Fluent temporal logic for discrete-time event-based models

Fluent model checking is an automated technique for verifying that an event-based operational model satisfies some state-based declarative properties. The link between the event-based and state-based formalisms is defined through fluents which are state predicates whose value are determined by the occurrences of initiating and terminating events that make the fluents values become true or false, respectively. The existing fluent temporal logic is convenient for reasoning about untimed event-based models but difficult to use for timed models. The paper extends fluent temporal logic with temporal operators for modelling timed properties of discrete-time event-based models. It presents two approaches that differ on whether the properties model the system state after the occurrence of each event or at a fixed time rate. Model checking of timed properties is made possible by translating them into the existing untimed framework. Copyright 2005 ACM

Public Health for the Internet φ Towards A New Grand Challenge for Information Management

Business incentives have brought us within a small factor of achieving the database community\u27s Grand Challenge set out in the Asilomar Report of 1998. This paper makes the case for a new, focused Grand Challenge: Public Health for the Internet. The goal of PHI (or φ) is to enable collectives of hosts on the Internet to jointly monitor and promote network health by sharing information on network conditions in a peer-to-peer fashion. We argue that this will be a positive effort for the research community for a variety of reasons, both in terms of its technical reach and its societal impact. This version of the φ vision is targeted at readers in the database research community, but the effort is clearly multidisciplinary. A more generalist version of this paper will be maintained at http://openphi.net

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Bostonia: The Boston University Alumni Magazine. Volume 6

Founded in 1900, Bostonia magazine is Boston University's main alumni publication, which covers alumni and student life, as well as university activities, events, and programs

Cancer-Related Fatigue and Sleep Disorders

Abstract Sleep disorders, such as difficulty falling asleep, problems maintaining sleep, poor sleep efficiency, early awakening, and excessive daytime sleepiness, are prevalent in patients with cancer. Such problems can become chronic in some patients, persisting for many months or years after completion of cancer therapy. For patients with cancer, sleep is potentially affected by a variety of factors, including the biochemical changes associated with the process of neoplastic growth and anticancer treatments, and symptoms that frequently accompany cancer, such as pain, fatigue, and depression. Fatigue is highly prevalent and persistent in patients with cancer and cancer survivors. Although cancerrelated fatigue and cancer-related sleep disorders are distinct, a strong interrelationship exists between these symptoms, and a strong possibility exists that they may be reciprocally related. The majority of studies that have assessed both sleep and fatigue in patients with cancer provide evidence supporting a strong correlation between cancer-related fatigue and various sleep parameters, including poor sleep quality, disrupted initiation and maintenance of sleep, nighttime awakening, restless sleep, and excessive daytime sleepiness. This paper reviews the data from these studies with a view toward suggesting further research that could advance our scientific understanding both of potential interrelationships between sleep disturbance and cancer-related fatigue and of clinical interventions to help with both fatigue and sleep disturbance. The Oncologist 2007;12(suppl 1)