Topic
Ensemble averaging
About: Ensemble averaging is a research topic. Over the lifetime, 651 publications have been published within this topic receiving 17056 citations.
Papers published on a yearly basis
Papers
TL;DR: In this article, the experimental techniques of single-molecule fluorescence spectroscopy and microscopy with emphasis on studies at room temperature where the same single molecule is studied for an extended period.
Abstract: Optical spectroscopy at the ultimate limit of a single molecule has grown over the past dozen years into a powerful technique for exploring the individual nanoscale behavior of molecules in complex local environments. Observing a single molecule removes the usual ensemble average, allowing the exploration of hidden heterogeneity in complex condensed phases as well as direct observation of dynamical state changes arising from photophysics and photochemistry, without synchronization. This article reviews the experimental techniques of single-molecule fluorescence spectroscopy and microscopy with emphasis on studies at room temperature where the same single molecule is studied for an extended period. Key to successful single-molecule detection is the need to optimize signal-to-noise ratio, and the physical parameters affecting both signal and noise are described in detail. Four successful microscopic methods including the wide-field techniques of epifluorescence and total internal reflection, as well as confocal and near-field optical scanning microscopies are described. In order to extract the maximum amount of information from an experiment, a wide array of properties of the emission can be recorded, such as polarization, spectrum, degree of energy transfer, and spatial position. Whatever variable is measured, the time dependence of the parameter can yield information about excited state lifetimes, photochemistry, local environmental fluctuations, enzymatic activity, quantum optics, and many other dynamical effects. Due to the breadth of applications now appearing, single-molecule spectroscopy and microscopy may be viewed as useful new tools for the study of dynamics in complex systems, especially where ensemble averaging or lack of synchronization may obscure the details of the process under study.
966 citations
TL;DR: In this article, a Bayesian statistical model is proposed that combines information from a multimodel ensemble of atmosphere-ocean general circulation models and observations to determine probability distributions of future temperature change on a regional scale.
Abstract: A Bayesian statistical model is proposed that combines information from a multimodel ensemble of atmosphere–ocean general circulation models (AOGCMs) and observations to determine probability distributions of future temperature change on a regional scale. The posterior distributions derived from the statistical assumptions incorporate the criteria of bias and convergence in the relative weights implicitly assigned to the ensemble members. This approach can be considered an extension and elaboration of the reliability ensemble averaging method. For illustration, the authors consider the output of mean surface temperature from nine AOGCMs, run under the A2 emission scenario from the Synthesis Report on Emission Scenarios (SRES), for boreal winter and summer, aggregated over 22 land regions and into two 30-yr averages representative of current and future climate conditions. The shapes of the final probability density functions of temperature change vary widely, from unimodal curves for regions where...
717 citations
TL;DR: In this article, a general classification of two-phase flows and a number of possible ways to formulate two-fluid models are discussed, and a general procedure to develop such a model is presented.
545 citations
TL;DR: This work found that ensemble averaging was found to be effective in controlling nonlinear instability, and the mysterious hidden layer could be given a phase space interpretation, and spectral analysis aided in understanding the nonlinear NN relat...
Abstract: Empirical or statistical methods have been introduced into meteorology and oceanography in four distinct stages: 1) linear regression (and correlation), 2) principal component analysis (PCA), 3) canonical correlation analysis, and recently 4) neural network (NN) models. Despite the great popularity of the NN models in many fields, there are three obstacles to adapting the NN method to meteorology–oceanography, especially in large-scale, low-frequency studies: (a) nonlinear instability with short data records, (b) large spatial data fields, and (c) difficulties in interpreting the nonlinear NN results. Recent research shows that these three obstacles can be overcome. For obstacle (a), ensemble averaging was found to be effective in controlling nonlinear instability. For (b), the PCA method was used as a prefilter for compressing the large spatial data fields. For (c), the mysterious hidden layer could be given a phase space interpretation, and spectral analysis aided in understanding the nonlinear NN relat...
475 citations
TL;DR: Serial use of partial least-squares, PLS, regression and a genetic algorithm, GA, is used to perform data reduction and identify the manifold of top 3D-QSAR models for a training set.
Abstract: 4D-QSAR analysis incorporates conformational and alignment freedom into the development of 3D-QSAR models for training sets of structure−activity data by performing ensemble averaging, the fourth “dimension”. The descriptors in 4D-QSAR analysis are the grid cell (spatial) occupancy measures of the atoms composing each molecule in the training set realized from the sampling of conformation and alignment spaces. Grid cell occupancy descriptors can be generated for any atom type, group, and/or model pharmacophore. A single “active” conformation can be postulated for each compound in the training set and combined with the optimal alignment for use in other molecular design applications including other 3D-QSAR methods. The influence of the conformational entropy of each compound on its activity can be estimated. Serial use of partial least-squares, PLS, regression and a genetic algorithm, GA, is used to perform data reduction and identify the manifold of top 3D-QSAR models for a training set. The unique manifo...
414 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 24 |
| 2020 | 33 |
| 2019 | 26 |
| 2018 | 23 |
| 2017 | 22 |
| 2016 | 30 |