Seizure detection algorithm for neonates based on wave-sequence analysis

Objective: The description and evaluation of the performance of a new real-time seizure detection algorithm in the newborn infant. Methods: The algorithm includes parallel fragmentation of EEG signal into waves; wave-feature extraction and averaging; elementary, preliminary and final detection. The algorithm detects EEG waves with heightened regularity, using wave intervals, amplitudes and shapes. The performance of the algorithm was assessed with the use of event-based and liberal and conservative time-based approaches and compared with the performance of Gotman's and Liu's algorithms. Results: The algorithm was assessed on multi-channel EEG records of 55 neonates including 17 with seizures. The algorithm showed sensitivities ranging 83-95% with positive predictive values (PPV) 48-77%. There were 2.0 false positive detections per hour. In comparison, Gotman's algorithm (with 30 s gap-closing procedure) displayed sensitivities of 45-88% and PPV 29-56%; with 7.4 false positives per hour and Liu's algorithm displayed sensitivities of 96-99%, and PPV 10-25%; with 15.7 false positives per hour. Conclusions: The wave-sequence analysis based algorithm displayed higher sensitivity, higher PPV and a substantially lower level of false positives than two previously published algorithms. Significance: The proposed algorithm provides a basis for major improvements in neonatal seizure detection and monitoring. Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.

A qualitative assessment of communicating spatial concepts in virtual and physical environments via a text-based medium

The pedagogical exercise described here was used to investigate how spatial communication about the manipulation of objects in a virtual and physical space is communicated between remote partners. It continues work done by others. Where it differs from previous research in this area is in its use of a qualitative methodology to study how these types of interactions are structured, communicated and interpreted via text-based media. What emerged from the qualitative analysis are new insights over the previous quantitative investigations. This paper reports on completed research.

Comparison of BR and QR Eigenvalue Algorithms for Power System Small Signal Stability Analysis

The BR algorithm is a novel and efficient method to find all eigenvalues of upper Hessenberg matrices and has never been applied to eigenanalysis for power system small signal stability. This paper analyzes differences between the BR and the QR algorithms with performance comparison in terms of CPU time based on stopping criteria and storage requirement. The BR algorithm utilizes accelerating strategies to improve its performance when computing eigenvalues of narrowly banded, nearly tridiagonal upper Hessenberg matrices. These strategies significantly reduce the computation time at a reasonable level of precision. Compared with the QR algorithm, the BR algorithm requires fewer iteration steps and less storage space without depriving of appropriate precision in solving eigenvalue problems of large-scale power systems. Numerical examples demonstrate the efficiency of the BR algorithm in pursuing eigenanalysis tasks of 39-, 68-, 115-, 300-, and 600-bus systems. Experiment results suggest that the BR algorithm is a more efficient algorithm for large-scale power system small signal stability eigenanalysis.

Architecture and morphogenesis of grain sorghum, Sorghum bicolor (L.) Moench

Plant architecture has been neglected in most studies of biomass allocation in crops. To help redress this situation for grain sorghum (Sorghum bicolor (L.) Moench), we used a 3D digitiser to measure the dimensions and orientations of vegetative and reproductive structures and derived thermal time-based functions for architectural changes during morphogenesis. Our plants, which were grown in a greenhouse, controlled environment cabinets and the field, covered a large, three-fold, size range when mature. This allowed us to detect some general architectural relationships and to fit morphogenetic functions common across the size range we observed. For example, the relationship between the lengths of successive fully-expanded leaves within a plant was nearly constant for all plants. The lengths of existing leaf blades were accurate predictors of the lengths of up to six subsequently-formed blades in our plants. Similar constant relationships were detected for internode lengths in the panicle and for heights above ground of the collars of successive leaves, even though these traits varied a lot between growth conditions. We suggest that such architectural relationships may be used to link the effect of previous growth conditions to future growth potential, and in that way to predict future partitioning. Our results provide the basis for a preliminary model of sorghum morphogenesis which could eventually become useful in conjunction with crop models by allowing resource acquisition to be related to changes in plant architecture during development. (C) 1999 Elsevier Science B.V. All rights reserved.

Extinction of affective learning: No evidence for dual process accounts of human learning

The acquisition and extinction of affective valence to neutral geometrical shape conditional stimuli was investigated in three experiments. Experiment 1 employed a differential conditioning procedure with aversive shock USs. Differential electrodermal responding was evident during acquisition and lost during extinction. As indexed by verbal ratings, the CS1 acquired negative valence during acquisition,which was reduced after extinction. Affective priming, a reaction time based demand free measure of stimulus valence, failed to provide evidence for affective learning. Experiment 2 employed pictures of happy and angry faces as USs.Valence ratings after acquisitionweremore positive for theCS paired with happy faces (CS-H) and less positive for the CS paired with angry faces (CS-A) than during baseline. Extinction training reduced the extent of acquired valence significantly for both CSs, however, ratings of the CS-A remained different from baseline. Affective priming confirmed these results yielding differences between CS-A and CS-H after acquisition for pleasant and unpleasant targets, but for pleasant targets only after extinction. Experiment 3 replicated the design of Experiment 2, but presented the US pictures backwardly masked. Neither rating nor affective priming measures yielded any evidence for affective learning. The present results confirm across two different experimental procedures that, contrary to predictions from dual process accounts of human learning, affective learning is subject to extinction.

Extending a model of shift-work tolerance

The present study contributes to theory and practice through the development of a model of shift-work tolerance with the potential to indicate interventions that reduce nurses' intention toward turnover and increase job satisfaction in hospital-based settings. Survey data from 1257 nurses were used to conduct structural equation modeling that examine the direct and indirect effects of supervisor and colleague support, team identity, team climate, and control over working environment on time-based work/life conflict, psychological well-being, physical symptoms, job satisfaction, and turnover intention. The analysis of the proposed model revealed a good fit The chi-square difference test was non-significant (χ2(26)=338.56), the fit indices were high (CFI=.923, NFI=.918, and NNFI=.868), the distribution of residuals was symmetric and approached zero, the average standardized residual was low (AASR=.04), and the standardized RMR was .072. In terms of the predictor variable, the final model explained 48% of the variance in turnover intention. The data revealed considerable evidence of both direct effects on adjustment and complex indirect links between levels of adjustment and work-related social support, team identity, team climate, and control. Nurses with high supervisor and coworker support experienced more positive team climates, identified more strongly with their team, and increased their perceptions of control over their work environment. This in turn lowered their appraisals of their time-based work/life conflict, which consequently increased their psychological well-being and job satisfaction and reduced their physical health symptoms and turnover intention. The type of shift schedule worked by the nurses influenced levels of turnover intention, control over work environment, time-based work/life conflict, and physical symptoms.

A scaleless data model for direct and progressive spatial query processing

A progressive spatial query retrieves spatial data based on previous queries (e.g., to fetch data in a more restricted area with higher resolution). A direct query, on the other side, is defined as an isolated window query. A multi-resolution spatial database system should support both progressive queries and traditional direct queries. It is conceptually challenging to support both types of query at the same time, as direct queries favour location-based data clustering, whereas progressive queries require fragmented data clustered by resolutions. Two new scaleless data structures are proposed in this paper. Experimental results using both synthetic and real world datasets demonstrate that the query processing time based on the new multiresolution approaches is comparable and often better than multi-representation data structures for both types of queries.

Prediction of slurry transport in SAG mills using SPH fluid flow in a dynamic DEM based porous media

DEM modelling of the motion of coarse fractions of the charge inside SAG mills has now been well established for more than a decade. In these models the effect of slurry has broadly been ignored due to its complexity. Smoothed particle hydrodynamics (SPH) provides a particle based method for modelling complex free surface fluid flows and is well suited to modelling fluid flow in mills. Previous modelling has demonstrated the powerful ability of SPH to capture dynamic fluid flow effects such as lifters crashing into slurry pools, fluid draining from lifters, flow through grates and pulp lifter discharge. However, all these examples were limited by the ability to model only the slurry in the mill without the charge. In this paper, we represent the charge as a dynamic porous media through which the SPH fluid is then able to flow. The porous media properties (specifically the spatial distribution of porosity and velocity) are predicted by time averaging the mill charge predicted using a large scale DEM model. This allows prediction of transient and steady state slurry distributions in the mill and allows its variation with operating parameters, slurry viscosity and slurry volume, to be explored. (C) 2006 Published by Elsevier Ltd.

An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters' responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers' behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief-desire-intention agent architecture. (C) 2002 Elsevier Science Ltd. All rights reserved.

Finite-difference time-domain-based studies of MRI pulsed field gradient-induced eddy currents inside the human body

In modern magnetic resonance imaging (MRI), patients are exposed to strong, rapidly switching magnetic gradient fields that, in extreme cases, may be able to elicit nerve stimulation. This paper presents theoretical investigations into the spatial distribution of induced current inside human tissues caused by pulsed z-gradient fields. A variety of gradient waveforms have been studied. The simulations are based on a new, high-definition, finite-difference time-domain method and a realistic inhomogeneous 10-mm resolution human body model with appropriate tissue parameters. it was found that the eddy current densities are affected not only by the pulse sequences but by many parameters such as the position of the body inside the gradient set, the local biological material properties and the geometry of the body. The discussion contains a comparison of these results with previous results found in the literature. This study and the new methods presented herein will help to further investigate the biological effects caused by the switched gradient fields in a MRI scan. (C) 2002 Wiley Periodicals, Inc.

Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects Adjustment

A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting. Copyright (C) 2004 John Wiley Sons, Ltd.

Mammography screening participation: effects of a media campaign targeting Italian-speaking women

Objectives: To evaluate the effect of a radio and newspaper campaign encouraging Italian-speaking women aged 50-69 years to attend a population-based mammography screening program. Methods: A series of radio scripts and newspaper advertisements ran weekly in the Italian-language media over two, four-week periods. Monthly mammography screens were analysed to determine if numbers of Italian-speaking women in the program increased during the two campaign periods, using interrupted time series regression analysis. A survey of Italian-speaking women attending BreastScreen NSW during the campaign period (n=240) investigated whether individuals had heard or seen the advertisements. Results: There was no statistically significant difference in the number of initial or subsequent mammograms in Italian-speaking women between the campaign periods and the period prior to (or after) the campaign. Twenty per cent of respondents cited the Italian media campaign as a prompt to attend. Fifty per cent had heard the radio ad and 30% had seen the newspaper ad encouraging Italian-speaking women to attend BSNSW. The most common prompt to attend was the BSNSW invitation letter, followed by information or recommendation from a GP. Conclusion: Radio and newspaper advertisements developed for the Italian community did not significantly increase attendance to BSNSW. Implications: Measures of program effectiveness based on self-report may not correspond to aggregate screening behaviour. The development of the media campaign in conjunction with the Italian community, and the provision of appropriate levels of resourcing, did not ensure the media campaign's success.

Anisotropy-based performance analysis of linear discrete time invariant control systems

The anisotropic norm of a linear discrete-time-invariant system measures system output sensitivity to stationary Gaussian input disturbances of bounded mean anisotropy. Mean anisotropy characterizes the degree of predictability (or colouredness) and spatial non-roundness of the noise. The anisotropic norm falls between the H-2 and H-infinity norms and accommodates their loss of performance when the probability structure of input disturbances is not exactly known. This paper develops a method for numerical computation of the anisotropic norm which involves linked Riccati and Lyapunov equations and an associated special type equation.