SEARCH · PubMed Health

Results for “ensemble”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5Linked to original sources

PubMed2005

Stop-flow programmable selectivity with a dual-column ensemble of microfabricated etched silicon columns and air as carrier gas.

A series-coupled ensemble of microfabricated GC columns made by dry reactive ion etching of silicon substrates is evaluated for use with pneumatic selectivity enhancement techniques for targeted pairs of volatile organic compounds. Each column is 3.0 m long with a 150 miceom wide by 240 microm deep cross section. Dynamic coating was used to prepare a nonpolar column with a dimethyl polysiloxane stationary phase and a moderately polar column with a trifluoropropylmethyl polysiloxane stationary phase. Each column generates 5000-6000 theoretical plates. The columns are operated in series with the nonpolar column connected to a split inlet, the polar column connected to a flame ionization detector, and a valve connected between the column junction point and the inlet to the first column. When the valve is closed, the effluent from the first column passes directly into the second column. When the valve is open, both ends of the first column are at the inlet pressure, and flow stops in this column while increased flow is obtained in the second column. For analyte pairs that are separated by the first column but coelute from the column ensemble, the valve is opened for a few seconds after the first component of the pair has passed into the second column but the second component is still in the first column. The result is enhanced separation of the pair in the ensemble chromatogram. Relatively thick cross-linked stationary-phase films are used to increase retention for volatile compounds. The combination of air carrier gas and stationary-phase film thickness in the range 1-2 microm requires the use of relatively low average carrier gas velocities (typically less than 10 cm/s) for adequate resolving power of the column ensemble. Selectivity enhancement under isothermal conditions for a 14-component mixture of volatile organic compounds is demonstrated where neither of the columns alone nor the column ensemble without selectivity enhancement could obtain a complete separation.

Air↗

PubMed1998

Dynamics of the conformational ensemble of partially folded bovine pancreatic trypsin inhibitor.

A single-disulfide variant of bovine pancreatic trypsin inhibitor (BPTI), [14-38]Abu, is a partially folded ensemble which includes two, and in one case three, conformations that interconvert slowly enough to exhibit separate cross-peaks in the amide region of homonuclear and heteronuclear NMR spectra. Each conformation is itself composed of many subconformations in rapid equilibrium. Partially folded BPTI undergoes local motions that are slow, noncooperative, independent fluctuations of short segments within the chain. Cooperative global unfolding of the ensemble is also observed. Heteronuclear NMR has been used to measure interconversion rate constants of partially folded conformational substates; the rate constants differ for each residue and vary over an order of magnitude. For local fluctuation, the forward rate constants for amide protons of the antiparallel beta-sheet are significantly smaller than the rest of the molecule, consistent with other indications that this is the most stable part of the partially folded protein. The reverse rate constants also vary; they are the highest for Ala 27 in the turn between the strands in the sheet and for Phe 33 in the antiparallel beta-sheet. Global unfolding interconversion rate constants vary over a 3-fold range, consistent with previously observed deviations from two-state behavior. Fast backbone dynamics, from T1, T2, and NOE relaxation parameters, are obtained for the slowly interchanging conformations in the partially folded ensemble. Clear differences are observed between the two conformations; one is more flexible and less compact than the other. In the more flexible and disordered partially folded conformation, intermediate exchange is detected for some backbone amides, namely, those in the central beta-sheet and the turn. These same sheet and turn residues are more ordered in the globally denatured ensemble as well. Our results suggest that the turn initiates formation of a partially folded ensemble in which the slow-exchange core is the most stable region and in which segmental fluctuations reflect multiple nuclei for folding of the rest of the molecule.

Animals↗

PubMed2002

Dynamic distribution of growth rates within the ensembles of colloidal II-VI and III-V semiconductor nanocrystals as a factor governing their photoluminescence efficiency.

The distribution of properties within ensembles of colloidally grown II-VI and III-V semiconductor nanocrystals was studied. A drastic difference in the photoluminescence efficiencies of size-selected fractions was observed for both organometallically prepared CdSe and InAs colloids and for CdTe nanocrystals synthesized in aqueous medium, indicating a general character of the phenomenon observed. The difference in the photoluminescence efficiencies is attributed to different averaged surface disorder of the nanocrystals originating from the Ostwald ripening growth mechanism when larger particles in the ensemble grow at the expense of dissolving smaller particles. At any stage of growth, only a fraction of particles within the ensemble of growing colloidal nanocrystals has the most perfect surface and, thus, shows the most efficient photoluminescence. This is explained by a theoretical model describing the evolution of an ensemble of nanocrystals in a colloidal solution. In an ensemble of growing nanocrystals, the fraction of particles with the highest photoluminescence corresponds to the particle size having nearly zero average growth rate. The small average growth rate leads to the lowest possible degree of surface disorder at any given reaction conditions.

Journal Article↗

PubMed2005

Direct measurement of single and ensemble average particle-surface potential energy profiles.

This work involves the development of a novel technique that integrates total internal reflection and video microscopy methods to simultaneously measure single particle and ensemble average particle-surface interactions. For the 2 mum silica colloids and glass coverslip used in this study, particle size polydispersity is found to be a dominant factor in determining the distribution of single particle profiles about ensemble average profiles. In conjunction with this observation, chemical and physical nonuniformity are not evident in any of our measurements even with sensitivity to interactions on the order of kT. One advantage of using ensemble averaging in conjunction with time averaging is the ability to dramatically decrease the time required to measure average particle-wall interactions which scales inversely with interfacial particle concentration. A number of experimental issues are addressed in the development of this technique including (1) combining single particle distribution functions, (2) statistical sampling of distribution functions using both time and ensemble averaging, and (3) correcting overlapping scattering signals between adjacent particles. The capabilities of the ensemble averaging technique are also demonstrated to provide unique measurements of particle-surface interactions in metastable systems by selecting only height excursions of levitated particles when calculating potentials. Ultimately, this new technique provides several important advantages over single particle measurements, which provides a foundation for measuring interactions in increasingly complex interfacial systems.

Journal Article↗

PubMed2000

Multi-unit recordings reveal context-dependent modulation of synchrony in odor-specific neural ensembles.

We used neural ensemble recording to examine odor-evoked ensemble patterns in the moth antennal (olfactory) lobe. Different odors are thought to evoke unique spatiotemporal patterns of glomerular activity, but little is known about the population dynamics underlying formation of these patterns. Using a silicon multielectrode array, we observed dynamic network interactions within and between glomeruli. Whereas brief odor pulses repeatedly triggered activity in the same coding ensemble, the temporal pattern of synchronous activity superimposed on the ensemble was neither oscillatory nor odor specific. Rather, synchrony strongly depended on contextual variables such as odor intensity and intermittency. Also, because of emergent inhibitory circuit interactions, odor blends evoked temporal ensemble patterns that could not be predicted from the responses to the individual odorants. Thus even at this early stage of information processing, the timing of odor-evoked neural representations is modulated by key stimulus factors unrelated to the molecular identity of the odor.

Action Potentials↗

PubMed2002

[Use of Ensemble tissue harmonic imaging to improve the resolution in ultrasound investigations of the head and neck area].

BACKGROUND: Using ultrasound diagnostic, deeper areas of tissue cannot be examined as easily as superficial areas. Therefore it was necessary to develop a new image processing technique for ultrasound platforms to improve the quality of sonographical resolution in deeper areas. Tissue Harmonic Imaging is a modern technique that uses the non-linear, "harmonic" parts of ultrasound waves. Ensemble Tissue Harmonic Imaging is a new technique that uses a "Wide Band Harmonic Imaging", based on a patented phase-inversion-technique, and improves imaging quality. AIM: Aim of the study is to show if Ensemble Harmonic Imaging can improve imaging quality even in superficial areas of tissue in comparison to fundamental B-Mode-technique. METHODS: A Sonoline Elegra(R) high-end-scanner with 7.5 MHz linear array was used for this study. Differences of techniques ("fundamental"-sonographic-mode versus Ensemble Tissue Harmonic Imaging(R)-mode) are shown by investigation of six patients with various lesions of the head and neck area. CONCLUSION: In all cases there was a gain of resolution by using Ensemble Tissue Harmonic Imaging even in superficial areas. Ensemble Tissue Harmonic Imaging improves the sonographical resolution and reduces the artifacts.

Artifacts↗

PubMed2005

A unified methodological framework for the simulation of nonisothermal ensembles.

A general framework is developed for the simulation of nonisothermal statistical-mechanical ensembles. This framework is intended to synthesize the formulation of advanced Monte Carlo simulation methods such as multihistogram reweighting, replica-exchange methods, and expanded ensemble techniques so that they can be applied to different nonisothermal ensembles. Using Lennard-Jones systems as test cases, novel implementations of these methods are demonstrated with different ensembles including the microcanonical, isobaric-isoenthalpic, and isobaric-semigrand ensembles. In particular, it is shown that the use of multiensemble methods allows the efficient simulation of microcanonical density of states, entropies, vapor-liquid and solid-liquid equilibrium for pure component systems, and fluid-phase coexistence for binary mixtures. In these applications, comparisons are also presented that highlight the advantages of the proposed multiensemble implementations over alternative methods used before.

Journal Article↗

PubMed2005

Molecular dynamics in the isothermal-isobaric ensemble: the requirement of a "shell" molecule. II. Simulation results.

The results of a series of constant pressure and temperature molecular-dynamics (MD) simulation studies based on the rigorous shell particle formulation of the isothermal-isobaric (NpT) ensemble are presented. These MD simulations validate the newly proposed constant pressure equations of motion in which a "shell" particle is used to define uniquely the volume of the system [M. J. Uline and D. S. Corti, J. Chem. Phys. (to be published), preceding paper]. Ensemble averages obtained with the new MD NpT algorithm match the ensemble averages obtained using the previously derived shell particle Monte Carlo NpT method [D. S. Corti, Mol. Phys. 100, 1887 (2002)]. In addition, we also verify that the Hoover NpT MD algorithm [W. G. Hoover, Phys. Rev. A 31, 1695 (1985); 34, 2499 (1986)] generates the correct ensemble averages, though only when periodic boundary conditions are employed. The extension of the shell particle MD algorithm to multicomponent systems is also discussed, in which we show for equilibrium properties that the identity of the shell particle is completely arbitrary when periodic boundary conditions are applied. Self-diffusion coefficients determined with the shell particle equations of motion are also identical to those obtained in other ensembles. 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 effects of the shell particle on the dynamics of the system. Overall, the shell particle MD algorithm is an effective simulation method for studying systems exposed to a constant external pressure and may provide an advantage over other existing constant pressure approaches when developing nonequilibrium MD methods.

Journal Article↗

PubMed2006

Relation between native ensembles and experimental structures of proteins.

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

Animals↗

PubMed1996

Ensemble codes involving hippocampal neurons are at risk during delayed performance tests.

Multielectrode recording techniques were used to record ensemble activity from 10 to 16 simultaneously active CA1 and CA3 neurons in the rat hippocampus during performance of a spatial delayed-nonmatch-to-sample task. Extracted sources of variance were used to assess the nature of two different types of errors that accounted for 30% of total trials. The two types of errors included ensemble "miscodes" of sample phase information and errors associated with delay-dependent corruption or disappearance of sample information at the time of the nonmatch response. Statistical assessment of trial sequences and associated "strength" of hippocampal ensemble codes revealed that miscoded error trials always followed delay-dependent error trials in which encoding was "weak," indicating that the two types of errors were "linked." It was determined that the occurrence of weakly encoded, delay-dependent error trials initiated an ensemble encoding "strategy" that increased the chances of being correct on the next trial and avoided the occurrence of further delay-dependent errors. Unexpectedly, the strategy involved "strongly" encoding response position information from the prior (delay-dependent) error trial and carrying it forward to the sample phase of the next trial. This produced a miscode type error on trials in which the "carried over" information obliterated encoding of the sample phase response on the next trial. Application of this strategy, irrespective of outcome, was sufficient to reorient the animal to the proper between trial sequence of response contingencies (nonmatch-to-sample) and boost performance to 73% correct on subsequent trials. The capacity for ensemble analyses of strength of information encoding combined with statistical assessment of trial sequences therefore provided unique insight into the "dynamic" nature of the role hippocampus plays in delay type memory tasks.

Action Potentials↗

PubMed2006

Maximum sustainable work rate for five protective clothing ensembles with respect to moisture vapor transmission rate and air permeability.

The fabrics associated with protective clothing affect heat stress, which influences productivity and risks of heat-related disorders. This study compared the work limiting effects of five protective coveralls and a semiclothed condition (t-shirt and shorts). Two fabric characteristics determined from bench tests, moisture vapor transmission rate (MVTR), and air permeability were also examined as possible predictors of ensemble performance. A progressive metabolic rate protocol was used where environmentalconditions (T(db) = 32 degrees C; T(pwb) = 26 degrees C) were held constant while treadmill speed was slowly increased. The limiting metabolic rate to just maintain thermal equilibrium was the critical point. At this point, critical speed and critical metabolic rate were noted and total evaporative resistance was calculated for each ensemble. Five acclimatized subjects wore each of the six clothing conditions in a random order. Statistically significant differences were found among the five protective garments and a semiclothed ensemble for critical treadmill speed (S(crit)), critical metabolic rate (M(crit)), and total evaporative resistance (R(e-t)). The semiclothed condition (S(crit) = 1.77 m/sec; M(crit) = 580 W; R(e-t) = 0.0099 kPa m2/W) and ensembles made from spunbonded, melt blown, spunbonded polypropylene (SMS) (1.72 m/sec; 560 W; 0.0135 kPa m2/W) and spunbonded polypropylene (1.67 m/sec; 550 W; 0.0126 kPa m2/W) were able to support higher work rates than fabrics made from Tyvek 1422-A (a nonwoven spunbonded olefin) (1.48 m/sec; 470 W; 0.0183 kPa m2/W) and a microporous film supported by spunbonded polypropylene (1.34 m/sec; 420 W; 0.0231 kPa m2/W). A tightly woven polyester ensemble (1.59 m/sec; 510 W; 0.0130 kPa m2/W) had intermediate values and was not significantly different from either group. Air permeability was a better predictor of fabric work limiting performance than MVTR. An air permeability on the order of 10,000 L/min cm2 bar would have little effect on maximum sustainable work.

Adult↗

PubMed1997

An automated approach for defining core atoms and domains in an ensemble of NMR-derived protein structures.

A single NMR-derived protein structure is usually deposited as an ensemble containing many structures, each consistent with the restraint set used. The number of NMR-derived structures deposited in the Protein Data Bank (PDB) is increasing rapidly. In addition, many of the structures deposited in an ensemble exhibit variation in only some regions of the structure, often with the majority of the structure remaining largely invariant across the family of structures. Therefore it is useful to determine the set of atoms whose positions are 'well defined' across an ensemble (also known as the 'core' atoms). We have developed a computer program, NMRCORE, which automatically defines (i) the core atoms, and (ii) the rigid body(ies), or domain(s), in which they occur. The program uses a sorted list of the variances in individual dihedral angles across the ensemble to define the core, followed by the automatic clustering of the variances in pairwise inter-atom distances across the ensemble to define the rigid body(ies) which comprise the core. The program is freely available via the World Wide Web (http://neon.chem.le.ac.uk/nmrcore/).

Algorithms↗

PubMed2001

Rigorous classical-mechanical derivation of a multiple-copy algorithm for sampling statistical mechanical ensembles.

We derive a rigorous, multiple-copy simulation algorithm that is formally equivalent to conventional classical molecular dynamics for an ensemble of systems, but may be used for rapid geometry optimizations. The derivation is accomplished by starting from an ensemble of copies of the entire system and applying a point coordinate transformation to a large subsystem defined as the bath. After the transformation, each atom of the bath is described by one "major" set of coordinates located at the average position of the ensemble of equivalent atoms and a set of "minor" coordinates that when combined with the "major" coordinates represent exact dynamics. Neglecting the "minor" set of coordinates results in a Hamiltonian and a probability density equivalent to those used in existing multiple-copy methods. Neglecting Hamilton's equations of motion for the minor variables gives the equations of motion for locally enhanced sampling. Numerical tests indicate that the algorithm can recover exact molecular dynamics of the ensemble, conventional multiple-copy dynamics, or results of intermediate accuracy. Thus, the algorithm provides a rigorous basis for multiple-copy dynamics, resolves many of the uncertainties associated with their current implementations, and offers the potential for calculating ensemble average properties in conjunction with finding a system's global minimum energy geometry.

Journal Article↗

PubMed2003

Dynamical mean-field theory of noisy spiking neuron ensembles: application to the Hodgkin-Huxley model.

A dynamical mean-field approximation (DMA) previously proposed by the present author [H. Hasegawa, Phys. Rev E 67, 041903 (2003)] has been extended to ensembles described by a general noisy spiking neuron model. Ensembles of N-unit neurons, each of which is expressed by coupled K-dimensional differential equations (DEs), are assumed to be subject to spatially correlated white noises. The original KN-dimensional stochastic DEs have been replaced by K(K+2)-dimensional deterministic DEs expressed in terms of means and the second-order moments of local and global variables: the fourth-order contributions are taken into account by the Gaussian decoupling approximation. Our DMA has been applied to an ensemble of Hodgkin-Huxley (HH) neurons (K=4), for which effects of the noise, the coupling strength, and the ensemble size on the response to a single-spike input have been investigated. Numerical results calculated by the DMA theory are in good agreement with those obtained by direct simulations, although the former computation is about a thousand times faster than the latter for a typical HH neuron ensemble with N=100.

Action Potentials↗

PubMed2006

From sample similarity to ensemble similarity: probabilistic distance measures in reproducing kernel Hilbert space.

This paper addresses the problem of characterizing ensemble similarity from sample similarity in a principled manner. Using reproducing kernel as a characterization of sample similarity, we suggest a probabilistic distance measure in the reproducing kernel Hilbert space (RKHS) as the ensemble similarity. Assuming normality in the RKHS, we derive analytic expressions for probabilistic distance measures that are commonly used in many applications, such as Chernoff distance (or the Bhattacharyya distance as its special case), Kullback-Leibler divergence, etc. Since the reproducing kernel implicitly embeds a nonlinear mapping, our approach presents a new way to study these distances whose feasibility and efficiency is demonstrated using experiments with synthetic and real examples. Further, we extend the ensemble similarity to the reproducing kernel for ensemble and study the ensemble similarity for more general data representations.

Algorithms↗

PubMed2006

Rotation forest: A new classifier ensemble method.

We propose a method for generating classifier ensembles based on feature extraction. To create the training data for a base classifier, the feature set is randomly split into K subsets (K is a parameter of the algorithm) and Principal Component Analysis (PCA) is applied to each subset. All principal components are retained in order to preserve the variability information in the data. Thus, K axis rotations take place to form the new features for a base classifier. The idea of the rotation approach is to encourage simultaneously individual accuracy and diversity within the ensemble. Diversity is promoted through the feature extraction for each base classifier. Decision trees were chosen here because they are sensitive to rotation of the feature axes, hence the name "forest." Accuracy is sought by keeping all principal components and also using the whole data set to train each base classifier. Using WEKA, we examined the Rotation Forest ensemble on a random selection of 33 benchmark data sets from the UCI repository and compared it with Bagging, AdaBoost, and Random Forest. The results were favorable to Rotation Forest and prompted an investigation into diversity-accuracy landscape of the ensemble models. Diversity-error diagrams revealed that Rotation Forest ensembles construct individual classifiers which are more accurate than these in AdaBoost and Random Forest, and more diverse than these in Bagging, sometimes more accurate as well.

Algorithms↗

PubMed2007

A comparison of decision tree ensemble creation techniques.

We experimentally evaluate bagging and seven other randomization-based approaches to creating an ensemble of decision tree classifiers. Statistical tests were performed on experimental results from 57 publicly available data sets. When cross-validation comparisons were tested for statistical significance, the best method was statistically more accurate than bagging on only eight of the 57 data sets. Alternatively, examining the average ranks of the algorithms across the group of data sets, we find that boosting, random forests, and randomized trees are statistically significantly better than bagging. Because our results suggest that using an appropriate ensemble size is important, we introduce an algorithm that decides when a sufficient number of classifiers has been created for an ensemble. Our algorithm uses the out-of-bag error estimate, and is shown to result in an accurate ensemble for those methods that incorporate bagging into the construction of the ensemble.

Algorithms↗

PubMed2005

An experimental bias-variance analysis of SVM ensembles based on resampling techniques.

Recently, bias-variance decomposition of error has been used as a tool to study the behavior of learning algorithms and to develop new ensemble methods well suited to the bias-variance characteristics of base learners. We propose methods and procedures, based on Domingo's unified bias-variance theory, to evaluate and quantitatively measure the bias-variance decomposition of error in ensembles of learning machines. We apply these methods to study and compare the bias-variance characteristics of single support vector machines (SVMs) and ensembles of SVMs based on resampling techniques, and their relationships with the cardinality of the training samples. In particular, we present an experimental bias-variance analysis of bagged and random aggregated ensembles of SVMs in order to verify their theoretical variance reduction properties. The experimental bias-variance analysis quantitatively characterizes the relationships between bagging and random aggregating, and explains the reasons why ensembles built on small subsamples of the data work with large databases. Our analysis also suggests new directions for research to improve on classical bagging.

Algorithms↗