cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2hl3hq
title: CCDC 2311313: Experimental Crystal Structure Determination

description: Related Article: Ting Wang, Leyu Bi, Liu Yang, Zixin Zeng, Xiaofei Ji, Ziyang Hu, Sai-Wing Tsang, Hin-Lap Yip, Qiang Fu, Alex K.-Y. Jen, Yongsheng Liu|2024|J.Am.Chem.Soc.|146|7555|doi:10.1021/jacs.3c13576
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2hp8hz
title: CCDC 2314351: Experimental Crystal Structure Determination

description: Related Article: Pengxuan Yin, Zijie Zhou, Lingsheng Shi, Chengzhi Xiang, Ling Ye, Min Han, Zhichuan Shi, Zhigang Zhao, Xuefeng Li|2024|Org.Lett.|26|2152|doi:10.1021/acs.orglett.4c00073
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2hz81t
title: CCDC 2322986: Experimental Crystal Structure Determination

description: Related Article: Xiaowei Liu, Kailei Li, Wei Shao, Wei Shen, Ming Li, Lei Zhou, Rongxing He|2024|Inorg.Chem.|63|5158|doi:10.1021/acs.inorgchem.4c00117
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2hz83w
title: CCDC 2322988: Experimental Crystal Structure Determination

description: Related Article: Xiaowei Liu, Kailei Li, Wei Shao, Wei Shen, Ming Li, Lei Zhou, Rongxing He|2024|Inorg.Chem.|63|5158|doi:10.1021/acs.inorgchem.4c00117
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.25466398
title: inter

description: HIc track
DOI: 10.6084/m9.figshare.25466398.v1
title: inter

description: HIc track
DOI: 10.6084/m9.figshare.25466389
title: systematic review data analysis

description: Systematic review, carried out based on the guiding question: which information and communication technologies are effective in improving the knowledge of hospitalized patients? The search took place in electronic databases: Scopus; National Library of Medicine and National Institutes of Health; Web of Science; Cumulative Index of Nursing and Allied Health Literature; Scientific Electronic Library Online; Cochrane and Excerpta Medica dataBASE. To search for gray literature, Google Scholar was used. The exposure factor was the educational intervention using information and communication technologies, and as an outcome: improved knowledge. Only randomized clinical trials were included, in all languages. Objective to evaluate the effectiveness of information and communication technologies in improving the knowledge of hospitalized patients. 1,153 articles were identified, of which four were included. The others revealed effectiveness in improving knowledge and the educational interventions were mediated by technology such as video, application and concept map.
DOI: 10.6084/m9.figshare.25466389.v1
title: systematic review data analysis

description: Systematic review, carried out based on the guiding question: which information and communication technologies are effective in improving the knowledge of hospitalized patients? The search took place in electronic databases: Scopus; National Library of Medicine and National Institutes of Health; Web of Science; Cumulative Index of Nursing and Allied Health Literature; Scientific Electronic Library Online; Cochrane and Excerpta Medica dataBASE. To search for gray literature, Google Scholar was used. The exposure factor was the educational intervention using information and communication technologies, and as an outcome: improved knowledge. Only randomized clinical trials were included, in all languages. Objective to evaluate the effectiveness of information and communication technologies in improving the knowledge of hospitalized patients. 1,153 articles were identified, of which four were included. The others revealed effectiveness in improving knowledge and the educational interventions were mediated by technology such as video, application and concept map.
DOI: 10.34740/kaggle/dsv/7925978
title: BBC News
DOI: 10.5281/zenodo.10518158
title: Exploring the Impact of the Output Format on the Evaluation of Large Language Models for Code Translation

description: Please find the most up to date version of the dataset athttps://github.com/RISElabQueens/forge24-code-translation

 

Thank you
DOI: 10.5281/zenodo.10518159
title: Exploring the Impact of the Output Format on the Evaluation of Large Language Models for Code Translation

description: Please find the most up to date version of the dataset athttps://github.com/RISElabQueens/forge24-code-translation

 

Thank you
DOI: 10.57710/alba-es-2023097860
title: Electronic properties of one and two dimensional phosphorene on curved copper

description: Phosphorene is an appealing 2D material that have attracted recent interest due to its metal to semiconducting properties depending on the dimensionality of the layer. While on Cu(111) a Dirac cone has been claimed for a 2D layer, on Ag(111) one-dimensional P chains have been found with a 1.5eV bandgap. We observe a large number of different phases when depositing P on curved Cu samples that feature straight and kinked steps before P adsorption. After phosphorene formation, close to (111) the steps of the substrate are maintained and the 2D structure preserves. For vicinal angles larger 7°, faceting sets in. We observe P at the border of the steps with a rather 1-D electronic structure and the opening of a band gap. Nevertheless, our lab based ARPES measurements are insufficient for a complete picture of the system, therefore we ask for additional synchrotron based measurements.
DOI: 10.5281/zenodo.10548167
title: Magnetic excitation moments for large moons of the giant planets

description: Text files containing the spatially uniform (degree-1) magnetic oscillations experienced by each large moon of the giant planets as a function of frequency, also known as the excitation moments. All moments are in complex notation relative to the J2000 epoch. Used for determining the strength of induced magnetic fields from the moons from an interior conductivity structure. This dataset is compatible for use with the MoonMag and PlanetProfile frameworks for calculating induced magnetic fields of target moons. Refer to the publication linked below for more information.

All vector components are in IAU coordinates, such that at the body center, +z is directed along the body spin axis, +x is directed approximately toward the parent planet in the plane of an IAU-defined meridian feature, and +y is directed approximately opposite to the orbital velocity to complete the right-handed set. For the uranian moons and Triton, the IAU +z axes are opposite the spin axes because of their angles relative to the solar system invariable plane; the +y axes for these bodies are therefore directed approximately along the orbital velocity vector.

Excitation fields are determined by evaluation of SPICE kernels over a time series at the location of the body center. Position information is inserted into a magnetospheric model for the parent planet and complex Fourier coefficients are inverted from the time series using linear least squares optimization. The magnetic field models we use for each planet are:



Jupiter - JRM33 + C2020 current sheet (Connerney et al., 2022, 2020) except Callisto, for which we use VIP4+K (Connerney et al., 1998; Khurana, 1997)

Saturn - Cassini 11 (Dougherty et al., 2018)

Uranus - AH5 (Herbert, 2009)

Neptune - O8 (Connerney et al., 1991)


ASCII text files are included for all major moons of these planets.
DOI: 10.5281/zenodo.10864716
title: Magnetic excitation moments for large moons of the giant planets

description: Text files containing the spatially uniform (degree-1) magnetic oscillations experienced by each large moon of the giant planets as a function of frequency, also known as the excitation moments. All moments are in complex notation relative to the J2000 epoch. Used for determining the strength of induced magnetic fields from the moons from an interior conductivity structure. This dataset is compatible for use with the MoonMag and PlanetProfile frameworks for calculating induced magnetic fields of target moons. Refer to the publication linked below for more information.

All vector components are in IAU coordinates, such that at the body center, +z is directed along the body spin axis, +x is directed approximately toward the parent planet in the plane of an IAU-defined meridian feature, and +y is directed approximately opposite to the orbital velocity to complete the right-handed set. For the uranian moons and Triton, the IAU +z axes are opposite the spin axes because of their angles relative to the solar system invariable plane; the +y axes for these bodies are therefore directed approximately along the orbital velocity vector.

Excitation fields are determined by evaluation of SPICE kernels over a time series at the location of the body center. Position information is inserted into a magnetospheric model for the parent planet and complex Fourier coefficients are inverted from the time series using linear least squares optimization. The magnetic field models we use for each planet are:



Jupiter - JRM33 + C2020 current sheet (Connerney et al., 2022, 2020) except Callisto, for which we use VIP4+K (Connerney et al., 1998; Khurana, 1997)

Saturn - Cassini 11+ (Cao et al., 2020)

Uranus - AH5 (Herbert, 2009)

Neptune - O8 (Connerney et al., 1991)


ASCII text files are included for all major moons of these planets.
DOI: 10.5281/zenodo.5057571
title: Magnetic excitation moments for large moons of the giant planets

description: Text files containing the spatially uniform (degree-1) magnetic oscillations experienced by each large moon of the giant planets as a function of frequency, also known as the excitation moments. All moments are in complex notation relative to the J2000 epoch. Used for determining the strength of induced magnetic fields from the moons from an interior conductivity structure. This dataset is compatible for use with the MoonMag and PlanetProfile frameworks for calculating induced magnetic fields of target moons. Refer to the publication linked below for more information.

All vector components are in IAU coordinates, such that at the body center, +z is directed along the body spin axis, +x is directed approximately toward the parent planet in the plane of an IAU-defined meridian feature, and +y is directed approximately opposite to the orbital velocity to complete the right-handed set. For the uranian moons and Triton, the IAU +z axes are opposite the spin axes because of their angles relative to the solar system invariable plane; the +y axes for these bodies are therefore directed approximately along the orbital velocity vector.

Excitation fields are determined by evaluation of SPICE kernels over a time series at the location of the body center. Position information is inserted into a magnetospheric model for the parent planet and complex Fourier coefficients are inverted from the time series using linear least squares optimization. The magnetic field models we use for each planet are:



Jupiter - JRM33 + C2020 current sheet (Connerney et al., 2022, 2020) except Callisto, for which we use VIP4+K (Connerney et al., 1998; Khurana, 1997)

Saturn - Cassini 11+ (Cao et al., 2020)

Uranus - AH5 (Herbert, 2009)

Neptune - O8 (Connerney et al., 1991)


ASCII text files are included for all major moons of these planets.
DOI: 10.5281/zenodo.5057572
title: Degree-1 magnetic excitation spectra for icy moons

description: Matlab .mat files each containing a struct named FTdata with the fields below, containing information about the spatially uniform (degree-1) magnetic oscillations applied to each moon by their parent planet as a function of frequency. Used for determining the strength of induced magnetic fields from the moons from an interior conductivity structure. This dataset is compatible for use with the <em>PlanetProfile</em> framework for calculating the strength of induced magnetic field based in bulk properties of a moon in question. Save the files into the MagneticInduction/FieldData directory. Each .mat file contains a Matlab struct FTdata with the following fields: <strong>frequency</strong> - the excitation frequency at which oscillations occur in Hz. This is the independent variable for the other fields. <strong>Bx_fft</strong> - magnitude of the excitation field <em>B<sub>x</sub></em> component at each frequency of oscillation in nT. <strong>By_fft</strong> - magnitude of the excitation field <em>B<sub>y</sub></em> component at each frequency of oscillation in nT. <strong>Bz_fft</strong> - magnitude of the excitation field <em>B<sub>z</sub></em> component at each frequency of oscillation in nT. All vector components are in IAU coordinates, such that at the body center, +<em>x</em> is directed toward the parent planet, +<em>z</em> is directed along the body spin axis, and +<em>y</em> is directed approximately opposite to the orbital velocity to complete the right-handed set. Excitation fields are determined by evaluation of SPICE kernels over a years-long time series at the location of the body center. Position information is inserted into a magnetospheric model for the parent planet and a Fourier transform is calculated from the time series. These data are the results of the Fourier transform. The magnetic field models we use for each planet are: <strong>Jupiter</strong> - JRM09 + Connerney current sheet model (Connerney et al., 2018, 1981) <strong>Saturn</strong> - The model of Burton et al. (2010) <strong>Uranus</strong> - AH<sub>5</sub> model (Herbert, 2009) <strong>Neptune</strong> - The model of Connerney et al. (1991)
description: {"references": ["Burton et al., 2010. \"Saturn's internal planetary magnetic field\" https://doi.org/10.1029/2010GL045148", "Connerney et al., 1981. \"Modeling the Jovian current sheet and inner magnetosphere\" https://doi.org/10.1029/JA086iA10p08370", "Connerney et al., 1991. \"The magnetic field of Neptune\" https://doi.org/10.1029/91JA01165", "Connerney et al., 2018. \"A New Model of Jupiter's Magnetic Field From Juno's First Nine Orbits\" https://doi.org/10.1002/2018GL077312", "Herbert, 2009. \"Aurora and magnetic field of Uranus\" https://doi.org/10.1029/2009JA014394"]}
DOI: 10.6084/m9.figshare.25460692.v1
title: Dataset (fisher drowning death risk factors)

description: Dataset on risk factors for small-scale fisher drowning deaths in Lake Victoria, Kenya
DOI: 10.5517/ccdc.csd.cc2j6f4b
title: CCDC 2329871: Experimental Crystal Structure Determination

description: Related Article: Pengxuan Yin, Zijie Zhou, Lingsheng Shi, Chengzhi Xiang, Ling Ye, Min Han, Zhichuan Shi, Zhigang Zhao, Xuefeng Li|2024|Org.Lett.|26|2152|doi:10.1021/acs.orglett.4c00073
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2j6svd
title: CCDC 2330234: Experimental Crystal Structure Determination

description: Related Article: Bo Yang, Suqiong Yan, Yuan Zhang, Shirong Ban, Hui Ma, Fanda Feng, Wei Huang|2024|J.Am.Chem.Soc.|146|7668|doi:10.1021/jacs.3c14262
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.10864717
title: Air Quality, Location, Time, Number of Passenger Data during commute in selected area of Klang Valley, Malaysia

description: The dataset contains information on date/time, location names, periods, vehicle types, settlement patterns, commute elevation levels, latitude, longitude, air pollutant exposure data, along with temperature and relative humidity data, and passenger numbers for 40 trips conducted across various transport microenvironments in selected areas of the Klang Valley.
DOI: 10.5281/zenodo.10864718
title: Air Quality, Location, Time, Number of Passenger Data during commute in selected area of Klang Valley, Malaysia

description: The dataset contains information on date/time, location names, periods, vehicle types, settlement patterns, commute elevation levels, latitude, longitude, air pollutant exposure data, along with temperature and relative humidity data, and passenger numbers for 40 trips conducted across various transport microenvironments in selected areas of the Klang Valley.
DOI: 10.34740/kaggle/dsv/7926156
title: WallStreetBets 2022
DOI: 10.6084/m9.figshare.25466461.v1
title: Data and Code for B3P2Augur

description: The blood-brain barrier serves as a critical interface between the bloodstream and brain tissue. It plays a pivotal role in safeguarding brain from harmful substances, thus protecting the integrity of the nervous system and preserving overall brain homeostasis. However, the prediction models for B3PPs have been hampered by issue of limited positive data. In response to this challenge, this study aimed to use data augmentation to process the data, in order to develop better prediction models.In this study, we analyzed the amino acid composition and sequence features of blood-brain barrier penetrating peptides, and finally presented B<sup>3</sup>P<sup>2</sup>Augur, a novel prediction model using borderline-SMOTE-based data augmentation and machine learning. Further analysis demonstrated that the model performs best on the independent set (AUROC=0.931) with a 25% data augmentation ratio. Additionally, B<sup>3</sup>P<sup>2</sup>Augur has been developed into a tool that can be executed on a computer, with the source code freely available.B<sup>3</sup>P<sup>2</sup>Augur improves the prediction performance compared with existing models and demonstrates the effectiveness of data augmentation algorithms in predicting blood-brain barrier penetrating peptides, which may be valuable for developing new peptides.<br>
DOI: 10.6084/m9.figshare.25236988.v2
title: Supplementary Table 4 (Source data for Figure 5 and Figure 6A)

description: Differentially expression analysis results from cell type-adjusted model and cell type-unadjusted model; Source data for Figure 5 and Figure 6A
DOI: 10.6084/m9.figshare.25236988
title: Source Data - Figure 5A

description: Source Data - Figure 5A
DOI: 10.6084/m9.figshare.25236988.v4
title: Source Data - Figure 5A

description: Source Data - Figure 5A
DOI: 10.6084/m9.figshare.25236988.v3
title: Supplementary Table 4

description: Differentially expression analysis results from cell type-adjusted model and cell type-unadjusted model.
DOI: 10.6084/m9.figshare.25236985
title: Source Data - Figure 4B

description: Source Data - Figure 4B
DOI: 10.6084/m9.figshare.25236985.v1
title: Figure 4B

description: <b>B)</b> Relative enrichment and percentage expressed in cluster of the top enriched pathways per NSC clusters. Color indicates relative enrichment. Size indicates percentage expressed in each NSC cluster
DOI: 10.6084/m9.figshare.25236985.v2
title: Source Data - Figure 4B

description: Source Data - Figure 4B
DOI: 10.6084/m9.figshare.25236973
title: Source Data - Figure 2C

description: Source Data - Figure 2C
DOI: 10.6084/m9.figshare.25236973.v2
title: Source Data - Figure 2C

description: Source Data - Figure 2C
DOI: 10.6084/m9.figshare.25236973.v1
title: Figure 2C

description: <b>C)</b> Boxplot of gene expression levels of classical gene markers for cell types present in the brain by major cell type cluster. Astrocytes (AST): <i>GFAP </i>and <i>AQP4</i>; Endothelial cells (EN): <i>FN1 </i>and <i>COL4A1</i>; Macrophage/microglia (MAC/MG): <i>CSF1R </i>and; Neurons and unipolar brush cells (NEU, NEU_EX, NEU_GN, UBC): <i>RBFOX3 </i>and <i>RELN</i>; Inhibitory neurons and interneurons (NEU_INH, NEU_INT): <i>GAD2</i>; Neural stem cells (NSC): <i>SOX2 </i>and <i>CD44</i>; Oligodendrocytes (OLIG): <i>MOG </i>and <i>PLP1</i>; Oligodendrocyte precursor cells (OPC): <i>PDGFRA</i>; Radial glial cells (RGC): <i>VIM, NES, </i>and <i>PAX6</i>; Stromal cells (ST):<i> FAP</i>; T cells (TC): <i>CD3E.</i>
DOI: 10.6084/m9.figshare.25236970
title: Source Data - Figure 2B

description: Source Data - Figure 2B
DOI: 10.6084/m9.figshare.25236970.v2
title: Source Data - Figure 2B

description: Source Data - Figure 2B
DOI: 10.6084/m9.figshare.25236970.v1
title: Figure 2B

description: Uniform Manifold Approximation and Projection (UMAP) clustering of the 84,700 nuclei colored based on major cell type.
DOI: 10.6084/m9.figshare.25236967
title: Source Data - Figure 2A

description: Source Data - Figure 2A
DOI: 10.6084/m9.figshare.25236967.v1
title: Figure 2A

description: Uniform Manifold Approximation and Projection (UMAP) clustering of the 84,700 nuclei colored based on tissue.
DOI: 10.6084/m9.figshare.25236967.v2
title: Source Data - Figure 2A

description: Source Data - Figure 2A
DOI: 10.6084/m9.figshare.25236838
title: Source Data - Figure 1B

description: Source Data - Figure 1B
DOI: 10.6084/m9.figshare.25236838.v1
title: Figure 1B

description: <b>Figure 1</b><b>B)</b> Example of genotype information (Pool #1) used to demultiplex samples. Blue indicates 100% alternate allele presence. Pink indicates heterogeneous alternate allele presence. White indicates no alternate allele depth presence. Tracking bars indicate the samples assigned based on HTO or genotype (GT).
DOI: 10.6084/m9.figshare.25236838.v2
title: Source Data - Figure 1B

description: Source Data - Figure 1B