Japan has been facing challenges relating to specifically defined rare diseases, called Nan-Byo in Japanese (literally ‘difficult’+‘illness’), and has already taken measures for them since 1972. This governmental support has surely benefited Nan-Byo patients; however, those suffering from medically unidentified conditions do not fall into this scheme and thus still confront difficulty in obtaining an examination, a diagnosis, and a treatment. To identify such rare and often undiagnosed diseases, we must integrate systematic diagnosis by medical experts with phenotypic and genetic data matching. Thus, in collaboration with Nan-Byo researchers and the Japanese universal healthcare system, the Japan Agency for Medical Research and Development launched the Initiative on Rare and Undiagnosed Diseases (IRUD) in 2015. IRUD is an ambitious challenge to construct a comprehensive medical network and an internationally compatible data-sharing framework. Synergizing with existing next-generation sequencing capabilities and other infrastructure, the nationwide medical research consortium has successfully grown to accept more than 2000 undiagnosed registrants by December 2016. We also aim at expanding the concept of microattribution throughout the initiative; that is, proper credit as collaborators shall be given to local primary care physicians, nurses and paramedics, patients, their family members, and those supporting the affected individuals whenever appropriate. As it shares many challenges among similar global efforts, IRUD’s future successes and lessons learned will significantly contribute to ongoing international endeavors, involving players in basic research, applied research, and societal implementation.

A novel CMOS architecture utilizing tensilekompressive silicon nitride capping layers to induce tensilekompressive strain in NMOSFETPMOSFET channel regions was developed. NMOSFET device delivers 1.05mA/pm on-current for 7OnA/pm off-current at 1V drain voltage. PMOS device exhibits peak 66% increase of linear drain current and 55% increase of saturation current. It was shown that drain current improvements both for N-and PMOSFETs strongly correlate with channel doping levels. Therefore, advanced methods of shallow and low resistance junction formation are required for maintaining low channel doping concentration and efficiently utilizing channel strain at sub40nm gate length.

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Recently, the maintenance of bridges has become a major social concern, and thus the development of a practical bridge management system is required. The present study is an attempt to develop a new bridge management system (BMS) for deteriorated concrete bridges by evaluating the output results from a bridge rating expert system that is currently under development. The proposed BMS offers various maintenance plans based on a combination of maintenance cost minimization and quality maximization. Genetic algorithms (GAs) are adopted for solving the optimization problem. These algorithms, which are based on the theory of evolution, create a suitable individual (optimal) solution through the repetition of three operators: selection, crossover, and mutation. Furthermore, applications to several existing concrete bridges are presented so as to demonstrate the validity of the proposed bridge management system.

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This paper proposes a simple method for localization using an electronic compass. Electronic compasses are often used to detect the heading of mobile robots. However, electronic compasses have one drawback when used inside a building: they can easily be disturbed by electromagnetic sources (e.g., power lines) or large ferro-magnetic structures (e.g., bookshelves). However, this paper introduces another indoor application of electronic compasses. We take advantage of the magnetic¯eld disturbances by using them as distinctive place recognition signatures. Wē rst gather information about the changing heading as our robot travels along the hallway outside the lab, and then store this information. As the robot traverses the hallway, it gathers the information from the electronic compass and matches it with the pre-stored data. If a match is found, the robot can determine its current position. We use a sequential least-squares approximation approach for matching the signature. The simulation results will show that the robot can distinguish its location by using these signatures.

Engineers have long employed control systems utilizing models and feedback loops to control real-world systems. Limitations of model-based control led to a generation of intelligent control techniques such as adaptive and fuzzy control. The human brain, on the other hand, is known to process a variety of inputs in parallel, and shift between different levels of cognitive activities while ignoring distractions to focus on the task in hand. This process, known as cognitive control in psychology, is unique to humans and a handful of animals. We are interested in implementing such cognitive control functionalities for our humanoid robot ISAC. This paper outlines the features of multiagent-based cognitive architecture for a humanoid robot and the progress made toward the realization of cognitive control functionalities using attention, working memory and internal rehearsal. Several experiments have been conducted to show that the implementation of an integrated cognitive robot architecture is feasible.