Dragon Training and Changing Culture: A Review of DreamWorks' How to Train Your Dragon

DreamWorks' How to Train Your Dragon is an animated coming-of-age story in which the hero uses behavioral techniques to befriend and then to train an adversary. This movie provides an example of the successful dissemination of behavioral principles and technologies to the general population. Although it does not represent best practices in every instance, the movie may be an indication of a broader social acceptance of behavioral approaches to conflict resolution.     

Adult temperament and childbearing over the life course

Emerging evidence suggests that temperament may predict childbearing. We examined the association between four temperament traits (novelty seeking, harm avoidance, reward dependence and persistence of the Temperament and Character Inventory) and childbearing over the life course in the population‐based Cardiovascular Risk in Young Finns study (n = 1535; 985 women, 550 men). Temperament was assessed when the participants were aged 20–35 and fertility history from adolescence to adulthood was reported by the participants at age 30–45. Discrete‐time survival analysis modelling indicated that high childbearing probability was predicted by low novelty seeking (standardized OR = 0.92; 95% confidence interval 0.88–0.97), low harm avoidance (OR = 0.90; 0.85–0.95), high reward dependence (OR = 1.09; 1.03–1.15) and low persistence (OR = 0.91; 0.87–0.96) with no sex differences or quadratic effects. These associations grew stronger with increase in numbers of children. The findings were substantially the same in a completely prospective analysis. Adjusting for education did not influence the associations. Despite its negative association with overall childbearing, high novelty seeking increased the probability of having children in participants who were not living with a partner (OR = 1.29; 1.12–1.49). These data provide novel evidence for the role of temperament in influencing childbearing, and suggest possible weak natural selection of temperament traits in contemporary humans. Copyright © 2009 John Wiley & Sons, Ltd.     

机器人辅助手术在普通外科的应用及进展

机器人在过去的20多年里为普通外科做出了突出的贡献,且在不断的实践和改进之下机器人正逐步得到越来越多的应用。本文就机器人技术的发展和在普通外科的手术领域包括胆囊切除术、食管及胃部手术、减肥手术、结直肠癌手术和内分泌手术的应用以及进展综述如下。     

电视胸腔镜在肺癌治疗中面临问题的思考

电视胸腔镜是一种新兴技术,顺应了生物—心理—社会医学模式变革的要求,但在实际应用中有其局限性,尤其在肺癌治疗中尚存在较大的争议。分析该技术产生的背景、临床应用价值及发展前景,用一分为二和“扬弃”方法比较新旧技术的优与劣,并用实践论对新技术进行检验。     

神经培养的发展史与启示

简述神经培养技术与各学科关系的现状并回顾神经培养的发展历史,将神经培养历史划分为萌芽期、起步期、迅速发展阶段和新发展阶段等.从神经培养技术发展的角度入手,分析了新技术的突破与学科发展的密切关系.     

台湾人工生殖技术管制之回顾与前瞻

台湾地区人工生殖技术的管制先后经历了道德管制和行政管制两个阶段,目前正积极总结各阶段管制模式的成败得失,努力构造《人工生殖法》的原则和框架,以提高人工生殖技术管制的合法性和有效性。     

Achievement Goal Impacts Students' Preferences for “Personalized Problems” in Computer-Adaptive Tests1

The contemporary development of psychometric theories and information technologies enables students to work on algorithm-based personalized tests in classroom settings. This study aims to investigate the relationship between students' achievement goals and what they prefer as “personalized problems” in computer-adaptive tests. We theoretically contrast achievement goals with developing competency through mastery and demonstrating competency through performance goals. We asked elementary and secondary school students to work on a computer-adaptive test and to complete questionnaires about what they prefer as “personalized problems” in computer-adaptive tests. The results revealed that while mastery goals positively predicted preference for challenging problems, performance goals positively predicted preference for problems that guaranteed students’ success. Moreover, only the preference for challenging problems positively predicted the intention to take computer-adaptive tests in the future. These results suggest that simply introducing a computer-adaptive test into the classroom may not be effective. We discuss how educational technologies should be integrated into human teaching activities.     

Emerging Technologies and the Future of Philosophy

This article examines how a class of emerging technologies—specifically, radical cognitive enhancements and artificial intelligence—has the potential to influence the future of philosophy. The article argues that progress in philosophy has been impeded, in part, by two specific constraints imposed on us by the natural architecture of our cognitive systems. Both of these constraints, though, could in principle be overcome by certain cognitive technologies currently being researched and/or developed. It surveys a number of these technologies, and then looks at a particular metaphilosophical stance (called “inflationism”) that advocates amplifying the abilities of philosophers rather than reducing the ambitions of philosophy, given the apparent “teleological gap” between philosophy's ultimate goal (i.e., “the truth”) and the limited capacities of our evolved mental machinery.