cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5597764
title: Trinity assembly of Downy mildew of Grapevine lesion samples DMG-E

description: De novo Trinity assembly of RNAseq NGS data
DOI: 10.1594/pangaea.807490
title: Total flux, particulate carbon and nitrogen flux measured on water bottle samples during Sagar Kanya cruise SK121
DOI: 10.1594/pangaea.842547
title: (Table 1) Ice thickness at lake Nam Co, Tibet, during 2008-2009

description: Lake ice change is one of the sensitive indicators of regional and global climate change. Different sources of data are used in monitoring lake ice phenology nowadays. Visible and Near Infrared bands of imagery (VNIR) are well suited for the observation of freshwater ice change, for example data from AVHRR and MODIS. Active and passive microwave data are also used for the observation of lake ice, e.g., from satellite altimetry and radiometry, backscattering coefficient from QuickSCAT, brightness temperature (Tb) from SSM/I, SMMR, and AMSR-E. Most of the studies are about lake ice cover phenology, while few studies focus on lake ice thickness. For example, Hall et al. using 5 GHz (6 cm) radiometer data showed a good relationship between Tb and ice thickness. Kang et al. found the seasonal evolution of Tb at 10.65 GHz and 18.7 GHz from AMSR-E to be strongly influenced by ice thickness. Many studies on lake ice phenology have been carried out since the 1970s in cold regions, especially in Canada, the USA, Europe, the Arctic, and Antarctica. However, on the Tibetan Plateau, very little research has focused on lake ice-cover change; only a small number of published papers on Qinghai Lake ice observations. The main goal of this study is to investigate the change in lake ice phenology at Nam Co on the Tibetan Plateau using MODIS and AMSR-E data (monitoring the date of freeze onset, the formation of stable ice cover, first appearance of water, and the complete disappearance of ice) during the period 2000-2009.
description: Data extracted in the frame of a joint ICSTI/PANGAEA IPY effort, see http://doi.pangaea.de/10.1594/PANGAEA.150150
description: Supplement to: Ye, Qinghua; Wei, Qiufang; Hochschild, Volker; Duguay, Claude R (2011): Integrated observations of lake ice at Nam Co on the Tibetan Plateau from 2001 to 2009. IGARSS 2011, IEEE International Geoscience and Remote Sensing Symposium, 24-29 July 2011, Vancouver, British Columbia, Canada, 3217-3220
DOI: 10.5281/zenodo.6371330
title: Biotic and abiotic drivers of coalescence asymmetry between soil and manure microbiomes

description: The dataset includes bacterial and fungal OTU tables for all soil and manure samples after 180 days incubation, bacterial and fungal OTU abundance tables, and data for variance partitioning analysis.
DOI: 10.5281/zenodo.6512353
title: IODP Expedition 372A Photomicrographs

description: Microscopic images of discrete samples were acquired using stereo and upright light microscopes and captured on digital cameras. Image files were uploaded along with a brief description and a record of the microscopic and lighting conditions when the image was taken.
DOI: 10.1594/pangaea.671506
title: Physical oceanography at station M62/5b-1255-CTD-LADCP

description: Depth calculated from pressure, algorithm by M. Walter
DOI: 10.1594/pangaea.833350
title: Scarp scan using terrestrial LiDAR at Spili Falut
DOI: 10.5281/zenodo.1215659
title: Rfid Location Dataset

description: The dataset includes measurements with a robot equipped with RFID antennas in a library enclosing 7000 tagged books with known locations.
DOI: 10.5281/zenodo.4635732
title: xPore: Detection of differential RNA modifications from direct RNA sequencing of human cell lines

description: xPore is a Python package for identification and quantification of differential RNA modifications from direct RNA sequencing. The detailed usage is documented at https://xpore.readthedocs.io/en/latest, while all scripts and source code are available at https://github.com/GoekeLab/xpore. All the preprocessed datasets used in the paper are provided here. Please cite our paper below when using these data.<br> Ploy N. Pratanwanich et al. "Detection of differential RNA modifications from direct RNA sequencing of human cell lines." bioRxiv (2020).
description: {"references": ["Ploy N. Pratanwanich et al. \"Detection of differential RNA modifications from direct RNA sequencing of human cell lines.\" bioRxiv (2020)."]}
DOI: 10.1594/pangaea.433524
title: Hourly sea level from coastal tide gauge station Beihai in 1984 (Research quality database)
DOI: 10.1594/pangaea.942321
title: Deep Fmask Dataset: Labeled dataset for Cloud, Shadow, Clear-Sky Land, Snow and Water Segmentation of Sentinel-2 Images over Snow and Ice Covered Regions

description: We present our dataset containing images with labeled polygons, annotated over Sentinel-2 L1C imagery from snow and ice-covered regions. We use similar labels as the Fmask cloud detection algorithm, i.e., clear-sky land, cloud, shadow, snow, and water. We annotated the labels manually using the QGIS software. The dataset consists of 45 scenes divided into validation (22 scenes) and test datasets (23 scenes). The source images were captured by the satellite between October 2019 and December 2020. We provide the list of '.SAFE' filenames containing the satellite imagery and these files can be downloaded from the Copernicus Open Access Hub. The dataset can be used to test and benchmark deep neural networks for the task of cloud, shadow, and snow segmentation.
description: The zip file contains the following:- label_mapping.txt - This file contains the mapping from labels used in the annotation to the class names.- test_SAFE_filenames.txt - This file contains the '*.SAFE' filenames that are part of the test dataset.- test_labels.zip - This zip file contains 23 '*.TIF' images that contain the labeled polygons for the Sentinel-2 imagery listed test_SAFE_filenames.txt- validation_SAFE_filenames.txt - This file contains the '*.SAFE' filenames that are part of the test dataset.- validation_labels.zip - This zip file contains 22 '.TIF' images that contain the labeled polygons for the Sentinel-2 imagery listed validation_SAFE_filenames.txt
DOI: 10.5281/zenodo.4288605
title: Digitized patient level time to event data of overall survival

description: This dataset contains digitized patient level time to event data for overall survival of patients with locally advanced and metastatic (stage IIIB/IV) Non-small cell lung cancer (NSCLC). The data can be used to recreate the original Kaplan-Meier survival curves that were published in randomized controlled trials, in order to perform secondary analysis on the survival data. In order to recreate a survival curve, you need two csv.files per trial arm that are in this <br> database: (1) starting with 'surv_', containing the individual patient level time to event data, and (2) starting with 'natrisk_', containing the corresponding numbers at risk table. For the methodology and r-code that can be used for this purpose we refer to article that is linked to this dataset.
description: The "Technology Assessment of Next Generation Sequencing in Personalized Oncology" (TANGO) project is funded by the ZonMw Personalised Medicine Programme under Dossier number: 846001002 in collaboration with KWF and Zilveren Kruis. The project period is 31 December 2016 – 31 May 2021.
DOI: 10.5281/zenodo.4458294
title: Data_Appendix C_Biomechanical Basis of Human Movement

description: Sample Kinematic and Kinetic Data Subject: 50-kg woman<br> Activity: Walking sampled at 120 Hz; one cycle from right foot touchdown to right foot<br> touchdown<br> Markers: Head, R shoulder, R elbow, R wrist, R hand, R crest (IC), R greater trochanter<br> (GT), R knee, R ankle, R heel, R fifth metatarsal (met), and R toe<br> Stride events: Right foot touchdown (RTD), left foot touchdown (LTD), and right foot<br> toe-off (RTO)<br>
DOI: 10.5281/zenodo.4480181
title: IODP Expedition 368X Photomicrographs

description: Microscopic images of discrete samples were acquired using stereo and upright light microscopes and captured on digital cameras. Image files were uploaded along with a brief description and a record of the microscopic and lighting conditions when the image was taken.
DOI: 10.5281/zenodo.6502312
title: Passive RFID indoor location dataset

description: We use four monostatic UHF antennas that operate in the frequency range from 902 to 928 MHz with a 6 dBi gain (isotropic antenna gain) for the implementation environment preparation. The equipment we used to perform the readings was the ThingMagic Mercury 6, a high-performance UHF RFID reader, supporting up to four monostatic antennas, digital inputs and outputs, and a Wi-Fi connection. Both devices are commercially available. We affixed 400 labels to objects placed side by side on the shelves in an auto parts store. The distance between the antennas and tags was 115 cm, and the distance between the antenna group was 250 cm. The reader interrogates the tags every 5 seconds and organizes the input information in a data collection formed by TagID, RSSI, Read Count (RC), True_x, and True_y. This interrogation time was defined by the minimum limit at which all tags were identified at least once by the antenna. In order to carry out data collection, the objects were placed in known positions. We performed 100 readings on each target tag, measuring the RSSI and the RC of each of the four antennas, totaling 40,000 readings.
DOI: 10.5281/zenodo.3686906
title: LoRa RSSI vs distance

description: The data set has been used in CityScan experiment within Fed4Fire+ continuous call. RSSI and packet loss between LoRa end device sending data packets and a set of stationary LoRa nodes were studied depending on the distance and other parameters. The data set contains location information transferred over LoRa from a single tag and registered by 10 nodes from CityLab testbed: Node 2, Node 4, Node 15, Node 18, Node 20, Node 21, Node 27, Node 33, Node 35, Node 36. The data is stored in CSV format (with the following columns):<br> <strong>node</strong> - id of the CityLab testbed node<br> (<strong>node_lat</strong>, <strong>node_lon</strong>) - GPS coordinates of the node<br> <strong>tag</strong> - id of the CityScan tag<br> (<strong>tag_lat</strong>, <strong>tag_lon</strong>) - GPS coordinates of the tag<br> <strong>tag_speed</strong> - Speed of the moving tag<br> <strong>dist_m</strong> - Distance between corresponding tag and node (meters)<br> <strong>ts</strong> - timestamp (milliseconds since the UNIX epoch: 1 January 1970)<br> <strong>num</strong> - a sequential number of submitted packet<br> <strong>rssi</strong> - received signal strength indication<br> <strong>received</strong> - Boolean attribute indicating whether or not the data packet was received
DOI: 10.5281/zenodo.5665894
title: 湖泊水位水量年变化速率

description: 2000-2020年全球500平方公里以上湖泊水位水量年变化速率
DOI: 10.5281/zenodo.3692315
title: Dataset for laboratory experiments of fragmenting rockfalls and rockslides

description: This data set provides movies for impact-fragmentation of sliding blocks recorded using high-speed camera during laboratory experiments, which can be useful for a thorough understanding of the evolutions of internal rock damages. The calculated data of area covered by deposit, aspect ratio of deposit, the travel distance of the center of mass on the horizontal plane, the travel distance of sliding mass on the horizontal plane, and the relative breakage ratio are also provided. In addition, we also provided the data of velocity profiles of blocks with different structures at t=0.1 s from x=0 m to x = 0.8 m. Dataset_S1. Data of area covered by deposit, aspect ratio of deposit, the travel distance of the center of mass on the horizontal plane, the travel distance of sliding mass on the horizontal plane, and the relative breakage ratio. The velocities of each tests derived from the pictures took by high speed camera (PIVLab code in Matlab is used for those calculation). The deposit parameters was calculated based on digital surface model (DSM) of deposit. <br> Dataset_S2. Videos of all tests. <br> Dataset_S3. Orthophotos and DSM of deposits for all tests.
DOI: 10.5281/zenodo.4738405
title: Supplementary Materials for 'Smartphone Distance Estimation Based on RSSI-Fuzzy Classification Approach'

description: Supplementary Materials for 'Smartphone Distance Estimation Based on RSSI-Fuzzy Classification Approach'
DOI: 10.5281/zenodo.1011311
title: Meningioma Dataset 10-13-17

description: The dataset (satra's) from the task "meningioma_001" (from *some* subjects in BrainBox, and only axial slices with tumor) on Medulina, that I've been using to train a deep learning network. The data is a .npz, when loaded (data = np.load() ) it has keys: ["X", "y", "labels"] where labels correspond to subject ids (to help you split the data). X is shape (188, 256, 256, 2) where there are 188 slices, 256x256 in dimension, with 2 channels, where the first is the grayscale image and the second is the aggregate "hint" from Medulina.

md5-data-hash: 0774e3e5c31ebc24a2c4503634b48ccc
DOI: 10.5281/zenodo.1219249
title: Rssi-Based Mobile Robot Localization Datasets

description: Experimental datasets used for an MSc project, titled "Outdoor Localization System for Mobile Robots Based on Radio-Frequency Signal Strength", for performing trajectory recovery of a mobile ground robot by data fusion of odometry, gyroscope and Received Signal Strength Indicator (RSSI), through Extended and Augmented-Extended Kalman Filter algorithms.

<br>
"experiment_1" contains the robot's data in "rosbags" (i.e. ROS' compressed robot data), recorded in a parking lot with ground-truth from an RTK GPS. The measurements recorded were wheel odometry, IMU accelerations/angular velocities, RSSI from three receiver-transmitter pairs, regular GPS position and RTK GPS position.

"experiment_2" contains the robot's data in "rosbags", recorded in the parking lot and in a second environment, a garden with tall trees and a nearby building. Both environments were recorded for later comparison, to see how the localization solution performed in a GPS-denied environment. All measurements were the same as in experiment 1, except for the exclusion of the common and RTK GPS.
DOI: 10.5281/zenodo.4525517
title: YOLO/Darknet BACH model nest area

description: Trained YOLO/Darknet model to use with BACH. Detecting ants in the nest section of experimental nests.
DOI: 10.5281/zenodo.4073072
title: SAL-Autarkic-Localization-RSSI-BLE-Dataset: SAL-RB-Dataset

description: The SAL-Autarkic-Localization-RSSI-BLE-Dataset (SAL-RB-Dataset) is a set of more than 20 000 labeled Received Signal Strength Indicator (RSSI) measurements for indoor localization with Bluetooth Low Energy (BLE)
DOI: 10.5281/zenodo.4090154
title: Lake ice thickness dataset

description: This dataset consist of three products including: (1) Lake ice thickness of 11 large lakes measured by satellite altimeters for 2002-2019; (2) Lake ice thickness and lake surface snow depth of 1260 lakes with an area &gt; 50 km<sup>2</sup> in the Northern Hemisphere modeled by a one-dimensional remote sensing lake ice model for 2003-2018; (3) Future lake ice thickness and surface snow depth for 2091-2099 modeled by the lake ice model with a modified ice growth module. This daily lake ice and snow thickness dataset could provide a benchmark for the estimation of global lake ice and snow mass, thereby improving our understanding of the ecological and economical significance of fresh water ice as well as its response to climate change.
DOI: 10.1594/pangaea.358831
title: Sand content of sediment core PS2426-4
DOI: 10.5281/zenodo.3686907
title: LoRa RSSI vs distance

description: The data set has been used in CityScan experiment within Fed4Fire+ continuous call. RSSI and packet loss between LoRa end device sending data packets and a set of stationary LoRa nodes were studied depending on the distance and other parameters. The data set contains location information transferred over LoRa from a single tag and registered by 10 nodes from CityLab testbed: Node 2, Node 4, Node 15, Node 18, Node 20, Node 21, Node 27, Node 33, Node 35, Node 36. The data is stored in CSV format (with the following columns):<br> <strong>node</strong> - id of the CityLab testbed node<br> (<strong>node_lat</strong>, <strong>node_lon</strong>) - GPS coordinates of the node<br> <strong>tag</strong> - id of the CityScan tag<br> (<strong>tag_lat</strong>, <strong>tag_lon</strong>) - GPS coordinates of the tag<br> <strong>tag_speed</strong> - Speed of the moving tag<br> <strong>dist_m</strong> - Distance between corresponding tag and node (meters)<br> <strong>ts</strong> - timestamp (milliseconds since the UNIX epoch: 1 January 1970)<br> <strong>num</strong> - a sequential number of submitted packet<br> <strong>rssi</strong> - received signal strength indication<br> <strong>received</strong> - Boolean attribute indicating whether or not the data packet was received
DOI: 10.5281/zenodo.6551614
title: BLE RSSI Database for Analyzing Routines of Community-Dwelling Older Adults

description: The database includes the RSSI information emitted by BLE beacons installed in an elderly care home and collected by smartwatches worn by volunteers. Raw data and processed data are provided. Also, files in the Python programming language are included to facilitate data manipulation.
DOI: 10.1594/pangaea.438843
title: Modal analyses of thin-sections of sediment core CRP-1 (Table 1)

description: During the course of the 1997 drilling campaign, lithostratigraphic boundaries were assigned to the CRP-l core on the basis of perceived changes in lithology. The geologically most important boundary in the core, between the Miocene and overlying Quaternary sections, was placed at 43.55 mbsf. This horizon was described in the core logs (Cape Roberts Science Team, 1998) as a contact between muddy, finegrained sandstone (which were assigned a Lower Miocene age based on diatom biostratigsaphy) and overlying diamictons containing Quaternary diatoms. This boundary is a major unconformity, recognisable on seismic reflection records. As such, it has considerable significance in the ongoing scientific analysis of the drillcore. During a re-examination of the core, focusing on the archive half held at the Antarctic Geology Research Facility of the Florida State University at Tallahassee; the authors noted that the core across the published boundary (43.55 mbsf) did not show any lithological change, but logged a sharp contact between dark olive grey, muddy sandstone and overlying diamicton at 43.15 mbsf (Fig. l). We suggest, therefore, that the core log in appendix l of Cape Roberts Science Team (1998) is misleading over this interval. In order to test the veracity of the suggested boundary revision, a series of thin-sections was examined and point-counted for framework grain abundances.
description: Supplement to: Fielding, Christopher R; Baker, Julian C; Woolfe, Ken; Howe, John; Lavelle, Mark (1998): Reassessment of the Miocene-Quaternary boundary in CRP-1, Cape Roberts Project, Antarctica. Terra Antartica, 5(3), 425-426
DOI: 10.1594/pangaea.903542
title: CTD temperature and salinity profiles along the transect Siglunes from several cruises
DOI: 10.5281/zenodo.1219248
title: Rssi-Based Mobile Robot Localization Datasets

description: Experimental datasets used for an MSc project, titled "Outdoor Localization System for Mobile Robots Based on Radio-Frequency Signal Strength", for performing trajectory recovery of a mobile ground robot by data fusion of odometry, gyroscope and Received Signal Strength Indicator (RSSI), through Extended and Augmented-Extended Kalman Filter algorithms.

<br>
"experiment_1" contains the robot's data in "rosbags" (i.e. ROS' compressed robot data), recorded in a parking lot with ground-truth from an RTK GPS. The measurements recorded were wheel odometry, IMU accelerations/angular velocities, RSSI from three receiver-transmitter pairs, regular GPS position and RTK GPS position.

"experiment_2" contains the robot's data in "rosbags", recorded in the parking lot and in a second environment, a garden with tall trees and a nearby building. Both environments were recorded for later comparison, to see how the localization solution performed in a GPS-denied environment. All measurements were the same as in experiment 1, except for the exclusion of the common and RTK GPS.
DOI: 10.5281/zenodo.6656332
title: Strawberry dataset for Semantic Segmentation

description: The dataset was annotated using the labelme tool, and it was trained using the pixellib.
DOI: 10.5281/zenodo.4495351
title: List of wind power projects in Vietnam

description: Historical inventory of wind power projects in Vietnam, updated 2021-01-21. Number of records = 473, of which 381 refer to active projects, and 162 have investment costs. Each record describes a wind project phase. The table includes projects at all stages of the lifecycle. Some have been mentioned years ago and are now of historical interest only, some have just a signed exploration MoU. All records are referenced to one or several public source(s). Fields: Record type, Project status, Project name, Owner, Location (hamlet, commune, province, region), Location type (onshore/nearshore/offshore), Capacity (MWp), Investment (VND or alternatively USD), Wind Plan lot #, Key milestone dates (MoU, Investment Licence, Construction start, Expected COD, Actual COD), Note and sources.
description: This release includes the data paper describing the dataset. Other files unchanged.
DOI: 10.5281/zenodo.50627
title: Baby

description: This is an item called Baby
DOI: 10.5281/zenodo.3663215
title: Simulation data and scripts for CFD-DEM simulation of saturated bi-disperse granular flows

description: Data set 1 - contains the raw data required to replicate and validate all plots in the main article. Sample case - a .zip file which includes codes which are needed to simulate a CFD-DEM case of a steady granular flow in water with cyclic boundaries in the stream wise direction. Also enclosed is a ReadMe.txt file detailing the implementation instructions for both Esys particle and OpenFOAM codes. Download links for Esys particle and OpenFOAM are also included Geo file generator - a .zip file which includes Esys particle codes that can be used to generate a .geo file specifying the initial position of the particles used in the test simulations. A ReadMe.txt file is enclosed with more detailed implementation instructions.
DOI: 10.1594/pangaea.868650
title: Physical oceanography during EAF-Nansen cruises: temperature and salinity
DOI: 10.5281/zenodo.6500097
title: 基于随机森林的加热卷烟烟叶原料适用性评估

description: 化学计量学
DOI: 10.5281/zenodo.6557993
title: Realistic GPS and IMU data

description: Recordings of both gps and imu during a Seafar vessel navigation. The following values come from the gnss unit: <pre><code> "heading_degrees": 154.453, "rot_degrees_min": 19.9, "lat_degrees": 51.212967072, "lon_degrees": 2.995510899, "sog_kph": 3.37,</code></pre> All the other values come from the IMU eg. <pre><code class="language-json"> "roll_degrees": 2.78, "pitch_degrees": 0.57, "yaw_degrees": 158.5, "roll_rate_rad_min": 0.0, "pitch_rate_rad_min": 0.0, "yaw_rate_rad_min": 0.51, "accel_x_ms2": -0.00137, "accel_y_ms2": 0.00784, "accel_z_ms2": -0.00171, "yaw_rate_degrees_min": 29.2208475517</code></pre> All acceleration values are gravity-compensated.
DOI: 10.15468/dl.f85v78
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((147.671058 -35.870434, 147.671058 -35.872679, 147.67555 -35.872679, 147.67555 -35.870434, 147.671058 -35.870434)), ((147.67555 -35.872679, 147.67555 -35.879417, 147.677796 -35.879417, 147.677796 -35.872679, 147.67555 -35.872679)), ((147.677796 -35.872679, 147.680041 -35.872679, 147.680041 -35.870434, 147.677796 -35.870434, 147.677796 -35.872679)), ((147.680041 -35.872679, 147.680041 -35.877171, 147.684533 -35.877171, 147.684533 -35.872679, 147.680041 -35.872679)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048070-240626123714530/datasets/export for details.
DOI: 10.34740/kaggle/dsv/9108251
title: Resampled