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Simple Summary: Australia exports large numbers of live cattle and sheep by sea to many destinations. Increasingly high animal welfare standards are being required of all livestock industries, and reports of substantial mortality events on some voyages have raised public concerns regarding animal welfare. Mortality rates alone do not assure stakeholders that livestock experience adequate welfare throughout the voyage. Determining the animal welfare status of large animal consignments is complex and requires many measures that are focused on the environment and resources provided, and also on how the animals respond to their surroundings. A list of measures, appropriate for use on cattle and sheep that enter the livestock export supply chain, was determined by reviewing three international welfare assessment protocols, and consulting the Australian livestock export standards and an animal health handbook used by shipboard veterinarians and stockpersons. After preliminary testing of the measures on a sheep and cattle voyage, we propose a protocol that is potentially practical and applicable for pen assessments for both species at pre-export and destination feedlot facilities and during sea transport. Proposing a protocol is the first step towards developing a system that evaluates livestock welfare throughout the export supply chain, and will contribute to improved industry transparency. Australian livestock industries face increased scrutiny from animal welfare groups and society, and the long-distance transport of livestock by sea has recently gained particular attention. Other than non-compliance with broad regulatory standards and voyage mortality rates, there is minimal information to ascertain the welfare of exported livestock. There is currently no standardised, validated animal welfare assessment protocol for livestock on-farm prior to live export or when undergoing transport. This study describes a novel assessment protocol suitable for use on live feeder and slaughter animals exported by sea from Australia. Health and welfare indicators for use in the livestock export supply chain were identified by reviewing three internationally recognised animal welfare assessment protocols for livestock; Welfare Quality®, AWIN and AssureWel, as well as consulting with industry compliance standards and guidelines. This paper proposes a welfare protocol designed to assess sheep and beef cattle exported by sea from Australia, and incorporates environmental-, resource-, management- and animal-based measures. In collaboration with industry, this welfare protocol can be tested on commercial livestock consignments, and be used for ongoing management, for increased transparency and to provide feedback to operators for continuous improvement. [ABSTRACT FROM AUTHOR]

This paper presents the results from a study on the application of an artificial neural network (ANN) model for regional flood frequency analysis (RFFA). The study was conducted using stream flow data from 88 gauging stations across New South Wales (NSW) in Australia. Five different models consisting of three to eight predictor variables (i.e., annual rainfall, drainage area, fraction forested area, potential evapotranspiration, rainfall intensity, river slope, shape factor and stream density) were tested. The results show that an ANN model with a higher number of predictor variables does not always improve the performance of RFFA models. For example, the model with three predictor variables performs considerably better than the models using a higher number of predictor variables, except for the one which contains all the eight predictor variables. The model with three predictor variables exhibits smaller median relative error values for 2- and 20-year return periods compared to the model containing eight predictor variables. However, for 5-, 10-, 50- and 100-year return periods, the model with eight predictor variables shows smaller median relative error values. The proposed ANN modelling framework can be adapted to other regions in Australia and abroad. [ABSTRACT FROM AUTHOR]

It is critically meaningful to accurately predict the ionospheric F2 layer critical frequency (foF2), which greatly limits the efficiency of communications, radar, and navigation systems. This paper introduced the entropy weight method to develop the combination prediction model (CPM) for long-term foF2 at Darwin (12.4° S, 131.5° E) in Australia. The weight coefficient of each individual model in the CPM is determined by using the entropy weight method after completing the simulation of the individual model in the calibration period. We analyzed two sets of data to validate the method used in this study: One set is from 2000 and 2009, which are included in the calibration period (1998–2016), and the other set is outside the calibration cycle (from 1997 and 2017). To examine the performance, the root mean square error (RMSE) of the observed monthly median foF2 value, the proposed CPM, the Union Radio Scientifique Internationale (URSI), and the International Radio Consultative Committee (CCIR) are compared. The yearly RMSE average values calculated from CPM were less than those calculated from URSI and CCIR in 1997, 2000, 2009, and 2017. In 2000 and 2009, the average percentage improvement between CPM and URSI is 9.01%, and the average percentage improvement between CPM and CCIR is 13.04%. Beyond the calibration period, the average percentage improvement between CPM and URSI is 13.2%, and the average percentage improvement between CPM and CCIR is 12.6%. The prediction results demonstrated that the proposed CPM has higher precision of prediction and stability than that of the URSI and CCIR, both within the calibration period and outside the calibration period. [ABSTRACT FROM AUTHOR]

Over recent decades, more and more cities worldwide have created semantic 3D city models of their built environments based on standards across multiple domains. 3D city models, which are often employed for a large range of tasks, go far beyond pure visualization. Due to different spatial scale requirements for planning and managing various built environments, integration of Geographic Information Systems (GIS) and Building Information Modeling (BIM) has emerged in recent years. Focus is now shifting to Precinct Information Modeling (PIM) which is in a more general sense to built-environment modeling. As scales change so do options to perform information modeling for different applications. How to implement data interoperability across these digital representations, therefore, becomes an emerging challenge. Moreover, with the growth of multi-source heterogeneous data consisting of semantic and varying 2D/3D spatial representations, data management becomes feasible for facilitating the development and deployment of PIM applications. How to use heterogeneous data in an integrating manner to further express PIM is an open and comprehensive topic. In this paper, we develop a semantic PIM based on multi-source heterogeneous data. Then, we tackle spatial data management problems in a Spatial Database Management System (SDBMS) solution for our defined unified model. Case studies on the University of New South Wales (UNSW) campus demonstrate the efficiency of our solution. [ABSTRACT FROM AUTHOR]

This paper uses hydrochemical and multi-isotope analysis to investigate geological controls on coal seam gas (CSG) saturation domains and gas well production performance in a high-rank (vitrinite reflectance (Rv) > 1.1) CSG field in the north-western Bowen Basin, Australia. New hydrochemical and stable isotope data were combined with existing geochemical datasets to refine hypotheses on the distribution and origins of CSG in two highly compartmentalized Permian coal seams. Stable isotopic results suggest that geographic variations in gas content, saturation and production reflect the extent of secondary microbial gas generation and retention as a function of hydrodynamics. δ13C and δ2H data support a gas mixing hypothesis with δ13C-CH4 increasing from secondary biogenic values to thermogenic values at depth (δ13C −62.2‰ to −46.3‰), whereas correlated methane and carbon dioxide carbon isotope compositions, Δ13C(CO2–CH4) values and δ13CDIC/alkalinity trends are largely consistent with microbial CO2 reduction. In addition, below 200 m, the majority of δ13C-CO2 values are positive (δ13C: −1.2‰ to 7.1‰) and δ13CDIC shows an erratic increase with depth for both seams that is characteristic of evolution via microbial activity. The progression of carbon isotope values along the CO2 reduction fractionation line suggests progressive depletion of the CO2 reservoir with increasing depth. Faults clearly segment coal seams into areas having significantly different production, with results of geochemical analysis suggesting that pooling of biogenic gas and waters and enhanced methanogenesis occur north of a faulted hinge zone. [ABSTRACT FROM AUTHOR]

This paper presents the quantification of uncertainties in the prediction of settlements of embankments built on prefabricated vertical drains (PVDs) improved soft soil deposits based on data collected from two well-documented projects, located in Karakore, Ethiopia, and Ballina, Australia. For this purpose, settlement prediction biases and settlement distributions were statistically computed based on analyses conducted on two Class A and Class C numerical predictions made using PLAXIS 2D finite element modelling. From the results of prediction bias, Class C predictions agreed well with the field measured settlements at both sites. In Class C predictions, the computed settlements were biased to the measured values. For Class A predictions, the calculated settlement values were in the range of mean and mean minus 3SD (standard deviations) for Karakore clay, and they were within mean and mean minus 2SD limit for the Ballina soil. The contributing factors to the settlement uncertainties of the Karakore site may include variability within the soil profile of the alluvial deposit, particularly the presence of interbedded granular layer within the soft layers, and the high embankment fills, and the limited number of samples available for laboratory testing. At the Ballina test embankment site, the uncertainties may have been associated with the presence of transitional layers at the bottom of estuarine clay and sensitivity of soft soil to sample disturbances and limitations in representing all the site conditions. [ABSTRACT FROM AUTHOR]

The north of Australia is known for its complex tidal system, where the highest astronomical tides (HATs) reach 12 m. This paper investigates the tidal behaviour in this region by developing spectral climatology for tide gauge and altimetry data. Power spectral density analysis is applied to detect the magnitude of ocean tides in 20 years of sea-level data from multimission satellite altimeters and tide gauges. The spectra of altimetry sea level anomaly (SLA) time series have their strongest peaks centred at approximately 2.11, 5.88, and 7.99 cycles per year (cpy), corresponding to the diurnal and semidiurnal tidal constituents K1, M2, and O1, respectively. Closer to the coastline, the spectra peak at high-frequency overtide and shallow-water constituents such as M4, MK4, and MK3. There have been many large, high-frequency spectral peaks near the coastline, indicating the difficulty of predicting tidal signals by coastal altimetry. Similar to altimetry observations, there are dominant semidiurnal and diurnal tidal peaks in tide gauge SLA time series accompanying a number of overtides. The semidiurnal and diurnal peaks are mostly higher on the northwest coast of Australia compared with the north and northeast coast. The results from both altimetry and tide gauges indicate that tidal range increases with increasing continental shelf. [ABSTRACT FROM AUTHOR]

This paper presents a summary of the key findings of the special issue of Atmosphere on Air Quality in New South Wales and discusses the implications of the work for policy makers and individuals. This special edition presents new air quality research in Australia undertaken by (or in association with) the Clean Air and Urban Landscapes hub, which is funded by the National Environmental Science Program on behalf of the Australian Government's Department of the Environment and Energy. Air pollution in Australian cities is generally low, with typical concentrations of key pollutants at much lower levels than experienced in comparable cities in many other parts of the world. Australian cities do experience occasional exceedances in ozone and PM2.5 (above air pollution guidelines), as well as extreme pollution events, often as a result of bushfires, dust storms, or heatwaves. Even in the absence of extreme events, natural emissions play a significant role in influencing the Australian urban environment, due to the remoteness from large regional anthropogenic emission sources. By studying air quality in Australia, we can gain a greater understanding of the underlying atmospheric chemistry and health risks in less polluted atmospheric environments, and the health benefits of continued reduction in air pollution. These conditions may be representative of future air quality scenarios for parts of the Northern Hemisphere, as legislation and cleaner technologies reduce anthropogenic air pollution in European, American, and Asian cities. However, in many instances, current legislation regarding emissions in Australia is significantly more lax than in other developed countries, making Australia vulnerable to worsening air pollution in association with future population growth. The need to avoid complacency is highlighted by recent epidemiological research, reporting associations between air pollution and adverse health outcomes even at air pollutant concentrations that are lower than Australia's national air quality standards. Improving air quality is expected to improve health outcomes at any pollution level, with specific benefits projected for reductions in long-term exposure to average PM2.5 concentrations. [ABSTRACT FROM AUTHOR]

Today's knowledge economy very much depends on the value created by the human resource of an organisation. In such a highly competitive environment, organisations have started to pay much attention to the recruitment and selection process, as employees form their main asset. However, the critical factors involved in the employee selection process is not well studied. Previous studies on the recruitment and selection process have been performed mainly to study the performance of the employees and the criteria attracting the right talent leading to employee retention and organizational efficiency. The distinction of this paper is that it studies the existing recruitment and selection process adopted by tertiary and dual education sectors in both urban and regional areas within Australia. The purpose of this research is to conduct an empirical study to identify the critical aspects of the employee selection process that can influence the decision based on different perspectives of the participants such as, hiring members, successful applicants as well as unsuccessful applicants. Various factors such as feedback provision, interview panel participation and preparations, relevance of interview questions, duration and bias were analysed, and their correlations were studied to gain insights in providing suitable recommendations for enhancing the process. [ABSTRACT FROM AUTHOR]

To address sustainability issues by facilitating the use of high-volume fly ash (HVFA) concrete in industry, this paper investigates the early age hydration properties of HVFA binders in concrete and the correlation between hydration properties and compressive strengths of the cement pastes. A new method of calculating the chemically bound water of HVFA binders was used and validated. Fly ash (FA) types used in this study were sourced from Indonesia and Australia for comparison. The water to binder (w/b) ratio was 0.4 and FA replacement levels were 40%, 50% and 60% by weight. Isothermal calorimetry tests were conducted to study the heat of hydration which was further converted to the adiabatic temperature rise. Thermo-gravimetric analysis (TGA) was employed to explore the chemically bound water (WB) of the binders. The results showed that Australian FA pastes had higher heat of hydration, adiabatic temperature rise, WB and compressive strength compared to Indonesian FA pastes. The new method of calculating chemically bound water can be successfully applied to HVFA binders. Linear correlation could be found between the WB and compressive strength. [ABSTRACT FROM AUTHOR]

In low-to-moderate seismicity (intraplate) regions where locally recorded strong motion data are too scare for conventional regression analysis, stochastic simulations based on seismological modelling have often been used to predict ground motions of future earthquakes. This modelling methodology has been practised in Central and Eastern North America (CENA) for decades. It is cautioned that ground motion prediction equations (GMPE) that have been developed for use in CENA might not always be suited for use in another intraplate region because of differences in the crustal structure. This paper introduces a regionally adjustable GMPE, known as the component attenuation model (CAM), by which a diversity of crustal conditions can be covered in one model. Input parameters into CAM have been configured in the same manner as a seismological model, as both types of models are based on decoupling the spectral properties of earthquake ground motions into a generic source factor and a regionally specific path factor (including anelastic and geometric attenuation factors) along with a crustal factor. Unlike seismological modelling, CAM is essentially a GMPE that can be adapted readily for use in different regions (or different areas within a region) without the need of undertaking any stochastic simulations, providing that parameters characterising the crustal structure have been identified. In addressing the challenge of validating a GMPE for use in an area where instrumental data are scarce, modified Mercalli intensity (MMI) data inferred from peak ground velocity values predicted by CAM are compared with records of MMI of past earthquake events, as reported in historical archives. South-Eastern Australia (SEA) and South-Eastern China (SEC) are the two study regions used in this article for demonstrating the viability of CAM as a ground motion prediction tool in an intraplate environment. [ABSTRACT FROM AUTHOR]

Spatio-temporal data fusion refers to the technique of combining high temporal resolution from coarse satellite images and high spatial resolution from fine satellite images. However, data availability remains a major limitation in algorithm development. Existing spatio-temporal data fusion algorithms require at least one known image pair between the fine and coarse resolution image. However, data which come from two different satellite platforms do not necessarily have an overlap in their overpass times, hence restricting the application of spatio-temporal data fusion. In this paper, a new algorithm named Hopfield Neural Network SPatio-tempOral daTa fusion model (HNN-SPOT) is developed by utilizing the optimization concept in the Hopfield neural network (HNN) for spatio-temporal image fusion. The algorithm derives a synthesized fine resolution image from a coarse spatial resolution satellite image (similar to downscaling), with the use of one fine resolution image taken on an arbitrary date and one coarse image taken on a predicted date. The HNN-SPOT particularly addresses the problem when the fine resolution and coarse resolution images are acquired from different satellite overpass times over the same geographic extent. Both simulated datasets and real datasets over Hong Kong and Australia have been used in the evaluation of HNN-SPOT. Results showed that HNN-SPOT was comparable with an existing fusion algorithm, the spatial and temporal adaptive reflectance fusion model (STARFM). HNN-SPOT assumes consistent spatial structure for the target area between the date of data acquisition and the prediction date. Therefore, it is more applicable to geographical areas with little or no land cover change. It is shown that HNN-SPOT can produce accurate fusion results with >90% of correlation coefficient over consistent land covers. For areas that have undergone land cover changes, HNN-SPOT can still produce a prediction about the outlines and the tone of the features, if they are large enough to be recorded in the coarse resolution image at the prediction date. HNN-SPOT provides a relatively new approach in spatio-temporal data fusion, and further improvements can be made by modifying or adding new goals and constraints in its HNN architecture. Owing to its lower demand for data prerequisites, HNN-SPOT is expected to increase the applicability of fine-scale applications in remote sensing, such as environmental modeling and monitoring. [ABSTRACT FROM AUTHOR]

The objective of this paper is to use remote sensing to measure on-road emissions and to examine the impact and usefulness of additional measurement devices at three sites. Supplementing remote sensing device (RSD) equipment with additional equipment increased the capture rate by almost 10%. Post-processing of raw data is essential to obtain useful and accurate information. A method is presented to identify vehicles with excessive emission levels (high emitters). First, an anomaly detection method is applied, followed by identification of cold start operating conditions using infrared vehicle profiles. Using this method, 0.6% of the vehicles in the full (enhanced) RSD data were identified as high emitters, of which 35% are likely in cold start mode where emissions typically stabilize to low hot running emission levels within a few minutes. Analysis of NOx RSD data confirms that poor real-world NOx performance of Euro 4/5 light-duty diesel vehicles observed around the world is also evident in Australian measurements. This research suggests that the continued dieselisation in Australia, in particular under the current Euro 5 emission standards and the more stringent NO2 air quality criteria expected in 2020 and 2025, could potentially result in local air quality issues near busy roads. [ABSTRACT FROM AUTHOR]

Notions of childhood in colonial Australia were informed by a variety of social contexts that varied across time and space and were given material expression in the memorialization of children's burials. Using data drawn from two studies of nineteenth-century cemeteries in rural South Australia, in this paper, we suggest an alternative way to understand children archaeologically that avoids the trap of essentialism: the notion of 'childness'. Childness is defined as the multiple conceptions of being, and being labeled, a child. The concept of being a child may be instantiated in different ways according to particular social, cultural, chronological, and religious contexts; childness is the measure of this variation. In Western historical settings, the most likely causes for such variation are the social processes of class and status via the closely associated ideologies of gentility and respectability and their attendant expectations around labor, as well as the shifts they represent in the social ideology of the family. Exploring childness, rather than children, provides an alternative way to approach the histories of contemporary Western understandings of childhood, including when particular types of childhood began and ended, and according to what criteria in different contexts, as well as how boundaries between child and adult were continually being established and re-negotiated. [ABSTRACT FROM AUTHOR]

There is a large body of research showing that psychological treatment can be effectively delivered via the internet, and Digital Mental Health Services (DMHS) are now delivering those interventions in routine care. However, not all attempts to translate these research outcomes into routine care have been successful. This paper draws on the experience of successful DMHS in Australia and Canada to describe ten lessons learned while establishing and delivering internet-delivered cognitive behavioural therapy (ICBT) and other mental health services as part of routine care. These lessons include learnings at four levels of analysis, including lessons learned working with (1) consumers, (2) therapists, (3) when operating DMHS, and (4) working within healthcare systems. Key themes include recognising that DMHS should provide not only treatment but also information and assessment services, that DMHS require robust systems for training and supervising therapists, that specialist skills are required to operate DMHS, and that the outcome data from DMHS can inform future mental health policy. We also confirm that operating such clinics is particularly challenging in the evolving funding, policy, and regulatory context, as well as increasing expectations from consumers about DMHS. Notwithstanding the difficulties of delivering DMHS, we conclude that the benefits of such services for the broader community significantly outweigh the challenges. [ABSTRACT FROM AUTHOR]

Cocoa is an important commodity crop, not only to produce chocolate, one of the most complex products from the sensory perspective, but one that commonly grows in developing countries close to the tropics. This paper presents novel techniques applied using cover photography and a novel computer application (VitiCanopy) to assess the canopy architecture of cocoa trees in a commercial plantation in Queensland, Australia. From the cocoa trees monitored, pod samples were collected, fermented, dried, and ground to obtain the aroma profile per tree using gas chromatography. The canopy architecture data were used as inputs in an artificial neural network (ANN) algorithm, with the aroma profile, considering six main aromas, as targets. The ANN model rendered high accuracy (correlation coefficient (R) = 0.82; mean squared error (MSE) = 0.09) with no overfitting. The model was then applied to an aerial image of the whole cocoa field studied to produce canopy vigor, and aroma profile maps up to the tree-by-tree scale. The tool developed could significantly aid the canopy management practices in cocoa trees, which have a direct effect on cocoa quality. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) are important precursors to the formation of ozone and fine particulate matter, the two pollutants of most concern in Sydney, Australia. Despite this importance, there are very few published measurements of ambient VOC concentrations in Australia. In this paper, we present mole fractions of several important VOCs measured during the campaign known as MUMBA (Measurements of Urban, Marine and Biogenic Air) in the Australian city of Wollongong (34°S). We particularly focus on measurements made during periods when clean marine air impacted the measurement site and on VOCs of biogenic origin. Typical unpolluted marine air mole fractions during austral summer 2012-2013 at latitude 34°S were established for CO2 (391.0 ± 0.6 ppm), CH4 (1760.1 ± 0.4 ppb), N2O (325.04 ± 0.08 ppb), CO (52.4 ± 1.7 ppb), O3 (20.5 ± 1.1 ppb), acetaldehyde (190 ± 40 ppt), acetone (260 ± 30 ppt), dimethyl sulphide (50 ± 10 ppt), benzene (20 ± 10 ppt), toluene (30 ± 20 ppt), C8H10 aromatics (23 ± 6 ppt) and C9H12 aromatics (36 ± 7 ppt). The MUMBA site was frequently influenced by VOCs of biogenic origin from a nearby strip of forested parkland to the east due to the dominant north-easterly afternoon sea breeze. VOCs from the more distant densely forested escarpment to the west also impacted the site, especially during two days of extreme heat and strong westerly winds. The relative amounts of different biogenic VOCs observed for these two biomes differed, with much larger increases of isoprene than of monoterpenes or methanol during the hot westerly winds from the escarpment than with cooler winds from the east. However, whether this was due to different vegetation types or was solely the result of the extreme temperatures is not entirely clear. We conclude that the clean marine air and biogenic signatures measured during the MUMBA campaign provide useful information about the typical abundance of several key VOCs and can be used to constrain chemical transport model simulations of the atmosphere in this poorly sampled region of the world. [ABSTRACT FROM AUTHOR]

Electricity load forecasting plays an essential role in improving the management efficiency of power generation systems. A large number of load forecasting models aiming at promoting the forecasting effectiveness have been put forward in the past. However, many traditional models have no consideration for the significance of data preprocessing and the constraints of individual forecasting models. Moreover, most of them only focus on the forecasting accuracy but ignore the forecasting stability, resulting in nonoptimal performance in practical applications. This paper presents a novel hybrid model that combines an advanced data preprocessing strategy, a deep neural network, and an avant-garde multi-objective optimization algorithm, overcoming the defects of traditional models and thus improving the forecasting performance effectively. In order to evaluate the validity of the proposed hybrid model, the electricity load data sampled in 30-min intervals from Queensland, Australia are used as a case to study. The experiments show that the new proposed model is obviously superior to all other traditional models. Furthermore, it provides an effective technical forecasting means for smart grid management. [ABSTRACT FROM AUTHOR]

Solar energy predictive models designed to emulate the long-term (e.g., monthly) global solar radiation (GSR) trained with satellite-derived predictors can be employed as decision tenets in the exploration, installation and management of solar energy production systems in remote and inaccessible solar-powered sites. In spite of a plethora of models designed for GSR prediction, deep learning, representing a state-of-the-art intelligent tool, remains an attractive approach for renewable energy exploration, monitoring and forecasting. In this paper, algorithms based on deep belief networks and deep neural networks are designed to predict long-term GSR. Deep learning algorithms trained with publicly-accessible Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data are tested in Australia's solar cities to predict the monthly GSR: single hidden layer and ensemble models. The monthly-scale MODIS-derived predictors (2003–2018) are adopted, with 15 diverse feature selection approaches including a Gaussian Emulation Machine for sensitivity analysis used to select optimal MODIS-predictor variables to simulate GSR against ground-truth values. Several statistical score metrics are adopted to comprehensively verify surface GSR simulations to ascertain the practicality of deep belief and deep neural networks. In the testing phase, deep learning models generate significantly lower absolute percentage bias (≤3%) and high Kling–Gupta efficiency (≥97.5%) values compared to the single hidden layer and ensemble model. This study ascertains that the optimal MODIS input variables employed in GSR prediction for solar energy applications can be relatively different for diverse sites, advocating a need for feature selection prior to the modelling of GSR. The proposed deep learning approach can be adopted to identify solar energy potential proactively in locations where it is impossible to install an environmental monitoring data acquisition instrument. Hence, MODIS and other related satellite-derived predictors can be incorporated for solar energy prediction as a strategy for long-term renewable energy exploration. [ABSTRACT FROM AUTHOR]

The barriers to women's achievement and career progression in the higher education sector have been well researched. It has long been acknowledged that career breaks for child-rearing, and women's self-beliefs about their abilities can impact negatively on their careers, and many programs and policies have been implemented to redress these around the world. This article is focussed around a regional Australian university, with multiple campuses distributed over 1000 km across two states. Courses, schools, and work teams are often spread across multiple campuses, and travel between campuses is sometimes a necessity; one that is time-consuming and requires time away from family. For some women, travelling is not possible due to family and other commitments or constraints. This paper explores how working in a regional university, with distributed campuses, has an additional impact on women's career progression. Through auto-ethnographic accounts of four female staff members, we explore the intersection of gender and location through case studies of personal experiences, investigating the effects that distance and travel limitations can have on participation in work team and networking events, access to professional development opportunities, and career progression within the institution. [ABSTRACT FROM AUTHOR]

This paper reports on the successful management of hyperphagia (exaggerated hunger) in a 14yr-old female with Prader–Willi syndrome (PWS). This child was diagnosed with PWS, (maternal uniparental disomy) at 18 months due to developmental delay, hypertonia, weight gain and extreme eating behaviour. Treatment of a supplement for appetite suppression commenced at 2 years of age. This single-case records ingestion of an Indian cactus succulent Caralluma fimbriata extract (CFE) over 12 years, resulting in anecdotal satiety, free access to food and management of weight within normal range. CFE was administered in a drink daily and dose was slowly escalated by observation for appetite suppression. Rigorous testing determined blood count, vitamins, key minerals, HbA1c, IGF-1 and function of the liver and thyroid all within normal range. The report suggests a strategy for early intervention against hyperphagia and obesity in PWS. This case was the instigator of the successful Australian PWS/CFE pilot and though anecdotal, the adolescent continues to ingest CFE followed by paediatricians at the Royal Children's Hospital Melbourne, Victoria, Australia. Future clinical trials are worth considering, to determine an appropriate dose for individuals with PWS. [ABSTRACT FROM AUTHOR]

Air-sea interactions play an important role in atmospheric circulation and boundary layer conditions through changing convection processes and surface heat fluxes, particularly in coastal areas. These changes can affect the concentrations, distributions, and lifetimes of atmospheric pollutants. In this Part II paper, the performance of the Weather Research and Forecasting model with chemistry (WRF/Chem) and the coupled WRF/Chem with the Regional Ocean Model System (ROMS) (WRF/Chem-ROMS) are intercompared for their applications over quadruple-nested domains in Australia during the three following field campaigns: The Sydney Particle Study Stages 1 and 2 (SPS1 and SPS2) and the Measurements of Urban, Marine, and Biogenic Air (MUMBA). The results are used to evaluate the impact of air-sea interaction representation in WRF/Chem-ROMS on model predictions. At 3, 9, and 27 km resolutions, compared to WRF/Chem, the explicit air-sea interactions in WRF/Chem-ROMS lead to substantial improvements in simulated sea-surface temperature (SST), latent heat fluxes (LHF), and sensible heat fluxes (SHF) over the ocean, in terms of statistics and spatial distributions, during all three field campaigns. The use of finer grid resolutions (3 or 9 km) effectively reduces the biases in these variables during SPS1 and SPS2 by WRF/Chem-ROMS, whereas it further increases these biases for WRF/Chem during all field campaigns. The large differences in SST, LHF, and SHF between the two models lead to different radiative, cloud, meteorological, and chemical predictions. WRF/Chem-ROMS generally performs better in terms of statistics and temporal variations for temperature and relative humidity at 2 m, wind speed and direction at 10 m, and precipitation. The percentage differences in simulated surface concentrations between the two models are mostly in the range of ±10% for CO, OH, and O3, ±25% for HCHO, ±30% for NO2, ±35% for H2O2, ±50% for SO2, ±60% for isoprene and terpenes, ±15% for PM2.5, and ±12% for PM10. WRF/Chem-ROMS at 3 km resolution slightly improves the statistical performance of many surface and column concentrations. WRF/Chem simulations with satellite-constrained boundary conditions (BCONs) improve the spatial distributions and magnitudes of column CO for all field campaigns and slightly improve those of the column NO2 for SPS1 and SPS2, column HCHO for SPS1 and MUMBA, and column O3 for SPS2 at 3 km over the Greater Sydney area. The satellite-constrained chemical BCONs reduce the model biases of surface CO, NO, and O3 predictions at 3 km for all field campaigns, surface PM2.5 predictions at 3 km for SPS1 and MUMBA, and surface PM10 predictions at all grid resolutions for all field campaigns. A more important role of chemical BCONs in the Southern Hemisphere, compared to that in the Northern Hemisphere reported in this work, indicates a crucial need in developing more realistic chemical BCONs for O3 in the relatively clean SH. [ABSTRACT FROM AUTHOR]

Air pollution and associated human exposure are important research areas in Greater Sydney, Australia. Several field campaigns were conducted to characterize the pollution sources and their impacts on ambient air quality including the Sydney Particle Study Stages 1 and 2 (SPS1 and SPS2), and the Measurements of Urban, Marine, and Biogenic Air (MUMBA). In this work, the Weather Research and Forecasting model with chemistry (WRF/Chem) and the coupled WRF/Chem with the Regional Ocean Model System (ROMS) (WRF/Chem-ROMS) are applied during these field campaigns to assess the models' capability in reproducing atmospheric observations. The model simulations are performed over quadruple-nested domains at grid resolutions of 81-, 27-, 9-, and 3-km over Australia, an area in southeastern Australia, an area in New South Wales, and the Greater Sydney area, respectively. A comprehensive model evaluation is conducted using surface observations from these field campaigns, satellite retrievals, and other data. This paper evaluates the performance of WRF/Chem-ROMS and its sensitivity to spatial grid resolutions. The model generally performs well at 3-, 9-, and 27-km resolutions for sea-surface temperature and boundary layer meteorology in terms of performance statistics, seasonality, and daily variation. Moderate biases occur for temperature at 2-m and wind speed at 10-m in the mornings and evenings due to the inaccurate representation of the nocturnal boundary layer and surface heat fluxes. Larger underpredictions occur for total precipitation due to the limitations of the cloud microphysics scheme or cumulus parameterization. The model performs well at 3-, 9-, and 27-km resolutions for surface O3 in terms of statistics, spatial distributions, and diurnal and daily variations. The model underpredicts PM2.5 and PM10 during SPS1 and MUMBA but overpredicts PM2.5 and underpredicts PM10 during SPS2. These biases are attributed to inaccurate meteorology, precursor emissions, insufficient SO2 conversion to sulfate, inadequate dispersion at finer grid resolutions, and underprediction in secondary organic aerosol. The model gives moderate biases for net shortwave radiation and cloud condensation nuclei but large biases for other radiative and cloud variables. The performance of aerosol optical depth and latent/sensible heat flux varies for different simulation periods. Among all variables evaluated, wind speed at 10-m, precipitation, surface concentrations of CO, NO, NO2, SO2, O3, PM2.5, and PM10, aerosol optical depth, cloud optical thickness, cloud condensation nuclei, and column NO2 show moderate-to-strong sensitivity to spatial grid resolutions. The use of finer grid resolutions (3- or 9-km) can generally improve the performance for those variables. While the performance for most of these variables is consistent with that over the U.S. and East Asia, several differences along with future work are identified to pinpoint reasons for such differences. [ABSTRACT FROM AUTHOR]

The reliable mathematical modelling of secondary petroleum migration that incorporates structural geology and mature source rocks in the basin model, allows for prediction of the reservoir location, yielding the significant enhancement of the probability of exploration success. We investigate secondary petroleum migration with a significant composition difference between the source and oil pools. In our case study, the secondary migration period is significantly shorter than the time of the hydrocarbon pulse generation. Therefore, neither adsorption nor dispersion of components can explain the concentration difference between the source rock and the reservoir. For the first time, the present paper proposes deep bed filtration of hydrocarbons with component kinetics retention by the rock as a physics mechanism explaining compositional grading. Introduction of the component capture rate into mass balance transport equation facilitates matching the concentration difference for heavy hydrocarbons, and the tuned filtration coefficients vary in their common range. The obtained values of filtration coefficients monotonically increase with molecular weight and consequently affects the size of the oleic component, as predicted by the analytical model of deep bed filtration. The modelling shows a negligible effect of component dispersion on the compositional grading. [ABSTRACT FROM AUTHOR]

The middle school concept, aimed at creating a more developmentally responsive learning environment for young adolescents, gained a stronghold in the later part of the 20th century. Proponents of this concept have argued continually for the holistic implementation of its six key characteristics if its benefits are to be realized. These characteristics include: (a) a challenging, integrative, and exploratory curriculum; (b) varied teaching and learning approaches; (c) assessment and evaluation that promote learning; (d) flexible organizational structures (i.e., including the physical space, scheduling, and grouping of students and teachers); (e) programs and policies that foster health, wellness and safety; and (f) comprehensive guidance and support services. Recently, Ellerbrock, Falbe, and Pomykal Franz identified key middle school organizational structures of people, place, and time as being interconnected and integral to effective middle school practices. Main also demonstrated the interconnected nature of these key characteristics and how organizational structures of people affected the successful implementation of other characteristics. Thus, how these organizational structures can and are being implemented has implications for our understanding of the effectiveness of other middle school practices. In this paper, researchers from both the United States and Australia examine and compare literature published between 2000 and 2018 addressing ways in which middle school/middle years organizational structures have been reported and categorized by structures of people, place, and time in these two countries. Pertinent literature related to organizational structures of middle schools in the United States and to middle years education in Australia was examined. Findings from studies and evaluations from each country are reported to provide an international perspective on the organizational structures of middle schools/middle years education across the two countries. Overall, since 2000, the body of knowledge about middle schools/middle years organizational structures has been surprisingly limited in comparison to their perceived importance in the field. This lack of research is concerning in the midst of educational reform in both countries, resulting in questions about the impact of school organizational structures on young adolescent development and learning. [ABSTRACT FROM AUTHOR]

Narrabeen-Collaroy Beach, located on the Northern Beaches of Sydney along the Pacific coast of southeast Australia, is one of the longest continuously monitored beaches in the world. This paper provides an overview of the evolution and international scientific impact of this long-term beach monitoring program, from its humble beginnings over 40 years ago using the rod and tape measure Emery field survey method; to today, where the application of remote sensing data collection including drones, satellites and crowd-sourced smartphone images, are now core aspects of this continuing and much expanded monitoring effort. Commenced in 1976, surveying at this beach for the first 30 years focused on in-situ methods, whereby the growing database of monthly beach profile surveys informed the coastal science community about fundamental processes such as beach state evolution and the role of cross-shore and alongshore sediment transport in embayment morphodynamics. In the mid-2000s, continuous (hourly) video-based monitoring was the first application of routine remote sensing at the site, providing much greater spatial and temporal resolution over the traditional monthly surveys. This implementation of video as the first of a now rapidly expanding range of remote sensing tools and techniques also facilitated much wider access by the international research community to the continuing data collection program at Narrabeen-Collaroy. In the past decade the video-based data streams have formed the basis of deeper understanding into storm to multi-year response of the shoreline to changing wave conditions and also contributed to progress in the understanding of estuary entrance dynamics. More recently, 'opportunistic' remote sensing platforms such as surf cameras and smartphones have also been used for image-based shoreline data collection. Commencing in 2011, a significant new focus for the Narrabeen-Collaroy monitoring program shifted to include airborne lidar (and later Unmanned Aerial Vehicles (UAVs)), in an enhanced effort to quantify the morphological impacts of individual storm events, understand key drivers of erosion, and the placing of these observations within their broader regional context. A fixed continuous scanning lidar installed in 2014 again improved the spatial and temporal resolution of the remote-sensed data collection, providing new insight into swash dynamics and the often-overlooked processes of post-storm beach recovery. The use of satellite data that is now readily available to all coastal researchers via Google Earth Engine continues to expand the routine data collection program and provide key insight into multi-decadal shoreline variability. As new and expanding remote sensing technologies continue to emerge, a key lesson from the long-term monitoring at Narrabeen-Collaroy is the importance of a regular re-evaluation of what data is most needed to progress the science. [ABSTRACT FROM AUTHOR]

In Australia since about the turn of the millennium, discrimination against Muslims has been increasingly normalized, made respectable, and presented as prudent precaution against violent extremism. Vilification of Muslims has posed as defending 'Australian values' against those who will not integrate. Liberal political leaders and press leader-writers who formerly espoused cultural pluralism now routinely hold up as inimical the Muslim folk devil by whose otherness the boundaries of acceptability of the national culture may be marked out and policed. The Muslim Other is positioned not only as culturally incommensurate, but dangerously so: dishonest, criminally inclined, violent, misogynist, homophobic, backward, uncivilized. On the far right, extremist nationalist organizations incite racist hatred under cover of this rhetoric, often cloaked as reasonable common sense. This paper undertakes an ideology analysis of political and media discussion, and examines the forms of social control that they advance and sustain. [ABSTRACT FROM AUTHOR]