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Nobuyuki Hinata,Keisuke Hieda,Hiromasa Sasaki,Tetsuji Kurokawa,Hideaki Miyake,Masato Fujisawa,Gen Murakami,Mineko Fujimiya 대한해부학회 2014 Anatomy & Cell Biology Vol.47 No.1
The paracolpium or paravaginal tissue is surrounded by the vaginal wall, the pubocervical fascia and the rectovaginal septum (Denonvilliers' fascia). To clarify the configuration of nerves and fasciae in and around the paracolpium, we examined histological sections of 10 elderly cadavers. The paracolpium contained the distal part of the pelvic autonomic nerve plexus and its branches: the cavernous nerve, the nerves to the urethra and the nerves to the internal anal sphincter (NIAS). The NIAS ran postero-inferiorly along the superior fascia of the levator ani muscle to reach the longitudinal muscle layer of the rectum. In two nulliparous and one multiparous women, the pubocervical fascia and the rectovaginal septum were distinct and connected with the superior fascia of the levator at the tendinous arch of the pelvic fasciae. In these three cadavers, the pelvic plexus and its distal branches were distributed almost evenly in the paracolpium and sandwiched by the pubocervical and Denonvilliers' fasciae. By contrast, in five multiparous women, these nerves were divided into the anterosuperior group (bladder detrusor nerves) and the postero-inferior group (NIAS, cavernous and urethral nerves) by the well-developed venous plexus in combination with the fragmented or unclear fasciae. Although the small number of specimens was a major limitation of this study, we hypothesized that, in combination with destruction of the basic fascial architecture due to vaginal delivery and aging, the pelvic plexus is likely to change from a sheet-like configuration to several bundles.
Nobuyuki Hinata,Keisuke Hieda,Hiromasa Sasaki,Gen Murakami,Shinichi Abe,Akio Matsubara,Hideaki Miyake,Masato Fujisawa 대한해부학회 2014 Anatomy & Cell Biology Vol.47 No.1
Although the pelvic autonomic plexus may be considered a mixture of sympathetic and parasympathetic nerves, little information on its composite fibers is available. Using 10 donated elderly cadavers, we investigated in detail the topohistology of nerve fibers in the posterior part of the periprostatic region in males and the infero-anterior part of the paracolpium in females. Neuronal nitric oxide synthase (nNOS) and vasoactive intestinal polypeptide (VIP) were used as parasympathetic nerve markers, and tyrosine hydroxylase (TH) was used as a marker of sympathetic nerves. In the region examined, nNOS-positive nerves (containing nNOS-positive fibers) were consistently predominant numerically. All fibers positive for these markers appeared to be thin, unmyelinated fibers. Accordingly, the pelvic plexus branches were classified into 5 types: triple-positive mixed nerves (nNOS+, VIP+, TH+, thick myelinated fibers + or -); double-positive mixed nerves (nNOS+, VIP-, TH+, thick myelinated fibers + or -); nerves in arterial walls (nNOS-, VIP+, TH+, thick myelinated fibers-); non-parasympathetic nerves (nNOS-, VIP-, TH+, thick myelinated fibers + or -); (although rare) pure sensory nerve candidates (nNOS-, VIP-, TH-, thick myelinated fibers+). Triple-positive nerves were 5-6 times more numerous in the paracolpium than in the periprostatic region. Usually, the parasympathetic nerve fibers did not occupy a specific site in a nerve, and were intermingled with sympathetic fibers. This morphology might be the result of an "incidentally" adopted nerve fiber route, rather than a targetspecific pathway.
Human-Robot Interface Using System Request Utterance Detection Based on Acoustic Features
Tetsuya Takiguchi,Tomoyuki Yamagata,Atsushi Sako,Nobuyuki Miyake,Jerome Revaud,Yasuo Ariki 보안공학연구지원센터 2008 International Journal of Hybrid Information Techno Vol.1 No.3
For a mobile robot to serve people in actual environments, such as a living room or a party room, it must be easy to control because some users might not even be capable of operating a computer keyboard. For non-expert users, speech recognition is one of the most effective communication tools when it comes to a hands-free (human-robot) interface. This paper describes a new mobile robot with hands-free speech recognition. For a hands-free speech interface, it is important to detect commands for a robot in spontaneous utterances. Our system can understand whether user’s utterances are commands for the robot or not, where commands are discriminated from humanhuman conversations by acoustic features. Then the robot can move according to the user’s voice (command). In order to capture the user’s voice only, a robust voice detection system with AdaBoost is also described.