Electrical and optical spectroscopy for quantitative screening of hepatic steatosis in donor livers.

Macro-steatosis in deceased donor livers is increasingly prevalent and is associated with poor or non-function of the liver upon reperfusion. Current assessment of the extent of steatosis depends upon the macroscopic assessment of the liver by the surgeon and histological examination, if available. In this paper we demonstrate electrical and optical spectroscopy techniques which quantitatively characterize fatty infiltration in liver tissue. Optical spectroscopy showed a correlation coefficient of 0.85 in humans when referenced to clinical hematoxylin and eosin (H&E) sections in 20 human samples. With further development, an optical probe may provide a comprehensive measure of steatosis across the liver at the time of procurement.

Hydrodynamic entrapment of bacteria swimming near a solid surface.

The near-surface motility of bacteria is important in the initial formation of biofilms and in many biomedical applications. The swimming motion of Escherichia coli near a solid surface is investigated both numerically and experimentally. A boundary element method is used to predict the hydrodynamic entrapment of E. coli bacteria, their trajectories, and the minimum separation of the cell from the surface. The numerical results show the existence of a stable swimming distance from the boundary that depends only on the shape of the cell body and the flagellum. The experimental validation of the numerical approach allows one to use the numerical method as a predictive tool to estimate with reasonable accuracy the near-wall motility of swimming bacteria of known geometry. The analysis of the numerical database demonstrated the existence of a correlation between the radius of curvature of the near-wall circular trajectory and the separation gap. Such correlation allows an indirect estimation of either of the two quantities by a direct measure of the other without prior knowledge of the cell geometry. This result may prove extremely important in those biomedical and technical applications in which the near-wall behavior of bacteria is of fundamental importance.

Preliminary evaluation of conceptual mechanical designs

Computational Design has traditionally required a great deal of geometrical and parametric data. This data can only be supplied at stages later than conceptual design, typically the detail stage, and design quality is given by some absolute fitness function. On the other hand, design evaluation offers a relative measure of design quality that requires only a sparse representation. Quality, in this case, is a measure of how well a design will complete its task.

The research intends to address the question: "Is it possible to evaluate a mechanical design at the conceptual design phase and be able to make some prediction of its quality?" Quality can be interpreted as success in the marketplace, success in performing the required task, or some other user requirement. This work aims to determine a minimum level of representation such that conceptual designs can be usefully evaluated without needing to capture detailed geometry. This representation will form the model for the conceptual designs that are being considered for evaluation. The method to be developed will be a case-based evaluation system, that uses a database of previous designs to support design exploration. The method will not be able to support novel design as case-based design implies the model topology must be fixed.

Measurement of liquid film thickness by optical fluorescence and its application to an oscillating piston positive displacement flowmeter

The movement of the circular piston in an oscillating piston positive displacement flowmeter is important in understanding the operation of the flowmeter, and the leakage of liquid past the piston plays a key role in the performance of the meter. The clearances between the piston and the chamber are small, typically less than 60 νm. In order to measure this film thickness a fluorescent dye was added to the water passing through the meter, which was illuminated with UV light. Visible light images were captured with a digital camera and analysed to give a measure of the film thickness with an uncertainty of less than 7%. It is known that this method lacks precision unless careful calibration is undertaken. Methods to achieve this are discussed in the paper. The grey level values for a range of film thicknesses were calibrated in situ with six dye concentrations to select the most appropriate one for the range of liquid film thickness. Data obtained for the oscillating piston flowmeter demonstrate the value of the fluorescence technique. The method is useful, inexpensive and straightforward and can be extended to other applications where measurement of liquid film thickness is required. © 2011 IOP Publishing Ltd.

Development of a tool for rapidly assessing the implementation difficulty and emissions benefits of innovations

Consumer goods manufacturers aiming to reduce the environmental impact associated with their products commonly pursue incremental change strategies, but more radical approaches may be required if we are to address the challenges of sustainable consumption. One strategy to realize step change reductions is to prepare a portfolio of innovations providing different levels of impact reduction in exchange for different levels of organizational resource commitment. In this research a tool is developed to support this strategy, starting with the assumption that through brainstorming or other eco-innovation approaches, a long-list of candidate innovations has been created. The tool assesses the potential greenhouse gas benefit of an innovative option against the difficulty of its implementation. A simple greenhouse gas benefit assessment method based on streamlined LCA was used to analyze impact reduction potential, and a novel measure of implementation difficulty was developed. The predictions of implementation difficulty were compared against expert opinion, and showed similar results indicating the measure can be used sensibly to predict implementation difficulty. The assessment of the environmental gain versus implementation difficulty is visualized in a matrix, showing the trade-offs of several options. The tool is deliberately simple with scalar measures of CO 2 emissions benefits and implementation difficulty so tool users must remain aware of other potential environmental burdens besides greenhouse gases (e.g. water, waste). In addition, although relative life cycle emissions benefits of an option may be low, the absolute impact of an option can be high and there may be other co-benefits, which could justify higher levels of implementation difficulty. Different types of consumer products (e.g. household, personal care, foods) have been evaluated using the tool. Initial trials of the tool within Unilever demonstrate that the tool facilitates rapid evaluation of low-carbon innovations. © 2011 Elsevier Ltd. All rights reserved.

Plasma enhancement of current from carbon cathodes for field emission displays

This paper examines the possibility of using a background gas medium to enhance the current available from low threshold carbon cathodes. The field emission current is used to initiate a plasma in the gas medium, and thereby achieve a current multiplication effect. Results on the variation of anode current as a function of electric field and gas pressure are presented. These are compared with model calculations to verify the principles of operation. The influence of ion bombardment on the long term performance thin film carbon cathodes is examined for He and Ar multiplication plasmas. A measure of the influence of current multiplication on display quality is presented by examining light output from two standard low voltage phosphors. Also studied are the influence of doping the carbon with N to lower the threshold voltage for emission as well as the consequent impact on anode current from the plasma.

Uncertainty management for on-line optimisation of a POMDP-based large-scale spoken dialogue system

The optimization of dialogue policies using reinforcement learning (RL) is now an accepted part of the state of the art in spoken dialogue systems (SDS). Yet, it is still the case that the commonly used training algorithms for SDS require a large number of dialogues and hence most systems still rely on artificial data generated by a user simulator. Optimization is therefore performed off-line before releasing the system to real users. Gaussian Processes (GP) for RL have recently been applied to dialogue systems. One advantage of GP is that they compute an explicit measure of uncertainty in the value function estimates computed during learning. In this paper, a class of novel learning strategies is described which use uncertainty to control exploration on-line. Comparisons between several exploration schemes show that significant improvements to learning speed can be obtained and that rapid and safe online optimisation is possible, even on a complex task. Copyright © 2011 ISCA.

X-ray observation of micro-failures in granular piles approaching an avalanche

An X-ray imaging technique is used to probe the stability of 3-dimensional granular packs in a slowly rotating drum. Well before the surface reaches the avalanche angle, we observe intermittent plastic events associated with collective rearrangements of the grains located in the vicinity of the free surface. The energy released by these discrete events grows as the system approaches the avalanche threshold. By testing various preparation methods, we show that the pre-avalanche dynamics is not solely controlled by the difference between the free surface inclination and the avalanche angle. As a consequence, the measure of the pre-avalanche dynamics is unlikely to serve as a tool for predicting macroscopic avalanches.

The most persistent soft-clique in a set of sampled graphs

When searching for characteristic subpatterns in potentially noisy graph data, it appears self-evident that having multiple observations would be better than having just one. However, it turns out that the inconsistencies introduced when different graph instances have different edge sets pose a serious challenge. In this work we address this challenge for the problem of finding maximum weighted cliques. We introduce the concept of most persistent soft-clique. This is subset of vertices, that 1) is almost fully or at least densely connected, 2) occurs in all or almost all graph instances, and 3) has the maximum weight. We present a measure of clique-ness, that essentially counts the number of edge missing to make a subset of vertices into a clique. With this measure, we show that the problem of finding the most persistent soft-clique problem can be cast either as: a) a max-min two person game optimization problem, or b) a min-min soft margin optimization problem. Both formulations lead to the same solution when using a partial Lagrangian method to solve the optimization problems. By experiments on synthetic data and on real social network data we show that the proposed method is able to reliably find soft cliques in graph data, even if that is distorted by random noise or unreliable observations. Copyright 2012 by the author(s)/owner(s).