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Arecibo ISR CLP/ULP/LULP ion-line spectra obtained from USRP receiver with 500 kHz bandwidth and 120-1400 km altitude range, experiment dates September 23-26, 2016. Used for Joint inversions of coded and uncoded long pulse1 F-region ISR returns measured at Arecibo.

This repository contains source data for key plots presented in the manuscript "Plasmon-driven exciton formation in a non-equilibrium Fermi liquid." Experimental data that was analyzed in Igor Pro 8 are presented as the .pxp files used to generate individual sub-plots. Electronic spectral function calculations are provided as .txt files, in which consecutive rows refer to the meshgrid x coordinate, y coordinate, spectral function (and, where relevant, axis-projected local angular momentum). We additionally include the Wannier model and DFT-obtained bulk band structure on which the Wannier model was based. Files are named as the number of the figure in the manuscript to which they correspond, with additional details included where necessary. <b>Details of file names:</b> 2a_DOS_Lxz_Ek_KGM_40layer_xnum_800kpt_tot.txt: Density of states, xz-axis projected local orbital angular momentum, for 800 points along the K-Gamma-M path, for a 40-layer model. 2c_composite_y.pxp: ARPES (angle-resolved photoemission spectroscopy) spectra along the ky axis, including both a scan near the Fermi level and a scan at high kinetic energies. 2d_LCP_RCP_diff_Sect_20K.pxp: difference between ARPES constant energy cuts at T=20 K at E0 + 0.23 eV taken with left- and right-circularly polarized photons. The polarization-integrated intensity at the constant energy cut is also included. 2e_DOS_L45_E11pt79_m0pt25to0pt25_xnum_800kpt_tot.txt: Density of states, xz-projected local orbital angular momentum, and corresponding k-points in two dimensions from ab-initio electronic structure calculations for a constant-energy cut. 3a_[x]_[y]ps: ARPES cut under excitation at a fluence of x uJ/cm2, measured y ps after photoexcitation. Measurements were performed at 9 K. 3b_[x]: Energy distribution curves under excitation at a fluence x uJ/cm2 at selected delay times after photoexcitation. 4a_ImSigma_vs_temperature.pxp: Imaginary self energy (extracted from ARPES linewidths) at different energies above E0 for selected lattice temperatures. 4b_EELS_lowE.pxp: Electron energy loss spectrum over a low energy range 5b_diff_55m15.pxp: Difference between momentum-integrated Tr-ARPES traces at 55 uJ/cm2 and 15 uJ/cm2 photoexcitation. Time-dependent intensity at each energy level has been normalized to a maximum of 1 for each individual fluence prior to subtraction. 5d_invtau_at_EX_vs_fluence.pxp: decay rate at a specified energy EX for different excitation fluences, from single exponential fits. <b>NOTE: Analyses based on the Wannier model presented here should cite both the associated Article and this dataset. For all other files in the repository, citing the dataset alone is sufficient.</b>

Chemical-free hydrothermal pretreatment of Miscanthus x giganteus (Mxg) at the lab scale using high liquid-to-solid ratios resulted in the recovery of anthocyanins and enhanced enzymatic digestibility of residual biomass. In this study, the process is scaled up by using a continuous hydrothermal pretreatment reactor operated at a low liquid-to-solid ratio (50 % w/w solids) as an important step towards commercialization. Anthocyanin yield was 70 % w/w at the pilot scale (50 kg of Mxg), compared to the 94 % w/w yield achieved at the lab scale (0.5 g of Mxg). The pretreated biomass was subsequently refined mechanically using a disc mill to increase the accessibility of cellulose by cellulases. Enzymatic saccharification of the pretreated and disc-milled residue yielded 238 g/L sugar concentration by operating in fed-batch mode at 50 % w/v solids content. Two strains of Rhodosporidium toruloides were evaluated for converting the hydrolysate sugars into microbial lipids, and strain Y-6987 had the highest lipid titer (11.0 g/L). Further, the residue left after enzymatic saccharification was determined to be enriched 1.7-fold in the lignin content. This lignin-rich residue has value as a feedstock for the production of sustainable aviation fuel precursors and other high-value lignin-based chemicals. Hence the proposed biorefinery based on Mxg creates an opportunity for generating revenue from multiple high-value products. As the demand for biofuels and biobased products is rising, the biorefinery products from Mxg would create a niche in the industrial sector.

Annotation of untargeted high-resolution full-scan LC-MS metabolomics data remains challenging due to individual metabolites generating multiple LC-MS peaks arising from isotopes, adducts, and fragments. Adduct annotation is a particular challenge, as the same mass difference between peaks can arise from adduct formation, fragmentation, or different biological species. To address this, here we describe a buffer modification workflow (BMW) in which the same sample is run by LC-MS in both liquid chromatography solvent with 14NH3–acetate buffer and in solvent with the buffer modified with 15NH3–formate. Buffer switching results in characteristic mass and signal intensity changes for adduct peaks, facilitating their annotation. This relatively simple and convenient chromatography modification annotated yeast metabolomics data with similar effectiveness to growing the yeast in isotope-labeled media. Application to mouse liver data annotated both known metabolite and known adduct peaks with 95% accuracy. Overall, it identified 26% of ∼27 000 liver LC-MS features as putative metabolites, of which ∼2600 showed HMDB or KEGG database formula match. This workflow is well suited to biological samples that cannot be readily isotope labeled, including plants, mammalian tissues, and tumors.

Data consist of 55 acoustic recordings collected using Autonomous Recording Units (ARUs) from two locations and sampling periods. Specifically, data include 60-minute WAV files (8 folders, each contains 5 WAV files) from a field trial during February 2025 whereby we shot shotguns at varying distance from ARUs at Emiquon Reserve owned by The Nature Conservancy. Data also include 60-minute WAV files (15 WAV files) from one ARU placed at Big Rice Lake State Fish and Wildlife Area on opening day of waterfowl hunting season during 10-26-2024. Filenames include the ARU ID separated by underscores and the associated date and time e.g., MINI10_20241026_060002.wav was from MINI10 on 10/26/24 at 6 AM.

Leesburg, VA to Indianapolis, Indiana: Sampling Rate: 0.1 Hz Total Travel Time: 31100007 ms or 518 minutes or 8.6 hours Distance Traveled: 570 miles via I-70 Number of Data Points: 3112 Device used: Samsung Galaxy S4 Date Recorded: 2017-01-15 Parameters Recorded: * ACCELEROMETER X (m/s²) * ACCELEROMETER Y (m/s²) * ACCELEROMETER Z (m/s²) * GRAVITY X (m/s²) * GRAVITY Y (m/s²) * GRAVITY Z (m/s²) * LINEAR ACCELERATION X (m/s²) * LINEAR ACCELERATION Y (m/s²) * LINEAR ACCELERATION Z (m/s²) * GYROSCOPE X (rad/s) * GYROSCOPE Y (rad/s) * GYROSCOPE Z (rad/s) * LIGHT (lux) * MAGNETIC FIELD X (microT) * MAGNETIC FIELD Y (microT) * MAGNETIC FIELD Z (microT) * ORIENTATION Z (azimuth °) * ORIENTATION X (pitch °) * ORIENTATION Y (roll °) * PROXIMITY (i) * ATMOSPHERIC PRESSURE (hPa) * Relative Humidity (%) * Temperature (F) * SOUND LEVEL (dB) * LOCATION Latitude * LOCATION Longitude * LOCATION Altitude (m) * LOCATION Altitude-google (m) * LOCATION Altitude-atmospheric pressure (m) * LOCATION Speed (kph) * LOCATION Accuracy (m) * LOCATION ORIENTATION (°) * Satellites in range * GPS NMEA * Time since start in ms * Current time in YYYY-MO-DD HH-MI-SS_SSS format Quality Notes: There are some things to note about the quality of this data set that you may want to consider while doing preprocessing. This dataset was taken continuously but had multiple stops to refuel (without the data recording ceasing). This can be removed by parsing out all data that has a speed of 0. The mount for this dataset was fairly stable (as can be seen by the consistent orientation angle throughout the dataset). It was mounted tightly between two seats in the back of the vehicle. Unfortunately, the frequency for this dataset was set fairly low at one per ten seconds.

Indianapolis Int'l Airport to Urbana: Sampling Rate: 2 Hz Total Travel Time: 5901534 ms or 98.4 minutes Number of Data Points: 11805 Distance Traveled: 124 miles via I-74 Device used: Samsung Galaxy S6 Date Recorded: 2016-11-27 Parameters Recorded: * ACCELEROMETER X (m/s²) * ACCELEROMETER Y (m/s²) * ACCELEROMETER Z (m/s²) * GRAVITY X (m/s²) * GRAVITY Y (m/s²) * GRAVITY Z (m/s²) * LINEAR ACCELERATION X (m/s²) * LINEAR ACCELERATION Y (m/s²) * LINEAR ACCELERATION Z (m/s²) * GYROSCOPE X (rad/s) * GYROSCOPE Y (rad/s) * GYROSCOPE Z (rad/s) * LIGHT (lux) * MAGNETIC FIELD X (microT) * MAGNETIC FIELD Y (microT) * MAGNETIC FIELD Z (microT) * ORIENTATION Z (azimuth °) * ORIENTATION X (pitch °) * ORIENTATION Y (roll °) * PROXIMITY (i) * ATMOSPHERIC PRESSURE (hPa) * SOUND LEVEL (dB) * LOCATION Latitude * LOCATION Longitude * LOCATION Altitude (m) * LOCATION Altitude-google (m) * LOCATION Altitude-atmospheric pressure (m) * LOCATION Speed (kph) * LOCATION Accuracy (m) * LOCATION ORIENTATION (°) * Satellites in range * GPS NMEA * Time since start in ms * Current time in YYYY-MO-DD HH-MI-SS_SSS format Quality Notes: There are some things to note about the quality of this data set that you may want to consider while doing preprocessing. This dataset was taken continuously as a single trip, no stop was made for gas along the way making this a very long continuous dataset. It starts in the parking lot of the Indianapolis International Airport and continues directly towards a gas station on Lincoln Avenue in Urbana, IL. There are a couple parts of the trip where the phones orientation had to be changed because my navigation cut out. These times are easy to account for based on Orientation X/Y/Z change. I would also advise cutting out the first couple hundred points or the points leading up to highway speed. The phone was mounted in the cupholder in the front seat of the car.

Arecibo ISR CLP ion-line spectra obtained from RI receiver with 500 kHz bandwidth and 120-640 km altitude range, experiment dates September 23-26, 2016. Used for Mitigation of ion-temperature/composition ambiguity in the inversion of F-region ion-line spectra measured at Arecibo using coded long pulses.

Yarrowia lipolytica was found natively to produce erythritol, mannitol, and arabitol during growth on glucose, fructose, mannose, and glycerol. Osmotic stress is known to increase sugar alcohol production, and was found to significantly increase erythritol production during growth on glycerol. To better understand erythritol production from glycerol, since it was the most promising sugar alcohol, we measured the expression of key genes and intracellular metabolites. Osmotic stress increased the expression of several key genes in the glycerol catabolic pathway and the pentose phosphate pathway. Analysis of intracellular metabolites revealed that amino acids, sugar alcohols, and polyamines are produced at higher levels in response to osmotic stress. Heterologous overexpression of the sugar alcohol phosphatase increased erythritol production and glycerol utilization in Y. lipolytica. We further increased erythritol production by increasing the expression of native glycerol kinase (GK), and transketolase (TKL). These data show the growth and titers produced.

Yarrowia lipolytica has been used to produce both citric acid and lipid-based bioproducts at high titers. In this study, we found that pH differentially affects citric acid and lipid production in Y. lipolytica W29, with citric acid production enhanced at more neutral pH’s and lipid production enhanced at more acid pH’s. To determine the mechanism governing this pH-dependent switch between citric acid and lipid production, we profiled gene expression at different pH’s and found that the relative expression of multiple transporters is increased at neutral pH. These results suggest that this pH-dependent switch is mediated at the level of citric acid transport rather than changes in the expression of the enzymes involved in citric acid and lipid metabolism. In further support of this mechanism, thermodynamic calculations suggest that citric acid secretion is more energetically favorable at neutral pH’s, assuming the fully protonated acid is the substrate for secretion. Collectively, these results provide new insights regarding citric acid and lipid production in Y. lipolytica and may offer new strategies for metabolic engineering and process design.

This repository includes scripts, datasets, and supplementary materials for the study, "NJMerge: A generic technique for scaling phylogeny estimation methods and its application to species trees", presented at RECOMB-CG 2018. The supplementary figures and tables referenced in the main paper can be found in njmerge-supplementary-materials.pdf. The latest version of NJMerge can be downloaded from Github: https://github.com/ekmolloy/njmerge. ***When downloading datasets, please note that the following errors.*** In README.txt, lines 37 and 38 should read: + fasttree-exon.tre contains lines 1-25, 1-100, or 1-1000 of fasttree-total.tre + fasttree-intron.tre contains lines 26-50, 101-200, or 1001-2000 of fasttree-total.tre Note that the file names (fasttree-exon.tre and fasttree-intron.tre) are swapped. In tools.zip, the compare_trees.py and the compare_tree_lists.py scripts incorrectly refer to the "symmetric difference error rate" as the "Robinson-Foulds error rate". Because the normalized symmetric difference and the normalized Robinson-Foulds distance are equal for binary trees, this does not impact the species tree error rates reported in the study. This could impact the gene tree error rates reported in the study (see data-gene-trees.csv in data.zip), as FastTree-2 returns trees with polytomies whenever 3 or more sequences in the input alignment are identical. Note that the normalized symmetric difference is always greater than or equal to the normalized Robinson-Foulds distance, so the gene tree error rates reported in the study are more conservative. In njmerge-supplementary-materials.pdf, the alpha parameter shown in Supplementary Table S2 is actually the divisor D, which is used to compute alpha for each gene as follows. 1. For each gene, a random value X between 0 and 1 is drawn from a uniform distribution. 2. Alpha is computed as -log(X) / D, where D is 4.2 for exons, 1.0 for UCEs, and 0.4 for introns (as stated in Table S2). Note that because the mean of the uniform distribution (between 0 and 1) is 0.5, the mean alpha value is -log(0.5) / 4.2 = 0.16 for exons, -log(0.5) / 1.0 = 0.69 for UCEs, and -log(0.5) / 0.4 = 1.73 for introns.

This dataset includes images and extracted centerlines from experiments looking at the formation and evolution of meltwater meandering channels on ice. The laboratory data includes centimeter- and millimeter-scale rivulets. Dataset also includes an image and corresponding centerlines from the Peterman Ice Island. All centerlines were manually digitized in Matlab but no distributable code was developed for the process. Once digitized, centerlines were smoothed and standardized following methods and routines developed by other authors (Zolezzi and Guneralp, 2016; Guneralp and Rhoads, 2008). Details about the preparation of the centerlines and processing with these methods is included in the dissertation by Fernández (2018) linked to this dataset. "Millimeter scale and Peterman Ice Island centerlines.pdf": This file includes the images of two mm-scale experimetns and the Peterman Ice Island image. Seventeen centerlines were digitized from the former and seven were digitized from the latter. Those centerlines are shown above the images themselves. "Centimeter scale rivulet images.pdf": This file includes images corresponding to all cm-scale centerlines used for the analysis presented in the dissertation by Fernandez (2018). Each image has a short caption indicating the run ID and the time at which it was captured. The images were used to extract centerlines to look at the planform evolution of cm-scale meltwater meandering rivulets on ice. Images include 26 centerlines from four different runs. "Meltwater meandering channel centerlines.xlsx": This spreadsheet contains the centerline data for all fifty centerlines. The workbook includes 51 sheets. The first 50 are related to each one of the channels. The mm scale and Peterman Ice Island ones are identified using the same IDs shown in "Millimeter scale and Peterman Ice Island centerlines.pdf". The cm-scale centerlines are identified by run ID and a number indicating the time in minutes (with t = 0 min being the time at which water started flowing over the ice block). The naming convention is also associated to the images in "Centimeter scale rivulet images.pdf". The last sheet in the workbook includes a summary of the channel widths measured from every image for each centerline. The 50 sheets with the centerline information have four columns each. The titles of the columns are X, Y, S, and C. X,Y are dimensionless coordinates of the centerline. S is dimensionless streamwise coordinate (location along the centerline). C is dimensionless curvature value. All these values were non-dimensionalized with the channel width. See Fernandez (2018), Zolezzi and Guneralp (2016), and Guneralp and Rhoads (2008) for more details regarding the process of smoothing, standardizing and non-dimensionalization of the centerline coordinates.

#### Details of Pseudomonas aeruginosa biofilm dataset #### ----------------*Folder Structure*------------------------------------- This dataset contains peak intensity tables extracted from mass spectrometry imaging (MSI) data using tools, SCiLS and MSI reader. There are 2 folders in "MSI-Data-Paeruginosa-biofilms-UIUC-DP-JVS-July2022.zip", each folder contains 3 sub-folders as listed below. 1. PellicleBiofilms-and-Supernatant [Pellicle biofilms collected from air-liquid interface and spend supernatant medium after 96 h incubation period]: (1) Full-Scan-Data-96h; (2) MSMS-data-from-C7-Quinolones-96h; and (3) MSMS-data-from-C9-Quinolones-96h 2. StaticBiofilms [Static biofilms grown on mucin surface]: (1) Full-Scan-Data; (2) MSMS-data-from-C7-Quinolones; and (3) MSMS-data-from-C9-Quinolones ----------------*File name*---------------------------------------------- Sample information is included in the file names for easy identification and processing. Attributes covered in file names are explained in the example below. *Example file name "Rep1-Stat-FRD1-mPat-48-FS"* ~ Each unit of information is separated by "-" ~Unit 1 - "Rep1" - Biological replicate ( Rep1, Rep2, and Rep3) ~Unit 2 - "Stat" - Sample type (Stat = Static Biofilm, Pel = Pellicle biofilm, Sup = Supernatant) ~Unit 3 - "FRD1" - Strain (FRD1 = Mucoid strain, PAO1C = Non-mucoid strain) ~Unit 4 - "mPat" - Type of mucin surface used (mPat = patterned mucin surface, mUni = uniform mucin surface) ~Unit 5 - "48" - Sample time point (hours = 48, 72, 96) ~Unit 6 - "FS" - Scan type used in MSI (FS = high resolution full-scan, 260 = targeted MS/MS of C7 quinolones (m/z 260), 288 = targeted MS/MS of C9 quinolones (m/z 288)) ----------------*File structure*------------------------------------------ All MSI data has been exported to CSV format. Each CSV files contains information about scan number, Coordinates (x,y,z), m/z values, extraction window (absolute), and corresponding intensities in the form of a matrix. ----------------*End of Information*--------------------------------------

This dataset contains the raw nuclear background radiation data collected in the engineering campus of University of Illinois at Urbana-Champaign. It contains three columns, x, y, and counts, which corresponds to longitude, latitude, and radiation count rate (counts per second). In addition to the original background radiation data, there are several separate files that contain the simulated radioactive sources. For more detailed README file, please refer to this documentation: <a href= "https://www.dropbox.com/s/xjhmeog7fvijml7/README.pdf?dl=0">https://www.dropbox.com/s/xjhmeog7fvijml7/README.pdf?dl=0</a>

This data contains bam files and transcripts in the simulated instances generated for the paper 'JUMPER: Discontinuous Transcript Assembly in SARS-CoV-2' submitted for RECOMB 2021. The folder 'bam' contained the simulated bam files aligned using STAR wile the reads were generated using the method polyester Note: in the readme file, close to the end of the document, please ignore this sentence: 'Those files can be opened by using [name of software].'

This dataset contains the emulated global multi-model urban climate projections under RCP 8.5 and RCP 4.5 used in the article "Global multi-model projections of local urban climates" (https://www.nature.com/articles/s41558-020-00958-8). Details about this dataset and the local urban climate emulator are described in the article. This dataset documents the monthly mean projections of urban temperatures and urban relative humidity of 26 CMIP5 Earth system models (ESMs) from 2006 to 2100 across the globe. This dataset may be useful for multiple communities regarding urban climate change, impacts, vulnerability, risks, and adaptation applications.

Corbicula spp. are one of the most prolific aquatic invasive species in the world and can have negative effects on aquatic ecosystems. We performed qualitative field surveys, examined literature accounts and natural history museum holdings, and accessed citizen science data sources to document the distribution of Corbicula in Mexico and shared drainages. Through 26 publications (N = 127 records), 312 museum holdings, and 446 iNaturalist records, we documented 885 records pertaining to Corbicula in Mexico and shared drainages. The first record of the species in Mexico was in 1969, and it has since been reported from 26 of the 32 Mexican states and most of the major river basins throughout the country. However, we suggest Corbicula is more prevalent in Mexico than we report in this work as it is often under sampled / under reported.

This dataset contains raw data associated with the red fox Y-chromosome assembly (see https://doi.org/10.3390/genes10060409). It includes a fasta file of the 171 scaffolds from the red fox reference genome assembly identified as likely to contain Y-chromosome sequence, the raw BLAST results, and the ABySS assemblies described in the manuscript.

¹²CO and ¹³CO maps for six molecular clouds in the Large Magellanic Cloud, obtained with the Atacama Large Millimeter/submillimeter Array (ALMA). See the associated article in the Astrophysical Journal, and README files within each ZIP archive. Please cite the article if you use these data.

Dataset with numerical routines and laboratory testing data associated with the manuscript: Bondarenko, N., Podladchikov, Y., Williams‐Stroud, S., & Makhnenko, R. (2025). Stratigraphy‐induced localization of microseismicity during CO2 injection in Illinois Basin. Journal of Geophysical Research: Solid Earth, 130, e2024JB029526. https://doi.org/10.1029/2024JB029526

Glucose and xylose are the major sugars present in cellulosic hydrolysates. The cellulosic sugars can be used for the production of platform chemicals. In this study, productions of lipid and ethanol by yeasts were compared for concentrated bioenergy sorghum syrup. Bioenergy sorghum was hydrothermally pretreated at 50% w/w solids in a continuous industrial reactor and sequentially mechanically refined using a burr mill to improve biomass accessibility for hydrolysis. Fed-batch enzymatic hydrolysis was conducted with 50% w/v solids loading and cellulase cocktail (50 FPU/g biomass) to achieve 230 g/L sugar concentration. Various strains of Rhodosporidium toruloides were evaluated for converting sugars into lipids, and strain Y-6987 had the highest lipid titer (9.2 g/L). The lipid titer was improved to 19.0 g/L by implementing a two-stage culture scheme, where the first stage was optimized for yeast growth and the second for lipid production. For ethanol production, the engineered Saccharomyces cerevisiae SR8ΔADH6 was used to coferment glucose and xylose. Ethanol fermentation was optimized for media nutrients (YP, YNB/urea, and urea), cellulosic sugar concentration, and sulfite conditioning to maximize the ethanol concentration from sorghum syrups. Fermentation of 70% v/v concentrated hydrolysate conditioned with sulfite produces 50.1 g/L ethanol from 141 g/L of sugars.

This dataset contains all the data for the results section in the study presented in the paper entitled "Chemistry Across Multiple Phases (CAMP) version 1.0: An integrated multi-phase chemistry mode" submitted to Geoscientific Model Development (GMD). In this paper, two sets of simulations were run to test CAMP with this results included here. This consists of (1) box model inputs and outputs presented in Section 4.2 for modal, binned and particle-resolved simulations to compare the application of identical chemical mechanisms to different aerosol representations and (2) the 3D Eulerian output presented in Section 4.3.

These data were used to make a predictive model of when ornate box turtles (Terrapene ornata) are likely to be above ground and at risk from fire. The data were generated using shell temperatures, soil temperatures at 0.35 m deep from known overwintering sites, and the spring and fall soil temperature inversion dates during 2019–2022 to infer if 26 individual radio-tracked turtles were above or below ground at three sites in Illinois.

References - Li, Fu, Umberto Villa, Seonyeong Park, and Mark A. Anastasio. "3-D stochastic numerical breast phantoms for enabling virtual imaging trials of ultrasound computed tomography." IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 69, no. 1 (2021): 135-146. DOI: 10.1109/TUFFC.2021.3112544 - Li, Fu; Villa, Umberto; Park, Seonyeong; Anastasio, Mark, 2021, "2D Acoustic Numerical Breast Phantoms and USCT Measurement Data", https://doi.org/10.7910/DVN/CUFVKE, Harvard Dataverse, V1 Overview - This dataset includes 1,089 two-dimensional slices extracted from 3D numerical breast phantoms (NBPs) for ultrasound computed tomography (USCT) studies. The anatomical structures of these NBPs were obtained using tools from the Virtual Imaging Clinical Trial for Regulatory Evaluation (VICTRE) project. The methods used to modify and extend the VICTRE NBPs for use in USCT studies are described in the publication cited above. - The NBPs in this dataset represent the following four ACR BI-RADS breast composition categories: > Type A - The breast is almost entirely fatty > Type B - There are scattered areas of fibroglandular density in the breast > Type C - The breast is heterogeneously dense > Type D - The breast is extremely dense - Each 2D slice is taken from a different 3D NBP, ensuring that no more than one slice comes from any single phantom. File Name Format - Each data file is stored as an HDF5 .mat file. The filenames follow this format: {type}{subject_id}.mat where{type} indicates the breast type (A, B, C, or D), and {subject_id} is a unique identifier assigned to each sample. For example, in the filename D510022534.mat, "D" represents the breast type, and "510022534" is the sample ID. File Contents - Each file contains the following variables: > "type": Breast type > "sos": Speed-of-sound map [mm/μs] > "den": Ambient density map [kg/mm³] > "att": Acoustic attenuation (power-law prefactor) map [dB/ MHzʸ mm] > "y": power-law exponent > "label": Tissue label map. Tissue types are denoted using the following labels: water (0), fat (1), skin (2), glandular tissue (29), ligament (88), lesion (200). - All spatial maps ("sos", "den", "att", and "label") have the same spatial dimensions of 2560 x 2560 pixels, with a pixel size of 0.1 mm x 0.1 mm. - "sos", "den", and "att" are float32 arrays, and "label" is an 8-bit unsigned integer array.