cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6229071
title: Segmentation Zoo Res-UNet models for Landsat-8 satellite imagery, Coast Train v1 Landsat-8 4-class subset.

description: <strong>Doodleverse/Segmentation Zoo models for Landsat-8 satellite imagery, Coast Train v1 Landsat-8 4-class subset.</strong> These model data are based on the Coast Train v1 Landsat-8 labeled imagery subset. Models have been fitted to 4 different types of data 1. NDWI (1 band): (g-nir)/(g+nir) 2. MNDWI (1 band): (swir-g)/(swir+g) 3. RGB (3 band): red, green, blue 4. RGB-NIR-SWIR (5 band): red, green, blue, nir, swir Classes are: {0: water, 1: whitewater, 2:sediment, 3:other}. These classes have been remapped from the original 11 classes<br> These files are used in conjunction with Segmentation Zoo* For each model, there are 3 files: 1. config file: this is the file that was used by Segmentation Gym** to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse. 2. weights file: this is the file that was created by the Segmentation Gym** function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym** function `seg_images_in_folder.py` or the Segmentation Zoo* function `select_model_and_batch_process_folder.py` to segment a folder of images 3. model card file: this is a json file containing the following fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata References * https://github.com/Doodleverse/segmentation_zoo ** https://github.com/Doodleverse/segmentation_gym
DOI: 10.5439/1095601
title: ARM: Ka ARM Zenith Radar (KAZR): moderate sensitivity mode

description: Ka ARM Zenith Radar (KAZR): moderate sensitivity mode
DOI: 10.5517/ccdc.csd.cc1pffn6
title: CCDC 1562048: Experimental Crystal Structure Determination

description: Related Article: Frank R. Fronczek|2017|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.6108672
title: differential harvest problem source + data + results

description: - source codes (ILP, CP, LocalSolver, VRPSolver)<br> - instance files<br> - result files
DOI: 10.5281/zenodo.7099164
title: Large zero bias peaks and dips in a four-terminal thin InAs-Al nanowire device

description: This file contains the raw data and processing codes of the paper 'Large zero bias peaks and dips in a four-terminal thin InAs-Al nanowire device'.
DOI: 10.15124/crd42015025193
title: The health benefits of the great outdoors: a systematic review of greenspace exposure and health outcomes

description: Systematic review protocol registration
DOI: 10.17632/4y32ks2t62.2
title: Oil Palm Empty Fruit Bunch (OPEFB) Fiber Length

description: This file provides five primary data sets on the length of oil palm empty fruit bunch (OPEFB) fibers resulting from conditioning processes, i.e., grinding and sieving.
DOI: 10.17632/5498jdrm87.1
title: SAFmaps - Macaw palm

description: Developed in the context of SAFmaps containing the georeferenced database and a case study report on SAF production based on the HEFA-SPK / macaw palm pathway. SAFmaps is a database platform with information on the potential of promising feedstock for the production of Sustainable Aviation Fuels (SAF) in Brazil. SAFmaps includes a database of different feedstocks, background information and assessment results.
DOI: 10.5061/dryad.1jd40.2
title: Data from: Similarity in temporal variation in sex-biased dispersal over short and long distances in the dark-eyed junco, Junco hyemalis
DOI: 10.5281/zenodo.6207765
title: Measurements of water levels and water temperature profiles in Lake Kinneret, in summer, during the period (2000 – 2020)

description: <em>The datasets include measurements of water levels and water temperature profiles in Lake Kinneret, in summer, during the period (2000 – 2020). </em><em>Lake Kinneret is located in Israel. </em>Shipboard measurements of water temperature profiles were taken at the deepest point of ~40 m near the lake center (32.82 N; 35.60 E). The <em>AML MINOS X probe was used (specifications are available online at https://geo-matching.com/ctd-systems/minos-x-ctd/svp). </em><em>Data of water temperature profiles are associated with the Kinneret Limnological Laboratory, Israel Oceanographic and Limnological Research (</em><em>http://kinneret.ocean.org.il/ar_3d_vb.aspx</em><em> ). Data of Lake Kinneret water levels are associated with the Israel Water and Sewage Authority (</em>https://www.gov.il/en/departments/water_authority/govil-landing-page<em> ). Data format: xlsx file. </em>There are two sheets in the Excel file: the first sheet includes water temperature profiles, while the second sheet includes lake water levels, in summer, during the period (2000 – 2020).
DOI: 10.5281/zenodo.6774534
title: Data set for the shells excavated at the Liang Abu site (East Kalimantan, Indonesia)

description: Data set for the 2431 shell excavated at the Liang Abu site (East Kalimantan, Indonesia).
DOI: 10.5517/ccdc.csd.cc1pffp7
title: CCDC 1562049: Experimental Crystal Structure Determination

description: Related Article: Frank R. Fronczek|2017|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccs7hm3
title: CCDC 722195: Experimental Crystal Structure Determination

description: Related Article: Amir Lashgari, Shahriar Ghamami|2014|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.19782643
title: Supplementary data: Associations of Alboglossiphonia leeches (Hirudinea: Glossiphoniidae) with sedentary animals and molluscs

description: This dataset contains supplementary data for the article "Hidden shelter-like associations of minute Alboglossiphonia leeches (Hirudinea: Glossiphoniidae) with sedentary animals and molluscs" as follows: <br> <strong>Table S1. </strong>Measurements of sponge-dwelling and free-living samples of <em>Alboglossiphonia pahariensis</em> Nesemann & Sharma, 2007 (Hirudinea: Glossiphoniidae) from Northern India (ethanol-preserved animals) [XLSX] <br> <strong>Table S2.</strong> Information on additional DNA sequences of <em>Alboglossiphonia</em> species used in this study (GenBank accession numbers of newly generated sequences are bold) [PDF]
DOI: 10.5066/f7kw5d32
title: DNA fingerprinting of Southern Mule Deer (Odocoileus hemionus fuliginatus) to determine movement across California State Route 67

description: The goal of this project was to primarily assess east-west connectivity across Route 67 and secondarily, north-south connectivity across Scripps Poway Parkway and Poway Road, two highly trafficked roads to the west of Route 67. We collected deer scat piles from both sides of these crossings in spring between March and June of 2015, and again in fall throughout October 2015. Collected pellets were extracted and amplified using protocols and loci developed by Bohonak and Mitelberg (2014). DNA fingerprinting results were used to investigate mule deer movement in the region directly by identifying individuals which had been captured multiple times throughout the study period. We also assessed movement indirectly through pedigree reconstruction and population structure analyses. This file contains 126 deer scat piles and the genotypes obtained at 15 microsatellite markers and one sex specific genetic marker. These represented 71 unique individual genotypes (45 females, 26 males) with 9 recapture events and 46 resampling events (defined as scat piles collected at the same location within one week of each other and matching the same unique genotype).
DOI: 10.5281/zenodo.2554344
title: Evaluation of Envision Rating System for Underground Transportation Infrastructure

description: Credit-by-credit evaluation of the Envision rating system for representative underground transportation projects. Related paper presented at the 2019 International Conference for Sustainable Infrastructure.
DOI: 10.5281/zenodo.3929562
title: Data set for the pottery excavated at the Liang Abu site (East Kalimantan, Indonesia)

description: A table describing 1105 pottery sherds excavated at the Liang Abu site (Est Kalimantan, Indonesia).
DOI: 10.5281/zenodo.4719577
title: Refitting pottery fragments from the Liang Abu rockshelter, Borneo

description: Liang Abu is an archaeological site in East Kalimantan, Indonesia. This dataset describes the relationships between pottery fragments found during excavations (2009-2012). Two types of relationships are defined. A <strong>connection</strong> relationship refers to a physical connection between two fragments that were part of the same object. A <strong>similarity</strong> relationship between fragments is defined if there is an acceptable likelihood that those fragments were part of the same object. The dataset is composed of three tables: <strong>relations-connection.csv</strong> (56x2): "connection" relationships between fragments. matrix. Each line describes a connection relationship between two fragments. There respective unique identifiers are given in column "frg_id1" and in column "frg_id2". <strong>relations-similarity.csv</strong> (47x2): "similarity" relationships between fragments. matrix. Column "frg_id" gives a fragment unique identifier, column "su_id" gives a unique identifier for the group of similar fragments it belongs to (similarity unit). <strong>fragments.csv</strong> (177x8): contextual information concerning each fragment, with the following columns: <em>frg_id</em>: unique fragment identifier <em>layer</em>: stratigraphic layer <em>zmin</em>: minimal depth in centimetres where the fragment was found <em>zmax</em>: maximal depth in centimetres where the fragment was found <em>square</em>: square where the fragment was found <em>sherd.type</em>: type of pottery sherd <em>thickness</em>: thickness of the fragments in millimetres <em>length</em>: length of the fragments in millimetres
description: {"references": ["Plutniak, Sebastien, Astolfo Araujo, Simon Puaud, Jean-Georges Ferrie, Adhi Agus Oktaviana, Bambang Sugiyanto, Jean-Michel Chazine et Francois-Xavier Ricaut. 2015. \"Borneo as a half empty pot: Pottery assemblage from Liang Abu, East Kalimantan, Quaternary International, doi: 10.1016/j.quaint.2015.11.080."]}
DOI: 10.5281/zenodo.6774530
title: Data set for the fauna material excavated at the Liang Abu site (East Kalimantan, Indonesia)

description: Data set for the fauna material excavated at the Liang Abu site (East Kalimanta, Indonesia): count by subphylum, class, order, family, genus, and species for the squares 11Ec, 11Ed, and12Eb.
DOI: 10.6084/m9.figshare.9122528.v1
title: Gallant et al. datasets for study "Disentangling the relative influences of global drivers of change in biodiversity: a study of the twentieth-century red fox expansion into the Canadian Arctic"

description: Gallant et al. datasets for study "Disentangling the relative influences of global drivers of change in biodiversity: a study of the twentieth-century red fox expansion into the Canadian Arctic"
DOI: 10.5066/p9wr0vb1
title: Aerial Imagery of the North Carolina Coast: 2019-08-30 and 2019-09-02, Pre-Hurricane Dorian

description: The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal vulnerability and response to disturbance events. A nadir (vertical) aerial imagery survey was conducted from Cape Lookout, North Carolina to the Virginia-North Carolina border on August 30th and September 2nd, 2019, to document pre-storm conditions in preparation for the passing of Hurricane Dorian. The observations along the coastline cover an approximately 275-kilometer-long by 300 to 700-meter-wide swath of coastline and encompass both highly developed towns as well as natural, undeveloped areas, including the federal lands of Cape Lookout National Seashore and Cape Hatteras National Seashore. Low altitude (300 meters above ground level) digital aerial imagery were acquired from a manned, fixed-wing aircraft using a Sony A7R 36 Megapixel digital camera, along with precise aircraft navigation Global Navigation Satellite System (GNSS) data. Data were collected in shore-parallel lines, flying at approximately 50 meters per second and capturing true color imagery at 1 Hertz, resulting in image footprints with approximately 75-80% endlap, 60-70% sidelap, and a ground sample distance (GSD) of 5.3 centimeters. The precise time of each image capture (flash event) was recorded, and the corresponding aircraft position was computed in post-processing from the aircraft navigation GNSS data; precise image positions can then be determined by accounting for the lever arm offsets between the aircraft GNSS antenna and the camera lens. Position data, provided as latitude/longitude/ellipsoid height, is referenced to the North American Datum of 1983 (NAD83(2011)).
DOI: 10.5281/zenodo.3929614
title: "Chronomodel" Bayesian chronological models for East Borneo, based on data from the Liang Abu and Kimanis sites

description: Bayesian chronological models generated using the <em>ChronoModel</em> software East Borneo (Indonesia), based on data from the Liang Abu and Kimanis (Arifin, 2017) archaeological sites. Two models were generated: a “<strong>conservative</strong>” model, observing the Bayesian approach and the distinction between<br> prior and posterior information; a “<strong>restricted</strong>” model: excluding possible outliers and without application of a “Fresh-<br> water reservoir effect” correction. Four files are provided: abu-kimanis-conservative-model.chr: model specification for the “conservative” model abu-kimanis-conservative-model_synthetic-stats-table.csv: results for the “conservative” model abu-kimanis-restricted-model.chr: model specification for the “restricted” model abu-kimanis_restricted-model_synthetic-stats-table.csv: results for the “restricted” model The .chr files can be open and edited using the <em>ChronoModel</em> software.
description: {"references": ["Arifin, K. 2017. \"Terminal Pleistocene and Early Holocene Human Occupation in the Rainforests of East Kalimantan,\" in New Perspectives in Southeast Asian and Pacific Prehistory, ed. by P. J. Piper, H. Matsumura, and D. Bulbeck, Acton: ANU Press, p. 97-124."]}
DOI: 10.13020/d6ph49
title: DynamoVis - Dynamic Visualization of Animal Movement Data

description: Exploring movement, as an important aspect of spatiotemporal processes, has gained new momentum from the availability of large spatiotemporal datasets. This has given rise to the development of new exploratory and analytical techniques to generate new insight into dynamic processes and the spatiotemporal context in which they operate. This study develops a new dynamic visualization tool, called ``DYNAMOVis: Dynamic Visualization of Movement'', developed for the exploratory analysis of movement in relation to the environment and geographic context. DYNAMOVis applies visual variables such as point and line width, color, and directional vector to visualize movement tracks in their attribute space (e.g. movement parameters and context attributes). 
Using real case studies from Movement Ecology, we show how hybrid and dynamic visualizations can strengthen spatiotemporal research by facilitating data exploration, generating new hypotheses, discovery of patterns and dependencies, as well as promoting interdisciplinary research collaborations.
DOI: 10.5281/zenodo.6367850
title: Variability in Antarctic Surface Climatology Across Regional Climate Models and Reanalysis: Datasets

description: This dataset includes output for snowfall, near-surface air temperature and melt from the following regional climate models (RCMs): Met Office Unified Model version 11.1 (MetUMv11.1), the Modèle Atmosphérique Régional version 3.10 (MARv3.10) and the Regional Atmospheric Climate Model version 2.3p2 (RACMOv2.3p2). The data is aggregated to monthly timesteps from initial 3/6hourly data. The code for aggregation is available here: https://github.com/Jez-Carter/Antarctica_Climate_Variability . Data goes from ~1971-2018 and includes two simulations from each RCM: 0.11° (12.25 km) and 0.44° (49 km) resolution simulations from the MetUM; ERA-Interim and ERA5 driven simulations from MAR and RACMO. The data used in the results for 'Variability in Antarctic Surface Climatology Across Regional Climate Models and Reanalysis Datasets' J.Carter et al, is included here and can be generated using the code available here: https://github.com/Jez-Carter/Antarctica_Climate_Variability . <strong>Data usage notice:</strong><br> If you use any of these results, please acknowledge the work of the people involved in producing them. Acknowledgements should have language similar to the below. "We thank C. Kittel and the MAR team which make available the model outputs, as well agencies (F.R.S - FNRS, CÉCI, and the Walloon Region) that provided computational resources for MAR simulations." In order to document MAR scientific impact and enable ongoing support of the model, users are encouraged to contact C. Kittel to add their works in the list of MAR-related publications. If you need other variables or output frequencies over Antarctica from: MAR, contact C.Kittel (c2kittel@gmail.com); RACMO, contact J.M. van Wessem; MetUM, contact A.Orr.
DOI: 10.5281/zenodo.6801033
title: Data for the publication: A parameterization of cirrus cloud formation: Revisiting competing ice nucleation

description: The files contain the data sets shown in the publication "A parameterization of cirrus cloud formation: Revisiting competing ice nucleation" to appear in J. Geophys. Res. Atmos. in 2022 (revised manuscript submitted) The files include a power point slide containing the schematic and xmgrace plot files containing the research data (ASCII) shown in all other figures that appear in the paper and its appendix.
DOI: 10.5281/zenodo.6687723
title: CPineMarineEcology/Blue-Groper-Oyster-Reef-Data: Blue Groper Oyster Reef Data

description: Data for the paper titled "Observation of Juvenile Eastern Blue Groper (Achoerodus viridis) on Remnant Oyster Reefs in New South Wales, Australia." by Pine et al. (2022) published in <em>Ecology</em> - in <em>The Scientific Naturalist</em> section.
DOI: 10.5281/zenodo.6774519
title: Data set for the lithic material excavated at the Liang Abu site (East Kalimantan, Indonesia)

description: Three tables describing the lithic material excavated at the Liang Abu site (East Kalimantan, Indonesia): abu-lithic-class.csv: count by class by stratigraphic layer abu-lithic-spatial-distribution.csv: count by square and stratigraphic layer abu-lithic-flakes.csv: morphometric values of the flakes
DOI: 10.5281/zenodo.7074190
title: Supplementary File_Nirmatrelvir_Research Integrity Assessment (Version 1)

description: Supplementary material (Research Integrity Assessment Tool (Version 1)) for the Cochrane Review "Nirmatrelvir combined with ritonavir for preventing and treating COVID-19".
DOI: 10.5281/zenodo.7081229
title: Processed data for "Effects of Anthropogenic Forcings on Multidecadal Variability of the Sea Level around the Japanese Coast Simulated by MRI-ESM2.0 for CMIP6"

description: Processed data for "Effects of Anthropogenic Forcings on Multidecadal Variability of the Sea Level around the Japanese Coast Simulated by MRI-ESM2.0 for CMIP6" submitted to Geophysical Research Letters. Detailed information is described in README.txt in the zip file.
DOI: 10.6084/m9.figshare.20098148.v1
title: Intra-facility_maternal_deaths_Lagos_2018-2019.csv

description: Maternal and perinatal deaths that occurred amongst pregnant women who presented in the emergency room of the 24 public hospitals providing emergency obstetric care (EmOC) in Lagos, Nigeria between 1st November 2018 and 30th October 2019 were identified. Specifically, maternal death was defined as “the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management, but not from accidental or incidental causes”. Perinatal death was defined as a foetal death occurring on or after 28-week gestation but before birth or neonatal death within seven days of life. Amongst these women, data on demographic characteristics, obstetric history, travel to the hospital, obstetric complication (as defined in the WHO’s Monitoring EmOC guidelines), and mode of birth were extracted. Based on the travel data extracted from the patient records, additional data were collected to estimate the driving distance (in kilometres (km)) and travel time (in minutes (mins)) of the pregnant women to the hospital using Google Maps (Alphabet Inc., Mountain View, California, US), which offers closer-to-reality estimates. To map the journeys in Google Maps, the street name of women’s self-reported addresses and referral points were geo-referenced for each woman who had traceable journeys in the application. The ‘typical time of travel’ feature in Google Maps was used for the period of the day of travel for specific time slots (9.00 a.m., 3.00 p.m., 6.00 p.m., and 9.00 p.m. for morning, afternoon, evening, or night journeys, respectively), based on awareness of peak and non-peak travel periods in Lagos. A check was subsequently conducted in Google Maps to ascertain whether there was an alternative public hospital closer to the pregnant woman’s self-reported address for the period of the day of travel to care. Data were processed in Microsoft Excel.