Engaging elementary students in learning science: An analysis of classroom dialogue

Research over a long period of time has continued to demonstrate problems in the teaching of science in school. In addition, declining levels of participation and interest in science and related fields have been reported from many particularly western countries. Among the strategies suggested is the recruitment of professional scientists and technologists either at the graduate level or advanced career level to change career and teach. In this study, we analysed how one beginning middle primary teacher engaged with students to support their science learning by establishing rich classroom discussions. We followed his evolving teaching expertise over three years focussing on his communicative practices informed by socio-cultural theory. His practices exemplified a non-interactive dialogical communicative approach where ideas were readily discussed but were concentrated on the class acquiring acceptable scientific understandings. His focus on the language of science was a significant aspect of his practice and one that emerged from his professional background. The study affirms the theoretical frameworks proposed by Mortimer and Scott (2003) highlighting how dialogue contributes to heightened student interest in science.

Director independence or decision bias? An investigation of alternative sources of agency costs in board decision making

Research into boards traditionally focuses on independent monitoring of management, with studies focused on the effect of board independence on firm performance. This thesis aims to broaden the research tradition by consolidating prior research and investigating how agents may circumvent independent monitoring. Meta-analysis of previous board independence-firm performance studies indicated no systematic relationship between board independence and firm performance. Next, a series of experiments demonstrated that the presentation of recommendations to directors may bias decision making irrespective of other information presented and the independence of the decision maker. Together, results suggest that independence may be less important than the agent's motivation to misdirect the monitoring process.

Use of physicochemical signatures to assess the sources of metals in urban road dust

Road deposited dust is a complex mixture of pollutants derived from a wide range of sources. Accurate identification of these sources is seminal for effective source-oriented control measures. A range of techniques such as enrichment factor analysis (EF), principal component analysis (PCA) and hierarchical cluster analysis (HCA) are available for identifying sources of complex mixtures. However, they have multiple deficiencies when applied individually. This study presents an approach for the effective utilisation of EF, PCA and HCA for source identification, so that their specific deficiencies on an individual basis are eliminated. EF analysis confirmed the non-soil origin of metals such as Na, Cu, Cd, Zn, Sn, K, Ca, Sb, Ba, Ti, Ni and Mo providing guidance in the identification of anthropogenic sources. PCA and HCA identified four sources, with soil and asphalt wear in combination being the most prominent sources. Other sources were tyre wear, brake wear and sea salt.

Numerical modelling of particle deposition in idealized porous channels

This project provides a steppingstone to comprehend the mechanisms that govern particulate fouling in metal foam heat exchangers. The method is based on development of an advanced Computational Fluid Dynamics model in addition to performing analytical validation. This novel method allows an engineer to better optimize heat exchanger designs, thereby mitigating fouling, reducing energy consumption caused by fouling, economize capital expenditure on heat exchanger maintenance, and reduce operation downtime. The robust model leads to the establishment of an alternative heat exchanger configuration that has lower pressure drop and particulate deposition propensity.

Effects of particle size distribution in the response of model granular materials in multi-ring shear

Rail track undergoes complex loading patterns under moving traffic conditions compared to roads due to its continued and discontinued multi-layered structure, including rail, sleepers, ballast layer, sub-ballast layer, and subgrade. Particle size distributions (PSDs) of ballast, subballast, and subgrade layers can be critical in cyclic plastic deformation of rail track under moving traffic on frequent track degradation of rail tracks, especially at bridge transition zones. Conventional test approaches: static shear and cyclic single-point load tests are however unable to replicate actual loading patterns of moving train. Multi-ring shear apparatus; a new type of torsional simple shear apparatus, which can reproduce moving traffic conditions, was used in this study to investigate influence of particle size distribution of rail track layers on cyclic plastic deformation. Three particle size distributions, using glass beads were examined under different loading patterns: cyclic sin-gle-point load, and cyclic moving wheel load to evaluate cyclic plastic deformation of rail track under different loading methods. The results of these tests suggest that particle size distributions of rail track structural layers have significant impacts on cyclic plastic deformation under moving train load. Further, the limitations in con-ventional test methods used in laboratories to estimate the plastic deformation of rail track materials lead to underestimate the plastic deformation of rail tracks.

Catalyst-free plasma enhanced growth of graphene from sustainable sources

Details of a fast and sustainable bottom-up process to grow large area high quality graphene films without the aid of any catalyst are reported in this paper. We used Melaleuca alternifolia, a volatile natural extract from tea tree plant as the precursor. The as-fabricated graphene films yielded a stable contact angle of 135°, indicating their potential application in very high hydrophobic coatings. The electronic devices formed by sandwiching pentacene between graphene and aluminum films demonstrated memristive behavior, and hence, these graphene films could find use in nonvolatile memory devices also.

Variability in exposure to ambient ultrafine particles in urban schools: Comparative assessment between Australia and Spain

Ambient ultrafine particle number concentrations (PNC) have inhomogeneous spatio-temporal distributions and depend on a number of different urban factors, including background conditions and distant sources. This paper quantitatively compares exposure to ambient ultrafine particles at urban schools in two cities in developed countries, with high insolation climatic conditions, namely Brisbane (Australia) and Barcelona (Spain). The analysis used comprehensive indoor and outdoor air quality measurements at 25 schools in Brisbane and 39 schools in Barcelona. PNC modes were analysed with respect to ambient temperature, land use and urban characteristics, combined with the measured elemental carbon concentrations, NOx (Brisbane) and NO2 (Barcelona). The trends and modes of the quantified weekday average daily cycles of ambient PNC exhibited significant differences between the two cities. PNC increases were observed during traffic rush hours in both cases. However, the mid-day peak was dominant in Brisbane schools and had the highest contribution to total PNC for both indoors and outdoors. In Barcelona, the contribution from traffic was highest for ambient PNC, while the mid-day peak had a slightly higher contribution for indoor concentrations. Analysis of the relationships between PNC and land use characteristics in Barcelona schools showed a moderate correlation with the percentage of road network area and an anti-correlation with the percentage of green area. No statistically significant correlations were found for Brisbane. Overall, despite many similarities between the two cities, school-based exposure patterns were different. The main source of ambient PNC at schools was shown to be traffic in Barcelona and mid-day new particle formation in Brisbane. The mid-day PNC peak in Brisbane could have been driven by the combined effect of background and meteorological conditions, as well as other local/distant sources. The results have implications for urban development, especially in terms of air quality mitigation and management at schools.

Bayesian mixture model estimation of aerosol particle size distributions

In this paper, we examine approaches to estimate a Bayesian mixture model at both single and multiple time points for a sample of actual and simulated aerosol particle size distribution (PSD) data. For estimation of a mixture model at a single time point, we use Reversible Jump Markov Chain Monte Carlo (RJMCMC) to estimate mixture model parameters including the number of components which is assumed to be unknown. We compare the results of this approach to a commonly used estimation method in the aerosol physics literature. As PSD data is often measured over time, often at small time intervals, we also examine the use of an informative prior for estimation of the mixture parameters which takes into account the correlated nature of the parameters. The Bayesian mixture model offers a promising approach, providing advantages both in estimation and inference.

Personal health records as sources of productivity evidence

Capturing data from various data repositories and integrating them for productivity improvements is common in modern business organisations. With the well-accepted concept of achieving positive gains through investment in employee health and wellness, organisations have started to capture both employee health and non-health data as Employer Sponsored electronic Personal Health Records (ESPHRs). However, non-health related data in ESPHRs has hardly been taken into consideration with outcomes such as employee productivity potentially being suited for further validation and stimulation of ESPHR usage. Here we analyse selected employee demographic information (age, gender, marital status, and job grade) and health-related outcomes (absenteeism and presenteeism) of employees for evidence-based decision making. Our study considered demographic and health-related outcomes of 700 employees. Surprisingly, the analysis shows that employees with high sick leave rates are also high performers. A factor analysis shows 92% of the variance in the data can be explained by three factors, with the job grade capable of explaining 62% of the variance. Work responsibilities may drive employees to maintain high work performance despite signs of sickness, so ESPHRs should focus attention on high performers. This finding suggests new ways of extracting value from ESPHRs to support organisational health and wellness management to help assure sustainability in organisational productivity.

A data fusion approach of multiple maintenance data sources for real-world reliability modelling

A central tenet in the theory of reliability modelling is the quantification of the probability of asset failure. In general, reliability depends on asset age and the maintenance policy applied. Usually, failure and maintenance times are the primary inputs to reliability models. However, for many organisations, different aspects of these data are often recorded in different databases (e.g. work order notifications, event logs, condition monitoring data, and process control data). These recorded data cannot be interpreted individually, since they typically do not have all the information necessary to ascertain failure and preventive maintenance times. This paper presents a methodology for the extraction of failure and preventive maintenance times using commonly-available, real-world data sources. A text-mining approach is employed to extract keywords indicative of the source of the maintenance event. Using these keywords, a Naïve Bayes classifier is then applied to attribute each machine stoppage to one of two classes: failure or preventive. The accuracy of the algorithm is assessed and the classified failure time data are then presented. The applicability of the methodology is demonstrated on a maintenance data set from an Australian electricity company.

Carbon dioxide emissions in the short run: The rate and sources of economic growth matter

This paper investigates the short-run effects of economic growth on carbon dioxide emissions from the combustion of fossil fuels and the manufacture of cement for 189 countries over the period 1961-2010. Contrary to what has previously been reported, we conclude that there is no strong evidence that the emissions-income elasticity is larger during individual years of economic expansion as compared to recession. Significant evidence of asymmetry emerges when effects over longer periods are considered. We find that economic growth tends to increase emissions not only in the same year, but also in subsequent years. Delayed effects - especially noticeable in the road transport sector - mean that emissions tend to grow more quickly after booms and more slowly after recessions. Emissions are more sensitive to fluctuations in industrial value added than agricultural value added, with services being an intermediate case. On the expenditure side, growth in consumption and growth in investment have similar implications for national emissions. External shocks have a relatively large emissions impact, and the short-run emissions-income elasticity does not appear to decline as incomes increase. Economic growth and emissions have been more tightly linked in fossil-fuel rich countries.

Changes in atmospheric concentrations of polycyclic aromatic hydrocarbons and polychlorinated biphenyls between the 1990s and 2010s in an Australian city and the role of bushfires as a source

Over recent decades, efforts have been made to reduce human exposure to atmospheric pollutants including polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) through emission control and abatement. Along with the potential changes in their concentrations resulting from these efforts, profiles of emission sources may have also changed over such extended timeframes. However relevant data are quite limited in the Southern Hemisphere. We revisited two sampling sites in an Australian city, where the concentration data in 1994/5 for atmospheric PAHs and PCBs were available. Monthly air samples from July 2013 to June 2014 at the two sites were collected and analysed for these compounds, using similar protocols to the original study. A prominent seasonal pattern was observed for PAHs with elevated concentrations in cooler months whereas PCB levels showed little seasonal variation. Compared to two decades ago, atmospheric concentrations of ∑13 PAHs (gaseous + particle-associated) in this city have decreased by approximately one order of magnitude and the apparent halving time ( t 1 / 2 ) was estimated as 6.2 ± 0.56 years. ∑6 iPCBs concentrations (median value; gaseous + particle-associated) have decreased by 80% with an estimated t 1 / 2 of 11 ± 2.9 years. These trends and values are similar to those reported for comparable sites in the Northern Hemisphere. To characterise emission source profiles, samples were also collected from a bushfire event and within a vehicular tunnel. Emissions from bushfires are suggested to be an important contributor to the current atmospheric concentrations of PAHs in this city. This contribution is more important in cooler months, i.e. June, July and August, and its importance may have increased over the last two decades.

What are the driving factors influencing the size distribution of airborne synthetic clay particles emitted from a jet milling process?

In the field of workplace air quality, measuring and analyzing the size distribution of airborne particles to identify their sources and apportion their contribution has become widely accepted, however, the driving factors that influence this parameter, particularly for nanoparticles (< 100 nm), have not been thoroughly determined. Identification of driving factors, and in turn, general trends in size distribution of emitted particles would facilitate the prediction of nanoparticles’ emission behavior and significantly contribute to their exposure assessment. In this study, a comprehensive analysis of the particle number size distribution data, with a particular focus on the ultrafine size range of synthetic clay particles emitted from a jet milling machine was conducted using the multi-lognormal fitting method. The results showed relatively high contribution of nanoparticles to the emissions in many of the tested cases, and also, that both surface treatment and feed rate of the machine are significant factors influencing the size distribution of the emitted particles of this size. In particular, applying surface treatments and increasing the machine feed rate have the similar effect of reducing the size of the particles, however, no general trend was found in variations of size distribution across different surface treatments and feed rates. The findings of our study demonstrate that for this process and other activities, where no general trend is found in the size distribution of the emitted airborne particles due to dissimilar effects of the driving factors, each case must be treated separately in terms of workplace exposure assessment and regulations.

Occupational release of engineered nanoparticles: A review

Characterising the release of different types of Engineered Nanoparticles (ENPs) from various processes is of critical importance for the assessment of human exposure, as well as understanding the possible health effects of these particles. Therefore, the main aim of this chapter is to present a comprehensive review of studies which report on the release of airborne ENPs in different nanotechnology workplaces. The chapter will cover topics of relevance to the occupational characterisation of ENP emissions, ranging from the identification of different particle release sources and scenarios, to measurement methods and working towards a more uniform approach to characterisation. Furthermore, a brief review of ENP exposure control strategies, together with the application of mathematical modelling as an effective tool for the characterisation of emissions at nanotechnology workplaces is included.