Contribution of the double layer to transient faradaic processes: implications for hydrodynamic modulated voltammetry of nanostructures

The electrochemistry of Pt nanostructured electrodes is investigated using hydrodynamic modulated voltammetry (HMV). Here a liquid crystal templating process is used to produce platinum-modified electrodes with a range of surface areas (roughness factor 42.4-280.8). The electroreduction of molecular oxygen at these nanostructured platinum surfaces is used to demonstrate the ability of HMV to discriminate between faradaic and nonfaradaic electrode reactions. The HMV approach shows that the reduction of molecular oxygen experiences considerable signal loss within the high pseudocapacitive region of the voltammetry. Evidence for the contribution of the double layer to transient mass transfer events is presented. In addition, a model circuit and appropriate theoretical analysis are used to illustrate the transient responses of a time variant faradaic component. This in conjunction with the experimental evidence shows that, far from being a passive component in this system, the double layer can contribute to HMV faradaic reactions under certain conditions.

Protein kinase C down-regulation, and not transient activation, correlates with melanocyte growth

The nontumorigenic, immortal line of murine melanocytes, Mel-ab, requires the continual presence of biologically active phorbol esters for growth (R. E. Wilson et al., Cancer Res., 49: 711–716, 1989). Comparable treatments of B16 murine melanoma cells result in partial inhibition of cell proliferation. The role of protein kinase C (PKC) in the modulation of growth of cells from these two melanocytic cell lines has been investigated. Significant levels of PKC were present in quiescent Mel-ab cells as determined by Western blotting, whereas no immunoreactive protein was detected in cell extracts from either proliferating Mel-ab or B16.F1 cells. Phosphorylation of a Mr 80,000 protein, which by one- and two-dimensional gel analysis comigrated with the known Mr 80,000 protein substrate of PKC in fibroblasts, was induced in 12-O-tetradecanoylphorbol-13-acetate-stimulated quiescent Mel-ab cells but not in proliferating Mel-ab cells or B16.F1 melanoma cells. Direct measurement of PKC activity in these cells demonstrated a 10-fold greater level of activity in quiescent Mel-ab cells (262 ± 50 pmol/min/mg SD) compared with growing cells (22.8 ± 11.8 pmol/min/mg SD). An intermediate level of activity was detected in proliferating B16.F1 melanoma cells (148.5 ± 20.4 pmol/min/mg SD). The subcellular distribution of PKC was dependent upon the growth state of the cells such that quiescent Mel-ab cells displayed a higher level of activity in the cytosol, whereas growing Melab cells displayed greater activity in the particulate fraction. Like many other transformed lines, B16.F1 melanoma cells constitutively expressed the majority of enzyme activity in the particulate fraction. Measurement of [3H]phorbol ester binding in intact cells paralleled the PKC activation data such that quiescent Mel-ab cells displayed binding of 1612 ± 147 cpm/106 cells, whereas proliferating Mel-ab and B16.F1 melanoma cells displayed binding of 652 ± 28 and 947 ± 81 cpm/106 cells, respectively. Membrane-permeant diacylglycerol analogues, which activated but did not down-regulate PKC, were devoid of growth-stimulating effects on melanocytes, even in the presence of the specific diacylglycerol kinase inhibitor, R59022. Together, these data show that PKC down-regulation, and not activation, correlates with the growth of melanocytes in culture.

Numerical modeling of the propagation environment in the atmospheric boundary layer over the Persian Gulf

Strong vertical gradients at the top of the atmospheric boundary layer affect the propagation of electromagnetic waves and can produce radar ducts. A three-dimensional, time-dependent, nonhydrostatic numerical model was used to simulate the propagation environment in the atmosphere over the Persian Gulf when aircraft observations of ducting had been made. A division of the observations into high- and low-wind cases was used as a framework for the simulations. Three sets of simulations were conducted with initial conditions of varying degrees of idealization and were compared with the observations taken in the Ship Antisubmarine Warfare Readiness/Effectiveness Measuring (SHAREM-115) program. The best results occurred with the initialization based on a sounding taken over the coast modified by the inclusion of data on low-level atmospheric conditions over the Gulf waters. The development of moist, cool, stable marine internal boundary layers (MIBL) in air flowing from land over the waters of the Gulf was simulated. The MIBLs were capped by temperature inversions and associated lapses of humidity and refractivity. The low-wind MIBL was shallower and the gradients at its top were sharper than in the high-wind case, in agreement with the observations. Because it is also forced by land–sea contrasts, a sea-breeze circulation frequently occurs in association with the MIBL. The size, location, and internal structure of the sea-breeze circulation were realistically simulated. The gradients of temperature and humidity that bound the MIBL cause perturbations in the refractivity distribution that, in turn, lead to trapping layers and ducts. The existence, location, and surface character of the ducts were well captured. Horizontal variations in duct characteristics due to the sea-breeze circulation were also evident. The simulations successfully distinguished between high- and low-wind occasions, a notable feature of the SHAREM-115 observations. The modeled magnitudes of duct depth and strength, although leaving scope for improvement, were most encouraging.

Particle swarm optimization aided orthogonal forward regression for unified data modeling

We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density function estimation. A particle swarm optimization (PSO) aided orthogonal forward regression (OFR) algorithm based on leave-one-out (LOO) criteria is developed to construct parsimonious radial basis function (RBF) networks with tunable nodes. Each stage of the construction process determines the center vector and diagonal covariance matrix of one RBF node by minimizing the LOO statistics. For regression applications, the LOO criterion is chosen to be the LOO mean square error, while the LOO misclassification rate is adopted in two-class classification applications. By adopting the Parzen window estimate as the desired response, the unsupervised density estimation problem is transformed into a constrained regression problem. This PSO aided OFR algorithm for tunable-node RBF networks is capable of constructing very parsimonious RBF models that generalize well, and our analysis and experimental results demonstrate that the algorithm is computationally even simpler than the efficient regularization assisted orthogonal least square algorithm based on LOO criteria for selecting fixed-node RBF models. Another significant advantage of the proposed learning procedure is that it does not have learning hyperparameters that have to be tuned using costly cross validation. The effectiveness of the proposed PSO aided OFR construction procedure is illustrated using several examples taken from regression and classification, as well as density estimation applications.

Modeling entangled dynamics: comparison between stochastic single-chain and multichain models

To test the effectiveness of stochastic single-chain models in describing the dynamics of entangled polymers, we systematically compare one such model; the slip-spring model; to a multichain model solved using stochastic molecular dynamics(MD) simulations (the Kremer-Grest model). The comparison involves investigating if the single-chain model can adequately describe both a microscopic dynamical and a macroscopic rheological quantity for a range of chain lengths. Choosing a particular chain length in the slip-spring model, the parameter values that best reproduce the mean-square displacement of a group of monomers is determined by fitting toMDdata. Using the same set of parameters we then test if the predictions of the mean-square displacements for other chain lengths agree with the MD calculations. We followed this by a comparison of the time dependent stress relaxation moduli obtained from the two models for a range of chain lengths. After identifying a limitation of the original slip-spring model in describing the static structure of the polymer chain as seen in MD, we remedy this by introducing a pairwise repulsive potential between the monomers in the chains. Poor agreement of the mean-square monomer displacements at short times can be rectified by the use of generalized Langevin equations for the dynamics and resulted in significantly improved agreement.

Ultrafast charge separation in a photoreactive rhenium-appended porphyrin assembly monitored by picosecond transient infrared spectroscopy

Rhenium(bipyridine)(tricarbonyl)(picoline) units have been linked covalently to tetraphenylmetalloporphyrins of magnesium and zinc via an amide bond between the bipyridine and one phenyl substituent of the porphyrin. The resulting complexes, abbreviated as [Re(CO)(3)(Pic)Bpy-MgTPP][OTf] and [Re(CO)(3)(Pic)Bpy-ZnTPP][OTf], exhibit no signs of electronic interaction between the Re(CO)(3)(bpy) units and the metalloporphyrin units in their ground states. However, emission spectroscopy reveals solvent-dependent quenching of porphyrin emission on irradiation into the long-wavelength absorption bands localized on the porphyrin. The characteristics of the excited states have been probed by picosecond time-resolved absorption (TRVIS) spectroscopy and time-resolved infrared (TRIR) spectroscopy in nitrile solvents. The presence of the charge-separated state involving electron transfer from MgTPP or ZnTPP to Re(bpy) is signaled in the TRIR spectra by a low-frequency shift in the nu(CO) bands of the Re(CO)(3) moiety similar to that observed by spectroelectrochemical reduction. Long-wavelength excitation of [Re(CO)(3)(Pic)Bpy-MTPP][OTf] results in characteristic TRVIS spectra of the S-1 state of the porphyrin that decay with a time constant of 17 ps (M = Mg) or 24 ps (M = Zn). The IR bands of the CS state appear on a time scale of less than 1 ps (Mg) or ca. 5 ps (Zn) and decay giving way to a vibrationally excited (i.e., hot) ground state via back electron transfer. The IR bands of the precursors recover with a time constant of 35 ps (Mg) or 55 ps (Zn). The short lifetimes of the charge-transfer states carry implications for the mechanism of reaction in the presence of triethylamine.

Generalized neurofuzzy network modeling algorithms using Bezier-Bernstein polynomial functions and additive decomposition

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bezier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bezier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bezier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bezier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

Optimal piecewise locally linear modeling

Associative memory networks such as Radial Basis Functions, Neurofuzzy and Fuzzy Logic used for modelling nonlinear processes suffer from the curse of dimensionality (COD), in that as the input dimension increases the parameterization, computation cost, training data requirements, etc. increase exponentially. Here a new algorithm is introduced for the construction of a Delaunay input space partitioned optimal piecewise locally linear models to overcome the COD as well as generate locally linear models directly amenable to linear control and estimation algorithms. The training of the model is configured as a new mixture of experts network with a new fast decision rule derived using convex set theory. A very fast simulated reannealing (VFSR) algorithm is utilized to search a global optimal solution of the Delaunay input space partition. A benchmark non-linear time series is used to demonstrate the new approach.

The application of Prony’s method to time-domain waveform data modeling in the presence of noise

In this paper,the Prony's method is applied to the time-domain waveform data modelling in the presence of noise.The following three problems encountered in this work are studied:(1)determination of the order of waveform;(2)de-termination of numbers of multiple roots;(3)determination of the residues.The methods of solving these problems are given and simulated on the computer.Finally,an output pulse of model PG-10N signal generator and the distorted waveform obtained by transmitting the pulse above mentioned through a piece of coaxial cable are modelled,and satisfactory results are obtained.So the effectiveness of Prony's method in waveform data modelling in the presence of noise is confirmed.

Modeling camera orientation and 3D structure from a sequence of images taken by a perambulating commercial video camera

In this paper we report the degree of reliability of image sequences taken by off-the-shelf TV cameras for modeling camera rotation and reconstructing 3D structure using computer vision techniques. This is done in spite of the fact that computer vision systems usually use imaging devices that are specifically designed for the human vision. Our scenario consists of a static scene and a mobile camera moving through the scene. The scene is any long axial building dominated by features along the three principal orientations and with at least one wall containing prominent repetitive planar features such as doors, windows bricks etc. The camera is an ordinary commercial camcorder moving along the axial axis of the scene and is allowed to rotate freely within the range +/- 10 degrees in all directions. This makes it possible that the camera be held by a walking unprofessional cameraman with normal gait, or to be mounted on a mobile robot. The system has been tested successfully on sequence of images of a variety of structured, but fairly cluttered scenes taken by different walking cameramen. The potential application areas of the system include medicine, robotics and photogrammetry.

Methods for kinematic modeling of biological and robotic systems

The main objective is to develop methods that automatically generate kinematic models for the movements of biological and robotic systems. Two methods for the identification of the kinematics are presented. The first method requires the elimination of the displacement variables that cannot be measured while the second method attempts to estimate the changes in these variables. The methods were tested using a planar two-revolute-joint linkage. Results show that the model parameters obtained agree with the actual parameters to within 5%. Moreover, the methods were applied to model head and neck movements in the sagittal plane. The results indicate that these movements are well modeled by a two-revolute-joint system. A spatial three-revolute-joint model was also discussed and tested.