cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5068/d1ft3h
title: Data from: Quantifying radiation belt electron loss processes at L &lt; 4

description: This dataset consists of the data from the seven figures in the published
 manuscript "Quantifying radiation belt electron loss processes at L
 &lt; 4" by Claudepierre et al. 2022. The published manuscript
 provides a comprehensive analysis of the processes that lead to
 quasilinear pitch-angle-scattering loss of electrons from the L &lt; 4
 region of the Earth's inner magnetosphere during geomagnetically
 quiet times. We consider scattering via Coulomb collisions, hiss waves,
 lightning-generated whistler (LGW) waves, waves from ground-based very-low
 frequency (VLF) transmitters, and electromagnetic ion cyclotron (EMIC)
 waves. The amplitude, frequency, and wave normal angle spectra of these
 waves are parameterized with empirical wave models, which are then used to
 compute pitch-angle diffusion coefficients. From these coefficients, we
 estimate the decay timescales, or lifetimes, of 30 keV - 4 MeV electrons
 and compare the results with timescales obtained from in-situ
 observations. We demonstrate good quantitative agreement between the two
 over most of the $L$ and energy range under investigation. Our analysis
 suggests that the electron decay timescales are very sensitive to the
 choice of plasmaspheric density model. At L &lt; 2, where our
 theoretical lifetimes do not agree well with the observations, we show
 that including Coulomb energy drag (ionization energy loss) in our
 calculations significantly improves the quantitative agreement with the
 observed decay timescales. We also use an accurate model of the
 geomagnetic field to provide an estimate of the effect that the drift-loss
 cone has on the theoretically-calculated electron lifetimes, which are
 usually obtained using an axisymmetric dipole field. 
description: The observational data was collected by the NASA Van Allen Probe
 spacecraft. The model data was obtained from theoretical diffusion
 coefficient calculations and Fokker-Planck simulations. 
description: The data files are provided in CSV format so that standard tools
 can open them (e.g., python, Matlab, Excel).
DOI: 10.22008/promice/data/ice_discharge/d/v02/bnizle
title: GIS_err.csv

description: Greenland error. Git hash: b511e1c
DOI: 10.22008/promice/data/ice_discharge/d/v02/jqzd1k
title: GIS_D.csv

description: Greenland discharge. Git hash: b511e1c
DOI: 10.22008/promice/data/ice_discharge/d/v02/nm2f9f
title: GIS.nc

description: Greenland discharge, coverage, and error. Git hash: b511e1c
DOI: 10.22008/promice/data/ice_discharge/d/v02/pw7vfe
title: README.txt

description: README. Git hash: b511e1c
DOI: 10.22008/promice/data/ice_discharge/d/v02/u2jxo7
title: region_coverage.csv

description: Regional coverage. Git hash: b511e1c
DOI: 10.22008/promice/data/ice_discharge/d/v02/c29txk
title: region_D.csv

description: Regional discharge. Git hash: b511e1c
DOI: 10.22008/promice/data/ice_discharge/d/v02/zmu6fz
title: region_err.csv

description: Regional error. Git hash: b511e1c
DOI: 10.22008/promice/data/ice_discharge/d/v02/3tsqdk
title: region.nc

description: Regional discharge, coverage, and error. Git hash: b511e1c
DOI: 10.22008/promice/data/ice_discharge/d/v02/4yjxze
title: sector_coverage.csv

description: Sector coverage. Git hash: b511e1c
DOI: 10.22008/promice/data/ice_discharge/d/v02/ifefrk
title: sector_D.csv

description: Sector discharge. Git hash: b511e1c
DOI: 10.22008/promice/data/ice_discharge/d/v02/2twjro
title: sector.nc

description: Sector discharge, coverage, and error. Git hash: b511e1c
DOI: 10.22008/promice/data/ice_discharge/d/v02/llnm8j
title: sector_err.csv

description: Sector error. Git hash: b511e1c
DOI: 10.22008/promice/data/ice_discharge/d/v02/xbk9dw
title: gate_coverage.csv

description: Gate coverage. Git hash: ed4766e
DOI: 10.22008/promice/data/ice_discharge/d/v02/brbobt
title: gate_err.csv

description: Gate errors. Git hash: ed4766e
DOI: 10.22008/promice/data/ice_discharge/d/v02/eeespu
title: gate_D.csv

description: Gate discharge. Git hash: ed4766e
DOI: 10.5061/dryad.cjsxksn84
title: Data from: Floral evolution and pollinator diversification in Hedychium: revisiting Darwin’s predictions using an integrative taxonomic approach

description: Hedychium J.Koenig (Zingiberaceae) is endemic to the Indo-Malayan Realm
 and is known for its vibrant and fragrant flowers. Historically, two
 different pollination syndromes characterize Hedychium: diurnal or bird
 pollination and nocturnal or moth pollination. In this study we aim to
 understand the evolution of nocturnal and diurnal flowers, and to test its
 putative association with lineage diversification in Hedychium. A
 molecular tree of Hedychium was used as a scaffold upon which we estimated
 ancestral character-states, phylogenetic signals, and correlations for
 certain categorical and continuous floral traits. Further, we employed
 phylomorphospace and trait-dependent diversification rate estimation
 analyses to understand phenotypic evolution and associated lineage
 diversification in Hedychium. Although floral color and size lacked any
 association with specific pollinators, white or pale flowers were most
 common in the early branching clades, when compared to bright-colored
 flowers which were more widely represented in the most derived clade IV.
 Five categorical and two continuous characters were identified to have
 informative evolutionary patterns which also emphasized that ecology may
 have played a critical role in the diversification of Hedychium. From our
 phylogenetic analyses and ecological observations, we conclude that
 specializations in pollinator interactions are rare in the hyperdiverse
 clade IV, thus challenging the role of both moth-specialization and
 bird-specialization as central factors in the diversification of
 Hedychium. However, our results also suggest that clade III (predominantly
 island clade) may show specializations, and future studies should
 investigate ecological and pollinator interactions, along with inclusion
 of new traits such as floral fragrance and anthesis time.
description: Please refer to the original manuscript
description: https://www.rstudio.com/
DOI: 10.22008/promice/data/ice_discharge/d/v02/796q0a
title: GIS_coverage.csv

description: Greenland coverage. Git hash: ed4766e
DOI: 10.22008/promice/data/ice_discharge/d/v02/mukxoo
title: gate.nc

description: Gate discharge, coverage, error, and metadata. Git hash: ed4766e
DOI: 10.22008/promice/data/ice_discharge/d/v02/84qgfi
title: GIS_D.csv

description: Greenland discharge. Git hash: ed4766e
DOI: 10.22008/promice/data/ice_discharge/d/v02/jbnn6i
title: GIS.nc

description: Greenland discharge, coverage, and error. Git hash: ed4766e
DOI: 10.22008/promice/data/ice_discharge/d/v02/tzrulh
title: GIS_err.csv

description: Greenland error. Git hash: ed4766e
DOI: 10.25338/b8s92g
title: Lithium-ion battery end-of-life life cycle assessment

description: Lithium-ion batteries are a key technology in decarbonizing the
 transportation and electricity sectors, yet the use of critical materials,
 such as cobalt, nickel, and lithium, leads to environmental and social
 impacts. Reusing, repurposing, and recycling batteries mitigate these
 impacts by extending their lifespan and reducing reliance on virgin
 materials. Innovation that reduces demand for these problematic materials
 and increases battery efficiency also reduces impacts. Two examples of
 this technological innovation include, 1) the development of energy-dense
 cathode chemistry containing less cobalt, a material with high social and
 environmental impacts; and 2) the use of columnar silicon thin film anode,
 which results in increased energy density compared to the commonly used
 graphite anode. This research assesses whether these technological
 innovations change the currently understood waste hierarchy, which
 prioritizes reuse or repurposing prior to recycling. This is of interest
 because retired high-cobalt batteries could supply their constituent
 materials sooner if recycled immediately and be used in low-cobalt,
 higher-performing batteries. The assessment considers the life cycle
 environmental impacts of two end-of-life management routes for a
 high-cobalt lithium-ion battery: first, recycling the battery immediately
 after the first use life to produce a new, and less material-intensive
 battery, and second, repurposing the battery for a stationary storage
 application followed by recycling. Findings show that battery reuse
 reduces life cycle environmental impacts relative to immediate recycling.
 Thus, from an environmental perspective, the waste hierarchy holds, and
 steps to retain the batteries in their highest value use, such as through
 repurposing, should still be prioritized.
description: The inventory has been sourced from EcoInvent and ReCiPe 2016
 midpoint and endpoint characterization factors were used to calculate
 results. Ellingsen et al (2014) and Kallitsis et al. (2021) provided the
 battery construction and relevant inventories.
DOI: 10.22008/promice/data/ice_discharge/d/v02/4m1z9k
title: README.txt

description: README. Git hash: ed4766e
DOI: 10.22008/promice/data/ice_discharge/d/v02/kd5abk
title: region_coverage.csv

description: Regional coverage. Git hash: ed4766e
DOI: 10.22008/promice/data/ice_discharge/d/v02/b7wgka
title: region_err.csv

description: Regional error. Git hash: ed4766e
DOI: 10.22008/promice/data/ice_discharge/d/v02/tnfwvr
title: region_D.csv

description: Regional discharge. Git hash: ed4766e
DOI: 10.5061/dryad.1rn8pk0x4
title: Single-cell expression and TCR data from CD19-specific CAR T cells in a phase I/II clinical trial

description: By leveraging single-cell transcriptome and T cell receptor (TCR)
 sequencing, we aimed to track the transcriptional signatures of CAR T cell
 clonotypes throughout the course of treatment and furthermore identify
 molecular patterns leading to potent CAR T cell cytotoxicity. The data
 presented in this study encompass blood and bone marrow samples from
 patients ≤ 21 years of age with relapsed or refractory B-cell acute
 lymphoblastic leukemia (B-ALL) participating in the SJCAR19 phase I/II
 clinical trial (NCT03573700). In brief, patients enrolled in the clinical
 trial received either 1 x 10^6 (dose level 1) or 3 x 10^6 (dose level 2)
 per kilogram of body weight following successful generation of autologous
 CAR T cell products and lymphodepleting chemotherapy. Peripheral blood was
 drawn from each participant every week until week 4 post-infusion, at week
 6 or 8, and month 3 or 6 if feasible. At week 4 post-infusion, blood
 marrow was also collected from participants. Total T cells (CD3+) were
 sorted from each post-infusion sample, as well as the pre-infusion CAR T
 cell products, and processed through 10x Genomics’ single-cell gene
 expression and V(D)J sequencing platform using the standard protocol. We
 identified a unique and unexpected transcriptional signature in a subset
 of pre-infusion CAR T cells that shared TCRs with post-infusion cytotoxic
 effector CAR T cells. Functional validation of cells with even a subset of
 these pre-effector markers demonstrated their immediate cytotoxic
 potential and resistance to exhaustion.
description: Cells were processed using the Chromium Single Cell V(D)J 5'
 reagents (10X Genomics). T cell receptor V(D)J cDNA was enriched using the
 Chromium Single Cell V(D)J Enrichment kit for Human T cells. Corresponding
 libraries were sequenced on the Illumina NovaSeq platform. Sequencing data
 were processed using CelLRanger v3.1.0 (10X Genomics) with the GRCh38
 reference (v3.0.0) modified to include the first 825 nucleotide bases of
 the CD19-CAR transcript. The resulting gene expression matrices were
 aggregated, with read depth normalization based on the number of mapped
 reads. TCR sequences were processed with version 3.1.0 of the GRCh38 V(D)J
 reference. Aggregated gene expression matrices were
 analyzed using Seurat (Hao et al, Cell 2021). Cells with fewer than 300
 detected genes, more than 4,999 detected genes, with at least 10% of their
 expression owed to mitochondrial genes, or with no detected CD19-CAR UMIs
 (unique molecular identifiers) were excluded from downstream analyses. TCR
 lineages were integrated with gene expression data using shared cellular
 barcodes. Additional analyses are described in the corresponding
 manuscript. 
description: RDS files can be accessed with the readRDS() function in the R
 statistical environment. The Seurat R package can be used to analyze
 Seurat objects and explore included metadata.
DOI: 10.22008/promice/data/ice_discharge/d/v02/rkqmzh
title: region.nc

description: Regional discharge, coverage, and error. Git hash: ed4766e
DOI: 10.22008/promice/data/ice_discharge/d/v02/em8wbe
title: sector_coverage.csv

description: Sector coverage. Git hash: ed4766e
DOI: 10.22008/promice/data/ice_discharge/d/v02/hezsfx
title: sector_D.csv

description: Sector discharge. Git hash: ed4766e
DOI: 10.22008/promice/data/ice_discharge/d/v02/9ixrlo
title: sector.nc

description: Sector discharge, coverage, and error. Git hash: ed4766e
DOI: 10.22008/promice/data/ice_discharge/d/v02/xlfr7w
title: sector_err.csv

description: Sector error. Git hash: ed4766e
DOI: 10.5061/dryad.zpc866tbh
title: A Twitter dataset for Monkeypox outbreak in 2022

description: Right after the COVID-19 pandemic, the Monkeypox virus has infected people
 from more than twenty different countries. The COVID-19 pandemic has badly
 hit the healthcare system, social culture, and the global economy. The
 world does not have the strength to go through another catastrophe. Thus,
 it is very important to contain Monkeypox and stop the spread. This
 dataset includes the tweet id and user id of 2,400,202 tweets
 gathered using keywords related to Monkeypox for researchers to study on
 different subjects such as Monkeypox trend prediction, Monkeypox
 stigmatization, and Monkeypox misinformation and fake news detection.
description: This dataset was gathered using
 Twitter developer's academic researcher API using
 keywords monkeypox or “monkey pox” or “viruela dei mono” or
 “variole du singe” or “variola do macoco” from May 1st to December 25th,
 2022. Originally, the metadata included tweet id, conversation id, in
 reply to user id and in reply to username (in case of the tweet being a
 reply), created at, type (i.e. tweet, replied to, or quoted), language,
 retweets count, reply count, like count, geo id, geo-country,
 geo-province/city, geo-coordinates, author id, author name, author
 username, author description, author-reported location, author hashtags,
 created account at, follower count, following count, tweet count, and
 image URL. However, to comply with Twitter developer's terms of use
 and privacy policy, only the tweet id and user id of 2,400,202 tweets are released to the
 public in this dataset.
description: In compliance with Twitter
 developer's term of use and privacy policy
 agreement<sup>1</sup>, the dataset includes only tweet ids. In
 order to have access to the actual tweets and other metadata the tweet ids
 need to be hydrated. One software that can hydrate the tweet ids is DocNow
 hydrator<sup>2</sup>. After installation, the hydrator needs
 to be authorized using your Twitter account. Next, the file containing the
 tweet ids should be uploaded to the hydrator. The hydrator will return the
 tweets and their metadata in .json by default. However, it can be returned
 in other formats such as .csv as well.
 1 Twitter Developer Platform,
 Developer Agreement and Policy, (Accessed June
 2022), https://developer.twitter.com/en/developer-terms/agreement-and-policy. 2 DocNow Hydrator, Aug 2021, (Accessed: June 2022), GitHub - DocNow/hydrator: Turn Tweet IDs into Twitter JSON & CSV from your desktop!.
DOI: 10.22008/promice/data/ice_discharge/d/v02/4mimoe
title: gate_coverage.csv

description: Gate coverage. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/rek8nk
title: gate_err.csv

description: Gate errors. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/xutile
title: gate_D.csv

description: Gate discharge. Git hash: 0349658
DOI: 10.57903/uj/kajvxf
title: Results of analysis of labelled L-Arginine metabolism in the isolated aorta of 8-month-old and 26-month-old C57BL/6 mice - research data
title: Wyniki analizy metabolizmu znakowanej L-argininy w izolowanej aorcie 8-miesięcznych i 26-miesięcznych myszy C57BL/6 - dane badawcze

description: This dataset contains raw results of tracer-based metabolomics of the aorta of 8-month-old and 26-month-old C57BL/6 mice using labelled L-arginine.
DOI: 10.22008/promice/data/ice_discharge/d/v02/b8iebm
title: gate.nc

description: Gate discharge, coverage, error, and metadata. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/k7ed3g
title: GIS_coverage.csv

description: Greenland coverage. Git hash: 0349658
DOI: 10.5061/dryad.gxd2547pr
title: Evaluation of assisted reproductive technology treatment outcomes based on stimulation dosages and anti-mullerian hormone levels

description: Background: Serum concentrations of anti-mullerian hormone (AMH)
 correlate with ovarian response during assisted reproductive (ART)
 treatment cycles. This prospective study was attempted to evaluate the
 selection of ovarian stimulation protocols based on serum AMH levels in
 patients and its impact on the results of ART. Results According to the
 AMH levels, majority of the patients were normal responders (52.4%)
 followed by high responders (29.8%) and low responders (17.8%). The
 average FSH, HMG per day and number of days HMG required was found to be
 significant among the different responders. Further, retrieval rate and
 blastulation rate was found to be significant among the different
 responders. A positive correlation was found between AMH and number of
 oocytes retrieved and number of oocytes successfully fertilized and it was
 found to be significant. In addition, there was a significant inverse
 relationship between AMH levels and age. Conclusion The study outcome
 reveals that retrieval rate, maturation rate, fertilization rate, embryo
 utilization rate and blasturation rate were higher among the high
 responders as compared to low responders. Thus, proper increase in dosages
 of ovarian stimulation protocol is required among the low responders to
 achieve quality embryos.
description: Based on the serum AMH, 191
 women were classified as low, normal and high responders. Follicle
 Stimulating Hormone (FSH) and Human Menopausal Gonadotropin (HMG) dosages
 in controlled ovarian stimulation were determined. Retrieval, maturation,
 fertilization and utilization rates were measured. Subgroup analysis was
 done using One way ANOVA followed by post hoc analysis. The relationship
 between AMH levels and fertilization was done using Pearson’s correlation analysis. A p value
 &lt;0.05 was considered as statistically
 significant.
DOI: 10.22008/promice/data/ice_discharge/d/v02/n83w6p
title: GIS_D.csv

description: Greenland discharge. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/sj7npc
title: GIS.nc

description: Greenland discharge, coverage, and error. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/w47wzd
title: GIS_err.csv

description: Greenland error. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/bq0rkp
title: README.txt

description: README. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/ij74sa
title: region_coverage.csv

description: Regional coverage. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/y3j78p
title: region_D.csv

description: Regional discharge. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/wgkpsh
title: region.nc

description: Regional discharge, coverage, and error. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/ywwxy2
title: region_err.csv

description: Regional error. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/hplr2d
title: sector_D.csv

description: Sector discharge. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/mi8zom
title: sector_coverage.csv

description: Sector coverage. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/mmsjyn
title: sector_err.csv

description: Sector error. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/vyzq3h
title: sector.nc

description: Sector discharge, coverage, and error. Git hash: 0349658
DOI: 10.22008/promice/data/ice_discharge/d/v02/pryxhz
title: gate_coverage.csv

description: Gate coverage. Git hash: 0f04be7b
DOI: 10.22008/promice/data/ice_discharge/d/v02/mpden8
title: gate_D.csv

description: Gate discharge. Git hash: 0f04be7b
DOI: 10.22008/promice/data/ice_discharge/d/v02/obr3ew
title: gate_err.csv

description: Gate errors. Git hash: 0f04be7b
DOI: 10.5061/dryad.qz612jmj7
title: To a charismatic rescue: Designing a blueprint to steer fishing cat conservation for safeguarding Indian wetlands

description: Wetland conservation in the Indo-tropics can benefit from the protection
 of the charismatic Fishing Cat. India, supporting ∼ 40%
 of its known range, is a stronghold for the species. Here, using multiple
 information sources we outline a framework to safeguard fishing cats in
 India. Specifically, we a) estimated district-level Conservation priority
 scores (using presence records, and habitat suitability and habitat
 connectivity) to identify ecologically important habitats, b) estimated
 state-level Conservation likelihood scores assessing the success potential
 of any conservation intervention, c) collated district-level Conservation
 initiative information identifying ongoing efforts for species and/or
 habitat conservation. We consecutively assessed the spatial congruence
 between (a), (b) and (c) to delineate species’ conservation areas
 and corresponding action goals (blueprint). Using information on habitat
 suitability, we also delineated survey landscapes. Although Fishing Cat
 records were found in 12 Indian states, only a small proportion of the
 state area was identified harbouring optimal habitat for the species.
 Three broad habitat clusters - Terai arc, Eastern coast, and Brahmaputra
 floodplains - were identified, with overall high habitat connectivity.
 Most districts ranking high in Conservation priority scored low in
 Conservation likelihood. Districts with Fishing Cat presence
 (n = 60) were delineated into four tiers of action
 landscapes and the majority of districts classified as survey landscapes
 (n = 156) were found in the Terai arc. We use our
 results to recommend and discuss conservation actions for districts
 identified in our blueprint. Flagship species conservation approach has
 substantial potential to enrich wetland conservation, for which our
 blueprint can act as a baseline.
DOI: 10.22008/promice/data/ice_discharge/d/v02/aixqr0
title: gate.nc

description: Gate discharge, coverage, error, and metadata. Git hash: 0f04be7b
DOI: 10.22008/promice/data/ice_discharge/d/v02/knz8dk
title: GIS_coverage.csv

description: Greenland coverage. Git hash: 0f04be7b
DOI: 10.22008/promice/data/ice_discharge/d/v02/wghf4u
title: GIS_D.csv

description: Greenland discharge. Git hash: 0f04be7b
DOI: 10.18112/openneuro.ds007275.v1.0.0
title: Semantic Mnemonic Similarity Task (sMST) - fMRI dataset
DOI: 10.22008/promice/data/ice_discharge/d/v02/bpu7py
title: GIS.nc

description: Greenland discharge, coverage, and error. Git hash: 0f04be7b
DOI: 10.22008/promice/data/ice_discharge/d/v02/jv6wyd
title: GIS_err.csv

description: Greenland error. Git hash: 0f04be7b