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Background:Gmelina arborea Roxb (Verbenaceae), also known as “Gambhari”, is an important medicinal plant in the Ayurveda. There are no meticulous scientific reports on effect of the plant on inflammation and pain.Objective:To study the anti-inflammatory and anti-nociceptive properties of aqueous extracts (AE) and methanol extracts (ME) of G. arborea.Materials and Methods:The AE and ME of stembark of G. arborea was prepared by cold maceration and Soxhlet extraction technique respectively. Anti-inflammatory activity was determined in Wistar albino rats in a model of acute plantar inflammation induced by carrageenan. The anti-nociceptive activity was evaluated by using hot plate test and writhing test in Swiss albino mice. Significant differences between the experimental groups were assessed by analysis of variance.Results:AE and ME at dose of 500 mg/kg showed maximum inhibition in carrageenan induced inflammation up to 30.15 and 31.21% respectively. In hot plate test, the AE and ME showed the maximum response of 8.8 ± 0.97 (P < 0.01) and 8.2 ± 1.24 (P < 0.01) respectively at dose of 500 mg/kg when compared with control. AE showed maximum inhibition of writhing response (84.3%) as compared to ME (77.9%) in writhing test at a dose of 500 mg/kg.Conclusion:The findings suggested that G. arborea possess significant anti-inflammatory and anti-nociceptive activities.

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This paper presents a scheduling approach, based on Genetic Algorithms(GA), developed to address the scheduling problem in manufacturing systems constrained by both machines and workers. The GA algorithm utilizes a new chromosome representatioiz, which takes into account machine and worker assignments to jobs. A study was conducted, using the proposed scheduling method, to compare the performance of six dispatching rules with respect to eight performance measures for two different shop characteristics: i ) dual-resources (machines and workers) constrained shop, and ii) single-resource constrained shop (machines only). An example is used for illustration. The results indicate that the dispatching rule which works best for a single-resource constrained shop is not necessarily the best rule for a dual-resources constrained system. Furthermore, it is shown that the most suitable dispatching rule depends' on the selected performance criteria and the characteristics of the manufacturing system. Notations 1. INTRODUCTION 1 k I t Ji Di Mi wk Ti Oij ' ij Sij Cij tijk =The ith job (i = I , 2, .., n) = The kth machine (k = I , 2, .., m) = The Ith worker l(1 = I , 2, .., p) = Time = Number of operations of Job i = Batch size of part i (i = I , 2, .., n) = Machine index = Worker index = Processing time of each part (sum of processing times of each operation) = Operation number j ofjob i = Ready time of operation j ofjob i = Starting time of operation 0, = Completion time of operation 0, = Processing time of operation 0, on = Efficiency of worker I on machine k = Due date ofjob i ( i = 1,2, .., n) = Utilization of machine k ( k = 1,2, .., m) = Utilization of worker 1 ( I = I ,2, .., p) = Release time of machine k = Release time of worker 1 machine k

Grid computing is emerging as the next generation computing environment. Various meta-computing and distributed computing environments are becoming grid compliant with the aim of achieving interoperability. We have developed a web-based development environment for distributed computing that supports heterogeneous resources and provides ease of use. We present herewith GANESH that achieves grid compliance using Globus and also extends features for added value. This paper describes GANESH architecture and its services, and explains its grid compliance and extended features. We also explain in this paper how and where it is interoperable with other environments.