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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15

PcapDB: Search Optimized Packet Capture, Version 0.1.0.0

PcapDB is a packet capture system designed to optimize the captured data for fast search in the typical (network incident response) use case. The technology involved in this software has been submitted via the IDEAS system and has been filed as a provisional patent. It includes the following primary components: capture: The capture component utilizes existing capture libraries to retrieve packets from network interfaces. Once retrieved the packets are passed to additional threads for sorting into flows and indexing. The sorted flows and indexes are passed to other threads so that they can be written to disk. These components are written in the C programming language. search: The search components provide a means to find relevant flows and the associated packets. A search query is parsed and represented as a search tree. Various search commands, written in C, are then used resolve this tree into a set of search results. The tree generation and search execution management components are written in python. interface: The PcapDB web interface is written in Python on the Django framework. It provides a series of pages, API's, and asynchronous tasks that allow the user to manage the capture system, perform searches, and retrieve results. Web page components are written in HTML,CSS and Javascript.

Ferrell, Paul↗

Pretty Linter GrumPhP

This software takes JSON and YAML files, and after running them through a linter, sorts the keys of objects alphabetically. This helps prevent the following problems when checking these data/config files into repositories: Problems where the entire file looks like it was removed and added due to Indentation changes Key sorting differences Merging issues when 2 or more people add data to the same or similar locations

Williams, Thom↗

Cell Population–resolved Multiomics Atlas of the Developing Lung

The lung is a vital organ that undergoes extensive morphological and functional changes during postnatal development. To disambiguate how different cell populations contribute to organ development, we performed proteomic and transcriptomic analyses of four sorted cell populations from the lung of human subjects aged 0 to 8 years-old with a focus on early life. The cell populations analyzed included epithelial, endothelial, mesenchymal, and immune cells. Our results revealed distinct molecular signatures for each of the sorted cell populations that enable the description of molecular shifts occurring in these populations during post-natal development. Here, we confirmed that the proteome of the different cell populations was distinct regardless of age and identified functions specific to each population. We identified a series of cell population protein markers, including those located at the cell surface, that show differential expression and distribution on RNA in situ hybridization and immunofluorescence imaging. We validated the spatial distribution of AT1 and endothelial cell surface markers. Temporal analyses of the proteome of each of the four populations revealed processes modulated during postnatal development and disambiguating results obtained on whole tissue proteome. Finally, the proteome was compared to a transcriptomics survey performed on the same lung samples to evaluate processes under post-transcriptional control.

59 BASIC BIOLOGICAL SCIENCES↗

A Triple-Moment Representation of Ice in the Predicted Particle Properties (P3) Microphysics Scheme

In the original Predicted Particle Properties (P3) bulk microphysics scheme, all ice-phase hydrometeors are represented by one or more “free” ice categories, where the physical properties evolve smoothly through changes to the four prognostic variables (per category), and with a two-moment representation of the particle size distribution. As such, the spectral dispersion cannot evolve independently, which thus results in limitations in representation of ice—in particular, hail—due to necessary constraints in the scheme to prevent excessive gravitational size sorting. To overcome this, P3 has been modified to include a three-moment representation of the size distribution of each ice category through the addition of a fifth prognostic variable, the sixth moment of the size distribution. The details of the three-moment ice parameterization in P3 are provided. The behavior of the modified scheme, with the single-ice-category configuration, is illustrated through simulations in a simple 1D kinematic model framework as well as with near large-eddy-resolving (250-m grid spacing) 3D simulations of a hail-producing supercell. It is shown that the three-moment ice configuration controls size sorting in a physically based way and leads to an improved capacity to simulate large, heavily rimed ice (hail), including mean and maximum sizes and reflectivity, and thus an overall improvement in the representation of ice-phase particles in the P3 scheme.

54 ENVIRONMENTAL SCIENCES↗

Study of Microphysical Signatures Based on Spectral Polarimetry during the RELAMPAGO Field Experiment in Argentina

Weather radars with dual-polarization capabilities enable the study of various characteristics of hydrometeors, including their size, shape, and orientation. Radar polarimetric measurements, coupled with Doppler information, allow for analysis in the spectral domain. This analysis can be leveraged to reveal valuable insight into the microphysics and kinematics of hydrometeors in precipitation systems. This paper uses spectral polarimetry to investigate precipitation microphysics and kinematics in storm environments observed during the Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) field experiment in Argentina. This study uses range–height indicator scan measurements from a C-band polarimetric Doppler weather radar deployed during the field campaign. Here, in this work, the impact of storm dynamics on hydrometeors is studied, including the size sorting of hydrometeors due to vertical wind shear. In addition, particle microphysical processes because of aggregation and growth of ice crystals in anvil clouds, as well as graupel formation resulting from the riming of ice crystals and dendrites, are also analyzed here. The presence of different particle size distributions because of the mixing of hydrometeors in a sheared environment and resulting size sorting has been reported using spectral differential reflectivity (sZ dr ) slope. Spectral reflectivity sZ h and sZ dr have also been used to understand the signature of ice crystal aggregation in an anvil cloud. The regions of pristine ice crystals are identified from vertical profiles of spectral polarimetric variables in anvil cloud because of sZ h < 0 dB and sZ dr values around 2 dB. It is also found that the growth process of these ice crystals causes a skewed bimodal sZ h spectrum due to the presence of both pristine ice crystals and dry snow. Next, graupel formation due to riming has been studied, and it is found that the riming process produces sZ h values of about 10 dB and corresponding sZ dr values of 1 dB. This positive sZ dr indicates the presence of needle/columnar secondary ice particles formed by ice multiplication processes in the riming zones. Last, the temporal evolution of a storm is investigated by analyzing changes in hydrometeor types with time and their influence on the spectral polarimetric variables.

54 ENVIRONMENTAL SCIENCES↗

Polarimetric Signatures in Landfalling Tropical Cyclones

Polarimetric radar observations from the NEXRAD WSR-88D operational radar network in the contiguous United States, routinely available since 2013, are used to reveal three prominent microphysical signatures in landfalling tropical cyclones: 1) hydrometeor size sorting within the eyewall convection, 2) vertical displacement of the melting layer within the inner core, and 3) dendritic growth layers within stratiform regions of the inner core. Size sorting signatures within eyewall convection are observed with greater frequency and prominence in more intense hurricanes, and are observed predominantly within the deep-layer environmental wind shear vector-relative quadrants that harbor the greatest frequency of deep convection (i.e., downshear and left-of-shear). Melting-layer displacements are shown that exceed 1 km in altitude compared to melting-layer altitudes in outer rainbands and are complemented by analyses of archived dropsonde data. Dendritic growth and attendant snow aggregation signatures in the inner core are found to occur more often when echo-top altitudes are low (≤10 km MSL), nearer the -15°C isotherm commonly associated with dendritic growth. These signatures, uniquely observed by polarimetric radar, provide greater insight into the physical structure and thermodynamic characteristics of tropical cyclones, which are important for improving rainfall estimation and the representation of tropical cyclones in numerical models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Severe Convective Storms in Limited Instability Organized by Pattern and Distribution

Abstract Severe convection occurring in high-shear, low-CAPE (HSLC) environments is a common cool-season threat in the southeastern United States. Previous studies of HSLC convection document the increased operational challenges that these environments present compared to their high-CAPE counterparts, corresponding to higher false-alarm ratios and lower probability of detection for severe watches and warnings. These environments can exhibit rapid destabilization in the hours prior to convection, sometimes associated with the release of potential instability. Here, we use self-organizing maps (SOMs) to objectively identify environmental patterns accompanying HSLC cool-season severe events and associate them with variations in severe weather frequency and distribution. Large-scale patterns exhibit modest variation within the HSLC subclass, featuring strong surface cyclones accompanied by vigorous upper-tropospheric troughs and northward-extending regions of instability, consistent with prior studies. In most patterns, severe weather occurs immediately ahead of a cold front. Other convective ingredients, such as lower-tropospheric vertical wind shear, near-surface equivalent potential temperature (θ e ) advection, and the release of potential instability, varied more significantly across patterns. No single variable used to train SOMs consistently demonstrated differences in the distribution of severe weather occurrence across patterns. Comparison of SOMs based on upper and lower quartiles of severe occurrence demonstrated that the release of potential instability was most consistently associated with higher-impact events in comparison to other convective ingredients. Overall, we find that previously developed HSLC composite parameters reasonably identify high-impact HSLC events. Significance Statement Even when atmospheric instability is not optimal for severe convective storms, in some situations they can still occur, presenting increased challenges to forecasters. These marginal environments may occur at night or during the cool season, when people are less attuned to severe weather threats. Here, we use a sorting algorithm to classify different weather patterns accompanying such storms, and we distinguish which specific patterns and weather system features are most strongly associated with severe storms. Our goals are to increase situational awareness for forecasters and to improve understanding of the processes leading to severe convection in marginal environments.

Meteorology & Atmospheric Sciences↗

SOC Synthetic Microstructure Bank

QUICK START: Start with property_library.html (can be found by typing the filename into the query box) and use the interactive table to filter, sort, and select a microstructure with the desired properties. Search for the alphabetic code to obtain the corresponding dataset. Full description: This is a bank of 1,970 unique 3-phase electrode microstructure files. When you account for reassigning phase IDs (e.g. declare that 1=Ni and 2=pore, instead of 1=pore and 2=Ni), it actually represents 5,910 unique electrode microstructures, each of which could be considered to be either an air or a fuel electrode (e.g. declare that the phase IDs correspond to pore, Ni, and YSZ; or that they correspond to pore, LSCF, and GDC; or whatever electron-conductor and ion-conductor combination is being studied). The voxel size is 50 nm and each electrode file contains a 4x4 grid of (12.5 micron)^3 sub-volumes. If placed together in a grid, they comprise a 50x50x12.5 micron electrode (note that the interfaces between sub-volumes will be sharp; this can be mitigated via simulating annealing/relaxation). The sub-volumes can also be used individually for a reasonably sized 12.5 micron cubic region-of-interest. A user can simply consider the voxel size to be a different value to rescale the volumes (and all of their morphological features, including particle size) as desired. These microstructures were generated using DREAM3D. The general procedure is outlined in https://doi.org/10.1016/j.jpowsour.2018.03.025 The file names are an alphabetic code having to do with the input parameters used in DREAM3D when they were generated. Most users would be best served by starting with the file property_library.html or property_library_subvols.html (which lists properties for each individual subvolume). These files contain a catalogue of the actual, measured properties of every microstructure in the database. Any combination of property values can be filtered and sorted until a desired electrode is found, at which point the user can find the file corresponding to that alphabetic code. The properties in the catalogue include connected TPB density, and for each phase: phase fraction, average particle size, polydispersity of particle size, tortuosity, and connected pair-wise interfacial area. They also include what fraction of each property is connected through to the interfaces of the volume. If the desired combination of properties is not found at first, remember that the phase IDs can be re-assigned arbitrarily, e.g. swapping 1s and 2s. In fact, the database was generated with this in mind so as not to generate redundant microstructures. If the database does not contain the desired property combinations, try to search for the other possible permutations of those properties with re-assigned phase IDs. Please cite https://doi.org/10.1149/10301.0909ecst for use. Please contact the maintainer, William K. Epting, for additional information or assistance.

3D microstructure↗

Unravel lipid accumulation mechanism in oleaginous yeast through single cell systems biology study

Searching for alternative and clean energy is one of the most important tasks today. Our research aimed at finding the best living condition for certain types of oleaginous yeasts for efficient lipid production. We found that R. glutinis yeast cells has great variability in lipid production among cells while Y. lipolytica cells has similar oil production ability. We found some individual cells shows much higher level of oil production. In order to further study these cases, we employed a label-free chemical sensitive microscopy method call stimulated Raman scattering (SRS). With SRS, we could measure the lipid content in each cell. We combined SRS microscopy with microfluidic device so that we can isolate cells with high fat content. We also developed SRS imaging technique that has higher imaging speed, which is highly desirable for high throughput cell screening and sorting. Since these cells has similar genome, it must be the transcriptome caused their difference in oil production. We developed a single cell transcriptome sequencing method to study which genes are responsible for elevated oil production. These methods that are developed for this project can easily be applied for many other areas of research. For example, the single transcriptome can be used to study the transcriptomes of other cell types. The high-speed SRS microscopy techniques can be used to speed up chemical imaging for lablefree histology or imaging distribution of chemicals in tissues of live mice or in humans. The developed microfluidic platform can be used to sort other type of cells, e.g., white blood cells for diagnosis of cancer or other blood diseases.

09 BIOMASS FUELS↗

Optimization of Diode Laser System to Treat Benign Prostate Hyperplasia Final Report CRADA No. TSB-1154-95

Benign prostate hyperplasia (BPH) is a pervasive condition of enlargement of the male prostate gland which leads to several urinary difficulties ranging from hesitancy to incontinence to kidney dysfunction in severe cases. Currently the most common therapy is transurethral resection of the prostate (TURP) utilizing an electrosurgical device. Although TURP is largely successful, new BPH therapy methods are desired to reduce the cost and recovery time, improve the success rate, and reduce side effects. Recently, lasers have been introduced for this purpose. Indigo Medical Inc. is currently engaged in the development, testing, and preparation for sales of a new diode laser based BPH therapy system. The development is based on laboratory experiments, animal studies, and a limited FDA-approved clinical trial in the US and in other countries. The addition of sophisticated numerical modeling, of the sort that has been highly developed at Lawrence Livermore National Laboratory, can greatly aid in the design of the system and treatment protocol. The benefits to DOE include the maintenance and advancement of numerical modeling expertise in radiation-matter interactions of the sort essential for the stockpile stewardship, inertial confinement fusion, and advanced manufacturing, and the push on advanced scientific computational methods, ultimately in areas such as 3-D transport.

42 ENGINEERING↗

Entity Resolution at Large Scale: Benchmarking and Algorithmics

We seek scalable benchmarks for entity resolution problems. Solutions to these problems range from trivial approaches such as string sorting to sophisticated methods such as statistical relational learning. The theoretical and practical complexity of these approaches varies widely, so one of the primary purposes of a benchmark will be to quantify the trade-off between solution quality and runtime. We are motivated by the ubiquitous nature of entity resolution as a fundamental problem faced by any organization that ingests large amounts of noisy text data. A benchmark is typically a rigid specification that provides an objective measure usable for ranking implementations of an algorithm. For example the Top500 and HPCG500 bench- marks rank supercomputers based on their performance of dense and sparse linear algebra problems (respectively). These two benchmarks require participants to report FLOPS counts attainable on various machines. Our purpose is slightly different. Whereas the supercomputing benchmarks mentioned above hold algorithms constant and aim to rank machines, we are primarily interested in ranking algorithms. As mentioned above, entity resolution problems can be approached in completely different ways. We believe that users of our benchmarks must decide what sort of procedure to run before comparing implementations and architectures. Eventually, we also wish to provide a mechanism for ranking machines while holding algorithmic approach constant . Our primary contributions are parallel algorithms for computing solution quality mea- sures per entity. We find in some real datasets that many entities are quite easy to resolve while others are difficult, with a heavy skew toward the former case. Therefore, measures such as global confusion matrices, F measures, etc. do not meet our benchmarking needs. We design methods for computing solution quality at the granularity of a single entity in order to know when proposed solutions do well in difficult situations (perhaps justifying extra computational), or struggling in easy situations. We report on progress toward a viable benchmark for comparing entity resolution algo- rithms. Our work is incomplete, but we have designed and prototyped several algorithms to help evalute the solution quality of competing approaches to these problems. We envision a benchmark in which the objective measure is a ratio of solution quality to runtime.

97 MATHEMATICS AND COMPUTING↗

Life Cycle Analysis and Life Cycle Costing for Municipal Solid Waste (MSW) Management and Materials Redeployment to Support ARPA-E’s Potential Program on Waste to Energy and Materials

Municipal solid waste infrastructure in the United States contains complex supply chains to transport, sort, and sequester waste. This project developed models to estimate the environmental and economic costs of waste infrastructure in the U.S. using data from several municipalities. Life cycle costing (LCC) models were developed for waste management relevant supply chain steps, including waste collection, sorting, landfilling, waste-to-energy, ash processing, and recycling. A waste-to-materials and energy (WTM&E) life cycle analysis (LCA) and LCC dashboard was developed in collaboration with Argonne National Laboratory (ANL) and an LCC tool was developed for additional analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

CrossLink: Geometry API [Slides]

The mesh generation process is very challenging and time consuming when working with complex CAD models. The process of creating and sorting geometric entities into groups appropriate for meshing is labor intensive and prone to error. In addition, the common data exchange formats such as STEP and IGES do not propagate information such as entity names that may be defined in the original model. Finally, entity counts change frequently with parameter variation as a result of tolerance-based geometry operations. Thus, sorting by index does not provide a robust and repeatable means for grouping. xGeom is a geometry library that enables the creation of NURBS curves and surfaces via a python scripting interface. xGeom is ideal for studying relatively simple models and is fully integrated with CrossLink’s mesh generation capabilities. For more complex models, xCAD is a python-based Creo Parametric CAD model driver that enables the model to be generated, queried, parametrically modified, regenerated, and exported without data loss and in a fully repeatable manner.

97 MATHEMATICS AND COMPUTING↗

Multiplexed Probing for Functional Capacity Measurements in Complex and Limited-Size Samples

A new strategy using glass as a solid support for functionalization with chemical probes has been recently developed with successful results. The next step in glass functionalization is to pair chemical probes with fluorescent glass microspheres. This approach gives us a way to directly quantify probe-bound protein using Fluorescence-Activated Cell Sorting (FACS). FACS has already shown to be amendable to glass microspheres, demonstrating changes in probe-bound protein concentration. Suitable probing conditions for gram-positive and negative microbes, complex microbial communities from myriad ecosystems, and eukaryotic cells/tissues have traditionally suffered from set-backs, such as limited protein per sample and conditions atypical for probing. To remedy this, we propose to: (1) Demonstrate probe functionalization specific to glass microspheres by paired fluorophore and use those activity probes successfully with proteomics. Probes that are currently available (CYP5, GSH/GST, Glycoside Hydrolase) can be easily prepared onto glass surfaces. Probe-bound microspheres can be tested in ratios, first with known amounts of purified protein and then complex microbiome lysates. (2) Our validated microspheres are then used to determine quantitative amounts of protein through FACS sorting. Complimenting these results by proteomics, prepared microspheres are then optimized and condensed into a user-friendly kit. Once successfully commercialized, this multiplexed assay can be used with little to no technical expertise, making this available to various industries users.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of Genetic Algorithm Based Multi-Objective Plant Reload Optimization Platform

The U.S. nuclear industry is facing a challenge in maintaining required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects of light-water reactor nuclear power plant operations. Safety can become more economical by using a risk-informed ecosystem, such as the one being developed in the Risk-Informed Systems Analysis Pathway under the U.S. Department of Energy Light Water Reactor Sustainability Program. The Light Water Reactor Sustainability Program promotes a wide range of research and development activities to maximize both the safety and economic efficiency of nuclear power plants through improved scientific understanding, especially given that many plants are now considering second license renewals. The Risk-Informed Systems Analysis Pathway has two main goals: Deploy methodologies and technologies that better represent safety margins and cost and safety factors; Develop advanced applications that enable cost-effective plant operations. The Plant Reload Optimization Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. This report summarizes genetic-algorithm-based multi-objective fuel reload optimization activities, specifically: Developing the non-dominated sorting genetic algorithm II optimizer in the Risk Analysis and Virtual ENviroment (RAVEN); Demonstrating and validating the developed non-dominated sorting genetic algorithm II optimizer using benchmark optimization problems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Highly Efficient Vacuum Smelting of Aluminum

The goal of this SBIR project was to develop and demonstrate an innovative aluminum smelting technology that will significantly increase the range of aluminum alloys that can be manufactured from recycling of scrap aluminum. This will result in reduction of need for primary aluminum with corresponding 95% energy and CO 2 emission benefits. The proposed melting of pre-sorted aluminum alloys using UHV’s patented high throughput sorter funded by ARPA-E METALS program in an energy efficient vacuum furnace avoids the typical 5% metal loss due to oxidation of molten metal. In addition, pre-sorting scrap into different categories (cast, wrought, extrusion and aerospace) allows lower cost production of high value aluminum alloys without the need for adding alloying elements to primary aluminum. During this SBIR project, pure aluminum and several different commercial alloys were procured and melted in a laboratory furnace in vacuum, CH4 and air environments. The slag and oxidation formation were measured using weight and cross-sectional scanning electron microscope. The results otained were mixed and did not show direct correlation between furnace pressure and oxidation. We believe that the results were tainted due to small furnace size and non-uniformity of oxidation layer. A more thorough investigation is required to prove the advantages of vacuum smelting which could not be performed due to the COVID-19 lockdowns during this project. The theoretical fact remains that in the absence of oxygen in the furnace, there should be no oxide after melting, however the team could not prove it experimentally, and thus decided to dis-continue the project.

36 MATERIALS SCIENCE↗

Single-nuclei transcriptome analysis of IgM+ cells isolated from channel catfish (Ictalurus punctatus) spleen

Catfish production is the primary aquaculture sector in the United States, and the key cultured species is channel catfish (Ictalurus punctatus). The major causes of production losses are pathogenic diseases, and the spleen, an important site of adaptive immunity, is implicated in these diseases. To examine the channel catfish immune system, single-nuclei transcriptomes of sorted and captured IgM + cells were produced from adult channel catfish. Three channel catfish (~1 kg) were euthanized, the spleen dissected, and the tissue dissociated. The lymphocytes were isolated using a Ficoll gradient and IgM + cells were then sorted with flow cytometry. The IgM + cells were lysed and single-nuclei libraries generated using a Chromium Next GEM Single Cell 3’ GEM Kit and the Chromium X Instrument (10x Genomics) and sequenced with the Illumina NovaSeq X Plus sequencer. The reads were aligned to theI. punctatusreference assembly (Coco_2.0) using Cell Ranger, and normalization, cluster analysis, and differential gene expression analysis were carried out with Seurat. Across the three samples, approximately 753.5 million reads were generated for 18,686 cells. After filtering, 10,637 cells remained for the cluster analysis. The cluster analysis identified 16 clusters which were classified as B cells (10,276), natural killer-like (NK-like) cells (178), T cells or natural killer cells (45), hematopoietic stem and progenitor cells (HSPC)/megakaryocytes (MK) (66), myeloid/epithelial cells (40), and plasma cells (32). The B cell clusters were further defined as different populations of mature B cells, cycling B cells, and plasma cells. The plasma cells highly expressedighmand we demonstrated that the secreted form of the transcript was largely being expressed by these cells. This atlas provides insight into the gene expression of IgM + immune cells in channel catfish. The atlas is publicly available and could be used garner more important information regarding the gene expression of splenic immune cells.

Immunology↗

BONCAT-FACS-Seq reveals the active fraction of a biocrust community undergoing a wet-up event

Determining which microorganisms are active within soil communities remains a major technical endeavor in microbial ecology research. One promising method to accomplish this is coupling bioorthogonal non-canonical amino acid tagging (BONCAT) with fluorescence activated cell sorting (FACS) which sorts cells based on whether or not they are producing new proteins. Combined with shotgun metagenomic sequencing (Seq), we apply this method to profile the diversity and potential functional capabilities of both active and inactive microorganisms in a biocrust community after being resuscitated by a simulated rain event. We find that BONCAT-FACS-Seq is capable of discerning the pools of active and inactive microorganisms, especially within hours of applying the BONCAT probe. The active and inactive components of the biocrust community differed in species richness and composition at both 4 and 21 h after the wetting event. The active fraction of the biocrust community is marked by taxa commonly observed in other biocrust communities, many of which play important roles in species interactions and nutrient transformations. Among these, 11 families within the Firmicutes are enriched in the active fraction, supporting previous reports indicating that the Firmicutes are key early responders to biocrust wetting. We highlight the apparent inactivity of many Actinobacteria and Proteobacteria through 21 h after wetting, and note that members of the Chitinophagaceae, enriched in the active fraction, may play important ecological roles following wetting. Based on the enrichment of COGs in the active fraction, predation by phage and other bacterial members, as well as scavenging and recycling of labile nutrients, appear to be important ecological processes soon after wetting. To our knowledge, this is the first time BONCAT-FACS-Seq has been applied to biocrust samples, and therefore we discuss the potential advantages and shortcomings of coupling metagenomics to BONCAT to intact soil communities such as biocrust. In all, by pairing BONCAT-FACS and metagenomics, we are capable of highlighting the taxa and potential functions that typifies the microbes actively responding to a rain event.

59 BASIC BIOLOGICAL SCIENCES↗