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Sample records for molecular ensemble based

  1. Cosolvent-Based Molecular Dynamics for Ensemble Docking: Practical Method for Generating Druggable Protein Conformations.

    PubMed

    Uehara, Shota; Tanaka, Shigenori

    2017-04-07

    Protein flexibility is a major hurdle in current structure-based virtual screening (VS). In spite of the recent advances in high-performance computing, protein-ligand docking methods still demand tremendous computational cost to take into account the full degree of protein flexibility. In this context, ensemble docking has proven its utility and efficiency for VS studies, but it still needs a rational and efficient method to select and/or generate multiple protein conformations. Molecular dynamics (MD) simulations are useful to produce distinct protein conformations without abundant experimental structures. In this study, we present a novel strategy that makes use of cosolvent-based molecular dynamics (CMD) simulations for ensemble docking. By mixing small organic molecules into a solvent, CMD can stimulate dynamic protein motions and induce partial conformational changes of binding pocket residues appropriate for the binding of diverse ligands. The present method has been applied to six diverse target proteins and assessed by VS experiments using many actives and decoys of DEKOIS 2.0. The simulation results have revealed that the CMD is beneficial for ensemble docking. Utilizing cosolvent simulation allows the generation of druggable protein conformations, improving the VS performance compared with the use of a single experimental structure or ensemble docking by standard MD with pure water as the solvent.

  2. Algorithms and novel applications based on the isokinetic ensemble. I. Biophysical and path integral molecular dynamics

    NASA Astrophysics Data System (ADS)

    Minary, Peter; Martyna, Glenn J.; Tuckerman, Mark E.

    2003-02-01

    In this paper (Paper I) and a companion paper (Paper II), novel new algorithms and applications of the isokinetic ensemble as generated by Gauss' principle of least constraint, pioneered for use with molecular dynamics 20 years ago, are presented for biophysical, path integral, and Car-Parrinello based ab initio molecular dynamics. In Paper I, a new "extended system" version of the isokinetic equations of motion that overcomes the ergodicity problems inherent in the standard approach, is developed using a new theory of non-Hamiltonian phase space analysis [M. E. Tuckerman et al., Europhys. Lett. 45, 149 (1999); J. Chem. Phys. 115, 1678 (2001)]. Reversible multiple time step integrations schemes for the isokinetic methods, first presented by Zhang [J. Chem. Phys. 106, 6102 (1997)] are reviewed. Next, holonomic constraints are incorporated into the isokinetic methodology for use in fast efficient biomolecular simulation studies. Model and realistic examples are presented in order to evaluate, critically, the performance of the new isokinetic molecular dynamic schemes. Comparisons are made to the, now standard, canonical dynamics method, Nosé-Hoover chain dynamics [G. J. Martyna et al., J. Chem. Phys. 97, 2635 (1992)]. The new isokinetic techniques are found to yield more efficient sampling than the Nosé-Hoover chain method in both path integral molecular dynamics and biophysical molecular dynamics calculations. In Paper II, the use of isokinetic methods in Car-Parrinello based ab initio molecular dynamics calculations is presented.

  3. Quantum metrology with molecular ensembles

    SciTech Connect

    Schaffry, Marcus; Gauger, Erik M.; Morton, John J. L.; Fitzsimons, Joseph; Benjamin, Simon C.; Lovett, Brendon W.

    2010-10-15

    The field of quantum metrology promises measurement devices that are fundamentally superior to conventional technologies. Specifically, when quantum entanglement is harnessed, the precision achieved is supposed to scale more favorably with the resources employed, such as system size and time required. Here, we consider measurement of magnetic-field strength using an ensemble of spin-active molecules. We identify a third essential resource: the change in ensemble polarization (entropy increase) during the metrology experiment. We find that performance depends crucially on the form of decoherence present; for a plausible dephasing model, we describe a quantum strategy, which can indeed beat the standard strategy.

  4. Algorithms and novel applications based on the isokinetic ensemble. II. Ab initio molecular dynamics

    NASA Astrophysics Data System (ADS)

    Minary, Peter; Martyna, Glenn J.; Tuckerman, Mark E.

    2003-02-01

    In this paper (Paper II), the isokinetic dynamics scheme described in Paper I is combined with the plane-wave based Car-Parrinello (CP) ab initio molecular dynamics (MD) method [R. Car and M. Parrinello, Phys. Rev. Lett. 55, 2471 (1985)] to enable the efficient study of chemical reactions and metallic systems. The Car-Parrinello approach employs "on the fly" electronic structure calculations as a means of generating accurate internuclear forces for use in a molecular dynamics simulation. This is accomplished by the introduction of an extended Lagrangian that contains the electronic orbitals as fictitious dynamical variables (often expressed directly in terms of the expansion coefficients of the orbitals in a particular basis set). Thus, rather than quench the expansion coefficients to obtain the ground state energy and nuclear forces at every time step, the orbitals are "propagated" under conditions that allow them to fluctuate rapidly around their global minimum and, hence, generate an accurate approximation to the nuclear forces as the simulation proceeds. Indeed, the CP technique requires the dynamics of the orbitals to be both fast compared to the nuclear degrees of freedom while keeping the fictitious kinetic energy that allows them to be propagated dynamically as small as possible. While these conditions can be easy to achieve in many types of systems, in metals and highly exothermic chemical reactions difficulties arise. (Note, the CP dynamics of metals is incorrect because the nuclear motion does not occur on the ground state electronic surface but it can, nonetheless, provide useful information.) In order to alleviate these difficulties the isokinetic methods of Paper I are applied to derive isokinetic CP equations of motion. The efficacy of the new isokinetic CPMD method is demonstrated on model and realistic systems. The latter include, metallic systems, liquid aluminum, a small silicon sample, the 2×1 reconstruction of the silicon 100 surface, and the

  5. Molecular docking to ensembles of protein structures.

    PubMed

    Knegtel, R M; Kuntz, I D; Oshiro, C M

    1997-02-21

    Until recently, applications of molecular docking assumed that the macromolecular receptor exists in a single, rigid conformation. However, structural studies involving different ligands bound to the same target biomolecule frequently reveal modest but significant conformational changes in the target. In this paper, two related methods for molecular docking are described that utilize information on conformational variability from ensembles of experimental receptor structures. One method combines the information into an "energy-weighted average" of the interaction energy between a ligand and each receptor structure. The other method performs the averaging on a structural level, producing a "geometry-weighted average" of the inter-molecular force field score used in DOCK 3.5. Both methods have been applied in docking small molecules to ensembles of crystal and solution structures, and we show that experimentally determined binding orientations and computed energies of known ligands can be reproduced accurately. The use of composite grids, when conformationally different protein structures are available, yields an improvement in computational speed for database searches in proportion to the number of structures.

  6. Thermodynamics and kinetics of a molecular motor ensemble.

    PubMed Central

    Baker, J E; Thomas, D D

    2000-01-01

    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. PMID:11023881

  7. Thermodynamics and kinetics of a molecular motor ensemble.

    PubMed

    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.

  8. MSEBAG: a dynamic classifier ensemble generation based on `minimum-sufficient ensemble' and bagging

    NASA Astrophysics Data System (ADS)

    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.

  9. Ensemble-based global ocean data assimilation

    NASA Astrophysics Data System (ADS)

    Nadiga, Balasubramanya T.; Casper, W. Riley; Jones, Philip W.

    2013-12-01

    We present results of experiments performing global, ensemble-based, ocean-only data assimilation and assess the utility of such data assimilation in improving model predictions. The POP (Parallel Ocean Program) Ocean General Circulation Model (OGCM) is forced by interannually varying atmospheric fields of version 2 of the Coordinated Ocean Reference Experiment (CORE) data set, and temperature and salinity observations from the World Ocean Database 2009 (WOD09) are assimilated. The assimilation experiments are conducted over a period of about two years starting January 1, 1990 using the framework of the Data Assimilation Research Testbed (DART). We find that an inflation scheme that blends the ensemble-based sample error covariance with a static estimate of ensemble spread is necessary for the assimilations to be effective in the ocean model. We call this Climatology-based Spread Inflation or CSI for short. The effectiveness of the proposed inflation scheme is investigated in a low-order model; a series of experiments in this context demonstrates its effectiveness. Using a number of diagnostics, we show that the resulting assimilated state of ocean circulation is more realistic: In particular, the sea surface temperature (SST) shows reduced errors with respect to an unassimilated SST data set, and the subsurface temperature shows reduced errors with respect to observations. Finally, towards assessing the utility of assimilations for predictions, we show that the use of an assimilated state as initial condition leads to improved hindcast skill over a significant period of time; that is when the OGCM is initialized with an assimilated state and run forward, it is better able to predict unassimilated observations of the WOD09 than a control non-assimilating run (≈ 20% reduction in error) over a period of about three months. The loss of skill beyond this period is conjectured to be due, in part, to model error and prevents an improvement in the representation of

  10. Formulation of Liouville's theorem for grand ensemble molecular simulations

    NASA Astrophysics Data System (ADS)

    Delle Site, Luigi

    2016-02-01

    Liouville's theorem in a grand ensemble, that is for situations where a system is in equilibrium with a reservoir of energy and particles, is a subject that, to our knowledge, has not been explicitly treated in literature related to molecular simulation. Instead, Liouville's theorem, a central concept for the correct employment of molecular simulation techniques, is implicitly considered only within the framework of systems where the total number of particles is fixed. However, the pressing demand of applied science in treating open systems leads to the question of the existence and possible exact formulation of Liouville's theorem when the number of particles changes during the dynamical evolution of the system. The intention of this paper is to stimulate a debate about this crucial issue for molecular simulation.

  11. Argumentation based joint learning: a novel ensemble learning approach.

    PubMed

    Xu, Junyi; Yao, Li; Li, Le

    2015-01-01

    Recently, ensemble learning methods have been widely used to improve classification performance in machine learning. In this paper, we present a novel ensemble learning method: argumentation based multi-agent joint learning (AMAJL), which integrates ideas from multi-agent argumentation, ensemble learning, and association rule mining. In AMAJL, argumentation technology is introduced as an ensemble strategy to integrate multiple base classifiers and generate a high performance ensemble classifier. We design an argumentation framework named Arena as a communication platform for knowledge integration. Through argumentation based joint learning, high quality individual knowledge can be extracted, and thus a refined global knowledge base can be generated and used independently for classification. We perform numerous experiments on multiple public datasets using AMAJL and other benchmark methods. The results demonstrate that our method can effectively extract high quality knowledge for ensemble classifier and improve the performance of classification.

  12. Protein Remote Homology Detection Based on an Ensemble Learning Approach

    PubMed Central

    Chen, Junjie; Liu, Bingquan; Huang, Dong

    2016-01-01

    Protein remote homology detection is one of the central problems in bioinformatics. Although some computational methods have been proposed, the problem is still far from being solved. In this paper, an ensemble classifier for protein remote homology detection, called SVM-Ensemble, was proposed with a weighted voting strategy. SVM-Ensemble combined three basic classifiers based on different feature spaces, including Kmer, ACC, and SC-PseAAC. These features consider the characteristics of proteins from various perspectives, incorporating both the sequence composition and the sequence-order information along the protein sequences. Experimental results on a widely used benchmark dataset showed that the proposed SVM-Ensemble can obviously improve the predictive performance for the protein remote homology detection. Moreover, it achieved the best performance and outperformed other state-of-the-art methods. PMID:27294123

  13. Ensemble Sampling vs. Time Sampling in Molecular Dynamics Simulations of Thermal Conductivity

    SciTech Connect

    Gordiz, Kiarash; Singh, David J.; Henry, Asegun

    2015-01-29

    In this report we compare time sampling and ensemble averaging as two different methods available for phase space sampling. For the comparison, we calculate thermal conductivities of solid argon and silicon structures, using equilibrium molecular dynamics. We introduce two different schemes for the ensemble averaging approach, and show that both can reduce the total simulation time as compared to time averaging. It is also found that velocity rescaling is an efficient mechanism for phase space exploration. Although our methodology is tested using classical molecular dynamics, the ensemble generation approaches may find their greatest utility in computationally expensive simulations such as first principles molecular dynamics. For such simulations, where each time step is costly, time sampling can require long simulation times because each time step must be evaluated sequentially and therefore phase space averaging is achieved through sequential operations. On the other hand, with ensemble averaging, phase space sampling can be achieved through parallel operations, since each ensemble is independent. For this reason, particularly when using massively parallel architectures, ensemble sampling can result in much shorter simulation times and exhibits similar overall computational effort.

  14. Ensemble Sampling vs. Time Sampling in Molecular Dynamics Simulations of Thermal Conductivity

    DOE PAGES

    Gordiz, Kiarash; Singh, David J.; Henry, Asegun

    2015-01-29

    In this report we compare time sampling and ensemble averaging as two different methods available for phase space sampling. For the comparison, we calculate thermal conductivities of solid argon and silicon structures, using equilibrium molecular dynamics. We introduce two different schemes for the ensemble averaging approach, and show that both can reduce the total simulation time as compared to time averaging. It is also found that velocity rescaling is an efficient mechanism for phase space exploration. Although our methodology is tested using classical molecular dynamics, the ensemble generation approaches may find their greatest utility in computationally expensive simulations such asmore » first principles molecular dynamics. For such simulations, where each time step is costly, time sampling can require long simulation times because each time step must be evaluated sequentially and therefore phase space averaging is achieved through sequential operations. On the other hand, with ensemble averaging, phase space sampling can be achieved through parallel operations, since each ensemble is independent. For this reason, particularly when using massively parallel architectures, ensemble sampling can result in much shorter simulation times and exhibits similar overall computational effort.« less

  15. Large margin classifier-based ensemble tracking

    NASA Astrophysics Data System (ADS)

    Wang, Yuru; Liu, Qiaoyuan; Yin, Minghao; Wang, ShengSheng

    2016-07-01

    In recent years, many studies consider visual tracking as a two-class classification problem. The key problem is to construct a classifier with sufficient accuracy in distinguishing the target from its background and sufficient generalize ability in handling new frames. However, the variable tracking conditions challenges the existing methods. The difficulty mainly comes from the confused boundary between the foreground and background. This paper handles this difficulty by generalizing the classifier's learning step. By introducing the distribution data of samples, the classifier learns more essential characteristics in discriminating the two classes. Specifically, the samples are represented in a multiscale visual model. For features with different scales, several large margin distribution machine (LDMs) with adaptive kernels are combined in a Baysian way as a strong classifier. Where, in order to improve the accuracy and generalization ability, not only the margin distance but also the sample distribution is optimized in the learning step. Comprehensive experiments are performed on several challenging video sequences, through parameter analysis and field comparison, the proposed LDM combined ensemble tracker is demonstrated to perform with sufficient accuracy and generalize ability in handling various typical tracking difficulties.

  16. Verification of the Forecast Errors Based on Ensemble Spread

    NASA Astrophysics Data System (ADS)

    Vannitsem, S.; Van Schaeybroeck, B.

    2014-12-01

    The use of ensemble prediction systems allows for an uncertainty estimation of the forecast. Most end users do not require all the information contained in an ensemble and prefer the use of a single uncertainty measure. This measure is the ensemble spread which serves to forecast the forecast error. It is however unclear how best the quality of these forecasts can be performed, based on spread and forecast error only. The spread-error verification is intricate for two reasons: First for each probabilistic forecast only one observation is substantiated and second, the spread is not meant to provide an exact prediction for the error. Despite these facts several advances were recently made, all based on traditional deterministic verification of the error forecast. In particular, Grimit and Mass (2007) and Hopson (2014) considered in detail the strengths and weaknesses of the spread-error correlation, while Christensen et al (2014) developed a proper-score extension of the mean squared error. However, due to the strong variance of the error given a certain spread, the error forecast should be preferably considered as probabilistic in nature. In the present work, different probabilistic error models are proposed depending on the spread-error metrics used. Most of these models allow for the discrimination of a perfect forecast from an imperfect one, independent of the underlying ensemble distribution. The new spread-error scores are tested on the ensemble prediction system of the European Centre of Medium-range forecasts (ECMWF) over Europe and Africa. ReferencesChristensen, H. M., Moroz, I. M. and Palmer, T. N., 2014, Evaluation of ensemble forecast uncertainty using a new proper score: application to medium-range and seasonal forecasts. In press, Quarterly Journal of the Royal Meteorological Society. Grimit, E. P., and C. F. Mass, 2007: Measuring the ensemble spread-error relationship with a probabilistic approach: Stochastic ensemble results. Mon. Wea. Rev., 135, 203

  17. Representing rainfall uncertainties using radar ensembles: generation of radar based rainfall ensembles for QPE and QPF

    NASA Astrophysics Data System (ADS)

    Sempere-Torres, D.; Llort, X.; Roca, J.; Pegram, G.

    2009-04-01

    In the last years, new comprehension of the physics underlying the radar measurements as well as new technological advancements have allowed radar community to propose better algorithms and methodologies and significant advancements have been achieved in improving Quantitative Precipitation Estimates (QPE) and Quantitative Precipitation forecasting (QPF) by radar. Thus the study of the 2D uncertainties field associated to these estimates has become an important subject, specially to enhance the use of radar QPE and QPF in hydrological studies, as well as in providing a reference for satellite precipitations measurements. In this context the use of radar-based rainfall ensembles (i.e. equiprobable rainfall field scenarios generated to be compatible with the observations/forecasts and with the inferred structure of the uncertainties) has been seen as an extremely interesting tool to represent their associated uncertainties. The generation of such radar ensembles requires first the full characterization of the 3D field of associated uncertainties (2D spatial plus temporal), since rainfall estimates show an error structure highly correlated in space and time. A full methodology to deal with this kind of radar-based rainfall ensembles is presented. Given a rainfall event, the 2D uncertainty fields associated to the radar estimates are defined for every time step using a benchmark, or reference field, based on the best available estimate of the rainfall field. This benchmark is built using an advanced non parametric interpolation of a dense raingauge network able to use the spatial structure provided by the radar observations, and is confined to the region in which this combination could be taken as a reference measurement (Velasco-Forero et al. 2008, doi:10.1016/j.advwatres.2008.10.004). Then the spatial and temporal structures of these uncertainty fields are characterized and a methodology to generate consistent multiple realisations of them is used to generate the

  18. A Link-Based Approach to the Cluster Ensemble Problem.

    PubMed

    Iam-On, Natthakan; Boongoen, Tossapon; Garrett, Simon; Price, Chris

    2011-12-01

    Cluster ensembles have recently emerged as a powerful alternative to standard cluster analysis, aggregating several input data clusterings to generate a single output clustering, with improved robustness and stability. From the early work, these techniques held great promise; however, most of them generate the final solution based on incomplete information of a cluster ensemble. The underlying ensemble-information matrix reflects only cluster-data point relations, while those among clusters are generally overlooked. This paper presents a new link-based approach to improve the conventional matrix. It achieves this using the similarity between clusters that are estimated from a link network model of the ensemble. In particular, three new link-based algorithms are proposed for the underlying similarity assessment. The final clustering result is generated from the refined matrix using two different consensus functions of feature-based and graph-based partitioning. This approach is the first to address and explicitly employ the relationship between input partitions, which has not been emphasized by recent studies of matrix refinement. The effectiveness of the link-based approach is empirically demonstrated over 10 data sets (synthetic and real) and three benchmark evaluation measures. The results suggest the new approach is able to efficiently extract information embedded in the input clusterings, and regularly illustrate higher clustering quality in comparison to several state-of-the-art techniques.

  19. Sampling-based ensemble segmentation against inter-operator variability

    NASA Astrophysics Data System (ADS)

    Huo, Jing; Okada, Kazunori; Pope, Whitney; Brown, Matthew

    2011-03-01

    Inconsistency and a lack of reproducibility are commonly associated with semi-automated segmentation methods. In this study, we developed an ensemble approach to improve reproducibility and applied it to glioblastoma multiforme (GBM) brain tumor segmentation on T1-weigted contrast enhanced MR volumes. The proposed approach combines samplingbased simulations and ensemble segmentation into a single framework; it generates a set of segmentations by perturbing user initialization and user-specified internal parameters, then fuses the set of segmentations into a single consensus result. Three combination algorithms were applied: majority voting, averaging and expectation-maximization (EM). The reproducibility of the proposed framework was evaluated by a controlled experiment on 16 tumor cases from a multicenter drug trial. The ensemble framework had significantly better reproducibility than the individual base Otsu thresholding method (p<.001).

  20. A method of determining RNA conformational ensembles using structure-based calculations of residual dipolar couplings

    NASA Astrophysics Data System (ADS)

    Borkar, Aditi N.; De Simone, Alfonso; Montalvao, Rinaldo W.; Vendruscolo, Michele

    2013-06-01

    We describe a method of determining the conformational fluctuations of RNA based on the incorporation of nuclear magnetic resonance (NMR) residual dipolar couplings (RDCs) as replica-averaged structural restraints in molecular dynamics simulations. In this approach, the alignment tensor required to calculate the RDCs corresponding to a given conformation is estimated from its shape, and multiple replicas of the RNA molecule are simulated simultaneously to reproduce in silico the ensemble-averaging procedure performed in the NMR measurements. We provide initial evidence that with this approach it is possible to determine accurately structural ensembles representing the conformational fluctuations of RNA by applying the reference ensemble test to the trans-activation response element of the human immunodeficiency virus type 1.

  1. Wang-Landau Reaction Ensemble Method: Simulation of Weak Polyelectrolytes and General Acid-Base Reactions.

    PubMed

    Landsgesell, Jonas; Holm, Christian; Smiatek, Jens

    2017-02-14

    We present a novel method for the study of weak polyelectrolytes and general acid-base reactions in molecular dynamics and Monte Carlo simulations. The approach combines the advantages of the reaction ensemble and the Wang-Landau sampling method. Deprotonation and protonation reactions are simulated explicitly with the help of the reaction ensemble method, while the accurate sampling of the corresponding phase space is achieved by the Wang-Landau approach. The combination of both techniques provides a sufficient statistical accuracy such that meaningful estimates for the density of states and the partition sum can be obtained. With regard to these estimates, several thermodynamic observables like the heat capacity or reaction free energies can be calculated. We demonstrate that the computation times for the calculation of titration curves with a high statistical accuracy can be significantly decreased when compared to the original reaction ensemble method. The applicability of our approach is validated by the study of weak polyelectrolytes and their thermodynamic properties.

  2. Bayesian Energy Landscape Tilting: Towards Concordant Models of Molecular Ensembles

    PubMed Central

    Beauchamp, Kyle A.; Pande, Vijay S.; Das, Rhiju

    2014-01-01

    Predicting biological structure has remained challenging for systems such as disordered proteins that take on myriad conformations. Hybrid simulation/experiment strategies have been undermined by difficulties in evaluating errors from computational model inaccuracies and data uncertainties. Building on recent proposals from maximum entropy theory and nonequilibrium thermodynamics, we address these issues through a Bayesian energy landscape tilting (BELT) scheme for computing Bayesian hyperensembles over conformational ensembles. BELT uses Markov chain Monte Carlo to directly sample maximum-entropy conformational ensembles consistent with a set of input experimental observables. To test this framework, we apply BELT to model trialanine, starting from disagreeing simulations with the force fields ff96, ff99, ff99sbnmr-ildn, CHARMM27, and OPLS-AA. BELT incorporation of limited chemical shift and 3J measurements gives convergent values of the peptide’s α, β, and PPII conformational populations in all cases. As a test of predictive power, all five BELT hyperensembles recover set-aside measurements not used in the fitting and report accurate errors, even when starting from highly inaccurate simulations. BELT’s principled framework thus enables practical predictions for complex biomolecular systems from discordant simulations and sparse data. PMID:24655513

  3. Sequential ensemble-based optimal design for parameter estimation

    NASA Astrophysics Data System (ADS)

    Man, Jun; Zhang, Jiangjiang; Li, Weixuan; Zeng, Lingzao; Wu, Laosheng

    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.

  4. Current path in light emitting diodes based on nanowire ensembles.

    PubMed

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

    2012-11-23

    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.

  5. Knowledge-Based Methods To Train and Optimize Virtual Screening Ensembles

    PubMed Central

    2016-01-01

    Ensemble docking can be a successful virtual screening technique that addresses the innate conformational heterogeneity of macromolecular drug targets. Yet, lacking a method to identify a subset of conformational states that effectively segregates active and inactive small molecules, ensemble docking may result in the recommendation of a large number of false positives. Here, three knowledge-based methods that construct structural ensembles for virtual screening are presented. Each method selects ensembles by optimizing an objective function calculated using the receiver operating characteristic (ROC) curve: either the area under the ROC curve (AUC) or a ROC enrichment factor (EF). As the number of receptor conformations, N, becomes large, the methods differ in their asymptotic scaling. Given a set of small molecules with known activities and a collection of target conformations, the most resource intense method is guaranteed to find the optimal ensemble but scales as O(2N). A recursive approximation to the optimal solution scales as O(N2), and a more severe approximation leads to a faster method that scales linearly, O(N). The techniques are generally applicable to any system, and we demonstrate their effectiveness on the androgen nuclear hormone receptor (AR), cyclin-dependent kinase 2 (CDK2), and the peroxisome proliferator-activated receptor δ (PPAR-δ) drug targets. Conformations that consisted of a crystal structure and molecular dynamics simulation cluster centroids were used to form AR and CDK2 ensembles. Multiple available crystal structures were used to form PPAR-δ ensembles. For each target, we show that the three methods perform similarly to one another on both the training and test sets. PMID:27097522

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

    PubMed

    Filatov, Michael

    2016-01-01

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

  7. Muscle activation described with a differential equation model for large ensembles of locally coupled molecular motors.

    PubMed

    Walcott, Sam

    2014-10-01

    Molecular motors, by turning chemical energy into mechanical work, are responsible for active cellular processes. Often groups of these motors work together to perform their biological role. Motors in an ensemble are coupled and exhibit complex emergent behavior. Although large motor ensembles can be modeled with partial differential equations (PDEs) by assuming that molecules function independently of their neighbors, this assumption is violated when motors are coupled locally. It is therefore unclear how to describe the ensemble behavior of the locally coupled motors responsible for biological processes such as calcium-dependent skeletal muscle activation. Here we develop a theory to describe locally coupled motor ensembles and apply the theory to skeletal muscle activation. The central idea is that a muscle filament can be divided into two phases: an active and an inactive phase. Dynamic changes in the relative size of these phases are described by a set of linear ordinary differential equations (ODEs). As the dynamics of the active phase are described by PDEs, muscle activation is governed by a set of coupled ODEs and PDEs, building on previous PDE models. With comparison to Monte Carlo simulations, we demonstrate that the theory captures the behavior of locally coupled ensembles. The theory also plausibly describes and predicts muscle experiments from molecular to whole muscle scales, suggesting that a micro- to macroscale muscle model is within reach.

  8. Stochastic dynamics of small ensembles of non-processive molecular motors: the parallel cluster model.

    PubMed

    Erdmann, Thorsten; Albert, Philipp J; Schwarz, Ulrich S

    2013-11-07

    Non-processive molecular motors have to work together in ensembles in order to generate appreciable levels of force or movement. In skeletal muscle, for example, hundreds of myosin II molecules cooperate in thick filaments. In non-muscle cells, by contrast, small groups with few tens of non-muscle myosin II motors contribute to essential cellular processes such as transport, shape changes, or mechanosensing. Here we introduce a detailed and analytically tractable model for this important situation. Using a three-state crossbridge model for the myosin II motor cycle and exploiting the assumptions of fast power stroke kinetics and equal load sharing between motors in equivalent states, we reduce the stochastic reaction network to a one-step master equation for the binding and unbinding dynamics (parallel cluster model) and derive the rules for ensemble movement. We find that for constant external load, ensemble dynamics is strongly shaped by the catch bond character of myosin II, which leads to an increase of the fraction of bound motors under load and thus to firm attachment even for small ensembles. This adaptation to load results in a concave force-velocity relation described by a Hill relation. For external load provided by a linear spring, myosin II ensembles dynamically adjust themselves towards an isometric state with constant average position and load. The dynamics of the ensembles is now determined mainly by the distribution of motors over the different kinds of bound states. For increasing stiffness of the external spring, there is a sharp transition beyond which myosin II can no longer perform the power stroke. Slow unbinding from the pre-power-stroke state protects the ensembles against detachment.

  9. Stochastic dynamics of small ensembles of non-processive molecular motors: The parallel cluster model

    SciTech Connect

    Erdmann, Thorsten; Albert, Philipp J.; Schwarz, Ulrich S.

    2013-11-07

    Non-processive molecular motors have to work together in ensembles in order to generate appreciable levels of force or movement. In skeletal muscle, for example, hundreds of myosin II molecules cooperate in thick filaments. In non-muscle cells, by contrast, small groups with few tens of non-muscle myosin II motors contribute to essential cellular processes such as transport, shape changes, or mechanosensing. Here we introduce a detailed and analytically tractable model for this important situation. Using a three-state crossbridge model for the myosin II motor cycle and exploiting the assumptions of fast power stroke kinetics and equal load sharing between motors in equivalent states, we reduce the stochastic reaction network to a one-step master equation for the binding and unbinding dynamics (parallel cluster model) and derive the rules for ensemble movement. We find that for constant external load, ensemble dynamics is strongly shaped by the catch bond character of myosin II, which leads to an increase of the fraction of bound motors under load and thus to firm attachment even for small ensembles. This adaptation to load results in a concave force-velocity relation described by a Hill relation. For external load provided by a linear spring, myosin II ensembles dynamically adjust themselves towards an isometric state with constant average position and load. The dynamics of the ensembles is now determined mainly by the distribution of motors over the different kinds of bound states. For increasing stiffness of the external spring, there is a sharp transition beyond which myosin II can no longer perform the power stroke. Slow unbinding from the pre-power-stroke state protects the ensembles against detachment.

  10. Ensemble-Based Assimilation of Aerosol Observations in GEOS-5

    NASA Technical Reports Server (NTRS)

    Buchard, V.; Da Silva, A.

    2016-01-01

    MERRA-2 is the latest Aerosol Reanalysis produced at NASA's Global Modeling Assimilation Office (GMAO) from 1979 to present. This reanalysis is based on a version of the GEOS-5 model radiatively coupled to GOCART aerosols and includes assimilation of bias corrected Aerosol Optical Depth (AOD) from AVHRR over ocean, MODIS sensors on both Terra and Aqua satellites, MISR over bright surfaces and AERONET data. In order to assimilate lidar profiles of aerosols, we are updating the aerosol component of our assimilation system to an Ensemble Kalman Filter (EnKF) type of scheme using ensembles generated routinely by the meteorological assimilation. Following the work performed with the first NASA's aerosol reanalysis (MERRAero), we first validate the vertical structure of MERRA-2 aerosol assimilated fields using CALIOP data over regions of particular interest during 2008.

  11. Ensemble polarimetric SAR image classification based on contextual sparse representation

    NASA Astrophysics Data System (ADS)

    Zhang, Lamei; Wang, Xiao; Zou, Bin; Qiao, Zhijun

    2016-05-01

    Polarimetric SAR image interpretation has become one of the most interesting topics, in which the construction of the reasonable and effective technique of image classification is of key importance. Sparse representation represents the data using the most succinct sparse atoms of the over-complete dictionary and the advantages of sparse representation also have been confirmed in the field of PolSAR classification. However, it is not perfect, like the ordinary classifier, at different aspects. So ensemble learning is introduced to improve the issue, which makes a plurality of different learners training and obtained the integrated results by combining the individual learner to get more accurate and ideal learning results. Therefore, this paper presents a polarimetric SAR image classification method based on the ensemble learning of sparse representation to achieve the optimal classification.

  12. Protonation states and conformational ensemble in ligand-based QSAR modeling.

    PubMed

    De Benedetti, Pier G

    2013-01-01

    Drug affinity and function depend on the different protonation species (present in the biological context) that generate different conformational ensembles with different structural features and, hence, different physico-chemical properties. In the present review article these strongly interdependent structural features will be considered for their crucial role in ligand-based QSAR modeling and drug design by using quantum chemical electronic/reactivity descriptors and molecular shape description. Some selected and relevant examples illustrate the role of these molecular descriptors, computed on the bioactive protonation states and conformers, as determinant factors in mechanistic/causative QSAR analysis.

  13. 2010 oil spill: trajectory projections based on ensemble drifter analyses

    NASA Astrophysics Data System (ADS)

    Chang, Yu-Lin; Oey, Leo; Xu, Fang-Hua; Lu, Hung-Fu; Fujisaki, Ayumi

    2011-06-01

    An accurate method for long-term (weeks to months) projections of oil spill trajectories based on multi-year ensemble analyses of simulated surface and subsurface ( z = -800 m) drifters released at the northern Gulf of Mexico spill site is demonstrated during the 2010 oil spill. The simulation compares well with satellite images of the actual oil spill which show that the surface spread of oil was mainly confined to the northern shelf and slope of the Gulf of Mexico, with some (more limited) spreading over the north/northeastern face of the Loop Current, as well as northwestward toward the Louisiana-Texas shelf. At subsurface, the ensemble projection shows drifters spreading south/southwestward, and this tendency agrees well with ADCP current measurements near the spill site during the months of May-July, which also show southward mean currents. An additional model analysis during the spill period (Apr-Jul/2010) confirms the above ensemble projection. The 2010 analysis confirms that the reason for the surface oil spread to be predominantly confined to the northern Gulf shelf and slope is because the 2010 wind was more southerly compared to climatology and also because a cyclone existed north of the Loop Current which moreover was positioned to the south of the spilled site.

  14. Assessing an ensemble docking-based virtual screening strategy for kinase targets by considering protein flexibility.

    PubMed

    Tian, Sheng; Sun, Huiyong; Pan, Peichen; Li, Dan; Zhen, Xuechu; Li, Youyong; Hou, Tingjun

    2014-10-27

    In this study, to accommodate receptor flexibility, based on multiple receptor conformations, a novel ensemble docking protocol was developed by using the naïve Bayesian classification technique, and it was evaluated in terms of the prediction accuracy of docking-based virtual screening (VS) of three important targets in the kinase family: ALK, CDK2, and VEGFR2. First, for each target, the representative crystal structures were selected by structural clustering, and the capability of molecular docking based on each representative structure to discriminate inhibitors from non-inhibitors was examined. Then, for each target, 50 ns molecular dynamics (MD) simulations were carried out to generate an ensemble of the conformations, and multiple representative structures/snapshots were extracted from each MD trajectory by structural clustering. On average, the representative crystal structures outperform the representative structures extracted from MD simulations in terms of the capabilities to separate inhibitors from non-inhibitors. Finally, by using the naïve Bayesian classification technique, an integrated VS strategy was developed to combine the prediction results of molecular docking based on different representative conformations chosen from crystal structures and MD trajectories. It was encouraging to observe that the integrated VS strategy yields better performance than the docking-based VS based on any single rigid conformation. This novel protocol may provide an improvement over existing strategies to search for more diverse and promising active compounds for a target of interest.

  15. Ensemble-based docking: From hit discovery to metabolism and toxicity predictions

    SciTech Connect

    Evangelista, Wilfredo; Weir, Rebecca; Ellingson, Sally; Harris, Jason B.; Kapoor, Karan; Smith, Jeremy C.; Baudry, Jerome

    2016-07-29

    The use of ensemble-based docking for the exploration of biochemical pathways and toxicity prediction of drug candidates is described. We describe the computational engineering work necessary to enable large ensemble docking campaigns on supercomputers. We show examples where ensemble-based docking has significantly increased the number and the diversity of validated drug candidates. Finally, we illustrate how ensemble-based docking can be extended beyond hit discovery and toward providing a structural basis for the prediction of metabolism and off-target binding relevant to pre-clinical and clinical trials.

  16. Quantum repeaters based on atomic ensembles and linear optics

    NASA Astrophysics Data System (ADS)

    Sangouard, Nicolas; Simon, Christoph; de Riedmatten, Hugues; Gisin, Nicolas

    2011-01-01

    The distribution of quantum states over long distances is limited by photon loss. Straightforward amplification as in classical telecommunications is not an option in quantum communication because of the no-cloning theorem. This problem could be overcome by implementing quantum repeater protocols, which create long-distance entanglement from shorter-distance entanglement via entanglement swapping. Such protocols require the capacity to create entanglement in a heralded fashion, to store it in quantum memories, and to swap it. One attractive general strategy for realizing quantum repeaters is based on the use of atomic ensembles as quantum memories, in combination with linear optical techniques and photon counting to perform all required operations. Here the theoretical and experimental status quo of this very active field are reviewed. The potentials of different approaches are compared quantitatively, with a focus on the most immediate goal of outperforming the direct transmission of photons.

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

    PubMed

    Parton, Daniel L; Grinaway, Patrick B; Hanson, Sonya M; Beauchamp, Kyle A; Chodera, John D

    2016-06-01

    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 (super)families, 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 tyrosine kinase

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

    PubMed Central

    Parton, Daniel L.; Grinaway, Patrick B.; Hanson, Sonya M.; Beauchamp, Kyle A.; Chodera, John D.

    2016-01-01

    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 (super)families, 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 tyrosine

  19. A Sidekick for Membrane Simulations: Automated Ensemble Molecular Dynamics Simulations of Transmembrane Helices

    PubMed Central

    Hall, Benjamin A; Halim, Khairul Abd; Buyan, Amanda; Emmanouil, Beatrice; Sansom, Mark S P

    2016-01-01

    The interactions of transmembrane (TM) α-helices with the phospholipid membrane and with one another are central to understanding the structure and stability of integral membrane proteins. These interactions may be analysed via coarse-grained molecular dynamics (CGMD) simulations. To obtain statistically meaningful analysis of TM helix interactions, large (N ca. 100) ensembles of CGMD simulations are needed. To facilitate the running and analysis of such ensembles of simulations we have developed Sidekick, an automated pipeline software for performing high throughput CGMD simulations of α-helical peptides in lipid bilayer membranes. Through an end-to-end approach, which takes as input a helix sequence and outputs analytical metrics derived from CGMD simulations, we are able to predict the orientation and likelihood of insertion into a lipid bilayer of a given helix of family of helix sequences. We illustrate this software via analysis of insertion into a membrane of short hydrophobic TM helices containing a single cationic arginine residue positioned at different positions along the length of the helix. From analysis of these ensembles of simulations we estimate apparent energy barriers to insertion which are comparable to experimentally determined values. In a second application we use CGMD simulations to examine self-assembly of dimers of TM helices from the ErbB1 receptor tyrosine kinase, and analyse the numbers of simulation repeats necessary to obtain convergence of simple descriptors of the mode of packing of the two helices within a dimer. Our approach offers proof-of-principle platform for the further employment of automation in large ensemble CGMD simulations of membrane proteins. PMID:26580541

  20. Development of Ensemble Model Based Water Demand Forecasting Model

    NASA Astrophysics Data System (ADS)

    Kwon, Hyun-Han; So, Byung-Jin; Kim, Seong-Hyeon; Kim, Byung-Seop

    2014-05-01

    In recent years, Smart Water Grid (SWG) concept has globally emerged over the last decade and also gained significant recognition in South Korea. Especially, there has been growing interest in water demand forecast and optimal pump operation and this has led to various studies regarding energy saving and improvement of water supply reliability. Existing water demand forecasting models are categorized into two groups in view of modeling and predicting their behavior in time series. One is to consider embedded patterns such as seasonality, periodicity and trends, and the other one is an autoregressive model that is using short memory Markovian processes (Emmanuel et al., 2012). The main disadvantage of the abovementioned model is that there is a limit to predictability of water demands of about sub-daily scale because the system is nonlinear. In this regard, this study aims to develop a nonlinear ensemble model for hourly water demand forecasting which allow us to estimate uncertainties across different model classes. The proposed model is consist of two parts. One is a multi-model scheme that is based on combination of independent prediction model. The other one is a cross validation scheme named Bagging approach introduced by Brieman (1996) to derive weighting factors corresponding to individual models. Individual forecasting models that used in this study are linear regression analysis model, polynomial regression, multivariate adaptive regression splines(MARS), SVM(support vector machine). The concepts are demonstrated through application to observed from water plant at several locations in the South Korea. Keywords: water demand, non-linear model, the ensemble forecasting model, uncertainty. Acknowledgements This subject is supported by Korea Ministry of Environment as "Projects for Developing Eco-Innovation Technologies (GT-11-G-02-001-6)

  1. Random Coding Bounds for DNA Codes Based on Fibonacci Ensembles of DNA Sequences

    DTIC Science & Technology

    2008-07-01

    COVERED (From - To) 6 Jul 08 – 11 Jul 08 4. TITLE AND SUBTITLE RANDOM CODING BOUNDS FOR DNA CODES BASED ON FIBONACCI ENSEMBLES OF DNA SEQUENCES ... sequences which are generalizations of the Fibonacci sequences . 15. SUBJECT TERMS DNA Codes, Fibonacci Ensembles, DNA Computing, Code Optimization 16...coding bound on the rate of DNA codes is proved. To obtain the bound, we use some ensembles of DNA sequences which are generalizations of the Fibonacci

  2. Leveraging Gibbs Ensemble Molecular Dynamics and Hybrid Monte Carlo/Molecular Dynamics for Efficient Study of Phase Equilibria.

    PubMed

    Gartner, Thomas E; Epps, Thomas H; Jayaraman, Arthi

    2016-11-08

    We describe an extension of the Gibbs ensemble molecular dynamics (GEMD) method for studying phase equilibria. Our modifications to GEMD allow for direct control over particle transfer between phases and improve the method's numerical stability. Additionally, we found that the modified GEMD approach had advantages in computational efficiency in comparison to a hybrid Monte Carlo (MC)/MD Gibbs ensemble scheme in the context of the single component Lennard-Jones fluid. We note that this increase in computational efficiency does not compromise the close agreement of phase equilibrium results between the two methods. However, numerical instabilities in the GEMD scheme hamper GEMD's use near the critical point. We propose that the computationally efficient GEMD simulations can be used to map out the majority of the phase window, with hybrid MC/MD used as a follow up for conditions under which GEMD may be unstable (e.g., near-critical behavior). In this manner, we can capitalize on the contrasting strengths of these two methods to enable the efficient study of phase equilibria for systems that present challenges for a purely stochastic GEMC method, such as dense or low temperature systems, and/or those with complex molecular topologies.

  3. Ensemble Classifier Strategy Based on Transient Feature Fusion in Electronic Nose

    NASA Astrophysics Data System (ADS)

    Bagheri, Mohammad Ali; Montazer, Gholam Ali

    2011-09-01

    In this paper, we test the performance of several ensembles of classifiers and each base learner has been trained on different types of extracted features. Experimental results show the potential benefits introduced by the usage of simple ensemble classification systems for the integration of different types of transient features.

  4. Molecular dynamics in the isothermal-isobaric ensemble: the requirement of a "shell" molecule. III. Discontinuous potentials.

    PubMed

    Uline, Mark J; Corti, David S

    2008-07-07

    Based on the approach of Gruhn and Monson [Phys. Rev. E 63, 061106 (2001)], we present a new method for deriving the collisions dynamics for particles that interact via discontinuous potentials. By invoking the conservation of the extended Hamiltonian, we generate molecular dynamics (MD) algorithms for simulating the hard-sphere and square-well fluids within the isothermal-isobaric (NpT) ensemble. Consistent with the recent rigorous reformulation of the NpT ensemble partition function, the equations of motion impose a constant external pressure via the introduction of a shell particle of known mass [M. J. Uline and D. S. Corti, J. Chem. Phys. 123, 164101 (2005); 123, 164102 (2005)], which serves to define uniquely the volume of the system. The particles are also connected to a temperature reservoir through the use of a chain of Nose-Hoover thermostats, the properties of which are not affected by a hard-sphere or square-well collision. By using the Liouville operator formalism and the Trotter expansion theorem to integrate the equations of motion, the update of the thermostat variables can be decoupled from the update of the positions of the particles and the momentum changes upon a collision. Hence, once the appropriate collision dynamics for the isobaric-isenthalpic (NpH) equations of motion is known, the adaptation of the algorithm to the NpT ensemble is straightforward. Results of MD simulations for the pure component square-well fluid are presented and serve to validate our algorithm. Finally, since the mass of the shell particle is known, the system itself, and not a piston of arbitrary mass, controls the time scales for internal pressure and volume fluctuations. We therefore consider the influence of the shell particle algorithm on the dynamics of the square-well fluid.

  5. g_contacts: Fast contact search in bio-molecular ensemble data

    NASA Astrophysics Data System (ADS)

    Blau, Christian; Grubmuller, Helmut

    2013-12-01

    Short-range interatomic interactions govern many bio-molecular processes. Therefore, identifying close interaction partners in ensemble data is an essential task in structural biology and computational biophysics. A contact search can be cast as a typical range search problem for which efficient algorithms have been developed. However, none of those has yet been adapted to the context of macromolecular ensembles, particularly in a molecular dynamics (MD) framework. Here a set-decomposition algorithm is implemented which detects all contacting atoms or residues in maximum O(Nlog(N)) run-time, in contrast to the O(N2) complexity of a brute-force approach. Catalogue identifier: AEQA_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEQA_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 8945 No. of bytes in distributed program, including test data, etc.: 981604 Distribution format: tar.gz Programming language: C99. Computer: PC. Operating system: Linux. RAM: ≈Size of input frame Classification: 3, 4.14. External routines: Gromacs 4.6[1] Nature of problem: Finding atoms or residues that are closer to one another than a given cut-off. Solution method: Excluding distant atoms from distance calculations by decomposing the given set of atoms into disjoint subsets. Running time:≤O(Nlog(N)) References: [1] S. Pronk, S. Pall, R. Schulz, P. Larsson, P. Bjelkmar, R. Apostolov, M. R. Shirts, J.C. Smith, P. M. Kasson, D. van der Spoel, B. Hess and Erik Lindahl, Gromacs 4.5: a high-throughput and highly parallel open source molecular simulation toolkit, Bioinformatics 29 (7) (2013).

  6. Confidence-based ensemble for GBM brain tumor segmentation

    NASA Astrophysics Data System (ADS)

    Huo, Jing; van Rikxoort, Eva M.; Okada, Kazunori; Kim, Hyun J.; Pope, Whitney; Goldin, Jonathan; Brown, Matthew

    2011-03-01

    It is a challenging task to automatically segment glioblastoma multiforme (GBM) brain tumors on T1w post-contrast isotropic MR images. A semi-automated system using fuzzy connectedness has recently been developed for computing the tumor volume that reduces the cost of manual annotation. In this study, we propose a an ensemble method that combines multiple segmentation results into a final ensemble one. The method is evaluated on a dataset of 20 cases from a multi-center pharmaceutical drug trial and compared to the fuzzy connectedness method. Three individual methods were used in the framework: fuzzy connectedness, GrowCut, and voxel classification. The combination method is a confidence map averaging (CMA) method. The CMA method shows an improved ROC curve compared to the fuzzy connectedness method (p < 0.001). The CMA ensemble result is more robust compared to the three individual methods.

  7. Molecular Dynamics and Monte Carlo simulations in the microcanonical ensemble: Quantitative comparison and reweighting techniques.

    PubMed

    Schierz, Philipp; Zierenberg, Johannes; Janke, Wolfhard

    2015-10-07

    Molecular Dynamics (MD) and Monte Carlo (MC) simulations are the most popular simulation techniques for many-particle systems. Although they are often applied to similar systems, it is unclear to which extent one has to expect quantitative agreement of the two simulation techniques. In this work, we present a quantitative comparison of MD and MC simulations in the microcanonical ensemble. For three test examples, we study first- and second-order phase transitions with a focus on liquid-gas like transitions. We present MD analysis techniques to compensate for conservation law effects due to linear and angular momentum conservation. Additionally, we apply the weighted histogram analysis method to microcanonical histograms reweighted from MD simulations. By this means, we are able to estimate the density of states from many microcanonical simulations at various total energies. This further allows us to compute estimates of canonical expectation values.

  8. Nonlinear stability and ergodicity of ensemble based Kalman filters

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

    The ensemble Kalman filter (EnKF) and ensemble square root filter (ESRF) are data assimilation methods used to combine high dimensional, nonlinear dynamical models with observed data. Despite their widespread usage in climate science and oil reservoir simulation, very little is known about the long-time behavior of these methods and why they are effective when applied with modest ensemble sizes in large dimensional turbulent dynamical systems. By following the basic principles of energy dissipation and controllability of filters, this paper establishes a simple, systematic and rigorous framework for the nonlinear analysis of EnKF and ESRF with arbitrary ensemble size, focusing on the dynamical properties of boundedness and geometric ergodicity. The time uniform boundedness guarantees that the filter estimate will not diverge to machine infinity in finite time, which is a potential threat for EnKF and ESQF known as the catastrophic filter divergence. Geometric ergodicity ensures in addition that the filter has a unique invariant measure and that initialization errors will dissipate exponentially in time. We establish these results by introducing a natural notion of observable energy dissipation. The time uniform bound is achieved through a simple Lyapunov function argument, this result applies to systems with complete observations and strong kinetic energy dissipation, but also to concrete examples with incomplete observations. With the Lyapunov function argument established, the geometric ergodicity is obtained by verifying the controllability of the filter processes; in particular, such analysis for ESQF relies on a careful multivariate perturbation analysis of the covariance eigen-structure.

  9. Possible Room-Temperature Ferromagnetism in Self-Assembled Ensembles of Paramagnetic and Diamagnetic Molecular Semiconductors.

    PubMed

    Dhara, Barun; Tarafder, Kartick; Jha, Plawan K; Panja, Soumendra N; Nair, Sunil; Oppeneer, Peter M; Ballav, Nirmalya

    2016-12-15

    Owing to long spin-relaxation time and chemically customizable physical properties, molecule-based semiconductor materials like metal-phthalocyanines offer promising alternatives to conventional dilute magnetic semiconductors/oxides (DMSs/DMOs) to achieve room-temperature (RT) ferromagnetism. However, air-stable molecule-based materials exhibiting both semiconductivity and magnetic-order at RT have so far remained elusive. We present here the concept of supramolecular arrangement to accomplish possibly RT ferromagnetism. Specifically, we observe a clear hysteresis-loop (Hc ≈ 120 Oe) at 300 K in the magnetization versus field (M-H) plot of the self-assembled ensembles of diamagnetic Zn-phthalocyanine having peripheral F atoms (ZnFPc; S = 0) and paramagnetic Fe-phthalocyanine having peripehral H atoms (FePc; S = 1). Tauc plot of the self-assembled FePc···ZnFPc ensembles showed an optical band gap of ∼1.05 eV and temperature-dependent current-voltage (I-V) studies suggest semiconducting characteristics in the material. Using DFT+U quantum-chemical calculations, we reveal the origin of such unusual ferromagnetic exchange-interaction in the supramolecular FePc···ZnFPc system.

  10. Monte Carlo and Molecular Dynamics in the Multicanonical Ensemble: Connections between Wang-Landau Sampling and Metadynamics

    NASA Astrophysics Data System (ADS)

    Vogel, Thomas; Perez, Danny; Junghans, Christoph

    2014-03-01

    We show direct formal relationships between the Wang-Landau iteration [PRL 86, 2050 (2001)], metadynamics [PNAS 99, 12562 (2002)] and statistical temperature molecular dynamics [PRL 97, 050601 (2006)], the major Monte Carlo and molecular dynamics work horses for sampling from a generalized, multicanonical ensemble. We aim at helping to consolidate the developments in the different areas by indicating how methodological advancements can be transferred in a straightforward way, avoiding the parallel, largely independent, developments tracks observed in the past.

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

    PubMed Central

    Simidjievski, Nikola; Todorovski, Ljupčo; Džeroski, Sašo

    2016-01-01

    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. PMID:27078633

  12. Dynamic Metabolic Model Building Based on the Ensemble Modeling Approach

    SciTech Connect

    Liao, James C.

    2016-10-01

    Ensemble modeling of kinetic systems addresses the challenges of kinetic model construction, with respect to parameter value selection, and still allows for the rich insights possible from kinetic models. This project aimed to show that constructing, implementing, and analyzing such models is a useful tool for the metabolic engineering toolkit, and that they can result in actionable insights from models. Key concepts are developed and deliverable publications and results are presented.

  13. Initial perturbations based on the ensemble transform (ET) technique in the NCEP global operational forecast system

    NASA Astrophysics Data System (ADS)

    Wei, Mozheng; Toth, Zoltan; Wobus, Richard; Zhu, Yuejian

    2008-01-01

    Since modern data assimilation (DA) involves the repetitive use of dynamical forecasts, errors in analyses share characteristics of those in short-range forecasts. Initial conditions for an ensemble prediction/forecast system (EPS or EFS) are expected to sample uncertainty in the analysis field. Ensemble forecasts with such initial conditions can therefore (a) be fed back to DA to reduce analysis uncertainty, as well as (b) sample forecast uncertainty related to initial conditions. Optimum performance of both DA and EFS requires a careful choice of initial ensemble perturbations. DA can be improved with an EFS that represents the dynamically conditioned part of forecast error covariance as accurately as possible, while an EFS can be improved by initial perturbations reflecting analysis error variance. Initial perturbation generation schemes that dynamically cycle ensemble perturbations reminiscent to how forecast errors are cycled in DA schemes may offer consistency between DA and EFS, and good performance for both. In this paper, we introduce an EFS based on the initial perturbations that are generated by the Ensemble Transform (ET) and ET with rescaling (ETR) methods to achieve this goal. Both ET and ETR are generalizations of the breeding method (BM). The results from ensemble systems based on BM, ET, ETR and the Ensemble Transform Kalman Filter (ETKF) method are experimentally compared in the context of ensemble forecast performance. Initial perturbations are centred around a 3D-VAR analysis, with a variance equal to that of estimated analysis errors. Of the four methods, the ETR method performed best in most probabilistic scores and in terms of the forecast error explained by the perturbations. All methods display very high time consistency between the analysis and forecast perturbations. It is expected that DA performance can be improved by the use of forecast error covariance from a dynamically cycled ensemble either with a variational DA approach (coupled

  14. An integrated uncertainty and ensemble-based data assimilation approach for improved operational streamflow predictions

    NASA Astrophysics Data System (ADS)

    He, M.; Hogue, T. S.; Margulis, S. A.; Franz, K. J.

    2012-03-01

    The current study proposes an integrated uncertainty and ensemble-based data assimilation framework (ICEA) and evaluates its viability in providing operational streamflow predictions via assimilating snow water equivalent (SWE) data. This step-wise framework applies a parameter uncertainty analysis algorithm (ISURF) to identify the uncertainty structure of sensitive model parameters, which is subsequently formulated into an Ensemble Kalman Filter (EnKF) to generate updated snow states for streamflow prediction. The framework is coupled to the US National Weather Service (NWS) snow and rainfall-runoff models. Its applicability is demonstrated for an operational basin of a western River Forecast Center (RFC) of the NWS. Performance of the framework is evaluated against existing operational baseline (RFC predictions), the stand-alone ISURF and the stand-alone EnKF. Results indicate that the ensemble-mean prediction of ICEA considerably outperforms predictions from the other three scenarios investigated, particularly in the context of predicting high flows (top 5th percentile). The ICEA streamflow ensemble predictions capture the variability of the observed streamflow well, however the ensemble is not wide enough to consistently contain the range of streamflow observations in the study basin. Our findings indicate that the ICEA has the potential to supplement the current operational (deterministic) forecasting method in terms of providing improved single-valued (e.g., ensemble mean) streamflow predictions as well as meaningful ensemble predictions.

  15. An integrated uncertainty and ensemble-based data assimilation approach for improved operational streamflow predictions

    NASA Astrophysics Data System (ADS)

    He, M.; Hogue, T. S.; Margulis, S. A.; Franz, K. J.

    2011-08-01

    The current study proposes an integrated uncertainty and ensemble-based data assimilation framework (ICEA) and evaluates its viability in providing operational streamflow predictions via assimilating snow water equivalent (SWE) data. This step-wise framework applies a parameter uncertainty analysis algorithm (ISURF) to identify the uncertainty structure of sensitive model parameters, which is subsequently formulated into an Ensemble Kalman Filter (EnKF) to generate updated snow states for streamflow prediction. The framework is coupled to the US National Weather Service (NWS) snow and rainfall-runoff models. Its applicability is demonstrated for an operational basin of a western River Forecast Center (RFC) of the NWS. Performance of the framework is evaluated against existing operational baseline (RFC predictions), the stand-alone ISURF, and the stand-alone EnKF. Results indicate that the ensemble-mean prediction of ICEA considerably outperforms predictions from the other three scenarios investigated, particularly in the context of predicting high flows (top 5th percentile). The ICEA streamflow ensemble predictions capture the variability of the observed streamflow well, however the ensemble is not wide enough to consistently contain the range of streamflow observations in the study basin. Our findings indicate that the ICEA has the potential to supplement the current operational (deterministic) forecasting method in terms of providing improved single-valued (e.g., ensemble mean) streamflow predictions as well as meaningful ensemble predictions.

  16. Force sensor based tool condition monitoring using a heterogeneous ensemble learning model.

    PubMed

    Wang, Guofeng; Yang, Yinwei; Li, Zhimeng

    2014-11-14

    Tool condition monitoring (TCM) plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM), hidden Markov model (HMM) and radius basis function (RBF) are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR) algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability.

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

    PubMed Central

    Wang, Guofeng; Yang, Yinwei; Li, Zhimeng

    2014-01-01

    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. PMID:25405514

  18. A Gibbs-ensemble based technique for Monte Carlo simulation of electric double layer capacitors (EDLC) at constant voltage.

    PubMed

    Punnathanam, Sudeep N

    2014-05-07

    Current methods for molecular simulations of Electric Double Layer Capacitors (EDLC) have both the electrodes and the electrolyte region in a single simulation box. This necessitates simulation of the electrode-electrolyte region interface. Typical capacitors have macroscopic dimensions where the fraction of the molecules at the electrode-electrolyte region interface is very low. Hence, large systems sizes are needed to minimize the electrode-electrolyte region interfacial effects. To overcome these problems, a new technique based on the Gibbs Ensemble is proposed for simulation of an EDLC. In the proposed technique, each electrode is simulated in a separate simulation box. Application of periodic boundary conditions eliminates the interfacial effects. This in addition to the use of constant voltage ensemble allows for a more convenient comparison of simulation results with experimental measurements on typical EDLCs.

  19. AWE-WQ: Fast-Forwarding Molecular Dynamics Using the Accelerated Weighted Ensemble

    PubMed Central

    2015-01-01

    A limitation of traditional molecular dynamics (MD) is that reaction rates are difficult to compute. This is due to the rarity of observing transitions between metastable states since high energy barriers trap the system in these states. Recently the weighted ensemble (WE) family of methods have emerged which can flexibly and efficiently sample conformational space without being trapped and allow calculation of unbiased rates. However, while WE can sample correctly and efficiently, a scalable implementation applicable to interesting biomolecular systems is not available. We provide here a GPLv2 implementation called AWE-WQ of a WE algorithm using the master/worker distributed computing WorkQueue (WQ) framework. AWE-WQ is scalable to thousands of nodes and supports dynamic allocation of computer resources, heterogeneous resource usage (such as central processing units (CPU) and graphical processing units (GPUs) concurrently), seamless heterogeneous cluster usage (i.e., campus grids and cloud providers), and support for arbitrary MD codes such as GROMACS, while ensuring that all statistics are unbiased. We applied AWE-WQ to a 34 residue protein which simulated 1.5 ms over 8 months with peak aggregate performance of 1000 ns/h. Comparison was done with a 200 μs simulation collected on a GPU over a similar timespan. The folding and unfolded rates were of comparable accuracy. PMID:25207854

  20. Application of ensemble classifier in EEG-based motor imagery tasks

    NASA Astrophysics Data System (ADS)

    Liu, Bianhong; Hao, Hongwei

    2007-12-01

    Electroencephalogram (EEG) recorded during motor imagery tasks can be used to move a cursor to a target on a computer screen. Such an EEG-based brain-computer interface (BCI) can provide a new communication channel for the subjects with neuromuscular disorders. To achieve higher speed and more accuracy to enhance the practical applications of BCI in computer aid medical systems, the ensemble classifier is used for the single classification. The ERDs at the electrodes C3 and C4 are calculated and then stacked together into the feature vector for the ensemble classifier. The ensemble classifier is based on Linear Discriminant Analysis (LDA) and Nearest Neighbor (NN). Furthermore, it considers the feedback. This method is successfully used in the 2003 international data analysis competition on BCI-tasks (data set III). The results show that the ensemble classifier succeed with a recognition as 90%, on average, which is 5% and 3% higher than that of using the LDA and NN separately. Moreover, the ensemble classifier outperforms LDA and NN in the whole time course. With adequate recognition, ease of use and clearly understood, the ensemble classifier can meet the need of time-requires for single classification.

  1. Overlapped partitioning for ensemble classifiers of P300-based brain-computer interfaces.

    PubMed

    Onishi, Akinari; Natsume, Kiyohisa

    2014-01-01

    A P300-based brain-computer interface (BCI) enables a wide range of people to control devices that improve their quality of life. Ensemble classifiers with naive partitioning were recently applied to the P300-based BCI and these classification performances were assessed. However, they were usually trained on a large amount of training data (e.g., 15300). In this study, we evaluated ensemble linear discriminant analysis (LDA) classifiers with a newly proposed overlapped partitioning method using 900 training data. In addition, the classification performances of the ensemble classifier with naive partitioning and a single LDA classifier were compared. One of three conditions for dimension reduction was applied: the stepwise method, principal component analysis (PCA), or none. The results show that an ensemble stepwise LDA (SWLDA) classifier with overlapped partitioning achieved a better performance than the commonly used single SWLDA classifier and an ensemble SWLDA classifier with naive partitioning. This result implies that the performance of the SWLDA is improved by overlapped partitioning and the ensemble classifier with overlapped partitioning requires less training data than that with naive partitioning. This study contributes towards reducing the required amount of training data and achieving better classification performance.

  2. Classification of lung cancer using ensemble-based feature selection and machine learning methods.

    PubMed

    Cai, Zhihua; Xu, Dong; Zhang, Qing; Zhang, Jiexia; Ngai, Sai-Ming; Shao, Jianlin

    2015-03-01

    Lung cancer is one of the leading causes of death worldwide. There are three major types of lung cancers, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) and carcinoid. NSCLC is further classified into lung adenocarcinoma (LADC), squamous cell lung cancer (SQCLC) as well as large cell lung cancer. Many previous studies demonstrated that DNA methylation has emerged as potential lung cancer-specific biomarkers. However, whether there exists a set of DNA methylation markers simultaneously distinguishing such three types of lung cancers remains elusive. In the present study, ROC (Receiving Operating Curve), RFs (Random Forests) and mRMR (Maximum Relevancy and Minimum Redundancy) were proposed to capture the unbiased, informative as well as compact molecular signatures followed by machine learning methods to classify LADC, SQCLC and SCLC. As a result, a panel of 16 DNA methylation markers exhibits an ideal classification power with an accuracy of 86.54%, 84.6% and a recall 84.37%, 85.5% in the leave-one-out cross-validation (LOOCV) and independent data set test experiments, respectively. Besides, comparison results indicate that ensemble-based feature selection methods outperform individual ones when combined with the incremental feature selection (IFS) strategy in terms of the informative and compact property of features. Taken together, results obtained suggest the effectiveness of the ensemble-based feature selection approach and the possible existence of a common panel of DNA methylation markers among such three types of lung cancer tissue, which would facilitate clinical diagnosis and treatment.

  3. Molecular dynamics simulation of configurational ensembles compatible with experimental FRET efficiency data through a restraint on instantaneous FRET efficiencies.

    PubMed

    Reif, Maria M; Oostenbrink, Chris

    2014-12-15

    Förster resonance energy transfer (FRET) measurements are widely used to investigate (bio)molecular interactions or/and association. FRET efficiencies, the primary data obtained from this method, give, in combination with the common assumption of isotropic chromophore orientation, detailed insight into the lengthscale of molecular phenomena. This study illustrates the application of a FRET efficiency restraint during classical atomistic molecular dynamics simulations of a mutant mastoparan X peptide in either water or 7 M aqueous urea. The restraint forces acting on the donor and acceptor chromophores ensure that the sampled peptide configurational ensemble satisfies the experimental primary data by modifying interchromophore separation and chromophore transition dipole moment orientations. By means of a conformational cluster analysis, it is seen that indeed different configurational ensembles may be sampled without and with application of the restraint. In particular, while the FRET efficiency and interchromophore distances monitored in an unrestrained simulation may differ from the experimentally-determined values, they can be brought in agreement with experimental data through usage of the FRET efficiency restraining potential. Furthermore, the present results suggest that the assumption of isotropic chromophore orientation is not always justified. The FRET efficiency restraint allows the generation of configurational ensembles that may not be accessible with unrestrained simulations, and thereby supports a meaningful interpretation of experimental FRET results in terms of the underlying molecular degrees of freedom. Thus, it offers an additional tool to connect the realms of computer and wet-lab experimentation.

  4. Intelligent Ensemble Forecasting System of Stock Market Fluctuations Based on Symetric and Asymetric Wavelet Functions

    NASA Astrophysics Data System (ADS)

    Lahmiri, Salim; Boukadoum, Mounir

    2015-08-01

    We present a new ensemble system for stock market returns prediction where continuous wavelet transform (CWT) is used to analyze return series and backpropagation neural networks (BPNNs) for processing CWT-based coefficients, determining the optimal ensemble weights, and providing final forecasts. Particle swarm optimization (PSO) is used for finding optimal weights and biases for each BPNN. To capture symmetry/asymmetry in the underlying data, three wavelet functions with different shapes are adopted. The proposed ensemble system was tested on three Asian stock markets: The Hang Seng, KOSPI, and Taiwan stock market data. Three statistical metrics were used to evaluate the forecasting accuracy; including, mean of absolute errors (MAE), root mean of squared errors (RMSE), and mean of absolute deviations (MADs). Experimental results showed that our proposed ensemble system outperformed the individual CWT-ANN models each with different wavelet function. In addition, the proposed ensemble system outperformed the conventional autoregressive moving average process. As a result, the proposed ensemble system is suitable to capture symmetry/asymmetry in financial data fluctuations for better prediction accuracy.

  5. Ensembles of satellite aerosol retrievals based on three AATSR algorithms within aerosol_cci

    NASA Astrophysics Data System (ADS)

    Kosmale, Miriam; Popp, Thomas

    2016-04-01

    Ensemble techniques are widely used in the modelling community, combining different modelling results in order to reduce uncertainties. This approach could be also adapted to satellite measurements. Aerosol_cci is an ESA funded project, where most of the European aerosol retrieval groups work together. The different algorithms are homogenized as far as it makes sense, but remain essentially different. Datasets are compared with ground based measurements and between each other. Three AATSR algorithms (Swansea university aerosol retrieval, ADV aerosol retrieval by FMI and Oxford aerosol retrieval ORAC) provide within this project 17 year global aerosol records. Each of these algorithms provides also uncertainty information on pixel level. Within the presented work, an ensembles of the three AATSR algorithms is performed. The advantage over each single algorithm is the higher spatial coverage due to more measurement pixels per gridbox. A validation to ground based AERONET measurements shows still a good correlation of the ensemble, compared to the single algorithms. Annual mean maps show the global aerosol distribution, based on a combination of the three aerosol algorithms. In addition, pixel level uncertainties of each algorithm are used for weighting the contributions, in order to reduce the uncertainty of the ensemble. Results of different versions of the ensembles for aerosol optical depth will be presented and discussed. The results are validated against ground based AERONET measurements. A higher spatial coverage on daily basis allows better results in annual mean maps. The benefit of using pixel level uncertainties is analysed.

  6. GACEM: Genetic Algorithm Based Classifier Ensemble in a Multi-sensor System

    PubMed Central

    Xu, Rongwu; He, Lin

    2008-01-01

    Multi-sensor systems (MSS) have been increasingly applied in pattern classification while searching for the optimal classification framework is still an open problem. The development of the classifier ensemble seems to provide a promising solution. The classifier ensemble is a learning paradigm where many classifiers are jointly used to solve a problem, which has been proven an effective method for enhancing the classification ability. In this paper, by introducing the concept of Meta-feature (MF) and Trans-function (TF) for describing the relationship between the nature and the measurement of the observed phenomenon, classification in a multi-sensor system can be unified in the classifier ensemble framework. Then an approach called Genetic Algorithm based Classifier Ensemble in Multi-sensor system (GACEM) is presented, where a genetic algorithm is utilized for optimization of both the selection of features subset and the decision combination simultaneously. GACEM trains a number of classifiers based on different combinations of feature vectors at first and then selects the classifiers whose weight is higher than the pre-set threshold to make up the ensemble. An empirical study shows that, compared with the conventional feature-level voting and decision-level voting, not only can GACEM achieve better and more robust performance, but also simplify the system markedly. PMID:27873866

  7. Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux

    USGS Publications Warehouse

    Xue, Y.; Liu, S.; Hu, Y.; Yang, J.; Chen, Q.

    2007-01-01

    To improve the accuracy in prediction, Genetic Algorithm based Adaptive Neural Network Ensemble (GA-ANNE) is presented. Intersections are allowed between different training sets based on the fuzzy clustering analysis, which ensures the diversity as well as the accuracy of individual Neural Networks (NNs). Moreover, to improve the accuracy of the adaptive weights of individual NNs, GA is used to optimize the cluster centers. Empirical results in predicting carbon flux of Duke Forest reveal that GA-ANNE can predict the carbon flux more accurately than Radial Basis Function Neural Network (RBFNN), Bagging NN ensemble, and ANNE. ?? 2007 IEEE.

  8. Multimodal Degradation Prognostics Based on Switching Kalman Filter Ensemble.

    PubMed

    Lim, Pin; Goh, Chi Keong; Tan, Kay Chen; Dutta, Partha

    2017-01-01

    For accurate prognostics, users have to determine the current health of the system and predict future degradation pattern of the system. An increasingly popular approach toward tackling prognostic problems involves the use of switching models to represent various degradation phases, which the system undergoes. Such approaches have the advantage of determining the exact degradation phase of the system and being able to handle nonlinear degradation models through piecewise linear approximation. However, limitations of such existing methods include, limited applicability due to the discretization of predicted remaining useful life, insufficient robustness due to the use of single models and others. This paper circumvents these limitations by proposing a hybrid of ensemble methods with switching methods. The proposed method first implements a switching Kalman filter (SKF) to classify between various linear degradation phases, then predict the future propagation of fault dimension using appropriate Kalman filters for each phase. This proposed method achieves both continuous and discrete prediction values representing the remaining life and degradation phase of the system, respectively. The proposed framework is shown via a case study on benchmark simulated aeroengine data sets. The evaluation of the proposed framework shows that the proposed method achieves better accuracy and robustness against noise compared with other methods reported in the literature. The results also indicate the effectiveness of the SKF in detecting the switching point between various degradation modes.

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

    PubMed

    Escobedo, Fernando A

    2007-11-07

    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. Martinez-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.

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

    NASA Astrophysics Data System (ADS)

    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.

  11. Accurate eQTL prioritization with an ensemble-based framework.

    PubMed

    Zeng, Haoyang; Edwards, Matthew D; Guo, Yuchun; Gifford, David K

    2017-02-21

    We present a novel ensemble-based computational framework, EnsembleExpr, that achieved the best performance in the Fourth Critical Assessment of Genome Interpretation (CAGI4) "eQTL-causal SNPs" challenge for identifying eQTLs and prioritizing their gene expression effects. Expression quantitative trait loci (eQTLs) are genome sequence variants that result in gene expression changes and thus are prime suspects in the search for contributions to the causality of complex traits. When EnsembleExpr is trained on data from massively parallel reporter assays (MPRA) it accurately predicts reporter expression levels from unseen regulatory sequences and identifies sequence variants that exhibit significant changes in reporter expression. Compared with other state-of-the-art methods, EnsembleExpr achieved competitive performance when applied on eQTL datasets determined by other protocols. We envision EnsembleExpr to be a resource to help interpret non-coding regulatory variants and prioritize disease-associated mutations for downstream validation. This article is protected by copyright. All rights reserved.

  12. Determination of the DFN modeling domain size based on ensemble variability of equivalent permeability

    NASA Astrophysics Data System (ADS)

    Ji, S. H.; Koh, Y. K.

    2015-12-01

    Conceptualization of the fracture network in a disposal site is important for the safety assessment of a subsurface repository for radioactive waste. To consider the uncertainty of the stochastically conceptualized discrete fracture networks (DFNs), the ensemble variability of equivalent permeability was evaluated by defining different network structures with various fracture densities and characterization levels, and analyzing the ensemble mean and variability of the equivalent permeability of the networks, where the characterization level was defined as the ratio of the number of deterministically conceptualized fractures to the total number of fractures in the domain. The results show that the hydraulic property of the generated fractures were similar among the ensembles when the fracture density was larger than the specific fracture density where the domain size was equal to the correlation length of a given fracture network. In a sparsely fracture network where the fracture density was smaller than the specific fracture density, the ensemble variability was too large to ensure the consistent property from the stochastic DFN modeling. Deterministic information for a portion of a fracture network could reduce the uncertainty of the hydraulic property only when the fracture density was larger than the specific fracture density. Based on these results, the DFN modeling domain size for KAERI's (Korea Atomic Energy Research Institute) URT (Underground Research Tunnel) site to guarantee a less variable hydraulic property of the fracture network was determined by calculating the correlation length, and verified by evaluating the ensemble variability of the equivalent permeability.

  13. Ensemble-based Regional Climate Prediction: Political Impacts

    NASA Astrophysics Data System (ADS)

    Miguel, E.; Dykema, J.; Satyanath, S.; Anderson, J. G.

    2008-12-01

    Accurate forecasts of regional climate, including temperature and precipitation, have significant implications for human activities, not just economically but socially. Sub Saharan Africa is a region that has displayed an exceptional propensity for devastating civil wars. Recent research in political economy has revealed a strong statistical relationship between year to year fluctuations in precipitation and civil conflict in this region in the 1980s and 1990s. To investigate how climate change may modify the regional risk of civil conflict in the future requires a probabilistic regional forecast that explicitly accounts for the community's uncertainty in the evolution of rainfall under anthropogenic forcing. We approach the regional climate prediction aspect of this question through the application of a recently demonstrated method called generalized scalar prediction (Leroy et al. 2009), which predicts arbitrary scalar quantities of the climate system. This prediction method can predict change in any variable or linear combination of variables of the climate system averaged over a wide range spatial scales, from regional to hemispheric to global. Generalized scalar prediction utilizes an ensemble of model predictions to represent the community's uncertainty range in climate modeling in combination with a timeseries of any type of observational data that exhibits sensitivity to the scalar of interest. It is not necessary to prioritize models in deriving with the final prediction. We present the results of the application of generalized scalar prediction for regional forecasts of temperature and precipitation and Sub Saharan Africa. We utilize the climate predictions along with the established statistical relationship between year-to-year rainfall variability in Sub Saharan Africa to investigate the potential impact of climate change on civil conflict within that region.

  14. Improving SVDD classification performance on hyperspectral images via correlation based ensemble technique

    NASA Astrophysics Data System (ADS)

    Uslu, Faruk Sukru; Binol, Hamidullah; Ilarslan, Mustafa; Bal, Abdullah

    2017-02-01

    Support Vector Data Description (SVDD) is a nonparametric and powerful method for target detection and classification. The SVDD constructs a minimum hypersphere enclosing the target objects as much as possible. It has advantages of sparsity, good generalization and using kernel machines. In many studies, different methods have been offered in order to improve the performance of the SVDD. In this paper, we have presented ensemble methods to improve classification performance of the SVDD in remotely sensed hyperspectral imagery (HSI) data. Among various ensemble approaches we have selected bagging technique for training data set with different combinations. As a novel technique for weighting we have proposed a correlation based weight coefficients assignment. In this technique, correlation between each bagged classifier is calculated to give coefficients to weighted combinators. To verify the improvement performance, two hyperspectral images are processed for classification purpose. The obtained results show that the ensemble SVDD has been found to be significantly better than conventional SVDD in terms of classification accuracy.

  15. Cavity QED based on collective magnetic dipole coupling: spin ensembles as hybrid two-level systems.

    PubMed

    Imamoğlu, Atac

    2009-02-27

    We analyze the magnetic dipole coupling of an ensemble of spins to a superconducting microwave stripline structure, incorporating a Josephson junction based transmon qubit. We show that this system is described by an embedded Jaynes-Cummings model: in the strong coupling regime, collective spin-wave excitations of the ensemble of spins pick up the nonlinearity of the cavity mode, such that the two lowest eigenstates of the coupled spin wave-microwave cavity-Josephson junction system define a hybrid two-level system. The proposal described here enables new avenues for nonlinear optics using optical photons coupled to spin ensembles via Raman transitions. The possibility of strong coupling cavity QED with magnetic dipole transitions also opens up the possibility of extending quantum information processing protocols to spins in silicon or graphene, without the need for single-spin confinement.

  16. Ensembl 2007.

    PubMed

    Hubbard, T J P; Aken, B L; Beal, K; Ballester, B; Caccamo, M; Chen, Y; Clarke, L; Coates, G; Cunningham, F; Cutts, T; Down, T; Dyer, S C; Fitzgerald, S; Fernandez-Banet, J; Graf, S; Haider, S; Hammond, M; Herrero, J; Holland, R; Howe, K; Howe, K; Johnson, N; Kahari, A; Keefe, D; Kokocinski, F; Kulesha, E; Lawson, D; Longden, I; Melsopp, C; Megy, K; Meidl, P; Ouverdin, B; Parker, A; Prlic, A; Rice, S; Rios, D; Schuster, M; Sealy, I; Severin, J; Slater, G; Smedley, D; Spudich, G; Trevanion, S; Vilella, A; Vogel, J; White, S; Wood, M; Cox, T; Curwen, V; Durbin, R; Fernandez-Suarez, X M; Flicek, P; Kasprzyk, A; Proctor, G; Searle, S; Smith, J; Ureta-Vidal, A; Birney, E

    2007-01-01

    The Ensembl (http://www.ensembl.org/) project provides a comprehensive and integrated source of annotation of chordate genome sequences. Over the past year the number of genomes available from Ensembl has increased from 15 to 33, with the addition of sites for the mammalian genomes of elephant, rabbit, armadillo, tenrec, platypus, pig, cat, bush baby, common shrew, microbat and european hedgehog; the fish genomes of stickleback and medaka and the second example of the genomes of the sea squirt (Ciona savignyi) and the mosquito (Aedes aegypti). Some of the major features added during the year include the first complete gene sets for genomes with low-sequence coverage, the introduction of new strain variation data and the introduction of new orthology/paralog annotations based on gene trees.

  17. Operational optimization of irrigation scheduling for citrus trees using an ensemble based data assimilation approach

    NASA Astrophysics Data System (ADS)

    Hendricks Franssen, H.; Han, X.; Martinez, F.; Jimenez, M.; Manzano, J.; Chanzy, A.; Vereecken, H.

    2013-12-01

    Data assimilation (DA) techniques, like the local ensemble transform Kalman filter (LETKF) not only offer the opportunity to update model predictions by assimilating new measurement data in real time, but also provide an improved basis for real-time (DA-based) control. This study focuses on the optimization of real-time irrigation scheduling for fields of citrus trees near Picassent (Spain). For three selected fields the irrigation was optimized with DA-based control, and for other fields irrigation was optimized on the basis of a more traditional approach where reference evapotranspiration for citrus trees was estimated using the FAO-method. The performance of the two methods is compared for the year 2013. The DA-based real-time control approach is based on ensemble predictions of soil moisture profiles, using the Community Land Model (CLM). The uncertainty in the model predictions is introduced by feeding the model with weather predictions from an ensemble prediction system (EPS) and uncertain soil hydraulic parameters. The model predictions are updated daily by assimilating soil moisture data measured by capacitance probes. The measurement data are assimilated with help of LETKF. The irrigation need was calculated for each of the ensemble members, averaged, and logistic constraints (hydraulics, energy costs) were taken into account for the final assigning of irrigation in space and time. For the operational scheduling based on this approach only model states and no model parameters were updated by the model. Other, non-operational simulation experiments for the same period were carried out where (1) neither ensemble weather forecast nor DA were used (open loop), (2) Only ensemble weather forecast was used, (3) Only DA was used, (4) also soil hydraulic parameters were updated in data assimilation and (5) both soil hydraulic and plant specific parameters were updated. The FAO-based and DA-based real-time irrigation control are compared in terms of soil moisture

  18. Recognition of multiple imbalanced cancer types based on DNA microarray data using ensemble classifiers.

    PubMed

    Yu, Hualong; Hong, Shufang; Yang, Xibei; Ni, Jun; Dan, Yuanyuan; Qin, Bin

    2013-01-01

    DNA microarray technology can measure the activities of tens of thousands of genes simultaneously, which provides an efficient way to diagnose cancer at the molecular level. Although this strategy has attracted significant research attention, most studies neglect an important problem, namely, that most DNA microarray datasets are skewed, which causes traditional learning algorithms to produce inaccurate results. Some studies have considered this problem, yet they merely focus on binary-class problem. In this paper, we dealt with multiclass imbalanced classification problem, as encountered in cancer DNA microarray, by using ensemble learning. We utilized one-against-all coding strategy to transform multiclass to multiple binary classes, each of them carrying out feature subspace, which is an evolving version of random subspace that generates multiple diverse training subsets. Next, we introduced one of two different correction technologies, namely, decision threshold adjustment or random undersampling, into each training subset to alleviate the damage of class imbalance. Specifically, support vector machine was used as base classifier, and a novel voting rule called counter voting was presented for making a final decision. Experimental results on eight skewed multiclass cancer microarray datasets indicate that unlike many traditional classification approaches, our methods are insensitive to class imbalance.

  19. Application of dynamic linear regression to improve the skill of ensemble-based deterministic ozone forecasts

    SciTech Connect

    Pagowski, M O; Grell, G A; Devenyi, D; Peckham, S E; McKeen, S A; Gong, W; Monache, L D; McHenry, J N; McQueen, J; Lee, P

    2006-02-02

    Forecasts from seven air quality models and surface ozone data collected over the eastern USA and southern Canada during July and August 2004 provide a unique opportunity to assess benefits of ensemble-based ozone forecasting and devise methods to improve ozone forecasts. In this investigation, past forecasts from the ensemble of models and hourly surface ozone measurements at over 350 sites are used to issue deterministic 24-h forecasts using a method based on dynamic linear regression. Forecasts of hourly ozone concentrations as well as maximum daily 8-h and 1-h averaged concentrations are considered. It is shown that the forecasts issued with the application of this method have reduced bias and root mean square error and better overall performance scores than any of the ensemble members and the ensemble average. Performance of the method is similar to another method based on linear regression described previously by Pagowski et al., but unlike the latter, the current method does not require measurements from multiple monitors since it operates on individual time series. Improvement in the forecasts can be easily implemented and requires minimal computational cost.

  20. An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

    PubMed

    Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

    2016-01-01

    For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system.

  1. An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy

    PubMed Central

    Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

    2016-01-01

    For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system. PMID:27835638

  2. Probing dynamic conformations of the high-molecular-weight αB-crystallin heat shock protein ensemble by NMR spectroscopy.

    PubMed

    Baldwin, Andrew J; Walsh, Patrick; Hansen, D Flemming; Hilton, Gillian R; Benesch, Justin L P; Sharpe, Simon; Kay, Lewis E

    2012-09-19

    Solution- and solid-state nuclear magnetic resonance (NMR) spectroscopy are highly complementary techniques for studying supra-molecular structure. Here they are employed for investigating the molecular chaperone αB-crystallin, a polydisperse ensemble of between 10 and 40 identical subunits with an average molecular mass of approximately 600 kDa. An IxI motif in the C-terminal region of each of the subunits is thought to play a critical role in regulating the size distribution of oligomers and in controlling the kinetics of subunit exchange between them. Previously published solid-state NMR and X-ray results are consistent with a bound IxI conformation, while solution NMR studies provide strong support for a highly dynamic state. Here we demonstrate through FROSTY (freezing rotational diffusion of protein solutions at low temperature and high viscosity) MAS (magic angle spinning) NMR that both populations are present at low temperatures (<0 °C), while at higher temperatures only the mobile state is observed. Solution NMR relaxation dispersion experiments performed under physiologically relevant conditions establish that the motif interchanges between flexible (highly populated) and bound (sparsely populated) states. This work emphasizes the importance of using multiple methods in studies of supra-molecules, especially for highly dynamic ensembles where sample conditions can potentially affect the conformational properties observed.

  3. A hybrid space approach for ensemble-based 4-D variational data assimilation

    NASA Astrophysics Data System (ADS)

    Shao, Aimei; Xi, Shuang; Qiu, Chongjian; Xu, Qin

    2009-09-01

    A new scheme is developed to improve the ensemble-based 4-D variational data assimilation (En4DVar). In this scheme, leading singular vectors are extracted from 4-D ensemble perturbations in a hybrid space and then used to construct the analysis increment to fit the 4-D innovation (observation minus background) data. The hybrid space combines the 4-D observation space with only a gridded 3-D subspace at the end of each assimilation cycle, so its dimension can be much smaller than the dimension of the fully gridded 4-D space used in the original En4DVar. This improves the computational efficiency. With this hybrid space approach, the analysis increment can fit the 4-D innovation data in the observation space directly and also provide the necessary initial condition in the gridded 3-D subspace exclusively for the model integration into the next assimilation cycle, so the background covariance matrix can be and only needs to be constructed by the ensemble perturbations in the 3-D subspace. This reduces the rank deficiency of the ensemble-constructed covariance matrix and improves analysis accuracy as long as the observations are not too sparse. The potential merits of the new scheme are demonstrated by assimilation experiments performed with an imperfect shallow-water equation model and simulated observations.

  4. Three-dimensional theory of quantum memories based on {Lambda}-type atomic ensembles

    SciTech Connect

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

    2011-10-15

    We develop a three-dimensional theory for quantum memories based on light storage in ensembles of {Lambda}-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 {Lambda}-type atomic ensembles allow for highly efficient backward and forward memories even for small Fresnel numbers F(greater-or-similar sign)0.1.

  5. An ensemble of dissimilarity based classifiers for Mackerel gender determination

    NASA Astrophysics Data System (ADS)

    Blanco, A.; Rodriguez, R.; Martinez-Maranon, I.

    2014-03-01

    Mackerel is an infravalored fish captured by European fishing vessels. A manner to add value to this specie can be achieved by trying to classify it attending to its sex. Colour measurements were performed on Mackerel females and males (fresh and defrozen) extracted gonads to obtain differences between sexes. Several linear and non linear classifiers such as Support Vector Machines (SVM), k Nearest Neighbors (k-NN) or Diagonal Linear Discriminant Analysis (DLDA) can been applied to this problem. However, theyare usually based on Euclidean distances that fail to reflect accurately the sample proximities. Classifiers based on non-Euclidean dissimilarities misclassify a different set of patterns. We combine different kind of dissimilarity based classifiers. The diversity is induced considering a set of complementary dissimilarities for each model. The experimental results suggest that our algorithm helps to improve classifiers based on a single dissimilarity.

  6. A novel method for molecular dynamics simulation in the isothermal-isobaric ensemble

    NASA Astrophysics Data System (ADS)

    Huang, Cunkui; Li, Chunli; Choi, Phillip Y. K.; Nandakumar, K.; Kostiuk, Larry W.

    2011-01-01

    A novel algorithm is proposed to study fluid properties in the isothermal-isobaric (NPT) ensemble. The major feature of this approach is that the constant pressure in the NPT ensemble is created by two auto-adjusting boundaries that allow the system volume to fluctuate. Relative to other methods used to create the NPT ensemble, this approach is simpler to perform since no additional variables are introduced into the simulation system. To test this method, two systems with the same constant target pressure and temperature but different thermostats (Nose-Hoover and Berendsen) were performed by using a commonly used cut-off distance (i.e. r c = 2.5σ). The simulation results show that the proposed method works well in terms of creating spatially uniform mean temperature, pressure and density while still allowing appropriate levels of instantaneous fluctuations for observable quantities. The fluctuations of the system volume produced by this method were compared with that calculated by the theoretical equation. To test the reliability of the proposed method, additional simulations were carried out at eight different thermodynamic states but with the use of a longer cut-off distance (r c = 4.5σ). The results were compared with those obtained using the Nose-Hoover barostat with an r c of 4.5σ, as well as with experiments. The comparison shows that the results using the algorithm proposed in this article agree well with those obtained using other methods.

  7. Dual control cell reaction ensemble molecular dynamics: A method for simulations of reactions and adsorption in porous materials

    NASA Astrophysics Data System (ADS)

    Lísal, Martin; Brennan, John K.; Smith, William R.; Siperstein, Flor R.

    2004-09-01

    We present a simulation tool to study fluid mixtures that are simultaneously chemically reacting and adsorbing in a porous material. The method is a combination of the reaction ensemble Monte Carlo method and the dual control volume grand canonical molecular dynamics technique. The method, termed the dual control cell reaction ensemble molecular dynamics method, allows for the calculation of both equilibrium and nonequilibrium transport properties in porous materials such as diffusion coefficients, permeability, and mass flux. Control cells, which are in direct physical contact with the porous solid, are used to maintain the desired reaction and flow conditions for the system. The simulation setup closely mimics an actual experimental system in which the thermodynamic and flow parameters are precisely controlled. We present an application of the method to the dry reforming of methane reaction within a nanoscale reactor model in the presence of a semipermeable membrane that was modeled as a porous material similar to silicalite. We studied the effects of the membrane structure and porosity on the reaction species permeability by considering three different membrane models. We also studied the effects of an imposed pressure gradient across the membrane on the mass flux of the reaction species. Conversion of syngas (H2/CO) increased significantly in all the nanoscale membrane reactor models considered. A brief discussion of further potential applications is also presented.

  8. Dual control cell reaction ensemble molecular dynamics: a method for simulations of reactions and adsorption in porous materials.

    PubMed

    Lisal, Martin; Brennan, John K; Smith, William R; Siperstein, Flor R

    2004-09-08

    We present a simulation tool to study fluid mixtures that are simultaneously chemically reacting and adsorbing in a porous material. The method is a combination of the reaction ensemble Monte Carlo method and the dual control volume grand canonical molecular dynamics technique. The method, termed the dual control cell reaction ensemble molecular dynamics method, allows for the calculation of both equilibrium and nonequilibrium transport properties in porous materials such as diffusion coefficients, permeability, and mass flux. Control cells, which are in direct physical contact with the porous solid, are used to maintain the desired reaction and flow conditions for the system. The simulation setup closely mimics an actual experimental system in which the thermodynamic and flow parameters are precisely controlled. We present an application of the method to the dry reforming of methane reaction within a nanoscale reactor model in the presence of a semipermeable membrane that was modeled as a porous material similar to silicalite. We studied the effects of the membrane structure and porosity on the reaction species permeability by considering three different membrane models. We also studied the effects of an imposed pressure gradient across the membrane on the mass flux of the reaction species. Conversion of syngas (H2/CO) increased significantly in all the nanoscale membrane reactor models considered. A brief discussion of further potential applications is also presented.

  9. A Remodeled Hsp90 Molecular Chaperone Ensemble with the Novel Cochaperone Aarsd1 Is Required for Muscle Differentiation.

    PubMed

    Echeverría, Pablo C; Briand, Pierre-André; Picard, Didier

    2016-04-01

    Hsp90 is the ATP-consuming core component of a very abundant molecular chaperone machine that handles a substantial portion of the cytosolic proteome. Rather than one machine, it is in fact an ensemble of molecular machines, since most mammalian cells express two cytosolic isoforms of Hsp90 and a subset of up to 40 to 50 cochaperones and regulate their interactions and functions by a variety of posttranslational modifications. We demonstrate that the Hsp90 ensemble is fundamentally remodeled during muscle differentiation and that this remodeling is not just a consequence of muscle differentiation but possibly one of the drivers to accompany and to match the vast proteomic changes associated with this process. As myoblasts differentiate into myotubes, Hsp90α disappears and only Hsp90β remains, which is the only isoform capable of interacting with the novel muscle-specific Hsp90 cochaperone Aarsd1L. Artificially maintaining Hsp90α or knocking down Aarsd1L expression interferes with the differentiation of C2C12 myotubes. During muscle differentiation, Aarsd1L replaces the more ubiquitous cochaperone p23 and in doing so dampens the activity of the glucocorticoid receptor, one of the Hsp90 clients relevant to muscle functions. This cochaperone switch protects muscle cells against the inhibitory effects of glucocorticoids and may contribute to preventing muscle wasting induced by excess glucocorticoids.

  10. A Remodeled Hsp90 Molecular Chaperone Ensemble with the Novel Cochaperone Aarsd1 Is Required for Muscle Differentiation

    PubMed Central

    Echeverría, Pablo C.; Briand, Pierre-André

    2016-01-01

    Hsp90 is the ATP-consuming core component of a very abundant molecular chaperone machine that handles a substantial portion of the cytosolic proteome. Rather than one machine, it is in fact an ensemble of molecular machines, since most mammalian cells express two cytosolic isoforms of Hsp90 and a subset of up to 40 to 50 cochaperones and regulate their interactions and functions by a variety of posttranslational modifications. We demonstrate that the Hsp90 ensemble is fundamentally remodeled during muscle differentiation and that this remodeling is not just a consequence of muscle differentiation but possibly one of the drivers to accompany and to match the vast proteomic changes associated with this process. As myoblasts differentiate into myotubes, Hsp90α disappears and only Hsp90β remains, which is the only isoform capable of interacting with the novel muscle-specific Hsp90 cochaperone Aarsd1L. Artificially maintaining Hsp90α or knocking down Aarsd1L expression interferes with the differentiation of C2C12 myotubes. During muscle differentiation, Aarsd1L replaces the more ubiquitous cochaperone p23 and in doing so dampens the activity of the glucocorticoid receptor, one of the Hsp90 clients relevant to muscle functions. This cochaperone switch protects muscle cells against the inhibitory effects of glucocorticoids and may contribute to preventing muscle wasting induced by excess glucocorticoids. PMID:26884463

  11. Reduced-order flow modeling and geological parameterization for ensemble-based data assimilation

    NASA Astrophysics Data System (ADS)

    He, Jincong; Sarma, Pallav; Durlofsky, Louis J.

    2013-06-01

    Reduced-order modeling represents an attractive approach for accelerating computationally expensive reservoir simulation applications. In this paper, we introduce and apply such a methodology for data assimilation problems. The technique applied to provide flow simulation results, trajectory piecewise linearization (TPWL), has been used previously for production optimization problems, where it has provided large computational speedups. The TPWL model developed here represents simulation results for new geological realizations in terms of a linearization around previously simulated (training) cases. The high-dimensional representation of the states is projected into a low-dimensional subspace using proper orthogonal decomposition. The geological models are also represented in reduced terms using a Karhunen-Loève expansion of the log-transmissibility field. Thus, both the reservoir states and geological parameters are described very concisely. The reduced-order representation of flow and geology is appropriate for use with ensemble-based data assimilation procedures, and here it is incorporated into an ensemble Kalman filter (EnKF) framework to enrich the ensemble at a low cost. The method is able to reconstruct full-order states, which are required by EnKF, whenever necessary. The combined technique enables EnKF to be applied using many fewer high-fidelity reservoir simulations than would otherwise be required to avoid ensemble collapse. For two- and three-dimensional example cases, it is demonstrated that EnKF results using 50 high-fidelity simulations along with 150 TPWL simulations are much better than those using only 50 high-fidelity simulations (for which ensemble collapse is observed) and are, in fact, comparable to the results achieved using 200 high-fidelity simulations.

  12. System for NIS Forecasting Based on Ensembles Analysis

    SciTech Connect

    2014-01-02

    BMA-NIS is a package/library designed to be called by a script (e.g. Perl or Python). The software itself is written in the language of R. The software assists electric power delivery systems in planning resource availability and demand, based on historical data and current data variables. Net Interchange Schedule (NIS) is the algebraic sum of all energy scheduled to flow into or out of a balancing area during any interval. Accurate forecasts for NIS are important so that the Area Control Error (ACE) stays within an acceptable limit. To date, there are many approaches for forecasting NIS but all none of these are based on single models that can be sensitive to time of day and day of week effects.

  13. Ensemble method: Community detection based on game theory

    NASA Astrophysics Data System (ADS)

    Zhang, Xia; Xia, Zhengyou; Xu, Shengwu; Wang, J. D.

    2014-08-01

    Timely and cost-effective analytics over social network has emerged as a key ingredient for success in many businesses and government endeavors. Community detection is an active research area of relevance to analyze online social network. The problem of selecting a particular community detection algorithm is crucial if the aim is to unveil the community structure of a network. The choice of a given methodology could affect the outcome of the experiments because different algorithms have different advantages and depend on tuning specific parameters. In this paper, we propose a community division model based on the notion of game theory, which can combine advantages of previous algorithms effectively to get a better community classification result. By making experiments on some standard dataset, it verifies that our community detection model based on game theory is valid and better.

  14. DNA based molecular motors

    NASA Astrophysics Data System (ADS)

    Michaelis, Jens; Muschielok, Adam; Andrecka, Joanna; Kügel, Wolfgang; Moffitt, Jeffrey R.

    2009-12-01

    Most of the essential cellular processes such as polymerisation reactions, gene expression and regulation are governed by mechanical processes. Controlled mechanical investigations of these processes are therefore required in order to take our understanding of molecular biology to the next level. Single-molecule manipulation and force spectroscopy have over the last 15 years been developed into extremely powerful techniques. Applying these techniques to the investigation of proteins and DNA molecules has led to a mechanistic understanding of protein function on the level of single molecules. As examples for DNA based molecular machines we will describe single-molecule experiments on RNA polymerases as well as on the packaging of DNA into a viral capsid-a process that is driven by one of the most powerful molecular motors.

  15. DARPA Ensemble-Based Modeling Large Graphs & Applications to Social Networks

    DTIC Science & Technology

    2015-07-29

    processes on social networks. Specific connectivity schemes affect influence propagation and epidemic spread, and is also responsible for Web page...AFRL-OSR-VA-TR-2015-0212 DARPA EnsembleBased Modeling Large Graphs & Applications to Social Networks Zoltan Toroczkai UNIVERSITY OF NOTRE DAME DU LAC...for this collection of information is estimated to average 1 hour per response , including the time for reviewing instructions, searching existing data

  16. Using multi-compartment ensemble modeling as an investigative tool of spatially distributed biophysical balances: application to hippocampal oriens-lacunosum/moleculare (O-LM) cells.

    PubMed

    Sekulić, Vladislav; Lawrence, J Josh; Skinner, Frances K

    2014-01-01

    Multi-compartmental models of neurons provide insight into the complex, integrative properties of dendrites. Because it is not feasible to experimentally determine the exact density and kinetics of each channel type in every neuronal compartment, an essential goal in developing models is to help characterize these properties. To address biological variability inherent in a given neuronal type, there has been a shift away from using hand-tuned models towards using ensembles or populations of models. In collectively capturing a neuron's output, ensemble modeling approaches uncover important conductance balances that control neuronal dynamics. However, conductances are never entirely known for a given neuron class in terms of its types, densities, kinetics and distributions. Thus, any multi-compartment model will always be incomplete. In this work, our main goal is to use ensemble modeling as an investigative tool of a neuron's biophysical balances, where the cycling between experiment and model is a design criterion from the start. We consider oriens-lacunosum/moleculare (O-LM) interneurons, a prominent interneuron subtype that plays an essential gating role of information flow in hippocampus. O-LM cells express the hyperpolarization-activated current (Ih). Although dendritic Ih could have a major influence on the integrative properties of O-LM cells, the compartmental distribution of Ih on O-LM dendrites is not known. Using a high-performance computing cluster, we generated a database of models that included those with or without dendritic Ih. A range of conductance values for nine different conductance types were used, and different morphologies explored. Models were quantified and ranked based on minimal error compared to a dataset of O-LM cell electrophysiological properties. Co-regulatory balances between conductances were revealed, two of which were dependent on the presence of dendritic Ih. These findings inform future experiments that differentiate between

  17. Using Multi-Compartment Ensemble Modeling As an Investigative Tool of Spatially Distributed Biophysical Balances: Application to Hippocampal Oriens-Lacunosum/Moleculare (O-LM) Cells

    PubMed Central

    Sekulić, Vladislav; Lawrence, J. Josh; Skinner, Frances K.

    2014-01-01

    Multi-compartmental models of neurons provide insight into the complex, integrative properties of dendrites. Because it is not feasible to experimentally determine the exact density and kinetics of each channel type in every neuronal compartment, an essential goal in developing models is to help characterize these properties. To address biological variability inherent in a given neuronal type, there has been a shift away from using hand-tuned models towards using ensembles or populations of models. In collectively capturing a neuron's output, ensemble modeling approaches uncover important conductance balances that control neuronal dynamics. However, conductances are never entirely known for a given neuron class in terms of its types, densities, kinetics and distributions. Thus, any multi-compartment model will always be incomplete. In this work, our main goal is to use ensemble modeling as an investigative tool of a neuron's biophysical balances, where the cycling between experiment and model is a design criterion from the start. We consider oriens-lacunosum/moleculare (O-LM) interneurons, a prominent interneuron subtype that plays an essential gating role of information flow in hippocampus. O-LM cells express the hyperpolarization-activated current (Ih). Although dendritic Ih could have a major influence on the integrative properties of O-LM cells, the compartmental distribution of Ih on O-LM dendrites is not known. Using a high-performance computing cluster, we generated a database of models that included those with or without dendritic Ih. A range of conductance values for nine different conductance types were used, and different morphologies explored. Models were quantified and ranked based on minimal error compared to a dataset of O-LM cell electrophysiological properties. Co-regulatory balances between conductances were revealed, two of which were dependent on the presence of dendritic Ih. These findings inform future experiments that differentiate between

  18. Clustering-Based Ensemble Learning for Activity Recognition in Smart Homes

    PubMed Central

    Jurek, Anna; Nugent, Chris; Bi, Yaxin; Wu, Shengli

    2014-01-01

    Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks. PMID:25014095

  19. Clustering-based ensemble learning for activity recognition in smart homes.

    PubMed

    Jurek, Anna; Nugent, Chris; Bi, Yaxin; Wu, Shengli

    2014-07-10

    Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks.

  20. Design of protein switches based on an ensemble model of allostery.

    PubMed

    Choi, Jay H; Laurent, Abigail H; Hilser, Vincent J; Ostermeier, Marc

    2015-04-22

    Switchable proteins that can be regulated through exogenous or endogenous inputs have a broad range of biotechnological and biomedical applications. Here we describe the design of switchable enzymes based on an ensemble allosteric model. First, we insert an enzyme domain into an effector-binding domain such that both domains remain functionally intact. Second, we induce the fusion to behave as a switch through the introduction of conditional conformational flexibility designed to increase the conformational entropy of the enzyme domain in a temperature- or pH-dependent fashion. We confirm the switching behaviour in vitro and in vivo. Structural and thermodynamic studies support the hypothesis that switching result from an increase in conformational entropy of the enzyme domain in the absence of effector. These results support the ensemble model of allostery and embody a strategy for the design of protein switches.

  1. An ensemble classification-based approach applied to retinal blood vessel segmentation.

    PubMed

    Fraz, Muhammad Moazam; Remagnino, Paolo; Hoppe, Andreas; Uyyanonvara, Bunyarit; Rudnicka, Alicja R; Owen, Christopher G; Barman, Sarah A

    2012-09-01

    This paper presents a new supervised method for segmentation of blood vessels in retinal photographs. This method uses an ensemble system of bagged and boosted decision trees and utilizes a feature vector based on the orientation analysis of gradient vector field, morphological transformation, line strength measures, and Gabor filter responses. The feature vector encodes information to handle the healthy as well as the pathological retinal image. The method is evaluated on the publicly available DRIVE and STARE databases, frequently used for this purpose and also on a new public retinal vessel reference dataset CHASE_DB1 which is a subset of retinal images of multiethnic children from the Child Heart and Health Study in England (CHASE) dataset. The performance of the ensemble system is evaluated in detail and the incurred accuracy, speed, robustness, and simplicity make the algorithm a suitable tool for automated retinal image analysis.

  2. Random feature subspace ensemble based Extreme Learning Machine for liver tumor detection and segmentation.

    PubMed

    Huang, Weimin; Yang, Yongzhong; Lin, Zhiping; Huang, Guang-Bin; Zhou, Jiayin; Duan, Yuping; Xiong, Wei

    2014-01-01

    This paper presents a new approach to detect and segment liver tumors. The detection and segmentation of liver tumors can be formulized as novelty detection or two-class classification problem. Each voxel is characterized by a rich feature vector, and a classifier using random feature subspace ensemble is trained to classify the voxels. Since Extreme Learning Machine (ELM) has advantages of very fast learning speed and good generalization ability, it is chosen to be the base classifier in the ensemble. Besides, majority voting is incorporated for fusion of classification results from the ensemble of base classifiers. In order to further increase testing accuracy, ELM autoencoder is implemented as a pre-training step. In automatic liver tumor detection, ELM is trained as a one-class classifier with only healthy liver samples, and the performance is compared with two-class ELM. In liver tumor segmentation, a semi-automatic approach is adopted by selecting samples in 3D space to train the classifier. The proposed method is tested and evaluated on a group of patients' CT data and experiment show promising results.

  3. Planetary gearbox condition monitoring of ship-based satellite communication antennas using ensemble multiwavelet analysis method

    NASA Astrophysics Data System (ADS)

    Chen, Jinglong; Zhang, Chunlin; Zhang, Xiaoyan; Zi, Yanyang; He, Shuilong; Yang, Zhe

    2015-03-01

    Satellite communication antennas are key devices of a measurement ship to support voice, data, fax and video integration services. Condition monitoring of mechanical equipment from the vibration measurement data is significant for guaranteeing safe operation and avoiding the unscheduled breakdown. So, condition monitoring system for ship-based satellite communication antennas is designed and developed. Planetary gearboxes play an important role in the transmission train of satellite communication antenna. However, condition monitoring of planetary gearbox still faces challenges due to complexity and weak condition feature. This paper provides a possibility for planetary gearbox condition monitoring by proposing ensemble a multiwavelet analysis method. Benefit from the property on multi-resolution analysis and the multiple wavelet basis functions, multiwavelet has the advantage over characterizing the non-stationary signal. In order to realize the accurate detection of the condition feature and multi-resolution analysis in the whole frequency band, adaptive multiwavelet basis function is constructed via increasing multiplicity and then vibration signal is processed by the ensemble multiwavelet transform. Finally, normalized ensemble multiwavelet transform information entropy is computed to describe the condition of planetary gearbox. The effectiveness of proposed method is first validated through condition monitoring of experimental planetary gearbox. Then this method is used for planetary gearbox condition monitoring of ship-based satellite communication antennas and the results support its feasibility.

  4. Exploring the Alzheimer amyloid-β peptide conformational ensemble: A review of molecular dynamics approaches.

    PubMed

    Tran, Linh; Ha-Duong, Tâp

    2015-07-01

    Alzheimer's disease is one of the most common dementia among elderly worldwide. There is no therapeutic drugs until now to treat effectively this disease. One main reason is due to the poorly understood mechanism of Aβ peptide aggregation, which plays a crucial role in the development of Alzheimer's disease. It remains challenging to experimentally or theoretically characterize the secondary and tertiary structures of the Aβ monomer because of its high flexibility and aggregation propensity, and its conformations that lead to the aggregation are not fully identified. In this review, we highlight various structural ensembles of Aβ peptide revealed and characterized by computational approaches in order to find converging structures of Aβ monomer. Understanding how Aβ peptide forms transiently stable structures prior to aggregation will contribute to the design of new therapeutic molecules against the Alzheimer's disease.

  5. Ensembl 2017

    PubMed Central

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

    2017-01-01

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

  6. Super Ensemble-based Aviation Turbulence Guidance (SEATG) for Air Traffic Management (ATM)

    NASA Astrophysics Data System (ADS)

    Kim, Jung-Hoon; Chan, William; Sridhar, Banavar; Sharman, Robert

    2014-05-01

    Super Ensemble (ensemble of ten turbulence metrics from time-lagged ensemble members of weather forecast data)-based Aviation Turbulence Guidance (SEATG) is developed using Weather Research and Forecasting (WRF) model and in-situ eddy dissipation rate (EDR) observations equipped on commercial aircraft over the contiguous United States. SEATG is a sequence of five procedures including weather modeling, calculating turbulence metrics, mapping EDR-scale, evaluating metrics, and producing final SEATG forecast. This uses similar methodology to the operational Graphic Turbulence Guidance (GTG) with three major improvements. First, SEATG use a higher resolution (3-km) WRF model to capture cloud-resolving scale phenomena. Second, SEATG computes turbulence metrics for multiple forecasts that are combined at the same valid time resulting in an time-lagged ensemble of multiple turbulence metrics. Third, SEATG provides both deterministic and probabilistic turbulence forecasts to take into account weather uncertainties and user demands. It is found that the SEATG forecasts match well with observed radar reflectivity along a surface front as well as convectively induced turbulence outside the clouds on 7-8 Sep 2012. And, overall performance skill of deterministic SEATG against the observed EDR data during this period is superior to any single turbulence metrics. Finally, probabilistic SEATG is used as an example application of turbulence forecast for air-traffic management. In this study, a simple Wind-Optimal Route (WOR) passing through the potential areas of probabilistic SEATG and Lateral Turbulence Avoidance Route (LTAR) taking into account the SEATG are calculated at z = 35000 ft (z = 12 km) from Los Angeles to John F. Kennedy international airports. As a result, WOR takes total of 239 minutes with 16 minutes of SEATG areas for 40% of moderate turbulence potential, while LTAR takes total of 252 minutes travel time that 5% of fuel would be additionally consumed to entirely

  7. BODIPY-based azamacrocyclic ensemble for selective fluorescence detection and quantification of homocysteine in biological applications.

    PubMed

    Li, Zan; Geng, Zhi-Rong; Zhang, Cui; Wang, Xiao-Bo; Wang, Zhi-Lin

    2015-10-15

    Considering the significant role of plasma homocysteine in physiological processes, two ensembles (F465-Cu(2+) and F508-Cu(2+)) were constructed based on a BODIPY (4,4-difluoro-1,3,5,7-tetramethyl-4-bora-3a,4a-diaza-s-indacene) scaffold conjugated with an azamacrocyclic (1,4,7-triazacyclononane and 1,4,7,10-tetraazacyclododecane) Cu(2+) complex. The results of this effort demonstrated that the F465-Cu(2+) ensemble could be employed to detect homocysteine in the presence of other biologically relevant species, including cysteine and glutathione, under physiological conditions with high selectivity and sensitivity in the turn-on fluorescence mode, while the F508-Cu(2+) ensemble showed no fluorescence responses toward biothiols. A possible mechanism for this homocysteine-specific specificity involving the formation of a homocysteine-induced six-membered ring sandwich structure was proposed and confirmed for the first time by time-dependent fluorescence spectra, ESI-MS and EPR. The detection limit of homocysteine in deproteinized human serum was calculated to be 241.4 nM with a linear range of 0-90.0 μM and the detection limit of F465 for Cu(2+) is 74.7 nM with a linear range of 0-6.0 μM (F508, 80.2 nM, 0-7.0 μM). We have demonstrated the application of the F465-Cu(2+) ensemble for detecting homocysteine in human serum and monitoring the activity of cystathionine β-synthase in vitro.

  8. Fireball as the result of self-organization of an ensemble of diamagnetic electron-ion nanoparticles in molecular gas

    SciTech Connect

    Lopasov, V. P.

    2011-12-15

    The conditions for dissipative self-organization of a fireball (FB) is a molecular gas by means of a regular correction of an elastic collision of water and nitrogen molecules by the field of a coherent bi-harmonic light wave (BLW) are presented. The BWL field is generated due to conversion of energy of a linear lightning discharge into light energy. A FB consists of two components: an ensemble of optically active diamagnetic electron-ion nanoparticles and a standing wave of elliptical polarization (SWEP). It is shown that the FB lifetime depends on the energies accumulated by nanoparticles and the SWEP field and on the stability of self-oscillations of the energy between nanoparticles and SWEP.

  9. Role of different Pd/Pt ensembles in determining CO chemisorption on Au-based bimetallic alloys: A first-principles study

    NASA Astrophysics Data System (ADS)

    Ham, Hyung Chul; Manogaran, Dhivya; Hwang, Gyeong S.; Han, Jonghee; Kim, Hyoung-Juhn; Nam, Suk Woo; Lim, Tae Hoon

    2015-03-01

    Using spin-polarized density functional calculations, we investigate the role of different Pd/Pt ensembles in determining CO chemisorption on Au-based bimetallic alloys through a study of the energetics, charge transfer, geometric and electronic structures of CO on various Pd/Pt ensembles (monomer/dimer/trimer/tetramer). We find that the effect of Pd ensembles on the reduction of CO chemisorption energy is much larger than the Pt ensemble case. In particular, small-sized Pd ensembles like monomer show a substantial reduction of CO chemisorption energy compared to the pure Pd (1 1 1) surface, while there are no significant size and shape effects of Pt ensembles on CO chemisorption energy. This is related to two factors: (1) the steeper potential energy surface (PES) of CO in Pd (1 1 1) than in Pt (1 1 1), indicating that the effect of switch of binding site preference on CO chemisorption energy is much larger in Pd ensembles than in Pt ensembles, and (2) down-shift of d-band in Pd ensembles/up-shift of d-band in Pt ensembles as compared to the corresponding pure Pd (1 1 1)/Pt (1 1 1) surfaces, suggesting more reduced activity of Pd ensembles toward CO adsorption than the Pt ensemble case. We also present the different bonding mechanism of CO on Pd/Pt ensembles by the analysis of orbital resolved density of state.

  10. A Statistical Investigation of the Sensitivity of Ensemble-Based Kalman Filters to Covariance Filtering

    DTIC Science & Technology

    2011-09-01

    averaging: A review. Mon. Wea. Rev., 138, 3693 –3720. Bishop, C. H., and D . Hodyss, 2007: Flow adaptive moderation of spurious ensemble correlations...beyond a prescribed distance d . Some localization functions do not change the sample-based estimate p̂buy of the covariance when the distance ju 2 yj...associated with the pair of state vector components is smaller than d , but replaces p̂buy with zero when ju 2 yj $ d (e.g., (Houtekamer and Mitchell

  11. Ensemble-based evaluation of extreme water levels for the eastern Baltic Sea

    NASA Astrophysics Data System (ADS)

    Eelsalu, Maris; Soomere, Tarmo

    2016-04-01

    The risks and damages associated with coastal flooding that are naturally associated with an increase in the magnitude of extreme storm surges are one of the largest concerns of countries with extensive low-lying nearshore areas. The relevant risks are even more contrast for semi-enclosed water bodies such as the Baltic Sea where subtidal (weekly-scale) variations in the water volume of the sea substantially contribute to the water level and lead to large spreading of projections of future extreme water levels. We explore the options for using large ensembles of projections to more reliably evaluate return periods of extreme water levels. Single projections of the ensemble are constructed by means of fitting several sets of block maxima with various extreme value distributions. The ensemble is based on two simulated data sets produced in the Swedish Meteorological and Hydrological Institute. A hindcast by the Rossby Centre Ocean model is sampled with a resolution of 6 h and a similar hindcast by the circulation model NEMO with a resolution of 1 h. As the annual maxima of water levels in the Baltic Sea are not always uncorrelated, we employ maxima for calendar years and for stormy seasons. As the shape parameter of the Generalised Extreme Value distribution changes its sign and substantially varies in magnitude along the eastern coast of the Baltic Sea, the use of a single distribution for the entire coast is inappropriate. The ensemble involves projections based on the Generalised Extreme Value, Gumbel and Weibull distributions. The parameters of these distributions are evaluated using three different ways: maximum likelihood method and method of moments based on both biased and unbiased estimates. The total number of projections in the ensemble is 40. As some of the resulting estimates contain limited additional information, the members of pairs of projections that are highly correlated are assigned weights 0.6. A comparison of the ensemble-based projection of

  12. Interrogating Emergent Transport Properties for Molecular Motor Ensembles: A Semi-analytical Approach

    PubMed Central

    Materassi, Donatello; Li, Mingang; Hays, Thomas; Salapaka, Murti

    2016-01-01

    Intracellular transport is an essential function in eucaryotic cells, facilitated by motor proteins—proteins converting chemical energy into kinetic energy. It is understood that motor proteins work in teams enabling unidirectional and bidirectional transport of intracellular cargo over long distances. Disruptions of the underlying transport mechanisms, often caused by mutations that alter single motor characteristics, are known to cause neurodegenerative diseases. For example, phosphorylation of kinesin motor domain at the serine residue is implicated in Huntington’s disease, with a recent study of phosphorylated and phosphomimetic serine residues indicating lowered single motor stalling forces. In this article we report the effects of mutations of this nature on transport properties of cargo carried by multiple wild-type and mutant motors. Results indicate that mutants with altered stall forces might determine the average velocity and run-length even when they are outnumbered by wild type motors in the ensemble. It is shown that mutants gain a competitive advantage and lead to an increase in the expected run-length when the load on the cargo is in the vicinity of the mutant’s stalling force or a multiple of its stalling force. A separate contribution of this article is the development of a semi-analytic method to analyze transport of cargo by multiple motors of multiple types. The technique determines transition rates between various relative configurations of motors carrying the cargo using the transition rates between various absolute configurations. This enables a computation of biologically relevant quantities like average velocity and run-length without resorting to Monte Carlo simulations. It can also be used to introduce alterations of various single motor parameters to model a mutation and to deduce effects of such alterations on the transport of a common cargo by multiple motors. Our method is easily implementable and we provide a software package

  13. An investigation of ensemble-based assimilation of satellite altimetry and tide gauge data in storm surge prediction

    NASA Astrophysics Data System (ADS)

    Etala, Paula; Saraceno, Martín; Echevarría, Pablo

    2015-03-01

    Cyclogenesis and long-fetched winds along the southeastern coast of South America may lead to floods in populated areas, as the Buenos Aires Province, with important economic and social impacts. A numerical model (SMARA) has already been implemented in the region to forecast storm surges. The propagation time of the surge in such extensive and shallow area allows the detection of anomalies based on observations from several hours up to the order of a day prior to the event. Here, we investigate the impact and potential benefit of storm surge level data assimilation into the SMARA model, with the objective of improving the forecast. In the experiments, the surface wind stress from an ensemble prediction system drives a storm surge model ensemble, based on the operational 2-D depth-averaged SMARA model. A 4-D Local Ensemble Transform Kalman Filter (4D-LETKF) initializes the ensemble in a 6-h cycle, assimilating the very few tide gauge observations available along the northern coast and satellite altimeter data. The sparse coverage of the altimeters is a challenge to data assimilation; however, the 4D-LETKF evolving covariance of the ensemble perturbations provides realistic cross-track analysis increments. Improvements on the forecast ensemble mean show the potential of an effective use of the sparse satellite altimeter and tidal gauges observations in the data assimilation prototype. Furthermore, the effects of the localization scale and of the observational errors of coastal altimetry and tidal gauges in the data assimilation approach are assessed.

  14. Subspace ensembles for classification

    NASA Astrophysics Data System (ADS)

    Sun, Shiliang; Zhang, Changshui

    2007-11-01

    Ensemble learning constitutes one of the principal current directions in machine learning and data mining. In this paper, we explore subspace ensembles for classification by manipulating different feature subspaces. Commencing with the nature of ensemble efficacy, we probe into the microcosmic meaning of ensemble diversity, and propose to use region partitioning and region weighting to implement effective subspace ensembles. Individual classifiers possessing eminent performance on a partitioned region reflected by high neighborhood accuracies are deemed to contribute largely to this region, and are assigned large weights in determining the labels of instances in this area. A robust algorithm “Sena” that incarnates the mechanism is presented, which is insensitive to the number of nearest neighbors chosen to calculate neighborhood accuracies. The algorithm exhibits improved performance over the well-known ensembles of bagging, AdaBoost and random subspace. The difference of its effectivity with varying base classifiers is also investigated.

  15. The Ensemble Canon

    NASA Technical Reports Server (NTRS)

    MIittman, David S

    2011-01-01

    Ensemble is an open architecture for the development, integration, and deployment of mission operations software. Fundamentally, it is an adaptation of the Eclipse Rich Client Platform (RCP), a widespread, stable, and supported framework for component-based application development. By capitalizing on the maturity and availability of the Eclipse RCP, Ensemble offers a low-risk, politically neutral path towards a tighter integration of operations tools. The Ensemble project is a highly successful, ongoing collaboration among NASA Centers. Since 2004, the Ensemble project has supported the development of mission operations software for NASA's Exploration Systems, Science, and Space Operations Directorates.

  16. Basin-scale runoff prediction: An Ensemble Kalman Filter framework based on global hydrometeorological data sets

    NASA Astrophysics Data System (ADS)

    Lorenz, Christof; Tourian, Mohammad J.; Devaraju, Balaji; Sneeuw, Nico; Kunstmann, Harald

    2015-10-01

    In order to cope with the steady decline of the number of in situ gauges worldwide, there is a growing need for alternative methods to estimate runoff. We present an Ensemble Kalman Filter based approach that allows us to conclude on runoff for poorly or irregularly gauged basins. The approach focuses on the application of publicly available global hydrometeorological data sets for precipitation (GPCC, GPCP, CRU, UDEL), evapotranspiration (MODIS, FLUXNET, GLEAM, ERA interim, GLDAS), and water storage changes (GRACE, WGHM, GLDAS, MERRA LAND). Furthermore, runoff data from the GRDC and satellite altimetry derived estimates are used. We follow a least squares prediction that exploits the joint temporal and spatial auto- and cross-covariance structures of precipitation, evapotranspiration, water storage changes and runoff. We further consider time-dependent uncertainty estimates derived from all data sets. Our in-depth analysis comprises of 29 large river basins of different climate regions, with which runoff is predicted for a subset of 16 basins. Six configurations are analyzed: the Ensemble Kalman Filter (Smoother) and the hard (soft) Constrained Ensemble Kalman Filter (Smoother). Comparing the predictions to observed monthly runoff shows correlations larger than 0.5, percentage biases lower than ± 20%, and NSE-values larger than 0.5. A modified NSE-metric, stressing the difference to the mean annual cycle, shows an improvement of runoff predictions for 14 of the 16 basins. The proposed method is able to provide runoff estimates for nearly 100 poorly gauged basins covering an area of more than 11,500,000 km2 with a freshwater discharge, in volume, of more than 125,000 m3/s.

  17. Basin-scale runoff prediction: An Ensemble Kalman Filter framework based on global hydrometeorological data sets

    NASA Astrophysics Data System (ADS)

    Kunstmann, Harald; Lorenz, Christof; Tourian, Mohammad; Devaraju, Balaji; Sneeuw, Nico

    2016-04-01

    In order to cope with the steady decline of the number of in situ gauges worldwide, there is a growing need for alternative methods to estimate runoff. We present an Ensemble Kalman Filter based approach that allows us to conclude on runoff for poorly or irregularly gauged basins. The approach focuses on the application of publicly available global hydrometeorological data sets for precipitation (GPCC, GPCP, CRU, UDEL), evapotranspiration (MODIS, FLUXNET, GLEAM, ERA interim, GLDAS), and water storage changes (GRACE, WGHM, GLDAS, MERRA LAND). Furthermore, runoff data from the GRDC and satellite altimetry derived estimates are used. We follow a least squares prediction that exploits the joint temporal and spatial auto- and cross-covariance structures of precipitation, evapotranspiration, water storage changes and runoff. We further consider time-dependent uncertainty estimates derived from all data sets. Our in-depth analysis comprises of 29 large river basins of different climate regions, with which runoff is predicted for a subset of 16 basins. Six configurations are analyzed: the Ensemble Kalman Filter (Smoother) and the hard (soft) Constrained Ensemble Kalman Filter (Smoother). Comparing the predictions to observed monthly runoff shows correlations larger than 0.5, percentage biases lower than ± 20%, and NSE-values larger than 0.5. A modified NSE-metric, stressing the difference to the mean annual cycle, shows an improvement of runoff predictions for 14 of the 16 basins. The proposed method is able to provide runoff estimates for nearly 100 poorly gauged basins covering an area of more than 11,500,000 km2 with a freshwater discharge, in volume, of more than 125,000 m3/s.

  18. CMIP5 ensemble-based spatial rainfall projection over homogeneous zones of India

    NASA Astrophysics Data System (ADS)

    Akhter, Javed; Das, Lalu; Deb, Argha

    2016-11-01

    Performances of the state-of-the-art CMIP5 models in reproducing the spatial rainfall patterns over seven homogeneous rainfall zones of India viz. North Mountainous India (NMI), Northwest India (NWI), North Central India (NCI), Northeast India (NEI), West Peninsular India (WPI), East Peninsular India (EPI) and South Peninsular India (SPI) have been assessed using different conventional performance metrics namely spatial correlation (R), index of agreement (d-index), Nash-Sutcliffe efficiency (NSE), Ratio of RMSE to the standard deviation of the observations (RSR) and mean bias (MB). The results based on these indices revealed that majority of the models are unable to reproduce finer-scaled spatial patterns over most of the zones. Thereafter, four bias correction methods i.e. Scaling, Standardized Reconstruction, Empirical Quantile Mapping and Gamma Quantile Mapping have been applied on GCM simulations to enhance the skills of the GCM projections. It has been found that scaling method compared to other three methods shown its better skill in capturing mean spatial patterns. Multi-model ensemble (MME) comprising 25 numbers of better performing bias corrected (Scaled) GCMs, have been considered for developing future rainfall patterns over seven zones. Models' spread from ensemble mean (uncertainty) has been found to be larger in RCP 8.5 than RCP4.5 ensemble. In general, future rainfall projections from RCP 4.5 and RCP 8.5 revealed an increasing rainfall over seven zones during 2020s, 2050s, and 2080s. The maximum increase has been found over southwestern part of NWI (12-30%), northwestern part of WPI (3-30%), southeastern part of NEI (5-18%) and northern and eastern part of SPI (6-24%). However, the contiguous region comprising by the southeastern part of NCI and northeastern part of EPI, may experience slight decreasing rainfall (about 3%) during 2020s whereas the western part of NMI may also receive around 3% reduction in rainfall during both 2050s and 2080s.

  19. Ensemble learning for spatial interpolation of soil potassium content based on environmental information.

    PubMed

    Liu, Wei; Du, Peijun; Wang, Dongchen

    2015-01-01

    One important method to obtain the continuous surfaces of soil properties from point samples is spatial interpolation. In this paper, we propose a method that combines ensemble learning with ancillary environmental information for improved interpolation of soil properties (hereafter, EL-SP). First, we calculated the trend value for soil potassium contents at the Qinghai Lake region in China based on measured values. Then, based on soil types, geology types, land use types, and slope data, the remaining residual was simulated with the ensemble learning model. Next, the EL-SP method was applied to interpolate soil potassium contents at the study site. To evaluate the utility of the EL-SP method, we compared its performance with other interpolation methods including universal kriging, inverse distance weighting, ordinary kriging, and ordinary kriging combined geographic information. Results show that EL-SP had a lower mean absolute error and root mean square error than the data produced by the other models tested in this paper. Notably, the EL-SP maps can describe more locally detailed information and more accurate spatial patterns for soil potassium content than the other methods because of the combined use of different types of environmental information; these maps are capable of showing abrupt boundary information for soil potassium content. Furthermore, the EL-SP method not only reduces prediction errors, but it also compliments other environmental information, which makes the spatial interpolation of soil potassium content more reasonable and useful.

  20. An ensemble method based on uninformative variable elimination and mutual information for spectral multivariate calibration

    NASA Astrophysics Data System (ADS)

    Tan, Chao; Wang, Jinyue; Wu, Tong; Qin, Xin; Li, Menglong

    2010-12-01

    Based on the combination of uninformative variable elimination (UVE), bootstrap and mutual information (MI), a simple ensemble algorithm, named ESPLS, is proposed for spectral multivariate calibration (MVC). In ESPLS, those uninformative variables are first removed; and then a preparatory training set is produced by bootstrap, on which a MI spectrum of retained variables is calculated. The variables that exhibit higher MI than a defined threshold form a subspace on which a candidate partial least-squares (PLS) model is constructed. This process is repeated. After a number of candidate models are obtained, a small part of models is picked out to construct an ensemble model by simple/weighted average. Four near/mid-infrared (NIR/MIR) spectral datasets concerning the determination of six components are used to verify the proposed ESPLS. The results indicate that ESPLS is superior to UVEPLS and its combination with MI-based variable selection (SPLS) in terms of both the accuracy and robustness. Besides, from the perspective of end-users, ESPLS does not increase the complexity of a calibration when enhancing its performance.

  1. Reaction Ensemble Molecular Dynamics: Direct Simulation of the Dynamic Equilibrium Properties of Chemically Reacting Mixtures

    DTIC Science & Technology

    2006-09-01

    Therefore, dynamic quantities of reaction mixtures such as the velocity autocorrelation functions and the diffusion coefficients can be accurately...using the virial expression [25]. A standard NVT molecular dynamics method was em- ployed with the equations of motion solved using the Verlet leapfrog...configurational energy, pressure, and species concen- trations) are compared to quantities calculated by the RxMC approach. Second , the dynamic quantities

  2. Molecular Simulation of Shocked Materials Using Reaction Ensemble Monte Carlo: Part 1. Application to Nitrogen Dissociation

    DTIC Science & Technology

    2006-11-01

    constituting the chemically reacting species is conserved. Thermochemical software such as the chemical equilibrium code (12) and Cheetah (13) are...stoichiometric coefficient of species i in reaction j; ξj is the molecular extent of reaction for reaction j; qint,i is the quantum partition function for the...Detonation Properties of PETN. J. Chem. Phys. 1984, 81, 1251. 13. Fried, L. E. Cheetah 3.0 User’s Manual; Lawrence Livermore National Laboratory

  3. Applications of Ensemble-based Data Assimilation Techniques for Aquifer Characterization using Tracer Data at Hanford 300 Area

    SciTech Connect

    Chen, Xingyuan; Hammond, Glenn E.; Murray, Christopher J.; Rockhold, Mark L.; Vermeul, Vincent R.; Zachara, John M.

    2013-10-31

    Subsurface aquifer characterization often involves high parameter dimensionality and requires tremendous computational resources if employing a full Bayesian approach. Ensemble-based data assimilation techniques, including filtering and smoothing, are computationally efficient alternatives. Despite the increasing number of applications of ensemble-based methods in assimilating flow and transport related data for subsurface aquifer charaterization, most are limited to either synthetic studies or two-dimensional problems. In this study, we applied ensemble-based techniques for assimilating field tracer experimental data obtained from the Integrated Field Research Challenge (IFRC) site at the Hanford 300 Area. The forward problem was simulated using the massively-parallel three-dimensional flow and transport code PFLOTRAN to effectively deal with the highly transient flow boundary conditions at the site and to meet the computational demands of ensemble-based methods. This study demonstrates the effectiveness of ensemble-based methods for characterizing a heterogeneous aquifer by sequentially assimilating multiple types of data. The necessity of employing high performance computing is shown to enable increasingly mechanistic non-linear forward simulations to be performed within the data assimilation framework for a complex system with reasonable turnaround time.

  4. In silico prediction of toxicity of non-congeneric industrial chemicals using ensemble learning based modeling approaches

    SciTech Connect

    Singh, Kunwar P. Gupta, Shikha

    2014-03-15

    Ensemble learning approach based decision treeboost (DTB) and decision tree forest (DTF) models are introduced in order to establish quantitative structure–toxicity relationship (QSTR) for the prediction of toxicity of 1450 diverse chemicals. Eight non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals was evaluated using Tanimoto similarity index. Stochastic gradient boosting and bagging algorithms supplemented DTB and DTF models were constructed for classification and function optimization problems using the toxicity end-point in T. pyriformis. Special attention was drawn to prediction ability and robustness of the models, investigated both in external and 10-fold cross validation processes. In complete data, optimal DTB and DTF models rendered accuracies of 98.90%, 98.83% in two-category and 98.14%, 98.14% in four-category toxicity classifications. Both the models further yielded classification accuracies of 100% in external toxicity data of T. pyriformis. The constructed regression models (DTB and DTF) using five descriptors yielded correlation coefficients (R{sup 2}) of 0.945, 0.944 between the measured and predicted toxicities with mean squared errors (MSEs) of 0.059, and 0.064 in complete T. pyriformis data. The T. pyriformis regression models (DTB and DTF) applied to the external toxicity data sets yielded R{sup 2} and MSE values of 0.637, 0.655; 0.534, 0.507 (marine bacteria) and 0.741, 0.691; 0.155, 0.173 (algae). The results suggest for wide applicability of the inter-species models in predicting toxicity of new chemicals for regulatory purposes. These approaches provide useful strategy and robust tools in the screening of ecotoxicological risk or environmental hazard potential of chemicals. - Graphical abstract: Importance of input variables in DTB and DTF classification models for (a) two-category, and (b) four-category toxicity intervals in T. pyriformis data. Generalization and predictive abilities of the

  5. Soft sensor modeling based on variable partition ensemble method for nonlinear batch processes

    NASA Astrophysics Data System (ADS)

    Wang, Li; Chen, Xiangguang; Yang, Kai; Jin, Huaiping

    2017-01-01

    Batch processes are always characterized by nonlinear and system uncertain properties, therefore, the conventional single model may be ill-suited. A local learning strategy soft sensor based on variable partition ensemble method is developed for the quality prediction of nonlinear and non-Gaussian batch processes. A set of input variable sets are obtained by bootstrapping and PMI criterion. Then, multiple local GPR models are developed based on each local input variable set. When a new test data is coming, the posterior probability of each best performance local model is estimated based on Bayesian inference and used to combine these local GPR models to get the final prediction result. The proposed soft sensor is demonstrated by applying to an industrial fed-batch chlortetracycline fermentation process.

  6. Fault Diagnosis of Rotating Machinery Based on an Adaptive Ensemble Empirical Mode Decomposition

    PubMed Central

    Lei, Yaguo; Li, Naipeng; Lin, Jing; Wang, Sizhe

    2013-01-01

    The vibration based signal processing technique is one of the principal tools for diagnosing faults of rotating machinery. Empirical mode decomposition (EMD), as a time-frequency analysis technique, has been widely used to process vibration signals of rotating machinery. But it has the shortcoming of mode mixing in decomposing signals. To overcome this shortcoming, ensemble empirical mode decomposition (EEMD) was proposed accordingly. EEMD is able to reduce the mode mixing to some extent. The performance of EEMD, however, depends on the parameters adopted in the EEMD algorithms. In most of the studies on EEMD, the parameters were selected artificially and subjectively. To solve the problem, a new adaptive ensemble empirical mode decomposition method is proposed in this paper. In the method, the sifting number is adaptively selected, and the amplitude of the added noise changes with the signal frequency components during the decomposition process. The simulation, the experimental and the application results demonstrate that the adaptive EEMD provides the improved results compared with the original EEMD in diagnosing rotating machinery. PMID:24351666

  7. Prognostics of Proton Exchange Membrane Fuel Cells stack using an ensemble of constraints based connectionist networks

    NASA Astrophysics Data System (ADS)

    Javed, Kamran; Gouriveau, Rafael; Zerhouni, Noureddine; Hissel, Daniel

    2016-08-01

    Proton Exchange Membrane Fuel Cell (PEMFC) is considered the most versatile among available fuel cell technologies, which qualify for diverse applications. However, the large-scale industrial deployment of PEMFCs is limited due to their short life span and high exploitation costs. Therefore, ensuring fuel cell service for a long duration is of vital importance, which has led to Prognostics and Health Management of fuel cells. More precisely, prognostics of PEMFC is major area of focus nowadays, which aims at identifying degradation of PEMFC stack at early stages and estimating its Remaining Useful Life (RUL) for life cycle management. This paper presents a data-driven approach for prognostics of PEMFC stack using an ensemble of constraint based Summation Wavelet- Extreme Learning Machine (SW-ELM) models. This development aim at improving the robustness and applicability of prognostics of PEMFC for an online application, with limited learning data. The proposed approach is applied to real data from two different PEMFC stacks and compared with ensembles of well known connectionist algorithms. The results comparison on long-term prognostics of both PEMFC stacks validates our proposition.

  8. Ensemble of One-Class Classifiers for Personal Risk Detection Based on Wearable Sensor Data

    PubMed Central

    Rodríguez, Jorge; Barrera-Animas, Ari Y.; Trejo, Luis A.; Medina-Pérez, Miguel Angel; Monroy, Raúl

    2016-01-01

    This study introduces the One-Class K-means with Randomly-projected features Algorithm (OCKRA). OCKRA is an ensemble of one-class classifiers built over multiple projections of a dataset according to random feature subsets. Algorithms found in the literature spread over a wide range of applications where ensembles of one-class classifiers have been satisfactorily applied; however, none is oriented to the area under our study: personal risk detection. OCKRA has been designed with the aim of improving the detection performance in the problem posed by the Personal RIsk DEtection(PRIDE) dataset. PRIDE was built based on 23 test subjects, where the data for each user were captured using a set of sensors embedded in a wearable band. The performance of OCKRA was compared against support vector machine and three versions of the Parzen window classifier. On average, experimental results show that OCKRA outperformed the other classifiers for at least 0.53% of the area under the curve (AUC). In addition, OCKRA achieved an AUC above 90% for more than 57% of the users. PMID:27690054

  9. Fault diagnosis of rotating machinery based on an adaptive ensemble empirical mode decomposition.

    PubMed

    Lei, Yaguo; Li, Naipeng; Lin, Jing; Wang, Sizhe

    2013-12-09

    The vibration based signal processing technique is one of the principal tools for diagnosing faults of rotating machinery. Empirical mode decomposition (EMD), as a time-frequency analysis technique, has been widely used to process vibration signals of rotating machinery. But it has the shortcoming of mode mixing in decomposing signals. To overcome this shortcoming, ensemble empirical mode decomposition (EEMD) was proposed accordingly. EEMD is able to reduce the mode mixing to some extent. The performance of EEMD, however, depends on the parameters adopted in the EEMD algorithms. In most of the studies on EEMD, the parameters were selected artificially and subjectively. To solve the problem, a new adaptive ensemble empirical mode decomposition method is proposed in this paper. In the method, the sifting number is adaptively selected, and the amplitude of the added noise changes with the signal frequency components during the decomposition process. The simulation, the experimental and the application results demonstrate that the adaptive EEMD provides the improved results compared with the original EEMD in diagnosing rotating machinery.

  10. Ensemble of One-Class Classifiers for Personal Risk Detection Based on Wearable Sensor Data.

    PubMed

    Rodríguez, Jorge; Barrera-Animas, Ari Y; Trejo, Luis A; Medina-Pérez, Miguel Angel; Monroy, Raúl

    2016-09-29

    This study introduces the One-Class K-means with Randomly-projected features Algorithm (OCKRA). OCKRA is an ensemble of one-class classifiers built over multiple projections of a dataset according to random feature subsets. Algorithms found in the literature spread over a wide range of applications where ensembles of one-class classifiers have been satisfactorily applied; however, none is oriented to the area under our study: personal risk detection. OCKRA has been designed with the aim of improving the detection performance in the problem posed by the Personal RIsk DEtection(PRIDE) dataset. PRIDE was built based on 23 test subjects, where the data for each user were captured using a set of sensors embedded in a wearable band. The performance of OCKRA was compared against support vector machine and three versions of the Parzen window classifier. On average, experimental results show that OCKRA outperformed the other classifiers for at least 0.53% of the area under the curve (AUC). In addition, OCKRA achieved an AUC above 90% for more than 57% of the users.

  11. On the structure of crystalline and molten cryolite: Insights from the ab initio molecular dynamics in NpT ensemble

    NASA Astrophysics Data System (ADS)

    Bučko, Tomáš; Šimko, František

    2016-02-01

    Ab initio molecular dynamics simulations in isobaric-isothermal ensemble have been performed to study the low- and the high-temperature crystalline and liquid phases of cryolite. The temperature induced transitions from the low-temperature solid (α) to the high-temperature solid phase (β) and from the phase β to the liquid phase have been simulated using a series of MD runs performed at gradually increasing temperature. The structure of crystalline and liquid phases is analysed in detail and our computational approach is shown to reliably reproduce the available experimental data for a wide range of temperatures. Relatively frequent reorientations of the AlF6 octahedra observed in our simulation of the phase β explain the thermal disorder in positions of the F- ions observed in X-ray diffraction experiments. The isolated AlF63-, AlF52-, AlF4-, as well as the bridged Al 2 Fm 6 - m ionic entities have been identified as the main constituents of cryolite melt. In accord with the previous high-temperature NMR and Raman spectroscopic experiments, the compound AlF5 2 - has been shown to be the most abundant Al-containing species formed in the melt. The characteristic vibrational frequencies for the AlFn 3 - n species in realistic environment have been determined and the computed values have been found to be in a good agreement with experiment.

  12. Deconvoluting Protein (Un)folding Structural Ensembles Using X-Ray Scattering, Nuclear Magnetic Resonance Spectroscopy and Molecular Dynamics Simulation.

    PubMed

    Nasedkin, Alexandr; Marcellini, Moreno; Religa, Tomasz L; Freund, Stefan M; Menzel, Andreas; Fersht, Alan R; Jemth, Per; van der Spoel, David; Davidsson, Jan

    2015-01-01

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

  13. Structural insights for designed alanine-rich helices: Comparing NMR helicity measures and conformational ensembles from molecular dynamics simulation

    PubMed Central

    Song, Kun; Stewart, James M.; Fesinmeyer, R. Matthew

    2013-01-01

    The temperature dependence of helical propensities for the peptides Ac-ZGG-(KAAAA)3X-NH2 (Z = Y or G, X = A, K, and d-Arg) were studied both experimentally and by molecular dynamics simulations. Good agreement is observed in both the absolute helical propensities as well as relative helical content along the sequence; the global minimum on the calculated free energy landscape corresponds to a single α-helical conformation running from K4 – A18 with some terminal fraying, particularly at the C-terminus. Energy component analysis shows that the single helix state has favorable intramolecular electrostatic energy due to hydrogen bonds, and that less-favorable two-helix globular states have favorable solvation energy. The central lysine residues do not appear to increase helicity; however, both experimental and simulation studies show increasing helicity in the series X = Ala → Lys → d-Arg. This C-capping preference was also experimentally confirmed in Ac-(KAAAA)3X-GY-NH2 and (KAAAA)3X-GY-NH2 sequences. The roles of the C-capping groups, and of lysines throughout the sequence, in the MD-derived ensembles are analyzed in detail. PMID:18428207

  14. Massively parallel molecular-dynamics simulation of ice crystallisation and melting: the roles of system size, ensemble, and electrostatics.

    PubMed

    English, Niall J

    2014-12-21

    Ice crystallisation and melting was studied via massively parallel molecular dynamics under periodic boundary conditions, using approximately spherical ice nano-particles (both "isolated" and as a series of heterogeneous "seeds") of varying size, surrounded by liquid water and at a variety of temperatures. These studies were performed for a series of systems ranging in size from ∼1 × 10(6) to 8.6 × 10(6) molecules, in order to establish system-size effects upon the nano-clusters" crystallisation and dissociation kinetics. Both "traditional" four-site and "single-site" and water models were used, with and without formal point charges, dipoles, and electrostatics, respectively. Simulations were carried out in the microcanonical and isothermal-isobaric ensembles, to assess the influence of "artificial" thermo- and baro-statting, and important disparities were observed, which declined upon using larger systems. It was found that there was a dependence upon system size for both ice growth and dissociation, in that larger systems favoured slower growth and more rapid melting, given the lower extent of "communication" of ice nano-crystallites with their periodic replicae in neighbouring boxes. Although the single-site model exhibited less variation with system size vis-à-vis the multiple-site representation with explicit electrostatics, its crystallisation-dissociation kinetics was artificially fast.

  15. Massively parallel molecular-dynamics simulation of ice crystallisation and melting: The roles of system size, ensemble, and electrostatics

    NASA Astrophysics Data System (ADS)

    English, Niall J.

    2014-12-01

    Ice crystallisation and melting was studied via massively parallel molecular dynamics under periodic boundary conditions, using approximately spherical ice nano-particles (both "isolated" and as a series of heterogeneous "seeds") of varying size, surrounded by liquid water and at a variety of temperatures. These studies were performed for a series of systems ranging in size from ˜1 × 106 to 8.6 × 106 molecules, in order to establish system-size effects upon the nano-clusters" crystallisation and dissociation kinetics. Both "traditional" four-site and "single-site" and water models were used, with and without formal point charges, dipoles, and electrostatics, respectively. Simulations were carried out in the microcanonical and isothermal-isobaric ensembles, to assess the influence of "artificial" thermo- and baro-statting, and important disparities were observed, which declined upon using larger systems. It was found that there was a dependence upon system size for both ice growth and dissociation, in that larger systems favoured slower growth and more rapid melting, given the lower extent of "communication" of ice nano-crystallites with their periodic replicae in neighbouring boxes. Although the single-site model exhibited less variation with system size vis-à-vis the multiple-site representation with explicit electrostatics, its crystallisation-dissociation kinetics was artificially fast.

  16. Single-molecule imaging of non-equilibrium molecular ensembles on the millisecond timescale

    PubMed Central

    Juette, Manuel F.; Terry, Daniel S.; Wasserman, Michael R.; Altman, Roger B.; Zhou, Zhou; Zhao, Hong; Blanchard, Scott C.

    2016-01-01

    Molecular recognition is often driven by transient processes beyond the reach of detection. Single-molecule fluorescence microscopy methods are uniquely suited for detecting such non-accumulating intermediates, yet achieving the time resolution and statistics to realize this potential has proven challenging. Here, we present a single-molecule fluorescence resonance energy transfer (smFRET) imaging and analysis platform leveraging advances in scientific complementary metal-oxide semiconductor (sCMOS) detectors that enable the imaging of more than 10,000 individual molecules simultaneously at millisecond rates. The utility of this advance is demonstrated through quantitative measurements of previously obscured processes relevant to the fidelity mechanism in protein synthesis. PMID:26878382

  17. Electrical characterization of ensemble of GaN nanowires grown by the molecular beam epitaxy technique

    NASA Astrophysics Data System (ADS)

    Kolkovsky, Vl.; Zytkiewicz, Z. R.; Sobanska, M.; Klosek, K.

    2013-08-01

    High quality Schottky contacts are formed on GaN nanowires (NWs) structures grown by the molecular beam epitaxy technique on Si(111) substrate. The current-voltage characteristics show the rectification ratio of about 103 and the leakage current of about 10-4 A/cm2 at room temperature. From the capacitance-voltage measurements the free carrier concentration in GaN NWs is determined as about 1016 cm-3. Two deep levels (H200 and E280) are found in the structures containing GaN NWs. H200 is attributed to an extended defect located at the interface between the substrate and SiNx or near the sidewalls at the bottom of the NWs whereas E280 is tentatively assigned to a gallium-vacancy- or nitrogen interstitials-related defect.

  18. Hidden Conformation Events in DNA Base Extrusions: A Generalized Ensemble Path Optimization and Equilibrium Simulation Study

    PubMed Central

    Cao, Liaoran; Lv, Chao; Yang, Wei

    2013-01-01

    DNA base extrusion is a crucial component of many biomolecular processes. Elucidating how bases are selectively extruded from the interiors of double-strand DNAs is pivotal to accurately understanding and efficiently sampling this general type of conformational transitions. In this work, the on-the-path random walk (OTPRW) method, which is the first generalized ensemble sampling scheme designed for finite-temperature-string path optimizations, was improved and applied to obtain the minimum free energy path (MFEP) and the free energy profile of a classical B-DNA major-groove base extrusion pathway. Along the MFEP, an intermediate state and the corresponding transition state were located and characterized. The MFEP result suggests that a base-plane-elongation event rather than the commonly focused base-flipping event is dominant in the transition state formation portion of the pathway; and the energetic penalty at the transition state is mainly introduced by the stretching of the Watson-Crick base pair. Moreover to facilitate the essential base-plane-elongation dynamics, the surrounding environment of the flipped base needs to be intimately involved. Further taking the advantage of the extended-dynamics nature of the OTPRW Hamiltonian, an equilibrium generalized ensemble simulation was performed along the optimized path; and based on the collected samples, several base-flipping (opening) angle collective variables were evaluated. In consistence with the MFEP result, the collective variable analysis result reveals that none of these commonly employed flipping (opening) angles alone can adequately represent the base extrusion pathway, especially in the pre-transition-state portion. As further revealed by the collective variable analysis, the base-pairing partner of the extrusion target undergoes a series of in-plane rotations to facilitate the base-plane-elongation dynamics. A base-plane rotation angle is identified to be a possible reaction coordinate to represent

  19. Comparison of ensemble post-processing approaches, based on empirical and dynamical error modelisation of rainfall-runoff model forecasts

    NASA Astrophysics Data System (ADS)

    Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.

    2012-04-01

    In the context of a national energy company (EDF : Electricité de France), hydro-meteorological forecasts are necessary to ensure safety and security of installations, meet environmental standards and improve water ressources management and decision making. Hydrological ensemble forecasts allow a better representation of meteorological and hydrological forecasts uncertainties and improve human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. An operational hydrological ensemble forecasting chain has been developed at EDF since 2008 and is being used since 2010 on more than 30 watersheds in France. This ensemble forecasting chain is characterized ensemble pre-processing (rainfall and temperature) and post-processing (streamflow), where a large human expertise is solicited. The aim of this paper is to compare 2 hydrological ensemble post-processing methods developed at EDF in order improve ensemble forecasts reliability (similar to Monatanari &Brath, 2004; Schaefli et al., 2007). The aim of the post-processing methods is to dress hydrological ensemble forecasts with hydrological model uncertainties, based on perfect forecasts. The first method (called empirical approach) is based on a statistical modelisation of empirical error of perfect forecasts, by streamflow sub-samples of quantile class and lead-time. The second method (called dynamical approach) is based on streamflow sub-samples of quantile class and streamflow variation, and lead-time. On a set of 20 watersheds used for operational forecasts, results show that both approaches are necessary to ensure a good post-processing of hydrological ensemble, allowing a good improvement of reliability, skill and sharpness of ensemble forecasts. The comparison of the empirical and dynamical approaches shows the limits of the empirical approach which is not able to take into account hydrological

  20. Ensemble Methods

    NASA Astrophysics Data System (ADS)

    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

  1. Compressed sensing of hyperspectral images based on scrambled block Hadamard ensemble

    NASA Astrophysics Data System (ADS)

    Wang, Li; Feng, Yan

    2016-11-01

    A fast measurement matrix based on scrambled block Hadamard ensemble for compressed sensing (CS) of hyperspectral images (HSI) is investigated. The proposed measurement matrix offers several attractive features. First, the proposed measurement matrix possesses Gaussian behavior, which illustrates that the matrix is universal and requires a near-optimal number of samples for exact reconstruction. In addition, it could be easily implemented in the optical domain due to its integer-valued elements. More importantly, the measurement matrix only needs small memory for storage in the sampling process. Experimental results on HSIs reveal that the reconstruction performance of the proposed measurement matrix is comparable or better than Gaussian matrix and Bernoulli matrix using different reconstruction algorithms while consuming less computational time. The proposed matrix could be used in CS of HSI, which would save the storage memory on board, improve the sampling efficiency, and ameliorate the reconstruction quality.

  2. A Human ECG Identification System Based on Ensemble Empirical Mode Decomposition

    PubMed Central

    Zhao, Zhidong; Yang, Lei; Chen, Diandian; Luo, Yi

    2013-01-01

    In this paper, a human electrocardiogram (ECG) identification system based on ensemble empirical mode decomposition (EEMD) is designed. A robust preprocessing method comprising noise elimination, heartbeat normalization and quality measurement is proposed to eliminate the effects of noise and heart rate variability. The system is independent of the heart rate. The ECG signal is decomposed into a number of intrinsic mode functions (IMFs) and Welch spectral analysis is used to extract the significant heartbeat signal features. Principal component analysis is used reduce the dimensionality of the feature space, and the K-nearest neighbors (K-NN) method is applied as the classifier tool. The proposed human ECG identification system was tested on standard MIT-BIH ECG databases: the ST change database, the long-term ST database, and the PTB database. The system achieved an identification accuracy of 95% for 90 subjects, demonstrating the effectiveness of the proposed method in terms of accuracy and robustness. PMID:23698274

  3. Inferring Alcoholism SNPs and Regulatory Chemical Compounds Based on Ensemble Bayesian Network.

    PubMed

    Chen, Huan; Sun, Jiatong; Jiang, Hong; Wang, Xianyue; Wu, Lingxiang; Wu, Wei; Wang, Qh

    2016-12-20

    The disturbance of consciousness is one of the most common symptoms of those have alcoholism and may cause disability and mortality. Previous studies indicated that several single nucleotide polymorphisms (SNP) increase the susceptibility of alcoholism. In this study, we utilized the Ensemble Bayesian Network (EBN) method to identify causal SNPs of alcoholism based on the verified GAW14 data. Thirteen out of eighteen SNPs directly connected with alcoholism were found concordance with potential risk regions of alcoholism in OMIM database. As a number of SNPs were found contributing to alteration on gene expression, known as expression quantitative trait loci (eQTLs), we further sought to identify chemical compounds acting as regulators of alcoholism genes captured by causal SNPs. Chloroprene and valproic acid were identified as the expression regulators for genes C11orf66 and SALL3 which were captured by alcoholism SNPs, respectively.

  4. Data-worth analysis through probabilistic collocation-based Ensemble Kalman Filter

    NASA Astrophysics Data System (ADS)

    Dai, Cheng; Xue, Liang; Zhang, Dongxiao; Guadagnini, Alberto

    2016-09-01

    We propose a new and computationally efficient data-worth analysis and quantification framework keyed to the characterization of target state variables in groundwater systems. We focus on dynamically evolving plumes of dissolved chemicals migrating in randomly heterogeneous aquifers. An accurate prediction of the detailed features of solute plumes requires collecting a substantial amount of data. Otherwise, constraints dictated by the availability of financial resources and ease of access to the aquifer system suggest the importance of assessing the expected value of data before these are actually collected. Data-worth analysis is targeted to the quantification of the impact of new potential measurements on the expected reduction of predictive uncertainty based on a given process model. Integration of the Ensemble Kalman Filter method within a data-worth analysis framework enables us to assess data worth sequentially, which is a key desirable feature for monitoring scheme design in a contaminant transport scenario. However, it is remarkably challenging because of the (typically) high computational cost involved, considering that repeated solutions of the inverse problem are required. As a computationally efficient scheme, we embed in the data-worth analysis framework a modified version of the Probabilistic Collocation Method-based Ensemble Kalman Filter proposed by Zeng et al. (2011) so that we take advantage of the ability to assimilate data sequentially in time through a surrogate model constructed via the polynomial chaos expansion. We illustrate our approach on a set of synthetic scenarios involving solute migrating in a two-dimensional random permeability field. Our results demonstrate the computational efficiency of our approach and its ability to quantify the impact of the design of the monitoring network on the reduction of uncertainty associated with the characterization of a migrating contaminant plume.

  5. Constructing Better Classifier Ensemble Based on Weighted Accuracy and Diversity Measure

    PubMed Central

    Chao, Lidia S.

    2014-01-01

    A weighted accuracy and diversity (WAD) method is presented, a novel measure used to evaluate the quality of the classifier ensemble, assisting in the ensemble selection task. The proposed measure is motivated by a commonly accepted hypothesis; that is, a robust classifier ensemble should not only be accurate but also different from every other member. In fact, accuracy and diversity are mutual restraint factors; that is, an ensemble with high accuracy may have low diversity, and an overly diverse ensemble may negatively affect accuracy. This study proposes a method to find the balance between accuracy and diversity that enhances the predictive ability of an ensemble for unknown data. The quality assessment for an ensemble is performed such that the final score is achieved by computing the harmonic mean of accuracy and diversity, where two weight parameters are used to balance them. The measure is compared to two representative measures, Kappa-Error and GenDiv, and two threshold measures that consider only accuracy or diversity, with two heuristic search algorithms, genetic algorithm, and forward hill-climbing algorithm, in ensemble selection tasks performed on 15 UCI benchmark datasets. The empirical results demonstrate that the WAD measure is superior to others in most cases. PMID:24672402

  6. Ensemble Models

    EPA Science Inventory

    Ensemble forecasting has been used for operational numerical weather prediction in the United States and Europe since the early 1990s. An ensemble of weather or climate forecasts is used to characterize the two main sources of uncertainty in computer models of physical systems: ...

  7. Polypeptides Based Molecular Electronics

    DTIC Science & Technology

    2008-10-06

    can be nanoengineer/ nanoassemble individual building blocks at the molecular level, atom by atom, to form conducting channel towards realization of...properties of the self-assembled interconnects are characterized as well. These peptides can be nanoengineer/ nanoassemble individual building blocks at

  8. An exact approach for studying cargo transport by an ensemble of molecular motors

    PubMed Central

    2013-01-01

    Background Intracellular transport is crucial for many cellular processes where a large fraction of the cargo is transferred by motor-proteins over a network of microtubules. Malfunctions in the transport mechanism underlie a number of medical maladies. Existing methods for studying how motor-proteins coordinate the transfer of a shared cargo over a microtubule are either analytical or are based on Monte-Carlo simulations. Approaches that yield analytical results, while providing unique insights into transport mechanism, make simplifying assumptions, where a detailed characterization of important transport modalities is difficult to reach. On the other hand, Monte-Carlo based simulations can incorporate detailed characteristics of the transport mechanism; however, the quality of the results depend on the number and quality of simulation runs used in arriving at results. Here, for example, it is difficult to simulate and study rare-events that can trigger abnormalities in transport. Results In this article, a semi-analytical methodology that determines the probability distribution function of motor-protein behavior in an exact manner is developed. The method utilizes a finite-dimensional projection of the underlying infinite-dimensional Markov model, which retains the Markov property, and enables the detailed and exact determination of motor configurations, from which meaningful inferences on transport characteristics of the original model can be derived. Conclusions Under this novel probabilistic approach new insights about the mechanisms of action of these proteins are found, suggesting hypothesis about their behavior and driving the design and realization of new experiments. The advantages provided in accuracy and efficiency make it possible to detect rare events in the motor protein dynamics, that could otherwise pass undetected using standard simulation methods. In this respect, the model has allowed to provide a possible explanation for possible mechanisms

  9. The impact of Ensemble-based data assimilation on the predictability of landfalling Hurricane Katrina (2005)

    NASA Astrophysics Data System (ADS)

    Zhang, H.; Pu, Z.

    2012-12-01

    Accurate forecasts of the track, intensity and structure of a landfalling hurricane can save lives and mitigate social impacts. Over the last two decades, significant improvements have been achieved for hurricane forecasts. However, only a few of studies have emphasized landfalling hurricanes. Specifically, there are difficulties in predicting hurricane landfall due to the uncertainties in representing the atmospheric near-surface conditions in numerical weather prediction models, the complicated interaction between the atmosphere and the ocean, and the multiple-scale dynamical and physical processes accompanying storm development. In this study, the impact of the assimilation of conventional and satellite observations on the predictability of landfalling hurricanes is examined by using a mesoscale community Weather Research and Forecasting (WRF) model and an ensemble Kalman filter developed by NCAR Data Assimilation Research Testbed (DART). Hurricane Katrina (2005) was chosen as a case study since it was one of the deadliest disasters in US history. The minimum sea level pressure from the best track, QuikScat ocean surface wind vectors, surface mesonet observations, airborne Doppler radar derived wind components and available conventional observations are assimilated in a series of experiments to examine the data impacts on the predictability of Hurricane Katrina. The analyses and forecasts show that ensemble-based data assimilation significantly improves the forecast of Hurricane Katrina. The assimilation improves the track forecast through modifying the storm structures and related environmental fields. Cyclonic increments are clearly seen in vorticity and wind analyses. Temperature and humidity fields are also modified by the data assimilation. The changes in relevant fields help organize the structure of the storm, intensify the circulation, and result in a positive impact on the evolution of the storm in both analyses and forecasts. The forecasts in the

  10. Comparison of ensemble-based state and parameter estimation methods for soil moisture data assimilation

    NASA Astrophysics Data System (ADS)

    Chen, Weijing; Huang, Chunlin; Shen, Huanfeng; Li, Xin

    2015-12-01

    Model parameters are a source of uncertainty that can easily cause systematic deviation and significantly affect the accuracy of soil moisture generation in assimilation systems. This study addresses the issue of retrieving model parameters related to soil moisture via the simultaneous estimation of states and parameters based on the Common Land Model (CoLM). The state-parameter estimation algorithms AEnKF (Augmented Ensemble Kalman Filter), DEnKF (Dual Ensemble Kalman Filter) and SODA (Simultaneous optimization and data assimilation) are entirely implemented within an EnKF framework to investigate how the three algorithms can correct model parameters and improve the accuracy of soil moisture estimation. The analysis is illustrated by assimilating the surface soil moisture levels from varying observation intervals using data from Mongolian plateau sites. Furthermore, a radiation transfer model is introduced as an observation operator to analyze the influence of brightness temperature assimilation on states and parameters that are estimated at different microwave signal frequencies. Three cases were analyzed for both soil moisture and brightness temperature assimilation, focusing on the progressive incorporation of parameter uncertainty, forcing data uncertainty and model uncertainty. It has been demonstrated that EnKF is outperformed by all other methods, as it consistently maintains a bias. State-parameter estimation algorithms can provide a more accurate estimation of soil moisture than EnKF. AEnKF is the most robust method, with the lowest RMSE values for retrieving states and parameters dealing only with parameter uncertainty, but it possesses disadvantages related to increasing sources of uncertainty and decreasing numbers of observations. SODA performs well under the complex situations in which DEnKF shows slight disadvantages in terms of statistical indicators; however, the former consumes far more memory and time than the latter.

  11. Bayesian model aggregation for ensemble-based estimates of protein pKa values

    SciTech Connect

    Gosink, Luke J.; Hogan, Emilie A.; Pulsipher, Trenton C.; Baker, Nathan A.

    2014-03-01

    This paper investigates an ensemble-based technique called Bayesian Model Averaging (BMA) to improve the performance of protein amino acid p$K_a$ predictions. Structure-based p$K_a$ calculations play an important role in the mechanistic interpretation of protein structure and are also used to determine a wide range of protein properties. A diverse set of methods currently exist for p$K_a$ prediction, ranging from empirical statistical models to {\\it ab initio} quantum mechanical approaches. However, each of these methods are based on a set of assumptions that have inherent bias and sensitivities that can effect a model's accuracy and generalizability for p$K_a$ prediction in complicated biomolecular systems. We use BMA to combine eleven diverse prediction methods that each estimate pKa values of amino acids in staphylococcal nuclease. These methods are based on work conducted for the pKa Cooperative and the pKa measurements are based on experimental work conducted by the Garc{\\'i}a-Moreno lab. Our study demonstrates that the aggregated estimate obtained from BMA outperforms all individual prediction methods in our cross-validation study with improvements from 40-70\\% over other method classes. This work illustrates a new possible mechanism for improving the accuracy of p$K_a$ prediction and lays the foundation for future work on aggregate models that balance computational cost with prediction accuracy.

  12. Application of NARR-based NLDAS Ensemble Simulations to Continental-Scale Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Alonge, C. J.; Cosgrove, B. A.

    2008-05-01

    Government estimates indicate that droughts cause billions of dollars of damage to agricultural interests each year. More effective identification of droughts would directly benefit decision makers, and would allow for the more efficient allocation of resources that might mitigate the event. Land data assimilation systems, with their high quality representations of soil moisture, present an ideal platform for drought monitoring, and offer many advantages over traditional modeling systems. The recently released North American Regional Reanalysis (NARR) covers the NLDAS domain and provides all fields necessary to force the NLDAS for 27 years. This presents an ideal opportunity to combine NARR and NLDAS resources into an effective real-time drought monitor. Toward this end, our project seeks to validate and explore the NARR's suitability as a base for drought monitoring applications - both in terms of data set length and accuracy. Along the same lines, the project will examine the impact of the use of different (longer) LDAS model climatologies on drought monitoring, and will explore the advantages of ensemble simulations versus single model simulations in drought monitoring activities. We also plan to produce a NARR- and observation-based high quality 27 year, 1/8th degree, 3-hourly, land surface and meteorological forcing data sets. An investigation of the best way to force an LDAS-type system will also be made, with traditional NLDAS and NLDASE forcing options explored. This presentation will focus on an overview of the drought monitoring project, and will include a summary of recent progress. Developments include the generation of forcing data sets, ensemble LSM output, and production of model-based drought indices over the entire NLDAS domain. Project forcing files use 32km NARR model output as a data backbone, and include observed precipitation (blended CPC gauge, PRISM gauge, Stage II, HPD, and CMORPH) and a GOES-based bias correction of downward solar

  13. Generic Learning-Based Ensemble Framework for Small Sample Size Face Recognition in Multi-Camera Networks.

    PubMed

    Zhang, Cuicui; Liang, Xuefeng; Matsuyama, Takashi

    2014-12-08

    Multi-camera networks have gained great interest in video-based surveillance systems for security monitoring, access control, etc. Person re-identification is an essential and challenging task in multi-camera networks, which aims to determine if a given individual has already appeared over the camera network. Individual recognition often uses faces as a trial and requires a large number of samples during the training phrase. This is difficult to fulfill due to the limitation of the camera hardware system and the unconstrained image capturing conditions. Conventional face recognition algorithms often encounter the "small sample size" (SSS) problem arising from the small number of training samples compared to the high dimensionality of the sample space. To overcome this problem, interest in the combination of multiple base classifiers has sparked research efforts in ensemble methods. However, existing ensemble methods still open two questions: (1) how to define diverse base classifiers from the small data; (2) how to avoid the diversity/accuracy dilemma occurring during ensemble. To address these problems, this paper proposes a novel generic learning-based ensemble framework, which augments the small data by generating new samples based on a generic distribution and introduces a tailored 0-1 knapsack algorithm to alleviate the diversity/accuracy dilemma. More diverse base classifiers can be generated from the expanded face space, and more appropriate base classifiers are selected for ensemble. Extensive experimental results on four benchmarks demonstrate the higher ability of our system to cope with the SSS problem compared to the state-of-the-art system.

  14. Investigating the Utility of Oblique Tree-Based Ensembles for the Classification of Hyperspectral Data

    PubMed Central

    Poona, Nitesh; van Niekerk, Adriaan; Ismail, Riyad

    2016-01-01

    Ensemble classifiers are being widely used for the classification of spectroscopic data. In this regard, the random forest (RF) ensemble has been successfully applied in an array of applications, and has proven to be robust in handling high dimensional data. More recently, several variants of the traditional RF algorithm including rotation forest (rotF) and oblique random forest (oRF) have been applied to classifying high dimensional data. In this study we compare the traditional RF, rotF, and oRF (using three different splitting rules, i.e., ridge regression, partial least squares, and support vector machine) for the classification of healthy and infected Pinus radiata seedlings using high dimensional spectroscopic data. We further test the robustness of these five ensemble classifiers to reduced spectral resolution by spectral resampling (binning) of the original spectral bands. The results showed that the three oblique random forest ensembles outperformed both the traditional RF and rotF ensembles. Additionally, the rotF ensemble proved to be the least robust of the five ensembles tested. Spectral resampling of the original bands provided mixed results. Nevertheless, the results demonstrate that using spectral resampled bands is a promising approach to classifying asymptomatic stress in Pinus radiata seedlings. PMID:27854290

  15. Estimating Parameters in Real-Time Under Changing Conditions Via the Ensemble Kalman Filter Based Method

    NASA Astrophysics Data System (ADS)

    Meng, S.; Xie, X.

    2014-12-01

    Hydrological model performance is usually not as acceptable as expected due to limited measurements and imperfect parameterization which is attributable to the uncertainties from model parameters and model structures. In applications, a general assumption is hold that model parameters are constant in a stationary condition during the simulation period, and the parameters are generally prescribed though calibration with observed data. In reality, but the model parameters related to the physical or conceptual characteristics of a catchment will travel in nonstationary conditions in response to climate transition and land use alteration. The travels or changes of parameters are especially evident for long-term hydrological simulations. Therefore, the assumption of using constant parameters under nonstationary condition is inappropriate, and it will deliver errors from the parameters to the outputs during the simulation and prediction. Even though a few of studies have acknowledged the parameter travel or change, little attention has been paid on the estimation of changing parameters. In this study, we employ an ensemble Kalman filter (EnKF) based method to trace parameter changes in real time. Through synthetic experiments, the capability of the EnKF-based is demonstrated by assimilating runoff observations into a rainfall-runoff model, i.e., the Xinanjing Model. In addition to the stationary condition, three typical nonstationary conditions are considered, i.e., the leap, linear and Ω-shaped transitions. To examine the robustness of the method, different errors from rainfall input, modelling and observations are investigated. The shuffled complex evolution (SCE-UA) algorithm is applied under the same conditions to make a comparison. The results show that the EnKF-based method is capable of capturing the general pattern of the parameter travels even for high levels of uncertainties. It provides better estimates than the SCE-UA method does by taking advantages of real

  16. Uncertainty analysis of neural network based flood forecasting models: An ensemble based approach for constructing prediction interval

    NASA Astrophysics Data System (ADS)

    Kasiviswanathan, K.; Sudheer, K.

    2013-05-01

    Artificial neural network (ANN) based hydrologic models have gained lot of attention among water resources engineers and scientists, owing to their potential for accurate prediction of flood flows as compared to conceptual or physics based hydrologic models. The ANN approximates the non-linear functional relationship between the complex hydrologic variables in arriving at the river flow forecast values. Despite a large number of applications, there is still some criticism that ANN's point prediction lacks in reliability since the uncertainty of predictions are not quantified, and it limits its use in practical applications. A major concern in application of traditional uncertainty analysis techniques on neural network framework is its parallel computing architecture with large degrees of freedom, which makes the uncertainty assessment a challenging task. Very limited studies have considered assessment of predictive uncertainty of ANN based hydrologic models. In this study, a novel method is proposed that help construct the prediction interval of ANN flood forecasting model during calibration itself. The method is designed to have two stages of optimization during calibration: at stage 1, the ANN model is trained with genetic algorithm (GA) to obtain optimal set of weights and biases vector, and during stage 2, the optimal variability of ANN parameters (obtained in stage 1) is identified so as to create an ensemble of predictions. During the 2nd stage, the optimization is performed with multiple objectives, (i) minimum residual variance for the ensemble mean, (ii) maximum measured data points to fall within the estimated prediction interval and (iii) minimum width of prediction interval. The method is illustrated using a real world case study of an Indian basin. The method was able to produce an ensemble that has an average prediction interval width of 23.03 m3/s, with 97.17% of the total validation data points (measured) lying within the interval. The derived

  17. An Approach for Identifying Cytokines Based on a Novel Ensemble Classifier

    PubMed Central

    Zou, Quan; Wang, Zhen; Guan, Xinjun; Liu, Bin; Wu, Yunfeng; Lin, Ziyu

    2013-01-01

    Biology is meaningful and important to identify cytokines and investigate their various functions and biochemical mechanisms. However, several issues remain, including the large scale of benchmark datasets, serious imbalance of data, and discovery of new gene families. In this paper, we employ the machine learning approach based on a novel ensemble classifier to predict cytokines. We directly selected amino acids sequences as research objects. First, we pretreated the benchmark data accurately. Next, we analyzed the physicochemical properties and distribution of whole amino acids and then extracted a group of 120-dimensional (120D) valid features to represent sequences. Third, in the view of the serious imbalance in benchmark datasets, we utilized a sampling approach based on the synthetic minority oversampling technique algorithm and K-means clustering undersampling algorithm to rebuild the training set. Finally, we built a library for dynamic selection and circulating combination based on clustering (LibD3C) and employed the new training set to realize cytokine classification. Experiments showed that the geometric mean of sensitivity and specificity obtained through our approach is as high as 93.3%, which proves that our approach is effective for identifying cytokines. PMID:24027761

  18. Surrogate model based iterative ensemble smoother for subsurface flow data assimilation

    NASA Astrophysics Data System (ADS)

    Chang, Haibin; Liao, Qinzhuo; Zhang, Dongxiao

    2017-02-01

    Subsurface geological formation properties often involve some degree of uncertainty. Thus, for most conditions, uncertainty quantification and data assimilation are necessary for predicting subsurface flow. The surrogate model based method is one common type of uncertainty quantification method, in which a surrogate model is constructed for approximating the relationship between model output and model input. Based on the prediction ability, the constructed surrogate model can be utilized for performing data assimilation. In this work, we develop an algorithm for implementing an iterative ensemble smoother (ES) using the surrogate model. We first derive an iterative ES scheme using a regular routine. In order to utilize surrogate models, we then borrow the idea of Chen and Oliver (2013) to modify the Hessian, and further develop an independent parameter based iterative ES formula. Finally, we establish the algorithm for the implementation of iterative ES using surrogate models. Two surrogate models, the PCE surrogate and the interpolation surrogate, are introduced for illustration. The performances of the proposed algorithm are tested by synthetic cases. The results show that satisfactory data assimilation results can be obtained by using surrogate models that have sufficient accuracy.

  19. An efficient tree classifier ensemble-based approach for pedestrian detection.

    PubMed

    Xu, Yanwu; Cao, Xianbin; Qiao, Hong

    2011-02-01

    Classification-based pedestrian detection systems (PDSs) are currently a hot research topic in the field of intelligent transportation. A PDS detects pedestrians in real time on moving vehicles. A practical PDS demands not only high detection accuracy but also high detection speed. However, most of the existing classification-based approaches mainly seek for high detection accuracy, while the detection speed is not purposely optimized for practical application. At the same time, the performance, particularly the speed, is primarily tuned based on experiments without theoretical foundations, leading to a long training procedure. This paper starts with measuring and optimizing detection speed, and then a practical classification-based pedestrian detection solution with high detection speed and training speed is described. First, an extended classification/detection speed metric, named feature-per-object (fpo), is proposed to measure the detection speed independently from execution. Then, an fpo minimization model with accuracy constraints is formulated based on a tree classifier ensemble, where the minimum fpo can guarantee the highest detection speed. Finally, the minimization problem is solved efficiently by using nonlinear fitting based on radial basis function neural networks. In addition, the optimal solution is directly used to instruct classifier training; thus, the training speed could be accelerated greatly. Therefore, a rapid and accurate classification-based detection technique is proposed for the PDS. Experimental results on urban traffic videos show that the proposed method has a high detection speed with an acceptable detection rate and a false-alarm rate for onboard detection; moreover, the training procedure is also very fast.

  20. Toward an Operational Particle Filter-Based Ensemble Data Assimilation System

    DTIC Science & Technology

    2014-09-22

    Monte Carlo (MCMC) algorithm to examine the strengths and limitations of ensemble data assimilation algorithms, when applied to estimation of...subject to potentially limiting assumptions about these probabil ities (e.g., Gaussian). By contrast, Markov chain Monte Carlo (MCMC) algorithms...H. Bishop, 2012: Nonlinear parameter estimation: Comparison of an Ensemble Kalman Smoother with a Markov chain Monte Carlo algorithm. Mon. Wea. Rev

  1. Multiple time step molecular dynamics in the optimized isokinetic ensemble steered with the molecular theory of solvation: Accelerating with advanced extrapolation of effective solvation forces

    SciTech Connect

    Omelyan, Igor E-mail: omelyan@icmp.lviv.ua; Kovalenko, Andriy

    2013-12-28

    We develop efficient handling of solvation forces in the multiscale method of multiple time step molecular dynamics (MTS-MD) of a biomolecule steered by the solvation free energy (effective solvation forces) obtained from the 3D-RISM-KH molecular theory of solvation (three-dimensional reference interaction site model complemented with the Kovalenko-Hirata closure approximation). To reduce the computational expenses, we calculate the effective solvation forces acting on the biomolecule by using advanced solvation force extrapolation (ASFE) at inner time steps while converging the 3D-RISM-KH integral equations only at large outer time steps. The idea of ASFE consists in developing a discrete non-Eckart rotational transformation of atomic coordinates that minimizes the distances between the atomic positions of the biomolecule at different time moments. The effective solvation forces for the biomolecule in a current conformation at an inner time step are then extrapolated in the transformed subspace of those at outer time steps by using a modified least square fit approach applied to a relatively small number of the best force-coordinate pairs. The latter are selected from an extended set collecting the effective solvation forces obtained from 3D-RISM-KH at outer time steps over a broad time interval. The MTS-MD integration with effective solvation forces obtained by converging 3D-RISM-KH at outer time steps and applying ASFE at inner time steps is stabilized by employing the optimized isokinetic Nosé-Hoover chain (OIN) ensemble. Compared to the previous extrapolation schemes used in combination with the Langevin thermostat, the ASFE approach substantially improves the accuracy of evaluation of effective solvation forces and in combination with the OIN thermostat enables a dramatic increase of outer time steps. We demonstrate on a fully flexible model of alanine dipeptide in aqueous solution that the MTS-MD/OIN/ASFE/3D-RISM-KH multiscale method of molecular dynamics

  2. Multiple time step molecular dynamics in the optimized isokinetic ensemble steered with the molecular theory of solvation: Accelerating with advanced extrapolation of effective solvation forces

    NASA Astrophysics Data System (ADS)

    Omelyan, Igor; Kovalenko, Andriy

    2013-12-01

    We develop efficient handling of solvation forces in the multiscale method of multiple time step molecular dynamics (MTS-MD) of a biomolecule steered by the solvation free energy (effective solvation forces) obtained from the 3D-RISM-KH molecular theory of solvation (three-dimensional reference interaction site model complemented with the Kovalenko-Hirata closure approximation). To reduce the computational expenses, we calculate the effective solvation forces acting on the biomolecule by using advanced solvation force extrapolation (ASFE) at inner time steps while converging the 3D-RISM-KH integral equations only at large outer time steps. The idea of ASFE consists in developing a discrete non-Eckart rotational transformation of atomic coordinates that minimizes the distances between the atomic positions of the biomolecule at different time moments. The effective solvation forces for the biomolecule in a current conformation at an inner time step are then extrapolated in the transformed subspace of those at outer time steps by using a modified least square fit approach applied to a relatively small number of the best force-coordinate pairs. The latter are selected from an extended set collecting the effective solvation forces obtained from 3D-RISM-KH at outer time steps over a broad time interval. The MTS-MD integration with effective solvation forces obtained by converging 3D-RISM-KH at outer time steps and applying ASFE at inner time steps is stabilized by employing the optimized isokinetic Nosé-Hoover chain (OIN) ensemble. Compared to the previous extrapolation schemes used in combination with the Langevin thermostat, the ASFE approach substantially improves the accuracy of evaluation of effective solvation forces and in combination with the OIN thermostat enables a dramatic increase of outer time steps. We demonstrate on a fully flexible model of alanine dipeptide in aqueous solution that the MTS-MD/OIN/ASFE/3D-RISM-KH multiscale method of molecular dynamics

  3. Plasmon-enhanced sensitivity of spin-based sensors based on a diamond ensemble of nitrogen vacancy color centers.

    PubMed

    Guo, Hao; Chen, Yulei; Wu, Dajin; Zhao, Rui; Tang, Jun; Ma, Zongmin; Xue, Chenyang; Zhang, Wendong; Liu, Jun

    2017-02-01

    A method for enhancement of the sensitivity of a spin sensor based on an ensemble of nitrogen vacancy (NV) color centers was demonstrated. Gold nanoparticles (NPs) were deposited on the bulk diamond, which had NV centers distributed on its surface. The experimental results demonstrate that, when using this simple method, plasmon enhancement of the deposited gold NPs produces an improvement of ∼10 times in the quantum efficiency and has also improved the signal-to-noise ratio by approximately ∼2.5 times. It was also shown that more electrons participated in the spin sensing process, leading to an improvement in the sensitivity of approximately seven times; this has been proved by Rabi oscillation and optical detection of magnetic resonance (ODMR) measurements. The proposed method has proved to be a more efficient way to design an ensemble of NV centers-based sensors; because the result increases in the number of NV centers, the quantum efficiency and the contrast ratio could greatly increase the device's sensitivity.

  4. Seasonal drought ensemble predictions based on multiple climate models in the upper Han River Basin, China

    NASA Astrophysics Data System (ADS)

    Ma, Feng; Ye, Aizhong; Duan, Qingyun

    2017-03-01

    An experimental seasonal drought forecasting system is developed based on 29-year (1982-2010) seasonal meteorological hindcasts generated by the climate models from the North American Multi-Model Ensemble (NMME) project. This system made use of a bias correction and spatial downscaling method, and a distributed time-variant gain model (DTVGM) hydrologic model. DTVGM was calibrated using observed daily hydrological data and its streamflow simulations achieved Nash-Sutcliffe efficiency values of 0.727 and 0.724 during calibration (1978-1995) and validation (1996-2005) periods, respectively, at the Danjiangkou reservoir station. The experimental seasonal drought forecasting system (known as NMME-DTVGM) is used to generate seasonal drought forecasts. The forecasts were evaluated against the reference forecasts (i.e., persistence forecast and climatological forecast). The NMME-DTVGM drought forecasts have higher detectability and accuracy and lower false alarm rate than the reference forecasts at different lead times (from 1 to 4 months) during the cold-dry season. No apparent advantage is shown in drought predictions during spring and summer seasons because of a long memory of the initial conditions in spring and a lower predictive skill for precipitation in summer. Overall, the NMME-based seasonal drought forecasting system has meaningful skill in predicting drought several months in advance, which can provide critical information for drought preparedness and response planning as well as the sustainable practice of water resource conservation over the basin.

  5. A single-ensemble clutter rejection method based on the analytic geometry for ultrasound color flow imaging.

    PubMed

    You, Wei; Wang, Yuanyuan

    2011-11-01

    In ultrasound color flow imaging (CFI), the single-ensemble eigen-based filters can reject clutter components using each slow-time ensemble individually. They have shown excellent spatial adaptability. This article proposes a novel clutter rejection method called the single-ensemble geometry filter (SGF), which is derived from an analytic geometry perspective. If the transmitted pulse number M equals two, the clutter component distribution on a two-dimensional (2-D) plane will be similar to a tilted ellipse. Therefore, the direction of the major axis of the ellipse can be used as the first principal component of the autocorrelation matrix estimated from multiple ensembles. Then the algorithm is generalized from 2-D to a higher dimensional space by using linear algebra representations of the ellipse. Comparisons have been made with the high-pass filter (HPF), the Hankel-singular value decomposition (SVD) filter and the recursive eigen-decomposition (RED) method using both simulated and human carotid data. Results show that compared with HPF and Hankel-SVD, the proposed filter causes less bias on the velocity estimation when the clutter velocity is close to that of the blood flow. On the other hand, the proposed filter does not need to update the autocorrelation matrix and can achieve better spatial adaptability than the RED.

  6. MRF-Based Spatial Expert Tracking of the Multi-Model Ensemble

    NASA Astrophysics Data System (ADS)

    McQuade, S.; Monteleoni, C.

    2013-12-01

    We consider the problem of adaptively combining the 'multi-model ensemble' of General Circulation Models (GCMs) that inform the Intergovernmental Panel on Climate Change (IPCC), drawn from major laboratories around the world. This problem can be treated as an expert tracking problem in the online setting, where an algorithm maintains a set of weights over the experts (here the GCMs are the experts). At each time interval these weights are used to make a combined projection, and then the weights can be updated based on the performance of experts. In this work we focus on tracking the GCMs at different geographic locations and effectively incorporating spatial influence and correlations between these locations. We approach this multi-model ensemble problem using a pairwise Markov Random Field (MRF), where the state of each hidden variable is the identity of the best GCM at a specific location. Our MRF takes the form of a lattice over the Earth, with links between neighboring locations. To establish reasonable energy functions for the MRF, we first show that the Fixed-Share algorithm for expert tracking over time can be expressed as a simple MRF. By expressing Fixed-Share as an MRF, we identify the energy function that corresponds to the switching dynamics (how the best expert switches over time). Since an MRF is an undirected graph, this 'switching' energy function can be naturally applied to spatial links between variables as well. To calculate the marginal probabilities of the hidden variables (i.e. our new beliefs over GCMs), we apply Loopy Belief Propagation (LBP) to the MRF. In LBP, each node sends messages to neighboring nodes about the sender's 'belief' of the neighbor's state. Figure 1 shows our initial results from an online evaluation of GCM temperature hindcasts from the IPCC Phase 3 Coupled Model Intercomparison Project (CMIP3) archive. The red line shows the mean loss of our method versus the spatial switching rate. The right-most point on the graph

  7. Effective Visualization of Temporal Ensembles.

    PubMed

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

    2016-01-01

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

  8. Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter.

    PubMed

    Wang, Xuan; Tandeo, Pierre; Fablet, Ronan; Husson, Romain; Guan, Lei; Chen, Ge

    2016-11-25

    The swell propagation model built on geometric optics is known to work well when simulating radiated swells from a far located storm. Based on this simple approximation, satellites have acquired plenty of large samples on basin-traversing swells induced by fierce storms situated in mid-latitudes. How to routinely reconstruct swell fields with these irregularly sampled observations from space via known swell propagation principle requires more examination. In this study, we apply 3-h interval pseudo SAR observations in the ensemble Kalman filter (EnKF) to reconstruct a swell field in ocean basin, and compare it with buoy swell partitions and polynomial regression results. As validated against in situ measurements, EnKF works well in terms of spatial-temporal consistency in far-field swell propagation scenarios. Using this framework, we further address the influence of EnKF parameters, and perform a sensitivity analysis to evaluate estimations made under different sets of parameters. Such analysis is of key interest with respect to future multiple-source routinely recorded swell field data. Satellite-derived swell data can serve as a valuable complementary dataset to in situ or wave re-analysis datasets.

  9. Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter

    PubMed Central

    Wang, Xuan; Tandeo, Pierre; Fablet, Ronan; Husson, Romain; Guan, Lei; Chen, Ge

    2016-01-01

    The swell propagation model built on geometric optics is known to work well when simulating radiated swells from a far located storm. Based on this simple approximation, satellites have acquired plenty of large samples on basin-traversing swells induced by fierce storms situated in mid-latitudes. How to routinely reconstruct swell fields with these irregularly sampled observations from space via known swell propagation principle requires more examination. In this study, we apply 3-h interval pseudo SAR observations in the ensemble Kalman filter (EnKF) to reconstruct a swell field in ocean basin, and compare it with buoy swell partitions and polynomial regression results. As validated against in situ measurements, EnKF works well in terms of spatial–temporal consistency in far-field swell propagation scenarios. Using this framework, we further address the influence of EnKF parameters, and perform a sensitivity analysis to evaluate estimations made under different sets of parameters. Such analysis is of key interest with respect to future multiple-source routinely recorded swell field data. Satellite-derived swell data can serve as a valuable complementary dataset to in situ or wave re-analysis datasets. PMID:27898005

  10. An Efficient Data-worth Analysis Framework via Probabilistic Collocation Method Based Ensemble Kalman Filter

    NASA Astrophysics Data System (ADS)

    Xue, L.; Dai, C.; Zhang, D.; Guadagnini, A.

    2015-12-01

    It is critical to predict contaminant plume in an aquifer under uncertainty, which can help assess environmental risk and design rational management strategies. An accurate prediction of contaminant plume requires the collection of data to help characterize the system. Due to the limitation of financial resources, ones should estimate the expectative value of data collected from each optional monitoring scheme before carried out. Data-worth analysis is believed to be an effective approach to identify the value of the data in some problems, which quantifies the uncertainty reduction assuming that the plausible data has been collected. However, it is difficult to apply the data-worth analysis to a dynamic simulation of contaminant transportation model owning to its requirement of large number of inverse-modeling. In this study, a novel efficient data-worth analysis framework is proposed by developing the Probabilistic Collocation Method based Ensemble Kalman Filter (PCKF). The PCKF constructs polynomial chaos expansion surrogate model to replace the original complex numerical model. Consequently, the inverse modeling can perform on the proxy rather than the original model. An illustrative example, considering the dynamic change of the contaminant concentration, is employed to demonstrate the proposed approach. The Results reveal that schemes with different sampling frequencies, monitoring networks location, prior data content will have significant impact on the uncertainty reduction of the estimation of contaminant plume. Our proposition is validated to provide the reasonable value of data from various schemes.

  11. A demonstration of ensemble-based assimilation methods with a layered OGCM from the perspective of operational ocean forecasting systems

    NASA Astrophysics Data System (ADS)

    Brusdal, K.; Brankart, J. M.; Halberstadt, G.; Evensen, G.; Brasseur, P.; van Leeuwen, P. J.; Dombrowsky, E.; Verron, J.

    2003-04-01

    A demonstration study of three advanced, sequential data assimilation methods, applied with the nonlinear Miami Isopycnic Coordinate Ocean Model (MICOM), has been performed within the European Commission-funded DIADEM project. The data assimilation techniques considered are the Ensemble Kalman Filter (EnKF), the Ensemble Kalman Smoother (EnKS) and the Singular Evolutive Extended Kalman (SEEK) Filter, which all in different ways resemble the original Kalman Filter. In the EnKF and EnKS an ensemble of model states is integrated forward in time according to the model dynamics, and statistical moments needed at analysis time are calculated from the ensemble of model states. The EnKS, as opposed to the EnKF, update the analysis also backward in time whenever new observations are available, thereby improving the estimated states at the previous analysis times. The SEEK filter reduces the computational burden of the error propagation by representing the errors in a subspace which is initially calculated from a truncated EOF analysis. A hindcast experiment, where sea-level anomaly and sea-surface temperature data are assimilated, has been conducted in the North Atlantic for the time period July until September 1996. In this paper, we describe the implementation of ensemble-based assimilation methods with a common theoretical framework, we present results from hindcast experiments achieved with the EnKF, EnKS and SEEK filter, and we discuss the relative merits of these methods from the perspective of operational marine monitoring and forecasting systems. We found that the three systems have similar performances, and they can be considered feasible technologically for building preoperational prototypes.

  12. Determining optimal clothing ensembles based on weather forecasts, with particular reference to outdoor winter military activities.

    PubMed

    Morabito, Marco; Pavlinic, Daniela Z; Crisci, Alfonso; Capecchi, Valerio; Orlandini, Simone; Mekjavic, Igor B

    2011-07-01

    Military and civil defense personnel are often involved in complex activities in a variety of outdoor environments. The choice of appropriate clothing ensembles represents an important strategy to establish the success of a military mission. The main aim of this study was to compare the known clothing insulation of the garment ensembles worn by soldiers during two winter outdoor field trials (hike and guard duty) with the estimated optimal clothing thermal insulations recommended to maintain thermoneutrality, assessed by using two different biometeorological procedures. The overall aim was to assess the applicability of such biometeorological procedures to weather forecast systems, thereby developing a comprehensive biometeorological tool for military operational forecast purposes. Military trials were carried out during winter 2006 in Pokljuka (Slovenia) by Slovene Armed Forces personnel. Gastrointestinal temperature, heart rate and environmental parameters were measured with portable data acquisition systems. The thermal characteristics of the clothing ensembles worn by the soldiers, namely thermal resistance, were determined with a sweating thermal manikin. Results showed that the clothing ensemble worn by the military was appropriate during guard duty but generally inappropriate during the hike. A general under-estimation of the biometeorological forecast model in predicting the optimal clothing insulation value was observed and an additional post-processing calibration might further improve forecast accuracy. This study represents the first step in the development of a comprehensive personalized biometeorological forecast system aimed at improving recommendations regarding the optimal thermal insulation of military garment ensembles for winter activities.

  13. Determining optimal clothing ensembles based on weather forecasts, with particular reference to outdoor winter military activities

    NASA Astrophysics Data System (ADS)

    Morabito, Marco; Pavlinic, Daniela Z.; Crisci, Alfonso; Capecchi, Valerio; Orlandini, Simone; Mekjavic, Igor B.

    2011-07-01

    Military and civil defense personnel are often involved in complex activities in a variety of outdoor environments. The choice of appropriate clothing ensembles represents an important strategy to establish the success of a military mission. The main aim of this study was to compare the known clothing insulation of the garment ensembles worn by soldiers during two winter outdoor field trials (hike and guard duty) with the estimated optimal clothing thermal insulations recommended to maintain thermoneutrality, assessed by using two different biometeorological procedures. The overall aim was to assess the applicability of such biometeorological procedures to weather forecast systems, thereby developing a comprehensive biometeorological tool for military operational forecast purposes. Military trials were carried out during winter 2006 in Pokljuka (Slovenia) by Slovene Armed Forces personnel. Gastrointestinal temperature, heart rate and environmental parameters were measured with portable data acquisition systems. The thermal characteristics of the clothing ensembles worn by the soldiers, namely thermal resistance, were determined with a sweating thermal manikin. Results showed that the clothing ensemble worn by the military was appropriate during guard duty but generally inappropriate during the hike. A general under-estimation of the biometeorological forecast model in predicting the optimal clothing insulation value was observed and an additional post-processing calibration might further improve forecast accuracy. This study represents the first step in the development of a comprehensive personalized biometeorological forecast system aimed at improving recommendations regarding the optimal thermal insulation of military garment ensembles for winter activities.

  14. Accelerating Monte Carlo molecular simulations by reweighting and reconstructing Markov chains: Extrapolation of canonical ensemble averages and second derivatives to different temperature and density conditions

    SciTech Connect

    Kadoura, Ahmad; Sun, Shuyu Salama, Amgad

    2014-08-01

    Accurate determination of thermodynamic properties of petroleum reservoir fluids is of great interest to many applications, especially in petroleum engineering and chemical engineering. Molecular simulation has many appealing features, especially its requirement of fewer tuned parameters but yet better predicting capability; however it is well known that molecular simulation is very CPU expensive, as compared to equation of state approaches. We have recently introduced an efficient thermodynamically consistent technique to regenerate rapidly Monte Carlo Markov Chains (MCMCs) at different thermodynamic conditions from the existing data points that have been pre-computed with expensive classical simulation. This technique can speed up the simulation more than a million times, making the regenerated molecular simulation almost as fast as equation of state approaches. In this paper, this technique is first briefly reviewed and then numerically investigated in its capability of predicting ensemble averages of primary quantities at different neighboring thermodynamic conditions to the original simulated MCMCs. Moreover, this extrapolation technique is extended to predict second derivative properties (e.g. heat capacity and fluid compressibility). The method works by reweighting and reconstructing generated MCMCs in canonical ensemble for Lennard-Jones particles. In this paper, system's potential energy, pressure, isochoric heat capacity and isothermal compressibility along isochors, isotherms and paths of changing temperature and density from the original simulated points were extrapolated. Finally, an optimized set of Lennard-Jones parameters (ε, σ) for single site models were proposed for methane, nitrogen and carbon monoxide.

  15. Ensemble models of proteins and protein domains based on distance distribution restraints.

    PubMed

    Jeschke, Gunnar

    2016-04-01

    Conformational ensembles of intrinsically disordered peptide chains are not fully determined by experimental observations. Uncertainty due to lack of experimental restraints and due to intrinsic disorder can be distinguished if distance distributions restraints are available. Such restraints can be obtained from pulsed dipolar electron paramagnetic resonance (EPR) spectroscopy applied to pairs of spin labels. Here, we introduce a Monte Carlo approach for generating conformational ensembles that are consistent with a set of distance distribution restraints, backbone dihedral angle statistics in known protein structures, and optionally, secondary structure propensities or membrane immersion depths. The approach is tested with simulated restraints for a terminal and an internal loop and for a protein with 69 residues by using sets of sparse restraints for underlying well-defined conformations and for published ensembles of a premolten globule-like and a coil-like intrinsically disordered protein.

  16. Self-Adaptive Prediction of Cloud Resource Demands Using Ensemble Model and Subtractive-Fuzzy Clustering Based Fuzzy Neural Network

    PubMed Central

    Chen, Zhijia; Zhu, Yuanchang; Di, Yanqiang; Feng, Shaochong

    2015-01-01

    In IaaS (infrastructure as a service) cloud environment, users are provisioned with virtual machines (VMs). To allocate resources for users dynamically and effectively, accurate resource demands predicting is essential. For this purpose, this paper proposes a self-adaptive prediction method using ensemble model and subtractive-fuzzy clustering based fuzzy neural network (ESFCFNN). We analyze the characters of user preferences and demands. Then the architecture of the prediction model is constructed. We adopt some base predictors to compose the ensemble model. Then the structure and learning algorithm of fuzzy neural network is researched. To obtain the number of fuzzy rules and the initial value of the premise and consequent parameters, this paper proposes the fuzzy c-means combined with subtractive clustering algorithm, that is, the subtractive-fuzzy clustering. Finally, we adopt different criteria to evaluate the proposed method. The experiment results show that the method is accurate and effective in predicting the resource demands. PMID:25691896

  17. Self-adaptive prediction of cloud resource demands using ensemble model and subtractive-fuzzy clustering based fuzzy neural network.

    PubMed

    Chen, Zhijia; Zhu, Yuanchang; Di, Yanqiang; Feng, Shaochong

    2015-01-01

    In IaaS (infrastructure as a service) cloud environment, users are provisioned with virtual machines (VMs). To allocate resources for users dynamically and effectively, accurate resource demands predicting is essential. For this purpose, this paper proposes a self-adaptive prediction method using ensemble model and subtractive-fuzzy clustering based fuzzy neural network (ESFCFNN). We analyze the characters of user preferences and demands. Then the architecture of the prediction model is constructed. We adopt some base predictors to compose the ensemble model. Then the structure and learning algorithm of fuzzy neural network is researched. To obtain the number of fuzzy rules and the initial value of the premise and consequent parameters, this paper proposes the fuzzy c-means combined with subtractive clustering algorithm, that is, the subtractive-fuzzy clustering. Finally, we adopt different criteria to evaluate the proposed method. The experiment results show that the method is accurate and effective in predicting the resource demands.

  18. Multi-model ensemble-based probabilistic prediction of tropical cyclogenesis using TIGGE model forecasts

    NASA Astrophysics Data System (ADS)

    Jaiswal, Neeru; Kishtawal, C. M.; Bhomia, Swati; Pal, P. K.

    2016-10-01

    An extended range tropical cyclogenesis forecast model has been developed using the forecasts of global models available from TIGGE portal. A scheme has been developed to detect the signatures of cyclogenesis in the global model forecast fields [i.e., the mean sea level pressure and surface winds (10 m horizontal winds)]. For this, a wind matching index was determined between the synthetic cyclonic wind fields and the forecast wind fields. The thresholds of 0.4 for wind matching index and 1005 hpa for pressure were determined to detect the cyclonic systems. These detected cyclonic systems in the study region are classified into different cyclone categories based on their intensity (maximum wind speed). The forecasts of up to 15 days from three global models viz., ECMWF, NCEP and UKMO have been used to predict cyclogenesis based on multi-model ensemble approach. The occurrence of cyclonic events of different categories in all the forecast steps in the grided region (10 × 10 km2) was used to estimate the probability of the formation of cyclogenesis. The probability of cyclogenesis was estimated by computing the grid score using the wind matching index by each model and at each forecast step and convolving it with Gaussian filter. The proposed method is used to predict the cyclogenesis of five named tropical cyclones formed during the year 2013 in the north Indian Ocean. The 6-8 days advance cyclogenesis of theses systems were predicted using the above approach. The mean lead prediction time for the cyclogenesis event of the proposed model has been found as 7 days.

  19. Endowing a Content-Based Medical Image Retrieval System with Perceptual Similarity Using Ensemble Strategy.

    PubMed

    Bedo, Marcos Vinicius Naves; Pereira Dos Santos, Davi; Ponciano-Silva, Marcelo; de Azevedo-Marques, Paulo Mazzoncini; Ferreira de Carvalho, André Ponce de León; Traina, Caetano

    2016-02-01

    Content-based medical image retrieval (CBMIR) is a powerful resource to improve differential computer-aided diagnosis. The major problem with CBMIR applications is the semantic gap, a situation in which the system does not follow the users' sense of similarity. This gap can be bridged by the adequate modeling of similarity queries, which ultimately depends on the combination of feature extractor methods and distance functions. In this study, such combinations are referred to as perceptual parameters, as they impact on how images are compared. In a CBMIR, the perceptual parameters must be manually set by the users, which imposes a heavy burden on the specialists; otherwise, the system will follow a predefined sense of similarity. This paper presents a novel approach to endow a CBMIR with a proper sense of similarity, in which the system defines the perceptual parameter depending on the query element. The method employs ensemble strategy, where an extreme learning machine acts as a meta-learner and identifies the most suitable perceptual parameter according to a given query image. This parameter defines the search space for the similarity query that retrieves the most similar images. An instance-based learning classifier labels the query image following the query result set. As the concept implementation, we integrated the approach into a mammogram CBMIR. For each query image, the resulting tool provided a complete second opinion, including lesion class, system certainty degree, and set of most similar images. Extensive experiments on a large mammogram dataset showed that our proposal achieved a hit ratio up to 10% higher than the traditional CBMIR approach without requiring external parameters from the users. Our database-driven solution was also up to 25% faster than content retrieval traditional approaches.

  20. A novel signal compression method based on optimal ensemble empirical mode decomposition for bearing vibration signals

    NASA Astrophysics Data System (ADS)

    Guo, Wei; Tse, Peter W.

    2013-01-01

    Today, remote machine condition monitoring is popular due to the continuous advancement in wireless communication. Bearing is the most frequently and easily failed component in many rotating machines. To accurately identify the type of bearing fault, large amounts of vibration data need to be collected. However, the volume of transmitted data cannot be too high because the bandwidth of wireless communication is limited. To solve this problem, the data are usually compressed before transmitting to a remote maintenance center. This paper proposes a novel signal compression method that can substantially reduce the amount of data that need to be transmitted without sacrificing the accuracy of fault identification. The proposed signal compression method is based on ensemble empirical mode decomposition (EEMD), which is an effective method for adaptively decomposing the vibration signal into different bands of signal components, termed intrinsic mode functions (IMFs). An optimization method was designed to automatically select appropriate EEMD parameters for the analyzed signal, and in particular to select the appropriate level of the added white noise in the EEMD method. An index termed the relative root-mean-square error was used to evaluate the decomposition performances under different noise levels to find the optimal level. After applying the optimal EEMD method to a vibration signal, the IMF relating to the bearing fault can be extracted from the original vibration signal. Compressing this signal component obtains a much smaller proportion of data samples to be retained for transmission and further reconstruction. The proposed compression method were also compared with the popular wavelet compression method. Experimental results demonstrate that the optimization of EEMD parameters can automatically find appropriate EEMD parameters for the analyzed signals, and the IMF-based compression method provides a higher compression ratio, while retaining the bearing defect

  1. Texture Descriptors Ensembles Enable Image-Based Classification of Maturation of Human Stem Cell-Derived Retinal Pigmented Epithelium

    PubMed Central

    Caetano dos Santos, Florentino Luciano; Skottman, Heli; Juuti-Uusitalo, Kati; Hyttinen, Jari

    2016-01-01

    Aims A fast, non-invasive and observer-independent method to analyze the homogeneity and maturity of human pluripotent stem cell (hPSC) derived retinal pigment epithelial (RPE) cells is warranted to assess the suitability of hPSC-RPE cells for implantation or in vitro use. The aim of this work was to develop and validate methods to create ensembles of state-of-the-art texture descriptors and to provide a robust classification tool to separate three different maturation stages of RPE cells by using phase contrast microscopy images. The same methods were also validated on a wide variety of biological image classification problems, such as histological or virus image classification. Methods For image classification we used different texture descriptors, descriptor ensembles and preprocessing techniques. Also, three new methods were tested. The first approach was an ensemble of preprocessing methods, to create an additional set of images. The second was the region-based approach, where saliency detection and wavelet decomposition divide each image in two different regions, from which features were extracted through different descriptors. The third method was an ensemble of Binarized Statistical Image Features, based on different sizes and thresholds. A Support Vector Machine (SVM) was trained for each descriptor histogram and the set of SVMs combined by sum rule. The accuracy of the computer vision tool was verified in classifying the hPSC-RPE cell maturation level. Dataset and Results The RPE dataset contains 1862 subwindows from 195 phase contrast images. The final descriptor ensemble outperformed the most recent stand-alone texture descriptors, obtaining, for the RPE dataset, an area under ROC curve (AUC) of 86.49% with the 10-fold cross validation and 91.98% with the leave-one-image-out protocol. The generality of the three proposed approaches was ascertained with 10 more biological image datasets, obtaining an average AUC greater than 97%. Conclusions Here we

  2. Probabilistic regional wind power forecasts based on calibrated Numerical Weather Forecast ensembles

    NASA Astrophysics Data System (ADS)

    Späth, Stephan; von Bremen, Lueder; Junk, Constantin; Heinemann, Detlev

    2014-05-01

    With increasing shares of installed wind power in Germany, accurate forecasts of wind speed and power get increasingly important for the grid integration of Renewable Energies. Applications like grid management and trading also benefit from uncertainty information. This uncertainty information can be provided by ensemble forecasts. These forecasts often exhibit systematic errors such as biases and spread deficiencies. The errors can be reduced by statistical post-processing. We use forecast data from the regional Numerical Weather Prediction model COSMO-DE EPS as input to regional wind power forecasts. In order to enhance the power forecast, we first calibrate the wind speed forecasts against the model analysis, so some of the model's systematic errors can be removed. Wind measurements at every grid point are usually not available and as we want to conduct grid zone forecasts, the model analysis is the best target for calibration. We use forecasts from the COSMO-DE EPS, a high-resolution ensemble prediction system with 20 forecast members. The model covers the region of Germany and surroundings with a vertical resolution of 50 model levels and a horizontal resolution of 0.025 degrees (approximately 2.8 km). The forecast range is 21 hours with model output available on an hourly basis. Thus, we use it for shortest-term wind power forecasts. The COSMO-DE EPS was originally designed with a focus on forecasts of convective precipitation. The COSMO-DE EPS wind speed forecasts at hub height were post-processed by nonhomogenous Gaussian regression (NGR; Thorarinsdottir and Gneiting, 2010), a calibration method that fits a truncated normal distribution to the ensemble wind speed forecasts. As calibration target, the model analysis was used. The calibration is able to remove some deficits of the COSMO-DE EPS. In contrast to the raw ensemble members, the calibrated ensemble members do not show anymore the strong correlations with each other and the spread-skill relationship

  3. Towards the knowledge-based design of universal influenza epitope ensemble vaccines

    PubMed Central

    Sheikh, Qamar M.; Gatherer, Derek; Reche, Pedro A; Flower, Darren R.

    2016-01-01

    Motivation: Influenza A viral heterogeneity remains a significant threat due to unpredictable antigenic drift in seasonal influenza and antigenic shifts caused by the emergence of novel subtypes. Annual review of multivalent influenza vaccines targets strains of influenza A and B likely to be predominant in future influenza seasons. This does not induce broad, cross protective immunity against emergent subtypes. Better strategies are needed to prevent future pandemics. Cross-protection can be achieved by activating CD8+ and CD4+ T cells against highly conserved regions of the influenza genome. We combine available experimental data with informatics-based immunological predictions to help design vaccines potentially able to induce cross-protective T-cells against multiple influenza subtypes. Results: To exemplify our approach we designed two epitope ensemble vaccines comprising highly conserved and experimentally verified immunogenic influenza A epitopes as putative non-seasonal influenza vaccines; one specifically targets the US population and the other is a universal vaccine. The USA-specific vaccine comprised 6 CD8+ T cell epitopes (GILGFVFTL, FMYSDFHFI, GMDPRMCSL, SVKEKDMTK, FYIQMCTEL, DTVNRTHQY) and 3 CD4+ epitopes (KGILGFVFTLTVPSE, EYIMKGVYINTALLN, ILGFVFTLTVPSERG). The universal vaccine comprised 8 CD8+ epitopes: (FMYSDFHFI, GILGFVFTL, ILRGSVAHK, FYIQMCTEL, ILKGKFQTA, YYLEKANKI, VSDGGPNLY, YSHGTGTGY) and the same 3 CD4+ epitopes. Our USA-specific vaccine has a population protection coverage (portion of the population potentially responsive to one or more component epitopes of the vaccine, PPC) of over 96 and 95% coverage of observed influenza subtypes. The universal vaccine has a PPC value of over 97 and 88% coverage of observed subtypes. Availability and Implementation: http://imed.med.ucm.es/Tools/episopt.html. Contact: d.r.flower@aston.ac.uk PMID:27402904

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

    NASA Astrophysics Data System (ADS)

    Natalello, Antonino; Santambrogio, Carlo; Grandori, Rita

    2017-01-01

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

  5. Ensemble-Based Estimates of the Predictability of Wind-Driven Coastal Ocean Flow Over Topography

    DTIC Science & Technology

    2008-01-01

    introduced in geophysi- cal fluid dynamics to quantify predictive information content in forecast ensembles (Kleeman 2002; Abramov et al. 2005). Here, we...National Ocean Partnership Program. 33 REFERENCES Abramov , R., A. Majda, and R. Kleeman, 2005: Information theory and predictability for low-frequency

  6. Ensemble-Based Instrumental Music Instruction: Dead-End Tradition or Opportunity for Socially Enlightened Teaching

    ERIC Educational Resources Information Center

    Heuser, Frank

    2011-01-01

    Public school music education in the USA remains wedded to large ensemble performance. Instruction tends to be teacher directed, relies on styles from the Western canon and exhibits little concern for musical interests of students. The idea that a fundamental purpose of education is the creation of a just society is difficult for many music…

  7. Forecasting European cold waves based on subsampling strategies of CMIP5 and Euro-CORDEX ensembles

    NASA Astrophysics Data System (ADS)

    Cordero-Llana, Laura; Braconnot, Pascale; Vautard, Robert; Vrac, Mathieu; Jezequel, Aglae

    2016-04-01

    Forecasting future extreme events under the present changing climate represents a difficult task. Currently there are a large number of ensembles of simulations for climate projections that take in account different models and scenarios. However, there is a need for reducing the size of the ensemble to make the interpretation of these simulations more manageable for impact studies or climate risk assessment. This can be achieved by developing subsampling strategies to identify a limited number of simulations that best represent the ensemble. In this study, cold waves are chosen to test different approaches for subsampling available simulations. The definition of cold waves depends on the criteria used, but they are generally defined using a minimum temperature threshold, the duration of the cold spell as well as their geographical extend. These climate indicators are not universal, highlighting the difficulty of directly comparing different studies. As part of the of the CLIPC European project, we use daily surface temperature data obtained from CMIP5 outputs as well as Euro-CORDEX simulations to predict future cold waves events in Europe. From these simulations a clustering method is applied to minimise the number of ensembles required. Furthermore, we analyse the different uncertainties that arise from the different model characteristics and definitions of climate indicators. Finally, we will test if the same subsampling strategy can be used for different climate indicators. This will facilitate the use of the subsampling results for a wide number of impact assessment studies.

  8. Ensembl 2016

    PubMed Central

    Yates, Andrew; Akanni, Wasiu; Amode, M. Ridwan; Barrell, Daniel; Billis, Konstantinos; Carvalho-Silva, Denise; Cummins, Carla; Clapham, Peter; Fitzgerald, Stephen; Gil, Laurent; Girón, Carlos García; Gordon, Leo; Hourlier, Thibaut; Hunt, Sarah E.; Janacek, Sophie H.; Johnson, Nathan; Juettemann, Thomas; Keenan, Stephen; Lavidas, Ilias; Martin, Fergal J.; Maurel, Thomas; McLaren, William; Murphy, Daniel N.; Nag, Rishi; Nuhn, Michael; Parker, Anne; Patricio, Mateus; Pignatelli, Miguel; Rahtz, Matthew; Riat, Harpreet Singh; Sheppard, Daniel; Taylor, Kieron; Thormann, Anja; Vullo, Alessandro; Wilder, Steven P.; Zadissa, Amonida; Birney, Ewan; Harrow, Jennifer; Muffato, Matthieu; Perry, Emily; Ruffier, Magali; Spudich, Giulietta; Trevanion, Stephen J.; Cunningham, Fiona; Aken, Bronwen L.; Zerbino, Daniel R.; Flicek, Paul

    2016-01-01

    The Ensembl project (http://www.ensembl.org) is a system for genome annotation, analysis, storage and dissemination designed to facilitate the access of genomic annotation from chordates and key model organisms. It provides access to data from 87 species across our main and early access Pre! websites. This year we introduced three newly annotated species and released numerous updates across our supported species with a concentration on data for the latest genome assemblies of human, mouse, zebrafish and rat. We also provided two data updates for the previous human assembly, GRCh37, through a dedicated website (http://grch37.ensembl.org). Our tools, in particular the VEP, have been improved significantly through integration of additional third party data. REST is now capable of larger-scale analysis and our regulatory data BioMart can deliver faster results. The website is now capable of displaying long-range interactions such as those found in cis-regulated datasets. Finally we have launched a website optimized for mobile devices providing views of genes, variants and phenotypes. Our data is made available without restriction and all code is available from our GitHub organization site (http://github.com/Ensembl) under an Apache 2.0 license. PMID:26687719

  9. Ensembl comparative genomics resources.

    PubMed

    Herrero, Javier; Muffato, Matthieu; Beal, Kathryn; Fitzgerald, Stephen; Gordon, Leo; Pignatelli, Miguel; Vilella, Albert J; Searle, Stephen M J; Amode, Ridwan; Brent, Simon; Spooner, William; Kulesha, Eugene; Yates, Andrew; Flicek, Paul

    2016-01-01

    Evolution provides the unifying framework with which to understand biology. The coherent investigation of genic and genomic data often requires comparative genomics analyses based on whole-genome alignments, sets of homologous genes and other relevant datasets in order to evaluate and answer evolutionary-related questions. However, the complexity and computational requirements of producing such data are substantial: this has led to only a small number of reference resources that are used for most comparative analyses. The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available. Database URL: http://www.ensembl.org.

  10. Comparison of Ensemble Kalman Filter groundwater-data assimilation methods based on stochastic moment equations and Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Panzeri, M.; Riva, M.; Guadagnini, A.; Neuman, S. P.

    2014-04-01

    Traditional Ensemble Kalman Filter (EnKF) data assimilation requires computationally intensive Monte Carlo (MC) sampling, which suffers from filter inbreeding unless the number of simulations is large. Recently we proposed an alternative EnKF groundwater-data assimilation method that obviates the need for sampling and is free of inbreeding issues. In our new approach, theoretical ensemble moments are approximated directly by solving a system of corresponding stochastic groundwater flow equations. Like MC-based EnKF, our moment equations (ME) approach allows Bayesian updating of system states and parameters in real-time as new data become available. Here we compare the performances and accuracies of the two approaches on two-dimensional transient groundwater flow toward a well pumping water in a synthetic, randomly heterogeneous confined aquifer subject to prescribed head and flux boundary conditions.

  11. A new data assimilation technique based on ensemble Kalman filter and Brownian bridges: An application to Richards' equation

    NASA Astrophysics Data System (ADS)

    Berardi, Marco; Andrisani, Andrea; Lopez, Luciano; Vurro, Michele

    2016-11-01

    In this paper a new data assimilation technique is proposed which is based on the ensemble Kalman filter (EnKF). Such a technique will be effective if few observations of a dynamical system are available and a large model error occurs. The idea is to acquire a fine grid of synthetic observations in two steps: (1) first we interpolate the real observations with suitable polynomial curves; (2) then we estimate the relative measurement errors by means of Brownian bridges. This technique has been tested on the Richards' equation, which governs the water flow in unsaturated soils, where a large model error has been introduced by solving the Richards' equation by means of an explicit numerical scheme. The application of this technique to some synthetic experiments has shown improvements with respect to the classical ensemble Kalman filter, in particular for problems with a large model error.

  12. Input Decimated Ensembles

    NASA Technical Reports Server (NTRS)

    Tumer, Kagan; Oza, Nikunj C.; Clancy, Daniel (Technical Monitor)

    2001-01-01

    Using an ensemble of classifiers instead of a single classifier has been shown to improve generalization performance in many pattern recognition problems. However, the extent of such improvement depends greatly on the amount of correlation among the errors of the base classifiers. Therefore, reducing those correlations while keeping the classifiers' performance levels high is an important area of research. In this article, we explore input decimation (ID), a method which selects feature subsets for their ability to discriminate among the classes and uses them to decouple the base classifiers. We provide a summary of the theoretical benefits of correlation reduction, along with results of our method on two underwater sonar data sets, three benchmarks from the Probenl/UCI repositories, and two synthetic data sets. The results indicate that input decimated ensembles (IDEs) outperform ensembles whose base classifiers use all the input features; randomly selected subsets of features; and features created using principal components analysis, on a wide range of domains.

  13. Comparison of Probabilistic Coastal Inundation Maps Based on Historical Storms and Statistically Modeled Storm Ensemble

    NASA Astrophysics Data System (ADS)

    Feng, X.; Sheng, Y.; Condon, A. J.; Paramygin, V. A.; Hall, T.

    2012-12-01

    which had been used for Western North Pacific (WNP) tropical cyclone (TC) genesis (Hall 2011) as well as North Atlantic tropical cyclone genesis (Hall and Jewson 2007). The introduction of these tracks complements the shortage of the historical samples and allows for more reliable PDFs required for implementation of JPM-OS. Using the 33,731 tracks and JPM-OS, an optimal storm ensemble is determined. This approach results in different storms/winds for storm surge and inundation modeling, and produces different Base Flood Elevation maps for coastal regions. Coastal inundation maps produced by the two different methods will be discussed in detail in the poster paper.

  14. Illumination correction of dyed fabrics approach using Bagging-based ensemble particle swarm optimization-extreme learning machine

    NASA Astrophysics Data System (ADS)

    Zhou, Zhiyu; Xu, Rui; Wu, Dichong; Zhu, Zefei; Wang, Haiyan

    2016-09-01

    Changes in illumination will result in serious color difference evaluation errors during the dyeing process. A Bagging-based ensemble extreme learning machine (ELM) mechanism hybridized with particle swarm optimization (PSO), namely Bagging-PSO-ELM, is proposed to develop an accurate illumination correction model for dyed fabrics. The model adopts PSO algorithm to optimize the input weights and hidden biases for the ELM neural network called PSO-ELM, which enhances the performance of ELM. Meanwhile, to further increase the prediction accuracy, a Bagging ensemble scheme is used to construct an independent PSO-ELM learning machine by taking bootstrap replicates of the training set. Then, the obtained multiple different PSO-ELM learners are aggregated to establish the prediction model. The proposed prediction model is evaluated with real dyed fabric images and discussed in comparison with several related methods. Experimental results show that the ensemble color constancy method is able to generate a more robust illuminant estimation model with better generalization performance.

  15. Vision-based posture recognition using an ensemble classifier and a vote filter

    NASA Astrophysics Data System (ADS)

    Ji, Peng; Wu, Changcheng; Xu, Xiaonong; Song, Aiguo; Li, Huijun

    2016-10-01

    Posture recognition is a very important Human-Robot Interaction (HRI) way. To segment effective posture from an image, we propose an improved region grow algorithm which combining with the Single Gauss Color Model. The experiment shows that the improved region grow algorithm can get the complete and accurate posture than traditional Single Gauss Model and region grow algorithm, and it can eliminate the similar region from the background at the same time. In the posture recognition part, and in order to improve the recognition rate, we propose a CNN ensemble classifier, and in order to reduce the misjudgments during a continuous gesture control, a vote filter is proposed and applied to the sequence of recognition results. Comparing with CNN classifier, the CNN ensemble classifier we proposed can yield a 96.27% recognition rate, which is better than that of CNN classifier, and the proposed vote filter can improve the recognition result and reduce the misjudgments during the consecutive gesture switch.

  16. Assessment of probability density function based on POD reduced-order model for ensemble-based data assimilation

    NASA Astrophysics Data System (ADS)

    Kikuchi, Ryota; Misaka, Takashi; Obayashi, Shigeru

    2015-10-01

    An integrated method of a proper orthogonal decomposition based reduced-order model (ROM) and data assimilation is proposed for the real-time prediction of an unsteady flow field. In this paper, a particle filter (PF) and an ensemble Kalman filter (EnKF) are compared for data assimilation and the difference in the predicted flow fields is evaluated focusing on the probability density function (PDF) of the model variables. The proposed method is demonstrated using identical twin experiments of an unsteady flow field around a circular cylinder at the Reynolds number of 1000. The PF and EnKF are employed to estimate temporal coefficients of the ROM based on the observed velocity components in the wake of the circular cylinder. The prediction accuracy of ROM-PF is significantly better than that of ROM-EnKF due to the flexibility of PF for representing a PDF compared to EnKF. Furthermore, the proposed method reproduces the unsteady flow field several orders faster than the reference numerical simulation based on the Navier-Stokes equations.

  17. High teleportation rates using cold-atom-ensemble-based quantum repeaters with Rydberg blockade

    NASA Astrophysics Data System (ADS)

    Solmeyer, Neal; Li, Xiao; Quraishi, Qudsia

    2016-04-01

    We present a simplified version of a repeater protocol in a cold neutral-atom ensemble with Rydberg excitations optimized for two-node entanglement generation and describe a protocol for quantum teleportation. Our proposal draws from previous proposals [B. Zhao et al., Phys. Rev. A 81, 052329 (2010), 10.1103/PhysRevA.81.052329; Y. Han et al., Phys. Rev. A 81, 052311 (2010), 10.1103/PhysRevA.81.052311] that described efficient and robust protocols for long-distance entanglement with many nodes. Using realistic experimental values, we predict an entanglement generation rate of ˜25 Hz and a teleportation rate of ˜5 Hz . Our predicted rates match the current state-of-the-art experiments for entanglement generation and teleportation between quantum memories. With improved efficiencies we predict entanglement generation and teleportation rates of ˜7.8 and ˜3.6 kHz, respectively, representing a two-order-of-magnitude improvement over the currently realized values. Cold-atom ensembles with Rydberg excitations are promising candidates for repeater nodes because collective effects in the ensemble can be used to deterministically generate a long-lived ground-state memory which may be efficiently mapped onto a directionally emitted single photon.

  18. Genre-based image classification using ensemble learning for online flyers

    NASA Astrophysics Data System (ADS)

    Pourashraf, Payam; Tomuro, Noriko; Apostolova, Emilia

    2015-07-01

    This paper presents an image classification model developed to classify images embedded in commercial real estate flyers. It is a component in a larger, multimodal system which uses texts as well as images in the flyers to automatically classify them by the property types. The role of the image classifier in the system is to provide the genres of the embedded images (map, schematic drawing, aerial photo, etc.), which to be combined with the texts in the flyer to do the overall classification. In this work, we used an ensemble learning approach and developed a model where the outputs of an ensemble of support vector machines (SVMs) are combined by a k-nearest neighbor (KNN) classifier. In this model, the classifiers in the ensemble are strong classifiers, each of which is trained to predict a given/assigned genre. Not only is our model intuitive by taking advantage of the mutual distinctness of the image genres, it is also scalable. We tested the model using over 3000 images extracted from online real estate flyers. The result showed that our model outperformed the baseline classifiers by a large margin.

  19. Ensemble: a web-based system for psychology survey and experiment management.

    PubMed

    Tomic, Stefan T; Janata, Petr

    2007-08-01

    We provide a description of Ensemble, a suite of Web-integrated modules for managing and analyzing data associated with psychology experiments in a small research lab. The system delivers interfaces via a Web browser for creating and presenting simple surveys without the need to author Web pages and with little or no programming effort. The surveys may be extended by selecting and presenting auditory and/or visual stimuli with MATLAB and Flash to enable a wide range of psychophysical and cognitive experiments which do not require the recording of precise reaction times. Additionally, one is provided with the ability to administer and present experiments remotely. The software technologies employed by the various modules of Ensemble are MySQL, PHP, MATLAB, and Flash. The code for Ensemble is open source and available to the public, so that its functions can be readily extended by users. We describe the architecture of the system, the functionality of each module, and provide basic examples of the interfaces.

  20. Rotaxane-based molecular muscles.

    PubMed

    Bruns, Carson J; Stoddart, J Fraser

    2014-07-15

    CONSPECTUS: More than two decades of investigating the chemistry of bistable mechanically interlocked molecules (MIMs), such as rotaxanes and catenanes, has led to the advent of numerous molecular switches that express controlled translational or circumrotational movement on the nanoscale. Directed motion at this scale is an essential feature of many biomolecular assemblies known as molecular machines, which carry out essential life-sustaining functions of the cell. It follows that the use of bistable MIMs as artificial molecular machines (AMMs) has been long anticipated. This objective is rarely achieved, however, because of challenges associated with coupling the directed motions of mechanical switches with other systems on which they can perform work. A natural source of inspiration for designing AMMs is muscle tissue, since it is a material that relies on the hierarchical organization of molecular machines (myosin) and filaments (actin) to produce the force and motion that underpin locomotion, circulation, digestion, and many other essential life processes in humans and other animals. Muscle is characterized at both microscopic and macroscopic length scales by its ability to generate forces that vary the distance between two points at the expense of chemical energy. Artificial muscles that mimic this ability are highly sought for applications involving the transduction of mechanical energy. Rotaxane-based molecular switches are excellent candidates for artificial muscles because their architectures intrinsically possess movable filamentous molecular components. In this Account, we describe (i) the different types of rotaxane "molecular muscle" architectures that express contractile and extensile motion, (ii) the molecular recognition motifs and corresponding stimuli that have been used to actuate them, and (iii) the progress made on integrating and scaling up these motions for potential applications. We identify three types of rotaxane muscles, namely, "daisy

  1. Single-ensemble-based eigen-processing methods for color flow imaging--Part I. The Hankel-SVD filter.

    PubMed

    Yu, Alfred C H; Cobbold, Richard S C

    2008-03-01

    Because of their adaptability to the slow-time signal contents, eigen-based filters have shown potential in improving the flow detection performance of color flow images. This paper proposes a new eigen-based filter called the Hankel-SVD filter that is intended to process each slowtime ensemble individually. The new filter is derived using the notion of principal Hankel component analysis, and it achieves clutter suppression by retaining only the principal components whose order is greater than the clutter eigen-space dimension estimated from a frequency based analysis algorithm. To assess its efficacy, the Hankel-SVD filter was first applied to synthetic slow-time data (ensemble size: 10) simulated from two different sets of flow parameters that model: 1) arterial imaging (blood velocity: 0 to 38.5 cm/s, tissue motion: up to 2 mm/s, transmit frequency: 5 MHz, pulse repetition period: 0.4 ms) and 2) deep vessel imaging (blood velocity: 0 to 19.2 cm/s, tissue motion: up to 2 cm/s, transmit frequency: 2 MHz, pulse repetition period: 2.0 ms). In the simulation analysis, the post-filter clutter-to- blood signal ratio (CBR) was computed as a function of blood velocity. Results show that for the same effective stopband size (50 Hz), the Hankel-SVD filter has a narrower transition region in the post-filter CBR curve than that of another type of adaptive filter called the clutter-downmixing filter. The practical efficacy of the proposed filter was tested by application to in vivo color flow data obtained from the human carotid arteries (transmit frequency: 4 MHz, pulse repetition period: 0.333 ms, ensemble size: 10). The resulting power images show that the Hankel-SVD filter can better distinguish between blood and moving-tissue regions (about 9 dB separation in power) than the clutter-downmixing filter and a fixed-rank multi ensemble-based eigen-filter (which showed a 2 to 3 dB separation).

  2. An automatic electroencephalography blinking artefact detection and removal method based on template matching and ensemble empirical mode decomposition.

    PubMed

    Bizopoulos, Paschalis A; Al-Ani, Tarik; Tsalikakis, Dimitrios G; Tzallas, Alexandros T; Koutsouris, Dimitrios D; Fotiadis, Dimitrios I

    2013-01-01

    Electrooculographic (EOG) artefacts are one of the most common causes of Electroencephalogram (EEG) distortion. In this paper, we propose a method for EOG Blinking Artefacts (BAs) detection and removal from EEG. Normalized Correlation Coefficient (NCC), based on a predetermined BA template library was used for detecting the BA. Ensemble Empirical Mode Decomposition (EEMD) was applied to the contaminated region and a statistical algorithm determined which Intrinsic Mode Functions (IMFs) correspond to the BA. The proposed method was applied in simulated EEG signals, which were contaminated with artificially created EOG BAs, increasing the Signal-to-Error Ratio (SER) of the EEG Contaminated Region (CR) by 35 dB on average.

  3. Evaluation and Sensitivity Analysis of An Ensemble-based Coupled Flash Flood and Landslide Modelling System Using Remote Sensing Forcing

    NASA Astrophysics Data System (ADS)

    Zhang, K.; Hong, Y.; Gourley, J. J.; Xue, X.; He, X.

    2015-12-01

    Heavy rainfall-triggered landslides are often associated with flood events and cause additional loss of life and property. It is pertinent to build a robust coupled flash flood and landslide disaster early warning system for disaster preparedness and hazard management based. In this study, we built an ensemble-based coupled flash flood and landslide disaster early warning system, which is aimed for operational use by the US National Weather Service, by integrating the Coupled Routing and Excess STorage (CREST) model and Sacramento Soil Moisture Accounting Model (SAC-SMA) with the physically based SLope-Infiltration-Distributed Equilibrium (SLIDE) landslide prediction model. We further evaluated this ensemble-based prototype warning system by conducting multi-year simulations driven by the Multi-Radar Multi-Sensor (MRMS) rainfall estimates in North Carolina and Oregon. We comprehensively evaluated the predictive capabilities of this system against observed and reported flood and landslides events. We then evaluated the sensitivity of the coupled system to the simulated hydrological processes. Our results show that the system is generally capable of making accurate predictions of flash flood and landslide events in terms of their locations and time of occurrence. The occurrence of predicted landslides show high sensitivity to total infiltration and soil water content, highlighting the importance of accurately simulating the hydrological processes on the accurate forecasting of rainfall triggered landslide events.

  4. Selective ensemble modeling load parameters of ball mill based on multi-scale frequency spectral features and sphere criterion

    NASA Astrophysics Data System (ADS)

    Tang, Jian; Yu, Wen; Chai, Tianyou; Liu, Zhuo; Zhou, Xiaojie

    2016-01-01

    It is difficult to model multi-frequency signal, such as mechanical vibration and acoustic signals of wet ball mill in the mineral grinding process. In this paper, these signals are decomposed into multi-scale intrinsic mode functions (IMFs) by the empirical mode decomposition (EMD) technique. A new adaptive multi-scale spectral features selection approach based on sphere criterion (SC) is applied to these IMFs frequency spectra. The candidate sub-models are constructed by the partial least squares (PLS) with the selected features. Finally, the branch and bound based selective ensemble (BBSEN) algorithm is applied to select and combine these ensemble sub-models. This method can be easily extended to regression and classification problems with multi-time scale signal. We successfully apply this approach to a laboratory-scale ball mill. The shell vibration and acoustic signals are used to model mill load parameters. The experimental results demonstrate that this novel approach is more effective than the other modeling methods based on multi-scale frequency spectral features.

  5. Motion based markerless gait analysis using standard events of gait and ensemble Kalman filtering.

    PubMed

    Vishnoi, Nalini; Mitra, Anish; Duric, Zoran; Gerber, Naomi Lynn

    2014-01-01

    We present a novel approach to gait analysis using ensemble Kalman filtering which permits markerless determination of segmental movement. We use image flow analysis to reliably compute temporal and kinematic measures including the translational velocity of the torso and rotational velocities of the lower leg segments. Detecting the instances where velocity changes direction also determines the standard events of a gait cycle (double-support, toe-off, mid-swing and heel-strike). In order to determine the kinematics of lower limbs, we model the synergies between the lower limb motions (thigh-shank, shank-foot) by building a nonlinear dynamical system using CMUs 3D motion capture database. This information is fed into the ensemble Kalman Filter framework to estimate the unobserved limb (upper leg and foot) motion from the measured lower leg rotational velocity. Our approach does not require calibrated cameras or special markers to capture movement. We have tested our method on different gait sequences collected from the sagttal plane and presented the estimated kinematics overlaid on the original image frames. We have also validated our approach by manually labeling the videos and comparing our results against them.

  6. The diagnostics of diabetes mellitus based on ensemble modeling and hair/urine element level analysis.

    PubMed

    Chen, Hui; Tan, Chao; Lin, Zan; Wu, Tong

    2014-07-01

    The aim of the present work focuses on exploring the feasibility of analyzing the relationship between diabetes mellitus and several element levels in hair/urine specimens by chemometrics. A dataset involving 211 specimens and eight element concentrations was used. The control group was divided into three age subsets in order to analyze the influence of age. It was found that the most obvious difference was the effect of age on the level of zinc and iron. The decline of iron concentration with age in hair was exactly consistent with the opposite trend in urine. Principal component analysis (PCA) was used as a tool for a preliminary evaluation of the data. Both ensemble and single support vector machine (SVM) algorithms were used as the classification tools. On average, the accuracy, sensitivity and specificity of ensemble SVM models were 99%, 100%, 99% and 97%, 89%, 99% for hair and urine samples, respectively. The findings indicate that hair samples are superior to urine samples. Even so, it can provide more valuable information for prevention, diagnostics, treatment and research of diabetes by simultaneously analyzing the hair and urine samples.

  7. Streamflow Simulations for the Mississippi River Basin Based on Ensemble Regional Climate Model Simulations

    NASA Astrophysics Data System (ADS)

    Arritt, R. W.; Jha, M.; Takle, E. S.; Gu, R.

    2004-12-01

    Ensemble simulations provide a useful tool for studying uncertainties in climate projections and for deriving probabilistic information from deterministic forecasts. Although a number of studies have examined variability within climate models, fewer have quantified the extent to which variability and uncertainty in climate simulations then propagates through impacts models. Here we evaluate the variability in simulated streamflow that result from taking the streamflow model's inputs from different members of an ensemble of simulations by a decadal-scale nested regional climate model. The regional climate model, RegCM3, simulated a domain covering the continental U.S. and most of Mexico for the period 1986-2003 using initial and lateral boundary conditions from the NCEP-DOE Reanalysis 2. Three RegCM3 realizations were created, each initialized one month apart but otherwise identical in configuration so that their collective behavior provides a measure of internal variability of the climate model. RegCM3 output for daily precipitation, temperature, and radiation were then used as input to the Soil and Water Assessment Tool (SWAT) over the upper Mississippi River basin. Seasonal and interannual variability of SWAT-predicted streamflow indicate that the internal variability of the RegCM3 climate model carries through to produce spread in simulated streamflow from SWAT.

  8. Comment on ``Preserving the Boltzmann ensemble in replica-exchange molecular dynamics'' [J. Chem. Phys. 129, 164112 (2008)

    NASA Astrophysics Data System (ADS)

    Fukuda, Ikuo

    2010-03-01

    A brief discussion of the ergodic description of constant temperature molecular dynamics (MD) is provided; the discussion is based on the analysis of criticisms raised in a recent paper [B. Cooke and S. C. Schmidler, J. Chem. Phys.129, 164112 (2008)]. In the paper, the following criticisms relating to the basic concepts of constant temperature MD are made in mathematical manners: (I) the Nosé-Hoover (NH) equation is not measure-preserving; (II) NH system and NH chain system are not ergodic under the Boltzmann measure; and (III) the Nosé Hamiltonian system as well as the Nosé-Poincaré Hamiltonian system is not ergodic. In this comment, I show the necessity for the reconsideration of these criticisms. The NH equation is measure-preserving, where the measure carries the Boltzmann-Gibbs density; this fact provides the compatibility between MD equation and the Boltzmann-Gibbs distribution. The arguments advanced in support of the above criticisms are unsound; ergodicities of those systems are still not theoretically judged. I discuss exact ergodic-theoretical expressions appropriate for constant temperature MD, and explain the reason behind the incorrect recognitions.

  9. Multi-Conformer Ensemble Docking to Difficult Protein Targets

    SciTech Connect

    Ellingson, Sally R.; Miao, Yinglong; Baudry, Jerome; Smith, Jeremy C.

    2014-09-08

    We investigate large-scale ensemble docking using five proteins from the Directory of Useful Decoys (DUD, dud.docking.org) for which docking to crystal structures has proven difficult. Molecular dynamics trajectories are produced for each protein and an ensemble of representative conformational structures extracted from the trajectories. Docking calculations are performed on these selected simulation structures and ensemble-based enrichment factors compared with those obtained using docking in crystal structures of the same protein targets or random selection of compounds. We also found simulation-derived snapshots with improved enrichment factors that increased the chemical diversity of docking hits for four of the five selected proteins. A combination of all the docking results obtained from molecular dynamics simulation followed by selection of top-ranking compounds appears to be an effective strategy for increasing the number and diversity of hits when using docking to screen large libraries of chemicals against difficult protein targets.

  10. BWM*: A Novel, Provable, Ensemble-based Dynamic Programming Algorithm for Sparse Approximations of Computational Protein Design.

    PubMed

    Jou, Jonathan D; Jain, Swati; Georgiev, Ivelin S; Donald, Bruce R

    2016-06-01

    Sparse energy functions that ignore long range interactions between residue pairs are frequently used by protein design algorithms to reduce computational cost. Current dynamic programming algorithms that fully exploit the optimal substructure produced by these energy functions only compute the GMEC. This disproportionately favors the sequence of a single, static conformation and overlooks better binding sequences with multiple low-energy conformations. Provable, ensemble-based algorithms such as A* avoid this problem, but A* cannot guarantee better performance than exhaustive enumeration. We propose a novel, provable, dynamic programming algorithm called Branch-Width Minimization* (BWM*) to enumerate a gap-free ensemble of conformations in order of increasing energy. Given a branch-decomposition of branch-width w for an n-residue protein design with at most q discrete side-chain conformations per residue, BWM* returns the sparse GMEC in O([Formula: see text]) time and enumerates each additional conformation in merely O([Formula: see text]) time. We define a new measure, Total Effective Search Space (TESS), which can be computed efficiently a priori before BWM* or A* is run. We ran BWM* on 67 protein design problems and found that TESS discriminated between BWM*-efficient and A*-efficient cases with 100% accuracy. As predicted by TESS and validated experimentally, BWM* outperforms A* in 73% of the cases and computes the full ensemble or a close approximation faster than A*, enumerating each additional conformation in milliseconds. Unlike A*, the performance of BWM* can be predicted in polynomial time before running the algorithm, which gives protein designers the power to choose the most efficient algorithm for their particular design problem.

  11. A modified Shockley equation taking into account the multi-element nature of light emitting diodes based on nanowire ensembles.

    PubMed

    Musolino, M; Tahraoui, A; Treeck, D van; Geelhaar, L; Riechert, H

    2016-07-08

    In this work we study how the multi-element nature of light emitting diodes (LEDs) based on nanowire (NW) ensembles influences their current voltage (I-V) characteristics. We systematically address critical issues of the fabrication process that can result in significant fluctuations of the electrical properties among the individual NWs in such LEDs, paying particular attention to the planarization step. Electroluminescence (EL) maps acquired for two nominally identical NW-LEDs reveal that small processing variations can result in a large difference in the number of individual nano-devices emitting EL. The lower number of EL spots in one of the LEDs is caused by its inhomogeneous electrical properties. The I-V characteristics of this LED cannot be described well by the classical Shockley model. We are able to take into account the multi-element nature of such LEDs and fit the I-V characteristics in the forward bias regime by employing an ad hoc adjusted version of the Shockley equation. More specifically, we introduce a bias dependence of the ideality factor. The basic considerations of our model should remain valid also for other types of devices based on ensembles of interconnected p-n junctions with inhomogeneous electrical properties, regardless of the employed material system.

  12. A mutual information-Dempster-Shafer based decision ensemble system for land cover classification of hyperspectral data

    NASA Astrophysics Data System (ADS)

    Pahlavani, Parham; Bigdeli, Behnaz

    2016-12-01

    Hyperspectral images contain extremely rich spectral information that offer great potential to discriminate between various land cover classes. However, these images are usually composed of tens or hundreds of spectrally close bands, which result in high redundancy and great amount of computation time in hyperspectral classification. Furthermore, in the presence of mixed coverage pixels, crisp classifiers produced errors, omission and commission. This paper presents a mutual information-Dempster-Shafer system through an ensemble classification approach for classification of hyperspectral data. First, mutual information is applied to split data into a few independent partitions to overcome high dimensionality. Then, a fuzzy maximum likelihood classifies each band subset. Finally, Dempster-Shafer is applied to fuse the results of the fuzzy classifiers. In order to assess the proposed method, a crisp ensemble system based on a support vector machine as the crisp classifier and weighted majority voting as the crisp fusion method are applied on hyperspectral data. Furthermore, a dimension reduction system is utilized to assess the effectiveness of mutual information band splitting of the proposed method. The proposed methodology provides interesting conclusions on the effectiveness and potentiality of mutual information-Dempster-Shafer based classification of hyperspectral data.

  13. A novel computer-aided diagnosis system for breast MRI based on feature selection and ensemble learning.

    PubMed

    Lu, Wei; Li, Zhe; Chu, Jinghui

    2017-03-06

    Breast cancer is a common cancer among women. With the development of modern medical science and information technology, medical imaging techniques have an increasingly important role in the early detection and diagnosis of breast cancer. In this paper, we propose an automated computer-aided diagnosis (CADx) framework for magnetic resonance imaging (MRI). The scheme consists of an ensemble of several machine learning-based techniques, including ensemble under-sampling (EUS) for imbalanced data processing, the Relief algorithm for feature selection, the subspace method for providing data diversity, and Adaboost for improving the performance of base classifiers. We extracted morphological, various texture, and Gabor features. To clarify the feature subsets' physical meaning, subspaces are built by combining morphological features with each kind of texture or Gabor feature. We tested our proposal using a manually segmented Region of Interest (ROI) data set, which contains 438 images of malignant tumors and 1898 images of normal tissues or benign tumors. Our proposal achieves an area under the ROC curve (AUC) value of 0.9617, which outperforms most other state-of-the-art breast MRI CADx systems. Compared with other methods, our proposal significantly reduces the false-positive classification rate.

  14. Assessing a robust ensemble-based Kalman filter for efficient ecosystem data assimilation of the Cretan Sea

    NASA Astrophysics Data System (ADS)

    Triantafyllou, G.; Hoteit, I.; Luo, X.; Tsiaras, K.; Petihakis, G.

    2013-09-01

    An application of an ensemble-based robust filter for data assimilation into an ecosystem model of the Cretan Sea is presented and discussed. The ecosystem model comprises two on-line coupled sub-models: the Princeton Ocean Model (POM) and the European Regional Seas Ecosystem Model (ERSEM). The filtering scheme is based on the Singular Evolutive Interpolated Kalman (SEIK) filter which is implemented with a time-local H∞ filtering strategy to enhance robustness and performances during periods of strong ecosystem variability. Assimilation experiments in the Cretan Sea indicate that robustness can be achieved in the SEIK filter by introducing an adaptive inflation scheme of the modes of the filter error covariance matrix. Twin-experiments are performed to evaluate the performance of the assimilation system and to study the benefits of using robust filtering in an ensemble filtering framework. Pseudo-observations of surface chlorophyll, extracted from a model reference run, were assimilated every two days. Simulation results suggest that the adaptive inflation scheme significantly improves the behavior of the SEIK filter during periods of strong ecosystem variability.

  15. A modified Shockley equation taking into account the multi-element nature of light emitting diodes based on nanowire ensembles

    NASA Astrophysics Data System (ADS)

    Musolino, M.; Tahraoui, A.; van Treeck, D.; Geelhaar, L.; Riechert, H.

    2016-07-01

    In this work we study how the multi-element nature of light emitting diodes (LEDs) based on nanowire (NW) ensembles influences their current voltage (I-V) characteristics. We systematically address critical issues of the fabrication process that can result in significant fluctuations of the electrical properties among the individual NWs in such LEDs, paying particular attention to the planarization step. Electroluminescence (EL) maps acquired for two nominally identical NW-LEDs reveal that small processing variations can result in a large difference in the number of individual nano-devices emitting EL. The lower number of EL spots in one of the LEDs is caused by its inhomogeneous electrical properties. The I-V characteristics of this LED cannot be described well by the classical Shockley model. We are able to take into account the multi-element nature of such LEDs and fit the I-V characteristics in the forward bias regime by employing an ad hoc adjusted version of the Shockley equation. More specifically, we introduce a bias dependence of the ideality factor. The basic considerations of our model should remain valid also for other types of devices based on ensembles of interconnected p-n junctions with inhomogeneous electrical properties, regardless of the employed material system.

  16. A novel hybrid decomposition-and-ensemble model based on CEEMD and GWO for short-term PM2.5 concentration forecasting

    NASA Astrophysics Data System (ADS)

    Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu

    2016-06-01

    To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.

  17. Hybrid MPI/OpenMP Implementation of the ORAC Molecular Dynamics Program for Generalized Ensemble and Fast Switching Alchemical Simulations.

    PubMed

    Procacci, Piero

    2016-06-27

    We present a new release (6.0β) of the ORAC program [Marsili et al. J. Comput. Chem. 2010, 31, 1106-1116] with a hybrid OpenMP/MPI (open multiprocessing message passing interface) multilevel parallelism tailored for generalized ensemble (GE) and fast switching double annihilation (FS-DAM) nonequilibrium technology aimed at evaluating the binding free energy in drug-receptor system on high performance computing platforms. The production of the GE or FS-DAM trajectories is handled using a weak scaling parallel approach on the MPI level only, while a strong scaling force decomposition scheme is implemented for intranode computations with shared memory access at the OpenMP level. The efficiency, simplicity, and inherent parallel nature of the ORAC implementation of the FS-DAM algorithm, project the code as a possible effective tool for a second generation high throughput virtual screening in drug discovery and design. The code, along with documentation, testing, and ancillary tools, is distributed under the provisions of the General Public License and can be freely downloaded at www.chim.unifi.it/orac .

  18. Carbon Nanotube Based Molecular Electronics

    NASA Technical Reports Server (NTRS)

    Srivastava, Deepak; Saini, Subhash; Menon, Madhu

    1998-01-01

    Carbon nanotubes and the nanotube heterojunctions have recently emerged as excellent candidates for nanoscale molecular electronic device components. Experimental measurements on the conductivity, rectifying behavior and conductivity-chirality correlation have also been made. While quasi-one dimensional simple heterojunctions between nanotubes with different electronic behavior can be generated by introduction of a pair of heptagon-pentagon defects in an otherwise all hexagon graphene sheet. Other complex 3- and 4-point junctions may require other mechanisms. Structural stability as well as local electronic density of states of various nanotube junctions are investigated using a generalized tight-binding molecular dynamics (GDBMD) scheme that incorporates non-orthogonality of the orbitals. The junctions investigated include straight and small angle heterojunctions of various chiralities and diameters; as well as more complex 'T' and 'Y' junctions which do not always obey the usual pentagon-heptagon pair rule. The study of local density of states (LDOS) reveal many interesting features, most prominent among them being the defect-induced states in the gap. The proposed three and four pointjunctions are one of the smallest possible tunnel junctions made entirely of carbon atoms. Furthermore the electronic behavior of the nanotube based device components can be taylored by doping with group III-V elements such as B and N, and BN nanotubes as a wide band gap semiconductor has also been realized in experiments. Structural properties of heteroatomic nanotubes comprising C, B and N will be discussed.

  19. An efficient ensemble of radial basis functions method based on quadratic programming

    NASA Astrophysics Data System (ADS)

    Shi, Renhe; Liu, Li; Long, Teng; Liu, Jian

    2016-07-01

    Radial basis function (RBF) surrogate models have been widely applied in engineering design optimization problems to approximate computationally expensive simulations. Ensemble of radial basis functions (ERBF) using the weighted sum of stand-alone RBFs improves the approximation performance. To achieve a good trade-off between the accuracy and efficiency of the modelling process, this article presents a novel efficient ERBF method to determine the weights through solving a quadratic programming subproblem, denoted ERBF-QP. Several numerical benchmark functions are utilized to test the performance of the proposed ERBF-QP method. The results show that ERBF-QP can significantly improve the modelling efficiency compared with several existing ERBF methods. Moreover, ERBF-QP also provides satisfactory performance in terms of approximation accuracy. Finally, the ERBF-QP method is applied to a satellite multidisciplinary design optimization problem to illustrate its practicality and effectiveness for real-world engineering applications.

  20. [Simulation of cropland soil moisture based on an ensemble Kalman filter].

    PubMed

    Liu, Zhao; Zhou, Yan-Lian; Ju, Wei-Min; Gao, Ping

    2011-11-01

    By using an ensemble Kalman filter (EnKF) to assimilate the observed soil moisture data, the modified boreal ecosystem productivity simulator (BEPS) model was adopted to simulate the dynamics of soil moisture in winter wheat root zones at Xuzhou Agro-meteorological Station, Jiangsu Province of China during the growth seasons in 2000-2004. After the assimilation of observed data, the determination coefficient, root mean square error, and average absolute error of simulated soil moisture were in the ranges of 0.626-0.943, 0.018-0.042, and 0.021-0.041, respectively, with the simulation precision improved significantly, as compared with that before assimilation, indicating the applicability of data assimilation in improving the simulation of soil moisture. The experimental results at single point showed that the errors in the forcing data and observations and the frequency and soil depth of the assimilation of observed data all had obvious effects on the simulated soil moisture.

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

    SciTech Connect

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

    2015-07-30

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

  2. Stability evaluation of short-circuiting gas metal arc welding based on ensemble empirical mode decomposition

    NASA Astrophysics Data System (ADS)

    Huang, Yong; Wang, Kehong; Zhou, Zhilan; Zhou, Xiaoxiao; Fang, Jimi

    2017-03-01

    The arc of gas metal arc welding (GMAW) contains abundant information about its stability and droplet transition, which can be effectively characterized by extracting the arc electrical signals. In this study, ensemble empirical mode decomposition (EEMD) was used to evaluate the stability of electrical current signals. The welding electrical signals were first decomposed by EEMD, and then transformed to a Hilbert–Huang spectrum and a marginal spectrum. The marginal spectrum is an approximate distribution of amplitude with frequency of signals, and can be described by a marginal index. Analysis of various welding process parameters showed that the marginal index of current signals increased when the welding process was more stable, and vice versa. Thus EEMD combined with the marginal index can effectively uncover the stability and droplet transition of GMAW.

  3. Bearing fault detection based on hybrid ensemble detector and empirical mode decomposition

    NASA Astrophysics Data System (ADS)

    Georgoulas, George; Loutas, Theodore; Stylios, Chrysostomos D.; Kostopoulos, Vassilis

    2013-12-01

    Aiming at more efficient fault diagnosis, this research work presents an integrated anomaly detection approach for seeded bearing faults. Vibration signals from normal bearings and bearings with three different fault locations, as well as different fault sizes and loading conditions are examined. The Empirical Mode Decomposition and the Hilbert Huang transform are employed for the extraction of a compact feature set. Then, a hybrid ensemble detector is trained using data coming only from the normal bearings and it is successfully applied for the detection of any deviation from the normal condition. The results prove the potential use of the proposed scheme as a first stage of an alarm signalling system for the detection of bearing faults irrespective of their loading condition.

  4. A WRF-based ensemble data assimilation system for dynamic downscaling of satellite precipitation information (Invited)

    NASA Astrophysics Data System (ADS)

    Zhang, S. Q.; Hou, A. Y.; Zupanski, M.; Cheung, S.

    2010-12-01

    For many hydrological applications, dynamic downscaling from global analyses has been used to provide local scale information on spatial and temporal distribution of precipitation and other associated environmental parameters. In the near future the NASA Global Precipitation Measurement (GPM) Mission will provide new sources of precipitation observations with unprecedented spatial and temporal coverage for better understanding and prediction of climate, weather and hydro-meteorological processes. However, in terms of using precipitation observations in global analyses and forecasts, the capability of current operational systems is generally limited by the global model resolution, the requirement of linearization of parameterized cloud physics, and the static forecast error statistics often with no distinction for clear sky or storm. In order to maximize the utilization of satellite precipitation observations in dynamic downscaling for hydrological applications, an ensemble data assimilation system (Goddard-WRF-EDAS) has been developed jointly by NASA Goddard and Colorado State University (CSU). The system takes advantages of the cloud-resolving high-resolution of the Weather Research and Forecasting (WRF) model with NASA Goddard microphysics and the flow-dependent estimation of forecast error covariance from the Maximum Likelihood Ensemble Filter (MLEF). Satellite observed radiances in precipitation regions are assimilated using Goddard Satellite Data Simulator Unit (SDSU) as the observation operator. Experimental results using current available satellite precipitation data (AMSR-E and TRMM-TMI) are presented to investigate the ability of the assimilation system in ingesting information from in-situ and satellite observations to produce dynamically downscaled precipitation. The results from the assimilation of precipitation-affected microwave radiances in a storm case and in a heavy rainfall event demonstrate the data impact to down-scaled precipitation and

  5. Effects of ensembles on methane hydrate nucleation kinetics.

    PubMed

    Zhang, Zhengcai; Liu, Chan-Juan; Walsh, Matthew R; Guo, Guang-Jun

    2016-06-21

    By performing molecular dynamics simulations to form a hydrate with a methane nano-bubble in liquid water at 250 K and 50 MPa, we report how different ensembles, such as the NPT, NVT, and NVE ensembles, affect the nucleation kinetics of the methane hydrate. The nucleation trajectories are monitored using the face-saturated incomplete cage analysis (FSICA) and the mutually coordinated guest (MCG) order parameter (OP). The nucleation rate and the critical nucleus are obtained using the mean first-passage time (MFPT) method based on the FS cages and the MCG-1 OPs, respectively. The fitting results of MFPT show that hydrate nucleation and growth are coupled together, consistent with the cage adsorption hypothesis which emphasizes that the cage adsorption of methane is a mechanism for both hydrate nucleation and growth. For the three different ensembles, the hydrate nucleation rate is quantitatively ordered as follows: NPT > NVT > NVE, while the sequence of hydrate crystallinity is exactly reversed. However, the largest size of the critical nucleus appears in the NVT ensemble, rather than in the NVE ensemble. These results are helpful for choosing a suitable ensemble when to study hydrate formation via computer simulations, and emphasize the importance of the order degree of the critical nucleus.

  6. The Ensembl gene annotation system

    PubMed Central

    Aken, Bronwen L.; Ayling, Sarah; Barrell, Daniel; Clarke, Laura; Curwen, Valery; Fairley, Susan; Fernandez Banet, Julio; Billis, Konstantinos; García Girón, Carlos; Hourlier, Thibaut; Howe, Kevin; Kähäri, Andreas; Kokocinski, Felix; Martin, Fergal J.; Murphy, Daniel N.; Nag, Rishi; Ruffier, Magali; Schuster, Michael; Tang, Y. Amy; Vogel, Jan-Hinnerk; White, Simon; Zadissa, Amonida; Flicek, Paul

    2016-01-01

    The Ensembl gene annotation system has been used to annotate over 70 different vertebrate species across a wide range of genome projects. Furthermore, it generates the automatic alignment-based annotation for the human and mouse GENCODE gene sets. The system is based on the alignment of biological sequences, including cDNAs, proteins and RNA-seq reads, to the target genome in order to construct candidate transcript models. Careful assessment and filtering of these candidate transcripts ultimately leads to the final gene set, which is made available on the Ensembl website. Here, we describe the annotation process in detail. Database URL: http://www.ensembl.org/index.html PMID:27337980

  7. Conformational Ensemble of hIAPP Dimer: Insight into the Molecular Mechanism by which a Green Tea Extract inhibits hIAPP Aggregation

    PubMed Central

    Mo, Yuxiang; Lei, Jiangtao; Sun, Yunxiang; Zhang, Qingwen; Wei, Guanghong

    2016-01-01

    Small oligomers formed early along human islet amyloid polypeptide (hIAPP) aggregation is responsible for the cell death in Type II diabetes. The epigallocatechin gallate (EGCG), a green tea extract, was found to inhibit hIAPP fibrillation. However, the inhibition mechanism and the conformational distribution of the smallest hIAPP oligomer – dimer are mostly unknown. Herein, we performed extensive replica exchange molecular dynamic simulations on hIAPP dimer with and without EGCG molecules. Extended hIAPP dimer conformations, with a collision cross section value similar to that observed by ion mobility-mass spectrometry, were observed in our simulations. Notably, these dimers adopt a three-stranded antiparallel β-sheet and contain the previously reported β-hairpin amyloidogenic precursor. We find that EGCG binding strongly blocks both the inter-peptide hydrophobic and aromatic-stacking interactions responsible for inter-peptide β-sheet formation and intra-peptide interaction crucial for β-hairpin formation, thus abolishes the three-stranded β-sheet structures and leads to the formation of coil-rich conformations. Hydrophobic, aromatic-stacking, cation-π and hydrogen-bonding interactions jointly contribute to the EGCG-induced conformational shift. This study provides, on atomic level, the conformational ensemble of hIAPP dimer and the molecular mechanism by which EGCG inhibits hIAPP aggregation. PMID:27620620

  8. Conformational Ensemble of hIAPP Dimer: Insight into the Molecular Mechanism by which a Green Tea Extract inhibits hIAPP Aggregation

    NASA Astrophysics Data System (ADS)

    Mo, Yuxiang; Lei, Jiangtao; Sun, Yunxiang; Zhang, Qingwen; Wei, Guanghong

    2016-09-01

    Small oligomers formed early along human islet amyloid polypeptide (hIAPP) aggregation is responsible for the cell death in Type II diabetes. The epigallocatechin gallate (EGCG), a green tea extract, was found to inhibit hIAPP fibrillation. However, the inhibition mechanism and the conformational distribution of the smallest hIAPP oligomer – dimer are mostly unknown. Herein, we performed extensive replica exchange molecular dynamic simulations on hIAPP dimer with and without EGCG molecules. Extended hIAPP dimer conformations, with a collision cross section value similar to that observed by ion mobility-mass spectrometry, were observed in our simulations. Notably, these dimers adopt a three-stranded antiparallel β-sheet and contain the previously reported β-hairpin amyloidogenic precursor. We find that EGCG binding strongly blocks both the inter-peptide hydrophobic and aromatic-stacking interactions responsible for inter-peptide β-sheet formation and intra-peptide interaction crucial for β-hairpin formation, thus abolishes the three-stranded β-sheet structures and leads to the formation of coil-rich conformations. Hydrophobic, aromatic-stacking, cation-π and hydrogen-bonding interactions jointly contribute to the EGCG-induced conformational shift. This study provides, on atomic level, the conformational ensemble of hIAPP dimer and the molecular mechanism by which EGCG inhibits hIAPP aggregation.

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

    NASA Astrophysics Data System (ADS)

    Walcott, Sam

    2013-03-01

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

  10. Progress in Multi-Center Probabilistic Wave Forecasting and Ensemble-Based Data Assimilation using LETKF at the US National Weather Service

    NASA Astrophysics Data System (ADS)

    Alves, Jose-Henrique; Bernier, Natacha; Etala, Paula; Wittmann, Paul

    2015-04-01

    The combination of ensemble predictions of Hs made by the US National Weather Service (NEW) and the US Navy Fleet Numerical Meteorological and Oceanography Center (FNMOC) has established the NFCENS, a probabilistic wave forecast system in operations at NCEP since 2011. Computed from 41 combined wave ensemble members, the new product outperforms deterministic and probabilistic forecasts and nowcasts of Hs issued separately at each forecast center, at all forecast ranges. The successful implementation of the NFCENS has brought new opportunities for collaboration with Environment Canada (EC). EC is in the process of adding new global wave model ensemble products to its existing suite of operational regional products. The planned upgrade to the current NFCENS wave multi-center ensemble includes the addition of 20 members from the Canadian WES. With this upgrade, the NFCENS will be renamed North American Wave Ensemble System (NAWES). As part of the new system implementation, new higher-resolution grids and upgrades to model physics using recent advances in source-term parameterizations are being tested. We provide results of a first validation of NAWES relative to global altimeter data, and buoy measurements of waves, as well as its ability to forecast waves during the 2012 North Atlantic hurricane Sandy. A second line of research involving wave ensembles at the NWS is the implementation of a LETKF-based data assimilation system developed in collaboration with the Argentinian Navy Meteorological Service. The project involves an implementation of the 4D-LETKF in the NWS global wave ensemble forecast system GWES. The 4-D scheme initializes a full 81-member ensemble in a 6-hour cycle. The LETKF determines the analysis ensemble locally in the space spanned by the ensemble, as a linear combination of the background perturbations. Observations from three altimeters and one scatterometer were used. Preliminary results for a prototype system running at the NWS, including

  11. Ensemble Kalman Filter vs Particle Filter in a Physically Based Coupled Model of Surface-Subsurface Flow (Invited)

    NASA Astrophysics Data System (ADS)

    Putti, M.; Camporese, M.; Pasetto, D.

    2010-12-01

    Data assimilation (DA) has recently received growing interest by the hydrological modeling community due to its capability to merge observations into model prediction. Among the many DA methods available, the Ensemble Kalman Filter (EnKF) and the Particle Filter (PF) are suitable alternatives for applications to detailed physically-based hydrological models. For each assimilation period, both methods use a Monte Carlo approach to approximate the state probability distribution (in terms of mean and covariance matrix) by a finite number of independent model trajectories, also called particles or realizations. The two approaches differ in the way the filtering distribution is evaluated. EnKF implements the classical Kalman filter, optimal only for linear dynamics and Gaussian error statistics. Particle filters, instead, use directly the recursive formula of the sequential Bayesian framework and approximate the posterior probability distributions by means of appropriate weights associated to each realization. We use the Sequential Importance Resampling (SIR) technique, which retains only the most probable particles, in practice the trajectories closest in a statistical sense to the observations, and duplicates them when needed. In contrast to EnKF, particle filters make no assumptions on the form of the prior distribution of the model state, and convergence to the true state is ensured for large enough ensemble size. In this study EnKF and PF have been implemented in a physically based catchment simulator that couples a three-dimensional finite element Richards equation solver with a finite difference diffusion wave approximation based on a digital elevation data for surface water dynamics. We report on the retrieval performance of the two schemes using a three-dimensional tilted v-catchment synthetic test case in which multi-source observations are assimilated (pressure head, soil moisture, and streamflow data). The comparison between the results of the two approaches

  12. Efficient ensemble system based on the copper binding motif for highly sensitive and selective detection of cyanide ions in 100% aqueous solutions by fluorescent and colorimetric changes.

    PubMed

    Jung, Kwan Ho; Lee, Keun-Hyeung

    2015-09-15

    A peptide-based ensemble for the detection of cyanide ions in 100% aqueous solutions was designed on the basis of the copper binding motif. 7-Nitro-2,1,3-benzoxadiazole-labeled tripeptide (NBD-SSH, NBD-SerSerHis) formed the ensemble with Cu(2+), leading to a change in the color of the solution from yellow to orange and a complete decrease of fluorescence emission. The ensemble (NBD-SSH-Cu(2+)) sensitively and selectively detected a low concentration of cyanide ions in 100% aqueous solutions by a colorimetric change as well as a fluorescent change. The addition of cyanide ions instantly removed Cu(2+) from the ensemble (NBD-SSH-Cu(2+)) in 100% aqueous solutions, resulting in a color change of the solution from orange to yellow and a "turn-on" fluorescent response. The detection limits for cyanide ions were lower than the maximum allowable level of cyanide ions in drinking water set by the World Health Organization. The peptide-based ensemble system is expected to be a potential and practical way for the detection of submicromolar concentrations of cyanide ions in 100% aqueous solutions.

  13. Rolling bearing fault detection and diagnosis based on composite multiscale fuzzy entropy and ensemble support vector machines

    NASA Astrophysics Data System (ADS)

    Zheng, Jinde; Pan, Haiyang; Cheng, Junsheng

    2017-02-01

    To timely detect the incipient failure of rolling bearing and find out the accurate fault location, a novel rolling bearing fault diagnosis method is proposed based on the composite multiscale fuzzy entropy (CMFE) and ensemble support vector machines (ESVMs). Fuzzy entropy (FuzzyEn), as an improvement of sample entropy (SampEn), is a new nonlinear method for measuring the complexity of time series. Since FuzzyEn (or SampEn) in single scale can not reflect the complexity effectively, multiscale fuzzy entropy (MFE) is developed by defining the FuzzyEns of coarse-grained time series, which represents the system dynamics in different scales. However, the MFE values will be affected by the data length, especially when the data are not long enough. By combining information of multiple coarse-grained time series in the same scale, the CMFE algorithm is proposed in this paper to enhance MFE, as well as FuzzyEn. Compared with MFE, with the increasing of scale factor, CMFE obtains much more stable and consistent values for a short-term time series. In this paper CMFE is employed to measure the complexity of vibration signals of rolling bearings and is applied to extract the nonlinear features hidden in the vibration signals. Also the physically meanings of CMFE being suitable for rolling bearing fault diagnosis are explored. Based on these, to fulfill an automatic fault diagnosis, the ensemble SVMs based multi-classifier is constructed for the intelligent classification of fault features. Finally, the proposed fault diagnosis method of rolling bearing is applied to experimental data analysis and the results indicate that the proposed method could effectively distinguish different fault categories and severities of rolling bearings.

  14. Future changes to drought characteristics over the Canadian Prairie Provinces based on NARCCAP multi-RCM ensemble

    NASA Astrophysics Data System (ADS)

    Masud, M. B.; Khaliq, M. N.; Wheater, H. S.

    2016-06-01

    This study assesses projected changes to drought characteristics in Alberta, Saskatchewan and Manitoba, the prairie provinces of Canada, using a multi-regional climate model (RCM) ensemble available through the North American Regional Climate Change Assessment Program. Simulations considered include those performed with six RCMs driven by National Center for Environmental Prediction reanalysis II for the 1981-2003 period and those driven by four Atmosphere-Ocean General Circulation Models for the 1970-1999 and 2041-2070 periods (i.e. eleven current and the same number of corresponding future period simulations). Drought characteristics are extracted using two drought indices, namely the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Regional frequency analysis is used to project changes to selected 20- and 50-year regional return levels of drought characteristics for fifteen homogeneous regions, covering the study area. In addition, multivariate analyses of drought characteristics, derived on the basis of 6-month SPI and SPEI values, are developed using the copula approach for each region. Analysis of multi-RCM ensemble-averaged projected changes to mean and selected return levels of drought characteristics show increases over the southern and south-western parts of the study area. Based on bi- and trivariate joint occurrence probabilities of drought characteristics, the southern regions along with the central regions are found highly drought vulnerable, followed by the southwestern and southeastern regions. Compared to the SPI-based analysis, the results based on SPEI suggest drier conditions over many regions in the future, indicating potential effects of rising temperatures on drought risks. These projections will be useful in the development of appropriate adaptation strategies for the water and agricultural sectors, which play an important role in the economy of the study area.

  15. Cardiopulmonary Resuscitation Pattern Evaluation Based on Ensemble Empirical Mode Decomposition Filter via Nonlinear Approaches

    PubMed Central

    Ma, Matthew Huei-Ming

    2016-01-01

    Good quality cardiopulmonary resuscitation (CPR) is the mainstay of treatment for managing patients with out-of-hospital cardiac arrest (OHCA). Assessment of the quality of the CPR delivered is now possible through the electrocardiography (ECG) signal that can be collected by an automated external defibrillator (AED). This study evaluates a nonlinear approximation of the CPR given to the asystole patients. The raw ECG signal is filtered using ensemble empirical mode decomposition (EEMD), and the CPR-related intrinsic mode functions (IMF) are chosen to be evaluated. In addition, sample entropy (SE), complexity index (CI), and detrended fluctuation algorithm (DFA) are collated and statistical analysis is performed using ANOVA. The primary outcome measure assessed is the patient survival rate after two hours. CPR pattern of 951 asystole patients was analyzed for quality of CPR delivered. There was no significant difference observed in the CPR-related IMFs peak-to-peak interval analysis for patients who are younger or older than 60 years of age, similarly to the amplitude difference evaluation for SE and DFA. However, there is a difference noted for the CI (p < 0.05). The results show that patients group younger than 60 years have higher survival rate with high complexity of the CPR-IMFs amplitude differences. PMID:27529068

  16. Predictive Skill of Meteorological Drought Based on Multi-Model Ensemble Forecasts: A Real-Time Assessment

    NASA Astrophysics Data System (ADS)

    Chen, L. C.; Mo, K. C.; Zhang, Q.; Huang, J.

    2014-12-01

    Drought prediction from monthly to seasonal time scales is of critical importance to disaster mitigation, agricultural planning, and multi-purpose reservoir management. Starting in December 2012, NOAA Climate Prediction Center (CPC) has been providing operational Standardized Precipitation Index (SPI) Outlooks using the North American Multi-Model Ensemble (NMME) forecasts, to support CPC's monthly drought outlooks and briefing activities. The current NMME system consists of six model forecasts from U.S. and Canada modeling centers, including the CFSv2, CM2.1, GEOS-5, CCSM3.0, CanCM3, and CanCM4 models. In this study, we conduct an assessment of the predictive skill of meteorological drought using real-time NMME forecasts for the period from May 2012 to May 2014. The ensemble SPI forecasts are the equally weighted mean of the six model forecasts. Two performance measures, the anomaly correlation coefficient and root-mean-square errors against the observations, are used to evaluate forecast skill.Similar to the assessment based on NMME retrospective forecasts, predictive skill of monthly-mean precipitation (P) forecasts is generally low after the second month and errors vary among models. Although P forecast skill is not large, SPI predictive skill is high and the differences among models are small. The skill mainly comes from the P observations appended to the model forecasts. This factor also contributes to the similarity of SPI prediction among the six models. Still, NMME SPI ensemble forecasts have higher skill than those based on individual models or persistence, and the 6-month SPI forecasts are skillful out to four months. The three major drought events occurred during the 2012-2014 period, the 2012 Central Great Plains drought, the 2013 Upper Midwest flash drought, and 2013-2014 California drought, are used as examples to illustrate the system's strength and limitations. For precipitation-driven drought events, such as the 2012 Central Great Plains drought

  17. Fault identification of rotor-bearing system based on ensemble empirical mode decomposition and self-zero space projection analysis

    NASA Astrophysics Data System (ADS)

    Jiang, Fan; Zhu, Zhencai; Li, Wei; Zhou, Gongbo; Chen, Guoan

    2014-07-01

    Accurately identifying faults in rotor-bearing systems by analyzing vibration signals, which are nonlinear and nonstationary, is challenging. To address this issue, a new approach based on ensemble empirical mode decomposition (EEMD) and self-zero space projection analysis is proposed in this paper. This method seeks to identify faults appearing in a rotor-bearing system using simple algebraic calculations and projection analyses. First, EEMD is applied to decompose the collected vibration signals into a set of intrinsic mode functions (IMFs) for features. Second, these extracted features under various mechanical health conditions are used to design a self-zero space matrix according to space projection analysis. Finally, the so-called projection indicators are calculated to identify the rotor-bearing system's faults with simple decision logic. Experiments are implemented to test the reliability and effectiveness of the proposed approach. The results show that this approach can accurately identify faults in rotor-bearing systems.

  18. DIME: R-package for identifying differential ChIP-seq based on an ensemble of mixture models

    PubMed Central

    Taslim, Cenny; Huang, Tim; Lin, Shili

    2011-01-01

    Summary: Differential Identification using Mixtures Ensemble (DIME) is a package for identification of biologically significant differential binding sites between two conditions using ChIP-seq data. It considers a collection of finite mixture models combined with a false discovery rate (FDR) criterion to find statistically significant regions. This leads to a more reliable assessment of differential binding sites based on a statistical approach. In addition to ChIP-seq, DIME is also applicable to data from other high-throughput platforms. Availability and implementation: DIME is implemented as an R-package, which is available at http://www.stat.osu.edu/~statgen/SOFTWARE/DIME. It may also be downloaded from http://cran.r-project.org/web/packages/DIME/. Contact: shili@stat.osu.edu PMID:21471015

  19. A novel approach for baseline correction in 1H-MRS signals based on ensemble empirical mode decomposition.

    PubMed

    Parto Dezfouli, Mohammad Ali; Dezfouli, Mohsen Parto; Rad, Hamidreza Saligheh

    2014-01-01

    Proton magnetic resonance spectroscopy ((1)H-MRS) is a non-invasive diagnostic tool for measuring biochemical changes in the human body. Acquired (1)H-MRS signals may be corrupted due to a wideband baseline signal generated by macromolecules. Recently, several methods have been developed for the correction of such baseline signals, however most of them are not able to estimate baseline in complex overlapped signal. In this study, a novel automatic baseline correction method is proposed for (1)H-MRS spectra based on ensemble empirical mode decomposition (EEMD). This investigation was applied on both the simulated data and the in-vivo (1)H-MRS of human brain signals. Results justify the efficiency of the proposed method to remove the baseline from (1)H-MRS signals.

  20. Tangent-linear and ensemble-based four-dimensional data assimilation strategies applied for assimilating conventional data and field observations for Hurricane Karl (2010)

    NASA Astrophysics Data System (ADS)

    Poterjoy, J.; Zhang, F.

    2014-12-01

    Two advanced four-dimensional ensemble data assimilation systems are applied for studying the genesis of Hurricane Karl (2010) using conventional observations and measurements collected during the Pre-Depression Investigation of Cloud Systems in the Tropics (PREDICT) field campaign. Both methods combine strategies from four-dimensional variational (4DVar) and Ensemble Kalman filter (EnKF) data assimilation techniques that have been developed for the Weather Research and Forecasting model. The first method, denoted E4DVar, operates in a manner similar to the traditional 4DVar data assimilation system, but with hybrid climate/ensemble background errors. The second method, denoted 4DEnVar, uses an ensemble of nonlinear model trajectories to replace the function of tangent linear and adjoint model operators in 4DVar, thus improving the parallelization of the data assimilation. Simulations initialized from E4DVar and 4DEnVar analyses provide track, genesis and intensity forecasts for Karl that are more accurate than an ensemble hybrid data assimilation method based on 3DVar (E3DVar). The two 4-D data assimilation methods are applied for studying Karl's genesis, while comparing their theoretical advantages and disadvantages for an application where the system dynamics evolve quickly in time, and are constrained by an unusually high number of in situ observations.

  1. Gold price analysis based on ensemble empirical model decomposition and independent component analysis

    NASA Astrophysics Data System (ADS)

    Xian, Lu; He, Kaijian; Lai, Kin Keung

    2016-07-01

    In recent years, the increasing level of volatility of the gold price has received the increasing level of attention from the academia and industry alike. Due to the complexity and significant fluctuations observed in the gold market, however, most of current approaches have failed to produce robust and consistent modeling and forecasting results. Ensemble Empirical Model Decomposition (EEMD) and Independent Component Analysis (ICA) are novel data analysis methods that can deal with nonlinear and non-stationary time series. This study introduces a new methodology which combines the two methods and applies it to gold price analysis. This includes three steps: firstly, the original gold price series is decomposed into several Intrinsic Mode Functions (IMFs) by EEMD. Secondly, IMFs are further processed with unimportant ones re-grouped. Then a new set of data called Virtual Intrinsic Mode Functions (VIMFs) is reconstructed. Finally, ICA is used to decompose VIMFs into statistically Independent Components (ICs). The decomposition results reveal that the gold price series can be represented by the linear combination of ICs. Furthermore, the economic meanings of ICs are analyzed and discussed in detail, according to the change trend and ICs' transformation coefficients. The analyses not only explain the inner driving factors and their impacts but also conduct in-depth analysis on how these factors affect gold price. At the same time, regression analysis has been conducted to verify our analysis. Results from the empirical studies in the gold markets show that the EEMD-ICA serve as an effective technique for gold price analysis from a new perspective.

  2. Ensemble Empirical Mode Decomposition based methodology for ultrasonic testing of coarse grain austenitic stainless steels.

    PubMed

    Sharma, Govind K; Kumar, Anish; Jayakumar, T; Purnachandra Rao, B; Mariyappa, N

    2015-03-01

    A signal processing methodology is proposed in this paper for effective reconstruction of ultrasonic signals in coarse grained high scattering austenitic stainless steel. The proposed methodology is comprised of the Ensemble Empirical Mode Decomposition (EEMD) processing of ultrasonic signals and application of signal minimisation algorithm on selected Intrinsic Mode Functions (IMFs) obtained by EEMD. The methodology is applied to ultrasonic signals obtained from austenitic stainless steel specimens of different grain size, with and without defects. The influence of probe frequency and data length of a signal on EEMD decomposition is also investigated. For a particular sampling rate and probe frequency, the same range of IMFs can be used to reconstruct the ultrasonic signal, irrespective of the grain size in the range of 30-210 μm investigated in this study. This methodology is successfully employed for detection of defects in a 50mm thick coarse grain austenitic stainless steel specimens. Signal to noise ratio improvement of better than 15 dB is observed for the ultrasonic signal obtained from a 25 mm deep flat bottom hole in 200 μm grain size specimen. For ultrasonic signals obtained from defects at different depths, a minimum of 7 dB extra enhancement in SNR is achieved as compared to the sum of selected IMF approach. The application of minimisation algorithm with EEMD processed signal in the proposed methodology proves to be effective for adaptive signal reconstruction with improved signal to noise ratio. This methodology was further employed for successful imaging of defects in a B-scan.

  3. Multi-model ensemble forecasts of tropical cyclones in 2010 and 2011 based on the Kalman Filter method

    NASA Astrophysics Data System (ADS)

    He, Chengfei; Zhi, Xiefei; You, Qinglong; Song, Bin; Fraedrich, Klaus

    2015-08-01

    This study conducted 24- to 72-h multi-model ensemble forecasts to explore the tracks and intensities (central mean sea level pressure) of tropical cyclones (TCs). Forecast data for the northwestern Pacific basin in 2010 and 2011 were selected from the China Meteorological Administration, European Centre for Medium-Range Weather Forecasts (ECMWF), Japan Meteorological Agency, and National Centers for Environmental Prediction datasets of the Observing System Research and Predictability Experiment Interactive Grand Global Ensemble project. The Kalman Filter was employed to conduct the TC forecasts, along with the ensemble mean and super-ensemble for comparison. The following results were obtained: (1) The statistical-dynamic Kalman Filter, in which recent observations are given more importance and model weighting coefficients are adjusted over time, produced quite different results from that of the super-ensemble. (2) The Kalman Filter reduced the TC mean absolute track forecast error by approximately 50, 80 and 100 km in the 24-, 48- and 72-h forecasts, respectively, compared with the best individual model (ECMWF). Also, the intensity forecasts were improved by the Kalman Filter to some extent in terms of average intensity deviation (AID) and correlation coefficients with reanalysis intensity data. Overall, the Kalman Filter technique performed better compared to multi-models, the ensemble mean, and the super-ensemble in 3-day forecasts. The implication of this study is that this technique appears to be a very promising statistical-dynamic method for multi-model ensemble forecasts of TCs.

  4. Ensemble pharmacophore meets ensemble docking: a novel screening strategy for the identification of RIPK1 inhibitors

    NASA Astrophysics Data System (ADS)

    Fayaz, S. M.; Rajanikant, G. K.

    2014-07-01

    Programmed cell death has been a fascinating area of research since it throws new challenges and questions in spite of the tremendous ongoing research in this field. Recently, necroptosis, a programmed form of necrotic cell death, has been implicated in many diseases including neurological disorders. Receptor interacting serine/threonine protein kinase 1 (RIPK1) is an important regulatory protein involved in the necroptosis and inhibition of this protein is essential to stop necroptotic process and eventually cell death. Current structure-based virtual screening methods involve a wide range of strategies and recently, considering the multiple protein structures for pharmacophore extraction has been emphasized as a way to improve the outcome. However, using the pharmacophoric information completely during docking is very important. Further, in such methods, using the appropriate protein structures for docking is desirable. If not, potential compound hits, obtained through pharmacophore-based screening, may not have correct ranks and scores after docking. Therefore, a comprehensive integration of different ensemble methods is essential, which may provide better virtual screening results. In this study, dual ensemble screening, a novel computational strategy was used to identify diverse and potent inhibitors against RIPK1. All the pharmacophore features present in the binding site were captured using both the apo and holo protein structures and an ensemble pharmacophore was built by combining these features. This ensemble pharmacophore was employed in pharmacophore-based screening of ZINC database. The compound hits, thus obtained, were subjected to ensemble docking. The leads acquired through docking were further validated through feature evaluation and molecular dynamics simulation.

  5. Interference-based molecular transistors

    PubMed Central

    Li, Ying; Mol, Jan A.; Benjamin, Simon C.; Briggs, G. Andrew D.

    2016-01-01

    Molecular transistors have the potential for switching with lower gate voltages than conventional field-effect transistors. We have calculated the performance of a single-molecule device in which there is interference between electron transport through the highest occupied molecular orbital and the lowest unoccupied molecular orbital of a single molecule. Quantum interference results in a subthreshold slope that is independent of temperature. For realistic parameters the change in gate potential required for a change in source-drain current of two decades is 20 mV, which is a factor of six smaller than the theoretical limit for a metal-oxide-semiconductor field-effect transistor. PMID:27646692

  6. Large-Scale Hybrid Density Functional Theory Calculations in the Condensed-Phase: Ab Initio Molecular Dynamics in the Isobaric-Isothermal Ensemble

    NASA Astrophysics Data System (ADS)

    Ko, Hsin-Yu; Santra, Biswajit; Distasio, Robert A., Jr.; Wu, Xifan; Car, Roberto

    Hybrid functionals are known to alleviate the self-interaction error in density functional theory (DFT) and provide a more accurate description of the electronic structure of molecules and materials. However, hybrid DFT in the condensed-phase has a prohibitively high associated computational cost which limits their applicability to large systems of interest. In this work, we present a general-purpose order(N) implementation of hybrid DFT in the condensed-phase using Maximally localized Wannier function; this implementation is optimized for massively parallel computing architectures. This algorithm is used to perform large-scale ab initio molecular dynamics simulations of liquid water, ice, and aqueous ionic solutions. We have performed simulations in the isothermal-isobaric ensemble to quantify the effects of exact exchange on the equilibrium density properties of water at different thermodynamic conditions. We find that the anomalous density difference between ice I h and liquid water at ambient conditions as well as the enthalpy differences between ice I h, II, and III phases at the experimental triple point (238 K and 20 Kbar) are significantly improved using hybrid DFT over previous estimates using the lower rungs of DFT This work has been supported by the Department of Energy under Grants No. DE-FG02-05ER46201 and DE-SC0008626.

  7. Interplay of hole transfer and host-guest interaction in a molecular dyad and triad: ensemble and single-molecule spectroscopy and sensing applications.

    PubMed

    Wu, Xiangyang; Liu, Fang; Wells, Kym L; Tan, Serena L J; Webster, Richard D; Tan, Howe-Siang; Zhang, Dawei; Xing, Bengang; Yeow, Edwin K L

    2015-02-16

    A new molecular dyad consisting of a Cy5 chromophore and ferrocene (Fc) and a triad consisting of Cy5, Fc, and β-cyclodextrin (CD) are synthesized and their photophysical properties investigated at both the ensemble and single-molecule levels. Hole transfer efficiency from Cy5 to Fc in the dyad is reduced upon addition of CD. This is due to an increase in the Cy5-Fc separation (r) when the Fc is encapsulated in the macrocyclic host. On the other hand, the triad adopts either a Fc-CD inclusion complex conformation in which hole transfer quenching of the Cy5 by Fc is minimal or a quasi-static conformation with short r and rapid charge transfer. Single-molecule fluorescence measurements reveal that r is lengthened when the triad molecules are deposited on a glass substrate. By combining intramolecular charge transfer and competitive supramolecular interaction, the triad acts as an efficient chemical sensor to detect different bioactive analytes such as amantadine hydrochloride and sodium lithocholate in aqueous solution and synthetic urine.

  8. A mapping of an ensemble of mitochondrial sequences for various organisms into 3D space based on the word composition.

    PubMed

    Aita, Takuyo; Nishigaki, Koichi

    2012-11-01

    To visualize a bird's-eye view of an ensemble of mitochondrial genome sequences for various species, we recently developed a novel method of mapping a biological sequence ensemble into Three-Dimensional (3D) vector space. First, we represented a biological sequence of a species s by a word-composition vector x(s), where its length [absolute value]x(s)[absolute value] represents the sequence length, and its unit vector x(s)/[absolute value]x(s)[absolute value] represents the relative composition of the K-tuple words through the sequence and the size of the dimension, N=4(K), is the number of all possible words with the length of K. Second, we mapped the vector x(s) to the 3D position vector y(s), based on the two following simple principles: (1) [absolute value]y(s)[absolute value]=[absolute value]x(s)[absolute value] and (2) the angle between y(s) and y(t) maximally correlates with the angle between x(s) and x(t). The mitochondrial genome sequences for 311 species, including 177 Animalia, 85 Fungi and 49 Green plants, were mapped into 3D space by using K=7. The mapping was successful because the angles between vectors before and after the mapping highly correlated with each other (correlation coefficients were 0.92-0.97). Interestingly, the Animalia kingdom is distributed along a single arc belt (just like the Milky Way on a Celestial Globe), and the Fungi and Green plant kingdoms are distributed in a similar arc belt. These two arc belts intersect at their respective middle regions and form a cross structure just like a jet aircraft fuselage and its wings. This new mapping method will allow researchers to intuitively interpret the visual information presented in the maps in a highly effective manner.

  9. Molecular simulation of aqueous electrolyte solubility. 2. Osmotic ensemble Monte Carlo methodology for free energy and solubility calculations and application to NaCl.

    PubMed

    Moučka, Filip; Lísal, Martin; Škvor, Jiří; Jirsák, Jan; Nezbeda, Ivo; Smith, William R

    2011-06-23

    We present a new and computationally efficient methodology using osmotic ensemble Monte Carlo (OEMC) simulation to calculate chemical potential-concentration curves and the solubility of aqueous electrolytes. The method avoids calculations for the solid phase, incorporating readily available data from thermochemical tables that are based on well-defined reference states. It performs simulations of the aqueous solution at a fixed number of water molecules, pressure, temperature, and specified overall electrolyte chemical potential. Insertion/deletion of ions to/from the system is implemented using fractional ions, which are coupled to the system via a coupling parameter λ that varies between 0 (no interaction between the fractional ions and the other particles in the system) and 1 (full interaction between the fractional ions and the other particles of the system). Transitions between λ-states are accepted with a probability following from the osmotic ensemble partition function. Biasing weights associated with the λ-states are used in order to efficiently realize transitions between them; these are determined by means of the Wang-Landau method. We also propose a novel scaling procedure for λ, which can be used for both nonpolarizable and polarizable models of aqueous electrolyte systems. The approach is readily extended to involve other solvents, multiple electrolytes, and species complexation reactions. The method is illustrated for NaCl, using SPC/E water and several force field models for NaCl from the literature, and the results are compared with experiment at ambient conditions. Good agreement is obtained for the chemical potential-concentration curve and the solubility prediction is reasonable. Future improvements to the predictions will require improved force field models.

  10. Structural Ensembles of Membrane-bound α-Synuclein Reveal the Molecular Determinants of Synaptic Vesicle Affinity

    PubMed Central

    Fusco, Giuliana; De Simone, Alfonso; Arosio, Paolo; Vendruscolo, Michele; Veglia, Gianluigi; Dobson, Christopher M.

    2016-01-01

    A detailed characterisation of the molecular determinants of membrane binding by α-synuclein (αS), a 140-residue protein whose aggregation is associated with Parkinson’s disease, is of fundamental significance to clarify the manner in which the balance between functional and dysfunctional processes are regulated for this protein. Despite its biological relevance, the structural nature of the membrane-bound state αS remains elusive, in part because of the intrinsically dynamic nature of the protein and also because of the difficulties in studying this state in a physiologically relevant environment. In the present study we have used solid-state NMR and restrained MD simulations to refine structure and topology of the N-terminal region of αS bound to the surface of synaptic-like membranes. This region has fundamental importance in the binding mechanism of αS as it acts as to anchor the protein to lipid bilayers. The results enabled the identification of the key elements for the biological properties of αS in its membrane-bound state. PMID:27273030

  11. Evaluation of WRF-based convection-permitting multi-physics ensemble forecasts over China for an extreme rainfall event on 21 July 2012 in Beijing

    NASA Astrophysics Data System (ADS)

    Zhu, Kefeng; Xue, Ming

    2016-11-01

    On 21 July 2012, an extreme rainfall event that recorded a maximum rainfall amount over 24 hours of 460 mm, occurred in Beijing, China. Most operational models failed to predict such an extreme amount. In this study, a convective-permitting ensemble forecast system (CEFS), at 4-km grid spacing, covering the entire mainland of China, is applied to this extreme rainfall case. CEFS consists of 22 members and uses multiple physics parameterizations. For the event, the predicted maximum is 415 mm d-1 in the probability-matched ensemble mean. The predicted high-probability heavy rain region is located in southwest Beijing, as was observed. Ensemble-based verification scores are then investigated. For a small verification domain covering Beijing and its surrounding areas, the precipitation rank histogram of CEFS is much flatter than that of a reference global ensemble. CEFS has a lower (higher) Brier score and a higher resolution than the global ensemble for precipitation, indicating more reliable probabilistic forecasting by CEFS. Additionally, forecasts of different ensemble members are compared and discussed. Most of the extreme rainfall comes from convection in the warm sector east of an approaching cold front. A few members of CEFS successfully reproduce such precipitation, and orographic lift of highly moist low-level flows with a significantly southeasterly component is suggested to have played important roles in producing the initial convection. Comparisons between good and bad forecast members indicate a strong sensitivity of the extreme rainfall to the mesoscale environmental conditions, and, to less of an extent, the model physics.

  12. One-day-ahead streamflow forecasting via super-ensembles of several neural network architectures based on the Multi-Level Diversity Model

    NASA Astrophysics Data System (ADS)

    Brochero, Darwin; Hajji, Islem; Pina, Jasson; Plana, Queralt; Sylvain, Jean-Daniel; Vergeynst, Jenna; Anctil, Francois

    2015-04-01

    Theories about generalization error with ensembles are mainly based on the diversity concept, which promotes resorting to many members of different properties to support mutually agreeable decisions. Kuncheva (2004) proposed the Multi Level Diversity Model (MLDM) to promote diversity in model ensembles, combining different data subsets, input subsets, models, parameters, and including a combiner level in order to optimize the final ensemble. This work tests the hypothesis about the minimisation of the generalization error with ensembles of Neural Network (NN) structures. We used the MLDM to evaluate two different scenarios: (i) ensembles from a same NN architecture, and (ii) a super-ensemble built by a combination of sub-ensembles of many NN architectures. The time series used correspond to the 12 basins of the MOdel Parameter Estimation eXperiment (MOPEX) project that were used by Duan et al. (2006) and Vos (2013) as benchmark. Six architectures are evaluated: FeedForward NN (FFNN) trained with the Levenberg Marquardt algorithm (Hagan et al., 1996), FFNN trained with SCE (Duan et al., 1993), Recurrent NN trained with a complex method (Weins et al., 2008), Dynamic NARX NN (Leontaritis and Billings, 1985), Echo State Network (ESN), and leak integrator neuron (L-ESN) (Lukosevicius and Jaeger, 2009). Each architecture performs separately an Input Variable Selection (IVS) according to a forward stepwise selection (Anctil et al., 2009) using mean square error as objective function. Post-processing by Predictor Stepwise Selection (PSS) of the super-ensemble has been done following the method proposed by Brochero et al. (2011). IVS results showed that the lagged stream flow, lagged precipitation, and Standardized Precipitation Index (SPI) (McKee et al., 1993) were the most relevant variables. They were respectively selected as one of the firsts three selected variables in 66, 45, and 28 of the 72 scenarios. A relationship between aridity index (Arora, 2002) and NN

  13. Emotion Recognition of Weblog Sentences Based on an Ensemble Algorithm of Multi-label Classification and Word Emotions

    NASA Astrophysics Data System (ADS)

    Li, Ji; Ren, Fuji

    Weblogs have greatly changed the communication ways of mankind. Affective analysis of blog posts is found valuable for many applications such as text-to-speech synthesis or computer-assisted recommendation. Traditional emotion recognition in text based on single-label classification can not satisfy higher requirements of affective computing. In this paper, the automatic identification of sentence emotion in weblogs is modeled as a multi-label text categorization task. Experiments are carried out on 12273 blog sentences from the Chinese emotion corpus Ren_CECps with 8-dimension emotion annotation. An ensemble algorithm RAKEL is used to recognize dominant emotions from the writer's perspective. Our emotion feature using detailed intensity representation for word emotions outperforms the other main features such as the word frequency feature and the traditional lexicon-based feature. In order to deal with relatively complex sentences, we integrate grammatical characteristics of punctuations, disjunctive connectives, modification relations and negation into features. It achieves 13.51% and 12.49% increases for Micro-averaged F1 and Macro-averaged F1 respectively compared to the traditional lexicon-based feature. Result shows that multiple-dimension emotion representation with grammatical features can efficiently classify sentence emotion in a multi-label problem.

  14. An Ensemble System Based on Hybrid EGARCH-ANN with Different Distributional Assumptions to Predict S&P 500 Intraday Volatility

    NASA Astrophysics Data System (ADS)

    Lahmiri, S.; Boukadoum, M.

    2015-10-01

    Accurate forecasting of stock market volatility is an important issue in portfolio risk management. In this paper, an ensemble system for stock market volatility is presented. It is composed of three different models that hybridize the exponential generalized autoregressive conditional heteroscedasticity (GARCH) process and the artificial neural network trained with the backpropagation algorithm (BPNN) to forecast stock market volatility under normal, t-Student, and generalized error distribution (GED) assumption separately. The goal is to design an ensemble system where each single hybrid model is capable to capture normality, excess skewness, or excess kurtosis in the data to achieve complementarity. The performance of each EGARCH-BPNN and the ensemble system is evaluated by the closeness of the volatility forecasts to realized volatility. Based on mean absolute error and mean of squared errors, the experimental results show that proposed ensemble model used to capture normality, skewness, and kurtosis in data is more accurate than the individual EGARCH-BPNN models in forecasting the S&P 500 intra-day volatility based on one and five-minute time horizons data.

  15. Niobate-based octahedral molecular sieves

    DOEpatents

    Nenoff, Tina M.; Nyman, May D.

    2006-10-17

    Niobate-based octahedral molecular sieves having significant activity for multivalent cations and a method for synthesizing such sieves are disclosed. The sieves have a net negatively charged octahedral framework, comprising niobium, oxygen, and octahedrally coordinated lower valence transition metals. The framework can be charge balanced by the occluded alkali cation from the synthesis method. The alkali cation can be exchanged for other contaminant metal ions. The ion-exchanged niobate-based octahedral molecular sieve can be backexchanged in acidic solutions to yield a solution concentrated in the contaminant metal. Alternatively, the ion-exchanged niobate-based octahedral molecular sieve can be thermally converted to a durable perovskite phase waste form.

  16. Niobate-based octahedral molecular sieves

    DOEpatents

    Nenoff, Tina M.; Nyman, May D.

    2003-07-22

    Niobate-based octahedral molecular sieves having significant activity for multivalent cations and a method for synthesizing such sieves are disclosed. The sieves have a net negatively charged octahedral framework, comprising niobium, oxygen, and octahedrally coordinated lower valence transition metals. The framework can be charge balanced by the occluded alkali cation from the synthesis method. The alkali cation can be exchanged for other contaminant metal ions. The ion-exchanged niobate-based octahedral molecular sieve can be backexchanged in acidic solutions to yield a solution concentrated in the contaminant metal. Alternatively, the ion-exchanged niobate-based octahedral molecular sieve can be thermally converted to a durable perovskite phase waste form.

  17. A Compound fault diagnosis for rolling bearings method based on blind source separation and ensemble empirical mode decomposition.

    PubMed

    Wang, Huaqing; Li, Ruitong; Tang, Gang; Yuan, Hongfang; Zhao, Qingliang; Cao, Xi

    2014-01-01

    A Compound fault signal usually contains multiple characteristic signals and strong confusion noise, which makes it difficult to separate week fault signals from them through conventional ways, such as FFT-based envelope detection, wavelet transform or empirical mode decomposition individually. In order to improve the compound faults diagnose of rolling bearings via signals' separation, the present paper proposes a new method to identify compound faults from measured mixed-signals, which is based on ensemble empirical mode decomposition (EEMD) method and independent component analysis (ICA) technique. With the approach, a vibration signal is firstly decomposed into intrinsic mode functions (IMF) by EEMD method to obtain multichannel signals. Then, according to a cross correlation criterion, the corresponding IMF is selected as the input matrix of ICA. Finally, the compound faults can be separated effectively by executing ICA method, which makes the fault features more easily extracted and more clearly identified. Experimental results validate the effectiveness of the proposed method in compound fault separating, which works not only for the outer race defect, but also for the rollers defect and the unbalance fault of the experimental system.

  18. A Cutting Pattern Recognition Method for Shearers Based on Improved Ensemble Empirical Mode Decomposition and a Probabilistic Neural Network.

    PubMed

    Xu, Jing; Wang, Zhongbin; Tan, Chao; Si, Lei; Liu, Xinhua

    2015-10-30

    In order to guarantee the stable operation of shearers and promote construction of an automatic coal mining working face, an online cutting pattern recognition method with high accuracy and speed based on Improved Ensemble Empirical Mode Decomposition (IEEMD) and Probabilistic Neural Network (PNN) is proposed. An industrial microphone is installed on the shearer and the cutting sound is collected as the recognition criterion to overcome the disadvantages of giant size, contact measurement and low identification rate of traditional detectors. To avoid end-point effects and get rid of undesirable intrinsic mode function (IMF) components in the initial signal, IEEMD is conducted on the sound. The end-point continuation based on the practical storage data is performed first to overcome the end-point effect. Next the average correlation coefficient, which is calculated by the correlation of the first IMF with others, is introduced to select essential IMFs. Then the energy and standard deviation of the reminder IMFs are extracted as features and PNN is applied to classify the cutting patterns. Finally, a simulation example, with an accuracy of 92.67%, and an industrial application prove the efficiency and correctness of the proposed method.

  19. A Cutting Pattern Recognition Method for Shearers Based on Improved Ensemble Empirical Mode Decomposition and a Probabilistic Neural Network

    PubMed Central

    Xu, Jing; Wang, Zhongbin; Tan, Chao; Si, Lei; Liu, Xinhua

    2015-01-01

    In order to guarantee the stable operation of shearers and promote construction of an automatic coal mining working face, an online cutting pattern recognition method with high accuracy and speed based on Improved Ensemble Empirical Mode Decomposition (IEEMD) and Probabilistic Neural Network (PNN) is proposed. An industrial microphone is installed on the shearer and the cutting sound is collected as the recognition criterion to overcome the disadvantages of giant size, contact measurement and low identification rate of traditional detectors. To avoid end-point effects and get rid of undesirable intrinsic mode function (IMF) components in the initial signal, IEEMD is conducted on the sound. The end-point continuation based on the practical storage data is performed first to overcome the end-point effect. Next the average correlation coefficient, which is calculated by the correlation of the first IMF with others, is introduced to select essential IMFs. Then the energy and standard deviation of the reminder IMFs are extracted as features and PNN is applied to classify the cutting patterns. Finally, a simulation example, with an accuracy of 92.67%, and an industrial application prove the efficiency and correctness of the proposed method. PMID:26528985

  20. [MicroRNA Target Prediction Based on Support Vector Machine Ensemble Classification Algorithm of Under-sampling Technique].

    PubMed

    Chen, Zhiru; Hong, Wenxue

    2016-02-01

    Considering the low accuracy of prediction in the positive samples and poor overall classification effects caused by unbalanced sample data of MicroRNA (miRNA) target, we proposes a support vector machine (SVM)-integration of under-sampling and weight (IUSM) algorithm in this paper, an under-sampling based on the ensemble learning algorithm. The algorithm adopts SVM as learning algorithm and AdaBoost as integration framework, and embeds clustering-based under-sampling into the iterative process, aiming at reducing the degree of unbalanced distribution of positive and negative samples. Meanwhile, in the process of adaptive weight adjustment of the samples, the SVM-IUSM algorithm eliminates the abnormal ones in negative samples with robust sample weights smoothing mechanism so as to avoid over-learning. Finally, the prediction of miRNA target integrated classifier is achieved with the combination of multiple weak classifiers through the voting mechanism. The experiment revealed that the SVM-IUSW, compared with other algorithms on unbalanced dataset collection, could not only improve the accuracy of positive targets and the overall effect of classification, but also enhance the generalization ability of miRNA target classifier.

  1. Evaluating Model Performance of an Ensemble-based Chemical Data Assimilation System During INTEX-B Field Mission

    NASA Technical Reports Server (NTRS)

    Arellano, A. F., Jr.; Raeder, K.; Anderson, J. L.; Hess, P. G.; Emmons, L. K.; Edwards, D. P.; Pfister, G. G.; Campos, T. L.; Sachse, G. W.

    2007-01-01

    We present a global chemical data assimilation system using a global atmosphere model, the Community Atmosphere Model (CAM3) with simplified chemistry and the Data Assimilation Research Testbed (DART) assimilation package. DART is a community software facility for assimilation studies using the ensemble Kalman filter approach. Here, we apply the assimilation system to constrain global tropospheric carbon monoxide (CO) by assimilating meteorological observations of temperature and horizontal wind velocity and satellite CO retrievals from the Measurement of Pollution in the Troposphere (MOPITT) satellite instrument. We verify the system performance using independent CO observations taken on board the NSFINCAR C-130 and NASA DC-8 aircrafts during the April 2006 part of the Intercontinental Chemical Transport Experiment (INTEX-B). Our evaluations show that MOPITT data assimilation provides significant improvements in terms of capturing the observed CO variability relative to no MOPITT assimilation (i.e. the correlation improves from 0.62 to 0.71, significant at 99% confidence). The assimilation provides evidence of median CO loading of about 150 ppbv at 700 hPa over the NE Pacific during April 2006. This is marginally higher than the modeled CO with no MOPITT assimilation (-140 ppbv). Our ensemble-based estimates of model uncertainty also show model overprediction over the source region (i.e. China) and underprediction over the NE Pacific, suggesting model errors that cannot be readily explained by emissions alone. These results have important implications for improving regional chemical forecasts and for inverse modeling of CO sources and further demonstrate the utility of the assimilation system in comparing non-coincident measurements, e.g. comparing satellite retrievals of CO with in-situ aircraft measurements. The work described above also brought to light several short-comings of the data assimilation approach for CO profiles. Because of the limited vertical

  2. Exploring ensemble visualization

    NASA Astrophysics Data System (ADS)

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

    2012-01-01

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

  3. Exploring Ensemble Visualization

    PubMed Central

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

    2012-01-01

    An ensemble is a collection of related datasets. Each dataset, or member, of an ensemble is normally large, multidimensional, and spatio-temporal. Ensembles are used extensively by scientists and mathematicians, for example, by executing a simulation repeatedly with slightly different input parameters and saving the results in an ensemble to see how parameter choices affect the simulation. To draw inferences from an ensemble, scientists need to compare data both within and between ensemble members. We propose two techniques to support ensemble exploration and comparison: a pairwise sequential animation method that visualizes locally neighboring members simultaneously, and a screen door tinting method that visualizes subsets of members using screen space subdivision. We demonstrate the capabilities of both techniques, first using synthetic data, then with simulation data of heavy ion collisions in high-energy physics. Results show that both techniques are capable of supporting meaningful comparisons of ensemble data. PMID:22347540

  4. GA(M)E-QSAR: a novel, fully automatic genetic-algorithm-(meta)-ensembles approach for binary classification in ligand-based drug design.

    PubMed

    Pérez-Castillo, Yunierkis; Lazar, Cosmin; Taminau, Jonatan; Froeyen, Mathy; Cabrera-Pérez, Miguel Ángel; Nowé, Ann

    2012-09-24

    Computer-aided drug design has become an important component of the drug discovery process. Despite the advances in this field, there is not a unique modeling approach that can be successfully applied to solve the whole range of problems faced during QSAR modeling. Feature selection and ensemble modeling are active areas of research in ligand-based drug design. Here we introduce the GA(M)E-QSAR algorithm that combines the search and optimization capabilities of Genetic Algorithms with the simplicity of the Adaboost ensemble-based classification algorithm to solve binary classification problems. We also explore the usefulness of Meta-Ensembles trained with Adaboost and Voting schemes to further improve the accuracy, generalization, and robustness of the optimal Adaboost Single Ensemble derived from the Genetic Algorithm optimization. We evaluated the performance of our algorithm using five data sets from the literature and found that it is capable of yielding similar or better classification results to what has been reported for these data sets with a higher enrichment of active compounds relative to the whole actives subset when only the most active chemicals are considered. More important, we compared our methodology with state of the art feature selection and classification approaches and found that it can provide highly accurate, robust, and generalizable models. In the case of the Adaboost Ensembles derived from the Genetic Algorithm search, the final models are quite simple since they consist of a weighted sum of the output of single feature classifiers. Furthermore, the Adaboost scores can be used as ranking criterion to prioritize chemicals for synthesis and biological evaluation after virtual screening experiments.

  5. [Molecular bases of cancer immunology].

    PubMed

    Barrera-Rodríguez, R; Peralta-Zaragoza, O; Madrid-Marina, V

    1995-01-01

    The immune system is a tight network of different types of cells and molecules. The coordinated action of these elements mounts a precise immune response against tumor cells. However, these cells present several escape mechanisms, leading to tumor progression. This paper shows several cellular and molecular events involved in the regulation of the immune response against tumor cells. The interaction of several molecules such as MHC, TcR, adhesins, tumor antigens and cytokines are discussed, as well as the most recent knowledge about escape mechanisms and immunotherapy.

  6. Risk assessment of agricultural water requirement based on a multi-model ensemble framework, southwest of Iran

    NASA Astrophysics Data System (ADS)

    Zamani, Reza; Akhond-Ali, Ali-Mohammad; Roozbahani, Abbas; Fattahi, Rouhollah

    2016-06-01

    Water shortage and climate change are the most important issues of sustainable agricultural and water resources development. Given the importance of water availability in crop production, the present study focused on risk assessment of climate change impact on agricultural water requirement in southwest of Iran, under two emission scenarios (A2 and B1) for the future period (2025-2054). A multi-model ensemble framework based on mean observed temperature-precipitation (MOTP) method and a combined probabilistic approach Long Ashton Research Station-Weather Generator (LARS-WG) and change factor (CF) have been used for downscaling to manage the uncertainty of outputs of 14 general circulation models (GCMs). The results showed an increasing temperature in all months and irregular changes of precipitation (either increasing or decreasing) in the future period. In addition, the results of the calculated annual net water requirement for all crops affected by climate change indicated an increase between 4 and 10 %. Furthermore, an increasing process is also expected regarding to the required water demand volume. The most and the least expected increase in the water demand volume is about 13 and 5 % for A2 and B1 scenarios, respectively. Considering the results and the limited water resources in the study area, it is crucial to provide water resources planning in order to reduce the negative effects of climate change. Therefore, the adaptation scenarios with the climate change related to crop pattern and water consumption should be taken into account.

  7. Modification of input datasets for the Ensemble Streamflow Prediction based on large-scale climatic indices and weather generator

    NASA Astrophysics Data System (ADS)

    Šípek, Václav; Daňhelka, Jan

    2015-09-01

    Ensemble Streamflow Prediction (ESP) provides an efficient tool for seasonal hydrological forecasts. In this study, we propose a new modification of input data series for the ESP system used for the runoff volume prediction with a lead of one month. These series are not represented by short historical weather datasets but by longer generated synthetic weather data series. Before their submission to the hydrological model, their number is restricted by relations among observed meteorological variables (average monthly precipitation and temperature) and large-scale climatic patterns and indices (e.g. North Atlantic Oscillation, sea level pressure values and two geopotential heights). This modification was tested over a four-year testing period using the river basin in central Europe. The LARS-WG weather generator proved to be a suitable tool for the extension of the historical weather records. The modified ESP approach proved to be more efficient in the majority of months compared both to the original ESP method and reference forecast (based on probability distribution of historical discharges). The improvement over traditional ESP was most obvious in the narrower forecast interval of the expected runoff volume. The inefficient forecasts of the modified ESP scheme (compared to traditional ESP) were conditioned by an insufficient restriction of input synthetic weather datasets by the climate forecast.

  8. Faults Diagnostics of Railway Axle Bearings Based on IMF’s Confidence Index Algorithm for Ensemble EMD

    PubMed Central

    Yi, Cai; Lin, Jianhui; Zhang, Weihua; Ding, Jianming

    2015-01-01

    As train loads and travel speeds have increased over time, railway axle bearings have become critical elements which require more efficient non-destructive inspection and fault diagnostics methods. This paper presents a novel and adaptive procedure based on ensemble empirical mode decomposition (EEMD) and Hilbert marginal spectrum for multi-fault diagnostics of axle bearings. EEMD overcomes the limitations that often hypothesize about data and computational efforts that restrict the application of signal processing techniques. The outputs of this adaptive approach are the intrinsic mode functions that are treated with the Hilbert transform in order to obtain the Hilbert instantaneous frequency spectrum and marginal spectrum. Anyhow, not all the IMFs obtained by the decomposition should be considered into Hilbert marginal spectrum. The IMFs’ confidence index arithmetic proposed in this paper is fully autonomous, overcoming the major limit of selection by user with experience, and allows the development of on-line tools. The effectiveness of the improvement is proven by the successful diagnosis of an axle bearing with a single fault or multiple composite faults, e.g., outer ring fault, cage fault and pin roller fault. PMID:25970256

  9. World Music Ensemble: Kulintang

    ERIC Educational Resources Information Center

    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…

  10. Definition of Ensemble Error Statistics for Optimal Ensemble Data Assimilation

    NASA Astrophysics Data System (ADS)

    Frehlich, R.

    2009-09-01

    Next generation data assimilation methods must include the state dependent observation errors, i.e., the spatial and temporal variations produced by the atmospheric turbulent field. A rigorous analysis of optimal data assimilation algorithms and ensemble forecast systems requires a definition of model "truth" or perfect measurement which then defines the total observation error and forecast error. Truth is defined as the spatial average of the continuous atmospheric state variables centered on the model grid locations. To be consistent with the climatology of turbulence, the spatial average is chosen as the effective spatial filter of the numerical model. The observation errors then consist of two independent components: an instrument error and an observation sampling error which describes the mismatch of the spatial average of the observation and the spatial average of the perfect measurement or "truth". The observation sampling error is related to the "error of representativeness" but is defined only in terms of the local statistics of the atmosphere and the sampling pattern of the observation. Optimal data assimilation requires an estimate of the local background error correlation as well as the local observation error correlation. Both of these local correlations can be estimated from ensemble assimilation techniques where each member of the ensemble are produced by generating and assimilating random observations consistent with the estimates of the local sampling errors based on estimates of the local turbulent statistics. A rigorous evaluation of these optimal ensemble data assimilation techniques requires a definition of the ensemble members and the ensemble average that describes the error correlations. A new formulation is presented that is consistent with the climatology of atmospheric turbulence and the implications of this formulation for ensemble forecast systems is discussed.

  11. Projected changes to winter temperature characteristics over Canada based on an RCM ensemble

    NASA Astrophysics Data System (ADS)

    Jeong, Dae Il; Sushama, Laxmi; Diro, Gulilat Tefera; Khaliq, M. Naveed

    2016-09-01

    Cold temperature and associated extremes often impact adversely human health and environment and bring disruptions in economic activities during winter over Canada. This study investigates projected changes in winter (December to March) period cold extreme days (i.e., cold nights, cold days, frost days, and ice days) and cold spells over Canada based on 11 regional climate model (RCM) simulations for the future 2040-2069 period with respect to the current 1970-1999 period. These simulations, available from the North American Regional Climate Change Assessment Program, were obtained with six different RCMs, when driven by four different Atmosphere-Ocean General Circulation Models, under the Special Report on Emissions Scenarios A2 scenario. Based on the reanalysis boundary conditions, the RCM simulations reproduce spatial patterns of observed mean values of the daily minimum and maximum temperatures and inter-annual variability of the number of cold nights over different Canadian climatic regions considered in the study. A comparison of current and future period simulations suggests decreases in the frequency of cold extreme events (i.e., cold nights, cold days and cold spells) and in selected return levels of maximum duration of cold spells over the entire study domain. Important regional differences are noticed as the simulations generally indicate smaller decreases in the characteristics of extreme cold events over western Canada compared to the other regions. The analysis also suggests an increase in the frequency of midwinter freeze-thaw events, due mainly to a decrease in the number of frost days and ice days for all Canadian regions. Especially, densely populated southern and coastal Canadian regions will require in depth studies to facilitate appropriate adaptation strategies as these regions are clearly expected to experience large increases in the frequency of freeze-thaw events.

  12. A general framework for multivariate multi-index drought prediction based on Multivariate Ensemble Streamflow Prediction (MESP)

    NASA Astrophysics Data System (ADS)

    Hao, Zengchao; Hao, Fanghua; Singh, Vijay P.

    2016-08-01

    Drought is among the costliest natural hazards worldwide and extreme drought events in recent years have caused huge losses to various sectors. Drought prediction is therefore critically important for providing early warning information to aid decision making to cope with drought. Due to the complicated nature of drought, it has been recognized that the univariate drought indicator may not be sufficient for drought characterization and hence multivariate drought indices have been developed for drought monitoring. Alongside the substantial effort in drought monitoring with multivariate drought indices, it is of equal importance to develop a drought prediction method with multivariate drought indices to integrate drought information from various sources. This study proposes a general framework for multivariate multi-index drought prediction that is capable of integrating complementary prediction skills from multiple drought indices. The Multivariate Ensemble Streamflow Prediction (MESP) is employed to sample from historical records for obtaining statistical prediction of multiple variables, which is then used as inputs to achieve multivariate prediction. The framework is illustrated with a linearly combined drought index (LDI), which is a commonly used multivariate drought index, based on climate division data in California and New York in the United States with different seasonality of precipitation. The predictive skill of LDI (represented with persistence) is assessed by comparison with the univariate drought index and results show that the LDI prediction skill is less affected by seasonality than the meteorological drought prediction based on SPI. Prediction results from the case study show that the proposed multivariate drought prediction outperforms the persistence prediction, implying a satisfactory performance of multivariate drought prediction. The proposed method would be useful for drought prediction to integrate drought information from various sources

  13. Ultrathin inorganic molecular nanowire based on polyoxometalates

    PubMed Central

    Zhang, Zhenxin; Murayama, Toru; Sadakane, Masahiro; Ariga, Hiroko; Yasuda, Nobuhiro; Sakaguchi, Norihito; Asakura, Kiyotaka; Ueda, Wataru

    2015-01-01

    The development of metal oxide-based molecular wires is important for fundamental research and potential practical applications. However, examples of these materials are rare. Here we report an all-inorganic transition metal oxide molecular wire prepared by disassembly of larger crystals. The wires are comprised of molybdenum(VI) with either tellurium(IV) or selenium(IV): {(NH4)2[XMo6O21]}n (X=tellurium(IV) or selenium(IV)). The ultrathin molecular nanowires with widths of 1.2 nm grow to micrometre-scale crystals and are characterized by single-crystal X-ray analysis, Rietveld analysis, scanning electron microscopy, X-ray photoelectron spectroscopy, ultraviolet–visible spectroscopy, thermal analysis and elemental analysis. The crystals can be disassembled into individual molecular wires through cation exchange and subsequent ultrasound treatment, as visualized by atomic force microscopy and transmission electron microscopy. The ultrathin molecular wire-based material exhibits high activity as an acid catalyst, and the band gap of the molecular wire-based crystal is tunable by heat treatment. PMID:26139011

  14. Algorithms on ensemble quantum computers.

    PubMed

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

    2010-06-01

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

  15. A hybrid model for PM₂.₅ forecasting based on ensemble empirical mode decomposition and a general regression neural network.

    PubMed

    Zhou, Qingping; Jiang, Haiyan; Wang, Jianzhou; Zhou, Jianling

    2014-10-15

    Exposure to high concentrations of fine particulate matter (PM₂.₅) can cause serious health problems because PM₂.₅ contains microscopic solid or liquid droplets that are sufficiently small to be ingested deep into human lungs. Thus, daily prediction of PM₂.₅ levels is notably important for regulatory plans that inform the public and restrict social activities in advance when harmful episodes are foreseen. A hybrid EEMD-GRNN (ensemble empirical mode decomposition-general regression neural network) model based on data preprocessing and analysis is firstly proposed in this paper for one-day-ahead prediction of PM₂.₅ concentrations. The EEMD part is utilized to decompose original PM₂.₅ data into several intrinsic mode functions (IMFs), while the GRNN part is used for the prediction of each IMF. The hybrid EEMD-GRNN model is trained using input variables obtained from principal component regression (PCR) model to remove redundancy. These input variables accurately and succinctly reflect the relationships between PM₂.₅ and both air quality and meteorological data. The model is trained with data from January 1 to November 1, 2013 and is validated with data from November 2 to November 21, 2013 in Xi'an Province, China. The experimental results show that the developed hybrid EEMD-GRNN model outperforms a single GRNN model without EEMD, a multiple linear regression (MLR) model, a PCR model, and a traditional autoregressive integrated moving average (ARIMA) model. The hybrid model with fast and accurate results can be used to develop rapid air quality warning systems.

  16. An assessment of a North American Multi-Model Ensemble (NMME) based global drought early warning forecast system

    NASA Astrophysics Data System (ADS)

    Wood, E. F.; Yuan, X.; Sheffield, J.; Pan, M.; Roundy, J.

    2013-12-01

    One of the key recommendations of the WCRP Global Drought Information System (GDIS) workshop is to develop an experimental real-time global monitoring and prediction system. While great advances has been made in global drought monitoring based on satellite observations and model reanalysis data, global drought forecasting has been stranded in part due to the limited skill both in climate forecast models and global hydrologic predictions. Having been working on drought monitoring and forecasting over USA for more than a decade, the Princeton land surface hydrology group is now developing an experimental global drought early warning system that is based on multiple climate forecast models and a calibrated global hydrologic model. In this presentation, we will test its capability in seasonal forecasting of meteorological, agricultural and hydrologic droughts over global major river basins, using precipitation, soil moisture and streamflow forecasts respectively. Based on the joint probability distribution between observations using Princeton's global drought monitoring system and model hindcasts and real-time forecasts from North American Multi-Model Ensemble (NMME) project, we (i) bias correct the monthly precipitation and temperature forecasts from multiple climate forecast models, (ii) downscale them to a daily time scale, and (iii) use them to drive the calibrated VIC model to produce global drought forecasts at a 1-degree resolution. A parallel run using the ESP forecast method, which is based on resampling historical forcings, is also carried out for comparison. Analysis is being conducted over global major river basins, with multiple drought indices that have different time scales and characteristics. The meteorological drought forecast does not have uncertainty from hydrologic models and can be validated directly against observations - making the validation an 'apples-to-apples' comparison. Preliminary results for the evaluation of meteorological drought onset

  17. Bioassays Based on Molecular Nanomechanics

    DOE PAGES

    Majumdar, Arun

    2002-01-01

    Recent experiments have shown that when specific biomolecular interactions are confined to one surface of a microcantilever beam, changes in intermolecular nanomechanical forces provide sufficient differential torque to bend the cantilever beam. This has been used to detect single base pair mismatches during DNA hybridization, as well as prostate specific antigen (PSA) at concentrations and conditions that are clinically relevant for prostate cancer diagnosis. Since cantilever motion originates from free energy change induced by specific biomolecular binding, this technique is now offering a common platform for label-free quantitative analysis of protein-protein binding, DNA hybridization DNA-protein interactions, and in general receptor-ligandmore » interactions. Current work is focused on developing “universal microarrays” of microcantilever beams for high-throughput multiplexed bioassays.« less

  18. A stochastic ensemble-based model to predict crop water requirements from numerical weather forecasts and VIS-NIR high resolution satellite images in Southern Italy

    NASA Astrophysics Data System (ADS)

    Pelosi, Anna; Falanga Bolognesi, Salvatore; De Michele, Carlo; Medina Gonzalez, Hanoi; Villani, Paolo; D'Urso, Guido; Battista Chirico, Giovanni

    2015-04-01

    Irrigation agriculture is one the biggest consumer of water in Europe, especially in southern regions, where it accounts for up to 70% of the total water consumption. The EU Common Agricultural Policy, combined with the Water Framework Directive, imposes to farmers and irrigation managers a substantial increase of the efficiency in the use of water in agriculture for the next decade. Ensemble numerical weather predictions can be valuable data for developing operational advisory irrigation services. We propose a stochastic ensemble-based model providing spatial and temporal estimates of crop water requirements, implemented within an advisory service offering detailed maps of irrigation water requirements and crop water consumption estimates, to be used by water irrigation managers and farmers. The stochastic model combines estimates of crop potential evapotranspiration retrieved from ensemble numerical weather forecasts (COSMO-LEPS, 16 members, 7 km resolution) and canopy parameters (LAI, albedo, fractional vegetation cover) derived from high resolution satellite images in the visible and near infrared wavelengths. The service provides users with daily estimates of crop water requirements for lead times up to five days. The temporal evolution of the crop potential evapotranspiration is simulated with autoregressive models. An ensemble Kalman filter is employed for updating model states by assimilating both ground based meteorological variables (where available) and numerical weather forecasts. The model has been applied in Campania region (Southern Italy), where a satellite assisted irrigation advisory service has been operating since 2006. This work presents the results of the system performance for one year of experimental service. The results suggest that the proposed model can be an effective support for a sustainable use and management of irrigation water, under conditions of water scarcity and drought. Since the evapotranspiration term represents a staple

  19. A probabilistic approach of the Flash Flood Early Warning System (FF-EWS) in Catalonia based on radar ensemble generation

    NASA Astrophysics Data System (ADS)

    Velasco, David; Sempere-Torres, Daniel; Corral, Carles; Llort, Xavier; Velasco, Enrique

    2010-05-01

    probabilistic component to the FF-EWS. As a first step, we have incorporated the uncertainty in rainfall estimates and forecasts based on an ensemble of equiprobable rainfall scenarios. The presented study has focused on a number of rainfall events and the performance of the FF-EWS evaluated in terms of its ability to produce probabilistic hazard warnings for decision-making support.

  20. A simulation study of the ensemble-based data assimilation of satellite-borne lidar aerosol observations

    NASA Astrophysics Data System (ADS)

    Sekiyama, T. T.; Tanaka, T. Y.; Miyoshi, T.

    2012-07-01

    A four-dimensional ensemble-based data assimilation system was assessed by observing system simulation experiments (OSSEs), in which the CALIPSO satellite was emulated via simulated satellite-borne lidar aerosol observations. Its performance over athree-month period was validated according to the Method for Object-based Diagnostic Evaluation (MODE), using aerosol optical thickness (AOT) distributions in East Asia as the objects of analysis. Consequently, this data assimilation system demonstrated the ability to produce better analyses of sulfate and dust aerosols in comparison to a free-running simulation model. For example, the mean centroid distance (from the truth) over a three-month collection period of aerosol plumes was improved from 2.15 grids (≈ 600 km) to 1.45 grids (≈ 400 km) for sulfate aerosols and from 2.59 grids (≈ 750 km) to 1.14 grids (≈ 330 km) for dust aerosols; the mean area ratio (to the truth) over a three-month collection period of aerosol plumes was improved from 0.49 to 0.76 for sulfate aerosols and from 0.51 to 0.72 for dust aerosols. The satellite-borne lidar data assimilation successfully improved the aerosol plume analysis and the dust emission estimation in the OSSEs. These results present great possibilities for the beneficial use of lidar data, whose distribution is vertically/temporally dense but horizontally sparse, when coupled with a four-dimensional data assimilation system. In addition, sensitivity tests were conducted, and their results indicated that the degree of freedom to control the aerosol variables was probably limited in the data assimilation because the meteorological field in the system was constrained to weather reanalysis using Newtonian relaxation. Further improvements to the aerosol analysis can be performed through the simultaneous assimilation of aerosol observations with meteorological observations. The OSSE results strongly suggest that the use of real CALIPSO data will have a beneficial effect on

  1. A fuzzy integral method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification across multiple subjects.

    PubMed

    Cacha, L A; Parida, S; Dehuri, S; Cho, S-B; Poznanski, R R

    2016-12-01

    The huge number of voxels in fMRI over time poses a major challenge to for effective analysis. Fast, accurate, and reliable classifiers are required for estimating the decoding accuracy of brain activities. Although machine-learning classifiers seem promising, individual classifiers have their own limitations. To address this limitation, the present paper proposes a method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification for application across multiple subjects. Similarly, the fuzzy integral (FI) approach has been employed as an efficient tool for combining different classifiers. The FI approach led to the development of a classifiers ensemble technique that performs better than any of the single classifier by reducing the misclassification, the bias, and the variance. The proposed method successfully classified the different cognitive states for multiple subjects with high accuracy of classification. Comparison of the performance improvement, while applying ensemble neural networks method, vs. that of the individual neural network strongly points toward the usefulness of the proposed method.

  2. Graphene-based nanoprobes for molecular diagnostics.

    PubMed

    Chen, Shixing; Li, Fuwu; Fan, Chunhai; Song, Shiping

    2015-10-07

    In recent years, graphene has received widespread attention owing to its extraordinary electrical, chemical, optical, mechanical and structural properties. Lately, considerable interest has been focused on exploring the potential applications of graphene in life sciences, particularly in disease-related molecular diagnostics. In particular, the coupling of functional molecules with graphene as a nanoprobe offers an excellent platform to realize the detection of biomarkers, such as nucleic acids, proteins and other bioactive molecules, with high performance. This article reviews emerging graphene-based nanoprobes in electrical, optical and other assay methods and their application in various strategies of molecular diagnostics. In particular, this review focuses on the construction of graphene-based nanoprobes and their special advantages for the detection of various bioactive molecules. Properties of graphene-based materials and their functionalization are also comprehensively discussed in view of the development of nanoprobes. Finally, future challenges and perspectives of graphene-based nanoprobes are discussed.

  3. Finding diversity for building one-day ahead Hydrological Ensemble Prediction System based on artificial neural network stacks

    NASA Astrophysics Data System (ADS)

    Brochero, Darwin; Anctil, Francois; Gagné, Christian; López, Karol

    2013-04-01

    In this study, we addressed the application of Artificial Neural Networks (ANN) in the context of Hydrological Ensemble Prediction Systems (HEPS). Such systems have become popular in the past years as a tool to include the forecast uncertainty in the decision making process. HEPS considers fundamentally the uncertainty cascade model [4] for uncertainty representation. Analogously, the machine learning community has proposed models of multiple classifier systems that take into account the variability in datasets, input space, model structures, and parametric configuration [3]. This approach is based primarily on the well-known "no free lunch theorem" [1]. Consequently, we propose a framework based on two separate but complementary topics: data stratification and input variable selection (IVS). Thus, we promote an ANN prediction stack in which each predictor is trained based on input spaces defined by the IVS application on different stratified sub-samples. All this, added to the inherent variability of classical ANN optimization, leads us to our ultimate goal: diversity in the prediction, defined as the complementarity of the individual predictors. The stratification application on the 12 basins used in this study, which originate from the second and third workshop of the MOPEX project [2], shows that the informativeness of the data is far more important than the quantity used for ANN training. Additionally, the input space variability leads to ANN stacks that outperform an ANN stack model trained with 100% of the available information but with a random selection of dataset used in the early stopping method (scenario R100P). The results show that from a deterministic view, the main advantage focuses on the efficient selection of the training information, which is an equally important concept for the calibration of conceptual hydrological models. On the other hand, the diversity achieved is reflected in a substantial improvement in the scores that define the

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

    NASA Astrophysics Data System (ADS)

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

    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.

  5. Probabilistic Forecast for 21st Century Climate Based on an Ensemble of Simulations using a Business-As-Usual Scenario

    NASA Astrophysics Data System (ADS)

    Scott, J. R.; Forest, C. E.; Sokolov, A. P.; Dutkiewicz, S.

    2011-12-01

    The behavior of the climate system is examined in an ensemble of runs using an Earth System Model of intermediate complexity. Climate "parameters" varied are the climate sensitivity, the aerosol forcing, and the strength of ocean heat uptake. Variations in the latter were accomplished by changing the strength of the oceans' background vertical mixing. While climate sensitivity and aerosol forcing can be varied over rather wide ranges, it is more difficult to create such variation in heat uptake while maintaining a realistic overturning ocean circulation. Therefore, separate ensembles were carried out for a few values of the vertical diffusion coefficient. Joint probability distributions for climate sensitivity and aerosol forcing are constructed by comparing results from 20th century simulations with available observational data. These distributions are then used to generate ensembles of 21st century simulations; results allow us to construct probabilistic distributions for changes in important climate change variables such as surface air temperature, sea level rise, and magnitude of the AMOC. Changes in the rate of air-sea flux of CO2 and the export of carbon into the deep ocean are also examined.

  6. Image Change Detection via Ensemble Learning

    SciTech Connect

    Martin, Benjamin W; Vatsavai, Raju

    2013-01-01

    The concept of geographic change detection is relevant in many areas. Changes in geography can reveal much information about a particular location. For example, analysis of changes in geography can identify regions of population growth, change in land use, and potential environmental disturbance. A common way to perform change detection is to use a simple method such as differencing to detect regions of change. Though these techniques are simple, often the application of these techniques is very limited. Recently, use of machine learning methods such as neural networks for change detection has been explored with great success. In this work, we explore the use of ensemble learning methodologies for detecting changes in bitemporal synthetic aperture radar (SAR) images. Ensemble learning uses a collection of weak machine learning classifiers to create a stronger classifier which has higher accuracy than the individual classifiers in the ensemble. The strength of the ensemble lies in the fact that the individual classifiers in the ensemble create a mixture of experts in which the final classification made by the ensemble classifier is calculated from the outputs of the individual classifiers. Our methodology leverages this aspect of ensemble learning by training collections of weak decision tree based classifiers to identify regions of change in SAR images collected of a region in the Staten Island, New York area during Hurricane Sandy. Preliminary studies show that the ensemble method has approximately 11.5% higher change detection accuracy than an individual classifier.

  7. On the Utility of a Modest Physics-Based High-Resolution WRF Ensemble for Hurricane Prediction: Hurricane Ivan as an Example

    NASA Astrophysics Data System (ADS)

    Tilley, J. S.; Bower, K. A.; Kumar, S. S.; Kucera, P. A.; Askelson, M. A.

    2005-05-01

    The remarkable 2004 Atlantic hurricane season featured six "major" hurricanes (according to the Saffir-Simpson (SS) intensity scale), four of which directly impacted the state of Florida (Charley, Frances, Ivan, Jeanne) within a six-week period. Of these, Hurricane Ivan distinguished itself with impressive statistics in terms of lifespan (22 days), maximum intensity (SS category 5), damage (est. 13 billion dollars) and U.S. deaths (26). A variety of tools are currently available to forecasters at the National Oceanographic and Atmospheric Administration's (NOAA) Tropical Prediction Center (TPC), including several deterministic and statistical models as well as the Florida State University superensemble (e.g., Shin and Krishnamurti, 2003a,b). Often a blend of solutions from the various packages is utilized, though in other cases the TPC forecasters will follow the solution from a preferred model based on recent performance for the tropical cyclone of interest. Given that the NOAA National Centers for Environmental Prediction (NCEP) continue to move towards an operational environment where a relatively modest ensemble (roughly 6 members), constructed from within the Weather Research and Forecasting (WRF) framework, will figure prominently in the near future (DiMego 2004), a timely question to ask is whether the performance of such an ensemble for tropical systems will add value to the tool box now available to TPC forecasters. While a fully robust answer to this question demands a period of extensive testing under operational conditions, individual case studies can provide significant insights into some aspects of the expected performance of such a modeling system. Therefore, in this presentation we will present early results and limited performance metrics for such a case study, focusing on the 30-hour period beginning with Hurricane Ivan's entrance into the Gulf of Mexico. We note that while our 7-member ensemble consists entirely of WRF model members, in line with

  8. Restoring electronic coherence/decoherence for a trajectory-based nonadiabatic molecular dynamics

    PubMed Central

    Zhu, Chaoyuan

    2016-01-01

    By utilizing the time-independent semiclassical phase integral, we obtained modified coupled time-dependent Schrödinger equations that restore coherences and induce decoherences within original simple trajectory-based nonadiabatic molecular dynamic algorithms. Nonadiabatic transition probabilities simulated from both Tully’s fewest switches and semiclassical Ehrenfest algorithms follow exact quantum electronic oscillations and amplitudes for three out of the four well-known model systems. Within the present theory, nonadiabatic transitions estimated from statistical ensemble of trajectories accurately follow those of the modified electronic wave functions. The present theory can be immediately applied to the molecular dynamic simulations of photochemical and photophysical processes involving electronic excited states. PMID:27063337

  9. Generalized kinetic theory of ensembles with variable charges

    NASA Astrophysics Data System (ADS)

    Ivlev, A. V.; Zhdanov, S. K.; Klumov, B. A.; Morfill, G. E.

    2005-09-01

    A generalized kinetic theory of gaseous ensembles of particles with variable charges is proposed. The evolution of the ensembles due to the mutual particle collisions is investigated. The cases of inhomogeneous and randomly fluctuating charges are studied. It is shown that the particle temperature in such ensembles increases with time, and in some cases can grow by orders of magnitude. The theory is compared with the molecular-dynamics simulations, the relevance to typical experimental conditions is analyzed, and astrophysical implications are discussed.

  10. Ensemble of Surrogates-based Optimization for Identifying an Optimal Surfactant-enhanced Aquifer Remediation Strategy at Heterogeneous DNAPL-contaminated Sites

    NASA Astrophysics Data System (ADS)

    Lu, W., Sr.; Xin, X.; Luo, J.; Jiang, X.; Zhang, Y.; Zhao, Y.; Chen, M.; Hou, Z.; Ouyang, Q.

    2015-12-01

    The purpose of this study was to identify an optimal surfactant-enhanced aquifer remediation (SEAR) strategy for aquifers contaminated by dense non-aqueous phase liquid (DNAPL) based on an ensemble of surrogates-based optimization technique. A saturated heterogeneous medium contaminated by nitrobenzene was selected as case study. A new kind of surrogate-based SEAR optimization employing an ensemble surrogate (ES) model together with a genetic algorithm (GA) is presented. Four methods, namely radial basis function artificial neural network (RBFANN), kriging (KRG), support vector regression (SVR), and kernel extreme learning machines (KELM), were used to create four individual surrogate models, which were then compared. The comparison enabled us to select the two most accurate models (KELM and KRG) to establish an ES model of the SEAR simulation model, and the developed ES model as well as these four stand-alone surrogate models was compared. The results showed that the average relative error of the average nitrobenzene removal rates between the ES model and the simulation model for 20 test samples was 0.8%, which is a high approximation accuracy, and which indicates that the ES model provides more accurate predictions than the stand-alone surrogate models. Then, a nonlinear optimization model was formulated for the minimum cost, and the developed ES model was embedded into this optimization model as a constrained condition. Besides, GA was used to solve the optimization model to provide the optimal SEAR strategy. The developed ensemble surrogate-optimization approach was effective in seeking a cost-effective SEAR strategy for heterogeneous DNAPL-contaminated sites. This research is expected to enrich and develop the theoretical and technical implications for the analysis of remediation strategy optimization of DNAPL-contaminated aquifers.

  11. Build an Ensemble-based Remote-Sensing Driven Coupled Flash Flood and Landslide Warning System and Its Evaluation Across the United States

    NASA Astrophysics Data System (ADS)

    Zhang, K.; Hong, Y.; Gourley, J. J.; Vergara, H. J.; Xue, X.; Lu, N.; Wooten, R.

    2014-12-01

    Flooding and flash flooding are the most costly weather-related natural hazards in the United States and world. Heavy rainfall-triggered landslides are often associated with flash flood events and cause additional loss of life and property. Therefore, it is important to understand the linkage and interaction between flash flood events and landslides. It is also pertinent to build a robust coupled flash flood and landslide disaster early warning system for disaster preparedness and hazard management. In this study, we built a coupled flash flood and landslide disaster early warning system, which is aimed for operational use by the US National Weather Service, based on an existing ensemble framework by extending the model ensemble and coupling a set of distributed hydrologic models, the Coupled Routing and Excess STorage (CREST) model and the SACramento Soil Moisture Accounting (SAC-SMA) model, with two physically based landslide prediction models, the SLope-Infiltration-Distributed Equilibrium (SLIDE) model and the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model. We tested this prototype warning system by conducting multi-year simulations driven by the Multi-Radar Multi-Sensor (MRMS) rainfall estimates at selected basins across the United States. We then comprehensively evaluated the predictive capabilities of this system against observed and reported flood and landslides events. Our results show that the system is generally capable of making accurate predictions of flash flood and landslide events in terms of their locations and time of occurrence. The recently developed ensemble framework also enables us to quantify the uncertainty of the predictions and the probabilities of anticipated disaster events.

  12. Generalized Ensemble Sampling of Enzyme Reaction Free Energy Pathways

    PubMed Central

    Wu, Dongsheng; Fajer, Mikolai I.; Cao, Liaoran; Cheng, Xiaolin; Yang, Wei

    2016-01-01

    Free energy path sampling plays an essential role in computational understanding of chemical reactions, particularly those occurring in enzymatic environments. Among a variety of molecular dynamics simulation approaches, the generalized ensemble sampling strategy is uniquely attractive for the fact that it not only can enhance the sampling of rare chemical events but also can naturally ensure consistent exploration of environmental degrees of freedom. In this review, we plan to provide a tutorial-like tour on an emerging topic: generalized ensemble sampling of enzyme reaction free energy path. The discussion is largely focused on our own studies, particularly ones based on the metadynamics free energy sampling method and the on-the-path random walk path sampling method. We hope that this mini presentation will provide interested practitioners some meaningful guidance for future algorithm formulation and application study. PMID:27498634

  13. Generalized Ensemble Sampling of Enzyme Reaction Free Energy Pathways.

    PubMed

    Wu, D; Fajer, M I; Cao, L; Cheng, X; Yang, W

    2016-01-01

    Free energy path sampling plays an essential role in computational understanding of chemical reactions, particularly those occurring in enzymatic environments. Among a variety of molecular dynamics simulation approaches, the generalized ensemble sampling strategy is uniquely attractive for the fact that it not only can enhance the sampling of rare chemical events but also can naturally ensure consistent exploration of environmental degrees of freedom. In this review, we plan to provide a tutorial-like tour on an emerging topic: generalized ensemble sampling of enzyme reaction free energy path. The discussion is largely focused on our own studies, particularly ones based on the metadynamics free energy sampling method and the on-the-path random walk path sampling method. We hope that this minipresentation will provide interested practitioners some meaningful guidance for future algorithm formulation and application study.

  14. Can the combined use of an ensemble based modelling approach and the analysis of measured meteorological trends lead to increased confidence in climate change impact assessments?

    NASA Astrophysics Data System (ADS)

    Gädeke, Anne; Koch, Hagen; Pohle, Ina; Grünewald, Uwe

    2014-05-01

    In anthropogenically heavily impacted river catchments, such as the Lusatian river catchments of Spree and Schwarze Elster (Germany), the robust assessment of possible impacts of climate change on the regional water resources is of high relevance for the development and implementation of suitable climate change adaptation strategies. Large uncertainties inherent in future climate projections may, however, reduce the willingness of regional stakeholder to develop and implement suitable adaptation strategies to climate change. This study provides an overview of different possibilities to consider uncertainties in climate change impact assessments by means of (1) an ensemble based modelling approach and (2) the incorporation of measured and simulated meteorological trends. The ensemble based modelling approach consists of the meteorological output of four climate downscaling approaches (DAs) (two dynamical and two statistical DAs (113 realisations in total)), which drive different model configurations of two conceptually different hydrological models (HBV-light and WaSiM-ETH). As study area serve three near natural subcatchments of the Spree and Schwarze Elster river catchments. The objective of incorporating measured meteorological trends into the analysis was twofold: measured trends can (i) serve as a mean to validate the results of the DAs and (ii) be regarded as harbinger for the future direction of change. Moreover, regional stakeholders seem to have more trust in measurements than in modelling results. In order to evaluate the nature of the trends, both gradual (Mann-Kendall test) and step changes (Pettitt test) are considered as well as both temporal and spatial correlations in the data. The results of the ensemble based modelling chain show that depending on the type (dynamical or statistical) of DA used, opposing trends in precipitation, actual evapotranspiration and discharge are simulated in the scenario period (2031-2060). While the statistical DAs

  15. Molecular profiling of neurons based on connectivity.

    PubMed

    Ekstrand, Mats I; Nectow, Alexander R; Knight, Zachary A; Latcha, Kaamashri N; Pomeranz, Lisa E; Friedman, Jeffrey M

    2014-05-22

    The complexity and cellular heterogeneity of neural circuitry presents a major challenge to understanding the role of discrete neural populations in controlling behavior. While neuroanatomical methods enable high-resolution mapping of neural circuitry, these approaches do not allow systematic molecular profiling of neurons based on their connectivity. Here, we report the development of an approach for molecularly profiling projective neurons. We show that ribosomes can be tagged with a camelid nanobody raised against GFP and that this system can be engineered to selectively capture translating mRNAs from neurons retrogradely labeled with GFP. Using this system, we profiled neurons projecting to the nucleus accumbens. We then used an AAV to selectively profile midbrain dopamine neurons projecting to the nucleus accumbens. By comparing the captured mRNAs from each experiment, we identified a number of markers specific to VTA dopaminergic projection neurons. The current method provides a means for profiling neurons based on their projections.

  16. Multi-Conformer Ensemble Docking to Difficult Protein Targets

    DOE PAGES

    Ellingson, Sally R.; Miao, Yinglong; Baudry, Jerome; ...

    2014-09-08

    We investigate large-scale ensemble docking using five proteins from the Directory of Useful Decoys (DUD, dud.docking.org) for which docking to crystal structures has proven difficult. Molecular dynamics trajectories are produced for each protein and an ensemble of representative conformational structures extracted from the trajectories. Docking calculations are performed on these selected simulation structures and ensemble-based enrichment factors compared with those obtained using docking in crystal structures of the same protein targets or random selection of compounds. We also found simulation-derived snapshots with improved enrichment factors that increased the chemical diversity of docking hits for four of the five selected proteins.more » A combination of all the docking results obtained from molecular dynamics simulation followed by selection of top-ranking compounds appears to be an effective strategy for increasing the number and diversity of hits when using docking to screen large libraries of chemicals against difficult protein targets.« less

  17. Optimal Weights in Serial Generalized-Ensemble Simulations.

    PubMed

    Chelli, Riccardo

    2010-07-13

    In serial generalized-ensemble simulations, the sampling of a collective coordinate of a system is enhanced through non-Boltzmann weighting schemes. A popular version of such methods is certainly the simulated tempering technique, which is based on a random walk in temperature ensembles to explore the phase space more thoroughly. The most critical aspect of serial generalized-ensemble methods with respect to their parallel counterparts, such as replica exchange, is the difficulty of weight determination. Here we propose an adaptive approach to update the weights on the fly during the simulation. The algorithm is based on generalized forms of the Bennett acceptance ratio and of the free energy perturbation. It does not require intensive communication between processors and, therefore, is prone to be used in distributed computing environments with modest computational cost. We illustrate the method in a series of molecular dynamics simulations of a model system and compare its performances to two recent approaches, one based on adaptive Bayesian-weighted histogram analysis and the other based on initial estimates of weight factors obtained by potential energy averages.

  18. Ensembl regulation resources

    PubMed Central

    Zerbino, Daniel R.; Johnson, Nathan; Juetteman, Thomas; Sheppard, Dan; Wilder, Steven P.; Lavidas, Ilias; Nuhn, Michael; Perry, Emily; Raffaillac-Desfosses, Quentin; Sobral, Daniel; Keefe, Damian; Gräf, Stefan; Ahmed, Ikhlak; Kinsella, Rhoda; Pritchard, Bethan; Brent, Simon; Amode, Ridwan; Parker, Anne; Trevanion, Steven; Birney, Ewan; Dunham, Ian; Flicek, Paul

    2016-01-01

    New experimental techniques in epigenomics allow researchers to assay a diversity of highly dynamic features such as histone marks, DNA modifications or chromatin structure. The study of their fluctuations should provide insights into gene expression regulation, cell differentiation and disease. The Ensembl project collects and maintains the Ensembl regulation data resources on epigenetic marks, transcription factor binding and DNA methylation for human and mouse, as well as microarray probe mappings and annotations for a variety of chordate genomes. From this data, we produce a functional annotation of the regulatory elements along the human and mouse genomes with plans to expand to other species as data becomes available. Starting from well-studied cell lines, we will progressively expand our library of measurements to a greater variety of samples. Ensembl’s regulation resources provide a central and easy-to-query repository for reference epigenomes. As with all Ensembl data, it is freely available at http://www.ensembl.org, from the Perl and REST APIs and from the public Ensembl MySQL database server at ensembldb.ensembl.org. Database URL: http://www.ensembl.org PMID:26888907

  19. Advanced ensemble modelling of flexible macromolecules using X-ray solution scattering

    PubMed Central

    Tria, Giancarlo; Mertens, Haydyn D. T.; Kachala, Michael; Svergun, Dmitri I.

    2015-01-01

    Dynamic ensembles of macromolecules mediate essential processes in biology. Understanding the mechanisms driving the function and molecular interactions of ‘unstructured’ and flexible molecules requires alternative approaches to those traditionally employed in structural biology. Small-angle X-ray scattering (SAXS) is an established method for structural characterization of biological macromolecules in solution, and is directly applicable to the study of flexible systems such as intrinsically disordered proteins and multi-domain proteins with unstructured regions. The Ensemble Optimization Method (EOM) [Bernadó et al. (2007 ▶). J. Am. Chem. Soc. 129, 5656–5664] was the first approach introducing the concept of ensemble fitting of the SAXS data from flexible systems. In this approach, a large pool of macromolecules covering the available conformational space is generated and a sub-ensemble of conformers coexisting in solution is selected guided by the fit to the experimental SAXS data. This paper presents a series of new developments and advancements to the method, including significantly enhanced functionality and also quantitative metrics for the characterization of the results. Building on the original concept of ensemble optimization, the algorithms for pool generation have been redesigned to allow for the construction of partially or completely symmetric oligomeric models, and the selection procedure was improved to refine the size of the ensemble. Quantitative measures of the flexibility of the system studied, based on the characteristic integral parameters of the selected ensemble, are introduced. These improvements are implemented in the new EOM version 2.0, and the capabilities as well as inherent limitations of the ensemble approach in SAXS, and of EOM 2.0 in particular, are discussed. PMID:25866658

  20. Extended Gibbs ensembles with flow

    SciTech Connect

    Ison, M. J.

    2007-11-15

    A recently proposed [Ph. Chomaz, F. Gulminelli, and O. Juillet, Ann. Phys. (Paris) 320, 135 (2005)] statistical treatment of finite unbound systems in the presence of collective motions is applied to a classical Lennard-Jones system, numerically simulated through molecular dynamics. In the ideal gas limit, the flow dynamics can be exactly recast into effective time-dependent Lagrange parameters acting on a standard Gibbs ensemble with an extra total energy conservation constraint. Using this same ansatz for the low-density freeze-out configurations of an interacting expanding system, we show that the presence of flow can have a sizable effect on the microstate distribution.

  1. Hybrid Data Assimilation without Ensemble Filtering

    NASA Technical Reports Server (NTRS)

    Todling, Ricardo; Akkraoui, Amal El

    2014-01-01

    The Global Modeling and Assimilation Office is preparing to upgrade its three-dimensional variational system to a hybrid approach in which the ensemble is generated using a square-root ensemble Kalman filter (EnKF) and the variational problem is solved using the Grid-point Statistical Interpolation system. As in most EnKF applications, we found it necessary to employ a combination of multiplicative and additive inflations, to compensate for sampling and modeling errors, respectively and, to maintain the small-member ensemble solution close to the variational solution; we also found it necessary to re-center the members of the ensemble about the variational analysis. During tuning of the filter we have found re-centering and additive inflation to play a considerably larger role than expected, particularly in a dual-resolution context when the variational analysis is ran at larger resolution than the ensemble. This led us to consider a hybrid strategy in which the members of the ensemble are generated by simply converting the variational analysis to the resolution of the ensemble and applying additive inflation, thus bypassing the EnKF. Comparisons of this, so-called, filter-free hybrid procedure with an EnKF-based hybrid procedure and a control non-hybrid, traditional, scheme show both hybrid strategies to provide equally significant improvement over the control; more interestingly, the filter-free procedure was found to give qualitatively similar results to the EnKF-based procedure.

  2. Creating ensembles of decision trees through sampling

    DOEpatents

    Kamath, Chandrika; Cantu-Paz, Erick

    2005-08-30

    A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.

  3. Integrated logic gate for fluorescence turn-on detection of histidine and cysteine based on Ag/Au bimetallic nanoclusters-Cu²⁺ ensemble.

    PubMed

    Sun, Jian; Yang, Fan; Zhao, Dan; Chen, Chuanxia; Yang, Xiurong

    2015-04-01

    By means of employing 11-mercaptoundecanoic acid (11-MUA) as a reducing agent and protecting ligand, we present straightforward one-pot preparation of fluorescent Ag/Au bimetallic nanoclusters (namely AgAuNCs@11-MUA) from AgNO3 and HAuCl4 in alkaline aqueous solution at room temperature. It is found that the fluorescence of AgAuNCs@11-MUA has been selectively quenched by Cu(2+) ions, and the nonfluorescence off-state of the as-prepared AgAuNCs@11-MUA-Cu(2+) ensemble can be effectively switched on upon the addition of histidine and cysteine. By incorporating Ni(2+) ions and N-ethylmaleimide, this phenomenon is further exploited as an integrated logic gate and a specific fluorescence turn-on assay for selectively and sensitively sensing histidine and cysteine has been designed and established based on the original noncovalent AgAuNCs@11-MUA-Cu(2+) ensemble. Under the optimal conditions, histidine and cysteine can be detected in the concentration ranges of 0.25-9 and 0.25-7 μM; besides, the detection limits are found to be 87 and 111 nM (S/N = 3), respectively. Furthermore, we demonstrate that the proposed AgAuNCs@11-MUA-based fluorescent assay can be successfully utilized for biological fluids sample analysis.

  4. Ensemble Data Mining Methods

    NASA Technical Reports Server (NTRS)

    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.

  5. Short-range ensemble predictions based on convection perturbations in the Eta Model for the Serra do Mar region in Brazil

    NASA Astrophysics Data System (ADS)

    Bustamante, J. F. F.; Chou, S. C.; Gomes, J. L.

    2009-04-01

    The Southeast Brazil, in the coastal and mountain region called Serra do Mar, between Sao Paulo and Rio de Janeiro, is subject to frequent events of landslides and floods. The Eta Model has been producing good quality forecasts over South America at about 40-km horizontal resolution. For that type of hazards, however, more detailed and probabilistic information on the risks should be provided with the forecasts. Thus, a short-range ensemble prediction system (SREPS) based on the Eta Model is being constructed. Ensemble members derived from perturbed initial and lateral boundary conditions did not provide enough spread for the forecasts. Members with model physics perturbation are being included and tested. The objective of this work is to construct more members for the Eta SREPS by adding physics perturbed members. The Eta Model is configured at 10-km resolution and 38 layers in the vertical. The domain covered is most of Southeast Brazil, centered over the Serra do Mar region. The constructed members comprise variations of the cumulus parameterization Betts-Miller-Janjic (BMJ) and Kain-Fritsch (KF) schemes. Three members were constructed from the BMJ scheme by varying the deficit of saturation pressure profile over land and sea, and 2 members of the KF scheme were included using the standard KF and a momentum flux added to KF scheme version. One of the runs with BMJ scheme is the control run as it was used for the initial condition perturbation SREPS. The forecasts were tested for 6 cases of South America Convergence Zone (SACZ) events. The SACZ is a common summer season feature of Southern Hemisphere that causes persistent rain for a few days over the Southeast Brazil and it frequently organizes over Serra do Mar region. These events are particularly interesting because of the persistent rains that can accumulate large amounts and cause generalized landslides and death. With respect to precipitation, the KF scheme versions have shown to be able to reach the

  6. Bayesian ensemble refinement by replica simulations and reweighting

    NASA Astrophysics Data System (ADS)

    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.

  7. A mercuric ensemble based on a cycloruthenated complex as a visual probe for iodide in aqueous solution

    NASA Astrophysics Data System (ADS)

    Su, Xianlong; Guo, Lieping; Ma, Yajuan; Li, Xianghong

    2016-01-01

    A new water-soluble cycloruthenated complex Ru(bthiq)(dcbpy)2+ (1, Hbthiq = 1-(2-benzo[b]thiophenyl)isoquinoline, dcbpy = 4,4‧-dicarboxylate-2,2‧-bipyridine) was designed and synthesized to form its mercuric ensemble (1-Hg2+) to achieve visual detection of iodide anions. The binding constant of 1-Hg2+ is calculated to be 2.40 × 104 M-1, which is lower than that of HgI2. Therefore, the addition of I- to the aqueous solution of 1-Hg2+lead to significant color changes from yellow to deep-red by the release of 1. The results showed that iodide anions could be easily detected by the naked eyes. The detection limit of iodide anion is calculated as 0.77 μM. In addition, an easily-prepared test strip of 1-Hg2+ was obtained successfully to detect iodide anions.

  8. Ensemble Classification of Alzheimer's Disease and Mild Cognitive Impairment Based on Complex Graph Measures from Diffusion Tensor Images

    PubMed Central

    Ebadi, Ashkan; Dalboni da Rocha, Josué L.; Nagaraju, Dushyanth B.; Tovar-Moll, Fernanda; Bramati, Ivanei; Coutinho, Gabriel; Sitaram, Ranganatha; Rashidi, Parisa

    2017-01-01

    The human brain is a complex network of interacting regions. The gray matter regions of brain are interconnected by white matter tracts, together forming one integrative complex network. In this article, we report our investigation about the potential of applying brain connectivity patterns as an aid in diagnosing Alzheimer's disease and Mild Cognitive Impairment (MCI). We performed pattern analysis of graph theoretical measures derived from Diffusion Tensor Imaging (DTI) data representing structural brain networks of 45 subjects, consisting of 15 patients of Alzheimer's disease (AD), 15 patients of MCI, and 15 healthy subjects (CT). We considered pair-wise class combinations of subjects, defining three separate classification tasks, i.e., AD-CT, AD-MCI, and CT-MCI, and used an ensemble classification module to perform the classification tasks. Our ensemble framework with feature selection shows a promising performance with classification accuracy of 83.3% for AD vs. MCI, 80% for AD vs. CT, and 70% for MCI vs. CT. Moreover, our findings suggest that AD can be related to graph measures abnormalities at Brodmann areas in the sensorimotor cortex and piriform cortex. In this way, node redundancy coefficient and load centrality in the primary motor cortex were recognized as good indicators of AD in contrast to MCI. In general, load centrality, betweenness centrality, and closeness centrality were found to be the most relevant network measures, as they were the top identified features at different nodes. The present study can be regarded as a “proof of concept” about a procedure for the classification of MRI markers between AD dementia, MCI, and normal old individuals, due to the small and not well-defined groups of AD and MCI patients. Future studies with larger samples of subjects and more sophisticated patient exclusion criteria are necessary toward the development of a more precise technique for clinical diagnosis. PMID:28293162

  9. An Ensemble Method to Distinguish Bacteriophage Virion from Non-Virion Proteins Based on Protein Sequence Characteristics.

    PubMed

    Zhang, Lina; Zhang, Chengjin; Gao, Rui; Yang, Runtao

    2015-09-09

    Bacteriophage virion proteins and non-virion proteins have distinct functions in biological processes, such as specificity determination for host bacteria, bacteriophage replication and transcription. Accurate identification of bacteriophage virion proteins from bacteriophage protein sequences is significant to understand the complex virulence mechanism in host bacteria and the influence of bacteriophages on the development of antibacterial drugs. In this study, an ensemble method for bacteriophage virion protein prediction from bacteriophage protein sequences is put forward with hybrid feature spaces incorporating CTD (composition, transition and distribution), bi-profile Bayes, PseAAC (pseudo-amino acid composition) and PSSM (position-specific scoring matrix). When performing on the training dataset 10-fold cross-validation, the presented method achieves a satisfactory prediction result with a sensitivity of 0.870, a specificity of 0.830, an accuracy of 0.850 and Matthew's correlation coefficient (MCC) of 0.701, respectively. To evaluate the prediction performance objectively, an independent testing dataset is used to evaluate the proposed method. Encouragingly, our proposed method performs better than previous studies with a sensitivity of 0.853, a specificity of 0.815, an accuracy of 0.831 and MCC of 0.662 on the independent testing dataset. These results suggest that the proposed method can be a potential candidate for bacteriophage virion protein prediction, which may provide a useful tool to find novel antibacterial drugs and to understand the relationship between bacteriophage and host bacteria. For the convenience of the vast majority of experimental Int. J. Mol. Sci. 2015, 16,21735 scientists, a user-friendly and publicly-accessible web-server for the proposed ensemble method is established.

  10. An Ensemble Method to Distinguish Bacteriophage Virion from Non-Virion Proteins Based on Protein Sequence Characteristics

    PubMed Central

    Zhang, Lina; Zhang, Chengjin; Gao, Rui; Yang, Runtao

    2015-01-01

    Bacteriophage virion proteins and non-virion proteins have distinct functions in biological processes, such as specificity determination for host bacteria, bacteriophage replication and transcription. Accurate identification of bacteriophage virion proteins from bacteriophage protein sequences is significant to understand the complex virulence mechanism in host bacteria and the influence of bacteriophages on the development of antibacterial drugs. In this study, an ensemble method for bacteriophage virion protein prediction from bacteriophage protein sequences is put forward with hybrid feature spaces incorporating CTD (composition, transition and distribution), bi-profile Bayes, PseAAC (pseudo-amino acid composition) and PSSM (position-specific scoring matrix). When performing on the training dataset 10-fold cross-validation, the presented method achieves a satisfactory prediction result with a sensitivity of 0.870, a specificity of 0.830, an accuracy of 0.850 and Matthew’s correlation coefficient (MCC) of 0.701, respectively. To evaluate the prediction performance objectively, an independent testing dataset is used to evaluate the proposed method. Encouragingly, our proposed method performs better than previous studies with a sensitivity of 0.853, a specificity of 0.815, an accuracy of 0.831 and MCC of 0.662 on the independent testing dataset. These results suggest that the proposed method can be a potential candidate for bacteriophage virion protein prediction, which may provide a useful tool to find novel antibacterial drugs and to understand the relationship between bacteriophage and host bacteria. For the convenience of the vast majority of experimental scientists, a user-friendly and publicly-accessible web-server for the proposed ensemble method is established. PMID:26370987

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

    PubMed

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

    2015-04-21

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

  12. Molecular-Based Devices and Circuits

    DTIC Science & Technology

    2008-09-23

    nano-cavities (50nm x 50nm) etched into the Si3N4 layer at the center of the electrode. Subsequently, molecules are self - assembled onto the bottom...various types of self assembled monolayers (SAMs) arranged in vertical configuration (Fig 2) . Each floor consists of different type of molecular layer...modified ferrocene film (Figure 2 compound 1) , and a the protein Azurin (Az). The Fc-based SAM can be used as a candidate for the bottom layer as we have

  13. Project FIRES [Firefighters' Integrated Response Equipment System]. Volume 2: Protective Ensemble Performance Standards, Phase 1B

    NASA Technical Reports Server (NTRS)

    Abeles, F. J.

    1980-01-01

    The design of the prototype protective ensemble was finalized. Prototype ensembles were fabricated and then subjected to a series of qualification tests which were based upon the protective ensemble performance standards PEPS requirements. Engineering drawings and purchase specifications were prepared for the new protective ensemble.

  14. Organic-based molecular switches for molecular electronics.

    PubMed

    Fuentes, Noelia; Martín-Lasanta, Ana; Alvarez de Cienfuegos, Luis; Ribagorda, Maria; Parra, Andres; Cuerva, Juan M

    2011-10-05

    In a general sense, molecular electronics (ME) is the branch of nanotechnology which studies the application of molecular building blocks for the fabrication of electronic components. Among the different types of molecules, organic compounds have been revealed as promising candidates for ME, due to the easy access, great structural diversity and suitable electronic and mechanical properties. Thanks to these useful capabilities, organic molecules have been used to emulate electronic devices at the nanoscopic scale. In this feature article, we present the diverse strategies used to develop organic switches towards ME with special attention to non-volatile systems.

  15. Dimensionality Reduction Through Classifier Ensembles

    NASA Technical Reports Server (NTRS)

    Oza, Nikunj C.; Tumer, Kagan; Norwig, Peter (Technical Monitor)

    1999-01-01

    In data mining, one often needs to analyze datasets with a very large number of attributes. Performing machine learning directly on such data sets is often impractical because of extensive run times, excessive complexity of the fitted model (often leading to overfitting), and the well-known "curse of dimensionality." In practice, to avoid such problems, feature selection and/or extraction are often used to reduce data dimensionality prior to the learning step. However, existing feature selection/extraction algorithms either evaluate features by their effectiveness across the entire data set or simply disregard class information altogether (e.g., principal component analysis). Furthermore, feature extraction algorithms such as principal components analysis create new features that are often meaningless to human users. In this article, we present input decimation, a method that provides "feature subsets" that are selected for their ability to discriminate among the classes. These features are subsequently used in ensembles of classifiers, yielding results superior to single classifiers, ensembles that use the full set of features, and ensembles based on principal component analysis on both real and synthetic datasets.

  16. History matching and parameter estimation of surface deformation data for a CO2 sequestration field project using ensemble-based algorithm

    NASA Astrophysics Data System (ADS)

    Ping, J.; Tavakoli, R.; Min, B.; Srinivasan, S.; Wheeler, M. F.

    2015-12-01

    Optimal management of subsurface processes requires the characterization of the uncertainty in reservoir description and reservoir performance prediction. The application of ensemble-based algorithms for history matching reservoir models has been steadily increasing over the past decade. However, the majority of implementations in the reservoir engineering have dealt only with production history matching. During geologic sequestration, the injection of large quantities of CO2 into the subsurface may alter the stress/strain field which in turn can lead to surface uplift or subsidence. Therefore, it is essential to couple multiphase flow and geomechanical response in order to predict and quantify the uncertainty of CO2 plume movement for long-term, large-scale CO2 sequestration projects. In this work, we simulate and estimate the properties of a reservoir that is being used to store CO2 as part of the In Salah Capture and Storage project in Algeria. The CO2 is separated from produced natural gas and is re-injected into downdip aquifer portion of the field from three long horizontal wells. The field observation data includes ground surface deformations (uplift) measured using satellite-based radar (InSAR), injection well locations and CO2 injection rate histories provided by the operators. We implement ensemble-based algorithms for assimilating both injection rate data as well as geomechanical observations (surface uplift) into reservoir model. The preliminary estimation results of horizontal permeability and material properties such as Young Modulus and Poisson Ratio are consistent with available measurements and previous studies in this field. Moreover, the existence of high-permeability channels/fractures within the reservoir; especially in the regions around the injection wells are confirmed. This estimation results can be used to accurately and efficiently predict and monitor the movement of CO2 plume.

  17. Multicolor Electrochromic Devices Based on Molecular Plasmonics.

    PubMed

    Stec, Grant J; Lauchner, Adam; Cui, Yao; Nordlander, Peter; Halas, Naomi J

    2017-03-28

    Polycyclic aromatic hydrocarbon (PAH) molecules, the hydrogen-terminated, sub-nanometer-scale version of graphene, support plasmon resonances with the addition or removal of a single electron. Typically colorless when neutral, they are transformed into vivid optical absorbers in either their positively or negatively charged states. Here, we demonstrate a low-voltage, multistate electrochromic device based on PAH plasmon resonances that can be reversibly switched between nearly colorless (0 V), olive (+4 V), and royal blue (-3.5 V). The device exhibits highly efficient color change compared to electrochromic polymers and metal oxides, lower power consumption than liquid crystals, and is shown to reversibly switch for at least 100 cycles. We also demonstrate the additive property of molecular plasmon resonances in a single-layer device to display a reversible, transmissive-to-black device. This work illuminates the potential of PAH molecular plasmonics for the development of color displays and large-area color-changing applications due to their processability and ultralow power consumption.

  18. Clinical features and molecular bases of neuroacanthocytosis.

    PubMed

    Rampoldi, Luca; Danek, Adrian; Monaco, Anthony P

    2002-08-01

    The term acanthocytosis is derived from the Greek for "thorn" and is used to describe a peculiar spiky appearance of erythrocytes. Acanthocytosis is found to be associated with at least three hereditary neurological disorders that are generally referred to as neuroacanthocytosis. Abetalipoproteinaemia is an autosomal recessive condition, characterised by absence of serum apolipoprotein B containing lipoproteins leading to fat intolerance and fat-soluble vitamin deficiency. This results in a progressive spinocerebellar ataxia with peripheral neuropathy and retinitis pigmentosa. Chorea-acanthocytosis is also an autosomal recessive condition and is characterised by chorea, orofaciolingual dyskinesia, dysphagia, dysarthria, areflexia, seizures and dementia. Some of its features, including choreic movements, peripheral neuropathy with areflexia, elevated serum creatine kinase levels and myopathy are shared by another form of neuroacanthocytosis, McLeod syndrome. Patients affected by this X-linked disorder also show abnormal expression of Kell blood group antigens and a permanent haemolytic state. In addition to these cases, acanthocytosis is occasionally associated with other neurological disorders, such as Hallervorden-Spatz disease. For each of the neuroacanthocytosis syndromes we review the main clinical features and their molecular bases. The recent molecular genetics findings are the first step towards the understanding of the pathogenetic mechanisms and eventually the search for effective treatments.

  19. Protein-based tumor molecular imaging probes

    PubMed Central

    Lin, Xin; Xie, Jin

    2013-01-01

    Molecular imaging is an emerging discipline which plays critical roles in diagnosis and therapeutics. It visualizes and quantifies markers that are aberrantly expressed during the disease origin and development. Protein molecules remain to be one major class of imaging probes, and the option has been widely diversified due to the recent advances in protein engineering techniques. Antibodies are part of the immunosystem which interact with target antigens with high specificity and affinity. They have long been investigated as imaging probes and were coupled with imaging motifs such as radioisotopes for that purpose. However, the relatively large size of antibodies leads to a half-life that is too long for common imaging purposes. Besides, it may also cause a poor tissue penetration rate and thus compromise some medical applications. It is under this context that various engineered protein probes, essentially antibody fragments, protein scaffolds, and natural ligands have been developed. Compared to intact antibodies, they possess more compact size, shorter clearance time, and better tumor penetration. One major challenge of using protein probes in molecular imaging is the affected biological activity resulted from random labeling. Site-specific modification, however, allows conjugation happening in a stoichiometric fashion with little perturbation of protein activity. The present review will discuss protein-based probes with focus on their application and related site-specific conjugation strategies in tumor imaging. PMID:20232092

  20. Illumination Variation-Resistant Video-Based Heart Rate Measurement Using Joint Blind Source Separation and Ensemble Empirical Mode Decomposition.

    PubMed

    Cheng, Juan; Chen, Xun; Xu, Lingxi; Wang, Z Jane

    2016-10-06

    Recent studies have demonstrated that heart rate (HR) could be estimated using video data (e.g., exploring human facial regions of interest (ROIs)) under well controlled conditions. However, in practice, the pulse signals may be contaminated by motions and illumination variations. In this paper, tackling the illumination variation challenge, we propose an illuminationrobust framework using joint blind source separation (JBSS) and ensemble empirical mode decomposition (EEMD) to effectively evaluate HR from webcam videos. The framework takes the hypotheses that both facial ROI and background ROI have similar illumination variations. The background ROI is then considered as a noise reference sensor to denoise the facial signals by using the JBSS technique to extract the underlying illumination variation sources. Further, the reconstructed illumination-resisted green channel of the facial ROI is detrended and decomposed into a number of intrinsic mode functions (IMFs) using EEMD to estimate the HR. Experimental results demonstrated that the proposed framework could estimate HR more accurately than the state-of-the-art methods. The Bland-Altman plots showed that it led to better agreement with HR ground truth with the mean bias 1.15 beat per minute (bpm), with 95 % limits from -15.43 bpm to 17.73 bpm, and the correlation coefficient 0.53. This study provides a promising solution for realistic non-contact and robust HR measurement applications.

  1. Projections of Water Stress Based on an Ensemble of Socioeconomic Growth and Climate Change Scenarios: A Case Study in Asia.

    PubMed

    Fant, Charles; Schlosser, C Adam; Gao, Xiang; Strzepek, Kenneth; Reilly, John

    2016-01-01

    The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios--internally consistent across economics, emissions, climate, and population--to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify the primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region's population will live in water-stressed regions in the near future. Tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers.

  2. Projections of water stress based on an ensemble of socioeconomic growth and climate change scenarios: A case study in Asia

    SciTech Connect

    Fant, Charles; Schlosser, C. Adam; Gao, Xiang; Strzepek, Kenneth; Reilly, John; Ebi, Kristie L.

    2016-03-30

    The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify the primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region’s population will live in water-stressed regions in the near future. Lastly, tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers.

  3. Six month-lead downscaling prediction of winter to spring drought in South Korea based on a multimodel ensemble

    NASA Astrophysics Data System (ADS)

    Sohn, Soo-Jin; Ahn, Joong-Bae; Tam, Chi-Yung

    2013-02-01

    Abstract The potential of using a dynamical-statistical method for long-lead drought prediction was investigated. In particular, the APEC Climate Center one-tier multimodel <span class="hlt">ensemble</span> (MME) was downscaled for predicting the standardized precipitation evapotranspiration index (SPEI) over 60 stations in South Korea. SPEI depends on both precipitation and temperature, and can incorporate the effect of global warming on the balance between precipitation and evapotranspiration. It was found that the one-tier MME has difficulty in capturing the local temperature and rainfall variations over extratropical land areas, and has no skill in predicting SPEI during boreal winter and spring. On the other hand, temperature and precipitation predictions were substantially improved in the downscaled MME. In conjunction with variance inflation, downscaled MME can give reasonably skillful 6 month-lead forecasts of SPEI for the winter to spring period. Our results could lead to more reliable hydrological extreme predictions for policymakers and stakeholders in the water management sector, and for better mitigation and climate adaptations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016NatSR...629962J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016NatSR...629962J"><span id="translatedtitle">Predictability of Precipitation Over the Conterminous U.S. <span class="hlt">Based</span> on the CMIP5 Multi-Model <span class="hlt">Ensemble</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jiang, Mingkai; Felzer, Benjamin S.; Sahagian, Dork</p> <p>2016-07-01</p> <p>Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model <span class="hlt">ensembles</span>, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950–2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040–2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4947969','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4947969"><span id="translatedtitle">Predictability of Precipitation Over the Conterminous U.S. <span class="hlt">Based</span> on the CMIP5 Multi-Model <span class="hlt">Ensemble</span></span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Jiang, Mingkai; Felzer, Benjamin S.; Sahagian, Dork</p> <p>2016-01-01</p> <p>Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model <span class="hlt">ensembles</span>, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950–2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040–2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment. PMID:27425819</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4814075','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4814075"><span id="translatedtitle">Projections of Water Stress <span class="hlt">Based</span> on an <span class="hlt">Ensemble</span> of Socioeconomic Growth and Climate Change Scenarios: A Case Study in Asia</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Fant, Charles; Schlosser, C. Adam; Gao, Xiang; Strzepek, Kenneth; Reilly, John</p> <p>2016-01-01</p> <p>The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large <span class="hlt">ensemble</span> of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify the primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region’s population will live in water-stressed regions in the near future. Tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers. PMID:27028871</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27425819','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27425819"><span id="translatedtitle">Predictability of Precipitation Over the Conterminous U.S. <span class="hlt">Based</span> on the CMIP5 Multi-Model <span class="hlt">Ensemble</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jiang, Mingkai; Felzer, Benjamin S; Sahagian, Dork</p> <p>2016-07-18</p> <p>Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model <span class="hlt">ensembles</span>, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950-2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040-2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1255116-projections-water-stress-based-ensemble-socioeconomic-growth-climate-change-scenarios-case-study-asia','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1255116-projections-water-stress-based-ensemble-socioeconomic-growth-climate-change-scenarios-case-study-asia"><span id="translatedtitle">Projections of water stress <span class="hlt">based</span> on an <span class="hlt">ensemble</span> of socioeconomic growth and climate change scenarios: A case study in Asia</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Fant, Charles; Schlosser, C. Adam; Gao, Xiang; ...</p> <p>2016-03-30</p> <p>The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large <span class="hlt">ensemble</span> of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify themore » primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region’s population will live in water-stressed regions in the near future. Lastly, tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1231194','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1231194"><span id="translatedtitle">Matlab Cluster <span class="hlt">Ensemble</span> Toolbox</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Sapio, Vincent De; Kegelmeyer, Philip</p> <p>2009-04-27</p> <p>This is a Matlab toolbox for investigating the application of cluster <span class="hlt">ensembles</span> to data classification, with the objective of improving the accuracy and/or speed of clustering. The toolbox divides the cluster <span class="hlt">ensemble</span> problem into four areas, providing functionality for each. These include, (1) synthetic data generation, (2) clustering to generate individual data partitions and similarity matrices, (3) consensus function generation and final clustering to generate <span class="hlt">ensemble</span> data partitioning, and (4) implementation of accuracy metrics. With regard to data generation, Gaussian data of arbitrary dimension can be generated. The kcenters algorithm can then be used to generate individual data partitions by either, (a) subsampling the data and clustering each subsample, or by (b) randomly initializing the algorithm and generating a clustering for each initialization. In either case an overall similarity matrix can be computed using a consensus function operating on the individual similarity matrices. A final clustering can be performed and performance metrics are provided for evaluation purposes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013JChPh.139l4102A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013JChPh.139l4102A"><span id="translatedtitle">Mapping variable ring polymer <span class="hlt">molecular</span> dynamics: A path-integral <span class="hlt">based</span> method for nonadiabatic processes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ananth, Nandini</p> <p>2013-09-01</p> <p>We introduce mapping-variable ring polymer <span class="hlt">molecular</span> dynamics (MV-RPMD), a model dynamics for the direct simulation of multi-electron processes. An extension of the RPMD idea, this method is <span class="hlt">based</span> on an exact, imaginary time path-integral representation of the quantum Boltzmann operator using continuous Cartesian variables for both electronic states and nuclear degrees of freedom. We demonstrate the accuracy of the MV-RPMD approach in calculations of real-time, thermal correlation functions for a range of two-state single-mode model systems with different coupling strengths and asymmetries. Further, we show that the <span class="hlt">ensemble</span> of classical trajectories employed in these simulations preserves the Boltzmann distribution and provides a direct probe into real-time coupling between electronic state transitions and nuclear dynamics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GML...tmp...23S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GML...tmp...23S"><span id="translatedtitle">Effects of chemical dispersants on oil spill drift paths in the German Bight—probabilistic assessment <span class="hlt">based</span> on numerical <span class="hlt">ensemble</span> simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schwichtenberg, Fabian; Callies, Ulrich; Groll, Nikolaus; Maßmann, Silvia</p> <p>2016-06-01</p> <p>Oil dispersed in the water column remains sheltered from wind forcing, so that an altered drift path is a key consequence of using chemical dispersants. In this study, <span class="hlt">ensemble</span> simulations were conducted <span class="hlt">based</span> on 7 years of simulated atmospheric and marine conditions, evaluating 2,190 hypothetical spills from each of 636 cells of a regular grid covering the inner German Bight (SE North Sea). Each simulation compares two idealized setups assuming either undispersed or fully dispersed oil. Differences are summarized in a spatial map of probabilities that chemical dispersant applications would help prevent oil pollution from entering intertidal coastal areas of the Wadden Sea. High probabilities of success overlap strongly with coastal regions between 10 m and 20 m water depth, where the use of chemical dispersants for oil spill response is a particularly contentious topic. The present study prepares the ground for a more detailed net environmental benefit analysis (NEBA) accounting also for toxic effects.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GML....37..163S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GML....37..163S"><span id="translatedtitle">Effects of chemical dispersants on oil spill drift paths in the German Bight—probabilistic assessment <span class="hlt">based</span> on numerical <span class="hlt">ensemble</span> simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schwichtenberg, Fabian; Callies, Ulrich; Groll, Nikolaus; Maßmann, Silvia</p> <p>2017-04-01</p> <p>Oil dispersed in the water column remains sheltered from wind forcing, so that an altered drift path is a key consequence of using chemical dispersants. In this study, <span class="hlt">ensemble</span> simulations were conducted <span class="hlt">based</span> on 7 years of simulated atmospheric and marine conditions, evaluating 2,190 hypothetical spills from each of 636 cells of a regular grid covering the inner German Bight (SE North Sea). Each simulation compares two idealized setups assuming either undispersed or fully dispersed oil. Differences are summarized in a spatial map of probabilities that chemical dispersant applications would help prevent oil pollution from entering intertidal coastal areas of the Wadden Sea. High probabilities of success overlap strongly with coastal regions between 10 m and 20 m water depth, where the use of chemical dispersants for oil spill response is a particularly contentious topic. The present study prepares the ground for a more detailed net environmental benefit analysis (NEBA) accounting also for toxic effects.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011WRR....47.0G02S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011WRR....47.0G02S"><span id="translatedtitle">Hydroclimatic projections for the Murray-Darling Basin <span class="hlt">based</span> on an <span class="hlt">ensemble</span> derived from Intergovernmental Panel on Climate Change AR4 climate models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sun, Fubao; Roderick, Michael L.; Lim, Wee Ho; Farquhar, Graham D.</p> <p>2011-12-01</p> <p>We assess hydroclimatic projections for the Murray-Darling Basin (MDB) using an <span class="hlt">ensemble</span> of 39 Intergovernmental Panel on Climate Change AR4 climate model runs <span class="hlt">based</span> on the A1B emissions scenario. The raw model output for precipitation, P, was adjusted using a quantile-<span class="hlt">based</span> bias correction approach. We found that the projected change, ΔP, between two 30 year periods (2070-2099 less 1970-1999) was little affected by bias correction. The range for ΔP among models was large (˜±150 mm yr-1) with all-model run and all-model <span class="hlt">ensemble</span> averages (4.9 and -8.1 mm yr-1) near zero, against a background climatological P of ˜500 mm yr-1. We found that the time series of actually observed annual P over the MDB was indistinguishable from that generated by a purely random process. Importantly, nearly all the model runs showed similar behavior. We used these facts to develop a new approach to understanding variability in projections of ΔP. By plotting ΔP versus the variance of the time series, we could easily identify model runs with projections for ΔP that were beyond the bounds expected from purely random variations. For the MDB, we anticipate that a purely random process could lead to differences of ±57 mm yr-1 (95% confidence) between successive 30 year periods. This is equivalent to ±11% of the climatological P and translates into variations in runoff of around ±29%. This sets a baseline for gauging modeled and/or observed changes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H41J..03B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H41J..03B"><span id="translatedtitle"><span class="hlt">Ensemble</span> postprocessing for probabilistic quantitative precipitation forecasts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bentzien, S.; Friederichs, P.</p> <p>2012-12-01</p> <p>Precipitation is one of the most difficult weather variables to predict in hydrometeorological applications. In order to assess the uncertainty inherent in deterministic numerical weather prediction (NWP), meteorological services around the globe develop <span class="hlt">ensemble</span> prediction systems (EPS) <span class="hlt">based</span> on high-resolution NWP systems. With non-hydrostatic model dynamics and without parameterization of deep moist convection, high-resolution NWP models are able to describe convective processes in more detail and provide more realistic mesoscale structures. However, precipitation forecasts are still affected by displacement errors, systematic biases and fast error growth on small scales. Probabilistic guidance can be achieved from an <span class="hlt">ensemble</span> setup which accounts for model error and uncertainty of initial and boundary conditions. The German Meteorological Service (Deutscher Wetterdienst, DWD) provides such an <span class="hlt">ensemble</span> system <span class="hlt">based</span> on the German-focused limited-area model COSMO-DE. With a horizontal grid-spacing of 2.8 km, COSMO-DE is the convection-permitting high-resolution part of the operational model chain at DWD. The COSMO-DE-EPS consists of 20 realizations of COSMO-DE, driven by initial and boundary conditions derived from 4 global models and 5 perturbations of model physics. <span class="hlt">Ensemble</span> systems like COSMO-DE-EPS are often limited with respect to <span class="hlt">ensemble</span> size due to the immense computational costs. As a consequence, they can be biased and exhibit insufficient <span class="hlt">ensemble</span> spread, and probabilistic forecasts may be not well calibrated. In this study, probabilistic quantitative precipitation forecasts are derived from COSMO-DE-EPS and evaluated at more than 1000 rain gauges located all over Germany. COSMO-DE-EPS is a frequently updated <span class="hlt">ensemble</span> system, initialized 8 times a day. We use the time-lagged approach to inexpensively increase <span class="hlt">ensemble</span> spread, which results in more reliable forecasts especially for extreme precipitation events. Moreover, we will show that statistical</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016PhRvE..94b1301S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016PhRvE..94b1301S"><span id="translatedtitle">First-order phase transitions in the real microcanonical <span class="hlt">ensemble</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schierz, Philipp; Zierenberg, Johannes; Janke, Wolfhard</p> <p>2016-08-01</p> <p>We present a simulation and data analysis technique to investigate first-order phase transitions and the associated transition barriers. The simulation technique is <span class="hlt">based</span> on the real microcanonical <span class="hlt">ensemble</span> where the sum of kinetic and potential energy is kept constant. The method is tested for the droplet condensation-evaporation transition in a Lennard-Jones system with up to 2048 particles at fixed density, using simple Metropolis-like sampling combined with a replica-exchange scheme. Our investigation of the microcanonical <span class="hlt">ensemble</span> properties reveals that the associated transition barrier is significantly lower than in the canonical counterpart. Along the line of investigating the microcanonical <span class="hlt">ensemble</span> behavior, we develop a framework for general <span class="hlt">ensemble</span> evaluations. This framework is <span class="hlt">based</span> on a clear separation between system-related and <span class="hlt">ensemble</span>-related properties, which can be exploited to specifically tailor artificial <span class="hlt">ensembles</span> suitable for first-order phase transitions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://eric.ed.gov/?q=Forte&pg=2&id=ED254263','ERIC'); return false;" href="http://eric.ed.gov/?q=Forte&pg=2&id=ED254263"><span id="translatedtitle">Music <span class="hlt">Ensemble</span>: Course Proposal.</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Kovach, Brian</p> <p></p> <p>A proposal is presented for a Music <span class="hlt">Ensemble</span> course to be offered at the Community College of Philadelphia for music students who have had previous vocal or instrumental training. A standardized course proposal cover form is followed by a statement of purpose for the course, a list of major course goals, a course outline, and a bibliography. Next,…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19810000222&hterms=wakefield&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dwakefield','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19810000222&hterms=wakefield&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dwakefield"><span id="translatedtitle">Protective Garment <span class="hlt">Ensemble</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wakefield, M. E.</p> <p>1982-01-01</p> <p>Protective garment <span class="hlt">ensemble</span> with internally-mounted environmental- control unit contains its own air supply. Alternatively, a remote-environmental control unit or an air line is attached at the umbilical quick disconnect. Unit uses liquid air that is vaporized to provide both breathing air and cooling. Totally enclosed garment protects against toxic substances.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H51G1460X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H51G1460X"><span id="translatedtitle">Prediction of Turbulent Heat Fluxes by Assimilation of Remotely Sensed Land Surface Temperature and Soil Moisture Data into an <span class="hlt">Ensemble-Based</span> Data Assimilation Framework</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xu, T.; Bateni, S. M.; Liu, S.</p> <p>2015-12-01</p> <p>Accurate estimation of turbulent heat fluxes is important for water resources planning and management, irrigation scheduling, and weather forecast. Land surface models (LSMs) can be used to simulate turbulent heat fluxes over large-scale domains. However, the application of LSMs is hindered due to the high uncertainty in model parameters and state variables. In this study, a dual-pass <span class="hlt">ensemble-based</span> data assimilation (DA) approach is developed to estimate turbulent heat fluxes. Initially, the common land model (CoLM) is used as the LSM (open-loop), and thereafter the <span class="hlt">ensemble</span> Kalman filter is employed to optimize the CoLM parameters and variables. The first pass of the DA scheme optimizes vegetation parameters of CoLM (which are related to the leaf stomatal conductance) on a weekly-basis by assimilating the MODIS land surface temperature (LST) data. The second pass optimizes the soil moisture state of CoLM on a daily-basis by assimilating soil moisture observations from Cosmic-ray instrument. The ultimate goal is to improve turbulent heat fluxes estimates from CoLM by optimizing its vegetation parameters and soil moisture state via assimilation of LST and soil moisture data into the proposed DA system. The DA approach is tested over a wet and densely vegetated site, called Daman in northwest of China. Results indicate that the CoLM (open-loop) model typically underestimates latent heat flux and overestimates sensible heat flux. By assimilation of LST in the first pass, the turbulent heat fluxes are improved compared to those of the open-loop. These fluxes become even more accurate by assimilation of soil moisture in the second pass of the DA approach. These findings illustrate that the introduced DA approach can successfully extract information in LST and soil moisture data to optimize the CoLM parameters and states and improve the turbulent heat fluxes estimates.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.1659T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.1659T"><span id="translatedtitle">Calibrated <span class="hlt">Ensemble</span> Forecasts using Quantile Regression Forests and <span class="hlt">Ensemble</span> Model Output Statistics.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Taillardat, Maxime; Mestre, Olivier; Zamo, Michaël; Naveau, Philippe</p> <p>2016-04-01</p> <p><span class="hlt">Ensembles</span> used for probabilistic weather forecasting tend to be biased and underdispersive. This presentation proposes a statistical method for postprocessing <span class="hlt">ensembles</span> <span class="hlt">based</span> on Quantile Regression Forests (QRF), a generalization of random forests for quantile regression. This method does not fit a parametric probability density function like in <span class="hlt">Ensemble</span> Model Output Statistics (EMOS) but provides an estimation of desired quantiles. This is a non-parametric approach which eliminates any assumption on the variable subject to calibration. This method can estimate quantiles using not only members of the <span class="hlt">ensemble</span> but any predictor available including statistics on other variables for example. The method is applied to the Météo-France 35-members <span class="hlt">ensemble</span> forecast (PEARP) for surface temperature and wind-speed for available lead times from 3 up to 54 hours and compared to EMOS. All postprocessed <span class="hlt">ensembles</span> are much better calibrated than the PEARP raw <span class="hlt">ensemble</span> and experiments on real data also show that QRF performs better than EMOS, and can bring a real gain for forecasters compared to EMOS. QRF provides sharp and reliable probabilistic forecasts. At last, classical scoring rules to verify predictive forecasts are completed by the introduction of entropy as a general measure of reliability.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5312701','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5312701"><span id="translatedtitle">Refining Disordered Peptide <span class="hlt">Ensembles</span> with Computational Amide I Spectroscopy: Application to Elastin-Like Peptides</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Reppert, Mike; Roy, Anish R.; Tempkin, Jeremy O. B.; Dinner, Aaron R.; Tokmakoff, Andrei</p> <p>2017-01-01</p> <p>The characterization of intrinsically disordered protein (IDP) <span class="hlt">ensembles</span> is complicated both by inherent heterogeneity and by the fact that many common experimental techniques function poorly when applied to IDPs. For this reason, the development of alternative structural tools for probing IDP <span class="hlt">ensembles</span> has attracted considerable attention. Here we describe our recent work in developing experimental and computational tools for characterizing IDP <span class="hlt">ensembles</span> using Amide I (backbone carbonyl stretch) vibrational spectroscopy. In this approach, the infrared (IR) absorption frequencies of isotope-labeled amide bonds probe their local electrostatic environments and structures. Empirical frequency maps allow us to use this spectroscopic data as a direct experimental test of atomistic structural models. We apply these methods to a family of short elastin-like peptides (ELPs), fragments of the elastin protein <span class="hlt">based</span> around the Pro-Gly turn motif characteristic of the elastomeric segments of the full protein. Using a maximum entropy analysis of experimental spectra on the basis of predicted spectra from <span class="hlt">molecular</span> dynamics (MD) <span class="hlt">ensembles</span>, we find that peptides with Ala or Val sidechains preceding the Pro-Gly turn unit exhibit a stronger tendency toward extended structures than do Gly-Pro-Gly motifs, suggesting an important role for steric interactions in tuning the <span class="hlt">molecular</span> properties of elastin. PMID:27736076</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_17 --> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.9176V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.9176V"><span id="translatedtitle">A probabilistic approach to forecast the uncertainty with <span class="hlt">ensemble</span> spread</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Van Schaeybroeck, Bert; Vannitsem, Stéphane</p> <p>2015-04-01</p> <p>For most purposes the information gathered from an <span class="hlt">ensemble</span> forecast is the <span class="hlt">ensemble</span> mean and its uncertainty. The <span class="hlt">ensemble</span> spread is commonly used as a measure of the uncertainty. We propose a method to assess whether the <span class="hlt">ensemble</span> spread is a good measure of uncertainty and to bring forward an underlying spread-skill relationship. Forecasting the uncertainty should be probabilistic of nature. This implies that, if only the <span class="hlt">ensemble</span> spread is available, a probability density function (PDF) for the uncertainty forecast must be reconstructed <span class="hlt">based</span> on one parameter. Different models are introduced for the composition of such PDFs and evaluated for different spread-error metrics. The uncertainty forecast can then be verified <span class="hlt">based</span> on probabilistic skill scores. For a perfectly reliable forecast the spread-error relationship is strongly heteroscedastic since the error can take a wide range of values, proportional to the <span class="hlt">ensemble</span> spread. This makes a proper statistical assessment of the spread-skill relation intricate. However, it is shown that a logarithmic transformation of both spread and error allows for alleviating the heteroscedasticity. A linear regression analysis can then be performed to check whether the flow-dependent spread is a realistic indicator of the uncertainty and to what extent <span class="hlt">ensemble</span> underdispersion or overdispersion depends on the <span class="hlt">ensemble</span> spread. The methods are tested on the <span class="hlt">ensemble</span> forecast of wind and geopotential height of the European Centre of Medium-range forecasts (ECMWF) over Europe and Africa. A comparison is also made with spread-skill analysis <span class="hlt">based</span> on binning methods.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/12764552','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/12764552"><span id="translatedtitle">PET-<span class="hlt">based</span> <span class="hlt">molecular</span> imaging in neuroscience.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jacobs, A H; Li, H; Winkeler, A; Hilker, R; Knoess, C; Rüger, A; Galldiks, N; Schaller, B; Sobesky, J; Kracht, L; Monfared, P; Klein, M; Vollmar, S; Bauer, B; Wagner, R; Graf, R; Wienhard, K; Herholz, K; Heiss, W D</p> <p>2003-07-01</p> <p>Positron emission tomography (PET) allows non-invasive assessment of physiological, metabolic and <span class="hlt">molecular</span> processes in humans and animals in vivo. Advances in detector technology have led to a considerable improvement in the spatial resolution of PET (1-2 mm), enabling for the first time investigations in small experimental animals such as mice. With the developments in radiochemistry and tracer technology, a variety of endogenously expressed and exogenously introduced genes can be analysed by PET. This opens up the exciting and rapidly evolving field of <span class="hlt">molecular</span> imaging, aiming at the non-invasive localisation of a biological process of interest in normal and diseased cells in animal models and humans in vivo. The main and most intriguing advantage of <span class="hlt">molecular</span> imaging is the kinetic analysis of a given <span class="hlt">molecular</span> event in the same experimental subject over time. This will allow non-invasive characterisation and "phenotyping" of animal models of human disease at various disease stages, under certain pathophysiological stimuli and after therapeutic intervention. The potential broad applications of imaging <span class="hlt">molecular</span> events in vivo lie in the study of cell biology, biochemistry, gene/protein function and regulation, signal transduction, transcriptional regulation and characterisation of transgenic animals. Most importantly, <span class="hlt">molecular</span> imaging will have great implications for the identification of potential <span class="hlt">molecular</span> therapeutic targets, in the development of new treatment strategies, and in their successful implementation into clinical application. Here, the potential impact of <span class="hlt">molecular</span> imaging by PET in applications in neuroscience research with a special focus on neurodegeneration and neuro-oncology is reviewed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5138219','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5138219"><span id="translatedtitle">Genetic Feedback Regulation of Frontal Cortical Neuronal <span class="hlt">Ensembles</span> Through Activity-Dependent Arc Expression and Dopaminergic Input</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Mastwal, Surjeet; Cao, Vania; Wang, Kuan Hong</p> <p>2016-01-01</p> <p>Mental functions involve coordinated activities of specific neuronal <span class="hlt">ensembles</span> that are embedded in complex brain circuits. Aberrant neuronal <span class="hlt">ensemble</span> dynamics is thought to form the neurobiological basis of mental disorders. A major challenge in mental health research is to identify these cellular <span class="hlt">ensembles</span> and determine what <span class="hlt">molecular</span> mechanisms constrain their emergence and consolidation during development and learning. Here, we provide a perspective <span class="hlt">based</span> on recent studies that use activity-dependent gene Arc/Arg3.1 as a cellular marker to identify neuronal <span class="hlt">ensembles</span> and a <span class="hlt">molecular</span> probe to modulate circuit functions. These studies have demonstrated that the transcription of Arc is activated in selective groups of frontal cortical neurons in response to specific behavioral tasks. Arc expression regulates the persistent firing of individual neurons and predicts the consolidation of neuronal <span class="hlt">ensembles</span> during repeated learning. Therefore, the Arc pathway represents a prototypical example of activity-dependent genetic feedback regulation of neuronal <span class="hlt">ensembles</span>. The activation of this pathway in the frontal cortex starts during early postnatal development and requires dopaminergic (DA) input. Conversely, genetic disruption of Arc leads to a hypoactive mesofrontal dopamine circuit and its related cognitive deficit. This mutual interaction suggests an auto-regulatory mechanism to amplify the impact of neuromodulators and activity-regulated genes during postnatal development. Such a mechanism may contribute to the association of mutations in dopamine and Arc pathways with neurodevelopmental psychiatric disorders. As the mesofrontal dopamine circuit shows extensive activity-dependent developmental plasticity, activity-guided modulation of DA projections or Arc <span class="hlt">ensembles</span> during development may help to repair circuit deficits related to neuropsychiatric disorders. PMID:27999532</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27999532','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27999532"><span id="translatedtitle">Genetic Feedback Regulation of Frontal Cortical Neuronal <span class="hlt">Ensembles</span> Through Activity-Dependent Arc Expression and Dopaminergic Input.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Mastwal, Surjeet; Cao, Vania; Wang, Kuan Hong</p> <p>2016-01-01</p> <p>Mental functions involve coordinated activities of specific neuronal <span class="hlt">ensembles</span> that are embedded in complex brain circuits. Aberrant neuronal <span class="hlt">ensemble</span> dynamics is thought to form the neurobiological basis of mental disorders. A major challenge in mental health research is to identify these cellular <span class="hlt">ensembles</span> and determine what <span class="hlt">molecular</span> mechanisms constrain their emergence and consolidation during development and learning. Here, we provide a perspective <span class="hlt">based</span> on recent studies that use activity-dependent gene Arc/Arg3.1 as a cellular marker to identify neuronal <span class="hlt">ensembles</span> and a <span class="hlt">molecular</span> probe to modulate circuit functions. These studies have demonstrated that the transcription of Arc is activated in selective groups of frontal cortical neurons in response to specific behavioral tasks. Arc expression regulates the persistent firing of individual neurons and predicts the consolidation of neuronal <span class="hlt">ensembles</span> during repeated learning. Therefore, the Arc pathway represents a prototypical example of activity-dependent genetic feedback regulation of neuronal <span class="hlt">ensembles</span>. The activation of this pathway in the frontal cortex starts during early postnatal development and requires dopaminergic (DA) input. Conversely, genetic disruption of Arc leads to a hypoactive mesofrontal dopamine circuit and its related cognitive deficit. This mutual interaction suggests an auto-regulatory mechanism to amplify the impact of neuromodulators and activity-regulated genes during postnatal development. Such a mechanism may contribute to the association of mutations in dopamine and Arc pathways with neurodevelopmental psychiatric disorders. As the mesofrontal dopamine circuit shows extensive activity-dependent developmental plasticity, activity-guided modulation of DA projections or Arc <span class="hlt">ensembles</span> during development may help to repair circuit deficits related to neuropsychiatric disorders.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4415763','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4415763"><span id="translatedtitle">A Bayesian <span class="hlt">Ensemble</span> Approach for Epidemiological Projections</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Lindström, Tom; Tildesley, Michael; Webb, Colleen</p> <p>2015-01-01</p> <p>Mathematical models are powerful tools for epidemiology and can be used to compare control actions. However, different models and model parameterizations may provide different prediction of outcomes. In other fields of research, <span class="hlt">ensemble</span> modeling has been used to combine multiple projections. We explore the possibility of applying such methods to epidemiology by adapting Bayesian techniques developed for climate forecasting. We exemplify the implementation with single model <span class="hlt">ensembles</span> <span class="hlt">based</span> on different parameterizations of the Warwick model run for the 2001 United Kingdom foot and mouth disease outbreak and compare the efficacy of different control actions. This allows us to investigate the effect that discrepancy among projections <span class="hlt">based</span> on different modeling assumptions has on the <span class="hlt">ensemble</span> prediction. A sensitivity analysis showed that the choice of prior can have a pronounced effect on the posterior estimates of quantities of interest, in particular for <span class="hlt">ensembles</span> with large discrepancy among projections. However, by using a hierarchical extension of the method we show that prior sensitivity can be circumvented. We further extend the method to include a priori beliefs about different modeling assumptions and demonstrate that the effect of this can have different consequences depending on the discrepancy among projections. We propose that the method is a promising analytical tool for <span class="hlt">ensemble</span> modeling of disease outbreaks. PMID:25927892</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22978601','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22978601"><span id="translatedtitle">Multiscale macromolecular simulation: role of evolving <span class="hlt">ensembles</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Singharoy, A; Joshi, H; Ortoleva, P J</p> <p>2012-10-22</p> <p>Multiscale analysis provides an algorithm for the efficient simulation of macromolecular assemblies. This algorithm involves the coevolution of a quasiequilibrium probability density of atomic configurations and the Langevin dynamics of spatial coarse-grained variables denoted order parameters (OPs) characterizing nanoscale system features. In practice, implementation of the probability density involves the generation of constant OP <span class="hlt">ensembles</span> of atomic configurations. Such <span class="hlt">ensembles</span> are used to construct thermal forces and diffusion factors that mediate the stochastic OP dynamics. Generation of all-atom <span class="hlt">ensembles</span> at every Langevin time step is computationally expensive. Here, multiscale computation for macromolecular systems is made more efficient by a method that self-consistently folds in <span class="hlt">ensembles</span> of all-atom configurations constructed in an earlier step, history, of the Langevin evolution. This procedure accounts for the temporal evolution of these <span class="hlt">ensembles</span>, accurately providing thermal forces and diffusions. It is shown that efficiency and accuracy of the OP-<span class="hlt">based</span> simulations is increased via the integration of this historical information. Accuracy improves with the square root of the number of historical timesteps included in the calculation. As a result, CPU usage can be decreased by a factor of 3-8 without loss of accuracy. The algorithm is implemented into our existing force-field <span class="hlt">based</span> multiscale simulation platform and demonstrated via the structural dynamics of viral capsomers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/919456','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/919456"><span id="translatedtitle">Marking up lattice QCD configurations and <span class="hlt">ensembles</span></span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>P.Coddington; B.Joo; C.M.Maynard; D.Pleiter; T.Yoshie</p> <p>2007-10-01</p> <p>QCDml is an XML-<span class="hlt">based</span> markup language designed for sharing QCD configurations and <span class="hlt">ensembles</span> world-wide via the International Lattice Data Grid (ILDG). <span class="hlt">Based</span> on the latest release, we present key ingredients of the QCDml in order to provide some starting points for colleagues in this community to markup valuable configurations and submit them to the ILDG.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ClDy...43.1303A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ClDy...43.1303A"><span id="translatedtitle">Development of an artificial neural network <span class="hlt">based</span> multi-model <span class="hlt">ensemble</span> to estimate the northeast monsoon rainfall over south peninsular India: an application of extreme learning machine</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Acharya, Nachiketa; Shrivastava, Nitin Anand; Panigrahi, B. K.; Mohanty, U. C.</p> <p>2014-09-01</p> <p>The south peninsular part of India gets maximum amount of rainfall during the northeast monsoon (NEM) season [October to November (OND)] which is the primary source of water for the agricultural activities in this region. A nonlinear method viz., Extreme learning machine (ELM) has been employed on general circulation model (GCM) products to make the multi-model <span class="hlt">ensemble</span> (MME) <span class="hlt">based</span> estimation of NEM rainfall (NEMR). The ELM is basically is an improved learning algorithm for the single feed-forward neural network (SLFN) architecture. The 27 year (1982-2008) lead-1 (using initial conditions of September for forecasting the mean rainfall of OND) hindcast runs (1982-2008) from seven GCM has been used to make MME. The improvement of the proposed method with respect to other regular MME (simple arithmetic mean of GCMs (EM) and singular value decomposition <span class="hlt">based</span> multiple linear regressions <span class="hlt">based</span> MME) has been assessed through several skill metrics like Spread distribution, multiplicative bias, prediction errors, the yield of prediction, Pearson's and Kendal's correlation coefficient and Wilmort's index of agreement. The efficiency of ELM estimated rainfall is established by all the stated skill scores. The performance of ELM in extreme NEMR years, out of which 4 years are characterized by deficit rainfall and 5 years are identified as excess, is also examined. It is found that the ELM could expeditiously capture these extremes reasonably well as compared to the other MME approaches.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014PhDT........20M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014PhDT........20M"><span id="translatedtitle">Primary structure and solution conditions determine conformational <span class="hlt">ensemble</span> properties of intrinsically disordered proteins</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mao, Hsuan-Han Alberto</p> <p></p> <p>Intrinsically disordered proteins (IDPs) are a class of proteins that do not exhibit well-defined three-dimensional structures. The absence of structure is intrinsic to their amino acid sequences, which are characterized by low hydrophobicity and high net charge per residue compared to folded proteins. Contradicting the classic structure-function paradigm, IDPs are capable of interacting with high specificity and affinity, often acquiring order in complex with protein and nucleic acid binding partners. This phenomenon is evident during cellular activities involving IDPs, which include transcriptional and translational regulation, cell cycle control, signal transduction, <span class="hlt">molecular</span> assembly, and <span class="hlt">molecular</span> recognition. Although approximately 30% of eukaryotic proteomes are intrinsically disordered, the nature of IDP conformational <span class="hlt">ensembles</span> remains unclear. In this dissertation, we describe relationships connecting characteristics of IDP conformational <span class="hlt">ensembles</span> to their primary structures and solution conditions. Using <span class="hlt">molecular</span> simulations and fluorescence experiments on a set of <span class="hlt">base</span>-rich IDPs, we find that net charge per residue segregates conformational <span class="hlt">ensembles</span> along a globule-to-coil transition. Speculatively generalizing this result, we propose a phase diagram that predicts an IDP's average size and shape <span class="hlt">based</span> on sequence composition and use it to generate hypotheses for a broad set of intrinsically disordered regions (IDRs). Simulations reveal that acid-rich IDRs, unlike their oppositely charged <span class="hlt">base</span>-rich counterparts, exhibit disordered globular <span class="hlt">ensembles</span> despite intra-chain repulsive electrostatic interactions. This apparent asymmetry is sensitive to simulation parameters for representing alkali and halide salt ions, suggesting that solution conditions modulate IDP conformational <span class="hlt">ensembles</span>. We refine the ion parameters using a calibration procedure that relies exclusively on crystal lattice properties. Simulations with these parameters recover swollen</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AcASn..57..326Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AcASn..57..326Y"><span id="translatedtitle"><span class="hlt">Ensemble</span> Pulsar Time Scale</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yin, D. S.; Gao, Y. P.; Zhao, S. H.</p> <p>2016-05-01</p> <p>Millisecond pulsars can generate another type of time scale that is totally independent of the atomic time scale, because the physical mechanisms of the pulsar time scale and the atomic time scale are quite different from each other. Usually the pulsar timing observational data are not evenly sampled, and the internals between data points range from several hours to more than half a month. What's more, these data sets are sparse. And all these make it difficult to generate an <span class="hlt">ensemble</span> pulsar time scale. Hence, a new algorithm to calculate the <span class="hlt">ensemble</span> pulsar time scale is proposed. Firstly, we use cubic spline interpolation to densify the data set, and make the intervals between data points even. Then, we employ the Vondrak filter to smooth the data set, and get rid of high-frequency noise, finally adopt the weighted average method to generate the <span class="hlt">ensemble</span> pulsar time scale. The pulsar timing residuals represent clock difference between the pulsar time and atomic time, and the high precision pulsar timing data mean the clock difference measurement between the pulsar time and atomic time with a high signal to noise ratio, which is fundamental to generate pulsar time. We use the latest released NANOGRAV (North American Nanohertz Observatory for Gravitational Waves) 9-year data set to generate the <span class="hlt">ensemble</span> pulsar time scale. This data set is from the newest NANOGRAV data release, which includes 9-year observational data of 37 millisecond pulsars using the 100-meter Green Bank telescope and 305-meter Arecibo telescope. We find that the algorithm used in this paper can lower the influence caused by noises in timing residuals, and improve long-term stability of pulsar time. Results show that the long-term (> 1 yr) frequency stability of the pulsar time is better than 3.4×10-15.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA624934','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA624934"><span id="translatedtitle"><span class="hlt">Molecular</span> Orbital <span class="hlt">Based</span> Design Guidelines for Hypergolic Energetic Ionic Liquids</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2015-01-01</p> <p>Journal Article 3. DATES COVERED (From - To) October 2013- December 2013 4. TITLE AND SUBTITLE <span class="hlt">Molecular</span> Orbital <span class="hlt">Based</span> Design Guidelines for Hypergolic... orbitals (HOMO) of the anions for a series of ionic liquids and the lowest occupied <span class="hlt">molecular</span> orbital (LUMO) of HNO3, and variation in the computed...code) 661-525-5657 Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. 239.18 DOI: 10.1002/prep.201400087 <span class="hlt">Molecular</span> Orbital <span class="hlt">Based</span> Design</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AMTD....8..759L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AMTD....8..759L"><span id="translatedtitle">Quantifying residual ionospheric errors in GNSS radio occultation bending angles <span class="hlt">based</span> on <span class="hlt">ensembles</span> of profiles from end-to-end simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, C. L.; Kirchengast, G.; Zhang, K.; Norman, R.; Li, Y.; Zhang, S. C.; Fritzer, J.; Schwaerz, M.; Wu, S. Q.; Tan, Z. X.</p> <p>2015-01-01</p> <p>The radio occultation (RO) technique using signals from the Global Navigation Satellite System (GNSS), in particular from the Global Positioning System (GPS) so far, is meanwhile widely used to observe the atmosphere for applications such as numerical weather prediction and global climate monitoring. The ionosphere is a major error source in RO measurements at stratospheric altitudes and a linear ionospheric correction of dual-frequency RO bending angles is commonly used to remove the first-order ionospheric effect. However, the residual ionopheric error (RIE) can still be significant so that it needs to be further mitigated for high accuracy applications, especially above about 30 km altitude where the RIE is most relevant compared to the magnitude of the neutral atmospheric bending angle. Quantification and careful analyses for better understanding of the RIE is therefore important towards enabling benchmark-quality stratospheric RO retrievals. Here we present such an analysis of bending angle RIEs covering the stratosphere and mesosphere, using quasi-realistic end-to-end simulations for a full-day <span class="hlt">ensemble</span> of RO events. <span class="hlt">Based</span> on the <span class="hlt">ensemble</span> simulations we assessed the variation of bending angle RIEs, both biases and SDs, with solar activity, latitudinal region, and with or without the assumption of ionospheric spherical symmetry and of co-existing observing system errors. We find that the bending angle RIE biases in the upper stratosphere and mesosphere, and in all latitudinal zones from low- to high-latitudes, have a clear negative tendency and a magnitude increasing with solar activity, in line with recent empirical studies <span class="hlt">based</span> on real RO data. The maximum RIE biases are found at low latitudes during daytime, where they amount to with in -0.03 to -0.05 μrad, the smallest at high latitudes (0 to -0.01 μrad; quiet space weather and winter conditions). Ionospheric spherical symmetry or asymmetries about the RO event location have only a minor influence on</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AMT.....8.2999L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AMT.....8.2999L"><span id="translatedtitle">Quantifying residual ionospheric errors in GNSS radio occultation bending angles <span class="hlt">based</span> on <span class="hlt">ensembles</span> of profiles from end-to-end simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, C. L.; Kirchengast, G.; Zhang, K.; Norman, R.; Li, Y.; Zhang, S. C.; Fritzer, J.; Schwaerz, M.; Wu, S. Q.; Tan, Z. X.</p> <p>2015-07-01</p> <p>The radio occultation (RO) technique using signals from the Global Navigation Satellite System (GNSS), in particular from the Global Positioning System (GPS) so far, is currently widely used to observe the atmosphere for applications such as numerical weather prediction and global climate monitoring. The ionosphere is a major error source in RO measurements at stratospheric altitudes, and a linear ionospheric correction of dual-frequency RO bending angles is commonly used to remove the first-order ionospheric effect. However, the residual ionospheric error (RIE) can still be significant so that it needs to be further mitigated for high-accuracy applications, especially above about 30 km altitude where the RIE is most relevant compared to the magnitude of the neutral atmospheric bending angle. Quantification and careful analyses for better understanding of the RIE is therefore important for enabling benchmark-quality stratospheric RO retrievals. Here we present such an analysis of bending angle RIEs covering the stratosphere and mesosphere, using quasi-realistic end-to-end simulations for a full-day <span class="hlt">ensemble</span> of RO events. <span class="hlt">Based</span> on the <span class="hlt">ensemble</span> simulations we assessed the variation of bending angle RIEs, both biases and standard deviations, with solar activity, latitudinal region and with or without the assumption of ionospheric spherical symmetry and co-existing observing system errors. We find that the bending angle RIE biases in the upper stratosphere and mesosphere, and in all latitudinal zones from low to high latitudes, have a clear negative tendency and a magnitude increasing with solar activity, which is in line with recent empirical studies <span class="hlt">based</span> on real RO data although we find smaller bias magnitudes, deserving further study in the future. The maximum RIE biases are found at low latitudes during daytime, where they amount to within -0.03 to -0.05 μrad, the smallest at high latitudes (0 to -0.01 μrad; quiet space weather and winter conditions</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28301770','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28301770"><span id="translatedtitle">Imaging and Optically Manipulating Neuronal <span class="hlt">Ensembles</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Carrillo-Reid, Luis; Yang, Weijian; Kang Miller, Jae-Eun; Peterka, Darcy S; Yuste, Rafael</p> <p>2017-03-15</p> <p>The neural code that relates the firing of neurons to the generation of behavior and mental states must be implemented by spatiotemporal patterns of activity across neuronal populations. These patterns engage selective groups of neurons, called neuronal <span class="hlt">ensembles</span>, which are emergent building blocks of neural circuits. We review optical and computational methods, <span class="hlt">based</span> on two-photon calcium imaging and two-photon optogenetics, to detect, characterize, and manipulate neuronal <span class="hlt">ensembles</span> in three dimensions. We review data using these methods in the mammalian cortex that demonstrate the existence of neuronal <span class="hlt">ensembles</span> in the spontaneous and evoked cortical activity in vitro and in vivo. Moreover, two-photon optogenetics enable the possibility of artificially imprinting neuronal <span class="hlt">ensembles</span> into awake, behaving animals and of later recalling those <span class="hlt">ensembles</span> selectively by stimulating individual cells. These methods could enable deciphering the neural code and also be used to understand the pathophysiology of neurological and mental diseases and design novel therapies. Expected final online publication date for the Annual Review of Biophysics Volume 46 is May 20, 2017. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20136746','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20136746"><span id="translatedtitle"><span class="hlt">Ensemble</span> habitat mapping of invasive plant species.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Stohlgren, Thomas J; Ma, Peter; Kumar, Sunil; Rocca, Monique; Morisette, Jeffrey T; Jarnevich, Catherine S; Benson, Nate</p> <p>2010-02-01</p> <p><span class="hlt">Ensemble</span> species distribution models combine the strengths of several species environmental matching models, while minimizing the weakness of any one model. <span class="hlt">Ensemble</span> models may be particularly useful in risk analysis of recently arrived, harmful invasive species because species may not yet have spread to all suitable habitats, leaving species-environment relationships difficult to determine. We tested five individual models (logistic regression, boosted regression trees, random forest, multivariate adaptive regression splines (MARS), and maximum entropy model or Maxent) and <span class="hlt">ensemble</span> modeling for selected nonnative plant species in Yellowstone and Grand Teton National Parks, Wyoming; Sequoia and Kings Canyon National Parks, California, and areas of interior Alaska. The models are <span class="hlt">based</span> on field data provided by the park staffs, combined with topographic, climatic, and vegetation predictors derived from satellite data. For the four invasive plant species tested, <span class="hlt">ensemble</span> models were the only models that ranked in the top three models for both field validation and test data. <span class="hlt">Ensemble</span> models may be more robust than individual species-environment matching models for risk analysis.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70035550','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70035550"><span id="translatedtitle"><span class="hlt">Ensemble</span> habitat mapping of invasive plant species</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Stohlgren, T.J.; Ma, P.; Kumar, S.; Rocca, M.; Morisette, J.T.; Jarnevich, C.S.; Benson, N.</p> <p>2010-01-01</p> <p><span class="hlt">Ensemble</span> species distribution models combine the strengths of several species environmental matching models, while minimizing the weakness of any one model. <span class="hlt">Ensemble</span> models may be particularly useful in risk analysis of recently arrived, harmful invasive species because species may not yet have spread to all suitable habitats, leaving species-environment relationships difficult to determine. We tested five individual models (logistic regression, boosted regression trees, random forest, multivariate adaptive regression splines (MARS), and maximum entropy model or Maxent) and <span class="hlt">ensemble</span> modeling for selected nonnative plant species in Yellowstone and Grand Teton National Parks, Wyoming; Sequoia and Kings Canyon National Parks, California, and areas of interior Alaska. The models are <span class="hlt">based</span> on field data provided by the park staffs, combined with topographic, climatic, and vegetation predictors derived from satellite data. For the four invasive plant species tested, <span class="hlt">ensemble</span> models were the only models that ranked in the top three models for both field validation and test data. <span class="hlt">Ensemble</span> models may be more robust than individual species-environment matching models for risk analysis. ?? 2010 Society for Risk Analysis.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA574591','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA574591"><span id="translatedtitle"><span class="hlt">Ensemble</span> Data Assimilation and Predictability of Tropical Cyclones</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2012-09-30</p> <p>on comparing and coupling the <span class="hlt">ensemble</span> and variational data assimilation methods for tropical cyclone applications. Mr. Melhauser, who started to work...understanding of tropical cyclone predictability and further developed <span class="hlt">ensemble-based</span> data assimilation methods for tropical cyclones. Now that we have</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA597758','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA597758"><span id="translatedtitle"><span class="hlt">Ensemble</span> Data Assimilation and Predictability of Tropical Cyclones</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2013-09-30</p> <p>comparing and coupling the <span class="hlt">ensemble</span> and variational data assimilation methods for tropical cyclone applications using past field campaign observations...understanding of tropical cyclone predictability and further developed <span class="hlt">ensemble-based</span> data assimilation methods for tropical cyclones. Now that we have</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://eric.ed.gov/?q=neural+AND+networks&pg=2&id=ED518411','ERIC'); return false;" href="http://eric.ed.gov/?q=neural+AND+networks&pg=2&id=ED518411"><span id="translatedtitle">Competitive Learning Neural Network <span class="hlt">Ensemble</span> Weighted by Predicted Performance</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Ye, Qiang</p> <p>2010-01-01</p> <p><span class="hlt">Ensemble</span> approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among <span class="hlt">base</span> classifiers promotes <span class="hlt">ensemble</span> performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/15006172','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/15006172"><span id="translatedtitle">Creating <span class="hlt">Ensembles</span> of Decision Trees Through Sampling</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Kamath,C; Cantu-Paz, E</p> <p>2001-07-26</p> <p>Recent work in classification indicates that significant improvements in accuracy can be obtained by growing an <span class="hlt">ensemble</span> of classifiers and having them vote for the most popular class. This paper focuses on <span class="hlt">ensembles</span> of decision trees that are created with a randomized procedure <span class="hlt">based</span> on sampling. Randomization can be introduced by using random samples of the training data (as in bagging or boosting) and running a conventional tree-building algorithm, or by randomizing the induction algorithm itself. The objective of this paper is to describe the first experiences with a novel randomized tree induction method that uses a sub-sample of instances at a node to determine the split. The empirical results show that <span class="hlt">ensembles</span> generated using this approach yield results that are competitive in accuracy and superior in computational cost to boosting and bagging.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_18 --> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24580576','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24580576"><span id="translatedtitle">Cavity cooling of an <span class="hlt">ensemble</span> spin system.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wood, Christopher J; Borneman, Troy W; Cory, David G</p> <p>2014-02-07</p> <p>We describe how sideband cooling techniques may be applied to large spin <span class="hlt">ensembles</span> in magnetic resonance. Using the Tavis-Cummings model in the presence of a Rabi drive, we solve a Markovian master equation describing the joint spin-cavity dynamics to derive cooling rates as a function of <span class="hlt">ensemble</span> size. Our calculations indicate that the coupled angular momentum subspaces of a spin <span class="hlt">ensemble</span> containing roughly 10(11) electron spins may be polarized in a time many orders of magnitude shorter than the typical thermal relaxation time. The described techniques should permit efficient removal of entropy for spin-<span class="hlt">based</span> quantum information processors and fast polarization of spin samples. The proposed application of a standard technique in quantum optics to magnetic resonance also serves to reinforce the connection between the two fields, which has recently begun to be explored in further detail due to the development of hybrid designs for manufacturing noise-resilient quantum devices.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3680205','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3680205"><span id="translatedtitle">Optimized gold nanoshell <span class="hlt">ensembles</span> for biomedical applications</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p></p> <p>2013-01-01</p> <p>We theoretically study the properties of the optimal size distribution in the <span class="hlt">ensemble</span> of hollow gold nanoshells (HGNs) that exhibits the best performance at in vivo biomedical applications. For the first time, to the best of our knowledge, we analyze the dependence of the optimal geometric means of the nanoshells’ thicknesses and core radii on the excitation wavelength and the type of human tissue, while assuming lognormal fit to the size distribution in a real HGN <span class="hlt">ensemble</span>. Regardless of the tissue type, short-wavelength, near-infrared lasers are found to be the most effective in both absorption- and scattering-<span class="hlt">based</span> applications. We derive approximate analytical expressions enabling one to readily estimate the parameters of optimal distribution for which an HGN <span class="hlt">ensemble</span> exhibits the maximum efficiency of absorption or scattering inside a human tissue irradiated by a near-infrared laser. PMID:23537206</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23537206','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23537206"><span id="translatedtitle">Optimized gold nanoshell <span class="hlt">ensembles</span> for biomedical applications.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sikdar, Debabrata; Rukhlenko, Ivan D; Cheng, Wenlong; Premaratne, Malin</p> <p>2013-03-28</p> <p>: We theoretically study the properties of the optimal size distribution in the <span class="hlt">ensemble</span> of hollow gold nanoshells (HGNs) that exhibits the best performance at in vivo biomedical applications. For the first time, to the best of our knowledge, we analyze the dependence of the optimal geometric means of the nanoshells' thicknesses and core radii on the excitation wavelength and the type of human tissue, while assuming lognormal fit to the size distribution in a real HGN <span class="hlt">ensemble</span>. Regardless of the tissue type, short-wavelength, near-infrared lasers are found to be the most effective in both absorption- and scattering-<span class="hlt">based</span> applications. We derive approximate analytical expressions enabling one to readily estimate the parameters of optimal distribution for which an HGN <span class="hlt">ensemble</span> exhibits the maximum efficiency of absorption or scattering inside a human tissue irradiated by a near-infrared laser.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/20857669','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/20857669"><span id="translatedtitle">Quantum measurement of a mesoscopic spin <span class="hlt">ensemble</span></span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Giedke, G.; Taylor, J. M.; Lukin, M. D.; D'Alessandro, D.; Imamoglu, A.</p> <p>2006-09-15</p> <p>We describe a method for precise estimation of the polarization of a mesoscopic spin <span class="hlt">ensemble</span> by using its coupling to a single two-level system. Our approach requires a minimal number of measurements on the two-level system for a given measurement precision. We consider the application of this method to the case of nuclear-spin <span class="hlt">ensemble</span> defined by a single electron-charged quantum dot: we show that decreasing the electron spin dephasing due to nuclei and increasing the fidelity of nuclear-spin-<span class="hlt">based</span> quantum memory could be within the reach of present day experiments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22159069','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22159069"><span id="translatedtitle">Optical materials <span class="hlt">based</span> on <span class="hlt">molecular</span> nanoparticles.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Patra, A; Chandaluri, Ch G; Radhakrishnan, T P</p> <p>2012-01-21</p> <p>A major part of contemporary nanomaterials research is focused on metal and semiconductor nanoparticles, constituted of extended lattices of atoms or ions. <span class="hlt">Molecular</span> nanoparticles assembled from small molecules through non-covalent interactions are relatively less explored but equally fascinating materials. Their unique and versatile characteristics have attracted considerable attention in recent years, establishing their identity and status as a novel class of nanomaterials. Optical characteristics of <span class="hlt">molecular</span> nanoparticles capture the essence of their nanoscale features and form the basis of a variety of applications. This review describes the advances made in the field of fabrication of <span class="hlt">molecular</span> nanoparticles, the wide spectrum of their optical and nonlinear optical characteristics and explorations of the potential applications that exploit their unique optical attributes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27085223','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27085223"><span id="translatedtitle">Logic circuits <span class="hlt">based</span> on <span class="hlt">molecular</span> spider systems.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Mo, Dandan; Lakin, Matthew R; Stefanovic, Darko</p> <p>2016-08-01</p> <p>Spatial locality brings the advantages of computation speed-up and sequence reuse to <span class="hlt">molecular</span> computing. In particular, <span class="hlt">molecular</span> walkers that undergo localized reactions are of interest for implementing logic computations at the nanoscale. We use <span class="hlt">molecular</span> spider walkers to implement logic circuits. We develop an extended multi-spider model with a dynamic environment wherein signal transmission is triggered via localized reactions, and use this model to implement three basic gates (AND, OR, NOT) and a cascading mechanism. We develop an algorithm to automatically generate the layout of the circuit. We use a kinetic Monte Carlo algorithm to simulate circuit computations, and we analyze circuit complexity: our design scales linearly with formula size and has a logarithmic time complexity.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/5206885','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/5206885"><span id="translatedtitle">Forecast of iceberg <span class="hlt">ensemble</span> drift</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>El-Tahan, M.S.; El-Tahan, H.W.; Venkatesh, S.</p> <p>1983-05-01</p> <p>The objectives of the study are to gain a better understanding of the characteristics of iceberg motion and the factors controlling iceberg drift, and to develop an iceberg <span class="hlt">ensemble</span> drift forecast system to be operated by the Canadian Atmospheric Environment Service. An extensive review of field and theoretical studies on iceberg behaviour, and the factors controlling iceberg motion has been carried out. Long term and short term behaviour of icebergs are critically examined. A quantitative assessment of the effects of the factors controlling iceberg motion is presented. The study indicated that wind and currents are the primary driving forces. Coriolis Force and ocean surface slope also have significant effects. As for waves, only the higher waves have a significant effect. Iceberg drift is also affected by iceberg size characteristics. <span class="hlt">Based</span> on the findings of the study a comprehensive computerized forecast system to predict the drift of iceberg <span class="hlt">ensembles</span> off Canada's east coast has been designed. The expected accuracy of the forecast system is discussed and recommendations are made for future improvements to the system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AdAtS..34...66Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AdAtS..34...66Y"><span id="translatedtitle">Impact of coastal radar observability on the forecast of the track and rainfall of Typhoon Morakot (2009) using WRF-<span class="hlt">based</span> <span class="hlt">ensemble</span> Kalman filter data assimilation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yue, Jian; Meng, Zhiyong; Yu, Cheng-Ku; Cheng, Lin-Wen</p> <p>2017-01-01</p> <p>This study explored the impact of coastal radar observability on the forecast of the track and rainfall of Typhoon Morakot (2009) using a WRF-<span class="hlt">based</span> <span class="hlt">ensemble</span> Kalman filter (EnKF) data assimilation (DA) system. The results showed that the performance of radar EnKF DA was quite sensitive to the number of radars being assimilated and the DA timing relative to the landfall of the tropical cyclone (TC). It was found that assimilating radial velocity (Vr) data from all the four operational radars during the 6 h immediately before TC landfall was quite important for the track and rainfall forecasts after the TC made landfall. The TC track forecast error could be decreased by about 43% and the 24-h rainfall forecast skill could be almost tripled. Assimilating Vr data from a single radar outperformed the experiment without DA, though with less improvement compared to the multiple-radar DA experiment. Different forecast performances were obtained by assimilating different radars, which was closely related to the first-time wind analysis increment, the location of moisture transport, the quasi-stationary rainband, and the local convergence line. However, only assimilating Vr data when the TC was farther away from making landfall might worsen TC track and rainfall forecasts. Besides, this work also demonstrated that Vr data from multiple radars, instead of a single radar, should be used for verification to obtain a more reliable assessment of the EnKF performance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJBm...60..307S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJBm...60..307S"><span id="translatedtitle">Future projections of labor hours <span class="hlt">based</span> on WBGT for Tokyo and Osaka, Japan, using multi-period <span class="hlt">ensemble</span> dynamical downscale simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Suzuki-Parker, Asuka; Kusaka, Hiroyuki</p> <p>2016-02-01</p> <p>Following the heatstroke prevention guideline by the Ministry of Health, Labor, and Welfare of Japan, "safe hours" for heavy and light labor are estimated <span class="hlt">based</span> on hourly wet-bulb globe temperature (WBGT) obtained from the three-member <span class="hlt">ensemble</span> multi-period (the 2000s, 2030s, 2050s, 2070s, and 2090s) climate projections using dynamical downscaling approach. Our target cities are Tokyo and Osaka, Japan. The results show that most of the current climate daytime hours are "light labor safe,", but these hours are projected to decrease by 30-40 % by the end of the twenty-first century. A 60-80 % reduction is projected for heavy labor hours, resulting in less than 2 hours available for safe performance of heavy labor. The number of "heavy labor restricted days" (days with minimum daytime WBGT exceeding the safe level threshold for heavy labor) is projected to increase from ~5 days in the 2000s to nearly two-thirds of the days in August in the 2090s.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014RaSc...49.1153T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014RaSc...49.1153T"><span id="translatedtitle">An <span class="hlt">ensemble</span> average method to estimate absolute TEC using radio beacon-<span class="hlt">based</span> differential phase measurements: Applicability to regions of large latitudinal gradients in plasma density</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Thampi, Smitha V.; Bagiya, Mala S.; Chakrabarty, D.; Acharya, Y. B.; Yamamoto, M.</p> <p>2014-12-01</p> <p>A GNU Radio Beacon Receiver (GRBR) system for total electron content (TEC) measurements using 150 and 400 MHz transmissions from Low-Earth Orbiting Satellites (LEOS) is fabricated in house and made operational at Ahmedabad (23.04°N, 72.54°E geographic, dip latitude 17°N) since May 2013. This system receives the 150 and 400 MHz transmissions from high-inclination LEOS. The first few days of observations are presented in this work to bring out the efficacy of an <span class="hlt">ensemble</span> average method to convert the relative TECs to absolute TECs. This method is a modified version of the differential Doppler-<span class="hlt">based</span> method proposed by de Mendonca (1962) and suitable even for ionospheric regions with large spatial gradients. Comparison of TECs derived from a collocated GPS receiver shows that the absolute TECs estimated by this method are reliable estimates over regions with large spatial gradient. This method is useful even when only one receiving station is available. The differences between these observations are discussed to bring out the importance of the spatial differences between the ionospheric pierce points of these satellites. A few examples of the latitudinal variation of TEC during different local times using GRBR measurements are also presented, which demonstrates the potential of radio beacon measurements in capturing the large-scale plasma transport processes in the low-latitude ionosphere.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011IJTPE.131...29K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011IJTPE.131...29K"><span id="translatedtitle">Evaluation of Relation between Distance and Insolation Fluctuation Independence <span class="hlt">based</span> on Coherence and <span class="hlt">Ensemble</span> Average of Insolation Fluctuations at Two Points</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kato, Takeyoshi; Inoue, Takato; Suzuoki, Yasuo</p> <p></p> <p>Power output fluctuation of high penetration photovoltaic power generation systems (PVSs) may cause negative impacts on the load frequency control (LFC) of an electric power utility. For the cost-effective mitigation, the proper evaluation of apparent electricity demand fluctuation is important, taking the power output of PVSs into account as a negative demand. If the actual power output patterns are independent among several points, the standard deviation (STD) of total power output fluctuation of PVSs located in several points can be estimated <span class="hlt">based</span> on the addition theorem of variance. Moreover, the central limit theorem may be applied if the probability distribution of insolation fluctuation is the same among several points. As a fundamental study to apply the stochastic methods, this study evaluates the following two factors to determine the distance between two points with which the insolation patterns of two points can be considered as independent: 1) the coherence of insolation fluctuation for various combinations of two points with different distances, 2) the correlation diagram of two different STDs, i.e. the STD of <span class="hlt">ensemble</span> average insolation fluctuation observed at two points and the averaged STD of each STD of insolation fluctuation at two points. The results suggest that the insolation fluctuation consisting of the cycles shorter than 30min can be considered as independent if the distance between two points is longer than 5km-10km.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2712746','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2712746"><span id="translatedtitle">sigReannot: an oligo-set re-annotation pipeline <span class="hlt">based</span> on similarities with the <span class="hlt">Ensembl</span> transcripts and Unigene clusters</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Casel, Pierrot; Moreews, François; Lagarrigue, Sandrine; Klopp, Christophe</p> <p>2009-01-01</p> <p>Background Microarray is a powerful technology enabling to monitor tens of thousands of genes in a single experiment. Most microarrays are now using oligo-sets. The design of the oligo-nucleotides is time consuming and error prone. Genome wide microarray oligo-sets are designed using as large a set of transcripts as possible in order to monitor as many genes as possible. Depending on the genome sequencing state and on the assembly state the knowledge of the existing transcripts can be very different. This knowledge evolves with the different genome builds and gene builds. Once the design is done the microarrays are often used for several years. The biologists working in EADGENE expressed the need of up-to-dated annotation files for the oligo-sets they share including information about the orthologous genes of model species, the Gene Ontology, the corresponding pathways and the chromosomal location. Results The results of SigReannot on a chicken micro-array used in the EADGENE project compared to the initial annotations show that 23% of the oligo-nucleotide gene annotations were not confirmed, 2% were modified and 1% were added. The interest of this up-to-date annotation procedure is demonstrated through the analysis of real data previously published. Conclusion SigReannot uses the oligo-nucleotide design procedure criteria to validate the probe-gene link and the <span class="hlt">Ensembl</span> transcripts as reference for annotation. It therefore produces a high quality annotation <span class="hlt">based</span> on reference gene sets. PMID:19615116</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1302921-multilevel-ensemble-kalman-filtering','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1302921-multilevel-ensemble-kalman-filtering"><span id="translatedtitle">Multilevel <span class="hlt">ensemble</span> Kalman filtering</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Hoel, Hakon; Law, Kody J. H.; Tempone, Raul</p> <p>2016-06-14</p> <p>This study embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the <span class="hlt">ensemble</span> Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. Finally, the resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA616716','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA616716"><span id="translatedtitle">ESPC Coupled Global <span class="hlt">Ensemble</span> Design</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2014-09-30</p> <p>1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. ESPC Coupled Global <span class="hlt">Ensemble</span> Design Justin McLay...range global atmospheric <span class="hlt">ensemble</span> forecasting system using the Navy Global Environmental Model (NAVGEM). Couple NAVGEM to a simple SST model that...SEP 2014 2. REPORT TYPE 3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE ESPC Coupled Global <span class="hlt">Ensemble</span> Design 5a. CONTRACT NUMBER</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5206477','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5206477"><span id="translatedtitle">Determining Cutoff Point of <span class="hlt">Ensemble</span> Trees <span class="hlt">Based</span> on Sample Size in Predicting Clinical Dose with DNA Microarray Data</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Karabulut, Erdem; Alpar, Celal Reha</p> <p>2016-01-01</p> <p>Background/Aim. Evaluating the success of dose prediction <span class="hlt">based</span> on genetic or clinical data has substantially advanced recently. The aim of this study is to predict various clinical dose values from DNA gene expression datasets using data mining techniques. Materials and Methods. Eleven real gene expression datasets containing dose values were included. First, important genes for dose prediction were selected using iterative sure independence screening. Then, the performances of regression trees (RTs), support vector regression (SVR), RT bagging, SVR bagging, and RT boosting were examined. Results. The results demonstrated that a regression-<span class="hlt">based</span> feature selection method substantially reduced the number of irrelevant genes from raw datasets. Overall, the best prediction performance in nine of 11 datasets was achieved using SVR; the second most accurate performance was provided using a gradient-boosting machine (GBM). Conclusion. Analysis of various dose values <span class="hlt">based</span> on microarray gene expression data identified common genes found in our study and the referenced studies. According to our findings, SVR and GBM can be good predictors of dose-gene datasets. Another result of the study was to identify the sample size of n = 25 as a cutoff point for RT bagging to outperform a single RT. PMID:28096893</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/8873992','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/8873992"><span id="translatedtitle">Grand canonical <span class="hlt">ensemble</span> Monte Carlo simulation of the dCpG/proflavine crystal hydrate.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Resat, H; Mezei, M</p> <p>1996-09-01</p> <p>The grand canonical <span class="hlt">ensemble</span> Monte Carlo <span class="hlt">molecular</span> simulation method is used to investigate hydration patterns in the crystal hydrate structure of the dCpG/proflavine intercalated complex. The objective of this study is to show by example that the recently advocated grand canonical <span class="hlt">ensemble</span> simulation is a computationally efficient method for determining the positions of the hydrating water molecules in protein and nucleic acid structures. A detailed <span class="hlt">molecular</span> simulation convergence analysis and an analogous comparison of the theoretical results with experiments clearly show that the grand <span class="hlt">ensemble</span> simulations can be far more advantageous than the comparable canonical <span class="hlt">ensemble</span> simulations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1233585','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1233585"><span id="translatedtitle">Grand canonical <span class="hlt">ensemble</span> Monte Carlo simulation of the dCpG/proflavine crystal hydrate.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Resat, H; Mezei, M</p> <p>1996-01-01</p> <p>The grand canonical <span class="hlt">ensemble</span> Monte Carlo <span class="hlt">molecular</span> simulation method is used to investigate hydration patterns in the crystal hydrate structure of the dCpG/proflavine intercalated complex. The objective of this study is to show by example that the recently advocated grand canonical <span class="hlt">ensemble</span> simulation is a computationally efficient method for determining the positions of the hydrating water molecules in protein and nucleic acid structures. A detailed <span class="hlt">molecular</span> simulation convergence analysis and an analogous comparison of the theoretical results with experiments clearly show that the grand <span class="hlt">ensemble</span> simulations can be far more advantageous than the comparable canonical <span class="hlt">ensemble</span> simulations. Images FIGURE 5 FIGURE 7 PMID:8873992</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24577605','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24577605"><span id="translatedtitle">Unidirectional light-driven <span class="hlt">molecular</span> motors <span class="hlt">based</span> on overcrowded alkenes.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cnossen, Arjen; Browne, Wesley R; Feringa, Ben L</p> <p>2014-01-01</p> <p>Over the last two decades, interest in nanotechnology has led to the design and synthesis of a toolbox of nanoscale versions of macroscopic devices and components. In <span class="hlt">molecular</span> nanotechnology, linear motors <span class="hlt">based</span> on rotaxanes and rotary motors <span class="hlt">based</span> on overcrowded alkenes are particularly promising for performing work at the nanoscale. In this chapter, progress on light-driven <span class="hlt">molecular</span> motors <span class="hlt">based</span> on overcrowded alkenes is reviewed. Both the so-called first and second generation <span class="hlt">molecular</span> motors are discussed, as well as their potential applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/16080726','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/16080726"><span id="translatedtitle">Quantitative <span class="hlt">molecular</span> thermochemistry <span class="hlt">based</span> on path integrals.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Glaesemann, Kurt R; Fried, Laurence E</p> <p>2005-07-15</p> <p>The calculation of thermochemical data requires accurate <span class="hlt">molecular</span> energies and heat capacities. Traditional methods rely upon the standard harmonic normal-mode analysis to calculate the vibrational and rotational contributions. We utilize path-integral Monte Carlo for going beyond the harmonic analysis and to calculate the vibrational and rotational contributions to ab initio energies. This is an application and an extension of a method previously developed in our group [J. Chem. Phys. 118, 1596 (2003)].</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA588956','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA588956"><span id="translatedtitle"><span class="hlt">Molecular</span> and Clinical <span class="hlt">Based</span> Cardiovascular Care Program</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2007-01-01</p> <p>pathogenesis of coronary artery, peripheral vascular , and cerebrovascular disease . Impairment of endothelial function has been demonstrated after high...cardio’Va~ ct•b.r disease , Subsequently, ultrnlow-fat diets (:;;1.0% of totlll caloric intake as fat), emphasi?.in,g the amount ra.thcr th<•.o the...cardiovascular disease at the <span class="hlt">molecular</span> disease stage and identify biomarkers predictive of sub- clinical CVD; and 3) Relate genomic/proteomic changes to the</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_19 --> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3159309','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3159309"><span id="translatedtitle"><span class="hlt">Molecular</span> <span class="hlt">Bases</span> of Cutaneous and Uveal Melanomas</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Gaudi, Sudeep; Messina, Jane L.</p> <p>2011-01-01</p> <p>Intensive research in recent years has begun to unlock the mysteries surrounding the <span class="hlt">molecular</span> pathogenesis of melanoma, the deadliest of skin cancers. The high-penetrance, low-frequency susceptibility gene CDKN2A produces tumor suppressor proteins that function in concert with p53 and retinoblastoma protein to thwart melanomagenesis. Aberrant CDKN2A gene products have been implicated in a great many cases of familial cutaneous melanoma. Sporadic cases, on the other hand, often involve constitutive signal transduction along the mitogen-activated protein kinase (MAPK) pathway, with particular focus falling upon mutated RAS and RAF protooncogenes. The proliferative effects of the MAPK pathway may be complemented by the antiapoptotic signals of the PI3K/AKT pathway. After skin, melanoma most commonly affects the eye. Data for the constitutive activation of the MAPK pathway in uveal melanoma exists as well, however, not through mutations of RAS and RAF. Rather, evidence implicates the proto-oncogene GNAQ. In the following discussion, we review the major <span class="hlt">molecular</span> pathways implicated in both familial and sporadic cutaneous melanomagenesis, the former accounting for approximately 10% of cases. Additionally, we discuss the <span class="hlt">molecular</span> pathways for which preliminary evidence suggests a role in uveal melanomagenesis. PMID:21876842</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2151381','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2151381"><span id="translatedtitle">Assistive technology and robotic control using motor cortex <span class="hlt">ensemble-based</span> neural interface systems in humans with tetraplegia</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Donoghue, John P; Nurmikko, Arto; Black, Michael; Hochberg, Leigh R</p> <p>2007-01-01</p> <p>This review describes the rationale, early stage development, and initial human application of neural interface systems (NISs) for humans with paralysis. NISs are emerging medical devices designed to allow persons with paralysis to operate assistive technologies or to reanimate muscles <span class="hlt">based</span> upon a command signal that is obtained directly from the brain. Such systems require the development of sensors to detect brain signals, decoders to transform neural activity signals into a useful command, and an interface for the user. We review initial pilot trial results of an NIS that is <span class="hlt">based</span> on an intracortical microelectrode sensor that derives control signals from the motor cortex. We review recent findings showing, first, that neurons engaged by movement intentions persist in motor cortex years after injury or disease to the motor system, and second, that signals derived from motor cortex can be used by persons with paralysis to operate a range of devices. We suggest that, with further development, this form of NIS holds promise as a useful new neurotechnology for those with limited motor function or communication. We also discuss the additional potential for neural sensors to be used in the diagnosis and management of various neurological conditions and as a new way to learn about human brain function. PMID:17272345</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23193252','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23193252"><span id="translatedtitle">Validation of a selective <span class="hlt">ensemble-based</span> classification scheme for myoelectric control using a three-dimensional Fitts' Law test.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Scheme, Erik J; Englehart, Kevin B</p> <p>2013-07-01</p> <p>When controlling a powered upper limb prosthesis it is important not only to know how to move the device, but also when not to move. A novel approach to pattern recognition control, using a selective multiclass one-versus-one classification scheme has been shown to be capable of rejecting unintended motions. This method was shown to outperform other popular classification schemes when presented with muscle contractions that did not correspond to desired actions. In this work, a 3-D Fitts' Law test is proposed as a suitable alternative to using virtual limb environments for evaluating real-time myoelectric control performance. The test is used to compare the selective approach to a state-of-the-art linear discriminant analysis classification <span class="hlt">based</span> scheme. The framework is shown to obey Fitts' Law for both control schemes, producing linear regression fittings with high coefficients of determination (R(2) > 0.936). Additional performance metrics focused on quality of control are discussed and incorporated in the evaluation. Using this framework the selective classification <span class="hlt">based</span> scheme is shown to produce significantly higher efficiency and completion rates, and significantly lower overshoot and stopping distances, with no significant difference in throughput.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4256725','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4256725"><span id="translatedtitle">Current and emerging opportunities for <span class="hlt">molecular</span> simulations in structure-<span class="hlt">based</span> drug design</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Michel, Julien</p> <p>2014-01-01</p> <p>An overview of the current capabilities and limitations of <span class="hlt">molecular</span> simulation of biomolecular complexes in the context of computer-aided drug design is provided. Steady improvements in computer hardware coupled with more refined representations of energetics are leading to a new appreciation of the driving forces of <span class="hlt">molecular</span> recognition. <span class="hlt">Molecular</span> simulations are poised to more frequently guide the interpretation of biophysical measurements of biomolecular complexes. Ligand design strategies emerge from detailed analyses of computed structural <span class="hlt">ensembles</span>. The feasibility of routine applications to ligand optimization problems hinges upon successful extensive large scale validation studies and the development of protocols to intelligently automate computations. PMID:24469595</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JPRS..126...68L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JPRS..126...68L"><span id="translatedtitle">Assimilating leaf area index of three typical types of subtropical forest in China from MODIS time series data <span class="hlt">based</span> on the integrated <span class="hlt">ensemble</span> Kalman filter and PROSAIL model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Xuejian; Mao, Fangjie; Du, Huaqiang; Zhou, Guomo; Xu, Xiaojun; Han, Ning; Sun, Shaobo; Gao, Guolong; Chen, Liang</p> <p>2017-04-01</p> <p>Subtropical forest ecosystems play essential roles in the global carbon cycle and in carbon sequestration functions, which challenge the traditional understanding of the main functional areas of carbon sequestration in the temperate forests of Europe and America. The leaf area index (LAI) is an important biological parameter in the spatiotemporal simulation of the carbon cycle, and it has considerable significance in carbon cycle research. Dynamic retrieval <span class="hlt">based</span> on remote sensing data is an important method with which to obtain large-scale high-accuracy assessments of LAI. This study developed an algorithm for assimilating LAI dynamics <span class="hlt">based</span> on an integrated <span class="hlt">ensemble</span> Kalman filter using MODIS LAI data, MODIS reflectance data, and canopy reflectance data modeled by PROSAIL, for three typical types of subtropical forest (Moso bamboo forest, Lei bamboo forest, and evergreen and deciduous broadleaf forest) in China during 2014-2015. There were some errors of assimilation in winter, because of the bad data quality of the MODIS product. Overall, the assimilated LAI well matched the observed LAI, with R2 of 0.82, 0.93, and 0.87, RMSE of 0.73, 0.49, and 0.42, and aBIAS of 0.50, 0.23, and 0.03 for Moso bamboo forest, Lei bamboo forest, and evergreen and deciduous broadleaf forest, respectively. The algorithm greatly decreased the uncertainty of the MODIS LAI in the growing season and it improved the accuracy of the MODIS LAI. The advantage of the algorithm is its use of biophysical parameters (e.g., measured LAI) in the LAI assimilation, which makes it possible to assimilate long-term MODIS LAI time series data, and to provide high-accuracy LAI data for the study of carbon cycle characteristics in subtropical forest ecosystems.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ERL....10h4013Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ERL....10h4013Z"><span id="translatedtitle">Estimating heat stress from climate-<span class="hlt">based</span> indicators: present-day biases and future spreads in the CMIP5 global climate model <span class="hlt">ensemble</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, Y.; Ducharne, A.; Sultan, B.; Braconnot, P.; Vautard, R.</p> <p>2015-08-01</p> <p>The increased exposure of human populations to heat stress is one of the likely consequences of global warming, and it has detrimental effects on health and labor capacity. Here, we consider the evolution of heat stress under climate change using 21 general circulation models (GCMs). Three heat stress indicators, <span class="hlt">based</span> on both temperature and humidity conditions, are used to investigate present-day model biases and spreads in future climate projections. Present day estimates of heat stress indicators from observational data shows that humid tropical areas tend to experience more frequent heat stress than other regions do, with a total frequency of heat stress 250-300 d yr-1. The most severe heat stress is found in the Sahel and south India. Present-day GCM simulations tend to underestimate heat stress over the tropics due to dry and cold model biases. The model <span class="hlt">based</span> estimates are in better agreement with observation in mid to high latitudes, but this is due to compensating errors in humidity and temperature. The severity of heat stress is projected to increase by the end of the century under climate change scenario RCP8.5, reaching unprecedented levels in some regions compared with observations. An analysis of the different factors contributing to the total spread of projected heat stress shows that spread is primarily driven by the choice of GCMs rather than the choice of indicators, even when the simulated indicators are bias-corrected. This supports the utility of the multi-model <span class="hlt">ensemble</span> approach to assess the impacts of climate change on heat stress.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/22251869','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/22251869"><span id="translatedtitle">Density of states for Gaussian unitary <span class="hlt">ensemble</span>, Gaussian orthogonal <span class="hlt">ensemble</span>, and interpolating <span class="hlt">ensembles</span> through supersymmetric approach</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Shamis, Mira</p> <p>2013-11-15</p> <p>We use the supersymmetric formalism to derive an integral formula for the density of states of the Gaussian Orthogonal <span class="hlt">Ensemble</span>, and then apply saddle-point analysis to give a new derivation of the 1/N-correction to Wigner's law. This extends the work of Disertori on the Gaussian Unitary <span class="hlt">Ensemble</span>. We also apply our method to the interpolating <span class="hlt">ensembles</span> of Mehta–Pandey.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JChPh.143m4111Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JChPh.143m4111Z"><span id="translatedtitle">Transition state <span class="hlt">ensemble</span> optimization for reactions of arbitrary complexity</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zinovjev, Kirill; Tuñón, Iñaki</p> <p>2015-10-01</p> <p>In the present work, we use Variational Transition State Theory (VTST) to develop a practical method for transition state <span class="hlt">ensemble</span> optimization by looking for an optimal hyperplanar dividing surface in a space of meaningful trial collective variables. These might be interatomic distances, angles, electrostatic potentials, etc. Restrained <span class="hlt">molecular</span> dynamics simulations are used to obtain on-the-fly estimates of <span class="hlt">ensemble</span> averages that guide the variations of the hyperplane maximizing the transmission coefficient. A central result of our work is an expression that quantitatively estimates the importance of the coordinates used for the localization of the transition state <span class="hlt">ensemble</span>. Starting from an arbitrarily large set of trial coordinates, one can distinguish those that are indeed essential for the advance of the reaction. This facilitates the use of VTST as a practical theory to study reaction mechanisms of complex processes. The technique was applied to the reaction catalyzed by an isochorismate pyruvate lyase. This reaction involves two simultaneous chemical steps and has a shallow transition state region, making it challenging to define a good reaction coordinate. Nevertheless, the hyperplanar transition state optimized in the space of 18 geometrical coordinates provides a transmission coefficient of 0.8 and a committor histogram well-peaked about 0.5, proving the strength of the method. We have also tested the approach with the study of the NaCl dissociation in aqueous solution, a stringest test for a method <span class="hlt">based</span> on transition state theory. We were able to find essential degrees of freedom consistent with the previous studies and to improve the transmission coefficient with respect to the value obtained using solely the NaCl distance as the reaction coordinate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008JChPh.128w4908P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008JChPh.128w4908P"><span id="translatedtitle">Stochastic dynamics of bionanosystems: Multiscale analysis and specialized <span class="hlt">ensembles</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pankavich, S.; Miao, Y.; Ortoleva, J.; Shreif, Z.; Ortoleva, P.</p> <p>2008-06-01</p> <p>An approach for simulating bionanosystems such as viruses and ribosomes is presented. This calibration-free approach is <span class="hlt">based</span> on an all-atom description for bionanosystems, a universal interatomic force field, and a multiscale perspective. The supramillion-atom nature of these bionanosystems prohibits the use of a direct <span class="hlt">molecular</span> dynamics approach for phenomena such as viral structural transitions or self-assembly that develop over milliseconds or longer. A key element of these multiscale systems is the cross-talk between, and consequent strong coupling of processes over many scales in space and time. Thus, overall nanoscale features of these systems control the relative probability of atomistic fluctuations, while the latter mediate the average forces and diffusion coefficients that induce the dynamics of these nanoscale features. This feedback loop is overlooked in typical coarse-grained methods. We elucidate the role of interscale cross-talk and overcome bionanosystem simulation difficulties with (1) automated construction of order parameters (OPs) describing suprananometer scale structural features, (2) construction of OP-dependent <span class="hlt">ensembles</span> describing the statistical properties of atomistic variables that ultimately contribute to the entropies driving the dynamics of the OPs, and (3) the derivation of a rigorous equation for the stochastic dynamics of the OPs. As the OPs capture hydrodynamic modes in the host medium, ``long-time tails'' in the correlation functions yielding the generalized diffusion coefficients do not emerge. Since the atomic-scale features of the system are treated statistically, several <span class="hlt">ensembles</span> are constructed that reflect various experimental conditions. Attention is paid to the proper use of the Gibbs hypothesized equivalence of long-time and <span class="hlt">ensemble</span> averages to accommodate the varying experimental conditions. The theory provides a basis for a practical, quantitative bionanosystem modeling approach that preserves the cross</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.4328V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.4328V"><span id="translatedtitle">The role of <span class="hlt">ensemble</span> post-processing for modeling the <span class="hlt">ensemble</span> tail</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Van De Vyver, Hans; Van Schaeybroeck, Bert; Vannitsem, Stéphane</p> <p>2016-04-01</p> <p>The past decades the numerical weather prediction community has witnessed a paradigm shift from deterministic to probabilistic forecast and state estimation (Buizza and Leutbecher, 2015; Buizza et al., 2008), in an attempt to quantify the uncertainties associated with initial-condition and model errors. An important benefit of a probabilistic framework is the improved prediction of extreme events. However, one may ask to what extent such model estimates contain information on the occurrence probability of extreme events and how this information can be optimally extracted. Different approaches have been proposed and applied on real-world systems which, <span class="hlt">based</span> on extreme value theory, allow the estimation of extreme-event probabilities conditional on forecasts and state estimates (Ferro, 2007; Friederichs, 2010). Using <span class="hlt">ensemble</span> predictions generated with a model of low dimensionality, a thorough investigation is presented quantifying the change of predictability of extreme events associated with <span class="hlt">ensemble</span> post-processing and other influencing factors including the finite <span class="hlt">ensemble</span> size, lead time and model assumption and the use of different covariates (<span class="hlt">ensemble</span> mean, maximum, spread...) for modeling the tail distribution. Tail modeling is performed by deriving extreme-quantile estimates using peak-over-threshold representation (generalized Pareto distribution) or quantile regression. Common <span class="hlt">ensemble</span> post-processing methods aim to improve mostly the <span class="hlt">ensemble</span> mean and spread of a raw forecast (Van Schaeybroeck and Vannitsem, 2015). Conditional tail modeling, on the other hand, is a post-processing in itself, focusing on the tails only. Therefore, it is unclear how applying <span class="hlt">ensemble</span> post-processing prior to conditional tail modeling impacts the skill of extreme-event predictions. This work is investigating this question in details. Buizza, Leutbecher, and Isaksen, 2008: Potential use of an <span class="hlt">ensemble</span> of analyses in the ECMWF <span class="hlt">Ensemble</span> Prediction System, Q. J. R. Meteorol</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://eric.ed.gov/?q=ewe&id=EJ832826','ERIC'); return false;" href="http://eric.ed.gov/?q=ewe&id=EJ832826"><span id="translatedtitle">The Oral Tradition in the Sankofa Drum and Dance <span class="hlt">Ensemble</span>: Student Perceptions</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Hess, Juliet</p> <p>2009-01-01</p> <p>The Sankofa Drum and Dance <span class="hlt">Ensemble</span> is a Ghanaian drum and dance <span class="hlt">ensemble</span> that focusses on music in the Ewe tradition. It is <span class="hlt">based</span> in an elementary school in the Greater Toronto Area and consists of students in Grade 4 through Grade 8. Students in the <span class="hlt">ensemble</span> study Ghanaian traditional Ewe drumming and dancing in the oral tradition. Nine students…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017NatCo...814473E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017NatCo...814473E"><span id="translatedtitle">Antibody-controlled actuation of DNA-<span class="hlt">based</span> <span class="hlt">molecular</span> circuits</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Engelen, Wouter; Meijer, Lenny H. H.; Somers, Bram; de Greef, Tom F. A.; Merkx, Maarten</p> <p>2017-02-01</p> <p>DNA-<span class="hlt">based</span> <span class="hlt">molecular</span> circuits allow autonomous signal processing, but their actuation has relied mostly on RNA/DNA-<span class="hlt">based</span> inputs, limiting their application in synthetic biology, biomedicine and <span class="hlt">molecular</span> diagnostics. Here we introduce a generic method to translate the presence of an antibody into a unique DNA strand, enabling the use of antibodies as specific inputs for DNA-<span class="hlt">based</span> <span class="hlt">molecular</span> computing. Our approach, antibody-templated strand exchange (ATSE), uses the characteristic bivalent architecture of antibodies to promote DNA-strand exchange reactions both thermodynamically and kinetically. Detailed characterization of the ATSE reaction allowed the establishment of a comprehensive model that describes the kinetics and thermodynamics of ATSE as a function of toehold length, antibody-epitope affinity and concentration. ATSE enables the introduction of complex signal processing in antibody-<span class="hlt">based</span> diagnostics, as demonstrated here by constructing <span class="hlt">molecular</span> circuits for multiplex antibody detection, integration of multiple antibody inputs using logic gates and actuation of enzymes and DNAzymes for signal amplification.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/15005930','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/15005930"><span id="translatedtitle">Approximate Splitting for <span class="hlt">Ensembles</span> of Trees using Histograms</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Kamath, C; Cantu-Paz, E; Littau, D</p> <p>2001-09-28</p> <p>Recent work in classification indicates that significant improvements in accuracy can be obtained by growing an <span class="hlt">ensemble</span> of classifiers and having them vote for the most popular class. Implicit in many of these techniques is the concept of randomization that generates different classifiers. In this paper, they focus on <span class="hlt">ensembles</span> of decision trees that are created using a randomized procedure <span class="hlt">based</span> on histograms. Techniques, such as histograms, that discretize continuous variables, have long been used in classification to convert the data into a form suitable for processing and to reduce the compute time. The approach combines the ideas behind discretization through histograms and randomization in <span class="hlt">ensembles</span> to create decision trees by randomly selecting a split point in an interval around the best bin boundary in the histogram. The experimental results with public domain data show that <span class="hlt">ensembles</span> generated using this approach are competitive in accuracy and superior in computational cost to other <span class="hlt">ensembles</span> techniques such as boosting and bagging.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19897076','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19897076"><span id="translatedtitle"><span class="hlt">Molecular</span> <span class="hlt">bases</span> of methamphetamine-induced neurodegeneration.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cadet, Jean Lud; Krasnova, Irina N</p> <p>2009-01-01</p> <p>Methamphetamine (METH) is a highly addictive psychostimulant drug, whose abuse has reached epidemic proportions worldwide. The addiction to METH is a major public concern because its chronic abuse is associated with serious health complications including deficits in attention, memory, and executive functions in humans. These neuropsychiatric complications might, in part, be related to drug-induced neurotoxic effects, which include damage to dopaminergic and serotonergic terminals, neuronal apoptosis, as well as activated astroglial and microglial cells in the brain. Thus, the purpose of the present paper is to review cellular and <span class="hlt">molecular</span> mechanisms that might be responsible for METH neurotoxicity. These include oxidative stress, activation of transcription factors, DNA damage, excitotoxicity, blood-brain barrier breakdown, microglial activation, and various apoptotic pathways. Several approaches that allow protection against METH-induced neurotoxic effects are also discussed. Better understanding of the cellular and <span class="hlt">molecular</span> mechanisms involved in METH toxicity should help to generate modern therapeutic approaches to prevent or attenuate the long-term consequences of psychostimulant use disorders in humans.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/1330296','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/1330296"><span id="translatedtitle">Modality-Driven Classification and Visualization of <span class="hlt">Ensemble</span> Variance</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Bensema, Kevin; Gosink, Luke; Obermaier, Harald; Joy, Kenneth I.</p> <p>2016-10-01</p> <p>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 <span class="hlt">ensemble</span> datasets produced by this technique present a special challenge to visualization researchers as the <span class="hlt">ensemble</span> 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 <span class="hlt">ensemble</span> distributions that are paramount to <span class="hlt">ensemble</span> 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 <span class="hlt">based</span> on the modality of the distribution of <span class="hlt">ensemble</span> 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 <span class="hlt">ensembles</span> to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the <span class="hlt">ensemble</span> members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the <span class="hlt">ensemble</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhLA..381...36B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhLA..381...36B"><span id="translatedtitle">Controlling charge current through a DNA <span class="hlt">based</span> <span class="hlt">molecular</span> transistor</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Behnia, S.; Fathizadeh, S.; Ziaei, J.</p> <p>2017-01-01</p> <p><span class="hlt">Molecular</span> electronics is complementary to silicon-<span class="hlt">based</span> electronics and may induce electronic functions which are difficult to obtain with conventional technology. We have considered a DNA <span class="hlt">based</span> <span class="hlt">molecular</span> transistor and study its transport properties. The appropriate DNA sequence as a central chain in <span class="hlt">molecular</span> transistor and the functional interval for applied voltages is obtained. I-V characteristic diagram shows the rectifier behavior as well as the negative differential resistance phenomenon of DNA transistor. We have observed the nearly periodic behavior in the current flowing through DNA. It is reported that there is a critical gate voltage for each applied bias which above it, the electrical current is always positive.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5293539','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5293539"><span id="translatedtitle">The <span class="hlt">molecular</span> <span class="hlt">bases</span> of the suicidal brain</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Turecki, Gustavo</p> <p>2017-01-01</p> <p>Suicide ranks among the leading causes of death around the world, and takes a heavy emotional and public health toll on most societies. Both distal and proximal factors contribute to suicidal behaviour. Distal factors — such as familial and genetic predisposition, as well as early-life adversity — increase the lifetime risk of suicide. They alter responses to stress and other processes through epigenetic modification of genes and associated changes in gene expression, and through the regulation of emotional and behavioural traits. Proximal factors associate with the precipitation of a suicidal event and include alterations in key neurotransmitter systems, inflammatory changes and glial dysfunction in the brain. This Review explores the key <span class="hlt">molecular</span> changes associated with suicidality, and presents some promising avenues for future research. PMID:25354482</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009JPSJ...78j4723F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009JPSJ...78j4723F"><span id="translatedtitle">Ab initio Path Integral <span class="hlt">Molecular</span> Dynamics <span class="hlt">Based</span> on Fragment <span class="hlt">Molecular</span> Orbital Method</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fujita, Takatoshi; Watanabe, Hirofumi; Tanaka, Shigenori</p> <p>2009-10-01</p> <p>We have developed an ab initio path integral <span class="hlt">molecular</span> dynamics method <span class="hlt">based</span> on the fragment <span class="hlt">molecular</span> orbital method. This “FMO-PIMD” method can treat both nuclei and electrons quantum mechanically, and is useful to simulate large hydrogen-bonded systems with high accuracy. After a benchmark calculation for water monomer, water trimer and glycine pentamer have been studied using the FMO-PIMD method to investigate nuclear quantum effects on structure and <span class="hlt">molecular</span> interactions. The applicability of the present approach is demonstrated through a number of test calculations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4990421','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4990421"><span id="translatedtitle"><span class="hlt">Molecular</span> dynamics-<span class="hlt">based</span> refinement and validation for sub-5 Å cryo-electron microscopy maps</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Singharoy, Abhishek; Teo, Ivan; McGreevy, Ryan; Stone, John E; Zhao, Jianhua; Schulten, Klaus</p> <p>2016-01-01</p> <p>Two structure determination methods, <span class="hlt">based</span> on the <span class="hlt">molecular</span> dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or <span class="hlt">ensembles</span> of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria <span class="hlt">based</span> on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services. DOI: http://dx.doi.org/10.7554/eLife.16105.001 PMID:27383269</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27383269','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27383269"><span id="translatedtitle"><span class="hlt">Molecular</span> dynamics-<span class="hlt">based</span> refinement and validation for sub-5 Å cryo-electron microscopy maps.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Singharoy, Abhishek; Teo, Ivan; McGreevy, Ryan; Stone, John E; Zhao, Jianhua; Schulten, Klaus</p> <p>2016-07-07</p> <p>Two structure determination methods, <span class="hlt">based</span> on the <span class="hlt">molecular</span> dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or <span class="hlt">ensembles</span> of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria <span class="hlt">based</span> on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_20 --> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://eric.ed.gov/?q=phylogeny&id=EJ938354','ERIC'); return false;" href="http://eric.ed.gov/?q=phylogeny&id=EJ938354"><span id="translatedtitle">Inquiry-<span class="hlt">Based</span> Learning of <span class="hlt">Molecular</span> Phylogenetics</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Campo, Daniel; Garcia-Vazquez, Eva</p> <p>2008-01-01</p> <p>Reconstructing phylogenies from nucleotide sequences is a challenge for students because it strongly depends on evolutionary models and computer tools that are frequently updated. We present here an inquiry-<span class="hlt">based</span> course aimed at learning how to trace a phylogeny <span class="hlt">based</span> on sequences existing in public databases. Computer tools are freely available…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ChPhB..24f0202G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ChPhB..24f0202G"><span id="translatedtitle">Reweighted <span class="hlt">ensemble</span> dynamics simulations: Theory, improvement, and application</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gong, Lin-Chen; Zhou, Xin; Ouyang, Zhong-Can</p> <p>2015-06-01</p> <p><span class="hlt">Based</span> on multiple parallel short <span class="hlt">molecular</span> dynamics simulation trajectories, we designed the reweighted <span class="hlt">ensemble</span> dynamics (RED) method to more efficiently sample complex (biopolymer) systems, and to explore their hierarchical metastable states. Here we further present an improvement to depress statistical errors of the RED and we discuss a few keys in practical application of the RED, provide schemes on selection of basis functions, and determination of the free parameter in the RED. We illustrate the application of the improvements in two toy models and in the solvated alanine dipeptide. The results show the RED enables us to capture the topology of multiple-state transition networks, to detect the diffusion-like dynamical behavior in an entropy-dominated system, and to identify solvent effects in the solvated peptides. The illustrations serve as general applications of the RED in more complex biopolymer systems. Project supported by the National Natural Science Foundation of China (Grant No. 11175250).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JChPh.145x4104F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JChPh.145x4104F"><span id="translatedtitle">Self-consistent implementation of <span class="hlt">ensemble</span> density functional theory method for multiple strongly correlated electron pairs</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Filatov, Michael; Liu, Fang; Kim, Kwang S.; Martínez, Todd J.</p> <p>2016-12-01</p> <p>The spin-restricted <span class="hlt">ensemble</span>-referenced Kohn-Sham (REKS) method is <span class="hlt">based</span> on an <span class="hlt">ensemble</span> representation of the density and is capable of correctly describing the non-dynamic electron correlation stemming from (near-)degeneracy of several electronic configurations. The existing REKS methodology describes systems with two electrons in two fractionally occupied orbitals. In this work, the REKS methodology is extended to treat systems with four fractionally occupied orbitals accommodating four electrons and self-consistent implementation of the REKS(4,4) method with simultaneous optimization of the orbitals and their fractional occupation numbers is reported. The new method is applied to a number of <span class="hlt">molecular</span> systems where simultaneous dissociation of several chemical bonds takes place, as well as to the singlet ground states of organic tetraradicals 2,4-didehydrometaxylylene and 1,4,6,9-spiro[4.4]nonatetrayl.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H43H1635L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H43H1635L"><span id="translatedtitle">Downscaling Satellite Data for Predicting Catchment-scale Root Zone Soil Moisture with Ground-<span class="hlt">based</span> Sensors and an <span class="hlt">Ensemble</span> Kalman Filter</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lin, H.; Baldwin, D. C.; Smithwick, E. A. H.</p> <p>2015-12-01</p> <p>Predicting root zone (0-100 cm) soil moisture (RZSM) content at a catchment-scale is essential for drought and flood predictions, irrigation planning, weather forecasting, and many other applications. Satellites, such as the NASA Soil Moisture Active Passive (SMAP), can estimate near-surface (0-5 cm) soil moisture content globally at coarse spatial resolutions. We develop a hierarchical <span class="hlt">Ensemble</span> Kalman Filter (EnKF) data assimilation modeling system to downscale satellite-<span class="hlt">based</span> near-surface soil moisture and to estimate RZSM content across the Shale Hills Critical Zone Observatory at a 1-m resolution in combination with ground-<span class="hlt">based</span> soil moisture sensor data. In this example, a simple infiltration model within the EnKF-model has been parameterized for 6 soil-terrain units to forecast daily RZSM content in the catchment from 2009 - 2012 <span class="hlt">based</span> on AMSRE. LiDAR-derived terrain variables define intra-unit RZSM variability using a novel covariance localization technique. This method also allows the mapping of uncertainty with our RZSM estimates for each time-step. A catchment-wide satellite-to-surface downscaling parameter, which nudges the satellite measurement closer to in situ near-surface data, is also calculated for each time-step. We find significant differences in predicted root zone moisture storage for different terrain units across the experimental time-period. Root mean square error from a cross-validation analysis of RZSM predictions using an independent dataset of catchment-wide in situ Time-Domain Reflectometry (TDR) measurements ranges from 0.060-0.096 cm3 cm-3, and the RZSM predictions are significantly (p < 0.05) correlated with TDR measurements [r = 0.47-0.68]. The predictive skill of this data assimilation system is similar to the Penn State Integrated Hydrologic Modeling (PIHM) system. Uncertainty estimates are significantly (p < 0.05) correlated to cross validation error during wet and dry conditions, but more so in dry summer seasons. Developing an</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/650344','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/650344"><span id="translatedtitle">Optimal separable <span class="hlt">bases</span> and <span class="hlt">molecular</span> collisions</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Poirier, Lionel W.</p> <p>1997-12-01</p> <p>A new methodology is proposed for the efficient determination of Green`s functions and eigenstates for quantum systems of two or more dimensions. For a given Hamiltonian, the best possible separable approximation is obtained from the set of all Hilbert space operators. It is shown that this determination itself, as well as the solution of the resultant approximation, are problems of reduced dimensionality for most systems of physical interest. Moreover, the approximate eigenstates constitute the optimal separable basis, in the sense of self-consistent field theory. These distorted waves give rise to a Born series with optimized convergence properties. Analytical results are presented for an application of the method to the two-dimensional shifted harmonic oscillator system. The primary interest however, is quantum reactive scattering in <span class="hlt">molecular</span> systems. For numerical calculations, the use of distorted waves corresponds to numerical preconditioning. The new methodology therefore gives rise to an optimized preconditioning scheme for the efficient calculation of reactive and inelastic scattering amplitudes, especially at intermediate energies. This scheme is particularly suited to discrete variable representations (DVR`s) and iterative sparse matrix methods commonly employed in such calculations. State to state and cumulative reactive scattering results obtained via the optimized preconditioner are presented for the two-dimensional collinear H + H<sub>2</sub> → H<sub>2</sub> + H system. Computational time and memory requirements for this system are drastically reduced in comparison with other methods, and results are obtained for previously prohibitive energy regimes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H34D..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H34D..08S"><span id="translatedtitle">Prediction of Regional Streamflow Frequency using Model Tree <span class="hlt">Ensembles</span>: A data-driven approach <span class="hlt">based</span> on natural and anthropogenic drainage area characteristics</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schnier, S.; Cai, X.</p> <p>2012-12-01</p> <p>This study introduces a highly accurate data-driven method to predict streamflow frequency statistics <span class="hlt">based</span> on known drainage area characteristics which yields insights into the dominant controls of regional streamflow. The model is enhanced by explicit consideration of human interference in local hydrology. The basic idea is to use decision trees (i.e., regression trees) to regionalize the dataset and create a model tree by fitting multi-linear equations to the leaves of the regression tree. We improve model accuracy and obtain a measure of variable importance by creating an <span class="hlt">ensemble</span> of randomized model trees using bootstrap aggregation (i.e., bagging). The database used to induce the models is built from public domain drainage area characteristics for 715 USGS stream gages (455 in Texas and 260 in Illinois). The database includes information on natural characteristics such as precipitation, soil type and slope, as well as anthropogenic ones including land cover, human population and water use. Model accuracy was evaluated using cross-validation and several performance metrics. During the validation, the gauges that are withheld from the analysis represent ungauged watersheds. The proposed method outperforms standard regression models such as the method of residuals for predictions in ungauged watersheds. Importantly, out-of-bag variable importance combined with models for 17 points along the flow duration curve (FDC) (i.e., from 0% to 100% exceedance frequency) yields insight into the dominant controls of regional streamflow. The most discriminant variables for high flows are drainage area and seasonal precipitation. Discriminant variables for low flows are more complex and model accuracy is improved with <span class="hlt">base</span>-flow data, which is particularly difficult to obtain for ungauged sites. Consideration of human activities, such as percent urban and water use, is also shown to improve accuracy of low flow predictions. Drainage area characteristics, especially</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A41E0036B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A41E0036B"><span id="translatedtitle">Probabilistic Prediction Of Intraseasonal Oscillations Of Indian Summer Monsoon Rainfall In Extended-range Scale Using A Self-organizing Map <span class="hlt">Based</span> <span class="hlt">Ensemble</span> Forecasting Technique</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Borah, N.; Sahai, A. K.; Chattopadhyay, R.; Joseph, S.; Goswami, B.</p> <p>2012-12-01</p> <p>The long-range prediction of the seasonal mean monsoon at least one season in advance is important but may not be very useful and meaningful when the mean is close to normal. This is because the spatio-temporal distribution of rainfall anomalies is very inhomogeneous even when the all India mean is close to normal. In such cases or otherwise, the Extended range prediction of active and break spells of the monsoon with 3-4 weeks in advance would be very useful for sowing, harvesting and water resources management and to anticipate and mitigate disasters associated with monsoon variability. The prediction of monsoon in the extended range time scale is a major challenge to the meteorological research community owing to its complexity. Efforts had been made to explore the potential for the extended-range prediction of monsoon ISO but became inconclusive. The comparable amplitude of Intraseasonal Variability to that of the seasonal cycle now provides optimism for extended range prediction. The empirical prediction of rainfall on the extended range largely relies on the evolution of the large scale dynamical parameters. <span class="hlt">Based</span> on the relationship of the large scale parameters and their past temporal evolution with rainfall an analog technique has been defined to separate various shades of intraseasonal oscillations from past data. For the prediction purpose analogs of the present ISO is being identified from the past database and the future is being predicted from the evolution of the past analog. Having proved this hypothesis in Chattopadhyay, Sahai and Goswami (JAS 2008) we have developed a non-linear statistical technique <span class="hlt">based</span> on this for large <span class="hlt">ensemble</span> of extended range empirical prediction and generation of probabilistic forecast of summer monsoon rainfall on regional and sub divisional scale over India from a large pool of parameters constructed depending on the variability on different regions and using a nonlinear pattern recognition technique known as Self</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011JCAMD..25..855L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011JCAMD..25..855L"><span id="translatedtitle">Mixed learning algorithms and features <span class="hlt">ensemble</span> in hepatotoxicity prediction</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liew, Chin Yee; Lim, Yen Ching; Yap, Chun Wei</p> <p>2011-09-01</p> <p>Drug-induced liver injury, although infrequent, is an important safety concern that can lead to fatality in patients and failure in drug developments. In this study, we have used an <span class="hlt">ensemble</span> of mixed learning algorithms and mixed features for the development of a model to predict hepatic effects. This robust method is <span class="hlt">based</span> on the premise that no single learning algorithm is optimum for all modelling problems. An <span class="hlt">ensemble</span> model of 617 <span class="hlt">base</span> classifiers was built from a diverse set of 1,087 compounds. The <span class="hlt">ensemble</span> model was validated internally with five-fold cross-validation and 25 rounds of y-randomization. In the external validation of 120 compounds, the <span class="hlt">ensemble</span> model had achieved an accuracy of 75.0%, sensitivity of 81.9% and specificity of 64.6%. The model was also able to identify 22 of 23 withdrawn drugs or drugs with black box warning against hepatotoxicity. Dronedarone which is associated with severe liver injuries, announced in a recent FDA drug safety communication, was predicted as hepatotoxic by the <span class="hlt">ensemble</span> model. It was found that the <span class="hlt">ensemble</span> model was capable of classifying positive compounds (with hepatic effects) well, but less so on negatives compounds when they were structurally similar. The <span class="hlt">ensemble</span> model built in this study is made available for public use.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5217832','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5217832"><span id="translatedtitle">SVM and SVM <span class="hlt">Ensembles</span> in Breast Cancer Prediction</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong</p> <p>2017-01-01</p> <p>Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM <span class="hlt">based</span> on different kernel functions. Moreover, it is unknown whether SVM classifier <span class="hlt">ensembles</span> which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM <span class="hlt">ensembles</span> over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM <span class="hlt">ensembles</span> are compared. The experimental results show that linear kernel <span class="hlt">based</span> SVM <span class="hlt">ensembles</span> <span class="hlt">based</span> on the bagging method and RBF kernel <span class="hlt">based</span> SVM <span class="hlt">ensembles</span> with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel <span class="hlt">based</span> SVM <span class="hlt">ensembles</span> <span class="hlt">based</span> on boosting perform better than the other classifiers. PMID:28060807</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28060807','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28060807"><span id="translatedtitle">SVM and SVM <span class="hlt">Ensembles</span> in Breast Cancer Prediction.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong</p> <p>2017-01-01</p> <p>Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM <span class="hlt">based</span> on different kernel functions. Moreover, it is unknown whether SVM classifier <span class="hlt">ensembles</span> which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM <span class="hlt">ensembles</span> over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM <span class="hlt">ensembles</span> are compared. The experimental results show that linear kernel <span class="hlt">based</span> SVM <span class="hlt">ensembles</span> <span class="hlt">based</span> on the bagging method and RBF kernel <span class="hlt">based</span> SVM <span class="hlt">ensembles</span> with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel <span class="hlt">based</span> SVM <span class="hlt">ensembles</span> <span class="hlt">based</span> on boosting perform better than the other classifiers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22371429','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22371429"><span id="translatedtitle"><span class="hlt">Ensemble</span> manifold regularization.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Geng, Bo; Tao, Dacheng; Xu, Chao; Yang, Linjun; Hua, Xian-Sheng</p> <p>2012-06-01</p> <p>We propose an automatic approximation of the intrinsic manifold for general semi-supervised learning (SSL) problems. Unfortunately, it is not trivial to define an optimization function to obtain optimal hyperparameters. Usually, cross validation is applied, but it does not necessarily scale up. Other problems derive from the suboptimality incurred by discrete grid search and the overfitting. Therefore, we develop an <span class="hlt">ensemble</span> manifold regularization (EMR) framework to approximate the intrinsic manifold by combining several initial guesses. Algorithmically, we designed EMR carefully so it 1) learns both the composite manifold and the semi-supervised learner jointly, 2) is fully automatic for learning the intrinsic manifold hyperparameters implicitly, 3) is conditionally optimal for intrinsic manifold approximation under a mild and reasonable assumption, and 4) is scalable for a large number of candidate manifold hyperparameters, from both time and space perspectives. Furthermore, we prove the convergence property of EMR to the deterministic matrix at rate root-n. Extensive experiments over both synthetic and real data sets demonstrate the effectiveness of the proposed framework.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5048093','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5048093"><span id="translatedtitle"><span class="hlt">Ensemble</span> Deep Learning for Biomedical Time Series Classification</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p></p> <p>2016-01-01</p> <p><span class="hlt">Ensemble</span> learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-<span class="hlt">based</span> <span class="hlt">ensemble</span> method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known <span class="hlt">ensemble</span> methods, such as Bagging and AdaBoost. PMID:27725828</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150003243','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150003243"><span id="translatedtitle">Device and Method for Gathering <span class="hlt">Ensemble</span> Data Sets</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Racette, Paul E. (Inventor)</p> <p>2014-01-01</p> <p>An <span class="hlt">ensemble</span> detector uses calibrated noise references to produce <span class="hlt">ensemble</span> sets of data from which properties of non-stationary processes may be extracted. The <span class="hlt">ensemble</span> detector comprising: a receiver; a switching device coupled to the receiver, the switching device configured to selectively connect each of a plurality of reference noise signals to the receiver; and a gain modulation circuit coupled to the receiver and configured to vary a gain of the receiver <span class="hlt">based</span> on a forcing signal; whereby the switching device selectively connects each of the plurality of reference noise signals to the receiver to produce an output signal derived from the plurality of reference noise signals and the forcing signal.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27725828','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27725828"><span id="translatedtitle"><span class="hlt">Ensemble</span> Deep Learning for Biomedical Time Series Classification.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jin, Lin-Peng; Dong, Jun</p> <p>2016-01-01</p> <p><span class="hlt">Ensemble</span> learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-<span class="hlt">based</span> <span class="hlt">ensemble</span> method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known <span class="hlt">ensemble</span> methods, such as Bagging and AdaBoost.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013JHyd..504...69T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013JHyd..504...69T"><span id="translatedtitle">Spatial prediction of flood susceptible areas using rule <span class="hlt">based</span> decision tree (DT) and a novel <span class="hlt">ensemble</span> bivariate and multivariate statistical models in GIS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tehrany, Mahyat Shafapour; Pradhan, Biswajeet; Jebur, Mustafa Neamah</p> <p>2013-11-01</p> <p>Decision tree (DT) machine learning algorithm was used to map the flood susceptible areas in Kelantan, Malaysia.We used an <span class="hlt">ensemble</span> frequency ratio (FR) and logistic regression (LR) model in order to overcome weak points of the LR.Combined method of FR and LR was used to map the susceptible areas in Kelantan, Malaysia.Results of both methods were compared and their efficiency was assessed.Most influencing conditioning factors on flooding were recognized.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3795498','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3795498"><span id="translatedtitle">An automated approach to network features of protein structure <span class="hlt">ensembles</span></span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Bhattacharyya, Moitrayee; Bhat, Chanda R; Vishveshwara, Saraswathi</p> <p>2013-01-01</p> <p>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-<span class="hlt">Ensemble</span>, which can handle structural <span class="hlt">ensembles</span> generated through <span class="hlt">molecular</span> 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-<span class="hlt">Ensemble</span> 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-<span class="hlt">Ensemble</span> toward examining structural <span class="hlt">ensemble</span> is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-<span class="hlt">Ensemble</span> 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-<span class="hlt">Ensemble</span> is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-<span class="hlt">Ensemble</span>/psn_index.html. PMID:23934896</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EPJB...89..191Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EPJB...89..191Z"><span id="translatedtitle">Electronic transport properties of a quinone-<span class="hlt">based</span> <span class="hlt">molecular</span> switch</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zheng, Ya-Peng; Bian, Bao-An; Yuan, Pei-Pei</p> <p>2016-09-01</p> <p>In this paper, we carried out first-principles calculations <span class="hlt">based</span> on density functional theory and non-equilibrium Green's function to investigate the electronic transport properties of a quinone-<span class="hlt">based</span> molecule sandwiched between two Au electrodes. The <span class="hlt">molecular</span> switch can be reversibly switched between the reduced hydroquinone (HQ) and oxidized quinone (Q) states via redox reactions. The switching behavior of two forms is analyzed through their I- V curves, transmission spectra and <span class="hlt">molecular</span> projected self-consistent Hamiltonian at zero bias. Then we discuss the transmission spectra of the HQ and Q forms at different bias, and explain the oscillation of current according to the transmission eigenstates of LUMO energy level for Q form. The results suggest that this kind of a quinone-<span class="hlt">based</span> molecule is usable as one of the good candidates for redox-controlled <span class="hlt">molecular</span> switches.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1001134','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1001134"><span id="translatedtitle">Deep <span class="hlt">Ensemble</span> Learning for Monaural Speech Separation</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2015-02-01</p> <p><span class="hlt">Ensemble</span> Learning for Monaural Speech Separation Xiao-Lei Zhang Department of Computer Science and Engineering The Ohio State University, Columbus...State University, Columbus, OH 43210, USA dwang@cse.ohio-state.edu Abstract – Monaural speech separation is a fundamental problem in robust speech...processing. Recently, deep neural network (DNN) <span class="hlt">based</span> speech separation methods, which predict either clean speech or an ideal time-frequency mask, have</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?direntryid=334179','PESTICIDES'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?direntryid=334179"><span id="translatedtitle">Insights into the deterministic skill of air quality <span class="hlt">ensembles</span> ...</span></a></p> <p><a target="_blank" href="http://www.epa.gov/pesticides/search.htm">EPA Pesticide Factsheets</a></p> <p></p> <p></p> <p>Simulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism). Multi-model <span class="hlt">ensembles</span> can improve the forecast skill, provided that certain mathematical conditions are fulfilled. In this work, four <span class="hlt">ensemble</span> methods were applied to two different datasets, and their performance was compared for ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM10). Apart from the unconditional <span class="hlt">ensemble</span> average, the approach behind the other three methods relies on adding optimum weights to members or constraining the <span class="hlt">ensemble</span> to those members that meet certain conditions in time or frequency domain. The two different datasets were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). The methods are evaluated against ground level observations collected from the EMEP (European Monitoring and Evaluation Programme) and Air<span class="hlt">Base</span> databases. The goal of the study is to quantify to what extent we can extract predictable signals from an <span class="hlt">ensemble</span> with superior skill over the single models and the <span class="hlt">ensemble</span> mean. Verification statistics show that the deterministic models simulate better O3 than NO2 and PM10, linked to different levels of complexity in the represented processes. The unconditional <span class="hlt">ensemble</span> mean achieves higher skill compared to each stati</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JPCM...29d5002B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JPCM...29d5002B"><span id="translatedtitle">Progressive freezing of interacting spins in isolated finite magnetic <span class="hlt">ensembles</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bhattacharya, Kakoli; Dupuis, Veronique; Le-Roy, Damien; Deb, Pritam</p> <p>2017-02-01</p> <p>Self-organization of magnetic nanoparticles into secondary nanostructures provides an innovative way for designing functional nanomaterials with novel properties, different from the constituent primary nanoparticles as well as their bulk counterparts. Collective magnetic properties of such complex closed packing of magnetic nanoparticles makes them more appealing than the individual magnetic nanoparticles in many technological applications. This work reports the collective magnetic behaviour of magnetic <span class="hlt">ensembles</span> comprising of single domain Fe3O4 nanoparticles. The present work reveals that the <span class="hlt">ensemble</span> formation is <span class="hlt">based</span> on the re-orientation and attachment of the nanoparticles in an iso-oriented fashion at the mesoscale regime. Comprehensive dc magnetic measurements show the prevalence of strong interparticle interactions in the <span class="hlt">ensembles</span>. Due to the close range organization of primary Fe3O4 nanoparticles in the <span class="hlt">ensemble</span>, the spins of the individual nanoparticles interact through dipolar interactions as realized from remnant magnetization measurements. Signature of super spin glass like behaviour in the <span class="hlt">ensembles</span> is observed in the memory studies carried out in field cooled conditions. Progressive freezing of spins in the <span class="hlt">ensembles</span> is corroborated from the Vogel-Fulcher fit of the susceptibility data. Dynamic scaling of relaxation reasserted slow spin dynamics substantiating cluster spin glass like behaviour in the <span class="hlt">ensembles</span>.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_21 --> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4183294','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4183294"><span id="translatedtitle">Motor coupling through lipid membranes enhances transport velocities for <span class="hlt">ensembles</span> of myosin Va</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Nelson, Shane R.; Trybus, Kathleen M.; Warshaw, David M.</p> <p>2014-01-01</p> <p>Myosin Va is an actin-<span class="hlt">based</span> <span class="hlt">molecular</span> motor responsible for transport and positioning of a wide array of intracellular cargoes. Although myosin Va motors have been well characterized at the single-molecule level, physiological transport is carried out by <span class="hlt">ensembles</span> of motors. Studies that explore the behavior of <span class="hlt">ensembles</span> of <span class="hlt">molecular</span> motors have used nonphysiological cargoes such as DNA linkers or glass beads, which do not reproduce one key aspect of vesicular systems—the fluid intermotor coupling of biological lipid membranes. Using a system of defined synthetic lipid vesicles (100- to 650-nm diameter) composed of either 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) (fluid at room temperature) or 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) (gel at room temperature) with a range of surface densities of myosin Va motors (32–125 motors per μm2), we demonstrate that the velocity of vesicle transport by <span class="hlt">ensembles</span> of myosin Va is sensitive to properties of the cargo. Gel-state DPPC vesicles bound with multiple motors travel at velocities equal to or less than vesicles with a single myosin Va (∼450 nm/s), whereas surprisingly, <span class="hlt">ensembles</span> of myosin Va are able to transport fluid-state DOPC vesicles at velocities significantly faster (>700 nm/s) than a single motor. To explain these data, we developed a Monte Carlo simulation that suggests that these reductions in velocity can be attributed to two distinct mechanisms of intermotor interference (i.e., load-dependent modulation of stepping kinetics and binding-site exclusion), whereas faster transport velocities are consistent with a model wherein the normal stepping behavior of the myosin is supplemented by the preferential detachment of the trailing motor from the actin track. PMID:25201964</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A13F0293M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A13F0293M"><span id="translatedtitle"><span class="hlt">Ensemble-based</span> diagnosis of the large-scale processes associated with multiple high-impact weather events over North America during late October 2007</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moore, B. J.; Bosart, L. F.; Keyser, D.</p> <p>2013-12-01</p> <p>During late October 2007, the interaction between a deep polar trough and Tropical Cyclone (TC) Kajiki off the eastern Asian coast perturbed the North Pacific jet stream and resulted in the development of a high-amplitude Rossby wave train extending into North America, contributing to three concurrent high-impact weather events in North America: wildfires in southern California associated with strong Santa Ana winds, a cold surge into eastern Mexico, and widespread heavy rainfall (~150 mm) in the south-central United States. Observational analysis indicates that these high-impact weather events were all dynamically linked with the development of a major high-latitude ridge over the eastern North Pacific and western North America and a deep trough over central North America. In this study, global operational <span class="hlt">ensemble</span> forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) obtained from The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global <span class="hlt">Ensemble</span> (TIGGE) archive are used to characterize the medium-range predictability of the large-scale flow pattern associated with the three events and to diagnose the large-scale atmospheric processes favorable, or unfavorable, for the occurrence of the three events. Examination of the ECMWF forecasts leading up to the time period of the three high-impact weather events (~23-25 October 2007) indicates that <span class="hlt">ensemble</span> spread (i.e., uncertainty) in the 500-hPa geopotential height field develops in connection with downstream baroclinic development (DBD) across the North Pacific, associated with the interaction between TC Kajiki and the polar trough along the eastern Asian coast, and subsequently moves downstream into North America, yielding considerable uncertainty with respect to the structure, amplitude, and position of the ridge-trough pattern over North America. <span class="hlt">Ensemble</span> sensitivity analysis conducted for key sensible weather parameters corresponding to the three high</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014PhDT........23V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014PhDT........23V"><span id="translatedtitle"><span class="hlt">Ensemble-based</span> analysis of Front Range severe convection on 6-7 June 2012: Forecast uncertainty and communication of weather information to Front Range decision-makers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vincente, Vanessa</p> <p></p> <p>The variation of topography in Colorado not only adds to the beauty of its landscape, but also tests our ability to predict warm season severe convection. Deficient radar coverage and limited observations make quantitative precipitation forecasting quite a challenge. Past studies have suggested that greater forecast skill of mesoscale convection initiation and precipitation characteristics are achievable considering an <span class="hlt">ensemble</span> with explicitly predicted convection compared to one that has parameterized convection. The range of uncertainty and probabilities in these forecasts can help forecasters in their precipitation predictions and communication of weather information to emergency managers (EMs). EMs serve an integral role in informing and protecting communities in anticipation of hazardous weather. An example of such an event occurred on the evening of 6 June 2012, where areas to the lee of the Rocky Mountain Front Range were impacted by flash-flood-producing severe convection that included heavy rain and copious amounts of hail. Despite the discrepancy in the timing, location and evolution of convection, the convection-allowing <span class="hlt">ensemble</span> forecasts generally outperformed those of the convection-parameterized <span class="hlt">ensemble</span> in representing the mesoscale processes responsible for the 6-7 June severe convective event. Key features sufficiently reproduced by several of the convection-allowing <span class="hlt">ensemble</span> members resembled the observations: 1) general location of a convergence boundary east of Denver, 2) convective initiation along the boundary, 3) general location of a weak cold front near the Wyoming/Nebraska border, and 4) cold pools and moist upslope characteristics that contributed to the backbuilding of convection. Members from the convection-parameterized <span class="hlt">ensemble</span> that failed to reproduce these results displaced the convergence boundary, produced a cold front that moved southeast too quickly, and used the cold front for convective initiation. The convection</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/15783619','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/15783619"><span id="translatedtitle">Teleportation of an atomic <span class="hlt">ensemble</span> quantum state.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Dantan, A; Treps, N; Bramati, A; Pinard, M</p> <p>2005-02-11</p> <p>We propose a protocol to achieve high fidelity quantum state teleportation of a macroscopic atomic <span class="hlt">ensemble</span> using a pair of quantum-correlated atomic <span class="hlt">ensembles</span>. We show how to prepare this pair of <span class="hlt">ensembles</span> using quasiperfect quantum state transfer processes between light and atoms. Our protocol relies on optical joint measurements of the atomic <span class="hlt">ensemble</span> states and magnetic feedback reconstruction.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://eric.ed.gov/?q=music+AND+funding&pg=4&id=EJ640050','ERIC'); return false;" href="http://eric.ed.gov/?q=music+AND+funding&pg=4&id=EJ640050"><span id="translatedtitle">Is It Curtains for Traditional <span class="hlt">Ensembles</span>?</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Van Zandt, Kathryn</p> <p>2001-01-01</p> <p>Focuses on traditional music <span class="hlt">ensembles</span> (orchestra, bands, and choir) discussing such issues as the affects of block scheduling and how to deal with scheduling issues, the effects of funding on large <span class="hlt">ensemble</span> programs, nontraditional <span class="hlt">ensembles</span> in music programs, and trying to teach the National Standards for Music Education within a large <span class="hlt">ensemble</span>.…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3032427','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3032427"><span id="translatedtitle">SAXS <span class="hlt">ensemble</span> refinement of ESCRT-III CHMP3 conformational transitions</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Różycki, Bartosz; Kim, Young C.; Hummer, Gerhard</p> <p>2010-01-01</p> <p>Summary We develop and implement an <span class="hlt">ensemble</span>-refinement method to study dynamic biomolecular assemblies with intrinsically disordered segments. Data from small angle X-ray scattering (SAXS) experiments and from coarse-grained <span class="hlt">molecular</span> simulations are combined by using a maximum-entropy approach. The method is applied to CHMP3 of ESCRT-III, a protein with multiple helical domains separated by flexible linkers. <span class="hlt">Based</span> on recent SAXS data by Lata et al. (J. Mol. Biol. 378, 818, 2008), we construct <span class="hlt">ensembles</span> of CHMP3 at low and high salt concentration to characterize its closed autoinhibited state and open active state. At low salt, helix α5 is bound to the tip of helices α1 and α2, in excellent agreement with a recent crystal structure. Helix α6 remains free in solution and does not appear to be part of the autoinhibitory complex. The simulation-<span class="hlt">based</span> <span class="hlt">ensemble</span> refinement is general and effectively increases the resolution of SAXS beyond shape information to atomically detailed structures. PMID:21220121</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3299414','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3299414"><span id="translatedtitle">Plasmonic-<span class="hlt">Based</span> Electrochemical Impedance Spectroscopy: Application to <span class="hlt">Molecular</span> Binding</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Lu, Jin; Wang, Wei; Wang, Shaopeng; Shan, Xiaonan; Li, Jinghong; Tao, Nongjian</p> <p>2012-01-01</p> <p>Plasmonic-<span class="hlt">based</span> electrochemical impedance spectroscopy (P-EIS) is developed to investigate <span class="hlt">molecular</span> binding on surfaces. Its basic principle relies on the sensitive dependence of surface plasmon resonance (SPR) signal on surface charge density, which is modulated by applying an AC potential to a SPR chip surface. The AC component of the SPR response gives the electrochemical impedance, and the DC component provides the conventional SPR detection. The plasmonic-<span class="hlt">based</span> impedance measured over a range of frequency is in quantitative agreement with the conventional electrochemical impedance. Compared to the conventional SPR detection, P-EIS is sensitive to <span class="hlt">molecular</span> binding taking place on the chip surface, and less sensitive to bulk refractive index changes or non-specific binding. Moreover, this new approach allows for simultaneous SPR and surface impedance analysis of <span class="hlt">molecular</span> binding processes. PMID:22122514</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/1166910','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/1166910"><span id="translatedtitle">Efficient <span class="hlt">Molecular</span> Dynamics Simulations of Multiple Radical Center Systems <span class="hlt">Based</span> on the Fragment <span class="hlt">Molecular</span> Orbital Method</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Nakata, Hiroya; Schmidt, Michael W; Fedorov, Dmitri G; Kitaura, Kazuo; Nakamura, Shinichiro; Gordon, Mark S</p> <p>2014-10-16</p> <p>The fully analytic energy gradient has been developed and implemented for the restricted open-shell Hartree–Fock (ROHF) method <span class="hlt">based</span> on the fragment <span class="hlt">molecular</span> orbital (FMO) theory for systems that have multiple open-shell molecules. The accuracy of the analytic ROHF energy gradient is compared with the corresponding numerical gradient, illustrating the accuracy of the analytic gradient. The ROHF analytic gradient is used to perform <span class="hlt">molecular</span> dynamics simulations of an unusual open-shell system, liquid oxygen, and mixtures of oxygen and nitrogen. These <span class="hlt">molecular</span> dynamics simulations provide some insight about how triplet oxygen molecules interact with each other. Timings reveal that the method can calculate the energy gradient for a system containing 4000 atoms in only 6 h. Therefore, it is concluded that the FMO-ROHF method will be useful for investigating systems with multiple open shells.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25238592','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25238592"><span id="translatedtitle">Efficient <span class="hlt">molecular</span> dynamics simulations of multiple radical center systems <span class="hlt">based</span> on the fragment <span class="hlt">molecular</span> orbital method.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Nakata, Hiroya; Schmidt, Michael W; Fedorov, Dmitri G; Kitaura, Kazuo; Nakamura, Shinichiro; Gordon, Mark S</p> <p>2014-10-16</p> <p>The fully analytic energy gradient has been developed and implemented for the restricted open-shell Hartree-Fock (ROHF) method <span class="hlt">based</span> on the fragment <span class="hlt">molecular</span> orbital (FMO) theory for systems that have multiple open-shell molecules. The accuracy of the analytic ROHF energy gradient is compared with the corresponding numerical gradient, illustrating the accuracy of the analytic gradient. The ROHF analytic gradient is used to perform <span class="hlt">molecular</span> dynamics simulations of an unusual open-shell system, liquid oxygen, and mixtures of oxygen and nitrogen. These <span class="hlt">molecular</span> dynamics simulations provide some insight about how triplet oxygen molecules interact with each other. Timings reveal that the method can calculate the energy gradient for a system containing 4000 atoms in only 6 h. Therefore, it is concluded that the FMO-ROHF method will be useful for investigating systems with multiple open shells.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20804173','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20804173"><span id="translatedtitle">High <span class="hlt">molecular</span> weight polyglycerol-<span class="hlt">based</span> multivalent mannose conjugates.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Kizhakkedathu, Jayachandran N; Creagh, A Louise; Shenoi, Rajesh A; Rossi, Nicholas A A; Brooks, Donald E; Chan, Timmy; Lam, Jonathan; Dandepally, Srinivasa R; Haynes, Charles A</p> <p>2010-10-11</p> <p>We report the synthesis and characterization of multivalent mannose conjugates <span class="hlt">based</span> on high <span class="hlt">molecular</span> weight hyperbranched polyglycerols (HPG). A range of glycoconjugates were synthesized from high <span class="hlt">molecular</span> weight HPGs (up to 493 kDa) and varying mannose units (22-303 per HPG). Hemagglutination assays using fresh human red blood cells and concanavalin A (Con A) showed that HPG-mannose conjugates exhibited a large enhancement in the relative potency of conjugates (as high as 40000) along with a significant increment in relative activity per sugar (up to 255). The size of the HPG scaffold and the number of mannose residues per HPG were all shown to influence the enhancement of binding interactions with Con A. Isothermal titration calorimetry (ITC) experiments confirmed the enhanced binding affinity and showed that both <span class="hlt">molecular</span> size and ligand density play important roles. The enhancement in Con A binding to the high <span class="hlt">molecular</span> weight HPG-mannose conjugates is due to a combination of inter- and intramolecular mannose binding. A few fold increments in the binding constant were obtained over mannose upon covalent attachment to HPG. The binding enhancement is due to the highly favorable entropic contribution to the multiple interactions of Con A to mannose residues on HPG. The high <span class="hlt">molecular</span> weight HPG-mannose conjugates showed positive cooperativity in binding to Con A. Although carbohydrate density has less of an effect on functional valency of the conjugate compared to the <span class="hlt">molecular</span> size, it determines the binding affinity.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23454721','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23454721"><span id="translatedtitle">Complementary <span class="hlt">ensemble</span> clustering of biomedical data.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Fodeh, Samah Jamal; Brandt, Cynthia; Luong, Thai Binh; Haddad, Ali; Schultz, Martin; Murphy, Terrence; Krauthammer, Michael</p> <p>2013-06-01</p> <p>The rapidly growing availability of electronic biomedical data has increased the need for innovative data mining methods. Clustering in particular has been an active area of research in many different application areas, with existing clustering algorithms mostly focusing on one modality or representation of the data. Complementary <span class="hlt">ensemble</span> clustering (CEC) is a recently introduced framework in which Kmeans is applied to a weighted, linear combination of the coassociation matrices obtained from separate <span class="hlt">ensemble</span> clustering of different data modalities. The strength of CEC is its extraction of information from multiple aspects of the data when forming the final clusters. This study assesses the utility of CEC in biomedical data, which often have multiple data modalities, e.g., text and images, by applying CEC to two distinct biomedical datasets (PubMed images and radiology reports) that each have two modalities. Referent to five different clustering approaches <span class="hlt">based</span> on the Kmeans algorithm, CEC exhibited equal or better performance in the metrics of micro-averaged precision and Normalized Mutual Information across both datasets. The reference methods included clustering of single modalities as well as <span class="hlt">ensemble</span> clustering of separate and merged data modalities. Our experimental results suggest that CEC is equivalent or more efficient than comparable Kmeans <span class="hlt">based</span> clustering methods using either single or merged data modalities.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015NPGD....2..833R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015NPGD....2..833R"><span id="translatedtitle">Multivariate localization methods for <span class="hlt">ensemble</span> Kalman filtering</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.</p> <p>2015-05-01</p> <p>In <span class="hlt">ensemble</span> Kalman filtering (EnKF), the small number of <span class="hlt">ensemble</span> 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 <span class="hlt">based</span> on taking the Schur (entry-wise) product of the <span class="hlt">ensemble-based</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015NPGeo..22..723R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015NPGeo..22..723R"><span id="translatedtitle">Multivariate localization methods for <span class="hlt">ensemble</span> Kalman filtering</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.</p> <p>2015-12-01</p> <p>In <span class="hlt">ensemble</span> Kalman filtering (EnKF), the small number of <span class="hlt">ensemble</span> 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 <span class="hlt">based</span> on taking the Schur (element-wise) product of the <span class="hlt">ensemble-based</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160007388','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160007388"><span id="translatedtitle">Improving Climate Projections Using "Intelligent" <span class="hlt">Ensembles</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Baker, Noel C.; Taylor, Patrick C.</p> <p>2015-01-01</p> <p>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 <span class="hlt">ensemble</span>, in which each model is given an equal weight. It has been shown that the <span class="hlt">ensemble</span> mean generally outperforms any single model. It is possible to use unequal weights to produce <span class="hlt">ensemble</span> means, in which models are weighted <span class="hlt">based</span> on performance (called "intelligent" <span class="hlt">ensembles</span>). 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" <span class="hlt">ensemble</span> method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" <span class="hlt">ensemble</span>-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70035772','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70035772"><span id="translatedtitle">Assessing the impact of land use change on hydrology by <span class="hlt">ensemble</span> modeling (LUCHEM) III: Scenario analysis</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Huisman, J.A.; Breuer, L.; Bormann, H.; Bronstert, A.; Croke, B.F.W.; Frede, H.-G.; Graff, T.; Hubrechts, L.; Jakeman, A.J.; Kite, G.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Viney, N.R.; Willems, P.</p> <p>2009-01-01</p> <p>An <span class="hlt">ensemble</span> of 10 hydrological models was applied to the same set of land use change scenarios. There was general agreement about the direction of changes in the mean annual discharge and 90% discharge percentile predicted by the <span class="hlt">ensemble</span> members, although a considerable range in the magnitude of predictions for the scenarios and catchments under consideration was obvious. Differences in the magnitude of the increase were attributed to the different mean annual actual evapotranspiration rates for each land use type. The <span class="hlt">ensemble</span> of model runs was further analyzed with deterministic and probabilistic <span class="hlt">ensemble</span> methods. The deterministic <span class="hlt">ensemble</span> method <span class="hlt">based</span> on a trimmed mean resulted in a single somewhat more reliable scenario prediction. The probabilistic reliability <span class="hlt">ensemble</span> averaging (REA) method allowed a quantification of the model structure uncertainty in the scenario predictions. It was concluded that the use of a model <span class="hlt">ensemble</span> has greatly increased our confidence in the reliability of the model predictions. ?? 2008 Elsevier Ltd.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010HESS...14.1639T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010HESS...14.1639T"><span id="translatedtitle">A past discharge assimilation system for <span class="hlt">ensemble</span> streamflow forecasts over France - Part 2: Impact on the <span class="hlt">ensemble</span> streamflow forecasts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Thirel, G.; Martin, E.; Mahfouf, J.-F.; Massart, S.; Ricci, S.; Regimbeau, F.; Habets, F.</p> <p>2010-08-01</p> <p>The use of <span class="hlt">ensemble</span> streamflow forecasts is developing in the international flood forecasting services. <span class="hlt">Ensemble</span> streamflow forecast systems can provide more accurate forecasts and useful information about the uncertainty of the forecasts, thus improving the assessment of risks. Nevertheless, these systems, like all hydrological forecasts, suffer from errors on initialization or on meteorological data, which lead to hydrological prediction errors. This article, which is the second part of a 2-part article, concerns the impacts of initial states, improved by a streamflow assimilation system, on an <span class="hlt">ensemble</span> streamflow prediction system over France. An assimilation system was implemented to improve the streamflow analysis of the SAFRAN-ISBA-MODCOU (SIM) hydro-meteorological suite, which initializes the <span class="hlt">ensemble</span> streamflow forecasts at Météo-France. This assimilation system, using the Best Linear Unbiased Estimator (BLUE) and modifying the initial soil moisture states, showed an improvement of the streamflow analysis with low soil moisture increments. The final states of this suite were used to initialize the <span class="hlt">ensemble</span> streamflow forecasts of Météo-France, which are <span class="hlt">based</span> on the SIM model and use the European Centre for Medium-range Weather Forecasts (ECMWF) 10-day <span class="hlt">Ensemble</span> Prediction System (EPS). Two different configurations of the assimilation system were used in this study: the first with the classical SIM model and the second using improved soil physics in ISBA. The effects of the assimilation system on the <span class="hlt">ensemble</span> streamflow forecasts were assessed for these two configurations, and a comparison was made with the original (i.e. without data assimilation and without the improved physics) <span class="hlt">ensemble</span> streamflow forecasts. It is shown that the assimilation system improved most of the statistical scores usually computed for the validation of <span class="hlt">ensemble</span> predictions (RMSE, Brier Skill Score and its decomposition, Ranked Probability Skill Score, False Alarm Rate, etc</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://eric.ed.gov/?q=Nucleic+AND+acids&pg=4&id=ED268011','ERIC'); return false;" href="http://eric.ed.gov/?q=Nucleic+AND+acids&pg=4&id=ED268011"><span id="translatedtitle">Computer-<span class="hlt">Based</span> Semantic Network in <span class="hlt">Molecular</span> Biology: A Demonstration.</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Callman, Joshua L.; And Others</p> <p></p> <p>This paper analyzes the hardware and software features that would be desirable in a computer-<span class="hlt">based</span> semantic network system for representing biology knowledge. It then describes in detail a prototype network of <span class="hlt">molecular</span> biology knowledge that has been developed using Filevision software and a Macintosh computer. The prototype contains about 100…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5321729','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5321729"><span id="translatedtitle">Antibody-controlled actuation of DNA-<span class="hlt">based</span> <span class="hlt">molecular</span> circuits</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Engelen, Wouter; Meijer, Lenny H. H.; Somers, Bram; de Greef, Tom F. A.; Merkx, Maarten</p> <p>2017-01-01</p> <p>DNA-<span class="hlt">based</span> <span class="hlt">molecular</span> circuits allow autonomous signal processing, but their actuation has relied mostly on RNA/DNA-<span class="hlt">based</span> inputs, limiting their application in synthetic biology, biomedicine and <span class="hlt">molecular</span> diagnostics. Here we introduce a generic method to translate the presence of an antibody into a unique DNA strand, enabling the use of antibodies as specific inputs for DNA-<span class="hlt">based</span> <span class="hlt">molecular</span> computing. Our approach, antibody-templated strand exchange (ATSE), uses the characteristic bivalent architecture of antibodies to promote DNA-strand exchange reactions both thermodynamically and kinetically. Detailed characterization of the ATSE reaction allowed the establishment of a comprehensive model that describes the kinetics and thermodynamics of ATSE as a function of toehold length, antibody–epitope affinity and concentration. ATSE enables the introduction of complex signal processing in antibody-<span class="hlt">based</span> diagnostics, as demonstrated here by constructing <span class="hlt">molecular</span> circuits for multiplex antibody detection, integration of multiple antibody inputs using logic gates and actuation of enzymes and DNAzymes for signal amplification. PMID:28211541</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://eric.ed.gov/?q=allergy&pg=2&id=EJ1090618','ERIC'); return false;" href="http://eric.ed.gov/?q=allergy&pg=2&id=EJ1090618"><span id="translatedtitle"><span class="hlt">Molecular</span> Recognition: Detection of Colorless Compounds <span class="hlt">Based</span> on Color Change</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Khalafi, Lida; Kashani, Samira; Karimi, Javad</p> <p>2016-01-01</p> <p>A laboratory experiment is described in which students measure the amount of cetirizine in allergy-treatment tablets <span class="hlt">based</span> on <span class="hlt">molecular</span> recognition. The basis of recognition is competition of cetirizine with phenolphthalein to form an inclusion complex with ß-cyclodextrin. Phenolphthalein is pinkish under basic condition, whereas it's complex form…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJAEO..52..126B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJAEO..52..126B"><span id="translatedtitle">High resolution multisensor fusion of SAR, optical and LiDAR data <span class="hlt">based</span> on crisp vs. fuzzy and feature vs. decision <span class="hlt">ensemble</span> systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bigdeli, Behnaz; Pahlavani, Parham</p> <p>2016-10-01</p> <p>Synthetic Aperture Radar (SAR) data are of high interest for different applications in remote sensing specially land cover classification. SAR imaging is independent of solar illumination and weather conditions. It can even penetrate some of the Earth's surface materials to return information about subsurface features. However, the response of radar is more a function of geometry and structure than a surface reflection occurs in optical images. In addition, the backscatter of objects in the microwave range depends on the frequency of the band used, and the grey values in SAR images are different from the usual assumption of the spectral reflectance of the Earth's surface. Consequently, SAR imaging is often used as a complementary technique to traditional optical remote sensing. This study presents different <span class="hlt">ensemble</span> systems for multisensor fusion of SAR, multispectral and LiDAR data. First, in decision <span class="hlt">ensemble</span> system, after extraction and selection of proper features from each data, crisp SVM (Support Vector Machine) and Fuzzy KNN (K Nearest Neighbor) are utilized on each feature space. Finally Bayesian Theory is applied to fuse SVMs when Decision Template (DT) and Dempster Shafer (DS) are applied as fuzzy decision fusion methods on KNNs. Second, in feature <span class="hlt">ensemble</span> system, features from all data are applied on a cube. Then classifications were performed by SVM and FKNN as crisp and fuzzy decision making system respectively. A co-registered TerrraSAR-X, WorldView-2 and LiDAR data set form San Francisco of USA was available to examine the effectiveness of the proposed method. The results show that combinations of SAR data with different sensor improves classification results for most of the classes.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_22 --> <div id="page_23" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="441"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JHyd..534..300V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JHyd..534..300V"><span id="translatedtitle">21st century drought outlook for major climate divisions of Texas <span class="hlt">based</span> on CMIP5 multimodel <span class="hlt">ensemble</span>: Implications for water resource management</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Venkataraman, Kartik; Tummuri, Spandana; Medina, Aldo; Perry, Jordan</p> <p>2016-03-01</p> <p>Management of water resources in Texas (United States) is a challenging endeavor due to rapid population growth in the recent past coupled with significant spatiotemporal variations in climate. While climate conditions impact the availability of water, over-usage and lack of efficient management further complicate the dynamics of supply availability. In this paper, we provide the first look at the impact of climate change projections from an <span class="hlt">ensemble</span> of Coupled Model Intercomparison Project Phase 5 (CMIP5) on 21st century drought characteristics under three future emission trajectories: Representative Concentration Pathway (RCP) 2.6, RCP 4.5 and RCP 8.5, using the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI). In addition, we evaluate the performance of the <span class="hlt">ensemble</span> in simulating historical (1950-1999) observations from multiple climate divisions in Texas. Overall, the <span class="hlt">ensemble</span> performs better in simulating historical temperature than precipitation. In semi-arid locations such as El Paso and Laredo, decreasing precipitation trends are projected even under the influence of climate policies represented by the RCP 4.5. There is little variability in the SPI across climate divisions and across RCPs. The SPEI, on the other hand, generally shows a decreasing trend toward the latter half of the 21st century, with multi-year droughts becoming the norm under the RCP 8.5, particularly in regions that are already dry, such as El Paso. Less severe droughts are projected for the sub-humid eastern edge of the state. Considering that state water planning agencies are already forecasting increased water shortages over the next 50 years, we recommend proactive approaches to risk management such as adjusting the planning tools for potential recurrence of multi-year droughts in regions that are already water-stressed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3395815','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3395815"><span id="translatedtitle">A <span class="hlt">molecular</span> diffusion <span class="hlt">based</span> utility model for Drosophila larval phototaxis</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p></p> <p>2012-01-01</p> <p>Background Generally, utility <span class="hlt">based</span> decision making models focus on experimental outcomes. In this paper we propose a utility model <span class="hlt">based</span> on <span class="hlt">molecular</span> diffusion to simulate the choice behavior of Drosophila larvae exposed to different light conditions. Methods In this paper, light/dark choice-<span class="hlt">based</span> Drosophila larval phototaxis is analyzed with our <span class="hlt">molecular</span> diffusion <span class="hlt">based</span> model. An ISCEM algorithm is developed to estimate the model parameters. Results By applying this behavioral utility model to light intensity and phototaxis data, we show that this model fits the experimental data very well. Conclusions Our model provides new insights into decision making mechanisms in general. From an engineering viewpoint, we propose that the model could be applied to a wider range of decision making practices. PMID:22300450</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3614370','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3614370"><span id="translatedtitle">Comparative Visualization of <span class="hlt">Ensembles</span> Using <span class="hlt">Ensemble</span> Surface Slicing</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Alabi, Oluwafemi S.; Wu, Xunlei; Harter, Jonathan M.; Phadke, Madhura; Pinto, Lifford; Petersen, Hannah; Bass, Steffen; Keifer, Michael; Zhong, Sharon; Healey, Chris; Taylor, Russell M.</p> <p>2012-01-01</p> <p>By definition, an <span class="hlt">ensemble</span> is a set of surfaces or volumes derived from a series of simulations or experiments. Sometimes the series is run with different initial conditions for one parameter to determine parameter sensitivity. The understanding and identification of visual similarities and differences among the shapes of members of an <span class="hlt">ensemble</span> is an acute and growing challenge for researchers across the physical sciences. More specifically, the task of gaining spatial understanding and identifying similarities and differences between multiple complex geometric data sets simultaneously has proved challenging. This paper proposes a comparison and visualization technique to support the visual study of parameter sensitivity. We present a novel single-image view and sampling technique which we call <span class="hlt">Ensemble</span> Surface Slicing (ESS). ESS produces a single image that is useful for determining differences and similarities between surfaces simultaneously from several data sets. We demonstrate the usefulness of ESS on two real-world data sets from our collaborators. PMID:23560167</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/377160','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/377160"><span id="translatedtitle">Intelligent DNA-<span class="hlt">based</span> <span class="hlt">molecular</span> diagnostics using linked genetic markers</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Pathak, D.K.; Perlin, M.W.; Hoffman, E.P.</p> <p>1994-12-31</p> <p>This paper describes a knowledge-<span class="hlt">based</span> system for <span class="hlt">molecular</span> diagnostics, and its application to fully automated diagnosis of X-linked genetic disorders. <span class="hlt">Molecular</span> diagnostic information is used in clinical practice for determining genetic risks, such as carrier determination and prenatal diagnosis. Initially, blood samples are obtained from related individuals, and PCR amplification is performed. Linkage-<span class="hlt">based</span> <span class="hlt">molecular</span> diagnosis then entails three data analysis steps. First, for every individual, the alleles (i.e., DNA composition) are determined at specified chromosomal locations. Second, the flow of genetic material among the individuals is established. Third, the probability that a given individual is either a carrier of the disease or affected by the disease is determined. The current practice is to perform each of these three steps manually, which is costly, time consuming, labor-intensive, and error-prone. As such, the knowledge-intensive data analysis and interpretation supersede the actual experimentation effort as the major bottleneck in <span class="hlt">molecular</span> diagnostics. By examining the human problem solving for the task, we have designed and implemented a prototype knowledge-<span class="hlt">based</span> system capable of fully automating linkage-<span class="hlt">based</span> <span class="hlt">molecular</span> diagnostics in X-linked genetic disorders, including Duchenne Muscular Dystrophy (DMD). Our system uses knowledge-<span class="hlt">based</span> interpretation of gel electrophoresis images to determine individual DNA marker labels, a constraint satisfaction search for consistent genetic flow among individuals, and a blackboard-style problem solver for risk assessment. We describe the system`s successful diagnosis of DMD carrier and affected individuals from raw clinical data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22567846','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22567846"><span id="translatedtitle">[Morphofunctional and <span class="hlt">molecular</span> <span class="hlt">bases</span> of pineal gland aging].</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Khavinson, V Kh; Lin'kova, N S</p> <p>2012-01-01</p> <p>The review analyzed morphology, <span class="hlt">molecular</span> and functional aspects of pineal gland aging and methods of it correction. The pineal gland is central organ, which regulates activity of neuroimmunoendocrine, antioxidant and other organisms systems. Functional activity of pineal gland is discreased at aging, which is the reason of melatonin level changing. The <span class="hlt">molecular</span> and morphology research demonstrated, that pineal gland hadn't strongly pronounced atrophy at aging. Long-term experience showed, that peptides extract of pineal gland epithalamin and synthetic tetrapeptide on it <span class="hlt">base</span> epithalon restored melatonin secretion in pineal gland and had strong regulatory activity at neuroimmunoendocrine and antioxidant organism systems.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19880062578&hterms=register&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dregister','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19880062578&hterms=register&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dregister"><span id="translatedtitle">A <span class="hlt">molecular</span> shift register <span class="hlt">based</span> on electron transfer</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hopfield, J. J.; Onuchic, Josenelson; Beratan, David N.</p> <p>1988-01-01</p> <p>An electronic shift-register memory at the <span class="hlt">molecular</span> level is described. The memory elements are <span class="hlt">based</span> on a chain of electron-transfer molecules and the information is shifted by photoinduced electron-transfer reactions. This device integrates designed electronic molecules onto a very large scale integrated (silicon microelectronic) substrate, providing an example of a '<span class="hlt">molecular</span> electronic device' that could actually be made. The design requirements for such a device and possible synthetic strategies are discussed. Devices along these lines should have lower energy usage and enhanced storage density.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4008699','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4008699"><span id="translatedtitle">NEW <span class="hlt">MOLECULAR</span> MEDICINE-<span class="hlt">BASED</span> SCAR MANAGEMENT STRATEGIES</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Arno, Anna I; Gauglitz, Gerd G; Barret, Juan P; Jeschke, Marc G</p> <p>2014-01-01</p> <p>Keloids and hypertrophic scars are prevalent disabling conditions with still suboptimal treatments. Basic science and <span class="hlt">molecular-based</span> medicine research has contributed to unravel new bench-to-bedside scar therapies, and to dissect the complex signaling pathways involved. Peptides such as transforming growth factor beta (TGF-β) superfamily, with SMADs, Ski, SnoN, Fussels, endoglin, DS-Sily, Cav-1p, AZX100, thymosin-β4 and other related molecules may emerge as targets to prevent and treat keloids and hypertrophic scars. The aim of this review is to describe the basic complexity of these new <span class="hlt">molecular</span> scar management strategies, and point out new fibrosis research lines. PMID:24438742</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011CPL...511..294S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011CPL...511..294S"><span id="translatedtitle">Theory of zwitterionic <span class="hlt">molecular-based</span> organic magnets</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shelton, William A.; Aprà, Edoardo; Sumpter, Bobby G.; Saraiva-Souza, Aldilene; Souza Filho, Antonio G.; Nero, Jordan Del; Meunier, Vincent</p> <p>2011-08-01</p> <p>We describe a class of organic <span class="hlt">molecular</span> magnets <span class="hlt">based</span> on zwitterionic molecules (betaine derivatives) possessing donor, π bridge, and acceptor groups. Using extensive electronic structure calculations we show the electronic ground-state in these systems is magnetic. In addition, we show that the large energy differences computed for the various magnetic states indicate a high Neel temperature. The quantum mechanical nature of the magnetic properties originates from the conjugated π bridge (only p electrons) in cooperation with the <span class="hlt">molecular</span> donor-acceptor character. The exchange interactions between electron spin are strong, local, and independent on the length of the π bridge.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/22093453','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/22093453"><span id="translatedtitle">Estimating preselected and postselected <span class="hlt">ensembles</span></span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Massar, Serge; Popescu, Sandu</p> <p>2011-11-15</p> <p>In analogy with the usual quantum state-estimation problem, we introduce the problem of state estimation for a pre- and postselected <span class="hlt">ensemble</span>. The problem has fundamental physical significance since, as argued by Y. Aharonov and collaborators, pre- and postselected <span class="hlt">ensembles</span> are the most basic quantum <span class="hlt">ensembles</span>. Two new features are shown to appear: (1) information is flowing to the measuring device both from the past and from the future; (2) because of the postselection, certain measurement outcomes can be forced never to occur. Due to these features, state estimation in such <span class="hlt">ensembles</span> is dramatically different from the case of ordinary, preselected-only <span class="hlt">ensembles</span>. We develop a general theoretical framework for studying this problem and illustrate it through several examples. We also prove general theorems establishing that information flowing from the future is closely related to, and in some cases equivalent to, the complex conjugate information flowing from the past. Finally, we illustrate our approach on examples involving covariant measurements on spin-1/2 particles. We emphasize that all state-estimation problems can be extended to the pre- and postselected situation. The present work thus lays the foundations of a much more general theory of quantum state estimation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28263635','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28263635"><span id="translatedtitle">Global <span class="hlt">Ensemble</span> Texture Representations are Critical to Rapid Scene Perception.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Brady, Timothy F; Shafer-Skelton, Anna; Alvarez, George A</p> <p>2017-03-06</p> <p>Traditionally, recognizing the objects within a scene has been treated as a prerequisite to recognizing the scene itself. However, research now suggests that the ability to rapidly recognize visual scenes could be supported by global properties of the scene itself rather than the objects within the scene. Here, we argue for a particular instantiation of this view: That scenes are recognized by treating them as a global texture and processing the pattern of orientations and spatial frequencies across different areas of the scene without recognizing any objects. To test this model, we asked whether there is a link between how proficient individuals are at rapid scene perception and how proficiently they represent simple spatial patterns of orientation information (global <span class="hlt">ensemble</span> texture). We find a significant and selective correlation between these tasks, suggesting a link between scene perception and spatial <span class="hlt">ensemble</span> tasks but not nonspatial summary statistics In a second and third experiment, we additionally show that global <span class="hlt">ensemble</span> texture information is not only associated with scene recognition, but that preserving only global <span class="hlt">ensemble</span> texture information from scenes is sufficient to support rapid scene perception; however, preserving the same information is not sufficient for object recognition. Thus, global <span class="hlt">ensemble</span> texture alone is sufficient to allow activation of scene representations but not object representations. Together, these results provide evidence for a view of scene recognition <span class="hlt">based</span> on global <span class="hlt">ensemble</span> texture rather than a view <span class="hlt">based</span> purely on objects or on nonspatially localized global properties. (PsycINFO Database Record</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25012476','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25012476"><span id="translatedtitle">Impact of <span class="hlt">ensemble</span> learning in the assessment of skeletal maturity.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cunha, Pedro; Moura, Daniel C; Guevara López, Miguel Angel; Guerra, Conceição; Pinto, Daniela; Ramos, Isabel</p> <p>2014-09-01</p> <p>The assessment of the bone age, or skeletal maturity, is an important task in pediatrics that measures the degree of maturation of children's bones. Nowadays, there is no standard clinical procedure for assessing bone age and the most widely used approaches are the Greulich and Pyle and the Tanner and Whitehouse methods. Computer methods have been proposed to automatize the process; however, there is a lack of exploration about how to combine the features of the different parts of the hand, and how to take advantage of <span class="hlt">ensemble</span> techniques for this purpose. This paper presents a study where the use of <span class="hlt">ensemble</span> techniques for improving bone age assessment is evaluated. A new computer method was developed that extracts descriptors for each joint of each finger, which are then combined using different <span class="hlt">ensemble</span> schemes for obtaining a final bone age value. Three popular <span class="hlt">ensemble</span> schemes are explored in this study: bagging, stacking and voting. Best results were achieved by bagging with a rule-<span class="hlt">based</span> regression (M5P), scoring a mean absolute error of 10.16 months. Results show that <span class="hlt">ensemble</span> techniques improve the prediction performance of most of the evaluated regression algorithms, always achieving best or comparable to best results. Therefore, the success of the <span class="hlt">ensemble</span> methods allow us to conclude that their use may improve computer-<span class="hlt">based</span> bone age assessment, offering a scalable option for utilizing multiple regions of interest and combining their output.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AdAtS..33...10Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AdAtS..33...10Z"><span id="translatedtitle"><span class="hlt">Ensemble</span> transform sensitivity method for adaptive observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Yu; Xie, Yuanfu; Wang, Hongli; Chen, Dehui; Toth, Zoltan</p> <p>2016-01-01</p> <p>The <span class="hlt">Ensemble</span> Transform (ET) method has been shown to be useful in providing guidance for adaptive observation deployment. It predicts forecast error variance reduction for each possible deployment using its corresponding transformation matrix in an <span class="hlt">ensemble</span> subspace. In this paper, a new ET-<span class="hlt">based</span> sensitivity (ETS) method, which calculates the gradient of forecast error variance reduction in terms of analysis error variance reduction, is proposed to specify regions for possible adaptive observations. ETS is a first order approximation of the ET; it requires just one calculation of a transformation matrix, increasing computational efficiency (60%-80% reduction in computational cost). An explicit mathematical formulation of the ETS gradient is derived and described. Both the ET and ETS methods are applied to the Hurricane Irene (2011) case and a heavy rainfall case for comparison. The numerical results imply that the sensitive areas estimated by the ETS and ET are similar. However, ETS is much more efficient, particularly when the resolution is higher and the number of <span class="hlt">ensemble</span> members is larger.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4393075','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4393075"><span id="translatedtitle">Hierarchical <span class="hlt">Ensemble</span> Methods for Protein Function Prediction</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p></p> <p>2014-01-01</p> <p>Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction <span class="hlt">based</span> on <span class="hlt">ensembles</span> of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” <span class="hlt">ensemble</span> decision, taking into account the hierarchical relationships between classes. The main hierarchical <span class="hlt">ensemble</span> methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JChPh.142o4111L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JChPh.142o4111L"><span id="translatedtitle">Optically induced transport through semiconductor-<span class="hlt">based</span> <span class="hlt">molecular</span> electronics</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Guangqi; Fainberg, Boris D.; Seideman, Tamar</p> <p>2015-04-01</p> <p>A tight binding model is used to investigate photoinduced tunneling current through a <span class="hlt">molecular</span> bridge coupled to two semiconductor electrodes. A quantum master equation is developed within a non-Markovian theory <span class="hlt">based</span> on second-order perturbation theory with respect to the molecule-semiconductor electrode coupling. The spectral functions are generated using a one dimensional alternating bond model, and the coupling between the molecule and the electrodes is expressed through a corresponding correlation function. Since the <span class="hlt">molecular</span> bridge orbitals are inside the bandgap between the conduction and valence bands, charge carrier tunneling is inhibited in the dark. Subject to the dipole interaction with the laser field, virtual <span class="hlt">molecular</span> states are generated via the absorption and emission of photons, and new tunneling channels open. Interesting phenomena arising from memory are noted. Such a phenomenon could serve as a switch.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/22415662','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/22415662"><span id="translatedtitle">Optically induced transport through semiconductor-<span class="hlt">based</span> <span class="hlt">molecular</span> electronics</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Li, Guangqi; Seideman, Tamar; Fainberg, Boris D.</p> <p>2015-04-21</p> <p>A tight binding model is used to investigate photoinduced tunneling current through a <span class="hlt">molecular</span> bridge coupled to two semiconductor electrodes. A quantum master equation is developed within a non-Markovian theory <span class="hlt">based</span> on second-order perturbation theory with respect to the molecule-semiconductor electrode coupling. The spectral functions are generated using a one dimensional alternating bond model, and the coupling between the molecule and the electrodes is expressed through a corresponding correlation function. Since the <span class="hlt">molecular</span> bridge orbitals are inside the bandgap between the conduction and valence bands, charge carrier tunneling is inhibited in the dark. Subject to the dipole interaction with the laser field, virtual <span class="hlt">molecular</span> states are generated via the absorption and emission of photons, and new tunneling channels open. Interesting phenomena arising from memory are noted. Such a phenomenon could serve as a switch.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013APS..MARU21005R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013APS..MARU21005R"><span id="translatedtitle">Nanocoax-<span class="hlt">based</span> <span class="hlt">molecular</span> imprint polymer for electrochemical biosensor</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rizal, Binod; Archibald, Michelle; Simko, Laura; Connolly, Timothy; Shepard, Stephen; Burns, Michael; Chiles, Thomas; Naughton, Michael</p> <p>2013-03-01</p> <p>We have used <span class="hlt">molecular</span> imprint polymerization (MIP) on planar, nanopillar, and nanocoax structures to fabricate label-free, all-electronic electrochemical biosensors with high selectivity and sensitivity. MIP-<span class="hlt">based</span> films of ~ 7 nm thickness are formed on gold-coated surfaces by electropolymerization of a solution containing phenol and a target protein (streptavidin, at 100 μg/ml, or 1 nanomole concentration) and subsequent removal of exposed target protein, leaving behind its <span class="hlt">molecular</span> imprint. With its <span class="hlt">molecular</span> memory, MIP subsequently specifically recognizes and binds target protein with attomolar sensitivity, detected via differential pulse voltammetry. We will discuss and compare the results of MIP for different proteins on planar, nanopillar, and nanocoax structures, along with their respective ultimate sensitivities. Supported by the NIH grants NCI CA137681 and NIAID AI100216.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1812217O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1812217O"><span id="translatedtitle">Climatological attribution of wind power ramp events in East Japan and their probabilistic forecast <span class="hlt">based</span> on multi-model <span class="hlt">ensembles</span> downscaled by analog <span class="hlt">ensemble</span> using self-organizing maps</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ohba, Masamichi; Nohara, Daisuke; Kadokura, Shinji</p> <p>2016-04-01</p> <p>Severe storms or other extreme weather events can interrupt the spin of wind turbines in large scale that cause unexpected "wind ramp events". In this study, we present an application of self-organizing maps (SOMs) for climatological attribution of the wind ramp events and their probabilistic prediction. The SOM is an automatic data-mining clustering technique, which allows us to summarize a high-dimensional data space in terms of a set of reference vectors. The SOM is applied to analyze and connect the relationship between atmospheric patterns over Japan and wind power generation. SOM is employed on sea level pressure derived from the JRA55 reanalysis over the target area (Tohoku region in Japan), whereby a two-dimensional lattice of weather patterns (WPs) classified during the 1977-2013 period is obtained. To compare with the atmospheric data, the long-term wind power generation is reconstructed by using a high-resolution surface observation network AMeDAS (Automated Meteorological Data Acquisition System) in Japan. Our analysis extracts seven typical WPs, which are linked to frequent occurrences of wind ramp events. Probabilistic forecasts to wind power generation and ramps are conducted by using the obtained SOM. The probability are derived from the multiple SOM lattices <span class="hlt">based</span> on the matching of output from TIGGE multi-model global forecast to the WPs on the lattices. Since this method effectively takes care of the empirical uncertainties from the historical data, wind power generation and ramp is probabilistically forecasted from the forecasts of global models. The predictability skill of the forecasts for the wind power generation and ramp events show the relatively good skill score under the downscaling technique. It is expected that the results of this study provides better guidance to the user community and contribute to future development of system operation model for the transmission grid operator.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21445589','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21445589"><span id="translatedtitle">Mito-GSAAC: mitochondria prediction using genetic <span class="hlt">ensemble</span> classifier and split amino acid composition.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Afridi, Tariq Habib; Khan, Asifullah; Lee, Yeon Soo</p> <p>2012-04-01</p> <p>Mitochondria are all-important organelles of eukaryotic cells since they are involved in processes associated with cellular mortality and human diseases. Therefore, trustworthy techniques are highly required for the identification of new mitochondrial proteins. We propose Mito-GSAAC system for prediction of mitochondrial proteins. The aim of this work is to investigate an effective feature extraction strategy and to develop an <span class="hlt">ensemble</span> approach that can better exploit the advantages of this feature extraction strategy for mitochondria classification. We investigate four kinds of protein representations for prediction of mitochondrial proteins: amino acid composition, dipeptide composition, pseudo amino acid composition, and split amino acid composition (SAAC). Individual classifiers such as support vector machine (SVM), k-nearest neighbor, multilayer perceptron, random forest, AdaBoost, and bagging are first trained. An <span class="hlt">ensemble</span> classifier is then built using genetic programming (GP) for evolving a complex but effective decision space from the individual decision spaces of the trained classifiers. The highest prediction performance for Jackknife test is 92.62% using GP-<span class="hlt">based</span> <span class="hlt">ensemble</span> classifier on SAAC features, which is the highest accuracy, reported so far on the Mitochondria dataset being used. While on the Malaria Parasite Mitochondria dataset, the highest accuracy is obtained by SVM using SAAC and it is further enhanced to 93.21% using GP-<span class="hlt">based</span> <span class="hlt">ensemble</span>. It is observed that SAAC has better discrimination power for mitochondria prediction over the rest of the feature extraction strategies. Thus, the improved prediction performance is largely due to the better capability of SAAC for discriminating between mitochondria and non-mitochondria proteins at the N and C terminus and the effective combination capability of GP. Mito-GSAAC can be accessed at http://111.68.99.218/Mito-GSAAC . It is expected that the novel approach and the accompanied predictor will have a</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010raqs.book..127K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010raqs.book..127K"><span id="translatedtitle">Virtual Screening and <span class="hlt">Molecular</span> Design <span class="hlt">Based</span> on Hierarchical Qsar Technology</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kuz'min, Victor E.; Artemenko, A. G.; Muratov, Eugene N.; Polischuk, P. G.; Ognichenko, L. N.; Liahovsky, A. V.; Hromov, A. I.; Varlamova, E. V.</p> <p></p> <p>This chapter is devoted to the hierarchical QSAR technology (HiT QSAR) <span class="hlt">based</span> on simplex representation of <span class="hlt">molecular</span> structure (SiRMS) and its application to different QSAR/QSPR tasks. The essence of this technology is a sequential solution (with the use of the information obtained on the previous steps) of the QSAR paradigm by a series of enhanced models <span class="hlt">based</span> on <span class="hlt">molecular</span> structure description (in a specific order from 1D to 4D). Actually, it's a system of permanently improved solutions. Different approaches for domain applicability estimation are implemented in HiT QSAR. In the SiRMS approach every molecule is represented as a system of different simplexes (tetratomic fragments with fixed composition, structure, chirality, and symmetry). The level of simplex descriptors detailed increases consecutively from the 1D to 4D representation of the <span class="hlt">molecular</span> structure. The advantages of the approach presented are an ability to solve QSAR/QSPR tasks for mixtures of compounds, the absence of the "<span class="hlt">molecular</span> alignment" problem, consideration of different physical-chemical properties of atoms (e.g., charge, lipophilicity), and the high adequacy and good interpretability of obtained models and clear ways for <span class="hlt">molecular</span> design. The efficiency of HiT QSAR was demonstrated by its comparison with the most popular modern QSAR approaches on two representative examination sets. The examples of successful application of the HiT QSAR for various QSAR/QSPR investigations on the different levels (1D-4D) of the <span class="hlt">molecular</span> structure description are also highlighted. The reliability of developed QSAR models as the predictive virtual screening tools and their ability to serve as the basis of directed drug design was validated by subsequent synthetic, biological, etc. experiments. The HiT QSAR is realized as the suite of computer programs termed the "HiT QSAR" software that so includes powerful statistical capabilities and a number of useful utilities.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20091881','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20091881"><span id="translatedtitle"><span class="hlt">Molecular</span> biomimetics: GEPI-<span class="hlt">based</span> biological routes to technology.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tamerler, Candan; Khatayevich, Dmitriy; Gungormus, Mustafa; Kacar, Turgay; Oren, E Emre; Hnilova, Marketa; Sarikaya, Mehmet</p> <p>2010-01-01</p> <p>In nature, the viability of biological systems is sustained via specific interactions among the tens of thousands of proteins, the major building blocks of organisms from the simplest single-celled to the most complex multicellular species. Biomolecule-material interaction is accomplished with <span class="hlt">molecular</span> specificity and efficiency leading to the formation of controlled structures and functions at all scales of dimensional hierarchy. Through evolution, Mother Nature developed <span class="hlt">molecular</span> recognition by successive cycles of mutation and selection. <span class="hlt">Molecular</span> specificity of probe-target interactions, e.g., ligand-receptor, antigen-antibody, is always <span class="hlt">based</span> on specific peptide <span class="hlt">molecular</span> recognition. Using biology as a guide, we can now understand, engineer, and control peptide-material interactions and exploit them as a new design tool for novel materials and systems. We adapted the protocols of combinatorially designed peptide libraries, via both cell surface or phage display methods; using these we select short peptides with specificity to a variety of practical materials. These genetically engineered peptides for inorganics (GEPI) are then studied experimentally to establish their binding kinetics and surface stability. The bound peptide structure and conformations are interrogated both experimentally and via modeling, and self-assembly characteristics are tested via atomic force microscopy. We further engineer the peptide binding and assembly characteristics using a computational biomimetics approach where bioinformatics <span class="hlt">based</span> peptide-sequence similarity analysis is developed to design higher generation function-specific peptides. The <span class="hlt">molecular</span> biomimetic approach opens up new avenues for the design and utilization of multifunctional <span class="hlt">molecular</span> systems in a wide-range of applications from tissue engineering, disease diagnostics, and therapeutics to various areas of nanotechnology where integration is required among inorganic, organic and biological materials. Here, we</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_23 --> <div id="page_24" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="461"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25919868','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25919868"><span id="translatedtitle">[<span class="hlt">Molecular</span> <span class="hlt">bases</span> of α-thalassemia in Argentina].</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Scheps, Karen G; Francipane, Liliana; Nash, Abigail; Cerrone, Gloria E; Copelli, Silvia B; Varela, Viviana</p> <p>2015-01-01</p> <p>The α-thalassemia is one of the most common hereditary disorders worldwide. Currently, <span class="hlt">molecular</span> diagnostics is the only available tool to achieve an accurate diagnosis. The purpose of this study was to characterize the <span class="hlt">molecular</span> <span class="hlt">bases</span> of these syndromes in our environment and to establish genotype-phenotype associations. Through a combination of different <span class="hlt">molecular</span> techniques and fluorescent in situ hybridization (FISH),we were able to find α-thalassemic mutations in 145 of the 184 patients (78.8%) studied with hematological parameters compatible with α-thalassemia. Deletions of the α-globin genes resulted the major <span class="hlt">molecular</span> cause of the disease, and the most frequent mutation was -α(3.7), found in homozygous and heterozygous genotypes. In patients with α° phenotypes, other prevalent mutations were( _MED) and (_CAL/CAMP). The description of a sub-telomeric deletion in a patient with α-thalassemia and mental retardation was also achieved. β-thalassemic mutations in heterozygous state were found in 7.6% of the patients, who presented α-thalassemic clinical features (microcytosis and Hb A₂levels below 3.5%). Hematologic profiles for the α+ and α° genotypes were established for adult and pediatric patients. Hopefully, this work will provide guidelines for the detection of possible α-thalassemic carriers. It also highlights the collaborative work of hematologists, the biochemical and <span class="hlt">molecular</span> biology laboratory and genetists, in order to provide appropriate genetic counseling.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25404035','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25404035"><span id="translatedtitle"><span class="hlt">Molecular</span> crowding-<span class="hlt">based</span> imprinted monolithic column for capillary electrochromatography.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zong, Hai-Yan; Liu, Xiao; Liu, Zhao-Sheng; Huang, Yan-Ping</p> <p>2015-03-01</p> <p><span class="hlt">Molecular</span> crowding is a new approach to stabilizing binding sites and improving <span class="hlt">molecular</span> recognition. In this work, the concept was applied to the preparation of imprinted monolithic columns for CEC. The imprinted monolithic column was synthesized using a mixture of d-zopiclone (d-ZOP)(template), methacrylic acid, ethylene glycol dimethacrylate, and poly(methyl methacrylate) (PMMA) (<span class="hlt">molecular</span> crowding agent). The resulting PMMA-<span class="hlt">based</span> imprinted capillary was able to separate ZOP enantiomers in CEC mode. The resolution of enantiomer separation achieved on the d-ZOP-imprinted monolithic column was up to 2.09. Some polymerization factors, such as template-monomer molar ratio, functional monomer-cross-linker molar ratio and the composition of the porogen, on the imprinting effect of resulting <span class="hlt">molecularly</span> imprinted polymer (MIP) monolithic column were systematically investigated. Chromatographic parameters, including pH values, the content of acetonitrile and the salt concentration on chiral separation were also studied. The results indicated the addition of PMMA resulted in MIPs with superior retention properties and excellent selectivity for d-ZOP, as compared to the MIPs prepared without addition of the crowding-inducing agent. The results revealed that <span class="hlt">molecular</span> crowding is an effective method for the preparation of a highly efficient MIP stationary phase for chiral separation in CEC.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4179059','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4179059"><span id="translatedtitle">Bio-Mimetic Sensors <span class="hlt">Based</span> on <span class="hlt">Molecularly</span> Imprinted Membranes</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Algieri, Catia; Drioli, Enrico; Guzzo, Laura; Donato, Laura</p> <p>2014-01-01</p> <p>An important challenge for scientific research is the production of artificial systems able to mimic the recognition mechanisms occurring at the <span class="hlt">molecular</span> level in living systems. A valid contribution in this direction resulted from the development of <span class="hlt">molecular</span> imprinting. By means of this technology, selective <span class="hlt">molecular</span> recognition sites are introduced in a polymer, thus conferring it bio-mimetic properties. The potential applications of these systems include affinity separations, medical diagnostics, drug delivery, catalysis, etc. Recently, bio-sensing systems using <span class="hlt">molecularly</span> imprinted membranes, a special form of imprinted polymers, have received the attention of scientists in various fields. In these systems imprinted membranes are used as bio-mimetic recognition elements which are integrated with a transducer component. The direct and rapid determination of an interaction between the recognition element and the target analyte (template) was an encouraging factor for the development of such systems as alternatives to traditional bio-assay methods. Due to their high stability, sensitivity and specificity, bio-mimetic sensors-<span class="hlt">based</span> membranes are used for environmental, food, and clinical uses. This review deals with the development of <span class="hlt">molecularly</span> imprinted polymers and their different preparation methods. Referring to the last decades, the application of these membranes as bio-mimetic sensor devices will be also reported. PMID:25196110</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25196110','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25196110"><span id="translatedtitle">Bio-mimetic sensors <span class="hlt">based</span> on <span class="hlt">molecularly</span> imprinted membranes.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Algieri, Catia; Drioli, Enrico; Guzzo, Laura; Donato, Laura</p> <p>2014-07-30</p> <p>An important challenge for scientific research is the production of artificial systems able to mimic the recognition mechanisms occurring at the <span class="hlt">molecular</span> level in living systems. A valid contribution in this direction resulted from the development of <span class="hlt">molecular</span> imprinting. By means of this technology, selective <span class="hlt">molecular</span> recognition sites are introduced in a polymer, thus conferring it bio-mimetic properties. The potential applications of these systems include affinity separations, medical diagnostics, drug delivery, catalysis, etc. Recently, bio-sensing systems using <span class="hlt">molecularly</span> imprinted membranes, a special form of imprinted polymers, have received the attention of scientists in various fields. In these systems imprinted membranes are used as bio-mimetic recognition elements which are integrated with a transducer component. The direct and rapid determination of an interaction between the recognition element and the target analyte (template) was an encouraging factor for the development of such systems as alternatives to traditional bio-assay methods. Due to their high stability, sensitivity and specificity, bio-mimetic sensors-<span class="hlt">based</span> membranes are used for environmental, food, and clinical uses. This review deals with the development of <span class="hlt">molecularly</span> imprinted polymers and their different preparation methods. Referring to the last decades, the application of these membranes as bio-mimetic sensor devices will be also reported.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3413134','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3413134"><span id="translatedtitle">DNA origami as biocompatible surface to match single-molecule and <span class="hlt">ensemble</span> experiments</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Gietl, Andreas; Holzmeister, Phil; Grohmann, Dina; Tinnefeld, Philip</p> <p>2012-01-01</p> <p>Single-molecule experiments on immobilized molecules allow unique insights into the dynamics of <span class="hlt">molecular</span> machines and enzymes as well as their interactions. The immobilization, however, can invoke perturbation to the activity of biomolecules causing incongruities between single molecule and <span class="hlt">ensemble</span> measurements. Here we introduce the recently developed DNA origami as a platform to transfer <span class="hlt">ensemble</span> assays to the immobilized single molecule level without changing the nano-environment of the biomolecules. The idea is a stepwise transfer of common functional assays first to the surface of a DNA origami, which can be checked at the <span class="hlt">ensemble</span> level, and then to the microscope glass slide for single-molecule inquiry using the DNA origami as a transfer platform. We studied the structural flexibility of a DNA Holliday junction and the TATA-binding protein (TBP)-induced bending of DNA both on freely diffusing molecules and attached to the origami structure by fluorescence resonance energy transfer. This resulted in highly congruent data sets demonstrating that the DNA origami does not influence the functionality of the biomolecule. Single-molecule data collected from surface-immobilized biomolecule-loaded DNA origami are in very good agreement with data from solution measurements supporting the fact that the DNA origami can be used as biocompatible surface in many fluorescence-<span class="hlt">based</span> measurements. PMID:22523083</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4613249','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4613249"><span id="translatedtitle">An Effective Antifreeze Protein Predictor with <span class="hlt">Ensemble</span> Classifiers and Comprehensive Sequence Descriptors</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Yang, Runtao; Zhang, Chengjin; Gao, Rui; Zhang, Lina</p> <p>2015-01-01</p> <p>Antifreeze proteins (AFPs) play a pivotal role in the antifreeze effect of overwintering organisms. They have a wide range of applications in numerous fields, such as improving the production of crops and the quality of frozen foods. Accurate identification of AFPs may provide important clues to decipher the underlying mechanisms of AFPs in ice-binding and to facilitate the selection of the most appropriate AFPs for several applications. <span class="hlt">Based</span> on an <span class="hlt">ensemble</span> learning technique, this study proposes an AFP identification system called AFP-<span class="hlt">Ensemble</span>. In this system, random forest classifiers are trained by different training subsets and then aggregated into a consensus classifier by majority voting. The resulting predictor yields a sensitivity of 0.892, a specificity of 0.940, an accuracy of 0.938 and a balanced accuracy of 0.916 on an independent dataset, which are far better than the results obtained by previous methods. These results reveal that AFP-<span class="hlt">Ensemble</span> is an effective and promising predictor for large-scale determination of AFPs. The detailed feature analysis in this study may give useful insights into the <span class="hlt">molecular</span> mechanisms of AFP-ice interactions and provide guidance for the related experimental validation. A web server has been designed to implement the proposed method. PMID:26370959</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H51F1419M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H51F1419M"><span id="translatedtitle">Real-time Reservoir Operation <span class="hlt">Based</span> on a Combination of Long-term and Short-term Optimization and Hydrological <span class="hlt">Ensemble</span> Forecasts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Meier, P.; Tilmant, A.; Boucher, M.; Anctil, F.</p> <p>2012-12-01</p> <p>In a reservoir system, benefits are usually increased if the system is operated in a coordinated manner. However, despite ever increasing computational power available to users, the optimization of a large system of reservoirs and hydropower stations remains a challenge, especially if uncertainties are included. When applying optimization methods, such as stochastic dynamic programming, the size of a problem becomes quickly too large to be solved. This situation is also known as the curse of dimensionality which limits the applicability of SDP to systems involving only two to three reservoirs. The fact that by design most reservoirs serve multiple purposes adds another difficulty when the operation is to be optimized. A method which is able to address the optimization of multi-purpose reservoirs even in large systems is stochastic dual dynamic programming (SDDP). This approximative dynamic programming technique represents the future benefit function with a number of hyperplanes. The SDDP model developed in this study maximizes the expected net benefits associated with the operation of a reservoir system on a midterm horizon (several years, monthly time step). SDDP provides, at each time step, estimates of the marginal water value stored in each reservoir. Reservoir operators, however, are interested in day-to-day decisions. To provide an operational optimization framework tailored for short-term decision support, the SDDP optimization can be coupled with a short-term nonlinear programming optimization using hydrological <span class="hlt">ensemble</span> forecasts. The short-term objective therefore consists of the total electricity production within the forecast horizon and the total value of water stored in all the reservoirs. Thus, maximizing this objective ensures that a short-term decision does not contradict the strategic planning. This optimization framework is implemented for the Gatineau river basin, a sub-basin of the Ottawa river north of the city of Ottawa. The Gatineau river</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040088766&hterms=crustacean&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dcrustacean','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040088766&hterms=crustacean&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dcrustacean"><span id="translatedtitle">Arthropod phylogeny <span class="hlt">based</span> on eight <span class="hlt">molecular</span> loci and morphology</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Giribet, G.; Edgecombe, G. D.; Wheeler, W. C.</p> <p>2001-01-01</p> <p>The interrelationships of major clades within the Arthropoda remain one of the most contentious issues in systematics, which has traditionally been the domain of morphologists. A growing body of DNA sequences and other types of <span class="hlt">molecular</span> data has revitalized study of arthropod phylogeny and has inspired new considerations of character evolution. Novel hypotheses such as a crustacean-hexapod affinity were <span class="hlt">based</span> on analyses of single or few genes and limited taxon sampling, but have received recent support from mitochondrial gene order, and eye and brain ultrastructure and neurogenesis. Here we assess relationships within Arthropoda <span class="hlt">based</span> on a synthesis of all well sampled <span class="hlt">molecular</span> loci together with a comprehensive data set of morphological, developmental, ultrastructural and gene-order characters. The <span class="hlt">molecular</span> data include sequences of three nuclear ribosomal genes, three nuclear protein-coding genes, and two mitochondrial genes (one protein coding, one ribosomal). We devised new optimization procedures and constructed a parallel computer cluster with 256 central processing units to analyse <span class="hlt">molecular</span> data on a scale not previously possible. The optimal 'total evidence' cladogram supports the crustacean-hexapod clade, recognizes pycnogonids as sister to other euarthropods, and indicates monophyly of Myriapoda and Mandibulata.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015MNRAS.454.2067C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015MNRAS.454.2067C"><span id="translatedtitle">Graph-<span class="hlt">based</span> interpretation of the <span class="hlt">molecular</span> interstellar medium segmentation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Colombo, D.; Rosolowsky, E.; Ginsburg, A.; Duarte-Cabral, A.; Hughes, A.</p> <p>2015-12-01</p> <p>We present a generalization of the giant <span class="hlt">molecular</span> cloud identification problem <span class="hlt">based</span> on cluster analysis. The method we designed, SCIMES (Spectral Clustering for Interstellar <span class="hlt">Molecular</span> Emission Segmentation) considers the dendrogram of emission in the broader framework of graph theory and utilizes spectral clustering to find discrete regions with similar emission properties. For Galactic <span class="hlt">molecular</span> cloud structures, we show that the characteristic volume and/or integrated CO luminosity are useful criteria to define the clustering, yielding emission structures that closely reproduce `by-eye' identification results. SCIMES performs best on well-resolved, high-resolution data, making it complementary to other available algorithms. Using 12CO(1-0) data for the Orion-Monoceros complex, we demonstrate that SCIMES provides robust results against changes of the dendrogram-construction parameters, noise realizations and degraded resolution. By comparing SCIMES with other cloud decomposition approaches, we show that our method is able to identify all canonical clouds of the Orion-Monoceros region, avoiding the overdivision within high-resolution survey data that represents a common limitation of several decomposition algorithms. The Orion-Monoceros objects exhibit hierarchies and size-line width relationships typical to the turbulent gas in <span class="hlt">molecular</span> clouds, although `the Scissors' region deviates from this common description. SCIMES represents a significant step forward in moving away from pixel-<span class="hlt">based</span> cloud segmentation towards a more physical-oriented approach, where virtually all properties of the ISM can be used for the segmentation of discrete objects.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1261448','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1261448"><span id="translatedtitle">Optimizing legacy <span class="hlt">molecular</span> dynamics software with directive-<span class="hlt">based</span> offload</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Michael Brown, W.; Carrillo, Jan-Michael Y.; Gavhane, Nitin; Thakkar, Foram M.; Plimpton, Steven J.</p> <p>2015-05-14</p> <p>The directive-<span class="hlt">based</span> programming models are one solution for exploiting many-core coprocessors to increase simulation rates in <span class="hlt">molecular</span> dynamics. They offer the potential to reduce code complexity with offload models that can selectively target computations to run on the CPU, the coprocessor, or both. In our paper, we describe modifications to the LAMMPS <span class="hlt">molecular</span> dynamics code to enable concurrent calculations on a CPU and coprocessor. We also demonstrate that standard <span class="hlt">molecular</span> dynamics algorithms can run efficiently on both the CPU and an x86-<span class="hlt">based</span> coprocessor using the same subroutines. As a consequence, we demonstrate that code optimizations for the coprocessor also result in speedups on the CPU; in extreme cases up to 4.7X. We provide results for LAMMAS benchmarks and for production <span class="hlt">molecular</span> dynamics simulations using the Stampede hybrid supercomputer with both Intel (R) Xeon Phi (TM) coprocessors and NVIDIA GPUs: The optimizations presented have increased simulation rates by over 2X for organic molecules and over 7X for liquid crystals on Stampede. The optimizations are available as part of the "Intel package" supplied with LAMMPS. (C) 2015 Elsevier B.V. All rights reserved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1261448-optimizing-legacy-molecular-dynamics-software-directive-based-offload','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1261448-optimizing-legacy-molecular-dynamics-software-directive-based-offload"><span id="translatedtitle">Optimizing legacy <span class="hlt">molecular</span> dynamics software with directive-<span class="hlt">based</span> offload</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Michael Brown, W.; Carrillo, Jan-Michael Y.; Gavhane, Nitin; ...</p> <p>2015-05-14</p> <p>The directive-<span class="hlt">based</span> programming models are one solution for exploiting many-core coprocessors to increase simulation rates in <span class="hlt">molecular</span> dynamics. They offer the potential to reduce code complexity with offload models that can selectively target computations to run on the CPU, the coprocessor, or both. In our paper, we describe modifications to the LAMMPS <span class="hlt">molecular</span> dynamics code to enable concurrent calculations on a CPU and coprocessor. We also demonstrate that standard <span class="hlt">molecular</span> dynamics algorithms can run efficiently on both the CPU and an x86-<span class="hlt">based</span> coprocessor using the same subroutines. As a consequence, we demonstrate that code optimizations for the coprocessor also resultmore » in speedups on the CPU; in extreme cases up to 4.7X. We provide results for LAMMAS benchmarks and for production <span class="hlt">molecular</span> dynamics simulations using the Stampede hybrid supercomputer with both Intel (R) Xeon Phi (TM) coprocessors and NVIDIA GPUs: The optimizations presented have increased simulation rates by over 2X for organic molecules and over 7X for liquid crystals on Stampede. The optimizations are available as part of the "Intel package" supplied with LAMMPS. (C) 2015 Elsevier B.V. All rights reserved.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/22308400','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/22308400"><span id="translatedtitle">Quantum Gibbs <span class="hlt">ensemble</span> Monte Carlo</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Fantoni, Riccardo; Moroni, Saverio</p> <p>2014-09-21</p> <p>We present a path integral Monte Carlo method which is the full quantum analogue of the Gibbs <span class="hlt">ensemble</span> Monte Carlo method of Panagiotopoulos to study the gas-liquid coexistence line of a classical fluid. Unlike previous extensions of Gibbs <span class="hlt">ensemble</span> Monte Carlo to include quantum effects, our scheme is viable even for systems with strong quantum delocalization in the degenerate regime of temperature. This is demonstrated by an illustrative application to the gas-superfluid transition of {sup 4}He in two dimensions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18094006','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18094006"><span id="translatedtitle">Standardised PCR-<span class="hlt">based</span> <span class="hlt">molecular</span> epidemiology of tuberculosis.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Allix-Béguec, C; Supply, P; Wanlin, M; Bifani, P; Fauville-Dufaux, M</p> <p>2008-05-01</p> <p>A population-<span class="hlt">based</span> <span class="hlt">molecular</span> epidemiology investigation has been undertaken to evaluate tuberculosis transmission and control in the Brussels-Capital Region (Belgium). All tuberculosis cases reported from January 2003 to December 2004 were investigated. In total, 536 Mycobacterium tuberculosis isolates (89% of culture-positive samples) were genotyped by the newly standardised 24 loci-<span class="hlt">based</span> mycobacterial interspersed repetitive unit-variable number tandem-repeat typing, spoligotyping and IS6110 fingerprinting. Of all the patients, 30% were grouped <span class="hlt">based</span> on strain clusters, suggesting a transmission index of 20%. An unsuspected outbreak entailing > or = 23 patients was evidenced by <span class="hlt">molecular</span> typing analysis and confirmed by contact tracing. Foreign-born status accounted for 79% of the studied patients, including 37.9% illegal immigrants and asylum seekers. Among foreign-born patients, asylum seekers and illegal immigrants were significantly less abundant in strain clusters than settled residents. Tuberculosis in the Brussels-Capital Region is a bi-faceted problem, comprising both persisting recent transmission and "imported diseases". <span class="hlt">Molecular</span> epidemiology <span class="hlt">based</span> on real-time genotyping techniques has proven invaluable in better understanding tuberculosis transmission. However, it will most efficiently contribute to tuberculosis control when implemented in an integrated public health system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC32A..08J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC32A..08J"><span id="translatedtitle">Selecting, weeding, and weighting biased climate model <span class="hlt">ensembles</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jackson, C. S.; Picton, J.; Huerta, G.; Nosedal Sanchez, A.</p> <p>2012-12-01</p> <p>In the Bayesian formulation, the "log-likelihood" is a test statistic for selecting, weeding, or weighting climate model <span class="hlt">ensembles</span> with observational data. This statistic has the potential to synthesize the physical and data constraints on quantities of interest. One of the thorny issues for formulating the log-likelihood is how one should account for biases. While in the past we have included a generic discrepancy term, not all biases affect predictions of quantities of interest. We make use of a 165-member <span class="hlt">ensemble</span> CAM3.1/slab ocean climate models with different parameter settings to think through the issues that are involved with predicting each model's sensitivity to greenhouse gas forcing given what can be observed from the <span class="hlt">base</span> state. In particular we use multivariate empirical orthogonal functions to decompose the differences that exist among this <span class="hlt">ensemble</span> to discover what fields and regions matter to the model's sensitivity. We find that the differences that matter are a small fraction of the total discrepancy. Moreover, weighting members of the <span class="hlt">ensemble</span> using this knowledge does a relatively poor job of adjusting the <span class="hlt">ensemble</span> mean toward the known answer. This points out the shortcomings of using weights to correct for biases in climate model <span class="hlt">ensembles</span> created by a selection process that does not emphasize the priorities of your log-likelihood.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007LNCS.4682.1162C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007LNCS.4682.1162C"><span id="translatedtitle">Evolutionary <span class="hlt">Ensemble</span> for In Silico Prediction of Ames Test Mutagenicity</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chen, Huanhuan; Yao, Xin</p> <p></p> <p>Driven by new regulations and animal welfare, the need to develop in silico models has increased recently as alternative approaches to safety assessment of chemicals without animal testing. This paper describes a novel machine learning <span class="hlt">ensemble</span> approach to building an in silico model for the prediction of the Ames test mutagenicity, one of a battery of the most commonly used experimental in vitro and in vivo genotoxicity tests for safety evaluation of chemicals. Evolutionary random neural <span class="hlt">ensemble</span> with negative correlation learning (ERNE) [1] was developed <span class="hlt">based</span> on neural networks and evolutionary algorithms. ERNE combines the method of bootstrap sampling on training data with the method of random subspace feature selection to ensure diversity in creating individuals within an initial <span class="hlt">ensemble</span>. Furthermore, while evolving individuals within the <span class="hlt">ensemble</span>, it makes use of the negative correlation learning, enabling individual NNs to be trained as accurate as possible while still manage to maintain them as diverse as possible. Therefore, the resulting individuals in the final <span class="hlt">ensemble</span> are capable of cooperating collectively to achieve better generalization of prediction. The empirical experiment suggest that ERNE is an effective <span class="hlt">ensemble</span> approach for predicting the Ames test mutagenicity of chemicals.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3909228','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3909228"><span id="translatedtitle">Context-<span class="hlt">based</span> preprocessing of <span class="hlt">molecular</span> docking data</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p></p> <p>2013-01-01</p> <p>Background Data preprocessing is a major step in data mining. In data preprocessing, several known techniques can be applied, or new ones developed, to improve data quality such that the mining results become more accurate and intelligible. Bioinformatics is one area with a high demand for generation of comprehensive models from large datasets. In this article, we propose a context-<span class="hlt">based</span> data preprocessing approach to mine data from <span class="hlt">molecular</span> docking simulation results. The test cases used a fully-flexible receptor (FFR) model of Mycobacterium tuberculosis InhA enzyme (FFR_InhA) and four different ligands. Results We generated an initial set of attributes as well as their respective instances. To improve this initial set, we applied two selection strategies. The first was <span class="hlt">based</span> on our context-<span class="hlt">based</span> approach while the second used the CFS (Correlation-<span class="hlt">based</span> Feature Selection) machine learning algorithm. Additionally, we produced an extra dataset containing features selected by combining our context strategy and the CFS algorithm. To demonstrate the effectiveness of the proposed method, we evaluated its performance <span class="hlt">based</span> on various predictive (RMSE, MAE, Correlation, and Nodes) and context (Precision, Recall and FScore) measures. Conclusions Statistical analysis of the results shows that the proposed context-<span class="hlt">based</span> data preprocessing approach significantly improves predictive and context measures and outperforms the CFS algorithm. Context-<span class="hlt">based</span> data preprocessing improves mining results by producing superior interpretable models, which makes it well-suited for practical applications in <span class="hlt">molecular</span> docking simulations using FFR models. PMID:24564276</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26295733','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26295733"><span id="translatedtitle"><span class="hlt">Molecular</span> Dynamics Simulations of Perylenediimide DNA <span class="hlt">Base</span> Surrogates.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Markegard, Cade B; Mazaheripour, Amir; Jocson, Jonah-Micah; Burke, Anthony M; Dickson, Mary N; Gorodetsky, Alon A; Nguyen, Hung D</p> <p>2015-09-03</p> <p>Perylene-3,4,9,10-tetracarboxylic diimides (PTCDIs) are a well-known class of organic materials. Recently, these molecules have been incorporated within DNA as <span class="hlt">base</span> surrogates, finding ready applications as probes of DNA structure and function. However, the assembly dynamics and kinetics of PTCDI DNA <span class="hlt">base</span> surrogates have received little attention to date. Herein, we employ constant temperature <span class="hlt">molecular</span> dynamics simulations to gain an improved understanding of the assembly of PTCDI dimers and trimers. We also use replica-exchange <span class="hlt">molecular</span> dynamics simulations to elucidate the energetic landscape dictating the formation of stacked PTCDI structures. Our studies provide insight into the equilibrium configurations of multimeric PTCDIs and hold implications for the construction of DNA-inspired systems from perylene-derived organic semiconductor building blocks.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013ARPC...64..151B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013ARPC...64..151B"><span id="translatedtitle"><span class="hlt">Molecular</span> Recognition and Ligand Association</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Baron, Riccardo; McCammon, J. Andrew</p> <p>2013-04-01</p> <p>We review recent developments in our understanding of <span class="hlt">molecular</span> recognition and ligand association, focusing on two major viewpoints: (a) studies that highlight new physical insight into the <span class="hlt">molecular</span> recognition process and the driving forces determining thermodynamic signatures of binding and (b) recent methodological advances in applications to protein-ligand binding. In particular, we highlight the challenges posed by compensating enthalpic and entropic terms, competing solute and solvent contributions, and the relevance of complex configurational <span class="hlt">ensembles</span> comprising multiple protein, ligand, and solvent intermediate states. As more complete physics is taken into account, computational approaches increase their ability to complement experimental measurements, by providing a microscopic, dynamic view of <span class="hlt">ensemble</span>-averaged experimental observables. Physics-<span class="hlt">based</span> approaches are increasingly expanding their power in pharmacology applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/10047578','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/10047578"><span id="translatedtitle">Envisioning the <span class="hlt">molecular</span> choreography of DNA <span class="hlt">base</span> excision repair.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Parikh, S S; Mol, C D; Hosfield, D J; Tainer, J A</p> <p>1999-02-01</p> <p>Recent breakthroughs integrate individual DNA repair enzyme structures, biochemistry and biology to outline the structural cell biology of the DNA <span class="hlt">base</span> excision repair pathways that are essential to genome integrity. Thus, we are starting to envision how the actions, movements, steps, partners and timing of DNA repair enzymes, which together define their <span class="hlt">molecular</span> choreography, are elegantly controlled by both the nature of the DNA damage and the structural chemistry of the participating enzymes and the DNA double helix.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AIPC.1362..289B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AIPC.1362..289B"><span id="translatedtitle"><span class="hlt">Molecularly</span> Imprinted Polymer <span class="hlt">Based</span> Sensor for the Detection of Theophylline</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Braga, Guilherme S.; Paterno, Leonardo G.; Fonseca, Fernando J.; del Valle, Manel</p> <p>2011-11-01</p> <p>A <span class="hlt">molecularly</span> imprinted polymer (MIP) impedance-<span class="hlt">based</span> sensor was employed to detect theophylline in distilled water. To evaluate its sensibility, impedance measurements were carried out in a diluted solution of theophylline (1 mM) and distilled water using MIP and NIP (reference non-imprinted polymer) sensors. MIP showed higher sensitivity to theophylline than the NIP. This feature shows their suitability for developing an electronic tongue system for determination of methylxanthines.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_24 --> <div id="page_25" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="481"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25647500','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25647500"><span id="translatedtitle"><span class="hlt">Ensemble-based</span> simultaneous emission estimates and improved forecast of radioactive pollution from nuclear power plant accidents: application to ETEX tracer experiment.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zhang, X L; Li, Q B; Su, G F; Yuan, M Q</p> <p>2015-04-01</p> <p>The accidental release of radioactive materials from nuclear power plant leads to radioactive pollution. We apply an augmented <span class="hlt">ensemble</span> Kalman filter (EnKF) with a chemical transport model to jointly estimate the emissions of Perfluoromethylcyclohexane (PMCH), a tracer substitute for radionuclides, from a point source during the European Tracer Experiment, and to improve the forecast of its dispersion downwind. We perturb wind fields to account for meteorological uncertainties. We expand the state vector of PMCH concentrations through continuously adding an a priori emission rate for each succeeding assimilation cycle. We adopt a time-correlated red noise to simulate the temporal emission fluctuation. The improved EnKF system rapidly updates (and reduces) the excessively large initial first-guess emissions, thereby significantly improves subsequent forecasts (r = 0.83, p < 0.001). It retrieves 94% of the total PMCH released and substantially reduces transport error (>80% average reduction of the normalized mean square error).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JMagR.241...53V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JMagR.241...53V"><span id="translatedtitle">Towards a true protein movie: A perspective on the potential impact of the <span class="hlt">ensemble-based</span> structure determination using exact NOEs</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vögeli, Beat; Orts, Julien; Strotz, Dean; Chi, Celestine; Minges, Martina; Wälti, Marielle Aulikki; Güntert, Peter; Riek, Roland</p> <p>2014-04-01</p> <p>Confined by the Boltzmann distribution of the energies of the states, a multitude of structural states are inherent to biomolecules. For a detailed understanding of a protein's function, its entire structural landscape at atomic resolution and insight into the interconversion between all the structural states (i.e. dynamics) are required. Whereas dedicated trickery with NMR relaxation provides aspects of local dynamics, and 3D structure determination by NMR is well established, only recently have several attempts been made to formulate a more comprehensive description of the dynamics and the structural landscape of a protein. Here, a perspective is given on the use of exact NOEs (eNOEs) for the elucidation of structural <span class="hlt">ensembles</span> of a protein describing the covered conformational space.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010HESSD...7.2455T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010HESSD...7.2455T"><span id="translatedtitle">A past discharge assimilation system for <span class="hlt">ensemble</span> streamflow forecasts over France - Part 2: Impact on the <span class="hlt">ensemble</span> streamflow forecasts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Thirel, G.; Martin, E.; Mahfouf, J.-F.; Massart, S.; Ricci, S.; Regimbeau, F.; Habets, F.</p> <p>2010-04-01</p> <p>The use of <span class="hlt">ensemble</span> streamflow forecasts is developing in the international flood forecasting services. Such systems can provide more accurate forecasts and useful information about the uncertainty of the forecasts, thus improving the assessment of risks. Nevertheless, these systems, like all hydrological forecasts, suffer from errors on initialization or on meteorological data, which lead to hydrological prediction errors. This article, which is the second part of a 2-part article, concerns the impacts of initial states, improved by a streamflow assimilation system, on an <span class="hlt">ensemble</span> streamflow prediction system over France. An assimilation system was implemented to improve the streamflow analysis of the SAFRAN-ISBA-MODCOU (SIM) hydro-meteorological suite, which initializes the <span class="hlt">ensemble</span> streamflow forecasts at Météo-France. This assimilation system, using the Best Linear Unbiased Estimator (BLUE) and modifying the initial soil moisture states, showed an improvement of the streamflow analysis with low soil moisture increments. The final states of this suite were used to initialize the <span class="hlt">ensemble</span> streamflow forecasts of Météo-France, which are <span class="hlt">based</span> on the SIM model and use the European Centre for Medium-range Weather Forecasts (ECMWF) 10-day <span class="hlt">Ensemble</span> Prediction System (EPS). Two different configurations of the assimilation system were used in this study: the first with the classical SIM model and the second using improved soil physics in ISBA. The effects of the assimilation system on the <span class="hlt">ensemble</span> streamflow forecasts were assessed for these two configurations, and a comparison was made with the original (i.e. without data assimilation and without the improved physics) <span class="hlt">ensemble</span> streamflow forecasts. It is shown that the assimilation system improved most of the statistical scores usually computed for the validation of <span class="hlt">ensemble</span> predictions (RMSE, Brier Skill Score and its decomposition, Ranked Probability Skill Score, False Alarm Rate, etc.), especially for the first</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4511640','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4511640"><span id="translatedtitle">Phylogeny of Kinorhyncha <span class="hlt">Based</span> on Morphology and Two <span class="hlt">Molecular</span> Loci</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Sørensen, Martin V.; Dal Zotto, Matteo; Rho, Hyun Soo; Herranz, Maria; Sánchez, Nuria; Pardos, Fernando; Yamasaki, Hiroshi</p> <p>2015-01-01</p> <p> rRNA had been omitted. Analysis of the morphological data produced results that were similar with those from the combined <span class="hlt">molecular</span> and morphological analysis. E.g., the morphological data also supported exclusion of Dracoderes from Cyclorhagida. The main differences between the morphological analysis and analyses <span class="hlt">based</span> on the combined datasets include: 1) Homalorhagida appears as monophyletic in the morphological tree only, 2) the morphological analyses position Franciscideres and the new genus within Cyclorhagida near Zelinkaderidae and Cateriidae, whereas analyses including <span class="hlt">molecular</span> data place the two genera inside Allomalorhagida, and 3) species of Campyloderes appear in a basal trichotomy within Kentrorhagata in the morphological tree, whereas analysis of the combined datasets places species of Campyloderes as a sister clade to Echinoderidae and Kentrorhagata. PMID:26200115</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26200115','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26200115"><span id="translatedtitle">Phylogeny of Kinorhyncha <span class="hlt">Based</span> on Morphology and Two <span class="hlt">Molecular</span> Loci.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sørensen, Martin V; Dal Zotto, Matteo; Rho, Hyun Soo; Herranz, Maria; Sánchez, Nuria; Pardos, Fernando; Yamasaki, Hiroshi</p> <p>2015-01-01</p> <p>RNA had been omitted. Analysis of the morphological data produced results that were similar with those from the combined <span class="hlt">molecular</span> and morphological analysis. E.g., the morphological data also supported exclusion of Dracoderes from Cyclorhagida. The main differences between the morphological analysis and analyses <span class="hlt">based</span> on the combined datasets include: 1) Homalorhagida appears as monophyletic in the morphological tree only, 2) the morphological analyses position Franciscideres and the new genus within Cyclorhagida near Zelinkaderidae and Cateriidae, whereas analyses including <span class="hlt">molecular</span> data place the two genera inside Allomalorhagida, and 3) species of Campyloderes appear in a basal trichotomy within Kentrorhagata in the morphological tree, whereas analysis of the combined datasets places species of Campyloderes as a sister clade to Echinoderidae and Kentrorhagata.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/15978569','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/15978569"><span id="translatedtitle">A novel <span class="hlt">ensemble</span> machine learning for robust microarray data classification.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Peng, Yonghong</p> <p>2006-06-01</p> <p>Microarray data analysis and classification has demonstrated convincingly that it provides an effective methodology for the effective diagnosis of diseases and cancers. Although much research has been performed on applying machine learning techniques for microarray data classification during the past years, it has been shown that conventional machine learning techniques have intrinsic drawbacks in achieving accurate and robust classifications. This paper presents a novel <span class="hlt">ensemble</span> machine learning approach for the development of robust microarray data classification. Different from the conventional <span class="hlt">ensemble</span> learning techniques, the approach presented begins with generating a pool of candidate <span class="hlt">base</span> classifiers <span class="hlt">based</span> on the gene sub-sampling and then the selection of a sub-set of appropriate <span class="hlt">base</span> classifiers to construct the classification committee <span class="hlt">based</span> on classifier clustering. Experimental results have demonstrated that the classifiers constructed by the proposed method outperforms not only the classifiers generated by the conventional machine learning but also the classifiers generated by two widely used conventional <span class="hlt">ensemble</span> learning methods (bagging and boosting).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.7139S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.7139S"><span id="translatedtitle">Shallow cumuli <span class="hlt">ensemble</span> statistics for development of a stochastic parameterization</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs</p> <p>2014-05-01</p> <p>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 <span class="hlt">ensembles</span>, 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 <span class="hlt">ensemble</span> theory, Craig and Cohen (2006) developed a theory for the fluctuations in a deep convective <span class="hlt">ensemble</span>. The micro-states of a deep convective cloud <span class="hlt">ensemble</span> are characterized by the cloud-<span class="hlt">base</span> mass flux, which, according to the theory, is exponentially distributed (Boltzmann distribution). Following their work, we study the shallow cumulus <span class="hlt">ensemble</span> statistics and the distribution of the cloud-<span class="hlt">base</span> 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 <span class="hlt">base</span> level, to retrieve the information about the individual cloud life cycles and the cloud <span class="hlt">ensemble</span> as a whole. In the case of shallow cumulus cloud <span class="hlt">ensemble</span>, the distribution of micro-states is a generalized exponential distribution. <span class="hlt">Based</span> on the empirical and theoretical findings, a stochastic model has been developed to simulate the shallow convective cloud <span class="hlt">ensemble</span> and to test the convective <span class="hlt">ensemble</span> theory. Stochastic model simulates a compound random process, with the number of convective elements drawn from a</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23564743','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23564743"><span id="translatedtitle"><span class="hlt">Molecular</span> switching behavior in isosteric DNA <span class="hlt">base</span> pairs.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jissy, A K; Konar, Sukanya; Datta, Ayan</p> <p>2013-04-15</p> <p>The structures and proton-coupled behavior of adenine-thymine (A-T) and a modified <span class="hlt">base</span> pair containing a thymine isostere, adenine-difluorotoluene (A-F), are studied in different solvents by dispersion-corrected density functional theory. The stability of the canonical Watson-Crick <span class="hlt">base</span> pair and the mismatched pair in various solvents with low and high dielectric constants is analyzed. It is demonstrated that A-F <span class="hlt">base</span> pairing is favored in solvents with low dielectric constant. The stabilization and conformational changes induced by protonation are also analyzed for the natural as well as the mismatched <span class="hlt">base</span> pair. DNA sequences capable of changing their sequence conformation on protonation are used in the construction of pH-<span class="hlt">based</span> <span class="hlt">molecular</span> switches. An acidic medium has a profound influence in stabilizing the isostere <span class="hlt">base</span> pair. Such a large gain in stability on protonation leads to an interesting pH-controlled <span class="hlt">molecular</span> switch, which can be incorporated in a natural DNA tract.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2535704','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2535704"><span id="translatedtitle">A <span class="hlt">Molecular</span> Selection Index Method <span class="hlt">Based</span> on Eigenanalysis</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Cerón-Rojas, J. Jesús; Castillo-González, Fernando; Sahagún-Castellanos, Jaime; Santacruz-Varela, Amalio; Benítez-Riquelme, Ignacio; Crossa, José</p> <p>2008-01-01</p> <p>The traditional <span class="hlt">molecular</span> selection index (MSI) employed in marker-assisted selection maximizes the selection response by combining information on <span class="hlt">molecular</span> markers linked to quantitative trait loci (QTL) and phenotypic values of the traits of the individuals of interest. This study proposes an MSI <span class="hlt">based</span> on an eigenanalysis method (<span class="hlt">molecular</span> eigen selection index method, MESIM), where the first eigenvector is used as a selection index criterion, and its elements determine the proportion of the trait's contribution to the selection index. This article develops the theoretical framework of MESIM. Simulation results show that the genotypic means and the expected selection response from MESIM for each trait are equal to or greater than those from the traditional MSI. When several traits are simultaneously selected, MESIM performs well for traits with