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Brief outline of Science Operations Centre activities for Gaia.
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Keplers primary mission is a search for earth-size exoplanets in the habitable zone of late-type stars using the transit method. To effectively accomplish this mission, Kepler orbits the Sun and stares nearly continuously at one field-of-view which was carefully selected to provide an appropriate density of target stars. The data transmission rates, operational cycles, and target management requirements implied by this mission design have been optimized and integrated into a comprehensive plan for science operations. The commissioning phase completed all critical tasks and accomplished all objectives within a week of the pre-launch plan. Since starting science, the nominal data collection timeline has been interrupted by two safemode events, several losses of fine point, and some small pointing adjustments. The most important anomalies are understood and mitigated, so Keplers technical performance metrics have improved significantly over this period and the prognosis for mission success is excellent. The Kepler data archive is established and hosting data for the science team, guest observers, and public. The first data sets to become publicly available include the monthly full-frame images, dropped targets, and individual sources as they are published. Data are released through the archive on a quarterly basis; the Kepler Results Catalog will be released annually starting in 2011.
The Hard X-ray Modulation Telescope ($Insight$-HXMT) was successfully launched on June 15th, 2017. It performs broad band X-ray scan survey of the Galactic Plane to detect new black holes and other objects in active states. It also observes X-ray binaries to study their X-ray variabilities. Here we will introduce the Science Operations of $Insight$-HXMT, which is responsible for collecting and evaluating observation proposals, scheduling observations, and monitoring the working status of the payloads.
Since July 2014, the Gaia mission has been engaged in a high-spatial-resolution, time-resolved, precise, accurate astrometric, and photometric survey of the entire sky. Aims: We present the Gaia Science Alerts project, which has been in operation since 1 June 2016. We describe the system which has been developed to enable the discovery and publication of transient photometric events as seen by Gaia. Methods: We outline the data handling, timings, and performances, and we describe the transient detection algorithms and filtering procedures needed to manage the high false alarm rate. We identify two classes of events: (1) sources which are new to Gaia and (2) Gaia sources which have undergone a significant brightening or fading. Validation of the Gaia transit astrometry and photometry was performed, followed by testing of the source environment to minimise contamination from Solar System objects, bright stars, and fainter near-neighbours. Results: We show that the Gaia Science Alerts project suffers from very low contamination, that is there are very few false-positives. We find that the external completeness for supernovae, $C_E=0.46$, is dominated by the Gaia scanning law and the requirement of detections from both fields-of-view. Where we have two or more scans the internal completeness is $C_I=0.79$ at 3 arcsec or larger from the centres of galaxies, but it drops closer in, especially within 1 arcsec. Conclusions: The per-transit photometry for Gaia transients is precise to 1 per cent at $G=13$, and 3 per cent at $G=19$. The per-transit astrometry is accurate to 55 milliarcseconds when compared to Gaia DR2. The Gaia Science Alerts project is one of the most homogeneous and productive transient surveys in operation, and it is the only survey which covers the whole sky at high spatial resolution (subarcsecond), including the Galactic plane and bulge.
We present discrete-event simulation models of the operations of primary health centres (PHCs) in the Indian context. Our PHC simulation models incorporate four types of patients seeking medical care: outpatients, inpatients, childbirth cases, and patients seeking antenatal care. A generic modelling approach was adopted to develop simulation models of PHC operations. This involved developing an archetype PHC simulation, which was then adapted to represent two other PHC configurations, differing in numbers of resources and types of services provided, encountered during PHC visits. A model representing a benchmark configuration conforming to government-mandated operational guidelines, with demand estimated from disease burden data and service times closer to international estimates (higher than observed), was also developed. Simulation outcomes for the three observed configurations indicate negligible patient waiting times and low resource utilisation values at observed patient demand estimates. However, simulation outcomes for the benchmark configuration indicated significantly higher resource utilisation. Simulation experiments to evaluate the effect of potential changes in operational patterns on reducing the utilisation of stressed resources for the benchmark case were performed. Our analysis also motivated the development of simple analytical approximations of the average utilisation of a server in a queueing system with characteristics similar to the PHC doctor/patient system. Our study represents the first step in an ongoing effort to establish the computational infrastructure required to analyse public health operations in India, and can provide researchers in other settings with hierarchical health systems a template for the development of simulation models of their primary healthcare facilities.
The Met Office Space Weather Operations Centre produces 24/7/365 space weather guidance, alerts, and forecasts to a wide range of government and commercial end users across the United Kingdom. Solar flare forecasts are one of its products, which are issued multiple times a day in two forms; forecasts for each active region on the solar disk over the next 24 hours, and full-disk forecasts for the next four days. Here the forecasting process is described in detail, as well as first verification of archived forecasts using methods commonly used in operational weather prediction. Real-time verification available for operational flare forecasting use is also described. The influence of human forecasters is highlighted, with human-edited forecasts outperforming original model results, and forecasting skill decreasing over longer forecast lead times.
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