cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1068447.09fu
title: SH1068447.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1068448.09fu
title: SH1068448.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1068449.09fu
title: SH1068449.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.4121/21666152
title: Dataset accompanying the publication: Utilisation of waste heat from PEM electrolysers – Unlocking local optimisation

description: This dataset contains raw model results from 3 different scenarios as part of a publicationon the utilisation of waste heat from a 2.5 MW electrolyser. It is being made public to act as supplementary data for publication(s) and the PhD thesis of Els van der Roest. Also, it might be used by other researchers.<br>The dataset was created during model runs in the period between March 2022 - December 2022 as part of the H-Flex project.<br>Abstract of the paper (published in The International Journal of Hydrogen Energy): Recovery of heat from electrolysers is potentially interesting to increase the total system efficiency, reduce CO<sub>2</sub> emissions, and increase the economic feasibility of both hydrogen and heat production. This study examines different designs for the utilisation of (waste) heat from a 2.5 MW<sub>el</sub> polymer electrolyte membrane (PEM) electrolyser. Redundancy is important in the design, to ensure safe operation regardless of the heat demand of the heat consumer. We analysed cases with local heat consumption (with/without a heat pump) and coupling with a district heating network (DHN). Overall, 14-15% of the electricity input to the stack can be utilised by a heat consumer, increasing the total system efficiency to 90% (HHV) with CO<sub>2</sub>-savings of 0.08 (DHN)-0.28 (direct use) tonne CO<sub>2</sub>/MWh<sub>heat,used</sub>. We performed a first-order techno-economic analysis showing that the levelized costs of the electrolyser heat (8.4-36.9 €/MWh) fall within the range of other industrial heat sources and below lower-temperature heat sources.<br>
DOI: 10.15156/bio/sh1068450.09fu
title: SH1068450.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1068451.09fu
title: SH1068451.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.4121/21666152.v1
title: Dataset accompanying the publication: Utilisation of waste heat from PEM electrolysers – Unlocking local optimisation

description: This dataset contains raw model results from 3 different scenarios as part of a publicationon the utilisation of waste heat from a 2.5 MW electrolyser. It is being made public to act as supplementary data for publication(s) and the PhD thesis of Els van der Roest. Also, it might be used by other researchers.<br>The dataset was created during model runs in the period between March 2022 - December 2022 as part of the H-Flex project.<br>Abstract of the paper (published in The International Journal of Hydrogen Energy): Recovery of heat from electrolysers is potentially interesting to increase the total system efficiency, reduce CO<sub>2</sub> emissions, and increase the economic feasibility of both hydrogen and heat production. This study examines different designs for the utilisation of (waste) heat from a 2.5 MW<sub>el</sub> polymer electrolyte membrane (PEM) electrolyser. Redundancy is important in the design, to ensure safe operation regardless of the heat demand of the heat consumer. We analysed cases with local heat consumption (with/without a heat pump) and coupling with a district heating network (DHN). Overall, 14-15% of the electricity input to the stack can be utilised by a heat consumer, increasing the total system efficiency to 90% (HHV) with CO<sub>2</sub>-savings of 0.08 (DHN)-0.28 (direct use) tonne CO<sub>2</sub>/MWh<sub>heat,used</sub>. We performed a first-order techno-economic analysis showing that the levelized costs of the electrolyser heat (8.4-36.9 €/MWh) fall within the range of other industrial heat sources and below lower-temperature heat sources.<br>
DOI: 10.15156/bio/sh1068452.09fu
title: SH1068452.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1068453.09fu
title: SH1068453.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1068454.09fu
title: SH1068454.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1068455.09fu
title: SH1068455.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.7910/dvn/n1klnv/drzm5o
title: footsure.wav

description: :unav
DOI: 10.7910/dvn/n1klnv/fqnbcq
title: appendix.tsv

description: :unav
DOI: 10.7910/dvn/n1klnv/jdta7j
title: artificial.tsv

description: :unav
DOI: 10.7910/dvn/n1klnv/lzeyyj
title: arduous.wav

description: :unav
DOI: 10.7910/dvn/n1klnv/rsfcss
title: arduous.tsv

description: :unav
DOI: 10.7910/dvn/n1klnv/ud5bo3
title: appendix.wav

description: :unav
DOI: 10.7910/dvn/lq2kfz/h8fanr
title: hadh_1.tsv
DOI: 10.7910/dvn/lq2kfz/houfs6
title: zush_1.wav
DOI: 10.7910/dvn/lq2kfz/lxsv3j
title: guth_1.wav
DOI: 10.7910/dvn/lq2kfz/m8lwsr
title: zush_1.tsv
DOI: 10.7910/dvn/lq2kfz/oceebl
title: rit_1.tsv
DOI: 10.7910/dvn/lq2kfz/p9lcmh
title: kad_1.wav
DOI: 10.7910/dvn/lq2kfz/rmrxkm
title: kadh_1.tsv
DOI: 10.7910/dvn/lq2kfz/rnr4vl
title: rip_1.tsv
DOI: 10.7910/dvn/lq2kfz/ry6zpt
title: rip_1.wav
DOI: 10.7910/dvn/n1klnv/0gbmcg
title: fond.tsv

description: :unav
DOI: 10.7910/dvn/n1klnv/1ojyrg
title: fond.wav

description: :unav
DOI: 10.7910/dvn/n1klnv/7ecwyv
title: alltogether.tsv

description: :unav
DOI: 10.7910/dvn/n1klnv/aohi05
title: apostolic.tsv

description: :unav
DOI: 10.7910/dvn/n1klnv/jddjuj
title: altering.tsv

description: :unav
DOI: 10.7910/dvn/n1klnv/m2clop
title: altering.wav

description: :unav
DOI: 10.7910/dvn/n1klnv/uhunxl
title: anonymity.wav

description: :unav
DOI: 10.7910/dvn/n1klnv/wr7g2x
title: alltogether.wav

description: :unav
DOI: 10.7910/dvn/n1klnv/xerux9
title: anonymity.tsv

description: :unav
DOI: 10.5281/zenodo.2720105
title: SQLite database to accompany the paper, "Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring"

description: This dataset is a SQLite database that accompanies methods and analysis described in the paper, "Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring" (Balantic & Donovan 2019, Bioacoustics, https://www.tandfonline.com/doi/full/10.1080/09524622.2019.1605309). 

A Github repository containing code for using the SQLite database also accompanies this paper at: http://github.com/cbalantic/false-positive-mitigation
description: A Github repository containing code for using the SQLite database also accompanies this paper at: http://github.com/cbalantic/false-positive-mitigation
description: {"references": ["Balantic, C. M., & Donovan, T. M. (2019). Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring. Bioacoustics, 1-26. DOI: 10.1080/09524622.2019.1605309"]}
DOI: 10.6073/pasta/7b347a6b2848a2fffa61f99ae5215784
title: Macrosystems EDDIE Module 3: Teleconnections

description: Ecosystems can be influenced by teleconnections, in which
  meteorological, societal, and/or ecological phenomenon link remote
  regions via cause and effect relationships. Because it is difficult to
  predict how ecosystems will respond to drivers from remote regions,
  many researchers are using models to simulate different teleconnection
  scenarios and see how ecosystems respond. For example, lake simulation
  models provide a powerful tool for exploring how lake thermal
  structure and ice cover respond to climate teleconnections such as the
  El Nino/Southern Oscillation (ENSO).

      
  In this module, students will learn how to set up a lake model and
  "force" the model with climate scenarios to test hypotheses
  about how far-away drivers interact with local lake characteristics to
  affect lake temperatures and ice cover in different lakes. The
  overarching goal of this module is for students to explore new
  modeling and computing tools while learning fundamental concepts about
  how teleconnections affect lake temperatures and ice cover. The A-B-C
  structure of this module makes it flexible and adaptable to a range of
  student levels and course structures.

      
  This dataset contains instructional materials and the files necessary
  to run the complete module. Readers are referred to the GLM science
  manual (Hipsey et al. 2014; 2019) for further details on model
  configuration.
DOI: 10.7910/dvn/lq2kfz/1bzeqt
title: zus_1.tsv
DOI: 10.7910/dvn/lq2kfz/ahs3dd
title: rim_1.wav
DOI: 10.7910/dvn/lq2kfz/kvl3gc
title: zus_1.wav
DOI: 10.7910/dvn/lq2kfz/pnozin
title: zung_1.wav
DOI: 10.7910/dvn/lq2kfz/rbc2s3
title: guth_1.tsv
DOI: 10.7910/dvn/lq2kfz/sak7kt
title: kad_1.tsv
DOI: 10.7910/dvn/lq2kfz/sm0t3s
title: juz_1.wav
DOI: 10.7910/dvn/lq2kfz/sxlmn2
title: rim_1.tsv
DOI: 10.7910/dvn/n1klnv/bs8d1l
title: folklore.wav

description: :unav
DOI: 10.7910/dvn/n1klnv/gacbx6
title: alaskan.wav

description: :unav
DOI: 10.7910/dvn/n1klnv/jp9vav
title: alaskan.tsv

description: :unav
DOI: 10.7910/dvn/n1klnv/lxflgn
title: aims.wav

description: :unav
DOI: 10.7910/dvn/n1klnv/n9gvxa
title: aims.tsv

description: :unav
DOI: 10.7910/dvn/n1klnv/x53etd
title: folklore.tsv

description: :unav
DOI: 10.5281/zenodo.2720104
title: SQLite database to accompany the paper, "Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring"

description: This dataset is a SQLite database that accompanies methods and analysis described in the paper, "Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring" (Balantic & Donovan 2019, Bioacoustics, https://www.tandfonline.com/doi/full/10.1080/09524622.2019.1605309). 

A Github repository containing code for using the SQLite database also accompanies this paper at: http://github.com/cbalantic/false-positive-mitigation
description: A Github repository containing code for using the SQLite database also accompanies this paper at: http://github.com/cbalantic/false-positive-mitigation
description: {"references": ["Balantic, C. M., & Donovan, T. M. (2019). Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring. Bioacoustics, 1-26. DOI: 10.1080/09524622.2019.1605309"]}
DOI: 10.7910/dvn/lq2kfz/ebotlu
title: jish_1.wav
DOI: 10.7910/dvn/lq2kfz/esx1ze
title: zung_1.tsv
DOI: 10.7910/dvn/lq2kfz/fzderl
title: zuth_1.wav
DOI: 10.7910/dvn/lq2kfz/hg8kni
title: zush_1.wav
DOI: 10.7910/dvn/lq2kfz/hgpjb4
title: gus_1.wav
DOI: 10.7910/dvn/lq2kfz/j5bcm3
title: jish_1.tsv
DOI: 10.7910/dvn/lq2kfz/jy2uij
title: gup_1.wav
DOI: 10.7910/dvn/lq2kfz/musy1u
title: zut_1.tsv
DOI: 10.7910/dvn/lq2kfz/ohso4f
title: zum_1.wav
DOI: 10.7910/dvn/lq2kfz/qciv9z
title: ril_1.wav
DOI: 10.7910/dvn/lq2kfz/qnxrt4
title: juz_1.tsv
DOI: 10.7910/dvn/lq2kfz/qvkuwh
title: ril_1.tsv
DOI: 10.7910/dvn/lq2kfz/vhepgm
title: zut_1.wav
DOI: 10.7910/dvn/lq2kfz/xpcewn
title: gus_1.tsv
DOI: 10.7910/dvn/lq2kfz/ykoqqv
title: zuth_1.tsv
DOI: 10.7910/dvn/n1klnv/bbtm6m
title: acclimatized.wav

description: :unav
DOI: 10.7910/dvn/n1klnv/dunxmu
title: acclimatized.tsv

description: :unav
DOI: 10.7910/dvn/n1klnv/p2pol6
title: firmament.wav

description: :unav
DOI: 10.7910/dvn/n1klnv/uhqwbv
title: adjacent.wav

description: :unav
DOI: 10.7910/dvn/n1klnv/yj6ypx
title: adjacent.tsv

description: :unav
DOI: 10.5281/zenodo.2718712
title: CRISPR knockout of EZH1 in AML cell line

description: We wanted to ensure the specificity of the EZH1 antibody that I was working with in previous posts, as well as creating a useful reagent to use in future experiments by generating a CRISPR knockout line of EZH1.
description: The SGC is a registered charity (number 1097737) that receives funds from AbbVie, Bayer Pharma AG, Boehringer Ingelheim, Canada Foundation for Innovation, Eshelman Institute for Innovation, Genome Canada through Ontario Genomics Institute [OGI-055], Innovative Medicines Initiative (EU/EFPIA) [ULTRA-DD grant no. 115766], Janssen, Merck KGaA, Darmstadt, Germany, MSD, Novartis Pharma AG, Ontario Ministry of Research, Innovation and Science (MRIS), Pfizer, São Paulo Research Foundation-FAPESP, Takeda, and Wellcome [106169/ZZ14/Z]. This project receives funding from the Leukemia and Lymphoma Society of Canada.
DOI: 10.5281/zenodo.2718713
title: CRISPR knockout of EZH1 in AML cell line

description: We wanted to ensure the specificity of the EZH1 antibody that I was working with in previous posts, as well as creating a useful reagent to use in future experiments by generating a CRISPR knockout line of EZH1.
description: The SGC is a registered charity (number 1097737) that receives funds from AbbVie, Bayer Pharma AG, Boehringer Ingelheim, Canada Foundation for Innovation, Eshelman Institute for Innovation, Genome Canada through Ontario Genomics Institute [OGI-055], Innovative Medicines Initiative (EU/EFPIA) [ULTRA-DD grant no. 115766], Janssen, Merck KGaA, Darmstadt, Germany, MSD, Novartis Pharma AG, Ontario Ministry of Research, Innovation and Science (MRIS), Pfizer, São Paulo Research Foundation-FAPESP, Takeda, and Wellcome [106169/ZZ14/Z]. This project receives funding from the Leukemia and Lymphoma Society of Canada.
DOI: 10.7910/dvn/lq2kfz/2fcp37
title: rat_1.wav
DOI: 10.7910/dvn/lq2kfz/2o62b4
title: zul_1.tsv
DOI: 10.7910/dvn/lq2kfz/8q29xo
title: zul_1.wav
DOI: 10.7910/dvn/lq2kfz/bs4mrf
title: guj_1.wav
DOI: 10.7910/dvn/lq2kfz/c960qn
title: zus_1.wav
DOI: 10.7910/dvn/lq2kfz/d8nfnm
title: zum_1.tsv
DOI: 10.7910/dvn/lq2kfz/gspuvq
title: jip_1.wav
DOI: 10.7910/dvn/lq2kfz/ibwod6
title: zush_1.tsv
DOI: 10.7910/dvn/lq2kfz/ndsujb
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DOI: 10.7910/dvn/lq2kfz/rn12vt
title: jip_1.tsv
DOI: 10.7910/dvn/lq2kfz/rt8zai
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DOI: 10.7910/dvn/lq2kfz/vm3wg7
title: zum_1.wav
DOI: 10.7910/dvn/lq2kfz/vne5ee
title: rib_1.tsv
DOI: 10.7910/dvn/lq2kfz/wo5ov8
title: zum_1.tsv
DOI: 10.7910/dvn/lq2kfz/xv3bui
title: rib_1.wav
DOI: 10.7910/dvn/n1klnv/8sh4ne
title: filtrate.wav

description: :unav
DOI: 10.7910/dvn/n1klnv/ddany7
title: firmament.tsv

description: :unav
DOI: 10.7910/dvn/lq2kfz/0c4wu4
title: zuk_1.wav
DOI: 10.7910/dvn/lq2kfz/1maahx
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DOI: 10.7910/dvn/lq2kfz/4pixaq
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DOI: 10.7910/dvn/lq2kfz/7wooit
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DOI: 10.7910/dvn/lq2kfz/apymli
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DOI: 10.7910/dvn/lq2kfz/jufe8w
title: radh_1.wav
DOI: 10.7910/dvn/lq2kfz/lrhc7x
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DOI: 10.7910/dvn/lq2kfz/nnaz32
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DOI: 10.7910/dvn/lq2kfz/sagdul
title: guj_1.tsv
DOI: 10.7910/dvn/lq2kfz/wmszvj
title: rat_1.tsv