This submission includes fact and logical data models for geothermal data concerning wells, fields, power plants and related analyses at Raft River, ID. The fact model is available in VizioModeler (native), html, UML, ORM-Specific, pdf, and as an XML Spy Project. An entity-relationship diagram is also included. Models are derived from tables, figures and other content in the following reports from the Raft River Geothermal Project: "Technical Report on the Raft River Geothermal Resource, Cassia County, Idaho," GeothermEx, Inc., August 2002. "Results from the Short-Term Well Testing Program at the Raft River Geothermal Field, Cassia County, Idaho," GeothermEx, Inc., October 2004.

This raster file represents land within the Raft River Study Area classified as either “irrigated” with a cell value of 1 or “non-irrigated” with a cell value of 0 at a 30-meter spatial resolution. These classifications were determined at the pixel level by a Random Forest supervised machine learning methodology. Random Forest models are often used to classify large datasets accurately and efficiently by assigning each pixel to one of a pre-determined set of labels or groups. The model works by using decision trees that split the data based on characteristics that make the resulting groups as different from each other as possible. The model “learns” the characteristics that correlate to each label based on manually classified data points, also known as training data.A variety of data can be supplied as input to the Random Forest model for it to use in making its classification determinations. Irrigation produces distinct signals in observational data that can be identified by machine learning algorithms. Additionally, datasets that provide the model with information on landscape characteristics that often influence whether irrigation is present are also useful. This dataset was classified by the Random Forest model using Level 2 (surface reflectance), Collection 2, Tier 1 data from Landsat 5 and Landsat 7, Mapping Evapotranspiration with Internalized Calibration (METRIC) data produced by IDWR, United States Geological Survey National Elevation Dataset (USGS NED) data, and Height Above Nearest Drainage (HAND) data. Landsat 5, Landsat 7, and HAND data are at a 30-meter spatial resolution, and the USGS NED data are at a 10-meter spatial resolution. The National Land Cover Dataset (NLCD) from the USGS, National Agriculture Imagery Program (NAIP) data from the USDA Farm Service Agency (FSA), Utah Water Related Land Use data from the Utah Division of Water Resources, Mapping Evapotranspiration with Internalized Calibration (METRIC) data (where available), and water rights data from IDWR were also used in determining irrigation status for the manually classified training data points but were not used for the machine learning model predictions. The final model results were manually reviewed prior to release, however, no extensive ground truthing process was implemented. “Speckling”, or small areas of incorrectly classified pixels, was reduced by masking all pixels with a slope value of 10% or greater as “non-irrigated”, regardless of the status they were assigned by the Random Forest model. Speckling within irrigated areas was reduced by a boundary clean smoothing technique.

This raster file represents land within the Raft River Study Area classified as either “irrigated” with a cell value of 1 or “non-irrigated” with a cell value of 0 at a 30-meter spatial resolution. These classifications were determined at the pixel level by a Random Forest supervised machine learning methodology. Random Forest models are often used to classify large datasets accurately and efficiently by assigning each pixel to one of a pre-determined set of labels or groups. The model works by using decision trees that split the data based on characteristics that make the resulting groups as different from each other as possible. The model “learns” the characteristics that correlate to each label based on manually classified data points, also known as training data. A variety of data can be supplied as input to the Random Forest model for it to use in making its classification determinations. Irrigation produces distinct signals in observational data that can be identified by machine learning algorithms. Additionally, datasets that provide the model with information on landscape characteristics that often influence whether irrigation is present are also useful. This dataset was classified by the Random Forest model using Level 2 (surface reflectance), Collection 2, Tier 1 data from Landsat 7 and Landsat 8, Mapping Evapotranspiration with Internalized Calibration (METRIC) data produced by IDWR, United States Geological Survey National Elevation Dataset (USGS NED) data, and Height Above Nearest Drainage (HAND) data. Landsat 7, Landsat 8, METRIC, and HAND data are at a 30-meter spatial resolution, and the USGS NED data are at a 10-meter spatial resolution. The Cropland Data Layer (CDL) from the United States Department of Agriculture (UDSA) National Agricultural Statistics Service (NASS), National Agriculture Imagery Program (NAIP) data from the USDA Farm Service Agency (FSA), Utah Water Related Land Use data from the Utah Division of Water Resources, and water rights data from IDWR were also used in determining irrigation status for the manually classified training data points but were not used for the machine learning model predictions. The final model results were manually reviewed prior to release, however, no extensive ground truthing process was implemented. “Speckling”, or small areas of incorrectly classified pixels, was reduced by masking all pixels with a slope value of 10% or greater as “non-irrigated”, regardless of the status they were assigned by the Random Forest model. Speckling within irrigated areas was reduced by a majority filter smoothing technique using a kernel of 8 nearest neighbors. A limited amount of manual corrections were also made to the final results.

vicaloy/llama2-chat-raft-software-life-cycle-models dataset hosted on Hugging Face and contributed by the HF Datasets community

Lipid rafts are highly ordered regions of the plasma membrane enriched in signaling proteins and lipids. Their biological potential is realized in exosomes, a subclass of extracellular vesicles (EVs) that originate from the lipid raft domains. Previous studies have shown that EVs derived from human placental mesenchymal stromal cells (PMSCs) possess strong neuroprotective and angiogenic properties. However, clinical translation of EVs is challenged by very low, impure, and heterogeneous yields. Therefore, in this study, lipid rafts are validated as a functional biomaterial that can recapitulate the exosomal membrane and then be synthesized into biomimetic nanovesicles. Lipidomic and proteomic analyses show that lipid raft isolates retain functional lipids and proteins comparable to PMSC-EV membranes. PMSC-derived lipid raft nanovesicles (LRNVs) are then synthesized at high yields using a facile, extrusion-based methodology. Evaluation of biological properties reveals that LRNVs can promote neurogenesis and angiogenesis through modulation of lipid raft-dependent signaling pathways. A proof-of-concept methodology further shows that LRNVs could be loaded with proteins or other bioactive cargo for greater disease-specific functionalities, thus presenting a novel type of biomimetic nanovesicles that can be leveraged as targeted therapeutics for regenerative medicine.

Raw magnetotelluric (MT) data covering the geothermal system at Raft River, Idaho. The data was acquired by Quantec Geoscience. This is a zipped file containing .edi raw MT data files.

Self-assemblies containing the nucleobase analogue 2,6-diacylaminopyridine (DAP) have been successfully prepared for the first time by aqueous seeded RAFT polymerization in high concentrations. For this purpose, a diblock copolymer containing poly(ethylene glycol) (PEG) and DAP polymethacrylate blocks was used as a macro-chain-transfer agent (PEG124-b-PDAP9-CTA) for the polymerization of 2-hydroxypropyl methacrylate (HPMA) in water. From the systematic variation of the degree of polymerization and solid concentration, a phase diagram has been generated that correlates both variables with the morphologies of this new system. Self-assemblies have been characterized by TEM and DLS, observing morphologies from low to high order (from spherical micelles to worms and to vesicles). Self-assembly morphologies are stable for almost a year, except in the case of worms that turn into spherical micelles after a few weeks. In addition, H-bonding supramolecular functionalization of the DAP repeating units during aqueous seeded RAFT polymerization has been examined by functionalization with a cross-linker with four thymine groups. Finally, the loading and the subsequent release of Nile Red have been proven in both supramolecular cross-linked and non-cross-linked self-assemblies.

This dataset contains maps of deformation covering Raft River, Idaho from 2007 to 2010 calculated from interferometric synthetic aperture radar data. This dataset is used in the study entitled "Inferring geothermal reservoir processes at the Raft River Geothermal Field, Idaho, USA through modeling InSAR-measured surface deformation" by F. Liu, et al. This dataset was derived from raw SAR data from the Envisat satellite missions operated by the European Space Agency (ESA) that are copyrighted by ESA and were provided through the WInSAR consortium at the UNAVCO facility. All pair directories use the image acquired on 3/11/2007 as a reference image.

To view specific information for each grd file, please use the GMT command "grdinfo" - e.g., for grd file In20070311_20071111/drho_utm.grd, use terminal command:

 grdinfo In20070311_20071111/drho_utm.grd

This dataset is published in relation to the manuscript 'Life cycle assessment of a hinged raft wave energy converter in multiple utility-scale arrays', under review for publication in The Journal of Power and Energy, Part A of the Proceedings of the Institution of Mechanical Engineers. This paper presents a life cycle assessment (LCA) of the Blue Horizon wave energy converter (WEC), deployed in four utility-scale arrays, including major array components (array cables, substation and export cable) and highly detailed vessel representation (types, modes and distances using modified background data processes scaled with specific fuel consumption). This dataset contains all of the foreground and background data necessary to replicate the findings of the study, as well as the derivation of the vessel conversion factors for modelling unit processes of vessel time, and the development of operation and maintenance data from literature.

The Risk Analysis Framework for Tropical Cyclones (RAFT)'s comprehensive and unified simulation of 40,000 synthetic North Atlantic tropical cyclone (TC) events are presented in this dataset. RAFT meticulously models these events based on large-scale environmental conditions, providing a valuable tool for in-depth TC impact analysis. The dataset encompasses detailed 6-hourly track information, along-track intensity metrics (including maximum wind speed and minimum pressure), the radius of maximum winds, and cumulative precipitation for each event. The primary dataset is encapsulated in a NetCDF4 file, "RAFT.NA.v20231016.nc", which contains a complete array of variables pertinent to the 40,000 synthetic TCs. These variables, detailed in Table 1 of the accompanying paper and summarized below, offer a comprehensive view of each TC event: Basin ID: Identifies the basin (1 for North Atlantic) Storm ID: Unique identification number for each TC, starting from 0 Year: Year of the environmental conditions used for modeling Jday: Julian day of the year, ranging from 0 to 365 Longitude (lon): Geographical longitude in degrees Latitude (lat): Geographical latitude in degrees Maximum Wind Speed (vmax): Measured in knots Minimum Pressure (mslp): Measured in hectopascals (hPa) Radius of Maximum Wind (rmax): Measured in nautical miles (nmi) Additionally, the dataset offers individualized accumulated rainfall data for each TC event, stored in NetCDF4 files named according to the convention "modeled_rainfall_ERA5_syn_{i}.h5", where "{i}" is the synthetic storm's ID. "ERA5" signifies the reanalysis input source, and "syn" indicates a synthetic track. This component of the dataset includes the following variables, all measured in total millimeters of precipitation: Total Accumulated Rainfall (p_accum) Frictional Precipitation Component (p_accum_f) Topographic Precipitation Component (p_accum_h) Shear-related Precipitation Component (p_accum_s) Vortex Stretching Precipitation Component (p_accum_t) The rainfall dataset is curated to focus on TC events within 600 km of the U.S. coast, reducing the number of rainfall events to 17,010 from the original 40,000, thereby enhancing its relevance and manageability. For user convenience, these events are compressed into grouped archives named "RAFT_accum_rainfall_{index}.tar.gz", where each "{index}" represents the index of the zipfile, containing up to 2,000 files for efficient data retrieval. The accumulated rainfall data is provided on a regular spatial grid, detailed in "RAFT_rainfall_latlon_grid.h5", which outlines the grid coordinates ('lat' and 'lon'). For comprehensive usage guidelines and further insights into this dataset, users are encouraged to refer to the associated paper. This dataset is not only a significant resource for researchers and analysts in the field of meteorology but also serves as a pivotal tool for understanding and predicting the impacts of tropical cyclones. How to cite: Xu, W., Balaguru, K., Judi, D.R. et al. A North Atlantic synthetic tropical cyclone track, intensity, and rainfall dataset. Sci Data 11, 130 (2024). https://doi.org/10.1038/s41597-024-02952-7 This work was supported by the Multisector Dynamics and Regional and Global Model Analysis program areas of the U.S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research as part of the multi-program, collaborative Integrated Coastal Modeling (ICoM) project. The Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830.

Metadata record for data from ASAC Project 2914 See the link below for public details on this project.

Can animals raft between countries on floating seaweed? We aim to answer that question using powerful genetic tools. We can tell whether gene flow is strong between populations of animals by comparing their mitochondrial DNA; this could show us whether animals from one species in New Zealand are isolated from individuals of the same species in Chile. If they are not isolated, how are they managing to maintain gene flow? We know there are many millions of clumps of floating seaweed in the Southern Ocean, and these might provide a means of intercontinental travel for a range of small invertebrates.

Project objectives: The primary objective of the project is to determine the effectiveness of rafting as a dispersal mechanism for sessile and semi-sessile organisms around the Southern Ocean using genetic tools.

The secondary objectives, by which the primary objective will be addressed, are:

• to examine the biogeography of bull kelp (Durvillaea antarctica) and its holdfast fauna around the Southern Ocean

• to undertake genetic analysis of a wide range of macroalgal (seaweed) species throughout the Southern Ocean to assess 1) whether sea ice indeed extended further north than previously believed, and 2) the ecological and evolutionary impacts of historic ice scour on Southern Ocean islands.

• to determine which holdfast invertebrates are the most common and ubiquitous in holdfasts of Durvillaea antarctica around the Southern Ocean

• to compare the genetic structure of populations of both the kelp itself, and select invertebrate taxa* from its holdfasts, on a number of spatial scales: --- genetic variation at HOLDFAST level: are members of a single species, e.g., the isopod Limnoria stephenseni, closely related within a single holdfast? --- genetic variation at SITE level: are members of a single species, e.g., Durvillaea antarctica itself, closely related at one site? In this case, a 'site' means a single intertidal rock platform. --- genetic variation at NATIONAL level: are there distinct biogeographic separations of species, or does a single species show distinct genetic disjunction, along the Chilean coastline and around the south island of New Zealand? --- genetic variation at OCEAN level: are species clearly connected (by gene flow) between Southern Ocean landmasses? The landmasses of interest are: Chile, New Zealand, and the subantarctic islands on which Durvillaea antarctica grows.

• The proposed taxa that this project will focus on are: the isopod genus Limnoria; the amphipod Parawaldeckia kidderi; the chiton genus Onithochiton; the polychaete worm families Terebellidae and Syllidae; a topshell; a bivalve; barnacles.

Progress against objectives:

Considerable progress has been made against the primary objective since the start of the project in 2006. We have collected (/ been sent) and analysed samples of bull-kelp (Durvillaea antarctica) and its associated invertebrate holdfast fauna from numerous sites around the Southern Ocean (subantarctic islands including Macquarie, Gough, Marion, Kerguelen, Crozet, Auckland, Antipodes, Campbell, Falkland Islands; along the coasts of New Zealand and Chile). Our results thus far have allowed us to determine not only that rafting facilitates long-distance dispersal of these otherwise sedentary taxa, but also that sea ice during the last ice ice likely had significant impacts on subantarctic intertidal ecosystems. Our conclusions have been published in several papers in high-impact journals.

The secondary objectives, by which the primary objective will be addressed, are:

• to examine the biogeography of bull kelp (Durvillaea antarctica) and its holdfast fauna - these objectives have now largely been achieved, and results published.

• to undertake genetic analysis of a wide range of macroalgal (seaweed) species throughout the Southern Ocean - this part of the project is ongoing, and will make use of samples collected over the austral summer from Macquarie Island (and other locations around the southern hemisphere). all samples have now been collected and are being processed in the laboratory.

• to determine which holdfast invertebrates are the most common and ubiquitous - this objective has been partially achieved (see Nikula et al. 2010), but research is ongoing.

• to compare the genetic structure of populations of both the kelp itself, and select invertebrate taxa from its holdfasts, on a number of spatial scales - this objective has been partially achieved (see Nikula et al. 2010 for results of Limnoria and Parawaldeckia genetic research) but additional research on these and other taxa continues.

The download file contains an excel spreadsheet detailing collection locations and accession numbers for the samples collected on Macquarie Island. A text document providing accession numbers for non-Antarctic related samples used in this project is also part of the download file. Quality: The figures provided in temporal and spatial coverage are approximate only.

Taken from the 2009-2010 progress report:

Field work: During the 2009/2010 season, Dr James Doube and other AAD personnel based at Macquarie Island were able to collect the macroalgal samples we requested. Field work was undertaken at two sites close to the Base: one on the east coast (Garden Cove, 57F 0496283 3960990) and one on the west coast (Cosray Rocks, 57F 0495752 3960973). Fieldwork involved collection of small samples of intertidal seaweeds (macroalgae) from rock platforms at Macquarie Islands. Samples were preserved in ethanol, and couriered to our department at the University of Otago. These samples were received on 14 May 2010, and are now being processed in the laboratory.

Field work for the broader project is ongoing - however, during the 2009 / 2010 summer, we collected (or were sent) samples from: - the Falkland Islands - central Chile - southern Chile (fiordland) - the New Zealand subantarctic (Campbell, Auckland, Snares, Antipodes and Bounty Islands) - Kerguelen Island - Marion Island - Gough Island - Tasmania, Australia

Difficulties affecting project: Not all target species of seaweed were obtained from all collection sites (both at Macquarie Is and elsewhere) - however, on the whole we have obtained most of our target taxa from a broad range of subantarctic locations.

Note from AADC, 2018-08-03: The original datasheet was reformatted to fit OBIS/GBFI/IPT Biodiversity.AQ standardS. The new datasheet "KelpRafts.csv" provides the dataset from Macquarie Island samples. Contains datasetID, occurrenceID, event date, decimal latitude, decimal longitude. The lowest taxonomical rank of the species identified that could be determined is provided, after matched in WoRMS (World Register of Marine Species). As the data is genetics identification the associatedSequence and associatedReferences are provided.

The synthesis of a series of novel, unsymmetrically substituted benzothiadiazole-containing vinyl monomers and their free radical polymerization with and without the control of a reversible addition−fragmentation chain transfer (RAFT) agent is reported. The resulting polymers with electroactive pendants show tunable absorption and emission spectra depending on their molecular architecture. Using RAFT allows the synthesis of block copolymers using a hole-transporting vinyl-triarylamine as a second monomer. Efficient energy transfer between the two pendants has been detected. Cyclic voltammetry and photoelectron spectroscopy in air measurements have been employed to reveal the location of the HOMO and LUMO of the block copolymers. The block copolymers also influence the morphology of spin-casted films and show rectifying behavior in organic photovoltaic devices.

Images of extruded liposomes composed of DPPC/DOPC/POPG/Chol 40/35/5/20 mol% from Heberle et al. 2020 Proc. Natl. Acad. Sci. USA 117:19943 (https://doi.org/10.1073/pnas.2002200117). Images were acquired on an FEI Polara G2 operating at an accelerating voltage of 300 kV equipped with a Gatan K2 Summit detector operated in counting mode. The Cs of the Polara microscope was 2 mm and the pixel size for image acquisition was 2.73 Å/pixel. Each image has a corresponding CSV file containing vesicle contours generated by the MEMNET program which is part of the TARDIS software package (https://github.com/SMLC-NYSBC/TARDIS).

DPPC is 1,2-dipalmitoyl-sn-glycero-3-phosphocholine
DOPC is 1,2-dioleoyl-sn-glycero-3-phosphocholine
POPG is 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-(1'-rac-glycerol)
Chol is cholesterol

Protein-Protein, Genetic, and Chemical Interactions for Schwarz K (2001):Podocin, a raft-associated component of the glomerular slit diaphragm, interacts with CD2AP and nephrin. curated by BioGRID (https://thebiogrid.org); ABSTRACT: NPHS2 was recently identified as a gene whose mutations cause autosomal recessive steroid-resistant nephrotic syndrome. Its product, podocin, is a new member of the stomatin family, which consists of hairpin-like integral membrane proteins with intracellular NH(2)- and COOH-termini. Podocin is expressed in glomerular podocytes, but its subcellular distribution and interaction with other proteins are unknown. Here we show, by immunoelectron microscopy, that podocin localizes to the podocyte foot process membrane, at the insertion site of the slit diaphragm. Podocin accumulates in an oligomeric form in lipid rafts of the slit diaphragm. Moreover, GST pull-down experiments reveal that podocin associates via its COOH-terminal domain with CD2AP, a cytoplasmic binding partner of nephrin, and with nephrin itself. That podocin interacts with CD2AP and nephrin in vivo is shown by coimmunoprecipitation of these proteins from glomerular extracts. Furthermore, in vitro studies reveal direct interaction of podocin and CD2AP. Hence, as with the erythrocyte lipid raft protein stomatin, podocin is present in high-order oligomers and may serve a scaffolding function. We postulate that podocin serves in the structural organization of the slit diaphragm and the regulation of its filtration function.

The energy of interaction (ΔG, in kJ.mol−1) has been determined by molecular docking of α-syn34-45/HH on a minimized dimer of each ganglioside, using Hyperchem and Molegro programs. The contribution of His-13/His-14 to the binding reaction is indicated in the last line of the table. Note that the expected contribution of two residues such as His-13/His-14 to a binding reaction involving equally all residues of a 12-mer peptide is 16.7%.