4,151 research outputs found

    Remote Camera and Trapping Survey of the Deep-water Shrimps Heterocarpus laevigatus and H. ensifer and the Geryonid Crab Chaceon granulatus in Palau

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    Time-lapse remote photo-sequences at 73-700 m depth off Palau, Western Caroline Islands, show that the caridean shrimp Heterocarpus laevigatus tends to be a solitary animal, occurring below ~350 m, that gradually accumulates around bait sites over a prolonged period. A smaller speies, H. ensifer, tends to move erratically in swarms, appearing in large numbers in the upper part of its range (<250 m) during the evening crepuscular period and disappearing at dawn. Trapping and photsequence data indicate the depth range of H. ensifer (during daylight) is ~250-550 M, while H. laevigatus ranges from 350 m to at least 800 m, along with the geryonid crab Chaceon granulatus. Combined trapping for Heterocarpus laevigatus and Chaceon granulatus, using a three-chamber box-trap and extended soak times (48-72 hr), may be an appropriate technique for small-scale deep-water fisheries along forereef slopes of Indo-Pacific archipelagoes

    On the Distribution and Fishery Potential of the Japanese Red Crab Chaceon granulatus in the Palauan Archipelago, Western Caroline Islands

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    A deep-water trapping survey in the Palauan archipelago, Western Caroline Islands, has revealed an abundance of the Japanese red crab, Chaceon granulatus. The recorded depth range (250-900 m) is similar to that of other geryonids, but the large numbers of females caught below 700 m is atypical. Mean yields in excess of 5 kg crabs plus 1 kg shrimp, Heterocarpus laevigatus, by-catch per trap-night were attainable at optimum depths. Chaceon granulatus is apparently a very large geryonid, with maximum weights of 2.02 kg and 1.51 kg recorded for male and female specimens, respectively. A range of body colors was observed: Orange-red shades appear to dominate the deeper waters (below 500 m) while yellow-tan colors are more abundant in the upper reaches. Preliminary evidence suggests that Chaceon granulatus is highly marketable, and the infrastructure in Palau is such that crabs could either be marketed fresh locally or airfreighted to Japan as a quick-frozen product. The high post-trapping survival rates observed indicate that maintaining crabs in live-holding tanks may be a feasible option. The large catches and quality of deep-water crabs taken suggests that the Palauan population of Chaceon granulatus may be able to support a small-scale fishery. It is not yet known whether this population is unusually large or whether these findings typify the deep forereef fauna of the region

    Pathways to apprenticeships and traineeships for people from culturally and linguistically diverse backgrounds

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    Western Australia is experiencing a substantial shortage of skilled labour. The State Government is committed to increasing participation in the workforce across the board, through schemes such as the Plans 4 Jobs, especially because of the current severe skills shortage in the economy. The State Government is also committed, through the four principles of civic values, fairness, equality, and participation enshrined in the WA Charter of Multiculturalism, to promoting the full participation of all groups in all aspects of our community – social, economic, and civil – and to removing any systemic barriers to full participation. This commitment is also embodied in the multi‐departmental Policy Framework for Substantive Equality. Aside from equity, denying equal opportunity also engenders resentment and hostility within our community, diminishes human value, and denies the state the full benefits of all its members’ talents. The cost of discrimination accrues to those who are denied opportunity and to the society which tolerates discrimination. Members of Culturally and Linguistically Diverse (CaLD) communities in this state, in particular those from new and emerging communities, do not currently participate in apprenticeships and traineeships in significant numbers; this is regrettable and it is recommended that measures be taken to remedy this. The Western Australian Department of Education and Training (DET) commissioned this report to investigate barriers to apprenticeships and traineeships confronting people from CaLD backgrounds, and to recommend strategies to improve their participation in apprenticeships and traineeships. The project was undertaken by the Australian Academy of Race Relations (AARR) at Murdoch University, for DET, during the period July – November 2005. DET has many good programmes to promote apprenticeships and traineeships, including to members of CaLD communities. However, the array and complexity of these can be daunting, resulting in a lack of awareness of all the programmes available

    Modelling solids friction factor for dense-phase pneumatic conveying of powders

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    This paper presents results from an investigation into power-function modelling of solids friction factor for the dilute-phase and fluidised dense-phase (FDP) conveying of powders. Three different diameters/lengths of pipeline were used to generate a wide range of steady-state data and also explore important scale-up issues. The effect of pressure tapping locations on the data and derived models was also investigated. Different sets of power-function model solutions were used for comparison purposes and also to check scale-up stability and accuracy. Comparisons with predictions from recent models developed by other researchers are included. It is concluded that certain forms of the power function model are more stable (in terms of scale-up) than others. The paper also demonstrates how existing models can go unreliable or unstable under certain scale-up conditions and discusses possible causes of such problems

    Theoretical Modelling of Rotary Valve Air Leakage for Pneumatic Conveying Systems

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    Rotary valve air leakage is an important parameter for the design and operation of many dilute- and dense-phase pneumatic conveying systems. Previous methods to estimate air leakage have been largely empirical and have been found inaccurate and/or limited in their use. This paper describes a new theoretical model that has been developed to estimate rotary valve (radial clearance) air leakage. Model predictions are compared with experimental data obtained on a rotating and stationary valve subjected to a wide range of operating pressures typical of dilute- and dense-phase systems. Knowing accurately the air leakage present for any given situation, the required total supplied air mass flow rate can be determined properly for the pneumatic conveying system, so that optimal transport velocities can be established

    Evaluation of Belt Conveyor Trajectories

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    Since the early 1900s, numerical methods have been used to predict the trajectory of material discharged from a belt conveyor. These methods range from the very basic to complex iterative approaches. Some methods predict similar paths and others vary noticeably, however it is clear that they cannot all be correct. The discrete element method (DEM) is also becoming more widely accepted as a design tool, however, hesitation still exists in some quarters stemming from the lack of experimental validation available. A conveyor transfer research facility has been commissioned at the University of Wollongong to experimentally investigate particle flow mechanisms through a variety of conveyor transfers. As part of this research, preliminary investigations into conveyor trajectories have been undertaken at varying belt speeds and material flow rates using granular polyethylene pellets. This paper presents the trajectory results of an experimental test program and compares these findings with numerous numerical trajectory methods as well as DEM simulations in an attempt to validate the predictive approaches available to generate conveyor trajectories. Early findings suggest the method of Booth provided the most accurate prediction, while the DEM also compares favourably to the experimental results

    A Bayesian spatio-temporal model of panel design data: airborne particle number concentration in Brisbane, Australia

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    This paper outlines a methodology for semi-parametric spatio-temporal modelling of data which is dense in time but sparse in space, obtained from a split panel design, the most feasible approach to covering space and time with limited equipment. The data are hourly averaged particle number concentration (PNC) and were collected, as part of the Ultrafine Particles from Transport Emissions and Child Health (UPTECH) project. Two weeks of continuous measurements were taken at each of a number of government primary schools in the Brisbane Metropolitan Area. The monitoring equipment was taken to each school sequentially. The school data are augmented by data from long term monitoring stations at three locations in Brisbane, Australia. Fitting the model helps describe the spatial and temporal variability at a subset of the UPTECH schools and the long-term monitoring sites. The temporal variation is modelled hierarchically with penalised random walk terms, one common to all sites and a term accounting for the remaining temporal trend at each site. Parameter estimates and their uncertainty are computed in a computationally efficient approximate Bayesian inference environment, R-INLA. The temporal part of the model explains daily and weekly cycles in PNC at the schools, which can be used to estimate the exposure of school children to ultrafine particles (UFPs) emitted by vehicles. At each school and long-term monitoring site, peaks in PNC can be attributed to the morning and afternoon rush hour traffic and new particle formation events. The spatial component of the model describes the school to school variation in mean PNC at each school and within each school ground. It is shown how the spatial model can be expanded to identify spatial patterns at the city scale with the inclusion of more spatial locations.Comment: Draft of this paper presented at ISBA 2012 as poster, part of UPTECH projec

    Machine Learning for Quantum Mechanical Properties of Atoms in Molecules

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    We introduce machine learning models of quantum mechanical observables of atoms in molecules. Instant out-of-sample predictions for proton and carbon nuclear chemical shifts, atomic core level excitations, and forces on atoms reach accuracies on par with density functional theory reference. Locality is exploited within non-linear regression via local atom-centered coordinate systems. The approach is validated on a diverse set of 9k small organic molecules. Linear scaling of computational cost in system size is demonstrated for saturated polymers with up to sub-mesoscale lengths
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