cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2dzpnr
title: CCDC 2234035: Experimental Crystal Structure Determination

description: Related Article: Hui-Xin Xiao, Pan-Pan Li, Bin Pan, Wu Liang, Fei Du, Yu Yu|2023|J.Org.Chem.|88|5861|doi:10.1021/acs.joc.3c00280
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: 10.26189/fn2y-5y17
title: De-identified Data of 150 South Australian Veterans entering the RSL-SA Advocacy Support Program in 2021
DOI: 10.34740/kaggle/dsv/5628455
title: Youtube Trending Video - Taiwan & Hong Kong
DOI: 10.6084/m9.figshare.22679116.v3
title: DRL_Code_Data.zip

description: This is the raw experiments data of the paper "Deep Online Recommendations for Connected E-taxis by Coupling Trajectory Mining and Reinforcement Learning"
DOI: 10.26189/et3n-p182
title: TikTok Project Data
DOI: 10.34740/kaggle/ds/3228325
title: sabdab-proteins
DOI: 10.26189/tz5p-a971
title: Cancel Culture Research Data
DOI: 10.26189/91zx-4f76
title: Food Allergy and Children Under 8 Years - Appendix A
DOI: 10.5281/zenodo.7903478
title: MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 1km SIN Grid in 2019

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 1 km spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 1 km 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. This dataset is the MUSES FVC product in 2019. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2018</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2020</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2019 Spatial Resolution: 1 km Temporal Resolution: 8 days Projection: Sinusoidal 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).
DOI: 10.5281/zenodo.7903477
title: MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 1km SIN Grid in 2019

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 1 km spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 1 km 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. This dataset is the MUSES FVC product in 2019. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2018</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2020</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2019 Spatial Resolution: 1 km Temporal Resolution: 8 days Projection: Sinusoidal 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).
DOI: 10.26189/9xxh-wd80
title: QoL Food Allergy Children 8 to 12 Years - Appendix B
DOI: 10.26189/4aev-hh73
title: Food Allergy QoL Teenagers -Appendix C
DOI: 10.25345/c5w950z3k
title: MassIVE MSV000091877 - "A Proteomic Study of Salmonella Infection and High Fat Diet on Mouse Liver using Data-Independent Acquisition Mass Spectrometry" Data
title: Data-independent acquisition of mouse liver with four treatments: normal chow diet and healthy (1-5), normal chow diet and inoculated with Salmonella (6-11), high fat diet and healthy (12-16), and high fat diet and inoculated with Salmonella (17-21).
DOI: 10.26189/wvpx-d842
title: Parents QoL Food Allergy - Appendix D
DOI: 10.26189/atxp-2s44
title: QoL Australian Parents Managing A Child With Food Allergy
DOI: 10.34740/kaggle/dsv/5628553
title: Polish-Ukrainian translations from Tatoeba
DOI: 10.6084/m9.figshare.22777052
title: Genomic, functional and structural analyses elucidate evolutionary innovation within the sea anemone 8 toxin family

description: Supplementary files for genomic, transcriptomic and proteomic datasets from sea anemone species <em>Actinia tenebrosa</em> and <em>Telmatactis stephensoni</em>. This includes genome annotations (gff3) for all genes, putative venom genes and sea anemone 8 (SA8) toxin family genes. Sequences are also provided for protein CDS (.aa), nucleotide CDS (.cds) and mRNA transcripts (.fasta). Genomes for <em>A. tenebrosa</em> and <em>T. stephensoni</em> were produced using combination of PacBio long-read (PacBio) and short-read (Illumina) DNA sequencing. Additionally, Hi-C sequencing (Phase Genomics) was performed to generate a chromosomal-level assembly for <em>A. tenebrosa.</em> This also includes alignment files (fasta) used for CAFE, sequence space and phylogenetic analyses: CAFE expansion/contraction tree highlights increased number of expanded gene families <em>in T. stephensoni</em> relative to other sea anemone species. Sequence space of the SA8 family was generated using 102 mature SA8 sequences from 14 actiniarian species spanning three superfamilies. Phylogenetic relationships among 71 sea anemone sequences from the SA8 gene family were inferred under maximum likelihood in IQ-TREE. Sequence space of the SA8 family and ShkT-domain containing sequences (ShK-like proteins, cysteine-rich secretory proteins).
DOI: 10.5281/zenodo.7905513
title: Does attitude toward programming predict computational thinking? Analysis of gender and programming experience effect among engineering students

description: This data was generated during the development of the FDPD project. Data were anonymized.
DOI: 10.5281/zenodo.7905512
title: Does attitude toward programming predict computational thinking? Analysis of gender and programming experience effect among engineering students

description: This data was generated during the development of the FDPD project. Data were anonymized.
DOI: 10.6084/m9.figshare.22776116
title: F-actin-Cell005-Cell008

description: 20-time points of structured illumination microscopy F-actin data
DOI: 10.6084/m9.figshare.21378674
title: Content validation template (CVT)

description: We propose a new method of questionnaire content validation via the content validation template (CVT). The CVT automatically rejects all items with poor item-level content validity index (I-CVI) from the raw dataset, then compute the overall final dataset for Gwet’s chance-corrected Agreement Coefficient 2 (AC<sub>2</sub>) and standard error (due to raters’ variation). Concurrent validation with two existing statistical software vindicate CVT’s accuracy for varying number of items, raters and rating scale. Built within a regular Excel, CVT offers most researchers a viable option for questionnaire content validation through robust inferential statistics that only require raw data entry; no manual calculations.
DOI: 10.6084/m9.figshare.21378674.v1
title: Content validation template (CVT)

description: We propose a new method of questionnaire content validation via the content validation template (CVT). The CVT automatically rejects all items with poor item-level content validity index (I-CVI) from the raw dataset, then compute the overall final dataset for Gwet’s chance-corrected Agreement Coefficient 2 (AC<sub>2</sub>) and standard error (due to raters’ variation). Concurrent validation with two existing statistical software vindicate CVT’s accuracy for varying number of items, raters and rating scale. Built within a regular Excel, CVT offers most researchers a viable option for questionnaire content validation through robust inferential statistics that only require raw data entry; no manual calculations.
DOI: 10.6084/m9.figshare.22776098
title: F-actin-Cell001-Cell004

description: 20-time points of structured illumination microscopy F-actin data
DOI: 10.5281/zenodo.7539634
title: Data and scripts for Fudan-NSA cloud fraction scheme

description: Data and scripts for preparing the Fudan-NSA cloud fraction scheme.
DOI: 10.5281/zenodo.7539633
title: Data and scripts for Fudan-NSA cloud fraction scheme

description: Data and scripts for preparing the Fudan-NSA cloud fraction scheme.
DOI: 10.17909/r20x-7268
title: Score-based LIkelihood Characterization (SLIC)
DOI: 10.17909/yj2m-1024
title: Score-based LIkelihood Characterization (SLIC) (JWST data)
DOI: 10.25582/data.2022-05.2511975/1932715
title: Data for EMSL Project 51819 from May 2022
DOI: 10.25582/data.2022-05.2512051/1972598
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2512262/1972599
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2512283/1972600
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2511883/1972601
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2511974/1972602
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2512002/1972603
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2512027/1972604
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2512034/1972605
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2512044/1972606
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2512000/1972607
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2512282/1972608
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2512287/1972609
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2511877/1972610
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2511934/1972611
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2511969/1972612
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2512218/1972613
title: Data for EMSL Project 50567 from May 2022
DOI: 10.25582/data.2022-05.2511940/1972614
title: Data for EMSL Project 50567 from May 2022
DOI: 10.5281/zenodo.7829642
title: Anypodetus leucothrix and Anypodetus londti species descriptions in SDD format

description: Natural-language species description of Anypodetus leucothrix and Anypodetus londti in SDD format exported from Lucid Builder 4.0.
description: {"references": ["Dikow, T. and Dubus, M. 2023. A review of the assassin-fly genus Anypodetus Hermann, 1907 with the description of a new species (Insecta, Diptera, Asilidae). African Invertebrates 64(2): 165\u2013206. doi:10.3897/AfrInvertebr.64.104283."]}
DOI: 10.5281/zenodo.7829641
title: Anypodetus leucothrix and Anypodetus londti species descriptions in SDD format

description: Natural-language species description of Anypodetus leucothrix and Anypodetus londti in SDD format exported from Lucid Builder 4.0.
description: {"references": ["Dikow, T. and Dubus, M. 2023. A review of the assassin-fly genus Anypodetus Hermann, 1907 with the description of a new species (Insecta, Diptera, Asilidae). African Invertebrates 64(2): 165\u2013206. doi:10.3897/AfrInvertebr.64.104283."]}
DOI: 10.5281/zenodo.7905521
title: Stellar models for "A prescription for the asteroseismic surface correction" by Li, Yaguang et al. (2023)

description: This folder publishes the stellar models utilized in Li et al. (2023) The stellar models presented here encompass a range of parameters: mass (0.7, 2.3) solar mass, Yinit (0.22, 0.32), [M/H] within (-0.94, 0.56) dex, and amlt (1.3, 2.7). All evolutionary tracks are calculated up to the point on the RGB when the p-mode large separtion Dnu equals 2 muHz. Each model entry (row) are presented with classical observables (Teff, radius, luminosity, ...) and radial modes (mode_freq, mode_inertia, mode_n, ...) For a comprehensive description of the stellar models, please refer to the paper. The folder contains three sets of stellar models. These models are stored in the "npy" format. They can be read in Python using the following code: "import numpy as np; data = np.load(filename, allow_pickle=True);" <br> - grid_models_surface_effect_corrected/tracks*.npy This set includes stellar models with frequencies that have surface effect removed. - grid_models_surface_effect_uncorrected/tracks*.npy This set includes stellar models with frequencies in the original uncorrected format. - stats_models_for_fDnu_ANN_weights.npy This file is a statistical stellar model fitted by an artificial neural network with fully connected layers. It can be used for calculating fDnu, the correction factor of the Dnu scaling relation, or for doing any stellar parameter inference using global parameters (such as numax, Dnu, Teff, lum, etc.). More details and example use cases can be found at https://github.com/parallelpro/surface/
DOI: 10.5281/zenodo.7905520
title: Stellar models for "A prescription for the asteroseismic surface correction" by Li, Yaguang et al. (2023)

description: This folder publishes the stellar models utilized in Li et al. (2023) The stellar models presented here encompass a range of parameters: mass (0.7, 2.3) solar mass, Yinit (0.22, 0.32), [M/H] within (-0.94, 0.56) dex, and amlt (1.3, 2.7). All evolutionary tracks are calculated up to the point on the RGB when the p-mode large separtion Dnu equals 2 muHz. Each model entry (row) are presented with classical observables (Teff, radius, luminosity, ...) and radial modes (mode_freq, mode_inertia, mode_n, ...) For a comprehensive description of the stellar models, please refer to the paper. The folder contains three sets of stellar models. These models are stored in the "npy" format. They can be read in Python using the following code: "import numpy as np; data = np.load(filename, allow_pickle=True);" <br> - grid_models_surface_effect_corrected/tracks*.npy This set includes stellar models with frequencies that have surface effect removed. - grid_models_surface_effect_uncorrected/tracks*.npy This set includes stellar models with frequencies in the original uncorrected format. - stats_models_for_fDnu_ANN_weights.npy This file is a statistical stellar model fitted by an artificial neural network with fully connected layers. It can be used for calculating fDnu, the correction factor of the Dnu scaling relation, or for doing any stellar parameter inference using global parameters (such as numax, Dnu, Teff, lum, etc.). More details and example use cases can be found at https://github.com/parallelpro/surface/
DOI: 10.6084/m9.figshare.22777217
title: Su et al-JAE-2023.xlsx

description: <em>Chilo suppressali</em>s is a highly destructive insect pest of rice crops. Chemical insecticides have been used as an effective method for controlling this pest. In this study, we evaluated the susceptibility of seven field populations of <em>C. suppressalis</em> from three regions in Hubei Province, China, to four different insecticides over a period of four years (2019-2022). Our results showed that the populations of <em>C. suppressalis</em> in these areas have evolved low to high levels of resistance to abamectin (Resistant Ratio, RR = 8.5-413.4). Furthermore, the field populations were susceptible to high levels of resistance to chlorantraniliprole (RR = 2.0-401.6) and showed moderate levels of resistance to triazophos (RR = 56.9-78.7) and chlorpyrifos (RR = 10.6-54.5). Correlation analysis indicated significant positive correlations between the susceptibility of abamectin and chlorantraniliprole and chlorpyrifos, as well as chlorpyrifos and chlorantraniliprole, and triazophos. This study provides valuable information on the current resistance status of field populations of <em>C. suppressalis</em>, which can aid in the judicious use of these insecticides and serve as an important reference for effective resistance management strategies.
DOI: 10.6084/m9.figshare.22777217.v1
title: Su et al-JAE-2023.xlsx

description: <em>Chilo suppressali</em>s is a highly destructive insect pest of rice crops. Chemical insecticides have been used as an effective method for controlling this pest. In this study, we evaluated the susceptibility of seven field populations of <em>C. suppressalis</em> from three regions in Hubei Province, China, to four different insecticides over a period of four years (2019-2022). Our results showed that the populations of <em>C. suppressalis</em> in these areas have evolved low to high levels of resistance to abamectin (Resistant Ratio, RR = 8.5-413.4). Furthermore, the field populations were susceptible to high levels of resistance to chlorantraniliprole (RR = 2.0-401.6) and showed moderate levels of resistance to triazophos (RR = 56.9-78.7) and chlorpyrifos (RR = 10.6-54.5). Correlation analysis indicated significant positive correlations between the susceptibility of abamectin and chlorantraniliprole and chlorpyrifos, as well as chlorpyrifos and chlorantraniliprole, and triazophos. This study provides valuable information on the current resistance status of field populations of <em>C. suppressalis</em>, which can aid in the judicious use of these insecticides and serve as an important reference for effective resistance management strategies.
DOI: 10.5281/zenodo.7905557
title: Supplementary File: followed by Predicting Religious Undergraduates' Career Development: The Salient Roles of Religious Calling, Life Satisfaction, and Quest Religiosity

description: Supplementary File: followed by Predicting Religious Undergraduates’ Career Development: The Salient Roles of Religious Calling, Life Satisfaction, and Quest Religiosity
DOI: 10.5281/zenodo.7905556
title: Supplementary File: followed by Predicting Religious Undergraduates' Career Development: The Salient Roles of Religious Calling, Life Satisfaction, and Quest Religiosity

description: Supplementary File: followed by Predicting Religious Undergraduates’ Career Development: The Salient Roles of Religious Calling, Life Satisfaction, and Quest Religiosity
DOI: 10.6084/m9.figshare.22777265
title: Figure data

description: The figure data generated in this study
DOI: 10.6084/m9.figshare.22777265.v1
title: Figure data

description: The figure data generated in this study
DOI: 10.6084/m9.figshare.22777275
title: Additional file 1 of Convergence of YAP/TAZ, TEAD and TP63 activity is associated with bronchial premalignant severity and progression

description: Additional file 1: Supplementary Table S1. HBEC patient info. Supplementary Table S2. siRNA information. Supplementary Table S3. ChIP-qPCR primers. Supplementary Table S4. TF amplification frequencies in TCGA LUSC. Supplementary Table S5. TF overexpression in TCGA LUSC compared to normal samples. Supplementary Table S6. Top enriched TFs by BART and ChEA3 among the top 500 genes upreguatled with histological grades (BART results were ranked by Irwin Hall p-value. ChEA3 results were ranked by the MeanRank results). Supplementary Table S7. Differential expression results for the TEAD-TP63 directly regulated genes. Supplementary Table S8. Differential expression results for the MHC II genes (shown in Figure 5C) by progression status in PML datasets.
DOI: 10.6084/m9.figshare.22777275.v1
title: Additional file 1 of Convergence of YAP/TAZ, TEAD and TP63 activity is associated with bronchial premalignant severity and progression

description: Additional file 1: Supplementary Table S1. HBEC patient info. Supplementary Table S2. siRNA information. Supplementary Table S3. ChIP-qPCR primers. Supplementary Table S4. TF amplification frequencies in TCGA LUSC. Supplementary Table S5. TF overexpression in TCGA LUSC compared to normal samples. Supplementary Table S6. Top enriched TFs by BART and ChEA3 among the top 500 genes upreguatled with histological grades (BART results were ranked by Irwin Hall p-value. ChEA3 results were ranked by the MeanRank results). Supplementary Table S7. Differential expression results for the TEAD-TP63 directly regulated genes. Supplementary Table S8. Differential expression results for the MHC II genes (shown in Figure 5C) by progression status in PML datasets.
DOI: 10.6084/m9.figshare.22777278
title: Additional file 2 of Convergence of YAP/TAZ, TEAD and TP63 activity is associated with bronchial premalignant severity and progression

description: Additional file 2: Supplementary Figure 1. TP63 isoform expression levels in TCGA-LUSC and in bronchial PML biopsy data related to Figure 1. Supplementary Figure 2. ChIP-seq analysis of YAP/TEAD/TP63 chromatin binding profiles related to Figure 2. Supplementary Figure 3. Transcriptomic analysis of TEAD-TP63 direct regulated target genes related to Figure 3. Supplementary Figure 4. Transcriptomic analysis of TEAD-TP63 direct regulated target genes in human bronchial PML data and lung scRNA-seq data related to Figure 4. Supplementary Figure 5. Analysis of CIITA in human bronchial PML data and lung scRNAseq data related to Figure 5.
DOI: 10.6084/m9.figshare.22777278.v1
title: Additional file 2 of Convergence of YAP/TAZ, TEAD and TP63 activity is associated with bronchial premalignant severity and progression

description: Additional file 2: Supplementary Figure 1. TP63 isoform expression levels in TCGA-LUSC and in bronchial PML biopsy data related to Figure 1. Supplementary Figure 2. ChIP-seq analysis of YAP/TEAD/TP63 chromatin binding profiles related to Figure 2. Supplementary Figure 3. Transcriptomic analysis of TEAD-TP63 direct regulated target genes related to Figure 3. Supplementary Figure 4. Transcriptomic analysis of TEAD-TP63 direct regulated target genes in human bronchial PML data and lung scRNA-seq data related to Figure 4. Supplementary Figure 5. Analysis of CIITA in human bronchial PML data and lung scRNAseq data related to Figure 5.
DOI: 10.6084/m9.figshare.22777304
title: Additional file 1 of Patient experience and repeatability of measurements made with the Pentacam HR in patients with keratoconus

description: Supplementary Material 1