The measurement of adenosine and estrogen receptor expression in rat brains following ovariectomy using quantitative PCR analysis

In our laboratory we have developed a quantitative-polymerase chain reaction (Q-PCR) strategy to examine the differential expression of adenosine receptor (ADOR), A(1), A(2A), A(2B) and A(3), and estrogen receptors (ER) alpha and beta. Brain and uterine mRNA were first used to optimise specific amplification conditions prior to SYBR Green I real time analysis of receptor subtype expression. SYBR Green I provided a convenient and sensitive means of examining specific PCR amplification product in real time, and allowed the generation of standard curves from which relative receptor abundance could be determined. Real time Q-PCR analysis was then performed, to examine changes in receptor expression levels in brains of adult female Wistar rats 3-month post ovariectomy. Comparison with sham-operated age-matched control rats demonstrated both comparative and absolute-copy number changes in receptor levels. Evaluation of both analytical methods investigated 18S rRNA as an internal reference for comparative gene expression analysis in the brain. The results of this study revealed preferential repression of ADORA(2A) (>4-fold down) and consistent (>2-fold) down-regulation of ADORA(1), ADORA(3), and ER-beta, following ovariectomy. No change was found in ADORA(2B) or ER-alpha. Analysis of absolute copy number in this study revealed a correlation between receptor expression in response to ovariectomy, and relative receptor subtype abundance in the brain.

Size characterization of airborne SiO2 nanoparticles with on-line and off-line measurement techniques : an interlaboratory comparison study

Results of an interlaboratory comparison on size characterization of SiO2 airborne nanoparticles using on-line and off-line measurement techniques are discussed. This study was performed in the framework of Technical Working Area (TWA) 34—“Properties of Nanoparticle Populations” of the Versailles Project on Advanced Materials and Standards (VAMAS) in the project no. 3 “Techniques for characterizing size distribution of airborne nanoparticles”. Two types of nano-aerosols, consisting of (1) one population of nanoparticles with a mean diameter between 30.3 and 39.0 nm and (2) two populations of non-agglomerated nanoparticles with mean diameters between, respectively, 36.2–46.6 nm and 80.2–89.8 nm, were generated for characterization measurements. Scanning mobility particle size spectrometers (SMPS) were used for on-line measurements of size distributions of the produced nano-aerosols. Transmission electron microscopy, scanning electron microscopy, and atomic force microscopy were used as off-line measurement techniques for nanoparticles characterization. Samples were deposited on appropriate supports such as grids, filters, and mica plates by electrostatic precipitation and a filtration technique using SMPS controlled generation upstream. The results of the main size distribution parameters (mean and mode diameters), obtained from several laboratories, were compared based on metrological approaches including metrological traceability, calibration, and evaluation of the measurement uncertainty. Internationally harmonized measurement procedures for airborne SiO2 nanoparticles characterization are proposed.

Remote measurement of diesel locomotive emission factors and particle size distributions

A technique for analysing exhaust emission plumes from unmodified locomotives under real world conditions is described and applied to the task of characterizing plumes from railway trains servicing an Australian shipping port. The method utilizes the simultaneous measurement, downwind of the railway line, of the following pollutants; particle number, PM2.5 mass fraction, SO2, NOx and CO2, with the last of these being used as an indicator of fuel combustion. Emission factors are then derived, in terms of number of particles and mass of pollutant emitted per unit mass of fuel consumed. Particle number size distributions are also presented. The practical advantages of the method are discussed including the capacity to routinely collect emission factor data for passing trains and to thereby build up a comprehensive real world database for a wide range of pollutants. Samples from 56 train movements were collected, analyzed and presented. The quantitative results for emission factors are: EF(N)=(1.7±1)×1016 kg-1, EF(PM2.5)= (1.1±0.5) g·kg-1, EF(NOx)= (28±14) g·kg-1, and EF(SO2 )= (1.4±0.4) g·kg-1. The findings are compared with comparable previously published work. Statistically significant (p<α, α=0.05) correlations within the group of locomotives sampled were found between the emission factors for particle number and both SO2 and NOx.

Methodological considerations for meal-induced thermogenesis : measurement duration and reproducibility

Meal-Induced Thermogenesis (MIT) research findings are highly inconsistent, in part, due to the variety of durations and protocols used to measure MIT. We aimed to determine: 1) the proportion of a 6 h MIT response completed at 3, 4 and 5 h; 2) the associations between the shorter durations and the 6 h measure; 3) whether shorter durations improved the reproducibility of the measurement. MIT was measured in response to a 2410 KJ mixed composition meal in ten individuals (5 male, 5 female) on two occasions. Energy expenditure was measured continuously for 6 h post-meal using indirect calorimetry and MIT was calculated as the increase in energy expenditure above the pre-meal RMR. On average, 76%, 89%, and 96% of the 6 h MIT response was completed within 3, 4 and 5 h respectively, and the MIT at each of these time points was strongly correlated to the 6 h MIT (range for correlations, r = 0.990 to 0.998; p < 0.01). The between-day CV for the 6 h measurement was 33%, but was significantly lower after 3 h of measurement (CV = 26%, p = 0.02). Despite variability in the total MIT between days, the proportion of the MIT that was complete at 3, 4 and 5 h was reproducible (mean CV: 5%). While 6 h is typically required to measure the complete MIT response, 3 h measures provide sufficient information about the magnitude of the MIT response and may be applicable for measuring individuals on repeated occasions.

Traffic safety culture : what can we learn from Australia?

-- The role of traffic safety culture in Australia -- A comparison of drink driving (a success story) and speeding (a work in progress) ―Countermeasure approaches ―Community attitudes, perceptions and behaviors -- Lessons from Australia for the further development of the traffic safety culture concept

User expertise in contemporary information systems : conceptualization, measurement and application

This research proposes a method for identifying user expertise in contemporary Information Systems (IS). It also proposes and develops a model for evaluating expertise. The aim of this study was to offer a common instrument that addresses the requirements of a contemporary Information System in a holistic way. This study demonstrates the application of the expertise construct in Information System evaluations, and shows that users of different expertise levels evaluate systems differently.

Pre-crash traffic flow trend analysis on motorways

Crashes on motorway contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence reduce crashes will help address congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a Short time window around the time of crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques, that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists, and that this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with traffic flow data of one hour prior to the crash using an incident detection algorithm. Traffic flow trends (traffic speed/occupancy time series) revealed that crashes could be clustered with regards of the dominant traffic flow pattern prior to the crash. Using the k-means clustering method allowed the crashes to be clustered based on their flow trends rather than their distance. Four major trends have been found in the clustering results. Based on these findings, crash likelihood estimation algorithms can be fine-tuned based on the monitored traffic flow conditions with a sliding window of 60 minutes to increase accuracy of the results and minimize false alarms.

Pre-crash and non-crash traffic flow trends analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk” clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.

Measurement, modelling and capacity analysis for novel, fixed multi-user single-antenna MIMO-OFDM system, in rural environments

High-speed broadband internet access is widely recognised as a catalyst to social and economic development. However, the provision of broadband Internet services with the existing solutions to rural population, scattered over an extensive geographical area, remains both an economic and technical challenge. As a feasible solution, the Commonwealth Scientific and Industrial Research Organization (CSIRO) proposed a highly spectrally efficient, innovative and cost-effective fixed wireless broadband access technology, which uses analogue TV frequency spectrum and Multi-User MIMO (MUMIMO) technology with Orthogonal-Frequency-Division-Multiplexing (OFDM). MIMO systems have emerged as a promising solution for the increasing demand of higher data rates, better quality of service, and higher network capacity. However, the performance of MIMO systems can be significantly affected by different types of propagation environments e.g., indoor, outdoor urban, or outdoor rural and operating frequencies. For instance, large spectral efficiencies associated with MIMO systems, which assume a rich scattering environment in urban environments, may not be valid for all propagation environments, such as outdoor rural environments, due to the presence of less scatterer densities. Since this is the first time a MU-MIMO-OFDM fixed broadband wireless access solution is deployed in a rural environment, questions from both theoretical and practical standpoints arise; For example, what capacity gains are available for the proposed solution under realistic rural propagation conditions?. Currently, no comprehensive channel measurement and capacity analysis results are available for MU-MIMO-OFDM fixed broadband wireless access systems which employ large scale multiple antennas at the Access Point (AP) and analogue TV frequency spectrum in rural environments. Moreover, according to the literature, no deterministic MU-MIMO channel models exist that define rural wireless channels by accounting for terrain effects. This thesis fills the aforementioned knowledge gaps with channel measurements, channel modeling and comprehensive capacity analysis for MU-MIMO-OFDM fixed wireless broadband access systems in rural environments. For the first time, channel measurements were conducted in a rural farmland near Smithton, Tasmania using CSIRO's broadband wireless access solution. A novel deterministic MU-MIMO-OFDM channel model, which can be used for accurate performance prediction of rural MUMIMO channels with dominant Line-of-Sight (LoS) paths, was developed under this research. Results show that the proposed solution can achieve 43.7 bits/s/Hz at a Signal-to- Noise Ratio (SNR) of 20 dB in rural environments. Based on channel measurement results, this thesis verifies that the deterministic channel model accurately predicts channel capacity in rural environments with a Root Mean Square (RMS) error of 0.18 bits/s/Hz. Moreover, this study presents a comprehensive capacity analysis of rural MU-MIMOOFDM channels using experimental, simulated and theoretical models. Based on the validated deterministic model, further investigations on channel capacity and the eects of capacity variation, with different user distribution angles (θ) around the AP, were analysed. For instance, when SNR = 20dB, the capacity increases from 15.5 bits/s/Hz to 43.7 bits/s/Hz as θ increases from 10° to 360°. Strategies to mitigate these capacity degradation effects are also presented by employing a suitable user grouping method. Outcomes of this thesis have already been used by CSIRO scientists to determine optimum user distribution angles around the AP, and are of great significance for researchers and MU-MUMO-OFDM system developers to understand the advantages and potential capacity gains of MU-MIMO systems in rural environments. Also, results of this study are useful to further improve the performance of MU-MIMO-OFDM systems in rural environments. Ultimately, this knowledge contribution will be useful in delivering efficient, cost-effective high-speed wireless broadband systems that are tailor-made for rural environments, thus, improving the quality of life and economic prosperity of rural populations.

Speech interference on residential balconies with road traffic noise

Residential balcony design influences speech interference levels caused by road traffic noise and a simplified design methodology is needed for optimising balcony acoustic treatments. This research comprehensively assesses speech interference levels and benefits of nine different balcony designs situated in urban street canyons through the use of a combined direct, specular reflection and diffuse reflection path theoretical model. This thesis outlines the theory, analysis and results that lead up to the presentation of a practical design guide which can be used to predict the acoustic effects of balcony geometry and acoustic treatments in streets with variable geometry and acoustic characteristics.

A fuzzy TOPSIS based multi criteria performance measurement model for lean supply chain

Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.

Characteristics of police-reported road traffic crashes in Ethiopia over a six year period

Ethiopia has one of Africa’s fastest growing non-oil producing economies and an increasing level of motorisation (AfDB, OECD, UNDP, & UNECA, 2012). This rapidly increasing mobility has created some unique road safety concerns; however there is scant published information and related commentary (United Nations Economic Commission for Africa, 2009). The objective of this paper is to quantify police-reported traffic crashes in Ethiopia and characterise the existing state of road safety. Six years (July 2005 - June 2011) of police-reported crash data were analysed, consisting of 12,140 fatal and 29,454 injury crashes on the country’s road network. The 12,140 fatal crashes involved 1,070 drivers, 5,702 passengers, and 7,770 pedestrians, totalling 14,542 fatalities, an average of 1.2 road user fatalities per crash. An important and glaring trend that emerges is that more than half of the fatalities in Ethiopia involve pedestrians. The majority of the crashes occur during daytime hours, involve males, and involve persons in the 18-50 age group—Ethiopia’s active workforce. Crashes frequently occur in mid blocks or roadways. The predominant collision between motor vehicles and pedestrians was a rollover on a road tangent section. Failing to observe the priority of pedestrians and speeding were the major causes of crashes attributed by police. Trucks and minibus taxis were involved in the majority of crashes, while automobiles (small vehicles) were less involved in crashes relative to other vehicle types, partially because small vehicles tend to be driven fewer kilometres per annum. These data illustrate and justify a high priority to identify and implement effective programs, policies, and countermeasures focused on reducing pedestrian crashes.

Traffic density estimation of signalised arterials with stop line detector and probe data

This research aims to develop a reliable density estimation method for signalised arterials based on cumulative counts from upstream and downstream detectors. In order to overcome counting errors associated with urban arterials with mid-link sinks and sources, CUmulative plots and Probe Integration for Travel timE estimation (CUPRITE) is employed for density estimation. The method, by utilizing probe vehicles’ samples, reduces or cancels the counting inconsistencies when vehicles’ conservation is not satisfied within a section. The method is tested in a controlled environment, and the authors demonstrate the effectiveness of CUPRITE for density estimation in a signalised section, and discuss issues associated with the method.

Filter and control performance bounds in the presence of model uncertainties with aerospace applications

This thesis establishes performance properties for approximate filters and controllers that are designed on the basis of approximate dynamic system representations. These performance properties provide a theoretical justification for the widespread application of approximate filters and controllers in the common situation where system models are not known with complete certainty. This research also provides useful tools for approximate filter designs, which are applied to hybrid filtering of uncertain nonlinear systems. As a contribution towards applications, this thesis also investigates air traffic separation control in the presence of measurement uncertainties.

Random breath testing in Queensland and Western Australia : Examination of how the random breath testing rate influences alcohol related traffic crash rates

In this paper we explore the relationship between monthly random breath testing (RBT) rates (per 1000 licensed drivers) and alcohol-related traffic crash (ARTC) rates over time, across two Australian states: Queensland and Western Australia. We analyse the RBT, ARTC and licensed driver rates across 12 years; however, due to administrative restrictions, we model ARTC rates against RBT rates for the period July 2004 to June 2009. The Queensland data reveals that the monthly ARTC rate is almost flat over the five year period. Based on the results of the analysis, an average of 5.5 ARTCs per 100,000 licensed drivers are observed across the study period. For the same period, the monthly rate of RBTs per 1000 licensed drivers is observed to be decreasing across the study with the results of the analysis revealing no significant variations in the data. The comparison between Western Australia and Queensland shows that Queensland's ARTC monthly percent change (MPC) is 0.014 compared to the MPC of 0.47 for Western Australia. While Queensland maintains a relatively flat ARTC rate, the ARTC rate in Western Australia is increasing. Our analysis reveals an inverse relationship between ARTC RBT rates, that for every 10% increase in the percentage of RBTs to licensed driver there is a 0.15 decrease in the rate of ARTCs per 100,000 licenced drivers. Moreover, in Western Australia, if the 2011 ratio of 1:2 (RBTs to annual number of licensed drivers) were to double to a ratio of 1:1, we estimate the number of monthly ARTCs would reduce by approximately 15. Based on these findings we believe that as the number of RBTs conducted increases the number of drivers willing to risk being detected for drinking driving decreases, because the perceived risk of being detected is considered greater. This is turn results in the number of ARTCs diminishing. The results of this study provide an important evidence base for policy decisions for RBT operations.