cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/7jnc5v
title: Swiss National Fungi Databank

description: This dataset provides distribution data of fungi in Switzerland of the National Data and Information Centre, called SwissFungi. SwissFungi is a partner of InfoSpecies, the network of Swiss data and information centers for fauna, flora and fungi. One of its main objectives is to document the spatial and temporal distribution of fungal species in Switzerland. The SwissFungi database currently contains more than 700'000 georeferenced fungi observations, distributed throughout Switzerland. The oldest observations date back to 1770. A large portion of the records date from 1990 until the present day. The database is continuously updated with new fungi records. The data have been validated and originate from national inventories, from research projects, from floristic observations by volunteers as well as from private and public herbaria and from literature. Please note that SwissFungi is not able to verify all incoming fungal records completely concerning correct identification or coordinate errors and therefore cannot guarantee the validity of the information.
DOI: 10.18739/a2fx7400t
title: Seasonal soil active layer measurements from a Circumpolar Active Layer monitoring (CALM) grid, (U56) 56 Mile, Alaska. 1996-2020

description: The Circumpolar Active Layer Monitoring (CALM) program represents the only coordinated program providing collection, standardization, open access, and dissemination of active-layer data world-wide. Widespread, systematic changes in the thickness of the active layer could have profound effects on the flux of greenhouse gases, on the human infrastructure in cold regions, and on landscape and hydrologic processes. It is therefore critical that observational and analytical procedures continue over decadal periods to assess trends and detect cumulative, long-term changes. This dataset contains active-layer observations conducted by the CALM program since the 1990s, supported by a series of National Science Foundation (NSF) awards. CALM program is an integral part of the Global Terrestrial Network for Permafrost. CALM 2020 data are significantly reduced due to pandemic-related travel restrictions. Available 2020 data are limited in terms of extent, and observations were not as controlled as previous years in terms of measurement timing or method, and therefore should be treated with caution.
DOI: 10.18739/a2b56d57v
title: Seasonal soil active layer measurements from a Circumpolar Active Layer monitoring (CALM) grid, (U32A) Sagwon Hills MNT, Alaska. 1995-2020

description: The Circumpolar Active Layer Monitoring (CALM) program represents the only coordinated program providing collection, standardization, open access, and dissemination of active-layer data world-wide. Widespread, systematic changes in the thickness of the active layer could have profound effects on the flux of greenhouse gases, on the human infrastructure in cold regions, and on landscape and hydrologic processes. It is therefore critical that observational and analytical procedures continue over decadal periods to assess trends and detect cumulative, long-term changes. This dataset contains active-layer observations conducted by the CALM program since the 1990s, supported by a series of National Science Foundation (NSF) awards. CALM program is an integral part of the Global Terrestrial Network for Permafrost. CALM 2020 data are significantly reduced due to pandemic-related travel restrictions. Available 2020 data are limited in terms of extent, and observations were not as controlled as previous years in terms of measurement timing or method, and therefore should be treated with caution.
DOI: 10.18739/a26d5pc27
title: Seasonal soil active layer measurements from a Circumpolar Active Layer monitoring (CALM) grid, (U32B) Sagwon Hills MAT, Alaska. 1995-2020

description: The Circumpolar Active Layer Monitoring (CALM) program represents the only coordinated program providing collection, standardization, open access, and dissemination of active-layer data world-wide. Widespread, systematic changes in the thickness of the active layer could have profound effects on the flux of greenhouse gases, on the human infrastructure in cold regions, and on landscape and hydrologic processes. It is therefore critical that observational and analytical procedures continue over decadal periods to assess trends and detect cumulative, long-term changes. This dataset contains active-layer observations conducted by the CALM program since the 1990s, supported by a series of National Science Foundation (NSF) awards. CALM program is an integral part of the Global Terrestrial Network for Permafrost. CALM 2020 data are significantly reduced due to pandemic-related travel restrictions. Available 2020 data are limited in terms of extent, and observations were not as controlled as previous years in terms of measurement timing or method, and therefore should be treated with caution.
DOI: 10.15468/qt9jpw
title: Swiss National Lichens Databank

description: This dataset provides distribution data of Lichens in Switzerland of the National Data and Information Centre, called Swiss Lichens. SwissLichens is a partner of InfoSpecies, the network of Swiss data and information centers for fauna, flora and fungi. One of its main objectives is to document the spatial and temporal distribution of species in Switzerland. The SwissLichens database currently contains more than 120'000 georeferenced Lichen observations, distributed throughout Switzerland. The oldest observations date back to 1790. A large portion of the records date from the last two decades of the last century to the present day. The database is continuously updated with new findings. The data have been validated and originate from national inventories, from research projects, from floristic observations by volunteers as well as from private and public herbaria and from literature.
DOI: 10.25919/8y61-ym29
title: Parkes observations for project P1068 semester 2021APRS_05

description: In the fast-moving world of Fast Radio Bursts (FRBs), the critical question of what fraction of FRBs emit repeat bursts remains unanswered. Of order 20 repeating FRBs are now known, and their spectro-temporal properties hint at differences with apparently non-repeating bursts - the poor statistics preclude a definitive diagnosis. FRB 180301 is a promising source for further study for multiple reasons: it is an active repeater similar to the FRB 121102 and the most active FRB source visible to Parkes, and it shows diverse polarization properties across the repeat bursts. We have detected multiple repeat bursts from this source in our campaign last semester. The signal-to-noise ratio (S/N) of these detections are not sufficiently significant to measure their spectro-polarimetric properties. We request Parkes observations with the UWL receiver to continue the monitoring of this FRB source in order to characterize the broadband emission properties. Some of the key goals for these future observations are: to constrain the repetition rate, identify any variation of pulse characteristics over time, measure the polarimetric properties and provide insight into the emission mechanisms. The diverse polarization angle swings in the FAST detections and significant circular polarization in the original Parkes detection indicate the progenitor is embedded in an extreme magneto-ionic environment with complex field structure that has not been seen before. Understanding these diverse polarization properties from this source could be the key to distinguish repeater sources from the apparent non-repeaters ones.
DOI: 10.5281/zenodo.4592538
title: Keast ApiNATOMY model of bladder innervation

description: This digital record documents the ApiNATOMY representation of neural circuits in the central and peripheral nervous system innervating the urinary bladder and urethra. ApiNATOMY is a set of tools that produces simple, consistent anatomy schematics overlaid with ontological information. These tools are used to build routing and connectivity graphs (or wiring diagrams). This record contains a docs folder, a source folder, and a README text file. The Docs folder contains 2 PDF documents, with a schematic image of the ApiNATOMY model and a slide presentation documenting the anatomical structures each neuron population travels through in the schematic image. The Source folder contains the ApiNATOMY representation of the model in JSON and .xlsx formats. Lastly, the README.md document includes a brief description, keywords, and reference publications to construct the knowledge within the model. Please note, the focus of SPARC is on peripheral connectivity of the ANS and its main points of interaction with the CNS. Therefore, any CNS circuitry represented is not comprehensive unless otherwise specified.
description: PMID:1358408 PMID:1619047 PMID:1726105 PMID:1765622 PMID:2713886 PMID:2891149 PMID:3225349 PMID:3558884 PMID:3722467 PMID:4700666 PMID:6736301 PMID:7174880 PMID:7636036 PMID:7644029 PMID:8786273 PMID:8923445 PMID:9421141 PMID:9442414 PMID:10494620 PMID:11382385 PMID:11748568 PMID:12811806 PMID:20484700 PMID:30704972
description: {"references": ["Vera PL, Nadelhaft I. Afferent and sympathetic innervation of the dome and the base of the urinary bladder of the female rat. Brain Res Bull. 1992 Nov;29(5):651-8. doi: 10.1016/0361-9230(92)90134-j. PMID: 1358408."]}
DOI: 10.18739/a22n4zj8g
title: Seasonal soil active layer measurements from a Circumpolar Active Layer monitoring (CALM) grid, (U11a) Imnavait Creek 1 kilometer grid, Alaska. 1995-2020.

description: The Circumpolar Active Layer Monitoring (CALM) program represents the only coordinated program providing collection, standardization, open access, and dissemination of active-layer data world-wide. Widespread, systematic changes in the thickness of the active layer could have profound effects on the flux of greenhouse gases, on the human infrastructure in cold regions, and on landscape and hydrologic processes. It is therefore critical that observational and analytical procedures continue over decadal periods to assess trends and detect cumulative, long-term changes. This dataset contains active-layer observations conducted by the CALM program since the 1990s, supported by a series of National Science Foundation (NSF) awards. CALM program is an integral part of the Global Terrestrial Network for Permafrost. CALM 2020 data are significantly reduced due to pandemic-related travel restrictions. Available 2020 data are limited in terms of extent, and observations were not as controlled as previous years in terms of measurement timing or method, and therefore should be treated with caution.
DOI: 10.18739/a2xw47x3g
title: Seasonal soil active layer measurements from a Circumpolar Active Layer monitoring (CALM) grid, (U3) Atkasuk, Alaska. 1995-2020

description: The Circumpolar Active Layer Monitoring (CALM) program represents the only coordinated program providing collection, standardization, open access, and dissemination of active-layer data world-wide. Widespread, systematic changes in the thickness of the active layer could have profound effects on the flux of greenhouse gases, on the human infrastructure in cold regions, and on landscape and hydrologic processes. It is therefore critical that observational and analytical procedures continue over decadal periods to assess trends and detect cumulative, long-term changes. This dataset contains active-layer observations conducted by the CALM program since the 1990s, supported by a series of National Science Foundation (NSF) awards. CALM program is an integral part of the Global Terrestrial Network for Permafrost. CALM 2020 data are significantly reduced due to pandemic-related travel restrictions. Available 2020 data are limited in terms of extent, and observations were not as controlled as previous years in terms of measurement timing or method, and therefore should be treated with caution.
DOI: 10.18739/a2t43j40j
title: Seasonal soil active layer measurements from a Circumpolar Active Layer monitoring (CALM) grid, (U11B) Imnavait Creek WET, Alaska. 1995-2020

description: The Circumpolar Active Layer Monitoring (CALM) program represents the only coordinated program providing collection, standardization, open access, and dissemination of active-layer data world-wide. Widespread, systematic changes in the thickness of the active layer could have profound effects on the flux of greenhouse gases, on the human infrastructure in cold regions, and on landscape and hydrologic processes. It is therefore critical that observational and analytical procedures continue over decadal periods to assess trends and detect cumulative, long-term changes. This dataset contains active-layer observations conducted by the CALM program since the 1990s, supported by a series of National Science Federation (NSF) awards. CALM program is an integral part of the Global Terrestrial Network for Permafrost. CALM 2020 data are significantly reduced due to pandemic-related travel restrictions. Available 2020 data are limited in terms of extent, and observations were not as controlled as previous years in terms of measurement timing or method, and therefore should be treated with caution.
DOI: 10.18739/a2pg1hp74
title: Seasonal soil active layer measurements from a Circumpolar Active Layer monitoring (CALM) grid, (U11C) Imnavait Creek MAT, Alaska. 1996-2020

description: The Circumpolar Active Layer Monitoring (CALM) program represents the only coordinated program providing collection, standardization, open access, and dissemination of active-layer data world-wide. Widespread, systematic changes in the thickness of the active layer could have profound effects on the flux of greenhouse gases, on the human infrastructure in cold regions, and on landscape and hydrologic processes. It is therefore critical that observational and analytical procedures continue over decadal periods to assess trends and detect cumulative, long-term changes. This dataset contains active-layer observations conducted by the CALM program since the 1990s, supported by a series of National Science Federation (NSF) awards. CALM program is an integral part of the Global Terrestrial Network for Permafrost. CALM 2020 data are significantly reduced due to pandemic-related travel restrictions. Available 2020 data are limited in terms of extent, and observations were not as controlled as previous years in terms of measurement timing or method, and therefore should be treated with caution.
DOI: 10.18739/a2jq0sw4g
title: Seasonal soil active layer measurements from a Circumpolar Active Layer monitoring (CALM) grid, (U12A) Toolik 1 kilometer grid , Alaska. 1995-2020

description: The Circumpolar Active Layer Monitoring (CALM) program represents the only coordinated program providing collection, standardization, open access, and dissemination of active-layer data world-wide. Widespread, systematic changes in the thickness of the active layer could have profound effects on the flux of greenhouse gases, on the human infrastructure in cold regions, and on landscape and hydrologic processes. It is therefore critical that observational and analytical procedures continue over decadal periods to assess trends and detect cumulative, long-term changes. This dataset contains active-layer observations conducted by the CALM program since the 1990s, supported by a series of National Science Federation (NSF) awards. CALM program is an integral part of the Global Terrestrial Network for Permafrost. CALM 2020 data are significantly reduced due to pandemic-related travel restrictions. Available 2020 data are limited in terms of extent, and observations were not as controlled as previous years in terms of measurement timing or method, and therefore should be treated with caution.
DOI: 10.5281/zenodo.4898341
title: Data used to generate Fig. 5 (tSNE & KNN)

description: The data used to generate Fig. 5 (tSNE & KNN) for "Learning Dynamics of Hierarchical Category Structure in Deep Non-Linear Networks", submitted to NeurIPS 2021. The data is subsampled (100 samples per time epoch) from the non-linear network trained on the hierarchical dataset. The pickle files contain the data features (across all layers) as well as the computed KNN matrix.
DOI: 10.5281/zenodo.4898106
title: Data for "Explainable AI uncovers how neural networks learn to regionalize in simulations of turbulent heat fluxes at FluxNet sites"

description: Data for "Explainable AI uncovers how neural networks learn to regionalize in simulations of turbulent heat fluxes at FluxNet sites" This is split out by site. Each site has three datasets. The `*_data.nc` contain the model input and outputs. The `*_lrp_qle.nc` contain the relevance scores for latent heat, and the `*_lrp_qh.nc` contain the relevance scores for sensible heat.
DOI: 10.5281/zenodo.4898105
title: Data for "Explainable AI uncovers how neural networks learn to regionalize in simulations of turbulent heat fluxes at FluxNet sites"

description: Data for "Explainable AI uncovers how neural networks learn to regionalize in simulations of turbulent heat fluxes at FluxNet sites" This is split out by site. Each site has three datasets. The `*_data.nc` contain the model input and outputs. The `*_lrp_qle.nc` contain the relevance scores for latent heat, and the `*_lrp_qh.nc` contain the relevance scores for sensible heat.
DOI: 10.5517/ccdc.csd.cc257yyb
title: CCDC 2003652: Experimental Crystal Structure Determination

description: Related Article: Si-Hua Hou, Adriana Y. Prichina, Guangbin Dong|2021|Angew.Chem.,Int.Ed.|60|13057|doi:10.1002/anie.202103553
DOI: 10.5517/ccdc.csd.cc26mvxm
title: CCDC 2044881: Experimental Crystal Structure Determination

description: Related Article: Stephan Hagspiel, Felipe Fantuzzi, Rian D. Dewhurst, Annalena Gärtner, Felix Lindl, Anna Lamprecht, Holger Braunschweig|2021|Angew.Chem.,Int.Ed.|60|13666|doi:10.1002/anie.202103521
DOI: 10.5517/ccdc.csd.cc26mvyn
title: CCDC 2044882: Experimental Crystal Structure Determination

description: Related Article: Stephan Hagspiel, Felipe Fantuzzi, Rian D. Dewhurst, Annalena Gärtner, Felix Lindl, Anna Lamprecht, Holger Braunschweig|2021|Angew.Chem.,Int.Ed.|60|13666|doi:10.1002/anie.202103521
DOI: 10.5517/ccdc.csd.cc26mvzp
title: CCDC 2044883: Experimental Crystal Structure Determination

description: Related Article: Stephan Hagspiel, Felipe Fantuzzi, Rian D. Dewhurst, Annalena Gärtner, Felix Lindl, Anna Lamprecht, Holger Braunschweig|2021|Angew.Chem.,Int.Ed.|60|13666|doi:10.1002/anie.202103521
DOI: 10.5517/ccdc.csd.cc26mw0r
title: CCDC 2044884: Experimental Crystal Structure Determination

description: Related Article: Stephan Hagspiel, Felipe Fantuzzi, Rian D. Dewhurst, Annalena Gärtner, Felix Lindl, Anna Lamprecht, Holger Braunschweig|2021|Angew.Chem.,Int.Ed.|60|13666|doi:10.1002/anie.202103521
DOI: 10.5517/ccdc.csd.cc26wkg4
title: CCDC 2052276: Experimental Crystal Structure Determination

description: Related Article: Shuai Zhao, Xiang-Xiang Chen, Nan Gao, Mingcheng Qian, Xin Chen|2021|J.Org.Chem.|86|7131|doi:10.1021/acs.joc.1c00418
DOI: 10.5517/ccdc.csd.cc27022f
title: CCDC 2055643: Experimental Crystal Structure Determination

description: Related Article: Wenjing Wang, Kongzhao Su, El-Sayed M. El-Sayed, Miao Yang, Daqiang Yuan|2021|ACS Applied Materials and Interfaces|13|24042|doi:10.1021/acsami.1c04573
DOI: 10.5517/ccdc.csd.cc27025j
title: CCDC 2055646: Experimental Crystal Structure Determination

description: Related Article: Wenjing Wang, Kongzhao Su, El-Sayed M. El-Sayed, Miao Yang, Daqiang Yuan|2021|ACS Applied Materials and Interfaces|13|24042|doi:10.1021/acsami.1c04573
DOI: 10.5517/ccdc.csd.cc27026k
title: CCDC 2055647: Experimental Crystal Structure Determination

description: Related Article: Wenjing Wang, Kongzhao Su, El-Sayed M. El-Sayed, Miao Yang, Daqiang Yuan|2021|ACS Applied Materials and Interfaces|13|24042|doi:10.1021/acsami.1c04573
DOI: 10.5517/ccdc.csd.cc27027l
title: CCDC 2055648: Experimental Crystal Structure Determination

description: Related Article: Wenjing Wang, Kongzhao Su, El-Sayed M. El-Sayed, Miao Yang, Daqiang Yuan|2021|ACS Applied Materials and Interfaces|13|24042|doi:10.1021/acsami.1c04573
DOI: 10.5517/ccdc.csd.cc27028m
title: CCDC 2055649: Experimental Crystal Structure Determination

description: Related Article: Wenjing Wang, Kongzhao Su, El-Sayed M. El-Sayed, Miao Yang, Daqiang Yuan|2021|ACS Applied Materials and Interfaces|13|24042|doi:10.1021/acsami.1c04573
DOI: 10.5517/ccdc.csd.cc27029n
title: CCDC 2055650: Experimental Crystal Structure Determination

description: Related Article: Wenjing Wang, Kongzhao Su, El-Sayed M. El-Sayed, Miao Yang, Daqiang Yuan|2021|ACS Applied Materials and Interfaces|13|24042|doi:10.1021/acsami.1c04573
DOI: 10.5517/ccdc.csd.cc2702bp
title: CCDC 2055651: Experimental Crystal Structure Determination

description: Related Article: Wenjing Wang, Kongzhao Su, El-Sayed M. El-Sayed, Miao Yang, Daqiang Yuan|2021|ACS Applied Materials and Interfaces|13|24042|doi:10.1021/acsami.1c04573
DOI: 10.5517/ccdc.csd.cc27314k
title: CCDC 2058497: Experimental Crystal Structure Determination

description: Related Article: Aneesa J Al-Ani, Posy Sugden, Chick C Wilson, Bernardo Castro-Dominguez|2021|Cryst.Growth Des.|21|3310|doi:10.1021/acs.cgd.1c00085
DOI: 10.5517/ccdc.csd.cc257yzc
title: CCDC 2003653: Experimental Crystal Structure Determination

description: Related Article: Si-Hua Hou, Adriana Y. Prichina, Guangbin Dong|2021|Angew.Chem.,Int.Ed.|60|13057|doi:10.1002/anie.202103553
DOI: 10.5517/ccdc.csd.cc27ddxz
title: CCDC 2067511: Experimental Crystal Structure Determination

description: Related Article: Si-Hua Hou, Adriana Y. Prichina, Guangbin Dong|2021|Angew.Chem.,Int.Ed.|60|13057|doi:10.1002/anie.202103553
DOI: 10.5281/zenodo.4898345
title: Hierarchical and partition datasets

description: The datasets used throughout the paper "Learning Dynamics of Hierarchical Category Structure in Deep Non-Linear Networks", submitted to NeurIPS 2021. These are synthetic datasets with hierarchical covariance structure (six hierarchies), P=936 features and C=64 categories (leaf node category). The hierarchical dataset is "synth_tree_nobj_64000_nclass_64_nhier_6_nfeat_936_beta_0.0001610_sigma_5.0000_norm_kemp_1_compressed.mat", while the partition dataset is "synth_tree_nobj_64000_nclass_64_nhier_6_nfeat_936_beta_0.0923671_sigma_5.0000_norm_kemp_1_compressed.mat". The data were generated in a manner similar to Kemp & Tenenbaum, 2008 and Saxe et al., 2019.
DOI: 10.5281/zenodo.4898344
title: Hierarchical and partition datasets

description: The datasets used throughout the paper "Learning Dynamics of Hierarchical Category Structure in Deep Non-Linear Networks", submitted to NeurIPS 2021. These are synthetic datasets with hierarchical covariance structure (six hierarchies), P=936 features and C=64 categories (leaf node category). The hierarchical dataset is "synth_tree_nobj_64000_nclass_64_nhier_6_nfeat_936_beta_0.0001610_sigma_5.0000_norm_kemp_1_compressed.mat", while the partition dataset is "synth_tree_nobj_64000_nclass_64_nhier_6_nfeat_936_beta_0.0923671_sigma_5.0000_norm_kemp_1_compressed.mat". The data were generated in a manner similar to Kemp & Tenenbaum, 2008 and Saxe et al., 2019.
DOI: 10.5281/zenodo.4898329
title: Input files for simulation of potassium channels using the AMOEBA polarizable force field

description: This dataset contains input Tinker xyz and key files for the simulation of KcsA potassium channels in DOPC bilayer, a simple script for converting CHARMM pdb file to Tinker xyz file, and modified Tinker source code to support one-dimensional position restraints.
description: {"references": ["Jing et al. Chemical Science, 2021. DOI: 10.1039/d1sc01887f"]}
DOI: 10.5281/zenodo.4898365
title: The Global Jukebox: Urban Strain

description: The data repository for the Urban strain dataset
DOI: 10.5281/zenodo.4898364
title: The Global Jukebox: Urban Strain

description: The data repository for the Urban strain dataset