cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0203326.10fu
title: SH0203326.10FU

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/sh0203327.10fu
title: SH0203327.10FU

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/sh0203328.10fu
title: SH0203328.10FU

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/sh0203329.10fu
title: SH0203329.10FU

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/sh0203330.10fu
title: SH0203330.10FU

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/sh0203331.10fu
title: SH0203331.10FU

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/sh0203332.10fu
title: SH0203332.10FU

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: 10.6084/m9.figshare.26719503
title: Additional file 8 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 8: Table S6
DOI: 10.6084/m9.figshare.26719503.v1
title: Additional file 8 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 8: Table S6
DOI: 10.6084/m9.figshare.26719506
title: Additional file 9 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 9: Table S7
DOI: 10.6084/m9.figshare.26719506.v1
title: Additional file 9 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 9: Table S7
DOI: 10.6084/m9.figshare.26719509
title: Additional file 10 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 10: Table S8
DOI: 10.6084/m9.figshare.26719509.v1
title: Additional file 10 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 10: Table S8
DOI: 10.6084/m9.figshare.26719512
title: Additional file 11 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 11: Table S9
DOI: 10.6084/m9.figshare.26719512.v1
title: Additional file 11 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 11: Table S9
DOI: 10.6084/m9.figshare.26719515
title: Additional file 12 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 12: Table S10
DOI: 10.6084/m9.figshare.26719515.v1
title: Additional file 12 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 12: Table S10
DOI: 10.6084/m9.figshare.26719518
title: Additional file 13 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 13: Table S11
DOI: 10.6084/m9.figshare.26719518.v1
title: Additional file 13 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 13: Table S11
DOI: 10.6084/m9.figshare.26719521
title: Additional file 14 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 14: Table S12
DOI: 10.6084/m9.figshare.26719521.v1
title: Additional file 14 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 14: Table S12
DOI: 10.6084/m9.figshare.26719524
title: Additional file 15 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 15: Table S13
DOI: 10.6084/m9.figshare.26719524.v1
title: Additional file 15 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 15: Table S13
DOI: 10.6084/m9.figshare.26719527
title: Additional file 16 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 16: Table S14
DOI: 10.6084/m9.figshare.26719527.v1
title: Additional file 16 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 16: Table S14
DOI: 10.6084/m9.figshare.26719530
title: Additional file 17 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 17: Table S15
DOI: 10.6084/m9.figshare.26719530.v1
title: Additional file 17 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 17: Table S15
DOI: 10.6084/m9.figshare.26719533
title: Additional file 18 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 18: Table S16
DOI: 10.6084/m9.figshare.26719533.v1
title: Additional file 18 of Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

description: Additional file 18: Table S16
DOI: 10.6084/m9.figshare.25815123
title: Additional file 1 of Unraveling transcriptomic signatures and dysregulated pathways in systemic lupus erythematosus across disease states

description: Additional file 1.
DOI: 10.6084/m9.figshare.25815123.v1
title: Additional file 1 of Unraveling transcriptomic signatures and dysregulated pathways in systemic lupus erythematosus across disease states

description: Additional file 1.
DOI: 10.6084/m9.figshare.26719677
title: Additional file 3 of PPAR-γ agonists reactivate the ALDOC-NR2F1 axis to enhance sensitivity to temozolomide and suppress glioblastoma progression

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.26719677.v1
title: Additional file 3 of PPAR-γ agonists reactivate the ALDOC-NR2F1 axis to enhance sensitivity to temozolomide and suppress glioblastoma progression

description: Supplementary Material 3
DOI: 10.7910/dvn/26236/1xarww
title: farmact.xls
DOI: 10.7910/dvn/26236/czigqw
title: INCOME.xls
DOI: 10.7910/dvn/26236/meiryi
title: IO_CODES.xls
DOI: 10.7910/dvn/26236/rr3pkn
title: rice_output.xls
DOI: 10.7910/dvn/26236/rtafqh
title: Total Cost_HH.xls
DOI: 10.7910/dvn/26236/sciywb
title: Project details.xlsx
DOI: 10.7910/dvn/26236/uzorkl
title: demog_farmchar.xls
DOI: 10.7910/dvn/26236/wuqbbd
title: material inputs.xls
DOI: 10.7910/dvn/26236/9svonh
title: EXPENDITURE.xls
DOI: 10.7910/dvn/26236/aeogmu
title: landprep.xls
DOI: 10.7910/dvn/26236/bt7bpx
title: Social Capital Assessment Tool (SCAT).xls
DOI: 10.7910/dvn/26236/zllykq
title: TABLE_IO.xls
DOI: 10.5281/zenodo.14885412
title: Output Dataset of Building Heating and Cooling Demands in Morocco

description: This repository is for the paper "The Interplay Between Climate and Urban Expansion on Building Energy Demand in Morocco".

This repository includes the gridded (0.1 x 0.1 degree) residential and commercial heating and cooling demand per unit floorspace for three scenarios (2005, 2018, 2018+1.5C) in Morocco. The outputs are simulated using the Building Energy Demand (BED) model.

Outputs include:



building_energy_demand_2005.nc

building_energy_demand_2018.nc

building_energy_demand_2018-plus-1.5.nc
DOI: 10.5281/zenodo.14885413
title: Output Dataset of Building Heating and Cooling Demands in Morocco

description: This repository is for the paper "The Interplay Between Climate and Urban Expansion on Building Energy Demand in Morocco".

This repository includes the gridded (0.1 x 0.1 degree) residential and commercial heating and cooling demand per unit floorspace for three scenarios (2005, 2018, 2018+1.5C) in Morocco. The outputs are simulated using the Building Energy Demand (BED) model.

Outputs include:



building_energy_demand_2005.nc

building_energy_demand_2018.nc

building_energy_demand_2018-plus-1.5.nc
DOI: 10.5281/zenodo.14885409
title: Cultivation and Phenology of an antimalarial promising plant Artemisia annua in North India region at Agra

description: Artemisia annua Linn.is an antimalarial medicinal plant species producing bioactive compound artemisinin. The plant is native to china and north Asia and has been induced to India since the 1984’s. In Agra it is cultivated in semi desert area under extremes of temperatures (15-480c). Saline soil is best suited for cultivation. It is a winter annual herb completed its life cycle in nine months from November to July. It require early winter establishment by seeds. Germination of seeds take in month of November-December at temperature (10-160c) whereas maximum vegetative growth retained by plant during time period February to last April. The yellow flowers appear in the summer (April- May) and a month later seed formation takes place. Maturation of seed almost completed in June. Growth of plant ceases in month of July and plant dies in the end of August. Dry plants intact fruits remain on the ground became brown in colour.
DOI: 10.5281/zenodo.14885410
title: Cultivation and Phenology of an antimalarial promising plant Artemisia annua in North India region at Agra

description: Artemisia annua Linn.is an antimalarial medicinal plant species producing bioactive compound artemisinin. The plant is native to china and north Asia and has been induced to India since the 1984’s. In Agra it is cultivated in semi desert area under extremes of temperatures (15-480c). Saline soil is best suited for cultivation. It is a winter annual herb completed its life cycle in nine months from November to July. It require early winter establishment by seeds. Germination of seeds take in month of November-December at temperature (10-160c) whereas maximum vegetative growth retained by plant during time period February to last April. The yellow flowers appear in the summer (April- May) and a month later seed formation takes place. Maturation of seed almost completed in June. Growth of plant ceases in month of July and plant dies in the end of August. Dry plants intact fruits remain on the ground became brown in colour.
DOI: 10.5281/zenodo.14885397
title: Artefatos IPO

description: Artefatos do IPO



casosdeuso.png: Diagrama de casos de uso criado durante o planejamento do projeto.

modelagem_db.png: Modelagem do banco de dados.

logs_de_teste.zip: Arquivos que podem ser usados como entrada para o IPO.

demo.mp4: Vídeo de demonstração.

telas_design.zip: Telas produzidas como design e para prototipação.

emerging-all.rules: Arquivo .rules para configuração.
DOI: 10.5281/zenodo.14885398
title: Artefatos IPO

description: Artefatos do IPO



casosdeuso.png: Diagrama de casos de uso criado durante o planejamento do projeto.

modelagem_db.png: Modelagem do banco de dados.

logs_de_teste.zip: Arquivos que podem ser usados como entrada para o IPO.

demo.mp4: Vídeo de demonstração.

telas_design.zip: Telas produzidas como design e para prototipação.

emerging-all.rules: Arquivo .rules para configuração.
DOI: 10.7910/dvn/26228/1fc0mo
title: RODENTICIDE_1.xlsx
DOI: 10.7910/dvn/26228/7kfp2o
title: INSECTICIDE.xlsx
DOI: 10.7910/dvn/26228/atyxr2
title: INSECTICIDE_1.xlsx
DOI: 10.7910/dvn/26228/b5gvob
title: PRODUCTION.xlsx
DOI: 10.7910/dvn/26228/b62xup
title: PEST KNOWLEDGE 3.xlsx
DOI: 10.7910/dvn/26228/byl9hr
title: HANDPICKING_1.xlsx
DOI: 10.7910/dvn/26228/ck6ywi
title: PEST QUESTIONS.xlsx
DOI: 10.7910/dvn/26228/dg8wsi
title: CAPITAL LOAN.xlsx
DOI: 10.7910/dvn/26228/dwr1he
title: GENERAL INFO_1.xlsx
DOI: 10.7910/dvn/26228/eyjvug
title: LAND PREP.xlsx
DOI: 10.7910/dvn/26228/ff7gsn
title: HERBICIDE.xlsx
DOI: 10.7910/dvn/26228/fn5k20
title: FARM PARCELS.xlsx
DOI: 10.7910/dvn/26228/gj34mb
title: HERBICIDE_1.xlsx
DOI: 10.7910/dvn/26228/hoez35
title: MOLLUSCICIDE.xlsx
DOI: 10.7910/dvn/26228/hwwimn
title: FARM INVESTMENT.xlsx
DOI: 10.7910/dvn/26228/iu5cmc
title: IRRIGATION_1.xlsx
DOI: 10.7910/dvn/26228/k2jtat
title: FERTILIZER.xlsx
DOI: 10.7910/dvn/26228/l4khao
title: FUNGICIDE_1.xlsx
DOI: 10.7910/dvn/26228/lm5ghy
title: MOLLUSCICIDE_1.xlsx
DOI: 10.7910/dvn/26228/lp3hlf
title: LAND PREP_1.xlsx
DOI: 10.7910/dvn/26228/mblril
title: HANDPICKING.xlsx
DOI: 10.7910/dvn/26228/mczeu8
title: FERTILIZER_1.xlsx
DOI: 10.7910/dvn/26228/nyun9j
title: FUNGICIDE.xlsx
DOI: 10.7910/dvn/26228/o3nyd6
title: GENERAL INFO.xlsx
DOI: 10.7910/dvn/26228/ohsvup
title: HARVESTING.xlsx
DOI: 10.7910/dvn/26228/rcmcqo
title: PEST KNOWLEDGE 1.xlsx
DOI: 10.7910/dvn/26228/su0ia7
title: FARM PARCELS_1.xlsx
DOI: 10.7910/dvn/26228/tnbgta
title: CROP ESTABLISHMENT_1.xlsx
DOI: 10.7910/dvn/26228/vwliti
title: CROP ESTABLISHMENT.xlsx
DOI: 10.7910/dvn/26228/w5wc9h
title: CAPITAL LOAN_1.xlsx
DOI: 10.7910/dvn/26228/ze9mql
title: PEST KNOWLEDGE 2.xlsx
DOI: 10.7910/dvn/26228/bf3vjk
title: PEST WOMEN.xlsx
DOI: 10.7910/dvn/26228/fzlz85
title: IRRIGATION.xlsx
DOI: 10.7910/dvn/26228/j57ngh
title: SEED_1.xlsx
DOI: 10.7910/dvn/26228/lddbzw
title: SEEDBED_1.xlsx
DOI: 10.7910/dvn/26228/nhigrr
title: Manual of documentation PORIA.doc
DOI: 10.7910/dvn/26228/qvvlxf
title: PEST MGT A.xlsx
DOI: 10.7910/dvn/26228/wwa69x
title: HARVESTING_1.xlsx
DOI: 10.7910/dvn/26228/xeiftk
title: WEEDING.xlsx
DOI: 10.7910/dvn/26228/xfgorl
title: PRODUCTION_1.xlsx
DOI: 10.7910/dvn/26228/xzwm4g
title: PEST MGT B.xlsx
DOI: 10.7910/dvn/26228/9z6lkc
title: Project details.xlsx
DOI: 10.7910/dvn/26228/ahucet
title: SEEDBED.xlsx
DOI: 10.7910/dvn/26228/fl9rsq
title: SEED.xlsx
DOI: 10.7910/dvn/26228/lqnrdg
title: RODENTICIDE.xlsx
DOI: 10.7910/dvn/26228/mbgwlw
title: WEEDING_1.xlsx
DOI: 10.7910/dvn/26228/uctp3d
title: TRAINING ORG.xlsx
DOI: 10.15468/dl.um79dy
title: Occurrence Download

description: A dataset containing 1906 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Nepal",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ageratum houstonianum Mill."
 ]
}

 The dataset includes 1906 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004102-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14885403
title: A Novel 3D Predictive Model for Prime Numbers

description: Prime numbers are fundamental to mathematics, yet their distribution remains one of the greatest unsolved problems. Traditional research has focused on analytical approaches such as the Riemann Hypothesis, but no simple function has been able to deterministically predict primes.

This paper introduces a novel approach to understanding prime distributions by analyzing prime number triplets in a three-dimensional coordinate system. I employ statistical modeling, machine learning, and regression techniques to derive highly accurate predictive equations for prime numbers. My findings suggest an unexpectedly strong relationship between prime triplets, challenging the conventional notion of prime randomness. This work opens new doors for prime number research and its applications in cryptography and computational number theory.
DOI: 10.15468/dl.f9km3g
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Database of North American beaver (Castor canadensis Kuhl, 1820) in Russia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 2003-2018"
 ]
}

 The dataset includes 12 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004104-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yw5hyr
title: Occurrence Download

description: A dataset containing 48151 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is The Australian Zooplankton Database (1938 onwards)"
 ]
}

 The dataset includes 48151 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004105-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.