40 resultados para Compactification and String Models


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Two algorithms that improve upon the sequent-peak procedure for reservoir capacity calculation are presented. The first incorporates storage-dependent losses (like evaporation losses) exactly as the standard linear programming formulation does. The second extends the first so as to enable designing with less than maximum reliability even when allowable shortfall in any failure year is also specified. Together, the algorithms provide a more accurate, flexible and yet fast method of calculating the storage capacity requirement in preliminary screening and optimization models.

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An analytical study for the static strength of adhesive lap joints is presented. The earlier solutions of Volkersen [i], DeBruyne[2] and others were limited to linear adhesives. The influence of adhesive non-linearity was first considered by Grimes' et al[3] and Dickson et al [4]. Recently Hart-Smith[5] successfully introduced elastic-plastic behaviour of the adhesive. In the present study the problem is formulated for general non-linear adhesive behaviour and an efficient numerical algorithm is written for the solution. Bilinear and trilinear models for the nonlinearity yield closed form analytical solutions.

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Molecular dynamics simulations have been carried out on all the jacalin-carbohydrate complexes of known structure, models of unliganded molecules derived from the complexes and also models of relevant complexes where X-ray structures are not available. Results of the simulations and the available crystal structures involving jacalin permit delineation of the relatively rigid and flexible regions of the molecule and the dynamical variability of the hydrogen bonds involved in stabilizing the structure. Local flexibility appears to be related to solvent accessibility. Hydrogen bonds involving side chains and water bridges involving buried water molecules appear to be important in the stabilization of loop structures. The lectin-carbohydrate interactions observed in crystal structures, the average parameters pertaining to them derived from simulations, energetic contribution of the stacking residue estimated from quantum mechanical calculations, and the scatter of the locations of carbohydrate and carbohydrate-binding residues are consistent with the known thermodynamic parameters of jacalin-carbohydrate interactions. The simulations, along with X-ray results, provide a fuller picture of carbohydrate binding by jacalin than provided by crystallographic analysis alone. The simulations confirm that in the unliganded structures water molecules tend to occupy the positions occupied by carbohydrate oxygens in the lectin-carbohydrate complexes. Population distributions in simulations of the free lectin, the ligands, and the complexes indicate a combination of conformational selection and induced fit. Proteins 2009; 77:760-777.

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In this paper the static noise margin for SET (single electron transistor) logic is defined and compact models for the noise margin are developed by making use of the MIB (Mahapatra-Ionescu-Banerjee) model. The variation of the noise margin with temperature and background charge is also studied. A chain of SET inverters is simulated to validate the definition of various logic levels (like VIH, VOH, etc.) and noise margin. Finally the noise immunity of SET logic is compared with current CMOS logic.

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The first step in the molybdenum cofactor (Moco) biosynthesis pathway involves the conversion of guanosine triphosphate (GTP) to precursor Z by two proteins (MoaA and MoaC). MoaA belongs to the S-adenosylmethioninedependent radical enzyme superfamily and is believed to generate protein and/or substrate radicals by reductive cleavage of S-adenosylmethionine using an Fe-S cluster. MoaC has been suggested to catalyze the release of pyrophosphate and the formation of the cyclic phosphate of precursor Z. However, structural evidence showing the binding of a substrate-like molecule to MoaC is not available. Here, apo and GTP-bound crystal structures of MoaC from Thermus thermophilus HB8 are reported. Furthermore, isothermal titration calorimetry experiments have been carried out in order to obtain thermodynamic parameters for the protein-ligand interactions. In addition, molecular-dynamics (MD) simulations have been carried out on the protein-ligand complex of known structure and on models of relevant complexes for which X-ray structures are not available. The biophysical, structural and MD results reveal the residues that are involved in substrate binding and help in speculating upon a possible mechanism.

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Randomly diluted quantum boson and spin models in two dimensions combine the physics of classical percolation with the well-known dimensionality dependence of ordering in quantum lattice models. This combination is rather subtle for models that order in two dimensions but have no true order in one dimension, as the percolation cluster near threshold is a fractal of dimension between 1 and 2: two experimentally relevant examples are the O(2) quantum rotor and the Heisenberg antiferromagnet. We study two analytic descriptions of the O(2) quantum rotor near the percolation threshold. First a spin-wave expansion is shown to predict long-ranged order, but there are statistically rare points on the cluster that violate the standard assumptions of spin-wave theory. A real-space renormalization group (RSRG) approach is then used to understand how these rare points modify ordering of the O(2) rotor. A new class of fixed points of the RSRG equations for disordered one-dimensional bosons is identified and shown to support the existence of long-range order on the percolation backbone in two dimensions. These results are relevant to experiments on bosons in optical lattices and superconducting arrays, and also (qualitatively) for the diluted Heisenberg antiferromagnet La-2(Zn,Mg)(x)Cu1-xO4.

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This paper reviews integrated economic and ecological models that address impacts and adaptation to climate change in the forest sector. Early economic model studies considered forests as one out of many possible impacts of climate change, while ecological model studies tended to limit the economic impacts to fixed price-assumptions. More recent studies include broader representations of both systems, but there are still few studies which can be regarded fully integrated. Full integration of ecological and economic models is needed to address forest management under climate change appropriately. The conclusion so far is that there are vast uncertainties about how climate change affects forests. This is partly due to the limited knowledge about the global implications of the social and economical adaptation to the effects of climate change on forests.

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Prior work on modeling interconnects has focused on optimizing the wire and repeater design for trading off energy and delay, and is largely based on low level circuit parameters. Hence these models are hard to use directly to make high level microarchitectural trade-offs in the initial exploration phase of a design. In this paper, we propose INTACTE, a tool that can be used by architects toget reasonably accurate interconnect area, delay, and power estimates based on a few architecture level parameters for the interconnect such as length, width (in number of bits), frequency, and latency for a specified technology and voltage. The tool uses well known models of interconnect delay and energy taking into account the wire pitch, repeater size, and spacing for a range of voltages and technologies.It then solves an optimization problem of finding the lowest energy interconnect design in terms of the low level circuit parameters, which meets the architectural constraintsgiven as inputs. In addition, the tool also provides the area, energy, and delay for a range of supply voltages and degrees of pipelining, which can be used for micro-architectural exploration of a chip. The delay and energy models used by the tool have been validated against low level circuit simulations. We discuss several potential applications of the tool and present an example of optimizing interconnect design in the context of clustered VLIW architectures. Copyright 2007 ACM.

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We study the bipartite entanglement of strongly correlated systems using exact diagonalization techniques. In particular, we examine how the entanglement changes in the presence of long-range interactions by studying the Pariser-Parr-Pople model with long-range interactions. We compare the results for this model with those obtained for the Hubbard and Heisenberg models with short-range interactions. This study helps us to understand why the density matrix renormalization group (DMRG) technique is so successful even in the presence of long-range interactions. To better understand the behavior of long-range interactions and why the DMRG works well with it, we study the entanglement spectrum of the ground state and a few excited states of finite chains. We also investigate if the symmetry properties of a state vector have any significance in relation to its entanglement. Finally, we make an interesting observation on the entanglement profiles of different states (across the energy spectrum) in comparison with the corresponding profile of the density of states. We use isotropic chains and a molecule with non-Abelian symmetry for these numerical investigations.

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Epoxy resin bonded mica splitting is the insulation of choice for machine stators. However, this system is seen to be relatively weak under time varying mechanical stress, in particular the vibration causing delamination of mica and deboning of mica from the resin matrix. The situation is accentuated under the combined action of electrical, thermal and mechanical stress. Physical and probabilistic models for failure of such systems have been proposed by one of the authors of this paper earlier. This paper presents a pragmatic accelerated failure data acquisition and analytical paradigm under multi factor coupled stress, Electrical, Thermal. The parameters of the phenomenological model so developed are estimated based on sound statistical treatment of failure data.

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We propose a new paradigm for displaying comments: showing comments alongside parts of the article they correspond to. We evaluate the effectiveness of various approaches for this task and show that a combination of bag of words and topic models performs the best.

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In the design of practical web page classification systems one often encounters a situation in which the labeled training set is created by choosing some examples from each class; but, the class proportions in this set are not the same as those in the test distribution to which the classifier will be actually applied. The problem is made worse when the amount of training data is also small. In this paper we explore and adapt binary SVM methods that make use of unlabeled data from the test distribution, viz., Transductive SVMs (TSVMs) and expectation regularization/constraint (ER/EC) methods to deal with this situation. We empirically show that when the labeled training data is small, TSVM designed using the class ratio tuned by minimizing the loss on the labeled set yields the best performance; its performance is good even when the deviation between the class ratios of the labeled training set and the test set is quite large. When the labeled training data is sufficiently large, an unsupervised Gaussian mixture model can be used to get a very good estimate of the class ratio in the test set; also, when this estimate is used, both TSVM and EC/ER give their best possible performance, with TSVM coming out superior. The ideas in the paper can be easily extended to multi-class SVMs and MaxEnt models.

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Ever increasing energy requirements, environmental concerns and energy security needs are strongly influencing engine researchers to consider renewable biofuels as alternatives to fossil fuels. Spray process being important in IC engine combustion, existing literature on various biofuel sprays is reviewed and summarized. Both experimental and computational research findings are reviewed in a detailed manner for compression ignition (CI) engine sprays and briefly for spark ignition (SI) engine sprays. The physics of basic atomization process of sprays from various injectors is included to highlight the most recent research findings followed by discussion highlighting the effect of physico-chemical properties on spray atomization for both biofuels and fossil fuels. Biodiesel sprays are found to penetrate faster and haw narrow spray plume angle and larger droplet sizes compared to diesel. Results of analytical and computational models are shown to be useful in shedding light on the actual process of atomization. However, further studies on understanding primary atomization and the effect of fuel properties on primary atomization are required. As far as secondary atomization is concerned, changes in regimes are observed to occur at higher air-jet velocities for biodiesel compared to those of diesel. Evaporating sprays revealed that the liquid length is longer for biodiesel. Pure plant oil sprays with potential use in CI engines may require alternative injector technology due to slower breakup as compared to diesel. Application of ethanol to gasoline engines may be feasible without any modifications to port fuel injection (PFI) engines. More studies are required on the application of alternative fuels to high pressure sprays used in Gasoline Direct Injection (GDI) engines.

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Himalayan region is one of the most active seismic regions in the world and many researchers have highlighted the possibility of great seismic event in the near future due to seismic gap. Seismic hazard analysis and microzonation of highly populated places in the region are mandatory in a regional scale. Region specific Ground Motion Predictive Equation (GMPE) is an important input in the seismic hazard analysis for macro- and micro-zonation studies. Few GMPEs developed in India are based on the recorded data and are applicable for a particular range of magnitudes and distances. This paper focuses on the development of a new GMPE for the Himalayan region considering both the recorded and simulated earthquakes of moment magnitude 5.3-8.7. The Finite Fault simulation model has been used for the ground motion simulation considering region specific seismotectonic parameters from the past earthquakes and source models. Simulated acceleration time histories and response spectra are compared with available records. In the absence of a large number of recorded data, simulations have been performed at unavailable locations by adopting Apparent Stations concept. Earthquakes recorded up to 2007 have been used for the development of new GMPE and earthquakes records after 2007 are used to validate new GMPE. Proposed GMPE matched very well with recorded data and also with other highly ranked GMPEs developed elsewhere and applicable for the region. Comparison of response spectra also have shown good agreement with recorded earthquake data. Quantitative analysis of residuals for the proposed GMPE and region specific GMPEs to predict Nepal-India 2011 earthquake of Mw of 5.7 records values shows that the proposed GMPE predicts Peak ground acceleration and spectral acceleration for entire distance and period range with lower percent residual when compared to exiting region specific GMPEs. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.

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The effects of the initial height on the temporal persistence probability of steady-state height fluctuations in up-down symmetric linear models of surface growth are investigated. We study the (1 + 1)-dimensional Family model and the (1 + 1)-and (2 + 1)-dimensional larger curvature (LC) model. Both the Family and LC models have up-down symmetry, so the positive and negative persistence probabilities in the steady state, averaged over all values of the initial height h(0), are equal to each other. However, these two probabilities are not equal if one considers a fixed nonzero value of h(0). Plots of the positive persistence probability for negative initial height versus time exhibit power-law behavior if the magnitude of the initial height is larger than the interface width at saturation. By symmetry, the negative persistence probability for positive initial height also exhibits the same behavior. The persistence exponent that describes this power-law decay decreases as the magnitude of the initial height is increased. The dependence of the persistence probability on the initial height, the system size, and the discrete sampling time is found to exhibit scaling behavior.