Flood Detection On Low Cost Orbital Hardware

Satellite imaging is a critical technology for monitoring and responding to natural disasters such as flooding. Despite the capabilities of modern satellites, there is still much to be desired from the perspective of first response organisations like UNICEF. Two main challenges are rapid access to data, and the ability to automatically identify flooded regions in images. We describe a prototypical flood segmentation system, identifying cloud, water and land, that could be deployed on a constellation of small satellites, performing processing on board to reduce downlink bandwidth by 2 orders of magnitude. We target PhiSat-1, part of the FSSCAT mission, which is planned to be launched by the European Space Agency (ESA) near the start of 2020 as a proof of concept for this new technology

A new Merluccius polli reference genome to investigate the effects of global change in West African waters

Genome resources have become crucial to assess genome-wide level of variation as well as to detect adaptive variation. This is particularly important for studying diversity in marine species inhabiting regions highly affected by accelerated climate warming and pollution, also known as global change. A greater awareness of the impacts of global change is urgently needed to ensure sustainable marine fisheries. Despite recent efforts, there are still many gaps in fish reference genomes, both geographical and taxonomic. Here, we sequence, assemble and annotate the genome of Merluccius polli. The total length of this new assembly (~582 Kb, N50 = 168Kb) is approximately 40% longer and much less fragmented than a previous version. Even though it might not be intrinsic of this species, low level of heterozygosity (1.16 SNPs/Kb) and low proportion of repeat content (9.21%) was found in this genome. This hake species has a wide latitudinal distribution; therefore, it is exposed to a changing temperature gradient and to a variety of contaminants in part of its distribution along West African coast. Special emphasis was laid on the identification and characterization of candidate genes known to respond to different stressors (depth, temperature, hypoxia, and heavy metals) happening along its geographical distribution. A total of 68 of the selected candidate genes known to be associated with responses to these stressors were found in the current assembly of the genome, and their predicted sequence can be considered as full-length. Therefore, it is expected that this genome would serve as a tool to further investigations of global change in one of the most stressed marine regions in the planet

Towards global flood mapping onboard low cost satellites with machine learning

Spaceborne Earth observation is a key technology for flood response, offering valuable information to decision makers on the ground. Very large constellations of small, nano satellites— ’CubeSats’ are a promising solution to reduce revisit time in disaster areas from days to hours. However, data transmission to ground receivers is limited by constraints on power and bandwidth of CubeSats. Onboard processing offers a solution to decrease the amount of data to transmit by reducing large sensor images to smaller data products. The ESA’s recent PhiSat-1 mission aims to facilitate the demonstration of this concept, providing the hardware capability to perform onboard processing by including a power-constrained machine learning accelerator and the software to run custom applications. This work demonstrates a flood segmentation algorithm that produces flood masks to be transmitted instead of the raw images, while running efficiently on the accelerator aboard the PhiSat-1. Our models are trained on WorldFloods: a newly compiled dataset of 119 globally verified flooding events from disaster response organizations, which we make available in a common format. We test the system on independent locations, demonstrating that it produces fast and accurate segmentation masks on the hardware accelerator, acting as a proof of concept for this approach

Cloud Mask Intercomparison eXercise (CMIX): An evaluation of cloud masking algorithms for Landsat 8 and Sentinel-2

Cloud cover is a major limiting factor in exploiting time-series data acquired by optical spaceborne remote sensing sensors. Multiple methods have been developed to address the problem of cloud detection in satellite imagery and a number of cloud masking algorithms have been developed for optical sensors but very few studies have carried out quantitative intercomparison of state-of-the-art methods in this domain. This paper summarizes results of the first Cloud Masking Intercomparison eXercise (CMIX) conducted within the Committee Earth Observation Satellites (CEOS) Working Group on Calibration & Validation (WGCV). CEOS is the forum for space agency coordination and cooperation on Earth observations, with activities organized under working groups. CMIX, as one such activity, is an international collaborative effort aimed at intercomparing cloud detection algorithms for moderate-spatial resolution (10–30 m) spaceborne optical sensors. The focus of CMIX is on open and free imagery acquired by the Landsat 8 (NASA/USGS) and Sentinel-2 (ESA) missions. Ten algorithms developed by nine teams from fourteen different organizations representing universities, research centers and industry, as well as space agencies (CNES, ESA, DLR, and NASA), are evaluated within the CMIX. Those algorithms vary in their approach and concepts utilized which were based on various spectral properties, spatial and temporal features, as well as machine learning methods. Algorithm outputs are evaluated against existing reference cloud mask datasets. Those datasets vary in sampling methods, geographical distribution, sample unit (points, polygons, full image labels), and generation approaches (experts, machine learning, sky images). Overall, the performance of algorithms varied depending on the reference dataset, which can be attributed to differences in how the reference datasets were produced. The algorithms were in good agreement for thick cloud detection, which were opaque and had lower uncertainties in their identification, in contrast to thin/semi-transparent clouds detection. Not only did CMIX allow identification of strengths and weaknesses of existing algorithms and potential areas of improvements, but also the problems associated with the existing reference datasets. The paper concludes with recommendations on generating new reference datasets, metrics, and an analysis framework to be further exploited and additional input datasets to be considered by future CMIX activities

Spread of a SARS-CoV-2 variant through Europe in the summer of 2020.

Following its emergence in late 2019, the spread of SARS-CoV-21,2 has been tracked by phylogenetic analysis of viral genome sequences in unprecedented detail3–5. Although the virus spread globally in early 2020 before borders closed, intercontinental travel has since been greatly reduced. However, travel within Europe resumed in the summer of 2020. Here we report on a SARS-CoV-2 variant, 20E (EU1), that was identified in Spain in early summer 2020 and subsequently spread across Europe. We find no evidence that this variant has increased transmissibility, but instead demonstrate how rising incidence in Spain, resumption of travel, and lack of effective screening and containment may explain the variant’s success. Despite travel restrictions, we estimate that 20E (EU1) was introduced hundreds of times to European countries by summertime travellers, which is likely to have undermined local efforts to minimize infection with SARS-CoV-2. Our results illustrate how a variant can rapidly become dominant even in the absence of a substantial transmission advantage in favourable epidemiological settings. Genomic surveillance is critical for understanding how travel can affect transmission of SARS-CoV-2, and thus for informing future containment strategies as travel resumes. © 2021, The Author(s), under exclusive licence to Springer Nature Limited

Sex- and age-related differences in the management and outcomes of chronic heart failure: an analysis of patients from the ESC HFA EORP Heart Failure Long-Term Registry

Aims: This study aimed to assess age- and sex-related differences in management and 1-year risk for all-cause mortality and hospitalization in chronic heart failure (HF) patients. Methods and results: Of 16 354 patients included in the European Society of Cardiology Heart Failure Long-Term Registry, 9428 chronic HF patients were analysed [median age: 66 years; 28.5% women; mean left ventricular ejection fraction (LVEF) 37%]. Rates of use of guideline-directed medical therapy (GDMT) were high (angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, beta-blockers and mineralocorticoid receptor antagonists: 85.7%, 88.7% and 58.8%, respectively). Crude GDMT utilization rates were lower in women than in men (all differences: P\ua0 64 0.001), and GDMT use became lower with ageing in both sexes, at baseline and at 1-year follow-up. Sex was not an independent predictor of GDMT prescription; however, age >75 years was a significant predictor of GDMT underutilization. Rates of all-cause mortality were lower in women than in men (7.1% vs. 8.7%; P\ua0=\ua00.015), as were rates of all-cause hospitalization (21.9% vs. 27.3%; P\ua075 years. Conclusions: There was a decline in GDMT use with advanced age in both sexes. Sex was not an independent predictor of GDMT or adverse outcomes. However, age >75 years independently predicted lower GDMT use and higher all-cause mortality in patients with LVEF 6445%

Tears evoke the intention to offer social support: A systematic investigation of the interpersonal effects of emotional crying across 41 countries

Tearful crying is a ubiquitous and likely uniquely human phenomenon. Scholars have argued that emotional tears serve an attachment function: Tears are thought to act as a social glue by evoking social support intentions. Initial experimental studies supported this proposition across several methodologies, but these were conducted almost exclusively on participants from North America and Europe, resulting in limited generalizability. This project examined the tears-social support intentions effect and possible mediating and moderating variables in a fully pre-registered study across 7007 participants (24,886 ratings) and 41 countries spanning all populated continents. Participants were presented with four pictures out of 100 possible targets with or without digitally-added tears. We confirmed the main prediction that seeing a tearful individual elicits the intention to support, d = 0.49 [0.43, 0.55]. Our data suggest that this effect could be mediated by perceiving the crying target as warmer and more helpless, feeling more connected, as well as feeling more empathic concern for the crier, but not by an increase in personal distress of the observer. The effect was moderated by the situational valence, identifying the target as part of one's group, and trait empathic concern. A neutral situation, high trait empathic concern, and low identification increased the effect. We observed high heterogeneity across countries that was, via split-half validation, best explained by country-level GDP per capita and subjective well-being with stronger effects for higher-scoring countries. These findings suggest that tears can function as social glue, providing one possible explanation why emotional crying persists into adulthood.</p

A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic.

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world