cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.znu7du
title: Occurrence Download

description: A dataset containing 3954 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-87.4014240999999998 39.4554234000000008, -87.4014240999999998 39.4591250100000011, -87.4014240999999998 39.4631791500000020, -87.4014240999999998 39.4661756900000000, -87.4014240999999998 39.4686434300000002, -87.4014240999999998 39.4730501000000018, -87.3991253100000023 39.4730501000000018, -87.3948802700000016 39.4730501000000018, -87.3916964900000011 39.4730501000000018, -87.3888664600000027 39.4730501000000018, -87.3849751799999979 39.4730501000000018, -87.3826757799999996 39.4730501000000018, -87.3787851000000018 39.4730501000000018, -87.3787851000000018 39.4691722299999981, -87.3787851000000018 39.4668807600000022, -87.3787851000000018 39.4631791500000020, -87.3787851000000018 39.4608876799999990, -87.3787851000000018 39.4577148699999967, -87.3787851000000018 39.4554234000000008, -87.3824989000000016 39.4554234000000008, -87.3876283299999983 39.4554234000000008, -87.3911658600000010 39.4554234000000008, -87.3971796699999999 39.4554234000000008, -87.4014240999999998 39.4554234000000008))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 3954 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0099387-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yx5kxb
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Material sample",
 "BasisOfRecord is Specimen",
 "BasisOfRecord is Machine Observation"
 ]
 },
 "Geometry POLYGON((-65.83008 -60.19616,-16.34766 -60.67318,-15.11719 -42.81152,-13.71094 -12.89749,-31.28906 10.83331,-43.24219 24.84657,-38.32031 36.87962,-25.83984 65.58572,-36.38672 67.54217,-47.63672 67.54217,-68.68652 67.25506,-69.16992 65.54937,-77.21191 64.68032,-78.00293 63.33241,-77.3877 62.20651,-72.68555 59.04055,-70.13672 53.85253,-76.24512 48.95137,-78.83789 41.83683,-82.44141 37.30028,-95.80078 33.57801,-101.77734 27.21556,-98.10791 18.16673,-94.81201 17.28771,-90.06592 14.96601,-87.60498 15.00846,-85.18799 13.94473,-84.35303 10.2933,-82.33154 8.68964,-81.10107 8.47237,-80.52979 8.6462,-79.29932 9.25394,-78.46436 8.9936,-77.03613 7.4932,-69.60937 2.1089,-50.97656 -14.26438,-68.99414 -40.5138,-72.1582 -51.01375,-68.4668 -54.41893,-65.83008 -60.19616))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Mesothuria gargantua Deichmann, 1930"
 ]
}

 The dataset includes 4 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0197498-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k2jpa5
title: Occurrence Download

description: A dataset containing 265 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-117.0937985999999995 32.7040373000000031, -117.0937985999999995 32.7055408700000001, -117.0937985999999995 32.7062926600000026, -117.0937985999999995 32.7073666399999965, -117.0937985999999995 32.7082795199999978, -117.0937985999999995 32.7094072000000011, -117.0929931999999951 32.7094072000000011, -117.0919730399999992 32.7094072000000011, -117.0911139600000013 32.7094072000000011, -117.0902548800000034 32.7094072000000011, -117.0891273299999966 32.7094072000000011, -117.0883219400000002 32.7094072000000011, -117.0868722400000053 32.7094072000000011, -117.0861205399999960 32.7094072000000011, -117.0848856000000069 32.7094072000000011, -117.0848856000000069 32.7086017199999972, -117.0848856000000069 32.7075277400000033, -117.0848856000000069 32.7068296500000031, -117.0848856000000069 32.7058630699999995, -117.0848856000000069 32.7051112799999970, -117.0848856000000069 32.7040373000000031, -117.0859594599999980 32.7040373000000031, -117.0875702400000051 32.7040373000000031, -117.0885904000000011 32.7040373000000031, -117.0892884099999947 32.7040373000000031, -117.0908455000000004 32.7040373000000031, -117.0921878099999986 32.7040373000000031, -117.0937985999999995 32.7040373000000031))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 265 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0092016-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b2xjef
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Parasenecio kangxianensis (Z.Ying Zhang & Y.H.Guo) Y.L.Chen"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0331363-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.saws3f
title: Occurrence Download

description: A dataset containing 10393 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-117.2577655000000050 32.7191639999999992, -117.2577655000000050 32.7225099200000002, -117.2577655000000050 32.7261346700000004, -117.2577655000000050 32.7289229399999968, -117.2577655000000050 32.7307353200000009, -117.2577655000000050 32.7332447599999981, -117.2577655000000050 32.7367301000000026, -117.2549703800000032 32.7367301000000026, -117.2530138000000051 32.7367301000000026, -117.2507777000000004 32.7367301000000026, -117.2477030700000000 32.7367301000000026, -117.2437898999999959 32.7367301000000026, -117.2437898999999959 32.7343600700000010, -117.2437898999999959 32.7310141500000000, -117.2437898999999959 32.7287835300000012, -117.2437898999999959 32.7266923299999988, -117.2437898999999959 32.7237646499999997, -117.2437898999999959 32.7211157899999989, -117.2437898999999959 32.7191639999999992, -117.2474235600000014 32.7191639999999992, -117.2496596499999981 32.7191639999999992, -117.2531535499999933 32.7191639999999992, -117.2552498900000018 32.7191639999999992, -117.2577655000000050 32.7191639999999992))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 10393 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0092019-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cqzfx8
title: Occurrence Download

description: A dataset containing 2424840 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 2424840 records from 2292 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0331367-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7ewm5q
title: Occurrence Download

description: A dataset containing 483544 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "OccurrenceStatus is Present",
 "TaxonKey is Apidae"
 ]
}

 The dataset includes 483544 records from 278 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0062129-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.27960681
title: Effectiveness of neuro-feedback on Alzheimer’s rehabilitation: a bibliometric analysis

description: Alzheimer’s Disease (AD) is a neurodegenerative disorder with limited treatment options. Neurofeedback, a technique that trains brainwaves, has shown promise in addressing cognitive impairments. To conduct a bibliometric analysis to explore the current research on neurofeedback as a treatment for AD. A systematic literature review was performed based on PRISMA guidelines on 142 papers. Different bibliometric parameters like the author’s country, author names, keywords, journal names, and country of citations were analyzed, and a network visualization chart was generated to understand the correlation of Alzheimer-related search terms to neurofeedback. Research is concentrated in Europe and North America, with a significant gap in Asian countries. A growing body of evidence supports the potential benefits of neurofeedback for AD. A strong correlation has been found between neurofeedback and AD-related terms. Clinical trials suggest positive outcomes for neurofeedback in improving cognitive impairments and working memory. Neurofeedback shows promise as a potential treatment for AD. Further research and clinical studies are needed to explore the full potential of neurofeedback for enhancing the quality of life for individuals with AD.
DOI: 10.6084/m9.figshare.27960681.v1
title: Effectiveness of neuro-feedback on Alzheimer’s rehabilitation: a bibliometric analysis

description: Alzheimer’s Disease (AD) is a neurodegenerative disorder with limited treatment options. Neurofeedback, a technique that trains brainwaves, has shown promise in addressing cognitive impairments. To conduct a bibliometric analysis to explore the current research on neurofeedback as a treatment for AD. A systematic literature review was performed based on PRISMA guidelines on 142 papers. Different bibliometric parameters like the author’s country, author names, keywords, journal names, and country of citations were analyzed, and a network visualization chart was generated to understand the correlation of Alzheimer-related search terms to neurofeedback. Research is concentrated in Europe and North America, with a significant gap in Asian countries. A growing body of evidence supports the potential benefits of neurofeedback for AD. A strong correlation has been found between neurofeedback and AD-related terms. Clinical trials suggest positive outcomes for neurofeedback in improving cognitive impairments and working memory. Neurofeedback shows promise as a potential treatment for AD. Further research and clinical studies are needed to explore the full potential of neurofeedback for enhancing the quality of life for individuals with AD.
DOI: 10.5281/zenodo.14533023
title: Figure Data for Oka (2025) "Deep ocean mixing mismatch between model and observational estimates"

description: Figure Data for Oka (2025) "Deep ocean mixing mismatch between model and observational estimates"
DOI: 10.5281/zenodo.14533024
title: Figure Data for Oka (2025) "Deep ocean mixing mismatch between model and observational estimates"

description: Figure Data for Oka (2025) "Deep ocean mixing mismatch between model and observational estimates"
DOI: 10.5281/zenodo.14620592
title: India Carbonated Beverages Market 2024 To 2033

description: India Carbonated Beverages Market Size, Trends and Insights By Product Type (Cola Drinks, Flavoured Carbonated Drinks, Diet and Zero Calorie Beverages, Others), By Packaging Type (Cans, Bottles, PET Bottles, Others), By Distribution Channel (Retail Stores, Supermarkets, convenience stores, Online Retail, Others), and By Region - Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

As per the current market research conducted by the CMI Team, the India Carbonated Beverages Market is expected to record a CAGR of 6.5% from 2024 to 2033. In 2024, the market size is projected to reach a valuation of USD 80.1 Billion. By 2033, the valuation is anticipated to reach USD 141.1 Billion.

India’s carbonated beverages market is a dynamic and rapidly evolving sector, characterized by significant growth driven by urbanization, increasing disposable incomes, and a young, experimental consumer base. Major players like Coca-Cola, PepsiCo, and Parle Agro dominate the market, offering a wide range of flavored sodas, sparkling water, and energy drinks.

Current trends focus on health and wellness, leading to the introduction of low-sugar and functional beverages. The market is also seeing a surge in e-commerce sales and digital marketing efforts. Sustainable packaging and corporate social responsibility initiatives are becoming increasingly important in shaping the industry’s future.

For more information, DOWNLOAD FREE SAMPLE Now at https://www.custommarketinsights.com/request-for-free-sample/?reportid=53074
DOI: 10.5281/zenodo.14620593
title: India Carbonated Beverages Market 2024 To 2033

description: India Carbonated Beverages Market Size, Trends and Insights By Product Type (Cola Drinks, Flavoured Carbonated Drinks, Diet and Zero Calorie Beverages, Others), By Packaging Type (Cans, Bottles, PET Bottles, Others), By Distribution Channel (Retail Stores, Supermarkets, convenience stores, Online Retail, Others), and By Region - Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

As per the current market research conducted by the CMI Team, the India Carbonated Beverages Market is expected to record a CAGR of 6.5% from 2024 to 2033. In 2024, the market size is projected to reach a valuation of USD 80.1 Billion. By 2033, the valuation is anticipated to reach USD 141.1 Billion.

India’s carbonated beverages market is a dynamic and rapidly evolving sector, characterized by significant growth driven by urbanization, increasing disposable incomes, and a young, experimental consumer base. Major players like Coca-Cola, PepsiCo, and Parle Agro dominate the market, offering a wide range of flavored sodas, sparkling water, and energy drinks.

Current trends focus on health and wellness, leading to the introduction of low-sugar and functional beverages. The market is also seeing a surge in e-commerce sales and digital marketing efforts. Sustainable packaging and corporate social responsibility initiatives are becoming increasingly important in shaping the industry’s future.

For more information, DOWNLOAD FREE SAMPLE Now at https://www.custommarketinsights.com/request-for-free-sample/?reportid=53074
DOI: 10.5281/zenodo.10695884
title: Auto-Tune Detection Dataset (ATD-Dataset)

description: We present a novel dataset for distinguishing auto-tuned musical compositions from authentic ones, filling a gap in existing resources. To create this dataset, we utilized the VocalSet and Musdb18 datasets from the Music Information Retrieval (MIR) domain. The dataset comprises 150 music recordings along with 3613 audio recordings from 20 professional singers. It is segmented into 'Training' and 'Test' subsets, with 50 music recordings allocated to the test subset and the remainder to the training subset. The following explains the file names and subdirectory names:

·        Simple: This directory contains song tracks in the test dataset without any postprocessing.

·        MP3_Compression: This directory contains MP3-compressed songs in the test dataset.

·        Random_Aug: This directory contains songs in the test dataset after random augmentation.

·        Auto_Tuned.wav: Auto-tuned versions of the vocal performances.

·        Original.wav: Original vocal performances.

·        st_Auto_Tuned.wav: Auto-tuned versions of the vocal performances, standardized to be a 10-second audio file.

·        st_Original.wav: Original vocal performances, standardized to be a 10-second audio file.

·        Auto_Tuned_Vocal.wav: Auto-tuned vocals of songs.

·        Original_Vocal.wav: Original vocals of songs.

·        Auto_Tuned_Song.wav: Auto-tuned songs.

·        Original_Song.wav: Original songs.

·        Auto_Tuned_Vocal_is.wav: Auto-tuned vocals extracted from mixed songs using the vocal isolator tool.

·        Original_Vocal_is.wav: Original vocals extracted from mixed songs using the vocal isolator tool.
DOI: 10.5281/zenodo.10695885
title: Auto-Tune Detection Dataset (ATD-Dataset)

description: We present a novel dataset for distinguishing auto-tuned musical compositions from authentic ones, filling a gap in existing resources. To create this dataset, we utilized the VocalSet and Musdb18 datasets from the Music Information Retrieval (MIR) domain. The dataset comprises 150 music recordings along with 3613 audio recordings from 20 professional singers. It is segmented into 'Training' and 'Test' subsets, with 50 music recordings allocated to the test subset and the remainder to the training subset. The following explains the file names and subdirectory names:

·        Simple: This directory contains song tracks in the test dataset without any postprocessing.

·        MP3_Compression: This directory contains MP3-compressed songs in the test dataset.

·        Random_Aug: This directory contains songs in the test dataset after random augmentation.

·        Auto_Tuned.wav: Auto-tuned versions of the vocal performances.

·        Original.wav: Original vocal performances.

·        st_Auto_Tuned.wav: Auto-tuned versions of the vocal performances, standardized to be a 10-second audio file.

·        st_Original.wav: Original vocal performances, standardized to be a 10-second audio file.

·        Auto_Tuned_Vocal.wav: Auto-tuned vocals of songs.

·        Original_Vocal.wav: Original vocals of songs.

·        Auto_Tuned_Song.wav: Auto-tuned songs.

·        Original_Song.wav: Original songs.

·        Auto_Tuned_Vocal_is.wav: Auto-tuned vocals extracted from mixed songs using the vocal isolator tool.

·        Original_Vocal_is.wav: Original vocals extracted from mixed songs using the vocal isolator tool.
DOI: 10.6084/m9.figshare.28172345
title: out_phase3_scenario1.dat

description: We developed a model integrating global carbon cycling with ocean geochemistry, guided by the solid Earth system evolution. Our model explicitly tracks the changing atmospheric <i>p</i>CO<sub>2</sub> and ocean pH using ocean charge balance, incorporating continental growth and mantle thermal evolution to self-consistently constrain the geochemical cycles of carbon, sodium, and magnesium.
DOI: 10.15468/dl.ry89md
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Wildlife Queensland - Platypus eDNA"
 ]
}

 The dataset includes 20 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0062132-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14620506
title: Enhanced site-specific fluorescent labeling of membrane proteins using native nanodiscs

description: Fluorescent labeling of membrane proteins is essential for exploring their functions, signaling pathways, interaction partners, and structural dynamics. Organic fluorophores are commonly used for this purpose due to their favorable photophysical properties and photostability. However, a persistent challenge is the inaccessibility of surface-exposed cysteine residues required for site-specific labeling, as these residues often become sequestered within detergent micelles during protein extraction. To address this limitation, we developed an approach based on polymer-encapsulated nanodiscs that preserves the protein’s native-like lipid-bilayer environment while ensuring accessibility of surface-exposed cysteine residues. In this method, His-tagged proteins embedded in native nanodiscs are retained on a nickel affinity column, allowing for simultaneous purification and labeling by adding fluorescent dyes. This versatile technique was demonstrated with two challenging-to-label membrane proteins, the potassium channel KvAP and the urea channel HpUreI, for which detergent-based labeling had failed. It opens new possibilities for studying a wide range of fluorescently labeled membrane proteins in near-native states, advancing applications in biophysics, structural biology, and drug discovery.
DOI: 10.5281/zenodo.14620507
title: Enhanced site-specific fluorescent labeling of membrane proteins using native nanodiscs

description: Fluorescent labeling of membrane proteins is essential for exploring their functions, signaling pathways, interaction partners, and structural dynamics. Organic fluorophores are commonly used for this purpose due to their favorable photophysical properties and photostability. However, a persistent challenge is the inaccessibility of surface-exposed cysteine residues required for site-specific labeling, as these residues often become sequestered within detergent micelles during protein extraction. To address this limitation, we developed an approach based on polymer-encapsulated nanodiscs that preserves the protein’s native-like lipid-bilayer environment while ensuring accessibility of surface-exposed cysteine residues. In this method, His-tagged proteins embedded in native nanodiscs are retained on a nickel affinity column, allowing for simultaneous purification and labeling by adding fluorescent dyes. This versatile technique was demonstrated with two challenging-to-label membrane proteins, the potassium channel KvAP and the urea channel HpUreI, for which detergent-based labeling had failed. It opens new possibilities for studying a wide range of fluorescently labeled membrane proteins in near-native states, advancing applications in biophysics, structural biology, and drug discovery.
DOI: 10.15468/dl.p3vrhs
title: Occurrence Download

description: A dataset containing 2063 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Savu Sea-Indonesia eDNA Dataset"
 ]
}

 The dataset includes 2063 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0062133-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hyp65r
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Vertebrate eDNA survey in nearshore marine environment"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0062135-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57754/fdat.ccxd6-wdj37
title: Korpusrecherche Verben Präteritum

description: Diese Korpusrecherche gibt einen Überblick über Verben im Präteritum mit bestimmten Zählquantoren.
description: Research carried out in work package C02 of the SFB 833.
DOI: 10.15468/dl.b7rmab
title: Occurrence Download

description: A dataset containing 106 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Chile",
 "TaxonKey is Ptiliidae"
 ]
}

 The dataset includes 106 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0062136-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.