cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5258/soton/d1222
title: Dataset to support Chandra observations of Jupiter's X-ray auroral emission during Juno apojove 2017

description: Dataset supports the paper 'Chandra observations of Jupiter's X-ray auroral emission during Juno apojove 2017' published in Journal of Geophysical Research: Planets (Special edition journal, Midway through Juno).
DOI: 10.14272/odjohiwklopsff-uhfffaoysa-n.1
title: pyrido[3,2-a]phenazine
title: InChI=1S/C15H9N3/c1-2-6-13-12(5-1)17-14-8-7-11-10(15(14)18-13)4-3-9-16-11/h1-9H

description: This dataset contains experimental data from a sample (pyrido[3,2-a]phenazine, InChI=1S/C15H9N3/c1-2-6-13-12(5-1)17-14-8-7-11-10(15(14)18-13)4-3-9-16-11/h1-9H). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) process
DOI: 10.14272/odjohiwklopsff-uhfffaoysa-n/bfo0000015
title: process (pyrido[3,2-a]phenazine)
title: InChI=1S/C15H9N3/c1-2-6-13-12(5-1)17-14-8-7-11-10(15(14)18-13)4-3-9-16-11/h1-9H

description: dataset for process Additional information to facilitate the assignment of signals to structure.
DOI: 10.14272/odjohiwklopsff-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (pyrido[3,2-a]phenazine)
title: InChI=1S/C15H9N3/c1-2-6-13-12(5-1)17-14-8-7-11-10(15(14)18-13)4-3-9-16-11/h1-9H

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, DMSO-d6, 25 °C): δ [ppm] = 9.51 (dd, J = 8.2, 1.7 Hz, 1H, H14), 9.12 (dd, J = 4.5, 1.7 Hz, 1H, H16), 8.39–8.29 (m, 2H, H1+H4), 8.23 (s, 2H, H11+H12), 8.05–8.00 (m, 2H, H2+H3), 7.86 (dd, J = 8.2, 4.5 Hz, 1H, H15).
DOI: 10.14272/odjohiwklopsff-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (pyrido[3,2-a]phenazine)
title: InChI=1S/C15H9N3/c1-2-6-13-12(5-1)17-14-8-7-11-10(15(14)18-13)4-3-9-16-11/h1-9H

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C{1H} NMR (101 MHz, DMSO-d6, 25 °C): δ [ppm] = 152.3 (C16), 149.3 (C18), 142.5 (C9), 142.5 (C10), 141.3 (C6), 140.9 (C5), 134.2 (C12), 132.5 (C14), 131.2 (C2), 131.1 (C3), 130.8 (C11), 129.3 (C1), 129.2 (C4), 126.0 (C17), 123.1 (C15).
DOI: 10.14272/sexrckwgfsxuoo-uhfffaoysa-n.1
title: benzo[a]phenazine
title: InChI=1S/C16H10N2/c1-2-6-12-11(5-1)9-10-15-16(12)18-14-8-4-3-7-13(14)17-15/h1-10H

description: This dataset contains experimental data from a sample (benzo[a]phenazine, InChI=1S/C16H10N2/c1-2-6-12-11(5-1)9-10-15-16(12)18-14-8-4-3-7-13(14)17-15/h1-10H). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) process
DOI: 10.14272/sexrckwgfsxuoo-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (benzo[a]phenazine)
title: InChI=1S/C16H10N2/c1-2-6-12-11(5-1)9-10-15-16(12)18-14-8-4-3-7-13(14)17-15/h1-10H

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, DMSO-d6, 25 °C): δ [ppm] = 9.29–9.23 (m, 1H, H15), 8.38–8.31 (m, 1H, H1), 8.30–8.25 (m, 1H, H4), 8.20 (d, J = 9.3 Hz, 1H, H11), 8.11–8.06 (m, 1H, H16), 8.02–7.93 (m, 3H, H2+H3+H12), 7.90–7.82 (m, 2H, H13+H14).
DOI: 10.14272/sexrckwgfsxuoo-uhfffaoysa-n/bfo0000015
title: process (benzo[a]phenazine)
title: InChI=1S/C16H10N2/c1-2-6-12-11(5-1)9-10-15-16(12)18-14-8-4-3-7-13(14)17-15/h1-10H

description: dataset for process Additional information to facilitate the assignment of signals to structure.
DOI: 10.14272/sexrckwgfsxuoo-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (benzo[a]phenazine)
title: InChI=1S/C16H10N2/c1-2-6-12-11(5-1)9-10-15-16(12)18-14-8-4-3-7-13(14)17-15/h1-10H

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C{1H} NMR (101 MHz, DMSO-d6, 25 °C): δ [ppm] = 143.1 (C10), 142.2 (C9), 141.7 (C6), 141.1 (C5), 133.4 (C11), 132.9 (C17), 130.5 (C2), 130.5 (C3), 130.2 (C18), 130.1 (C13), 129.2 (C1), 128.9 (C4), 128.5 (C16), 128.1 (C14), 126.8 (C12), 124.6 (C15).
DOI: 10.14272/xqwhzhodenelcj-uhfffaoysa-n.1
title: 2-[(dimethylamino)methyl]aniline
title: InChI=1S/C9H14N2/c1-11(2)7-8-5-3-4-6-9(8)10/h3-6H,7,10H2,1-2H3

description: This dataset contains experimental data from a sample (2-[(dimethylamino)methyl]aniline, InChI=1S/C9H14N2/c1-11(2)7-8-5-3-4-6-9(8)10/h3-6H,7,10H2,1-2H3). The datasets from the following experiments are available: 13C nuclear magnetic resonance spectroscopy (13C NMR) 1H nuclear magnetic resonance spectroscopy (1H NMR) process
DOI: 10.14272/xqwhzhodenelcj-uhfffaoysa-n/bfo0000015
title: process (2-[(dimethylamino)methyl]aniline)
title: InChI=1S/C9H14N2/c1-11(2)7-8-5-3-4-6-9(8)10/h3-6H,7,10H2,1-2H3

description: dataset for process Additional information to facilitate the assignment of signals to structure.
DOI: 10.14272/xqwhzhodenelcj-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (2-[(dimethylamino)methyl]aniline)
title: InChI=1S/C9H14N2/c1-11(2)7-8-5-3-4-6-9(8)10/h3-6H,7,10H2,1-2H3

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, Chloroform-d, 25 °C): δ [ppm] = 7.10 (td, J = 7.6, 1.5 Hz, 1H, H4), 7.01–6.97 (m, 1H, H6), 6.70–6.63 (m, 2H, H3+5), 4.62 (br s, 2H, NH2), 3.42 (s, 2H, H7), 2.20 (s, 6H, H8).
DOI: 10.14272/xqwhzhodenelcj-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (2-[(dimethylamino)methyl]aniline)
title: InChI=1S/C9H14N2/c1-11(2)7-8-5-3-4-6-9(8)10/h3-6H,7,10H2,1-2H3

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C{1H} NMR (101 MHz, Chloroform-d, 25 °C): δ [ppm] = 147.0 (C2), 130.2 (C6), 128.3 (C4), 123.3 (C1), 117.5 (C5), 115.4 (C3), 63.4 (C7), 45.0 (2C, C8).
DOI: 10.14272/fcamupirwknasd-uhfffaoysa-n.1
title: N,N-dimethyl-1-(2-nitrophenyl)methanamine
title: InChI=1S/C9H12N2O2/c1-10(2)7-8-5-3-4-6-9(8)11(12)13/h3-6H,7H2,1-2H3

description: This dataset contains experimental data from a sample (N,N-dimethyl-1-(2-nitrophenyl)methanamine, InChI=1S/C9H12N2O2/c1-10(2)7-8-5-3-4-6-9(8)11(12)13/h3-6H,7H2,1-2H3). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) process
DOI: 10.14272/fcamupirwknasd-uhfffaoysa-n/bfo0000015
title: process (N,N-dimethyl-1-(2-nitrophenyl)methanamine)
title: InChI=1S/C9H12N2O2/c1-10(2)7-8-5-3-4-6-9(8)11(12)13/h3-6H,7H2,1-2H3

description: dataset for process Additional information to facilitate the assignment of signals to structure
DOI: 10.14272/fcamupirwknasd-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (N,N-dimethyl-1-(2-nitrophenyl)methanamine)
title: InChI=1S/C9H12N2O2/c1-10(2)7-8-5-3-4-6-9(8)11(12)13/h3-6H,7H2,1-2H3

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, Chloroform-d, 25 °C): δ [ppm] = 7.83 (dd, J = 8.1, 1.2 Hz, 1H, H3), 7.63–7.59 (m, 1H, H5), 7.54 (td, J = 7.5, 1.3 Hz, 1H, H4), 7.41–7.36 (m, 1H, H6), 3.71 (s, 2H, H7), 2.22 (s, 6H, H8).
DOI: 10.14272/fcamupirwknasd-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (N,N-dimethyl-1-(2-nitrophenyl)methanamine)
title: InChI=1S/C9H12N2O2/c1-10(2)7-8-5-3-4-6-9(8)11(12)13/h3-6H,7H2,1-2H3

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C{1H} NMR (101 MHz, Chloroform-d, 25 °C): δ [ppm] = 149.8 (C2), 134.6 (C1), 132.6 (C4), 131.1 (C5), 127.9 (C6), 124.5 (C3), 60.4 (C7), 45.8 (2C, C8).
DOI: 10.5281/zenodo.3689736
title: Reference Windfarm database CNk8 90

description: Dataset for TotalControl reference windfarm database simulation of a conventionally neutral boundary layer flow with 90 degree inflow wind direction angle (Casename CNk8 90) Included Python files for loading and visualizing the data. Use the plot_*.py files. Further information, including description of the case and dataset can be found in the deliverable report at: https://cordis.europa.eu/project/id/727680/results "Database for reference wind farms part 2: windfarm simulations"
DOI: 10.5258/soton/d1253
title: Data for: An Analysis of Railway Track Behaviour based on Distributed Optical Fibre Acoustic Sensing

description: This dataset supports the publication: Milne, David et al (2020). An Analysis of Railway Track Behaviour based on Distributed Optical Fibre Acoustic Sensing. Mechanical Systems and Signal Processing.
DOI: 10.5281/zenodo.3691671
title: Smart meters data involved in Spanish Pilot

description: File containing the smart meters data involved in the project to forecasting system, distribution management system and optimiz&lt;acion to interacta with Invade platform
DOI: 10.5281/zenodo.3691670
title: Smart meters data involved in Spanish Pilot

description: File containing the smart meters data involved in the project to forecasting system, distribution management system and optimiz&lt;acion to interacta with Invade platform
DOI: 10.18716/nmrshiftdb2/75024
title: NMR data for InChI=1S/C21H22O4/c1-13(12-14(2)22)21(20(24)25-3)11-10-17-16-7-5-4-6-15(16)8-9-18(17)19(21)23/h4-9,13H,10-12H2,1-3H3
DOI: 10.6085/aa/rkpx00_xxxibtnxmbr21_20110509.40.1
title: (:unkn)
DOI: 10.18716/nmrshiftdb2/75026
title: NMR data for 4,4-dimethyl-1,3-oxazolidine
DOI: 10.17632/h2vsp2t84r.1
title: Efficient implementation of the continuous-time interaction-expansion quantum Monte Carlo method

description: We describe an open-source implementation of the continuous-time interaction-expansion quantum Monte Carlo method for cluster-type impurity models with onsite Coulomb interactions and complex Weiss functions. The code is based on the ALPS libraries.
DOI: 10.17632/dbwzdkttkb.1
title: Brownian Disks Lab: Simulating time-lapse microscopy experiments for exploring microrheology techniques and colloidal interactions

description: Brownian Disks Lab (BDL) is a Java-based application for the real-time generation and visualization of the motion of two-dimensional Brownian disks using Brownian Dynamics (BD) simulations. This software is designed to emulate time-lapse microscopy experiments of colloidal fluids in quasi-2D situations, such as sedimented layers of particles, optical trap confinement, or fluid interfaces. Microrheology of bio-inspired fluids through optical-based techniques such as videomicroscopy is a classic tool for obtaining the mechanical properties and molecular behavior of these materials. The results obtained by microrheology notably depend of the time-lapse value of the videomicroscopy setup, therefore, a tool to test the influence of the lack of statistics by simulating Brownian objects in experimental-like situations is needed. We simulate a colloidal fluid by using Brownian Dynamics (BD) simulations, where the particles are subjected to different external applied forces and inter-particle interactions. This software has been tested for the analysis of the microrheological consequences of attractive forces between particles [1], the influence of image analysis on experimental microrheological results [2], and to explore experimental diffusion with optical tweezers [3]. The output results of BDL are directly compatible with the format used by standard microrheological algorithms [4]. In a context of microrheology of complex bio-inspired fluids, we use this tool here to study if the lack of statistics may influence the observed potential of a bead trapped by optical tweezers.
DOI: 10.17632/3h6xffk9h6.1
title: CALANIE: Anisotropic elastic correction to the total energy, to mitigate the effect of periodic boundary conditions

description: CALANIE (CALculation of ANIsotropic Elastic energy) computer program evaluates the elastic interaction correction to the total energy of a localized object, for example a defect in a material simulated using an ab initio or molecular statics approach, resulting from the use of periodic boundary conditions. The correction, computed using a fully elastically anisotropic Green’s function formalism, arises from the elastic interaction between a defect and its own periodically translated images. The long-range field of elastic displacements produced by the defect is described in the elastic dipole approximation. Applications of the method are illustrated by two case studies, one involving an ab initio investigation of point defects and vacancy migration in FCC gold, and another a molecular statics simulation of a dislocation loop. We explore the convergence of the method as a function of the simulation cell size, and note the significance of taking into account the elastic correction in the limit where the size of the defect is comparable with the size of the simulation cell.
DOI: 10.18716/nmrshiftdb2/75022
title: NMR data for methyl (2S,5R)-5-hydroxy-5-methyl-6-oxo-2-phenylpiperidine-2-carboxylate
DOI: 10.17632/zp9gskrbvg.1
title: GPU accelerated simulation of channeling radiation of relativistic particles

description: In this paper we describe and demonstrate a C++ code written to determine the trajectory of particles traversing oriented single crystals and a CUDA code written to evaluate the radiation spectra from charged particles with arbitrary trajectories. The CUDA/C++ code can evaluate both classical and quantum mechanical radiation spectra for spin 0 and 1/2 particles. We include multiple Coulomb scattering and energy loss due to radiation emission which produces radiation spectra in agreement with experimental spectra for both positrons and electrons. We also demonstrate how GPUs can be used to speed up calculations by several orders of magnitude. This will allow research groups with limited funding or sparse access to super computers to do numerical calculations as if it were a super computer. We show that one Titan V GPU can replace up to 100 Xeon 36 core CPUs running in parallel. We also show that choosing a GPU for a specific job will have great impact on the performance, as some GPUs have better double precision performance than others.
DOI: 10.21227/fg0d-ev55
title: Open Repository for the Evaluation of Ransomware Detection Tools

description: This repository contains the results of running more than 70 samples of ransomware, from different families, dating since 2015. It contains the network traffic (DNS and TCP) and the Input/Output (I/O) operations generated by the malware while encrypting a network shared directory. These data are contained in three files for each ransomware sample: one with the information from the DNS requests, other with the TCP connections another one containing the I/O operations. This information can be useful for testing new and old ransomware detection tools and compare their results.
DOI: 10.6085/aa/rkpx00_xxxibtnxmbr22_20110616.40.1
title: (:unkn)
DOI: 10.17632/pkb252vtps.1
title: Phase-field study of IMC growth in Sn–Cu/Cu solder joints including elastoplastic effects -- data sets and codes

description: The main phase-field matlab code and accompanying set-up and postprocessing matlab codes used for the work presented in "Phase-field study of IMC growth in Sn–Cu/Cu solder joints including elastoplastic effects", A. Durga, P. Wollants, N. Moelans, Acta Materialia, 88, P241-258, 2020. Each folder contains all the programs and the obtained simulation results for one of the loading cases, as mentioned in the paper. The m-files sim_solderxxxxx.m and invoer_solderxxxxx.m contain all the information needed to start-up the simulations. All the input data and cases considered are listed in the article. The m-file multi_comp_interf_xxxxx.m is the main function containing the implementation of all equations. The m-file width_layer.m derives the width as a function of time from the result files and stores this information in width_time.mat file. The m-file postprocess_final_100000s.m is used to generate the figures used in the article and along with the accompanying files getlinfit_2m.m, getlinfit.m to obtain the growth coefficients ‘k’ which are reported in the article. For plotting profiles of elastic energy density, von Mises stress, etc. at a certain time step, an example file ‘postprocess_elasticenergydensity.m’ is provided in folder ‘AppTensY_EqEig’, which plots the elastic energy density profile for ‘AppTensY_EqEig’ case. The m-file ParabolicGPlotting.m is used to generate the plots of the parabolic Gibbs energy density functions used in the article. The figures used in the article are provided in the ‘Figures’ folder in both .fig and .eps formats.
DOI: 10.17632/5bdw8jcs3w.1
title: Integrative Engineering Project Modules - Learning Outcomes

description: List of learning outcomes for Engineering project modules that are intended to be integrative in nature.
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20060811.40.1
title: (:unkn)
DOI: 10.17632/8nz52pmttw.1
title: HVOF Residual Stress

description: The data present the residual stresses of thermally sprayed Inconel coatings on Stainless Steel substrates.
DOI: 10.5281/zenodo.3691680
title: Cycle-free Subclass Subsumption Relations of the LOD Cloud

description: These are the datasets from the SUBMASSIVE system (www.submassive.cc) Title of the paper: SUBMASSIVE: Resolving Cyclic Subclass Relations in Very Large Knowledge Graphs -- Original data: subC-all (all the subclass subsumption relations) Fully Automatic (FA) approach: refined-subC-FA (relations remain after FA processing) Semi-automatic (SA) approach: refined-subC-SA (relations remain after SA processing) Original data: subP-all (all the subproperty subsumption relations) refined-subP (relations remain)
description: www.submassive.cc
DOI: 10.5281/zenodo.3691681
title: Cycle-free Subclass Subsumption Relations of the LOD Cloud

description: These are the datasets from the SUBMASSIVE system (www.submassive.cc) Title of the paper: SUBMASSIVE: Resolving Cyclic Subclass Relations in Very Large Knowledge Graphs -- Original data: subC-all (all the subclass subsumption relations) Fully Automatic (FA) approach: refined-subC-FA (relations remain after FA processing) Semi-automatic (SA) approach: refined-subC-SA (relations remain after SA processing) Original data: subP-all (all the subproperty subsumption relations) refined-subP (relations remain)
description: www.submassive.cc
DOI: 10.18716/nmrshiftdb2/75020
title: NMR data for InChI=1S/C22H29NO5/c1-15(24)8-7-12-22(2)13-11-17(14-18(22)25)20(26)23-19(21(27)28-3)16-9-5-4-6-10-16/h4-6,9-10,17,19H,7-8,11-14H2,1-3H3,(H,23,26)/t17-,19?,22-/m1/s1
DOI: 10.17632/w2fbt6995f.1
title: 2020 thyroid US vs palpation

description: This excel composed the data of 700 GD patients including their age, genders, smoking, goiter symptom, thyroid size, soft tissue thickness of anterior neck, P-TV and US-TV.
DOI: 10.6085/aa/rkpx00_xxxibtnxmbr11_20110509.40.1
title: (:unkn)
DOI: 10.18716/nmrshiftdb2/75027
title: NMR data for InChI=1S/C11H23NO/c1-5-10-8-13-11(4,12-10)7-6-9(2)3/h9-10,12H,5-8H2,1-4H3
DOI: 10.6085/aa/purxxx_015mtbd014r00_20101019.40.1
title: (:unkn)
DOI: 10.6085/aa/purxxx_015mtbd014r00_20110117.40.1
title: (:unkn)
DOI: 10.17632/k85brnzfx9.2
title: Supplementary files - Prevalence and patient-reported outcomes of noncommunicable skin diseases among college students in China

description: Supplementary figures for manuscript "Prevalence and patient-reported outcomes of noncommunicable skin diseases among adolescents: a population-based study in China"
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20070714.40.1
title: (:unkn)
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20070813.40.1
title: (:unkn)
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20071001.40.1
title: (:unkn)
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20071027.40.1
title: (:unkn)
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20071128.40.1
title: (:unkn)
DOI: 10.18716/nmrshiftdb2/75025
title: NMR data for InChI=1S/C19H18N2O2/c1-3-7-14(8-4-1)16-12-22-18(20-16)11-19-21-17(13-23-19)15-9-5-2-6-10-15/h1-10,16-17H,11-13H2
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20071209.40.1
title: (:unkn)
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20080121.40.1
title: (:unkn)
DOI: 10.18716/nmrshiftdb2/75019
title: NMR data for InChI=1S/C14H19NO5/c1-5-20-14(17)13(15-9(2)16)11-7-6-10(18-3)8-12(11)19-4/h6-8,13H,5H2,1-4H3,(H,15,16)
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20110105.40.1
title: (:unkn)
DOI: 10.6085/aa/rkpx00_xxxibtnxmbr12_20110616.40.1
title: (:unkn)
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20110323.40.1
title: (:unkn)
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20110420.40.1
title: (:unkn)
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20110521.40.1
title: (:unkn)
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20110717.40.1
title: (:unkn)
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20110813.40.1
title: (:unkn)
DOI: 10.6085/aa/rkpx00_xxxibtnxtsr01_20111214.40.1
title: (:unkn)
DOI: 10.17632/8thfmxwmm4.1
title: Internet addiction and associated factors among medical and allied health sciences students in northern Tanzania: A cross-sectional study

description: This data is based on a cross-sectional study conducted between May and June 2018 at Kilimanjaro Christian Medical University College (KCMUCo) located in Moshi Municipality, Kilimanjaro region in North-eastern Tanzania. The study aimed to determine prevalence and factors associated with internet addiction among medical and allied health sciences students.
DOI: 10.17632/zknvry83v5.2
title: Prevalence, clinical features and risk factors of skin damages caused by enhanced infection-prevention measures among healthcare workers managing coronavirus disease-2019: a cross-sectional study in infected center of China-Supplementary Materials

description: Supplemental Material 1 (Questionnaire):From January to February 2020, self-administered on-line questionnaires were distributed to 700 individuals consisting of physicians and nurses who worked in the designated departments of tertiary hospitals in Hubei, China. All responders agreed to be published Supplemental Material 2 (Table): The characteristics of all participants.
DOI: 10.17632/zknvry83v5.1
title: Prevalence, clinical features and risk factors of skin damages caused by enhanced infection-prevention measures among healthcare workers managing coronavirus disease-2019: a cross-sectional study in infected center of China-Supplementary Materials

description: Supplemental Material 1 (Questionnaire):From January to February 2020, self-administered on-line questionnaires were distributed to 700 individuals consisting of physicians and nurses who worked in the designated departments of tertiary hospitals in Hubei, China. All responders agreed to be published Supplemental Material 2 (Table): The characteristics of all participants.
DOI: 10.18716/nmrshiftdb2/75029
title: NMR data for (3R,7aS)-7a-methyl-3-propan-2-yl-2,3,6,7-tetrahydropyrrolo[2,1-b][1,3]oxazol-5-one
DOI: 10.17632/rv2vycs7pg.1
title: Hfszeeman95—A program for computing weak and intermediate magnetic-field- and hyperfine-induced transition rates

description: Hfszeeman95 is an updated and extended Fortran 95 version of the Hfszeeman program (Andersson and Jönsson, 2008). Given relativistic atomic state functions generated by the Grasp2018 package (Fischer et al., 2019), Hfszeeman95 together with the accompanying Matlab/GNU Octave program Mithit allows for: (1) the computation and plotting of Zeeman energy splittings of magnetic fine- and hyperfine structure substates as functions of the strength of an external magnetic field, (2) the computation of transition rates between different magnetic fine- and hyperfine structure substates in the presence of an external magnetic field and rates of hyperfine-induced transitions in the field free limit, (3) the synthesization of spectral profiles for transitions obtained from (2). With the new features, Hfszeeman95 and the accompanying Matlab/GNU Octave program Mithit are useful for the analysis of observational spectra and to resolve the complex features due to the splitting of the fine and hyperfine levels.
DOI: 10.18716/nmrshiftdb2/75032
title: NMR data for InChI=1S/C9H9NO2/c11-9-10-8(6-12-9)7-4-2-1-3-5-7/h1-5,8H,6H2,(H,10,11)