cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/3yz-lhp-69w
title: Billardiera scandens Sm.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/n7t-xtg-p82
title: Piper L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/bce-xzg-ej8
title: Sesamum indicum L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/3sc-m60-qap
title: Glaucium flavum Crantz

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/y0w-kb6-gde
title: Hypecoum procumbens L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/h8k-a1d-2r0
title: Sesamum indicum L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/jr9-9xt-t7t
title: Sesamum indicum L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.15468/dl.xawrk8
title: Occurrence Download

description: A dataset containing 527519 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Acer campestre L."
 ]
}

 The dataset includes 527519 records from 2668 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0107277-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kwz4ud
title: Occurrence Download

description: A dataset containing 63 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Gentiana walujewii"
 ]
}

 The dataset includes 63 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008162-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.scwwvp
title: Occurrence Download

description: A dataset containing 149 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Larix sibirica"
 ]
}

 The dataset includes 149 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008163-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/b0s7u8om
title: Monthly excess of deaths in 2020

description: The dataset is from ISTAT, Italy's Istituto Nazionale di Statistica.
DOI: 10.57702/cp1e2ukc
title: AAPM Low-Dose CT Grand Challenge

description: The dataset used for training and testing the proposed neural network for conebeam artifact removal.
DOI: 10.15468/dl.tj67xc
title: Occurrence Download

description: A dataset containing 982 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Notropis shumardi",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 982 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080035-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/wnr0g3dl
title: Source-Free Domain Adaptation

description: Source-free domain adaptation (SFDA) aims to adapt a source model trained on a fully-labeled source domain to a related but unlabeled target domain.
DOI: 10.57702/nnc8wr3x
title: Rgbd Objects in the Wild

description: A synthetic 3D object learning from RGB-D videos.
DOI: 10.57702/te1o1bqd
title: SP Theory of Intelligence

description: The SP system has potential for substantial additional economies in the transmission of data (via the separation of encoding from grammar), and for substantial gains in computational efﬁciency (via information compression and probabilities, and via a synergy with data-centric computing), with consequent beneﬁts in energy efﬁciency, greater speed of processing with a given computational resource, and reductions in the size and weight of computers.
DOI: 10.57702/5rzeqp1i
title: Climatological dataset

description: This dataset is used to test the proposed algorithm LinCFA on real data.
DOI: 10.57702/2k5qwq2a
title: VGG

description: The dataset used in the paper is the VGG dataset, which is a collection of images used for training and testing VGG models.
DOI: 10.57702/j60e06dy
title: iNaturalist dataset

description: The iNaturalist dataset is a crowdsourced compendium of living organisms, with fine- and coarse-grained species distinctions, a heavy-tailed class size distribution, and bounding box annotations.
DOI: 10.57702/38n5wgjg
title: Trigger Detector Dataset

description: The dataset used to train the trigger detector, generated from a public dataset through data augmentation.
DOI: 10.57702/gg9uqbit
title: CORD-19

description: The CORD-19 dataset contains academic journal articles relating to a variety of coronaviruses and related viral infections, not only COVID-19, sourced from PubMed Central (PMC), PubMed, the World Health Organization (WHO), bioRxiv, medRxiv, and arXiv.
DOI: 10.57702/00jh5g3o
title: AR face recognition dataset

description: AR face recognition dataset
DOI: 10.57702/a5p0qwb1
title: Machine learning for perturbational single-cell omics

description: Single-cell perturbation response prediction using machine learning.
DOI: 10.57702/afvnlp82
title: A neural parametric singing synthesizer modeling timbre and expression from natural songs

description: A neural parametric singing synthesizer modeling timbre and expression from natural songs.
DOI: 10.57702/owy1ay62
title: Subjectivity Dataset

description: The Subjectivity dataset is a dataset provided by [Pang and Lee, 2004].
DOI: 10.57702/scyvo1hs
title: FMA Dataset

description: Music Genre Classiﬁcation (MGC) is an essential task in the research ﬁeld of Music Information Retrieval (MIR) Recently, inspired by the progress achieved by Deep Learning (DL) techniques, researchers have widely applied DL techs in the ﬁelds of MIR and achieved promising results in various tasks, especially MGC.
DOI: 10.57702/gd5mhvy6
title: i2b2 2012 dataset

description: The i2b2 2012 dataset is a corpus of clinical text that was created as part of an NLP challenge in 2012.
DOI: 10.57702/zd4xp65x
title: Audrey Dataset

description: The dataset used for training the models in the Audrey chatbot.
DOI: 10.57702/qpyl5zll
title: Optimized Demonstrations Dataset

description: The dataset used for training the downstream LfD method, containing optimized demonstrations.
DOI: 10.15468/dl.6uwm6f
title: Occurrence Download

description: A dataset containing 1717 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((5.56085 43.46024,5.52559 43.43252,5.51498 43.38939,5.53535 43.36749,5.60346 43.35465,5.63957 43.37912,5.66028 43.41712,5.63187 43.44416,5.55879 43.4611,5.56085 43.46024))",
 "OccurrenceStatus is Present",
 "TaxonKey is Mammalia"
 ]
}

 The dataset includes 1717 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080036-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/vmn064j3
title: Promoter Design

description: We use the promoter DNA sequence dataset containing 100k promoter sequences with the corresponding transcription initiation signal profiles.
DOI: 10.48544/692159d8-136f-49a0-9119-74d1c5228472
title: The Rotterdam Energy Transition Program: An integrated and multidisciplinary approach to sustainable energy education
DOI: 10.5281/zenodo.18493467
title: Antibacterial activity of Suberin and composites
DOI: 10.5281/zenodo.18493466
title: Antibacterial activity of Suberin and composites
DOI: 10.17026/dans-xjz-9mb8
title: Consumentenconjunctuuronderzoek - CCO 2017

description: &lt;p&gt;Doel:&lt;br&gt;Het verschaffen van actuele informatie over consumentenopvattingen met betrekking tot de algemene economische ontwikkeling en de financiële situatie van het eigen huishouden. Met behulp van het onderzoek wordt inzicht verkregen in de opvattingen van consumenten, onder meer ten aanzien van de aankoop van duurzame consumptiegoederen. Tevens worden veranderingen in optimisme of pessimisme op korte termijn gesignaleerd, waarmee vroegtijdig een indicatie van een mogelijke trendwijziging van de particuliere consumptie beschikbaar is.&lt;/p&gt;&lt;p&gt;Soort onderzoek:&lt;br&gt;De steekproefeenheid van het CCO is het particuliere huishouden en de steekproefeenheden worden getrokken op basis van een een aselecte tweetrapssteekproef. In de eerste trap wordt een steekproef van gemeenten getrokken en in de tweede trap een steekproef van adressen.&lt;/p&gt;&lt;p&gt;Doelpopulatie:&lt;br&gt;Nederlandse consumenten.&lt;/p&gt;&lt;p&gt;Waarnemingsmethode:&lt;br&gt;De verzameling van de gegevens vond in de periode 1972–1983 plaats aan de hand van een gestructureerde vragenlijst, waarmee door enquêtrices mondelinge interviews werden afgenomen bij Nederlandse particuliere huishoudens. Van het huishouden werd het hoofd of zijn/haar echtgeno(o)t(e)/vaste partner ondervraagd. Behalve in het eerste jaar, waarin alleen in de maanden mei en oktober werd geënquêteerd, werd het onderzoek steeds driemaal per jaar uitgevoerd, in de maanden januari, mei en oktober. Met ingang van januari 1984 heeft de dataverzameling van het CCO telefonisch plaatsgevonden. Naast de methode van waarneming veranderde in die maand ook de onderzoeksfrequentie. Deze werd verhoogd van drie- tot viermaal per jaar, met als enquêteperiodes de maanden januari, april, juli en oktober. In april 1986 werd de frequentie opnieuw verhoogd. Het onderzoek wordt sinds die datum maandelijks gehouden.&lt;/p&gt;&lt;p&gt;Berichtgevers:&lt;br&gt;Van het huishouden wordt het hoofd van het huishouden of zijn/haar echtgeno(o)t(e)/vaste partner ondervraagd.&lt;/p&gt;&lt;p&gt;Steekproefomvang:&lt;br&gt;De steekproefomvang bedraagt ruim 1600 huishoudens.&lt;/p&gt;&lt;p&gt;Controle- en correctiemethoden:&lt;br&gt;Er wordt gecontroleerd op interne consistentie waarbij gekeken wordt naar de achtergrondkenmerken van de respondenten en de plausibiliteit van de uitkomsten met voorgaande perioden.&lt;/p&gt;&lt;p&gt;De conjunctuuronderzoeken bij Nederlandse consumenten, waarmee het CBS in 1972 is gestart, worden mede op verzoek van de Europese Commissie uitgevoerd.&lt;/p&gt;&lt;p&gt;----&lt;/p&gt;&lt;p&gt;Dit betreft een beveiligd microbestand van het Centraal Bureau voor de Statistiek-CBS. Beveiligde micro-bestanden zijn bestanden die zodanig bewerkt zijn dat herkenning van individuen en huishoudens uitgesloten is.&lt;/p&gt;
description: Data Access Protocol has been added.
DOI: 10.5281/zenodo.18492327
title: SuperDARN data in netCDF format (2013-Oct)

description: 2013-Oct SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6480563
title: SuperDARN data in netCDF format (2013-Oct)

description: 2013-Oct SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.18493054
title: Magnetic and sedimentologic data of siliciclastic cave sediments from the Ferice Cave

description: This database contains the magnetic and sedimentologic data of siliciclastic cave sediments from the Ferice Cave (Apuseni Mts., Romania: 46.641411°° N, 22.523353°E, 555 m).
DOI: 10.5281/zenodo.18493053
title: Magnetic and sedimentologic data of siliciclastic cave sediments from the Ferice Cave

description: This database contains the magnetic and sedimentologic data of siliciclastic cave sediments from the Ferice Cave (Apuseni Mts., Romania: 46.641411°° N, 22.523353°E, 555 m).
DOI: 10.6084/m9.figshare.30738773
title: <i>Macromitrium giraldii</i> Müll.Hal. (Orthotrichaceae) recognised as a species on the basis of morphological and phylogenetic evidence

description: <i>Macromitrium giraldii</i> Müll.Hal. was previously considered a synonym of <i>M. japonicum</i> Dozy & Molk. Our ongoing research on the genus <i>Macromitrium</i> Brid. has enabled us to identify morphological differences between <i>M. japonicum</i> and <i>M. giraldii</i>, as well as a close similarity between the latter and the widely distributed East Asian <i>M. cavaleriei</i> Cardot & Thér. Here we present morphological and phylogenetic evidence supporting our speculation that <i>M. giraldii</i> and <i>M. cavarleriei</i> are conspecific, and that the former should be recognised. A morphological study of the original material of <i>Macromitrium giraldii</i>, <i>M. cavaleriei</i>, <i>M. japonicum</i> and their accepted synonyms was conducted, including recent specimens matching their descriptions. A phylogenetic analysis based on the nuclear ITS2 and the plastid <i>trn</i>L–F and <i>trn</i>G regions was performed to investigate relationships within the genus. The morphological and phylogenetic data support <i>Macromitrium giraldii</i> and <i>M. cavaleriei</i> as conspecific, with similarities observed in their branch leaves. All previously accepted synonyms of the latter are additionally confirmed to be <i>M. giraldii</i>. We here propose to synonymise these two species as <i>M. giraldii</i>, since this name has priority. Consequently, <i>M. giraldii</i> is distributed throughout China, as well as in Japan, South Korea, Vietnam, Nepal and India.
DOI: 10.6084/m9.figshare.30738773.v1
title: <i>Macromitrium giraldii</i> Müll.Hal. (Orthotrichaceae) recognised as a species on the basis of morphological and phylogenetic evidence

description: <i>Macromitrium giraldii</i> Müll.Hal. was previously considered a synonym of <i>M. japonicum</i> Dozy & Molk. Our ongoing research on the genus <i>Macromitrium</i> Brid. has enabled us to identify morphological differences between <i>M. japonicum</i> and <i>M. giraldii</i>, as well as a close similarity between the latter and the widely distributed East Asian <i>M. cavaleriei</i> Cardot & Thér. Here we present morphological and phylogenetic evidence supporting our speculation that <i>M. giraldii</i> and <i>M. cavarleriei</i> are conspecific, and that the former should be recognised. A morphological study of the original material of <i>Macromitrium giraldii</i>, <i>M. cavaleriei</i>, <i>M. japonicum</i> and their accepted synonyms was conducted, including recent specimens matching their descriptions. A phylogenetic analysis based on the nuclear ITS2 and the plastid <i>trn</i>L–F and <i>trn</i>G regions was performed to investigate relationships within the genus. The morphological and phylogenetic data support <i>Macromitrium giraldii</i> and <i>M. cavaleriei</i> as conspecific, with similarities observed in their branch leaves. All previously accepted synonyms of the latter are additionally confirmed to be <i>M. giraldii</i>. We here propose to synonymise these two species as <i>M. giraldii</i>, since this name has priority. Consequently, <i>M. giraldii</i> is distributed throughout China, as well as in Japan, South Korea, Vietnam, Nepal and India.
DOI: 10.15468/dl.yymwax
title: Occurrence Download

description: A dataset containing 297812 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation)",
 "Country is China",
 "Month is one of (January, February, March, November, December)",
 "OccurrenceStatus is Present",
 "TaxonKey is Animalia",
 "Year 2020-2021"
 ]
}

 The dataset includes 297812 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013576-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17601004
title: The data for: Glomhopper - A novel subfamily of tyrosine recombinase transposons are active and domesticated in Glomeromycota

description: All identifiers, Glomhopper loci and genomic assemblies are listed in Supplementary file S1, list of tables:

Table 1. List of genomes - list of Glomeromycota genomes used in the study

Table 2. Raw data RPS-tblastn - raw data from RPS-tblastn analysis (against CDD profile - CDD:432262)

Table 3. Genome neighbourhood - genomic surroundings of the DUF3504 domain - Glomhopper - identified by RPS-tblastn

Table 4. Starfish results - results from detecting repeats flanking a new transposon

Table 5. METAEUK results - METAEUK results analyzed by HMMer against the DUF3504 profile

Table 6. minimap2 results - alignment of full length copies on Glomeromycota genomes to the Rhizophagus irregularis GCA_026210795.1 (ASM2621079v1) reference genome

Table 7. Transcriptomics data - Glomhopper expression levels in different Mucoromycota species under stress and non-stress conditions.

HMM profile built from fungal DUF3504 sequences and applied for identification of Glomhopper copies is in Supplementary file S2.

Sequence alignment (aln format) and set of representative Glomhopper sequences (fasta format) with phage CRE integrase is in Supplementary file S3 and S4. Structure alignment (.pse) of 1crx and DUF3504 representative protein is in Supplementary  file S5.

Set of amino acid sequences (Supplementary file S6) and sequence alignment (Supplementary file S7) used for phylogenetic inference and clustering. Phylogenetic tree of diverse YR transposons in newick format (Supplementary file S8).

Set of sequences DUF3405 homologs used for CLANS analysis (Supplementary file S9).
DOI: 10.5281/zenodo.18493513
title: The data for: Glomhopper - A novel subfamily of tyrosine recombinase transposons are active and domesticated in Glomeromycota

description: All identifiers, Glomhopper loci and genomic assemblies are listed in Supplementary file S1, list of tables:

Table 1. List of genomes - list of Glomeromycota genomes used in the study

Table 2. Raw data RPS-tblastn - raw data from RPS-tblastn analysis (against CDD profile - CDD:432262)

Table 3. Genome neighbourhood - genomic surroundings of the DUF3504 domain - Glomhopper - identified by RPS-tblastn

Table 4. Starfish results - results from detecting repeats flanking a new transposon

Table 5. METAEUK results - METAEUK results analyzed by HMMer against the DUF3504 profile

Table 6. minimap2 results - alignment of full length copies on Glomeromycota genomes to the Rhizophagus irregularis GCA_026210795.1 (ASM2621079v1) reference genome

Table 7. Transcriptomics data - Glomhopper expression levels in different Mucoromycota species under stress and non-stress conditions.

HMM profile built from fungal DUF3504 sequences and applied for identification of Glomhopper copies is in Supplementary file S2.

Sequence alignment (aln format) and set of representative Glomhopper sequences (fasta format) with phage CRE integrase is in Supplementary file S3 and S4. Structure alignment (.pse) of 1crx and DUF3504 representative protein is in Supplementary  file S5.

Set of amino acid sequences (Supplementary file S6) and sequence alignment (Supplementary file S7) used for phylogenetic inference and clustering. Phylogenetic tree of diverse YR transposons in newick format (Supplementary file S8).

Set of sequences DUF3405 homologs used for CLANS analysis (Supplementary file S9).
DOI: 10.15468/dl.29uuqv
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-68.7787402757978 -12.536910877500041,-64.7787402757978 -12.536910877500041,-64.7787402757978 -8.536910877500041,-68.7787402757978 -8.536910877500041,-68.7787402757978 -12.536910877500041))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Psecas chapoda"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013608-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15721196
title: Data for "Coherent enhancement of collection of light from linear ion crystals"

description: Here we provide the experimental and theoretical data corresponding to the manuscript "Coherent enhancement of collection of light from linear ion crystals".  The Python code that was used to generate the theoretical data is also provided. 

 

Experimental data are in files Exp_2_ions.text,  Exp_2_ions_repeat.txt, etc. There you can see the relative enhancement P_D, rel dependence on the voltage applied to the tips. From these data, we obtained maximal values, which were then depicted in Figure 3 of the paper.

 

There are three programs harmonic_alpha=45st.py, n=05_alpha=45deg_phase.py, and ekvid_alpha=45st.py.

The program harmonic_alpha=45st.py was used for the majority of simulations.

Its modified version ekvid_alpha=45st.py was used for the generation of data in the file Fig2_c_n=05_equid_alpha=45deg_no_motion.txt.

Its modified version n=05_alpha=45deg_phase was used for the generation of data in the file Fig2_c_n=05_alpha=45deg_phase_no_motion.

 

In Fig2_b_...txt and Fig3_...txt files, there are ion numbers in the first column and their highest values of P_D, rel in the second column.

In Fig2_a_...txt and Fig2_c_n=05_equid_alpha=45deg_no_motion.txt files, there are NA in the first column, the highest values of P_D, rel for corresponding NA and the corresponding spatial length scale l.

In Fig Fig2_c_n=05_alpha=45deg_phase_no_motion.txt file, there are NA in the first column, the highest values of P_D, rel for corresponding NA. In this case, the spatial length scale l = l_min.