The relationship between diurnal type and time duration estimation at morning and evening times of day

This study investigates whether different diurnal types (morning versus evening) differ in their estimation of time duration at different times of the day. Given that the performance of morning and evening types is typically best at their preferred times of day, and assuming different diurnal trends in subjective alertness (arousal?) for morning and evening types, and adopting the attentional gate model of time duration estimation, it was predicted that morning types would tend to underestimate and be more accurate in the morning compared to evening types where the opposite pattern was expected. Nineteen morning types, 18 evening types and 18 intermediate types were drawn from a large sample (N=1175) of undergraduates administered the Early/Late Preference Scale. Groups performed a time duration estimation task using the production method for estimating 20-s unfilled intervals at two times of day: 0800/1830. The median absolute error, median directional error and frequency of under- and overestimation were analysed using repeated-measures ANOVA. While all differences were statistically non-significant, the following trends were observed: morning types performed better than evening types; participants overestimated in the morning and underestimated in the evening; and participants were more accurate later in the day. It was concluded that the trends are inconsistent with a relationship between subjective alertness and time duration estimation but consistent with a possible relationship between time duration estimation and diurnal body temperature fluctuations. (C) 2002 Elsevier Ltd. All rights reserved.

Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power

Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F-0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F-0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (D-LR) appeared to be an effective way to predict whether F-0 immigrants could be identified for a particular pair of populations using a given set of markers.

Estimation of concentration-dependent diffusion coefficient in drying process from the space-averaged concentration versus time with experimental data

The estimation of a concentration-dependent diffusion coefficient in a drying process is known as an inverse coefficient problem. The solution is sought wherein the space-average concentration is known as function of time (mass loss monitoring). The problem is stated as the minimization of a functional and gradient-based algorithms are used to solve it. Many numerical and experimental examples that demonstrate the effectiveness of the proposed approach are presented. Thin slab drying was carried out in an isothermal drying chamber built in our laboratory. The diffusion coefficients of fructose obtained with the present method are compared with existing literature results.

Modelling trickle irrigation: Comparison of analytical and numerical models for estimation of wetting front position with time

Irrigation practices that are profligate in their use of water have come under closer scrutiny by water managers and the public. Trickle irrigation has the propensity to increase water use efficiency but only if the system is designed to meet the soil and plant conditions. Recently we have provided a software tool, WetUp (http://www.clw.csiro.au/products/wetup/), to calculate the wetting patterns from trickle irrigation emitters. WetUp uses an analytical solution to calculate the wetted perimeter for both buried and surface emitters. This analytical solution has a number of assumptions, two of which are that the wetting front is defined by water content at which the hydraulic conductivity (K) is I mm day(-1) and that the flow occurs from a point source. Here we compare the wetting patterns calculated with a 2-dimensional numerical model, HYDRUS2D, for solving the water flow into typical soils with the analytical solution. The results show that the wetting patterns are similar, except when the soil properties result in the assumption of a point source no longer being a good description of the flow regime. Difficulties were also experienced with getting stable solutions with HYDRUS2D for soils with low hydraulic conductivities. (c) 2005 Elsevier Ltd. All rights reserved.

Heart rate variability characterization using a time-frequency based instantaneous frequency estimation technique

In this paper, a new method for characterizing the newborn heart rate variability (HRV) is proposed. The central of the method is the newly proposed technique for instantaneous frequency (IF) estimation specifically designed for nonstationary multicomponen signals such as HRV. The new method attempts to characterize the newborn HRV using features extracted from the time–frequency (TF) domain of the signal. These features comprise the IF, the instantaneous bandwidth (IB) and instantaneous energy (IE) of the different TF components of the HRV. Applied to the HRV of both normal and seizure suffering newborns, this method clearly reveals the locations of the spectral peaks and their time-varying nature. The total energy of HRV components, ET and ratio of energy concentrated in the low-frequency (LF) to that in high frequency (HF) components have been shown to be significant features in identifying the HRV of newborn with seizures.

A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies

This paper presents a metafrontier production function model for firms in different groups having different technologies. The metafrontier model enables the calculation of comparable technical efficiencies for firms operating under different technologies. The model also enables the technology gaps to be estimated for firms under different technologies relative to the potential technology available to the industry as a whole. The metafrontier model is applied in the analysis of panel data on garment firms in five different regions of Indonesia, assuming that the regional stochastic frontier production function models have technical inefficiency effects with the time-varying structure proposed by Battese and Coelli ( 1992).

A genetic estimation algorithm for parameters of stochastic ordinary differential equations

A generic method for the estimation of parameters for Stochastic Ordinary Differential Equations (SODEs) is introduced and developed. This algorithm, called the GePERs method, utilises a genetic optimisation algorithm to minimise a stochastic objective function based on the Kolmogorov-Smirnov statistic. Numerical simulations are utilised to form the KS statistic. Further, the examination of some of the factors that improve the precision of the estimates is conducted. This method is used to estimate parameters of diffusion equations and jump-diffusion equations. It is also applied to the problem of model selection for the Queensland electricity market. (C) 2003 Elsevier B.V. All rights reserved.

Overexpressed Ca-v beta 3 inhibits N-type (Ca(v)2.2) calcium channel currents through a hyperpolarizing shift of "ultra-slow" and "closed-state" inactivation

It has been shown that P auxiliary subunits increase current amplitude in voltage-dependent calcium channels. In this study, however, we found a hovel inhibitory effect of beta3 Subunit on macroscopic Ba2+ currents through recombinant N- and R-type calcium channels expressed in Xenopus oocytes. Overexpressed beta3 (12.5 ng/ cell cRNA) significantly suppressed N- and R-type, but not L-type, calcium channel currents at physiological holding potentials (HPs) of -60 and -80 mV At a HP of -80 mV, coinjection of various concentrations (0-12.5 ng) of the beta3 with Ca,.2.2alpha(1) and alpha(2)delta enhanced the maximum conductance of expressed channels at lower beta3 concentrations but at higher concentrations (>2.5 ng/cell) caused a marked inhibition. The beta3-induced Current suppression was reversed at a HP of - 120 mV, suggesting that the inhibition was voltage dependent. A high concentration of Ba-2divided by (40 mM) as a charge carrier also largely diminished the effect of P3 at -80 mV Therefore, experimental conditions (HP, divalent cation concentration, and P3 subunit concentration) approaching normal physiological conditions were critical to elucidate the full extent of this novel P3 effect. Steady-state inactivation curves revealed that N-type channels exhibited closed-state inactivation without P3, and that P3 caused an similar to40 mV negative shift of the inactivation, producing a second component with an inactivation midpoint of approximately -85 mV The inactivation of N-type channels in the presence of a high concentration (12.5 ng/cell) of P3 developed slowly and the time-dependent inactivation curve was best fit by the sum of two exponential functions with time constants of 14 s and 8.8 min at -80 mV Similar ultra-slow inactivation was observed for N-type channels Without P3. Thus, P3 can have a profound negative regulatory effect on N-type (and also R-type) calcium channels by Causing a hyperpolarizing shift of the inactivation without affecting ultra-slow and closed-state inactivation properties.

The practicality of adaptive phase estimation

Adaptive phase estimation is the process of estimating the phase of an electromagnetic field via a continually changing measurement. The measurement is varied in an attempt to optimize it at each moment. In this paper, we show that adaptive phase estimation is more accurate than nonadaptive phase estimation for continuous beams of light even when small time delays in the feedback are present. (c) 2005 Pleiades Publishing Inc.

On the estimation and comparison of short-rate models using the generalised method of moments

Subsequent to the influential paper of [Chan, K.C., Karolyi, G.A., Longstaff, F.A., Sanders, A.B., 1992. An empirical comparison of alternative models of the short-term interest rate. Journal of Finance 47, 1209-1227], the generalised method of moments (GMM) has been a popular technique for estimation and inference relating to continuous-time models of the short-term interest rate. GMM has been widely employed to estimate model parameters and to assess the goodness-of-fit of competing short-rate specifications. The current paper conducts a series of simulation experiments to document the bias and precision of GMM estimates of short-rate parameters, as well as the size and power of [Hansen, L.P., 1982. Large sample properties of generalised method of moments estimators. Econometrica 50, 1029-1054], J-test of over-identifying restrictions. While the J-test appears to have appropriate size and good power in sample sizes commonly encountered in the short-rate literature, GMM estimates of the speed of mean reversion are shown to be severely biased. Consequently, it is dangerous to draw strong conclusions about the strength of mean reversion using GMM. In contrast, the parameter capturing the levels effect, which is important in differentiating between competing short-rate specifications, is estimated with little bias. (c) 2006 Elsevier B.V. All rights reserved.

Aquatic passive sampling of herbicides on naked particle loaded membranes: Accelerated measurement and empirical estimation of kinetic parameters

Water-sampler equilibrium partitioning coefficients and aqueous boundary layer mass transfer coefficients for atrazine, diuron, hexazionone and fluometuron onto C18 and SDB-RPS Empore disk-based aquatic passive samplers have been determined experimentally under a laminar flow regime (Re = 5400). The method involved accelerating the time to equilibrium of the samplers by exposing them to three water concentrations, decreasing stepwise to 50% and then 25% of the original concentration. Assuming first-order Fickian kinetics across a rate-limiting aqueous boundary layer, both parameters are determined computationally by unconstrained nonlinear optimization. In addition, a method of estimation of mass transfer coefficients-therefore sampling rates-using the dimensionless Sherwood correlation developed for laminar flow over a flat plate is applied. For each of the herbicides, this correlation is validated to within 40% of the experimental data. The study demonstrates that for trace concentrations (sub 0.1 mu g/L) and these flow conditions, a naked Empore disk performs well as an integrative sampler over short deployments (up to 7 days) for the range of polar herbicides investigated. The SDB-RPS disk allows a longer integrative period than the C18 disk due to its higher sorbent mass and/or its more polar sorbent chemistry. This work also suggests that for certain passive sampler designs, empirical estimation of sampling rates may be possible using correlations that have been available in the chemical engineering literature for some time.

Population-based continuous optimization, probabilistic modelling and mean shift

Evolutionary algorithms perform optimization using a population of sample solution points. An interesting development has been to view population-based optimization as the process of evolving an explicit, probabilistic model of the search space. This paper investigates a formal basis for continuous, population-based optimization in terms of a stochastic gradient descent on the Kullback-Leibler divergence between the model probability density and the objective function, represented as an unknown density of assumed form. This leads to an update rule that is related and compared with previous theoretical work, a continuous version of the population-based incremental learning algorithm, and the generalized mean shift clustering framework. Experimental results are presented that demonstrate the dynamics of the new algorithm on a set of simple test problems.

Time-resolved photoluminescence spectroscopy of ligand-capped PbS nanocrystals

PbS nanocrystals are synthesized using colloidal techniques and have their surfaces capped with oleic acid. The absorption band edge of the PbS nanocrystals is tuned between 900 and 580 nm. The PbS nanocrystals exhibit tuneable photoluminescence with large non-resonant Stokes shifts of up to 500 mcV. The magnitude of the Stokes shift is found to be dependent upon the size of PbS nanocrystals. Time-resolved photoluminescence spectroscopy of the PbS nanocrystals reveals that the photouminescence has an extraordinarily long lifetime of 1 mus. This long fluorescence lifetime is attributed to the effect of dielectric screening similar to that observed in other IV-VI semiconductor nanocrystals.