cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/89e7d26780f9ea5aab83508e42ece1ba
title: SBC LTER: Reef: Kelp Forest Community Dynamics: Abundance and size of Giant Kelp (Macrocystis Pyrifera), ongoing since 2000

description: These data describe the abundance of giant kelp,Macrocystis
  pyrifera, and are part of the SBCLTER kelp forest
  monitoring program. The study was initiated in 2000, in the Santa
  Barbara Channel, California, USA, and this dataset is updated once per
  year. The number and size (number of fronds and diameter of holdfasts)
  of plants were recorded along permanent transects at nine reef sites
  located along the mainland coast of the Santa Barbara Channel and at
  two sites on the north side Santa Cruz Island. These sites reflect
  several oceanographic regimes in the channel and vary in distance from
  sources of terrestrial runoff.
DOI: 10.5255/ukda-sn-4996-3
title: Deaddocs: a Bibliographical Index of Obituaries and Posthumous Accounts in British Medical Journals and Related Sources, 1750-1850
DOI: 10.5255/ukda-sn-5005-3
title: Scottish-Registered Companies Investing Abroad, 1862-1914
DOI: 10.5255/ukda-sn-5077-3
title: Integrating Quantitative and Qualitative Research : Prospects and Limits, 1994-2003
DOI: 10.5281/zenodo.1299274
title: Colour Values From All Experiments

description: Colour values from all experiments to support thesis
DOI: 10.5281/zenodo.1299275
title: Colour Values From All Experiments

description: Colour values from all experiments to support thesis
DOI: 10.7910/dvn/fjszec/ggvwsz
title: gazbu-CSV.tab
DOI: 10.6073/pasta/dd9c861264dfa8c9a4ec880eef202649
title: SBC LTER: Reef: Long-term experiment: Kelp removal: Urchin size frequency distribution

description: These data describe the size frequency distribution of red and purple
  sea urchins at SBC LTER long-term kelp removal experiment sites. The
  diameter of the test (shell without spines) is recorded in centimeters
  to the nearest 0.5 cm for 50 red and 50 purple sea urchins located in
  40 m x 2 m transects in each sampling plot. These data can be combined
  with size-mass relationships established in the laboratory to provide
  a non-destructive estimate of red and urchin dry mass.

      
  The kelp removal experiment was initiated in 2008 at selected reef
  sites along the mainland coast of the Santa Barbara Channel. The
  following three giant kelp manipulations are maintained in sampling
  plots at each site:

      
  - Control: Macrocystis pyriferais left intact in
  a 2000 m2plot.

      
  - Annual removal: Macrocystis pyriferais removed
  from an adjacent 2000 m2plot once each
  winter and allowed to re-colonize over the course of the year.

      
  - Continuous removal: Macrocystis pyriferais
  removed from a 200 m2area within the 2000
  m2 plot on each sampling date.
DOI: 10.6073/pasta/ec0f2435a1db79542509653a386ed97e
title: SBC LTER: Reef: Long-term experiment: Kelp removal: Fish abundance

description: These data describe the abundance and size of reef-associated fish at
  SBC LTER long-term kelp removal experiment sites. The number and size
  of reef fish located 0-2 meters from the bottom within a 40 m x 2 m
  transect are recorded by a diver in each plot at the start of the
  sampling day. The number and sizes of cryptic fish associated with the
  bottom are recorded in the same 40m x 2 m transects in a separate
  survey. Cryptic species are recorded in selected 20 meter sub-sections
  of an 80 m2 permanent transect. Cryptic
  species are not recorded on continuous removal transects.

      
  The kelp removal experiment was initiated in 2008 at selected reef
  sites along the mainland coast of the Santa Barbara Channel. The
  following three giant kelp manipulations are maintained in sampling
  plots at each site:

      
  - Control: Macrocystis pyriferais left intact in
  a 2000 m2plot.

      
  - Annual removal: Macrocystis pyriferais removed
  from an adjacent 2000 m2plot once each
  winter and allowed to re-colonize over the course of the year.

      
  - Continuous removal: Macrocystis pyriferais
  removed from a 200 m2area within the 2000
  m2 plot on each sampling date.
DOI: 10.5281/zenodo.1245941
title: Jingju A Cappella Singing Dataset Part1

description: This is the 4th version of the dataset. The folder structure has been changed since the 2nd version, where the Laosheng folder has been moved directly into wav or textgrid folder.

<strong>Description:</strong>

This dataset is a collection of boundary annotations of a cappella singing performed by Beijing Opera (Jingju, 京剧) professional and amateur singers. 


	wav.zip: audio files in .wav format, mono or stereo.
	wav_mono.zip: audio files in .wav format, mono
	pycode.zip: util code for parsing the .textgrid annotation
	catalogue*.csv: recording metadata, source separation recordings are not included.
	textgrid.zip: phrase, syllable and phoneme annotation in Praat .textgrid format
	annotation_txt.zip: phrase, syllable and phoneme time boundaries (second) and labels in .txt format
	
		*phrase_char: phrase-level time boundaries, labeled in Mandarin characters
		*phrase: phrase-level time boundaries, labeled in Mandarin pinyin
		*syllable: syllable-level time boundaries, labeled in Mandarin pinyin
		*phoneme: phoneme-level time boundaries, labeled in X-SAMPA
	
	


The boundaries (onset and offset) have been annotated in both <strong>Praat TextGrid (textgrid.zip)</strong> and .<strong>txt (annotation_txt.zip)</strong> format hierarchically:


	phrase (line),
	syllable,
	phoneme


Singing units in pinyin and X-SAMPA have been annotated to a jingju a cappella singing audio dataset.

The corresponding audio files are the a cappella singing arias recordings, which are stereo or mono, sampled at 44.1 kHz, and stored as .wav files. The .wav files are recorded by two institutes: those file names ending with ‘qm’ are recorded by C4DM, Queen Mary University of London; others file names ending with ‘upf’ or ‘lon’ are recorded by MTG-UPF. Additionally, another collection of 15 clean singing recordings is included in this dataset. They are extracted from the commercial recordings which originally contains karaoke accompaniment and mixed versions.

<strong>If you use this audio dataset in your work, please cite (1) this dataset as well (2) the following publication:</strong>


D. A. A. Black, M. Li, and M. Tian, “Automatic Identification of Emotional Cues in Chinese Opera Singing,” in 13th Int. Conf. on Music Perception and Cognition (ICMPC-2014), 2014, pp. 250–255.


 

<strong>Details:</strong><br>
Annotation format, units, parsing code and other information please refer to https://github.com/MTG/jingjuPhonemeAnnotation

<br>
<strong>License:</strong><br>
Textgrid annotations are licensed under Creative Commons Attribution-NonCommercial 4.0 International License.

Wav audio ending with ‘upf’ or ‘lon’ is licensed under Creative Commons Attribution-NonCommercial 4.0 International.

For the license of .wav audio ending with ‘qm’ from C4DM Queen Mary University of London, please refer to this page http://isophonics.org/SingingVoiceDataset

<strong>Contact information:</strong>

Rong Gong: rong&lt;dot&gt;gong&lt;at&gt;upf&lt;dot&gt;edu

Rafael Caro Repetto: rafael&lt;dot&gt;caro&lt;at&gt;upf&lt;dot&gt;edu
DOI: 10.5281/zenodo.1245943
title: Jingju A Cappella Singing Dataset Part3

description: 这是京剧清唱数据库的第三部分。这个部分集中于音乐教育的应用。对每个唱段,我们采集了老师和学生的录音。

This is the 3rd part of the jingju a cappella singing dataset. This part focus on the music education application. For this purpose, we collected both "teacher" and "students" recordings for each aria.

<strong>文件 Files:</strong>


	wav_left.zip: audio files in .wav format, mono
	textgrid.zip: line, syllable and phoneme time boundaries and labels, in Praat .textgrid format
	annotation_txt.zip:  line, syllable and phoneme time boundaries and labels, in .txt format
	
		*phrase_char: phrase-level time boundaries, labeled in Mandarin characters
		*phrase: phrase-level time boundaries, labeled in Mandarin pinyin
		*syllable: syllable-level time boundaries, labeled in Mandarin pinyin
		*phoneme: phoneme-level time boundaries, labeled in X-SAMPA
	
	


 

<strong>艺术家 Artists:</strong>

示范录音取自3位年轻的专业京剧演员。学生录音取自几位非专业小学生和非艺术类大学的学生。

Teacher recordings are recorded by 3 professional young jingju performers. Student recordings are performed by several non-jingju professional primary school students and some non-art university students. 

 

<strong>标注 Annotation:</strong>

数据库包含一部分录音的唱句起始位置和音节起始位置标注,标注格式为Praat TextGrid。唱句标注包含有每一唱句的歌词,此歌词从曲谱提取,并不与实际演唱一致;音节标注包含拼音,音素标注为X-SAMPA,经过作者修正,试图与演唱发音一致。

The dataset contains the line and syllable boundary annotation for a part of recordings, in Praat TextGrid format. The line annotation contains the lyrics for each line, which is extracted from the score, and might not coherent with the actual singing; the syllable annotation contains pinyin, phoneme annotation uses X-SAMPA, corrected by the author to be coherent with the actual singing.

标注X-SAMPA格式和其他信息可以参考以下链接:

Annotation format, units, parsing code and other information please refer to:

https://github.com/MTG/jingjuPhonemeAnnotation

 

<strong>协议 License:</strong>

Creative Commons Attribution-NonCommercial 4.0

 

<strong>联系方式 Contact information</strong>:

<em>如果任何问题,请联系作者 </em><em>If you have any question, please contact the author:</em>

龚嵘 Rong Gong: Email - rong&lt;dot&gt;gong&lt;at&gt;upf&lt;dot&gt;edu, Wechat id - gongr86
DOI: 10.6073/pasta/43c5524d0d1369abb7290dfd98fb3d66
title: SBC LTER: Long-term experiment: Kelp Removal: Transect depth data

description: These data summarize depth information (mean, standard deviation and
  coefficient of variation) for all of the transects surveyed as part of
  the SBC LTER Long Term Kelp Removal Experiment. All data are expressed
  in meters, referenced to mean lower low water (MLLW). Each value is
  the result of 160 observations, four at each meter (n=160). The
  sampling locations in this dataset are 40 meter transects at four reef
  sites along the mainland coast of the Santa Barbara Channel,
  California, USA. These data were recorded in 2010.
DOI: 10.6073/pasta/63e09cd891bf2b323c5ad015648c2220
title: SBC LTER: Reef: Kelp Forest Community Dynamics: Transect depth data

description: These data provide summaries of depth information (mean, standard
  deviation and coefficient of variation) for all of the transects
  surveyed as part of the SBC LTER Kelp Forest Monitoring program. All
  data are expressed in meters, reference to mean lower low water
  (MLLW). Each value is the result of 160 observations, four at each
  meter (n=160). The sampling locations in this dataset are 40 meter
  transects at nine reef sites along the mainland coast of the Santa
  Barbara Channel and at two sites on the north side of Santa Cruz
  Island. Data were recorded in 2010.
DOI: 10.6073/pasta/be9107e5c13f5fe80bad2d342f6d00ec
title: SBC LTER: Reef: Long-term experiment: Kelp removal: Invertebrate and algal density

description: These data describe the abundance of common mobile macro invertebrates
  and macroalgae located at SBC LTER long-term kelp removal experiment
  sites. The number of individuals of approximately 50 taxa are recorded
  in 40 m x 2 m transects in each plot. Large algae and large mobile
  invertebrates are enumerated within selected 20
  m2sub-sections on each 40 m x 2 m transect
  and small algae and small invertebrates are enumerated in six
  permanent 1 m2quadrats positioned uniformly
  along the 40 m x 2 m transect.

      
  The kelp removal experiment was initiated in 2008 at selected reef
  sites along the mainland coast of the Santa Barbara Channel. The
  following three giant kelp manipulations are maintained in sampling
  plots at each site:

      
  - Control: Macrocystis pyriferais left intact in
  a 2000 m2plot.

      
  - Annual removal: Macrocystis pyriferais removed
  from an adjacent 2000 m2plot once each
  winter and allowed to re-colonize over the course of the year.

      
  - Continuous removal: Macrocystis pyriferais
  removed from a 200 m2area within the 2000
  m2 plot on each sampling date.
DOI: 10.4226/95/5b348fdedb86c
title: Modelling of flora and fauna in Nepal and adjacent Himalayas

description: PhD thesis dataset including the modelling of flora and fauna in Nepal and adjacent Himalayas. Climate change impacts for flora and fauna in the region were the posited from these models.
DOI: 10.5525/gla.researchdata.633
title: How fast is a twisted photon?
DOI: 10.17632/n2f2gb9m6h.1
title: Data for: Binder-free, Freestanding Cathodes Fabricated with an Ultra-rapid Diffusion of Sulfur into Carbon Nanofibers for Lithium-Sulfur Batteries

description: A rapid (5-second) sulfur deposition technique is demonstrated on electrospun carbon nanofibers to fabricate binder-free, freestanding cathodes for lithium-sulfur batteries. The 5-second procedure melts sulfur into carbon nanofiber mats, which play a significant role as a built-in conductive matrix to provide uninterrupted electron transport pathways throughout the electrode such that the heavy current collector is eliminated. Meanwhile, the large inter-fiber spacing facilitates electrolyte diffusion and provides sufficient space for sulfur integration during cathode fabrication and the volume expansion during lithium-sulfur redox reaction. This technique eliminates the need for slurry processing with insulating binders and toxic solvents as well as eliminating heavy current collectors. This ultra-rapid technique involving only 140 °C, 5 s, and slight pressure (&lt; 250 psi) offers a practical approach to light-weight sulfur cathodes compared to the conventional sulfur melt deposition techniques requiring high temperatures (155 - 300 °C), long times (8 - 10 h), and heavy components in the cell assembly. The cathodes thus obtained deliver a discharge capacity of ~ 550 mA h gsulfur-1 owing to their simple construction, with 100% capacity retention at 0.5C rate over 150 cycles. This translates to ~250 mA h gelectrode-1 (based on total mass at the cathode) which is comparable to highly sophisticated electrodes when the weight of the entire electrode and current collector is considered.
DOI: 10.5281/zenodo.1299158
title: Sensitive Detection Of Mitochondrial Structural Alterations On Simulated Data

description: Testing three different sensitive sequence aligners (BLAT, BLASTn, LAST) on simulated data generated from reference human mitochondrial genome along with genomes with a deletion and a duplication.  The aim is to identify the aligner best suited for detection of large structural alterations in the mitochondrial genome.
DOI: 10.5281/zenodo.1299159
title: Sensitive Detection Of Mitochondrial Structural Alterations On Simulated Data

description: Testing three different sensitive sequence aligners (BLAT, BLASTn, LAST) on simulated data generated from reference human mitochondrial genome along with genomes with a deletion and a duplication.  The aim is to identify the aligner best suited for detection of large structural alterations in the mitochondrial genome.
DOI: 10.5517/ccdc.csd.cc1220y3
title: CCDC 985054: Experimental Crystal Structure Determination

description: Related Article: Siddhartha S. Baisya and Parag S. Roy|2018|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc122wst
title: CCDC 985886: Experimental Crystal Structure Determination

description: Related Article: Md Afser Ali, Siddhartha S. Baisya and Parag S. Roy|2018|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc133phd
title: CCDC 1016443: Experimental Crystal Structure Determination

description: Related Article: Ru-Yi Jin, Chu-Yue Zeng, Xu-Hua Liang, Xiao-Hong Sun, Yuan-Fa Liu, Yan-Yan Wang, Sha Zhou|2018|Bioorg.Chem.|80|253|doi:10.1016/j.bioorg.2018.06.030
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc13rzd7
title: CCDC 1035939: Experimental Crystal Structure Determination

description: Related Article: Chandana Sen, Chiranjit Patra, Sudipa Mondol, Amitabha Datta, Debashis Mallick, Tapan Kumar Mondal, Tulin Askun, Pinar Celikboyun, Zerrin Cantürk, Chittaranjan Sinha|2018|Polyhedron|152|1|doi:10.1016/j.poly.2018.05.062
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cczt1sl
title: CCDC 917810: Experimental Crystal Structure Determination

description: Related Article: Di Wu, Lingfeng Chen, Shuangliang Ma, Huiying Luo, Jing Cao, Runfeng Chen, Zheng Duan, Francois Mathey|2018|Org.Lett.|20|4103|doi:10.1021/acs.orglett.8b01663
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.1298640
title: Dataset For Survey On Applications Of Graph Analysis

description: This archive contains data collected and processed while conducting our survey on graph analysis applications. We provide data from three stages of our process to facilitate validation and reproduction of our results. All results are provided in TSV format (Tab-Separated Values). The completed survey will be submitted for publication in the near future.

The file "1-query-results.tsv" contains the top 100 search results for 8 queries performed using Google Scholar. For each result we include the query used, the title of the result, and a link to the publication.

The file "2-filtered-relevant-results.tsv" contains the subset of search results we found to be relevant, i.e., the work describes an application of graph analysis.

The file "3-characterization-of-selected-results.tsv" contains a selection of 60 applications (articles) we reviewed and characterized based on our taxonomy for graph analysis applications. Included are the domain of each application and a set of characteristics. For each characteristic, a value of 1 represents that we consider the characteristic to be present in the surveyed application. Legend for characteristics:

    Graph features:<br>
    - Directed<br>
    - Weighted: vertex (V), edge (E), edge weights removed after filtering low weight edges from input (*).<br>
    - Heterogeneous: vertex (V), edge (E).<br>
    - Properties: vertex (V), edge (E).<br>
    - Temporal<br>
    Analysis methods:<br>
    - Neighborhood Statistics: clustering coefficient (C), degree distribution (D), other (*).<br>
    - Paths & Traversals: shortest path (S), average path length (A), maximum path length (M), traversal (T), other (*).<br>
    - Connectivity: weakly connected components (W), strongly connected components (S).<br>
    - Centrality & Ranking: betweenness centrality (B), closeness centrality (C), degree centrality (D), PageRank (P), other (*).<br>
    - Clustering: rule-based (R), community-based (C).<br>
    - Subgraph Isomorphism & Mining: pattern detection (P), subgraph isomorphism (S), frequent subgraph mining (F), discriminative subgraph mining (D).<br>
    - Graph Mutation: construction (C), reduction (R).<br>
DOI: 10.5281/zenodo.1298639
title: Dataset For Survey On Applications Of Graph Analysis

description: This archive contains data collected and processed while conducting our survey on graph analysis applications. We provide data from three stages of our process to facilitate validation and reproduction of our results. All results are provided in TSV format (Tab-Separated Values). The completed survey will be submitted for publication in the near future.

The file "1-query-results.tsv" contains the top 100 search results for 8 queries performed using Google Scholar. For each result we include the query used, the title of the result, and a link to the publication.

The file "2-filtered-relevant-results.tsv" contains the subset of search results we found to be relevant, i.e., the work describes an application of graph analysis.

The file "3-characterization-of-selected-results.tsv" contains a selection of 60 applications (articles) we reviewed and characterized based on our taxonomy for graph analysis applications. Included are the domain of each application and a set of characteristics. For each characteristic, a value of 1 represents that we consider the characteristic to be present in the surveyed application. Legend for characteristics:

    Graph features:<br>
    - Directed<br>
    - Weighted: vertex (V), edge (E), edge weights removed after filtering low weight edges from input (*).<br>
    - Heterogeneous: vertex (V), edge (E).<br>
    - Properties: vertex (V), edge (E).<br>
    - Temporal<br>
    Analysis methods:<br>
    - Neighborhood Statistics: clustering coefficient (C), degree distribution (D), other (*).<br>
    - Paths & Traversals: shortest path (S), average path length (A), maximum path length (M), traversal (T), other (*).<br>
    - Connectivity: weakly connected components (W), strongly connected components (S).<br>
    - Centrality & Ranking: betweenness centrality (B), closeness centrality (C), degree centrality (D), PageRank (P), other (*).<br>
    - Clustering: rule-based (R), community-based (C).<br>
    - Subgraph Isomorphism & Mining: pattern detection (P), subgraph isomorphism (S), frequent subgraph mining (F), discriminative subgraph mining (D).<br>
    - Graph Mutation: construction (C), reduction (R).<br>
DOI: 10.5285/8e0f07ce-d8ef-4286-92bd-9019875df5cb
title: Data files from study of Thermoremanent behavior in synthetic samples containing natural oxyexsolved titanomagnetite

description: All the raw experimental data obtained for the study reported in Hodgson, E., Grappone, J. M., Biggin, A. J., Hill, M. J., & Dekkers, M. J. (2018). Thermoremanent behavior in synthetic samples containing natural oxyexsolved titanomagnetite. Geochemistry, Geophysics, Geosystems, 19. https://doi.org/10.1029/2017GC007354
DOI: 10.5517/ccdc.csd.cc14b39w
title: CCDC 1052397: Experimental Crystal Structure Determination

description: Related Article: Mi Jin Kim, Myung Jin Jung, Yeong Joon Kim, Ha Kyoung Sung, Ju Young Lee, Sung Jin Ham, Chan Pil Park|2018|Tetrahedron Lett.|59|2989|doi:10.1016/j.tetlet.2018.06.051
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.