Preparation and Integration of ALHAT Precision Landing Technology for Morpheus Flight Testing

The Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) project has developed a suite of prototype sensors for enabling autonomous and safe precision land- ing of robotic or crewed vehicles on solid solar bodies under varying terrain lighting condi- tions. The sensors include a Lidar-based Hazard Detection System (HDS), a multipurpose Navigation Doppler Lidar (NDL), and a long-range Laser Altimeter (LAlt). Preparation for terrestrial ight testing of ALHAT onboard the Morpheus free- ying, rocket-propelled ight test vehicle has been in progress since 2012, with ight tests over a lunar-like ter- rain eld occurring in Spring 2014. Signi cant work e orts within both the ALHAT and Morpheus projects has been required in the preparation of the sensors, vehicle, and test facilities for interfacing, integrating and verifying overall system performance to ensure readiness for ight testing. The ALHAT sensors have undergone numerous stand-alone sensor tests, simulations, and calibrations, along with integrated-system tests in special- ized gantries, trucks, helicopters and xed-wing aircraft. A lunar-like terrain environment was constructed for ALHAT system testing during Morpheus ights, and vibration and thermal testing of the ALHAT sensors was performed based on Morpheus ights prior to ALHAT integration. High- delity simulations were implemented to gain insight into integrated ALHAT sensors and Morpheus GN&C system performance, and command and telemetry interfacing and functional testing was conducted once the ALHAT sensors and electronics were integrated onto Morpheus. This paper captures some of the details and lessons learned in the planning, preparation and integration of the individual ALHAT sen- sors, the vehicle, and the test environment that led up to the joint ight tests

Historical Research Approaches to the Analysis of Internationalisation

Historical research methods and approaches can improve understanding of the most appropriate techniques to confront data and test theories in internationalisation research. A critical analysis of all “texts” (sources), time series analyses, comparative methods across time periods and space, counterfactual analysis and the examination of outliers are shown to have the potential to improve research practices. Examples and applications are shown in these key areas of research with special reference to internationalisation processes. Examination of these methods allows us to see internationalisation processes as a sequenced set of decisions in time and space, path dependent to some extent but subject to managerial discretion. Internationalisation process research can benefit from the use of historical research methods in analysis of sources, production of time-lines, using comparative evidence across time and space and in the examination of feasible alternative choices

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

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 hospitalization2,3,4 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

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease