The Origin of Large-scale HI structures in the Magellanic Bridge

We investigate the formation of a number of key large-scale HI features in the ISM of the Magellanic Bridge using dissipationless numerical simulation techniques. This study comprises the first direct comparison between detailed HI maps of the Bridge and numerical simulations. We confirm that the SMC forms two tidal filaments: a near arm, which forms the connection between the SMC and LMC, and a counterarm. We show that the HI of the most dense part of the Bridge can become arranged into a bimodal configuration, and that the formation of a "loop" of HI, located off the North-Eastern edge of the SMC can be reproduced simply as a projection of the counter-arm, and without invoking localised energy-deposition processes such as SNe or stellar winds.Comment: 5 Pages, 4 Figures, Accepted - MNRAS let

Neural Sampling by Irregular Gating Inhibition of Spiking Neurons and Attractor Networks

A long tradition in theoretical neuroscience casts sensory processing in the brain as the process of inferring the maximally consistent interpretations of imperfect sensory input. Recently it has been shown that Gamma-band inhibition can enable neural attractor networks to approximately carry out such a sampling mechanism. In this paper we propose a novel neural network model based on irregular gating inhibition, show analytically how it implements a Monte-Carlo Markov Chain (MCMC) sampler, and describe how it can be used to model networks of both neural attractors as well as of single spiking neurons. Finally we show how this model applied to spiking neurons gives rise to a new putative mechanism that could be used to implement stochastic synaptic weights in biological neural networks and in neuromorphic hardware

Pittsburgh's Failed Industry Targeting Strategy of the 1960s

In the 1960's and early 1970's, public and private leaders made a substantial effort to promote Pittsburgh's existing transportation industry as a center for the emerging urban transportation market. The selection of the rapid transit industry for targeting in the 1960's purportedly addressed two issues. Despite national acclaim for its Renaissance redevelopment since World War II, the metropolitan region still needed an effective mass transportation system. Moreover, industrial development efforts had not substantially diversified the region's manufacturing base that still specialized in primary metals. Operating in the region's Renaissance tradition of a public and private partnership, corporate executives and public officials pursued a three-pronged strategy: build an innovative rapid transportation system for Allegheny County, use it as a showcase for testing and marketing rapid transit hardware of regional corporations, and promote the city as a center of the rapid transportation industry. They settled on Westinghouse's automated, rubber-tired vehicle running on a separate cement guideway, known locally as "Skybus," for the demonstration project and the region's mass transit solution. The mass transit plan and industry targeting strategy foundered by the early 1970's because leadership weakened in both poles of the partnership. The Westinghouse technology divided the corporate community, while populist political sentiment diminished the ability of the Democratic party's political machine to deliver key public decisions. The Pittsburgh case suggests that a successful industry targeting strategy may depend more on effective leadership and local politics than on the quality of the selection process and vigorous pursuit of traditional economic development programs in support of the targeted industry

Microscopic Description of Deeply Virtual Compton Scattering off Spin-0 Nuclei

We evaluate within a microscopic calculation the contributions of both coherent and incoherent deeply virtual Compton scattering from a spin-0 nucleus. The coherent contribution is obtained when the target nucleus recoils as a whole, whereas for incoherent scattering break-up configurations for the final nucleus into a an outgoing nucleon and an $A-1$ system are considered. The two processes encode different characteristics of generalized parton distributions.Comment: 7 pages, 3 figure

The attainable superconducting Tc in a model of phase coherence by percolation

The onset of macroscopic phase coherence in superconducting cuprates is considered to be determined by random percolation between mesoscopic Jahn-Teller pairs, stripes or clusters. The model is found to predict the onset of superconductivity near 6% doping, maximum Tc near 15% doping and Tc= T* at optimum doping, and accounts for the destruction of superconductivity by Zn doping near 7%. The model also predicts a relation between the pairing (pseudogap) energy and Tc in terms of experimentally measurable quantities.Comment: 3 pages + 3 postscript figure

A differential memristive synapse circuit for on-line learning in neuromorphic computing systems

Spike-based learning with memristive devices in neuromorphic computing architectures typically uses learning circuits that require overlapping pulses from pre- and post-synaptic nodes. This imposes severe constraints on the length of the pulses transmitted in the network, and on the network's throughput. Furthermore, most of these circuits do not decouple the currents flowing through memristive devices from the one stimulating the target neuron. This can be a problem when using devices with high conductance values, because of the resulting large currents. In this paper we propose a novel circuit that decouples the current produced by the memristive device from the one used to stimulate the post-synaptic neuron, by using a novel differential scheme based on the Gilbert normalizer circuit. We show how this circuit is useful for reducing the effect of variability in the memristive devices, and how it is ideally suited for spike-based learning mechanisms that do not require overlapping pre- and post-synaptic pulses. We demonstrate the features of the proposed synapse circuit with SPICE simulations, and validate its learning properties with high-level behavioral network simulations which use a stochastic gradient descent learning rule in two classification tasks.Comment: 18 Pages main text, 9 pages of supplementary text, 19 figures. Patente