Countdown to Launch of the First Microsatellites Qualified for Flight on Ariane-5 ASAP

In the fourth quarter of 2000, the first Ariane-5 to carry “piggy-back” payloads on the newly-designed ASAP ring is planned to be launched into a geo-synchronous orbit. The two 100kg spacecraft carried on the ring will be the second generation of microsatellites from the UK Defence Evaluation & Research Agency (DERA), called STRV-1c and –1d. Between them, these spacecraft carry 25 separate experiments sponsored by a wide variety of national and international government agencies, academia and industry. The experiments cover a wide range of technical research areas including new lightweight RF hardware, Internet-type communications protocols experiments, the latest radiation detectors, GPS experiments and debris detectors. The paper describes the process of assembly, integration and test of these small, but very challenging, spacecraft leading up to the launch campaign and initial operations phases. The management and technical lessons learned through the process of becoming the first microsatellites to be qualified for flight on the new Ariane-5 ASAP are also described

Early stages of phase selection in MOF formation observed in molecular Monte Carlo simulations

Metal-organic frameworks (MOF) comprising metal nodes bridged by organic linkers show great promise because of their guest-specific gas sorption, separation, drug-delivery, and catalytic properties. The selection of metal node, organic linker, and synthesis conditions in principle offers engineered control over both structure and function. For MOFs to realise their potential and to become more than just promising materials, a degree of predictability in the synthesis and a better understanding of the self-assembly or initial growth processes is of paramount importance. Using cobalt succinate, a MOF that exhibits a variety of phases depending on synthesis temperature and ligand to metal ratio, as proof of concept, we present a molecular Monte Carlo approach that allows us to simulate the early stage of MOF assembly. We introduce a new Contact Cluster Monte Carlo (CCMC) algorithm which uses a system of overlapping "virtual sites" to represent the coordination environment of the cobalt and both metal-metal and metal-ligand associations. Our simulations capture the experimentally observed synthesis phase distinction in cobalt succinate at 348 K. To the best of our knowledge this is the first case in which the formation of different MOF phases as a function of composition is captured by unbiased molecular simulations. The CCMC algorithm is equally applicable to any system in which short-range attractive interactions are a dominant feature, including hydrogen-bonding networks, metal-ligand coordination networks, or the assembly of particles with "sticky" patches, such as colloidal systems or the formation of protein complexes.</p

Second order QCD corrections to gluonic jet production at hadron colliders

We report on the calculation of the next-to-next-to-leading order (NNLO) QCD corrections to the production of two gluonic jets at hadron colliders. In previous work, we discussed gluonic dijet production in the gluon-gluon channel. Here, for the first time, we update our numerical results to include the leading colour contribution to the production of two gluonic jets via quark-antiquark scattering.Comment: 8 pages, 4 figures, Proceedings of "Loops and Legs in Quantum Field Theory", Weimar April 201

SIM-STEM Lab: Incorporating Compressed Sensing Theory for Fast STEM Simulation

Recently it has been shown that precise dose control and an increase in the overall acquisition speed of atomic resolution scanning transmission electron microscope (STEM) images can be achieved by acquiring only a small fraction of the pixels in the image experimentally and then reconstructing the full image using an inpainting algorithm. In this paper, we apply the same inpainting approach (a form of compressed sensing) to simulated, sub-sampled atomic resolution STEM images. We find that it is possible to significantly sub-sample the area that is simulated, the number of g-vectors contributing the image, and the number of frozen phonon configurations contributing to the final image while still producing an acceptable fit to a fully sampled simulation. Here we discuss the parameters that we use and how the resulting simulations can be quantifiably compared to the full simulations. As with any Compressed Sensing methodology, care must be taken to ensure that isolated events are not excluded from the process, but the observed increase in simulation speed provides significant opportunities for real time simulations, image classification and analytics to be performed as a supplement to experiments on a microscope to be developed in the future.Comment: 20 pages (includes 3 supplementary pages), 15 figures (includes 5 supplementary figures), submitted to Ultramicroscop

An adaptive two-arm clinical trial using early endpoints to inform decision making : design for a study of sub-acromial spacers for repair of rotator cuff tendon tears

Background There is widespread concern across the clinical and research communities that clinical trials, powered for patient-reported outcomes, testing new surgical procedures are often expensive and time-consuming, particularly when the new intervention is shown to be no better than the standard. Conventional (non-adaptive) randomised controlled trials (RCTs) are perceived as being particularly inefficient in this setting. Therefore, we have developed an adaptive group sequential design that allows early endpoints to inform decision making and show, through simulations and a worked example, that these designs are feasible and often preferable to conventional non-adaptive designs. The methodology is motivated by an ongoing clinical trial investigating a saline-filled balloon, inserted above the main joint of the shoulder at the end of arthroscopic debridement, for treatment of tears of rotor cuff tendons. This research question and setting is typical of many studies undertaken to assess new surgical procedures. Methods Test statistics are presented based on the setting of two early outcomes, and methods for estimation of sequential stopping boundaries are described. A framework for the implementation of simulations to evaluate design characteristics is also described. Results Simulations show that designs with one, two and three early looks are feasible and, with appropriately chosen futility stopping boundaries, have appealing design characteristics. A number of possible design options are described that have good power and a high probability of stopping for futility if there is no evidence of a treatment effect at early looks. A worked example, with code in R, provides a practical demonstration of how the design might work in a real study. Conclusions In summary, we show that adaptive designs are feasible and could work in practice. We describe the operating characteristics of the designs and provide guidelines for appropriate values for the stopping boundaries for the START:REACTS (Sub-acromial spacer for Tears Affecting Rotator cuff Tendons: a Randomised, Efficient, Adaptive Clinical Trial in Surgery) study

SenseAI: Real-Time Inpainting for Electron Microscopy

Despite their proven success and broad applicability to Electron Microscopy (EM) data, joint dictionary-learning and sparse-coding based inpainting algorithms have so far remained impractical for real-time usage with an Electron Microscope. For many EM applications, the reconstruction time for a single frame is orders of magnitude longer than the data acquisition time, making it impossible to perform exclusively subsampled acquisition. This limitation has led to the development of SenseAI, a C++/CUDA library capable of extremely efficient dictionary-based inpainting. SenseAI provides N-dimensional dictionary learning, live reconstructions, dictionary transfer and visualization, as well as real-time plotting of statistics, parameters, and image quality metrics.Comment: Presented in ISCS2

An approach to evaluating the impact of contaminants on flux deposition in gas turbines

Gas turbines are a key part of many countries’ power generation portfolios, but components such as blades can suffer from hot corrosion attack, which can decrease component lifetimes. Corrosion is driven by impurity levels in the fuel and air (e.g., species containing sulphur and/or alkali metals) and depends on environmental conditions (e.g., air pollution, seawater droplets), that can lead to formation of harmful species in the gas. Understanding and determining the deposition flux of such contaminants is crucial for understanding the problem. Thermodynamic simulations were used to determine types and amounts of potentially corrosive contaminants, this was followed by deposition fluxes calculations. An operating scenario, based upon an offshore platform was evaluated. The effectiveness of different filtration systems has been evaluated. The impurity levels of alkali metals, such as sodium, greatly impacts the calculated deposition flux of species linked to corrosion attack. The presence of Na2SO4, and K2SO4 was found, at temperature representative of stage 2 nozzle guide vanes. Lowering sulphur input (from fuel or air) can be an efficient way to decrease deposition, attention must also be paid to lowering the amount of alkali metal entering the gas turbine, which can be lowered by the filtration systems’ correct use

Simultaneous High-Speed and Low-Dose 4-D STEM Using Compressive Sensing Techniques

Here we show that compressive sensing allow 4-dimensional (4-D) STEM data to be obtained and accurately reconstructed with both high-speed and low fluence. The methodology needed to achieve these results compared to conventional 4-D approaches requires only that a random subset of probe locations is acquired from the typical regular scanning grid, which immediately generates both higher speed and the lower fluence experimentally. We also consider downsampling of the detector, showing that oversampling is inherent within convergent beam electron diffraction (CBED) patterns, and that detector downsampling does not reduce precision but allows faster experimental data acquisition. Analysis of an experimental atomic resolution yttrium silicide data-set shows that it is possible to recover over 25dB peak signal-to-noise in the recovered phase using 0.3% of the total data