Quantitative analysis of accuracy of an inertial/acoustic 6DOF tracking system in motion

An increasing number of neuroscience experiments are using virtual reality to provide a more immersive and less artificial experimental environment. This is particularly useful to navigation and three-dimensional scene perception experiments. Such experiments require accurate real-time tracking of the observer's head in order to render the virtual scene. Here, we present data on the accuracy of a commonly used six degrees of freedom tracker (Intersense IS900) when it is moved in ways typical of virtual reality applications. We compared the reported location of the tracker with its location computed by an optical tracking method. When the tracker was stationary, the root mean square error in spatial accuracy was 0.64 mm. However, we found that errors increased over ten-fold (up to 17 mm) when the tracker moved at speeds common in virtual reality applications. We demonstrate that the errors we report here are predominantly due to inaccuracies of the IS900 system rather than the optical tracking against which it was compared. (c) 2006 Elsevier B.V. All rights reserved.

Comparison of extrasystolic ECG signal classifiers using discrete wavelet transforms

This work compares and contrasts results of classifying time-domain ECG signals with pathological conditions taken from the MITBIH arrhythmia database. Linear discriminant analysis and a multi-layer perceptron were used as classifiers. The neural network was trained by two different methods, namely back-propagation and a genetic algorithm. Converting the time-domain signal into the wavelet domain reduced the dimensionality of the problem at least 10-fold. This was achieved using wavelets from the db6 family as well as using adaptive wavelets generated using two different strategies. The wavelet transforms used in this study were limited to two decomposition levels. A neural network with evolved weights proved to be the best classifier with a maximum of 99.6% accuracy when optimised wavelet-transform ECG data wits presented to its input and 95.9% accuracy when the signals presented to its input were decomposed using db6 wavelets. The linear discriminant analysis achieved a maximum classification accuracy of 95.7% when presented with optimised and 95.5% with db6 wavelet coefficients. It is shown that the much simpler signal representation of a few wavelet coefficients obtained through an optimised discrete wavelet transform facilitates the classification of non-stationary time-variant signals task considerably. In addition, the results indicate that wavelet optimisation may improve the classification ability of a neural network. (c) 2005 Elsevier B.V. All rights reserved.

An efficient numerical scheme for the two-dimensional shallow water equations using arithmetic averaging

A finite difference scheme based on flux difference splitting is presented for the solution of the two-dimensional shallow water equations of ideal fluid flow. A linearised problem, analogous to that of Riemann for gas dynamics is defined, and a scheme, based on numerical characteristic decomposition is presented for obtaining approximate solutions to the linearised problem, and incorporates the technique of operator splitting. An average of the flow variables across the interface between cells is required, and this average is chosen to be the arithmetic mean for computational efficiency leading to arithmetic averaging. This is in contrast to usual ‘square root’ averages found in this type of Riemann solver, where the computational expense can be prohibitive. The method of upwind differencing is used for the resulting scalar problems, together with a flux limiter for obtaining a second order scheme which avoids nonphysical, spurious oscillations. An extension to the two-dimensional equations with source terms is included. The scheme is applied to the one-dimensional problems of a breaking dam and reflection of a bore, and in each case the approximate solution is compared to the exact solution of ideal fluid flow. The scheme is also applied to a problem of stationary bore generation in a channel of variable cross-section. Finally, the scheme is applied to two other dam-break problems, this time in two dimensions with one having cylindrical symmetry. Each approximate solution compares well with those given by other authors.

High hydrostatic pressure resistance of Campylobacter jejuni after different sublethal stresses

Aims: To study the development of resistance responses in Campylobacter jejuni to High Hydrostatic Pressure (HHP) treatments after the exposure to different stressful conditions that may be encountered in food processing environments, such as acid pH, elevated temperatures and cold storage. Methods and Results: C. jejuni cells in exponential and stationary growth phase were exposed to different sublethal stresses (acid, heat and cold shocks) prior to evaluate the development of resistance responses to HHP. For exponential-phase cells, neither of the conditions tested increased nor decreased HHP resistance of C. jejuni. For stationary-phase cells, acid and heat adaptation sensitized C. jejuni cells to the subsequent pressure treatment. On the contrary, cold-adapted stationary-phase cells developed resistance to HHP. Conclusions: Whereas C. jejuni can be classified as a stress sensitive microorganism, our findings have demonstrated that it can develop resistance responses under different stressing conditions. The resistance of stationary phase C. jejuni to HHP was increased after cells were exposed to cold temperatures. Significance and Impact of the Study: The results of this study contribute to a better knowledge of the physiology of C. jejuni and its survival to food preservation agents. Results here presented may help in the design of combined processes for food preservation based on HHP technology.

Rhenium-to-benzoylpyridine and rhenium-to-bipyridine MLCT excited states offac-[Re(Cl)(4-benzoylpyridine)2(CO)3] andfac-[Re(4-benzoylpyridine)(CO)3(bpy)]+: a time-resolved spectroscopic and spectroelectrochemical study

The lowest allowed electronic transition of fac-[Re(Cl)(CO)(3)(bopy)(2)] (bopy = 4-benzoylpyridine) has a Re --> bopy MLCT character, as revealed by UV-vis and stationary resonance Raman spectroscopy. Accordingly, the lowest-lying, long-lived, excited state is Re --> bopy (MLCT)-M-3. Electronic depopulation of the Re(CO)(3) unit and population of a bopy pi* orbital upon excitation are evident by the upward shift of v(Cequivalent toO) vibrations and a downward shift of the ketone v(C=O) vibration, respectively, seen in picosecond time-resolved IR spectra. Moreover, reduction of a single bopy ligand in the (MLCT)-M-3 excited state is indicated by time-resolved visible and resonance Raman (TR3) spectra that show features typical of bopy(.-). In contrast, the lowest allowed electronic transition and lowest-lying excited state of a new complex fac-[Re(bopy)(CO)(3)(bpy)](+) (bpy = 2,2'-bipyridine) have been identified as Re --> bpy MLCT with no involvement of the bopy ligand, despite the fact that the first reduction of this complex is bopy-localized, as was proven spectroelectrochemically. This is a rare case in which the localizations of the lowest MLCT excitation and the first reduction are different. (MLCT)-M-3 excited states of both fac-[Re(Cl)(CO)(3)(bopy)(2)] and fac-[Re(bopy)(CO)(3)(bpy)](+) are initially formed vibrationally hot. Their relaxation is manifested by picosecond dynamic shifts of v(Cequivalent toO) IR bands. The X-ray structure of fac-[Re(bopy)(CO)(3)(bpy)](PF6CH3CN)-C-. has been determined.

Single trial BCI operation via Wackermann parameters

Accurate single trial P300 classification lends itself to fast and accurate control of Brain Computer Interfaces (BCIs). Highly accurate classification of single trial P300 ERPs is achieved by characterizing the EEG via corresponding stationary and time-varying Wackermann parameters. Subsets of maximally discriminating parameters are then selected using the Network Clustering feature selection algorithm and classified with Naive-Bayes and Linear Discriminant Analysis classifiers. Hence the method is assessed on two different data-sets from BCI competitions and is shown to produce accuracies of between approximately 70% and 85%. This is promising for the use of Wackermann parameters as features in the classification of single-trial ERP responses.

Bayesian model averaging and identification of structural breaks in time series

Bayesian Model Averaging (BMA) is used for testing for multiple break points in univariate series using conjugate normal-gamma priors. This approach can test for the number of structural breaks and produce posterior probabilities for a break at each point in time. Results are averaged over specifications including: stationary; stationary around trend and unit root models, each containing different types and number of breaks and different lag lengths. The procedures are used to test for structural breaks on 14 annual macroeconomic series and 11 natural resource price series. The results indicate that there are structural breaks in all of the natural resource series and most of the macroeconomic series. Many of the series had multiple breaks. Our findings regarding the existence of unit roots, having allowed for structural breaks in the data, are largely consistent with previous work.

The inhibitory effect of natural microflora of food on growth of Listeria monocytogenes in enrichment broths

The aims of this study were to (i) compare the inhibitory effects of the natural microflora of different foods on the growth of Listeria monocytogenes during enrichment in selective and non-selective broths; (ii) to isolate and identify components of the microflora of the most inhibitory food; and (iii) to determine which of these components was most inhibitory to growth of L. monocytogenes in co-culture studies. Growth of an antibioticresistant marker strain of L. monocytogenes was examined during enrichment of a range of different foods in Tryptone Soya Broth (TSB), Half Fraser Broth (HFB) and Oxoid Novel Enrichment (ONE) Broth. Inhibition of L. monocytogenes was greatest in the presence of minced beef, salami and soft cheese and least with prepared fresh salad and chicken pâté. For any particular food the numbers of L. monocytogenes present after 24 h enrichment in different broths increased in the order: TSB, HFB and ONE Broth. Numbers of L. monocytogenes recovered after enrichment in TSB were inversely related to the initial aerobic plate count (APC) in the food but with only a moderate coefficient of determination (R2) of 0.51 implying that microbial numbers and the composition of the microflora both influenced the degree of inhibition of L. monocytogenes. In HFB and ONE Broth the relationship between APC and final L. monocytogenes counts was weaker. The microflora of TSB after 24 h enrichment of minced beef consisted of lactic acid bacteria, Brochothrix thermosphacta, Pseudomonas spp., Enterobacteriaceae, and enterococci. In co-culture studies of L. monocytogenes with different components of the microflora in TSB, the lactic acid bacteria were the most inhibitory followed by the Enterobacteriaceae. The least inhibitory organisms were Pseudomonas sp., enterococci and B. thermosphacta. In HFB and ONE Broth the growth of Gram-negative organisms was inhibited but lactic acid bacteria still reached high numbers after 24 h. A more detailed study of the growth of low numbers of L. monocytogenes during enrichment of minced beef in TSB revealed that growth of L. monocytogenes ceased at a cell concentration of about 102 cfu/ml when lactic acid bacteria entered stationary phase. However in ONE Broth growth of lactic acid bacteria was slower than in TSB with a longer lag time allowing L. monocytogenes to achieve much higher numbers before lactic acid bacteria reached stationary phase. This work has identified the relative inhibitory effects of different components of a natural food microflora and shown that the ability of low numbers of L. monocytogenes to achieve high cell concentrations is highly dependent on the extent to which enrichment media are able to inhibit or delay growth of the more effective competitors.

Environmental factors influencing the inactivation of Cronobacter sakazakii by high hydrostatic pressure

The effect of High Hydrostatic Pressure (HHP) on the survival of Cronobacter sakazakii was investigated. Deviations from linearity were found on the survival curves and the Mafart equation accurately described the kinetics of inactivation. Comparisons between strains and treatments were made based on the time needed for a 5-log10 reduction in viable count. The ability of C. sakazakii to tolerate high pressure was straindependent with a 26-fold difference in resistance among four strains tested. Pressure resistance was greatest in the stationary growth phase and at the highest growth temperatures tested (30 and 37 °C). Cells treated in neutral pH buffer were 5-fold more resistant than those treated at pH 4.0, and 8-fold more sensitive than those treated in buffer with sucrose added (aw=0.98). Pressure resistance data obtained in buffer at the appropriate pH adequately estimated the resistance of C. sakazakii in chicken and vegetables soups. In contrast, a significant protective effect against high pressure was conferred by rehydrated powdered milk. As expected, treatment efficacy improved as pressure increased. z values of 112, 136 and 156 MPa were obtained for pH 4.0, pH 7.0 and aw=0.98 buffers, respectively. Cells with sublethal injury to their outer and cytoplasmic membranes were detected after HHP under all the conditions tested. The lower resistance of C. sakazakii cells when treated in media of pH 4.0 seemed to be due to a decreased barostability of the bacterial envelopes. Conversely, the higher resistance displayed in media of reduced water activity may relate to a higher stability of bacterial envelopes.

Path planning of robots in noisy workspaces using learning automata

The problem of a manipulator operating in a noisy workspace and required to move from an initial fixed position P0 to a final position Pf is considered. However, Pf is corrupted by noise, giving rise to Pˆf, which may be obtained by sensors. The use of learning automata is proposed to tackle this problem. An automaton is placed at each joint of the manipulator which moves according to the action chosen by the automaton (forward, backward, stationary) at each instant. The simultaneous reward or penalty of the automata enables avoiding any inverse kinematics computations that would be necessary if the distance of each joint from the final position had to be calculated. Three variable-structure learning algorithms are used, i.e., the discretized linear reward-penalty (DLR-P, the linear reward-penalty (LR-P ) and a nonlinear scheme. Each algorithm is separately tested with two (forward, backward) and three forward, backward, stationary) actions.

Discrete time representation of continuous time ARMA processes

This paper derives exact discrete time representations for data generated by a continuous time autoregressive moving average (ARMA) system with mixed stock and flow data. The representations for systems comprised entirely of stocks or of flows are also given. In each case the discrete time representations are shown to be of ARMA form, the orders depending on those of the continuous time system. Three examples and applications are also provided, two of which concern the stationary ARMA(2, 1) model with stock variables (with applications to sunspot data and a short-term interest rate) and one concerning the nonstationary ARMA(2, 1) model with a flow variable (with an application to U.S. nondurable consumers’ expenditure). In all three examples the presence of an MA(1) component in the continuous time system has a dramatic impact on eradicating unaccounted-for serial correlation that is present in the discrete time version of the ARMA(2, 0) specification, even though the form of the discrete time model is ARMA(2, 1) for both models.

The equatorial response to higher latitude forcing

The classic view, following Charney and Webster and Holton, is that significant midlatitude forcing of the Tropics can be expected only in regions with westerly winds in the upper troposphere because it is only in these regions that stationary Rossby waves will be able to propagate toward the equator. Here it is shown that higherlatitude forcing can project directly onto equatorial waves and give a significant tropical response in both easterly and westerly tropical flow. The equatorial response to higher-latitude forcing is considered in the context of a dry atmosphere and a localized higher-latitude forcing with eastward or westward phase speed. Previous ideas of the Doppler shifting of equatorial waves by zonal flows are extended to include consideration of a forcing involving a range of zonal wavenumbers. A Gill-type model suggests that there can be significant forcing of equatorial waves by either vorticity forcing or heating in higher latitudes. In agreement with the theory, the Kelvin wave response to eastward forcing is peaked at high frequencies/short periods but reduces only slowly with decreasing frequency. Primitive-equation experiments confirm the strong equatorial response associated with a deep Kelvin wave for forcing in midlatitudes. The response is strongest in the Eastern Hemisphere with its equatorial, upper-tropospheric easterlies. The possible importance of this equatorial response in the organization of large-scale, deep tropical convection and the initiation of the Madden–Julian oscillation is discussed. The ability of westward forcing in higher latitudes to trigger Rossby–gravity and Rossby waves is found in the primitive-equation model to be significant but rather less robust. These wave signatures are clearest in the lower troposphere. For shorter periods the Rossby–gravity wave dominates, and for upper-tropospheric forcing, downward and eastward wave activity propagation is seen. Upper-tropospheric westerlies are found to enhance the response.

Binaural prediction of speech intelligibility in reverberant rooms with multiple noise sources

When speech is in competition with interfering sources in rooms, monaural indicators of intelligibility fail to take account of the listener’s abilities to separate target speech from interfering sounds using the binaural system. In order to incorporate these segregation abilities and their susceptibility to reverberation, Lavandier and Culling [J. Acoust. Soc. Am. 127, 387–399 (2010)] proposed a model which combines effects of better-ear listening and binaural unmasking. A computationally efficient version of this model is evaluated here under more realistic conditions that include head shadow, multiple stationary noise sources, and real-room acoustics. Three experiments are presented in which speech reception thresholds were measured in the presence of one to three interferers using real-room listening over headphones, simulated by convolving anechoic stimuli with binaural room impulse-responses measured with dummy-head transducers in five rooms. Without fitting any parameter of the model, there was close correspondence between measured and predicted differences in threshold across all tested conditions. The model’s components of better-ear listening and binaural unmasking were validated both in isolation and in combination. The computational efficiency of this prediction method allows the generation of complex “intelligibility maps” from room designs. © 2012 Acoustical Society of America

Further investigation of the impact of idealised continents and SST distributions on the Northern Hemisphere storm tracks

Building on studies by Brayshaw et al. (2009, 2011) of the basic ingredients of the North Atlantic storm track (land-sea contrast, orography and SST), this article investigates the impact of Eurasian topography and Pacific SST anomalies on the North Pacific and Atlantic storm tracks through a hierarchy of atmospheric GCM simulations using idealised boundary conditions in the HadGAM1 model. The Himalaya-Tibet mountain complex is found to play a crucial role in shaping the North Pacific storm track. The northward deflection of the westerly flow around northern Tibet generates an extensive pool of very cold air in the north-eastern tip of the Asian continent, which strengthens the meridional temperature gradient and favours baroclinic growth in the western Pacific. The Kuroshio SST front is also instrumental in strengthening the Pacific storm track through its impact on near-surface baroclinicity, while the warm waters around Indonesia tend to weaken it through the impact on baroclinicity of stationary Rossby waves propagating poleward from the convective heating regions. Three mechanisms by which the Atlantic storm track may be affected by changes in the boundary conditions upstream of the Rockies are discussed. In the model configuration used here, stationary Rossby waves emanating from Tibet appear to weaken the North Atlantic storm track substantially, whereas those generated over the cold waters off Peru appear to strengthen it. Changes in eddy-driven surface winds over the Pacific generally appear to modify the flow over the Rocky Mountains, leading to consistent modifications in the Atlantic storm track. The evidence for each of these mechanisms is, however, ultimately equivocal in these simulations.

An analysis of long-term trends, seasonality and short-term dynamics in water quality data from Plynlimon, Wales

This paper examines two hydrochemical time-series derived from stream samples taken in the Upper Hafren catchment, Plynlimon, Wales. One time-series comprises data collected at 7-hour intervals over 22 months (Neal et al., submitted, this issue), while the other is based on weekly sampling over 20 years. A subset of determinands: aluminium, calcium, chloride, conductivity, dissolved organic carbon, iron, nitrate, pH, silicon and sulphate are examined within a framework of non-stationary time-series analysis to identify determinand trends, seasonality and short-term dynamics. The results demonstrate that both long-term and high-frequency monitoring provide valuable and unique insights into the hydrochemistry of a catchment. The long-term data allowed analysis of long-termtrends, demonstrating continued increases in DOC concentrations accompanied by declining SO4 concentrations within the stream, and provided new insights into the changing amplitude and phase of the seasonality of the determinands such as DOC and Al. Additionally, these data proved invaluable for placing the short-term variability demonstrated within the high-frequency data within context. The 7-hour data highlighted complex diurnal cycles for NO3, Ca and Fe with cycles displaying changes in phase and amplitude on a seasonal basis. The high-frequency data also demonstrated the need to consider the impact that the time of sample collection can have on the summary statistics of the data and also that sampling during the hours of darkness provides additional hydrochemical information for determinands which exhibit pronounced diurnal variability. Moving forward, this research demonstrates the need for both long-term and high-frequency monitoring to facilitate a full and accurate understanding of catchment hydrochemical dynamics.