This work investigates the problem of permuting a sparse rectangular matrix into block diagonal form. Block diagonal form of a matrix grants an inherent parallelism for the solution of the deriving problem, as recently investigated in the context of mathematical programming, LU factorization and QR factorization. We propose graph and hypergraph models to represent the nonzero structure of a matrix, which reduce the permutation problem to those of graph partitioning by vertex separator and hypergraph partitioning, respectively. Besides proposing the models to represent sparse matrices and investigating related combinatorial problems, we provide a detailed survey of relevant literature to bridge the gap between different societies, investigate existing techniques for partitioning and propose new ones, and finally present a thorough empirical study of these techniques. Our experiments on a wide range of matrices, using state-of-the-art graph and hypergraph partitioning tools MeTiS and PaToH, revealed that the proposed methods yield very effective solutions both in terms of solution quality and run time.

Summary

In exploring the epidemiology of infectious diseases, networks have been used to reconstruct contacts among individuals and/or populations. Summarizing networks using pathogen metadata (e.g. host species and place of isolation) and a phylogenetic tree is a nascent, alternative approach. In this paper, we introduce a tool for reconstructing transmission networks in arbitrary space from phylogenetic information and metadata. Our goals are to provide a means of deriving new insights and infection control strategies based on the dynamics of the pathogen lineages derived from networks and centrality metrics. We created a web-based application, called StrainHub, in which a user can input a phylogenetic tree based on genetic or other data along with characters derived from metadata using their preferred tree search method. StrainHub generates a transmission network based on character state changes in metadata, such as place or source of isolation, mapped on the phylogenetic tree. The user has the option to calculate centrality metrics on the nodes including betweenness, closeness, degree and a new metric, the source/hub ratio. The outputs include the network with values for metrics on its nodes and the tree with characters reconstructed. All of these results can be exported for further analysis.

Availability and implementation

strainhub.io and https://github.com/abschneider/StrainHub.

Congestive heart failure (CHF) is a cardiovascular disorder that affects approximately 4.6 million Americans and is a leading cause of death in the United States. Current research shows that strategies to promote early recognition and treatment of symptoms and enhance self-care management behaviors reduce unnecessary hospitalizations. However, mechanisms to monitor patients' health status and behaviors are limited by constraints imposed by the patient's geography, infirmity, or resources. Remote monitoring supports a more dynamic connection between healthcare providers and patients, improves health promotion and patient care through monitoring of health data, communicates health reminders, and makes provisions for patient feedback. This paper will describe two versions of Weight and Activity with Blood Pressure Monitoring System (WANDA [22]) that leverages sensor technology and wireless communication to monitor health status of patients with CHF. The WANDA system is built on a three-tier architecture consisting of sensors, a web server, and back-end database tiers. The system was developed in conjunction with the UCLA School of Nursing and the UCLA Wireless Health Institute to enable early detection of key clinical symptoms indicative of CHF-related decompensation in a real-time automated fashion and allows health professionals to offer surveillance, advice, and continuity of care and triggers early implementation of strategies to enhance adherence behaviors. The small study has enabled patients to reduce or maintain the number of readings which are out of the acceptable range. For diastolic, systolic, and heart rate values, the t-test results show that the WANDA study is effective for patients with CHF. © 2010 ACM.