An Energetic Variational Approach for ion transport

The transport and distribution of charged particles are crucial in the study of many physical and biological problems. In this paper, we employ an Energy Variational Approach to derive the coupled Poisson-Nernst-Planck-Navier-Stokes system. All physics is included in the choices of corresponding energy law and kinematic transport of particles. The variational derivations give the coupled force balance equations in a unique and deterministic fashion. We also discuss the situations with different types of boundary conditions. Finally, we show that the Onsager's relation holds for the electrokinetics, near the initial time of a step function applied field

Occupational Health and Safety(OHS) in Small and Medium Size Enterprises (SMEs): A Primary Review1 SANTE ET SECURITE

Problems of occupational health and safety(OHS) in small and medium size enterprises(SMEs) in that mainly are private enterprises, are severe in China where as, the corresponding theoretical study are lagged behind regretfully. This paper summarizes the representative progress in this discipline simply. The exploratory results will be used to make an initial evaluation of SMEs needs, and will help orient future research. Key words: Occupational health and safety, Small and Medium Size Enterprises, review Résumé: Les problèmes de Santé et sécurité professionnelles(OHS) dans les petites et moyennes entreprises(PME) sont principalement ceux dans les entreprises privées et sont graves partout en Chine. La recherche théorique correspondante est largement et malheureusement arriérée. Cette thèse fait un résumé sur le progrès représentatif dans cette seule discipline. Les résultats exploratoires seront utilisés pour faire une évaluation initiale des demandes des PMEs et nous aideront l’orientation des recherches futures. Mots-clés: Santé et sécurité professionnelles, les petites et moyennes entreprises, revu

Hybrid Artificial Bee Colony Algorithm and Particle Swarm Search for Global Optimization

Artificial bee colony (ABC) algorithm is one of the most recent swarm intelligence based algorithms, which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To overcome this problem, we propose a novel artificial bee colony algorithm based on particle swarm search mechanism. In this algorithm, for improving the convergence speed, the initial population is generated by using good point set theory rather than random selection firstly. Secondly, in order to enhance the exploitation ability, the employed bee, onlookers, and scouts utilize the mechanism of PSO to search new candidate solutions. Finally, for further improving the searching ability, the chaotic search operator is adopted in the best solution of the current iteration. Our algorithm is tested on some well-known benchmark functions and compared with other algorithms. Results show that our algorithm has good performance