Scalable Massively Parallel Artificial Neural Networks

There is renewed interest in computational intelligence, due to advances in algorithms, neuroscience, and computer hardware. In addition there is enormous interest in autonomous vehicles (air, ground, and sea) and robotics, which need significant onboard intelligence. Work in this area could not only lead to better understanding of the human brain but also very useful engineering applications. The functioning of the human brain is not well understood, but enormous progress has been made in understanding it and, in particular, the neocortex. There are many reasons to develop models of the brain. Artificial Neural Networks (ANN), one type of model, can be very effective for pattern recognition, function approximation, scientific classification, control, and the analysis of time series data. ANNs often use the back-propagation algorithm for training, and can require large training times especially for large networks, but there are many other types of ANNs. Once the network is trained for a particular problem, however, it can produce results in a very short time. Parallelization of ANNs could drastically reduce the training time. An object-oriented, massively-parallel ANN (Artificial Neural Network) software package SPANN (Scalable Parallel Artificial Neural Network) has been developed and is described here. MPI was use

VLBI ecliptic plane survey: VEPS-1

We present here the results of the first part of the VLBI Ecliptic Plane Survey (VEPS) program. The goal of the program is to find all compact sources within 7○̣5 of the ecliptic plane that are suitable as calibrators for anticipated phase referencing observations of spacecraft, and determine their positions with accuracy at the 1.5 nrad level. We run the program in two modes: search and refine. In the search mode, a complete sample of all sources brighter than 50 mJy at 5 GHz listed in the Parkes-MIT-NRAO and Green Bank 6 cm (GB6) catalogs, except those previously detected with VLBI, is observed. In the refining mode, the positions of all ecliptic plane sources, including those found in the search mode, are improved. By 2016 October, thirteen 24 hr sessions that targeted all sources brighter than 100 mJy have been observed and analyzed. Among 3320 observed target sources, 555 objects have been detected. We also conducted a number of follow-up VLBI experiments in the refining mode and improved the positions of 249 ecliptic plane sources

MAP1B Regulates Axonal Development by Modulating Rho-GTPase Rac1 Activity

This article shows a novel function for the MAP1B protein, related to the control of actin dynamics through interaction with Tiam1

Non-Small Cell Lung Carcinoma Cell Motility, Rac Activation and Metastatic Dissemination Are Mediated by Protein Kinase C Epsilon

Background: Protein kinase C (PKC) e, a key signaling transducer implicated in mitogenesis, survival, and cancer progression, is overexpressed in human primary non-small cell lung cancer (NSCLC). The role of PKCe in lung cancer metastasis has not yet been established. Principal Findings: Here we show that RNAi-mediated knockdown of PKCe in H358, H1299, H322, and A549 NSCLC impairs activation of the small GTPase Rac1 in response to phorbol 12-myristate 13-acetate (PMA), serum, or epidermal growth factor (EGF). PKCe depletion markedly impaired the ability of NSCLC cells to form membrane ruffles and migrate. Similar results were observed by pharmacological inhibition of PKCe with eV1-2, a specific PKCe inhibitor. PKCe was also required for invasiveness of NSCLC cells and modulated the secretion of extracellular matrix proteases and protease inhibitors. Finally, we found that PKCe-depleted NSCLC cells fail to disseminate to lungs in a mouse model of metastasis. Conclusions: Our results implicate PKCe as a key mediator of Rac signaling and motility of lung cancer cells, highlighting its potential as a therapeutic target

Design and optimisation of a footfall energy harvesting system

The scavenging of electrical energy from normal human activity has a number of attractions, and footfall energy is seen as one of the most attractive sources. However, footfall motion is characterised by relatively large forces and low velocities, and this makes it inherently poorly matched to electromagnetic generators which operate most efficiently at high speeds. In order to achieve an efficient velocity amplification, a novel mechanism has been developed which makes use of a spring and flywheel as energy storage elements and a ‘striker’ mechanism which controls energy storage and release. This energy harvesting mechanism is capable of being used either in footwear or under a floor. In this article, the structure of the proposed mechanism is described; the optimisation of the system parameters, based on a dynamic model, is discussed; and experimental results for an under-floor system are presented

moving distance

The proposed device is for measuring the movement of leg or arm. The device is composed of Arduino Nano and mini USB-HOST. Exploiting mouse's scroll wheel can provide the accurate measurement of the moving distance of leg or arm.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV