cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22737221
title: Nepal-Gender compliance experiment

description: Gender, compliance, public sector, survey experiment, Nepal
DOI: 10.6084/m9.figshare.22737221.v1
title: Nepal-Gender compliance experiment

description: Gender, compliance, public sector, survey experiment, Nepal
DOI: 10.6084/m9.figshare.22737281
title: <strong>3</strong> Графики взаимосвязи вегетационных индексов в фазе всходы*

description: В фазу всходы модели «PSSRAa, PSSRb – VOG1» и «PSSRAa, PSSRb – SIPI» показали высокую регрессионную зависимость переменных. В тоже время, модель «PSSRAa, PSSRb – SIPI» – обратно пропорциональную. В фазу кущения модели «PSSRAa, PSSRb – VOG1» и «PSSRAa, PSSRb – SIPI» произошло снижение взаимосвязи переменных. Однако, в моделе «PSSRAa, PSSRb – SIPI» корреляционная связь улучшается, возможно за счет увеличения концентрации хлорофилла (PSSRb). Следовательно, установленная взаимосвязь индексов позволяет не только фиксировать вегетационную фазу развития растений озимой пшеницы, но и отображать состояние возделываемой культуры.
DOI: 10.6084/m9.figshare.22737281.v1
title: <strong>3</strong> Графики взаимосвязи вегетационных индексов в фазе всходы*

description: В фазу всходы модели «PSSRAa, PSSRb – VOG1» и «PSSRAa, PSSRb – SIPI» показали высокую регрессионную зависимость переменных. В тоже время, модель «PSSRAa, PSSRb – SIPI» – обратно пропорциональную. В фазу кущения модели «PSSRAa, PSSRb – VOG1» и «PSSRAa, PSSRb – SIPI» произошло снижение взаимосвязи переменных. Однако, в моделе «PSSRAa, PSSRb – SIPI» корреляционная связь улучшается, возможно за счет увеличения концентрации хлорофилла (PSSRb). Следовательно, установленная взаимосвязь индексов позволяет не только фиксировать вегетационную фазу развития растений озимой пшеницы, но и отображать состояние возделываемой культуры.
DOI: 10.5281/zenodo.7890371
title: Data from: Crocodile perception of distress in Hominid baby cries

description: Dataset and all original statistical codes used in the article "Crocodile perception of distress in Hominid baby cries".
DOI: 10.5281/zenodo.7890370
title: Data from: Crocodile perception of distress in Hominid baby cries

description: Dataset and all original statistical codes used in the article "Crocodile perception of distress in Hominid baby cries".
DOI: 10.5281/zenodo.7890384
title: Data and Code

description: <strong>Assessment of eight insulin resistance surrogate indexes for predicting metabolic syndrome and hypertension in Thai law enforcement </strong><strong>officers</strong>
DOI: 10.5281/zenodo.7890383
title: Data and Code

description: <strong>Assessment of eight insulin resistance surrogate indexes for predicting metabolic syndrome and hypertension in Thai law enforcement </strong><strong>officers</strong>
DOI: 10.5281/zenodo.7885281
title: MUSES Fractional Vegetation Coverage (FVC) Monthly Global 500m SIN Grid in 2010

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 500 m spatial resolution and monthly temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 500 m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2010. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2009</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2011</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2010 Spatial Resolution: 500 m Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7885280
title: MUSES Fractional Vegetation Coverage (FVC) Monthly Global 500m SIN Grid in 2010

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 500 m spatial resolution and monthly temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 500 m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2010. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2009</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2011</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2010 Spatial Resolution: 500 m Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5517/ccdc.csd.cc2d15wj
title: CCDC 2205677: Experimental Crystal Structure Determination

description: Related Article: Ryoji Tanaka|2023|CSD Communication|||
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.cc2f2ny4
title: CCDC 2236896: Experimental Crystal Structure Determination

description: Related Article: Toni Grell, Evamarie Hey-Hawkins|2023|CSD Communication|||
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.cc2dy19q
title: CCDC 2232443: Experimental Crystal Structure Determination

description: Related Article: Ganesh Shivayogappa Sorabad, Ding-Yah Yang|2023|J.Org.Chem.|88|4730|doi:10.1021/acs.joc.3c00213
description: Related Article: ganesh sorabad|2023|CSD Communication|||
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.cc261z08
title: CCDC 2027679: Experimental Crystal Structure Determination

description: Related Article: ye zhang|2023|CSD Communication|||
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.cc2f2rcn
title: CCDC 2236971: Experimental Crystal Structure Determination

description: Related Article: Mikko Hänninen, Ari Lehtonen, Reijo Sillanpää|2023|CSD Communication|||
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.7890415
title: Supplementary S6.2 Economic calculation

description: This is the supplementary file for Chapter 6 of PhD thesis, entitled "An integrated epidemiological and economic analysis of foot and mouth disease (FMD) in Thailand: Evaluation of FMD control"
DOI: 10.5281/zenodo.7890414
title: Supplementary S6.2 Economic calculation

description: This is the supplementary file for Chapter 6 of PhD thesis, entitled "An integrated epidemiological and economic analysis of foot and mouth disease (FMD) in Thailand: Evaluation of FMD control"
DOI: 10.25345/c5j679651
title: MassIVE MSV000091841 - Enhancing bacterial fitness and recombinant enzyme yield by engineering the quality control protease HtrA of Bacillus subtilis
title: An alternative approach to limit the effects of secretion stress by modulating the protease activity of HtrA rather than completely removing this protease was investigated. Sample processing 16 OD600 units of bacterial culture were harvested from shake flasks or fermenters. Tubes were briefly immersed in liquid nitrogen to stop the metabolism of the cells. Cells were pelleted by centrifugation at 4000 rpm for 2 min at 4 degC and washed with 20 mM HEPES. Cell pellets were frozen in liquid nitrogen and stored at -80 degC until processing. After benzonase treatment, reduction and alkylation, and digestion with trypsin in an enzyme-to-sample mass ratio of 1:25 overnight at 37 degC, peptides were desalted on SP3 beads as previously described (Blankenburg et al. 2019). Lyophilized peptide samples were reconstituted in mass spectrometry Buffer A (2% acetonitrile in 0.1% acetic acid), For LC-MS/MS analyses tryptic peptide solutions were separated on an Ultimate 3000 nano-LC system (Thermo Fisher Scientific, MA, USA) and analysed on a Q Exactive HF mass spectrometer in data independent acquisition mode. Peptides were separated on a 25 cm Accucore column (75 um inner diameter, 2.6 um, 150 A, C18) at a flow rate of 300 nl/min in a binary buffer system of aqueous Buffer A (0.1% acetic acid, 2% acetonitrile in water) and organic Buffer B (0.1% acetic acid in 100% acetonitrile) by applying a linear gradient of buffer B from 5% up to 25% within 120 min. Data processing Identification and quantitation were performed via the DirectDIA approach in the Spectronaut software (Biognosys, Germany) using a predicted synthetic library fasta-file with database search against a Uniprot/Swissprot database restricted to entries from B. subtilis (version 20210705) with the addition of AmyQ (P00692), Chloramphenicol acetyltransferase (P00485), Kanamycin nucleotidyltransferase (P05057) and rRNA adenine N-6-methyltransferase (P13956). Analysis settings: tryptic peptides; variable modifications: oxidation at Met and protein N-terminal acetylation; missed cleavages: &gt;= 2; iRT peptide-based correlation of retention time ratios. Quantitation: with Interference Correction; protein grouping by Protein Group ID; peptide grouping by Stripped Sequence; precursor Q-value &lt; 0.001, without any imputation.
DOI: 10.23728/b2share.12a066f57cc246d2b3ddd288a03781ad
title: Monumento Naturale Torre Flavia (Roma, Italy) - Bird data of Torre Flavia

description: Data about presence of bird species observed within Monumento Naturale Torre Flavia (Rome, Italy) in the range 1933-2020.
DOI: 10.6084/m9.figshare.22730213.v1
title: The magnetic and geochemical data of Beigou section

description: The magnetic and geochemical data of Beigou section.
DOI: 10.57745/gqi86b
title: carrot_populations_info.tab

description: :unav
DOI: 10.57745/zc1ogq
title: Schonegger et al - 2023 - carrot populations datasets.zip

description: :unav
DOI: 10.5281/zenodo.7890435
title: NOBEL-BOX: A Ship-Based Low-Cost Instrument for Real-Time Ocean Monitoring and Analysis

description: This data is the measurement result obtained from the NOBEL-BOX instrument. The principle of NOBEL-BOX is to attach sensors in a container connected to a microcontroller and then measure directly. This data results from measurements using fresh water and sea water mixed to see the response from NOBEL BOX. Furthermore, data was also obtained from sea measurements in Pangandaran, West Java, Indonesia. These measurements include pH, water and water temperature, dissolved oxygen, TDS, and salinity. The use of this parameter is to see the condition of the sea so that it becomes a reference in mitigating and managing the ocean.
DOI: 10.5281/zenodo.7889391
title: MUSES Leaf Area Index (LAI) Monthly Global 1km SIN Grid in 2005

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global LAI product at 1 km spatial resolution and monthly temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2005. <em>Please <strong>click here</strong> to download the MUSES LAI product <strong>in 2004</strong></em>, <em>and <strong>click here</strong> to download the MUSES LAI product <strong>in 2006</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2005 Spatial Resolution: 1 km Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7889390
title: MUSES Leaf Area Index (LAI) Monthly Global 1km SIN Grid in 2005

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global LAI product at 1 km spatial resolution and monthly temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2005. <em>Please <strong>click here</strong> to download the MUSES LAI product <strong>in 2004</strong></em>, <em>and <strong>click here</strong> to download the MUSES LAI product <strong>in 2006</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2005 Spatial Resolution: 1 km Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.6084/m9.figshare.22737449
title: Supplementary_data_for_TRL_Cooksley_manuscript

description: Supplementary data for the manuscript "An integrative trait-based framework to infer resource budgets and life-histories of long-lived plants" by Cooksley <em>et al</em>.
DOI: 10.6084/m9.figshare.22737449.v1
title: Supplementary_data_for_TRL_Cooksley_manuscript

description: Supplementary data for the manuscript "An integrative trait-based framework to infer resource budgets and life-histories of long-lived plants" by Cooksley <em>et al</em>.
DOI: 10.22008/fk2/kdnzdt
title: 2-D reflection seismic surveys onshore Disko, Kuugannguaq valley, central West Greenland

description: For description of data set see: Avannaa Resources Kuuganguaq survey details.Size: 30 MB.
DOI: 10.5281/zenodo.7890446
title: Primary collected data for modelling the additive MAR/R process by means of the PBF-LB process based on the example of tool steel 1.2709 powder

description: For the evaluation of a MAR/R process, not only process-, material- and demonstrator-specific correlations and data must be combined. In addition to secondary data (e.g. databases, publications, etc.), primary data (e.g. process times, volume flows, etc.) must also be collected for the specific application. The attached table shows the primary data to be collected for the cradle-to-gate process depending on the process phases and steps. This data is used as support for ecological as well as economic process and component evaluations.
description: This research was conducted in the scope of the research project RePARE- Regeneration of product and production systems through additive repair and refurbishment (Funding reference number 033R229) which is funded by Federal Ministry of Education and Research (BMBF) within the funding measure "Resourceefficient Circular Economy - Innovative Product Cycles" (ReziProK). This research has been funded as well by the Ministry for Science and Culture of Lower Saxony (MWK) – School for Additive Manufacturing SAM.
DOI: 10.5281/zenodo.7890445
title: Primary collected data for modelling the additive MAR/R process by means of the PBF-LB process based on the example of tool steel 1.2709 powder

description: For the evaluation of a MAR/R process, not only process-, material- and demonstrator-specific correlations and data must be combined. In addition to secondary data (e.g. databases, publications, etc.), primary data (e.g. process times, volume flows, etc.) must also be collected for the specific application. The attached table shows the primary data to be collected for the cradle-to-gate process depending on the process phases and steps. This data is used as support for ecological as well as economic process and component evaluations.
description: This research was conducted in the scope of the research project RePARE- Regeneration of product and production systems through additive repair and refurbishment (Funding reference number 033R229) which is funded by Federal Ministry of Education and Research (BMBF) within the funding measure "Resourceefficient Circular Economy - Innovative Product Cycles" (ReziProK). This research has been funded as well by the Ministry for Science and Culture of Lower Saxony (MWK) – School for Additive Manufacturing SAM.
DOI: 10.22008/fk2/cxccmy/scnwdk
title: GRF23640.zip

description: :unav
DOI: 10.25919/vnyk-vj46
title: Parkes observations for project PX500 semester 2023APRS_02

description: This proposal relates to time purchased by the Chinese Academy of Sciences for Parkes follow-up confirmation and timing of FAST discoveries. As the observing time has been purchased this proposal (and the related PX501) does not require TAC grading. The primary reason for submitting a proposal is to ensure an outreach statement and that the proposal is entered into OPAL for the data archive to access. The Chinese team have two time requests. The time scheduled for the first, relating to this proposal, will be allocated in blocks of 24 hours and the data will become available in the data archive with an 18 month embargo period. The second type of time will be scheduled in shorter blocks and the data archived with a 10 year embargo.