Overview of ESA’s Earth Observation upcoming small satellites missions

The “New Space” paradigm, has enabled the creation of many new opportunities in the space sector like the development of a large number of missions based on small and nano-satellites. The European Space Agency (ESA) is supporting these new development approaches and technology advancements, including use of Commercial-Off-The-Shelf (COTS) components to enable missions based on small and nano satellites. ESA’s Earth Observation Programmes Directorate (ESA-EOP) is already involved not only in the implementation of technologies exploiting the capabilities offered by small and nano-satellites as a complement to the EOP scientific and application-driven flagship satellites, but also in the quick validation of new approaches like A.I, super resolution or more in general in orbit data processing. ESA-EOP developments in the area of small and nano satellites are spread in three different programmatic lines, each with its own objectives: Scout and F-sat Missions and the InCubed Programme. This paper presents the overall ESA-EOP small missions strategy providing a brief insight on the genesis of each programmatic line and their selection processes including an update of the status of the first initiatives and missions under development or study

The ESA ΦSat-2 Mission: An A.I Enhanced Multispectral CubeSat for Earth Observation

As part of an initiative to promote the development and implementation of innovative technologies on-board Earth Observation (EO) missions, the European Space Agency (ESA) kicked off the first Φsat related activities in 2018 with the aim of enhancing the already ongoing FSSCAT project with Artificial Intelligence (AI). The selected Φsat-2 concept will provide a combination of on-board processing capabilities (including AI) and a medium to high resolution multispectral instrument from Visible to Near Infra-Red (VIS/NIR) able to acquire 8 bands (7 + Panchromatic) provided by SIMERA SENSE Europe (BE). These resources will be made available to a series of dedicated applications that will run on-board the spacecraft. The mission prime is Open Cosmos (UK), supported by CGI (IT) to coordinate the payload operations for at least 12 months after LEOP and commissioning phase. During the nominal phase the various AI applications will be fine-tuned after the on-ground training and then routinely run. A series of AI applications that could be potentially embarked are under development. The first one is called SAT2MAP and is expected to autonomously detect streets from acquired images. It is developed by CGI (IT). The second AI application is an enhancement of the Φsat-1 cloud detection experiment, able to prioritize data to be downloaded to ground, based on standard cloud coverage and new concentration measurements. It is developed by KP Labs (PL) and it is based on a U-Ne. This application will mainly act as an on-board service for the other applications, relieving them of the task of assessing the presence of the clouds. The Autonomous Vessel Awareness application aims to detect and classify various vessel types in the maritime domain. This would enable a reduced amount of data to be downloaded (only image patches including the vessel) improving the response time for final users (e.g maritime authorities). In this case the AI technique used is a combination of Single Image Super resolution (SRCNN) and Yolo-based Convoluted Neural Network (CNN). The Deep Compression application generically reduces the amount of data to be downloaded to ground with limited information loss. The image is compressed on-board and then reconstructed on ground by means of a decoder. It can achieve a compression rate of about 7 per band. It is based on the use of a Convolutional Auto Encoder (CAE). Two more AI applications will be selected by ESA through a dedicated challenge open to institutions, Agencies and industries that will be run in the first half of 2023. The Φsat-2 mission successfully passed the CDR phase at the end of 2022 aiming for a launch in 2024

Protective effect of Tuscan black cabbage sprout extract against serum lipid increase and perturbations of liver antioxidant and detoxifying enzymes in rats fed a high-fat diet

A diet rich in fat is considered a primary risk factor for CVD, cancer and failures in metabolism and endocrine functions. Hyperlipidaemia generates oxidative stress and weakens antioxidant defences as well as metabolic detoxification systems. Brassicaceae are vegetables rich in glucosinolates and isothiocyanates, affecting enzymatic antioxidant as well as phase II enzymes and conceivably counteracting high-fat diet (HFD)-associated pathologies. The protective role of Tuscan black cabbage (a variety of kale) sprout extract (TBCSE) intake against HFD alterations was here studied. The effects on rat hepatic antioxidant as well as detoxifying enzymes, and serum lipid- and body weightlowering properties of TBCSE, were investigated. Feeding the animals with a HFD for 21 d increased body as well as liver weights, and induced hyperlipidaemia, as confirmed by a higher serum lipid profile v. control diet. Daily intragastric administration of TBCSE to HFD-fed rats lowered serum total cholesterol, TAG and NEFA. Body and liver weight gains were also reduced. Antioxidant (catalase, NAD(P)H:quinone reductase, oxidised glutathione reductase and superoxide dismutase) and phase II (glutathione S-transferase and uridine diphosphate glucuronosyl transferase) enzymes were down-regulated by the HFD, while the extract restored normal levels in most groups. Generation of toxic intermediates, and membrane fatty acid composition changes by the HFD, might account for the altered hepatic antioxidant and detoxifying enzyme functions. The recovering effects of TBCSE could be attributed to high flavonoid, phenolic and organosulphur compound content, which possess free-radical-scavenging properties, enhance the antioxidant status and stimulate lipid catabolism. TBCSE intake emerges to be an effective alimentary strategy to counteract the perturbations associated with a diet rich in fat