Synthesis, spectral characterization and in vitro microbiological evaluation of novel glyoxal, biacetyl and benzil bis-hydrazone macrocyclic Schiff bases and their Co(II), Ni(II) and Cu(II) complexes

A series of binuclear Co(II), Ni(II) and Cu(II) complexes were synthesized by the template condensation of glyoxal, biacetyl or benzil bis-hydrazide, 2,6-diformyl-4-methylphenol and Co(11), Ni(II) or Cu(II) chloride in a 2:2:2 M ratio in ethanol. These 22-membered macrocyclic complexes were characterized by elemental analyses, magnetic, molar conductance, spectral, thermal and fluorescence studies. Elemental analyses suggest the complexes have a 2:1 stoichiometry of the type (M2LX2]center dot nH(2)O and Ni(2)LX(2)2H(2)O]center dot nH(2)O (where M = Co(II) and Cu(II); L = H2L1, H2L2 and H2L3; X = Cl; n = 2). From the spectroscopic and magnetic studies, it has been concluded that the Co(11) and Cu(11) complexes display a five coordinated square pyramidal geometry and the Ni(II) complexes have a six coordinated octahedral geometry. The Schiff bases and their metal complexes have also been screened for their antibacterial and antifungal activities by the MIC method. (C) 2011 Elsevier Ltd. All rights reserved.

Characterization of RNA polymerase III transcription factor TFIIIC from the mulberry silkworm, Bombyx mori

Fractionation of nuclear extracts from posterior silk glands of mulberry silkworm Bombyx mori. resolved the transcription factor TFIIIC into two components (designated here as TFIIIC and TFIIIC1) as in HeLa cell nuclear extracts. The reconstituted transcription of tRNA genes required the presence of both components. The affinity purified TFIIIC is a heteromeric complex comprising of five subunits ranging from 44 to 240 kDa. Of these, the 51-kDa subunit could be specifically crosslinked to the B box of tRNA(1)(Gly). Purified swTFIIIC binds to the B box sequences with an affinity in the same range as of yTFIIIC or hTFIIIC2. Although an histone acetyl transferase (HAT) activity was associated with the TFIIIC fractions during the initial stages of purification. the HAT activity, unlike the human TFIIIC preparations, was separated at the final DNA affinity step. The tRNA transcription from DNA template was independent of HAT activity but the repressed transcription from chromatin template could be partially restored by external supplementation of the dissociated HAT activity. This is the first report on the purification and characterization of TFIIIC from insect systems.

An Optimized SDE Model for Slotted Aloha

We consider a stochastic differential equation (SDE) model of slotted Aloha with the retransmission probability as the associated parameter. We formulate the problem in both (a) the finite horizon and (b) the infinite horizon average cost settings. We apply the algorithm of 3] for the first setting, while for the second, we adapt a related algorithm from 2] that was originally developed in the simulation optimization framework. In the first setting, we obtain an optimal parameter trajectory that prescribes the parameter to use at any given instant while in the second setting, we obtain an optimal time-invariant parameter. Our algorithms are seen to exhibit good performance.

Discovery of Application Workloads from Network File Traces

An understanding of application I/O access patterns is useful in several situations. First, gaining insight into what applications are doing with their data at a semantic level helps in designing efficient storage systems. Second, it helps create benchmarks that mimic realistic application behavior closely. Third, it enables autonomic systems as the information obtained can be used to adapt the system in a closed loop.All these use cases require the ability to extract the application-level semantics of I/O operations. Methods such as modifying application code to associate I/O operations with semantic tags are intrusive. It is well known that network file system traces are an important source of information that can be obtained non-intrusively and analyzed either online or offline. These traces are a sequence of primitive file system operations and their parameters. Simple counting, statistical analysis or deterministic search techniques are inadequate for discovering application-level semantics in the general case, because of the inherent variation and noise in realistic traces.In this paper, we describe a trace analysis methodology based on Profile Hidden Markov Models. We show that the methodology has powerful discriminatory capabilities that enable it to recognize applications based on the patterns in the traces, and to mark out regions in a long trace that encapsulate sets of primitive operations that represent higher-level application actions. It is robust enough that it can work around discrepancies between training and target traces such as in length and interleaving with other operations. We demonstrate the feasibility of recognizing patterns based on a small sampling of the trace, enabling faster trace analysis. Preliminary experiments show that the method is capable of learning accurate profile models on live traces in an online setting. We present a detailed evaluation of this methodology in a UNIX environment using NFS traces of selected commonly used applications such as compilations as well as on industrial strength benchmarks such as TPC-C and Postmark, and discuss its capabilities and limitations in the context of the use cases mentioned above.

A Transcript Cleavage Factor of Mycobacterium tuberculosis Important for Its Survival

After initiation of transcription, a number of proteins participate during elongation and termination modifying the properties of the RNA polymerase (RNAP). Gre factors are one such group conserved across bacteria. They regulate transcription by projecting their N-terminal coiled-coil domain into the active center of RNAP through the secondary channel and stimulating hydrolysis of the newly synthesized RNA in backtracked elongation complexes. Rv1080c is a putative gre factor (MtbGre) in the genome of Mycobacterium tuberculosis. The protein enhanced the efficiency of promoter clearance by lowering abortive transcription and also rescued arrested and paused elongation complexes on the GC rich mycobacterial template. Although MtbGre is similar in domain organization and shares key residues for catalysis and RNAP interaction with the Gre factors of Escherichia coli, it could not complement an E. coli gre deficient strain. Moreover, MtbGre failed to rescue E. coli RNAP stalled elongation complexes, indicating the importance of specific protein-protein interactions for transcript cleavage. Decrease in the level of MtbGre reduced the bacterial survival by several fold indicating its essential role in mycobacteria. Another Gre homolog, Rv3788 was not functional in transcript cleavage activity indicating that a single Gre is sufficient for efficient transcription of the M. tuberculosis genome.

A gradient PCR-based screen for use in site-directed mutagenesis

Site-directed mutagenesis is widely used to study protein and nucleic acid structure and function. Despite recent advancements in the efficiency of procedures for site-directed mutagenesis, the fraction of site-directed mutants by most procedures rarely exceeds 50% on a routine basis and is never 100%. Hence it is typically necessary to sequence two or three clones each time a site-directed mutant is constructed. We describe a simple and robust gradient-PCR-based screen for distinguishing site-directed mutants from the starting, unmutated plasmid. The procedure can use either purified plasmid DNA or colony PCR, starting from a single colony. The screen utilizes the primer used for mutagenesis and a common outside primer that can be used for all other mutants constructed with the same template. Over 30 site-specific mutants in a variety of templates were successfully screened and all of the mutations detected were subsequently confirmed by DNA sequencing. A single base pair mismatch could be detected in an oligonucleotide of 36 bases. Detection efficiency was relatively independent of starting template concentration and the nature of the outside primer used. (C) 2003 Elsevier Science (USA). All rights reserved.

Solving a part classification problem using simulated annealing-like hybrid

Part classification and coding is still considered as laborious and time-consuming exercise. Keeping in view, the crucial role, which it plays, in developing automated CAPP systems, the attempts have been made in this article to automate a few elements of this exercise using a shape analysis model. In this study, a 24-vector directional template is contemplated to represent the feature elements of the parts (candidate and prototype). Various transformation processes such as deformation, straightening, bypassing, insertion and deletion are embedded in the proposed simulated annealing (SA)-like hybrid algorithm to match the candidate part with their prototype. For a candidate part, searching its matching prototype from the information data is computationally expensive and requires large search space. However, the proposed SA-like hybrid algorithm for solving the part classification problem considerably minimizes the search space and ensures early convergence of the solution. The application of the proposed approach is illustrated by an example part. The proposed approach is applied for the classification of 100 candidate parts and their prototypes to demonstrate the effectiveness of the algorithm. (C) 2003 Elsevier Science Ltd. 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.

Environment Education for Ecosystem Conservation

Conservation of natural resources through sustainable ecosystem management and development is the key to our secured future. The management of ecosystem involves inventorying and monitoring, and applying integrated technologies, methodologies and interdisciplinary approaches for its conservation. Hence, now it is even more critical than ever before for the humans to be environmentally literate. To realise this vision, both ecological and environmental education must become a fundamental part of the education system at all levels of education. Currently, it is even more critical than ever before for the humankind as a whole to have a clear understanding of environmental concerns and to follow sustainable development practices. The degradation of our environment is linked to continuing problems of pollution, loss of forest, solid waste disposal, and issues related to economic productivity and national as well as ecological security. Environmental management has gained momentum in the recent years with the initiatives focussing on managing environmental hazards and preventing possible disasters. Environmental issues make better sense, when one can understand them in the context of one’s own cognitive sphere. Environmental education focusing on real-world contexts and issues often begins close to home, encouraging learners to understand and forge connections with their immediate surroundings. The awareness, knowledge, and skills needed for these local connections and understandings provide a base for moving out into larger systems, broader issues, and a more sophisticated comprehension of causes, connections, and consequences. Environmental Education Programme at CES in collaboration with Karnataka Environment Research Foundation (KERF) referred as ‘Know your Ecosystem’ focuses on the importance of investigating the ecosystems within the context of human influences, incorporating an examination of ecology, economics, culture, political structure, and social equity as well as natural processes and systems. The ultimate goal of environment education is to develop an environmentally literate public. It needs to address the connection between our conception and practice of education and our relationship as human cultures to life-sustaining ecological systems. For each environmental issue there are many perspectives and much uncertainty. Environmental education cultivates the ability to recognise uncertainty, envision alternative scenarios, and adapt to changing conditions and information. These knowledge, skills, and mindset translate into a citizenry who is better equipped to address its common problems and take advantage of opportunities, whether environmental concerns are involved or not.

Efficiently Approximating Query Optimizer Plan Diagrams

Given a parametrized n-dimensional SQL query template and a choice of query optimizer, a plan diagram is a color-coded pictorial enumeration of the execution plan choices of the optimizer over the query parameter space. These diagrams have proved to be a powerful metaphor for the analysis and redesign of modern optimizers, and are gaining currency in diverse industrial and academic institutions. However, their utility is adversely impacted by the impractically large computational overheads incurred when standard brute-force exhaustive approaches are used for producing fine-grained diagrams on high-dimensional query templates. In this paper, we investigate strategies for efficiently producing close approximations to complex plan diagrams. Our techniques are customized to the features available in the optimizer's API, ranging from the generic optimizers that provide only the optimal plan for a query, to those that also support costing of sub-optimal plans and enumerating rank-ordered lists of plans. The techniques collectively feature both random and grid sampling, as well as inference techniques based on nearest-neighbor classifiers, parametric query optimization and plan cost monotonicity. Extensive experimentation with a representative set of TPC-H and TPC-DS-based query templates on industrial-strength optimizers indicates that our techniques are capable of delivering 90% accurate diagrams while incurring less than 15% of the computational overheads of the exhaustive approach. In fact, for full-featured optimizers, we can guarantee zero error with less than 10% overheads. These approximation techniques have been implemented in the publicly available Picasso optimizer visualization tool.

Environment Education for Ecosystem Conservation

Conservation of natural resources through sustainable ecosystem management and development is the key to our secured future. The management of ecosystem involves inventorying and monitoring, and applying integrated technologies, methodologies and interdisciplinary approaches for its conservation. Hence, now it is even more critical than ever before for the humans to be environmentally literate. To realise this vision, both ecological and environmental education must become a fundamental part of the education system at all levels of education. Currently, it is even more critical than ever before for the humankind as a whole to have a clear understanding of environmental concerns and to follow sustainable development practices. The degradation of our environment is linked to continuing problems of pollution, loss of forest, solid waste disposal, and issues related to economic productivity and national as well as ecological security. Environmental management has gained momentum in the recent years with the initiatives focussing on managing environmental hazards and preventing possible disasters. Environmental issues make better sense, when one can understand them in the context of one’s own cognitive sphere. Environmental education focusing on real-world contexts and issues often begins close to home, encouraging learners to understand and forge connections with their immediate surroundings. The awareness, knowledge, and skills needed for these local connections and understandings provide a base for moving out into larger systems, broader issues, and a more sophisticated comprehension of causes, connections, and consequences. Environmental Education Programme at CES in collaboration with Karnataka Environment Research Foundation (KERF) referred as ‘Know your Ecosystem’ focuses on the importance of investigating the ecosystems within the context of human influences, incorporating an examination of ecology, economics, culture, political structure, and social equity as well as natural processes and systems. The ultimate goal of environment education is to develop an environmentally literate public. It needs to address the connection between our conception and practice of education and our relationship as human cultures to life-sustaining ecological systems. For each environmental issue there are many perspectives and much uncertainty. Environmental education cultivates the ability to recognise uncertainty, envision alternative scenarios, and adapt to changing conditions and information. These knowledge, skills, and mindset translate into a citizenry who is better equipped to address its common problems and take advantage of opportunities, whether environmental concerns are involved or not.

Distributed Source Coding for Sensor Data Model and Estimation of Cluster Head Errors Using Bayesian and K-Near Neighborhood Classifiers in Deployment of Dense Wireless Sensor Networks

The lifetime calculation of large dense sensor networks with fixed energy resources and the remaining residual energy have shown that for a constant energy resource in a sensor network the fault rate at the cluster head is network size invariant when using the network layer with no MAC losses.Even after increasing the battery capacities in the nodes the total lifetime does not increase after a max limit of 8 times. As this is a serious limitation lots of research has been done at the MAC layer which allows to adapt to the specific connectivity, traffic and channel polling needs for sensor networks. There have been lots of MAC protocols which allow to control the channel polling of new radios which are available to sensor nodes to communicate. This further reduces the communication overhead by idling and sleep scheduling thus extending the lifetime of the monitoring application. We address the two issues which effects the distributed characteristics and performance of connected MAC nodes. (1) To determine the theoretical minimum rate based on joint coding for a correlated data source at the singlehop, (2a) to estimate cluster head errors using Bayesian rule for routing using persistence clustering when node densities are the same and stored using prior probability at the network layer, (2b) to estimate the upper bound of routing errors when using passive clustering were the node densities at the multi-hop MACS are unknown and not stored at the multi-hop nodes a priori. In this paper we evaluate many MAC based sensor network protocols and study the effects on sensor network lifetime. A renewable energy MAC routing protocol is designed when the probabilities of active nodes are not known a priori. From theoretical derivations we show that for a Bayesian rule with known class densities of omega1, omega2 with expected error P* is bounded by max error rate of P=2P* for single-hop. We study the effects of energy losses using cross-layer simulation of - large sensor network MACS setup, the error rate which effect finding sufficient node densities to have reliable multi-hop communications due to unknown node densities. The simulation results show that even though the lifetime is comparable the expected Bayesian posterior probability error bound is close or higher than Pges2P*.

Environment Education for Ecosystem Conservation

Conservation of natural resources through sustainable ecosystem management and development is the key to our secured future. The management of ecosystem involves inventorying and monitoring, and applying integrated technologies, methodologies and interdisciplinary approaches for its conservation. Hence, now it is even more critical than ever before for the humans to be environmentally literate. To realise this vision, both ecological and environmental education must become a fundamental part of the education system at all levels of education. Currently, it is even more critical than ever before for the humankind as a whole to have a clear understanding of environmental concerns and to follow sustainable development practices. The degradation of our environment is linked to continuing problems of pollution, loss of forest, solid waste disposal, and issues related to economic productivity and national as well as ecological security. Environmental management has gained momentum in the recent years with the initiatives focussing on managing environmental hazards and preventing possible disasters. Environmental issues make better sense, when one can understand them in the context of one’s own cognitive sphere. Environmental education focusing on real-world contexts and issues often begins close to home, encouraging learners to understand and forge connections with their immediate surroundings. The awareness, knowledge, and skills needed for these local connections and understandings provide a base for moving out into larger systems, broader issues, and a more sophisticated comprehension of causes, connections, and consequences. Environmental Education Programme at CES in collaboration with Karnataka Environment Research Foundation (KERF) referred as ‘Know your Ecosystem’ focuses on the importance of investigating the ecosystems within the context of human influences, incorporating an examination of ecology, economics, culture, political structure, and social equity as well as natural processes and systems. The ultimate goal of environment education is to develop an environmentally literate public. It needs to address the connection between our conception and practice of education and our relationship as human cultures to life-sustaining ecological systems. For each environmental issue there are many perspectives and much uncertainty. Environmental education cultivates the ability to recognise uncertainty, envision alternative scenarios, and adapt to changing conditions and information. These knowledge, skills, and mindset translate into a citizenry who is better equipped to address its common problems and take advantage of opportunities, whether environmental concerns are involved or not.

Synthesis, structural characterization and ferroelectric properties of Pb(0.76)Ca(0.24)TiO(3) nanotubes

A capillary-enforced template-based method has been applied to fabricate Pb(0.76)Ca(0.24)TiO(3) (PCT24) nanotubes via filling PCT24 precursor solution, prepared by modified sol-gel method, into nanochannels of anodic aluminum oxide templates. The morphology and structure of as-prepared PCT24 were examined by scanning electron microscopy, transmission electron microscopy (TEM) and X-ray diffraction techniques. The obtained PCT24 nanotubes with diameter of similar to 200 nm and wall thickness of similar to 20 nm exhibited a tetragonal perovskite structure. High resolution TEM (HRTEM) analysis confirmed that as-obtained PCT24 nanotubes made up of nanoparticles (5-8 nm) which were randomly aligned in the nanotubes. Formation of some solid crystalline PCT24 nanorods, Y-junctions and multi-branches were observed. Interconnections in the pores of template are responsible for the growth of Y-junctions and multi-branches. The possible formation mechanism of PCT24 nanotubes/nanorods was discussed. Ferroelectric hysteresis loops of PCT24 nanotube arrays were measured, showing a room temperature ferroelectric characteristic of as-prepared PCT24 nanotubes. (C) 2011 Elsevier B.V. All rights reserved.

Compositionally modulated Pb(Mg1/3Nb2/3)O-3-PbTiO3 relaxor thin films deposited by pulsed excimer laser ablation technique

Thin films of (1-x)Pb(Mg1/3Nb2/3)O-3 - xPbTiO(3) (x = 0.1 to 0.3)(PMN-PT) were deposited on the platinum coated silicon substrate by pulsed excimer laser ablation technique. A template layer of LaSr0.5Co0.5O3 (LSCO) was deposited on platinum substrate prior to the deposition of PMN-PT thin films. The composition and the structure of the films were modulated via proper variation of the deposition parameter such as substrate temperature, laser fluence and thickness of the template layers. We observed the impact of the thickness of LSCO template layer on the orientation of the films. A room temperature dielectric constant varying from 2000 to 4500 was noted for different composition of the films. The dielectric properties of the films were studied over the frequency range of 100 Hz - 100 kHz over a wide range of temperatures. The films exhibited the relaxor- type behavior that was characterized by the frequency dispersion of the temperature of dielectric constant maxima (T-m) and also diffuse phase transition. C1 Indian Inst Sci, Mat Res Ctr, Bangalore, Karnataka 560012 India.