Experimental evaluation of hotspot identification methods

Identifying crash “hotspots”, “blackspots”, “sites with promise”, or “high risk” locations is standard practice in departments of transportation throughout the US. The literature is replete with the development and discussion of statistical methods for hotspot identification (HSID). Theoretical derivations and empirical studies have been used to weigh the benefits of various HSID methods; however, a small number of studies have used controlled experiments to systematically assess various methods. Using experimentally derived simulated data—which are argued to be superior to empirical data, three hot spot identification methods observed in practice are evaluated: simple ranking, confidence interval, and Empirical Bayes. Using simulated data, sites with promise are known a priori, in contrast to empirical data where high risk sites are not known for certain. To conduct the evaluation, properties of observed crash data are used to generate simulated crash frequency distributions at hypothetical sites. A variety of factors is manipulated to simulate a host of ‘real world’ conditions. Various levels of confidence are explored, and false positives (identifying a safe site as high risk) and false negatives (identifying a high risk site as safe) are compared across methods. Finally, the effects of crash history duration in the three HSID approaches are assessed. The results illustrate that the Empirical Bayes technique significantly outperforms ranking and confidence interval techniques (with certain caveats). As found by others, false positives and negatives are inversely related. Three years of crash history appears, in general, to provide an appropriate crash history duration.

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.

The influence of underreported crashes on hotspot identification

Hot spot identification (HSID) plays a significant role in improving the safety of transportation networks. Numerous HSID methods have been proposed, developed, and evaluated in the literature. The vast majority of HSID methods reported and evaluated in the literature assume that crash data are complete, reliable, and accurate. Crash under-reporting, however, has long been recognized as a threat to the accuracy and completeness of historical traffic crash records. As a natural continuation of prior studies, the paper evaluates the influence that under-reported crashes exert on HSID methods. To conduct the evaluation, five groups of data gathered from Arizona Department of Transportation (ADOT) over the course of three years are adjusted to account for fifteen different assumed levels of under-reporting. Three identification methods are evaluated: simple ranking (SR), empirical Bayes (EB) and full Bayes (FB). Various threshold levels for establishing hotspots are explored. Finally, two evaluation criteria are compared across HSID methods. The results illustrate that the identification bias—the ability to correctly identify at risk sites--under-reporting is influenced by the degree of under-reporting. Comparatively speaking, crash under-reporting has the largest influence on the FB method and the least influence on the SR method. Additionally, the impact is positively related to the percentage of the under-reported PDO crashes and inversely related to the percentage of the under-reported injury crashes. This finding is significant because it reveals that despite PDO crashes being least severe and costly, they have the most significant influence on the accuracy of HSID.

Of ivory towers and boundary spanners

We all live in a yellow submarine… When I go to work in the morning, in the office building that hosts our BPM research group, on the way up to our level I come by this big breakout room that hosts a number of computer scientists, working away at the next generation software algorithms and iPad applications (I assume). I have never actually been in that room, but every now and then the door is left ajar for a while and I can spot couches, lots (I mean, lots!) of monitors, the odd scientist, a number of Lara Croft posters, and the usual room equipment you’d probably expect from computer scientists (and, no, it’s not like that evil Dennis guy from the Jurassic Park movie, buried in chips, coke, and flickering code screens… It’s also not like the command room from the Nebuchadnezzar, Neo’s hovercraft in the Matrix movies, although I still strongly believe these green lines of code make a good screensaver).

Proactive detection of high collision concentration locations on highways

In previous research (Chung et al., 2009), the potential of the continuous risk profile (CRP) to proactively detect the systematic deterioration of freeway safety levels was presented. In this paper, this potential is investigated further, and an algorithm is proposed for proactively detecting sites where the collision rate is not sufficiently high to be classified as a high collision concentration location but where a systematic deterioration of safety level is observed. The approach proposed compares the weighted CRP across different years and uses the cumulative sum (CUSUM) algorithm to detect the sites where changes in collision rate are observed. The CRPs of the detected sites are then compared for reproducibility. When high reproducibility is observed, a growth factor is used for sequential hypothesis testing to determine if the collision profiles are increasing over time. Findings from applying the proposed method using empirical data are documented in the paper together with a detailed description of the method.

Using operations research methodologies to improve operating theatre scheduling

A hospital consists of a number of wards, units and departments that provide a variety of medical services and interact on a day-to-day basis. Nearly every department within a hospital schedules patients for the operating theatre (OT) and most wards receive patients from the OT following post-operative recovery. Because of the interrelationships between units, disruptions and cancellations within the OT can have a flow-on effect to the rest of the hospital. This often results in dissatisfied patients, nurses and doctors, escalating waiting lists, inefficient resource usage and undesirable waiting times. The objective of this study is to use Operational Research methodologies to enhance the performance of the operating theatre by improving elective patient planning using robust scheduling and improving the overall responsiveness to emergency patients by solving the disruption management and rescheduling problem. OT scheduling considers two types of patients: elective and emergency. Elective patients are selected from a waiting list and scheduled in advance based on resource availability and a set of objectives. This type of scheduling is referred to as ‘offline scheduling’. Disruptions to this schedule can occur for various reasons including variations in length of treatment, equipment restrictions or breakdown, unforeseen delays and the arrival of emergency patients, which may compete for resources. Emergency patients consist of acute patients requiring surgical intervention or in-patients whose conditions have deteriorated. These may or may not be urgent and are triaged accordingly. Most hospitals reserve theatres for emergency cases, but when these or other resources are unavailable, disruptions to the elective schedule result, such as delays in surgery start time, elective surgery cancellations or transfers to another institution. Scheduling of emergency patients and the handling of schedule disruptions is an ‘online’ process typically handled by OT staff. This means that decisions are made ‘on the spot’ in a ‘real-time’ environment. There are three key stages to this study: (1) Analyse the performance of the operating theatre department using simulation. Simulation is used as a decision support tool and involves changing system parameters and elective scheduling policies and observing the effect on the system’s performance measures; (2) Improve viability of elective schedules making offline schedules more robust to differences between expected treatment times and actual treatment times, using robust scheduling techniques. This will improve the access to care and the responsiveness to emergency patients; (3) Address the disruption management and rescheduling problem (which incorporates emergency arrivals) using innovative robust reactive scheduling techniques. The robust schedule will form the baseline schedule for the online robust reactive scheduling model.

Opinions, attitudes and driving experiences of car and racing "enthusiasts" : results of the Ontario Car and Racing Club Survey

In recent years, car club and racing websites and forums have become an increasingly popular way for car enthusiasts to access racing and car club news, chat-rooms and message boards. However, no North American research has been found that has examined opinions and driving experiences of car and racing enthusiasts. The purpose of this study was to examine car club members’ opinions about and experiences with various aspects of driving, road safety and traffic legislation, with a particular focus on street racing. A web-based questionnaire (Survey Monkey) was developed using the expert panel method and was primarily based on validated instruments or questions that were developed from other surveys. The questionnaire included: 1) driver concerns regarding traffic safety issues and legislation; 2) attitudes regarding various driving activities; 3) leisure-time activities, including club activities; 4) driving experiences, including offences and collisions; and 5) socio-demographic questions. The survey was pre- tested and piloted. Electronic information letters were sent out to an identified list of car clubs and forums situated in southern Ontario. Car club participants were invited to fill out the questionnaire. This survey found that members of car clubs share similar concerns regarding various road safety issues with samples of Canadian drivers, although a smaller percentage of car club members are concerned about speeding-related driving. Car club members had varied opinions regarding Ontario’s Street Racers, Stunt and Aggressive Drivers Legislation. The respondents agreed the most with the new offences regarding not sitting in the driver’s seat, having a person in the trunk, or driving as close as possible to another vehicle, pedestrian or object on or near the highway without a reason. The majority disagreed with police powers of impoundment and on-the-spot licence suspensions. About three quarters of respondents reported no collisions or police stops for traffic offences in the past five years. Of those who had been stopped, the most common offence was reported as speeding. This study is the first in Canada to examine car club members’ opinions about and experiences with various aspects of driving, road safety and traffic legislation. Given the ubiquity of car clubs and fora in Canada, insights on members’ opinions and practices provide important information to road safety researchers.

People, content, location : sweet spotting urban screens for situated engagement

A growing body of research is looking at ways to bring the processes and benefits of online deliberation to the places they are about and in turn allow a larger, targeted proportion of the urban public to have a voice, be heard, and engage in questions of city planning and design. Seeking to take advantage of the civic opportunities of situated engagement through public screens and mobile devices, our research informed a public urban screen content application DIS that we deployed and evaluated in a wide range of real world public and urban environments. For example, it is currently running on the renowned urban screen at Federation Square in Melbourne. We analysed the data from these user studies within a conceptual framework that positions situated engagement across three key parameters: people, content, and location. We propose a way to identify the sweet spot within the nexus of these parameters to help deploy and run interactive systems to maximise the quality of the situated engagement for civic and related deliberation purposes.

UHT milk contains multiple forms of αS1-casein that undergo degradative changes during storage

Milk proteins are susceptible to chemical changes during processing and storage. We used proteomic tools to analyse bovine αS1-casein in UHT milk. 2-D gels of freshly processed milk αS1-casein was presented as five or more spots due to genetic polymorphism and variable phosphorylation. MS analysis after phosphopeptide enrichment allowed discrimination between phosphorylation states and genetic variants. We identified a new alternatively-spliced isoform with a deletion of exon 17, producing a new C-terminal sequence, K164SQVNSEGLHSYGL177, with a novel phosphorylation site at S174. Storage of UHT milk at elevated temperatures produced additional, more acidic αS1-casein spots on the gels and decreased the resolution of minor forms. MS analysis indicated that non-enzymatic deamidation and loss of the N-terminal dipeptide were the major contributors to the changing spot pattern. These results highlight the important role of storage temperature in the stability of milk proteins and the utility of proteomic techniques for analysis of proteins in food.

Empirical evaluation of alternative approaches in identifying crash hot spots

This study proposes a framework of a model-based hot spot identification method by applying full Bayes (FB) technique. In comparison with the state-of-the-art approach [i.e., empirical Bayes method (EB)], the advantage of the FB method is the capability to seamlessly integrate prior information and all available data into posterior distributions on which various ranking criteria could be based. With intersection crash data collected in Singapore, an empirical analysis was conducted to evaluate the following six approaches for hot spot identification: (a) naive ranking using raw crash data, (b) standard EB ranking, (c) FB ranking using a Poisson-gamma model, (d) FB ranking using a Poisson-lognormal model, (e) FB ranking using a hierarchical Poisson model, and (f) FB ranking using a hierarchical Poisson (AR-1) model. The results show that (a) when using the expected crash rate-related decision parameters, all model-based approaches perform significantly better in safety ranking than does the naive ranking method, and (b) the FB approach using hierarchical models significantly outperforms the standard EB approach in correctly identifying hazardous sites.

Fusion of morphological images for airborne target detection

Several track-before-detection approaches for image based aircraft detection have recently been examined in an important automated aircraft collision detection application. A particularly popular approach is a two stage processing paradigm which involves: a morphological spatial filter stage (which aims to emphasize the visual characteristics of targets) followed by a temporal or track filter stage (which aims to emphasize the temporal characteristics of targets). In this paper, we proposed new spot detection techniques for this two stage processing paradigm that fuse together raw and morphological images or fuse together various different morphological images (we call these approaches morphological reinforcement). On the basis of flight test data, the proposed morphological reinforcement operations are shown to offer superior signal to-noise characteristics when compared to standard spatial filter options (such as the close-minus-open and adaptive contour morphological operations). However, system operation characterised curves, which examine detection verses false alarm characteristics after both processing stages, illustrate that system performance is very data dependent.

HIV-1 subtype C Pr55gag virus-like particle vaccine efficiently boosts baboons primed with a matched DNA vaccine

A DNA vaccine expressing human immunodeficiency virus type 1 (HIV-1) southern African subtype C Gag (pTHGag) and a recombinant baculovirus Pr55gag virus-like particle prepared using a subtype C Pr55gag protein (Gag VLP) was tested in a prime-boost inoculation regimen in Chacma baboons. The response of five baboons to Gag peptides in a gamma interferon (IFN-γ) enzyme-linked immunospot (ELISPOT) assay after three pTHGag immunizations ranged from 100 to 515 spot-forming units (s.f.u.) per 106 peripheral blood mononuclear cells (PBMCs), whilst the response of two baboons to the Gag VLP vaccine ranged from 415 to 465 s.f.u. per 106 PBMCs. An increase in the Gag-specific response to a range of 775-3583 s.f.u. per 106 PBMCs was achieved by boosting with Gag VLPs the five baboons that were primed with pTHGag. No improvement in Gag responses was achieved in this prime-boost inoculation regimen by increasing the number of pTHGag inoculations to six. IFN-γ responses were mapped to several peptides, some of which have been reported to be targeted by PBMCs from HIV-1 subtype C-infected individuals. Gag VLPs, given as a single-modality regimen, induced a predominantly CD8+ T-cell IFN-γ response and interleukin-2 was a major cytokine within a mix of predominantly Th1 cytokines produced by a DNA-VLP prime-boost modality. The prime-boost inoculation regimen induced high serum p24 antibody titres in all baboons, which were several fold above that induced by the individual vaccines. Overall, this study demonstrated that these DNA prime/VLP boost vaccine regimens are highly immunogenic in baboons, inducing high-magnitude and broad multifunctional responses, providing support for the development of these products for clinical trials. © 2008 SGM.

Self-assembled hyperbranched polymer - gold nanoparticle hybrids : understanding the effect of polymer coverage on assembly size and SERS performance

In the past few years, remarkable progress has been made in unveiling novel and unique optical properties of strongly coupled plasmonic nanostructures. However, application of such plasmonic nanostructures in biomedicine remains challenging due to the lack of facile and robust assembly methods for producing stable nanostructures. Previous attempts to achieve plasmonic nano-assemblies using molecular ligands were limited due to the lack of flexibility that could be exercised in forming them. Here, we report the utilization of tailor-made hyperbranched polymers (HBP) as linkers to assemble gold nanoparticles (NPs) into nano-assemblies. The ease and flexibility in tuning the particle size and number of branch ends of a HBP makes it an ideal candidate as a linker, as opposed to DNA, small organic molecules and linear or dendrimeric polymers. We report a strong correlation of polymer (HBP) concentration with the size of the hybrid nano-assemblies and “hot-spot” density. We have shown that such solutions of stable HBP-gold nano-assemblies can be barcoded with various Raman tags to provide improved surface-enhanced Raman scattering (SERS) compared with non-aggregated NP systems. These Raman barcoded hybrid nano-assemblies, with further optimization of NP shape, size and “hot-spot” density, may find application as diagnostic tools in nanomedicine.

Planar radial spots in a three-component FitzHugh-Nagumo system

Localized planar patterns arise in many reaction-diffusion models. Most of the paradigm equations that have been studied so far are two-component models. While stationary localized structures are often found to be stable in such systems, travelling patterns either do not exist or are found to be unstable. In contrast, numerical simulations indicate that localized travelling structures can be stable in three-component systems. As a first step towards explaining this phenomenon, a planar singularly perturbed three-component reaction-diffusion system that arises in the context of gas-discharge systems is analysed in this paper. Using geometric singular perturbation theory, the existence and stability regions of radially symmetric stationary spot solutions are delineated and, in particular, stable spots are shown to exist in appropriate parameter regimes. This result opens up the possibility of identifying and analysing drift and Hopf bifurcations, and their criticality, from the stationary spots described here.

Learning personalized tag ontology from user tagging information

The cross-sections of the Social Web and the Semantic Web has put folksonomy in the spot light for its potential in overcoming knowledge acquisition bottleneck and providing insight for "wisdom of the crowds". Folksonomy which comes as the results of collaborative tagging activities has provided insight into user's understanding about Web resources which might be useful for searching and organizing purposes. However, collaborative tagging vocabulary poses some challenges since tags are freely chosen by users and may exhibit synonymy and polysemy problem. In order to overcome these challenges and boost the potential of folksonomy as emergence semantics we propose to consolidate the diverse vocabulary into a consolidated entities and concepts. We propose to extract a tag ontology by ontology learning process to represent the semantics of a tagging community. This paper presents a novel approach to learn the ontology based on the widely used lexical database WordNet. We present personalization strategies to disambiguate the semantics of tags by combining the opinion of WordNet lexicographers and users’ tagging behavior together. We provide empirical evaluations by using the semantic information contained in the ontology in a tag recommendation experiment. The results show that by using the semantic relationships on the ontology the accuracy of the tag recommender has been improved.