A further exploration of sensation seeking propensity, reward sensitivity, depression, anxiety, and the risky behaviour of young novice drivers in a structural equation model

Young novice drivers constitute a major public health concern due to the number of crashes in which they are involved, and the resultant injuries and fatalities. Previous research suggests psychological traits (reward sensitivity, sensation seeking propensity), and psychological states (anxiety, depression) influence their risky behaviour. The relationships between gender, anxiety, depression, reward sensitivity, sensation seeking propensity and risky driving are explored. Participants (390 intermediate drivers, 17-25 years) completed two online surveys at a six month interval. Surveys comprised sociodemographics, Brief Sensation Seeking Scale, Kessler’s Psychological Distress Scale, an abridged Sensitivity to Reward Questionnaire, and risky driving behaviour was measured by the Behaviour of Young Novice Drivers Scale. Structural equation modelling revealed anxiety, reward sensitivity and sensation seeking propensity predicted risky driving. Gender was a moderator, with only reward sensitivity predicting risky driving for males. Future interventions which consider the role of rewards, sensation seeking, and mental health may contribute to improved road safety for younger and older road users alike.

Ureaplasma parvum : understanding the complexities of intra-amniotic infection in an ovine model

The human Ureaplasma species are the most frequently isolated bacteria from the upper genital tract of pregnant women and can cause clinically asymptomatic, intra-uterine infections, which are difficult to treat with antimicrobials. Ureaplasma infection of the upper genital tract during pregnancy has been associated with numerous adverse outcomes including preterm birth, chorioamnionitis and neonatal respiratory diseases. The mechanisms by which ureaplasmas are able to chronically colonise the amniotic fluid and avoid eradication by (i) the host immune response and (ii) maternally-administered antimicrobials, remain virtually unexplored. To address this gap within the literature, this study investigated potential mechanisms by which ureaplasmas are able to cause chronic, intra-amniotic infections in an established ovine model. In this PhD program of research the effectiveness of standard, maternal erythromycin for the treatment of chronic, intra-amniotic ureaplasma infections was evaluated. At 55 days of gestation pregnant ewes received an intra-amniotic injection of either: a clinical Ureaplasma parvum serovar 3 isolate that was sensitive to macrolide antibiotics (n = 16); or 10B medium (n = 16). At 100 days of gestation, ewes were then randomised to receive either maternal erythromycin treatment (30 mg/kg/day for four days) or no treatment. Ureaplasmas were isolated from amniotic fluid, chorioamnion, umbilical cord and fetal lung specimens, which were collected at the time of preterm delivery of the fetus (125 days of gestation). Surprisingly, the numbers of ureaplasmas colonising the amniotic fluid and fetal tissues were not different between experimentally-infected animals that received erythromycin treatment or infected animals that did not receive treatment (p > 0.05), nor were there any differences in fetal inflammation and histological chorioamnionitis between these groups (p > 0.05). These data demonstrate the inability of maternal erythromycin to eradicate intra-uterine ureaplasma infections. Erythromycin was detected in the amniotic fluid of animals that received antimicrobial treatment (but not in those that did not receive treatment) by liquid chromatography-mass spectrometry; however, the concentrations were below therapeutic levels (<10 – 76 ng/mL). These findings indicate that the ineffectiveness of standard, maternal erythromycin treatment of intra-amniotic ureaplasma infections may be due to the poor placental transfer of this drug. Subsequently, the phenotypic and genotypic characteristics of ureaplasmas isolated from the amniotic fluid and chorioamnion of pregnant sheep after chronic, intra-amniotic infection and low-level exposure to erythromycin were investigated. At 55 days of gestation twelve pregnant ewes received an intra-amniotic injection of a clinical U. parvum serovar 3 isolate, which was sensitive to macrolide antibiotics. At 100 days of gestation, ewes received standard maternal erythromycin treatment (30 mg/kg/day for four days, n = 6) or saline (n = 6). Preterm fetuses were surgically delivered at 125 days of gestation and ureaplasmas were cultured from the amniotic fluid and the chorioamnion. The minimum inhibitory concentrations (MICs) of erythromycin, azithromycin and roxithromycin were determined for cultured ureaplasma isolates, and antimicrobial susceptibilities were different between ureaplasmas isolated from the amniotic fluid (MIC range = 0.08 – 1.0 mg/L) and chorioamnion (MIC range = 0.06 – 5.33 mg/L). However, the increased resistance to macrolide antibiotics observed in chorioamnion ureaplasma isolates occurred independently of exposure to erythromycin in vivo. Remarkably, domain V of the 23S ribosomal RNA gene (which is the target site of macrolide antimicrobials) of chorioamnion ureaplasmas demonstrated significant variability (125 polymorphisms out of 422 sequenced nucleotides, 29.6%) when compared to the amniotic fluid ureaplasma isolates and the inoculum strain. This sequence variability did not occur as a consequence of exposure to erythromycin, as the nucleotide substitutions were identical between chorioamnion ureaplasmas isolated from different animals, including those that did not receive erythromycin treatment. We propose that these mosaic-like 23S ribosomal RNA gene sequences may represent gene fragments transferred via horizontal gene transfer. The significant differences observed in (i) susceptibility to macrolide antimicrobials and (ii) 23S ribosomal RNA sequences of ureaplasmas isolated from the amniotic fluid and chorioamnion suggests that the anatomical site from which they were isolated may exert selective pressures that alter the socio-microbiological structure of the bacterial population, by selecting for genetic changes and altered antimicrobial susceptibility profiles. The final experiment for this PhD examined antigenic size variation of the multiple banded antigen (MBA, a surface-exposed lipoprotein and predicted ureaplasmal virulence factor) in chronic, intra-amniotic ureaplasma infections. Previously defined ‘virulent-derived’ and ‘avirulent-derived’ clonal U. parvum serovar 6 isolates (each expressing a single MBA protein) were injected into the amniotic fluid of pregnant ewes (n = 20) at 55 days of gestation, and amniotic fluid was collected by amniocentesis every two weeks until the time of near-term delivery of the fetus (at 140 days of gestation). Both the avirulent and virulent clonal ureaplasma strains generated MBA size variants (ranging in size from 32 – 170 kDa) within the amniotic fluid of pregnant ewes. The mean number of MBA size variants produced within the amniotic fluid was not different between the virulent (mean = 4.2 MBA variants) and avirulent (mean = 4.6 MBA variants) ureaplasma strains (p = 0.87). Intra-amniotic infection with the virulent strain was significantly associated with the presence of meconium-stained amniotic fluid (p = 0.01), which is an indicator of fetal distress in utero. However, the severity of histological chorioamnionitis was not different between the avirulent and virulent groups. We demonstrated that ureaplasmas were able to persist within the amniotic fluid of pregnant sheep for 85 days, despite the host mounting an innate and adaptive immune response. Pro-inflammatory cytokines (interleukin (IL)-1â, IL-6 and IL-8) were elevated within the chorioamnion tissue of pregnant sheep from both the avirulent and virulent treatment groups, and this was significantly associated with the production of anti-ureaplasma IgG antibodies within maternal sera (p < 0.05). These findings suggested that the inability of the host immune response to eradicate ureaplasmas from the amniotic cavity may be due to continual size variation of MBA surface-exposed epitopes. Taken together, these data confirm that ureaplasmas are able to cause long-term in utero infections in a sheep model, despite standard antimicrobial treatment and the development of a host immune response. The overall findings of this PhD project suggest that ureaplasmas are able to cause chronic, intra-amniotic infections due to (i) the limited placental transfer of erythromycin, which prevents the accumulation of therapeutic concentrations within the amniotic fluid; (ii) the ability of ureaplasmas to undergo rapid selection and genetic variation in vivo, resulting in ureaplasma isolates with variable MICs to macrolide antimicrobials colonising the amniotic fluid and chorioamnion; and (iii) antigenic size variation of the MBA, which may prevent eradication of ureaplasmas by the host immune response and account for differences in neonatal outcomes. The outcomes of this program of study have improved our understanding of the biology and pathogenesis of this highly adapted microorganism.

Investigating the potential value of individual parameters of histological grading systems in a sheep model of cartilage damage : the modified Mankin method

A total histological grade does not necessarily distinguish between different manifestations of cartilage damage or degeneration. An accurate and reliable histological assessment method is required to separate normal and pathological tissue within a joint during treatment of degenerative joint conditions and to sub-classify the latter in meaningful ways. The Modified Mankin method may be adaptable for this purpose. We investigated how much detail may be lost by assigning one composite score/grade to represent different degenerative components of the osteoarthritic condition. We used four ovine injury models (sham surgery, anterior cruciate ligament/medial collateral ligament instability, simulated anatomic anterior cruciate ligament reconstruction and meniscal removal) to induce different degrees and potentially 'types' (mechanisms) of osteoarthritis. Articular cartilage was systematically harvested, prepared for histological examination and graded in a blinded fashion using a Modified Mankin grading method. Results showed that the possible permutations of cartilage damage were significant and far more varied than the current intended use that histological grading systems allow. Of 1352 cartilage specimens graded, 234 different manifestations of potential histological damage were observed across 23 potential individual grades of the Modified Mankin grading method. The results presented here show that current composite histological grading may contain additional information that could potentially discern different stages or mechanisms of cartilage damage and degeneration in a sheep model. This approach may be applicable to other grading systems.

Relative entropy rate based model selection for linear hybrid system filters of uncertain nonlinear systems

Hybrid system representations have been exploited in a number of challenging modelling situations, including situations where the original nonlinear dynamics are too complex (or too imprecisely known) to be directly filtered. Unfortunately, the question of how to best design suitable hybrid system models has not yet been fully addressed, particularly in the situations involving model uncertainty. This paper proposes a novel joint state-measurement relative entropy rate based approach for design of hybrid system filters in the presence of (parameterised) model uncertainty. We also present a design approach suitable for suboptimal hybrid system filters. The benefits of our proposed approaches are illustrated through design examples and simulation studies.

An improved model of tumour-immune system interactions

The immune system plays an important role in defending the body against tumours and other threats. Currently, mechanisms involved in immune system interactions with tumour cells are not fully understood. Here we develop a mathematical tool that can be used in aiding to address this shortfall in understanding. This paper de- scribes a hybrid cellular automata model of the interaction between a growing tumour and cells of the innate and specific immune system including the effects of chemokines that builds on previous models of tumour-immune system interactions. In particular, the model is focused on the response of immune cells to tumour cells and how the dynamics of the tumour cells change due to the immune system of the host. We present results and predictions of in silico experiments including simulations of Kaplan-Meier survival-like curves.

Stigmergy in Web 2.0 : a model for site dynamics

Building Web 2.0 sites does not necessarily ensure the success of the site. We aim to better understand what improves the success of a site by drawing insight from biologically inspired design patterns. Web 2.0 sites provide a mechanism for human interaction enabling powerful intercommunication between massive volumes of users. Early Web 2.0 site providers that were previously dominant are being succeeded by newer sites providing innovative social interaction mechanisms. Understanding what site traits contribute to this success drives research into Web sites mechanics using models to describe the associated social networking behaviour. Some of these models attempt to show how the volume of users provides a self-organising and self-contextualisation of content. One model describing coordinated environments is called stigmergy, a term originally describing coordinated insect behavior. This paper explores how exploiting stigmergy can provide a valuable mechanism for identifying and analysing online user behavior specifically when considering that user freedom of choice is restricted by the provided web site functionality. This will aid our building better collaborative Web sites improving the collaborative processes.

IL-18 inhibits growth of murine orthotopic prostate carcinomas via both adaptive and innate immune mechanisms

Interleukin(IL)-18 is a pleiotrophic cytokine with functions in immune modulation, angiogenesis and bone metabolism. In this study, the potential of IL-18 as an immunotherapy for prostate cancer (PCa) was examined using the murine model of prostate carcinoma, RM1 and a bone metastatic variant RM1(BM)/B4H7-luc. RM1 and RM1(BM)/B4H7-luc cells were stably transfected to express bioactive IL-18. These cells were implanted into syngeneic immunocompetent mice, with or without an IL-18-neutralising antibody (αIL-18, SK113AE4). IL-18 significantly inhibited the growth of both subcutaneous and orthotopic RM1 tumors and the IL-18 neutralizing antibody abrogated the tumor growth-inhibition. In vivo neutralization of interferon-gamma (IFN-γ) completely eliminated the anti-tumor effects of IL-18 confirming an essential role of IFN-γ as a down-stream mediator of the anti-tumor activity of IL-18. Tumors from mice in which IL-18 and/or IFN-γ was neutralized contained significantly fewer CD4+ and CD8+ T cells than those with functional IL-18. The essential role of adaptive immunity was demonstrated as tumors grew more rapidly in RAG1−/− mice or in mice depleted of CD4+ and/or CD8+ cells than in normal mice. The tumors in RAG1−/− mice were also significantly smaller when IL-18 was present, indicating that innate immune mechanisms are involved. IL-18 also induced an increase in tumor infiltration of macrophages and neutrophils but not NK cells. In other experiments, direct injection of recombinant IL-18 into established tumors also inhibited tumor growth, which was associated with an increase in intratumoral macrophages, but not T cells. These results suggest that local IL-18 in the tumor environment can significantly potentiate anti-tumor immunity in the prostate and clearly demonstrate that this effect is mediated by innate and adaptive immune mechanisms.

Application of a human bone engineering platform to an in vitro and in vivo breast cancer metastasis model

Breast cancer in its advanced stage has a high predilection to the skeleton. Currently, treatment options of breast cancer-related bone metastasis are restricted to only palliative therapeutic modalities. This is due to the fact that mechanisms regarding the breast cancer celI-bone colonisation as well as the interactions of breast cancer cells with the bone microenvironment are not fully understood, yet. This might be explained through a lack of appropriate in vitro and in vivo models that are currently addressing the above mentioned issue. Hence the hypothesis that the translation of a bone tissue engineering platform could lead to improved and more physiological in vitro and in vivo model systems in order to investigate breast cancer related bone colonisation was embraced in this PhD thesis. Therefore the first objective was to develop an in vitro model system that mimics human mineralised bone matrix to the highest possible extent to examine the specific biological question, how the human bone matrix influences breast cancer cell behaviour. Thus, primary human osteoblasts were isolated from human bone and cultured under osteogenic conditions. Upon ammonium hydroxide treatment, a cell-free intact mineralised human bone matrix was left behind. Analyses revealed a similar protein and mineral composition of the decellularised osteoblast matrix to human bone. Seeding of a panel of breast cancer cells onto the bone mimicking matrix as well as reference substrates like standard tissue culture plastic and collagen coated tissue culture plastic revealed substrate specific differences of cellular behaviour. Analyses of attachment, alignment, migration, proliferation, invasion, as well as downstream signalling pathways showed that these cellular properties were influenced through the osteoblast matrix. The second objective of this PhD project was the development of a human ectopic bone model in NOD/SCID mice using medical grade polycaprolactone tricalcium phosphate (mPCL-TCP) scaffold. Human osteoblasts and mesenchymal stem cells were seeded onto an mPCL-TCP scaffold, fabricated using a fused deposition modelling technique. After subcutaneous implantation in conjunction with the bone morphogenetic protein 7, limited bone formation was observed due to the mechanical properties of the applied scaffold and restricted integration into the soft tissue of flank of NOD/SCID mice. Thus, a different scaffold fabrication technique was chosen using the same polymer. Electrospun tubular scaffolds were seeded with human osteoblasts, as they showed previously the highest amount of bone formation and implanted into the flanks of NOD/SCID mice. Ectopic bone formation with sufficient vascularisation could be observed. After implantation of breast cancer cells using a polyethylene glycol hydrogel in close proximity to the newly formed bone, macroscopic communication between the newly formed bone and the tumour could be observed. Taken together, this PhD project showed that bone tissue engineering platforms could be used to develop an in vitro and in vivo model system to study cancer cell colonisation in the bone microenvironment.

Practical stability of approximating discrete-time filters with respect to model mismatch

This paper establishes practical stability results for an important range of approximate discrete-time filtering problems involving mismatch between the true system and the approximating filter model. Practical stability is established in the sense of an asymptotic bound on the amount of bias introduced by the model approximation. Our analysis applies to a wide range of estimation problems and justifies the common practice of approximating intractable infinite dimensional nonlinear filters by simpler computationally tractable filters.

Articulation in property programs : an international multi-campus tertiary model

This paper will present program developers and institutional administrators with a program delivery model suitable for cross cultural international delivery developing students from industry through to master’s level tertiary qualifications. The model was designed to meet the needs of property professionals from an industry where technical qualifications are the norm and tertiary qualifications are emerging. A further need was to develop and deliver a program that enhanced the University’s current program profile in both the domestic and international arenas. Early identification of international educational partners, industry need and the ability to service the program were vital to the successful development of Master of Property program. The educational foundations of the program rest in educational partners, local tutorial support, international course management, cultural awareness of and in content, online communication fora, with a delivery focus on problem-based learning, self-directed study, teamwork and the development of a global understanding and awareness of the international property markets. In enrolling students from a diverse cultural background with technical qualifications and/or extensive work experience there are a number of educational barriers to be overcome for all students to successfully progress and complete the program. These barriers disappear when the following mechanisms are employed: individual student pathways, tutorial support by qualified peers, enculturation into tertiary practice, assessment tasks that recognise cultural norms and values, and finally that value is placed on the experiential knowledge, cultural practices and belief systems of the students.

A psychosocial model of young adult passengers’ intervening in unsafe driving of their friends

Young adults are over-represented in motor vehicle crashes and the carrying of same passengers puts them at greater risk of crashing. The current study examined characteristics of the passengers who might play a positive role in reducing friends’ crashes by actively engaging in strategies to protect such friends. A psychosocial theoretical model of prosocial behavior including self-process and contextual cues explained intervening behavior among primarily novice driver college students (n=242) with the exception of the self-process, perspective taking. The results of this study provide support for countermeasure development that accounts for the positive role of peers to increase road safety, and reduce the incidence of crashes, among young adults.

A study on the effects of routing symbol design on process model comprehension

Process modeling grammars are used to create models of business processes. In this paper, we discuss how different routing symbol designs affect an individual's ability to comprehend process models. We conduct an experiment with 154 students to ascertain which visual design principles influence process model comprehension. Our findings suggest that design principles related to perceptual discriminability and pop out improve comprehension accuracy. Furthermore, semantic transparency and aesthetic design of symbols lower the perceived difficulty of comprehension. Our results inform important principles about notational design of process modeling grammars and the effective use of process modeling in practice.

An integrated educational model for continuing nurse education

Aim This paper reports on the development and evaluation of an integrated clinical learning model to inform ongoing education for surgical nurses. The research aim was to evaluate the effectiveness of implementing a Respiratory Skills Update (ReSKU) education program, in the context of organisational utility, on improving surgical nurses' practice in the area of respiratory assessment. Background Continuous development and integration of technological innovations and research in the healthcare environment mandate the need for continuing education for nurses. Despite an increased worldwide emphasis on this, there is scant empirical evidence of program effectiveness. Methods A quasi experimental pre test, post test non–equivalent control group design evaluated the impact of the ReSKU program on surgical nurses' clinical practice. The 2008 study was conducted in a 400 bed regional referral public hospital and was consistent with contemporary educational approaches using multi-modal, interactive teaching strategies. Findings The study demonstrated statistically significant differences between groups regarding reported use of respiratory skills, three months after ReSKU program attendance. Between group data analysis indicated that the intervention group's reported beliefs and attitudes pertaining to subscale descriptors showed statistically significant differences in three of the six subscales. Conclusion The construct of critical thinking in the clinical context, combined with clinical reasoning and purposeful reflection, was a powerful educational strategy to enhance competency and capability in clinicians.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

Querying a building information model for construction-specific spatial information

The design and construction community has shown increasing interest in adopting building information models (BIMs). The richness of information provided by BIMs has the potential to streamline the design and construction processes by enabling enhanced communication, coordination, automation and analysis. However, there are many challenges in extracting construction-specific information out of BIMs. In most cases, construction practitioners have to manually identify the required information, which is inefficient and prone to error, particularly for complex, large-scale projects. This paper describes the process and methods we have formalized to partially automate the extraction and querying of construction-specific information from a BIM. We describe methods for analyzing a BIM to query for spatial information that is relevant for construction practitioners, and that is typically represented implicitly in a BIM. Our approach integrates ifcXML data and other spatial data to develop a richer model for construction users. We employ custom 2D topological XQuery predicates to answer a variety of spatial queries. The validation results demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.