cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48597/uebr-tm96
title: Measurement of Potassium at Víznar

description: Measurement of Potassium at Víznar
DOI: 10.48597/uedc-rc98
title: Measurement of Inorganics in precipitation at Víznar

description: Measurement of Inorganics in precipitation at Víznar
DOI: 10.48597/uf5j-hnwx
title: Measurement of Sulphate_corrected at Penausende

description: Measurement of Sulphate_corrected at Penausende
DOI: 10.48597/umdu-naj9
title: Measurement of Sulphate_corrected at Penausende

description: Measurement of Sulphate_corrected at Penausende
DOI: 10.48597/ut77-ksj4
title: Measurement of Inorganics in precipitation at Víznar

description: Measurement of Inorganics in precipitation at Víznar
DOI: 10.48597/uycw-t4k4
title: Measurement of Inorganics in precipitation at Penausende

description: Measurement of Inorganics in precipitation at Penausende
DOI: 10.48597/vh6c-n2cc
title: Measurement of Sodium at Niembro

description: Measurement of Sodium at Niembro
DOI: 10.48597/vr9u-4mn3
title: Measurement of Sulphate_corrected at Niembro

description: Measurement of Sulphate_corrected at Niembro
DOI: 10.48597/w3gm-s4cf
title: Measurement of Inorganics in precipitation at Mahón

description: Measurement of Inorganics in precipitation at Mahón
DOI: 10.48597/wkne-am6f
title: Measurement of Inorganics in precipitation at Víznar

description: Measurement of Inorganics in precipitation at Víznar
DOI: 10.48597/wyk3-5w56
title: Measurement of Inorganics in precipitation at Víznar

description: Measurement of Inorganics in precipitation at Víznar
DOI: 10.5281/zenodo.7535296
title: WeatherPon: A Weather and Machine Learning-based Coupon Recommendation Mechanism in Digital Marketing

description: These are the datasets that we used.
DOI: 10.5281/zenodo.7535295
title: WeatherPon: A Weather and Machine Learning-based Coupon Recommendation Mechanism in Digital Marketing

description: These are the datasets that we used.
DOI: 10.21227/6856-5h18
title: TNCOVID_19

description: Data preprocessing is a fundamental stage in deep learning modeling and serves as the cornerstone of reliable data analytics. These deep learning models require significant amounts of training data to be effective, with small datasets often resulting in overfitting and poor performance on large datasets. One solution to this problem is parallelization in data modeling, which allows the model to fit the training data more effectively, leading to higher accuracy on large data sets and higher performance overall. In this research, we developed a novel approach that effectively deployed tools such as MPI and MPI4Py from parallel computing to handle data preprocessing and deep learning modeling processes. As a case study, the technique is applied to COVID-19 data from state of Tennessee, USA. Finally, the effectiveness of our approach is demonstrated by comparing it with existing methods without parallel computing concepts like MPI4Py. Our results demonstrate promising outcome for the deployment of parallel computing in modeling to minimize high computational cost
DOI: 10.5281/zenodo.7535196
title: Dataset for Personalizing Over-the-Counter Hearing Aids using Pairwise Comparisons

description: This is the initial release of the dataset.
DOI: 10.5281/zenodo.7535197
title: Dataset for Personalizing Over-the-Counter Hearing Aids using Pairwise Comparisons

description: This is the initial release of the dataset.
DOI: 10.5281/zenodo.7535300
title: [IO Islamic 174] Niżâmî's Mathnawîs

description: <strong>Niżâmî's Mathnawîs.</strong> <strong>This manuscript is now IO Islamic 986 in the India Office collections.</strong> <strong>[metadata:</strong> <strong>Hermann Ethé</strong><strong><em>, </em></strong><strong><em>Catalogue of Persian Manuscripts in the Library of the India Office,</em></strong> <strong>2 vols. (Oxford: India Office, 1903): volume 1,</strong> <strong>number 174 here with notations and hyperlinks].</strong> 986 Another set of three mathnawîs by Niżâmî. This copy contains: 1.Makhzan-alasrâr, on fol. 1<sup>b</sup>. 2. Lailâ u Majnûn on fol. 30<sup>b</sup>. 3.Khusrau u Shîrîn, on fol. 80<sup>b</sup>; this last mathnawî is by mistake headed كتاب خسرو و شيرين امير خسرو, but that it is Niżâmî’s, and not Amîr Khusrau’s poem of the same name, we learn from the beginning: خداوند درى ( در read) توفيق بگشاى نظامى را ره توفيق بنماى Copied A.H. 976, the first mathnawî in the month Dhû-alḥijjah (A.D. 1569, May-June), the second in the month Dhû-alḳa’dah (A.D. 1569, April-May), the third in the month Rabî’-althânî (A.D. 1568, September-October), by Muḥammad bin ‘Alâ-aldîn. No. 174, ff. 149, 4 coll., each ll. 21; small, but distinct Nasta’lîḳ; most headings left blank; an illuminated frontispiece at the beginning of each mathnawî; the first two pages most splendidly adorned; size, 11<sup>3/8</sup> in. by 7 in.
DOI: 10.5281/zenodo.7535299
title: [IO Islamic 174] Niżâmî's Mathnawîs

description: <strong>Niżâmî's Mathnawîs.</strong> <strong>This manuscript is now IO Islamic 986 in the India Office collections.</strong> <strong>[metadata:</strong> <strong>Hermann Ethé</strong><strong><em>, </em></strong><strong><em>Catalogue of Persian Manuscripts in the Library of the India Office,</em></strong> <strong>2 vols. (Oxford: India Office, 1903): volume 1,</strong> <strong>number 174 here with notations and hyperlinks].</strong> 986 Another set of three mathnawîs by Niżâmî. This copy contains: 1.Makhzan-alasrâr, on fol. 1<sup>b</sup>. 2. Lailâ u Majnûn on fol. 30<sup>b</sup>. 3.Khusrau u Shîrîn, on fol. 80<sup>b</sup>; this last mathnawî is by mistake headed كتاب خسرو و شيرين امير خسرو, but that it is Niżâmî’s, and not Amîr Khusrau’s poem of the same name, we learn from the beginning: خداوند درى ( در read) توفيق بگشاى نظامى را ره توفيق بنماى Copied A.H. 976, the first mathnawî in the month Dhû-alḥijjah (A.D. 1569, May-June), the second in the month Dhû-alḳa’dah (A.D. 1569, April-May), the third in the month Rabî’-althânî (A.D. 1568, September-October), by Muḥammad bin ‘Alâ-aldîn. No. 174, ff. 149, 4 coll., each ll. 21; small, but distinct Nasta’lîḳ; most headings left blank; an illuminated frontispiece at the beginning of each mathnawî; the first two pages most splendidly adorned; size, 11<sup>3/8</sup> in. by 7 in.
DOI: 10.5281/zenodo.7532965
title: GRCh38 modified reference

description: This is the modified GRCh38 reference generated by fixing the falsely duplicated regions and falsely collapsed regions.
DOI: 10.5281/zenodo.7532964
title: GRCh38 modified reference

description: This is the modified GRCh38 reference generated by fixing the falsely duplicated regions and falsely collapsed regions.
DOI: 10.5281/zenodo.7535205
title: Anthropogenic Bromoform at the Extratropical Tropopause

description: This dataset contains the new emission inventory used for the simulations presented in the paper and the simulation outputs.
DOI: 10.5281/zenodo.7535355
title: [IO Islamic 768] Niżâmî's Mathnawîs

description: <strong>Niżâmî's Mathnawîs.</strong> <strong>This manuscript is now IO Islamic 988 in the India Office collections.</strong> <strong>[metadata:</strong> <strong>Hermann Ethé</strong><strong><em>, </em></strong><strong><em>Catalogue of Persian Manuscripts in the Library of the India Office,</em></strong> <strong>2 vols. (Oxford: India Office, 1903): volume 1,</strong> <strong>number 768 here with notations and hyperlinks].</strong> 988 An incomplete copy of two mathnawîs by Niżâmî. 1.Lailâ u Majnûn, on fol. 1<sup>b</sup>. 2. Khusrau u Shîrîn, on fol. 55<sup>b</sup>. The first mathnawî is dated A.H. 92 (=1092, A.D. 1681), the second is incomplete at the end; its last bait corresponds to No. 141 (973 in this Cat.), fol. 119<sup>b</sup>, l. 12. No. 768, ff. 125, 4 coll., each ll. 21; small, but clear and distinct Nasta’lîḳ; an illuminated frontispiece at the beginning of either mathnawî; the original leaves are put into a modern margin; size, 10<sup>3/8</sup> in. by 6<sup>1/2</sup> in.
DOI: 10.5281/zenodo.7535354
title: [IO Islamic 768] Niżâmî's Mathnawîs

description: <strong>Niżâmî's Mathnawîs.</strong> <strong>This manuscript is now IO Islamic 988 in the India Office collections.</strong> <strong>[metadata:</strong> <strong>Hermann Ethé</strong><strong><em>, </em></strong><strong><em>Catalogue of Persian Manuscripts in the Library of the India Office,</em></strong> <strong>2 vols. (Oxford: India Office, 1903): volume 1,</strong> <strong>number 768 here with notations and hyperlinks].</strong> 988 An incomplete copy of two mathnawîs by Niżâmî. 1.Lailâ u Majnûn, on fol. 1<sup>b</sup>. 2. Khusrau u Shîrîn, on fol. 55<sup>b</sup>. The first mathnawî is dated A.H. 92 (=1092, A.D. 1681), the second is incomplete at the end; its last bait corresponds to No. 141 (973 in this Cat.), fol. 119<sup>b</sup>, l. 12. No. 768, ff. 125, 4 coll., each ll. 21; small, but clear and distinct Nasta’lîḳ; an illuminated frontispiece at the beginning of either mathnawî; the original leaves are put into a modern margin; size, 10<sup>3/8</sup> in. by 6<sup>1/2</sup> in.
DOI: 10.5281/zenodo.7532975
title: 2nd version of modified GRCh38 reference

description: This is the 2nd version of Modified GRCh38 reference that excludes decoys related to FANCD2, DUSP22 and GPRIN2 genes as these are the complex genes.
DOI: 10.5281/zenodo.7532974
title: 2nd version of modified GRCh38 reference

description: This is the 2nd version of Modified GRCh38 reference that excludes decoys related to FANCD2, DUSP22 and GPRIN2 genes as these are the complex genes.
DOI: 10.6084/m9.figshare.21787100.v1
title: data_macro_figshare.xlsx

description: Here we analysed the resistance, resilience, and recovery of aggregate functions and composition of a community exposed to the experimental removal of the giant kelp <em>Macrocystis pyrifera</em>. We studied a species-rich macrobenthic community in a sub-Antarctic perennial kelp forest that regularly thins and recovers during the year. A pulsed loss of giant kelp from extreme destructive storms was mimicked and the understorey was monitored for 12 months.
DOI: 10.6084/m9.figshare.21787100
title: Dataset of breaking down the ecological stability of a giant kelp forest community

description: Here we analysed the resistance, resilience, and recovery of aggregate functions and composition of a community exposed to the experimental removal of the giant kelp <em>Macrocystis pyrifera</em>. We studied a species-rich macrobenthic community in a sub-Antarctic perennial kelp forest that regularly thins and recovers during the year. A pulsed loss of giant kelp from extreme destructive storms was mimicked and the understorey was monitored for 12 months.
DOI: 10.6084/m9.figshare.21787100.v3
title: Dataset of breaking down the ecological stability of a giant kelp forest community

description: Here we analysed the resistance, resilience, and recovery of aggregate functions and composition of a community exposed to the experimental removal of the giant kelp <em>Macrocystis pyrifera</em>. We studied a species-rich macrobenthic community in a sub-Antarctic perennial kelp forest that regularly thins and recovers during the year. A pulsed loss of giant kelp from extreme destructive storms was mimicked and the understorey was monitored for 12 months.
DOI: 10.6084/m9.figshare.21787100.v2
title: data_macro_figshare.xlsx

description: Here we analysed the resistance, resilience, and recovery of aggregate functions and composition of a community exposed to the experimental removal of the giant kelp <em>Macrocystis pyrifera</em>. We studied a species-rich macrobenthic community in a sub-Antarctic perennial kelp forest that regularly thins and recovers during the year. A pulsed loss of giant kelp from extreme destructive storms was mimicked and the understorey was monitored for 12 months.
DOI: 10.5281/zenodo.7316545
title: Dataset: A database of near-field head-related transfer functions based on measurements with a laser spark source

description: This is a database of near-field head-related transfer functions (HRTFs) of an artificial head, measured at four distances (0.2, 0.3, 0.4 and 0.5 m), with 49 positions recorded at each distance, for a total of 196 measurement points. The HRTFs were recorded using an acoustic pulse created by a laser-induced breakdown of air (LIB), which realizes a close to ideal, massless, monopole sound source. The repository contains the original measurement data (raw_data.zip), the derived HRTFs both with (NF_LIB_HRTF_LFE.sofa) and without (NF_LIB_HRTF_measured.sofa) a low-frequency extension (LFE) applied, as well as the MATLAB code used to process the measurement data and to apply the LFE (LIB_HRTF_DB.zip). The database is made publicly available to support future research into nearby sound localization, and virtual/augmented reality applications. Please see the accompanying paper for further details: Marschall et al. (2023), A database of near-field head-related transfer functions based on measurements with a laser spark source, Applied Acoustics.
DOI: 10.5281/zenodo.7316544
title: Dataset: A database of near-field head-related transfer functions based on measurements with a laser spark source

description: This is a database of near-field head-related transfer functions (HRTFs) of an artificial head, measured at four distances (0.2, 0.3, 0.4 and 0.5 m), with 49 positions recorded at each distance, for a total of 196 measurement points. The HRTFs were recorded using an acoustic pulse created by a laser-induced breakdown of air (LIB), which realizes a close to ideal, massless, monopole sound source. The repository contains the original measurement data (raw_data.zip), the derived HRTFs both with (NF_LIB_HRTF_LFE.sofa) and without (NF_LIB_HRTF_measured.sofa) a low-frequency extension (LFE) applied, as well as the MATLAB code used to process the measurement data and to apply the LFE (LIB_HRTF_DB.zip). The database is made publicly available to support future research into nearby sound localization, and virtual/augmented reality applications. Please see the accompanying paper for further details: Marschall et al. (2023), A database of near-field head-related transfer functions based on measurements with a laser spark source, Applied Acoustics.
DOI: 10.6084/m9.figshare.20205638
title: Individual Bacterial Protein Sequence Files

description: Protein FASTA files for individual bacterial strains used to build the 16S_Sample-Matched and 16S_Pooled databases, and to calculate Database Depth for the different samples.
DOI: 10.6084/m9.figshare.20205638.v1
title: Individual Bacterial Protein Sequence Files

description: Protein FASTA files for individual bacterial strains used to build the 16S_Sample-Matched and 16S_Pooled databases, and to calculate Database Depth for the different samples.
DOI: 10.6084/m9.figshare.20164250
title: Global Database Search Results

description: Results of searching a subset of six samples against the Global database.
DOI: 10.6084/m9.figshare.20164250.v1
title: Global Database Search Results

description: Results of searching a subset of six samples against the Global database.
DOI: 10.6084/m9.figshare.20164322
title: 16S_Pooled Database

description: FASTA files for the 16S_Pooled database. These files are for the initial database, which was used to perform an initial search of the data, then proteins that matched at least one spectrum were used to create a refined 16S_Pooled database.
DOI: 10.6084/m9.figshare.20164322.v1
title: 16S_Pooled Database

description: FASTA files for the 16S_Pooled database. These files are for the initial database, which was used to perform an initial search of the data, then proteins that matched at least one spectrum were used to create a refined 16S_Pooled database.
DOI: 10.6084/m9.figshare.20164352
title: 16S_Sample-Matched Databases

description: FASTA files for the 16S_Sample-Matched databases. These files are for the initial database, which was used to perform an initial search of the data, then proteins that matched at least one spectrum were used to create refined 16S_Sample-Matched databases.
DOI: 10.6084/m9.figshare.20164352.v1
title: 16S_Sample-Matched Databases

description: FASTA files for the 16S_Sample-Matched databases. These files are for the initial database, which was used to perform an initial search of the data, then proteins that matched at least one spectrum were used to create refined 16S_Sample-Matched databases.
DOI: 10.6084/m9.figshare.20164394
title: Shotgun_Pooled Database

description: FASTA files for the Shotgun_Pooled database. These files are for the initial database, which was used to perform an initial search of the data, then proteins that matched at least one spectrum were used to create a refined Shotgun_Pooled database.
DOI: 10.6084/m9.figshare.20164394.v1
title: Shotgun_Pooled Database

description: FASTA files for the Shotgun_Pooled database. These files are for the initial database, which was used to perform an initial search of the data, then proteins that matched at least one spectrum were used to create a refined Shotgun_Pooled database.
DOI: 10.6084/m9.figshare.20164403
title: Shotgun_Sample-Matched Databases

description: FASTA files for the Shotgun_Sample-Matched databases. These files are for the initial databases, which were used to perform an initial search of the data, then proteins that matched at least one spectrum were used to create refined Shotgun_Sample-Matched databases.
DOI: 10.6084/m9.figshare.20164403.v1
title: Shotgun_Sample-Matched Databases

description: FASTA files for the Shotgun_Sample-Matched databases. These files are for the initial databases, which were used to perform an initial search of the data, then proteins that matched at least one spectrum were used to create refined Shotgun_Sample-Matched databases.
DOI: 10.6084/m9.figshare.20164415
title: Hybrid Sample-Matched Databases

description: FASTA files for the Hybrid_Sample-Matched databases. These files are for the initial databases, which were used to perform an initial search of the data, then proteins that matched at least one spectrum were used to create refined databases.
DOI: 10.6084/m9.figshare.20164415.v1
title: Hybrid Sample-Matched Databases

description: FASTA files for the Hybrid_Sample-Matched databases. These files are for the initial databases, which were used to perform an initial search of the data, then proteins that matched at least one spectrum were used to create refined databases.
DOI: 10.6084/m9.figshare.20164469
title: 16S_Reference Databases

description: FASTA files for the 16S_Reference databases. These files are for the initial databases, which were used to perform an initial search of the data, then proteins that matched at least one spectrum were used to create a refined 16S_Reference databases.
DOI: 10.6084/m9.figshare.20164469.v1
title: 16S_Reference Databases

description: FASTA files for the 16S_Reference databases. These files are for the initial databases, which were used to perform an initial search of the data, then proteins that matched at least one spectrum were used to create a refined 16S_Reference databases.
DOI: 10.6084/m9.figshare.20173580
title: Human Proteins

description: FASTA file of all human proteins used to build databases in this study.
DOI: 10.6084/m9.figshare.20173580.v1
title: Human Proteins

description: FASTA file of all human proteins used to build databases in this study.
DOI: 10.6084/m9.figshare.20173583
title: Contaminant Proteins

description: FASTA file of all contaminant proteins used to build databases in this study.
DOI: 10.6084/m9.figshare.20173586
title: Bacterial Proteins

description: FASTA files containing all bacterial proteins used to build databases in this study. "NCBI_Bacteria" contains publicly-available protein sequences. "genes_annotated" contains bacterial proteins translated from metagenomic sequencing of the samples.
DOI: 10.6084/m9.figshare.20173589
title: Fungal Proteins

description: FASTA file of fungal proteins from common vaginal fungi, used to build the 16S_Pooled database.
DOI: 10.6084/m9.figshare.20173589.v1
title: Fungal Proteins

description: FASTA file of fungal proteins from common vaginal fungi, used to build the 16S_Pooled database.
DOI: 10.6084/m9.figshare.20173592
title: Trichomonas vaginalis Proteins

description: FASTA file containing T. vaginalis proteins used in this study.
DOI: 10.6084/m9.figshare.20173592.v1
title: Trichomonas vaginalis Proteins

description: FASTA file containing T. vaginalis proteins used in this study.
DOI: 10.6084/m9.figshare.20173598
title: Global Bacterial Proteins

description: FASTA file of bacterial proteins present in the refined Global database. Used to analyze the results of the Global database searches.
DOI: 10.6084/m9.figshare.20173598.v1
title: Global Bacterial Proteins

description: FASTA file of bacterial proteins present in the refined Global database. Used to analyze the results of the Global database searches.
DOI: 10.6084/m9.figshare.20173601
title: Global Fungal Proteins

description: FASTA file of fungal proteins present in the refined Global database. Used to analyze the results of searching the Global database.
DOI: 10.6084/m9.figshare.20173601.v1
title: Global Fungal Proteins

description: FASTA file of fungal proteins present in the refined Global database. Used to analyze the results of searching the Global database.
DOI: 10.6084/m9.figshare.21899019
title: Surf Data WCT 2019 - Final.xlsx

description: This dataset is part of a research study on the effect of pressure on performance in elite surfing. <br> Further description of this dataset will be added upon publication of the research.
DOI: 10.6084/m9.figshare.21267363
title: Identifying the current and future status of freshwater connectivity corridors in the Amazon Basin

description: This repository contains supplementary data and technical documentation for the research article by B. Caldas, M.L. Thieme, N. Shahbol, M. Eduarda Coelho, G. Grill, P.A. Van Damme, R. Aranha, C. Cañas, C. Fagundes, N. Frale, E.E. Herrera-Collazos, C. Jézéquel, M. Montoya, F. Mosquera- Guerra, M. Oliveira-da-Costa, M. Paschoalini, P. Petry, T. Oberdorff, F. Trujillo, P.A. Tedesco, M. Lambert Ribeiro. <strong>Identifying the current and future status of freshwater connectivity corridors in the Amazon Basin</strong>. <em>Conservation Science and Practice</em>. DOI: 10.1111/csp2.12853
DOI: 10.18112/openneuro.ds004401.v1.0.1
title: PS13 Molecular Imaging Brain Atlas (Kim 2021)
DOI: 10.35077/act-ask
title: Neuron Morphology data in .swc format from Patch-seq experiments in mouse cortex, Cell ID 993243528

description: Mouse cortical neurons display diverse morphology, physiology and gene expression profiles. We use a method called Patch-seq, where these three data modalities are assayed simultaneously from the same neuron, to understand how the genetic profile of mouse cortical neuron types corresponds to their morphological and electrophysiological phenotypes. This collection may contain image stacks (TIFF), reconstruction files in image space (.swc, µm), a transformed file (.swc, µm) oriented so that the y axis extends vertically towards the pia surface, and a marker file (.marker, µm) indicating nodes where dendrites were truncated (10), reconstruction was not continued (20), or surface of tissue was closest to soma (30).
description: manual tracing
description: DATASET METADATA: title:'Neuron Morphology data in .swc format from Patch-seq experiments in mouse cortex, Cell ID 993243528', GeneralModality:'cell morphology', Technique:'PATCH-Seq' SPECIMEN METADATA: LocalID:'993243528.0', Species:'mouse', NCBITaxonomy:'NCBI:txid10090', SampleLocalID:'993243528.0', Locations:'VISp1' INSTRUMENT METADATA: MicroscopeType:'NA', MicroscopeManufacturerAndModel:'NA' IMAGE METADATA: xAxis:'NA', yAxis:'NA', zAxis:'NA', stepSizeX:'0.114', stepSizeY:'0.114', stepSizeZ:'0.28'