategies, once mutual cooperation has been observed for a threshold number of rounds they stop checking their co-player’s behaviour every round, and instead only check it with some probability. By doing so, they reduce the opportunity cost of verifying whether the action of their co-player was actually cooperative. We demonstrate that these trust-based strategies can outcompete strategies that are always conditional, such as Tit-for-Tat, when the opportunity cost is non-negligible. We argue that this cost is likely to be greater when the interaction is between people and intelligent agents, because of the reduced transparency of the agent. Consequently, we expect people to use trust-based strategies more frequently in interactions with intelligent agents. Our results provide new, important insights into the design of mechanisms for facilitating interactions between humans and intelligent agents, where trust is an essential factor.     

The Power of a “Maverick” in Collaborative Problem Solving: An Experimental Investigation of Individual Perspective‐Taking Within a Group

Integrating different perspectives is a sophisticated strategy for developing constructive interactions in collaborative problem solving. However, cognitive aspects such as individuals’ knowledge and bias often obscure group consensus and produce conflict. This study investigated collaborative problem solving, focusing on a group member interacting with another member having a different perspective (a “maverick”). It was predicted that mavericks might mitigate disadvantages and facilitate perspective taking during problem solving. Thus, 344 university students participated in two laboratory‐based experiments by engaging in a simple rule‐discovery task that raised conflicts among perspectives. They interacted with virtual partners whose conversations were controlled by multiple conversational agents. Results show that when participants interacted with a maverick during the task, they were able to take others’ perspectives and integrate different perspectives to solve the problem. Moreover, when participants interacted in groups with a positive mood, groups with a maverick outperformed groups having several perspectives.     

Motivated learning for the development of autonomous systems

A new machine learning approach known as motivated learning (ML) is presented in this work. Motivated learning drives a machine to develop abstract motivations and choose its own goals. ML also provides a self-organizing system that controls a machine’s behavior based on competition between dynamically-changing pain signals. This provides an interplay of externally driven and internally generated control signals. It is demonstrated that ML not only yields a more sophisticated learning mechanism and system of values than reinforcement learning (RL), but is also more efficient in learning complex relations and delivers better performance than RL in dynamically-changing environments. In addition, this paper shows the basic neural network structures used to create abstract motivations, higher level goals, and subgoals. Finally, simulation results show comparisons between ML and RL in environments of gradually increasing sophistication and levels of difficulty.     

Prospects in Ritual Studies

Michael B. Aune and Valerie DeMarinis, Religious and Social Ritual: Interdisciplinary Explorations. Albany, State University of New York Press, 1996. vii+323 pp., $20.50 (hardback) ISBN 0 7914 2825 7, $19.95 (paperback) ISBN 0 7914 2826 7.

Grimes, Ronald L. Beginnings in Ritual Studies. Rev. ed. Columbia, University of South Carolina Press, 1995, xxviii+299 pp., $21.95 (paperback) ISBN 1 5700 001 4.