Scanning electron microscopy of nerve fibers in human fetal cochlea

The cochleas of four human fetuses ranging 22–25 weeks gestation were studied by scanning electron microscopy (SEM) for the purpose of obtaining a better understanding of the nerve fiber arrangement in the human ear. After critical point drying, the specimens were dissected and the floor of the tunnel of Corti and the outer wall of Nuel's space were exposed for observation. Upper cochlear turns, especially the apical turn, seemed to be still immature. Observed nerve fibers were classified into three types:

• 1 Spiral fibers: Fibers traveling basalward and following the shape of the cochlea were found in both the tunnel of Corti and Nuel's space and believed to be the afferent nerves responsible for innervating the outer hair cells
• 2 Radial fibers: radiating outward from the osseous spiral lamina—one such radial fiber transversing high in the tunnel space (supposedly the efferent nerve servicing the outer hair cells), and another sort of radial fiber (found crossing the tunnel floor), the nature of which was uncertain.
• 3 Irregular fibers: Consisting of thin, randomly running fibers within the cochlea. The destination of these fibers was not determined, but possibly they represent transitory nerve branchings of afferent or more probably efferent nerves, which would later regress during maturation.

     

An Advanced Oscillation Mixing Method for Improving the Cooling Uniformity in Quenching

In quenching, the cooling uniformity is most important to diminish distortion occurring on work pieces. As a trial to accomplish uniform cooling, therefore, there exist various mixing methods of a quenchant and the quenchant circulation with an external pump has so far been the well accepted mixing method. However, this study proposes an advanced oscillation mixing method that can improve more the cooling uniformity in quenching. The proposed method includes a stirrer in oscillating motion, so that the simultaneous oscillating and mixing movements of the stirrer are considered to provide efecfively the uniform cooling characteristics for the quenchant. In comparison with the case of the circulation pump mixing, the investigation using the oscillation mixing method has demonstrated the following two experimental facts:(1) the short vapor blanket stage caused by the quick breakage of the oil vapor blanket and (2) the reduced variation of the quenching distortion.     

Negative bias illumination stress assessment of indium gallium zinc oxide thin‐film transistors

Electrical performance stability of indium gallium zinc oxide (IGZO) thin‐film transistors (TFTs) is evaluated under negative bias illumination stress (NBIS). A bottom‐gate IGZO TFT whose top surface is passivated with zinc tin silicon oxide (ZTSO) exhibits a dramatic improvement in NBIS stability compared with that of an unpassivated, bottom‐gate IGZO TFT. Oxygen chemisorption/desorption at the channel layer top surface is proposed to explain why an unpassivated TFT exhibits significantly more NBIS than a passivated TFT.     

Extrasynaptic-GABA-mediated neuromodulation in a sensory cortical neural network

Simulating a neural network model of an early sensory cortical area, we investigated how gamma-aminobutyric acid (GABA) accumulated in extracellular space (ambient GABA), which depends on the synaptic activity of GABAergic interneurons, acts on the GABAa-receptors located on extrasynaptic membrane regions of principal cells (P), feedback inhibitory cells (F) and lateral inhibitory cells (L). The ambient GABA enhanced the selective responsiveness of P-cells to a target feature stimulus, if it acted on the extrasynaptic GABAa-receptors of P-cells. The ambient GABA led to depolarizing P-cells during ongoing (spontaneous) neuronal-activity periods, if it acted on the extrasynaptic GABAa-receptors of F or L cells. This membrane depolarization contributed to establishing an ongoing subthreshold neuronal state, by which the P-cells could respond quickly to the target stimulus. We suggest that the combinatorial inhibition of P, F, and L cells, meditated by extrasynaptic GABAa-receptors recognizing ambient GABA, is crucial for processing the information of relevant sensory features and for establishing an ongoing subthreshold cortical state that prepares as a ready state for subsequent sensory input. A failure in neuronal-activity-dependent regulation of ambient GABA, stemming largely from the depletion of GABA in extracellular space during senescence, may cause the degeneration of intracortical inhibition that leads to cognitive dysfunction in old animals.     

Robust control method for the inverted pendulum system with structured uncertainty caused by measurement error

In this article, we propose a design method for an inverted pendulum system with a structured uncertainty. We consider that such an uncertainty is caused by a measurement error in the rotation angle of the pendulum and effects on the system structure that cannot be included in the nominal elements. For the uncertain system obtained, we apply an integral tracking control and the guaranteed cost control to design a robust, stable, tracking control system. Finally, we show the effectiveness of our method through a numerical example.     

Vehicle inductive signatures recognition using a Madaline neural network

In this paper, we report results obtained with a Madaline neural network trained to classify inductive signatures of two vehicles classes: trucks with one rear axle and trucks with double rear axle. In order to train the Madaline, the inductive signatures were pre-processed and both classes, named C2 and C3, were subdivided into four subclasses. Thus, the initial classification task was split into four smaller tasks (theoretically) easier to be performed. The heuristic adopted in the training attempts to minimize the effects of the input space non-linearity on the classifier performance by uncoupling the learning of the classes and, for this, we induce output Adalines to specialize in learning one of the classes. The percentages of correct classifications presented concern patterns which were not submitted to the neural network in the training process, and, therefore, they indicate the neural network generalization ability. The results are good and stimulate the maintenance of this research on the use of Madaline networks in vehicle classification tasks using not linearly separable inductive signatures.     

Scale free interval graphs

Scale free graphs have attracted attention by their non-uniform structure that can be used as a model for various social and physical networks. In this paper, we propose a natural and simple random model for generating scale free interval graphs. The model generates a set of intervals randomly under a certain distribution, which defines a random interval graph. The main advantage of the model is its simpleness. The structure/properties of generated graphs are analyzable by relatively simple probabilistic and/or combinatorial arguments, which is different from many other models. Based on such arguments, we show for our random interval graph that its degree distribution follows a power law, and that it has a large average clustering coefficient.     

Interactive learning and management of visual information via human-like software robot

To achieve smooth real-world interaction between people and computers, we developed a system that displays a three-dimensional computer-graphic human-like image from the waist up (anthropomorphic software robot: hereinafter “robot”) on the display, that interactively sees and hears, and that has fine and detailed control functions such as facial expressions, line of sight, and pointing at targets with its finger. The robot visually searches and identifies persons and objects in real space that it has learned in advance (registered space, which was our office in this case), manages the history information of the places and times it found objects and/or persons, and tells the user, indicating their three-dimensional positions with line of sight and its finger. It interactively learns new objects and persons with line of with their names and owners. By using this function, the robot can engage in simple dialogue (do a task) with the user. Osamu Hasegawa, Ph.D.: He received the B.E. and M.E. degrees from the Science University of Tokyo, in 1988, 1990 respectively. He received Ph.D. degree from the University of Tokyo, in 1993. Currently, he is a senior research scientist at the Electrotechnical Laboratory (ETL), Tsukuba, Japan. His research interests include Computer Vision and Multi-modal Human Interface. Dr. Hasegawa is a member of the AAAI, the Institute of Electronics, Information and Communication Engineers, Japan (IEICE), Information Processing Society of Japan and others. Katsuhiko Sakaue, Ph.D.: He received the B.E., M.E., and Ph.D. degrees all in electronic engineering from the University of Tokyo, in 1976, 1978 and 1981, respectively. In 1981, he joined the Electrotechnical Laboratory, Ministry of International Trade and Industry, and engaged in researches in image processing and computer vision. He received the Encouragement Prize in 1979 from IEICE, and the Paper Award in 1985 from Information Processing Society of Japan. He is a member of IEICE, IEEE, IPSJ, ITE. Satoru Hayamizu, Ph.D.: He is a leader of Interactive Intermodal Integration Lab. at Electrotechnical Laboratory. He received the B.E., M.E., Ph.D. degrees from Tokyo University. Since 1981, he has been working on speech recognition, spoken dialogue, and communication with artifacts. From 1989 to 1990, he was a visiting scholar in Carnegie Mellon University and in 1994 a visiting scientist in LIMSI/CNRS.     

An application of the 2-nitrobenzenesulfenyl method to proteomic profiling of human colorectal carcinoma: A novel approach for biomarker discovery

In the development of novel biomarkers, the proteomic approach is advantageous because using it the cancer-associated proteins can be directly identified. We previously developed a 2-nitrobenzenesulfenyl (NBS) method to improve quantitative proteome analysis. Here, we applied this method to proteomic profiling of colorectal carcinoma (CRC) to identify novel proteins with altered expression in CRC. Each pair of tumor and normal tissue specimens from 12 CRC patients was analyzed, and approximately 5000 NBS-labeled paired peaks were quantified. Peaks with altered signal intensities (>1.5-fold) and occurring frequently in the samples (>70%) were selected, and 128 proteins were identified by MS/MS analyses as differentially expressed proteins in CRC tissues. Many proteins were newly revealed to be CRC related; 30 were reported in earlier studies of CRC. Six proteins that were up-regulated in CRC (ZYX, RAN, RCN1, AHCY, LGALS1, and VIM) were further characterized and validated by Western blot and immunohistochemistry. All six were found to be CRC-localized, either in cancer cells or in stroma cells near the cancer cells. These results indicate that the proteins identified in this study are novel candidates for CRC markers, and that the NBS method is useful in proteome mining to discover novel biomarkers.     

Spatiotemporal conversion of auditory information for cochleotopic mapping

Auditory communication signals such as monkey calls are complex FM vocal sounds and in general induce action potentials in different timing in the primary auditory cortex. Delay line scheme is one of the effective ways for detecting such neuronal timing. However, the scheme is not straightforwardly applicable if the time intervals of signals are beyond the latency time of delay lines. In fact, monkey calls are often expressed in longer time intervals (hundreds of milliseconds to seconds) and are beyond the latency times observed in the brain (less than several hundreds of milliseconds). Here, we propose a cochleotopic map similar to that in vision known as a retinotopic map. We show that information about monkey calls could be mapped on a cochleotopic cortical network as spatiotemporal firing patterns of neurons, which can then be decomposed into simple (linearly sweeping) FM components and integrated into unified percepts by higher cortical networks. We suggest that the spatiotemporal conversion of auditory information may be essential for developing the cochleotopic map, which could serve as the foundation for later processing, or monkey call identification by higher cortical areas.