Effective numerical treatment of sub-diffusion equation with non-smooth solution

In this paper we investigate a sub-diffusion equation for simulating the anomalous diffusion phenomenon in real physical environment. Based on an equivalent transformation of the original sub-diffusion equation followed by the use of a smooth operator, we devise a high-order numerical scheme by combining the Nystrom method in temporal direction with the compact finite difference method and the spectral method in spatial direction. The distinct advantage of this approach in comparison with most current methods is its high convergence rate even though the solution of the anomalous sub-diffusion equation usually has lower regularity on the starting point. The effectiveness and efficiency of our proposed method are verified by several numerical experiments.Comment: 15 pages, 6 figure

Control over stress induces plasticity of individual prefrontal cortical neurons: A conductance-based neural simulation

Behavioral control over stressful stimuli induces resilience to future conditions when control is lacking. The medial prefrontal cortex(mPFC) is a critically important brain region required for plasticity of stress resilience. We found that control over stress induces plasticity of the intrinsic voltage-gated conductances of pyramidal neurons in the PFC. To gain insight into the underlying biophysical mechanisms of this plasticity we used the conductance- based neural simulation software tool, NEURON, to model the increase in membrane excitability associated with resilience to stress. A ball and stick multicompartment conductance-based model was used to realistically fit passive and active data traces from prototypical pyramidal neurons in neurons in rats with control over tail shock stress and those lacking control. The results indicate that the plasticity of membrane excitability associated with control over stress can be attributed to an increase in Na+ and Ca2+ T-type conductances and an increase in the leak conductance. Using simulated dendritic synaptic inputs we observed an increase in excitatory postsynaptic summation and amplification resulting in elevated action potential output. This realistic simulation suggests that control over stress enhances the output of the PFC and offers specific testable hypotheses to guide future electrophysiological mechanistic studies in animal models of resilience and vulnerability to stress

NPRF: A Neural Pseudo Relevance Feedback Framework for Ad-hoc Information Retrieval

Pseudo-relevance feedback (PRF) is commonly used to boost the performance of traditional information retrieval (IR) models by using top-ranked documents to identify and weight new query terms, thereby reducing the effect of query-document vocabulary mismatches. While neural retrieval models have recently demonstrated strong results for ad-hoc retrieval, combining them with PRF is not straightforward due to incompatibilities between existing PRF approaches and neural architectures. To bridge this gap, we propose an end-to-end neural PRF framework that can be used with existing neural IR models by embedding different neural models as building blocks. Extensive experiments on two standard test collections confirm the effectiveness of the proposed NPRF framework in improving the performance of two state-of-the-art neural IR models.Comment: Full paper in EMNLP 201