Occupational Health and Safety, Courts and Crime: the legal construction of occupational health and safety offences in Victoria

This book reports on an empirically-based study of the manner in which the Magistrates' Courts in Victoria, construct occupational health and safety (OHS) issues when hearing prosecutions for offences under the Victorian OHS legislation. Prosecution has always been a controversial element in the enforcement armoury of OHS regulators, but at the same time it has long been argued that the low level of fines imposed by courts has had an important chilling effect on the OHS inspectorate's enforcement approaches, and on the impact of OHS legislation. Using a range of empirical research methods, including three samples of OHS prosecutions carried out in the Victorian Magistrates' Courts, Professor Johnstone shows how courts, inspectors, prosecutors and defence counsel are involved in filtering or reshaping OHS issues during the prosecution process, both pre-trial and in court. He argues that OHS offences are constructed by focusing on "events", in most cases incidents resulting in injury or death. This "event-focus" ensures that the attention of the parties is drawn to the details of the incident, and away from the broader context of the event. During the court-based sentencing process defence counsel is able to adopt a range of techniques which isolate the incident from its micro and macro contexts, thereby individualising and decontextualising the incident.

An examination of Saudi high school teachers' ICT knowledge and implementation

This study investigated Saudi high school teachers' implementation of ICT in schools. The study also explored the relationship between the teachers' level of TPACK and their implementation of ICT. In the first phase of the study, more than 250 Saudi teachers from Al-Madinah administrative area filled in a four-part self reported questionnaire while in the second, 12 teachers completed semi-structured interviews. Findings from both phases of the study revealed that Saudi high school teachers demonstrated low level of effectiveness of ICT implementation. Among a number of barriers, Teachers' TPACK knowledge was found as the best predictor of the effectiveness of ICT implementation.

Impact of simulated hyperopia on academic-related performance in children

Purpose: To investigate the impact of simulated hyperopia and sustained near work on children’s ability to perform a range of academic-related tasks. Methods: Fifteen visually normal children (mean age: 10.9 ± 0.8 years; 10 males and 5 females) were recruited. Performance on a range of standardised academic-related outcome measures was assessed with and without 2.50 D of simulated bilateral hyperopia (administered in a randomised order), before and after 20 minutes of sustained near work, at two separate testing sessions. Academic-related measures included a standardised reading test (the Neale Analysis of Reading Ability), visual information processing tests (Coding and Symbol Search subtests from the Wechsler Intelligence Scale for Children) and a reading-related eye movement test (the Developmental Eye Movement test). Results: Simulated bilateral hyperopia and sustained near work each independently impaired reading, visual information processing and reading-related eye movement performance (p<0.001). A significant interaction was also demonstrated between these factors (p<0.001), with the greatest decrement in performance observed when simulated hyperopia was combined with sustained near work. This combination resulted in performance reductions of between 5% and 24% across the range of academic-related measures. A significant moderate correlation was also found between the change in horizontal near heterophoria and the change in several of the academic-related outcome measures, following the addition of simulated hyperopia. Conclusions: A relatively low level of simulated bilateral hyperopia impaired children’s performance on a range of academic–related outcome measures, with sustained near work further exacerbating this effect. Further investigations are required to determine the impact of correcting low levels of hyperopia on academic performance in children.

Coding livecoding

Livecoding is an artistic programming practice in which an artist's low-level interaction can be observed with sufficiently high fidelity to allow for transcription and analysis. This paper presents the first reported" coding" of livecoding videos. From an identified corpus of videos available on the web, we coded performances of two different livecoding artists, recording both the (textual) programming edit events and the musical effect of these edits.

Towards universal search design

For people with cognitive disabilities, technology is more often thought of as a support mechanism, rather than a source of division that may require intervention to equalize access across the cognitive spectrum. This paper presents a first attempt at formalizing the digital gap created by the generalization of search engines. This was achieved through the development of a mapping of cognitive abilities required by users to execute low- level tasks during a standard Web search task. The mapping demonstrates how critical these abilities are to successfully use search engines with an adequate level of independence. It will lead to a set of design guidelines for search engine interfaces that will allow for the engagement of users of all abilities, and also, more importantly, in search algorithms such as query suggestion and measure of relevance (i.e. ranking).

Relevance feature discovery for text mining

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of large scale terms and data patterns. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, there has been often held the hypothesis that pattern-based methods should perform better than term-based ones in describing user preferences; yet, how to effectively use large scale patterns remains a hard problem in text mining. To make a breakthrough in this challenging issue, this paper presents an innovative model for relevance feature discovery. It discovers both positive and negative patterns in text documents as higher level features and deploys them over low-level features (terms). It also classifies terms into categories and updates term weights based on their specificity and their distributions in patterns. Substantial experiments using this model on RCV1, TREC topics and Reuters-21578 show that the proposed model significantly outperforms both the state-of-the-art term-based methods and the pattern based methods.

Shape up or ship out : can we enhance productivity in coastal aquaculture to compete with other uses?

Coastal resources are coming under increasing pressure from competition between recreational, commercial and conservation uses. This is particularly so in coastal areas adjacent to major population centres. Given high recreational and conservation values in such areas, economic activities need to be highly efficient in order to persist. Management of these industries must therefore also encourage efficient production and full utilisation of the areas available. In order to achieve this, managers must first understand the level and drivers of productivity, and how these can be influenced. In this study, by way of illustration, the focus was on the Sydney rock oyster industry within Queensland's Moreton Bay, a multiple use marine park with high recreational and conservation value adjacent to Australia's third largest city. Productivity of the oyster industry in Moreton Bay is currently low compared to historic levels, and management has an objective of reversing this trend. It is unclear whether this difference is due to oyster farmers' business choices and personal characteristics or whether varying environmental conditions in the Moreton Bay limit the capacity of the oyster industry. These require different management responses in order to enhance productivity. The study examined different productivity measures of the oyster industry using data envelopment analysis (DEA) to determine where productivity gains can be made and by how much. The findings suggest that the industry is operating at a high level of capacity utilisation, but a low level of efficiency. The results also suggest that both demographic and environmental conditions affect technical efficiency in the Bay, with water characteristics improvements and appropriate training potentially providing the greatest benefits to the industry. Methods used in this study are transferable to other industries and provide a means by which coastal aquaculture may be managed to ensure it remains competitive with other uses of coastal resources.

Risk factors for delayed healing in venous leg ulcers : a review of the literature

Background Chronic leg ulcers, remaining unhealed after 4–6 weeks, affect 1-3% of the population, with treatment costly and health service resource intensive. Venous disease contributes to approximately 70% of all chronic leg ulcers and these ulcers are often associated with pain, reduced mobility and a decreased quality of life. Despite evidence-based care, 30% of these ulcers are unlikely to heal within a 24-week period and therefore the recognition and identification of risk factors for delayed healing of venous leg ulcers would be beneficial. Aim To review the available evidence on risk factors for delayed healing of venous leg ulcers. Methods: A review of the literature in regard to risk factors for delayed healing in venous leg ulcers was conducted from January 2000 to December 2013. Evidence was sourced through searches of relevant databases and websites for resources addressing risk factors for delayed healing in venous leg ulcers specifically. Results Twenty-seven studies, of mostly low-level evidence (Level III and IV), identified risk factors associated with delayed healing. Risk factors that were consistently identified included: larger ulcer area, longer ulcer duration, a previous history of ulceration, venous abnormalities and lack of high compression. Additional potential predictors with inconsistent or varying evidence to support their influence on delayed healing of venous leg ulcers included decreased mobility and/or ankle range of movement, poor nutrition and increased age. Discussion Findings from this review indicate that a number of physiological risk factors are asso- ciated with delayed healing in venous leg ulcers and that social and/or psychological risk factors should also be considered and examined further. Conclusion The findings from this review can assist health professionals to identify prognostic indicators or risk factors significantly associated with delayed healing in venous leg ulcers. This will facilitate realistic outcome planning and inform implementation of appropriate early strategies to promote healing.

Curiosity driven reinforcement learning for motion planning on humanoids

Most previous work on artificial curiosity (AC) and intrinsic motivation focuses on basic concepts and theory. Experimental results are generally limited to toy scenarios, such as navigation in a simulated maze, or control of a simple mechanical system with one or two degrees of freedom. To study AC in a more realistic setting, we embody a curious agent in the complex iCub humanoid robot. Our novel reinforcement learning (RL) framework consists of a state-of-the-art, low-level, reactive control layer, which controls the iCub while respecting constraints, and a high-level curious agent, which explores the iCub's state-action space through information gain maximization, learning a world model from experience, controlling the actual iCub hardware in real-time. To the best of our knowledge, this is the first ever embodied, curious agent for real-time motion planning on a humanoid. We demonstrate that it can learn compact Markov models to represent large regions of the iCub's configuration space, and that the iCub explores intelligently, showing interest in its physical constraints as well as in objects it finds in its environment.

In silico biology : making the most of parallel computing

Biological systems are typically complex and adaptive, involving large numbers of entities, or organisms, and many-layered interactions between these. System behaviour evolves over time, and typically benefits from previous experience by retaining memory of previous events. Given the dynamic nature of these phenomena, it is non-trivial to provide a comprehensive description of complex adaptive systems and, in particular, to define the importance and contribution of low-level unsupervised interactions to the overall evolution process. In this chapter, the authors focus on the application of the agent-based paradigm in the context of the immune response to HIV. Explicit implementation of lymph nodes and the associated lymph network, including lymphatic chain structure, is a key objective, and requires parallelisation of the model. Steps taken towards an optimal communication strategy are detailed.

Template-based circuit understanding

When verifying or reverse-engineering digital circuits, one often wants to identify and understand small components in a larger system. A possible approach is to show that the sub-circuit under investigation is functionally equivalent to a reference implementation. In many cases, this task is difficult as one may not have full information about the mapping between input and output of the two circuits, or because the equivalence depends on settings of control inputs. We propose a template-based approach that automates this process. It extracts a functional description for a low-level combinational circuit by showing it to be equivalent to a reference implementation, while synthesizing an appropriate mapping of input and output signals and setting of control signals. The method relies on solving an exists/forall problem using an SMT solver, and on a pruning technique based on signature computation.

Development of a cost-effective and flexible vibration DAQ system for long-term continuous structural health monitoring

In the structural health monitoring (SHM) field, long-term continuous vibration-based monitoring is becoming increasingly popular as this could keep track of the health status of structures during their service lives. However, implementing such a system is not always feasible due to on-going conflicts between budget constraints and the need of sophisticated systems to monitor real-world structures under their demanding in-service conditions. To address this problem, this paper presents a comprehensive development of a cost-effective and flexible vibration DAQ system for long-term continuous SHM of a newly constructed institutional complex with a special focus on the main building. First, selections of sensor type and sensor positions are scrutinized to overcome adversities such as low-frequency and low-level vibration measurements. In order to economically tackle the sparse measurement problem, a cost-optimized Ethernet-based peripheral DAQ model is first adopted to form the system skeleton. A combination of a high-resolution timing coordination method based on the TCP/IP command communication medium and a periodic system resynchronization strategy is then proposed to synchronize data from multiple distributed DAQ units. The results of both experimental evaluations and experimental–numerical verifications show that the proposed DAQ system in general and the data synchronization solution in particular work well and they can provide a promising cost-effective and flexible alternative for use in real-world SHM projects. Finally, the paper demonstrates simple but effective ways to make use of the developed monitoring system for long-term continuous structural health evaluation as well as to use the instrumented building herein as a multi-purpose benchmark structure for studying not only practical SHM problems but also synchronization related issues.

Towards robust automatic affective classification of images using facial expressions for practical applications

Affect is an important feature of multimedia content and conveys valuable information for multimedia indexing and retrieval. Most existing studies for affective content analysis are limited to low-level features or mid-level representations, and are generally criticized for their incapacity to address the gap between low-level features and high-level human affective perception. The facial expressions of subjects in images carry important semantic information that can substantially influence human affective perception, but have been seldom investigated for affective classification of facial images towards practical applications. This paper presents an automatic image emotion detector (IED) for affective classification of practical (or non-laboratory) data using facial expressions, where a lot of “real-world” challenges are present, including pose, illumination, and size variations etc. The proposed method is novel, with its framework designed specifically to overcome these challenges using multi-view versions of face and fiducial point detectors, and a combination of point-based texture and geometry. Performance comparisons of several key parameters of relevant algorithms are conducted to explore the optimum parameters for high accuracy and fast computation speed. A comprehensive set of experiments with existing and new datasets, shows that the method is effective despite pose variations, fast, and appropriate for large-scale data, and as accurate as the method with state-of-the-art performance on laboratory-based data. The proposed method was also applied to affective classification of images from the British Broadcast Corporation (BBC) in a task typical for a practical application providing some valuable insights.

No acute and persistent DNA damage after an Ironman triathlon

During acute and strenuous exercise, the enhanced formation of reactive oxygen species can induce damage to lipids, proteins, and nucleic acids. The aim of this study was to investigate the effect of an Ironman triathlon (3.8 km swim, 180 km cycle, 42 km run), as a prototype of ultra-endurance exercise, on DNA stability. As biomarkers of genomic instability, the number of micronuclei, nucleoplasmic bridges, and nuclear buds were measured within the cytokinesis-block micronucleus cytome assay in once-divided peripheral lymphocytes of 20 male triathletes. Blood samples were taken 2 days before, within 20 min after the race, and 5 and 19 days post-race. Overall, the number of micronuclei decreased (P < 0.05) after the race, remained at a low level until 5 days post-race, and declined further to 19 days post-race (P < 0.01). The frequency of nucleoplasmic bridges and nuclear buds did not change immediately after the triathlon. The number of nucleoplasmic bridge declined from 2 days pre-race to 19 days post-exercise (P < 0.05). The frequency of nuclear buds increased after the triathlon, peaking 5 days post-race (P < 0.01) and decreased to basic levels 19 days after the race (P < 0.01). The results suggest that an Ironman triathlon does not cause long-lasting DNA damage in well-trained athletes.

The presence of executive deficits in patients with Obstructive Sleep Apnoea

Obstructive sleep apnoea (OSA) is a chronic condition in which the upper airways collapse repeatedly during sleep, completely or partially obstructing breathing. This obstruction leads to chronic intermittent hypoxia and severe sleep fragmentation, disrupting the restorative functions of sleep. Beebe and Gozal (2002)a developed a theory which hypothesises that disruption of the restorative functions of sleep lead to a chronic low level brain damage most evident in executive functions (EF). Neuropsychological testing of EF, volumetric MRI, magnetic resonance spectroscopy, event related potentials and CSF biomarkers all provide support for this theory. Little research has been done to explore the nature of the subjective complaint and it’s impact on the activities of daily living.