Ion production rate in a boreal forest based on ion, particle and radiation measurements

International audienceIn this study the ion production rates in a boreal forest were studied based on two different methods: 1) cluster ion and particle concentration measurements, 2) external radiation and radon concentration measurements. Both methods produced reasonable estimates for ion production rates. The average ion production rate calculated from aerosol particle size distribution and air ion mobility distribution measurements was 2.6 ion pairs cm-3s-1, and based on external radiation and radon measurements, 4.5 ion pairs cm-3s-1. The first method based on ion and particle measurements gave lower values for the ion production rates especially during the day. A possible reason for this is that particle measurements started only from 3nm, so the sink of small ions during the nucleation events was underestimated. It may also be possible that the hygroscopic growth factors of aerosol particles were underestimated. Another reason for the discrepancy is the nucleation mechanism itself. If the ions are somehow present in the nucleation process, there could have been an additional ion sink during the nucleation days

Finding Finite Models in Multi-Sorted First-Order Logic

This work extends the existing MACE-style finite model finding approach to multi-sorted first order logic. This existing approach iteratively assumes increasing domain sizes and encodes the related ground problem as a SAT problem. When moving to the multi-sorted setting each sort may have a different domain size, leading to an explosion in the search space. This paper focusses on methods to tame that search space. The key approach adds additional information to the SAT encoding to suggest which domains should be grown. Evaluation of an implementation of techniques in the Vampire theorem prover shows that they dramatically reduce the search space and that this is an effective approach to find finite models in multi-sorted first order logic.Comment: SAT 201

SMEAR Estonia : Perspectives of a large-scale forest ecosystem – Atmosphere research infrastructure

Non peer reviewe

A Pragmatic, Scalable Approach to Correct-by-Construction Process Composition Using Classical Linear Logic Inference

The need for rigorous process composition is encountered in many situations pertaining to the development and analysis of complex systems. We discuss the use of Classical Linear Logic (CLL) for correct-by-construction resource-based process composition, with guaranteed deadlock freedom, systematic resource accounting, and concurrent execution. We introduce algorithms to automate the necessary inference steps for binary compositions of processes in parallel, conditionally, and in sequence. We combine decision procedures and heuristics to achieve intuitive and practically useful compositions in an applied setting.Comment: Post-proceedings paper presented at the 28th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2018), Frankfurt am Main, Germany, 4-6 September 2018 (arXiv:1808.03326). arXiv admin note: substantial text overlap with arXiv:1803.0261