On the choice of parameters in solar structure inversion

The observed solar p-mode frequencies provide a powerful diagnostic of the internal structure of the Sun and permit us to test in considerable detail the physics used in the theory of stellar structure. Amongst the most commonly used techniques for inverting such helioseismic data are two implementations of the optimally localized averages (OLA) method, namely the Subtractive Optimally Localized Averages (SOLA) and Multiplicative Optimally Localized Averages (MOLA). Both are controlled by a number of parameters, the proper choice of which is very important for a reliable inference of the solar internal structure. Here we make a detailed analysis of the influence of each parameter on the solution and indicate how to arrive at an optimal set of parameters for a given data set.Comment: 14 pages, 15 figures. Accepted for publication on MNRA

Uganda aquaculture value chains: strategic planning mission: summary report

This report presents the findings and recommendations of a strategic planning mission to reevaluate the feasibility of WorldFish implementing a fish value chain research program in Uganda under the CGIAR Research Program on Livestock and Fish (L&F). The over-arching goal of L&F is to increase productivity of small-scale livestock and fish systems so as to increase availability and affordability of meat, milk and fish for poor consumers and, in doing so, to reduce poverty through greater participation by the poor along animal source food value chains. This will be achieved by making a small number of carefully selected animal source food value chains function better, for example by identifying and addressing key constraints and opportunities (from production to consumption), improving institutional arrangements and capacities, and supporting the establishment of enabling pro-poor policy and institutional environments

Uganda aquaculture value chains: strategic planning mission report

This report presents the findings and recommendations of a strategic planning mission to reevaluate the feasibility of WorldFish implementing a fish value chain research program in Uganda under the CGIAR Research Program on Livestock and Fish (L&F). The over-arching goal of L&F is to increase productivity of small-scale livestock and fish systems so as to increase availability and affordability of meat, milk and fish for poor consumers and, in doing so, to reduce poverty through greater participation by the poor along animal source food value chains. This will be achieved by making a small number of carefully selected animal source food value chains function better, for example by identifying and addressing key constraints and opportunities (from production to consumption), improving institutional arrangements and capacities, and supporting the establishment of enabling pro-poor policy and institutional environments

ADIPLS -- the Aarhus adiabatic oscillation package

Development of the Aarhus adiabatic pulsation code started around 1978. Although the main features have been stable for more than a decade, development of the code is continuing, concerning numerical properties and output. The code has been provided as a generally available package and has seen substantial use at a number of installations. Further development of the package, including bringing the documentation closer to being up to date, is planned as part of the HELAS Coordination Action.Comment: Astrophys. Space Sci., in the pres

TarTar: A Timed Automata Repair Tool

We present TarTar, an automatic repair analysis tool that, given a timed diagnostic trace (TDT) obtained during the model checking of a timed automaton model, suggests possible syntactic repairs of the analyzed model. The suggested repairs include modified values for clock bounds in location invariants and transition guards, adding or removing clock resets, etc. The proposed repairs are guaranteed to eliminate executability of the given TDT, while preserving the overall functional behavior of the system. We give insights into the design and architecture of TarTar, and show that it can successfully repair 69% of the seeded errors in system models taken from a diverse suite of case studies.Comment: 15 pages, 7 figure