Evaluation of a hybrid scaffold/cell construct in repair of high-load-bearing osteochondral defects in rabbits

The objective of this study was to evaluate the feasibility and potential of a hybrid scaffold system in large- and high-load-bearing osteochondral defects repair. The implants were made of medical-grade PCL (mPCL) for the bone compartment whereas fibrin glue was used for the cartilage part. Both matrices were seeded with allogenic bone marrow-derived mesenchymal cells (BMSC) and implanted in the defect (4 mm diameter×5 mm depth) on medial femoral condyle of adult New Zealand White rabbits. Empty scaffolds were used at the control side. Cell survival was tracked via fluorescent labeling. The regeneration process was evaluated by several techniques at 3 and 6 months post-implantation. Mature trabecular bone regularly formed in the mPCL scaffold at both 3 and 6 months post-operation. Micro-Computed Tomography showed progression of mineralization from the host–tissue interface towards the inner region of the grafts. At 3 months time point, the specimens showed good cartilage repair. In contrast, the majority of 6 months specimens revealed poor remodeling and fissured integration with host cartilage while other samples could maintain good cartilage appearance. In vivo viability of the transplanted cells was demonstrated for the duration of 5 weeks. The results demonstrated that mPCL scaffold is a potential matrix for osteochondral bone regeneration and that fibrin glue does not inherit the physical properties to allow for cartilage regeneration in a large and high-load-bearing defect site. Keywords: Osteochondral tissue engineering; Scaffold; Bone marrow-derived precursor cells; Fibrin glue

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros

Expected safety performance of rural signalized intersections in South Korea

Understanding the expected safety performance of rural signalized intersections is critical for (a) identifying high-risk sites where the observed safety performance is substantially worse than the expected safety performance, (b) understanding influential factors associated with crashes, and (c) predicting the future performance of sites and helping plan safety-enhancing activities. These three critical activities are routinely conducted for safety management and planning purposes in jurisdictions throughout the United States and around the world. This paper aims to develop baseline expected safety performance functions of rural signalized intersections in South Korea, which to date have not yet been established or reported in the literature. Data are examined from numerous locations within South Korea for both three-legged and four-legged configurations. The safety effects of a host of operational and geometric variables on the safety performance of these sites are also examined. In addition, supplementary tables and graphs are developed for comparing the baseline safety performance of sites with various geometric and operational features. These graphs identify how various factors are associated with safety. The expected safety prediction tables offer advantages over regression prediction equations by allowing the safety manager to isolate specific features of the intersections and examine their impact on expected safety. The examination of the expected safety performance tables through illustrated examples highlights the need to correct for regression-to-the-mean effects, emphasizes the negative impacts of multicollinearity, shows why multivariate models do not translate well to accident modification factors, and illuminates the need to examine road safety carefully and methodically. Caveats are provided on the use of the safety performance prediction graphs developed in this paper.

Identifying large truck hot spots using crash counts and PDOEs

Large trucks are involved in a disproportionately small fraction of the total crashes but a disproportionately large fraction of fatal crashes. Large truck crashes often result in significant congestion due to their large physical dimensions and from difficulties in clearing crash scenes. Consequently, preventing large truck crashes is critical to improving highway safety and operations. This study identifies high risk sites (hot spots) for large truck crashes in Arizona and examines potential risk factors related to the design and operation of the high risk sites. High risk sites were identified using both state of the practice methods (accident reduction potential using negative binomial regression with long crash histories) and a newly proposed method using Property Damage Only Equivalents (PDOE). The hot spots identified via the count model generally exhibited low fatalities and major injuries but large minor injuries and PDOs, while the opposite trend was observed using the PDOE methodology. The hot spots based on the count model exhibited large AADTs, whereas those based on the PDOE showed relatively small AADTs but large fractions of trucks and high posted speed limits. Documented site investigations of hot spots revealed numerous potential risk factors, including weaving activities near freeway junctions and ramps, absence of acceleration lanes near on-ramps, small shoulders to accommodate large trucks, narrow lane widths, inadequate signage, and poor lighting conditions within a tunnel.

Correlates of sitting time in working age Australian women : who should be targeted with interventions to decrease sitting time?

Background: While there is emerging evidence that sedentary behavior is negatively associated with health risk, research on the correlates of sitting time in adults is scarce. Methods: Self-report data from 7,724 women born between 1973-1978 and 8,198 women born between 1946-1951 were collected as part of the Australian Longitudinal Study on Women’s Health. Linear regression models were computed to examine whether demographic, family and caring duties, time use, health and health behavior variables were associated with weekday sitting time. Results: Mean sitting time (SD) was 6.60 (3.32) hours/day for the 1973-1978 cohort and 5.70 (3.04) hours/day for the 1946-1951 cohort. Indicators of socio-economic advantage, such as full11 time work and skilled occupations in both cohorts and university education in the mid-age cohort, were associated with high sitting time. A cluster of ‘healthy behaviours’ was associated with lower sitting time in the mid-aged women (moderate/high physical activity levels, non-smoking, non-drinking). For both cohorts, sitting time was highest in women in full-time work, in skilled occupations and in those who spent the most time in passive leisure. Conclusions: The results suggest that, in young and mid-aged women, interventions for reducing sitting time should focus on both occupational and leisure-time sitting.

Lateral shearing interferometry, dynamic wavefront sensing, and high-speed videokeratoscopy for noninvasive assessment of tear film surface characteristics : a comparitive study

There are several noninvasive techniques for assessing the kinetics of tear film, but no comparative studies have been conducted to evaluate their efficacies. Our aim is to test and compare techniques based on high-speed videokeratoscopy (HSV), dynamic wavefront sensing (DWS), and lateral shearing interferometry (LSI). Algorithms are developed to estimate the tear film build-up time TBLD, and the average tear film surface quality in the stable phase of the interblink interval TFSQAv. Moderate but significant correlations are found between TBLD measured with LSI and DWS based on vertical coma (Pearson's r2=0.34, p<0.01) and higher order rms (r2=0.31, p<0.01), as well as between TFSQAv measured with LSI and HSV (r2=0.35, p<0.01), and between LSI and DWS based on the rms fit error (r2=0.40, p<0.01). No significant correlation is found between HSV and DWS. All three techniques estimate tear film build-up time to be below 2.5 sec, and they achieve a remarkably close median value of 0.7 sec. HSV appears to be the most precise method for measuring tear film surface quality. LSI appears to be the most sensitive method for analyzing tear film build-up.

Vitamin D intake needed to maintain target serum 25-Hydroxyvitamin D concentrations in participants with low sun exposure and dark skin pigmentation is substantially higher than current recommendations

Cutaneous cholecalciferol synthesis has not been considered in making recommendations for vitamin D intake. Our objective was to model the effects of sun exposure, vitamin D intake, and skin reflectance (pigmentation) on serum 25-hydroxyvitamin D (25[OH]D) in young adults with a wide range of skin reflectance and sun exposure. Four cohorts of participants (n = 72 total) were studied for 7-8 wk in the fall, winter, spring, and summer in Davis, CA [38.5° N, 121.7° W, Elev. 49 ft (15 m)]. Skin reflectance was measured using a spectrophotometer, vitamin D intake using food records, and sun exposure using polysulfone dosimeter badges. A multiple regression model (R^sup 2^ = 0.55; P < 0.0001) was developed and used to predict the serum 25(OH)D concentration for participants with low [median for African ancestry (AA)] and high [median for European ancestry (EA)] skin reflectance and with low [20th percentile, ~20 min/d, ~18% body surface area (BSA) exposed] and high (80th percentile, ~90 min/d, ~35% BSA exposed) sun exposure, assuming an intake of 200 IU/d (5 ug/d). Predicted serum 25(OH)D concentrations for AA individuals with low and high sun exposure in the winter were 24 and 42 nmol/L and in the summer were 40 and 60 nmol/L. Corresponding values for EA individuals were 35 and 60 nmol/L in the winter and in the summer were 58 and 85 nmol/L. To achieve 25(OH)D ≥75 nmol/L, we estimate that EA individuals with high sun exposure need 1300 IU/d vitamin D intake in the winter and AA individuals with low sun exposure need 2100-3100 IU/d year-round.

'I am smart and I am not joking': Aiming high in the middle years of schooling

In this paper, we draw on accounts from students to inform a Middle Schooling movement that has been variously described as "arrested", "unfinished" and "exhausted". We propose that if the Middle Schooling movement is to understand the changing worlds of students and develop new approaches in the middle years of schooling, then it is important to draw on the insights that individual students can provide by conducting research with "students-as-informants". The early adolescent informants to this paper report high hopes for their futures (despite their lower socio-economic surroundings), which reinforces the importance of supporting successful learner identities and highlights the role of schooling in the decline of adolescent student aspirations. However, their insights did not stop at the individual learner, with students also identifying cultural and structural constraints to reform. As such, we argue that students may be both an important resource for inquiry into individual school reform and for the Middle Schooling movement internationally.

Beyond statistical procedures for predictive modelling: Data mining algorithms and support for university research at QUT

In a seminal data mining article, Leo Breiman [1] argued that to develop effective predictive classification and regression models, we need to move away from the sole dependency on statistical algorithms and embrace a wider toolkit of modeling algorithms that include data mining procedures. Nevertheless, many researchers still rely solely on statistical procedures when undertaking data modeling tasks; the sole reliance on these procedures has lead to the development of irrelevant theory and questionable research conclusions ([1], p.199). We will outline initiatives that the HPC & Research Support group is undertaking to engage researchers with data mining tools and techniques; including a new range of seminars, workshops, and one-on-one consultations covering data mining algorithms, the relationship between data mining and the research cycle, and limitations and problems with these new algorithms. Organisational limitations and restrictions to these initiatives are also discussed.

Wavelet based approaches and high resolution methods for complex process models

Many industrial processes and systems can be modelled mathematically by a set of Partial Differential Equations (PDEs). Finding a solution to such a PDF model is essential for system design, simulation, and process control purpose. However, major difficulties appear when solving PDEs with singularity. Traditional numerical methods, such as finite difference, finite element, and polynomial based orthogonal collocation, not only have limitations to fully capture the process dynamics but also demand enormous computation power due to the large number of elements or mesh points for accommodation of sharp variations. To tackle this challenging problem, wavelet based approaches and high resolution methods have been recently developed with successful applications to a fixedbed adsorption column model. Our investigation has shown that recent advances in wavelet based approaches and high resolution methods have the potential to be adopted for solving more complicated dynamic system models. This chapter will highlight the successful applications of these new methods in solving complex models of simulated-moving-bed (SMB) chromatographic processes. A SMB process is a distributed parameter system and can be mathematically described by a set of partial/ordinary differential equations and algebraic equations. These equations are highly coupled; experience wave propagations with steep front, and require significant numerical effort to solve. To demonstrate the numerical computing power of the wavelet based approaches and high resolution methods, a single column chromatographic process modelled by a Transport-Dispersive-Equilibrium linear model is investigated first. Numerical solutions from the upwind-1 finite difference, wavelet-collocation, and high resolution methods are evaluated by quantitative comparisons with the analytical solution for a range of Peclet numbers. After that, the advantages of the wavelet based approaches and high resolution methods are further demonstrated through applications to a dynamic SMB model for an enantiomers separation process. This research has revealed that for a PDE system with a low Peclet number, all existing numerical methods work well, but the upwind finite difference method consumes the most time for the same degree of accuracy of the numerical solution. The high resolution method provides an accurate numerical solution for a PDE system with a medium Peclet number. The wavelet collocation method is capable of catching up steep changes in the solution, and thus can be used for solving PDE models with high singularity. For the complex SMB system models under consideration, both the wavelet based approaches and high resolution methods are good candidates in terms of computation demand and prediction accuracy on the steep front. The high resolution methods have shown better stability in achieving steady state in the specific case studied in this Chapter.

Critical analysis of high particle number emissions from accelerating compressed natural gas buses

Compressed natural gas (CNG) engines are thought to be less harmful to the environment than conventional diesel engines, especially in terms of particle emissions. Although, this is true with respect to particulate matter (PM) emissions, results of particle number (PN) emission comparisons have been inconclusive. In this study, results of on-road and dynamometer studies of buses were used to derive several important conclusions. We show that, although PN emissions from CNG buses are significantly lower than from diesel buses at low engine power, they become comparable at high power. For diesel buses, PN emissions are not significantly different between acceleration and operation at steady maximum power. However, the corresponding PN emissions from CNG buses when accelerating are an order of magnitude greater than when operating at steady maximum power. During acceleration under heavy load, PN emissions from CNG buses are an order of magnitude higher than from diesel buses. The particles emitted from CNG buses are too small to contribute to PM10 emissions or contribute to a reduction of visibility, and may consist of semivolatile nanoparticles.

Strengthening of circular hollow steel tubular sections using high modulus CFRP sheets

This paper describes the behaviour of very high strength (VHS) circular steel tubes strengthened by carbon fibre reinforced polymer (CFRP) and subjected to axial tension. A series of tests were conducted with different bond lengths and number of layers. The distribution of strain through the thickness of CFRP layers and along CFRP bond length was studied. The strain was found to generally decrease along the CFRP bond length far from the joint. The strain through the thickness of the CFRP layers was also found to decrease from bottom to top layer. The effective bond length for high modulus CFRP was established. Finally empirical models were developed to estimate the maximum load for a given CFRP arrangement.

Accountability through high-stakes testing and curriculum change

The motivation for secondary school principals in Queensland, Australia, to investigate curriculum change coincided with the commencement in 2005 of the state government’s publication of school exit test results as a measure of accountability. Aligning the schools’ curriculum with the requirements of high-stakes testing is considered by many academics and teachers as negative outcome of accountability for reasons such as ‘teaching to the test’ and narrowing the curriculum. However, this article outlines empirical evidence that principals are instigating curriculum change to improve published high-stakes test results. Three principals in this study offered several reasons as to why they wished to implement changes to school curricula. One reason articulated by all three was the pressures of accountability, particularly through the publication of high-stakes test data which has now become commonplace in education systems of many Western Nations.

Use of lifts and refuge floors for fire evacuation in high rise apartment buildings

If current population and accommodation trends continue, Australian cities will, in the future, have noticeable numbers of apartment buildings over 60 storeys high. With an aging population it follows that a significant proportion of those occupying these buildings will be senior citizens, many of whom will have some form of disability. For these occupants a fire emergency in a high rise building presents a serious problem. Currently lifts cannot be used for evacuation and going down 60 storeys in a fire isolated staircase would be physically impossible for many. Therefore, for many, the temptation to remain in one’s unit will be very strong. With an awareness of this behaviour trend in older residents, many researchers have, in recent years, explored the possible wider use of lifts in a fire emergency. So far the use of lifts for evacuation has been approved for a small number of buildings but wide acceptance of this solution is still to be achieved. This paper concludes that even in high-rise apartment buildings where lifts are approved for evacuation, architects should design the building with alternative evacuation routes and provide suitable safe refuge areas for those who cannot use the stairs when the lifts are unavailable.

The role of bricolage and resource constraints in high potential sustainability ventures

Sustainability decisions and their impacts may be among the greatest challenges facing the world in the 21st century (Davos 2000). Apart from adaptation on the part of established organizations these challenges are arguably going to require solutions developed by new actors However, young ventures have only recently begun generating research interest within sustainability literature (Shepherd et al. 2009). In particular, little is known about resource behaviours of these ventures and how they adapt to substantial resource constraints. One promising theory that has been identified as a way that some entrepreneurs manage constraints is bricolage: a construct defined as “making do by applying combinations of the resources at hand to new problems and opportunities” (Baker and Nelson 2005: 333). Bricolage may be critical as the means of continued venture success as these ventures are frequently developed in severe resource constraint, owing to higher levels of technical sophistication (Rothaermel and Deeds 2006). Further, they are often developed by entrepreneurs committed to personal and social goals of resourcefulness, including values that focus on conservation rather than consumption of resources (Shepherd et al. 2009). In this paper, using seven novel cases of high potential sustainability firms from CAUSEE we consider how constraints impact resource behaviours and further illustrate and extend bricolage domains previously developed by Baker and Nelson (2005) with recommendations for theory and practice provided.