DIA-datasnooping and identifiability

In this contribution, we present and analyze datasnooping in the context of the DIA method. As the DIA method for the detection, identification and adaptation of mismodelling errors is concerned with estimation and testing, it is the combination of both that needs to be considered. This combination is rigorously captured by the DIA estimator. We discuss and analyze the DIA-datasnooping decision probabilities and the construction of the corresponding partitioning of misclosure space. We also investigate the circumstances under which two or more hypotheses are nonseparable in the identification step. By means of a theorem on the equivalence between the nonseparability of hypotheses and the inestimability of parameters, we demonstrate that one can forget about adapting the parameter vector for hypotheses that are nonseparable. However, as this concerns the complete vector and not necessarily functions of it, we also show that parameter functions may exist for which adaptation is still possible. It is shown how this adaptation looks like and how it changes the structure of the DIA estimator. To demonstrate the performance of the various elements of DIA-datasnooping, we apply the theory to some selected examples. We analyze how geometry changes in the measurement setup affect the testing procedure, by studying their partitioning of misclosure space, the decision probabilities and the minimal detectable and identifiable biases. The difference between these two minimal biases is highlighted by showing the difference between their corresponding contributing factors. We also show that if two alternative hypotheses, say (Formula presented.) and (Formula presented.), are nonseparable, the testing procedure may have different levels of sensitivity to (Formula presented.)-biases compared to the same (Formula presented.)-biases

Testing of a new single-frequency GNSS carrier phase attitude determination method: land, ship and aircraft experiments

Global navigation satellite system (GNSS) ambiguity resolution is the process of resolving the unknown cycle ambiguities of the carrier phase data as integers. The sole purpose of ambiguity resolution is to use the integer ambiguity constraints as a means of improving significantly on the precision of the remaining GNSS model parameters. In this contribution, we consider the problem of ambiguity resolution for GNSS attitude determination. We analyse the performance of a new ambiguity resolution method for GNSS attitude determination. As it will be shown, this method provides a numerically efficient, highly reliable and robust solution of the nonlinearly constrained integer least-squares GNSS compass estimators. The analyses have been done by means of a unique set of extensive experimental tests, using simulated as well as actual GNSS data and using receivers of different manufacturers and type as well as different platforms. The executed field tests cover two static land experiments, one in the Netherlands and one in Australia, and two dynamic experiments, a low-dynamics vessel experiment and high-dynamics aircraft experiment. In our analyses, we focus on stand-alone, unaided, single-frequency, single epoch attitude determination, as this is the most challenging case of GNSS compass processing

Distributional theory for the DIA method

The DIA method for the detection, identification and adaptation of model misspecifications combines estimation with testing. The aim of the present contribution is to introduce a unifying framework for the rigorous capture of this combination. By using a canonical model formulation and a partitioning of misclosure space, we show that the whole estimation–testing scheme can be captured in one single DIA estimator. We study the characteristics of this estimator and discuss some of its distributional properties. With the distribution of the DIA estimator provided, one can then study all the characteristics of the combined estimation and testing scheme, as well as analyse how they propagate into final outcomes. Examples are given, as well as a discussion on how the distributional properties compare with their usage in practice

Low-cost, high-precision, single-frequency GPS–BDS RTK positioning

The integration of the Chinese BDS with other systems, such as the American GPS, makes precise RTK positioning possible with low-cost receivers. We investigate the performance of low-cost ublox receivers, which cost a few hundred USDs, while making use of L1 GPS + B1 BDS data in Dunedin, New Zealand. Comparisons will be made to L1 + L2 GPS and survey-grade receivers which cost several thousand USDs. The least-squares variance component estimation procedure is used to determine the code and phase variances and covariances of the receivers and thus formulate a realistic stochastic model. Otherwise, the ambiguity resolution and hence positioning performance would deteriorate. For the same reasons, the existence of receiver-induced time correlation is also investigated. The low-cost RTK performance is then evaluated by formal and empirical ambiguity success rates and positioning precisions. It will be shown that the code and phase precision of the low-cost receivers can be significantly improved by using survey-grade antennas, since they have better signal reception and multipath suppression abilities in comparison with low-cost patch antennas. It will also be demonstrated that the low-cost receivers can achieve competitive ambiguity resolution and positioning performance to survey-grade dual-frequency GPS receivers

Importance of highly selective LC–MS/MS analysis for the accurate quantification of tamoxifen and its metabolites: focus on endoxifen and 4-hydroxytamoxifen

The antiestrogenic effect of tamoxifen is mainly attributable to the active metabolites endoxifen and 4-hydroxytamoxifen. This effect is assumed to be concentration-dependent and therefore quantitative analysis of tamoxifen and metabolites for clinical studies and therapeutic drug monitoring is increasing. We investigated the large discrepancies in reported mean endoxifen and 4-hydroxytamoxifen concentrations. Two published LC–MS/MS methods are used to analyse a set of 75 serum samples from patients treated with tamoxifen. The method from Teunissen et al. (J Chrom B, 879:1677–1685, 2011) separates endoxifen and 4-hydroxytamoxifen from other tamoxifen metabolites with similar masses and fragmentation patterns. The second method, published by Gjerde et al. (J Chrom A, 1082:6–14, 2005) however lacks selectivity, resulting in a factor 2–3 overestimation of the endoxifen and 4-hydroxytamoxifen levels, respectively. We emphasize the use of highly selective LC–MS/MS methods for the quantification of tamoxifen and its metabolites in biological samples

S-system theory applied to array-based GNSS ionospheric sensing

The GPS carrier-phase and code data have proven to be valuable sources of measuring the Earth’s ionospheric total electron content (TEC). With the development of new GNSSs with multi frequency data, many more ionosphere-sensing combinations of different precision can be formed as input of ionospheric modelling. We present the general way of interpreting such combinations through an application of S-system theory and address how their precision propagates into that of the unbiased TEC solution. Presenting the data relevant to TEC determination, we propose the usage of an array of GNSS antennas to improve the TEC precision and to expedite the rather long observational time-span required for high-precision TEC determination

A comparison of 3D particle, fluid and hybrid simulations for negative streamers

In the high field region at the head of a discharge streamer, the electron energy distribution develops a long tail. In negative streamers, these electrons can run away and contribute to energetic processes such as terrestrial gamma-ray and electron flashes. Moreover, electron density fluctuations can accelerate streamer branching. To track energies and locations of single electrons in relevant regions, we have developed a 3D hybrid model that couples a particle model in the region of high fields and low electron densities with a fluid model in the rest of the domain. Here we validate our 3D hybrid model on a 3D (super-)particle model for negative streamers in overvolted gaps, and we show that it almost reaches the computational efficiency of a 3D fluid model. We also show that the extended fluid model approximates the particle and the hybrid model well until stochastic fluctuations become important, while the classical fluid model underestimates velocities and ionization densities. We compare density fluctuations and the onset of branching between the models, and we compare the front velocities with an analytical approximation

New developments of biofluid-based biomarkers for routine diagnosis and disease trajectories in frontotemporal dementia

Frontotemporal dementia (FTD) covers a spectrum of neurodegenerative disorders with different phenotypes, genetic backgrounds, and pathological states. Its clinicopathological diversity challenges the diagnostic process and the execution of clinical trials, calling for specific diagnostic biomarkers of pathologic FTD types. There is also a need for biomarkers that facilitate disease staging, quantification of severity, monitoring in clinics and observational studies, and for evaluation of target engagement and treatment response in clinical trials. This review discusses current FTD biofluid-based biomarker knowledge taking into account the differing applications. The limitations, knowledge gaps, and challenges for the development and implementation of such markers are also examined. Strategies to overcome these hurdles are proposed, including the technologies available, patient cohorts, and collaborative research initiatives. Access to robust and reliable biomarkers that define the exact underlying pathophysiological FTD process will meet the needs for specific diagnosis, disease quantitation, clinical monitoring, and treatment development

Prediction of obstructive sleep apnea:comparative performance of three screening instruments on the apnea-hypopnea index and the oxygen desaturation index

PURPOSE: To evaluate the performance of the NoSAS (neck, obesity, snoring, age, sex) score, the STOP-Bang (snoring, tiredness, observed apneas, blood pressure, body mass index, age, neck circumference, gender) questionnaire, and the Epworth sleepiness score (ESS) as a screening tool for obstructive sleep apnea (OSA) severity based on the apnea-hypopnea index (AHI) and the oxygen desaturation index (ODI). METHODS: Data from 235 patients who were monitored by ambulant polysomnography (PSG) were retrospectively analyzed. OSA severity was classified based on the AHI; similar classification categories were made based on the ODI. Discrimination was assessed by the area under the curve (AUC), while predictive parameters were calculated by four-grid contingency tables. RESULTS: The NoSAS score and the STOP-Bang questionnaire were both equally adequate screening tools for the AHI and the ODI with AUC ranging from 0.695 to 0.767 and 0.684 to 0.767, respectively. Both questionnaires perform better when used as a continuous variable. The ESS did not show adequate discrimination for screening for OSA (AUC ranging from 0.450 to 0.525). Male gender, age, and BMI proved to be the strongest individual predictors in this cohort. CONCLUSION: This is the first study to evaluate the predictive performance of three different screening instruments with respect to both the AHI and the ODI. This is important, due to increasing evidence that the ODI may have a higher reproducibility in the clinical setting. The NoSAS score and the STOP-Bang questionnaire proved to be equally adequate to predict OSA severity based on both the AHI and the ODI. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11325-020-02219-6) contains supplementary material, which is available to authorized users