The Generalized Method of Wavelet Moments with Exogenous Inputs: a Fast Approach for the Analysis of GNSS Position Time Series

The Global Navigation Satellite System (GNSS) daily position time series are often described as the sum of stochastic processes and geophysical signals which allow studying global and local geodynamical effects such as plate tectonics, earthquakes, or ground water variations. In this work we propose to extend the Generalized Method of Wavelet Moments (GMWM) to estimate the parameters of linear models with correlated residuals. This statistical inferential framework is applied to GNSS daily position time series data to jointly estimate functional (geophysical) as well as stochastic noise models. Our method is called GMWMX, with X standing for eXogeneous variable: it is semi-parametric, computationally efficient and scalable. Unlike standard methods such as the widely used Maximum Likelihood Estimator (MLE), our methodology offers statistical guarantees, such as consistency and asymptotic normality, without relying on strong parametric assumptions. At the Gaussian model, our results show that the estimated parameters are similar to the ones obtained with the MLE. The computational performances of our approach has important practical implications. Indeed, the estimation of the parameters of large networks of thousands of GNSS stations quickly becomes computationally prohibitive. Compared to standard methods, the processing time of the GMWMX is over $1000$ times faster and allows the estimation of large scale problems within minutes on a standard computer. We validate the performances of our method via Monte-Carlo simulations by generating GNSS daily position time series with missing observations and we consider composite stochastic noise models including processes presenting long-range dependence such as power-law or Mat\'ern processes. The advantages of our method are also illustrated using real time series from GNSS stations located in the Eastern part of the USA.Comment: 30 pages, 11 figures, 3 table

Estimation of offsets in GPS time-series and application to the detection of earthquake deformation in the far-field

Extracting geophysical signals from Global Positioning System (GPS) coordinate time-series is a well-established practice that has led to great insights into how the Earth deforms. Often small discontinuities are found in such time-series and are traceable to either broad-scale deformation (i.e. earthquakes) or discontinuities due to equipment changes and/or failures. Estimating these offsets accurately enables the identification of coseismic deformation estimates in the former case, and the removal of unwanted signals in the latter case which then allows tectonic rates to be estimated more accurately. We develop a method to estimate accurately discontinuities in time series of GPS positions at specified epochs, based on a so-called ‘offset series’. The offset series are obtained by varying the amount of GPS data before and after an event while estimating the offset. Two methods, a mean and a weighted mean method, are then investigated to produce the estimated discontinuity from the offset series. The mean method estimates coseismic offsets without making assumptions about geophysical processes that may be present in the data (i.e. tectonic rate, seasonal variations), whereas the weighted mean method includes estimating coseismic offsets with a model of these processes. We investigate which approach is the most appropriate given certain lengths of available data and noise within the time-series themselves. For the Sumatra–Andaman event, with 4.5 yr of pre-event data, we show that between 2 and 3 yr of post-event data are required to produce accurate offset estimates with the weighted mean method. With less data, the mean method should be used, but the uncertainties of the estimated discontinuity are larger

Chicken Embryonic-Stem Cells Are Permissive to Poxvirus Recombinant Vaccine Vectors.

The discovery of mammalian pluripotent embryonic stem cells (ESC) has revolutionised cell research and regenerative medicine. More recently discovered chicken ESC (cESC), though less intensively studied, are increasingly popular as vaccine substrates due to a dearth of avian cell lines. Information on the comparative performance of cESC with common vaccine viruses is limited. Using RNA-sequencing, we compared cESC transcriptional programmes elicited by stimulation with chicken type I interferon or infection with vaccine viruses routinely propagated in primary chicken embryo fibroblasts (CEF). We used poxviruses (fowlpox virus (FWPV) FP9, canarypox virus (CNPV), and modified vaccinia virus Ankara (MVA)) and a birnavirus (infectious bursal disease virus (IBDV) PBG98). Interferon-stimulated genes (ISGs) were induced in cESC to levels comparable to those in CEF and immortalised chicken fibroblast DF-1 cells. cESC are permissive (with distinct host transcriptional responses) to MVA, FP9, and CNPV but, surprisingly, not to PBG98. MVA, CNPV, and FP9 suppressed innate immune responses, while PBG98 induced a subset of ISGs. Dysregulation of signalling pathways (i.e., NFκB, TRAF) was observed, which might affect immune responses and viral replication. In conclusion, we show that cESC are an attractive alternative substrate to study and propagate poxvirus recombinant vaccine vectors

Satellite mapping in cities and below cities: how good is it now?

Global navigation satellite systems (GNSS) have existed since the launch of the US global positioning system constellation in 1978. There is an increasing need for better maps in the digital age, particularly for buried utilities. One of the most convenient methods for creating accurate maps is the use of navigation satellites for positioning. However, built-up urban areas are not ideal for the use of this positioning technology. This paper provides an update on the situation regarding GNSS and assesses how new satellites and signals are contributing to better positioning availability by carrying out a test in a controlled environment. The results show that using combined satellite systems improves availability in urban canyons in some cases, but not in all scenarios. In addition, pipeline mapping technology has been tested and been shown to be an effective means of mapping pipes deep under the ground over short distances

Investigating multi-GNSS performance in the UK and China based on a zero-baseline measurement approach

GPS is the positioning tool of choice for a wide variety of applications where accurate (cm level or less) positions are required. However GPS is susceptible to a variety of errors that degrade both the quality of the position solution and the availability of these solutions. The contribution of additional observations from other GNSS systems may improve the quality of the positioning solution. This study investigates the contribution of the GLONASS and BeiDou systems and the potential improvement to the precision achieved compared to positioning using GPS only measurements. Furthermore, it is investigated whether the combination of the satellite systems can limit the noise level of the GPS-only solution. A series of zero-baseline measurements, of 1 Hz sampling rate, were recorded with different types of pairs of receivers over 12 consecutive days in the UK and in China simultaneously. The novel part in this study is comparing the simultaneous GNSS real measurements recorded in the UK and China. Moreover, the correlation between the geometry and positional precision was investigated. The results indicate an improvement in a multi-GNSS combined solution compared to the GPS-only solution, especially when the GPS-only solution derives from weak satellite geometry, or the GPS-only solution is not available. Furthermore, all the outliers due to poor satellite coverage with the individual solutions are limited and their precision is improved, agreeing also with the improvement in the mean of the GDOP, i.e. the mean GDOP was improved from 3.0 for the GPS only solution to 1.8 for the combined solution. However, the combined positioning did not show significant positional improvement when GPS has a good geometry and availability

Markov Chain Monte Carlo and the Application to Geodetic Time Series Analysis

The time evolution of geophysical phenomena can be characterised by stochastic time series. The stochastic nature of the signal stems from the geophysical phenomena involved and any noise, which may be due to, e.g., un-modelled effects or measurement errors. Until the 1990's, it was usually assumed that white noise could fully characterise this noise. However, this was demonstrated to be not the case and it was proven that this assumption leads to underestimated uncertainties of the geophysical parameters inferred from the geodetic time series. Therefore, in order to fully quantify all the uncertainties as robustly as possible, it is imperative to estimate not only the deterministic but also the stochastic parameters of the time series. In this regard, the Markov Chain Monte Carlo (MCMC) method can provide a sample of the distribution function of all parameters, including those regarding the noise, e.g., spectral index and amplitudes. After presenting the MCMC method and its implementation in our MCMC software we apply it to synthetic and real time series and perform a cross-evaluation using Maximum Likelihood Estimation (MLE) as implemented in the CATS software. Several examples as to how the MCMC method performs as a parameter estimation method for geodetic time series are given in this chapter. These include the applications to GPS position time series, superconducting gravity time series and monthly mean sea level (MSL) records, which all show very different stochastic properties. The impact of the estimated parameter uncertainties on sub-sequentially derived products is briefly demonstrated for the case of plate motion models. Finally, the MCMC results for weekly downsampled versions of the benchmark synthetic GNSS time series as provided in Chapter 2 are presented separately in an appendix

Cytostatic Factor Proteins Are Present in Male Meiotic Cells and β-Nerve Growth Factor Increases Mos Levels in Rat Late Spermatocytes

Background: In co-cultures of pachytene spermatocytes with Sertoli cells, beta-NGF regulates the second meiotic division by blocking secondary spermatocytes in metaphase (metaphase II), and thereby lowers round spermatid formation. In vertebrates, mature oocytes are arrested at metaphase II until fertilization, because of the presence of cytostatic factor (CSF) in their cytoplasm. By analogy, we hypothesized the presence of CSF in male germ cells. Methodology/Principal Findings: We show here, that Mos, Emi2, cyclin E and Cdk2, the four proteins of CSF, and their respective mRNAs, are present in male rat meiotic cells; this was assessed by using Western blotting, immunocytochemistry and reverse transcriptase PCR. We measured the relative cellular levels of Mos, Emi2, Cyclin E and Cdk2 in the meiotic cells by flow cytometry and found that the four proteins increased throughout the first meiotic prophase, reaching their highest levels in middle to late pachytene spermatocytes, then decreased following the meiotic divisions. In co-cultures of pachytene spermatocytes with Sertoli cells, beta-NGF increased the number of metaphases II, while enhancing Mos and Emi2 levels in middle to late pachytene spermatocytes, pachytene spermatocytes in division and secondary spermatocytes. Conclusion/Significance: Our results suggest that CSF is not restricted to the oocyte. In addition, they reinforce the view that NGF, by enhancing Mos in late spermatocytes, is one of the intra-testicular factors which adjusts the number of round spermatids that can be supported by Sertoli cells

Transcriptome Analysis of H2O2-Treated Wheat Seedlings Reveals a H2O2-Responsive Fatty Acid Desaturase Gene Participating in Powdery Mildew Resistance

Hydrogen peroxide (H2O2) plays important roles in plant biotic and abiotic stress responses. However, the effect of H2O2 stress on the bread wheat transcriptome is still lacking. To investigate the cellular and metabolic responses triggered by H2O2, we performed an mRNA tag analysis of wheat seedlings under 10 mM H2O2 treatment for 6 hour in one powdery mildew (PM) resistant (PmA) and two susceptible (Cha and Han) lines. In total, 6,156, 6,875 and 3,276 transcripts were found to be differentially expressed in PmA, Han and Cha respectively. Among them, 260 genes exhibited consistent expression patterns in all three wheat lines and may represent a subset of basal H2O2 responsive genes that were associated with cell defense, signal transduction, photosynthesis, carbohydrate metabolism, lipid metabolism, redox homeostasis, and transport. Among genes specific to PmA, ‘transport’ activity was significantly enriched in Gene Ontology analysis. MapMan classification showed that, while both up- and down- regulations were observed for auxin, abscisic acid, and brassinolides signaling genes, the jasmonic acid and ethylene signaling pathway genes were all up-regulated, suggesting H2O2-enhanced JA/Et functions in PmA. To further study whether any of these genes were involved in wheat PM response, 19 H2O2-responsive putative defense related genes were assayed in wheat seedlings infected with Blumeria graminis f. sp. tritici (Bgt). Eight of these genes were found to be co-regulated by H2O2 and Bgt, among which a fatty acid desaturase gene TaFAD was then confirmed by virus induced gene silencing (VIGS) to be required for the PM resistance. Together, our data presents the first global picture of the wheat transcriptome under H2O2 stress and uncovers potential links between H2O2 and Bgt responses, hence providing important candidate genes for the PM resistance in wheat