Confidence-based Reasoning in Stochastic Constraint Programming

In this work we introduce a novel approach, based on sampling, for finding assignments that are likely to be solutions to stochastic constraint satisfaction problems and constraint optimisation problems. Our approach reduces the size of the original problem being analysed; by solving this reduced problem, with a given confidence probability, we obtain assignments that satisfy the chance constraints in the original model within prescribed error tolerance thresholds. To achieve this, we blend concepts from stochastic constraint programming and statistics. We discuss both exact and approximate variants of our method. The framework we introduce can be immediately employed in concert with existing approaches for solving stochastic constraint programs. A thorough computational study on a number of stochastic combinatorial optimisation problems demonstrates the effectiveness of our approach.Comment: 53 pages, working draf

Paroxysmal Nocturnal Hemoglobinuria in Myelofibrosis

Abstract Ten consecutive patients with myelofibrosis were examined for the following signs of PNH: Ham’s test, the sucrose hemolysis test, low red cell acetylcholinesterase (ACHE) activity and intravascular hemolysis. Two of the patients displayed all these signs and also had clinical symptoms of PNH. Two patients had positive sucrose hemolysis tests, low red cell ACHE and intravascular hemolysis. One patient had a positive sucrose hemolysis test and low red cell ACHE. The remaining patients had no signs of PNH. In two of the patients, the PNH signs disappeared after splenectomy. The concurrence of myelofibrosis and PNH supports the hypothesis that PNH is a disease of the common hemopoietic stem cell.</jats:p