Safe Design Project : Review of occupational health and safety legal requirements for designers, manufacturers, suppliers, importers and other relevant obligation bearers

In seeking to achieve Australian workplaces free from injury and disease NOHSC works to lead and coordinate national efforts to prevent workplace death, injury and disease. We seek to achieve our mission through the quality and relevance of information we provide and to influence the activities of all parties with roles in improving Australia’s OHS performance. NOHSC has five strategic objectives: • improving national data systems and analysis, • improving national access to OHS information, • improving national components of the OHS and related regulatory framework, • facilitating and coordinating national OHS research efforts, • monitoring progress against the National OHS Improvement Framework. This publication is a contribution to achieving those objectives

Anomaly detection in online social networks : using data-mining techniques and fuzzy logic

This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

Spatial and temporal variability in a residual soil profile

It is well understood that that there is variation inherent in all testing techniques, and that all soil and rock materials also contain some degree of natural variability. Less consideration is normally given to variation associated with natural material heterogeneity within a site, or the relative condition of the material at the time of testing. This paper assesses the impact of spatial and temporal variability upon repeated insitu testing of a residual soil and rock profile present within a single residential site over a full calendar year, and thus range of seasonal conditions. From this repeated testing, the magnitude of spatial and temporal variation due to seasonal conditions has demonstrated that, depending on the selected location and moisture content of the subsurface at the time of testing, up to a 35% variation within the test results can be expected. The results have also demonstrated that the completed insitu test technique has a similarly large measurement and inherent variability error and, for the investigated site, up to a 60% variation in normalised results was observed. From these results, it is recommended that the frequency and timing of insitu tests should be considered when deriving geotechnical design parameters from a limited data set.

A data mining based method for discovery of web services and their compositions

Due to the availability of huge number of web services, finding an appropriate Web service according to the requirements of a service consumer is still a challenge. Moreover, sometimes a single web service is unable to fully satisfy the requirements of the service consumer. In such cases, combinations of multiple inter-related web services can be utilised. This paper proposes a method that first utilises a semantic kernel model to find related services and then models these related Web services as nodes of a graph. An all-pair shortest-path algorithm is applied to find the best compositions of Web services that are semantically related to the service consumer requirement. The recommendation of individual and composite Web services composition for a service request is finally made. Empirical evaluation confirms that the proposed method significantly improves the accuracy of service discovery in comparison to traditional keyword-based discovery methods.

Hydrological consequences of land-cover change: Quantifying the influence of plants on soil moisture with time-lapse electrical resistivity

Electrical resistivity of soils and sediments is strongly influenced by the presence of interstitial water. Taking advantage of this dependency, electrical-resistivity imaging (ERI) can be effectively utilized to estimate subsurface soil-moisture distributions. The ability to obtain spatially extensive data combined with time-lapse measurements provides further opportunities to understand links between land use and climate processes. In natural settings, spatial and temporal changes in temperature and porewater salinity influence the relationship between soil moisture and electrical resistivity. Apart from environmental factors, technical, theoretical, and methodological ambiguities may also interfere with accurate estimation of soil moisture from ERI data. We have examined several of these complicating factors using data from a two-year study at a forest-grassland ecotone, a boundary between neighboring but different plant communities.At this site, temperature variability accounts for approximately 20-45 of resistivity changes from cold winter to warm summer months. Temporal changes in groundwater conductivity (mean=650 S/cm =57.7) and a roughly 100-S/cm spatial difference between the forest and grassland had only a minor influence on the moisture estimates. Significant seasonal fluctuations in temperature and precipitation had negligible influence on the basic measurement errors in data sets. Extracting accurate temporal changes from ERI can be hindered by nonuniqueness of the inversion process and uncertainties related to time-lapse inversion schemes. The accuracy of soil moisture obtained from ERI depends on all of these factors, in addition to empirical parameters that define the petrophysical soil-moisture/resistivity relationship. Many of the complicating factors and modifying variables to accurately quantify soil moisture changes with ERI can be accounted for using field and theoretical principles.

Normative requirements for regulatory compliance: An abstract formal framework

By definition, regulatory rules (in legal context called norms) intend to achieve specific behaviour from business processes, and might be relevant to the whole or part of a business process. They can impose conditions on different aspects of process models, e.g., control-flow, data and resources etc. Based on the rules sets, norms can be classified into various classes and sub-classes according to their effects. This paper presents an abstract framework consisting of a list of norms and a generic compliance checking approach on the idea of (possible) execution of processes. The proposed framework is independent of any existing formalism, and provides a conceptually rich and exhaustive ontology and semantics of norms needed for business process compliance checking. The possible uses of the proposed framework include to compare different compliance management frameworks (CMFs).

New paradigm, new educational requirements? Australian viewpoints on education for digital libraries

The rise in popularity of the digital library has lead to studies addressing digital library education and curricula development to emanate from the United States and Europe. However, to date very little research has been conducted with an Australian focus. Additionally, very few studies worldwide have sought the opinions of practitioners and the influence that these opinions may have on developing appropriate digital library curricula. The current paper is drawn from a larger study which sought to determine the skills and knowledge required of library and information professionals to work in a digital library environment. Data were collected via an online questionnaire from two target groups: practitioners working in academic libraries and Library and Information Science (LIS) educators across Australia. This paper examines in depth the findings from the survey specifically relating to the following topics. Firstly, whether or not there is a need for an educational programme to be targeted solely at the digital library environment. Secondly, the preferred delivery options for such a programme, and preferred models of digital library education. In addition, a determination on the elements which should be included in the curricula of a digital library education programme are discussed. Findings are compared and discussed with reference to the literature which informed the study. Finally, implications for the sustainability of library education programmes in Australia are identified and directions for further research highlighted.

An application of fuzzy DL-Based semantic perception to soil container classification

Semantic perception and object labeling are key requirements for robots interacting with objects on a higher level. Symbolic annotation of objects allows the usage of planning algorithms for object interaction, for instance in a typical fetchand-carry scenario. In current research, perception is usually based on 3D scene reconstruction and geometric model matching, where trained features are matched with a 3D sample point cloud. In this work we propose a semantic perception method which is based on spatio-semantic features. These features are defined in a natural, symbolic way, such as geometry and spatial relation. In contrast to point-based model matching methods, a spatial ontology is used where objects are rather described how they "look like", similar to how a human would described unknown objects to another person. A fuzzy based reasoning approach matches perceivable features with a spatial ontology of the objects. The approach provides a method which is able to deal with senor noise and occlusions. Another advantage is that no training phase is needed in order to learn object features. The use-case of the proposed method is the detection of soil sample containers in an outdoor environment which have to be collected by a mobile robot. The approach is verified using real world experiments.

Straightforward data management at QUT

QUT Library Research Support has simplified and streamlined the process of research data management planning, storage, discovery and reuse through collaboration and the use of integrated and tailored online tools, and a simplification of the metadata schema. This poster presents the integrated data management services a QUT, including QUT’s Data Management Planning Tool, Research Data Finder, Spatial Data Finder and Software Finder, and information on the simplified Registry Interchange Format – Collections and Services (RIF-CS) Schema. The QUT Data Management Planning (DMP) Tool was built using the Digital Curation Centre’s DMP Online Tool and modified to QUT’s needs and policies. The tool allows researchers and Higher Degree Research students to plan how to handle research data throughout the active phase of their research. The plan is promoted as a ‘live’ document’ and researchers are encouraged to update it as required. The information entered into the plan can be made private or shared with supervisors, project members and external examiners. A plan is mandatory when requesting storage space on the QUT Research Data Storage Service. QUT’s Research Data Finder is integrated with QUT’s Academic Profiles and the Data Management Planning Tool to create a seamless data management process. This process aims to encourage the creation of high quality rich records which facilitate discovery and reuse of quality data. The Registry Interchange Format – Collections and Services (RIF-CS) Schema that is used in the QUT Research Data Finder was simplified to “RIF-CS lite” to reflect mandatory and optional metadata requirements. RIF-CS lite removed schema fields that were underused or extra to the needs of the users and system. This has reduced the amount of metadata fields required from users and made integration of systems a far more simple process where field content is easily shared across services making the process of collecting metadata as transparent as possible.

Investigation of structural requirements of anticancer activity at the paclitaxel/tubulin binding site using CoMFA and CoMSIA

CoMFA and CoMSIA analysis were utilized in this investigation to define the important interacting regions in paclitaxel/tubulin binding site and to develop selective paclitaxel-like active compounds. The starting geometry of paclitaxel analogs was taken from the crystal structure of docetaxel. A total of 28 derivatives of paclitaxel were divided into two groups—a training set comprising of 19 compounds and a test set comprising of nine compounds. They were constructed and geometrically optimized using SYBYL v6.6. CoMFA studies provided a good predictability (q2 = 0.699, r2 = 0.991, PC = 6, S.E.E. = 0.343 and F = 185.910). They showed the steric and electrostatic properties as the major interacting forces whilst the lipophilic property contribution was a minor factor for recognition forces of the binding site. These results were in agreement with the experimental data of the binding activities of these compounds. Five fields in CoMSIA analysis (steric, electrostatic, hydrophobic, hydrogen-bond acceptor and donor properties) were considered contributors in the ligand–receptor interactions. The results obtained from the CoMSIA studies were: q2 = 0.535, r2 = 0.983, PC = 5, S.E.E. = 0.452 and F = 127.884. The data obtained from both CoMFA and CoMSIA studies were interpreted with respect to the paclitaxel/tubulin binding site. This intuitively suggested where the most significant anchoring points for binding affinity are located. This information could be used for the development of new compounds having paclitaxel-like activity with new chemical entities to overcome the existing pharmaceutical barriers and the economical problem associated with the synthesis of the paclitaxel analogs. These will boost the wide use of this useful class of compounds, i.e. in brain tumors as the most of the present active compounds have poor blood–brain barrier crossing ratios and also, various tubulin isotypes has shown resistance to taxanes and other antimitotic agents.

Colonoscopy requirements of population screening for colorectal cancer in New Zealand

Aim: To estimate the colonoscopy burden of introducing population screening for colorectal cancer in New Zealand. Methods: Screening for colorectal cancer using biennial immunochemical faecal occult blood tests offered to people aged 50-74 years of age was modelled using population estimates from Statistics New Zealand for 2011-2031. Modelling to determine colonoscopy requirements was based on participation and test positivity rates from published results of screening programmes. Estimates of the number of procedures required for ongoing adenoma surveillance were calculated using screening literature results of adenoma yield, and New Zealand Guidelines for Adenoma Surveillance. Sensitivity analysis was undertaken on key parameters. Results: For a test positivity of 6.4%, biennial screening using immunochemical faecal occult blood testing with a 60% participation rate, would require 18,000 colonoscopies nationally, increasing to 28,000 by 2031. The majority of procedures are direct referrals from a positive FOBT, with surveillance colonoscopy numbers building over time. Conclusion: Colonoscopy requirements for immunochemical faecal occult blood based population screening for colorectal cancer are high. Significant expansion of services is required and careful management of surveillance procedures to ensure timely delivery of initial colonoscopies whilst maintaining symptomatic services. A model re-run informed by data from the screening pilot will allow improved estimates for the New Zealand setting.

Effect of nitrification inhibitors (DMPP and 3MP+ TZ) on soil nitrous oxide emissions from a sub-tropical vegetable production system in Queensland, Australia

The use of nitrification inhibitors, in combination with ammonium based fertilisers, has been promoted recently as an effective method to reduce nitrous oxide (N2O) emissions from fertilised agricultural fields, whilst increasing yield and nitrogen use efficiency. Vegetable cropping systems are often characterised by high inputs of nitrogen fertiliser and consequently elevated emissions of nitrous oxide (N2O) can be expected. However, to date only limited data is available on the use of nitrification inhibitors in sub-tropical vegetable systems. A field experiment investigated the effect of the nitrification inhibitors (DMPP & 3MP+TZ) on N2O emissions and yield from a typical vegetable production system in sub-tropical Australia. Soil N2O fluxes were monitored continuously over an entire year with a fully automated system. Measurements were taken from three subplots for each treatment within a randomized complete blocks design. There was a significant inhibition effect of DMPP and 3MP+TZ on N2O emissions and soil mineral N content directly following the application of the fertiliser over the vegetable cropping phase. However this mitigation was offset by elevated N2O emissions from the inhibitor treatments over the post-harvest fallow period. Cumulative annual N2O emissions amounted to 1.22 kg-N/ha, 1.16 kg-N/ha, 1.50 kg-N/ha and 0.86 kg-N/ha in the conventional fertiliser (CONV), the DMPP treatment, the 3MP+TZ treatment and the zero fertiliser (0N) respectively. Corresponding fertiliser induced emission factors (EFs) were low with only 0.09 - 0.20% of the total applied fertiliser lost as N2O. There was no significant effect of the nitrification inhibitors on yield compared to the CONV treatment for the three vegetable crops (green beans, broccoli, lettuce) grown over the experimental period. This study highlights that N2O emissions from such vegetable cropping system are primarily controlled by post-harvest emissions following the incorporation of vegetable crop residues into the soil. It also shows that the use of nitrification inhibitors can lead to elevated N2O emissions by storing N in the soil profile that is available to soil microbes during the decomposition of the vegetable residues over the post-harvest phase. Hence the use of nitrification inhibitors in vegetable systems has to be treated carefully and fertiliser rates need to be adjusted to avoid excess soil nitrogen during the postharvest phase.

Consistent responses of soil microbial communities to elevated nutrient inputs in grasslands across the globe

Soil microorganisms are critical to ecosystem functioning and the maintenance of soil fertility. However, despite global increases in the inputs of nitrogen (N) and phosphorus (P) to ecosystems due to human activities, we lack a predictive understanding of how microbial communities respond to elevated nutrient inputs across environmental gradients. Here we used high-throughput sequencing of marker genes to elucidate the responses of soil fungal, archaeal, and bacterial communities using an N and P addition experiment replicated at 25 globally distributed grassland sites. We also sequenced metagenomes from a subset of the sites to determine how the functional attributes of bacterial communities change in response to elevated nutrients. Despite strong compositional differences across sites, microbial communities shifted in a consistent manner with N or P additions, and the magnitude of these shifts was related to the magnitude of plant community responses to nutrient inputs. Mycorrhizal fungi and methanogenic archaea decreased in relative abundance with nutrient additions, as did the relative abundances of oligotrophic bacterial taxa. The metagenomic data provided additional evidence for this shift in bacterial life history strategies because nutrient additions decreased the average genome sizes of the bacterial community members and elicited changes in the relative abundances of representative functional genes. Our results suggest that elevated N and P inputs lead to predictable shifts in the taxonomic and functional traits of soil microbial communities, including increases in the relative abundances of faster-growing, copiotrophic bacterial taxa, with these shifts likely to impact belowground ecosystems worldwide.

Adopting healthcare big data in Sri Lankan healthcare sector

The concept of big data has already outperformed traditional data management efforts in almost all industries. Other instances it has succeeded in obtaining promising results that provide value from large-scale integration and analysis of heterogeneous data sources for example Genomic and proteomic information. Big data analytics have become increasingly important in describing the data sets and analytical techniques in software applications that are so large and complex due to its significant advantages including better business decisions, cost reduction and delivery of new product and services [1]. In a similar context, the health community has experienced not only more complex and large data content, but also information systems that contain a large number of data sources with interrelated and interconnected data attributes. That have resulted in challenging, and highly dynamic environments leading to creation of big data with its enumerate complexities, for instant sharing of information with the expected security requirements of stakeholders. When comparing big data analysis with other sectors, the health sector is still in its early stages. Key challenges include accommodating the volume, velocity and variety of healthcare data with the current deluge of exponential growth. Given the complexity of big data, it is understood that while data storage and accessibility are technically manageable, the implementation of Information Accountability measures to healthcare big data might be a practical solution in support of information security, privacy and traceability measures. Transparency is one important measure that can demonstrate integrity which is a vital factor in the healthcare service. Clarity about performance expectations is considered to be another Information Accountability measure which is necessary to avoid data ambiguity and controversy about interpretation and finally, liability [2]. According to current studies [3] Electronic Health Records (EHR) are key information resources for big data analysis and is also composed of varied co-created values [3]. Common healthcare information originates from and is used by different actors and groups that facilitate understanding of the relationship for other data sources. Consequently, healthcare services often serve as an integrated service bundle. Although a critical requirement in healthcare services and analytics, it is difficult to find a comprehensive set of guidelines to adopt EHR to fulfil the big data analysis requirements. Therefore as a remedy, this research work focus on a systematic approach containing comprehensive guidelines with the accurate data that must be provided to apply and evaluate big data analysis until the necessary decision making requirements are fulfilled to improve quality of healthcare services. Hence, we believe that this approach would subsequently improve quality of life.