363 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
Classical and novel hormonal influences on renal tubular transport and the emerging concept of “intracrine” regulation
No full textWhere to go: Interpreting natural directions using global inference
No full textAn important component of human-robot interaction is that people need to be able to instruct robots to move to other locations using naturally given directions. When giving directions, people often make mistakes such as labelling errors (e.g., left vs. right) and errors of omission (skipping important decision points in a sequence). Furthermore, people often use multiple levels of granularity in specifying directions, referring to locations using single object landmarks, multiple landmarks in a given location, or identifying large regions as a single location. The challenge is to identify the correct path to a destination from a sequence of noisy, possibly erroneous directions. In our work we cast this problem as probabilistic inference: given a set of directions, an agent should automatically find the path with the geometry and physical appearance to maximize the likelihood of those directions. We use a specific variant of a Markov Random Field (MRF) to represent our model, and gather multi-granularity representation information using existing large tagged datasets. On a dataset of route directions collected in a large third floor university building, we found that our algorithm correctly inferred the true final destination in 47 out of the 55 cases successfully followed by humans volunteers. These results suggest that our algorithm is performing well relative to human users. In the future this work will be included in a broader system for autonomously constructing environmental representations that support natural human-robot interaction for direction giving.United States. Air Force Office of Scientific Research (Agile Robotics project, contract number 7000038334)National Science Foundation (U.S.) (NSF Division of Information and Intelligent Systems under grant # 0546467)Massachusetts Institute of Technology (Hugh Hampton Young Memorial Fund Fellowship)United States. Office of Naval Research (MURI N00014-07-1-0749
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
Barrow Weight-lifting club
No full textweight-lifting, e. williams, p. williams, J. Brunskill, H. Field, A. Hardie, A. Smith, H. Adams, J Stewar
C-peptide reverses TGF- 1-induced changes in renal proximal tubular cells: implications for treatment of diabetic nephropathy
No full textHills CE, Al-Rasheed N, Al-Rasheed N, Willars GB, Brunskill NJ. C-peptide reverses TGF-beta 1-induced changes in renal proximal tubular cells: implications for treatment of diabetic nephropathy. Am J Physiol Renal Physiol 296: F614-F621, 2009. First published December 17, 2008; doi:10.1152/ajprenal.90500.2008.-The crucial pathology underlying progressive chronic kidney disease in diabetes is tubulointerstitial fibrosis. Central to this process is epithelial-mesenchymal transformation (EMT) of proximal tubular epithelial cells driven by maladaptive transforming growth factor-beta 1 (TGF-beta 1) signaling. Novel signaling roles for C-peptide have recently been discovered with evidence emerging that C-peptide may mitigate microvascular complications of diabetes. We studied the potential for C-peptide to interrupt injurious TGF-beta 1 signaling pathways and thus block development of EMT in HK2 human kidney proximal tubular cells. Cells were incubated with TGF-beta 1 either alone or with C-peptide in low or high glucose. Changes in cell morphology, TGF-beta 1 receptor expression, vimentin, E-cadherin, and phosphorylated Smads were assessed. Luciferase reporters were used to assess Smad activity. The cytoskeleton was visualized by TRITC-phalloidin staining. The typical TGF-beta 1-stimulated, EMT-associated morphological alterations of proximal tubular cells, including increased vimentin expression, decreased E-cadherin expression, and cytoskeletal rearrangements, were prevented by C-peptide treatment. C-peptide also blocked TGF-beta 1-induced upregulation of expression of both type I and type II TGF-beta 1 receptors and attenuated TGF-beta 1-mediated Smad phosphorylation and Smad transcriptional activity. These effects of c-peptide were inhibited by pertussis toxin. The results demonstrate that C-peptide almost completely reversed the morphological changes in PT cells induced by TGF-beta 1 and suggest a role or c-peptide as a renoprotective agent in diabetic nephropathy
Pro-coagulant haemostatic factors for the prevention and treatment of bleeding in patients without haemophilia
No full textThe 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.
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-
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
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