A second space age spanning omics, platforms and medicine across orbits.

The recent acceleration of commercial, private and multi-national spaceflight has created an unprecedented level of activity in low Earth orbit, concomitant with the largest-ever number of crewed missions entering space and preparations for exploration-class (lasting longer than one year) missions. Such rapid advancement into space from many new companies, countries and space-related entities has enabled a 'second space age'. This era is also poised to leverage, for the first time, modern tools and methods of molecular biology and precision medicine, thus enabling precision aerospace medicine for the crews. The applications of these biomedical technologies and algorithms are diverse, and encompass multi-omic, single-cell and spatial biology tools to investigate human and microbial responses to spaceflight. Additionally, they extend to the development of new imaging techniques, real-time cognitive assessments, physiological monitoring and personalized risk profiles tailored for astronauts. Furthermore, these technologies enable advancements in pharmacogenomics, as well as the identification of novel spaceflight biomarkers and the development of corresponding countermeasures. In this Perspective, we highlight some of the recent biomedical research from the National Aeronautics and Space Administration, Japan Aerospace Exploration Agency, European Space Agency and other space agencies, and detail the entrance of the commercial spaceflight sector (including SpaceX, Blue Origin, Axiom and Sierra Space) into aerospace medicine and space biology, the first aerospace medicine biobank, and various upcoming missions that will utilize these tools to ensure a permanent human presence beyond low Earth orbit, venturing out to other planets and moons.

Risk measures for power failures in transmission systems.

We present a novel framework for evaluating the risk of failures in power transmission systems. We use the concept of systemic risk measures from the financial mathematics literature with models of power system failures in order to quantify the risk of the entire power system for design and comparative purposes. The proposed risk measures provide the collection of capacity vectors for the components in the system that lead to acceptable outcomes. Keys to the formulation of our measures of risk are two elements: a model of system behavior that provides the (distribution of) outcomes based on component capacities and an acceptability criterion that determines whether a (random) outcome is acceptable from an aggregated point of view. We examine the effects of altering the line capacities on energy not served under a variety of networks, flow manipulation methods, load shedding schemes, and load profiles using Monte Carlo simulations. Our results provide a quantitative comparison of the performance of these schemes, measured by the required line capacity. These results provide more complete descriptions of the risks of power failures than the previous, one-dimensional metrics.