cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14272/sdrxybxmbmauep-uhfffaoysa-m.1
title: C30H28ClN
title: InChI=1S/C30H28N.ClH/c1-2-23-3-11-27(12-4-23)22-31-19-17-29(18-20-31)30-21-26-10-9-24-5-7-25(8-6-24)13-15-28(30)16-14-26;/h2-8,11-12,14,16-21H,1,9-10,13,15,22H2;1H/q+1;/p-1

description: This is a physical chemical entity[CHEBI_24431] associated with a molecule[CHEBI_25367]. The molecule[CHEBI_25367] can be described by the following structural desciptors[cheminf_000085]: InChI descriptor[cheminf_000113]: InChI=1S/C30H28N.ClH/c1-2-23-3-11-27(12-4-23)22-31-19-17-29(18-20-31)30-21-26-10-9-24-5-7-25(8-6-24)13-15-28(30)16-14-26;/h2-8,11-12,14,16-21H,1,9-10,13,15,22H2;1H/q+1;/p-1, and canonical SMILES descriptor[cheminf_000007]: C=Cc1ccc(cc1)C[n+]1ccc(cc1)c1cc2CCc3ccc(CCc1cc2)cc3.[Cl-], and by the IUPAC name[cheminf_000107]: . The physical chemical entity[CHEBI_24431] has a component solvent[CHEBI_46787] which is described by the canonical SMILES descriptor[cheminf_000007]: The physical chemical entity[CHEBI_24431] has the following Sample ID as registered in the research data repository chemotion (www.chemotion-repository.net, https://doi.org/10.25504/FAIRsharing.iagXcR): CRS-33150 The physical chemical entity[CHEBI_24431] can be described by the physical descriptors [CHEMINF_000025]: Melting point descriptor[CHEMINF_000256]: 202.9 (°C) Boiling point descriptor[CHEMINF_000257]: Refractive index descriptor[CHEMINF_000253]: The physical chemical entity[CHEBI_24431] can be further described by the following assays[OBI:0000070][CHMO:0001133]: CHMO:0000593 | 1H nuclear magnetic resonance spectroscopy (1H NMR) CHMO:0000595 | 13C nuclear magnetic resonance spectroscopy (13C NMR) CHMO:0000630 | infrared absorption spectroscopy (IR) CHMO:0000470 | mass spectrometry (MS) The physical chemical entity[CHEBI_24431] was deposited to the Molecule Archive of the Karlsruhe Insitute of Technology (KIT) with the following Sample ID: Used ontologies: CHEBI - Chemical Entities of Biological Interest CHEMINF - chemical information ontology (information entities about chemical entities) CHMO - Chemical Methods Ontology OBI - Ontology for Biomedical Investigations
DOI: 10.14272/sdrxybxmbmauep-uhfffaoysa-m/chmo0000470
title: mass spectrometry (MS) ()
title: InChI=1S/C30H28N.ClH/c1-2-23-3-11-27(12-4-23)22-31-19-17-29(18-20-31)30-21-26-10-9-24-5-7-25(8-6-24)13-15-28(30)16-14-26;/h2-8,11-12,14,16-21H,1,9-10,13,15,22H2;1H/q+1;/p-1

description: dataset for mass spectrometry (MS) ESI-MS for [C30H28N]+: Calc. m/z = 402.2217, found m/z = 402.2212.
DOI: 10.14272/sdrxybxmbmauep-uhfffaoysa-m/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C30H28N.ClH/c1-2-23-3-11-27(12-4-23)22-31-19-17-29(18-20-31)30-21-26-10-9-24-5-7-25(8-6-24)13-15-28(30)16-14-26;/h2-8,11-12,14,16-21H,1,9-10,13,15,22H2;1H/q+1;/p-1

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (126 MHz, D2O) δ = 157.0 (C, CAr), 143.7 (2C, CAr), 141.4 (C, CAr), 140.6 (C, CAr), 139.9 (C, CAr), 139.0 (C, CAr), 138.8 (C, CAr), 137.0 (C, CAr), 136.0 (C, CAr), 135.7 (C, CVinyl), 135.6 (C, CAr), 133.7 (C, CAr), 133.1 (C, CAr), 132.5 (C, CAr), 132.5 (C, CAr), 131.8 (C, CAr), 129.5 (C, CAr), 129.3 (2C, CAr), 128.0 (2C, CAr), 127.2 (2C, CAr), 115.8 (C, CVinyl), 63.4 (C, CH2), 34.5 (C, CH2), 34.2 (2C, CH2), 33.4 (C, CH2).
DOI: 10.14272/sdrxybxmbmauep-uhfffaoysa-m/chmo0000630
title: infrared absorption spectroscopy (IR) ()
title: InChI=1S/C30H28N.ClH/c1-2-23-3-11-27(12-4-23)22-31-19-17-29(18-20-31)30-21-26-10-9-24-5-7-25(8-6-24)13-15-28(30)16-14-26;/h2-8,11-12,14,16-21H,1,9-10,13,15,22H2;1H/q+1;/p-1

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 3626 (m), 3616 (m), 3605 (m), 3592 (m), 3584 (m), 3384 (vs), 3377 (vs), 3109 (s), 3088 (s), 3006 (vs), 2982 (s), 2969 (s), 2956 (s), 2927 (vs), 2852 (m), 1633 (vs), 1510 (m), 1455 (m), 1153 (m), 805 (m) cm–1.
DOI: 10.6084/m9.figshare.23765169
title: human Langerhans Islets data

description: Human Langerhans Islets data used to train a machine learning algorithm able to classify beta and alpha cells. Static autofluoresnce and FLIM data are stored in R64 files (either single-cell segmented or not) and immunosfluorescence data are present as png of tif files. Data are organized according to donor source.
DOI: 10.5281/zenodo.8188543
title: Distribution, seasonality, and water-mass transformation of temperature and salinity inversions in the southern Yellow Sea

description: This dataset contains the used data at Stn. H08 and those transect stations obtained during the spring and summer cruises from 2017 to 2022. It is a supplementary of the manuscript "Distribution, seasonality, and water-mass transformation of temperature and salinity inversions in the southern Yellow Sea". Please let me know if you need any more information.
DOI: 10.5281/zenodo.8188542
title: Distribution, seasonality, and water-mass transformation of temperature and salinity inversions in the southern Yellow Sea

description: This dataset contains the used data at Stn. H08 and those transect stations obtained during the spring and summer cruises from 2017 to 2022. It is a supplementary of the manuscript "Distribution, seasonality, and water-mass transformation of temperature and salinity inversions in the southern Yellow Sea". Please let me know if you need any more information.
DOI: 10.14272/wnlqryagfimnbw-uhfffaoysa-m/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C22H22N.ClH/c1-23-14-12-21(13-15-23)22-16-19-7-6-17-2-4-18(5-3-17)8-10-20(22)11-9-19;/h2-5,9,11-16H,6-8,10H2,1H3;1H/q+1;/p-1

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, D2O) δ = 8.76 (d, J = 6.5 Hz, 2H, HAr), 8.14 (d, J = 6.4 Hz, 2H, HAr), 6.86 (d, J = 6.2 Hz, 3H, HAr), 6.77 (dd, J = 7.7, 1.9 Hz, 1H, HAr), 6.72 (td, J = 8.3, 1.9 Hz, 2H, HAr), 6.53 (dd, J = 7.9, 1.9 Hz, 1H, HAr), 4.39 (s, 3H, CH3), 3.40 (ddd, J = 13.5, 9.9, 3.2 Hz, 1H, CH2), 3.26–3.07 (m, 5H, CH2), 2.99 (ddd, J = 13.3, 10.1, 3.1 Hz, 1H, CH2), 2.58 (ddd, J = 13.4, 9.9, 5.6 Hz, 1H, CH2).
DOI: 10.14272/wnlqryagfimnbw-uhfffaoysa-m/chmo0000470
title: mass spectrometry (MS) ()
title: InChI=1S/C22H22N.ClH/c1-23-14-12-21(13-15-23)22-16-19-7-6-17-2-4-18(5-3-17)8-10-20(22)11-9-19;/h2-5,9,11-16H,6-8,10H2,1H3;1H/q+1;/p-1

description: dataset for mass spectrometry (MS) ESI-MS for [C22H22N]+: Calc. m/z = 300.1747, found m/z = 300.1744.
DOI: 10.14272/wnlqryagfimnbw-uhfffaoysa-m/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C22H22N.ClH/c1-23-14-12-21(13-15-23)22-16-19-7-6-17-2-4-18(5-3-17)8-10-20(22)11-9-19;/h2-5,9,11-16H,6-8,10H2,1H3;1H/q+1;/p-1

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (126 MHz, D2O, ppm) δ = 156.4 (1C, CAr), 144.6 (2C, CAr), 141.5 (1C, CAr), 140.6 (1C, CAr), 139.9 (1C, CAr), 138.8 (1C, CAr), 137.0 (1C, CAr), 135.9 (1C, CAr), 135.8 (1C, CAr), 133.7 (1C, CAr), 133.2 (1C, CAr), 132.4 (1C, CAr), 131.8 (1C, CAr), 129.5 (1C, CAr), 127.7 (2C, CAr), 47.2 (1C, CH3), 34.6 (1C, CH2), 34.3 (1C, CH2), 34.2 (1C, CH2), 33.4 (1C, CH2).
DOI: 10.14272/wnlqryagfimnbw-uhfffaoysa-m/chmo0000630
title: infrared absorption spectroscopy (IR) ()
title: InChI=1S/C22H22N.ClH/c1-23-14-12-21(13-15-23)22-16-19-7-6-17-2-4-18(5-3-17)8-10-20(22)11-9-19;/h2-5,9,11-16H,6-8,10H2,1H3;1H/q+1;/p-1

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 3370 (vs), 3360 (vs), 3116 (s), 3090 (s), 3016 (vs), 2923 (vs), 2895 (vs), 2852 (vs), 1637 (vs), 1591 (m), 1563 (m), 1516 (s), 1500 (m), 1460 (m), 1456 (m), 1197 (m), 847 (m), 718 (m), 640 (m), 486 (m) cm–1.
DOI: 10.14272/wnlqryagfimnbw-uhfffaoysa-m.1
title: C22H22ClN
title: InChI=1S/C22H22N.ClH/c1-23-14-12-21(13-15-23)22-16-19-7-6-17-2-4-18(5-3-17)8-10-20(22)11-9-19;/h2-5,9,11-16H,6-8,10H2,1H3;1H/q+1;/p-1

description: This is a physical chemical entity[CHEBI_24431] associated with a molecule[CHEBI_25367]. The molecule[CHEBI_25367] can be described by the following structural desciptors[cheminf_000085]: InChI descriptor[cheminf_000113]: InChI=1S/C22H22N.ClH/c1-23-14-12-21(13-15-23)22-16-19-7-6-17-2-4-18(5-3-17)8-10-20(22)11-9-19;/h2-5,9,11-16H,6-8,10H2,1H3;1H/q+1;/p-1, and canonical SMILES descriptor[cheminf_000007]: C[n+]1ccc(cc1)c1cc2ccc1CCc1ccc(CC2)cc1.[Cl-], and by the IUPAC name[cheminf_000107]: . The physical chemical entity[CHEBI_24431] has a component solvent[CHEBI_46787] which is described by the canonical SMILES descriptor[cheminf_000007]: The physical chemical entity[CHEBI_24431] has the following Sample ID as registered in the research data repository chemotion (www.chemotion-repository.net, https://doi.org/10.25504/FAIRsharing.iagXcR): CRS-33138 The physical chemical entity[CHEBI_24431] can be described by the physical descriptors [CHEMINF_000025]: Melting point descriptor[CHEMINF_000256]: 163.2 (°C) Boiling point descriptor[CHEMINF_000257]: Refractive index descriptor[CHEMINF_000253]: The physical chemical entity[CHEBI_24431] can be further described by the following assays[OBI:0000070][CHMO:0001133]: CHMO:0000593 | 1H nuclear magnetic resonance spectroscopy (1H NMR) CHMO:0000595 | 13C nuclear magnetic resonance spectroscopy (13C NMR) CHMO:0000630 | infrared absorption spectroscopy (IR) CHMO:0000470 | mass spectrometry (MS) The physical chemical entity[CHEBI_24431] was deposited to the Molecule Archive of the Karlsruhe Insitute of Technology (KIT) with the following Sample ID: Used ontologies: CHEBI - Chemical Entities of Biological Interest CHEMINF - chemical information ontology (information entities about chemical entities) CHMO - Chemical Methods Ontology OBI - Ontology for Biomedical Investigations
DOI: 10.6084/m9.figshare.23771127.v11
title: Population genomic analysis of Ellobium chinense

description: Mapped bam file and SNPs
DOI: 10.6084/m9.figshare.23771127.v12
title: Population genomic analysis of Ellobium chinense

description: Mapped bam file and SNPs
DOI: 10.6084/m9.figshare.23770569
title: Characterization of the iPhone LiDAR Sensor for Vibration Measurement and Modal Analysis - Dataset

description: Introduction <br> This dataset contains multiple test results conducted for the paper "Characterization of the iPhone LiDAR Sensor for Vibration Measurement and Modal Analysis". <br> Data Information <br> This dataset consists of displacement readings collected by a laser displacement transducer (L) and/or a light detection and ranging (LiDAR) sensor from an Apple iPhone 13 Pro. The LiDAR data was collected using two different apps: Stray Scanner (SS) returns full depth maps and PhyPhox collects depth at a specific coordinate. Two different structures were used as targets for the tests: a stiff plate, simulating rigid body movement, and a steel cantilever with four expected mode shapes within a low (&gt; 60 Hz) frequency range. Tests consist of the targets being static, oscillating harmonically in a single frequency, or randomly as a response of a pre-defined spectrum. The oscillation tests were carried out with the aid of an air-bearing shaker. <br> Further details <br> Additional test details can be found on the README files along with the dataset. A MATLAB function to load specific test cases is also provided.
DOI: 10.6084/m9.figshare.23789811
title: result-analysis.xlsx

description: <strong>Performance Analysis </strong> The metrics are used to assess the performance of the proposed method in the simulations: download cost, download time and packet redundancy or useful information transmission subject to realistic constraints regarding peer's demand, capacity and dynamicity. 1. <strong>Download cost:</strong> This metric refers to the effort of the client need to spend in the system to download the needed data. 2. <strong>Download time:</strong> This metric refers to the time needed for the client to download the entire content. 3. <strong>Packet redundancy:</strong> This metric is referred to transmit and obtain useful information to and from other peers in the network. 4. <strong>Failure rate:</strong> It is defined as the number of peers is not able to complete the downloading of entire content due to missing of some blocks in the network. <strong>Link Stress:</strong> It is the ratio between the number of packets sent over a link and the number of useful packets to maximum nodes transmitted over the link. For example, a stress of 4 respects to case where each packet is transmitted four times over a link. Effective utilization of available bandwidth is evaluated for peers to exchange the content.
DOI: 10.6084/m9.figshare.23789811.v1
title: result-analysis.xlsx

description: <strong>Performance Analysis </strong> The metrics are used to assess the performance of the proposed method in the simulations: download cost, download time and packet redundancy or useful information transmission subject to realistic constraints regarding peer's demand, capacity and dynamicity. 1. <strong>Download cost:</strong> This metric refers to the effort of the client need to spend in the system to download the needed data. 2. <strong>Download time:</strong> This metric refers to the time needed for the client to download the entire content. 3. <strong>Packet redundancy:</strong> This metric is referred to transmit and obtain useful information to and from other peers in the network. 4. <strong>Failure rate:</strong> It is defined as the number of peers is not able to complete the downloading of entire content due to missing of some blocks in the network. <strong>Link Stress:</strong> It is the ratio between the number of packets sent over a link and the number of useful packets to maximum nodes transmitted over the link. For example, a stress of 4 respects to case where each packet is transmitted four times over a link. Effective utilization of available bandwidth is evaluated for peers to exchange the content.
DOI: 10.5281/zenodo.8188443
title: AMR Files for FLAG from the Earnings Call Dataset

description: Parsed AMR annotation files for FLAG on the Earnings Call Dataset.
DOI: 10.5281/zenodo.8188442
title: AMR Files for FLAG from the Earnings Call Dataset

description: Parsed AMR annotation files for FLAG on the Earnings Call Dataset.
DOI: 10.6084/m9.figshare.21755882
title: Formative assessment COVID

description: Formative assessment and survey data
DOI: 10.6084/m9.figshare.21755882.v2
title: Formative assessment COVID

description: Formative assessment and survey data
DOI: 10.6084/m9.figshare.21755882.v1
title: Formative assessment COVID

description: Formative assessment and survey data
DOI: 10.5281/zenodo.8188554
title: Anonymised answers to the Delphi 2 survey

description: The MESOC project adopted a modified version of the Delphi methodology, based on two consecutive survey rounds involving experts from all over the world in late 2021 - early 2022 on the topic of assessing the societal value of culture, the results of which have been discussed in an expert workshop held in Athens in May 2022. The second survey went more in-depth into the topics of social impact evaluation of culture and into the typologies of transition variables and related proxies that may serve to detect the transformational changes induced by cultural projects and policies. The influence of these variables has been analysed through the lens of the three main dimensions of the MESOC project: Health and Wellbeing; People Engagement and Participation; Urban and Territorial Renovation. Invited experts were representatives of different groups that play an important role in the researched field, namely: Academics and consultants; Directors / managers of cultural projects; Public administration and policy makers, and private foundations supporting cultural projects aiming at social impact. The criteria for identifying the experts to be consulted were to have a sample composed by half academic and consultant specialists of culture and creativity and the other half by professionals from the cultural private and public sector. The second group was mainly chosen by the partners, starting from the participants in the first survey round, the results of which are also made available here on Zenodo. As a byproduct of the survey, an interactive set of reusable and empirically validated guidelines for academics and practitioners willing to replicate the MESOC approach on a different scale can be retrived online at: https://www.mesoc-project.eu/resources/methodological-guidelines/interactive
DOI: 10.5281/zenodo.8188555
title: Anonymised answers to the Delphi 2 survey

description: The MESOC project adopted a modified version of the Delphi methodology, based on two consecutive survey rounds involving experts from all over the world in late 2021 - early 2022 on the topic of assessing the societal value of culture, the results of which have been discussed in an expert workshop held in Athens in May 2022. The second survey went more in-depth into the topics of social impact evaluation of culture and into the typologies of transition variables and related proxies that may serve to detect the transformational changes induced by cultural projects and policies. The influence of these variables has been analysed through the lens of the three main dimensions of the MESOC project: Health and Wellbeing; People Engagement and Participation; Urban and Territorial Renovation. Invited experts were representatives of different groups that play an important role in the researched field, namely: Academics and consultants; Directors / managers of cultural projects; Public administration and policy makers, and private foundations supporting cultural projects aiming at social impact. The criteria for identifying the experts to be consulted were to have a sample composed by half academic and consultant specialists of culture and creativity and the other half by professionals from the cultural private and public sector. The second group was mainly chosen by the partners, starting from the participants in the first survey round, the results of which are also made available here on Zenodo. As a byproduct of the survey, an interactive set of reusable and empirically validated guidelines for academics and practitioners willing to replicate the MESOC approach on a different scale can be retrived online at: https://www.mesoc-project.eu/resources/methodological-guidelines/interactive
DOI: 10.5281/zenodo.7874661
title: Improving gross primary production estimation accuracy on the Qinghai-Tibet Plateau considering the effect of atmospheric CO2 fertilization

description: This GPP dataset was generated by the improved GPP estimation model which introduced atmospheric CO<sub>2</sub> fertilization effect and canopy-to-leaf CO<sub>2</sub> concentration gradients into the CASA model. The dataset was provided in TIF format at a month interval. The valid value ranges from 0 to 1000, and the background filled value is set to NoData. The scale factor of the data is 1. Each TIF file represents a month GPP at a daily cumulative value (unit: g C m<sup>-2</sup> month<sup>-1</sup>).
DOI: 10.5281/zenodo.7874660
title: Improving gross primary production estimation accuracy on the Qinghai-Tibet Plateau considering the effect of atmospheric CO2 fertilization

description: This GPP dataset was generated by the improved GPP estimation model which introduced atmospheric CO<sub>2</sub> fertilization effect and canopy-to-leaf CO<sub>2</sub> concentration gradients into the CASA model. The dataset was provided in TIF format at a month interval. The valid value ranges from 0 to 1000, and the background filled value is set to NoData. The scale factor of the data is 1. Each TIF file represents a month GPP at a daily cumulative value (unit: g C m<sup>-2</sup> month<sup>-1</sup>).
DOI: 10.14272/zjspyaoolgybti-vchvfrdlsa-l/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C32H26N2.2ClH/c1-3-29-4-2-6-31-14-12-26-17-21-34(22-18-26)24-28-9-7-27(8-10-28)23-33-19-15-25(16-20-33)11-13-30(5-1)32(29)31;;/h1-22H,23-24H2;2*1H/q+2;;/p-2/b13-11+,14-12+;;

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (126 MHz, D2O, ppm) δ = 153.9 (2C, CAr), 143.2 (2C, Cvinyl), 143.0 (4C, CAr), 138.3 (2C, CAr), 134.2 (1C, CAr), 133.8 (2C, CAr), 131.3 (2C, CAr), 130.0 (1C, CAr), 129.9 (4C, CAr), 129.1 (2C, CAr), 126.4 (2C, CAr), 124.1 (4C, CAr), 123.3 (2C, Cvinyl), 64.4 (2C, CH2).
DOI: 10.14272/zjspyaoolgybti-vchvfrdlsa-l.1
title: C32H26Cl2N2
title: InChI=1S/C32H26N2.2ClH/c1-3-29-4-2-6-31-14-12-26-17-21-34(22-18-26)24-28-9-7-27(8-10-28)23-33-19-15-25(16-20-33)11-13-30(5-1)32(29)31;;/h1-22H,23-24H2;2*1H/q+2;;/p-2/b13-11+,14-12+;;

description: This is a physical chemical entity[CHEBI_24431] associated with a molecule[CHEBI_25367]. The molecule[CHEBI_25367] can be described by the following structural desciptors[cheminf_000085]: InChI descriptor[cheminf_000113]: InChI=1S/C32H26N2.2ClH/c1-3-29-4-2-6-31-14-12-26-17-21-34(22-18-26)24-28-9-7-27(8-10-28)23-33-19-15-25(16-20-33)11-13-30(5-1)32(29)31;;/h1-22H,23-24H2;2*1H/q+2;;/p-2/b13-11+,14-12+;;, and canonical SMILES descriptor[cheminf_000007]: c1cc2/C=C/c3cc[n+](cc3)Cc3ccc(C[n+]4ccc(/C=C/c5c2c(c1)ccc5)cc4)cc3.[Cl-].[Cl-], and by the IUPAC name[cheminf_000107]: . The physical chemical entity[CHEBI_24431] has a component solvent[CHEBI_46787] which is described by the canonical SMILES descriptor[cheminf_000007]: The physical chemical entity[CHEBI_24431] has the following Sample ID as registered in the research data repository chemotion (www.chemotion-repository.net, https://doi.org/10.25504/FAIRsharing.iagXcR): CRS-35128 The physical chemical entity[CHEBI_24431] can be described by the physical descriptors [CHEMINF_000025]: Melting point descriptor[CHEMINF_000256]: 183.1 (°C) Boiling point descriptor[CHEMINF_000257]: Refractive index descriptor[CHEMINF_000253]: The physical chemical entity[CHEBI_24431] can be further described by the following assays[OBI:0000070][CHMO:0001133]: CHMO:0000593 | 1H nuclear magnetic resonance spectroscopy (1H NMR) CHMO:0000595 | 13C nuclear magnetic resonance spectroscopy (13C NMR) CHMO:0000630 | infrared absorption spectroscopy (IR) CHMO:0000470 | mass spectrometry (MS) The physical chemical entity[CHEBI_24431] was deposited to the Molecule Archive of the Karlsruhe Insitute of Technology (KIT) with the following Sample ID: Used ontologies: CHEBI - Chemical Entities of Biological Interest CHEMINF - chemical information ontology (information entities about chemical entities) CHMO - Chemical Methods Ontology OBI - Ontology for Biomedical Investigations
DOI: 10.14272/zjspyaoolgybti-vchvfrdlsa-l/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C32H26N2.2ClH/c1-3-29-4-2-6-31-14-12-26-17-21-34(22-18-26)24-28-9-7-27(8-10-28)23-33-19-15-25(16-20-33)11-13-30(5-1)32(29)31;;/h1-22H,23-24H2;2*1H/q+2;;/p-2/b13-11+,14-12+;;

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, D2O, ppm) δ = 8.54 (d, J = 6.6 Hz, 4H, HAr), 8.05 (d, J = 8.2 Hz, 2H, HAr), 8.02 (d, J = 15.7 Hz, 2H, Hvinyl), 7.82 (d, J = 7.2 Hz, 2H, HAr), 7.71 (d, J = 6.6 Hz, 4H, HAr), 7.64 (d, J = 7.8 Hz, 2H, HAr), 7.62 (s, 4H, HAr), 7.20 (d, J = 15.7 Hz, 2H, Hvinyl), 5.67 (s, 4H, CH2).
DOI: 10.14272/zjspyaoolgybti-vchvfrdlsa-l/chmo0000470
title: mass spectrometry (MS) ()
title: InChI=1S/C32H26N2.2ClH/c1-3-29-4-2-6-31-14-12-26-17-21-34(22-18-26)24-28-9-7-27(8-10-28)23-33-19-15-25(16-20-33)11-13-30(5-1)32(29)31;;/h1-22H,23-24H2;2*1H/q+2;;/p-2/b13-11+,14-12+;;

description: dataset for mass spectrometry (MS) ESI-MS for [C32H26N2]2+: Calc. m/z = 219.1043, found m/z = 219.1040.