Implantation of osteogenic differentiated donor mesenchymal stem cells causes recruitment of host cells

The interaction between host and donor cells is believed to play an important role in osteogenesis. However, it is still unclear how donor osteogenic cells behave and interact with host cells in vivo. The purpose of this study was to track the interactions between transplanted osteogenic cells and host cells during osteogenesis. In vitro migration assay was carried out to investigate the ability of osteogenic differentiated humanmesenchymal stemcells (O-hMSCs) to recruit MSCs. At the in vivo level, O-hMSCs were implanted subcutaneously or into skull defects in severe combined immunodeficient (SCID) mice. New bone formation was observed bymicro-CT and histological procedures. In situ hybridization (ISH) against human Alu sequences was performed to distinguish donor osteogenic cells from host cells. In vitro migration assay revealed an increased migration potential of MSCs by co-culturing with O-hMSCs. In agreement with the results of in vitro studies, ISH against human Alu sequences showed that host mouse MSCs migrated in large numbers into the transplantation site in response to O-hMSCs. Interestingly, host cells recruited by O-hMSCs were the major cell populations in newly formed bone tissues, indicating that O-hMSCs can trigger and initiate osteogenesis when transplanted in orthotopic sites. The observations fromthis study demonstrated that in vitro induced O-hMSCs were able to attract hostMSCs in vivo andwere involved inosteogenesis togetherwith host cells,whichmay be of importance for bone tissue-engineering applications.

Misericordiae Antemortem - The 1955 Mount Superbus Crash

On the 9th April 1955, RAAF Lincoln Bomber A73-64, on a mercy flight to transfer a critically ill infant from Townsville to Brisbane, crashed at Mount Superbus killing the four crew and two civilians on board. The immediate search and rescue was organised by a group of Brisbane bushwalkers who were camping in the area. Police and RAAF personnel subsequently joined the civilians at the crash site to recover the victims. During their initial search of the crash they located what were believed to be the remains of five adults. The arrival of the RAAF Senior Medical Officer (SMO) the following day revealed that only four adult bodies had been found and the bodies of both civilians, an adult and infant, were missing. Later that day the remains of six victims were recovered from the crash site and conveyed to the Warwick Police Station for identification. The RAAF SMO was responsible for the identifications of the aircrew while the Government Medical Officer, police and coroner were responsible for the identifications of the civilians. Eight days later, further remains of the infant were found by a civilian looking through the wreckage. This paper uses archival records not previously researched from a Disaster Victim Identification (DVI) perspective to stimulate interest among forensic practitioners, criminologists and other interested parties in the history of DVI and how practices in Australia have evolved.

Visual motion perception predicts driving hazard perception ability

PURPOSE: To examine the basis of previous findings of an association between indices of driving safety and visual motion sensitivity and to examine whether this association could be explained by low-level changes in visual function. METHODS: 36 visually normal participants (aged 19 – 80 years), completed a battery of standard vision tests including visual acuity, contrast sensitivity and automated visual fields. and two tests of motion perception including sensitivity for movement of a drifting Gabor stimulus, and sensitivity for displacement in a random-dot kinematogram (Dmin). Participants also completed a hazard perception test (HPT) which measured participants’ response times to hazards embedded in video recordings of real world driving which has been shown to be linked to crash risk. RESULTS: Dmin for the random-dot stimulus ranged from -0.88 to -0.12 log minutes of arc, and the minimum drift rate for the Gabor stimulus ranged from 0.01 to 0.35 cycles per second. Both measures of motion sensitivity significantly predicted response times on the HPT. In addition, while the relationship involving the HPT and motion sensitivity for the random-dot kinematogram was partially explained by the other visual function measures, the relationship with sensitivity for detection of the drifting Gabor stimulus remained significant even after controlling for these variables. CONCLUSION: These findings suggest that motion perception plays an important role in the visual perception of driving-relevant hazards independent of other areas of visual function and should be further explored as a predictive test of driving safety. Future research should explore the causes of reduced motion perception in order to develop better interventions to improve road safety.

The causes of sinuous crustal-scale deformation patterns in hot orogens: Evidence from scaled analogue experiments and the southern Central Andes

The cause of upper-crustal segmentation into rhomb-shaped, shear zone-bound domains associated with contractional sedimentary basins in hot, wide orogens is not well understood. Here we use scaled multilayered analogue experiments to investigate the role of an orogen-parallel crustal-strength gradient on the formation of such structures. We show that the aspect ratio and size of domains, the sinuous character and abundance of transpressional shear zones vary with the integrated mechanical strength of crust. Upper-crustal deformation patterns and the degree of strain localization in the experiments are controlled by the ratio between the brittle and ductile strength in the model crust as well as gradients in tectonic and buoyancy forces. The experimental results match the first-order kinematic and structural characteristics of the southern Central Andes and provide insight on the dynamics of underlying deformation patterns in hot, wide orogens.

A comparison of perceived crash risk among cyclists and drivers in Brisbane

The Queensland Government has implemented strategies promoting a shift from individual car use to active transport, a transition which requires drivers to adapt to sharing the road with increased numbers of people cycling through transport network. For this to occur safely, changes in both road infrastructure and road user expectations and behaviors will be needed. Creating separate cycle infrastructure does not remove the need for cyclists to commence, cross or finish travel on shared roads. Currently intersections are one of the predominant shared road spaces where crashes result in cyclists being injured or killed. This research investigates how Brisbane cyclists and drivers perceive risk when interacting with other road users at intersections. The current study replicates a French study conducted by co-authors Chaurand and Delhomme in 2011 and extends it to assess gender effects which have been reported in other Australian cycling research. An online survey was administered to experienced cyclists and drivers. Participants rated the level of risk they felt when imagining a number of different road situations. Based on the earlier French study it is expected that perceived crash risk will be influenced both by the participant’s mode of travel and the type of interacting vehicle and perceived risk will be greater when the interaction is with a car than a bicycle. It is predicted that risk perception will decrease as the level of experience increases and that male participants will have a higher perception of skill and lower perception of risk than females. The findings of this Queensland study will provide a valuable insight into perceived risk and the traffic behaviours of drivers and cyclists when interacting with other road users and results will be available for presentation at the Congress.

Causes of corruption : evidence from China

This study explores the causes of corruption in China using provincial panel data. Using both fixed effects and instrumental variables approaches, we find that provinces with greater anti-corruption efforts, higher educational attainment, historic influence from Anglo-American church universities, greater openness, more access to media, higher relative wages of government employees and a greater representation of women in the legislature are markedly less corrupt; whereas social heterogeneity, regulation and resources abundance breed substantial corruption. We also find that fiscal decentralization depresses corruption significantly. Finally, we identify a positive relationship between corruption and economic development in China, which is driven primarily by the transition to a market economy.

Comparing cooperative and non-cooperative crash risk assessment

Cooperative Systems provide, through the multiplication of information sources over the road, a lot of potential to improve the assessment of the road risk describing a particular driving situation. In this paper, we compare the performance of a cooperative risk assessment approach against a non-cooperative approach; we used an advanced simulation framework, allowing for accurate and detailed, close-to-reality simulations. Risk is estimated, in both cases, with combinations of indicators based on the TTC. For the non-cooperative approach, vehicles are equipped only with an AAC-like forward-facing ranging sensor. On the other hand, for the cooperative approach, vehicles share information through 802.11p IVC and create an augmented map representing their environment; risk indicators are then extracted from this map. Our system shows that the cooperative risk assessment provides a systematic increase of forward warning to most of the vehicles involved in a freeway emergency braking scenario, compared to a non-cooperative system.

Comparison of moped, scooter and motorcycle crash risk and crash severity

The increased popularity of mopeds and motor scooters in Australia and elsewhere in the last decade has contributed substantially to the greater use of powered two-wheelers (PTWs) as a whole. As the exposure of mopeds and scooters has increased, so too has the number of reported crashes involving those PTW types, but there is currently little research comparing the safety of mopeds and, particularly, larger scooters with motorcycles. This study compared the crash risk and crash severity of motorcycles, mopeds and larger scooters in Queensland, Australia. Comprehensive data cleansing was undertaken to separate motorcycles, mopeds and larger scooters in police-reported crash data covering the five years to 30 June 2008. The crash rates of motorcycles (including larger scooters) and mopeds in terms of registered vehicles were similar over this period, although the moped crash rate showed a stronger downward trend. However, the crash rates in terms of distance travelled were nearly four times higher for mopeds than for motorcycles (including larger scooters). More comprehensive distance travelled data is needed to confirm these findings. The overall severity of moped and scooter crashes was significantly lower than motorcycle crashes but an ordered probit regression model showed that crash severity outcomes related to differences in crash characteristics and circumstances, rather than differences between PTW types per se. Greater motorcycle crash severity was associated with higher (>80 km/h) speed zones, horizontal curves, weekend, single vehicle and nighttime crashes. Moped crashes were more severe at night and in speed zones of 90 km/h or more. Larger scooter crashes were more severe in 70 km/h zones (than 60 km/h zones) but not in higher speed zones, and less severe on weekends than on weekdays. The findings can be used to inform potential crash and injury countermeasures tailored to users of different PTW types.

A data mining driven crash risk profiling method for road asset management

This thesis takes a new data mining approach for analyzing road/crash data by developing models for the whole road network and generating a crash risk profile. Roads with an elevated crash risk due to road surface friction deficit are identified. The regression tree model, predicting road segment crash rate, is applied in a novel deployment coined regression tree extrapolation that produces a skid resistance/crash rate curve. Using extrapolation allows the method to be applied across the network and cope with the high proportion of missing road surface friction values. This risk profiling method can be applied in other domains.

Understanding worker perceptions of common incidents at roadworks in Queensland

The process of building safer roads and roadsides needs to be managed to minimise risks to both the road using public and roadworkers. However, detailed and accurate data on fatalities and injuries at roadworks across Australia are not available. The lack of reliable safety records and consequent poor understanding of the hazards at roadworks motivated this research to examine the common trends in incidents and to understand workers' perceptions of the causes of incidents at roadworks. To achieve these aims, 66 roadworks personnel were interviewed in Queensland including road construction workers, traffic controllers, engineers, and managers. Qualitative analyses identified several major issues and themes. Vehicles driving into work areas, traffic controllers hit by vehicles, rear end crashes at roadwork approaches, and reversing incidents involving work vehicles and machinery were the most common types of incidents. Roadworkers perceived driver errors, such as violation of speed limits, distracted driving, and ignoring signage and traffic controllers' instructions as the main causes of the incidents.

Pre-crash traffic flow trend analysis on motorways

Crashes on motorway contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence reduce crashes will help address congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a Short time window around the time of crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques, that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists, and that this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with traffic flow data of one hour prior to the crash using an incident detection algorithm. Traffic flow trends (traffic speed/occupancy time series) revealed that crashes could be clustered with regards of the dominant traffic flow pattern prior to the crash. Using the k-means clustering method allowed the crashes to be clustered based on their flow trends rather than their distance. Four major trends have been found in the clustering results. Based on these findings, crash likelihood estimation algorithms can be fine-tuned based on the monitored traffic flow conditions with a sliding window of 60 minutes to increase accuracy of the results and minimize false alarms.

Pre-crash and non-crash traffic flow trends analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk” clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.