cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25403/upresearchdata.23783265
title: The impact of flexible working arrangements on employees

description: The dataset presented underpin a dissertation on evaluating the impact of flexible working arrangements on employee satistaction, motivation and performance. The data was collected via a survey that targeted working individuals that are over the age of 18. SmartPLS was used to analyse the data. SmartPLS Structural Models.zip contains the SmartPLS files for the structural models that were used, titled main structural model and subdivided structural model. In the dissertation, for the analysis of the <em>q</em><sup><em>2</em></sup> effect size, model re-estimation was conducted in which a specific predecessor of an endogenous latent variable was removed (i.e. flexible working arrangements, motivation, and satisfaction) in order to obtain the values to complete the calculation. Complete dataset containing biographics, indicators, and questions (included for comprehension).<em>csv</em> contains the full dataset, along with the biographic data, to identify which questions were associated with the indicators. This dataset has been included for comprehension and was not analysed using SmartPLS. Complete dataset used for analysis.csv contains the full dataset. It only contains the indicators and the survey responses. The remaining datasets (30 and Under (age).csv, 31 and over (age).csv, female.csv, male.csv, No has not made prior use of flexible working arrangements.csv, and Yes has made prior use of flexible working arrangements.csv) contain the filtered data which was used for the comparative analysis. Each dataset only contains survey responses associated with the specific category, i.e. age 30 and under, age 31 and over, female, male, no has not made prior use of flexible working arrangements, and yes has made prior use of flexible working arrangements. All datasets were applied to the SmartPLS Structural Model titled main structural model to obtain results. The SmartPLS structural model titled subdivided structural model only made use of the dataset complete dataset used for analysis.csv, in which the indicators associated with flexible working hours and flexible working locations were linked to the associated latent variable, either flexible working hours or flexible working locations. For the questions that were asked in the reverse/negative format, their answers were reversed/recoded so that all data was presented in the same progression, starting from the least desirable outcome, coded as 1, to the most desirable outcome, coded as 5.
DOI: 10.5281/zenodo.6972497
title: SMARTFARM Eddy Covariance Demonstration Data Set of Five Agro-ecosystem Sites

description: Demonstration data set from five eddy covariance towers at agro-ecosystem sites that are funded under the DOE ARPA-E SMARTFARM program in Phase I. Data set is provided to restricted users for the purpose of operational and performance qualification only. Data sets include 13-26 weeks of all 30 minute interval data for all sensor modalities per the sensor workbook and FOA. Full data sets will be published through Ameriflux at https://ameriflux.lbl.gov/ starting August 12, 2022, with annual updates thereafter. Some data, such as methane and nitrous oxide are embargoed. This work was funded through the U.S. Department of Energy, ARPA-E, under Cooperative Agreement DE-AR0001228 led by ARVA Intelligence Corp. (https://www.arvaintelligence.com) in collaboration with Lawrence Berkeley National Laboratory (LBNL).
description: Data file is password protected. Please request the password to open the zip file from the lead author at mschuppenhauer@lbl.gov.
DOI: 10.5281/zenodo.6972498
title: SMARTFARM Eddy Covariance Demonstration Data Set of Five Agro-ecosystem Sites

description: Demonstration data set from five eddy covariance towers at agro-ecosystem sites that are funded under the DOE ARPA-E SMARTFARM program in Phase I. Data set is provided to restricted users for the purpose of operational and performance qualification only. Data sets include 13-26 weeks of all 30 minute interval data for all sensor modalities per the sensor workbook and FOA. Full data sets will be published through Ameriflux at https://ameriflux.lbl.gov/ starting August 12, 2022, with annual updates thereafter. Some data, such as methane and nitrous oxide are embargoed. This work was funded through the U.S. Department of Energy, ARPA-E, under Cooperative Agreement DE-AR0001228 led by ARVA Intelligence Corp. (https://www.arvaintelligence.com) in collaboration with Lawrence Berkeley National Laboratory (LBNL).
description: Data file is password protected. Please request the password to open the zip file from the lead author at mschuppenhauer@lbl.gov.
DOI: 10.15479/at:ista:13116
title: Chiral and nematic phases of flexible active filaments

description: The emergence of large-scale order in self-organized systems relies on local interactions between individual components. During bacterial cell division, FtsZ -- a prokaryotic homologue of the eukaryotic protein tubulin -- polymerizes into treadmilling filaments that further organize into a cytoskeletal ring. In vitro, FtsZ filaments can form dynamic chiral assemblies. However, how the active and passive properties of individual filaments relate to these large-scale self-organized structures remains poorly understood. Here, we connect single filament properties with the mesoscopic scale by combining minimal active matter simulations and biochemical reconstitution experiments. We show that density and flexibility of active chiral filaments define their global order. At intermediate densities, curved, flexible filaments organize into chiral rings and polar bands. An effectively nematic organization dominates for high densities and for straight, mutant filaments with increased rigidity. Our predicted phase diagram captures these features quantitatively, demonstrating how the flexibility, density and chirality of active filaments affect their collective behaviour. Our findings shed light on the fundamental properties of active chiral matter and explain how treadmilling FtsZ filaments organize during bacterial cell division.
DOI: 10.5517/ccdc.csd.cc2c0m89
title: CCDC 2175340: Experimental Crystal Structure Determination

description: Related Article: Hao Luo, Fang-Zi Liu, Yan Liu, Zhaoyang Chu, KaKing Yan|2023|J.Am.Chem.Soc.|145|15118|doi:10.1021/jacs.3c00614
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.cc2d1bmf
title: CCDC 2205824: Experimental Crystal Structure Determination

description: Related Article: Debashish Mishra, Sagarika Rajkhowa, Prodeep Phukan|2023|iScience|26|107258|doi:10.1016/j.isci.2023.107258
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.cc2d4v8p
title: CCDC 2209192: Experimental Crystal Structure Determination

description: Related Article: Qi Li, Yuting Liu, Lijuan Liang, Xiangyu Zhang, Kun Huang, Dabin Qin|2023|Spectrochim.Acta,Part A|302|123124|doi:10.1016/j.saa.2023.123124
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: 10.5281/zenodo.8189831
title: data from Robust multisensory deviance detection in the mouse parietal associative area

description: This is all the data analysed in the paper "Robust multisensory deviance detection in the mouse parietal associative area." It goes along with the code in https://zenodo.org/record/8189912
DOI: 10.5281/zenodo.8189783
title: data from Robust multisensory deviance detection in the mouse parietal associative area

description: This is all the data analysed in the paper "Robust multisensory deviance detection in the mouse parietal associative area." It goes along with the code in https://zenodo.org/record/8189912
DOI: 10.5281/zenodo.8165164
title: Data for "A New Year-Round Weather Regime Classification for North America"

description: This dataset supports the work presented in <em>"A New Year-Round Weather Regime Classification for North America" </em>by Lee et al. (2023), published in <em>Journal of Climate</em>: https://doi.org/10.1175/JCLI-D-23-0214.1 The dataset includes the Z500 climatology and anomalies, the EOFs/PCs, and the parameters required to attribute each day to a regime, alongside the regimes as assigned over 1979-2022 (time series in netCDF and csv formats). In addition, we also supply the standardized projection of each day onto the cluster-mean normalized Z500 anomalies for each regime, termed the Weather Regime Index (WRI).
DOI: 10.6073/pasta/468096edabcc03e130f50552d9e80ec3
title: Sawgrass above ground biomass from the Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, August 1999 - ongoing

description: Sawgrass biomass is measured for TS/Ph-1, 2, 3, & 6 since 1999; TS/Ph-4 & 5 since 1997 to 2006; SRS-1b, 2, & 3 since 2000; SRS1c for 2005 to 2006, and SRS1d since 2006. Three 1 m2 plots are placed on each site. The sites are measured every two months. The number of sawgrass plants is counted for each 1 m2 plot and one third or a minimum of fifteen plants is measured. For each measured plant, measurements of the total number of live leaves, length of the live leaves, and culm diameter at the base are taken. From these measurements we calculate the average leaf length, and the sum of the length of the leaves. We created a model for biomass using a stepwise regression to see which of the variables measured and calculated are more correlated to explain plant biomass. Obtaining the mean biomass for the plants within the plot and multiplying it by the number of plants counted in the plot calculates biomass for each plot. The total biomass for each plot is summed with the other two plots in the same site, and they are averaged to obtain one biomass number per site. To validate our model, plant clippings are obtained in which four plants are clipped (small, medium, large, inflorescence) from each site. The same measurements are applied to the clipped plants as those applied to the measured plants in the plots. The plant clippings are oven dried at 70 degrees C and weighed.
DOI: 10.5066/p9y3ec24
title: Groundwater-level altitudes and volatile and semi-volatile organic compound concentrations at the Petro-Chemical Systems, Inc. (Turtle Bayou) Superfund site, Liberty County, Texas, 2023

description: In 2023, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, collected groundwater-level altitude and water-quality data from monitoring wells at the Petro-Chemical Systems, Inc. (Turtle Bayou) Superfund Site in Liberty County, Texas. The data were collected to obtain information that could be used to provide an update on the status of groundwater contamination at the site. This data release documents the groundwater-level altitudes, field properties, and water-quality data obtained in 2023 from six of the 11 monitoring wells where similar data were collected by the U.S. Geological Survey in August and September 2020 (Braun and Becher 2022). The environmental and quality-control data from the water-quality samples collected at each well that was sampled in April 2023 are included. Each water-quality sample was analyzed for a suite of volatile and semi-volatile organic compounds.
DOI: 10.5281/zenodo.8189935
title: Data for "Characterization of Intact Eukaryotic Cells with Subcellular Spatial Resolution by Photothermal-Induced Resonance Infrared Spectroscopy and Imaging"

description: Dataset used for the article "Characterization of Intact Eukaryotic Cells with Subcellular Spatial Resolution by Photothermal-Induced Resonance Infrared Spectroscopy and Imaging" Molecules 2019, 24, 4504; doi:10.3390/molecules24244504
description: Grants UMO-2018/31/B/NZ1/01345 MRPO.05.01.00-12-013/15
DOI: 10.5281/zenodo.8189934
title: Data for "Characterization of Intact Eukaryotic Cells with Subcellular Spatial Resolution by Photothermal-Induced Resonance Infrared Spectroscopy and Imaging"

description: Dataset used for the article "Characterization of Intact Eukaryotic Cells with Subcellular Spatial Resolution by Photothermal-Induced Resonance Infrared Spectroscopy and Imaging" Molecules 2019, 24, 4504; doi:10.3390/molecules24244504
description: Grants UMO-2018/31/B/NZ1/01345 MRPO.05.01.00-12-013/15
DOI: 10.6084/m9.figshare.23792286
title: Geriatric ICF items

description: ICF-based outcome measures
DOI: 10.6084/m9.figshare.23792286.v1
title: Geriatric ICF items

description: ICF-based outcome measures
DOI: 10.25403/upresearchdata.23776212.v1
title: Computer-aided data analysis for Little Seeds organization's strategic and operational staff members' tasks

description: This qualitative data is aimed at exploring collaboration between the Dutch Reformed Church and church-affiliated social welfare organisations in order to alleviate poverty striken communities. The data was collected through eight semi-structured interviews and were recorded, transcribed, translated to English (from Afrikaans), and captured in verbatim records. Open coding was then done using Atlas.ti which is a computer-based qualitative data analysis program. The semi-structured interview questions predicted six themes. Atlas.ti created six maps that each captured the reaction of respondents, revealing data for qualitative analysis. <br>
DOI: 10.25403/upresearchdata.23776212
title: Computer-aided data analysis for Little Seeds organization's strategic and operational staff members' tasks

description: This qualitative data is aimed at exploring collaboration between the Dutch Reformed Church and church-affiliated social welfare organisations in order to alleviate poverty striken communities. The data was collected through eight semi-structured interviews and were recorded, transcribed, translated to English (from Afrikaans), and captured in verbatim records. Open coding was then done using Atlas.ti which is a computer-based qualitative data analysis program. The semi-structured interview questions predicted six themes. Atlas.ti created six maps that each captured the reaction of respondents, revealing data for qualitative analysis. <br>
DOI: 10.7488/ds/7492
title: Human astrocytes and microglia show augmented ingestion of synapses in Alzheimer’s disease via MFG-E8

description: Synapse loss correlates with cognitive decline in Alzheimer’s disease (AD). Data from mouse models suggests microglia are important for synapse degeneration, but direct human evidence for any glial involvement in synapse removal in human AD remains to be established. Here we observe astrocytes and microglia from human brains contain greater amounts of synaptic protein in AD compared to non-disease controls, and that proximity to amyloid-β plaques and the APOE4 risk gene exacerbate this effect. In culture, mouse and human astrocytes and primary mouse and human microglia phagocytose AD patient-derived synapses more than synapses from controls. Inhibiting interactions of MFG-E8 rescues the elevated engulfment of AD synapses by astrocytes and microglia without affecting control synapse uptake. Thus, AD promotes increased synapse ingestion by human glial cells at least in part via an MFG-E8 opsonophagocytic mechanism with potential for targeted therapeutic manipulation. This dataset contains the spreadsheets analysed in the study (in a zip file) and the R Notebook used for statistical analysis. The dataset relates to the upcoming M. Tzioras, M.J.D. Daniels, C. Davies, P. Baxter, D. King, S. McKay, B. Varga, K. Popovic, M. Hernandez, A.J. Stevenson, J. Barrington, E. Drinkwater, J. Borella, R.K. Holloway, J. Tulloch, J. Moss, C. Latta, J. Kandasamy, D. Sokol, C. Smith, V.E. Miron, R.T. Káradóttir, G.E. Hardingham, C.M. Henstridge, P.M. Brennan, B.W. McColl, T.L. Spires-Jones (accepted). 'Human astrocytes and microglia show augmented ingestion of synapses in Alzheimer’s disease via MFG-E8' https://doi.org/10.1101/795930 .
DOI: 10.5281/zenodo.8189914
title: TCGA Bladder Urothelial Carcinoma (BLCA) Clinical Data

description: <strong>Abstract:</strong> The Cancer Genome Atlas (TCGA) was a large-scale collaborative project initiated by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). It aimed to comprehensively characterize the genomic and molecular landscape of various cancer types. This dataset includes curated survival data from the Pan-cancer Atlas paper titled "An Integrated TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR) to drive high quality survival outcome analytics". The paper highlights four types of carefully curated survival endpoints, and recommends the use of the endpoints of OS, PFI, DFI, and DSS for each TCGA cancer type. The dataset also includes phenotypic information about BLCA. The Sample IDs are unique identifiers, which can be paired with the gene expression dataset. <strong>Inspiration:</strong> This dataset was uploaded to UBRITE for GTKB project. <strong>Instruction:</strong> The survival and phenotype data were merged into one file. <strong>Acknowledgments:</strong> Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11. https://doi.org/10.1016/j.cell.2018.02.052 Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8 The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113–1120 (2013). https://doi.org/10.1038/ng.2764 <strong>U-BRITE last update: </strong>07/13/2023
description: UBRITE location: /data/project/ubrite/gtkb/TCGA/Clinical
description: {"references": ["Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11.\u00a0https://doi.org/10.1016/j.cell.2018.02.052", "Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8", "The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113\u20131120 (2013). https://doi.org/10.1038/ng.2764"]}
DOI: 10.5281/zenodo.8189913
title: TCGA Bladder Urothelial Carcinoma (BLCA) Clinical Data

description: <strong>Abstract:</strong> The Cancer Genome Atlas (TCGA) was a large-scale collaborative project initiated by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). It aimed to comprehensively characterize the genomic and molecular landscape of various cancer types. This dataset includes curated survival data from the Pan-cancer Atlas paper titled "An Integrated TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR) to drive high quality survival outcome analytics". The paper highlights four types of carefully curated survival endpoints, and recommends the use of the endpoints of OS, PFI, DFI, and DSS for each TCGA cancer type. The dataset also includes phenotypic information about BLCA. The Sample IDs are unique identifiers, which can be paired with the gene expression dataset. <strong>Inspiration:</strong> This dataset was uploaded to UBRITE for GTKB project. <strong>Instruction:</strong> The survival and phenotype data were merged into one file. <strong>Acknowledgments:</strong> Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11. https://doi.org/10.1016/j.cell.2018.02.052 Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8 The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113–1120 (2013). https://doi.org/10.1038/ng.2764 <strong>U-BRITE last update: </strong>07/13/2023
description: UBRITE location: /data/project/ubrite/gtkb/TCGA/Clinical
description: {"references": ["Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11.\u00a0https://doi.org/10.1016/j.cell.2018.02.052", "Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8", "The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113\u20131120 (2013). https://doi.org/10.1038/ng.2764"]}
DOI: 10.5517/ccdc.csd.cc2bm98k
title: CCDC 2163498: Experimental Crystal Structure Determination

description: Related Article: Miaomiao Zhu, Zhengqi Chai, Tianyu Li, Junnian Wei, Ze-Jie Lv, Wen-Xiong Zhang|2023|Inorg.Chem.Front.|10|4569|doi:10.1039/D3QI00946G
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.cc2f1m15
title: CCDC 2235876: Experimental Crystal Structure Determination

description: Related Article: Albert Artigas, Florian Rigoulet, Michel Giorgi, Denis Hagebaum-Reignier, Yannick Carissan, Yoann Coquerel|2023|J.Am.Chem.Soc.|145|15084|doi:10.1021/jacs.3c05415
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.cc2f1m48
title: CCDC 2235879: Experimental Crystal Structure Determination

description: Related Article: Albert Artigas, Florian Rigoulet, Michel Giorgi, Denis Hagebaum-Reignier, Yannick Carissan, Yoann Coquerel|2023|J.Am.Chem.Soc.|145|15084|doi:10.1021/jacs.3c05415
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.