Desiccated Cyanobacteria Serve As Efficient Plasmid DNA Carriers in Space Flight
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Abstract On‐orbit close proximity operations involve robotic spacecraft maneuvering and making decisions for a growing number of mission scenarios demanding autonomy, including on‐orbit assembly, repair, and astronaut assistance. Of these scenarios, on‐orbit assembly is an enabling technology that will allow large space structures to be built in situ, using smaller building block modules. However, like many of these scenarios, robotic on‐orbit assembly involves several technical hurdles, such as changing system models. For instance, grappled modules moved by a free‐flying “assembler” robot can cause significant changes in the combined system inertia, which have cascading impacts on motion planning and control portions of the autonomy stack. Further, on‐orbit assembly and other scenarios require collision‐avoiding motion planning, particularly when operating in a “construction site” scenario of multiple assembler robots and structures. Multiple key technologies that address these complicating factors for autonomous microgravity close proximity operations are detailed in this work, in particular: (1) application of global long‐horizon planning, accomplished using offline and online sampling‐based planner options that consider the system dynamics; (2) adaptation of the recently proposed RATTLE information‐aware planning framework for on‐orbit reconfiguration model learning; and (3) connection with robust control tools to provide low‐level control robustness using current system knowledge. These approaches were demonstrated for an autonomous on‐orbit assembly use case by the RElative Satellite sWarming and Robotic Maneuvering (ReSWARM) experiments using NASA's Astrobee robots on the International Space Station. Results of the ReSWARM experiments are provided along with significant operational and implementation detail discussing the practicalities of hardware implementation and unique aspects of working with the Astrobee free‐flyer robots in microgravity. ReSWARM provides a base set of planning and control tools for robotic close proximity operations, demonstrates them in microgravity, and outlines some of the important hardware aspects that future autonomous free‐flyers will need to consider.
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This paper provides a derivation of a direct-sampling approach for modeling continuously varying cross sections in tetrahedral-mesh-based Monte Carlo codes. Specifically, cross sections are spatially approximated using linear nodal finite elements. A linearization strategy is provided for non-linearly varying cross sections. The method is verified against seven analytical pure-absorber test problems. These test problems also highlight the benefit of using linear finite elements over element-wise-constant cross sections.
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A search for new neutron-rich isotopes beyond $Z=28$ and $N=50$ was performed using a 345 MeV/nucleon $^{238}$U beam at RI Beam Factory in RIKEN Nishina Center. The BigRIPS separator and state-of-the-art radiation detectors were used to efficiently separate and identify the produced nuclei. For the first time, we have observed and determined the production cross sections for eight neutron-rich isotopes $^{72}$Cr, $^{74,75}$Mn, $^{77}$Fe, $^{79,80}$Co, $^{85}$Cu, and $^{90}$Ga. This study broadens our understanding of nuclear existence and paves the way for investigating the properties of neutron-rich medium-mass nuclei.
Neutron diffraction beamlines have traditionally relied on deploying large detector arrays of 3 He tubes or neutron-sensitive scintillators coupled with photomultipliers to efficiently probe crystallographic and microstructure information of a given material. Given the large upfront cost of custom-made data acquisition systems and the recent scarcity of 3 He, new diffraction beamlines or upgrades to existing ones demand innovative approaches. This paper introduces a novel Timepix3-based event-mode imaging neutron diffraction detector system as well as first results of a silicon powder diffraction measurement made at the HIPPO neutron powder diffractometer at the Los Alamos Neutron Science Center. Notably, these initial measurements were conducted simultaneously with the 3 He array on HIPPO, enabling direct comparison. Data reduction for this type of data was implemented in the MAUD code, enabling Rietveld analysis. Results from the Timepix3-based setup and HIPPO were benchmarked against McStas simulations, showing good agreement for peak resolution. With further development, systems such as the one presented here may substantially reduce the cost of detector systems for new neutron instrumentation as well as for upgrades of existing beamlines.
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The dataset contains Normalized Difference Vegetation Index (NDVI) and multispectral images collected on June 18, 2022 using an UAS (Unmanned Aerial System) Yuneec H520, Mapir Survey 3, and Parrot Sequoia cameras. This data was created to accompany the following datasets:- NGEE Arctic CO2, CH4 and Energy Eddy-Covariance (EC) Flux Tower Auxiliary Measurements, Council Road Mile Marker 71, Seward Peninsula, Alaska (https://doi.org/10.5440/1526749)- Sun-induced chlorophyll fluorescence/eddy covariance measurements at NGEE Arctic Council site, Seward Peninsula, Alaska, 2022 (https://doi.org/10.15485/2466175)- NGEE Arctic Meteorological Data from Instrumented PCDC Stations, Council Site, Seward Peninsula, Alaska, 2018 - 2023 (https://doi.org/10.5440/1529604)Survey 3 is RGN (Red, Greeen, Near Infra Red) camera with 87° Horizontal Field of View (HFOV) (19mm) f/2.8 Aperture, 550nm/660nm/850nm (Red+Green+NIR) filter transmission and produced geo referenced jpg and raw format images. Parrot Sequoia is a camera with 16 megapixel RGB (Red, Green, Blue) sensor and 1.2 megapixel monochrome sensors in discrete spectral bands: Green (550nm - 40Nm Bandwidth), Red (660nm - 40nm Bandwidth), Red Edge (735nm - 10nm Bandwidth) and Near Infrared (790nm - 40nm Bandwidth).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
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Presentation slides
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This is a poster that we will present at HTSC. All the content is from our Scitech paper: https://doi.org/10.2514/6.2024-1293
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