Geocenter coordinates estimated from GNSS data as viewed by perturbation theory

Time series of geocenter coordinates were determined with data of two global navigation satellite systems (GNSSs), namely the U.S. GPS (Global Positioning System) and the Russian GLONASS (Global’naya Nawigatsionnaya Sputnikowaya Sistema). The data was recorded in the years 2008–2011 by a global network of 92 permanently observing GPS/GLONASS receivers. Two types of daily solutions were generated independently for each GNSS, one including the estimation of geocenter coordinates and one without these parameters. A fair agreement for GPS and GLONASS was found in the geocenter x- and y-coordinate series. Our tests, however, clearly reveal artifacts in the z-component determined with the GLONASS data. Large periodic excursions in the GLONASS geocenter z-coordinates of about 40 cm peak-to-peak are related to the maximum elevation angles of the Sun above/below the orbital planes of the satellite system and thus have a period of about 4 months (third of a year). A detailed analysis revealed that the artifacts are almost uniquely governed by the differences of the estimates of direct solar radiation pressure (SRP) in the two solution series (with and without geocenter estimation). A simple formula is derived, describing the relation between the geocenter z-coordinate and the corresponding parameter of the SRP. The effect can be explained by first-order perturbation theory of celestial mechanics. The theory also predicts a heavy impact on the GNSS-derived geocenter if once-per-revolution SRP parameters are estimated in the direction of the satellite’s solar panel axis. Specific experiments using GPS observations revealed that this is indeed the case. Although the main focus of this article is on GNSS, the theory developed is applicable to all satellite observing techniques. We applied the theory to satellite laser ranging (SLR) solutions using LAGEOS. It turns out that the correlation between geocenter and SRP parameters is not a critical issue for the SLR solutions. The reasons are threefold: The direct SRP is about a factor of 30–40 smaller for typical geodetic SLR satellites than for GNSS satellites, allowing it in most cases to not solve for SRP parameters (ruling out the correlation between these parameters and the geocenter coordinates); the orbital arc length of 7 days (which is typically used in SLR analysis) contains more than 50 revolutions of the LAGEOS satellites as compared to about two revolutions of GNSS satellites for the daily arcs used in GNSS analysis; the orbit geometry is not as critical for LAGEOS as for GNSS satellites, because the elevation angle of the Sun w.r.t. the orbital plane is usually significantly changing over 7 days.

Health risk appraisal in older people 6: factors associated with self-reported poor vision and uptake of eye tests in older people

BACKGROUND Although free eye testing is available in the UK from a nation-wide network of optometrists, there is evidence of unrecognised, tractable vision loss amongst older people. A recent review identified this unmet need as a priority for further investigation, highlighting the need to understand public perceptions of eye services and barriers to service access and utilisation. This paper aims to identify risk factors for (1) having poor vision and (2) not having had an eyesight check among community-dwelling older people without an established ophthalmological diagnosis. METHODS Secondary analysis of self-reported data from the ProAge trial. 1792 people without a known ophthalmological diagnosis were recruited from three group practices in London. RESULTS Almost two in ten people in this population of older individuals without known ophthalmological diagnoses had self-reported vision loss, and more than a third of them had not had an eye test in the previous twelve months. In this sample, those with limited education, depressed mood, need for help with instrumental and basic activities of daily living (IADLs and BADLs), and subjective memory complaints were at increased risk of fair or poor self-reported vision. Individuals with basic education only were at increased risk for not having had an eye test in the previous 12 months (OR 1.52, 95% CI 1.17-1.98 p=0.002), as were those with no, or only one chronic condition (OR 1.850, 95% CI 1.382-2.477, p<0.001). CONCLUSIONS Self-reported poor vision in older people without ophthalmological diagnoses is associated with other functional losses, with no or only one chronic condition, and with depression. This pattern of disorders may be the basis for case finding in general practice. Low educational attainment is an independent determinant of not having had eye tests, as well as a factor associated with undiagnosed vision loss. There are other factors, not identified in this study, which determine uptake of eye testing in those with self-reported vision loss. Further exploration is needed to identify these factors and lead towards effective case finding.

Variability between laboratories performing coagulation tests with identical platforms: a nationwide evaluation study.

BACKGROUND While the assessment of analytical precision within medical laboratories has received much attention in scientific enquiry, the degree of as well as the sources causing variation between them remains incompletely understood. In this study, we quantified the variance components when performing coagulation tests with identical analytical platforms in different laboratories and computed intraclass correlations coefficients (ICC) for each coagulation test. METHODS Data from eight laboratories measuring fibrinogen twice in twenty healthy subjects with one out of 3 different platforms and single measurements of prothrombin time (PT), and coagulation factors II, V, VII, VIII, IX, X, XI and XIII were analysed. By platform, the variance components of (i) the subjects, (ii) the laboratory and the technician and (iii) the total variance were obtained for fibrinogen as well as (i) and (iii) for the remaining factors using ANOVA. RESULTS The variability for fibrinogen measurements within a laboratory ranged from 0.02 to 0.04, the variability between laboratories ranged from 0.006 to 0.097. The ICC for fibrinogen ranged from 0.37 to 0.66 and from 0.19 to 0.80 for PT between the platforms. For the remaining factors the ICC's ranged from 0.04 (FII) to 0.93 (FVIII). CONCLUSIONS Variance components that could be attributed to technicians or laboratory procedures were substantial, led to disappointingly low intraclass correlation coefficients for several factors and were pronounced for some of the platforms. Our findings call for sustained efforts to raise the level of standardization of structures and procedures involved in the quantification of coagulation factors.