The management of transport construction projects : a survey of public sector organisations in Queensland Australia

Construction procurement organisations in the Australian framework provide broad guidelines on project management in setting benchmark performance measurements and processes for evaluating their projects. Despite this, little has been known in the project management practise in transport construction projects in Australia, in particular Queensland. Questionnaire data from 53 project management practitioners employed in State and City public sector organisations in Queensland,suggested that many practitioners in the public sector have little or a lack of understanding of government regulatory policies, which are used as economic evaluation tools for project options. Public sector project managers perceive socio-economic evaluation tools as inappropriate for public sector projects. The survey results also found conducting risk management analysis, developing a risk register and mitigation of risks were most effective way of managing risk. This study provides an opportunity for the public sector to review and provide training on project management practices and government regulatory policies governing public projects. This will improve project management practitioners’ understanding and interpretation of government regulatory policies.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

Publishing Engineering Education Resources: A Collaborative Web Project.

Web is a powerful hypermedia-based information retrieval mechanism that provides a user-friendly access across all major computer platforms connected over Internet. This paper demonstrates the application of Web technology when used as an educational delivery tool. It also reports on the development of a prototype electronic publishing project where Web technology was used to deliver power engineering educational resources. The resulting hyperbook will contain diverse teaching resources such as hypermedia-based modular educational units and computer simulation programs that are linked in a meaningful and structured way. The use of Web for disseminating information of this nature has many advantages that cannot possibly be achieved otherwise. PREAMBLE The continual increase of low-cost functionality available in desktop computing has opened up a new possibility in learning within a wider educational framework. This technology also is supported by enhanced features offered by new and ...

Pretreatment malnutrition and quality of life - association with prolonged length of hospital stay among patients with gynecological cancer: A cohort study

Background Length of hospital stay (LOS) is a surrogate marker for patients' well-being during hospital treatment and is associated with health care costs. Identifying pretreatment factors associated with LOS in surgical patients may enable early intervention in order to reduce postoperative LOS. Methods This cohort study enrolled 157 patients with suspected or proven gynecological cancer at a tertiary cancer centre (2004-2006). Before commencing treatment, the scored Patient Generated - Subjective Global Assessment (PG-SGA) measuring nutritional status and the Functional Assessment of Cancer Therapy-General (FACT-G) scale measuring quality of life (QOL) were completed. Clinical and demographic patient characteristics were prospectively obtained. Patients were grouped into those with prolonged LOS if their hospital stay was greater than the median LOS and those with average or below average LOS. Results Patients' mean age was 58 years (SD 14 years). Preoperatively, 81 (52%) patients presented with suspected benign disease/pelvic mass, 23 (15%) with suspected advanced ovarian cancer, 36 (23%) patients with suspected endometrial and 17 (11%) with cervical cancer, respectively. In univariate models prolonged LOS was associated with low serum albumin or hemoglobin, malnutrition (PG-SGA score and PG-SGA group B or C), low pretreatment FACT-G score, and suspected diagnosis of cancer. In multivariable models, PG-SGA group B or C, FACT-G score and suspected diagnosis of advanced ovarian cancer independently predicted LOS. Conclusions Malnutrition, low quality of life scores and being diagnosed with advanced ovarian cancer are the major determinants of prolonged LOS amongst gynecological cancer patients. Interventions addressing malnutrition and poor QOL may decrease LOS in gynecological cancer patients.

Video-stimulated accounts: Young children accounting for interactional matters in front of peers

Research in the early years places increasing importance on participatory methods to engage children. The playback of video-recording to stimulate conversation is a research method that enables children’s accounts to be heard and attends to a participatory view. During video-stimulated sessions, participants watch an extract of video-recording of a specific event in which they were involved, and then account for their participation in that event. Using an interactional perspective, this paper draws distinctions between video-stimulated accounts and a similar research method, popular in education, that of video-stimulated recall. Reporting upon a study of young children’s interactions in a playground, video-stimulated accounts are explicated to show how the participants worked toward the construction of events in the video-stimulated session. This paper discusses how the children account for complex matters within their social worlds, and manage the accounting of others in the video-stimulated session. When viewed from an interactional perspective and used alongside fine grained analytic approaches, video-stimulated accounts are an effective method to provide the standpoint of the children involved and further the competent child paradigm.

Reconciling the supply of and demand for carbon cycle science in the US agricultural sector

When asking the question, ``How can institutions design science policies for the benefit of decision makers?'' Sarewitz and Pielke Sarewitz, D., Pielke Jr., R.A., this issue. The neglected heart of science policy: reconciling supply of and demand for science. Environ. Sci. Policy 10] posit the idea of ``reconciling supply and demand of science'' as a conceptual tool for assessment of science programs. We apply the concept to the U.S. Department of Agriculture's (USDA) carbon cycle science program. By evaluating the information needs of decision makers, or the ``demand'', along with the supply of information by the USDA, we can ascertain where matches between supply and demand exist, and where science policies might miss opportunities. We report the results of contextual mapping and of interviews with scientists at the USDA to evaluate the production and use of current agricultural global change research, which has the stated goal of providing ``optimal benefit'' to decision makers on all levels. We conclude that the USDA possesses formal and informal mechanisms by which scientists evaluate the needs of users, ranging from individual producers to Congress and the President. National-level demands for carbon cycle science evolve as national and international policies are explored. Current carbon cycle science is largely derived from those discussions and thus anticipates the information needs of producers. However, without firm agricultural carbon policies, such information is currently unimportant to producers. (C) 2006 Elsevier Ltd. All rights reserved.

Diagnostic and treatment pathways for men with prostate cancer in Queensland : investigating spatial and demographic inequalities

Background: Patterns of diagnosis and management for men diagnosed with prostate cancer in Queensland, Australia, have not yet been systematically documented and so assumptions of equity are untested. This longitudinal study investigates the association between prostate cancer diagnostic and treatment outcomes and key area-level characteristics and individual-level demographic, clinical and psychosocial factors.---------- Methods/Design: A total of 1064 men diagnosed with prostate cancer between February 2005 and July 2007 were recruited through hospital-based urology outpatient clinics and private practices in the centres of Brisbane, Townsville and Mackay (82% of those referred). Additional clinical and diagnostic information for all 6609 men diagnosed with prostate cancer in Queensland during the study period was obtained via the population-based Queensland Cancer Registry. Respondent data are collected using telephone and self-administered questionnaires at pre-treatment and at 2 months, 6 months, 12 months, 24 months, 36 months, 48 months and 60 months post-treatment. Assessments include demographics, medical history, patterns of care, disease and treatment characteristics together with outcomes associated with prostate cancer, as well as information about quality of life and psychological adjustment. Complementary detailed treatment information is abstracted from participants’ medical records held in hospitals and private treatment facilities and collated with health service utilisation data obtained from Medicare Australia. Information about the characteristics of geographical areas is being obtained from data custodians such as the Australian Bureau of Statistics. Geo-coding and spatial technology will be used to calculate road travel distances from patients’ residences to treatment centres. Analyses will be conducted using standard statistical methods along with multilevel regression models including individual and area-level components.---------- Conclusions: Information about the diagnostic and treatment patterns of men diagnosed with prostate cancer is crucial for rational planning and development of health delivery and supportive care services to ensure equitable access to health services, regardless of geographical location and individual characteristics. This study is a secondary outcome of the randomised controlled trial registered with the Australian New Zealand Clinical Trials Registry (ACTRN12607000233426)

Connecting people and resource consumption in real time

The authors currently engage in two projects to improve human-computer interaction (HCI) designs that can help conserve resources. The projects explore motivation and persuasion strategies relevant to ubiquitous computing systems that bring real-time consumption data into the homes and hands of residents in Brisbane, Australia. The first project seeks to increase understanding among university staff of the tangible and negative effects that excessive printing has on the workplace and local environment. The second project seeks to shift attitudes toward domestic energy conservation through software and hardware that monitor real-time, in situ electricity consumption in homes across Queensland. The insights drawn from these projects will help develop resource consumption user archetypes, providing a framework linking people to differing interface design requirements.

Health risk from the use of roof-harvested rainwater in Southeast Queensland, Australia, as potable or nonpotable water, determined using quantitative microbial risk assessment

A total of 214 rainwater samples from 82 tanks were collected in urban Southeast Queensland (SEQ) in Australia and analysed for the zoonotic bacterial and protozoan pathogen using real-time binary PCR and quantitative PCR (qPCR). Quantitative Microbial Risk Assessment (QMRA) analysis was used to quantify the risk of infection associated with the exposure to potential pathogens from potable and non-potable uses of roof-harvested rainwater. Of the 214 samples tested, 10.7%, 9.8%, and 5.6%, and 0.4% samples were positive for Salmonella invA, Giardia lamblia β-giardin , Legionella pneumophila mip, and Campylobacter jejuni mapA genes. Cryptosporidium parvum could not be detected. The estimated numbers of viable Salmonella spp., G. lamblia β-giradin, and L. pneumophila genes ranged from 1.6 × 101 to 9.5 × 101 cells, 1.4 × 10-1 to 9.0 × 10-1 cysts, and 1.5 × 101 to 4.3 × 101 per 1000 ml of water, respectively. Six risk scenarios were considered from exposure to Salmonella spp., G. lamblia and L. pneumophila. For Salmonella spp., and G. lamblia, these scenarios were: (1) liquid ingestion due to drinking of rainwater on a daily basis (2) accidental liquid ingestion due to garden hosing twice a week (3) aerosol ingestion due to showering on a daily basis, and (4) aerosol ingestion due to hosing twice a week. For L. pneumophila, these scenarios were: (5) aerosol inhalation due to showering on a daily basis, and (6) aerosol inhalation due to hosing twice a week. The risk of infection from Salmonella spp., G. lamblia, and L. pneumophila associated with the use of rainwater for showering and garden hosing was calculated to be well below the threshold value of one extra infection per 10,000 persons per year in urban SEQ. However, the risk of infection from ingesting Salmonella spp. and G. lamblia via drinking exceeds this threshold value, and indicates that if undisinfected rainwater were ingested by drinking, then the gastrointestinal diseases of Salmonellosis and Giardiasis is expected to range from 5.0 × 100 to 2.8 × 101 (Salmonellosis) and 1.0 × 101 to 6.4 × 101 (Giardiasis) cases per 10,000 persons per year, respectively. Since this health risk seems higher than that expected from the reported incidences of gastroenteritis, the assumptions used to estimate these infection risks are critically examined. Nonetheless, it would seem prudent to disinfect rainwater for potable use.

Listening to voices of self : digital journaling among gifted young adolescents

The lives of gifted young adolescents are often subject to adult-generated and expert narratives that can impact a developing sense of self. However, opportunities for gifted young adolescents to represent themselves as informants can emerge through digital forms of qualitative research. This paper reports on the value of digital writing of journal entries, delivered by email to a researcher over several months, as an alternative to face-to-face interviews. Journaling methods combined with techniques of 'listening for voices' can support young adolescents in generating their own multi-vocal narratives of self. This method capturing self-narratives in email form has the potential to produce rich understandings of individual young adolescents' self-constructions.

Empathy, neutrality and emotional intelligence: a balancing act for the emotional Einstein

Emotions play a central role in mediation as they help to define the scope and direction of a conflict. When a party to mediation expresses (and hence entrusts) their emotions to those present in a mediation, a mediator must do more than simply listen - they must attend to these emotions. Mediator empathy is an essential skill for communicating to a party that their feelings have been heard and understood, but it can lead mediators into trouble. Whilst there might exist a theoretical divide between the notions of empathy and sympathy, the very best characteristics of mediators (caring and compassionate nature) may see empathy and sympathy merge - resulting in challenges to mediator neutrality. This article first outlines the semantic difference between empathy and sympathy and the role that intrapsychic conflict can play in the convergence of these behavioural phenomena. It then defines emotional intelligence in the context of a mediation, suggesting that only the most emotionally intelligent mediators are able to emotionally connect with the parties, but maintain an impression of impartiality – the quality of remaining ‘attached yet detached’ to the process. It is argued that these emotionally intelligent mediators have the common qualities of strong self-awareness and emotional self-regulation.

Channel-aware routing in MANETs with route handoff

In wireless mobile ad hoc networks (MANETs), packet transmission is impaired by radio link fluctuations. This paper proposes a novel channel adaptive routing protocol which extends the Ad-hoc On-Demand Multipath Distance Vector routing protocol (AOMDV) to accommodate channel fading. Specifically, the proposed Channel Aware AOMDV (CA-AOMDV) uses the channel average non-fading duration as a routing metric to select stable links for path discovery, and applies a preemptive handoff strategy to maintain reliable connections by exploiting channel state information. Using the same information, paths can be reused when they become available again, rather than being discarded. We provide new theoretical results for the downtime and lifetime of a live-die-live multiple path system, as well as detailed theoretical expressions for common network performance measures, providing useful insights into the differences in performance between CA-AOMDV and AOMDV. Simulation and theoretical results show that CA-AOMDV has greatly improved network performance over AOMDV.

Contribution of transmembrane domain V amino acids to β1l-adrenoceptor activity and affinity

Introduction. There are two binding sites on the β1-adrenoceptor (AR), β1H and β1L corresponding to high and low affinity binding sites respectively, which can be activated to cause cardiostimulation. Some β-blockers that block β1AR and β2ARs can activate β1LARs at higher concentrations than those required to cause blockade. The β2AR does not form a corresponding low affinity binding site and therefore we postulated that heterologous amino acids are responsible for the formation of β1LAR. Aim. To investigate whether heterologous amino acids of transmembrane domain V (TMDV) of β1AR and β2ARs contribute to β1LAR. Methods. β1ARs, β2ARs and mutant β1ARs containing all (β1(β2TMDV)AR) or single amino acids of TMDV of the β2AR were prepared and stably expressed in Chinese Hamster Ovary cells. Concentration-effect curves for cyclicAMP accumulation were carried out for (-)-CGP12177 in the absence or presence of (-)-bupranolol. Results. The potencies (pEC50) of (-)-CGP12177 were β2AR (9.24 ± 0.14, n = 5), β1(V230I)AR (9.07 ± 0.07, n = 10), β1(β2TMDV)AR (8.86 ± 0.10, n = 15), β1(R222Q)AR (8.09 ± 0.29, n = 6), β1AR (8.00 ± 0.11, n = 11). The affinities (pKB) of (-)-bupranolol were β2AR (9.82 ± 0.52, n = 5), β1(V230I)AR (7.64 ± 0.12, n = 8), β1(β2TMV)AR (8.06 ± 0.17, n = 8), β1(R222Q)AR (7.33 ± 0.23, n = 5), β1AR (7.23 ± 0.23, n = 5). Discussion. The potency of (-)-CGP12177 was higher at β2AR than at β1AR consistent with activation through a low affinity site at the β1AR (β1LAR). The presence of V230 in β1AR accounted for the lower potency of (-)-CGP 12177. The affinity of (-)-bupranolol was lower at β1AR compared to β2AR. The presence of V230 in β1AR accounted in part for the lower affinity. In conclusion TMDV of the β1AR contributes in part to the low affinity binding site of β1AR.

Reduction of environmental effects of civil aircraft through multi-objective flight plan optimisation

With rising environmental alarm, the reduction of critical aircraft emissions including carbon dioxides (CO2) and nitrogen oxides (NOx) is one of most important aeronautical problems. There can be many possible attempts to solve such problem by designing new wing/aircraft shape, new efficient engine, etc. The paper rather provides a set of acceptable flight plans as a first step besides replacing current aircrafts. The paper investigates a green aircraft design optimisation in terms of aircraft range, mission fuel weight (CO2) and NOx using advanced Evolutionary Algorithms coupled to flight optimisation system software. Two multi-objective design optimisations are conducted to find the best set of flight plans for current aircrafts considering discretised altitude and Mach numbers without designing aircraft shape and engine types. The objectives of first optimisation are to maximise range of aircraft while minimising NOx with constant mission fuel weight. The second optimisation considers minimisation of mission fuel weight and NOx with fixed aircraft range. Numerical results show that the method is able to capture a set of useful trade-offs that reduce NOx and CO2 (minimum mission fuel weight).

Vulnerability of eco-environmental health to climate change : the views of government stakeholders and other specialists in Queensland, Australia

Background: There is overwhelming scientific evidence that human activities have changed and will continue to change the climate of the Earth. Eco-environmental health, which refers to the interdependencies between ecological systems and population health and well-being, is likely to be significantly influenced by climate change. The aim of this study was to examine perceptions from government stakeholders and other relevant specialists about the threat of climate change, their capacity to deal with it, and how to develop and implement a framework for assessing vulnerability of eco-environmental health to climate change.---------- Methods: Two focus groups were conducted in Brisbane, Australia with representatives from relevant government agencies, non-governmental organisations, and the industry sector (n = 15) involved in the discussions. The participants were specialists on climate change and public health from governmental agencies, industry, and nongovernmental organisations in South-East Queensland.---------- Results: The specialists perceived climate change to be a threat to eco-environmental health and had substantial knowledge about possible implications and impacts. A range of different methods for assessing vulnerability were suggested by the participants and the complexity of assessment when dealing with multiple hazards was acknowledged. Identified factors influencing vulnerability were perceived to be of a social, physical and/or economic nature. They included population growth, the ageing population with associated declines in general health and changes in the vulnerability of particular geographical areas due to for example, increased coastal development, and financial stress. Education, inter-sectoral collaboration, emergency management (e.g. development of early warning systems), and social networks were all emphasised as a basis for adapting to climate change. To develop a framework, different approaches were discussed for assessing eco-environmental health vulnerability, including literature reviews to examine the components of vulnerability such as natural hazard risk and exposure and to investigate already existing frameworks for assessing vulnerability.---------- Conclusion: The study has addressed some important questions in regard to government stakeholders and other specialists’ views on the threat of climate change and its potential impacts on eco-environmental health. These findings may have implications in climate change and public health decision-making.