Effects of cold water immersion on knee joint position sense in healthy volunteers

The purpose of this study was to determine the effects of cryotherapy, in the form of cold water immersion, on knee joint position sense. Fourteen healthy volunteers, with no previous knee injury or pre-existing clinical condition, participated in this randomized cross-over trial. The intervention consisted of a 30-min immersion, to the level of the umbilicus, in either cold (14 ± 1°C) or tepid water(28 ± 1°C). Approximately one week later, in a randomized fashion, the volunteers completed the remaining immersion. Active ipsilateral limb repositioning sense of the right knee was measured, using weight-bearing and non-weight bearing assessments, employing video-recorded 3D motion analysis. These assessments were conducted immediately before and after a cold and tepid water immersion. No significant differences were found between treatments for the absolute (P = 0.29), relative (P = 0.21) or variable error (P = 0.86). The average effect size of the outcome measures was modest (range –0.49 to 0.9) and all the associated 95% confidence intervals for these effect sizes crossed zero. These results indicate that there is no evidence of an enhanced risk of injury, following a return to sporting activity, after cold water.

Functional and advanced functional and causal relationship diagrams for remote condition monitoring

Analysing the condition of an asset is a big challenge as there can be many aspects which can contribute to the overall functional reliability of the asset that have to be considered. In this paper we propose a two-step functional and causal relationship diagram (FCRD) to address this problem. In the first step, the FCRD is designed to facilitate the analysis of the condition of an asset by evaluating the interdependence (functional and causal) relationships between different components of the asset with the help of a relationship diagram. This is followed by the advanced FCRD (AFCRD) which refines the information from the FCRD into a comprehensive and manageable format. This new two-step methodology for asset condition monitoring is tested and validated for the case of a water treatment plant. © IMechE 2012.

A note on the ‘Linsanity’ of measuring the relative efficiency of National Basketball Association (NBA) guards

This note examines the productive efficiency of 62 starting guards during the 2011/12 National Basketball Association (NBA) season. This period coincides with the phenomenal and largely unanticipated performance of New York Knicks’ starting point guard Jeremy Lin and the attendant public and media hype known as Linsanity. We employ a data envelopment analysis (DEA) approach that includes allowance for an undesirable output, here turnovers per game, with the desirable outputs of points, rebounds, assists, steals, and blocks per game and an input of minutes per game. The results indicate that depending upon the specification, between 29 and 42 percent of NBA guards are fully efficient, including Jeremy Lin, with a mean inefficiency of 3.7 and 19.2 percent. However, while Jeremy Lin is technically efficient, he seldom serves as a benchmark for inefficient players, at least when compared with established players such as Chris Paul and Dwayne Wade. This suggests the uniqueness of Jeremy Lin’s productive solution and may explain why his unique style of play, encompassing individual brilliance, unselfish play, and team leadership, is of such broad public appeal.

Condition deterioration prediction of bridge elements using Dynamic Bayesian Networks (DBNs)

The ability of bridge deterioration models to predict future condition provides significant advantages in improving the effectiveness of maintenance decisions. This paper proposes a novel model using Dynamic Bayesian Networks (DBNs) for predicting the condition of bridge elements. The proposed model improves prediction results by being able to handle, deterioration dependencies among different bridge elements, the lack of full inspection histories, and joint considerations of both maintenance actions and environmental effects. With Bayesian updating capability, different types of data and information can be utilised as inputs. Expert knowledge can be used to deal with insufficient data as a starting point. The proposed model established a flexible basis for bridge systems deterioration modelling so that other models and Bayesian approaches can be further developed in one platform. A steel bridge main girder was chosen to validate the proposed model.

A spatial collision avoidance strategy for UAVs in a non-cooperative environment

This paper presents a feasible spatial collision avoidance approach for fixed-wing unmanned aerial vehicles (UAVs). The proposed strategy aims to achieve the desired relative bearing in the horizontal plane and relative elevation in the vertical plane so that the host aircraft is able to avoid collision with the intruder aircraft in 3D. The host aircraft will follow a desired trajectory in the collision avoidance course and resume the pre-arranged trajectory after collision is avoided. The approaching stopping condition is determined for the host aircraft to trigger an evasion maneuver to avoid collision in terms of measured heading. A switching controller is designed to achieve the spatial collision avoidance strategy. Simulation results demonstrate that the proposed approach can effectively avoid spatial collision, making it suitable for integration into flight control systems of UAVs.

Mesoporous bioactive glass scaffolds for efficient delivery of vascular endothelial growth factor

In this article, we, for the first time, investigated mesoporous bioactive glass scaffolds for the delivery of vascular endothelial growth factor. We have found that mesoporous bioactive glass scaffolds have significantly higher loading efficiency and more sustained release of vascular endothelial growth factor than non-mesoporous bioactive glass scaffolds. In addition, vascular endothelial growth factor delivery from mesoporous bioactive glass scaffolds has improved the viability of endothelial cells. The study has suggested that mesopore structures in mesoporous bioactive glass scaffolds play an important role in improving the loading efficiency, decreasing the burst release, and maintaining the bioactivity of vascular endothelial growth factor, indicating that mesoporous bioactive glass scaffolds are an excellent carrier of vascular endothelial growth factor for potential bone tissue engineering applications.

Development of a 3D culture system to study the skeletal metastasis of prostate cancer

In the cancer research field, most in vitro studies still rely on two-dimensional (2D) cultures. However, the trend is rapidly shifting towards using a three-dimensional (3D) culture system. This is because 3D models better recapitulate the microenvironment of cells, and therefore, yield cellular and molecular responses that more accurately describe the pathophysiology of cancer. By adopting technology platforms established by the tissue engineering discipline, it is now possible to grow cancer cells in extracellular matrix (ECM)-like environments and dictate the biophysical and biochemical properties of the matrix. In addition, 3D models can be modified to recapitulate different stages of cancer progression for instance from the initial development of tumor to metastasis. Inevitably, to recapitulate a heterotypic condition, comprising more than one cell type, it requires a more complex 3D model. To date, 3D models that are available for studying the prostate cancer (CaP)-bone interactions are still lacking. Therefore, the aim of this study is to establish a co-culture model that allows investigation of direct and indirect CaP-bone interactions. Prior to that, 3D polyethylene glycol (PEG)-based hydrogel cultures for CaP cells were first developed and growth conditions were optimised. Characterization of the 3D hydrogel cultures show that LNCaP cells form a multicellular mass that resembles avascular tumor. In comparison to 2D cultures, besides the difference in cell morphology, the response of LNCaP cells to the androgen analogue (R1881) stimulation is different compared to the cells in 2D cultures. This discrepancy between 2D and 3D cultures is likely associated with the cell-cell contact, density and ligand-receptor interactions. Following the 3D monoculture study, a 3D direct co-culture model of CaP cells and the human tissue engineered bone (hTEBC) construct was developed. Interactions between the CaP cells and human osteoblasts (hOBs) resulted in elevation of Matrix Metalloproteinase 9 (MMP9) for PC-3 cells and Prostate Specific Antigen (PSA) for LNCaP cells. To further investigate the paracrine interaction of CaP cells and (hOBs), a 3D indirect co-culture model was developed, where LNCaP cells embedded within PEG hydrogels were co-cultured with hTEBC. It was found that the cellular changes observed reflect the early event of CaP colonizing the bone site. In the absence of androgens, interestingly, up-regulation of PSA and other kallikreins is also detected in the co-culture compared to the LNCaP monoculture. This non androgenic stimulation could be triggered by the soluble factors secreted by the hOB such as Interleukin-6. There are also decrease in alkaline phosphatase (ALP) activity and down-regulation of genes of the hOB when co-cultured with LNCaP cells that have not been previously described. These genes include transforming growth factor β1 (TGFβ1), osteocalcin and Vimentin. However, no changes to epithelial markers (e.g E-cadherin, Cytokeratin 8) were observed in both cell types from the co-culture. Some of these intriguing changes observed in the co-cultures that had not been previously described have enriched the basic knowledge of the CaP cell-bone interaction. From this study, we have shown evidence of the feasibility and versatility of our established 3D models. These models can be adapted to test various hypotheses for studies pertaining to underlying mechanisms of bone metastasis and could provide a vehicle for anticancer drug screening purposes in the future.

An analysis of holding cost impact on housing affordability in relation to midsized Greenfield residential property developments in South East Queensland

The position of housing demand and supply is not consistent. The Australian situation counters the experience demonstrated in many other parts of the world in the aftermath of the Global Financial Crisis, with residential housing prices proving particularly resilient. A seemingly inexorable housing demand remains a critical issue affecting the socio-economic landscape. Underpinned by high levels of population growth fuelled by immigration, and further buoyed by sustained historically low interest rates, increasing income levels, and increased government assistance for first home buyers, this strong housing demand level ensures problems related to housing affordability continue almost unabated. A significant, but less visible factor impacting housing affordability relates to holding costs. Although only one contributor in the housing affordability matrix, the nature and extent of holding cost impact requires elucidation: for example, the computation and methodology behind the calculation of holding costs varies widely - and in some instances completely ignored. In addition, ambiguity exists in terms of the inclusion of various elements that comprise holding costs, thereby affecting the assessment of their relative contribution. Such anomalies may be explained by considering that assessment is conducted over time in an ever-changing environment. A strong relationship with opportunity cost - in turn dependant inter alia upon prevailing inflation and / or interest rates - adds further complexity. By extending research in the general area of housing affordability, this thesis seeks to provide a detailed investigation of those elements related to holding costs specifically in the context of midsized (i.e. between 15-200 lots) greenfield residential property developments in South East Queensland. With the dimensions of holding costs and their influence over housing affordability determined, the null hypothesis H0 that holding costs are not passed on can be addressed. Arriving at these conclusions involves the development of robust economic and econometric models which seek to clarify the componentry impacts of holding cost elements. An explanatory sequential design research methodology has been adopted, whereby the compilation and analysis of quantitative data and the development of an economic model is informed by the subsequent collection and analysis of primarily qualitative data derived from surveying development related organisations. Ultimately, there are significant policy implications in relation to the framework used in Australian jurisdictions that promote, retain, or otherwise maximise, the opportunities for affordable housing.

Severity of driver injury and vehicle damage in traffic crashes at intersections: A Bayesian hierarchical analysis

Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using Intra-class Correlation Coefficient (ICC) and Deviance Information Criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time, in good street lighting condition, involving pedestrian injuries are associated with a lower severity, while those in night time, at T/Y type intersections, on right-most lane, and installed with red light camera have larger odds of being severe. Moreover, heavy vehicles have a better resistance on severe crash, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries.

Influence of medium range transport of particles from nucleation burst on particle number concentration within the urban airshed

An elevated particle number concentration (PNC) observed during nucleation events could play a significant contribution to the total particle load and therefore to the air pollution in the urban environments. Therefore, a field measurement study of PNC was commenced to investigate the temporal and spatial variations of PNC within the urban airshed of Brisbane, Australia. PNC was monitored at urban (QUT), roadside (WOO) and semi-urban (ROC) areas around the Brisbane region during 2009. During the morning traffic peak period, the highest relative fraction of PNC reached about 5% at QUT and WOO on weekdays. PNC peaks were observed around noon, which correlated with the highest solar radiation levels at all three stations, thus suggesting that high PNC levels were likely to be associated with new particle formation caused by photochemical reactions. Wind rose plots showed relatively higher PNC for the NE direction, which was associated with industrial pollution, accounting for 12%, 9% and 14% of overall PNC at QUT, WOO and ROC, respectively. Although there was no significant correlation between PNC at each station, the variation of PNC was well correlated among three stations during regional nucleation events. In addition, PNC at ROC was significantly influenced by upwind urban pollution during the nucleation burst events, with the average enrichment factor of 15.4. This study provides an insight into the influence of regional nucleation events on PNC in the Brisbane region and it the first study to quantify the effect of urban pollution on semi-urban PNC through the nucleation events. © 2012 Author(s).

Use of hierarchical cluster analysis to assess the representativeness of a baseline groundwater quality monitoring network: comparison of New Zealand’s national and regional groundwater monitoring programs

Baseline monitoring of groundwater quality aims to characterize the ambient condition of the resource and identify spatial or temporal trends. Sites comprising any baseline monitoring network must be selected to provide a representative perspective of groundwater quality across the aquifer(s) of interest. Hierarchical cluster analysis (HCA) has been used as a means of assessing the representativeness of a groundwater quality monitoring network, using example datasets from New Zealand. HCA allows New Zealand's national and regional monitoring networks to be compared in terms of the number of water-quality categories identified in each network, the hydrochemistry at the centroids of these water-quality categories, the proportions of monitoring sites assigned to each water-quality category, and the range of concentrations for each analyte within each water-quality category. Through the HCA approach, the National Groundwater Monitoring Programme (117 sites) is shown to provide a highly representative perspective of groundwater quality across New Zealand, relative to the amalgamated regional monitoring networks operated by 15 different regional authorities (680 sites have sufficient data for inclusion in HCA). This methodology can be applied to evaluate the representativeness of any subset of monitoring sites taken from a larger network.

HMM triangle relative entropy concepts in sequential change detection applied to vision-based dim target manoeuvre detection

The quick detection of abrupt (unknown) parameter changes in an observed hidden Markov model (HMM) is important in several applications. Motivated by the recent application of relative entropy concepts in the robust sequential change detection problem (and the related model selection problem), this paper proposes a sequential unknown change detection algorithm based on a relative entropy based HMM parameter estimator. Our proposed approach is able to overcome the lack of knowledge of post-change parameters, and is illustrated to have similar performance to the popular cumulative sum (CUSUM) algorithm (which requires knowledge of the post-change parameter values) when examined, on both simulated and real data, in a vision-based aircraft manoeuvre detection problem.

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.