Time-dependent R -matrix theory for ultrafast atomic processes

We describe an ab initio nonperturbative time-dependent R-matrix theory for ultrafast atomic processes. This theory enables investigations of the interaction of few-femtosecond and -attosecond pulse lasers with complex multielectron atoms and atomic ions. A derivation and analysis of the basic equations are given, which propagate the atomic wave function in the presence of the laser field forward in time in the internal and external R-matrix regions. To verify the accuracy of the approach, we investigate two-photon ionization of Ne irradiated by an intense laser pulse and compare current results with those obtained using the R-matrix Floquet method and an alternative time-dependent method. We also verify the capability of the current approach by applying it to the study of two-dimensional momentum distributions of electrons ejected from Ne due to irradiation by a sequence of 2 as light pulses in the presence of a 780 nm laser field.

Characterisation of fluidised bed granulation processes using in situ Raman spectroscopy

Previous work by the authors Walker et al. [2007b. Fluidised bed characterisation using Raman spectroscopy: applications to pharmaceutical processing. Chemical Engineering Science 62, 3832–3838] illustrated that Raman spectroscopy could be used to provide 3-D maps of the concentration and chemical structure of particles in motion in a fluidised bed, within a relatively short (120 s) time window. Moreover, we reported that the technique, as outlined, has the potential to give detailed in-situ information on how the structure and composition of granules/powders within the fluidised bed (dryer or granulator) vary with the position and evolve with time. In this study we extended the original work by shortening the time window of the Raman spectroscopic analysis to 10 s, which has allowed the in-situ real-time characterisation of a fluidised bed granulation process. Here we show an important new use of the technique which allows in-situ measurement of the composition of the material within the fluidised bed in three spatial dimensions and as a function of time. This is achieved by recording Raman spectra using a probe positioned within the fluidised bed on a long-travel x–y–z stage. In these experiments the absolute Raman intensity is used to provide a direct measure of the amount of any given material in the probed volume, i.e. a particle density. Particle density profiles have been calculated over the granulation time and show how the volume of the fluidised bed decreases with an increase mean granule size. The Raman spectroscopy analysis indicated that nucleation/coalescence in this co-melt fluidised hot melt granulation system occurred over a relatively short time frame (t<30 s). The Raman spectroscopic technique demonstrated accurate correlation with independent granulation experiments which provided particle size distribution analysis. The similarity of the data indicates that the Raman spectra accurately represent solids ratios within the bed, and thus the techniques quantitative capabilities for future use in the pharmaceutical industry.

Convergence acceleration of the doubly periodic Green's function for the analysis of thin wire arrays

A method is proposed to accelerate the evaluation of the Green's function of an infinite double periodic array of thin wire antennas. The method is based on the expansion of the Green's function into series corresponding to the propagating and evanescent waves and the use of Poisson and Kummer transformations enhanced with the analytic summation of the slowly convergent asymptotic terms. Unlike existing techniques the procedure reported here provides uniform convergence regardless of the geometrical parameters of the problem or plane wave excitation wavelength. In addition, it is numerically stable and does not require numerical integration or internal tuning parameters, since all necessary series are directly calculated in terms of analytical functions. This means that for nonlinear problem scenarios that the algorithm can be deployed without run time intervention or recursive adjustment within a harmonic balance engine. Numerical examples are provided to illustrate the efficiency and accuracy of the developed approach as compared with the Ewald method for which these classes of problems requires run time splitting parameter adaptation.

Adaptive data echo cancellation using cost function adaptation

For a digital echo canceller it is desirable to reduce the adaptation time, during which the transmission of useful data is not possible. LMS is a non-optimal algorithm in this case as the signals involved are statistically non-Gaussian. Walach and Widrow (IEEE Trans. Inform. Theory 30 (2) (March 1984) 275-283) investigated the use of a power of 4, while other research established algorithms with arbitrary integer (Pei and Tseng, IEEE J. Selected Areas Commun. 12(9)(December 1994) 1540-1547) or non-quadratic power (Shah and Cowan, IEE.Proc.-Vis. Image Signal Process. 142 (3) (June 1995) 187-191). This paper suggests that continuous and automatic, adaptation of the error exponent gives a more satisfactory result. The family of cost function adaptation (CFA) stochastic gradient algorithm proposed allows an increase in convergence rate and, an improvement of residual error. As special case the staircase CFA algorithm is first presented, then the smooth CFA is developed. Details of implementations are also discussed. Results of simulation are provided to show the properties of the proposed family of algorithms. (C) 2000 Elsevier Science B.V. All rights reserved.

A time-domain approach to the analysis and modeling of on-body propagation characteristics using synchronized measurements at 2.45 GHz

Modeling of on-body propagation channels is of paramount importance to those wishing to evaluate radio channel performance for wearable devices in body area networks (BANs). Difficulties in modeling arise due to the highly variable channel conditions related to changes in the user's state and local environment. This study characterizes these influences by using time-series analysis to examine and model signal characteristics for on-body radio channels in user stationary and mobile scenarios in four different locations: anechoic chamber, open office area, hallway, and outdoor environment. Autocorrelation and cross-correlation functions are reported and shown to be dependent on body state and surroundings. Autoregressive (AR) transfer functions are used to perform time-series analysis and develop models for fading in various on-body links. Due to the non-Gaussian nature of the logarithmically transformed observed signal envelope in the majority of mobile user states, a simple method for reproducing the failing based on lognormal and Nakagami statistics is proposed. The validity of the AR models is evaluated using hypothesis testing, which is based on the Ljung-Box statistic, and the estimated distributional parameters of the simulator output compared with those from experimental results.

Using time-to-contact information to assess potential collision modulates both visual and temporal prediction networks

Accurate estimates of the time-to-contact (TTC) of approaching objects are crucial for survival. We used an ecologically valid driving simulation to compare and contrast the neural substrates of egocentric (head-on approach) and allocentric (lateral approach) TTC tasks in a fully factorial, event-related fMRI design. Compared to colour control tasks, both egocentric and allocentric TTC tasks activated left ventral premotor cortex/frontal operculum and inferior parietal cortex, the same areas that have previously been implicated in temporal attentional orienting. Despite differences in visual and cognitive demands, both TTC and temporal orienting paradigms encourage the use of temporally predictive information to guide behaviour, suggesting these areas may form a core network for temporal prediction. We also demonstrated that the temporal derivative of the perceptual index tau (tau-dot) held predictive value for making collision judgements and varied inversely with activity in primary visual cortex (V1). Specifically, V1 activity increased with the increasing likelihood of reporting a collision, suggesting top-down attentional modulation of early visual processing areas as a function of subjective collision. Finally, egocentric viewpoints provoked a response bias for reporting collisions, rather than no-collisions, reflecting increased caution for head-on approaches. Associated increases in SMA activity suggest motor preparation mechanisms were engaged, despite the perceptual nature of the task.

Electrical and Rheological Percolation of PMMA/MWCNT Nanocomposites as a Function of CNT Geometry and Functionality

The ability of carbon nanotubes (CNTs) to reinforce and enhance the electrical conductivity of polymer matrices is a function of both the aspect ratio and surface chemistry of the CNTs. Hitherto, due to the variability in MWCNT synthesis methods it has not been possible to study the effect of MWCNT aspect ratio and functionality on polymer composite properties. This paper was the first to report the correlation between MWCNT aspect ratio and functionality on the formation of electrical and rheological percolated networks. Furthermore, the fundamental ballistic conductance of MWCNTs made using arc discharge and chemical vapour deposition techniques was reported.

Gene-environment interactions and aging visual function: a classical twin study.

OBJECTIVE:
To elucidate the contribution of environmental versus genetic factors to the significant losses in visual function associated with normal aging.
DESIGN:
A classical twin study.
PARTICIPANTS:
Forty-two twin pairs (21 monozygotic and 21 dizygotic; age 57-75 years) with normal visual acuity recruited through the Australian Twin Registry.
METHODS:
Cone function was evaluated by establishing absolute cone contrast thresholds to flicker (4 and 14 Hz) and isoluminant red and blue colors under steady state adaptation. Adaptation dynamics were determined for both cones and rods. Bootstrap resampling was used to return robust intrapair correlations for each parameter.
MAIN OUTCOME MEASURES:
Psychophysical thresholds and adaptational time constants.
RESULTS:
The intrapair correlations for all color and flicker thresholds, as well as cone absolute threshold, were significantly higher in monozygotic compared with dizygotic twin pairs (P<0.05). Rod absolute thresholds (P = 0.28) and rod and cone recovery rate (P = 0.83; P = 0.79, respectively) did not show significant differences between monozygotic and dizygotic twins in their intrapair correlations, indicating that steady-state cone thresholds and flicker thresholds have a marked genetic contribution, in contrast with rod thresholds and adaptive processes, which are influenced more by environmental factors over a lifetime.
CONCLUSIONS:
Genes and the environment contribute differently to important neuronal processes in the retina and the role they may play in the decline in visual function as we age. Consequently, retinal structures involved in rod thresholds and adaptive processes may be responsive to appropriate environmental manipulation. Because the functions tested are commonly impaired in the early stages of age-related macular degeneration, which is known to have a multifactorial etiology, this study supports the view that pathogenic pathways early in the disease may be altered by appropriate environmental intervention.

Validity of a 1 minute walk test for children with cerebral palsy.

The concurrent validity of a 1 minute walk test at a child's maximum walking speed was assessed in children with bilateral spastic cerebral palsy (BSCP). The distance covered during the 1 minute walk test was compared with the children's gross motor function as assessed by the Gross Motor Function Measure (GMFM). Twenty-four male and 10 female children with CP (mean age 11y, range 4 to 16y) participated in the study. Gross Motor Function Classification System (GMFCS) levels were; level I (n=3), level II (n=17), level III (n=10), and level IV (n=4). Participants had clinical diagnoses of symmetrical diplegia (n=19), asymmetrical diplegia (n=14), and quadriplegia (n=1). Results showed a significant correlation between GMFM score and the distance covered during the 1 minute walk (r=0.92; p<0.001). There was also a significant decrease in the distance walked with increasing GMFCS level (p<0.001). We concluded that the 1 minute walk test is a valid measure for assessing functional ability in children with ambulatory BSCP. Its cost-effectiveness and user friendliness make it a potentially useful tool in the clinical setting. Further study needs to address its reliability and ability to detect change over time.

Psychophysical Function in Age-related Maculopathy

Age-related macular degeneration (AMD), the late stage of age-related maculopathy (ARM), is the leading cause of blind registration in developed Countries. The Visual loss in AMD occurs due to dysfunction and death of photoreceptors (rods and cones) secondary to an atrophic or a neovascular event. The psychophysical tests of vision, which depend on the functional status of the photoreceptors, may detect subtle alterations in the macula before morphological fundus changes are apparent ophthalmoscopically, and before traditional measures of visual acuity exhibit deterioration, and may be a useful tool for assessing and monitoring patients with ARM. Furthermore, worsening of these visual functions over time may reflect disease progression, and some of these, alone or iti combination with other parameters, may act as a prognostic indicator for identifying eyes at, risk for developing neovascular AMD. Lastly, psychophysical tests often correlate with subjective and relatively undefined symptoms in patients With early ARM, and may reflect limitation of daily activities for ARM patients. However, clinical studies investigating psychophysical function have largely been cross-sectional in nature, with small sample sizes, and lack consistency in terms Of the grading and classification of ARM. This article aims to comprehensively review the literature germane to psychophysical tests in ARM, and to furnish the reader with an insight into this complex area of research. (Surv Ophdialmol 54:167-210, 2009. (C) 2009 Elsevier Inc. All rights reserved.)

Genetic Algorithm Search for Predictive Patterns in Multidimensional Time Series

Based on an algorithm for pattern matching in character strings, we implement a pattern matching machine that searches for occurrences of patterns in multidimensional time series. Before the search process takes place, time series are encoded in user-designed alphabets. The patterns, on the other hand, are formulated as regular expressions that are composed of letters from these alphabets and operators. Furthermore, we develop a genetic algorithm to breed patterns that maximize a user-defined fitness function. In an application to financial data, we show that patterns bred to predict high exchange rates volatility in training samples retain statistically significant predictive power in validation samples.

Density-potential mapping in time-dependent density-functional theory

The key questions of uniqueness and existence in time-dependent density-functional theory are usually formulated only for potentials and densities that are analytic in time. Simple examples, standard in quantum mechanics, lead, however, to nonanalyticities. We reformulate these questions in terms of a nonlinear Schroedinger equation with a potential that depends nonlocally on the wave function.

Modeling Multivariate Interest Rates Using Time-Varying Copulas and Reducible Nonlinear Stochastic Differential Equations

We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein--Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe--Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. (JEL: C13, C32, G12) Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

Combined R-matrix eigenstate basis set and finite-difference propagation method for the time-dependent Schrodinger equation: The one-electron case

In this work we present the theoretical framework for the solution of the time-dependent Schrödinger equation (TDSE) of atomic and molecular systems under strong electromagnetic fields with the configuration space of the electron’s coordinates separated over two regions; that is, regions I and II. In region I the solution of the TDSE is obtained by an R-matrix basis set representation of the time-dependent wave function. In region II a grid representation of the wave function is considered and propagation in space and time is obtained through the finite-difference method. With this, a combination of basis set and grid methods is put forward for tackling multiregion time-dependent problems. In both regions, a high-order explicit scheme is employed for the time propagation. While, in a purely hydrogenic system no approximation is involved due to this separation, in multielectron systems the validity and the usefulness of the present method relies on the basic assumption of R-matrix theory, namely, that beyond a certain distance (encompassing region I) a single ejected electron is distinguishable from the other electrons of the multielectron system and evolves there (region II) effectively as a one-electron system. The method is developed in detail for single active electron systems and applied to the exemplar case of the hydrogen atom in an intense laser field.

Dynamics of Gompertzian tumour growth under environmental fluctuations

We investigate the effect of correlated additive and multiplicative Gaussian white noise oil the Gompertzian growth of tumours. Our results are obtained by Solving numerically the time-dependent Fokker-Planck equation (FPE) associated with the stochastic dynamics. In Our numerical approach we have adopted B-spline functions as a truncated basis to expand the approximated eigenfunctions. The eigenfunctions and eigenvalues obtained using this method are used to derive approximate solutions of the dynamics under Study. We perform simulations to analyze various aspects, of the probability distribution. of the tumour cell populations in the transient- and steady-state regimes. More precisely, we are concerned mainly with the behaviour of the relaxation time (tau) to the steady-state distribution as a function of (i) of the correlation strength (lambda) between the additive noise and the multiplicative noise and (ii) as a function of the multiplicative noise intensity (D) and additive noise intensity (alpha). It is observed that both the correlation strength and the intensities of additive and multiplicative noise, affect the relaxation time.