NASA Astrobiology Institute

Intra-vehicular free-flying robots are anticipated to support various work in human spaceflight while working side-by-side with astronauts. Such example of robots includes NASA’s Astrobee, DLR’s CIMON, and JAXA’s Int-Ball, which are deployed on the International Space Station. This paper presents the first joint analyses of these robot’s shared experiences, co-authored by their development and operation team members. Despite the different origins and design philosophies, the development and operations of these platforms encountered various convergences. Hence, this paper presents a detailed overview of these robots, presenting their objectives, design, and onboard operations. Hence, joint lessons learned across the lifecycle are presented, from design to on-orbit operations. These lessons learned are anticipated to serve for future development and research as design recommendations.

Nutrient recycling by marine megafauna is a key ecosystem service that has been disturbed by anthropogenic activity. While some hypotheses attribute Southern Ocean ecosystem restructuring to disruptions in micronutrient cycling after the elimination of two million great whales, there is little knowledge of trace metal lability in whale excrement. Here we measured high concentrations of dissolved iron and copper in five baleen whale fecal samples and characterized micromolar levels of organic metal-binding ligands as a proxy for their availability. The iron-ligand pool consisted of weakly-binding ligands and intermediate-binding ligands which enhanced iron stability and potential bioavailability. In comparison, 47 novel strongly-binding metallophores dominated copper-binding, curtailing its potential toxicity. These results illustrate how marine megafauna transform prey biomass into highly-labile micronutrients that they inject directly into the surface ocean, a mechanism whaling reduced by over 90%. Thus, the rapid restructuring of pelagic ecosystems through overharvesting may cause large biogeochemical feedbacks, altering primary productivity and carbon sequestration processes in the ocean.

As we assess the habitability of other worlds, we are limited by being able to only study terrestrial life adapted to terrestrial conditions. The environments found on Earth, though tremendously diverse, do not approach the multitude of potentially habitable environments beyond Earth, and so limited terrestrial adaptive capabilities tell us little about the fundamental biochemical boundaries of life. One approach to this problem is to use experimental laboratory evolution to adapt microbes to these novel environmental conditions. This approach can be dramatically improved through functional metagenomics, large-scale introduction of foreign genetic material to screen for phenotypes in a new host organism. This takes advantage of Earth’s immense biological diversity with high-throughput screening for genetic tools that can facilitate adaptation. We address a key gap in functional metagenomics work by exploring the impact of the experimental parameters chosen for functional metagenomics libraries. Experimental design dictates both fragment size and copy number, and we show that both can have outsized effects on the resultant phenotypes in non-intuitive ways. These results highlight the potential of functional metagenomics for adapting life rapidly to challenging new environments, with important implications in both astrobiology and bioindustry, while also emphasizing the impacts of decisions in experimental design.

Eleven lines of promethium Pm II in the spectra of the magnetic peculiar A0 V star HD 25354 were analysed thoroughly in order to obtain information about how the short-lived element lines behave in spectra acquired on different observation dates. It has turned out that the intensity variations in time are typical for these lines with some of them being observed as emissive or absent at certain time intervals. The obtained list of Pm II lines in the spectra of the magnetic peculiar star HD 25354 has been employed to investigate promethium abundances in atmospheres of other stars, such as HR 465 (Teff = 111,840 K), HIP 13962 (Teff = 6,250 K) and BL 138 (Teff = 3,939 K). The investigation interval has been limited to the spectral range of 4000–5800 Å and oscillator strengths within –0.76 < log gf < 0.4.

The success of the Transiting Exoplanet Survey Satellite mission has led to the discovery of an abundance of Venus Zone terrestrial planets that orbit relatively bright host stars. Atmospheric observations of these planets play a crucial role in understanding the evolutionary history of terrestrial planets, past habitable states, and the divergence of Venus and Earth climates. The transmission spectrum of a Venus-like exoplanet can be difficult to distinguish from that of an Earthlike exoplanet however, which could severely limit what can be learned from studying exoVenuses. In this work we further investigate differences in transmission between hypothetical exoEarths and exoVenuses, both with varying amounts of atmospheric carbon dioxide (CO2). The exoEarths and exoVenuses were modeled assuming they orbit TRAPPIST-1 on the runaway greenhouse boundary. We simulated James Webb Space Telescope Near-Infrared Spectrograph PRISM transit observations of both sets of planets between 0.6 and 5.2 μm, and quantified the detectability of major absorption features in their transmission spectra. The exoEarth spectra include several large methane (CH4) features that can be detected in as few as six transits. The CH4 feature at 3.4 μm is the optimal for feature for discerning an exoEarth from an exoVenus since it is easily detectable and does not overlap with CO2 features. The sulfur dioxide (SO2) feature at 4.0 μm is the best indicator of an exoVenus, but it is detectable in atmospheres with reduced CO2 abundance.

Simple SummaryPessoa postulates that bran anatomy associated with the processing and expression of emotion-laden content, such as the amygdala and limbic cortices, is resource capacity-limited. Thus, brains require multichannel or parallel structure-function connectivity to effectively perceive, motivate, integrate, represent, recall, and execute cognitive-emotional relationships. Pessoa employs 2D graph network theory to support his views on distributed brain organization and operation, concluding that brains evolve through dual-process competition and cooperation to form highly embedded computational architectures with little structure–function compartmentalization. Low-dimensional graph theory has become a popular mathematical tool to model, simulate, and visualize evolving complex, sometimes intractable, brain networks. Graph theory offers advantages to study and understand various biological and technological network behaviors and, for Pessoa, it permits a framework that accounts for structure–function features thus far poorly explained by perhaps “traditional” perspectives, which advocate for the mapping of structure–function relationships onto well-localized brain areas. Pessoa nonetheless fails to fully appreciate the significance of weak-to-strong structure-function correlations for brain dynamics and why those correlations, caused by differential control parameters such as Hebbian and antiHebbian neuronal plasticity, are best assessed using neural field theories. Neural fields demonstrate that embedded brain networks optimally evolve between exotic computational phases and continuum limits with the accompaniment of some network partitioning, rather than unconstrained embeddedness, when rendering healthy cognitive-emotional functionality.In The cognitive-emotional brain, Pessoa overlooks continuum effects on nonlinear brain network connectivity by eschewing neural field theories and physiologically derived constructs representative of neuronal plasticity. The absence of this content, which is so very important for understanding the dynamic structure-function embedding and partitioning of brains, diminishes the rich competitive and cooperative nature of neural networks and trivializes Pessoa’s arguments, and similar arguments by other authors, on the phylogenetic and operational significance of an optimally integrated brain filled with variable-strength neural connections. Riemannian neuromanifolds, containing limit-imposing metaplastic Hebbian- and antiHebbian-type control variables, simulate scalable network behavior that is difficult to capture from the simpler graph-theoretic analysis preferred by Pessoa and other neuroscientists. Field theories suggest the partitioning and performance benefits of embedded cognitive-emotional networks that optimally evolve between exotic classical and quantum computational phases, where matrix singularities and condensations produce degenerate structure-function homogeneities unrealistic of healthy brains. Some network partitioning, as opposed to unconstrained embeddedness, is thus required for effective execution of cognitive-emotional network functions and, in our new era of neuroscience, should be considered a critical aspect of proper brain organization and operation.

High-resolution far-ultraviolet broadband Fourier-transform photoabsorption spectra of 32S16O, 33S16O, 34S16O, and 36S16O are recorded in a microwave discharge seeded with SO2. The and bands are observed or inferred in the –51,000 cm−1 (196 to 233 nm) spectral range. This is the first experimental detection of a level and of any of these observed bands in an S-substituted isotopologue. Additional measurements of provide a calibration of the SO column density. Measured band profiles are fitted to an effective-Hamiltonian model of coupled excited B 3Σ− and C 3Π states along with their predissociation linewidths and absorption band strengths. Electronic-state potential-energy curves and transition moments are deduced. The end result is a list of line frequencies, f-values, and dissociation widths describing the far-ultraviolet photodissociation spectrum of SO that is accurate enough for computing atmospheric photolytic isotope-fractionation. Linelists, and photoabsorption and photodissociation cross sections are available as supplementary data.

A new version of the Earth system model of intermediate complexity (CANOPS-GRB) was developed for use in quantitatively assessing the dynamics and stability of atmospheric and oceanic chemistry over geologic timescales. The new release is designed to represent the coupled major element cycles of C, N, P, O, and S, as well as the global redox budget (GRB) in Earth’s exogenic (ocean-atmosphere-crust) system, using a process-based approach. This framework provides a mechanistic model of the evolution of atmospheric and oceanic O2 levels on geologic timescales and enables comparison with a wide variety of geological records to further constrain the processes driving Earth’s oxygenation. A complete detailed description of the resulting Earth system model and its new features are provided. The performance of CANOPS-GRB is then evaluated by comparing a steady-state simulation under present-day conditions with a comprehensive set of oceanic data and existing global estimates of bio-element cycling. The dynamic response of the model is also examined by varying phosphorus availability in the exogenic system. CANOPS-GRB reliably simulates the short- and long-term evolution of the coupled C-N-P-O2-S biogeochemical cycles and is generally applicable across any period of Earth’s history given suitable modifications to boundary conditions and forcing regime. The simple and adaptable design of the model also makes it useful to interrogate a wide range of problems related to Earth’s oxygenation history and Earth-like exoplanets more broadly. The model source code is available on GitHub, and represents a unique community tool for investigating the dynamics and stability of atmospheric and oceanic chemistry on long timescales.