An integrative top-down and bottom-up qualitative model construction framework for exploration of biochemical systems

The authors would like to thank the support on this research by the CRISP project (Combinatorial Responses In Stress Pathways) funded by the BBSRC (BB/F00513X/1) under the Systems Approaches to Biological Research (SABR) Initiative.Peer reviewedPublisher PD

Multifluid eulerian modelling of a silicon fluidized bed chemical vapor deposition process : analysis of various kinetic models

Using the multifluid Eulerian code MFIX, the silicon Fluidized Bed Chemical Vapor Deposition process from silane (SiH4) has been modelled under transient conditions. In order to constitute an experimental database, a preliminary experimental study has been performed using a bed of Geldart’s group B particles. After a detailed analysis and comparison of the kinetic models available in the literature, four of them have been implemented in the MFIX code and two hydrodynamic models have been tested. 3-D simulations have shown that a strong interaction exists between the bed hydrodynamics, heat and reactive mass transfers and that Si deposition from silane mainly occurs in the dense zones of the bed whereas the unsaturated species silylene (SiH2) forms in bubbles and slugs and leads to Si deposition mainly at their periphery; its contribution to deposition can be locally as high as that of SiH4. The average contribution of SiH2 to deposition increases with the inlet concentration of silane and can reach 30%. The kinetic models derived from the law of Furusawa et al. and from the data compiled by Buss et al. and the hydrodynamic model based on the true granular energy equation and the Princeton solid phase stress model have revealed to be the most appropriate ones for the conditions tested

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Computational and Mathematical Modelling of the EGF Receptor System

This chapter gives an overview of computational and mathematical modelling of the EGF receptor system. It begins with a survey of motivations for producing such models, then describes the main approaches that are taken to carrying out such modelling, viz. differential equations and individual-based modelling. Finally, a number of projects that applying modelling and simulation techniques to various aspects of the EGF receptor system are described