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At least 73 records · Page 4

Integrated structural dynamics uncover new modes of B12 photoreceptor activation

**SACLA** A crystallographic pump-power titration was first carried-out with pump laser fluences of 12, 30, 60 and 120 uJ.cm-2 and a time delay of 3 us. Then, a time-series was performed with a pump-laser fluence of 30 uJ.cm-2 (~2.4 absorbed photon per chromophore) and time-delays of 10 ns, 300 ns, 3 µs, 100 us and 3 ms. Finally, two time-delays (10 ns and 3 us) were collected with a pump laser fluence of 12 uJ.cm-2. Raw images, crystFEL streams and merged mtzs are available for all collected dat **SwissFEL** A time series with a pump laser fluence of 30 mJ.cm-2 was performed at time delys of 3 µs and 10 ms. Raw images, crystFEL streams and merged mtzs are available for all collected datasets. Refined detector geometry for each experimental campaign is also provided (crystFEL format)

RIOS-SANTACRUZ, Ronald↗

Integrated structural dynamics uncover new modes of B12 photoreceptor activation

**SACLA** A crystallographic pump-power titration was first carried-out with pump laser fluences of 12, 30, 60 and 120 ??J.cm-2 and a time delay of 3 ??s. Then, a time-series was performed with a pump-laser fluence of 30 ??J.cm-2 (~2.4 absorbed photon per chromophore) and time-delays of 10 ns, 300 ns, 3 ??s, 100 ??s and 3 ms. Finally, two time-delays (10 ns and 3 ??s) were collected with a pump laser fluence of 12 ??J.cm-2. Raw images, crystFEL streams and merged mtzs are available for all collected dat **SwissFEL** A time series with a pump laser fluence of 30 mJ.cm-2 was performed at time delys of 3 ??s and 10 ms. Raw images, crystFEL streams and merged mtzs are available for all collected datasets. Refined detector geometry for each experimental campaign is also provided (crystFEL format)

RIOS-SANTACRUZ, Ronald↗

Supplemental material for paper "Radiosonde-to-Space (R2S) atmospheric specifications: Bridging observations and models for infrasound propagation"

This document describes the supplemental materials for the paper: TITLE: "Radiosonde-to-Space (R2S) atmospheric specifications: Bridging observations and models for infrasound propagation" DOI: xxxxxxxxxxx JOURNAL: TBD Written by Loring Schaible, September 17, 2025 This folder contains eight subfolders, each for a specific date and UTC time (in format YYYY-MM-DD_HH). All eight of these dates are exemplified and described in the manuscript. Within each folder is six documents. As an example, consider the folder "2022-12-31_00". The six files are comprised of: - Two text files (extension .txt) that describe the atmospheric specifications of Albuquerque, NM. One is the G2S model, the other is the R2S model. "G2S_2022-12-31_00.txt" "R2S_2022-12-31_00.txt" - Two text files (extension .dat) that contain the ground arrivals predicted by infraGA using the parameters described in the manuscript. One each for the two atmospheric specification models above, G2S and R2S. "G2S_2022-12-31_00.arrivals.dat" "R2S_2022-12-31_00.arrivals.dat" - Two image files (extension .png) that illustrate the predicted arrivals contained in the two files above. One image shows all arrivals as either black (G2S) or red (R2S). The other image shows the same but with arrivals common to both models in gray. "2022-12-31_00_Arrivals.png" "2022-12-31_00_DifArrivals.png"

Schaible, Loring Pratt [Sandia National Laboratori↗

How structural elements evolving from bacterial to human SLC6 transporters enabled new functional properties

Background. Much of the structure-based mechanistic understandings of the function of SLC6A neurotransmitter transporters emerged from the study of their bacterial LeuT-fold homologs. It has become evident, however, that structural differences such as the long N- and C-termini of the eukaryotic neurotransmitter transporters are involved in an expanded set of functional properties to the eukaryotic transporters. These functional properties are not shared by the bacterial homologs, which lack the structural elements that appeared later in evolution. However, mechanistic insights into some of the measured functional properties of the eukaryotic transporters that have been suggested to involve these structural elements are sparse or merely descriptive. Results. To learn how the structural elements added in evolution enable mechanisms of the eukaryotic transporters in ways not shared with their bacterial LeuT-like homologs, we focused on the human dopamine transporter (hDAT) as a prototype. We present the results of a study employing large-scale molecular dynamics simulations and comparative Markov state model analysis of experimentally determined properties of the wild-type and mutant hDAT constructs. These offer a quantitative outline of mechanisms in which a rich spectrum of interactions of the hDAT N-terminus and C-terminus contribute to the regulation of transporter function (e.g., by phosphorylation) and/or to entirely new phenotypes (e.g., reverse uptake (efflux)) that were added in evolution. Conclusions. The findings are consistent with the proposal that the size of eukaryotic neurotransmitter transporter termini increased during evolution to enable more functions (e.g., efflux) not shared with the bacterial homologs. The mechanistic explanations for the experimental findings about the modulation of function in DAT, the serotonin transporter, and other eukaryotic transporters reveal separate roles for the distal and proximal segments of the much larger N-terminus in eukaryotic transporters compared to the bacterial ones. The involvement of the proximal and distal segments — such as the role of the proximal segment in sustaining transport in phosphatidylinositol 4,5-bisphosphate-depleted membranes and of the distal segment in modulating efflux — may represent an evolutionary adaptation required for the function of eukaryotic transporters expressed in various cell types of the same organism that differ in the lipid composition and protein complement of their membrane environment.

59 BASIC BIOLOGICAL SCIENCES↗

Neutron powder diffraction, Mossbauer Spectroscopy and Optical Spectroscopy to study magnetic and nuclear lattices in Fe-based oxychlorides Ca2FeO3Cl, Sr2FeO3Cl and Sr3Fe2O5Cl2

Data for Neutron Diffraction, Mossbauer Spectoscopy and Optical Spectroscopy are contained on all three samples (Ca2FeO3Cl, Sr2FeO3Cl, and Sr3Fe2O5Cl2). Mossbauer data are in the folder "MossbauerSpectroscopy". This contains details of files and examples to read the data. The Optical Spectroscopy are in the folder "AbsorptionData", this contains one file with explanatory headers. The neutron diffraction data are in the "NeutronDiffractionData" folder. The data was collected on the HB-2A powder diffractometer at HFIR. The autoreduced files are corrected using a vanadium standard and are in arbitrary intensity units. The RawData folder contains the uncorrected data with metadata for motor positions and temperature. All measurements were collected with a constant neuton wavelength of 2.41 Angstrom. An excel spreadsheet "NeutronDiffractionData_IPTS-29118_summary" contains details for each scan. Sr3Fe2O5Cl2 data were collected at only room temperature. Ca2FeO3Cl and Sr2FeO3Cl data were collected at 4K and room temperature. The autoreduced .dat fileformat is three columns corresponding to: Two-theta, Intensity and Intensity_error.

fe-based oxychlorides↗

Utah FORGE: Phase 3 Magnetotelluric (MT) Data

New high-quality tensor MT data at 122 sites, including the vertical magnetic field and utilizing ultra-remote referencing, have been acquired over the Utah FORGE project area. The results will be used to delineate the densities of faults and fractures in crystalline basement rocks, to define the heat sources, and to derive baseline 3D resistivity structure for later MT monitoring of temporal changes in resistivity structure following well stimulation in the EGS reservoir. There are three files here related to Utah FORGE magnetotelluric (MT) data acquisition and processing. The FORGE MT EDIs zip file contains the observed MT responses in industry-standard EDI format. For each site, there is an EDI response file that utilized a local independent reference for noise cancellation, and a file that utilized a distant reference cancelling noise associated with the DC transmission line of the Delta IPP passing down the west side of Milford Valley. These two site files could be merged as appropriate. The FORGE Model Cell Center file contains the model volume of the 3D Forge MT inversion for characterizing the resistivity structure in the project area. It was derived using finite element inversion methodology described in Wannamaker et al, in the attached FORGE Phase3 Geophysics paper, from the MT observation EDI files. It is ASCII format (.dat) and entries are defined at top of the file in a simple x-y-z-Rho listing in UTM coordinates. The element layers drape the topography so the Rho value layers are not purely horizontal slices. This greatly simplifies the listing.

15 GEOTHERMAL ENERGY↗

EGS Collab Experiment 1: Continuous Active-Source Seismic Monitoring (CASSM) Data

The U.S. Department of Energy's Enhanced Geothermal System (EGS) Collab project aims to improve our understanding of hydraulic stimulations in crystalline rock for enhanced geothermal energy production through execution of intensely monitored meso-scale experiments. The first experiment was performed at the 4850 ft level of the Sanford Underground Research Facility (SURF), approximately 1.5 km below the surface at Lead, South Dakota. The data reported here were collected by the continuous active-source seismic monitoring (CASSM) system (Ajo-Franklin et al., 2011). This system was permanently installed in the testbed and consisted of 17 piezoelectric sources that were recorded by 2-12 channel hydrophone arrays, 18 3-C accelerometers, and 4 3-C geophones at a Nyquist frequency of 24kHz. The source array was activated in a repeated sequence of shots (each source fired 16 times and stacked into resultant waveforms) for the duration of the experiment (April 25, 2018 - March 7, 2019) with few exceptions. Please see the attached documents describing the source / receiver geometry. The data are available in both seg2 (.dat extension) and segy (.sgy extension) format. Each segy file contains multiple seg2 files.

15 GEOTHERMAL ENERGY↗

EGS Collab Experiment 2: Continuous Active Source Seismic Monitoring (CASSM)

The dataset contains continuous active-source seismic monitoring (CASSM) data collected during EGS Collab Experiment 2, conducted from February to September 2022 at the Sanford Underground Research Facility in Lead, South Dakota. This experiment aimed to investigate enhanced geothermal systems through high-pressure fluid injections at depths of 1200-1500 meters. The seismic monitoring system included 16 three-component piezoelectric accelerometers and 24 hydrophones installed in boreholes around the injection zones, recording signals from piezoelectric seismic sources. Data were acquired using both continuous and triggered recording systems, with sampling rates of up to 100 kHz. The raw data are organized by timestamps and stored in .dat format, with accompanying log files. Calibration certificates for selected accelerometers are provided to aid in correcting sensor responses, though users are advised to consider possible effects of enclosures and installation on sensor performance. Users are strongly advised to consult the accompanying report, which outlines the experimental setup, data acquisition, sensor specifications, and recording systems.

15 GEOTHERMAL ENERGY↗

RANS Simulation RRF of Single Full Scale DOE RM1 MHK Turbine

Attached are the .cas and .dat files for the Reynolds Averaged Navier-Stokes (RANS) simulation of a single full scale DOE RM1 turbine implemented in ANSYS FLUENT CFD-package. In this case study taking advantage of the symmetry of the DOE RM1 geometry, only half of the geometry is modeled using (Single) Rotating Reference Frame model [RRF]. In this model RANS equations, coupled with k-\omega turbulence closure model, are solved in the rotating reference frame. The actual geometry of the turbine blade is included and the turbulent boundary layer along the blade span is simulated using wall-function approach. The rotation of the blade is modeled by applying periodic boundary condition to sets of plane of symmetry. This case study simulates the performance and flow field in both the near and far wake of the device at the desired operating conditions. The results of these simulations showed good agreement to the only publicly available numerical simulation of the device done in the NREL. Please see the attached paper.

16 TIDAL AND WAVE POWER↗

RANS Simulation VBM of Single Full Scale DOE RM1 MHK Turbine

Attached are the .cas and .dat files along with the required User Defined Functions (UDFs) and look-up table of lift and drag coefficients for Reynolds Averaged Navier-Stokes (RANS) simulation of a single full scale DOE RM1 turbine implemented in ANSYS FLUENT CFD-package. In this case study the flow field around and in the wake of the full scale DOE RM1 turbine is simulated using Blade Element Model (a.k.a Virtual Blade Model [VBM]) by solving RANS equations coupled with k-\omega turbulence closure model. It should be highlighted that in this simulation the actual geometry of the rotor blade is not modeled. The effect of turbine rotating blades are modeled using the Blade Element Theory. This simulation provides an accurate estimate for the performance of device and structure of it's turbulent far wake. Due to the simplifications implemented for modeling the rotating blades in this model, VBM is limited to capture details of the flow field in near wake region of the device.

16 TIDAL AND WAVE POWER↗

RANS Simulation RRF of Single Lab-Scaled DOE RM1 MHK Turbine

Attached are the .cas and .dat files for the Reynolds Averaged Navier-Stokes (RANS) simulation of a single lab-scaled DOE RM1 turbine implemented in ANSYS FLUENT CFD-package. The lab-scaled DOE RM1 is a re-design geometry, based of the full scale DOE RM1 design, producing same power output as the full scale model, while operating at matched Tip Speed Ratio values at reachable laboratory Reynolds number (see attached paper). In this case study taking advantage of the symmetry of lab-scaled DOE RM1 geometry, only half of the geometry is models using (Single) Rotating Reference Frame model [RRF]. In this model RANS equations, coupled with k-\omega turbulence closure model, are solved in the rotating reference frame. The actual geometry of the turbine blade is included and the turbulent boundary layer along the blade span is simulated using wall-function approach. The rotation of the blade is modeled by applying periodic boundary condition to sets of plane of symmetry. This case study simulates the performance and flow field in the near and far wake of the device at the desired operating conditions. The results of these simulations were validated against in-house experimental data. Please see the attached paper.

16 TIDAL AND WAVE POWER↗

RANS Simulation ADM of the NREL Phase VI wind turbine modeled as MHK Turbine

Attached are the .cas and .dat files for the Reynolds Averaged Navier-Stokes (RANS) simulation of a single lab-scaled DOE RM1 turbine implemented in ANSYS FLUENT CFD-package. In this case study the flow field around and in the wake of the NREL Phase VI wind turbine, modeled is MHK turbine, is simulated using Actuator Disk Model (ADM) (a.k.a Porous Media) by solving RANS equations coupled with a turbulence closure model. It should be highlighted that in this simulation the actual geometry of the rotor blade is not modeled. The effect of turbine rotating blades are modeled using the Actuator Disk Theory (see the stated section of attached M.Sc. thesis for more details).

16 TIDAL AND WAVE POWER↗

RANS Simulation VBM of Array of Three Coaxial Lab Scaled DOE RM1 MHK Turbine with 5D Spacing

Attached are the .cas and .dat files along with the required User Defined Functions (UDFs) and look-up table of lift and drag coefficients for the Reynolds Averaged Navier-Stokes (RANS) simulation of three coaxially located lab-scaled DOE RM1 turbine implemented in ANSYS FLUENT CFD-package. The lab-scaled DOE RM1 is a re-design geometry, based of the full scale DOE RM1 design, producing same power output as the full scale model, while operating at matched Tip Speed Ratio values at reachable laboratory Reynolds number (see attached paper). In this case study the flow field around and in the wake of the lab-scaled DOE RM1 turbines in a coaxial array is simulated using Blade Element Model (a.k.a Virtual Blade Model [VBM]) by solving RANS equations coupled with k-\omega turbulence closure model. It should be highlighted that in this simulation the actual geometry of the rotor blade is not modeled. The effect of turbine rotating blades are modeled using the Blade Element Theory. This simulation provides an accurate estimate for the performance of each device and structure of their turbulent far wake. The results of these simulations were validated against the developed in-house experimental data. Simulations for other turbine configurations are available upon request.

16 TIDAL AND WAVE POWER↗

2017 Western Passage Tidal Energy Resource Characterization Measurements

These data are from tidal resource characterization measurements collected between April and July 2017 in Western Passage near Eastport, Maine, USA. The dataset contains the following four sub-datasets, each of which is described in more detail in the README.pdf. 1. A bottom-mounted Teledyne RDI Workhorse 600 kHz acoustic Doppler current profiler (ADCP) was deployed at 44.92015 N, 66.98915 W in ~50 m of water from 3 April to 18 July (106 days). Data were recorded in 6-minute increments in the ENU (East, magnetic North, Up) coordinate system with bin-mapping enabled. 2. A bottom-mounted Nortek Signature 500 kHz ADCP was deployed at 44.92192 N, 66.98913 W in ~50 m of water from 4 April to 18 July (105 days). Data were sampled and recorded at 2 Hz and recorded in the ENU (East, magnetic North, Up) coordinate system. 3. Between those stations along a cross-channel transect, a Stable Tidal Turbulence Mooring (STTM) positioned ~10 m above the seabed was deployed for one week during a spring tide. The STTM was outfitted with two Nortek Vector acoustic Doppler velocimeters equipped with inertial motion units (ADVs), a bottom-tracking downward-looking Teledyne RDI Workhorse 600 kHz ADCP to provide motion-corrected flow and turbulence characteristics at high temporal resolution, and an upward-looking Teledyne RDI Sentinel V20 ADCP. The STTM was deployed at 44.92098 N, 66.98922 W from 24-31 May. 4. A vessel-mounted Teledyne RDI Workhorse 300 kHz ADCP collected current data along three transects over two days, 4-5 April. The data processing used DOLfYN version 0.11.2. All hdf5 files (i.e., files ending in `.h5`) contained here can be opened using that version of DOLfYN (e.g., `dat = dolfyn.load('')`). All distances are in meters (e.g., depth, range, MLLW, hab, eta, z_), and all velocities in m/s. See the DOLfYN documentation https://lkilcher.github.io/dolfyn/), and/or the Nortek and Teledyne RDI documentation for additional details. Additional details on the dataset can be found in the README.pdf, including: - Format details of each data file. - How to regenerate the data-processing (using the files in the `wp2017_processing.zip` archive).

16 TIDAL AND WAVE POWER↗

Washington Air-Sea Interaction Research Facility Waves and Currents Test Data

This archive includes data from the University of Washington WASIRF (Washington Air-Sea Interaction Research Facility) flume. WASIRF is a laboratory testing tank at the Northwest National Marine Renewable Energy Center designed to investigate wind-wave-current interactions. It includes test data for simultaneous waves and current generation done at the WASIRF lab. A report included in the archive further details testing methodology. Wave and current data is provided in .dat files.

16 TIDAL AND WAVE POWER↗

Performance of Elevated Hinge Flap Wavemaker

This data includes a sweep of regular wave runs characterizing the performance of an elevated hinge flap wavemaker. Maximum wave heights were run for 13 periods in a range from 0.5 s to 6 s. Data is saved in several formats including 'raw' analog voltages, 'mat' matlab files,'txt' csv, and 'dat' ASCII.

16 TIDAL AND WAVE POWER↗

The LAKE model input dataset for three Arctic lakes

This dataset contains meteorological data collected for three Arctic lakes and compiled to satisfy input requirements of the LAKE 2.0 model. The dataset was generated to act as a benchmarking dataset for future model-data inter-comparisons. The LAKE 2.0 model simulates temperatures within the water later and the sedimentary layer of a lake. The LAKE2.0. is an open-source code and available to download via this weblike http://tesla.parallel.ru/Viktor/LAKE/-/wikis/LAKE-model (last visit July 14, 2021). The meteorological data are required to simulate the surface energy balance at the surface of a lake. This dataset includes a compilation of the meteorological data pulled from multiple data streams, including National Oceanic and Atmospheric Administration (NOAA) climate data, Circumarctic Lakes Observation Network (CALON) data, and the United States Geological Survey (USGS) data. The data were compiled for three Arctic lakes: FoxDen (66.55877, -164.45670), Atqasuk (70.452497, -156.951984), and Toolik (68.63150, -149.60740). Each meteorological data is in comma-delimited format (file extension ‘.dat’) and includes eight columns: Temperature [K], Pressure [Pa], longwave downward radiation [W/m2], shortwave downward radiation [W/m2], “U” wind speed [m/s], ”V” wind speed [m/s], humidity [kg/kg], precipitation [m/s]. In addition to the meteorological data file, we included setup and driver files. The Toolik lake is the deepest out of three lakes and has inflowing and outflowing groundwater data. InflowOutflowREADME.txt has more information about inflow and outflow flies. The other two lakes are much shallower and modeled as a closed system (i.e. no water inflow or outflow).

54 ENVIRONMENTAL SCIENCES↗

Model, data, and code for paper "Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x"

The data package includes data, model, and code that support the analyses and conclusions in the paper titled “modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x”. The primary goal of this paper is to demonstrate that key streamflow properties such as water depth, flow velocity, and dynamic pressure in a natural river at 30-kilometer scale over 5 years can be reliably and efficiently modeled using the computational framework presented in this paper. To support the paper, various data types from remote sensing, field observations, and computational models are used. Specific details are described as follows. Firstly, the river bathymetry data was obtained from a Light Detection and Ranging (LiDAR) survey. This data is then converted to a triangulated surface format, STL, for mesh generation in OpenFOAM. The STL data can be found in Model_Setups/BaseCase_2013To2015/constant/triSurface. The OpenFOAM mesh generated using this STL file can be found in constant/polyMesh. Other model setups, boundary and initial conditions can be found in /system and /0.org under folder BaseCase_2013To2015. A similar data structure can also be found in BaseCase_2018To2019 for the simulations during 2018 and 2019. Secondly, the OpenFOAM simulations need the upstream discharge and water depth information at the upstream boundary to drive the model. These data are generated from a one-dimensional hydraulic model and the data can be found under the folder Model_Setups /1D model Mass1 data. The mass1_65.csv and mass1_191.csv files include the results of the 1D model at the model inlet and outlet, respectively. The Matlab source code Mass1ToOFBC20182019.m is used to convert these data into OpenFOAM boundary condition setups.With the above OpenFOAM model, it can generate data for water surface elevation, flow velocity, and dynamic pressure. In this paper, the water surface elevation was measured at 7 locations during different periods between 2011 and 2019. The exact survey locations (see Fig1_SurveyLocations.txt) can be found in folder Fig_1. The variation of water stage over time at the 7 locations can be found in folder /Observation_WSE. The data type include .txt, .csv, .xlsx, and .mat. The .mat data can be loaded by Matlab.We also measured the flow velocities at 12 cross-sections along the river. At each cross-section, we recorded the x, y locations, depth, three velocity components u,v,w. These data are saved to a Matlab format which can be found under folder /Observation_Velocity and /Fig_1. The relative locations of velocity survey locations to the river bathymetry can be found in Figure 1c.The water stage data at the 7 locations from OpenFOAM, 1D, and 2D hydraulic models are also provided to evaluate the long-term performance of 3D models vs 1D/2D models. The water stage data for the 7 locations from OpenFOAM have been saved to .mat format and can be found in /OpenFOAM_WSE. The water stage data from the 1D model are saved in .csv format and can be found in /Mass1_WSE. The water stage from the 2D model is saved as .mat format and can be found in / Mass2_WSEIn addition, the OpenFOAM model outputs the information of hydrostatic and hydrodynamic pressure. They are saved as .mat format under folder /Fig_11/2013_1. As the files are too large, we only uploaded the data for January 2013. The area of different ratio of dynamic pressure to static pressure for all simulation range, i.e., 2013-2015, are saved to .mat format. They can be found in /Fig_11/PA. Further, the data of wall clock time versus the solution time of the OpenFOAM modeling are also saved to .mat format under folder /Fig_13/LogsMat. In summary, the data package contains seven data types, including .txt, .csv, .xlsx, .dat, .stl, .m, and .mat. The former 4 types can be directly open using a text editor or Microsoft Office. The .mat format needs to be read by Matlab. The Matlab source code .m files need to be run with Matlab. The OpenFOAM setups can be visualized in ParaView. The .stl file can be opened in ParaView or Blender. The data in subfolders Fig_1 to Fig_10 and Fig_12 are copied from the aforementioned data folders to generate specific figures for the paper. A readME.txt file is included in each subfolder to further describe how the data in each folder are generated and used to support the paper.Please use the data package's DOI to cite the data package. Please contact yunxiang.chen@pnnl.gov if you need more data related to the paper.

54 ENVIRONMENTAL SCIENCES↗