Cyclometalated complexes derived from calix[4] arene bisphosphites and their catalytic applications in cross-coupling reactions

Palladium and platinum dichloride complexes of a series of symmetrically and unsymmetrically substituted 25,26;27,28-dibridged p-tert-butyl-calix[4]arene bisphosphites in which two proximal phenolic oxygen atoms of p-tert-butyl-or p-H-calix[4]arene are connected to a P(OR) ( R = substituted phenyl) moiety have been synthesized. The palladium dichloride complexes of calix[4]arene bisphosphites bearing sterically bulky aryl substituents undergo cyclometalation by C-C or C-H bond scission. An example of cycloplatinated complex is also reported. The complexes have been characterized by NMR spectroscopic and single crystal X-ray diffraction studies. During crystallization of the palladium dichloride complex of a symmetrically substituted calix[4]arene bisphosphite in dichloromethane, insertion of oxygen occurs into the Pd-P bond to give a P,O-coordinated palladium dichloride complex. The calix[4]arene framework in these bisphosphites and their metal complexes adopt distorted cone conformation; the cone conformation is more flattened in the metal complexes than in the free calix[4]arene bisphosphites. Some of these cyclometalated complexes proved to be active catalysts for Heck and Suzuki C-C cross-coupling reactions but, on an average, the yields are only modest. (C) 2011 Elsevier B.V. All rights reserved.

Strategies for Rescheduling Tightly-Coupled Parallel Applications in Multi-Cluster Grids

As computational Grids are increasingly used for executing long running multi-phase parallel applications, it is important to develop efficient rescheduling frameworks that adapt application execution in response to resource and application dynamics. In this paper, three strategies or algorithms have been developed for deciding when and where to reschedule parallel applications that execute on multi-cluster Grids. The algorithms derive rescheduling plans that consist of potential points in application execution for rescheduling and schedules of resources for application execution between two consecutive rescheduling points. Using large number of simulations, it is shown that the rescheduling plans developed by the algorithms can lead to large decrease in application execution times when compared to executions without rescheduling on dynamic Grid resources. The rescheduling plans generated by the algorithms are also shown to be competitive when compared to the near-optimal plans generated by brute-force methods. Of the algorithms, genetic algorithm yielded the most efficient rescheduling plans with 9-12% smaller average execution times than the other algorithms.

An Effective Seamless Connectivity Scheme for Ubiquitous Applications

The idea of ubiquity and seamless connectivity in networks is gaining more importance in recent times because of the emergence of mobile devices with added capabilities like multiple interfaces and more processing abilities. The success of ubiquitous applications depends on how effectively the user is provided with seamless connectivity. In a ubiquitous application, seamless connectivity encompasses the smooth migration of a user between networks and providing him/her with context based information automatically at all times. In this work, we propose a seamless connectivity scheme in the true sense of ubiquitous networks by providing smooth migration to a user along with providing information based on his/her contexts automatically without re-registration with the foreign network. The scheme uses Ubi-SubSystems(USS) and Soft-Switches(SS) for maintaining the ubiquitous application resources and the users. The scheme has been tested by considering the ubiquitous touring system with several sets of tourist spots and users.

Swam Intelligent Based Inverse Model for Laboratory Double Reservoir Diffusion Experiments

Theoretical approaches are of fundamental importance to predict the potential impact of waste disposal facilities on ground water contamination. Appropriate design parameters are, in general, estimated by fitting the theoretical models to a field monitoring or laboratory experimental data. Double-reservoir diffusion (Transient Through-Diffusion) experiments are generally conducted in the laboratory to estimate the mass transport parameters of the proposed barrier material. These design parameters are estimated by manual parameter adjusting techniques (also called eye-fitting) like Pollute. In this work an automated inverse model is developed to estimate the mass transport parameters from transient through-diffusion experimental data. The proposed inverse model uses particle swarm optimization (PSO) algorithm which is based on the social behaviour of animals for finding their food sources. Finite difference numerical solution of the transient through-diffusion mathematical model is integrated with the PSO algorithm to solve the inverse problem of parameter estimation.The working principle of the new solver is demonstrated by estimating mass transport parameters from the published transient through-diffusion experimental data. The estimated values are compared with the values obtained by existing procedure. The present technique is robust and efficient. The mass transport parameters are obtained with a very good precision in less time