cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/r1w6-8h42
title: Quantitative Assessment of Functional Object Interactions After Stroke

description: Many individuals after stroke exhibit upper extremity (UE) motor impairments. Manual interactions with objects are ubiquitous in everyday life and impaired interactive abilities result in loss of independence. Hence, understanding how deficits of UE manifest in functional interactions with objects is important for neurorehabilitation. However, detailed quantitative measurements of such intricate skills have been elusive so that current quantification of motor impairment has focused on impairment. This paper introduces a portable, low-cost device custom-designed (MAGIC Table) to record real-time kinematics of a functional skill, the transport of a complex object, i.e., a ‘cup of coffee’, on a table surface. Participants move a 3D-printed cup with a rolling ball inside, representing the sloshing coffee. Three participants after stroke and three able-bodied participants performed a planar elbow flexion-extension movement while holding the cup without losing the ball. Performance recorded via a webcam mounted above the table, was evaluated with both conventional metrics, i.e., movement time and smoothness, and novel kinematic metrics, i.e., risk and predictability, derived in previous theoretical research on the same task. Movement time and smoothness were less sensitive to functional ability than risk and predictability. Able-bodied participants engaged in more risky strategies, but also prioritized predictability of object dynamics. The stroke survivors were risk averse and had less predictable interactions. These results showed the feasibility of the new device and promise that the new theory-based analyses can be leveraged for novel insights into functional skill after stroke.
DOI: 10.6084/m9.figshare.20063363
title: Xanthism in Phyllomedusidae (Amphibia: Anura), with a review on anuran colour anomalies.docx

description: We have compiled a list of colour anomalies in anurans by accessing papers published in the journals <em>Herpetological Review, Herpetology Notes</em>, and <em>Herpetological Bulletin</em>, as well as via Internet searches using the keywords ‘color/colour/coloration’, ‘anomaly/anomalies’, and ‘anurans/tadpoles’. Such a procedure was adopted because most of the anuran colour records are anecdotal and thus not published in highly indexed journals. We classified these records within six biogeographic realms (Nearctic, Neotropic, Palearctic, Afrotropic, Indomalayan, and Australasia) according to Dinerstein et al. (2017). Papers on chromatic anomalies in anurans published in the year 2022 were included in our review until the peer review deadline of our article
DOI: 10.6084/m9.figshare.20063363.v1
title: Xanthism in Phyllomedusidae (Amphibia: Anura), with a review on anuran colour anomalies.docx

description: We have compiled a list of colour anomalies in anurans by accessing papers published in the journals <em>Herpetological Review, Herpetology Notes</em>, and <em>Herpetological Bulletin</em>, as well as via Internet searches using the keywords ‘color/colour/coloration’, ‘anomaly/anomalies’, and ‘anurans/tadpoles’. Such a procedure was adopted because most of the anuran colour records are anecdotal and thus not published in highly indexed journals. We classified these records within six biogeographic realms (Nearctic, Neotropic, Palearctic, Afrotropic, Indomalayan, and Australasia) according to Dinerstein et al. (2017). Papers on chromatic anomalies in anurans published in the year 2022 were included in our review until the peer review deadline of our article
DOI: 10.6084/m9.figshare.20063402
title: Mm1 tumor single cell RNA-seq data

description: Seurat matrix referring to scRNA-seq of Mm1 mouse tumors in CyC manuscript
DOI: 10.6084/m9.figshare.20063402.v1
title: Mm1 tumor single cell RNA-seq data

description: Seurat matrix referring to scRNA-seq of Mm1 mouse tumors in CyC manuscript
DOI: 10.6084/m9.figshare.20063375
title: Invasive grass and litter accumulation constrain bee and plant diversity in altered grasslands

description: Ecologists consider biological invasions one of the primary drivers of global change. Many remaining grasslands in North America have extensive invasions of exotic grass species that have replaced native plant species. In the Northern Great Plains, exotic cool-season grasses Kentucky bluegrass (<em>Poa pratensis</em>) and smooth brome (<em>Bromus inermis</em>), paired with human alterations to the landscape and historical disturbance regimes, have resulted in functionally and structurally altered grassland plant communities. These changes may extend to impact species that rely on these plant communities, such as bees. Bees are ecologically diverse and serve important pollinator roles but are at risk from the loss and change of floral and nesting resources in plant communities. Our objectives were to determine whether Kentucky bluegrass and smooth brome alter the bee and forb species richness in invaded Northern Great Plains grasslands and how litter accumulation, grass cover, and the amount of bare ground interact with bee functional traits. To do this, we surveyed 67 grassland sites from 2017-2020 with two bee-sampling methods (268 netting and bee bowl surveys total) and vegetation cover surveys at each site. We collected 20,111 bees from 182 bee species and observed 249 forb and shrub species in vegetation surveys. Bee richness was higher with greater forb richness, but the latter was significantly lower with thicker litter depths and higher with a greater coverage of all grasses other than Kentucky bluegrass and smooth brome. Bee trait analyses showed varying relationships with plant community variables. Of these, litter depth and Kentucky bluegrass cover reduced ground-nesting bee abundance while small-bodied bees increased with bare ground. While our results support the close relationship between bee and plant diversity, we also found litter depth, in particular, influenced the structure of these two communities. Specifically, Kentucky bluegrass and smooth brome are two exotic grass species associated with thatch-forming litter layers, especially under idle management that appear to simplify bee and forb communities. Our results make apparent the importance in maintaining structural and compositional diversity in invaded grasslands to support diverse bee communities.
DOI: 10.6084/m9.figshare.20063375.v1
title: Invasive grass and litter accumulation constrain bee and plant diversity in altered grasslands

description: Ecologists consider biological invasions one of the primary drivers of global change. Many remaining grasslands in North America have extensive invasions of exotic grass species that have replaced native plant species. In the Northern Great Plains, exotic cool-season grasses Kentucky bluegrass (<em>Poa pratensis</em>) and smooth brome (<em>Bromus inermis</em>), paired with human alterations to the landscape and historical disturbance regimes, have resulted in functionally and structurally altered grassland plant communities. These changes may extend to impact species that rely on these plant communities, such as bees. Bees are ecologically diverse and serve important pollinator roles but are at risk from the loss and change of floral and nesting resources in plant communities. Our objectives were to determine whether Kentucky bluegrass and smooth brome alter the bee and forb species richness in invaded Northern Great Plains grasslands and how litter accumulation, grass cover, and the amount of bare ground interact with bee functional traits. To do this, we surveyed 67 grassland sites from 2017-2020 with two bee-sampling methods (268 netting and bee bowl surveys total) and vegetation cover surveys at each site. We collected 20,111 bees from 182 bee species and observed 249 forb and shrub species in vegetation surveys. Bee richness was higher with greater forb richness, but the latter was significantly lower with thicker litter depths and higher with a greater coverage of all grasses other than Kentucky bluegrass and smooth brome. Bee trait analyses showed varying relationships with plant community variables. Of these, litter depth and Kentucky bluegrass cover reduced ground-nesting bee abundance while small-bodied bees increased with bare ground. While our results support the close relationship between bee and plant diversity, we also found litter depth, in particular, influenced the structure of these two communities. Specifically, Kentucky bluegrass and smooth brome are two exotic grass species associated with thatch-forming litter layers, especially under idle management that appear to simplify bee and forb communities. Our results make apparent the importance in maintaining structural and compositional diversity in invaded grasslands to support diverse bee communities.
DOI: 10.5281/zenodo.6640230
title: Parastichopus regalis decontaminated gx

description: .
DOI: 10.5281/zenodo.6640229
title: Parastichopus regalis decontaminated gx

description: .
DOI: 10.5281/zenodo.6640245
title: Pseudoscaphirhynchus fedtschenkoi decontaminated gx

description: .
DOI: 10.5281/zenodo.6640244
title: Pseudoscaphirhynchus fedtschenkoi decontaminated gx

description: .
DOI: 10.5281/zenodo.6640237
title: Bergia puertoricense decontamination gx

description: .
DOI: 10.5281/zenodo.6640236
title: Bergia puertoricense decontamination gx

description: .
DOI: 10.5281/zenodo.6339639
title: Quantitative relationships between river and channel-belt planform patterns

description: This repository contains shapefiles of channel-belt centerline and edges used a manuscript titled "Quantitative relationships between river and channel-belt planform patterns" in Geology
DOI: 10.5281/zenodo.6339638
title: Quantitative relationships between river and channel-belt planform patterns

description: This repository contains shapefiles of channel-belt centerline and edges used a manuscript titled "Quantitative relationships between river and channel-belt planform patterns" in Geology
DOI: 10.5519/qd.1thejsp8
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1001 records)
DOI: 10.5281/zenodo.6640258
title: Dryas integrifolia decontaminated gx

description: .
DOI: 10.5281/zenodo.6640257
title: Dryas integrifolia decontaminated gx

description: .
DOI: 10.6069/a2gd-j353
title: Development Assistance for Human Resources for Health 1990-2020

description: These development assistance for human resources for health (DAHRH) estimates are generated using data from IHME’s Development Assistance for health Database DAH, COVID development assistance database and the Organization for Economic Cooperation and Development’s Creditor Reporting System (CRS) online database. The IHME databases enables comprehensive analysis of donor funding aimed towards activities that support the health workforce in low- and middle-income countries from key agencies. The DAHRH estimates are disaggregated by source of funds, channel (disbursing agency) of funding, geographic region (Global Burden of Disease Study (GBD) super region), and the type of human resources for health activities supported (program areas).
DOI: 10.5281/zenodo.2614004
title: CMT precipitation dataset for numerical models of the ocean

description: Total and liquid precipitation datasets created with the method described in <strong>Bias and trend correction of precipitation datasets to force ocean models</strong> (<em>Dussin, JTECH, in revision)</em>.
description: This research from the Geophysical Fluid Dynamics Laboratory is supported by NOAA's Science Collaboration Program and administered by UCAR's Cooperative Programs for the Advancement of Earth System Science (CPAESS) under awards NA16NWS4620043 and NA18NWS4620043B.
DOI: 10.5281/zenodo.2614003
title: CMT precipitation dataset for numerical models of the ocean

description: Total and liquid precipitation datasets created with the method described in <strong>Bias and trend correction of precipitation datasets to force ocean models</strong> (<em>Dussin, JTECH, in revision)</em>.
description: This research from the Geophysical Fluid Dynamics Laboratory is supported by NOAA's Science Collaboration Program and administered by UCAR's Cooperative Programs for the Advancement of Earth System Science (CPAESS) under awards NA16NWS4620043 and NA18NWS4620043B.
DOI: 10.6084/m9.figshare.20063450
title: This flower is our bed: long-term citizen science reveals that hummingbird flies select sleeping places by the shape of the flowers

description: Dataset for the manuscript "This flower is our bed: long-term citizen science reveals that hummingbird flies select sleeping places by the shape of the flowers"
DOI: 10.5281/zenodo.6640285
title: Mouse Brain snRNASeq and Visium Demo Dataset for CelEry

description: ## snRNASeq data generated from control mouse brain 3 brain regions. Animal IDs 7 Brain region codes:<br> 7W-1: WhiteMatter<br> 7H-1: Hippo<br> 7G-1: GreyMatter 10X standard mm10 (3.0.0) reference was used, on cellranger 5.0.0 with --include-introns on. <br> ## Visium data generated from the same animal control mouse full half brains Animal IDs 14 (075B slice) 10X standard mm10 (2020-A) reference and spaceranger 1.1.0 was used<br>
DOI: 10.5281/zenodo.6640284
title: Mouse Brain snRNASeq and Visium Demo Dataset for CelEry

description: ## snRNASeq data generated from control mouse brain 3 brain regions. Animal IDs 7 Brain region codes:<br> 7W-1: WhiteMatter<br> 7H-1: Hippo<br> 7G-1: GreyMatter 10X standard mm10 (3.0.0) reference was used, on cellranger 5.0.0 with --include-introns on. <br> ## Visium data generated from the same animal control mouse full half brains Animal IDs 14 (075B slice) 10X standard mm10 (2020-A) reference and spaceranger 1.1.0 was used<br>
DOI: 10.5281/zenodo.6640283
title: SocialDisNER corpus: gold standard annotations for detection of disease mentions in Spanish tweets

description: Gold Standard annotations for <strong>SocialDisNER </strong>(SMM4H 2022 – Task 10) shared task. <strong>Introduction:</strong><br> The <strong>SocialDisNER corpus</strong> of the SMM4H 2022 – Task 10 task will focus on the recognition of disease mentions in tweets written in Spanish after selecting primarily<strong><em> first-hand experience of diseases</em></strong> and other health-relevant content (from patient associations, professional healthcare institutions, and through followers of patient association accounts of a <em>diversity of pathologies</em> including rare diseases, mental health, cancer, etc..). The corpus was manually annotated by medical experts following the SMM4H-SocialDisNER guidelines. These guidelines were adapted from previous efforts used to annotate patient clinical records and medical literature. It covers rules for annotating <strong>mentions of diseases</strong> in health-related tweets in Spanish, The training set consists of 5000 tweets written in Spanish and the validation set consists of 2500 tweets written in Spanish. Both sets have been manually annotated by healthcare professionals. The unannotated test set will be published shortly. The structure of the dataset is: socialdisner.zip: <strong><em>train-valid-txt-files</em></strong>: folder with training and validation text files. One text file per tweet, the file name corresponds to the tweet id. One sub-directory per corpus split (train and valid). The files named <em>ids_dev_set.txt</em> and<em> ids_train_set.txt </em>contain the list of file identifiers for each of the data splits (validation and train). <strong><em>mentions.tsv</em></strong>: This file contains the manually annotated disease mentions. The file has the following fields: <em>tweets_id</em>: This is the id of the tweet, using Twitter API you can query the content of the tweet. <em>Begin</em>: This is the position in the tweet where the annotation was found. <em>End</em>: This is the position of the last character of the annotation in the tweet. <em>Type: </em>This is the type of entity found, in our case "ENFERMEDAD". <em>Extraction</em>: This is the literal extraction, in other words, the fragment of text which refers to the annotation. For further information, please visit https://temu.bsc.es/socialdisner/ Do not share the data with other individuals/teams without permission from the task organizer. Tweets IDs are the primary source of information. Tweet texts are provided as support material. By downloading this resource, you agree to the Twitter Terms of Service, Privacy Policy, Developer Agreement, and Developer Policy.
DOI: 10.13012/b2idb-3112432_v1
title: County-level Data of Nitrogen Fertilizer and Manure Inputs for Corn Production in the United States

description: This dataset includes five files developed using the procedures described in the article 'Developing County-level Data of Nitrogen Fertilizer and Manure Inputs for Corn Production in the United States' and Supplemental Information published in the Journal of Cleaner Production in 2021. Citation: Xia, Yushu, Hoyoung Kwon, and Michelle Wander. "Developing county-level data of nitrogen fertilizer and manure inputs for corn production in the United States." Journal of Cleaner Production 309 (2021): e126957. Brief method: The fertilizer and manure inputs for corn were generated with a top-down approach by assigning county-level total N inputs reported by USGS to different crops using state- and county-level survey data. The corn N needs were estimated using empirical extension-based equations coupled with soil and environmental covariates. The estimates of fertilizer N inputs were further refined for corn grain and silage production at the county level and gap-filling (using state-level averages) was carried out to generate final files for U.S. county-level N inputs. The dataset is provided in an alternative format in Google Earth Engine: https://code.earthengine.google.com/13a0078e7ee727bc001e045ad0e8c6fc
DOI: 10.5517/ccdc.csd.cc2bf2mh
title: CCDC 2157526: Experimental Crystal Structure Determination

description: Related Article: Evangelos Pilichos, Mercè Font-Bardia, Joan Cano, Albert Escuer, Júlia Mayans|2022|Dalton Trans.|51|8986|doi:10.1039/D2DT00880G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.20063480
title: June 2022 Small GEA simulation

description: README <br> Simulations correspond to those originally run in Lotterhos and Whitlock, 2015 (https://doi.org/10.1111/mec.13100). RDA was run as in Forester et al. 2017 (DOI: 10.1111/mec.14584), and loci that has locus scores +-3SD were considered significant. <br> Files: <br> meta.7z contains meta.test.csv, which contains the original simulation metadata from Lotterhos and Whitlock 2015 as provided in the SummaryFiles directory, with two additional columns appended: SNP (which can be ignored), Pval (which is the p-value for a multiple CMR knockoffs test), RDA (which signifies whether a locus was significant in redundancy analysis/RDA) and causal (which was used to calculate model performance). <br> Inds.csv indicates the simulations from Lotterhos and Whitlock 2015 used in this short test. <br> Analysis.R provides code to recreate the figure GEA.pdf, given the meta.test.csv file. <br> FastRDAscores.R provides a quick function to calculate locus scores/species scores for a univariate RDA. Note that values are scaled, and are equivalent to scaling locus scores from RDA, but outlier tests should be unaffected. <br>
DOI: 10.34740/kaggle/dsv/3796899
title: US counties COVID 19 dataset
DOI: 10.5281/zenodo.6640270
title: Buteogallus aequinoctialis decontaminated gx

description: .
DOI: 10.5281/zenodo.6640269
title: Buteogallus aequinoctialis decontaminated gx

description: .
DOI: 10.5281/zenodo.6629912
title: RL-MLZerD: Multimeric protein docking using reinforcement learning

description: This is the dataset used in the publication:<strong> RL-MLZerD: Multimeric protein docking using reinforcement learning by Tunde Aderinwale, Charles Christoffer and Daisuke Kihara</strong>, in submission 2022. The dataset included 30 protein complexes targets from 3 to 5 chains used for docking. Each target in the dataset are randomly rotated and shifted three times to remove bias to the starting conformation. We also include the docking results for each target in the corresponding directory for all the methods reported in the manuscript. For each target, 1500 to 12,000 models were provided that were generated by RL-MLZerD, 1700 to 12,000 models for Multi-LZerD, about 100 to 300 models by Combdock, and 5 models each by Alphafold-Multimer, Alphafold-Multimer (no template), and ColabFold respectively. Directory description: Target: contains all the files related to all experiment for that target e.g 1A0R<br> Target/*_mod_run_? contain files for all random rotation experiments and combdock results. e.g 1A0R/1A0R_mod_run_1/<br> Target/*_mod_combine_athird contains files for combined rotation experiment for RL-MLZerD and Multilzerd. e.g 1A0R/1A0R_mod_combine_athird/<br> Target/alphafold_multimer contains prediction files for AlphaFold-Multimer, both regular and no template run. e.g alphafold_multimer/1a0r and alphafold_multimer/1a0r_nodb<br> Target/colabfold contains prediction files for ColabFold results. e.g colabfold/prediction_1a0r
DOI: 10.5281/zenodo.6629911
title: RL-MLZerD: Multimeric protein docking using reinforcement learning

description: This is the dataset used in the publication:<strong> RL-MLZerD: Multimeric protein docking using reinforcement learning by Tunde Aderinwale, Charles Christoffer and Daisuke Kihara</strong>, in submission 2022. The dataset included 30 protein complexes targets from 3 to 5 chains used for docking. Each target in the dataset are randomly rotated and shifted three times to remove bias to the starting conformation. We also include the docking results for each target in the corresponding directory for all the methods reported in the manuscript. For each target, 1500 to 12,000 models were provided that were generated by RL-MLZerD, 1700 to 12,000 models for Multi-LZerD, about 100 to 300 models by Combdock, and 5 models each by Alphafold-Multimer, Alphafold-Multimer (no template), and ColabFold respectively. Directory description: Target: contains all the files related to all experiment for that target e.g 1A0R<br> Target/*_mod_run_? contain files for all random rotation experiments and combdock results. e.g 1A0R/1A0R_mod_run_1/<br> Target/*_mod_combine_athird contains files for combined rotation experiment for RL-MLZerD and Multilzerd. e.g 1A0R/1A0R_mod_combine_athird/<br> Target/alphafold_multimer contains prediction files for AlphaFold-Multimer, both regular and no template run. e.g alphafold_multimer/1a0r and alphafold_multimer/1a0r_nodb<br> Target/colabfold contains prediction files for ColabFold results. e.g colabfold/prediction_1a0r
DOI: 10.5517/ccdc.csd.cc2bf2nj
title: CCDC 2157527: Experimental Crystal Structure Determination

description: Related Article: Evangelos Pilichos, Mercè Font-Bardia, Joan Cano, Albert Escuer, Júlia Mayans|2022|Dalton Trans.|51|8986|doi:10.1039/D2DT00880G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.