Thermal and chemical denaturation of Bacillus circulans xylanase: A biophysical chemistry laboratory module.

Science.gov (United States)

Raabe, Richard; Gentile, Lisa

2008-11-01

A number of institutions have been, or are in the process of, modifying their biochemistry major to include some emphasis on the quantitative physical chemistry of biomolecules. Sometimes this is done as a replacement for part for the entire physical chemistry requirement, while at other institutions this is incorporated as a component into the traditional two-semester biochemistry series. The latter is the model used for biochemistry and molecular biology majors at the University of Richmond, whose second semester of biochemistry is a course entitled Proteins: Structure, Function, and Biophysics. What is described herein is a protein thermodynamics laboratory module, using the protein Bacillus circulans xylanase, which reinforces many lecture concepts, including: (i) the denatured (D) state ensemble of a protein can be different, depending on how it was populated; (ii) intermediate states may be detected by some spectroscopic techniques but not by others; (iii) the use and assumptions of the van't Hoff approach to calculate ΔH(o) , ΔS(o) , and ΔG(o) (T) for thermal protein unfolding transitions; and (iv) the use and assumptions of an approach that allows determination of the Gibb's free energy of a protein unfolding transition based on the linear dependence of ΔG(o) on the concentration of denaturant used. This module also requires students to design their own experimental protocols and spend time in the primary literature, both important parts of an upper division lab. Copyright © 2008 International Union of Biochemistry and Molecular Biology, Inc.

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...

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.

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.

Sampling the Denatured State of Polypeptides in Water, Urea, and Guanidine Chloride to Strict Equilibrium Conditions with the Help of Massively Parallel Computers.

Science.gov (United States)

Meloni, Roberto; Camilloni, Carlo; Tiana, Guido

2014-02-11

The denatured state of polypeptides and proteins, stabilized by chemical denaturants like urea and guanidine chloride, displays residual secondary structure when studied by nuclear-magnetic-resonance spectroscopy. However, these experimental techniques are weakly sensitive, and thus molecular-dynamics simulations can be useful to complement the experimental findings. To sample the denatured state, we made use of massively-parallel computers and of a variant of the replica exchange algorithm, in which the different branches, connected with unbiased replicas, favor the formation and disruption of local secondary structure. The algorithm is applied to the second hairpin of GB1 in water, in urea, and in guanidine chloride. We show with the help of different criteria that the simulations converge to equilibrium. It results that urea and guanidine chloride, besides inducing some polyproline-II structure, have different effect on the hairpin. Urea disrupts completely the native region and stabilizes a state which resembles a random coil, while guanidine chloride has a milder effect.

'Lazy' quantum ensembles

International Nuclear Information System (INIS)

Parfionov, George; Zapatrin, Roman

2006-01-01

We compare different strategies aimed to prepare an ensemble with a given density matrix ρ. Preparing the ensemble of eigenstates of ρ with appropriate probabilities can be treated as 'generous' strategy: it provides maximal accessible information about the state. Another extremity is the so-called 'Scrooge' ensemble, which is mostly stingy in sharing the information. We introduce 'lazy' ensembles which require minimal effort to prepare the density matrix by selecting pure states with respect to completely random choice. We consider two parties, Alice and Bob, playing a kind of game. Bob wishes to guess which pure state is prepared by Alice. His null hypothesis, based on the lack of any information about Alice's intention, is that Alice prepares any pure state with equal probability. Then, the average quantum state measured by Bob turns out to be ρ, and he has to make a new hypothesis about Alice's intention solely based on the information that the observed density matrix is ρ. The arising 'lazy' ensemble is shown to be the alternative hypothesis which minimizes type I error

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.

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.

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.).

Using fluorescence correlation spectroscopy to study conformational changes in denatured proteins.

Science.gov (United States)

Sherman, Eilon; Itkin, Anna; Kuttner, Yosef Yehuda; Rhoades, Elizabeth; Amir, Dan; Haas, Elisha; Haran, Gilad

2008-06-01

Fluorescence correlation spectroscopy (FCS) is a sensitive analytical tool that allows dynamics and hydrodynamics of biomolecules to be studied under a broad range of experimental conditions. One application of FCS of current interest is the determination of the size of protein molecules in the various states they sample along their folding reaction coordinate, which can be accessed through the measurement of diffusion coefficients. It has been pointed out that the analysis of FCS curves is prone to artifacts that may lead to erroneous size determination. To set the stage for FCS studies of unfolded proteins, we first show that the diffusion coefficients of small molecules as well as proteins can be determined accurately even in the presence of high concentrations of co-solutes that change the solution refractive index significantly. Indeed, it is found that the Stokes-Einstein relation between the measured diffusion coefficient and solution viscosity holds even in highly concentrated glycerol or guanidinium hydrochloride (GuHCl) solutions. These measurements form the basis for an investigation of the structure of the denatured state of two proteins, the small protein L and the larger, three-domain protein adenylate kinase (AK). FCS is found useful for probing expansion in the denatured state beyond the unfolding transition. It is shown that the denatured state of protein L expands as the denaturant concentration increases, in a process akin to the transition from a globule to a coil in polymers. This process continues at least up to 5 M GuHCl. On the other hand, the denatured state of AK does not seem to expand much beyond 2 M GuHCl, a result that is in qualitative accord with single-molecule fluorescence histograms. Because both the unfolding transition and the coil-globule transition of AK occur at a much lower denaturant concentration than those of protein L, a possible correlation between the two phenomena is suggested.

Dynamic and structural study of neocarzinostatin native and denatured states, by differential microcalorimetry, optical spectroscopies and X-ray and neutron scattering

International Nuclear Information System (INIS)

Russo, Daniela

2000-01-01

A structural and dynamic characterization of proteins denatured states is essential to the understanding of mechanisms which control proteins folding. It is in this framework that this study has been undertaken in taking as model the neocarzinostatin globular protein. It is formed with seven cell-layers which form a barrel pattern maintained by two bi-sulfur bonds. A full characterization of native and denatured states, both from structural and dynamic point of view, has been implemented with several techniques able to bring data at different levels. During the experiments, ncs has been stabilized by temperature and by the use of a chaotropic agent: the guanidinium chloride (gdmcl). Small angle x-ray and neutron scattering have allowed us to obtain data on the variation of the protein compactness in terms of gdmcl temperature and concentration. The diffusion spectra show that ncs loses completely its globular structure above 80 C or in presence of about 5 m of gdmcl. Temperature and concentration of half denaturation are tm= 70 C and cm=3.5 m (in heavy water), respectively. Spectra analysis of strongly denatured protein has allowed us to obtain values of its chain length and of its persistence length which are in agreement with those theoretically estimated. Experiments have been carried out too to measure the radius of gyration to zero concentration and the second virial coefficient of the solution in order to estimate the interactions between the molecules. A full characterization has been performed in terms of gdmcl temperature and concentration by fluorescence and circular dichroism. These two techniques reveal the variations of the local three-dimensional structure and secondary structure of the protein respectively. Microcalorimetry measurements have shown that thermal denaturation of ncs is completely reversible and has been used to measure the enthalpy variation during the transition. At last, it has been possible to study ncs intramolecular dynamics in

Use of anionic denaturing detergents to purify insoluble proteins after overexpression

Directory of Open Access Journals (Sweden)

Schlager Benjamin

2012-12-01

Full Text Available Background Many proteins form insoluble protein aggregates, called “inclusion bodies”, when overexpressed in E. coli. This is the biggest obstacle in biotechnology. Ever since the reversible denaturation of proteins by chaotropic agents such as urea or guanidinium hydrochloride had been shown, these compounds were predominantly used to dissolve inclusion bodies. Other denaturants exist but have received much less attention in protein purification. While the anionic, denaturing detergent sodiumdodecylsulphate (SDS is used extensively in analytical SDS-PAGE, it has rarely been used in preparative purification. Results Here we present a simple and versatile method to purify insoluble, hexahistidine-tagged proteins under denaturing conditions. It is based on dissolution of overexpressing bacterial cells in a buffer containing sodiumdodecylsulfate (SDS and whole-lysate denaturation of proteins. The excess of detergent is removed by cooling and centrifugation prior to affinity purification. Host- and overexpressed proteins do not co-precipitate with SDS and the residual concentration of detergent is compatible with affinity purification on Ni/NTA resin. We show that SDS can be replaced with another ionic detergent, Sarkosyl, during purification. Key advantages over denaturing purification in urea or guanidinium are speed, ease of use, low cost of denaturant and the compatibility of buffers with automated FPLC. Conclusion Ionic, denaturing detergents are useful in breaking the solubility barrier, a major obstacle in biotechnology. The method we present yields detergent-denatured protein. Methods to refold proteins from a detergent denatured state are known and therefore we propose that the procedure presented herein will be of general application in biotechnology.

Denatured fuel cycles

International Nuclear Information System (INIS)

Till, C.E.

1979-01-01

This paper traces the history of the denatured fuel concept and discusses the characteristics of fuel cycles based on the concept. The proliferation resistance of denatured fuel cycles, the reactor types they involve, and the limitations they place on energy generation potential are discussed. The paper concludes with some remarks on the outlook for such cycles

Fluorescence lifetime components reveal kinetic intermediate states upon equilibrium denaturation of carbonic anhydrase II.

Science.gov (United States)

Nemtseva, Elena V; Lashchuk, Olesya O; Gerasimova, Marina A; Melnik, Tatiana N; Nagibina, Galina S; Melnik, Bogdan S

2017-12-21

In most cases, intermediate states of multistage folding proteins are not 'visible' under equilibrium conditions but are revealed in kinetic experiments. Time-resolved fluorescence spectroscopy was used in equilibrium denaturation studies. The technique allows for detecting changes in the conformation and environment of tryptophan residues in different structural elements of carbonic anhydrase II which in its turn has made it possible to study the intermediate states of carbonic anhydrase II under equilibrium conditions. The results of equilibrium and kinetic experiments using wild-type bovine carbonic anhydrase II and its mutant form with the substitution of leucine for alanine at position 139 (L139A) were compared. The obtained lifetime components of intrinsic tryptophan fluorescence allowed for revealing that, the same as in kinetic experiments, under equilibrium conditions the unfolding of carbonic anhydrase II ensues through formation of intermediate states.

Isothermal chemical denaturation of large proteins: Path-dependence and irreversibility.

Science.gov (United States)

Wafer, Lucas; Kloczewiak, Marek; Polleck, Sharon M; Luo, Yin

2017-12-15

State functions (e.g., ΔG) are path independent and quantitatively describe the equilibrium states of a thermodynamic system. Isothermal chemical denaturation (ICD) is often used to extrapolate state function parameters for protein unfolding in native buffer conditions. The approach is prudent when the unfolding/refolding processes are path independent and reversible, but may lead to erroneous results if the processes are not reversible. The reversibility was demonstrated in several early studies for smaller proteins, but was assumed in some reports for large proteins with complex structures. In this work, the unfolding/refolding of several proteins were systematically studied using an automated ICD instrument. It is shown that: (i) the apparent unfolding mechanism and conformational stability of large proteins can be denaturant-dependent, (ii) equilibration times for large proteins are non-trivial and may introduce significant error into calculations of ΔG, (iii) fluorescence emission spectroscopy may not correspond to other methods, such as circular dichroism, when used to measure protein unfolding, and (iv) irreversible unfolding and hysteresis can occur in the absence of aggregation. These results suggest that thorough confirmation of the state functions by, for example, performing refolding experiments or using additional denaturants, is needed when quantitatively studying the thermodynamics of protein unfolding using ICD. Copyright © 2017 Elsevier Inc. All rights reserved.

Girsanov reweighting for path ensembles and Markov state models

Science.gov (United States)

Donati, L.; Hartmann, C.; Keller, B. G.

2017-06-01

The sensitivity of molecular dynamics on changes in the potential energy function plays an important role in understanding the dynamics and function of complex molecules. We present a method to obtain path ensemble averages of a perturbed dynamics from a set of paths generated by a reference dynamics. It is based on the concept of path probability measure and the Girsanov theorem, a result from stochastic analysis to estimate a change of measure of a path ensemble. Since Markov state models (MSMs) of the molecular dynamics can be formulated as a combined phase-space and path ensemble average, the method can be extended to reweight MSMs by combining it with a reweighting of the Boltzmann distribution. We demonstrate how to efficiently implement the Girsanov reweighting in a molecular dynamics simulation program by calculating parts of the reweighting factor "on the fly" during the simulation, and we benchmark the method on test systems ranging from a two-dimensional diffusion process and an artificial many-body system to alanine dipeptide and valine dipeptide in implicit and explicit water. The method can be used to study the sensitivity of molecular dynamics on external perturbations as well as to reweight trajectories generated by enhanced sampling schemes to the original dynamics.

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].

World Music Ensemble: Kulintang

Science.gov (United States)

Beegle, Amy C.

2012-01-01

As instrumental world music ensembles such as steel pan, mariachi, gamelan and West African drums are becoming more the norm than the exception in North American school music programs, there are other world music ensembles just starting to gain popularity in particular parts of the United States. The kulintang ensemble, a drum and gong ensemble…

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.

Chimera states in an ensemble of linearly locally coupled bistable oscillators

Science.gov (United States)

Shchapin, D. S.; Dmitrichev, A. S.; Nekorkin, V. I.

2017-11-01

Chimera states in a system with linear local connections have been studied. The system is a ring ensemble of analog bistable self-excited oscillators with a resistive coupling. It has been shown that the existence of chimera states is not due to the nonidentity of oscillators and noise, which is always present in real experiments, but is due to the nonlinear dynamics of the system on invariant tori with various dimensions.

Highly Perturbed pKa Values in the Unfolded State of Hen Egg White Lysozyme

OpenAIRE

Bradley, John; O'Meara, Fergal; Farrell, Damien; Nielsen, Jens Erik

2012-01-01

The majority of pKa values in protein unfolded states are close to the amino acid model pKa values, thus reflecting the weak intramolecular interactions present in the unfolded ensemble of most proteins. We have carried out thermal denaturation measurements on the WT and eight mutants of HEWL from pH 1.5 to pH 11.0 to examine the unfolded state pKa values and the pH dependence of protein stability for this enzyme. The availability of accurate pKa values for the folded state of HEWL and separa...

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

-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......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...

27 CFR 19.456 - Adding denaturants.

Science.gov (United States)

2010-04-01

... proprietor shall submit a flow diagram of the intended process or method of adding denaturants. (Sec. 201... OF THE TREASURY LIQUORS DISTILLED SPIRITS PLANTS Denaturing Operations and Manufacture of Articles...

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

Science.gov (United States)

Vogtt, K; Winter, R

2005-08-01

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 (80 degrees C) and under high pressure conditions at low temperature (3.75 kbar, -13 degrees C). 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.

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)

K. Vogtt

2005-08-01

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.

Dynamics of Ionic Liquid-Assisted Refolding of Denatured Cytochrome c: A Study of Preferential Interactions toward Renaturation.

Science.gov (United States)

Singh, Upendra Kumar; Patel, Rajan

2018-05-25

In vitro refolding of denatured protein and the influence of the alkyl chain on the refolding of a protein were tested using long chain imidazolium chloride salts, 1-methyl-3-octylimidazolium chloride [C 8 mim][Cl], and 1-decyl-3-methylimidazolium chloride [C 10 mim][Cl]. The horse heart cytochrome c (h-cyt c) was denatured by urea and guanidinium hydrochloride (GdnHCl), as well as by base-induced denaturation at pH 13, to provide a broad overview of the overall refolding behavior. The variation in the alkyl chain of the ionic liquids (ILs) showed a profound effect on the refolding of denatured h-cyt c. The ligand-induced refolding was correlated to understand the mechanism of the conformational stability of proteins in aqueous solutions of ILs. The results showed that the long chain ILs having the [C 8 mim] + and [C 10 mim] + cations promote the refolding of alkali-denatured h-cyt c. The IL having the [C 10 mim] + cation efficiently refolded the alkali-denatured h-cyt c with the formation of the MG state, whereas the IL having the [C 8 mim] + cation, which is known to be compatible for protein stability, shows slight refolding and forms a different transition state. The lifetime results show successful refolding of alkaline-denatured h-cyt c by both of the ILs, however, more refolding was observed in the case of [C 10 mim][Cl], and this was correlated with the fast and medium lifetimes (τ 1 and τ 2 ) obtained, which show an increase accompanied by an increase in secondary structure. The hydrophobic interactions plays an important role in the refolding of chemically and alkali-denatured h-cyt c by long chain imidazolium ILs. The formation of the MG state by [C 10 mim][Cl] was also confirmed, as some regular structure exists far below the CMC of IL. The overall results suggested that the [C 10 mim] + cation bound to the unfolded h-cyt c triggers its refolding by electrostatic and hydrophobic interactions that stabilize the MG state.

Symmetric minimally entangled typical thermal states for canonical and grand-canonical ensembles

Science.gov (United States)

Binder, Moritz; Barthel, Thomas

2017-05-01

Based on the density matrix renormalization group (DMRG), strongly correlated quantum many-body systems at finite temperatures can be simulated by sampling over a certain class of pure matrix product states (MPS) called minimally entangled typical thermal states (METTS). When a system features symmetries, these can be utilized to substantially reduce MPS computation costs. It is conceptually straightforward to simulate canonical ensembles using symmetric METTS. In practice, it is important to alternate between different symmetric collapse bases to decrease autocorrelations in the Markov chain of METTS. To this purpose, we introduce symmetric Fourier and Haar-random block bases that are efficiently mixing. We also show how grand-canonical ensembles can be simulated efficiently with symmetric METTS. We demonstrate these approaches for spin-1 /2 X X Z chains and discuss how the choice of the collapse bases influences autocorrelations as well as the distribution of measurement values and, hence, convergence speeds.

Cold denaturation of the HIV-1 protease monomer

DEFF Research Database (Denmark)

Rösner, Heike Ilona; Caldarini, Martina; Prestel, Andreas

2017-01-01

The HIV-1-protease is a complex protein which in its active form adopts a homodimer dominated by -sheet structures. We have discovered a cold-denatured state of the monomeric subunit of HIV-1-protease which is populated above 0ºC and therefore directly accessible to various spectroscopic approac...

Generating maximally-path-entangled number states in two spin ensembles coupled to a superconducting flux qubit

Science.gov (United States)

Maleki, Yusef; Zheltikov, Aleksei M.

2018-01-01

An ensemble of nitrogen-vacancy (NV) centers coupled to a circuit QED device is shown to enable an efficient, high-fidelity generation of high-N00N states. Instead of first creating entanglement and then increasing the number of entangled particles N , our source of high-N00N states first prepares a high-N Fock state in one of the NV ensembles and then entangles it to the rest of the system. With such a strategy, high-N N00N states can be generated in just a few operational steps with an extraordinary fidelity. Once prepared, such a state can be stored over a longer period of time due to the remarkably long coherence time of NV centers.

Distribution, transition and thermodynamic stability of protein conformations in the denaturant-induced unfolding of proteins.

Science.gov (United States)

Bian, Liujiao; Ji, Xu

2014-01-01

Extensive and intensive studies on the unfolding of proteins require appropriate theoretical model and parameter to clearly illustrate the feature and characteristic of the unfolding system. Over the past several decades, four approaches have been proposed to describe the interaction between proteins and denaturants, but some ambiguity and deviations usually occur in the explanation of the experimental data. In this work, a theoretical model was presented to show the dependency of the residual activity ratio of the proteins on the molar denaturant concentration. Through the characteristic unfolding parameters ki and Δmi in this model, the distribution, transition and thermodynamic stability of protein conformations during the unfolding process can be quantitatively described. This model was tested with the two-state unfolding of bovine heart cytochrome c and the three-state unfolding of hen egg white lysozyme induced by both guanidine hydrochloride and urea, the four-state unfolding of bovine carbonic anhydrase b induced by guanidine hydrochloride and the unfolding of some other proteins induced by denaturants. The results illustrated that this model could be used accurately to reveal the distribution and transition of protein conformations in the presence of different concentrations of denaturants and to evaluate the unfolding tendency and thermodynamic stability of different conformations. In most denaturant-induced unfolding of proteins, the unfolding became increasingly hard in next transition step and the proteins became more unstable as they attained next successive stable conformation. This work presents a useful method for people to study the unfolding of proteins and may be used to describe the unfolding and refolding of other biopolymers induced by denaturants, inducers, etc.

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.

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

Denatured plutonium: a study of deterrent action. Final report

International Nuclear Information System (INIS)

Hutchins, B.A.

1975-07-01

The safeguarding of nuclear reactor fuel includes physical security methods as well as technological process options. The purpose of this study was to provide a preliminary evaluation of a technological option; the introduction of denaturing as a deterrent to illicit plutonium diversion. Denaturing is accomplished by coextracting some highly-radioactive fission products with the plutonium during reprocessing of spent fuel. The radioactive denaturant is always in companion with the plutonium through all subsequent fuel cycle steps - and serves as a deterrent to diversion or illicit usage of this fissile source. In concept the denaturing approach is simple and straightforward. This report provides a preliminary analysis of denaturing which can be achieved within the framework of present reprocessing technology. The impact of denaturing is indicated by comparison to a conventional (i.e., non-denatured) light water reacter cycle approach

The canonical ensemble redefined - 1: Formalism

International Nuclear Information System (INIS)

Venkataraman, R.

1984-12-01

For studying the thermodynamic properties of systems we propose an ensemble that lies in between the familiar canonical and microcanonical ensembles. We point out the transition from the canonical to microcanonical ensemble and prove from a comparative study that all these ensembles do not yield the same results even in the thermodynamic limit. An investigation of the coupling between two or more systems with these ensembles suggests that the state of thermodynamical equilibrium is a special case of statistical equilibrium. (author)

Guanidinium-Induced Denaturation by Breaking of Salt Bridges.

Science.gov (United States)

Meuzelaar, Heleen; Panman, Matthijs R; Woutersen, Sander

2015-12-07

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 a series of peptides containing Arg/Glu and Lys/Glu salt bridges that either stabilize or destabilize the folded conformation. The peptides containing stabilizing salt bridges are found to be denatured much more efficiently by Gdm(+) than the peptides containing destabilizing salt bridges. Complementary 2D-infrared measurements suggest a denaturation mechanism in which Gdm(+) binds to side-chain carboxylate groups involved in salt bridges. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Bullying Victimization among Music Ensemble and Theatre Students in the United States

Science.gov (United States)

Elpus, Kenneth; Carter, Bruce Allen

2016-01-01

The purpose of this study was to analyze the prevalence of reported school victimization through physical, verbal, social/relational, and cyberbullying aggression among music ensemble and theatre students in the middle and high schools of the United States as compared to their peers involved in other school-based activities. We analyzed nationally…

Protein folding simulations by generalized-ensemble algorithms.

Science.gov (United States)

Yoda, Takao; Sugita, Yuji; Okamoto, Yuko

2014-01-01

In the protein folding problem, conventional simulations in physical statistical mechanical ensembles, such as the canonical ensemble with fixed temperature, face a great difficulty. This is because there exist a huge number of local-minimum-energy states in the system and the conventional simulations tend to get trapped in these states, giving wrong results. Generalized-ensemble algorithms are based on artificial unphysical ensembles and overcome the above difficulty by performing random walks in potential energy, volume, and other physical quantities or their corresponding conjugate parameters such as temperature, pressure, etc. The advantage of generalized-ensemble simulations lies in the fact that they not only avoid getting trapped in states of energy local minima but also allows the calculations of physical quantities as functions of temperature or other parameters from a single simulation run. In this article we review the generalized-ensemble algorithms. Four examples, multicanonical algorithm, replica-exchange method, replica-exchange multicanonical algorithm, and multicanonical replica-exchange method, are described in detail. Examples of their applications to the protein folding problem are presented.

Eigenfunction statistics of Wishart Brownian ensembles

International Nuclear Information System (INIS)

Shukla, Pragya

2017-01-01

We theoretically analyze the eigenfunction fluctuation measures for a Hermitian ensemble which appears as an intermediate state of the perturbation of a stationary ensemble by another stationary ensemble of Wishart (Laguerre) type. Similar to the perturbation by a Gaussian stationary ensemble, the measures undergo a diffusive dynamics in terms of the perturbation parameter but the energy-dependence of the fluctuations is different in the two cases. This may have important consequences for the eigenfunction dynamics as well as phase transition studies in many areas of complexity where Brownian ensembles appear. (paper)

Symmetric minimally entangled typical thermal states, grand-canonical ensembles, and the influence of the collapse bases

Science.gov (United States)

Binder, Moritz; Barthel, Thomas

Based on DMRG, strongly correlated quantum many-body systems at finite temperatures can be simulated by sampling over a certain class of pure matrix product states (MPS) called minimally entangled typical thermal states (METTS). Here, we show how symmetries of the system can be exploited to considerably reduce computation costs in the METTS algorithm. While this is straightforward for the canonical ensemble, we introduce a modification of the algorithm to efficiently simulate the grand-canonical ensemble under utilization of symmetries. In addition, we construct novel symmetry-conserving collapse bases for the transitions in the Markov chain of METTS that improve the speed of convergence of the algorithm by reducing autocorrelations.

Loss of conformational entropy in protein folding calculated using realistic ensembles and its implications for NMR-based calculations

Science.gov (United States)

Baxa, Michael C.; Haddadian, Esmael J.; Jumper, John M.; Freed, Karl F.; Sosnick, Tobin R.

2014-01-01

The loss of conformational entropy is a major contribution in the thermodynamics of protein folding. However, accurate determination of the quantity has proven challenging. We calculate this loss using molecular dynamic simulations of both the native protein and a realistic denatured state ensemble. For ubiquitin, the total change in entropy is TΔSTotal = 1.4 kcal⋅mol−1 per residue at 300 K with only 20% from the loss of side-chain entropy. Our analysis exhibits mixed agreement with prior studies because of the use of more accurate ensembles and contributions from correlated motions. Buried side chains lose only a factor of 1.4 in the number of conformations available per rotamer upon folding (ΩU/ΩN). The entropy loss for helical and sheet residues differs due to the smaller motions of helical residues (TΔShelix−sheet = 0.5 kcal⋅mol−1), a property not fully reflected in the amide N-H and carbonyl C=O bond NMR order parameters. The results have implications for the thermodynamics of folding and binding, including estimates of solvent ordering and microscopic entropies obtained from NMR. PMID:25313044

Reversibility of partial denaturation of DNA

International Nuclear Information System (INIS)

Acuna, M.I.; Mingot, F.; Davila, C.A.

1976-01-01

The recovery of hypochromicity in a partially denatured DNA sample when salt concentration is suddenly increased at a intermediate stage of the thermal transition is studied. The results of CsCl gradient analysis, PEG/DEX partition analysis, behaviour in a new thermal transition hydrodynamic properties and transforming ability, support the view that the process is an intramolecular double chain denaturation. The degree of denaturation irreversibility is dependent on single chain molecular weight of DNA (discontinuities denisty) and upon the helicity value at which salt concentration jump is performed. Both dependences are formally interpreted according to Elton's model for base distribution in DNA. Kinetically the process behaves as being an hydrodynamically limited rewinding. (author)

Thermal denaturation of type I collagen vitrified gels

International Nuclear Information System (INIS)

Xia, Zhiyong; Calderon-Colon, Xiomara; Trexler, Morgana; Elisseeff, Jennifer; Guo, Qiongyu

2012-01-01

Highlights: ► We analyzed the denaturation of vitrigels synthesized under different conditions. ► Overall denaturation kinetics consisted of both reversible and irreversible steps. ► 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 °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.

Equilibrium unfolding of A. niger RNase: pH dependence of chemical and thermal denaturation.

Science.gov (United States)

Kumar, Gundampati Ravi; Sharma, Anurag; Kumari, Moni; Jagannadham, Medicherla V; Debnath, Mira

2011-08-01

Equilibrium unfolding of A. niger RNase with chemical denaturants, for example GuHCl and urea, and thermal unfolding have been studied as a function of pH using fluorescence, far-UV, near-UV, and absorbance spectroscopy. Because of their ability to affect electrostatic interactions, pH and chemical denaturants have a marked effect on the stability, structure, and function of many globular proteins. ANS binding studies have been conducted to enable understanding of the folding mechanism of the protein in the presence of the denaturants. Spectroscopic studies by absorbance, fluorescence, and circular dichroism and use of K2D software revealed that the enzyme has α + β type secondary structure with approximately 29% α-helix, 24% β-sheet, and 47% random coil. Under neutral conditions the enzyme is stable in urea whereas GuHCl-induced equilibrium unfolding was cooperative. A. niger RNase has little ANS binding even under neutral conditions. Multiple intermediates were populated during the pH-induced unfolding of A. niger RNase. Urea and temperature-induced unfolding of A. niger RNase into the molten globule-like state is non-cooperative, in contrast to the cooperativity seen with the native protein, suggesting the presence of two parts/domains, in the molecular structure of A. niger RNase, with different stability that unfolds in steps. Interestingly, the GuHCl-induced unfolding of the A state (molten globule state) of A. niger RNase is unique, because a low concentration of denaturant not only induces structural change but also facilitates transition from one molten globule like state (A(MG1)) into another (I(MG2)).

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…

Minimum error discrimination for an ensemble of linearly independent pure states

International Nuclear Information System (INIS)

Singal, Tanmay; Ghosh, Sibasish

2016-01-01

Inspired by the work done by Belavkin (1975 Stochastics 1 315) and independently by Mochon, (2006 Phys. Rev. A 73 032328), we formulate the problem of minimum error discrimination (MED) of any ensemble of n linearly independent pure states by stripping the problem of its rotational covariance and retaining only the rotationally invariant aspect of the problem. This is done by embedding the optimal conditions in a matrix equality as well as matrix inequality. Employing the implicit function theorem in these conditions we get a set of first-order coupled ordinary nonlinear differential equations which can be used to drag the solution from an initial point (where solution is known) to another point (whose solution is sought). This way of obtaining the solution can be done through a simple Taylor series expansion and analytic continuation when required. Thus, we complete the work done by Belavkin and Mochon by ultimately leading their theory to a solution for the MED problem of linearly independent pure state ensembles. We also compare the computational complexity of our technique with the barrier-type interior point method of SDP and show that our technique is computationally as efficient as (actually, a bit more than) the SDP algorithm, with the added advantage of being much simpler to implement. (paper)

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

KAUST Repository

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

2015-01-01

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

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...

Thermally responsive silicon nanowire arrays for native/denatured-protein separation

International Nuclear Information System (INIS)

Wang Hongwei; Wang Yanwei; Yuan Lin; Wang Lei; Yang Weikang; Wu Zhaoqiang; Li Dan; Chen Hong

2013-01-01

We present our findings of the selective adsorption of native and denatured proteins onto thermally responsive, native-protein resistant poly(N-isopropylacrylamide) (PNIPAAm) decorated silicon nanowire arrays (SiNWAs). The PNIPAAm–SiNWAs surface, which shows very low levels of native-protein adsorption, favors the adsorption of denatured proteins. The amount of denatured-protein adsorption is higher at temperatures above the lower critical solution temperature (LCST) of PNIPAAm. Temperature cycling surrounding the LCST, which ensures against thermal denaturation of native proteins, further increases the amount of denatured-protein adsorption. Moreover, the PNIPAAm–SiNWAs surface is able to selectively adsorb denatured protein even from mixtures of different protein species; meanwhile, the amount of native proteins in solution is kept nearly at its original level. It is believed that these results will not only enrich current understanding of protein interactions with PNIPAAm-modified SiNWAs surfaces, but may also stimulate applications of PNIPAAm–SiNWAs surfaces for native/denatured protein separation. (paper)

Refining Markov state models for conformational dynamics using ensemble-averaged data and time-series trajectories

Science.gov (United States)

Matsunaga, Y.; Sugita, Y.

2018-06-01

A data-driven modeling scheme is proposed for conformational dynamics of biomolecules based on molecular dynamics (MD) simulations and experimental measurements. In this scheme, an initial Markov State Model (MSM) is constructed from MD simulation trajectories, and then, the MSM parameters are refined using experimental measurements through machine learning techniques. The second step can reduce the bias of MD simulation results due to inaccurate force-field parameters. Either time-series trajectories or ensemble-averaged data are available as a training data set in the scheme. Using a coarse-grained model of a dye-labeled polyproline-20, we compare the performance of machine learning estimations from the two types of training data sets. Machine learning from time-series data could provide the equilibrium populations of conformational states as well as their transition probabilities. It estimates hidden conformational states in more robust ways compared to that from ensemble-averaged data although there are limitations in estimating the transition probabilities between minor states. We discuss how to use the machine learning scheme for various experimental measurements including single-molecule time-series trajectories.

Detection of urea-induced internal denaturation of dsDNA using solid-state nanopores.

Science.gov (United States)

Singer, Alon; Kuhn, Heiko; Frank-Kamenetskii, Maxim; Meller, Amit

2010-11-17

The ability to detect and measure dsDNA thermal fluctuations is of immense importance in understanding the underlying mechanisms responsible for transcription and replication regulation. We describe here the ability of solid-state nanopores to detect sub-nanometer changes in DNA structure as a result of chemically enhanced thermal fluctuations. In this study, we investigate the subtle changes in the mean effective diameter of a dsDNA molecule with 3-5 nm solid-state nanopores as a function of urea concentration and the DNA's AT content. Our studies reveal an increase in the mean effective diameter of a DNA molecule of approximately 0.6 nm at 8.7 M urea. In agreement with the mechanism of DNA local denaturation, we observe a sigmoid dependence of these effects on urea concentration. We find that the translocation times in urea are markedly slower than would be expected if the dynamics were governed primarily by viscous effects. Furthermore, we find that the sensitivity of the nanopore is sufficient to statistically differentiate between DNA molecules of nearly identical lengths differing only in sequence and AT content when placed in 3.5 M urea. Our results demonstrate that nanopores can detect subtle structural changes and are thus a valuable tool for detecting differences in biomolecules' environment.

Detection of urea-induced internal denaturation of dsDNA using solid-state nanopores

International Nuclear Information System (INIS)

Singer, Alon; Kuhn, Heiko; Frank-Kamenetskii, Maxim; Meller, Amit

2010-01-01

The ability to detect and measure dsDNA thermal fluctuations is of immense importance in understanding the underlying mechanisms responsible for transcription and replication regulation. We describe here the ability of solid-state nanopores to detect sub-nanometer changes in DNA structure as a result of chemically enhanced thermal fluctuations. In this study, we investigate the subtle changes in the mean effective diameter of a dsDNA molecule with 3-5 nm solid-state nanopores as a function of urea concentration and the DNA's AT content. Our studies reveal an increase in the mean effective diameter of a DNA molecule of approximately 0.6 nm at 8.7 M urea. In agreement with the mechanism of DNA local denaturation, we observe a sigmoid dependence of these effects on urea concentration. We find that the translocation times in urea are markedly slower than would be expected if the dynamics were governed primarily by viscous effects. Furthermore, we find that the sensitivity of the nanopore is sufficient to statistically differentiate between DNA molecules of nearly identical lengths differing only in sequence and AT content when placed in 3.5 M urea. Our results demonstrate that nanopores can detect subtle structural changes and are thus a valuable tool for detecting differences in biomolecules' environment.

Ensemble methods for handwritten digit recognition

DEFF Research Database (Denmark)

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

1992-01-01

Neural network ensembles are applied to handwritten digit recognition. The individual networks of the ensemble are combinations of sparse look-up tables (LUTs) with random receptive fields. It is shown that the consensus of a group of networks outperforms the best individual of the ensemble....... 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...... by optimizing the receptive fields. It is concluded that it is possible to improve performance significantly by introducing moderate-size ensembles; in particular, a 20-25% improvement has been found. The ensemble random LUTs, when trained on a medium-size database, reach a performance (without rejects) of 94...

Extension of the GHJW theorem for operator ensembles

International Nuclear Information System (INIS)

Choi, Jeong Woon; Hong, Dowon; Chang, Ku-Young; Chi, Dong Pyo; Lee, Soojoon

2011-01-01

The Gisin-Hughston-Jozsa-Wootters theorem plays an important role in analyzing various theories about quantum information, quantum communication, and quantum cryptography. It means that any purifications on the extended system which yield indistinguishable state ensembles on their subsystem should have a specific local unitary relation. In this Letter, we show that the local relation is also established even when the indistinguishability of state ensembles is extended to that of operator ensembles.

Chemical Denaturants Smoothen Ruggedness on the Free Energy Landscape of Protein Folding.

Science.gov (United States)

Malhotra, Pooja; Jethva, Prashant N; Udgaonkar, Jayant B

2017-08-08

To characterize experimentally the ruggedness of the free energy landscape of protein folding is challenging, because the distributed small free energy barriers are usually dominated by one, or a few, large activation free energy barriers. This study delineates changes in the roughness of the free energy landscape by making use of the observation that a decrease in ruggedness is accompanied invariably by an increase in folding cooperativity. Hydrogen exchange (HX) coupled to mass spectrometry was used to detect transient sampling of local energy minima and the global unfolded state on the free energy landscape of the small protein single-chain monellin. Under native conditions, local noncooperative openings result in interconversions between Boltzmann-distributed intermediate states, populated on an extremely rugged "uphill" energy landscape. The cooperativity of these interconversions was increased by selectively destabilizing the native state via mutations, and further by the addition of a chemical denaturant. The perturbation of stability alone resulted in seven backbone amide sites exchanging cooperatively. The size of the cooperatively exchanging and/or unfolding unit did not depend on the extent of protein destabilization. Only upon the addition of a denaturant to a destabilized mutant variant did seven additional backbone amide sites exchange cooperatively. Segmentwise analysis of the HX kinetics of the mutant variants further confirmed that the observed increase in cooperativity was due to the smoothing of the ruggedness of the free energy landscape of folding of the protein by the chemical denaturant.

27 CFR 19.464 - Denatured spirits inventories.

Science.gov (United States)

2010-04-01

... 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 at... inventories. 19.464 Section 19.464 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE...

Development of Gridded Ensemble Precipitation and Temperature Datasets for the Contiguous United States Plus Hawai'i and Alaska

Science.gov (United States)

Newman, A. J.; Clark, M. P.; Nijssen, B.; Wood, A.; Gutmann, E. D.; Mizukami, N.; Longman, R. J.; Giambelluca, T. W.; Cherry, J.; Nowak, K.; Arnold, J.; Prein, A. F.

2016-12-01

Gridded precipitation and temperature products are inherently uncertain due to myriad factors. These include interpolation from a sparse observation network, measurement representativeness, and measurement errors. Despite this inherent uncertainty, uncertainty is typically not included, or is a specific addition to each dataset without much general applicability across different datasets. A lack of quantitative uncertainty estimates for hydrometeorological forcing fields limits their utility to support land surface and hydrologic modeling techniques such as data assimilation, probabilistic forecasting and verification. To address this gap, we have developed a first of its kind gridded, observation-based ensemble of precipitation and temperature at a daily increment for the period 1980-2012 over the United States (including Alaska and Hawaii). A longer, higher resolution version (1970-present, 1/16th degree) has also been implemented to support real-time hydrologic- monitoring and prediction in several regional US domains. We will present the development and evaluation of the dataset, along with initial applications of the dataset for ensemble data assimilation and probabilistic evaluation of high resolution regional climate model simulations. We will also present results on the new high resolution products for Alaska and Hawaii (2 km and 250 m respectively), to complete the first ensemble observation based product suite for the entire 50 states. Finally, we will present plans to improve the ensemble dataset, focusing on efforts to improve the methods used for station interpolation and ensemble generation, as well as methods to fuse station data with numerical weather prediction model output.

Combining extrapolation with ghost interaction correction in range-separated ensemble density functional theory for excited states

Science.gov (United States)

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

2017-11-01

The extrapolation technique of Savin [J. Chem. Phys. 140, 18A509 (2014)], which was initially applied to range-separated ground-state-density-functional Hamiltonians, is adapted in this work to ghost-interaction-corrected (GIC) range-separated ensemble density-functional theory (eDFT) for excited states. While standard extrapolations rely on energies that decay as μ-2 in the large range-separation-parameter μ limit, we show analytically that (approximate) range-separated GIC ensemble energies converge more rapidly (as μ-3) towards their pure wavefunction theory values (μ → +∞ limit), thus requiring a different extrapolation correction. The purpose of such a correction is to further improve on the convergence and, consequently, to obtain more accurate excitation energies for a finite (and, in practice, relatively small) μ value. As a proof of concept, we apply the extrapolation method to He and small molecular systems (viz., H2, HeH+, and LiH), thus considering different types of excitations such as Rydberg, charge transfer, and double excitations. Potential energy profiles of the first three and four singlet Σ+ excitation energies in HeH+ and H2, respectively, are studied with a particular focus on avoided crossings for the latter. Finally, the extraction of individual state energies from the ensemble energy is discussed in the context of range-separated eDFT, as a perspective.

On-line Learning of Unlearnable True Teacher through Mobile Ensemble Teachers

Science.gov (United States)

Hirama, Takeshi; Hukushima, Koji

2008-09-01

The on-line learning of a hierarchical learning model is studied by a method based on statistical mechanics. In our model, a student of a simple perceptron learns from not a true teacher directly, but ensemble teachers who learn from a true teacher with a perceptron learning rule. Since the true teacher and ensemble teachers are expressed as nonmonotonic and simple perceptrons, respectively, the ensemble teachers go around the unlearnable true teacher with the distance between them fixed in an asymptotic steady state. The generalization performance of the student is shown to exceed that of the ensemble teachers in a transient state, as was shown in similar ensemble-teachers models. Furthermore, it is found that moving the ensemble teachers even in the steady state, in contrast to the fixed ensemble teachers, is efficient for the performance of the student.

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.

Multilevel ensemble Kalman filtering

KAUST Repository

Hoel, Haakon; Chernov, Alexey; Law, Kody; Nobile, Fabio; Tempone, Raul

2016-01-01

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.

Fock-state view of weak-value measurements and implementation with photons and atomic ensembles

International Nuclear Information System (INIS)

Simon, Christoph; Polzik, Eugene S.

2011-01-01

Weak measurements in combination with postselection can give rise to a striking amplification effect (related to a large ''weak value''). We show that this effect can be understood by viewing the initial state of the pointer as the ground state of a fictional harmonic oscillator. This perspective clarifies the relationship between the weak-value regime and other measurement techniques and inspires a proposal to implement fully quantum weak-value measurements combining photons and atomic ensembles.

Shallow cumuli ensemble statistics for development of a stochastic parameterization

Science.gov (United States)

Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs

2014-05-01

According to a conventional deterministic approach to the parameterization of moist convection in numerical atmospheric models, a given large scale forcing produces an unique response from the unresolved convective processes. This representation leaves out the small-scale variability of convection, as it is known from the empirical studies of deep and shallow convective cloud ensembles, there is a whole distribution of sub-grid states corresponding to the given large scale forcing. Moreover, this distribution gets broader with the increasing model resolution. This behavior is also consistent with our theoretical understanding of a coarse-grained nonlinear system. We propose an approach to represent the variability of the unresolved shallow-convective states, including the dependence of the sub-grid states distribution spread and shape on the model horizontal resolution. Starting from the Gibbs canonical ensemble theory, Craig and Cohen (2006) developed a theory for the fluctuations in a deep convective ensemble. The micro-states of a deep convective cloud ensemble are characterized by the cloud-base mass flux, which, according to the theory, is exponentially distributed (Boltzmann distribution). Following their work, we study the shallow cumulus ensemble statistics and the distribution of the cloud-base mass flux. We employ a Large-Eddy Simulation model (LES) and a cloud tracking algorithm, followed by a conditional sampling of clouds at the cloud base level, to retrieve the information about the individual cloud life cycles and the cloud ensemble as a whole. In the case of shallow cumulus cloud ensemble, the distribution of micro-states is a generalized exponential distribution. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate the shallow convective cloud ensemble and to test the convective ensemble theory. Stochastic model simulates a compound random process, with the number of convective elements drawn from a

Analyzing Protein Denaturation using Fast Differential Scanning Calorimetry

NARCIS (Netherlands)

Splinter, R.; Van Herwaarden, A.W.; Iervolino, E.; Vanden Poel, G.; Istrate, D.; Sarro, P.M.

2012-01-01

This paper investigates the possibility to measure protein denaturation with Fast Differential Scanning Calorimetry (FDSC). Cancer can be diagnosed by measuring protein denaturation in blood plasma using Differential Scanning Calorimetry (DSC). FDSC can reduce diagnosis time from hours to minutes,

Insights into signal transduction by a hybrid FixL: Denaturation study of on and off states of a multi-domain oxygen sensor.

Science.gov (United States)

Guimarães, Wellinson G; Gondim, Ana C S; Costa, Pedro Mikael da Silva; Gilles-Gonzalez, Marie-Alda; Lopes, Luiz G F; Carepo, Marta S P; Sousa, Eduardo H S

2017-07-01

FixL from Rhizobium etli (ReFixL) is a hybrid oxygen sensor protein. Signal transduction in ReFixL is effected by a switch off of the kinase activity on binding of an oxygen molecule to ferrous heme iron in another domain. Cyanide can also inhibit the kinase activity upon binding to the heme iron in the ferric state. The unfolding by urea of the purified full-length ReFixL in both active pentacoordinate form, met-FixL(Fe III ) and inactive cyanomet-FixL (Fe III -CN - ) form was monitored by UV-visible absorption spectroscopy, circular dichroism (CD) and fluorescence spectroscopy. The CD and UV-visible absorption spectroscopy revealed two states during unfolding, whereas fluorescence spectroscopy identified a three-state unfolding mechanism. The unfolding mechanism was not altered for the active compared to the inactive state; however, differences in the ΔG H2O were observed. According to the CD results, compared to cyanomet-FixL, met-FixL was more stable towards chemical denaturation by urea (7.2 vs 4.8kJmol -1 ). By contrast, electronic spectroscopy monitoring of the Soret band showed cyanomet-FixL to be more stable than met-FixL (18.5 versus 36.2kJmol -1 ). For the three-state mechanism exhibited by fluorescence, the ΔG H2O for both denaturation steps were higher for the active-state met-FixL than for cyanomet-FixL. The overall stability of met-FixL is higher in comparison to cyanomet-FixL suggesting a more compact protein in the active form. Nonetheless, hydrogen bonding by bound cyanide in the inactive state promotes the stability of the heme domain. This work supports a model of signal transduction by FixL that is likely shared by other heme-based sensors. Copyright © 2017 Elsevier Inc. All rights reserved.

The effect of Na+ and K+ on the thermal denaturation of Na+ and + K+-dependent ATPase.

Science.gov (United States)

Fischer, T H

1983-01-01

To increase our understanding of the physical nature of the Na+ and K+ forms of the Na+ + K+-dependent ATPase, thermal-denaturation studies were conducted in different types of ionic media. Thermal-denaturation measurements were performed by measuring the regeneration of ATPase activity after slow pulse exposure to elevated temperatures. Two types of experiments were performed. First, the dependence of the thermal-denaturation rate on Na+ and K+ concentrations was examined. It was found that both cations stabilized the pump protein. Also, K+ was a more effective stabilizer of the native state than was Na+. Secondly, a set of thermodynamic parameters was obtained by measuring the temperature-dependence of the thermal-denaturation rate under three ionic conditions: 60 mM-K+, 150 mM-Na+ and no Na+ or K+. It was found that ion-mediated stabilization of the pump protein was accompanied by substantial increases in activation enthalpy and entropy, the net effect being a less-pronounced increase in activation free energy. PMID:6309139

On the Generation of Random Ensembles of Qubits and Qutrits Computing Separability Probabilities for Fixed Rank States

Directory of Open Access Journals (Sweden)

Khvedelidze Arsen

2018-01-01

Full Text Available The generation of random mixed states is discussed, aiming for the computation of probabilistic characteristics of composite finite dimensional quantum systems. In particular, we consider the generation of random Hilbert-Schmidt and Bures ensembles of qubit and qutrit pairs and compute the corresponding probabilities to find a separable state among the states of a fixed rank.

Reversible thermal denaturation of immobilized rhodanese

International Nuclear Information System (INIS)

Horowitz, P.; Bowman, S.

1987-01-01

For the first time, the enzyme rhodanese had been refolded after thermal denaturation. This was previously not possible because of the strong tendency for the soluble enzyme to aggregate at temperatures above 37 degrees C. The present work used rhodanese that was covalently coupled to a solid support under conditions that were found to preserve enzyme activity. Rhodanese was immobilized using an N-hydroxymalonimidyl derivative of Sepharose containing a 6-carbon spacer. The number of immobilized competent active sites was measured by using [ 35 S]SO 3 (2-) to form an active site persulfide that is the obligatory catalytic intermediate. Soluble enzyme was irreversibly inactivated in 10 min at 52 degrees C. The immobilized enzyme regained at least 30% of its original activity even after boiling for 20 min. The immobilized enzyme had a Km and Vmax that were each approximately 3 times higher than the corresponding values for the native enzyme. After preincubation at high temperatures, progress curves for the immobilized enzyme showed induction periods of up to 5 min before attaining apparently linear steady states. The pH dependence of the activity was the same for both the soluble and the immobilized enzyme. These results indicate significant stabilization of rhodanese after immobilization, and instabilities caused by adventitious solution components are not the sole reasons for irreversibility of thermal denaturation seen with the soluble enzyme. The results are consistent with models for rhodanese that invoke protein association as a major cause of inactivation of the enzyme. Furthermore, the induction period in the progress curves is consistent with studies which show that rhodanese refolding proceeds through intermediate states

Quantum ensembles of quantum classifiers.

Science.gov (United States)

Schuld, Maria; Petruccione, Francesco

2018-02-09

Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.

Measurement of the quantum superposition state of an imaging ensemble of photons prepared in orbital angular momentum states using a phase-diversity method

International Nuclear Information System (INIS)

Uribe-Patarroyo, Nestor; Alvarez-Herrero, Alberto; Belenguer, Tomas

2010-01-01

We propose the use of a phase-diversity technique to estimate the orbital angular momentum (OAM) superposition state of an ensemble of photons that passes through an optical system, proceeding from an extended object. The phase-diversity technique permits the estimation of the optical transfer function (OTF) of an imaging optical system. As the OTF is derived directly from the wave-front characteristics of the observed light, we redefine the phase-diversity technique in terms of a superposition of OAM states. We test this new technique experimentally and find coherent results among different tests, which gives us confidence in the estimation of the photon ensemble state. We find that this technique not only allows us to estimate the square of the amplitude of each OAM state, but also the relative phases among all states, thus providing complete information about the quantum state of the photons. This technique could be used to measure the OAM spectrum of extended objects in astronomy or in an optical communication scheme using OAM states. In this sense, the use of extended images could lead to new techniques in which the communication is further multiplexed along the field.

The classicality and quantumness of a quantum ensemble

International Nuclear Information System (INIS)

Zhu Xuanmin; Pang Shengshi; Wu Shengjun; Liu Quanhui

2011-01-01

In this Letter, we investigate the classicality and quantumness of a quantum ensemble. We define a quantity called ensemble classicality based on classical cloning strategy (ECCC) to characterize how classical a quantum ensemble is. An ensemble of commuting states has a unit ECCC, while a general ensemble can have a ECCC 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 the ensemble used in a quantum key distribution (QKD) protocol is exactly the attainable lower bound of the error rate in the sifted key. - Highlights: → A quantity is defined to characterize how classical a quantum ensemble is. → The classicality of an ensemble is closely related to the cloning performance. → Another quantity is also defined to investigate how quantum an ensemble is. → This quantity gives the lower bound of the error rate in a QKD protocol.

Light water reactors with a denatured thorium fuel cycle

International Nuclear Information System (INIS)

1978-05-01

Discussed in this paper is the performance of denatured thorium fuel cycles in PWR plants of conventional design, such as those currently in operation or under construction. Although some improvement in U 3 O 8 utilization is anticipated in PWRs optimized explicitly for the denatured thorium fuel cycle, this paper is limited to a discussion of the performance of denatured thorium fuels in conventional PWRs and consequently the data presented is representative of the use of thorium fuel in existing PWRs or those presently under construction. In subsequent sections of this paper, the design of the PWR, its performance on the denatured thorium fuel cycle, safety, accident and environmental considerations, and technological status and R and D requirements are discussed

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.

Transurethral radiofrequency collagen denaturation for the treatment of women with urinary incontinence.

Science.gov (United States)

Kang, Diana; Han, Julia; Neuberger, Molly M; Moy, M Louis; Wallace, Sheila A; Alonso-Coello, Pablo; Dahm, Philipp

2015-03-18

evidence using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. We included in the analysis one small sham-controlled randomised trial of 173 women performed in the United States. Participants enrolled in this study had been diagnosed with stress UI and were randomly assigned to transurethral radiofrequency collagen denaturation (treatment) or a sham surgery using a non-functioning catheter (no treatment). Mean age of participants in the 12-month multi-centre trial was 50 years (range 22 to 76 years).Of three patient-important primary outcomes selected for this systematic review, the number of women reporting UI symptoms after intervention was not reported. No serious adverse events were reported for the transurethral radiofrequency collagen denaturation arm or the sham treatment arm during the 12-month trial. Owing to high risk of bias and imprecision, we downgraded the quality of evidence for this outcome to low. The effect of transurethral radiofrequency collagen denaturation on the number of women with an incontinence quality of life (I-QOL) score improvement ≥ 10 points at 12 months was as follows: RR 1.11, 95% CI 0.77 to 1.62; participants = 142, but the confidence interval was wide. For this outcome, the quality of evidence was also low as the result of high risk of bias and imprecision.We found no evidence on the number of women undergoing repeat continence surgery. The risk of other adverse events (pain/dysuria (RR 5.73, 95% CI 0.75 to 43.70; participants = 173); new detrusor overactivity (RR 1.36, 95% CI 0.63 to 2.93; participants = 173); and urinary tract infection (RR 0.95, 95% CI 0.24 to 3.86; participants = 173) could not be established reliably as the trial was small. Evidence was insufficient for assessment of whether use of transurethral radiofrequency collagen denaturation was associated with an increased rate of urinary retention, haematuria and hesitancy compared with sham treatment in 173 participants. The GRADE

Single Molecular Level Probing of Structure and Dynamics of Papain Under Denaturation.

Science.gov (United States)

Sengupta, Bhaswati; Chaudhury, Apala; Das, Nilimesh; Sen, Pratik

2017-01-01

Papain is a cysteine protease enzyme present in papaya and known to help in digesting peptide. Thus the structure and function of the active site of papain is of interest. The objective of present study is to unveil the overall structural transformation and the local structural change around the active site of papain as a function of chemical denaturant. Papain has been tagged at Cys-25 with a thiol specific fluorescence probe N-(7- dimethylamino-4-methylcoumarin-3-yl) iodoacetamide (DACIA). Guanidine hydrochloride (GnHCl) has been used as the chemical denaturant. Steady state, time-resolved, and single molecular level fluorescence techniques was applied to map the change in the local environment. It is found that papain undergoes a two-step denaturation in the presence of GnHCl. Fluorescence correlation spectroscopic (FCS) data indicate that the size (hydrodynamic diameter) of native papain is ~36.8 Å, which steadily increases to ~53 Å in the presence of 6M GnHCl. FCS study also reveals that the conformational fluctuation time of papain is 6.3 µs in its native state, which decreased to 2.7 µs in the presence of 0.75 M GnHCl. Upon further increase in GnHCl concentration the conformational fluctuation time increase monotonically till 6 M GnHCl, where the time constant is measured as 14 µs. On the other hand, the measurement of ellipticity, hence the helical structure, by circular dichroism spectroscopy is found to be incapable to capture such structural transformation. It is concluded that in the presence of small amount of GnHCl the active site of papain takes up a more compact structure (although the overall size increases) than in the native state, which has been designated as the intermediate state. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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.

Parallel quantum computing in a single ensemble quantum computer

International Nuclear Information System (INIS)

Long Guilu; Xiao, L.

2004-01-01

We propose a parallel quantum computing mode for ensemble quantum computer. In this mode, some qubits are in pure states while other qubits are in mixed states. It enables a single ensemble quantum computer to perform 'single-instruction-multidata' type of parallel computation. Parallel quantum computing can provide additional speedup in Grover's algorithm and Shor's algorithm. In addition, it also makes a fuller use of qubit resources in an ensemble quantum computer. As a result, some qubits discarded in the preparation of an effective pure state in the Schulman-Varizani and the Cleve-DiVincenzo algorithms can be reutilized

Dissipation induced asymmetric steering of distant atomic ensembles

Science.gov (United States)

Cheng, Guangling; Tan, Huatang; Chen, Aixi

2018-04-01

The asymmetric steering effects of separated atomic ensembles denoted by the effective bosonic modes have been explored by the means of quantum reservoir engineering in the setting of the cascaded cavities, in each of which an atomic ensemble is involved. It is shown that the steady-state asymmetric steering of the mesoscopic objects is unconditionally achieved via the dissipation of the cavities, by which the nonlocal interaction occurs between two atomic ensembles, and the direction of steering could be easily controlled through variation of certain tunable system parameters. One advantage of the present scheme is that it could be rather robust against parameter fluctuations, and does not require the accurate control of evolution time and the original state of the system. Furthermore, the double-channel Raman transitions between the long-lived atomic ground states are used and the atomic ensembles act as the quantum network nodes, which makes our scheme insensitive to the collective spontaneous emission of atoms.

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.

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...... and peaks in the intensity trace along the extended molecule. We demonstrate that this structure arises from the physics of local denaturation: statistical mechanical calculations of sequence-dependent melting probability can predict the barcode to be observed experimentally for a given sequence...

Ensemble of Transition State Structures for the Cis-Trans Isomerization of N-Methylacetamide

Energy Technology Data Exchange (ETDEWEB)

Mantz, Yves A. [National Energy Technology Lab. (NETL), Pittsburgh, PA, (United States); Branduardi, Davide [Italian Inst. of Technology, Genoa (Italy); Bussi, Giovanni [Univ. of Modena and Reggio Emilia and INFM-CNR (Italy); Parrinello, Michele [ETH Zurich, Lugano (Switzerland). Dept. of Chemistry and Applied Biosciences

2009-09-17

The cis-trans isomerization of N-methylacetamide (NMA), a model peptidic fragment, is studied theoretically in vacuo and in explicit water solvent at 300 K using the metadynamics technique. The computed cis-trans free energy difference is very similar for NMA(g) and NMA(aq), in agreement with experimental measurements of population ratios and theoretical studies at 0 K. By exploiting the flexibility in the definition of a pair of recently introduced collective variables (Branduardi, D.; Gervasio, F. L.; Parrinello, M. J. Chem. Phys. 2007, 126, 054103), an ensemble of transition state structures is generated at finite temperature for both NMA(g) and NMA(aq), as verified by computing committor distribution functions. Ensemble members of NMA(g) are shown to have correlated values of the backbone dihedral angle and a second dihedral angle involving the amide hydrogen atom. The dynamical character of these structures is preserved in the presence of solvent, whose influence on the committor functions can be modeled using effective friction/noise terms.

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

Energy Technology Data Exchange (ETDEWEB)

Rozentur-Shkop, Eva; Goobes, Gil; Chill, Jordan H., E-mail: Jordan.Chill@biu.ac.il [Bar Ilan University, Department of Chemistry (Israel)

2016-12-15

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({sup 15}N,{sup 13}Cα) couplings. This concept was realized using a unidirectional (H)NCO {sup 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({sup 15}N,{sup 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{sup 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

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.

A Review of Mine Rescue Ensembles for Underground Coal Mining in the United States.

Science.gov (United States)

Kilinc, F Selcen; Monaghan, William D; Powell, Jeffrey B

The mining industry is among the top ten industries nationwide with high occupational injury and fatality rates, and mine rescue response may be considered one of the most hazardous activities in mining operations. In the aftermath of an underground mine fire, explosion or water inundation, specially equipped and trained teams have been sent underground to fight fires, rescue entrapped miners, test atmospheric conditions, investigate the causes of the disaster, or recover the dead. Special personal protective ensembles are used by the team members to improve the protection of rescuers against the hazards of mine rescue and recovery. Personal protective ensembles used by mine rescue teams consist of helmet, cap lamp, hood, gloves, protective clothing, boots, kneepads, facemask, breathing apparatus, belt, and suspenders. While improved technology such as wireless warning and communication systems, lifeline pulleys, and lighted vests have been developed for mine rescuers over the last 100 years, recent research in this area of personal protective ensembles has been minimal due to the trending of reduced exposure of rescue workers. In recent years, the exposure of mine rescue teams to hazardous situations has been changing. However, it is vital that members of the teams have the capability and proper protection to immediately respond to a wide range of hazardous situations. Currently, there are no minimum requirements, best practice documents, or nationally recognized consensus standards for protective clothing used by mine rescue teams in the United States (U.S.). The following review provides a summary of potential issues that can be addressed by rescue teams and industry to improve potential exposures to rescue team members should a disaster situation occur. However, the continued trending in the mining industry toward non-exposure to potential hazards for rescue workers should continue to be the primary goal. To assist in continuing this trend, the mining industry

Scalable quantum information processing with atomic ensembles and flying photons

International Nuclear Information System (INIS)

Mei Feng; Yu Yafei; Feng Mang; Zhang Zhiming

2009-01-01

We present a scheme for scalable quantum information processing with atomic ensembles and flying photons. Using the Rydberg blockade, we encode the qubits in the collective atomic states, which could be manipulated fast and easily due to the enhanced interaction in comparison to the single-atom case. We demonstrate that our proposed gating could be applied to generation of two-dimensional cluster states for measurement-based quantum computation. Moreover, the atomic ensembles also function as quantum repeaters useful for long-distance quantum state transfer. We show the possibility of our scheme to work in bad cavity or in weak coupling regime, which could much relax the experimental requirement. The efficient coherent operations on the ensemble qubits enable our scheme to be switchable between quantum computation and quantum communication using atomic ensembles.

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...... 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...

Quasideterministic generation of maximally entangled states of two mesoscopic atomic ensembles by adiabatic quantum feedback

International Nuclear Information System (INIS)

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

2005-01-01

We introduce an efficient, quasideterministic scheme to generate maximally entangled states of two atomic ensembles. The scheme is based on quantum nondemolition measurements of total atomic populations and on adiabatic quantum feedback conditioned by the measurements outputs. The high efficiency of the scheme is tested and confirmed numerically for ideal photodetection as well as in the presence of losses

Reliability of multi-model and structurally different single-model ensembles

Energy Technology Data Exchange (ETDEWEB)

Yokohata, Tokuta [National Institute for Environmental Studies, Center for Global Environmental Research, Tsukuba, Ibaraki (Japan); Annan, James D.; Hargreaves, Julia C. [Japan Agency for Marine-Earth Science and Technology, Research Institute for Global Change, Yokohama, Kanagawa (Japan); Collins, Matthew [University of Exeter, College of Engineering, Mathematics and Physical Sciences, Exeter (United Kingdom); Jackson, Charles S.; Tobis, Michael [The University of Texas at Austin, Institute of Geophysics, 10100 Burnet Rd., ROC-196, Mail Code R2200, Austin, TX (United States); Webb, Mark J. [Met Office Hadley Centre, Exeter (United Kingdom)

2012-08-15

The performance of several state-of-the-art climate model ensembles, including two multi-model ensembles (MMEs) and four structurally different (perturbed parameter) single model ensembles (SMEs), are investigated for the first time using the rank histogram approach. In this method, the reliability of a model ensemble is evaluated from the point of view of whether the observations can be regarded as being sampled from the ensemble. Our analysis reveals that, in the MMEs, the climate variables we investigated are broadly reliable on the global scale, with a tendency towards overdispersion. On the other hand, in the SMEs, the reliability differs depending on the ensemble and variable field considered. In general, the mean state and historical trend of surface air temperature, and mean state of precipitation are reliable in the SMEs. However, variables such as sea level pressure or top-of-atmosphere clear-sky shortwave radiation do not cover a sufficiently wide range in some. It is not possible to assess whether this is a fundamental feature of SMEs generated with particular model, or a consequence of the algorithm used to select and perturb the values of the parameters. As under-dispersion is a potentially more serious issue when using ensembles to make projections, we recommend the application of rank histograms to assess reliability when designing and running perturbed physics SMEs. (orig.)

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 RUM...

Time-dependent generalized Gibbs ensembles in open quantum systems

Science.gov (United States)

Lange, Florian; Lenarčič, Zala; Rosch, Achim

2018-04-01

Generalized Gibbs ensembles have been used as powerful tools to describe the steady state of integrable many-particle quantum systems after a sudden change of the Hamiltonian. Here, we demonstrate numerically that they can be used for a much broader class of problems. We consider integrable systems in the presence of weak perturbations which break both integrability and drive the system to a state far from equilibrium. Under these conditions, we show that the steady state and the time evolution on long timescales can be accurately described by a (truncated) generalized Gibbs ensemble with time-dependent Lagrange parameters, determined from simple rate equations. We compare the numerically exact time evolutions of density matrices for small systems with a theory based on block-diagonal density matrices (diagonal ensemble) and a time-dependent generalized Gibbs ensemble containing only a small number of approximately conserved quantities, using the one-dimensional Heisenberg model with perturbations described by Lindblad operators as an example.

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 Sale...

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

Steady state ensembles of thermal radiation in a layered media with a constant heat flux

International Nuclear Information System (INIS)

Budaev, Bair V.; Bogy, David B.

2013-01-01

This paper describes steady-state ensembles of thermally excited electromagnetic radiation in nano-scale layered media with a constant non-vanishing heat flux across the layers. It is shown that Planck's law of thermal radiation, the principle of equivalence, and the laws of wave propagation in layered media, imply that in order for the ensemble of thermally excited electromagnetic fields to exist in a medium consisting of a stack of layers between two half-space, the net heat flux across the layers must exceed a certain threshold that is determined by the temperatures of the half spaces and by the reflective properties of the entire structure. The obtained results provide a way for estimating the radiative heat transfer coefficient of nano-scale layered structures. (copyright 2013 by WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

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.)

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.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 whole ensemble with its

Quark ensembles with infinite correlation length

OpenAIRE

Molodtsov, S. V.; Zinovjev, G. M.

2014-01-01

By studying quark ensembles with infinite correlation length we formulate the quantum field theory model that, as we show, is exactly integrable and develops an instability of its standard vacuum ensemble (the Dirac sea). We argue such an instability is rooted in high ground state degeneracy (for 'realistic' space-time dimensions) featuring a fairly specific form of energy distribution, and with the cutoff parameter going to infinity this inherent energy distribution becomes infinitely narrow...

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.

Resonance assignment of disordered protein with repetitive and overlapping sequence using combinatorial approach reveals initial structural propensities and local restrictions in the denatured state

Energy Technology Data Exchange (ETDEWEB)

Malik, Nikita; Kumar, Ashutosh, E-mail: askutoshk@iitb.ac.in [Indian Institute of Technology Bombay, Department of Bioscience and Bioengineering (India)

2016-09-15

NMR resonance assignment of intrinsically disordered proteins poses a challenge because of the limited dispersion of amide proton chemical shifts. This becomes even more complex with the increase in the size of the system. Residue specific selective labeling/unlabeling experiments have been used to resolve the overlap, but require multiple sample preparations. Here, we demonstrate an assignment strategy requiring only a single sample of uniformly labeled {sup 13}C,{sup 15}N-protein. We have used a combinatorial approach, involving 3D-HNN, CC(CO)NH and 2D-MUSIC, which allowed us to assign a denatured centromeric protein Cse4 of 229 residues. Further, we show that even the less sensitive experiments, when used in an efficient manner can lead to the complete assignment of a complex system without the use of specialized probes in a relatively short time frame. The assignment of the amino acids discloses the presence of local structural propensities even in the denatured state accompanied by restricted motion in certain regions that provides insights into the early folding events of the protein.

Resonance assignment of disordered protein with repetitive and overlapping sequence using combinatorial approach reveals initial structural propensities and local restrictions in the denatured state

International Nuclear Information System (INIS)

Malik, Nikita; Kumar, Ashutosh

2016-01-01

NMR resonance assignment of intrinsically disordered proteins poses a challenge because of the limited dispersion of amide proton chemical shifts. This becomes even more complex with the increase in the size of the system. Residue specific selective labeling/unlabeling experiments have been used to resolve the overlap, but require multiple sample preparations. Here, we demonstrate an assignment strategy requiring only a single sample of uniformly labeled "1"3C,"1"5N-protein. We have used a combinatorial approach, involving 3D-HNN, CC(CO)NH and 2D-MUSIC, which allowed us to assign a denatured centromeric protein Cse4 of 229 residues. Further, we show that even the less sensitive experiments, when used in an efficient manner can lead to the complete assignment of a complex system without the use of specialized probes in a relatively short time frame. The assignment of the amino acids discloses the presence of local structural propensities even in the denatured state accompanied by restricted motion in certain regions that provides insights into the early folding events of the protein.

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.

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.

Multivariate localization methods for ensemble Kalman filtering

KAUST Repository

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

2015-01-01

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 (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.

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.

Vibrational energy relaxation: proposed pathway of fast local chromatin denaturation

International Nuclear Information System (INIS)

Harder, D.; Greinert, R.

2002-01-01

The molecular mechanism responsible for the a component of exchange-type chromosome aberrations, of chromosome fragmentation and of reproductive cell death is one of the unsolved issues of radiation biology. Under review is whether vibrational energy relaxation in the constitutive biopolymers of chromatin, induced by inelastic energy deposition events and mediated via highly excited vibrational states, may provide a pathway of fast local chromatin denaturation, thereby producing the severe DNA lesion able to interact chemically with other, non-damaged chromatin. (author)

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...

Adiabatic passage and ensemble control of quantum systems

International Nuclear Information System (INIS)

Leghtas, Z; Sarlette, A; Rouchon, P

2011-01-01

This paper considers population transfer between eigenstates of a finite quantum ladder controlled by a classical electric field. Using an appropriate change of variables, we show that this setting can be set in the framework of adiabatic passage, which is known to facilitate ensemble control of quantum systems. Building on this insight, we present a mathematical proof of robustness for a control protocol-chirped pulse-practised by experimentalists to drive an ensemble of quantum systems from the ground state to the most excited state. We then propose new adiabatic control protocols using a single chirped and amplitude-shaped pulse, to robustly perform any permutation of eigenstate populations, on an ensemble of systems with unknown coupling strengths. These adiabatic control protocols are illustrated by simulations on a four-level ladder.

Single-particle model of a strongly driven, dense, nanoscale quantum ensemble

Science.gov (United States)

DiLoreto, C. S.; Rangan, C.

2018-01-01

We study the effects of interatomic interactions on the quantum dynamics of a dense, nanoscale, atomic ensemble driven by a strong electromagnetic field. We use a self-consistent, mean-field technique based on the pseudospectral time-domain method and a full, three-directional basis to solve the coupled Maxwell-Liouville equations. We find that interatomic interactions generate a decoherence in the state of an ensemble on a much faster time scale than the excited-state lifetime of individual atoms. We present a single-particle model of the driven, dense ensemble by incorporating interactions into a dephasing rate. This single-particle model reproduces the essential physics of the full simulation and is an efficient way of rapidly estimating the collective dynamics of a dense ensemble.

Quark ensembles with the infinite correlation length

Science.gov (United States)

Zinov'ev, G. M.; Molodtsov, S. V.

2015-01-01

A number of exactly integrable (quark) models of quantum field theory with the infinite correlation length have been considered. It has been shown that the standard vacuum quark ensemble—Dirac sea (in the case of the space-time dimension higher than three)—is unstable because of the strong degeneracy of a state, which is due to the character of the energy distribution. When the momentum cutoff parameter tends to infinity, the distribution becomes infinitely narrow, leading to large (unlimited) fluctuations. Various vacuum ensembles—Dirac sea, neutral ensemble, color superconductor, and BCS state—have been compared. In the case of the color interaction between quarks, the BCS state has been certainly chosen as the ground state of the quark ensemble.

Quark ensembles with the infinite correlation length

International Nuclear Information System (INIS)

Zinov’ev, G. M.; Molodtsov, S. V.

2015-01-01

A number of exactly integrable (quark) models of quantum field theory with the infinite correlation length have been considered. It has been shown that the standard vacuum quark ensemble—Dirac sea (in the case of the space-time dimension higher than three)—is unstable because of the strong degeneracy of a state, which is due to the character of the energy distribution. When the momentum cutoff parameter tends to infinity, the distribution becomes infinitely narrow, leading to large (unlimited) fluctuations. Various vacuum ensembles—Dirac sea, neutral ensemble, color superconductor, and BCS state—have been compared. In the case of the color interaction between quarks, the BCS state has been certainly chosen as the ground state of the quark ensemble

Quark ensembles with the infinite correlation length

Energy Technology Data Exchange (ETDEWEB)

Zinov’ev, G. M. [National Academy of Sciences of Ukraine, Bogoliubov Institute for Theoretical Physics (Ukraine); Molodtsov, S. V., E-mail: molodtsov@itep.ru [Joint Institute for Nuclear Research (Russian Federation)

2015-01-15

A number of exactly integrable (quark) models of quantum field theory with the infinite correlation length have been considered. It has been shown that the standard vacuum quark ensemble—Dirac sea (in the case of the space-time dimension higher than three)—is unstable because of the strong degeneracy of a state, which is due to the character of the energy distribution. When the momentum cutoff parameter tends to infinity, the distribution becomes infinitely narrow, leading to large (unlimited) fluctuations. Various vacuum ensembles—Dirac sea, neutral ensemble, color superconductor, and BCS state—have been compared. In the case of the color interaction between quarks, the BCS state has been certainly chosen as the ground state of the quark ensemble.

Heavy water reactors on the denatured thorium cycles

International Nuclear Information System (INIS)

1978-05-01

This paper presents preliminary technical and economic data to INFCE on the denatured U-233/Thorium fuel cycle for use in early comparisons of alternate nuclear systems. The once-through uranium fuel cycle is discussed in a companion paper. In presenting this preliminary information at this time, it is recognized that there are several other denatured thorium fuel cycles of potential interest, such as the U-235/thorium cycle which could be implemented at an earlier date. Information on these alternate cycles is currently being developed, and will be provided to INFCE when available

An Efficient State–Parameter Filtering Scheme Combining Ensemble Kalman and Particle Filters

KAUST Repository

Ait-El-Fquih, Boujemaa

2017-12-11

This work addresses the state-parameter filtering problem for dynamical systems with relatively large-dimensional state and low-dimensional parameters\\' vector. A Bayesian filtering algorithm combining the strengths of the particle filter (PF) and the ensemble Kalman filter (EnKF) is proposed. At each assimilation cycle of the proposed EnKF-PF, the PF is first used to sample the parameters\\' ensemble followed by the EnKF to compute the state ensemble conditional on the resulting parameters\\' ensemble. The proposed scheme is expected to be more efficient than the traditional state augmentation techniques, which suffer from the curse of dimensionality and inconsistency that is particularly pronounced when the state is a strongly nonlinear function of the parameters. In the new scheme, the EnKF and PF interact via their ensembles\\' members, in contrast with the recently introduced two-stage EnKF-PF (TS-EnKF-PF), which exchanges point estimates between EnKF and PF while requiring almost double the computational load. Numerical experiments are conducted with the Lorenz-96 model to assess the behavior of the proposed filter and to evaluate its performances against the joint PF, joint EnKF, and TS-EnKF-PF. Numerical results suggest that the EnKF-PF performs best in all tested scenarios. It was further found to be more robust, successfully estimating both state and parameters in different sensitivity experiments.

An Efficient State–Parameter Filtering Scheme Combining Ensemble Kalman and Particle Filters

KAUST Repository

Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim

2017-01-01

This work addresses the state-parameter filtering problem for dynamical systems with relatively large-dimensional state and low-dimensional parameters' vector. A Bayesian filtering algorithm combining the strengths of the particle filter (PF) and the ensemble Kalman filter (EnKF) is proposed. At each assimilation cycle of the proposed EnKF-PF, the PF is first used to sample the parameters' ensemble followed by the EnKF to compute the state ensemble conditional on the resulting parameters' ensemble. The proposed scheme is expected to be more efficient than the traditional state augmentation techniques, which suffer from the curse of dimensionality and inconsistency that is particularly pronounced when the state is a strongly nonlinear function of the parameters. In the new scheme, the EnKF and PF interact via their ensembles' members, in contrast with the recently introduced two-stage EnKF-PF (TS-EnKF-PF), which exchanges point estimates between EnKF and PF while requiring almost double the computational load. Numerical experiments are conducted with the Lorenz-96 model to assess the behavior of the proposed filter and to evaluate its performances against the joint PF, joint EnKF, and TS-EnKF-PF. Numerical results suggest that the EnKF-PF performs best in all tested scenarios. It was further found to be more robust, successfully estimating both state and parameters in different sensitivity experiments.

Improving Climate Projections Using "Intelligent" Ensembles

Science.gov (United States)

Baker, Noel C.; Taylor, Patrick C.

2015-01-01

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and

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).

Interim assessment of the denatured 233U fuel cycle: feasibility and nonproliferation characteristics

International Nuclear Information System (INIS)

Abbott, L.S.; Bartine, D.E.; Burns, T.J.

1979-12-01

A fuel cycle that employs 233 U denatured with 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 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 233 U cycles are compared to those of the conventional Pu/U cycle. In addition, several nuclear power systems that employ denatured 233 U fuel and are based on the energy center concept are evaluated

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.

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.

On Ensemble Nonlinear Kalman Filtering with Symmetric Analysis Ensembles

KAUST Repository

Luo, Xiaodong; Hoteit, Ibrahim; Moroz, Irene M.

2010-01-01

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].

Internal Spin Control, Squeezing and Decoherence in Ensembles of Alkali Atomic Spins

Science.gov (United States)

Norris, Leigh Morgan

Large atomic ensembles interacting with light are one of the most promising platforms for quantum information processing. In the past decade, novel applications for these systems have emerged in quantum communication, quantum computing, and metrology. Essential to all of these applications is the controllability of the atomic ensemble, which is facilitated by a strong coupling between the atoms and light. Non-classical spin squeezed states are a crucial step in attaining greater ensemble control. The degree of entanglement present in these states, furthermore, serves as a benchmark for the strength of the atom-light interaction. Outside the broader context of quantum information processing with atomic ensembles, spin squeezed states have applications in metrology, where their quantum correlations can be harnessed to improve the precision of magnetometers and atomic clocks. This dissertation focuses upon the production of spin squeezed states in large ensembles of cold trapped alkali atoms interacting with optical fields. While most treatments of spin squeezing consider only the case in which the ensemble is composed of two level systems or qubits, we utilize the entire ground manifold of an alkali atom with hyperfine spin f greater than or equal to 1/2, a qudit. Spin squeezing requires non-classical correlations between the constituent atomic spins, which are generated through the atoms' collective coupling to the light. Either through measurement or multiple interactions with the atoms, the light mediates an entangling interaction that produces quantum correlations. Because the spin squeezing treated in this dissertation ultimately originates from the coupling between the light and atoms, conventional approaches of improving this squeezing have focused on increasing the optical density of the ensemble. The greater number of internal degrees of freedom and the controllability of the spin-f ground hyperfine manifold enable novel methods of enhancing squeezing. In

An ensemble classifier to predict track geometry degradation

International Nuclear Information System (INIS)

Cárdenas-Gallo, Iván; Sarmiento, Carlos A.; Morales, Gilberto A.; Bolivar, Manuel A.; Akhavan-Tabatabaei, Raha

2017-01-01

Railway operations are inherently complex and source of several problems. In particular, track geometry defects are one of the leading causes of train accidents in the United States. This paper presents a solution approach which entails the construction of an ensemble classifier to forecast the degradation of track geometry. Our classifier is constructed by solving the problem from three different perspectives: deterioration, regression and classification. We considered a different model from each perspective and our results show that using an ensemble method improves the predictive performance. - Highlights: • We present an ensemble classifier to forecast the degradation of track geometry. • Our classifier considers three perspectives: deterioration, regression and classification. • We construct and test three models and our results show that using an ensemble method improves the predictive performance.

Precision bounds for gradient magnetometry with atomic ensembles

Science.gov (United States)

Apellaniz, Iagoba; Urizar-Lanz, Iñigo; Zimborás, Zoltán; Hyllus, Philipp; Tóth, Géza

2018-05-01

We study gradient magnetometry with an ensemble of atoms with arbitrary spin. We calculate precision bounds for estimating the gradient of the magnetic field based on the quantum Fisher information. For quantum states that are invariant under homogeneous magnetic fields, we need to measure a single observable to estimate the gradient. On the other hand, for states that are sensitive to homogeneous fields, a simultaneous measurement is needed, as the homogeneous field must also be estimated. We prove that for the cases studied in this paper, such a measurement is feasible. We present a method to calculate precision bounds for gradient estimation with a chain of atoms or with two spatially separated atomic ensembles. We also consider a single atomic ensemble with an arbitrary density profile, where the atoms cannot be addressed individually, and which is a very relevant case for experiments. Our model can take into account even correlations between particle positions. While in most of the discussion we consider an ensemble of localized particles that are classical with respect to their spatial degree of freedom, we also discuss the case of gradient metrology with a single Bose-Einstein condensate.

Exact method for numerically analyzing a model of local denaturation in superhelically stressed DNA

International Nuclear Information System (INIS)

Fye, R.M.; Benham, C.J.

1999-01-01

Local denaturation, the separation at specific sites of the two strands comprising the DNA double helix, is one of the most fundamental processes in biology, required to allow the base sequence to be read both in DNA transcription and in replication. In living organisms this process can be mediated by enzymes which regulate the amount of superhelical stress imposed on the DNA. We present a numerically exact technique for analyzing a model of denaturation in superhelically stressed DNA. This approach is capable of predicting the locations and extents of transition in circular superhelical DNA molecules of kilobase lengths and specified base pair sequences. It can also be used for closed loops of DNA which are typically found in vivo to be kilobases long. The analytic method consists of an integration over the DNA twist degrees of freedom followed by the introduction of auxiliary variables to decouple the remaining degrees of freedom, which allows the use of the transfer matrix method. The algorithm implementing our technique requires O(N 2 ) operations and O(N) memory to analyze a DNA domain containing N base pairs. However, to analyze kilobase length DNA molecules it must be implemented in high precision floating point arithmetic. An accelerated algorithm is constructed by imposing an upper bound M on the number of base pairs that can simultaneously denature in a state. This accelerated algorithm requires O(MN) operations, and has an analytically bounded error. Sample calculations show that it achieves high accuracy (greater than 15 decimal digits) with relatively small values of M (M<0.05N) for kilobase length molecules under physiologically relevant conditions. Calculations are performed on the superhelical pBR322 DNA sequence to test the accuracy of the method. With no free parameters in the model, the locations and extents of local denaturation predicted by this analysis are in quantitatively precise agreement with in vitro experimental measurements

Temporal intermittency and the lifetime of chimera states in ensembles of nonlocally coupled chaotic oscillators

Science.gov (United States)

Semenova, N. I.; Strelkova, G. I.; Anishchenko, V. S.; Zakharova, A.

2017-06-01

We describe numerical results for the dynamics of networks of nonlocally coupled chaotic maps. Switchings in time between amplitude and phase chimera states have been first established and studied. It has been shown that in autonomous ensembles, a nonstationary regime of switchings has a finite lifetime and represents a transient process towards a stationary regime of phase chimera. The lifetime of the nonstationary switching regime can be increased to infinity by applying short-term noise perturbations.

27 CFR 20.148 - Manufacture of articles with completely denatured alcohol.

Science.gov (United States)

2010-04-01

... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Manufacture of articles with completely denatured alcohol. 20.148 Section 20.148 Alcohol, Tobacco Products and Firearms ALCOHOL... ALCOHOL AND RUM Sale and Use of Completely Denatured Alcohol § 20.148 Manufacture of articles with...

Momentum distribution functions in ensembles: the inequivalence of microcannonical and canonical ensembles in a finite ultracold system.

Science.gov (United States)

Wang, Pei; Xianlong, Gao; Li, Haibin

2013-08-01

It is demonstrated in many thermodynamic textbooks that the equivalence of the different ensembles is achieved in the thermodynamic limit. In this present work we discuss the inequivalence of microcanonical and canonical ensembles in a finite ultracold system at low energies. We calculate the microcanonical momentum distribution function (MDF) in a system of identical fermions (bosons). We find that the microcanonical MDF deviates from the canonical one, which is the Fermi-Dirac (Bose-Einstein) function, in a finite system at low energies where the single-particle density of states and its inverse are finite.

Microcanonical ensemble extensive thermodynamics of Tsallis statistics

International Nuclear Information System (INIS)

Parvan, A.S.

2005-01-01

The microscopic foundation of the generalized equilibrium statistical mechanics based on the Tsallis entropy is given by using the Gibbs idea of statistical ensembles of the classical and quantum mechanics.The equilibrium distribution functions are derived by the thermodynamic method based upon the use of the fundamental equation of thermodynamics and the statistical definition of the functions of the state of the system. It is shown that if the entropic index ξ = 1/q - 1 in the microcanonical ensemble is an extensive variable of the state of the system, then in the thermodynamic limit z bar = 1/(q - 1)N = const the principle of additivity and the zero law of thermodynamics are satisfied. In particular, the Tsallis entropy of the system is extensive and the temperature is intensive. Thus, the Tsallis statistics completely satisfies all the postulates of the equilibrium thermodynamics. Moreover, evaluation of the thermodynamic identities in the microcanonical ensemble is provided by the Euler theorem. The principle of additivity and the Euler theorem are explicitly proved by using the illustration of the classical microcanonical ideal gas in the thermodynamic limit

Microcanonical ensemble extensive thermodynamics of Tsallis statistics

International Nuclear Information System (INIS)

Parvan, A.S.

2006-01-01

The microscopic foundation of the generalized equilibrium statistical mechanics based on the Tsallis entropy is given by using the Gibbs idea of statistical ensembles of the classical and quantum mechanics. The equilibrium distribution functions are derived by the thermodynamic method based upon the use of the fundamental equation of thermodynamics and the statistical definition of the functions of the state of the system. It is shown that if the entropic index ξ=1/(q-1) in the microcanonical ensemble is an extensive variable of the state of the system, then in the thermodynamic limit z-bar =1/(q-1)N=const the principle of additivity and the zero law of thermodynamics are satisfied. In particular, the Tsallis entropy of the system is extensive and the temperature is intensive. Thus, the Tsallis statistics completely satisfies all the postulates of the equilibrium thermodynamics. Moreover, evaluation of the thermodynamic identities in the microcanonical ensemble is provided by the Euler theorem. The principle of additivity and the Euler theorem are explicitly proved by using the illustration of the classical microcanonical ideal gas in the thermodynamic limit

Preparation of denatured protein bone sterilized with gamma radiation

International Nuclear Information System (INIS)

Luna Z, D.

2005-01-01

The bone is one of the tissues more transplanted in the entire world by that the bone necessity for transplant every day becomes bigger. In the Bank of tissues Radio sterilized of the ININ the amnion and the pig skin are routinely processed. The tissue with which will be continued is with bone. Due to that in our country it doesn't have enough bone of human origin for the necessities required in the bone transplant, an option is the bone of bovine. Of this bone one can obtain denatured protein bone, with the same characteristics of the denatured protein human bone, the one which has been proven that it has good acceptance and incorporation in the human body when is transplanted. The method for the obtaining of the denatured protein bone of bovine, with the confirmation of the final product by means of X-ray diffraction is described. The radiosterilization of this bone with gamma rays and the determination of the lead content. (Author)

Reproducing multi-model ensemble average with Ensemble-averaged Reconstructed Forcings (ERF) in regional climate modeling

Science.gov (United States)

Erfanian, A.; Fomenko, L.; Wang, G.

2016-12-01

Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling

Mutation of charged residues to neutral ones accelerates urea denaturation of HP-35.

Science.gov (United States)

Wei, Haiyan; Yang, Lijiang; Gao, Yi Qin

2010-09-16

Following the studies of urea denaturation of β-hairpins using molecular dynamics, in this paper, molecular dynamics simulations of two peptides, a 35 residue three helix bundle villin headpiece protein HP-35 and its doubly norleucine-substituent mutant (Lys24Nle/Lys29Nle) HP-35 NleNle, were undertaken in urea solutions to understand the molecular mechanism of urea denaturation of α-helices. The mutant HP-35 NleNle was found to denature more easily than the wild type. During the expansion of the small hydrophobic core, water penetration occurs first, followed by that of urea molecules. It was also found that the initial hydration of the peptide backbone is achieved through water hydrogen bonding with the backbone CO groups during the denaturation of both polypeptides. The mutation of the two charged lysine residues to apolar norleucine enhances the accumulation of urea near the hydrophobic core and facilitates the denaturation process. Urea also interacts directly with the peptide backbone as well as side chains, thereby stabilizing nonnative conformations. The mechanism revealed here is consistent with the previous study on secondary structure of β-hairpin polypeptide, GB1, PEPTIDE 1, and TRPZIP4, suggesting that there is a general mechanism in the denaturation of protein backbone hydrogen bonds by urea.

Interim assessment of the denatured 233U fuel cycle: feasibility and nonproliferation characteristics

International Nuclear Information System (INIS)

Abbott, L.S.; Bartine, D.E.; Burns, T.J.

1978-12-01

A fuel cycle that employs 233 U denatured with 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 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 233 U cycles are compared to those of the conventional Pu/U cycle. In addition, several nuclear power systems that employ denatured 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 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

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.

Mesoscopic modeling of DNA denaturation rates: Sequence dependence and experimental comparison

Energy Technology Data Exchange (ETDEWEB)

Dahlen, Oda, E-mail: oda.dahlen@ntnu.no; Erp, Titus S. van, E-mail: titus.van.erp@ntnu.no [Department of Chemistry, Norwegian University of Science and Technology (NTNU), Høgskoleringen 5, Realfagbygget D3-117 7491 Trondheim (Norway)

2015-06-21

Using rare event simulation techniques, we calculated DNA denaturation rate constants for a range of sequences and temperatures for the Peyrard-Bishop-Dauxois (PBD) model with two different parameter sets. We studied a larger variety of sequences compared to previous studies that only consider DNA homopolymers and DNA sequences containing an equal amount of weak AT- and strong GC-base pairs. Our results show that, contrary to previous findings, an even distribution of the strong GC-base pairs does not always result in the fastest possible denaturation. In addition, we applied an adaptation of the PBD model to study hairpin denaturation for which experimental data are available. This is the first quantitative study in which dynamical results from the mesoscopic PBD model have been compared with experiments. Our results show that present parameterized models, although giving good results regarding thermodynamic properties, overestimate denaturation rates by orders of magnitude. We believe that our dynamical approach is, therefore, an important tool for verifying DNA models and for developing next generation models that have higher predictive power than present ones.

Role of cyclobutane dimers in UV-denaturation of DNA

International Nuclear Information System (INIS)

Zavil'gel'skij, G.B.; Zuev, A.V.

1978-01-01

UV irradiation of double-stranded DNA produces local denatured regions. The evidence presented indicates that these single-stranded regions arise from photoproducts other than pyrimidine dimers. The irradiation of T2 DNA at 8x10 4 erg/mm 2 (254 nm) produces 6-8% thymine dimers, amd Tsub(mel) drops by 12-14 deg C, accompanied by a significant broadening of the transition profile. The kinetics of denatured region formation and lowering Tsub(mel) corresponds to that of formation of crosslinkages and differs markedly from the kinetics of formation of cyclobutane pyrimidine dimers. Treatment of UV-irradiated DNA with light in the presence of yeast photoreactivating enzyme monomerizes almost all thymine dimers but does not change the Tsub(mel). Local denatured regions are detected in UV-irradiated DNA and are absent from AcPhM-sensibilized DNA, which contains 20-25% thymine dimers, as determined by the accridine orange fluorescence technique. S1 nuclease from Aspergillis oryzae produces single-strand breaks in UV-irradiated DNA of phage PM2 but is not active on AcPhM-treated PM2 DNA, which contains about 50 thymine dimers. It is supposed that the formation of a cyclobutane dimer only weakens the hydrogen bonds in the AT base pair rather than breaks them. Local denatured regions are thought to arise from the accumulation in UV-irradiated DNA (254 nm) of the sufficient number of photoproducts with impaired ability to base pairing

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.

Interpolation of property-values between electron numbers is inconsistent with ensemble averaging

Energy Technology Data Exchange (ETDEWEB)

Miranda-Quintana, Ramón Alain [Laboratory of Computational and Theoretical Chemistry, Faculty of Chemistry, University of Havana, Havana (Cuba); Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario L8S 4M1 (Canada); Ayers, Paul W. [Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario L8S 4M1 (Canada)

2016-06-28

In this work we explore the physical foundations of models that study the variation of the ground state energy with respect to the number of electrons (E vs. N models), in terms of general grand-canonical (GC) ensemble formulations. In particular, we focus on E vs. N models that interpolate the energy between states with integer number of electrons. We show that if the interpolation of the energy corresponds to a GC ensemble, it is not differentiable. Conversely, if the interpolation is smooth, then it cannot be formulated as any GC ensemble. This proves that interpolation of electronic properties between integer electron numbers is inconsistent with any form of ensemble averaging. This emphasizes the role of derivative discontinuities and the critical role of a subsystem’s surroundings in determining its properties.

High-Temperature unfolding of a trp-Cage mini-protein: a molecular dynamics simulation study

Directory of Open Access Journals (Sweden)

Seshasayee Aswin Sai Narain

2005-03-01

Full Text Available Abstract Background Trp cage is a recently-constructed fast-folding miniprotein. It consists of a short helix, a 3,10 helix and a C-terminal poly-proline that packs against a Trp in the alpha helix. It is known to fold within 4 ns. Results High-temperature unfolding molecular dynamics simulations of the Trp cage miniprotein have been carried out in explicit water using the OPLS-AA force-field incorporated in the program GROMACS. The radius of gyration (Rg and Root Mean Square Deviation (RMSD have been used as order parameters to follow the unfolding process. Distributions of Rg were used to identify ensembles. Conclusion Three ensembles could be identified. While the native-state ensemble shows an Rg distribution that is slightly skewed, the second ensemble, which is presumably the Transition State Ensemble (TSE, shows an excellent fit. The denatured ensemble shows large fluctuations, but a Gaussian curve could be fitted. This means that the unfolding process is two-state. Representative structures from each of these ensembles are presented here.

Ensembl 2004.

Science.gov (United States)

Birney, E; Andrews, D; Bevan, P; Caccamo, M; Cameron, G; Chen, Y; Clarke, L; Coates, G; Cox, T; Cuff, J; Curwen, V; Cutts, T; Down, T; Durbin, R; Eyras, E; Fernandez-Suarez, X M; Gane, P; Gibbins, B; Gilbert, J; Hammond, M; Hotz, H; Iyer, V; Kahari, A; Jekosch, K; Kasprzyk, A; Keefe, D; Keenan, S; Lehvaslaiho, H; McVicker, G; Melsopp, C; Meidl, P; Mongin, E; Pettett, R; Potter, S; Proctor, G; Rae, M; Searle, S; Slater, G; Smedley, D; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Storey, R; Ureta-Vidal, A; Woodwark, C; Clamp, M; Hubbard, T

2004-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organize biology around the sequences of large genomes. It is a comprehensive and integrated source of annotation of large genome sequences, available via interactive website, web services or flat files. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. The facilities of the system range from sequence analysis to data storage and visualization and installations exist around the world both in companies and at academic sites. With a total of nine genome sequences available from Ensembl and more genomes to follow, recent developments have focused mainly on closer integration between genomes and external data.

The expression and proangiogenic effect of nucleolin during the recovery of heat-denatured HUVECs.

Science.gov (United States)

Liang, Pengfei; Jiang, Bimei; Lv, Chunliu; Huang, Xu; Sun, Li; Zhang, Pihong; Huang, Xiaoyuan

2013-10-01

The present study aims to examine the expression patterns and roles of nucleolin during the recovery of heat-denatured human umbilical vein endothelial cells (HUVECs). Deep partial thickness burn model in Sprague-Dawley rats and the heat denatured cell model (52°C, 35s) were used. The expression of nucleolin was measured using Western blot analysis and real-time PCR. Angiogenesis was assessed using in vitro parameters including endothelial cell proliferation, transwell migration assay, and scratched wound healing. Gene transfection and RNA interference approaches were employed to investigate the roles of nucleolin. Nucleolin mRNA and protein expression showed a time-dependent increase during the recovery of heat-denatured dermis and HUVECs. Heat-denaturation time-dependently promoted cell growth, adhesion, migration, scratched wound healing and formation of tube-like structures in HUVECs. These effects of heat denaturation on endothelial wound healing and formation of tube-like structures were prevented by knockdown of nucleolin, whereas over-expression of nucleolin increased cell growth, migration, and formation of tube-like structures in cultured HUVEC endothelial cells. In addition, we found that the expression of vascular endothelial growth factor (VEGF) increased during the recovery of heat-denatured dermis and HUVECs, and nucleolin up-regulated VEGF in HUVECs. The present study reveals that the expression of nucleolin is up-regulated, and plays a pro-angiogenic role during the recovery of heat-denatured dermis and its mechanism is probably dependent on production of VEGF. We find a novel and important pro-angiogenic role of nucleolin during the recovery of heat-denatured dermis. Copyright © 2013 Elsevier B.V. All rights reserved.

Cation-Induced Stabilization and Denaturation of DNA Origami Nanostructures in Urea and Guanidinium Chloride.

Science.gov (United States)

Ramakrishnan, Saminathan; Krainer, Georg; Grundmeier, Guido; Schlierf, Michael; Keller, Adrian

2017-11-01

The stability of DNA origami nanostructures under various environmental conditions constitutes an important issue in numerous applications, including drug delivery, molecular sensing, and single-molecule biophysics. Here, the effect of Na + and Mg 2+ concentrations on DNA origami stability is investigated in the presence of urea and guanidinium chloride (GdmCl), two strong denaturants commonly employed in protein folding studies. While increasing concentrations of both cations stabilize the DNA origami nanostructures against urea denaturation, they are found to promote DNA origami denaturation by GdmCl. These inverse behaviors are rationalized by a salting-out of Gdm + to the hydrophobic DNA base stack. The effect of cation-induced DNA origami denaturation by GdmCl deserves consideration in the design of single-molecule studies and may potentially be exploited in future applications such as selective denaturation for purification purposes. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ensemble Kalman filtering with residual nudging

KAUST Repository

Luo, X.; Hoteit, Ibrahim

2012-01-01

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

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.

Ensemble Kalman methods for inverse problems

International Nuclear Information System (INIS)

Iglesias, Marco A; Law, Kody J H; Stuart, Andrew M

2013-01-01

The ensemble Kalman filter (EnKF) was introduced by Evensen in 1994 (Evensen 1994 J. Geophys. Res. 99 10143–62) as a novel method for data assimilation: state estimation for noisily observed time-dependent problems. Since that time it has had enormous impact in many application domains because of its robustness and ease of implementation, and numerical evidence of its accuracy. In this paper we propose the application of an iterative ensemble Kalman method for the solution of a wide class of inverse problems. In this context we show that the estimate of the unknown function that we obtain with the ensemble Kalman method lies in a subspace A spanned by the initial ensemble. Hence the resulting error may be bounded above by the error found from the best approximation in this subspace. We provide numerical experiments which compare the error incurred by the ensemble Kalman method for inverse problems with the error of the best approximation in A, and with variants on traditional least-squares approaches, restricted to the subspace A. In so doing we demonstrate that the ensemble Kalman method for inverse problems provides a derivative-free optimization method with comparable accuracy to that achieved by traditional least-squares approaches. Furthermore, we also demonstrate that the accuracy is of the same order of magnitude as that achieved by the best approximation. Three examples are used to demonstrate these assertions: inversion of a compact linear operator; inversion of piezometric head to determine hydraulic conductivity in a Darcy model of groundwater flow; and inversion of Eulerian velocity measurements at positive times to determine the initial condition in an incompressible fluid. (paper)

A variational ensemble scheme for noisy image data assimilation

Science.gov (United States)

Yang, Yin; Robinson, Cordelia; Heitz, Dominique; Mémin, Etienne

2014-05-01

Data assimilation techniques aim at recovering a system state variables trajectory denoted as X, along time from partially observed noisy measurements of the system denoted as Y. These procedures, which couple dynamics and noisy measurements of the system, fulfill indeed a twofold objective. On one hand, they provide a denoising - or reconstruction - procedure of the data through a given model framework and on the other hand, they provide estimation procedures for unknown parameters of the dynamics. A standard variational data assimilation problem can be formulated as the minimization of the following objective function with respect to the initial discrepancy, η, from the background initial guess: δ« J(η(x)) = 1∥Xb (x) - X (t ,x)∥2 + 1 tf∥H(X (t,x ))- Y (t,x)∥2dt. 2 0 0 B 2 t0 R (1) where the observation operator H links the state variable and the measurements. The cost function can be interpreted as the log likelihood function associated to the a posteriori distribution of the state given the past history of measurements and the background. In this work, we aim at studying ensemble based optimal control strategies for data assimilation. Such formulation nicely combines the ingredients of ensemble Kalman filters and variational data assimilation (4DVar). It is also formulated as the minimization of the objective function (1), but similarly to ensemble filter, it introduces in its objective function an empirical ensemble-based background-error covariance defined as: B ≡ )(Xb - )T>. (2) Thus, it works in an off-line smoothing mode rather than on the fly like sequential filters. Such resulting ensemble variational data assimilation technique corresponds to a relatively new family of methods [1,2,3]. It presents two main advantages: first, it does not require anymore to construct the adjoint of the dynamics tangent linear operator, which is a considerable advantage with respect to the method's implementation, and second, it enables the handling of a flow

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.

Neutronics calculations for denatured molten salt reactors: Assessing resource requirements and proliferation-risk attributes

International Nuclear Information System (INIS)

Ahmad, Ali; McClamrock, Edward B.; Glaser, Alexander

2015-01-01

Highlights: • We study the proliferation-risk and resource attributes of denatured MSRs. • MSRs offer significantly better resource efficiency compared to light-water reactors. • Denatured single-fluid MSRs reactors offer promising non-proliferation attributes. - Abstract: Molten salt reactors (MSRs) are often advocated as a radical but worthwhile alternative to traditional reactor concepts based on solid fuels. This article builds upon the existing research into MSRs to model and simulate the operation of thorium-fueled single-fluid and two-fluid reactors. The analysis is based on neutronics calculations and focuses on denatured MSR systems. Resource utilization and basic proliferation-risk attributes are compared to those of standard light-water reactors. Depending on specific design choices, even fully denatured reactors could reduce uranium and enrichment requirements by a factor of 3–4. Overall, denatured single-fluid designs appear as the most promising candidate technology minimizing both design complexity and overall proliferation risks despite being somewhat less attractive from the perspective of resource utilization

Improved spin squeezing of an atomic ensemble through internal state control

Science.gov (United States)

Hemmer, Daniel; Montano, Enrique; Deutsch, Ivan; Jessen, Poul

2016-05-01

Squeezing of collective atomic spins is typically generated by quantum backaction from a QND measurement of the relevant spin component. In this scenario the degree of squeezing is determined by the measurement resolution relative to the quantum projection noise (QPN) of a spin coherent state (SCS). Greater squeezing can be achieved through optimization of the 3D geometry of probe and atom cloud, or by placing the atoms in an optical cavity. We explore here a complementary strategy that relies on quantum control of the large internal spin available in alkali atoms such as Cs. Using a combination of rf and uw magnetic fields, we coherently map the internal spins in our ensemble from the SCS (| f = 4, m = 4>) to a ``cat'' state which is an equal superposition of | f = 4, m = 4>and | f = 4, m = -4>. This increases QPN by a factor of 2 f = 8 relative to the SCS, and therefore the amount of backaction and spin-spin entanglement produced by our QND measurement. In a final step, squeezing generated in the cat state basis can be mapped back to the SCS basis, where it corresponds to increased squeezing of the physical spin. Our experiments suggest that up to 8dB of metrologically useful squeezing can be generated in this way, compared to ~ 3 dB in an otherwise identical experiment starting from a SCS.

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.

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

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.

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.

Glutamate Induced Thermal Equilibrium Intermediate and Counteracting Effect on Chemical Denaturation of Proteins.

Science.gov (United States)

Anumalla, Bramhini; Prabhu, N Prakash

2018-01-25

When organisms are subjected to stress conditions, one of their adaptive responses is accumulation of small organic molecules called osmolytes. These osmolytes affect the structure and stability of the biological macromolecules including proteins. The present study examines the effect of a negatively charged amino acid osmolyte, glutamate (Glu), on two model proteins, ribonuclease A (RNase A) and α-lactalbumin (α-LA), which have positive and negative surface charges at pH 7, respectively. These proteins follow two-state unfolding transitions during both heat and chemical induced denaturation processes. The addition of Glu stabilizes the proteins against temperature and induces an early equilibrium intermediate during unfolding. The stability is found to be enthalpy-driven, and the free energy of stabilization is more for α-LA compared to RNase A. The decrease in the partial molar volume and compressibility of both of the proteins in the presence of Glu suggests that the proteins attain a more compact state through surface hydration which could provide a more stable conformation. This is also supported by molecule dynamic simulation studies which demonstrate that the water density around the proteins is increased upon the addition of Glu. Further, the intermediates could be completely destabilized by lower concentrations (∼0.5 M) of guanidinium chloride and salt. However, urea subverts the Glu-induced intermediate formed by α-LA, whereas it only slightly destabilizes in the case of RNase A which has a positive surface charge and could possess charge-charge interactions with Glu. This suggests that, apart from hydration, columbic interactions might also contribute to the stability of the intermediate. Gdm-induced denaturation of RNase A and α-LA in the absence and the presence of Glu at different temperatures was carried out. These results also show the Glu-induced stabilization of both of the proteins; however, all of the unfolding transitions followed two-state

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.

9 CFR 325.13 - Denaturing procedures.

Science.gov (United States)

2010-01-01

... the appropriate agent shall be used to give the material a distinctive color, odor, or taste so that... thoroughly mixing therein denaturing oil, No. 2 fuel oil, brucine dissolved in a mixture of alcohol and pine... distinctive a color, odor, or taste that it cannot be confused with an article of human food. [35 FR 15605...

Ocean Predictability and Uncertainty Forecasts Using Local Ensemble Transfer Kalman Filter (LETKF)

Science.gov (United States)

Wei, M.; Hogan, P. J.; Rowley, C. D.; Smedstad, O. M.; Wallcraft, A. J.; Penny, S. G.

2017-12-01

Ocean predictability and uncertainty are studied with an ensemble system that has been developed based on the US Navy's operational HYCOM using the Local Ensemble Transfer Kalman Filter (LETKF) technology. One of the advantages of this method is that the best possible initial analysis states for the HYCOM forecasts are provided by the LETKF which assimilates operational observations using ensemble method. The background covariance during this assimilation process is implicitly supplied with the ensemble avoiding the difficult task of developing tangent linear and adjoint models out of HYCOM with the complicated hybrid isopycnal vertical coordinate for 4D-VAR. The flow-dependent background covariance from the ensemble will be an indispensable part in the next generation hybrid 4D-Var/ensemble data assimilation system. The predictability and uncertainty for the ocean forecasts are studied initially for the Gulf of Mexico. The results are compared with another ensemble system using Ensemble Transfer (ET) method which has been used in the Navy's operational center. The advantages and disadvantages are discussed.

Force Sensor Based Tool Condition Monitoring Using a Heterogeneous Ensemble Learning Model

Directory of Open Access Journals (Sweden)

Guofeng Wang

2014-11-01

Full Text Available 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.

Cooperative unfolding of apolipoprotein A-1 induced by chemical denaturation.

Science.gov (United States)

Eckhardt, D; Li-Blatter, X; Schönfeld, H-J; Heerklotz, H; Seelig, J

2018-05-25

Apolipoprotein A-1 (Apo A-1) plays an important role in lipid transfer and obesity. Chemical unfolding of α-helical Apo A-1 is induced with guanidineHCl and monitored with differential scanning calorimetry (DSC) and CD spectroscopy. The unfolding enthalpy and the midpoint temperature of unfolding decrease linearly with increasing guanidineHCl concentration, caused by the weak binding of denaturant. At room temperature, binding of 50-60 molecules guanidineHCl leads to a complete Apo A-1 unfolding. The entropy of unfolding decreases to a lesser extent than the unfolding enthalpy. Apo A-1 chemical unfolding is a dynamic multi-state equilibrium that is analysed with the Zimm-Bragg theory modified for chemical unfolding. The chemical Zimm-Bragg theory predicts the denaturant binding constant K D and the protein cooperativity σ. Chemical unfolding of Apo A-1 is two orders of magnitude less cooperative than thermal unfolding. The free energy of thermal unfolding is ~0.2 kcal/mol per amino acid residue and ~1.0 kcal/mol for chemical unfolding at room temperature. The Zimm-Bragg theory calculates conformational probabilities and the chemical Zimm-Bragg theory predicts stretches of α-helical segments in dynamic equilibrium, unfolding and refolding independently and fast. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling.

Science.gov (United States)

Hart, Emma; Sim, Kevin

2016-01-01

We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyper-heuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.

Entropy of network ensembles

Science.gov (United States)

Bianconi, Ginestra

2009-03-01

In this paper we generalize the concept of random networks to describe network ensembles with nontrivial features by a statistical mechanics approach. This framework is able to describe undirected and directed network ensembles as well as weighted network ensembles. These networks might have nontrivial community structure or, in the case of networks embedded in a given space, they might have a link probability with a nontrivial dependence on the distance between the nodes. These ensembles are characterized by their entropy, which evaluates the cardinality of networks in the ensemble. In particular, in this paper we define and evaluate the structural entropy, i.e., the entropy of the ensembles of undirected uncorrelated simple networks with given degree sequence. We stress the apparent paradox that scale-free degree distributions are characterized by having small structural entropy while they are so widely encountered in natural, social, and technological complex systems. We propose a solution to the paradox by proving that scale-free degree distributions are the most likely degree distribution with the corresponding value of the structural entropy. Finally, the general framework we present in this paper is able to describe microcanonical ensembles of networks as well as canonical or hidden-variable network ensembles with significant implications for the formulation of network-constructing algorithms.

Modelling machine ensembles with discrete event dynamical system theory

Science.gov (United States)

Hunter, Dan

1990-01-01

Discrete Event Dynamical System (DEDS) theory can be utilized as a control strategy for future complex machine ensembles that will be required for in-space construction. The control strategy involves orchestrating a set of interactive submachines to perform a set of tasks for a given set of constraints such as minimum time, minimum energy, or maximum machine utilization. Machine ensembles can be hierarchically modeled as a global model that combines the operations of the individual submachines. These submachines are represented in the global model as local models. Local models, from the perspective of DEDS theory , are described by the following: a set of system and transition states, an event alphabet that portrays actions that takes a submachine from one state to another, an initial system state, a partial function that maps the current state and event alphabet to the next state, and the time required for the event to occur. Each submachine in the machine ensemble is presented by a unique local model. The global model combines the local models such that the local models can operate in parallel under the additional logistic and physical constraints due to submachine interactions. The global model is constructed from the states, events, event functions, and timing requirements of the local models. Supervisory control can be implemented in the global model by various methods such as task scheduling (open-loop control) or implementing a feedback DEDS controller (closed-loop control).

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

On the v-representability of ensemble densities of electron systems

Science.gov (United States)

Gonis, A.; Däne, M.

2018-05-01

Analogously to the case at zero temperature, where the density of the ground state of an interacting many-particle system determines uniquely (within an arbitrary additive constant) the external potential acting on the system, the thermal average of the density over an ensemble defined by the Boltzmann distribution at the minimum of the thermodynamic potential, or the free energy, determines the external potential uniquely (and not just modulo a constant) acting on a system described by this thermodynamic potential or free energy. The paper describes a formal procedure that generates the domain of a constrained search over general ensembles (at zero or elevated temperatures) that lead to a given density, including as a special case a density thermally averaged at a given temperature, and in the case of a v-representable density determines the external potential leading to the ensemble density. As an immediate consequence of the general formalism, the concept of v-representability is extended beyond the hitherto discussed case of ground state densities to encompass excited states as well. Specific application to thermally averaged densities solves the v-representability problem in connection with the Mermin functional in a manner analogous to that in which this problem was recently settled with respect to the Hohenberg and Kohn functional. The main formalism is illustrated with numerical results for ensembles of one-dimensional, non-interacting systems of particles under a harmonic potential.

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.

Ensemble support vector machine classification of dementia using structural MRI and mini-mental state examination.

Science.gov (United States)

Sørensen, Lauge; Nielsen, Mads

2018-05-15

The International Challenge for Automated Prediction of MCI from MRI data offered independent, standardized comparison of machine learning algorithms for multi-class classification of normal control (NC), mild cognitive impairment (MCI), converting MCI (cMCI), and Alzheimer's disease (AD) using brain imaging and general cognition. We proposed to use an ensemble of support vector machines (SVMs) that combined bagging without replacement and feature selection. SVM is the most commonly used algorithm in multivariate classification of dementia, and it was therefore valuable to evaluate the potential benefit of ensembling this type of classifier. The ensemble SVM, using either a linear or a radial basis function (RBF) kernel, achieved multi-class classification accuracies of 55.6% and 55.0% in the challenge test set (60 NC, 60 MCI, 60 cMCI, 60 AD), resulting in a third place in the challenge. Similar feature subset sizes were obtained for both kernels, and the most frequently selected MRI features were the volumes of the two hippocampal subregions left presubiculum and right subiculum. Post-challenge analysis revealed that enforcing a minimum number of selected features and increasing the number of ensemble classifiers improved classification accuracy up to 59.1%. The ensemble SVM outperformed single SVM classifications consistently in the challenge test set. Ensemble methods using bagging and feature selection can improve the performance of the commonly applied SVM classifier in dementia classification. This resulted in competitive classification accuracies in the International Challenge for Automated Prediction of MCI from MRI data. Copyright © 2018 Elsevier B.V. All rights reserved.

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

Using synchronization in multi-model ensembles to improve prediction

Science.gov (United States)

Hiemstra, P.; Selten, F.

2012-04-01

In recent decades, many climate models have been developed to understand and predict the behavior of the Earth's climate system. Although these models are all based on the same basic physical principles, they still show different behavior. This is for example caused by the choice of how to parametrize sub-grid scale processes. One method to combine these imperfect models, is to run a multi-model ensemble. The models are given identical initial conditions and are integrated forward in time. A multi-model estimate can for example be a weighted mean of the ensemble members. We propose to go a step further, and try to obtain synchronization between the imperfect models by connecting the multi-model ensemble, and exchanging information. The combined multi-model ensemble is also known as a supermodel. The supermodel has learned from observations how to optimally exchange information between the ensemble members. In this study we focused on the density and formulation of the onnections within the supermodel. The main question was whether we could obtain syn-chronization between two climate models when connecting only a subset of their state spaces. Limiting the connected subspace has two advantages: 1) it limits the transfer of data (bytes) between the ensemble, which can be a limiting factor in large scale climate models, and 2) learning the optimal connection strategy from observations is easier. To answer the research question, we connected two identical quasi-geostrohic (QG) atmospheric models to each other, where the model have different initial conditions. The QG model is a qualitatively realistic simulation of the winter flow on the Northern hemisphere, has three layers and uses a spectral imple-mentation. We connected the models in the original spherical harmonical state space, and in linear combinations of these spherical harmonics, i.e. Empirical Orthogonal Functions (EOFs). We show that when connecting through spherical harmonics, we only need to connect 28% of

On the radioimmunological determination of native and heat denaturated protein

International Nuclear Information System (INIS)

Menzel, E.J.; Glatz, F.; Technische Univ., Vienna

1981-01-01

Precipitation radioimmunoassay, solid phase radioimmunoassay and passive hemagglutination were examined for their efficiency in the determination of native or denaturated soy proteins. Native as well as autoclaved soy protein could be determined quantitatively in the precipitation radioimmunoassay, using antisera directed against the native product. In the solid phase technique only the autoclaved soy protein could be detected with high sensitivity. In the passive hemagglutination reaction, no agglutination could be observed with erythrocytes coated with autoclaved soy protein. Only antisera against the denaturated (autoclaved) soy protein agglutinated these erythrocytes. (orig.) [de

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

NARCIS (Netherlands)

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

2018-01-01

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

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

Ensemble Kalman filtering with one-step-ahead smoothing

KAUST Repository

Raboudi, Naila F.

2018-01-11

The ensemble Kalman filter (EnKF) is widely used for sequential data assimilation. It operates as a succession of forecast and analysis steps. In realistic large-scale applications, EnKFs are implemented with small ensembles and poorly known model error statistics. This limits their representativeness of the background error covariances and, thus, their performance. This work explores the efficiency of the one-step-ahead (OSA) smoothing formulation of the Bayesian filtering problem to enhance the data assimilation performance of EnKFs. Filtering with OSA smoothing introduces an updated step with future observations, conditioning the ensemble sampling with more information. This should provide an improved background ensemble in the analysis step, which may help to mitigate the suboptimal character of EnKF-based methods. Here, the authors demonstrate the efficiency of a stochastic EnKF with OSA smoothing for state estimation. They then introduce a deterministic-like EnKF-OSA based on the singular evolutive interpolated ensemble Kalman (SEIK) filter. The authors show that the proposed SEIK-OSA outperforms both SEIK, as it efficiently exploits the data twice, and the stochastic EnKF-OSA, as it avoids observational error undersampling. They present extensive assimilation results from numerical experiments conducted with the Lorenz-96 model to demonstrate SEIK-OSA’s capabilities.

Realization of Deutsch-like algorithm using ensemble computing

International Nuclear Information System (INIS)

Wei Daxiu; Luo Jun; Sun Xianping; Zeng Xizhi

2003-01-01

The Deutsch-like algorithm [Phys. Rev. A. 63 (2001) 034101] distinguishes between even and odd query functions using fewer function calls than its possible classical counterpart in a two-qubit system. But the similar method cannot be applied to a multi-qubit system. We propose a new approach for solving Deutsch-like problem using ensemble computing. The proposed algorithm needs an ancillary qubit and can be easily extended to multi-qubit system with one query. Our ensemble algorithm beginning with a easily-prepared initial state has three main steps. The classifications of the functions can be obtained directly from the spectra of the ancilla qubit. We also demonstrate the new algorithm in a four-qubit molecular system using nuclear magnetic resonance (NMR). One hydrogen and three carbons are selected as the four qubits, and one of carbons is ancilla qubit. We choice two unitary transformations, corresponding to two functions (one odd function and one even function), to validate the ensemble algorithm. The results show that our experiment is successfully and our ensemble algorithm for solving the Deutsch-like problem is virtual

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.

Phagocytosis by macrophages mediated by receptors for denatured proteins - dependence on tyrosine protein kinases

Directory of Open Access Journals (Sweden)

M.R. Hespanhol

2002-03-01

Full Text Available Previous studies have demonstrated that some components of the leukocyte cell membrane, CR3 (Mac-1, CD11b/CD18 and p150/95, are able to bind to denatured proteins. Thus, it is of interest to know which effector functions of these cells can be triggered by these receptors when they interact with particles or surfaces covered with denatured proteins. In the present study we analyzed their possible role as mediators of phagocytosis of red cells covered with denatured bovine serum albumin (BSA by mouse peritoneal macrophages. We observed that a macrophages are able to recognize (bind to these red cells, b this interaction can be inhibited by denatured BSA in the fluid phase, c there is no phagocytosis of these particles by normal macrophages, d phagocytosis mediated by denatured BSA can be, however, effectively triggered in inflammatory macrophages induced by glycogen or in macrophages activated in vivo with LPS, and e this phagocytic capacity is strongly dependent on the activity of tyrosine protein kinases in its signal transduction pathway, as demonstrated by using three kinds of enzyme inhibitors (genistein, quercetin and herbimycin A.

An automated approach to network features of protein structure ensembles

Science.gov (United States)

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

2013-01-01

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. PMID:23934896

[Inactivating Effect of Heat-Denatured Lysozyme on Murine Norovirus in Bread Fillings].

Science.gov (United States)

Takahashi, Michiko; Yasuda, Yuka; Takahashi, Hajime; Takeuchi, Akira; Kuda, Takashi; Kimura, Bon

2018-01-01

In this study, we investigated the viability of murine norovirus strain 1 (MNV-1), a surrogate for human norovirus, in bread fillings used for making stuffed buns and pastries. The inactivating effect of heat-denatured lysozyme, which was recently reported to have an antiviral effect, on MNV-1 contaminating the bread fillings was also examined. MNV-1 was inoculated into two types of fillings (chocolate cream, marmalade jam) at 4.5 log PFU/g, and the bread fillings were stored at 4℃ for 5 days. MNV-1 remained viable in the bread fillings during storage. However, addition of 1% heat-denatured lysozyme to the fillings resulted in a decrease of MNV-1 infectivity immediately after inoculation, in both fillings. On the fifth day of storage, MNV-1 infectivity was decreased by 1.2 log PFU/g in chocolate cream and by 0.9 log PFU/g in marmalade jam. Although the mechanism underlying the anti-norovirus effect of heat-denatured lysozyme has not been clarified, our results suggest that heat-denatured lysozyme can be used as an inactivating agent against norovirus in bread fillings.

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.

Bidirectional Modulation of Intrinsic Excitability in Rat Prelimbic Cortex Neuronal Ensembles and Non-Ensembles after Operant Learning.

Science.gov (United States)

Whitaker, Leslie R; Warren, Brandon L; Venniro, Marco; Harte, Tyler C; McPherson, Kylie B; Beidel, Jennifer; Bossert, Jennifer M; Shaham, Yavin; Bonci, Antonello; Hope, Bruce T

2017-09-06

Learned associations between environmental stimuli and rewards drive goal-directed learning and motivated behavior. These memories are thought to be encoded by alterations within specific patterns of sparsely distributed neurons called neuronal ensembles that are activated selectively by reward-predictive stimuli. Here, we use the Fos promoter to identify strongly activated neuronal ensembles in rat prelimbic cortex (PLC) and assess altered intrinsic excitability after 10 d of operant food self-administration training (1 h/d). First, we used the Daun02 inactivation procedure in male FosLacZ-transgenic rats to ablate selectively Fos-expressing PLC neurons that were active during operant food self-administration. Selective ablation of these neurons decreased food seeking. We then used male FosGFP-transgenic rats to assess selective alterations of intrinsic excitability in Fos-expressing neuronal ensembles (FosGFP + ) that were activated during food self-administration and compared these with alterations in less activated non-ensemble neurons (FosGFP - ). Using whole-cell recordings of layer V pyramidal neurons in an ex vivo brain slice preparation, we found that operant self-administration increased excitability of FosGFP + neurons and decreased excitability of FosGFP - neurons. Increased excitability of FosGFP + neurons was driven by increased steady-state input resistance. Decreased excitability of FosGFP - neurons was driven by increased contribution of small-conductance calcium-activated potassium (SK) channels. Injections of the specific SK channel antagonist apamin into PLC increased Fos expression but had no effect on food seeking. Overall, operant learning increased intrinsic excitability of PLC Fos-expressing neuronal ensembles that play a role in food seeking but decreased intrinsic excitability of Fos - non-ensembles. SIGNIFICANCE STATEMENT Prefrontal cortex activity plays a critical role in operant learning, but the underlying cellular mechanisms are

Limited-area short-range ensemble predictions targeted for heavy rain in Europe

Directory of Open Access Journals (Sweden)

K. Sattler

2005-01-01

Full Text Available Inherent uncertainties in short-range quantitative precipitation forecasts (QPF from the high-resolution, limited-area numerical weather prediction model DMI-HIRLAM (LAM are addressed using two different approaches to creating a small ensemble of LAM simulations, with focus on prediction of extreme rainfall events over European river basins. The first ensemble type is designed to represent uncertainty in the atmospheric state of the initial condition and at the lateral LAM boundaries. The global ensemble prediction system (EPS from ECMWF serves as host model to the LAM and provides the state perturbations, from which a small set of significant members is selected. The significance is estimated on the basis of accumulated precipitation over a target area of interest, which contains the river basin(s under consideration. The selected members provide the initial and boundary data for the ensemble integration in the LAM. A second ensemble approach tries to address a portion of the model-inherent uncertainty responsible for errors in the forecasted precipitation field by utilising different parameterisation schemes for condensation and convection in the LAM. Three periods around historical heavy rain events that caused or contributed to disastrous river flooding in Europe are used to study the performance of the LAM ensemble designs. The three cases exhibit different dynamic and synoptic characteristics and provide an indication of the ensemble qualities in different weather situations. Precipitation analyses from the Deutsche Wetterdienst (DWD are used as the verifying reference and a comparison of daily rainfall amounts is referred to the respective river basins of the historical cases.

The Effects of Classical Guitar Ensembles on Student Self-Perceptions and Acquisition of Music Skills

Science.gov (United States)

Kramer, John R.

2012-01-01

Classical guitar ensembles are increasing in the United States as popular alternatives to band, choir, and orchestra. Classical guitar ensembles are offered at many middle and high schools as fine arts electives as one of the only options for classical guitarists to participate in ensembles. The purpose of this study was to explore the development…

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

Ensemble streamflow assimilation with the National Water Model.

Science.gov (United States)

Rafieeinasab, A.; McCreight, J. L.; Noh, S.; Seo, D. J.; Gochis, D.

2017-12-01

Through case studies of flooding across the US, we compare the performance of the National Water Model (NWM) data assimilation (DA) scheme to that of a newly implemented ensemble Kalman filter approach. The NOAA National Water Model (NWM) is an operational implementation of the community WRF-Hydro modeling system. As of August 2016, the NWM forecasts of distributed hydrologic states and fluxes (including soil moisture, snowpack, ET, and ponded water) over the contiguous United States have been publicly disseminated by the National Center for Environmental Prediction (NCEP) . It also provides streamflow forecasts at more than 2.7 million river reaches up to 30 days in advance. The NWM employs a nudging scheme to assimilate more than 6,000 USGS streamflow observations and provide initial conditions for its forecasts. A problem with nudging is how the forecasts relax quickly to open-loop bias in the forecast. This has been partially addressed by an experimental bias correction approach which was found to have issues with phase errors during flooding events. In this work, we present an ensemble streamflow data assimilation approach combining new channel-only capabilities of the NWM and HydroDART (a coupling of the offline WRF-Hydro model and NCAR's Data Assimilation Research Testbed; DART). Our approach focuses on the single model state of discharge and incorporates error distributions on channel-influxes (overland and groundwater) in the assimilation via an ensemble Kalman filter (EnKF). In order to avoid filter degeneracy associated with a limited number of ensemble at large scale, DART's covariance inflation (Anderson, 2009) and localization capabilities are implemented and evaluated. The current NWM data assimilation scheme is compared to preliminary results from the EnKF application for several flooding case studies across the US.

The DC electrical conductivity calculation purely from the dissipative component of the AC conductivity III. statistical ensemble inherent to state with DC current

International Nuclear Information System (INIS)

Milinski, N.; Milinski, E.

2002-01-01

Amorphous conductors such as liquid metals and alloys are subject to dc conductivity σ calculation here. Principal aim is to explore the impact on σ of the constitutive equation α * = 1, formulated and developed in the preceding papers. The nearly free electrons (NFE) model has been applied. Alkali metals are assumed to fit this model well, and sodium the best. Consequently, the results on these metals have been assumed reliable and relevant for conclusions making. The conclusion we made is: instead of the Fermi radius k f proper for the statistical ensemble in state of thermodynamics equilibrium, a new k ' f number is needed to be introduced into the linear response formula when calculating σ and α * . This k ' f is the length of the corresponding axis of ellipsoid proper for describing the statistical ensemble in the state with dc current. In the traditional interpretation of the linear response formula (Kubo formula) this conversion has been overlooked. Parameters of the mentioned ellipsoids are determined in this paper for a number of liquid metals of valency numbers 1,2,3,4, in addition to a selection of some binary and ternary conducting alloys. It is up to experimental measurements to decide how real this concept of restructuring the statistical ensemble is. (Authors)

On the forecast skill of a convection-permitting ensemble

Science.gov (United States)

Schellander-Gorgas, Theresa; Wang, Yong; Meier, Florian; Weidle, Florian; Wittmann, Christoph; Kann, Alexander

2017-01-01

The 2.5 km convection-permitting (CP) ensemble AROME-EPS (Applications of Research to Operations at Mesoscale - Ensemble Prediction System) is evaluated by comparison with the regional 11 km ensemble ALADIN-LAEF (Aire Limitée Adaption dynamique Développement InterNational - Limited Area Ensemble Forecasting) to show whether a benefit is provided by a CP EPS. The evaluation focuses on the abilities of the ensembles to quantitatively predict precipitation during a 3-month convective summer period over areas consisting of mountains and lowlands. The statistical verification uses surface observations and 1 km × 1 km precipitation analyses, and the verification scores involve state-of-the-art statistical measures for deterministic and probabilistic forecasts as well as novel spatial verification methods. The results show that the convection-permitting ensemble with higher-resolution AROME-EPS outperforms its mesoscale counterpart ALADIN-LAEF for precipitation forecasts. The positive impact is larger for the mountainous areas than for the lowlands. In particular, the diurnal precipitation cycle is improved in AROME-EPS, which leads to a significant improvement of scores at the concerned times of day (up to approximately one-third of the scored verification measure). Moreover, there are advantages for higher precipitation thresholds at small spatial scales, which are due to the improved simulation of the spatial structure of precipitation.

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.

27 CFR 19.41 - Claims on spirits, denatured spirits, articles, or wines lost or destroyed in bond.

Science.gov (United States)

2010-04-01

..., denatured spirits, articles, or wines lost or destroyed in bond. 19.41 Section 19.41 Alcohol, Tobacco... DISTILLED SPIRITS PLANTS Taxes Claims § 19.41 Claims on spirits, denatured spirits, articles, or wines lost..., relating to the destruction or loss of spirits, denatured spirits, articles, or wines in bond, shall be...

Drying and denaturation characteristics of whey protein isolate in the presence of lactose and trehalose.

Science.gov (United States)

Haque, M Amdadul; Chen, Jie; Aldred, Peter; Adhikari, Benu

2015-06-15

The denaturation kinetics of whey protein isolate (WPI), in the presence and absence of lactose and trehalose, was quantified in a convective air-drying environment. Single droplets of WPI, WPI-lactose and WPI-trehalose were dried in conditioned air (2.5% RH, 0.5m/s air velocity) at two temperatures (65°C and 80°C) for 500s. The initial solid concentration of these solutions was 10% (w/v) in all the samples. Approximately 68% of WPI was denatured when it was dried in the absence of sugars. Addition of 20% trehalose prevented the irreversible denaturation of WPI at both temperatures. Thirty percent lactose was required to prevent denaturation of WPI at 65°C and the same amount of lactose protected only 70% of WPI from denaturation at 80°C. The secondary structures of WPI were found to be altered by the drying-induced stresses, even in the presence of 20% trehalose and 30% lactose. Copyright © 2014 Elsevier Ltd. All rights reserved.

Control of inhomogeneous atomic ensembles of hyperfine qudits

DEFF Research Database (Denmark)

Mischuck, Brian Edward; Merkel, Seth T.; Deutsch, Ivan H.

2012-01-01

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 semianalytic 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 semianalytic protocol...

The efficacy of denaturing actinide elements as a means of decreasing materials attractiveness

Energy Technology Data Exchange (ETDEWEB)

Hase, K.R.; Bathke, C.G. [Los Alamos National Laboratory: P.O. Box 1663, Los Alamos, NM 87545 (United States); Ebbinghaus, B.B.; Sleaford, B.W.; Robel, M. [Lawrence Livermore National Laboratory: P.O. Box 808, Livermore, CA 94551 (United States); Collins, B.A.; Prichard, A.W. [Pacific Northwest National Laboratory: P.O. Box 999, Richland, WA 99352 (United States)

2013-07-01

This study considers the concept of denaturing as applied to the actinide elements present in spent fuel as a means to reduce materials attractiveness. Highly attractive materials generally have low values of bare critical mass, heat content, and dose. To denature an attractive element, its spent-fuel isotopic composition (isotopic vector) is intentionally modified by introducing sufficient quantities of a significantly less attractive isotope to dilute the concentration of a highly attractive isotope so that the overall attractiveness of the element is reduced. The authors used FOM (Figure of Merit) formula as the material attractiveness metric for their parametric determination of the attractiveness of the Pu and U. Materials attractiveness needs to be considered in three distinct phases in the process to construct a nuclear explosive device (NED): the acquisition phase, processing phase, and utilization phase. The results show that denaturing uranium with {sup 238}U is actually an effective means of reducing the attractiveness. For uranium with a large minority of {sup 235}U, a mixture of 80% {sup 238}U to 20% {sup 235}U is required to reduce the attractiveness to low. For uranium with a large concentration of {sup 233}U, a mixture of 88% {sup 238}U to 12% {sup 233}U is required to reduce the attractiveness to low. The results also show that denaturing plutonium with {sup 238}Pu is less effective than denaturing uranium with {sup 238}U. Using {sup 238}Pu as the denaturing agent would require 80% or more by mass in order to reduce the attractiveness to low. No amount of {sup 240}Pu is enough to reduce the plutonium attractiveness below medium. The combination of {sup 238}Pu and {sup 240}Pu would require approximately 70% {sup 238}Pu and 25% {sup 240}Pu by mass to reduce the plutonium attractiveness to low.

The efficacy of denaturing actinide elements as a means of decreasing materials attractiveness

International Nuclear Information System (INIS)

Hase, K.R.; Bathke, C.G.; Ebbinghaus, B.B.; Sleaford, B.W.; Robel, M.; Collins, B.A.; Prichard, A.W.

2013-01-01

This study considers the concept of denaturing as applied to the actinide elements present in spent fuel as a means to reduce materials attractiveness. Highly attractive materials generally have low values of bare critical mass, heat content, and dose. To denature an attractive element, its spent-fuel isotopic composition (isotopic vector) is intentionally modified by introducing sufficient quantities of a significantly less attractive isotope to dilute the concentration of a highly attractive isotope so that the overall attractiveness of the element is reduced. The authors used FOM (Figure of Merit) formula as the material attractiveness metric for their parametric determination of the attractiveness of the Pu and U. Materials attractiveness needs to be considered in three distinct phases in the process to construct a nuclear explosive device (NED): the acquisition phase, processing phase, and utilization phase. The results show that denaturing uranium with 238 U is actually an effective means of reducing the attractiveness. For uranium with a large minority of 235 U, a mixture of 80% 238 U to 20% 235 U is required to reduce the attractiveness to low. For uranium with a large concentration of 233 U, a mixture of 88% 238 U to 12% 233 U is required to reduce the attractiveness to low. The results also show that denaturing plutonium with 238 Pu is less effective than denaturing uranium with 238 U. Using 238 Pu as the denaturing agent would require 80% or more by mass in order to reduce the attractiveness to low. No amount of 240 Pu is enough to reduce the plutonium attractiveness below medium. The combination of 238 Pu and 240 Pu would require approximately 70% 238 Pu and 25% 240 Pu by mass to reduce the plutonium attractiveness to low

Optimized expanded ensembles for simulations involving molecular insertions and deletions. II. Open systems

Science.gov (United States)

Escobedo, Fernando A.

2007-11-01

In the Grand Canonical, osmotic, and Gibbs ensembles, chemical potential equilibrium is attained via transfers of molecules between the system and either a reservoir or another subsystem. In this work, the expanded ensemble (EXE) methods described in part I [F. A. Escobedo and F. J. Martínez-Veracoechea, J. Chem. Phys. 127, 174103 (2007)] of this series are extended to these ensembles to overcome the difficulties associated with implementing such whole-molecule transfers. In EXE, such moves occur via a target molecule that undergoes transitions through a number of intermediate coupling states. To minimize the tunneling time between the fully coupled and fully decoupled states, the intermediate states could be either: (i) sampled with an optimal frequency distribution (the sampling problem) or (ii) selected with an optimal spacing distribution (staging problem). The sampling issue is addressed by determining the biasing weights that would allow generating an optimal ensemble; discretized versions of this algorithm (well suited for small number of coupling stages) are also presented. The staging problem is addressed by selecting the intermediate stages in such a way that a flat histogram is the optimized ensemble. The validity of the advocated methods is demonstrated by their application to two model problems, the solvation of large hard spheres into a fluid of small and large spheres, and the vapor-liquid equilibrium of a chain system.

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.

27 CFR 19.32 - Assessment of tax on spirits, denatured spirits, or wines in bond which are lost, destroyed or...

Science.gov (United States)

2010-04-01

... spirits, denatured spirits, or wines in bond which are lost, destroyed or removed without authorization... spirits, denatured spirits, or wines in bond which are lost, destroyed or removed without authorization. When spirits, denatured spirits, or wines in bond are lost or destroyed (except spirits, denatured...

Nonsurgical Transurethral Radiofrequency Collagen Denaturation: Results at Three Years after Treatment

Directory of Open Access Journals (Sweden)

Denise M. Elser

2011-01-01

Full Text Available Objective. To assess treatment efficacy and quality of life in women with stress urinary incontinence 3 years after treatment with nonsurgical transurethral radiofrequency collagen denaturation. Methods. This prospective study included 139 women with stress urinary incontinence due to bladder outlet hypermobility. Radiofrequency collagen denaturation was performed using local anesthesia in an office setting. Assessments included incontinence quality of life (I-QOL and urogenital distress inventory (UDI-6 instruments. Results. In total, 139 women were enrolled and 136 women were treated (mean age, 47 years. At 36 months, intent-to-treat analysis (n=139 revealed significant improvements in quality of life. Mean I-QOL score improved 17 points from baseline (P=.0004, while mean UDI-6 score improved (decreased 19 points (P=.0005. Conclusions. Transurethral collagen denaturation is a low-risk, office-based procedure that results in durable quality-of-life improvements in a significant proportion of women for as long as 3 years.

The expression of miR-125b regulates angiogenesis during the recovery of heat-denatured HUVECs.

Science.gov (United States)

Zhou, Situo; Zhang, Pihong; Liang, Pengfei; Huang, Xiaoyuan

2015-06-01

In previous studies we found that miR-125b was down-regulated in denatured dermis of deep partial thickness burn patients. Moreover, miR-125b inhibited tumor-angiogenesis associated with the decrease of ERBB2 and VEGF expression in ovarian cancer cells and breast cancer cells, etc. In this study, we investigated the expression patterns and roles of miR-125b during the recovery of denatured dermis and heat-denatured human umbilical vein endothelial cells (HUVECs). Deep partial thickness burns in Sprague-Dawley rats and the heat-denatured cells (52°C, 35 s) were used for analysis. Western blot analysis and real-time PCR were applied to evaluate the expression of miR-125b and ERBB2 and VEGF. The ability of angiogenesis in heat-denatured HUVECs was analyzed by scratch wound healing and tube formation assay after pri-miR-125b or anti-miR-125b transfection. miR-125b expression was time-dependent during the recovery of heat-denatured dermis and HUVECs. Moreover, miR-125b regulated ERBB2 mRNA and Protein Expression and regulated angiogenesis association with regulating the expression of VEGF in heat-denatured HUVECs. Taken together our results show that the expression of miR-125b is time-dependent and miR-125b plays a regulatory role of angiogenesis during wound healing after burns. Copyright © 2014 Elsevier Ltd and ISBI. All rights reserved.

Complement-fixing antibodies against denatured HLA and MICA antigens are associated with antibody mediated rejection.

Science.gov (United States)

Cai, Junchao; Terasaki, Paul I; Zhu, Dong; Lachmann, Nils; Schönemann, Constanze; Everly, Matthew J; Qing, Xin

2016-02-01

We have found antibodies against denatured HLA class I antigens in the serum of allograft recipients which were not significantly associated with graft failure. It is unknown whether transplant recipients also have denatured HLA class II and MICA antibodies. The effects of denatured HLA class I, class II, and MICA antibodies on long-term graft outcome were further investigated based on their ability to fix complement c1q. In this 4-year retrospective cohort study, post-transplant sera from 975 kidney transplant recipients were tested for antibodies against denatured HLA/MICA antigens and these antibodies were further classified based on their ability to fix c1q. Thirty percent of patients had antibodies against denatured HLA class I, II, or MICA antigens. Among them, 8.5% and 21.5% of all patients had c1q-fixing and non c1q-fixing antibodies respectively. There was no significant difference on graft survival between patients with or without antibodies against denatured HLA/MICA. However, when these antibodies were further classified according to their ability to fix c1q, patients with c1q-fixing antibodies had a significantly lower graft survival rate than patients without antibodies or patients with non c1q-fixing antibodies (p=0.008). In 169 patients who lost renal grafts, 44% of them had c1q-fixing antibodies against denatured HLA/MICA antigens, which was significantly higher than that in patients with functioning renal transplants (25%, pantibodies were more significantly associated with graft failure caused by AMR (72.73%) or mixed AMR/CMR (61.9%) as compared to failure due to CMR (35.3%) or other causes (39.2%) (p=0.026). Transplant recipients had antibodies against denatured HLA class I, II, and MICA antigens. However, only c1q-fixing antibodies were associated with graft failure which was related to antibody mediated rejection. Copyright © 2015 Elsevier Inc. All rights reserved.

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...

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

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......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...... 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...

Ensemble averaged coherent state path integral for disordered bosons with a repulsive interaction (Derivation of mean field equations)

International Nuclear Information System (INIS)

Mieck, B.

2007-01-01

We consider bosonic atoms with a repulsive contact interaction in a trap potential for a Bose-Einstein condensation (BEC) and additionally include a random potential. The ensemble averages for two models of static (I) and dynamic (II) disorder are performed and investigated in parallel. The bosonic many body systems of the two disorder models are represented by coherent state path integrals on the Keldysh time contour which allow exact ensemble averages for zero and finite temperatures. These ensemble averages of coherent state path integrals therefore present alternatives to replica field theories or super-symmetric averaging techniques. Hubbard-Stratonovich transformations (HST) lead to two corresponding self-energies for the hermitian repulsive interaction and for the non-hermitian disorder-interaction. The self-energy of the repulsive interaction is absorbed by a shift into the disorder-self-energy which comprises as an element of a larger symplectic Lie algebra sp(4M) the self-energy of the repulsive interaction as a subalgebra (which is equivalent to the direct product of M x sp(2); 'M' is the number of discrete time intervals of the disorder-self-energy in the generating function). After removal of the remaining Gaussian integral for the self-energy of the repulsive interaction, the first order variations of the coherent state path integrals result in the exact mean field or saddle point equations, solely depending on the disorder-self-energy matrix. These equations can be solved by continued fractions and are reminiscent to the 'Nambu-Gorkov' Green function formalism in superconductivity because anomalous terms or pair condensates of the bosonic atoms are also included into the selfenergies. The derived mean field equations of the models with static (I) and dynamic (II) disorder are particularly applicable for BEC in d=3 spatial dimensions because of the singularity of the density of states at vanishing wavevector. However, one usually starts out from

Pseudomonas aeruginosa cytochrome c551 denaturation by five systematic urea derivatives that differ in the alkyl chain length.

Science.gov (United States)

Kobayashi, Shinya; Fujii, Sotaro; Koga, Aya; Wakai, Satoshi; Matubayasi, Nobuyuki; Sambongi, Yoshihiro

2017-07-01

Reversible denaturation of Pseudomonas aeruginosa cytochrome c 551 (PAc 551 ) could be followed using five systematic urea derivatives that differ in the alkyl chain length, i.e. urea, N-methylurea (MU), N-ethylurea (EU), N-propylurea (PU), and N-butylurea (BU). The BU concentration was the lowest required for the PAc 551 denaturation, those of PU, EU, MU, and urea being gradually higher. Furthermore, the accessible surface area difference upon PAc 551 denaturation caused by BU was found to be the highest, those by PU, EU, MU, and urea being gradually lower. These findings indicate that urea derivatives with longer alkyl chains are stronger denaturants. In this study, as many as five systematic urea derivatives could be applied for the reversible denaturation of a single protein, PAc 551 , for the first time, and the effects of the alkyl chain length on protein denaturation were systematically verified by means of thermodynamic parameters.

Ensemble modeling for aromatic production in Escherichia coli.

Directory of Open Access Journals (Sweden)

Matthew L Rizk

2009-09-01

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.

On the Use of Potential Denaturing Agents for Ethanol in Direct Ethanol Fuel Cells

Directory of Open Access Journals (Sweden)

Domnik Bayer

2011-01-01

Full Text Available Acidic or alkaline direct ethanol fuel cells (DEFCs can be a sustainable alternative for power generation if they are fuelled with bio-ethanol. However, in order to keep the fuel cheap, ethanol has to be exempted from tax on spirits by denaturing. In this investigation the potential denaturing agents fusel oil, tert-butyl ethyl ether, and Bitrex were tested with regard to their compatibility with fuel cells. Experiments were carried out both in sulphuric acid and potassium hydroxide solution. Beside, basic electrochemical tests, differential electrochemical mass spectrometry (DEMS and fuel cell tests were conducted. It was found that fusel oil is not suitable as denaturing agent for DEFC. However, tert-butyl ethyl ether does not seem to hinder the ethanol conversion as much. Finally, a mixture of tert-butyl ethyl ether and Bitrex can be proposed as promising candidate as denaturing agent for use in acidic and alkaline DEFC.

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

Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing

KAUST Repository

Toye, Habib

2017-05-26

We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation and of the Data Research Testbed (DART) for ensemble data assimilation. DART has been configured to integrate all members of an ensemble adjustment Kalman filter (EAKF) in parallel, based on which we adapted the ensemble operations in DART to use an invariant ensemble, i.e., an ensemble Optimal Interpolation (EnOI) algorithm. This approach requires only single forward model integration in the forecast step and therefore saves substantial computational cost. To deal with the strong seasonal variability of the Red Sea, the EnOI ensemble is then seasonally selected from a climatology of long-term model outputs. Observations of remote sensing sea surface height (SSH) and sea surface temperature (SST) are assimilated every 3 days. Real-time atmospheric fields from the National Center for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) are used as forcing in different assimilation experiments. We investigate the behaviors of the EAKF and (seasonal-) EnOI and compare their performances for assimilating and forecasting the circulation of the Red Sea. We further assess the sensitivity of the assimilation system to various filtering parameters (ensemble size, inflation) and atmospheric forcing.

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.

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

KAUST Repository

Luo, Xiaodong; Hoteit, Ibrahim

2014-01-01

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.

Effects of thermally induced denaturation on technological-functional properties of whey protein isolate-based films.

Science.gov (United States)

Schmid, M; Krimmel, B; Grupa, U; Noller, K

2014-09-01

This study examined how and to what extent the degree of denaturation affected the technological-functional properties of whey protein isolate (WPI)-based coatings. It was observed that denaturation affected the material properties of WPI-coated films significantly. Surface energy decreased by approximately 20% compared with native coatings. Because the surface energy of a coating should be lower than that of the substrate, this might result in enhanced wettability characteristics between WPI-based solution and substrate surface. Water vapor barrier properties increased by about 35% and oxygen barrier properties increased by approximately 33%. However, significant differences were mainly observed between coatings made of fully native WPI and ones with a degree of denaturation of 25%. Higher degrees of denaturation did not lead to further improvement of material properties. This observation offers cost-saving potential: a major share of denatured whey proteins may be replaced by fully native ones that are not exposed to energy-intensive heat treatment. Furthermore, native WPI solutions can be produced with higher dry matter content without gelatinizing. Hence, less moisture has to be removed through drying, resulting in reduced energy consumption. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Encoding qubits into oscillators with atomic ensembles and squeezed light

Science.gov (United States)

Motes, Keith R.; Baragiola, Ben Q.; Gilchrist, Alexei; Menicucci, Nicolas C.

2017-05-01

The Gottesman-Kitaev-Preskill (GKP) encoding of a qubit within an oscillator provides a number of advantages when used in a fault-tolerant architecture for quantum computing, most notably that Gaussian operations suffice to implement all single- and two-qubit Clifford gates. The main drawback of the encoding is that the logical states themselves are challenging to produce. Here we present a method for generating optical GKP-encoded qubits by coupling an atomic ensemble to a squeezed state of light. Particular outcomes of a subsequent spin measurement of the ensemble herald successful generation of the resource state in the optical mode. We analyze the method in terms of the resources required (total spin and amount of squeezing) and the probability of success. We propose a physical implementation using a Faraday-based quantum nondemolition interaction.

Charge transfer excitations from exact and approximate ensemble Kohn-Sham theory

Science.gov (United States)

Gould, Tim; Kronik, Leeor; Pittalis, Stefano

2018-05-01

By studying the lowest excitations of an exactly solvable one-dimensional soft-Coulomb molecular model, we show that components of Kohn-Sham ensembles can be used to describe charge transfer processes. Furthermore, we compute the approximate excitation energies obtained by using the exact ensemble densities in the recently formulated ensemble Hartree-exchange theory [T. Gould and S. Pittalis, Phys. Rev. Lett. 119, 243001 (2017)]. Remarkably, our results show that triplet excitations are accurately reproduced across a dissociation curve in all cases tested, even in systems where ground state energies are poor due to strong static correlations. Singlet excitations exhibit larger deviations from exact results but are still reproduced semi-quantitatively.

Raman spectral markers of collagen denaturation and hydration in human cortical bone tissue are affected by radiation sterilization and high cycle fatigue damage.

Science.gov (United States)

Flanagan, Christopher D; Unal, Mustafa; Akkus, Ozan; Rimnac, Clare M

2017-11-01

Thermal denaturation and monotonic mechanical damage alter the organic and water-related compartments of cortical bone. These changes can be detected using Raman spectroscopy. However, less is known regarding Raman sensitivity to detect the effects of cyclic fatigue damage and allograft sterilization doses of gamma radiation. To determine if Raman spectroscopic biomarkers of collagen denaturation and hydration are sensitive to the effects of (a) high cycle fatigue damage and (b) 25kGy irradiation. Unirradiated and gamma-radiation sterilized human cortical bone specimens previously tested in vitro under high-cycle (> 100,000 cycles) fatigue conditions at 15MPa, 25MPa, 35MPa, 45MPa, and 55MPa cyclic stress levels were studied. Cortical bone Raman spectral profiles from wavenumber ranges of 800-1750cm -1 and 2700-3800cm -1 were obtained and compared from: a) non-fatigue vs fatigue fracture sites and b) radiated vs. unirradiated states. Raman biomarker ratios 1670/1640 and 3220/2949, which reflect collagen denaturation and organic matrix (mainly collagen)-bound water, respectively, were assessed. One- and two-way ANOVA analyses were utilized to identify differences between groups along with interaction effects between cyclic fatigue and radiation-induced damage. Cyclic fatigue damage resulted in increases in collagen denaturation (1670/1640: 1.517 ± 0.043 vs 1.579 ± 0.021, p Raman spectroscopy can detect the effects of cyclic fatigue damage and 25kGy irradiation via increases in organic matrix (mainly collagen)-bound water. A Raman measure of collagen denaturation was sensitive to cyclic fatigue damage but not 25kGy irradiation. Collagen denaturation was correlated with organic matrix-bound water, suggesting that denaturation of collagen to gelatinous form may expose more binding sites to water by unwinding the triple alpha chains. This research may eventually be useful to help identify allograft quality and more appropriately match donors to recipients. Copyright �

Localization of atomic ensembles via superfluorescence

International Nuclear Information System (INIS)

Macovei, Mihai; Evers, Joerg; Keitel, Christoph H.; Zubairy, M. Suhail

2007-01-01

The subwavelength localization of an ensemble of atoms concentrated to a small volume in space is investigated. The localization relies on the interaction of the ensemble with a standing wave laser field. The light scattered in the interaction of the standing wave field and the atom ensemble depends on the position of the ensemble relative to the standing wave nodes. This relation can be described by a fluorescence intensity profile, which depends on the standing wave field parameters and the ensemble properties and which is modified due to collective effects in the ensemble of nearby particles. We demonstrate that the intensity profile can be tailored to suit different localization setups. Finally, we apply these results to two localization schemes. First, we show how to localize an ensemble fixed at a certain position in the standing wave field. Second, we discuss localization of an ensemble passing through the standing wave field

Ensembl 2017

OpenAIRE

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; Gir?n, Carlos Garc?a; Gordon, Leo; Hourlier, Thibaut; Hunt, Sarah E.

2016-01-01

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 ...

Ensemble Sampling

OpenAIRE

Lu, Xiuyuan; Van Roy, Benjamin

2017-01-01

Thompson sampling has emerged as an effective heuristic for a broad range of online decision problems. In its basic form, the algorithm requires computing and sampling from a posterior distribution over models, which is tractable only for simple special cases. This paper develops ensemble sampling, which aims to approximate Thompson sampling while maintaining tractability even in the face of complex models such as neural networks. Ensemble sampling dramatically expands on the range of applica...

Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

Directory of Open Access Journals (Sweden)

Nikola Simidjievski

Full Text Available Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting, significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.

Spectral shift controlled reactors, denatured U-233/thorium cycle

International Nuclear Information System (INIS)

1978-05-01

This paper presents technical and economic data on the SSCR which may be of use in the International Fuel Cycle Evaluation Program to intercompare alternative nuclear systems. Included in this paper are data on the denatured U-233/thorium cycle. This cycle shows a proliferation advantage over more classical thorium fuel cycle (e.g., highly-enriched U-235/thorium or plutonium/thorium) due to the elimination of chemically-separable, concentrated fissile material from unirradiated nuclear fuel. The U-233 is denatured by mixing with depleted uranium to a concentration no greater than 12 w/o. An exogenous source of U-233 is assumed in this paper, since U-233 does not occur in nature and only a limited supply has been produced to date for research and development work

Village Building Identification Based on Ensemble Convolutional Neural Networks

Science.gov (United States)

Guo, Zhiling; Chen, Qi; Xu, Yongwei; Shibasaki, Ryosuke; Shao, Xiaowei

2017-01-01

In this study, we present the Ensemble Convolutional Neural Network (ECNN), an elaborate CNN frame formulated based on ensembling state-of-the-art CNN models, to identify village buildings from open high-resolution remote sensing (HRRS) images. First, to optimize and mine the capability of CNN for village mapping and to ensure compatibility with our classification targets, a few state-of-the-art models were carefully optimized and enhanced based on a series of rigorous analyses and evaluations. Second, rather than directly implementing building identification by using these models, we exploited most of their advantages by ensembling their feature extractor parts into a stronger model called ECNN based on the multiscale feature learning method. Finally, the generated ECNN was applied to a pixel-level classification frame to implement object identification. The proposed method can serve as a viable tool for village building identification with high accuracy and efficiency. The experimental results obtained from the test area in Savannakhet province, Laos, prove that the proposed ECNN model significantly outperforms existing methods, improving overall accuracy from 96.64% to 99.26%, and kappa from 0.57 to 0.86. PMID:29084154

Modified denatured lysozyme effectively solubilizes fullerene c60 nanoparticles in water

Science.gov (United States)

Siepi, Marialuisa; Politi, Jane; Dardano, Principia; Amoresano, Angela; De Stefano, Luca; Monti, Daria Maria; Notomista, Eugenio

2017-08-01

Fullerenes, allotropic forms of carbon, have very interesting pharmacological effects and engineering applications. However, a very low solubility both in organic solvents and water hinders their use. Fullerene C60, the most studied among fullerenes, can be dissolved in water only in the form of nanoparticles of variable dimensions and limited stability. Here the effect on the production of C60 nanoparticles by a native and denatured hen egg white lysozyme, a highly basic protein, has been systematically studied. In order to obtain a denatured, yet soluble, lysozyme derivative, the four disulfides of the native protein were reduced and exposed cysteines were alkylated by 3-bromopropylamine, thus introducing eight additional positive charges. The C60 solubilizing properties of the modified denatured lysozyme proved to be superior to those of the native protein, allowing the preparation of biocompatible highly homogeneous and stable C60 nanoparticles using lower amounts of protein, as demonstrated by dynamic light scattering, transmission electron microscopy and atomic force microscopy studies. This lysozyme derivative could represent an effective tool for the solubilization of other carbon allotropes.

EnsembleGASVR: A novel ensemble method for classifying missense single nucleotide polymorphisms

KAUST Repository

Rapakoulia, Trisevgeni; Theofilatos, Konstantinos A.; Kleftogiannis, Dimitrios A.; Likothanasis, Spiridon D.; Tsakalidis, Athanasios K.; Mavroudi, Seferina P.

2014-01-01

do not support their predictions with confidence scores. Results: To overcome these limitations, a novel ensemble computational methodology is proposed. EnsembleGASVR facilitates a twostep algorithm, which in its first step applies a novel

Cluster perturbation theory for calculation of electronic properties of ensembles of metal nanoclusters

Science.gov (United States)

Zhumagulov, Yaroslav V.; Krasavin, Andrey V.; Kashurnikov, Vladimir A.

2018-05-01

The method is developed for calculation of electronic properties of an ensemble of metal nanoclusters with the use of cluster perturbation theory. This method is applied to the system of gold nanoclusters. The Greens function of single nanocluster is obtained by ab initio calculations within the framework of the density functional theory, and then is used in Dyson equation to group nanoclusters together and to compute the Greens function as well as the electron density of states of the whole ensemble. The transition from insulator state of a single nanocluster to metallic state of bulk gold is observed.

EnsembleGraph: Interactive Visual Analysis of Spatial-Temporal Behavior for Ensemble Simulation Data

Energy Technology Data Exchange (ETDEWEB)

Shu, Qingya; Guo, Hanqi; Che, Limei; Yuan, Xiaoru; Liu, Junfeng; Liang, Jie

2016-04-19

We present a novel visualization framework—EnsembleGraph— for analyzing ensemble simulation data, in order to help scientists understand behavior similarities between ensemble members over space and time. A graph-based representation is used to visualize individual spatiotemporal regions with similar behaviors, which are extracted by hierarchical clustering algorithms. A user interface with multiple-linked views is provided, which enables users to explore, locate, and compare regions that have similar behaviors between and then users can investigate and analyze the selected regions in detail. The driving application of this paper is the studies on regional emission influences over tropospheric ozone, which is based on ensemble simulations conducted with different anthropogenic emission absences using the MOZART-4 (model of ozone and related tracers, version 4) model. We demonstrate the effectiveness of our method by visualizing the MOZART-4 ensemble simulation data and evaluating the relative regional emission influences on tropospheric ozone concentrations. Positive feedbacks from domain experts and two case studies prove efficiency of our method.

Chimera at the phase-flip transition of an ensemble of identical nonlinear oscillators

Science.gov (United States)

Gopal, R.; Chandrasekar, V. K.; Senthilkumar, D. V.; Venkatesan, A.; Lakshmanan, M.

2018-06-01

A complex collective emerging behavior characterized by coexisting coherent and incoherent domains is termed as a chimera state. We bring out the existence of a new type of chimera in a nonlocally coupled ensemble of identical oscillators driven by a common dynamic environment. The latter facilitates the onset of phase-flip bifurcation/transitions among the coupled oscillators of the ensemble, while the nonlocal coupling induces a partial asynchronization among the out-of-phase synchronized oscillators at this onset. This leads to the manifestation of coexisting out-of-phase synchronized coherent domains interspersed by asynchronous incoherent domains elucidating the existence of a different type of chimera state. In addition to this, a rich variety of other collective behaviors such as clusters with phase-flip transition, conventional chimera, solitary state and complete synchronized state which have been reported using different coupling architectures are found to be induced by the employed couplings for appropriate coupling strengths. The robustness of the resulting dynamics is demonstrated in ensembles of two paradigmatic models, namely Rössler oscillators and Stuart-Landau oscillators.

Ensembler: Enabling High-Throughput Molecular Simulations at the Superfamily Scale.

Directory of Open Access Journals (Sweden)

Daniel L Parton

2016-06-01

Full Text Available The rapidly expanding body of available genomic and protein structural data provides a rich resource for understanding protein dynamics with biomolecular simulation. While computational infrastructure has grown rapidly, simulations on an omics scale are not yet widespread, primarily because software infrastructure to enable simulations at this scale has not kept pace. It should now be possible to study protein dynamics across entire (superfamilies, exploiting both available structural biology data and conformational similarities across homologous proteins. Here, we present a new tool for enabling high-throughput simulation in the genomics era. Ensembler takes any set of sequences-from a single sequence to an entire superfamily-and shepherds them through various stages of modeling and refinement to produce simulation-ready structures. This includes comparative modeling to all relevant PDB structures (which may span multiple conformational states of interest, reconstruction of missing loops, addition of missing atoms, culling of nearly identical structures, assignment of appropriate protonation states, solvation in explicit solvent, and refinement and filtering with molecular simulation to ensure stable simulation. The output of this pipeline is an ensemble of structures ready for subsequent molecular simulations using computer clusters, supercomputers, or distributed computing projects like Folding@home. Ensembler thus automates much of the time-consuming process of preparing protein models suitable for simulation, while allowing scalability up to entire superfamilies. A particular advantage of this approach can be found in the construction of kinetic models of conformational dynamics-such as Markov state models (MSMs-which benefit from a diverse array of initial configurations that span the accessible conformational states to aid sampling. We demonstrate the power of this approach by constructing models for all catalytic domains in the human

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.

Evaluation of denaturing gradient gel electrophoresis (DGGE) used ...

African Journals Online (AJOL)

Denaturing gradient gel electrophoresis (DGGE) is a powerful method used to study structure of bacterial communities, without cultivation, based on the diversity of the genes coding for ribosomal RNA. However, the results are strongly dependent on the respective target region of the used primer systems. Therefore, three ...

Can decadal climate predictions be improved by ocean ensemble dispersion filtering?

Science.gov (United States)

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

2017-12-01

Decadal predictions by Earth system models aim to capture the state and phase of the climate several years inadvance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-termweather forecasts represent an initial value problem and long-term climate projections represent a boundarycondition problem, the decadal climate prediction falls in-between these two time scales. The ocean memorydue to its heat capacity holds big potential skill on the decadal scale. In recent years, more precise initializationtechniques of coupled Earth system models (incl. atmosphere and ocean) have improved decadal predictions.Ensembles are another important aspect. Applying slightly perturbed predictions results in an ensemble. Insteadof using and evaluating one prediction, but the whole ensemble or its ensemble average, improves a predictionsystem. However, climate models in general start losing the initialized signal and its predictive skill from oneforecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improvedby a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. Wefound that this procedure, called ensemble dispersion filter, results in more accurate results than the standarddecadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions showan increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with largerensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from oceanensemble dispersion filtering toward the ensemble mean. This study is part of MiKlip (fona-miklip.de) - a major project on decadal climate prediction in Germany.We focus on the Max-Planck-Institute Earth System Model using the low-resolution version (MPI-ESM-LR) andMiKlip's basic initialization strategy as in 2017 published decadal climate forecast: http

Breaking of ensembles of linear and nonlinear oscillators

International Nuclear Information System (INIS)

Buts, V.A.

2016-01-01

Some results concerning the study of the dynamics of ensembles of linear and nonlinear oscillators are stated. It is shown that, in general, a stable ensemble of linear oscillator has a limited number of oscillators. This number has been defined for some simple models. It is shown that the features of the dynamics of linear oscillators can be used for conversion of the low-frequency energy oscillations into high frequency oscillations. The dynamics of coupled nonlinear oscillators in most cases is chaotic. For such a case, it is shown that the statistical characteristics (moments) of chaotic motion can significantly reduce potential barriers that keep the particles in the capture region

Heat capacity changes in RNA folding: application of perturbation theory to hammerhead ribozyme cold denaturation.

Science.gov (United States)

Mikulecky, Peter J; Feig, Andrew L

2004-01-01

In proteins, empirical correlations have shown that changes in heat capacity (DeltaC(P)) scale linearly with the hydrophobic surface area buried upon folding. The influence of DeltaC(P) on RNA folding has been widely overlooked and is poorly understood. In addition to considerations of solvent reorganization, electrostatic effects might contribute to DeltaC(P)s of folding in polyanionic species such as RNAs. Here, we employ a perturbation method based on electrostatic theory to probe the hot and cold denaturation behavior of the hammerhead ribozyme. This treatment avoids much of the error associated with imposing two-state folding models on non-two-state systems. Ribozyme stability is perturbed across a matrix of solvent conditions by varying the concentration of NaCl and methanol co-solvent. Temperature-dependent unfolding is then monitored by circular dichroism spectroscopy. The resulting array of unfolding transitions can be used to calculate a DeltaC(P) of folding that accurately predicts the observed cold denaturation temperature. We confirm the accuracy of the calculated DeltaC(P) by using isothermal titration calorimetry, and also demonstrate a methanol-dependence of the DeltaC(P). We weigh the strengths and limitations of this method for determining DeltaC(P) values. Finally, we discuss the data in light of the physical origins of the DeltaC(P)s for RNA folding and consider their impact on biological function.

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.

U.S. leans toward denatured thorium cycle

International Nuclear Information System (INIS)

Smock, R.

1977-01-01

Denatured thorium appears to be the most promising among the nonproliferating alternatives to the plutonium cycle, which the Carter Administration is trying to cancel. Criteria for a better system include uranium utilization comparable to current light water reactors and minimal separation of fissile material into the waste stream. Comparisons with other systems conclude that thorium is preferable because it can lead to an acceptable fast breeder. The thorium cycle can be placed in energy centers for sensitive facilities and can also be introduced into ongoing light water systems. Reprocessing can be handled in the centers, where thorium can be mixed with plutonium for use in reactors within the center, while light water reactors operate on the outside. Any fuel leaving the center would be unsuitable for weapons. Later adaptation to in-center fast breeders will extend energy supplies, although a thorium breeder will be less efficient than a plutonium fast breeder. Denatured thorium is a technical answer to a complex political problem, but those in the nuclear industry see the U.S. goal of a nonproliferating fuel as futile in the light of world politics and breeder efforts in other countries

Interaction of ATP with acid-denatured cytochrome c via coupled folding-binding mechanism

International Nuclear Information System (INIS)

Ahluwalia, Unnati; Deep, Shashank

2012-01-01

Highlights: ► Interaction between ATP and cyt c takes place via coupled binding–folding mechanism. ► Binding of ATP to cyt c is endothermic. ► GTP and CTP induce similar level of helicity in acid-denatured cyt c as with ATP. ► Compactness induced by ATP is far greater than ADP or AMP. - Abstract: The non-native conformations of the cytochrome c (cyt c) are believed to play key roles in a number of physiological processes. Nucleotides are supposed to act as allosteric effectors in these processes by regulating structural transitions among different conformations of cyt c. To understand the interaction between acid denatured cytochrome c and nucleotides, spectroscopic and calorimetric techniques were utilized to observe the structural features of the induced conformation and the energetics of interaction of acid denatured cyt c with different nucleotides. Structure induction in the acid denatured cyt c was observed on the addition of the ∼1 mM nucleotide tri-phosphates (ATP/GTP/CTP) at 25 °C, however, not in the presence of 1 mM nucleotide mono and diphosphates. ATP-bound cyt c at pH 2.0 is likely to have a conformation that has intact α-helical domain. However, Met80-Fe(III) axial bond is still ruptured. Observed thermodynamics reflect interaction between nucleotide and cyt c via coupled binding–folding mechanism. DSC data suggest the preferential binding of the ATP to the folded conformation with respect to the acid denatured cyt c. ITC data indicate that the exothermic folding of cyt c was accompanied by endothermic binding of ATP to cyt c.

State updating of a distributed hydrological model with Ensemble Kalman Filtering: Effects of updating frequency and observation network density on forecast accuracy

Science.gov (United States)

Rakovec, O.; Weerts, A.; Hazenberg, P.; Torfs, P.; Uijlenhoet, R.

2012-12-01

This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model (Rakovec et al., 2012a). The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property). Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a relatively quickly responding catchment in the Belgian Ardennes. The uncertain precipitation model forcings were obtained using a time-dependent multivariate spatial conditional simulation method (Rakovec et al., 2012b), which is further made conditional on preceding simulations. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty. Rakovec, O., Weerts, A. H., Hazenberg, P., Torfs, P. J. J. F., and Uijlenhoet, R.: State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy, Hydrol. Earth Syst. Sci. Discuss., 9, 3961-3999, doi:10.5194/hessd-9-3961-2012, 2012a. Rakovec, O., Hazenberg, P., Torfs, P. J. J. F., Weerts, A. H., and Uijlenhoet, R.: Generating spatial precipitation ensembles: impact of

Dynamical predictive power of the generalized Gibbs ensemble revealed in a second quench.

Science.gov (United States)

Zhang, J M; Cui, F C; Hu, Jiangping

2012-04-01

We show that a quenched and relaxed completely integrable system is hardly distinguishable from the corresponding generalized Gibbs ensemble in a dynamical sense. To be specific, the response of the quenched and relaxed system to a second quench can be accurately reproduced by using the generalized Gibbs ensemble as a substitute. Remarkably, as demonstrated with the transverse Ising model and the hard-core bosons in one dimension, not only the steady values but even the transient, relaxation dynamics of the physical variables can be accurately reproduced by using the generalized Gibbs ensemble as a pseudoinitial state. This result is an important complement to the previously established result that a quenched and relaxed system is hardly distinguishable from the generalized Gibbs ensemble in a static sense. The relevance of the generalized Gibbs ensemble in the nonequilibrium dynamics of completely integrable systems is then greatly strengthened.

Detection of human DNA polymorphisms with a simplified denaturing gradient gel electrophoresis technique.

OpenAIRE

Noll, W W; Collins, M

1987-01-01

Single base pair differences between otherwise identical DNA molecules can result in altered melting behavior detectable by denaturing gradient gel electrophoresis. We have developed a simplified procedure for using denaturing gradient gel electrophoresis to detect base pair changes in genomic DNA. Genomic DNA is digested with restriction enzymes and hybridized in solution to labeled single-stranded probe DNA. The excess probe is then hybridized to complementary phage M13 template DNA, and th...

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. © 2016 The Author(s).

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.

Representation of photon limited data in emission tomography using origin ensembles

OpenAIRE

Sitek, A

2008-01-01

Representation and reconstruction of data obtained by emission tomography scanners are challenging due to high noise levels in the data. Typically, images obtained using tomographic measurements are represented using grids. In this work, we define images as sets of origins of events detected during tomographic measurements; we call these origin ensembles (OEs). A state in the ensemble is characterized by a vector of 3N parameters Y, where the parameters are the coordinates of origins of detec...

Joys of Community Ensemble Playing: The Case of the Happy Roll Elastic Ensemble in Taiwan

Science.gov (United States)

Hsieh, Yuan-Mei; Kao, Kai-Chi

2012-01-01

The Happy Roll Elastic Ensemble (HREE) is a community music ensemble supported by Tainan Culture Centre in Taiwan. With enjoyment and friendship as its primary goals, it aims to facilitate the joys of ensemble playing and the spirit of social networking. This article highlights the key aspects of HREE's development in its first two years…

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.

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

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.

Gridded Calibration of Ensemble Wind Vector Forecasts Using Ensemble Model Output Statistics

Science.gov (United States)

Lazarus, S. M.; Holman, B. P.; Splitt, M. E.

2017-12-01

A computationally efficient method is developed that performs gridded post processing of ensemble wind vector forecasts. An expansive set of idealized WRF model simulations are generated to provide physically consistent high resolution winds over a coastal domain characterized by an intricate land / water mask. Ensemble model output statistics (EMOS) is used to calibrate the ensemble wind vector forecasts at observation locations. The local EMOS predictive parameters (mean and variance) are then spread throughout the grid utilizing flow-dependent statistical relationships extracted from the downscaled WRF winds. Using data withdrawal and 28 east central Florida stations, the method is applied to one year of 24 h wind forecasts from the Global Ensemble Forecast System (GEFS). Compared to the raw GEFS, the approach improves both the deterministic and probabilistic forecast skill. Analysis of multivariate rank histograms indicate the post processed forecasts are calibrated. Two downscaling case studies are presented, a quiescent easterly flow event and a frontal passage. Strengths and weaknesses of the approach are presented and discussed.

Membrane bridging and hemifusion by denaturated Munc18.

Directory of Open Access Journals (Sweden)

Yi Xu

Full Text Available Neuronal Munc18-1 and members of the Sec1/Munc18 (SM protein family play a critical function(s in intracellular membrane fusion together with SNARE proteins, but the mechanism of action of SM proteins remains highly enigmatic. During experiments designed to address this question employing a 7-nitrobenz-2-oxa-1,3-diazole (NBD fluorescence de-quenching assay that is widely used to study lipid mixing between reconstituted proteoliposomes, we observed that Munc18-1 from squid (sMunc18-1 was able to increase the apparent NBD fluorescence emission intensity even in the absence of SNARE proteins. Fluorescence emission scans and dynamic light scattering experiments show that this phenomenon arises at least in part from increased light scattering due to sMunc18-1-induced liposome clustering. Nuclear magnetic resonance and circular dichroism data suggest that, although native sMunc18-1 does not bind significantly to lipids, sMunc18-1 denaturation at 37 °C leads to insertion into membranes. The liposome clustering activity of sMunc18-1 can thus be attributed to its ability to bridge two membranes upon (perhaps partial denaturation; correspondingly, this activity is hindered by addition of glycerol. Cryo-electron microscopy shows that liposome clusters induced by sMunc18-1 include extended interfaces where the bilayers of two liposomes come into very close proximity, and clear hemifusion diaphragms. Although the physiological relevance of our results is uncertain, they emphasize the necessity of complementing fluorescence de-quenching assays with alternative experiments in studies of membrane fusion, as well as the importance of considering the potential effects of protein denaturation. In addition, our data suggest a novel mechanism of membrane hemifusion induced by amphipathic macromolecules that does not involve formation of a stalk intermediate.

Detection of human DNA polymorphisms with a simplified denaturing gradient gel electrophoresis technique

International Nuclear Information System (INIS)

Noll, W.W.; Collins, M.

1987-01-01

Single base pair differences between otherwise identical DNA molecules can result in altered melting behavior detectable by denaturing gradient gel electrophoresis. The authors have developed a simplified procedure for using denaturing gradient gel electrophoresis to detect base pair changes in genomic DNA. Genomic DNA is digested with restriction enzymes and hybridized in solution to labeled single-stranded probe DNA. The excess probe is then hybridized to complementary phage M13 template DNA, and the reaction mixture is electrophoresed on a denaturing gradient gel. Only the genomic DNA probe hybrids migrate into the gel. Differences in hybrid mobility on the gel indicate base pair changes in the genomic DNA. They have used this technique to identify two polymorphic sites within a 1.2-kilobase region of human chromosome 20. This approach should greatly facilitate the identification of DNA polymorphisms useful for gene linkage studies and the diagnosis of genetic diseases

Ensemble Modeling for Robustness Analysis in engineering non-native metabolic pathways.

Science.gov (United States)

Lee, Yun; Lafontaine Rivera, Jimmy G; Liao, James C

2014-09-01

Metabolic pathways in cells must be sufficiently robust to tolerate fluctuations in expression levels and changes in environmental conditions. Perturbations in expression levels may lead to system failure due to the disappearance of a stable steady state. Increasing evidence has suggested that biological networks have evolved such that they are intrinsically robust in their network structure. In this article, we presented Ensemble Modeling for Robustness Analysis (EMRA), which combines a continuation method with the Ensemble Modeling approach, for investigating the robustness issue of non-native pathways. EMRA investigates a large ensemble of reference models with different parameters, and determines the effects of parameter drifting until a bifurcation point, beyond which a stable steady state disappears and system failure occurs. A pathway is considered to have high bifurcational robustness if the probability of system failure is low in the ensemble. To demonstrate the utility of EMRA, we investigate the bifurcational robustness of two synthetic central metabolic pathways that achieve carbon conservation: non-oxidative glycolysis and reverse glyoxylate cycle. With EMRA, we determined the probability of system failure of each design and demonstrated that alternative designs of these pathways indeed display varying degrees of bifurcational robustness. Furthermore, we demonstrated that target selection for flux improvement should consider the trade-offs between robustness and performance. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

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.

Non-Boltzmann Ensembles and Monte Carlo Simulations

International Nuclear Information System (INIS)

Murthy, K. P. N.

2016-01-01

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

Heat denaturation of soy glycinin : Influence of pH and ionic strength on molecular structure

NARCIS (Netherlands)

Lakemond, C.M.M.; Jongh, de H.H.J.; Hessing, M.; Gruppen, H.; Voragen, A.G.J.

2000-01-01

The 7S/11S glycinin equilibrium as found in Lakemond et al. (J. Agric. Food Chem. 2000, 48, xxxx-xxxx) at ambient temperatures influences heat denaturation. It is found that the 7S form of glycinin denatures at a lower temperature than the 11S form, as demonstrated by a combination of calorimetric

Kinetic evidence for a two-stage mechanism of protein denaturation by guanidinium chloride.

Science.gov (United States)

Jha, Santosh Kumar; Marqusee, Susan

2014-04-01

Dry molten globular (DMG) intermediates, an expanded form of the native protein with a dry core, have been observed during denaturant-induced unfolding of many proteins. These observations are counterintuitive because traditional models of chemical denaturation rely on changes in solvent-accessible surface area, and there is no notable change in solvent-accessible surface area during the formation of the DMG. Here we show, using multisite fluorescence resonance energy transfer, far-UV CD, and kinetic thiol-labeling experiments, that the guanidinium chloride (GdmCl)-induced unfolding of RNase H also begins with the formation of the DMG. Population of the DMG occurs within the 5-ms dead time of our measurements. We observe that the size and/or population of the DMG is linearly dependent on [GdmCl], although not as strongly as the second and major step of unfolding, which is accompanied by core solvation and global unfolding. This rapid GdmCl-dependent population of the DMG indicates that GdmCl can interact with the protein before disrupting the hydrophobic core. These results imply that the effect of chemical denaturants cannot be interpreted solely as a disruption of the hydrophobic effect and strongly support recent computational studies, which hypothesize that chemical denaturants first interact directly with the protein surface before completely unfolding the protein in the second step (direct interaction mechanism).

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.

Ensembl 2002: accommodating comparative genomics.

Science.gov (United States)

Clamp, M; Andrews, D; Barker, D; Bevan, P; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Hubbard, T; Kasprzyk, A; Keefe, D; Lehvaslaiho, H; Iyer, V; Melsopp, C; Mongin, E; Pettett, R; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Birney, E

2003-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web site or as flat files. Ensembl also integrates manually annotated gene structures from external sources where available. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. These range from sequence analysis to data storage and visualisation and installations exist around the world in both companies and at academic sites. With both human and mouse genome sequences available and more vertebrate sequences to follow, many of the recent developments in Ensembl have focusing on developing automatic comparative genome analysis and visualisation.

Skill of Global Raw and Postprocessed Ensemble Predictions of Rainfall over Northern Tropical Africa

Science.gov (United States)

Vogel, Peter; Knippertz, Peter; Fink, Andreas H.; Schlueter, Andreas; Gneiting, Tilmann

2018-04-01

Accumulated precipitation forecasts are of high socioeconomic importance for agriculturally dominated societies in northern tropical Africa. In this study, we analyze the performance of nine operational global ensemble prediction systems (EPSs) relative to climatology-based forecasts for 1 to 5-day accumulated precipitation based on the monsoon seasons 2007-2014 for three regions within northern tropical Africa. To assess the full potential of raw ensemble forecasts across spatial scales, we apply state-of-the-art statistical postprocessing methods in form of Bayesian Model Averaging (BMA) and Ensemble Model Output Statistics (EMOS), and verify against station and spatially aggregated, satellite-based gridded observations. Raw ensemble forecasts are uncalibrated, unreliable, and underperform relative to climatology, independently of region, accumulation time, monsoon season, and ensemble. Differences between raw ensemble and climatological forecasts are large, and partly stem from poor prediction for low precipitation amounts. BMA and EMOS postprocessed forecasts are calibrated, reliable, and strongly improve on the raw ensembles, but - somewhat disappointingly - typically do not outperform climatology. Most EPSs exhibit slight improvements over the period 2007-2014, but overall have little added value compared to climatology. We suspect that the parametrization of convection is a potential cause for the sobering lack of ensemble forecast skill in a region dominated by mesoscale convective systems.

Verification of Ensemble Forecasts for the New York City Operations Support Tool

Science.gov (United States)

Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

2012-12-01

The New York City water supply system operated by the Department of Environmental Protection (DEP) serves nine million people. It covers 2,000 square miles of portions of the Catskill, Delaware, and Croton watersheds, and it includes nineteen reservoirs and three controlled lakes. DEP is developing an Operations Support Tool (OST) to support its water supply operations and planning activities. OST includes historical and real-time data, a model of the water supply system complete with operating rules, and lake water quality models developed to evaluate alternatives for managing turbidity in the New York City Catskill reservoirs. OST will enable DEP to manage turbidity in its unfiltered system while satisfying its primary objective of meeting the City's water supply needs, in addition to considering secondary objectives of maintaining ecological flows, supporting fishery and recreation releases, and mitigating downstream flood peaks. The current version of OST relies on statistical forecasts of flows in the system based on recent observed flows. To improve short-term decision making, plans are being made to transition to National Weather Service (NWS) ensemble forecasts based on hydrologic models that account for short-term weather forecast skill, longer-term climate information, as well as the hydrologic state of the watersheds and recent observed flows. To ensure that the ensemble forecasts are unbiased and that the ensemble spread reflects the actual uncertainty of the forecasts, a statistical model has been developed to post-process the NWS ensemble forecasts to account for hydrologic model error as well as any inherent bias and uncertainty in initial model states, meteorological data and forecasts. The post-processor is designed to produce adjusted ensemble forecasts that are consistent with the DEP historical flow sequences that were used to develop the system operating rules. A set of historical hindcasts that is representative of the real-time ensemble

NCAR's Experimental Real-time Convection-allowing Ensemble Prediction System

Science.gov (United States)

Schwartz, C. S.; Romine, G. S.; Sobash, R.; Fossell, K.

2016-12-01

Since April 2015, the National Center for Atmospheric Research's (NCAR's) Mesoscale and Microscale Meteorology (MMM) Laboratory, in collaboration with NCAR's Computational Information Systems Laboratory (CISL), has been producing daily, real-time, 10-member, 48-hr ensemble forecasts with 3-km horizontal grid spacing over the conterminous United States (http://ensemble.ucar.edu). These computationally-intensive, next-generation forecasts are produced on the Yellowstone supercomputer, have been embraced by both amateur and professional weather forecasters, are widely used by NCAR and university researchers, and receive considerable attention on social media. Initial conditions are supplied by NCAR's Data Assimilation Research Testbed (DART) software and the forecast model is NCAR's Weather Research and Forecasting (WRF) model; both WRF and DART are community tools. This presentation will focus on cutting-edge research results leveraging the ensemble dataset, including winter weather predictability, severe weather forecasting, and power outage modeling. Additionally, the unique design of the real-time analysis and forecast system and computational challenges and solutions will be described.

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 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 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.

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.

Denaturing of plutonium by transmutation of minor-actinides for enhancement of proliferation resistance

International Nuclear Information System (INIS)

Sagara, Hiroshi; Saito, Masaki; Peryoga, Yoga; Ezoubtchenko, Alexey; Takivayev, Alan

2005-01-01

Feasibility study for the plutonium denaturing by utilizing minor-actinide transmutation in light water reactors has been performed. And the intrinsic feature of proliferation resistance of plutonium has been discussed based on IAEA's publication and Kessler's proposal. The analytical results show that not only 238 Pu but also other plutonium isotopes with even-mass-number have very important role for denaturing of plutonium due to their relatively large critical mass and noticeably high spontaneous fission neutron generation. With the change of the minor-actinide doping ratio in U-Pu mix oxide fuel and moderator to fuel ratio, it is found that the reactor-grade plutonium from conventional light water reactors can be denatured to satisfy the proliferation resistance criterion based on the Kessler's proposal but not to be sufficient for the criterion based on IAEA's publication. It has been also confirmed that all the safety coefficients take negative value throughout the irradiation. (author)

Quantum and classical parallelism in parity algorithms for ensemble quantum computers

International Nuclear Information System (INIS)

Stadelhofer, Ralf; Suter, Dieter; Banzhaf, Wolfgang

2005-01-01

The determination of the parity of a string of N binary digits is a well-known problem in classical as well as quantum information processing, which can be formulated as an oracle problem. It has been established that quantum algorithms require at least N/2 oracle calls. We present an algorithm that reaches this lower bound and is also optimal in terms of additional gate operations required. We discuss its application to pure and mixed states. Since it can be applied directly to thermal states, it does not suffer from signal loss associated with pseudo-pure-state preparation. For ensemble quantum computers, the number of oracle calls can be further reduced by a factor 2 k , with k is a member of {{1,2,...,log 2 (N/2}}, provided the signal-to-noise ratio is sufficiently high. This additional speed-up is linked to (classical) parallelism of the ensemble quantum computer. Experimental realizations are demonstrated on a liquid-state NMR quantum computer

Thermal denaturation of sunflower globulins in low moisture conditions

International Nuclear Information System (INIS)

Rouilly, A.; Orliac, O.; Silvestre, F.; Rigal, L.

2003-01-01

DSC analysis in pressure resisting pans of sunflower oil cake makes appear the endothermic peak of sunflower globulins denaturation. Its temperature decreases from 189.5 to 119.9 deg. C while the corresponding enthalpy increases from 2.6 to 3.3 J/g of sample, or from 6.7 to 12.2 J/g of dry protein, when the samples moisture content varies from 0 to 30.0% of the total weight. The plot of the denaturation temperature versus the moisture content is not linear but has a rounded global shape and seems to follow the hydration behavior of the proteins, modeled with the sorption isotherm. As it can be seen on scanning electron microscopy (SEM) micrographs, protein corpuscles 'melt' after such a thermal treatment and large aggregates form by coagulation. Moisture dependence of the 'fusion' temperature of native proteic organization, in low moisture conditions, offers so a new characterization method for the use of vegetable proteins in agro-materials

Thermal denaturation of sunflower globulins in low moisture conditions

Energy Technology Data Exchange (ETDEWEB)

Rouilly, A.; Orliac, O.; Silvestre, F.; Rigal, L

2003-03-05

DSC analysis in pressure resisting pans of sunflower oil cake makes appear the endothermic peak of sunflower globulins denaturation. Its temperature decreases from 189.5 to 119.9 deg. C while the corresponding enthalpy increases from 2.6 to 3.3 J/g of sample, or from 6.7 to 12.2 J/g of dry protein, when the samples moisture content varies from 0 to 30.0% of the total weight. The plot of the denaturation temperature versus the moisture content is not linear but has a rounded global shape and seems to follow the hydration behavior of the proteins, modeled with the sorption isotherm. As it can be seen on scanning electron microscopy (SEM) micrographs, protein corpuscles 'melt' after such a thermal treatment and large aggregates form by coagulation. Moisture dependence of the 'fusion' temperature of native proteic organization, in low moisture conditions, offers so a new characterization method for the use of vegetable proteins in agro-materials.

Derivation of a thermodynamic closure relation in the isothermal-isobaric ensemble using quasi-Gaussian entropy theory

NARCIS (Netherlands)

Apol, M.E F; Amadei, A; Berendsen, H.J.C.

1996-01-01

In an analogous way as was done previously in the canonical ensemble, we derived for dilute gases an approximated thermodynamic closure relation in the isothermal-isobaric ensemble using quasi-Gaussian entropy theory. For the Gamma state, we formulated equations for the temperature dependence of

Evaluation of gasoline-denatured ethanol as a carbon source for denitrification.

Science.gov (United States)

Kazasi, Anna; Boardman, Gregory D; Bott, Charles B

2013-06-01

In this study concerning denitrification, the performance of three carbon sources, methanol (MeOH), ethanol (EtOH) and gasoline-denatured ethanol (dEtOH), was compared and evaluated on the basis of treatment efficiency, inhibition potential and cost. The gasoline denaturant considered here contained mostly aliphatic compounds and little of the components that typically boost the octane rating, such as benzene, toluene, ethylbenzene and xylenes. Results were obtained using three lab-scale SBRs operated at SRT of 12.0 +/- 0.9 days. After biomass was acclimated, denitrification rates with dEtOH were similar to those of EtOH (201 +/- 50 and 197 +/- 28 NO3-N/g MLVSS x d, respectively), and higher than those of MeOH (165 +/- 49 mg NO3-N/g MLVSS x d). The denaturant did not affect biomass production, nitrification or denitrification. Effluent soluble COD concentrations were always less than the analytical detection limit. Although the cost of dEtOH ($2.00/kg nitrate removed) was somewhat higher than that of methanol ($1.63/kg nitrate removed), the use of dEtOH is very promising and utilities will have to decide if it is worth paying a little extra to take advantage of its benefits.

Electron spin contrast of Purcell-enhanced nitrogen-vacancy ensembles in nanodiamonds

Science.gov (United States)

Bogdanov, S.; Shalaginov, M. Y.; Akimov, A.; Lagutchev, A. S.; Kapitanova, P.; Liu, J.; Woods, D.; Ferrera, M.; Belov, P.; Irudayaraj, J.; Boltasseva, A.; Shalaev, V. M.

2017-07-01

Nitrogen-vacancy centers in diamond allow for coherent spin-state manipulation at room temperature, which could bring dramatic advances to nanoscale sensing and quantum information technology. We introduce a method for the optical measurement of the spin contrast in dense nitrogen-vacancy (NV) ensembles. This method brings insight into the interplay between the spin contrast and fluorescence lifetime. We show that for improving the spin readout sensitivity in NV ensembles, one should aim at modifying the far-field radiation pattern rather than enhancing the emission rate.

Deterministic Mean-Field Ensemble Kalman Filtering

KAUST Repository

Law, Kody

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.

Deterministic Mean-Field Ensemble Kalman Filtering

KAUST Repository

Law, Kody; Tembine, Hamidou; Tempone, Raul

2016-01-01

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.

Musical ensembles in Ancient Mesapotamia

NARCIS (Netherlands)

Krispijn, T.J.H.; Dumbrill, R.; Finkel, I.

2010-01-01

Identification of musical instruments from ancient Mesopotamia by comparing musical ensembles attested in Sumerian and Akkadian texts with depicted ensembles. Lexicographical contributions to the Sumerian and Akkadian lexicon.

Constraining the ensemble Kalman filter for improved streamflow forecasting

Science.gov (United States)

Maxwell, Deborah H.; Jackson, Bethanna M.; McGregor, James

2018-05-01

Data assimilation techniques such as the Ensemble Kalman Filter (EnKF) are often applied to hydrological models with minimal state volume/capacity constraints enforced during ensemble generation. Flux constraints are rarely, if ever, applied. Consequently, model states can be adjusted beyond physically reasonable limits, compromising the integrity of model output. In this paper, we investigate the effect of constraining the EnKF on forecast performance. A "free run" in which no assimilation is applied is compared to a completely unconstrained EnKF implementation, a 'typical' hydrological implementation (in which mass constraints are enforced to ensure non-negativity and capacity thresholds of model states are not exceeded), and then to a more tightly constrained implementation where flux as well as mass constraints are imposed to force the rate of water movement to/from ensemble states to be within physically consistent boundaries. A three year period (2008-2010) was selected from the available data record (1976-2010). This was specifically chosen as it had no significant data gaps and represented well the range of flows observed in the longer dataset. Over this period, the standard implementation of the EnKF (no constraints) contained eight hydrological events where (multiple) physically inconsistent state adjustments were made. All were selected for analysis. Mass constraints alone did little to improve forecast performance; in fact, several were significantly degraded compared to the free run. In contrast, the combined use of mass and flux constraints significantly improved forecast performance in six events relative to all other implementations, while the remaining two events showed no significant difference in performance. Placing flux as well as mass constraints on the data assimilation framework encourages physically consistent state estimation and results in more accurate and reliable forward predictions of streamflow for robust decision-making. We also

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...

Multilevel ensemble Kalman filter

KAUST Repository

Chernov, Alexey; Hoel, Haakon; Law, Kody; Nobile, Fabio; Tempone, Raul

2016-01-01

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.

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.

Dynamics of heterogeneous oscillator ensembles in terms of collective variables

Science.gov (United States)

Pikovsky, Arkady; Rosenblum, Michael

2011-04-01

We consider general heterogeneous ensembles of phase oscillators, sine coupled to arbitrary external fields. Starting with the infinitely large ensembles, we extend the Watanabe-Strogatz theory, valid for identical oscillators, to cover the case of an arbitrary parameter distribution. The obtained equations yield the description of the ensemble dynamics in terms of collective variables and constants of motion. As a particular case of the general setup we consider hierarchically organized ensembles, consisting of a finite number of subpopulations, whereas the number of elements in a subpopulation can be both finite or infinite. Next, we link the Watanabe-Strogatz and Ott-Antonsen theories and demonstrate that the latter one corresponds to a particular choice of constants of motion. The approach is applied to the standard Kuramoto-Sakaguchi model, to its extension for the case of nonlinear coupling, and to the description of two interacting subpopulations, exhibiting a chimera state. With these examples we illustrate that, although the asymptotic dynamics can be found within the framework of the Ott-Antonsen theory, the transients depend on the constants of motion. The most dramatic effect is the dependence of the basins of attraction of different synchronous regimes on the initial configuration of phases.

Evaluation of bias-correction methods for ensemble streamflow volume forecasts

Directory of Open Access Journals (Sweden)

T. Hashino

2007-01-01

Full Text Available Ensemble prediction systems are used operationally to make probabilistic streamflow forecasts for seasonal time scales. However, hydrological models used for ensemble streamflow prediction often have simulation biases that degrade forecast quality and limit the operational usefulness of the forecasts. This study evaluates three bias-correction methods for ensemble streamflow volume forecasts. All three adjust the ensemble traces using a transformation derived with simulated and observed flows from a historical simulation. The quality of probabilistic forecasts issued when using the three bias-correction methods is evaluated using a distributions-oriented verification approach. Comparisons are made of retrospective forecasts of monthly flow volumes for a north-central United States basin (Des Moines River, Iowa, issued sequentially for each month over a 48-year record. The results show that all three bias-correction methods significantly improve forecast quality by eliminating unconditional biases and enhancing the potential skill. Still, subtle differences in the attributes of the bias-corrected forecasts have important implications for their use in operational decision-making. Diagnostic verification distinguishes these attributes in a context meaningful for decision-making, providing criteria to choose among bias-correction methods with comparable skill.

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

KAUST Repository

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

2016-01-01

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.

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.

Origins of protein denatured state compactness and hydrophobic clustering in aqueous urea: inferences from nonpolar potentials of mean force.

Science.gov (United States)

Shimizu, Seishi; Chan, Hue Sun

2002-12-01

Free energies of pairwise hydrophobic association are simulated in aqueous solutions of urea at concentrations ranging from 0-8 M. Consistent with the expectation that hydrophobic interactions are weakened by urea, the association of relatively large nonpolar solutes is destabilized by urea. However, the association of two small methane-sized nonpolar solutes in water has the opposite tendency of being slightly strengthened by the addition of urea. Such size effects and the dependence of urea-induced stability changes on the configuration of nonpolar solutes are not predicted by solvent accessible surface area approaches based on energetic parameters derived from bulk-phase solubilities of model compounds. Thus, to understand hydrophobic interactions in proteins, it is not sufficient to rely solely on transfer experiment data that effectively characterize a single nonpolar solute in an aqueous environment but not the solvent-mediated interactions among two or more nonpolar solutes. We find that the m-values for the rate of change of two-methane association free energy with respect to urea concentration is a dramatically nonmonotonic function of the spatial separation between the two methanes, with a distance-dependent profile similar to the corresponding two-methane heat capacity of association in pure water. Our results rationalize the persistence of residual hydrophobic contacts in some proteins at high urea concentrations and explain why the heat capacity signature (DeltaC(P)) of a compact denatured state can be similar to DeltaC(P) values calculated by assuming an open random-coil-like unfolded state. Copyright 2002 Wiley-Liss, Inc.

Origins of pressure-induced protein transitions.

Science.gov (United States)

Chalikian, Tigran V; Macgregor, Robert B

2009-12-18

The molecular mechanisms underlying pressure-induced protein denaturation can be analyzed based on the pressure-dependent differences in the apparent volume occupied by amino acids inside the protein and when they are exposed to water in an unfolded conformation. We present here an analysis for the peptide group and the 20 naturally occurring amino acid side chains based on volumetric parameters for the amino acids in the interior of the native state, the micelle-like interior of the pressure-induced denatured state, and the unfolded conformation modeled by N-acetyl amino acid amides. The transfer of peptide groups from the protein interior to water becomes increasingly favorable as pressure increases. Thus, solvation of peptide groups represents a major driving force in pressure-induced protein denaturation. Polar side chains do not appear to exhibit significant pressure-dependent changes in their preference for the protein interior or solvent. The transfer of nonpolar side chains from the protein interior to water becomes more unfavorable as pressure increases. We conclude that a sizeable population of nonpolar side chains remains buried inside a solvent-inaccessible core of the pressure-induced denatured state. At elevated pressures, this core may become packed almost as tightly as the interior of the native state. The presence and partial disappearance of large intraglobular voids is another driving force facilitating pressure-induced denaturation of individual proteins. Our data also have implications for the kinetics of protein folding and shed light on the nature of the folding transition state ensemble.

Multi-Model Ensemble Wake Vortex Prediction

Science.gov (United States)

Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

2015-01-01

Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

Unravelling the hydrophobicity of urea in water using thermodiffusion: implications for protein denaturation.

Science.gov (United States)

Niether, Doreen; Di Lecce, Silvia; Bresme, Fernando; Wiegand, Simone

2018-01-03

Urea is widely used as a protein denaturant in aqueous solutions. Experimental and computer simulation studies have shown that it dissolves in water almost ideally at high concentrations, introducing little disruption in the water hydrogen bonded structure. However, at concentrations of the order of 5 M or higher, urea induces denaturation in a wide range of proteins. The origin of this behaviour is not completely understood, but it is believed to stem from a balance between urea-protein and urea-water interactions, with urea becoming possibly hydrophobic at a specific concentration range. The small changes observed in the water structure make it difficult to connect the denaturation effects to the solvation properties. Here we show that the exquisite sensitivity of thermodiffusion to solute-water interactions allows the identification of the onset of hydrophobicity of urea-water mixtures. The hydrophobic behaviour is reflected in a sign reversal of the temperature dependent slope of the Soret coefficient, which is observed, both in experiments and non-equilibrium computer simulations at ∼5 M concentration of urea in water. This concentration regime corresponds to the one where abrupt changes in the denaturation of proteins are commonly observed. We show that the onset of hydrophobicity is intrinsically connected to the urea-water interactions. Our results allow us to identify correlations between the Soret coefficient and the partition coefficient, log P, hence establishing the thermodiffusion technique as a powerful approach to study hydrophobicity.

A correlated Walks' theory for DNA denaturation

International Nuclear Information System (INIS)

Mejdani, R.

1994-08-01

We have shown that by using a correlated Walks' theory for the lattice gas model on a one-dimensional lattice, we can study, beside the saturation curves obtained before for the enzyme kinetics, also the DNA denaturation process. In the limit of no interactions between sites the equation for melting curves of DNA reduces to the random model equation. Thus our leads naturally to this classical equation in the limiting case. (author). 22 refs, 3 figs

Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics

Institute of Scientific and Technical Information of China (English)

Zhaoxia PU; Joshua HACKER

2009-01-01

This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, ensemble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition (also called phase transition) and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined.

Monthly ENSO Forecast Skill and Lagged Ensemble Size

Science.gov (United States)

Trenary, L.; DelSole, T.; Tippett, M. K.; Pegion, K.

2018-04-01

The mean square error (MSE) of a lagged ensemble of monthly forecasts of the Niño 3.4 index from the Climate Forecast System (CFSv2) is examined with respect to ensemble size and configuration. Although the real-time forecast is initialized 4 times per day, it is possible to infer the MSE for arbitrary initialization frequency and for burst ensembles by fitting error covariances to a parametric model and then extrapolating to arbitrary ensemble size and initialization frequency. Applying this method to real-time forecasts, we find that the MSE consistently reaches a minimum for a lagged ensemble size between one and eight days, when four initializations per day are included. This ensemble size is consistent with the 8-10 day lagged ensemble configuration used operationally. Interestingly, the skill of both ensemble configurations is close to the estimated skill of the infinite ensemble. The skill of the weighted, lagged, and burst ensembles are found to be comparable. Certain unphysical features of the estimated error growth were tracked down to problems with the climatology and data discontinuities.

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

On the Use of Potential Denaturing Agents for Ethanol in Direct Ethanol Fuel Cells

OpenAIRE

Domnik Bayer; Florina Jung; Birgit Kintzel; Martin Joos; Carsten Cremers; Dierk Martin; Jörg Bernard; Jens Tübke

2011-01-01

Acidic or alkaline direct ethanol fuel cells (DEFCs) can be a sustainable alternative for power generation if they are fuelled with bio-ethanol. However, in order to keep the fuel cheap, ethanol has to be exempted from tax on spirits by denaturing. In this investigation the potential denaturing agents fusel oil, tert-butyl ethyl ether, and Bitrex were tested with regard to their compatibility with fuel cells. Experiments were carried out both in sulphuric acid and potassium hydroxide solution...

Alternative Hamiltonian for molecular dynamics simulations in the grand canonical ensemble

International Nuclear Information System (INIS)

Lo, C.; Palmer, B.

1995-01-01

An alternative to the Hamiltonian of Cagin and Pettitt for performing molecular dynamics simulations in the grand canonical ensemble is presented and used as the basis for a new algorithm. The algorithm is tested on the ideal gas and the truncated and shifted Lennard-Jones fluid. Simulations are used to calculate the vapor--liquid coexistence points for the Lennard-Jones system and are found to be in agreement with previous calculations using Gibbs ensemble calculations and with the Nicolas equation of state. Simulations are also performed on the Lennard-Jones solid

Coupling an Ensemble of Electrons on Superfluid Helium to a Superconducting Circuit

Directory of Open Access Journals (Sweden)

Ge Yang

2016-03-01

Full Text Available The quantized lateral motional states and the spin states of electrons trapped on the surface of superfluid helium have been proposed as basic building blocks of a scalable quantum computer. Circuit quantum electrodynamics allows strong dipole coupling between electrons and a high-Q superconducting microwave resonator, enabling such sensitive detection and manipulation of electron degrees of freedom. Here, we present the first realization of a hybrid circuit in which a large number of electrons are trapped on the surface of superfluid helium inside a coplanar waveguide resonator. The high finesse of the resonator allows us to observe large dispersive shifts that are many times the linewidth and make fast and sensitive measurements on the collective vibrational modes of the electron ensemble, as well as the superfluid helium film underneath. Furthermore, a large ensemble coupling is observed in the dispersive regime during experiment, and it shows excellent agreement with our numeric model. The coupling strength of the ensemble to the cavity is found to be ≈1  MHz per electron, indicating the feasibility of achieving single electron strong coupling.

Generalized ensemble method applied to study systems with strong first order transitions

Science.gov (United States)

Małolepsza, E.; Kim, J.; Keyes, T.

2015-09-01

At strong first-order phase transitions, the entropy versus energy or, at constant pressure, enthalpy, exhibits convex behavior, and the statistical temperature curve correspondingly exhibits an S-loop or back-bending. In the canonical and isothermal-isobaric ensembles, with temperature as the control variable, the probability density functions become bimodal with peaks localized outside of the S-loop region. Inside, states are unstable, and as a result simulation of equilibrium phase coexistence becomes impossible. To overcome this problem, a method was proposed by Kim, Keyes and Straub [1], where optimally designed generalized ensemble sampling was combined with replica exchange, and denoted generalized replica exchange method (gREM). This new technique uses parametrized effective sampling weights that lead to a unimodal energy distribution, transforming unstable states into stable ones. In the present study, the gREM, originally developed as a Monte Carlo algorithm, was implemented to work with molecular dynamics in an isobaric ensemble and coded into LAMMPS, a highly optimized open source molecular simulation package. The method is illustrated in a study of the very strong solid/liquid transition in water.

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

New technique for ensemble dressing combining Multimodel SuperEnsemble and precipitation PDF

Science.gov (United States)

Cane, D.; Milelli, M.

2009-09-01

The Multimodel SuperEnsemble technique (Krishnamurti et al., Science 285, 1548-1550, 1999) is a postprocessing method for the estimation of weather forecast parameters reducing direct model output errors. It differs from other ensemble analysis techniques by the use of an adequate weighting of the input forecast models to obtain a combined estimation of meteorological parameters. Weights are calculated by least-square minimization of the difference between the model and the observed field during a so-called training period. Although it can be applied successfully on the continuous parameters like temperature, humidity, wind speed and mean sea level pressure (Cane and Milelli, Meteorologische Zeitschrift, 15, 2, 2006), the Multimodel SuperEnsemble gives good results also when applied on the precipitation, a parameter quite difficult to handle with standard post-processing methods. Here we present our methodology for the Multimodel precipitation forecasts applied on a wide spectrum of results over Piemonte very dense non-GTS weather station network. We will focus particularly on an accurate statistical method for bias correction and on the ensemble dressing in agreement with the observed precipitation forecast-conditioned PDF. Acknowledgement: this work is supported by the Italian Civil Defence Department.

Denaturation of proteins by surfactants studied by the Taylor dispersion analysis.

Directory of Open Access Journals (Sweden)

Aldona Jelińska

Full Text Available We showed that the Taylor Dispersion Analysis (TDA is a fast and easy to use method for the study of denaturation proteins. We applied TDA to study denaturation of β-lactoglobulin, transferrin, and human insulin by anionic surfactant sodium dodecyl sulfate (SDS. A series of measurements at constant protein concentration (for transferrin was 1.9 x 10-5 M, for β- lactoglobulin was 7.6 x 10-5 M, and for insulin was 1.2 x 10-4 M and varying SDS concentrations were carried out in the phosphate-buffered saline (PBS. The structural changes were analyzed based on the diffusion coefficients of the complexes formed at various surfactant concentrations. The concentration of surfactant was varied in the range from 1.2 x 10-4 M to 8.7 x 10-2 M. We determined the minimum concentration of the surfactant necessary to change the native conformation of the proteins. The minimal concentration of SDS for β-lactoglobulin and transferrin was 4.3 x 10-4 M and for insulin 2.3 x 10-4 M. To evaluate the TDA as a novel method for studying denaturation of proteins we also applied other methods i.e. electronic circular dichroism (ECD and dynamic light scattering (DLS to study the same phenomenon. The results obtained using these methods were in agreement with the results from TDA.

The National Solo and Ensemble Contest 1929-1937

Science.gov (United States)

Meyers, Brian D.

2012-01-01

This study is the first investigation of the nine-year history of the National Solo and Ensemble Contests, held in the United States in conjunction with the National School Band and Orchestra Contests of the late 1920s and early to mid-1930s. Primary sources used include letters from those involved with the planning of the contests, meeting…

Effect of heating strategies on whey protein denaturation--Revisited by liquid chromatography quadrupole time-of-flight mass spectrometry.

Science.gov (United States)

Akkerman, M; Rauh, V M; Christensen, M; Johansen, L B; Hammershøj, M; Larsen, L B

2016-01-01

Previous standards in the area of effect of heat treatment processes on milk protein denaturation were based primarily on laboratory-scale analysis and determination of denaturation degrees by, for example, electrophoresis. In this study, whey protein denaturation was revisited by pilot-scale heating strategies and liquid chromatography quadrupole time-of-flight mass spectrometer (LC/MC Q-TOF) analysis. Skim milk was heat treated by the use of 3 heating strategies, namely plate heat exchanger (PHE), tubular heat exchanger (THE), and direct steam injection (DSI), under various heating temperatures (T) and holding times. The effect of heating strategy on the degree of denaturation of β-lactoglobulin and α-lactalbumin was determined using LC/MC Q-TOF of pH 4.5-soluble whey proteins. Furthermore, effect of heating strategy on the rennet-induced coagulation properties was studied by oscillatory rheometry. In addition, rennet-induced coagulation of heat-treated micellar casein concentrate subjected to PHE was studied. For skim milk, the whey protein denaturation increased significantly as T and holding time increased, regardless of heating method. High denaturation degrees were obtained for T >100°C using PHE and THE, whereas DSI resulted in significantly lower denaturation degrees, compared with PHE and THE. Rennet coagulation properties were impaired by increased T and holding time regardless of heating method, although DSI resulted in less impairment compared with PHE and THE. No significant difference was found between THE and PHE for effect on rennet coagulation time, whereas the curd firming rate was significantly larger for THE compared with PHE. Micellar casein concentrate possessed improved rennet coagulation properties compared with skim milk receiving equal heat treatment. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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 cou...

Hybrid quantum circuit with a superconducting qubit coupled to an electron spin ensemble

Energy Technology Data Exchange (ETDEWEB)

Kubo, Yuimaru; Grezes, Cecile; Vion, Denis; Esteve, Daniel; Bertet, Patrice [Quantronics Group, SPEC (CNRS URA 2464), CEA-Saclay, 91191 Gif-sur-Yvette (France); Diniz, Igor; Auffeves, Alexia [Institut Neel, CNRS, BP 166, 38042 Grenoble (France); Isoya, Jun-ichi [Research Center for Knowledge Communities, University of Tsukuba, 305-8550 Tsukuba (Japan); Jacques, Vincent; Dreau, Anais; Roch, Jean-Francois [LPQM (CNRS, UMR 8537), Ecole Normale Superieure de Cachan, 94235 Cachan (France)

2013-07-01

We report the experimental realization of a hybrid quantum circuit combining a superconducting qubit and an ensemble of electronic spins. The qubit, of the transmon type, is coherently coupled to the spin ensemble consisting of nitrogen-vacancy (NV) centers in a diamond crystal via a frequency-tunable superconducting resonator acting as a quantum bus. Using this circuit, we prepare arbitrary superpositions of the qubit states that we store into collective excitations of the spin ensemble and retrieve back into the qubit. We also report a new method for detecting the magnetic resonance of electronic spins at low temperature with a qubit using the hybrid quantum circuit, as well as our recent progress on spin echo experiments.

Stacking Ensemble Learning for Short-Term Electricity Consumption Forecasting

Directory of Open Access Journals (Sweden)

Federico Divina

2018-04-01

Full Text Available The ability to predict short-term electric energy demand would provide several benefits, both at the economic and environmental level. For example, it would allow for an efficient use of resources in order to face the actual demand, reducing the costs associated to the production as well as the emission of CO 2 . To this aim, in this paper we propose a strategy based on ensemble learning in order to tackle the short-term load forecasting problem. In particular, our approach is based on a stacking ensemble learning scheme, where the predictions produced by three base learning methods are used by a top level method in order to produce final predictions. We tested the proposed scheme on a dataset reporting the energy consumption in Spain over more than nine years. The obtained experimental results show that an approach for short-term electricity consumption forecasting based on ensemble learning can help in combining predictions produced by weaker learning methods in order to obtain superior results. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that using an ensemble scheme can achieve very accurate predictions, and thus that it is a suitable approach for addressing the short-term load forecasting problem.

Denaturation/Renaturation of Organophosphorus Acid Anhydrolase (OPAA) Using Guanidinium Hydrochloride and Urea

National Research Council Canada - National Science Library

Ong, K. K; Sun, Z; Cheng, T. C; Wei, Y; Yuan, J. M; Yin, R

2004-01-01

.... Using organophosphorus acid anhydrolase (OPAA) as the model protein, a guanidinium hydrochloride and urea denaturation/renaturation study was conducted and measured both optically and enzymatically...

Denaturation/Renaturation of Organophosphorus Acid Anhydrolase (OPAA) Using Guanidinium Hydrochloride and Urea

National Research Council Canada - National Science Library

Ong, K. K; Sun, Z; Cheng, T. C; Wei, Y; Yuan, J. M; Yin, R

2004-01-01

...; thereby indicating conformational changes. Similar results were obtained with circular dichroism as the peak representing the alpha-helix conformation decreased as denaturant concentration was increased...

Generating spin squeezing states and Greenberger-Horne-Zeilinger entanglement using a hybrid phonon-spin ensemble in diamond

Science.gov (United States)

Xia, Keyu; Twamley, Jason

2016-11-01

Quantum squeezing and entanglement of spins can be used to improve the sensitivity in quantum metrology. Here we propose a scheme to create collective coupling of an ensemble of spins to a mechanical vibrational mode actuated by an external magnetic field. We find an evolution time where the mechanical motion decouples from the spins, and the accumulated geometric phase yields a squeezing of 5.9 dB for 20 spins. We also show the creation of a Greenberger-Horne-Zeilinger spin state for 20 spins with a fidelity of ˜0.62 at cryogenic temperature. The numerical simulations show that the geometric-phase-based scheme is mostly immune to thermal mechanical noise.

A Theoretical Analysis of Why Hybrid Ensembles Work

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Kuo-Wei Hsu

2017-01-01

Full Text Available Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles.

Data assimilation for groundwater flow modelling using Unbiased Ensemble Square Root Filter: Case study in Guantao, North China Plain

Science.gov (United States)

Li, N.; Kinzelbach, W.; Li, H.; Li, W.; Chen, F.; Wang, L.

2017-12-01

Data assimilation techniques are widely used in hydrology to improve the reliability of hydrological models and to reduce model predictive uncertainties. This provides critical information for decision makers in water resources management. This study aims to evaluate a data assimilation system for the Guantao groundwater flow model coupled with a one-dimensional soil column simulation (Hydrus 1D) using an Unbiased Ensemble Square Root Filter (UnEnSRF) originating from the Ensemble Kalman Filter (EnKF) to update parameters and states, separately or simultaneously. To simplify the coupling between unsaturated and saturated zone, a linear relationship obtained from analyzing inputs to and outputs from Hydrus 1D is applied in the data assimilation process. Unlike EnKF, the UnEnSRF updates parameter ensemble mean and ensemble perturbations separately. In order to keep the ensemble filter working well during the data assimilation, two factors are introduced in the study. One is called damping factor to dampen the update amplitude of the posterior ensemble mean to avoid nonrealistic values. The other is called inflation factor to relax the posterior ensemble perturbations close to prior to avoid filter inbreeding problems. The sensitivities of the two factors are studied and their favorable values for the Guantao model are determined. The appropriate observation error and ensemble size were also determined to facilitate the further analysis. This study demonstrated that the data assimilation of both model parameters and states gives a smaller model prediction error but with larger uncertainty while the data assimilation of only model states provides a smaller predictive uncertainty but with a larger model prediction error. Data assimilation in a groundwater flow model will improve model prediction and at the same time make the model converge to the true parameters, which provides a successful base for applications in real time modelling or real time controlling strategies

Thermal stability of chemically denatured green fluorescent protein (GFP) A preliminary study

Energy Technology Data Exchange (ETDEWEB)

Nagy, Attila; Malnasi-Csizmadia, Andras; Somogyi, Bela; Lorinczy, Denes

2004-02-09

Green fluorescent protein (GFP) is a light emitter in the bioluminescence reaction of the jellyfish Aequorea victoria. The protein consist of 238 amino acids and produces green fluorescent light ({lambda}{sub max}=508 nm), when irradiated with near ultraviolet light. The fluorescence is due to the presence of chromophore consisting of an imidazolone ring, formed by a post-translational modification of the tripeptide -Ser{sup 65}-Tyr{sup 66}-Gly{sup 67}-, which buried into {beta}-barrel. GFP is extremely compact and heat stable molecule. In this work, we present data for the effect of chemical denaturing agent on the thermal stability of GFP. When denaturing agent is applied, global thermal stability and the melting point of the molecule is decreases, that can be monitored with differential scanning calorimetry. The results indicate, that in 1-6 M range of GuHCl the melting temperature is decreasing continuously from 83 to 38 deg. C. Interesting finding, that the calculated calorimetric enthalpy decreases with GuHCl concentration up to 3 M (5.6-0.2 kJ mol{sup -1}), but at 4 M it jumps to 8.4 and at greater concentration it is falling down to 1.1 kJ mol{sup -1}. First phenomena, i.e. the decrease of melting point with increasing GuHCl concentration can be easily explained by the effect of the extended chemical denaturation, when less and less amount of heat required to diminish the remaining hydrogen bonds in {beta}-barrel. The surprising increase of calorimetric enthalpy at 4 M concentration of GuHCl could be the consequence of a dimerization or a formation of stable complex between GFP and denaturing agent as well as a precipitation at an extreme GuHCl concentration. We are planning further experiments to elucidate fluorescent consequence of these processes.

New type of chimera and mutual synchronization of spatiotemporal structures in two coupled ensembles of nonlocally interacting chaotic maps

Science.gov (United States)

Bukh, Andrei; Rybalova, Elena; Semenova, Nadezhda; Strelkova, Galina; Anishchenko, Vadim

2017-11-01

We study numerically the dynamics of a network made of two coupled one-dimensional ensembles of discrete-time systems. The first ensemble is represented by a ring of nonlocally coupled Henon maps and the second one by a ring of nonlocally coupled Lozi maps. We find that the network of coupled ensembles can realize all the spatio-temporal structures which are observed both in the Henon map ensemble and in the Lozi map ensemble while uncoupled. Moreover, we reveal a new type of spatiotemporal structure, a solitary state chimera, in the considered network. We also establish and describe the effect of mutual synchronization of various complex spatiotemporal patterns in the system of two coupled ensembles of Henon and Lozi maps.

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.

Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

Science.gov (United States)

Wei, Jiangfeng; Dirmeyer, Paul A.; Yang, Zong-Liang; Chen, Haishan

2017-10-01

Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.

Improving wave forecasting by integrating ensemble modelling and machine learning

Science.gov (United States)

O'Donncha, F.; Zhang, Y.; James, S. C.

2017-12-01

Modern smart-grid networks use technologies to instantly relay information on supply and demand to support effective decision making. Integration of renewable-energy resources with these systems demands accurate forecasting of energy production (and demand) capacities. For wave-energy converters, this requires wave-condition forecasting to enable estimates of energy production. Current operational wave forecasting systems exhibit substantial errors with wave-height RMSEs of 40 to 60 cm being typical, which limits the reliability of energy-generation predictions thereby impeding integration with the distribution grid. In this study, we integrate physics-based models with statistical learning aggregation techniques that combine forecasts from multiple, independent models into a single "best-estimate" prediction of the true state. The Simulating Waves Nearshore physics-based model is used to compute wind- and currents-augmented waves in the Monterey Bay area. Ensembles are developed based on multiple simulations perturbing input data (wave characteristics supplied at the model boundaries and winds) to the model. A learning-aggregation technique uses past observations and past model forecasts to calculate a weight for each model. The aggregated forecasts are compared to observation data to quantify the performance of the model ensemble and aggregation techniques. The appropriately weighted ensemble model outperforms an individual ensemble member with regard to forecasting wave conditions.

Limit Cycles and Chaos via Quasi-periodicity in Two Coupled Ensembles of Ultra-cold Atoms.

Science.gov (United States)

Patra, Aniket; Yuzbashyan, Emil; Altshuler, Boris

We study the dynamics of two mesoscopic ensembles of ultra-cold two level atoms, which are collectively coupled to an optical cavity and are being pumped incoherently to the excited state. Whereas the time independent steady states are well understood, little is known about the time dependent ones. We explore and categorize various time dependent steady states, e.g. limit cycles and chaotic behavior. We draw a non-equilibrium phase diagram indicating different steady-state behaviors in different parts of the parameter space. We discuss the synchronization of the two ensembles in the time dependent steady states. We also show the onset of chaos via quasi-periodicity. The rich time dependent steady-state behavior, especially the existence of chaos, opens up possibilities for several engineering applications. Supported in part by the University and Louis Bevier Graduate Fellowship.

Three-dimensional theory of quantum memories based on Λ-type atomic ensembles

International Nuclear Information System (INIS)

Zeuthen, Emil; Grodecka-Grad, Anna; Soerensen, Anders S.

2011-01-01

We develop a three-dimensional theory for quantum memories based on light storage in ensembles of Λ-type atoms, where two long-lived atomic ground states are employed. We consider light storage in an ensemble of finite spatial extent and we show that within the paraxial approximation the Fresnel number of the atomic ensemble and the optical depth are the only important physical parameters determining the quality of the quantum memory. We analyze the influence of these parameters on the storage of light followed by either forward or backward read-out from the quantum memory. We show that for small Fresnel numbers the forward memory provides higher efficiencies, whereas for large Fresnel numbers the backward memory is advantageous. The optimal light modes to store in the memory are presented together with the corresponding spin waves and outcoming light modes. We show that for high optical depths such Λ-type atomic ensembles allow for highly efficient backward and forward memories even for small Fresnel numbers F(greater-or-similar sign)0.1.

Sequential Events in the Irreversible Thermal Denaturation of Human Brain-Type Creatine Kinase by Spectroscopic Methods

Directory of Open Access Journals (Sweden)

Yan-Song Gao

2010-06-01

Full Text Available The non-cooperative or sequential events which occur during protein thermal denaturation are closely correlated with protein folding, stability, and physiological functions. In this research, the sequential events of human brain-type creatine kinase (hBBCK thermal denaturation were studied by differential scanning calorimetry (DSC, CD, and intrinsic fluorescence spectroscopy. DSC experiments revealed that the thermal denaturation of hBBCK was calorimetrically irreversible. The existence of several endothermic peaks suggested that the denaturation involved stepwise conformational changes, which were further verified by the discrepancy in the transition curves obtained from various spectroscopic probes. During heating, the disruption of the active site structure occurred prior to the secondary and tertiary structural changes. The thermal unfolding and aggregation of hBBCK was found to occur through sequential events. This is quite different from that of muscle-type CK (MMCK. The results herein suggest that BBCK and MMCK undergo quite dissimilar thermal unfolding pathways, although they are highly conserved in the primary and tertiary structures. A minor difference in structure might endow the isoenzymes dissimilar local stabilities in structure, which further contribute to isoenzyme-specific thermal stabilities.

New concept of statistical ensembles

International Nuclear Information System (INIS)

Gorenstein, M.I.

2009-01-01

An extension of the standard concept of the statistical ensembles is suggested. Namely, the statistical ensembles with extensive quantities fluctuating according to an externally given distribution is introduced. Applications in the statistical models of multiple hadron production in high energy physics are discussed.

A class of energy-based ensembles in Tsallis statistics

International Nuclear Information System (INIS)

Chandrashekar, R; Naina Mohammed, S S

2011-01-01

A comprehensive investigation is carried out on the class of energy-based ensembles. The eight ensembles are divided into two main classes. In the isothermal class of ensembles the individual members are at the same temperature. A unified framework is evolved to describe the four isothermal ensembles using the currently accepted third constraint formalism. The isothermal–isobaric, grand canonical and generalized ensembles are illustrated through a study of the classical nonrelativistic and extreme relativistic ideal gas models. An exact calculation is possible only in the case of the isothermal–isobaric ensemble. The study of the ideal gas models in the grand canonical and the generalized ensembles has been carried out using a perturbative procedure with the nonextensivity parameter (1 − q) as the expansion parameter. Though all the thermodynamic quantities have been computed up to a particular order in (1 − q) the procedure can be extended up to any arbitrary order in the expansion parameter. In the adiabatic class of ensembles the individual members of the ensemble have the same value of the heat function and a unified formulation to described all four ensembles is given. The nonrelativistic and the extreme relativistic ideal gases are studied in the isoenthalpic–isobaric ensemble, the adiabatic ensemble with number fluctuations and the adiabatic ensemble with number and particle fluctuations

The Ensembl genome database project.

Science.gov (United States)

Hubbard, T; Barker, D; Birney, E; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Huminiecki, L; Kasprzyk, A; Lehvaslaiho, H; Lijnzaad, P; Melsopp, C; Mongin, E; Pettett, R; Pocock, M; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Clamp, M

2002-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of the human genome sequence, with confirmed gene predictions that have been integrated with external data sources, and is available as either an interactive web site or as flat files. It is also an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements from sequence analysis to data storage and visualisation. The Ensembl site is one of the leading sources of human genome sequence annotation and provided much of the analysis for publication by the international human genome project of the draft genome. The Ensembl system is being installed around the world in both companies and academic sites on machines ranging from supercomputers to laptops.

Comparative analyses of amplicon migration behavior in differing denaturing gradient gel electrophoresis (DGGE) systems

Science.gov (United States)

Thornhill, D. J.; Kemp, D. W.; Sampayo, E. M.; Schmidt, G. W.

2010-03-01

Denaturing gradient gel electrophoresis (DGGE) is commonly utilized to identify and quantify microbial diversity, but the conditions required for different electrophoretic systems to yield equivalent results and optimal resolution have not been assessed. Herein, the influence of different DGGE system configuration parameters on microbial diversity estimates was tested using Symbiodinium, a group of marine eukaryotic microbes that are important constituents of coral reef ecosystems. To accomplish this, bacterial clone libraries were constructed and sequenced from cultured isolates of Symbiodinium for the ribosomal DNA internal transcribed spacer 2 (ITS2) region. From these, 15 clones were subjected to PCR with a GC clamped primer set for DGGE analyses. Migration behaviors of the resulting amplicons were analyzed using a range of conditions, including variation in the composition of the denaturing gradient, electrophoresis time, and applied voltage. All tests were conducted in parallel on two commercial DGGE systems, a C.B.S. Scientific DGGE-2001, and the Bio-Rad DCode system. In this context, identical nucleotide fragments exhibited differing migration behaviors depending on the model of apparatus utilized, with fragments denaturing at a lower gradient concentration and applied voltage on the Bio-Rad DCode system than on the C.B.S. Scientific DGGE-2001 system. Although equivalent PCR-DGGE profiles could be achieved with both brands of DGGE system, the composition of the denaturing gradient and application of electrophoresis time × voltage must be appropriately optimized to achieve congruent results across platforms.

Hemichrome formation during hemoglobin Zurich denaturation

International Nuclear Information System (INIS)

Zago, M.A.; Costa, F.F.; Botura, C.; Baffa, O.

1988-01-01

Electron paramagnetic resonance (EPR)spectrum of hemoglobin Zurich, after oxidation, storage and heating, showed several absorption derives in the high field region (g ≅ 2) which are indicative of hemichrome formation. Characteristic visible spectra of hemichromes were observed for oxidized Hb Zurich and for its spontaneous precipitate. The proportional increase of EPR signals at g ≅ 2 and decrease at g = 6.37, the constant ratio of absorbance at 540 nm to 280 nm during heating, and the similarity of this ratio for spontaneously precipitated HbA and for Hb Zurich indicate that heme is not lost during the first steps of Hb Zurich denaturation. (author) [pt

Advanced Atmospheric Ensemble Modeling Techniques

Energy Technology Data Exchange (ETDEWEB)

Buckley, R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Chiswell, S. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Kurzeja, R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Maze, G. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Viner, B. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Werth, D. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2017-09-29

Ensemble modeling (EM), the creation of multiple atmospheric simulations for a given time period, has become an essential tool for characterizing uncertainties in model predictions. We explore two novel ensemble modeling techniques: (1) perturbation of model parameters (Adaptive Programming, AP), and (2) data assimilation (Ensemble Kalman Filter, EnKF). The current research is an extension to work from last year and examines transport on a small spatial scale (<100 km) in complex terrain, for more rigorous testing of the ensemble technique. Two different release cases were studied, a coastal release (SF6) and an inland release (Freon) which consisted of two release times. Observations of tracer concentration and meteorology are used to judge the ensemble results. In addition, adaptive grid techniques have been developed to reduce required computing resources for transport calculations. Using a 20- member ensemble, the standard approach generated downwind transport that was quantitatively good for both releases; however, the EnKF method produced additional improvement for the coastal release where the spatial and temporal differences due to interior valley heating lead to the inland movement of the plume. The AP technique showed improvements for both release cases, with more improvement shown in the inland release. This research demonstrated that transport accuracy can be improved when models are adapted to a particular location/time or when important local data is assimilated into the simulation and enhances SRNL’s capability in atmospheric transport modeling in support of its current customer base and local site missions, as well as our ability to attract new customers within the intelligence community.

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.

Atomistic structural ensemble refinement reveals non-native structure stabilizes a sub-millisecond folding intermediate of CheY

International Nuclear Information System (INIS)

Shi, Jade; Schwantes, Christian; Bilsel, Osman

2017-01-01

The dynamics of globular proteins can be described in terms of transitions between a folded native state and less-populated intermediates, or excited states, which can play critical roles in both protein folding and function. Excited states are by definition transient species, and therefore are difficult to characterize using current experimental techniques. We report an atomistic model of the excited state ensemble of a stabilized mutant of an extensively studied flavodoxin fold protein CheY. We employed a hybrid simulation and experimental approach in which an aggregate 42 milliseconds of all-atom molecular dynamics were used as an informative prior for the structure of the excited state ensemble. The resulting prior was then refined against small-angle X-ray scattering (SAXS) data employing an established method (EROS). The most striking feature of the resulting excited state ensemble was an unstructured N-terminus stabilized by non-native contacts in a conformation that is topologically simpler than the native state. We then predict incisive single molecule FRET experiments, using these results, as a means of model validation. Our study demonstrates the paradigm of uniting simulation and experiment in a statistical model to study the structure of protein excited states and rationally design validating experiments.

Chemical denaturation of globular proteins at the air/water interface: an x-ray and neutron reflectometry study

International Nuclear Information System (INIS)

Perriman, A.W.; Henderson, M.J.; White, J.W.

2003-01-01

Full text: X-ray and neutron reflectometry has been used to probe the equilibrium surface structure of hen egg white lysozyme (lysozyme) and bovine β -lactoglobulin (β -lactoglobulin) under denaturing conditions at the air-water interface. This was achieved by performing experiments on 10 mg mL -1 protein solutions containing increasing concentrations of the chemical denaturant guanidinium hydrochloride (G.HCl). For solutions containing no G.HCl, the surface structure of the proteins was represented by a two-layer model with total thicknesses of 48 Angstroms and 38 Angstroms for lysozyme and β -lactoglobulin, respectively. The total volume of a single protein molecule and the associated water molecules was evaluated to be approximately 45 (0.3) nm 3 for lysozyme, and 60 (0.3) nm 3 for β-lactoglobulin. The thickness dimensions and the total volumes compared favourably with the crystal dimensions of 45 x 30 x 30 Angstroms (40.5 nm 3 ),1 and 36 x 36 x 36 Angstroms (47 nm 3 ) 2 for lysozyme and β -lactoglobulin, respectively. This comparison suggests that when no denaturant was present, the structures of lysozyme and β -lactoglobulin were near to their native conformations at the air-water interface. The response to the presence of the chemical denaturant was different for each protein. The surface layer of β-lactoglobulin expanded at very low concentrations (0.2 mol dm -3 ) of G.HCl. In contrast, the lysozyme layer contracted. At higher concentrations, unfolding of both the proteins led to the formation of a third diffuse layer. In general, lysozyme appeared to be less responsive to the chemical denaturant, which is most likely a result of the higher disulfide content of lysozyme. A protocol allowing quantitative thermodynamic analysis of the contribution from the air-water interface to the chemical denaturation of a protein was developed

Light qubit storage and retrieval using macroscopic atomic ensembles

International Nuclear Information System (INIS)

Sherson, J.; Soerensen, A. S.; Polzik, E. S.; Fiurasek, J.; Moelmer, K.

2006-01-01

We present an experimentally feasible protocol for the complete storage and retrieval of arbitrary light states in an atomic quantum memory using the Faraday interaction between light and matter. Our protocol relies on multiple passages of a single light pulse through the atomic ensemble without the impractical requirement of kilometer-long delay lines between the passages. A time-dependent interaction strength enables the storage and retrieval of states with arbitrary pulse shapes. The fidelity approaches unity exponentially without squeezed or entangled initial states, as illustrated by calculations for a photonic qubit

Rotationally invariant family of Levy-like random matrix ensembles

International Nuclear Information System (INIS)

Choi, Jinmyung; Muttalib, K A

2009-01-01

We introduce a family of rotationally invariant random matrix ensembles characterized by a parameter λ. While λ = 1 corresponds to well-known critical ensembles, we show that λ ≠ 1 describes 'Levy-like' ensembles, characterized by power-law eigenvalue densities. For λ > 1 the density is bounded, as in Gaussian ensembles, but λ < 1 describes ensembles characterized by densities with long tails. In particular, the model allows us to evaluate, in terms of a novel family of orthogonal polynomials, the eigenvalue correlations for Levy-like ensembles. These correlations differ qualitatively from those in either the Gaussian or the critical ensembles. (fast track communication)

Diversity in random subspacing ensembles

NARCIS (Netherlands)

Tsymbal, A.; Pechenizkiy, M.; Cunningham, P.; Kambayashi, Y.; Mohania, M.K.; Wöß, W.

2004-01-01

Ensembles of learnt models constitute one of the main current directions in machine learning and data mining. It was shown experimentally and theoretically that in order for an ensemble to be effective, it should consist of classifiers having diversity in their predictions. A number of ways are

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...

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: use...... promising results have been obtained for both single (including charge transfer) and double excitations with spin-independent short-range local and semilocal functionals. Even at the Kohn-Sham ensemble DFT level, which is recovered when the range-separation parameter is set to 0, LIM performs better than...

AUC-Maximizing Ensembles through Metalearning.

Science.gov (United States)

LeDell, Erin; van der Laan, Mark J; Petersen, Maya

2016-05-01

Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree.

Urban runoff forecasting with ensemble weather predictions

DEFF Research Database (Denmark)

Pedersen, Jonas Wied; Courdent, Vianney Augustin Thomas; Vezzaro, Luca

This research shows how ensemble weather forecasts can be used to generate urban runoff forecasts up to 53 hours into the future. The results highlight systematic differences between ensemble members that needs to be accounted for when these forecasts are used in practice.......This research shows how ensemble weather forecasts can be used to generate urban runoff forecasts up to 53 hours into the future. The results highlight systematic differences between ensemble members that needs to be accounted for when these forecasts are used in practice....

Online Learning of Commission Avoidant Portfolio Ensembles

OpenAIRE

Uziel, Guy; El-Yaniv, Ran

2016-01-01

We present a novel online ensemble learning strategy for portfolio selection. The new strategy controls and exploits any set of commission-oblivious portfolio selection algorithms. The strategy handles transaction costs using a novel commission avoidance mechanism. We prove a logarithmic regret bound for our strategy with respect to optimal mixtures of the base algorithms. Numerical examples validate the viability of our method and show significant improvement over the state-of-the-art.

Two-dimensional salt and temperature DNA denaturation analysis using a magnetoresistive sensor

DEFF Research Database (Denmark)

Rizzi, Giovanni; Dufva, Martin; Hansen, Mikkel Fougt

2017-01-01

We present a microfluidic system and its use to measure DNA denaturation curves by varying the temperature or salt (Na+) concentration. The readout is based on real-time measurements of DNA hybridization using magnetoresistive sensors and magnetic nanoparticles (MNPs) as labels. We report the first...... melting curves of DNA hybrids measured as a function of continuously decreasing salt concentration at fixed temperature and compare them to the corresponding curves obtained vs. temperature at fixed salt concentration. The magnetoresistive sensor platform provided reliable results under varying....... The results demonstrate that concentration melting provides an attractive alternative to temperature melting in on-chip DNA denaturation experiments and further show that the magnetoresistive platform is attractive due to its low cross-sensitivity to temperature and liquid composition....

A Simple Ensemble Simulation Technique for Assessment of Future Variations in Specific High-Impact Weather Events

Science.gov (United States)

Taniguchi, Kenji

2018-04-01

To investigate future variations in high-impact weather events, numerous samples are required. For the detailed assessment in a specific region, a high spatial resolution is also required. A simple ensemble simulation technique is proposed in this paper. In the proposed technique, new ensemble members were generated from one basic state vector and two perturbation vectors, which were obtained by lagged average forecasting simulations. Sensitivity experiments with different numbers of ensemble members, different simulation lengths, and different perturbation magnitudes were performed. Experimental application to a global warming study was also implemented for a typhoon event. Ensemble-mean results and ensemble spreads of total precipitation, atmospheric conditions showed similar characteristics across the sensitivity experiments. The frequencies of the maximum total and hourly precipitation also showed similar distributions. These results indicate the robustness of the proposed technique. On the other hand, considerable ensemble spread was found in each ensemble experiment. In addition, the results of the application to a global warming study showed possible variations in the future. These results indicate that the proposed technique is useful for investigating various meteorological phenomena and the impacts of global warming. The results of the ensemble simulations also enable the stochastic evaluation of differences in high-impact weather events. In addition, the impacts of a spectral nudging technique were also examined. The tracks of a typhoon were quite different between cases with and without spectral nudging; however, the ranges of the tracks among ensemble members were comparable. It indicates that spectral nudging does not necessarily suppress ensemble spread.

Dependence of high density nitrogen-vacancy center ensemble coherence on electron irradiation doses and annealing time

Science.gov (United States)

Zhang, C.; Yuan, H.; Zhang, N.; Xu, L. X.; Li, B.; Cheng, G. D.; Wang, Y.; Gui, Q.; Fang, J. C.

2017-12-01

Negatively charged nitrogen-vacancy (NV-) center ensembles in diamond have proved to have great potential for use in highly sensitive, small-package solid-state quantum sensors. One way to improve sensitivity is to produce a high-density NV- center ensemble on a large scale with a long coherence lifetime. In this work, the NV- center ensemble is prepared in type-Ib diamond using high energy electron irradiation and annealing, and the transverse relaxation time of the ensemble—T 2—was systematically investigated as a function of the irradiation electron dose and annealing time. Dynamical decoupling sequences were used to characterize T 2. To overcome the problem of low signal-to-noise ratio in T 2 measurement, a coupled strip lines waveguide was used to synchronously manipulate NV- centers along three directions to improve fluorescence signal contrast. Finally, NV- center ensembles with a high concentration of roughly 1015 mm-3 were manipulated within a ~10 µs coherence time. By applying a multi-coupled strip-lines waveguide to improve the effective volume of the diamond, a sub-femtotesla sensitivity for AC field magnetometry can be achieved. The long-coherence high-density large-scale NV- center ensemble in diamond means that types of room-temperature micro-sized solid-state quantum sensors with ultra-high sensitivity can be further developed in the near future.

Does internal variability change in response to global warming? A large ensemble modelling study of tropical rainfall

Science.gov (United States)

Milinski, S.; Bader, J.; Jungclaus, J. H.; Marotzke, J.

2017-12-01

There is some consensus on mean state changes of rainfall under global warming; changes of the internal variability, on the other hand, are more difficult to analyse and have not been discussed as much despite their importance for understanding changes in extreme events, such as droughts or floodings. We analyse changes in the rainfall variability in the tropical Atlantic region. We use a 100-member ensemble of historical (1850-2005) model simulations with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1) to identify changes of internal rainfall variability. To investigate the effects of global warming on the internal variability, we employ an additional ensemble of model simulations with stronger external forcing (1% CO2-increase per year, same integration length as the historical simulations) with 68 ensemble members. The focus of our study is on the oceanic Atlantic ITCZ. We find that the internal variability of rainfall over the tropical Atlantic does change due to global warming and that these changes in variability are larger than changes in the mean state in some regions. From splitting the total variance into patterns of variability, we see that the variability on the southern flank of the ITCZ becomes more dominant, i.e. explaining a larger fraction of the total variance in a warmer climate. In agreement with previous studies, we find that changes in the mean state show an increase and narrowing of the ITCZ. The large ensembles allow us to do a statistically robust differentiation between the changes in variability that can be explained by internal variability and those that can be attributed to the external forcing. Furthermore, we argue that internal variability in a transient climate is only well defined in the ensemble domain and not in the temporal domain, which requires the use of a large ensemble.

Analyzing a steady-state phenomenon using an ensemble of sequential transient events: A proof of concept on photocurrent of bacteriorhodopsin upon continuous photoexcitation

Energy Technology Data Exchange (ETDEWEB)

Hung, Chang-Wei; Chu, Li-Kang, E-mail: lkchu@mx.nthu.edu.tw [Department of Chemistry, National Tsing Hua University, 101, Sec. 2, Kuang-Fu Rd., Hsinchu 30013, Taiwan (China); Ho, Ching-Hwa [Interdisplinary Program of Science, National Tsing Hua University, 101, Sec. 2, Kuang-Fu Rd., Hsinchu 30013, Taiwan (China)

2014-10-14

The proton pump activity of bacteriorhodopsin in aqueous solution upon excitation with modulated continuous light was monitored electrochemically and analyzed by superimposing a series of transient proton translocation events Hᵢ⁺(t). An evolution function f(t)=(he{sup –lt}+k)/(h+k) , including a decay and a stationary offset, was introduced to weight the contribution of the individual transient events evolving with time in the envelope of the steady-state event. The evolution of the total proton concentration can be treated as an ensemble of weighted sequential transient events, H{sub total}⁺(t)=Σ{{sub i=0}sup n}Hᵢ⁺(t)∙f(t), and the temporal profile of the photocurrent is derived by differentiating the proton concentration with respect to time, (table) . The temporal profiles of the bacteriorhodopsin photocurrent in pH range of 6.3–8.1 were analyzed using a well-defined kinetics model and restricted mathematical formulization, and fitted temporal behaviors agreed with the observations. This successful proof-of-concept study on analyzing a steady-state phenomenon using an ensemble of sequential transient events can be generalized to quantify other phenomena upon continuous stimulation, such as estimation of the light-driven ion pump activities of the photosynthetic proteins upon illumination.

A retrospective streamflow ensemble forecast for an extreme hydrologic event: a case study of Hurricane Irene and on the Hudson River basin

Science.gov (United States)

Saleh, Firas; Ramaswamy, Venkatsundar; Georgas, Nickitas; Blumberg, Alan F.; Pullen, Julie

2016-07-01

This paper investigates the uncertainties in hourly streamflow ensemble forecasts for an extreme hydrological event using a hydrological model forced with short-range ensemble weather prediction models. A state-of-the art, automated, short-term hydrologic prediction framework was implemented using GIS and a regional scale hydrological model (HEC-HMS). The hydrologic framework was applied to the Hudson River basin ( ˜ 36 000 km2) in the United States using gridded precipitation data from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) and was validated against streamflow observations from the United States Geologic Survey (USGS). Finally, 21 precipitation ensemble members of the latest Global Ensemble Forecast System (GEFS/R) were forced into HEC-HMS to generate a retrospective streamflow ensemble forecast for an extreme hydrological event, Hurricane Irene. The work shows that ensemble stream discharge forecasts provide improved predictions and useful information about associated uncertainties, thus improving the assessment of risks when compared with deterministic forecasts. The uncertainties in weather inputs may result in false warnings and missed river flooding events, reducing the potential to effectively mitigate flood damage. The findings demonstrate how errors in the ensemble median streamflow forecast and time of peak, as well as the ensemble spread (uncertainty) are reduced 48 h pre-event by utilizing the ensemble framework. The methodology and implications of this work benefit efforts of short-term streamflow forecasts at regional scales, notably regarding the peak timing of an extreme hydrologic event when combined with a flood threshold exceedance diagram. Although the modeling framework was implemented on the Hudson River basin, it is flexible and applicable in other parts of the world where atmospheric reanalysis products and streamflow data are available.

Potentialities of ensemble strategies for flood forecasting over the Milano urban area

Science.gov (United States)

Ravazzani, Giovanni; Amengual, Arnau; Ceppi, Alessandro; Homar, Víctor; Romero, Romu; Lombardi, Gabriele; Mancini, Marco

2016-08-01

Analysis of ensemble forecasting strategies, which can provide a tangible backing for flood early warning procedures and mitigation measures over the Mediterranean region, is one of the fundamental motivations of the international HyMeX programme. Here, we examine two severe hydrometeorological episodes that affected the Milano urban area and for which the complex flood protection system of the city did not completely succeed. Indeed, flood damage have exponentially increased during the last 60 years, due to industrial and urban developments. Thus, the improvement of the Milano flood control system needs a synergism between structural and non-structural approaches. First, we examine how land-use changes due to urban development have altered the hydrological response to intense rainfalls. Second, we test a flood forecasting system which comprises the Flash-flood Event-based Spatially distributed rainfall-runoff Transformation, including Water Balance (FEST-WB) and the Weather Research and Forecasting (WRF) models. Accurate forecasts of deep moist convection and extreme precipitation are difficult to be predicted due to uncertainties arising from the numeric weather prediction (NWP) physical parameterizations and high sensitivity to misrepresentation of the atmospheric state; however, two hydrological ensemble prediction systems (HEPS) have been designed to explicitly cope with uncertainties in the initial and lateral boundary conditions (IC/LBCs) and physical parameterizations of the NWP model. No substantial differences in skill have been found between both ensemble strategies when considering an enhanced diversity of IC/LBCs for the perturbed initial conditions ensemble. Furthermore, no additional benefits have been found by considering more frequent LBCs in a mixed physics ensemble, as ensemble spread seems to be reduced. These findings could help to design the most appropriate ensemble strategies before these hydrometeorological extremes, given the computational

Coherent Rabi Dynamics of a Superradiant Spin Ensemble in a Microwave Cavity

Science.gov (United States)

Rose, B. C.; Tyryshkin, A. M.; Riemann, H.; Abrosimov, N. V.; Becker, P.; Pohl, H.-J.; Thewalt, M. L. W.; Itoh, K. M.; Lyon, S. A.

2017-07-01

We achieve the strong-coupling regime between an ensemble of phosphorus donor spins in a highly enriched 28Si crystal and a 3D dielectric resonator. Spins are polarized beyond Boltzmann equilibrium using spin-selective optical excitation of the no-phonon bound exciton transition resulting in N =3.6 ×1 013 unpaired spins in the ensemble. We observe a normal mode splitting of the spin-ensemble-cavity polariton resonances of 2 g √{N }=580 kHz (where each spin is coupled with strength g ) in a cavity with a quality factor of 75 000 (γ ≪κ ≈60 kHz , where γ and κ are the spin dephasing and cavity loss rates, respectively). The spin ensemble has a long dephasing time (T2*=9 μ s ) providing a wide window for viewing the dynamics of the coupled spin-ensemble-cavity system. The free-induction decay shows up to a dozen collapses and revivals revealing a coherent exchange of excitations between the superradiant state of the spin ensemble and the cavity at the rate g √{N }. The ensemble is found to evolve as a single large pseudospin according to the Tavis-Cummings model due to minimal inhomogeneous broadening and uniform spin-cavity coupling. We demonstrate independent control of the total spin and the initial Z projection of the psuedospin using optical excitation and microwave manipulation, respectively. We vary the microwave excitation power to rotate the pseudospin on the Bloch sphere and observe a long delay in the onset of the superradiant emission as the pseudospin approaches full inversion. This delay is accompanied by an abrupt π -phase shift in the peusdospin microwave emission. The scaling of this delay with the initial angle and the sudden phase shift are explained by the Tavis-Cummings model.

Intrinsic alterations in the partial molar volume on the protein denaturation: surficial Kirkwood-Buff approach.

Science.gov (United States)

Yu, Isseki; Takayanagi, Masayoshi; Nagaoka, Masataka

2009-03-19

The partial molar volume (PMV) of the protein chymotrypsin inhibitor 2 (CI2) was calculated by all-atom MD simulation. Denatured CI2 showed almost the same average PMV value as that of native CI2. This is consistent with the phenomenological question of the protein volume paradox. Furthermore, using the surficial Kirkwood-Buff approach, spatial distributions of PMV were analyzed as a function of the distance from the CI2 surface. The profiles of the new R-dependent PMV indicate that, in denatured CI2, the reduction in the solvent electrostatic interaction volume is canceled out mainly by an increment in thermal volume in the vicinity of its surface. In addition, the PMV of the denatured CI2 was found to increase in the region in which the number density of water atoms is minimum. These results provide a direct and detailed picture of the mechanism of the protein volume paradox suggested by Chalikian et al.

Proposed hybrid-classifier ensemble algorithm to map snow cover area

Science.gov (United States)

Nijhawan, Rahul; Raman, Balasubramanian; Das, Josodhir

2018-01-01

Metaclassification ensemble approach is known to improve the prediction performance of snow-covered area. The methodology adopted in this case is based on neural network along with four state-of-art machine learning algorithms: support vector machine, artificial neural networks, spectral angle mapper, K-mean clustering, and a snow index: normalized difference snow index. An AdaBoost ensemble algorithm related to decision tree for snow-cover mapping is also proposed. According to available literature, these methods have been rarely used for snow-cover mapping. Employing the above techniques, a study was conducted for Raktavarn and Chaturangi Bamak glaciers, Uttarakhand, Himalaya using multispectral Landsat 7 ETM+ (enhanced thematic mapper) image. The study also compares the results with those obtained from statistical combination methods (majority rule and belief functions) and accuracies of individual classifiers. Accuracy assessment is performed by computing the quantity and allocation disagreement, analyzing statistic measures (accuracy, precision, specificity, AUC, and sensitivity) and receiver operating characteristic curves. A total of 225 combinations of parameters for individual classifiers were trained and tested on the dataset and results were compared with the proposed approach. It was observed that the proposed methodology produced the highest classification accuracy (95.21%), close to (94.01%) that was produced by the proposed AdaBoost ensemble algorithm. From the sets of observations, it was concluded that the ensemble of classifiers produced better results compared to individual classifiers.

Bayesian ensemble refinement by replica simulations and reweighting

Science.gov (United States)

Hummer, Gerhard; Köfinger, Jürgen

2015-12-01

We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.

Multi-criterion model ensemble of CMIP5 surface air temperature over China

Science.gov (United States)

Yang, Tiantian; Tao, Yumeng; Li, Jingjing; Zhu, Qian; Su, Lu; He, Xiaojia; Zhang, Xiaoming

2018-05-01

The global circulation models (GCMs) are useful tools for simulating climate change, projecting future temperature changes, and therefore, supporting the preparation of national climate adaptation plans. However, different GCMs are not always in agreement with each other over various regions. The reason is that GCMs' configurations, module characteristics, and dynamic forcings vary from one to another. Model ensemble techniques are extensively used to post-process the outputs from GCMs and improve the variability of model outputs. Root-mean-square error (RMSE), correlation coefficient (CC, or R) and uncertainty are commonly used statistics for evaluating the performances of GCMs. However, the simultaneous achievements of all satisfactory statistics cannot be guaranteed in using many model ensemble techniques. In this paper, we propose a multi-model ensemble framework, using a state-of-art evolutionary multi-objective optimization algorithm (termed MOSPD), to evaluate different characteristics of ensemble candidates and to provide comprehensive trade-off information for different model ensemble solutions. A case study of optimizing the surface air temperature (SAT) ensemble solutions over different geographical regions of China is carried out. The data covers from the period of 1900 to 2100, and the projections of SAT are analyzed with regard to three different statistical indices (i.e., RMSE, CC, and uncertainty). Among the derived ensemble solutions, the trade-off information is further analyzed with a robust Pareto front with respect to different statistics. The comparison results over historical period (1900-2005) show that the optimized solutions are superior over that obtained simple model average, as well as any single GCM output. The improvements of statistics are varying for different climatic regions over China. Future projection (2006-2100) with the proposed ensemble method identifies that the largest (smallest) temperature changes will happen in the

Monte Carlo Molecular Simulation with Isobaric-Isothermal and Gibbs-NPT Ensembles

KAUST Repository

Du, Shouhong

2012-01-01

This thesis presents Monte Carlo methods for simulations of phase behaviors of Lennard-Jones fluids. The isobaric-isothermal (NPT) ensemble and Gibbs-NPT ensemble are introduced in detail. NPT ensemble is employed to determine the phase diagram of pure component. The reduced simulation results are verified by comparison with the equation of state by by Johnson et al. and results with L-J parameters of methane agree considerably with the experiment measurements. We adopt the blocking method for variance estimation and error analysis of the simulation results. The relationship between variance and number of Monte Carlo cycles, error propagation and Random Number Generator performance are also investigated. We review the Gibbs-NPT ensemble employed for phase equilibrium of binary mixture. The phase equilibrium is achieved by performing three types of trial move: particle displacement, volume rearrangement and particle transfer. The simulation models and the simulation details are introduced. The simulation results of phase coexistence for methane and ethane are reported with comparison of the experimental data. Good agreement is found for a wide range of pressures. The contribution of this thesis work lies in the study of the error analysis with respect to the Monte Carlo cycles and number of particles in some interesting aspects.

Monte Carlo Molecular Simulation with Isobaric-Isothermal and Gibbs-NPT Ensembles

KAUST Repository

Du, Shouhong

2012-05-01

This thesis presents Monte Carlo methods for simulations of phase behaviors of Lennard-Jones fluids. The isobaric-isothermal (NPT) ensemble and Gibbs-NPT ensemble are introduced in detail. NPT ensemble is employed to determine the phase diagram of pure component. The reduced simulation results are verified by comparison with the equation of state by by Johnson et al. and results with L-J parameters of methane agree considerably with the experiment measurements. We adopt the blocking method for variance estimation and error analysis of the simulation results. The relationship between variance and number of Monte Carlo cycles, error propagation and Random Number Generator performance are also investigated. We review the Gibbs-NPT ensemble employed for phase equilibrium of binary mixture. The phase equilibrium is achieved by performing three types of trial move: particle displacement, volume rearrangement and particle transfer. The simulation models and the simulation details are introduced. The simulation results of phase coexistence for methane and ethane are reported with comparison of the experimental data. Good agreement is found for a wide range of pressures. The contribution of this thesis work lies in the study of the error analysis with respect to the Monte Carlo cycles and number of particles in some interesting aspects.

Evaluation of medium-range ensemble flood forecasting based on calibration strategies and ensemble methods in Lanjiang Basin, Southeast China

Science.gov (United States)

Liu, Li; Gao, Chao; Xuan, Weidong; Xu, Yue-Ping

2017-11-01

Ensemble flood forecasts by hydrological models using numerical weather prediction products as forcing data are becoming more commonly used in operational flood forecasting applications. In this study, a hydrological ensemble flood forecasting system comprised of an automatically calibrated Variable Infiltration Capacity 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 the parallel programmed ε-NSGA II multi-objective algorithm. According to the solutions by ε-NSGA II, two differently parameterized models are determined to simulate daily flows and peak flows at each of the three hydrological stations. Then a simple yet effective modular approach is proposed to combine these daily and peak flows at the same station into one composite series. Five ensemble methods and various evaluation metrics are adopted. The results show that ε-NSGA II can provide an objective determination on parameter estimation, and the parallel program permits a more efficient simulation. It is also demonstrated that the forecasts from ECMWF have more favorable skill scores than other Ensemble Prediction Systems. The multimodel ensembles have advantages over all the single model ensembles and the multimodel methods weighted on members and skill scores outperform other methods. Furthermore, the overall performance at three stations can be satisfactory up to ten days, however the hydrological errors can degrade the skill score by approximately 2 days, and the influence persists until a lead time of 10 days with a weakening trend. With respect to peak flows selected by the Peaks Over Threshold approach, the ensemble means from single models or multimodels are generally underestimated, indicating that the ensemble mean can bring overall improvement in forecasting of flows. For

Ensemble method for dengue prediction.

Science.gov (United States)

Buczak, Anna L; Baugher, Benjamin; Moniz, Linda J; Bagley, Thomas; Babin, Steven M; Guven, Erhan

2018-01-01

In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico) during four dengue seasons: 1) peak height (i.e., maximum weekly number of cases during a transmission season; 2) peak week (i.e., week in which the maximum weekly number of cases occurred); and 3) total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date. Our approach used ensemble models created by combining three disparate types of component models: 1) two-dimensional Method of Analogues models incorporating both dengue and climate data; 2) additive seasonal Holt-Winters models with and without wavelet smoothing; and 3) simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations. Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week. The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

Ensemble method for dengue prediction.

Directory of Open Access Journals (Sweden)

Anna L Buczak

Full Text Available In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico during four dengue seasons: 1 peak height (i.e., maximum weekly number of cases during a transmission season; 2 peak week (i.e., week in which the maximum weekly number of cases occurred; and 3 total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date.Our approach used ensemble models created by combining three disparate types of component models: 1 two-dimensional Method of Analogues models incorporating both dengue and climate data; 2 additive seasonal Holt-Winters models with and without wavelet smoothing; and 3 simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations.Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week.The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

Reacting to different types of concept drift: the Accuracy Updated Ensemble algorithm.

Science.gov (United States)

Brzezinski, Dariusz; Stefanowski, Jerzy

2014-01-01

Data stream mining has been receiving increased attention due to its presence in a wide range of applications, such as sensor networks, banking, and telecommunication. One of the most important challenges in learning from data streams is reacting to concept drift, i.e., unforeseen changes of the stream's underlying data distribution. Several classification algorithms that cope with concept drift have been put forward, however, most of them specialize in one type of change. In this paper, we propose a new data stream classifier, called the Accuracy Updated Ensemble (AUE2), which aims at reacting equally well to different types of drift. AUE2 combines accuracy-based weighting mechanisms known from block-based ensembles with the incremental nature of Hoeffding Trees. The proposed algorithm is experimentally compared with 11 state-of-the-art stream methods, including single classifiers, block-based and online ensembles, and hybrid approaches in different drift scenarios. Out of all the compared algorithms, AUE2 provided best average classification accuracy while proving to be less memory consuming than other ensemble approaches. Experimental results show that AUE2 can be considered suitable for scenarios, involving many types of drift as well as static environments.

A generalized polynomial chaos based ensemble Kalman filter with high accuracy

International Nuclear Information System (INIS)

Li Jia; Xiu Dongbin

2009-01-01

As one of the most adopted sequential data assimilation methods in many areas, especially those involving complex nonlinear dynamics, the ensemble Kalman filter (EnKF) has been under extensive investigation regarding its properties and efficiency. Compared to other variants of the Kalman filter (KF), EnKF is straightforward to implement, as it employs random ensembles to represent solution states. This, however, introduces sampling errors that affect the accuracy of EnKF in a negative manner. Though sampling errors can be easily reduced by using a large number of samples, in practice this is undesirable as each ensemble member is a solution of the system of state equations and can be time consuming to compute for large-scale problems. In this paper we present an efficient EnKF implementation via generalized polynomial chaos (gPC) expansion. The key ingredients of the proposed approach involve (1) solving the system of stochastic state equations via the gPC methodology to gain efficiency; and (2) sampling the gPC approximation of the stochastic solution with an arbitrarily large number of samples, at virtually no additional computational cost, to drastically reduce the sampling errors. The resulting algorithm thus achieves a high accuracy at reduced computational cost, compared to the classical implementations of EnKF. Numerical examples are provided to verify the convergence property and accuracy improvement of the new algorithm. We also prove that for linear systems with Gaussian noise, the first-order gPC Kalman filter method is equivalent to the exact Kalman filter.

Aqueous Solutions of the Ionic Liquid 1-butyl-3-methylimidazolium Chloride Denature Proteins

International Nuclear Information System (INIS)

Baker, Gary A.; Heller, William T.

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

Urea and Guanidinium Induced Denaturation of a Trp-Cage Miniprotein

Czech Academy of Sciences Publication Activity Database

Heyda, Jan; Kožíšek, Milan; Bednárová, Lucie; Thompson, G.; Konvalinka, Jan; Vondrášek, Jiří; Jungwirth, Pavel

2011-01-01

Roč. 115, č. 28 (2011), s. 8910-8924 ISSN 1520-6106 R&D Projects: GA MŠk LC512; GA ČR GA203/08/0114 Institutional research plan: CEZ:AV0Z40550506 Keywords : trp-cage denaturation * urea * guanidinium * molecular dynamics Subject RIV: CC - Organic Chemistry Impact factor: 3.696, year: 2011

Using simulation to interpret experimental data in terms of protein conformational ensembles.

Science.gov (United States)

Allison, Jane R

2017-04-01

In their biological environment, proteins are dynamic molecules, necessitating an ensemble structural description. Molecular dynamics simulations and solution-state experiments provide complimentary information in the form of atomically detailed coordinates and averaged or distributions of structural properties or related quantities. Recently, increases in the temporal and spatial scale of conformational sampling and comparison of the more diverse conformational ensembles thus generated have revealed the importance of sampling rare events. Excitingly, new methods based on maximum entropy and Bayesian inference are promising to provide a statistically sound mechanism for combining experimental data with molecular dynamics simulations. Copyright © 2016 Elsevier Ltd. All rights reserved.

A calorimetric study of the interactions in the aqueous solutions of lysozyme in the presence of denaturing cosolvents

Energy Technology Data Exchange (ETDEWEB)

Castronuovo, Giuseppina, E-mail: giuseppina.castronuovo@unina.it [Department of Chemistry, University Federico II of Naples, Complesso Universitario Monte S. Angelo, via Cintia, 80126 Naples (Italy); Niccoli, Marcella [Department of Chemistry, University Federico II of Naples, Complesso Universitario Monte S. Angelo, via Cintia, 80126 Naples (Italy)

2012-09-10

Highlights: Black-Right-Pointing-Pointer A thermodynamic method is reported to monitor the chemical denaturation of lysozyme. Black-Right-Pointing-Pointer The enthalpic interaction coefficients are very useful parameters to gain information about the mechanism through which two hydrated molecules interact in solution. Black-Right-Pointing-Pointer Hypotheses are proposed about the mechanism underlying the denaturation of lysozyme induced by high concentrations of urea or ethanol. - Abstract: A thermodynamic method is reported to monitor the chemical denaturation of lysozyme. Heats of dilution of the protein in concentrated aqueous solutions of urea or ethanol have been determined at 298.15 K by flow microcalorimetry. The pairwise enthalpic interaction coefficients of the protein in the different solvent media are derived. These parameters allow to gain information about the influence of the cosolvents on the interactions acting between two interacting hydrated molecules of lysozyme, hence on the denaturation process. At increasing urea concentration, up to about 6 mol kg{sup -1}, the values of the interaction coefficients are large and negative and remain almost unaltered. The invariance of the coefficients underlines that, even in highly concentrated urea, the hydration shell of the protein is such to maintain essentially unaltered the native conformation. At higher urea concentrations, a sudden change in the sign of the coefficients monitors the variation in the interactions between two hydrated denatured protein molecules. The same trend is found when ethanol is the cosolvent. At increasing concentration of the cosolvent, coefficients are, at first, almost invariant. After that, denaturation occurs, detected as a jump toward much more negative values. The results obtained are rationalized on the basis of those previously found for small model molecules in concentrated solutions of urea or ethanol. The thermodynamic framework allows useful comments to be made on

A calorimetric study of the interactions in the aqueous solutions of lysozyme in the presence of denaturing cosolvents

International Nuclear Information System (INIS)

Castronuovo, Giuseppina; Niccoli, Marcella

2012-01-01

Highlights: ► A thermodynamic method is reported to monitor the chemical denaturation of lysozyme. ► The enthalpic interaction coefficients are very useful parameters to gain information about the mechanism through which two hydrated molecules interact in solution. ► Hypotheses are proposed about the mechanism underlying the denaturation of lysozyme induced by high concentrations of urea or ethanol. - Abstract: A thermodynamic method is reported to monitor the chemical denaturation of lysozyme. Heats of dilution of the protein in concentrated aqueous solutions of urea or ethanol have been determined at 298.15 K by flow microcalorimetry. The pairwise enthalpic interaction coefficients of the protein in the different solvent media are derived. These parameters allow to gain information about the influence of the cosolvents on the interactions acting between two interacting hydrated molecules of lysozyme, hence on the denaturation process. At increasing urea concentration, up to about 6 mol kg −1 , the values of the interaction coefficients are large and negative and remain almost unaltered. The invariance of the coefficients underlines that, even in highly concentrated urea, the hydration shell of the protein is such to maintain essentially unaltered the native conformation. At higher urea concentrations, a sudden change in the sign of the coefficients monitors the variation in the interactions between two hydrated denatured protein molecules. The same trend is found when ethanol is the cosolvent. At increasing concentration of the cosolvent, coefficients are, at first, almost invariant. After that, denaturation occurs, detected as a jump toward much more negative values. The results obtained are rationalized on the basis of those previously found for small model molecules in concentrated solutions of urea or ethanol. The thermodynamic framework allows useful comments to be made on the possible mode of action of the two cosolvents on the stability of proteins

Contact planarization of ensemble nanowires

Science.gov (United States)

Chia, A. C. E.; LaPierre, R. R.

2011-06-01

The viability of four organic polymers (S1808, SC200, SU8 and Cyclotene) as filling materials to achieve planarization of ensemble nanowire arrays is reported. Analysis of the porosity, surface roughness and thermal stability of each filling material was performed. Sonication was used as an effective method to remove the tops of the nanowires (NWs) to achieve complete planarization. Ensemble nanowire devices were fully fabricated and I-V measurements confirmed that Cyclotene effectively planarizes the NWs while still serving the role as an insulating layer between the top and bottom contacts. These processes and analysis can be easily implemented into future characterization and fabrication of ensemble NWs for optoelectronic device applications.

Ensemble forecasting of species distributions.

Science.gov (United States)

Araújo, Miguel B; New, Mark

2007-01-01

Concern over implications of climate change for biodiversity has led to the use of bioclimatic models to forecast the range shifts of species under future climate-change scenarios. Recent studies have demonstrated that projections by alternative models can be so variable as to compromise their usefulness for guiding policy decisions. Here, we advocate the use of multiple models within an ensemble forecasting framework and describe alternative approaches to the analysis of bioclimatic ensembles, including bounding box, consensus and probabilistic techniques. We argue that, although improved accuracy can be delivered through the traditional tasks of trying to build better models with improved data, more robust forecasts can also be achieved if ensemble forecasts are produced and analysed appropriately.

Acetic acid denaturing pulsed field capillary electrophoresis for RNA separation.

Science.gov (United States)

Li, Zhenqing; Dou, Xiaoming; Ni, Yi; Sumitomo, Keiko; Yamaguchi, Yoshinori

2010-10-01

Based on our previous work of in-capillary denaturing polymer electrophoresis, we present a study of RNA molecular separation up to 6.0 kilo nucleotide by pulsed field CE. This is the first systematic investigation of electrophoresis of a larger molecular mass RNA in linear hydroxyethylcellulose (HEC) under pulsed field conditions. The parameters that may influence the separation performance, e.g. gel polymer concentration, modulation depth and pulse frequency, are analyzed in terms of resolution and mobility. For denaturing and separating RNA in the capillary simultaneously, 2 M acetic acid was added into the HEC polymer to serve as separation buffer. Result shows that (i) in pulsed field conditions, RNA separation can be achieved in a wide range of concentration of HEC polymer, and RNA fragments between 0.3 and 0.6 kilo nucleotide are sensitive to the polymer concentration; (ii) under certain pulsed field conditions, RNA fragments move linearly as the modulation depth increases; (iii) 12.5 Hz is the resonance frequency for RNA reorientation time and applied frequency.

Efficient Ensemble State-Parameters Estimation Techniques in Ocean Ecosystem Models: Application to the North Atlantic

Science.gov (United States)

El Gharamti, M.; Bethke, I.; Tjiputra, J.; Bertino, L.

2016-02-01

Given the recent strong international focus on developing new data assimilation systems for biological models, we present in this comparative study the application of newly developed state-parameters estimation tools to an ocean ecosystem model. It is quite known that the available physical models are still too simple compared to the complexity of the ocean biology. Furthermore, various biological parameters remain poorly unknown and hence wrong specifications of such parameters can lead to large model errors. Standard joint state-parameters augmentation technique using the ensemble Kalman filter (Stochastic EnKF) has been extensively tested in many geophysical applications. Some of these assimilation studies reported that jointly updating the state and the parameters might introduce significant inconsistency especially for strongly nonlinear models. This is usually the case for ecosystem models particularly during the period of the spring bloom. A better handling of the estimation problem is often carried out by separating the update of the state and the parameters using the so-called Dual EnKF. The dual filter is computationally more expensive than the Joint EnKF but is expected to perform more accurately. Using a similar separation strategy, we propose a new EnKF estimation algorithm in which we apply a one-step-ahead smoothing to the state. 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. Unlike the classical filtering path, the new scheme starts with an update step and later a model propagation step is performed. We test the performance of the new smoothing-based schemes against the standard EnKF in a one-dimensional configuration of the Norwegian Earth System Model (NorESM) in the North Atlantic. We use nutrients profile (up to 2000 m deep) data and surface partial CO2 measurements from Mike weather station (66o N, 2o E) to estimate

Strongly nonexponential time-resolved fluorescence of quantum-dot ensembles in three-dimensional photonic crystals

DEFF Research Database (Denmark)

Nikolaev, Ivan S.; Lodahl, Peter; van Driel, A. Floris

2007-01-01

We observe experimentally that ensembles of quantum dots in three-dimensional 3D photonic crystals reveal strongly nonexponential time-resolved emission. These complex emission decay curves are analyzed with a continuous distribution of decay rates. The log-normal distribution describes the decays...... parameter. This interpretation qualitatively agrees with the calculations of the 3D projected local density of states. We therefore conclude that fluorescence decay of ensembles of quantum dots is highly nonexponential to an extent that is controlled by photonic crystals....

Conductor gestures influence evaluations of ensemble performance.

Science.gov (United States)

Morrison, Steven J; Price, Harry E; Smedley, Eric M; Meals, Cory D

2014-01-01

Previous research has found that listener evaluations of ensemble performances vary depending on the expressivity of the conductor's gestures, even when performances are otherwise identical. It was the purpose of the present study to test whether this effect of visual information was evident in the evaluation of specific aspects of ensemble performance: articulation and dynamics. We constructed a set of 32 music performances that combined auditory and visual information and were designed to feature a high degree of contrast along one of two target characteristics: articulation and dynamics. We paired each of four music excerpts recorded by a chamber ensemble in both a high- and low-contrast condition with video of four conductors demonstrating high- and low-contrast gesture specifically appropriate to either articulation or dynamics. Using one of two equivalent test forms, college music majors and non-majors (N = 285) viewed sixteen 30 s performances and evaluated the quality of the ensemble's articulation, dynamics, technique, and tempo along with overall expressivity. Results showed significantly higher evaluations for performances featuring high rather than low conducting expressivity regardless of the ensemble's performance quality. Evaluations for both articulation and dynamics were strongly and positively correlated with evaluations of overall ensemble expressivity.

Statistical ensembles in quantum mechanics

International Nuclear Information System (INIS)

Blokhintsev, D.

1976-01-01

The interpretation of quantum mechanics presented in this paper is based on the concept of quantum ensembles. This concept differs essentially from the canonical one by that the interference of the observer into the state of a microscopic system is of no greater importance than in any other field of physics. Owing to this fact, the laws established by quantum mechanics are not of less objective character than the laws governing classical statistical mechanics. The paradoxical nature of some statements of quantum mechanics which result from the interpretation of the wave functions as the observer's notebook greatly stimulated the development of the idea presented. (Auth.)

The GMAO Hybrid Ensemble-Variational Atmospheric Data Assimilation System: Version 2.0

Science.gov (United States)

Todling, Ricardo; El Akkraoui, Amal

2018-01-01

This document describes the implementation and usage of the Goddard Earth Observing System (GEOS) Hybrid Ensemble-Variational Atmospheric Data Assimilation System (Hybrid EVADAS). Its aim is to provide comprehensive guidance to users of GEOS ADAS interested in experimenting with its hybrid functionalities. The document is also aimed at providing a short summary of the state-of-science in this release of the hybrid system. As explained here, the ensemble data assimilation system (EnADAS) mechanism added to GEOS ADAS to enable hybrid data assimilation applications has been introduced to the pre-existing machinery of GEOS in the most non-intrusive possible way. Only very minor changes have been made to the original scripts controlling GEOS ADAS with the objective of facilitating its usage by both researchers and the GMAO's near-real-time Forward Processing applications. In a hybrid scenario two data assimilation systems run concurrently in a two-way feedback mode such that: the ensemble provides background ensemble perturbations required by the ADAS deterministic (typically high resolution) hybrid analysis; and the deterministic ADAS provides analysis information for recentering of the EnADAS analyses and information necessary to ensure that observation bias correction procedures are consistent between both the deterministic ADAS and the EnADAS. The nonintrusive approach to introducing hybrid capability to GEOS ADAS means, in particular, that previously existing features continue to be available. Thus, not only is this upgraded version of GEOS ADAS capable of supporting new applications such as Hybrid 3D-Var, 3D-EnVar, 4D-EnVar and Hybrid 4D-EnVar, it remains possible to use GEOS ADAS in its traditional 3D-Var mode which has been used in both MERRA and MERRA-2. Furthermore, as described in this document, GEOS ADAS also supports a configuration for exercising a purely ensemble-based assimilation strategy which can be fully decoupled from its variational component. We

Spin squeezing of atomic ensembles via nuclear-electronic spin entanglement

DEFF Research Database (Denmark)

Fernholz, Thomas; Krauter, Hanna; Jensen, Kasper

2008-01-01

quantum limit for quantum memory experiments and applications in quantum metrology and is thus a complementary alternative to spin squeezing obtained via inter-atom entanglement. Squeezing of the collective spin is verified by quantum state tomography.......We demonstrate spin squeezing in a room temperature ensemble of 1012 Cesium atoms using their internal structure, where the necessary entanglement is created between nuclear and electronic spins of each individual atom. This state provides improvement in measurement sensitivity beyond the standard...

Multimodel ensemble simulations of present-day and near-future tropospheric ozone

NARCIS (Netherlands)

Stevenson, D.S.; Dentener, F.J.; Schultz, M.G.; Ellingsen, K.; Noije, van T.P.C.; Wild, O.; Zeng, G.; Amann, M.; Atherton, C.S.; Bell, N.; Bergmann, D.J.; Bey, I.; Butler, T.; Cofala, J.; Collins, W.J.; Derwent, R.G.; Doherty, R.M.; Drevet, J.; Eskes, H.J.; Fiore, A.M.; Gauss, M.; Hauglustaine, D.A.; Horowitz, L.W.; Isaksen, I.S.A.; Krol, M.C.; Lamarque, J.F.; Lawrence, M.G.; Montanaro, V.; Muller, J.F.; Pitari, G.; Prather, M.J.; Pyle, J.A.; Rast, S.; Rodriguez, J.M.; Sanderson, M.G.; Savage, N.H.; Shindell, D.T.; Strahan, S.E.; Sudo, K.; Szopa, S.

2006-01-01

Global tropospheric ozone distributions, budgets, and radiative forcings from an ensemble of 26 state-of-the-art atmospheric chemistry models have been intercompared and synthesized as part of a wider study into both the air quality and climate roles of ozone. Results from three 2030 emissions

Modality-Driven Classification and Visualization of Ensemble Variance

Energy Technology Data Exchange (ETDEWEB)

Bensema, Kevin; Gosink, Luke; Obermaier, Harald; Joy, Kenneth I.

2016-10-01

Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no information about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.

Evidence of non-coincidence of normalized sigmoidal curves of two different structural properties for two-state protein folding/unfolding

International Nuclear Information System (INIS)

Rahaman, Hamidur; Khan, Md. Khurshid Alam; Hassan, Md. Imtaiyaz; Islam, Asimul; Moosavi-Movahedi, Ali Akbar; Ahmad, Faizan

2013-01-01

Highlights: ► Non-coincidence of normalized sigmoidal curves of two different structural properties is consistence with the two-state protein folding/unfolding. ► DSC measurements of denaturation show a two-state behavior of g-cyt-c at pH 6.0. ► Urea-induced denaturation of g-cyt-c is a variable two- state process at pH 6.0. ► GdmCl-induced denaturation of g-cyt-c is a fixed two- state process at pH 6.0. -- Abstract: In practice, the observation of non-coincidence of normalized sigmoidal transition curves measured by two different structural properties constitutes a proof of existence of thermodynamically stable intermediate(s) on the folding ↔ unfolding pathway of a protein. Here we give first experimental evidence that this non-coincidence is also observed for a two-state protein denaturation. Proof of this evidence comes from our studies of denaturation of goat cytochrome-c (g-cyt-c) at pH 6.0. These studies involve differential scanning calorimetry (DSC) measurements in the absence of urea and measurements of urea-induced denaturation curves monitored by observing changes in absorbance at 405, 530, and 695 nm and circular dichroism (CD) at 222, 405, and 416 nm. DSC measurements showed that denaturation of the protein is a two-state process, for calorimetric and van’t Hoff enthalpy changes are, within experimental errors, identical. Normalization of urea-induced denaturation curves monitored by optical properties leads to noncoincident sigmoidal curves. Heat-induced transition of g-cyt-c in the presence of different urea concentrations was monitored by CD at 222 nm and absorption at 405 nm. It was observed that these two different structural probes gave not only identical values of T m (transition temperature), ΔH m (change in enthalpy at T m ) and ΔC p (constant-pressure heat capacity change), but these thermodynamic parameters in the absence of urea are also in agreement with those obtained from DSC measurements

Establishment of a New National Reference Ensemble of Water Triple Point Cells

Science.gov (United States)

Senn, Remo

2017-10-01

The results of the Bilateral Comparison EURAMET.T-K3.5 (w/VSL, The Netherlands) with the goal to link Switzerland's ITS-90 realization (Ar to Al) to the latest key comparisons gave strong indications for a discrepancy in the realization of the triple point of water. Due to the age of the cells of about twenty years, it was decided to replace the complete reference ensemble with new "state-of-the-art" cells. Three new water triple point cells from three different suppliers were purchased, as well as a new maintenance bath for an additional improvement of the realization. In several loops measurements were taken, each cell of both ensembles intercompared, and the deviations and characteristics determined. The measurements show a significant lower average value of the old ensemble of 0.59 ± 0.25 mK (k=2) in comparison with the new one. Likewise, the behavior of the old cells is very unstable with a drift downward during the realization of the triple point. Based on these results the impact of the new ensemble on the ITS-90 realization from Ar to Al was calculated and set in the context to performed calibrations and their related uncertainties in the past. This paper presents the instrumentation, cells, measurement procedure, results, uncertainties and impact of the new national reference ensemble of water triple point cells on the current ITS-90 realization in Switzerland.

Finite temperature grand canonical ensemble study of the minimum electrophilicity principle.

Science.gov (United States)

Miranda-Quintana, Ramón Alain; Chattaraj, Pratim K; Ayers, Paul W

2017-09-28

We analyze the minimum electrophilicity principle of conceptual density functional theory using the framework of the finite temperature grand canonical ensemble. We provide support for this principle, both for the cases of systems evolving from a non-equilibrium to an equilibrium state and for the change from one equilibrium state to another. In doing so, we clearly delineate the cases where this principle can, or cannot, be used.

Radioimmunoassay and heat denaturation enzyme assay for the detection of Tay-Sachs heterozygotes during pregnancy

International Nuclear Information System (INIS)

Nguyen, C.; Gold, R.J.M.; Mahuran, D.; Lowden, J.A.

1981-01-01

Tay-Sachs disease results from a loss of activity of hexosaminidase A (HEX A) in body tissues and fluids. Heterozygotes for the disease are usually identified by their relatively low ratio of heat-labile HEX A to total hexosaminidase. During pregnancy an intermediate isoenzyme (HEX I) increases in activity in serum and obscures the heterozygote status. HEX I does not increase in leucocytes, tears and other body tissues but because of technical difficulties in these assays the authors examined the feasibility of using a radioimmunoassay for HEX A. By univariate analysis, the heat denaturation assay gave a lower cost of misclassification for non-pregnant normals while RIA did so for pregnant normals. A combination of both tests led to reduced cost of misclassification compared to either alone. Bayesian analysis of bivariate gaussian density functions for heat denaturation and for radioimmunoassays of HEX isoenzymes was employed to calculate misclassification frequencies. Among the parameters examined, HEX A measured by RIA and % HEX A by heat-denaturation assay were the two having the best discriminatory power. (Auth.)

Kinetics and dynamics of near-resonant vibrational energy transfer in gas ensembles of atmospheric interest

Science.gov (United States)

McCaffery, Anthony J.

2018-03-01

This study of near-resonant, vibration-vibration (V-V) gas-phase energy transfer in diatomic molecules uses the theoretical/computational method, of Marsh & McCaffery (Marsh & McCaffery 2002 J. Chem. Phys. 117, 503 (doi:10.1063/1.1489998)) The method uses the angular momentum (AM) theoretical formalism to compute quantum-state populations within the component molecules of large, non-equilibrium, gas mixtures as the component species proceed to equilibration. Computed quantum-state populations are displayed in a number of formats that reveal the detailed mechanism of the near-resonant V-V process. Further, the evolution of quantum-state populations, for each species present, may be followed as the number of collision cycles increases, displaying the kinetics of evolution for each quantum state of the ensemble's molecules. These features are illustrated for ensembles containing vibrationally excited N2 in H2, O2 and N2 initially in their ground states. This article is part of the theme issue `Modern theoretical chemistry'.

Bioactive focus in conformational ensembles: a pluralistic approach

Science.gov (United States)

Habgood, Matthew

2017-12-01

Computational generation of conformational ensembles is key to contemporary drug design. Selecting the members of the ensemble that will approximate the conformation most likely to bind to a desired target (the bioactive conformation) is difficult, given that the potential energy usually used to generate and rank the ensemble is a notoriously poor discriminator between bioactive and non-bioactive conformations. In this study an approach to generating a focused ensemble is proposed in which each conformation is assigned multiple rankings based not just on potential energy but also on solvation energy, hydrophobic or hydrophilic interaction energy, radius of gyration, and on a statistical potential derived from Cambridge Structural Database data. The best ranked structures derived from each system are then assembled into a new ensemble that is shown to be better focused on bioactive conformations. This pluralistic approach is tested on ensembles generated by the Molecular Operating Environment's Low Mode Molecular Dynamics module, and by the Cambridge Crystallographic Data Centre's conformation generator software.

T1ρ is superior to T2 mapping for the evaluation of articular cartilage denaturalization with osteoarthritis: radiological-pathological correlation after total knee arthroplasty.

Science.gov (United States)

Takayama, Yukihisa; Hatakenaka, Masamitsu; Tsushima, Hidetoshi; Okazaki, Ken; Yoshiura, Takashi; Yonezawa, Masato; Nishikawa, Kei; Iwamoto, Yukihide; Honda, Hiroshi

2013-04-01

We compared the diagnostic performance of T1ρ and T2 mappings in the evaluation of denatured articular cartilage with osteoarthritis of the knee. 2D-Sagittal T1ρ and T2 mappings of the knee were obtained from 16 patients before total knee arthroplasty. After surgery, specimens of the femur and tibia were regionally segmented according to a 5-point scale of the severity of denaturalization. The T1ρ and T2 values in the full thickness of the articular cartilage in each region were measured by two observers. The two mappings were compared for their ability to differentiate between normal and denatured articular cartilage and also for their usefulness in grading the severity of the denaturalization using the area under receiver operating characteristic curves (Az). A pT2 mapping for the differentiation between normal and denatured articular cartilage (pT2 mapping could not. However, there were no significant differences between the two mappings in the discrimination of mild versus moderate denaturalization or of moderate versus severe denaturalization. The two observers showed good agreement in the results (intraclass correlation coefficient=0.81 for T1ρ and 0.92 for T2). T1ρ mapping is superior to T2 mapping for the evaluation of denatured articular cartilage with osteoarthritis of the knee. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Harmony Search Based Parameter Ensemble Adaptation for Differential Evolution

Directory of Open Access Journals (Sweden)

Rammohan Mallipeddi

2013-01-01

Full Text Available In differential evolution (DE algorithm, depending on the characteristics of the problem at hand and the available computational resources, different strategies combined with a different set of parameters may be effective. In addition, a single, well-tuned combination of strategies and parameters may not guarantee optimal performance because different strategies combined with different parameter settings can be appropriate during different stages of the evolution. Therefore, various adaptive/self-adaptive techniques have been proposed to adapt the DE strategies and parameters during the course of evolution. In this paper, we propose a new parameter adaptation technique for DE based on ensemble approach and harmony search algorithm (HS. In the proposed method, an ensemble of parameters is randomly sampled which form the initial harmony memory. The parameter ensemble evolves during the course of the optimization process by HS algorithm. Each parameter combination in the harmony memory is evaluated by testing them on the DE population. The performance of the proposed adaptation method is evaluated using two recently proposed strategies (DE/current-to-pbest/bin and DE/current-to-gr_best/bin as basic DE frameworks. Numerical results demonstrate the effectiveness of the proposed adaptation technique compared to the state-of-the-art DE based algorithms on a set of challenging test problems (CEC 2005.

Assessment of Surface Air Temperature over China Using Multi-criterion Model Ensemble Framework

Science.gov (United States)

Li, J.; Zhu, Q.; Su, L.; He, X.; Zhang, X.

2017-12-01

The General Circulation Models (GCMs) are designed to simulate the present climate and project future trends. It has been noticed that the performances of GCMs are not always in agreement with each other over different regions. Model ensemble techniques have been developed to post-process the GCMs' outputs and improve their prediction reliabilities. To evaluate the performances of GCMs, root-mean-square error, correlation coefficient, and uncertainty are commonly used statistical measures. However, the simultaneous achievements of these satisfactory statistics cannot be guaranteed when using many model ensemble techniques. Meanwhile, uncertainties and future scenarios are critical for Water-Energy management and operation. In this study, a new multi-model ensemble framework was proposed. It uses a state-of-art evolutionary multi-objective optimization algorithm, termed Multi-Objective Complex Evolution Global Optimization with Principle Component Analysis and Crowding Distance (MOSPD), to derive optimal GCM ensembles and demonstrate the trade-offs among various solutions. Such trade-off information was further analyzed with a robust Pareto front with respect to different statistical measures. A case study was conducted to optimize the surface air temperature (SAT) ensemble solutions over seven geographical regions of China for the historical period (1900-2005) and future projection (2006-2100). The results showed that the ensemble solutions derived with MOSPD algorithm are superior over the simple model average and any single model output during the historical simulation period. For the future prediction, the proposed ensemble framework identified that the largest SAT change would occur in the South Central China under RCP 2.6 scenario, North Eastern China under RCP 4.5 scenario, and North Western China under RCP 8.5 scenario, while the smallest SAT change would occur in the Inner Mongolia under RCP 2.6 scenario, South Central China under RCP 4.5 scenario, and

Ensemble Weight Enumerators for Protograph LDPC Codes

Science.gov (United States)

Divsalar, Dariush

2006-01-01

Recently LDPC codes with projected graph, or protograph structures have been proposed. In this paper, finite length ensemble weight enumerators for LDPC codes with protograph structures are obtained. Asymptotic results are derived as the block size goes to infinity. In particular we are interested in obtaining ensemble average weight enumerators for protograph LDPC codes which have minimum distance that grows linearly with block size. As with irregular ensembles, linear minimum distance property is sensitive to the proportion of degree-2 variable nodes. In this paper the derived results on ensemble weight enumerators show that linear minimum distance condition on degree distribution of unstructured irregular LDPC codes is a sufficient but not a necessary condition for protograph LDPC codes.

Interchange reaction of disulfides and denaturation of oxytocin by copper(II)/ascorbic acid/O2 system.

Science.gov (United States)

Inoue, H; Hirobe, M

1987-05-29

The interchange reaction of disulfides was caused by the copper(II)/ascorbic acid/O2 system. The incubation of two symmetric disulfides, L-cystinyl-bis-L-phenylalanine (PP) and L-cystinyl-bis-L-tyrosine (TT), with L-ascorbic acid and CuSO4 in potassium phosphate buffer (pH 7.2, 50 mM) resulted in the formation of an asymmetric disulfide, L-cystinyl-L-phenylalanine-L-tyrosine (PT), and the final ratio of PP:PT:TT was 1:2:1. As the reaction was inhibited by catalase and DMSO only at the initial time, hydroxyl radical generated by the copper(II)/ascorbic acid/O2 system seemed to be responsible for the initiation of the reaction. Oxytocin and insulin were denatured by this system, and catalase and DMSO similarly inhibited these denaturations. As the composition of amino acids was unchanged after the reaction, hydroxyl radical was thought to cause the cleavage and/or interchange reaction of disulfides to denature the peptides.

Ensemble atmospheric dispersion calculations for decision support systems

International Nuclear Information System (INIS)

Borysiewicz, M.; Potempski, S.; Galkowski, A.; Zelazny, R.

2003-01-01

This document describes two approaches to long-range atmospheric dispersion of pollutants based on the ensemble concept. In the first part of the report some experiences related to the exercises undertaken under the ENSEMBLE project of the European Union are presented. The second part is devoted to the implementation of mesoscale numerical prediction models RAMS and atmospheric dispersion model HYPACT on Beowulf cluster and theirs usage for ensemble forecasting and long range atmospheric ensemble dispersion calculations based on available meteorological data from NCEO, NOAA (USA). (author)

Studying pressure denaturation of a protein by molecular dynamics simulations.

Science.gov (United States)

Sarupria, Sapna; Ghosh, Tuhin; García, Angel E; Garde, Shekhar

2010-05-15

Many globular proteins unfold when subjected to several kilobars of hydrostatic pressure. This "unfolding-up-on-squeezing" is counter-intuitive in that one expects mechanical compression of proteins with increasing pressure. Molecular simulations have the potential to provide fundamental understanding of pressure effects on proteins. However, the slow kinetics of unfolding, especially at high pressures, eliminates the possibility of its direct observation by molecular dynamics (MD) simulations. Motivated by experimental results-that pressure denatured states are water-swollen, and theoretical results-that water transfer into hydrophobic contacts becomes favorable with increasing pressure, we employ a water insertion method to generate unfolded states of the protein Staphylococcal Nuclease (Snase). Structural characteristics of these unfolded states-their water-swollen nature, retention of secondary structure, and overall compactness-mimic those observed in experiments. Using conformations of folded and unfolded states, we calculate their partial molar volumes in MD simulations and estimate the pressure-dependent free energy of unfolding. The volume of unfolding of Snase is negative (approximately -60 mL/mol at 1 bar) and is relatively insensitive to pressure, leading to its unfolding in the pressure range of 1500-2000 bars. Interestingly, once the protein is sufficiently water swollen, the partial molar volume of the protein appears to be insensitive to further conformational expansion or unfolding. Specifically, water-swollen structures with relatively low radii of gyration have partial molar volume that are similar to that of significantly more unfolded states. We find that the compressibility change on unfolding is negligible, consistent with experiments. We also analyze hydration shell fluctuations to comment on the hydration contributions to protein compressibility. Our study demonstrates the utility of molecular simulations in estimating volumetric properties

Representation of photon limited data in emission tomography using origin ensembles

Energy Technology Data Exchange (ETDEWEB)

Sitek, A [Radiology Department, Brigham and Women' s Hospital and Harvard Medical School, 75 Francis Street, Boston, MA 02115 (United States)], E-mail: asitek@bwh.harvard.edu

2008-06-21

Representation and reconstruction of data obtained by emission tomography scanners are challenging due to high noise levels in the data. Typically, images obtained using tomographic measurements are represented using grids. In this work, we define images as sets of origins of events detected during tomographic measurements; we call these origin ensembles (OEs). A state in the ensemble is characterized by a vector of 3N parameters Y, where the parameters are the coordinates of origins of detected events in a three-dimensional space and N is the number of detected events. The 3N-dimensional probability density function (PDF) for that ensemble is derived, and we present an algorithm for OE image estimation from tomographic measurements. A displayable image (e.g. grid based image) is derived from the OE formulation by calculating ensemble expectations based on the PDF using the Markov chain Monte Carlo method. The approach was applied to computer-simulated 3D list-mode positron emission tomography data. The reconstruction errors for a 10 000 000 event acquisition for simulated ranged from 0.1 to 34.8%, depending on object size and sampling density. The method was also applied to experimental data and the results of the OE method were consistent with those obtained by a standard maximum-likelihood approach. The method is a new approach to representation and reconstruction of data obtained by photon-limited emission tomography measurements.

Representation of photon limited data in emission tomography using origin ensembles

Science.gov (United States)

Sitek, A.

2008-06-01

Representation and reconstruction of data obtained by emission tomography scanners are challenging due to high noise levels in the data. Typically, images obtained using tomographic measurements are represented using grids. In this work, we define images as sets of origins of events detected during tomographic measurements; we call these origin ensembles (OEs). A state in the ensemble is characterized by a vector of 3N parameters Y, where the parameters are the coordinates of origins of detected events in a three-dimensional space and N is the number of detected events. The 3N-dimensional probability density function (PDF) for that ensemble is derived, and we present an algorithm for OE image estimation from tomographic measurements. A displayable image (e.g. grid based image) is derived from the OE formulation by calculating ensemble expectations based on the PDF using the Markov chain Monte Carlo method. The approach was applied to computer-simulated 3D list-mode positron emission tomography data. The reconstruction errors for a 10 000 000 event acquisition for simulated ranged from 0.1 to 34.8%, depending on object size and sampling density. The method was also applied to experimental data and the results of the OE method were consistent with those obtained by a standard maximum-likelihood approach. The method is a new approach to representation and reconstruction of data obtained by photon-limited emission tomography measurements.

Representation of photon limited data in emission tomography using origin ensembles

International Nuclear Information System (INIS)

Sitek, A

2008-01-01

Representation and reconstruction of data obtained by emission tomography scanners are challenging due to high noise levels in the data. Typically, images obtained using tomographic measurements are represented using grids. In this work, we define images as sets of origins of events detected during tomographic measurements; we call these origin ensembles (OEs). A state in the ensemble is characterized by a vector of 3N parameters Y, where the parameters are the coordinates of origins of detected events in a three-dimensional space and N is the number of detected events. The 3N-dimensional probability density function (PDF) for that ensemble is derived, and we present an algorithm for OE image estimation from tomographic measurements. A displayable image (e.g. grid based image) is derived from the OE formulation by calculating ensemble expectations based on the PDF using the Markov chain Monte Carlo method. The approach was applied to computer-simulated 3D list-mode positron emission tomography data. The reconstruction errors for a 10 000 000 event acquisition for simulated ranged from 0.1 to 34.8%, depending on object size and sampling density. The method was also applied to experimental data and the results of the OE method were consistent with those obtained by a standard maximum-likelihood approach. The method is a new approach to representation and reconstruction of data obtained by photon-limited emission tomography measurements

Stochastic Approaches Within a High Resolution Rapid Refresh Ensemble

Science.gov (United States)

Jankov, I.

2017-12-01

It is well known that global and regional numerical weather prediction (NWP) ensemble systems are under-dispersive, producing unreliable and overconfident ensemble forecasts. Typical approaches to alleviate this problem include the use of multiple dynamic cores, multiple physics suite configurations, or a combination of the two. While these approaches may produce desirable results, they have practical and theoretical deficiencies and are more difficult and costly to maintain. An active area of research that promotes a more unified and sustainable system is the use of stochastic physics. Stochastic approaches include Stochastic Parameter Perturbations (SPP), Stochastic Kinetic Energy Backscatter (SKEB), and Stochastic Perturbation of Physics Tendencies (SPPT). The focus of this study is to assess model performance within a convection-permitting ensemble at 3-km grid spacing across the Contiguous United States (CONUS) using a variety of stochastic approaches. A single physics suite configuration based on the operational High-Resolution Rapid Refresh (HRRR) model was utilized and ensemble members produced by employing stochastic methods. Parameter perturbations (using SPP) for select fields were employed in the Rapid Update Cycle (RUC) land surface model (LSM) and Mellor-Yamada-Nakanishi-Niino (MYNN) Planetary Boundary Layer (PBL) schemes. Within MYNN, SPP was applied to sub-grid cloud fraction, mixing length, roughness length, mass fluxes and Prandtl number. In the RUC LSM, SPP was applied to hydraulic conductivity and tested perturbing soil moisture at initial time. First iterative testing was conducted to assess the initial performance of several configuration settings (e.g. variety of spatial and temporal de-correlation lengths). Upon selection of the most promising candidate configurations using SPP, a 10-day time period was run and more robust statistics were gathered. SKEB and SPPT were included in additional retrospective tests to assess the impact of using

Ensemble-Based Data Assimilation in Reservoir Characterization: A Review

Directory of Open Access Journals (Sweden)

Seungpil Jung

2018-02-01

Full Text Available This paper presents a review of ensemble-based data assimilation for strongly nonlinear problems on the characterization of heterogeneous reservoirs with different production histories. It concentrates on ensemble Kalman filter (EnKF and ensemble smoother (ES as representative frameworks, discusses their pros and cons, and investigates recent progress to overcome their drawbacks. The typical weaknesses of ensemble-based methods are non-Gaussian parameters, improper prior ensembles and finite population size. Three categorized approaches, to mitigate these limitations, are reviewed with recent accomplishments; improvement of Kalman gains, add-on of transformation functions, and independent evaluation of observed data. The data assimilation in heterogeneous reservoirs, applying the improved ensemble methods, is discussed on predicting unknown dynamic data in reservoir characterization.

Various multistage ensembles for prediction of heating energy consumption

Directory of Open Access Journals (Sweden)

Radisa Jovanovic

2015-04-01

Full Text Available Feedforward neural network models are created for prediction of daily heating energy consumption of a NTNU university campus Gloshaugen using actual measured data for training and testing. Improvement of prediction accuracy is proposed by using neural network ensemble. Previously trained feed-forward neural networks are first separated into clusters, using k-means algorithm, and then the best network of each cluster is chosen as member of an ensemble. Two conventional averaging methods for obtaining ensemble output are applied; simple and weighted. In order to achieve better prediction results, multistage ensemble is investigated. As second level, adaptive neuro-fuzzy inference system with various clustering and membership functions are used to aggregate the selected ensemble members. Feedforward neural network in second stage is also analyzed. It is shown that using ensemble of neural networks can predict heating energy consumption with better accuracy than the best trained single neural network, while the best results are achieved with multistage ensemble.

Quantifying polypeptide conformational space: sensitivity to conformation and ensemble definition.

Science.gov (United States)

Sullivan, David C; Lim, Carmay

2006-08-24

Quantifying the density of conformations over phase space (the conformational distribution) is needed to model important macromolecular processes such as protein folding. In this work, we quantify the conformational distribution for a simple polypeptide (N-mer polyalanine) using the cumulative distribution function (CDF), which gives the probability that two randomly selected conformations are separated by less than a "conformational" distance and whose inverse gives conformation counts as a function of conformational radius. An important finding is that the conformation counts obtained by the CDF inverse depend critically on the assignment of a conformation's distance span and the ensemble (e.g., unfolded state model): varying ensemble and conformation definition (1 --> 2 A) varies the CDF-based conformation counts for Ala(50) from 10(11) to 10(69). In particular, relatively short molecular dynamics (MD) relaxation of Ala(50)'s random-walk ensemble reduces the number of conformers from 10(55) to 10(14) (using a 1 A root-mean-square-deviation radius conformation definition) pointing to potential disconnections in comparing the results from simplified models of unfolded proteins with those from all-atom MD simulations. Explicit waters are found to roughen the landscape considerably. Under some common conformation definitions, the results herein provide (i) an upper limit to the number of accessible conformations that compose unfolded states of proteins, (ii) the optimal clustering radius/conformation radius for counting conformations for a given energy and solvent model, (iii) a means of comparing various studies, and (iv) an assessment of the applicability of random search in protein folding.

Current path in light emitting diodes based on nanowire ensembles

International Nuclear Information System (INIS)

Limbach, F; Hauswald, C; Lähnemann, J; Wölz, M; Brandt, O; Trampert, A; Hanke, M; Jahn, U; Calarco, R; Geelhaar, L; Riechert, H

2012-01-01

Light emitting diodes (LEDs) have been fabricated using ensembles of free-standing (In, Ga)N/GaN nanowires (NWs) grown on Si substrates in the self-induced growth mode by molecular beam epitaxy. Electron-beam-induced current analysis, cathodoluminescence as well as biased μ-photoluminescence spectroscopy, transmission electron microscopy, and electrical measurements indicate that the electroluminescence of such LEDs is governed by the differences in the individual current densities of the single-NW LEDs operated in parallel, i.e. by the inhomogeneity of the current path in the ensemble LED. In addition, the optoelectronic characterization leads to the conclusion that these NWs exhibit N-polarity and that the (In, Ga)N quantum well states in the NWs are subject to a non-vanishing quantum confined Stark effect. (paper)

Faithful remote state preparation using finite classical bits and a nonmaximally entangled state

International Nuclear Information System (INIS)

Ye Mingyong; Zhang Yongsheng; Guo Guangcan

2004-01-01

We present many ensembles of states that can be remotely prepared by using minimum classical bits from Alice to Bob and their previously shared entangled state and prove that we have found all the ensembles in two-dimensional case. Furthermore we show that any pure quantum state can be remotely and faithfully prepared by using finite classical bits from Alice to Bob and their previously shared nonmaximally entangled state though no faithful quantum teleportation protocols can be achieved by using a nonmaximally entangled state

Popular Music and the Instrumental Ensemble.

Science.gov (United States)

Boespflug, George

1999-01-01

Discusses popular music, the role of the musical performer as a creator, and the styles of jazz and popular music. Describes the pop ensemble at the college level, focusing on improvisation, rehearsals, recording, and performance. Argues that pop ensembles be used in junior and senior high school. (CMK)

Theoretical aspects of pressure and solute denaturation of proteins: A Kirkwood-buff-theory approach

Science.gov (United States)

Ben-Naim, Arieh

2012-12-01

A new approach to the problem of pressure-denaturation (PD) and solute-denaturation (SD) of proteins is presented. The problem is formulated in terms of Le Chatelier principle, and a solution is sought in terms of the Kirkwood-Buff theory of solutions. It is found that both problems have one factor in common; the excluded volumes of the folded and the unfolded forms with respect to the solvent molecules. It is shown that solvent-induced effects operating on hydrophilic groups along the protein are probably the main reason for PD. On the other hand, the SD depends on the preferential solvation of the folded and the unfolded forms with respect to solvent and co-solvent molecules.

Resistance to DNA denaturation in irradiated Chinese hamster V79 fibroblasts is linked to cell shape

International Nuclear Information System (INIS)

Olive, P.L.; Vanderbyl, S.; MacPhail, S.H.

1991-01-01

Exponentially growing Chinese hamster V79-171b lung fibroblasts seeded at high density on plastic (approximately 7 x 10(3) cells/cm2) flatten, elongate, and produce significant amounts of extracellular fibronectin. When lysed in weak alkali/high salt, the rate of DNA denaturation following exposure to ionizing radiation is exponential. Conversely, cells plated at low density (approximately 7 x 10(2) cells/cm2) on plastic are more rounded 24 h later, produce little extracellular fibronectin, and display unusual DNA denaturation kinetics after X-irradiation. DNA in these cells resists denaturation, as though constraints to DNA unwinding have developed. Cell doubling time and distribution of cells in the growth cycle are identical for both high and low density cultures as is cell survival in response to radiation damage. The connection between DNA conformation and cell shape was examined further in low density cultures grown in conditioned medium. Under these conditions, cells at low density were able to elongate, and DNA denaturation of low density cultures was identical to that of high density cultures. Conversely, cytochalasin D, which interferes with actin polymerization causing cells to round up and release fibronectin, allowed development of constraints in high density cultures. These results suggest that DNA conformation is sensitive to changes in cell shape which result when cells are grown in different environments. However, these changes in DNA conformation detected by the DNA unwinding assay do not appear to play a direct role in radiation-induced cell killing

Topological quantization of ensemble averages

International Nuclear Information System (INIS)

Prodan, Emil

2009-01-01

We define the current of a quantum observable and, under well-defined conditions, we connect its ensemble average to the index of a Fredholm operator. The present work builds on a formalism developed by Kellendonk and Schulz-Baldes (2004 J. Funct. Anal. 209 388) to study the quantization of edge currents for continuous magnetic Schroedinger operators. The generalization given here may be a useful tool to scientists looking for novel manifestations of the topological quantization. As a new application, we show that the differential conductance of atomic wires is given by the index of a certain operator. We also comment on how the formalism can be used to probe the existence of edge states

Genetic Algorithm Optimized Neural Networks Ensemble as ...

African Journals Online (AJOL)

Marquardt algorithm by varying conditions such as inputs, hidden neurons, initialization, training sets and random Gaussian noise injection to ... Several such ensembles formed the population which was evolved to generate the fittest ensemble.

Isoenergic modification of whey protein structure by denaturation and crosslinking using transglutaminase

DEFF Research Database (Denmark)

Stender, Emil G. P.; Koutina, Glykeria; Almdal, Kristoffer

2018-01-01

Transglutaminase (TG) catalyzes formation of covalent bonds between lysine and glutamine side chains and has applications in manipulation of food structure. Physical properties of a whey protein mixture (SPC) denatured either at elevated pH or by heat-treatment and followed by TG catalyzed...

A Role For Ca 2+ in the Thermal and Urea Denaturation of ...

African Journals Online (AJOL)

Giant African snail (Achatina achatina) becomes dormant (aestivate) under harsh environmental conditions like dry seasons. During this period the animal accumulates urea and is faced with thermal death. The stability towards thermal and urea denaturation of haemocyanin from aestivating and nonaestivating A. achatina ...

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...

Decoupling of size and shape fluctuations in heteropolymeric sequences reconciles discrepancies in SAXS vs. FRET measurements.

Science.gov (United States)

Fuertes, Gustavo; Banterle, Niccolò; Ruff, Kiersten M; Chowdhury, Aritra; Mercadante, Davide; Koehler, Christine; Kachala, Michael; Estrada Girona, Gemma; Milles, Sigrid; Mishra, Ankur; Onck, Patrick R; Gräter, Frauke; Esteban-Martín, Santiago; Pappu, Rohit V; Svergun, Dmitri I; Lemke, Edward A

2017-08-01

Unfolded states of proteins and native states of intrinsically disordered proteins (IDPs) populate heterogeneous conformational ensembles in solution. The average sizes of these heterogeneous systems, quantified by the radius of gyration ( R G ), can be measured by small-angle X-ray scattering (SAXS). Another parameter, the mean dye-to-dye distance ( R E ) for proteins with fluorescently labeled termini, can be estimated using single-molecule Förster resonance energy transfer (smFRET). A number of studies have reported inconsistencies in inferences drawn from the two sets of measurements for the dimensions of unfolded proteins and IDPs in the absence of chemical denaturants. These differences are typically attributed to the influence of fluorescent labels used in smFRET and to the impact of high concentrations and averaging features of SAXS. By measuring the dimensions of a collection of labeled and unlabeled polypeptides using smFRET and SAXS, we directly assessed the contributions of dyes to the experimental values R G and R E For chemically denatured proteins we obtain mutual consistency in our inferences based on R G and R E , whereas for IDPs under native conditions, we find substantial deviations. Using computations, we show that discrepant inferences are neither due to methodological shortcomings of specific measurements nor due to artifacts of dyes. Instead, our analysis suggests that chemical heterogeneity in heteropolymeric systems leads to a decoupling between R E and R G that is amplified in the absence of denaturants. Therefore, joint assessments of R G and R E combined with measurements of polymer shapes should provide a consistent and complete picture of the underlying ensembles.

Multimodel ensemble simulations of of present-day and near-future tropospheric ozone

NARCIS (Netherlands)

Stevenson, D.S.; Dentener, F.J.; van Noije, T.P.C.; Eskes, H.J.; Krol, M.C.

2006-01-01

Global tropospheric ozone distributions, budgets, and radiative forcings from an ensemble of 26 state-of-the-art atmospheric chemistry models have been intercompared and synthesized as part of a wider study into both the air quality and climate roles of ozone. Results from three 2030 emissions

Derivation of Mayer Series from Canonical Ensemble

International Nuclear Information System (INIS)

Wang Xian-Zhi

2016-01-01

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. (paper)

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.

Ensemble-marginalized Kalman filter for linear time-dependent PDEs with noisy boundary conditions: Application to heat transfer in building walls

KAUST Repository

Iglesias, Marco

2017-11-26

In this work, we present the ensemble-marginalized Kalman filter (EnMKF), a sequential algorithm analogous to our previously proposed approach [1,2], for estimating the state and parameters of linear parabolic partial differential equations in initial-boundary value problems when the boundary data are noisy. We apply EnMKF to infer the thermal properties of building walls and to estimate the corresponding heat flux from real and synthetic data. Compared with a modified Ensemble Kalman Filter (EnKF) that is not marginalized, EnMKF reduces the bias error, avoids the collapse of the ensemble without needing to add inflation, and converges to the mean field posterior using $50\\\\%$ or less of the ensemble size required by EnKF. According to our results, the marginalization technique in EnMKF is key to performance improvement with smaller ensembles at any fixed time.

A novel test method for measuring the thermal properties of clothing ensembles under dynamic conditions

International Nuclear Information System (INIS)

Wan, X; Fan, J

2008-01-01

The dynamic thermal properties of clothing ensembles are important to thermal transient comfort, but have so far not been properly quantified. In this paper, a novel test procedure and new index based on measurements on the sweating fabric manikin-Walter are proposed to quantify and measure the dynamic thermal properties of clothing ensembles. Experiments showed that the new index is correlated to the changing rate of the body temperature of the wearer, which is an important indicator of thermal transient comfort. Clothing ensembles having higher values of the index means the wearer will have a faster changing rate of body temperature and shorter duration before approaching a dangerous thermo-physiological state, when he changes from 'resting' to 'exercising' mode. Clothing should therefore be designed to reduce the value of the index

Uranium production in thorium/denatured uranium fueled PWRs

International Nuclear Information System (INIS)

Arthur, W.B.

1977-01-01

Uranium-232 buildup in a thorium/denatured uranium fueled pressurized water reactor, PWR(Th), was studied using a modified version of the spectrum-dependent zero dimensional depletion code, LEOPARD. The generic Combustion Engineering System 80 reactor design was selected as the reactor model for the calculations. Reactors fueled with either enriched natural uranium and self-generated recycled uranium or uranium from a thorium breeder and self-generated recycled uranium were considered. For enriched natural uranium, concentrations of 232 U varied from about 135 ppM ( 232 U/U weight basis) in the zeroth generation to about 260 ppM ( 232 U/U weight basis) at the end of the fifth generation. For the case in which thorium breeder fuel (with its relatively high 232 U concentration) was used as reactor makeup fuel, concentrations of 232 U varied from 441 ppM ( 232 U/U weight basis) at discharge from the first generation to about 512 ppM ( 232 U/U weight basis) at the end of the fifth generation. Concentrations in freshly fabricated fuel for this later case were 20 to 35% higher than the discharge concentration. These concentrations are low when compared to those of other thorium fueled reactor types (HTGR and MSBR) because of the relatively high 238 U concentration added to the fuel as a denaturant. Excellent agreement was found between calculated and existing experimental values. Nevertheless, caution is urged in the use of these values because experimental results are very limited, and the relevant nuclear data, especially for 231 Pa and 232 U, are not of high quality

Effects of high pressure freezing (HPF) on denaturation of natural actomyosin extracted from prawn (Metapenaeus ensis).

Science.gov (United States)

Cheng, Lina; Sun, Da-Wen; Zhu, Zhiwei; Zhang, Zhihang

2017-08-15

Effects of protein denaturation caused by high pressure freezing, involving Pressure-Factors (pressure, time) and Freezing-Factors (temperature, phase transition, recrystallization, ice crystal types), are complicated. In the current study, the conformation and functional changes of natural actomyosin (NAM) under pressure assisted freezing (PAF, 100,150,300,400,500MPa P -20°C/25min ), pressure shift freezing (PSF, 200MPa P -20°C/25min ), and immersion freezing ( 0.1MPa P -20°C/5min ) after pressure was released to 0.1MPa, as compared to normal immersion freezing process (IF, 0.1MPa P -20°C/30min ). Results indicated that PSF ( 200MPa P -20°C/30min ) could reduce the denaturation of frozen NAM and a pressure of 300MPa was the critical point to induce such a denaturation. During the periods of B→D in PSF or B→C→D in PAF, the generation and growth of ice crystals played an important role on changing the secondary and tertiary structure of the treated NAM. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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.

Ensemble inequivalence: Landau theory and the ABC model

International Nuclear Information System (INIS)

Cohen, O; Mukamel, D

2012-01-01

It is well known that systems with long-range interactions may exhibit different phase diagrams when studied within two different ensembles. In many of the previously studied examples of ensemble inequivalence, the phase diagrams differ only when the transition in one of the ensembles is first order. By contrast, in a recent study of a generalized ABC model, the canonical and grand-canonical ensembles of the model were shown to differ even when they both exhibit a continuous transition. Here we show that the order of the transition where ensemble inequivalence may occur is related to the symmetry properties of the order parameter associated with the transition. This is done by analyzing the Landau expansion of a generic model with long-range interactions. The conclusions drawn from the generic analysis are demonstrated for the ABC model by explicit calculation of its Landau expansion. (paper)

Signal Peptide and Denaturing Temperature are Critical Factors for Efficient Mammalian Expression and Immunoblotting of Cannabinoid Receptors*

Science.gov (United States)

WANG, Chenyun; WANG, Yingying; WANG, Miao; CHEN, Jiankui; YU, Nong; SONG, Shiping; KAMINSKI, Norbert E.; ZHANG, Wei

2013-01-01

Summary Many researchers employed mammalian expression system to artificially express cannabinoid receptors, but immunoblot data that directly prove efficient protein expression can hardly be seen in related research reports. In present study, we demonstrated cannabinoid receptor protein was not able to be properly expressed with routine mammalian expression system. This inefficient expression was rescued by endowing an exogenous signal peptide ahead of cannabinoid receptor peptide. In addition, the artificially synthesized cannabinoid receptor was found to aggregate under routine sample denaturing temperatures (i.e., ≥95°C), forming a large molecular weight band when analyzed by immunoblotting. Only denaturing temperatures ≤75°C yielded a clear band at the predicted molecular weight. Collectively, we showed that efficient mammalian expression of cannabinoid receptors need a signal peptide sequence, and described the requirement for a low sample denaturing temperature in immunoblot analysis. These findings provide very useful information for efficient mammalian expression and immunoblotting of membrane receptors. PMID:22528237

Preparation of denatured protein bone sterilized with gamma radiation; Preparacion de hueso desproteinizado esterilizado con radiacion gamma

Energy Technology Data Exchange (ETDEWEB)

Luna Z, D [ININ, 52045 Ocoyoacac, Estado de Mexico (Mexico)

2005-07-01

The bone is one of the tissues more transplanted in the entire world by that the bone necessity for transplant every day becomes bigger. In the Bank of tissues Radio sterilized of the ININ the amnion and the pig skin are routinely processed. The tissue with which will be continued is with bone. Due to that in our country it doesn't have enough bone of human origin for the necessities required in the bone transplant, an option is the bone of bovine. Of this bone one can obtain denatured protein bone, with the same characteristics of the denatured protein human bone, the one which has been proven that it has good acceptance and incorporation in the human body when is transplanted. The method for the obtaining of the denatured protein bone of bovine, with the confirmation of the final product by means of X-ray diffraction is described. The radiosterilization of this bone with gamma rays and the determination of the lead content. (Author)

Preparation of denatured protein bone sterilized with gamma radiation; Preparacion de hueso desproteinizado esterilizado con radiacion gamma

Energy Technology Data Exchange (ETDEWEB)

Luna Z, D. [ININ, 52045 Ocoyoacac, Estado de Mexico (Mexico)]. e-mail: dlz@nuclear.inin.mx

2005-07-01

The bone is one of the tissues more transplanted in the entire world by that the bone necessity for transplant every day becomes bigger. In the Bank of tissues Radio sterilized of the ININ the amnion and the pig skin are routinely processed. The tissue with which will be continued is with bone. Due to that in our country it doesn't have enough bone of human origin for the necessities required in the bone transplant, an option is the bone of bovine. Of this bone one can obtain denatured protein bone, with the same characteristics of the denatured protein human bone, the one which has been proven that it has good acceptance and incorporation in the human body when is transplanted. The method for the obtaining of the denatured protein bone of bovine, with the confirmation of the final product by means of X-ray diffraction is described. The radiosterilization of this bone with gamma rays and the determination of the lead content. (Author)

Regionalization of post-processed ensemble runoff forecasts

Directory of Open Access Journals (Sweden)

J. O. Skøien

2016-05-01

Full Text Available For many years, meteorological models have been run with perturbated initial conditions or parameters to produce ensemble forecasts that are used as a proxy of the uncertainty of the forecasts. However, the ensembles are usually both biased (the mean is systematically too high or too low, compared with the observed weather, and has dispersion errors (the ensemble variance indicates a too low or too high confidence in the forecast, compared with the observed weather. The ensembles are therefore commonly post-processed to correct for these shortcomings. Here we look at one of these techniques, referred to as Ensemble Model Output Statistics (EMOS (Gneiting et al., 2005. Originally, the post-processing parameters were identified as a fixed set of parameters for a region. The application of our work is the European Flood Awareness System (http://www.efas.eu, where a distributed model is run with meteorological ensembles as input. We are therefore dealing with a considerably larger data set than previous analyses. We also want to regionalize the parameters themselves for other locations than the calibration gauges. The post-processing parameters are therefore estimated for each calibration station, but with a spatial penalty for deviations from neighbouring stations, depending on the expected semivariance between the calibration catchment and these stations. The estimated post-processed parameters can then be used for regionalization of the postprocessing parameters also for uncalibrated locations using top-kriging in the rtop-package (Skøien et al., 2006, 2014. We will show results from cross-validation of the methodology and although our interest is mainly in identifying exceedance probabilities for certain return levels, we will also show how the rtop package can be used for creating a set of post-processed ensembles through simulations.

Denaturing of single electrospun fibrinogen fibers studied by deep ultraviolet fluorescence microscopy.

Science.gov (United States)

Kim, Jeongyong; Song, Hugeun; Park, Inho; Carlisle, Christine R; Bonin, Keith; Guthold, Martin

2011-03-01

Deep ultraviolet (DUV) microscopy is a fluorescence microscopy technique to image unlabeled proteins via the native fluorescence of some of their amino acids. We constructed a DUV fluorescence microscope, capable of 280 nm wavelength excitation by modifying an inverted optical microscope. Moreover, we integrated a nanomanipulator-controlled micropipette into this instrument for precise delivery of picoliter amounts of fluid to selected regions of the sample. In proof-of-principle experiments, we used this instrument to study, in situ, the effect of a denaturing agent on the autofluorescence intensity of single, unlabeled, electrospun fibrinogen nanofibers. Autofluorescence emission from the nanofibers was excited at 280 nm and detected at ∼350 nm. A denaturant solution was discretely applied to small, select sections of the nanofibers and a clear local reduction in autofluorescence intensity was observed. This reduction is attributed to the dissolution of the fibers and the unfolding of proteins in the fibers. Copyright © 2010 Wiley-Liss, Inc.

Teaching what one does not know: strangeness and denaturation in (autobiographical narrations

Directory of Open Access Journals (Sweden)

Jorge Luiz da Cunha

2014-01-01

Full Text Available The thematic focus in this text are the estrangement/denaturation processes in (autobiographical narrations. The aim of this study was to reflect on the possibility to promote estrangement/denatura - tion in (autobiographical writings made by teenagers in the space/ time of the classroom environment. The methodological proposal consisted on developing (autobiographical writings by students from sociology classes in High School. A total of 138 teenagers from a public school, attending the first school trimester in the year 2013, have participated in the study. The concepts of estrangement/de - naturation are located in the anthropology field and, the work with (autobiographical narrations is located in the socio-clinic perspec - tives and of biographization processes. The results indicate that (autobiographical narrations provide estrangements/denaturation and go towards teaching what one does not know. We can, then, conclude that this possibility, as an educational act, may generate knowledge suspension to self-inventiveness.

Assessment and economic valuation of air pollution impacts on human health over Europe and the United States as calculated by a multi-model ensemble in the framework of AQMEII3

Science.gov (United States)

The impact of air pollution on human health and the associated external costs in Europe and the United States (US) for the year 2010 are modeled by a multi-model ensemble of regional models in the frame of the third phase of the Air Quality Modelling Evaluation International Init...

Pauci ex tanto numero: reducing redundancy in multi-model ensembles

Science.gov (United States)

Solazzo, E.; Riccio, A.; Kioutsioukis, I.; Galmarini, S.

2013-02-01

We explicitly address the fundamental issue of member diversity in multi-model ensembles. To date no attempts in this direction are documented within the air quality (AQ) community, although the extensive use of ensembles in this field. Common biases and redundancy are the two issues directly deriving from lack of independence, undermining the significance of a multi-model ensemble, and are the subject of this study. Shared biases among models will determine a biased ensemble, making therefore essential the errors of the ensemble members to be independent so that bias can cancel out. Redundancy derives from having too large a portion of common variance among the members of the ensemble, producing overconfidence in the predictions and underestimation of the uncertainty. The two issues of common biases and redundancy are analysed in detail using the AQMEII ensemble of AQ model results for four air pollutants in two European regions. We show that models share large portions of bias and variance, extending well beyond those induced by common inputs. We make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble with the advantage of being poorly correlated. Selecting the members for generating skilful, non-redundant ensembles from such subsets proved, however, non-trivial. We propose and discuss various methods of member selection and rate the ensemble performance they produce. In most cases, the full ensemble is outscored by the reduced ones. We conclude that, although independence of outputs may not always guarantee enhancement of scores (but this depends upon the skill being investigated) we discourage selecting the members of the ensemble simply on the basis of scores, that is, independence and skills need to be considered disjointly.

Deciphering allogeneic antibody response against native and denatured HLA epitopes in organ transplantation.

Science.gov (United States)

Visentin, Jonathan; Guidicelli, Gwendaline; Moreau, Jean-François; Lee, Jar-How; Taupin, Jean-Luc

2015-07-01

Anti-HLA donor-specific antibodies are deleterious for organ transplant survival. Class I HLA donor-specific antibodies are identified by using the Luminex single antigen beads (LSAB) assay, which also detects anti-denatured HLA antibodies (anti-dHLAs). Anti-dHLAs are thought to be unable to recognize native HLA (nHLA) on the cell surface and therefore to be clinically irrelevant. Acid denaturation of nHLA on LSAB allows anti-dHLAs to be discriminated from anti-nHLAs. We previously defined a threshold for the ratio between mean fluorescence intensity against acid-treated (D for denaturation) and nontreated (N) LSAB, D ≥ 1.2 N identifying the anti-dHLAs. However, some anti-dHLAs remained able to bind nHLA on lymphocytes in flow cytometry crossmatches, and some anti-nHLAs conserved significant reactivity toward acid-treated LSAB. After depleting serum anti-nHLA reactivity with HLA-typed cells, we analyzed the residual LSAB reactivity toward nontreated and acid-treated LSABs, and then evaluated the ability of antibodies to recognize nHLA alleles individually. We observed that sera can contain mixtures of anti-nHLAs and anti-dHLAs, or anti-nHLAs recognizing acid-resistant epitopes, all possibly targeting the same allele(s). Therefore, the anti-HLA antibody response can be highly complex and subtle, as is the accurate identification of pathogenic anti-HLA antibodies in human serum. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

KAUST Repository

Altaf, Muhammad

2014-08-01

This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.

A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

KAUST Repository

Altaf, Muhammad; Butler, T.; Mayo, T.; Luo, X.; Dawson, C.; Heemink, A. W.; Hoteit, Ibrahim

2014-01-01

This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.

Performance Analysis of Local Ensemble Kalman Filter

Science.gov (United States)

Tong, Xin T.

2018-03-01

Ensemble Kalman filter (EnKF) is an important data assimilation method for high-dimensional geophysical systems. Efficient implementation of EnKF in practice often involves the localization technique, which updates each component using only information within a local radius. This paper rigorously analyzes the local EnKF (LEnKF) for linear systems and shows that the filter error can be dominated by the ensemble covariance, as long as (1) the sample size exceeds the logarithmic of state dimension and a constant that depends only on the local radius; (2) the forecast covariance matrix admits a stable localized structure. In particular, this indicates that with small system and observation noises, the filter error will be accurate in long time even if the initialization is not. The analysis also reveals an intrinsic inconsistency caused by the localization technique, and a stable localized structure is necessary to control this inconsistency. While this structure is usually taken for granted for the operation of LEnKF, it can also be rigorously proved for linear systems with sparse local observations and weak local interactions. These theoretical results are also validated by numerical implementation of LEnKF on a simple stochastic turbulence in two dynamical regimes.

HIGH-RESOLUTION ATMOSPHERIC ENSEMBLE MODELING AT SRNL

Energy Technology Data Exchange (ETDEWEB)

Buckley, R.; Werth, D.; Chiswell, S.; Etherton, B.

2011-05-10

The High-Resolution Mid-Atlantic Forecasting Ensemble (HME) is a federated effort to improve operational forecasts related to precipitation, convection and boundary layer evolution, and fire weather utilizing data and computing resources from a diverse group of cooperating institutions in order to create a mesoscale ensemble from independent members. Collaborating organizations involved in the project include universities, National Weather Service offices, and national laboratories, including the Savannah River National Laboratory (SRNL). The ensemble system is produced from an overlapping numerical weather prediction model domain and parameter subsets provided by each contributing member. The coordination, synthesis, and dissemination of the ensemble information are performed by the Renaissance Computing Institute (RENCI) at the University of North Carolina-Chapel Hill. This paper discusses background related to the HME effort, SRNL participation, and example results available from the RENCI website.

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.

Disease-associated mutations that alter the RNA structural ensemble.

Directory of Open Access Journals (Sweden)

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.

The Hydrologic Ensemble Prediction Experiment (HEPEX)

Science.gov (United States)

Wood, A. W.; Thielen, J.; Pappenberger, F.; Schaake, J. C.; Hartman, R. K.

2012-12-01

The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF). With support from the US National Weather Service (NWS) and the European Commission (EC), the HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support in emergency management and water resources sectors. The strategy to meet this goal includes meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. HEPEX has organized about a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Today, the HEPEX mission is to demonstrate the added value of hydrological ensemble prediction systems (HEPS) for emergency management and water resources sectors to make decisions that have important consequences for economy, public health, safety, and the environment. HEPEX is now organised around six major themes that represent core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

Changes in Appetitive Associative Strength Modulates Nucleus Accumbens, But Not Orbitofrontal Cortex Neuronal Ensemble Excitability.

Science.gov (United States)

Ziminski, Joseph J; Hessler, Sabine; Margetts-Smith, Gabriella; Sieburg, Meike C; Crombag, Hans S; Koya, Eisuke

2017-03-22

Cues that predict the availability of food rewards influence motivational states and elicit food-seeking behaviors. If a cue no longer predicts food availability, then animals may adapt accordingly by inhibiting food-seeking responses. Sparsely activated sets of neurons, coined "neuronal ensembles," have been shown to encode the strength of reward-cue associations. Although alterations in intrinsic excitability have been shown to underlie many learning and memory processes, little is known about these properties specifically on cue-activated neuronal ensembles. We examined the activation patterns of cue-activated orbitofrontal cortex (OFC) and nucleus accumbens (NAc) shell ensembles using wild-type and Fos-GFP mice, which express green fluorescent protein (GFP) in activated neurons, after appetitive conditioning with sucrose and extinction learning. We also investigated the neuronal excitability of recently activated, GFP+ neurons in these brain areas using whole-cell electrophysiology in brain slices. Exposure to a sucrose cue elicited activation of neurons in both the NAc shell and OFC. In the NAc shell, but not the OFC, these activated GFP+ neurons were more excitable than surrounding GFP- neurons. After extinction, the number of neurons activated in both areas was reduced and activated ensembles in neither area exhibited altered excitability. These data suggest that learning-induced alterations in the intrinsic excitability of neuronal ensembles is regulated dynamically across different brain areas. Furthermore, we show that changes in associative strength modulate the excitability profile of activated ensembles in the NAc shell. SIGNIFICANCE STATEMENT Sparsely distributed sets of neurons called "neuronal ensembles" encode learned associations about food and cues predictive of its availability. Widespread changes in neuronal excitability have been observed in limbic brain areas after associative learning, but little is known about the excitability changes that

Ensemble of different approaches for a reliable person re-identification system

Directory of Open Access Journals (Sweden)

Loris Nanni

2016-07-01

Full Text Available An ensemble of approaches for reliable person re-identification is proposed in this paper. The proposed ensemble is built combining widely used person re-identification systems using different color spaces and some variants of state-of-the-art approaches that are proposed in this paper. Different descriptors are tested, and both texture and color features are extracted from the images; then the different descriptors are compared using different distance measures (e.g., the Euclidean distance, angle, and the Jeffrey distance. To improve performance, a method based on skeleton detection, extracted from the depth map, is also applied when the depth map is available. The proposed ensemble is validated on three widely used datasets (CAVIAR4REID, IAS, and VIPeR, keeping the same parameter set of each approach constant across all tests to avoid overfitting and to demonstrate that the proposed system can be considered a general-purpose person re-identification system. Our experimental results show that the proposed system offers significant improvements over baseline approaches. The source code used for the approaches tested in this paper will be available at https://www.dei.unipd.it/node/2357 and http://robotics.dei.unipd.it/reid/.

Pauci ex tanto numero: reduce redundancy in multi-model ensembles

Science.gov (United States)

Solazzo, E.; Riccio, A.; Kioutsioukis, I.; Galmarini, S.

2013-08-01

We explicitly address the fundamental issue of member diversity in multi-model ensembles. To date, no attempts in this direction have been documented within the air quality (AQ) community despite the extensive use of ensembles in this field. Common biases and redundancy are the two issues directly deriving from lack of independence, undermining the significance of a multi-model ensemble, and are the subject of this study. Shared, dependant biases among models do not cancel out but will instead determine a biased ensemble. Redundancy derives from having too large a portion of common variance among the members of the ensemble, producing overconfidence in the predictions and underestimation of the uncertainty. The two issues of common biases and redundancy are analysed in detail using the AQMEII ensemble of AQ model results for four air pollutants in two European regions. We show that models share large portions of bias and variance, extending well beyond those induced by common inputs. We make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble with the advantage of being poorly correlated. Selecting the members for generating skilful, non-redundant ensembles from such subsets proved, however, non-trivial. We propose and discuss various methods of member selection and rate the ensemble performance they produce. In most cases, the full ensemble is outscored by the reduced ones. We conclude that, although independence of outputs may not always guarantee enhancement of scores (but this depends upon the skill being investigated), we discourage selecting the members of the ensemble simply on the basis of scores; that is, independence and skills need to be considered disjointly.

Data assimilation in integrated hydrological modeling using ensemble Kalman filtering

DEFF Research Database (Denmark)

Rasmussen, Jørn; Madsen, H.; Jensen, Karsten Høgh

2015-01-01

Groundwater head and stream discharge is assimilated using the ensemble transform Kalman filter in an integrated hydrological model with the aim of studying the relationship between the filter performance and the ensemble size. In an attempt to reduce the required number of ensemble members...... and estimating parameters requires a much larger ensemble size than just assimilating groundwater head observations. However, the required ensemble size can be greatly reduced with the use of adaptive localization, which by far outperforms distance-based localization. The study is conducted using synthetic data...

Reduction of Used Memory Ensemble Kalman Filtering (RumEnKF): A data assimilation scheme for memory intensive, high performance computing

Science.gov (United States)

Hut, Rolf; Amisigo, Barnabas A.; Steele-Dunne, Susan; van de Giesen, Nick

2015-12-01

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. RumEnKF reduces the used memory compared to the EnKF when the number of ensemble members is greater than half the number of state variables. In this paper, three simple models are used (auto-regressive, low dimensional Lorenz and high dimensional Lorenz) to show that RumEnKF performs similarly to the EnKF. Furthermore, it is also shown that increasing the ensemble size has a similar impact on the estimation error from the three algorithms.

Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices

Directory of Open Access Journals (Sweden)

F. Fundel

2013-01-01

Full Text Available Streamflow droughts, characterized by low runoff as consequence of a drought event, affect numerous aspects of life. Economic sectors that are impacted by low streamflow are, e.g., power production, agriculture, tourism, water quality management and shipping. Those sectors could potentially benefit from forecasts of streamflow drought events, even of short events on the monthly time scales or below. Numerical hydrometeorological models have increasingly been used to forecast low streamflow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the evaluation of low streamflow and of the derived indices as duration, severity and magnitude, characterizing streamflow droughts up to a lead time of one month.

The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification reveals that, compared to probabilistic peak-flow forecasts, which show skill up to a lead time of two weeks, forecasts of streamflow droughts are skilful over the entire forecast range of one month. For forecasts at the lower end of the runoff regime, the quality of the initial state seems to be crucial to achieve a good forecast quality in the longer range. It is shown that the states used in this study to initialize forecasts satisfy this requirement. The produced forecasts of streamflow drought indices, derived from the ensemble forecasts, could be beneficially included in a decision-making process. This is valid for probabilistic forecasts of streamflow drought events falling below a daily varying threshold, based on a quantile derived from a runoff climatology. Although the forecasts have a tendency to overpredict streamflow droughts, it is shown that the relative economic value of the ensemble forecasts reaches up to 60%, in case a forecast user is able to take preventive

Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices

Science.gov (United States)

Fundel, F.; Jörg-Hess, S.; Zappa, M.

2013-01-01

Streamflow droughts, characterized by low runoff as consequence of a drought event, affect numerous aspects of life. Economic sectors that are impacted by low streamflow are, e.g., power production, agriculture, tourism, water quality management and shipping. Those sectors could potentially benefit from forecasts of streamflow drought events, even of short events on the monthly time scales or below. Numerical hydrometeorological models have increasingly been used to forecast low streamflow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the evaluation of low streamflow and of the derived indices as duration, severity and magnitude, characterizing streamflow droughts up to a lead time of one month. The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification reveals that, compared to probabilistic peak-flow forecasts, which show skill up to a lead time of two weeks, forecasts of streamflow droughts are skilful over the entire forecast range of one month. For forecasts at the lower end of the runoff regime, the quality of the initial state seems to be crucial to achieve a good forecast quality in the longer range. It is shown that the states used in this study to initialize forecasts satisfy this requirement. The produced forecasts of streamflow drought indices, derived from the ensemble forecasts, could be beneficially included in a decision-making process. This is valid for probabilistic forecasts of streamflow drought events falling below a daily varying threshold, based on a quantile derived from a runoff climatology. Although the forecasts have a tendency to overpredict streamflow droughts, it is shown that the relative economic value of the ensemble forecasts reaches up to 60%, in case a forecast user is able to take preventive action based on the forecast.

Stabilizing effect of biochar on soil extracellular enzymes after a denaturing stress.

Science.gov (United States)

Elzobair, Khalid A; Stromberger, Mary E; Ippolito, James A

2016-01-01

Stabilizing extracellular enzymes may maintain enzymatic activity while protecting enzymes from proteolysis and denaturation. A study determined whether a fast pyrolysis hardwood biochar (CQuest™) would reduce evaporative losses, subsequently stabilizing soil extracellular enzymes and prohibiting potential enzymatic activity loss following a denaturing stress (microwaving). Soil was incubated in the presence of biochar (0%, 1%, 2%, 5%, or 10% by wt.) for 36 days and then exposed to microwave energies (0, 400, 800, 1600, or 3200 J g(-1) soil). Soil enzymes (β-glucosidase, β-d-cellobiosidase, N-acetyl-β-glucosaminidase, phosphatase, leucine aminopeptidase, β-xylosidase) were analyzed by fluorescence-based assays. Biochar amendment reduced leucine aminopeptidase and β-xylosidase potential activity after the incubation period and prior to stress exposure. The 10% biochar rate reduced soil water loss at the lowest stress level (400 J microwave energy g(-1) soil). Enzyme stabilization was demonstrated for β-xylosidase; intermediate biochar application rates prevented a complete loss of this enzyme's potential activity after soil was exposed to 400 (1% biochar treatment) or 1600 (5% biochar treatment) J microwave energy g(-1) soil. Remaining enzyme potential activities were not affected by biochar, and activities decreased with increasing stress levels. We concluded that biochar has the potential to reduce evaporative soil water losses and stabilize certain extracellular enzymes where activity is maintained after a denaturing stress; this effect was biochar rate and enzyme dependent. While biochar may reduce the potential activity of certain soil extracellular enzymes, this phenomenon was not universal as the majority of enzymes assayed in this study were unaffected by exposure to biochar. Copyright © 2015 Elsevier Ltd. All rights reserved.

Constraining a compositional flow model with flow-chemical data using an ensemble-based Kalman filter

KAUST Repository

Gharamti, M. E.; Kadoura, A.; Valstar, J.; Sun, S.; Hoteit, Ibrahim

2014-01-01

Isothermal compositional flow models require coupling transient compressible flows and advective transport systems of various chemical species in subsurface porous media. Building such numerical models is quite challenging and may be subject to many sources of uncertainties because of possible incomplete representation of some geological parameters that characterize the system's processes. Advanced data assimilation methods, such as the ensemble Kalman filter (EnKF), can be used to calibrate these models by incorporating available data. In this work, we consider the problem of estimating reservoir permeability using information about phase pressure as well as the chemical properties of fluid components. We carry out state-parameter estimation experiments using joint and dual updating schemes in the context of the EnKF with a two-dimensional single-phase compositional flow model (CFM). Quantitative and statistical analyses are performed to evaluate and compare the performance of the assimilation schemes. Our results indicate that including chemical composition data significantly enhances the accuracy of the permeability estimates. In addition, composition data provide more information to estimate system states and parameters than do standard pressure data. The dual state-parameter estimation scheme provides about 10% more accurate permeability estimates on average than the joint scheme when implemented with the same ensemble members, at the cost of twice more forward model integrations. At similar computational cost, the dual approach becomes only beneficial after using large enough ensembles.

Constraining a compositional flow model with flow-chemical data using an ensemble-based Kalman filter

KAUST Repository

Gharamti, M. E.

2014-03-01

Isothermal compositional flow models require coupling transient compressible flows and advective transport systems of various chemical species in subsurface porous media. Building such numerical models is quite challenging and may be subject to many sources of uncertainties because of possible incomplete representation of some geological parameters that characterize the system\\'s processes. Advanced data assimilation methods, such as the ensemble Kalman filter (EnKF), can be used to calibrate these models by incorporating available data. In this work, we consider the problem of estimating reservoir permeability using information about phase pressure as well as the chemical properties of fluid components. We carry out state-parameter estimation experiments using joint and dual updating schemes in the context of the EnKF with a two-dimensional single-phase compositional flow model (CFM). Quantitative and statistical analyses are performed to evaluate and compare the performance of the assimilation schemes. Our results indicate that including chemical composition data significantly enhances the accuracy of the permeability estimates. In addition, composition data provide more information to estimate system states and parameters than do standard pressure data. The dual state-parameter estimation scheme provides about 10% more accurate permeability estimates on average than the joint scheme when implemented with the same ensemble members, at the cost of twice more forward model integrations. At similar computational cost, the dual approach becomes only beneficial after using large enough ensembles.

Ensemble-based Probabilistic Forecasting at Horns Rev

DEFF Research Database (Denmark)

Pinson, Pierre; Madsen, Henrik

2009-01-01

forecasting methodology. In a first stage, ensemble forecasts of meteorological variables are converted to power through a suitable power curve model. This modelemploys local polynomial regression, and is adoptively estimated with an orthogonal fitting method. The obtained ensemble forecasts of wind power...

DroidEnsemble: Detecting Android Malicious Applications with Ensemble of String and Structural Static Features

KAUST Repository

Wang, Wei

2018-05-11

Android platform has dominated the Operating System of mobile devices. However, the dramatic increase of Android malicious applications (malapps) has caused serious software failures to Android system and posed a great threat to users. The effective detection of Android malapps has thus become an emerging yet crucial issue. Characterizing the behaviors of Android applications (apps) is essential to detecting malapps. Most existing work on detecting Android malapps was mainly based on string static features such as permissions and API usage extracted from apps. There also exists work on the detection of Android malapps with structural features, such as Control Flow Graph (CFG) and Data Flow Graph (DFG). As Android malapps have become increasingly polymorphic and sophisticated, using only one type of static features may result in false negatives. In this work, we propose DroidEnsemble that takes advantages of both string features and structural features to systematically and comprehensively characterize the static behaviors of Android apps and thus build a more accurate detection model for the detection of Android malapps. We extract each app’s string features, including permissions, hardware features, filter intents, restricted API calls, used permissions, code patterns, as well as structural features like function call graph. We then use three machine learning algorithms, namely, Support Vector Machine (SVM), k-Nearest Neighbor (kNN) and Random Forest (RF), to evaluate the performance of these two types of features and of their ensemble. In the experiments, We evaluate our methods and models with 1386 benign apps and 1296 malapps. Extensive experimental results demonstrate the effectiveness of DroidEnsemble. It achieves the detection accuracy as 95.8% with only string features and as 90.68% with only structural features. DroidEnsemble reaches the detection accuracy as 98.4% with the ensemble of both types of features, reducing 9 false positives and 12 false

Micro-CT imaging of denatured chitin by silver to explore honey bee and insect pathologies.

Directory of Open Access Journals (Sweden)

Peter R Butzloff

Full Text Available BACKGROUND: Chitin and cuticle coatings are important to the environmental and immune defense of honey bees and insect pollinators. Pesticides or environmental effects may target the biochemistry of insect chitin and cuticle coating. Denaturing of chitin involves a combination of deacetylation, intercalation, oxidation, Schweiger-peeling, and the formation of amine hydrochloride salt. The term "denatured chitin" calls attention to structural and property changes to the internal membranes and external carapace of organisms so that some properties affecting biological activities are diminished. METHODOLOGY/PRINCIPAL FINDINGS: A case study was performed on honey bees using silver staining and microscopic computer-tomographic x-ray radiography (micro-CT. Silver nitrate formed counter-ion complexes with labile ammonium cations and reacted with amine hydrochloride. Silver was concentrated in the peritrophic membrane, on the abdomen, in the glossa, at intersegmental joints (tarsi, at wing attachments, and in tracheal air sacs. Imaged mono-esters and fatty acids from cuticle coating on external surfaces were apparently reduced by an alcohol pretreatment. CONCLUSIONS/SIGNIFICANCE: The technique provides 3-dimensional and sectional images of individual honey bees consistent with the chemistries of silver reaction and complex formation with denatured chitin. Environmental exposures and influences such as gaseous nitric oxide intercalant, trace oxidants such as ozone gas, oligosachharide salt conversion, exposure to acid rain, and chemical or biochemical denaturing by pesticides may be studied using this technique. Peritrophic membranes, which protect against food abrasion, microorganisms, and permit efficient digestion, were imaged. Apparent surface damage to the corneal lenses of compound eyes by dilute acid exposure consistent with chitin amine hydrochloride formation was imaged. The technique can contribute to existing insect pathology research, and may

Micro-CT Imaging of Denatured Chitin by Silver to Explore Honey Bee and Insect Pathologies

Science.gov (United States)

Butzloff, Peter R.

2011-01-01

Background Chitin and cuticle coatings are important to the environmental and immune defense of honey bees and insect pollinators. Pesticides or environmental effects may target the biochemistry of insect chitin and cuticle coating. Denaturing of chitin involves a combination of deacetylation, intercalation, oxidation, Schweiger-peeling, and the formation of amine hydrochloride salt. The term “denatured chitin” calls attention to structural and property changes to the internal membranes and external carapace of organisms so that some properties affecting biological activities are diminished. Methodology/Principal Findings A case study was performed on honey bees using silver staining and microscopic computer-tomographic x-ray radiography (micro-CT). Silver nitrate formed counter-ion complexes with labile ammonium cations and reacted with amine hydrochloride. Silver was concentrated in the peritrophic membrane, on the abdomen, in the glossa, at intersegmental joints (tarsi), at wing attachments, and in tracheal air sacs. Imaged mono-esters and fatty acids from cuticle coating on external surfaces were apparently reduced by an alcohol pretreatment. Conclusions/Significance The technique provides 3-dimensional and sectional images of individual honey bees consistent with the chemistries of silver reaction and complex formation with denatured chitin. Environmental exposures and influences such as gaseous nitric oxide intercalant, trace oxidants such as ozone gas, oligosachharide salt conversion, exposure to acid rain, and chemical or biochemical denaturing by pesticides may be studied using this technique. Peritrophic membranes, which protect against food abrasion, microorganisms, and permit efficient digestion, were imaged. Apparent surface damage to the corneal lenses of compound eyes by dilute acid exposure consistent with chitin amine hydrochloride formation was imaged. The technique can contribute to existing insect pathology research, and may provide an

A second-order unconstrained optimization method for canonical-ensemble density-functional methods

Science.gov (United States)

Nygaard, Cecilie R.; Olsen, Jeppe

2013-03-01

A second order converging method of ensemble optimization (SOEO) in the framework of Kohn-Sham Density-Functional Theory is presented, where the energy is minimized with respect to an ensemble density matrix. It is general in the sense that the number of fractionally occupied orbitals is not predefined, but rather it is optimized by the algorithm. SOEO is a second order Newton-Raphson method of optimization, where both the form of the orbitals and the occupation numbers are optimized simultaneously. To keep the occupation numbers between zero and two, a set of occupation angles is defined, from which the occupation numbers are expressed as trigonometric functions. The total number of electrons is controlled by a built-in second order restriction of the Newton-Raphson equations, which can be deactivated in the case of a grand-canonical ensemble (where the total number of electrons is allowed to change). To test the optimization method, dissociation curves for diatomic carbon are produced using different functionals for the exchange-correlation energy. These curves show that SOEO favors symmetry broken pure-state solutions when using functionals with exact exchange such as Hartree-Fock and Becke three-parameter Lee-Yang-Parr. This is explained by an unphysical contribution to the exact exchange energy from interactions between fractional occupations. For functionals without exact exchange, such as local density approximation or Becke Lee-Yang-Parr, ensemble solutions are favored at interatomic distances larger than the equilibrium distance. Calculations on the chromium dimer are also discussed. They show that SOEO is able to converge to ensemble solutions for systems that are more complicated than diatomic carbon.

Effective non-denaturing purification method for improving the solubility of recombinant actin-binding proteins produced by bacterial expression.

Science.gov (United States)

Chung, Jeong Min; Lee, Sangmin; Jung, Hyun Suk

2017-05-01

Bacterial expression is commonly used to produce recombinant and truncated mutant eukaryotic proteins. However, heterologous protein expression may render synthesized proteins insoluble. The conventional method used to express a poorly soluble protein, which involves denaturation and refolding, is time-consuming and inefficient. There are several non-denaturing approaches that can increase the solubility of recombinant proteins that include using different bacterial cell strains, altering the time of induction, lowering the incubation temperature, and employing different detergents for purification. In this study, we compared several non-denaturing protocols to express and purify two insoluble 34 kDa actin-bundling protein mutants. The solubility of the mutant proteins was not affected by any of the approaches except for treatment with the detergent sarkosyl. These results indicate that sarkosyl can effectively improve the solubility of insoluble proteins during bacterial expression. Copyright © 2016. Published by Elsevier Inc.

Crossover ensembles of random matrices and skew-orthogonal polynomials

International Nuclear Information System (INIS)

Kumar, Santosh; Pandey, Akhilesh

2011-01-01

Highlights: → We study crossover ensembles of Jacobi family of random matrices. → We consider correlations for orthogonal-unitary and symplectic-unitary crossovers. → We use the method of skew-orthogonal polynomials and quaternion determinants. → We prove universality of spectral correlations in crossover ensembles. → We discuss applications to quantum conductance and communication theory problems. - Abstract: In a recent paper (S. Kumar, A. Pandey, Phys. Rev. E, 79, 2009, p. 026211) we considered Jacobi family (including Laguerre and Gaussian cases) of random matrix ensembles and reported exact solutions of crossover problems involving time-reversal symmetry breaking. In the present paper we give details of the work. We start with Dyson's Brownian motion description of random matrix ensembles and obtain universal hierarchic relations among the unfolded correlation functions. For arbitrary dimensions we derive the joint probability density (jpd) of eigenvalues for all transitions leading to unitary ensembles as equilibrium ensembles. We focus on the orthogonal-unitary and symplectic-unitary crossovers and give generic expressions for jpd of eigenvalues, two-point kernels and n-level correlation functions. This involves generalization of the theory of skew-orthogonal polynomials to crossover ensembles. We also consider crossovers in the circular ensembles to show the generality of our method. In the large dimensionality limit, correlations in spectra with arbitrary initial density are shown to be universal when expressed in terms of a rescaled symmetry breaking parameter. Applications of our crossover results to communication theory and quantum conductance problems are also briefly discussed.