992 resultados para Pesticide application


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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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Two new solution processable, low band gap donor-acceptor (D-A) copolymers (P1 and P2) comprising a cyclopentac] thiophene (CPT) based oligomers as donors and benzoc]1,2,5] selenadiazole (BDS) and 2-dodecyl1,2,3]-benzotriazole (BTAz) as acceptors were synthesized and characterized and their field effect transistor properties were studied. The internal charge transfer interaction between the electron-donating CPT based oligothiophene and the electron-accepting BDS or BTAz unit effectively reduces the band gap in polymers to 1.3 and 1.66 eV with low lying highest occupied molecular orbital (HOMO). The absorption spectrum of P1 was found to be more red shifted than that of P2 because of incorporation of the more electron-withdrawing BDS unit. The color of neutral P1 was found to be green in both solution and film states with two major bands in the absorption spectra; however, neutral P2 revealed one dominant absorption exhibiting red color in both solution and film state which could be attributed to the less electron-withdrawing effect of the BTAz unit. The polymers were further characterized by GPC, TGA, DSC and cyclic voltammetry. P1 and P2 exhibited charge carrier mobilities as high as 9 x 10(-3) cm(2) V-1 s(-1) and 2.56 x 10(-3) cm 2 V-1 s(-1), respectively with the current on/off ratio (I-on/I-off) in the order of 10(2).

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A flexible composite suitable for MHz frequency application has been developed by combining Fe3O4 and polyvinyl alcohol (PVA). The loss factor and the permeability have been evaluated. At an optimum weight percentage of Fe3O4 in the PVA matrix, the frequency at which the loss factor gives a minimum shifts to the MHz region. The loss factor has been found to be lower by one order of magnitude at 70 MHz compared to the presently used nickel zinc ferrite. The Henkel plot and the Cole-Cole plot have been obtained for the understanding of the high magnetic permeability and the low loss factor. (C) 2012 American Institute of Physics. doi:10.1063/1.3672867]

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Exascale systems of the future are predicted to have mean time between failures (MTBF) of less than one hour. Malleable applications, where the number of processors on which the applications execute can be changed during executions, can make use of their malleability to better tolerate high failure rates. We present AdFT, an adaptive fault tolerance framework for long running malleable applications to maximize application performance in the presence of failures. AdFT framework includes cost models for evaluating the benefits of various fault tolerance actions including checkpointing, live-migration and rescheduling, and runtime decisions for dynamically selecting the fault tolerance actions at different points of application execution to maximize performance. Simulations with real and synthetic failure traces show that our approach outperforms existing fault tolerance mechanisms for malleable applications yielding up to 23% improvement in application performance, and is effective even for petascale systems and beyond.

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Computational grids with multiple batch systems (batch grids) can be powerful infrastructures for executing long-running multi-component parallel applications. In this paper, we evaluate the potential improvements in throughput of long-running multi-component applications when the different components of the applications are executed on multiple batch systems of batch grids. We compare the multiple batch executions with executions of the components on a single batch system without increasing the number of processors used for executions. We perform our analysis with a foremost long-running multi-component application for climate modeling, the Community Climate System Model (CCSM). We have built a robust simulator that models the characteristics of both the multi-component application and the batch systems. By conducting large number of simulations with different workload characteristics and queuing policies of the systems, processor allocations to components of the application, distributions of the components to the batch systems and inter-cluster bandwidths, we show that multiple batch executions lead to 55% average increase in throughput over single batch executions for long-running CCSM. We also conducted real experiments with a practical middleware infrastructure and showed that multi-site executions lead to effective utilization of batch systems for executions of CCSM and give higher simulation throughput than single-site executions. Copyright (c) 2011 John Wiley & Sons, Ltd.

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In 2003, Babin et al. theoretically predicted (J. Appl. Phys. 94:4244, 2003) that fabrication of organic-inorganic hybrid materials would probably be required to implement structures with multiple photonic band gaps. In tune with their prediction, we report synthesis of such an inorganic-organic nanocomposite, comprising Cu4O3-CuO-C thin films that experimentally exhibit the highest (of any known material) number (as many as eleven) of photonic band gaps in the near infrared. On contrary to the report by Wang et al. (Appl. Phys. Lett. 84:1629, 2004) that photonic crystals with multiple stop gaps require highly correlated structural arrangement such as multilayers of variable thicknesses, we demonstrate experimental realization of multiple stop gaps in completely randomized structures comprising inorganic oxide nanocrystals (Cu4O3 and CuO) randomly embedded in a randomly porous carbonaceous matrix. We report one step synthesis of such nanostructured films through the metalorganic chemical vapor deposition technique using a single source metalorganic precursor, Cu-4(deaH)(dea)(oAc)(5) a <...aEuro parts per thousand(CH3)(2)CO. The films displaying multiple (4/9/11) photonic band gaps with equal transmission losses in the infrared are promising materials to find applications as multiple channel photonic band gap based filter for WDM technology.

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We propose a Riesz transform approach to the demodulation of digital holograms. The Riesz transform is a higher-dimensional extension of the Hilbert transform and is steerable to a desired orientation. Accurate demodulation of the hologram requires a reliable methodology by which quadrature-phase functions (or simply, quadratures) can be constructed. The Riesz transform, by itself, does not yield quadratures. However, one can start with the Riesz transform and construct the so-called vortex operator by employing the notion of quasi-eigenfunctions, and this approach results in accurate quadratures. The key advantage of using the vortex operator is that it effectively handles nonplanar fringes (interference patterns) and has the ability to compensate for the local orientation. Therefore, this method results in aberration-free holographic imaging even in the case when the wavefronts are not planar. We calibrate the method by estimating the orientation from a reference hologram, measured with an empty field of view. Demodulation results on synthesized planar as well as nonplanar fringe patterns show that the accuracy of demodulation is high. We also perform validation on real experimental measurements of Caenorhabditis elegans acquired with a digital holographic microscope. (c) 2012 Optical Society of America

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Two new hydroxynaphthyl-hydrazone based fluorogenic chemosensors R-1 and R-2 have been synthesized by Schiff base condensation of Tris(4-formylphenyl)amine with 1-hydroxynaphthalene-2-hydrazide and 1-hydroxynaphthalene-2-carbohydrazone, respectively. They are examined as highly selective and sensitive receptors for Cu2+ ions in aqueous medium. Electronic absorption as well as fluorescence titration studies of receptors R-1 and R-2 with different metal cations in H2O/CH3CN medium showed highly selective and very rapid (< 2 min) binding affinity towards Cu2+ ions even in the presence of other commonly coexisting metal ions such as Na+, K+, Mg2+, Ca2+, Mn2+, Fe2+, Co2+, Ni2+, Zn2+, Cd2+ and Hg2+. Quantification of the fluorescence titration analysis indicated that these newly synthesized receptors (R-1 and R-2) can indicate the presence of Cu2+ ions even at very low concentrations of 598 and 676 ppt, respectively. In addition, the propensity of these receptors as bio-imaging fluorescent probes to detect Cu2+ ions in human cervical HeLa cancer cell lines and their cytotoxicity against HeLa cells have been investigated.

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It is generally known that addition of conducting or insulating particles to mineral transformer oil, lowers its breakdown strength, E-d. However, if the particulates are of molecular dimensions, or nanoparticles, (NPs), as they are called, the breakdown strength is seen to increase considerably. Recent experiments by the authors on oil cooled power equipment such as transformers showed that, nanofluids comprising NPs of selected oxides of iron, such as Fe(3)o(4), called magnetite, added to transformer oil increased the breakdown voltage of the virgin oil and more importantly a remarkable enhancement in the thermal conductivity and the viscosity and hence an increased loadability of the transformer for a given top oil temperature (TOT).

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A new phenanthrene based chemosensor has been synthesized and investigated to act as highly selective fluorescence and visual sensor for Cu2+ ion with very low detection limit of 1.58 nM: this has also been used to image Cu2+ in human cervical HeLa cancer cells. (C) 2012 Elsevier B.V. All rights reserved.

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We report on the novel flow sensing application of piezoelectric ZnO thin film deposited on Phynox alloy sensing element. Characterization of piezoelectric ZnO films deposited on Phynox (Elgiloy) substrate at different RF powers is discussed. ZnO films deposited at RF power of 100W were found to have fine c-axis orientation, possesses excellent surface morphology with lower rms surface roughness of 1.87 nm and maximum d(31) coefficient value 4.7 pm V-1. The thin cantilever strip of Phynox alloy with ZnO film as a sensing layer for flow sensing has been tested for flow rates ranging from 2 to 18 L min(-1). A detailed theoretical analysis of the experimental set-up showing the relationship between output voltage and force at a particular flow rate has been discussed. The sensitivity of now sensing element is similar to 18 mV/(L min(-1)) and typical response time is of the order of 20 m s. The sensing element is calibrated using in-house developed testing set-up. (C) 2012 Elsevier B.V. All rights reserved.

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We consider a visual search problem studied by Sripati and Olson where the objective is to identify an oddball image embedded among multiple distractor images as quickly as possible. We model this visual search task as an active sequential hypothesis testing problem (ASHT problem). Chernoff in 1959 proposed a policy in which the expected delay to decision is asymptotically optimal. The asymptotics is under vanishing error probabilities. We first prove a stronger property on the moments of the delay until a decision, under the same asymptotics. Applying the result to the visual search problem, we then propose a ``neuronal metric'' on the measured neuronal responses that captures the discriminability between images. From empirical study we obtain a remarkable correlation (r = 0.90) between the proposed neuronal metric and speed of discrimination between the images. Although this correlation is lower than with the L-1 metric used by Sripati and Olson, this metric has the advantage of being firmly grounded in formal decision theory.

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Recently nano scale zero valent iron particles (nZVI) have been considered as smart adsorbent for environmental and groundwater remediation. Although several synthetic methods are available for the preparation of nZVI, air stable nZVI are not available for remediation works. Further, challenges demand synthesis of nZVI without stabilizers and capping agents. A modified methodology for the synthesis of air stable nZVI has been developed without any capping agents and characterized by powder X-Ray Diffraction (XRD), Scanning Electron Microscopy Energy-dispersive X-Ray (SEM-EDS), Transmission Electron Microscopy (TEM) and X-Ray Photoelectron Spectroscopy (XPS). The results of the present study suggest that the synthetic nZVI are air-stable over a period of one year and consists of particles of 30-40 nm in diameter. Although a layer of less than 3 am thick oxide/hydroxide is observed by TEM and XPS, it appears to be due to oxidation of outer surface during analysis. Adsorption study has shown that the synthetic nZVI are more effective adsorbent than the commercial nZVI and can remove simultaneously arsenite As-III] and arsenate As-V] from water without prior reduction of As-V to As-III. The removal process is adsorptive rather than precipitative and the removal of As-III is greater than that of As-V.

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We address the problem of phase retrieval, which is frequently encountered in optical imaging. The measured quantity is the magnitude of the Fourier spectrum of a function (in optics, the function is also referred to as an object). The goal is to recover the object based on the magnitude measurements. In doing so, the standard assumptions are that the object is compactly supported and positive. In this paper, we consider objects that admit a sparse representation in some orthonormal basis. We develop a variant of the Fienup algorithm to incorporate the condition of sparsity and to successively estimate and refine the phase starting from the magnitude measurements. We show that the proposed iterative algorithm possesses Cauchy convergence properties. As far as the modality is concerned, we work with measurements obtained using a frequency-domain optical-coherence tomography experimental setup. The experimental results on real measured data show that the proposed technique exhibits good reconstruction performance even with fewer coefficients taken into account for reconstruction. It also suppresses the autocorrelation artifacts to a significant extent since it estimates the phase accurately.