54,309 research outputs found

    Managing international students attendance with consideration of completion and satisfaction

    Get PDF
    Internationalization is one of the many expectations of TEC, as per the TEC Strategy (2007). This includes having a noticeable level of students from overseas, is covered in our institute’s business plan and is reported our annual report (2008). Servicing these students is guided by the Code of Practice for the Pastoral care of International Students (2003), amongst other things. This paper reports our experiences when the institution tightened up attendance habits of international students for their visa requirements. At the end of the year we revisited our actions, looked at attendance statistics and also considered data about related matters of completion and student satisfaction. We noticed several students attending less than 80% required for their visas, relationship between attendance and module pass rates and nothing specific re student satisfaction. There were some idiosyncrasies with student satisfaction measurement worthwhile noting. We also experienced several problems with our information systems, such as functionality shortcomings for our growing population sub-groups and mismatch between these systems. Further study might include experiences with relevant information systems elsewhere in the institution and rest of the sector. More formal research can and should now be planned, including the use of our pilot use of an online attendance system from 2008. We believe our insights and process would be useful to others even though it does not sit in the framework of ICT teaching contents proposed by Simon (2007) and used by Simon et at (2008) when profiling NACCQ conference papers 2000-2007

    Rapid Profiling of Marine Notches Using a Handheld Laser Distance Meter

    Get PDF
    A rapid, single-user profiling method for rocky shores is described. The Leica Disto D8 handheld laser distance meter measures distance up to 100 m and inclination in 360 degrees. It automatically calculates horizontal distance and vertical elevation. Memory storage accommodates data for 30 measurement points, allowing easy plotting of shore profiles. This technique allows even inaccessible, dangerous, and overhanging cliff faces to be evaluated faithfully and within minutes. It is a major improvement over standard methods that often involve risky coasteering and climbing. Examples are given from marine notches in Thailand

    Deep Learning Models for Planetary Seismicity Detection

    Get PDF
    Research in planetary seismology is fundamentally constrained by a lack of data. Seismo-logical science products of future missions can typically only be informed by theoretical signal/noise characteristics of the environment or likely Earth-analogues. Although objectives can be re-assessed after some initial data-collection upon lander arrival, transfer of high-resolution data back to Earth is costly on lander power usage. Over the last several years, development of GPU computing techniques and open-source high-level APIs have led to rapid advances in deep learning within the fields of computer vision, natural language processing, and collaborative filtering. These techniques are actively being adapted in seismology for a variety of tasks, including: earthquake detection, seismic phase discrimination, and ground-motion prediction. Until the recent detection of mars quakes during the Mars InSight mission, the only other measurements of seismicity recorded outside of Earth was on the Moon during the Apollo missions between 1969 to 1977. These unique data sets have been periodically revisited using new seismological methods, including ambient noise interferometry and Hidden Markov Models. Our objective is to develop a deep learning seismic detector and use it to catalog moonquakes from the Apollo 17 Lunar Seismic Profiling Experiment (LSPE) and compare the results with those obtained by other methods. Additionally, we will assess the accuracy tradeoff between using a training set of lunar data and one composed of Earth seismicity. In this document, we present preliminary results using a prototype classifier trained on a small set of earthquakes that was able to obtain detections for LSPE moonquakes with a greater accuracy than a recent study using Hidden Markov Models

    The contribution of Alu exons to the human proteome.

    Get PDF
    BackgroundAlu elements are major contributors to lineage-specific new exons in primate and human genomes. Recent studies indicate that some Alu exons have high transcript inclusion levels or tissue-specific splicing profiles, and may play important regulatory roles in modulating mRNA degradation or translational efficiency. However, the contribution of Alu exons to the human proteome remains unclear and controversial. The prevailing view is that exons derived from young repetitive elements, such as Alu elements, are restricted to regulatory functions and have not had adequate evolutionary time to be incorporated into stable, functional proteins.ResultsWe adopt a proteotranscriptomics approach to systematically assess the contribution of Alu exons to the human proteome. Using RNA sequencing, ribosome profiling, and proteomics data from human tissues and cell lines, we provide evidence for the translational activities of Alu exons and the presence of Alu exon derived peptides in human proteins. These Alu exon peptides represent species-specific protein differences between primates and other mammals, and in certain instances between humans and closely related primates. In the case of the RNA editing enzyme ADARB1, which contains an Alu exon peptide in its catalytic domain, RNA sequencing analyses of A-to-I editing demonstrate that both the Alu exon skipping and inclusion isoforms encode active enzymes. The Alu exon derived peptide may fine tune the overall editing activity and, in limited cases, the site selectivity of ADARB1 protein products.ConclusionsOur data indicate that Alu elements have contributed to the acquisition of novel protein sequences during primate and human evolution
    corecore