198 research outputs found

    Integrating language learning practises in first year science disciplines

    Full text link
    Student retention and progression rates are a matter of concern for most institutions in the higher education sector (Burton & Dowling, 2005;. Simpson, 2006;. Tinto & Pusser, 2006) in Australia. There is also a substantial body of literature concentrating on the first year experience at university (for example, in the Australian context, see Krause, Hartley, James, McInnis, & Centre for the Study of Higher Education. University of Melbourne, 2005). One of the particular concerns is that the diversity of the student body is rapidly increasing. Of course, with diversity comes with differentiated level of preparation for academic study within the student body

    Language difficulties in first year Science

    Full text link
    A key goal of the study entitled ‘A cross-disciplinary approach to language support for first year students in the science disciplines’, funded by the Carrick Institute for Learning and Teaching in Higher Education, is to examine the role of language in the learning of science by first-year university students. The disciplines involved are Physics, Chemistry and Biology. This national project also aims to transfer active learning skills, which are widely used in language teaching, to the teaching of science in first year. The paper discusses the background to the study, reports on some of the preliminary results on the language difficulties faced by first year student cohorts in science from data collected in 2008, and describes the framework we have established for the organization and delivery of first year science courses to be implemented in semester one 2009

    Embedding in-discipline language support for first year students in the sciences

    Full text link
    This paper reports on a project which aims at addressing the need to cater for the language needs of a diverse student body (both domestic and international student body) by embedding strategic approaches to learning and teaching in first year sciences in tertiary education. These strategies consist of active learning skills which are widely used in language learning. The disciplines covered by the project are Biology, Chemistry and Physics and involves the University of Canberra (UC), University of Sydney (USyd), University of Tasmania (UTAS), University of Technology, Sydney (UTS) and University of Newcastle (Newcastle) in Australia. This project is funded by the Australian Learning and Teaching Council (ALTC). The paper discusses the background to the study and reports on results on the language difficulties faced by first year science student cohorts from data collected in 2008 as well as qualitative data was also collected on 2008 students’ attitudes towards online science learning. It will also report on the results on the implementation of the learning strategies at UTS and UTAS in Physics and Chemistry disciplines in 2009. Keywords: First year science teaching, role of language in science teaching, active learning skill

    Liveness-Driven Random Program Generation

    Get PDF
    Randomly generated programs are popular for testing compilers and program analysis tools, with hundreds of bugs in real-world C compilers found by random testing. However, existing random program generators may generate large amounts of dead code (computations whose result is never used). This leaves relatively little code to exercise a target compiler's more complex optimizations. To address this shortcoming, we introduce liveness-driven random program generation. In this approach the random program is constructed bottom-up, guided by a simultaneous structural data-flow analysis to ensure that the generator never generates dead code. The algorithm is implemented as a plugin for the Frama-C framework. We evaluate it in comparison to Csmith, the standard random C program generator. Our tool generates programs that compile to more machine code with a more complex instruction mix.Comment: Pre-proceedings paper presented at the 27th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur, Belgium, 10-12 October 2017 (arXiv:1708.07854

    Fecal microbiota in client-owned obese dogs changes after weight loss with a high-fiber-high-protein diet

    Get PDF
    Background. The fecal microbiota from obese individuals can induce obesity in animal models. In addition, studies in humans, animal models and dogs have revealed that the fecal microbiota of subjects with obesity is different from that of lean subjects and changes after weight loss. However, the impact of weight loss on the fecal microbiota in dogs with obesity has not been fully characterized. Methods. In this study, we used 16S rRNA gene sequencing to investigate the differences in the fecal microbiota of 20 pet dogs with obesity that underwent a weight loss program. The endpoint of the weight loss program was individually tailored to the ideal body weight of each dog. In addition, we evaluated the qPCR based Dysbiosis Index before and after weight loss. Results. After weight loss, the fecal microbiota structure of dogs with obesity changed significantly (weighted ANOSIM; p = 0.016, R = 0.073), showing an increase in bacterial richness (p = 0.007), evenness (p = 0.007) and the number of bacterial species (p = 0.007). The fecal microbiota composition of obese dogs after weight loss was characterized by a decrease in Firmicutes (92.3% to 78.2%, q = 0.001), and increase in Bacteroidetes (1.4% to 10.1%, q = 0.002) and Fusobacteria (1.6% to 6.2%, q = 0.040). The qPCR results revealed an overall decrease in the Dysbiosis Index, driven mostly due to a significant decrease in E. coli (p = 0.030), and increase in Fusobacterium spp. (p = 0.017). Conclusion. The changes observed in the fecal microbiota of dogs with obesity after weight loss with a weight loss diet rich in fiber and protein were in agreement with previous studies in humans, that reported an increase of bacterial biodiversity and a decrease of the ratio Firmicutes/Bacteroidetes

    The scattering of muons in low Z materials

    Full text link
    This paper presents the measurement of the scattering of 172 MeV/c muons in assorted materials, including liquid hydrogen, motivated by the need to understand ionisation cooling for muon acceleration. Data are compared with predictions from the Geant 4 simulation code and this simulation is used to deconvolute detector effects. The scattering distributions obtained are compared with the Moliere theory of multiple scattering and, in the case of liquid hydrogen, with ELMS. With the exception of ELMS, none of the models are found to provide a good description of the data. The results suggest that ionisation cooling will work better than would be predicted by Geant 4.7.0p01.Comment: pdfeTeX V 3.141592-1.21a-2.2, 30 pages with 22 figure

    Identification of extracellular glycerophosphodiesterases in Pseudomonas and their role in soil organic phosphorus remineralisation

    Get PDF
    In soils, phosphorus (P) exists in numerous organic and inorganic forms. However, plants can only acquire inorganic orthophosphate (Pi), meaning global crop production is frequently limited by P availability. To overcome this problem, rock phosphate fertilisers are heavily applied, often with negative environmental and socio-economic consequences. The organic P fraction of soil contains phospholipids that are rapidly degraded resulting in the release of bioavailable Pi. However, the mechanisms behind this process remain unknown. We identified and experimentally confirmed the function of two secreted glycerolphosphodiesterases, GlpQI and GlpQII, found in Pseudomonas stutzeri DSM4166 and Pseudomonas fluorescens SBW25, respectively. A series of co-cultivation experiments revealed that in these Pseudomonas strains, cleavage of glycerolphosphorylcholine and its breakdown product G3P occurs extracellularly allowing other bacteria to benefit from this metabolism. Analyses of metagenomic and metatranscriptomic datasets revealed that this trait is widespread among soil bacteria with Actinobacteria and Proteobacteria, specifically Betaproteobacteria and Gammaproteobacteria, the likely major players
    corecore