Systems-based accident analysis in the led outdoor activity domain : application and evaluation of a risk management framework

Safety-compromising accidents occur regularly in the led outdoor activity domain. Formal accident analysis is an accepted means of understanding such events and improving safety. Despite this, there remains no universally accepted framework for collecting and analysing accident data in the led outdoor activity domain. This article presents an application of Rasmussen's risk management framework to the analysis of the Lyme Bay sea canoeing incident. This involved the development of an Accimap, the outputs of which were used to evaluate seven predictions made by the framework. The Accimap output was also compared to an analysis using an existing model from the led outdoor activity domain. In conclusion, the Accimap output was found to be more comprehensive and supported all seven of the risk management framework's predictions, suggesting that it shows promise as a theoretically underpinned approach for analysing, and learning from, accidents in the led outdoor activity domain.

Development of accident modification factors on intersection crash maneuvers

In order to estimate the safety impact of roadway interventions engineers need to collect, analyze, and interpret the results of carefully implemented data collection efforts. The intent of these studies is to develop Accident Modification Factors (AMF's), which are used to predict the safety impact of various road safety features at other locations or in upon future enhancements. Models are typically estimated to estimate AMF's for total crashes, but can and should be estimated for crash outcomes as well. This paper first describes data collected with the intent estimate AMF's for rural intersections in the state of Georgia within the United Sates. Modeling results of crash prediction models for the crash outcomes: angle, head-on, rear-end, sideswipe (same direction and opposite direction) and pedestrian-involved crashes are then presented and discussed. The analysis reveals that factors such as the Annual Average Daily Traffic (AADT), the presence of turning lanes, and the number of driveways have a positive association with each type of crash, while the median width and the presence of lighting are negatively associated with crashes. The model covariates are related to crash outcome in different ways, suggesting that crash outcomes are associated with different pre-crash conditions.

Empirical investigation of interactive highway safety design model accident prediction algorithm : Rural intersections

One major gap in transportation system safety management is the ability to assess the safety ramifications of design changes for both new road projects and modifications to existing roads. To fulfill this need, FHWA and its many partners are developing a safety forecasting tool, the Interactive Highway Safety Design Model (IHSDM). The tool will be used by roadway design engineers, safety analysts, and planners throughout the United States. As such, the statistical models embedded in IHSDM will need to be able to forecast safety impacts under a wide range of roadway configurations and environmental conditions for a wide range of driver populations and will need to be able to capture elements of driving risk across states. One of the IHSDM algorithms developed by FHWA and its contractors is for forecasting accidents on rural road segments and rural intersections. The methodological approach is to use predictive models for specific base conditions, with traffic volume information as the sole explanatory variable for crashes, and then to apply regional or state calibration factors and accident modification factors (AMFs) to estimate the impact on accidents of geometric characteristics that differ from the base model conditions. In the majority of past approaches, AMFs are derived from parameter estimates associated with the explanatory variables. A recent study for FHWA used a multistate database to examine in detail the use of the algorithm with the base model-AMF approach and explored alternative base model forms as well as the use of full models that included nontraffic-related variables and other approaches to estimate AMFs. That research effort is reported. The results support the IHSDM methodology.

Accident prediction model for railway-highway interfaces

Considerable past research has explored relationships between vehicle accidents and geometric design and operation of road sections, but relatively little research has examined factors that contribute to accidents at railway-highway crossings. Between 1998 and 2002 in Korea, about 95% of railway accidents occurred at highway-rail grade crossings, resulting in 402 accidents, of which about 20% resulted in fatalities. These statistics suggest that efforts to reduce crashes at these locations may significantly reduce crash costs. The objective of this paper is to examine factors associated with railroad crossing crashes. Various statistical models are used to examine the relationships between crossing accidents and features of crossings. The paper also compares accident models developed in the United States and the safety effects of crossing elements obtained using Korea data. Crashes were observed to increase with total traffic volume and average daily train volumes. The proximity of crossings to commercial areas and the distance of the train detector from crossings are associated with larger numbers of accidents, as is the time duration between the activation of warning signals and gates. The unique contributions of the paper are the application of the gamma probability model to deal with underdispersion and the insights obtained regarding railroad crossing related vehicle crashes. Considerable past research has explored relationships between vehicle accidents and geometric design and operation of road sections, but relatively little research has examined factors that contribute to accidents at railway-highway crossings. Between 1998 and 2002 in Korea, about 95% of railway accidents occurred at highway-rail grade crossings, resulting in 402 accidents, of which about 20% resulted in fatalities. These statistics suggest that efforts to reduce crashes at these locations may significantly reduce crash costs. The objective of this paper is to examine factors associated with railroad crossing crashes. Various statistical models are used to examine the relationships between crossing accidents and features of crossings. The paper also compares accident models developed in the United States and the safety effects of crossing elements obtained using Korea data. Crashes were observed to increase with total traffic volume and average daily train volumes. The proximity of crossings to commercial areas and the distance of the train detector from crossings are associated with larger numbers of accidents, as is the time duration between the activation of warning signals and gates. The unique contributions of the paper are the application of the gamma probability model to deal with underdispersion and the insights obtained regarding railroad crossing related vehicle crashes.

Development of accident prediction models for rural highway intersections

A study was done to develop macrolevel crash prediction models that can be used to understand and identify effective countermeasures for improving signalized highway intersections and multilane stop-controlled highway intersections in rural areas. Poisson and negative binomial regression models were fit to intersection crash data from Georgia, California, and Michigan. To assess the suitability of the models, several goodness-of-fit measures were computed. The statistical models were then used to shed light on the relationships between crash occurrence and traffic and geometric features of the rural signalized intersections. The results revealed that traffic flow variables significantly affected the overall safety performance of the intersections regardless of intersection type and that the geometric features of intersections varied across intersection type and also influenced crash type.

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.

Morphological investigations of supported titania photocatalysts

Due in no small part to an increasing need to augment existing water purification strategies, the synthesis of titania photocatalysts has been under considerable examination. However, in order to make the use of titania photocatalysts commercially viable there needs to be an increase in the efficiency of the catalysts while decreasing the potential toxicity. Due to its high porosity and novel optical properties, inverse opal titania derived from colloidal crystal templating offers one of the most efficient solutions. While a number of synthesis methods for inverse opal titania have been presented in the literature, the co�]deposition method offers the most effective method of generating the relative large areas of inverse opal material. The factors which affect the codeposition method and the mechanism by which titania inverse opals form in general remain relatively unstudied. This manuscript presents an examination of the morphology of inverse opals generated by the co�]deposition method while proposing a mechanism by which the inverse structures form.

Mechanistic investigations into interactions between IGF-I and IGFBPs and their impact on facilitating cell migration on vitronectin

Numerous studies have reported links between insulin-like growth factors (IGFs) and the extra-cellular matrix protein vitronectin (VN). We ourselves have reported that IGF-I binds to VN via IGF-binding proteins (IGFBPs) to stimulate HaCaT and MCF-7 cell migration. Here, we detail the functional evaluation of IGFBP-1, -2, -3, -4 and -6 in the presence and absence of IGF-I and VN. The data presented here, combined with our prior data on IGFBP-5, suggest that IGFBP-3, -4 and -5 are the most effective at stimulating cell migration in combination with IGF-I and VN. In addition, we demonstrate that different regions within IGFBP-3 and -4 are critical for complex formation. Furthermore, we examine whether multi-protein complexes of IGF-I and IGFBPs associated with fibronectin and collagen IV are also able to enhance functional biological responses.

Young drivers’ optimism bias for accident risk and driving skill : accountability and insight experience manipulations

This study aimed to determine whether two brief, low cost interventions would reduce young drivers’ optimism bias for their driving skills and accident risk perceptions. This tendency for such drivers to perceive themselves as more skilful and less prone to driving accidents than their peers may lead to less engagement in precautionary driving behaviours and a greater engagement in more dangerous driving behaviour. 243 young drivers (aged 17 - 25 years) were randomly allocated to one of three groups: accountability, insight or control. All participants provided both overall and specific situation ratings of their driving skills and accident risk relative to a typical young driver. Prior to completing the questionnaire, those in the accountability condition were first advised that their driving skills and accident risk would be later assessed via a driving simulator. Those in the insight condition first underwent a difficult computer-based hazard perception task designed to provide participants with insight into their potential limitations when responding to hazards in difficult and unpredictable driving situations. Participants in the control condition completed only the questionnaire. Results showed that the accountability manipulation was effective in reducing optimism bias in terms of participants’ comparative ratings of their accident risk in specific situations, though only for less experienced drivers. In contrast, among more experienced males, participants in the insight condition showed greater optimism bias for overall accident risk than their counterparts in the accountability or control groups. There were no effects of the manipulations on drivers’ skills ratings. The differential effects of the two types of manipulations on optimism bias relating to one’s accident risk in different subgroups of the young driver sample highlight the importance of targeting interventions for different levels of experience. Accountability interventions may be beneficial for less experienced young drivers but the results suggest exercising caution with the use of insight type interventions, particularly hazard perception style tasks, for more experienced young drivers typically still in the provisional stage of graduated licensing systems.

Spatiotemporal investigations of DNA damage repair using microbeams

Cellular response to radiation damage is made by a complex network of pathways and feedback loops whose spatiotemporal organisation is still unclear despite its decisive role in determining the fate of the damaged cell. Revealing the dynamic sequence of the repair proteins is therefore critical in understanding how the DNA repair mechanisms work. There are also still open questions regarding the possible movement of damaged chromatin domains and its role as trigger for lesion recognition and signalling in the DNA repair context. The single-cell approach and the high spatial resolution offered by microbeams provide the perfect tool to study and quantify the dynamic processes associated with the induction and repair of DNA damage. We have followed the development of radiation-induced foci for three DNA damage markers (i.e. γ-H2AX, 53BP1 and hSSB1) using normal fibroblasts (AG01522), human breast adenocarcinoma cells (MCF7) and human fibrosarcoma cells (HT1080) stably transfected with yellow fluorescent protein fusion proteins following irradiation with the QUB X-ray microbeam (carbon X-rays <2 µm spot). The size and intensity of the foci has been analysed as a function of dose and time post-irradiation to investigate the dynamics of the above-mentioned DNA repair processes and monitor the remodelling of chromatin structure that the cell undergoes to deal with DNA damage.

Noising around : investigations in mobile learning

In this paper we present an account of children's interactions with a mobile technology prototype within a school context. The Noise Detectives trial was conducted in a school setting with the aim of better understanding the role of mobile technology as a mediator within science learning activities. Over eighty children, aged between ten and twelve, completed an outdoor data gathering activity using a mobile learning prototype that included paper and digital components. They measured and recorded noise levels at a range of locations throughout the schools. We analyzed the activity to determine how the components of the prototype were integrated into the learning activity, and to identify differences in behavior that resulted from using these components. We present design implications that resulted from observed differences in prototype use and appropriation.