Element Material Exposure Experiment by EFFU

The National Space Development Agency of Japan (NASDA) is planning to perform an 'Element Material Exposure Experiment' using the Exposed Facility Flyer Unit (EFFU). This paper presents an initial design of experiments proposed for this project by our company. The EFFU is installed on the Space Flyer Unit (SFU) as a partial model of the Space Station JEM exposed facility. The SFU is scheduled to be launched by H-2 rocket in January or February of 1994, then various tests will be performed for three months, on orbit of 500 km altitude, and it will be retrieved by the U.S. Space Shuttle and returned to the ground. The mission sequence is shown

Gene expression profiling in rats with depressive-like behavior

Individual differences indicate stronger phenotypes than model animals especially in behavioral studies, and some animals show unexpected behaviors in control and animal model groups. High-throughput analysis including cDNA microarray analysis are more affected by individual differences, because more samples are needed to reduce the difference in multiple factor analysis than single factor analysis such as real-time PCR. We measured the depressive-like behavior of over 100 normal rats in the forced swimming test and selected the rats for control and depression group from them to minimize the individual difference using data of force swimming test. Here, we provided the detail of methods and quality control parameters for the cDNA microarray data. This dataset can reflect the increase of depressive-like behavior. The dataset is deposited in the gene expression omnibus (GEO), series GSE63377

General Architecture for Hardware Implementation of Genetic Algorithm

FCCM 2006 : 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines , Apr 24-26, 2006 , Napa, CA, USAIn this paper, the authors propose a technique to flexibly implement genetic algorithms (GAs) for various problems on FPGAs. For the purpose, the authors propose a common architecture for GA. The proposed architecture allows designers to easily implement a GA as a hardware circuit consisting of parallel pipelines which execute GA operations. The proposed architecture is scalable to increase the number of parallel pipelines. The architecture is applicable to various problems and allows designers to estimate the size of resulting circuits. The authors give a model for predicting the size of resulting circuits from given parameters. Based on the proposed method, the authors have implemented a tool to facilitate GA circuit design and development. Through experiments using knapsack problem and traveling salesman problem (TSP), the authors show that the FPGA circuits synthesized based on the proposed method run much faster and consume much lower power than software implementation on a PC and the model can predict the size of the resulting circuit accurately enough

Increased excretion of urinary cyclic GMP in primary hepatoma and preneoplastic liver.

Urinary excretion of cyclic GMP (cGMP) and the plasma level of cyclic AMP (cAMP) were determined in patients with liver diseases. The urinary excretion of cGMP, expressed on the basis of creatinine excreted per day, was at significantly higher levels not only in primary hepatoma but also in liver cirrhosis, while the plasma level of cAMP was higher only in liver cirrhosis. Thus, the ratio of urinary cGMP excretion to plasma cAMP level in primary hepatoma was significantly higher than that in liver cirrhosis. In cirrhotic patients studied by catheterization, the level of cGMP in the hepatic vein was significantly lower than that in the superior mesenteric or portal vein, indicating the uptake of cGMP by the liver. Since cGMP excretion correlated with KICG both in liver cirrhosis and primary hepatoma, the increased cGMP excretion appeared to be explained by a reduced uptake of cGMP by the liver.</p

Video ads dissemination through WiFi-cellular hybrid networks

PerCom2009 : The Seventh Annual IEEE International Conference on Pervasive Computing and Communications , Mar 16-20, 2009 , Dallas, TX, USAIn this paper, we propose a method for video ads dissemination through a hybrid network consisting of WiFi and cellular networks, in order to provide timely delivery of video ads with preferred content to users according to the users' contexts. In recent years, video download/streaming services for cellular phones have already become popular. Among various video delivery services, a service for disseminating video ads according to the users' contexts is expected to achieve high advertising effects. However, context-aware video ads dissemination will consume large bandwidth since the size of video ad is rather large and the same ad is required at different time from various users. We propose a new video ads dissemination method for mobile terminals which utilizes both WiFi and cellular networks. In the proposed method, a file of video ad is divided into pieces and each node exchanges the pieces with neighbor nodes using WiFi ad hoc communication so that the usage of cellular network is reduced. In order to make the method works effectively for a large number of nodes, we propose an algorithm where mobile nodes autonomously and probabilistically decide their actions without a central control. Through simulations, we confirmed that our method reduces cellular network usage by about 93% compared with a case that all nodes download video ads via cellular network, and works effectively in cases with a large number of nodes and high mobility

A Method to Plan Group Tours with Joining and Forking

SEAL2006 : Asia-Pacific Conference on Simulated Evolution and Learning , Oct 15-18, 2006 , Hefei, ChinaGroup sightseeing has some advantages in terms of required budget and so on. Some travel agents provide package tours of group sightseeing, but participants have to follow a predetermined schedule in tour, and thus there may be no plan which perfectly satisfies the tourist's expectation. In this paper, we formalize a problem to find group sightseeing schedules for each user from given users’ preferences and time restrictions corresponding to each destination. We also propose a Genetic Algorithm-based algorithm to solve the problem. We implemented and evaluated the method, and confirmed that our algorithm finds efficient routes for group sightseeing