cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/6b32f4ea012a6068106736d886546441
title: Spatial and Temporal Patterns in Atmospheric Deposition of Dissolved Organic Carbon

description: Atmospheric deposition of dissolved organic carbon (DOC) to terrestrial ecosystems is a small, but rarely studied component of the global carbon (C) cycle. Emissions of volatile organic compounds (VOC) and organic particulates are the sources of atmospheric C and deposition represents a major pathway for the removal of organic C from the atmosphere. Here, we evaluate the spatial and temporal patterns of DOC deposition using 70 datasets at least one year in length ranging from 40° south to 66° north latitude. Globally, the median DOC concentration in bulk deposition was 1.7 mg L-1. The DOC concentrations were significantly higher in tropical (&lt; 25°) latitudes compared to temperate (&gt; 25°) latitudes. DOC deposition was significantly higher in the tropics because of both higher DOC concentrations and precipitation. Using the global median or latitudinal specific DOC concentrations leads to a calculated global deposition of 202 or 295 Tg C yr-1 respectively. Many sites exhibited seasonal variability in DOC concentration. At temperate sites, DOC concentrations were higher during the growing season; at tropical sites, DOC concentrations were higher during the dry season. Thirteen of the thirty-four long-term (&gt; 10 years) datasets showed significant declines in DOC concentration over time with the others showing no significant change. Based on the magnitude and timing of the various sources of organic C to the atmosphere, biogenic VOCs likely explain the latitudinal pattern and the seasonal pattern at temperate latitudes while decreases in anthropogenic emissions are the most likely explanation for the declines in DOC concentration.
DOI: 10.6084/m9.figshare.5813877.v3
title: Carbocupration of heterosubstituted alkynes

description: Inputs and outputs
DOI: 10.6084/m9.figshare.21318264
title: sentiment

description: describe
DOI: 10.6084/m9.figshare.21318264.v1
title: sentiment

description: describe
DOI: 10.5517/ccdc.csd.cc21m3ph
title: CCDC 1895206: Experimental Crystal Structure Determination

description: Related Article: Burcu Topaloğlu Aksoy, Ismail Erol, Hakan Kandemir, Mehmet F. Saglam, Ibrahim F. Sengul, Bünyemin Çoşut|2023|Inorg.Chim.Acta|544|121230|doi:10.1016/j.ica.2022.121230
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.cc24jfvz
title: CCDC 1982011: Experimental Crystal Structure Determination

description: Related Article: Manoj K. Pal, A. P. Wadawale, Nitish Chauhan, Ananda Guha Majumdar, M. Subramanian, N. Bhuvanesh, Sandip Dey|2021|Polyhedron|211|115547|doi:10.1016/j.poly.2021.115547
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.cc26qgcs
title: CCDC 2047375: Experimental Crystal Structure Determination

description: Related Article: Karin Preinerová, Miroslava Puchoňová, Martin Schoeller, Vladimír Kuchtanin, Noémi Molnárová, Svetlana Kryštofová, Milan Mazúr, Ivan Iľko, Viera Peterková, Ján Moncol|2022|Polyhedron|227|116146|doi:10.1016/j.poly.2022.116146
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.cc26qgdt
title: CCDC 2047376: Experimental Crystal Structure Determination

description: Related Article: Karin Preinerová, Miroslava Puchoňová, Martin Schoeller, Vladimír Kuchtanin, Noémi Molnárová, Svetlana Kryštofová, Milan Mazúr, Ivan Iľko, Viera Peterková, Ján Moncol|2022|Polyhedron|227|116146|doi:10.1016/j.poly.2022.116146
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: 10.6073/pasta/8b74750eed1af2b987e02b4b466e12e7
title: SBC LTER: Ocean: Ocean Currents and Biogeochemistry: Nearshore water profiles (monthly CTD and chemistry), ongoing since 2000

description: This data package contains water chemistry measurements taken monthly at these reefs in the nearshore areas of the Santa Barbra Channel, CA, USA: Arroyo Quemado, Bullito, Naples, Arroyo Burro, Mohawk and Carpinteria. Measurements include standard CTD parameters, nutrients, pigments, particulate CN, total dissolved N and P, stable isotopes of C and N (not all parameters are measured at all stations). Sampling began in November 2000. Some stations are sampled only occasionally. During the first 2 years, CTD data were collected with a SBE19 Seacat Profiler and water samples with a pump. Starting in February 2003, a SBE19-Plus with a rosette sampler was used. There are 3 tables in this dataset. Water chemistry and profiles from "registered stations" (see geographic coverage) are in 2 tables with "registered" in their name. CTD profiles are often collected ad hoc, or as "stations of opportunity". These have been collected in a third table as "non-registered". The station codes for these may be reused, and are not recorded in metadata (but can be found in data).
DOI: 10.5066/p9gf1hy3
title: Data to Fit an Occupancy Model to Trapping Data for the Northwestern Pond Turtle and Red-Eared Slider in the Sacramento Valley (2018) and Sacramento-San Joaquin River Delta (2019)

description: These data represent the results of trapping efforts for native northwestern pond turtles (Actinemys marmorata) and non-native red-eared sliders (Trachemys scripta elegans) in wetlands and irrigation canals in agricultural regions of the Sacramento Valley in 2018 and the Sacramento-San Joaquin River Delta in 2019. In addition to detection data for these two turtle species, the dataset includes habitat data from each trapped site and data on the capture rate of fish, frogs, and tadpoles at each site. These data support the following publication: Fulton, A.M., Rose, J.P. and Halstead, B.J., 2022. Rural turtles: estimating the occupancy of northwestern pond turtles and non-native red-eared sliders in agricultural habitats in california's sacramento valley and sacramento-san joaquin river delta. Northwestern Naturalist, 103(2), pp.97-109. https://doi.org/10.1898/NWN20-22
DOI: 10.6084/m9.figshare.15079074
title: Supplemetary material final draft.docx

description: Evaluation of intestinal response to zinc restriction in pigs. Supplementary table 1 shows the growth performance of pigs in different treatment groups. Supplementary tables 2 and 3 show the differentially expressed genes (DEGs) in ZnR compared with Zn100 and Zn50 respectively. Supplementary tables 4-11 show the panther analysis of the DEGs. Supplementary figure 1 shows top three upregulated and downregulated canonical pathways through IPA analysis of differentially expressed genes in Zn100 compared with Zn50. Z-score &gt;2 or &lt;-2 were considered significantly upregulated (black columns) or downregulated (grey columns) respectively. n=8 for Zn100 and Zn50. <br>
DOI: 10.6084/m9.figshare.15079074.v3
title: Supplemetary material final draft.docx

description: Evaluation of intestinal response to zinc restriction in pigs.Supplementary table 1 shows the growth performance of pigs in different treatment groups. Supplementary tables 2 and 3 show the differentially expressed genes (DEGs) in ZnR compared with ZnCl100 and ZnCl50 respectively.Supplementary tables 4-11 show the panther analysis of the DEGs. Supplementary figure 1 shows top three upregulated and downregulated canonical pathways through IPA analysis of differentially expressed genes in ZnCl100 compared with ZnCl50. Z-score &gt;2 or &lt;-2 were considered significantly upregulated (black columns) or downregulated (grey columns) respectively. n=8 for ZnCl100 and ZnCl50. Supplementary figure 2 shows independent examination of tissue samples by qPCR revealed significant changes similar to log2 fold change values in DEGs. * Mann-Whitney unpaired non-parametric test (p&lt;0.05 was considered significant). n=7 for ZnR, n=8 for ZnCl100 and ZnCl50.
DOI: 10.25921/k32h-dw60
title: EM710 Water Column Sonar Data Collected During NF2001
DOI: 10.5281/zenodo.7190830
title: botula_fusca_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7190829
title: botula_fusca_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7189920
title: Assessing the importance of interspecific interactions in the evolution of microbial communities

description: These data and script are related to the article entitled "Assessing the importance of interspecific interactions in the evolution of microbial communities". This study reports the results of an experiment that aimed at understanding the role of interactions between bacterial species in the evolutionary responses of bacterial communities. The phenotype (optical density) of eight communities composed of two bacterial strains was assessed before and after an experimental evolution of five months (with a transfer each 3.5 days) and compared to the phenotype of communities rebuilt from the same strains that evolved in isolation. The phenotype of the bacterial strains of the study grown in isolation under the three evolutionary treatments (ancestor, evolved in isolation, evolved in community) was also assessed. All the data and codes needed to reproduce the figures and tables presented in the manuscript are provided.
DOI: 10.5281/zenodo.7189919
title: Assessing the importance of interspecific interactions in the evolution of microbial communities

description: These data and script are related to the article entitled "Assessing the importance of interspecific interactions in the evolution of microbial communities". This study reports the results of an experiment that aimed at understanding the role of interactions between bacterial species in the evolutionary responses of bacterial communities. The phenotype (optical density) of eight communities composed of two bacterial strains was assessed before and after an experimental evolution of five months (with a transfer each 3.5 days) and compared to the phenotype of communities rebuilt from the same strains that evolved in isolation. The phenotype of the bacterial strains of the study grown in isolation under the three evolutionary treatments (ancestor, evolved in isolation, evolved in community) was also assessed. All the data and codes needed to reproduce the figures and tables presented in the manuscript are provided.
DOI: 10.5281/zenodo.7190923
title: phoronis_ovalis_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7190922
title: phoronis_ovalis_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7190942
title: SPSS dataset for data-1989549

description: This research used a quantitative and exploratory approach through the collection and analysis of data (SPSS) from a total of 377 survey respondents.
DOI: 10.5281/zenodo.7190941
title: SPSS dataset for data-1989549

description: This research used a quantitative and exploratory approach through the collection and analysis of data (SPSS) from a total of 377 survey respondents.
DOI: 10.6084/m9.figshare.19665828
title: Naves-Alegre et al. (2022) - Data and code

description: Data for manuscript <strong>“</strong><em><strong>Scavenging in the realm of senses: smell and vision drive recruitment at carcasses in Neotropical ecosystems”</strong></em> accepted in <em>Proceedings of the Royal Society B</em>
DOI: 10.6084/m9.figshare.19665828.v3
title: Naves-Alegre et al. (2022) - Data and code

description: Data for manuscript <strong>“</strong><em><strong>Scavenging in the realm of senses: smell and vision drive recruitment at carcasses in Neotropical ecosystems”</strong></em> accepted in <em>Proceedings of the Royal Society B</em>
DOI: 10.6084/m9.figshare.19665828.v2
title: Naves-Alegre et al. (2022) - Data and code

description: Data for manuscript <strong>“</strong><em><strong>Scavenging in the realm of senses: smell and vision drive recruitment at carcasses in neotropical ecosystems”</strong></em> submitted for consideration for publication in <em>Proceedings of the Royal Society B</em>
DOI: 10.17632/sdmx343stj.1
title: Dimensionless Sherwood number data pertaining to micro-structured heterogeneous steam reforming reactor systems at different flow velocities

description: The Sherwood number, also called the mass transfer Nusselt number, is a dimensionless number used in mass-transfer operation. The Sherwood number represents the ratio of the convective mass transfer to the rate of diffusive mass transport. Using dimensional analysis, the Sherwood number can also be further defined as a function of the Reynolds and Schmidt numbers. A more specific correlation is the Froessling equation. This form is applicable to molecular diffusion from a single spherical particle. It is particularly valuable in situations where the Reynolds number and Schmidt number are readily available. Since the Reynolds and Schmidt numbers are both dimensionless numbers, the Sherwood number is also dimensionless. These correlations are the mass transfer analogies to heat transfer correlations of the Nusselt number in terms of the Reynolds number and Prandtl number. For a correlation for a given geometry, a heat transfer correlation for the Nusselt number in terms of the Reynolds number and the Prandtl number can be used as a mass transfer correlation by replacing the Prandtl number with the analogous dimensionless number for mass transfer, the Schmidt number, and replacing the Nusselt number with the analogous dimensionless number for mass transfer, the Sherwood number. As an example, a heat transfer correlation for spheres is given by the Ranz-Marshall correlation. This correlation can be made into a mass transfer correlation. This is a very concrete way of demonstrating the analogies between different forms of transport phenomena.
Contributor: Junjie Chen, E-mail address: koncjj@gmail.com, ORCID: 0000-0002-5022-6863, Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China
DOI: 10.17632/fzxjwrt53m.1
title: Genes/proteins involved in aluminum tolerance in Oryza sativa subsp. japonica

description: This dataset contains a total of 1084 unique genes in a total of 1100 genes identified via literature search to find Oryza sativa subsp. japonica gene IDs reported being related to aluminum tolerance using peer-reviewed articles which used proteomics, transcriptomics, GWAS, QTL, and SSR related-techniques 
(Fukuda et al., 2007; Famoso et al., 2011; Arenhart et al., 2013; Wang et al., 2013; L. Yang et al., 2013; Arenhart et al., 2014; Wang et al., 2014; Zhang et al., 2016; Arbelaez et al., 2017; Cohen and Leach, 2019; Zhang et al., 2019b, 2019a; Tyagi et al., 2020)
DOI: 10.17632/fzxjwrt53m.2
title: Genes/proteins involved in aluminum tolerance in Oryza sativa subsp. japonica

description: This dataset contains a total of 1084 unique genes in a total of 1100 genes identified via literature search to find Oryza sativa subsp. japonica gene IDs reported being related to aluminum tolerance using peer-reviewed articles which used proteomics, transcriptomics, GWAS, QTL, and SSR related-techniques 
(Fukuda et al., 2007; Famoso et al., 2011; Arenhart et al., 2013; Wang et al., 2013; L. Yang et al., 2013; Arenhart et al., 2014; Wang et al., 2014; Zhang et al., 2016; Arbelaez et al., 2017; Cohen and Leach, 2019; Zhang et al., 2019b, 2019a; Tyagi et al., 2020)


References:

•	Fukuda, T., Saito, A., Wasaki, J., Shinano, T., Osaki, M., 2007. Metabolic alterations proposed by proteome in rice roots grown under low P and high Al concentration under low pH. Plant Sci. 172, 1157–1165. https://doi.org/10.1016/j.plantsci.2007.02.020
•	Famoso, A.N., Zhao, K., Clark, R.T., Tung, C.-W., Wright, M.H., Bustamante, C., Kochian, L.V., McCouch, S.R., 2011. Genetic Architecture of Aluminum Tolerance in Rice (Oryza sativa) Determined through Genome-Wide Association Analysis and QTL Mapping. PLoS Genet. 7, e1002221. 
•	Arenhart, R.A., Bai, Y., Valter de Oliveira, L.F., Bucker Neto, L., Schunemann, M., Maraschin, F. dos S., Mariath, J., Silverio, A., Sachetto-Martins, G., Margis, R., Wang, Z.-Y., Margis-Pinheiro, M., 2014. New Insights into Aluminum Tolerance in Rice: The ASR5 Protein Binds the STAR1 Promoter and Other Aluminum-Responsive Genes. Mol. Plant 7, 709–721. https://doi.org/10.1093/mp/sst160
•	Wang, C.Y., Shen, R.F., Wang, C., Wang, W., 2013. Root protein profile changes induced by Al exposure in two rice cultivars differing in Al tolerance. J. Proteomics 78, 281–293. https://doi.org/10.1016/j.jprot.2012.09.035
•	Yang, L., Tian, D., Todd, C.D., Luo, Y., Hu, X., 2013. Comparative Proteome Analyses Reveal that Nitric Oxide Is an Important Signal Molecule in the Response of Rice to Aluminum Toxicity. J. Proteome Res. 12, 1316–1330. https://doi.org/10.1021/pr300971n
•	Arenhart, R.A., De Lima, J.C., Pedron, M., Carvalho, F.E.L., Da Silveira, J.A.G., Rosa, S.B., Caverzan, A., Andrade, C.M.B., Schünemann, M., Margis, R., Margis-Pinheiro, M., 2013. Involvement of ASR genes in aluminium tolerance mechanisms in rice: ASR genes and aluminium tolerance in rice. Plant Cell Environ. 36, 52–67. https://doi.org/10.1111/j.1365-3040.2012.02553.x
•	Wang, Z.Q., Xu, X.Y., Gong, Q.Q., Xie, C., Fan, W., Yang, J.L., Lin, Q.S., Zheng, S.J., 2014. Root proteome of rice studied by iTRAQ provides integrated insight into aluminum stress tolerance mechanisms in plants. J. Proteomics 98, 189–205. https://doi.org/10.1016/j.jprot.2013.12.023
•	Zhang, P., Zhong, K., Tong, H., Shahid, M.Q., Li, J., 2016. Association Mapping for Aluminum Tolerance in a Core Collection of Rice Landraces. Front. Plant Sci. 7. https://doi.org/10.3389/fpls.2016.01415
DOI: 10.17632/fzxjwrt53m.3
title: Genes/proteins involved in aluminum tolerance in Oryza sativa subsp. japonica

description: This dataset contains a total of 1084 unique genes in a total of 1100 genes identified via literature search to find Oryza sativa subsp. japonica gene IDs reported being related to aluminum tolerance using peer-reviewed articles which used proteomics, transcriptomics, GWAS, QTL, and SSR related-techniques 

(Fukuda et al., 2007; Famoso et al., 2011; Arenhart et al., 2013; Wang et al., 2013; L. Yang et al., 2013; Arenhart et al., 2014; Wang et al., 2014; Zhang et al., 2016; Arbelaez et al., 2017; Cohen and Leach, 2019; Zhang et al., 2019b, 2019a; Tyagi et al., 2020)

Two files are available to download: 
- Genes_to_Mendeley.xlsx (Genes id, Description and reference)
- data_mendeley_description.docx (Contains the references where the genes were extracted)
DOI: 10.17632/h6d5jhmypf.1
title: Concerted two-proton-coupled electron transfer (2PCET) reaction between 1,2-dihydroxynaphthalene and superoxide radical anion

description: 2PCET mechanisms between 1,2-dihydroxynaphthalene (12H<sub>2</sub>NQ) and superoxide radical anion (O<sub>2</sub><sup>•−</sup>) in <i>N</i>,<i>N</i>-dimethylformamide. The 2PCET occurs as an intra-complex reaction after the formation of prereactive complex. This reaction was theoretically obtained using the density functional theory (DFT) level with the Becke three-parameter Lee–Yang–Parr functional.
DOI: 10.5517/ccdc.csd.cc26qgfv
title: CCDC 2047377: Experimental Crystal Structure Determination

description: Related Article: Karin Preinerová, Miroslava Puchoňová, Martin Schoeller, Vladimír Kuchtanin, Noémi Molnárová, Svetlana Kryštofová, Milan Mazúr, Ivan Iľko, Viera Peterková, Ján Moncol|2022|Polyhedron|227|116146|doi:10.1016/j.poly.2022.116146
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.cc26qggw
title: CCDC 2047378: Experimental Crystal Structure Determination

description: Related Article: Karin Preinerová, Miroslava Puchoňová, Martin Schoeller, Vladimír Kuchtanin, Noémi Molnárová, Svetlana Kryštofová, Milan Mazúr, Ivan Iľko, Viera Peterková, Ján Moncol|2022|Polyhedron|227|116146|doi:10.1016/j.poly.2022.116146
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.cc26qghx
title: CCDC 2047379: Experimental Crystal Structure Determination

description: Related Article: Karin Preinerová, Miroslava Puchoňová, Martin Schoeller, Vladimír Kuchtanin, Noémi Molnárová, Svetlana Kryštofová, Milan Mazúr, Ivan Iľko, Viera Peterková, Ján Moncol|2022|Polyhedron|227|116146|doi:10.1016/j.poly.2022.116146
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.cc26qgjy
title: CCDC 2047380: Experimental Crystal Structure Determination

description: Related Article: Karin Preinerová, Miroslava Puchoňová, Martin Schoeller, Vladimír Kuchtanin, Noémi Molnárová, Svetlana Kryštofová, Milan Mazúr, Ivan Iľko, Viera Peterková, Ján Moncol|2022|Polyhedron|227|116146|doi:10.1016/j.poly.2022.116146
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.cc26qgkz
title: CCDC 2047381: Experimental Crystal Structure Determination

description: Related Article: Karin Preinerová, Miroslava Puchoňová, Martin Schoeller, Vladimír Kuchtanin, Noémi Molnárová, Svetlana Kryštofová, Milan Mazúr, Ivan Iľko, Viera Peterková, Ján Moncol|2022|Polyhedron|227|116146|doi:10.1016/j.poly.2022.116146
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.