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expression and localization of two types of AQP5 in Xenopus tropicalis under hydration and dehydration.

Recent studies have reported the effectiveness of robotic rehabilitation of paralyzed upper limbs in stroke patients. For example, the Single-Joint Hybrid Assistive Limb has been shown to improve upper limb impairments. However, limited data are available on the effectiveness of robotic rehabilitation of the upper limb with regards to daily living. In this case study, an accelerometer was adopted to examine whether rehabilitation using the Single-Joint Hybrid Assistive Limb improved upper limb activity during daily living in a stroke patient. [Participant and Methods] The participant was a 69-year-old male diagnosed with stroke and left hemiparesis. The Single-Joint Hybrid Assistive Limb was applied to the participant's elbow on the paralyzed side. The participant wore an accelerometer on each wrist to measure the activities of the upper limbs. Clinical tests of the paralyzed upper limb were also performed. [Results] The activity of the paralytic limb was significantly higher after Single-Joint Hybrid Assistive Limb intervention than before the intervention. On the other hand, none of the results of the clinical tests changed beyond a clinically important difference. [Conclusion] The Single-Joint Hybrid Assistive Limb could be useful for promoting active use of a paralyzed upper limb in daily living. In addition, an accelerometer could be especially useful for evaluating the effects of robotic rehabilitation.

Recent studies on embodied cognitive science have shown us the possibility of emergence of more complex and nontrivial behaviors with quite simple designs if the designer takes the dynamics of the system-environment interaction into account properly. In this paper, we report our tentative classification experiments of several objects using the human-like autonomous robot, "WAMOEBAIRi". As modeling the environment, we focus on not only static aspects of the environment but also dynamic aspects of it including that of the system own. The visualized result of this experiment shows the integration of multimodal sensor datasef acquired by the system-environment interaction ("grasping") enable robust categorization of several objects. Finally, in discussion, we demonstrate a possible application to making "invariance in motion" emerge consequently by extending this sppraneh.

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