A multivariate approach to the identification of surrogate parameters for heavy metals in stormwater

Stormwater is a potential and readily available alternative source for potable water in urban areas. However, its direct use is severely constrained by the presence of toxic pollutants, such as heavy metals (HMs). The presence of HMs in stormwater is of concern because of their chronic toxicity and persistent nature. In addition to human health impacts, metals can contribute to adverse ecosystem health impact on receiving waters. Therefore, the ability to predict the levels of HMs in stormwater is crucial for monitoring stormwater quality and for the design of effective treatment systems. Unfortunately, the current laboratory methods for determining HM concentrations are resource intensive and time consuming. In this paper, applications of multivariate data analysis techniques are presented to identify potential surrogate parameters which can be used to determine HM concentrations in stormwater. Accordingly, partial least squares was applied to identify a suite of physicochemical parameters which can serve as indicators of HMs. Datasets having varied characteristics, such as land use and particle size distribution of solids, were analyzed to validate the efficacy of the influencing parameters. Iron, manganese, total organic carbon, and inorganic carbon were identified as the predominant parameters that correlate with the HM concentrations. The practical extension of the study outcomes to urban stormwater management is also discussed.

Linear adaptive channel equalization for multiuser MIMO-OFDM systems

Linear adaptive channel equalization using the least mean square (LMS) algorithm and the recursive least-squares(RLS) algorithm for an innovative multi-user (MU) MIMOOFDM wireless broadband communications system is proposed. The proposed equalization method adaptively compensates the channel impairments caused by frequency selectivity in the propagation environment. Simulations for the proposed adaptive equalizer are conducted using a training sequence method to determine optimal performance through a comparative analysis. Results show an improvement of 0.15 in BER (at a SNR of 16 dB) when using Adaptive Equalization and RLS algorithm compared to the case in which no equalization is employed. In general, adaptive equalization using LMS and RLS algorithms showed to be significantly beneficial for MU-MIMO-OFDM systems.

Chronological categorization and decomposition of customer loads

The majority of distribution utilities do not have accurate information on the constituents of their loads. This information is very useful in managing and planning the network, adequately and economically. Customer loads are normally categorized in three main sectors: 1) residential; 2) industrial; and 3) commercial. In this paper, penalized least-squares regression and Euclidean distance methods are developed for this application to identify and quantify the makeup of a feeder load with unknown sectors/subsectors. This process is done on a monthly basis to account for seasonal and other load changes. The error between the actual and estimated load profiles are used as a benchmark of accuracy. This approach has shown to be accurate in identifying customer types in unknown load profiles, and is used in cross-validation of the results and initial assumptions.

Extending and validating the is-impact model in Saudi Arabia : accounting for computer network quality

Organizations from every industry sector seek to enhance their business performance and competitiveness through the deployment of contemporary information systems (IS), such as Enterprise Systems (ERP). Investments in ERP are complex and costly, attracting scrutiny and pressure to justify their cost. Thus, IS researchers highlight the need for systematic evaluation of information system success, or impact, which has resulted in the introduction of varied models for evaluating information systems. One of these systematic measurement approaches is the IS-Impact Model introduced by a team of researchers at Queensland University of technology (QUT) (Gable, Sedera, & Chan, 2008). The IS-Impact Model is conceptualized as a formative, multidimensional index that consists of four dimensions. Gable et al. (2008) define IS-Impact as "a measure at a point in time, of the stream of net benefits from the IS, to date and anticipated, as perceived by all key-user-groups" (p.381). The IT Evaluation Research Program (ITE-Program) at QUT has grown the IS-Impact Research Track with the central goal of conducting further studies to enhance and extend the IS-Impact Model. The overall goal of the IS-Impact research track at QUT is "to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice" (Gable, 2009). In order to achieve that, the IS-Impact research track advocates programmatic research having the principles of tenacity, holism, and generalizability through extension research strategies. This study was conducted within the IS-Impact Research Track, to further generalize the IS-Impact Model by extending it to the Saudi Arabian context. According to Hofsted (2012), the national culture of Saudi Arabia is significantly different from the Australian national culture making the Saudi Arabian culture an interesting context for testing the external validity of the IS-Impact Model. The study re-visits the IS-Impact Model from the ground up. Rather than assume the existing instrument is valid in the new context, or simply assess its validity through quantitative data collection, the study takes a qualitative, inductive approach to re-assessing the necessity and completeness of existing dimensions and measures. This is done in two phases: Exploratory Phase and Confirmatory Phase. The exploratory phase addresses the first research question of the study "Is the IS-Impact Model complete and able to capture the impact of information systems in Saudi Arabian Organization?". The content analysis, used to analyze the Identification Survey data, indicated that 2 of the 37 measures of the IS-Impact Model are not applicable for the Saudi Arabian Context. Moreover, no new measures or dimensions were identified, evidencing the completeness and content validity of the IS-Impact Model. In addition, the Identification Survey data suggested several concepts related to IS-Impact, the most prominent of which was "Computer Network Quality" (CNQ). The literature supported the existence of a theoretical link between IS-Impact and CNQ (CNQ is viewed as an antecedent of IS-Impact). With the primary goal of validating the IS-Impact model within its extended nomological network, CNQ was introduced to the research model. The Confirmatory Phase addresses the second research question of the study "Is the Extended IS-Impact Model Valid as a Hierarchical Multidimensional Formative Measurement Model?". The objective of the Confirmatory Phase was to test the validity of IS-Impact Model and CNQ Model. To achieve that, IS-Impact, CNQ, and IS-Satisfaction were operationalized in a survey instrument, and then the research model was assessed by employing the Partial Least Squares (PLS) approach. The CNQ model was validated as a formative model. Similarly, the IS-Impact Model was validated as a hierarchical multidimensional formative construct. However, the analysis indicated that one of the IS-Impact Model indicators was insignificant and can be removed from the model. Thus, the resulting Extended IS-Impact Model consists of 4 dimensions and 34 measures. Finally, the structural model was also assessed against two aspects: explanatory and predictive power. The analysis revealed that the path coefficient between CNQ and IS-Impact is significant with t-value= (4.826) and relatively strong with â = (0.426) with CNQ explaining 18% of the variance in IS-Impact. These results supported the hypothesis that CNQ is antecedent of IS-Impact. The study demonstrates that the quality of Computer Network affects the quality of the Enterprise System (ERP) and consequently the impacts of the system. Therefore, practitioners should pay attention to the Computer Network quality. Similarly, the path coefficient between IS-Impact and IS-Satisfaction was significant t-value = (17.79) and strong â = (0.744), with IS-Impact alone explaining 55% of the variance in Satisfaction, consistent with results of the original IS-Impact study (Gable et al., 2008). The research contributions include: (a) supporting the completeness and validity of IS-Impact Model as a Hierarchical Multi-dimensional Formative Measurement Model in the Saudi Arabian context, (b) operationalizing Computer Network Quality as conceptualized in the ITU-T Recommendation E.800 (ITU-T, 1993), (c) validating CNQ as a formative measurement model and as an antecedent of IS Impact, and (d) conceptualizing and validating IS-Satisfaction as a reflective measurement model and as an immediate consequence of IS Impact. The CNQ model provides a framework to perceptually measure Computer Network Quality from multiple perspectives. The CNQ model features an easy-to-understand, easy-to-use, and economical survey instrument.

In pursuit of tourism destination brand loyalty : visitor relationship management orientation of destination marketing organisations

The proposition underpinning this study is engaging in meaningful dialogue with previous visitors represents an efficient and effective use of resources for a destination marketing organization (DMO), compared to above the line advertising in broadcast media. However there has been a lack of attention in the tourism literature relating to destination switching, loyalty and customer relationship management (CRM) to test such a proposition. This paper reports an investigation of visitor relationship marketing (VRM) orientation among DMOs. A model of CRM orientation, which was developed from the wider marketing literature and a prior qualitative study, was used to develop a scale to operationalise DMO visitor relationship orientation. Due to a small sample, the Partial Least Squares (PLS) method of structural equation modelling was used to analyse the data. Although the sample limits the ability to generalise, the results indicated the DMOs’ visitor orientation is generally responsive and reactive rather than proactive.

Near infrared (NIR) absorption spectra correlates with subchondral bone micro-CT parameters in osteoarthritic rat models

Determining the properties and integrity of subchondral bone in the developmental stages of osteoarthritis, especially in a form that can facilitate real-time characterization for diagnostic and decision-making purposes, is still a matter for research and development. This paper presents relationships between near infrared absorption spectra and properties of subchondral bone obtained from 3 models of osteoarthritic degeneration induced in laboratory rats via: (i) menisectomy (MSX); (ii) anterior cruciate ligament transaction (ACL); and (iii) intra-articular injection of mono-ido-acetate (1 mg) (MIA), in the right knee joint, with 12 rats per model group (N = 36). After 8 weeks, the animals were sacrificed and knee joints were collected. A custom-made diffuse reflectance NIR probe of diameter 5 mm was placed on the tibial surface and spectral data were acquired from each specimen in the wavenumber range 4000–12 500 cm− 1. After spectral acquisition, micro computed tomography (micro-CT) was performed on the samples and subchondral bone parameters namely: bone volume (BV) and bone mineral density (BMD) were extracted from the micro-CT data. Statistical correlation was then conducted between these parameters and regions of the near infrared spectra using multivariate techniques including principal component analysis (PCA), discriminant analysis (DA), and partial least squares (PLS) regression. Statistically significant linear correlations were found between the near infrared absorption spectra and subchondral bone BMD (R2 = 98.84%) and BV (R2 = 97.87%). In conclusion, near infrared spectroscopic probing can be used to detect, qualify and quantify changes in the composition of the subchondral bone, and could potentially assist in distinguishing healthy from OA bone as demonstrated with our laboratory rat models.

Labour, social and health outcomes of immigrants in Australia : effects of language proficiency using the IV approach

Language has been of interest to numerous economists since the late 20th century, with the majority of the studies focusing on its effects on immigrants’ labour market outcomes; earnings in particular. However, language is an endogenous variable, which along with its susceptibility to measurement error causes biases in ordinary-least-squares estimates. The instrumental variables method overcomes the shortcomings of ordinary least squares in modelling endogenous explanatory variables. In this dissertation, age at arrival combined with country of origin form an instrument creating a difference-in-difference scenario, to address the issue of endogeneity and attenuation error in language proficiency. The first half of the study aims to investigate the extent to which English speaking ability of immigrants improves their labour market outcomes and social assimilation in Australia, with the use of the 2006 Census. The findings have provided evidence that support the earlier studies. As expected, immigrants in Australia with better language proficiency are able to earn higher income, attain higher level of education, have higher probability of completing tertiary studies, and have more hours of work per week. Language proficiency also improves social integration, leading to higher probability of marriage to a native and higher probability of obtaining citizenship. The second half of the study further investigates whether language proficiency has similar effects on a migrant’s physical and mental wellbeing, health care access and lifestyle choices, with the use of three National Health Surveys. However, only limited evidence has been found with respect to the hypothesised causal relationship between language and health for Australian immigrants.

Mathematical modelling of LiFePO4 cathodes

LiFePO4 is a commercially available battery material with good theoretical discharge capacity, excellent cycle life and increased safety compared with competing Li-ion chemistries. It has been the focus of considerable experimental and theoretical scrutiny in the past decade, resulting in LiFePO4 cathodes that perform well at high discharge rates. This scrutiny has raised several questions about the behaviour of LiFePO4 material during charge and discharge. In contrast to many other battery chemistries that intercalate homogeneously, LiFePO4 can phase-separate into highly and lowly lithiated phases, with intercalation proceeding by advancing an interface between these two phases. The main objective of this thesis is to construct mathematical models of LiFePO4 cathodes that can be validated against experimental discharge curves. This is in an attempt to understand some of the multi-scale dynamics of LiFePO4 cathodes that can be difficult to determine experimentally. The first section of this thesis constructs a three-scale mathematical model of LiFePO4 cathodes that uses a simple Stefan problem (which has been used previously in the literature) to describe the assumed phase-change. LiFePO4 crystals have been observed agglomerating in cathodes to form a porous collection of crystals and this morphology motivates the use of three size-scales in the model. The multi-scale model developed validates well against experimental data and this validated model is then used to examine the role of manufacturing parameters (including the agglomerate radius) on battery performance. The remainder of the thesis is concerned with investigating phase-field models as a replacement for the aforementioned Stefan problem. Phase-field models have recently been used in LiFePO4 and are a far more accurate representation of experimentally observed crystal-scale behaviour. They are based around the Cahn-Hilliard-reaction (CHR) IBVP, a fourth-order PDE with electrochemical (flux) boundary conditions that is very stiff and possesses multiple time and space scales. Numerical solutions to the CHR IBVP can be difficult to compute and hence a least-squares based Finite Volume Method (FVM) is developed for discretising both the full CHR IBVP and the more traditional Cahn-Hilliard IBVP. Phase-field models are subject to two main physicality constraints and the numerical scheme presented performs well under these constraints. This least-squares based FVM is then used to simulate the discharge of individual crystals of LiFePO4 in two dimensions. This discharge is subject to isotropic Li+ diffusion, based on experimental evidence that suggests the normally orthotropic transport of Li+ in LiFePO4 may become more isotropic in the presence of lattice defects. Numerical investigation shows that two-dimensional Li+ transport results in crystals that phase-separate, even at very high discharge rates. This is very different from results shown in the literature, where phase-separation in LiFePO4 crystals is suppressed during discharge with orthotropic Li+ transport. Finally, the three-scale cathodic model used at the beginning of the thesis is modified to simulate modern, high-rate LiFePO4 cathodes. High-rate cathodes typically do not contain (large) agglomerates and therefore a two-scale model is developed. The Stefan problem used previously is also replaced with the phase-field models examined in earlier chapters. The results from this model are then compared with experimental data and fit poorly, though a significant parameter regime could not be investigated numerically. Many-particle effects however, are evident in the simulated discharges, which match the conclusions of recent literature. These effects result in crystals that are subject to local currents very different from the discharge rate applied to the cathode, which impacts the phase-separating behaviour of the crystals and raises questions about the validity of using cathodic-scale experimental measurements in order to determine crystal-scale behaviour.

Rapid quantification of methamphetamine: using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR) and Chemometrics

In Australia and increasingly worldwide, methamphetamine is one of the most commonly seized drugs analysed by forensic chemists. The current well-established GC/MS methods used to identify and quantify methamphetamine are lengthy, expensive processes, but often rapid analysis is requested by undercover police leading to an interest in developing this new analytical technique. Ninety six illicit drug seizures containing methamphetamine (0.1% - 78.6%) were analysed using Fourier Transform Infrared Spectroscopy with an Attenuated Total Reflectance attachment and Chemometrics. Two Partial Least Squares models were developed, one using the principal Infrared Spectroscopy peaks of methamphetamine and the other a Hierarchical Partial Least Squares model. Both of these models were refined to choose the variables that were most closely associated with the methamphetamine % vector. Both of the models were excellent, with the principal peaks in the Partial Least Squares model having Root Mean Square Error of Prediction 3.8, R2 0.9779 and lower limit of quantification 7% methamphetamine. The Hierarchical Partial Least Squares model had lower limit of quantification 0.3% methamphetamine, Root Mean Square Error of Prediction 5.2 and R2 0.9637. Such models offer rapid and effective methods for screening illicit drug samples to determine the percentage of methamphetamine they contain.

Achieving high reliability for ambiguity resolutions with multiple GNSS constellations

Global Navigation Satellite Systems (GNSS)-based observation systems can provide high precision positioning and navigation solutions in real time, in the order of subcentimetre if we make use of carrier phase measurements in the differential mode and deal with all the bias and noise terms well. However, these carrier phase measurements are ambiguous due to unknown, integer numbers of cycles. One key challenge in the differential carrier phase mode is to fix the integer ambiguities correctly. On the other hand, in the safety of life or liability-critical applications, such as for vehicle safety positioning and aviation, not only is high accuracy required, but also the reliability requirement is important. This PhD research studies to achieve high reliability for ambiguity resolution (AR) in a multi-GNSS environment. GNSS ambiguity estimation and validation problems are the focus of the research effort. Particularly, we study the case of multiple constellations that include initial to full operations of foreseeable Galileo, GLONASS and Compass and QZSS navigation systems from next few years to the end of the decade. Since real observation data is only available from GPS and GLONASS systems, the simulation method named Virtual Galileo Constellation (VGC) is applied to generate observational data from another constellation in the data analysis. In addition, both full ambiguity resolution (FAR) and partial ambiguity resolution (PAR) algorithms are used in processing single and dual constellation data. Firstly, a brief overview of related work on AR methods and reliability theory is given. Next, a modified inverse integer Cholesky decorrelation method and its performance on AR are presented. Subsequently, a new measure of decorrelation performance called orthogonality defect is introduced and compared with other measures. Furthermore, a new AR scheme considering the ambiguity validation requirement in the control of the search space size is proposed to improve the search efficiency. With respect to the reliability of AR, we also discuss the computation of the ambiguity success rate (ASR) and confirm that the success rate computed with the integer bootstrapping method is quite a sharp approximation to the actual integer least-squares (ILS) method success rate. The advantages of multi-GNSS constellations are examined in terms of the PAR technique involving the predefined ASR. Finally, a novel satellite selection algorithm for reliable ambiguity resolution called SARA is developed. In summary, the study demonstrats that when the ASR is close to one, the reliability of AR can be guaranteed and the ambiguity validation is effective. The work then focuses on new strategies to improve the ASR, including a partial ambiguity resolution procedure with a predefined success rate and a novel satellite selection strategy with a high success rate. The proposed strategies bring significant benefits of multi-GNSS signals to real-time high precision and high reliability positioning services.

Genetic improvement of giant freshwater prawn in Vietnam

The giant freshwater prawn (Macrobrachium rosenbergii) or GFP is one of the most important freshwater crustacean species in the inland aquaculture sector of many tropical and subtropical countries. Since the 1990’s, there has been rapid global expansion of freshwater prawn farming, especially in Asian countries, with an average annual rate of increase of 48% between 1999 and 2001 (New, 2005). In Vietnam, GFP is cultured in a variety of culture systems, typically in integrated or rotational rice-prawn culture (Phuong et al., 2006) and has become one of the most common farmed aquatic species in the country, due to its ability to grow rapidly and to attract high market price and high demand. Despite potential for expanded production, sustainability of freshwater prawn farming in the region is currently threatened by low production efficiency and vulnerability of farmed stocks to disease. Commercial large scale and small scale GFP farms in Vietnam have experienced relatively low stock productivity, large size and weight variation, a low proportion of edible meat (large head to body ratio), scarcity of good quality seed stock. The current situation highlights the need for a systematic stock improvement program for GFP in Vietnam aimed at improving economically important traits in this species. This study reports on the breeding program for fast growth employing combined (between and within) family selection in giant freshwater prawn in Vietnam. The base population was synthesized using a complete diallel cross including 9 crosses from two local stocks (DN and MK strains) and a third exotic stock (Malaysian strain - MY). In the next three selection generations, matings were conducted between genetically unrelated brood stock to produce full-sib and (paternal) half-sib families. All families were produced and reared separately until juveniles in each family were tagged as a batch using visible implant elastomer (VIE) at a body size of approximately 2 g. After tags were verified, 60 to 120 juveniles chosen randomly from each family were released into two common earthen ponds of 3,500 m2 pond for a grow-out period of 16 to 18 weeks. Selection applied at harvest on body weight was a combined (between and within) family selection approach. 81, 89, 96 and 114 families were produced for the Selection line in the F0, F1, F2 and F3 generations, respectively. In addition to the Selection line, 17 to 42 families were produced for the Control group in each generation. Results reported here are based on a data set consisting of 18,387 body and 1,730 carcass records, as well as full pedigree information collected over four generations. Variance and covariance components were estimated by restricted maximum likelihood fitting a multi-trait animal model. Experiments assessed performance of VIE tags in juvenile GFP of different size classes and individuals tagged with different numbers of tags showed that juvenile GFP at 2 g were of suitable size for VIE tags with no negative effects evident on growth or survival. Tag retention rates were above 97.8% and tag readability rates were 100% with a correct assignment rate of 95% through to mature animal size of up to 170 g. Across generations, estimates of heritability for body traits (body weight, body length, cephalothorax length, abdominal length, cephalothorax width and abdominal width) and carcass weight traits (abdominal weight, skeleton-off weight and telson-off weight) were moderate and ranged from 0.14 to 0.19 and 0.17 to 0.21, respectively. Body trait heritabilities estimated for females were significantly higher than for males whereas carcass weight trait heritabilities estimated for females and males were not significantly different (P > 0.05). Maternal and common environmental effects for body traits accounted for 4 to 5% of the total variance and were greater in females (7 to 10%) than in males (4 to 5%). Genetic correlations among body traits were generally high in both sexes. Genetic correlations between body and carcass weight traits were also high in the mixed sexes. Average selection response (% per generation) for body weight (transformed to square root) estimated as the difference between the Selection and the Control group was 7.4% calculated from least squares means (LSMs), 7.0% from estimated breeding values (EBVs) and 4.4% calculated from EBVs between two consecutive generations. Favourable correlated selection responses (estimated from LSMs) were detected for other body traits (12.1%, 14.5%, 10.4%, 15.5% and 13.3% for body length, cephalothorax length, abdominal length, cephalothorax width and abdominal width, respectively) over three selection generations. Data in the second selection generation showed positive correlated responses for carcass weight traits (8.8%, 8.6% and 8.8% for abdominal weight, skeleton-off weight and telson-off weight, respectively). Data in the third selection generation showed that heritability for body traits were moderate and ranged from 0.06 to 0.11 and 0.11 to 0.22 at weeks 10 and 18, respectively. Body trait heritabilities estimated at week 10 were not significantly lower than at week 18. Genetic correlations between body traits within age and genetic correlations for body traits between ages were generally high. Overall our results suggest that growth rate responds well to the application of family selection and carcass weight traits can also be improved in parallel, using this approach. Moreover, selection for high growth rate in GFP can be undertaken successfully before full market size has been reached. The outcome of this study was production of an improved culture strain of GFP for the Vietnamese culture industry that will be trialed in real farm production environments to confirm the genetic gains identified in the experimental stock improvement program.

Pixel value to electron density conversion for a Megavoltage Cone Beam CT System

Introduction: The motivation for developing megavoltage (and kilovoltage) cone beam CT (MV CBCT) capabilities in the radiotherapy treatment room was primarily based on the need to improve patient set-up accuracy. There has recently been an interest in using the cone beam CT data for treatment planning. Accurate treatment planning, however, requires knowledge of the electron density of the tissues receiving radiation in order to calculate dose distributions. This is obtained from CT, utilising a conversion between CT number and electron density of various tissues. The use of MV CBCT has particular advantages compared to treatment planning with kilovoltage CT in the presence of high atomic number materials and requires the conversion of pixel values from the image sets to electron density. Therefore, a study was undertaken to characterise the pixel value to electron density relationship for the Siemens MV CBCT system, MVision, and determine the effect, if any, of differing the number of monitor units used for acquisition. If a significant difference with number of monitor units was seen then pixel value to ED conversions may be required for each of the clinical settings. The calibration of the MV CT images for electron density offers the possibility for a daily recalculation of the dose distribution and the introduction of new adaptive radiotherapy treatment strategies. Methods: A Gammex Electron Density CT Phantom was imaged with the MVCB CT system. The pixel value for each of the sixteen inserts, which ranged from 0.292 to 1.707 relative electron density to the background solid water, was determined by taking the mean value from within a region of interest centred on the insert, over 5 slices within the centre of the phantom. These results were averaged and plotted against the relative electron densities of each insert with a linear least squares fit was preformed. This procedure was performed for images acquired with 5, 8, 15 and 60 monitor units. Results: The linear relationship between MVCT pixel value and ED was demonstrated for all monitor unit settings and over a range of electron densities. The number of monitor units utilised was found to have no significant impact on this relationship. Discussion: It was found that the number of MU utilised does not significantly alter the pixel value obtained for different ED materials. However, to ensure the most accurate and reproducible MV to ED calibration, one MU setting should be chosen and used routinely. To ensure accuracy for the clinical situation this MU setting should correspond to that which is used clinically. If more than one MU setting is used clinically then an average of the CT values acquired with different numbers of MU could be utilized without loss in accuracy. Conclusions: No significant differences have been shown between the pixel value to ED conversion for the Siemens MV CT cone beam unit with change in monitor units. Thus as single conversion curve could be utilised for MV CT treatment planning. To fully utilise MV CT imaging for radiotherapy treatment planning further work will be undertaken to ensure all corrections have been made and dose calculations verified. These dose calculations may be either for treatment planning purposes or for reconstructing the delivered dose distribution from transit dosimetry measurements made using electronic portal imaging devices. This will potentially allow the cumulative dose distribution to be determined through the patient’s multi-fraction treatment and adaptive treatment strategies developed to optimize the tumour response.

Mortality and cost outcomes of elderly trauma patients admitted to intensive care and the general wards of an Australian tertiary referral hospital

Mortality and cost outcomes of elderly intensive care unit (ICU) trauma patients were characterised in a retrospective cohort study from an Australian tertiary ICU. Trauma patients admitted between January 2000 and December 2005 were grouped into three major age categories: aged ≥65 years admitted into ICU (n=272); aged ≥65 years admitted into general ward (n=610) and aged <65 years admitted into ICU (n=1617). Hospital mortality predictors were characterised as odds ratios (OR) using logistic regression. The impact of predictor variables on (log) total hospital-stay costs was determined using least squares regression. An alternate treatment-effects regression model estimated the mortality cost-effect as an endogenous variable. Mortality predictors (P ≤0.0001, comparator: ICU ≥65 years, ventilated) were: ICU <65 not-ventilated (OR 0.014); ICU <65 ventilated (OR 0.090); ICU age ≥65 not-ventilated (OR 0.061) and ward ≥65 (OR 0.086); increasing injury severity score and increased Charlson comorbidity index of 1 and 2, compared with zero (OR 2.21 [1.40 to 3.48] and OR 2.57 [1.45 to 4.55]). The raw mean daily ICU and hospital costs in A$ 2005 (US$) for age <65 and ≥65 to ICU, and ≥65 to the ward were; for year 2000: ICU, $2717 (1462) and $2777 (1494); hospital, $1837 (988) and $1590 (855); ward $933 (502); for year 2005: ICU, $3202 (2393) and $3086 (2307); hospital, $1938 (1449) and $1914 (1431); ward $1180 (882). Cost increments were predicted by age ≥65 and ICU admission, increasing injury severity score, mechanical ventilation, Charlson comorbidity index increments and hospital survival. Mortalitycost-effect was estimated at -63% by least squares regression and -82% by treatment-effects regression model. Patient demographic factors, injury severity and its consequences predict both cost and survival in trauma. The cost mortality effect was biased upwards by conventional least squares regression estimation.

Measuring IS-support : a conceptual model

This paper reports on a conceptual model of a larger research effort proceeding from a central interest in the importance of assessing the IS-Support provided to key-user groups. This study conceptualised a new multidimensional IS-Support construct with four dimensions: training, documentation, assistance and authorisation, which form the overarching construct – IS-Support. We argue that a holistic measure for assessing IS-Support should consist of dimensions, and measures, that together assess the variety of the support provided to IS key-user groups. The proposed IS-Support construct is defined as the support the IS key-user groups receive to increase their capabilities in utilising information systems within the organisation. With two interrelated phases, conceptualisation phase and validation phase, to rigorously hypothesise and validate a measurement model, the IS-Support model, proposed in this study, is intended to include the characteristics of analytic theory.

Young men utilise limited neuromuscular prepartion to regulate post-impact knee mechanics during step landing

Purpose The neuromuscular mechanisms determining the mechanical behaviour of the knee during landing impact remain poorly understood. It was hypothesised that neuromuscular preparation is subject-specific and ranges along a continuum from passive to active. Methods A group of healthy men (N = 12) stepped-down from a knee-high platform for 60 consecutive trials. Surface EMG of the quadriceps and hamstrings was used to determine pre-impact onset timing, activation amplitude and cocontraction for each trial. Partial least squares regression was used to associate pre-impact preparation with post-impact knee stiffness and coordination. Results The group analysis revealed few significant changes in pre-impact preparation across trial blocks. Single-subject analyses revealed changes in muscle activity that varied in size and direction between individuals. Further, the association between pre-impact preparation and post-impact knee mechanics was subject-specific and ranged along a continuum of strategies. Conclusion The findings suggest that neuromuscular preparation during step landing is subject-specific and its association to post-impact knee mechanics occurs along a continuum, ranging from passive to active control strategies. Further work should examine the implications of these strategies on the distribution of knee forces in-vivo.