983 resultados para tag


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Analytical solution is presented to convert a given driving-point impedance function (in s-domain) into a physically realisable ladder network with inductive coupling between any two sections and losses considered. The number of sections in the ladder network can vary, but its topology is assumed fixed. A study of the coefficients of the numerator and denominator polynomials of the driving-point impedance function of the ladder network, for increasing number of sections, led to the identification of certain coefficients, which exhibit very special properties. Generalised expressions for these specific coefficients have also been derived. Exploiting their properties, it is demonstrated that the synthesis method essentially turns out to be an exercise of solving a set of linear, simultaneous, algebraic equations, whose solution directly yields the ladder network elements. The proposed solution is novel, simple and guarantees a unique network. Presently, the formulation can synthesise a unique ladder network up to six sections.

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The development of a neural network based power system damping controller (PSDC) for a static VAr compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system

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As power systems grow in their size and interconnections, their complexity increases. Rising costs due to inflation and increased environmental concerns has made transmission, as well as generation systems be operated closer to design limits. Hence power system voltage stability and voltage control are emerging as major problems in the day-to-day operation of stressed power systems. For secure operation and control of power systems under normal and contingency conditions it is essential to provide solutions in real time to the operator in energy control center (ECC). Artificial neural networks (ANN) are emerging as an artificial intelligence tool, which give fast, though approximate, but acceptable solutions in real time as they mostly use the parallel processing technique for computation. The solutions thus obtained can be used as a guide by the operator in ECC for power system control. This paper deals with development of an ANN architecture, which provide solutions for monitoring, and control of voltage stability in the day-to-day operation of power systems.

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This paper presents a method for placement of Phasor Measurement Units, ensuring the monitoring of vulnerable buses which are obtained based on transient stability analysis of the overall system. Real-time monitoring of phase angles across different nodes, which indicates the proximity to instability, the very purpose will be well defined if the PMUs are placed at buses which are more vulnerable. The issue is to identify the key buses where the PMUs should be placed when the transient stability prediction is taken into account considering various disturbances. Integer Linear Programming technique with equality and inequality constraints is used to find out the optimal placement set with key buses identified from transient stability analysis. Results on IEEE-14 bus system are presented to illustrate the proposed approach.

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Present day power systems are growing in size and complexity of operation with inter connections to neighboring systems, introduction of large generating units, EHV 400/765 kV AC transmission systems, HVDC systems and more sophisticated control devices such as FACTS. For planning and operational studies, it requires suitable modeling of all components in the power system, as the number of HVDC systems and FACTS devices of different type are incorporated in the system. This paper presents reactive power optimization with three objectives to minimize the sum of the squares of the voltage deviations (ve) of the load buses, minimization of sum of squares of voltage stability L-indices of load buses (¿L2), and also the system real power loss (Ploss) minimization. The proposed methods have been tested on typical sample system. Results for Indian 96-bus equivalent system including HVDC terminal and UPFC under normal and contingency conditions are presented.

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Capillary pumped loop (CPL) and loop heat pipe (LHP) are passive two-phase heat transport devices. They have been gaining importance as a part of the thermal control system of spacecraft. The evaporation heat transfer coefficient at the tooth-wick interface of an LHP or CPL has a significant impact on the evaporator temperature. It is also the main parameter in sizing of a CPL or LHP. Experimentally determined evaporation heat transfer coefficients from a three-port CPL with tubular axially grooved (TAG) evaporator and a TAG LHP with acetone, R-134A, and ammonia as working fluids are presented in this paper. The influences of working fluid, hydrodynamic blocks in the core, evaporator configuration (LHP or CPL), and adverse elevation (evaporator above condenser) on the heat transfer coefficient are presented.

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Deoxyhypusine hydroxylase (DOHH) catalyzes the final step in the post-translational synthesis of an unusual amino acid hypusine (N-(sic)-(4-amino-2-hydroxybutyl) lysine), which is present on only one cellular protein, eukaryotic initiation factor 5A (eIF5A). We present here the molecular and structural basis of the function of DOHH from the protozoan parasite, Leishmania donovani, which causes visceral leishmaniasis. The L. donovani DOHH gene is 981 bp and encodes a putative polypeptide of 326 amino acids. DOHH is a HEAT-repeat protein with eight tandem repeats of alpha-helical pairs. Four conserved histidine-glutamate sequences have been identified that may act as metal coordination sites. A similar to 42 kDa recombinant protein with a His-tag was obtained by heterologous expression of DOHH in Escherichia coli. Purified recombinant DOHH effectively catalyzed the hydroxylation of the intermediate, eIF5A-deoxyhypusine (eIF5A-Dhp), in vitro. L. donovani DOHH (LdDOHH) showed similar to 40.6% sequence identity with its human homolog. The alignment of L. donovani DOHH with the human homolog shows that there are two significant insertions in the former, corresponding to the alignment positions 159-162 (four amino acid residues) and 174-183 (ten amino acid residues) which are present in the variable loop connecting the N- and C-terminal halves of the protein, the latter being present near the substrate binding site. Deletion of the ten-amino-acid-long insertion decreased LdDOHH activity to 14% of the wild type recombinant LdDOHH. Metal chelators like ciclopirox olamine (CPX) and mimosine significantly inhibited the growth of L. donovani and DOHH activity in vitro. These inhibitors were more effective against the parasite enzyme than the human enzyme. This report, for the first time, confirms the presence of a complete hypusine pathway in a kinetoplastid unlike eubacteria and archaea. The structural differences between the L. donovani DOHH and the human homolog may be exploited for structure based design of selective inhibitors against the parasite.

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Ethnopharmacological relevance: Medicinal plants have played an important role in treating and preventing a variety of diseases throughout the world. Khampti tribal people living in the far-flung Lohit district of the Eastern Arunachal Himalaya, India still depend on medicinal plants and most of them have a general knowledge of medicinal plants which are used for treating a variety of ailments. This survey was undertaken in Lohit district in order to inventory the medicinal plants used in folk medicine to treat diabetes mellitus. Materials and methods: Field investigations were conducted in seventeen remote villages of Lohit district starting from April 2002 to May 2004 through interviews among 251 key informants who were selected randomly during our household survey. To elucidate community domains and determine differences in indigenous traditional knowledge of medicinal plants with anti-diabetic efficacy, we repeated our field survey starting from April 2008 to May 2010 with one hundred traditional healers locally called as ``Chau ya'' in Khampti of Lohit district. ``Chau ya'' traditional healers who know and use medicinal plants for treating diabetes mellitus were interviewed using a semi-structured questionnaire. Results: This study reports an ethnobotanical survey of medicinal plants in Lohit district of Arunachal Pradesh reputed for the treatment of diabetes mellitus. Forty-six plant species were identified in the study area to treat diabetes mellitus by the Khamptis ``Chau ya'' traditional healers. Comparative published literature survey analysis of this study with other ethnobotanical surveys of plants used traditionally in treating diabetes mellitus suggests that eleven plant species make claims of new reports on antidiabetic efficacy. These plant species are Begonia roxburghii, Calamus tenuis, Callicarpa arborea, Cuscuta reflexa, Dillenia indica, Diplazium esculentum, Lectuca gracilis, Millingtonia hortensis, Oxalis griffithii, Saccharum spontaneum, and Solanum viarum. Some of the plants reported in this study have an antidiabetic effect on rodent models but none have sufficient clinical evidence of effectiveness. Conclusions: The wide variety of medicinal plants that are used to treat diabetes mellitus in this area supports the importance of plants in the primary healthcare system of the rural people of Lohit district of Arunachal Pradesh. The finding of new plant uses in the current study reveals the importance of the documentation of such ethnobotanical knowledge. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

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Cyclic di-GMP (c-di-GMP), a ubiquitous bacterial second messenger, has emerged as a key controller of several biological processes. Numbers of reports that deal with the mechanistic aspects of this second messenger have appeared in the literature. However, the lack of a reporter tag attached to the c-di-GMP at times limits the understanding of further details. In this study, we have chemically coupled N-methylisatoic anhydride (MANT) with c-di-GMP, giving rise to Mant-(c-di-GMP) or MANT-CDG. We have characterized the chemical and physical properties and spectral behavior of MANT-CDG. The fluorescence of MANT-CDG is sensitive to changes in the microenvironment, which helped us study its interaction with three different c-di-GMP binding proteins (a diguanylate cyclase, a phosphodiesterase, and a PilZ domain-containing protein). In addition, we have shown here that MANT-CDG can inhibit diguanylate cyclase activity; however, it is hydrolyzed by c-di-GMP specific phosphodiesterase. Taken together, our data suggest that MANT-CDG behaves like native c-di-GMP, and this study raises the possibility that MANT-CDG will be a valuable research tool for the in vitro characterization of c-di-GMP signaling factors.

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Energy and energy services are the backbone of growth and development in India and is increasingly dependent upon the use of fossil based fuels that lead to greenhouse gases (GHG) emissions and related concerns. Algal biofuels are being evolved as carbon (C)-neutral alternative biofuels. Algae are photosynthetic microorganisms that convert sunlight, water and carbon dioxide (CO2) to various sugars and lipids Tri-Acyl-Glycols (TAG) and show promise as an alternative, renewable and green fuel source for India. Compared to land based oilseed crops algae have potentially higher yields (5-12 g/m(2)/d) and can use locations and water resources not suited for agriculture. Within India, there is little additional land area for algal cultivation and therefore needs to be carried out in places that are already used for agriculture, e.g. flooded paddy lands (20 Mha) with village level technologies and on saline wastelands (3 Mha). Cultivating algae under such conditions requires novel multi-tier, multi-cyclic approaches of sharing land area without causing threats to food and water security as well as demand for additional fertilizer resources by adopting multi-tier cropping (algae-paddy) in decentralized open pond systems. A large part of the algal biofuel production is possible in flooded paddy crop land before the crop reaches dense canopies, in wastewaters (40 billion litres per day), in salt affected lands and in nutrient/diversity impoverished shallow coastline fishery. Mitigation will be achieved through avoidance of GHG, C-capture options and substitution of fossil fuels. Estimates made in this paper suggest that nearly half of the current transportation petro-fuels could be produced at such locations without disruption of food security, water security or overall sustainability. This shift can also provide significant mitigation avenues. The major adaptation needs are related to socio-technical acceptance for reuse of various wastelands, wastewaters and waste-derived energy and by-products through policy and attitude change efforts.

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Escherichia coli-mycobacterium shuttle vectors are important tools for gene expression and gene replacement in mycobacteria. However, most of the currently available vectors are limited in their use because of the lack of extended multiple cloning sites (MCSs) and convenience of appending an epitope tag(s) to the cloned open reading frames (ORFs). Here we report a new series of vectors that allow for the constitutive and regulatable expression of proteins, appended with peptide tag sequences at their N and C termini, respectively. The applicability of these vectors is demonstrated by the constitutive and induced expression of the Mycobacterium tuberculosis pknK gene, coding for protein kinase K, a serine-threonine protein kinase. Furthermore, a suicide plasmid with expanded MCS for creating gene replacements, a plasmid for chromosomal integrations at the commonly used L5 attB site, and a hypoxia-responsive vector, for expression of a gene(s) under hypoxic conditions that mimic latency, have also been created. Additionally, we have created a vector for the coexpression of two proteins controlled by two independent promoters, with each protein being in fusion with a different tag. The shuttle vectors developed in the present study are excellent tools for the analysis of gene function in mycobacteria and are a valuable addition to the existing repertoire of vectors for mycobacterial research.

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The biosynthesis of triacylglycerol (TAG) occurs in the microsomal membranes of eukaryotes. Here, we report the identification and functional characterization of diacylglycerol acyltransferase (DGAT), a member of the 10 S cytosolic TAG biosynthetic complex (TBC) in Rhodotorula glutinis. Both a full-length and an N-terminally truncated cDNA clone of a single gene were isolated from R. glutinis. The DGAT activity of the protein encoded by RgDGAT was confirmed in vivo by the heterologous expression of cDNA in a Saccharomyces cerevisiae quadruple mutant (H1246) that is defective in TAG synthesis. RgDGAT overexpression in yeast was found to be capable of acylating diacylglycerol (DAG) in an acyl-CoA-dependent manner. Quadruple mutant yeast cells exhibit growth defects in the presence of oleic acid, but wild-type yeast cells do not. In an in vivo fatty acid supplementation experiment, RgDGAT expression rescued quadruple mutant growth in an oleate-containing medium. We describe a soluble acyl-CoA-dependent DAG acyltransferase from R. glutinis that belongs to the DGAT3 class of enzymes. The study highlights the importance of an alternative TAG biosynthetic pathway in oleaginous yeasts.

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In plants, calcium-dependent protein kinases (CDPKs) are key intermediates in calcium-mediated signaling that couple changes in Ca2+ levels to a specific response. In the present study, we report the high-level soluble expression of calcium-dependent protein kinase1 from Cicer arietinum (CaCDPK1) in Escherichia coli. The expression of soluble CaCDPK1 was temperature dependent with a yield of 3-4 mg/l of bacterial culture. CaCDPK1 expressed as histidine-tag fusion protein was purified using Ni-NTA affinity chromatography till homogeneity. The recombinant CaCDPK1 protein exhibited both calcium-dependent autophosphorylation and substrate phosphorylation activities with a V (max) and K (m) value of 13.2 nmol/min/mg and 34.3 mu M, respectively, for histone III-S as substrate. Maximum autophosphorylation was seen only in the presence of calcium. Optimum temperature for autophosphorylation was found to be 37 A degrees C. The recombinant protein showed optimum pH range of 6-9. The role of autophosphorylation in substrate phosphorylation was investigated using histone III-S as exogenous substrate. Our results show that autophosphorylation happens before substrate phosphorylation and it happens via intra-molecular mechanism as the activity linearly depends on enzyme concentrations. Autophosphorylation enhances the kinase activity and reduces the lag phase of activation, and CaCDPK1 can utilize both ATP and GTP as phosphodonor but ATP is preferred than GTP.

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This work proposes a boosting-based transfer learning approach for head-pose classification from multiple, low-resolution views. Head-pose classification performance is adversely affected when the source (training) and target (test) data arise from different distributions (due to change in face appearance, lighting, etc). Under such conditions, we employ Xferboost, a Logitboost-based transfer learning framework that integrates knowledge from a few labeled target samples with the source model to effectively minimize misclassifications on the target data. Experiments confirm that the Xferboost framework can improve classification performance by up to 6%, when knowledge is transferred between the CLEAR and FBK four-view headpose datasets.

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Non-negative matrix factorization [5](NMF) is a well known tool for unsupervised machine learning. It can be viewed as a generalization of the K-means clustering, Expectation Maximization based clustering and aspect modeling by Probabilistic Latent Semantic Analysis (PLSA). Specifically PLSA is related to NMF with KL-divergence objective function. Further it is shown that K-means clustering is a special case of NMF with matrix L2 norm based error function. In this paper our objective is to analyze the relation between K-means clustering and PLSA by examining the KL-divergence function and matrix L2 norm based error function.