198 resultados para Third generation

em Indian Institute of Science - Bangalore - Índia


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In this paper, downscaling models are developed using a support vector machine (SVM) for obtaining projections of monthly mean maximum and minimum temperatures (T-max and T-min) to river-basin scale. The effectiveness of the model is demonstrated through application to downscale the predictands for the catchment of the Malaprabha reservoir in India, which is considered to be a climatically sensitive region. The probable predictor variables are extracted from (1) the National Centers for Environmental Prediction (NCEP) reanalysis dataset for the period 1978-2000, and (2) the simulations from the third-generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 1978-2100. The predictor variables are classified into three groups, namely A, B and C. Large-scale atmospheric variables Such as air temperature, zonal and meridional wind velocities at 925 nib which are often used for downscaling temperature are considered as predictors in Group A. Surface flux variables such as latent heat (LH), sensible heat, shortwave radiation and longwave radiation fluxes, which control temperature of the Earth's surface are tried as plausible predictors in Group B. Group C comprises of all the predictor variables in both the Groups A and B. The scatter plots and cross-correlations are used for verifying the reliability of the simulation of the predictor variables by the CGCM3 and to Study the predictor-predictand relationships. The impact of trend in predictor variables on downscaled temperature was studied. The predictor, air temperature at 925 mb showed an increasing trend, while the rest of the predictors showed no trend. The performance of the SVM models that are developed, one for each combination of predictor group, predictand, calibration period and location-based stratification (land, land and ocean) of climate variables, was evaluated. In general, the models which use predictor variables pertaining to land surface improved the performance of SVM models for downscaling T-max and T-min

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During the course of genome studies in a rural community in the South Indian state of Karnataka, DNA-based investigations and counselling for familial adenomatous polyposis (FAP) were requested via the community physician. The proposita died in 1940 and FAP had been clinically diagnosed in 2 of her 5 children, both deceased. DNA samples from 2 affected individuals in the third generation were screened for mutations in the APC gene, and a frame-shift mutation was identified in exon 15 with a common deletion at codon 1061. Predictive testing for the mutation was then organized on a voluntary basis. There were 11 positive tests, including confirmatory positives on 2 persons diagnosed by colonoscopy, and to date surgery has been successfully undertaken on 3 previously undiagnosed adults. The ongoing success of the study indicates that, with appropriate access to the facilities offered by collaborating centres, predictive testing is feasible for diseases such as FAP and could be of significant benefit to communities in economically less developed countries.

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General relativity has very specific predictions for the gravitational waveforms from inspiralling compact binaries obtained using the post-Newtonian (PN) approximation. We investigate the extent to which the measurement of the PN coefficients, possible with the second generation gravitational-wave detectors such as the Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) and the third generation gravitational-wave detectors such as the Einstein Telescope (ET), could be used to test post-Newtonian theory and to put bounds on a subclass of parametrized-post-Einstein theories which differ from general relativity in a parametrized sense. We demonstrate this possibility by employing the best inspiralling waveform model for nonspinning compact binaries which is 3.5PN accurate in phase and 3PN in amplitude. Within the class of theories considered, Advanced LIGO can test the theory at 1.5PN and thus the leading tail term. Future observations of stellar mass black hole binaries by ET can test the consistency between the various PN coefficients in the gravitational-wave phasing over the mass range of 11-44M(circle dot). The choice of the lower frequency cutoff is important for testing post-Newtonian theory using the ET. The bias in the test arising from the assumption of nonspinning binaries is indicated.

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Hardware constraints, which motivate receive antenna selection, also require that various antenna elements at the receiver be sounded sequentially to obtain estimates required for selecting the `best' antenna and for coherently demodulating data thereafter. Consequently, the channel state information at different antennas is outdated by different amounts and corrupted by noise. We show that, for this reason, simply selecting the antenna with the highest estimated channel gain is not optimum. Rather, a preferable strategy is to linearly weight the channel estimates of different antennas differently, depending on the training scheme. We derive closed-form expressions for the symbol error probability (SEP) of AS for MPSK and MQAM in time-varying Rayleigh fading channels for arbitrary selection weights, and validate them with simulations. We then characterize explicitly the optimal selection weights that minimize the SEP. We also consider packet reception, in which multiple symbols of a packet are received by the same antenna. New suboptimal, but computationally efficient weighted selection schemes are proposed for reducing the packet error rate. The benefits of weighted selection are also demonstrated using a practical channel code used in third generation cellular systems. Our results show that optimal weighted selection yields a significant performance gain over conventional unweighted selection.

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This report deals with a study of the properties of internal cavities of dendritic macromolecules that are capable Of encapsulating and mediating photoreactions of guest molecules. The internal cavity structures of dendrimers are determined by the interfacial regions between the aqueous exterior and hydrocarbon like interior constituted by the linkers that connect symmetrically sited branch points constituting the dendrimer and head groups that cap the dendrimers. Phloroglucinol-based poly(alkyl aryl ether) dendrimers constituted with a homologous series of alkyl linkers were undertaken for the current study. Twelve dendrimers within first, second, and third generations, having ethyl, n-propyl, n-butyl, and n-pentyl groups as the linkers and hydroxyl groups at peripheries in each generation, were synthesized. Encapsulation of pyrene and coumarins by aqueous basic solutions of dendrimers were monitored-by UV-vis and fluorescence spectroscopies, which showed that a lower generation dendrimer with an optimal alkyl linker presented better encapsulation abilities than a higher generation dendrimer. Norrish type I photoreaction of dibenzyl ketone was carried out within the above: series of dendrimers to probe their abilities to hold guests and reactive inthermediate radical pairs within themselves. The extent of cage effect from the series of third generation dendrimers was observed to be higher with dendrimers having an n-pentyl group as the linker.

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We review the current status of various aspects of biopolymer translocation through nanopores and the challenges and opportunities it offers. Much of the interest generated by nanopores arises from their potential application to third-generation cheap and fast genome sequencing. Although the ultimate goal of single-nucleotide identification has not yet been reached, great advances have been made both from a fundamental and an applied point of view, particularly in controlling the translocation time, fabricating various kinds of synthetic pores or genetically engineering protein nanopores with tailored properties, and in devising methods (used separately or in combination) aimed at discriminating nucleotides based either on ionic or transverse electron currents, optical readout signatures, or on the capabilities of the cellular machinery. Recently, exciting new applications have emerged, for the detection of specific proteins and toxins (stochastic biosensors), and for the study of protein folding pathways and binding constants of protein-protein and protein-DNA complexes. The combined use of nanopores and advanced micromanipulation techniques involving optical/magnetic tweezers with high spatial resolution offers unique opportunities for improving the basic understanding of the physical behavior of biomolecules in confined geometries, with implications for the control of crucial biological processes such as protein import and protein denaturation. We highlight the key works in these areas along with future prospects. Finally, we review theoretical and simulation studies aimed at improving fundamental understanding of the complex microscopic mechanisms involved in the translocation process. Such understanding is a pre-requisite to fruitful application of nanopore technology in high-throughput devices for molecular biomedical diagnostics.

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Accurate system planning and performance evaluation requires knowledge of the joint impact of scheduling, interference, and fading. However, current analyses either require costly numerical simulations or make simplifying assumptions that limit the applicability of the results. In this paper, we derive analytical expressions for the spectral efficiency of cellular systems that use either the channel-unaware but fair round robin scheduler or the greedy, channel-aware but unfair maximum signal to interference ratio scheduler. As is the case in real deployments, non-identical co-channel interference at each user, both Rayleigh fading and lognormal shadowing, and limited modulation constellation sizes are accounted for in the analysis. We show that using a simple moment generating function-based lognormal approximation technique and an accurate Gaussian-Q function approximation leads to results that match simulations well. These results are more accurate than erstwhile results that instead used the moment-matching Fenton-Wilkinson approximation method and bounds on the Q function. The spectral efficiency of cellular systems is strongly influenced by the channel scheduler and the small constellation size that is typically used in third generation cellular systems.

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Dendritic rnicroenvironments defined by dynamic internal cavities of a dendrimer were probed through geometric isomerization of stilbene and azobenzene. A third-generation poly(alkyl aryl ether) dendrimer with hydrophilic exterior and hydrophobic interior was used as a reaction cavity in aqueous medium. The dynamic inner cavity sizes were varied by utilizing alkyl linkers that connect the branch junctures from ethyl to n-pentyl moiety (C(2)G(3)-C(5)G(3)). Dendrimers constituted with n-pentyl linker were found to afford higher solubilities of stilbene and azobenzene. Direct irradiation of trans-stilbene showed that C(5)G(3) and C(4)G(3) dendrimers afforded considerable phenanthrene formation, in addition to cis-stilbene, whereas C(3)G(3) and C(2)G(3) gave only cis-stilbene. An electron-transfer sensitized trans-cis isomerization, using cresyl violet perchlorate as the sensitizer, also led to similar results. Thermal isomerization of cis-azobenzene to trans-azobenzene within dendritic microenvironments revealed that the activation energy of the cis- to trans-isomer was increasing in the series C(5)G(3) < C(4)G(3) < C(3)G(3)

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A two-stage methodology is developed to obtain future projections of daily relative humidity in a river basin for climate change scenarios. In the first stage, Support Vector Machine (SVM) models are developed to downscale nine sets of predictor variables (large-scale atmospheric variables) for Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) (A1B, A2, B1, and COMMIT) to R (H) in a river basin at monthly scale. Uncertainty in the future projections of R (H) is studied for combinations of SRES scenarios, and predictors selected. Subsequently, in the second stage, the monthly sequences of R (H) are disaggregated to daily scale using k-nearest neighbor method. The effectiveness of the developed methodology is demonstrated through application to the catchment of Malaprabha reservoir in India. For downscaling, the probable predictor variables are extracted from the (1) National Centers for Environmental Prediction reanalysis data set for the period 1978-2000 and (2) simulations of the third-generation Canadian Coupled Global Climate Model for the period 1978-2100. The performance of the downscaling and disaggregation models is evaluated by split sample validation. Results show that among the SVM models, the model developed using predictors pertaining to only land location performed better. The R (H) is projected to increase in the future for A1B and A2 scenarios, while no trend is discerned for B1 and COMMIT.

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Accurate supersymmetric spectra are required to confront data from direct and indirect searches of supersymmetry. SuSeFLAV is a numerical tool capable of computing supersymmetric spectra precisely for various supersymmetric breaking scenarios applicable even in the presence of flavor violation. The program solves MSSM RGEs with complete 3 x 3 flavor mixing at 2-loop level and one loop finite threshold corrections to all MSSM parameters by incorporating radiative electroweak symmetry breaking conditions. The program also incorporates the Type-I seesaw mechanism with three massive right handed neutrinos at user defined mass scales and mixing. It also computes branching ratios of flavor violating processes such as l(j) -> l(i)gamma, l(j) -> 3 l(i), b -> s gamma and supersymmetric contributions to flavor conserving quantities such as (g(mu) - 2). A large choice of executables suitable for various operations of the program are provided. Program summary Program title: SuSeFLAV Catalogue identifier: AEOD_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEOD_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License No. of lines in distributed program, including test data, etc.: 76552 No. of bytes in distributed program, including test data, etc.: 582787 Distribution format: tar.gz Programming language: Fortran 95. Computer: Personal Computer, Work-Station. Operating system: Linux, Unix. Classification: 11.6. Nature of problem: Determination of masses and mixing of supersymmetric particles within the context of MSSM with conserved R-parity with and without the presence of Type-I seesaw. Inter-generational mixing is considered while calculating the mass spectrum. Supersymmetry breaking parameters are taken as inputs at a high scale specified by the mechanism of supersymmetry breaking. RG equations including full inter-generational mixing are then used to evolve these parameters up to the electroweak breaking scale. The low energy supersymmetric spectrum is calculated at the scale where successful radiative electroweak symmetry breaking occurs. At weak scale standard model fermion masses, gauge couplings are determined including the supersymmetric radiative corrections. Once the spectrum is computed, the program proceeds to various lepton flavor violating observables (e.g., BR(mu -> e gamma), BR(tau -> mu gamma) etc.) at the weak scale. Solution method: Two loop RGEs with full 3 x 3 flavor mixing for all supersymmetry breaking parameters are used to compute the low energy supersymmetric mass spectrum. An adaptive step size Runge-Kutta method is used to solve the RGEs numerically between the high scale and the electroweak breaking scale. Iterative procedure is employed to get the consistent radiative electroweak symmetry breaking condition. The masses of the supersymmetric particles are computed at 1-loop order. The third generation SM particles and the gauge couplings are evaluated at the 1-loop order including supersymmetric corrections. A further iteration of the full program is employed such that the SM masses and couplings are consistent with the supersymmetric particle spectrum. Additional comments: Several executables are presented for the user. Running time: 0.2 s on a Intel(R) Core(TM) i5 CPU 650 with 3.20 GHz. (c) 2012 Elsevier B.V. All rights reserved.

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The Large Hadron Collider (LHC) has completed its run at 8 TeV with the experiments ATLAS and CMS having collected about 25 fb(-1) of data each. Discovery of a light Higgs boson coupled with lack of evidence for supersymmetry at the LHC so far, has motivated studies of supersymmetry in the context of naturalness with the principal focus being the third generation squarks. In this work, we analyze the prospects of the flavor violating decay mode (t) over tilde (1) -> c chi(0)(1) at 8 and 13 TeV center-of-mass energy at the LHC. This channel is also relevant in the dark matter context for the stop-coannihilation scenario, where the relic density depends on the mass difference between the lighter stop quark ((t) over tilde (1)) and the lightest neutralino (chi(0)(1)) states. This channel is extremely challenging to probe, especially for situations when the mass difference between the lighter stop quark and the lightest neutralino is small. Using certain kinematical properties of signal events we find that the level of backgrounds can be reduced substantially. We find that the prospect for this channel is limited due to the low production cross section for top squarks and limited luminosity at 8 TeV, but at the 13 TeV LHC with 100 fb(-1) luminosity, it is possible to probe top squarks with masses up to similar to 450 GeV. We also discuss how the sensitivity could be significantly improved by tagging charm jets.

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A variety of methods are available to estimate future solar radiation (SR) scenarios at spatial scales that are appropriate for local climate change impact assessment. However, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. Three methodologies to guide the estimation of SR are discussed in this study, namely: Case 1: SR is measured, Case 2: SR is measured but sparse and Case 3: SR is not measured. In Case 1, future SR scenarios are derived using several downscaling methodologies that transfer the simulated large-scale information of global climate models to a local scale ( measurements). In Case 2, the SR was first estimated at the local scale for a longer time period using sparse measured records, and then future scenarios were derived using several downscaling methodologies. In Case 3: the SR was first estimated at a regional scale for a longer time period using complete or sparse measured records of SR from which SR at the local scale was estimated. Finally, the future scenarios were derived using several downscaling methodologies. The lack of observed SR data, especially in developing countries, has hindered various climate change impact studies. Hence, this was further elaborated by applying the Case 3 methodology to a semi-arid Malaprabha reservoir catchment in southern India. A support vector machine was used in downscaling SR. Future monthly scenarios of SR were estimated from simulations of third-generation Canadian General Circulation Model (CGCM3) for various SRES emission scenarios (A1B, A2, B1, and COMMIT). Results indicated a projected decrease of 0.4 to 12.2 W m(-2) yr(-1) in SR during the period 2001-2100 across the 4 scenarios. SR was calculated using the modified Hargreaves method. The decreasing trends for the future were in agreement with the simulations of SR from the CGCM3 model directly obtained for the 4 scenarios.

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We report the synthesis of branched ZnO nanostructures by vapour phase transport and their multistage effect in enhancing the field emission behaviour. First, the ZnO nanowires (first generation) are grown and second generation nanowires are grown on first one and so on to obtain the branched structures. The number of branches increases and the diameter of the branches decreases till the third generation nanowires. Fourth generation onwards, dense branched structures are obtained eventually yielding nanoforest-like morphology. The field emission behaviour is found to improve till the third generation and is assigned to smaller diameter of the branches. (C) 2014 AIP Publishing LLC.

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Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001-10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies.

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A water soluble third generation poly(alkyl aryl ether) dendrimer was examined for its ability to solubilize hydrophobic polyaromatic molecules in water and facilitate non-radiative resonance energy transfer between them. One to two orders of magnitude higher aqueous solubilities of pyrene (PY), perylene (PE), acridine yellow (AY) and acridine orange (AO) were observed in presence of a defined concentration of the dendrimer. A reduction in the quantum yield of the donor PY* emission and a partial decrease in lifetime of the donor excited state revealed the occurrence of energy transfer from dendrimer solubilized excited PY to ground state PE molecules, both present within a dendrimer. The energy transfer efficiency was estimated to be similar to 61%. A cascade resonance energy transfer in a three component system, PY*-to-PE-to-AY and PY*-to-PE-to-AO, was demonstrated through incorporation of AY or AO in the two component PY-PE system. In the three-component system, excitation of PY resulted in emission from AY or AO via a cascade energy transfer process. Careful choice of dye molecules with good spectral overlap and the employment of dendrimer as the medium enabled us to expand absorption-emission wavelengths, from similar to 330 nm to similar to 600 nm in aqueous solution. (C) 2015 Elsevier B.V. All rights reserved.