Blockage in a blood vessel due to cardiovascular disease such as arteriosclerosis or aneurysms requires minimally invasive placement of a mesh tube or platinum coil stent via a catheter to open the affected area. Stents are positioned using a guide wire via a catheter, but the stent may be dropped on the way to its destination and requires much time in surgery, increasing the burden on the patient. Medical apparatuses are thus desired having a mechanism to grasp artifacts securely in blood vessels. We designed prototype microforceps for use on the end of a catheter for grasping operation in blood vessels and to contribute to medical apparatuses in this field. The microforceps we designed using a minimum number of parts uses metal injection molding (MIM) to realize strong mass production. Microforceps installed in the tip of a catheter. Stress analysis verified its capability to grasp, bend and turn within the confines of a blood vessels model.
This paper considers a dynamic quantization problem for multi-rate sampling feedback systems. First, we give an optimal dynamic quantizer for systems with fast sampling input and slow sampling output, which has a different structure from those in the single-rate case. Second, we show an upper bound of the performance of dynamic quantizers for systems with slow sampling input and fast sampling output. Based on this, we provide a method to obtain a suboptimal solution. Numerical examples are given to demonstrate the effectiveness of our dynamic quantizers.
To make an agile decision in a rational manner, role of optimization engineering has been notified increasingly under diversified customer demand. With this point of view, in this paper, we have proposed a new evolutionary method serving as an optimization technique in the paradigm of optimization engineering. The developed method has prospects to solve globally various complicated problem appearing in real world applications. It is evolved from the conventional method known as Nelder and Mead’s Simplex method by virtue of idea borrowed from recent meta-heuristic method such as PSO. Mentioning an algorithm to handle linear inequality constraints effectively, we have validated effectiveness of the proposed method through comparison with other methods using several benchmark problems.