Supervised Associative Learning in Spiking Neural Network

In this paper, we propose a simple supervised associative learning approach for spiking neural networks. In an excitatory-inhibitory network paradigm with Izhikevich spiking neurons, synaptic plasticity is implemented on excitatory to excitatory synapses dependent on both spike emission rates and spike timings. As results of learning, the network is able to associate not just familiar stimuli but also novel stimuli observed through synchronised activity within the same subpopulation and between two associated subpopulations

The FPGA-based Continious FFT Tune Measurement System for the LHC and its test at the CERN SPS

A base band tune (BBQ) measurement system has been developed at CERN. This system is based on a high-sensitivity direct-diode detection technique followed by a high resolution FFT algorithm implemented in an FPGA. The system allows acquisition of continuous real-time spectra with 32-bit resolution, while a digital frequency synthesiser (DFS) can provide an acquisition synchronised chirp excitation. All the implemented algorithms support dynamic reconfiguration of processing and excitation parameters. Results from both laboratory measurements and tests performed with beam at the CERN SPS are presented

Transverse Impedance of LHC Collimators

The transverse impedance in the LHC is expected to be dominated by the numerous collimators, most of which are made of Fibre-Reinforced-Carbon to withstand the impacts of high intensity proton beams in case of failures, and which will be moved very close to the beam, with full gaps of few millimetres, in order to protect surrounding super-conducting equipments. We present an estimate of the transverse resistive-wall impedance of the LHC collimators, the total impedance in the LHC at injection and top energy, the induced coupled-bunch growth rates and tune shifts, and finally the result of the comparison of the theoretical predictions with measurements performed in 2004 and 2006 on a prototype collimator installed in the SPS

Estimating Level of Engagement from Ocular Landmarks

E-learning offers many advantages like being economical, flexible and customizable, but also has challenging aspects such as lack of – social-interaction, which results in contemplation and sense of remoteness. To overcome these and sustain learners’ motivation, various stimuli can be incorporated. Nevertheless, such adjustments initially require an assessment of engagement level. In this respect, we propose estimating engagement level from facial landmarks exploiting the facts that (i) perceptual decoupling is promoted by blinking during mentally demanding tasks; (ii) eye strain increases blinking rate, which also scales with task disengagement; (iii) eye aspect ratio is in close connection with attentional state and (iv) users’ head position is correlated with their level of involvement. Building empirical models of these actions, we devise a probabilistic estimation framework. Our results indicate that high and low levels of engagement are identified with considerable accuracy, whereas medium levels are inherently more challenging, which is also confirmed by inter-rater agreement of expert coders

Microscopic Analysis For Water Stressed By High Electric Fields In The Prebreakdown Regime

Analysis of the electrical double layer at the electrode-water interface for voltages close to the breakdown point has been carried out based on a static, Monte Carlo approach. It is shown that strong dipole realignment, ion-ion correlation, and finite-size effects can greatly modify the electric fields and local permittivity (hence, leading to optical structure) at the electrode interface. Dramatic enhancements of Schottky injection, providing a source for electronic controlled breakdown, are possible. It is also shown that large pressures associated with the Maxwell stress tensor would be created at the electrode boundaries. Our results depend on the ionic density, and are in keeping with recent observations. A simple, perturbative analysis shows that high field regions with a sharp variation in permittivity can potentially be critical spots for instability initiation. This suggests that the use of polished electrodes, or composite materials, or alternative nonpolar liquids might help enhance high-voltage operation

MicroRNA-135b promotes cancer progression by acting as a downstream effector of oncogenic pathways in colon cancer

MicroRNA deregulation is frequent in human colorectal cancers (CRCs), but little is known as to whether it represents a bystander event or actually drives tumor progression in vivo. We show that miR-135b overexpression is triggered in mice and humans by APC loss, PTEN/PI3K pathway deregulation, and SRC overexpression and promotes tumor transformation and progression. We show that miR-135b upregulation is common in sporadic and inflammatory bowel disease-associated human CRCs and correlates with tumor stage and poor clinical outcome. Inhibition of miR-135b in CRC mouse models reduces tumor growth by controlling genes involved in proliferation, invasion, and apoptosis. We identify miR-135b as a key downsteam effector of oncogenic pathways and a potential target for CRC treatment

Computational modeling with spiking neural networks

This chapter reviews recent developments in the area of spiking neural networks (SNN) and summarizes the main contributions to this research field. We give background information about the functioning of biological neurons, discuss the most important mathematical neural models along with neural encoding techniques, learning algorithms, and applications of spiking neurons. As a specific application, the functioning of the evolving spiking neural network (eSNN) classification method is presented in detail and the principles of numerous eSNN based applications are highlighted and discussed

Diphenyl Difluoroketone: A Potent Chemotherapy Candidate for Human Hepatocellular Carcinoma

Diphenyl difluoroketone (EF24), a molecule having structural similarity to curcumin, was recently reported to inhibit proliferation of various cancer cells significantly. Here we try to determine the effect and mechanism of EF24 on hepatocellular carcinoma. 2 µM EF24 was found to inhibit the proliferation of PLC/PRF/5, Hep3B, HepG2, SK-HEP-1 and Huh 7 cell lines. However, even 8 µM EF24 treatment did not affect the proliferation of normal liver LO2 cells. Accordingly, 20 mg/kg/d EF24 inhibited the growth of the tumor xenografts conspicuously while causing no apparent change in liver, spleen or body weight. In addition, significant apoptosis and G2/M phase cell cycle arrest were found using flow cytometry. Besides, caspases and PARP activation and features typical of apoptosis including fragmented nuclei with condensed chromatin were also observed. Furthermore, the mechanism was targeted at the reduction of nuclear factor kappa b (NF-κB) pathway and the NF-κB–regulated gene products Bcl-2, COX-2, Cyclin B1. Our study has offered a strategy that EF24 being a therapeutic agent for hepatocellular carcinoma