cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22691793.v1
title: Exploration of molecular interactions between scoparone and associated compounds with Constitutive androstane receptor (CAR) leading to gallstone prevention: an in silico investigation

description: Scoparone (6, 7 dimethylesculetin) is a biologically active compound derived from the herb <i>Artemisia capillaris</i> having anti-inflammatory, anti-lipemic, and anti-allergic roles. Activation of the constitutive androstane receptor (CAR) in primary hepatocytes of both wild-type and humanized CAR mice by scoparone, accelerates bilirubin and cholesterol clearance <i>in vivo</i>. This can prevent gallstones which is a dreaded gastrointestinal disease. To date, surgery is regarded as the gold standard for treating gallstones. The molecular interactions between scoparone and CAR leading to gallstone prevention are not yet explored. In this study, we have analyzed these interactions through an <i>insilico</i> approach. After extracting the CAR structures (mice and human) from the protein databank and 6, 7-dimethylesuletin from PubChem, energy minimization of both the receptors was done to make them stable followed by docking. Next, a simulation was performed to stabilize the docked complexes. Through docking, H-bonds and pi-pi interactions were found in the complexes, which imply a stable interaction, thus activating the CAR. A similarity search for scoparone was performed and the selected compounds were docked with the CAR receptors. Esculentin acetate and scopoletin acetate interacted with human CAR through pi-alkyl and H-bond respectively. While Fraxidin methyl ether, fraxinol methyl ether, and 6, 7 diethoxycoumarin interacted with mice CAR through H-bond and Pi-Pi T-shaped bonds. The selected complexes were simulated further. Our results are in accordance with the hypothesis in the literature. We have also analyzed the drug likeliness, absorption, non-carcinogenicity, and other properties of scoparone which can support further <i>in vivo</i> studies. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.22691793.v2
title: Exploration of molecular interactions between scoparone and associated compounds with Constitutive androstane receptor (CAR) leading to gallstone prevention: an in silico investigation

description: Scoparone (6, 7 dimethylesculetin) is a biologically active compound derived from the herb <i>Artemisia capillaris</i> having anti-inflammatory, anti-lipemic, and anti-allergic roles. Activation of the constitutive androstane receptor (CAR) in primary hepatocytes of both wild-type and humanized CAR mice by scoparone, accelerates bilirubin and cholesterol clearance <i>in vivo</i>. This can prevent gallstones which is a dreaded gastrointestinal disease. To date, surgery is regarded as the gold standard for treating gallstones. The molecular interactions between scoparone and CAR leading to gallstone prevention are not yet explored. In this study, we have analyzed these interactions through an <i>insilico</i> approach. After extracting the CAR structures (mice and human) from the protein databank and 6, 7-dimethylesuletin from PubChem, energy minimization of both the receptors was done to make them stable followed by docking. Next, a simulation was performed to stabilize the docked complexes. Through docking, H-bonds and pi-pi interactions were found in the complexes, which imply a stable interaction, thus activating the CAR. A similarity search for scoparone was performed and the selected compounds were docked with the CAR receptors. Esculentin acetate and scopoletin acetate interacted with human CAR through pi-alkyl and H-bond respectively. While Fraxidin methyl ether, fraxinol methyl ether, and 6, 7 diethoxycoumarin interacted with mice CAR through H-bond and Pi-Pi T-shaped bonds. The selected complexes were simulated further. Our results are in accordance with the hypothesis in the literature. We have also analyzed the drug likeliness, absorption, non-carcinogenicity, and other properties of scoparone which can support further <i>in vivo</i> studies. Communicated by Ramaswamy H. Sarma
DOI: 10.34740/kaggle/dsv/7501529
title: Polish-Ukrainian translations from Tatoeba
DOI: 10.34740/kaggle/dsv/7501530
title: BBC News
DOI: 10.5281/zenodo.10578307
title: Pixel-dependent offset, gain, variance and readnoise maps for CS505MUP polarisation camera

description: These four tif files are the pixel-dependent camera offset (in ADU counts), gain (in ADU counts/photoelectron), variance (in ADU counts^2) and readout noise (in photoelectrons) for the full sensor of a polarization camera (CS505MUP, Thorlabs), as measured using the camera calibration method described in the Supplementary material of the following paper:



Huang, F., Hartwich, T., Rivera-Molina, F. et al. Video-rate nanoscopy using sCMOS camera–specific single-molecule localization algorithms. Nat Methods 10, 653–658 (2013). https://doi.org/10.1038/nmeth.2488
DOI: 10.5517/ccdc.csd.cc2g1s7k
title: CCDC 2265828: Experimental Crystal Structure Determination

description: Related Article: Wang Shen, Xiyao Lu, Yu Shen, Junjian Li, Aiqun Jia, Shi Tang|2023|J.Org.Chem.|89|1108|doi:10.1021/acs.joc.3c02249
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.cc2g1xfw
title: CCDC 2265958: Experimental Crystal Structure Determination

description: Related Article: Wang Shen, Xiyao Lu, Yu Shen, Junjian Li, Aiqun Jia, Shi Tang|2023|J.Org.Chem.|89|1108|doi:10.1021/acs.joc.3c02249
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.23734134.v1
title: 20230723_figshare_DIRECT.zip

description: All data required to reproduce the DIRECT sampling results in the manuscript "Robust Training of Machine Learning Interatomic Potentials with Dimensionality Reduction and Stratified Sampling".
It contains training, validation and test data for M3GNet-MS and M3GNet-DIRECT UPs, training and test data for MTP-AL and MTP-DIRECT for Ti-H, as well as pre-processed M3GNet features of the 1.3 million structures in <em>MPF.2021.2.8.all</em> and the 274,000 M3GNet MD structures of Ti-H.
DOI: 10.6084/m9.figshare.25100216
title: Anexo A. Bases de datos de las medias y medianas de las variables empleadas en el modelamiento espacial.

description: Bases de datos de las medias y medianas de la precipitación, los índices de vegetación y humedad, el modelo digital de terreno y las variables edáficas empleadas en el modelamiento espacial.
DOI: 10.6084/m9.figshare.23734134
title: 20230723_figshare_DIRECT

description: All data required to reproduce the DIRECT sampling results in the manuscript "Robust Training of Machine Learning Interatomic Potentials with Dimensionality Reduction and Stratified Sampling".It contains the below data:Training, validation, and test data as well as model parameters of M3GNet-MS and M3GNet-DIRECT universal potentials.Training and test data as well as model parameters of MTP-AL and MTP-DIRECT for Ti-H.Pre-processed M3GNet structural features of the 1.3 million structures in <i>MPF.2021.2.8.All</i> and the 274,000 M3GNet MD structures of Ti-H.
DOI: 10.6084/m9.figshare.23734134.v2
title: 20230723_figshare_DIRECT

description: All data required to reproduce the DIRECT sampling results in the manuscript "Robust Training of Machine Learning Interatomic Potentials with Dimensionality Reduction and Stratified Sampling".It contains the below data:Training, validation, and test data as well as model parameters of M3GNet-MS and M3GNet-DIRECT universal potentials.Training and test data as well as model parameters of MTP-AL and MTP-DIRECT for Ti-H.Pre-processed M3GNet structural features of the 1.3 million structures in <i>MPF.2021.2.8.All</i> and the 274,000 M3GNet MD structures of Ti-H.
DOI: 10.6084/m9.figshare.25100363
title: Anexo B. Bases de datos finales empleadas en el modelamiento espacial.

description: Base de datos con la matriz de medias y medianas empleada para el modelamiento espacial y la matriz del modelo final.
DOI: 10.6084/m9.figshare.25100363.v1
title: Anexo B. Bases de datos finales empleadas en el modelamiento espacial.

description: Base de datos con la matriz de medias y medianas empleada para el modelamiento espacial y la matriz del modelo final.
DOI: 10.34740/kaggle/dsv/7501729
title: WallStreetBets 2022
DOI: 10.6084/m9.figshare.25100123
title: <b>The potential of </b><b><i>Sonneratia caseolaris</i></b><b> mangrove leaves extract as a bioactive food ingredient using various water extract</b>

description: <b>Fig. </b><b>1</b> Ligands-Keap1 interactions and the amino acid residues involved. A-D. Visualization of molecular docking results between inhibitors, Tempo, Betaine, and Choline with Keap1 protein. The top row shows each ligand's position that binds to the Keap1 protein. The bottom row shows the amino acid residues involved in the interactions of the inhibitor, Tempo, Betaine, and Choline with the Keap1 protein. Keap1 protein is presented as a pink ribbon. The compounds are presented in the form of colored sticks, namely inhibitors (blue), Tempo (orange), Betaine (gray), and Choline (yellow).<b>Figure 2.</b> Molecular dynamic simulation. The stability of the ligand-Keap1 interaction complex during the simulation was indicated by (A) the RMSD of the ligand-Keap1 complex value, (B) the RMSD of the Ligand movement value, (C) the RMSF value, and (C) the number of hydrogen bonds.<b>Ta</b><b>b</b><b>l</b><b>e</b><b> 1.</b> Phytochemical properties, antioxidant activity, and mass yield percentage of various <i>S. Caseolaris</i> leaves water extract<b>Tab</b><b>le </b><b>2.</b> Bioactive compounds of various S. Caseolaris leaves water extract using LC-HRMS<br>
DOI: 10.34740/kaggle/dsv/7501727
title: AI recognition dataset
DOI: 10.6084/m9.figshare.24152160
title: Balancing non-CO2 GHG emissions and soil carbon sequestration in U.S. rice paddies: implications for natural climate solutions

description: The U.S. rice paddy systems play an increasingly vital role in ensuring food security, which also contribute massive anthropogenic non-CO<sub>2</sub> (CH<sub>4</sub> and N<sub>2</sub>O) greenhouse gas (GHG) emissions with expanding cultivation area. However, the magnitude and spatiotemporal variations of net GHG balance, i.e., trade-offs between SOC (Soil Organic Carbon) sequestration and non-CO<sub>2</sub> GHG emissions, in paddy soils and the drivers of their changes, have not yet been rigorously assessed. Integrating an improved agricultural ecosystem model with a meta-analysis of multiple field studies (a total of 322 site-year data representing 43 locations for U.S. rice paddies and 3402 site-year data representing 1113 locations for global rice paddies), here we found that U.S. rice paddy was a rapidly growing net GHG emission source, increased 138% from 3.73 ± 1.16 Tg CO<sub>2</sub>eq yr<sup>-1</sup> in the 1960s to 8.88 ± 2.65 Tg CO<sub>2</sub>eq yr<sup>-1</sup> in the 2010s. CH<sub>4</sub> emission made the most significant contribution (10.12 ± 2.28 Tg CO<sub>2</sub>eq yr<sup>-1</sup>) to this increase in net GHG emissions in the 2010s, but increasing N<sub>2</sub>O emissions, accounting for ~2.4% (0.21 ± 0.03 Tg CO<sub>2</sub>eq yr<sup>-1</sup>), cannot be ignored. SOC sequestration could offset about 14.0% (1.45 ± 0.46 Tg CO<sub>2</sub>eq yr<sup>-1</sup>) of the climate-warming effects of soil non-CO<sub>2</sub> GHG emissions in the 2010s. The intensification of land use/cover area, atmospheric CO<sub>2</sub>,synthetic N fertilizer usage and the application of manure were the dominant factors that induced net GHG emissions aggravation in rice paddies. Climate change was also critical in aggravating ~21% of soil N<sub>2</sub>O emission and ~10% of soil CO<sub>2</sub> release in the 2010s. However, adopting no/reduced tillage resulted in a substantial decrease of ~10 % in net soil GHG emissions, and non-continuous irrigation exhibited the potential to mitigate around 39% of soil non-CO<sub>2</sub> GHG emissions. Overall, the cost of this net GHG emissions for achieving increased U.S. rice yield markedly declined from 1960 to 2018, resulting in 0.84 ± 0.18 kg CO<sub>2</sub>eq ha<sup>-1</sup> of net soil GHGs on average for each kilogram of grain produced in the 2010s. There would be a great potential to reduce emissions intensity in the mid-South U.S., especially the Mississippi Delta region, through optimization of the synthetic N fertilizer and manure ratio, reduction of tillage practices, and implementation of non-continuous irrigation. Our findings underscore the importance of net CO<sub>2</sub> GHG mitigation in U.S. rice paddies for achieving net zero-emission and climate-friendly rice production.Unit: CH4 (g C/m2); N2O (g N/m2); CO2 (g C/m2)
DOI: 10.5517/ccdc.csd.cc2d04p8
title: CCDC 2204679: Experimental Crystal Structure Determination

description: Related Article: Maryam Taghizadeh Shool, Hadi Amiri Rudbari, José V. Cuevas-Vicario, Andrea Rodríguez-Rubio, Claudio Stagno, Nunzio Iraci, Thomas Efferth, Ejlal A. Omer, Tanja Schirmeister, Olivier Blacque, Nakisa Moini, Esmail Sheibani, Nicola Micale|2023|Inorg.Chem.|63|1083|doi:10.1021/acs.inorgchem.3c03414
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.cc2hd7hn
title: CCDC 2305671: Experimental Crystal Structure Determination

description: Related Article: Lachlan J. N. Waddell, Claire Wilson, Andrew Sutherland|2023|J.Org.Chem.|89|1275|doi:10.1021/acs.joc.3c02571
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.10578648
title: LOLT156-example

description: NOT-156: A Low-light and Thermal Infrared Multi-modal Benchmark for Night Object Tracking

This paper has been submitted to the CVPR. The whole dataset will be released soon, some examples could be downloaded here.
DOI: 10.5281/zenodo.8093214
title: LOLT156-example

description: <strong>LOLT156: A Low-Light and Thermal Infrared Object Tracking Benchmark</strong> This paper has been submitted to the 37th Conference on Neural Information Processing Systems (NeurIPS 2023) Track on Datasets and Benchmarks. The whole dataset will be released soon, some examples could be downloaded here.
DOI: 10.5281/zenodo.10578657
title: NOT-156-example

description: NOT-156: A Low-light and Thermal Infrared Multi-modal Benchmark for Night Object Tracking

This paper has been submitted to the CVPR. The whole dataset will be released soon, some examples could be downloaded here.
DOI: 10.5281/zenodo.8093213
title: NOT-156-example

description: NOT-156: A Low-light and Thermal Infrared Multi-modal Benchmark for Night Object Tracking

This paper has been submitted to the CVPR. The whole dataset will be released soon, some examples could be downloaded here.
DOI: 10.25919/j0vh-ve59
title: Effector screen

description: Sequencing files and associated data
DOI: 10.6084/m9.figshare.25100381
title: Trait mindfulness and academic performance_Raw data

description: Here is the raw data for our article (The relationship between trait mindfulness and academic performance: A meta-analysis).
DOI: 10.6084/m9.figshare.24886164.v1
title: CO2 fluxes from global and 39 major basins' river networks

description: Annual dataset of totoal CO2 flux, mean CO2 gradient, mean gas exchange rate, and total river areas for global river networks and rivers at 39 major basins. In total, we have 40 .csv files.Four columns in each .csv file: (1) Total CO2 flux (Tg C/yr), (2) mean CO2 gradient (ppm), (3) mean gas exchange rage (m/d), and (4) total river areas (biliion m2).
DOI: 10.5281/zenodo.10494926
title: SCTrans: Scenario Dataset for Simulation Testing of Autonomous Driving Systems

description: In this work, we introduce a transformation-based approach, namely SCTrans, which utilizes existing real-world traffic scenario datasets to create simulation scenario files. For more approach details, please see our ICSE-24 paper.

To curate an initial version of our scenario dataset, we randomly selected 1,994 valid traffic scenario recording files as data sources, from representative traffic scenario datasets, including CommonRoad[1], inD[2], and highD[3]. Finally, we got 1,994 simulation scenario files and 426 map description files, which are compatible with advanced ADS testing platforms (e.g., LGSVL[4]+Apollo[5] and Carla[6]+Autoware[7]. For ease of using our scenarios, we provide scenario-runner scripts for LGSVL and Carla, available at our Github Repo[8]. Besides, for ease of scenario selection, we manually label all our simulation scenarios according to ISO 21448 (i.e., guiding principles for ADS SOTIF testing). The labeling results are listed in scenario-tag.xlsx.

======== How to Use ========

Please refer to our Github Website. We provide the refined versions of the LGSVL & Carla scenario runners. The scenario-runner directory contains the complete, modified source code along with comprehensive usage instructions.
DOI: 10.5281/zenodo.10146005
title: The Impact of Code Ownership of DevOps Artefacts on the Outcome of DevOps CI Builds

description: # The Impact of Code Ownership of DevOps Artefacts on the Outcome of DevOps CI Builds
This is the replication package of an empirical analysis on a dataset of 892,193 DevOps CircleCI builds spanning 1,689 Open-Source Software projects.
We employ a two-pronged approach to our study. First, we investigate the impact of chronological code ownership of DevOps artefacts on the outcome of a DevOps CI build on a build level. Second, we study the impact of the Skewness of DevOps contributions on the success rate of DevOps CI builds on a project level.
DOI: 10.5281/zenodo.10146006
title: The Impact of Code Ownership of DevOps Artefacts on the Outcome of DevOps CI Builds

description: # The Impact of Code Ownership of DevOps Artefacts on the Outcome of DevOps CI Builds
This is the replication package of an empirical analysis on a dataset of 892,193 DevOps CircleCI builds spanning 1,689 Open-Source Software projects.
We employ a two-pronged approach to our study. First, we investigate the impact of chronological code ownership of DevOps artefacts on the outcome of a DevOps CI build on a build level. Second, we study the impact of the Skewness of DevOps contributions on the success rate of DevOps CI builds on a project level.
DOI: 10.5281/zenodo.10570324
title: The Impact of Code Ownership of DevOps Artefacts on the Outcome of DevOps CI Builds

description: # The Impact of Code Ownership of DevOps Artefacts on the Outcome of DevOps CI Builds
This is the replication package of an empirical analysis on a dataset of 892,193 DevOps CircleCI builds spanning 1,689 Open-Source Software projects.
We employ a two-pronged approach to our study. First, we investigate the impact of chronological code ownership of DevOps artefacts on the outcome of a DevOps CI build on a build level. Second, we study the impact of the Skewness of DevOps contributions on the success rate of DevOps CI builds on a project level.
DOI: 10.5281/zenodo.10578690
title: The Impact of Code Ownership of DevOps Artefacts on the Outcome of DevOps CI Builds

description: # The Impact of Code Ownership of DevOps Artefacts on the Outcome of DevOps CI Builds
This is the replication package of an empirical analysis on a dataset of 892,193 DevOps CircleCI builds spanning 1,689 Open-Source Software projects.
We employ a two-pronged approach to our study. First, we investigate the impact of chronological code ownership of DevOps artefacts on the outcome of a DevOps CI build on a build level. Second, we study the impact of the Skewness of DevOps contributions on the success rate of DevOps CI builds on a project level.
DOI: 10.7910/dvn/mo1mxq
title: Replication Data for: Strategic Ambiguity, Strategic Clarity, and Dual Clarity

description: These files provide the materials needed to replicate the tables and figures in the main text and appendix for "Strategic Ambiguity, Strategic Clarity, and Dual Clarity" accepted by Foreign Policy Analysis. (2024-01-28)
DOI: 10.5281/zenodo.10578343
title: Grapegenomics.com - Genome release: Vitis vinifera cv. Chardonnay cl. 04 v2.0

description: https://www.grapegenomics.com/pages/VvChar/
DOI: 10.5281/zenodo.10578344
title: Grapegenomics.com - Genome release: Vitis vinifera cv. Chardonnay cl. 04 v2.0

description: https://www.grapegenomics.com/pages/VvChar/
DOI: 10.5281/zenodo.10532671
title: Enhancing Generalizability in Protein-Ligand Binding Affinity Prediction with Multimodal Contrastive Learning

description: The data sets for training ConBAP
DOI: 10.5281/zenodo.10532672
title: Enhancing Generalizability in Protein-Ligand Binding Affinity Prediction with Multimodal Contrastive Learning

description: The data sets for training ConBAP
DOI: 10.5281/zenodo.10578647
title: Enhancing Generalizability in Protein-Ligand Binding Affinity Prediction with Multimodal Contrastive Learning

description: The data sets for training ConBAP
DOI: 10.5281/zenodo.10024020
title: Equation of State of Liquid Fe7C3 and Thermodynamic Modeling of the Liquidus Phase Relations in the Fe-C System
DOI: 10.5281/zenodo.10024021
title: Equation of State of Liquid Fe7C3 and Thermodynamic Modeling of the Liquidus Phase Relations in the Fe-C System
DOI: 10.5281/zenodo.10576904
title: Equation of State of Liquid Fe7C3 and Thermodynamic Modeling of the Liquidus Phase Relations in the Fe-C System
DOI: 10.6084/m9.figshare.24777084.v1
title: Data Descriptor: EEG and physiological signals data from university students during interaction with the Neurohumanities Lab's partially immersive space. (Raw EEG Data)Data Descriptor: EEG and physiological signals data from university students during interaction with the Neurohumanities Lab's partially immersive space.

description: This collection includes the data recordings from EEG signal of subjects interacting with the Neurohumanities Lab partial-inmersive space at Monterrey, MX, during October 2023 from "Neurohumanties Lab" project.
DOI: 10.34740/kaggle/dsv/7502133
title: Social Soirées: A Narrative and Relational Dataset