cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5519/qd.zbyhrqgg
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (15 records)
DOI: 10.5281/zenodo.8195682
title: Study on soybean transcriptomics

description: Study of exogenous melatonin on transcriptomics of soybean under drought stress
DOI: 10.5281/zenodo.8195681
title: Study on soybean transcriptomics

description: Study of exogenous melatonin on transcriptomics of soybean under drought stress
DOI: 10.34740/kaggle/dsv/6217252
title: arXiv Dataset
DOI: 10.6084/m9.figshare.23804604
title: Total, ionic and electronic conductivity.xlsx

description: conductivity of LMS
DOI: 10.5281/zenodo.8196170
title: anatoma_sagamiana_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196169
title: anatoma_sagamiana_zanfona_1.fasta.gz

description: .
DOI: 10.5519/qd.prr601ae
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (6 records)
DOI: 10.5519/qd.zt2icnvl
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4 records)
DOI: 10.5281/zenodo.8196174
title: urticina_crassicornis_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196173
title: urticina_crassicornis_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196180
title: pseudorimula_midatlantica_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196179
title: pseudorimula_midatlantica_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196186
title: peltospira_smaragdina_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196185
title: peltospira_smaragdina_zanfona_1.fasta.gz

description: .
DOI: 10.6084/m9.figshare.23804700
title: Tabela de Custos do sistema TEvap.

description: Tabela com os custos estimados do sistema TEvap com base no SINAPI (2023).
DOI: 10.6084/m9.figshare.23804700.v1
title: Tabela de Custos do sistema TEvap.

description: Tabela com os custos estimados do sistema TEvap com base no SINAPI (2023).
DOI: 10.5281/zenodo.8196188
title: peltospira_smaragdina_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196187
title: peltospira_smaragdina_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196192
title: peltospira_operculata_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196191
title: peltospira_operculata_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196202
title: lepetodrilus_cristatus_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196201
title: lepetodrilus_cristatus_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7820056
title: Hourly SNOTEL Data

description: This workflow build on STAR★Methods published in Heggli et al., 2022 (https://doi.org/10.1016/j.isci.2022.104240). The data and code published here is free to use, but please cite the original paper with the peer-reviewed STAR★Methods when using the data or this code. This code reflects improvements to the original code and was presented at 2023 Western Snow Conference. Level 3 hand-cleaned data produced by Anne Heggli with these methods can be found in this repository. PRIOR TO USE PLEASE UNDERSTAND:<br> The temperature parameter incorporates the NOAA9 9th order polynomial bias correction issued by the NRCS in the Level 1 data process. <br> The code includes an experimental precipitation QC process that should be used with an abundance of caution as precipitation gauges experience snow plugs that can result in entire snowfall events being missed for days to weeks on end.<br> This is an evolving workflow that is a step towards improving the quality of hourly SNOTEL data. I do expect to improve upon these methods in the coming years and I hope that others will collaborate to improve the code and process so that we may all be able to make use of the rich data set. <br> This data process is not an official product of the NRCS and should not be reflected as one in any research. It is just one method to make use of the SNOTEL network data. HOW TO USE THE CODE:<br> These files are designed to be used consecutively. <br> First, use the DownloadSNOTEL.py file to download hourly and daily SNOTEL data from the stations and water years of interest. <br> Second, use SNOTEL_L0.py file to remove the daily QC'd value in the midnight stamps.<br> Third, use SNOTEL_L1.py followed by SNOTEL_L2.py file to automate the Level 1 and Level 2 process. If you wish to clean the data manually (Level 3), don't hesitate to get in touch with anne.heggli@dri.edu for the Level 3 process. I am happy to share and help, but it is a bit complicated so I would prefer to walk anyone through these methods if they would like to use them. QA & QC FLAGS:<br> Flag : Name : Description<br> Quality Assurance (QA) Flags<br> R : Raw : No Human Review<br> F : Flagged : Automated QC Flag Assigned<br> P : Provisional : Preliminary Human Review<br> A : Approved : Processing and Final Review Completed<br> Quality Control (QC) Flags<br> V : Valid : Valid observed value<br> E : Edit : Edit existing value<br> S : Suspect : Suspect value
DOI: 10.5281/zenodo.7820055
title: Hourly SNOTEL Data

description: This workflow build on STAR★Methods published in Heggli et al., 2022 (https://doi.org/10.1016/j.isci.2022.104240). The data and code published here is free to use, but please cite the original paper with the peer-reviewed STAR★Methods when using the data or this code. This code reflects improvements to the original code and was presented at 2023 Western Snow Conference. Level 3 hand-cleaned data produced by Anne Heggli with these methods can be found in this repository. PRIOR TO USE PLEASE UNDERSTAND:<br> The temperature parameter incorporates the NOAA9 9th order polynomial bias correction issued by the NRCS in the Level 1 data process. <br> The code includes an experimental precipitation QC process that should be used with an abundance of caution as precipitation gauges experience snow plugs that can result in entire snowfall events being missed for days to weeks on end.<br> This is an evolving workflow that is a step towards improving the quality of hourly SNOTEL data. I do expect to improve upon these methods in the coming years and I hope that others will collaborate to improve the code and process so that we may all be able to make use of the rich data set. <br> This data process is not an official product of the NRCS and should not be reflected as one in any research. It is just one method to make use of the SNOTEL network data. HOW TO USE THE CODE:<br> These files are designed to be used consecutively. <br> First, use the DownloadSNOTEL.py file to download hourly and daily SNOTEL data from the stations and water years of interest. <br> Second, use SNOTEL_L0.py file to remove the daily QC'd value in the midnight stamps.<br> Third, use SNOTEL_L1.py followed by SNOTEL_L2.py file to automate the Level 1 and Level 2 process. If you wish to clean the data manually (Level 3), don't hesitate to get in touch with anne.heggli@dri.edu for the Level 3 process. I am happy to share and help, but it is a bit complicated so I would prefer to walk anyone through these methods if they would like to use them. QA & QC FLAGS:<br> Flag : Name : Description<br> Quality Assurance (QA) Flags<br> R : Raw : No Human Review<br> F : Flagged : Automated QC Flag Assigned<br> P : Provisional : Preliminary Human Review<br> A : Approved : Processing and Final Review Completed<br> Quality Control (QC) Flags<br> V : Valid : Valid observed value<br> E : Edit : Edit existing value<br> S : Suspect : Suspect value
DOI: 10.5281/zenodo.8196212
title: lepetodrilus_galriftensis_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196211
title: lepetodrilus_galriftensis_zanfona_1.fasta.gz

description: .
DOI: 10.34740/kaggle/dsv/6217337
title: Youtube Trending Video - Taiwan & Hong Kong
DOI: 10.5281/zenodo.8196216
title: lepetodrilus_ovalis_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196215
title: lepetodrilus_ovalis_zanfona_1.fasta.gz

description: .
DOI: 10.6084/m9.figshare.23804757.v1
title: GoNogo-XMeng.xlsx

description: The experimental design employed a 3 (characters: father, mother, romantic partner) × 2 (attribute: positive, negative) within-subject design, utilizing a Go/No-go associative task. The discrimination index (d') was used as the dependent variable, representing participants' ability to differentiate between attributes associated with different relationship types.
DOI: 10.6084/m9.figshare.23804757
title: GoNogo-XMeng.xlsx

description: The experimental design employed a 3 (characters: father, mother, romantic partner) × 2 (attribute: positive, negative) within-subject design, utilizing a Go/No-go associative task. The discrimination index (d') was used as the dependent variable, representing participants' ability to differentiate between attributes associated with different relationship types.
DOI: 10.5281/zenodo.8196226
title: lepetodrilus_tevnianus_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196225
title: lepetodrilus_tevnianus_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196241
title: nodopelta_heminoda_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196240
title: nodopelta_heminoda_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8196252
title: euphysa_ruthae_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8196251
title: euphysa_ruthae_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.6084/m9.figshare.23796678
title: Table 6: The results of the analysis of sentences written in the article

description: This table contains information about the results of the analysis of sentences written in the article
DOI: 10.6084/m9.figshare.23796678.v2
title: Table 6: The results of the analysis of sentences written in the article

description: This table contains information about the results of the analysis of sentences written in the article
DOI: 10.6084/m9.figshare.23796678.v1
title: Table 7: The results of the analysis of sentences written in the article

description: This table contains information about the results of the analysis of sentences written in the article
DOI: 10.6084/m9.figshare.23676327.v2
title: <strong>Human pressure thresholds drive trade-offs between biodiversity and ecosystem functions in global rivers</strong>

description: The data and code were used only for the reproduction of the main results of the paper
DOI: 10.6084/m9.figshare.23591913
title: <strong>Climate and microbial composition rather than species richness promote multiple ecosystem services across elevational gradients</strong>

description: Mountains are biodiversity hotspots and provide a wide range of ecosystem services. Yet, it remains unclear how ecosystem services change with elevation and if they are predominately regulated by climate or biodiversity. Here, we investigated the elevational distributions of five key ecosystem services (net plant productivity, soil organic carbon, organic matter decomposition, macronutrients, micronutrients) and the diversity of plants and microbes on three mountains of the Hengduan Mountains region, southern China. We found that elevational patterns of plant and bacterial richness and ecosystem services were significant on the three subtropical mountains, with most of patterns changing progressively from unimodal to monotonic with changes in the base elevation. Unexpectedly, plant and bacterial richness were negatively correlated with multiple ecosystem services. Instead, climate and soil pH were the key predictor of most ecosystem services which were additionally triggered by changes of the microbial species composition. This study is the first to observe correlative elevational patterns of biodiversity and ecosystem services with comparable montane gradients. Our results suggest that climate and microbial composition rather than species richness promote multiple ecosystem services across elevational gradients. These novel findings have important implications for understanding mountain biogeography and biodiversity-ecosystem services relationship under global change scenarios.
DOI: 10.6084/m9.figshare.23591913.v1
title: <strong>Climate and microbial composition rather than species richness promote multiple ecosystem services across elevational gradients</strong>

description: Mountains are biodiversity hotspots and provide a wide range of ecosystem services. Yet, it remains unclear how ecosystem services change with elevation and if they are predominately regulated by climate or biodiversity. Here, we investigated the elevational distributions of five key ecosystem services (net plant productivity, soil organic carbon, organic matter decomposition, macronutrients, micronutrients) and the diversity of plants and microbes on three mountains of the Hengduan Mountains region, southern China. We found that elevational patterns of plant and bacterial richness and ecosystem services were significant on the three subtropical mountains, with most of patterns changing progressively from unimodal to monotonic with changes in the base elevation. Unexpectedly, plant and bacterial richness were negatively correlated with multiple ecosystem services. Instead, climate and soil pH were the key predictor of most ecosystem services which were additionally triggered by changes of the microbial species composition. This study is the first to observe correlative elevational patterns of biodiversity and ecosystem services with comparable montane gradients. Our results suggest that climate and microbial composition rather than species richness promote multiple ecosystem services across elevational gradients. These novel findings have important implications for understanding mountain biogeography and biodiversity-ecosystem services relationship under global change scenarios.
DOI: 10.5517/ccdc.csd.cc26gjqy
title: CCDC 2039760: Experimental Crystal Structure Determination

description: Related Article: Yuanyuan Zhang, Jiaping Wu, Wangzhen Qiu, Lihao Liao, Bo Wang, Xiaodan Zhao|2023|Org.Lett.|25|5173|doi:10.1021/acs.orglett.3c01999
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: 10.5517/ccdc.csd.cc26gjrz
title: CCDC 2039761: Experimental Crystal Structure Determination

description: Related Article: Yuanyuan Zhang, Jiaping Wu, Wangzhen Qiu, Lihao Liao, Bo Wang, Xiaodan Zhao|2023|Org.Lett.|25|5173|doi:10.1021/acs.orglett.3c01999
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: 10.5517/ccdc.csd.cc2czbrg
title: CCDC 2203906: Experimental Crystal Structure Determination

description: Related Article: Li Feng, Yuling Teng, Xiangdong Yu, Zeliang Wang, Weidong Rao|2023|Org.Lett.|25|4956|doi:10.1021/acs.orglett.3c01503
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: 10.5517/ccdc.csd.cc2czbsh
title: CCDC 2203907: Experimental Crystal Structure Determination

description: Related Article: Li Feng, Yuling Teng, Xiangdong Yu, Zeliang Wang, Weidong Rao|2023|Org.Lett.|25|4956|doi:10.1021/acs.orglett.3c01503
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: 10.5517/ccdc.csd.cc2czbtj
title: CCDC 2203908: Experimental Crystal Structure Determination

description: Related Article: Li Feng, Yuling Teng, Xiangdong Yu, Zeliang Wang, Weidong Rao|2023|Org.Lett.|25|4956|doi:10.1021/acs.orglett.3c01503
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: 10.5517/ccdc.csd.cc2czbwl
title: CCDC 2203910: Experimental Crystal Structure Determination

description: Related Article: Li Feng, Yuling Teng, Xiangdong Yu, Zeliang Wang, Weidong Rao|2023|Org.Lett.|25|4956|doi:10.1021/acs.orglett.3c01503
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: 10.5517/ccdc.csd.cc2f246w
title: CCDC 2236377: Experimental Crystal Structure Determination

description: Related Article: Li Feng, Yuling Teng, Xiangdong Yu, Zeliang Wang, Weidong Rao|2023|Org.Lett.|25|4956|doi:10.1021/acs.orglett.3c01503
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: 10.5517/ccdc.csd.cc2fl4kr
title: CCDC 2251764: Experimental Crystal Structure Determination

description: Related Article: Hongling Xie, Lei Chen, Zhengyu Han, Zhenkun Yang, Jianwei Sun, Hai Huang|2023|Org.Lett.|25|5011|doi:10.1021/acs.orglett.3c01646
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: 10.5517/ccdc.csd.cc2fn0bg
title: CCDC 2253555: Experimental Crystal Structure Determination

description: Related Article: Weidong Jiang, Ye Li, Jian-Quan Liu, Xiang-Shan Wang|2023|Org.Lett.|25|5123|doi:10.1021/acs.orglett.3c01873
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: 10.5517/ccdc.csd.cc2fn0x1
title: CCDC 2253573: Experimental Crystal Structure Determination

description: Related Article: Weidong Jiang, Ye Li, Jian-Quan Liu, Xiang-Shan Wang|2023|Org.Lett.|25|5123|doi:10.1021/acs.orglett.3c01873
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: 10.5517/ccdc.csd.cc2fndp6
title: CCDC 2253938: Experimental Crystal Structure Determination

description: Related Article: Eugene A. Katlenok, Dmitry M. Kryukov, Alexander E. Kurtsevich, Konstantin M. Degtyarenko, Rashid R. Valiev, Oleg V. Levin, Vadim Yu. Kukushkin, Anton V. Rozhkov|2023|Inorg.Chem.|62|11080|doi:10.1021/acs.inorgchem.3c01136
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: 10.5517/ccdc.csd.cc2fndq7
title: CCDC 2253939: Experimental Crystal Structure Determination

description: Related Article: Eugene A. Katlenok, Dmitry M. Kryukov, Alexander E. Kurtsevich, Konstantin M. Degtyarenko, Rashid R. Valiev, Oleg V. Levin, Vadim Yu. Kukushkin, Anton V. Rozhkov|2023|Inorg.Chem.|62|11080|doi:10.1021/acs.inorgchem.3c01136
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: 10.5517/ccdc.csd.cc2fndr8
title: CCDC 2253940: Experimental Crystal Structure Determination

description: Related Article: Eugene A. Katlenok, Dmitry M. Kryukov, Alexander E. Kurtsevich, Konstantin M. Degtyarenko, Rashid R. Valiev, Oleg V. Levin, Vadim Yu. Kukushkin, Anton V. Rozhkov|2023|Inorg.Chem.|62|11080|doi:10.1021/acs.inorgchem.3c01136
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: 10.5517/ccdc.csd.cc2fnds9
title: CCDC 2253941: Experimental Crystal Structure Determination

description: Related Article: Eugene A. Katlenok, Dmitry M. Kryukov, Alexander E. Kurtsevich, Konstantin M. Degtyarenko, Rashid R. Valiev, Oleg V. Levin, Vadim Yu. Kukushkin, Anton V. Rozhkov|2023|Inorg.Chem.|62|11080|doi:10.1021/acs.inorgchem.3c01136
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: 10.5517/ccdc.csd.cc2fqfby
title: CCDC 2255880: Experimental Crystal Structure Determination

description: Related Article: Hongling Xie, Lei Chen, Zhengyu Han, Zhenkun Yang, Jianwei Sun, Hai Huang|2023|Org.Lett.|25|5011|doi:10.1021/acs.orglett.3c01646
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.23802354
title: Extended Data File 1.xlsx

description: a spreadsheet in the MS Excel format listing cell type, biological processes, disease entities and their prevalence in the literature associated with GPX4. Additionally, relevant keywords for each of the three categories is organized into appropriate groupings.
DOI: 10.6084/m9.figshare.23802354.v1
title: Extended Data File 1.xlsx

description: a spreadsheet in the MS Excel format listing cell type, biological processes, disease entities and their prevalence in the literature associated with GPX4. Additionally, relevant keywords for each of the three categories is organized into appropriate groupings.