cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc25w6v4
title: CCDC 2022156: Experimental Crystal Structure Determination

description: Related Article: Peter De'Ath, Mark R.J. Elsegood, Christopher A.G. Halliwell, Martin B. Smith|2021|J.Organomet.Chem.|937|121704|doi:10.1016/j.jorganchem.2021.121704
DOI: 10.5517/ccdc.csd.cc25w6w5
title: CCDC 2022157: Experimental Crystal Structure Determination

description: Related Article: Peter De'Ath, Mark R.J. Elsegood, Christopher A.G. Halliwell, Martin B. Smith|2021|J.Organomet.Chem.|937|121704|doi:10.1016/j.jorganchem.2021.121704
DOI: 10.5517/ccdc.csd.cc25w6x6
title: CCDC 2022158: Experimental Crystal Structure Determination

description: Related Article: Peter De'Ath, Mark R.J. Elsegood, Christopher A.G. Halliwell, Martin B. Smith|2021|J.Organomet.Chem.|937|121704|doi:10.1016/j.jorganchem.2021.121704
DOI: 10.5517/ccdc.csd.cc25w6y7
title: CCDC 2022159: Experimental Crystal Structure Determination

description: Related Article: Peter De'Ath, Mark R.J. Elsegood, Christopher A.G. Halliwell, Martin B. Smith|2021|J.Organomet.Chem.|937|121704|doi:10.1016/j.jorganchem.2021.121704
DOI: 10.5517/ccdc.csd.cc25w6z8
title: CCDC 2022160: Experimental Crystal Structure Determination

description: Related Article: Peter De'Ath, Mark R.J. Elsegood, Christopher A.G. Halliwell, Martin B. Smith|2021|J.Organomet.Chem.|937|121704|doi:10.1016/j.jorganchem.2021.121704
DOI: 10.5517/ccdc.csd.cc26b91x
title: CCDC 2035678: Experimental Crystal Structure Determination

description: Related Article: Norihisa Hoshino, Tomoyuki Akutagawa|2020|Chem.-Eur.J.|27|4064|doi:10.1002/chem.202004492
DOI: 10.5517/ccdc.csd.cc26b92y
title: CCDC 2035679: Experimental Crystal Structure Determination

description: Related Article: Norihisa Hoshino, Tomoyuki Akutagawa|2020|Chem.-Eur.J.|27|4064|doi:10.1002/chem.202004492
DOI: 10.5517/ccdc.csd.cc26b93z
title: CCDC 2035680: Experimental Crystal Structure Determination

description: Related Article: Norihisa Hoshino, Tomoyuki Akutagawa|2020|Chem.-Eur.J.|27|4064|doi:10.1002/chem.202004492
DOI: 10.5517/ccdc.csd.cc26b940
title: CCDC 2035681: Experimental Crystal Structure Determination

description: Related Article: Norihisa Hoshino, Tomoyuki Akutagawa|2020|Chem.-Eur.J.|27|4064|doi:10.1002/chem.202004492
DOI: 10.5517/ccdc.csd.cc26b951
title: CCDC 2035682: Experimental Crystal Structure Determination

description: Related Article: Norihisa Hoshino, Tomoyuki Akutagawa|2020|Chem.-Eur.J.|27|4064|doi:10.1002/chem.202004492
DOI: 10.5517/ccdc.csd.cc26b962
title: CCDC 2035683: Experimental Crystal Structure Determination

description: Related Article: Norihisa Hoshino, Tomoyuki Akutagawa|2020|Chem.-Eur.J.|27|4064|doi:10.1002/chem.202004492
DOI: 10.5517/ccdc.csd.cc26b973
title: CCDC 2035684: Experimental Crystal Structure Determination

description: Related Article: Norihisa Hoshino, Tomoyuki Akutagawa|2020|Chem.-Eur.J.|27|4064|doi:10.1002/chem.202004492
DOI: 10.5517/ccdc.csd.cc26b984
title: CCDC 2035685: Experimental Crystal Structure Determination

description: Related Article: Norihisa Hoshino, Tomoyuki Akutagawa|2020|Chem.-Eur.J.|27|4064|doi:10.1002/chem.202004492
DOI: 10.5517/ccdc.csd.cc256v19
title: CCDC 2002570: Experimental Crystal Structure Determination

description: Related Article: Klaus Banert, Manuel Heck, Andreas Ihle, Tharallah Shoker, Michael Wörle, A. Daniel Boese|2020|Chem.-Eur.J.|27|3700|doi:10.1002/chem.202003933
DOI: 10.5517/ccdc.csd.cc25gw7s
title: CCDC 2010295: Experimental Crystal Structure Determination

description: Related Article: Yong Zhang, Weiren Qiu, Yingming Yao|2021|J.Organomet.Chem.|937|121728|doi:10.1016/j.jorganchem.2021.121728
DOI: 10.5517/ccdc.csd.cc25gw9v
title: CCDC 2010297: Experimental Crystal Structure Determination

description: Related Article: Yong Zhang, Weiren Qiu, Yingming Yao|2021|J.Organomet.Chem.|937|121728|doi:10.1016/j.jorganchem.2021.121728
DOI: 10.5517/ccdc.csd.cc25gwbw
title: CCDC 2010298: Experimental Crystal Structure Determination

description: Related Article: Yong Zhang, Weiren Qiu, Yingming Yao|2021|J.Organomet.Chem.|937|121728|doi:10.1016/j.jorganchem.2021.121728
DOI: 10.17632/x44cwfdrxn.1
title: Data for: ASTEC code DBA analysis of a passive mitigation strategy on a generic IRIS SMR

description: The plot data are the simulation results of the DBA analisys conducted by the ASTEC code on a generic IRIS reactor. The simulated transient involvs the adoption of the standard passive mitigation strategy of the IRIS reactor following a DVI line break accident scenario.
DOI: 10.25919/zsyv-ey11
title: Parkes observations for project PX500 semester 2020OCTS_08

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.
DOI: 10.5281/zenodo.4571643
title: Supplementary Data—Table S1

description: Supplementary Data—Table S1. Attached to the following paper: Chossière GP, Xu H, Dixit Y, Isaacs S, Eastham SD, Allroggen F, Speth RL, Barrett SRH, "Air pollution impacts of COVID-19 containment measures"
DOI: 10.5281/zenodo.4091778
title: Supplementary Data—Table S1

description: Supplementary Data—Table S1. Attached to the following paper: Chossière GP, Xu H, Dixit Y, Isaacs S, Eastham SD, Allroggen F, Speth RL, Barrett SRH, "Air pollution impacts of COVID-19 containment measures"
DOI: 10.5281/zenodo.3986016
title: Anon

description: Anon
DOI: 10.5281/zenodo.3986015
title: Anon

description: Anon
DOI: 10.7298/nzhv-4579
title: Data from: Anthropogenic Perturbations to the Atmospheric Molybdenum Cycle
DOI: 10.25442/hku.14073497
title: Supporting data for '"Untouched" Myanmar: An Ethnography of a Tourism Frontier'

description: This dataset includes raw and analytical files generated during research for the PhD thesis, '"Untouched" Myanmar: An Ethnography of a Tourism Frontier'. The dataset includes interview recordings, interview transcripts, metadata files, images used within the thesis manuscript, research ethics approval documents, and questions asked of interview participants.<br>The thesis project investigates the discourse of contemporary tourism. In addition to sociolinguistic and literary analysis, the project used a linguistic-ethnographic approach to analyze discourse. Tourists were recruited for interviews during participant observation and asked questions from the listed set in an unstructured format.<br><br><br>
DOI: 10.25442/hku.14073497.v1
title: Supporting data for '"Untouched" Myanmar: An Ethnography of a Tourism Frontier'

description: This dataset includes raw and analytical files generated during research for the PhD thesis, '"Untouched" Myanmar: An Ethnography of a Tourism Frontier'. The dataset includes interview recordings, interview transcripts, metadata files, images used within the thesis manuscript, research ethics approval documents, and questions asked of interview participants.<br>The thesis project investigates the discourse of contemporary tourism. In addition to sociolinguistic and literary analysis, the project used a linguistic-ethnographic approach to analyze discourse. Tourists were recruited for interviews during participant observation and asked questions from the listed set in an unstructured format.<br><br><br>
DOI: 10.7277/g0jr-nf67
title: Development of a Seismic Design Methodology for Precast Floor Diaphragms (NEES-2005-0046)

description: &lt;p&gt;&lt;strong&gt;Title: &lt;/strong&gt;Development of a Seismic Design Methodology for Precast Floor Diaphragms (NEES-2005-0046)&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Year Of Curation: &lt;/strong&gt;2011&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Description: &lt;/strong&gt;The Precast/Prestressed Concrete Institute (PCI) is conducting a large area of emphasis research project on precast concrete diaphragms. The project has an ultimate goal of developing a comprehensive seismic design methodology.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Award: &lt;/strong&gt;http://www.nsf.gov/awardsearch/showAward?AWD_ID=0324522&lt;/p&gt; &lt;p&gt;&lt;strong&gt;PIs &amp; CoPIs: &lt;/strong&gt;CPF 02-06&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Dates: &lt;/strong&gt;October 01, 2004 - September 30, 2008&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Organizations: &lt;/strong&gt;Lehigh University, PA, United States, University of Arizona, AZ, United States, University of California, San Diego, CA, United States&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Facilities: &lt;/strong&gt;University of Arizona, AZ, United States, Lehigh University, PA, United States, University of California, San Diego, CA, United States&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Sponsor: &lt;/strong&gt;CPF - n/a - 02-06&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Keywords: &lt;/strong&gt;Precast Concrete Diaphragms, Shaking Table Test, Precast Floor Diaphragm&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Publications: &lt;/strong&gt;&lt;/p&gt; &lt;p&gt;&quot;Preliminary Results of the Shake-Table Testing for the Development of a Diaphragm Seismic Design Methodology&quot;&lt;/p&gt; &lt;p&gt;&quot;Seismic demands in precast concrete diaphragms&quot;&lt;/p&gt; &lt;p&gt;Matthew Schoettler, 2010, &quot;Seismic Demands in Precast Concrete Diaphragms&quot;&lt;/p&gt; &lt;nb:citations&gt;&lt;/nb:citations&gt;
DOI: 10.5067/c663v8751rea
title: SORCE SOLSTICE FUV and MUV Level 3 Solar Spectral Irradiance 1.0nm Res 24-Hour Means V018
DOI: 10.5281/zenodo.3742742
title: Corn-Soy Data Layer

description: <strong>Dataset Abstract:</strong> Field-level monitoring of crop types in the United States via the Cropland Data Layer (CDL) has played an important role in improving production forecasts and enabling large-scale study of agricultural inputs and outcomes. Although CDL offers crop type maps across the conterminous US from 2008 onward, such maps are missing in many Midwestern states or are uneven in quality before 2008. To fill these data gaps, we used the now-public Landsat archive and cloud computing services to map corn and soybean at 30m resolution across the US Midwest from 1999-2018. Our training data were CDL from 2008-2018, and we validated the predictions on CDL 1999-2007 where available, county-level crop acreage statistics, and state-level crop rotation statistics. The corn-soybean maps, which we call the Corn-Soy Data Layer (CSDL), are publicly hosted on Google Earth Engine and also available for download on Zenodo. <strong>Summary of Methods:</strong> Using Google Earth Engine, we trained a random forest classifier to classify each pixel of the study area into corn, soybean, and an aggregated "other crops" class. CDL 2008-2018 data were used as labels. The features input to the model were harmonic regression coefficients fit to the NIR, SWIR1, SWIR2, and GCVI bands/indices of time series from Landsat 5, 7, and 8 Surface Reflectance observations. Cloudy pixels were masked out using the <em>pixel_qa</em> band provided with Landsat Surface Reflectance products. <strong>Map Legend:</strong> 0 = outside study area 1 = corn 5 = soy 9 = other crop 255 = non-crop (masked by NLCD) Values were chosen to be consistent with CDL values when possible. <strong>Usage Notes:</strong> We recommend that users consider metrics such as (1) user's and producer's accuracy with CDL and (2) R<sup>2</sup> with NASS statistics across space and time to determine in which states/counties and years CSDL is of high quality. This can be done with the CSV file of user's and producer's accuracies included in this Zenodo, and annual county-level statistics and example code we have included in our repo at https://github.com/LobellLab/csdl. <strong>Updates:</strong> <strong>March 1, 2021:</strong> Fixed an issue where 255 (non-crop) values were represented as NAs instead. CSDL now contains the 255 values representing non-crop. <strong>October 20, 2020:</strong> Fixed projection issues in the previous version. The CSDL projection now matches that of CDL. <strong>July 13, 2020:</strong> We revised how we used NLCD to mask out non-crop pixels from our maps. Instead of using one cropland mask (the union of cropland across all NLCD maps) for all years of CSDL, we used a different cropland mask (the last available NLCD) for each year of CSDL. We also reprojected the CSDL maps to the same projection as CDL to make it easier for users to transition between or combine the two datasets.
DOI: 10.5281/zenodo.4110647
title: Corn-Soy Data Layer

description: <strong>Dataset Abstract:</strong> Field-level monitoring of crop types in the United States via the Cropland Data Layer (CDL) has played an important role in improving production forecasts and enabling large-scale study of agricultural inputs and outcomes. Although CDL offers crop type maps across the conterminous US from 2008 onward, such maps are missing in many Midwestern states or are uneven in quality before 2008. To fill these data gaps, we used the now-public Landsat archive and cloud computing services to map corn and soybean at 30m resolution across the US Midwest from 1999-2018. Our training data were CDL from 2008-2018, and we validated the predictions on CDL 1999-2007 where available, county-level crop acreage statistics, and state-level crop rotation statistics. The corn-soybean maps, which we call the Corn-Soy Data Layer (CSDL), are publicly hosted on Google Earth Engine and also available for download on Zenodo. <strong>Summary of Methods:</strong> Using Google Earth Engine, we trained a random forest classifier to classify each pixel of the study area into corn, soybean, and an aggregated "other crops" class. CDL 2008-2018 data were used as labels. The features input to the model were harmonic regression coefficients fit to the NIR, SWIR1, SWIR2, and GCVI bands/indices of time series from Landsat 5, 7, and 8 Surface Reflectance observations. Cloudy pixels were masked out using the <em>pixel_qa</em> band provided with Landsat Surface Reflectance products. <strong>Map Legend:</strong> 0 = outside study area 1 = corn 5 = soy 9 = other crop 255 = non-crop (masked by NLCD) Values were chosen to be consistent with CDL values when possible. <strong>Usage Notes:</strong> We recommend that users consider metrics such as (1) user's and producer's accuracy with CDL and (2) R<sup>2</sup> with NASS statistics across space and time to determine in which states/counties and years CSDL is of high quality. This can be done with the CSV file of user's and producer's accuracies included in this Zenodo, and annual county-level statistics and example code we have included in our repo at https://github.com/LobellLab/csdl. <strong>Updates:</strong> <strong>October 20, 2020:</strong> Fixed projection issues in the previous version. The CSDL projection now matches that of CDL. <strong>July 13, 2020:</strong> We revised how we used NLCD to mask out non-crop pixels from our maps. Instead of using one cropland mask (the union of cropland across all NLCD maps) for all years of CSDL, we used a different cropland mask (the last available NLCD) for each year of CSDL. We also reprojected the CSDL maps to the same projection as CDL to make it easier for users to transition between or combine the two datasets.
DOI: 10.6084/m9.figshare.14138585
title: Online PBL _combined data

description: This is a set of combined data comparing the learning experiences of pre-clinical medical students in virtual problem-based learning (PBL) at the beginning and end of implementation of virtual PBL.
DOI: 10.17632/svth7pvkp5.1
title: Data for: TLSAN: Time-aware Long- and Short-term Attention Network for Next-item Recommendation

description: Amazon exposes the official datasets (http://jmcauley.ucsd.edu/data/amazon/) which have filtered out users and items with less than 5 reviews and removed a large amount of invalid data. Because of above advantages, these datasets are widely utilized by researchers. We also chose Amazon's dataset for experiments. In our experiments, only users, items, interactions, and category information are utilized. We do the preprocessing in the following two steps: 1. Remove the users whose interactions less than 10 and the items which interactions less than 8 to ensure the effectiveness of each user and item. 2. Select the users with more than 4 sessions, and select up to 90 behavior records for the remaining users. This step guarantees the existence of long- and short-term behavior records and all behavior records occurred within recent three months.
DOI: 10.17632/h2wf4wy9m4.1
title: Data for: The impact of Volcanic activity on the deposition of organic-rich shales: Evidences from carbon isotopic and geochemical compositions

description: Carbon isotopic and geochemical characteristics of the sediments in Late Ordovician and Early Silurian
DOI: 10.26188/12824822.v4
title: Freelance et al. 2020 photic environment sensory adaptation data

description: Data contains compound eye ommatidia diameter and antennal sensilla density metrics for 12 closely-related pairs of insect species that vary in the photic environment (day, dim-light) in which they are active for foraging and reproduction. Each species pair is from a separate taxonomic family with one day- and one dim-light- active species.
DOI: 10.26188/12824822
title: Freelance et al. 2020 photic environment sensory adaptation data

description: Data contains compound eye ommatidia diameter and antennal sensilla density metrics for 12 closely-related pairs of insect species that vary in the photic environment (day, dim-light) in which they are active for foraging and reproduction. Each species pair is from a separate taxonomic family with one day- and one dim-light- active species.
DOI: 10.26188/12824822.v3
title: Freelance et al. 2020 photic environment sensory adaptation data

description: Data contains compound eye ommatidia diameter and antennal sensilla density metrics for 12 closely-related pairs of insect species that vary in the photic environment (day, dim-light) in which they are active for foraging and reproduction. Each species pair is from a separate taxonomic family with one day- and one dim-light- active species.
DOI: 10.7277/zx2x-8n64
title: TSUNAMOS: A Validated, Multi-Scale Tsunami Model for Hybrid Numerical-Experimental Simulation (NEES-2008-0577)

description: &lt;p&gt;&lt;strong&gt;Title&lt;/strong&gt;: TSUNAMOS: A Validated, Multi-Scale Tsunami Model for Hybrid Numerical-Experimental Simulation (NEES-2008-0577)&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Year Of Curation: &lt;/strong&gt;2013&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Description: &lt;/strong&gt;The objectives of the proposed research program are to 1) improve understanding of nearshore, three-dimensional tsunami evolution through an extensive set of physical experiments using NEES facilities; 2) create an extensible framework to provide a systematic structure for validating computational models with experimental and field data; 3) refine modeling capabilities and couple the various components together to create a multi-scale simulation tool; and 4) develop a sustainable education and outreach program that educates the general public about tsunamis and appropriate responses to them. Nearshore evolution of tsunami waves, such as 3D breaking through focusing and bathymetry, and overland flow across irregular and rough topographies, will be investigated. Concurrent to the experimental effort, a comprehensive tsunami simulator, TSUNAMOS (Tsunami Open Source Community Model), will be developed. &lt;/p&gt; &lt;p&gt;&lt;strong&gt;Award: &lt;/strong&gt;http://www.nsf.gov/awardsearch/showAward?AWD_ID=0619083&lt;/p&gt; &lt;p&gt;&lt;strong&gt;PIs &amp; CoPIs: &lt;/strong&gt;Patrick Lynett, Philip Liu&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Dates: &lt;/strong&gt;September 21, 2006 - October 01, 2009&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Organizations: &lt;/strong&gt;Cornell University, NY, United States,,Oregon State University, OR, United States&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Facilities: &lt;/strong&gt;Oregon State University, OR, United States&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Sponsor: &lt;/strong&gt;NSF - 0619083 &lt;/p&gt; &lt;p&gt;&lt;strong&gt;Keywords: &lt;/strong&gt;solitary wave, run-up, free surface measurements,tsunami, conical island,dye study, flow motions, ,velocity, turbulence&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Publications: &lt;/strong&gt;&lt;br /&gt; David Swigler; Sangyoung Son; Duncan Bryant; Scott Socolofsky, &quot;Experimental Study of Solitary Wave Evolution over a 3D Shallow Shelf&quot;&lt;br /&gt; David Townley Swingler, &quot;Laboratory Study Investigating the Three-Dimensional Turbulence and Kinematic Properties Associated with a Breaking Solitary Wave&quot;&lt;/p&gt; &lt;nb:citations&gt;&lt;/nb:citations&gt;
DOI: 10.13011/m3-g1ek-5g42
title: Automated iterative refinement of parameters
DOI: 10.5281/zenodo.4270621
title: probe

description: Probe setup
DOI: 10.5281/zenodo.4270620
title: probe

description: Probe setup
DOI: 10.6084/m9.figshare.4256624
title: Critical current characterisation of SuperPower Advanced Pinning 2G HTS superconducting wire

description: Detailed measurements of the critical current of a commercial 2G HTS REBCO wire as a function of temperature, magnetic field, and field angle, performed at the Robinson Research Institute of Victoria University of Wellington.
DOI: 10.6084/m9.figshare.4256624.v1
title: Critical current characterisation of SuperPower Advanced Pinning 2G HTS superconducting wire

description: Detailed measurements of the critical current of a commercial 2G HTS YBCO wire as a function of temperature, magnetic field, and field angle, performed at the Robinson Research Institute of Victoria University of Wellington.This data is referenced in N. M. Strickland and S. C. Wimbush, <i>The magnetic-field dependence of critical current: what we really need to know</i>, IEEE Trans. Appl. Supercond. (2016) submitted.
DOI: 10.6084/m9.figshare.13487094.v4
title: Supplemental File 6. Interview Analysis

description: Interview data
DOI: 10.6084/m9.figshare.13487094
title: Supplemental File 6. Interview Analysis

description: Interview data
DOI: 10.6084/m9.figshare.13487094.v3
title: Supplemental File 6. Interview Analysis

description: Interview data
DOI: 10.6084/m9.figshare.13487094.v2
title: Supplemental File 6. Interview Analysis

description: Interview data
DOI: 10.6084/m9.figshare.3759318
title: Critical current characterisation of SuperPower M4 Advanced Pinning 2G HTS superconducting wire

description: This dataset has been superseded. The new dataset is at https://doi.org/10.6084/m9.figshare.4256624, while the original dataset is at https://doi.org/10.6084/m9.figshare.3759318.v2.<br>
DOI: 10.6084/m9.figshare.3759318.v3
title: Critical current characterisation of SuperPower M4 Advanced Pinning 2G HTS superconducting wire

description: This dataset has been superseded. The new dataset is at https://doi.org/10.6084/m9.figshare.4256624, while the original dataset is at https://doi.org/10.6084/m9.figshare.3759318.v2.<br>
DOI: 10.6084/m9.figshare.3759318.v2
title: Critical current characterisation of SuperPower M4 Advanced Pinning 2G HTS superconducting wire

description: Detailed measurements of the critical current of a commercial 2G HTS YBCO wire as a function of temperature, magnetic field, and field angle, performed at the Robinson Research Institute of Victoria University of Wellington.
DOI: 10.11577/1767965
title: MyD88 TIR domain higher-order assembly interactions revealed by microcrystal electron diffraction and serial femtosecond crystallography
DOI: 10.5281/zenodo.4278256
title: Spatiotemporal variation of groundwater recharge in the lower reaches of the Poyang Lake Basin, China: Insights from stable hydrogen and oxygen isotopes

description: isotopes in groundwater and precipitation