Landscape valuation through discrete choice experiments: Current practice and future research reflections

This work has been presented in: V Conference AERNA, Faro (Portugal), 30 May 2012-1 June 2012 and IV Workshop on Valuation Methods in Agro-food and Environmental Economics, Castelldefels (Barcelona, Spain), 12 July 2012-13 July 2012.

Online exercise for the design and simulation of PCR and PCR-RFLP experiments

[EN] Background: Polymerase Chain Reaction (PCR) and Restriction Fragment Length Polymorphism of PCR products (PCR-RFLP) are extensively used molecular biology techniques. An exercise for the design and simulation of PCR and PCR-RFLP experiments will be a useful educational tool. Findings: An online PCR and PCR-RFLP exercise has been create that requires users to find the target genes,compare them, design primers, search for restriction endonucleases, and finally to simulate the experiment. Each user of the service is randomly assigned a gene from Escherichia coli; to complete the exercise, users must design an experiment capable of distinguishing among E. coli strains. By applying the experimental procedure to all completely sequenced E. coli, a basic understanding of strain comparison and clustering can also be acquired. Comparison of results obtained in different experiments is also very instructive. Conclusions: The exercise is freely available at http://insilico.ehu.es/edu.

Some experiments on solving multistage stochastic mixed 0-1 programs with time stochastic dominance constraints

In this work we extend to the multistage case two recent risk averse measures for two-stage stochastic programs based on first- and second-order stochastic dominance constraints induced by mixed-integer linear recourse. Additionally, we consider Time Stochastic Dominance (TSD) along a given horizon. Given the dimensions of medium-sized problems augmented by the new variables and constraints required by those risk measures, it is unrealistic to solve the problem up to optimality by plain use of MIP solvers in a reasonable computing time, at least. Instead of it, decomposition algorithms of some type should be used. We present an extension of our Branch-and-Fix Coordination algorithm, so named BFC-TSD, where a special treatment is given to cross scenario group constraints that link variables from different scenario groups. A broad computational experience is presented by comparing the risk neutral approach and the tested risk averse strategies. The performance of the new version of the BFC algorithm versus the plain use of a state-of-the-artMIP solver is also reported.