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Developing space occupancy - Perspectives on NASA future space program planning
Potential future manned space flight missions for the time after the development of the space transportation system with the space shuttle are considered, taking into account a sequence of activities concerning a gradually increasing penetration of space by man. The activities are related to the permanent occupancy of near-earth space, the permanent occupancy of near-moon space, the full self-sufficiency of man in earth-moon space, and the permanent occupancy of heliocentric space. Attention is given to Mars orbiting stations, the exploration of the asteroids, comet exploration, planet engineering programs, heliocentric orbit installation, the evolution of the earth orbit space community, space industrialization technology, lunar base development, and evolutionary paths to far-future space endeavors.
Dawn Mission: A Journey in Space and Time
By successively orbiting both 4 Vesta and 1 Ceres the Dawn mission directly addresses the longstanding goals of NASA and the planetary community to understand the origin and evolution of the solar system by obtaining geophysical and geochemical data on diverse main belt asteroids. Ceres and Vesta are two complementary terrestrial protoplanets (one apparently "wet" and one "dry"), whose accretion was terminated by the formation of Jupiter. Ceres is little changed since it formed in the early solar system, while Vesta has experienced significant heating and differentiation. Both have remained intact over the age of the solar system, thereby retaining a record of events and processes from the time of planet formation. Detailed study of the geophysics and geochemistry of these two bodies provides critical benchmarks for the early solar system conditions and processes that shaped its subsequent evolution. Dawn provides the missing context for both primitive and evolved meteoritic data, thus playing a central role in understanding terrestrial planet formation and the evolution of the asteroid belt. Dawn is to be launched in May 2006 arriving at Vesta in 2010 and Ceres in 2014, stopping at each to make 11 months of orbital measurements. The spacecraft uses solar electric propulsion both in cruise and in orbit to make most efficient use of its xenon propellant. The spacecraft carries a framing camera, visible and infrared mapping spectrometer, gamma ray/neutron spectrometer, a laser altimeter, magnetometer, and radio science.
PSI/J: A Portable Interface for Submitting, Monitoring, and Managing Jobs
It is generally desirable for high-performance computing (HPC) applications to be portable between HPC systems, for example to make use of more performant hardware, make effective use of allocations, and to co-locate compute jobs with large datasets. Unfortunately, moving scientific applications between HPC systems is challenging for various reasons, most notably that HPC systems have different HPC schedulers. We introduce PSI/J, a job management abstraction API intended to simplify the construction of software components and applications that are portable over various HPC scheduler implementations. We argue that such a system is both necessary and that no viable alternative currently exists. We analyze similar notable APIs and attempt to determine the factors that influenced their evolution and adoption by the HPC community. We base the design of PSI/J on that analysis. We describe how PSI/J has been integrated in three workflow systems and one application, and also show via experiments that PSI/J imposes minimal overhead.
Impacts of directed evolution and soil management legacy on the maize rhizobiome
Domestication and agricultural intensification dramatically altered maize and its cultivation environment. Changes in maize genetics (G) and environmental (E) conditions increased productivity under high-synthetic-input conditions. However, novel selective pressures on the rhizobiome may have incurred undesirable tradeoffs in organic agroecosystems, where plants obtain nutrients via microbially mediated processes including mineralization of organic matter. Using twelve maize genotypes representing an evolutionary transect (teosintes, landraces, inbred parents of modern elite germplasm, and modern hybrids) and two agricultural soils with contrasting long-term management, here we integrated analyses of rhizobiome community structure, potential microbe-microbe interactions, and N-cycling functional genes to better understand the impacts of maize evolution and soil management legacy on rhizobiome recruitment. We show complex shifts in rhizobiome communities during directed evolution of maize (defined as the transition from teosinte to modern hybrids), with a larger effect of domestication (teosinte to landraces) than modern breeding (inbreds to hybrids) on rhizobiome structure and greater impacts of modern breeding on potential microbe-microbe interactions. Rhizobiome structure was significantly correlated with plant nutrient composition. Furthermore, plant biomass and nutrient content were affected by G x E interactions in which teosinte and landrace genotypes had better relative performance in the organic legacy soil than inbred and modern genotypes. The abundance of six N-cycling genes of relevance for plant nutrition and N loss pathways did not significantly differ between teosinte and modern rhizospheres in either soil management legacy. These results provide insight into the potential for improving maize adaptation to organic systems and contribute to interdisciplinary efforts toward developing resource-efficient, biologically based agroecosystems.
Studying Microbial Adaptation in the Laboratory: Sensor & Control Upgrades for an Experimental Evolution Biofluidics System
Experimental evolution (EE) involves iteratively exposing a microbial community to specific stressors to study its response to changes in environment over time. EE work is commonly done manually in the laboratory, but, when there are many environmental variables to measure and adjust, it is highly labor intensive, prone to human error, and challenging to scale. Single-purpose automated continuous culturing chambers exist, but implement only limited stressor types. A more general-purpose design is desirable. The BeING Lab at Ames Research Center created the prototype Automated Adaptive Directed Evolution Chamber (AADEC) to address these problems, beginning with Escherichia coli tolerance of short-wave ultraviolet (UV-C) radiation and of temperature. In newer versions, AADEC monitors microbial activity and can adjust the UV-C and temperature levels automatically. An optical density measurement is used to determine how many cells are present in the growth medium—over time, this corresponds to how many survive and reproduce. Oxidation-reduction potential provides information on consumed metabolic energy, and pH and electrical conductivity on metabolic products. Dissolved oxygen content is used to determine aerobic vs anaerobic growth. A Raspberry Pi computer processes all this data to set the UV-C stressor level. AADEC’s auxiliary systems include peristaltic pumps to change media and agitation to counteract cell settling. These actuators can also act as additional stressors. With the Raspberry Pi monitoring sensors and adjusting actuators in real time, AADEC takes measurements and controls the environment much more accurately than can be done with a manual EE implementation. The third and latest AADEC iteration is the first to simplify design and usage with circuits on PCBs and the ability to pre-program experimental protocols. Still planned is expansion to a multi-well design for the study of varying cell cultures in parallel, which will enable researchers to retain and re-inoculate cultures exhibiting the desired trait most strongly while flushing out others. AADEC’s special capabilities make it a valuable tool for studying life under multiple stressors, enabling scientists to replicate changes in climate on microbes for study in a lab setting.
In situ neutron scattering study of nanostructured PbTe-PbS bulk thermoelectric material
Nanostructures play an important role in thermoelectric materials. Their thermal stability, such as phase change and evolution at elevated temperatures, is thus of great interest to the thermoelectric community. In this study, in situ neutron diffraction was used to examine the phase evolution of nanostructured bulk PbTe-PbS materials fabricated using hot pressing and pulsed electrical current sintering (PECS). The PbS second phase was observed in all samples in the as-pressed condition. The temperature dependent lattice parameter and phase composition data show an initial formation of PbS precipitates followed by a redissolution during heating. The redissolution process started around 570 600 K, and completed at approximately 780 K. During cooling, the PECS sample followed a reversible curve while the heating/cooling behavior of the hot pressed sample was irreversible.
Convergent evolution and horizontal gene transfer in Arctic Ocean microalgae
Microbial communities in the world ocean are affected strongly by oceanic circulation, creating characteristic marine biomes. The high connectivity of most of the ocean makes it difficult to disentangle selective retention of colonizing genotypes (with traits suited to biome specific conditions) from evolutionary selection, which would act on founder genotypes over time. The Arctic Ocean is exceptional with limited exchange with other oceans and ice covered since the last ice age. To test whether Arctic microalgal lineages evolved apart from algae in the global ocean, we sequenced four lineages of microalgae isolated from Arctic waters and sea ice. Here we show convergent evolution and highlight geographically limited HGT as an ecological adaptive force in the form of PFAM complements and horizontal acquisition of key adaptive genes. Notably, ice-binding proteins were acquired and horizontally transferred among Arctic strains. A comparison with Tara Oceans metagenomes and metatranscriptomes confirmed mostly Arctic distributions of these IBPs. The phylogeny of Arctic-specific genes indicated that these events were independent of bacterial-sourced HGTs in Antarctic Southern Ocean microalgae.
Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data
Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) to compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.
Tectonic and geological setting influence hot spring microbiology
Hydrothermal systems form at divergent and convergent boundaries of lithospheric plates and within plates due to weakened crust and mantle plumes, playing host to diverse microbial ecosystems. Little is known of how differences in tectonic setting influence the geochemical and microbial compositions of these hydrothermal ecosystems. Here, for this work, coordinated geochemical and microbial community analyses were conducted on 87 high-temperature (>65°C) water and sediment samples from hot springs in Yellowstone National Park, Wyoming, USA ( n = 41; mantle plume setting), Iceland ( n = 41, divergent boundary), and Japan ( n = 5; convergent boundary). Region-specific variation in geochemistry and sediment-associated 16S rRNA gene amplicon sequence variant (ASV) composition was observed, with 16S rRNA gene assemblages being nearly completely distinguished by region and pH being the most explanatory parameter within regions. Several low abundance ASVs exhibited cosmopolitan distributions across regions, while most high-abundance ASVs were only identified in specific regions. The presence of some cosmopolitan ASVs across regions argues against dispersal limitation primarily shaping the distribution of taxa among regions. Rather, the results point to local tectonic and geologic characteristics shaping the geochemistry of continental hydrothermal systems that then select for distinct microbial assemblages. These results provide new insights into the co-evolution of hydrothermal systems and their microbial communities.
PERISCOPE: PERIapsis Subsurface Cave Optical Explorer
The PERISCOPE study focuses primarily on lunar caves, due to the potential for being imaged in orbital scenarios. In the intervening years, from 2012-2015, scientists developed further rationales and interest in the scientific value of lunar caves. It does not appear that they are likely to be sinks for water-ice due to the relatively warm temperatures(~-20 degrees Celsius) in the caves leading to geologically-rapid migration of unbound water due to sublimation, and inevitable loss through any skylights. However, the skylights themselves reveal apparent complex layering, which may speak to a more complex multi-stage evolution of mare flood basalts than previously considered, and so their examination may provide even more insight into the lunar mare, which in turn provide a primary record of early solar system crustal formal and evolution processes. Further extrapolation of these insights can be found within the exoplanet community of researchers,who find the information useful for calibrating star formation and planetary evolution models. In addition, catalogues of lunar and martian skylights, "caves" or "atypical pit craters" have been developed, with numbers for both bodies now in the low hundreds thanks to additional high resolution surveys and revisiting the existing image databases.
Microbial communities of the Laurentian Great Lakes reflect connectivity and local biogeochemistry
The Laurentian Great Lakes are a vast, interconnected freshwater system spanning strong physicochemical gradients, thus constituting a powerful natural laboratory for addressing fundamental questions about microbial ecology and evolution. We present a comparative analysis of pelagic microbial communities across all five Laurentian Great Lakes, focusing on Bacterial and Archaeal picoplankton characterized via 16S rRNA amplicon sequencing. We collected samples throughout the water column from the major basins of each lake in spring and summer over 2 years. Two oligotypes, classified as LD12 (Alphaproteobacteria) and acI-B1 (Actinobacteria), were among the most abundant in every sample. At the same time, microbial communities showed distinct patterns with depth during summer stratification. Deep hypolimnion samples were frequently dominated by a Chloroflexi oligotype that reached up to 19% relative abundance. Stratified surface communities differed between the colder, less productive upper lakes (Superior, Michigan, Huron) and warmer, more productive lower lakes (Erie, Ontario), in part due to an Actinobacteria oligotype (acI-C2) that averaged 7.7% of sequences in the lower lakes but <0.2% in the upper lakes. Together, our findings suggest that both hydrologic connectivity and local selective pressures shape microbial communities in the Great Lakes and establish a framework for future investigations.
Bootstrapping outperforms community‐weighted approaches for estimating the shapes of phenotypic distributions
Abstract Estimating phenotypic distributions of populations and communities is central to many questions in ecology and evolution. These distributions can be characterized by their moments (mean, variance, skewness and kurtosis) or diversity metrics (e.g. functional richness). Typically, such moments and metrics are calculated using community‐weighted approaches (e.g. abundance‐weighted mean). We propose an alternative bootstrapping approach that allows flexibility in trait sampling and explicit incorporation of intraspecific variation, and show that this approach significantly improves estimation while allowing us to quantify uncertainty. We assess the performance of different approaches for estimating the moments of trait distributions across various sampling scenarios, taxa and datasets by comparing estimates derived from simulated samples with the true values calculated from full datasets. Simulations differ in sampling intensity (individuals per species), sampling biases (abundance, size), trait data source (local vs. global) and estimation method (two types of community‐weighting, two types of bootstrapping). We introduce the traitstrap R package, which contains a modular and extensible set of bootstrapping and weighted‐averaging functions that use community composition and trait data to estimate the moments of community trait distributions with their uncertainty. Importantly, the first function in the workflow, trait_fill , allows the user to specify hierarchical structures (e.g. plot within site, experiment vs. control, species within genus) to assign trait values to each taxon in each community sample. Across all taxa, simulations and metrics, bootstrapping approaches were more accurate and less biased than community‐weighted approaches. With bootstrapping, a sample size of 9 or more measurements per species per trait generally included the true mean within the 95% CI. It reduced average percent errors by 26%–74% relative to community‐weighting. Random sampling across all species outperformed both size‐ and abundance‐biased sampling. Our results suggest randomly sampling ~9 individuals per sampling unit and species, covering all species in the community and analysing the data using nonparametric bootstrapping generally enable reliable inference on trait distributions, including the central moments, of communities. By providing better estimates of community trait distributions, bootstrapping approaches can improve our ability to link traits to both the processes that generate them and their effects on ecosystems.
Cross-linked structure of network evolution
We study the temporal co-variation of network co-evolution via the cross-link structure of networks, for which we take advantage of the formalism of hypergraphs to map cross-link structures back to network nodes. We investigate two sets of temporal network data in detail. In a network of coupled nonlinear oscillators, hyperedges that consist of network edges with temporally co-varying weights uncover the driving co-evolution patterns of edge weight dynamics both within and between oscillator communities. In the human brain, networks that represent temporal changes in brain activity during learning exhibit early co-evolution that then settles down with practice. Subsequent decreases in hyperedge size are consistent with emergence of an autonomous subgraph whose dynamics no longer depends on other parts of the network. Our results on real and synthetic networks give a poignant demonstration of the ability of cross-link structure to uncover unexpected co-evolution attributes in both real and synthetic dynamical systems. This, in turn, illustrates the utility of analyzing cross-links for investigating the structure of temporal networks.
Real-time materials evolution visualized withinintact cycling alkaline batteries
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Lower viral evolutionary pressure under stable versus fluctuating conditions in subzero Arctic brines
Climate change threatens Earth’s ice-based ecosystems which currently offer archives and eco-evolutionary experiments in the extreme. Arctic cryopeg brine (marine-derived, within permafrost) and sea ice brine, similar in subzero temperature and high salinity but different in temporal stability, are inhabited by microbes adapted to these extreme conditions. However, little is known about their viruses (community composition, diversity, interaction with hosts, or evolution) or how they might respond to geologically stable cryopeg versus fluctuating sea ice conditions. We used long- and short-read viromics and metatranscriptomics to study viruses in Arctic cryopeg brine, sea ice brine, and underlying seawater, recovering 11,088 vOTUs (~species-level taxonomic unit), a 4.4-fold increase of known viruses in these brines. More specifically, the long-read-powered viromes doubled the number of longer (≥25 kb) vOTUs generated and recovered more hypervariable regions by >5-fold compared to short-read viromes. Distribution assessment, by comparing to known viruses in public databases, supported that cryopeg brine viruses were of marine origin yet distinct from either sea ice brine or seawater viruses, while 94% of sea ice brine viruses were also present in seawater. A virus-encoded, ecologically important exopolysaccharide biosynthesis gene was identified, and many viruses (~half of metatranscriptome-inferred “active” vOTUs) were predicted as actively infecting the dominant microbial genera Marinobacter and Polaribacter in cryopeg and sea ice brines, respectively. Evolutionarily, microdiversity (intra-species genetic variations) analyses suggested that viruses within the stable cryopeg brine were under significantly lower evolutionary pressures than those in the fluctuating sea ice environment, while many sea ice brine virus-tail genes were under positive selection, indicating virus-host co-evolutionary arms races. Our results confirmed the benefits of long-read-powered viromics in understanding the environmental virosphere through significantly improved genomic recovery, expanding viral discovery and the potential for biological inference. Evidence of viruses actively infecting the dominant microbes in subzero brines and modulating host metabolism underscored the potential impact of viruses on these remote and underexplored extreme ecosystems. Microdiversity results shed light on different strategies viruses use to evolve and adapt when extreme conditions are stable versus fluctuating. Together, these findings verify the value of long-read-powered viromics and provide foundational data on viral evolution and virus-microbe interactions in Earth’s destabilized and rapidly disappearing cryosphere.
Multiple social platforms reveal actionable signals for software vulnerability awareness: A study of GitHub, Twitter and Reddit
Software vulnerabilities are flaws in computer systems that leave users open to attack. In many cases, these vulnerabilities go unnoticed and remain unresolved in codebases. Thus, awareness of software vulnerabilities among the public is crucial to ensure effective cybersecurity practices, the development of high quality software, and ultimately national security. This awareness can be better understood by studying the spread and evolution of software vulnerability discussions in online communities. This work is the first to evaluate and contrast how discussions about software vulnerabilities spread on three social platforms -- Twitter, GitHub, and Reddit. To lay the groundwork, we showcase a novel fundamental framework for measuring information spread that identifies the spread mechanisms and observables across platforms, the units of information, and the groups of measurements that can be applied to focus on a specific phenomena e.g., information cascades. We then analyze and contrast social network topologies for three example social networks and measure the scale and speed of the spread of discussion of specific vulnerabilities to understand how far and how widely they spread, how many users participate in discussions, and the duration of their spread. To demonstrate the awareness of more impactful software vulnerabilities, a subset of our analysis focuses on vulnerabilities targeted during recent major cyber attacks as well as vulnerabilities exploited by advanced persistent threat groups. We discover that usually, vulnerability discussions start on GitHub, before occurring on Twitter and Reddit. While studying how some user-level and content-level characteristics influence vulnerability spread, we observe that Twitter discussions started by users predicted to be humans have larger size, breadth, depth, adoption rate, lifetime, and structural virality compared to those started by users predicted to be bots. On Reddit, we contrast the differences in thread structure that originate from posts with positive, negative and neutral polarity. We find that posts that are positive have larger, deeper and wider discussions compared to negative and neutral posts. We anticipate the results of our analysis to not only increase the understanding of software vulnerability awareness but also inform models for simulating information spread across multiple social environments online.
Protocyanobacteria: Oxygenic and Anoxygenic photosynthesis in mat-forming bacteria
The oldest record of life is preserved in prePhanerozoic stromatolites dated 3500 million years old and is most likely of filamentous mat-forming cyanobacteria. The sedimentary records of cyanobacterial mats in stromatolites are the most abundant record of life throughout the prePhanerozoic. Stromatolites persisted into the Phanerozoic Eon, yet they become much less pronounced relative to earlier ones. The abundance and persistence of cyanobacterial mats throughout most of geological time point to the evolutionary success of these kinds of microbial communities and their possible role in the evolution of the earth and atmosphere.