Identifying sources of global contention in constraint satisfaction search

Much work has been done on learning from failure in search to boost solving of combinatorial problems, such as clause-learning and clause-weighting in boolean satisfiability (SAT), nogood and explanation-based learning, and constraint weighting in constraint satisfaction problems (CSPs). Many of the top solvers in SAT use clause learning to good effect. A similar approach (nogood learning) has not had as large an impact in CSPs. Constraint weighting is a less fine-grained approach where the information learnt gives an approximation as to which variables may be the sources of greatest contention. In this work we present two methods for learning from search using restarts, in order to identify these critical variables prior to solving. Both methods are based on the conflict-directed heuristic (weighted-degree heuristic) introduced by Boussemart et al. and are aimed at producing a better-informed version of the heuristic by gathering information through restarting and probing of the search space prior to solving, while minimizing the overhead of these restarts. We further examine the impact of different sampling strategies and different measurements of contention, and assess different restarting strategies for the heuristic. Finally, two applications for constraint weighting are considered in detail: dynamic constraint satisfaction problems and unary resource scheduling problems.

Comparison between local anaesthetic agents, lidocaine and bupivacaine, in patients undergoing third molar extraction in terms of patient satisfaction.

AIMS: (1) To determine if anaesthetic agent bupivacaine, has a prolonged effect on the period of acute postoperative pain when compared to lidocaine, a shorter acting agent. (2) To determine patient’s post-operative satisfaction and preference with regard to anaesthetic choice. METHODS: This double blind, randomised, interventional clinical trial included 85 patients. All patients had bilateral impacted lower third molars of removed under general anaesthetic. All patients received 0.5% plain bupivacaine on one randomly allocated side, with 2% lidocaine (with adrenaline) administered on the opposite side. Pain was measured using visual analogue scales at 0, 30, 60 minutes and 3, 4, 6 and 8 hours post-surgery. Pain was analysed for 1 week following surgery. Psychological evaluations and patient reported outcomes, including patient satisfaction were evaluated. RESULTS: A significant difference in pain (P=0.001) was seen during the 3-8 hour post-operative period. The upper limit of the 95% confidence interval was 10.0 or above at 3hours and 4 hours post-surgery. Two-thirds of patients preferred bupivacaine. CONCLUSION: Longer lasting anaesthetics such as bupivacaine offer a longer period of analgesia, and improve overall patient satisfaction.