Quantifying the roles of cell motility and cell proliferation in a circular barrier assay

Moving fronts of cells are essential features of embryonic development, wound repair and cancer metastasis. This paper describes a set of experiments to investigate the roles of random motility and proliferation in driving the spread of an initially confined cell population. The experiments include an analysis of cell spreading when proliferation was inhibited. Our data have been analysed using two mathematical models: a lattice-based discrete model and a related continuum partial differential equation model. We obtain independent estimates of the random motility parameter, D, and the intrinsic proliferation rate, λ, and we confirm that these estimates lead to accurate modelling predictions of the position of the leading edge of the moving front as well as the evolution of the cell density profiles. Previous work suggests that systems with a high λ/D ratio will be characterized by steep fronts, whereas systems with a low λ/D ratio will lead to shallow diffuse fronts and this is confirmed in the present study. Our results provide evidence that continuum models, based on the Fisher–Kolmogorov equation, are a reliable platform upon which we can interpret and predict such experimental observations.

Urban renewal, migration and memories : the affordances of place-based pedagogies for developing immigrant students’ literate repertoires

This paper reports on the new literacy demands in the middle years of schooling project in which the affordances of placed-based pedagogy are being explored through teacher inquiries and classroom-based design experiments. The school is located within a large-scale urban renewal project in which houses are being demolished and families relocated. The original school buildings have recently been demolished and replaced by a large ‘superschool’ which serves a bigger student population from a wider area. Drawing on both quantitative and qualitative data, the teachers reported that the language literacy learning of students (including a majority of students learning English as a second language) involved in the project exceeded their expectations. The project provided the motivation for them to develop their oral language repertoires, by involving them in processes such as conducting interviews with adults for their oral histories, through questioning the project manager in regular meetings, and through reporting to their peers and the wider community at school assemblies. At the same time students’ written and multimodal documentation of changes in the neighbourhood and the school grounds extended their literate and semiotic repertoires as they produced books, reports, films, powerpoints, visual designs and models of structures.

Slice, mine and dice : complexity-aware automated discovery of business process models

Automated process discovery techniques aim at extracting models from information system logs in order to shed light into the business processes supported by these systems. Existing techniques in this space are effective when applied to relatively small or regular logs, but otherwise generate large and spaghetti-like models. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. The result is a collection of process models -- each one representing a variant of the business process -- as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically by means of subprocess extraction. The proposed technique allows users to set a desired bound for the complexity of the produced models. Experiments on real-life logs show that the technique produces collections of models that are up to 64% smaller than those extracted under the same complexity bounds by applying existing trace clustering techniques.

A comprehensive investigation of the risky driving behaviour of young novice drivers

Young novice drivers - that is, drivers aged 16-25 years who are relatively inexperienced in driving on the road and have a novice (Learner, Provisional) driver's licence - have been overrepresented in car crash, injury and fatality statistics around the world for decades. There are numerous persistent characteristics evident in young novice driver crashes, fatalities and offences, including variables relating to the young driver themselves, broader social influences which include their passengers, the car they drive, and when and how they drive, and their risky driving behaviour in particular. Moreover, there are a range of psychosocial factors influencing the behaviour of young novice drivers, including the social influences of parents and peers, and person-related factors such as age-related factors, attitudes, and sensation seeking. Historically, a range of approaches have been developed to manage the risky driving behaviour of young novice drivers. Traditional measures predominantly relying upon education have had limited success in regulating the risky driving behaviour of the young novice driver. In contrast, interventions such as graduated driver licensing (GDL) which acknowledges young novice drivers' limitations - principally pertaining to their chronological and developmental age, and their driving inexperience - have shown to be effective in ameliorating this pervasive public health problem. In practice, GDL is a risk management tool that is designed to reduce driving at risky times (e.g., at night) or in risky driving conditions (e.g., with passengers), while still enabling novice drivers to obtain experience. In this regard, the GDL program in Queensland, Australia, was considerably enhanced in July 2007, and major additions to the program include mandated Learner practice of 100 hours recorded in a logbook, and passenger limits during night driving in the Provisional phase. Road safety researchers have also continued to consider the influential role played by the young driver's psychosocial characteristics, including psychological traits and states. In addition, whilst the majority of road safety user research is epidemiological in nature, contemporary road safety research is increasingly applying psychological and criminological theories. Importantly, such theories not only can guide young novice driver research, they can also inform the development and evaluation of countermeasures targeting their risky driving behaviour. The research is thus designed to explore the self-reported behaviours - and the personal, psychosocial, and structural influences upon the behaviours - of young novice drivers This thesis incorporates three stages of predominantly quantitative research to undertake a comprehensive investigation of the risky driving behaviour of young novices. Risky driving behaviour increases the likelihood of the young novice driver being involved in a crash which may harm themselves or other road users, and deliberate risky driving such as driving in excess of the posted speed limits is the focus of the program of research. The extant literature examining the nature of the risky behaviour of the young novice driver - and the contributing factors for this behaviour - while comprehensive, has not led to the development of a reliable instrument designed specifically to measure the risky behaviour of the young novice driver. Therefore the development and application of such a tool (the Behaviour of Young Novice Drivers Scale, or BYNDS) was foremost in the program of research. In addition to describing the driving behaviours of the young novice, a central theme of this program of research was identifying, describing, and quantifying personal, behavioural, and environmental influences upon young novice driver risky behaviour. Accordingly the 11 papers developed from the three stages of research which comprise this thesis are framed within Bandura's reciprocal determinism model which explicitly considers the reciprocal relationship between the environment, the person, and their behaviour. Stage One comprised the foundation research and operationalised quantitative and qualitative methodologies to finalise the instrument used in Stages Two and Three. The first part of Stage One involved an online survey which was completed by 761 young novice drivers who attended tertiary education institutions across Queensland. A reliable instrument for measuring the risky driving behaviour of young novices was developed (the BYNDS) and is currently being operationalised in young novice driver research in progress at the Centre for Injury Research and Prevention in Philadelphia, USA. In addition, regression analyses revealed that psychological distress influenced risky driving behaviour, and the differential influence of depression, anxiety, sensitivity to punishments and rewards, and sensation seeking propensity were explored. Path model analyses revealed that punishment sensitivity was mediated by anxiety and depression; and the influence of depression, anxiety, reward sensitivity and sensation seeking propensity were moderated by the gender of the driver. Specifically, for males, sensation seeking propensity, depression, and reward sensitivity were predictive of self-reported risky driving, whilst for females anxiety was also influential. In the second part of Stage One, 21 young novice drivers participated in individual and small group interviews. The normative influences of parents, peers, and the Police were explicated. Content analysis supported four themes of influence through punishments, rewards, and the behaviours and attitudes of parents and friends. The Police were also influential upon the risky driving behaviour of young novices. The findings of both parts of Stage One informed the research of Stage Two. Stage Two was a comprehensive investigation of the pre-Licence and Learner experiences, attitudes, and behaviours, of young novice drivers. In this stage, 1170 young novice drivers from across Queensland completed an online or paper survey exploring their experiences, behaviours and attitudes as a pre- and Learner driver. The majority of novices did not drive before they were licensed (pre-Licence driving) or as an unsupervised Learner, submitted accurate logbooks, intended to follow the road rules as a Provisional driver, and reported practicing predominantly at the end of the Learner period. The experience of Learners in the enhanced-GDL program were also examined and compared to those of Learner drivers who progressed through the former-GDL program (data collected previously by Bates, Watson, & King, 2009a). Importantly, current-GDL Learners reported significantly more driving practice and a longer Learner period, less difficulty obtaining practice, and less offence detection and crash involvement than Learners in the former-GDL program. The findings of Stage Two informed the research of Stage Three. Stage Three was a comprehensive exploration of the driving experiences, attitudes and behaviours of young novice drivers during their first six months of Provisional 1 licensure. In this stage, 390 of the 1170 young novice drivers from Stage Two completed another survey, and data collected during Stages Two and Three allowed a longitudinal investigation of self-reported risky driving behaviours, such as GDL-specific and general road rule compliance; risky behaviour such as pre-Licence driving, crash involvement and offence detection; and vehicle ownership, paying attention to Police presence, and punishment avoidance. Whilst the majority of Learner and Provisional drivers reported compliance with GDL-specific and general road rules, 33% of Learners and 50% of Provisional drivers reported speeding by 10-20 km/hr at least occasionally. Twelve percent of Learner drivers reported pre-Licence driving, and these drivers were significantly more risky as Learner and Provisional drivers. Ten percent of males and females reported being involved in a crash, and 10% of females and 18% of males had been detected for an offence, within the first six months of independent driving. Additionally, 75% of young novice drivers reported owning their own car within six months of gaining their Provisional driver's licence. Vehicle owners reported significantly shorter Learner periods and more risky driving exposure as a Provisional driver. Paying attention to Police presence on the roads appeared normative for young novice drivers: 91% of Learners and 72% of Provisional drivers reported paying attention. Provisional drivers also reported they actively avoided the Police: 25% of males and 13% of females; 23% of rural drivers and 15% of urban drivers. Stage Three also allowed the refinement of the risky behaviour measurement tool (BYNDS) created in Stage One; the original reliable 44-item instrument was refined to a similarly reliable 36-item instrument. A longitudinal exploration of the influence of anxiety, depression, sensation seeking propensity and reward sensitivity upon the risky behaviour of the Provisional driver was also undertaken using data collected in Stages Two and Three. Consistent with the research of Stage One, structural equation modeling revealed anxiety, reward sensitivity and sensation seeking propensity predicted self-reported risky driving behaviour. Again, gender was a moderator, with only reward sensitivity predicting risky driving for males. A measurement model of Akers' social learning theory (SLT) was developed containing six subscales operationalising the four constructs of differential association, imitation, personal attitudes, and differential reinforcement, and the influence of parents and peers was captured within the items in a number of these constructs. Analyses exploring the nature and extent of the psychosocial influences of personal characteristics (step 1), Akers' SLT (step 2), and elements of the prototype/willingness model (PWM) (step 3) upon self-reported speeding by the Provisional driver in a hierarchical multiple regression model found the following significant predictors: gender (male), car ownership (own car), reward sensitivity (greater sensitivity), depression (greater depression), personal attitudes (more risky attitudes), and speeding (more speeding) as a Learner. The research findings have considerable implications for road safety researchers, policy-makers, mental health professionals and medical practitioners alike. A broad range of issues need to be considered when developing, implementing and evaluating interventions for both the intentional and unintentional risky driving behaviours of interest. While a variety of interventions have been historically utilised, including education, enforcement, rehabilitation and incentives, caution is warranted. A multi-faceted approach to improving novice road safety is more likely to be effective, and new and existing countermeasures should capitalise on the potential of parents, peers and Police to be a positive influence upon the risky behaviour of young novice drivers. However, the efficacy of some interventions remains undetermined at this time. Notwithstanding this caveat, countermeasures such as augmenting and strengthening Queensland's GDL program and targeting parents and adolescents particularly warrant further attention. The findings of the research program suggest that Queensland's current-GDL can be strengthened by increasing compliance of young novice drivers with existing conditions and restrictions. The rates of speeding reported by the young Learner driver are particularly alarming for a number of reasons. The Learner is inexperienced in driving, and travelling in excess of speed limits places them at greater risk as they are also inexperienced in detecting and responding appropriately to driving hazards. In addition, the Learner period should provide the foundation for a safe lifetime driving career, enabling the development and reinforcement of non-risky driving habits. Learners who sped reported speeding by greater margins, and at greater frequencies, when they were able to drive independently. Other strategies could also be considered to enhance Queensland's GDL program, addressing both the pre-Licence adolescent and their parents. Options that warrant further investigation to determine their likely effectiveness include screening and treatment of novice drivers by mental health professionals and/or medical practitioners; and general social skills training. Considering the self-reported pre-licence driving of the young novice driver, targeted education of parents may need to occur before their child obtains a Learner licence. It is noteworthy that those participants who reported risky driving during the Learner phase also were more likely to report risky driving behaviour during the Provisional phase; therefore it appears vital that the development of safe driving habits is encouraged from the beginning of the novice period. General education of parents and young novice drivers should inform them of the considerably-increased likelihood of risky driving behaviour, crashes and offences associated with having unlimited access to a vehicle in the early stages of intermediate licensure. Importantly, parents frequently purchase the car that is used by the Provisional driver, who typically lives at home with their parents, and therefore parents are ideally positioned to monitor the journeys of their young novice driver during this early stage of independent driving. Parents are pivotal in the development of their driving child: they are models who are imitated and are sources of attitudes, expectancies, rewards and punishments; and they provide the most driving instruction for the Learner. High rates of self-reported speeding by Learners suggests that GDL programs specifically consider the nature of supervision during the Learner period, encouraging supervisors to be vigilant to compliance with general and GDL-specific road rules, and especially driving in excess of speed limit. Attitudes towards driving are formed before the adolescent reaches the age when they can be legally licensed. Young novice drivers with risky personal attitudes towards driving reported more risky driving behaviour, suggesting that countermeasures should target such attitudes and that such interventions might be implemented before the adolescent is licensed. The risky behaviours and attitudes of friends were also found to be influential, and given that young novice drivers tend to carry their friends as their passengers, a group intervention such as provided in a school class context may prove more effective. Social skills interventions that encourage the novice to resist the negative influences of their friends and their peer passengers, and to not imitate the risky driving behaviour of their friends, may also be effective. The punishments and rewards anticipated from and administered by friends were also found to influence the self-reported risky behaviour of the young novice driver; therefore young persons could be encouraged to sanction the risky, and to reward the non-risky, driving of their novice friends. Adolescent health programs and related initiatives need to more specifically consider the risks associated with driving. Young novice drivers are also adolescents, a developmental period associated with depression and anxiety. Depression, anxiety, and sensation seeking propensity were found to be predictive of risky driving; therefore interventions targeting psychological distress, whilst discouraging the expression of sensation seeking propensity whilst driving, warrant development and trialing. In addition, given that reward sensitivity was also predictive, a scheme which rewards novice drivers for safe driving behaviour - rather than rewarding the novice through emotional and instrumental rewards for risky driving behaviour - requires further investigation. The Police were also influential in the risky driving behaviour of young novices. Young novice drivers who had been detected for an offence, and then avoided punishment, reacted differentially, with some drivers appearing to become less risky after the encounter, whilst for others their risky behaviour appeared to be reinforced and therefore was more likely to be performed again. Such drivers saw t

Estimating the effects of ambient temperature on mortality : methodological challenges and proposed solutions

The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.

Attitudes of future special education teachers toward gifted students and their education

Saudi Arabian education is undergoing substantial reform in the context of a nation transitioning from a resource-rich economy to a knowledge economy. Gifted students are important human resources for such developing countries. However, there are some concerns emanating from the international literature that gifted students have been neglected in many schools due to teachers’ attitudes toward them. The literature shows that future teachers also hold similar negative attitudes, especially those in Special Education courses who, as practicing teachers, are often responsible for supporting the gifted education process. The purpose of this study was to explore whether these attitudes are held by future special education teachers in Saudi Arabia, and how the standard gifted education course, delivered as part of their program, impacts on their attitudes toward gifted students. The study was strongly influenced by the Theory of Reasoned Action (Ajzen, 1980, 2012) and the Theory of Personal Knowledge (Polanyi, 1966), which both suggest that attitudes are related to people’s (i.e. teachers’) beliefs. A mixed methods design was used to collect quantitative and qualitative data from a cohort of students enrolled in a teacher education program at a Saudi Arabian university. The program was designed for students majoring in special education. The quantitative component of the study involved an investigation of a cohort of future special education teachers taking a semester-long course in gifted education. The data were primarily sourced from a standard questionnaire instrument modified in the Arabic language, and supplemented with questions that probed the future teachers’ attitudes toward gifted children. The participants, 90 special education future teachers, were enrolled in an introductory course about gifted education. The questionnaire contained 34 items from the "Opinions about the Gifted and Their Education" (Gagné, 1991) questionnaire, utilising a five-point Likert scale. The quantitative data were analysed through the use of descriptive statistics, Spearman correlation Coefficients, Paired Samples t-test, and Multiple Linear Regression. The qualitative component focussed on eight participants enrolled in the gifted education course. The primary source of the qualitative data was informed by individual semi-structured interviews with each of these participants. The findings, based on both the quantitative and qualitative data, indicated that the majority of future special education teachers held, overall, slightly positive attitudes toward gifted students and their education. However, the participants were resistant to offering special services for the gifted within the regular classroom, even when a comparison was made on equity grounds with disabled students. While the participants held ambivalent attitudes toward ability grouping, their attitudes were positive toward grade acceleration. Further, the majority agreed that gifted students are likely to be rejected by their teachers. Despite such judgments, they considered the gifted to be a valuable resource for Saudi society. Differences within the cohort were found when two variables emerged as potential predictors of attitude: age, experience, and participants’ hometown. The younger (under 25 years old) future special education teachers, with no internship or school practice experience, held more positive attitudes toward the gifted students, with respect to their general needs, than did the older participants with previous school experiences. Additionally, participants from a rural region were more resistant toward gifted education than future teachers from urban areas. The findings also indicated that the attitudes of most of the participants were significantly improved, as a result of the course, toward ability grouping such as special classes and schools, but remained highly concerned about differentiation within regular classrooms with either elitism or time pressure. From the findings, it can be confirmed that a lectured-based course can serve as a starting point from which to focus future teachers’ attention on the varied needs of the gifted, and as a conduit for learning about special services for the gifted. However, by itself, the course appears to have minimal influence on attitudes toward differentiation. As a consequence, there is merit in its redevelopment, and the incorporation of more practical opportunities for future teachers to experience the teaching of the gifted.

A systematic approach for selecting lean strategies and assessing leanness in manufacturing organizations

Lean strategies have been developed to eliminate or reduce manufacturing waste and thus improve operational efficiency in manufacturing processes. However, implementing lean strategies requires a large amount of resources and, in practice, manufacturers encounter difficulties in selecting appropriate lean strategies within their resource constraints. There is currently no systematic methodology available for selecting appropriate lean strategies within a manufacturer's resource constraints. In the lean transformation process, it is also critical to measure the current and desired leanness levels in order to clearly evaluate lean implementation efforts. Despite the fact that many lean strategies are utilized to reduce or eliminate manufacturing waste, little effort has been directed towards properly assessing the leanness of manufacturing organizations. In practice, a single or specific group of metrics (either qualitative or quantitative) will only partially measure the overall leanness. Existing leanness assessment methodologies do not offer a comprehensive evaluation method, integrating both quantitative and qualitative lean measures into a single quantitative value for measuring the overall leanness of an organization. This research aims to develop mathematical models and a systematic methodology for selecting appropriate lean strategies and evaluating the leanness levels in manufacturing organizations. Mathematical models were formulated and a methodology was developed for selecting appropriate lean strategies within manufacturers' limited amount of available resources to reduce their identified wastes. A leanness assessment model was developed by using the fuzzy concept to assess the leanness level and to recommend an optimum leanness value for a manufacturing organization. In the proposed leanness assessment model, both quantitative and qualitative input factors have been taken into account. Based on program developed in MATLAB and C#, a decision support tool (DST) was developed for decision makers to select lean strategies and evaluate the leanness value based on the proposed models and methodology hence sustain the lean implementation efforts. A case study was conducted to demonstrate the effectiveness of these proposed models and methodology. Case study results suggested that out of 10 wastes identified, the case organization (ABC Limited) is able to improve a maximum of six wastes from the selected workstation within their resource limitations. The selected wastes are: unnecessary motion, setup time, unnecessary transportation, inappropriate processing, work in process and raw material inventory and suggested lean strategies are: 5S, Just-In-Time, Kanban System, the Visual Management System (VMS), Cellular Manufacturing, Standard Work Process using method-time measurement (MTM), and Single Minute Exchange of Die (SMED). From the suggested lean strategies, the impact of 5S was demonstrated by measuring the leanness level of two different situations in ABC. After that, MTM was suggested as a standard work process for further improvement of the current leanness value. The initial status of the organization showed a leanness value of 0.12. By applying 5S, the leanness level significantly improved to reach 0.19 and the simulation of MTM as a standard work method shows the leanness value could be improved to 0.31. The optimum leanness value of ABC was calculated to be 0.64. These leanness values provided a quantitative indication of the impacts of improvement initiatives in terms of the overall leanness level to the case organization. Sensitivity analsysis and a t-test were also performed to validate the model proposed. This research advances the current knowledge base by developing mathematical models and methodologies to overcome lean strategy selection and leanness assessment problems. By selecting appropriate lean strategies, a manufacturer can better prioritize implementation efforts and resources to maximize the benefits of implementing lean strategies in their organization. The leanness index is used to evaluate an organization's current (before lean implementation) leanness state against the state after lean implementation and to establish benchmarking (the optimum leanness state). Hence, this research provides a continuous improvement tool for a lean manufacturing organization.

A cross-discipline and collaborative approach to identifying the predictors of environmentally friendly and health protective behaviour

Background. As a society, our interaction with the environment is having a negative impact on human health. For example, an increase in car use for short trips, over walking or cycling, has contributed to an increase in obesity, diabetes and poor heart health and also contributes to pollution, which is associated with asthma and other respiratory diseases. In order to change the nature of that interaction, to be more positive and healthy, it is recommended that individuals adopt a range of environmentally friendly behaviours (such as walking for transport and reducing the use of plastics). Effective interventions aimed at increasing such behaviours will need to be evidence based and there is a need for the rapid communication of information from the point of research, into policy and practice. Further, a number of health disciplines, including psychology and public health, share a common mission to promote health and well-being. Therefore, the objective of this project is to take a cross-discipline and collaborative approach to reveal psychological mechanisms driving environmentally friendly behaviour. This objective is further divided into three broad aims, the first of which is to take a cross-discipline and collaborative approach to research. The second aim is to explore and identify the salient beliefs which most strongly predict environmentally friendly behaviour. The third aim is to build an augmented model to explain environmentally friendly behaviour. The thesis builds on the understanding that an interdisciplinary collaborative approach will facilitate the rapid transfer of knowledge to inform behaviour change interventions. Methods. The application of this approach involved two surveys which explored the psycho-social predictors of environmentally friendly behaviour. Following a qualitative pilot study, and in collaboration with an expert panel comprising academics, industry professionals and government representatives, a self-administered, Theory of Planned Behaviour (TPB) based, mail survey was distributed to a random sample of 3000 residents of Brisbane and Moreton Bay Region (Queensland, Australia). This survey explored specific beliefs including attitudes, norms, perceived control, intention and behaviour, as well as environmental altruism and green identity, in relation to walking for transport and switching off lights when not in use. Following analysis of the mail survey data and based on feedback from participants and key stakeholders, an internet survey was employed (N=451) to explore two additional behaviours, switching off appliances at the wall when not in use, and shopping with reusable bags. This work is presented as a series of interrelated publications which address each of the research aims. Presentation of Findings. Chapter five of this thesis consists of a published paper which addresses the first aim of the research and outlines the collaborative and multidisciplinary approach employed in the mail survey. The paper argued that forging alliances with those who are in a position to immediately utilise the findings of research has the potential to improve the quality and timely communication of research. Illustrating this timely communication, Chapter six comprises a report presented to Moreton Bay Regional Council (MBRC). This report addresses aim's one and two. The report contains a summary of participation in a range of environmentally friendly behaviours and identifies the beliefs which most strongly predicted walking for transport and switching off lights (from the mail survey). These salient beliefs were then recommended as targets for interventions and included: participants believing that they might save money; that their neighbours also switch off lights; that it would be inconvenient to walk for transport and that their closest friend also walks for transport. Chapter seven also addresses the second aim and presents a published conference paper in which the salient beliefs predicting the four specified behaviours (from both surveys) are identified and potential applications for intervention are discussed. Again, a range of TPB based beliefs, including descriptive normative beliefs, were predictive of environmentally friendly behaviour. This paper was also provided to MBRC, along with recommendations for applying the findings. For example, as descriptive normative beliefs were consistently correlated with environmentally friendly behaviour, local councils could engage in marketing and interventions (workshops, letter box drops, internet promotions) which encourage parents and friends to model, rather than simply encourage, environmentally friendly behaviour. The final two papers, presented in Chapters eight and nine, addresses the third aim of the project. These papers each present two behaviours together to inform a TPB based theoretical model with which to predict environmentally friendly behaviour. A generalised model is presented, which is found to predict the four specific behaviours under investigation. The role of demographics was explored across each of the behaviour specific models. It was found that some behaviour's differ by age, gender, income or education. In particular, adjusted models predicted more of the variance in walking for transport amongst younger participants and females. Adjusted models predicted more variance in switching off lights amongst those with a bachelor degree or higher and predicted more variance in switching off appliances amongst those on a higher income. Adjusted models predicted more variance in shopping with reusable bags for males, people 40 years or older, those on a higher income and those with a bachelor degree or higher. However, model structure and general predictability was relatively consistent overall. The models provide a general theoretical framework from which to better understand the motives and predictors of environmentally friendly behaviour. Conclusion. This research has provided an example of the benefits of a collaborative interdisciplinary approach. It has identified a number of salient beliefs which can be targeted for social marketing campaigns and educational initiatives; and these findings, along with recommendations, have been passed on to a local council to be used as part of their ongoing community engagement programs. Finally, the research has informed a practical model, as well as behaviour specific models, for predicting sustainable living behaviours. Such models can highlight important core constructs from which targeted interventions can be designed. Therefore, this research represents an important step in undertaking collaborative approaches to improving population health through human-environment interactions.

Characteristics of chemotherapy practice in rural and remote area health facilities in Queensland

Objective The overall objective of this study was to document the nature of the chemotherapy nursing practice of rural and remote area nurses in Queensland. Design A questionnaire survey that elicited descriptive quantitative and qualitative data. Setting Forty-seven rural and remote area health facilities in Queensland involved in the administration of chemotherapy. Subjects Sixty-seven Queensland rural and remote area nurses involved in the administration of cytotoxic drugs. Main outcome measures: Characteristics of chemotherapy practice including context of practice, amount and type of chemotherapy administered, logistical problems, level of support from referral centres, policies and procedures, safety issues. Results The results indicate that the risks to nursing staff and the potential for poor patient outcomes are higher than in specialist chemotherapy facilities. This is largely due to the human and material resource constraints characteristic of rural practice. These include a lack of understanding on the part of metropolitan-based health departments and the specialist cancer centres that refer patients to rural areas of the constraints that may adversely influence patient outcomes. Conclusions It is essential that steps are taken to ensure that rural and remote area cancer patients have equitable access to safe and competent chemotherapy care delivered in their choice of context, and the results of this study provide guidance on ways that this can be achieved.

Lattice-free descriptions of collective motion with crowding and adhesion

Cell-to-cell adhesion is an important aspect of malignant spreading that is often observed in images from the experimental cell biology literature. Since cell-to-cell adhesion plays an important role in controlling the movement of individual malignant cells, it is likely that cell-to-cell adhesion also influences the spatial spreading of populations of such cells. Therefore, it is important for us to develop biologically realistic simulation tools that can mimic the key features of such collective spreading processes to improve our understanding of how cell-to-cell adhesion influences the spreading of cell populations. Previous models of collective cell spreading with adhesion have used lattice-based random walk frameworks which may lead to unrealistic results, since the agents in the random walk simulations always move across an artificial underlying lattice structure. This is particularly problematic in high-density regions where it is clear that agents in the random walk align along the underlying lattice, whereas no such regular alignment is ever observed experimentally. To address these limitations, we present a lattice-free model of collective cell migration that explicitly incorporates crowding and adhesion. We derive a partial differential equation description of the discrete process and show that averaged simulation results compare very well with numerical solutions of the partial differential equation.

Visualization of predictive distributions for discrete spatial-temporal log Cox processes approximated with MCMC

An important aspect of decision support systems involves applying sophisticated and flexible statistical models to real datasets and communicating these results to decision makers in interpretable ways. An important class of problem is the modelling of incidence such as fire, disease etc. Models of incidence known as point processes or Cox processes are particularly challenging as they are ‘doubly stochastic’ i.e. obtaining the probability mass function of incidents requires two integrals to be evaluated. Existing approaches to the problem either use simple models that obtain predictions using plug-in point estimates and do not distinguish between Cox processes and density estimation but do use sophisticated 3D visualization for interpretation. Alternatively other work employs sophisticated non-parametric Bayesian Cox process models, but do not use visualization to render interpretable complex spatial temporal forecasts. The contribution here is to fill this gap by inferring predictive distributions of Gaussian-log Cox processes and rendering them using state of the art 3D visualization techniques. This requires performing inference on an approximation of the model on a discretized grid of large scale and adapting an existing spatial-diurnal kernel to the log Gaussian Cox process context.

Quality Information System: Investigating the conception, role, models and suggesting conceptual and hierarchal models

In the current business world which companies’ competition is very compact in the business arena, quality in manufacturing and providing products and services can be considered as a means of seeking excellence and success of companies in this competition arena. Entering the era of e-commerce and emergence of new production systems and new organizational structures, traditional management and quality assurance systems have been challenged. Consequently, quality information system has been gained a special seat as one of the new tools of quality management. In this paper, quality information system has been studied with a review of the literature of the quality information system, and the role and position of quality Information System (QIS) among other information systems of a organization is investigated. The quality Information system models are analyzed and by analyzing and assessing presented models in quality information system a conceptual and hierarchical model of quality information system is suggested and studied. As a case study the hierarchical model of quality information system is developed by evaluating hierarchical models presented in the field of quality information system based on the Shetabkar Co.

Are in vitro estimates of cell diffusivity and cell proliferation rate sensitive to assay geometry?

Cells respond to various biochemical and physical cues during wound–healing and tumour progression. In vitro assays used to study these processes are typically conducted in one particular geometry and it is unclear how the assay geometry affects the capacity of cell populations to spread, or whether the relevant mechanisms, such as cell motility and cell proliferation, are somehow sensitive to the geometry of the assay. In this work we use a circular barrier assay to characterise the spreading of cell populations in two different geometries. Assay 1 describes a tumour–like geometry where a cell population spreads outwards into an open space. Assay 2 describes a wound–like geometry where a cell population spreads inwards to close a void. We use a combination of discrete and continuum mathematical models and automated image processing methods to obtain independent estimates of the effective cell diffusivity, D, and the effective cell proliferation rate, λ. Using our parameterised mathematical model we confirm that our estimates of D and λ accurately predict the time–evolution of the location of the leading edge and the cell density profiles for both assay 1 and assay 2. Our work suggests that the effective cell diffusivity is up to 50% lower for assay 2 compared to assay 1, whereas the effective cell proliferation rate is up to 30% lower for assay 2 compared to assay 1.

Understanding and impacting the practice of business process management

This presentation will explore how BPM research can seamlessly combine the academic requirement of rigor with the aim to impact the practice of Business Process Management. After a brief introduction into the research agendas as they are perceived by different BPM communities, two research projects will be discussed that illustrate how empirically-informed quantitative and qualitative research, combined with design science, can lead to outcomes that BPM practitioners are willing to adopt. The first project studies the practice of process modeling using Information Systems theory, and demonstrates how a better understanding of this practice can inform the design of modeling notations and methods. The second project studies the adoption of process management within organizations, and leads to models of how organizations can incrementally transition to greater levels of BPM maturity. The presentation will conclude with recommendations for how the BPM research and practitioner communities can increasingly benefit from each other.

Comparing different approach and avoidance models of learning and personality in the prediction of work, university, and leadership outcomes

Jackson (2005) developed a hybrid model of personality and learning, known as the learning styles profiler (LSP) which was designed to span biological, socio-cognitive, and experiential research foci of personality and learning research. The hybrid model argues that functional and dysfunctional learning outcomes can be best understood in terms of how cognitions and experiences control, discipline, and re-express the biologically based scale of sensation-seeking. In two studies with part-time workers undertaking tertiary education (N equals 137 and 58), established models of approach and avoidance from each of the three different research foci were compared with Jackson's hybrid model in their predictiveness of leadership, work, and university outcomes using self-report and supervisor ratings. Results showed that the hybrid model was generally optimal and, as hypothesized, that goal orientation was a mediator of sensation-seeking on outcomes (work performance, university performance, leader behaviours, and counterproductive work behaviour). Our studies suggest that the hybrid model has considerable promise as a predictor of work and educational outcomes as well as dysfunctional outcomes.