The photoredox ability of a hexarhenium(III) cluster, [Re 6 (l 3 -S) 8 Cl 6 ] 4-, in acetonitrile was examined on the basis of the emission quenching experiments of the cluster by a series of neutral organic electron acceptors (A). The photoinduced electron transfer quenching rate constants and the relevant activation parameters demonstrated that the hexarhenium(III) cluster acted as a useful photoredox sensitizer towards various A and the system gave a high charge separation yield owing to electrostatic repulsion between the product ions: [Re 6 (l 3 -S) 8 Cl 6 ] 3-and A -. These results were proved explicitly by nanosecond transient absorption spectroscopy.

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Control S y s t e m consists of many components which have a f e w s t a t e values. We have proposed the method to model such Sequential Control Systems by Petri nets with place invariant to restrict and to be suitable for the s t a t e values, and also the way to divide a large Petri net t o some small sub nets using the same place invariant. A typical sequential control system, an automated measuring tank system, will be discussed here t o show the effectiveness of the modelling and analyzing methods. Finally, we take advantage o f transition invariant properties in order to analyze such divided sub n e t s .

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00260006/11.jpg"" width=""300"" />Proposed LRRC concept</div> In previous work, we proposed controlling powerassisted carts by using a motor torque limiter that achieves the desired load-reduction ratio even if torque saturates. We assumed, however, that the operator accelerates smoothly up to the target speed, so that when velocity is affected largely by the input force of walking, prediction error becomes large and the target load reduction ratio was not achieved. To solve this problem, we propose an improving the achievement rate of the target load reduction ratio in two steps, first, by predicting the number of steps toward target speed from initial input and, second, by switching the prediction model. We use cart input force and speed to predict operator acceleration patterns. Our proposal predicts operator needs and delivers the desired loadreduction ratio by predicting operation. Results show that the achievement rate of the target load-reduction ratio is improved by using our proposed control. In other words, applying our proposal improves the short available time of power-assisted carts. </span>