BACKGROUND With limited numbers of intensive care unit (ICU) beds available, increasing patient acuity is expected to contribute to episodes of inpatient deterioration on general wards. OBJECTIVE To prospectively validate a predictive algorithm for clinical deterioration in general–medical ward patients, and to conduct a trial of real‐time alerts based on this algorithm. DESIGN Randomized, controlled crossover study. SETTING/PATIENTS Academic center with patients hospitalized on 8 general wards between July 2007 and December 2011. INTERVENTIONS Real‐time alerts were generated by an algorithm designed to predict the need for ICU transfer using electronically available data. The alerts were sent by text page to the nurse manager on intervention wards. MEASUREMENTS Intensive care unit transfer, hospital mortality, and hospital length of stay. RESULTS Patients meeting the alert threshold were at nearly 5.3‐fold greater risk of ICU transfer (95% confidence interval [CI]: 4.6‐6.0) than those not satisfying the alert threshold (358 of 2353 [15.2%] vs 512 of 17678 [2.9%]). Patients with alerts were at 8.9‐fold greater risk of death (95% CI: 7.4‐10.7) than those without alerts (244 of 2353 [10.4%] vs 206 of 17678 [1.2%]). Among patients identified by the early warning system, there were no differences in the proportion of patients who were transferred to the ICU or who died in the intervention group as compared with the control group. CONCLUSIONS Real‐time alerts were highly specific for clinical deterioration resulting in ICU transfer and death, and were associated with longer hospital length of stay. However, an intervention notifying a nurse of the risk did not result in improvement in these outcomes. Journal of Hospital Medicine 2013;8:236–242. © 2013 Society of Hospital Medicine

Topology control can reduce power consumption and channel contention in wireless sensor networks by adjusting the transmission power. However, topology control for wireless sensor networks faces significant challenges, especially in indoor environments where wireless characteristics are extremely complex and dynamic. We first provide insights on the design of robust topology control schemes based on an empirical study in an office building. For example, our analysis shows that Received Signal Strength Indicator and Link Quality Indicator are not always robust indicators of Packet Reception Rate in indoor environments due to significant multi-path effects. We then present Adaptive and Robust Topology control (ART), a novel and practical topology control algorithm with several salient features: (1) ART is robust in indoor environments as it does not rely on simplifying assumptions about the wireless properties; (2) ART can adapt to variations in both link quality and contention;(3) ART introduces zero communication overhead for applications which already use acknowledgements. We have implemented ART as a topology layer in TinyOS 2.x. Our topology layer only adds 12 bytes of RAM per neighbor and 1.5 kilobytes of ROM, and requires minimal changes to upper-layer routing protocols. The advantages of ART have been demonstrated through empirical results on a 28-node indoor testbed.

Our deteriorating civil infrastructure faces the critical challenge of long-term structural health monitoring for damage detection and localization. In contrast to existing research that often separates the designs of wireless sensor networks and structural engineering algorithms, this paper proposes a cyber-physical co-design approach to structural health monitoring based on wireless sensor networks. Our approach closely integrates (1) flexibility-based damage localization methods that allow a tradeoff between the number of sensors and the resolution of damage localization, and (2) an energy-efficient, multi-level computing architecture specifically designed to leverage the multi-resolution feature of the flexibility-based approach. The proposed approach has been implemented on the Intel Imote2 platform. Experiments on a physical beam and simulations of a truss structure demonstrate the system's efficacy in damage localization and energy efficiency.

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Abstract. The Business Process Execution Language (BPEL) has become the dominant means for expressing traditional business processes as workflows. The widespread deployment of mobile devices like PDAs and mobile phones has created a vast computational and communication resource for these workflows to exploit. However, BPEL so far has been deployed only on relatively heavyweight server platforms such as Apache Tomcat, leaving the potential created by these lower-end devices untapped. This paper presents Sliver, a BPEL workflow process execution engine that supports a wide variety of devices ranging from mobile phones to desktop PCs. We discuss the design decisions that allow Sliver to operate within the limited resources of a mobile phone or PDA. We also evaluate the performance of a prototype implementation of Sliver.