313 research outputs found
Bone Marrow Stem Cell Treatment for Ischemic Heart Disease in Patients with No Option of Revascularization: A Systematic Review and Meta-Analysis
No full textPMCID: PMC3686792This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Barrow Weight-lifting club
No full textweight-lifting, e. williams, p. williams, J. Brunskill, H. Field, A. Hardie, A. Smith, H. Adams, J Stewar
Experimental and numerical modelling of wheel rail contact and wear
No full textIn the field of simulation of railroad vehicles, there are many numerical models to estimate the interaction forces between the wheel and rail. The main advantage of these models is that they can be used together with multi-body dynamics software to calculate the motion of a vehicle in real time. However, the result of these contact models is usually post-processed to estimate wear on the profiles and some hypotheses assumed by the contact models may be inadequate for wear analysis. This is the case when considering surface roughness, which is not introduced in the numerical models and makes wear prediction imprecise. In this work an experimental method based on the measurement of ultrasonic reflection is used to solve the contact problem, together with a FASTSIM (simplified theory of rolling contact) algorithm. This technique is suitable to deal with rough surfaces and gives a better approximation of the material behaviour. Wear is estimated by means of the energy dissipation approach (T·gamma). Two different contacts are investigated, using wheel and rail profiles coming from unused and worn specimens. In order to obtain realistic results, special care is taken when locating the specimens to reproduce the same contact that appears between the wheel and the rail in the track.The corresponding author gratefully acknowledges the cooperation of C. Hardwick and Portec Rail Inc. for supplying the Miniprof device. This research was supported by Universitat Politecnica de Valencia (Spain).Rovira Cardete, A.; Roda Buch, A.; Marshall, M.; Brunskill, H.; Lewis, R. (2011). Experimental and numerical modelling of wheel rail contact and wear. Wear. 271(5-6):911-924. doi:10.1016/j.wear.2011.03.024S9119242715-
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming
No full textIn this paper, we introduce BNN-DP, an efficient algorithmic framework for analysis of adversarial robustness of Bayesian Neural Networks (BNNs). Given a compact set of input points T ⊂ Rn, BNN-DP computes lower and upper bounds on the BNN's predictions for all the points in T. The framework is based on an interpretation of BNNs as stochastic dynamical systems, which enables the use of Dynamic Programming (DP) algorithms to bound the prediction range along the layers of the network. Specifically, the method uses bound propagation techniques and convex relaxations to derive a backward recursion procedure to over-approximate the prediction range of the BNN with piecewise affine functions. The algorithm is general and can handle both regression and classification tasks. On a set of experiments on various regression and classification tasks and BNN architectures, we show that BNN-DP outperforms state-of-the-art methods by up to four orders of magnitude in both tightness of the bounds and computational efficiency.Team Luca Laurent
Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts
No full textWe investigate online classification with paid stochastic experts. Here, before making their prediction, each expert must be paid. The amount that we pay each expert directly influences the accuracy of their prediction through some unknown Lipschitz “productivity” function. In each round, the learner must decide how much to pay each expert and then make a prediction. They incur a cost equal to a weighted sum of the prediction error and upfront payments for all experts. We introduce an online learning algorithm whose total cost after rounds exceeds that of a predictor which knows the productivity of all experts in advance by at most where is the number of experts. In order to achieve this result, we combine Lipschitz bandits and online classification with surrogate losses. These tools allow us to improve upon the bound of order one would obtain in the standard Lipschitz bandit setting. Our algorithm is empirically evaluated on synthetic data
The electronics industry: inward investment versus indigenous development -- the policy debate
No full textIn this paper the public policy implications of an active government strategy aimed at enhancing the competitiveness of the electronics industry in Britain are examined. The author argues that as a general principle industrial policy should be both designed and applied at as low a level as possible. To achieve this a comprehensive but decentralised institutional economic development network will need to be created.
Association and interactions of GTP-binding proteins with rat medullary H(+)-ATPase
No full text Guanosine 5'-triphosphate (GTP)-binding proteins (G proteins) are expressed in a heterogeneous manner in the mammalian kidney. In particular, cells of the medullary collecting tubule demonstrate a complex pattern of G protein expression both between cell types and between the polarized surfaces of individual cells. Intercalated cells expressing the H(+)-ATPase are also prevalent in this nephron segment. To examine interactions between G proteins and the H(+)-ATPase, we performed immunocytochemical studies on perfusion-fixed sections of rat kidney using polyclonal anti-G protein antibodies and E11, a mouse monoclonal antibody to the 31-kDa subunit of the vacuolar H(+)-ATPase. G alpha s subunits were consistently not associated with cells containing the H(+)-ATPase in this nephron segment, whereas G alpha i-2, G alpha i-3, and G alpha q/11 were. Some intercalated cells that stained prominently for the proton pump in the apical membrane did not, however, stain for any G protein alpha-subunit. We prepared medullary membrane vesicles highly enriched for the H(+)-ATPase to examine possible functional interactions of G proteins with the H(+)-ATPase by the acridine orange method. These vesicles were also highly enriched for G protein subunits. Proton transport was significantly increased in the presence of guanosine 5'-O-(3-thiotriphosphate), and this held true in the absence of chloride. This excludes an effect on chloride conductance indirectly stimulating the H(+)-ATPase. Guanine nucleotides did not affect the proton leak of the vesicles. Thus some G proteins are associated with the H(+)-ATPase and can regulate its function; however, the particular G proteins involved remain to be identified. </jats:p
Counterfactual imagination impairs memory for true actions: EEG and behavioural evidence
No full textImagined events can be misremembered as experienced, leading to memory distortions. However, less is known regarding how imagining counterfactual versions of past events can impair existing memories. We addressed this issue, and used EEG to investigate the neurocognitive processes involved when retrieving memories of true events that are associated with a competing imagined event. Participants first performed simple actions with everyday objects (e.g., rolling dice). A week later, they were shown pictures of some of the objects and either imagined the same action they had originally performed, or imagined a counterfactual action (e.g., stacking the dice). Subsequent tests showed that memory for performed actions was reduced after counterfactual imagination when compared to both veridical imagination and a baseline condition that had not been imagined at all, providing novel evidence that counterfactual imagination impairs true memories beyond simple forgetting over time. ERPs and EEG oscillations showed evidence of separate processes associated with memory retrieval versus post-retrieval processes that were recruited to support recall of memories that were challenging to access. The findings show that counterfactual imagination can cause impairments to sensorimotor-rich event memories, and provide new evidence regarding the neurocognitive mechanisms that are recruited when people need to distinguish memories of imagined versus true events
Towards Theoretical Understanding of Inverse Reinforcement Learning
No full textInverse reinforcement learning (IRL) denotes a powerful family of algorithms for recovering a reward function justifying the behavior demonstrated by an expert agent. A well-known limitation of IRL is the ambiguity in the choice of the reward function, due to the existence of multiple rewards that explain the observed behavior. This limitation has been recently circumvented by formulating IRL as the problem of estimating the feasible reward set, i.e., the region of the rewards compatible with the expert’s behavior. In this paper, we make a step towards closing the theory gap of IRL in the case of finite-horizon problems with a generative model. We start by formally introducing the problem of estimating the feasible reward set, the corresponding PAC requirement, and discussing the properties of particular classes of rewards. Then, we provide the first minimax lower bound on the sample complexity for the problem of estimating the feasible reward set of order , being and the number of states and actions respectively, the horizon, the desired accuracy, and the confidence. We analyze the sample complexity of a uniform sampling strategy (US-IRL), proving a matching upper bound up to logarithmic factors. Finally, we outline several open questions in IRL and propose future research directions
The layered perovskites (C<sub>3</sub>H<sub>7</sub>NH<sub>3</sub>)<sub>2</sub>MnCl<sub>4</sub>(PAMC) and (C<sub>2</sub>H<sub>5</sub>NH<sub>3</sub>)<sub>2</sub>MnCl<sub>4</sub>(EAMC): birefringence studies and the symmetry of the commensurately modulated ε phase of PAMC
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