Optimum satellite relay positions with application to a TDRS-1 Indian Ocean relay

An Indian Ocean satellite relay is examined. The relay satellite position is optimized by minimizing the sum of downlink and satellite to satellite link losses. Osculating orbital elements are used for fast intensive orbital computation. Integrated Van Vleck gaseous attenuation and a Crane rain model are used for downlink attenuation. Circular polarization losses on the satellite to satellite link are found dynamically. Space to ground link antenna pointing losses are included as a function of yaw ans spacecraft limits. Relay satellite positions between 90 to 100 degrees East are found attractive for further study

Downlink Probability Density Functions for EOS-McMurdo Sound

The visibility times and communication link dynamics for the Earth Observations Satellite (EOS)-McMurdo Sound direct downlinks have been studied. The 16 day EOS periodicity may be shown with the Goddard Trajectory Determination System (GTDS) and the entire 16 day period should be simulated for representative link statistics. We desire many attributes of the downlink, however, and a faster orbital determination method is desirable. We use the method of osculating elements for speed and accuracy in simulating the EOS orbit. The accuracy of the method of osculating elements is demonstrated by closely reproducing the observed 16 day Landsat periodicity. An autocorrelation function method is used to show the correlation spike at 16 days. The entire 16 day record of passes over McMurdo Sound is then used to generate statistics for innage time, outage time, elevation angle, antenna angle rates, and propagation loss. The levation angle probability density function is compared with 1967 analytic approximation which has been used for medium to high altitude satellites. One practical result of this comparison is seen to be the rare occurrence of zenith passes. The new result is functionally different than the earlier result, with a heavy emphasis on low elevation angles. EOS is one of a large class of sun synchronous satellites which may be downlinked to McMurdo Sound. We examine delay statistics for an entire group of sun synchronous satellites ranging from 400 km to 1000 km altitude. Outage probability density function results are presented three dimensionally

Survival extrapolation in the presence of cause specific hazards.

Health economic evaluations require estimates of expected survival from patients receiving different interventions, often over a lifetime. However, data on the patients of interest are typically only available for a much shorter follow-up time, from randomised trials or cohorts. Previous work showed how to use general population mortality to improve extrapolations of the short-term data, assuming a constant additive or multiplicative effect on the hazards for all-cause mortality for study patients relative to the general population. A more plausible assumption may be a constant effect on the hazard for the specific cause of death targeted by the treatments. To address this problem, we use independent parametric survival models for cause-specific mortality among the general population. Because causes of death are unobserved for the patients of interest, a polyhazard model is used to express their all-cause mortality as a sum of latent cause-specific hazards. Assuming proportional cause-specific hazards between the general and study populations then allows us to extrapolate mortality of the patients of interest to the long term. A Bayesian framework is used to jointly model all sources of data. By simulation, we show that ignoring cause-specific hazards leads to biased estimates of mean survival when the proportion of deaths due to the cause of interest changes through time. The methods are applied to an evaluation of implantable cardioverter defibrillators for the prevention of sudden cardiac death among patients with cardiac arrhythmia. After accounting for cause-specific mortality, substantial differences are seen in estimates of life years gained from implantable cardioverter defibrillators

Calibration of complex models through Bayesian evidence synthesis: a demonstration and tutorial.

Decision-analytic models must often be informed using data that are only indirectly related to the main model parameters. The authors outline how to implement a Bayesian synthesis of diverse sources of evidence to calibrate the parameters of a complex model. A graphical model is built to represent how observed data are generated from statistical models with unknown parameters and how those parameters are related to quantities of interest for decision making. This forms the basis of an algorithm to estimate a posterior probability distribution, which represents the updated state of evidence for all unknowns given all data and prior beliefs. This process calibrates the quantities of interest against data and, at the same time, propagates all parameter uncertainties to the results used for decision making. To illustrate these methods, the authors demonstrate how a previously developed Markov model for the progression of human papillomavirus (HPV-16) infection was rebuilt in a Bayesian framework. Transition probabilities between states of disease severity are inferred indirectly from cross-sectional observations of prevalence of HPV-16 and HPV-16-related disease by age, cervical cancer incidence, and other published information. Previously, a discrete collection of plausible scenarios was identified but with no further indication of which of these are more plausible. Instead, the authors derive a Bayesian posterior distribution, in which scenarios are implicitly weighted according to how well they are supported by the data. In particular, we emphasize the appropriate choice of prior distributions and checking and comparison of fitted models

Cost-effectiveness of initial stress cardiovascular MR, stress SPECT or stress echocardiography as a gate-keeper test, compared with upfront invasive coronary angiography in the investigation and management of patients with stable chest pain: Mid-term outcomes from the CECaT randomised controlled trial

Objectives: To compare outcomes and cost-effectiveness of various initial imaging strategies in the management of stable chest pain in a long-term prospective randomised trial. Setting: Regional cardiothoracic referral centre in the east of England. Participants: 898 patients (69% man) entered the study with 869 alive at 2 years of follow-up. Patients were included if they presented for assessment of stable chest pain with a positive exercise test and no prior history of ischaemic heart disease. Exclusion criteria were recent infarction, unstable symptoms or any contraindication to stress MRI. Primary outcome measures: The primary outcomes of this follow-up study were survival up to a minimum of 2 years post-treatment, quality-adjusted survival and cost-utility of each strategy. Results: 898 patients were randomised. Compared with angiography, mortality was marginally higher in the groups randomised to cardiac MR (HR 2.6, 95% CI 1.1 to 6.2), but similar in the single photon emission CT-methoxyisobutylisonitrile (SPECT-MIBI; HR 1.0, 95% CI 0.4 to 2.9) and ECHO groups (HR 1.6, 95% CI 0.6 to 4.0). Although SPECT-MIBI was marginally superior to other non-invasive tests there were no other significant differences between the groups in mortality, quality-adjusted survival or costs. Conclusions: Non-invasive cardiac imaging can be used safely as the initial diagnostic test to diagnose coronary artery disease without adverse effects on patient outcomes or increased costs, relative to angiography. These results should be interpreted in the context of recent advances in imaging technology. Trial registration: ISRCTN 47108462, UKCRN 3696

Non-parametric frailty Cox models for hierarchical time-to-event data.

We propose a novel model for hierarchical time-to-event data, for example, healthcare data in which patients are grouped by their healthcare provider. The most common model for this kind of data is the Cox proportional hazard model, with frailties that are common to patients in the same group and given a parametric distribution. We relax the parametric frailty assumption in this class of models by using a non-parametric discrete distribution. This improves the flexibility of the model by allowing very general frailty distributions and enables the data to be clustered into groups of healthcare providers with a similar frailty. A tailored Expectation-Maximization algorithm is proposed for estimating the model parameters, methods of model selection are compared, and the code is assessed in simulation studies. This model is particularly useful for administrative data in which there are a limited number of covariates available to explain the heterogeneity associated with the risk of the event. We apply the model to a clinical administrative database recording times to hospital readmission, and related covariates, for patients previously admitted once to hospital for heart failure, and we explore latent clustering structures among healthcare providers.MR

Investigation of the chemocatalytic and biocatalytic valorization of a range of different lignin preparations: The importance of β-O-4 content

A set of seven different lignin preparations was generated from a range of organosolv (acidic, alkaline, ammonia-treated, and dioxane-based), ionic liquid, autohydrolysis, and Kraft pretreatments of lignocelluloses. Each lignin was characterized by 2D HSQC NMR spectroscopy, showing significant variability in the β-O-4 content of the different lignin samples. Each lignin was then valorised using three biocatalytic methods (microbial biotransformation with Rhodococcus jostii RHA045, treatment with Pseudomonas fluorescens Dyp1B or Sphingobacterium sp. T2 manganese superoxide dismutase) and two chemocatalytic methods (catalytic hydrogenation using Pt/alumina catalyst, DDQ benzylic oxidation/Zn reduction). Highest product yields for DDQ/Zn valorization were observed from poplar ammonia percolation-organosolv lignin, which had the highest β-O-4 content of the investigated lignins and also gave the highest yield of syringaldehyde (243 mg L -1 ) when using R. jostii RHA045 and the most enzymatic products using P. fluorescens Dyp1B. The highest product yield from the Pt/alumina hydrogenation was observed using oak dioxasolv lignin, which also had a high β-O-4 content. In general, highest product yields for both chemocatalytic and biocatalytic valorization methods were obtained from preparations that showed highest β-O-4 content, while variable yields were obtained with preparations containing intermediate β-O-4 content, and little or no product was obtained with preparations containing low β-O-4 content

Perchlorate and Volatiles of the Brine of Lake Vida (Antarctica): Implication for the in Situ Analysis of Mars Sediments

The cold (-13.4 C), cryoencapsulated, anoxic, interstitial brine of the 27 m-thick ice of Lake Vida (Victoria Valley, Antarctica) contains 49 microgram L-1 of perchlorate and 11 microgram L-1 of chlorate. Lake Vida brine (LVBr) may provide an analog for potential oxychlorine-rich subsurface brine on Mars. LVBr volatiles were analyzed by solid-phase microextraction (SPME) gas chromatography-mass spectrometry (GC-MS) with two different SPME fibers. With the exception of volatile organic sulfur compounds, most other volatiles observed were artifacts produced in the GC injector when the thermal decomposition products of oxychlorines reacted with reduced carbon derived from LVBr and the SPME fiber phases. Analysis of MilliQ water with perchlorate (40 microgram L-1) showed low level of organic artifacts, reflecting carbon limitation. In order to observe sample-derived organic compounds, both in analog samples and on Mars, the molar abundance of reduced carbon in a sample must exceed those of O2 and Cl2 produced during decomposition of oxychlorines. This suggests that the abundance of compounds observed by the Sample Analysis at Mars (SAM) instruments in Sheepbed samples (CB-3, CB5, and CB6) may be controlled by an increase in the reduced-carbon/oxychlorine ratio of these samples. To increase chances of in situ detection of Martian organics during pyrolysis-GC-MS, we propose that the derivatization agents stored on SAM may be used as an external source of reduced carbon, increasing artificially the reduced-carbon to perchlorate ratio during pyrolysis, allowing the expression of more abundant and perhaps more diverse Martian organic matter