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In goal-oriented requirements engineering, goal conflict identification is of fundamental importance for requirements analysis. The task aims to find the feasible situations which make the goals diverge within the domain, called boundary conditions (BCs). However, the existing approaches for goal conflict identification fail to find sufficient BCs and general BCs which cover more combinations of circumstances. From the BCs found by these existing approaches, we have observed an interesting phenomenon that there are some pairs of BCs are similar in formula structure, which occurs frequently in the experimental cases. In other words, once a BC is found, a new BC may be discovered quickly by slightly changing the former. It inspires us to develop a local search algorithm named LOGION to find BCs, in which the structural similarity is captured by the neighborhood relation of formulae. Based on structural similarity, LOGION can find a lot of BCs in a short time. Moreover, due to the large number of BCs identified, it potentially selects more general BCs from them. By taking experiments on a set of cases, we show that LOG I ON effectively exploits the structural similarity of BCs. We also compare our algorithm against the two state-of-the-art approaches. The experimental results show that LOGION produces one order of magnitude more BCs than the state-of-the-art approaches and confirm that LOGION finds out more general BCs thanks to a large number of BCs.

Introduction Marathon, as a long-distance aerobic exercise, has become a fashionable or popular sport. However, little is known about the holistic metabolic changes occurring within the serum metabolome of athletes after the completion of a marathon. Objectives The goal of current study was to have an in-depth understanding of the impact of marathon on human metabolomics as well as the relationships among a variety of metabolites. Methods The 20 studied subjects were all adult males who participated in a marathon. The serum samples of these participants were collected before and after the marathon and the biochemical metabolites in the serum were identified by an untargeted two-dimensional gas chromatography time-of-flight mass spectrometry. Results All participants completed the marathon within 3 h. Compared to those before exercise, serum urea and creatine kinase, as well as cortisol, elevated significantly (p p p p p p p p 2max, and hemoglobin were correlated with the serum metabonomic indicators, so were serum testosterone and cortisol. Conclusion These results illustrate that the metabolism of glucose and lipid of the athletes was enhanced following the marathon match. In addition, the metabolism of glucosamine was decreased and the metabolism of caffeine was increased. Our data provide new insights for marathon performance and nutritional status.

In recent years, multi-agent epistemic planning has received attention from both dynamic logic and planning communities. Existing implementations of multi-agent epistemic planning are based on compilation into classical planning and suffer from various limitations, such as generating only linear plans, restriction to public actions, and incapability to handle disjunctive beliefs. In this paper, we propose a general representation language for multi-agent epistemic planning where the initial KB and the goal, the preconditions and effects of actions can be arbitrary multi-agent epistemic formulas, and the solution is an action tree branching on sensing results. To support efficient reasoning in the multi-agent KD45 logic, we make use of a normal form called alternating cover disjunctive formulas (ACDFs). We propose basic revision and update algorithms for ACDFs. We also handle static propositional common knowledge, which we call constraints. Based on our reasoning, revision and update algorithms, adapting the PrAO algorithm for contingent planning from the literature, we implemented a multi-agent epistemic planner called MEPK. Our experimental results show the viability of our approach., Comment: One of the authors think it's not appropriate to show this work there days. Then we discussed, we want submit a new work and this one together later