Dedicated emergency theatres improve service delivery and surgeons' job satisfaction

Background
There are well-described benefits to separating emergency and elective surgery. Geelong Hospital lacked the resources to implement a separate acute surgical unit, but instituted daily dedicated emergency general surgery operating sessions, managed by an on-site consultant. This study aims to assess the impact of this on service delivery and surgeons' job satisfaction.
Methods
From 1 February 2011, daily half-day operating lists were allocated for general surgical emergencies. Patients treated on these lists were studied prospectively until 31 December 2011. Theatre waiting times and hospital stay were compared with the previous year. A quality-of-life questionnaire was administered to participating surgeons before the project commenced and after 6 months.
Results
A total of 966 patients underwent surgery during an emergency general surgery admission in the control period, and 984 underwent surgery during the study period. The median time from arrival in the emergency department (ED) to surgery was reduced from 19 (18–21) h in the control group to 18 (17–19) h in the study group (P = 0.033). The time from booking surgery to operation was reduced from 4.8 (4.3–5.4) h to 3.9 (3.5–4.3) h (P < 0.0001). For patients undergoing emergency laparotomy, the time from booking to surgery was reduced from 3.1 (2.2–4.1) to 2.4 (1.8–2.9) h, and hospital stay was reduced from 13 (11–15) to 10 (9–12) days (P = 0.0089). The surgeons' responses to the questionnaires showed improvement in job satisfaction (P < 0.0001).
Conclusion
This intervention has improved service delivery for emergency surgery patients, and improved the participating surgeons' job satisfaction.

Developing online construction technology resources in tectonic design education

We outline issues of importance in relation to tectonic design within the architectural profession and the relationship to architectural education in Australia. Twelve years of research and curriculum development at Deakin University is discussed, involving the creation of online resources and case studies, digitally-integrated projects relating to building construction and design studio education. The ethos behind the Construction Primer of engaging students as ‘amateur researchers’ in a way that ensures ‘that student research work is worth more than course assessment’ forms the pedagogical foundation of much of this work. A model of Socially Networked Construction Technology education has been developed that integrates social networks and the Internet to engage students in tectonic design within and outside the classroom through authentic curricula. Through the use of Virtual Galleries, Blogs, YouTube and social networks, a culture of peer learning and sharing has been developed. Through shared knowledge facilitated through social networks, great potential lies for expanding the synergies between higher order learning and online resource development for design decision support.

Role assessment of GIS analysis and its reliability while ranking urban sustainability using scenarios specific to regional climate, community and culture

Urban Sustainability expresses the level of conservation of a city while living a town or consuming its urban resources, but the measurement of urban sustainability depends on what are considered important indicators of conservation besides the permitted levels of consumption in accordance with adopted criteria. This criterion should have common factors that are shared for all the members tested or cities to be evaluated as in this particular case for Abu Dhabi, but also have specific factors that are related to the geographic place, community and culture, that is the measures of urban sustainability specific to a middle east climate, community and culture where GIS Vector and Raster analysis have a role or add a value in urban sustainability measurements or grading are considered herein. Scenarios were tested using various GIS data types to replicate urban history (ten years period), current status and expected future of Abu Dhabi City setting factors to climate, community needs and culture. The useful Vector or Raster GIS data sets that are related to every scenario where selected and analysed in the sense of how and how much it can benefit the urban sustainability ranking in quantity and quality tests, this besides assessing the suitable data nature, type and format, the important topology rules to be considered, the useful attributes to be added, the relationships which should be maintained between data types of a geo- database, and specify its usage in a specific scenario test, then setting weights to each and every data type representing some elements of a phenomenon related to urban suitability factor. The results of assessing the role of GIS analysis provided data collection specifications such as the measures of accuracy reliable to a certain type of GIS functional analysis used in an urban sustainability ranking scenario tests. This paper reflects the prior results of the research that is conducted to test the multidiscipline evaluation of urban sustainability using different indicator metrics, that implement vector GIS Analysis and Raster GIS analysis as basic tools to assist the evaluation and increase of its reliability besides assessing and decomposing it, after which a hypothetical implementation of the chosen evaluation model represented by various scenarios was implemented on the planned urban sustainability factors for a certain period of time to appraise the expected future grade of urban sustainability and come out with advises associated with scenarios for assuring gap filling and relative high urban future sustainability. The results this paper is reflecting are concentrating on the elements of vector and raster GIS analysis that assists the proper urban sustainability grading within the chosen model, the reliability of spatial data collected; analysis selected and resulted spatial information. Starting from selecting some important indicators to comprise the model which include regional culture, climate and community needs an example of what was used is Energy Demand & Consumption (Cooling systems). Thus, this factor is related to the climate and it‟s regional specific as the temperature varies around 30-45 degrees centigrade in city areas, GIS 3D Polygons of building data used to analyse the volume of buildings, attributes „building heights‟, estimate the number of floors from the equation, following energy demand was calculated and consumption for the unit volume, and compared it in scenario with possible sustainable energy supply or using different environmental friendly cooling systems this is followed by calculating the cooling system effects on an area unit selected to be 1 sq. km, combined with the level of greenery area, and open space, as represented by parks polygons, trees polygons, empty areas, pedestrian polygons and road surface area polygons. (initial measures showed that cooling system consumption can be reduced by around 15 -20 % with a well-planned building distributions, proper spaces and with using environmental friendly products and building material, temperature levels were also combined in the scenario extracted from satellite images as interpreted from thermal bands 3 times during the period of assessment. Other examples of the assessment of GIS analysis to urban sustainability took place included Waste Productivity, some effects of greenhouse gases measured by the intensity of road polygons and closeness to dwelling areas, industry areas as defined from land use land cover thematic maps produced from classified satellite images then vectors were created to take part in defining their role within the scenarios. City Noise and light intensity assessment was also investigated, as the region experiences rapid development and noise is magnified due to construction activities, closeness of the airports, and highways. The assessment investigated the measures taken by urban planners to reduce degradation or properly manage it. Finally as a conclusion tables were presented to reflect the scenario results in combination with GIS data types, analysis types, and the level of GIS data reliability to measure the sustainability level of a city related to cultural and regional demands.

The contribution of job and partner satisfaction to the homeostatic defense of subjective wellbeing

Two studies investigate subjective wellbeing (SWB) homeostasis. The first investigates the contribution of job satisfaction (JS) and partner satisfaction (PS) to the homeostatic defense of SWB. The extant model of homeostasis does not include either variable. The second study investigates the relationship between Homeostatically Protected Mood (HPMood) and other factors involved in the homeostatic model. It has been proposed that HPMood is the basic, biologically determined, positive mood that saturates SWB and other related variables, and forms the basis of the SWB set-point. Thus, if HPMood is an individual difference and it perfuses other homeostatic variables, then HPMood should be responsible for much of the shared variance between such variables. Two comparative samples are involved. One is a group of 171 Hong Kong Chinese recruited through convenience sampling. The other is a group of 343 Australians recruited via a general population survey. Results indicate that both JS and PS predict significant variance in Global Life Satisfaction beyond the existing factors in the homeostatic model. It is also found that, after controlling for the effect of HPMood, the strength of correlations between SWB and other homeostatic variables is significantly diminished. The implications of these findings are discussed.

Sustainable construction : reliable forecasting for building construction prices

A reliable forecasting for future construction costs or prices would help to ensure the budget of a construction project can be well planned and limited resources can be allocated more appropriately in construction firms. Although many studies have been focused on the construction price modelling and forecasting, few researchers have considered the impacts of the global economic events and seasonality in price modelling and forecasting. In this study, an advanced multivariate modelling technique, namely the vector correction (VEC) model with dummy variables was employed and the impacts of the global economic event and seasonality were factored into the forecasting model for the building construction price in the Australian construction market. Research findings suggest that a long-run equilibrium relationship exists among the price, levels of supply and demand in the construction market. The reliability of forecasting models was examined by mean absolute percentage error (MAPE) and The Theil's inequality coefficient U tests. The results of MAPE and U tests suggest that the conventional VEC model and the VEC model with dummy variable are both acceptable for forecasting building construction prices, while the VEC model that considered external impacts achieves higher prediction accuracy than the conventional VEC model does.

Neural network ensemble : evaluation of aggregation algorithms for electricity demand forecasting

This paper examines and analyzes different aggregation algorithms to improve accuracy of forecasts obtained using neural network (NN) ensembles. These algorithms include equal-weights combination of Best NN models, combination of trimmed forecasts, and Bayesian Model Averaging (BMA). The predictive performance of these algorithms are evaluated using Australian electricity demand data. The output of the aggregation algorithms of NN ensembles are compared with a Naive approach. Mean absolute percentage error is applied as the performance index for assessing the quality of aggregated forecasts. Through comprehensive simulations, it is found that the aggregation algorithms can significantly improve the forecasting accuracies. The BMA algorithm also demonstrates the best performance amongst aggregation algorithms investigated in this study.

The effects of the late 2000s global financial crisis on Australia's construction demand

An accurate measurement of the impacts of external shocks on construction demand will enable construction industry policymakers and developers to make allowances for future occurrences and advance the construction industry in a sustainable manner. This paper aims to measurethe dynamic effects of the late 2000s global financial crisis on the level of demand in the Australian construction industry. The vector error correction (VEC) model with intervention indicators is employed to estimate the external impact from the crisis on a macro-level construction economic indicator, namely construction demand. The methodology comprises six main stages to produce appropriate VEC models that describe the characteristics of the underlying process. Research findings suggestthat overall residential and non-residential construction demand were affected significantly by the recent crisis and seasonality. Non-residentialconstruction demand was disrupted more than residential construction demand at the crisis onset. The residential constructionindustry is more reactive and is able to recover faster following the crisis in comparison with the non-residential industry. The VEC model with intervention indicators developed in this study can be used as an experiment for an advanced econometric method. This can be used to analyse the effects of special eventsand factors not only on construction but also on other industries.

GLOA : a new job scheduling algorithm for grid computing

The purpose of grid computing is to produce a virtual supercomputer by using free resources available through widespread networks such as the Internet. This resource distribution, changes in resource availability, and an unreliable communication infrastructure pose a major challenge for efficient resource allocation. Because of the geographical spread of resources and their distributed management, grid scheduling is considered to be a NP-complete problem. It has been shown that evolutionary algorithms offer good performance for grid scheduling. This article uses a new evaluation (distributed) algorithm inspired by the effect of leaders in social groups, the group leaders' optimization algorithm (GLOA), to solve the problem of scheduling independent tasks in a grid computing system. Simulation results comparing GLOA with several other evaluation algorithms show that GLOA produces shorter makespans.

The influence of organisational commitment, job involvement and utility perceptions on trainees’ motivation to improve work through learning

Workplace training is a key strategy often used by organisations to optimise performance. Further, trainee motivation is a key determinant of the degree to which the material learned in a training programme will be transferred to the workplace, enhancing the performance of the trainee. This study investigates the relationship between several components of the Revised Human Resource Development (HRD) Evaluation and Research Model. This model provides a framework for diagnosing and understanding the causal influences of HRD intervention outcomes on training effectiveness. Data were obtained from an online questionnaire completed by 105 employees of various organisations. Findings revealed that affective organisational commitment, job involvement and utility perceptions are predictors of motivation to learn and transfer learning. An interaction effect was found, with increased affective organisational commitment predicting greater motivation to learn when training was of lower perceived utility. These findings suggest that the design and delivery of training should emphasise the relevance and utility of the programme in order to encourage greater trainee motivation and maximise return on investment. Additionally, implementing strategies aimed at promoting organisational commitment would appear beneficial.

Job strain — attributable depression in a sample of working Australians: assessing the contribution to health inequalities

Background The broad aim of this study was to assess the contribution of job strain to mental health inequalities by (a) estimating the proportion of depression attributable to job strain (low control and high demand jobs), (b) assessing variation in attributable risk by occupational skill level, and (c) comparing numbers of job strain–attributable depression cases to numbers of compensated 'mental stress' claims. Methods Standard population attributable risk (PAR) methods were used to estimate the proportion of depression attributable to job strain. An adjusted Odds Ratio (OR) of 1.82 for job strain in relation to depression was obtained from a recently published meta-analysis and combined with exposure prevalence data from the Australian state of Victoria. Job strain exposure prevalence was determined from a 2003 population-based telephone survey of working Victorians (n = 1101, 66% response rate) using validated measures of job control (9 items, Cronbach's alpha = 0.80) and psychological demands (3 items, Cronbach's alpha = 0.66). Estimates of absolute numbers of prevalent cases of depression and successful stress-related workers' compensation claims were obtained from publicly available Australian government sources. Results Overall job strain-population attributable risk (PAR) for depression was 13.2% for males [95% CI 1.1, 28.1] and 17.2% [95% CI 1.5, 34.9] for females. There was a clear gradient of increasing PAR with decreasing occupational skill level. Estimation of job strain–attributable cases (21,437) versus "mental stress" compensation claims (696) suggest that claims statistics underestimate job strain–attributable depression by roughly 30-fold. Conclusion Job strain and associated depression risks represent a substantial, preventable, and inequitably distributed public health problem. The social patterning of job strain-attributable depression parallels the social patterning of mental illness, suggesting that job strain is an important contributor to mental health inequalities. The numbers of compensated 'mental stress' claims compared to job strain-attributable depression cases suggest that there is substantial under-recognition and under-compensation of job strain-attributable depression. Primary, secondary, and tertiary intervention efforts should be substantially expanded, with intervention priorities based on hazard and associated health outcome data as an essential complement to claims statistics.

Cost of reproduction in the Queensland fruit fly: Y-model versus lethal protein hypothesis

The trade-off between lifespan and reproduction is commonly explained by differential allocation of limited resources. Recent research has shown that the ratio of protein to carbohydrate (P : C) of a fly's diet mediates the lifespan–reproduction trade-off, with higher P : C diets increasing egg production but decreasing lifespan. To test whether this P : C effect is because of changing allocation strategies (Y-model hypothesis) or detrimental effects of protein ingestion on lifespan (lethal protein hypothesis), we measured lifespan and egg production in Queensland fruit flies varying in reproductive status (mated, virgin and sterilized females, virgin males) that were fed one of 18 diets varying in protein and carbohydrate amounts. The Y-model predicts that for sterilized females and for males, which require little protein for reproduction, there will be no effect of P : C ratio on lifespan; the lethal protein hypothesis predicts that the effect of P : C ratio should be similar in all groups. In support of the lethal protein hypothesis, and counter to the Y-model, the P : C ratio of the ingested diets had similar effects for all groups. We conclude that the trade-off between lifespan and reproduction is mediated by the detrimental side-effects of protein ingestion on lifespan.