COTSAT Small Spacecraft Cost Optimization for Government and Commercial Use

Cost Optimized Test of Spacecraft Avionics and Technologies (COTSAT-1) is an ongoing spacecraft research and development project at NASA Ames Research Center (ARC). The prototype spacecraft, also known as CheapSat, is the first of what could potentially be a series of rapidly produced low-cost spacecraft. The COTSAT-1 team is committed to realizing the challenging goal of building a fully functional spacecraft for $500K parts and$2.0M labor. The project's efforts have resulted in significant accomplishments within the scope of a limited budget and schedule. Completion and delivery of the flight hardware to the Engineering Directorate at NASA Ames occurred in February 2009 and a cost effective qualification program is currently under study. The COTSAT-1 spacecraft is now located at NASA Ames Research Center and is awaiting a cost effective launch opportunity. This paper highlights the advancements of the COTSAT-1 spacecraft cost reduction techniques

Tracking of Energy Performance Indicators in Residential Building Stocks – Different Approaches and Common Results - EPISCOPE Synthesis Report No. 4

A central task of IEE EPISCOPE project was to carry out energy balance calculations and scenario analysis for national, regional or local residential building stocks against the background of energy saving and climate protection targets. The EPISCOPE Synthesis Report No. 4 documents the individual approaches of collecting information for the investigated residential building stocks as a foundation for building stock models and scenario calculations. Issues related to the availability of data and data quality are discussed, and concepts for a continuous monitoring (a regular data collection) are presented as a basis for a future tracking of energy performance in the observed building stocks

Percutaneous coronary angioplasty versus coronary artery bypass grafting in treatment of unprotected left main stenosis (NOBLE) : a prospective, randomised, open-label, non-inferiority trial

Background Coronary artery bypass grafting (CABG) is the standard treatment for revascularisation in patients with left main coronary artery disease, but use of percutaneous coronary intervention (PCI) for this indication is increasing. We aimed to compare PCI and CABG for treatment of left main coronary artery disease. Methods In this prospective, randomised, open-label, non-inferiority trial, patients with left main coronary artery disease were enrolled in 36 centres in northern Europe and randomised 1: 1 to treatment with PCI or CABG. Eligible patients had stable angina pectoris, unstable angina pectoris, or non-ST-elevation myocardial infarction. Exclusion criteria were ST-elevation myocardial infarction within 24 h, being considered too high risk for CABG or PCI, or expected survival of less than 1 year. The primary endpoint was major adverse cardiac or cerebrovascular events (MACCE), a composite of all-cause mortality, non-procedural myocardial infarction, any repeat coronary revascularisation, and stroke. Non-inferiority of PCI to CABG required the lower end of the 95% CI not to exceed a hazard ratio (HR) of 1 . 35 after up to 5 years of follow-up. The intention-to-treat principle was used in the analysis if not specified otherwise. This trial is registered with ClinicalTrials.gov identifier, number NCT01496651. Findings Between Dec 9, 2008, and Jan 21, 2015, 1201 patients were randomly assigned, 598 to PCI and 603 to CABG, and 592 in each group entered analysis by intention to treat. Kaplan-Meier 5 year estimates of MACCE were 29% for PCI (121 events) and 19% for CABG (81 events), HR 1 . 48 (95% CI 1 . 11-1 . 96), exceeding the limit for non-inferiority, and CABG was significantly better than PCI (p=0 . 0066). As-treated estimates were 28% versus 19% (1 . 55, 1 . 18-2 . 04, p= 0 . 0015). Comparing PCI with CABG, 5 year estimates were 12% versus 9% (1 . 07, 0 . 67-1 . 72, p= 0 . 77) for all-cause mortality, 7% versus 2% (2 . 88, 1 . 40-5 . 90, p= 0 . 0040) for non-procedural myocardial infarction, 16% versus 10% (1 . 50, 1 . 04-2 . 17, p= 0 . 032) for any revascularisation, and 5% versus 2% (2 . 25, 0 . 93-5 . 48, p= 0 . 073) for stroke. Interpretation The findings of this study suggest that CABG might be better than PCI for treatment of left main stem coronary artery disease.Peer reviewe

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Differential predictors for alcohol use in adolescents as a function of familial risk

Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions

Differential predictors for alcohol use in adolescents as a function of familial risk

Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions