cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14856129
title: Effects of different postures on the hemodynamics and cardiovascular autonomic control responses to exercise in postural orthostatic tachycardia syndrome

description: Abstract



Purpose: To assess the effects of two different body positions on the cardiovascular autonomic profile during a single bout of exercise in patients with postural orthostatic tachycardia syndrome (POTS).

Methods: Thirteen patients with POTS and thirteen healthy controls (C) participated in the study. ECG, respiration, beat-by-beat arterial pressure and O2 consumption (VO2) were continuously recorded while on a cycle ergometer in supine and upright positions, before and during exercise (6 min, 50 Watts). Spectral analysis of RR intervals and systolic arterial pressure (SAP) variability provided indexes of cardiac sympathovagal interaction (LF/HF ratio), cardiac vagal modulation (HFRR, high-frequency component of RR variability, ~ 0.25 Hz), sympathetic vasomotor control (LFSAP, low-frequency component of SAP variability, 0.1 Hz) and baroreflex sensitivity (BRS, αLF).

Results: While supine, patients with POTS showed lower HFRR and αLF, greater heart rate (HR), LF/HF and LFSAP, compared with C, suggesting cardiovascular sympathetic over-activity and reduced BRS. While sitting upright, POTS showed greater HR and reduced HFRR and αLF compared with C. During supine exercise, SAP, HR, LF/HF increased and HFRR and αLF decreased similarly in POTS and C. In POTS, upright sitting exercise was associated with slightly higher ˙VO2V˙O2 , a greater increase in HR whereas LFSAP was lower than in C.

Conclusion: Upright exercise was associated with excessive enhancement of HR and a blunted increase of the sympathetic vasomotor control in POTS. Conversely, supine exercise-induced hemodynamic and autonomic changes similar in POTS and C, thus making supine exercise potentially more suitable for physical rehabilitation in POTS.
DOI: 10.17632/dvf2mgs2ys.1
title: Seesaw protein: Design of a protein that adopts interconvertible alternative functional conformations and its dynamics.

description: Raw data
DOI: 10.17909/cn6n-xg90
title: JWST Resolved Stellar Populations Early Release Science ("JWSTSTARS")

description: The JWST Resolved Stellar Population Early Release Science (ERS) Program obtained NIRCam and NIRISS imaging of 3 resolved stellar targets in the Local Group: globular cluster M92, ultra-faint dwarf galaxy Draco II, and star-forming dwarf galaxy WLM. NIRCam was the primary instrument and observed each target in 4 filters: M92 (F090W, F150W, F277W, F444W), Draco II (F090W, F150W, F360M, F480M), WLM (F090W, F150W, F250M, F430M). NIRISS was used in parallel and obtained imaging in 2 filters (F090W, F150W). The 3rd exposure of M92, for both NIRCam and NIRISS, is not included in the analysis as it suffered from excess astrometric jitter and cannot produce adequate photometry. See Weisz et al. 2024 for more details.

Using this imaging data, the ERS team developed JWST NIRCam and NIRISS modules for DOLPHOT, a crowded field stellar photometry package widely used in nearby galaxies. This data release includes the full, multiband photometric catalogs produced by DOLPHOT for each field and the id2 drizzled reference images used for astrometrically aligning images for each target. The NIRISS field for Draco II did not contain prominent member stars, and the photometric catalog is not included in this data release.  

The FITS images used for this data release have the following JWST pipeline versioning information: CAL_VER=1.11.4, CRDS_VER=11.17.2, and CRDS_CTX=jwst_p1147.pmap.
DOI: 10.5281/zenodo.14526294
title: Simulation for the calibration of radiation housekeeping monitor onboard BepiColombo/MMO and application to the inner heliosphere exploration

description: I appreciate your interest in this paper.

These archived data are used for Kinoshita et al., (2024).

If you have further questions about these data, please feel free to contact me.

E-mail: g-kinoshita20686@g.ecc.u-tokyo.ac.jp

 

Sincerely,

Gaku Kinoshita
DOI: 10.17632/6wr5f87gvk.1
title: sulfur XANES and geochemical data

description: this dataset included geochemical data from PBr and BBM peat profiles, as well as sulfur K-edge XANES data from selective peat samples, sulfur K-edge XANES data of standard also presented
DOI: 10.17632/8dr67bw4mz.2
title: Experimental data from the manuscript "Post-Return Stroke VHF Electromagnetic Activity in North-Western Mediterranean Cloud-to-Ground Lightning Flashes"

description: The dataset consists of magnetic field recordings of 92 cloud-to-ground flashes analyzed in the manuscript "Post-Return Stroke VHF Electromagnetic Activity in North-Western Mediterranean Cloud-to-Ground Lightning Flashes".
DOI: 10.25326/236
title: L1 SAETTA science data

description: The Level 1 (L1) SAETTA data consist in time and space locations of VHF sources that are radiated by lightning flashes in the 60-66 MHz VHF band. The L1 SAETTA data are processed from the L0 SAETTA raw data collected by the 12 sensors deployed over Corsica. Each VHF source is described by its time occurrence, its geo-location, its VHF amplitude, and two quality control parameters. The L1 SAETTA data are stored per 10-min period in ASCII format, and are archived per year, then per month, and finally per day.

A detailed description of the SAETTA network is available in Coquillat et al. (2019; https://doi.org/10.5194/amt-12-5765-2019).
DOI: 10.25606/surf.8f3ac424d6694282
title: LDBC Social Network Benchmark graphs

description: The graphs were generated by the LDBC Social Network Benchmark's Datagen (Hadoop variant, https://github.com/ldbc/ldbc_snb_datagen_hadoop/releases/tag/v0.3.5). The available scale factors are: SF1, SF3, ..., SF1000. Stored in zstd-compressed CSV files. - social_network-csv_basic: data sets produced using the CsvBasic serializer and the "yyyy-MM-dd'T'HH:mm:ss.SSSZ" datetime formatter (StringDateFormatter). - social_network-csv_basic-longdateformatter: data sets produced using the CsvBasic serializer and the unix epoch milli datetime formatter (LongDateFormatter). - social_network-csv_composite: data sets produced using the CsvComposite serializer and the "yyyy-MM-dd'T'HH:mm:ss.SSSZ" datetime formatter (StringDateFormatter). - social_network-csv_composite-longdateformatter: data sets produced using the CsvComposite serializer and the unix epoch milli datetime formatter (LongDateFormatter). - social_network-csv_composite_merge_foreign: data sets produced using the CsvCompositeMergeForeign serializer and the "yyyy-MM-dd'T'HH:mm:ss.SSSZ" datetime formatter (StringDateFormatter). - social_network-csv_composite_merge_foreign-longdateformatter: data sets produced using the CsvCompositeMergeForeign serializer and the unix epoch milli datetime formatter (LongDateFormatter). - social_network-csv_merge_foreign: data sets produced using the CsvMergeForeign serializer and the "yyyy-MM-dd'T'HH:mm:ss.SSSZ" datetime formatter (StringDateFormatter). - social_network-csv_merge_foreign-longdateformatter: data sets produced using the CsvMergeForeign serializer and the unix epoch milli datetime formatter (LongDateFormatter). - social_network-ttl: data sets produced using the Turtle serializer and the "yyyy-MM-dd'T'HH:mm:ss.SSSXXX" datetime formatter (StringDateFormatter). - substitution_parameters: query substitution parameters produced by the parameter generator (paramgen) component. - updatestreams: update streams defining insert operations. They are available in variants with the following partition numbers: 2^k (1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024) and 6×2^k (24, 48, 96, 192, 384, 768). Disclaimer. These data sets (including the social network graphs, query substitution parameters, and update streams) are part of the LDBC Social Network Benchmark's Interactive workload which is protected by the LDBC trademark. When using these data sets in publications, it is required to indicate which tier the benchmarked implementation belongs to based on the tiers described in the LDBC fair use policy (https://ldbcouncil.org/benchmarks/snb/). If you have any questions, please reach out to info@ldbcouncil.org. Website: https://ldbcouncil.org/benchmarks/snb/ Related publication: Renzo Angles, János Benjamin Antal, Alex Averbuch, Peter A. Boncz, Orri Erling, Andrey Gubichev, Vlad Haprian, Moritz Kaufmann, Josep Lluís Larriba-Pey, Norbert Martínez-Bazan, József Marton, Marcus Paradies, Minh-Duc Pham, Arnau Prat-Pérez, Mirko Spasic, Benjamin A. Steer, Gábor Szárnyas, Jack Waudby: The LDBC Social Network Benchmark. CoRR abs/2001.02299 (2020). https://arxiv.org/abs/2001.02299
DOI: 10.35111/vpqe-bz17
title: King Saud University Arabic Speech Database

description: <h3>Introduction</h3><br>
<p>King Saud University Arabic Speech Database was developed by Speech Group (SG) at <a href="http://ksu.edu.sa/en/">King Saud University</a> and contains 590 hours of recorded Arabic speech from 269 male and female speakers. The utterances include read and spontaneous speech. The recordings were conducted in varied environments representing quiet and noisy settings.</p><br>
<h3>Data</h3><br>
<p>The corpus was designed principally for speaker recognition research. However, other possible applications include first language recognition, mobile effect, multichannel effect, and use of different type of microphones. The speech sources are word lists, sentence lists, paragraphs and question and answer sessions. Read speech text includes the following:</p><br>
<ul><br>
<li>Sets of sentences devised to cover allophones of each phoneme, phonetic balance, and differentiation of accents.</li><br>
<li>Word lists developed to minimize missing phonemes and to represent nasals fricatives, commonly used words, and numbers.</li><br>
<li>Two paragraphs selected because they included all letters of the alphabet and were easy to read.</li><br>
</ul><br>
<p>Spontaneous speech was captured through question and answer sessions where speakers answer questions displayed on screen. The questions were on general topics such as the weather and food and included the speaker name or number.</p><br>
<p>The speakers were Saudis and non-Saudis. Among the non-Saudi participants were Arabs and non-Arabs. All female speakers were either Saudis or non-Saudi Arabs. Male speakers included non-Arabs from the Indian subcontinent, Africa, South East Asia and East Europe. Non-Arab participants were required to be able to read Arabic at an acceptable level. Most of the Non-Arab speakers were from the fourth level in the <a href="http://ali.ksu.edu.sa/en">Arabic Linguistics Institute</a> at King Saud University. The non-Saudi participants represented 28 nationalities and were chosen from clusters of areas or countries.</p><br>
<p>Each speaker was recorded in three different environments: in a soundproof room , in an office and in a cafeteria. The recordings were collected via different microphones and a mobile phone and averaged between 16-19 minutes. The recordings were done in three sessions with a time-gap of an approximately 6 weeks.</p><br>
<p>The data was verified for missing recordings, problems with the recording system or errors in the recording process. All files are presented as two channel 48 kHz 16-bit FLAC compressed PCM wav files. Note that sizes and file names in the documentation are for the uncompressed wav files.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2014S02.m.wav" rel="nofollow">male sample</a> and <a href="desc/addenda/LDC2014S02.f.wav" rel="nofollow">female sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2014 King Saud University, © 2014 Trustees of the University of Pennsylvania
DOI: 10.48668/0npbok
title: Perception of Online Communities towards the Use of Cancer Immunotherapy: A Data Mining Study of 3.6 Million Web-based Posts from Social Media Platforms Using BERTopic

description: Posts from online communities about immunotherapy are included.
DOI: 10.5066/p13uwmyl
title: Greater sage-grouse genetic data and R code for evaluating conservation translocations in the northwestern United States, 1992–2021 (ver. 1.1, December 2024)

description: Conservation translocations are a common wildlife management tool that can be difficult to implement and evaluate for effectiveness. Genetic information can provide unique insight regarding local impact of translocations (e.g., presence and retention of introduced genetic variation) and identifying suitable source and recipient populations (e.g., adaptive similarity). We developed two genetic data sets and wrote statistical code to evaluate conservation translocation effectiveness into the isolated northwestern region of the greater sage-grouse (Centrocercus urophasianus) distribution and to retrospectively evaluate adaptive divergence among source and recipient populations. Our first data set was microsatellite-based and derived from biological samples (feathers, tissue, and blood) collected from the translocation source populations and the northwestern recipient populations (in Washington state) before and after translocation. These data were used to evaluate neutral change in genetic variation resulting from translocation efforts. We wrote code for statistical analyses to evaluate two things in our microsatellite-based data. First, we developed a simulation model to predict the genetic effect of conservation translocations and compare the predictions to what was observed. Second, we developed a statistical model to estimate the probability that individuals sampled post-translocation are the offspring of two individuals from the same population or from individuals from two distinct populations. Our second data set was whole-genome sequencing data (derived from tissue and blood samples) for the source and Washington populations prior to translocation efforts. These data were used to characterize genome-wide adaptive divergence patterns that may influence translocation outcomes.

First posted - February, 6, 2024
Revised - December 20, 2024 (version 1.1)
DOI: 10.5281/zenodo.10777460
title: cigFacies: a massive-scale benchmark dataset of seismic facies and its application

description: cigFacies is a dataset create by the Computational Interpretation Group (CIG) for the AI-based automatic seismic facies classification in 3-D seismic data, Hui Gao, Xinming Wu, Xiaoming Sun and Mingcai Hou are the main contributors to the dataset.

This is the benchmark skeletonization datasets of seismic facies, guided by the knowledge graph of seismic facies and constructed from three different stategies (field seismic data, synthetic data and GAN-based generation).

Below are some brief desription of the datasets:

1) The "The benchmark skeletonization datasets" file consists of 5 classes of seismic facies.

2) The "parallel_class", "clinoform_class", "fill_class", "hummocky_class" and "chaotic_class" consist of 2000, 1500, 1500, 1500, 1500 stratigraphic skeletonization data constructed from field seismic data, synthetic data and GAN-based generation, respectively.







The source codes for constructing the benchmark dataset of seismic facies and deep learning for seismic facies classification have been uploaded to Github and are freely available at cigFaciesNet.
DOI: 10.5281/zenodo.13995530
title: Ion-scale Characteristics of the Martian Magnetic Pile-up Boundary Layer
DOI: 10.5281/zenodo.14524940
title: Spin-down of solar-mass protostars in magnetospheric accretion paradigm

description: Supplemental materials for Takasao, Kunitomo, Suzuki, Iwasaki & Tomida (2025, ApJ). The stellar evolution code MESA version 12115 was used to simulate protostellar evolution models. The "Takasao2025.zip" file contains



data/1Msun-HIST-H98.data: our fiducial evolutionary model using the protostellar mass accretion rate in Hartmann et al. (1998)

data/1Msun-HIST-H16.data: an evolutionary model using the accretion rate in Hartmann et al. (2016)

inlists/inlist_simplex_search_controls specifies input parameters

inlists/src/accretion.data specifies the accretion rate

inlists/src/history.inc controls output data in history.data files

ReadMe.md: a ReadMe file


See https://zenodo.org/records/5506424 for the other input flies.
DOI: 10.5281/zenodo.14607175
title: A global seafood methylmercury concentration dataset during 1995-2022

description: The database provides detailed records of global seafood methylmercury (MeHg) concentrations from 1995 to 2022. The database is classified based on two scales: marine area and nation. All data files are stored in XLSX and CSV formats, and the related codes used to construct this database are saved as Python files (.py ).
DOI: 10.5281/zenodo.7156189
title: Historical Arabidopsis thaliana genomes from Germany

description: We report short-read Illumina sequencing of 35 <em>Arabidopsis thaliana</em> herbarium specimens collected in Southern Germany from 1817 to 1957. The historical genomes were sequenced to an average depth of ~7X. The herbarium-derived sequences showed patterns of degradation typical of ancient DNA with average read lengths of 78 bp, endogenous DNA content between 26%-93% (mean 72%; median 74%) and enrichment of cytosine to thymine substitutions at the read’s termini. We provide the sequences to the public with open access.
DOI: 10.5281/zenodo.7187528
title: Historical Arabidopsis thaliana genomes from across its native range.

description: We report short-read Illumina sequencing of 131 <em>Arabidopsis thaliana </em>herbarium specimens across its native range collected from 1820 to 2010. Sequencing depth averaged ~6X across these genomes. Sequences from the herbarium samples showed the expected degradation patterns typical of ancient DNA with endogenous DNA content between 18.01-88.26% (mean 56%; median 74%) and enrichment of cytosine to thymine substitutions at fragment ends. We provide access to the sequences upon request.
DOI: 10.5281/zenodo.8318394
title: NanoPyx - Figures' Data

description: <strong>a549_mt.tif </strong> Data used in Figure "Microscopy image processing workflow using NanoPyx methods". Fixed A549 cells immunolabelled against ß-tubulin with Alexa Fluor™ 647. Acquired using a Nanoimager microscope (Oxford Nanoimaging; ONI) equipped with a 100 × oil-immersion objective (Olympus 100x NA 1.45) Image size 10000x283x283 (pixel size 117 nm) .tif 16-bit <strong>huvec_nuclei.tif</strong> Data used in Figure "Comparative run times of multiple implementations of an algorithm, ran on a consumer-grade laptop and a professional workstation". Human Umbilical Vein Endothelial Cells (HUVEC) stained with DAPI Acquired in a Marianas spinning-disk confocal microscope. The objective used was a 63x oil (NA 1.4 oil, Plan-Apochromat, M27). Image size 100x512x512 .tif 16-bit
description: Funding Bodies: R.H., P.M.P and R.P. acknowledge support from LS4FUTURE Associated Laboratory (LA/P/0087/2020). R.H., B.M.S. and I.C. acknowledge the support of the Gulbenkian Foundation (Fundação Calouste Gulbenkian), the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 101001332), the European Commission through the Horizon Europe program (AI4LIFE project with grant agreement 101057970-AI4LIFE, and RT-SuperES project with grant agreement 101099654-RT-SuperES), the European Molecular Biology Organization (EMBO) Installation Grant (EMBO-2020-IG-4734) and the Chan Zuckerberg Initiative Visual Proteomics Grant (vpi-0000000044 with DOI:10.37921/743590vtudfp In addition, A.D.B acknowledges the FCT 2021.06849.BD fellowship. R.H. and B.M.S. also acknowledge that this project has been made possible in part by a grant from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundations (Chan Zuckerberg Initiative Napari Plugin Foundations Grants Cycle 2, NP2-0000000085). P.M.P and R.P. acknowledge support from Fundação para a Ciência e Tecnologia (Portugal) project grant (PTDC/BIA-MIC/2422/2020) and the MOSTMICRO-ITQB R&D Unit (UIDB/04612/2020, UIDP/04612/2020), P.M.P acknowledges support from La Caixa Junior Leader Fellowship (LCF/BQ/PI20/11760012) financed by "la Caixa" Foundation (ID 100010434) and by European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 847648, and a from a Maratona da Saúde award. This study was supported by the Academy of Finland (338537 to G.J.), the Sigrid Juselius Foundation (to G.J.), the Cancer Society of Finland (Syöpäjärjestöt; to G.J.), and the Solutions for Health strategic funding to Åbo Akademi University (to G.J.). This research was supported by InFLAMES Flagship Programme of the Academy of Finland (decision number: 337531).
DOI: 10.6073/pasta/53ae2afd051a6a082a2ab129e4281e13
title: LAGOS-US GEO v1.0: Data module of lake geospatial ecological context at multiple spatial and temporal scales in the conterminous U.S.

description: The LAGOS-US GEO data package is one of the core data modules of LAGOS-US, an extensible research-ready platform designed to study the 479,950 lakes and reservoirs larger than or equal to 1 ha in the conterminous US (48 states plus the District of Columbia). The GEO module contains data on the geospatial and temporal ecological setting (e.g., land use, terrain, soils, climate, hydrology, atmospheric deposition, and human influence) quantified at multiple spatial divisions (e.g., equidistant buffers around lakes, watersheds, hydrologic basins, political boundaries, and ecoregions) relevant to the LAGOS-US lake population defined in the LAGOS-US LOCUS module. The database design that supports the LAGOS-US research platform was created based on several important design features: lakes are the fundamental unit of consideration, all lakes in the spatial extent above the minimum size must be represented, and most information is connected to individual lakes. The design is modular, interoperable (the modules can be used with each other), and extensible (future database modules can be developed and used in the LAGOS-US research platform by others). Users are encouraged to use the other two core data modules that are part of the LAGOS-US platform: LOCUS (location, identifiers, and physical characteristics of lakes and their watersheds) and LIMNO (in situ lake physical, chemical, and biological measurements through time) that are each found in their own data packages.
DOI: 10.6103/share.easy.800
title: easySHARE