A scalable and self-adapting notification framework for healthcare information systems

There has been a great interest in publish/subscribe systems in recent years. This interest, coupled with the pervasiveness of light-weight electronic devices, such as cellular phones and personal digital assistants, has opened a new arena in publish/subscribe networks. Currently, many broker overlay networks are static and rarely change in structure. Often, a network overlay structure is predefined or manually modified. This paper presents a dynamic broker network for disseminating critical lab and patient information in a Healthcare information system. The reported work builds upon previous network optimization research on ad hoc publish/subscribe networks. The underlying framework utilizes user-defined cost functions to satisfy quality of service constraints. In essence, the broker network optimization problem is reduced to an incremental search problem to generate low cost network configurations. Certain reliability issues are also addressed by providing a scheduling algorithm to selectively retransmit information and handle broker connectivity failures.     

Optimization of a proton exchange membrane fuel cell membrane electrode assembly

A computational framework for fuel cell analysis and optimization is presented as an innovative alternative to the time consuming trial-and-error process currently used for fuel cell design. The framework is based on a two-dimensional through-the-channel isothermal, isobaric and single phase membrane electrode assembly (MEA) model. The model input parameters are the manufacturing parameters used to build the MEA: platinum loading, platinum to carbon ratio, electrolyte content and gas diffusion layer porosity. The governing equations of the fuel cell model are solved using Netwon’s algorithm and an adaptive finite element method in order to achieve near quadratic convergence and a mesh independent solution respectively. The analysis module is used to solve the optimization problem of finding the optimal MEA composition for maximizing performance. To solve the optimization problem a gradient-based optimization algorithm is used in conjunction with analytical sensitivities. By using a gradient-based method and analytical sensitivities, the framework presented is capable of solving a complete MEA optimization problem with state-of-the-art electrode models in approximately 30 min, making it a viable alternative for solving large-scale fuel cell problems.     

How Internet software companies negotiate quality

In Internet speed development, innovation and time-to-market work against software quality. Browser giants like Microsoft Internet Explorer and Netscape Navigator are openly dealing with quality issues. The practices of application and smaller niche firms are less clear, but there are important trends     

Mental health services for homeless mentally ill persons: Federal initiatives and current service trends.

Recent research suggests that approximately one third of the population of homeless single adults suffer from severe mental illnesses. Despite multiple health, mental health, and social welfare needs, this population is often unable to obtain necessary housing and community-based services. For this reason, since 1982, the National Institute of Mental Health (NIMH) has undertaken a number of federal initiatives to encourage research and assist states and localities in improving services focused on this vulnerable subgroup of the homeless population. This article describes the target population, NIMH research findings, and current mental health programs—with particular emphasis on two mental health programs established under the Stewart B. McKinney Homeless Assistance Act. Proposed future directions for federal research and evaluation efforts in this area are also discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Differences between organic and schizophrenic groups on the Halstead-Reitan battery: A reply to Watson.

Questions C. G. Watson's (see PA, Vol 52:Issue 3) attempt to explain apparent inconsistencies in findings between his and the present authors' studies in terms of sample differences. Despite Watson's reanalysis of his data by matched pairs, he fails adequately to control for differences in chronicity. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Fluorescence recovery assay for the detection of protein-DNA binding

We report a novel and straightforward fluorescence recovery assay which enables the detection of protein-DNA interactions and simultaneously determines relative binding affinities of sequence-specific DNA-binding proteins for a variety of DNA sequences in a multiplexed format. The detection of protein-DNA binding is accomplished by monitoring fluorescence recovery during exonuclease digestion of DNA sequences that are modified with fluorophore-quencher pairs. Retardation of fluorescence recovery occurs with binding of the protein to the putative DNA binding element, which arrests exonuclease digestion. The assay detects protein-DNA binding in a homogeneous solution simply, quickly, and reliably without using radioisotopes. Multiplexing is possible by labeling different DNA sequences with spectrally distinct dyes, allowing simultaneous analysis of experimental and control binding reactions in the same mixture.     

Human activity recognition in videos using a single example

This paper presents a novel approach for action recognition, localization and video matching based on a hierarchical codebook model of local spatio-temporal video volumes. Given a single example of an activity as a query video, the proposed method finds similar videos to the query in a target video dataset. The method is based on the bag of video words (BOV) representation and does not require prior knowledge about actions, background subtraction, motion estimation or tracking. It is also robust to spatial and temporal scale changes, as well as some deformations. The hierarchical algorithm codes a video as a compact set of spatio-temporal volumes, while considering their spatio-temporal compositions in order to account for spatial and temporal contextual information. This hierarchy is achieved by first constructing a codebook of spatio-temporal video volumes. Then a large contextual volume containing many spatio-temporal volumes (ensemble of volumes) is considered. These ensembles are used to construct a probabilistic model of video volumes and their spatio-temporal compositions. The algorithm was applied to three available video datasets for action recognition with different complexities (KTH, Weizmann, and MSR II) and the results were superior to other approaches, especially in the case of a single training example and cross-dataset¹ action recognition.     

RECIST Applied to Realistic Tumor Models

RECIST (Response Evaluation Criteria in Solid Tumors) is a linear measure intended to predict tumor size in medical computed tomography (CT). In this work, using purely geometrical considerations, we estimate how well RECIST can predict the volume of randomly-oriented tumor models, each composed of the union of ellipsoids. The principal conclusion is that RECIST is likely to work less well for realistic tumors than for ellipsoids.     

Elaboration of energy saving renovation measures for urban existing residential buildings in north China based on simulation and site investigations

It is necessary to determine whether to implement a retrofit measure or not based on its energy saving and economic benefits, when conducting a retrofit project. The common way to do that is to set up a building simulation model and calculate its energy saving and economic benefits. Because of the great discrepancy between the actuality and the building simulation model, it is very important to use the factual energy use to calibrate the model, so as to accurately predict the benefits of retrofit measures. Although the energy efficiency retrofit of residential buildings in north China is implemented in a large scale, it seldom knows whether the commonly used retrofit packages are optimized. Therefore, a typical residential building is selected in Beijing, and the energy saving and economic benefits of different retrofit measures are analyzed using a simulation model calibrated with its actual space heating energy use, and the optimized retrofit packages are put forward. Results shows the retrofit of space heating system is a very attractive measure due to its relatively low investment but good energy saving benefit, and roof retrofit is also cost effective, while window retrofit and wall retrofit are not economic to conduct separately. Four optimized retrofit packages are figured out to realize the 50% and 65% reductions of space heating intensity required in the energy efficiency standards, which have less investment costs compared with currently widely used packages, and the retrofit packages for the 65% reduction is more cost-effective than the packages for the 50% reduction.