An indexing model for stormwater quality in the Gold Coast

In the era of climate change sustainable urban development and in particular provision of sustainable urban infrastructure has become a key concept in dealing with environmental challenges. This paper discusses issues affecting stormwater quality and introduces a new indexing model that is to be used in evaluation of the stormwater quality in urban areas. The model has recently been developed and will be tested in a number of pilot projects in the Gold Coast, one of the fastest growing and environmentally challenged cities of Australia.

Biological performance of a polycaprolactone-based scaffold used as fusion cage device in a large animal model of spinal reconstructive surgery

A bioactive and bioresorbable scaffold fabricated from medical grade poly (epsilon-caprolactone) and incorporating 20% beta-tricalcium phosphate (mPCL–TCP) was recently developed for bone regeneration at load bearing sites. In the present study, we aimed to evaluate bone ingrowth into mPCL–TCP in a large animal model of lumbar interbody fusion. Six pigs underwent a 2-level (L3/4; L5/6) anterior lumbar interbody fusion (ALIF) implanted with mPCL–TCP þ 0.6 mg rhBMP-2 as treatment group while four other pigs implanted with autogenous bone graft served as control. Computed tomographic scanning and histology revealed complete defect bridging in all (100%) specimen from the treatment group as early as 3 months. Histological evidence of continuing bone remodeling and maturation was observed at 6 months. In the control group, only partial bridging was observed at 3 months and only 50% of segments in this group showed complete defect bridging at 6 months. Furthermore, 25% of segments in the control group showed evidence of graft fracture, resorption and pseudoarthrosis. In contrast, no evidence of graft fractures, pseudoarthrosis or foreign body reaction was observed in the treatment group. These results reveal that mPCL–TCP scaffolds could act as bone graft substitutes by providing a suitable environment for bone regeneration in a dynamic load bearing setting such as in a porcine model of interbody spine fusion.

Establishment of a preclinical ovine model for tibial segmental bone defect repair by applying bone tissue engineering strategies

Currently, well-established clinical therapeutic approaches for bone reconstruction are restricted to the transplantation of autografts and allografts, and the implantation of metal devices or ceramic-based implants to assist bone regeneration. Bone grafts possess osteoconductive and osteoinductive properties, however they are limited in access and availability and associated with donor site morbidity, haemorrhage, risk of infection, insufficient transplant integration, graft devitalisation, and subsequent resorption resulting in decreased mechanical stability. As a result, recent research focuses on the development of alternative therapeutic concepts. The field of tissue engineering has emerged as an important approach to bone regeneration. However, bench to bedside translations are still infrequent as the process towards approval by regulatory bodies is protracted and costly, requiring both comprehensive in vitro and in vivo studies. The subsequent gap between research and clinical translation, hence commercialization, is referred to as the ‘Valley of Death’ and describes a large number of projects and/or ventures that are ceased due to a lack of funding during the transition from product/technology development to regulatory approval and subsequently commercialization. One of the greatest difficulties in bridging the Valley of Death is to develop good manufacturing processes (GMP) and scalable designs and to apply these in pre-clinical studies. In this article, we describe part of the rationale and road map of how our multidisciplinary research team has approached the first steps to translate orthopaedic bone engineering from bench to bedside byestablishing a pre-clinical ovine critical-sized tibial segmental bone defect model and discuss our preliminary data relating to this decisive step.

Integrating engineering model eliciting activities in elementary school curricula

This paper argues for a future-oriented, inclusion of Engineering Model Eliciting Activities (EngMEAs) in elementary mathematics curricula. In EngMEAs students work with meaningful engineering problems that capitalise on and extend their existing mathematics and science learning, to develop, revise and document powerful models, while working in groups. The models developed by six groups of 12-year students in solving the Natural Gas activity are presented. Results showed that student models adequately solved the problem, although student models did not take into account all the data provided. Student solutions varied to the extent students employed the engineering context in their models and to their understanding of the mathematical concepts involved in the problem. Finally, recommendations for implementing EngMEAs and for further research are discussed.

Innovation implementation effectiveness : a multiorganizational test of Klein Conn and Sorra’s model.

In an empirical test and extension of Klein Conn and Sorra’s model of innovation implementation effectiveness, we apply structural equation modelling to identify the generalizability of their data-modified model in comparison with their theorised model. We examined the implementation of various types of innovations in a sample of 135 organizations. We found that the data supported the original model rather than the data-modified model, such that implementation climate mediated polices and practices and implementation effectiveness, while implementation effectiveness partially mediated the relationship between implementation climate and innovation effectiveness. Furthermore, we extend their model to suggest that non-financial resources availability plays a critical role in implementation policies and practices.

Multi-vehicles interaction graph model for cooperative collision warning system

Cooperative collision warning system for road vehicles, enabled by recent advances in positioning systems and wireless communication technologies, can potentially reduce traffic accident significantly. To improve the system, we propose a graph model to represent interactions between multiple road vehicles in a specific region and at a specific time. Given a list of vehicles in vicinity, we can generate the interaction graph using several rules that consider vehicle's properties such as position, speed, heading, etc. Safety applications can use the model to improve emergency warning accuracy and optimize wireless channel usage. The model allows us to develop some congestion control strategies for an efficient multi-hop broadcast protocol.

Interpersonal pattern dynamics and adaptive behavior in multiagent neurobiological systems : conceptual model and data

Ecological dynamics characterizes adaptive behavior as an emergent, self-organizing property of interpersonal interactions in complex social systems. The authors conceptualize and investigate constraints on dynamics of decisions and actions in the multiagent system of team sports. They studied coadaptive interpersonal dynamics in rugby union to model potential control parameter and collective variable relations in attacker–defender dyads. A videogrammetry analysis revealed how some agents generated fluctuations by adapting displacement velocity to create phase transitions and destabilize dyadic subsystems near the try line. Agent interpersonal dynamics exhibited characteristics of chaotic attractors and informational constraints of rugby union boxed dyadic systems into a low dimensional attractor. Data suggests that decisions and actions of agents in sports teams may be characterized as emergent, self-organizing properties, governed by laws of dynamical systems at the ecological scale. Further research needs to generalize this conceptual model of adaptive behavior in performance to other multiagent populations.

The explicit hazard model – part 1: theoretical development

Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Appropriate mathematical models that are capable of estimating times to failures and the probability of failures in the future are essential in EAM. In most real-life situations, the lifetime of an engineering asset is influenced and/or indicated by different factors that are termed as covariates. Hazard prediction with covariates is an elemental notion in the reliability theory to estimate the tendency of an engineering asset failing instantaneously beyond the current time assumed that it has already survived up to the current time. A number of statistical covariate-based hazard models have been developed. However, none of them has explicitly incorporated both external and internal covariates into one model. This paper introduces a novel covariate-based hazard model to address this concern. This model is named as Explicit Hazard Model (EHM). Both the semi-parametric and non-parametric forms of this model are presented in the paper. The major purpose of this paper is to illustrate the theoretical development of EHM. Due to page limitation, a case study with the reliability field data is presented in the applications part of this study.

Mechanisms of improvement in treatment for depression : test of a self-efficacy and performance model

Tested D. J. Kavanagh's (1983) depression model's explanation of response to cognitive-behavioral treatment among 19 20–60 yr old Ss who received treatment and 24 age-matched Ss who were assigned to a waiting list. Measures included the Beck Depression Inventory and self-efficacy (SE) and self-monitoring scales. Rises in SE and self-monitored performance of targeted skills were closely associated with the improved depression scores of treated Ss. Improvements in the depression of waiting list Ss occurred through random, uncontrolled events rather than via a systematic increase in specific skills targeted in treatment. SE regarding assertion also predicted depression scores over a 12-wk follow-up.

The Explicit Hazard Model – Part 2 : Applications

Hazard and reliability prediction of an engineering asset is one of the significant fields of research in Engineering Asset Health Management (EAHM). In real-life situations where an engineering asset operates under dynamic operational and environmental conditions, the lifetime of an engineering asset can be influenced and/or indicated by different factors that are termed as covariates. The Explicit Hazard Model (EHM) as a covariate-based hazard model is a new approach for hazard prediction which explicitly incorporates both internal and external covariates into one model. EHM is an appropriate model to use in the analysis of lifetime data in presence of both internal and external covariates in the reliability field. This paper presents applications of the methodology which is introduced and illustrated in the theory part of this study. In this paper, the semi-parametric EHM is applied to a case study so as to predict the hazard and reliability of resistance elements on a Resistance Corrosion Sensor Board (RCSB).