cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14272/bmimnrpaepiydn-uhfffaoysa-n/chmo0000593.3
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (3-methyl-1H-quinoxalin-2-one)
title: InChI=1S/C9H8N2O/c1-6-9(12)11-8-5-3-2-4-7(8)10-6/h2-5H,1H3,(H,11,12)

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, DMSO-d6, ppm) δ = 2.39 (s, 3H), 7.21–7.30 (m, 2H), 7.46 (ddd, 3J = 8.3 Hz, 3J = 7.2 Hz, 4J = 1.4 Hz, 1H), 7.68 (dd, 3J = 7.8 Hz, 4J = 1.0 Hz, 1H), 12.29 (s, 1H). Impuritiy: 3.34 ppm (Water).
DOI: 10.14272/bmimnrpaepiydn-uhfffaoysa-n/chmo0000630.3
title: infrared absorption spectroscopy (IR) (3-methyl-1H-quinoxalin-2-one)
title: InChI=1S/C9H8N2O/c1-6-9(12)11-8-5-3-2-4-7(8)10-6/h2-5H,1H3,(H,11,12)

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 3003, 2959, 2891, 2833, 2769, 2706, 1657, 1640, 1601, 1565, 1500, 1485, 1459, 1431, 1422, 1378, 1353, 1343, 1319, 1285, 1276, 1207, 1188, 1156, 1122, 1089, 1026, 1006, 975, 962, 945, 928, 888, 853, 779, 751, 725, 691, 599, 584, 561, 476, 467, 452, 416, 398 cm–1.
DOI: 10.14272/bmimnrpaepiydn-uhfffaoysa-n/chmo0000596.2
title: distortionless enhancement with polarization transfer (DEPT) (3-methyl-1H-quinoxalin-2-one)
title: InChI=1S/C9H8N2O/c1-6-9(12)11-8-5-3-2-4-7(8)10-6/h2-5H,1H3,(H,11,12)

description: dataset for distortionless enhancement with polarization transfer (DEPT)
DOI: 10.14272/bmimnrpaepiydn-uhfffaoysa-n/chmo0000470.4
title: mass spectrometry (MS) (3-methyl-1H-quinoxalin-2-one)
title: InChI=1S/C9H8N2O/c1-6-9(12)11-8-5-3-2-4-7(8)10-6/h2-5H,1H3,(H,11,12)

description: dataset for mass spectrometry (MS) MS (EI, 70 eV, 80 °C), m/z (%): 161 (10) [M+H]+, 160 (100) [M]+, 132 (96), 131 (63), 90 (13), 64 (11), 63 (16).HRMS–EI (m/z): [M]+ calcd for C9H8ON2 160.0631; found 160.0632.
DOI: 10.14272/bmimnrpaepiydn-uhfffaoysa-n/chmo0000596.3
title: distortionless enhancement with polarization transfer (DEPT) (3-methyl-1H-quinoxalin-2-one)
title: InChI=1S/C9H8N2O/c1-6-9(12)11-8-5-3-2-4-7(8)10-6/h2-5H,1H3,(H,11,12)

description: dataset for distortionless enhancement with polarization transfer (DEPT)
DOI: 10.18430/m37kcn
title: X-ray diffraction data for the reconstructed ancestor of HIUases and Transthyretins (7KCN)
DOI: 10.14272/aziggtbmccwnpw-uhfffaoysa-n/chmo0000593.1
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (3-methylquinoxaline-2-carbaldehyde)
title: InChI=1S/C10H8N2O/c1-7-10(6-13)12-9-5-3-2-4-8(9)11-7/h2-6H,1H3

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, CDCl3, ppm) δ = 3.05 (s, 3H), 7.81 (ddd, 3J = 8.3 Hz, 3J = 6.8 Hz, 4J = 1.4 Hz, 1H), 7.90 (ddd, 3J = 8.4 Hz, 3J = 6.9 Hz, 4J = 1.5 Hz, 1H), 8.10 (dd, 3J = 8.4 Hz, 4J = 1.5 Hz, 1H), 8.20 (dd, 3J = 8.4 Hz, 4J = 1.5 Hz, 1H), 10.32 (s, 1H). Impurities (ppm): 1.25 (grease).
DOI: 10.14272/aziggtbmccwnpw-uhfffaoysa-n.2
title: 3-methyl-2-quinoxalinecarboxaldehyde
title: InChI=1S/C10H8N2O/c1-7-10(6-13)12-9-5-3-2-4-8(9)11-7/h2-6H,1H3

description: This dataset contains experimental data from a sample (3-methylquinoxaline-2-carbaldehyde, InChI=1S/C10H8N2O/c1-7-10(6-13)12-9-5-3-2-4-8(9)11-7/h2-6H,1H3). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) mass spectrometry (MS) infrared absorption spectroscopy (IR) distortionless enhancement with polarization transfer (DEPT) distortionless enhancement with polarization transfer (DEPT)
DOI: 10.14272/aziggtbmccwnpw-uhfffaoysa-n/chmo0000595.1
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (3-methylquinoxaline-2-carbaldehyde)
title: InChI=1S/C10H8N2O/c1-7-10(6-13)12-9-5-3-2-4-8(9)11-7/h2-6H,1H3

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (101 MHz, CDCl3, ppm) δ = 23.3 (+, CH3), 128.7 (+), 130.1 (+), 130.2 (+), 133.2 (+), 141.0 (Cquart), 142.8 (Cquart), 145.4 (Cquart), 153.7 (Cquart), 194.1 (+).
DOI: 10.14272/aziggtbmccwnpw-uhfffaoysa-n/chmo0000596.3
title: distortionless enhancement with polarization transfer (DEPT) (3-methylquinoxaline-2-carbaldehyde)
title: InChI=1S/C10H8N2O/c1-7-10(6-13)12-9-5-3-2-4-8(9)11-7/h2-6H,1H3

description: dataset for distortionless enhancement with polarization transfer (DEPT)
DOI: 10.14272/aziggtbmccwnpw-uhfffaoysa-n/chmo0000470.1
title: mass spectrometry (MS) (3-methylquinoxaline-2-carbaldehyde)
title: InChI=1S/C10H8N2O/c1-7-10(6-13)12-9-5-3-2-4-8(9)11-7/h2-6H,1H3

description: dataset for mass spectrometry (MS) MS (EI, 70 eV, 30 °C), m/z (%): 173 (12) [M+H]+, 172 (100) [M]+, 144 (57), 143 (95), 118 (10), 117 (13), 102 (46), 76 (22), 75 (20), 51 (12).HRMS–EI (m/z): [M]+ calcd for C10H8ON2 172.0631; found 172.0632.
DOI: 10.14272/aziggtbmccwnpw-uhfffaoysa-n/chmo0000630.1
title: infrared absorption spectroscopy (IR) (3-methylquinoxaline-2-carbaldehyde)
title: InChI=1S/C10H8N2O/c1-7-10(6-13)12-9-5-3-2-4-8(9)11-7/h2-6H,1H3

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 3055, 3030, 2992, 2961, 2921, 2870, 1703, 1547, 1483, 1465, 1425, 1394, 1373, 1354, 1317, 1302, 1258, 1218, 1167, 1133, 1120, 1079, 1035, 1017, 1007, 997, 962, 904, 813, 793, 752, 705, 683, 618, 598, 547, 535, 511, 494, 469, 458, 438, 421, 395, 380 cm–1.
DOI: 10.14272/aziggtbmccwnpw-uhfffaoysa-n/chmo0000596.2
title: distortionless enhancement with polarization transfer (DEPT) (3-methylquinoxaline-2-carbaldehyde)
title: InChI=1S/C10H8N2O/c1-7-10(6-13)12-9-5-3-2-4-8(9)11-7/h2-6H,1H3

description: dataset for distortionless enhancement with polarization transfer (DEPT)
DOI: 10.4246/ca_dwr_waterbalance_20210519_2002-md58308852a60db20bfbce499226a1bc570.zip
title: CA_DWR_WaterBalance_20210519_2002-md58308852a60db20bfbce499226a1bc570.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2003-md5ed055fa08867b9933a148fb26582f7a7.zip
title: CA_DWR_WaterBalance_20210519_2003-md5ed055fa08867b9933a148fb26582f7a7.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2005-md50047bac80d0bfc2fcac9d6fa4de22792.zip
title: CA_DWR_WaterBalance_20210519_2005-md50047bac80d0bfc2fcac9d6fa4de22792.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2004-md5e89287138921829a47ccd3c206f7a611.zip
title: CA_DWR_WaterBalance_20210519_2004-md5e89287138921829a47ccd3c206f7a611.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2006-md5097b09a1496d054e48c975eae3614715.zip
title: CA_DWR_WaterBalance_20210519_2006-md5097b09a1496d054e48c975eae3614715.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2007-md5848b81f5600deee3526a98b4bf52eee1.zip
title: CA_DWR_WaterBalance_20210519_2007-md5848b81f5600deee3526a98b4bf52eee1.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2008-md5d5c3fe55c5a5e9a9b11475a60194f4b8.zip
title: CA_DWR_WaterBalance_20210519_2008-md5d5c3fe55c5a5e9a9b11475a60194f4b8.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2009-md50ae6c804d8d511356f52bb3de53e52b5.zip
title: CA_DWR_WaterBalance_20210519_2009-md50ae6c804d8d511356f52bb3de53e52b5.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2010-md50c8bdd21a252f24a21c56d4c346294e3.zip
title: CA_DWR_WaterBalance_20210519_2010-md50c8bdd21a252f24a21c56d4c346294e3.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2011-md559f519da760e29eb042d803e332bf9e7.zip
title: CA_DWR_WaterBalance_20210519_2011-md559f519da760e29eb042d803e332bf9e7.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2012-md56ab4094523c19f7cdefd7f5ec6cded3f.zip
title: CA_DWR_WaterBalance_20210519_2012-md56ab4094523c19f7cdefd7f5ec6cded3f.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2013-md588dbae72ac58945fc63db767889ba660.zip
title: CA_DWR_WaterBalance_20210519_2013-md588dbae72ac58945fc63db767889ba660.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2014-md59443a932d9aafd4befaca273f92990df.zip
title: CA_DWR_WaterBalance_20210519_2014-md59443a932d9aafd4befaca273f92990df.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2016-md55aa5b8c76170b891cd6fe3c013cd96bf.zip
title: CA_DWR_WaterBalance_20210519_2016-md55aa5b8c76170b891cd6fe3c013cd96bf.zip
DOI: 10.4246/ca_dwr_waterbalance_20210519_2015-md5a989de27cc01cbbf3810c1b1584d4ecf.zip
title: CA_DWR_WaterBalance_20210519_2015-md5a989de27cc01cbbf3810c1b1584d4ecf.zip
DOI: 10.25810/9cc0-s415
title: Solar Proxy Model for the SSI3 Composite

description: Proxy model of solar spectral irradiance variability were developed for creating the SSI3 composite data set.  A merge of these proxy models is described here.

REFERENCE:

T. N. Woods & M. T. DeLand, An Improved Solar Spectral Irradiance Composite Record, Earth and Space Climate, submitted, 2021.
DOI: 10.15468/u7uy88
title: Notulae to the Italian native vascular flora: 11

description: This dataset contains the digitized treatments in Plazi based on the original journal article Bartolucci, Fabrizio, Domina, Gianniantonio, Andreatta, Sebastiano, Argenti, Carlo, Bacchetta, Gianluigi, Ballelli, Sandro, Banfi, Enrico, Barberis, Davide, Barberis, Giuseppina, Bedini, Gianni, Bolpagni, Rossano, Bonali, Fabrizio, Bovio, Maurizio, Briozzo, Ian, Brusco, Agostino, Caldarella, Orazio, Campus, Giuliano, Cancellieri, Laura, Carotenuto, Luciana, Cheli, Emanuele, Dagnino, Davide, Guacchio, Emanuele Del, Farris, Emmanuele, Ferretti, Giulio, Filibeck, Goffredo, Foggi, Bruno, Gabellini, Antonio, Galasso, Gabriele, Gianguzzi, Lorenzo, Gottschlich, Guenter, Gubellini, Leonardo, Hofmann, Nicole, Iamonico, Duilio, Laface, Valentina L. A., Lonati, Michele, Lucarini, Domenico, Lupoletti, Jacopo, Marchiano, Roberto, Marenzi, Paolo, Martignoni, Marco, Mei, Giacomo, Menini, Flavio, Merli, Marco, Musarella, Carmelo M., Orsenigo, Simone, Peccenini, Simonetta, Pennesi, Riccardo, Peruzzi, Lorenzo, Pica, Antonio, Pinzani, Lorenzo, Piovesan, Gianluca, Pittarello, Marco, Podda, Lina, Enri, Simone Ravetto, Roma-Marzio, Francesco, Rosati, Leonardo, Spampinato, Giovanni, Stinca, Adriano, Tonelli, Sarah, Trenchi, Maurizio, Turcato, Claudia, Viciani, Daniele, Lastrucci, Lorenzo (2021): Notulae to the Italian native vascular flora: 11. Italian Botanist 11: 77-92, DOI: http://dx.doi.org/10.3897/italianbotanist.11.68048, URL: http://dx.doi.org/10.3897/italianbotanist.11.68048
DOI: 10.15468/4mabdd
title: An illustrated key to the species of Gasteruption Latreille (Hymenoptera, Gasteruptiidae) from Palaearctic China, with description of four new species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Tan, Jiang-Li, Achterberg, Cornelis van, Wu, Jia-Xuan, Wang, Hang, Zhang, Qi-Jing (2021): An illustrated key to the species of Gasteruption Latreille (Hymenoptera, Gasteruptiidae) from Palaearctic China, with description of four new species. ZooKeys 1038: 1-103, DOI: http://dx.doi.org/10.3897/zookeys.1038.64978, URL: http://dx.doi.org/10.3897/zookeys.1038.64978
DOI: 10.15468/ah7z7k
title: A new species of Pilarella (Copepoda, Calanoida, Arietellidae) from the hyperbenthic layer of Japan, with a molecular phylogenetic analysis of some representative genera of the Arietellidae

description: This dataset contains the digitized treatments in Plazi based on the original journal article Komeda, Sota, Adachi, Kenta, Ohtsuka, Susumu (2021): A new species of Pilarella (Copepoda, Calanoida, Arietellidae) from the hyperbenthic layer of Japan, with a molecular phylogenetic analysis of some representative genera of the Arietellidae. ZooKeys 1038: 179-194, DOI: http://dx.doi.org/10.3897/zookeys.1038.63170, URL: http://dx.doi.org/10.3897/zookeys.1038.63170
DOI: 10.15468/gexbaw
title: A new genus and eight newly recorded genera of Braconinae Nees (Hymenoptera, Braconidae) from China, with descriptions of fourteen new species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Li, Yang, Achterberg, Cornelis van, Chen, Xue-xin (2020): A new genus and eight newly recorded genera of Braconinae Nees (Hymenoptera, Braconidae) from China, with descriptions of fourteen new species. ZooKeys 1038: 105-178, DOI: http://dx.doi.org/10.3897/zookeys.1038.55258, URL: http://dx.doi.org/10.3897/zookeys.1038.55258
DOI: 10.5281/zenodo.4774258
title: Magicwand: A platform to provide high-quality, reliable, and reproducible data sets for low-and-slow DDoS attacks

description: <strong>Magicwand Data Tool Datasets</strong> The following datasets were generated utilizing the https://github.com/twosixlabs/magicwand-datatool tool (described below). <strong>Magicwand Data Tool </strong> The Magicwand Datatool is a PCAP generation platform to facilitate machine learning model development for identifying benign traffic vs. malicious "low volume" denial of service traffic. Magicwand is a platform to provide high-quality, reliable, and reproducible data sets for low-and-slow DDoS attacks. With the use of Docker images and customizable JSON files, users can generate a multitude of network traffic PCAPS. For complete documentation on Magicwand, a gallery of available attacks, the configuration guide, tutorials, and teaching resources, frequently asked questions, and more, please read our documentation. <strong>Relevant Versions for Generated Data</strong> magicwand: 1.0.4<br> OS: macOS 11.2.3<br> Docker: Docker version 20.10.5, build 55c4c88
DOI: 10.5281/zenodo.4774257
title: Magicwand: A platform to provide high-quality, reliable, and reproducible data sets for low-and-slow DDoS attacks

description: <strong>Magicwand Data Tool Datasets</strong> The following datasets were generated utilizing the https://github.com/twosixlabs/magicwand-datatool tool (described below). <strong>Magicwand Data Tool </strong> The Magicwand Datatool is a PCAP generation platform to facilitate machine learning model development for identifying benign traffic vs. malicious "low volume" denial of service traffic. Magicwand is a platform to provide high-quality, reliable, and reproducible data sets for low-and-slow DDoS attacks. With the use of Docker images and customizable JSON files, users can generate a multitude of network traffic PCAPS. For complete documentation on Magicwand, a gallery of available attacks, the configuration guide, tutorials, and teaching resources, frequently asked questions, and more, please read our documentation. <strong>Relevant Versions for Generated Data</strong> magicwand: 1.0.4<br> OS: macOS 11.2.3<br> Docker: Docker version 20.10.5, build 55c4c88
DOI: 10.34740/kaggle/dsv/2250730
title: MuSe: The Musical Sentiment Dataset
DOI: 10.6084/m9.figshare.14251130.v2
title: Does different activation between the medial and the lateral gastrocnemius during walking translate into different fascicle behavior ?

description: The file contains all the results analyzed in the study in .mat format and an example of EMG and ultrasound raw data for one participant. These files are accompanied by an "user guide" document which explains how the data and file are organized. All methodological considerations are described in the scientific article linked to the data.
DOI: 10.15784/601445
title: Larsen C automatic weather station data 2008–2011

description: As part of IPY-0732946, three automatic weather stations (Larsen 1, 2, 3) were installed along a latitudinal gradient on the Larsen C ice shelf. The stations were installed in December 2008 (Larsen 3 AWS did not come online until 2009) and operated through the end of the project in November 2011.
DOI: 10.21227/pvt8-3n83
title: Machine Learning on FPGA for Robust Si3N4-gate ISFET pH Sensor in Industrial IoT Applications

description: This dataset consists of temporal and temperature drift characteristics of Si3N4-gate iSFET andsupplementary files
DOI: 10.5517/ccdc.csd.cc22521d
title: CCDC 1911492: Experimental Crystal Structure Determination

description: Related Article: Abdul Ajees Abdul Salam, Upendra Nayek, Geetha Mathew, M.K. Unnikrishnan|2021|J.Mol.Struct.|1240|130600|doi:10.1016/j.molstruc.2021.130600
DOI: 10.5517/ccdc.csd.cc24bdc8
title: CCDC 1976199: Experimental Crystal Structure Determination

description: Related Article: MA. Gomathi, C. Karnan, T. Sivanesan, J. Christina Rhoda, S. Manivannan, V. Ragavendran, G. Vinitha, AR. Prabakaran|2021|Chem.Phys.Lett.|776|138705|doi:10.1016/j.cplett.2021.138705
DOI: 10.5517/ccdc.csd.cc24yxbc
title: CCDC 1994953: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc2527zh
title: CCDC 1998166: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc25t4w1
title: CCDC 2020173: Experimental Crystal Structure Determination

description: Related Article: Nicholas A. Phillips, Richard Y. Kong, Andrew J. P. White, Mark R. Crimmin|2021|Angew.Chem.,Int.Ed.|60|12013|doi:10.1002/anie.202100919
DOI: 10.5517/ccdc.csd.cc25t4x2
title: CCDC 2020174: Experimental Crystal Structure Determination

description: Related Article: Nicholas A. Phillips, Richard Y. Kong, Andrew J. P. White, Mark R. Crimmin|2021|Angew.Chem.,Int.Ed.|60|12013|doi:10.1002/anie.202100919
DOI: 10.5517/ccdc.csd.cc25t4y3
title: CCDC 2020175: Experimental Crystal Structure Determination

description: Related Article: Nicholas A. Phillips, Richard Y. Kong, Andrew J. P. White, Mark R. Crimmin|2021|Angew.Chem.,Int.Ed.|60|12013|doi:10.1002/anie.202100919
DOI: 10.5517/ccdc.csd.cc25t4z4
title: CCDC 2020176: Experimental Crystal Structure Determination

description: Related Article: Nicholas A. Phillips, Richard Y. Kong, Andrew J. P. White, Mark R. Crimmin|2021|Angew.Chem.,Int.Ed.|60|12013|doi:10.1002/anie.202100919
DOI: 10.5517/ccdc.csd.cc26phl0
title: CCDC 2046452: Experimental Crystal Structure Determination

description: Related Article: M. Gloria Quintanilla, Ivan Pérez, Beatriz de Francisco, Avelino Martin, Noemi Salardon, J. Luis de la Fuente, Belen Batanero|2021|J.Electroanal.Chem.|892|115265|doi:10.1016/j.jelechem.2021.115265
DOI: 10.5517/ccdc.csd.cc26q6gm
title: CCDC 2047130: Experimental Crystal Structure Determination

description: Related Article: Xiao-Tong Zhao, Chun Lei, Jin-Qiu You, Ting Zhao, Mei-Hua Yu, Xun-Long Shi, Xiao Hu, Ai-Jun Hou|2021|Bioorg.Chem.|112|104916|doi:10.1016/j.bioorg.2021.104916
DOI: 10.5517/ccdc.csd.cc26q6hn
title: CCDC 2047131: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc26tnxm
title: CCDC 2050461: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc26tnyn
title: CCDC 2050462: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc26vw43
title: CCDC 2051615: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc26wh0m
title: CCDC 2052200: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc26wh1n
title: CCDC 2052201: Experimental Crystal Structure Determination

description: Related Article: Olga A. Lodochnikova, Daut R. Islamov, Daria P. Gerasimova, Dmitry V. Zakharychev, Alina F. Saifina, Svetlana V. Pestova, Evgeny S. Izmest'ev, Svetlana A. Rubtsova, Roman S. Pavelyev, Ilfat Z. Rakhmatullin, Vladimir V. Klochkov, Olga V. Ostolopovskaya, Liliya E. Nikitina, Patrick Rollin|2021|J.Mol.Struct.|1239|130491|doi:10.1016/j.molstruc.2021.130491
DOI: 10.5517/ccdc.csd.cc26wh2p
title: CCDC 2052202: Experimental Crystal Structure Determination

description: Related Article: Olga A. Lodochnikova, Daut R. Islamov, Daria P. Gerasimova, Dmitry V. Zakharychev, Alina F. Saifina, Svetlana V. Pestova, Evgeny S. Izmest'ev, Svetlana A. Rubtsova, Roman S. Pavelyev, Ilfat Z. Rakhmatullin, Vladimir V. Klochkov, Olga V. Ostolopovskaya, Liliya E. Nikitina, Patrick Rollin|2021|J.Mol.Struct.|1239|130491|doi:10.1016/j.molstruc.2021.130491
DOI: 10.5517/ccdc.csd.cc26wh3q
title: CCDC 2052203: Experimental Crystal Structure Determination

description: Related Article: Olga A. Lodochnikova, Daut R. Islamov, Daria P. Gerasimova, Dmitry V. Zakharychev, Alina F. Saifina, Svetlana V. Pestova, Evgeny S. Izmest'ev, Svetlana A. Rubtsova, Roman S. Pavelyev, Ilfat Z. Rakhmatullin, Vladimir V. Klochkov, Olga V. Ostolopovskaya, Liliya E. Nikitina, Patrick Rollin|2021|J.Mol.Struct.|1239|130491|doi:10.1016/j.molstruc.2021.130491
DOI: 10.5517/ccdc.csd.cc26wh4r
title: CCDC 2052204: Experimental Crystal Structure Determination

description: Related Article: Olga A. Lodochnikova, Daut R. Islamov, Daria P. Gerasimova, Dmitry V. Zakharychev, Alina F. Saifina, Svetlana V. Pestova, Evgeny S. Izmest'ev, Svetlana A. Rubtsova, Roman S. Pavelyev, Ilfat Z. Rakhmatullin, Vladimir V. Klochkov, Olga V. Ostolopovskaya, Liliya E. Nikitina, Patrick Rollin|2021|J.Mol.Struct.|1239|130491|doi:10.1016/j.molstruc.2021.130491
DOI: 10.5281/zenodo.4700327
title: Updated Input-Output tables of islands-case studies (projected to 2015)

description: In order to assess the macroeconomic effects of climate change impacts on the Soclimpact islands-case studies, both models, GINFORS and GEM-E3 were runned. They are essentially based on applications of IO accounting frameworks. The need to apply subnational analysis comes as consequence of spatial heterogeneity. While the aggregate effects alert policy makers for the sign and the magnitude of the impacts country-wide, these effects are not evenly distributed between regions. There may be outliers in both tails (positive and negative) but policy makers should aim at alleviating extreme negative effects on regional economies. IO data are on a regional level most of the times available, but often not very recent, scattered, and full of gaps. Therefore, the development of a consistent up to date data set was carried out in Soclimpact -task and deliverable 6.1(Updated Database of Islands: Methodological framework). IO data sets are projected to the year 2015, while macroeconomic estimates of climate impacts was carried out until 2100. More info =&gt; https://zenodo.org/record/4073090#.YH1Vv-hKiUk