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At least 181 records · Page 10Linked to original sources
PubMed2005

Far-field optical microscopy of single metal nanoparticles.

Individual noble-metal particles, with sizes ranging from a few tenths to some hundreds of nanometers, can now be detected by far-field optics. Single-particle microscopy gives access to inhomogeneity, distributions, and fluctuations, which were previously hidden in ensemble experiments. Scattering methods rely on dark-field illumination, spectral signatures of the metal particles, or both. More advanced techniques provide high sensitivity and improved selectivity with respect to other scatterers by isolating metal-specific signals, for example the refractive index change due to heating of the environment by a pump beam or the time-resolved optical response of the particle to a short pump pulse. We review and compare linear and nonlinear methods in far-field optical microscopy that have reached the single-particle regime by means of scattered light, thermal effects, photoluminescence, or nonlinear frequency generation.

Journal Article↗
PubMed2005

Monte Carlo simulations of gas solubility in the ionic liquid 1-n-butyl-3-methylimidazolium hexafluorophosphate.

The Henry's constants of water, carbon dioxide, ethane, ethene, methane, oxygen, and nitrogen are computed in the ionic liquid 1-n-butyl-3-methylimidazolium hexafluorophosphate ([bmim][PF(6)]) using test particle insertion and expanded ensemble Monte Carlo methods. The partial molar enthalpy and partial molar entropy of solvation are also computed for water, carbon dioxide, and oxygen. The results from the simulations are compared against experimental data from the literature. In addition, the accuracy and precision of the two methods in determining the Henry's constant are examined. Local organization of the ionic liquid around a solute molecule is analyzed, and the interactions responsible for the experimentally observed solubility trends are identified.

Journal Article↗
PubMed2004

Computer simulation study of the global phase behavior of linear rigid Lennard-Jones chain molecules: comparison with flexible models.

The global phase behavior (i.e., vapor-liquid and fluid-solid equilibria) of rigid linear Lennard-Jones (LJ) chain molecules is studied. The phase diagrams for three-center and five-center rigid model molecules are obtained by computer simulation. The segment-segment bond lengths are L = sigma, so that models of tangent monomers are considered in this study. The vapor-liquid equilibrium conditions are obtained using the Gibbs ensemble Monte Carlo method and by performing isobaric-isothermal NPT calculations at zero pressure. The phase envelopes and critical conditions are compared with those of flexible LJ molecules of tangent segments. An increase in the critical temperature of linear rigid chains with respect to their flexible counterparts is observed. In the limit of infinitely long chains the critical temperature of linear rigid LJ chains of tangent segments seems to be higher than that of flexible LJ chains. The solid-fluid equilibrium is obtained by Gibbs-Duhem integration, and by performing NPT simulations at zero pressure. A stabilization of the solid phase, an increase in the triple-point temperature, and a widening of the transition region are observed for linear rigid chains when compared to flexible chains with the same number of segments. The triple-point temperature of linear rigid LJ chains increases dramatically with chain length. The results of this work suggest that the fluid-vapor transition could be metastable with respect to the fluid-solid transition for chains with more than six LJ monomer units.

Journal Article↗
PubMed2005

Simulations of vapor water clusters at vapor-liquid equilibrium.

The Gibbs-ensemble Monte Carlo methods based on the extended single point charge [H. J. C. Berendsen, J. R. Grigera, and T. P. Straatsma, J. Phys. Chem. 91, 6269 (1987)] potential-energy surface have been used to study the clustering of vapor phase water under vapor-liquid equilibrium conditions between 300 and 600 K. It is seen that the number of clusters, as well as the cluster size, increase with temperature. This is primarily due to the increase in vapor density that accompanies the temperature increase at equilibrium. In addition, due to entropic effects, the percentage of clusters that have linear (or open) topologies increases with temperature and dominates over the minimum-energy cyclic topologies at the temperatures studied here. These results are insensitive to the number of molecules used in the simulations and the criterion used to define a water cluster.

Journal Article↗
PubMed2006

Free energy of the solid C60 fullerene orientational order-disorder transition.

The free energies of the orientationally ordered crystal phase of C60 at low temperatures and the disordered crystal phase at high temperatures are calculated to an accuracy of +/-0.05 kJ/mol using the expanded ensemble Monte Carlo method with the potential model of Sprik et al. [J. Phys. Chem. 96, 2027 (1992)]. The order-disorder transition temperature at zero pressure is determined directly from these free energies, and is found to be consistent with the abrupt changes in configurational energy and unit cell size also found in simulation. A modification of the potential results in predictions of the transition temperature of 257 K and the entropy change of 18.1 J/mol K at this transition, which are in good agreement with the experimental values of 260 K and 19 J/mol K, respectively. The orientational distinguishability in the ordered phase and the indistinguishability in the disordered phase lead to a contribution to the entropy difference of k ln 60, with 60 being the symmetry number of C60. This quantum mechanical correction is important for the accurate prediction of the phase transition properties of the C60 crystals.

Journal Article↗
PubMed1999

Sorted averaging--principle and application to auditory brainstem responses.

A new averaging method for evoked potentials, called sorted averaging, is presented. The method requires an ensemble of sweeps stored in memory and is based on the principle of interchangeability of individual sweeps within this ensemble. Sorted averaging is applied by sorting all sweeps according to their estimated background noise and successive averaging of this sorted ensemble, starting with low-noise sweeps. Signal-to-noise power ratio (SNR2) is estimated by calculating the inverse single point variance (Elberling & Don, 1984). This SNR2 estimate increases linearly with the number of sweeps for standard averaging and shows a clear maximum for sorted averaging. Auditory brainstem responses to click stimuli at 70 dB nHL in 20 normal hearing subjects were recorded and 4000 individual sweeps during each run were stored for analysis. In an off-line analysis, SNR2 for standard averaging with 10 microV artefact rejection, for weighted averaging and for sorted averaging were calculated. Sorted averaging was found to yield a significantly higher SNR2.

Acoustic Stimulation↗
PubMed2000

Correlation of stress and structure in a simple fluid confined to a pore with furrowed walls

A Lennard-Jones (12,6) film confined between two furrowed walls was simulated by the grand canonical ensemble Monte Carlo method. The walls are constructed by gouging triangular grooves in planar substrates that are structureless on the molecular scale. The furrows are infinitely long in one transverse direction (y) and of nanoscopic width (s(x)) and depth (D). The furrows in the two walls are maintained parallel and in register. The diagonal components of the stress tensor (T(alphaalpha), alpha=x,y,z) are computed as functions of D and the separation between the substrates (s(z)) at fixed temperature, chemical potential, and s(x). The T(alphaalpha) for the film between the furrowed walls are strongly shifted from their counterparts for the film between flat (i.e., planar) walls. The shifts are rationalized in terms of the structure of the film, which becomes more ordered as the furrows deepen and the packing of film molecules becomes more restricted in the two dimensions normal to the y direction. The results demonstrate the profound impact of the coupling between molecular and nanoscopic scales on the properties of geometrically constrained fluids.

Journal Article↗
PubMed2001

Twist-averaged boundary conditions in continuum quantum Monte Carlo algorithms.

We develop and test Quantum Monte Carlo algorithms that use a"twist" or a phase in the wave function for fermions in periodic boundary conditions. For metallic systems, averaging over the twist results in faster convergence to the thermodynamic limit than periodic boundary conditions for properties involving the kinetic energy and has the same computational complexity. We determine exponents for the rate of convergence to the thermodynamic limit for the components of the energy of coulomb systems. We show results with twist averaged variational Monte Carlo on free particles, the Stoner model and the electron gas using Hartree-Fock, Slater-Jastrow, and three-body and backflow wave function. We also discuss the use of twist averaging in the grand canonical ensemble, and numerical methods to accomplish the twist averaging.

Journal Article↗
PubMed2005

Automated detection of prostatic adenocarcinoma from high-resolution ex vivo MRI.

Prostatic adenocarcinoma is the most commonly occurring cancer among men in the United States, second only to skin cancer. Currently, the only definitive method to ascertain the presence of prostatic cancer is by trans-rectal ultrasound (TRUS) directed biopsy. Owing to the poor image quality of ultrasound, the accuracy of TRUS is only 20%-25%. High-resolution magnetic resonance imaging (MRI) has been shown to have a higher accuracy of prostate cancer detection compared to ultrasound. Consequently, several researchers have been exploring the use of high resolution MRI in performing prostate biopsies. Visual detection of prostate cancer, however, continues to be difficult owing to its apparent lack of shape, and the fact that several malignant and benign structures have overlapping intensity and texture characteristics. In this paper, we present a fully automated computer-aided detection (CAD) system for detecting prostatic adenocarcinoma from 4 Tesla ex vivo magnetic resonance (MR) imagery of the prostate. After the acquired MR images have been corrected for background inhomogeneity and nonstandardness, novel three-dimensional (3-D) texture features are extracted from the 3-D MRI scene. A Bayesian classifier then assigns each image voxel a "likelihood" of malignancy for each feature independently. The "likelihood" images generated in this fashion are then combined using an optimally weighted feature combination scheme. Quantitative evaluation was performed by comparing the CAD results with the manually ascertained ground truth for the tumor on the MRI. The tumor labels on the MR slices were determined manually by an expert by visually registering the MR slices with the corresponding regions on the histology slices. We evaluated our CAD system on a total of 33 two-dimensional (2-D) MR slices from five different 3-D MR prostate studies. Five slices from two different glands were used for training. Our feature combination scheme was found to outperform the individual texture features, and also other popularly used feature combination methods, including AdaBoost, ensemble averaging, and majority voting. Further, in several instances our CAD system performed better than the experts in terms of accuracy, the expert segmentations being determined solely from visual inspection of the MRI data. In addition, the intrasystem variability (changes in CAD accuracy with changes in values of system parameters) was significantly lower than the corresponding intraobserver and interobserver variability. CAD performance was found to be very similar for different training sets. Future work will focus on extending the methodology to guide high-resolution MRI-assisted in vivo prostate biopsies.

Adenocarcinoma↗
PubMed1990

Inclusion of thermal motion in crystallographic structures by restrained molecular dynamics.

A protein crystal structure is usually described by one single structure, which largely omits the dynamical behavior of the molecule. A molecular dynamics method with a time-averaged crystallographic restraint was used to overcome this limitation. This method yields an ensemble of structures in which all possible thermal motions are allowed, that is, in additional to isotropic distributions, anisotropic and anharmonic positional distributions occur as well. In the case of bovine pancreatic phospholipase A2, this description markedly improves agreement with the observed x-ray diffraction data compared to the results of the classical one-model structure description. Time-averaged crystallographically restrained molecular dynamics reveals large mobilities in the loops involved in lipid bilayer association.

Animals↗
PubMed1999

Illuminating single molecules in condensed matter.

Efficient collection and detection of fluorescence coupled with careful minimization of background from impurities and Raman scattering now enable routine optical microscopy and study of single molecules in complex condensed matter environments. This ultimate method for unraveling ensemble averages leads to the observation of new effects and to direct measurements of stochastic fluctuations. Experiments at cryogenic temperatures open new directions in molecular spectroscopy, quantum optics, and solid-state dynamics. Room-temperature investigations apply several techniques (polarization microscopy, single-molecule imaging, emission time dependence, energy transfer, lifetime studies, and the like) to a growing array of biophysical problems where new insight may be gained from direct observations of hidden static and dynamic inhomogeneity.

Chemistry, Physical↗
PubMed2005

Determination of the interfacial water content in protein-protein complexes from free energy simulations.

The question as to how many tightly or weakly bound water molecules are located in interfaces between protein-protein complex constituents is addressed from a phase equilibrium point of view by developing a theory in the canonical ensemble. A fast method based on free energy simulations is described for computing the number of water molecules in the interface regions. Results are given for 211 interfacial cavities of 26 antigen-antibody complexes for which experimentally determined structures are found in the Protein Data Bank. The accuracy of the method is assessed and the computational water content is compared with experimental data, revealing the amount of water molecules not resolved by experimental approaches.

Antigen-Antibody Complex↗
PubMed1976

A method for the treatment of metamerism in colorimetry.

All of the spectrally different colors that match according to an observer form a metamer ensemble. We present a new method to generate the metamer ensembles for both direct light and reflecting-surface-color problems. The method is based on the properties of particular metameric functions (the simple elements) and is particularly appropriate for treating problems of theoretical limits of metamerism. The method is illustrated with several practical examples and is compared with previously known methods.

Color Perception↗
PubMed2002

Designability of alpha-helical proteins.

A typical protein structure is a compact packing of connected alpha-helices and/or beta-strands. We have developed a method for generating the ensemble of compact structures a given set of helices and strands can form. The method is tested on structures composed of four alpha-helices connected by short turns. All such natural four-helix bundles that are connected by short turns seen in nature are reproduced to closer than 3.6 A per residue within the ensemble. Because structures with no natural counterpart may be targets for ab initio structure design, the designability of each structure in the ensemble-defined as the number of sequences with that structure as their lowest-energy state-is evaluated using a hydrophobic energy. For the case of four alpha-helices, a small set of highly designable structures emerges, most of which have an analog among the known four-helix fold families; however, several packings and topologies with no analogs in protein database are identified.

Amino Acid Sequence↗
PubMed2005

A method and software for segmentation of anatomic object ensembles by deformable m-reps.

Deformable shape models (DSMs) comprise a general approach that shows great promise for automatic image segmentation. Published studies by others and our own research results strongly suggest that segmentation of a normal or near-normal object from 3D medical images will be most successful when the DSM approach uses (1) knowledge of the geometry of not only the target anatomic object but also the ensemble of objects providing context for the target object and (2) knowledge of the image intensities to be expected relative to the geometry of the target and contextual objects. The segmentation will be most efficient when the deformation operates at multiple object-related scales and uses deformations that include not just local translations but the biologically important transformations of bending and twisting, i.e., local rotation, and local magnification. In computer vision an important class of DSM methods uses explicit geometric models in a Bayesian statistical framework to provide a priori information used in posterior optimization to match the DSM against a target image. In this approach a DSM of the object to be segmented is placed in the target image data and undergoes a series of rigid and nonrigid transformations that deform the model to closely match the target object. The deformation process is driven by optimizing an objective function that has terms for the geometric typicality and model-to-image match for each instance of the deformed model. The success of this approach depends strongly on the object representation, i.e., the structural details and parameter set for the DSM, which in turn determines the analytic form of the objective function. This paper describes a form of DSM called m-reps that has or allows these properties, and a method of segmentation consisting of large to small scale posterior optimization of m-reps. Segmentation by deformable m-reps, together with the appropriate data representations, visualizations, and user interface, has been implemented in software that accomplishes 3D segmentations in a few minutes. Software for building and training models has also been developed. The methods underlying this software and its abilities are the subject of this paper.

Algorithms↗
PubMed1987

Protein kinase assay by paper-trichloroacetic acid method: high performance using phosphocellulose paper and washing an ensemble of samples on flat sheets.

Phosphocellulose paper has been found to be the paper of choice in assaying protein kinase activities using [gamma-32P]ATP by the trichloroacetic acid method of precipitation and washing. A study of binding of ATP of increasing concentrations at constant specific activity with Whatman 3MM or ATP-coated Whatman 3 MM papers (in vogue) versus phosphocellulose paper (proposed here) has shown that the latter has the least affinity for ATP when washing is done with either trichloracetic acid or trichloroacetic acid containing pyrophosphate. In an experiment where the placental cytosolic protein kinase was serially diluted, the phosphocellulose paper was found to give higher signal/noise ratios at all dilutions studied compared to the other two papers. With regard to the technological side of washing the papers, we have found that the traditional method of cutting papers into small squares before loading the samples is perhaps not the best. Instead, we propose the use of a flat sheet matrix for loading the samples because this method ensures uniformity of washing among the samples while shaking is performed on a simple shaker. In addition, the whole paper matrix can provide an almost instantaneous autoradiogram of hundreds of samples facilitating biochemical experimentation with protein kinases.

Adenosine Triphosphate↗
PubMedDate not supplied

Neural network studies. 4. Introduction to associative neural networks.

Associative neural network (ASNN) represents a combination of an ensemble of feed-forward neural networks and the k-nearest neighbor technique. This method uses the correlation between ensemble responses as a measure of distance amid the analyzed cases for the nearest neighbor technique. This provides an improved prediction by the bias correction of the neural network ensemble. An associative neural network has a memory that can coincide with the training set. If new data becomes available, the network further improves its predictive ability and provides a reasonable approximation of the unknown function without a need to retrain the neural network ensemble. This feature of the method dramatically improves its predictive ability over traditional neural networks and k-nearest neighbor techniques, as demonstrated using several artificial data sets and a program to predict lipophilicity of chemical compounds. Another important feature of ASNN is the possibility to interpret neural network results by analysis of correlations between data cases in the space of models. It is shown that analysis of such correlations makes it possible to provide "property-targeted" clustering of data. The possible applications and importance of ASNN in drug design and medicinal and combinatorial chemistry are discussed. The method is available on-line at http://www.vcclab.org/lab/asnn.

Neural Networks, Computer↗
PubMed1994

An enhanced approach to adaptive processing of the brain stem auditory evoked potential.

The present paper describes an adaptive signal enhancer (ASE) method for improving signal-to-noise ratio (SNR) and also for tracking the variation of brain-stem auditory evoked potential (BAEP). The enhancer has two inputs: a primary input which is the original data to be processed, consisting of signal badly corrupted by noise, and a reference input. A method called dynamic averaging (DA) is introduced to obtain the reference input. The improved reference signal allows closer tracking of evoked potential in each subsequent trial. For BAEP measurement in human, the SNR is typically very low. It requires about 200 ensembles to generate the reference input acceptable for ASE, and tracking of the variation of BAEP can be obtained satisfactorily. Our results show that while ensemble averaging is still needed, the total number of ensembles is greatly reduced. The adaptive method thus reduces the time of measurement for BAEP compared with the conventional method of ensemble averaging.

Electricity↗