Preliminary results on the chemical composition of outdoor airborne particles at urban schools and possible implications for the air quality in classrooms

Vehicle emissions are a significant source of fine particles (Dp < 2.5 µm) in an urban environment. These fine particles have been shown to have detrimental health effects, with children thought to be more susceptible. Vehicle emissions are mainly carbonaceous in nature, and carbonaceous aerosols can be defined as either elemental carbon (EC) or organic carbon (OC). EC is a soot-like material emitted from primary sources while OC fraction is a complex mixture of hundreds of organic compounds from either primary or secondary sources (Cao et al., 2006). Therefore the ratio of OC/EC can aid in the identification of source. The purpose of this paper is to use the concentration of OC and EC in fine particles to determine the levels of vehicle emissions in schools. It is expected that this will improve the understanding of the potential exposure of children in a school environment to vehicle emissions.

Questions and Answers : Contract Law [4th ed.]

LexisNexis Questions & Answers - Contract Law provides an understanding of contract law and gives a clear and systematic approach to analysing and answering problem and exam questions. Each chapter commences with a summary of the relevant cases and identification of the key issues. Each question is followed by a suggested answer plan, a sample answer and comments on how the answer might be assessed by an examiner. The author also offers advice on common errors to avoid and practical hints and tips on how to achieve higher marks.

Potentials of social media for tacit knowledge sharing amongst physicians : preliminary findings

Tacit knowledge sharing amongst physicians, such as the sharing of clinical experiences, skills, or know-how, or know-whom, is known to have a significant impact on the quality of medical diagnosis and decisions. This paper posits that social media can provide new opportunities for tacit knowledge sharing amongst physicians, and demonstrates this by presenting findings from a review of relevant literature and a survey conducted with physicians. Semi-structured interviews were conducted with ten physicians from around the world who were active users of social media. Initial thematic analysis revealed eight themes as potential contributions of social web tools to facilitate tacit knowledge flow amongst physicians. The emergent themes are defined, linked to the literature, and supported by instances of interview transcripts. Findings presented here are preliminary, and final results will be reported after accomplishing all phases of data collection and analysis.

Efficient safety information retrieval on construction sites : a preliminary methodology

IT-supported field data management benefits on-site construction management by improving accessibility to the information and promoting efficient communication between project team members. However, most of on-site safety inspections still heavily rely on subjective judgment and manual reporting processes and thus observers’ experiences often determine the quality of risk identification and control. This study aims to develop a methodology to efficiently retrieve safety-related information so that the safety inspectors can easily access to the relevant site safety information for safer decision making. The proposed methodology consists of three stages: (1) development of a comprehensive safety database which contains information of risk factors, accident types, impact of accidents and safety regulations; (2) identification of relationships among different risk factors based on statistical analysis methods; and (3) user-specified information retrieval using data mining techniques for safety management. This paper presents an overall methodology and preliminary results of the first stage research conducted with 101 accident investigation reports.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

Using neo-Piagetian theory, formative in-Class tests and think alouds to better understand student thinking : a preliminary report on computer programming

It is acknowledged around the world that many university students struggle with learning to program (McCracken et al., 2001; McGettrick et al., 2005). In this paper, we describe how we have developed a research programme to systematically study and incrementally improve our teaching. We have adopted a research programme with three elements: (1) a theory that provides an organising framework for defining the type of phenomena and data of interest, (2) data on how the class as a whole performs on formative assessment tasks that are framed from within the organising framework, and (3) data from one-on-one think aloud sessions, to establish why students struggle with some of those in-class formative assessment tasks. We teach introductory computer programming, but this three-element structure of our research is applicable to many areas of engineering education research.

Executive function development and stress effects on driving performance : preliminary findings from a young adult sample.

This chapter presents a pilot study examining the interactive contributions of executive function development/impairment and psychosocial stress to young adults’ (17-30 years old) driving behaviour in a simulator city scenario.

Preliminary Design and Performance Estimation of Radial Inflow Turbines: An Automated Approach

A comprehensive one-dimensional meanline design approach for radial inflow turbines is described in the present work. An original code was developed in Python that takes a novel approach to the automatic selection of feasible machines based on pre-defined performance or geometry characteristics for a given application. It comprises a brute-force search algorithm that traverses the entire search space based on key non-dimensional parameters and rotational speed. In this study, an in-depth analysis and subsequent implementation of relevant loss models as well as selection criteria for radial inflow turbines is addressed. Comparison with previously published designs, as well as other available codes, showed good agreement. Sample (real and theoretical) test cases were trialed and results showed good agreement when compared to other available codes. The presented approach was found to be valid and the model was found to be a useful tool with regards to the preliminary design and performance estimation of radial inflow turbines, enabling its integration with other thermodynamic cycle analysis and three-dimensional blade design codes.

How do older adults respond to Active Australia physical activity questions? Lessons from cognitive interviews

The aim of this study was to examine older adults’ understanding and interpretation of a validated questionnaire for physical activity surveillance, the Active Australia Survey (AAS). To address this aim, cognitive interviewing techniques were used during face-to-face semi-structured interviews with 44 adults aged 65-89 years. Qualitative data analysis revealed that participants were confused with questionnaire phrasing, misunderstood the scope of activities to include in answers, and misunderstood the time frame of activities to report. They also struggled to accurately estimate the frequency and duration of their activities. Our findings suggest that AAS questions may be interpreted differently by older adults than intended by survey developers. Findings also suggest that older adults use a range of methods for calculating PA frequency and duration. The issues revealed in this study may be useful for adapting AAS for use in older community-dwelling adults.

An update on the Mackay Renewable Biocommodities Pilot Plant : preliminary trial results

THE Mackay Renewable Biocommodities Pilot Plant is a pilot scale facility owned and operated by QUT for research and demonstration of the conversion of lignocellulosic biomass such as sugarcane bagasse into biofuels. The pilot plant accommodates unique state-of-the-art equipment to process a wide range of feedstocks and is strategically located on the site of the Mackay Sugar Ltd Racecourse Mill. Major facilities include a biomass handling system, pre-treatment reactor, saccharification reactor, fermentors, distillation column and bioseparations equipment. This paper provides an update on the design, construction, commissioning and start-up of the facility. In addition, the paper provides results from preliminary facility trials on the pre-treatment of sugarcane bagasse for cellulosic ethanol production.

Commercial developments in airport precincts : lease and valuation issues : preliminary study

Over the past 30 years the nature of airport precincts has changed significantly from purely aviation services to a full range of retail, commercial, industrial and other non aviation uses. Most major airports in Australia are owned and operated by the private sector but are subject to long term head leases to the Federal Government, with subsequent sub leases in place to users of the land. The lease term available for both aviation and non aviation tenants is subject to the head lease term and in a number of Australian airport locations, these head leases are now two-thirds through their initial 50 year lease term and this is raising a number of issues from a valuation and ongoing development perspective. . For our airport precincts to continue to offer levels of infrastructure and services that are comparable or better than many commercial centres in the same location, policy makers need to understand the impact the uncertainty that exists when the current lease term is nearing expiration, especially in relation to the renewed lease term and rental payments. This paper reviews the changes in airport precinct ownership, management and development in Australia and highlights the valuation and rental assessment issues that are currently facing this property sector.

Simulation of phosphine flow in vertical grain storage : a preliminary numerical study

To fumigate grain stored in a silo, phosphine gas is distributed by a combination of diffusion and fan-forced advection. This initial study of the problem mainly focuses on the advection, numerically modelled as fluid flow in a porous medium. We find satisfactory agreement between the flow predictions of two Computational Fluid Dynamics packages, Comsol and Fluent. The flow predictions demonstrate that the highest velocity (>0.1 m/s) occurs less than 0.2m from the inlet and reduces drastically over one metre of silo height, with the flow elsewhere less than 0.002 m/s or 1% of the velocity injection. The flow predictions are examined to identify silo regions where phosphine dosage levels are likely to be too low for effective grain fumigation.

Preliminary reliability and validity testing of a self-efficacy questionnaire for Chinese family caregivers

Objectives: To develop and test preliminary reliability and validity of a Self-Efficacy Questionnaire for Chinese Family Caregivers (SEQCFC). Methods: A cross-sectional survey of 196 family caregivers (CGs) of people with dementia (CGs) was conducted to determine the factor structure of a SEQCFC of people with dementia. Following factor analyses, preliminary testing was performed, including internal consistency, 4-week test retest reliability, and construct and convergent validity. Results: Factor analyses with direct oblimin rotation were performed. Eight items were removed and five subscales(selfefficacy for gathering information about treatment, symptoms and health care; obtaining support; responding to behaviour disturbances; managing household, personal and medical care; and managing distress associated with caregiving) were identified. The Cronbach’s alpha coefficients for the whole scale and for each subscale were all over 0.80. The 4-week testretest reliabilities for the whole scale and for each subscale ranged from 0.64 to 0.85. The convergent validity was acceptable. Conclusions: Evidence for the preliminary testing of the SEQCFC was encouraging. A future follow-up study using confirmatory factor analysis with a new sample from different recruitment centres in Shanghai will be conducted. Future psychometric property testings of the questionnaire will be required for CGs from other regions of mainland China.

The effects of linguistic factors on student performance on economics multiple choice questions

This paper proposes a framework to analyse performance on multiple choice questions with the focus on linguistic factors. Item Response Theory (IRT) is deployed to estimate ability and question difficulty levels. A logistic regression model is used to detect Differential Item Functioning questions. Probit models testify relationships between performance and linguistic factors controlling the effects of question construction and students’ background. Empirical results have important implications. The lexical density of stems affects performance. The use of non-Economics specialised vocabulary has differing impacts on the performance of students with different language backgrounds. The IRT-based ability and difficulty help explain performance variations.