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RI-RICH, a ring-imaging Cherenkov counter for radioactive ions, has been developed to measure the velocity of the ions at intermediate energies. Our RI-RICH system consists of six multi-anode photomultiplier tubes covered with 360-nm bandpass filters and a radiator made of quartz or BK7. For the primary 132Xe beam with a velocity of β = 0 . 712 , a velocity resolution of Δ β ∕ β = 4 . 9 × 1 0 − 4 (one standard deviation σ ) and a detection efficiency of more than 99.99% were achieved. For the secondary beams with Z = 44 – 55 and β ≃ 0 . 70 , we successfully performed particle identification using the B ρ - Δ E - β method. The velocity resolutions of RI-RICH for these nuclides were equivalent to a more than 6 σ separation for the mass number.

Sensory overresponsivity (SOR) emerges before anxiety and positively predicts subsequent increasing levels of anxiety in individuals with autism spectrum disorder (ASD). Sensory seeking behavior occurs as compensation for SOR, and individuals may seek sensory input in one sensory domain to compensate for SOR. Tactile seeking behavior is sufficient to decrease social anxiety in communicating with unfamiliar people. We assessed the effectiveness of hugging a huggable device before a conversation for reducing the psychological stress associated with speaking to an unfamiliar person or robot. Our analysis showed a significant effect, with Hugvie contributing to decreased stress for both interlocutors. Thus, this study demonstrated the efficacy of hugging it before conversation, which emphasizes the importance of tactile seeking for individuals with ASD.

Technological agents could be effective tools to be used in interventions for enhancing social orienting for some young children with ASD. We examined response to social bids in preschool children with ASD and typical development (TD) at a very early age (i.e., around 3 years) using social prompts presented by technological agents of various forms and human comparisons. Children with ASD demonstrated less response overall to social bids compared to TD controls, across agents or human. They responded more often to a simple humanoid robot and the simple avatar compared to the human. These results support the potential utilization of specific robotic and technological agents for harnessing and potentially increasing motivation to socially-relevant behaviors in some young children with ASD.

It is unclear how a human attributes the cause of failure to the robot in a human-robot interaction. We aim to identify the relationship between causal attribution and mind perception in a repeated game with an agent. We investigated causal attribution of the participant to the agent: which decision of the participant or the partner agent caused the unexpectedly small amount of the reward. We conducted experiments with three agent conditions: a human, robot, and computer. The results showed that the agency score negatively correlated with the degree of causal attribution to the partner agent. In particular, correlations of scores of “thought,” “memory,” “planning,” and “self-control” that are sub-items of agency were significant. This implied the impression that “the agent acted to succeed” might reduce causal attribution. In addition, we found that decrease in the scores of mind perception correlated with the degree of causal attribution to the partner agent. This suggests that a sense of betrayal of the prior expectation by the partner agent through the game might lead to causal attribution to the partner agent.

We investigated the feasibility of our novel evaluation system for use with children with autism spectrum disorders (ASD). We prepared the experimental setting with two humanoid robots in reference to the birthday party scene in the Autism Diagnostic Observational Schedule (ADOS). We assessed the relationship between social communication ability measured in the ADOS condition (i.e., with a human clinician) and in a robotic condition for children with ASD. There were significant correlations between the social communication scores in the gold-standard ADOS condition and the robotic condition for children with ASD. The current work provides support for a unique application of a robotic system (i.e., two robot-mediated interaction) to evaluate the severity of autistic traits for children with ASD.

Hiroshi Ishiguro gave a lecture to a group of young students. We employed CommU, the desktop social robot, to manage the questions and answers for the talk. We encouraged the students to ask questions anytime. Half of the classroom was told to ask questions by raising their hand while the other half was shown an online messaging system developed for CommU, which allows the audience to post questions, which the robot would directly say. We had a gatekeeper to monitor for invalid sentences. In the middle of the presentation we asked the students to shift roles. The robot used a neural network based estimator of interruptibility to find the best time to speak. We did not expect too many questions, but the audience really embraced using the robot. They posted 44 questions to the presenter through CommU. On the other hand they asked 8 direct questions by raising their hands and standing up. Students thought that they gained more information from the lecturer using the robot than using the conventional method. In this instance we didn't stop the students from asking too many questions, but in a real-world application the gatekeeper will have to play an important role.

In recent decades and years classroom teaching has been influenced by the appearance of digital devices and the pervasiveness of the internet. In recent years robots started appearing in learning environments. Even though classroom presentations improved considerably, interaction between students and teachers has not improved greatly. We propose a new way of using a desktop robot and an online voting/messaging system to make the classroom experience more interactive. Concretely, in this paper we report on a lecture which was assisted by a robot. The students posted questions and opinions on an online messaging platform. The messages were then sent to the robot to be posed to the teacher, either directly or through a voting procedure. Students found this new way of interaction very efficient and useful for improving their communication with the teacher. At the same time the number of interactions should be controlled so it does not interfere with the teaching process.

Our research goal was to develop a robot counseling system. It is important for a counselor to promote self-disclosure of clients to reduce their anxiety feelings. However, when a counselor is human, clients sometimes hesitate to disclose intrusive topics due to embarrassment and self-esteem issues. We hypothesized that a robot counselor, on account of its unique kind of agency, could remove mental barriers between the counselor and the client, and promote in-depth self-disclosure about negative topics. In this study, we prepared two robots (an android and a desktop robot) as robot counselors. First, we confirmed that subjects eagerly self-disclosed to these prepared robots from the numbers of spoken words about self-disclosure in preliminary experiment. And next, we conducted the experiment to verify whether it is possible to expose more of subjects' weakness to robots than humans. The experimental result suggested that robots can draw out subjects' self-disclosure about negative topics than the human counselor.

We conducted a pilot experiment to examine the potential of a communication robot for supporting verbal interaction among adolescents with autism spectrum disorders (ASD) and their caregivers. Three teenagers with ASD indirectly conversed with their teacher via a desktop humanoid robot for around 40 min on average per day. In this situation, they showed some positive tendencies such as non-echolalic responses and talk about problems related to human relationships; they had not shown such tendencies before when they directly talked with their teacher in their daily life. During the trials, they also showed changes in their attitudes toward their teachers and friends; this implies that individuals with ASD could use their experience of communication with a robot for communication with a human. A quantitative analysis of the utterances in the trials suggested that reduced utterances from a caregiver might positively influence individuals with ASD toward sharing more information.