cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3893276
title: Crustaceans from the Gulf of Mexico and Mexican Caribbean at the "Colección Carcinológica de Yucatán" at UMDI-Sisal, Facultad de Ciencias, UNAM, México.

description: The dataset contains information on the “<em>Colección Carcinológica de Yucatán</em>” (federal register <em>YUC-CC-255-11</em>) at the Unidad Multidisciplinaria de Docencia e Investigación, Facultad de Ciencias, UNAM. This dataset represents only specimens identified to genus and species (3951 specimens) from localities at the coast, depth sea, and coral reefs at the Gulf of Mexico and Mexican Caribbean for a period of time from 1976 to 2020. The specimens at the collection have been either identified or validated by professional crustacean taxonomists, providing a significant level of trust in the data. The taxonomists that participated in this process appear in the list of authors.
DOI: 10.21258/1614333
title: Inventario forestale nazionale svizzero - Tabella n. 897669
DOI: 10.14272/rjlccsuqzuoztj-uhfffaoysa-m/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C27H31N4O7.BrH/c1-32-24-3-2-19-14-23-21-16-26-25(37-18-38-26)15-20(21)4-6-31(23)17-22(19)27(24)36-13-12-35-11-10-34-9-8-33-7-5-29-30-28;/h2-3,14-17H,4-13,18H2,1H3;1H/q+1;/p-1

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, DMSO-d6, ppm) δ 9.78 (s, 1H), 8.95 (s, 1H), 8.20 (d, J = 9.2 Hz, 1H), 8.01 (d, J = 9.1 Hz, 1H), 7.81 (s, 1H), 7.10 (s, 1H), 6.18 (s, 2H), 4.93 (t, J = 6.2 Hz, 2H), 4.42 (t, J = 4.4 Hz, 2H), 4.06 (s, 3H), 3.81 (t, J = 4.4 Hz, 2H), 3.60–3.48 (m, 12H), 3.22 (t, J = 3.1 Hz, 2H).
DOI: 10.14272/rjlccsuqzuoztj-uhfffaoysa-m/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C27H31N4O7.BrH/c1-32-24-3-2-19-14-23-21-16-26-25(37-18-38-26)15-20(21)4-6-31(23)17-22(19)27(24)36-13-12-35-11-10-34-9-8-33-7-5-29-30-28;/h2-3,14-17H,4-13,18H2,1H3;1H/q+1;/p-1

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (126 MHz, DMSO-d6, ppm) δ 150.6, 149.9, 147.7, 145.5, 142.6, 137.5, 133.0, 130.7, 126.6, 123.6, 122.0, 120.3, 120.3, 108.5, 105.5, 102.1, 73.1, 69.8, 69.6, 69.6, 69.5, 69.4, 69.2, 57.0, 55.5, 50.0, 26.4.
DOI: 10.21258/1597755
title: Inventario forestale nazionale svizzero - Tabella n. 897838
DOI: 10.21258/1550767
title: Inventaire forestier national suisse - Tableau no 899284
DOI: 10.5281/zenodo.3893250
title: Marine Flatworms (Polycladida) from the Gulf of Mexico and Mexican Caribbean at the "Colección Regional de Policládidos de la Península de Yucatán" at Faculty of Science, UNAM

description: The dataset contains information about the collection “Policládidos de la Península de Yucatán” at the Unidad Multidisciplinaria de Docencia e Investigación, Faculty of Science, UNAM. This dataset represents only specimens of Order Polycladida identified to genus and species (122 specimens) from 12 localities of coastal lagoons and coral reefs at the Gulf of Mexico and Mexican Caribbean for a period of time from 2017 to 2019. The dataset contains information about specimens belonging to 12 families, 17 genera, and 19 species. The specimens at the collection have been either identified or validated by professional taxonomists, providing a significant level of trust in the data. The taxonomists that participated in this process appear in the list of authors
DOI: 10.5281/zenodo.3893249
title: Marine Flatworms (Polycladida) from the Gulf of Mexico and Mexican Caribbean at the "Colección Regional de Policládidos de la Península de Yucatán" at Faculty of Science, UNAM

description: The dataset contains information about the collection “Policládidos de la Península de Yucatán” at the Unidad Multidisciplinaria de Docencia e Investigación, Faculty of Science, UNAM. This dataset represents only specimens of Order Polycladida identified to genus and species (122 specimens) from 12 localities of coastal lagoons and coral reefs at the Gulf of Mexico and Mexican Caribbean for a period of time from 2017 to 2019. The dataset contains information about specimens belonging to 12 families, 17 genera, and 19 species. The specimens at the collection have been either identified or validated by professional taxonomists, providing a significant level of trust in the data. The taxonomists that participated in this process appear in the list of authors
DOI: 10.21258/1590571
title: Inventario forestale nazionale svizzero - Tabella n. 899284
DOI: 10.21258/1592042
title: Inventario forestale nazionale svizzero - Tabella n. 891772
DOI: 10.21258/1594974
title: Inventario forestale nazionale svizzero - Tabella n. 897631
DOI: 10.21258/1553534
title: Inventaire forestier national suisse - Tableau no 898800
DOI: 10.21258/1569782
title: Inventaire forestier national suisse - Tableau no 898964
DOI: 10.21258/1569339
title: Inventaire forestier national suisse - Tableau no 897292
DOI: 10.21258/1591236
title: Inventario forestale nazionale svizzero - Tabella n. 897151
DOI: 10.21258/1552081
title: Inventaire forestier national suisse - Tableau no 897644
DOI: 10.21258/1541442
title: Inventaire forestier national suisse - Tableau no 897141
DOI: 10.21258/1557419
title: Inventaire forestier national suisse - Tableau no 898787
DOI: 10.21258/1534171
title: Inventaire forestier national suisse - Tableau no 891804
DOI: 10.21258/1619453
title: Inventario forestale nazionale svizzero - Tabella n. 897560
DOI: 10.21258/1590360
title: Inventario forestale nazionale svizzero - Tabella n. 897502
DOI: 10.21258/1592364
title: Inventario forestale nazionale svizzero - Tabella n. 897229
DOI: 10.21258/1586656
title: Inventario forestale nazionale svizzero - Tabella n. 902179
DOI: 10.21258/1569074
title: Inventaire forestier national suisse - Tableau no 891992
DOI: 10.21258/1616215
title: Inventario forestale nazionale svizzero - Tabella n. 897046
DOI: 10.21258/1556640
title: Inventaire forestier national suisse - Tableau no 896915
DOI: 10.21258/1617385
title: Inventario forestale nazionale svizzero - Tabella n. 899411
DOI: 10.21258/1591352
title: Inventario forestale nazionale svizzero - Tabella n. 902082
DOI: 10.5281/zenodo.4066776
title: Figure Data for the paper: "Observation of the onset of a blue jet into the stratosphere"

description: Data files for the figures in Neubert et al. (2019): "Observation of the onset of a blue jet into the stratosphere". The data is given per panel of the respective figure. Figure and panel are indicated in the file name. The photometer data is given as one time sequence without the separation in frames, while the camera data is stored per frame. The different frames have their own tab in the .xlsx files. More information on the data of this study is given in the main paper.
DOI: 10.5281/zenodo.4066775
title: Figure Data for the paper: "Observation of the onset of a blue jet into the stratosphere"

description: Data files for the figures in Neubert et al. (2019): "Observation of the onset of a blue jet into the stratosphere". The data is given per panel of the respective figure. Figure and panel are indicated in the file name. The photometer data is given as one time sequence without the separation in frames, while the camera data is stored per frame. The different frames have their own tab in the .xlsx files. More information on the data of this study is given in the main paper.
DOI: 10.21258/1594244
title: Inventario forestale nazionale svizzero - Tabella n. 902291
DOI: 10.21258/1557625
title: Inventaire forestier national suisse - Tableau no 891860
DOI: 10.21258/1617724
title: Inventario forestale nazionale svizzero - Tabella n. 893054
DOI: 10.21258/1616862
title: Inventario forestale nazionale svizzero - Tabella n. 891925
DOI: 10.21258/1532309
title: Inventaire forestier national suisse - Tableau no 891878
DOI: 10.6084/m9.figshare.12318653
title: Projected losses of ecosystem services due to coastal erosion in Europe

description: This dataset provides projections of losses to coastal ecosystem services induced by coastal erosion in Europe for years 2050 and 2100. It is particularly based on Corine Land Cover 2018 and probabilistic erosion projections by the European Commission - Joint Research Centre.
DOI: 10.6084/m9.figshare.12318653.v3
title: Projected losses of ecosystem services due to coastal erosion in Europe

description: This dataset provides projections of losses to coastal ecosystem services induced by coastal erosion in Europe for years 2050 and 2100. It is particularly based on Corine Land Cover 2018 and probabilistic erosion projections by the European Commission - Joint Research Centre
DOI: 10.21258/1546207
title: Inventaire forestier national suisse - Tableau no 891928
DOI: 10.5281/zenodo.4318006
title: model data of 90 ma

description: modeling data for the Asia
DOI: 10.5281/zenodo.4318005
title: model data of 90 ma

description: modeling data for the Asia
DOI: 10.21258/1568830
title: Inventaire forestier national suisse - Tableau no 892036
DOI: 10.21258/1569177
title: Inventaire forestier national suisse - Tableau no 897012
DOI: 10.21258/1618923
title: Inventario forestale nazionale svizzero - Tabella n. 897506
DOI: 10.5281/zenodo.4300382
title: Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant - Datasets, Trained Models, BNN Samples, and MCMC Chains

description: We publish the training/validation/test datasets, trained model weights, configuration files, Bayesian neural network samples, and MCMC chains used to produce the figures in the LSST DESC paper, "Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant." They are formatted to be used with the DESC package "H0rton" (https://github.com/jiwoncpark/h0rton). Additional descriptions can be found in the README. Please contact Ji Won Park (@jiwoncpark) on GitHub or make an issue for any questions.
DOI: 10.5281/zenodo.4300381
title: Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant - Datasets, Trained Models, BNN Samples, and MCMC Chains

description: We publish the training/validation/test datasets, trained model weights, configuration files, Bayesian neural network samples, and MCMC chains used to produce the figures in the LSST DESC paper, "Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant." They are formatted to be used with the DESC package "H0rton" (https://github.com/jiwoncpark/h0rton). Additional descriptions can be found in the README. Please contact Ji Won Park (@jiwoncpark) on GitHub or make an issue for any questions.
DOI: 10.21258/1542332
title: Inventaire forestier national suisse - Tableau no 899631
DOI: 10.21258/1559984
title: Inventaire forestier national suisse - Tableau no 899458
DOI: 10.21258/1582683
title: Inventario forestale nazionale svizzero - Tabella n. 892837
DOI: 10.21258/1545946
title: Inventaire forestier national suisse - Tableau no 897518
DOI: 10.21258/1566216
title: Inventaire forestier national suisse - Tableau no 897751
DOI: 10.21258/1545987
title: Inventaire forestier national suisse - Tableau no 898085
DOI: 10.21258/1584068
title: Inventario forestale nazionale svizzero - Tabella n. 896914
DOI: 10.21258/1534074
title: Inventaire forestier national suisse - Tableau no 902169
DOI: 10.21227/1h27-e241
title: Aviation droplet detection based on DNN

description: Deep learning has been widely used in various sensor detection fields to realize intelligent detection tasks. However, there are always restrictions on how these functions can be integrated into embedded devices to complete mobile and convenient sensing detection tasks. Therefore, the MobileNet_SSD, A lightweight model after simplification and optimization, is used in this paper to design a portable visual sensor system for the detection of spray droplet deposition in drone applications. The sensing system includes a droplet deposition image loop acquisition device and a supporting host computer interactive platform. It introduces the Sarsa algorithm to establish an adaptive model of light intensity to enhance the robustness and combines Deep Neural Networks and image processing technology to achieve rapid loop detection of droplet deposition parameters on the mobile terminal. Experimental results indicate that the proposed sensor can adapt to light changes in complex environments, and accurately measure the deposition parameters of different droplet density images. Furthermore, it is of great significance to detect the quality of drone sprays, master the rules of droplet deposition, and understand the effects of pesticide spraying.
DOI: 10.21227/3sw5-za78
title: Aviation droplet detection based on DNN

description: Deep learning has been widely used in various sensor detection fields to realize intelligent detection tasks. However, there are always restrictions on how these functions can be integrated into embedded devices to complete mobile and convenient sensing detection tasks. Therefore, the MobileNet_SSD, A lightweight model after simplification and optimization, is used in this paper to design a portable visual sensor system for the detection of spray droplet deposition in drone applications. The sensing system includes a droplet deposition image loop acquisition device and a supporting host computer interactive platform. It introduces the Sarsa algorithm to establish an adaptive model of light intensity to enhance the robustness and combines Deep Neural Networks and image processing technology to achieve rapid loop detection of droplet deposition parameters on the mobile terminal. Experimental results indicate that the proposed sensor can adapt to light changes in complex environments, and accurately measure the deposition parameters of different droplet density images. Furthermore, it is of great significance to detect the quality of drone sprays, master the rules of droplet deposition, and understand the effects of pesticide spraying.
DOI: 10.21258/1621088
title: Inventario forestale nazionale svizzero - Tabella n. 897508
DOI: 10.21258/1568632
title: Inventaire forestier national suisse - Tableau no 897619
DOI: 10.21258/1538697
title: Inventaire forestier national suisse - Tableau no 899085
DOI: 10.6084/m9.figshare.12927545
title: Metabolomics - Raw metabolites datasets

description: Raw datasets of abundances of identified metabolites. "raw data long_cleaned" is the dataset in a long format, with each column representing a different variable. "raw full data_no duplo" is the dataset in a wide format, where each column is an individual bird, while metabolites are on different rows.
DOI: 10.21258/1586280
title: Inventario forestale nazionale svizzero - Tabella n. 899149
DOI: 10.6084/m9.figshare.12927539
title: Metabolomics - Lists of significant metabolites from LMM

description: Lists of metabolites found to be significantly affected by the interaction of treatment and time of day, only by treatment, or only by time of day
DOI: 10.6084/m9.figshare.12927539.v1
title: Metabolomics - Lists of significant metabolites from LMM

description: Lists of metabolites found to be significantly affected by the interaction of treatment and time of day, only by treatment, or only by time of day
DOI: 10.6084/m9.figshare.12927536
title: Metabolomics - PCA factor loading tables

description: Factor loading tables produced by two PCA run on only daytime samples or only nighttime samples, using the interactive dataset
DOI: 10.6084/m9.figshare.12927536.v1
title: Metabolomics - PCA factor loading tables

description: Factor loading tables produced by two PCA run on only daytime samples or only nighttime samples, using the interactive dataset
DOI: 10.6084/m9.figshare.13325480
title: Activity - periodogram data

description: Raw data from chronoshop on period length for each bird, to use for periodogram analysis (tau)
DOI: 10.6084/m9.figshare.13325480.v1
title: Activity - periodogram data

description: Raw data from chronoshop on period length for each bird, to use for periodogram analysis (tau)
DOI: 10.6084/m9.figshare.13302476.v1
title: Activity-individuals info

description: Information for each individual used in the activity analyses
DOI: 10.6084/m9.figshare.13302476
title: Activity-individuals info

description: Information for each individual used in the activity analyses
DOI: 10.6084/m9.figshare.13302467
title: Activity-averages for four traits

description: Dataset with activity data resulted from post-processing with Chronoshop, which generated daily values for onset, offset and total activity and nocturnal activity, for each individual bird
DOI: 10.6084/m9.figshare.13302467.v1
title: Activity-averages for four traits

description: Dataset with activity data resulted from post-processing with Chronoshop, which generated daily values for onset, offset and total activity and nocturnal activity, for each individual bird
DOI: 10.6084/m9.figshare.13302455.v1
title: Activity data-high resolution

description: High resolution activity dataset with binned activity for each individual bird (individuals in columns)
DOI: 10.6084/m9.figshare.13302455
title: Activity data-high resolution

description: High resolution activity dataset with binned activity for each individual bird (individuals in columns)
DOI: 10.6084/m9.figshare.13302452.v1
title: Spleen gene expression data

description: Raw data from gene expression analyses of spleen tissue
DOI: 10.6084/m9.figshare.13302452
title: Spleen gene expression data

description: Raw data from gene expression analyses of spleen tissue
DOI: 10.6084/m9.figshare.13302443
title: Liver gene expression data

description: Raw data from gene expression analyses of liver tissue
DOI: 10.6084/m9.figshare.13302437.v1
title: Hippocampus gene expression data

description: Raw data from gene expression analyses of hippocampus tissue
DOI: 10.6084/m9.figshare.13302437
title: Hippocampus gene expression data

description: Raw data from gene expression analyses of hippocampus tissue
DOI: 10.6084/m9.figshare.13302428.v1
title: Hypothalamus gene expression data

description: Raw data from gene expression analyses of hypothalamus tissue
DOI: 10.6084/m9.figshare.13302428
title: Hypothalamus gene expression data

description: Raw data from gene expression analyses of hypothalamus tissue
DOI: 10.6084/m9.figshare.13302419.v1
title: Metabolomics - IDEOM dataset

description: This is the raw dataset produced through the IDEOM platform by Glasgow Polyomics.
DOI: 10.6084/m9.figshare.13302419
title: Metabolomics - IDEOM dataset

description: This is the raw dataset produced through the IDEOM platform by Glasgow Polyomics.
DOI: 10.6084/m9.figshare.12927548.v1
title: Metabolomics - Individual information for each bird sample

description: individual info for each bird sample
DOI: 10.6084/m9.figshare.12927548
title: Metabolomics - Individual information for each bird sample

description: individual info for each bird sample
DOI: 10.21258/1530009
title: Inventaire forestier national suisse - Tableau no 897482
DOI: 10.21258/1544116
title: Inventaire forestier national suisse - Tableau no 898262
DOI: 10.25919/xkrg-9p32
title: Parkes observations for project P1066 semester 2020APRS_04

description: We propose 36 hrs of Parkes observations to continue our successful Deeper, Wider, Faster (DWF) program to detect fast transients and fast radio burst (FRB) counterparts and help resolve their nature. DWF coordinates over 60 observatories worldwide at all wavelengths, from radio to gamma-ray to detect and follow-up FRBs and other elusive fast (millisecond-to-hours duration) transients. Crucially, we coordinate simultaneous deep, fast-cadenced, wide-field observations at all wavelengths to observe the same field at the same time as Parkes, enabling multi-wavelength detection before, during, and after the radio detection. Little to no multi-wavelength observations to any significant depth have been done on these timescales, leaving this parameter space underexplored. DWF coordinates major facilities such as South Pole Telescope (mm/sub-mm), GROND (infrared), CTIO Dark Energy Camera (optical), Astrosat (UV/X-ray), HXMT (X-ray), HESS (gamma-ray), and Pierre Auger (high-energy). We perform realtime data processing and transient identification at all wavelengths that enables triggering our deep, rapid-response (within minutes) follow up programs for deep spectroscopy and imaging using the world's largest telescopes (e.g., Keck, VLT, Gemini, SALT, ATCA).
DOI: 10.21258/1618605
title: Inventario forestale nazionale svizzero - Tabella n. 892891
DOI: 10.21258/1622767
title: Inventario forestale nazionale svizzero - Tabella n. 897775
DOI: 10.21258/1591791
title: Inventario forestale nazionale svizzero - Tabella n. 891896
DOI: 10.21258/1589797
title: Inventario forestale nazionale svizzero - Tabella n. 898734
DOI: 10.21258/1587366
title: Inventario forestale nazionale svizzero - Tabella n. 899561
DOI: 10.21258/1548300
title: Inventaire forestier national suisse - Tableau no 897298
DOI: 10.21258/1544817
title: Inventaire forestier national suisse - Tableau no 897763
DOI: 10.21258/1624668
title: Inventario forestale nazionale svizzero - Tabella n. 898176
DOI: 10.5281/zenodo.4318041
title: Earthquake catalogs southern Kansas

description: Relocated earthquake catalog (Data Set S1) and original non-relocated enhanced catalog (Data Set S2) for southern Kansas.
DOI: 10.5281/zenodo.4318040
title: Earthquake catalogs southern Kansas

description: Relocated earthquake catalog (Data Set S1) and original non-relocated enhanced catalog (Data Set S2) for southern Kansas.
DOI: 10.21258/1619036
title: Inventario forestale nazionale svizzero - Tabella n. 897002
DOI: 10.21258/1620173
title: Inventario forestale nazionale svizzero - Tabella n. 897239
DOI: 10.21258/1610756
title: Inventario forestale nazionale svizzero - Tabella n. 893070
DOI: 10.21258/1539027
title: Inventaire forestier national suisse - Tableau no 892987
DOI: 10.21258/1589050
title: Inventario forestale nazionale svizzero - Tabella n. 897282
DOI: 10.21258/1584685
title: Inventario forestale nazionale svizzero - Tabella n. 898733
DOI: 10.21258/1597331
title: Inventario forestale nazionale svizzero - Tabella n. 897016
DOI: 10.21258/1576217
title: Inventaire forestier national suisse - Tableau no 897880
DOI: 10.18112/openneuro.ds003424.v1.0.0
title: Identification of an Amygdala-Thalamic Circuit That Acts as a Central Gain Mechanism in Taste Perception
DOI: 10.6084/m9.figshare.13368848
title: A Collection of the Modeled Historical Land Use Data for the United States

description: Researchers at the USGS have used a wide range of historical data sources and a spatially explicit modeling framework to model historical land use in the United States. This figshare repository is a collection of those datasets. See the references below for more details.<br>References:Sohl et al. 2018. Modeled historical land use and land cover for the conterminous United States: 1938-1992: USGS data release, https://doi.org/10.5066/F7KK99RR<br><br>Sohl et al. 2018. Conterminous United States Land Cover Projections - 1992 to 2100: USGS data release, https://doi.org/10.5066/P95AK9HP<br>
DOI: 10.21258/1584997
title: Inventario forestale nazionale svizzero - Tabella n. 897368
DOI: 10.21258/1615079
title: Inventario forestale nazionale svizzero - Tabella n. 897396
DOI: 10.25919/7tzs-5t36
title: Parkes observations for project P1006 semester 2019APRS_32

description: We propose observations with the ultra-wide-bandwidth, low-frequency receiver installed at the Parkes telescope to carry out the first ultra-high time resolution, coherently de-dispersed search for pulsars in globular clusters. We have chosen the 11 most likely clusters for new discoveries. These clusters all have at least three pulsars already known allowing us to have a precise estimate of the pulsar dispersion measures and our observations will provide the first ultra-wide-bandwidth observation of these pulsars. Our observing strategy will enable us to search for extremely narrow pulsars and even pulsars with sub-millisecond periods.
DOI: 10.21258/1554870
title: Inventaire forestier national suisse - Tableau no 897600