cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.11065699
title: MSMVA analysis.
title: Field aligned current structures measured by Swarm spacecraft

description: This repository contains the results of the multiscale field-aligned current (FAC) analysis applied to four crossings of the auroral region by the Swarm spacecraft. These data files accompany the initial submission of the paper "The structure of field-aligned current systems as inferred from the multiscale minimum variance analysis" to Earth and Space Science. 

The multiscale analysis is applied to the high resolution magnetic field measurements (50 Hz) from Swarm spacecraft. The data files are given in the netCDF format.  Each data file contains the following variables:

Input:time [s] - seconds elapsed since January 1, 1970 UTC.Bx, By, Bz [nT] - the magnetic field perturbation in MFA (magnetic field aligned) coordinates.  

The multiscale analysis relies on performing the minimum variance analysis over an array of central times and interval widths (scale). The analysis provides the time and scale dependence of the eigenvalues of the magnetic field variance matrix. The scale derivatives of the maximum and minimum eigenvalue are used to estimate the geometric aspect ratio of the measured field-aligned current structures. 

Output:out_win_wid [s] - the array of interval widths (scale). out_time_msmva [s] - the array of central times.

out_lmax [nT^2] - the matrix of maximum eigenvalues.                  out_lmin [nT^2] - the matrix of minimum eigenvalues.                                                                                           df1_lmax [nT^2/s] - the derivative of maximum eigenvalue with respect to scale.                              df1_lmin [nT^2/s] - the derivative of minimum eigenvalue with respect to scale.

out_angle [deg] - the orientation of the FACs.
DOI: 10.5281/zenodo.12702273
title: Historical Pollen Records from `The Productivity-Stability Trade-off in Global Food Systems'

description: Historical pollen records from Europe used to detect evidence of agricultural development on plant pollen dynamics.
DOI: 10.5281/zenodo.13322571
title: Data and Code for Analysis of Bottom Trawling Impact on Sedimentary Organic Carbon in the North Sea

description: Data and Code for Analysis of Bottom Trawling Impact on Sedimentary Organic Carbon in the North Sea
DOI: 10.5281/zenodo.13870645
title: Codes for identification of the earliest terrestrial trace fossils

description: This repository contains the CFDEM (www.cfdem.com(opens in new window)) and Matlab codes with our own developments to reproduce trace fossils in different environments (three zip files) and deduce putative trace-makers (CurveGithub.m). You can also get access to a free software for trace-maker identification through https://zenodo.org/records/10259553(opens in new window).

Codes.zip contains the CFDEM solvers to reproduce translational and rotational motion of the trace-makers/appendages (cfdemSolverPisoSTL0, cfdemSolverPisoSTL), along with the necessary semi-resolved force models (gradPForce, viscForce, GidaspowDragsemi). Steps to compile these codes are written in Readme within the compressed file. If you want to use relatively coarse mesh (mesh size at least three times larger than sediment diameter) to accelerate simulations, please use the default unresolved forces models. In that case, only the provided solvers needs to be compiled. But the force model lists in case/CFD/constant/couplingProperies needs to be adjusted. Please refer to the benchmark cases in www.cfdem.com(opens in new window) to learn to use CFDEM.

Benchmark_case.zip contains a benchmark validation of the moving cube on submerged sands. Appendage.zip contains a moving appendage on subaerial wet sands. The details about how to run the cases are written in the Readme file in each compressed file.
DOI: 10.5281/zenodo.4085873
title: Discrete flow cytometry from the Gradients 2017 cruise using a BD Influx Cell Sorter

description: The dataset consists of BD Influx-based analysis of phytoplankton populations and heterotrophic bacteria from discrete flow cytometry data collected during the Gradients 2017 (Gradients 2/MGL1704) oceanographic research cruise in the Northeast Pacific Ocean. The analysis includes cell abundance, forward light scatter, and pigment fluorescence of individual cells, including bacteria, picoeukaryotes and the cyanobacteria Prochlorococcus and Synechococcus. Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: https://github.com/fribalet/FCSplankton
description: This work was supported by grants from the Simons Foundation (#574495 to FR, #329108, #426570SP and #549945 to EVA).
DOI: 10.5281/zenodo.6451335
title: Spatial Scaling Challenge. COST Action CA17134 SENSECO. Working Group 1

description: This dataset contains the data, documentation, and scripts that compose the <strong>SPATIAL SCALING CHALLENGE</strong> organized in the framework of the <strong>SENSECO COST Action CA17143</strong> “Optical synergies for spatiotemporal SENsing of Scalable ECOphysiological traits” (https://www.senseco.eu/), by the <strong>Working Group 1</strong><strong>.</strong> “Closing the scaling gap: from leaf measurements to satellite images” (https://www.senseco.eu/working-groups/wg1-scaling-gap/). The <strong>SPATIAL SCALING CHALLENGE</strong> is an open exercise where we challenge the remote sensing community to retrieve relevant vegetation biophysical and physiological variables such as leaf chlorophyll content (<em>C</em><sub>ab</sub>), leaf area index (<em>LAI</em>), maximal carboxylation rate (V<sub>c</sub><sub>max,25</sub>), and non-photochemical quenching (<em>NPQ</em>) from simulated (hyperspectral reflectance (<em>HDRF</em>), sun-induced chlorophyll fluorescence (<em>F</em>) and land surface temperature (<em>LST)</em>) imagery. The dataset contains the simulated remote sensing and field data, their description, and scripts in Matlab, Python, and R languages to facilitate importing and handling the data and producing the standardized outputs necessary to participate. <strong>IMPORTANT:</strong> <strong>Additional data</strong> that can be used at the discretion of the participants have been released in <strong>https://doi.org/10.5281/zenodo.6530187</strong> The <strong>SPATIAL SCALING CHALLENGE</strong> aims at gathering the community’s expertise and knowledge to tackle the scaling problems posed by variables of different nature. These experiences will be summarized in a journal article where all the participants are invited to contribute. The exercise is internationally open. Ph.D. students, early career and senior researchers, spin-offs, and companies working in the field of remote sensing of vegetation ecophysiology are welcome to participate. <strong>STILL OPEN FOR PARTICIPATION! New deadline 31<sup>st</sup> of October 2022.</strong> Follow all the <strong>communications and updates</strong> of the <strong>SPATIAL SCALING CHALLENGE</strong> in the RG site: <strong>https://www.researchgate.net/project/Spatial-Scaling-Challenge-COST-Action-CA17134-SENSECO-Working-Group-1</strong>.
DOI: 10.5281/zenodo.6530187
title: Spatial Scaling Challenge - Additional Data. COST Action CA17134 SENSECO. Working Group 1

description: This dataset contains the data additional data provided for the <strong>SPATIAL SCALING CHALLENGE</strong> organized in the framework of the <strong>SENSECO COST Action CA17143</strong> “Optical synergies for spatiotemporal SENsing of Scalable ECOphysiological traits” (https://www.senseco.eu/), by the <strong>Working Group 1</strong><strong>.</strong> “Closing the scaling gap: from leaf measurements to satellite images” (https://www.senseco.eu/working-groups/wg1-scaling-gap/). The main dataset, documentation and scripts of the <strong>SPATIAL SCALING CHALLENGE</strong> must be downloaded from<strong>: https://doi.org/10.5281/zenodo.6451335</strong> This additional dataset includes half-hourly time series of down-welling incoming spectral irradiance (W m<sup>-2</sup> µm<sup>-1</sup>) in the visible and near-infrared domains as measured by a field spectroradiometer operating in a nearby ecosystem station. The inclusion of these data in the Spatial Scaling Challenge is at the discretion of the participants. The <strong>SPATIAL SCALING CHALLENGE</strong> aims at gathering the community’s expertise and knowledge to tackle the scaling problems posed by variables of different nature. These experiences will be summarized in a journal article where all the participants are invited to contribute. The exercise is internationally open. Ph.D. students, early career and senior researchers, spin-offs, and companies working in the field of remote sensing of vegetation ecophysiology are welcome to participate. <strong>STILL OPEN FOR PARTICIPATION! New deadline 31<sup>st</sup> of October 2022.</strong> Follow all the <strong>communications and updates</strong> of the <strong>SPATIAL SCALING CHALLENGE</strong> in the RG site: <strong>https://www.researchgate.net/project/Spatial-Scaling-Challenge-COST-Action-CA17134-SENSECO-Working-Group-1</strong>.
DOI: 10.5281/zenodo.8176730
title: Salt-Affected Soils in Italy

description: Soil salinization and sodification risks are two of the main threats in agricultural soils of Italy<br> (Dazzi, 2008). In Italy they are mainly due to irrigation with saline waters (Dazzi and Lo Papa,<br> 2013), to seawater intrusion (Castrignanò et al., 2008, Dazzi and Lo Papa, 2013, Selvaggi et al.,<br> 2010), and to saline parent materials (Dazzi and Fierotti, 1994). The water level is strictly regulated<br> by channels and pumping stations (Vittori Antisari et al., 2020; Buscaroli and Zannoni, 2010;<br> Teatini et al., 2007), and seawater intrusion along rivers, canals and in the groundwater aquifer is<br> exacerbated by subsidence (Teatini et al., 2005). The salt-rich parent material can be exposed due<br> to soil erosion (Piccarreta et al., 2006; Cocco et al., 2015). In the last decades, several Italian regional<br> authorities for soil data produced soil salinity (risk) maps, resorting to different mapping<br> approaches. Previous examples of salinity risk maps of Italy have been also attempted (Dazzi, 2008,<br> Costantini et al. 2009). This works presents the maps of salt-affected soils of Italy, as part of the 1k<br> grid GSSmap, realized adopting the procedure proposed by the Global Soil Partnership (GSP), and<br> involving the Italian regional authorities, which are part of the Italian Soil Partnership.
description: Acknowledgements We acknowledge the Italian Soil Partnership for the collaboration and the project SoilHUB (DM Mipaaf n. 35851 05/11/2019) for the financial support. The following regional authorities are particularly acknowledged for data provision and validation of the results: Raffaele Cherchi, General Director, and Gianni Piredda, Director of the Service for Environmental Researches of AGRIS (Sardinia); the General Direction of ARPAV (Veneto); the General Direction of ERSA (Friuli Venezia Giulia); Bernardo Gozzini, the General Administrator of LaMMA Consortium (Tuscany); Lorenzo Bisogni, the Director of the Agroenvironmental Policies (Marche); Monica Guida, Director of the Geological, Seismic and Soil Service (Emilia Romagna), Sandra di Ferdinando, Director of the Service for Characterization of Quality Productions of ARSIAL (Lazio); Domenico Campanile, and Francesco Bellino, Service for the Sustainable Management of Environmental Resources (Apulia). We acknowledge for the data provision the private enterprise SO.IN.G. s.r.l. and its Director Annalisa Morelli. The views expressed in this information product are those of the author(s) and do not necessarily reflect the views or policies of FAO.
DOI: 10.5281/zenodo.8297751
title: Field and Model Data for Bottom Trawling Impacts in the North Sea

description: This dataset includes both field measurement and modeled results of bottom trawling in the North Sea for the period of 1950-2020.
DOI: 10.5284/1020234
title: La Grava The Archaeology and History of a Royal Manor and Alien Priory of Fontevrault

description: The site of La Grava (known locally as Grove Priory) lies on the border between historic Bedfordshire and Buckinghamshire, south of Leighton Buzzard. Much of the core of the site and elements of its associated field closes (1.85ha of an area of 7.8ha) was excavated in advance of quarrying between 1973 and 1985, making it one of the most extensive projects on a monastic/manorial site in the UK in the 20th century.
Excavations of the area of earthworks were initiated originally on the basis of this being the site of La Grava, an alien priory of the Order of Fontevrault in Anjou. However, evidence from all periods, from the Mesolithic onwards, was recovered from the site.
DOI: 10.5523/bris.21h9f9e30v9cl2fapjggz4q1x7
title: REMAP Open dataset
title: REMAP Open: an open dataset of REal-world Mobility Activities in Parkinson's disease

description: Parkinson's disease (PD) is a neurodegenerative disorder characterised by motor symptoms, such as gait dysfunction and postural instability. Technological tools to continuously monitor outcomes could capture the hour-by-hour symptom fluctuations of PD. Development of such tools is hampered by the lack of labelled datasets from home settings. To this end, we propose REMAP, a human rater-labelled dataset of REal-world Mobility Activities in Parkinson's disease including people with and without PD doing sit-to-stand transitions and turns in gait while living in a home setting. These discrete activities are captured from free-living (unobserved, unstructured) and during clinical assessments. The PD participants withheld their dopaminergic medications for a time (causing increased symptoms), so their events are labelled as being “on” or “off” medications. We include skeleton pose camera data. We present this open dataset, where the skeleton pose data is coarsened for anonymisation. We illustrate use-case code measuring sit-to-stand duration, tested on both coarsened and refined data. This is a sister dataset so our controlled dataset (available on application) where there is more refined skeleton pose data and accelerometry.
DOI: 10.5523/bris.2o94rzjooyzf42w850dqg0spfh
title: REMAP Controlled dataset
title: REMAP Controlled: a controlled dataset of REal-world Mobility Activities in Parkinson's disease

description: Parkinson's disease (PD) is a neurodegenerative disorder characterised by motor symptoms, such as gait dysfunction and postural instability. Technological tools to continuously monitor outcomes could capture the hour-by-hour symptom fluctuations of PD. Development of such tools is hampered by the lack of labelled datasets from home settings. To this end, we propose REMAP, a human rater-labelled dataset of REal-world Mobility Activities in Parkinson's disease including people with and without PD doing sit-to-stand transitions and turns in gait while living in a home setting. These discrete activities are captured from free-living (unobserved, unstructured) and during clinical assessments. The PD participants withheld their dopaminergic medications for a time (causing increased symptoms), so their events are labelled as being “on” or “off” medications. We include accelerometry from wrist-worn wearables and skeleton pose camera data. We present this controlled dataset available on application where there is more refined data (this is a sister dataset to the open dataset, REMAP Open, where the data is coarsened for anonymisation). Use of this dataset is governed by the data.bris Research Data Access Agreement for Controlled data (https://www.bristol.ac.uk/staff/researchers/data/accessing-research-data/); commercial use may be arranged under bespoke agreements.
DOI: 10.6084/m9.figshare.26214830
title: Multidimensional influence drives leadership and composition-dependent success in octopus-fish hunting groups

description: Data S1. Detailed description of the dataset regarding:

Number of blocks (subgroups) per scene (groups)

Total number of individuals (scene-level)

Dataset of individuals present per block and scene

Data S2. 3D (x,y,z) reconstructed tracks for all individuals in octopus-fish groups.

Timeblock is the same as block, FRAME_IDX is frame number, along with individual_id(id) per dataset (hunting group). NA = absent in a given frame.

Data S3. Record of partner control mechanisms registered.

Video, time of video, and block, provide temporal information. Event (punch or fish displacement), actor and receiver IDs and presence of blacktipgrouper (btg) or blue goatfish (ygf) are also coded.

Data S4. Structures field experiment log.

Encoded are day of the dive, status of the structure, reaction by the octopus, seconds doing web-over, fish attack (yes or no), and octopus id

**Data S5. **Web-over data.

Encoded are field site, scene/dataset, timeblock, time of start and end of web-over and calculated web-over duration. Presence of blacktipgrouper (btg) and/or blue goatfish (ygf) are also coded, as well as octopus hunting alone (in column 'bi').
DOI: 10.6084/m9.figshare.27179205
title: Supplementary Material for: The utility of an HPV genotype assay for cancer screening in self-collected urine/vaginal samples from Japanese women.

description: Objectives
The high incidence of invasive cervical cancer among those who have not undergone cancer screening is a serious problem. This study aimed to investigate the utility of HPV test results from self-collected urine and vaginal samples as screening tools.
Design
The study was conducted in two steps. First, the appropriate storage container, temperature, and time until urine HPV assay performance were verified. Second, the results of spot urine testing under those conditions and of gynecologist-collected cervical and self-collected vaginal samples were compared to verify the feasibility of using the BD Onclarity® HPV assay for individuals with abnormal cervical cytology.
Participants/Materials, Setting, Methods
The participants were 121 women with abnormal cervical cytology. Self-collected urine and vaginal samples, along with gynecologist-collected cervical samples, were tested for HPV using the BD Onclarity® HPV assay. The optimal conditions for urine sample storage were identified by comparing the HPV detection rates under various conditions.
Results
Urine stored in a BD Probe Tec™ (QxUPT) for less than 72 hours at room temperature was found to have the highest HPV positivity rate. Under these conditions, the detection rates of HPV in urine, cervical, and vaginal samples were examined. HPV type 16 was detected in 41.7% of the cervical samples, type 18 in 10%, and types 31 and 52 in 12.6% each. The concordance rate for HPV testing between clinician-collected cervical and urine samples was 63.9% (kappa 0.34; 95% CI: 0.21–0.47), and that between clinician-collected cervical and self-collected vaginal samples was 77.8% (kappa 0.68; 95% CI: 0.53–0.83), indicating good concordance. In a population with an HPV-related lesion/tumor prevalence of approximately 70%, the sensitivity of HPV testing was 82.7% for the cervix, 46.4% for urine, and 75.7% for vaginal samples.
Limitations
The primary limitation is the lower detection rate of HPV in spot urine samples than in other sample types, indicating room for methodological improvement. The study's findings are based on a specific population, which may limit generalizability.
Conclusions
We investigated the optimal self-collected urine-to-testing time and temperature. Self-collected vaginal and urine HPV tests show moderate–high concordance with clinician-collected cervical HPV tests, suggesting their potential utility for women who do not undergo regular cancer screening. However, the sensitivity was not high in spot urine. Therefore, further large-scale studies are needed to verify these findings and optimize testing methods to encourage broader participation in cancer screening programs.
DOI: 10.5281/zenodo.1227121
title: Demand: A Collection Of Multi-Channel Recordings Of Acoustic Noise In Diverse Environments

description: <strong>DEMAND: Diverse Environments Multichannel Acoustic Noise Database</strong>

A database of 16-channel environmental noise recordings

<strong>Introduction</strong>

Microphone arrays, a (typically regular) arrangement of several microphones, allow for a number of interesting signal processing techniques. The correlation of audio signals from microphones that are located in close proximity with each other can, for example, be used to determine the spatial location of sound source relative to the array, or to isolate or enhance a signal based on the direction from which the sound reaches the array.

Typically, experiments with microphone arrays that consider acoustic background noise use controlled environments or simulated environments. Such artificial setups will in general be sparse in terms of noise sources. Other pre-existing real-world noise databases (e.g. the AURORA-2 corpus, the CHiME background noise data, or the NOISEX-92 database) tend to provide only a very limited variety of environments and are limited to at most 2 channels.

The DEMAND (Diverse Environments Multichannel Acoustic Noise Database) presented here provides a set of recordings that allow testing of algorithms using real-world noise in a variety of settings. This version provides 15 recordings. All recordings are made with a 16-channel array, with the smallest distance between microphones being 5 cm and the largest being 21.8 cm.

<strong>License</strong>

This work, the audio data and the document describing it, is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.

<strong>The data</strong>

A description of the data and the recording equipment is provided in the file <strong>DEMAND.pdf</strong>. All recordings are available as 16 single-channel WAV files in one directory at both 48 kHz and 16 kHz sampling rates. All files are compressed into "zip" files.

<strong>Other information</strong>

The MATLAB scripts listed in the documentation can be found in the file <strong>scripts.zip</strong>.

<strong>The Authors</strong>

This work was created by Joachim Thiemann (IRISA-CNRS), Nobutaka Ito (University of Tokyo), and Emmanuel Vincent (Inria Rennes - Bretagne Atlantique). It was supported by Inria under the Associate Team Program VERSAMUS.
description: Supported by Inria under the Associate Team Program VERSAMUS
DOI: 10.15468/dl.ecqknr
title: Occurrence Download

description: A dataset containing 13401 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Oryza rufipogon Griff."
 ]
}

 The dataset includes 13401 records from 132 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002250-241106120511685/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k6s9kf
title: Occurrence Download

description: A dataset containing 851 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Quercus ilex L.)",
 "Country is one of (Spain)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 851 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002251-241106120511685/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5518/1172
title: Crystallisation, Dissolution and Saturation Temperatures Data for a Model Fuel in Presence of a Cold-Flow Improver

description: Crystallisation and solubility data are provided for a model fuel in the absence and presence of a flow improving additive.
DOI: 10.5281/zenodo.14049572
title: ЮКСАК ИЛМ СОҲИБИ АЗИЗУДДИН ИЙЖИЙНИНГ ҲАЁТИ ВА ИЖОДИ
DOI: 10.5281/zenodo.14049573
title: ЮКСАК ИЛМ СОҲИБИ АЗИЗУДДИН ИЙЖИЙНИНГ ҲАЁТИ ВА ИЖОДИ