cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.m4mxhx
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((144.762749 -36.797949, 144.762749 -36.809178, 144.764994 -36.809178, 144.764994 -36.797949, 144.762749 -36.797949))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0075276-240626123714530/datasets/export for details.
DOI: 10.15468/dl.jn2c3u
title: Occurrence Download

description: A dataset containing 12123753 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 12123753 records from 2247 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0075264-240626123714530/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.30973264
title: Correlation of lip length and thickness with malocclusion: a cephalometric study

description: The length and thickness of the upper and lower lips are critical parameters that must be considered during orthodontic assessment. This is because skeletal deformities can sometimes be masked by well-developed soft tissue coverage. In our study wecorrelate the relationship between soft tissues and skeletal patterns by measuring the length and thickness of the upper and lower lips in Iraqi adults, and relating these measurements to skeletal Class I, Class II, and Class III
DOI: 10.6084/m9.figshare.30973264.v1
title: Correlation of lip length and thickness with malocclusion: a cephalometric study

description: The length and thickness of the upper and lower lips are critical parameters that must be considered during orthodontic assessment. This is because skeletal deformities can sometimes be masked by well-developed soft tissue coverage. In our study wecorrelate the relationship between soft tissues and skeletal patterns by measuring the length and thickness of the upper and lower lips in Iraqi adults, and relating these measurements to skeletal Class I, Class II, and Class III
DOI: 10.6084/m9.figshare.30973405
title: Test data nf-flu

description: NCBI test data for nf-flu!
DOI: 10.6084/m9.figshare.30973405.v1
title: Test data nf-flu

description: NCBI test data for nf-flu!
DOI: 10.5281/zenodo.18099290
title: Semper Fie DataSet
DOI: 10.5281/zenodo.18099291
title: Semper Fie DataSet
DOI: 10.15468/dl.62tqza
title: Occurrence Download

description: A dataset containing 17779 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-75.4305 6.03865,-75.44129 6.03596,-75.43649 6.03065,-75.4384 6.02309,-75.44996 6.02032,-75.46111 6.02357,-75.47133 6.0204,-75.48073 6.0259,-75.4922 6.02095,-75.49412 6.02529,-75.50405 6.02317,-75.50069 6.01086,-75.51412 6.00004,-75.52281 5.98662,-75.53425 5.98831,-75.54793 5.98564,-75.55768 5.99076,-75.5753 5.97965,-75.5941 5.98527,-75.59299 5.97679,-75.5971 5.97131,-75.60324 5.97849,-75.6028 5.96794,-75.59894 5.96726,-75.60318 5.95386,-75.60265 5.92852,-75.60773 5.92346,-75.61144 5.91303,-75.60951 5.90318,-75.61427 5.8965,-75.61649 5.88073,-75.60473 5.86976,-75.59714 5.84736,-75.60602 5.85291,-75.6084 5.86113,-75.6233 5.8627,-75.61984 5.8437,-75.6115 5.83397,-75.61421 5.82062,-75.62073 5.81376,-75.62197 5.80672,-75.61844 5.80014,-75.62049 5.78258,-75.61742 5.76557,-75.62269 5.75409,-75.6308 5.75265,-75.61588 5.74353,-75.60694 5.74453,-75.59999 5.73484,-75.58833 5.7515,-75.58893 5.77686,-75.58731 5.78439,-75.58183 5.78937,-75.57398 5.78801,-75.58835 5.8063,-75.5901 5.82598,-75.57923 5.84098,-75.57453 5.84317,-75.57472 5.83503,-75.56603 5.83835,-75.57145 5.84764,-75.57173 5.86333,-75.56951 5.86663,-75.56513 5.85238,-75.55669 5.85608,-75.56163 5.86668,-75.54153 5.8771,-75.53601 5.86954,-75.52915 5.87627,-75.51677 5.89918,-75.53371 5.89854,-75.53347 5.904,-75.52713 5.9171,-75.51608 5.9247,-75.51464 5.93302,-75.50515 5.9322,-75.49427 5.94783,-75.48824 5.95136,-75.48857 5.95836,-75.49672 5.96007,-75.49219 5.96667,-75.49725 5.97491,-75.49074 5.9792,-75.48642 5.9983,-75.48225 6.00528,-75.46888 6.00248,-75.4717 5.99539,-75.48345 5.99136,-75.47182 5.99278,-75.4639 5.99855,-75.45931 5.99562,-75.46352 5.98949,-75.4527 5.99124,-75.4495 5.98575,-75.44744 5.99161,-75.45295 5.99645,-75.4443 6.00168,-75.42431 6.00776,-75.41962 6.01372,-75.41758 6.02447,-75.423 6.02453,-75.41696 6.03567,-75.4305 6.03865))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 17779 records from 70 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069396-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14347132
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.yh7gvg
title: Occurrence Download

description: A dataset containing 954 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-75.4305 6.03865,-75.44129 6.03596,-75.43649 6.03065,-75.4384 6.02309,-75.44996 6.02032,-75.46111 6.02357,-75.47133 6.0204,-75.48073 6.0259,-75.4922 6.02095,-75.49412 6.02529,-75.50405 6.02317,-75.50069 6.01086,-75.51412 6.00004,-75.52281 5.98662,-75.53425 5.98831,-75.54793 5.98564,-75.55768 5.99076,-75.5753 5.97965,-75.5941 5.98527,-75.59299 5.97679,-75.5971 5.97131,-75.60324 5.97849,-75.6028 5.96794,-75.59894 5.96726,-75.60318 5.95386,-75.60265 5.92852,-75.60773 5.92346,-75.61144 5.91303,-75.60951 5.90318,-75.61427 5.8965,-75.61649 5.88073,-75.60473 5.86976,-75.59714 5.84736,-75.60602 5.85291,-75.6084 5.86113,-75.6233 5.8627,-75.61984 5.8437,-75.6115 5.83397,-75.61421 5.82062,-75.62073 5.81376,-75.62197 5.80672,-75.61844 5.80014,-75.62049 5.78258,-75.61742 5.76557,-75.62269 5.75409,-75.6308 5.75265,-75.61588 5.74353,-75.60694 5.74453,-75.59999 5.73484,-75.58833 5.7515,-75.58893 5.77686,-75.58731 5.78439,-75.58183 5.78937,-75.57398 5.78801,-75.58835 5.8063,-75.5901 5.82598,-75.57923 5.84098,-75.57453 5.84317,-75.57472 5.83503,-75.56603 5.83835,-75.57145 5.84764,-75.57173 5.86333,-75.56951 5.86663,-75.56513 5.85238,-75.55669 5.85608,-75.56163 5.86668,-75.54153 5.8771,-75.53601 5.86954,-75.52915 5.87627,-75.51677 5.89918,-75.53371 5.89854,-75.53347 5.904,-75.52713 5.9171,-75.51608 5.9247,-75.51464 5.93302,-75.50515 5.9322,-75.49427 5.94783,-75.48824 5.95136,-75.48857 5.95836,-75.49672 5.96007,-75.49219 5.96667,-75.49725 5.97491,-75.49074 5.9792,-75.48642 5.9983,-75.48225 6.00528,-75.46888 6.00248,-75.4717 5.99539,-75.48345 5.99136,-75.47182 5.99278,-75.4639 5.99855,-75.45931 5.99562,-75.46352 5.98949,-75.4527 5.99124,-75.4495 5.98575,-75.44744 5.99161,-75.45295 5.99645,-75.4443 6.00168,-75.42431 6.00776,-75.41962 6.01372,-75.41758 6.02447,-75.423 6.02453,-75.41696 6.03567,-75.4305 6.03865))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 954 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069397-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18099467
title: body image search strategy
DOI: 10.5281/zenodo.18099359
title: Bending-related faults offshore of the Alaska Peninsula

description: This text file contains the positions of bending faults in the subducting Pacific plate offshore of the Alaska Peninsula, which were mapped from bathymetry data.  The approximate area of mapping is between 161-155ºW and 53-55ºN. These faults are described in detail in Clarke et al. (2024).  The columns are longitude and latitude, and each fault is separated by a line with a '>'. The file is formatted for plotting with Generic Mapping Tools (GMT).
DOI: 10.5281/zenodo.18099358
title: Bending-related faults offshore of the Alaska Peninsula

description: This text file contains the positions of bending faults in the subducting Pacific plate offshore of the Alaska Peninsula, which were mapped from bathymetry data.  The approximate area of mapping is between 161-155ºW and 53-55ºN. These faults are described in detail in Clarke et al. (2024).  The columns are longitude and latitude, and each fault is separated by a line with a '>'. The file is formatted for plotting with Generic Mapping Tools (GMT).
DOI: 10.15468/dl.rarqu4
title: Occurrence Download

description: A dataset containing 261945 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "GadmGid is NLD",
 "OccurrenceStatus is Present",
 "TaxonKey is Apus apus",
 "Year 1975-2025"
 ]
}

 The dataset includes 261945 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069394-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dxr76h
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "StateProvince is Guizhou",
 "TaxonKey is Potamidae",
 "Year 2015-2025"
 ]
}

 The dataset includes 25 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069399-251120083545085/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.30120799
title: Diagnosing nutrient deficiencies in Kinnow using a yield-quality optimization approach and machine learning

description: While Diagnosis and Recommendation Integrated System (DRIS) and Compositional Nutrient Diagnosis (CND), have been widely used for diagnosing nutrient imbalances, they often overlook fruit quality, which is equally vital for market success. To address this limitation, we proposed a novel, more precise methodology that integrates both yield and quality into diagnostic frameworks. Leaf and soil samples from 351 Kinnow orchards in Abohar, Punjab (India), were analyzed during 2017–2019 and 2022. Populations were classified based on aggregate score of yield and fruit quality attributes, derived through ‘Analytical Hierarchy Process’. Nutrient norms were refined using Mahalanobis distance and cate-nelson analysis. Results revealed severe deficiencies of Mg (98.3%), Mn (98.3%), P (82.8%), S (79.3%), and Zn (75.9%), along with moderate deficiencies in N (51.7%) and Ca (56.9%). Crucially, the modified CND-clr (centred log ratio) approach outperformed traditional DRIS/CND (RMSEP: 21.45 vs. 13.44), demonstrating enhanced diagnostic precision. The production constraints related to soil were further identified using a random forest algorithm, demonstrated high soil pH, EC, and CaCO<sub>3</sub> as key limiting factors. This framework offers a more precise approach to nutrient management in global fruit cultivation. A novel multicriteria approach integrating yield and fruit quality improved nutrient diagnostic efficacy in Kinnow.Modified CND-clr outperformed traditional DRIS and CND methods, offering more precise nutrient thresholds for dual yield-quality optimization.Machine learning revealed high soil pH, EC, CaCO<sub>3</sub>, and widespread S, P, Mg, and Zn deficiencies as key constraints limiting Kinnow productivity in South-Western Punjab. A novel multicriteria approach integrating yield and fruit quality improved nutrient diagnostic efficacy in Kinnow. Modified CND-clr outperformed traditional DRIS and CND methods, offering more precise nutrient thresholds for dual yield-quality optimization. Machine learning revealed high soil pH, EC, CaCO<sub>3</sub>, and widespread S, P, Mg, and Zn deficiencies as key constraints limiting Kinnow productivity in South-Western Punjab.
DOI: 10.6084/m9.figshare.30120799.v1
title: Diagnosing nutrient deficiencies in Kinnow using a yield-quality optimization approach and machine learning

description: While Diagnosis and Recommendation Integrated System (DRIS) and Compositional Nutrient Diagnosis (CND), have been widely used for diagnosing nutrient imbalances, they often overlook fruit quality, which is equally vital for market success. To address this limitation, we proposed a novel, more precise methodology that integrates both yield and quality into diagnostic frameworks. Leaf and soil samples from 351 Kinnow orchards in Abohar, Punjab (India), were analyzed during 2017–2019 and 2022. Populations were classified based on aggregate score of yield and fruit quality attributes, derived through ‘Analytical Hierarchy Process’. Nutrient norms were refined using Mahalanobis distance and cate-nelson analysis. Results revealed severe deficiencies of Mg (98.3%), Mn (98.3%), P (82.8%), S (79.3%), and Zn (75.9%), along with moderate deficiencies in N (51.7%) and Ca (56.9%). Crucially, the modified CND-clr (centred log ratio) approach outperformed traditional DRIS/CND (RMSEP: 21.45 vs. 13.44), demonstrating enhanced diagnostic precision. The production constraints related to soil were further identified using a random forest algorithm, demonstrated high soil pH, EC, and CaCO<sub>3</sub> as key limiting factors. This framework offers a more precise approach to nutrient management in global fruit cultivation. A novel multicriteria approach integrating yield and fruit quality improved nutrient diagnostic efficacy in Kinnow.Modified CND-clr outperformed traditional DRIS and CND methods, offering more precise nutrient thresholds for dual yield-quality optimization.Machine learning revealed high soil pH, EC, CaCO<sub>3</sub>, and widespread S, P, Mg, and Zn deficiencies as key constraints limiting Kinnow productivity in South-Western Punjab. A novel multicriteria approach integrating yield and fruit quality improved nutrient diagnostic efficacy in Kinnow. Modified CND-clr outperformed traditional DRIS and CND methods, offering more precise nutrient thresholds for dual yield-quality optimization. Machine learning revealed high soil pH, EC, CaCO<sub>3</sub>, and widespread S, P, Mg, and Zn deficiencies as key constraints limiting Kinnow productivity in South-Western Punjab.
DOI: 10.6084/m9.figshare.30255886
title: Morphological, physiological and kinetic parameters related to nitrogen uptake efficiency in hop cultivars (<i>Humulus lupulus</i> L.)

description: Hops are cultivated in fertile soils in temperate climates. However, have been cultivated in countries in subtropical and tropical regions, where the soils have low availability of nitrogen (N) to plants. Therefore, N fertilization is necessary. However, hop cultivars may have different kinetic parameters of absorption, which may provide greater or lesser efficiency in the absorption of N forms. The study aimed to evaluate the kinetic parameters related to the absorption of mineral N forms in hop cultivars. Cultivars <i>‘Cascade’</i>, <i>‘Chinook’</i>, and <i>‘Columbus’</i> after 21 days of cultivation in a 50% Hoagland solution were transferred to a CaSO<sub>4</sub> solution (0.01 mol L<sup>−1</sup>) for 10 days, in order to deplete their internal reserves. Photosynthetic and morphological variables, total N concentration in cultivar organs, and NO<sub>3</sub><sup>-</sup> and NH<sub>4</sub><sup>+</sup> concentrations in the solution was analyzed. Cultivar <i>‘Columbus’</i> showed higher fresh matter production potential, good photosynthetic performance, higher maximum absorption rate values for NO<sub>3</sub><sup>-</sup> and NH<sub>4</sub><sup>+</sup>, and higher NO<sub>3</sub><sup>-</sup> influx values, indicating that it is suitable for cultivation in substrates with high N availability. Cultivar <i>‘Chinook</i>’ had the greatest photosynthetic potential and, therefore, it can show rapid growth and high productivity and lower concentration minimum value, indicating that it can perform well in environments with low N availability. ‘<i>Cascade</i>’ showed higher root growth potential, higher tissue N concentration values in different parts, and higher NH<sub>4</sub><sup>+</sup> influx values, indicating that it is suitable for soils with high NH<sub>4</sub><sup>+</sup> availability. Kinetic parameters can be used to select genotypes that are more efficient in nutrient uptake. Hop cultivation is possible in southern Brazil. Different hop cultivars in different effects at photosynthetic and kinetic parameters. The amount and form of N available in the soil can increase the efficiency of certain hop varieties. It is possible to produce more sustainably and save resources with the knowledge of the kinetic parameters of hop cultivars.
DOI: 10.6084/m9.figshare.30255886.v1
title: Morphological, physiological and kinetic parameters related to nitrogen uptake efficiency in hop cultivars (<i>Humulus lupulus</i> L.)

description: Hops are cultivated in fertile soils in temperate climates. However, have been cultivated in countries in subtropical and tropical regions, where the soils have low availability of nitrogen (N) to plants. Therefore, N fertilization is necessary. However, hop cultivars may have different kinetic parameters of absorption, which may provide greater or lesser efficiency in the absorption of N forms. The study aimed to evaluate the kinetic parameters related to the absorption of mineral N forms in hop cultivars. Cultivars <i>‘Cascade’</i>, <i>‘Chinook’</i>, and <i>‘Columbus’</i> after 21 days of cultivation in a 50% Hoagland solution were transferred to a CaSO<sub>4</sub> solution (0.01 mol L<sup>−1</sup>) for 10 days, in order to deplete their internal reserves. Photosynthetic and morphological variables, total N concentration in cultivar organs, and NO<sub>3</sub><sup>-</sup> and NH<sub>4</sub><sup>+</sup> concentrations in the solution was analyzed. Cultivar <i>‘Columbus’</i> showed higher fresh matter production potential, good photosynthetic performance, higher maximum absorption rate values for NO<sub>3</sub><sup>-</sup> and NH<sub>4</sub><sup>+</sup>, and higher NO<sub>3</sub><sup>-</sup> influx values, indicating that it is suitable for cultivation in substrates with high N availability. Cultivar <i>‘Chinook</i>’ had the greatest photosynthetic potential and, therefore, it can show rapid growth and high productivity and lower concentration minimum value, indicating that it can perform well in environments with low N availability. ‘<i>Cascade</i>’ showed higher root growth potential, higher tissue N concentration values in different parts, and higher NH<sub>4</sub><sup>+</sup> influx values, indicating that it is suitable for soils with high NH<sub>4</sub><sup>+</sup> availability. Kinetic parameters can be used to select genotypes that are more efficient in nutrient uptake. Hop cultivation is possible in southern Brazil. Different hop cultivars in different effects at photosynthetic and kinetic parameters. The amount and form of N available in the soil can increase the efficiency of certain hop varieties. It is possible to produce more sustainably and save resources with the knowledge of the kinetic parameters of hop cultivars.
DOI: 10.5067/caliop/calipso/cal_lid_l2_01kmclay-standard-v5-00
title: CALIPSO Lidar Level 2 1 km Cloud Layer, V5-00
DOI: 10.48527/szetqg/ph7uav
title: export_02.xls

description: :unav
DOI: 10.48527/szetqg/54snvz
title: export_03.xls

description: :unav
DOI: 10.48527/szetqg/xnqf8a
title: export_06.xls

description: :unav
DOI: 10.48527/szetqg/cudeze
title: export_05.xls

description: :unav
DOI: 10.48527/szetqg/yd6n8q
title: export_01.xls

description: :unav
DOI: 10.48527/szetqg
title: Sound datasets: EduCITY e o ruído

description: Sound datasets: EduCITY e o ruído
DOI: 10.48527/szetqg/9yxa7r
title: export_04.xls

description: :unav
DOI: 10.5281/zenodo.16639187
title: Dataset for: Surface Hopping with Fully Correlated Methods

description: These datasets contain the initial conditions and dynamics generated by Newton-X (Newton-X v3.5.2) through interfaces with multiple third-party software. It contains simulations of Fulevene and Pyrrole at different electronic structure methods. It accompanies the paper: Surface Hopping with Fully Correlated Methods. Available at: https://doi.org/10.26434/chemrxiv-2025-jc6dp-v2.
DOI: 10.5281/zenodo.16639188
title: Dataset for: Surface Hopping with Fully Correlated Methods

description: These datasets contain the initial conditions and dynamics generated by Newton-X (Newton-X v3.5.2) through interfaces with multiple third-party software. It contains simulations of Fulevene and Pyrrole at different electronic structure methods. It accompanies the paper: Surface Hopping with Fully Correlated Methods. Available at: https://doi.org/10.26434/chemrxiv-2025-jc6dp-v2.
DOI: 10.15468/dl.7bnaxy
title: Occurrence Download

description: A dataset containing 156358 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "Geometry POLYGON((-28.87543 -4.34732,-44.67148 -0.3525,-60.86743 -27.25532,-58.26808 -40.9356,-50.47003 -42.13294,-28.87543 -4.34732))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "PublishingOrg is 28eb1a3f-1c15-4a95-931a-4af90ecb574d",
 "TaxonKey is Lepidoptera"
 ]
}

 The dataset includes 156358 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069398-251120083545085/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.30973675
title: SDG$ in Saudi EFL Textbooks

description: Education plays an important role in making a more sustainable and fair world. The United Nations’ Sustainable Development Goal 4 (Quality Education) calls for every learner to gain the knowledge and values needed to build a sustainable future. This study examines how these ideas, especially those under Target 4.7 of SDG 4, are represented in English-language textbooks used in Saudi secondary schools.
DOI: 10.6084/m9.figshare.30973675.v1
title: SDG$ in Saudi EFL Textbooks

description: Education plays an important role in making a more sustainable and fair world. The United Nations’ Sustainable Development Goal 4 (Quality Education) calls for every learner to gain the knowledge and values needed to build a sustainable future. This study examines how these ideas, especially those under Target 4.7 of SDG 4, are represented in English-language textbooks used in Saudi secondary schools.
DOI: 10.48527/6lykhz/dmnktp
title: export_01.xls

description: :unav
DOI: 10.48527/6lykhz/bhxcom
title: export_06.xls

description: :unav
DOI: 10.48527/6lykhz/xvwiep
title: export_02.xls

description: :unav
DOI: 10.48527/6lykhz/pvi4jh
title: export_04.xls

description: :unav
DOI: 10.48527/6lykhz/cfzn2o
title: export_05.xls

description: :unav
DOI: 10.48527/6lykhz/sdtkoz
title: export_03.xls

description: :unav
DOI: 10.48527/6lykhz
title: Particules datasets: EduCITY e a qualidade do ar

description: Particules datasets: EduCITY e a qualidade do ar
DOI: 10.48527/yeppkz/neqjig
title: export_06.xls

description: :unav
DOI: 10.48527/yeppkz/si6r4k
title: export_12.xls

description: :unav
DOI: 10.48527/yeppkz/eyaxs0
title: export_10.xls

description: :unav
DOI: 10.48527/yeppkz/avvh4j
title: export_14.xls

description: :unav
DOI: 10.48527/yeppkz/xyegvg
title: export_11.xls

description: :unav
DOI: 10.48527/yeppkz/46nbmb
title: export_15.xls

description: :unav
DOI: 10.48527/yeppkz/duzrnt
title: export_04.xls

description: :unav
DOI: 10.48527/yeppkz/oryv4s
title: export_08.xls

description: :unav
DOI: 10.48527/yeppkz/t7wvi4
title: export_05.xls

description: :unav
DOI: 10.48527/yeppkz/htq29a
title: export_07.xls

description: :unav
DOI: 10.48527/yeppkz/evuw22
title: export_01.xls

description: :unav
DOI: 10.48527/yeppkz/sjczce
title: export_03.xls

description: :unav
DOI: 10.48527/yeppkz/xcngde
title: export_02.xls

description: :unav
DOI: 10.48527/yeppkz/ea9vny
title: export_13.xls

description: :unav
DOI: 10.48527/yeppkz/nwwkpu
title: export_09.xls

description: :unav
DOI: 10.48527/yeppkz
title: Sound datasets: Demo NEI23

description: Sound datasets: Demo NEI23