Ionospheric corrections tailored to the Galileo High Accuracy Service

The Galileo High Accuracy Service (HAS) is a new capability of the European Global Navigation Satellite System that is currently under development. The Galileo HAS will start providing satellite orbit and clock corrections (i.e. non-dispersive effects) and soon it will also correct dispersive effects such as inter-frequency biases and, in its full capability, ionospheric delay. We analyse here an ionospheric correction system based on the fast precise point positioning (Fast-PPP) and its potential application to the Galileo HAS. The aim of this contribution is to present some recent upgrades to the Fast-PPP model, with the emphasis on the model geometry and the data used. The results show the benefits of integer ambiguity resolution to obtain unambiguous carrier phase measurements as input to compute the Fast-PPP model. Seven permanent stations are used to assess the errors of the Fast-PPP ionospheric corrections, with baseline distances ranging from 100 to 1000 km from the reference receivers used to compute the Fast-PPP corrections. The 99% of the GPS and Galileo errors in well-sounded areas and in mid-latitude stations are below one total electron content unit. In addition, large errors are bounded by the error prediction of the Fast-PPP model, in the form of the variance of the estimation of the ionospheric corrections. Therefore, we conclude that Fast-PPP is able to provide ionospheric corrections with the required ionospheric accuracy, and realistic confidence bounds, for the Galileo HAS.

Gaussian process NARX model for damage detection in composite aircraft structures

This paper demonstrates the Gaussian process regression model's applicability combined with a nonlinear autoregressive exogenous (NARX) framework using experimental data measured with PZTs' patches bonded in a composite aeronautical structure for concerning a novel SHM strategy. A stiffened carbon-epoxy plate regarding a healthy condition and simulated damage on the center of the bottom part of the stiffener is utilized. Comparing the performance in terms of simulation errors is made to observe if the identified models can represent and predict the waveform with confidence bounds considering the confounding effect produced by noise or possible temperature variations assuming a dataset preprocessed using principal component analysis. The results of the GP-NARX identified model have attested correct classification with a reduced number of false alarms, even with model uncertainties propagation regarding healthy and damaged conditions.

Monte Carlo analysis of frequency domain thermoreflectance data for quantitative measurement of interfacial thermal conductance at solid-liquid interfaces modified with self-assembled monolayers

A Monte Carlo method, implemented for quantifying confidence bounds on thermoreflectance (TR) measurements of interfacial thermal conductance G at solid-liquid interfaces modified with self-assembled monolayers (SAMs) is presented in this paper. Here we used 1-decanethiol (1DT) and 1H,1H,2H,2H-Perfluorodecanethiol (PFDT) SAMs to achieve two distinct work of adhesion. Using TR measurements in conjunction with Monte Carlo simulations, we determined G values to be 51 ± 7 MWm-2K-1, 58 ± 8 MWm-2K-1, and 72 ± 17 MWm-2K-1 for Au-PFDT-H2O, Au-1DT-H2O, and Au-H2O, respectively. Our results with the new confidence bounds position our experimental data on surfaces modified with SAMs comparable to literature. However, contrary to previous results shown in the literature, our data showed that a significant decrease in G can be seen for DI water on bare Au that was exposed in ambient for extended period. Our results indicate that G could be influenced by factors beyond a simple work of adhesion, an indication also seen from the work of Park et al.. To solidify this finding, further investigation is necessary to better understand G dependence on surface wettability.

A Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas Systems

The use of automated insulin delivery systems has become a reality for people with type 1 diabetes (T1D), with several hybrid systems already on the market. One of the particularities of this technology is that the patient is in the loop. People with T1D are the plant to control and also a plant operator, because they may have to provide information to the control loop. The most immediate information provided by patients that affects performance and safety are the announcement of meals and exercise. Therefore, to ensure safety and performance, the human factor impact needs to be addressed by designing fault monitoring strategies. In this paper, a monitoring system is developed to diagnose potential patient modes and faults. The monitoring system is based on the residual generation of a bank of observers. To that aim, a linear parameter varying (LPV) polytopic representation of the system is adopted and a bank of Kalman filters is designed using linear matrix inequalities (LMI). The system uncertainty is propagated using a zonotopic-set representation, which allows determining confidence bounds for each of the observer outputs and residuals. For the detection of modes, a hybrid automaton model is generated and diagnosis is performed by interpreting the events and transitions within the automaton. The developed system is tested in simulation, showing the potential benefits of using the proposed approach for artificial pancreas systems.

Results of comparing astronomical-geodetic and navigational-geodetic methods of determining the components of the deflection of vertical

The authors present the results of comparing the components of deflection of vertical obtained through astronomical-geodetic and navigational-geodetic methods. The first one is based on comparing astronomical and geodetic coordinates of a location. This method has recently been widely implemented in a digital zenith camera systems using a small-sized digital telescope with an astronomical camera based on CCD or CMOS technologies, a high-precision inclinometer and satellite navigation system receiver. In this case, the combination of a telescope, an astronomical camera and an inclinometer enables determining the local direction of the plumb line, expressed by astronomical coordinates, from observations of stars at the zenith and using high-precision star catalogs. The navigational-geodetic method is based on comparing the results of the normal heights’ increments, defined through geometric leveling, and geodetic heights, computed with the relative method of satellite coordinate determinations. For each method, random and systematic components of the error and its confidence bounds were calculated; the absolute values of the deflection of vertical components at two geographically separated points were compared.

Pharmacokinetics of Oral Formulations of Gepotidacin (GSK2140944), a Triazaacenaphthylene Bacterial Type II Topoisomerase Inhibitor, in Healthy Adult and Adolescent Participants

Gepotidacin is a novel, first-in-class triazaacenaphthylene antibiotic that may provide a new treatment option for antibiotic-resistant pathogens. Two pharmacokinetic evaluations of oral gepotidacin are presented; a relative bioavailability study that guided formulation development, followed by an adult and adolescent study of the final formulation. In the relative bioavailability study, after gepotidacin administration to 26 healthy adults as free base roller compacted (RC) tablets, free base high shear wet granulation (HSWG) tablets, and mesylate salt reference capsules, the RC tablet exposure ratios and 90% confidence intervals (CIs) were within the 0.80 to 1.25 confidence bounds; however, the HSWG tablet maximum observed concentration (C max ) was higher compared to the reference (ratio: 1.15; 90% CIs: 1.0113, 1.3047). In the healthy adult (n=16) and adolescent (n=17) study, a gepotidacin mesylate salt tablet was evaluated as a 1,500-mg single dose, 2 doses administered 6 or 12 h apart (6,000 mg total), or placebo. Single-dose mean C max was ∼27% higher in adolescents versus adults and area under the concentration-time curve (AUC) was comparable in both populations. After 2 doses were administered, mean C max was similar for both ages and mean AUC was ∼35% higher in adolescents versus adults. Concentrations increased proportionally with dose. Safety-risk profiles were similar in both ages. Across studies, the most common adverse events were gastrointestinal. Overall, the pharmacokinetics of the final gepotidacin mesylate salt tablet have been well-characterized, enrollment of adolescents into the pivotal trials is supported, and dosing intervals were determined that should provide adequate exposures for microbiological efficacy.

Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction

A promise of genomics in precision medicine is to provide individualized genetic risk predictions. Polygenic risk scores (PRS), computed by aggregating effects from many genomic variants, have been developed as a useful tool in complex disease research. However, the application of PRS as a tool for predicting an individual’s disease susceptibility in a clinical setting is challenging because PRS typically provide a relative measure of risk evaluated at the level of a group of people but not at individual level. Here, we introduce a machine-learning technique, Mondrian Cross-Conformal Prediction (MCCP), to estimate the confidence bounds of PRS-to-disease-risk prediction. MCCP can report disease status conditional probability value for each individual and give a prediction at a desired error level. Moreover, with a user-defined prediction error rate, MCCP can estimate the proportion of sample (coverage) with a correct prediction.