Profiling hospitals based on emergency readmission: a multilevel transition modelling approach

Emergency readmission is seen as an important part of the United Kingdom government policy to improve the quality of care that patients receive. In this context, patients and the public have the right to know how well different health organizations are performing. Most methods for profiling estimate the expected numbers of adverse outcomes (e.g. readmission, mortality) for each organization. A number of statistical concerns have been raised, such as the differences in hospital sizes and the unavailability of relevant data for risk adjustment. Having recognized these statistical concerns, a new framework known as the multilevel transition model is developed. Hospital specific propensities of the first, second and further readmissions are considered to be measures of performance, where these measures are used to define a new performance index. During the period 1997 and 2004, the national (English) hospital episodes statistics dataset comprise more than 5 million patient readmissions. Implementing a multilevel model using the complete population dataset could possibly take weeks to estimate the parameters. To resolve the problem, we extract 1000 random samples from the original data, where each random sample is likely to lead to differing hospital performance measures. For computational efficiency a Grid implementation of the model is developed. Analysing the output from the full 1000 sample, we noticed that 4 out of the 5 worst performing hospitals treating cancer patients were in London. These hospitals are known to be the leading NHS Trusts in England, providing diverse range of services to complex patients, and therefore it is inevitable to expect higher numbers of emergency readmissions.     

A numerical hydrodynamic and thermal characterization of an inter-strata liquid cooling solution for 3D ICs

A novel integrated thermal management solution is proposed to alleviate hot spots in a contemporary 3D IC architecture. The solution employs a series of integrated microchannels, interconnected through each stratum by through silicon fluidic vias (TSFVs), and permits the transfer of heat, via a coolant, from hot to cold zones. This microfluidic system is driven by an integrated AC electrokinetic pump embedded in the channel walls. Recent advancements in electrokinetic micropump technology have allowed greater increases in fluid velocity (mm/s) while operating within the voltage constraints of a 3D IC. This paper presents a 2D simulation of an electrokinetic micropump operating at V_pp = 1.5 V in a 40 μm channel and examines its velocity profile for six frequencies in the range 100 ≤ ω ≤ 100 MHz. An optimum frequency of 100 kHz was established within this range and this was further examined with a constant heat flux of 186 W/cm2 imposed on the wall for an inlet fluid temperature of 40°C. Temperature profiles are presented at the channel-silicon interface and compared with theory.     

How to take into account general and contextual knowledge for interactive aiding design: Towards the coupling of CSP and CBR approaches

The goal of this paper is to show how it is possible to support design decisions with two different tools relying on two kinds of knowledge: case-based reasoning operating with contextual knowledge embodied in past cases and constraint filtering that operates with general knowledge formalized using constraints. Our goals are, firstly to make an overview of existing works that analyses the various ways to associate these two kinds of aiding tools essentially in a sequential way. Secondly, we propose an approach that allows us to use them simultaneously in order to assist design decisions with these two kinds of knowledge. The paper is organized as follows. In the first section, we define the goal of the paper and recall the background of case-based reasoning and constraint filtering. In the second section, the industrial problem which led us to consider these two kinds of knowledge is presented. In the third section, an overview of the various possibilities of using these two aiding decision tools in a sequential way is drawn up. In the fourth section, we propose an approach that allows us to use both aiding decision tools in a simultaneous and iterative way according to the availability of knowledge. An example dealing with helicopter maintenance illustrates our proposals.     

A finite macro-element for corroded reinforced concrete

This paper proposes a model of the mechanical behaviour of corroded reinforced concrete members subjected to bending under service load. The model is based on the formulation of a macro-element to be used in FEM analysis, having a length equal to the distance between two consecutive flexural cracks and a cross-section equal to the member cross-section. The mechanical formulation is directly written in generalized variables (bending moment and curvature) and is based on the concept of the transfer length necessary for the transmission of tensile load from re-bar to tensile concrete thanks to the bond. It is thus possible to take into account the effect of reinforcement corrosion on the bond between re-bar and concrete, by increasing the transfer length versus intensity of corrosion. The variation of the transfer length versus corrosion is expressed using a scalar damage parameter. A first experimental validation is performed on a 17-year-old beam kept in a chloride environment under its service load.     

American = White?

Six studies investigated the extent to which American ethnic groups (African, Asian, and White) are associated with the category "American." Although strong explicit commitments to egalitarian principles were expressed in Study 1, Studies 2-6 consistently revealed that both African and Asian Americans as groups are less associated with the national category "American" than are White Americans. Under some circumstances, a dissociation between mean levels of explicit beliefs and implicit responses emerged such that an ethnic minority was explicitly regarded to be more American than were White Americans, but implicit measures showed the reverse pattern (Studies 3 and 4). In addition, Asian American participants themselves showed the American = White effect, although African Americans did not (Study 5). The American = White association was positively correlated with the strength of national identity in White Americans. Together, these studies provide evidence that to be American is implicitly synonymous with being White. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Sequential Compatibility Effects and Cognitive Control: Does Conflict Really Matter?

Although it is widely accepted that control mechanisms are necessary for human behavior to be adapted, very little is known about how such mechanisms are recruited. A suggestion to fill the gap was put forward by M. M. Botvinick, T. S. Braver, C. S. Carter, D. M. Barch, and J. D. Cohen (2001), who proposed the conflict-loop theory. This theory has been successful in accounting for the reduction of compatibility effects after an incompatible trial: The level of conflict being, on average, higher during an incompatible trial, more control occurs after such a trial. The authors have tested this prediction by sorting the trials on the basis of amount of conflict (quantified by the electromyographic activity) they presented. A reduction of the compatibility effect was observed after incompatible trials, but it was independent of the level of conflict on previous trials, suggesting that the conflict does not trigger changes in executive control. Consequences for the conflict monitoring model are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Unsupervised writer adaptation applied to handwritten text recognition

This paper deals with the problem of off-line handwritten text recognition. It presents a system of text recognition that exploits an original principle of adaptation to the handwriting to be recognized. The adaptation principle is based on the automatic learning, during the recognition, of the graphical characteristics of the handwriting. This on-line adaptation of the recognition system relies on the iteration of two steps: a word recognition step that allows to label the writer's representations (allographs) on the whole text and a re-evaluation step of character models. Tests carried out on a sample of 15 writers, all unknown by the system, show the interest of the proposed adaptation scheme since we obtain during iterations an improvement of recognition rates both at the letter and the word levels.     

MIM零件烧结过程中收缩和变形的数值模拟

为描述金属粉末注射成形坯件在烧结过程中的收缩和变形行为,基于连续介质力学原理建立了符合粘塑性本构关系的宏观烧结模型。该模型通过有限元软件Abaqus的用户子程序实现,进行烧结过程的数值模拟。分析了由于坯件重力、非均匀初始密度分布以及坯件支承体之间的摩擦力等因素而引起的非均匀收缩和变形。通过与试验结果的比较,验证了烧结模型和数值方法的正确性。     

Nanometric Scale Investigation of Phase Transformations in Advanced Steels for Automotive Application

The current trend toward producing lighter vehicles in the automotive industry is driven by the need to conform to the new exhaust emission control regulations. This objective presents a challenge to steel manufacturers. The difficulty lies in designing new alloys with an optimum strength/formability/cost balance for the various components. Here, the key to success lies in controlling the steel microstructure and especially the phase transformations at the smallest possible scale. Among the different alloying elements, light elements such as carbon and boron are of prime importance due to their major effects on the kinetics of phase transformations. Characterization tools combining high spatial and analytical resolution such as secondary ion mass spectrometry (SIMS) and field emission gun-transmission electron microscopy (TEM) were used. In this article, the examples presented are as follows. (1) Boron segregation and precipitation effects to control hardenability in martensitic steels. (2) Local carbon distribution in advanced high-strength steels, with a specific emphasis on martensite tempering. Links have been established between the boron and carbon distribution and the formability.     

Modelling and predicting partial orders from pairwise belief functions

In this paper, we introduce a generic way to represent and manipulate pairwise information about partial orders (representing rankings, preferences, ...) with belief functions. We provide generic and practical tools to make inferences from this pairwise information and illustrate their use on the machine learning problems that are label ranking and multi-label prediction. Our approach differs from most other quantitative approaches handling complete or partial orders, in the sense that partial orders are here considered as primary objects and not as incomplete specifications of ideal but unknown complete orders.