Research Interests: Chemistry, Biological Chemistry, Medicine, Extracellular Matrix, Biological Sciences, and 15 moreLiver Cirrhosis, Liver, Mutation, Collagen, Mice, Chronic Disease, Animals, Hepatic Stellate Cells, Myofibroblasts, CHEMICAL SCIENCES, Fibronectin, Carbon Tetrachloride, Transforming Growth Factor Beta, Biological Availability, and Medical and Health Sciences
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Cooperative objects’ transportation simulation was performed by a swarm of units acquiring the learning ability on the network of units. It is well known that several kinds of insects may achieve complex tasks in a group, where each... more
Cooperative objects’ transportation simulation was performed by a swarm of units acquiring the learning ability on the network of units. It is well known that several kinds of insects may achieve complex tasks in a group, where each insect may play its role by the information of its surroundings. This collective behavior, as emerged in a group of social insects, has been called “swarm intelligence.” Although the swarm intelligence has been applied to control a robotic swarm, these artificial systems still depend on controllers placed outside of a swarm to get rules for each robot. In order to improve the system and implement the natural behavior into the artificial control system, a swarm should have the learning ability that may correct and acquire its behavior by itself. In this study, a cooperative transportation task of different-sized objects to the proper destinations by lots of units was simulated. Transportation goals were varied to the size of objects. In addition, the unit...
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A new concept of odorant receptor vectors composed of the half maximal effective concentration (EC50) of each receptor to odorant molecules was proposed. Odors are mainly subjective and qualitative evaluation has been per-formed until... more
A new concept of odorant receptor vectors composed of the half maximal effective concentration (EC50) of each receptor to odorant molecules was proposed. Odors are mainly subjective and qualitative evaluation has been per-formed until now. Therefore, we attempted to quantitatively express the direct association between odorant receptors and odor molecules in this study. The degree of similarity evaluated by taking inner product of the odorant receptor vectors was verified by comparing with the results by sensory evaluation tests published in past literatures in the form of correlation coefficient. A multi-layered artificial neural network whose input was the elements of prescribed odorant receptor vector was also introduced to identify odorant molecules in the output layer. As a result, the inner product of proposed odorant receptor vector might evaluate the degree of similarity quantitatively among various odorants. Further, it might be possible to identify odorant molecules by the...