Design and baseline data from the vanguard of the Comparison of Depression Interventions after Acute Coronary Syndrome (CODIACS) randomized controlled trial

This paper describes the rationale and design of the vanguard for the Comparison of Depression Interventions after Acute Coronary Syndrome (CODIACS), a multicenter, randomized, controlled trial of a patient preference‐based, stepped care protocol for persistent depressive symptoms after acute coronary syndrome (ACS). The overall aim of the vanguard phase was to determine whether the patient-preference, stepped care protocol, which is based on the intervention used in the recent Coronary Psychosocial Evaluation Studies (COPES) trial, was feasible in patients with recent ACS who were recruited from 5 geographically diverse sites. Innovative design features of this trial include randomization to either initial patient-preference of treatment or to a referred care arm in which the primary care provider decided upon care. Additionally, delivery of psychotherapy was accomplished by telephone, or webcam, depending upon patient preference. The vanguard phase provides estimates of eligibility and screening/enrollment ratios, patient acceptance of screening, and retention. In this report, we describe the innovative features and the baseline results of the vanguard phase of CODIACS. The data from this vanguard study will be used to finalize planning for a large, phase III clinical trial designed to evaluate the effect of treatment on depressive symptoms, coronary events, and death

The Φ-Sat-1 mission: the first on-board deep neural network demonstrator for satellite earth observation

Artificial intelligence is paving the way for a new era of algorithms focusing directly on the information contained in the data, autonomously extracting relevant features for a given application. While the initial paradigm was to have these applications run by a server hosted processor, recent advances in microelectronics provide hardware accelerators with an efficient ratio between computation and energy consumption, enabling the implementation of artificial intelligence algorithms 'at the edge'. In this way only the meaningful and useful data are transmitted to the end-user, minimising the required data bandwidth, and reducing the latency with respect to the cloud computing model. In recent years, European Space Agency is promoting the development of disruptive innovative technologies on-board Earth Observation missions. In this field, the most advanced experiment to date is the Φ-sat-1, which has demonstrated the potential of Artificial Intelligence as a reliable and accurate tool for cloud detection on-board a hyperspectral imaging mission. The activities involved included demonstrating the robustness of the Intel Movidius Myriad 2 hardware accelerator against ionising radiation, developing a Cloudscout segmentation neural network, run on Myriad 2, to identify, classify, and eventually discard on-board the cloudy images, and assessing of the innovative Hyperscout-2 hyperspectral sensor. This mission represents the first official attempt to successfully run an AI Deep Convolutional Neural Network (CNN) directly inferencing on a dedicated accelerator on-board a satellite, opening the way for a new era of discovery and commercial applications driven by the deployment of on-board AI

Identifying Earth-impacting asteroids using an artificial neural network

By means of a fully connected artificial neural network, we identified asteroids with the potential to impact Earth. The resulting instrument, named the Hazardous Object Identifier (HOI), was trained on the basis of an artificial set of known impactors which were generated by launching objects from Earth’s surface and integrating them backward in time. HOI was able to identify 95.25% of the known impactors simulated that were present in the test set as potential impactors. In addition, HOI was able to identify 90.99% of the potentially hazardous objects identified by NASA, without being trained on them directly

Adverse Drug Reactions in Children - International Surveillance and Evaluation (ADVISE) : A Multicentre Cohort Study

Background: A previous meta-analysis reported that 9.5% of hospitalized children suffered from an adverse drug reaction (ADR); however, reported incidences among studies varied. Objective: To enhance the knowledge of ADRs in paediatric hospitalized patients at a global level we investigated the incidence and characteristics of ADRs in hospitalized children in European and non-European countries. Methods: A prospective observational cohort study was conducted in academic and non-academic hospitals in five countries: Australia, Germany, Hong Kong, Malaysia and the UK. Children aged 0-18 years admitted during a 3-month period (between 1 October 2008 and 31 December 2009) were recruited. The main outcome measures were incidence, causality and outcome of ADRs. Results: A total of 1278 patients (1340 admissions) were included [Australia n=146 (149 admissions), Germany n=376 (407), Hong Kong n=143 (149), Malaysia n=300 (314) and the UK n=313 (321)]. The median age was 2 years (interquartile range [TOR] 0-7). Patients received a total of 5367 drugs (median 3; IQR 2-5) and median length of hospital stay was 4 days (IQR 3-7). A total of 380 ADRs were identified in 211 patients. The resultant ADR incidence of 16.5% (95% Cl 14.5, 18.7) varied significantly between countries (p<0.001). The highest incidences were observed in Malaysia and the UK. 65.3% (n=248) of A DRs were found to be probable, and 24% of the ADRs were serious, with one being fatal. Conclusions: By comparing data from five countries in Europe, Asia and Australia we have shown that the incidence of ADRs in hospitalized children is at least as high as incidences published in adults. However, the variation between countries was mainly due to different populations and treatment strategies. Particular attention should be given to opioid use in hospitalized children.Peer reviewe

FSSCat: The Federated Satellite Systems 3Cat Mission: Demonstrating the Capabilities of CubeSats to Monitor Essential Climate Variables of the Water Cycle

10 pages, 6 figures, 1 tableThe Federated Satellite Systems/ 3 Cat-5 (FSSCat) mission was the winner of the European Space Agency (ESA) Sentinel Small Satellite (S 3 ) Challenge and overall winner of the 2017 Copernicus Masters competition. It consisted of two six-unit CubeSats. The Earth observation payloads were 1) the Flexible Microwave Payload 2 (FMPL-2) onboard 3 Cat-5/A, an L-band microwave radiometer and GNSS reflectometer (GNSS-R) implemented using a software-defined radio (SDR), and 2) the HyperScout-2 onboard 3 Cat-5/B, a hyperspectral camera, with the first experiment using artificial intelligence to discard cloudy images. FSSCat was launched on 3 September 2020 and injected into a 535-km synchronous orbit. 3 Cat-5/A was operated for three months until the payload was probably damaged by a solar flare and coronal mass ejection. During this time, all scientific requirements were met, including the generation of coarse-resolution and downscaled soil moisture (SM) maps, sea ice extent (SIE) maps, concentration and thickness maps, and even wind speed (WS) and sea surface salinity (SSS) maps, which were not originally foreseen. 3 Cat-5/B was operated a few more months until the number of images acquired met the requirements. This article briefly describes the FSSCat mission and the FMPL-2 payload and summarizes the main scientific resultsWith the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)Peer reviewe