cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20639608
title: Analysis of Mouse Vocal Communication (AMVOC): a deep, unsupervised method for rapid detection, analysis and classification of ultrasonic vocalisations

description: Some aspects of the neural mechanisms underlying mouse ultrasonic vocalisations (USVs) are a useful model for the neurobiology of human speech and speech-related disorders. Much of the research on vocalisations and USVs is limited to offline methods and supervised classification of USVs, hindering the discovery of new types of vocalisations and the study of real-time free behaviour. To address these issues, we developed AMVOC (Analysis of Mouse VOcal Communication) as a free, open-source software to detect and analyse USVs. When compared to hand-annotated ground-truth USV data, AMVOC’s detection functionality (both offline and online) has high accuracy and outperforms leading methods in noisy conditions. AMVOC also includes an unsupervised deep learning approach that facilitates discovery and analysis of USV data by training a model and clustering USVs based on latent features extracted by a convolutional autoencoder. The clustering is visualised in a graphical user interface (GUI) which allows users to evaluate clustering performance. These results can be used to explore the vocal repertoire space of individual animals. In this way, AMVOC will facilitate vocal analyses in a broader range of experimental conditions and allow users to develop previously inaccessible experimental designs for the study of mouse vocal behaviour.
DOI: 10.6084/m9.figshare.20639608.v1
title: Analysis of Mouse Vocal Communication (AMVOC): a deep, unsupervised method for rapid detection, analysis and classification of ultrasonic vocalisations

description: Some aspects of the neural mechanisms underlying mouse ultrasonic vocalisations (USVs) are a useful model for the neurobiology of human speech and speech-related disorders. Much of the research on vocalisations and USVs is limited to offline methods and supervised classification of USVs, hindering the discovery of new types of vocalisations and the study of real-time free behaviour. To address these issues, we developed AMVOC (Analysis of Mouse VOcal Communication) as a free, open-source software to detect and analyse USVs. When compared to hand-annotated ground-truth USV data, AMVOC’s detection functionality (both offline and online) has high accuracy and outperforms leading methods in noisy conditions. AMVOC also includes an unsupervised deep learning approach that facilitates discovery and analysis of USV data by training a model and clustering USVs based on latent features extracted by a convolutional autoencoder. The clustering is visualised in a graphical user interface (GUI) which allows users to evaluate clustering performance. These results can be used to explore the vocal repertoire space of individual animals. In this way, AMVOC will facilitate vocal analyses in a broader range of experimental conditions and allow users to develop previously inaccessible experimental designs for the study of mouse vocal behaviour.
DOI: 10.25345/c5b853t5p
title: MassIVE MSV000091503 - A MARK4-FTO-PKR axis mediates cap-dependent translation of stress related proteins on cytoskeletal ribosomes in hyperacute stress in cancer cells
title: SILAC labelled peptides from control and UV or 2-deoxy glucose treated A549 cells. Control is light labelled and treatment groups are heavy labelled. Fractions are as per below: UV1: APM-0331-2 to APM-0331-6 UV2: APM-0331-12 to APM-0331-16 2DG1: APM-0331-7 to APM-0331-11 2DG2: APM-0331-17 to APM-0331-21
DOI: 10.5281/zenodo.7636104
title: Cellular and molecular heterogeneities and signatures, and pathological trajectories of fatal COVID-19 lungs defined by spatial single-cell transcriptome analysis

description: Spatial in-situ data analysis.
DOI: 10.5281/zenodo.7636103
title: Cellular and molecular heterogeneities and signatures, and pathological trajectories of fatal COVID-19 lungs defined by spatial single-cell transcriptome analysis

description: Spatial in-situ data analysis.
DOI: 10.5517/ccdc.csd.cc29yd8y
title: CCDC 2143410: Experimental Crystal Structure Determination

description: Related Article: Qian-Wen Li, Le-Yu Bi, Mohamed Saber Lassoued, Qian-Cheng Luo, Rong Yan, Xin-Kai Ding, Gao-Yang Gou, Yan-Zhen Zheng|2023|Nanoscale|15|5265|doi:10.1039/D2NR06996B
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.cc2bkf6k
title: CCDC 2161698: Experimental Crystal Structure Determination

description: Related Article: André Mang, Nils Rotthowe, Katawoura Beltako, Michael Linseis, Fabian Pauly, Rainer F. Winter|2023|Nanoscale|15|5305|doi:10.1039/D2NR05670D
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.cc2bkf8m
title: CCDC 2161700: Experimental Crystal Structure Determination

description: Related Article: André Mang, Nils Rotthowe, Katawoura Beltako, Michael Linseis, Fabian Pauly, Rainer F. Winter|2023|Nanoscale|15|5305|doi:10.1039/D2NR05670D
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.cc2bkf9n
title: CCDC 2161701: Experimental Crystal Structure Determination

description: Related Article: André Mang, Nils Rotthowe, Katawoura Beltako, Michael Linseis, Fabian Pauly, Rainer F. Winter|2023|Nanoscale|15|5305|doi:10.1039/D2NR05670D
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.cc2bkfcq
title: CCDC 2161703: Experimental Crystal Structure Determination

description: Related Article: André Mang, Nils Rotthowe, Katawoura Beltako, Michael Linseis, Fabian Pauly, Rainer F. Winter|2023|Nanoscale|15|5305|doi:10.1039/D2NR05670D
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.cc2d17rg
title: CCDC 2205735: Experimental Crystal Structure Determination

description: Related Article: Zhihui Feng, Dongxue Zhang, Hui Guo, Wenqing Su, Yupeng Tian, Xiaohe Tian|2023|Nanoscale|15|5486|doi:10.1039/D2NR05392F
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.cc2d8f15
title: CCDC 2212626: Experimental Crystal Structure Determination

description: Related Article: Sota Funaki, Tokuhisa Kawawaki, Tomoshige Okada, Kana Takemae, Sakiat Hossain, Yoshiki Niihori, Takumi Naito, Makito Takagi, Tomomi Shimazaki, Soichi Kikkawa, Seiji Yamazoe, Masanori Tachikawa, Yuichi Negishi|2023|Nanoscale|15|5201|doi:10.1039/D2NR06952K
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.cc29yd9z
title: CCDC 2143411: Experimental Crystal Structure Determination

description: Related Article: Qian-Wen Li, Le-Yu Bi, Mohamed Saber Lassoued, Qian-Cheng Luo, Rong Yan, Xin-Kai Ding, Gao-Yang Gou, Yan-Zhen Zheng|2023|Nanoscale|15|5265|doi:10.1039/D2NR06996B
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.cc2f4v0g
title: CCDC 2238975: Experimental Crystal Structure Determination

description: Related Article: Zhipeng Zhang, Jin-Feng Liao, Guichuan Xing|2023|Nanoscale|15|5241|doi:10.1039/D2NR06975J
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.cc2f4v1h
title: CCDC 2238976: Experimental Crystal Structure Determination

description: Related Article: Zhipeng Zhang, Jin-Feng Liao, Guichuan Xing|2023|Nanoscale|15|5241|doi:10.1039/D2NR06975J
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.cc2f4v2j
title: CCDC 2238977: Experimental Crystal Structure Determination

description: Related Article: Zhipeng Zhang, Jin-Feng Liao, Guichuan Xing|2023|Nanoscale|15|5241|doi:10.1039/D2NR06975J
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.7693938
title: igvf_05_ultra_megalodon

description: igvf_05_ultra_0_mod_mappings.5mC.sorted.bam igvf_05_ultra_0_mod_mappings.5mC.sorted.bam.bai
DOI: 10.5281/zenodo.7693937
title: igvf_05_ultra_megalodon

description: igvf_05_ultra_0_mod_mappings.5mC.sorted.bam igvf_05_ultra_0_mod_mappings.5mC.sorted.bam.bai
DOI: 10.25921/2czh-w976
title: EM304 Water Column Sonar Data Collected During EX2205
DOI: 10.6084/m9.figshare.22290787
title: Data and wilcoxon tests.xlsx

description: The excel file compiles the number and frequency of words and terms related to digitalization and remote working found in the annual reports (ARs) of 173 UK banks from 2018-2020. Annual reports are downloaded from home websites of the banks. Wilcoxon signed-rank test and sentiment analysis are utilized to test whether COVID-19 has significantly impacted the word frequencies pertained to digitalization and RW in ARs of 173 banks in the UK from 2018 to 2020.
DOI: 10.18739/a2n29p78f
title: A dataset of 512x512 tundra lakes imagery and binary masks from Sentinel-1 in the Yamal and Alaska areas, summer, 2015-2022

description: Data are available at: arcticdata.io/data/10.18739/A2N29P78F Permafrost tundra contains more than twice as much carbon as is currently in the atmosphere and is warming six times as fast as the global mean. Tundra lakes dynamics is a robust indicator of Global climate processes and still not well understood. Satellite data, particularly, from synthetic aperture radar (SAR) are a great source for tundra lakes recognition and their changes monitoring. However, manual analysis of their boundaries can be slow and inefficient, therefore reliable automated algorithms are required. This dataset aimed to fill the gap of the ground truth satellite images for algorithms training and validation and contains synthetic aperture radar imagery of tundra lakes from Sentonel-1 complemented with manually labeled masks of the lakes. The dataset covers two test sites in Yamal and Alaska areas for the summer months of 2015-2022. The images are generated for machine learning algorithms with a spatial resolution of 512x512 pixels.
DOI: 10.5281/zenodo.7739941
title: MUSES Leaf Area Index (LAI) Monthly Global 500m SIN Grid in 2017

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 LAI product at 500m spatial resolution and monthly temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2017. Please <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2016</strong></em><strong>, </strong>and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2018</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2017 Spatial Resolution: 500m Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7739940
title: MUSES Leaf Area Index (LAI) Monthly Global 500m SIN Grid in 2017

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 LAI product at 500m spatial resolution and monthly temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2017. Please <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2016</strong></em><strong>, </strong>and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2018</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2017 Spatial Resolution: 500m Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.25919/05ng-y229
title: Parkes observations for project P960 semester 2022OCTS_06

description: We aim to carry out receiver pointing and characterisation tests of Parkes receivers. Typically, these tests are carried out after the receiver package is installed, but time does not always allow for proper characterisation. Receivers for consideration include UWL, MARS and 13MM packages. In addition to cross-referencing C007 for flux calibration via pointing, we aim to conduct gain-elevation and system temperature experiments using the Moon, to ensure users of the Parkes Observatory have the most accurate information available for calibration purposes.
DOI: 10.6084/m9.figshare.21824580.v4
title: Melt rate time series from Totten Ice Shelf

description: ApRES melt rate time series from the Totten Ice Shelf, sites TI01, TI02, TI04, TI05 and updated bathymetry as published in Vaňková et al. Please cite the following paper if using this data:<br> Vaňková I., J. Paul Winberry, S. Cook, K. W. Nicholls, C. A. Greene, B. K. Galton-Fenzi. High and highly variable basal<br> melting observed at Totten Ice Shelf, East Antarctica. Submitted. <br> The melt rate data will be eventually archived more systematically here: https://data.aad.gov.au/metadata/records/fulldisplay/AAS_4436_Totten_Glacier_ApRES <br> Both bathymetry files have a x (PS71), y(PS71), and bed variable. "totten_bathymetry.nc" is 2km resolution and output of the inversion. "totten_bathymetry_bm.nc" is the 2km inversion results interpolated onto the bedmachine grid.
DOI: 10.5519/qd.1ziwojpx
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (710 records)
DOI: 10.6085/aa/bckx00_xxxix03xmsr01_20210707.50.1
title: MARINe/PISCO: Intertidal: site temperature data: Bob Creek, Oregon (BCKX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Bob Creek, Oregon by MARINe/PISCO. Measurements were collected using HOBO Tidbit MX Water Temperature 400ft Data Logger (Onset Computer Corp. MX2203) beginning 2021-07-12. Site temperature loggers are bolted down in a wire cage at various locations within each site. Mussel growth temperature loggers are bolted down in a wire cage at high, mid, or low positions within a mussel bed. Temperature is recorded at 10 or 15 minute intervals.
DOI: 10.6085/aa/bckx00_xxxix03xmsr01_20210707.40.1
title: (:unkn)
DOI: 10.6085/aa/carx00_xxxix03xmsr01_20210707.50.1
title: MARINe/PISCO: Intertidal: site temperature data: Cape Arago, Oregon (CARX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Cape Arago, Oregon by MARINe/PISCO. Measurements were collected using HOBO Tidbit MX Water Temperature 400ft Data Logger (Onset Computer Corp. MX2203) beginning 2021-07-11. Site temperature loggers are bolted down in a wire cage at various locations within each site. Mussel growth temperature loggers are bolted down in a wire cage at high, mid, or low positions within a mussel bed. Temperature is recorded at 10 or 15 minute intervals.
DOI: 10.6085/aa/carx00_xxxix03xmsr01_20210707.40.1
title: (:unkn)
DOI: 10.6085/aa/ianmxx_xxxix01xmsr01_20210407.50.1
title: MARINe/PISCO: Intertidal: site temperature data: Andrew Molera, California (IANMXX)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Andrew Molera, California by MARINe/PISCO. Measurements were collected using HOBO Pendant MX Water Temperature Data Logger (Onset Computer Corp. MX2201) beginning 2021-04-30. Site temperature loggers are bolted down in a wire cage at various locations within each site. Mussel growth temperature loggers are bolted down in a wire cage at high, mid, or low positions within a mussel bed. Temperature is recorded at 10 or 15 minute intervals.
DOI: 10.6085/aa/ianmxx_xxxix01xmsr01_20210407.40.1
title: (:unkn)
DOI: 10.6085/aa/ianmxx_xxxix01xmsr01_20211124.50.1
title: MARINe/PISCO: Intertidal: site temperature data: Andrew Molera, California (IANMXX)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Andrew Molera, California by MARINe/PISCO. Measurements were collected using HOBO Pendant MX Water Temperature Data Logger (Onset Computer Corp. MX2201) beginning 2021-12-03. Site temperature loggers are bolted down in a wire cage at various locations within each site. Mussel growth temperature loggers are bolted down in a wire cage at high, mid, or low positions within a mussel bed. Temperature is recorded at 10 or 15 minute intervals.
DOI: 10.6085/aa/ianmxx_xxxix01xmsr01_20211124.40.1
title: (:unkn)
DOI: 10.6085/aa/ianmxx_xxxix01xmsr01_20220331.50.1
title: MARINe/PISCO: Intertidal: site temperature data: Andrew Molera, California (IANMXX)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Andrew Molera, California by MARINe/PISCO. Measurements were collected using HOBO Pendant MX Water Temperature Data Logger (Onset Computer Corp. MX2201) beginning 2022-04-21. Site temperature loggers are bolted down in a wire cage at various locations within each site. Mussel growth temperature loggers are bolted down in a wire cage at high, mid, or low positions within a mussel bed. Temperature is recorded at 10 or 15 minute intervals.
DOI: 10.6085/aa/ianmxx_xxxix01xmsr01_20220331.40.1
title: (:unkn)