cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15151/esrf-es-1179910889
title: iNEXT Discovery: Structural biology for translational research and discovery.

description: The aim of this proposal is to provide user access to Online crystallography and fragment screening pipelines based on the combination of EMBL’s HTX Lab services and the CrystalDirect Technology and automated data collection at ESRF’s MX beamlines, supported through the collaborative EMBL-ESRF Joint Structural Biology Group (JSBG). This will include three different user access modalities: 1) Large-Scale Fragment Screening, 2) Structural characterization of ligand-target complexes and 3) Online Crystallography (automated protein-to-structure pipeline). This work will be carried out in the context of international collaborative projects. Access to these modalities will require competitive application and peer-review through projects like the E.C. funded iNEXT Discovery or the recently awarded ISIDORe.
DOI: 10.14469/hpc/12435
title: Layered BiOI single crystals capable of detecting low dose rates of X-rays

description: Experimental and computational data to support publication Abstract of paper: Detecting low dose rates of X-rays is critical for making safer radiology instruments, but is limited by the absorber materials available. Here, we develop bismuth oxyiodide (BiOI) single crystals into effective X-ray detectors. BiOI features complex lattice dynamics, owing to the ionic character of the lattice and weak van der Waals interactions between layers. Through use of ultrafast spectroscopy, first-principles computations and detailed optical and structural characterisation, we show that photoexcited charge-carriers in BiOI couple to intralayer breathing phonon modes, forming large polarons, thus enabling longer drift lengths for the photoexcited carriers than would be expected if self-trapping occurred. This, combined with the low and stable dark currents and high linear X-ray attenuation coefficients, leads to strong detector performance. High sensitivities reaching 1.1e3 μC Gyair-1 cm-2 are achieved, and the lowest dose rate directly measured by the detectors was 22 nGyair s-1. The photophysical principles discussed herein offer new design avenues for novel materials with heavy elements and low-dimensional electronic structures for (opto)electronic applications.
DOI: 10.6084/m9.figshare.19762963
title: Sturgeon-Paddlefish Whole Genome Duplication Data

description: Contains Code and Raw Data for Redmond et al 2023, Independent rediploidization masks shared whole genome duplication in the sturgeon-paddlefish ancestor
DOI: 10.34740/kaggle/dsv/5556294
title: YouTube Daily
DOI: 10.5517/ccdc.csd.cc2fmtqm
title: CCDC 2253381: Experimental Crystal Structure Determination

description: Related Article: H.J.S. Prasad, Devaraju, H.S. Yathirajan, M. Akkurt, S. Foro, R. Balerao, R.J. Butcher|2023|Acta Crystallogr.,Sect.E:Cryst.Commun.|79|423|doi:10.1107/S205698902300302X
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.cc2fmtrn
title: CCDC 2253382: Experimental Crystal Structure Determination

description: Related Article: H.J.S. Prasad, Devaraju, H.S. Yathirajan, M. Akkurt, S. Foro, R. Balerao, R.J. Butcher|2023|Acta Crystallogr.,Sect.E:Cryst.Commun.|79|423|doi:10.1107/S205698902300302X
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.cc2fn34c
title: CCDC 2253642: Experimental Crystal Structure Determination

description: Related Article: B.M. Ahmed, M. Zeller, G. Mezei|2023|Acta Crystallogr.,Sect.E:Cryst.Commun.|79|428|doi:10.1107/S2056989023003055
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.cc2fn3v2
title: CCDC 2253664: Experimental Crystal Structure Determination

description: Related Article: Y.P. Petrenko, D.M. Khomenko, R.O. Doroshchuk, I.V. Raspertova, S. Shova, R.D. Lampeka|2023|Acta Crystallogr.,Sect.E:Cryst.Commun.|79|432|doi:10.1107/S2056989023003079
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.cc2cxpff
title: CCDC 2202315: Experimental Crystal Structure Determination

description: Related Article: S.N. Chandana, D.P. Ganesha, N.R. Sreenatha, A.S. Harisha, B.N. Lakshminarayana|2023|Acta Crystallogr.,Sect.E:Cryst.Commun.|79|446|doi:10.1107/S2056989023003134
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.cc2fngyj
title: CCDC 2254008: Experimental Crystal Structure Determination

description: Related Article: M. Urlep, J. Cerkovnik, M. Lozinšek|2023|IUCrData|8|x230314|doi:10.1107/S2414314623003140
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.cc2fnnh8
title: CCDC 2254180: Experimental Crystal Structure Determination

description: Related Article: A. Ressel, A. Krupp, C. Strohmann|2023|Acta Crystallogr.,Sect.E:Cryst.Commun.|79|458|doi:10.1107/S2056989023003158
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.cc2fnqnh
title: CCDC 2254247: Experimental Crystal Structure Determination

description: Related Article: A.N. Khalilov, V.N. Khrustalev, L.V. Aleksandrova, M. Akkurt, R.M. Rzayev, A. Bhattarai, İ.G. Mamedov|2023|Acta Crystallogr.,Sect.E:Cryst.Commun.|79|436|doi:10.1107/S2056989023003171
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.cc2fp61d
title: CCDC 2254693: Experimental Crystal Structure Determination

description: Related Article: Vinaya, H.G. Anil Kumar, T.M. Mohan Kumar, B. Lakshmana, Y.B. Basavaraju, H.S. Yathirajan, S. Parkin|2023|Acta Crystallogr.,Sect.E:Cryst.Commun.|79|451|doi:10.1107/S2056989023003225
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.cc2fp62f
title: CCDC 2254694: Experimental Crystal Structure Determination

description: Related Article: Vinaya, H.G. Anil Kumar, T.M. Mohan Kumar, B. Lakshmana, Y.B. Basavaraju, H.S. Yathirajan, S. Parkin|2023|Acta Crystallogr.,Sect.E:Cryst.Commun.|79|451|doi:10.1107/S2056989023003225
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.cc2fp63g
title: CCDC 2254695: Experimental Crystal Structure Determination

description: Related Article: Vinaya, H.G. Anil Kumar, T.M. Mohan Kumar, B. Lakshmana, Y.B. Basavaraju, H.S. Yathirajan, S. Parkin|2023|Acta Crystallogr.,Sect.E:Cryst.Commun.|79|451|doi:10.1107/S2056989023003225
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.cc2fp64h
title: CCDC 2254696: Experimental Crystal Structure Determination

description: Related Article: Vinaya, H.G. Anil Kumar, T.M. Mohan Kumar, B. Lakshmana, Y.B. Basavaraju, H.S. Yathirajan, S. Parkin|2023|Acta Crystallogr.,Sect.E:Cryst.Commun.|79|451|doi:10.1107/S2056989023003225
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.7199036
title: Data associated with the publication "Assembling membraneless organelles from de novo designed proteins"

description: Raw data used in the manuscript "Assembling membraneless organelles from de novo designed proteins"
DOI: 10.5281/zenodo.7688563
title: Data associated with the publication "Assembling membraneless organelles from de novo designed proteins"

description: Raw data used in the manuscript "Assembling membraneless organelles from de novo designed proteins"
DOI: 10.5281/zenodo.7199035
title: Data associated with the publication "Assembling membraneless organelles from de novo designed proteins"

description: Raw data used in the manuscript "Assembling membraneless organelles from de novo designed proteins"
DOI: 10.5281/zenodo.7878607
title: Data associated with the publication "Assembling membraneless organelles from de novo designed proteins"

description: Raw data used in the manuscript "Assembling membraneless organelles from de novo designed proteins"
DOI: 10.6084/m9.figshare.22722055
title: compMDP-AE

description: This is the artifact of the paper “Compositional Probabilistic Model Checking with String Diagrams of MDPs”.
DOI: 10.6084/m9.figshare.22722055.v1
title: compMDP-AE

description: This is the artifact of the paper “Compositional Probabilistic Model Checking with String Diagrams of MDPs”.
DOI: 10.5281/zenodo.7830282
title: dcfvhgv

description: <strong>sakakmalkms</strong>
DOI: 10.5281/zenodo.7878628
title: dcfvhgv

description: <strong>sakakmalkms</strong>
DOI: 10.5281/zenodo.7830283
title: kmkmakmskm

description: p
DOI: 10.5281/zenodo.7878678
title: Identification of hybrids between the Japanese giant salamander and Chinese giant salamander using deep learning and smartphone images

description: Biological invasions are recognized as one of the factors causing biodiversity loss. Incomplete reproductive isolation with a closely related species can result in hybridization when a non-native species is introduced into a new habitat. Management of hybrids is essential for biodiversity conservation; however, the distinction between the two species becomes a challenge in cases of hybrids with similar characteristics to native species. Although image recognition technology can be a powerful tool for identifying hybrids, studies have yet to utilize deep learning approaches. Hence, this study aimed to identify hybrids between native Japanese giant salamanders (<em>Andrias japonicus</em>) and non-native Chinese giant salamanders (<em>Andrias davidianus</em>) using EfficientNet and smartphone images. We used smartphone images of 11 native individuals (with 5 training and 6 test images) and 20 hybrid individuals (with 5 training and 15 test images). In our experimental environment, an AI model constructed with efficientNet-V2 showed 100% accuracy in identifying hybrids. In addition, highlighting the regions that influenced the AI model's predictions using Grad-CAM revealed that salamander head spots are responsible for correctly classifying native and hybrid species. The results of this study revealed that our approach is one of the methods that enable the identification of hybrids, which was previously considered difficult without identification by the experts. Furthermore, since this study achieved high-performance identification using smartphone images, it is expected to be applied to a wide range of low-cost identification using citizen science.
DOI: 10.5281/zenodo.7878677
title: Identification of hybrids between the Japanese giant salamander and Chinese giant salamander using deep learning and smartphone images

description: Biological invasions are recognized as one of the factors causing biodiversity loss. Incomplete reproductive isolation with a closely related species can result in hybridization when a non-native species is introduced into a new habitat. Management of hybrids is essential for biodiversity conservation; however, the distinction between the two species becomes a challenge in cases of hybrids with similar characteristics to native species. Although image recognition technology can be a powerful tool for identifying hybrids, studies have yet to utilize deep learning approaches. Hence, this study aimed to identify hybrids between native Japanese giant salamanders (<em>Andrias japonicus</em>) and non-native Chinese giant salamanders (<em>Andrias davidianus</em>) using EfficientNet and smartphone images. We used smartphone images of 11 native individuals (with 5 training and 6 test images) and 20 hybrid individuals (with 5 training and 15 test images). In our experimental environment, an AI model constructed with efficientNet-V2 showed 100% accuracy in identifying hybrids. In addition, highlighting the regions that influenced the AI model's predictions using Grad-CAM revealed that salamander head spots are responsible for correctly classifying native and hybrid species. The results of this study revealed that our approach is one of the methods that enable the identification of hybrids, which was previously considered difficult without identification by the experts. Furthermore, since this study achieved high-performance identification using smartphone images, it is expected to be applied to a wide range of low-cost identification using citizen science.
DOI: 10.21227/m9k5-4179
title: Traffic flow data

description: In our dataset Traffic forecast data, Traffic data contains Traffic flow data and Traffic speed data.where Traffic flow data contains the data we want to forecast and Traffic speed data is the external information we introduce The forecast range is *min.The forecast range is *min These four folders contain Adjacency matrix + multiorder matrix and Adjacency matrix + multiorder matrix + global matrix for different forecast durations, respectively.The folders Adjacency matrix and global matrix contain the Just consider the adjacency matrix and Adjacency matrix + global matrix, which are the case with only the adjacency matrix and the case with the adjacency matrix and global information, respectively case.
DOI: 10.5281/zenodo.7867413
title: 5D-NP-FABTECH_FNH - Open Dataset for "Facile Handling of 3D Two-Photon Polymerized Microstructures by Ultra-Conformable Freestanding Polymeric Membranes"

description: This is the open dataset for the paper: "Frank Marco den Hoed, Ottomaniello Andrea, Omar Tricinci, Luca Cesarecciu, Marco Carlotti, Patrizio Raffa and Virgilio Mattoli, Facile Handling of 3D Two-Photon Polymerized Microstructures by Ultra-Conformable Freestanding Polymeric Membranes, On line (2023) [DOI:10.5281/zenodo.7837976]". This include the Supplementary Information file ("Supplementary-Info-AdvFuncMater_denHoed-Ottomaniello_2023.pdf"), all the source material used for the paper preparation and more. For each folder (sub-dataset) there is a corresponding readme file describing the content and including metadata
DOI: 10.5281/zenodo.7867412
title: 5D-NP-FABTECH_FNH - Open Dataset for "Facile Handling of 3D Two-Photon Polymerized Microstructures by Ultra-Conformable Freestanding Polymeric Membranes"

description: This is the open dataset for the paper: "Frank Marco den Hoed, Ottomaniello Andrea, Omar Tricinci, Luca Cesarecciu, Marco Carlotti, Patrizio Raffa and Virgilio Mattoli, Facile Handling of 3D Two-Photon Polymerized Microstructures by Ultra-Conformable Freestanding Polymeric Membranes, On line (2023) [DOI:10.5281/zenodo.7837976]". This include the Supplementary Information file ("Supplementary-Info-AdvFuncMater_denHoed-Ottomaniello_2023.pdf"), all the source material used for the paper preparation and more. For each folder (sub-dataset) there is a corresponding readme file describing the content and including metadata
DOI: 10.6084/m9.figshare.22722160
title: data for analysis.xlsx

description: Data include information about metabolic requirements for incremental shuttle walking tests and the same protocol performed on a treadmill walking test.
DOI: 10.5281/zenodo.7854625
title: Dataset for Broadband three-mode converter and multiplexer based on cascaded symmetric Y-junctions and subwavelength engineered MMI and phase shifters

description: This dataset contains the raw data for the figures (Fig. 5, Fig. 6 and Fig. 7) in the publication entitled "Broadband three-mode converter and multiplexer based on cascaded symmetric Y-junctions and subwavelength engineered MMI and phase shifters" published by Optics and Laser Technology (DOI: 10.1016/j.optlastec.2023.109513). Datafiles are in .txt format. All relevant information regarding the dataset, how it was obtained and its context is contained in the manuscript.
description: This work has been funded in part by the Spanish Ministry of Science and Innovation (MICINN) under grants RTI2018-097957-B-C33, PID2020-115353RA-I00; the Spanish State Research Agency (MCIN/ AEI/10.13039/501100011033); the Community of Madrid – FEDER funds (S2018/NMT-4326); the European Union – NextGenerationEU through the Recovery, Transformation and Resilience Plan (DIN2020- 011488, PTQ2021-011974); and the European Union's Horizon Europe research and innovation program under the Marie Sklodowska-Curie grant agreement Nº 101062518.
DOI: 10.5281/zenodo.7854624
title: Dataset for Broadband three-mode converter and multiplexer based on cascaded symmetric Y-junctions and subwavelength engineered MMI and phase shifters

description: This dataset contains the raw data for the figures (Fig. 5, Fig. 6 and Fig. 7) in the publication entitled "Broadband three-mode converter and multiplexer based on cascaded symmetric Y-junctions and subwavelength engineered MMI and phase shifters" published by Optics and Laser Technology (DOI: 10.1016/j.optlastec.2023.109513). Datafiles are in .txt format. All relevant information regarding the dataset, how it was obtained and its context is contained in the manuscript.
description: This work has been funded in part by the Spanish Ministry of Science and Innovation (MICINN) under grants RTI2018-097957-B-C33, PID2020-115353RA-I00; the Spanish State Research Agency (MCIN/ AEI/10.13039/501100011033); the Community of Madrid – FEDER funds (S2018/NMT-4326); the European Union – NextGenerationEU through the Recovery, Transformation and Resilience Plan (DIN2020- 011488, PTQ2021-011974); and the European Union's Horizon Europe research and innovation program under the Marie Sklodowska-Curie grant agreement Nº 101062518.
DOI: 10.34740/kaggle/dsv/5556707
title: Egypt Gold Prices | Daily Updated
DOI: 10.34740/kaggle/dsv/5556805
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.5281/zenodo.7878745
title: BMRQ_dataset

description: dataset for publication
DOI: 10.5281/zenodo.7878744
title: BMRQ_dataset

description: dataset for publication
DOI: 10.15139/s3/tvcl0j
title: Replication Data for: POLI 784 Final Project

description: This is replication and extension project for POLI 784 course.
DOI: 10.15139/s3/nc5pgv
title: Replication and Extension for Bos et al. (2022) "This One's for the Boys"

description: This is a replication of several analyses of the Bos et al. (2022) article, "This One's For the Boys: How Gendered Political Socialization Limits Girls' Political Ambitions and Interests." I provide my own extension of their project. This replication and extension was completed as part of the requirements for POLI 784 at UNC Chapel Hill.
DOI: 10.5281/zenodo.7878797
title: desmognathus_abditus_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7878796
title: desmognathus_abditus_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7878801
title: desmognathus_ochrophaeus_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7878800
title: desmognathus_ochrophaeus_zanfona_1.fasta.gz

description: .
DOI: 10.34740/kaggle/dsv/5557069
title: 2021 World Population (updated daily)
DOI: 10.5281/zenodo.7878524
title: MUSES Fractional Vegetation Coverage (FVC) Monthly Global 0.05º Geographic Grid Since 1981

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 0.05º spatial resolution and monthly temporal resolution. The MUSES FVC product is provided on Geographic grid and spans from 1981 to 2018 (continuously updated). It was generated from the MUSES LAI product at 0.05º resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. <strong>Dataset Characteristics:</strong> Spatial Coverage: 180º W – 180º E, 90º S – 90º N; Temporal Coverage: 1981 – 2018; Spatial Resolution: 0.05º (approximately 5 km); Temporal Resolution: 1 month; Projection: Geographic; Data Format: HDF; Scale: 0.004; Valid Range: 0 – 250. <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).