A novel laser ranging system for measurement of ground-to-satellite distances

A technique was developed for improving the precision of laser ranging measurements of ground-to-satellite distances. The method employs a mode-locked laser transmitter and utilizes an image converter tube equipped with deflection plates in measuring the time of flight of the laser pulse to a distant retroreflector and back. Samples of the outgoing and returning light pulses are focussed on the photocathode of the image converter tube, whose deflection plates are driven by a high-voltage 120 MHz sine wave derived from a very stable oscillator. From the relative positions of the images produced at the output phosphor by the two light pulses, it is possible to make a precise determination of the fractional amount by which the time of flight exceeds some large integral multiple of the period of the deflection sinusoid

The quantum paraelectric behavior of SrTiO_{3} revisited: relevance of the structural phase transition temperature

It has been known for a long time that the low temperature behavior shown by the dielectric constant of quantum paraelectric $SrTiO_{3}$ can not be fitted properly by Barrett's formula using a single zero point energy or saturation temperature ($T_{1}$). As it was originally shown [K. A. M\"{u}ller and H. Burkard, Phys. Rev. B {\bf 19}, 3593 (1979)] a crossover between two different saturation temperatures ($T_{1l}$=77.8K and $T_{1h}$=80K) at $T\sim10K$ is needed to explain the low and high temperature behavior of the dielectric constant. However, the physical reason for the crossover between these two particular values of the saturation temperature at $T\sim10K$ is unknown. In this work we show that the crossover between these two values of the saturation temperature at $T\sim10K$ can be taken as a direct consequence of (i) the quantum distribution of frequencies $g(\Omega)\propto\Omega^{2}$ associated with the complete set of low-lying modes and (ii) the existence of a definite maximum phonon frequency given by the structural transition critical temperature $T_{tr}$.Comment: 8 pages, 3 figure

Transforming discrete choice experiment latent scale values for EQ-5D-3L using the visual analogue scale

Background Discrete choice experiments (DCEs) are widely used to elicit health state preferences. However, additional information is required to transform values to a scale with dead valued at 0 and full health valued at 1. This paper presents DCE-VAS, an understandable and easy anchoring method with low participant burden based on the visual analogue scale (VAS). Methods Responses from 1450 members of the UK general public to a discrete choice experiment (DCE) were analysed using mixed logit models. Latent scale valuations were anchored to a full health = 1, dead = 0 scale using participants’ VAS ratings of three states including the dead. The robustness of results was examined. This included a filtering procedure with the influence each individual respondent had on valuation being calculated, and those whose influence was more than two standard deviations away from the mean excluded. Results Coefficients in all models were in the expected direction and statistically significant. Excluding respondents who self-reported not understanding the VAS task did not significantly influence valuation, but excluding a small number who valued 33333 extremely low did. However, after eight respondents were removed via the filtering procedure, valuations were robust to removing other participants. Conclusion DCE-VAS is a feasible way of anchoring DCE results to a 0–1 anchored scale with low additional respondent burden

Unsupervised machine learning of integrated health and social care data from the Macmillan Improving the Cancer Journey service in Glasgow

Background: Improving the Cancer Journey (ICJ) was launched in 2014 by Glasgow City Council and Macmillan Cancer Support. As part of routine service, data is collected on ICJ users including demographic and health information, results from holistic needs assessments and quality of life scores as measured by EQ-5D health status. There is also data on the number and type of referrals made and feedback from users on the overall service. By applying artificial intelligence and interactive visualization technologies to this data, we seek to improve service provision and optimize resource allocation.Method: An unsupervised machine-learning algorithm was deployed to cluster the data. The classical k-means algorithm was extended with the k-modes technique for categorical data, and the gap heuristic automatically identified the number of clusters. The resulting clusters are used to summarize complex data sets and produce three-dimensional visualizations of the data landscape. Furthermore, the traits of new ICJ clients are predicted by approximately matching their details to the nearest existing cluster center.Results: Cross-validation showed the model’s effectiveness over a wide range of traits. For example, the model can predict marital status, employment status and housing type with an accuracy between 2.4 to 4.8 times greater than random selection. One of the most interesting preliminary findings is that area deprivation (measured through Scottish Index of Multiple Deprivation-SIMD) is a better predictor of an ICJ client’s needs than primary diagnosis (cancer type).Conclusion: A key strength of this system is its ability to rapidly ingest new data on its own and derive new predictions from those data. This means the model can guide service provision by forecasting demand based on actual or hypothesized data. The aim is to provide intelligent person-centered recommendations. The machine-learning model described here is part of a prototype software tool currently under development for use by the cancer support community.Disclosure: Funded by Macmillan Cancer Support</p

Dynamical elastic bodies in Newtonian gravity

Well-posedness for the initial value problem for a self-gravitating elastic body with free boundary in Newtonian gravity is proved. In the material frame, the Euler-Lagrange equation becomes, assuming suitable constitutive properties for the elastic material, a fully non-linear elliptic-hyperbolic system with boundary conditions of Neumann type. For systems of this type, the initial data must satisfy compatibility conditions in order to achieve regular solutions. Given a relaxed reference configuration and a sufficiently small Newton's constant, a neigborhood of initial data satisfying the compatibility conditions is constructed

Research Directions in Network Service Chaining

Network Service Chaining (NSC) is a service deployment concept that promises increased flexibility and cost efficiency for future carrier networks. NSC has received considerable attention in the standardization and research communities lately. However, NSC is largely undefined in the peer-reviewed literature. In fact, a literature review reveals that the role of NSC enabling technologies is up for discussion, and so are the key research challenges lying ahead. This paper addresses these topics by motivating our research interest towards advanced dynamic NSC and detailing the main aspects to be considered in the context of carrier-grade telecommunication networks. We present design considerations and system requirements alongside use cases that illustrate the advantages of adopting NSC. We detail prominent research challenges during the typical lifecycle of a network service chain in an operational telecommunications network, including service chain description, programming, deployment, and debugging, and summarize our security considerations. We conclude this paper with an outlook on future work in this are

Quasar accretion disk sizes from continuum reverberation mapping in the DES standard-star fields

Measurements of the physical properties of accretion disks in active galactic nuclei are important for better understanding the growth and evolution of supermassive black holes. We present the accretion disk sizes of 22 quasars from continuum reverberation mapping with data from the Dark Energy Survey (DES) standard star fields and the supernova C fields. We construct continuum lightcurves with the \textit{griz} photometry that span five seasons of DES observations. These data sample the time variability of the quasars with a cadence as short as one day, which corresponds to a rest frame cadence that is a factor of a few higher than most previous work. We derive time lags between bands with both JAVELIN and the interpolated cross-correlation function method, and fit for accretion disk sizes using the JAVELIN Thin Disk model. These new measurements include disks around black holes with masses as small as $\sim10^7$ $M_{\odot}$, which have equivalent sizes at 2500\AA \, as small as $\sim 0.1$ light days in the rest frame. We find that most objects have accretion disk sizes consistent with the prediction of the standard thin disk model when we take disk variability into account. We have also simulated the expected yield of accretion disk measurements under various observational scenarios for the Large Synoptic Survey Telescope Deep Drilling Fields. We find that the number of disk measurements would increase significantly if the default cadence is changed from three days to two days or one day.Comment: 33 pages, 24 figure