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Sample records for denatured state ensemble

  1. Protein folding by distributed computing and the denatured state ensemble.

    Science.gov (United States)

    Marianayagam, Neelan J; Fawzi, Nicolas L; Head-Gordon, Teresa

    2005-11-15

    The distributed computing (DC) paradigm in conjunction with the folding@home (FH) client server has been used to study the folding kinetics of small peptides and proteins, giving excellent agreement with experimentally measured folding rates, although pathways sampled in these simulations are not always consistent with the folding mechanism. In this study, we use a coarse-grain model of protein L, whose two-state kinetics have been characterized in detail by using long-time equilibrium simulations, to rigorously test a FH protocol using approximately 10,000 short-time, uncoupled folding simulations starting from an extended state of the protein. We show that the FH results give non-Poisson distributions and early folding events that are unphysical, whereas longer folding events experience a correct barrier to folding but are not representative of the equilibrium folding ensemble. Using short-time, uncoupled folding simulations started from an equilibrated denatured state ensemble (DSE), we also do not get agreement with the equilibrium two-state kinetics because of overrepresented folding events arising from higher energy subpopulations in the DSE. The DC approach using uncoupled short trajectories can make contact with traditionally measured experimental rates and folding mechanism when starting from an equilibrated DSE, when the simulation time is long enough to sample the lowest energy states of the unfolded basin and the simulated free-energy surface is correct. However, the DC paradigm, together with faster time-resolved and single-molecule experiments, can also reveal the breakdown in the two-state approximation due to observation of folding events from higher energy subpopulations in the DSE.

  2. Manifestations of native topology in the denatured state ensemble of Rhodopseudomonas palustris cytochrome c'.

    Science.gov (United States)

    Dar, Tanveer A; Schaeffer, R Dustin; Daggett, Valerie; Bowler, Bruce E

    2011-02-15

    To provide insight into the role of local sequence in the nonrandom coil behavior of the denatured state, we have extended our measurements of histidine-heme loop formation equilibria for cytochrome c' to 6 M guanidine hydrochloride. We observe that there is some reduction in the scatter about the best fit line of loop stability versus loop size data in 6 M versus 3 M guanidine hydrochloride, but the scatter is not eliminated. The scaling exponent, ν(3), of 2.5 ± 0.2 is also similar to that found previously in 3 M guanidine hydrochloride (2.6 ± 0.3). Rates of histidine-heme loop breakage in the denatured state of cytochrome c' show that some histidine-heme loops are significantly more persistent than others at both 3 and 6 M guanidine hydrochloride. Rates of histidine-heme loop formation more closely approximate random coil behavior. This observation indicates that heterogeneity in the denatured state ensemble results mainly from contact persistence. When mapped onto the structure of cytochrome c', the histidine-heme loops with slow breakage rates coincide with chain reversals between helices 1 and 2 and between helices 2 and 3. Molecular dynamics simulations of the unfolding of cytochrome c' at 498 K show that these reverse turns persist in the unfolded state. Thus, these portions of the primary structure of cytochrome c' set up the topology of cytochrome c' in the denatured state, predisposing the protein to fold efficiently to its native structure.

  3. Urea denatured state ensembles contain extensive secondary structure that is increased in hydrophobic proteins

    Science.gov (United States)

    Nick Pace, C; Huyghues-Despointes, Beatrice M P; Fu, Hailong; Takano, Kazufumi; Scholtz, J Martin; Grimsley, Gerald R

    2010-01-01

    The goal of this article is to gain a better understanding of the denatured state ensemble (DSE) of proteins through an experimental and computational study of their denaturation by urea. Proteins unfold to different extents in urea and the most hydrophobic proteins have the most compact DSE and contain almost as much secondary structure as folded proteins. Proteins that unfold to the greatest extent near pH 7 still contain substantial amounts of secondary structure. At low pH, the DSE expands due to charge–charge interactions and when the net charge per residue is high, most of the secondary structure is disrupted. The proteins in the DSE appear to contain substantial amounts of polyproline II conformation at high urea concentrations. In all cases considered, including staph nuclease, the extent of unfolding by urea can be accounted for using the data and approach developed in the laboratory of Wayne Bolen (Auton et al., Proc Natl Acad Sci 2007; 104:15317–15323). PMID:20198681

  4. Statistical mechanics of the denatured state of a protein using replica-averaged metadynamics.

    Science.gov (United States)

    Camilloni, Carlo; Vendruscolo, Michele

    2014-06-25

    The characterization of denatured states of proteins is challenging because the lack of permanent structure in these states makes it difficult to apply to them standard methods of structural biology. In this work we use all-atom replica-averaged metadynamics (RAM) simulations with NMR chemical shift restraints to determine an ensemble of structures representing an acid-denatured state of the 86-residue protein ACBP. This approach has enabled us to reach convergence in the free energy landscape calculations, obtaining an ensemble of structures in relatively accurate agreement with independent experimental data used for validation. By observing at atomistic resolution the transient formation of native and non-native structures in this acid-denatured state of ACBP, we rationalize the effects of single-point mutations on the folding rate, stability, and transition-state structures of this protein, thus characterizing the role of the unfolded state in determining the folding process.

  5. Urea-temperature phase diagrams capture the thermodynamics of denatured state expansion that accompany protein unfolding.

    Science.gov (United States)

    Tischer, Alexander; Auton, Matthew

    2013-09-01

    We have analyzed the thermodynamic properties of the von Willebrand factor (VWF) A3 domain using urea-induced unfolding at variable temperature and thermal unfolding at variable urea concentrations to generate a phase diagram that quantitatively describes the equilibrium between native and denatured states. From this analysis, we were able to determine consistent thermodynamic parameters with various spectroscopic and calorimetric methods that define the urea-temperature parameter plane from cold denaturation to heat denaturation. Urea and thermal denaturation are experimentally reversible and independent of the thermal scan rate indicating that all transitions are at equilibrium and the van't Hoff and calorimetric enthalpies obtained from analysis of individual thermal transitions are equivalent demonstrating two-state character. Global analysis of the urea-temperature phase diagram results in a significantly higher enthalpy of unfolding than obtained from analysis of individual thermal transitions and significant cross correlations describing the urea dependence of ΔH0 and ΔCP0 that define a complex temperature dependence of the m-value. Circular dichroism (CD) spectroscopy illustrates a large increase in secondary structure content of the urea-denatured state as temperature increases and a loss of secondary structure in the thermally denatured state upon addition of urea. These structural changes in the denatured ensemble make up ∼40% of the total ellipticity change indicating a highly compact thermally denatured state. The difference between the thermodynamic parameters obtained from phase diagram analysis and those obtained from analysis of individual thermal transitions illustrates that phase diagrams capture both contributions to unfolding and denatured state expansion and by comparison are able to decipher these contributions.

  6. Denatured-state energy landscapes of a protein structural database reveal the energetic determinants of a framework model for folding.

    Science.gov (United States)

    Wang, Suwei; Gu, Jenny; Larson, Scott A; Whitten, Steven T; Hilser, Vincent J

    2008-09-19

    Position-specific denatured-state thermodynamics were determined for a database of human proteins by use of an ensemble-based model of protein structure. The results of modeling denatured protein in this manner reveal important sequence-dependent thermodynamic properties in the denatured ensembles as well as fundamental differences between the denatured and native ensembles in overall thermodynamic character. The generality and robustness of these results were validated by performing fold-recognition experiments, whereby sequences were matched with their respective folds based on amino acid propensities for the different energetic environments in the protein, as determined through cluster analysis. Correlation analysis between structure and energetic information revealed that sequence segments destined for beta-sheet in the final native fold are energetically more predisposed to a broader repertoire of states than are sequence segments destined for alpha-helix. These results suggest that within the subensemble of mostly unstructured states, the energy landscapes are dominated by states in which parts of helices adopt structure, whereas structure formation for sequences destined for beta-strand is far less probable. These results support a framework model of folding, which suggests that, in general, the denatured state has evolutionarily evolved to avoid low-energy conformations in sequences that ultimately adopt beta-strand. Instead, the denatured state evolved so that sequence segments that ultimately adopt alpha-helix and coil will have a high intrinsic structure formation capability, thus serving as potential nucleation sites.

  7. Formation of Native and Non-native Interactions in Ensembles of Denatured ACBP Molecules from Paramagnetic Relaxation Enhancement Studies

    DEFF Research Database (Denmark)

    Kristjansdottir, S.; Lindorff-Larsen, Kresten; Fieber, W.;

    2005-01-01

    in the denatured states with those in the transition state for folding we also provided new insights into the mechanism of formation of the native state of this protein. Keywords: protein folding; denatured state; NMR; molecular dynamics; structural studies Abbreviations: ACBP, acyl coenzyme A binding protein; Gu...... of the residual structure in the denatured state of ACBP under these different conditions has enabled us to infer that regions in the N and C-terminal parts of the protein sequence have a high tendency to interact in the unfolded state under physiological conditions. By comparing the structural features...

  8. Protein's native state stability in a chemically induced denaturation mechanism.

    Science.gov (United States)

    Olivares-Quiroz, L; Garcia-Colin, L S

    2007-05-21

    In this work, we present a generalization of Zwanzig's protein unfolding analysis [Zwanzig, R., 1997. Two-state models of protein folding kinetics. Proc. Natl Acad. Sci. USA 94, 148-150; Zwanzig, R., 1995. Simple model of protein folding kinetics. Proc. Natl Acad. Sci. USA 92, 9801], in order to calculate the free energy change Delta(N)(D)F between the protein's native state N and its unfolded state D in a chemically induced denaturation. This Extended Zwanzig Model (EZM) is both based on an equilibrium statistical mechanics approach and the inclusion of experimental denaturation curves. It enables us to construct a suitable partition function Z and to derive an analytical formula for Delta(N)(D)F in terms of the number K of residues of the macromolecule, the average number nu of accessible states for each single amino acid and the concentration C(1/2) where the midpoint of the ND transition occurs. The results of the EZM for proteins where chemical denaturation follows a sigmoidal-type profile, as it occurs for the case of the T70N human variant of lysozyme (PDB code: T70N) [Esposito, G., et al., 2003. J. Biol. Chem. 278, 25910-25918], can be splitted into two lines. First, EZM shows that for sigmoidal denaturation profiles, the internal degrees of freedom of the chain play an outstanding role in the stability of the native state. On the other hand, that under certain conditions DeltaF can be written as a quadratic polynomial on concentration C(1/2), i.e., DeltaF approximately aC(1/2)(2)+bC(1/2)+c, where a,b,c are constant coefficients directly linked to protein's size K and the averaged number of non-native conformations nu. Such functional form for DeltaF has been widely known to fit experimental measures in chemically induced protein denaturation [Yagi, M., et al., 2003. J. Biol. Chem. 278, 47009-47015; Asgeirsson, B., Guojonsdottir, K., 2006. Biochim. Biophys. Acta 1764, 190-198; Sharma, S., et al., 2006. Protein Pept. Lett. 13(4), 323-329; Salem, M., et al

  9. Increasing protein stability: Importance of ΔCp and the denatured state

    Science.gov (United States)

    Fu, Hailong; Grimsley, Gerald; Scholtz, J Martin; Pace, C Nick

    2010-01-01

    Increasing the conformational stability of proteins is an important goal for both basic research and industrial applications. In vitro selection has been used successfully to increase protein stability, but more often site-directed mutagenesis is used to optimize the various forces that contribute to protein stability. In previous studies, we showed that improving electrostatic interactions on the protein surface and improving the β-turn sequences were good general strategies for increasing protein stability, and used them to increase the stability of RNase Sa. By incorporating seven of these mutations in RNase Sa, we increased the stability by 5.3 kcal/mol. Adding one more mutation, D79F, gave a total increase in stability of 7.7 kcal/mol, and a melting temperature 28°C higher than the wild-type enzyme. Surprisingly, the D79F mutation lowers the change in heat capacity for folding, ΔCp, by 0.6 kcal/mol/K. This suggests that this mutation stabilizes structure in the denatured state ensemble. We made other mutants that give some insight into the structure present in the denatured state. Finally, the thermodynamics of folding of these stabilized variants of RNase Sa are compared with those observed for proteins from thermophiles. PMID:20340133

  10. Influence of denatured and intermediate states of folding on protein aggregation.

    Science.gov (United States)

    Fawzi, Nicolas L; Chubukov, Victor; Clark, Louis A; Brown, Scott; Head-Gordon, Teresa

    2005-04-01

    We simulate the aggregation thermodynamics and kinetics of proteins L and G, each of which self-assembles to the same alpha/beta [corrected] topology through distinct folding mechanisms. We find that the aggregation kinetics of both proteins at an experimentally relevant concentration exhibit both fast and slow aggregation pathways, although a greater proportion of protein G aggregation events are slow relative to those of found for protein L. These kinetic differences are correlated with the amount and distribution of intrachain contacts formed in the denatured state ensemble (DSE), or an intermediate state ensemble (ISE) if it exists, as well as the folding timescales of the two proteins. Protein G aggregates more slowly than protein L due to its rapidly formed folding intermediate, which exhibits native intrachain contacts spread across the protein, suggesting that certain early folding intermediates may be selected for by evolution due to their protective role against unwanted aggregation. Protein L shows only localized native structure in the DSE with timescales of folding that are commensurate with the aggregation timescale, leaving it vulnerable to domain swapping or nonnative interactions with other chains that increase the aggregation rate. Folding experiments that characterize the structural signatures of the DSE, ISE, or the transition state ensemble (TSE) under nonaggregating conditions should be able to predict regions where interchain contacts will be made in the aggregate, and to predict slower aggregation rates for proteins with contacts that are dispersed across the fold. Since proteins L and G can both form amyloid fibrils, this work also provides mechanistic and structural insight into the formation of prefibrillar species.

  11. Entanglement in a Solid State Spin Ensemble

    CERN Document Server

    Simmons, Stephanie; Riemann, Helge; Abrosimov, Nikolai V; Becker, Peter; Pohl, Hans-Joachim; Thewalt, Mike L W; Itoh, Kohei M; Morton, John J L

    2010-01-01

    Entanglement is the quintessential quantum phenomenon and a necessary ingredient in most emerging quantum technologies, including quantum repeaters, quantum information processing (QIP) and the strongest forms of quantum cryptography. Spin ensembles, such as those in liquid state nuclear magnetic resonance, have been powerful in the development of quantum control methods, however, these demonstrations contained no entanglement and ultimately constitute classical simulations of quantum algorithms. Here we report the on-demand generation of entanglement between an ensemble of electron and nuclear spins in isotopically engineered phosphorus-doped silicon. We combined high field/low temperature electron spin resonance (3.4 T, 2.9 K) with hyperpolarisation of the 31P nuclear spin to obtain an initial state of sufficient purity to create a non-classical, inseparable state. The state was verified using density matrix tomography based on geometric phase gates, and had a fidelity of 98% compared with the ideal state a...

  12. Dynamical ensembles in stationary states

    Energy Technology Data Exchange (ETDEWEB)

    Gallavotti, G. [Universita di Roma la Sapienza, Rome (Italy); Cohen, E.G.D. [Rockefeller Univ., New York, NY (United States)

    1995-09-01

    We propose, as a generalization of an idea of Ruelle`s to describe turbulent fluid flow, a chaotic hypothesis for reversible dissipative many-particle systems in nonequilibrium stationary states in general. This implies an extension of the zeroth law of thermodynamics to nonequilibrium states and it leads to the identification of a unique distribution {mu} describing the asymptotic properties of the time evolution of the system for initial data randomly chosen with respect to a uniform distribution on phase space. For conservative systems in thermal equilibrium the chaotic hypothesis implies the ergodic hypothesis. We outline a procedure to obtain the distribution {mu}: it leads to a new unifying point of view for the phase space behavior of dissipative and conservative systems. The chaotic hypothesis is confirmed in a nontrivial, parameter-free, way by a recent computer experiment on the entropy production fluctuations in a shearing fluid far from equilibrium. Similar applications to other models are proposed, in particular to a model for the Kolmogorov-Obuchov theory for turbulent flow.

  13. Stabilizing Effect of Various Polyols on the Native and the Denatured States of Glucoamylase

    Directory of Open Access Journals (Sweden)

    Mohammed Suleiman Zaroog

    2013-01-01

    Full Text Available Different spectral probes were employed to study the stabilizing effect of various polyols, such as, ethylene glycol (EG, glycerol (GLY, glucose (GLC and trehalose (TRE on the native (N, the acid-denatured (AD and the thermal-denatured (TD states of Aspergillus niger glucoamylase (GA. Polyols induced both secondary and tertiary structural changes in the AD state of enzyme as reflected from altered circular dichroism (CD, tryptophan (Trp, and 1-anilinonaphthalene-8-sulfonic acid (ANS fluorescence characteristics. Thermodynamic analysis of the thermal denaturation curve of native GA suggested significant increase in enzyme stability in the presence of GLC, TRE, and GLY (in decreasing order while EG destabilized it. Furthermore, CD and fluorescence characteristics of the TD state at 71°C in the presence of polyols showed greater effectiveness of both GLC and TRE in inducing native-like secondary and tertiary structures compared to GLY and EG.

  14. Exact ensemble density-functional theory for excited states

    CERN Document Server

    Yang, Zeng-hui; Pribram-Jones, Aurora; Burke, Kieron; Needs, Richard J; Ullrich, Carsten A

    2014-01-01

    We construct exact Kohn-Sham potentials for the ensemble density-functional theory (EDFT) of excited states from the ground and excited states of helium. The exchange-correlation potential is compared with current approximations, which miss prominent features. The ensemble derivative discontinuity is tested, and the virial theorem is proven and illustrated.

  15. AFM visualization at a single-molecule level of denaturated states of proteins on graphite.

    Science.gov (United States)

    Barinov, Nikolay A; Prokhorov, Valery V; Dubrovin, Evgeniy V; Klinov, Dmitry V

    2016-10-01

    Different graphitic materials are either already used or believed to be advantageous in biomedical and biotechnological applications, e.g., as biomaterials or substrates for sensors. Most of these applications or associated important issues, such as biocompatibility, address the problem of adsorption of protein molecules and, in particular the conformational state of the adsorbed protein molecule on graphite. High-resolution AFM demonstrates highly oriented pyrolytic graphite (HOPG) induced denaturation of four proteins of blood plasma, such as ferritin, fibrinogen, human serum albumin (HSA) and immunoglobulin G (IgG), at a single molecule level. Protein denaturation is accompanied by the decrease of the heights of protein globules and spreading of the denatured protein fraction on the surface. In contrast, the modification of HOPG with the amphiphilic oligoglycine-hydrocarbon derivative monolayer preserves the native-like conformation and provides even more mild conditions for the protein adsorption than typically used mica. Protein unfolding on HOPG may have universal character for "soft" globular proteins. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Two conformational states in D-shaped DNA: Effects of local denaturation

    Science.gov (United States)

    Lee, O.-Chul; Kim, Cheolhee; Kim, Jae-Yeol; Lee, Nam Ki; Sung, Wokyung

    2016-06-01

    The bending of double-stranded(ds) DNA on the nano-meter scale plays a key role in many cellular processes such as nucleosome packing, transcription-control, and viral-genome packing. In our recent study, a nanometer-sized dsDNA bent into a D shape was formed by hybridizing a circular single-stranded(ss) DNA and a complementary linear ssDNA. Our fluorescence resonance energy transfer (FRET) measurement of D-DNA revealed two types of conformational states: a less-bent state and a kinked state, which can transform into each other. To understand the origin of the two deformed states of D-DNA, here we study the presence of open base-pairs in the ds portion by using the breathing-DNA model to simulate the system. We provide strong evidence that the two states are due to the emergence of local denaturation, i.e., a bubble in the middle and two forks at ends of the dsDNA portion. We also study the system analytically and find that the free-energy landscape is bistable with two minima representative of the two states. The kink and fork sizes estimated by the analytical calculation are also in excellent agreement with the results of the simulation. Thus, this combined experimental-simulation-analytical study corroborates that highly bent D-DNA reduces bending stress via local denaturation.

  17. Generation of Exotic Quantum States of a Cold Atomic Ensemble

    DEFF Research Database (Denmark)

    Christensen, Stefan Lund

    . Furthermore, the nonclassical properties of the created state is inferred through the use of atomic quadrature quasi-probability distributions. The second generated state is a collective-single-excitation state — the atomic equivalent of a single photon. This state is created by the detection of a heralding......Over the last decades quantum effects have become more and more controllable, leading to the implementations of various quantum information protocols. These protocols are all based on utilizing quantum correlation. In this thesis we consider how states of an atomic ensemble with such correlations...... can be created and characterized. First we consider a spin-squeezed state. This state is generated by performing quantum non-demolition measurements of the atomic population difference. We show a spectroscopically relevant noise reduction of -1.7dB, the ensemble is in a many-body entangled state...

  18. Probabilistic Determination of Native State Ensembles of Proteins

    DEFF Research Database (Denmark)

    Olsson, Simon; Vögeli, Beat Rolf; Cavalli, Andrea

    2014-01-01

    The motions of biological macromolecules are tightly coupled to their functions. However, while the study of fast motions has become increasingly feasible in recent years, the study of slower, biologically important motions remains difficult. Here, we present a method to construct native state...... ensembles of proteins by the combination of physical force fields and experimental data through modern statistical methodology. As an example, we use NMR residual dipolar couplings to determine a native state ensemble of the extensively studied third immunoglobulin binding domain of protein G (GB3...

  19. Ultrafast folding of WW domains without structured aromatic clusters in the denatured state.

    Science.gov (United States)

    Ferguson, N; Johnson, C M; Macias, M; Oschkinat, H; Fersht, A

    2001-11-06

    Ultrafast-folding proteins are important for combining experiment and simulation to give complete descriptions of folding pathways. The WW domain family comprises small proteins with a three-stranded antiparallel beta-sheet topology. Previous studies on the 57-residue YAP 65 WW domain indicate the presence of residual structure in the chemically denatured state. Here we analyze three minimal core WW domains of 38-44 residues. There was little spectroscopic or thermodynamic evidence for residual structure in either their chemically or thermally denatured states. Folding and unfolding kinetics, studied by using rapid temperature-jump and continuous-flow techniques, show that each domain folds and unfolds very rapidly in a two-state transition through a highly compact transition state. Folding half-times were as short as 17 micros at 25 degrees C, within an order of magnitude of the predicted maximal rate of loop formation. The small size and topological simplicity of these domains, in conjunction with their very rapid two-state folding, may allow us to reduce the difference in time scale between experiment and theoretical simulation.

  20. Generation of Exotic Quantum States of a Cold Atomic Ensemble

    DEFF Research Database (Denmark)

    Christensen, Stefan Lund

    Over the last decades quantum effects have become more and more controllable, leading to the implementations of various quantum information protocols. These protocols are all based on utilizing quantum correlation. In this thesis we consider how states of an atomic ensemble with such correlations...... — a nanofiber based light-atom interface. Using a dual-frequency probing method we measure and prepare an ensemble with a sub-Poissonian atom number distribution. This is a first step towards the implementation of more exotic quantum states.......Over the last decades quantum effects have become more and more controllable, leading to the implementations of various quantum information protocols. These protocols are all based on utilizing quantum correlation. In this thesis we consider how states of an atomic ensemble with such correlations...... can be created and characterized. First we consider a spin-squeezed state. This state is generated by performing quantum non-demolition measurements of the atomic population difference. We show a spectroscopically relevant noise reduction of -1.7dB, the ensemble is in a many-body entangled state...

  1. Probabilistic Determination of Native State Ensembles of Proteins.

    Science.gov (United States)

    Olsson, Simon; Vögeli, Beat Rolf; Cavalli, Andrea; Boomsma, Wouter; Ferkinghoff-Borg, Jesper; Lindorff-Larsen, Kresten; Hamelryck, Thomas

    2014-08-12

    The motions of biological macromolecules are tightly coupled to their functions. However, while the study of fast motions has become increasingly feasible in recent years, the study of slower, biologically important motions remains difficult. Here, we present a method to construct native state ensembles of proteins by the combination of physical force fields and experimental data through modern statistical methodology. As an example, we use NMR residual dipolar couplings to determine a native state ensemble of the extensively studied third immunoglobulin binding domain of protein G (GB3). The ensemble accurately describes both local and nonlocal backbone fluctuations as judged by its reproduction of complementary experimental data. While it is difficult to assess precise time-scales of the observed motions, our results suggest that it is possible to construct realistic conformational ensembles of biomolecules very efficiently. The approach may allow for a dramatic reduction in the computational as well as experimental resources needed to obtain accurate conformational ensembles of biological macromolecules in a statistically sound manner.

  2. Adiabatically deformed ensemble: Engineering nonthermal states of matter

    Science.gov (United States)

    Kennes, D. M.

    2017-07-01

    We propose a route towards engineering nonthermal states of matter, which show largely unexplored physics. The main idea relies on the adiabatic passage of a thermal ensemble under slow variations of the system Hamiltonian. If the temperature of the initial thermal ensemble is either zero or infinite, the ensemble after the passage is a simple thermal one with the same vanishing or infinite temperature. However, for any finite nonzero temperature, intriguing nonthermal ensembles can be achieved. We exemplify this in (a) a single oscillator, (b) a dimerized interacting one-dimensional chain of spinless fermions, (c) a BCS-type superconductor, and (d) the topological Kitaev chain. We solve these models with a combination of methods: either exactly, numerically using the density matrix renormalization group, or within an approximate functional renormalization group scheme. The designed states show strongly nonthermal behavior in each of the considered models. For example, for the chain of spinless fermions we exemplify how long-ranged nonthermal power-law correlations can be stabilized, and for the Kitaev chain we elucidate how the nonthermal ensemble can largely alter the transition temperature separating topological and trivial phases.

  3. A model for luminescence of localized state ensemble

    OpenAIRE

    Li, Q.; Xu, S. J.; Xie, M H; Tong, S. Y.

    2004-01-01

    A distribution function for localized carriers, $f(E,T)=\\frac{1}{e^{(E-E_a)/k_BT}+\\tau_{tr}/\\tau_r}$, is proposed by solving a rate equation, in which, electrical carriers' generation, thermal escape, recapture and radiative recombination are taken into account. Based on this distribution function, a model is developed for luminescence from localized state ensemble with a Gaussian-type density of states. The model reproduces quantitatively all the anomalous temperature behaviors of localized ...

  4. Consistent View of Polypeptide Chain Expansion in Chemical Denaturants from Multiple Experimental Methods.

    Science.gov (United States)

    Borgia, Alessandro; Zheng, Wenwei; Buholzer, Karin; Borgia, Madeleine B; Schüler, Anja; Hofmann, Hagen; Soranno, Andrea; Nettels, Daniel; Gast, Klaus; Grishaev, Alexander; Best, Robert B; Schuler, Benjamin

    2016-09-14

    There has been a long-standing controversy regarding the effect of chemical denaturants on the dimensions of unfolded and intrinsically disordered proteins: A wide range of experimental techniques suggest that polypeptide chains expand with increasing denaturant concentration, but several studies using small-angle X-ray scattering (SAXS) have reported no such increase of the radius of gyration (Rg). This inconsistency challenges our current understanding of the mechanism of chemical denaturants, which are widely employed to investigate protein folding and stability. Here, we use a combination of single-molecule Förster resonance energy transfer (FRET), SAXS, dynamic light scattering (DLS), and two-focus fluorescence correlation spectroscopy (2f-FCS) to characterize the denaturant dependence of the unfolded state of the spectrin domain R17 and the intrinsically disordered protein ACTR in two different denaturants. Standard analysis of the primary data clearly indicates an expansion of the unfolded state with increasing denaturant concentration irrespective of the protein, denaturant, or experimental method used. This is the first case in which SAXS and FRET have yielded even qualitatively consistent results regarding expansion in denaturant when applied to the same proteins. To more directly illustrate this self-consistency, we used both SAXS and FRET data in a Bayesian procedure to refine structural ensembles representative of the observed unfolded state. This analysis demonstrates that both of these experimental probes are compatible with a common ensemble of protein configurations for each denaturant concentration. Furthermore, the resulting ensembles reproduce the trend of increasing hydrodynamic radius with denaturant concentration obtained by 2f-FCS and DLS. We were thus able to reconcile the results from all four experimental techniques quantitatively, to obtain a comprehensive structural picture of denaturant-induced unfolded state expansion, and to

  5. Ensembles of physical states and random quantum circuits on graphs

    CERN Document Server

    Hamma, Alioscia; Zanardi, Paolo

    2012-01-01

    In this paper we continue and extend the investigations of the ensembles of random physical states introduced in A. Hamma et al arXiv:1109.4391. These ensembles are constructed by finite-length random quantum circuits (RQC) acting on (hyper)edges of an underlying (hyper)graph structure. The latter encodes for the locality structure associated with finite-time quantum evolutions generated by physical i.e., local, Hamiltonians. Our goal is to analyze physical properties of typical states in these ensembles, in particular here we focus on proxies of quantum entanglement as purity and $\\alpha$-Renyi entropies. The problem is formulated in terms of matrix elements of superoperators which depend on the graph structure, choice of probability measure over the local unitaries and circuit length. In the $\\alpha=2$ case these superoperators act on a restricted multi-qubit space generated by permutation operators associated to the subsets of vertices of the graph. For permutationally invariant interactions the dynamics c...

  6. Transition state ensemble optimization for reactions of arbitrary complexity

    Science.gov (United States)

    Zinovjev, Kirill; Tuñón, Iñaki

    2015-10-01

    In the present work, we use Variational Transition State Theory (VTST) to develop a practical method for transition state ensemble optimization by looking for an optimal hyperplanar dividing surface in a space of meaningful trial collective variables. These might be interatomic distances, angles, electrostatic potentials, etc. Restrained molecular dynamics simulations are used to obtain on-the-fly estimates of ensemble averages that guide the variations of the hyperplane maximizing the transmission coefficient. A central result of our work is an expression that quantitatively estimates the importance of the coordinates used for the localization of the transition state ensemble. Starting from an arbitrarily large set of trial coordinates, one can distinguish those that are indeed essential for the advance of the reaction. This facilitates the use of VTST as a practical theory to study reaction mechanisms of complex processes. The technique was applied to the reaction catalyzed by an isochorismate pyruvate lyase. This reaction involves two simultaneous chemical steps and has a shallow transition state region, making it challenging to define a good reaction coordinate. Nevertheless, the hyperplanar transition state optimized in the space of 18 geometrical coordinates provides a transmission coefficient of 0.8 and a committor histogram well-peaked about 0.5, proving the strength of the method. We have also tested the approach with the study of the NaCl dissociation in aqueous solution, a stringest test for a method based on transition state theory. We were able to find essential degrees of freedom consistent with the previous studies and to improve the transmission coefficient with respect to the value obtained using solely the NaCl distance as the reaction coordinate.

  7. Entanglement in a solid-state spin ensemble.

    Science.gov (United States)

    Simmons, Stephanie; Brown, Richard M; Riemann, Helge; Abrosimov, Nikolai V; Becker, Peter; Pohl, Hans-Joachim; Thewalt, Mike L W; Itoh, Kohei M; Morton, John J L

    2011-02-03

    Entanglement is the quintessential quantum phenomenon. It is a necessary ingredient in most emerging quantum technologies, including quantum repeaters, quantum information processing and the strongest forms of quantum cryptography. Spin ensembles, such as those used in liquid-state nuclear magnetic resonance, have been important for the development of quantum control methods. However, these demonstrations contain no entanglement and ultimately constitute classical simulations of quantum algorithms. Here we report the on-demand generation of entanglement between an ensemble of electron and nuclear spins in isotopically engineered, phosphorus-doped silicon. We combined high-field (3.4 T), low-temperature (2.9 K) electron spin resonance with hyperpolarization of the (31)P nuclear spin to obtain an initial state of sufficient purity to create a non-classical, inseparable state. The state was verified using density matrix tomography based on geometric phase gates, and had a fidelity of 98% relative to the ideal state at this field and temperature. The entanglement operation was performed simultaneously, with high fidelity, on 10(10) spin pairs; this fulfils one of the essential requirements for a silicon-based quantum information processor.

  8. Ensemble Theory for Stealthy Hyperuniform Disordered Ground States

    Directory of Open Access Journals (Sweden)

    S. Torquato

    2015-05-01

    Full Text Available It has been shown numerically that systems of particles interacting with isotropic “stealthy” bounded long-ranged pair potentials (similar to Friedel oscillations have classical ground states that are (counterintuitively disordered, hyperuniform, and highly degenerate. Disordered hyperuniform systems have received attention recently because they are distinguishable exotic states of matter poised between a crystal and liquid that are endowed with novel thermodynamic and physical properties. The task of formulating an ensemble theory that yields analytical predictions for the structural characteristics and other properties of stealthy degenerate ground states in d-dimensional Euclidean space R^{d} is highly nontrivial because the dimensionality of the configuration space depends on the number density ρ and there is a multitude of ways of sampling the ground-state manifold, each with its own probability measure for finding a particular ground-state configuration. The purpose of this paper is to take some initial steps in this direction. Specifically, we derive general exact relations for thermodynamic properties (energy, pressure, and isothermal compressibility that apply to any ground-state ensemble as a function of ρ in any d, and we show how disordered degenerate ground states arise as part of the ground-state manifold. We also derive exact integral conditions that both the pair correlation function g_{2}(r and structure factor S(k must obey for any d. We then specialize our results to the canonical ensemble (in the zero-temperature limit by exploiting an ansatz that stealthy states behave remarkably like “pseudo”-equilibrium hard-sphere systems in Fourier space. Our theoretical predictions for g_{2}(r and S(k are in excellent agreement with computer simulations across the first three space dimensions. These results are used to obtain order metrics, local number variance, and nearest-neighbor functions across dimensions. We also derive

  9. Ensemble Theory for Stealthy Hyperuniform Disordered Ground States

    Science.gov (United States)

    Torquato, S.; Zhang, G.; Stillinger, F. H.

    2015-04-01

    It has been shown numerically that systems of particles interacting with isotropic "stealthy" bounded long-ranged pair potentials (similar to Friedel oscillations) have classical ground states that are (counterintuitively) disordered, hyperuniform, and highly degenerate. Disordered hyperuniform systems have received attention recently because they are distinguishable exotic states of matter poised between a crystal and liquid that are endowed with novel thermodynamic and physical properties. The task of formulating an ensemble theory that yields analytical predictions for the structural characteristics and other properties of stealthy degenerate ground states in d -dimensional Euclidean space Rd is highly nontrivial because the dimensionality of the configuration space depends on the number density ρ and there is a multitude of ways of sampling the ground-state manifold, each with its own probability measure for finding a particular ground-state configuration. The purpose of this paper is to take some initial steps in this direction. Specifically, we derive general exact relations for thermodynamic properties (energy, pressure, and isothermal compressibility) that apply to any ground-state ensemble as a function of ρ in any d , and we show how disordered degenerate ground states arise as part of the ground-state manifold. We also derive exact integral conditions that both the pair correlation function g2(r ) and structure factor S (k ) must obey for any d . We then specialize our results to the canonical ensemble (in the zero-temperature limit) by exploiting an ansatz that stealthy states behave remarkably like "pseudo"-equilibrium hard-sphere systems in Fourier space. Our theoretical predictions for g2(r ) and S (k ) are in excellent agreement with computer simulations across the first three space dimensions. These results are used to obtain order metrics, local number variance, and nearest-neighbor functions across dimensions. We also derive accurate analytical

  10. Heat Denaturation of Protein Structures and Chlorophyll States in PSII Membranes

    Institute of Scientific and Technical Information of China (English)

    李冬海; 阮翔; 许强; 王可玢; 公衍道; 匡廷云; 赵南明

    2002-01-01

    Heat denaturation is an important technique in the study of the structure and function of photosynthetic proteins. Heat denaturation of photosystem II (PSII) membrane was studied using circular dichroism (CD) spectroscopy, differential scanning calorimetry (DSC) and oxygen electrode. Complete loss of oxygen-evolving activity of the PSII membrane was observed at temperatures below 45℃. The decrease of excitonic interaction between chlorophyll molecules occurred more rapidly than the change of the protein secondary structure of the PSII membrane at temperatures above 45℃. The results indicate that the protein secondary structure of the membrane proteins in PSII membranes is more stable than the excitonic interaction between chlorophyll molecules during heat denaturation.

  11. Toward quantum state tomography of a single polariton state of an atomic ensemble

    DEFF Research Database (Denmark)

    Christensen, S.L.; Béguin, J.B.; Sørensen, H.L.

    2013-01-01

    We present a proposal and a feasibility study for the creation and quantum state tomography of a single polariton state of an atomic ensemble. The collective non-classical and non-Gaussian state of the ensemble is generated by detection of a single forward-scattered photon. The state...... the feasibility of the proposed method for the detection of a non-classical and non-Gaussian state of the mesoscopic atomic ensemble. This work represents the first attempt at hybrid discrete-continuous variable quantum state processing with atomic memories....... is subsequently characterized by atomic state tomography performed using strong dispersive light-atom interaction followed by a homodyne measurement on the transmitted light. The proposal is backed by preliminary experimental results showing projection noise limited sensitivity and a simulation demonstrating...

  12. Typicality in Ensembles of Quantum States: Monte Carlo Sampling vs Analytical Approximations

    CERN Document Server

    Fresch, Barbara

    2009-01-01

    Random Quantum States are presently of interest in the fields of quantum information theory and quantum chaos. Moreover, a detailed study of their properties can shed light on some foundational issues of the quantum statistical mechanics such as the emergence of well defined thermal properties from the pure quantum mechanical description of large many body systems. When dealing with an ensemble of pure quantum states, two questions naturally arise: what is the probability density function on the parameters which specify the state of the system in a given ensemble? And, does there exist a most typical value of a function of interest in the considered ensemble? Here two different ensembles are considered: the Random Pure State Ensemble (RPSE) and the Fixed Expectation Energy Ensemble (FEEE). By means of a suitable parameterization of the wave function in terms of populations and phases, we focus on the probability distribution of the populations in such ensembles. A comparison is made between the distribution i...

  13. Thermodynamic state ensemble models of cis-regulation.

    Directory of Open Access Journals (Sweden)

    Marc S Sherman

    Full Text Available A major goal in computational biology is to develop models that accurately predict a gene's expression from its surrounding regulatory DNA. Here we present one class of such models, thermodynamic state ensemble models. We describe the biochemical derivation of the thermodynamic framework in simple terms, and lay out the mathematical components that comprise each model. These components include (1 the possible states of a promoter, where a state is defined as a particular arrangement of transcription factors bound to a DNA promoter, (2 the binding constants that describe the affinity of the protein-protein and protein-DNA interactions that occur in each state, and (3 whether each state is capable of transcribing. Using these components, we demonstrate how to compute a cis-regulatory function that encodes the probability of a promoter being active. Our intention is to provide enough detail so that readers with little background in thermodynamics can compose their own cis-regulatory functions. To facilitate this goal, we also describe a matrix form of the model that can be easily coded in any programming language. This formalism has great flexibility, which we show by illustrating how phenomena such as competition between transcription factors and cooperativity are readily incorporated into these models. Using this framework, we also demonstrate that Michaelis-like functions, another class of cis-regulatory models, are a subset of the thermodynamic framework with specific assumptions. By recasting Michaelis-like functions as thermodynamic functions, we emphasize the relationship between these models and delineate the specific circumstances representable by each approach. Application of thermodynamic state ensemble models is likely to be an important tool in unraveling the physical basis of combinatorial cis-regulation and in generating formalisms that accurately predict gene expression from DNA sequence.

  14. State estimation of connected vehicles using a nonlinear ensemble filter

    Institute of Scientific and Technical Information of China (English)

    刘江; 陈华展; 蔡伯根; 王剑

    2015-01-01

    The concept of connected vehicles is with great potentials for enhancing the road transportation systems in the future. To support the functions and applications under the connected vehicles frame, the estimation of dynamic states of the vehicles under the cooperative environments is a fundamental issue. By integrating multiple sensors, localization modules in OBUs (on-board units) require effective estimation solutions to cope with various operation conditions. Based on the filtering estimation framework for sensor fusion, an ensemble Kalman filter (EnKF) is introduced to estimate the vehicle’s state with observations from navigation satellites and neighborhood vehicles, and the original EnKF solution is improved by using the cubature transformation to fulfill the requirements of the nonlinearity approximation capability, where the conventional ensemble analysis operation in EnKF is modified to enhance the estimation performance without increasing the computational burden significantly. Simulation results from a nonlinear case and the cooperative vehicle localization scenario illustrate the capability of the proposed filter, which is crucial to realize the active safety of connected vehicles in future intelligent transportation.

  15. Conductor and Ensemble Performance Expressivity and State Festival Ratings

    Science.gov (United States)

    Price, Harry E.; Chang, E. Christina

    2005-01-01

    This study is the second in a series examining the relationship between conducting and ensemble performance. The purpose was to further examine the associations among conductor, ensemble performance expressivity, and festival ratings. Participants were asked to rate the expressivity of video-only conducting and parallel audio-only excerpts from a…

  16. Hybrid quantum processors: molecular ensembles as quantum memory for solid state circuits.

    Science.gov (United States)

    Rabl, P; DeMille, D; Doyle, J M; Lukin, M D; Schoelkopf, R J; Zoller, P

    2006-07-21

    We investigate a hybrid quantum circuit where ensembles of cold polar molecules serve as long-lived quantum memories and optical interfaces for solid state quantum processors. The quantum memory realized by collective spin states (ensemble qubit) is coupled to a high-Q stripline cavity via microwave Raman processes. We show that, for convenient trap-surface distances of a few microm, strong coupling between the cavity and ensemble qubit can be achieved. We discuss basic quantum information protocols, including a swap from the cavity photon bus to the molecular quantum memory, and a deterministic two qubit gate. Finally, we investigate coherence properties of molecular ensemble quantum bits.

  17. Hybrid Quantum Processors: molecular ensembles as quantum memory for solid state circuits

    CERN Document Server

    Rabl, P; Doyle, J M; Lukin, M D; Schölkopf, R J; Zoller, P

    2006-01-01

    We investigate a hybrid quantum circuit where ensembles of cold polar molecules serve as long-lived quantum memories and optical interfaces for solid state quantum processors. The quantum memory realized by collective spin states (ensemble qubit) is coupled to a high-Q stripline cavity via microwave Raman processes. We show that for convenient trap-surface distances of a few $\\mu$m, strong coupling between the cavity and ensemble qubit can be achieved. We discuss basic quantum information protocols, including a swap from the cavity photon bus to the molecular quantum memory, and a deterministic two qubit gate. Finally, we investigate coherence properties of molecular ensemble quantum bits.

  18. A comparison of the pH, urea, and temperature-denatured states of barnase by heteronuclear NMR: implications for the initiation of protein folding.

    Science.gov (United States)

    Arcus, V L; Vuilleumier, S; Freund, S M; Bycroft, M; Fersht, A R

    1995-11-24

    The denatured states of barnase that are induced by urea, acid, and high temperature and acid have been assigned and characterised by high resolution heteronuclear NMR. The assignment was completed using a combination of triple-resonance and magnetisation-transfer methods. The latter was facilitated by selecting a suitable mutant of barnase (Ile-->Val51) which has an appropriate rate of interconversion between native and denatured states in urea. 3J NH-C alpha H coupling constants were determined for pH and urea-denatured barnase and intrinsic "random coil" coupling constants are shown to be different for different residue types. All the denatured states are highly unfolded. But, a consistent series of weak correlations in chemical shift, NOESY and coupling constant data provides evidence that the acid-denatured state has some residual structure in regions that form the first and second helices and the central strands of beta-sheet in the native protein. The acid/temperature-denatured states has less structure in these regions, and the urea-denatured state, less still. These observations may be combined with detailed analyses of the folding pathway of barnase from kinetic studies to illuminate the relevance of residual structure in the denatured states of proteins to the mechanism of protein folding. First, the folding of barnase is known to proceed in its later stages through structures in which the first helix and centre of the beta-sheet are extensively formed. Thus, embryonic initiation sites for these do exist in the denatured states and so could well develop into true nuclei. Second, it has been clearly established that the second helix is unfolded in these later states, and so residual structure in this region of the protein is non-productive. These data fit a model of protein folding in which local nucleation sites are latent in the denatured state and develop only when they make interactions elsewhere in the protein that stabilise them during the folding

  19. [Denaturalized psychoanalysts].

    Science.gov (United States)

    Peglau, Andreas

    2011-01-01

    This paper presents hitherto unknown material from the German Foreign Office referring to the denaturalization of Therese Benedek, Bruno Bettelheim, Adolf Storfer and Wilhelm Reich by Nazi Germany. It corroborates the finding that nobody was persecuted by the Nazis solely on the basis of psychoanalytic activities or membership in a psychoanalytic organization.

  20. Matrices of fidelities for ensembles of quantum states and the Holevo quantity

    CERN Document Server

    Fannes, Mark; Roga, Wojciech; Zyczkowski, Karol

    2011-01-01

    The entropy of the Gram matrix of a joint purification of an ensemble of K mixed states yields an upper bound for the Holevo information Chi of the ensemble. In this work we combine geometrical and probabilistic aspects of the ensemble in order to obtain useful bounds for Chi. This is done by constructing various correlation matrices involving fidelities between every pair of states from the ensemble. For K=3 quantum states we design a matrix of root fidelities that is positive and the entropy of which is conjectured to upper bound Chi. Slightly weaker bounds are established for arbitrary ensembles. Finally, we investigate correlation matrices involving multi-state fidelities in relation to the Holevo quantity.

  1. Distributed orbital state quantum cloning with atomic ensembles via quantum Zeno dynamics

    CERN Document Server

    Shen, Li-Tuo; Yang, Zhen-Biao

    2011-01-01

    We propose a scheme for distributed orbital state quantum cloning with atomic ensembles based on the quantum Zeno dynamics. These atomic ensembles which consist of identical three-level atoms are trapped in distant cavities connected by a single-mode integrated optical star coupler. These qubits can be manipulated through appropriate modulation of the coupling constants between atomic ensemble and classical field, and the cavity decay can be largely suppressed as the number of atoms in the ensemble qubits increases. The present scheme provides a new way to construct the quantum communication network.

  2. Structural and dynamical study about denatured states of yeast phosphoglycerate kinase by neutrons scattering and X-rays; Etude structurale et dynamique des etats denatures de la phosphoglycerate kinase de levure par diffusion des neutrons et des rayons X

    Energy Technology Data Exchange (ETDEWEB)

    Receveur, V

    1997-04-28

    During a long time, the neutron scattering and X-rays techniques have not been used for the studies bearing on the folding of proteins. The compactness and the globularness of a protein are two structural characteristics describing the denatured states and the intermediate states of folding, and the neutrons and x-rays scattering are probably the two techniques the most appropriate to give this kind of information; they are sensible to the spatial extent and to the molecules compactness, and to their general shape. For these three or four last years, the works using these techniques are increasing, giving precious knowledge on the different steps of folding and on the interactions stabilizing the denatured or intermediate states. This thesis falls into this category. (N.C.).

  3. Urea denaturation of barnase: pH dependence and characterization of the unfolded state.

    Science.gov (United States)

    Pace, C N; Laurents, D V; Erickson, R E

    1992-03-17

    To investigate the pH dependence of the conformational stability of barnase, urea denaturation curves were determined over the pH range 2-10. The maximum conformational stability of barnase is 9 kcal mol-1 and occurs between pH 5 and 6. The dependence of delta G on urea concentration increases from 1850 cal mol-1 M-1 at high pH to about 3000 cal mol-1 M-1 near pH 3. This suggests that the unfolded conformations of barnase become more accessible to urea as the net charge on the molecule increases. Previous studies suggested that in 8 M urea barnase unfolds more completely than ribonuclease T1, even with the disulfide bonds broken [Pace, C.N., Laurents, D. V., & Thomson, J.A. (1990) Biochemistry 29, 2564-2572]. In support of this, solvent perturbation difference spectroscopy showed that in 8 M urea the Trp and Tyr residues in barnase are more accessible to perturbation by dimethyl sulfoxide than in ribonuclease T1 with the disulfide bonds broken.

  4. On the efficiency of biased sampling of the multiple state path ensemble

    NARCIS (Netherlands)

    Rogal, J.; Bolhuis, P.G.

    2010-01-01

    Developed for complex systems undergoing rare events involving many (meta)stable states, the multiple state transition path sampling aims to sample from an extended path ensemble including all possible trajectories between any pair of (meta)stable states. The key issue for an efficient sampling of t

  5. Adaptive Ensemble Covariance Localization in Ensemble 4D-VAR State Estimation

    Science.gov (United States)

    2011-04-01

    Tposterr (t)] 2 give the global average of the square of the posterior error of the state estimate in the tropo - sphere of zonal wind u, meridional...decreases with the cosine of latitude. To make sure that the errors pertained primarily to the tropo - sphere, only the lower 23 model levels

  6. Mechanisms of appearance of amplitude and phase chimera states in ensembles of nonlocally coupled chaotic systems

    Science.gov (United States)

    Bogomolov, Sergey A.; Slepnev, Andrei V.; Strelkova, Galina I.; Schöll, Eckehard; Anishchenko, Vadim S.

    2017-02-01

    We explore the bifurcation transition from coherence to incoherence in ensembles of nonlocally coupled chaotic systems. It is firstly shown that two types of chimera states, namely, amplitude and phase, can be found in a network of coupled logistic maps, while only amplitude chimera states can be observed in a ring of continuous-time chaotic systems. We reveal a bifurcation mechanism by analyzing the evolution of space-time profiles and the coupling function with varying coupling coefficient and formulate the necessary and sufficient conditions for realizing the chimera states in the ensembles.

  7. Controllable Quantum State Transfer Between a Josephson Charge Qubit and an Electronic Spin Ensemble

    Science.gov (United States)

    Yan, Run-Ying; Wang, Hong-Ling; Feng, Zhi-Bo

    2016-01-01

    We propose a theoretical scheme to implement controllable quantum state transfer between a superconducting charge qubit and an electronic spin ensemble of nitrogen-vacancy centers. By an electro-mechanical resonator acting as a quantum data bus, an effective interaction between the charge qubit and the spin ensemble can be achieved in the dispersive regime, by which state transfers are switchable due to the adjustable electrical coupling. With the accessible experimental parameters, we further numerically analyze the feasibility and robustness. The present scheme could provide a potential approach for transferring quantum states controllably with the hybrid system.

  8. Solid-State NMR-Restrained Ensemble Dynamics of a Membrane Protein in Explicit Membranes.

    Science.gov (United States)

    Cheng, Xi; Jo, Sunhwan; Qi, Yifei; Marassi, Francesca M; Im, Wonpil

    2015-04-21

    Solid-state NMR has been used to determine the structures of membrane proteins in native-like lipid bilayer environments. Most structure calculations based on solid-state NMR observables are performed using simulated annealing with restrained molecular dynamics and an energy function, where all nonbonded interactions are represented by a single, purely repulsive term with no contributions from van der Waals attractive, electrostatic, or solvation energy. To our knowledge, this is the first application of an ensemble dynamics technique performed in explicit membranes that uses experimental solid-state NMR observables to obtain the refined structure of a membrane protein together with information about its dynamics and its interactions with lipids. Using the membrane-bound form of the fd coat protein as a model membrane protein and its experimental solid-state NMR data, we performed restrained ensemble dynamics simulations with different ensemble sizes in explicit membranes. For comparison, a molecular dynamics simulation of fd coat protein was also performed without any restraints. The average orientation of each protein helix is similar to a structure determined by traditional single-conformer approaches. However, their variations are limited in the resulting ensemble of structures with one or two replicas, as they are under the strong influence of solid-state NMR restraints. Although highly consistent with all solid-state NMR observables, the ensembles of more than two replicas show larger orientational variations similar to those observed in the molecular dynamics simulation without restraints. In particular, in these explicit membrane simulations, Lys(40), residing at the C-terminal side of the transmembrane helix, is observed to cause local membrane curvature. Therefore, compared to traditional single-conformer approaches in implicit environments, solid-state NMR restrained ensemble simulations in explicit membranes readily characterize not only protein

  9. Passage from a pure state description to the microcanonical ensemble description for closed quantum systems

    Indian Academy of Sciences (India)

    N D Hari Dass; B Sathiapalan; Kalyanarama

    2002-08-01

    We have addressed the foundational issue of how a macroscopic quantum system starting off as a pure state tends towards a mixed state described by the microcanonical ensemble. The earlier works of von Neumann and Van Kampen are also reviewed. A simple criterion is given as to when the above mentioned passage can take place.

  10. Ensemble-based characterization of unbound and bound states on protein energy landscape

    CERN Document Server

    Ruvinsky, Anatoly M; Tuzikov, Alexander V; Vakser, Ilya A

    2012-01-01

    Characterization of protein energy landscape and conformational ensembles is important for understanding mechanisms of protein folding and function. We studied ensembles of bound and unbound conformations of six proteins to explore their binding mechanisms and characterize the energy landscapes in implicit solvent. First, results show that bound and unbound spectra often significantly overlap. Moreover, the larger the overlap the smaller the RMSD between bound and unbound conformational ensembles. Second, the analysis of the unbound-to-bound changes points to conformational selection as the binding mechanism for four of the proteins. Third, the center of the unbound spectrum has a higher energy than the center of the corresponding bound spectrum of the dimeric and multimeric states for most of the proteins. This suggests that the unbound states often have larger entropy than the bound states considered outside of the complex. Fourth, the exhaustively long minimization, making small intra-rotamer adjustments, ...

  11. Determination of an ensemble of structures representing the denatured state of the bovine acyl-coenzyme a binding protein

    DEFF Research Database (Denmark)

    Lindorff-Larsen, Kresten; Kristjansdottir, Sigridur; Teilum, Kaare;

    2004-01-01

    is highly heterogeneous. The high sensitivity of the computational method that we present, however, enabled us to identify long-range interactions between two regions, located near the N- and C-termini, that include both native and non-native elements. The preferential formation of these contacts suggests...

  12. Dynamic Polariton and Quantum State Swapping Between an Electromagnetic Field and Atomic Ensemble

    Institute of Scientific and Technical Information of China (English)

    汪凯戈; 杨国建

    2002-01-01

    We analyse a dynamical swapping of the quantum state in coupled harmonic oscillators. The result can be applied to the interaction of a single-mode field with atomic ensemble in the weak field case. Similar to the case of electromagnetic induced transparency (EIT), a dynamic polariton is formed. Therefore, the quantum state of the field can be completely mapped on to the atomic medium, and vice versa. Using this dynamical swapping and the adiabatic transfer in the EIT between the field and atomic ensemble, we propose a scheme in which both the quantum and the coherent information can be transferred from one field to another.

  13. Residue-specific description of non-native transient structures in the ensemble of acid-denatured structures of the all-beta protein c-src SH3

    DEFF Research Database (Denmark)

    Rösner, Heike I; Poulsen, Flemming Martin

    2010-01-01

    Secondary chemical shift analysis has been used to characterize the unfolded state of acid-denatured c-src SH3. Even though native c-src SH3 adopts an all-beta fold, we found evidence of transient helicity in regions corresponding to native loops. In particular, residues 40-46, connecting the n......-src loop to the third beta-strand, exhibited an apparent helicity of nearly 45%. Furthermore, the RT loop and the diverging turn appeared to adopt non-native-like helical conformations. Interestingly, none of the residues found in transient helical conformations exhibited significant varphi-values [Riddle......, D. S., et al. (1999) Nat. Struct. Biol. 6, 1016-1024]. This indicated that the transient helicity has no influence or only a weak influence on the actual protein folding reaction. The residual structural propensities were compared to those of other SH3 domains, revealing heterogeneity...

  14. Quantum entanglement at ambient conditions in a macroscopic solid-state spin ensemble.

    Science.gov (United States)

    Klimov, Paul V; Falk, Abram L; Christle, David J; Dobrovitski, Viatcheslav V; Awschalom, David D

    2015-11-01

    Entanglement is a key resource for quantum computers, quantum-communication networks, and high-precision sensors. Macroscopic spin ensembles have been historically important in the development of quantum algorithms for these prospective technologies and remain strong candidates for implementing them today. This strength derives from their long-lived quantum coherence, strong signal, and ability to couple collectively to external degrees of freedom. Nonetheless, preparing ensembles of genuinely entangled spin states has required high magnetic fields and cryogenic temperatures or photochemical reactions. We demonstrate that entanglement can be realized in solid-state spin ensembles at ambient conditions. We use hybrid registers comprising of electron-nuclear spin pairs that are localized at color-center defects in a commercial SiC wafer. We optically initialize 10(3) identical registers in a 40-μm(3) volume (with [Formula: see text] fidelity) and deterministically prepare them into the maximally entangled Bell states (with 0.88 ± 0.07 fidelity). To verify entanglement, we develop a register-specific quantum-state tomography protocol. The entanglement of a macroscopic solid-state spin ensemble at ambient conditions represents an important step toward practical quantum technology.

  15. Denaturant-Dependent Conformational Changes in a [beta]-Trefoil Protein: Global and Residue-Specific Aspects of an Equilibrium Denaturation Process

    Energy Technology Data Exchange (ETDEWEB)

    Latypov, Ramil F.; Liu, Dingjiang; Jacob, Jaby; Harvey, Timothy S.; Bondarenko, Pavel V.; Kleemann, Gerd R.; Brems, David N.; Raibekas, Andrei A.; (Amgen)

    2010-01-12

    Conformational properties of the folded and unfolded ensembles of human interleukin-1 receptor antagonist (IL-1ra) are strongly denaturant-dependent as evidenced by high-resolution two-dimensional nuclear magnetic resonance (NMR), limited proteolysis, and small-angle X-ray scattering (SAXS). The folded ensemble was characterized in detail in the presence of different urea concentrations by 1H-15N HSQC NMR. The {beta}-trefoil fold characteristic of native IL-1ra was preserved until the unfolding transition region beginning at 4 M urea. At the same time, a subset of native resonances disappeared gradually starting at low denaturant concentrations, indicating noncooperative changes in the folded state. Additional evidence of structural perturbations came from the chemical shift analysis, nonuniform and bell-shaped peak intensity profiles, and limited proteolysis. In particular, the following nearby regions of the tertiary structure became progressively destabilized with increasing urea concentrations: the {beta}-hairpin interface of trefoils 1 and 2 and the H2a-H2 helical region. These regions underwent small-scale perturbations within the native baseline region in the absence of populated molten globule-like states. Similar regions were affected by elevated temperatures known to induce irreversible aggregation of IL-1ra. Further evidence of structural transitions invoking near-native conformations came from an optical spectroscopy analysis of its single-tryptophan variant W17A. The increase in the radius of gyration was associated with a single equilibrium unfolding transition in the case of two different denaturants, urea and guanidine hydrochloride (GuHCl). However, the compactness of urea- and GuHCl-unfolded molecules was comparable only at high denaturant concentrations and deviated under less denaturing conditions. Our results identified the role of conformational flexibility in IL-1ra aggregation and shed light on the nature of structural transitions within the

  16. Operational Ensemble River Forecasting in the United States and Australia: Practices and Challenges

    Science.gov (United States)

    Pagano, T. C.

    2012-04-01

    Operational river forecasts have been long produced to support water resources management in the United States and Australia. These forecasts cover a range of timescales from flash flooding (e.g. minutes to hours ahead) to seasonal (e.g. months ahead) and are generated by a range of statistical (e.g. regression-based) and dynamical (e.g. rainfall-runoff) model based techniques. Forecast uncertainty is commonly estimated operationally by using an ensemble of future precipitation scenarios and/or a measure of historical model error. Retrospective ensemble forecasting and the use of reforecasts for bias-adjustment and post-processing have become popular research topics and a few successful demonstration projects exist in both countries. Practical methods of post-processing, such as ensemble dressing, have been used to improve the probabilistic reliability of forecasts. The translation of predictions of probability distributions of streamflow into temporally and spatially consistent ensemble hydrographs remains an area for further development. However, probabilistic forecast communication and use remains a stumbling block for many. Furthermore, ensemble generation and post-processing typically require completely automated systems, making it difficult for humans to contribute their expertise to the forecasting process. This talk draws on ten years of experience as an operational forecaster with the US Department of Agriculture and as a developer of short-term flood forecasting systems to support the Australian Bureau of Meteorology.

  17. Ensemble DFT Approach to Excited States of Strongly Correlated Molecular Systems.

    Science.gov (United States)

    Filatov, Michael

    2016-01-01

    Ensemble density functional theory (DFT) is a novel time-independent formalism for obtaining excitation energies of many-body fermionic systems. A considerable advantage of ensemble DFT over the more common Kohn-Sham (KS) DFT and time-dependent DFT formalisms is that it enables one to account for strong non-dynamic electron correlation in the ground and excited states of molecular systems in a transparent and accurate fashion. Despite its positive aspects, ensemble DFT has not so far found its way into the repertoire of methods of modern computational chemistry, probably because of the perceived lack of practically affordable implementations of the theory. The spin-restricted ensemble-referenced KS (REKS) method is perhaps the first computationally feasible implementation of the ideas behind ensemble DFT which enables one to describe accurately electronic transitions in a wide class of molecular systems, including strongly correlated molecules (biradicals, molecules undergoing bond breaking/formation), extended π-conjugated systems, donor-acceptor charge transfer adducts, etc.

  18. Linear interpolation method in ensemble Kohn-Sham and range-separated density-functional approximations for excited states

    CERN Document Server

    Senjean, Bruno; Jensen, Hans Jørgen Aa; Fromager, Emmanuel

    2015-01-01

    The computation of excitation energies in range-separated ensemble density-functional theory (DFT) is discussed. The latter approach is appealing as it enables the rigorous formulation of a multi-determinant state-averaged DFT method. In the exact theory, the short-range density functional, that complements the long-range wavefunction-based ensemble energy contribution, should vary with the ensemble weights even when the density is held fixed. This weight dependence ensures that the range-separated ensemble energy varies linearly with the ensemble weights. When the (weight-independent) ground-state short-range exchange-correlation functional is used in this context, curvature appears thus leading to an approximate weight-dependent excitation energy. In order to obtain unambiguous approximate excitation energies, we simply propose to interpolate linearly the ensemble energy between equiensembles. It is shown that such a linear interpolation method (LIM) effectively introduces weight dependence effects. LIM has...

  19. MCMC for non-linear state space models using ensembles of latent sequences

    OpenAIRE

    2013-01-01

    Non-linear state space models are a widely-used class of models for biological, economic, and physical processes. Fitting these models to observed data is a difficult inference problem that has no straightforward solution. We take a Bayesian approach to the inference of unknown parameters of a non-linear state model; this, in turn, requires the availability of efficient Markov Chain Monte Carlo (MCMC) sampling methods for the latent (hidden) variables and model parameters. Using the ensemble ...

  20. 1H, 15N and 13C assignments of domain 5 of Dictyostelium discoideum gelation factor (ABP-120) in its native and 8M urea-denatured states.

    Science.gov (United States)

    Hsu, Shang-Te Danny; Cabrita, Lisa D; Christodoulou, John; Dobson, Christopher M

    2009-06-01

    The gelation factor from Dictyostelium discoideum (ABP-120) is an actin binding protein consisting of six immunoglobulin (Ig) domains in the C-terminal rod domain. We have recently used the pair of domains 5 and 6 of ABP-120 as a model system for studying multi-domain nascent chain folding on the ribosome. Here we present the NMR assignments of domain 5 in its native and 8M urea-denatured states.

  1. Exact ensemble density functional theory for excited states in a model system: Investigating the weight dependence of the correlation energy

    Science.gov (United States)

    Deur, Killian; Mazouin, Laurent; Fromager, Emmanuel

    2017-01-01

    Ensemble density functional theory (eDFT) is an exact time-independent alternative to time-dependent DFT (TD-DFT) for the calculation of excitation energies. Despite its formal simplicity and advantages in contrast to TD-DFT (multiple excitations, for example, can be easily taken into account in an ensemble), eDFT is not standard, which is essentially due to the lack of reliable approximate exchange-correlation (x c ) functionals for ensembles. Following Smith et al. [Phys. Rev. B 93, 245131 (2016), 10.1103/PhysRevB.93.245131], we propose in this work to construct an exact eDFT for the nontrivial asymmetric Hubbard dimer, thus providing more insight into the weight dependence of the ensemble x c energy in various correlation regimes. For that purpose, an exact analytical expression for the weight-dependent ensemble exchange energy has been derived. The complementary exact ensemble correlation energy has been computed by means of Legendre-Fenchel transforms. Interesting features like discontinuities in the ensemble x c potential in the strongly correlated limit have been rationalized by means of a generalized adiabatic connection formalism. Finally, functional-driven errors induced by ground-state density-functional approximations have been studied. In the strictly symmetric case or in the weakly correlated regime, combining ensemble exact exchange with ground-state correlation functionals gives better ensemble energies than when calculated with the ground-state exchange-correlation functional. However, when approaching the asymmetric equiensemble in the strongly correlated regime, the former approximation leads to highly curved ensemble energies with negative slope which is unphysical. Using both ground-state exchange and correlation functionals gives much better results in that case. In fact, exact ensemble energies are almost recovered in some density domains. The analysis of density-driven errors is left for future work.

  2. Sequence-Specific Solvent Accessibilities of Protein Residues in Unfolded Protein Ensembles

    OpenAIRE

    Bernadó, Pau,; Blackledge, Martin; Sancho, Javier

    2006-01-01

    Protein stability cannot be understood without the correct description of the unfolded state. We present here an efficient method for accurate calculation of atomic solvent exposures for denatured protein ensembles. The method used to generate the ensembles has been shown to reproduce diverse biophysical experimental data corresponding to natively and chemically unfolded proteins. Using a data set of 19 nonhomologous proteins containing from 98 to 579 residues, we report average accessibiliti...

  3. Impact of state updating and multi-parametric ensemble for streamflow hindcasting in European river basins

    Science.gov (United States)

    Noh, S. J.; Rakovec, O.; Kumar, R.; Samaniego, L. E.

    2015-12-01

    Accurate and reliable streamflow prediction is essential to mitigate social and economic damage coming from water-related disasters such as flood and drought. Sequential data assimilation (DA) may facilitate improved streamflow prediction using real-time observations to correct internal model states. In conventional DA methods such as state updating, parametric uncertainty is often ignored mainly due to practical limitations of methodology to specify modeling uncertainty with limited ensemble members. However, if parametric uncertainty related with routing and runoff components is not incorporated properly, predictive uncertainty by model ensemble may be insufficient to capture dynamics of observations, which may deteriorate predictability. Recently, a multi-scale parameter regionalization (MPR) method was proposed to make hydrologic predictions at different scales using a same set of model parameters without losing much of the model performance. The MPR method incorporated within the mesoscale hydrologic model (mHM, http://www.ufz.de/mhm) could effectively represent and control uncertainty of high-dimensional parameters in a distributed model using global parameters. In this study, we evaluate impacts of streamflow data assimilation over European river basins. Especially, a multi-parametric ensemble approach is tested to consider the effects of parametric uncertainty in DA. Because augmentation of parameters is not required within an assimilation window, the approach could be more stable with limited ensemble members and have potential for operational uses. To consider the response times and non-Gaussian characteristics of internal hydrologic processes, lagged particle filtering is utilized. The presentation will be focused on gains and limitations of streamflow data assimilation and multi-parametric ensemble method over large-scale basins.

  4. Efficient and robust generation of maximally entangled states of two atomic ensembles by adiabatic quantum feedback

    CERN Document Server

    Lisi, A D; Illuminati, F; Vitali, D; Lisi, Antonio Di; Siena, Silvio De; Illuminati, Fabrizio; Vitali, David

    2004-01-01

    We introduce an efficient and robust scheme to generate maximally entangled states of two atomic ensembles. The scheme is based on quantum non-demolition measurements of total atomic populations and on quantum feedback conditioned by the measurements outputs. The high efficiency of the scheme is tested and confirmed numerically for photo-detection with ideal efficiency as well as in the presence of losses.

  5. Single DNA denaturation and bubble dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Metzler, Ralf [Physics Department, Technical University of Munich, James Franck Strasse, 85747 Garching (Germany); Ambjoernsson, Tobias [Chemistry Department, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 (United States); Hanke, Andreas [Department of Physics and Astronomy, University of Texas, 80 Fort Brown, Brownsville (United States); Fogedby, Hans C [Department of Physics and Astronomy, University of Arhus, Ny Munkegade, 8000 Arhus C (Denmark)], E-mail: metz@ph.tum.de

    2009-01-21

    While the Watson-Crick double-strand is the thermodynamically stable state of DNA in a wide range of temperature and salt conditions, even at physiological conditions local denaturation bubbles may open up spontaneously due to thermal activation. By raising the ambient temperature, titration, or by external forces in single molecule setups bubbles proliferate until full denaturation of the DNA occurs. Based on the Poland-Scheraga model we investigate both the equilibrium transition of DNA denaturation and the dynamics of the denaturation bubbles with respect to recent single DNA chain experiments for situations below, at, and above the denaturation transition. We also propose a new single molecule setup based on DNA constructs with two bubble zones to measure the bubble coalescence and extract the physical parameters relevant to DNA breathing. Finally we consider the interplay between denaturation bubbles and selectively single-stranded DNA binding proteins.

  6. Single DNA denaturation and bubble dynamics

    DEFF Research Database (Denmark)

    Metzler, Ralf; Ambjörnsson, Tobias; Hanke, Andreas

    2009-01-01

    for situations below, at, and above the denaturation transition. We also propose a new single molecule setup based on DNA constructs with two bubble zones to measure the bubble coalescence and extract the physical parameters relevant to DNA breathing. Finally we consider the interplay between denaturation......While the Watson-Crick double-strand is the thermodynamically stable state of DNA in a wide range of temperature and salt conditions, even at physiological conditions local denaturation bubbles may open up spontaneously due to thermal activation. By raising the ambient temperature, titration......, or by external forces in single molecule setups bubbles proliferate until full denaturation of the DNA occurs. Based on the Poland-Scheraga model we investigate both the equilibrium transition of DNA denaturation and the dynamics of the denaturation bubbles with respect to recent single DNA chain experiments...

  7. Partially synchronized states in an ensemble of chemo-mechanical oscillators

    Science.gov (United States)

    Kumar, Pawan; Verma, Dinesh Kumar; Parmananda, P.

    2017-08-01

    Partially synchronized (clustered) states are defined as coexisting coherent (synchronized) and incoherent (unsynchronized) domains in an ensemble of interacting oscillators. We report these clustered states in experiments involving an ensemble of sixteen mercury beating heart (MBH) oscillators. These oscillators interact via resistors and are subjected to two different network schemes: 1) All to all and 2) Nonlocal. For the all to all network, the coupling strengths were inhomogeneously distributed, whereas for the nonlocal network scenario, each oscillator was coupled, with an identical coupling strength, with four of its nearest neighbors in either direction. For both of these network schemes, partially synchronized states results into grouping of these oscillators, wherein some oscillators are synchronized and rest are unsynchronized. For all to all network, the partially synchronized states are observed, for the intermediate inhomogeneities, when subjected to the power law and the 'U' shape profiles of coupling strengths. Irrespective of the coupling profile chosen, low inhomogeneities in the coupling strengths leaves all the oscillators in a single coherent state whereas for the high inhomogeneities scenarios oscillators are located in the incoherent domain. In comparison, for the nonlocal network partially synchronized states emerge when the coupling constant is appropriately chosen. The experimental results for both these network scenarios have been analyzed using the redox time series (chemical activity) and the time evolution of the normalized areas for the mercury drop (mechanical activity). The existence of partially synchronized states in the experiments was verified using different diagnostic tools such as time series plot, space-time plot and average frequency.

  8. Ensemble data assimilation for ocean biogeochemical state and parameter estimation at different sites

    Science.gov (United States)

    Gharamti, M. E.; Tjiputra, J.; Bethke, I.; Samuelsen, A.; Skjelvan, I.; Bentsen, M.; Bertino, L.

    2017-04-01

    We develop an efficient data assimilation system that aims at quantifying the uncertainties of various biogeochemical states and parameters. We explore the use of four different ensemble estimation techniques for tuning poorly constrained ecosystem parameters using a one-dimensional configuration of the Ocean Biogeochemical General Circulation Model. The schemes are all EnKF-based operating sequentially in time but have different correction equations. The 1D model is used to simulate the biogeochemical cycle at three different stations in mid and high latitudes. We assimilate monthly climatological profiles of nitrate, silicate, phosphate and oxygen in addition to seasonal surface pCO2 data, between 2006 and 2010. We use the data to optimize eleven ecosystem parameters in addition to all state variables of the model, describing the dynamical processes of the water column. Our assimilation results suggest the following: (1) Among all tested schemes, the one-step-ahead smoothing-based ensemble Kalman filter (OSA-EnKF) is robust and the most accurate, providing consistent and reliable state-parameter ensemble realizations. (2) Given the large uncertainties associated with the ecosystem parameters, estimating only the state variables is generally inconclusive and biased. (3) The OSA-EnKF successfully recovers the observed seasonal variability of the ecosystem dynamics at all stations and helps optimizing the parameters, eventually reducing the prediction errors of the nutrients' concentrations. (4) The estimates of the parameters may have some temporally correlated features and they can also vary spatially between different regions depending on the magnitude of the bias in the observed variables and other factors such as the intensity of the bloom period. We further show that the presented assimilation system has the potential to be used in global models.

  9. One plus two-body random matrix ensembles with parity: Density of states and parity ratios

    CERN Document Server

    Vyas, Manan; Srivastava, P C

    2011-01-01

    One plus two-body embedded Gaussian orthogonal ensemble of random matrices with parity [EGOE(1+2)-$\\pi$] generated by a chaos producing two-body interaction in the presence of a mean-field, for spinless identical fermion systems, is defined in terms of two mixing parameters and a gap between the positive $(\\pi=+)$ and negative $(\\pi=-)$ parity single particle (sp) states. Numerical calculations are used to demonstrate, using realistic values of the mixing parameters appropriate for some nuclei, that this ensemble generates Gaussian form (with corrections) for fixed parity eigenvalue densities (i.e. state densities). The random matrix model also generates many features in parity ratios of state densities that are similar to those predicted by a method based on the Fermi-gas model for nuclei. We have also obtained a simple formula for the spectral variances defined over fixed-$(m_1,m_2)$ spaces, where $m_1$ is the number of fermions in the $+$ve parity sp states and $m_2$ is the number of fermions in the $-$ve ...

  10. Dynamic State Estimation and Parameter Calibration of DFIG based on Ensemble Kalman Filter

    Energy Technology Data Exchange (ETDEWEB)

    Fan, Rui; Huang, Zhenyu; Wang, Shaobu; Diao, Ruisheng; Meng, Da

    2015-07-30

    With the growing interest in the application of wind energy, doubly fed induction generator (DFIG) plays an essential role in the industry nowadays. To deal with the increasing stochastic variations introduced by intermittent wind resource and responsive loads, dynamic state estimation (DSE) are introduced in any power system associated with DFIGs. However, sometimes this dynamic analysis canould not work because the parameters of DFIGs are not accurate enough. To solve the problem, an ensemble Kalman filter (EnKF) method is proposed for the state estimation and parameter calibration tasks. In this paper, a DFIG is modeled and implemented with the EnKF method. Sensitivity analysis is demonstrated regarding the measurement noise, initial state errors and parameter errors. The results indicate this EnKF method has a robust performance on the state estimation and parameter calibration of DFIGs.

  11. Limits for compression of quantum information carried by ensembles of mixed states

    CERN Document Server

    Horodecki, M

    1998-01-01

    We consider the problem of compression of the quantum information carried by ensemble of mixed states. We prove that for arbitrary coding schemes the least number of qubits needed to convey the signal states asymptotically faithfully is bounded from below by the Holevo function $S(\\varrho)-\\sum_ip_iS(\\varrho_i)$. We also show that a compression protocol can be composed with another one, provided that the latter offers perfect transmission. Such a compound protocol is applied to the case of binary source. It is conjectured to reach the obtained bound. Finally, we point out that in the case of mixed signal states there could be a difference between the maximal compression rates at the coding schemes which are ``blind'' to the signal and the ones which assume the knowledge about the identities of the signal states.

  12. Ensemble velocity of non-processive molecular motors with multiple chemical states

    CERN Document Server

    Vilfan, Andrej

    2014-01-01

    We study the ensemble velocity of non-processive motor proteins, described with multiple chemical states. In particular, we discuss the velocity as a function of ATP concentration. Even a simple model which neglects the strain-dependence of transition rates, reverse transition rates and nonlinearities in the elasticity can show interesting functional dependencies, which deviate significantly from the frequently assumed Michaelis-Menten form. We discuss how the oder of events in the duty cycle can be inferred from the measured dependence. The model also predicts the possibility of velocity reversal at a certain ATP concentration if the duty cycle contains several conformational changes of opposite directionalities.

  13. Accessing Many-Body Localized States through the Generalized Gibbs Ensemble

    Science.gov (United States)

    Inglis, Stephen; Pollet, Lode

    2016-09-01

    We show how the thermodynamic properties of large many-body localized systems can be studied using quantum Monte Carlo simulations. We devise a heuristic way of constructing local integrals of motion of high quality, which are added to the Hamiltonian in conjunction with Lagrange multipliers. The ground state simulation of the shifted Hamiltonian corresponds to a high-energy state of the original Hamiltonian in the case of exactly known local integrals of motion. The inevitable mixing between eigenstates as a consequence of nonperfect integrals of motion is weak enough such that the characteristics of many-body localized systems are not averaged out, unlike the standard ensembles of statistical mechanics. Our method paves the way to study higher dimensions and indicates that a fully many-body localized phase in 2D, where (nearly) all eigenstates are localized, is likely to exist.

  14. The Low pH Unfolded State of the C-terminal Domain of the Ribosomal Protein L9 Contains Significant Secondary Structure in the Absence of Denaturant but is No More Compact than the Low pH Urea Unfolded State

    Science.gov (United States)

    Shan, Bing; Bhattacharya, Shibani; Eliezer, David; Raleigh, Daniel P

    2009-01-01

    There is considerable interest in the properties of the unfolded states of proteins, particularly unfolded states which can be populated in the absence of high concentrations of denaturants. Interest in the unfolded state ensemble reflects the fact that it is the starting point for protein folding as well as the reference state for protein stability studies, and can be the starting state for pathological aggregation. The unfolded state of the C-terminal domain (residues 58 to 149) of the ribosomal protein L9 (CTL9) can be populated in the absence of denaturant at low pH. CTL9 is a 92 residue globular α, β protein. The low pH unfolded state contains more secondary structure than low pH urea unfolded state but it is not a molten globule. Backbone (1H, 13C and 15N) NMR assignments as well as side chain 13Cβ and 1Hβ assignments and 15N R2 values were obtained for the pH 2.0 unfolded form of CTL9 and for the urea unfolded state at pH 2.5. Analysis of the deviations of the chemical shifts from random coil values indicates that residues that comprise the two helices in the native state show a clear preference to adopt helical φ, ψ angles in the pH 2.0 unfolded state. There is a less pronounced but nevertheless clear tendency for residues 107 to 124 to preferentially populate helical φ, ψ values in the unfolded state. The urea unfolded state has no detectable tendency to populate any type of secondary structure even though it is as compact as the pH 2.0 unfolded state. Comparison of the two unfolded forms of CTL9 provides direct experimental evidence that states which differ significantly in their secondary structure can have identical hydrodynamic properties. This in turn demonstrates that global parameters such as Rh or Rg are very poor indicators of “random coil” behavior. PMID:18707127

  15. The low-pH unfolded state of the C-terminal domain of the ribosomal protein L9 contains significant secondary structure in the absence of denaturant but is no more compact than the low-pH urea unfolded state.

    Science.gov (United States)

    Shan, Bing; Bhattacharya, Shibani; Eliezer, David; Raleigh, Daniel P

    2008-09-01

    There is considerable interest in the properties of the unfolded states of proteins, particularly unfolded states which can be populated in the absence of high concentrations of denaturants. Interest in the unfolded state ensemble reflects the fact that it is the starting point for protein folding as well as the reference state for protein stability studies and can be the starting state for pathological aggregation. The unfolded state of the C-terminal domain (residues 58-149) of the ribosomal protein L9 (CTL9) can be populated in the absence of denaturant at low pH. CTL9 is a 92-residue globular alpha, beta protein. The low-pH unfolded state contains more secondary structure than the low-pH urea unfolded state, but it is not a molten globule. Backbone ( (1)H, (13)C, and (15)N) NMR assignments as well as side chain (13)C beta and (1)H beta assignments and (15)N R 2 values were obtained for the pH 2.0 unfolded form of CTL9 and for the urea unfolded state at pH 2.5. Analysis of the deviations of the chemical shifts from random coil values indicates that residues that comprise the two helices in the native state show a clear preference for adopting helical phi and psi angles in the pH 2.0 unfolded state. There is a less pronounced but nevertheless clear tendency for residues 107-124 to preferentially populate helical phi and psi values in the unfolded state. The urea unfolded state has no detectable tendency to populate any type of secondary structure even though it is as compact as the pH 2.0 unfolded state. Comparison of the two unfolded forms of CTL9 provides direct experimental evidence that states which differ significantly in their secondary structure can have identical hydrodynamic properties. This in turn demonstrates that global parameters such as R h or R g are very poor indicators of "random coil" behavior.

  16. On the (in)consistency of a multi-model ensemble of the past 30 years land surface state.

    Science.gov (United States)

    Dutra, Emanuel; Schellekens, Jaap; Beck, Hylke; Balsamo, Gianpaolo

    2016-04-01

    Global land-surface and hydrological models are a fundamental tool in understanding the land-surface state and evolution either coupled to atmospheric models for climate and weather predictions or in stand-alone mode. In this study we take a recently developed dataset consisting in stand-alone simulations by 10 global hydrological and land surface models sharing the same atmospheric forcing for the period 1979-2012 (the eart2Observe dataset). This multi-model ensemble provides the first freely available dataset with such a spatial/temporal scale that allows for a characterization of the multi-model characteristics such as inter-model consistency and error-spread relationship. We will present a metric for the ensemble consistency using the concept of potential predictability, that can be interpreted as a proxy for the multi-model agreement. Initial results point to regions of low inter-model agreement in the polar and tropical regions, the latter also present when comparing globally available precipitation datasets. In addition to this, the discharge ensemble spread around the ensemble mean was compared to the error of the ensemble mean for several large-scale and small scale basins. This showed a general under-estimation of the ensemble spread, particularly in tropical basins, suggesting that the current dataset lacks the representation of the precipitation uncertainty in the input meteorological data.

  17. Multiscale approach to the determination of the photoactive yellow protein signaling state ensemble.

    Directory of Open Access Journals (Sweden)

    Mary A Rohrdanz

    2014-10-01

    Full Text Available The nature of the optical cycle of photoactive yellow protein (PYP makes its elucidation challenging for both experiment and theory. The long transition times render conventional simulation methods ineffective, and yet the short signaling-state lifetime makes experimental data difficult to obtain and interpret. Here, through an innovative combination of computational methods, a prediction and analysis of the biological signaling state of PYP is presented. Coarse-grained modeling and locally scaled diffusion map are first used to obtain a rough bird's-eye view of the free energy landscape of photo-activated PYP. Then all-atom reconstruction, followed by an enhanced sampling scheme; diffusion map-directed-molecular dynamics are used to focus in on the signaling-state region of configuration space and obtain an ensemble of signaling state structures. To the best of our knowledge, this is the first time an all-atom reconstruction from a coarse grained model has been performed in a relatively unexplored region of molecular configuration space. We compare our signaling state prediction with previous computational and more recent experimental results, and the comparison is favorable, which validates the method presented. This approach provides additional insight to understand the PYP photo cycle, and can be applied to other systems for which more direct methods are impractical.

  18. Multiscale approach to the determination of the photoactive yellow protein signaling state ensemble.

    Science.gov (United States)

    A Rohrdanz, Mary; Zheng, Wenwei; Lambeth, Bradley; Vreede, Jocelyne; Clementi, Cecilia

    2014-10-01

    The nature of the optical cycle of photoactive yellow protein (PYP) makes its elucidation challenging for both experiment and theory. The long transition times render conventional simulation methods ineffective, and yet the short signaling-state lifetime makes experimental data difficult to obtain and interpret. Here, through an innovative combination of computational methods, a prediction and analysis of the biological signaling state of PYP is presented. Coarse-grained modeling and locally scaled diffusion map are first used to obtain a rough bird's-eye view of the free energy landscape of photo-activated PYP. Then all-atom reconstruction, followed by an enhanced sampling scheme; diffusion map-directed-molecular dynamics are used to focus in on the signaling-state region of configuration space and obtain an ensemble of signaling state structures. To the best of our knowledge, this is the first time an all-atom reconstruction from a coarse grained model has been performed in a relatively unexplored region of molecular configuration space. We compare our signaling state prediction with previous computational and more recent experimental results, and the comparison is favorable, which validates the method presented. This approach provides additional insight to understand the PYP photo cycle, and can be applied to other systems for which more direct methods are impractical.

  19. Solid state multi-ensemble quantum computer in waveguide circuit model

    CERN Document Server

    Moiseev, Sergey A; Gubaidullin, Firdus F

    2010-01-01

    The first realization of solid state quantum computer was demonstrated recently by using artificial atoms -- transmons in superconducting resonator. Here, we propose a novel architecture of flexible and scalable quantum computer based on a waveguide circuit coupling many quantum nodes of controlled atomic ensembles. For the first time, we found the optimal practically attainable parameters of the atoms and circuit for 100{%} efficiency of quantum memory for multi qubit photon fields and confirmed experimentally the predicted perfect storage. Then we revealed self modes for reversible transfer of qubits between the quantum memory node and arbitrary other nodes. We found a realization of iSWAP gate via direct coupling of two arbitrary nodes with a processing rate accelerated proportionally to number of atoms in the node. A large number of the two-qubit gates can be simultaneously realized in the circuit for implementation of parallel quantum processing. Dynamic coherent elimination procedure of excess quantum s...

  20. The state of the art of flood forecasting - Hydrological Ensemble Prediction Systems

    Science.gov (United States)

    Thielen-Del Pozo, J.; Pappenberger, F.; Salamon, P.; Bogner, K.; Burek, P.; de Roo, A.

    2010-09-01

    Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Because of the specific characteristics of each catchment, varying data availability and end-user demands, the design of the best flood forecasting system may differ from catchment to catchment. However, despite the differences in concept and data needs, there is one underlying issue that spans across all systems. There has been an growing awareness and acceptance that uncertainty is a fundamental issue of flood forecasting and needs to be dealt with at the different spatial and temporal scales as well as the different stages of the flood generating processes. Today, operational flood forecasting centres change increasingly from single deterministic forecasts to probabilistic forecasts with various representations of the different contributions of uncertainty. The move towards these so-called Hydrological Ensemble Prediction Systems (HEPS) in flood forecasting represents the state of the art in forecasting science, following on the success of the use of ensembles for weather forecasting (Buizza et al., 2005) and paralleling the move towards ensemble forecasting in other related disciplines such as climate change predictions. The use of HEPS has been internationally fostered by initiatives such as "The Hydrologic Ensemble Prediction Experiment" (HEPEX), created with the aim to investigate how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes. The advantages of quantifying the different contributions of uncertainty as well as the overall uncertainty to obtain reliable and useful flood forecasts also for extreme events

  1. Collective dynamics of solid-state spin chains and ensembles in quantum information processing

    Science.gov (United States)

    Ping, Yuting

    This thesis is concerned with the collective dynamics in different spin chains and spin ensembles in solid-state materials. The focus is on the manipulation of electron spins, through spin-spin and spin-photon couplings controlled by voltage potentials or electromagnetic fields. A brief review of various systems is provided to describe the possible physical implementation of the ideas, and also outlines the basis of the adopted effective interaction models. The first two ideas presented explore the collective behaviour of non-interacting spin chains with external couplings. One focuses on mapping the identical state of spin-singlet pairs in two currents onto two distant, static spins downstream, creating distributed entanglement that may be accessed. The other studies a quantum memory consisting of an array of non-interacting, static spins, which may encode and decode multiple flying spins. Both chains could effectively `enhance' weak couplings in a cumulative fashion, and neither scheme requires active quantum control. Moreover, the distributed entanglement generated can offer larger separation between the qubits than more conventional protocols that only exploit the tunnelling effects between quantum dots. The quantum memory can also `smooth' the statistical fluctuations in the effects of local errors when the stored information is spread. Next, an interacting chain of static spins with nearest-neighbour interactions is introduced to connect distant end spins. Previously, it has been shown that this approach provides a cubic speed-up when compared with the direct coupling between the target spins. The practicality of this scheme is investigated by analysing realistic error effects via numerical simulations, and from that perspective relaxation of the nearest-neighbour assumption is proposed. Finally, a non-interacting electron spin ensemble is reviewed as a quantum memory to store single photons from an on-chip stripline cavity. It is then promoted to a full

  2. Exact Solution to the Extended Zwanzig Model for Quasi-Sigmoidal Chemically Induced Denaturation Profiles: Specific Heat and Configurational Entropy

    Directory of Open Access Journals (Sweden)

    G. E. Aguilar-Pineda

    2014-01-01

    Full Text Available Temperature and chemically induced denaturation comprise two of the most characteristic mechanisms to achieve the passage from the native state N to any of the unstructured states Dj in the denatured ensemble in proteins and peptides. In this work we present a full analytical solution for the configurational partition function qs of a homopolymer chain poly-X in the extended Zwanzig model (EZM for a quasisigmoidal denaturation profile. This solution is built up from an EZM exact solution in the case where the fraction α of native contacts follows exact linear dependence on denaturant’s concentration ζ; thus an analytical solution for L in the case of an exact linear denaturation profile is also provided. A recently established connection between the number ν of potential nonnative conformations per residue and temperature-independent helical propensity ω complements the model in order to identify specific proteinogenic poly-X chains, where X represents any of the twenty naturally occurring aminoacid residues. From qs, equilibrium thermodynamic potentials like entropy and average internal energy 〈E〉 and thermodynamic susceptibilities like specific heat C are calculated for poly-valine (poly-V and poly-alanine (poly-A chains. The influence of the rate at which native contacts denature as function of ζ on thermodynamic stability is also discussed.

  3. The Ensembl REST API: Ensembl Data for Any Language.

    Science.gov (United States)

    Yates, Andrew; Beal, Kathryn; Keenan, Stephen; McLaren, William; Pignatelli, Miguel; Ritchie, Graham R S; Ruffier, Magali; Taylor, Kieron; Vullo, Alessandro; Flicek, Paul

    2015-01-01

    We present a Web service to access Ensembl data using Representational State Transfer (REST). The Ensembl REST server enables the easy retrieval of a wide range of Ensembl data by most programming languages, using standard formats such as JSON and FASTA while minimizing client work. We also introduce bindings to the popular Ensembl Variant Effect Predictor tool permitting large-scale programmatic variant analysis independent of any specific programming language. The Ensembl REST API can be accessed at http://rest.ensembl.org and source code is freely available under an Apache 2.0 license from http://github.com/Ensembl/ensembl-rest. © The Author 2014. Published by Oxford University Press.

  4. A Bayesian Consistent Dual Ensemble Kalman Filter for State-Parameter Estimation in Subsurface Hydrology

    CERN Document Server

    Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim

    2015-01-01

    Ensemble Kalman filtering (EnKF) is an efficient approach to addressing uncertainties in subsurface groundwater models. The EnKF sequentially integrates field data into simulation models to obtain a better characterization of the model's state and parameters. These are generally estimated following joint and dual filtering strategies, in which, at each assimilation cycle, a forecast step by the model is followed by an update step with incoming observations. The Joint-EnKF directly updates the augmented state-parameter vector while the Dual-EnKF employs two separate filters, first estimating the parameters and then estimating the state based on the updated parameters. In this paper, we reverse the order of the forecast-update steps following the one-step-ahead (OSA) smoothing formulation of the Bayesian filtering problem, based on which we propose a new dual EnKF scheme, the Dual-EnKF$_{\\rm OSA}$. Compared to the Dual-EnKF, this introduces a new update step to the state in a fully consistent Bayesian framework...

  5. Ensemble Kalman Filtering with a Divided State-Space Strategy for Coupled Data Assimilation Problems

    KAUST Repository

    Luo, Xiaodong

    2014-12-01

    This study considers the data assimilation problem in coupled systems, which consists of two components (subsystems) interacting with each other through certain coupling terms. A straightforward way to tackle the assimilation problem in such systems is to concatenate the states of the subsystems into one augmented state vector, so that a standard ensemble Kalman filter (EnKF) can be directly applied. This work presents a divided state-space estimation strategy, in which data assimilation is carried out with respect to each individual subsystem, involving quantities from the subsystem itself and correlated quantities from other coupled subsystems. On top of the divided state-space estimation strategy, the authors also consider the possibility of running the subsystems separately. Combining these two ideas, a few variants of the EnKF are derived. The introduction of these variants is mainly inspired by the current status and challenges in coupled data assimilation problems and thus might be of interest from a practical point of view. Numerical experiments with a multiscale Lorenz 96 model are conducted to evaluate the performance of these variants against that of the conventional EnKF. In addition, specific for coupled data assimilation problems, two prototypes of extensions of the presented methods are also developed in order to achieve a trade-offbetween efficiency and accuracy.

  6. A Bayesian consistent dual ensemble Kalman filter for state-parameter estimation in subsurface hydrology

    Science.gov (United States)

    Ait-El-Fquih, Boujemaa; El Gharamti, Mohamad; Hoteit, Ibrahim

    2016-08-01

    Ensemble Kalman filtering (EnKF) is an efficient approach to addressing uncertainties in subsurface groundwater models. The EnKF sequentially integrates field data into simulation models to obtain a better characterization of the model's state and parameters. These are generally estimated following joint and dual filtering strategies, in which, at each assimilation cycle, a forecast step by the model is followed by an update step with incoming observations. The joint EnKF directly updates the augmented state-parameter vector, whereas the dual EnKF empirically employs two separate filters, first estimating the parameters and then estimating the state based on the updated parameters. To develop a Bayesian consistent dual approach and improve the state-parameter estimates and their consistency, we propose in this paper a one-step-ahead (OSA) smoothing formulation of the state-parameter Bayesian filtering problem from which we derive a new dual-type EnKF, the dual EnKFOSA. Compared with the standard dual EnKF, it imposes a new update step to the state, which is shown to enhance the performance of the dual approach with almost no increase in the computational cost. Numerical experiments are conducted with a two-dimensional (2-D) synthetic groundwater aquifer model to investigate the performance and robustness of the proposed dual EnKFOSA, and to evaluate its results against those of the joint and dual EnKFs. The proposed scheme is able to successfully recover both the hydraulic head and the aquifer conductivity, providing further reliable estimates of their uncertainties. Furthermore, it is found to be more robust to different assimilation settings, such as the spatial and temporal distribution of the observations, and the level of noise in the data. Based on our experimental setups, it yields up to 25 % more accurate state and parameter estimations than the joint and dual approaches.

  7. A Bayesian consistent dual ensemble Kalman filter for state-parameter estimation in subsurface hydrology

    KAUST Repository

    Ait-El-Fquih, Boujemaa

    2016-08-12

    Ensemble Kalman filtering (EnKF) is an efficient approach to addressing uncertainties in subsurface ground-water models. The EnKF sequentially integrates field data into simulation models to obtain a better characterization of the model\\'s state and parameters. These are generally estimated following joint and dual filtering strategies, in which, at each assimilation cycle, a forecast step by the model is followed by an update step with incoming observations. The joint EnKF directly updates the augmented state-parameter vector, whereas the dual EnKF empirically employs two separate filters, first estimating the parameters and then estimating the state based on the updated parameters. To develop a Bayesian consistent dual approach and improve the state-parameter estimates and their consistency, we propose in this paper a one-step-ahead (OSA) smoothing formulation of the state-parameter Bayesian filtering problem from which we derive a new dual-type EnKF, the dual EnKF(OSA). Compared with the standard dual EnKF, it imposes a new update step to the state, which is shown to enhance the performance of the dual approach with almost no increase in the computational cost. Numerical experiments are conducted with a two-dimensional (2-D) synthetic groundwater aquifer model to investigate the performance and robustness of the proposed dual EnKFOSA, and to evaluate its results against those of the joint and dual EnKFs. The proposed scheme is able to successfully recover both the hydraulic head and the aquifer conductivity, providing further reliable estimates of their uncertainties. Furthermore, it is found to be more robust to different assimilation settings, such as the spatial and temporal distribution of the observations, and the level of noise in the data. Based on our experimental setups, it yields up to 25% more accurate state and parameter estimations than the joint and dual approaches.

  8. Drought Prediction over the United States Using the North American Multi Model Ensemble

    Science.gov (United States)

    Mo, K. C.; Lettenmaier, D. P.

    2014-12-01

    We analyzed the skill of drought forecasts over the United States based on drought indices derived from the hydroclimate forecasts from the North American Multi model ensemble (NMME). The test period is from 1982-2010 and forecasts are initialized from the beginning of January, April, July and October. We analyzed the forecast skill of drought indices such as the 6-month standardized precipitation index (SPI6), monthly mean soil moisture percentiles (SMP) and the 3-month standardized runoff index (SRI3). The soil moisture and runoff were obtained by drive the Variable Infiltration Capacity land model with forcing derived from the NMME members (NMME_VIC). Drought indices from each member were computed and they were put into percentiles determined from all members in the training period at a given lead. We then formed an ensemble grand mean by averaging all indices together and determined the concurrence measure which is the extent to which all different members agree. We find that : 1) The grand mean has higher skill than individual member; 2) During winter, forecasts are skillful in the regimes where the initial conditions dominant contributions to skill, the agreement between the grand mean and members are above 70-80% . At high leads, the concurrence measure drops to 50-60%, even when forecasts are unskillful. 3) During summer, forecast skill is low and concurrence measure drops to 10-30%, 4). The skill of drought forecasts is regionally and seasonally dependent. The NMME_VIC forecasts tend to over forecast drought events with large false alarm rate. After lead-1, the low thread score indicates no skill. The forecast errors will be analyzed to determine the origin of forecast skill.

  9. Optimizing a dynamical decoupling protocol for solid-state electronic spin ensembles in diamond

    Science.gov (United States)

    Farfurnik, D.; Jarmola, A.; Pham, L. M.; Wang, Z. H.; Dobrovitski, V. V.; Walsworth, R. L.; Budker, D.; Bar-Gill, N.

    2015-08-01

    We demonstrate significant improvements of the spin coherence time of a dense ensemble of nitrogen-vacancy (NV) centers in diamond through optimized dynamical decoupling (DD). Cooling the sample down to 77 K suppresses longitudinal spin relaxation T1 effects and DD microwave pulses are used to increase the transverse coherence time T2 from ˜0.7 ms up to ˜30 ms . We extend previous work of single-axis (Carr-Purcell-Meiboom-Gill) DD towards the preservation of arbitrary spin states. Following a theoretical and experimental characterization of pulse and detuning errors, we compare the performance of various DD protocols. We identify that the optimal control scheme for preserving an arbitrary spin state is a recursive protocol, the concatenated version of the XY8 pulse sequence. The improved spin coherence might have an immediate impact on improvements of the sensitivities of ac magnetometry. Moreover, the protocol can be used on denser diamond samples to increase coherence times up to NV-NV interaction time scales, a major step towards the creation of quantum collective NV spin states.

  10. Improving the coherence properties of solid-state spin ensembles via optimized dynamical decoupling

    Science.gov (United States)

    Farfurnik, D.; Jarmola, A.; Pham, L. M.; Wang, Z. H.; Dobrovitski, V. V.; Walsworth, R. L.; Budker, D.; Bar-Gill, N.

    2016-04-01

    In this work, we optimize a dynamical decoupling (DD) protocol to improve the spin coherence properties of a dense ensemble of nitrogen-vacancy (NV) centers in diamond. Using liquid nitrogen-based cooling and DD microwave pulses, we increase the transverse coherence time T2 from ˜ 0.7 ms up to ˜ 30 ms. We extend previous work of single-axis (Carr-Purcell-Meiboom-Gill) DD towards the preservation of arbitrary spin states. After performing a detailed analysis of pulse and detuning errors, we compare the performance of various DD protocols. We identify that the concatenated XY8 pulse sequences serves as the optimal control scheme for preserving an arbitrary spin state. Finally, we use the concatenated sequences to demonstrate an immediate improvement of the AC magnetic sensitivity up to a factor of two at 250 kHz. For future work, similar protocols may be used to increase coherence times up to NV-NV interaction time scales, a major step toward the creation of quantum collective NV spin states.

  11. Performance comparison of meso-scale ensemble wave forecasting systems for Mediterranean sea states

    Science.gov (United States)

    Pezzutto, Paolo; Saulter, Andrew; Cavaleri, Luigi; Bunney, Christopher; Marcucci, Francesca; Torrisi, Lucio; Sebastianelli, Stefano

    2016-08-01

    This paper compares the performance of two wind and wave short range ensemble forecast systems for the Mediterranean Sea. In particular, it describes a six month verification experiment carried out by the U.K. Met Office and Italian Air Force Meteorological Service, based on their respective systems: the Met Office Global-Regional Ensemble Prediction System and the Nettuno Ensemble Prediction System. The latter is the ensemble version of the operational Nettuno forecast system. Attention is focused on the differences between the two implementations (e.g. grid resolution and initial ensemble members sampling) and their effects on the prediction skill. The cross-verification of the two ensemble systems shows that from a macroscopic point of view the differences cancel out, suggesting similar skill. More in-depth analysis indicates that the Nettuno wave forecast is better resolved but, on average, slightly less reliable than the Met Office product. Assessment of the added value of the ensemble techniques at short range in comparison with the deterministic forecast from Nettuno, reveals that adopting the ensemble approach has small, but substantive, advantages.

  12. Multiple conformational states of a new hematopoietic cytokine (megakaryocyte growth and development factor): pH- and urea-induced denaturation.

    Science.gov (United States)

    Hamburger, J B; Chen, E; Narhi, L O; Wu, G M; Brems, D N

    1998-09-01

    The effect of pH and urea on the conformation of recombinant human megakaryocyte growth and development factor (rHuMGDF) was determined by circular dichroism, intrinsic fluorescence spectroscopy, and equilibrium ultracentrifugation. The conformation of rHuMGDF was dependent on pH and urea concentration. Multiple folding forms were evidenced by multiple pH-induced transitions and urea-induced equilibrium transitions that deviated from a simple two-state process. In neutral to alkaline pH, rHuMGDF exists as a monomer, but an acid-induced conformational state self-associates to form a soluble aggregate. A folding intermediate(s) was observed with a more stable secondary structure than tertiary structure and was dependent on the pH of the urea-induced denaturation. The differences in the stabilities of the folding states were most distinct in the pH range of 4.5 to 6.5. The presence of intermediates in the folding pathway of rHuMGDF are similar to findings of previous studies of related growth factors that share a common three-dimensional structure.

  13. Prediction and validation of protein intermediate states from structurally rich ensembles and coarse-grained simulations

    Science.gov (United States)

    Orellana, Laura; Yoluk, Ozge; Carrillo, Oliver; Orozco, Modesto; Lindahl, Erik

    2016-08-01

    Protein conformational changes are at the heart of cell functions, from signalling to ion transport. However, the transient nature of the intermediates along transition pathways hampers their experimental detection, making the underlying mechanisms elusive. Here we retrieve dynamic information on the actual transition routes from principal component analysis (PCA) of structurally-rich ensembles and, in combination with coarse-grained simulations, explore the conformational landscapes of five well-studied proteins. Modelling them as elastic networks in a hybrid elastic-network Brownian dynamics simulation (eBDIMS), we generate trajectories connecting stable end-states that spontaneously sample the crystallographic motions, predicting the structures of known intermediates along the paths. We also show that the explored non-linear routes can delimit the lowest energy passages between end-states sampled by atomistic molecular dynamics. The integrative methodology presented here provides a powerful framework to extract and expand dynamic pathway information from the Protein Data Bank, as well as to validate sampling methods in general.

  14. Dual states estimation of a subsurface flow-transport coupled model using ensemble Kalman filtering

    KAUST Repository

    El Gharamti, Mohamad

    2013-10-01

    Modeling the spread of subsurface contaminants requires coupling a groundwater flow model with a contaminant transport model. Such coupling may provide accurate estimates of future subsurface hydrologic states if essential flow and contaminant data are assimilated in the model. Assuming perfect flow, an ensemble Kalman filter (EnKF) can be used for direct data assimilation into the transport model. This is, however, a crude assumption as flow models can be subject to many sources of uncertainty. If the flow is not accurately simulated, contaminant predictions will likely be inaccurate even after successive Kalman updates of the contaminant model with the data. The problem is better handled when both flow and contaminant states are concurrently estimated using the traditional joint state augmentation approach. In this paper, we introduce a dual estimation strategy for data assimilation into a one-way coupled system by treating the flow and the contaminant models separately while intertwining a pair of distinct EnKFs, one for each model. The presented strategy only deals with the estimation of state variables but it can also be used for state and parameter estimation problems. This EnKF-based dual state-state estimation procedure presents a number of novel features: (i) it allows for simultaneous estimation of both flow and contaminant states in parallel; (ii) it provides a time consistent sequential updating scheme between the two models (first flow, then transport); (iii) it simplifies the implementation of the filtering system; and (iv) it yields more stable and accurate solutions than does the standard joint approach. We conducted synthetic numerical experiments based on various time stepping and observation strategies to evaluate the dual EnKF approach and compare its performance with the joint state augmentation approach. Experimental results show that on average, the dual strategy could reduce the estimation error of the coupled states by 15% compared with the

  15. Wigner Function:from Ensemble Average of Density Operator to Its Matrix Element in Entangled Pure States

    Institute of Scientific and Technical Information of China (English)

    FANHong-Yi

    2002-01-01

    We show that the Wigner function W=Tr(Δρ)( an ensemble average of the density operator ρ,Δis the Wigner operator) can be expressed as a matrix element of ρ in the entangled pure states.In doing so,converting from quantum master equations to time-evolution equation of the Wigner functions seems direct and concise,The entangled states are defined in the enlarged Fock space with a fictitious freedom.

  16. Real Time Cardan Shaft State Estimation of High-Speed Train Based on Ensemble Empirical Mode Decomposition

    OpenAIRE

    Cai Yi; Jianhui Lin; Tengda Ruan; Yanping Li

    2015-01-01

    Due to the special location and structure of transmission system on high-speed train named CRH5, dynamic unbalance state of the cardan shaft will pose a threat to the train servicing safety, so effective methods that test the cardan shaft operating information and estimate the performance state in real time are needed. In this study a useful estimation method based on ensemble empirical mode decomposition (EEMD) is presented. By using this method, time-frequency characteristic of cardan shaft...

  17. Ghost-interaction correction in ensemble density-functional theory for excited states with and without range separation

    Science.gov (United States)

    Alam, Md. Mehboob; Knecht, Stefan; Fromager, Emmanuel

    2016-07-01

    Ensemble density-functional theory (eDFT) suffers from the so-called "ghost-interaction" error when approximate exchange-correlation functionals are used. In this work, we present a rigorous ghost-interaction correction (GIC) scheme in the context of range-separated eDFT. The method relies on an exact decomposition of the ensemble short-range exchange-correlation energy into a multideterminantal exact exchange term, which involves the long-range interacting ensemble density matrix, instead of the Kohn-Sham (KS) one, and a complementary density-functional correlation energy. A generalized adiabatic connection formula is derived for the latter. In order to perform practical calculations, the complementary correlation functional is simply modeled by its ground-state local density approximation (LDA), while long-range interacting ground- and excited-state wave functions are obtained self-consistently by combining a long-range configuration-interaction calculation with a short-range LDA potential. We show that the GIC reduces the curvature of approximate range-separated ensemble energies drastically while providing considerably more accurate excitation energies, even for charge-transfer and double excitations. Interestingly, the method performs well also in the context of standard KS-eDFT, which is recovered when the range-separation parameter is set to 0.

  18. Improving streamflow simulations in the Western United States via ensemble snow data assimilation

    Science.gov (United States)

    Huang, C.; Newman, A. J.; Clark, M. P.; Wood, A. W.; Zheng, X.

    2015-12-01

    The seasonal snowpack is a critical source of water in the western US. Past studies of snow data assimilation (DA) show that the better estimates of snow have the potential to enhance the precision of runoff prediction. In this study we select nine basins across the western United States, with a clear snow cover period and supporting snow water equivalent (SWE) measuring gauges, to test the ability of DA of SWE to improve streamflow simulations made with the coupled Snow17 and Sacramento Soil Moisture Accounting (SAC) models. We find that the relatively drier basins with little snow or runoff and basins with relatively complex snow runoff dynamics have less potential for improvement using SWE DA. For the higher potential basins, sensitivity analysis of the Ensemble Kalman Filter (EnKF) DA behavior shows that the correct estimation of SWE mean value is more important than accurately estimating of observed and forecasted error variance, which nonetheless can strongly influence SWE DA performance. This presentation describes key findings from the study, and also comments on different strategies for representing observed SWE, which typically differs from modeled SWE, in performing SWE DA.

  19. Solid-state ensemble of highly entangled photon sources at rubidium atomic transitions

    Science.gov (United States)

    Keil, Robert; Zopf, Michael; Chen, Yan; Höfer, Bianca; Zhang, Jiaxiang; Ding, Fei; Schmidt, Oliver G.

    2017-05-01

    Semiconductor InAs/GaAs quantum dots grown by the Stranski-Krastanov method are among the leading candidates for the deterministic generation of polarization-entangled photon pairs. Despite remarkable progress in the past 20 years, many challenges still remain for this material, such as the extremely low yield, the low degree of entanglement and the large wavelength distribution. Here, we show that with an emerging family of GaAs/AlGaAs quantum dots grown by droplet etching and nanohole infilling, it is possible to obtain a large ensemble of polarization-entangled photon emitters on a wafer without any post-growth tuning. Under pulsed resonant two-photon excitation, all measured quantum dots emit single pairs of entangled photons with ultra-high purity, high degree of entanglement and ultra-narrow wavelength distribution at rubidium transitions. Therefore, this material system is an attractive candidate for the realization of a solid-state quantum repeater--among many other key enabling quantum photonic elements.

  20. Changes of storm properties in the United States: Observations and multimodel ensemble projections

    Science.gov (United States)

    Jiang, Peng; Yu, Zhongbo; Gautam, Mahesh R.; Yuan, Feifei; Acharya, Kumud

    2016-07-01

    Changes in climate are likely to induce changes in precipitation characteristics including intensity, frequency, duration and patterns of events. In this paper, we evaluate the performance of multiple regional climate models (RCMs) in the North American Regional Climate Change Assessment Program (NARCCAP) to simulate storm properties including storm duration, inter-storm period, storm intensity, and within-storm patterns at eight locations in the continental US. We also investigate the future projections of them based on precipitation from NARCCAP historic runs and future runs. Results illustrate that NARCCAP RCMs are consistent with observed precipitation in the seasonal variation of storm duration and inter-storm period, but fail to simulate the magnitude. The ability to simulate the seasonal trend of average storm intensity varies among locations. Within-storm patterns from RCMs exhibit greater variability than from observed records. Comparisons between RCM-historic simulations and RCM projections indicate that there is a large variation in the future changes in storm properties. However, multi-model ensembles of the storm properties suggest that most regions of the United States will experience future changes in storm properties that includes shorter storm duration, longer inter-storm period, and larger average storm intensity.

  1. Ensemble Kalman Filtering with Residual Nudging: An Extension to State Estimation Problems with Nonlinear Observation Operators

    KAUST Repository

    Luo, Xiaodong

    2014-10-01

    The ensemble Kalman filter (EnKF) is an efficient algorithm for many data assimilation problems. In certain circumstances, however, divergence of the EnKF might be spotted. In previous studies, the authors proposed an observation-space-based strategy, called residual nudging, to improve the stability of the EnKF when dealing with linear observation operators. The main idea behind residual nudging is to monitor and, if necessary, adjust the distances (misfits) between the real observations and the simulated ones of the state estimates, in the hope that by doing so one may be able to obtain better estimation accuracy. In the present study, residual nudging is extended and modified in order to handle nonlinear observation operators. Such extension and modification result in an iterative filtering framework that, under suitable conditions, is able to achieve the objective of residual nudging for data assimilation problems with nonlinear observation operators. The 40-dimensional Lorenz-96 model is used to illustrate the performance of the iterative filter. Numerical results show that, while a normal EnKF may diverge with nonlinear observation operators, the proposed iterative filter remains stable and leads to reasonable estimation accuracy under various experimental settings.

  2. Solid-state ensemble of highly entangled photon sources at rubidium atomic transitions

    CERN Document Server

    Keil, Robert; Chen, Yan; Hoefer, Bianca; Zhang, Jiaxiang; Ding, Fei; Schmidt, Oliver G

    2016-01-01

    Semiconductor InAs/GaAs quantum dots grown by the Stranski-Krastanov method are among the leading candidates for the deterministic generation of polarization entangled photon pairs. Despite remarkable progress in the last twenty years, many challenges still remain for this material, such as the extremely low yield (<1% quantum dots can emit entangled photons), the low degree of entanglement, and the large wavelength distribution. Here we show that, with an emerging family of GaAs/AlGaAs quantum dots grown by droplet etching and nanohole infilling, it is possible to obtain a large ensemble (close to 100%) of polarization-entangled photon emitters on a wafer without any post-growth tuning. Under pulsed resonant two-photon excitation, all measured quantum dots emit single pairs of entangled photons with ultra-high purity, high degree of entanglement (fidelity up to F=0.91, with a record high concurrence C=0.90), and ultra-narrow wavelength distribution at rubidium transitions. Therefore, a solid-state quantum...

  3. Model-independent interpretation of NMR relaxation data for unfolded proteins: the acid-denatured state of ACBP

    DEFF Research Database (Denmark)

    Modig, Kristofer; Poulsen, Flemming

    2008-01-01

    We have investigated the acid-unfolded state of acyl-coenzyme A binding protein (ACBP) using (15)N laboratory frame nuclear magnetic resonance (NMR) relaxation experiments at three magnetic field strengths. The data have been analyzed using standard model-free fitting and models involving....... The analysis also shows that the relaxation data are consistent with and complementary to information obtained from other parameters, especially secondary chemical shifts and residual dipolar couplings, and strengthens the conclusions of previous observations that three out of the four regions that form...

  4. Evaluation of snow data assimilation using the ensemble Kalman filter for seasonal streamflow prediction in the western United States

    Science.gov (United States)

    Huang, Chengcheng; Newman, Andrew J.; Clark, Martyn P.; Wood, Andrew W.; Zheng, Xiaogu

    2017-01-01

    In this study, we examine the potential of snow water equivalent data assimilation (DA) using the ensemble Kalman filter (EnKF) to improve seasonal streamflow predictions. There are several goals of this study. First, we aim to examine some empirical aspects of the EnKF, namely the observational uncertainty estimates and the observation transformation operator. Second, we use a newly created ensemble forcing dataset to develop ensemble model states that provide an estimate of model state uncertainty. Third, we examine the impact of varying the observation and model state uncertainty on forecast skill. We use basins from the Pacific Northwest, Rocky Mountains, and California in the western United States with the coupled Snow-17 and Sacramento Soil Moisture Accounting (SAC-SMA) models. We find that most EnKF implementation variations result in improved streamflow prediction, but the methodological choices in the examined components impact predictive performance in a non-uniform way across the basins. Finally, basins with relatively higher calibrated model performance (> 0.80 NSE) without DA generally have lesser improvement with DA, while basins with poorer historical model performance show greater improvements.

  5. Wigner Function:from Ensemble Average of Density Operator to Its One Matrix Element in Entangled Pure States

    Institute of Scientific and Technical Information of China (English)

    FAN Hong-Yi

    2002-01-01

    We show that the Wigner function W = Tr(△ρ) (an ensemble average of the density operator ρ, △ is theWigner operator) can be expressed as a matrix element of ρ in the entangled pure states. In doing so, converting fromquantum master equations to time-evolution equation of the Wigner functions seems direct and concise. The entangledstates are defined in the enlarged Fock space with a fictitious freedom.

  6. A One-Step-Ahead Smoothing-Based Joint Ensemble Kalman Filter for State-Parameter Estimation of Hydrological Models

    KAUST Repository

    El Gharamti, Mohamad

    2015-11-26

    The ensemble Kalman filter (EnKF) recursively integrates field data into simulation models to obtain a better characterization of the model’s state and parameters. These are generally estimated following a state-parameters joint augmentation strategy. In this study, we introduce a new smoothing-based joint EnKF scheme, in which we introduce a one-step-ahead smoothing of the state before updating the parameters. Numerical experiments are performed with a two-dimensional synthetic subsurface contaminant transport model. The improved performance of the proposed joint EnKF scheme compared to the standard joint EnKF compensates for the modest increase in the computational cost.

  7. Are Charge-State Distributions a Reliable Tool Describing Molecular Ensembles of Intrinsically Disordered Proteins by Native MS?

    Science.gov (United States)

    Natalello, Antonino; Santambrogio, Carlo; Grandori, Rita

    2016-10-01

    Native mass spectrometry (MS) has become a central tool of structural proteomics, but its applicability to the peculiar class of intrinsically disordered proteins (IDPs) is still object of debate. IDPs lack an ordered tridimensional structure and are characterized by high conformational plasticity. Since they represent valuable targets for cancer and neurodegeneration research, there is an urgent need of methodological advances for description of the conformational ensembles populated by these proteins in solution. However, structural rearrangements during electrospray-ionization (ESI) or after the transfer to the gas phase could affect data obtained by native ESI-MS. In particular, charge-state distributions (CSDs) are affected by protein conformation inside ESI droplets, while ion mobility (IM) reflects protein conformation in the gas phase. This review focuses on the available evidence relating IDP solution ensembles with CSDs, trying to summarize cases of apparent consistency or discrepancy. The protein-specificity of ionization patterns and their responses to ligands and buffer conditions suggests that CSDs are imprinted to protein structural features also in the case of IDPs. Nevertheless, it seems that these proteins are more easily affected by electrospray conditions, leading in some cases to rearrangements of the conformational ensembles.

  8. Are Charge-State Distributions a Reliable Tool Describing Molecular Ensembles of Intrinsically Disordered Proteins by Native MS?

    Science.gov (United States)

    Natalello, Antonino; Santambrogio, Carlo; Grandori, Rita

    2017-01-01

    Native mass spectrometry (MS) has become a central tool of structural proteomics, but its applicability to the peculiar class of intrinsically disordered proteins (IDPs) is still object of debate. IDPs lack an ordered tridimensional structure and are characterized by high conformational plasticity. Since they represent valuable targets for cancer and neurodegeneration research, there is an urgent need of methodological advances for description of the conformational ensembles populated by these proteins in solution. However, structural rearrangements during electrospray-ionization (ESI) or after the transfer to the gas phase could affect data obtained by native ESI-MS. In particular, charge-state distributions (CSDs) are affected by protein conformation inside ESI droplets, while ion mobility (IM) reflects protein conformation in the gas phase. This review focuses on the available evidence relating IDP solution ensembles with CSDs, trying to summarize cases of apparent consistency or discrepancy. The protein-specificity of ionization patterns and their responses to ligands and buffer conditions suggests that CSDs are imprinted to protein structural features also in the case of IDPs. Nevertheless, it seems that these proteins are more easily affected by electrospray conditions, leading in some cases to rearrangements of the conformational ensembles.

  9. Stability of collagen during denaturation.

    Science.gov (United States)

    Penkova, R; Goshev, I; Gorinstein, S; Nedkov, P

    1999-05-01

    The stability of calf skin collagen (CSC) type I during thermal and chemical denaturation in the presence of glycerol was investigated. Thermal denaturation of type I collagen was performed in the presence of glycerol or in combination with urea and sodium chloride. The denaturation curves obtained in the presence of urea or sodium chloride retained their original shape without glycerol. These curves were shifted upward proportionally to the glycerol concentration in the reaction medium. This means that glycerol and the denaturants act independently. The explanation is based on the difference in the mechanism of their action on the collagen molecule.

  10. DART: A Community Facility Providing State-of-the-Art, Efficient Ensemble Data Assimilation for Large (Coupled) Geophysical Models

    Science.gov (United States)

    Hoar, T. J.; Anderson, J. L.; Collins, N.; Kershaw, H.; Hendricks, J.; Raeder, K.; Mizzi, A. P.; Barré, J.; Gaubert, B.; Madaus, L. E.; Aydogdu, A.; Raeder, J.; Arango, H.; Moore, A. M.; Edwards, C. A.; Curchitser, E. N.; Escudier, R.; Dussin, R.; Bitz, C. M.; Zhang, Y. F.; Shrestha, P.; Rosolem, R.; Rahman, M.

    2016-12-01

    Strongly-coupled ensemble data assimilation with multiple high-resolution model components requires massive state vectors which need to be efficiently stored and accessed throughout the assimilation process. Supercomputer architectures are tending towards increasing the number of cores per node but have the same or less memory per node. Recent advances in the Data Assimilation Research Testbed (DART), a freely-available community ensemble data assimilation facility that works with dozens of large geophysical models, have addressed the need to run with a smaller memory footprint on a higher node count by utilizing MPI-2 one-sided communication to do non-blocking asynchronous access of distributed data. DART runs efficiently on many computational platforms ranging from laptops through thousands of cores on the newest supercomputers. Benefits of the new DART implementation will be shown. In addition, overviews of the most recently supported models will be presented: CAM-CHEM, WRF-CHEM, CM1, OpenGGCM, FESOM, ROMS, CICE5, TerrSysMP (COSMO, CLM, ParFlow), JULES, and CABLE. DART provides a comprehensive suite of software, documentation, and tutorials that can be used for ensemble data assimilation research, operations, and education. Scientists and software engineers at NCAR are available to support DART users who want to use existing DART products or develop their own applications. Current DART users range from university professors teaching data assimilation, to individual graduate students working with simple models, through national laboratories and state agencies doing operational prediction with large state-of-the-art models.

  11. Ground State Properties of Many-Body Systems in the Two-Body Random Ensemble and Random Matrix Theory

    CERN Document Server

    Santos, L F; Jacquod, P; Kusnezov, Dimitri; Jacquod, Ph.

    2002-01-01

    We explore generic ground-state and low-energy statistical properties of many-body bosonic and fermionic one- and two-body random ensembles (TBRE) in the dense limit, and contrast them with Random Matrix Theory (RMT). Weak differences in distribution tails can be attributed to the regularity or chaoticity of the corresponding Hamiltonians rather than the particle statistics. We finally show the universality of the distribution of the angular momentum gap between the lowest energy levels in consecutive J-sectors for the four models considered.

  12. ENSO feedbacks and their relationships with the mean state in a flux adjusted ensemble

    Science.gov (United States)

    Ferrett, Samantha; Collins, Matthew

    2016-11-01

    The El Niño Southern Oscillation (ENSO) is governed by a combination of amplifying and damping ocean-atmosphere feedbacks in the equatorial Pacific. Here we quantify these feedbacks in a flux adjusted HadCM3 perturbed physics ensemble under present day conditions and a future emissions scenario using the Bjerknes Stability Index (BJ index). Relationships between feedbacks and both the present day biases and responses under climate change of the mean equatorial Pacific climate are investigated. Despite minimised mean sea surface temperature biases through flux adjustment, the important dominant ENSO feedbacks still show biases with respect to observed feedbacks and inter-ensemble diversity. The dominant positive thermocline and zonal advective feedbacks are found to be weaker in ensemble members with stronger mean zonal advection. This is due to a weaker sensitivity of the thermocline slope and zonal surface ocean currents in the east Pacific to surface wind stress anomalies. A drier west Pacific is also found to be linked to weakened shortwave and latent heat flux damping, suggesting a link between ENSO characteristics and the hydrological cycle. In contrast to previous studies using the BJ index that find positive relationships between the index and ENSO amplitude, here they are weakly or negatively correlated, both for present day conditions and for projected differences. This is caused by strong thermodynamic damping which dominates over positive feedbacks, which alone approximate ENSO amplitude well. While the BJ index proves useful for individual linear feedback analysis, we urge caution in using the total linear BJ index alone to assess the reasons for ENSO amplitude biases and its future change in models.

  13. The X-like shaped spatiotemporal structure of the biphoton entangled state in a cold two-level atomic ensemble

    Science.gov (United States)

    Zhang, Dasen; Zhang, Zhiming

    2017-01-01

    We study the spatiotemporal structure of the biphoton entangled state generated by the four-wave mixing (FWM) process in a cold two-level atomic ensemble. We analyze, for the first time, the X-like shaped structure of the biphoton entangled state and the geometry of the biphoton correlation for different lengths and densities of the cold atomic ensemble. The propagation equations of the photon pairs generated from FWM process are derived in a spatiotemporal framework. By means of the input-output relations of the propagation equations, the biphoton amplitude function is obtained in a spatiotemporal domain. In the given frequency range, the biphoton amplitude displays an X-like shaped geometry, nonfactorizable in the space-time domain. Such an X-like shaped spatiotemporal structure is caused by the phase matching and the FWM gain. The former leads to the X-like shaped envelope of the biphoton correlation, while the latter gives rise to the oscillations around the X-like shaped envelope. PMID:28218235

  14. The X-like shaped spatiotemporal structure of the biphoton entangled state in a cold two-level atomic ensemble.

    Science.gov (United States)

    Zhang, Dasen; Zhang, Zhiming

    2017-02-20

    We study the spatiotemporal structure of the biphoton entangled state generated by the four-wave mixing (FWM) process in a cold two-level atomic ensemble. We analyze, for the first time, the X-like shaped structure of the biphoton entangled state and the geometry of the biphoton correlation for different lengths and densities of the cold atomic ensemble. The propagation equations of the photon pairs generated from FWM process are derived in a spatiotemporal framework. By means of the input-output relations of the propagation equations, the biphoton amplitude function is obtained in a spatiotemporal domain. In the given frequency range, the biphoton amplitude displays an X-like shaped geometry, nonfactorizable in the space-time domain. Such an X-like shaped spatiotemporal structure is caused by the phase matching and the FWM gain. The former leads to the X-like shaped envelope of the biphoton correlation, while the latter gives rise to the oscillations around the X-like shaped envelope.

  15. Ensemble Methods

    Science.gov (United States)

    Re, Matteo; Valentini, Giorgio

    2012-03-01

    Ensemble methods are statistical and computational learning procedures reminiscent of the human social learning behavior of seeking several opinions before making any crucial decision. The idea of combining the opinions of different "experts" to obtain an overall “ensemble” decision is rooted in our culture at least from the classical age of ancient Greece, and it has been formalized during the Enlightenment with the Condorcet Jury Theorem[45]), which proved that the judgment of a committee is superior to those of individuals, provided the individuals have reasonable competence. Ensembles are sets of learning machines that combine in some way their decisions, or their learning algorithms, or different views of data, or other specific characteristics to obtain more reliable and more accurate predictions in supervised and unsupervised learning problems [48,116]. A simple example is represented by the majority vote ensemble, by which the decisions of different learning machines are combined, and the class that receives the majority of “votes” (i.e., the class predicted by the majority of the learning machines) is the class predicted by the overall ensemble [158]. In the literature, a plethora of terms other than ensembles has been used, such as fusion, combination, aggregation, and committee, to indicate sets of learning machines that work together to solve a machine learning problem [19,40,56,66,99,108,123], but in this chapter we maintain the term ensemble in its widest meaning, in order to include the whole range of combination methods. Nowadays, ensemble methods represent one of the main current research lines in machine learning [48,116], and the interest of the research community on ensemble methods is witnessed by conferences and workshops specifically devoted to ensembles, first of all the multiple classifier systems (MCS) conference organized by Roli, Kittler, Windeatt, and other researchers of this area [14,62,85,149,173]. Several theories have been

  16. Spontaneous creation and persistence of ground-state coherence in a resonantly driven intra-cavity atomic ensemble

    CERN Document Server

    Norris, D G; Orozco, L A; Barberis-Blostein, P; Carmichael, H J; 10.1103/PhysRevA.86.053816

    2012-01-01

    The spontaneous creation and persistence of ground-state coherence in an ensemble of intracavity Rb atoms has been observed as a quantum beat. Our system realizes a quantum eraser, where the detection of a first photon prepares a superposition of ground-state Zeeman sublevels, while detection of a second erases the stored information. Beats appear in the time-delayed photon-photon coincidence rate (intensity correlation function). We study the beats theoretically and experimentally as a function of system parameters, and find them remarkably robust against perturbations such as spontaneous emission. Although beats arise most simply through single-atom-mediated quantum interference, scattering pathways involving pairs of atoms interfere also in our intracavity experiment. We present a detailed model which identifies all sources of interference and accounts for experimental realities such as imperfect pre-pumping of the atomic beam, cavity birefringence, and the transit of atoms across the cavity mode.

  17. Comparison of chemical and thermal protein denaturation by combination of computational and experimental approaches. II

    Science.gov (United States)

    Wang, Qian; Christiansen, Alexander; Samiotakis, Antonios; Wittung-Stafshede, Pernilla; Cheung, Margaret S.

    2011-11-01

    Chemical and thermal denaturation methods have been widely used to investigate folding processes of proteins in vitro. However, a molecular understanding of the relationship between these two perturbation methods is lacking. Here, we combined computational and experimental approaches to investigate denaturing effects on three structurally different proteins. We derived a linear relationship between thermal denaturation at temperature Tb and chemical denaturation at another temperature Tu using the stability change of a protein (ΔG). For this, we related the dependence of ΔG on temperature, in the Gibbs-Helmholtz equation, to that of ΔG on urea concentration in the linear extrapolation method, assuming that there is a temperature pair from the urea (Tu) and the aqueous (Tb) ensembles that produces the same protein structures. We tested this relationship on apoazurin, cytochrome c, and apoflavodoxin using coarse-grained molecular simulations. We found a linear correlation between the temperature for a particular structural ensemble in the absence of urea, Tb, and the temperature of the same structural ensemble at a specific urea concentration, Tu. The in silico results agreed with in vitro far-UV circular dichroism data on apoazurin and cytochrome c. We conclude that chemical and thermal unfolding processes correlate in terms of thermodynamics and structural ensembles at most conditions; however, deviations were found at high concentrations of denaturant.

  18. NYYD Ensemble

    Index Scriptorium Estoniae

    2002-01-01

    NYYD Ensemble'i duost Traksmann - Lukk E.-S. Tüüri teosega "Symbiosis", mis on salvestatud ka hiljuti ilmunud NYYD Ensemble'i CDle. 2. märtsil Rakvere Teatri väikeses saalis ja 3. märtsil Rotermanni Soolalaos, kavas Tüür, Kaumann, Berio, Reich, Yun, Hauta-aho, Buckinx

  19. Microwave-enhanced folding and denaturation of globular proteins

    DEFF Research Database (Denmark)

    Bohr, Henrik; Bohr, Jakob

    2000-01-01

    It is shown that microwave irradiation can affect the kinetics of the folding process of some globular proteins, especially beta-lactoglobulin. At low temperature the folding from the cold denatured phase of the protein is enhanced, while at a higher temperature the denaturation of the protein from...... its folded state is enhanced. In the latter case, a negative temperature gradient is needed for the denaturation process, suggesting that the effects of the microwaves are nonthermal. This supports the notion that coherent topological excitations can exist in proteins. The application of microwaves...

  20. pE-DB: a database of structural ensembles of intrinsically disordered and of unfolded proteins

    Science.gov (United States)

    Varadi, Mihaly; Kosol, Simone; Lebrun, Pierre; Valentini, Erica; Blackledge, Martin; Dunker, A. Keith; Felli, Isabella C.; Forman-Kay, Julie D.; Kriwacki, Richard W.; Pierattelli, Roberta; Sussman, Joel; Svergun, Dmitri I.; Uversky, Vladimir N.; Vendruscolo, Michele; Wishart, David; Wright, Peter E.; Tompa, Peter

    2014-01-01

    The goal of pE-DB (http://pedb.vib.be) is to serve as an openly accessible database for the deposition of structural ensembles of intrinsically disordered proteins (IDPs) and of denatured proteins based on nuclear magnetic resonance spectroscopy, small-angle X-ray scattering and other data measured in solution. Owing to the inherent flexibility of IDPs, solution techniques are particularly appropriate for characterizing their biophysical properties, and structural ensembles in agreement with these data provide a convenient tool for describing the underlying conformational sampling. Database entries consist of (i) primary experimental data with descriptions of the acquisition methods and algorithms used for the ensemble calculations, and (ii) the structural ensembles consistent with these data, provided as a set of models in a Protein Data Bank format. PE-DB is open for submissions from the community, and is intended as a forum for disseminating the structural ensembles and the methodologies used to generate them. While the need to represent the IDP structures is clear, methods for determining and evaluating the structural ensembles are still evolving. The availability of the pE-DB database is expected to promote the development of new modeling methods and leads to a better understanding of how function arises from disordered states. PMID:24174539

  1. Real Time Cardan Shaft State Estimation of High-Speed Train Based on Ensemble Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    Cai Yi

    2015-01-01

    Full Text Available Due to the special location and structure of transmission system on high-speed train named CRH5, dynamic unbalance state of the cardan shaft will pose a threat to the train servicing safety, so effective methods that test the cardan shaft operating information and estimate the performance state in real time are needed. In this study a useful estimation method based on ensemble empirical mode decomposition (EEMD is presented. By using this method, time-frequency characteristic of cardan shaft can be extracted effectively by separating the gearbox vibration acceleration data. Preliminary analysis suggests that the pinions rotating vibration separated from gearbox vibration by EEMD can be used as important assessment basis to estimate cardan shaft state. With two sets gearbox vibration signals collected from the in-service train at different running speed, the comparative analysis verifies that the proposed method has high effectiveness for cardan-shaft state estimate. Of course, it needs further research to quantify the performance state of cardan shaft based on this method.

  2. Contrast and phase-shift of a trapped atom interferometer using a thermal ensemble with internal state labelling

    CERN Document Server

    Dupont-Nivet, M; Schwartz, S

    2016-01-01

    We report a theoretical study of a double-well Ramsey interferometer using internal state labelling. We consider the use of a thermal ensemble of cold atoms rather than a Bose-Einstein condensate to minimize the effects of atomic interactions. To maintain a satisfactory level of coherence in this case, a high degree of symmetry is required between the two arms of the interferometer. Assuming that the splitting and recombination processes are adiabatic, we theoretically derive the phase-shift and the contrast of such an interferometer in the presence of gravity or an acceleration field. We also consider using a "shortcut to adiabaticity" protocol to speed up the splitting process and discuss how such a procedure affects the phase shift and contrast. We find that the two procedures lead to phase-shifts of the same form.

  3. Hysteresis in pressure-driven DNA denaturation.

    Directory of Open Access Journals (Sweden)

    Enrique Hernández-Lemus

    Full Text Available In the past, a great deal of attention has been drawn to thermal driven denaturation processes. In recent years, however, the discovery of stress-induced denaturation, observed at the one-molecule level, has revealed new insights into the complex phenomena involved in the thermo-mechanics of DNA function. Understanding the effect of local pressure variations in DNA stability is thus an appealing topic. Such processes as cellular stress, dehydration, and changes in the ionic strength of the medium could explain local pressure changes that will affect the molecular mechanics of DNA and hence its stability. In this work, a theory that accounts for hysteresis in pressure-driven DNA denaturation is proposed. We here combine an irreversible thermodynamic approach with an equation of state based on the Poisson-Boltzmann cell model. The latter one provides a good description of the osmotic pressure over a wide range of DNA concentrations. The resulting theoretical framework predicts, in general, the process of denaturation and, in particular, hysteresis curves for a DNA sequence in terms of system parameters such as salt concentration, density of DNA molecules and temperature in addition to structural and configurational states of DNA. Furthermore, this formalism can be naturally extended to more complex situations, for example, in cases where the host medium is made up of asymmetric salts or in the description of the (helical-like charge distribution along the DNA molecule. Moreover, since this study incorporates the effect of pressure through a thermodynamic analysis, much of what is known from temperature-driven experiments will shed light on the pressure-induced melting issue.

  4. Reducing the allowable kinetic space by constructing ensemble of dynamic models with the same steady-state flux.

    Science.gov (United States)

    Tan, Yikun; Rivera, Jimmy G Lafontaine; Contador, Carolina A; Asenjo, Juan A; Liao, James C

    2011-01-01

    Dynamic models of metabolism are instrumental for gaining insight and predicting possible outcomes of perturbations. Current approaches start from the selection of lumped enzyme kinetics and determine the parameters within a large parametric space. However, kinetic parameters are often unknown and obtaining these parameters requires detailed characterization of enzyme kinetics. In many cases, only steady-state fluxes are measured or estimated, but these data have not been utilized to construct dynamic models. Here, we extend the previously developed Ensemble Modeling methodology by allowing various kinetic rate expressions and employing a more efficient solution method for steady states. We show that anchoring the dynamic models to the same flux reduces the allowable parameter space significantly such that sampling of high dimensional kinetic parameters becomes meaningful. The methodology enables examination of the properties of the model's structure, including multiple steady states. Screening of models based on limited steady-state fluxes or metabolite profiles reduces the parameter space further and the remaining models become increasingly predictive. We use both succinate overproduction and central carbon metabolism in Escherichia coli as examples to demonstrate these results. Published by Elsevier Inc.

  5. Dual state-parameter optimal estimation of one-dimensional open channel model using ensemble Kalman filter

    Institute of Scientific and Technical Information of China (English)

    LAI Rui-xun; FANG Hong-wei; HE Guo-jian; YU Xin; YANG Ming; WANG Ming

    2013-01-01

    In this paper,both state variables and parameters of one-dimensional open channel model are estimated using a framework of the Ensemble Kalman Filter (EnKF).Compared with observation,the predicted accuracy of water level and discharge are improved while the parameters of the model are identified simultaneously.With the principles of the EnKF,a state-space description of the Saint-Venant equation is constructed by perturbing the measurements with Gaussian error distribution.At the same time,the roughness,one of the key parameters in one-dimensional open channel,is also considered as a state variable to identify its value dynamically.The updated state variables and the parameters are then used as the initial values of the next time step to continue the assimilation process.The usefulness and the capability of the dual EnKF are demonstrated in the lower Yellow River during the water-sediment regulation in 2009.In the optimization process,the errors between the prediction and the observation are analyzed,and the rationale of inverse roughness is discussed.It is believed that (1) the flexible approach of the dual EnKF can improve the accuracy of predicting water level and discharge,(2) it provides a probabilistic way to identify the model error which is feasible to implement but hard to handle in other filter systems,and (3) it is practicable for river engineering and management.

  6. An Iterative Ensemble Kalman Filter with One-Step-Ahead Smoothing for State-Parameters Estimation of Contaminant Transport Models

    KAUST Repository

    Gharamti, M. E.

    2015-05-11

    The ensemble Kalman filter (EnKF) is a popular method for state-parameters estimation of subsurface flow and transport models based on field measurements. The common filtering procedure is to directly update the state and parameters as one single vector, which is known as the Joint-EnKF. In this study, we follow the one-step-ahead smoothing formulation of the filtering problem, to derive a new joint-based EnKF which involves a smoothing step of the state between two successive analysis steps. The new state-parameters estimation scheme is derived in a consistent Bayesian filtering framework and results in separate update steps for the state and the parameters. This new algorithm bears strong resemblance with the Dual-EnKF, but unlike the latter which first propagates the state with the model then updates it with the new observation, the proposed scheme starts by an update step, followed by a model integration step. We exploit this new formulation of the joint filtering problem and propose an efficient model-integration-free iterative procedure on the update step of the parameters only for further improved performances. Numerical experiments are conducted with a two-dimensional synthetic subsurface transport model simulating the migration of a contaminant plume in a heterogenous aquifer domain. Contaminant concentration data are assimilated to estimate both the contaminant state and the hydraulic conductivity field. Assimilation runs are performed under imperfect modeling conditions and various observational scenarios. Simulation results suggest that the proposed scheme efficiently recovers both the contaminant state and the aquifer conductivity, providing more accurate estimates than the standard Joint and Dual EnKFs in all tested scenarios. Iterating on the update step of the new scheme further enhances the proposed filter’s behavior. In term of computational cost, the new Joint-EnKF is almost equivalent to that of the Dual-EnKF, but requires twice more model

  7. Canonical-ensemble state-averaged complete active space self-consistent field (SA-CASSCF) strategy for problems with more diabatic than adiabatic states: Charge-bond resonance in monomethine cyanines

    Science.gov (United States)

    Olsen, Seth

    2015-01-01

    This paper reviews basic results from a theory of the a priori classical probabilities (weights) in state-averaged complete active space self-consistent field (SA-CASSCF) models. It addresses how the classical probabilities limit the invariance of the self-consistency condition to transformations of the complete active space configuration interaction (CAS-CI) problem. Such transformations are of interest for choosing representations of the SA-CASSCF solution that are diabatic with respect to some interaction. I achieve the known result that a SA-CASSCF can be self-consistently transformed only within degenerate subspaces of the CAS-CI ensemble density matrix. For uniformly distributed ("microcanonical") SA-CASSCF ensembles, self-consistency is invariant to any unitary CAS-CI transformation that acts locally on the ensemble support. Most SA-CASSCF applications in current literature are microcanonical. A problem with microcanonical SA-CASSCF models for problems with "more diabatic than adiabatic" states is described. The problem is that not all diabatic energies and couplings are self-consistently resolvable. A canonical-ensemble SA-CASSCF strategy is proposed to solve the problem. For canonical-ensemble SA-CASSCF, the equilibrated ensemble is a Boltzmann density matrix parametrized by its own CAS-CI Hamiltonian and a Lagrange multiplier acting as an inverse "temperature," unrelated to the physical temperature. Like the convergence criterion for microcanonical-ensemble SA-CASSCF, the equilibration condition for canonical-ensemble SA-CASSCF is invariant to transformations that act locally on the ensemble CAS-CI density matrix. The advantage of a canonical-ensemble description is that more adiabatic states can be included in the support of the ensemble without running into convergence problems. The constraint on the dimensionality of the problem is relieved by the introduction of an energy constraint. The method is illustrated with a complete active space valence

  8. Canonical-ensemble state-averaged complete active space self-consistent field (SA-CASSCF) strategy for problems with more diabatic than adiabatic states: Charge-bond resonance in monomethine cyanines

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Seth, E-mail: seth.olsen@uq.edu.au [School of Mathematics and Physics, The University of Queensland, Brisbane QLD 4072 (Australia)

    2015-01-28

    This paper reviews basic results from a theory of the a priori classical probabilities (weights) in state-averaged complete active space self-consistent field (SA-CASSCF) models. It addresses how the classical probabilities limit the invariance of the self-consistency condition to transformations of the complete active space configuration interaction (CAS-CI) problem. Such transformations are of interest for choosing representations of the SA-CASSCF solution that are diabatic with respect to some interaction. I achieve the known result that a SA-CASSCF can be self-consistently transformed only within degenerate subspaces of the CAS-CI ensemble density matrix. For uniformly distributed (“microcanonical”) SA-CASSCF ensembles, self-consistency is invariant to any unitary CAS-CI transformation that acts locally on the ensemble support. Most SA-CASSCF applications in current literature are microcanonical. A problem with microcanonical SA-CASSCF models for problems with “more diabatic than adiabatic” states is described. The problem is that not all diabatic energies and couplings are self-consistently resolvable. A canonical-ensemble SA-CASSCF strategy is proposed to solve the problem. For canonical-ensemble SA-CASSCF, the equilibrated ensemble is a Boltzmann density matrix parametrized by its own CAS-CI Hamiltonian and a Lagrange multiplier acting as an inverse “temperature,” unrelated to the physical temperature. Like the convergence criterion for microcanonical-ensemble SA-CASSCF, the equilibration condition for canonical-ensemble SA-CASSCF is invariant to transformations that act locally on the ensemble CAS-CI density matrix. The advantage of a canonical-ensemble description is that more adiabatic states can be included in the support of the ensemble without running into convergence problems. The constraint on the dimensionality of the problem is relieved by the introduction of an energy constraint. The method is illustrated with a complete active space

  9. "A space-time ensemble Kalman filter for state and parameter estimation of groundwater transport models"

    Science.gov (United States)

    Briseño, Jessica; Herrera, Graciela S.

    2010-05-01

    Herrera (1998) proposed a method for the optimal design of groundwater quality monitoring networks that involves space and time in a combined form. The method was applied later by Herrera et al (2001) and by Herrera and Pinder (2005). To get the estimates of the contaminant concentration being analyzed, this method uses a space-time ensemble Kalman filter, based on a stochastic flow and transport model. When the method is applied, it is important that the characteristics of the stochastic model be congruent with field data, but, in general, it is laborious to manually achieve a good match between them. For this reason, the main objective of this work is to extend the space-time ensemble Kalman filter proposed by Herrera, to estimate the hydraulic conductivity, together with hydraulic head and contaminant concentration, and its application in a synthetic example. The method has three steps: 1) Given the mean and the semivariogram of the natural logarithm of hydraulic conductivity (ln K), random realizations of this parameter are obtained through two alternatives: Gaussian simulation (SGSim) and Latin Hypercube Sampling method (LHC). 2) The stochastic model is used to produce hydraulic head (h) and contaminant (C) realizations, for each one of the conductivity realizations. With these realization the mean of ln K, h and C are obtained, for h and C, the mean is calculated in space and time, and also the cross covariance matrix h-ln K-C in space and time. The covariance matrix is obtained averaging products of the ln K, h and C realizations on the estimation points and times, and the positions and times with data of the analyzed variables. The estimation points are the positions at which estimates of ln K, h or C are gathered. In an analogous way, the estimation times are those at which estimates of any of the three variables are gathered. 3) Finally the ln K, h and C estimate are obtained using the space-time ensemble Kalman filter. The realization mean for each one

  10. Preparation of pseudopure state in nuclear spin ensemble using CNOT gates combination

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Nuclear magnetic resonance (NMR) is one of the experimental schemes for quantum computation. Most initial state of quantum algorithm in NMR computation is the pseudopure state. Until now, there are several methods to prepare pseudopure state. This note, based on the idea of controlled-not (CNOT) gates combination, has analyzed the characteristics of this method in the odd- and even-qubit system. Also, we have designed the pulse sequence for a 4-qubit sample to obtain pseudopure state, and realized it in the experiment. This method reduces the complexity of experiment and gives a high signal-to-noise (S/N) ratio.

  11. Statistical mechanics of thermal denaturation of DNA oligomers

    Indian Academy of Sciences (India)

    Navin Singh; Yashwant Singh

    2003-08-01

    Double stranded DNA chain is known to have non-trivial elasticity. We study the effect of this elasticity on the denaturation profile of DNA oligomer by constraining one base pair at one end of the oligomer to remain in unstretched (or intact) state. The effect of this constraint on the denaturation profile of the oligomer has been calculated using the Peyrard–Bishop Hamiltonian. The denaturation profile is found to be very different from the free (i.e. without the constraint) oligomer. We have also examined how this constraint affects the denaturation profile of the oligomer having a segment of defect sites located at different parts of the chain.

  12. Accessing many-body localized states through the Generalized Gibbs Ensemble

    OpenAIRE

    Inglis, Stephen; Pollet, Lode

    2016-01-01

    We show how the thermodynamic properties of large many-body localized systems can be studied using quantum Monte Carlo simulations. To this end we devise a heuristic way of constructing local integrals of motion of very high quality, which are added to the Hamiltonian in conjunction with Lagrange multipliers. The ground state simulation of the shifted Hamiltonian corresponds to a high-energy state of the original Hamiltonian in case of exactly known local integrals of motion. We can show that...

  13. Many-body Systems Interacting via a Two-body Random Ensemble; 1, Angular Momentum distribution in the ground states

    CERN Document Server

    Zhao, Y M; Yoshinaga, N

    2002-01-01

    In this paper, we discuss the angular momentum distribution in the ground states of many-body systems interacting via a two-body random ensemble. Beginning with a few simple examples, a simple approach to predict P(I)'s, angular momenta I ground state (g.s.) probabilities, of a few solvable cases, such as fermions in a small single-j shell and d boson systems, is given. This method is generalized to predict P(I)'s of more complicated cases, such as even or odd number of fermions in a large single-j shell or a many-j shell, d-boson, sd-boson or sdg-boson systems, etc. By this method we are able to tell which interactions are essential to produce a sizable P(I) in a many-body system. The g.s. probability of maximum angular momentum $I_{max}$ is discussed. An argument on the microscopic foundation of our approach, and certain matrix elements which are useful to understand the observed regularities, are also given or addressed in detail. The low seniority chain of 0 g.s. by using the same set of two-body interact...

  14. Using Analysis State to Construct a Forecast Error Covariance Matrix in Ensemble Kalman Filter Assimilation

    Institute of Scientific and Technical Information of China (English)

    ZHENG Xiaogu; WU Guocan; ZHANG Shupeng; LIANG Xiao; DAI Yongjiu; LI Yong

    2013-01-01

    Correctly estimating the forecast error covariance matrix is a key step in any data assimilation scheme.If it is not correctly estimated,the assimilated states could be far from the true states.A popular method to address this problem is error covariance matrix inflation.That is,to multiply the forecast error covariance matrix by an appropriate factor.In this paper,analysis states are used to construct the forecast error covariance matrix and an adaptive estimation procedure associated with the error covariance matrix inflation technique is developed.The proposed assimilation scheme was tested on the Lorenz-96 model and 2D Shallow Water Equation model,both of which are associated with spatially correlated observational systems.The experiments showed that by introducing the proposed structure of the forecast error covariance matrix and applying its adaptive estimation procedure,the assimilation results were further improved.

  15. Multiscale Approach to the Determination of the Photoactive Yellow Protein Signaling State Ensemble

    NARCIS (Netherlands)

    Rohrdanz, M.A.; Zheng, W.; Lambeth, B.; Vreede, J.; Clementi, C.

    2014-01-01

    The nature of the optical cycle of photoactive yellow protein (PYP) makes its elucidation challenging for both experiment and theory. The long transition times render conventional simulation methods ineffective, and yet the short signaling-state lifetime makes experimental data difficult to obtain a

  16. Exact ensemble density functional theory for excited states in a model system: investigating the weight dependence of the correlation energy

    CERN Document Server

    Deur, Killian; Fromager, Emmanuel

    2016-01-01

    Ensemble density functional theory (eDFT) is an exact time-independent alternative to time-dependent DFT (TD-DFT) for the calculation of excitation energies. Despite its formal simplicity and advantages in contrast to TD-DFT (multiple excitations, for example, can be easily taken into account in an ensemble), eDFT is not standard which is essentially due to the lack of reliable approximate exchange-correlation (xc) functionals for ensembles. Following Burke and coworkers [Phys. Rev. B 93, 245131 (2016)], we propose in this work to construct an exact eDFT for the nontrivial asymmetric Hubbard dimer, thus providing more insight into the weight dependence of the ensemble xc energy in various correlation regimes. For that purpose, an exact analytical expression for the weight-dependent ensemble exchange energy has been derived. The complementary exact ensemble correlation energy has been computed by means of Legendre-Fenchel transforms. Interesting features like discontinuities in the ensemble xc potential in the...

  17. Ghost interaction correction in ensemble density-functional theory for excited states with and without range separation

    CERN Document Server

    Alam, Md Mehboob; Fromager, Emmanuel

    2016-01-01

    Ensemble density-functional theory (eDFT) suffers from the "ghost-interaction" (GI) error when approximate exchange-correlation functionals are used. In this letter, we present a rigorous GI correction (GIC) in the context of multideterminantal range-separated eDFT. The method, which relies on a double generalized adiabatic connection for ensembles, is equally applicable to standard Kohn-Sham eDFT. We show that GIC reduces the curvature of approximate ensemble energies drastically while providing considerably more accurate excitation energies, even for charge-transfer and double excitations.

  18. Impact of hyperbolicity on chimera states in ensembles of nonlocally coupled chaotic oscillators

    Energy Technology Data Exchange (ETDEWEB)

    Semenova, N.; Anishchenko, V. [Department of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov (Russian Federation); Zakharova, A.; Schöll, E. [Institut für Theoretische Physik, TU Berlin, Hardenbergstraße 36, 10623 Berlin (Germany)

    2016-06-08

    In this work we analyse nonlocally coupled networks of identical chaotic oscillators. We study both time-discrete and time-continuous systems (Henon map, Lozi map, Lorenz system). We hypothesize that chimera states, in which spatial domains of coherent (synchronous) and incoherent (desynchronized) dynamics coexist, can be obtained only in networks of chaotic non-hyperbolic systems and cannot be found in networks of hyperbolic systems. This hypothesis is supported by numerical simulations for hyperbolic and non-hyperbolic cases.

  19. Structural heterogeneity of the μ-opioid receptor’s conformational ensemble in the apo state

    Science.gov (United States)

    Sena, Diniz M.; Cong, Xiaojing; Giorgetti, Alejandro; Kless, Achim; Carloni, Paolo

    2017-04-01

    G-protein coupled receptors (GPCRs) are the largest and most pharmaceutically relevant family of membrane proteins. Here, fully unbiased, enhanced sampling simulations of a constitutively active mutant (CAM) of a class A GPCR, the μ-opioid receptor (μOR), demonstrates repeated transitions between the inactive (IS) and active-like (AS-L) states. The interconversion features typical activation/inactivation patterns involving established conformational rearrangements of conserved residues. By contrast, wild-type μOR remains in IS during the same course of simulation, consistent with the low basal activity of the protein. The simulations point to an important role of residue W2936.48 at the “toggle switch” in the mutation-induced constitutive activation. Such role has been already observed for other CAMs of class A GPCRs. We also find a significantly populated intermediate state, rather similar to IS. Based on the remarkable accord between simulations and experiments, we suggest here that this state, which has escaped so far experimental characterization, might constitute an early step in the activation process of the apo μOR CAM.

  20. Evaluation of Origin Ensemble algorithm for image reconstruction for pixelated solid-state detectors with large number of channels

    Science.gov (United States)

    Kolstein, M.; De Lorenzo, G.; Mikhaylova, E.; Chmeissani, M.; Ariño, G.; Calderón, Y.; Ozsahin, I.; Uzun, D.

    2013-04-01

    The Voxel Imaging PET (VIP) Pathfinder project intends to show the advantages of using pixelated solid-state technology for nuclear medicine applications. It proposes designs for Positron Emission Tomography (PET), Positron Emission Mammography (PEM) and Compton gamma camera detectors with a large number of signal channels (of the order of 106). For PET scanners, conventional algorithms like Filtered Back-Projection (FBP) and Ordered Subset Expectation Maximization (OSEM) are straightforward to use and give good results. However, FBP presents difficulties for detectors with limited angular coverage like PEM and Compton gamma cameras, whereas OSEM has an impractically large time and memory consumption for a Compton gamma camera with a large number of channels. In this article, the Origin Ensemble (OE) algorithm is evaluated as an alternative algorithm for image reconstruction. Monte Carlo simulations of the PET design are used to compare the performance of OE, FBP and OSEM in terms of the bias, variance and average mean squared error (MSE) image quality metrics. For the PEM and Compton camera designs, results obtained with OE are presented.

  1. A composite state method for ensemble data assimilation with multiple limited-area models

    Directory of Open Access Journals (Sweden)

    Matthew Kretschmer

    2015-04-01

    Full Text Available Limited-area models (LAMs allow high-resolution forecasts to be made for geographic regions of interest when resources are limited. Typically, boundary conditions for these models are provided through one-way boundary coupling from a coarser resolution global model. Here, data assimilation is considered in a situation in which a global model supplies boundary conditions to multiple LAMs. The data assimilation method presented combines information from all of the models to construct a single ‘composite state’, on which data assimilation is subsequently performed. The analysis composite state is then used to form the initial conditions of the global model and all of the LAMs for the next forecast cycle. The method is tested by using numerical experiments with simple, chaotic models. The results of the experiments show that there is a clear forecast benefit to allowing LAM states to influence one another during the analysis. In addition, adding LAM information at analysis time has a strong positive impact on global model forecast performance, even at points not covered by the LAMs.

  2. Supernova equations of state including full nuclear ensemble with in-medium effects

    Science.gov (United States)

    Furusawa, Shun; Sumiyoshi, Kohsuke; Yamada, Shoichi; Suzuki, Hideyuki

    2017-01-01

    We construct new equations of state for baryons at sub-nuclear densities for the use in core-collapse supernova simulations. The abundance of various nuclei is obtained together with thermodynamic quantities. The formulation is an extension of the previous model, in which we adopted the relativistic mean field theory with the TM1 parameter set for nucleons, the quantum approach for d, t, h and α as well as the liquid drop model for the other nuclei under the nuclear statistical equilibrium. We reformulate the model of the light nuclei other than d, t, h and α based on the quasi-particle description. Furthermore, we modify the model so that the temperature dependences of surface and shell energies of heavy nuclei could be taken into account. The pasta phases for heavy nuclei and the Pauli- and self-energy shifts for d, t, h and α are taken into account in the same way as in the previous model. We find that nuclear composition is considerably affected by the modifications in this work, whereas thermodynamical quantities are not changed much. In particular, the washout of shell effect has a great impact on the mass distribution above T ∼ 1 MeV. This improvement may have an important effect on the rates of electron captures and coherent neutrino scatterings on nuclei in supernova cores.

  3. Diffusion relaxation times of nonequilibrium isolated small bodies and their solid phase ensembles to equilibrium states

    Science.gov (United States)

    Tovbin, Yu. K.

    2017-08-01

    The possibility of obtaining analytical estimates in a diffusion approximation of the times needed by nonequilibrium small bodies to relax to their equilibrium states based on knowledge of the mass transfer coefficient is considered. This coefficient is expressed as the product of the self-diffusion coefficient and the thermodynamic factor. A set of equations for the diffusion transport of mixture components is formulated, characteristic scales of the size of microheterogeneous phases are identified, and effective mass transfer coefficients are constructed for them. Allowing for the developed interface of coexisting and immiscible phases along with the porosity of solid phases is discussed. This approach can be applied to the diffusion equalization of concentrations of solid mixture components in many physicochemical systems: the mutual diffusion of components in multicomponent systems (alloys, semiconductors, solid mixtures of inert gases) and the mass transfer of an absorbed mobile component in the voids of a matrix consisting of slow components or a mixed composition of mobile and slow components (e.g., hydrogen in metals, oxygen in oxides, and the transfer of molecules through membranes of different natures, including polymeric).

  4. Joint State and Parameter Estimation for Two Land Surface Models Using the Ensemble Kalman Filter and Particle Filter

    Science.gov (United States)

    Zhang, Hongjuan; Hendricks-Franssen, Harrie-Jan; Han, Xujun; Vrugt, Jasper A.; Vereecken, Harry

    2016-04-01

    Land surface models (LSMs) resolve the water and energy balance with different parameters and state variables. Many of the parameters of these models cannot be measured directly in the field, and require calibration against flux and soil moisture data. Two LSMs are used in our work: Variable Infiltration Capacity Hydrologic Model (VIC) and the Community Land Model (CLM). Temporal variations in soil moisture content at 5, 20 and 50 cm depth in the Rollesbroich experimental watershed in Germany are simulated in both LSMs. Data assimilation (DA) provides a good way to jointly estimate soil moisture content and soil properties of the resolved soil domain. Four DA methods combined with the two LSMs are used in our work: the Ensemble Kalman Filter (EnKF) using state augmentation or dual estimation, the Residual Resampling Particle Filter (RRPF) and Markov chain Monte Carlo Particle Filter (MCMCPF). These four DA methods are tuned and calibrated for a five month period, and subsequently evaluated for another five month period. Performances of the two LSMs and the four DA methods are compared. Our results show that all DA methods improve the estimation of soil moisture content of the VIC and CLM models, especially if the soil hydraulic properties (VIC), the maximum baseflow velocity (VIC) and/or soil texture (CLM) are jointly estimated with soil moisture content. The augmentation and dual estimation methods performed slightly better than RRPF and MCMCPF in the evaluation period. The differences in simulated soil moisture content between CLM and VIC were larger than variations among the DA methods. The CLM performed better than the VIC model. The strong underestimation of soil moisture content in the third layer of the VIC model is likely related to an inadequate parameterization of groundwater drainage.

  5. Automated identification of sleep states from EEG signals by means of ensemble empirical mode decomposition and random under sampling boosting.

    Science.gov (United States)

    Hassan, Ahnaf Rashik; Bhuiyan, Mohammed Imamul Hassan

    2017-03-01

    Automatic sleep staging is essential for alleviating the burden of the physicians of analyzing a large volume of data by visual inspection. It is also a precondition for making an automated sleep monitoring system feasible. Further, computerized sleep scoring will expedite large-scale data analysis in sleep research. Nevertheless, most of the existing works on sleep staging are either multichannel or multiple physiological signal based which are uncomfortable for the user and hinder the feasibility of an in-home sleep monitoring device. So, a successful and reliable computer-assisted sleep staging scheme is yet to emerge. In this work, we propose a single channel EEG based algorithm for computerized sleep scoring. In the proposed algorithm, we decompose EEG signal segments using Ensemble Empirical Mode Decomposition (EEMD) and extract various statistical moment based features. The effectiveness of EEMD and statistical features are investigated. Statistical analysis is performed for feature selection. A newly proposed classification technique, namely - Random under sampling boosting (RUSBoost) is introduced for sleep stage classification. This is the first implementation of EEMD in conjunction with RUSBoost to the best of the authors' knowledge. The proposed feature extraction scheme's performance is investigated for various choices of classification models. The algorithmic performance of our scheme is evaluated against contemporary works in the literature. The performance of the proposed method is comparable or better than that of the state-of-the-art ones. The proposed algorithm gives 88.07%, 83.49%, 92.66%, 94.23%, and 98.15% for 6-state to 2-state classification of sleep stages on Sleep-EDF database. Our experimental outcomes reveal that RUSBoost outperforms other classification models for the feature extraction framework presented in this work. Besides, the algorithm proposed in this work demonstrates high detection accuracy for the sleep states S1 and REM

  6. Squeezing of Collective Excitations in Spin Ensembles

    DEFF Research Database (Denmark)

    Kraglund Andersen, Christian; Mølmer, Klaus

    2012-01-01

    We analyse the possibility to create two-mode spin squeezed states of two separate spin ensembles by inverting the spins in one ensemble and allowing spin exchange between the ensembles via a near resonant cavity field. We investigate the dynamics of the system using a combination of numerical an...

  7. Ensembl 2017

    Science.gov (United States)

    Aken, Bronwen L.; Achuthan, Premanand; Akanni, Wasiu; Amode, M. Ridwan; Bernsdorff, Friederike; Bhai, Jyothish; Billis, Konstantinos; Carvalho-Silva, Denise; Cummins, Carla; Clapham, Peter; Gil, Laurent; Girón, Carlos García; Gordon, Leo; Hourlier, Thibaut; Hunt, Sarah E.; Janacek, Sophie H.; Juettemann, Thomas; Keenan, Stephen; Laird, Matthew R.; Lavidas, Ilias; Maurel, Thomas; McLaren, William; Moore, Benjamin; Murphy, Daniel N.; Nag, Rishi; Newman, Victoria; Nuhn, Michael; Ong, Chuang Kee; Parker, Anne; Patricio, Mateus; Riat, Harpreet Singh; Sheppard, Daniel; Sparrow, Helen; Taylor, Kieron; Thormann, Anja; Vullo, Alessandro; Walts, Brandon; Wilder, Steven P.; Zadissa, Amonida; Kostadima, Myrto; Martin, Fergal J.; Muffato, Matthieu; Perry, Emily; Ruffier, Magali; Staines, Daniel M.; Trevanion, Stephen J.; Cunningham, Fiona; Yates, Andrew; Zerbino, Daniel R.; Flicek, Paul

    2017-01-01

    Ensembl (www.ensembl.org) is a database and genome browser for enabling research on vertebrate genomes. We import, analyse, curate and integrate a diverse collection of large-scale reference data to create a more comprehensive view of genome biology than would be possible from any individual dataset. Our extensive data resources include evidence-based gene and regulatory region annotation, genome variation and gene trees. An accompanying suite of tools, infrastructure and programmatic access methods ensure uniform data analysis and distribution for all supported species. Together, these provide a comprehensive solution for large-scale and targeted genomics applications alike. Among many other developments over the past year, we have improved our resources for gene regulation and comparative genomics, and added CRISPR/Cas9 target sites. We released new browser functionality and tools, including improved filtering and prioritization of genome variation, Manhattan plot visualization for linkage disequilibrium and eQTL data, and an ontology search for phenotypes, traits and disease. We have also enhanced data discovery and access with a track hub registry and a selection of new REST end points. All Ensembl data are freely released to the scientific community and our source code is available via the open source Apache 2.0 license. PMID:27899575

  8. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Haakon

    2016-01-08

    The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

  9. Dynamic light scattering study of peanut agglutinin: Size, shape and urea denaturation

    Indian Academy of Sciences (India)

    Sagarika Dev; Avadhesha Surolia

    2006-12-01

    Peanut agglutinin (PNA) is a homotetrameric protein with a unique open quaternary structure. PNA shows non-two state profile in chaotrope induced denaturation. It passes through a monomeric molten globule like state before complete denaturation (Reddy et al 1999). This denaturation profile is associated with the change in hydrodynamic radius of the native protein. Though the molten globule-like state is monomeric in nature it expands in size due to partial denaturation. The size and shape of the native PNA as well as the change in hydrodynamic radius of the protein during denaturation has been studied by dynamic light scattering (DLS). The generation of two species is evident from the profile of hydrodynamic radii. This study also reveals the extent of compactness of the intermediate state.

  10. Partially folded intermediates during trypsinogen denaturation

    Directory of Open Access Journals (Sweden)

    Martins N.F.

    1999-01-01

    Full Text Available The equilibrium unfolding of bovine trypsinogen was studied by circular dichroism, differential spectra and size exclusion HPLC. The change in free energy of denaturation was = 6.99 ± 1.40 kcal/mol for guanidine hydrochloride and = 6.37 ± 0.57 kcal/mol for urea. Satisfactory fits of equilibrium unfolding transitions required a three-state model involving an intermediate in addition to the native and unfolded forms. Size exclusion HPLC allowed the detection of an intermediate population of trypsinogen whose Stokes radii varied from 24.1 ± 0.4 Å to 26.0 ± 0.3 Å for 1.5 M and 2.5 M guanidine hydrochloride, respectively. During urea denaturation, the range of Stokes radii varied from 23.9 ± 0.3 Å to 25.7 ± 0.6 Å for 4.0 M and 6.0 M urea, respectively. Maximal intrinsic fluorescence was observed at about 3.8 M urea with 8-aniline-1-naphthalene sulfonate (ANS binding. These experimental data indicate that the unfolding of bovine trypsinogen is not a simple transition and suggest that the equilibrium intermediate population comprises one intermediate that may be characterized as a molten globule. To obtain further insight by studying intermediates representing different stages of unfolding, we hope to gain a better understanding of the complex interrelations between protein conformation and energetics.

  11. Cooperative formation of native-like tertiary contacts in the ensemble of unfolded states of a four-helix protein

    DEFF Research Database (Denmark)

    Bruun, Susanne W; Iesmantavicius, Vytautas; Danielsson, Jens

    2010-01-01

    In studies of the ensembles of unfolded structures of a four-helix bundle protein, we have detected the presence of potential precursors of native tertiary structures. These observations were based on the perturbation of NMR chemical shifts of the protein backbone atoms by single site mutations. ...

  12. Linear interpolation method in ensemble Kohn-Sham and range-separated density-functional approximations for excited states

    DEFF Research Database (Denmark)

    Senjean, Bruno; Knecht, Stefan; Jensen, Hans Jørgen Aa

    2015-01-01

    Gross-Oliveira-Kohn density-functional theory (GOK-DFT) for ensembles is, in principle, very attractive but has been hard to use in practice. A practical model based on GOK-DFT for the calculation of electronic excitation energies is discussed. The model relies on two modifications of GOK-DFT: us...

  13. Residual ordered structure in denatured proteins and the problem of protein folding.

    Science.gov (United States)

    Basharov, Mahmud A

    2012-02-01

    Structural characteristics of numerous globular proteins in the denatured state have been reviewed using literature data. Recent more precise experiments show that in contrast to the conventional standpoint, proteins under strongly denaturing conditions do not unfold completely and adopt a random coil state, but contain significant residual ordered structure. These results cast doubt on the basis of the conventional approach representing the process of protein folding as a spontaneous transition of a polypeptide chain from the random coil state to the unique globular structure. The denaturation of proteins is explained in terms of the physical properties of proteins such as stability, conformational change, elasticity, irreversible denaturation, etc. The spontaneous renaturation of some denatured proteins most probably is merely the manifestation of the physical properties (e.g., the elasticity) of the proteins per se, caused by the residual structure present in the denatured state. The pieces of the ordered structure might be the centers of the initiation of renaturation, where the restoration of the initial native conformation of denatured proteins begins. Studies on the denaturation of proteins hardly clarify how the proteins fold into the native conformation during the successive residue-by-residue elongation of the polypeptide chain on the ribosome.

  14. On Ensemble Nonlinear Kalman Filtering with Symmetric Analysis Ensembles

    KAUST Repository

    Luo, Xiaodong

    2010-09-19

    The ensemble square root filter (EnSRF) [1, 2, 3, 4] is a popular method for data assimilation in high dimensional systems (e.g., geophysics models). Essentially the EnSRF is a Monte Carlo implementation of the conventional Kalman filter (KF) [5, 6]. It is mainly different from the KF at the prediction steps, where it is some ensembles, rather then the means and covariance matrices, of the system state that are propagated forward. In doing this, the EnSRF is computationally more efficient than the KF, since propagating a covariance matrix forward in high dimensional systems is prohibitively expensive. In addition, the EnSRF is also very convenient in implementation. By propagating the ensembles of the system state, the EnSRF can be directly applied to nonlinear systems without any change in comparison to the assimilation procedures in linear systems. However, by adopting the Monte Carlo method, the EnSRF also incurs certain sampling errors. One way to alleviate this problem is to introduce certain symmetry to the ensembles, which can reduce the sampling errors and spurious modes in evaluation of the means and covariances of the ensembles [7]. In this contribution, we present two methods to produce symmetric ensembles. One is based on the unscented transform [8, 9], which leads to the unscented Kalman filter (UKF) [8, 9] and its variant, the ensemble unscented Kalman filter (EnUKF) [7]. The other is based on Stirling’s interpolation formula (SIF), which results in the divided difference filter (DDF) [10]. Here we propose a simplified divided difference filter (sDDF) in the context of ensemble filtering. The similarity and difference between the sDDF and the EnUKF will be discussed. Numerical experiments will also be conducted to investigate the performance of the sDDF and the EnUKF, and compare them to a well‐established EnSRF, the ensemble transform Kalman filter (ETKF) [2].

  15. Ensemble-based data assimilation for operational flood forecasting - On the merits of state estimation for 1D hydrodynamic forecasting through the example of the ;Adour Maritime; river

    Science.gov (United States)

    Barthélémy, S.; Ricci, S.; Rochoux, M. C.; Le Pape, E.; Thual, O.

    2017-09-01

    This study presents the implementation and the merits of an Ensemble Kalman Filter (EnKF) algorithm with an inflation procedure on the 1D shallow water model MASCARET in the framework of operational flood forecasting on the ;Adour Maritime; river (South West France). In situ water level observations are sequentially assimilated to correct both water level and discharge. The stochastic estimation of the background error statistics is achieved over an ensemble of MASCARET integrations with perturbed hydrological boundary conditions. It is shown that the geometric characteristics of the network as well as the hydrological forcings and their temporal variability have a significant impact on the shape of the univariate (water level) and multivariate (water level and discharge) background error covariance functions and thus on the EnKF analysis. The performance of the EnKF algorithm is examined for observing system simulation experiments as well as for a set of eight real flood events (2009-2014). The quality of the ensemble is deemed satisfactory as long as the forecast lead time remains under the transfer time of the network, when perfect hydrological forcings are considered. Results demonstrate that the simulated hydraulic state variables can be improved over the entire network, even where no data are available, with a limited ensemble size and thus a computational cost compatible with operational constraints. The improvement in the water level Root-Mean-Square Error obtained with the EnKF reaches up to 88% at the analysis time and 40% at a 4-h forecast lead time compared to the standalone model.

  16. The dynamics of the DNA denaturation transition

    CERN Document Server

    van Erp, Titus S

    2012-01-01

    The dynamics of the DNA denaturation is studied using the Peyrard-Bishop-Dauxois model. The denaturation rate of double stranded polymers decreases exponentially as function of length below the denaturation temperature. Above Tc, the rate shows a minimum, but then increases as function of length. We also examine the influence of sequence and solvent friction. Molecules having the same number of weak and strong base-pairs can have significantly different opening rates depending on the order of base-pairs.

  17. Bubbles and denaturation in DNA

    CERN Document Server

    Van Erp, T S; Peyrard, M; Erp, Titus S. van; Cuesta-Lopez, Santiago; Peyrard, Michel

    2006-01-01

    The local opening of DNA is an intriguing phenomenon from a statistical physics point of view, but is also essential for its biological function. For instance, the transcription and replication of our genetic code can not take place without the unwinding of the DNA double helix. Although these biological processes are driven by proteins, there might well be a relation between these biological openings and the spontaneous bubble formation due to thermal fluctuations. Mesoscopic models, like the Peyrard-Bishop-Dauxois model, have fairly accurately reproduced some experimental denaturation curves and the sharp phase transition in the thermodynamic limit. It is, hence, tempting to see whether these models could be used to predict the biological activity of DNA. In a previous study, we introduced a method that allows to obtain very accurate results on this subject, which showed that some previous claims in this direction, based on molecular dynamics studies, were premature. This could either imply that the present...

  18. DNA denaturation in ionic solution

    Science.gov (United States)

    Maity, Arghya; Singh, Amar; Singh, Navin

    2016-05-01

    Salt or cations, present in solution play an important role in DNA denaturation and folding kinetics of DNA helix. In this work we study the thermal melting of double stranded DNA (dsDNA) molecule using Peyrard Bishop Dauxois (PBD) model. We modify the potential of H-bonding between the bases of the complimentary strands to introduce the salt and solvent effect. We choose different DNA sequences having different contents of GC pairs and calculate the melting temperatures. The melting temperature increases logarithmically with the salt concentration of the solution. The more GC base pairs in the chain enhance the stability of DNA chain at a fix salt concentration. The obtained results are in good accordance with experimental findings.

  19. Composed ensembles of random unitary ensembles

    CERN Document Server

    Pozniak, M; Kus, M; Pozniak, Marcin; Zyczkowski, Karol; Kus, Marek

    1997-01-01

    Composed ensembles of random unitary matrices are defined via products of matrices, each pertaining to a given canonical circular ensemble of Dyson. We investigate statistical properties of spectra of some composed ensembles and demonstrate their physical relevance. We discuss also the methods of generating random matrices distributed according to invariant Haar measure on the orthogonal and unitary group.

  20. Estimating preselected and postselected ensembles

    Energy Technology Data Exchange (ETDEWEB)

    Massar, Serge [Laboratoire d' Information Quantique, C.P. 225, Universite libre de Bruxelles (U.L.B.), Av. F. D. Rooselvelt 50, B-1050 Bruxelles (Belgium); Popescu, Sandu [H. H. Wills Physics Laboratory, University of Bristol, Tyndall Avenue, Bristol BS8 1TL (United Kingdom); Hewlett-Packard Laboratories, Stoke Gifford, Bristol BS12 6QZ (United Kingdom)

    2011-11-15

    In analogy with the usual quantum state-estimation problem, we introduce the problem of state estimation for a pre- and postselected ensemble. The problem has fundamental physical significance since, as argued by Y. Aharonov and collaborators, pre- and postselected ensembles are the most basic quantum ensembles. Two new features are shown to appear: (1) information is flowing to the measuring device both from the past and from the future; (2) because of the postselection, certain measurement outcomes can be forced never to occur. Due to these features, state estimation in such ensembles is dramatically different from the case of ordinary, preselected-only ensembles. We develop a general theoretical framework for studying this problem and illustrate it through several examples. We also prove general theorems establishing that information flowing from the future is closely related to, and in some cases equivalent to, the complex conjugate information flowing from the past. Finally, we illustrate our approach on examples involving covariant measurements on spin-1/2 particles. We emphasize that all state-estimation problems can be extended to the pre- and postselected situation. The present work thus lays the foundations of a much more general theory of quantum state estimation.

  1. The classicality and quantumness of a quantum ensemble

    CERN Document Server

    Zhu, Xuanmin; Wu, Shengjun; Liu, Quanhui

    2010-01-01

    In this paper, we investigate the classicality and quantumness of a quantum ensemble. We define a quantity called classicality to characterize how classical a quantum ensemble is. An ensemble of commuting states that can be manipulated classically has a unit classicality, while a general ensemble has a classicality less than 1. We also study how quantum an ensemble is by defining a related quantity called quantumness. We find that the classicality of an ensemble is closely related to how perfectly the ensemble can be cloned, and that the quantumness of an ensemble is essentially responsible for the security of quantum key distribution(QKD) protocols using that ensemble. Furthermore, we show that the quantumness of an ensemble used in a QKD protocol is exactly the attainable lower bound of the error rate in the sifted key.

  2. Non-local quantum evolution of entangled ensemble states in neural nets and its significance for brain function and a theory of consciousness

    CERN Document Server

    Bieberich, E

    1999-01-01

    Current quantum theories of consciousness suggest a configuration space of an entangled ensemble state as global work space for conscious experience. This study will describe a procedure for adjustment of the singlet evolution of a quantum computation to a classical signal input by action potentials. The computational output of an entangled state in a single neuron will be selected in a network environment by "survival of the fittest" coupling with other neurons. Darwinian evolution of this coupling will result in a binding of action potentials to a convoluted orbit of phase-locked oscillations with harmonic, m-adic, or fractal periodicity. Progressive integration of signal inputs will evolve a present memory space independent from the history of construction. Implications for mental processes, e.g., associative memory, creativity, and consciousness will be discussed. A model for the generation of quantum coherence in a single neuron will be suggested.

  3. Coherent control of ground state excitons in the nonlinear regime within an ensemble of self-assembled InAs quantum dots

    Energy Technology Data Exchange (ETDEWEB)

    Moldaschl, Thomas; Mueller, Thomas; Golka, Sebastian; Parz, Wolfgang; Strasser, Gottfried; Unterrainer, Karl [Photonics Institute and Center for Micro- and Nanostructures, Vienna University of Technology (Austria)

    2009-04-15

    In this work femtosecond spectral hole burning spectroscopy is used to resonantly excite ground state excitons in an ensemble of self-assembled InAs/GaAs quantum dots with a strong pump pulse. Two fundamental coherent nonlinear effects are observed with the aid of the intrinsic time- and frequency resolution of the setup: The low temperature Rabi oscillation of the two-level system associated with the excitonic ground state transition and the observation of two-photon absorption in the surrounding GaAs crystal matrix. The emergence of the latter effect also infers the existence of charged excitons in the nominally undoped QD sample, backed up by the observation of additional spectral holes next to the excitonic transitions. (copyright 2009 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  4. The Partition Ensemble Fallacy Fallacy

    CERN Document Server

    Nemoto, K; Nemoto, Kae; Braunstein, Samuel L.

    2002-01-01

    The Partition Ensemble Fallacy was recently applied to claim no quantum coherence exists in coherent states produced by lasers. We show that this claim relies on an untestable belief of a particular prior distribution of absolute phase. One's choice for the prior distribution for an unobservable quantity is a matter of `religion'. We call this principle the Partition Ensemble Fallacy Fallacy. Further, we show an alternative approach to construct a relative-quantity Hilbert subspace where unobservability of certain quantities is guaranteed by global conservation laws. This approach is applied to coherent states and constructs an approximate relative-phase Hilbert subspace.

  5. Analysis of peeling decoder for MET ensembles

    CERN Document Server

    Hinton, Ryan

    2009-01-01

    The peeling decoder introduced by Luby, et al. allows analysis of LDPC decoding for the binary erasure channel (BEC). For irregular ensembles, they analyze the decoder state as a Markov process and present a solution to the differential equations describing the process mean. Multi-edge type (MET) ensembles allow greater precision through specifying graph connectivity. We generalize the the peeling decoder for MET ensembles and derive analogous differential equations. We offer a new change of variables and solution to the node fraction evolutions in the general (MET) case. This result is preparatory to investigating finite-length ensemble behavior.

  6. Identifying outliers of non-Gaussian groundwater state data based on ensemble estimation for long-term trends

    Science.gov (United States)

    Jeong, Jina; Park, Eungyu; Han, Weon Shik; Kim, Kueyoung; Choung, Sungwook; Chung, Il Moon

    2017-05-01

    A hydrogeological dataset often includes substantial deviations that need to be inspected. In the present study, three outlier identification methods - the three sigma rule (3σ), inter quantile range (IQR), and median absolute deviation (MAD) - that take advantage of the ensemble regression method are proposed by considering non-Gaussian characteristics of groundwater data. For validation purposes, the performance of the methods is compared using simulated and actual groundwater data with a few hypothetical conditions. In the validations using simulated data, all of the proposed methods reasonably identify outliers at a 5% outlier level; whereas, only the IQR method performs well for identifying outliers at a 30% outlier level. When applying the methods to real groundwater data, the outlier identification performance of the IQR method is found to be superior to the other two methods. However, the IQR method shows limitation by identifying excessive false outliers, which may be overcome by its joint application with other methods (for example, the 3σ rule and MAD methods). The proposed methods can be also applied as potential tools for the detection of future anomalies by model training based on currently available data.

  7. Ensemble methods for handwritten digit recognition

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Liisberg, Christian; Salamon, P.

    1992-01-01

    . It is further shown that it is possible to estimate the ensemble performance as well as the learning curve on a medium-size database. In addition the authors present preliminary analysis of experiments on a large database and show that state-of-the-art performance can be obtained using the ensemble approach...

  8. Exploring ensemble visualization

    Science.gov (United States)

    Phadke, Madhura N.; Pinto, Lifford; Alabi, Oluwafemi; Harter, Jonathan; Taylor, Russell M., II; Wu, Xunlei; Petersen, Hannah; Bass, Steffen A.; Healey, Christopher G.

    2012-01-01

    An ensemble is a collection of related datasets. Each dataset, or member, of an ensemble is normally large, multidimensional, and spatio-temporal. Ensembles are used extensively by scientists and mathematicians, for example, by executing a simulation repeatedly with slightly different input parameters and saving the results in an ensemble to see how parameter choices affect the simulation. To draw inferences from an ensemble, scientists need to compare data both within and between ensemble members. We propose two techniques to support ensemble exploration and comparison: a pairwise sequential animation method that visualizes locally neighboring members simultaneously, and a screen door tinting method that visualizes subsets of members using screen space subdivision. We demonstrate the capabilities of both techniques, first using synthetic data, then with simulation data of heavy ion collisions in high-energy physics. Results show that both techniques are capable of supporting meaningful comparisons of ensemble data.

  9. How water contributes to pressure and cold denaturation of proteins

    CERN Document Server

    Bianco, Valentino

    2015-01-01

    The mechanisms of cold- and pressure-denaturation of proteins are matter of debate and are commonly understood as due to water-mediated interactions. Here we study several cases of proteins, with or without a unique native state, with or without hydrophilic residues, by means of a coarse-grain protein model in explicit solvent. We show, using Monte Carlo simulations, that taking into account how water at the protein interface changes its hydrogen bond properties and its density fluctuations is enough to predict protein stability regions with elliptic shapes in the temperature-pressure plane, consistent with previous theories. Our results clearly identify the different mechanisms with which water participates to denaturation and open the perspective to develop advanced computational design tools for protein engineering.

  10. A new equation of state for core-collapse supernovae based on realistic nuclear forces and including a full nuclear ensemble

    Science.gov (United States)

    Furusawa, S.; Togashi, H.; Nagakura, H.; Sumiyoshi, K.; Yamada, S.; Suzuki, H.; Takano, M.

    2017-09-01

    We have constructed a nuclear equation of state (EOS) that includes a full nuclear ensemble for use in core-collapse supernova simulations. It is based on the EOS for uniform nuclear matter that two of the authors derived recently, applying a variational method to realistic two- and three-body nuclear forces. We have extended the liquid drop model of heavy nuclei, utilizing the mass formula that accounts for the dependences of bulk, surface, Coulomb and shell energies on density and/or temperature. As for light nuclei, we employ a quantum-theoretical mass evaluation, which incorporates the Pauli- and self-energy shifts. In addition to realistic nuclear forces, the inclusion of in-medium effects on the full ensemble of nuclei makes the new EOS one of the most realistic EOSs, which covers a wide range of density, temperature and proton fraction that supernova simulations normally encounter. We make comparisons with the FYSS EOS, which is based on the same formulation for the nuclear ensemble but adopts the relativistic mean field theory with the TM1 parameter set for uniform nuclear matter. The new EOS is softer than the FYSS EOS around and above nuclear saturation densities. We find that neutron-rich nuclei with small mass numbers are more abundant in the new EOS than in the FYSS EOS because of the larger saturation densities and smaller symmetry energy of nuclei in the former. We apply the two EOSs to 1D supernova simulations and find that the new EOS gives lower electron fractions and higher temperatures in the collapse phase owing to the smaller symmetry energy. As a result, the inner core has smaller masses for the new EOS. It is more compact, on the other hand, due to the softness of the new EOS and bounces at higher densities. It turns out that the shock wave generated by core bounce is a bit stronger initially in the simulation with the new EOS. The ensuing outward propagations of the shock wave in the outer core are very similar in the two simulations, which

  11. CME Ensemble Forecasting - A Primer

    Science.gov (United States)

    Pizzo, V. J.; de Koning, C. A.; Cash, M. D.; Millward, G. H.; Biesecker, D. A.; Codrescu, M.; Puga, L.; Odstrcil, D.

    2014-12-01

    SWPC has been evaluating various approaches for ensemble forecasting of Earth-directed CMEs. We have developed the software infrastructure needed to support broad-ranging CME ensemble modeling, including composing, interpreting, and making intelligent use of ensemble simulations. The first step is to determine whether the physics of the interplanetary propagation of CMEs is better described as chaotic (like terrestrial weather) or deterministic (as in tsunami propagation). This is important, since different ensemble strategies are to be pursued under the two scenarios. We present the findings of a comprehensive study of CME ensembles in uniform and structured backgrounds that reveals systematic relationships between input cone parameters and ambient flow states and resulting transit times and velocity/density amplitudes at Earth. These results clearly indicate that the propagation of single CMEs to 1 AU is a deterministic process. Thus, the accuracy with which one can forecast the gross properties (such as arrival time) of CMEs at 1 AU is determined primarily by the accuracy of the inputs. This is no tautology - it means specifically that efforts to improve forecast accuracy should focus upon obtaining better inputs, as opposed to developing better propagation models. In a companion paper (deKoning et al., this conference), we compare in situ solar wind data with forecast events in the SWPC operational archive to show how the qualitative and quantitative findings presented here are entirely consistent with the observations and may lead to improved forecasts of arrival time at Earth.

  12. Excitation energies from ensemble DFT

    Science.gov (United States)

    Borgoo, Alex; Teale, Andy M.; Helgaker, Trygve

    2015-12-01

    We study the evaluation of the Gross-Oliveira-Kohn expression for excitation energies E1-E0=ɛ1-ɛ0+∂E/xc,w[ρ] ∂w | ρ =ρ0. This expression gives the difference between an excitation energy E1 - E0 and the corresponding Kohn-Sham orbital energy difference ɛ1 - ɛ0 as a partial derivative of the exchange-correlation energy of an ensemble of states Exc,w[ρ]. Through Lieb maximisation, on input full-CI density functions, the exchange-correlation energy is evaluated accurately and the partial derivative is evaluated numerically using finite difference. The equality is studied numerically for different geometries of the H2 molecule and different ensemble weights. We explore the adiabatic connection for the ensemble exchange-correlation energy. The latter may prove useful when modelling the unknown weight dependence of the exchange-correlation energy.

  13. State-based decoding of hand and finger kinematics using neuronal ensemble and LFP activity during dexterous reach-to-grasp movements.

    Science.gov (United States)

    Aggarwal, Vikram; Mollazadeh, Mohsen; Davidson, Adam G; Schieber, Marc H; Thakor, Nitish V

    2013-06-01

    The performance of brain-machine interfaces (BMIs) that continuously control upper limb neuroprostheses may benefit from distinguishing periods of posture and movement so as to prevent inappropriate movement of the prosthesis. Few studies, however, have investigated how decoding behavioral states and detecting the transitions between posture and movement could be used autonomously to trigger a kinematic decoder. We recorded simultaneous neuronal ensemble and local field potential (LFP) activity from microelectrode arrays in primary motor cortex (M1) and dorsal (PMd) and ventral (PMv) premotor areas of two male rhesus monkeys performing a center-out reach-and-grasp task, while upper limb kinematics were tracked with a motion capture system with markers on the dorsal aspect of the forearm, hand, and fingers. A state decoder was trained to distinguish four behavioral states (baseline, reaction, movement, hold), while a kinematic decoder was trained to continuously decode hand end point position and 18 joint angles of the wrist and fingers. LFP amplitude most accurately predicted transition into the reaction (62%) and movement (73%) states, while spikes most accurately decoded arm, hand, and finger kinematics during movement. Using an LFP-based state decoder to trigger a spike-based kinematic decoder [r = 0.72, root mean squared error (RMSE) = 0.15] significantly improved decoding of reach-to-grasp movements from baseline to final hold, compared with either a spike-based state decoder combined with a spike-based kinematic decoder (r = 0.70, RMSE = 0.17) or a spike-based kinematic decoder alone (r = 0.67, RMSE = 0.17). Combining LFP-based state decoding with spike-based kinematic decoding may be a valuable step toward the realization of BMI control of a multifingered neuroprosthesis performing dexterous manipulation.

  14. Unconditional two-mode squeezing of separated atomic ensembles

    CERN Document Server

    Parkins, A S; Solano, E

    2005-01-01

    We propose schemes for the unconditional preparation of a two-mode squeezed state of effective bosonic modes realized in a pair of atomic ensembles interacting collectively with optical cavity and laser fields. The scheme uses Raman transitions between stable atomic ground states and under ideal conditions produces pure entangled states in the steady state. The scheme works both for ensembles confined within a single cavity and for ensembles confined in separate, cascaded cavities.

  15. State analysis using the Local Ensemble Transform Kalman Filter (LETKF) and the three-layer circulation structure of the Luzon Strait and the South China Sea

    Science.gov (United States)

    Xu, Fang-Hua; Oey, Lie-Yauw

    2014-06-01

    A new circulation model of the western North Pacific Ocean based on the parallelized version of the Princeton Ocean Model and incorporating the Local Ensemble Transform Kalman Filter (LETKF) data assimilation scheme has been developed. The new model assimilates satellite data and is tested for the period January 1 to April 3, 2012 initialized from a 24-year simulation to estimate the ocean state focusing in the South China Sea (SCS). Model results are compared against estimates based on the optimum interpolation (OI) assimilation scheme and are validated against independent Argo float and transport data to assess model skills. LETKF provides improved estimates of the western North Pacific Ocean state including transports through various straits in the SCS. In the Luzon Strait, the model confirms, for the first time, the three-layer transport structure previously deduced in the literature from sparse observations: westward in the upper and lower layers and eastward in the middle layer. This structure is shown to be robust, and the related dynamics are analyzed using the results of a long-term (18 years) unassimilated North Pacific Ocean model. Potential vorticity and mass conservations suggest a basin-wide cyclonic circulation in the upper layer of the SCS ( z > -570 m), an anticyclonic circulation in the middle layer (-570 m ≥ z > -2,000 m), and, in the abyssal basin (reduced-gravity model as being caused by overflow over the deep sill of the Luzon Strait, coupled with intense, localized upwelling west of the strait.

  16. Demonstration of sufficient control for two rounds of quantum error correction in a solid state ensemble quantum information processor

    CERN Document Server

    Moussa, Osama; Ryan, Colm A; Laflamme, Raymond

    2011-01-01

    We report the implementation of a 3-qubit quantum error correction code (QECC) on a quantum information processor realized by the magnetic resonance of Carbon nuclei in a single crystal of Malonic Acid. The code corrects for phase errors induced on the qubits due to imperfect decoupling of the magnetic environment represented by nearby spins, as well as unwanted evolution under the internal Hamiltonian. We also experimentally demonstrate sufficiently high fidelity control to implement two rounds of quantum error correction. This is a demonstration of state-of-the-art control in solid state nuclear magnetic resonance, a leading test-bed for the implementation of quantum algorithms.

  17. Demonstration of sufficient control for two rounds of quantum error correction in a solid state ensemble quantum information processor.

    Science.gov (United States)

    Moussa, Osama; Baugh, Jonathan; Ryan, Colm A; Laflamme, Raymond

    2011-10-14

    We report the implementation of a 3-qubit quantum error-correction code on a quantum information processor realized by the magnetic resonance of carbon nuclei in a single crystal of malonic acid. The code corrects for phase errors induced on the qubits due to imperfect decoupling of the magnetic environment represented by nearby spins, as well as unwanted evolution under the internal Hamiltonian. We also experimentally demonstrate sufficiently high-fidelity control to implement two rounds of quantum error correction. This is a demonstration of state-of-the-art control in solid state nuclear magnetic resonance, a leading test bed for the implementation of quantum algorithms.

  18. Reversible Projective Measurement in Quantum Ensembles

    CERN Document Server

    Khitrin, Anatoly; Lee, Jae-Seung

    2010-01-01

    We present experimental NMR demonstration of a scheme of reversible projective measurement, which allows extracting information on outcomes and probabilities of a projective measurement in a non-destructive way, with a minimal net effect on the quantum state of an ensemble. The scheme uses reversible dynamics and weak measurement of the intermediate state. The experimental system is an ensemble of 133Cs (S = 7/2) nuclei in a liquid-crystalline matrix.

  19. Chemical shift prediction for denatured proteins

    Energy Technology Data Exchange (ETDEWEB)

    Prestegard, James H., E-mail: jpresteg@ccrc.uga.edu; Sahu, Sarata C.; Nkari, Wendy K.; Morris, Laura C.; Live, David; Gruta, Christian

    2013-02-15

    While chemical shift prediction has played an important role in aspects of protein NMR that include identification of secondary structure, generation of torsion angle constraints for structure determination, and assignment of resonances in spectra of intrinsically disordered proteins, interest has arisen more recently in using it in alternate assignment strategies for crosspeaks in {sup 1}H-{sup 15}N HSQC spectra of sparsely labeled proteins. One such approach involves correlation of crosspeaks in the spectrum of the native protein with those observed in the spectrum of the denatured protein, followed by assignment of the peaks in the latter spectrum. As in the case of disordered proteins, predicted chemical shifts can aid in these assignments. Some previously developed empirical formulas for chemical shift prediction have depended on basis data sets of 20 pentapeptides. In each case the central residue was varied among the 20 amino common acids, with the flanking residues held constant throughout the given series. However, previous choices of solvent conditions and flanking residues make the parameters in these formulas less than ideal for general application to denatured proteins. Here, we report {sup 1}H and {sup 15}N shifts for a set of alanine based pentapeptides under the low pH urea denaturing conditions that are more appropriate for sparse label assignments. New parameters have been derived and a Perl script was created to facilitate comparison with other parameter sets. A small, but significant, improvement in shift predictions for denatured ubiquitin is demonstrated.

  20. Rousseau's Philosophy of Transformative, "Denaturing" Education

    Science.gov (United States)

    Riley, Patrick

    2011-01-01

    Rousseau's political philosophy presents the great legislator as a civic educator who must over time transform naturally self-loving egoists into citizens animated by a general will without destroying freedom. This is an educational process which is "denaturing" but which aims to produce autonomous adults who can ultimately say to their teacher…

  1. State and parameter estimation of two land surface models using the ensemble Kalman filter and the particle filter

    Directory of Open Access Journals (Sweden)

    H. Zhang

    2017-09-01

    Full Text Available Land surface models (LSMs use a large cohort of parameters and state variables to simulate the water and energy balance at the soil–atmosphere interface. Many of these model parameters cannot be measured directly in the field, and require calibration against measured fluxes of carbon dioxide, sensible and/or latent heat, and/or observations of the thermal and/or moisture state of the soil. Here, we evaluate the usefulness and applicability of four different data assimilation methods for joint parameter and state estimation of the Variable Infiltration Capacity Model (VIC-3L and the Community Land Model (CLM using a 5-month calibration (assimilation period (March–July 2012 of areal-averaged SPADE soil moisture measurements at 5, 20, and 50 cm depths in the Rollesbroich experimental test site in the Eifel mountain range in western Germany. We used the EnKF with state augmentation or dual estimation, respectively, and the residual resampling PF with a simple, statistically deficient, or more sophisticated, MCMC-based parameter resampling method. The performance of the calibrated LSM models was investigated using SPADE water content measurements of a 5-month evaluation period (August–December 2012. As expected, all DA methods enhance the ability of the VIC and CLM models to describe spatiotemporal patterns of moisture storage within the vadose zone of the Rollesbroich site, particularly if the maximum baseflow velocity (VIC or fractions of sand, clay, and organic matter of each layer (CLM are estimated jointly with the model states of each soil layer. The differences between the soil moisture simulations of VIC-3L and CLM are much larger than the discrepancies among the four data assimilation methods. The EnKF with state augmentation or dual estimation yields the best performance of VIC-3L and CLM during the calibration and evaluation period, yet results are in close agreement with the PF using MCMC resampling. Overall, CLM demonstrated the

  2. Making Tree Ensembles Interpretable

    OpenAIRE

    Hara, Satoshi; Hayashi, Kohei

    2016-01-01

    Tree ensembles, such as random forest and boosted trees, are renowned for their high prediction performance, whereas their interpretability is critically limited. In this paper, we propose a post processing method that improves the model interpretability of tree ensembles. After learning a complex tree ensembles in a standard way, we approximate it by a simpler model that is interpretable for human. To obtain the simpler model, we derive the EM algorithm minimizing the KL divergence from the ...

  3. Effects of protein and phosphate buffer concentrations on thermal denaturation of lysozyme analyzed by isoconversional method.

    Science.gov (United States)

    Cao, X M; Tian, Y; Wang, Z Y; Liu, Y W; Wang, C X

    2016-07-03

    Thermal denaturation of lysozymes was studied as a function of protein concentration, phosphate buffer concentration, and scan rate using differential scanning calorimetry (DSC), which was then analyzed by the isoconversional method. The results showed that lysozyme thermal denaturation was only slightly affected by the protein concentration and scan rate. When the protein concentration and scan rate increased, the denaturation temperature (Tm) also increased accordingly. On the contrary, the Tm decreased with the increase of phosphate buffer concentration. The denaturation process of lysozymes was accelatated and the thermal stability was reduced with the increase of phosphate concentration. One part of degeneration process was not reversible where the aggregation occurred. The other part was reversible. The apparent activation energy (Ea) was computed by the isoconversional method. It decreased with the increase of the conversion ratio (α). The observed denaturation process could not be described by a simple reaction mechanism. It was not a process involving 2 standard reversible states, but a multi-step process. The new opportunities for investigating the kinetics process of protein denaturation can be supplied by this novel isoconversional method.

  4. Steady state of a low-density ensemble of atoms in a monochromatic field taking into account recoil effects

    Science.gov (United States)

    Prudnikov, O. N.; Il'enkov, R. Ya.; Taichenachev, A. V.; Tumaikin, A. M.; Yudin, V. I.

    2011-06-01

    A method has been developed for obtaining the steady-state solution of a quantum kinetic equation for the atomic density matrix in an arbitrarily polarized monochromatic field with the complete inclusion of recoil effects and degeneracy of atomic levels in the projection of the angular momentum. This method makes it possible to obtain the most general solution beyond the previously accepted approximations (semiclassical approximation, secular approximation, etc.). In particular, it has been shown that the laser cooling temperature is a function of not only the depth of the optical potential (as was previously thought), but also the mass of an atom.

  5. Lipid Dynamics Studied by Calculation of 31P Solid-State NMR Spectra Using Ensembles from Molecular Dynamics Simulations

    DEFF Research Database (Denmark)

    Hansen, Sara Krogh; Vestergaard, Mikkel; Thøgersen, Lea;

    2014-01-01

    We present a method to calculate 31P solid-state NMR spectra based on the dynamic input from extended molecular dynamics (MD) simulations. The dynamic information confered by MD simulations is much more comprehensive than the information provided by traditional NMR dynamics models based on......, for example, order parameters. Therefore, valuable insight into the dynamics of biomolecules may be achieved by the present method. We have applied this method to study the dynamics of lipid bilayers containing the antimicrobial peptide alamethicin, and we show that the calculated 31P spectra obtained...

  6. Sequence-Specific Solvent Accessibilities of Protein Residues in Unfolded Protein Ensembles

    Science.gov (United States)

    Bernadó, Pau; Blackledge, Martin; Sancho, Javier

    2006-01-01

    Protein stability cannot be understood without the correct description of the unfolded state. We present here an efficient method for accurate calculation of atomic solvent exposures for denatured protein ensembles. The method used to generate the ensembles has been shown to reproduce diverse biophysical experimental data corresponding to natively and chemically unfolded proteins. Using a data set of 19 nonhomologous proteins containing from 98 to 579 residues, we report average accessibilities for all residue types. These averaged accessibilities are considerably lower than those previously reported for tripeptides and close to the lower limit reported by Creamer and co-workers. Of importance, we observe remarkable sequence dependence for the exposure to solvent of all residue types, which indicates that average residue solvent exposures can be inappropriate to interpret mutational studies. In addition, we observe smaller influences of both protein size and protein amino acid composition in the averaged residue solvent exposures for individual proteins. Calculating residue-specific solvent accessibilities within the context of real sequences is thus necessary and feasible. The approach presented here may allow a more precise parameterization of protein energetics as a function of polar- and apolar-area burial and opens new ways to investigate the energetics of the unfolded state of proteins. PMID:17012314

  7. Climate change effects on wildland fire risk in the Northeastern and Great Lakes states predicted by a downscaled multi-model ensemble

    Science.gov (United States)

    Kerr, Gaige Hunter; DeGaetano, Arthur T.; Stoof, Cathelijne R.; Ward, Daniel

    2016-11-01

    This study is among the first to investigate wildland fire risk in the Northeastern and the Great Lakes states under a changing climate. We use a multi-model ensemble (MME) of regional climate models from the Coordinated Regional Downscaling Experiment (CORDEX) together with the Canadian Forest Fire Weather Index System (CFFWIS) to understand changes in wildland fire risk through differences between historical simulations and future projections. Our results are relatively homogeneous across the focus region and indicate modest increases in the magnitude of fire weather indices (FWIs) during northern hemisphere summer. The most pronounced changes occur in the date of the initialization of CFFWIS and peak of the wildland fire season, which in the future are trending earlier in the year, and in the significant increases in the length of high-risk episodes, defined by the number of consecutive days with FWIs above the current 95th percentile. Further analyses show that these changes are most closely linked to expected changes in the focus region's temperature and precipitation. These findings relate to the current understanding of particulate matter vis-à-vis wildfires and have implications for human health and local and regional changes in radiative forcings. When considering current fire management strategies which could be challenged by increasing wildland fire risk, fire management agencies could adapt new strategies to improve awareness, prevention, and resilience to mitigate potential impacts to critical infrastructure and population.

  8. Alcohol-induced structural transitions in the acid-denatured Bacillus licheniformis α-amylase

    Directory of Open Access Journals (Sweden)

    Adyani Azizah Abd Halim

    2017-01-01

    Full Text Available Alcohol-induced structural changes in the acid-denatured Bacillus licheniformis α-amylase (BLA at pH 2.0 were studied by far-ultra violet circular dichroism, intrinsic, three-dimensional and 8-anilino-1-naphthalene sulfonic acid (ANS fluorescence, acrylamide quenching and thermal denaturation. All the alcohols used in this study produced partial refolding in the acid-denatured BLA as evident from the increased mean residue ellipticity at 222 nm, increased intrinsic fluorescence and decreased ANS fluorescence. The order of effectiveness of these alcohols to induce a partially folded state of BLA was found to be: 2,2,2-trifluoroethanol/tert-butanol > 1-propanol/2-propanol > 2-chloroethanol > ethanol > methanol. Three-dimensional fluorescence and acrylamide quenching results obtained in the presence of 5.5 M tert-butanol also suggested formation of a partially folded state in the acid-denatured BLA. However, 5.5 M tert-butanol-induced state of BLA showed a non-cooperative thermal transition. All these results suggested formation of a partially folded state of the acid-denatured BLA in the presence of these alcohols. Furthermore, their effectiveness was found to be guided by their chain length, position of methyl groups and presence of the substituents.

  9. Transient regional climate change: analysis of the summer climate response in a high-resolution, century-scale, ensemble experiment over the continental United States.

    Science.gov (United States)

    Diffenbaugh, Noah S; Ashfaq, Moetasim; Scherer, Martin

    2011-12-27

    Integrating the potential for climate change impacts into policy and planning decisions requires quantification of the emergence of sub-regional climate changes that could occur in response to transient changes in global radiative forcing. Here we report results from a high-resolution, century-scale, ensemble simulation of climate in the United States, forced by atmospheric constituent concentrations from the Special Report on Emissions Scenarios (SRES) A1B scenario. We find that 21(st) century summer warming permanently emerges beyond the baseline decadal-scale variability prior to 2020 over most areas of the continental U.S. Permanent emergence beyond the baseline annual-scale variability shows much greater spatial heterogeneity, with emergence occurring prior to 2030 over areas of the southwestern U.S., but not prior to the end of the 21(st) century over much of the southcentral and southeastern U.S. The pattern of emergence of robust summer warming contrasts with the pattern of summer warming magnitude, which is greatest over the central U.S. and smallest over the western U.S. In addition to stronger warming, the central U.S. also exhibits stronger coupling of changes in surface air temperature, precipitation, and moisture and energy fluxes, along with changes in atmospheric circulation towards increased anticylonic anomalies in the mid-troposphere and a poleward shift in the mid-latitude jet aloft. However, as a fraction of the baseline variability, the transient warming over the central U.S. is smaller than the warming over the southwestern or northeastern U.S., delaying the emergence of the warming signal over the central U.S. Our comparisons with observations and the Coupled Model Intercomparison Project Phase 3 (CMIP3) ensemble of global climate model experiments suggest that near-term global warming is likely to cause robust sub-regional-scale warming over areas that exhibit relatively little baseline variability. In contrast, where there is greater

  10. Transient regional climate change: analysis of the summer climate response in a high-resolution, century-scale, ensemble experiment over the continental United States

    Science.gov (United States)

    Diffenbaugh, Noah S.; Ashfaq, Moetasim; Scherer, Martin

    2013-01-01

    Integrating the potential for climate change impacts into policy and planning decisions requires quantification of the emergence of sub-regional climate changes that could occur in response to transient changes in global radiative forcing. Here we report results from a high-resolution, century-scale, ensemble simulation of climate in the United States, forced by atmospheric constituent concentrations from the Special Report on Emissions Scenarios (SRES) A1B scenario. We find that 21st century summer warming permanently emerges beyond the baseline decadal-scale variability prior to 2020 over most areas of the continental U.S. Permanent emergence beyond the baseline annual-scale variability shows much greater spatial heterogeneity, with emergence occurring prior to 2030 over areas of the southwestern U.S., but not prior to the end of the 21st century over much of the southcentral and southeastern U.S. The pattern of emergence of robust summer warming contrasts with the pattern of summer warming magnitude, which is greatest over the central U.S. and smallest over the western U.S. In addition to stronger warming, the central U.S. also exhibits stronger coupling of changes in surface air temperature, precipitation, and moisture and energy fluxes, along with changes in atmospheric circulation towards increased anticylonic anomalies in the mid-troposphere and a poleward shift in the mid-latitude jet aloft. However, as a fraction of the baseline variability, the transient warming over the central U.S. is smaller than the warming over the southwestern or northeastern U.S., delaying the emergence of the warming signal over the central U.S. Our comparisons with observations and the Coupled Model Intercomparison Project Phase 3 (CMIP3) ensemble of global climate model experiments suggest that near-term global warming is likely to cause robust sub-regional-scale warming over areas that exhibit relatively little baseline variability. In contrast, where there is greater

  11. Classical and Quantum Ensembles via Multiresolution. II. Wigner Ensembles

    OpenAIRE

    2004-01-01

    We present the application of the variational-wavelet analysis to the analysis of quantum ensembles in Wigner framework. (Naive) deformation quantization, the multiresolution representations and the variational approach are the key points. We construct the solutions of Wigner-like equations via the multiscale expansions in the generalized coherent states or high-localized nonlinear eigenmodes in the base of the compactly supported wavelets and the wavelet packets. We demonstrate the appearanc...

  12. The origin of emissive states of carbon nanoparticles derived from ensemble-averaged and single-molecular studies.

    Science.gov (United States)

    Demchenko, Alexander P; Dekaliuk, Mariia O

    2016-08-01

    At present, there is no consensus understanding on the origin of photoluminescence of carbon nanoparticles, particularly the so-called carbon dots. Providing comparative analysis of spectroscopic studies in solution and on a single-molecular level, we demonstrate that these particles behave collectively as fixed single dipoles and probably are the quantum emitter entities. Their spectral and lifetime heterogeneity in solutions is explained by variation of the local chemical environment within and around luminescence centers. Hence, the carbon dots possess a unique hybrid combination of fluorescence properties peculiar to dye molecules, their conjugates and semiconductor nanocrystals. It is proposed that their optical properties are due to generation of H-aggregate-type excitonic states with their coherence spreading over the whole nanoparticles.

  13. The origin of emissive states of carbon nanoparticles derived from ensemble-averaged and single-molecular studies

    Science.gov (United States)

    Demchenko, Alexander P.; Dekaliuk, Mariia O.

    2016-07-01

    At present, there is no consensus understanding on the origin of photoluminescence of carbon nanoparticles, particularly the so-called carbon dots. Providing comparative analysis of spectroscopic studies in solution and on a single-molecular level, we demonstrate that these particles behave collectively as fixed single dipoles and probably are the quantum emitter entities. Their spectral and lifetime heterogeneity in solutions is explained by variation of the local chemical environment within and around luminescence centers. Hence, the carbon dots possess a unique hybrid combination of fluorescence properties peculiar to dye molecules, their conjugates and semiconductor nanocrystals. It is proposed that their optical properties are due to generation of H-aggregate-type excitonic states with their coherence spreading over the whole nanoparticles.

  14. Adiabatic Passage of Collective Excitations in Atomic Ensembles

    Institute of Scientific and Technical Information of China (English)

    LIYong; MIAOYuan-Xiu; SUNChang-Pu

    2004-01-01

    We describe a theoretical scheme that allows for transfer of quantum states of atomic collective excitation between two macroscopic atomic ensembles localized in two spatially-separated domains. The conception is based on the occurrence of double-exciton dark states due to the collective destructive quantum interference of the emissions from the two atomic ensembles. With an adiabatically coherence manipulation for the atom-field couplings by stimulated Rmann scattering, the dark states will extrapolate from an exciton state of an ensemble to that of another. This realizes the transport of quantum information among atomic ensembles.

  15. Adiabatic Passage of Collective Excitations in Atomic Ensembles

    Institute of Scientific and Technical Information of China (English)

    LI Yong; MIAO Yuan-Xiu; SUN Chang-Pu

    2004-01-01

    We describe a theoretical scheme that allows for transfer of quantum states of atomic collective excitation between two macroscopic atomic ensembles localized in two spatially-separated domains. The conception is based on the occurrence of double-exciton dark states due to the collective destructive quantum interference of the emissions from the two atomic ensembles. With an adiabatically coherence manipulation for the atom-field couplings by stimulated Ramann scattering, the dark states will extrapolate from an exciton state of an ensemble to that of another. This realizes the transport of quantum information among atomic ensembles.

  16. [Characterization of thermal denaturation process of proteinase K by spectrometry].

    Science.gov (United States)

    Zhang, Qi-Bing; Na, Xin-Zhu; Yin, Zong-Ning

    2013-07-01

    The effect of different temperatures on the activity and conformational changes of proteinase K was studied. Methods Proteinase K was treated with different temperatures, then denatured natural substrate casein was used to assay enzyme activity, steady-state and time-resolved fluorescence spectroscopy was used to study tertiary structure, and circular dichroism was used to study secondary structure. Results show with the temperature rising from 25 to 65 degrees C, the enzyme activity and half-life of proteinase K dropped, maximum emission wavelength red shifted from 335 to 354 nm with fluorescence intensity decreasing. Synchronous fluorescence intensity of tryptophan residues decreased and that of tyrosine residues increased. Fluorescence lifetime of tryptophan residues reduced from 4. 427 1 to 4. 032 4 ns and the fraction of alpha-helix dropped. It was concluded that it is simple and accurate to use steady-state/time-resolved fluorescence spectroscopy and circular dichroism to investigate thermal stability of proteinase K. Thermal denaturation of proteinase K followed a three-state process. Fluorescence intensity of proteinase K was affected by fluorescence resonance energy transfer from tyrosine to tryptophan residues. The alpha-helix was the main structure to maintain conformational stability of enzyme active site of proteinase K.

  17. Multilevel ensemble Kalman filter

    KAUST Repository

    Chernov, Alexey

    2016-01-06

    This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

  18. Guanidinium-induced denaturation by breaking of salt bridges

    NARCIS (Netherlands)

    Meuzelaar, H.; Panman, M.R.; Woutersen, S.

    2015-01-01

    Despite its wide use as a denaturant, the mechanism by which guanidinium (Gdm+) induces protein unfolding remains largely unclear. Herein, we show evidence that Gdm+ can induce denaturation by disrupting salt bridges that stabilize the folded conformation. We study the Gdm+-​induced denaturation of

  19. Theory and Practice of Phase-aware Ensemble Forecasting

    Science.gov (United States)

    Schulte, J. A.; Georgas, N.

    2016-12-01

    The timing of events represents a source of uncertainty in ensemble forecasting that can produce misleading ensemble statistics. A general theory is presented to overcome drawbacks of traditional ensemble forecasting statistics that perform poorly in the presence of timing disagreements among ensemble members. It was shown, in particular, that ensemble forecasts containing substantial uncertainty in timing can produce non-trivial higher-order statistical moments, rendering the ensemble mean inappropriate as a best available estimate of the future state of the forecast parameter in question. A set of theoretical experiments showed that the existence of large timing differences among ensemble members can produce negative ensemble skewness even when the ensemble members are sinusoids whose amplitudes are drawn from a normal distribution: Consistently, the ensemble mean will tend to fall on the left tail of the normal distribution representing the originally sampled amplitudes, rather than at the mean or median. To remedy the left-tail placement problem of the ensemble mean, a new generally applicable ensemble statistic - the phase-aware ensemble mean - is proposed that is more robust against ensemble skewness resulting from timing spread. The computation of the phase-aware mean involves the transformation of all ensemble members to wavelet space and the subsequent inverse wavelet transformation of the product of the ensemble mean wavelet phase and modulus back to the time domain. The new methods were applied to storm surge reforecasts for Hurricane Irene and Sandy at 8 stations located around the New York City metropolitan area. The phase-aware ensemble mean was found to perform better at detecting the magnitude of events compared to the traditional ensemble mean, consistent with the results from theoretical experiments. The ensemble mean, moreover, was found to be consistently located on the left tail of distributions representing future peak storm surge outcomes. A

  20. Towards predictive data-driven simulations of wildfire spread - Part II: Ensemble Kalman Filter for the state estimation of a front-tracking simulator of wildfire spread

    Science.gov (United States)

    Rochoux, M. C.; Emery, C.; Ricci, S.; Cuenot, B.; Trouve, A.

    2015-08-01

    This paper is the second part in a series of two articles, which aims at presenting a data-driven modeling strategy for forecasting wildfire spread scenarios based on the assimilation of the observed fire front location and on the sequential correction of model parameters or model state. This model relies on an estimation of the local rate of fire spread (ROS) as a function of environmental conditions based on Rothermel's semi-empirical formulation, in order to propagate the fire front with an Eulerian front-tracking simulator. In Part I, a data assimilation (DA) system based on an ensemble Kalman filter (EnKF) was implemented to provide a spatially uniform correction of biomass fuel and wind parameters and thereby, produce an improved forecast of the wildfire behavior (addressing uncertainties in the input parameters of the ROS model only). In Part II, the objective of the EnKF algorithm is to sequentially update the two-dimensional coordinates of the markers along the discretized fire front, in order to provide a spatially distributed correction of the fire front location and thereby, a more reliable initial condition for further model time-integration (addressing all sources of uncertainties in the ROS model). The resulting prototype data-driven wildfire spread simulator is first evaluated in a series of verification tests using synthetically generated observations; tests include representative cases with spatially varying biomass properties and temporally varying wind conditions. In order to properly account for uncertainties during the EnKF update step and to accurately represent error correlations along the fireline, it is shown that members of the EnKF ensemble must be generated through variations in estimates of the fire's initial location as well as through variations in the parameters of the ROS model. The performance of the prototype simulator based on state estimation (SE) or parameter estimation (PE) is then evaluated by comparison with data taken from

  1. Polar or apolar--the role of polarity for urea-induced protein denaturation.

    Directory of Open Access Journals (Sweden)

    Martin C Stumpe

    2008-11-01

    Full Text Available Urea-induced protein denaturation is widely used to study protein folding and stability; however, the molecular mechanism and driving forces of this process are not yet fully understood. In particular, it is unclear whether either hydrophobic or polar interactions between urea molecules and residues at the protein surface drive denaturation. To address this question, here, many molecular dynamics simulations totalling ca. 7 micros of the CI2 protein in aqueous solution served to perform a computational thought experiment, in which we varied the polarity of urea. For apolar driving forces, hypopolar urea should show increased denaturation power; for polar driving forces, hyperpolar urea should be the stronger denaturant. Indeed, protein unfolding was observed in all simulations with decreased urea polarity. Hyperpolar urea, in contrast, turned out to stabilize the native state. Moreover, the differential interaction preferences between urea and the 20 amino acids turned out to be enhanced for hypopolar urea and suppressed (or even inverted for hyperpolar urea. These results strongly suggest that apolar urea-protein interactions, and not polar interactions, are the dominant driving force for denaturation. Further, the observed interactions provide a detailed picture of the underlying molecular driving forces. Our simulations finally allowed characterization of CI2 unfolding pathways. Unfolding proceeds sequentially with alternating loss of secondary or tertiary structure. After the transition state, unfolding pathways show large structural heterogeneity.

  2. Spectral diagonal ensemble Kalman filters

    CERN Document Server

    Kasanický, Ivan; Vejmelka, Martin

    2015-01-01

    A new type of ensemble Kalman filter is developed, which is based on replacing the sample covariance in the analysis step by its diagonal in a spectral basis. It is proved that this technique improves the aproximation of the covariance when the covariance itself is diagonal in the spectral basis, as is the case, e.g., for a second-order stationary random field and the Fourier basis. The method is extended by wavelets to the case when the state variables are random fields, which are not spatially homogeneous. Efficient implementations by the fast Fourier transform (FFT) and discrete wavelet transform (DWT) are presented for several types of observations, including high-dimensional data given on a part of the domain, such as radar and satellite images. Computational experiments confirm that the method performs well on the Lorenz 96 problem and the shallow water equations with very small ensembles and over multiple analysis cycles.

  3. DSC study of denaturation of β-lactoglobulin B

    Institute of Scientific and Technical Information of China (English)

    王邦宁; 谈夫

    1995-01-01

    The denaturation of bovine β-lactoglobulin B (β-Lg B) has been studied in phosphate solutions with various concentrations of GuHCl with differential scanning calorimetry The experiments demonstrated that the presence of GuHCl made the β-Lg B undergo both cold denaturation and heat denaturation under the condition of a high concentration of the protein. The enthalpy changes of both kinds of denaturation exhibit opposite signs. Both the cold denaturation and the renaturation of the protein are reproducible, but its heat denaturation is irreversible. The cooperation among monomer molecules of the protein is involved in its heat denaturation The heat denaturation of the protein can be represented by the thermodynamic model Nc D→F. The activation energy of heat denaturation is 285 kJ/mol, which imples that the depression of temperature and enthalpy of heat denaturation of the P-Lg B does not result from decreasing considerably the activation energy by GuHCl As for the cold denaturation of the protein, es

  4. Ensemble Machine Learning Methods and Applications

    CERN Document Server

    Ma, Yunqian

    2012-01-01

    It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face detection and are now being applied in areas as diverse as object trackingand bioinformatics.   Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including various contributions from researchers in leading industrial research labs. At once a solid theoretical study and a practical guide, the volume is a windfall for r...

  5. Ensemble Learning for Free with Evolutionary Algorithms ?

    CERN Document Server

    Gagné, Christian; Schoenauer, Marc; Tomassini, Marco

    2007-01-01

    Evolutionary Learning proceeds by evolving a population of classifiers, from which it generally returns (with some notable exceptions) the single best-of-run classifier as final result. In the meanwhile, Ensemble Learning, one of the most efficient approaches in supervised Machine Learning for the last decade, proceeds by building a population of diverse classifiers. Ensemble Learning with Evolutionary Computation thus receives increasing attention. The Evolutionary Ensemble Learning (EEL) approach presented in this paper features two contributions. First, a new fitness function, inspired by co-evolution and enforcing the classifier diversity, is presented. Further, a new selection criterion based on the classification margin is proposed. This criterion is used to extract the classifier ensemble from the final population only (Off-line) or incrementally along evolution (On-line). Experiments on a set of benchmark problems show that Off-line outperforms single-hypothesis evolutionary learning and state-of-art ...

  6. Hydrological Ensemble Prediction System (HEPS)

    Science.gov (United States)

    Thielen-Del Pozo, J.; Schaake, J.; Martin, E.; Pailleux, J.; Pappenberger, F.

    2010-09-01

    Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Following on the success of the use of ensembles for weather forecasting, the hydrological community now moves increasingly towards Hydrological Ensemble Prediction Systems (HEPS) for improved flood forecasting using operationally available NWP products as inputs. However, these products are often generated on relatively coarse scales compared to hydrologically relevant basin units and suffer systematic biases that may have considerable impact when passed through the non-linear hydrological filters. Therefore, a better understanding on how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes is necessary. The "Hydrologic Ensemble Prediction Experiment" (HEPEX), is an international initiative consisting of hydrologists, meteorologist and end-users to advance probabilistic hydrologic forecast techniques for flood, drought and water management applications. Different aspects of the hydrological ensemble processor are being addressed including • Production of useful meteorological products relevant for hydrological applications, ranging from nowcasting products to seasonal forecasts. The importance of hindcasts that are consistent with the operational weather forecasts will be discussed to support bias correction and downscaling, statistically meaningful verification of HEPS, and the development and testing of operating rules; • Need for downscaling and post-processing of weather ensembles to reduce bias before entering hydrological applications; • Hydrological model and parameter uncertainty and how to correct and

  7. Ensemble Data Mining Methods

    Science.gov (United States)

    Oza, Nikunj C.

    2004-01-01

    Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve better prediction accuracy than any of the individual models could on their own. The basic goal when designing an ensemble is the same as when establishing a committee of people: each member of the committee should be as competent as possible, but the members should be complementary to one another. If the members are not complementary, Le., if they always agree, then the committee is unnecessary---any one member is sufficient. If the members are complementary, then when one or a few members make an error, the probability is high that the remaining members can correct this error. Research in ensemble methods has largely revolved around designing ensembles consisting of competent yet complementary models.

  8. Ensemble Data Mining Methods

    Data.gov (United States)

    National Aeronautics and Space Administration — Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve...

  9. Extended Ensemble Monte Carlo

    OpenAIRE

    Iba, Yukito

    2000-01-01

    ``Extended Ensemble Monte Carlo''is a generic term that indicates a set of algorithms which are now popular in a variety of fields in physics and statistical information processing. Exchange Monte Carlo (Metropolis-Coupled Chain, Parallel Tempering), Simulated Tempering (Expanded Ensemble Monte Carlo), and Multicanonical Monte Carlo (Adaptive Umbrella Sampling) are typical members of this family. Here we give a cross-disciplinary survey of these algorithms with special emphasis on the great f...

  10. Ensembl variation resources

    Directory of Open Access Journals (Sweden)

    Marin-Garcia Pablo

    2010-05-01

    Full Text Available Abstract Background The maturing field of genomics is rapidly increasing the number of sequenced genomes and producing more information from those previously sequenced. Much of this additional information is variation data derived from sampling multiple individuals of a given species with the goal of discovering new variants and characterising the population frequencies of the variants that are already known. These data have immense value for many studies, including those designed to understand evolution and connect genotype to phenotype. Maximising the utility of the data requires that it be stored in an accessible manner that facilitates the integration of variation data with other genome resources such as gene annotation and comparative genomics. Description The Ensembl project provides comprehensive and integrated variation resources for a wide variety of chordate genomes. This paper provides a detailed description of the sources of data and the methods for creating the Ensembl variation databases. It also explores the utility of the information by explaining the range of query options available, from using interactive web displays, to online data mining tools and connecting directly to the data servers programmatically. It gives a good overview of the variation resources and future plans for expanding the variation data within Ensembl. Conclusions Variation data is an important key to understanding the functional and phenotypic differences between individuals. The development of new sequencing and genotyping technologies is greatly increasing the amount of variation data known for almost all genomes. The Ensembl variation resources are integrated into the Ensembl genome browser and provide a comprehensive way to access this data in the context of a widely used genome bioinformatics system. All Ensembl data is freely available at http://www.ensembl.org and from the public MySQL database server at ensembldb.ensembl.org.

  11. Demonstrating the value of larger ensembles in forecasting physical systems

    Directory of Open Access Journals (Sweden)

    Reason L. Machete

    2016-12-01

    Full Text Available Ensemble simulation propagates a collection of initial states forward in time in a Monte Carlo fashion. Depending on the fidelity of the model and the properties of the initial ensemble, the goal of ensemble simulation can range from merely quantifying variations in the sensitivity of the model all the way to providing actionable probability forecasts of the future. Whatever the goal is, success depends on the properties of the ensemble, and there is a longstanding discussion in meteorology as to the size of initial condition ensemble most appropriate for Numerical Weather Prediction. In terms of resource allocation: how is one to divide finite computing resources between model complexity, ensemble size, data assimilation and other components of the forecast system. One wishes to avoid undersampling information available from the model's dynamics, yet one also wishes to use the highest fidelity model available. Arguably, a higher fidelity model can better exploit a larger ensemble; nevertheless it is often suggested that a relatively small ensemble, say ~16 members, is sufficient and that larger ensembles are not an effective investment of resources. This claim is shown to be dubious when the goal is probabilistic forecasting, even in settings where the forecast model is informative but imperfect. Probability forecasts for a ‘simple’ physical system are evaluated at different lead times; ensembles of up to 256 members are considered. The pure density estimation context (where ensemble members are drawn from the same underlying distribution as the target differs from the forecasting context, where one is given a high fidelity (but imperfect model. In the forecasting context, the information provided by additional members depends also on the fidelity of the model, the ensemble formation scheme (data assimilation, the ensemble interpretation and the nature of the observational noise. The effect of increasing the ensemble size is quantified by

  12. Supercoiling induces denaturation bubbles in circular DNA.

    Science.gov (United States)

    Jeon, Jae-Hyung; Adamcik, Jozef; Dietler, Giovanni; Metzler, Ralf

    2010-11-12

    We present a theoretical framework for the thermodynamic properties of supercoiling-induced denaturation bubbles in circular double-stranded DNA molecules. We explore how DNA supercoiling, ambient salt concentration, and sequence heterogeneity impact on the bubble occurrence. An analytical derivation of the probability distribution to find multiple bubbles is derived and the relevance for supercoiled DNA discussed. We show that in vivo sustained DNA bubbles are likely to occur due to partial twist release in regions rich in weaker AT base pairs. Single DNA plasmid imaging experiments clearly demonstrate the existence of bubbles in free solution.

  13. Ensemble data assimilation with an adjusted forecast spread

    Directory of Open Access Journals (Sweden)

    Sabrina Rainwater

    2013-04-01

    Full Text Available Ensemble data assimilation typically evolves an ensemble of model states whose spread is intended to represent the algorithm's uncertainty about the state of the physical system that produces the data. The analysis phase treats the forecast ensemble as a random sample from a background distribution, and it transforms the ensemble according to the background and observation error statistics to provide an appropriate sample for the next forecast phase. We find that in the presence of model nonlinearity and model error, it can be fruitful to rescale the ensemble spread prior to the forecast and then reverse this rescaling after the forecast. We call this approach forecast spread adjustment, which we discuss and test in this article using an ensemble Kalman filter and a 2005 model due to Lorenz. We argue that forecast spread adjustment provides a tunable parameter, that is, complementary to covariance inflation, which cumulatively increases ensemble spread to compensate for underestimation of uncertainty. We also show that as the adjustment parameter approaches zero, the filter approaches the extended Kalman filter if the ensemble size is sufficiently large. We find that varying the adjustment parameter can significantly reduce analysis and forecast errors in some cases. We evaluate how the improvement provided by forecast spread adjustment depends on ensemble size, observation error and model error. Our results indicate that the technique is most effective for small ensembles, small observation error and large model error, though the effectiveness depends significantly on the nature of the model error.

  14. Reversible Dimerization of Acid-Denatured ACBP Controlled by Helix A4

    DEFF Research Database (Denmark)

    Fieber, Wolfgang; Kragelund, Birthe Brandt; Meldal, Morten Peter;

    2005-01-01

    of dimers and revealed a cooperative stabilization of helix A4 in this process. This emphasizes its special role in the structure formation in the denatured state of ACBP. No dimers are formed in the presence of guanidine hydrochloride, which underlines the fundamental difference between the nature...

  15. Assessing the value of post-processed state-of-the-art long-term weather forecast ensembles for agricultural water management mediated by farmers' behaviours

    Science.gov (United States)

    Li, Yu; Giuliani, Matteo; Castelletti, Andrea

    2016-04-01

    Recent advances in modelling of coupled ocean-atmosphere dynamics significantly improved skills of long-term climate forecast from global circulation models (GCMs). These more accurate weather predictions are supposed to be a valuable support to farmers in optimizing farming operations (e.g. crop choice, cropping and watering time) and for more effectively coping with the adverse impacts of climate variability. Yet, assessing how actually valuable this information can be to a farmer is not straightforward and farmers' response must be taken into consideration. Indeed, in the context of agricultural systems potentially useful forecast information should alter stakeholders' expectation, modify their decisions, and ultimately produce an impact on their performance. Nevertheless, long-term forecast are mostly evaluated in terms of accuracy (i.e., forecast quality) by comparing hindcast and observed values and only few studies investigated the operational value of forecast looking at the gain of utility within the decision-making context, e.g. by considering the derivative of forecast information, such as simulated crop yields or simulated soil moisture, which are essential to farmers' decision-making process. In this study, we contribute a step further in the assessment of the operational value of long-term weather forecasts products by embedding these latter into farmers' behavioral models. This allows a more critical assessment of the forecast value mediated by the end-users' perspective, including farmers' risk attitudes and behavioral patterns. Specifically, we evaluate the operational value of thirteen state-of-the-art long-range forecast products against climatology forecast and empirical prediction (i.e. past year climate and historical average) within an integrated agronomic modeling framework embedding an implicit model of the farmers' decision-making process. Raw ensemble datasets are bias-corrected and downscaled using a stochastic weather generator, in

  16. 27 CFR 21.151 - List of denaturants authorized for denatured spirits.

    Science.gov (United States)

    2010-04-01

    ... TOBACCO TAX AND TRADE BUREAU, DEPARTMENT OF THE TREASURY LIQUORS FORMULAS FOR DENATURED ALCOHOL AND RUM... (Glycerol), U.S.P S.D.A. 31-A. Green soap, U.S.P S.D.A. 27-B. Guaiacol, N.F.X S.D.A. 38-B. Heptane C.D.A....

  17. 78 FR 38628 - Reclassification of Specially Denatured Spirits and Completely Denatured Alcohol Formulas and...

    Science.gov (United States)

    2013-06-27

    ... alcohol. 13-A 10 gallons of ethyl ether. 19 100 gallons of ethyl ether. 23-A 8 gallons of acetone, U.S.P... alcohol. 32 5 gallons of ethyl ether. 35-A 4.25 gallons of ethyl acetate having an ester content of 100... regulations regarding the production, warehousing, denaturing, distribution, sale, export, and use...

  18. Classical and Quantum Ensembles via Multiresolution. II. Wigner Ensembles

    CERN Document Server

    Fedorova, A N; Fedorova, Antonina N.; Zeitlin, Michael G.

    2004-01-01

    We present the application of the variational-wavelet analysis to the analysis of quantum ensembles in Wigner framework. (Naive) deformation quantization, the multiresolution representations and the variational approach are the key points. We construct the solutions of Wigner-like equations via the multiscale expansions in the generalized coherent states or high-localized nonlinear eigenmodes in the base of the compactly supported wavelets and the wavelet packets. We demonstrate the appearance of (stable) localized patterns (waveletons) and consider entanglement and decoherence as possible applications.

  19. Minimal redefinition of the OSV ensemble

    CERN Document Server

    Parvizi, S; Parvizi, Shahrokh; Tavanfar, Alireza

    2005-01-01

    In the interesting conjecture, Z_{BH}=|Z_{top}|^2, proposed by Ooguri, Strominger and Vafa (OSV), the black hole ensemble is a mixed ensemble, and resulting degeneracy of states as obtained from the ensemble inverse-Laplace integration, suffer from prefactors which do not respect the (relevant) electric-magnetic dualities. One idea to overcome this deficiency, as claimed recently, is imposing a nontrivial measure for the ensemble sum. We address this problem and upon a redefinition of the OSV ensemble whose variables are as numerous as the electric potentials, show that for restoring the symmetry no non-Euclidean measure is needful. In detail, we rewrite the OSV free energy as a function of new variables which are combinations of the electric-potentials and the black hole charges. Subsequently the Legendre transformation which bridges between the entropy and the black hole free energy in terms of these variables, points to a generalized ensemble. In this context we will consider all the cases of relevance: sm...

  20. The semantic similarity ensemble

    Directory of Open Access Journals (Sweden)

    Andrea Ballatore

    2013-12-01

    Full Text Available Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach.

  1. Ensemble Methods Foundations and Algorithms

    CERN Document Server

    Zhou, Zhi-Hua

    2012-01-01

    An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field. After presenting background and terminology, the book covers the main algorithms and theories, including Boosting, Bagging, Random Forest, averaging and voting schemes, the Stacking method, mixture of experts, and diversity measures. It also discusses multiclass extension, noise tolerance, error-ambiguity a

  2. A Localized Ensemble Kalman Smoother

    Science.gov (United States)

    Butala, Mark D.

    2012-01-01

    Numerous geophysical inverse problems prove difficult because the available measurements are indirectly related to the underlying unknown dynamic state and the physics governing the system may involve imperfect models or unobserved parameters. Data assimilation addresses these difficulties by combining the measurements and physical knowledge. The main challenge in such problems usually involves their high dimensionality and the standard statistical methods prove computationally intractable. This paper develops and addresses the theoretical convergence of a new high-dimensional Monte-Carlo approach called the localized ensemble Kalman smoother.

  3. Deformed Gaussian Orthogonal Ensemble Analysis of the Interacting Boson Model

    CERN Document Server

    Pato, M P; Lima, C L; Hussein, M S; Alhassid, Y

    1994-01-01

    A Deformed Gaussian Orthogonal Ensemble (DGOE) which interpolates between the Gaussian Orthogonal Ensemble and a Poissonian Ensemble is constructed. This new ensemble is then applied to the analysis of the chaotic properties of the low lying collective states of nuclei described by the Interacting Boson Model (IBM). This model undergoes a transition order-chaos-order from the $SU(3)$ limit to the $O(6)$ limit. Our analysis shows that the quantum fluctuations of the IBM Hamiltonian, both of the spectrum and the eigenvectors, follow the expected behaviour predicted by the DGOE when one goes from one limit to the other.

  4. Relation between native ensembles and experimental structures of proteins

    DEFF Research Database (Denmark)

    Best, R. B.; Lindorff-Larsen, Kresten; DePristo, M. A.

    2006-01-01

    Different experimental structures of the same protein or of proteins with high sequence similarity contain many small variations. Here we construct ensembles of "high-sequence similarity Protein Data Bank" (HSP) structures and consider the extent to which such ensembles represent the structural...... Data Bank ensembles; moreover, we show that the effects of uncertainties in structure determination are insufficient to explain the results. These results highlight the importance of accounting for native-state protein dynamics in making comparisons with ensemble-averaged experimental data and suggest...

  5. Sufficient minimal model for DNA denaturation: Integration of harmonic scalar elasticity and bond energies.

    Science.gov (United States)

    Singh, Amit Raj; Granek, Rony

    2016-10-14

    We study DNA denaturation by integrating elasticity - as described by the Gaussian network model - with bond binding energies, distinguishing between different base pairs and stacking energies. We use exact calculation, within the model, of the Helmholtz free-energy of any partial denaturation state, which implies that the entropy of all formed "bubbles" ("loops") is accounted for. Considering base pair bond removal single events, the bond designated for opening is chosen by minimizing the free-energy difference for the process, over all remaining base pair bonds. Despite of its great simplicity, for several known DNA sequences our results are in accord with available theoretical and experimental studies. Moreover, we report free-energy profiles along the denaturation pathway, which allow to detect stable or meta-stable partial denaturation states, composed of bubble, as local free-energy minima separated by barriers. Our approach allows to study very long DNA strands with commonly available computational power, as we demonstrate for a few random sequences in the range 200-800 base-pairs. For the latter, we also elucidate the self-averaging property of the system. Implications for the well known breathing dynamics of DNA are elucidated.

  6. Sufficient minimal model for DNA denaturation: Integration of harmonic scalar elasticity and bond energies

    Science.gov (United States)

    Singh, Amit Raj; Granek, Rony

    2016-10-01

    We study DNA denaturation by integrating elasticity — as described by the Gaussian network model — with bond binding energies, distinguishing between different base pairs and stacking energies. We use exact calculation, within the model, of the Helmholtz free-energy of any partial denaturation state, which implies that the entropy of all formed "bubbles" ("loops") is accounted for. Considering base pair bond removal single events, the bond designated for opening is chosen by minimizing the free-energy difference for the process, over all remaining base pair bonds. Despite of its great simplicity, for several known DNA sequences our results are in accord with available theoretical and experimental studies. Moreover, we report free-energy profiles along the denaturation pathway, which allow to detect stable or meta-stable partial denaturation states, composed of bubble, as local free-energy minima separated by barriers. Our approach allows to study very long DNA strands with commonly available computational power, as we demonstrate for a few random sequences in the range 200-800 base-pairs. For the latter, we also elucidate the self-averaging property of the system. Implications for the well known breathing dynamics of DNA are elucidated.

  7. Can A Denaturant Stabilize DNA? Pyridine Reverses DNA Denaturation in Acidic pH.

    Science.gov (United States)

    Portella, Guillem; Terrazas, Montserrat; Villegas, Núria; González, Carlos; Orozco, Modesto

    2015-09-01

    The stability of DNA is highly dependent on the properties of the surrounding solvent, such as ionic strength, pH, and the presence of denaturants and osmolytes. Addition of pyridine is known to unfold DNA by replacing π-π stacking interactions between bases, stabilizing conformations in which the nucleotides are solvent exposed. We show here experimental and theoretical evidences that pyridine can change its role and in fact stabilize the DNA under acidic conditions. NMR spectroscopy and MD simulations demonstrate that the reversal in the denaturing role of pyridine is specific, and is related to its character as pseudo groove binder. The present study sheds light on the nature of DNA stability and on the relationship between DNA and solvent, with clear biotechnological implications.

  8. Visualizing ensembles in structural biology.

    Science.gov (United States)

    Melvin, Ryan L; Salsbury, Freddie R

    2016-06-01

    Displaying a single representative conformation of a biopolymer rather than an ensemble of states mistakenly conveys a static nature rather than the actual dynamic personality of biopolymers. However, there are few apparent options due to the fixed nature of print media. Here we suggest a standardized methodology for visually indicating the distribution width, standard deviation and uncertainty of ensembles of states with little loss of the visual simplicity of displaying a single representative conformation. Of particular note is that the visualization method employed clearly distinguishes between isotropic and anisotropic motion of polymer subunits. We also apply this method to ligand binding, suggesting a way to indicate the expected error in many high throughput docking programs when visualizing the structural spread of the output. We provide several examples in the context of nucleic acids and proteins with particular insights gained via this method. Such examples include investigating a therapeutic polymer of FdUMP (5-fluoro-2-deoxyuridine-5-O-monophosphate) - a topoisomerase-1 (Top1), apoptosis-inducing poison - and nucleotide-binding proteins responsible for ATP hydrolysis from Bacillus subtilis. We also discuss how these methods can be extended to any macromolecular data set with an underlying distribution, including experimental data such as NMR structures.

  9. Protective Garment Ensemble

    Science.gov (United States)

    Wakefield, M. E.

    1982-01-01

    Protective garment ensemble with internally-mounted environmental- control unit contains its own air supply. Alternatively, a remote-environmental control unit or an air line is attached at the umbilical quick disconnect. Unit uses liquid air that is vaporized to provide both breathing air and cooling. Totally enclosed garment protects against toxic substances.

  10. Music Ensemble: Course Proposal.

    Science.gov (United States)

    Kovach, Brian

    A proposal is presented for a Music Ensemble course to be offered at the Community College of Philadelphia for music students who have had previous vocal or instrumental training. A standardized course proposal cover form is followed by a statement of purpose for the course, a list of major course goals, a course outline, and a bibliography. Next,…

  11. Neural Network Ensembles

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Salamon, Peter

    1990-01-01

    We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....

  12. Kinetically controlled refolding of a heat-denatured hyperthermostable protein

    NARCIS (Netherlands)

    Koutsopoulos, Sotirios; van der Oost, John; Norde, Willem

    2007-01-01

    The thermal denaturation of endo-beta-1,3-glucanase from the hyperthermophilic microorganism Pyrococcus furiosus was studied by calorimetry. The calorimetric profile revealed two transitions at 109 and 144 degrees C, corresponding to protein denaturation and complete unfolding, respectively, as

  13. Kinetically controlled refolding of a heat denatured hyperthermostable protein

    NARCIS (Netherlands)

    Koutsopoulos, S.; Oost, van der J.; Norde, W.

    2007-01-01

    The thermal denaturation of endo-ß-1,3-glucanase from the hyperthermophilic microorganism Pyrococcus furiosus was studied by calorimetry. The calorimetric profile revealed two transitions at 109 and 144¿°C, corresponding to protein denaturation and complete unfolding, respectively, as shown by

  14. 19 CFR 10.56 - Vegetable oils, denaturing; release.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 1 2010-04-01 2010-04-01 false Vegetable oils, denaturing; release. 10.56 Section... Vegetable Oils § 10.56 Vegetable oils, denaturing; release. (a) Olive, palm-kernel, rapeseed, sunflower, and sesame oil shall be classifiable under subheadings 1509.10.20, 1509.10.40, 1509.90.20, 1509.90.40,...

  15. 27 CFR 19.464 - Denatured spirits inventories.

    Science.gov (United States)

    2010-04-01

    ... inventories. 19.464 Section 19.464 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE... of Articles Inventories § 19.464 Denatured spirits inventories. Each proprietor shall take a physical inventory of all denatured spirits in the processing account at the close of each calendar quarter and...

  16. 27 CFR 20.144 - Packages of completely denatured alcohol.

    Science.gov (United States)

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Packages of completely denatured alcohol. 20.144 Section 20.144 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE BUREAU, DEPARTMENT OF THE TREASURY LIQUORS DISTRIBUTION AND USE OF DENATURED ALCOHOL AND RUM...

  17. 27 CFR 20.261 - Records of completely denatured alcohol.

    Science.gov (United States)

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Records of completely denatured alcohol. 20.261 Section 20.261 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE BUREAU, DEPARTMENT OF THE TREASURY LIQUORS DISTRIBUTION AND USE OF DENATURED ALCOHOL AND...

  18. Locally Accessible Information from Multipartite Ensembles

    Institute of Scientific and Technical Information of China (English)

    SONG Wei

    2009-01-01

    We present a universal Holevo-like upper bound on the locally accessible information for arbitrary multipartite ensembles.This bound allows us to analyze the indistinguishability of a set of orthogonal states under local operations and classical communication.We also derive the upper bound for the capacity of distributed dense coding with multipartite senders and multipartite receivers.

  19. Statistical theory of hierarchical avalanche ensemble

    OpenAIRE

    Olemskoi, Alexander I.

    1999-01-01

    The statistical ensemble of avalanche intensities is considered to investigate diffusion in ultrametric space of hierarchically subordinated avalanches. The stationary intensity distribution and the steady-state current are obtained. The critical avalanche intensity needed to initiate the global avalanche formation is calculated depending on noise intensity. The large time asymptotic for the probability of the global avalanche appearance is derived.

  20. Gradual disordering of the native state on a slow two-state folding protein monitored by single-molecule fluorescence spectroscopy and NMR.

    Science.gov (United States)

    Campos, Luis A; Sadqi, Mourad; Liu, Jianwei; Wang, Xiang; English, Douglas S; Muñoz, Victor

    2013-10-24

    Theory predicts that folding free energy landscapes are intrinsically malleable and as such are expected to respond to perturbations in topographically complex ways. Structural changes upon perturbation have been observed experimentally for unfolded ensembles, folding transition states, and fast downhill folding proteins. However, the native state of proteins that fold in a two-state fashion is conventionally assumed to be structurally invariant during unfolding. Here we investigate how the native and unfolded states of the chicken α-spectrin SH3 domain (a well characterized slow two-state folder) change in response to chemical denaturants and/or temperature. We can resolve the individual properties of the two end-states across the chemical unfolding transition employing single-molecule fluorescence spectroscopy (SM-FRET) and across the thermal unfolding transition by NMR because SH3 folds-unfolds in the slow chemical exchange regime. Our results demonstrate that α-spectrin SH3 unfolds in a canonical way in the sense that it converts between the native state and an unfolded ensemble that expands in response to chemical denaturants. However, as conditions become increasingly destabilizing, the native state also expands gradually, and a large fraction of its native intramolecular hydrogen bonds break up. This gradual disordering of the native state takes place in times shorter than the 100 μs resolution of our SM-FRET experiments. α-Spectrin SH3 thus showcases the extreme plasticity of folding landscapes, which extends to the native state of slow two-state proteins. Our results point to the idea that folding mechanisms under physiological conditions might be quite different from those obtained by linear extrapolation from denaturing conditions. Furthermore, they highlight a pressing need for re-evaluating the conventional procedures for analyzing and interpreting folding experiments, which may be based on too-simplistic assumptions.

  1. Deterministic entanglement of Rydberg ensembles by engineered dissipation

    DEFF Research Database (Denmark)

    Dasari, Durga; Mølmer, Klaus

    2014-01-01

    We propose a scheme that employs dissipation to deterministically generate entanglement in an ensemble of strongly interacting Rydberg atoms. With a combination of microwave driving between different Rydberg levels and a resonant laser coupling to a short lived atomic state, the ensemble can...... be driven towards a dark steady state that entangles all atoms. The long-range resonant dipole-dipole interaction between different Rydberg states extends the entanglement beyond the van der Walls interaction range with perspectives for entangling large and distant ensembles....

  2. Nonextensivity in magnetic nanoparticle ensembles

    Science.gov (United States)

    Binek, Ch.; Polisetty, S.; He, Xi; Mukherjee, T.; Rajesh, R.; Redepenning, J.

    2006-08-01

    A superconducting quantum interference device and Faraday rotation technique are used to study dipolar interacting nanoparticles embedded in a polystyrene matrix. Magnetization isotherms are measured for three cylindrically shaped samples of constant diameter but various heights. Detailed analysis of the isotherms supports Tsallis’ conjecture of a magnetic equation of state that involves temperature and magnetic field variables scaled by the logarithm of the number of magnetic nanoparticles. This unusual scaling of thermodynamic variables, which are conventionally considered to be intensive, originates from the nonextensivity of the Gibbs free energy in three-dimensional dipolar interacting particle ensembles. Our experimental evidence for nonextensivity is based on the data collapse of various isotherms that require scaling of the field variable in accordance with Tsallis’ equation of state.

  3. Thermal denaturation of protein studied by terahertz time-domain spectroscopy

    Science.gov (United States)

    Fu, Xiuhua; Li, Xiangjun; Liu, Jianjun; Du, Yong; Hong, Zhi

    2012-12-01

    In this study, the absorption spectra of native or thermal protein were measured in 0.2-1.4THz using terahertz time-domain spectroscopy (THz-TDS) system at room temperature, their absorption spectra and the refractive spectra were obtained. Experimental results indicate that protein both has strong absorption but their characteristics were not distinct in the THz region, and the absorption decreased during thermal denatured state. In order to prove protein had been denatured, we used Differential scanning calorimeter (DSC) measured their denatured temperature, from their DSC heating traces, collagen Td=101℃, Bovine serum albumin Td=97℃. While we also combined the Fourier transform infrared spectrometer (FTIR) to investigate their secondary and tertiary structure before and after denatuation, but the results did not have the distinct changes. We turned the absorption spectra and the refractive spectra to the dielectric spectra, and used the one-stage Debye model simulated the terahertz dielectric spectra of protein before and after denaturation. This research proved that the terahertz spectrum technology is feasible in testing protein that were affected by temperature or other factors which can provide theoretical foundation in the further study about the THz spectrum of protein and peptide temperature stability.

  4. Denaturing Effects of Urea and Guanidine Hydrochloride on Hyperthermophilic Esterase from Aeropyrum pernix K1

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The changes in the activity and the conformation of the hyperthermophilic esterase derived from aerobic thermophilic Aeropyrumpernix K1 (APE1547) were studied during denaturation by guanidine hydrochloride (GdnHCl)and urea. The denaturation course of APE1547 was followed by the steady-state and time resolved fluorescence methods. An increase in the denaturant concentration in the denatured system can significantly enhance the inactivation and unfolding of APE1547. The enzyme can be completely inactivated with a urea concentration of 2. 7 mol/L or a GdnHCl concentration of 7.5 mol/L. The fluorescence emission maximum of the enzyme protein red shifts in magnitude to a maximum value(355 nm) when the concentration of GdnHCl is 5.1 mol/L. The experimental results indicate that APE1547 has a high resistance to urea. Unfolding of APE1547 in GdnHCl(4.2-6.0 mol/L) was shown to be an irreversible process. The present results indicate that the ion pairs in this protein may be a key factor for the stability of this esterase.

  5. Excitations and benchmark ensemble density functional theory for two electrons

    CERN Document Server

    Pribram-Jones, Aurora; Trail, John R; Burke, Kieron; Needs, Richard J; Ullrich, Carsten A

    2014-01-01

    A new method for extracting ensemble Kohn-Sham potentials from accurate excited state densities is applied to a variety of two electron systems, exploring the behavior of exact ensemble density functional theory. The issue of separating the Hartree energy and the choice of degenerate eigenstates is explored. A new approximation, spin eigenstate Hartree-exchange (SEHX), is derived. Exact conditions that are proven include the signs of the correlation energy components, the virial theorem for both exchange and correlation, and the asymptotic behavior of the potential for small weights of the excited states. Many energy components are given as a function of the weights for two electrons in a one-dimensional flat box, in a box with a large barrier to create charge transfer excitations, in a three-dimensional harmonic well (Hooke's atom), and for the He atom singlet-triplet ensemble, singlet-triplet-singlet ensemble, and triplet bi-ensemble.

  6. Excitations and benchmark ensemble density functional theory for two electrons

    Energy Technology Data Exchange (ETDEWEB)

    Pribram-Jones, Aurora; Burke, Kieron [Department of Chemistry, University of California-Irvine, Irvine, California 92697 (United States); Yang, Zeng-hui; Ullrich, Carsten A. [Department of Physics and Astronomy, University of Missouri, Columbia, Missouri 65211 (United States); Trail, John R.; Needs, Richard J. [Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Cambridge CB3 0HE (United Kingdom)

    2014-05-14

    A new method for extracting ensemble Kohn-Sham potentials from accurate excited state densities is applied to a variety of two-electron systems, exploring the behavior of exact ensemble density functional theory. The issue of separating the Hartree energy and the choice of degenerate eigenstates is explored. A new approximation, spin eigenstate Hartree-exchange, is derived. Exact conditions that are proven include the signs of the correlation energy components and the asymptotic behavior of the potential for small weights of the excited states. Many energy components are given as a function of the weights for two electrons in a one-dimensional flat box, in a box with a large barrier to create charge transfer excitations, in a three-dimensional harmonic well (Hooke's atom), and for the He atom singlet-triplet ensemble, singlet-triplet-singlet ensemble, and triplet bi-ensemble.

  7. Induced Ginibre ensemble of random matrices and quantum operations

    CERN Document Server

    Fischmann, J; Khoruzhenko, B A; Sommers, H -J; Zyczkowski, K

    2011-01-01

    A generalisation of the Ginibre ensemble of non-Hermitian random square matrices is introduced. The corresponding probability measure is induced by the ensemble of rectangular Gaussian matrices via a quadratisation procedure. We derive the joint probability density of eigenvalues for such induced Ginibre ensemble and study various spectral correlation functions for complex and real matrices, and analyse universal behaviour in the limit of large dimensions. In this limit the eigenvalues of the induced Ginibre ensemble cover uniformly a ring in the complex plane. The real induced Ginibre ensemble is shown to be useful to describe statistical properties of evolution operators associated with random quantum operations, for which the dimensions of the input state and the output state do differ.

  8. Thermal denaturation of A-DNA

    Science.gov (United States)

    Valle-Orero, J.; Wildes, A. R.; Theodorakopoulos, N.; Cuesta-López, S.; Garden, J.-L.; Danilkin, S.; Peyrard, M.

    2014-11-01

    The DNA molecule can take various conformational forms. Investigations focus mainly on the so-called ‘B-form’, schematically drawn in the famous paper by Watson and Crick [1]. This is the usual form of DNA in a biological environment and is the only form that is stable in an aqueous environment. Other forms, however, can teach us much about DNA. They have the same nucleotide base pairs for ‘building blocks’ as B-DNA, but with different relative positions, and studying these forms gives insight into the interactions between elements under conditions far from equilibrium in the B-form. Studying the thermal denaturation is particularly interesting because it provides a direct probe of those interactions which control the growth of the fluctuations when the ‘melting’ temperature is approached. Here we report such a study on the ‘A-form’ using calorimetry and neutron scattering. We show that it can be carried further than a similar study on B-DNA, requiring the improvement of thermodynamic models for DNA.

  9. Hierarchical Bayes Ensemble Kalman Filtering

    CERN Document Server

    Tsyrulnikov, Michael

    2015-01-01

    Ensemble Kalman filtering (EnKF), when applied to high-dimensional systems, suffers from an inevitably small affordable ensemble size, which results in poor estimates of the background error covariance matrix ${\\bf B}$. The common remedy is a kind of regularization, usually an ad-hoc spatial covariance localization (tapering) combined with artificial covariance inflation. Instead of using an ad-hoc regularization, we adopt the idea by Myrseth and Omre (2010) and explicitly admit that the ${\\bf B}$ matrix is unknown and random and estimate it along with the state (${\\bf x}$) in an optimal hierarchical Bayes analysis scheme. We separate forecast errors into predictability errors (i.e. forecast errors due to uncertainties in the initial data) and model errors (forecast errors due to imperfections in the forecast model) and include the two respective components ${\\bf P}$ and ${\\bf Q}$ of the ${\\bf B}$ matrix into the extended control vector $({\\bf x},{\\bf P},{\\bf Q})$. Similarly, we break the traditional backgrou...

  10. Effective Visualization of Temporal Ensembles.

    Science.gov (United States)

    Hao, Lihua; Healey, Christopher G; Bass, Steffen A

    2016-01-01

    An ensemble is a collection of related datasets, called members, built from a series of runs of a simulation or an experiment. Ensembles are large, temporal, multidimensional, and multivariate, making them difficult to analyze. Another important challenge is visualizing ensembles that vary both in space and time. Initial visualization techniques displayed ensembles with a small number of members, or presented an overview of an entire ensemble, but without potentially important details. Recently, researchers have suggested combining these two directions, allowing users to choose subsets of members to visualization. This manual selection process places the burden on the user to identify which members to explore. We first introduce a static ensemble visualization system that automatically helps users locate interesting subsets of members to visualize. We next extend the system to support analysis and visualization of temporal ensembles. We employ 3D shape comparison, cluster tree visualization, and glyph based visualization to represent different levels of detail within an ensemble. This strategy is used to provide two approaches for temporal ensemble analysis: (1) segment based ensemble analysis, to capture important shape transition time-steps, clusters groups of similar members, and identify common shape changes over time across multiple members; and (2) time-step based ensemble analysis, which assumes ensemble members are aligned in time by combining similar shapes at common time-steps. Both approaches enable users to interactively visualize and analyze a temporal ensemble from different perspectives at different levels of detail. We demonstrate our techniques on an ensemble studying matter transition from hadronic gas to quark-gluon plasma during gold-on-gold particle collisions.

  11. Stabilization of Human Serum Albumin against Urea Denaturation by Diazepam and Ketoprofen.

    Science.gov (United States)

    Manoharan, Pralad; Wong, Yin H; Tayyab, Saad

    2015-01-01

    Stabilizing effect of diazepam and ketoprofen, Sudlow's site II markers on human serum albumin (HSA) against urea denaturation was studied using fluorescence spectroscopy. The two-step, three-state urea transition of HSA was transformed into a single-step, two-state transition with the abolishment of the intermediate state along with a shift of the transition curve towards higher urea concentrations in the presence of diazepam or ketoprofen. Interestingly, a greater shift in the transition curve of HSA was observed in the presence of ketoprofen compared to diazepam. A comparison of the intrinsic fluorescence and three-dimensional fluorescence spectra of HSA and partially-denatured HSAs, obtained in the absence and the presence of diazepam or ketoprofen suggested significant retention of native-like conformation in the partially-denatured states of HSA in the presence of Sudlow's site II markers. Taken together, all these results suggested stabilization of HSA in the presence of diazepam or ketoprofen, being greater in the presence of ketoprofen.

  12. [Some properties of complexes formed by small heat shock proteins with denatured actin].

    Science.gov (United States)

    Pivovarova, A V; Chebotareva, N A; Guseev, N B; Levitskiĭ, D I

    2008-01-01

    We applied different methods to analyze the effects of the recombinant wild-type small heat shock protein with an apparent molecular mass of 27 kD (Hsp27-wt) and its S15,78,82D mutant (Hsp27-3D), which mimics the naturally occurring phosphorylation of this protein, on the thermal denaturation and aggregation of F-actin. It has been shown that, at the weight ratio of Hsp27/actin equal to 1/4, both Hsp27-wt and Hsp27-3D do not affect the thermal unfolding of F-actin but effectively prevent the aggregation of F-actin by forming soluble complexes with denatured actin. The formation of these complexes occurs upon heating and accompanies the F-actin thermal denaturation. It is known that Hsp27-wt forms high-molecular-mass oligomers, whereas Hsp27-3D forms small dimers or tetramers. However, the complexes formed by Hsp27-wt and Hsp27-3D with denatured actin did not differ in their size, as measured by dynamic light scattering, and demonstrated the same hydrodynamic radius of 17-18 nm. On the other hand, the sedimentation coefficients of these complexes were distributed within the range 10-45 S in the case of Hsp27-3D and 18-60 S in the case of Hsp27-wt. Thus, the ability of Hsp27 to form soluble complexes with denatured actin does not significantly depend on the initial oligomeric state of Hsp27.

  13. The role of ensemble post-processing for modeling the ensemble tail

    Science.gov (United States)

    Van De Vyver, Hans; Van Schaeybroeck, Bert; Vannitsem, Stéphane

    2016-04-01

    The past decades the numerical weather prediction community has witnessed a paradigm shift from deterministic to probabilistic forecast and state estimation (Buizza and Leutbecher, 2015; Buizza et al., 2008), in an attempt to quantify the uncertainties associated with initial-condition and model errors. An important benefit of a probabilistic framework is the improved prediction of extreme events. However, one may ask to what extent such model estimates contain information on the occurrence probability of extreme events and how this information can be optimally extracted. Different approaches have been proposed and applied on real-world systems which, based on extreme value theory, allow the estimation of extreme-event probabilities conditional on forecasts and state estimates (Ferro, 2007; Friederichs, 2010). Using ensemble predictions generated with a model of low dimensionality, a thorough investigation is presented quantifying the change of predictability of extreme events associated with ensemble post-processing and other influencing factors including the finite ensemble size, lead time and model assumption and the use of different covariates (ensemble mean, maximum, spread...) for modeling the tail distribution. Tail modeling is performed by deriving extreme-quantile estimates using peak-over-threshold representation (generalized Pareto distribution) or quantile regression. Common ensemble post-processing methods aim to improve mostly the ensemble mean and spread of a raw forecast (Van Schaeybroeck and Vannitsem, 2015). Conditional tail modeling, on the other hand, is a post-processing in itself, focusing on the tails only. Therefore, it is unclear how applying ensemble post-processing prior to conditional tail modeling impacts the skill of extreme-event predictions. This work is investigating this question in details. Buizza, Leutbecher, and Isaksen, 2008: Potential use of an ensemble of analyses in the ECMWF Ensemble Prediction System, Q. J. R. Meteorol

  14. Eigenstate Gibbs ensemble in integrable quantum systems

    Science.gov (United States)

    Nandy, Sourav; Sen, Arnab; Das, Arnab; Dhar, Abhishek

    2016-12-01

    The eigenstate thermalization hypothesis conjectures that for a thermodynamically large system in one of its energy eigenstates, the reduced density matrix describing any finite subsystem is determined solely by a set of relevant conserved quantities. In a chaotic quantum system, only the energy is expected to play that role and hence eigenstates appear locally thermal. Integrable systems, on the other hand, possess an extensive number of such conserved quantities and therefore the reduced density matrix requires specification of all the corresponding parameters (generalized Gibbs ensemble). However, here we show by unbiased statistical sampling of the individual eigenstates with a given finite energy density that the local description of an overwhelming majority of these states of even such an integrable system is actually Gibbs-like, i.e., requires only the energy density of the eigenstate. Rare eigenstates that cannot be represented by the Gibbs ensemble can also be sampled efficiently by our method and their local properties are then shown to be described by appropriately truncated generalized Gibbs ensembles. We further show that the presence of these rare eigenstates differentiates the model from the chaotic case and leads to the system being described by a generalized Gibbs ensemble at long time under a unitary dynamics following a sudden quench, even when the initial state is a typical (Gibbs-like) eigenstate of the prequench Hamiltonian.

  15. A Hierarchical Bayes Ensemble Kalman Filter

    Science.gov (United States)

    Tsyrulnikov, Michael; Rakitko, Alexander

    2017-01-01

    A new ensemble filter that allows for the uncertainty in the prior distribution is proposed and tested. The filter relies on the conditional Gaussian distribution of the state given the model-error and predictability-error covariance matrices. The latter are treated as random matrices and updated in a hierarchical Bayes scheme along with the state. The (hyper)prior distribution of the covariance matrices is assumed to be inverse Wishart. The new Hierarchical Bayes Ensemble Filter (HBEF) assimilates ensemble members as generalized observations and allows ordinary observations to influence the covariances. The actual probability distribution of the ensemble members is allowed to be different from the true one. An approximation that leads to a practicable analysis algorithm is proposed. The new filter is studied in numerical experiments with a doubly stochastic one-variable model of "truth". The model permits the assessment of the variance of the truth and the true filtering error variance at each time instance. The HBEF is shown to outperform the EnKF and the HEnKF by Myrseth and Omre (2010) in a wide range of filtering regimes in terms of performance of its primary and secondary filters.

  16. A J-modulated protonless NMR experiment characterizes the conformational ensemble of the intrinsically disordered protein WIP.

    Science.gov (United States)

    Rozentur-Shkop, Eva; Goobes, Gil; Chill, Jordan H

    2016-12-01

    Intrinsically disordered proteins (IDPs) are multi-conformational polypeptides that lack a single stable three-dimensional structure. It has become increasingly clear that the versatile IDPs play key roles in a multitude of biological processes, and, given their flexible nature, NMR is a leading method to investigate IDP behavior on the molecular level. Here we present an IDP-tailored J-modulated experiment designed to monitor changes in the conformational ensemble characteristic of IDPs by accurately measuring backbone one- and two-bond J((15)N,(13)Cα) couplings. This concept was realized using a unidirectional (H)NCO (13)C-detected experiment suitable for poor spectral dispersion and optimized for maximum coverage of amino acid types. To demonstrate the utility of this approach we applied it to the disordered actin-binding N-terminal domain of WASp interacting protein (WIP), a ubiquitous key modulator of cytoskeletal changes in a range of biological systems. One- and two-bond J((15)N,(13)Cα) couplings were acquired for WIP residues 2-65 at various temperatures, and in denaturing and crowding environments. Under native conditions fitted J-couplings identified in the WIP conformational ensemble a propensity for extended conformation at residues 16-23 and 45-60, and a helical tendency at residues 28-42. These findings are consistent with a previous study of the based upon chemical shift and RDC data and confirm that the WIP(2-65) conformational ensemble is biased towards the structure assumed by this fragment in its actin-bound form. The effects of environmental changes upon this ensemble were readily apparent in the J-coupling data, which reflected a significant decrease in structural propensity at higher temperatures, in the presence of 8 M urea, and under the influence of a bacterial cell lysate. The latter suggests that crowding can cause protein unfolding through protein-protein interactions that stabilize the unfolded state. We conclude that J-couplings are

  17. Cavity Cooling for Ensemble Spin Systems

    Science.gov (United States)

    Cory, David

    2015-03-01

    Recently there has been a surge of interest in exploring thermodynamics in quantum systems where dissipative effects can be exploited to perform useful work. One such example is quantum state engineering where a quantum state of high purity may be prepared by dissipative coupling through a cold thermal bath. This has been used to great effect in many quantum systems where cavity cooling has been used to cool mechanical modes to their quantum ground state through coupling to the resolved sidebands of a high-Q resonator. In this talk we explore how these techniques may be applied to an ensemble spin system. This is an attractive process as it potentially allows for parallel remove of entropy from a large number of quantum systems, enabling an ensemble to achieve a polarization greater than thermal equilibrium, and potentially on a time scale much shorter than thermal relaxation processes. This is achieved by the coupled angular momentum subspaces of the ensemble behaving as larger effective spins, overcoming the weak individual coupling of individual spins to a microwave resonator. Cavity cooling is shown to cool each of these subspaces to their respective ground state, however an additional algorithmic step or dissipative process is required to couple between these subspaces and enable cooling to the full ground state of the joint system.

  18. Imprinting and recalling cortical ensembles.

    Science.gov (United States)

    Carrillo-Reid, Luis; Yang, Weijian; Bando, Yuki; Peterka, Darcy S; Yuste, Rafael

    2016-08-12

    Neuronal ensembles are coactive groups of neurons that may represent building blocks of cortical circuits. These ensembles could be formed by Hebbian plasticity, whereby synapses between coactive neurons are strengthened. Here we report that repetitive activation with two-photon optogenetics of neuronal populations from ensembles in the visual cortex of awake mice builds neuronal ensembles that recur spontaneously after being imprinted and do not disrupt preexisting ones. Moreover, imprinted ensembles can be recalled by single- cell stimulation and remain coactive on consecutive days. Our results demonstrate the persistent reconfiguration of cortical circuits by two-photon optogenetics into neuronal ensembles that can perform pattern completion. Copyright © 2016, American Association for the Advancement of Science.

  19. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Hakon

    2016-06-14

    This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.

  20. Thermal denaturation of type I collagen vitrified gels

    Energy Technology Data Exchange (ETDEWEB)

    Xia, Zhiyong, E-mail: zhiyong.xia@jhuapl.edu [The Johns Hopkins University, Applied Physics Laboratory, Laurel, MD 20723 (United States); Calderon-Colon, Xiomara [The Johns Hopkins University, Applied Physics Laboratory, Laurel, MD 20723 (United States); Trexler, Morgana, E-mail: morgana.trexler@jhuapl.edu [The Johns Hopkins University, Applied Physics Laboratory, Laurel, MD 20723 (United States); Elisseeff, Jennifer; Guo, Qiongyu [The Johns Hopkins University, Department of Biomedical Engineering, Baltimore, MD 21231 (United States)

    2012-01-10

    Highlights: Black-Right-Pointing-Pointer We analyzed the denaturation of vitrigels synthesized under different conditions. Black-Right-Pointing-Pointer Overall denaturation kinetics consisted of both reversible and irreversible steps. Black-Right-Pointing-Pointer More stable vitrigels were formed under high level of vitrification. - Abstract: The denaturation kinetics of type I collagen vitrigels synthesized under different vitrification time and temperature were analyzed by the classical Kissinger approach and the advanced model free kinetics (AMFK) using the Vyazovkin algorithm. The AMFK successfully elucidated the overall denaturation into reversible and irreversible processes. Depending on vitrification conditions, the activation energy for the irreversible process ranged from 100 to 200 kJ/mol, and the reversible enthalpy ranged from 250 to 300 kJ/mol. All of these values increased with the vitrification time and temperature, indicating that a more stable and complex structure formed with increased vitrification. The classical Kissinger method predicted the presence of a critical temperate of approximately 60 Degree-Sign C for the transition between reversible and irreversible processes. Scanning electron microscopy revealed the presence of fibril structures in vitrigels both before and after full denaturation; however the fibrils had became thicker and rougher after denaturation.

  1. Quantum Ensemble Classification: A Sampling-Based Learning Control Approach.

    Science.gov (United States)

    Chen, Chunlin; Dong, Daoyi; Qi, Bo; Petersen, Ian R; Rabitz, Herschel

    2017-06-01

    Quantum ensemble classification (QEC) has significant applications in discrimination of atoms (or molecules), separation of isotopes, and quantum information extraction. However, quantum mechanics forbids deterministic discrimination among nonorthogonal states. The classification of inhomogeneous quantum ensembles is very challenging, since there exist variations in the parameters characterizing the members within different classes. In this paper, we recast QEC as a supervised quantum learning problem. A systematic classification methodology is presented by using a sampling-based learning control (SLC) approach for quantum discrimination. The classification task is accomplished via simultaneously steering members belonging to different classes to their corresponding target states (e.g., mutually orthogonal states). First, a new discrimination method is proposed for two similar quantum systems. Then, an SLC method is presented for QEC. Numerical results demonstrate the effectiveness of the proposed approach for the binary classification of two-level quantum ensembles and the multiclass classification of multilevel quantum ensembles.

  2. Critical behavior in topological ensembles

    CERN Document Server

    Bulycheva, K; Nechaev, S

    2014-01-01

    We consider the relation between three physical problems: 2D directed lattice random walks in an external magnetic field, ensembles of torus knots, and 5d Abelian SUSY gauge theory with massless hypermultiplet in $\\Omega$ background. All these systems exhibit the critical behavior typical for the "area+length" statistics of grand ensembles of 2D directed paths. In particular, using the combinatorial description, we have found the new critical behavior in the ensembles of the torus knots and in the instanton ensemble in 5d gauge theory. The relation with the integrable model is discussed.

  3. Decadal climate predictions improved by ocean ensemble dispersion filtering

    Science.gov (United States)

    Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.

    2017-06-01

    Decadal predictions by Earth system models aim to capture the state and phase of the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-term weather forecasts represent an initial value problem and long-term climate projections represent a boundary condition problem, the decadal climate prediction falls in-between these two time scales. In recent years, more precise initialization techniques of coupled Earth system models and increased ensemble sizes have improved decadal predictions. However, climate models in general start losing the initialized signal and its predictive skill from one forecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improved by a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. We found that this procedure, called ensemble dispersion filter, results in more accurate results than the standard decadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions show an increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with larger ensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from ocean ensemble dispersion filtering toward the ensemble mean.type="synopsis">type="main">Plain Language SummaryDecadal predictions aim to predict the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. The ocean memory due to its heat capacity holds big potential skill. In recent years, more precise initialization techniques of coupled Earth system models (incl. atmosphere and ocean) have improved decadal predictions. Ensembles are another important aspect. Applying slightly perturbed predictions to trigger the famous butterfly effect results in an ensemble. Instead of evaluating one prediction, but the

  4. Deconvoluting Protein (Unfolding Structural Ensembles Using X-Ray Scattering, Nuclear Magnetic Resonance Spectroscopy and Molecular Dynamics Simulation.

    Directory of Open Access Journals (Sweden)

    Alexandr Nasedkin

    Full Text Available The folding and unfolding of protein domains is an apparently cooperative process, but transient intermediates have been detected in some cases. Such (unfolding intermediates are challenging to investigate structurally as they are typically not long-lived and their role in the (unfolding reaction has often been questioned. One of the most well studied (unfolding pathways is that of Drosophila melanogaster Engrailed homeodomain (EnHD: this 61-residue protein forms a three helix bundle in the native state and folds via a helical intermediate. Here we used molecular dynamics simulations to derive sample conformations of EnHD in the native, intermediate, and unfolded states and selected the relevant structural clusters by comparing to small/wide angle X-ray scattering data at four different temperatures. The results are corroborated using residual dipolar couplings determined by NMR spectroscopy. Our results agree well with the previously proposed (unfolding pathway. However, they also suggest that the fully unfolded state is present at a low fraction throughout the investigated temperature interval, and that the (unfolding intermediate is highly populated at the thermal midpoint in line with the view that this intermediate can be regarded to be the denatured state under physiological conditions. Further, the combination of ensemble structural techniques with MD allows for determination of structures and populations of multiple interconverting structures in solution.

  5. Reaction of Native and Denatured Brucella abortus (S19 Proteins with Antibody Using Affinity Chromatography and Immunoblotting

    Directory of Open Access Journals (Sweden)

    R. Karimi

    2005-01-01

    Full Text Available Western blotting or immunoblotting commonly use for study of reaction between antigens and antibodies. Denaturation of many proteins in immunoblotting can affect greatly the reactivity of antibodies and outcome of the procedure.In this study proteins of Brucella abortus (S19 was extracted by a mild method and reaction of the extracted proteins with serum of infected human and goat and immunized rabbit compared by affinity chromatography and immunoblotting. Gamma globulin (mostly IgG fraction of the sera was precipitated by half saturation of ammonium sulfate and linked to activated sepharose 4B. The extracted proteins were loaded on the affinity column. Attached proteins was eluted by low pH and analyzed by SDS-PAGE. Reaction of the total extract and eluted fractions with IgG fraction of sera was evaluated by Western blotting.Upon the results of affinity chromatography and immunoblotting, Brucella proteins can be classified in four groups: 1- The proteins that adsorbed to the affinity column and react with IgG in westernblotting. 2- Proteins that react with IgG in native state but no in denatured state. 3- Proteins that do not react with IgG in native state but react in denatured state. 4- Proteins that do not react with IgG in native and denatured state.

  6. 27 CFR 19.57 - Recovery and reuse of denatured spirits in manufacturing processes.

    Science.gov (United States)

    2010-04-01

    ... denatured spirits in manufacturing processes. 19.57 Section 19.57 Alcohol, Tobacco Products and Firearms... denatured spirits in manufacturing processes. The following persons are not, by reason of the activities...) Manufacturers who use denatured spirits, or articles or substances containing denatured spirits, in a process...

  7. Ensemble Bayesian forecasting system Part I: Theory and algorithms

    Science.gov (United States)

    Herr, Henry D.; Krzysztofowicz, Roman

    2015-05-01

    The ensemble Bayesian forecasting system (EBFS), whose theory was published in 2001, is developed for the purpose of quantifying the total uncertainty about a discrete-time, continuous-state, non-stationary stochastic process such as a time series of stages, discharges, or volumes at a river gauge. The EBFS is built of three components: an input ensemble forecaster (IEF), which simulates the uncertainty associated with random inputs; a deterministic hydrologic model (of any complexity), which simulates physical processes within a river basin; and a hydrologic uncertainty processor (HUP), which simulates the hydrologic uncertainty (an aggregate of all uncertainties except input). It works as a Monte Carlo simulator: an ensemble of time series of inputs (e.g., precipitation amounts) generated by the IEF is transformed deterministically through a hydrologic model into an ensemble of time series of outputs, which is next transformed stochastically by the HUP into an ensemble of time series of predictands (e.g., river stages). Previous research indicated that in order to attain an acceptable sampling error, the ensemble size must be on the order of hundreds (for probabilistic river stage forecasts and probabilistic flood forecasts) or even thousands (for probabilistic stage transition forecasts). The computing time needed to run the hydrologic model this many times renders the straightforward simulations operationally infeasible. This motivates the development of the ensemble Bayesian forecasting system with randomization (EBFSR), which takes full advantage of the analytic meta-Gaussian HUP and generates multiple ensemble members after each run of the hydrologic model; this auxiliary randomization reduces the required size of the meteorological input ensemble and makes it operationally feasible to generate a Bayesian ensemble forecast of large size. Such a forecast quantifies the total uncertainty, is well calibrated against the prior (climatic) distribution of

  8. Analysis and optimization of weighted ensemble sampling

    CERN Document Server

    Aristoff, David

    2016-01-01

    We give a mathematical framework for weighted ensemble (WE) sampling, a binning and resampling technique for efficiently computing probabilities in molecular dynamics. We prove that WE sampling is unbiased in a very general setting that includes adaptive binning. We show that when WE is used for stationary calculations in tandem with a Markov state model (MSM), the MSM can be used to optimize the allocation of replicas in the bins.

  9. A past discharge assimilation system for ensemble streamflow forecasts over France – Part 2: Impact on the ensemble streamflow forecasts

    Directory of Open Access Journals (Sweden)

    G. Thirel

    2010-08-01

    Full Text Available The use of ensemble streamflow forecasts is developing in the international flood forecasting services. Ensemble streamflow forecast systems can provide more accurate forecasts and useful information about the uncertainty of the forecasts, thus improving the assessment of risks. Nevertheless, these systems, like all hydrological forecasts, suffer from errors on initialization or on meteorological data, which lead to hydrological prediction errors. This article, which is the second part of a 2-part article, concerns the impacts of initial states, improved by a streamflow assimilation system, on an ensemble streamflow prediction system over France. An assimilation system was implemented to improve the streamflow analysis of the SAFRAN-ISBA-MODCOU (SIM hydro-meteorological suite, which initializes the ensemble streamflow forecasts at Météo-France. This assimilation system, using the Best Linear Unbiased Estimator (BLUE and modifying the initial soil moisture states, showed an improvement of the streamflow analysis with low soil moisture increments. The final states of this suite were used to initialize the ensemble streamflow forecasts of Météo-France, which are based on the SIM model and use the European Centre for Medium-range Weather Forecasts (ECMWF 10-day Ensemble Prediction System (EPS. Two different configurations of the assimilation system were used in this study: the first with the classical SIM model and the second using improved soil physics in ISBA. The effects of the assimilation system on the ensemble streamflow forecasts were assessed for these two configurations, and a comparison was made with the original (i.e. without data assimilation and without the improved physics ensemble streamflow forecasts. It is shown that the assimilation system improved most of the statistical scores usually computed for the validation of ensemble predictions (RMSE, Brier Skill Score and its decomposition, Ranked Probability Skill Score, False Alarm

  10. ESPC Coupled Global Ensemble Design

    Science.gov (United States)

    2014-09-30

    coupled system infrastructure and forecasting capabilities. Initial operational capability is targeted for 2018. APPROACH 1. It is recognized...provided will be the probability distribution function (PDF) of environmental conditions. It is expected that this distribution will have skill. To...system would be the initial capability for ensemble forecasts . Extensions to fully coupled ensembles would be the next step. 2. Develop an extended

  11. Dodine as a transparent protein denaturant for circular dichroism and infrared studies.

    Science.gov (United States)

    Guin, Drishti; Sye, Kori; Dave, Kapil; Gruebele, Martin

    2016-05-01

    The fungicide dodine combines the cooperative denaturation properties of guanidine with the mM denaturation activity of SDS. It was previously tested only on two small model proteins. Here we show that it can be used as a chemical denaturant for phosphoglycerate kinase (PGK), a much larger two-domain enzyme. In addition to its properties as a chemical denaturant, dodine facilitates thermal denaturation of PGK, and we show for the first time that it also facilitates pressure denaturation of a protein. Much higher quality circular dichroism and amide I' infrared spectra of PGK can be obtained in dodine than in guanidine, opening the possibility for use of dodine as a denaturant when UV or IR detection is desirable. One caution is that dodine denaturation, like other detergent-based denaturants, is less reversible than guanidine denaturation. © 2016 The Protein Society.

  12. Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) II: Ensemble combinations and predictions

    Science.gov (United States)

    Viney, N.R.; Bormann, H.; Breuer, L.; Bronstert, A.; Croke, B.F.W.; Frede, H.; Graff, T.; Hubrechts, L.; Huisman, J.A.; Jakeman, A.J.; Kite, G.W.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Willems, P.

    2009-01-01

    This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9-year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles, in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in

  13. Quantum canonical ensemble: A projection operator approach

    Science.gov (United States)

    Magnus, Wim; Lemmens, Lucien; Brosens, Fons

    2017-09-01

    Knowing the exact number of particles N, and taking this knowledge into account, the quantum canonical ensemble imposes a constraint on the occupation number operators. The constraint particularly hampers the systematic calculation of the partition function and any relevant thermodynamic expectation value for arbitrary but fixed N. On the other hand, fixing only the average number of particles, one may remove the above constraint and simply factorize the traces in Fock space into traces over single-particle states. As is well known, that would be the strategy of the grand-canonical ensemble which, however, comes with an additional Lagrange multiplier to impose the average number of particles. The appearance of this multiplier can be avoided by invoking a projection operator that enables a constraint-free computation of the partition function and its derived quantities in the canonical ensemble, at the price of an angular or contour integration. Introduced in the recent past to handle various issues related to particle-number projected statistics, the projection operator approach proves beneficial to a wide variety of problems in condensed matter physics for which the canonical ensemble offers a natural and appropriate environment. In this light, we present a systematic treatment of the canonical ensemble that embeds the projection operator into the formalism of second quantization while explicitly fixing N, the very number of particles rather than the average. Being applicable to both bosonic and fermionic systems in arbitrary dimensions, transparent integral representations are provided for the partition function ZN and the Helmholtz free energy FN as well as for two- and four-point correlation functions. The chemical potential is not a Lagrange multiplier regulating the average particle number but can be extracted from FN+1 -FN, as illustrated for a two-dimensional fermion gas.

  14. Relation between native ensembles and experimental structures of proteins

    DEFF Research Database (Denmark)

    Best, R. B.; Lindorff-Larsen, Kresten; DePristo, M. A.

    2006-01-01

    Data Bank ensembles; moreover, we show that the effects of uncertainties in structure determination are insufficient to explain the results. These results highlight the importance of accounting for native-state protein dynamics in making comparisons with ensemble-averaged experimental data and suggest......Different experimental structures of the same protein or of proteins with high sequence similarity contain many small variations. Here we construct ensembles of "high-sequence similarity Protein Data Bank" (HSP) structures and consider the extent to which such ensembles represent the structural...... heterogeneity of the native state in solution. We find that different NMR measurements probing structure and dynamics of given proteins in solution, including order parameters, scalar couplings, and residual dipolar couplings, are remarkably well reproduced by their respective high-sequence similarity Protein...

  15. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

    Roh, S.

    2015-05-08

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

  16. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

    Roh, S.

    2015-12-03

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

  17. Multivariate localization methods for ensemble Kalman filtering

    Directory of Open Access Journals (Sweden)

    S. Roh

    2015-05-01

    Full Text Available In ensemble Kalman filtering (EnKF, the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

  18. Multivariate localization methods for ensemble Kalman filtering

    Science.gov (United States)

    Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.

    2015-12-01

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

  19. Botnet analysis using ensemble classifier

    Directory of Open Access Journals (Sweden)

    Anchit Bijalwan

    2016-09-01

    Full Text Available This paper analyses the botnet traffic using Ensemble of classifier algorithm to find out bot evidence. We used ISCX dataset for training and testing purpose. We extracted the features of both training and testing datasets. After extracting the features of this dataset, we bifurcated these features into two classes, normal traffic and botnet traffic and provide labelling. Thereafter using modern data mining tool, we have applied ensemble of classifier algorithm. Our experimental results show that the performance for finding bot evidence using ensemble of classifiers is better than single classifier. Ensemble based classifiers perform better than single classifier by either combining powers of multiple algorithms or introducing diversification to the same classifier by varying input in bot analysis. Our results are showing that by using voting method of ensemble based classifier accuracy is increased up to 96.41% from 93.37%.

  20. Pressure-assisted cold denaturation of hen egg white lysozyme: the influence of co-solvents probed by hydrogen exchange nuclear magnetic resonance

    Directory of Open Access Journals (Sweden)

    Vogtt K.

    2005-01-01

    Full Text Available COSY proton nuclear magnetic resonance was used to measure the exchange rates of amide protons of hen egg white lysozyme (HEWL in the pressure-assisted cold-denatured state and in the heat-denatured state. After dissolving lysozyme in deuterium oxide buffer, labile protons exchange for deuterons in such a way that exposed protons are substituted rapidly, whereas "protected" protons within structured parts of the protein are substituted slowly. The exchange rates k obs were determined for HEWL under heat treatment (80ºC and under high pressure conditions at low temperature (3.75 kbar, -13ºC. Moreover, the influence of co-solvents (sorbitol, urea on the exchange rate was examined under pressure-assisted cold denaturation conditions, and the corresponding protection factors, P, were determined. The exchange kinetics upon heat treatment was found to be a two-step process with initial slow exchange followed by a fast one, showing residual protection in the slow-exchange state and P-factors in the random-coil-like range for the final temperature-denatured state. Addition of sorbitol (500 mM led to an increase of P-factors for the pressure-assisted cold denatured state, but not for the heat-denatured state. The presence of 2 M urea resulted in a drastic decrease of the P-factors of the pressure-assisted cold denatured state. For both types of co-solvents, the effect they exert appears to be cooperative, i.e., no particular regions within the protein can be identified with significantly diverse changes of P-factors.

  1. A modified iterative ensemble Kalman filter data assimilation method

    Science.gov (United States)

    Xu, Baoxiong; Bai, Yulong; Wang, Yizhao; Li, Zhe; Ma, Boyang

    2017-08-01

    High nonlinearity is a typical characteristic associated with data assimilation systems. Additionally, iterative ensemble based methods have attracted a large amount of research attention, which has been focused on dealing with nonlinearity problems. To solve the local convergence problem of the iterative ensemble Kalman filter, a modified iterative ensemble Kalman filter algorithm was put forward, which was based on a global convergence strategy from the perspective of a Gauss-Newton iteration. Through self-adaption, the step factor was adjusted to enable every iteration to approach expected values during the process of the data assimilation. A sensitivity experiment was carried out in a low dimensional Lorenz-63 chaotic system, as well as a Lorenz-96 model. The new method was tested via ensemble size, observation variance, and inflation factor changes, along with other aspects. Meanwhile, comparative research was conducted with both a traditional ensemble Kalman filter and an iterative ensemble Kalman filter. The results showed that the modified iterative ensemble Kalman filter algorithm was a data assimilation method that was able to effectively estimate a strongly nonlinear system state.

  2. Ensembles of a small number of conformations with relative populations

    Energy Technology Data Exchange (ETDEWEB)

    Vammi, Vijay, E-mail: vsvammi@iastate.edu; Song, Guang, E-mail: gsong@iastate.edu [Iowa State University, Bioinformatics and Computational Biology Program, Department of Computer Science (United States)

    2015-12-15

    In our previous work, we proposed a new way to represent protein native states, using ensembles of a small number of conformations with relative Populations, or ESP in short. Using Ubiquitin as an example, we showed that using a small number of conformations could greatly reduce the potential of overfitting and assigning relative populations to protein ensembles could significantly improve their quality. To demonstrate that ESP indeed is an excellent alternative to represent protein native states, in this work we compare the quality of two ESP ensembles of Ubiquitin with several well-known regular ensembles or average structure representations. Extensive amount of significant experimental data are employed to achieve a thorough assessment. Our results demonstrate that ESP ensembles, though much smaller in size comparing to regular ensembles, perform equally or even better sometimes in all four different types of experimental data used in the assessment, namely, the residual dipolar couplings, residual chemical shift anisotropy, hydrogen exchange rates, and solution scattering profiles. This work further underlines the significance of having relative populations in describing the native states.

  3. Concrete ensemble Kalman filters with rigorous catastrophic filter divergence.

    Science.gov (United States)

    Kelly, David; Majda, Andrew J; Tong, Xin T

    2015-08-25

    The ensemble Kalman filter and ensemble square root filters are data assimilation methods used to combine high-dimensional, nonlinear dynamical models with observed data. Ensemble methods are indispensable tools in science and engineering and have enjoyed great success in geophysical sciences, because they allow for computationally cheap low-ensemble-state approximation for extremely high-dimensional turbulent forecast models. From a theoretical perspective, the dynamical properties of these methods are poorly understood. One of the central mysteries is the numerical phenomenon known as catastrophic filter divergence, whereby ensemble-state estimates explode to machine infinity, despite the true state remaining in a bounded region. In this article we provide a breakthrough insight into the phenomenon, by introducing a simple and natural forecast model that transparently exhibits catastrophic filter divergence under all ensemble methods and a large set of initializations. For this model, catastrophic filter divergence is not an artifact of numerical instability, but rather a true dynamical property of the filter. The divergence is not only validated numerically but also proven rigorously. The model cleanly illustrates mechanisms that give rise to catastrophic divergence and confirms intuitive accounts of the phenomena given in past literature.

  4. Concrete ensemble Kalman filters with rigorous catastrophic filter divergence

    Science.gov (United States)

    Kelly, David; Majda, Andrew J.; Tong, Xin T.

    2015-01-01

    The ensemble Kalman filter and ensemble square root filters are data assimilation methods used to combine high-dimensional, nonlinear dynamical models with observed data. Ensemble methods are indispensable tools in science and engineering and have enjoyed great success in geophysical sciences, because they allow for computationally cheap low-ensemble-state approximation for extremely high-dimensional turbulent forecast models. From a theoretical perspective, the dynamical properties of these methods are poorly understood. One of the central mysteries is the numerical phenomenon known as catastrophic filter divergence, whereby ensemble-state estimates explode to machine infinity, despite the true state remaining in a bounded region. In this article we provide a breakthrough insight into the phenomenon, by introducing a simple and natural forecast model that transparently exhibits catastrophic filter divergence under all ensemble methods and a large set of initializations. For this model, catastrophic filter divergence is not an artifact of numerical instability, but rather a true dynamical property of the filter. The divergence is not only validated numerically but also proven rigorously. The model cleanly illustrates mechanisms that give rise to catastrophic divergence and confirms intuitive accounts of the phenomena given in past literature. PMID:26261335

  5. Virus inactivation by protein denaturants used in affinity chromatography.

    Science.gov (United States)

    Roberts, Peter L; Lloyd, David

    2007-10-01

    Virus inactivation by a number of protein denaturants commonly used in gel affinity chromatography for protein elution and gel recycling has been investigated. The enveloped viruses Sindbis, herpes simplex-1 and vaccinia, and the non-enveloped virus polio-1 were effectively inactivated by 0.5 M sodium hydroxide, 6 M guanidinium thiocyanate, 8 M urea and 70% ethanol. However, pH 2.6, 3 M sodium thiocyanate, 6 M guanidinium chloride and 20% ethanol, while effectively inactivating the enveloped viruses, did not inactivate polio-1. These studies demonstrate that protein denaturants are generally effective for virus inactivation but with the limitation that only some may inactivate non-enveloped viruses. The use of protein denaturants, together with virus reduction steps in the manufacturing process should ensure that viral cross contamination between manufacturing batches of therapeutic biological products is prevented and the safety of the product ensured.

  6. Unusual cold denaturation of a small protein domain.

    Science.gov (United States)

    Buchner, Ginka S; Shih, Natalie; Reece, Amy E; Niebling, Stephan; Kubelka, Jan

    2012-08-21

    A thermal unfolding study of the 45-residue α-helical domain UBA(2) using circular dichroism is presented. The protein is highly thermostable and exhibits a clear cold unfolding transition with the onset near 290 K without denaturant. Cold denaturation in proteins is rarely observed in general and is quite unique among small helical protein domains. The cold unfolding was further investigated in urea solutions, and a simple thermodynamic model was used to fit all thermal and urea unfolding data. The resulting thermodynamic parameters are compared to those of other small protein domains. Possible origins of the unusual cold unfolding of UBA(2) are discussed.

  7. OBSERVATION OF DNA PARTIAL DENATURATION BY ATOMIC FORCE MICROSCOPY

    Institute of Scientific and Technical Information of China (English)

    Xin-hua Dai; Zhi-gang Wang; Bo Xiao; Yong-jun Zhang; Chen Wang; Chun-li Bai; Xiao-li Zhang; Jian Xu

    2004-01-01

    Atomic force microscopy was used to investigate the DNA-cetyltrimethylammonium bromide (CTAB) complexes adsorbed on highly ordered pyrolytic graphite (HOPG). These complexes, at low concentrations, can automatically spread out on the surface of HOPG. The DNA-CTAB complexes display a typically extended structure rather than a globular structure. Partially denaturated DNA produced by binding CTAB to DNA is directly observed by AFM with high resolution.The three-dimensional resolution of partially denaturated DNA obtained by AFM is not available by any other technique at present.

  8. Single-molecule denaturation mapping of DNA in nanofluidic channels

    DEFF Research Database (Denmark)

    Reisner, Walter; Larsen, Niels Bent; Silahtaroglu, Asli

    2010-01-01

    Here we explore the potential power of denaturation mapping as a single-molecule technique. By partially denaturing YOYO (R)-1-labeled DNA in nanofluidic channels with a combination of formamide and local heating, we obtain a sequence-dependent "barcode" corresponding to a series of local dips....... Consequently, the technique is sensitive to sequence variation without requiring enzymatic labeling or a restriction step. This technique may serve as the basis for a new mapping technology ideally suited for investigating the long-range structure of entire genomes extracted from single cells....

  9. Quantum data compression of a qubit ensemble.

    Science.gov (United States)

    Rozema, Lee A; Mahler, Dylan H; Hayat, Alex; Turner, Peter S; Steinberg, Aephraim M

    2014-10-17

    Data compression is a ubiquitous aspect of modern information technology, and the advent of quantum information raises the question of what types of compression are feasible for quantum data, where it is especially relevant given the extreme difficulty involved in creating reliable quantum memories. We present a protocol in which an ensemble of quantum bits (qubits) can in principle be perfectly compressed into exponentially fewer qubits. We then experimentally implement our algorithm, compressing three photonic qubits into two. This protocol sheds light on the subtle differences between quantum and classical information. Furthermore, since data compression stores all of the available information about the quantum state in fewer physical qubits, it could allow for a vast reduction in the amount of quantum memory required to store a quantum ensemble, making even today's limited quantum memories far more powerful than previously recognized.

  10. Face Recognition using Optimal Representation Ensemble

    CERN Document Server

    Li, Hanxi; Gao, Yongsheng

    2011-01-01

    Recently, the face recognizers based on linear representations have been shown to deliver state-of-the-art performance. In real-world applications, however, face images usually suffer from expressions, disguises and random occlusions. The problematic facial parts undermine the validity of the linear-subspace assumption and thus the recognition performance deteriorates significantly. In this work, we address the problem in a learning-inference-mixed fashion. By observing that the linear-subspace assumption is more reliable on certain face patches rather than on the holistic face, some Bayesian Patch Representations (BPRs) are randomly generated and interpreted according to the Bayes' theory. We then train an ensemble model over the patch-representations by minimizing the empirical risk w.r.t the "leave-one-out margins". The obtained model is termed Optimal Representation Ensemble (ORE), since it guarantees the optimality from the perspective of Empirical Risk Minimization. To handle the unknown patterns in tes...

  11. Eigenstate Gibbs Ensemble in Integrable Quantum Systems

    CERN Document Server

    Nandy, Sourav; Das, Arnab; Dhar, Abhishek

    2016-01-01

    The Eigenstate Thermalization Hypothesis implies that for a thermodynamically large system in one of its eigenstates, the reduced density matrix describing any finite subsystem is determined solely by a set of {\\it relevant} conserved quantities. In a generic system, only the energy plays that role and hence eigenstates appear locally thermal. Integrable systems, on the other hand, possess an extensive number of such conserved quantities and hence the reduced density matrix requires specification of an infinite number of parameters (Generalized Gibbs Ensemble). However, here we show by unbiased statistical sampling of the individual eigenstates with a given finite energy density, that the local description of an overwhelming majority of these states of even such an integrable system is actually Gibbs-like, i.e. requires only the energy density of the eigenstate. Rare eigenstates that cannot be represented by the Gibbs ensemble can also be sampled efficiently by our method and their local properties are then s...

  12. Conformational properties of the unfolded state of Im7 in nondenaturing conditions.

    Science.gov (United States)

    Pashley, Clare L; Morgan, Gareth J; Kalverda, Arnout P; Thompson, Gary S; Kleanthous, Colin; Radford, Sheena E

    2012-02-17

    The unfolded ensemble in aqueous solution represents the starting point of protein folding. Characterisation of this species is often difficult since the native state is usually predominantly populated at equilibrium. Previous work has shown that the four-helix protein, Im7 (immunity protein 7), folds via an on-pathway intermediate. While the transition states and folding intermediate have been characterised in atomistic detail, knowledge of the unfolded ensemble under the same ambient conditions remained sparse. Here, we introduce destabilising amino acid substitutions into the sequence of Im7, such that the unfolded state becomes predominantly populated at equilibrium in the absence of denaturant. Using far- and near-UV CD, fluorescence, urea titration and heteronuclear NMR experiments, we show that three amino acid substitutions (L18A-L19A-L37A) are sufficient to prevent Im7 folding, such that the unfolded state is predominantly populated at equilibrium. Using measurement of chemical shifts, (15)N transverse relaxation rates and sedimentation coefficients, we show that the unfolded species of L18A-L19A-L37A deviates significantly from random-coil behaviour. Specifically, we demonstrate that this unfolded species is compact (R(h)=25 Å) relative to the urea-denatured state (R(h)≥30 Å) and contains local clusters of hydrophobic residues in regions that correspond to the four helices in the native state. Despite these interactions, there is no evidence for long-range stabilising tertiary interactions or persistent helical structure. The results reveal an unfolded ensemble that is conformationally restricted in regions of the polypeptide chain that ultimately form helices I, II and IV in the native state.

  13. Lyophilization-induced protein denaturation in phosphate buffer systems: monomeric and tetrameric beta-galactosidase.

    Science.gov (United States)

    Pikal-Cleland, K A; Carpenter, J F

    2001-09-01

    During freezing in phosphate buffers, selective precipitation of a less soluble buffer component and subsequent pH shifts may induce protein denaturation. Previous reports indicate significantly more inactivation and secondary structural perturbation of monomeric and tetrameric beta-galactosidase (beta-gal) during freeze-thawing in sodium phosphate (NaP) buffer as compared with potassium phosphate (KP) buffer. This observation was attributed to the significant pH shifts (from 7.0 to as low as 3.8) observed during freezing in the NaP buffer (1). In the current study, we investigated the impact of the additional stress of dehydration after freezing on the recovery of active protein on reconstitution and the retention of the native structure in the dried state. Freeze-drying monomeric and tetrameric beta-gal in either NaP or KP buffer resulted in significant secondary structural perturbations, which were greatest for the NaP samples. However, similar recoveries of active monomeric protein were observed after freeze-thawing and freeze-drying, indicating that most dehydration-induced unfolding was reversible on reconstitution of the freeze-dried protein. In contrast, the tetrameric protein was more susceptible to dehydration-induced denaturation as seen by the greater loss in activity after reconstitution of the freeze-dried samples relative to that measured after freeze-thawing. To ensure optimal protein stability during freeze-drying, the protein must be protected from both freezing and dehydration stresses. Although poly(ethylene glycol) and dextran are preferentially excluded solutes and should confer protection during freezing, they were unable to prevent lyophilization-induced denaturation. In addition, Tween did not foster maintenance of native protein during freeze-drying. However, sucrose, which hydrogen bonds to dried protein in the place of lost water, greatly reduced freezing- and drying-induced denaturation, as observed by the high retention of native

  14. Ensemble manifold regularization.

    Science.gov (United States)

    Geng, Bo; Tao, Dacheng; Xu, Chao; Yang, Linjun; Hua, Xian-Sheng

    2012-06-01

    We propose an automatic approximation of the intrinsic manifold for general semi-supervised learning (SSL) problems. Unfortunately, it is not trivial to define an optimization function to obtain optimal hyperparameters. Usually, cross validation is applied, but it does not necessarily scale up. Other problems derive from the suboptimality incurred by discrete grid search and the overfitting. Therefore, we develop an ensemble manifold regularization (EMR) framework to approximate the intrinsic manifold by combining several initial guesses. Algorithmically, we designed EMR carefully so it 1) learns both the composite manifold and the semi-supervised learner jointly, 2) is fully automatic for learning the intrinsic manifold hyperparameters implicitly, 3) is conditionally optimal for intrinsic manifold approximation under a mild and reasonable assumption, and 4) is scalable for a large number of candidate manifold hyperparameters, from both time and space perspectives. Furthermore, we prove the convergence property of EMR to the deterministic matrix at rate root-n. Extensive experiments over both synthetic and real data sets demonstrate the effectiveness of the proposed framework.

  15. A past discharge assimilation system for ensemble streamflow forecasts over France – Part 2: Impact on the ensemble streamflow forecasts

    Directory of Open Access Journals (Sweden)

    G. Thirel

    2010-04-01

    Full Text Available The use of ensemble streamflow forecasts is developing in the international flood forecasting services. Such systems can provide more accurate forecasts and useful information about the uncertainty of the forecasts, thus improving the assessment of risks. Nevertheless, these systems, like all hydrological forecasts, suffer from errors on initialization or on meteorological data, which lead to hydrological prediction errors. This article, which is the second part of a 2-part article, concerns the impacts of initial states, improved by a streamflow assimilation system, on an ensemble streamflow prediction system over France. An assimilation system was implemented to improve the streamflow analysis of the SAFRAN-ISBA-MODCOU (SIM hydro-meteorological suite, which initializes the ensemble streamflow forecasts at Météo-France. This assimilation system, using the Best Linear Unbiased Estimator (BLUE and modifying the initial soil moisture states, showed an improvement of the streamflow analysis with low soil moisture increments. The final states of this suite were used to initialize the ensemble streamflow forecasts of Météo-France, which are based on the SIM model and use the European Centre for Medium-range Weather Forecasts (ECMWF 10-day Ensemble Prediction System (EPS. Two different configurations of the assimilation system were used in this study: the first with the classical SIM model and the second using improved soil physics in ISBA. The effects of the assimilation system on the ensemble streamflow forecasts were assessed for these two configurations, and a comparison was made with the original (i.e. without data assimilation and without the improved physics ensemble streamflow forecasts. It is shown that the assimilation system improved most of the statistical scores usually computed for the validation of ensemble predictions (RMSE, Brier Skill Score and its decomposition, Ranked Probability Skill Score, False Alarm Rate, etc., especially

  16. Phase-selective entrainment of nonlinear oscillator ensembles

    Science.gov (United States)

    Zlotnik, Anatoly; Nagao, Raphael; Kiss, István Z.; Li-Shin, Jr.

    2016-03-01

    The ability to organize and finely manipulate the hierarchy and timing of dynamic processes is important for understanding and influencing brain functions, sleep and metabolic cycles, and many other natural phenomena. However, establishing spatiotemporal structures in biological oscillator ensembles is a challenging task that requires controlling large collections of complex nonlinear dynamical units. In this report, we present a method to design entrainment signals that create stable phase patterns in ensembles of heterogeneous nonlinear oscillators without using state feedback information. We demonstrate the approach using experiments with electrochemical reactions on multielectrode arrays, in which we selectively assign ensemble subgroups into spatiotemporal patterns with multiple phase clusters. The experimentally confirmed mechanism elucidates the connection between the phases and natural frequencies of a collection of dynamical elements, the spatial and temporal information that is encoded within this ensemble, and how external signals can be used to retrieve this information.

  17. Knowledge based cluster ensemble for cancer discovery from biomolecular data.

    Science.gov (United States)

    Yu, Zhiwen; Wongb, Hau-San; You, Jane; Yang, Qinmin; Liao, Hongying

    2011-06-01

    The adoption of microarray techniques in biological and medical research provides a new way for cancer diagnosis and treatment. In order to perform successful diagnosis and treatment of cancer, discovering and classifying cancer types correctly is essential. Class discovery is one of the most important tasks in cancer classification using biomolecular data. Most of the existing works adopt single clustering algorithms to perform class discovery from biomolecular data. However, single clustering algorithms have limitations, which include a lack of robustness, stability, and accuracy. In this paper, we propose a new cluster ensemble approach called knowledge based cluster ensemble (KCE) which incorporates the prior knowledge of the data sets into the cluster ensemble framework. Specifically, KCE represents the prior knowledge of a data set in the form of pairwise constraints. Then, the spectral clustering algorithm (SC) is adopted to generate a set of clustering solutions. Next, KCE transforms pairwise constraints into confidence factors for these clustering solutions. After that, a consensus matrix is constructed by considering all the clustering solutions and their corresponding confidence factors. The final clustering result is obtained by partitioning the consensus matrix. Comparison with single clustering algorithms and conventional cluster ensemble approaches, knowledge based cluster ensemble approaches are more robust, stable and accurate. The experiments on cancer data sets show that: 1) KCE works well on these data sets; 2) KCE not only outperforms most of the state-of-the-art single clustering algorithms, but also outperforms most of the state-of-the-art cluster ensemble approaches.

  18. Long-range interacting systems in the unconstrained ensemble

    Science.gov (United States)

    Latella, Ivan; Pérez-Madrid, Agustín; Campa, Alessandro; Casetti, Lapo; Ruffo, Stefano

    2017-01-01

    Completely open systems can exchange heat, work, and matter with the environment. While energy, volume, and number of particles fluctuate under completely open conditions, the equilibrium states of the system, if they exist, can be specified using the temperature, pressure, and chemical potential as control parameters. The unconstrained ensemble is the statistical ensemble describing completely open systems and the replica energy is the appropriate free energy for these control parameters from which the thermodynamics must be derived. It turns out that macroscopic systems with short-range interactions cannot attain equilibrium configurations in the unconstrained ensemble, since temperature, pressure, and chemical potential cannot be taken as a set of independent variables in this case. In contrast, we show that systems with long-range interactions can reach states of thermodynamic equilibrium in the unconstrained ensemble. To illustrate this fact, we consider a modification of the Thirring model and compare the unconstrained ensemble with the canonical and grand-canonical ones: The more the ensemble is constrained by fixing the volume or number of particles, the larger the space of parameters defining the equilibrium configurations.

  19. Long-range interacting systems in the unconstrained ensemble.

    Science.gov (United States)

    Latella, Ivan; Pérez-Madrid, Agustín; Campa, Alessandro; Casetti, Lapo; Ruffo, Stefano

    2017-01-01

    Completely open systems can exchange heat, work, and matter with the environment. While energy, volume, and number of particles fluctuate under completely open conditions, the equilibrium states of the system, if they exist, can be specified using the temperature, pressure, and chemical potential as control parameters. The unconstrained ensemble is the statistical ensemble describing completely open systems and the replica energy is the appropriate free energy for these control parameters from which the thermodynamics must be derived. It turns out that macroscopic systems with short-range interactions cannot attain equilibrium configurations in the unconstrained ensemble, since temperature, pressure, and chemical potential cannot be taken as a set of independent variables in this case. In contrast, we show that systems with long-range interactions can reach states of thermodynamic equilibrium in the unconstrained ensemble. To illustrate this fact, we consider a modification of the Thirring model and compare the unconstrained ensemble with the canonical and grand-canonical ones: The more the ensemble is constrained by fixing the volume or number of particles, the larger the space of parameters defining the equilibrium configurations.

  20. Quantum teleportation between remote atomic-ensemble quantum memories

    CERN Document Server

    Bao, Xiao-Hui; Li, Che-Ming; Yuan, Zhen-Sheng; Lu, Chao-Yang; Pan, Jian-Wei

    2012-01-01

    Quantum teleportation and quantum memory are two crucial elements for large-scale quantum networks. With the help of prior distributed entanglement as a "quantum channel", quantum teleportation provides an intriguing means to faithfully transfer quantum states among distant locations without actual transmission of the physical carriers. Quantum memory enables controlled storage and retrieval of fast-flying photonic quantum bits with stationary matter systems, which is essential to achieve the scalability required for large-scale quantum networks. Combining these two capabilities, here we realize quantum teleportation between two remote atomic-ensemble quantum memory nodes, each composed of 100 million rubidium atoms and connected by a 150-meter optical fiber. The spinwave state of one atomic ensemble is mapped to a propagating photon, and subjected to Bell-state measurements with another single photon that is entangled with the spinwave state of the other ensemble. Two-photon detection events herald the succe...

  1. Diurnal Ensemble Surface Meteorology Statistics

    Data.gov (United States)

    U.S. Environmental Protection Agency — Excel file containing diurnal ensemble statistics of 2-m temperature, 2-m mixing ratio and 10-m wind speed. This Excel file contains figures for Figure 2 in the...

  2. PSO-Ensemble Demo Application

    DEFF Research Database (Denmark)

    2004-01-01

    Within the framework of the PSO-Ensemble project (FU2101) a demo application has been created. The application use ECMWF ensemble forecasts. Two instances of the application are running; one for Nysted Offshore and one for the total production (except Horns Rev) in the Eltra area. The output...... is available via two password-protected web-pages hosted at IMM and is used daily by Elsam and E2....

  3. Similarity measures for protein ensembles

    DEFF Research Database (Denmark)

    Lindorff-Larsen, Kresten; Ferkinghoff-Borg, Jesper

    2009-01-01

    Analyses of similarities and changes in protein conformation can provide important information regarding protein function and evolution. Many scores, including the commonly used root mean square deviation, have therefore been developed to quantify the similarities of different protein conformations...... a synthetic example from molecular dynamics simulations. We then apply the algorithms to revisit the problem of ensemble averaging during structure determination of proteins, and find that an ensemble refinement method is able to recover the correct distribution of conformations better than standard single...

  4. PSO-Ensemble Demo Application

    DEFF Research Database (Denmark)

    2004-01-01

    Within the framework of the PSO-Ensemble project (FU2101) a demo application has been created. The application use ECMWF ensemble forecasts. Two instances of the application are running; one for Nysted Offshore and one for the total production (except Horns Rev) in the Eltra area. The output is a...... is available via two password-protected web-pages hosted at IMM and is used daily by Elsam and E2....

  5. Denaturation of membrane proteins and hyperthermic cell killing

    NARCIS (Netherlands)

    Burgman, Paulus Wilhelmus Johannes Jozef

    1993-01-01

    Summarizing: heat induced denaturation of membrane proteins is probably related to hyperthermic cell killing. Induced resistance of heat sensitive proteins seems to be involved in the development of thermotolerance. Although many questions remain still to be answered, it appears that HSP72, when

  6. Sequential ensemble-based optimal design for parameter estimation: SEQUENTIAL ENSEMBLE-BASED OPTIMAL DESIGN

    Energy Technology Data Exchange (ETDEWEB)

    Man, Jun [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Zhang, Jiangjiang [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Li, Weixuan [Pacific Northwest National Laboratory, Richland Washington USA; Zeng, Lingzao [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Wu, Laosheng [Department of Environmental Sciences, University of California, Riverside California USA

    2016-10-01

    The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.

  7. Dynamic Analogue Initialization for Ensemble Forecasting

    Institute of Scientific and Technical Information of China (English)

    LI Shan; RONG Xingyao; LIU Yun; LIU Zhengyu; Klaus FRAEDRICH

    2013-01-01

    This paper introduces a new approach for the initialization of ensemble numerical forecasting:Dynamic Analogue Initialization (DAI).DAI assumes that the best model state trajectories for the past provide the initial conditions for the best forecasts in the future.As such,DAI performs the ensemble forecast using the best analogues from a full size ensemble.As a pilot study,the Lorenz63 and Lorenz96 models were used to test DAI's effectiveness independently.Results showed that DAI can improve the forecast significantly.Especially in lower-dimensional systems,DAI can reduce the forecast RMSE by ~50% compared to the Monte Carlo forecast (MC).This improvement is because DAI is able to recognize the direction of the analysis error through the embedding process and therefore selects those good trajectories with reduced initial error.Meanwhile,a potential improvement of DAI is also proposed,and that is to find the optimal range of embedding time based on the error's growing speed.

  8. Urea Induced Denaturation of Pre-Q1 Riboswitch

    Science.gov (United States)

    Yoon, Jeseong; Thirumalai, Devarajan; Hyeon, Changbong

    2013-01-01

    Urea, a polar molecule with a large dipole moment, not only destabilizes the folded RNA structures, but can also enhance the folding rates of large ribozymes. Unlike the mechanism of urea-induced unfolding of proteins, which is well understood, the action of urea on RNA has barely been explored. We performed extensive all atom molecular dynamics (MD) simulations to determine the molecular underpinnings of urea-induced RNA denaturation. Urea displays its denaturing power in both secondary and tertiary motifs of the riboswitch (RS) structure. Our simulations reveal that the denaturation of RNA structures is mainly driven by the hydrogen bonds and stacking interactions of urea with the bases. Through detailed studies of the simulation trajectories, we found that geminate pairs between urea and bases due to hydrogen bonds and stacks persist only ~ (0.1-1) ns, which suggests that urea-base interaction is highly dynamic. Most importantly, the early stage of base pair disruption is triggered by penetration of water molecules into the hydrophobic domain between the RNA bases. The infiltration of water into the narrow space between base pairs is critical in increasing the accessibility of urea to transiently disrupted bases, thus allowing urea to displace inter base hydrogen bonds. This mechanism, water-induced disruption of base-pairs resulting in the formation of a "wet" destabilized RNA followed by solvation by urea, is the exact opposite of the two-stage denaturation of proteins by urea. In the latter case, initial urea penetration creates a dry-globule, which is subsequently solvated by water penetration leading to global protein unfolding. Our work shows that the ability to interact with both water and polar, non-polar components of nucleotides makes urea a powerful chemical denaturant for nucleic acids.

  9. Band structure and decay channels of thorium-229 low-lying isomeric state for ensemble of thorium atoms adsorbed on calcium fluoride

    Energy Technology Data Exchange (ETDEWEB)

    Borisyuk, Petr V.; Vasilyev, Oleg S.; Krasavin, Andrey V.; Troyan, Victor I. [National Research Nuclear University ' ' MEPhI' ' (Moscow Engineering Physics Institute), Kashirskoye shosse 31, 115409 Moscow (Russian Federation); Lebedinskii, Yury Yu. [National Research Nuclear University ' ' MEPhI' ' (Moscow Engineering Physics Institute), Kashirskoye shosse 31, 115409 Moscow (Russian Federation); Moscow Institute of Physics and Technology (State University), Institutskiy per. 9, 141700 Dolgoprudny, Moscow region (Russian Federation); Tkalya, Eugene V. [Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Leninskie gory, 119991 Moscow (Russian Federation); Nuclear Safety Institute of Russian Academy of Science, Bol' shaya Tulskaya 52, 115191 Moscow (Russian Federation)

    2015-12-15

    The results are presented on the study of the electronic structure of thorium atoms adsorbed by the liquid atomic layer deposition from aqueous solution of thorium nitrate on the surface of CaF{sub 2}. The chemical state of the atoms and the change of the band structure in the surface layers of Th/CaF{sub 2} system on CaF{sub 2} substrate were investigated by XPS and REELS techniques. It was found that REELS spectra for Th/CaF{sub 2} system include peaks in the region of low energy losses (3-7 eV) which are missing in the similar spectra for pure CaF{sub 2}. It is concluded that the presence of the observed features in the REELS spectra is associated with the chemical state of thorium atoms and is caused by the presence of uncompensated chemical bonds at the Th/CaF{sub 2} interface, and, therefore, by the presence of unbound 6d- and 7s-electrons of thorium atoms. Assuming the equivalence of the electronic configuration of thorium-229 and thorium-232 atoms, an estimate was made on the time decay of the excited state of thorium-229 nuclei through the channel of the electron conversion. It was found that the relaxation time is about 40 μs for 6d-electrons, and about 1 μs for 7s-electrons. (copyright 2015 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  10. Band structure and decay channels of thorium-229 low-lying isomeric state for ensemble of thorium atoms adsorbed on calcium fluoride

    OpenAIRE

    Borisyuk, P. V.; Vasilyev, O S; Krasavin, A.V.; Lebedinskii, Yu Yu; V. I. Troyan; Tkalya, E. V.

    2015-01-01

    The results are presented on the study of the electronic structure of thorium atoms adsorbed by the liquid atomic layer deposition from aqueous solution of thorium nitrate on the surface of CaF2. The chemical state of the atoms and the change of the band structure in the surface layers of Th/CaF2 system on CaF2 substrate were investigated by XPS and REELS techniques. It was found that REELS spectra for Th/CaF2 system include peaks in the region of low energy losses (3-7 eV) which are missing ...

  11. Ensemble data assimilation for the reconstruction of mantle circulation

    Science.gov (United States)

    Bocher, Marie; Coltice, Nicolas; Fournier, Alexandre; Tackley, Paul

    2016-04-01

    The surface tectonics of the Earth is the result of mantle dynamics. This link between internal and surface dynamics can be used to reconstruct the evolution of mantle circulation. This is classically done by imposing plate tectonics reconstructions as boundary conditions on numerical models of mantle convection. However, this technique does not account for uncertainties in plate tectonics reconstructions and does not allow any dynamical feedback of mantle dynamics on surface tectonics to develop. Mantle convection models are now able to produce surface tectonics comparable to that of the Earth to first order. We capitalize on these convection models to propose a more consistent integration of plate tectonics reconstructions into mantle convection models. For this purpose, we use the ensemble Kalman filter. This method has been developed and successfully applied to meteorology, oceanography and even more recently outer core dynamics. It consists in integrating sequentially a time series of data into a numerical model, starting from an ensemble of possible initial states. The initial ensemble of states is designed to represent an approximation of the probability density function (pdf) of the a priori state of the system. Whenever new observations are available, each member of the ensemble states is corrected considering both the approximated pdf of the state, and the pdf of the new data. Between two observation times, each ensemble member evolution is computed independently, using the convection model. This technique provides at each time an approximation of the pdf of the state of the system, in the form of a finite ensemble of states. We perform synthetic experiments to assess the efficiency of this method for the reconstruction of mantle circulation.

  12. Denaturing and non-denaturing gel electrophoresis as methods for the detection ofjunctional diversity in rearranged T cell receptor sequences

    NARCIS (Netherlands)

    Offermans, M.T.C.; Sonneveld, R.D.; Bakker, E.; Deutz-Terlouw, P.P.; Geus, B. de; Rozing, J.

    1995-01-01

    Two nucleic acid gel electrophoresis techniques were tested as a possible tool for analyzing junctional diversity in rearranged T cell receptor (TcR) sequences in order to define the extent of T cell heterogeneity. For this purpose denaturing gradient gel electrophoresis (DGGE) as well as

  13. Testing the dependence of stabilizing effect of osmolytes on the fractional increase in the accessible surface area on thermal and chemical denaturations of proteins.

    Science.gov (United States)

    Rahman, Safikur; Ali, Syed Ausaf; Islam, Asimul; Hassan, Md Imtaiyaz; Ahmad, Faizan

    2016-02-01

    Here we have generated two different denatured states using heat- and guanidinium chloride (GdmCl)-induced denaturations of three disulfide bond free proteins (barstar, cytochrome-c and myoglobin). We have observed that these two denatured states of barstar and myoglobin are structurally and energetically different, for, heat-induced denatured state contains many un-melted residual structure that has a significant amount of secondary and tertiary interactions. We show that structural properties of the denatured state determine the magnitude of the protein stabilization in terms of Gibbs free energy change (ΔGD°) induced by an osmolyte, i.e., the greater the exposed surface area, the greater is the stabilization. Furthermore, we predicted the m-values (ability of osmolyte to fold or unfold proteins) using Tanford's transfer-free energy model for the transfer of proteins to osmolyte solutions. We observed that, for each protein, m-value is comparable with our experimental data in cases of TMAO (trimethylamine-N-oxide) and sarcosine. However, a significant discrepancy between predicted and experimental m-values were observed in the case of glycine-betaine.

  14. Selecting, weeding, and weighting biased climate model ensembles

    Science.gov (United States)

    Jackson, C. S.; Picton, J.; Huerta, G.; Nosedal Sanchez, A.

    2012-12-01

    In the Bayesian formulation, the "log-likelihood" is a test statistic for selecting, weeding, or weighting climate model ensembles with observational data. This statistic has the potential to synthesize the physical and data constraints on quantities of interest. One of the thorny issues for formulating the log-likelihood is how one should account for biases. While in the past we have included a generic discrepancy term, not all biases affect predictions of quantities of interest. We make use of a 165-member ensemble CAM3.1/slab ocean climate models with different parameter settings to think through the issues that are involved with predicting each model's sensitivity to greenhouse gas forcing given what can be observed from the base state. In particular we use multivariate empirical orthogonal functions to decompose the differences that exist among this ensemble to discover what fields and regions matter to the model's sensitivity. We find that the differences that matter are a small fraction of the total discrepancy. Moreover, weighting members of the ensemble using this knowledge does a relatively poor job of adjusting the ensemble mean toward the known answer. This points out the shortcomings of using weights to correct for biases in climate model ensembles created by a selection process that does not emphasize the priorities of your log-likelihood.

  15. An automated approach to network features of protein structure ensembles.

    Science.gov (United States)

    Bhattacharyya, Moitrayee; Bhat, Chanda R; Vishveshwara, Saraswathi

    2013-10-01

    Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of β2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html.

  16. Brownian dynamics simulations of sequence-dependent duplex denaturation in dynamically superhelical DNA

    Science.gov (United States)

    Mielke, Steven P.; Grønbech-Jensen, Niels; Krishnan, V. V.; Fink, William H.; Benham, Craig J.

    2005-09-01

    The topological state of DNA in vivo is dynamically regulated by a number of processes that involve interactions with bound proteins. In one such process, the tracking of RNA polymerase along the double helix during transcription, restriction of rotational motion of the polymerase and associated structures, generates waves of overtwist downstream and undertwist upstream from the site of transcription. The resulting superhelical stress is often sufficient to drive double-stranded DNA into a denatured state at locations such as promoters and origins of replication, where sequence-specific duplex opening is a prerequisite for biological function. In this way, transcription and other events that actively supercoil the DNA provide a mechanism for dynamically coupling genetic activity with regulatory and other cellular processes. Although computer modeling has provided insight into the equilibrium dynamics of DNA supercoiling, to date no model has appeared for simulating sequence-dependent DNA strand separation under the nonequilibrium conditions imposed by the dynamic introduction of torsional stress. Here, we introduce such a model and present results from an initial set of computer simulations in which the sequences of dynamically superhelical, 147 base pair DNA circles were systematically altered in order to probe the accuracy with which the model can predict location, extent, and time of stress-induced duplex denaturation. The results agree both with well-tested statistical mechanical calculations and with available experimental information. Additionally, we find that sites susceptible to denaturation show a propensity for localizing to supercoil apices, suggesting that base sequence determines locations of strand separation not only through the energetics of interstrand interactions, but also by influencing the geometry of supercoiling.

  17. Evaluating the trade-offs between ensemble size and ensemble resolution in an ensemble-variational data assimilation system

    Science.gov (United States)

    Lei, Lili; Whitaker, Jeffrey S.

    2017-06-01

    The current NCEP operational four-dimensional ensemble-variational data assimilation system uses a control forecast at T1534 resolution coupled with an 80 member ensemble at T574 resolution. Given an increase in computing resources, and assuming the control forecast resolution is fixed, would it be better to increase the ensemble size and keep the ensemble resolution the same, or increase the ensemble resolution and keep the ensemble size the same? To answer this question, experiments are conducted at reduced resolutions. Two sets of experiments are conducted which both use approximately four times more computational resources than the control experiment that uses a control forecast at T670 and an 80 member ensemble at T254. One increases the ensemble size to 320 but keeps the ensemble resolution at T254; and the other increases the ensemble resolution to T670 but retains an 80 ensemble size. When ensemble size increases to 320, turning off the static component of the background-error covariance does not degrade performance. When the data assimilation parameters are tuned for optimal performance, increasing either ensemble size or ensemble resolution can improve the forecast performance. Increasing ensemble resolution is slightly, but significantly better than increasing ensemble size for these experiments, particularly when considering errors at smaller scales. Much of the benefit of increasing ensemble resolution comes about by eliminating the need for a deterministic control forecast and running all of the background forecasts at the same resolution. In this "single-resolution" mode, the control forecast is replaced by an ensemble average, which reduces small-scale errors significantly.

  18. Theoretical Study on Effects of Salt and Temperature on Denaturation Transition of Double-stranded DNA

    Institute of Scientific and Technical Information of China (English)

    DONG Rui-Xin; YAN Xun-Ling; PANG Xiao-Feng; JIANG Shan; LIU Sheng-Gang

    2004-01-01

    We investigate the statistical mechanics properties of a nonlinear dynamics model of the denaturation of the DNA double-helix and study the effects of salt concentration and temperature on denaturation transition of DNA. The specific heat, entropy, and denaturation temperature of the system versus salt concentration are obtained. These results show that the denaturation of DNA not only depends on the temperature but also is influenced by the salt concentration in the solution of DNA, which are in agreement with experimental measurement.

  19. Algorithms on ensemble quantum computers.

    Science.gov (United States)

    Boykin, P Oscar; Mor, Tal; Roychowdhury, Vwani; Vatan, Farrokh

    2010-06-01

    In ensemble (or bulk) quantum computation, all computations are performed on an ensemble of computers rather than on a single computer. Measurements of qubits in an individual computer cannot be performed; instead, only expectation values (over the complete ensemble of computers) can be measured. As a result of this limitation on the model of computation, many algorithms cannot be processed directly on such computers, and must be modified, as the common strategy of delaying the measurements usually does not resolve this ensemble-measurement problem. Here we present several new strategies for resolving this problem. Based on these strategies we provide new versions of some of the most important quantum algorithms, versions that are suitable for implementing on ensemble quantum computers, e.g., on liquid NMR quantum computers. These algorithms are Shor's factorization algorithm, Grover's search algorithm (with several marked items), and an algorithm for quantum fault-tolerant computation. The first two algorithms are simply modified using a randomizing and a sorting strategies. For the last algorithm, we develop a classical-quantum hybrid strategy for removing measurements. We use it to present a novel quantum fault-tolerant scheme. More explicitly, we present schemes for fault-tolerant measurement-free implementation of Toffoli and σ(z)(¼) as these operations cannot be implemented "bitwise", and their standard fault-tolerant implementations require measurement.

  20. Motor-motor interactions in ensembles of muscle myosin: using theory to connect single molecule to ensemble measurements

    Science.gov (United States)

    Walcott, Sam

    2013-03-01

    Interactions between the proteins actin and myosin drive muscle contraction. Properties of a single myosin interacting with an actin filament are largely known, but a trillion myosins work together in muscle. We are interested in how single-molecule properties relate to ensemble function. Myosin's reaction rates depend on force, so ensemble models keep track of both molecular state and force on each molecule. These models make subtle predictions, e.g. that myosin, when part of an ensemble, moves actin faster than when isolated. This acceleration arises because forces between molecules speed reaction kinetics. Experiments support this prediction and allow parameter estimates. A model based on this analysis describes experiments from single molecule to ensemble. In vivo, actin is regulated by proteins that, when present, cause the binding of one myosin to speed the binding of its neighbors; binding becomes cooperative. Although such interactions preclude the mean field approximation, a set of linear ODEs describes these ensembles under simplified experimental conditions. In these experiments cooperativity is strong, with the binding of one molecule affecting ten neighbors on either side. We progress toward a description of myosin ensembles under physiological conditions.

  1. Accurate Atom Counting in Mesoscopic Ensembles

    CERN Document Server

    Hume, D B; Joos, M; Muessel, W; Strobel, H; Oberthaler, M K

    2013-01-01

    Many cold atom experiments rely on precise atom number detection, especially in the context of quantum-enhanced metrology where effects at the single particle level are important. Here, we investigate the limits of atom number counting via resonant fluorescence detection for mesoscopic samples of trapped atoms. We characterize the precision of these fluorescence measurements beginning from the single-atom level up to more than one thousand. By investigating the primary noise sources, we obtain single-atom resolution for atom numbers as high as 1200. This capability is an essential prerequisite for future experiments with highly entangled states of mesoscopic atomic ensembles.

  2. Accurate Atom Counting in Mesoscopic Ensembles

    Science.gov (United States)

    Hume, D. B.; Stroescu, I.; Joos, M.; Muessel, W.; Strobel, H.; Oberthaler, M. K.

    2013-12-01

    Many cold atom experiments rely on precise atom number detection, especially in the context of quantum-enhanced metrology where effects at the single particle level are important. Here, we investigate the limits of atom number counting via resonant fluorescence detection for mesoscopic samples of trapped atoms. We characterize the precision of these fluorescence measurements beginning from the single-atom level up to more than one thousand. By investigating the primary noise sources, we obtain single-atom resolution for atom numbers as high as 1200. This capability is an essential prerequisite for future experiments with highly entangled states of mesoscopic atomic ensembles.

  3. Accurate atom counting in mesoscopic ensembles.

    Science.gov (United States)

    Hume, D B; Stroescu, I; Joos, M; Muessel, W; Strobel, H; Oberthaler, M K

    2013-12-20

    Many cold atom experiments rely on precise atom number detection, especially in the context of quantum-enhanced metrology where effects at the single particle level are important. Here, we investigate the limits of atom number counting via resonant fluorescence detection for mesoscopic samples of trapped atoms. We characterize the precision of these fluorescence measurements beginning from the single-atom level up to more than one thousand. By investigating the primary noise sources, we obtain single-atom resolution for atom numbers as high as 1200. This capability is an essential prerequisite for future experiments with highly entangled states of mesoscopic atomic ensembles.

  4. Linking neuronal ensembles by associative synaptic plasticity.

    Directory of Open Access Journals (Sweden)

    Qi Yuan

    Full Text Available Synchronized activity in ensembles of neurons recruited by excitatory afferents is thought to contribute to the coding information in the brain. However, the mechanisms by which neuronal ensembles are generated and modified are not known. Here we show that in rat hippocampal slices associative synaptic plasticity enables ensembles of neurons to change by incorporating neurons belonging to different ensembles. Associative synaptic plasticity redistributes the composition of different ensembles recruited by distinct inputs such as to specifically increase the similarity between the ensembles. These results show that in the hippocampus, the ensemble of neurons recruited by a given afferent projection is fluid and can be rapidly and persistently modified to specifically include neurons from different ensembles. This linking of ensembles may contribute to the formation of associative memories.

  5. Understanding the structural ensembles of a highly extended disordered protein.

    Science.gov (United States)

    Daughdrill, Gary W; Kashtanov, Stepan; Stancik, Amber; Hill, Shannon E; Helms, Gregory; Muschol, Martin; Receveur-Bréchot, Véronique; Ytreberg, F Marty

    2012-01-01

    Developing a comprehensive description of the equilibrium structural ensembles for intrinsically disordered proteins (IDPs) is essential to understanding their function. The p53 transactivation domain (p53TAD) is an IDP that interacts with multiple protein partners and contains numerous phosphorylation sites. Multiple techniques were used to investigate the equilibrium structural ensemble of p53TAD in its native and chemically unfolded states. The results from these experiments show that the native state of p53TAD has dimensions similar to a classical random coil while the chemically unfolded state is more extended. To investigate the molecular properties responsible for this behavior, a novel algorithm that generates diverse and unbiased structural ensembles of IDPs was developed. This algorithm was used to generate a large pool of plausible p53TAD structures that were reweighted to identify a subset of structures with the best fit to small angle X-ray scattering data. High weight structures in the native state ensemble show features that are localized to protein binding sites and regions with high proline content. The features localized to the protein binding sites are mostly eliminated in the chemically unfolded ensemble; while, the regions with high proline content remain relatively unaffected. Data from NMR experiments support these results, showing that residues from the protein binding sites experience larger environmental changes upon unfolding by urea than regions with high proline content. This behavior is consistent with the urea-induced exposure of nonpolar and aromatic side-chains in the protein binding sites that are partially excluded from solvent in the native state ensemble.

  6. Data assimilation using a climatologically augmented local ensemble transform Kalman filter

    Directory of Open Access Journals (Sweden)

    Matthew Kretschmer

    2015-05-01

    Full Text Available Ensemble data assimilation methods are potentially attractive because they provide a computationally affordable (and computationally parallel means of obtaining flow-dependent background-error statistics. However, a limitation of these methods is that the rank of their flow-dependent background-error covariance estimate, and hence the space of possible analysis increments, is limited by the number of forecast ensemble members. To overcome this deficiency ensemble methods typically use empirical localisation, which allows more degrees of freedom for the analysis increment by suppressing spatially distant background correlations. The method presented here improves the performance of an Ensemble Kalman filter by increasing the size of the ensemble at analysis time in order to boost the rank of its background-error covariance estimate. The additional ensemble members added to the forecast ensemble at analysis time are created by adding a collection of ‘climatological’ perturbations to the forecast ensemble mean. These perturbations are constant in time and provide state space directions, possibly missed by the dynamically forecasted background ensemble, in which the analysis increment can correct the forecast mean based on observations. As the climatological perturbations are calculated once, there is negligible computational cost in obtaining the additional ensemble members at each analysis cycle. Included here are a formulation of the method, results of numerical experiments conducted with a spatiotemporally chaotic model in one spatial dimension and discussion of possible future extensions and applications. The numerical tests indicate that the method presented here has significant potential for improving analyses and forecasts.

  7. Conservation of Mass and Preservation of Positivity with Ensemble-Type Kalman Filter Algorithms

    Science.gov (United States)

    Janjic, Tijana; Mclaughlin, Dennis; Cohn, Stephen E.; Verlaan, Martin

    2014-01-01

    This paper considers the incorporation of constraints to enforce physically based conservation laws in the ensemble Kalman filter. In particular, constraints are used to ensure that the ensemble members and the ensemble mean conserve mass and remain nonnegative through measurement updates. In certain situations filtering algorithms such as the ensemble Kalman filter (EnKF) and ensemble transform Kalman filter (ETKF) yield updated ensembles that conserve mass but are negative, even though the actual states must be nonnegative. In such situations if negative values are set to zero, or a log transform is introduced, the total mass will not be conserved. In this study, mass and positivity are both preserved by formulating the filter update as a set of quadratic programming problems that incorporate non-negativity constraints. Simple numerical experiments indicate that this approach can have a significant positive impact on the posterior ensemble distribution, giving results that are more physically plausible both for individual ensemble members and for the ensemble mean. In two examples, an update that includes a non-negativity constraint is able to properly describe the transport of a sharp feature (e.g., a triangle or cone). A number of implementation questions still need to be addressed, particularly the need to develop a computationally efficient quadratic programming update for large ensemble.

  8. Rheological properties of sweet potato starch before and after denaturalization

    Institute of Scientific and Technical Information of China (English)

    肖华西; 林亲录; 夏新剑; 李丽辉; 林利忠; 吴卫国

    2008-01-01

    Based on the sweet potato starch,cationic starch,acetic starch and cationic-acetic compoundedly modified starch were made through chemical denaturalization.The above three kinds of static rheological parameter and dynamic rheological parameter were measured,respectively.The experimental result reveals that the thermal stability of starchy viscosity increases after chemical denaturalization.Under the condition of identical shearing rate,the shear stress of cationic-acetic ester compoundedly modified sweet potato starch paste is the largest among these kinds of sweet potato starch.This attributes to a phenomenon of shearing thinning.Furthermore,raw sweet potato starch has a larger gel intensity than that of modified starch.

  9. Influence of Ficoll on urea induced denaturation of fibrinogen

    Science.gov (United States)

    Sankaranarayanan, Kamatchi; Meenakshisundaram, N.

    2016-03-01

    Ficoll is a neutral, highly branched polymer used as a molecular crowder in the study of proteins. Ficoll is also part of Ficoll-Paque used in biology laboratories to separate blood to its components (erythrocytes, leukocytes etc.,). Role of Ficoll in the urea induced denaturation of protein Fibrinogen (Fg) has been analyzed using fluorescence, circular dichroism, molecular docking and interfacial studies. Fluorescence studies show that Ficoll prevents quenching of Fg in the presence of urea. From the circular dichroism spectra, Fg shows conformational transition to random coil with urea of 6 M concentration. Ficoll helps to shift this denaturation concentration to 8 M and thus constraints by shielding Fg during the process. Molecular docking studies indicate that Ficoll interacts favorably with the protein than urea. The surface tension and shear viscosity analysis shows clearly that the protein is shielded by Ficoll.

  10. Ensemble Kalman filtering with residual nudging

    Directory of Open Access Journals (Sweden)

    Xiaodong Luo

    2012-10-01

    Full Text Available Covariance inflation and localisation are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF by (in effect adjusting the sample covariances of the estimates in the state space. In this work, an additional auxiliary technique, called residual nudging, is proposed to monitor and, if necessary, adjust the residual norms of state estimates in the observation space. In an EnKF with residual nudging, if the residual norm of an analysis is larger than a pre-specified value, then the analysis is replaced by a new one whose residual norm is no larger than a pre-specified value. Otherwise, the analysis is considered as a reasonable estimate and no change is made. A rule for choosing the pre-specified value is suggested. Based on this rule, the corresponding new state estimates are explicitly derived in case of linear observations. Numerical experiments in the 40-dimensional Lorenz 96 model show that introducing residual nudging to an EnKF may improve its accuracy and/or enhance its stability against filter divergence, especially in the small ensemble scenario.

  11. Ensemble Kalman filtering with residual nudging

    KAUST Repository

    Luo, X.

    2012-10-03

    Covariance inflation and localisation are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF) by (in effect) adjusting the sample covariances of the estimates in the state space. In this work, an additional auxiliary technique, called residual nudging, is proposed to monitor and, if necessary, adjust the residual norms of state estimates in the observation space. In an EnKF with residual nudging, if the residual norm of an analysis is larger than a pre-specified value, then the analysis is replaced by a new one whose residual norm is no larger than a pre-specified value. Otherwise, the analysis is considered as a reasonable estimate and no change is made. A rule for choosing the pre-specified value is suggested. Based on this rule, the corresponding new state estimates are explicitly derived in case of linear observations. Numerical experiments in the 40-dimensional Lorenz 96 model show that introducing residual nudging to an EnKF may improve its accuracy and/or enhance its stability against filter divergence, especially in the small ensemble scenario.

  12. A mollified Ensemble Kalman filter

    CERN Document Server

    Bergemann, Kay

    2010-01-01

    It is well recognized that discontinuous analysis increments of sequential data assimilation systems, such as ensemble Kalman filters, might lead to spurious high frequency adjustment processes in the model dynamics. Various methods have been devised to continuously spread out the analysis increments over a fixed time interval centered about analysis time. Among these techniques are nudging and incremental analysis updates (IAU). Here we propose another alternative, which may be viewed as a hybrid of nudging and IAU and which arises naturally from a recently proposed continuous formulation of the ensemble Kalman analysis step. A new slow-fast extension of the popular Lorenz-96 model is introduced to demonstrate the properties of the proposed mollified ensemble Kalman filter.

  13. Matrix product purifications for canonical ensembles and quantum number distributions

    Science.gov (United States)

    Barthel, Thomas

    2016-09-01

    Matrix product purifications (MPPs) are a very efficient tool for the simulation of strongly correlated quantum many-body systems at finite temperatures. When a system features symmetries, these can be used to reduce computation costs substantially. It is straightforward to compute an MPP of a grand-canonical ensemble, also when symmetries are exploited. This paper provides and demonstrates methods for the efficient computation of MPPs of canonical ensembles under utilization of symmetries. Furthermore, we present a scheme for the evaluation of global quantum number distributions using matrix product density operators (MPDOs). We provide exact matrix product representations for canonical infinite-temperature states, and discuss how they can be constructed alternatively by applying matrix product operators to vacuum-type states or by using entangler Hamiltonians. A demonstration of the techniques for Heisenberg spin-1 /2 chains explains why the difference in the energy densities of canonical and grand-canonical ensembles decays as 1 /L .

  14. Temperature induced denaturation of collagen in acidic solution.

    Science.gov (United States)

    Mu, Changdao; Li, Defu; Lin, Wei; Ding, Yanwei; Zhang, Guangzhao

    2007-07-01

    The denaturation of collagen solution in acetic acid has been investigated by using ultra-sensitive differential scanning calorimetry (US-DSC), circular dichroism (CD), and laser light scattering (LLS). US-DSC measurements reveal that the collagen exhibits a bimodal transition, i.e., there exists a shoulder transition before the major transition. Such a shoulder transition can recover from a cooling when the collagen is heated to a temperature below 35 degrees C. However, when the heating temperature is above 37 degrees C, both the shoulder and major transitions are irreversible. CD measurements demonstrate the content of triple helix slowly decreases with temperature at a temperature below 35 degrees C, but it drastically decreases at a higher temperature. Our experiments suggest that the shoulder transition and major transition arise from the defibrillation and denaturation of collagen, respectively. LLS measurements show the average hydrodynamic radius R(h), radius of gyration R(g)of the collagen gradually decrease before a sharp decrease at a higher temperature. Meanwhile, the ratio R(g)/R(h) gradually increases at a temperature below approximately 34 degrees C and drastically increases in the range 34-40 degrees C, further indicating the defibrillation of collagen before the denaturation.

  15. [DNA degradation during standard alkaline of thermal denaturation].

    Science.gov (United States)

    Drozhdeniuk, A P; Sulimova, G E; Vaniushin, B F

    1976-01-01

    Essential degradation 8 DNA (up to 10 per cent) with liberation of acid-soluble fragments takes place on the standard alkaline (0,01 M sodium phosphate, pH 12, 60 degrees, 15 min) or thermal (0.06 M sodium phosphate buffer, pH 6.8, 102 degrees C, 15 min) denaturation. This degradation is more or less selective: fraction of low molecular weight fragments, isolated by hydroxyapatite cromatography and eluted by 0.06 M sodium phosphate buffer, pH 6.8 is rich in adenine and thymine and contains about 2 times less 5-methylcytosine than the total wheat germ DNA. The degree of degradation of DNA on thermal denaturation is higher than on alkaline degradation. Therefore while studying reassociation of various DNA, one and the same standard method of DNA denaturation should be used. Besides, both the level of DNA degradation and the nature of the resulting products (fragments) should be taken into account.

  16. The guanidine hydrochloride-induced denaturation of CP43 and CP47 studied by terahertz time-domain spectroscopy

    Institute of Scientific and Technical Information of China (English)

    QU YuanGang; CHEN Hua; QIN XiaoChun; WANG Li; LI LiangBi; KUANG TingYun

    2007-01-01

    Terahertz time-domain spectroscopy (THz-TDS) is a new technique in studying the conformational state of a molecule in recent years. In this work, we reported the first use of THz-TDS to examine the denaturation of two photosynthesis membrane proteins: CP43 and CP47. THz-TDS was proven to be useful in discriminating the different conformational states of given proteins with similar structure and in monitoring the denaturation process of proteins. Upon treatment with guanidine hydrochloride (GuHCI),a 1.8 THz peak appeared for CP47 and free chlorophyll a (Chi a). This peak was deemed to originate from the interaction between Chli a and GuHCI molecules. The Chl a molecules in CP47 interacted with GuHCI more easily than those in CP43.

  17. Effects of pH on proteins: predictions for ensemble and single-molecule pulling experiments.

    Science.gov (United States)

    O'Brien, Edward P; Brooks, Bernard R; Thirumalai, D

    2012-01-18

    Protein conformations change among distinct thermodynamic states as solution conditions (temperature, denaturants, pH) are altered or when they are subjected to mechanical forces. A quantitative description of the changes in the relative stabilities of the various thermodynamic states is needed to interpret and predict experimental outcomes. We provide a framework based on the Molecular Transfer Model (MTM) to account for pH effects on the properties of globular proteins. The MTM utilizes the partition function of a protein calculated from molecular simulations at one set of solution conditions to predict protein properties at another set of solution conditions. To take pH effects into account, we utilized experimentally measured pK(a) values in the native and unfolded states to calculate the free energy of transferring a protein from a reference pH to the pH of interest. We validate our approach by demonstrating that the native-state stability as a function of pH is accurately predicted for chymotrypsin inhibitor 2 (CI2) and protein G. We use the MTM to predict the response of CI2 and protein G subjected to a constant force (f) and varying pH. The phase diagrams of CI2 and protein G as a function of f and pH are dramatically different and reflect the underlying pH-dependent stability changes in the absence of force. The calculated equilibrium free energy profiles as functions of the end-to-end distance of the two proteins show that, at various pH values, CI2 unfolds via an intermediate when subjected to f. The locations of the two transition states move toward the more unstable state as f is changed, which is in accord with the Hammond-Leffler postulate. In sharp contrast, force-induced unfolding of protein G occurs in a single step. Remarkably, the location of the transition state with respect to the folded state is independent of f, which suggests that protein G is mechanically brittle. The MTM provides a natural framework for predicting the outcomes of ensemble

  18. Hybrid ensemble 4DVar assimilation of stratospheric ozone using a global shallow water model

    Science.gov (United States)

    Allen, Douglas R.; Hoppel, Karl W.; Kuhl, David D.

    2016-07-01

    Wind extraction from stratospheric ozone (O3) assimilation is examined using a hybrid ensemble 4-D variational assimilation (4DVar) shallow water model (SWM) system coupled to the tracer advection equation. Stratospheric radiance observations are simulated using global observations of the SWM fluid height (Z), while O3 observations represent sampling by a typical polar-orbiting satellite. Four ensemble sizes were examined (25, 50, 100, and 1518 members), with the largest ensemble equal to the number of dynamical state variables. The optimal length scale for ensemble localization was found by tuning an ensemble Kalman filter (EnKF). This scale was then used for localizing the ensemble covariances that were blended with conventional covariances in the hybrid 4DVar experiments. Both optimal length scale and optimal blending coefficient increase with ensemble size, with optimal blending coefficients varying from 0.2-0.5 for small ensembles to 0.5-1.0 for large ensembles. The hybrid system outperforms conventional 4DVar for all ensemble sizes, while for large ensembles the hybrid produces similar results to the offline EnKF. Assimilating O3 in addition to Z benefits the winds in the hybrid system, with the fractional improvement in global vector wind increasing from ˜ 35 % with 25 and 50 members to ˜ 50 % with 1518 members. For the smallest ensembles (25 and 50 members), the hybrid 4DVar assimilation improves the zonal wind analysis over conventional 4DVar in the Northern Hemisphere (winter-like) region and also at the Equator, where Z observations alone have difficulty constraining winds due to lack of geostrophy. For larger ensembles (100 and 1518 members), the hybrid system results in both zonal and meridional wind error reductions, relative to 4DVar, across the globe.

  19. A study of the thermal denaturation of the S-layer protein from Lactobacillus salivarius

    Science.gov (United States)

    Lighezan, Liliana; Georgieva, Ralitsa; Neagu, Adrian

    2012-09-01

    Surface layer (S-layer) proteins display an intrinsic self-assembly property, forming monomolecular crystalline arrays, identified in outermost structures of the cell envelope in many organisms, such as bacteria and archaea. Isolated S-layer proteins also possess the ability to recrystallize into regular lattices, being used in biotechnological applications, such as controlling the architecture of biomimetic surfaces. To this end, the stability of the S-layer proteins under high-temperature conditions is very important. In this study, the S-layer protein has been isolated from Lactobacillus salivarius 16 strain of human origin, and purified by cation-exchange chromatography. Using circular dichroism (CD) spectroscopy, we have investigated the thermal denaturation of the S-layer protein. The far- and near-UV CD spectra have been collected, and the temperature dependence of the CD signal in these spectral domains has been analyzed. The variable temperature results show that the secondary and tertiary structures of the S-layer protein change irreversibly due to the heating of the sample. After the cooling of the heated protein, the secondary and tertiary structures are partially recovered. The denaturation curves show that the protein unfolding depends on the sample concentration and on the heating rate. The secondary and tertiary structures of the protein suffer changes in the same temperature range. We have also detected an intermediate state in the protein denaturation pathway. Our results on the thermal behavior of the S-layer protein may be important for the use of S-layer proteins in biotechnological applications, as well as for a better understanding of the structure and function of S-layer proteins.

  20. Hierarchical Bayes Ensemble Kalman Filter for geophysical data assimilation

    Science.gov (United States)

    Tsyrulnikov, Michael; Rakitko, Alexander

    2016-04-01

    In the Ensemble Kalman Filter (EnKF), the forecast error covariance matrix B is estimated from a sample (ensemble), which inevitably implies a degree of uncertainty. This uncertainty is especially large in high dimensions, where the affordable ensemble size is orders of magnitude less than the dimensionality of the system. Common remedies include ad-hoc devices like variance inflation and covariance localization. The goal of this study is to optimize the account for the inherent uncertainty of the B matrix in EnKF. Following the idea by Myrseth and Omre (2010), we explicitly admit that the B matrix is unknown and random and estimate it along with the state (x) in an optimal hierarchical Bayes analysis scheme. We separate forecast errors into predictability errors (i.e. forecast errors due to uncertainties in the initial data) and model errors (forecast errors due to imperfections in the forecast model) and include the two respective components P and Q of the B matrix into the extended control vector (x,P,Q). Similarly, we break the traditional forecast ensemble into the predictability-error related ensemble and model-error related ensemble. The reason for the separation of model errors from predictability errors is the fundamental difference between the two sources of error. Model error are external (i.e. do not depend on the filter's performance) whereas predictability errors are internal to a filter (i.e. are determined by the filter's behavior). At the analysis step, we specify Inverse Wishart based priors for the random matrices P and Q and conditionally Gaussian prior for the state x. Then, we update the prior distribution of (x,P,Q) using both observation and ensemble data, so that ensemble members are used as generalized observations and ordinary observations are allowed to influence the covariances. We show that for linear dynamics and linear observation operators, conditional Gaussianity of the state is preserved in the course of filtering. At the forecast

  1. Guanidinium chloride and urea denaturations of beta-lactoglobulin A at pH 2.0 and 25 degrees C: the equilibrium intermediate contains non-native structures (helix, tryptophan and hydrophobic patches).

    Science.gov (United States)

    Dar, Tanveer Ali; Singh, Laishram Rajendrakumar; Islam, Asimul; Anjum, Farah; Moosavi-Movahedi, Ali Akbar; Ahmad, Faizan

    2007-05-01

    We have carried out guanidinium chloride (GdmCl) and urea denaturations of bovine beta-lactoglobulin A (beta-lgA) at pH 2.0 and 25 degrees C, using far-UV and near-UV circular dichroism, near-UV absorption and tryptophan fluorescence spectroscopies. The stable intermediate state that occurs during GdmCl denaturation has been characterized by the far- and near-UV circular dichroism, tryptophan difference absorption, tryptophan fluorescence and 8-anilino-1-naphthalene sulphonic acid binding measurements. Following conclusions have been reached. (a) Urea-induced denaturation is not a two-state process. (b) GdmCl-induced denaturation is composed of two distinct two-state processes. (c) alpha-Helical content, burial of tryptophan residues and burial of hydrophobic surface area are more in the GdmCl-induced stable intermediate than those originally present in the native protein.

  2. Higher precision estimates of regional polar warming by ensemble regression of climate model projections

    Energy Technology Data Exchange (ETDEWEB)

    Bracegirdle, Thomas J. [British Antarctic Survey, Cambridge (United Kingdom); Stephenson, David B. [University of Exeter, Mathematics Research Institute, Exeter (United Kingdom); NCAS-Climate, Reading (United Kingdom)

    2012-12-15

    This study presents projections of twenty-first century wintertime surface temperature changes over the high-latitude regions based on the third Coupled Model Inter-comparison Project (CMIP3) multi-model ensemble. The state-dependence of the climate change response on the present day mean state is captured using a simple yet robust ensemble linear regression model. The ensemble regression approach gives different and more precise estimated mean responses compared to the ensemble mean approach. Over the Arctic in January, ensemble regression gives less warming than the ensemble mean along the boundary between sea ice and open ocean (sea ice edge). Most notably, the results show 3 C less warming over the Barents Sea ({proportional_to} 7 C compared to {proportional_to} 10 C). In addition, the ensemble regression method gives projections that are 30 % more precise over the Sea of Okhostk, Bering Sea and Labrador Sea. For the Antarctic in winter (July) the ensemble regression method gives 2 C more warming over the Southern Ocean close to the Greenwich Meridian ({proportional_to} 7 C compared to {proportional_to} 5 C). Projection uncertainty was almost half that of the ensemble mean uncertainty over the Southern Ocean between 30 W to 90 E and 30 % less over the northern Antarctic Peninsula. The ensemble regression model avoids the need for explicit ad hoc weighting of models and exploits the whole ensemble to objectively identify overly influential outlier models. Bootstrap resampling shows that maximum precision over the Southern Ocean can be obtained with ensembles having as few as only six climate models. (orig.)

  3. Quantum Memory for Microwave Photons in an Inhomogeneously Broadened Spin Ensemble

    DEFF Research Database (Denmark)

    Julsgaard, Brian; Grezes, Cécile; Bertet, Patrice

    2013-01-01

    We propose a multi-mode quantum memory protocol able to store the quantum state of the field in a microwave resonator into an ensemble of electronic spins. The stored information is protected against inhomogeneous broadening of the spin ensemble by spin-echo techniques resulting in memory times o...

  4. Combining 2-m temperature nowcasting and short range ensemble forecasting

    Directory of Open Access Journals (Sweden)

    A. Kann

    2011-12-01

    Full Text Available During recent years, numerical ensemble prediction systems have become an important tool for estimating the uncertainties of dynamical and physical processes as represented in numerical weather models. The latest generation of limited area ensemble prediction systems (LAM-EPSs allows for probabilistic forecasts at high resolution in both space and time. However, these systems still suffer from systematic deficiencies. Especially for nowcasting (0–6 h applications the ensemble spread is smaller than the actual forecast error. This paper tries to generate probabilistic short range 2-m temperature forecasts by combining a state-of-the-art nowcasting method and a limited area ensemble system, and compares the results with statistical methods. The Integrated Nowcasting Through Comprehensive Analysis (INCA system, which has been in operation at the Central Institute for Meteorology and Geodynamics (ZAMG since 2006 (Haiden et al., 2011, provides short range deterministic forecasts at high temporal (15 min–60 min and spatial (1 km resolution. An INCA Ensemble (INCA-EPS of 2-m temperature forecasts is constructed by applying a dynamical approach, a statistical approach, and a combined dynamic-statistical method. The dynamical method takes uncertainty information (i.e. ensemble variance from the operational limited area ensemble system ALADIN-LAEF (Aire Limitée Adaptation Dynamique Développement InterNational Limited Area Ensemble Forecasting which is running operationally at ZAMG (Wang et al., 2011. The purely statistical method assumes a well-calibrated spread-skill relation and applies ensemble spread according to the skill of the INCA forecast of the most recent past. The combined dynamic-statistical approach adapts the ensemble variance gained from ALADIN-LAEF with non-homogeneous Gaussian regression (NGR which yields a statistical mbox{correction} of the first and second moment (mean bias and dispersion for Gaussian distributed continuous

  5. Multimodel ensembles of wheat growth

    DEFF Research Database (Denmark)

    Martre, Pierre; Wallach, Daniel; Asseng, Senthold

    2015-01-01

    , but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24...

  6. Global Ensemble Forecast System (GEFS) [1 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  7. Four-dimensional Localization and the Iterative Ensemble Kalman Smoother

    Science.gov (United States)

    Bocquet, M.

    2015-12-01

    The iterative ensemble Kalman smoother (IEnKS) is a data assimilation method meant for efficiently tracking the state ofnonlinear geophysical models. It combines an ensemble of model states to estimate the errors similarly to the ensemblesquare root Kalman filter, with a 4D-variational analysis performed within the ensemble space. As such it belongs tothe class of ensemble variational methods. Recently introduced 4DEnVar or the 4D-LETKF can be seen as particular casesof the scheme. The IEnKS was shown to outperform 4D-Var, the ensemble Kalman filter (EnKF) and smoother, with low-ordermodels in all investigated dynamical regimes. Like any ensemble method, it could require the use of localization of theanalysis when the state space dimension is high. However, localization for the IEnKS is not as straightforward as forthe EnKF. Indeed, localization needs to be defined across time, and it needs to be as much as possible consistent withthe dynamical flow within the data assimilation variational window. We show that a Liouville equation governs the timeevolution of the localization operator, which is linked to the evolution of the error correlations. It is argued thatits time integration strongly depends on the forecast dynamics. Using either covariance localization or domainlocalization, we propose and test several localization strategies meant to address the issue: (i) a constant and uniformlocalization, (ii) the propagation through the window of a restricted set of dominant modes of the error covariancematrix, (iii) the approximate propagation of the localization operator using model covariant local domains. Theseschemes are illustrated on the one-dimensional Lorenz 40-variable model.

  8. Characterizing RNA ensembles from NMR data with kinematic models

    DEFF Research Database (Denmark)

    Fonseca, Rasmus; Pachov, Dimitar V.; Bernauer, Julie;

    2014-01-01

    the conformational landscapes of 3D RNA encoded by NMR proton chemical shifts. KGSrna resolves motionally averaged NMR data into structural contributions; when coupled with residual dipolar coupling data, a KGSrna ensemble revealed a previously uncharacterized transient excited state of the HIV-1 trans...

  9. Ambiguity in Ensemble Forecasting: Evolution, Estimate Validation and Value

    Science.gov (United States)

    2009-09-01

    background-error covariance ( bP̂ ) from Equation (12)(c) must be estimated diagnostically from the ensemble of background states using Equation (12)(a...Although the beta- fit does not always provide a quality fit to the ˆTp data, it was sufficient for the pedagogical purpose here. For this forecast

  10. Equivalence of dynamical ensembles and Navier-Stokes equations

    CERN Document Server

    Gallavotti, G

    1996-01-01

    A reversible version of the Navier Stokes equation is studied. A conjecture emerges stating the equivalence between the reversible equation and the usual Navier Stokes equation. The latter appears as a statement of ensembles equivalence in the limit of infinite Reynolds number, which plays the role of the thermodynamic limit.

  11. Reservoir History Matching Using Ensemble Kalman Filters with Anamorphosis Transforms

    KAUST Repository

    Aman, Beshir M.

    2012-12-01

    This work aims to enhance the Ensemble Kalman Filter performance by transforming the non-Gaussian state variables into Gaussian variables to be a step closer to optimality. This is done by using univariate and multivariate Box-Cox transformation. Some History matching methods such as Kalman filter, particle filter and the ensemble Kalman filter are reviewed and applied to a test case in the reservoir application. The key idea is to apply the transformation before the update step and then transform back after applying the Kalman correction. In general, the results of the multivariate method was promising, despite the fact it over-estimated some variables.

  12. Effect of sulfoxides on the thermal denaturation of hen lysozyme: A calorimetric and Raman study

    Science.gov (United States)

    Torreggiani, A.; Di Foggia, M.; Manco, I.; De Maio, A.; Markarian, S. A.; Bonora, S.

    2008-11-01

    A multidisciplinary study of the thermal denaturation of lysozyme in the presence of three sulfoxides with different length in hydrocarbon chain (DMSO, DESO, and DPSO) was carried out by means of DSC, Raman spectroscopy, and SDS-PAGE techniques. In particular, the Td and Δ H values obtained from the calorimetric measurements showed that lysozyme is partially unfolded by sulfoxides but most of the conformation holds native state. The sulfoxide denaturing ability increases in the order DPSO > DESO > DMSO. Moreover, only DMSO and DESO have a real effect in preventing the heat-induced inactivation of the protein and their maximum heat-protective ability is reached when the DMSO and DESO amount is ⩾25% w/w. The sulfoxide ability to act as effective protective agents against the heat-induced inactivation was confirmed by the protein analysis. The enzymatic activity, as well as the SDS-PAGE analysis, suggested that DESO, having a low hydrophobic character and a great ability to stabilise the three-dimensional water structure, is the most heat-protective sulfoxide. An accurate evaluation of the heat-induced conformational changes of the lysozyme structure before and after sulfoxide addition was obtained by the analysis of the Raman spectra. The addition of DMSO or DESO in low concentration resulted to sensitively decrease the heat-induced structural modifications of the protein.

  13. Urea-induced denaturation of apolipoprotein serum amyloid A reveals marginal stability of hexamer

    Science.gov (United States)

    Wang, Limin; Colón, Wilfredo

    2005-01-01

    Serum Amyloid A (SAA) is an acute phase reactant protein that is predominantly found bound to high-density lipoprotein in plasma. Upon inflammation, the plasma concentration of SAA can increase dramatically, occasionally leading to the development of amyloid A (AA) amyloidosis, which involves the deposition of SAA amyloid fibrils in major organs. We previously found that the murine isoform SAA2.2 exists in aqueous solution as a hexamer containing a central channel. Here we show using various biophysical and biochemical techniques that the SAA2.2 hexamer can be totally dissociated into monomer by ~2 M urea, with the concerted loss of its α-helical structure. However, limited trypsin proteolysis experiments in urea showed a conserved digestion profile, suggesting the preservation of major backbone topological features in the urea-denatured state of SAA2.2. The marginal stability of hexameric SAA2.2 and the presence of residual structure in the denatured monomeric protein suggest that both forms may interconvert in vivo to exert different functions to meet the various needs during normal physiological conditions and in response to inflammatory stimuli. PMID:15937280

  14. Statistical coil model of the unfolded state: resolving the reconciliation problem.

    Science.gov (United States)

    Jha, Abhishek K; Colubri, Andrés; Freed, Karl F; Sosnick, Tobin R

    2005-09-13

    An unfolded state ensemble is generated by using a self-avoiding statistical coil model that is based on backbone conformational frequencies in a coil library, a subset of the Protein Data Bank. The model reproduces two apparently contradicting behaviors observed in the chemically denatured state for a variety of proteins, random coil scaling of the radius of gyration and the presence of significant amounts of local backbone structure (NMR residual dipolar couplings). The most stretched members of our unfolded ensemble dominate the residual dipolar coupling signal, whereas the uniformity of the sign of the couplings follows from the preponderance of polyproline II and beta conformers in the coil library. Agreement with the NMR data substantially improves when the backbone conformational preferences include correlations arising from the chemical and conformational identity of neighboring residues. Although the unfolded ensembles match the experimental observables, they do not display evidence of native-like topology. By providing an accurate representation of the unfolded state, our statistical coil model can be used to improve thermodynamic and kinetic modeling of protein folding.

  15. Ensemble Forecasting of Volcanic Emissions in Hawai’i

    Directory of Open Access Journals (Sweden)

    Andre Kristofer Pattantyus

    2015-03-01

    Full Text Available Deterministic model forecasts do not convey to the end users the forecast uncertainty the models possess as a result of physics parameterizations, simplifications in model representation of physical processes, and errors in initial conditions. This lack of understanding leads to a level of uncertainty in the forecasted value when only a single deterministic model forecast is available. Increasing computational power and parallel software architecture allows multiple simulations to be carried out simultaneously that yield useful measures of model uncertainty that can be derived from ensemble model results. The Hybrid Single Particle Lagrangian Integration Trajectory and Dispersion model has the ability to generate ensemble forecasts. A meteorological ensemble was formed to create probabilistic forecast products and an ensemble mean forecast for volcanic emissions from the Kilauea volcano that impacts the state of Hawai’i. The probabilistic forecast products show uncertainty in pollutant concentrations that are especially useful for decision-making regarding public health. Initial comparison of the ensemble mean forecasts with observations and a single model forecast show improvements in event timing for both sulfur dioxide and sulfate aerosol forecasts.  

  16. Collagen thermal denaturation study for thermal angioplasty based on modified kinetic model: relation between the artery mechanical properties and collagen denaturation rate

    Science.gov (United States)

    Shimazaki, N.; Hayashi, T.; Kunio, M.; Arai, T.

    2010-02-01

    We have been developing the novel short-term heating angioplasty in which sufficient artery lumen-dilatation was attained with thermal softening of collagen fiber in artery wall. In the present study, we investigated on the relation between the mechanical properties of heated artery and thermal denaturation fractures of arterial collagen in ex vivo. We employed Lumry-Eyring model to estimate temperature- and time-dependent thermal denaturation fractures of arterial collagen fiber during heating. We made a kinetic model of arterial collagen thermal denaturation by adjustment of K and k in this model, those were the equilibrium constant of reversible denaturation and the rate constant of irreversible denaturation. Meanwhile we demonstrated that the change of reduced scattering coefficient of whole artery wall during heating reflected the reversible denaturation of the collagen in artery wall. Based on this phenomenon, the K was determined experimentally by backscattered light intensity measurement (at 633nm) of extracted porcine carotid artery during temperature elevation and descending (25°C-->80°C-->25°C). We employed the value of according to our earlier report in which the time-and temperature- dependent irreversible denaturation amount of the artery collagen fiber that was assessed by the artery birefringence. Then, the time- and temperature- dependent reversible (irreversible) denaturation fraction defined as the reversible ((irreversible) denatured collagen amount) / (total collagen amount) was calculated by the model. Thermo-mechanical analysis of artery wall was performed to compare the arterial mechanical behaviors (softening, shrinkage) during heating with the calculated denaturation fraction with the model. In any artery temperature condition in 70-80°, the irreversible denaturation fraction at which the artery thermal shrinkage started was estimated to be around 20%. On the other hand, the calculated irreversible denaturation fraction remained below

  17. Toward a General-Purpose Heterogeneous Ensemble for Pattern Classification

    Directory of Open Access Journals (Sweden)

    Loris Nanni

    2015-01-01

    Full Text Available We perform an extensive study of the performance of different classification approaches on twenty-five datasets (fourteen image datasets and eleven UCI data mining datasets. The aim is to find General-Purpose (GP heterogeneous ensembles (requiring little to no parameter tuning that perform competitively across multiple datasets. The state-of-the-art classifiers examined in this study include the support vector machine, Gaussian process classifiers, random subspace of adaboost, random subspace of rotation boosting, and deep learning classifiers. We demonstrate that a heterogeneous ensemble based on the simple fusion by sum rule of different classifiers performs consistently well across all twenty-five datasets. The most important result of our investigation is demonstrating that some very recent approaches, including the heterogeneous ensemble we propose in this paper, are capable of outperforming an SVM classifier (implemented with LibSVM, even when both kernel selection and SVM parameters are carefully tuned for each dataset.

  18. Toward a General-Purpose Heterogeneous Ensemble for Pattern Classification.

    Science.gov (United States)

    Nanni, Loris; Brahnam, Sheryl; Ghidoni, Stefano; Lumini, Alessandra

    2015-01-01

    We perform an extensive study of the performance of different classification approaches on twenty-five datasets (fourteen image datasets and eleven UCI data mining datasets). The aim is to find General-Purpose (GP) heterogeneous ensembles (requiring little to no parameter tuning) that perform competitively across multiple datasets. The state-of-the-art classifiers examined in this study include the support vector machine, Gaussian process classifiers, random subspace of adaboost, random subspace of rotation boosting, and deep learning classifiers. We demonstrate that a heterogeneous ensemble based on the simple fusion by sum rule of different classifiers performs consistently well across all twenty-five datasets. The most important result of our investigation is demonstrating that some very recent approaches, including the heterogeneous ensemble we propose in this paper, are capable of outperforming an SVM classifier (implemented with LibSVM), even when both kernel selection and SVM parameters are carefully tuned for each dataset.

  19. Purification of an unpolarized spin ensemble into entangled singlet pairs

    CERN Document Server

    Greiner, Johannes N; Wrachtrup, Jörg

    2016-01-01

    Dynamical polarization of nuclear spin ensembles is of central importance for magnetic resonance studies, precision sensing and for applications in quantum information theory. Here we propose a scheme to generate long-lived singlet pairs in an unpolarized nuclear spin ensemble which is dipolar coupled to the electron spins of a Nitrogen Vacancy center in diamond. The quantum mechanical back-action induced by frequent spin-selective readout of the NV centers allows the nuclear spins to pair up into maximally entangled singlet pairs. Counterintuitively, the robustness of the pair formation to dephasing noise improves with increasing size of the spin ensemble. We also show how the paired nuclear spin state allows for enhanced sensing capabilities of NV centers in diamond.

  20. An Adaptive Approach to Mitigate Background Covariance Limitations in the Ensemble Kalman Filter

    KAUST Repository

    Song, Hajoon

    2010-07-01

    A new approach is proposed to address the background covariance limitations arising from undersampled ensembles and unaccounted model errors in the ensemble Kalman filter (EnKF). The method enhances the representativeness of the EnKF ensemble by augmenting it with new members chosen adaptively to add missing information that prevents the EnKF from fully fitting the data to the ensemble. The vectors to be added are obtained by back projecting the residuals of the observation misfits from the EnKF analysis step onto the state space. The back projection is done using an optimal interpolation (OI) scheme based on an estimated covariance of the subspace missing from the ensemble. In the experiments reported here, the OI uses a preselected stationary background covariance matrix, as in the hybrid EnKF–three-dimensional variational data assimilation (3DVAR) approach, but the resulting correction is included as a new ensemble member instead of being added to all existing ensemble members. The adaptive approach is tested with the Lorenz-96 model. The hybrid EnKF–3DVAR is used as a benchmark to evaluate the performance of the adaptive approach. Assimilation experiments suggest that the new adaptive scheme significantly improves the EnKF behavior when it suffers from small size ensembles and neglected model errors. It was further found to be competitive with the hybrid EnKF–3DVAR approach, depending on ensemble size and data coverage.

  1. Denatured ethanol release into gasoline residuals, Part 1: Source behaviour

    Science.gov (United States)

    Freitas, Juliana G.; Barker, James F.

    2013-05-01

    With the increasing use of ethanol in fuels, it is important to evaluate its fate when released into the environment. While ethanol is less toxic than other organic compounds present in fuels, one of the concerns is the impact ethanol might have on the fate of gasoline hydrocarbons in groundwater. One possible concern is the spill of denatured ethanol (E95: ethanol containing 5% denaturants, usually hydrocarbons) in sites with pre-existing gasoline contamination. In that scenario, ethanol is expected to increase the mobility of the NAPL phase by acting as a cosolvent and decreasing interfacial tension. To evaluate the E95 behaviour and its impacts on pre-existing gasoline, a field test was performed at the CFB-Borden aquifer. Initially gasoline contamination was created releasing 200 L of E10 (gasoline with 10% ethanol) into the unsaturated zone. One year later, 184 L of E95 was released on top of the gasoline contamination. The site was monitored using soil cores, multilevel wells and one glass access tube. At the end of the test, the source zone was excavated and the compounds remaining were quantified. E95 ethanol accumulated and remained within the capillary fringe and unsaturated zone for more than 200 days, despite ~ 1 m oscillations in the water table. The gasoline mobility increased and it was redistributed in the source zone. Gasoline NAPL saturations in the soil increased two fold in the source zone. However, water table oscillations caused a separation between the NAPL and ethanol: NAPL was smeared and remained in deeper positions while ethanol moved upwards following the water table rise. Similarly, the E95 denaturants that initially were within the ethanol-rich phase became separated from ethanol after the water table oscillation, remaining below the ethanol rich zone. The separation between ethanol and hydrocarbons in the source after water table oscillation indicates that ethanol's impact on hydrocarbon residuals is likely limited to early times.

  2. Thermal, chemical and pH induced denaturation of a multimeric β-galactosidase reveals multiple unfolding pathways.

    Directory of Open Access Journals (Sweden)

    Devesh Kishore

    Full Text Available BACKGROUND: In this case study, we analysed the properties of unfolded states and pathways leading to complete denaturation of a multimeric chick pea β-galactosidase (CpGAL, as obtained from treatment with guanidium hydrochloride, urea, elevated temperature and extreme pH. METHODOLOGY/PRINCIPAL FINDINGS: CpGAL, a heterodimeric protein with native molecular mass of 85 kDa, belongs to α+β class of protein. The conformational stability and thermodynamic parameters of CpGAL unfolding in different states were estimated and interpreted using circular dichroism and fluorescence spectroscopic measurements. The enzyme was found to be structurally and functionally stable in the entire pH range and upto 50 °C temperature. Further increase in temperature induces unfolding followed by aggregation. Chemical induced denaturation was found to be cooperative and transitions were irreversible, non-coincidental and sigmoidal. Free energy of protein unfolding (ΔG(0 and unfolding constant (K(obs were also calculated for chemically denatured CpGAL. SIGNIFICANCE: The protein seems to use different pathways for unfolding in different environments and is a classical example of how the environment dictates the path a protein might take to fold while its amino acid sequence only defines its final three-dimensional conformation. The knowledge accumulated could be of immense biotechnological significance as well.

  3. Strategies for denaturing the weapons-grade plutonium stockpile

    Energy Technology Data Exchange (ETDEWEB)

    Buckner, M.R.; Parks, P.B.

    1992-10-01

    In the next few years, approximately 50 metric tons of weapons-grade plutonium and 150 metric tons of highly-enriched uranium (HEU) may be removed from nuclear weapons in the US and declared excess. These materials represent a significant energy resource that could substantially contribute to our national energy requirements. HEU can be used as fuel in naval reactors, or diluted with depleted uranium for use as fuel in commercial reactors. This paper proposes to use the weapons-grade plutonium as fuel in light water reactors. The first such reactor would demonstrate the dual objectives of producing electrical power and denaturing the plutonium to prevent use in nuclear weapons.

  4. RNA Denaturation: Excluded Volume, Pseudoknots, and Transition Scenarios

    Science.gov (United States)

    Baiesi, M.; Orlandini, E.; Stella, A. L.

    2003-11-01

    A lattice model of RNA denaturation which fully accounts for the excluded volume effects among nucleotides is proposed. A numerical study shows that interactions forming pseudoknots must be included in order to get a sharp continuous transition. Otherwise a smooth crossover occurs from the swollen linear polymer behavior to highly ramified, almost compact conformations with secondary structures. In the latter scenario, which is appropriate when these structures are much more stable than pseudoknot links, probability distributions for the lengths of both loops and main branches obey scaling with nonclassical exponents.

  5. DSC study of cold and heat denaturation processes of β-lactoglobulin A with guanidine hydrochloride

    Institute of Scientific and Technical Information of China (English)

    王邦宁; 谈夫

    1997-01-01

    The cold and heat denaturations of bovine β-lactoglobuhn A (β-lg A) has been studied in solutions of guanidine hydrochloride (GuHCl) by differential scanning calorimelry (DSC) The experimental results are presented and discussed.It is shown that the number of protons bound by the monomeric molecules of β-lg A was unchanged before and after its heat denaturation below pH 3,and that the activation energy of the heat denaturation was depressed owing to the presence of GuHCl.In the solutions with 2.50 and 3.06 mol/L of GuHCl,both the cold and heat denat-urations of β-lg A were observed.In comparison with the heat denaturation,the activation energy of cold denaturation was far lower and the number of GuHCl molecules bound by the unfolded polypeptide chains after cold denaturation increased a lot.The absolute value of the enthalpy of cold denaturation was larger than that of heat denaturation It was found by the analysis that the contribution to the total denaturational enthalpy of conformational change i

  6. The regulatory subunit of PKA-I remains partially structured and undergoes β-aggregation upon thermal denaturation.

    Directory of Open Access Journals (Sweden)

    Khanh K Dao

    Full Text Available BACKGROUND: The regulatory subunit (R of cAMP-dependent protein kinase (PKA is a modular flexible protein that responds with large conformational changes to the binding of the effector cAMP. Considering its highly dynamic nature, the protein is rather stable. We studied the thermal denaturation of full-length RIα and a truncated RIα(92-381 that contains the tandem cyclic nucleotide binding (CNB domains A and B. METHODOLOGY/PRINCIPAL FINDINGS: As revealed by circular dichroism (CD and differential scanning calorimetry, both RIα proteins contain significant residual structure in the heat-denatured state. As evidenced by CD, the predominantly α-helical spectrum at 25°C with double negative peaks at 209 and 222 nm changes to a spectrum with a single negative peak at 212-216 nm, characteristic of β-structure. A similar α→β transition occurs at higher temperature in the presence of cAMP. Thioflavin T fluorescence and atomic force microscopy studies support the notion that the structural transition is associated with cross-β-intermolecular aggregation and formation of non-fibrillar oligomers. CONCLUSIONS/SIGNIFICANCE: Thermal denaturation of RIα leads to partial loss of native packing with exposure of aggregation-prone motifs, such as the B' helices in the phosphate-binding cassettes of both CNB domains. The topology of the β-sandwiches in these domains favors inter-molecular β-aggregation, which is suppressed in the ligand-bound states of RIα under physiological conditions. Moreover, our results reveal that the CNB domains persist as structural cores through heat-denaturation.

  7. Cluster Ensemble-based Image Segmentation

    Directory of Open Access Journals (Sweden)

    Xiaoru Wang

    2013-07-01

    Full Text Available Image segmentation is the foundation of computer vision applications. In this paper, we propose a new\tcluster ensemble-based image\tsegmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories of images. Second, we exploit the PageRank idea from Internet applications and apply it to the image segmentation task. This can improve the final segmentation results by combining the spatial information of the image and the semantic similarity of regions. Our experiments on four public image databases validate the superiority of our algorithm over conventional single type of feature or multiple types of features-based algorithms, since our algorithm can fuse multiple types of features effectively for better segmentation results. Moreover, our method is also proved to be very competitive in comparison with other state-of-the-art segmentation algorithms.

  8. Deterministic Mean-Field Ensemble Kalman Filtering

    KAUST Repository

    Law, Kody J. H.

    2016-05-03

    The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland, Monbet, and Tran [Large sample asymptotics for the ensemble Kalman filter, in The Oxford Handbook of Nonlinear Filtering, Oxford University Press, Oxford, UK, 2011, pp. 598--631] is extended to non-Gaussian state-space models. A density-based deterministic approximation of the mean-field limit EnKF (DMFEnKF) is proposed, consisting of a PDE solver and a quadrature rule. Given a certain minimal order of convergence k between the two, this extends to the deterministic filter approximation, which is therefore asymptotically superior to standard EnKF for dimension d<2k. The fidelity of approximation of the true distribution is also established using an extension of the total variation metric to random measures. This is limited by a Gaussian bias term arising from nonlinearity/non-Gaussianity of the model, which arises in both deterministic and standard EnKF. Numerical results support and extend the theory.

  9. Symanzik flow on HISQ ensembles

    CERN Document Server

    Bazavov, A; Brown, N; DeTar, C; Foley, J; Gottlieb, Steven; Heller, U M; Hetrick, J E; Laiho, J; Levkova, L; Oktay, M; Sugar, R L; Toussaint, D; Van de Water, R S; Zhou, R

    2013-01-01

    We report on a scale determination with gradient-flow techniques on the $N_f = 2 + 1 + 1$ HISQ ensembles generated by the MILC collaboration. The lattice scale $w_0/a$, originally proposed by the BMW collaboration, is computed using Symanzik flow at four lattice spacings ranging from 0.15 to 0.06 fm. With a Taylor series ansatz, the results are simultaneously extrapolated to the continuum and interpolated to physical quark masses. We give a preliminary determination of the scale $w_0$ in physical units, along with associated systematic errors, and compare with results from other groups. We also present a first estimate of autocorrelation lengths as a function of flowtime for these ensembles.

  10. Statistical Analysis of Protein Ensembles

    Science.gov (United States)

    Máté, Gabriell; Heermann, Dieter

    2014-04-01

    As 3D protein-configuration data is piling up, there is an ever-increasing need for well-defined, mathematically rigorous analysis approaches, especially that the vast majority of the currently available methods rely heavily on heuristics. We propose an analysis framework which stems from topology, the field of mathematics which studies properties preserved under continuous deformations. First, we calculate a barcode representation of the molecules employing computational topology algorithms. Bars in this barcode represent different topological features. Molecules are compared through their barcodes by statistically determining the difference in the set of their topological features. As a proof-of-principle application, we analyze a dataset compiled of ensembles of different proteins, obtained from the Ensemble Protein Database. We demonstrate that our approach correctly detects the different protein groupings.

  11. Statistical Analysis of Protein Ensembles

    Directory of Open Access Journals (Sweden)

    Gabriell eMáté

    2014-04-01

    Full Text Available As 3D protein-configuration data is piling up, there is an ever-increasing need for well-defined, mathematically rigorous analysis approaches, especially that the vast majority of the currently available methods rely heavily on heuristics. We propose an analysis framework which stems from topology, the field of mathematics which studies properties preserved under continuous deformations. First, we calculate a barcode representation of the molecules employing computational topology algorithms. Bars in this barcode represent different topological features. Molecules are compared through their barcodes by statistically determining the difference in the set of their topological features. As a proof-of-principle application, we analyze a dataset compiled of ensembles of different proteins, obtained from the Ensemble Protein Database. We demonstrate that our approach correctly detects the different protein groupings.

  12. Calorimetric Study of Thermal Denaturation of Superoxide Dismutase

    Institute of Scientific and Technical Information of China (English)

    王邦宁; 谈夫

    1994-01-01

    The thermal denaturation of superoxide dismutase (SOD) from bovine erythrocytes was studied at various pH values of different buffers and at various concentrations of solutions of two neutral salts by differential scanning calorimetry. The experiments performed indicate that the PIPES is a buffer non-coordinating with the SOD, and that the binding of the anions studied influences more or less the thermal denaturation of SOD, but the effect on the oxidation form of SOD is more apparent. A new conformer of SOD with lower thermostability was discovered by the experiments performed in different buffers at certain pH values higher than the isoelectric point of SOD, or at higher concentrations of neutral salt solutions. The new conformer may be converted irreversibly into the usual conformer with high thermostability during heating. Based on the thermodynamic parameters obtained in distilled water and by thermodynamic analysis using the Ooi’s model, it is revealed that the large enthalpy △Hdc contributed by

  13. Denatured Thermodynamics of Proteins in Weak Cation-exchange Chromatography

    Institute of Scientific and Technical Information of China (English)

    LI Rong; CHEN Guo-Liang

    2003-01-01

    The thermostability of some proteins in weak cation-exchange chromatography was investigated at 20-80 ℃. The results show that there is a fixed thermal denaturation transition temperature for each protein. The appearance of the thermal transition temperature indicates that the conformations of the proteins are destroyed seriously. The thermal behavior of the proteins in weak cation-exchange and hydrophobic interaction chromatographies were compared in a wide temperature range. It was found that the proteins have a higher thermostability in a weak cation-exchange chromatography system. The thermodynamic parameters(ΔH0, ΔS0) of those proteins were determined by means of Vant Hoff relationship(lnk-1/T). According to standard entropy change(ΔS0), the conformational change of the proteins was judged in the chromatographic process. The linear relationships between ΔH0 and ΔS0 can be used to evaluate "compensation temperature"(β) at the protein denaturation and identify the identity of the protein retention mechanism in weak cation-exchange chromatography.

  14. Optical real-time measurement of collagen denaturation

    Science.gov (United States)

    Sankaran, Vanitha; Walsh, Joseph T., Jr.

    1997-06-01

    Linear birefringence is a property of collagenous tissue that results from both its composition and structure. Previous investigations have shown that birefringence provides an indication of structural changes in collagen during slow heating. We now report the birefringent response of both mature and young rat tail tendon to laser-heating. The results indicate that denaturation of collagen from mature rats induced by a 200-microsecond(s) -long Ho:YAG laser pulse may not be described accurately by kinetic parameters. Several second-long pulses of CO2 laser pulse may not be described from young rats fit an Arrhenius model with Ea equals 12.1 kcal/mol and A equals e18.03 s-1. Typically, for slow-heating of collagen, Ea equals kcal/mol and A equals e120 s-1. Thus, it seems likely that the temperature and energy needed to initiate collagen denaturation is lower in young collagen, possibly due to its decreased hydroxyproline content and consequent decreased thermal stability.

  15. Second-harmonic generation investigation of collagen thermal denaturation

    Science.gov (United States)

    Chen, Wei-Liang; Sun, Yen; Lin, Sung-Jan; Jee, Shiou-Hwa; Chen, Yang-Fang; Lin, Ling-Chih; So, Peter T. C.; Dong, Chen-Yuan

    2007-02-01

    Using the technique of second-harmonic generation (SHG) microscopy we obtained large area image of type I collagen from rat tail tendon as it is heated from 40°C to 70°C for 0 to 180 minutes. The high resolution images allowed us to investigate the collagen structural change. We observed that heating the tendon below the temperature of 54°C does not produce any change in the averaged SHG intensity. At the heating temperature of 54°C and above, we find that increasing the heating temperature and time leads to decreasing SHG intensity. As the tendon is heated above 54°C, a decrease in the SHG signal occurs uniformly throughout the tendon, but the regions where the SHG signal vanishes form a tiger-tail like pattern. By comparing the relative SHG intensities in small and large areas, we found that the denaturation process responsible for forming the tiger-tail like pattern occurs at a higher rate than the global denaturation process occurring throughout the tendon. Our results show that second-harmonic generation microscopy is effective in monitoring the thermal damage to collagen and has potential applications in biomedicine.

  16. Light-mediated non-Gaussian entanglement of atomic ensembles

    Science.gov (United States)

    Pettersson, Olov; Byrnes, Tim

    2017-04-01

    We analyze a similar scheme for producing light-mediated entanglement between atomic ensembles, as first realized by Julsgaard, Kozhekin, and Polzik [Nature (London) 413, 400 (2001), 10.1038/35096524]. In the standard approach to modeling the scheme, a Holstein-Primakoff approximation is made, where the atomic ensembles are treated as bosonic modes, and is only valid for short interaction times. In this paper, we solve the time evolution without this approximation, which extends the region of validity of the interaction time. For short entangling times, we find that this produces a state with characteristics similar to those of a two-mode squeezed state, in agreement with standard predictions. For long entangling times, the state evolves into a non-Gaussian form, and the characteristics of the two-mode squeezed state start to diminish. This is attributed to more exotic types of entangled states being generated. We characterize the states by examining the Fock-state probability distributions, Husimi Q distributions, and nonlocal entanglement between the ensembles. We compare and connect several quantities obtained by using the Holstein-Primakoff approach and our exact time evolution methods.

  17. Heterogeneity of mitochondrial DNA from Saccharomyces carlsbergensis. Denaturation mapping by electron microscopy.

    DEFF Research Database (Denmark)

    Christiansen, Gunna; Christiansen, C; Bak, AL

    1975-01-01

    Electronmicroscopic observation of the denaturation pattern of 130 partially denaturated linear mitochondrial DNA molecules from Saccharomyces carlsbergensis was used to investigate the distribution of AT-rich sequences within the mitochondrial genome. The molecules were observed after heating...... denaturated sequences in the mitochondrial DNA. These sequences which presumably correspond to the very AT-rich regions, known to exist in the yeast mitochondrial DNA, were found at intervals of about 0.5 - 3 mum on the map....

  18. 27 CFR 21.92 - Denaturants listed as U.S.P. or N.F.

    Science.gov (United States)

    2010-04-01

    ....P. or N.F. 21.92 Section 21.92 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND... for Denaturants § 21.92 Denaturants listed as U.S.P. or N.F. Denaturing materials and products listed in this part as “U.S.P.” or “N.F.” shall meet the specifications set forth in the current...

  19. Efficient Kernel-Based Ensemble Gaussian Mixture Filtering

    KAUST Repository

    Liu, Bo

    2015-11-11

    We consider the Bayesian filtering problem for data assimilation following the kernel-based ensemble Gaussian-mixture filtering (EnGMF) approach introduced by Anderson and Anderson (1999). In this approach, the posterior distribution of the system state is propagated with the model using the ensemble Monte Carlo method, providing a forecast ensemble that is then used to construct a prior Gaussian-mixture (GM) based on the kernel density estimator. This results in two update steps: a Kalman filter (KF)-like update of the ensemble members and a particle filter (PF)-like update of the weights, followed by a resampling step to start a new forecast cycle. After formulating EnGMF for any observational operator, we analyze the influence of the bandwidth parameter of the kernel function on the covariance of the posterior distribution. We then focus on two aspects: i) the efficient implementation of EnGMF with (relatively) small ensembles, where we propose a new deterministic resampling strategy preserving the first two moments of the posterior GM to limit the sampling error; and ii) the analysis of the effect of the bandwidth parameter on contributions of KF and PF updates and on the weights variance. Numerical results using the Lorenz-96 model are presented to assess the behavior of EnGMF with deterministic resampling, study its sensitivity to different parameters and settings, and evaluate its performance against ensemble KFs. The proposed EnGMF approach with deterministic resampling suggests improved estimates in all tested scenarios, and is shown to require less localization and to be less sensitive to the choice of filtering parameters.

  20. Quantum leakage of collective excitations of atomic ensemble induced by spatial motion

    Institute of Scientific and Technical Information of China (English)

    LI; Yng(李勇); YI; Su(易俗); YOU; Li(尤力); SUN; Changpu(孙昌璞)

    2003-01-01

    We generalize the conception of quantum leakage for the atomic collective excitation states. By making use of the atomic coherence state approach, we study the influence of the atomic spatial motion on the symmetric collective states of 2-level atomic ensemble due to inhomogeneous coupling. In the macroscopic limit, we analyze the quantum decoherence of the collective atomic state by calculating the quantum leakage for a very large ensemble at a finite temperature. Our investigations show that the fidelity of the atomic system will not be good in the case of atom number N →∞. Therefore, quantum leakage is an inevitable problem in using the atomic ensemble as a quantum information memory. The detailed calculations shed theoretical light on quantum processing using atomic ensemble collective qubit.

  1. Ensemble modeling for aromatic production in Escherichia coli.

    Directory of Open Access Journals (Sweden)

    Matthew L Rizk

    Full Text Available Ensemble Modeling (EM is a recently developed method for metabolic modeling, particularly for utilizing the effect of enzyme tuning data on the production of a specific compound to refine the model. This approach is used here to investigate the production of aromatic products in Escherichia coli. Instead of using dynamic metabolite data to fit a model, the EM approach uses phenotypic data (effects of enzyme overexpression or knockouts on the steady state production rate to screen possible models. These data are routinely generated during strain design. An ensemble of models is constructed that all reach the same steady state and are based on the same mechanistic framework at the elementary reaction level. The behavior of the models spans the kinetics allowable by thermodynamics. Then by using existing data from the literature for the overexpression of genes coding for transketolase (Tkt, transaldolase (Tal, and phosphoenolpyruvate synthase (Pps to screen the ensemble, we arrive at a set of models that properly describes the known enzyme overexpression phenotypes. This subset of models becomes more predictive as additional data are used to refine the models. The final ensemble of models demonstrates the characteristic of the cell that Tkt is the first rate controlling step, and correctly predicts that only after Tkt is overexpressed does an increase in Pps increase the production rate of aromatics. This work demonstrates that EM is able to capture the result of enzyme overexpression on aromatic producing bacteria by successfully utilizing routinely generated enzyme tuning data to guide model learning.

  2. Electrochemical behaviour of denatured ethanol for use in direct ethanol fuel cells

    Energy Technology Data Exchange (ETDEWEB)

    Bayer, Domnik; Kintzel, Birgit; Joos, Martin; Cremers, Carsten; Tuebke, Jens [Fraunhofer-Institut fuer Chemische Technologie (ICT), Pfinztal (Germany)

    2010-07-01

    In the present study, two denaturing agents, an adjuvant to a denaturing agent and a mixture of a denaturing agend and the adjuvant were tested with regard to their fuel cell compatibility. Therefore, various electrochemical tests including cyclic voltammetry, chronoamperometry and differential electrochemical mass spectroscopy have been conducted at platinum as model catalyst in acidic and alkaline medium. In addition, the most promising denaturing agent, a mixture of tert-butyl ethyl ether (ETBE) with the adjuvant Bitrex {sup registered}, has also been tested at commercial fuel cell catalysts in both acidic and alkaline media. (orig.)

  3. Visualization of early events in acetic acid denaturation of HIV-1 protease: a molecular dynamics study.

    Directory of Open Access Journals (Sweden)

    Aditi Narendra Borkar

    Full Text Available Protein denaturation plays a crucial role in cellular processes. In this study, denaturation of HIV-1 Protease (PR was investigated by all-atom MD simulations in explicit solvent. The PR dimer and monomer were simulated separately in 9 M acetic acid (9 M AcOH solution and water to study the denaturation process of PR in acetic acid environment. Direct visualization of the denaturation dynamics that is readily available from such simulations has been presented. Our simulations in 9 M AcOH reveal that the PR denaturation begins by separation of dimer into intact monomers and it is only after this separation that the monomer units start denaturing. The denaturation of the monomers is flagged off by the loss of crucial interactions between the α-helix at C-terminal and surrounding β-strands. This causes the structure to transit from the equilibrium dynamics to random non-equilibrating dynamics. Residence time calculations indicate that denaturation occurs via direct interaction of the acetic acid molecules with certain regions of the protein in 9 M AcOH. All these observations have helped to decipher a picture of the early events in acetic acid denaturation of PR and have illustrated that the α-helix and the β-sheet at the C-terminus of a native and functional PR dimer should maintain both the stability and the function of the enzyme and thus present newer targets for blocking PR function.

  4. Data assimilation the ensemble Kalman filter

    CERN Document Server

    Evensen, Geir

    2007-01-01

    Data Assimilation comprehensively covers data assimilation and inverse methods, including both traditional state estimation and parameter estimation. This text and reference focuses on various popular data assimilation methods, such as weak and strong constraint variational methods and ensemble filters and smoothers. It is demonstrated how the different methods can be derived from a common theoretical basis, as well as how they differ and/or are related to each other, and which properties characterize them, using several examples. Rather than emphasize a particular discipline such as oceanography or meteorology, it presents the mathematical framework and derivations in a way which is common for any discipline where dynamics is merged with measurements. The mathematics level is modest, although it requires knowledge of basic spatial statistics, Bayesian statistics, and calculus of variations. Readers will also appreciate the introduction to the mathematical methods used and detailed derivations, which should b...

  5. Predicting protein dynamics from structural ensembles

    CERN Document Server

    Copperman, J

    2015-01-01

    The biological properties of proteins are uniquely determined by their structure and dynamics. A protein in solution populates a structural ensemble of metastable configurations around the global fold. From overall rotation to local fluctuations, the dynamics of proteins can cover several orders of magnitude in time scales. We propose a simulation-free coarse-grained approach which utilizes knowledge of the important metastable folded states of the protein to predict the protein dynamics. This approach is based upon the Langevin Equation for Protein Dynamics (LE4PD), a Langevin formalism in the coordinates of the protein backbone. The linear modes of this Langevin formalism organize the fluctuations of the protein, so that more extended dynamical cooperativity relates to increasing energy barriers to mode diffusion. The accuracy of the LE4PD is verified by analyzing the predicted dynamics across a set of seven different proteins for which both relaxation data and NMR solution structures are available. Using e...

  6. China’s First Modern Dance Ensemble

    Institute of Scientific and Technical Information of China (English)

    1992-01-01

    After four years’hardwork by both Chineseand foreign artiststhe Guangdong ExperimentalModern Dance Ensemble,thefirst of its kind in China,wasestablished on June 6,1992,in the Friendship Theater ofGuangzhou.Ms、Yang Meiqi,a famous Chinese folk danceeducator,was chosen as headand Mr.Willy Tsao,a famousyoung Hongkong dancer,as artisticdirector.China’s Central TV Stationreported the news.Recommended by Ms.ChiangChing,a Chinese-American dancer,Yang Meiqi went to Durham,NorthCarolina,in the United States in thesummer of 1986.to attend the Amer-ican Dance Festival.The moderndances put on during the festivalfascinated her with their universal“language,”flexible movement,cho-reography and scientific training.“Isn’t this just What China’s dance

  7. Sensitivity of small myosin II ensembles from different isoforms to mechanical load and ATP concentration

    Science.gov (United States)

    Erdmann, Thorsten; Bartelheimer, Kathrin; Schwarz, Ulrich S.

    2016-11-01

    Based on a detailed crossbridge model for individual myosin II motors, we systematically study the influence of mechanical load and adenosine triphosphate (ATP) concentration on small myosin II ensembles made from different isoforms. For skeletal and smooth muscle myosin II, which are often used in actomyosin gels that reconstitute cell contractility, fast forward movement is restricted to a small region of phase space with low mechanical load and high ATP concentration, which is also characterized by frequent ensemble detachment. At high load, these ensembles are stalled or move backwards, but forward motion can be restored by decreasing ATP concentration. In contrast, small ensembles of nonmuscle myosin II isoforms, which are found in the cytoskeleton of nonmuscle cells, are hardly affected by ATP concentration due to the slow kinetics of the bound states. For all isoforms, the thermodynamic efficiency of ensemble movement increases with decreasing ATP concentration, but this effect is weaker for the nonmuscle myosin II isoforms.

  8. Total correlations of the diagonal ensemble as a generic indicator for ergodicity breaking in quantum systems

    OpenAIRE

    Pietracaprina, Francesca; Gogolin, Christian; Goold, John

    2016-01-01

    The diagonal ensemble is the infinite time average of a quantum state following unitary dynamics. In analogy to the time average of a classical phase space dynamics, it is intimately related to the ergodic properties of the quantum system giving information on the spreading of the initial state in the eigenstates of the Hamiltonian. In this work we apply a concept from quantum information, known as total correlations, to the diagonal ensemble. Forming an upper-bound on the multipartite entang...

  9. Ensembles

    OpenAIRE

    2012-01-01

    Licence; En 1935, un groupe de mathématiciens français eut l'ambition de reconstruire tout l'édifice mathématique (sans S pour bien montrer l'unité) selon la pensée formaliste de Hilbert. Les membres fondateurs ont été Henri Cartan, Claude Chevalley, Jean Delsarte, Jean Dieudonné, André Weil auxquels se joindra René de Possel. En juillet 1935 fut donc créé, lors d'un séminaire en Auvergne le groupe 'Nicolas Bourbaki'. Le nom de cette association fait référence en fait à une anecdote qui se pa...

  10. Macrostate equivalence of two general ensembles and specific relative entropies

    Science.gov (United States)

    Mori, Takashi

    2016-08-01

    The two criteria of ensemble equivalence, i.e., macrostate equivalence and measure equivalence, are investigated for a general pair of states. Macrostate equivalence implies the two ensembles are indistinguishable by the measurement of macroscopic quantities obeying the large-deviation principle, and measure equivalence means that the specific relative entropy of these two states vanishes in the thermodynamic limit. It is shown that measure equivalence implies a macrostate equivalence for a general pair of states by deriving an inequality connecting the large-deviation rate functions to the specific relative Renyi entropies. The result is applicable to both quantum and classical systems. As applications, a sufficient condition for thermalization, the time scale of quantum dynamics of macrovariables, and the second law with strict irreversibility in a quantum quench are discussed.

  11. A sub-ensemble theory of ideal quantum measurement processes

    Science.gov (United States)

    Allahverdyan, Armen E.; Balian, Roger; Nieuwenhuizen, Theo M.

    2017-01-01

    In order to elucidate the properties currently attributed to ideal measurements, one must explain how the concept of an individual event with a well-defined outcome may emerge from quantum theory which deals with statistical ensembles, and how different runs issued from the same initial state may end up with different final states. This so-called "measurement problem" is tackled with two guidelines. On the one hand, the dynamics of the macroscopic apparatus A coupled to the tested system S is described mathematically within a standard quantum formalism, where " q-probabilities" remain devoid of interpretation. On the other hand, interpretative principles, aimed to be minimal, are introduced to account for the expected features of ideal measurements. Most of the five principles stated here, which relate the quantum formalism to physical reality, are straightforward and refer to macroscopic variables. The process can be identified with a relaxation of S + A to thermodynamic equilibrium, not only for a large ensemble E of runs but even for its sub-ensembles. The different mechanisms of quantum statistical dynamics that ensure these types of relaxation are exhibited, and the required properties of the Hamiltonian of S + A are indicated. The additional theoretical information provided by the study of sub-ensembles remove Schrödinger's quantum ambiguity of the final density operator for E which hinders its direct interpretation, and bring out a commutative behaviour of the pointer observable at the final time. The latter property supports the introduction of a last interpretative principle, needed to switch from the statistical ensembles and sub-ensembles described by quantum theory to individual experimental events. It amounts to identify some formal " q-probabilities" with ordinary frequencies, but only those which refer to the final indications of the pointer. The desired properties of ideal measurements, in particular the uniqueness of the result for each individual

  12. The Reduced Rank of Ensemble Kalman Filter to Estimate the Temperature of Non Isothermal Continue Stirred Tank Reactor

    OpenAIRE

    Erna Apriliani; Dieky Adzkiya; Arief Baihaqi

    2011-01-01

    Kalman filter is an algorithm to estimate the state variable of dynamical stochastic system. The square root ensemble Kalman filter is an modification of Kalman filter. The square root ensemble Kalman filter is proposed to keep the computational stability and reduce the computational time. In this paper we study the efficiency of the reduced rank ensemble Kalman filter. We apply this algorithm to the non isothermal continue stirred tank reactor problem. We decompose the covariance of the ense...

  13. A Global Hydrological Ensemble Forecasting System: Uncertainty Quantification and Data Assimilation

    Science.gov (United States)

    Hong, Y.; Zhang, Y.; Xue, X.; Wang, X.; Gourley, J. J.; Kirstetter, P.

    2012-12-01

    A Global Hydrological Ensemble Forecasting System (GHEFS) driven by TRMM Multi-satellite Prediction Analysis (TMPA) precipitation ensembles and Global Ensemble Forecast System (GEFS) Quantitative Precipitation Forecast (QPF) ensembles, via the Coupled Routing and Excess STorage (CREST) distributed hydrological model, provides deterministic and probabilistic (e.g. 95% confidence boundaries) simulations of streamflow. The TMPA inputs enable flood monitoring and short-term forecasts while the GEFS ensembles provide for forecasts up to a seven-day lead time. This talk will focus on a quantification of the system's uncertainty and streamflow ensemble prediction generation using the following three techniques: 1) an error model that first quantifies and then perturbs both temporal and spatial variability of the real-time, TMPA precipitation estimates by considering the version-7 research product as the reference rainfall product; 2) in forecast mode, utilization of the Ensemble Transform method to account for the uncertainty of GEFS forecasts from its initial condition errors; 3) a sequential data assimilation approach - the Ensemble Square Root Kalman Filter (EnSRF) applied to update the CREST model's internal states whenever observations (e.g. streamflow, soil moisture, and actual ET etc.) are available. The GHEFS is validated in several basins in the U.S. and other continents in terms of flood detection capability (e.g. CSI, NSCE, Peak, Timing), showing improved prognostic capability by offering more time for responding agencies and yielding unique uncertainty information about the magnitude of the forecast impacts.

  14. Analysis of mesoscale forecasts using ensemble methods

    CERN Document Server

    Gross, Markus

    2016-01-01

    Mesoscale forecasts are now routinely performed as elements of operational forecasts and their outputs do appear convincing. However, despite their realistic appearance at times the comparison to observations is less favorable. At the grid scale these forecasts often do not compare well with observations. This is partly due to the chaotic system underlying the weather. Another key problem is that it is impossible to evaluate the risk of making decisions based on these forecasts because they do not provide a measure of confidence. Ensembles provide this information in the ensemble spread and quartiles. However, running global ensembles at the meso or sub mesoscale involves substantial computational resources. National centers do run such ensembles, but the subject of this publication is a method which requires significantly less computation. The ensemble enhanced mesoscale system presented here aims not at the creation of an improved mesoscale forecast model. Also it is not to create an improved ensemble syste...

  15. Measuring social interaction in music ensembles.

    Science.gov (United States)

    Volpe, Gualtiero; D'Ausilio, Alessandro; Badino, Leonardo; Camurri, Antonio; Fadiga, Luciano

    2016-05-05

    Music ensembles are an ideal test-bed for quantitative analysis of social interaction. Music is an inherently social activity, and music ensembles offer a broad variety of scenarios which are particularly suitable for investigation. Small ensembles, such as string quartets, are deemed a significant example of self-managed teams, where all musicians contribute equally to a task. In bigger ensembles, such as orchestras, the relationship between a leader (the conductor) and a group of followers (the musicians) clearly emerges. This paper presents an overview of recent research on social interaction in music ensembles with a particular focus on (i) studies from cognitive neuroscience; and (ii) studies adopting a computational approach for carrying out automatic quantitative analysis of ensemble music performances.

  16. Gibbs Ensembles of Nonintersecting Paths

    CERN Document Server

    Borodin, Alexei

    2008-01-01

    We consider a family of determinantal random point processes on the two-dimensional lattice and prove that members of our family can be interpreted as a kind of Gibbs ensembles of nonintersecting paths. Examples include probability measures on lozenge and domino tilings of the plane, some of which are non-translation-invariant. The correlation kernels of our processes can be viewed as extensions of the discrete sine kernel, and we show that the Gibbs property is a consequence of simple linear relations satisfied by these kernels. The processes depend on infinitely many parameters, which are closely related to parametrization of totally positive Toeplitz matrices.

  17. Wind Power Prediction using Ensembles

    DEFF Research Database (Denmark)

    Giebel, Gregor; Badger, Jake; Landberg, Lars

    2005-01-01

    offshore wind farm and the whole Jutland/Funen area. The utilities used these forecasts for maintenance planning, fuel consumption estimates and over-the-weekend trading on the Leipzig power exchange. Othernotable scientific results include the better accuracy of forecasts made up from a simple...... superposition of two NWP provider (in our case, DMI and DWD), an investigation of the merits of a parameterisation of the turbulent kinetic energy within thedelivered wind speed forecasts, and the finding that a “naïve” downscaling of each of the coarse ECMWF ensemble members with higher resolution HIRLAM did...

  18. Quantum Repeaters and Atomic Ensembles

    DEFF Research Database (Denmark)

    Borregaard, Johannes

    a previous protocol, thereby enabling fast local processing, which greatly enhances the distribution rate. We then move on to describe our work on improving the stability of atomic clocks using entanglement. Entanglement can potentially push the stability of atomic clocks to the so-called Heisenberg limit......, which is the absolute upper limit of the stability allowed by the Heisenberg uncertainty relation. It has, however, been unclear whether entangled state’s enhanced sensitivity to noise would prevent reaching this limit. We have developed an adaptive measurement protocol, which circumvents this problem...... based on atomic ensembles....

  19. Heterogeneous versus Homogeneous Machine Learning Ensembles

    Directory of Open Access Journals (Sweden)

    Petrakova Aleksandra

    2015-12-01

    Full Text Available The research demonstrates efficiency of the heterogeneous model ensemble application for a cancer diagnostic procedure. Machine learning methods used for the ensemble model training are neural networks, random forest, support vector machine and offspring selection genetic algorithm. Training of models and the ensemble design is performed by means of HeuristicLab software. The data used in the research have been provided by the General Hospital of Linz, Austria.

  20. Interpreting Tree Ensembles with inTrees

    OpenAIRE

    Deng, Houtao

    2014-01-01

    Tree ensembles such as random forests and boosted trees are accurate but difficult to understand, debug and deploy. In this work, we provide the inTrees (interpretable trees) framework that extracts, measures, prunes and selects rules from a tree ensemble, and calculates frequent variable interactions. An rule-based learner, referred to as the simplified tree ensemble learner (STEL), can also be formed and used for future prediction. The inTrees framework can applied to both classification an...

  1. Irreversible denaturation of maltodextrin glucosidase studied by differential scanning calorimetry, circular dichroism, and turbidity measurements.

    Science.gov (United States)

    Goyal, Megha; Chaudhuri, Tapan K; Kuwajima, Kunihiro

    2014-01-01

    Thermal denaturation of Escherichia coli maltodextrin glucosidase was studied by differential scanning calorimetry, circular dichroism (230 nm), and UV-absorption measurements (340 nm), which were respectively used to monitor heat absorption, conformational unfolding, and the production of solution turbidity. The denaturation was irreversible, and the thermal transition recorded at scan rates of 0.5-1.5 K/min was significantly scan-rate dependent, indicating that the thermal denaturation was kinetically controlled. The absence of a protein-concentration effect on the thermal transition indicated that the denaturation was rate-limited by a mono-molecular process. From the analysis of the calorimetric thermograms, a one-step irreversible model well represented the thermal denaturation of the protein. The calorimetrically observed thermal transitions showed excellent coincidence with the turbidity transitions monitored by UV-absorption as well as with the unfolding transitions monitored by circular dichroism. The thermal denaturation of the protein was thus rate-limited by conformational unfolding, which was followed by a rapid irreversible formation of aggregates that produced the solution turbidity. It is thus important to note that the absence of the protein-concentration effect on the irreversible thermal denaturation does not necessarily means the absence of protein aggregation itself. The turbidity measurements together with differential scanning calorimetry in the irreversible thermal denaturation of the protein provided a very effective approach for understanding the mechanisms of the irreversible denaturation. The Arrhenius-equation parameters obtained from analysis of the thermal denaturation were compared with those of other proteins that have been reported to show the one-step irreversible thermal denaturation. Maltodextrin glucosidase had sufficiently high kinetic stability with a half-life of 68 days at a physiological temperature (37°C).

  2. Role of different Pd/Pt ensembles in determining CO chemisorption on Au-based bimetallic alloys: A first-principles study

    Energy Technology Data Exchange (ETDEWEB)

    Ham, Hyung Chul, E-mail: hchahm@kist.re.kr [Department of Chemical Engineering, The University of Texas at Austin, Austin, TX 78712 (United States); Fuel Cell Research Center, Korea Institute of Science and Technology, Seoul (Korea, Republic of); Manogaran, Dhivya [Department of Chemistry and Biochemistry, The University of Texas at Austin, Austin, TX 78712 (United States); Hwang, Gyeong S., E-mail: gshwang@che.utexas.edu [Department of Chemical Engineering, The University of Texas at Austin, Austin, TX 78712 (United States); Han, Jonghee; Kim, Hyoung-Juhn; Nam, Suk Woo; Lim, Tae Hoon [Fuel Cell Research Center, Korea Institute of Science and Technology, Seoul (Korea, Republic of)

    2015-03-30

    Graphical abstract: - Highlights: • Pd ensembles greatly reduce CO adsorption energy as compared to Pt ensembles. • The steeper potential energy surface of CO adsorption in Pd(1 1 1) than in Pt(1 1 1). • Switch of binding site preference in ensembles is key to determining CO adsorption. • Opposite electronic (ligand) effect in Pd and Pt ensemble. - Abstract: Using spin-polarized density functional calculations, we investigate the role of different Pd/Pt ensembles in determining CO chemisorption on Au-based bimetallic alloys through a study of the energetics, charge transfer, geometric and electronic structures of CO on various Pd/Pt ensembles (monomer/dimer/trimer/tetramer). We find that the effect of Pd ensembles on the reduction of CO chemisorption energy is much larger than the Pt ensemble case. In particular, small-sized Pd ensembles like monomer show a substantial reduction of CO chemisorption energy compared to the pure Pd (1 1 1) surface, while there are no significant size and shape effects of Pt ensembles on CO chemisorption energy. This is related to two factors: (1) the steeper potential energy surface (PES) of CO in Pd (1 1 1) than in Pt (1 1 1), indicating that the effect of switch of binding site preference on CO chemisorption energy is much larger in Pd ensembles than in Pt ensembles, and (2) down-shift of d-band in Pd ensembles/up-shift of d-band in Pt ensembles as compared to the corresponding pure Pd (1 1 1)/Pt (1 1 1) surfaces, suggesting more reduced activity of Pd ensembles toward CO adsorption than the Pt ensemble case. We also present the different bonding mechanism of CO on Pd/Pt ensembles by the analysis of orbital resolved density of state.

  3. Optical readout of the quantum collective motion of an array of atomic ensembles.

    Science.gov (United States)

    Botter, Thierry; Brooks, Daniel W C; Schreppler, Sydney; Brahms, Nathan; Stamper-Kurn, Dan M

    2013-04-12

    We create an ultracold-atom-based cavity optomechanical system in which the center-of-mass modes of motion of as many as six distinguishable atomic ensembles are prepared and optically detected near their ground states. We demonstrate that the collective motional state of one atomic ensemble can be selectively addressed while preserving neighboring ensembles near their ground states to better than 95% per excitation quantum. We also show that our system offers nanometer-scale spatial resolution of each atomic ensemble via optomechanical imaging. This technique enables the in situ parallel sensing of potential landscapes, a capability relevant to active research areas of atomic physics and force-field detection in optomechanics.

  4. Using Ensemble Streamflows for Power Marketing at Bonneville Power Administration

    Science.gov (United States)

    Barton, S. B.; Koski, P.

    2014-12-01

    Bonneville Power Administration (BPA) is a federal non-profit agency within the Pacific Northwest responsible for marketing the power generated from 31 federal hydro projects throughout the Columbia River Basin. The basin encompasses parts of five states and portions of British Columbia, Canada. BPA works with provincial entities, federal and state agencies, and tribal members to manage the water resources for a variety of purposes including flood risk management, power generation, fisheries, irrigation, recreation, and navigation. This basin is subject to significant hydrologic variability in terms of seasonal volume and runoff shape from year to year which presents new water management challenges each year. The power generation planning group at BPA includes a team of meteorologists and hydrologists responsible for preparing both short-term (up to three weeks) and mid-term (up to 18 months) weather and streamflow forecasts including ensemble streamflow data. Analysts within the mid-term planning group are responsible for running several different hydrologic models used for planning studies. These models rely on these streamflow ensembles as a primary input. The planning studies are run bi-weekly to help determine the amount of energy available, or energy inventory, for forward marketing (selling or purchasing energy up to a year in advance). These studies are run with the objective of meeting the numerous multi-purpose objectives of the basin under the various streamflow conditions within the ensemble set. In addition to ensemble streamflows, an ensemble of seasonal volume forecasts is also provided for the various water conditions in order to set numerous constraints on the system. After meeting all the various requirements of the system, a probabilistic energy inventory is calculated and used for marketing purposes.

  5. Scale-free brain ensemble modulated by phase synchronization

    Institute of Scientific and Technical Information of China (English)

    Dan WU; Chao-yi LI; Jie LIU; Jing LU; De-zhong YAO

    2014-01-01

    To listen to brain activity as a piece of music, we proposed the scale-free brainwave music (SFBM) technology, which could translate the scalp electroencephalogram (EEG) into music notes according to the power law of both EEG and music. In the current study, this methodology was further extended to a musical ensemble of two channels. First, EEG data from two selected channels are translated into musical instrument digital interface (MIDI) sequences, where the EEG parameters modulate the pitch, duration, and volume of each musical note. The phase synchronization index of the two channels is computed by a Hilbert transform. Then the two MIDI sequences are integrated into a chorus according to the phase synchronization index. The EEG with a high synchronization index is represented by more consonant musical intervals, while the low index is expressed by inconsonant musical intervals. The brain ensemble derived from real EEG segments illustrates differences in harmony and pitch distribution during the eyes-closed and eyes-open states. Furthermore, the scale-free phenomena exist in the brainwave ensemble. Therefore, the scale-free brain ensemble modulated by phase synchronization is a new attempt to express the EEG through an auditory and musical way, and it can be used for EEG monitoring and bio-feedback.

  6. Local ensemble assimilation scheme with global constraints and conservation

    Science.gov (United States)

    Barth, Alexander; Yan, Yajing; Alvera-Azcárate, Aida; Beckers, Jean-Marie

    2016-12-01

    Ensemble assimilation schemes applied in their original, global formulation respect linear conservation properties if the ensemble perturbations are set up accordingly. For realistic ocean systems, only a relatively small number of ensemble members can be calculated. A localization of the ensemble increment is therefore necessary to filter out spurious long-range correlations. The conservation of the global properties will be lost if the assimilation is performed locally, since the conservation requires a coupling between all model grid points which is removed by the localization. The distribution of ocean observations is often highly inhomogeneous. Systematic errors of the observed parts of the ocean state can lead to spurious adjustment of the non-observed parts via data assimilation and thus to a spurious increase or decrease in long-term simulations of global properties which should be conserved. In this paper, we propose a local assimilation scheme (with different variants and assumptions) which can satisfy global conservation properties. The proposed scheme can also be used for non-local observation operators. Different variants of the proposed scheme are tested in an idealized model and compared to the traditional covariance localization with an ad-hoc step enforcing conservation. It is shown that the inclusion of the conservation property reduces the total RMS error and that the presented stochastic and deterministic schemes avoiding error space rotation provide better results than the traditional covariance localization.

  7. Ensemble prediction experiments using conditional nonlinear optimal perturbation

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Two methods for initialization of ensemble forecasts are compared, namely, singular vector (SV) and conditional nonlinear optimal perturbation (CNOP). The comparison is done for forecast lengths of up to 10 days with a three-level quasi-geostrophic (QG) atmospheric model in a perfect model scenario. Ten cases are randomly selected from 1982/1983 winter to 1993/1994 winter (from December to the following February). Anomaly correlation coefficient (ACC) is adopted as a tool to measure the quality of the predicted ensembles on the Northern Hemisphere 500 hPa geopotential height. The results show that the forecast quality of ensemble samples in which the first SV is replaced by CNOP is higher than that of samples composed of only SVs in the medium range, based on the occurrence of weather re-gime transitions in Northern Hemisphere after about four days. Besides, the reliability of ensemble forecasts is evaluated by the Rank Histograms. The above conclusions confirm and extend those reached earlier by the authors, which stated that the introduction of CNOP improves the forecast skill under the condition that the analysis error belongs to a kind of fast-growing error by using a barotropic QG model.

  8. Ensemble prediction experiments using conditional nonlinear optimal perturbation

    Institute of Scientific and Technical Information of China (English)

    JIANG ZhiNa; MU Mu; WANG DongHai

    2009-01-01

    Two methods for initialization of ensemble forecasts are compared, namely, singular vector (SV) and conditional nonlinear optimal perturbation (CNOP). The comparison is done for forecast lengths of up to 10 days with a three-level quasi-geostrophic (QG) atmospheric model in a perfect model scenario. Ten cases are randomly selected from 1982/1983 winter to 1993/1994 winter (from 12 to the following February). Anomaly correlation coefficient (ACC) is adopted as a tool to measure the quality of the predicted ensembles on the Northern Hemisphere 500 hPa geopotential height. The results show that the forecast quality of ensemble samples in which the first SV is replaced by CNOP is higher than that of samples composed of only SVs in the medium range, based on the occurrence of weather re-gime transitions in Northern Hemisphere after about four days. Besides, the reliability of ensemble forecasts is evaluated by the Rank Histograms. The above conclusions confirm .and extend those reached earlier by the authors, which stated that the introduction of CNOP improves the forecast skill under the condition that the analysis error belongs to a kind of fast-growing error by using a barotropic QG model.

  9. The generation of denatured reactor plutonium by different options of the fuel cycle

    Energy Technology Data Exchange (ETDEWEB)

    Broeders, C.H.M.; Kessler, G. [Inst. for Neutron Physics and Reactor Technology, Research Center Karlsruhe (Germany)

    2006-11-15

    Denatured (proliferation resistant) reactor plutonium can be generated in a number of different fuel cycle options. First denatured reactor plutonium can be obtained if, instead of low enriched U-235 PWR fuel, re-enriched U-235/U-236 from reprocessed uranium is used (fuel type A). Also the envisaged existing 2,500 t of reactor plutonium (being generated world wide up to the year 2010), mostly stored in intermediate fuel storage facilities at present, could be converted during a transition phase into denatured reactor plutonium by the options fuel type B and D. Denatured reactor plutonium could have the same safeguards standard as present low enriched (<20% U-235) LWR fuel. It could be incinerated by recycling once or twice in PWRs and subsequently by multi-recycling in FRs (CAPRA type or IFRs). Once denatured, such reactor plutonium could remain denatured during multiple recycling. In a PWR, e.g., denatured reactor plutonium could be destroyed at a rate of about 250 kg/GWey. While denatured reactor plutonium could be recycled and incinerated under relieved IAEA safeguards, neptunium would still have to be monitored by the IAEA in future for all cases in which considerable amounts of neptunium are produced. (orig.)

  10. Thermal, chemical and pH induced unfolding of turmeric root lectin: modes of denaturation.

    Directory of Open Access Journals (Sweden)

    Himadri Biswas

    Full Text Available Curcuma longa rhizome lectin, of non-seed origin having antifungal, antibacterial and α-glucosidase inhibitory activities, forms a homodimer with high thermal stability as well as acid tolerance. Size exclusion chromatography and dynamic light scattering show it to be a dimer at pH 7, but it converts to a monomer near pH 2. Circular dichroism spectra and fluorescence emission maxima are virtually indistinguishable from pH 7 to 2, indicating secondary and tertiary structures remain the same in dimer and monomer within experimental error. The tryptophan environment as probed by acrylamide quenching data yielded very similar data at pH 2 and pH 7, implying very similar folding for monomer and dimer. Differential scanning calorimetry shows a transition at 350.3 K for dimer and at 327.0 K for monomer. Thermal unfolding and chemical unfolding induced by guanidinium chloride for dimer are both reversible and can be described by two-state models. The temperatures and the denaturant concentrations at which one-half of the protein molecules are unfolded, are protein concentration-dependent for dimer but protein concentration-independent for monomer. The free energy of unfolding at 298 K was found to be 5.23 Kcal mol-1 and 14.90 Kcal mol-1 for the monomer and dimer respectively. The value of change in excess heat capacity upon protein denaturation (ΔCp is 3.42 Kcal mol-1 K-1 for dimer. The small ΔCp for unfolding of CLA reflects a buried hydrophobic core in the folded dimeric protein. These unfolding experiments, temperature dependent circular dichroism and dynamic light scattering for the dimer at pH 7 indicate its higher stability than for the monomer at pH 2. This difference in stability of dimeric and monomeric forms highlights the contribution of inter-subunit interactions in the former.

  11. Aqueous Solutions of the Ionic Liquid 1-butyl-3-methylimidazolium Chloride Denature Proteins

    Energy Technology Data Exchange (ETDEWEB)

    Baker, Gary A [ORNL; Heller, William T [ORNL

    2009-01-01

    As we advance our understanding, ionic liquids (ILs) are finding ever broader scope within the chemical sciences including, most recently, pharmaceutical, enzymatic, and bioanalytical applications. With examples of enzymatic activity reported in both neat ILs and in IL/water mixtures, enzymes are frequently assumed to adopt a quasi-native conformation, even if little work has been carried out to date toward characterizing the conformation, dynamics, active-site perturbation, cooperativity of unfolding transitions, free energy of stabilization, or aggregation/oligomerization state of enzymes in the presence of an IL solvent component. In this study, human serum albumin and equine heart cytochrome c were characterized in aqueous solutions of the fully water-miscible IL 1-butyl-3-methylimidazolium chloride, [bmim]Cl, by small-angle neutron and X-ray scattering. At [bmim]Cl concentrations up to 25 vol.%, these two proteins were found to largely retain their higher-order structures whereas both proteins become highly denatured at the highest IL concentration studied here (i.e., 50 vol.% [bmim]Cl). The response of these proteins to [bmim]Cl is analogous to their behavior in the widely studied denaturants guanidine hydrochloride and urea which similarly lead to random coil conformations at excessive molar concentrations. Interestingly, human serum albumin dimerizes in response to [bmim]Cl, whereas cytochrome c remains predominantly in monomeric form. These results have important implications for enzymatic studies in aqueous IL media, as they suggest a facile pathway through which biocatalytic activity can be altered in these nascent and potentially green electrolyte systems.

  12. On truncated generalized Gibbs ensembles in the Ising field theory

    Science.gov (United States)

    Essler, F. H. L.; Mussardo, G.; Panfil, M.

    2017-01-01

    We discuss the implementation of two different truncated Generalized Gibbs Ensembles (GGE) describing the stationary state after a mass quench process in the Ising Field Theory. One truncated GGE is based on the semi-local charges of the model, the other on regularized versions of its ultra-local charges. We test the efficiency of the two different ensembles by comparing their predictions for the stationary state values of the single-particle Green’s function G(x)= of the complex fermion field \\psi (x) . We find that both truncated GGEs are able to recover G(x), but for a given number of charges the semi-local version performs better.

  13. Control of inhomogeneous atomic ensembles of hyperfine qudits

    CERN Document Server

    Mischuck, Brian E; Deutsch, Ivan H

    2011-01-01

    We study the ability to control d-dimensional quantum systems (qudits) encoded in the hyperfine spin of alkali-metal atoms through the application of radio- and microwave-frequency magnetic fields in the presence of inhomogeneities in amplitude and detuning. Such a capability is essential to the design of robust pulses that mitigate the effects of experimental uncertainty and also for application to tomographic addressing of particular members of an extended ensemble. We study the problem of preparing an arbitrary state in the Hilbert space from an initial fiducial state. We prove that inhomogeneous control of qudit ensembles is possible based on a semi-analytic protocol that synthesizes the target through a sequence of alternating rf and microwave-driven SU(2) rotations in overlapping irreducible subspaces. Several examples of robust control are studied, and the semi-analytic protocol is compared to a brute force, full numerical search. For small inhomogeneities, < 1%, both approaches achieve average fide...

  14. Ensemble Kalman filtering with residual nudging

    CERN Document Server

    Luo, Xiaodong; 10.3402/tellusa.v64i0.17130

    2012-01-01

    Covariance inflation and localization are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF) by (in effect) adjusting the sample covariances of the estimates in the state space. In this work an additional auxiliary technique, called residual nudging, is proposed to monitor and, if necessary, adjust the residual norms of state estimates in the observation space. In an EnKF with residual nudging, if the residual norm of an analysis is larger than a pre-specified value, then the analysis is replaced by a new one whose residual norm is no larger than a pre-specified value. Otherwise the analysis is considered as a reasonable estimate and no change is made. A rule for choosing the pre-specified value is suggested. Based on this rule, the corresponding new state estimates are explicitly derived in case of linear observations. Numerical experiments in the 40-dimensional Lorenz 96 model show that introducing residual nudging to an EnKF may improve its accuracy and/o...

  15. In Vitro Reassembly of Tobacco Ribulose-1,5-bisphosphate Carboxylase/ Oxygenase from Fully Denatured Subunits

    Institute of Scientific and Technical Information of China (English)

    Zhen-Hua YONG; Gen-Yun CHEN; Jiao-Nai SHI; Da-Quan XU

    2006-01-01

    It has been generally proved impossible to reassemble ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) from fully denatured subunits in vitro in higher plant, because large subunit of fully denatured Rubisco is liable to precipitate when the denaturant is removed by common methods of direct dilution and one-step dialysis. In our experiment, the problem of precipitation was resolved by an improved gradual dialysis method, which gradually decreased the concentration of denaturant. However, fully denatured Rubisco subunits still could not be reassembled into holoenzyme using gradual dialysis unless chaperonin 60was added. The restored activity of reassembled Rubisco was approximately 8% of natural enzyme. The quantity of reassembled Rubisco increased greatly when heat shock protein 70 was present in the reassembly process. ATP and Mg2+ were unnecessary for in vitro reassembly of Rubisco, and Mg2+ inhibited the reassembly process. The reassembly was weakened when ATP, Mg2+ and K+ existed together in the reassembly process.

  16. In situ observation of collagen thermal denaturation by second harmonic generation microscopy

    Science.gov (United States)

    Liao, C.-S.; Zhuo, Z.-Y.; Yu, J.-Y.; Chao, P.-H. G.; Chu, S.-W.

    2010-02-01

    Collagen denaturation is of fundamental importance for clinical treatment. Conventionally, the denaturation process is quantified by the shrinkage of collagen fibers, but the underlying molecular origin has not been fully understood. Since second harmonic generation (SHG) is related to the molecular packing of the triple helix in collagen fibers, this nonlinear signal provides an insight of molecular dynamics during thermal denaturation. With the aid of SHG microscopy, we found a new step in collagen thermal denaturation process, de-crimp. During the de-crimp step, the characteristic crimp pattern of collagen fascicles disappeared due to the breakage of interconnecting bonds between collagen fibrils, while SHG intensity remained unchanged, suggesting the intactness of the triple helical molecules. At higher temperature, shrinkage is observed with strongly reduced SHG intensity, indicating denaturation at the molecular level.

  17. Refolding of detergent-denatured lysozyme using β-cyclodextrin-assisted ion exchange chromatography.

    Science.gov (United States)

    Zhang, Li; Zhang, Qinming; Wang, Chaozhan

    2013-03-01

    Chromatography-based protein refolding is widely used. Detergent is increasingly used for protein solubilization from inclusion bodies. Therefore, it is necessary to develop a refolding method for detergent-denatured/solubilized proteins based on liquid chromatography. In the present work, sarkosyl-denatured/dithiothreitol-reduced lysozyme was used as a model, and a refolding method based on ion exchange chromatography, assisted by β-cyclodextrin, was developed for refolding detergent-denatured proteins. Many factors affecting the refolding, such as concentration of urea, concentration of β-cyclodextrin, pH and flow rate of mobile phases, were investigated to optimize the refolding conditions for sarkosyl-denatured lysozymes. The results showed that the sarkosyl-denatured lysozyme could be successfully refolded using β-cyclodextrin-assisted ion exchange chromatography.

  18. Towards Segmenting Consumer Stereo Videos: Benchmark, Baselines and Ensembles

    OpenAIRE

    Chiu, Wei-Chen; GALASSO, Fabio; Fritz, Mario

    2016-01-01

    Are we ready to segment consumer stereo videos? The amount of this data type is rapidly increasing and encompasses rich information of appearance, motion and depth cues. However, the segmentation of such data is still largely unexplored. First, we propose therefore a new benchmark: videos, annotations and metrics to measure progress on this emerging challenge. Second, we evaluate several state of the art segmentation methods and propose a novel ensemble method based on recent spectral theory....

  19. Stochastic ensembles, conformationally adaptive teamwork, and enzymatic detoxification.

    Science.gov (United States)

    Atkins, William M; Qian, Hong

    2011-05-17

    It has been appreciated for a long time that enzymes exist as conformational ensembles throughout multiple stages of the reactions they catalyze, but there is renewed interest in the functional implications. The energy landscape that results from conformationlly diverse poteins is a complex surface with an energetic topography in multiple dimensions, even at the transition state(s) leading to product formation, and this represents a new paradigm. At the same time there has been renewed interest in conformational ensembles, a new paradigm concerning enzyme function has emerged, wherein catalytic promiscuity has clear biological advantages in some cases. "Useful", or biologically functional, promiscuity or the related behavior of "multifunctionality" can be found in the immune system, enzymatic detoxification, signal transduction, and the evolution of new function from an existing pool of folded protein scaffolds. Experimental evidence supports the widely held assumption that conformational heterogeneity promotes functional promiscuity. The common link between these coevolving paradigms is the inherent structural plasticity and conformational dynamics of proteins that, on one hand, lead to complex but evolutionarily selected energy landscapes and, on the other hand, promote functional promiscuity. Here we consider a logical extension of the overlap between these two nascent paradigms: functionally promiscuous and multifunctional enzymes such as detoxification enzymes are expected to have an ensemble landscape with more states accessible on multiple time scales than substrate specific enzymes. Two attributes of detoxification enzymes become important in the context of conformational ensembles: these enzymes metabolize multiple substrates, often in substrate mixtures, and they can form multiple products from a single substrate. These properties, combined with complex conformational landscapes, lead to the possibility of interesting time-dependent, or emergent

  20. Improved customer choice predictions using ensemble methods

    NARCIS (Netherlands)

    M.C. van Wezel (Michiel); R. Potharst (Rob)

    2005-01-01

    textabstractIn this paper various ensemble learning methods from machine learning and statistics are considered and applied to the customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible models like decision trees and thus leads to

  1. Layered Ensemble Architecture for Time Series Forecasting.

    Science.gov (United States)

    Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin

    2016-01-01

    Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods.

  2. Ensemble models of neutrophil trafficking in severe sepsis.

    Directory of Open Access Journals (Sweden)

    Sang Ok Song

    Full Text Available A hallmark of severe sepsis is systemic inflammation which activates leukocytes and can result in their misdirection. This leads to both impaired migration to the locus of infection and increased infiltration into healthy tissues. In order to better understand the pathophysiologic mechanisms involved, we developed a coarse-grained phenomenological model of the acute inflammatory response in CLP (cecal ligation and puncture-induced sepsis in rats. This model incorporates distinct neutrophil kinetic responses to the inflammatory stimulus and the dynamic interactions between components of a compartmentalized inflammatory response. Ensembles of model parameter sets consistent with experimental observations were statistically generated using a Markov-Chain Monte Carlo sampling. Prediction uncertainty in the model states was quantified over the resulting ensemble parameter sets. Forward simulation of the parameter ensembles successfully captured experimental features and predicted that systemically activated circulating neutrophils display impaired migration to the tissue and neutrophil sequestration in the lung, consequently contributing to tissue damage and mortality. Principal component and multiple regression analyses of the parameter ensembles estimated from survivor and non-survivor cohorts provide insight into pathologic mechanisms dictating outcome in sepsis. Furthermore, the model was extended to incorporate hypothetical mechanisms by which immune modulation using extracorporeal blood purification results in improved outcome in septic rats. Simulations identified a sub-population (about 18% of the treated population that benefited from blood purification. Survivors displayed enhanced neutrophil migration to tissue and reduced sequestration of lung neutrophils, contributing to improved outcome. The model ensemble presented herein provides a platform for generating and testing hypotheses in silico, as well as motivating further experimental

  3. Ensemble Kalman filter versus ensemble smoother for assessing hydraulic conductivity via tracer test data assimilation

    Directory of Open Access Journals (Sweden)

    E. Crestani

    2013-04-01

    Full Text Available Estimating the spatial variability of hydraulic conductivity K in natural aquifers is important for predicting the transport of dissolved compounds. Especially in the nonreactive case, the plume evolution is mainly controlled by the heterogeneity of K. At the local scale, the spatial distribution of K can be inferred by combining the Lagrangian formulation of the transport with a Kalman-filter-based technique and assimilating a sequence of time-lapse concentration C measurements, which, for example, can be evaluated on site through the application of a geophysical method. The objective of this work is to compare the ensemble Kalman filter (EnKF and the ensemble smoother (ES capabilities to retrieve the hydraulic conductivity spatial distribution in a groundwater flow and transport modeling framework. The application refers to a two-dimensional synthetic aquifer in which a tracer test is simulated. Moreover, since Kalman-filter-based methods are optimal only if each of the involved variables fit to a Gaussian probability density function (pdf and since this condition may not be met by some of the flow and transport state variables, issues related to the non-Gaussianity of the variables are analyzed and different transformation of the pdfs are considered in order to evaluate their influence on the performance of the methods. The results show that the EnKF reproduces with good accuracy the hydraulic conductivity field, outperforming the ES regardless of the pdf of the concentrations.

  4. Self-consistent thermodynamics for the Tsallis statistics in the grand canonical ensemble: Nonrelativistic hadron gas

    Energy Technology Data Exchange (ETDEWEB)

    Parvan, A.S. [Joint Institute for Nuclear Research, Bogoliubov Laboratory of Theoretical Physics, Dubna (Russian Federation); Horia Hulubei National Institute of Physics and Nuclear Engineering, Department of Theoretical Physics, Bucharest (Romania); Moldova Academy of Sciences, Institute of Applied Physics, Chisinau (Moldova, Republic of)

    2015-09-15

    In the present paper, the Tsallis statistics in the grand canonical ensemble was reconsidered in a general form. The thermodynamic properties of the nonrelativistic ideal gas of hadrons in the grand canonical ensemble was studied numerically and analytically in a finite volume and the thermodynamic limit. It was proved that the Tsallis statistics in the grand canonical ensemble satisfies the requirements of the equilibrium thermodynamics in the thermodynamic limit if the thermodynamic potential is a homogeneous function of the first order with respect to the extensive variables of state of the system and the entropic variable z = 1/(q - 1) is an extensive variable of state. The equivalence of canonical, microcanonical and grand canonical ensembles for the nonrelativistic ideal gas of hadrons was demonstrated. (orig.)

  5. Desynchronization in an ensemble of globally coupled chaotic bursting neuronal oscillators by dynamic delayed feedback control

    CERN Document Server

    Che, Yanqiu; Li, Ruixue; Li, Huiyan; Han, Chunxiao; Wang, Jiang; Wei, Xile

    2014-01-01

    In this paper, we propose a dynamic delayed feedback control approach for desynchronization of chaotic-bursting synchronous activities in an ensemble of globally coupled neuronal oscillators. We demonstrate that the difference signal between an ensemble's mean field and its time delayed state, filtered and fed back to the ensemble, can suppress the self-synchronization in the ensemble. These individual units are decoupled and stabilized at the desired desynchronized states while the stimulation signal reduces to the noise level. The effectiveness of the method is illustrated by examples of two different populations of globally coupled chaotic-bursting neurons. The proposed method has potential for mild, effective and demand-controlled therapy of neurological diseases characterized by pathological synchronization.

  6. Non-Boltzmann Ensembles and Monte Carlo Simulations

    Science.gov (United States)

    Murthy, K. P. N.

    2016-10-01

    Boltzmann sampling based on Metropolis algorithm has been extensively used for simulating a canonical ensemble and for calculating macroscopic properties of a closed system at desired temperatures. An estimate of a mechanical property, like energy, of an equilibrium system, is made by averaging over a large number microstates generated by Boltzmann Monte Carlo methods. This is possible because we can assign a numerical value for energy to each microstate. However, a thermal property like entropy, is not easily accessible to these methods. The reason is simple. We can not assign a numerical value for entropy, to a microstate. Entropy is not a property associated with any single microstate. It is a collective property of all the microstates. Toward calculating entropy and other thermal properties, a non-Boltzmann Monte Carlo technique called Umbrella sampling was proposed some forty years ago. Umbrella sampling has since undergone several metamorphoses and we have now, multi-canonical Monte Carlo, entropic sampling, flat histogram methods, Wang-Landau algorithm etc. This class of methods generates non-Boltzmann ensembles which are un-physical. However, physical quantities can be calculated as follows. First un-weight a microstates of the entropic ensemble; then re-weight it to the desired physical ensemble. Carry out weighted average over the entropic ensemble to estimate physical quantities. In this talk I shall tell you of the most recent non- Boltzmann Monte Carlo method and show how to calculate free energy for a few systems. We first consider estimation of free energy as a function of energy at different temperatures to characterize phase transition in an hairpin DNA in the presence of an unzipping force. Next we consider free energy as a function of order parameter and to this end we estimate density of states g(E, M), as a function of both energy E, and order parameter M. This is carried out in two stages. We estimate g(E) in the first stage. Employing g

  7. Perception of ensemble statistics requires attention.

    Science.gov (United States)

    Jackson-Nielsen, Molly; Cohen, Michael A; Pitts, Michael A

    2017-02-01

    To overcome inherent limitations in perceptual bandwidth, many aspects of the visual world are represented as summary statistics (e.g., average size, orientation, or density of objects). Here, we investigated the relationship between summary (ensemble) statistics and visual attention. Recently, it was claimed that one ensemble statistic in particular, color diversity, can be perceived without focal attention. However, a broader debate exists over the attentional requirements of conscious perception, and it is possible that some form of attention is necessary for ensemble perception. To test this idea, we employed a modified inattentional blindness paradigm and found that multiple types of summary statistics (color and size) often go unnoticed without attention. In addition, we found attentional costs in dual-task situations, further implicating a role for attention in statistical perception. Overall, we conclude that while visual ensembles may be processed efficiently, some amount of attention is necessary for conscious perception of ensemble statistics.

  8. Popular Ensemble Methods: An Empirical Study

    CERN Document Server

    Maclin, R; 10.1613/jair.614

    2011-01-01

    An ensemble consists of a set of individually trained classifiers (such as neural networks or decision trees) whose predictions are combined when classifying novel instances. Previous research has shown that an ensemble is often more accurate than any of the single classifiers in the ensemble. Bagging (Breiman, 1996c) and Boosting (Freund and Shapire, 1996; Shapire, 1990) are two relatively new but popular methods for producing ensembles. In this paper we evaluate these methods on 23 data sets using both neural networks and decision trees as our classification algorithm. Our results clearly indicate a number of conclusions. First, while Bagging is almost always more accurate than a single classifier, it is sometimes much less accurate than Boosting. On the other hand, Boosting can create ensembles that are less accurate than a single classifier -- especially when using neural networks. Analysis indicates that the performance of the Boosting methods is dependent on the characteristics of the data set being exa...

  9. Generation of scenarios from calibrated ensemble forecasts with a dynamic ensemble copula coupling approach

    CERN Document Server

    Bouallegue, Zied Ben; Theis, Susanne E; Pinson, Pierre

    2015-01-01

    Probabilistic forecasts in the form of ensemble of scenarios are required for complex decision making processes. Ensemble forecasting systems provide such products but the spatio-temporal structures of the forecast uncertainty is lost when statistical calibration of the ensemble forecasts is applied for each lead time and location independently. Non-parametric approaches allow the reconstruction of spatio-temporal joint probability distributions at a low computational cost.For example, the ensemble copula coupling (ECC) method consists in rebuilding the multivariate aspect of the forecast from the original ensemble forecasts. Based on the assumption of error stationarity, parametric methods aim to fully describe the forecast dependence structures. In this study, the concept of ECC is combined with past data statistics in order to account for the autocorrelation of the forecast error. The new approach which preserves the dynamical development of the ensemble members is called dynamic ensemble copula coupling (...

  10. Binding of DNA by a dinitro-diester calix[4]arene: denaturation and condensation of DNA.

    Science.gov (United States)

    Ostos, F J; Lebron, J A; Moyá, M L; Deasy, M; López-Cornejo, P

    2015-03-01

    A study of a dinitro-diester calix[4]arene (5,17-(3-nitrobenzylideneamino)-11,23-di-tert-butyl-25,27-diethoxycarbonyl methyleneoxy-26,28-dihydroxycalix[4]arene) interaction with calf-thymus DNA was carried out using several techniques. The measurements were done at various molar ratios X=[calixarene]/[DNA]. Results show diverse changes in the DNA conformation depending on the X value. Thus, at low macrocycle concentrations, the calixarene binds to the polynucleotide. This interaction, mainly in groove mode, weakens the hydrogen bonds between base pairs of the helix inducing denaturation of the double strands, as well as condensation of the macromolecule, from an extended coil state to a globular state. An opposite effect is observed at X molar ratios higher than 0.07. The de-condensation of DNA happens, that is, the transition from a compact state to a more extended conformation, probably due to the stacking of calixarene molecules in the solution. Results also show the importance of making a proper choice of the system under consideration.

  11. Dissociative mechanism of F-actin thermal denaturation.

    Science.gov (United States)

    Mikhailova, V V; Kurganov, B I; Pivovarova, A V; Levitsky, D I

    2006-11-01

    We have applied differential scanning calorimetry to investigate thermal unfolding of F-actin. It has been shown that the thermal stability of F-actin strongly depends on ADP concentration. The transition temperature, T(m), increases with increasing ADP concentration up to 1 mM. The T(m) value also depends on the concentration of F-actin: it increases by almost 3 degrees C as the F-actin concentration is increased from 0.5 to 2.0 mg/ml. Similar dependence of the T(m) value on protein concentration was demonstrated for F-actin stabilized by phalloidin, whereas it was much less pronounced in the presence of AlF4(-). However, T(m) was independent of protein concentration in the case of monomeric G-actin. The results suggest that at least two reversible stages precede irreversible thermal denaturation of F-actin; one of them is dissociation of ADP from actin subunits, and another is dissociation of subunits from the ends of actin filaments. The model explains why unfolding of F-actin depends on both ADP and protein concentration.

  12. Group Theory for Embedded Random Matrix Ensembles

    CERN Document Server

    Kota, V K B

    2014-01-01

    Embedded random matrix ensembles are generic models for describing statistical properties of finite isolated quantum many-particle systems. For the simplest spinless fermion (or boson) systems with say $m$ fermions (or bosons) in $N$ single particle states and interacting with say $k$-body interactions, we have EGUE($k$) [embedded GUE of $k$-body interactions) with GUE embedding and the embedding algebra is $U(N)$. In this paper, using EGUE($k$) representation for a Hamiltonian that is $k$-body and an independent EGUE($t$) representation for a transition operator that is $t$-body and employing the embedding $U(N)$ algebra, finite-$N$ formulas for moments up to order four are derived, for the first time, for the transition strength densities (transition strengths multiplied by the density of states at the initial and final energies). In the asymptotic limit, these formulas reduce to those derived for the EGOE version and establish that in general bivariate transition strength densities take bivariate Gaussian ...

  13. An integrated uncertainty and ensemble-based data assimilation approach for improved operational streamflow predictions

    Directory of Open Access Journals (Sweden)

    M. He

    2011-08-01

    Full Text Available The current study proposes an integrated uncertainty and ensemble-based data assimilation framework (ICEA and evaluates its viability in providing operational streamflow predictions via assimilating snow water equivalent (SWE data. This step-wise framework applies a parameter uncertainty analysis algorithm (ISURF to identify the uncertainty structure of sensitive model parameters, which is subsequently formulated into an Ensemble Kalman Filter (EnKF to generate updated snow states for streamflow prediction. The framework is coupled to the US National Weather Service (NWS snow and rainfall-runoff models. Its applicability is demonstrated for an operational basin of a western River Forecast Center (RFC of the NWS. Performance of the framework is evaluated against existing operational baseline (RFC predictions, the stand-alone ISURF, and the stand-alone EnKF. Results indicate that the ensemble-mean prediction of ICEA considerably outperforms predictions from the other three scenarios investigated, particularly in the context of predicting high flows (top 5th percentile. The ICEA streamflow ensemble predictions capture the variability of the observed streamflow well, however the ensemble is not wide enough to consistently contain the range of streamflow observations in the study basin. Our findings indicate that the ICEA has the potential to supplement the current operational (deterministic forecasting method in terms of providing improved single-valued (e.g., ensemble mean streamflow predictions as well as meaningful ensemble predictions.

  14. An integrated uncertainty and ensemble-based data assimilation approach for improved operational streamflow predictions

    Directory of Open Access Journals (Sweden)

    M. He

    2012-03-01

    Full Text Available The current study proposes an integrated uncertainty and ensemble-based data assimilation framework (ICEA and evaluates its viability in providing operational streamflow predictions via assimilating snow water equivalent (SWE data. This step-wise framework applies a parameter uncertainty analysis algorithm (ISURF to identify the uncertainty structure of sensitive model parameters, which is subsequently formulated into an Ensemble Kalman Filter (EnKF to generate updated snow states for streamflow prediction. The framework is coupled to the US National Weather Service (NWS snow and rainfall-runoff models. Its applicability is demonstrated for an operational basin of a western River Forecast Center (RFC of the NWS. Performance of the framework is evaluated against existing operational baseline (RFC predictions, the stand-alone ISURF and the stand-alone EnKF. Results indicate that the ensemble-mean prediction of ICEA considerably outperforms predictions from the other three scenarios investigated, particularly in the context of predicting high flows (top 5th percentile. The ICEA streamflow ensemble predictions capture the variability of the observed streamflow well, however the ensemble is not wide enough to consistently contain the range of streamflow observations in the study basin. Our findings indicate that the ICEA has the potential to supplement the current operational (deterministic forecasting method in terms of providing improved single-valued (e.g., ensemble mean streamflow predictions as well as meaningful ensemble predictions.

  15. Nonisothermal denaturation kinetics of human hair and the effects of oxidation.

    Science.gov (United States)

    Wortmann, F-J; Popescu, C; Sendelbach, G

    2006-12-15

    Human hair as alpha-keratin fiber exhibits a complex morphology, which for the context of this investigation is considered as a filament/matrix-composite, comprising the intermediate filaments (IF) and a variety of amorphous protein components as matrix. Differential scanning calorimetry (DSC) under aqueous conditions was used to analyze the denaturation of the alpha-helical material in the IFs and to assess the changes imparted by repeated, oxidative bleaching processes. The DSC curves were submitted to kinetic analysis by applying the Friedman method and assuming first order kinetics. It was found that the course of the denaturation process remains largely unchanged through oxidation, despite the fact that pronounced decreases of denaturation temperature as well as of enthalpy occur. In parallel, the reaction rate constant at the denaturation temperature, k(TD), increases with repeated treatments, that is with cumulative chemical modification. However, this effect is in fact small compared to the overall change of k(T) through the denaturation process. This leads to conclude that once the temperature rise in combination with the chemical change has induced a suitable drop of the viscosity of the matrix around the IFs, denaturation of the remaining helical material occurs along a pathway that is largely independent of temperature and of the pretreatment history. This emphasizes the kinetic control of the matrix over the denaturation process of the helical segments in the filament/matrix composite. Copyright 2006 Wiley Periodicals, Inc.

  16. Studies on the refolding of the reduced-denatured insulin with size exclusion chromatography

    Institute of Scientific and Technical Information of China (English)

    BAI Quan; KONG Yu; DONG Cuihua; GENG Xindu

    2005-01-01

    The refolding of the reduced-denatured insulin from bovine pancreas was investigated with the size exclusion chromatography (SEC). It was shown that the reduced-denatured insulin originally denatured with 7.0 mol·L-1 guanidine hydrochloride (GuHCl) or 8.0 mol·L-1 urea could not be refolded with a non-oxidized mobile phase. Although the oxidized and reduced glutathione (GSSG and GSH) were employed in the oxidized mobile phase, the reduced-denatured insulin still could not be renatured. However, in the presence of 2.0 mol·L-1 urea in the oxidized mobile phase employed, the reduced-denatured insulin can be refolded with SEC, and the aggregation of denatured insulin can be diminished by urea. In addition, the disulfide exchange of reduced-denatured insulin also can be accelerated with GSSG/GSH in the oxidized mobile phase. The three disulfide bridges of insulin were formed correctly and the reduced-unfolded insulin can be renatured completely. The results were further tested with reversed-phase liquid chromatography (RPLC) and hydrophobic interaction chromatography (HIC).

  17. Calculations of canonical averages from the grand canonical ensemble.

    Science.gov (United States)

    Kosov, D S; Gelin, M F; Vdovin, A I

    2008-02-01

    Grand canonical and canonical ensembles become equivalent in the thermodynamic limit, but when the system size is finite the results obtained in the two ensembles deviate from each other. In many important cases, the canonical ensemble provides an appropriate physical description but it is often much easier to perform the calculations in the corresponding grand canonical ensemble. We present a method to compute averages in the canonical ensemble based on calculations of the expectation values in the grand canonical ensemble. The number of particles, which is fixed in the canonical ensemble, is not necessarily the same as the average number of particles in the grand canonical ensemble.

  18. Force sensor based tool condition monitoring using a heterogeneous ensemble learning model.

    Science.gov (United States)

    Wang, Guofeng; Yang, Yinwei; Li, Zhimeng

    2014-11-14

    Tool condition monitoring (TCM) plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM), hidden Markov model (HMM) and radius basis function (RBF) are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR) algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability.

  19. Assessment of collagen crosslinking and denaturation for the design of regenerative scaffolds.

    Science.gov (United States)

    Madaghiele, Marta; Calò, Emanuela; Salvatore, Luca; Bonfrate, Valentina; Pedone, Deborah; Frigione, Mariaenrica; Sannino, Alessandro

    2016-01-01

    Crosslinking and denaturation were two variables that deeply affected the performance of collagen-based scaffolds designed for tissue regeneration. If crosslinking enhances the mechanical properties and the enzymatic resistance of collagen, while masking or reducing the available cell binding sites, denaturation has very opposite effects, as it impairs the mechanical and the enzymatic stability of collagen, but increases the number of exposed cell adhesive domains. The quantification of both crosslinking and denaturation was thus fundamental to the design of collagen-based scaffolds for selected applications. The aim of this work was to investigate the extents of crosslinking and denaturation of collagen-based films upon dehydrothermal (DHT) treatment, that is, one of the most commonly employed methods for zero-length crosslinking that shows the unique ability to induce partial denaturation. Swelling measurements, differential scanning calorimetry, Fourier transform infrared spectroscopy, colorimetric assays for the quantification of primary amines, and mechanical tests were performed to analyze the effect of the DHT temperature on crosslinking and denaturation. In particular, chemically effective and elastically effective crosslink densities were evaluated. Both crosslinking and denaturation were found to increase with the DHT temperature, although according to different trends. The results also showed that DHT treatments performed at temperatures up to 120°C maintained the extent of denaturation under 25%. Coupling a mild DHT treatment with further crosslinking may thus be very useful not only to modulate the crosslink density, but also to induce a limited amount of denaturation, which shows potential to partially compensate the loss of cell binding sites caused by crosslinking.

  20. Hybrid Data Assimilation without Ensemble Filtering

    Science.gov (United States)

    Todling, Ricardo; Akkraoui, Amal El

    2014-01-01

    The Global Modeling and Assimilation Office is preparing to upgrade its three-dimensional variational system to a hybrid approach in which the ensemble is generated using a square-root ensemble Kalman filter (EnKF) and the variational problem is solved using the Grid-point Statistical Interpolation system. As in most EnKF applications, we found it necessary to employ a combination of multiplicative and additive inflations, to compensate for sampling and modeling errors, respectively and, to maintain the small-member ensemble solution close to the variational solution; we also found it necessary to re-center the members of the ensemble about the variational analysis. During tuning of the filter we have found re-centering and additive inflation to play a considerably larger role than expected, particularly in a dual-resolution context when the variational analysis is ran at larger resolution than the ensemble. This led us to consider a hybrid strategy in which the members of the ensemble are generated by simply converting the variational analysis to the resolution of the ensemble and applying additive inflation, thus bypassing the EnKF. Comparisons of this, so-called, filter-free hybrid procedure with an EnKF-based hybrid procedure and a control non-hybrid, traditional, scheme show both hybrid strategies to provide equally significant improvement over the control; more interestingly, the filter-free procedure was found to give qualitatively similar results to the EnKF-based procedure.

  1. A new deterministic Ensemble Kalman Filter with one-step-ahead smoothing for storm surge forecasting

    KAUST Repository

    Raboudi, Naila

    2016-11-01

    The Ensemble Kalman Filter (EnKF) is a popular data assimilation method for state-parameter estimation. Following a sequential assimilation strategy, it breaks the problem into alternating cycles of forecast and analysis steps. In the forecast step, the dynamical model is used to integrate a stochastic sample approximating the state analysis distribution (called analysis ensemble) to obtain a forecast ensemble. In the analysis step, the forecast ensemble is updated with the incoming observation using a Kalman-like correction, which is then used for the next forecast step. In realistic large-scale applications, EnKFs are implemented with limited ensembles, and often poorly known model errors statistics, leading to a crude approximation of the forecast covariance. This strongly limits the filter performance. Recently, a new EnKF was proposed in [1] following a one-step-ahead smoothing strategy (EnKF-OSA), which involves an OSA smoothing of the state between two successive analysis. At each time step, EnKF-OSA exploits the observation twice. The incoming observation is first used to smooth the ensemble at the previous time step. The resulting smoothed ensemble is then integrated forward to compute a "pseudo forecast" ensemble, which is again updated with the same observation. The idea of constraining the state with future observations is to add more information in the estimation process in order to mitigate for the sub-optimal character of EnKF-like methods. The second EnKF-OSA "forecast" is computed from the smoothed ensemble and should therefore provide an improved background. In this work, we propose a deterministic variant of the EnKF-OSA, based on the Singular Evolutive Interpolated Ensemble Kalman (SEIK) filter. The motivation behind this is to avoid the observations perturbations of the EnKF in order to improve the scheme\\'s behavior when assimilating big data sets with small ensembles. The new SEIK-OSA scheme is implemented and its efficiency is demonstrated

  2. Relaxation rate for an ultrafast folding protein is independent of chemical denaturant concentration.

    Science.gov (United States)

    Cellmer, Troy; Henry, Eric R; Kubelka, Jan; Hofrichter, James; Eaton, William A

    2007-11-28

    The connection between free-energy surfaces and chevron plots has been investigated in a laser temperature jump kinetic study of a small ultrafast folding protein, the 35-residue subdomain from the villin headpiece. Unlike all other proteins that have been studied so far, no measurable dependence of the unfolding/refolding relaxation rate on denaturant concentration was observed over a wide range of guanidinium chloride concentration. Analysis with a simple Ising-like theoretical model shows that this denaturant-invariant relaxation rate can be explained by a large movement of the major free energy barrier, together with a denaturant- and reaction coordinate-dependent diffusion coefficient.

  3. Protein denaturation and functional properties of Lenient Steam Injection heat treated whey protein concentrate

    DEFF Research Database (Denmark)

    Dickow, Jonatan Ahrens; Kaufmann, Niels; Wiking, Lars

    2012-01-01

    Whey protein concentrate (WPC) was heat treated by use of the novel heat treatment method of Lenient Steam Injection (LSI) to elucidate new functional properties in relation to heat-induced gelation of heat treated WPC. Denaturation was measured by both DSC and FPLC, and the results of the two...... methods were highly correlated. Temperatures of up to 90 °C were applicable using LSI, whereas only 68 °C could be reached by plate heat exchange before coagulation/fouling. Denaturation of whey proteins increased with increasing heat treatment temperature up to a degree of 30–35% denaturation at 90 °C...

  4. On the Effect of Sodium Chloride and Sodium Sulfate on Cold Denaturation.

    Directory of Open Access Journals (Sweden)

    Andrea Pica

    Full Text Available Both sodium chloride and sodium sulfate are able to stabilize yeast frataxin, causing an overall increase of its thermodynamic stability curve, with a decrease in the cold denaturation temperature and an increase in the hot denaturation one. The influence of low concentrations of these two salts on yeast frataxin stability can be assessed by the application of a theoretical model based on scaled particle theory. First developed to figure out the mechanism underlying cold denaturation in water, this model is able to predict the stabilization of globular proteins provided by these two salts. The densities of the salt solutions and their temperature dependence play a fundamental role.

  5. MSEBAG: a dynamic classifier ensemble generation based on `minimum-sufficient ensemble' and bagging

    Science.gov (United States)

    Chen, Lei; Kamel, Mohamed S.

    2016-01-01

    In this paper, we propose a dynamic classifier system, MSEBAG, which is characterised by searching for the 'minimum-sufficient ensemble' and bagging at the ensemble level. It adopts an 'over-generation and selection' strategy and aims to achieve a good bias-variance trade-off. In the training phase, MSEBAG first searches for the 'minimum-sufficient ensemble', which maximises the in-sample fitness with the minimal number of base classifiers. Then, starting from the 'minimum-sufficient ensemble', a backward stepwise algorithm is employed to generate a collection of ensembles. The objective is to create a collection of ensembles with a descending fitness on the data, as well as a descending complexity in the structure. MSEBAG dynamically selects the ensembles from the collection for the decision aggregation. The extended adaptive aggregation (EAA) approach, a bagging-style algorithm performed at the ensemble level, is employed for this task. EAA searches for the competent ensembles using a score function, which takes into consideration both the in-sample fitness and the confidence of the statistical inference, and averages the decisions of the selected ensembles to label the test pattern. The experimental results show that the proposed MSEBAG outperforms the benchmarks on average.

  6. Weighted ensemble based automatic detection of exudates in fundus photographs.

    Science.gov (United States)

    Prentasic, Pavle; Loncaric, Sven

    2014-01-01

    Diabetic retinopathy (DR) is a visual complication of diabetes, which has become one of the leading causes of preventable blindness in the world. Exudate detection is an important problem in automatic screening systems for detection of diabetic retinopathy using color fundus photographs. In this paper, we present a method for detection of exudates in color fundus photographs, which combines several preprocessing and candidate extraction algorithms to increase the exudate detection accuracy. The first stage of the method consists of an ensemble of several exudate candidate extraction algorithms. In the learning phase, simulated annealing is used to determine weights for combining the results of the ensemble candidate extraction algorithms. The second stage of the method uses a machine learning-based classification for detection of exudate regions. The experimental validation was performed using the DRiDB color fundus image set. The validation has demonstrated that the proposed method achieved higher accuracy in comparison to state-of-the art methods.

  7. A model for ensemble NMR quantum computer using antiferromagnetic structure

    CERN Document Server

    Kokin, A A

    2000-01-01

    The one-dimensional homonuclear periodic array of nuclear spins I = 1/2,owing to hyperfine interaction of nuclear spins with electronic magneticmoments in antiferromagnetic structure, is considered. The neighbor nuclearspins in such array are opposite oriented and have resonant frequenciesdetermined by hyperfine interaction constant, applied magnetic field value andinteraction with the left and right nuclear neighbor spins. The resonantfrequencies difference of nuclear spins, when the neighbor spins have differentand the same states, is used to control the spin dynamics by means of selectiveresonant RF-pulses both for single nuclear spins and for ensemble of nuclearspins with the same resonant frequency. A model for the NMR quantum computer of cellular-automata type based on anone-dimensional homonuclear periodic array of spins is proposed. This model maybe generalized to a large ensemble of parallel working one-dimensional arraysand to two-dimensional and three-dimensional structures.

  8. Multiverse as an ensemble of stable and unstable Universes

    CERN Document Server

    Urbanowski, K

    2015-01-01

    Calculations performed within the Standard Model suggest that the electroweak vacuum is unstable if the mass of the Higgs particle is around 125 --- 126 GeV. Recent LHC results concerning the mass of the Higgs boson indicate that its mass is around 125.7 GeV. So it is possible that the vacuum in our Universe may be unstable. This means that it is reasonable to analyze properties of Universes with unstable vacua. We analyze properties of an ensemble of Universes with unstable vacua considered as an ensemble of unstable systems from the point of view of the quantum theory of unstable states and we try to explain why the universes with the unstable vacuum needs not decay.

  9. Loschmidt echoes in two-body random matrix ensembles

    Science.gov (United States)

    Pižorn, Iztok; Prosen, Tomaž; Seligman, Thomas H.

    2007-07-01

    Fidelity decay is studied for quantum many-body systems with a dominant independent particle Hamiltonian resulting, e.g., from a mean field theory with a weak two-body interaction. The diagonal terms of the interaction are included in the unperturbed Hamiltonian, while the off-diagonal terms constitute the perturbation that distorts the echo. We give the linear response solution for this problem in a random matrix framework. While the ensemble average shows no surprising behavior, we find that the typical ensemble member as represented by the median displays a very slow fidelity decay known as “freeze.” Numerical calculations confirm this result and show that the ground state even on average displays the freeze. This may contribute to explanation of the “unreasonable” success of mean field theories.

  10. Statistical ensembles of virialized halo matter density profiles

    CERN Document Server

    Carron, Julien

    2013-01-01

    We define and study statistical ensembles of matter density profiles describing spherically symmetric, virialized dark matter haloes of finite extent with a given mass and total gravitational potential energy. We provide an exact solution for the grand canonical partition functional, and show its equivalence to that of the microcanonical ensemble. We obtain analytically the mean profiles that correspond to an overwhelming majority of micro-states. All such profiles have an infinitely deep potential well, with the singular isothermal sphere arising in the infinite temperature limit. Systems with virial radius larger than gravitational radius exhibit a localization of a finite fraction of the energy in the very center. The universal logarithmic inner slope of unity of the NFW haloes is predicted at any mass and energy if an upper bound is set to the maximal depth of the potential well. In this case, the statistically favored mean profiles compare well to the NFW profiles. For very massive haloes the agreement b...

  11. Impact of hybrid GSI analysis using ETR ensembles

    Indian Academy of Sciences (India)

    V S Prasad; C J Johny

    2016-04-01

    Performance of a hybrid assimilation system combining 3D Var based NGFS (NCMRWF Global ForecastSystem) with ETR (Ensemble Transform with Rescaling) based Global Ensemble Forecast (GEFS) ofresolution T-190L28 is investigated. The experiment is conducted for a period of one week in June 2013and forecast skills over different spatial domains are compared with respect to mean analysis state.Rainfall forecast is verified over Indian region against combined observations of IMD and NCMRWF.Hybrid assimilation produced marginal improvements in overall forecast skill in comparison with 3DVar. Hybrid experiment made significant improvement in wind forecasts in all the regions on verificationagainst mean analysis. The verification of forecasts with radiosonde observations also show improvementin wind forecasts with the hybrid assimilation. On verification against observations, hybrid experimentshows more improvement in temperature and wind forecasts at upper levels. Both hybrid and operational3D Var failed in prediction of extreme rainfall event over Uttarakhand on 17 June, 2013.

  12. The quaternary structure of the recombinant bovine odorant-binding protein is modulated by chemical denaturants.

    Directory of Open Access Journals (Sweden)

    Olga V Stepanenko

    Full Text Available A large group of odorant-binding proteins (OBPs has attracted great scientific interest as promising building blocks in constructing optical biosensors for dangerous substances, such as toxic and explosive molecules. Native tissue-extracted bovine OBP (bOBP has a unique dimer folding pattern that involves crossing the α-helical domain in each monomer over the other monomer's β-barrel. In contrast, recombinant bOBP maintaining the high level of stability inherent to native tissue bOBP is produced in a stable native-like state with a decreased tendency for dimerization and is a mixture of monomers and dimers in a buffered solution. This work is focused on the study of the quaternary structure and the folding-unfolding processes of the recombinant bOBP in the absence and in the presence of guanidine hydrochloride (GdnHCl. Our results show that the recombinant bOBP native dimer is only formed at elevated GdnHCl concentrations (1.5 M. This process requires re-organizing the protein structure by progressing through the formation of an intermediate state. The bOBP dimerization process appears to be irreversible and it occurs before the protein unfolds. Though the observed structural changes for recombinant bOBP at pre-denaturing GdnHCl concentrations show a local character and the overall protein structure is maintained, such changes should be considered where the protein is used as a sensitive element in a biosensor system.

  13. 4DVAR by ensemble Kalman smoother

    CERN Document Server

    Mandel, Jan; Gratton, Serge

    2013-01-01

    We propose to use the ensemble Kalman smoother (EnKS) as linear least squares solver in the Gauss-Newton method for the large nonlinear least squares in incremental 4DVAR. The ensemble approach is naturally parallel over the ensemble members and no tangent or adjoint operators are needed. Further, adding a regularization term results in replacing the Gauss-Newton method, which may diverge, by^M the Levenberg-Marquardt method, which is known to be convergent. The regularization is implemented efficiently as an additional observation in the EnKS.

  14. Derivation of Mayer Series from Canonical Ensemble

    Science.gov (United States)

    Wang, Xian-Zhi

    2016-02-01

    Mayer derived the Mayer series from both the canonical ensemble and the grand canonical ensemble by use of the cluster expansion method. In 2002, we conjectured a recursion formula of the canonical partition function of a fluid (X.Z. Wang, Phys. Rev. E 66 (2002) 056102). In this paper we give a proof for this formula by developing an appropriate expansion of the integrand of the canonical partition function. We further derive the Mayer series solely from the canonical ensemble by use of this recursion formula.

  15. Sequential Ensembles Tolerant to Synthetic Aperture Radar (SAR Soil Moisture Retrieval Errors

    Directory of Open Access Journals (Sweden)

    Ju Hyoung Lee

    2016-04-01

    Full Text Available Due to complicated and undefined systematic errors in satellite observation, data assimilation integrating model states with satellite observations is more complicated than field measurements-based data assimilation at a local scale. In the case of Synthetic Aperture Radar (SAR soil moisture, the systematic errors arising from uncertainties in roughness conditions are significant and unavoidable, but current satellite bias correction methods do not resolve the problems very well. Thus, apart from the bias correction process of satellite observation, it is important to assess the inherent capability of satellite data assimilation in such sub-optimal but more realistic observational error conditions. To this end, time-evolving sequential ensembles of the Ensemble Kalman Filter (EnKF is compared with stationary ensemble of the Ensemble Optimal Interpolation (EnOI scheme that does not evolve the ensembles over time. As the sensitivity analysis demonstrated that the surface roughness is more sensitive to the SAR retrievals than measurement errors, it is a scope of this study to monitor how data assimilation alters the effects of roughness on SAR soil moisture retrievals. In results, two data assimilation schemes all provided intermediate values between SAR overestimation, and model underestimation. However, under the same SAR observational error conditions, the sequential ensembles approached a calibrated model showing the lowest Root Mean Square Error (RMSE, while the stationary ensemble converged towards the SAR observations exhibiting the highest RMSE. As compared to stationary ensembles, sequential ensembles have a better tolerance to SAR retrieval errors. Such inherent nature of EnKF suggests an operational merit as a satellite data assimilation system, due to the limitation of bias correction methods currently available.

  16. RumEnKF: running very large Ensembles Kalman Filter by forgetting what you just did.

    Science.gov (United States)

    Hut, R.; Amisigo, B. A.; Steele-Dunne, S. C.; Van De Giesen, N.

    2014-12-01

    The eWaterCycle project works towards running an operational hyper-resolution hydrological global model, assimilating incoming satellite data in real time, and making 14 day predictions of floods and droughts. A problem encountered in the eWatercycle project is that the computer memory needed to store a single ensemble member becomes so large that storing enough ensembles to run the EnKF is impossible, even when using mitigating strategies such as covariance inflation or localization. Reduction of Used Memory Ensemble Kalman Filtering (RumEnKF) is introduced as a variant on the Ensemble Kalman Filter (EnKF). RumEnKF differs from EnKF in that it does not store the entire ensemble, but rather only saves the first two moments of the ensemble distribution. In this way, the number of ensemble members that can be calculated is less dependent on available memory, and mainly on available computing power (CPU). RumEnKF is developed to make optimal use of current generation super computer architecture, where the number of available floating point operations (flops) increases more rapidly than the available memory and where inter-node communication can quickly become a bottleneck. In this presentation, two simple models are used (auto-regressive and Lorenz) to show that RumEnKF performs similar to the EnKF. Furthermore, it is also shown that increasing the ensemble size has a similar impact on the estimation error from the two algorithms In this preliminary results, RumEnKF reduces the used memory compared to the EnKF when the number of ensemble members is greater than half the number of state variables. Future research will focus on strategies to further reduce the memory burden of running non-linear data assimilation on very large models.

  17. The influence of applied heat treatments on whey protein denaturation

    Directory of Open Access Journals (Sweden)

    Fetahagić Safet

    2002-01-01

    . Distribution of nitrogen matter from milk 8%+3%DWP heat treated at 85ºC/10 min, 90ºC/10 min and 95ºC/10 min to sera samples were 9.64%, 8.66% and 8.67%, respectively. Whey protein denaturation increased with increasing of the temperature of the applied heat treatment. Denaturation was the most significant for milk sample 11%.

  18. Conformational diversity of acid-denatured cytochrome c studied by a matrix analysis of far-UV CD spectra.

    Science.gov (United States)

    Konno, T

    1998-04-01

    The singular value decomposition (SVD) analysis was applied to a large set of far-ultraviolet circular dichroism (far-UV CD) spectra (100-400 spectra) of horse heart cytochrome c (cyt c). The spectra were collected at pH 1.7-5.0 in (NH4)2SO4, sorbitol and 2,2,2-trifluoroethanol (TFE) solutions. The present purpose is to develop a rigorous matrix method applied to far-UV CD spectra to resolve in details conformational properties of proteins in the non-native (or denatured) regions. The analysis established that three basis spectral components are contained in a data set of difference spectra (referred to the spectrum of the native state) used here. By a further matrix transformation, any observed spectrum could be decomposed into fractions of the native (N), the molten-globule (MG), the highly denatured (D), and the alcohol-induced helical (H) spectral forms. This method could determine fractional transition curves of each conformer as a function of solution conditions, which gave the results consistent with denaturation curves of cyt c monitored by other spectroscopic methods. The results in sorbitol solutions, for example, suggested that the preferential hydration effect of the co-solvent stabilizes the MG conformer of cyt c. This report has found that the systematic SVD analysis of the far-UV CD spectra is a powerful tool for the conformational analysis of the non-native species of a protein when it is suitably supplemented with other experimental methods.

  19. The non-uniform early structural response of globular proteins to cold denaturing conditions: A case study with Yfh1

    Energy Technology Data Exchange (ETDEWEB)

    Chatterjee, Prathit; Bagchi, Sayan, E-mail: n.sengupta@ncl.res.in, E-mail: s.bagchi@ncl.res.in; Sengupta, Neelanjana, E-mail: n.sengupta@ncl.res.in, E-mail: s.bagchi@ncl.res.in [Physical Chemistry Division, CSIR-National Chemical Laboratory, Pune 411008 (India)

    2014-11-28

    The mechanism of cold denaturation in proteins is often incompletely understood due to limitations in accessing the denatured states at extremely low temperatures. Using atomistic molecular dynamics simulations, we have compared early (nanosecond timescale) structural and solvation properties of yeast frataxin (Yfh1) at its temperature of maximum stability, 292 K (T{sub s}), and the experimentally observed temperature of complete unfolding, 268 K (T{sub c}). Within the simulated timescales, discernible “global” level structural loss at T{sub c} is correlated with a distinct increase in surface hydration. However, the hydration and the unfolding events do not occur uniformly over the entire protein surface, but are sensitive to local structural propensity and hydrophobicity. Calculated infrared absorption spectra in the amide-I region of the whole protein show a distinct red shift at T{sub c} in comparison to T{sub s}. Domain specific calculations of IR spectra indicate that the red shift primarily arises from the beta strands. This is commensurate with a marked increase in solvent accessible surface area per residue for the beta-sheets at T{sub c}. Detailed analyses of structure and dynamics of hydration water around the hydrophobic residues of the beta-sheets show a more bulk water like behavior at T{sub c} due to preferential disruption of the hydrophobic effects around these domains. Our results indicate that in this protein, the surface exposed beta-sheet domains are more susceptible to cold denaturing conditions, in qualitative agreement with solution NMR experimental results.

  20. Nonextensivity in Magnetic Nanocluster Ensembles

    Science.gov (United States)

    Binek, Christian; Polisetty, Srinivas; He, Xi; Mukherjee, Tathagata; Rajasekeran, Rajesh; Redepenning, Jody

    2006-03-01

    We study the scaling behavior of dipolar interacting nanoparticles in 3D samples of various sizes but constant particle density. Ferromagnetic γ-Fe2O3 clusters embedded in a polystyrene matrix are fabricated by thermal decomposition of metal carbonyls. Transmission electron microscopy reveals a narrow size distribution of 12 nm clusters. They are randomly dispersed in the matrix with an average separation of 80 nm. Magnetization isotherms of these single domain particle ensembles are measured by SQUID magnetometry above the blocking temperature TB =115K where non-equilibrium effects are avoided. After demagnetization corrections which convert the applied magnetic fields into internal fields, H, a data collapse is achieved when scaling the magnetic moment, m, and H by appropriate factors. The latter are theoretically predicted functions of the number of particles and determined here numerically. Scaling of H takes into account the nonextensive (NE) behavior of dipolar interacting particles. In the case of long range interactions a scaling schema has been proposed by Tsallis and confirmed by simulations. The controversial field of NE thermodynamics requires however experimental evidence provided here.

  1. Ensemble Dynamics and Bred Vectors

    CERN Document Server

    Balci, Nusret; Restrepo, Juan M; Sell, George R

    2011-01-01

    We introduce the new concept of an EBV to assess the sensitivity of model outputs to changes in initial conditions for weather forecasting. The new algorithm, which we call the "Ensemble Bred Vector" or EBV, is based on collective dynamics in essential ways. By construction, the EBV algorithm produces one or more dominant vectors. We investigate the performance of EBV, comparing it to the BV algorithm as well as the finite-time Lyapunov Vectors. We give a theoretical justification to the observed fact that the vectors produced by BV, EBV, and the finite-time Lyapunov vectors are similar for small amplitudes. Numerical comparisons of BV and EBV for the 3-equation Lorenz model and for a forced, dissipative partial differential equation of Cahn-Hilliard type that arises in modeling the thermohaline circulation, demonstrate that the EBV yields a size-ordered description of the perturbation field, and is more robust than the BV in the higher nonlinear regime. The EBV yields insight into the fractal structure of th...

  2. Deterministically Entangling Two Remote Atomic Ensembles via Light-Atom Mixed Entanglement Swapping.

    Science.gov (United States)

    Liu, Yanhong; Yan, Zhihui; Jia, Xiaojun; Xie, Changde

    2016-05-11

    Entanglement of two distant macroscopic objects is a key element for implementing large-scale quantum networks consisting of quantum channels and quantum nodes. Entanglement swapping can entangle two spatially separated quantum systems without direct interaction. Here we propose a scheme of deterministically entangling two remote atomic ensembles via continuous-variable entanglement swapping between two independent quantum systems involving light and atoms. Each of two stationary atomic ensembles placed at two remote nodes in a quantum network is prepared to a mixed entangled state of light and atoms respectively. Then, the entanglement swapping is unconditionally implemented between the two prepared quantum systems by means of the balanced homodyne detection of light and the feedback of the measured results. Finally, the established entanglement between two macroscopic atomic ensembles is verified by the inseparability criterion of correlation variances between two anti-Stokes optical beams respectively coming from the two atomic ensembles.

  3. Particle Kalman Filtering: A Nonlinear Bayesian Framework for Ensemble Kalman Filters

    CERN Document Server

    Hoteit, Ibrahim; Pham, Dinh-Tuan

    2011-01-01

    This paper investigates an approximation scheme of the optimal nonlinear Bayesian filter based on the Gaussian mixture representation of the state probability distribution function. The resulting filter is similar to the particle filter, but is different from it in that, the standard weight-type correction in the particle filter is complemented by the Kalman-type correction with the associated covariance matrices in the Gaussian mixture. We show that this filter is an algorithm in between the Kalman filter and the particle filter, and therefore is referred to as the particle Kalman filter (PKF). In the PKF, the solution of a nonlinear filtering problem is expressed as the weighted average of an "ensemble of Kalman filters" operating in parallel. Running an ensemble of Kalman filters is, however, computationally prohibitive for realistic atmospheric and oceanic data assimilation problems. For this reason, we consider the construction of the PKF through an "ensemble" of ensemble Kalman filters (EnKFs) instead, ...

  4. Cavity quantum electrodynamics with a Rydberg-blocked atomic ensemble

    DEFF Research Database (Denmark)

    Guerlin, Christine; Brion, Etienne; Esslinger, Tilman

    2010-01-01

    The realization of a Jaynes-Cummings model in the optical domain is proposed for an atomic ensemble. The scheme exploits the collective coupling of the atoms to a quantized cavity mode and the nonlinearity introduced by coupling to high-lying Rydberg states. A two-photon transition resonantly......> and the collectively excited state |E> with a single Rydberg excitation distributed evenly on all atoms. The collectively enhanced coupling of all atoms to the cavity field with coherent coupling strengths which are much larger than the decay rates in the system leads to the strong coupling regime of the resulting...

  5. Stochastic dynamics of small ensembles of non-processive molecular motors: the parallel cluster model.

    Science.gov (United States)

    Erdmann, Thorsten; Albert, Philipp J; Schwarz, Ulrich S

    2013-11-07

    Non-processive molecular motors have to work together in ensembles in order to generate appreciable levels of force or movement. In skeletal muscle, for example, hundreds of myosin II molecules cooperate in thick filaments. In non-muscle cells, by contrast, small groups with few tens of non-muscle myosin II motors contribute to essential cellular processes such as transport, shape changes, or mechanosensing. Here we introduce a detailed and analytically tractable model for this important situation. Using a three-state crossbridge model for the myosin II motor cycle and exploiting the assumptions of fast power stroke kinetics and equal load sharing between motors in equivalent states, we reduce the stochastic reaction network to a one-step master equation for the binding and unbinding dynamics (parallel cluster model) and derive the rules for ensemble movement. We find that for constant external load, ensemble dynamics is strongly shaped by the catch bond character of myosin II, which leads to an increase of the fraction of bound motors under load and thus to firm attachment even for small ensembles. This adaptation to load results in a concave force-velocity relation described by a Hill relation. For external load provided by a linear spring, myosin II ensembles dynamically adjust themselves towards an isometric state with constant average position and load. The dynamics of the ensembles is now determined mainly by the distribution of motors over the different kinds of bound states. For increasing stiffness of the external spring, there is a sharp transition beyond which myosin II can no longer perform the power stroke. Slow unbinding from the pre-power-stroke state protects the ensembles against detachment.

  6. Stochastic dynamics of small ensembles of non-processive molecular motors: The parallel cluster model

    Science.gov (United States)

    Erdmann, Thorsten; Albert, Philipp J.; Schwarz, Ulrich S.

    2013-11-01

    Non-processive molecular motors have to work together in ensembles in order to generate appreciable levels of force or movement. In skeletal muscle, for example, hundreds of myosin II molecules cooperate in thick filaments. In non-muscle cells, by contrast, small groups with few tens of non-muscle myosin II motors contribute to essential cellular processes such as transport, shape changes, or mechanosensing. Here we introduce a detailed and analytically tractable model for this important situation. Using a three-state crossbridge model for the myosin II motor cycle and exploiting the assumptions of fast power stroke kinetics and equal load sharing between motors in equivalent states, we reduce the stochastic reaction network to a one-step master equation for the binding and unbinding dynamics (parallel cluster model) and derive the rules for ensemble movement. We find that for constant external load, ensemble dynamics is strongly shaped by the catch bond character of myosin II, which leads to an increase of the fraction of bound motors under load and thus to firm attachment even for small ensembles. This adaptation to load results in a concave force-velocity relation described by a Hill relation. For external load provided by a linear spring, myosin II ensembles dynamically adjust themselves towards an isometric state with constant average position and load. The dynamics of the ensembles is now determined mainly by the distribution of motors over the different kinds of bound states. For increasing stiffness of the external spring, there is a sharp transition beyond which myosin II can no longer perform the power stroke. Slow unbinding from the pre-power-stroke state protects the ensembles against detachment.

  7. A 4D-Ensemble-Variational System for Data Assimilation and Ensemble Initialization

    Science.gov (United States)

    Bowler, Neill; Clayton, Adam; Jardak, Mohamed; Lee, Eunjoo; Jermey, Peter; Lorenc, Andrew; Piccolo, Chiara; Pring, Stephen; Wlasak, Marek; Barker, Dale; Inverarity, Gordon; Swinbank, Richard

    2016-04-01

    The Met Office has been developing a four-dimensional ensemble variational (4DEnVar) data assimilation system over the past four years. The 4DEnVar system is intended both as data assimilation system in its own right and also an improved means of initializing the Met Office Global and Regional Ensemble Prediction System (MOGREPS). The global MOGREPS ensemble has been initialized by running an ensemble of 4DEnVars (En-4DEnVar). The scalability and maintainability of ensemble data assimilation methods make them increasingly attractive, and 4DEnVar may be adopted in the context of the Met Office's LFRic project to redevelop the technical infrastructure to enable its Unified Model (MetUM) to be run efficiently on massively parallel supercomputers. This presentation will report on the results of the 4DEnVar development project, including experiments that have been run using ensemble sizes of up to 200 members.

  8. An Ensemble-Based Smoother with Retrospectively Updated Weights for Highly Nonlinear Systems

    Science.gov (United States)

    Chin, T. M.; Turmon, M. J.; Jewell, J. B.; Ghil, M.

    2006-01-01

    Monte Carlo computational methods have been introduced into data assimilation for nonlinear systems in order to alleviate the computational burden of updating and propagating the full probability distribution. By propagating an ensemble of representative states, algorithms like the ensemble Kalman filter (EnKF) and the resampled particle filter (RPF) rely on the existing modeling infrastructure to approximate the distribution based on the evolution of this ensemble. This work presents an ensemble-based smoother that is applicable to the Monte Carlo filtering schemes like EnKF and RPF. At the minor cost of retrospectively updating a set of weights for ensemble members, this smoother has demonstrated superior capabilities in state tracking for two highly nonlinear problems: the double-well potential and trivariate Lorenz systems. The algorithm does not require retrospective adaptation of the ensemble members themselves, and it is thus suited to a streaming operational mode. The accuracy of the proposed backward-update scheme in estimating non-Gaussian distributions is evaluated by comparison to the more accurate estimates provided by a Markov chain Monte Carlo algorithm.

  9. Model error estimation in ensemble data assimilation

    Directory of Open Access Journals (Sweden)

    S. Gillijns

    2007-01-01

    Full Text Available A new methodology is proposed to estimate and account for systematic model error in linear filtering as well as in nonlinear ensemble based filtering. Our results extend the work of Dee and Todling (2000 on constant bias errors to time-varying model errors. In contrast to existing methodologies, the new filter can also deal with the case where no dynamical model for the systematic error is available. In the latter case, the applicability is limited by a matrix rank condition which has to be satisfied in order for the filter to exist. The performance of the filter developed in this paper is limited by the availability and the accuracy of observations and by the variance of the stochastic model error component. The effect of these aspects on the estimation accuracy is investigated in several numerical experiments using the Lorenz (1996 model. Experimental results indicate that the availability of a dynamical model for the systematic error significantly reduces the variance of the model error estimates, but has only minor effect on the estimates of the system state. The filter is able to estimate additive model error of any type, provided that the rank condition is satisfied and that the stochastic errors and measurement errors are significantly smaller than the systematic errors. The results of this study are encouraging. However, it remains to be seen how the filter performs in more realistic applications.

  10. General approaches in ensemble quantum computing

    Indian Academy of Sciences (India)

    V Vimalan; N Chandrakumar

    2008-01-01

    We have developed methodology for NMR quantum computing focusing on enhancing the efficiency of initialization, of logic gate implementation and of readout. Our general strategy involves the application of rotating frame pulse sequences to prepare pseudopure states and to perform logic operations. We demonstrate experimentally our methodology for both homonuclear and heteronuclear spin ensembles. On model two-spin systems, the initialization time of one of our sequences is three-fourths (in the heteronuclear case) or one-fourth (in the homonuclear case), of the typical pulsed free precession sequences, attaining the same initialization efficiency. We have implemented the logical SWAP operation in homonuclear AMX spin systems using selective isotropic mixing, reducing the duration taken to a third compared to the standard re-focused INEPT-type sequence. We introduce the 1D version for readout of the rotating frame SWAP operation, in an attempt to reduce readout time. We further demonstrate the Hadamard mode of 1D SWAP, which offers 2N-fold reduction in experiment time for a system with -working bits, attaining the same sensitivity as the standard 1D version.

  11. Denaturing gradient gel electrophoresis profiling of bacterial communities composition in Arabian Sea

    Digital Repository Service at National Institute of Oceanography (India)

    Singh, S.K.; Ramaiah, N.

    Denaturing gradient gel electrophoresis (DGGE) was used to elucidate spatial and temporal variations in bacterial community composition (BCC) from four locations along the central west coast of India. DNA extracts from 36 water samples collected...

  12. Streptokinase Recovery by Cross-Flow Microfiltration: Study of Enzyme Denaturation

    National Research Council Canada - National Science Library

    HERNANDEZ-PINZON, Inmaculada; MILLAN, Francisco; BAUTISTA, Juan

    1997-01-01

    ...% remained in the retentate. Immunological experiments using polyclonal antibodies against SK have demonstrated that SK activity loss during CFMF processes could be related to denaturation of SK, forming molecules of lower or no activity...

  13. Single molecule study of the DNA denaturation phase transition in the force-torsion space

    CERN Document Server

    Salerno, D; Mai, I; Brogioli, D; Ziano, R; Cassina, V; Mantegazza, F

    2012-01-01

    We use the "magnetic tweezers" technique to reveal the structural transitions that DNA undergoes in the force-torsion space. In particular, we focus on regions corresponding to negative supercoiling. These regions are characterized by the formation of so-called denaturation bubbles, which have an essential role in the replication and transcription of DNA. We experimentally map the region of the force-torsion space where the denaturation takes place. We observe that large fluctuations in DNA extension occur at one of the boundaries of this region, i.e., when the formation of denaturation bubbles and of plectonemes are competing. To describe the experiments, we introduce a suitable extension of the classical model. The model correctly describes the position of the denaturation regions, the transition boundaries, and the measured values of the DNA extension fluctuations.

  14. How Chain Length and Charge Affect Surfactant Denaturation of Acyl Coenzyme A Binding Protein (ACBP)

    DEFF Research Database (Denmark)

    Andersen, Kell Kleiner; Otzen, Daniel

    2009-01-01

    Using intrinsic tryptophan fluorescence, equilibria and kinetics of unfolding of acyl coenzyme A binding protein (ACBP) have been investigated in sodium alkyl sulfate surfactants of different chain length (8-16 carbon atoms) and with different proportions of the nonionic surfactant dodecyl...... maltoside (DDM). The aim has been to determine how surfactant chain length and micellar charge affect the denaturation mechanism. ACBP denatures in two steps irrespective of surfactant chain length, but with increasing chain length, the potency of the denaturant rises more rapidly than the critical micelle...... constants increases linearly with denaturant concentration below the cmc but declines at higher concentrations. Both shortening chain length and decreasing micellar charge reduce the overall kinetics of unfolding and makes the dependence of unfolding rate constants on surfactant concentration more complex...

  15. The Reduced Rank of Ensemble Kalman Filter to Estimate the Temperature of Non Isothermal Continue Stirred Tank Reactor

    Directory of Open Access Journals (Sweden)

    Erna Apriliani

    2011-01-01

    Full Text Available Kalman filter is an algorithm to estimate the state variable of dynamical stochastic system. The square root ensemble Kalman filter is an modification of Kalman filter. The square root ensemble Kalman filter is proposed to keep the computational stability and reduce the computational time. In this paper we study the efficiency of the reduced rank ensemble Kalman filter. We apply this algorithm to the non isothermal continue stirred tank reactor problem. We decompose the covariance of the ensemble estimation by using the singular value decomposition (the SVD, and then we reduced the rank of the diagonal matrix of those singular values. We make a simulation by using Matlab program. We took some the number of ensemble such as 100, 200 and 500. We compared the computational time and the accuracy between the square root ensemble Kalman filter and the ensemble Kalman filter. The reduced rank ensemble Kalman filter can’t be applied in this problem because the dimension of state variable is too less.

  16. Transition from Poisson to circular unitary ensemble

    Indian Academy of Sciences (India)

    Vinayak; Akhilesh Pandey

    2009-09-01

    Transitions to universality classes of random matrix ensembles have been useful in the study of weakly-broken symmetries in quantum chaotic systems. Transitions involving Poisson as the initial ensemble have been particularly interesting. The exact two-point correlation function was derived by one of the present authors for the Poisson to circular unitary ensemble (CUE) transition with uniform initial density. This is given in terms of a rescaled symmetry breaking parameter Λ. The same result was obtained for Poisson to Gaussian unitary ensemble (GUE) transition by Kunz and Shapiro, using the contour-integral method of Brezin and Hikami. We show that their method is applicable to Poisson to CUE transition with arbitrary initial density. Their method is also applicable to the more general ℓ CUE to CUE transition where CUE refers to the superposition of ℓ independent CUE spectra in arbitrary ratio.

  17. Ensemble treatments of thermal pairing in nuclei

    Science.gov (United States)

    Hung, Nguyen Quang; Dang, Nguyen Dinh

    2009-10-01

    A systematic comparison is conducted for pairing properties of finite systems at nonzero temperature as predicted by the exact solutions of the pairing problem embedded in three principal statistical ensembles, namely the grandcanonical ensemble, canonical ensemble and microcanonical ensemble, as well as the unprojected (FTBCS1+SCQRPA) and Lipkin-Nogami projected (FTLN1+SCQRPA) theories that include the quasiparticle number fluctuation and coupling to pair vibrations within the self-consistent quasiparticle random-phase approximation. The numerical calculations are performed for the pairing gap, total energy, heat capacity, entropy, and microcanonical temperature within the doubly-folded equidistant multilevel pairing model. The FTLN1+SCQRPA predictions are found to agree best with the exact grand-canonical results. In general, all approaches clearly show that the superfluid-normal phase transition is smoothed out in finite systems. A novel formula is suggested for extracting the empirical pairing gap in reasonable agreement with the exact canonical results.

  18. Effect of mechanical denaturation on surface free energy of protein powders

    OpenAIRE

    Mohammad, Mohammad Amin; Grimsey, Ian M.; Forbes, Robert T.; Blagbrough, Ian S; Barbara R. Conway

    2016-01-01

    Globular proteins are important both as therapeutic agents and excipients. However, their fragile native\\ud conformations can be denatured during pharmaceutical processing, which leads to modification of\\ud the surface energy of their powders and hence their performance. Lyophilized powders of hen eggwhite\\ud lysozyme and �-galactosidase from Aspergillus oryzae were used as models to study the effects\\ud of mechanical denaturation on the surface energies of basic and acidic protein powders, r...

  19. Avoiding adsorption of DNA to polypropylene tubes and denaturation of short DNA fragments

    OpenAIRE

    Gaillard, Claire; Strauss, Francois

    1998-01-01

    Two problems can arise when working with small quantities of DNA in polypropylene tubes: first, significant amounts of DNA can become lost by sticking to the tube walls; second, short DNA fragments tend to denature when binding to polypropylene. In addition, DNA also tends to denature upon dehydration. We have found that a simple way to solve these problems is by using polyallomer tubes instead of polypropylene and by avoiding certain salts, such as sodium acetate, when drying DNA.

  20. Quenching the anisotropic heisenberg chain: exact solution and generalized Gibbs ensemble predictions.

    Science.gov (United States)

    Wouters, B; De Nardis, J; Brockmann, M; Fioretto, D; Rigol, M; Caux, J-S

    2014-09-12

    We study quenches in integrable spin-1/2 chains in which we evolve the ground state of the antiferromagnetic Ising model with the anisotropic Heisenberg Hamiltonian. For this nontrivially interacting situation, an application of the first-principles-based quench-action method allows us to give an exact description of the postquench steady state in the thermodynamic limit. We show that a generalized Gibbs ensemble, implemented using all known local conserved charges, fails to reproduce the exact quench-action steady state and to correctly predict postquench equilibrium expectation values of physical observables. This is supported by numerical linked-cluster calculations within the diagonal ensemble in the thermodynamic limit.

  1. Ozone ensemble forecast with machine learning algorithms

    OpenAIRE

    Mallet, Vivien; Stoltz, Gilles; Mauricette, Boris

    2009-01-01

    International audience; We apply machine learning algorithms to perform sequential aggregation of ozone forecasts. The latter rely on a multimodel ensemble built for ozone forecasting with the modeling system Polyphemus. The ensemble simulations are obtained by changes in the physical parameterizations, the numerical schemes, and the input data to the models. The simulations are carried out for summer 2001 over western Europe in order to forecast ozone daily peaks and ozone hourly concentrati...

  2. Cluster Ensemble-based Image Segmentation

    OpenAIRE

    Xiaoru Wang; Junping Du; Shuzhe Wu; Xu Li; Fu Li

    2013-01-01

    Image segmentation is the foundation of computer vision applications. In this paper, we propose a new cluster ensemble-based image segmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories ...

  3. Calibrating ensemble reliability whilst preserving spatial structure

    Directory of Open Access Journals (Sweden)

    Jonathan Flowerdew

    2014-03-01

    Full Text Available Ensemble forecasts aim to improve decision-making by predicting a set of possible outcomes. Ideally, these would provide probabilities which are both sharp and reliable. In practice, the models, data assimilation and ensemble perturbation systems are all imperfect, leading to deficiencies in the predicted probabilities. This paper presents an ensemble post-processing scheme which directly targets local reliability, calibrating both climatology and ensemble dispersion in one coherent operation. It makes minimal assumptions about the underlying statistical distributions, aiming to extract as much information as possible from the original dynamic forecasts and support statistically awkward variables such as precipitation. The output is a set of ensemble members preserving the spatial, temporal and inter-variable structure from the raw forecasts, which should be beneficial to downstream applications such as hydrological models. The calibration is tested on three leading 15-d ensemble systems, and their aggregation into a simple multimodel ensemble. Results are presented for 12 h, 1° scale over Europe for a range of surface variables, including precipitation. The scheme is very effective at removing unreliability from the raw forecasts, whilst generally preserving or improving statistical resolution. In most cases, these benefits extend to the rarest events at each location within the 2-yr verification period. The reliability and resolution are generally equivalent or superior to those achieved using a Local Quantile-Quantile Transform, an established calibration method which generalises bias correction. The value of preserving spatial structure is demonstrated by the fact that 3×3 averages derived from grid-scale precipitation calibration perform almost as well as direct calibration at 3×3 scale, and much better than a similar test neglecting the spatial relationships. Some remaining issues are discussed regarding the finite size of the output

  4. Impacts of calibration strategies and ensemble methods on ensemble flood forecasting over Lanjiang basin, Southeast China

    Science.gov (United States)

    Liu, Li; Xu, Yue-Ping

    2017-04-01

    Ensemble flood forecasting driven by numerical weather prediction products is becoming more commonly used in operational flood forecasting applications.In this study, a hydrological ensemble flood forecasting system based on Variable Infiltration Capacity (VIC) model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated.The hydrological model is optimized by parallel programmed ɛ-NSGAII multi-objective algorithm and two respectively parameterized models are determined to simulate daily flows and peak flows coupled with a modular approach.The results indicatethat the ɛ-NSGAII algorithm permits more efficient optimization and rational determination on parameter setting.It is demonstrated that the multimodel ensemble streamflow mean have better skills than the best singlemodel ensemble mean (ECMWF) and the multimodel ensembles weighted on members and skill scores outperform other multimodel ensembles. For typical flood event, it is proved that the flood can be predicted 3-4 days in advance, but the flows in rising limb can be captured with only 1-2 days ahead due to the flash feature. With respect to peak flows selected by Peaks Over Threshold approach, the ensemble means from either singlemodel or multimodels are generally underestimated as the extreme values are smoothed out by ensemble process.

  5. Towards a GME ensemble forecasting system: Ensemble initialization using the breeding technique

    Directory of Open Access Journals (Sweden)

    Jan D. Keller

    2008-12-01

    Full Text Available The quantitative forecast of precipitation requires a probabilistic background particularly with regard to forecast lead times of more than 3 days. As only ensemble simulations can provide useful information of the underlying probability density function, we built a new ensemble forecasting system (GME-EFS based on the GME model of the German Meteorological Service (DWD. For the generation of appropriate initial ensemble perturbations we chose the breeding technique developed by Toth and Kalnay (1993, 1997, which develops perturbations by estimating the regions of largest model error induced uncertainty. This method is applied and tested in the framework of quasi-operational forecasts for a three month period in 2007. The performance of the resulting ensemble forecasts are compared to the operational ensemble prediction systems ECMWF EPS and NCEP GFS by means of ensemble spread of free atmosphere parameters (geopotential and temperature and ensemble skill of precipitation forecasting. This comparison indicates that the GME ensemble forecasting system (GME-EFS provides reasonable forecasts with spread skill score comparable to that of the NCEP GFS. An analysis with the continuous ranked probability score exhibits a lack of resolution for the GME forecasts compared to the operational ensembles. However, with significant enhancements during the 3 month test period, the first results of our work with the GME-EFS indicate possibilities for further development as well as the potential for later operational usage.

  6. Level density for deformations of the Gaussian orthogonal ensemble

    CERN Document Server

    Bertuola, A C; Hussein, M S; Pato, M P; Sargeant, A J

    2004-01-01

    Formulas are derived for the average level density of deformed, or transition, Gaussian orthogonal random matrix ensembles. After some general considerations about Gaussian ensembles we derive formulas for the average level density for (i) the transition from the Gaussian orthogonal ensemble (GOE) to the Poisson ensemble and (ii) the transition from the GOE to $m$ GOEs.

  7. Thermal denaturation behavior of collagen fibrils in wet and dry environment.

    Science.gov (United States)

    Suwa, Yosuke; Nam, Kwangwoo; Ozeki, Kazuhide; Kimura, Tsuyoshi; Kishida, Akio; Masuzawa, Toru

    2016-04-01

    We have developed a new minimally invasive technique--integrated low-level energy adhesion technique (ILEAT)--which uses heat, pressure, and low-frequency vibrations for binding living tissues. Because the adhesion mechanism of the living tissues is not fully understood, we investigated the effect of thermal energy on the collagen structure in living tissues using ILEAT. To study the effect of thermal energy and heating time on the structure of the collagen fibril, samples were divided in two categories-wet and dry. Further, atomic force microscopy was used to analyze the collagen fibril structure before and after heating. Results showed that collagen fibrils in water denatured after 1 minute at temperatures higher than 80 °C, while partial denaturation was observed at temperatures of 80 °C and a heating time of 1 min. Furthermore, complete denaturation was achieved after 90 min, suggesting that the denaturation rate is temperature and time dependent. Moreover, the collagen fibrils in dry condition maintained their native structure even after being heated to 120 °C for 90 min in the absence of water, which specifically suppressed denaturation. However, partial denaturation of collagen fibrils could not be prevented, because this determines the adhesion between the collagen molecules, and stabilizes tissue bonding.

  8. Interim assessment of the denatured /sup 233/U fuel cycle: feasibility and nonproliferation characteristics

    Energy Technology Data Exchange (ETDEWEB)

    Abbott, L.S.; Bartine, D.E.; Burns, T.J. (eds.)

    1978-12-01

    A fuel cycle that employs /sup 233/U denatured with /sup 238/U and mixed with thorium fertile material is examined with respect to its proliferation-resistance characteristics and its technical and economic feasibility. The rationale for considering the denatured /sup 233/U fuel cycle is presented, and the impact of the denatured fuel on the performance of Light-Water Reactors, Spectral-Shift-Controlled Reactors, Gas-Cooled Reactors, Heavy-Water Reactors, and Fast Breeder Reactors is discussed. The scope of the R, D and D programs to commercialize these reactors and their associated fuel cycles is also summarized and the resource requirements and economics of denatured /sup 233/U cycles are compared to those of the conventional Pu/U cycle. In addition, several nuclear power systems that employ denatured /sup 233/U fuel and are based on the energy center concept are evaluated. Under this concept, dispersed power reactors fueled with denatured or low-enriched uranium fuel are supported by secure energy centers in which sensitive activities of the nuclear cycle are performed. These activities include /sup 233/U production by Pu-fueled transmuters (thermal or fast reactors) and reprocessing. A summary chapter presents the most significant conclusions from the study and recommends areas for future work.

  9. Effect of mechanical denaturation on surface free energy of protein powders.

    Science.gov (United States)

    Mohammad, Mohammad Amin; Grimsey, Ian M; Forbes, Robert T; Blagbrough, Ian S; Conway, Barbara R

    2016-10-01

    Globular proteins are important both as therapeutic agents and excipients. However, their fragile native conformations can be denatured during pharmaceutical processing, which leads to modification of the surface energy of their powders and hence their performance. Lyophilized powders of hen egg-white lysozyme and β-galactosidase from Aspergillus oryzae were used as models to study the effects of mechanical denaturation on the surface energies of basic and acidic protein powders, respectively. Their mechanical denaturation upon milling was confirmed by the absence of their thermal unfolding transition phases and by the changes in their secondary and tertiary structures. Inverse gas chromatography detected differences between both unprocessed protein powders and the changes induced by their mechanical denaturation. The surfaces of the acidic and basic protein powders were relatively basic, however the surface acidity of β-galactosidase was higher than that of lysozyme. Also, the surface of β-galactosidase powder had a higher dispersive energy compared to lysozyme. The mechanical denaturation decreased the dispersive energy and the basicity of the surfaces of both protein powders. The amino acid composition and molecular conformation of the proteins explained the surface energy data measured by inverse gas chromatography. The biological activity of mechanically denatured protein powders can either be reversible (lysozyme) or irreversible (β-galactosidase) upon hydration. Our surface data can be exploited to understand and predict the performance of protein powders within pharmaceutical dosage forms. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Biophysical analysis of phaseolin denaturation induced by urea, guanidinium chloride, pH, and temperature.

    Science.gov (United States)

    Dyer, J M; Nelson, J W; Murai, N

    1992-06-01

    The structural stability of phaseolin was determined by using absorbance, circular dichroism (CD), fluorescence emission, and fluorescence polarization anisotropy to monitor denaturation induced by urea, guanidinium chloride (GdmCl), pH changes, increasing temperature, or a combination thereof. Initial results indicated that phaseolin remained folded to a similar extent in the presence or absence of 6.0 M urea or GdmCl at room temperature. In 6.0 M GdmCl, phaseolin denatures at approximately 65 degrees C when probed with absorbance, CD, and fluorescence polarization anisotropy. The transition occurs at lower temperatures by decreasing pH. Kinetic measurements of denaturation using CD indicated that the denaturation is slow below 55 degrees C and is associated with an activation energy of 52 kcal/mol in 6.0 M GdmCl. In addition, kinetic measurement using fluorescence emission indicated that the single tryptophan residue was sensitive to at least two steps of the denaturation process. The fluorescence emission appeared to reflect some other structural perturbation than protein denaturation, as fluorescence inflection occurred approximately 5 degrees C prior to the changes observed in absorbance, CD, and fluorescence polarization anisotropy.

  11. Calcium Binding and Disulfide Bonds Regulate the Stability of Secretagogin towards Thermal and Urea Denaturation

    Science.gov (United States)

    Weiffert, Tanja; Ní Mhurchú, Niamh; O’Connell, David; Linse, Sara

    2016-01-01

    Secretagogin is a calcium-sensor protein with six EF-hands. It is widely expressed in neurons and neuro-endocrine cells of a broad range of vertebrates including mammals, fishes and amphibia. The protein plays a role in secretion and interacts with several vesicle-associated proteins. In this work, we have studied the contribution of calcium binding and disulfide-bond formation to the stability of the secretagogin structure towards thermal and urea denaturation. SDS-PAGE analysis of secretagogin in reducing and non-reducing conditions identified a tendency of the protein to form dimers in a redox-dependent manner. The denaturation of apo and Calcium-loaded secretagogin was studied by circular dichroism and fluorescence spectroscopy under conditions favoring monomer or dimer or a 1:1 monomer: dimer ratio. This analysis reveals significantly higher stability towards urea denaturation of Calcium-loaded secretagogin compared to the apo protein. The secondary and tertiary structure of the Calcium-loaded form is not completely denatured in the presence of 10 M urea. Reduced and Calcium-loaded secretagogin is found to refold reversibly after heating to 95°C, while both oxidized and reduced apo secretagogin is irreversibly denatured at this temperature. Thus, calcium binding greatly stabilizes the structure of secretagogin towards chemical and heat denaturation. PMID:27812162

  12. Tissue sealing device associated thermal spread: a comparison of histologic methods for detecting adventitial collagen denaturation

    Science.gov (United States)

    Jones, Ryan M.; Grisez, Brian T.; Thomas, Aaron C.; Livengood, Ryan H.; Coad, James E.

    2013-02-01

    Thermal spread (thermal tissue damage) results from heat conduction through the tissues immediately adjacent to a hyperthermic tissue sealing device. The extent of such heat conduction can be assessed by the detection of adventitial collagen denaturation. Several histologic methods have been reported to measure adventitial collagen denaturation as a marker of thermal spread. This study compared hematoxylin and eosin staining, Gomori trichrome staining and loss of collagen birefringence for the detection of collagen denaturation. Twenty-eight ex vivo porcine carotid arteries were sealed with a commercially available, FDA-approved tissue sealing device. Following formalin fixation and paraffin embedding, two 5-micron tissue sections were hematoxylin and eosin and Gomori trichrome stained. The hematoxylin and eosin-stained section was evaluated by routine bright field microscopy and under polarized light. The trichromestained section was evaluated by routine bright field microscopy. Radial and midline adventitial collagen denaturation measurements were made for both the top and bottom jaw sides of each seal. The adventitial collagen denaturation lengths were determined using these three methods and statistically compared. The results showed that thermal spread, as represented by histologically detected collagen denaturation, is technique dependent. In this study, the trichrome staining method detected significantly less thermal spread than the hematoxylin and eosin staining and birefringence methods. Of the three methods, hematoxylin and eosin staining provided the most representative results for true thermal spread along the adjacent artery.

  13. Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad

    2015-12-08

    Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.

  14. Ensemble forecasting of potential habitat for three invasive fishes

    Science.gov (United States)

    Poulos, Helen M.; Chernoff, Barry; Fuller, Pam L.; Butman, David

    2012-01-01

    Aquatic invasive species pose major ecological and economic threats to aquatic ecosystems worldwide via displacement, predation, or hybridization with native species and the alteration of aquatic habitats and hydrologic cycles. Modeling the habitat suitability of alien aquatic species through spatially explicit mapping is an increasingly important risk assessment tool. Habitat modeling also facilitates identification of key environmental variables influencing invasive species distributions. We compared four modeling methods to predict the potential continental United States distributions of northern snakehead Channa argus (Cantor, 1842), round goby Neogobius melanostomus (Pallas, 1814), and silver carp Hypophthalmichthys molitrix (Valenciennes, 1844) using maximum entropy (Maxent), the genetic algorithm for rule set production (GARP), DOMAIN, and support vector machines (SVM). We used inventory records from the USGS Nonindigenous Aquatic Species Database and a geographic information system of 20 climatic and environmental variables to generate individual and ensemble distribution maps for each species. The ensemble maps from our study performed as well as or better than all of the individual models except Maxent. The ensemble and Maxent models produced significantly higher accuracy individual maps than GARP, one-class SVMs, or DOMAIN. The key environmental predictor variables in the individual models were consistent with the tolerances of each species. Results from this study provide insights into which locations and environmental conditions may promote the future spread of invasive fish in the US.

  15. Thermodynamics and kinetics of a molecular motor ensemble.

    Science.gov (United States)

    Baker, J E; Thomas, D D

    2000-10-01

    If, contrary to conventional models of muscle, it is assumed that molecular forces equilibrate among rather than within molecular motors, an equation of state and an expression for energy output can be obtained for a near-equilibrium, coworking ensemble of molecular motors. These equations predict clear, testable relationships between motor structure, motor biochemistry, and ensemble motor function, and we discuss these relationships in the context of various experimental studies. In this model, net work by molecular motors is performed with the relaxation of a near-equilibrium intermediate step in a motor-catalyzed reaction. The free energy available for work is localized to this step, and the rate at which this free energy is transferred to work is accelerated by the free energy of a motor-catalyzed reaction. This thermodynamic model implicitly deals with a motile cell system as a dynamic network (not a rigid lattice) of molecular motors within which the mechanochemistry of one motor influences and is influenced by the mechanochemistry of other motors in the ensemble.

  16. Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad

    2015-10-02

    Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.

  17. Fluctuations in a quasi-stationary shallow cumulus cloud ensemble

    Directory of Open Access Journals (Sweden)

    M. Sakradzija

    2014-08-01

    Full Text Available We propose an approach to stochastic parameterization of shallow cumulus clouds to represent the convective variability and its dependence on the model resolution. To collect the information about the individual cloud lifecycles and the cloud ensemble as a whole, we employ a Large-Eddy Simulation model (LES and a cloud tracking algorithm, followed by conditional sampling of clouds at the cloud-base level. In the case of a shallow cumulus ensemble, the cloud-base mass flux distribution is bimodal due to the different shallow cloud subtypes. Each distribution mode can be approximated with a Weibull distribution, explaining the deviation from a single-parameter exponential shape through the diversity in cloud lifecycles. The exponential distribution of cloud mass flux previously suggested for deep convection parameterization is a special case of the Weibull distribution, which opens a way towards unification of the statistical convective ensemble formalism of shallow and deep cumulus clouds. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate a shallow convective cloud ensemble. It is formulated as a compound random process, with the number of convective elements drawn from a Poisson distribution, and the cloud mass flux sampled from a mixed Weibull distribution. Convective memory is accounted for through the explicit cloud lifecycles, making the model formulation consistent with the choice of the Weibull cloud mass flux distribution function. The memory of individual shallow clouds is required to capture the correct convective variability. The resulting distribution of the subgrid convective states in the considered shallow cumulus case is scale-adaptive – the smaller the grid size, the broader the distribution.

  18. Fluctuations in a quasi-stationary shallow cumulus cloud ensemble

    Directory of Open Access Journals (Sweden)

    M. Sakradzija

    2015-01-01

    Full Text Available We propose an approach to stochastic parameterisation of shallow cumulus clouds to represent the convective variability and its dependence on the model resolution. To collect information about the individual cloud lifecycles and the cloud ensemble as a whole, we employ a large eddy simulation (LES model and a cloud tracking algorithm, followed by conditional sampling of clouds at the cloud-base level. In the case of a shallow cumulus ensemble, the cloud-base mass flux distribution is bimodal, due to the different shallow cloud subtypes, active and passive clouds. Each distribution mode can be approximated using a Weibull distribution, which is a generalisation of exponential distribution by accounting for the change in distribution shape due to the diversity of cloud lifecycles. The exponential distribution of cloud mass flux previously suggested for deep convection parameterisation is a special case of the Weibull distribution, which opens a way towards unification of the statistical convective ensemble formalism of shallow and deep cumulus clouds. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate a shallow convective cloud ensemble. It is formulated as a compound random process, with the number of convective elements drawn from a Poisson distribution, and the cloud mass flux sampled from a mixed Weibull distribution. Convective memory is accounted for through the explicit cloud lifecycles, making the model formulation consistent with the choice of the Weibull cloud mass flux distribution function. The memory of individual shallow clouds is required to capture the correct convective variability. The resulting distribution of the subgrid convective states in the considered shallow cumulus case is scale-adaptive – the smaller the grid size, the broader the distribution.

  19. Ensemble positive unlabeled learning for disease gene identification.

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    Peng Yang

    Full Text Available An increasing number of genes have been experimentally confirmed in recent years as causative genes to various human diseases. The newly available knowledge can be exploited by machine learning methods to discover additional unknown genes that are likely to be associated with diseases. In particular, positive unlabeled learning (PU learning methods, which require only a positive training set P (confirmed disease genes and an unlabeled set U (the unknown candidate genes instead of a negative training set N, have been shown to be effective in uncovering new disease genes in the current scenario. Using only a single source of data for prediction can be susceptible to bias due to incompleteness and noise in the genomic data and a single machine learning predictor prone to bias caused by inherent limitations of individual methods. In this paper, we propose an effective PU learning framework that integrates multiple biological data sources and an ensemble of powerful machine learning classifiers for disease gene identification. Our proposed method integrates data from multiple biological sources for training PU learning classifiers. A novel ensemble-based PU learning method EPU is then used to integrate multiple PU learning classifiers to achieve accurate and robust disease gene predictions. Our evaluation experiments across six disease groups showed that EPU achieved significantly better results compared with various state-of-the-art prediction methods as well as ensemble learning classifiers. Through integrating multiple biological data sources for training and the outputs of an ensemble of PU learning classifiers for prediction, we are able to minimize the potential bias and errors in individual data sources and machine learning algorithms to achieve more accurate and robust disease gene predictions. In the future, our EPU method provides an effective framework to integrate the additional biological and computational resources for better disease

  20. Disease-associated mutations that alter the RNA structural ensemble.

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    Matthew Halvorsen

    2010-08-01

    Full Text Available Genome-wide association studies (GWAS often identify disease-associated mutations in intergenic and non-coding regions of the genome. Given the high percentage of the human genome that is transcribed, we postulate that for some observed associations the disease phenotype is caused by a structural rearrangement in a regulatory region of the RNA transcript. To identify such mutations, we have performed a genome-wide analysis of all known disease-associated Single Nucleotide Polymorphisms (SNPs from the Human Gene Mutation Database (HGMD that map to the untranslated regions (UTRs of a gene. Rather than using minimum free energy approaches (e.g. mFold, we use a partition function calculation that takes into consideration the ensemble of possible RNA conformations for a given sequence. We identified in the human genome disease-associated SNPs that significantly alter the global conformation of the UTR to which they map. For six disease-states (Hyperferritinemia Cataract Syndrome, beta-Thalassemia, Cartilage-Hair Hypoplasia, Retinoblastoma, Chronic Obstructive Pulmonary Disease (COPD, and Hypertension, we identified multiple SNPs in UTRs that alter the mRNA structural ensemble of the associated genes. Using a Boltzmann sampling procedure for sub-optimal RNA structures, we are able to characterize and visualize the nature of the conformational changes induced by the disease-associated mutations in the structural ensemble. We observe in several cases (specifically the 5' UTRs of FTL and RB1 SNP-induced conformational changes analogous to those observed in bacterial regulatory Riboswitches when specific ligands bind. We propose that the UTR and SNP combinations we identify constitute a "RiboSNitch," that is a regulatory RNA in which a specific SNP has a structural consequence that results in a disease phenotype. Our SNPfold algorithm can help identify RiboSNitches by leveraging GWAS data and an analysis of the mRNA structural ensemble.