International epidemiology of prostate cancer : geographical distribution and secular trends

This review outlines current international patterns in prostate cancer incidence and mortality rates and survival, including recent trends and a discussion of the possible impact of prostate-specific antigen (PSA) testing on the observed data. Internationally, prostate cancer is the second most common cancer diagnosed among men (behind lung cancer), and is the sixth most common cause of cancer death among men. Prostate cancer is particularly prevalent in developed countries such as the United States and the Scandinavian countries, with about a six-fold difference between high-incidence and low-incidence countries. Interpretation of trends in incidence and survival are complicated by the increasing impact of PSA testing, particularly in more developed countries. As Western influences become more pronounced in less developed countries, prostate cancer incidence rates in those countries are tending to increase, even though the prevalence of PSA testing is relatively low. Larger proportions of younger men are being diagnosed with prostate cancer and living longer following diagnosis of prostate cancer, which has many implications for health systems. Decreasing mortality rates are becoming widespread among more developed countries, although it is not clear whether this is due to earlier diagnosis (PSA testing), improved treatment, or some combination of these or other factors.

The effectiveness of using a simple ARIA based geographical classification to identify road crash patterns in rural and urban areas of Queensland

Research has noted a ‘pronounced pattern of increase with increasing remoteness' of death rates in road crashes. However, crash characteristics by remoteness are not commonly or consistently reported, with definitions of rural and urban often relying on proxy representations such as prevailing speed limit. The current paper seeks to evaluate the efficacy of the Accessibility / Remoteness Index of Australia (ARIA+) to identifying trends in road crashes. ARIA+ does not rely on road-specific measures and uses distances to populated centres to attribute a score to an area, which can in turn be grouped into 5 classifications of increasing remoteness. The current paper uses applications of these classifications at the broad level of Australian Bureau of Statistics' Statistical Local Areas, thus avoiding precise crash locating or dedicated mapping software. Analyses used Queensland road crash database details for all 31,346 crashes resulting in a fatality or hospitalisation occurring between 1st July, 2001 and 30th June 2006 inclusive. Results showed that this simplified application of ARIA+ aligned with previous definitions such as speed limit, while also providing further delineation. Differences in crash contributing factors were noted with increasing remoteness such as a greater representation of alcohol and ‘excessive speed for circumstances.' Other factors such as the predominance of younger drivers in crashes differed little by remoteness classification. The results are discussed in terms of the utility of remoteness as a graduated rather than binary (rural/urban) construct and the potential for combining ARIA crash data with census and hospital datasets.

Images of desire : cognitive models of craving

Cognitive modelling of phenomena in clinical practice allows the operationalisation of otherwise diffuse descriptive terms such as craving or flashbacks. This supports the empirical investigation of the clinical phenomena and the development of targeted treatment interventions. This paper focuses on the cognitive processes underpinning craving, which is recognised as a motivating experience in substance dependence. We use a high-level cognitive architecture, Interacting Cognitive Subsystems (ICS), to compare two theories of craving: Tiffany's theory, centred on the control of automated action schemata, and our own Elaborated Intrusion theory of craving. Data from a questionnaire study of the subjective aspects of everyday desires experienced by a large non-clinical population are presented. Both the data and the high-level modelling support the central claim of the Elaborated Intrusion theory that imagery is a key element of craving, providing the subjective experience and mediating much of the associated disruption of concurrent cognition.

Towards an automatic road lane marks extraction based on ISODATA segmentation and shadow detection from large-scale aerial images

The automatic extraction of road features from remote sensed images has been a topic of great interest within the photogrammetric and remote sensing communities for over 3 decades. Although various techniques have been reported in the literature, it is still challenging to efficiently extract the road details with the increasing of image resolution as well as the requirement for accurate and up-to-date road data. In this paper, we will focus on the automatic detection of road lane markings, which are crucial for many applications, including lane level navigation and lane departure warning. The approach consists of four steps: i) data preprocessing, ii) image segmentation and road surface detection, iii) road lane marking extraction based on the generated road surface, and iv) testing and system evaluation. The proposed approach utilized the unsupervised ISODATA image segmentation algorithm, which segments the image into vegetation regions, and road surface based only on the Cb component of YCbCr color space. A shadow detection method based on YCbCr color space is also employed to detect and recover the shadows from the road surface casted by the vehicles and trees. Finally, the lane marking features are detected from the road surface using the histogram clustering. The experiments of applying the proposed method to the aerial imagery dataset of Gympie, Queensland demonstrate the efficiency of the approach.

Taxonomy and diagnostics of fruit fly infesting Opiine Braconids in Australia and the South Pacific

Opiine wasps (Hymenoptera: Braconidae: Opiinae) are parasitoids of dacine fruit flies (Diptera: Tephritidae: Dacinae), the primary horticultural pests of Australia and the South Pacific. Effective use of opiines for biological control of fruit flies is limited by poor taxonomy and identification difficulties. To overcome these problems, this thesis had two aims: (i) to carry out traditional taxonomic research on the fruit fly infesting opine braconids of Australia and the South Pacific; and (ii) to transfer the results of the taxonomic research into user friendly diagnostic tools. Curated wasp material was borrowed from all major Australian museum collections holding specimens. This was supplemented by a large body of material gathered as part of a major fruit fly project in Papua New Guinea: nearly 4000 specimens were examined and identified. Each wasp species was illustrated using traditional scientific drawings, full colour photomicroscopy and scanning electron microscopy. An electronic identification key was developed using Lucid software and diagnostic images were loaded on the web-based Pest and Diseases Image Library (PaDIL). A taxonomic synopsis and distribution and host records for each of the 15 species of dacine-parasitising opiine braconids found in the South Pacific is presented. Biosteres illusorius Fischer (1971) was formally transferred to the genus Fopius and a new species, Fopius ferrari Carmichael and Wharton (2005), was described. Other species dealt with were Diachasmimorpha hageni (Fullaway, 1952), D. kraussii (Fullaway, 1951), D. longicaudata (Ashmead, 1905), D. tryoni (Cameron, 1911), Fopius arisanus (Sonan, 1932), F. deeralensis (Fullaway, 1950), F. schlingeri Wharton (1999), Opius froggatti Fullaway (195), Psyttalia fijiensis (Fullaway, 1936), P. muesebecki (Fischer, 1963), P. novaguineensis (Szépliget, 1900i) and Utetes perkinsi (Fullaway, 1950). This taxonomic component of the thesis has been formally published in the scientific literature. An interactive diagnostics package (“OpiineID”) was developed, the centre of which is a Lucid based multi-access key. Because the diagnostics package is computer based, without the space limitations of the journal publication, there is no pictorial limit in OpiineID and so it is comprehensively illustrated with SEM photographs, full colour photographs, line drawings and fully rendered illustrations. The identification key is only one small component of OpiineID and the key is supported by fact sheets with morphological descriptions, host associations, geographical information and images. Each species contained within the OpiineID package has also been uploaded onto the PaDIL website (www.padil.gov.au). Because the identification of fruit fly parasitoids is largely of concern to fruit fly workers, rather than braconid specialists, this thesis deals directly with an area of growing importance to many areas of pure and applied biology; the nexus between taxonomy and diagnostics. The Discussion chapter focuses on this area, particularly the opportunities offered by new communication and information tools as new ways delivering the outputs of taxonomic science.

Automated road pavement marking detection from high resolution aerial images based on Multi-resolution image analysis and anisotropic Gaussian filtering

Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.