4 research outputs found

    In-Orbit Demonstration of the iSIM-170 Optical Payload Onboard the ISS

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    iSIM-170 is anoptical payload for Earth Observations with sub-meterresolution in VNIR bands. The payload will be in-orbit-demonstrated at the ISS after a successful launch with the HTV-9 mission by JAXA and afte its installation on the Kibo module occurred on June 11th, 2020. Prior to its flight, iSIM-170 underwent an accelerated development programme culminating in the successful completion of all verifications and reviews. iSIM-170 has been developed by the Spanish company SATLANTIS, in collaboration with the University of Florida, to become the gold standard of imaging payloads for microsatellites. It consists of four integrated components: a binocular diffraction-limited set of telescopes; a high precision, robust and light alloy structure; a set of CMOS array detector units; and a high-performance-reconfigurable on-board image processor. The goal of this in-orbit-demonstration mission consists of commissioning the payload and characterizing the overall instrument’s capabilities, especially its ability to provide a factor ~2-3 improvement on spatial resolution below its diffraction limit design, using our super-resolution algorithms. The payload will be operated for three months to obtain TRL-8 qualification performing uplink and downlink activities managed by JAXA, as intermediary between iSIM-170and SATLANTIS. Preliminary results demonstrating iSIM image quality will be shown at this conference

    Deep execution monitor for robot assistive tasks

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    We consider a novel approach to high-level robot task execution for a robot assistive task. In this work we explore the problem of learning to predict the next subtask by introducing a deep model for both sequencing goals and for visually evaluating the state of a task. We show that deep learning for monitoring robot tasks execution very well supports the interconnection between task-level planning and robot operations. These solutions can also cope with the natural non-determinism of the execution monitor.We show that a deep execution monitor leverages robot performance. We measure the improvement taking into account some robot helping tasks performed at a warehouse

    Treatment of pregnancies complicated by intrauterine growth restriction with nitric oxide donors increases placental expression of Epidermal Growth Factor-Like Domain 7 and improves fetal growth: A pilot study

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    Intrauterine growth restriction (IUGR) is a pathological condition of pregnancy with high perinatal mortality and morbidity, characterized by inadequate fetal growth associated to altered maternal hemodynamics with impaired uteroplacental blood flow and placental insufficiency. To date, iatrogenic premature delivery remains the elective therapeutic strategy. However, in recent years the possibility of a therapeutic approach with vasodilators and myorelaxants, such as nitric oxide (NO) donors, has gained interest. NO controls many endothelial cell functions, including angiogenesis and vascular permeability, by regulating the expression of angiogenic factors, such as Vascular Endothelial Growth Factor. In the present study, we investigated if treatment of pregnancies complicated by IUGR with NO donors affects the expression of Epidermal Growth Factor-Like Domain 7 (EGFL7), a secreted endothelial factor, previously demonstrated to be expressed by both endothelial and trophoblast cells and involved in proper placental development. NO donor treatment induced placental levels of EGFL7 and, in association with oral fluids, significantly improved fetal growth. Ex vivo experiments confirmed that NO donors increased expression and secretion of EGFL7 by villous explants. To specifically investigate the potential response of trophoblast cells to NO, we treated HTR8-sVneo cells with NO donors and observed induction of EGFL7 expression. Altogether, our findings indicate that NO induces endothelial and trophoblast expression of EGFL7 in the placenta and improves fetal growth, suggesting a correlation between placental levels of EGFL7 and pregnancy outcome
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