cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/hs66b42sf7.1
title: Identifying transcription-factor combinations to modulate circadian rhythms by leveraging virtual knockouts on transcription networks

description: The mammalian circadian systems consist of indigenous, self-sustained 24-hours rhythm generators. They comprise many genes, molecules, and regulators. To decode their systematic controls, a robust computational approach, LogicTRN was employed. It integrates TF-occupancy and time-series gene-expression data as input. The model equations were constructed and solved to determine the transcriptional regulatory logics in the mouse transcriptome network. This hypothesizes to explore the underlying mechanisms of combinatorial transcriptional regulations for circadian rhythms in the mouse. We reconstructed the quantitative transcriptional-regulatory networks for circadian gene regulation at a dynamic scale. Transcriptional-simulations with virtually knocked-out TFs were performed to estimate their influence on networks. The potential TF/TF-combinations modulating the circadian rhythms were identified. Of them, CLOCK/CRY1 double knockout preserves the highest modulating capacity. Our quantitative framework offers a quick, robust, and physiologically relevant way to characterize the TF-combinations to modulate the circadian rhythms at a dynamic scale effectively.
DOI: 10.17632/hs66b42sf7.2
title: Identifying transcription-factor combinations to modulate circadian rhythms by leveraging virtual knockouts on transcription networks
DOI: 10.5281/zenodo.3713964
title: Automated Evolution of Feature Logging Statement Levels Using Git Histories and Degree of Interest

description: This data is double-blind.
DOI: 10.17632/ycfwwyyx7d.2
title: Active power load dataset

description: Historical load data at each hour of the day for the period from September-2018 to November-2018 was taken from 33/11 kV substation near Kakatiya University in Warangal. The time series data-set consists of a total of 2184 samples. It has been observed that load data distribution follows the normal distribution with a mean value of 6028 kW and a standard deviation of 1066 kW. Out of 2184 load samples in the specified time period, 95% of data points were falling between 5983 and 6072 kW..
DOI: 10.17632/3ywwnkhpxn.1
title: Improving Broadband Policy Design Using Market Data: A General Framework and an Application to Brazil

description: This dataset contains all databases and codes used in the paper "Improving Broadband Policy Design Using Market Data: A General Framework and an Application to Brazil".
DOI: 10.17632/935k9jnhsn.1
title: Data for: 3668705

description: Stata file
DOI: 10.17632/7fgg44snzd.1
title: Biological Evaluation of a Novel Bilirubin Adsorbent and Its Therapeutic Effect on Animal Models of Hyperbilirubinemia

description: Background: Hyperbilirubinemia caused severe hepatobiliary diseases with various causes, especially hepatic fibrosis and cirrhosis caused by end-stage hepatitis B and C. Plasma adsorption perfusion has an absolute advantage in treating patients with hyperbilirubinemia and liver failure. A safe and effective adsorbent in PP is the key to clear bilirubin. The adsorbent must have good blood compatibility and high adsorption rate for bilirubin. Methods and Results: In the early stage, the homopolymer predispersion system is used to improve the traditional suspension polymerization and obtain a new porous polymer adsorption resin ERM-0100. The experimental results showed that ERM-0100 exhibited high specific surface area and uniform particle size distribution. The results of biocompatibility tests, including cytotoxicity, acute toxicity test, intradermal reaction, sensitization reaction, and hemolysis test, suggested that ERM-0100 met the requirements of GB/T 16886.5-2017 “Biological Evaluation of Medical Devices” and had a good biological phase. Good biocompatibility laid the foundation for subsequent determination of bilirubin adsorption in vivo in ERM-0100. This work used the experimental pure Bama Xiang pig to establish a high-bilirubin animal model via the surgical and drug methods. As such, the stability of the animal model, the safety of ERM-0100 in vivo, and the in vivo effectiveness of the resin material were evaluated. Conclusion: In this study, Bama pigs were used to establish a hyperbilirubinemia animal model using surgical methods to evaluate the biocompatibility and the effectiveness of ERM-0100 , which may reduce domestic patient's financial burden.
DOI: 10.17632/8j793f24bb.2
title: Histone deacetylase 3 couples mitochondria to drive inflammation by configuring fatty acid oxidation
DOI: 10.17632/6h2hh5gxxv.1
title: Akhtar Parvez

description: This dataset is on Covid-19 pertaining to India
DOI: 10.17632/9g2jzvr6ss.1
title: SELF-DIFFUSION OF Fe AND Pt IN L10-ORDERED FePt: MOLECULAR DYNAMICS SIMULATION

description: Supplementary and raw data to the article entitled “Self-diffusion of Fe and Pt in L10-ordered FePt: molecular dynamics simulation” submitted to Computational Materials Science.
DOI: 10.17632/vdy2nksk4h.1
title: Extreme wind speed (Kara Sea)

description: This dataset contains wind speed values from ERA5 Reanalysis (obtained from zonal and meridional components of wind speed at 10 meters) for the Kara Sea area for the period 1979-2019. The “real” summer for Arctic is very short, and we used here the data only for July and August. Each dat-file in Archive (total 609 files) is for each grid cell according to grid step of ERA5 (0.25°×0.25°). In order to apply statistical approaches, we composed our data according to the independence condition. Each data sample includes only independent extreme values. We selected the maximum wind speeds from 3-day intervals in wind speed data for each grid cell. Our samples were divided into sea ice and open water conditions, because in some regions, the share of days with ice cover reached 40-50%. As a criterion for this division, we used the concentration threshold of 15%: the days with a sea ice concentration higher than 15% were considered as sea ice conditions and lower than 15% meant open water. We used only open water samples, and in this Archive, we present only these data. These data can be used for statistical analysis.
DOI: 10.17632/4ypj4xxp68.5
title: The description of the model for "Molecular mechanisms of action determine inhibition of paroxysmal depolarizing shifts by NMDA receptor antagonists in rat cortical neurons"

description: The program code, executable files and full list of model parameters and settings used for the modelling of the paroxizmal depolorizing shift in the pyramydal cells and fast-spiking interneurons in prefrontal cortex
DOI: 10.17632/c37bvvxp3z.8
title: ESI and MSI data sets2

description: Check the referred paper : https://link.springer.com/article/10.1007/s10509-017-3131-y
DOI: 10.17632/vdfzk3tjtm.2
title: Polarized Light Microscopy for depiction of myelinated nerve fibers

description: A tool to evaluate polarized light microscopy images of brain tissue obtained at different polarimeter angles in order to depict myelinated nerve fibers with information on fiber direction and inclination.
DOI: 10.17632/95bkkgcvnn.1
title: Domestic Material Consumption - Europe (NUTS 2) regions

description: The dataset provides regional (NUTS 2) estimates for the DMC indicator from 2006 to 2015. The provision of granular data on material consumption represents a critical input for comparative research conducted at regional level. It can potentially advance the general understanding of metabolic systems and their influencing factors at local levels, supporting the design of place-based policies and strategies in support of sustainable resource use. The methodology is based on a three-steps econometric model, including: (1) global model specification, (2) optimization of parameters, and (3) regional extrapolation. Step (1) focuses on the identification of the best regression model describing DMC patterns across European countries. The main output of this first task is the estimation of the global parameters (i.e. the regression coefficients observed between DMC and its explanatory variables at European level). Step (2) calibrates the model in order to reflect the specific socio-metabolic regimes of the different countries. This calibration is implemented by an optimization algorithm that automatically adjusts the estimated parameters based on the specific characteristics of each country. This generates a set of country-specific parameters. Finally, in Step (3) we extrapolate the regional figures for DMC by applying the country-specific parameters on the selected explicative variables, measured at the regional level. Even though the method relies on the assumption of same model specification across scales – similarly to other top-down approaches –, it offers two important advantages on how territorial heterogeneity is considered in the model. First it considers the issue of national regimes dependency, and second it avoids approximation based on a single proxy factor by accounting for multiple correlations.. A detailed description of the methodology is provided in https://doi.org/10.1111/jiec.13000.
DOI: 10.34740/kaggle/dsv/1404307
title: Country Data
DOI: 10.5517/ccdc.csd.cc23rtwl
title: CCDC 1959320: Experimental Crystal Structure Determination

description: Related Article: Jindou Yang, Mi Sook Seo, Kyung Ha Kim, Yong‐Min Lee, Shunichi Fukuzumi, Jason Shearer, Wonwoo Nam|2020|Angew.Chem.,Int.Ed.|59|13581|doi:10.1002/anie.202005091
DOI: 10.5517/ccdc.csd.cc23y7w6
title: CCDC 1964528: Experimental Crystal Structure Determination

description: Related Article: wei yuan, Chuan He|2019|CSD Communication|||
description: Related Article: Delong Mu,  Wei Yuan,  Shuyou Chen,  Na Wang,  Bo Yang,  Lijun You,  Bing Zu,  Peiyuan Yu,  Chuan He|2020|J.Am.Chem.Soc.|142|13459|doi:10.1021/jacs.0c04863
DOI: 10.5517/ccdc.csd.cc23y86k
title: CCDC 1964538: Experimental Crystal Structure Determination

description: Related Article: Delong Mu,  Wei Yuan,  Shuyou Chen,  Na Wang,  Bo Yang,  Lijun You,  Bing Zu,  Peiyuan Yu,  Chuan He|2020|J.Am.Chem.Soc.|142|13459|doi:10.1021/jacs.0c04863
description: Related Article: wei yuan, Chuan He|2019|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc247z5k
title: CCDC 1973868: Experimental Crystal Structure Determination

description: Related Article: Jindou Yang, Mi Sook Seo, Kyung Ha Kim, Yong‐Min Lee, Shunichi Fukuzumi, Jason Shearer, Wonwoo Nam|2020|Angew.Chem.,Int.Ed.|59|13581|doi:10.1002/anie.202005091
DOI: 10.14272/otdujvqmqbnmcd-uhfffaoysa-n.1
title: 4-(4-carboxyphenyl)-3-nitrobenzoic acid
title: InChI=1S/C14H9NO6/c16-13(17)9-3-1-8(2-4-9)11-6-5-10(14(18)19)7-12(11)15(20)21/h1-7H,(H,16,17)(H,18,19)

description: This dataset contains experimental data from a sample (4-(4-carboxyphenyl)-3-nitrobenzoic acid, InChI=1S/C14H9NO6/c16-13(17)9-3-1-8(2-4-9)11-6-5-10(14(18)19)7-12(11)15(20)21/h1-7H,(H,16,17)(H,18,19)). 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) high-resolution mass spectrometry (HRMS)
DOI: 10.14272/otdujvqmqbnmcd-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (4-(4-carboxyphenyl)-3-nitrobenzoic acid)
title: InChI=1S/C14H9NO6/c16-13(17)9-3-1-8(2-4-9)11-6-5-10(14(18)19)7-12(11)15(20)21/h1-7H,(H,16,17)(H,18,19)

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, DMSO-d6, ppm) δ = 13.44 (bs, 2H, CO2H), 8.47 (d, 1H, J = 1.5 Hz, CH), 8.28 (dd, 1H, J = 8.0 Hz, J = 1.5 Hz, CH), 8.04–8.02 (m, 2H, CH), 7.73 (d, 1H, J = 8.0 Hz, CH), 7.53–7.51 (m, 2H, CH). Impurities: the spectrum contains small impurities.
DOI: 10.14272/otdujvqmqbnmcd-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (4-(4-carboxyphenyl)-3-nitrobenzoic acid)
title: InChI=1S/C14H9NO6/c16-13(17)9-3-1-8(2-4-9)11-6-5-10(14(18)19)7-12(11)15(20)21/h1-7H,(H,16,17)(H,18,19)

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (125 MHz, DMSO-d6, ppm) δ = 166.9 (CO2H), 165.3 (CO2H), 148.5 (Cq), 140.7 (Cq), 138.3 (Cq), 133.3 (CH), 132.6 (CH), 131.8 (Cq), 130.9 (Cq), 129.7 (2C, CH), 128.1 (2C, CH), 125.0 (CH).
DOI: 10.14272/otdujvqmqbnmcd-uhfffaoysa-n/chmo0000470
title: mass spectrometry (MS) (4-(4-carboxyphenyl)-3-nitrobenzoic acid)
title: InChI=1S/C14H9NO6/c16-13(17)9-3-1-8(2-4-9)11-6-5-10(14(18)19)7-12(11)15(20)21/h1-7H,(H,16,17)(H,18,19)

description: dataset for mass spectrometry (MS) EI (m/z, 70 eV, 220 °C): 287 (70) [M]+, 270 (34) [M–OH]+, 242 (37) [M–CO2H]+.
DOI: 10.14272/otdujvqmqbnmcd-uhfffaoysa-n/chmo0000498
title: high-resolution mass spectrometry (HRMS) (4-(4-carboxyphenyl)-3-nitrobenzoic acid)
title: InChI=1S/C14H9NO6/c16-13(17)9-3-1-8(2-4-9)11-6-5-10(14(18)19)7-12(11)15(20)21/h1-7H,(H,16,17)(H,18,19)

description: dataset for high-resolution mass spectrometry (HRMS) HRMS–EI (m/z): [M]+ calcd for C14H9NO6, 287.0424; found, 287.0422.
DOI: 10.25810/zwvy-tv09
title: FIRED CONUS: Daily

description:         This is the daily level polygons for the FIRED events product for the coterminous United States. It is derived from the MODIS MCD64A1 burned area product (see https://lpdaac.usgs.gov/products/mcd64a1v006/ for more details). The MCD64A1 is a monthly raster grid of estimated burned dates. We converted these rasters into events by stacking the entire time series into a spatial-temporal data cube, then used an algorithm to assign event identification numbers to pixels that fit into the same 3-dimensional spatial temporal window. The primary benefit to this dataset over others is the ability to calculate fire spread rate. For each of these products (FIRED CONUS: events and FIRED CONUS: daily) the event identification numbers are the same, but the event-level product has only single polygons for the entire event, while the daily product has separate polygons for each date. See the accompanying metadata files for the statistics provided by each data set. See the associated paper (currently in review, preprint DOI: https://doi.org/10.32942/osf.io/nkzpg) for more details on the methods and more.
DOI: 10.6078/m7nv9gc1
title: Late Chalcolithic Archaeobotanical Remains at Çadır Höyük, Turkey
DOI: 10.14272/hhucqmbkbnwoly-uhfffaoysa-n.2
title: C24H20N6O4
title: InChI=1S/C24H20N6O4/c1-33-23(31)17-7-3-15(4-8-17)21-11-20(14-28-30-26)22(12-19(21)13-27-29-25)16-5-9-18(10-6-16)24(32)34-2/h3-12H,13-14H2,1-2H3

description: This dataset contains experimental data from a sample (methyl 4-[2,5-bis(azidomethyl)-4-(4-methoxycarbonylphenyl)phenyl]benzoate, InChI=1S/C24H20N6O4/c1-33-23(31)17-7-3-15(4-8-17)21-11-20(14-28-30-26)22(12-19(21)13-27-29-25)16-5-9-18(10-6-16)24(32)34-2/h3-12H,13-14H2,1-2H3). 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) high-resolution mass spectrometry (HRMS) mass spectrometry (MS)
DOI: 10.14272/hhucqmbkbnwoly-uhfffaoysa-n/chmo0000470
title: mass spectrometry (MS) (methyl 4-[2,5-bis(azidomethyl)-4-(4-methoxycarbonylphenyl)phenyl]benzoate)
title: InChI=1S/C24H20N6O4/c1-33-23(31)17-7-3-15(4-8-17)21-11-20(14-28-30-26)22(12-19(21)13-27-29-25)16-5-9-18(10-6-16)24(32)34-2/h3-12H,13-14H2,1-2H3

description: dataset for mass spectrometry (MS) EI (m/z, 70 eV, 210 °C): 456 (1) [M]+, 428 (63) [M–N2]+, 399 (100) [M–CO2Me]+.
DOI: 10.14272/hhucqmbkbnwoly-uhfffaoysa-n/chmo0000498
title: high-resolution mass spectrometry (HRMS) (methyl 4-[2,5-bis(azidomethyl)-4-(4-methoxycarbonylphenyl)phenyl]benzoate)
title: InChI=1S/C24H20N6O4/c1-33-23(31)17-7-3-15(4-8-17)21-11-20(14-28-30-26)22(12-19(21)13-27-29-25)16-5-9-18(10-6-16)24(32)34-2/h3-12H,13-14H2,1-2H3

description: dataset for high-resolution mass spectrometry (HRMS) HRMS–EI (m/z): [M]+ calcd for C24H20N6O4, 456.1548; found, 456.1546.
DOI: 10.14272/hhucqmbkbnwoly-uhfffaoysa-n/chmo0000470.1
title: mass spectrometry (MS) (methyl 4-[2,5-bis(azidomethyl)-4-(4-methoxycarbonylphenyl)phenyl]benzoate)
title: InChI=1S/C24H20N6O4/c1-33-23(31)17-7-3-15(4-8-17)21-11-20(14-28-30-26)22(12-19(21)13-27-29-25)16-5-9-18(10-6-16)24(32)34-2/h3-12H,13-14H2,1-2H3

description: dataset for mass spectrometry (MS) EI (m/z, 70 eV, 210 °C): 456 (1) [M]+, 428 (63) [M–N2]+, 427 (54), 400 (33), 399 (100) [M–CO2CH3]+, 386 (28), 385 (48), 341 (56), 326 (37), 314 (32), 43 (91).
DOI: 10.14272/hhucqmbkbnwoly-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (methyl 4-[2,5-bis(azidomethyl)-4-(4-methoxycarbonylphenyl)phenyl]benzoate)
title: InChI=1S/C24H20N6O4/c1-33-23(31)17-7-3-15(4-8-17)21-11-20(14-28-30-26)22(12-19(21)13-27-29-25)16-5-9-18(10-6-16)24(32)34-2/h3-12H,13-14H2,1-2H3

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, CDCl3, ppm) δ = 8.16–8.15 (m, 4H, CH), 7.50–7.48 (m, 4H, CH), 7.43 (s, 2H, CH), 4.33 (s, 4H, CH2N3), 3.97 (s, 6H, CO2CH3).
DOI: 10.14272/hhucqmbkbnwoly-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (methyl 4-[2,5-bis(azidomethyl)-4-(4-methoxycarbonylphenyl)phenyl]benzoate)
title: InChI=1S/C24H20N6O4/c1-33-23(31)17-7-3-15(4-8-17)21-11-20(14-28-30-26)22(12-19(21)13-27-29-25)16-5-9-18(10-6-16)24(32)34-2/h3-12H,13-14H2,1-2H3

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (125 MHz, ppm) δ = 166.9 (2C, CO2CH3), 144.0 (2C, Cq), 141.2 (2C, Cq), 133.3 (2C, Cq), 131.6 (2C, CH), 130.0 (4C, CH), 129.9 (2C, Cq), 129.4 (4C, CH), 52.4 (2C, CO2CH3), 52.3 (2C, CH2N3).
DOI: 10.14272/vypzghxepuxqiy-uhfffaoysa-n.3
title: 4-[2,5-bis(azidomethyl)-4-(4-carboxyphenyl)phenyl]benzoic acid
title: InChI=1S/C22H16N6O4/c23-27-25-11-17-10-20(14-3-7-16(8-4-14)22(31)32)18(12-26-28-24)9-19(17)13-1-5-15(6-2-13)21(29)30/h1-10H,11-12H2,(H,29,30)(H,31,32)

description: This dataset contains experimental data from a sample (4-[2,5-bis(azidomethyl)-4-(4-carboxyphenyl)phenyl]benzoic acid, InChI=1S/C22H16N6O4/c23-27-25-11-17-10-20(14-3-7-16(8-4-14)22(31)32)18(12-26-28-24)9-19(17)13-1-5-15(6-2-13)21(29)30/h1-10H,11-12H2,(H,29,30)(H,31,32)). 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) high-resolution mass spectrometry (HRMS) mass spectrometry (MS)
DOI: 10.14272/vypzghxepuxqiy-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (4-[2,5-bis(azidomethyl)-4-(4-carboxyphenyl)phenyl]benzoic acid)
title: InChI=1S/C22H16N6O4/c23-27-25-11-17-10-20(14-3-7-16(8-4-14)22(31)32)18(12-26-28-24)9-19(17)13-1-5-15(6-2-13)21(29)30/h1-10H,11-12H2,(H,29,30)(H,31,32)

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, DMSO-d6, ppm) δ = 13.10 (bs, 2H, CO2H), 8.07–8.06 (m, 4H, CH), 7.58–7.57 (m, 4H, CH), 7.55 (s, 2H, CH), 4.50 (s, 4H, CH2N3).
DOI: 10.14272/vypzghxepuxqiy-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (4-[2,5-bis(azidomethyl)-4-(4-carboxyphenyl)phenyl]benzoic acid)
title: InChI=1S/C22H16N6O4/c23-27-25-11-17-10-20(14-3-7-16(8-4-14)22(31)32)18(12-26-28-24)9-19(17)13-1-5-15(6-2-13)21(29)30/h1-10H,11-12H2,(H,29,30)(H,31,32)

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (125 MHz, DMSO-d6, ppm) δ = 167.1 (2C, CO2H), 143.4 (2C, Cq), 140.4 (2C, Cq), 133.2 (2C, Cq), 131.8 (2C, CH), 130.1 (2C, Cq), 129.5 (4C, CH), 129.2 (4C, CH), 51.2 (2C, CH2N3).
DOI: 10.14272/vypzghxepuxqiy-uhfffaoysa-n/chmo0000470
title: mass spectrometry (MS) (4-[2,5-bis(azidomethyl)-4-(4-carboxyphenyl)phenyl]benzoic acid)
title: InChI=1S/C22H16N6O4/c23-27-25-11-17-10-20(14-3-7-16(8-4-14)22(31)32)18(12-26-28-24)9-19(17)13-1-5-15(6-2-13)21(29)30/h1-10H,11-12H2,(H,29,30)(H,31,32)

description: dataset for mass spectrometry (MS) EI (m/z, 70 eV, 140 °C): 428 (26) [M]+, 399 [M–H–N2]+, 386 (18) [M–N3]+, 372 (11) [M–N4]+, 341 (21) [M–CO2H–N3]+.
DOI: 10.14272/vypzghxepuxqiy-uhfffaoysa-n/chmo0000498
title: high-resolution mass spectrometry (HRMS) (4-[2,5-bis(azidomethyl)-4-(4-carboxyphenyl)phenyl]benzoic acid)
title: InChI=1S/C22H16N6O4/c23-27-25-11-17-10-20(14-3-7-16(8-4-14)22(31)32)18(12-26-28-24)9-19(17)13-1-5-15(6-2-13)21(29)30/h1-10H,11-12H2,(H,29,30)(H,31,32)

description: dataset for high-resolution mass spectrometry (HRMS) HRMS–EI (m/z): [M]+ calcd for C22H16N6O4, 428.1237; found, 428.1233.
DOI: 10.14272/vypzghxepuxqiy-uhfffaoysa-n/chmo0000470.1
title: mass spectrometry (MS) (4-[2,5-bis(azidomethyl)-4-(4-carboxyphenyl)phenyl]benzoic acid)
title: InChI=1S/C22H16N6O4/c23-27-25-11-17-10-20(14-3-7-16(8-4-14)22(31)32)18(12-26-28-24)9-19(17)13-1-5-15(6-2-13)21(29)30/h1-10H,11-12H2,(H,29,30)(H,31,32)

description: dataset for mass spectrometry (MS) EI (m/z, 70 eV, 140 °C): 428 (3) [M]+.
DOI: 10.5281/zenodo.3975400
title: Data for manuscript "Suppression of CO2 outgassing by gas bubbles under a hurricane"

description: Matlab data files containing data used to plot figures in the manuscript "Suppression of CO2 outgassing by gas bubbles under a hurricane"
DOI: 10.5281/zenodo.3975399
title: Data for manuscript "Suppression of CO2 outgassing by gas bubbles under a hurricane"

description: Matlab data files containing data used to plot figures in the manuscript "Suppression of CO2 outgassing by gas bubbles under a hurricane"
DOI: 10.14272/vbrxsywnzwfbaq-uhfffaoysa-n.2
title: C22H22O4S2
title: InChI=1S/C22H22O4S2/c1-5-25-21(23)19-11-17(13(3)27-19)15-7-9-16(10-8-15)18-12-20(28-14(18)4)22(24)26-6-2/h7-12H,5-6H2,1-4H3

description: This dataset contains experimental data from a sample (InChI=1S/C22H22O4S2/c1-5-25-21(23)19-11-17(13(3)27-19)15-7-9-16(10-8-15)18-12-20(28-14(18)4)22(24)26-6-2/h7-12H,5-6H2,1-4H3). 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)
DOI: 10.14272/vbrxsywnzwfbaq-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C22H22O4S2/c1-5-25-21(23)19-11-17(13(3)27-19)15-7-9-16(10-8-15)18-12-20(28-14(18)4)22(24)26-6-2/h7-12H,5-6H2,1-4H3

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, CDCl3, ppm) δ = 7.79 (s, 2H, C3H), 7.44 (s, 4H, CH), 4.36 (q, 4H, J = 7.0 Hz, OCH2CH3), 2.58 (s, 6H, ArCH3), 1.39 (t, 6H, J = 7.0 Hz, OCH2CH3). Impurities: the spectrum contains small impurities.
DOI: 10.14272/vbrxsywnzwfbaq-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C22H22O4S2/c1-5-25-21(23)19-11-17(13(3)27-19)15-7-9-16(10-8-15)18-12-20(28-14(18)4)22(24)26-6-2/h7-12H,5-6H2,1-4H3

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (125 MHz, CDCl3, ppm) δ = 162.2 (2C, CO2Et), 142.2 (2C, Cq), 139.2 (2C, Cq), 135.1 (2C, C3H), 134.5 (2C, Cq), 129.7 (2C, Cq), 128.7 (4C, CH), 61.0 (2C, OCH2CH3), 14.9 (2C, ArCH3), 14.4 (2C, OCH2CH3).
DOI: 10.14272/vbrxsywnzwfbaq-uhfffaoysa-n/chmo0000470
title: mass spectrometry (MS) ()
title: InChI=1S/C22H22O4S2/c1-5-25-21(23)19-11-17(13(3)27-19)15-7-9-16(10-8-15)18-12-20(28-14(18)4)22(24)26-6-2/h7-12H,5-6H2,1-4H3

description: dataset for mass spectrometry (MS) EI (m/z, 70 eV, 100 °C): 414 (10) [M]+. HRMS–EI (m/z): [M]+ calcd for C22H22O4S2, 414.0960; found, 414.0956.
DOI: 10.14272/vbrxsywnzwfbaq-uhfffaoysa-n/chmo0000630
title: infrared absorption spectroscopy (IR) ()
title: InChI=1S/C22H22O4S2/c1-5-25-21(23)19-11-17(13(3)27-19)15-7-9-16(10-8-15)18-12-20(28-14(18)4)22(24)26-6-2/h7-12H,5-6H2,1-4H3

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 3074, 3061, 2993, 2957, 2947, 2924, 2901, 2869, 2853, 1706, 1553, 1518, 1475, 1451, 1443, 1409, 1389, 1379, 1362, 1352, 1272, 1240, 1148, 1133, 1114, 1082, 1022, 1012, 990, 974, 905, 878, 867, 847, 830, 810, 800, 748, 708, 700, 674, 657, 644, 610, 583, 565, 532, 480, 425, 408, 387 cm–1.