cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/z4py-t931
title: Windows and Artificial Light Sources

description: The dataset comprises a diverse collection of images featuring windows alongside various artificial light sources, such as bulbs, LEDs, and tube lights. Each image captures the interplay of natural and artificial illumination, offering a rich visual spectrum that encompasses different lighting scenarios. This compilation is invaluable for applications ranging from architectural design and interior decor to computer vision and image processing. Researchers and developers can leverage this dataset to train and enhance algorithms for recognizing and analyzing lighting conditions within diverse environments. With over a hundred images, the dataset provides a robust foundation for exploring the nuanced relationships between windows and artificial lighting, contributing to advancements in both aesthetic and technological domains.
DOI: 10.6084/m9.figshare.24625263
title: Virtual autopsy using 7T MRI vs classic fetal autopsy.xlsx

description: <b>Introduction:</b> Studies that analyses the diagnostic utility and clinic potential of whole-body fetal imaging using ultra-high magnetic are lacking. This study aimed to determine the diagnostic accuracy of virtual autopsy using ultra-high field magnetic resonance imaging at 7 T vs classic autopsy as the reference in the assessment of small second-trimester fetuses. Additionally, we tested a shorter T2‐weighted imaging protocol.<b>Material and methods:</b> Thirty consecutive fetuses (13–19 weeks of gestation, weighing 16–300 g) resulting from spontaneous and therapeutic terminations of pregnancy were considered. After fixation in 10% formalin solution (48 h to 1 week), all fetuses were scanned using a two‐dimensional turbo high-resolution multi-slice relaxation time T2‐weighted imaging protocol followed by an invasive autopsy. The diagnostic accuracy of virtual autopsy vs classic autopsy was calculated for 990 anatomic structures (30 fetuses × 33 items). Sensitivity, specificity, positive predictive value, negative predictive value, and Cohen’s k coefficient of agreement with their 95% confidence intervals, as well as the McNemar test, were used to define the agreement of the two diagnostic methods, overall, by anatomic segment (cerebral, pulmonary, cardiovascular, renal, facial, and skeletal), and across three gestational age intervals (13–14, 15–16, and 17–19 weeks).<b>Results</b>: Compared with classic autopsy, virtual autopsy had a sensitivity of 92.04% [95% confidence interval 85.42–96.29] and a specificity of 97.87% [94.64–99.42], with a positive predictive value of 96.30% [90.78–98.56] and a negative predictive value of 95.34% [91.61–97.45], achieving a diagnostic accuracy for detecting structural abnormalities in second-trimester fetuses of 95.68% [92.73–97.68]. Cohen’s k was 0.907. The diagnostic accuracy of the virtual autopsy at 7 T for malformed fetuses was superior for analyzing the cerebral system in small fetuses with pronounced autolysis; was equivalent to classic autopsy when analyzing pulmonary, cardiovascular, and renal systems; and was inferior for evaluating fetal intestines. The diagnostic sensitivity of virtual autopsy at 7 T for describing structural abnormalities increased with fetal gestational age.<b>Conclusions:</b> Virtual autopsy using magnetic resonance imaging at 7 T and a turbo high-resolution multi-slice relaxation time T2‐weighted imaging protocol is a feasible postmortem diagnostic tool to identify structural anomalies in fetuses.
DOI: 10.6084/m9.figshare.24625263.v1
title: Virtual autopsy using 7T MRI vs classic fetal autopsy.xlsx

description: <b>Introduction:</b> Studies that analyses the diagnostic utility and clinic potential of whole-body fetal imaging using ultra-high magnetic are lacking. This study aimed to determine the diagnostic accuracy of virtual autopsy using ultra-high field magnetic resonance imaging at 7 T vs classic autopsy as the reference in the assessment of small second-trimester fetuses. Additionally, we tested a shorter T2‐weighted imaging protocol.<b>Material and methods:</b> Thirty consecutive fetuses (13–19 weeks of gestation, weighing 16–300 g) resulting from spontaneous and therapeutic terminations of pregnancy were considered. After fixation in 10% formalin solution (48 h to 1 week), all fetuses were scanned using a two‐dimensional turbo high-resolution multi-slice relaxation time T2‐weighted imaging protocol followed by an invasive autopsy. The diagnostic accuracy of virtual autopsy vs classic autopsy was calculated for 990 anatomic structures (30 fetuses × 33 items). Sensitivity, specificity, positive predictive value, negative predictive value, and Cohen’s k coefficient of agreement with their 95% confidence intervals, as well as the McNemar test, were used to define the agreement of the two diagnostic methods, overall, by anatomic segment (cerebral, pulmonary, cardiovascular, renal, facial, and skeletal), and across three gestational age intervals (13–14, 15–16, and 17–19 weeks).<b>Results</b>: Compared with classic autopsy, virtual autopsy had a sensitivity of 92.04% [95% confidence interval 85.42–96.29] and a specificity of 97.87% [94.64–99.42], with a positive predictive value of 96.30% [90.78–98.56] and a negative predictive value of 95.34% [91.61–97.45], achieving a diagnostic accuracy for detecting structural abnormalities in second-trimester fetuses of 95.68% [92.73–97.68]. Cohen’s k was 0.907. The diagnostic accuracy of the virtual autopsy at 7 T for malformed fetuses was superior for analyzing the cerebral system in small fetuses with pronounced autolysis; was equivalent to classic autopsy when analyzing pulmonary, cardiovascular, and renal systems; and was inferior for evaluating fetal intestines. The diagnostic sensitivity of virtual autopsy at 7 T for describing structural abnormalities increased with fetal gestational age.<b>Conclusions:</b> Virtual autopsy using magnetic resonance imaging at 7 T and a turbo high-resolution multi-slice relaxation time T2‐weighted imaging protocol is a feasible postmortem diagnostic tool to identify structural anomalies in fetuses.
DOI: 10.5281/zenodo.10202027
title: egregia_menziesii_zanfona_1.fasta.gz

description: egregia_menziesii_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.10202028
title: egregia_menziesii_zanfona_1.fasta.gz

description: egregia_menziesii_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.8116595
title: Sideband thermometry of ion crystals

description: Experimental data for thermometry measurements with a linear 4-ion crystal as well as a planar 19-ion crystal.
DOI: 10.5281/zenodo.8116596
title: Sideband thermometry of ion crystals

description: Experimental data for thermometry measurements with a linear 4-ion crystal as well as a planar 19-ion crystal.
DOI: 10.5281/zenodo.6107721
title: Magnetic Resonance Imaging Copper Sulfate Dataset

description: The data has been produced by the Institut für Mikrostrukturtechnik (IMT) at Karlsruher Institut für Technologie (KIT). This data set represents the DICOM (Digital Imaging and Communications in Medicine) files, which belong to one MRI (Magnetic Resonance Imaging) study and contain a series of images that have been measured with different protocols. The samples shown by the images are tubes, which contain different concentrations of CuSO4. The DICOM file headers have metadata tags, which embody additional information about the study and the particular series.
DOI: 10.5281/zenodo.6107720
title: Magnetic Resonance Imaging Copper Sulfate Dataset

description: The data has been produced by the Institut für Mikrostrukturtechnik (IMT) at Karlsruher Institut für Technologie (KIT). This dataset represents the DICOM (Digital Imaging and Communications in Medicine) files, which belong to one MRI (Magnetic Resonance Imaging) study and contain a series of images that have been measured with different protocols. The samples shown by the images are tubes, which contain different concentrations of CuSO4. The DICOM file headers have metadata tags, which embody additional information about the study and the particular series.
DOI: 10.5281/zenodo.7319761
title: Magnetic Resonance Imaging Copper Sulfate Dataset

description: The data has been produced by the Institut für Mikrostrukturtechnik (IMT) at Karlsruher Institut für Technologie (KIT). This dataset represents the DICOM (Digital Imaging and Communications in Medicine) files, which belong to one MRI (Magnetic Resonance Imaging) study and contain a series of images that have been measured with different protocols. The samples shown by the images are tubes, which contain different concentrations of CuSO4. The DICOM file headers have metadata tags, which embody additional information about the study and the particular series.
description: {"references": ["https://metarepo.nffa.eu/api/v1/metadata/5bc69277-711c-4eb0-937d-d81c59dbbe36?version=1"]}
DOI: 10.5281/zenodo.10198815
title: A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers

description: Trained models and basecalled reads.
DOI: 10.5281/zenodo.10199807
title: A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers

description: Trained models and basecalled reads.
DOI: 10.5281/zenodo.7413315
title: A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers

description: Trained models and basecalled reads.
DOI: 10.5281/zenodo.7413316
title: A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers

description: Trained models and basecalled reads.
DOI: 10.5281/zenodo.10202065
title: A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers

description: Trained models and basecalled reads.
DOI: 10.5281/zenodo.10202070
title: cedrela_odorata_zanfona_1.fasta.gz

description: cedrela_odorata_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.10202069
title: cedrela_odorata_zanfona_1.fasta.gz

description: cedrela_odorata_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.10202078
title: gambusia_yucatana_zanfona_1.fasta.gz

description: gambusia_yucatana_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.10202077
title: gambusia_yucatana_zanfona_1.fasta.gz

description: gambusia_yucatana_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.10202086
title: eurytoma_californica_zanfona_1.fasta.gz

description: eurytoma_californica_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.10202087
title: eurytoma_californica_zanfona_1.fasta.gz

description: eurytoma_californica_zanfona_1.fasta.gz
DOI: 10.6084/m9.figshare.24625332
title: Male Social Information Use Datasheet

description: Dataset for male social information use
DOI: 10.6084/m9.figshare.24625332.v1
title: Male Social Information Use Datasheet

description: Dataset for male social information use
DOI: 10.6084/m9.figshare.24625335
title: Female Social Information Use 1

description: Dataset for the first set of female social information use experiements
DOI: 10.6084/m9.figshare.24625335.v1
title: Female Social Information Use 1

description: Dataset for the first set of female social information use experiements
DOI: 10.6084/m9.figshare.24625338
title: Female Social Information Use 2

description: Dataset for female social information use for the second set of experiments
DOI: 10.6084/m9.figshare.24625338.v1
title: Female Social Information Use 2

description: Dataset for female social information use for the second set of experiments
DOI: 10.25345/c53j39b66
title: MassIVE MSV000093475 - GNPS_Aviwe Alternaria alternata P02PL2
title: Untargeted metabolomics of Alternaria alternata P02PL2, Matandela Aviwe MSc 2023
DOI: 10.6084/m9.figshare.24625302
title: Iniquitate datasets and processed files

description: These are the resources (datasets and already processed integration files) necessary to rerun the Iniquitate experimental results, as indicated through the GitHub directory https://github.com/hsmaan/Iniquitate. The pre-print associated with this work is available at https://www.biorxiv.org/content/10.1101/2022.10.06.511156v3
DOI: 10.5281/zenodo.10202139
title: heliconius_charithonia_zanfona_1.fasta.gz

description: heliconius_charithonia_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.10202140
title: heliconius_charithonia_zanfona_1.fasta.gz

description: heliconius_charithonia_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.10198866
title: Climate Security on social media: raw and processed data from Twitter

description: This dataset reflects climate security dialogues on Twitter, from January 2014 to May 2023.
description: This work was carried out with support from the CGIAR Initiative on Climate Resilience, ClimBeR, and the CGIAR Initiative on Fragility, Conflict, and Migration. We would like to thank all funders who supported this research through their contributions to the CGIAR Trust Fund: https://www.cgiar.org/funders/.
DOI: 10.6084/m9.figshare.24625350
title: Prior features for PriLer models

description: Prior features used to build PriLer gene expression models
DOI: 10.5281/zenodo.10202146
title: malus_domestica_zanfona_1.fasta.gz

description: malus_domestica_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.10202145
title: malus_domestica_zanfona_1.fasta.gz

description: malus_domestica_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.10202161
title: mareca_americana_zanfona_1.fasta.gz

description: mareca_americana_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.10202162
title: mareca_americana_zanfona_1.fasta.gz

description: mareca_americana_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.10202105
title: Scientometric Indexes of Scientific Journals

description: Scientometric data from 62,856 journals consolidated from Scopus, SJC, Diamond Journals, ISSN database, Google Scholar and Brazilian QUALIS (2022). Its purpose is to support researchers who want to analyze and compare various scientometric attributes and also the economic model used by scientific journals around the world.
CSV UTF-8 File, separated by semicolon.
Metadata:
ISSN-L: Journal Identified used by ISSN
ISSN: Secondary Journal identifier (used for Print or other medium versions);
Name is in the journal origin language;
"ASJC" is the Knowledge Area Code based on All Science Journal Category used by Citescore/Scopus;
"Citescore" is based on 2022 Scopus;
"Google H5" are based on 2020 database;
"Qualis" is the Brazilian score calculated for the 2017-2021 quadrienal;
Country Name (País) is in English merged from all databases;
"Modelo" can have 3 values: D-Diamond Journals (No money involved), T-Closed (You have to pay to access), A-APC (You have to pay to publish);
This is a working in progress and we intend to add more atributes and fill some gaps on knowledge areas field (ASJC) and other empty attributes.
DOI: 10.5281/zenodo.10202106
title: Scientometric Indexes of Scientific Journals

description: Scientometric data from 62,856 journals consolidated from Scopus, SJC, Diamond Journals, ISSN database, Google Scholar and Brazilian QUALIS (2022). Its purpose is to support researchers who want to analyze and compare various scientometric attributes and also the economic model used by scientific journals around the world.
CSV UTF-8 File, separated by semicolon.
Metadata:
ISSN-L: Journal Identified used by ISSN
ISSN: Secondary Journal identifier (used for Print or other medium versions);
Name is in the journal origin language;
"ASJC" is the Knowledge Area Code based on All Science Journal Category used by Citescore/Scopus;
"Citescore" is based on 2022 Scopus;
"Google H5" are based on 2020 database;
"Qualis" is the Brazilian score calculated for the 2017-2021 quadrienal;
Country Name (País) is in English merged from all databases;
"Modelo" can have 3 values: D-Diamond Journals (No money involved), T-Closed (You have to pay to access), A-APC (You have to pay to publish);
This is a working in progress and we intend to add more atributes and fill some gaps on knowledge areas field (ASJC) and other empty attributes.
DOI: 10.34740/kaggle/dsv/7038579
title: Top Spotify Songs in 73 Countries (Daily Updated)
DOI: 10.34740/kaggle/dsv/7038586
title: Forex Exchange Rates Since 2004 (Updated Daily)
DOI: 10.34740/kaggle/dsv/7038612
title: Trending Youtube Video Statistics (113 Countries)
DOI: 10.57992/nmrxiv.p21
title: Tetrahydro protoberberine derivatives
DOI: 10.57992/nmrxiv.p21.s102
title: Propyl ethoxy ethyl Des Br
DOI: 10.57992/nmrxiv.p21.s102.d561
title: 5
DOI: 10.57992/nmrxiv.p21.s102.d562
title: 2
DOI: 10.57992/nmrxiv.p21.s102.d563
title: 6
DOI: 10.57992/nmrxiv.p21.s102.d564
title: 1
DOI: 10.57992/nmrxiv.p21.s102.d565
title: 4
DOI: 10.57992/nmrxiv.p21.s102.d566
title: 3
DOI: 10.57992/nmrxiv.p21.s103
title: Hexyl propyl des-Br
DOI: 10.57992/nmrxiv.p21.s103.d567
title: 1
DOI: 10.57992/nmrxiv.p21.s103.d568
title: 2
DOI: 10.57992/nmrxiv.p21.s104
title: Propyl Pentyl final dried data.topspin
DOI: 10.57992/nmrxiv.p21.s104.d569
title: 4
DOI: 10.57992/nmrxiv.p21.s104.d570
title: 2
DOI: 10.57992/nmrxiv.p21.s104.d571
title: 1
DOI: 10.57992/nmrxiv.p21.s104.d572
title: 3
DOI: 10.57992/nmrxiv.p21.s105
title: Hexyl Ethoxy ethyl
DOI: 10.57992/nmrxiv.p21.s105.d573
title: 2
DOI: 10.57992/nmrxiv.p21.s105.d574
title: 1
DOI: 10.57992/nmrxiv.p21.s105.d575
title: 3
DOI: 10.57992/nmrxiv.p21.s106
title: Hexyl Ethoxy Ethyl PF
DOI: 10.57992/nmrxiv.p21.s106.d576
title: 2
DOI: 10.57992/nmrxiv.p21.s107
title: Butyl Amide
DOI: 10.57992/nmrxiv.p21.s107.d577
title: 1
DOI: 10.57992/nmrxiv.p21.s108
title: Propyl Ethyl Prefinal
DOI: 10.57992/nmrxiv.p21.s108.d578
title: 1
DOI: 10.57992/nmrxiv.p21.s108.d579
title: 3
DOI: 10.57992/nmrxiv.p21.s108.d580
title: 2
DOI: 10.57992/nmrxiv.p21.s108.d581
title: 4
DOI: 10.57992/nmrxiv.p21.s109
title: Propyl Propyl final dried data.topspin
DOI: 10.57992/nmrxiv.p21.s109.d582
title: 4
DOI: 10.57992/nmrxiv.p21.s109.d583
title: 3
DOI: 10.57992/nmrxiv.p21.s109.d584
title: 2
DOI: 10.57992/nmrxiv.p21.s110
title: Propyl Propyl final dried data.topspin
DOI: 10.57992/nmrxiv.p21.s110.d585
title: 1
DOI: 10.57992/nmrxiv.p21.s111
title: OH ACID
DOI: 10.57992/nmrxiv.p21.s111.d586
title: 1
DOI: 10.57992/nmrxiv.p21.s112
title: propyl PS data
DOI: 10.57992/nmrxiv.p21.s112.d587
title: 5
DOI: 10.57992/nmrxiv.p21.s112.d588
title: 4
DOI: 10.57992/nmrxiv.p21.s112.d589
title: 2
DOI: 10.57992/nmrxiv.p21.s112.d590
title: 1
DOI: 10.57992/nmrxiv.p21.s112.d591
title: 7
DOI: 10.57992/nmrxiv.p21.s112.d592
title: 6
DOI: 10.57992/nmrxiv.p21.s112.d593
title: 3
DOI: 10.57992/nmrxiv.p21.s113
title: Hexyl PS
DOI: 10.57992/nmrxiv.p21.s113.d594
title: 10
DOI: 10.57992/nmrxiv.p21.s113.d595
title: 8
DOI: 10.57992/nmrxiv.p21.s113.d596
title: 9
DOI: 10.57992/nmrxiv.p21.s113.d597
title: 11
DOI: 10.57992/nmrxiv.p21.s113.d598
title: 7
DOI: 10.57992/nmrxiv.p21.s113.d599
title: 4
DOI: 10.57992/nmrxiv.p21.s113.d600
title: 15
DOI: 10.57992/nmrxiv.p21.s113.d601
title: 3
DOI: 10.57992/nmrxiv.p21.s113.d602
title: 13
DOI: 10.57992/nmrxiv.p21.s113.d603
title: 12
DOI: 10.57992/nmrxiv.p21.s113.d604
title: 2
DOI: 10.57992/nmrxiv.p21.s113.d605
title: 16
DOI: 10.57992/nmrxiv.p21.s113.d606
title: 6
DOI: 10.57992/nmrxiv.p21.s113.d607
title: 1
DOI: 10.57992/nmrxiv.p21.s113.d608
title: 14
DOI: 10.57992/nmrxiv.p21.s113.d609
title: 5
DOI: 10.57992/nmrxiv.p21.s114
title: Hexyl amine pure
DOI: 10.57992/nmrxiv.p21.s114.d610
title: 1
DOI: 10.57992/nmrxiv.p21.s115
title: butyl PC success
DOI: 10.57992/nmrxiv.p21.s115.d611
title: 3
DOI: 10.57992/nmrxiv.p21.s116
title: Propyl Pentyl Des Br.topspin
DOI: 10.57992/nmrxiv.p21.s116.d612
title: 2
DOI: 10.57992/nmrxiv.p21.s116.d613
title: 3
DOI: 10.57992/nmrxiv.p21.s116.d614
title: 1
DOI: 10.57992/nmrxiv.p21.s117
title: hexyl pentyl
DOI: 10.57992/nmrxiv.p21.s117.d615
title: 3
DOI: 10.57992/nmrxiv.p21.s117.d616
title: 2
DOI: 10.57992/nmrxiv.p21.s118
title: Hexyl Ethyl
DOI: 10.57992/nmrxiv.p21.s118.d617
title: 1
DOI: 10.57992/nmrxiv.p21.s118.d618
title: 3
DOI: 10.57992/nmrxiv.p21.s118.d619
title: 2
DOI: 10.57992/nmrxiv.p21.s119
title: Hexyl pentyl prefinal
DOI: 10.57992/nmrxiv.p21.s119.d620
title: 1
DOI: 10.57992/nmrxiv.p21.s120
title: OPr-Obn bromo Acid pure
DOI: 10.57992/nmrxiv.p21.s120.d621
title: 1
DOI: 10.57992/nmrxiv.p21.s121
title: Propyl Pict Pingler
DOI: 10.57992/nmrxiv.p21.s121.d622
title: 5
DOI: 10.57992/nmrxiv.p21.s121.d623
title: 1
DOI: 10.57992/nmrxiv.p21.s121.d624
title: 9
DOI: 10.57992/nmrxiv.p21.s121.d625
title: 3
DOI: 10.57992/nmrxiv.p21.s121.d626
title: 2
DOI: 10.57992/nmrxiv.p21.s121.d627
title: 6
DOI: 10.57992/nmrxiv.p21.s121.d628
title: 8
DOI: 10.57992/nmrxiv.p21.s121.d629
title: 4
DOI: 10.57992/nmrxiv.p21.s121.d630
title: 7
DOI: 10.57992/nmrxiv.p21.s122
title: TBDPS acid OH amine amide 2
DOI: 10.57992/nmrxiv.p21.s122.d631
title: 1
DOI: 10.57992/nmrxiv.p21.s123
title: Propyl Propyl Pre final
DOI: 10.57992/nmrxiv.p21.s123.d632
title: 1
DOI: 10.57992/nmrxiv.p21.s123.d633
title: 2
DOI: 10.57992/nmrxiv.p21.s124
title: Hex-But-Des_Br
DOI: 10.57992/nmrxiv.p21.s124.d634
title: 1
DOI: 10.20783/dias.31
title: Ocean Renalysis
title: DIAS_ODAPv3.1

description: The 4D-VAR assimilation system used here is the same as in Masuda et al. [2003] covering the global ocean. The OGCM is version 3 of the GFDL Modular Ocean Model (MOM; Pacanowski and Griffies, 1999), which is equipped with several sophisticated parameterization schemes, for example, nonlocal K Profile Parameterization (Large et al., 1994) for mixed layer physics, Gent and McWilliams's scheme (Gent and McWiiliams, 1990) for isopycnal mixing, and quicker advection scheme (Leonald, 1979). The horizontal resolution is 1in both latitude and longitude, with 36 vertical levels spaced from 10m near the sea surface to 400m at the bottom. This model has good capability to reproduce ocean circulation processes and is expected to form a platform suitable for the use of the 4D-VAR adjoint model. The assimilated elements in this study are the temperature and salinity from the World Ocean Database 1998 (for climatologies) and the FNMOC, OI SST values, and sea-surface dynamic-height anomaly data compiled by AVISO. All observational data were averaged onto 1 degree by 1 degree bins and then compiled as series of 10-day means for the surface data and monthly means for the subsurface data.
DOI: 10.57992/nmrxiv.p21.s124.d635
title: 2
DOI: 10.57992/nmrxiv.p21.s125
title: propyl_Noyori
DOI: 10.57992/nmrxiv.p21.s125.d636
title: 1
DOI: 10.57992/nmrxiv.p21.s126
title: TBDPS acid Propyl Amine Amide
DOI: 10.57992/nmrxiv.p21.s126.d637
title: 1
DOI: 10.57992/nmrxiv.p21.s127
title: Propyl pentyl Pre-final
DOI: 10.57992/nmrxiv.p21.s127.d638
title: 1
DOI: 10.57992/nmrxiv.p21.s127.d639
title: 2
DOI: 10.57992/nmrxiv.p21.s128
title: Propyl ethyl final dried data.topspin
DOI: 10.57992/nmrxiv.p21.s128.d640
title: 1
DOI: 10.57992/nmrxiv.p21.s128.d641
title: 3
DOI: 10.57992/nmrxiv.p21.s129
title: Propyl cyclopentyl Pre-Final
DOI: 10.57992/nmrxiv.p21.s129.d642
title: 1
DOI: 10.57992/nmrxiv.p21.s129.d643
title: 2
DOI: 10.57992/nmrxiv.p21.s130
title: Propyl Ethoxy Ethyl Prefinal
DOI: 10.57992/nmrxiv.p21.s130.d644
title: 2
DOI: 10.57992/nmrxiv.p21.s130.d645
title: 1
DOI: 10.57992/nmrxiv.p21.s131
title: Propyl propyl Des Br.topspin
DOI: 10.57992/nmrxiv.p21.s131.d646
title: 2
DOI: 10.57992/nmrxiv.p21.s131.d647
title: 1
DOI: 10.57992/nmrxiv.p21.s132
title: TBS Bn Amine
DOI: 10.57992/nmrxiv.p21.s132.d648
title: 1
DOI: 10.57992/nmrxiv.p21.s133
title: OH amine TBDPS acid amibe
DOI: 10.57992/nmrxiv.p21.s133.d649
title: 1
DOI: 10.57992/nmrxiv.p21.s134
title: OH-Amine
DOI: 10.57992/nmrxiv.p21.s134.d650
title: 1
DOI: 10.57992/nmrxiv.p21.s134.d651
title: 4
DOI: 10.57992/nmrxiv.p21.s134.d652
title: 3
DOI: 10.57992/nmrxiv.p21.s135
title: Hexylm Hexyl Des Br
DOI: 10.57992/nmrxiv.p21.s135.d653
title: 2
DOI: 10.57992/nmrxiv.p21.s135.d654
title: 3
DOI: 10.57992/nmrxiv.p21.s136
title: propyl hexyl final data.topspin
DOI: 10.57992/nmrxiv.p21.s136.d655
title: 1
DOI: 10.57992/nmrxiv.p21.s137
title: Butyl Amide
DOI: 10.57992/nmrxiv.p21.s137.d656
title: 4
DOI: 10.57992/nmrxiv.p21.s137.d657
title: 2
DOI: 10.57992/nmrxiv.p21.s137.d658
title: 5
DOI: 10.57992/nmrxiv.p21.s137.d659
title: 3
DOI: 10.57992/nmrxiv.p21.s138
title: OH, OTBDPS, DiOBn amide
DOI: 10.57992/nmrxiv.p21.s138.d660
title: 1
DOI: 10.57992/nmrxiv.p21.s139
title: Propyl ethyl prefinal 2
DOI: 10.57992/nmrxiv.p21.s139.d661
title: 1
DOI: 10.57992/nmrxiv.p21.s140
title: Hexyl Pentyl des-Br
DOI: 10.57992/nmrxiv.p21.s140.d662
title: 1
DOI: 10.57992/nmrxiv.p21.s140.d663
title: 2
DOI: 10.57992/nmrxiv.p21.s141
title: TBDPS-OH amide
DOI: 10.57992/nmrxiv.p21.s141.d664
title: 1