Analysis of multi-constellation GNSS PPP solutions under phase scintillations at high latitudes

In the past few years, the rapid evolution of multi-constellation navigation satellite systems boosted the development of many scientific and engineering applications. More than 100 satellites will be available in a few years, when all the four global constellations (GPS, GLONASS, Galileo, and Beidou) will be fully deployed. This high number of visible satellites has improved the performance of precise point positioning (PPP) techniques both in terms of accuracy and of session length, especially easing the modeling of ionospheric biases. However, in the presence of severe environmental and atmospheric conditions, the performance of PPP considerably deteriorates. It is the case of high-latitude scenarios, where the satellites coverage is limited, the satellites geometry is poor and ionospheric scintillation are frequent. This paper analyzes the quality of PPP solutions in terms of accuracy and convergence time, for a GNSS station in Antarctica. Single and multi-constellation results are compared, proving the benefits of the availability of a higher number of satellites as well as the improved robustness to the presence of moderate and strong phase scintillations. The use of PPP multi-constellation at high latitudes is indeed essential to guarantee high accuracy, and to obtain a low convergence time, of the order of tens of minutes

A mass-market Galileo receiver: Its algorithms and performance

The two main GNSS receiver market segments, professional high-precision receivers and mass market/consumer receivers, have very different structure, objectives, features, architecture, and cost. The code-delay estimation is performed in the software receiver by a parallel correlation unit, giving as output a multi-correlation with certain chip spacing. This approach presents some advantages, mostly the fact that the number of correlation values that can be provided is thousands of times greater, compared to a standard receiver channel. Use of multiple correlators increases multipath-rejection capabilities, essential features in mass-market receivers, especially for positioning in urban scenarios. The TTFF was estimated with about 50 tests, in hot, warm, and cold start, first using both GPS and Galileo satellites, and then using only one constellation. In the second case only the 2D fix is considered, since, according to the scenario described, at maximum three satellites are in view

Analysis of the ionospheric scintillations during 20-21 January 2016 from SANAE by means of the DemoGRAPE scintillation receivers

This paper presents ionospheric scintillation data recorded at SANAE in Antarctica during a moderate geomagnetic storm on 20-21 January 2016 which gives evidence of the advantages of the new generation of instrumentation for monitoring ionospheric scintillation. The data was collected as part of the DemoGRAPE project aimed at the demonstration of cutting edge technology for the empirical assessment of the ionospheric delay and ionospheric scintillations in the polar regions which affect the accuracy of satellite navigation

Formation of ionospheric irregularities over Southeast Asia during the 2015 St. Patrickˈs Day storm

We investigate the geospace response to the 2015 St. Patrickˈs Day storm leveraging on instruments spread over Southeast Asia (SEA), covering a wide longitudinal sector of the low-latitude ionosphere. A regional characterization of the storm is provided, identifying the peculiarities of ionospheric irregularity formation. The novelties of this work are the characterization in a broad longitudinal range and the methodology relying on the integration of data acquired by Global Navigation Satellite System (GNSS) receivers, magnetometers, ionosondes, and Swarm satellites. This work is a legacy of the project EquatoRial Ionosphere Characterization in Asia (ERICA). ERICA aimed to capture the features of both crests of the equatorial ionospheric anomaly (EIA) and trough (EIT) by means of a dedicated measurement campaign. The campaign lasted from March to October 2015 and was able to observe the ionospheric variability causing effects on radio systems, GNSS in particular. The multiinstrumental and multiparametric observations of the region enabled an in-depth investigation of the response to the largest geomagnetic storm of the current solar cycle in a region scarcely reported in literature. Our work discusses the comparison between northern and southern crests of the EIA in the SEA region. The observations recorded positive and negative ionospheric storms, spread F conditions, scintillation enhancement and inhibition, and total electron content variability. The ancillary information on the local magnetic field highlights the variety of ionospheric perturbations during the different storm phases. The combined use of ionospheric bottomside, topside, and integrated information points out how the storm affects the F layer altitude and the consequent enhancement/suppression of scintillations.Published12211–122331A. Geomagnetismo e Paleomagnetismo2A. Fisica dell'alta atmosfera1IT. Reti di monitoraggio e Osservazioni5IT. Osservazioni satellitariJCR Journalope

Immunoglobulin G1 Fc glycosylation as an early hallmark of severe COVID-19.

Background: Immunoglobulin G1 (IgG1) effector functions are impacted by the structure of fragment crystallizable (Fc) tail-linked N-glycans. Low fucosylation levels on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) protein-specific IgG1 has been described as a hallmark of severe coronavirus disease 2019 (COVID-19) and may lead to activation of macrophages via immune complexes thereby promoting inflammatory responses, altogether suggesting involvement of IgG1 Fc glycosylation modulated immune mechanisms in COVID-19. Methods: In this prospective, observational single center cohort study, IgG1 Fc glycosylation was analyzed by liquid chromatography-mass spectrometry following affinity capturing from serial plasma samples of 159 SARS-CoV-2 infected hospitalized patients. Findings: At baseline close to disease onset, anti-S IgG1 glycosylation was highly skewed when compared to total plasma IgG1. A rapid, general reduction in glycosylation skewing was observed during the disease course. Low anti-S IgG1 galactosylation and sialylation as well as high bisection were early hallmarks of disease severity, whilst high galactosylation and sialylation and low bisection were found in patients with low disease severity. In line with these observations, anti-S IgG1 glycosylation correlated with various inflammatory markers. Interpretation: Association of low galactosylation, sialylation as well as high bisection with disease severity and inflammatory markers suggests that further studies are needed to understand how anti-S IgG1 glycosylation may contribute to disease mechanism and to evaluate its biomarker potential. Funding: This project received funding from the European Commission's Horizon2020 research and innovation program for H2020-MSCA-ITN IMforFUTURE, under grant agreement number 721815, and supported by Crowdfunding Wake Up To Corona, organized by the Leiden University Fund

Afucosylated IgG characterizes enveloped viral responses and correlates with COVID-19 severity

Immunoglobulin G (IgG) antibodies are crucial for protection against invading pathogens. A highly conserved N-linked glycan within the IgG-Fc tail, which is essential for IgG function, shows variable composition in humans. Afucosylated IgG variants are already used in anticancer therapeutic antibodies for their increased activity through Fc receptors (Fc gamma RIIIa). Here, we report that afucosylated IgG (approximately 6% of total IgG in humans) are specifically formed against enveloped viruses but generally not against other antigens. This mediates stronger Fc gamma RIIIa responses but also amplifies brewing cytokine storms and immune-mediated pathologies. Critically ill COVID-19 patients, but not those with mild symptoms, had high concentrations of afucosylated IgG antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), amplifying proinflammatory cytokine release and acute phase responses. Thus, antibody glycosylation plays a critical role in immune responses to enveloped viruses, including COVID-19.Proteomic

High titers and low fucosylation of early human anti-SARS-CoV-2 IgG promote inflammation by alveolar macrophages

Patients diagnosed with coronavirus disease 2019 (COVID-19) become critically ill primarily around the time of activation of the adaptive immune response. Here, we provide evidence that antibodies play a role in the worsening of disease at the time of seroconversion. We show that early-phase severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) spike protein-specific immunoglobulin G (IgG) in serum of critically ill COVID-19 patients induces excessive inflammatory responses by human alveolar macrophages. We identified that this excessive inflammatory response is dependent on two antibody features that are specific for patients with severe COVID-19. First, inflammation is driven by high titers of anti-spike IgG, a hallmark of severe disease. Second, we found that anti-spike IgG from patients with severe COVID-19 is intrinsically more proinflammatory because of different glycosylation, particularly low fucosylation, of the antibody Fc tail. Low fucosylation of anti-spike IgG was normalized in a few weeks after initial infection with SARS-CoV-2, indicating that the increased antibody-dependent inflammation mainly occurs at the time of seroconversion. We identified Fc gamma receptor (Fc gamma R) Ila and FeyRIII as the two primary IgG receptors that are responsible for the induction of key COVID-19-associated cytokines such as interleukin-6 and tumor necrosis factor. In addition, we show that anti-spike IgG-activated human macrophages can subsequently break pulmonary endothelial barrier integrity and induce microvascular thrombosis in vitro. Last, we demonstrate that the inflammatory response induced by anti-spike IgG can be specifically counteracted by fostamatinib, an FDA- and EMA-approved therapeutic small-molecule inhibitor of Syk kinase.Proteomic

Femme wemenou

Réunion: Séminaire interafricain sur l'éducation sexuelle en Afrique tropicale, 16-25 avril 1973, Bamako, MLDans IDL-26

Exploiting standardized metadata for GNSS SDR remote processing: A case study

The proliferation of ad-hoc, highly customized, GNSS Software-defined radio (SDR) receivers and raw data collection systems is opening new opportunities for research focused on the analysis of new approaches in GNSS data processing. Especially when looking at the post-processing of GNSS signals for monitoring purposes, the availability of big-sized raw digital samples allows for the application of different algorithms and processing strategies on the same data-set, thus enabling valuable comparisons and proper tuning of the algorithms themselves. A side effect is that the huge quantity of GNSS data collections, grabbed in disparate scenarios and environmental conditions and distributed all around the world, is making hard to share this data between different research labs, thus limiting the possibility of conducting extensive analysis of relevant ionospheric phenomena affecting the quality to the GNSS signal. In this paper, the authors propose a novel methodology to deal with the processing and the management of this huge amount of data, and guarantee interoperability of different data collection and data processing systems leveraging on the adoption of a new emerging and open standard for GNSS metadata which is now under standardization by the ION GNSS SDR Metadata Standardization Working Group

A machine learning approach to GNSS scintillation detection: automatic soft inspection of the events

Classical approaches for the automatic detection of ionospheric scintillation events in Global Navigation Satellite System (GNSS) receivers are based on the observation of indices (e.g. S4) that are obtained by processing parameters assessed at the signal processing stages of the receiver. Such values are the result of algorithms that imply specific processing choices (such as detrending, averaging and threshold operations) which influence the final performance of the detection. To reach good levels of accuracy and generalization for the identification and classification of the physical phenomenon, these approaches may require an additional human effort to refine the detection results by means of a manual inspection of the events, which is expensive and time consuming. This paper proposes a new methodology for the detection of ionospheric scintillation events based on Machine Learning techniques applied to GNSS data. This method, based on Decision Trees algorithms, aims at overcoming the limitation of the classical approaches by identifying scintillation events “as if” done by a human operator through visual inspection. This approach is automatic, unbound from traditional scintillation indices and features improved detection, false alarm, and missed detection rates when compared to standard methods