Temporal variability of GNSS-Reflectometry ocean wind speed retrieval performance during the UK TechDemoSat-1 mission

This paper presents the temporal evolution of Global Navigation Satellite System Reflectometry (GNSS-R) ocean wind speed retrieval performance during three years of the UK TechDemoSat-1 (TDS-1) mission. TDS-1 was launched in July 2014 and provides globally distributed spaceborne GNSS-R data over a lifespan of over three years, including several months of 24/7 operations. TDS-1 wind speeds are computed using the NOC Calibrated Bistatic Radar Equation algorithm version 0.5 (C-BRE v0.5), and are evaluated against ERA5 high resolution re-analysis data over the period 2015–2018. Analyses reveal significant temporal variability in TDS-1 monthly wind speed retrieval performance over the three years, with the best performance (~2 m∙s−1) achieved in the early part of the mission (May 2015). The temporal variability of retrieval performance is found to be driven by several non-geophysical factors, including TDS-1 platform attitude uncertainty and spatial/temporal changes in GPS transmit power from certain satellites. Evidence is presented of the impact of the GPS Block IIF Flex mode on retrieved GNSS-R wind speed after January 2017, which results in significantly underestimated ocean winds over a large region covering the North Atlantic, northern Indian Ocean, the Mediterranean, the Black Sea, and the Sea of Okhotsk. These GPS transmit power changes are shown to induce large negative wind speed biases of up to 3 m∙s−1. Analyses are also presented of the sensitivity of TDS-1 wind speed retrieval to platform attitude uncertainty using statistical simulations. It is suggested that a 4° increase in attitude uncertainty can produce up to 1 m∙s−1 increase in RMSE, and that TDS-1 attitude data do not fully reflect actual platform attitude. We conclude that the lack of knowledge about the GNSS-R nadir antenna gain map and TDS-1 platform-attitude limits the ability to determine the achievable wind speed retrieval performance with GNSS-R on TDS-1. The paper provides recommendations that accurate attitude knowledge and a good characterisation of GNSS-R nadir antenna patterns should be prioritised for future GNSS-R missions

Automated detection of coastal upwelling in the Western Indian Ocean: Towards an operational “Upwelling Watch” system

Coastal upwelling is an oceanographic process that brings cold, nutrient-rich waters to the ocean surface from depth. These nutrient-rich waters help drive primary productivity which forms the foundation of ecological systems and the fisheries dependent on them. Although coastal upwelling systems of the Western Indian Ocean (WIO) are seasonal (i.e., only present for part of the year) with large variability driving strong fluctuations in fish catch, they sustain food security and livelihoods for millions of people via small-scale (subsistence and artisanal) fisheries. Due to the socio-economic importance of these systems, an "Upwelling Watch" analysis is proposed, for producing updates/alerts on upwelling presence and extremes. We propose a methodology for the detection of coastal upwelling using remotely-sensed daily chlorophyll-a and Sea Surface Temperature (SST) data. An unsupervised machine learning approach, K-means clustering, is used to detect upwelling areas off the Somali coast (WIO), where the Somali upwelling – regarded as the largest in the WIO and the fifth most important upwelling system globally – takes place. This automatic detection approach successfully delineates the upwelling core and surrounds, as well as non-upwelling ocean regions. The technique is shown to be robust with accurate classification of out-of-sample data (i.e., data not used for training the detection model). Once upwelling regions have been identified, the classification of extreme upwelling events was performed using confidence intervals derived from the full remote sensing record. This work has shown promise within the Somali upwelling system with aims to expand it to the rest of the WIO upwellings. This upwelling detection and classification method can aid fisheries management and also provide broader scientific insights into the functioning of these important oceanographic features

An assessment of CyGNSS v3.0 level 1 observables over the ocean

Global Navigation Satellite System Reflectometry (GNSS-R) is a rapidly developing Earth observation technology that makes use of signals of opportunity from Global Navigation Satellite Systems that have been reflected off the Earth’s surface. The Cyclone Global Navigation Satellite System (CyGNSS) is a constellation of eight small satellites launched by NASA in 2016, carrying dedicated GNSS-R payloads to measure ocean surface wind speed at low latitudes (±35° North/South). The ESA ECOLOGY project evaluated CyGNSS v3.0 products, which were recently released following various calibration updates. This paper examines the performance of the new calibration by evaluating CyGNSS v3.0 Level-1 Normalised Bistatic Radar Cross Section (NBRCS) and Leading Edge Slope (LES) data from individual CyGNSS units and different GPS transmitters under constant ocean wind conditions. Results indicate that L1 NBRCS from individual CyGNSS units are well inter-calibrated and remarkably stable over time, a significant improvement over previous versions of the products. However, prominent geographical biases reaching over 3 dB are found in NBRCS, linked to factors including the choice of GPS transmitter and the bistatic geometry. L1 LES shows similar anomalies as well as a secondary geographical pattern of biases. These findings provide a basis for further improvement of CyGNSS Level-2 wind products and have wider applicability to improving the calibration of GNSS-R sensors for the remote sensing of non-ocean Earth surfaces

Analysis of Technology Improvement Opportunities for a 1.5MW Wind Turbine using a Hybrid Stochastic Approach in Life Cycle Assessment

This paper presents an analysis of potential technological advancements for a 1.5 MW wind turbine using a hybrid stochastic method to improve uncertainty estimates of embodied energy and embodied carbon. The analysis is specifically aimed at these two quantities due to the fact that LCA based design decision making is of utmost importance at the concept design stage. In the presented case studies, better results for the baseline turbine were observed compared to turbines with the proposed technological advancements. Embodied carbon and embodied energy results for the baseline turbine show that there is about 85% probability that the turbine manufacturers may have lost the chance to reduce carbon emissions, and 50% probability that they may have lost the chance to reduce the primary energy consumed during its manufacture. The paper also highlights that the adopted methodology can be used to support design decision making and hence is more feasible for LCA studies

Teriparatide and stress fracture healing in young adults (RETURN – Research on Efficacy of Teriparatide Use in the Return of recruits to Normal duty): study protocol for a randomised controlled trial

Background: Stress fractures are a common and potentially debilitating overuse injury to bone and occur frequently among military recruits and athletes. Recovery from a lower body stress fracture typically requires several weeks of physical rehabilitation. Teriparatide, a recombinant form of the bioactive portion of parathyroid hormone (1–34 amino acids), is used to treat osteoporosis, prevent osteoporotic fractures, and enhance fracture healing due to its net anabolic effect on bone. The study aim is to investigate the effect of teriparatide on stress fracture healing in young, otherwise healthy adults undergoing military training. Methods: In a two-arm, parallel, prospective, randomised controlled, intention-to-treat trial, Army recruits (n = 136 men and women, 18–40 years) with a magnetic resonance imaging (MRI) diagnosed lower body stress fracture (pelvic girdle, sacrum, coccyx, or lower limb) will be randomised to receive either usual Army standard care, or teriparatide and usual Army standard care. Teriparatide will be self-administered by subcutaneous injections (20 μg/day) for 16 weeks, continuing to 24 weeks where a fracture remains unhealed at week 16. The primary outcome will be the improvement in radiological healing by two grades or more, or reduction to grade zero, 8 weeks after randomisation, assessed using Fredericson grading of MRI by radiologists blind to the randomisation. Secondary outcomes will be time to radiological healing, assessed by MRI at 8, 10, 12, 14, 16, 20 and 24 weeks, until healed; time to clinical healing, assessed using a clinical severity score of injury signs and symptoms; time to discharge from Army physical rehabilitation; pain, assessed by visual analogue scale; health-related quality of life, using the Short Form (36) Health Survey; and adverse events. Exploratory outcomes will include blood and urine biochemistry; bone density and morphology assessed using dual-energy X-ray absorptiometry, peripheral quantitative computed tomography (pQCT), and high-resolution pQCT; physical activity measured using accelerometers; and long-term future fracture rate. Discussion: This study will evaluate whether teriparatide, in addition to standard care, is more effective for stress fracture healing than standard care alone in Army recruits who have sustained a lower body stress fracture. Trial registration: ClinicalTrials.govNCT04196855. Registered on 12 December 2019

Wize Mirror - a smart, multisensory cardio-metabolic risk monitoring system

In the recent years personal health monitoring systems have been gaining popularity, both as a result of the pull from the general population, keen to improve well-being and early detection of possibly serious health conditions and the push from the industry eager to translate the current significant progress in computer vision and machine learning into commercial products. One of such systems is the Wize Mirror, built as a result of the FP7 funded SEMEOTICONS (SEMEiotic Oriented Technology for Individuals CardiOmetabolic risk self-assessmeNt and Self-monitoring) project. The project aims to translate the semeiotic code of the human face into computational descriptors and measures, automatically extracted from videos, multispectral images, and 3D scans of the face. The multisensory platform, being developed as the result of that project, in the form of a smart mirror, looks for signs related to cardio-metabolic risks. The goal is to enable users to self-monitor their well-being status over time and improve their life-style via tailored user guidance. This paper is focused on the description of the part of that system, utilising computer vision and machine learning techniques to perform 3D morphological analysis of the face and recognition of psycho-somatic status both linked with cardio-metabolic risks. The paper describes the concepts, methods and the developed implementations as well as reports on the results obtained on both real and synthetic datasets

A comparison of phase imaging and quantitative susceptibility mapping in the imaging of multiple sclerosis lesions at ultrahigh field

Objective The aim of this study was to compare the use of high-resolution phase and QSM images acquired at ultra-high field in the investigation of multiple sclerosis (MS) lesions with peripheral rings, and to discuss their usefulness for drawing inferences about underlying tissue composition. Materials and methods Thirty-nine Subjects were scanned at 7 T, using 3D T2*-weighted and T1-weighted sequences. Phase images were then unwrapped and filtered, and quantitative susceptibility maps were generated using a thresholded k-space division method. Lesions were compared visually and using a 1D profiling algorithm. Results Lesions displaying peripheral rings in the phase images were identified in 10 of the 39 subjects. Dipolar projections were apparent in the phase images outside of the extent of several of these lesions; however, QSM images showed peripheral rings without such projections. These projections appeared ring-like in a small number of phase images where no ring was observed in QSM. 1D profiles of six well-isolated example lesions showed that QSM contrast corresponds more closely to the magnitude images than phase contrast. Conclusions Phase images contain dipolar projections, which confounds their use in the investigation of tissue composition in MS lesions. Quantitative susceptibility maps correct these projections, providing insight into the composition of MS lesions showing peripheral rings

Upper limits on the strength of periodic gravitational waves from PSR J1939+2134

The first science run of the LIGO and GEO gravitational wave detectors presented the opportunity to test methods of searching for gravitational waves from known pulsars. Here we present new direct upper limits on the strength of waves from the pulsar PSR J1939+2134 using two independent analysis methods, one in the frequency domain using frequentist statistics and one in the time domain using Bayesian inference. Both methods show that the strain amplitude at Earth from this pulsar is less than a few times $10^{-22}$.Comment: 7 pages, 1 figure, to appear in the Proceedings of the 5th Edoardo Amaldi Conference on Gravitational Waves, Tirrenia, Pisa, Italy, 6-11 July 200

Improving the sensitivity to gravitational-wave sources by modifying the input-output optics of advanced interferometers

We study frequency dependent (FD) input-output schemes for signal-recycling interferometers, the baseline design of Advanced LIGO and the current configuration of GEO 600. Complementary to a recent proposal by Harms et al. to use FD input squeezing and ordinary homodyne detection, we explore a scheme which uses ordinary squeezed vacuum, but FD readout. Both schemes, which are sub-optimal among all possible input-output schemes, provide a global noise suppression by the power squeeze factor, while being realizable by using detuned Fabry-Perot cavities as input/output filters. At high frequencies, the two schemes are shown to be equivalent, while at low frequencies our scheme gives better performance than that of Harms et al., and is nearly fully optimal. We then study the sensitivity improvement achievable by these schemes in Advanced LIGO era (with 30-m filter cavities and current estimates of filter-mirror losses and thermal noise), for neutron star binary inspirals, and for narrowband GW sources such as low-mass X-ray binaries and known radio pulsars. Optical losses are shown to be a major obstacle for the actual implementation of these techniques in Advanced LIGO. On time scales of third-generation interferometers, like EURO/LIGO-III (~2012), with kilometer-scale filter cavities, a signal-recycling interferometer with the FD readout scheme explored in this paper can have performances comparable to existing proposals. [abridged]Comment: Figs. 9 and 12 corrected; Appendix added for narrowband data analysi