Using a Kinect Interface to Develop an Interactive 3D Tabletop Display

Since the release of the motion picture ’Minority Report’ in 2002, which depicts Tom Cruise interacting with a video display using only hand gestures, there has been a significant interest in the development of intelligent display technology, that users are able to interact with using gestures. In the real world it is common place for us to use gestures and body language to re-enforce our communication. It therefore becomes very natural for us to want to interact with our virtual media in the same way. Traditional methods for pose recognition involve using cameras to track the position of the user. However this can be very challenging to complete acurately in a variety of environments where camera can become occluded or the lighting conditions can change. In this research we prototyped a 3D tabletop display and explored the Kinect game controller as a possible solution to tracking the pose and gesture of a user whilst interacting with our display

Development of tools for the automated analysis of spectra generated by tandem mass spectrometry

Background While multiple tools exist for the analysis and identification of spectra generated in shotgun proteomics experiments, few easily implemented tools exist that allow for the automated analysis of the quality of spectra. A researcher’s knowledge of the quality of a spectra from an experiment can be helpful in determining possible reasons for misidentification or lack of identification of spectra in a sample. Materials and methods We are developing a automated high throughput method that analyses spectra from 2d-LC-MS/MS datasets to determine their quality and overall determines the quality of the run. We will then compare our programs to existing programs that perform a similar function. Our program calculates a quality score based on the following metrics: signal/noise ratio, absolute signal intensity, peak number, predicted mass distances between peak, and percent of incoming mass accounted for by peaks. These scores are then graphed against the outputs of common database search algorithms in order to display the following four categories: High-quality/Identified, High-quality/Unidentified, Low-quality/Identified, and Low-quality/Unidentified. We are currently testing the algorithm against 2d-LC-MS/MS runs of a mixed protein standard and blanks with no peptide spectra. The application samples are a time series of metaproteomes collected from environmental ground waters after biostimulation

Development of tools for the automated analysis of spectra generated by tandem mass spectrometry

Background While multiple tools exist for the analysis and identification of spectra generated in shotgun proteomics experiments, few easily implemented tools exist that allow for the automated analysis of the quality of spectra. A researcher’s knowledge of the quality of a spectra from an experiment can be helpful in determining possible reasons for misidentification or lack of identification of spectra in a sample. Materials and methods We are developing a automated high throughput method that analyses spectra from 2d-LC-MS/MS datasets to determine their quality and overall determines the quality of the run. We will then compare our programs to existing programs that perform a similar function. Our program calculates a quality score based on the following metrics: signal/noise ratio, absolute signal intensity, peak number, predicted mass distances between peak, and percent of incoming mass accounted for by peaks. These scores are then graphed against the outputs of common database search algorithms in order to display the following four categories: High-quality/Identified, High-quality/Unidentified, Low-quality/Identified, and Low-quality/Unidentified. We are currently testing the algorithm against 2d-LC-MS/MS runs of a mixed protein standard and blanks with no peptide spectra. The application samples are a time series of metaproteomes collected from environmental ground waters after biostimulation

Pathogenic potential of respirable spodumene cleavage fragments following application of regulatory counting criteria for asbestiform fibres

Health risks from exposure to lithium-bearing spodumene cleavage fragments are unknown. While asbestiform fibres can lead to fibrosis, mesothelioma and lung cancer, controversy remains whether non-asbestiform cleavage fragments, having equivalent dimensions, elicit similar pathologic responses. The mineralogy of respirable particles from two alpha (α) - spodumene concentrate grades (chemical and technical) were characterised using semi-quantitative X-ray diffraction (XRD). Particles were measured using scanning electron microscopy (SEM) and the dimensions (length [L], diameter [D], aspect ratio [AR]) applied to regulatory counting criteria for asbestiform fibres. Application of the current World Health Organization (WHO) and National Occupational Health and Safety Commission (NOHSC) counting criteria, L ˃ 5 µm, D ˂ 3 µm, AR ˃ 3 : 1, to 10 SEM images of each grade identified 47 countable particles in the chemical and 37 in the technical concentrate test samples. Of these particles, 17 and 16 in the chemical and technical test samples, respectively, satisfied the more rigorous, previously used Mines Safety and Inspection Regulations 1995 (Western Australia [WA]) criteria, L ˃ 5 µm and D ≤ 1 µm. The majority of the countable particles were consistent with α - spodumene cleavage fragments. These results suggest elongated α - spodumene particles may pose a health risk. It is recommended the precautionary principle be applied to respirable α - spodumene particles and the identification and control of dust hazards in spodumene extraction, handling and processing industries be implemented

Factors Influencing the Green House Gas Footprint of US Dairy Farms

Environmental Economics and Policy, Livestock Production/Industries,

The Aerodynamic Performance of an Over-the-Rotor Liner with Circumferential Grooves on a High Bypass Ratio Turbofan Rotor

No abstract availabl