Final report of work-with-IT: the JISC study into evolution of working practices

Technology is increasingly being used to underpin business processes across teaching and learning, research, knowledge exchange and business support activities in both HE and FE. The introduction of technology has a significant impact on the working practices of staff, often requiring them to work in a radically different way. Change in any situation can be unsettling and problematic and, where not effectively managed, can lead to poor service or functionality and disenfranchised staff. These issues can have a direct impact on institutional effectiveness, reputation and the resulting student experience. The Work-with-IT project, based at the University of Strathclyde, sought to examine changes to working practices across HE and FE, the impact on staff roles and relationships and the new skills sets that are required to meet these changes

Events, processes, and the time of a killing

The paper proposes a novel solution to the problem of the time of a killing (ToK), which persistently besets theories of act-individuation. The solution proposed claims to expose a crucial wrong-headed assumption in the debate, according to which ToK is essentially a problem of locating some event that corresponds to the killing. The alternative proposal put forward here turns on recognizing a separate category of dynamic occurents, viz. processes. The paper does not aim to mount a comprehensive defense of process ontology, relying instead on extant defenses. The primary aim is rather to put process ontology to work in diagnosing the current state of play over ToK, and indeed in solving it

Development and application of an HDF5 schema for SKA-scale image cube visualization

In this paper, we describe an HDF5 schema created to support the efficient visualization of the large image cubes that will be produced by SKA Phase 1 and precursor radio telescopes. We demonstrate how the “HDF5-IDIA” schema’s features can improve the performance of visualization software, using both low-level metrics and real-world tests of the schema’s implementation in CARTA, an image viewer that is being developed to replace the existing CyberSKA and CASA viewers

Artificial Neural Network to predict mean monthly total ozone in Arosa, Switzerland

Present study deals with the mean monthly total ozone time series over Arosa, Switzerland. The study period is 1932-1971. First of all, the total ozone time series has been identified as a complex system and then Artificial Neural Networks models in the form of Multilayer Perceptron with back propagation learning have been developed. The models are Single-hidden-layer and Two-hidden-layer Perceptrons with sigmoid activation function. After sequential learning with learning rate 0.9 the peak total ozone period (February-May) concentrations of mean monthly total ozone have been predicted by the two neural net models. After training and validation, both of the models are found skillful. But, Two-hidden-layer Perceptron is found to be more adroit in predicting the mean monthly total ozone concentrations over the aforesaid period.Comment: 22 pages, 14 figure

Exploring and interrogating astrophysical data in virtual reality

Scientists across all disciplines increasingly rely on machine learning algorithms to analyse and sort datasets of ever increasing volume and complexity. Although trends and outliers are easily extracted, careful and close inspection will still be necessary to explore and disentangle detailed behaviour, as well as identify systematics and false positives. We must therefore incorporate new technologies to facilitate scientific analysis and exploration. Astrophysical data is inherently multi-parameter, with the spatial-kinematic dimensions at the core of observations and simulations. The arrival of mainstream virtual-reality (VR) headsets and increased GPU power, as well as the availability of versatile development tools for video games, has enabled scientists to deploy such technology to effectively interrogate and interact with complex data. In this paper we present development and results from custom-built interactive VR tools, called the iDaVIE suite, that are informed and driven by research on galaxy evolution, cosmic large-scale structure, galaxy–galaxy interactions, and gas/kinematics of nearby galaxies in survey and targeted observations. In the new era of Big Data ushered in by major facilities such as the SKA and LSST that render past analysis and refinement methods highly constrained, we believe that a paradigm shift to new software, technology and methods that exploit the power of visual perception, will play an increasingly important role in bridging the gap between statistical metrics and new discovery. We have released a beta version of the iDaVIE software system that is free and open to the community

Effect of high temperature deposition on CoSi 2 phase formation

Abstract: This paper discusses the nucleation behaviour of the CoSi to CoSi2 transformation from cobalt silicide thin films grown by deposition at elevated substrate temperatures ranging from 375 °C to 600 °C. A combination of channelling, real-time Rutherford backscattering spectrometry, real-time x-ray diffraction, and transmission electron microscopy was used to investigate the effect of the deposition temperature on the subsequent formation temperature of CoSi2, its growth behaviour, and the epitaxial quality of the CoSi2 thus formed. The temperature at which deposition took place was observed to exert a significant and systematic influence on both the formation temperature of CoSi2 and its growth mechanism. CoSi films grown at the lowest temperatures were found to increase the CoSi2 nucleation temperature above that of CoSi2 grown by conventional solid phase reaction, whereas the higher deposition temperatures reduced the nucleation temperature significantly. In addition, a systematic change in growth mechanism of the subsequent CoSi2 growth occurs as a function of deposition temperature. First, the CoSi2 growth rate from films grown at the lower reactive deposition temperatures is substantially lower than that grown at higher reactive deposition temperatures, even though the onset of growth occurs at a higher temperature, Second, for deposition temperatures below 450 °C, the growth appears columnar, indicating nucleation controlled growth. Elevated deposition temperatures, on the other hand, render the CoSi2 formation process layer-by-layer which indicates enhanced nucleation of the CoSi2 and diffusion controlled growth. Our results further indicate that this observed trend is most likely related to stress and changes in microstructure introduced during reactive deposition of the CoSi film. The deposition temperature therefore provides a handle to tune the CoSi2 growth mechanism

On the growth kinetics of Ni(Pt) silicide thin films

We report on the effect of Pt on the growth kinetics of δ-Ni2Si and Ni 1−xPtxSi thin films formed by solid phase reaction of a Ni(Pt) alloyed thin film on Si(100). The study was performed by real-time Rutherford backscattering spectrometry examining the silicide growth rates for initial Pt concentrations of 0, 1, 3, 7, and 10 at. % relative to the Ni content. Pt was found to exert a drastic effect on the growth kinetics of both phases. δ-Ni2Si growth is slowed down tremendously, which results in the simultaneous growth of this phase with Ni 1−xPtxSi. Activation energies extracted for the Ni 1−xPtxSi growth process exhibit an increase from Ea = 1.35 ± 0.06 eV for binary NiSi to Ea = 2.7 ± 0.2 eV for Ni 1−xPtxSi with an initial Pt concentration of 3 at. %. Further increasing the Pt content to 10 at. % merely increases the activation energy for Ni 1−xPtxSi growth to Ea = 3.1 ± 0.5 eV

RISK MANAGEMENT FOR CHIROPRACTORS AND OSTEOPATHS: Imaging Guidelines for Conditions Commonly Seen in Practice

This article is the second in a series of articles dealing with risk management in the practise of chiropractic and osteopathy, prepared by the COCA Risk Management Subcommittee

Exploring and interrogating astrophysical data in virtual reality

Scientists across all disciplines increasingly rely on machine learning algorithms to analyse and sort datasets of ever increasing volume and complexity. Although trends and outliers are easily extracted, careful and close inspection will still be necessary to explore and disentangle detailed behaviour, as well as identify systematics and false positives. We must therefore incorporate new technologies to facilitate scientific analysis and exploration. Astrophysical data is inherently multi-parameter, with the spatial-kinematic dimensions at the core of observations and simulations. The arrival of mainstream virtual-reality (VR) headsets and increased GPU power, as well as the availability of versatile development tools for video games, has enabled scientists to deploy such technology to effectively interrogate and interact with complex data. In this paper we present development and results from custom-built interactive VR tools, called the iDaVIE suite, that are informed and driven by research on galaxy evolution, cosmic large-scale structure, galaxy–galaxy interactions, and gas/kinematics of nearby galaxies in survey and targeted observations. In the new era of Big Data ushered in by major facilities such as the SKA and LSST that render past analysis and refinement methods highly constrained, we believe that a paradigm shift to new software, technology and methods that exploit the power of visual perception, will play an increasingly important role in bridging the gap between statistical metrics and new discovery. We have released a beta version of the iDaVIE software system that is free and open to the community

Sn diffusion during Ni germanide growth on Ge1– xSnx

We report on the redistribution of Sn during Ni germanide formation on Ge1– x Sn x /〈Ge(100)〉 and its influence on the thin film growth and properties. These results show that the reaction involves the formation of Ni5Ge3 and NiGe. Sn redistributes homogenously in both phases, in which the Sn/Ge ratio retains the ratio of the as-deposited Ge1– x Sn x film. Sn continues to diffuse after full NiGe formation and segregates in two regions: (1) at the interface between the germanide and Ge1– x Sn x and (2) at the surface, which has major implications for the thin film and contact properties