New approximation for free surface flow of groundwater: capillarity correction

An existing capillarity correction for free surface groundwater flow as modelled by the Boussinesq equation is re-investigated. Existing solutions, based on the shallow flow expansion, have considered only the zeroth-order approximation. Here, a second-order capillarity correction to tide-induced watertable fluctuations in a coastal aquifer adjacent to a sloping beach is derived. A new definition of the capillarity correction is proposed for small capillary fringes, and a simplified solution is derived. Comparisons of the two models show that the simplified model can be used in most cases. The significant effects of higher-order capillarity corrections on tidal fluctuations in a sloping beach are also demonstrated. (c) 2004 Elsevier Ltd. All rights reserved.

Two-dimensional approximation for tide-induced watertable fluctuations in a sloping sandy beach

The prediction of watertable fluctuations in a coastal aquifer is important for coastal management. However, most previous approaches have based on the one-dimensional Boussinesq equation, neglecting variations in the coastline and beach slope. In this paper, a closed-form analytical solution for a two-dimensional unconfined coastal aquifer bounded by a rhythmic coastline is derived. In the new model, the effect of beach slope is also included, a feature that has not been considered in previous two-dimensional approximations. Three small parameters, the shallow water parameter (epsilon), the amplitude parameter (a) and coastline parameter (beta) are used in the perturbation approximation. The numerical results demonstrate the significant influence of both the coastline shape and beach slopes on tide-driven coastal groundwater fluctuations. (c) 2004 Elsevier Ltd. All rights reserved.

Vibrational dynamics and structure of natural feldspars

The present study gives a contribution to the knowledge on the Na-feldspar and plagioclases, extending the database of the Raman spectra of plagioclases with different chemical compositions and structural orders. This information may be used for the future planetary explorations by “rovers”, for the investigation of ceramics nanocrystal materials and for the mineralogical phase identification in sediments. Na-feldspar and plagioclase solid solution have been investigated by Raman spectroscopy in order to determine the relationships between the vibrational changes and the plagioclase crystal chemistry and structure. We focused on the Raman micro-spectroscopy technique, being a non-destructive method, suited for contactless analysis with high spatial resolution. Chemical and structural analyses have been performed on natural samples to test the usefulness of Raman spectroscopy as a tool in the study of the pressure-induced structural deformations, the disordering processes due to change in the Al-Si distribution in the tetrahedral sites and, finally, in the determination of the anorthitic content (Anx) in plagioclase minerals. All the predicted 39 Ag Raman active modes have been identified and assigned to specific patterns of atomic vibrational motion. A detailed comparison between experimental and computed Raman spectra has been performed and previous assignments have been revised, solving some discrepancies reported in recent literature. The ab initio calculation at the hybrid HF/DFT level with the WC1LYP Hamiltonian has proven to give excellent agreement between calculated and experimentally measured Raman wavenumbers and intensities in triclinic minerals. A short digression on the 36 infrared active modes of Na-feldspar has been done too. The identification of all 39 computed Raman modes in the experimentally measured spectra of the fully ordered Na-feldspar, known as low albite, along with the detailed description of each vibrational mode, has been essential to extend the comparative analysis to the high pressure and high temperature structural forms of albite, which reflect the physical–chemical conditions of the hosting rocks. The understanding of feldspar structure response to pressure and temperature is crucial in order to constrain crustal behaviour. The compressional behaviour of the Na-feldspar has been investigated for the first time by Raman spectroscopy. The absence of phase transitions and the occurrence of two secondary compression mechanisms acting at different pressures have been confirmed. Moreover, Raman data suggest that the internal structural changes are confined to a small pressure interval, localized around 6 GPa, not spread out from 4 to 8 GPa as suggested by previous X-rays studies on elasticity. The dominant compression mechanisms act via tetrahedral tilting, while the T-O bond lengths remain nearly constant at moderate compressional regimes. At the spectroscopic level, this leads to the strong pressure dependencies of T-O-T bending modes, as found for the four modes at 478, 508, 578 and 815 cm-1. The Al-Si distribution in the tetrahedral sites affects also the Raman spectrum of Na-feldspar. In particular, peak broadening is more sensitive than peak position to changes in the degree of order. Raman spectroscopy is found to be a good probe for local ordering, in particular being sensitive to the first annealing steps, when the macroscopic order parameter is still high. Even though Raman data are scattered and there are outliers in the estimated values of the degree of order, the average peak linewidths of the Na-feldspar characteristic doublet band, labelled here as υa and υb, as a function of the order parameter Qod show interesting trends: both peak linewidths linearly increase until saturation. From Qod values lower than 0.6, peak broadening is no more affected by the Al-Si distribution. Moreover, the disordering process is found to be heterogeneous. SC-XRD and Raman data have suggested an inter-crystalline inhomogeneity of the samples, i.e., the presence of regions with different defect density on the micrometric scale. Finally, the influence of Ca-Na substitution in the plagioclase Raman spectra has been investigated. Raman spectra have been collected on a series of well characterized natural, low structural plagioclases. The variations of the Raman modes as a function of the chemical composition and the structural order have been determined. The number of the observed Raman bands at each composition gives information about the unit-cell symmetry: moving away from the C1 structures, the number of the Raman bands enhances, as the number of formula units in the unit cell increases. The modification from an “albite-like” Raman spectrum to a more “anorthite-like” spectrum occurs from sample An78 onwards, which coincides with the appearance of c reflections in the diffraction patterns of the samples. The evolution of the Raman bands υa and υb displays two changes in slope at ~An45 and ~An75: the first one occurs between e2 and e1 plagioclases, the latter separates e1 and I1 plagioclases with only b reflections in their diffraction patterns from I1 and P1 samples having b and c reflections too. The first variation represents exactly the e2→e1 phase transitions, whereas the second one corresponds in good approximation to the C1→I1 transition, which has been determined at ~An70 by previous works. The I1→P1 phase transition in the anorthite-rich side of the solid solution is not highlighted in the collected Raman spectra. Variations in peak broadening provide insights into the behaviour of the order parameter on a local scale, suggesting an increase in the structural disorder within the solid solution, as the structures have to incorporate more Al atoms to balance the change from monovalent to divalent cations. All the information acquired on these natural plagioclases has been used to produce a protocol able to give a preliminary estimation of the chemical composition of an unknown plagioclase from its Raman spectrum. Two calibration curves, one for albite-rich plagioclases and the other one for the anorthite-rich plagioclases, have been proposed by relating the peak linewidth of the most intense Raman band υa and the An content. It has been pointed out that the dependence of the composition from the linewidth can be obtained only for low structural plagioclases with a degree of order not far away from the references. The proposed tool has been tested on three mineralogical samples, two of meteoric origin and one of volcanic origin. Chemical compositions by Raman spectroscopy compare well, within an error of about 10%, with those obtained by elemental techniques. Further analyses on plagioclases with unknown composition will be necessary to validate the suggested method and introduce it as routine tool for the determination of the chemical composition from Raman data in planetary missions.

Neural network regression with input uncertainty

It is generally assumed when using Bayesian inference methods for neural networks that the input data contains no noise or corruption. For real-world (errors in variable) problems this is clearly an unsafe assumption. This paper presents a Bayesian neural network framework which allows for input noise given that some model of the noise process exists. In the limit where this noise process is small and symmetric it is shown, using the Laplace approximation, that there is an additional term to the usual Bayesian error bar which depends on the variance of the input noise process. Further, by treating the true (noiseless) input as a hidden variable and sampling this jointly with the network's weights, using Markov Chain Monte Carlo methods, it is demonstrated that it is possible to infer the unbiassed regression over the noiseless input.

Error-correcting code on a cactus:A solvable model

An exact solution to a family of parity check error-correcting codes is provided by mapping the problem onto a Husimi cactus. The solution obtained in the thermodynamic limit recovers the replica-symmetric theory results and provides a very good approximation to finite systems of moderate size. The probability propagation decoding algorithm emerges naturally from the analysis. A phase transition between decoding success and failure phases is found to coincide with an information-theoretic upper bound. The method is employed to compare Gallager and MN codes.

Error-correcting codes on a Bethe-like lattice

We analyse Gallager codes by employing a simple mean-field approximation that distorts the model geometry and preserves important interactions between sites. The method naturally recovers the probability propagation decoding algorithm as a minimization of a proper free-energy. We find a thermodynamical phase transition that coincides with information theoretical upper-bounds and explain the practical code performance in terms of the free-energy landscape.

Neural Network Modelling with Input Uncertainty: Theory and Application

It is generally assumed when using Bayesian inference methods for neural networks that the input data contains no noise. For real-world (errors in variable) problems this is clearly an unsafe assumption. This paper presents a Bayesian neural network framework which accounts for input noise provided that a model of the noise process exists. In the limit where the noise process is small and symmetric it is shown, using the Laplace approximation, that this method adds an extra term to the usual Bayesian error bar which depends on the variance of the input noise process. Further, by treating the true (noiseless) input as a hidden variable, and sampling this jointly with the network’s weights, using a Markov chain Monte Carlo method, it is demonstrated that it is possible to infer the regression over the noiseless input. This leads to the possibility of training an accurate model of a system using less accurate, or more uncertain, data. This is demonstrated on both the, synthetic, noisy sine wave problem and a real problem of inferring the forward model for a satellite radar backscatter system used to predict sea surface wind vectors.

Bayesian error bars for regression

Regression problems are concerned with predicting the values of one or more continuous quantities, given the values of a number of input variables. For virtually every application of regression, however, it is also important to have an indication of the uncertainty in the predictions. Such uncertainties are expressed in terms of the error bars, which specify the standard deviation of the distribution of predictions about the mean. Accurate estimate of error bars is of practical importance especially when safety and reliability is an issue. The Bayesian view of regression leads naturally to two contributions to the error bars. The first arises from the intrinsic noise on the target data, while the second comes from the uncertainty in the values of the model parameters which manifests itself in the finite width of the posterior distribution over the space of these parameters. The Hessian matrix which involves the second derivatives of the error function with respect to the weights is needed for implementing the Bayesian formalism in general and estimating the error bars in particular. A study of different methods for evaluating this matrix is given with special emphasis on the outer product approximation method. The contribution of the uncertainty in model parameters to the error bars is a finite data size effect, which becomes negligible as the number of data points in the training set increases. A study of this contribution is given in relation to the distribution of data in input space. It is shown that the addition of data points to the training set can only reduce the local magnitude of the error bars or leave it unchanged. Using the asymptotic limit of an infinite data set, it is shown that the error bars have an approximate relation to the density of data in input space.

Satellite borne radar altimetry : empirical orbit refinement and ocean signal recovery techniques

Measurements of the sea surface obtained by satellite borne radar altimetry are irregularly spaced and contaminated with various modelling and correction errors. The largest source of uncertainty for low Earth orbiting satellites such as ERS-1 and Geosat may be attributed to orbital modelling errors. The empirical correction of such errors is investigated by examination of single and dual satellite crossovers, with a view to identifying the extent of any signal aliasing: either by removal of long wavelength ocean signals or introduction of additional error signals. From these studies, it was concluded that sinusoidal approximation of the dominant one cycle per revolution orbit error over arc lengths of 11,500 km did not remove a significant mesoscale ocean signal. The use of TOPEX/Poseidon dual crossovers with ERS-1 was shown to substantially improve the radial accuracy of ERS-1, except for some absorption of small TOPEX/Poseidon errors. The extraction of marine geoid information is of great interest to the oceanographic community and was the subject of the second half of this thesis. Firstly through determination of regional mean sea surfaces using Geosat data, it was demonstrated that a dataset with 70cm orbit error contamination could produce a marine geoid map which compares to better than 12cm with an accurate regional high resolution gravimetric geoid. This study was then developed into Optimal Fourier Transform Interpolation, a technique capable of analysing complete altimeter datasets for the determination of consistent global high resolution geoid maps. This method exploits the regular nature of ascending and descending data subsets thus making possible the application of fast Fourier transform algorithms. Quantitative assessment of this method was limited by the lack of global ground truth gravity data, but qualitative results indicate good signal recovery from a single 35-day cycle.

An econometric analysis of international tourism demand in Hong Kong : a cointegration and error correction approach

The purpose of this study is to develop econometric models to better understand the economic factors affecting inbound tourist flows from each of six origin countries that contribute to Hong Kong’s international tourism demand. To this end, we test alternative cointegration and error correction approaches to examine the economic determinants of tourist flows to Hong Kong, and to produce accurate econometric forecasts of inbound tourism demand. Our empirical findings show that permanent income is the most significant determinant of tourism demand in all models. The variables of own price, weighted substitute prices, trade volume, the share price index (as an indicator of changes in wealth in origin countries), and a dummy variable representing the Beijing incident (1989) are also found to be important determinants for some origin countries. The average long-run income and own price elasticity was measured at 2.66 and – 1.02, respectively. It was hypothesised that permanent income is a better explanatory variable of long-haul tourism demand than current income. A novel approach (grid search process) has been used to empirically derive the weights to be attached to the lagged income variable for estimating permanent income. The results indicate that permanent income, estimated with empirically determined relatively small weighting factors, was capable of producing better results than the current income variable in explaining long-haul tourism demand. This finding suggests that the use of current income in previous empirical tourism demand studies may have produced inaccurate results. The share price index, as a measure of wealth, was also found to be significant in two models. Studies of tourism demand rarely include wealth as an explanatory forecasting long-haul tourism demand. However, finding a satisfactory proxy for wealth common to different countries is problematic. This study indicates with the ECM (Error Correction Models) based on the Engle-Granger (1987) approach produce more accurate forecasts than ECM based on Pesaran and Shin (1998) and Johansen (1988, 1991, 1995) approaches for all of the long-haul markets and Japan. Overall, ECM produce better forecasts than the OLS, ARIMA and NAÏVE models, indicating the superiority of the application of a cointegration approach for tourism demand forecasting. The results show that permanent income is the most important explanatory variable for tourism demand from all countries but there are substantial variations between countries with the long-run elasticity ranging between 1.1 for the U.S. and 5.3 for U.K. Price is the next most important variable with the long-run elasticities ranging between -0.8 for Japan and -1.3 for Germany and short-run elasticities ranging between – 0.14 for Germany and -0.7 for Taiwan. The fastest growing market is Mainland China. The findings have implications for policies and strategies on investment, marketing promotion and pricing.

Numerical approximation of the one-dimensional inverse Cauchy–Stefan problem using a method of fundamental solutions

We investigate an application of the method of fundamental solutions (MFS) to the one-dimensional parabolic inverse Cauchy–Stefan problem, where boundary data and the initial condition are to be determined from the Cauchy data prescribed on a given moving interface. In [B.T. Johansson, D. Lesnic, and T. Reeve, A method of fundamental solutions for the one-dimensional inverse Stefan Problem, Appl. Math Model. 35 (2011), pp. 4367–4378], the inverse Stefan problem was considered, where only the boundary data is to be reconstructed on the fixed boundary. We extend the MFS proposed in Johansson et al. (2011) and show that the initial condition can also be simultaneously recovered, i.e. the MFS is appropriate for the inverse Cauchy-Stefan problem. Theoretical properties of the method, as well as numerical investigations, are included, showing that accurate results can be efficiently obtained with small computational cost.

Non-Gaussian error probability in optical soliton transmission

We find the probability distribution of the fluctuating parameters of a soliton propagating through a medium with additive noise. Our method is a modification of the instanton formalism (method of optimal fluctuation) based on a saddle-point approximation in the path integral. We first solve consistently a fundamental problem of soliton propagation within the framework of noisy nonlinear Schrödinger equation. We then consider model modifications due to in-line (filtering, amplitude and phase modulation) control. It is examined how control elements change the error probability in optical soliton transmission. Even though a weak noise is considered, we are interested here in probabilities of error-causing large fluctuations which are beyond perturbation theory. We describe in detail a new phenomenon of soliton collapse that occurs under the combined action of noise, filtering and amplitude modulation. © 2004 Elsevier B.V. All rights reserved.

Refractive error, cognitive demand and nearwork-induced transient myopia

Purpose. Whereas many previous studies have identified the association between sustained near work and myopia, few have assessed the influence of concomitant levels of cognitive effort. This study investigates the effect of cognitive effort on near-work induced transient myopia (NITM). Methods. Subjects comprised of six early onset myopes (EOM; mean age 23.7 yrs; mean onset 10.8 yrs), six late-onset myopes (LOM; mean age 23.2 yrs; mean onset 20.0 yrs) and six emmetropes (EMM; mean age 23.8 yrs). Dynamic, monocular, ocular accommodation was measured with the Shin-Nippon SRW-5000 autorefractor. Subjects engaged passively or actively in a 5 minute arithmetic sum checking task presented monocularly on an LCD monitor via a Badal optical system. In all conditions the task was initially located at near (4.50 D) and immediately following the task instantaneously changed to far (0.00 D) for a further 5 minutes. The combinations of active (A) and passive (P) cognition were randomly allocated as P:P; A:P; A:A; P:A. Results. For the initial near task, LOMs were shown to have a significantly less accurate accommodative response than either EOMs or EMMs (p < 0.001). For the far task, post hoc analyses for refraction identified EOMs as demonstrating significant NITM compared to LOMs (p < 0.05), who in turn showed greater NITM than EMMs (p < 0.001). The data show that for EOMs the level of cognitive activity operating during the near and far tasks determines the persistence of NITM; persistence being maximal when active cognition at near is followed by passive cognition at far. Conclusions. Compared with EMMs, EOMs and LOMs are particularly susceptible to NITM such that sustained near vision reduces subsequent accommodative accuracy for far vision. It is speculated that the marked NITM found in EOM may be a consequence of the crystalline lens thinning shown to be a developmental feature of EOM. Whereas the role of small amounts of retinal defocus in myopigenesis remains equivocal, the results show that account needs to be taken of cognitive demand in assessing phenomena such as NITM.

Optimization of Rational Approximations by Continued Fractions

The paper has been presented at the 12th International Conference on Applications of Computer Algebra, Varna, Bulgaria, June, 2006.