892 resultados para Towards Seamless Integration of Geoscience Models and Data


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This paper reports the results of employing an artificial bee colony search algorithm for synthesizing a mutually coupled lumped-parameter ladder-network representation of a transformer winding, starting from its measured magnitude frequency response. The existing bee colony algorithm is suitably adopted by appropriately defining constraints, inequalities, and bounds to restrict the search space and thereby ensure synthesis of a nearly unique ladder network corresponding to each frequency response. Ensuring near-uniqueness while constructing the reference circuit (i.e., representation of healthy winding) is the objective. Furthermore, the synthesized circuits must exhibit physical realizability. The proposed method is easy to implement, time efficient, and problems associated with the supply of initial guess in existing methods are circumvented. Experimental results are reported on two types of actual, single, and isolated transformer windings (continuous disc and interleaved disc).

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This paper reports the results of employing an artificial bee colony search algorithm for synthesizing a mutually coupled lumped-parameter ladder-network representation of a transformer winding, starting from its measured magnitude frequency response. The existing bee colony algorithm is suitably adopted by appropriately defining constraints, inequalities, and bounds to restrict the search space and thereby ensure synthesis of a nearly unique ladder network corresponding to each frequency response. Ensuring near-uniqueness while constructing the reference circuit (i.e., representation of healthy winding) is the objective. Furthermore, the synthesized circuits must exhibit physical realizability. The proposed method is easy to implement, time efficient, and problems associated with the supply of initial guess in existing methods are circumvented. Experimental results are reported on two types of actual, single, and isolated transformer windings (continuous disc and interleaved disc).

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This paper presents the advanced analytical methodologies such as Double- G and Double - K models for fracture analysis of concrete specimens made up of high strength concrete (HSC, HSC1) and ultra high strength concrete. Brief details about characterization and experimentation of HSC, HSC1 and UHSC have been provided. Double-G model is based on energy concept and couples the Griffith's brittle fracture theory with the bridging softening property of concrete. The double-K fracture model is based on stress intensity factor approach. Various fracture parameters such as cohesive fracture toughness (4), unstable fracture toughness (K-Ic(c)), unstable fracture toughness (K-Ic(un)) and initiation fracture toughness (K-Ic(ini)) have been evaluated based on linear elastic fracture mechanics and nonlinear fracture mechanics principles. Double-G and double-K method uses the secant compliance at the peak point of measured P-CMOD curves for determining the effective crack length. Bi-linear tension softening model has been employed to account for cohesive stresses ahead of the crack tip. From the studies, it is observed that the fracture parameters obtained by using double - G and double - K models are in good agreement with each other. Crack extension resistance has been estimated by using the fracture parameters obtained through double - K model. It is observed that the values of the crack extension resistance at the critical unstable point are almost equal to the values of the unstable fracture toughness K-Ic(un) of the materials. The computed fracture parameters will be useful for crack growth study, remaining life and residual strength evaluation of concrete structural components.

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Facet-based sentiment analysis involves discovering the latent facets, sentiments and their associations. Traditional facet-based sentiment analysis algorithms typically perform the various tasks in sequence, and fail to take advantage of the mutual reinforcement of the tasks. Additionally,inferring sentiment levels typically requires domain knowledge or human intervention. In this paper, we propose aseries of probabilistic models that jointly discover latent facets and sentiment topics, and also order the sentiment topics with respect to a multi-point scale, in a language and domain independent manner. This is achieved by simultaneously capturing both short-range syntactic structure and long range semantic dependencies between the sentiment and facet words. The models further incorporate coherence in reviews, where reviewers dwell on one facet or sentiment level before moving on, for more accurate facet and sentiment discovery. For reviews which are supplemented with ratings, our models automatically order the latent sentiment topics, without requiring seed-words or domain-knowledge. To the best of our knowledge, our work is the first attempt to combine the notions of syntactic and semantic dependencies in the domain of review mining. Further, the concept of facet and sentiment coherence has not been explored earlier either. Extensive experimental results on real world review data show that the proposed models outperform various state of the art baselines for facet-based sentiment analysis.

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For improved water management and efficiency of use in agriculture, studies dealing with coupled crop-surface water-groundwater models are needed. Such integrated models of crop and hydrology can provide accurate quantification of spatio-temporal variations of water balance parameters such as soil moisture store, evapotranspiration and recharge in a catchment. Performance of a coupled crop-hydrology model would depend on the availability of a calibrated crop model for various irrigated/rainfed crops and also on an accurate knowledge of soil hydraulic parameters in the catchment at relevant scale. Moreover, such a coupled model should be designed so as to enable the use/assimilation of recent satellite remote sensing products (optical and microwave) in order to model the processes at catchment scales. In this study we present a framework to couple a crop model with a groundwater model for applications to irrigated groundwater agricultural systems. We discuss the calibration of the STICS crop model and present a methodology to estimate the soil hydraulic parameters by inversion of crop model using both ground and satellite based data. Using this methodology we demonstrate the feasibility of estimation of potential recharge due to spatially varying soil/crop matrix.

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Authentication protocols are very much essential for secure communication in mobile ad hoc networks (MANETs). A number of authentication protocols for MANETs have been proposed in the literature which provide the basic authentication service while trying to optimize their performance and resource consumption parameters. A problem with most of these protocols is that the underlying networking environment on which they are applicable have been left unspecified. As a result, lack of specifications about the networking environments applicable to an authentication protocol for MANETs can mislead about the performance and the applicability of the protocol. In this paper, we first characterize networking environment for a MANET as its 'Membership Model' which is defined as a set of specifications related to the 'Membership Granting Server' (MGS) and the 'Membership Set Pattern' (MSP) of the MANET. We then identify various types of possible membership models for a MANET. In order to illustrate that while designing an authentication protocol for a MANET, it is very much necessary to consider the underlying membership model of the MANET, we study a set of six representative authentication protocols, and analyze their applicability for the membership models as enumerated in this paper. The analysis shows that the same protocol may not perform equally well in all membership models. In addition, there may be membership models which are important from the point of view of users, but for which no authentication protocol is available.

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Titanium carbide (TiC) is an electrically conducting refractory interstitial compound possessing several unique properties. A cost-effective, efficient and non-Pt electrocatalyst based on TiC is explored and the multi-functionality of TiC towards various electrochemical reactions that are of significant interest in low temperature fuel cells is studied. Ameliorated activities towards oxygen reduction reaction (ORR) and borohydride oxidation are observed with TiC-carbon composites. High sensitivity and selectivity towards ORR have been demonstrated with very good methanol tolerance. The charge transfer interactions between TiC and carbon seem to play a vital role in the improved activity as compared to their individual counterparts. The present study opens up a way to realize completely Pt-free borohydride fuel cell architecture.

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The localization and dispersion quality of as received NH2 terminated multiwall carbon nanotubes (MWNT-I) and ethylene diamine (EDA) functionalized MWNTs in melt mixed blends of polycarbonate ( PC) and poly(styrene-co-acrylonitrile) (SAN) were assessed in this study using rheo-electrical and electromagnetic interference (EMI) shielding measurements. In order to improve the dispersion quality and also to selectively localize MWNTs in the PC phase of the blends, EDA was grafted onto MWNTs by two different strategies like diazonium reaction of the para-substituted benzene ring of MWNTs with EDA ( referred to as MWNT-II) and acylation of carboxyl functionalized MWNTs with thionyl chloride ( referred to as MWNT-III). By this approach we could systematically vary the concentration of NH2 functional groups on the surface of MWNTs at a fixed concentration (1 wt%) in PC/SAN blends. XPS was carried to evaluate the % concentration of N in different MWNTs and was observed to be highest for MWNT-III manifesting in a large surface coverage of EDA on the surface of MWNTs. Viscoelastic properties and melt electrical conductivities were measured to assess the dispersion quality of MWNTs using a rheo-electrical set-up both in the quiescent as well as under steady shear conditions. Rheological properties revealed chain scission of PC in the presence of MWNT-III which is due to specific interactions between EDA and PC leading to smaller PC grafts on the surface of MWNTs. The observed viscoelastic properties in the blends were further correlated with the phase morphologies under quiescent and annealed conditions. Electromagnetic interference (EMI) shielding effectiveness in X and K-u-band frequencies were measured to explore these composites for EMI shielding applications. Interestingly, MWNT-II showed the highest electrical conductivity and EMI shielding in the blends.

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Background: mIHF belongs to a subfamily of proteins, distinct from E. coli IHF. Results: Functionally important amino acids of mIHF and the mechanism(s) underlying DNA binding, DNA bending, and site-specific recombination are distinct from that of E. coli IHF. Conclusion: mIHF functions could contribute beyond nucleoid compaction. Significance: Because mIHF is essential for growth, the molecular mechanisms identified here can be exploited in drug screening efforts. The annotated whole-genome sequence of Mycobacterium tuberculosis revealed that Rv1388 (Mtihf) is likely to encode for a putative 20-kDa integration host factor (mIHF). However, very little is known about the functional properties of mIHF or the organization of the mycobacterial nucleoid. Molecular modeling of the mIHF three-dimensional structure, based on the cocrystal structure of Streptomyces coelicolor IHF duplex DNA, a bona fide relative of mIHF, revealed the presence of Arg-170, Arg-171, and Arg-173, which might be involved in DNA binding, and a conserved proline (Pro-150) in the tight turn. The phenotypic sensitivity of Escherichia coli ihfA and ihfB strains to UV and methyl methanesulfonate could be complemented with the wild-type Mtihf but not its alleles bearing mutations in the DNA-binding residues. Protein-DNA interaction assays revealed that wild-type mIHF, but not its DNA-binding variants, binds with high affinity to fragments containing attB and attP sites and curved DNA. Strikingly, the functionally important amino acid residues of mIHF and the mechanism(s) underlying its binding to DNA, DNA bending, and site-specific recombination are fundamentally different from that of E. coli IHF. Furthermore, we reveal novel insights into IHF-mediated DNA compaction depending on the placement of its preferred binding sites; mIHF promotes DNA compaction into nucleoid-like or higher order filamentous structures. We therefore propose that mIHF is a distinct member of a subfamily of proteins that serve as essential cofactors in site-specific recombination and nucleoid organization and that these findings represent a significant advance in our understanding of the role(s) of nucleoid-associated proteins.

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Increasingly, scientific collaborations and contracts cross country borders. The need for assurance that the quality of animal welfare and the caliber of animal research conducted are equivalent among research partners around the globe is of concern to the scientific and laboratory animal medicine communities, the general public, and other key stakeholders. Therefore, global harmonization of animal care and use standards and practices, with the welfare of the animals as a cornerstone, is essential. In the evolving global landscape of enhanced attention to animal welfare, a widely accepted path to achieving this goal is the successful integration of the 3Rs in animal care and use programs. Currently, awareness of the 3Rs, their implementation, and the resulting animal care and use standards and practices vary across countries. This variability has direct effects on the animals used in research and potentially the data generated and may also have secondary effects on the country's ability to be viewed as a global research partner. Here we review the status of implementation of the 3Rs worldwide and focus on 3 countries-Brazil, China and India-with increasing economic influence and an increasing footprint in the biomedical research enterprise.

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Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.

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A novel design for the geometric configuration of honeycombs using a seamless combination of auxetic and conventional cores- elements with negative and positive Possion ratios respectively, has been presented. The proposed design has been shown to generate a superior band gap property while retaining all major advantages of a purely conventional or purely auxetic honeycomb structure. Seamless combination ensures that joint cardinality is also retained. Several configurations involving different degree of auxeticity and different proportions auxetic and conventional elements have been analyzed. It has been shown that the preferred configurations open up wide and clean band gap at a significantly lower frequency ranges compared to their pure counterparts. In view of existence of band gaps being desired feature for the phononic applications, reported results might be appealing. Use of such design may enable superior vibration control as well. Proposed configurations can be made isovolumic and iso-weight giving designers a fairer ground of applying such configurations without significantly changing size and weight criteria.

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The annotated whole-genome sequence of Mycobacterium tuberculosis indicated that Rv1388 (Mtihf) likely encodes a putative 20 kDa integration host factor (mIHF). However, very little is known about the functional properties of mIHF or organization of mycobacterial nucleoid. Molecular modeling of the mIHF three-dimensional structure, based on the cocrystal structure of Streptomyces coelicolor IHF-duplex DNA, a bona fide relative of mIHF, revealed the presence of Arg170, Arg171, and Arg173, which might be involved in DNA binding, and a conserved proline (P150) in the tight turn. The phenotypic sensitivity of Escherichia coli Delta ihfA and Delta ihfB strains to UV and methylmethanesulfonate could be complemented with the wild-type Mtihf, but not its alleles bearing mutations in the DNA-binding residues. Protein DNA interaction assays revealed that wild-type mIHF, but not its DNA-binding variants, bind with high affinity to fragments containing attB and attP sites and curved DNA. Strikingly, the functionally important amino acid residues of mIHF and the mechanism(s) underlying its binding to DNA, DNA bending, and site-specific recombination are fundamentally different from that of E. coli IHF alpha beta. Furthermore, we reveal novel insights into IHF-mediated DNA compaction depending on the placement of its preferred binding sites; mIHF promotes compaction of DNA into nucleoid-like or higher-order filamentous structures. We hence propose that mIHF is a distinct member of a subfamily of proteins that serve as essential cofactors in site-specific recombination and nucleoid organization and that these findings represent a significant advance in our understanding of the role(s) of nucleoid-associated proteins.

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Classical models are not successful in describing discharge characteristics of a lead-acid battery when the current density is varied over a wide range. A model is developed in this work to overcome this lacuna by introducing into the standard models two mechanisms that have not been used earlier. Lead sulfate particles nucleate and grow on active materials of electrodes during discharge, resulting in coverage of active area. Increasing rate of discharge builds supersaturation of lead sulfate rapidly, and causes increased extents of nucleation and coverage. Electrodes behave almost like an insulator due to deposition of lead sulfate when active materials are converted to a critical extent, and this can stop discharge process. Influence of this mechanism is also rate dependent. The new model developed is tested against data on polarization behavior, and capacity drawn as a function of current. The model successfully predicts both polarization curves and Peukert behavior. The model is used to predict charge that can be drawn at a current after partial discharge at a different current. Model suggests that altering nucleation behavior can be useful in enhancing capacity available for discharge. (C) 2015 The Electrochemical Society.

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In this paper, we describe models and algorithms for detection and tracking of group and individual targets. We develop two novel group dynamical models, within a continuous time setting, that aim to mimic behavioural properties of groups. We also describe two possible ways of modeling interactions between closely using Markov Random Field (MRF) and repulsive forces. These can be combined together with a group structure transition model to create realistic evolving group models. We use a Markov Chain Monte Carlo (MCMC)-Particles Algorithm to perform sequential inference. Computer simulations demonstrate the ability of the algorithm to detect and track targets within groups, as well as infer the correct group structure over time. ©2008 IEEE.