Deriving state machines from tinyos programs using symbolic execution.

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Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reliable and efficient programming abstractions for wireless sensor networks

It is currently difficult to build practical and reliable programming systems out of distributed and resource-constrained sensor devices. The state of the art in today’s sensornet programming is centered around a component-based language called nesC. nesC is a nodelevel language—a program is written for an individual node in the network—and nesC programs use the services of an operating system called TinyOS. We are pursuing an approach to programming sensor networks that significantly raises the level of abstraction over this practice. The critical change is one of perspective: rather than writing programs from the point of view of an individual node, programmers implement a central program that conceptually has access to the entire network. This approach pushes to the compiler the task of producing node-level programs that implement the desired behavior. We present the Pleiades programming language, its compiler