Aphasia is a language disorder that occurs after a stroke and impairs listening, speaking, reading, writing, and calculation skills. Patients with post-stroke aphasia in Japan are increasing due to population aging and the advancement of medical treatment. Opportunities for adequate speech therapy in chronic stroke are limited due to time constraints. Recent studies have reported that intensive speech therapy for a short period of time or continuous speech therapy using high-tech equipment, including speech applications (apps, can improve aphasia even in (...) the chronic stage. However, its underlying mechanism for improving language function and its effect on other cognitive functions remains unclear. In the present study, we investigated whether intensive speech therapy using a newly developed speech support app could improve aphasia and other cognitive functions in patients with chronic stroke. Furthermore, we examined whether it can alter the brain network related to language and other cortical areas. Thus, we conducted a prospective, single-comparison study to examine the effects of a new speech support app on language and cognitive functions and used resting state functional MRI (rs-fMRI) regions of interest (ROI) to ROI analysis to determine changes in the related brain network. Two patients with chronic stroke participated in this study. They used the independent speech therapy system to perform eight sets of 20 randomly presented words/time (taking approximately 20 min), for 8 consecutive weeks. Their language, higher cognitive functions including attention function, and rs-fMRI, were evaluated before and after the rehabilitation intervention using the speech support app. Both patients had improved pronunciation, daily conversational situations, and attention. The rs-fMRI analysis showed increased functional connectivity of brain regions associated with language and attention related areas. Our results show that intensive speech therapy using this speech support app can improve language and attention functions even in the chronic stage of stroke, and may be a useful tool for patients with aphasia. In the future, we will conduct longitudinal studies with larger numbers of patients, which we hope will continue the trends seen in the current study, and provide even stronger evidence for the usefulness of this new speech support app. (shrink)

慶応義塾大学法学部のゼミナール「伊東乾民事訴訟法研究会」の卒業生の会「乾会」による論文集。今回はテーマを民事訴訟法に限ることなく、現在関心を持っている法律分野について執筆した。.

はたして科学は万能なのか。19世紀以来の「科学主義」は、現在なお「自然主義」の衣を纏って生き続けている。本書は「科学主義」と「反科学主義」をともに退け、科学を自然というテクストを解読する解釈学的営みと して捉え直す。ハンソンとクーンの「新科学哲学」、クワインの「知識の全体論」、ウィトゲンシュタインの「アスペクト論」を手がかりに、科学哲学に「科学的理性批判」という本来の哲学的課題を担わせることを目指す 。ここに新たに論文3篇を加え、サイエンス・ウォーズや実在論/反実在論など、現代の哲学状況と切り結ぶスリリングな論考。.

Reinforcement learning is very effective for robot learning. Because it does not need priori knowledge and has higher capability of reactive and adaptive behaviors. In our previous works, we proposed new reinforcement learning algorithm: “Q-learning with Dynamic Structuring of Exploration Space Based on Genetic Algorithm (QDSEGA)”. It is designed for complicated systems with large action-state space like a robot with many redundant degrees of freedom. And we applied it to 50 link manipulator and effective behavior is acquired. However optimality and (...) fault tolerance of the proposed algorithm were not considered and to demonstrate effectiveness of the proposed algorithm other applications are necessary. Acquiring of locomotion patterns by a multi-legged robot is a very interesting problem. As it has many redundant degrees of freedom, application of usual reinforcement learning is difficult and an optimal locomotion has not been acquired using previous reinforcement learning algorithm. And the redundancy of the robot is effective to the fault tolerance and various locomotion patterns can be acquired for adapting the faults of the legs. In this paper, we applied QDSEGA to acquiring of locomotion pattern by the multi-legged robot and considered the optimality and fault tolerance. Effective behavior has been obtained by using our proposed algorithm. (shrink)

Reinforcement learning has recently received much attention as a learning method for complicated systems, e.g., robot systems. It does not need prior knowledge and has higher capability of reactive and adaptive behaviors. However increase in dimensionality of the action-state space makes it diffcult to accomplish learning. The applicability of the existing reinforcement learning algorithms are effective for simple tasks with relatively small action-state space. In this paper, we propose a new reinforcement learning algorithm: “Q-learning with Dynamic Structuring of Exploration Space (...) Based on Genetic Algorithm ”. The algorithm is applicable to systems with high dimensional action and interior state spaces, for example a robot with many redundant degrees of freedom. To demonstrate the effectiveness of the proposed algorithm simulations of obstacle avoidance by a 50 links manipulator have been carried out. It is shown that effective behavior can be learned by using the proposed algorithm. (shrink)

It has been suggested that preparing to teach and teaching are conditionally effective in enhancing one’s own learning. This paper focuses on interactivity—the level of teacher-student interaction in expected or actual teaching—as the potential key to understanding and controlling the variability in the effectiveness of learning by preparing to teach and teaching. By summarizing and reanalyzing the results of previous studies, I suggest that the learning benefits of studying with the expectation of direct teaching (i.e., teaching a student face-to-face) are (...) greater than those of studying with the expectation of indirect teaching (i.e., teaching a student indirectly by creating a lecture video, providing written explanations, or using other means) and that learning by direct teaching surpasses learning by explaining to oneself or indirect teaching at least after preparing to do so. Next, three candidate explanations for the impact of interactivity are discussed: the advantages of asking and answering questions, obtaining additional information about and from one’s student, and enhancing one’s motivation to process learning material deeply while preparing to teach and teaching. Finally, I conclude with the remaining questions and directions for future research. (shrink)

Study of Vaiśeṣika philosophy with special reference to Vaiśeṣikadaśapadārthaśāstra.

Many educators today think that the school's lessons and activities do not stimulate or engage students' imaginations. In order to alleviate this problem, they tend to use images in conjunction with, or sometimes rather than, words; they employ so-called imaginative or creative activities rather than chalk and talk. However, these principles and methods are based on somewhat misguided or trivial understanding of the importance of imagination in students' lives. Dewey's understanding of the relevance of imagination gives us a useful perspective (...) to better understand where imaginative engagement becomes crucial in education. (shrink)

To explain why students learn effectively by teaching, explaining to others in particular, Koh and colleagues advanced the retrieval practice hypothesis, which attributes the learning benefits entirely to the effect of practicing retrieval, that is, effortfully recalling to-be-taught information for the provision of instructional explanations. After delineating the rationale behind the retrieval practice hypothesis, the current situation of research, and the limitations of the existing approach, this paper proposes three tests for the evaluation of the hypothesis that address whether explaining (...) to others after initial studying surpasses restudying in learning performance, whether the amount of effort to retrieve to-be-taught information from memory moderates the learning effects of explaining to others, and whether the degree of elaboration during retrieval practice positively predicts the outcomes of learning by merely recalling to-be-taught information. Evidence is examined regarding whether each test is passed, and future directions for research on the retrieval practice hypothesis are discussed. (shrink)

Drawing on theories of institutional evolution, this article contends that despite the centrality of occupationally based social insurance in postwar Korea and Taiwan, the welfare state has in fact deepened considerably. The analysis is structured around three distinct eras of social policy reform in Korea and Taiwan: the developmental state, democratic transition, and postindustrialism. The authors contend that during each of these eras, the institutional purposes of social policy were altered to meet certain socioeconomic objectives. New institutional purposes were grafted (...) onto the prevailing social insurance model, changing the outcomes of social policy. The developmental state era was productivist in purpose, democratic reform during the 1980s reoriented social insurance toward universalist and redistributive principles, and the post-1997 era refocused social insurance to meet the imperatives of flexible labor markets, demographic shifts, and economic globalization. (shrink)

Intelligent humanoid robots (IHRs) are becoming likely to be integrated into nursing practice. However, a proper integration of IHRs requires a detailed description and explanation of their essential capabilities, particularly regarding their competencies in replicating and portraying emotive functions such as empathy. Existing humanoid robots can exhibit rudimentary forms of empathy; as these machines slowly become commonplace in healthcare settings, they will be expected to express empathy as a natural function, rather than merely to portray artificial empathy as a replication (...) of human empathy. This article works with a twofold purpose: firstly, to consider the impact of artificial empathy in nursing and, secondly, to describe the influence of Affective Developmental Robotics (ADR) in anticipation of the empathic behaviour presented by artificial humanoid robots. The ADR has demonstrated that it can be one means by which humanoid nurse robots can achieve expressions of more relatable artificial empathy. This will be one of the vital models for intelligent humanoid robots currently in nurse robot development for the healthcare industry. A discussion of IHRs demonstrating artificial empathy is critical to nursing practice today, particularly in healthcare settings dense with technology. (shrink)

In the October edition of the Journal of Medical Ethics, Akabayashi and colleagues state that ’to establish a heterogeneous [induced pluripotent stem cell] iPSC bank covering roughly 80% of Japan’s population…the Japanese government decided to invest JPY110 billion over 10 years in regenerative medicine research; a quarter of this was to be allocated to the iPSC stock project'. While they claim this amount of money to be an unfair distribution of state resources, we believe their assessment is based on a (...) misunderstanding of the facts. Similarly, other criticisms by them are based on mistaken interpretations. This article is a rebuttal to the arguments that form the basis of Akabayashi and colleagues’ five criticisms by explaining their misinterpretations. (shrink)

『哲学探究』以後、最晩期に独立した地位を与える。ウィトゲンシュタインの知識の哲学。.