204 resultados para level sets


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We present noise measurements of a phase fluorometric oxygen sensor that sets the limits of accuracy for this instrument. We analyze the phase sensitive detection measurement system with the signal ''shot'' noise being the only significant contribution to the system noise. Based on the modulated optical power received by the photomultiplier, the analysis predicts a noise spectral power density that was within 3 dB of the measured power spectral noise density. Our results demonstrate that at a received optical power of 20 fW the noise level was low enough to permit the detection of a change oxygen concentration of 1% at the sensor. We also present noise measurements of a new low-cost version of this instrument that uses a photodiode instead of a photomultiplier. These measurements show that the noise for this instrument was limited by noise generated in the preamplifier following the photodiode. (C) 1996 Society of Photo-Optical Instrumentation Engineers.

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Ligand-induced conformational changes in proteins are of immense functional relevance. It is a major challenge to elucidate the network of amino acids that are responsible for the percolation of ligand-induced conformational changes to distal regions in the protein from a global perspective. Functionally important subtle conformational changes (at the level of side-chain noncovalent interactions) upon ligand binding or as a result of environmental variations are also elusive in conventional studies such as those using root-mean-square deviations (r.m.s.d.s). In this article, the network representation of protein structures and their analyses provides an efficient tool to capture these variations (both drastic and subtle) in atomistic detail in a global milieu. A generalized graph theoretical metric, using network parameters such as cliques and/or communities, is used to determine similarities or differences between structures in a rigorous manner. The ligand-induced global rewiring in the protein structures is also quantified in terms of network parameters. Thus, a judicious use of graph theory in the context of protein structures can provide meaningful insights into global structural reorganizations upon perturbation and can also be helpful for rigorous structural comparison. Data sets for the present study include high-resolution crystal structures of serine proteases from the S1A family and are probed to quantify the ligand-induced subtle structural variations.

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Experimental ionic conductivity of different alkali ions in water shows markedly different dependences on pressure. Existing theories such as that of Hubbard-Onsager are unable to explain these dependences on pressure of the ionic conductivity for all ions. We report molecular dynamics investigation of potassium chloride solution at low dilution in water at several pressures between 1 bar and 2 kbar. Two different potential models have been employed. One of the models successfully reproduces the experimentally observed trend in ionic conductivity of K+ ions in water over the 0.001-2 kbar range. We also propose a theoretical explanation, albeit at a qualitative level, to account for the dependence of ionic conductivity on pressure in terms of the previously studied Levitation Effect. It also provides a microscopic picture in terms of the pore network in liquid water.

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Theoretical studies at the HF and Becke3LYP levels using 6-31G* basis sets were carried out on a series of [n]peristylanes and [n]oxa[n]peristylanes (n = 3-6) to understand their structure and energetics. The structures of the [3]- and [4]peristylanes (1, 2) and their era-derivatives (5, 6) were calculated to have the anticipated high symmetry, C-nv. In contrast, a C-s structure (9) at HF/6-31G* and another (25) at the Becke3LYP/6-31G* level were calculated for the [5]oxa[5]peristylane. The energy difference between them is extremely small even though there are major differences in the structures indicating every soft potential energy surface: On the other hand, the potential energy surface of [6]oxa[6]peristylane is not as soft. Similar structures were also calculated for the top rings. Calculations on the seco-compounds 11-14 and 15-19 (Table 4) indicate that there is no unusual strain involved in the formation of 27 from 19. The Li+ interaction energies of the [n]oxa[n]peristylanes are 61.7 (n = 3), 72.8 (n = 4), 84.2 (n = 5) and 91.7 (n = 6) kcal mol(-1) at the Becke3LYP/6-3IG* level. Dramatic differences between the C-C bond lengths obtained from the solid state X-ray diffraction studies and those from the calculations for the [n]oxa[n]peristylanes were also observed.

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An understanding of application I/O access patterns is useful in several situations. First, gaining insight into what applications are doing with their data at a semantic level helps in designing efficient storage systems. Second, it helps create benchmarks that mimic realistic application behavior closely. Third, it enables autonomic systems as the information obtained can be used to adapt the system in a closed loop.All these use cases require the ability to extract the application-level semantics of I/O operations. Methods such as modifying application code to associate I/O operations with semantic tags are intrusive. It is well known that network file system traces are an important source of information that can be obtained non-intrusively and analyzed either online or offline. These traces are a sequence of primitive file system operations and their parameters. Simple counting, statistical analysis or deterministic search techniques are inadequate for discovering application-level semantics in the general case, because of the inherent variation and noise in realistic traces.In this paper, we describe a trace analysis methodology based on Profile Hidden Markov Models. We show that the methodology has powerful discriminatory capabilities that enable it to recognize applications based on the patterns in the traces, and to mark out regions in a long trace that encapsulate sets of primitive operations that represent higher-level application actions. It is robust enough that it can work around discrepancies between training and target traces such as in length and interleaving with other operations. We demonstrate the feasibility of recognizing patterns based on a small sampling of the trace, enabling faster trace analysis. Preliminary experiments show that the method is capable of learning accurate profile models on live traces in an online setting. We present a detailed evaluation of this methodology in a UNIX environment using NFS traces of selected commonly used applications such as compilations as well as on industrial strength benchmarks such as TPC-C and Postmark, and discuss its capabilities and limitations in the context of the use cases mentioned above.

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We have studied the power spectral density [S(f) = gamma/f(alpha)] of universal conductance fluctuations (UCF's) in heavily doped single crystals of Si, when the scatterers themselves act as the primary source of dephasing. We observed that the scatterers, with internal dynamics like two-level-systems, produce a significant, temperature-dependent reduction in the spectral slope alpha when T less than or similar to 10 K, as compared to the bare 1/f (alphaapproximate to1) spectrum at higher temperatures. It is further shown that an upper cutoff frequency (f(m)) in the UCF spectrum is necessary in order to restrict the magnitude of conductance fluctuations, [(deltaG(phi))(2)], per phase coherent region (L-phi(3)) to [(deltaGphi)(2)](1/2) less than or similar to e(2)/h. We find that f(m) approximate to tau(D)(-1), where tau(D) = L-2/D, is the time scale of the diffusive motion of the electron along the active length (L) of the sample (D is the electron diffusivity).

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Electrical conductivity and thermopower are studied in the conducting polymer polypyrrole doped with varying levels of the dopant hexafluoro phosphate (PF6). A single sample is prepared by galvanostatic electrochemical polymerization at -40 degreesC. From this sample, six samples having different dopant levels and correspondingly different conductivity are prepared by dedoping. Low temperature d.c. electrical conductivity measurement shows the metal-insulator transition from fully doped sample to dedoped samples. On the metallic side the data are fitted to the localization-interaction model. In critical regime, it follows the power law. On the insulating side, it is variable range hopping. Thermopower measurements are done in the temperature range 300 K to 20 K. Thermopower is linear for samples on the metallic side and becomes more and more non-linear on the insulating side. It is described using a combination of the linear metallic term and the non-linear hopping term. (C) 2002 Elsevier Science B.V. All rights reserved.

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This paper reports ab intio, DFT and transition state theory (TST) calculations on HF, HCI and CIF elimination reactions from CH2Cl-CH2F molecule. Both the ground state and the transition state for HX elimination reactions have been optimized at HF, MP2 and DFT calculations with 6-31G*, 6-31G** and 6-311++G** basis sets. In addition, CCSD(T) single point calculations were carried out with MP2/6-311++G** optimized geometry for more accurate determination of the energies of the minima and transition state, compared to the other methods employed here. Classical barriers are converted to Arrhenius activation energy by TST calculations for comparisons with experimental results. The pre-exponential factors, A, calculated at all levels of theory are significantly larger than the experimental values. For activation energy, E-a DFT gives good results for HF elimination, within 4-8 W mol(-1) from experimental values. None of the methods employed, including CCSD(T), give comparable results for HCI elimination reactions. However, rate constants calculated by CCSD(T) method are in very good agreement with experiment for HCI elimination and they are in reasonable agreement for HF elimination reactions. Due to the strong correlation between A and E., the rate constants could be fit to a lower A and E-a (as given by experimental fitting, corresponding to a tight TS) or to larger A and E-a (as given by high level ab initio calculations, corresponding to a loose TS). The barrier for CIF elimination is determined to be 607 U mol(-1) at HF level and it is unlikely to be important for CH2FCH2Cl. Results for other CH2X-CH2Y (X,Y = F/Cl) are included for comparison.

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We address the problem of allocating a single divisible good to a number of agents. The agents have concave valuation functions parameterized by a scalar type. The agents report only the type. The goal is to find allocatively efficient, strategy proof, nearly budget balanced mechanisms within the Groves class. Near budget balance is attained by returning as much of the received payments as rebates to agents. Two performance criteria are of interest: the maximum ratio of budget surplus to efficient surplus, and the expected budget surplus, within the class of linear rebate functions. The goal is to minimize them. Assuming that the valuation functions are known, we show that both problems reduce to convex optimization problems, where the convex constraint sets are characterized by a continuum of half-plane constraints parameterized by the vector of reported types. We then propose a randomized relaxation of these problems by sampling constraints. The relaxed problem is a linear programming problem (LP). We then identify the number of samples needed for ``near-feasibility'' of the relaxed constraint set. Under some conditions on the valuation function, we show that value of the approximate LP is close to the optimal value. Simulation results show significant improvements of our proposed method over the Vickrey-Clarke-Groves (VCG) mechanism without rebates. In the special case of indivisible goods, the mechanisms in this paper fall back to those proposed by Moulin, by Guo and Conitzer, and by Gujar and Narahari, without any need for randomization. Extension of the proposed mechanisms to situations when the valuation functions are not known to the central planner are also discussed. Note to Practitioners-Our results will be useful in all resource allocation problems that involve gathering of information privately held by strategic users, where the utilities are any concave function of the allocations, and where the resource planner is not interested in maximizing revenue, but in efficient sharing of the resource. Such situations arise quite often in fair sharing of internet resources, fair sharing of funds across departments within the same parent organization, auctioning of public goods, etc. We study methods to achieve near budget balance by first collecting payments according to the celebrated VCG mechanism, and then returning as much of the collected money as rebates. Our focus on linear rebate functions allows for easy implementation. The resulting convex optimization problem is solved via relaxation to a randomized linear programming problem, for which several efficient solvers exist. This relaxation is enabled by constraint sampling. Keeping practitioners in mind, we identify the number of samples that assures a desired level of ``near-feasibility'' with the desired confidence level. Our methodology will occasionally require subsidy from outside the system. We however demonstrate via simulation that, if the mechanism is repeated several times over independent instances, then past surplus can support the subsidy requirements. We also extend our results to situations where the strategic users' utility functions are not known to the allocating entity, a common situation in the context of internet users and other problems.

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In data mining, an important goal is to generate an abstraction of the data. Such an abstraction helps in reducing the space and search time requirements of the overall decision making process. Further, it is important that the abstraction is generated from the data with a small number of disk scans. We propose a novel data structure, pattern count tree (PC-tree), that can be built by scanning the database only once. PC-tree is a minimal size complete representation of the data and it can be used to represent dynamic databases with the help of knowledge that is either static or changing. We show that further compactness can be achieved by constructing the PC-tree on segmented patterns. We exploit the flexibility offered by rough sets to realize a rough PC-tree and use it for efficient and effective rough classification. To be consistent with the sizes of the branches of the PC-tree, we use upper and lower approximations of feature sets in a manner different from the conventional rough set theory. We conducted experiments using the proposed classification scheme on a large-scale hand-written digit data set. We use the experimental results to establish the efficacy of the proposed approach. (C) 2002 Elsevier Science B.V. All rights reserved.

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A multilevel inverter topology for seven-level space vector generation is proposed in this paper. In this topology, the seven-level structure is realized using two conventional two-level inverters and six capacitor-fed H-bridge cells. It needs only two isolated dc-voltage sources of voltage rating V(dc)/2 where V(dc) is the dc voltage magnitude required by the conventional neutral point clamped (NPC) seven-level topology. The proposed topology is capable of maintaining the H-bridge capacitor voltages at the required level of V(dc)/6 under all operating conditions, covering the entire linear modulation and overmodulation regions, by making use of the switching state redundancies. In the event of any switch failure in H-bridges, this inverter can operate in three-level mode, a feature that enhances the reliability of the drive system. The two-level inverters, which operate at a higher voltage level of V(dc)/2, switch less compared to the H-bridges, which operate at a lower voltage level of V(dc)/6, resulting in switching loss reduction. The experimental verification of the proposed topology is carried out for the entire modulation range, under steady state as well as transient conditions.

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We observe linewidths below the natural linewidth for a probe laser on a degenerate two-level F -> F' transition, when the same transition is driven by a strong control laser. We take advantage of the fact that each level of the transition is made of multiple magnetic sublevels, and use the phenomenon of electromagnetically induced transparency (EIT) or absorption ( EIA) in multilevel systems. Optical pumping by the control laser redistributes the population so that only a few sublevels contribute to the probe absorption, an explanation which is verified by a density-matrix analysis of the relevant sublevels. We observe more than a factor of 3 reduction in linewidth in the D(2) line of Rb in room-temperature vapor. Such subnatural features vastly increase the scope of applications of EIT, such as high-resolution spectroscopy and tighter locking of lasers to atomic transitions, since it is not always possible to find a suitable third level. (C) 2011 Elsevier B.V. All rights reserved.

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Efficiency of organic photovoltaic cells based on organic electron donor/organic electron acceptor junctions can be strongly improved when the transparent conductive Anode is coated with a Buffer Layer (ABL). Here, the effects of a metal (gold) or oxide (molybdenum oxide) ABL are reported, as a function of the Highest Occupied Molecular Orbital (HOMO) of different electron donors. The results indicate that a good matching between the work function of the anode and the highest occupied molecular orbital of the donor material is the major factor limiting the hole transfer efficiency. Indeed, gold is efficient as ABL only when the HOMO of the organic donor is close to its work function Phi(Au). Therefore we show that the MoO(3) oxide has a wider field of application as ABL than gold. (C) 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim