An extended range of stable-symmetric-conservative Flux Reconstruction correction functions

The Flux Reconstruction (FR) approach offers an efficient route to achieving high-order accuracy on unstructured grids. Additionally, FR offers a flexible framework for defining a range of numerical schemes in terms of so-called FR correction functions. Recently, a one-parameter family of FR correction functions were identified that lead to stable schemes for 1D linear advection problems. In this study we develop a procedure for identifying an extended range of stable, symmetric, and conservative FR correction functions. The procedure is applied to identify ranges of such correction functions for various orders of accuracy. Numerical experiments are undertaken, and the results found to be in agreement with the theoretical findings

Low-Noise Amplification of a Continuous Variable Quantum State

We present an experimental realization of a low-noise, phase-insensitive optical amplifier using a four-wave mixing interaction in hot Rb vapor. Performance near the quantum limit for a range of amplifier gains, including near unity, can be achieved. Such low-noise amplifiers are essential for so-called quantum cloning machines and are useful in quantum information protocols. We demonstrate that amplification and ``cloning'' of one half of a two-mode squeezed state is possible while preserving entanglement.Comment: To appear in Physical Review Letters July 3rd. 4 pages, 4 figure

Savannah River Site Levels of Control Implementation

The Savannah River Site (SRS) established a prescriptive approach to defining and protecting major contributors to defense in depth in the mid '90s. This approach came in partial response to the Defense Nuclear Facility Safety Board (DNFSB) criticism at the time of inconsistent classifications between similar facilities at the site. This basic approach of a rigorous and prescriptive minimum definition of levels of control has been in place since that time. Recently SRS has changed its policy of defining major contributors to defense in depth to be a more qualitative approach, with no prescribed minimum number of levels of control. However, to assure that consistency is maintained, guidance has been developed to identify areas of attention when identifying the major contributors to defense in depth that receive the Safety Significant functional classification label or that are protected within the technical safety requirements. This paper discusses this guidance and its implementation within the overall hazard analysis and functional classification process. Based on the experience with selecting safety structures, systems and components (SSCs) and Administrative Controls, the Savannah River Site has moved from a prescriptive process of control selection based on numbers of levels of control (LOCs) and moved to an informed qualitative process. The guidance within the SRS procedure that governs control selection should permit consistency of application yet be true to the direction in the DOE standard in having these controls selected qualitatively with no prescribed minimum or maximum numbers of safety related controls. This revision to the SRS functional classification procedure and methodology manual has been conceptually approved by the SRS Authorization Basis Steering Committee responsible for the procedure

Literature-based discovery of diabetes- and ROS-related targets

Abstract Background Reactive oxygen species (ROS) are known mediators of cellular damage in multiple diseases including diabetic complications. Despite its importance, no comprehensive database is currently available for the genes associated with ROS. Methods We present ROS- and diabetes-related targets (genes/proteins) collected from the biomedical literature through a text mining technology. A web-based literature mining tool, SciMiner, was applied to 1,154 biomedical papers indexed with diabetes and ROS by PubMed to identify relevant targets. Over-represented targets in the ROS-diabetes literature were obtained through comparisons against randomly selected literature. The expression levels of nine genes, selected from the top ranked ROS-diabetes set, were measured in the dorsal root ganglia (DRG) of diabetic and non-diabetic DBA/2J mice in order to evaluate the biological relevance of literature-derived targets in the pathogenesis of diabetic neuropathy. Results SciMiner identified 1,026 ROS- and diabetes-related targets from the 1,154 biomedical papers (http://jdrf.neurology.med.umich.edu/ROSDiabetes/). Fifty-three targets were significantly over-represented in the ROS-diabetes literature compared to randomly selected literature. These over-represented targets included well-known members of the oxidative stress response including catalase, the NADPH oxidase family, and the superoxide dismutase family of proteins. Eight of the nine selected genes exhibited significant differential expression between diabetic and non-diabetic mice. For six genes, the direction of expression change in diabetes paralleled enhanced oxidative stress in the DRG. Conclusions Literature mining compiled ROS-diabetes related targets from the biomedical literature and led us to evaluate the biological relevance of selected targets in the pathogenesis of diabetic neuropathy.http://deepblue.lib.umich.edu/bitstream/2027.42/78315/1/1755-8794-3-49.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/2/1755-8794-3-49-S7.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/3/1755-8794-3-49-S10.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/4/1755-8794-3-49-S8.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/5/1755-8794-3-49-S3.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/6/1755-8794-3-49-S1.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/7/1755-8794-3-49-S4.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/8/1755-8794-3-49-S2.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/9/1755-8794-3-49-S12.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/10/1755-8794-3-49-S11.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/11/1755-8794-3-49-S9.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/12/1755-8794-3-49-S5.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/13/1755-8794-3-49-S6.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/14/1755-8794-3-49.pdfPeer Reviewe

DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders

This paper presents a novel deep learning-based method for learning a functional representation of mammalian neural images. The method uses a deep convolutional denoising autoencoder (CDAE) for generating an invariant, compact representation of in situ hybridization (ISH) images. While most existing methods for bio-imaging analysis were not developed to handle images with highly complex anatomical structures, the results presented in this paper show that functional representation extracted by CDAE can help learn features of functional gene ontology categories for their classification in a highly accurate manner. Using this CDAE representation, our method outperforms the previous state-of-the-art classification rate, by improving the average AUC from 0.92 to 0.98, i.e., achieving 75% reduction in error. The method operates on input images that were downsampled significantly with respect to the original ones to make it computationally feasible

Recognition without identification, erroneous familiarity, and déjà vu

Déjà vu is characterized by the recognition of a situation concurrent with the awareness that this recognition is inappropriate. Although forms of déjà vu resolve in favor of the inappropriate recognition and therefore have behavioral consequences, typical déjà vu experiences resolve in favor of the awareness that the sensation of recognition is inappropriate. The resultant lack of behavioral modification associated with typical déjà vu means that clinicians and experimenters rely heavily on self-report when observing the experience. In this review, we focus on recent déjà vu research. We consider issues facing neuropsychological, neuroscientific, and cognitive experimental frameworks attempting to explore and experimentally generate the experience. In doing this, we suggest the need for more experimentation and amore cautious interpretation of research findings, particularly as many techniques being used to explore déjà vu are in the early stages of development.PostprintPeer reviewe

Caspase-2 is upregulated after sciatic nerve transection and its inhibition protects dorsal root ganglion neurons from Apoptosis after serum withdrawal

Sciatic nerve (SN) transection-induced apoptosis of dorsal root ganglion neurons (DRGN) is one factor determining the efficacy of peripheral axonal regeneration and the return of sensation. Here, we tested the hypothesis that caspase-2(CASP2) orchestrates apoptosis of axotomised DRGN both in vivo and in vitro by disrupting the local neurotrophic supply to DRGN. We observed significantly elevated levels of cleaved CASP2 (C-CASP2), compared to cleaved caspase-3 (C-CASP3), within TUNEL+DRGN and DRG glia (satellite and Schwann cells) after SN transection. A serum withdrawal cell culture model, which induced 40% apoptotic death in DRGN and 60% in glia, was used to model DRGN loss after neurotrophic factor withdrawal. Elevated C-CASP2 and TUNEL were observed in both DRGN and DRG glia, with C-CASP2 localisation shifting from the cytosol to the nucleus, a required step for induction of direct CASP2-mediated apoptosis. Furthermore, siRNAmediated downregulation of CASP2 protected 50% of DRGN from apoptosis after serum withdrawal, while downregulation of CASP3 had no effect on DRGN or DRG glia survival. We conclude that CASP2 orchestrates the death of SN-axotomised DRGN directly and also indirectly through loss of DRG glia and their local neurotrophic factor support. Accordingly, inhibiting CASP2 expression is a potential therapy for improving both the SN regeneration response and peripheral sensory recovery

Direct entropy determination and application to artificial spin ice

From thermodynamic origins, the concept of entropy has expanded to a range of statistical measures of uncertainty, which may still be thermodynamically significant. However, laboratory measurements of entropy continue to rely on direct measurements of heat. New technologies that can map out myriads of microscopic degrees of freedom suggest direct determination of configurational entropy by counting in systems where it is thermodynamically inaccessible, such as granular and colloidal materials, proteins and lithographically fabricated nanometre-scale arrays. Here, we demonstrate a conditional-probability technique to calculate entropy densities of translation-invariant states on lattices using limited configuration data on small clusters, and apply it to arrays of interacting nanometre-scale magnetic islands (artificial spin ice). Models for statistically disordered systems can be assessed by applying the method to relative entropy densities. For artificial spin ice, this analysis shows that nearest-neighbour correlations drive longer-range ones.Comment: 10 page

Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics

Dozens of new models on fixation prediction are published every year and compared on open benchmarks such as MIT300 and LSUN. However, progress in the field can be difficult to judge because models are compared using a variety of inconsistent metrics. Here we show that no single saliency map can perform well under all metrics. Instead, we propose a principled approach to solve the benchmarking problem by separating the notions of saliency models, maps and metrics. Inspired by Bayesian decision theory, we define a saliency model to be a probabilistic model of fixation density prediction and a saliency map to be a metric-specific prediction derived from the model density which maximizes the expected performance on that metric given the model density. We derive these optimal saliency maps for the most commonly used saliency metrics (AUC, sAUC, NSS, CC, SIM, KL-Div) and show that they can be computed analytically or approximated with high precision. We show that this leads to consistent rankings in all metrics and avoids the penalties of using one saliency map for all metrics. Our method allows researchers to have their model compete on many different metrics with state-of-the-art in those metrics: "good" models will perform well in all metrics.Comment: published at ECCV 201

Collapse of superconductivity in a hybrid tin-graphene Josephson junction array

When a Josephson junction array is built with hybrid superconductor/metal/superconductor junctions, a quantum phase transition from a superconducting to a two-dimensional (2D) metallic ground state is predicted to happen upon increasing the junction normal state resistance. Owing to its surface-exposed 2D electron gas and its gate-tunable charge carrier density, graphene coupled to superconductors is the ideal platform to study the above-mentioned transition between ground states. Here we show that decorating graphene with a sparse and regular array of superconducting nanodisks enables to continuously gate-tune the quantum superconductor-to-metal transition of the Josephson junction array into a zero-temperature metallic state. The suppression of proximity-induced superconductivity is a direct consequence of the emergence of quantum fluctuations of the superconducting phase of the disks. Under perpendicular magnetic field, the competition between quantum fluctuations and disorder is responsible for the resilience at the lowest temperatures of a superconducting glassy state that persists above the upper critical field. Our results provide the entire phase diagram of the disorder and magnetic field-tuned transition and unveil the fundamental impact of quantum phase fluctuations in 2D superconducting systems.Comment: 25 pages, 6 figure