EO-Alert: A Satellite Architecture for Detection and Monitoring of Extreme Events in Real Time

This paper presents the architecture and results achieved by the EO-ALERT H2020 project. EO-ALERT proposes the definition and development of the next-generation Earth Observation (EO) data processing chain, based on a novel flight segment architecture that moves optimised key EO data processing elements from the ground segment to onboard the satellite, with the aim of delivering the EO products to the end user with very low latency (in almost real-time). This paper presents the EO-ALERT architecture, its performance and hardware. Performances are presented for two reference user scenarios; ship detection and extreme weather nowcasting/monitoring. The hardware testing results show that, when implemented using Commercial Off-The-Shelf (COTS) components and available communication links, the proposed architecture can deliver EO products and alerts to the end user with a latency lower than one-point-five minutes, for both SAR and Optical Very High Resolution (VHR) missions, demonstrating the viability of the EO-ALERT concept and architecture

Population Pharmacokinetics of Telapristone (CDB-4124) and its Active Monodemethylated Metabolite CDB-4453, with a Mixture Model for Total Clearance

Telapristone is a selective progesterone antagonist that is being developed for the long-term treatment of symptoms associated with endometriosis and uterine fibroids. The population pharmacokinetics of telapristone (CDB-4124) and CDB-4453 was investigated using nonlinear mixed-effects modeling. Data from two clinical studies (n = 32) were included in the analysis. A two-compartment (parent) one compartment (metabolite) mixture model (with two populations for apparent clearance) with first-order absorption and elimination adequately described the pharmacokinetics of telapristone and CDB-4453. Telapristone was rapidly absorbed with an absorption rate constant (Ka) of 1.26 h−1. Moderate renal impairment resulted in a 74% decrease in Ka. The population estimates for oral clearance (CL/F) for the two populations were 11.6 and 3.34 L/h, respectively, with 25% of the subjects being allocated to the high-clearance group. Apparent volume of distribution for the central compartment (V2/F) was 37.4 L, apparent inter-compartmental clearance (Q/F) was 21.9 L/h, and apparent peripheral volume of distribution for the parent (V4/F) was 120 L. The ratio of the fraction of telapristone converted to CDB-4453 to the distribution volume of CDB-4453 (Fmetest) was 0.20/L. Apparent volume of distribution of the metabolite compartment (V3/F) was fixed to 1 L and apparent clearance of the metabolite (CLM/F) was 2.43 L/h. A two-compartment parent-metabolite model adequately described the pharmacokinetics of telapristone and CDB-4453. The clearance of telapristone was separated into two populations and could be the result of metabolism via polymorphic CYP3A5

EO-ALERT: A Novel Architecture for the Next Generation of Earth Observation Satellites Supporting Rapid Civil Alerts

The EO-ALERT project proposes the definition and development of the next-generation Earth Observation (EO) data processing chain, based on a novel flight segment architecture that moves opti-mised key EO data processing elements from the ground segment to on-board the satellite, with the aim of delivering EO products to the end user with very low latency. EO-ALERT achieves, globally, latencies below five minutes for EO products delivery, and below 1 minute in some scenarios. The proposed archi-tecture combines innovations in the on-board elements of the data chain and the communications, namely: on-board reconfigurable data handling, on-board image generation and processing for the generation of alerts (EO products) using Artificial Intelligence (AI), on-board AI-based data compression and encryption, high-speed on-board avionics, and reconfigurable high data rate communication links to ground, including a separate chain for alerts with minimum latency and global coverage. This paper pre-sents the proposed architecture, its performance and hardware, considering two different user scenarios: ship detection and extreme weather nowcasting. The results show that, when implemented using COTS components and available communication links, the proposed architecture can deliver alerts to ground with latency below five minutes, for both SAR and Optical missions, demonstrating the viability of the EO-ALERT concept

EO-ALERT: A Novel Architecture for the Next Generation of Earth Observation Satellites Supporting Rapid Civil Alerts

Satellite Earth Observation (EO) data is ubiquitously used in many applications, providing basic services to society, such as environment monitoring, emergency management and civilian security. Due to the increasing request of EO products by the market, the classical EO data chain generates a severe bottleneck problem, further exacerbated in constellations. A huge amount of EO raw data generated on-board the satellite must be transferred to ground, slowing down the EO product availability, increasing latency, and hampering the growth of applications in accordance with the increased user demand. This paper provides an overview of the results achieved by the EO-ALERT project (http://eo-alert-h2020.eu/), an H2020 European Union research activity led by DEIMOS Space. EO-ALERT proposes the definition and development of the next-generation EO data processing chain, based on a novel flight segment architecture that moves optimised key EO data processing elements from the ground segment to on-board the satellite, with the aim of delivering the EO products to the end user with very low latency (quasi-real-time). EO-ALERT achieves, globally, latencies below five minutes for EO products delivery, reaching latencies below 1 minute in some scenarios. The proposed architecture solves the above challenges through a combination of innovations in the on-board elements of the data chain and the communications. Namely, the architecture introduces innovative technological solutions, including on-board reconfigurable data handling, on-board image generation and processing for the generation of alerts (EO products) using Artificial Intelligence (AI), on-board data compression and encryption using AI, high-speed on-board avionics, and reconfigurable high data rate communication links to ground, including a separate chain for alerts with minimum latency and global coverage. The paper presents the proposed architecture, its performance and hardware, considering two different user scenarios; ship detection and extreme weather observation/nowcasting. The results show that, when implemented using COTS components and available communication links, the proposed architecture can deliver alerts to ground with latency lower than five minutes, for both SAR and Optical missions, demonstrating the viability of the EOALERT concept and architecture. The paper also discusses the implementation on an avionics test bench for testing the architecture with real EO data, with the aim of demonstrating that it can meet the requirements of the considered scenarios in terms of detection performance and provides technologies at a high TRL (4-5). When proven, this will open unprecedented opportunities for the exploitation of civil EO products, especially in latency sensitive scenarios, such as disaster management

A Novel Satellite Architecture for the Next Generation of Earth Observation Satellites Supporting Rapid Alerts

The EO-ALERT European Commission H2020 project proposes the definition, development, and verification and validation through ground hardware testing, of a next-generation Earth Observation (EO) data processing chain. The proposed data processing chain is based on a novel flight segment architecture that moves EO data processing elements traditionally executed in the ground segment to on-board the satellite, with the aim of delivering EO products to the end user with very low latency. EO-ALERT achieves, globally, latencies below five minutes for EO products delivery, and below one minute in realistic scenarios. The proposed EO-ALERT architecture is enabled by on-board processing, recent improvements in processing hardware using Commercial Off-The-Shelf (COTS) components, and persistent space-to-ground communications links. EO-ALERT combines innovations in the on-board elements of the data chain and the communications, namely: on-board reconfigurable data handling, on-board image generation and processing for the generation of alerts (EO products) using Machine Learning (ML) and Artificial Intelligence (AI), on-board AI-based data compression and encryption, high-speed on-board avionics, and reconfigurable high data rate communication links to ground, including a separate chain for alerts with minimum latency and global coverage. This paper presents the proposed architecture, its hardware realization for the ground testing in a representative environment and its performance. The architecture’s performance is evaluated considering two different user scenarios where very low latency (almost-real-time) EO product delivery is required: ship detection and extreme weather monitoring/nowcasting. The hardware testing results show that, when implemented using COTS components and available communication links, the proposed architecture can deliver alerts to the end user with a latency below five minutes, for both SAR and Optical missions, demonstrating the viability of the EO-ALERT architecture. In particular, in several test scenarios, for both the TerraSAR-X SAR and DEIMOS-2 Optical Very High Resolution (VHR) missions, hardware testing of the proposed architecture has shown it can deliver EO products and alerts to the end user globally, with latency lower than one-point-five minutes

Improving interinstitutional and intertechnology consistency of pulmonary SBRT by dose prescription to the mean internal target volume dose.

Dose, fractionation, normalization and the dose profile inside the target volume vary substantially in pulmonary stereotactic body radiotherapy (SBRT) between different institutions and SBRT technologies. Published planning studies have shown large variations of the mean dose in planning target volume (PTV) and gross tumor volume (GTV) or internal target volume (ITV) when dose prescription is performed to the PTV covering isodose. This planning study investigated whether dose prescription to the mean dose of the ITV improves consistency in pulmonary SBRT dose distributions. This was a multi-institutional planning study by the German Society of Radiation Oncology (DEGRO) working group Radiosurgery and Stereotactic Radiotherapy. CT images and structures of ITV, PTV and all relevant organs at risk (OAR) for two patients with early stage non-small cell lung cancer (NSCLC) were distributed to all participating institutions. Each institute created a treatment plan with the technique commonly used in the institute for lung SBRT. The specified dose fractionation was 3 × 21.5 Gy normalized to the mean ITV dose. Additional dose objectives for target volumes and OAR were provided. In all, 52 plans from 25 institutions were included in this analysis: 8 robotic radiosurgery (RRS), 34 intensity-modulated (MOD), and 10 3D-conformal (3D) radiation therapy plans. The distribution of the mean dose in the PTV did not differ significantly between the two patients (median 56.9 Gy vs 56.6 Gy). There was only a small difference between the techniques, with RRS having the lowest mean PTV dose with a median of 55.9 Gy followed by MOD plans with 56.7 Gy and 3D plans with 57.4 Gy having the highest. For the different organs at risk no significant difference between the techniques could be found. This planning study pointed out that multiparameter dose prescription including normalization on the mean ITV dose in combination with detailed objectives for the PTV and ITV achieve consistent dose distributions for peripheral lung tumors in combination with an ITV concept between different delivery techniques and across institutions

Outward expansion of the lunar wake: ARTEMIS observations

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95030/1/grl29516.pd

How Did the Spider Cross the River? Behavioral Adaptations for River-Bridging Webs in Caerostris darwini (Araneae: Araneidae)

Interspecific coevolution is well described, but we know significantly less about how multiple traits coevolve within a species, particularly between behavioral traits and biomechanical properties of animals' "extended phenotypes". In orb weaving spiders, coevolution of spider behavior with ecological and physical traits of their webs is expected. Darwin's bark spider (Caerostris darwini) bridges large water bodies, building the largest known orb webs utilizing the toughest known silk. Here, we examine C. darwini web building behaviors to establish how bridge lines are formed over water. We also test the prediction that this spider's unique web ecology and architecture coevolved with new web building behaviors.We observed C. darwini in its natural habitat and filmed web building. We observed 90 web building events, and compared web building behaviors to other species of orb web spiders.Caerostris darwini uses a unique set of behaviors, some unknown in other spiders, to construct its enormous webs. First, the spiders release unusually large amounts of bridging silk into the air, which is then carried downwind, across the water body, establishing bridge lines. Second, the spiders perform almost no web site exploration. Third, they construct the orb capture area below the initial bridge line. In contrast to all known orb-weavers, the web hub is therefore not part of the initial bridge line but is instead built de novo. Fourth, the orb contains two types of radial threads, with those in the upper half of the web doubled. These unique behaviors result in a giant, yet rather simplified web. Our results continue to build evidence for the coevolution of behavioral (web building), ecological (web microhabitat) and biomaterial (silk biomechanics) traits that combined allow C. darwini to occupy a unique niche among spiders

Kelvin‐Helmholtz instabilities at the magnetic cavity boundary of comet 67P/Churyumov‐Gerasimenko

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94670/1/jgra21763.pd