cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/hxxuhs/1bfuuc
title: DIM_CRPS.tab

description: :unav
DOI: 10.7910/dvn/hxxuhs/lkt6vr
title: DIM_PHASES.tab

description: :unav
DOI: 10.7910/dvn/hxxuhs/qx8bj0
title: FACT_PUBLICATIONS.tab

description: :unav
DOI: 10.7910/dvn/hxxuhs/swkyfc
title: DIM_PUBLICATIONS_INFO.tab

description: :unav
DOI: 10.7910/dvn/ikohap/9zbdb6
title: FACT_TRAINEES_2018.tab

description: :unav
DOI: 10.7910/dvn/ikohap/celmok
title: DIM_GENDER.tab

description: :unav
DOI: 10.17632/s2dvgdpf8n.4
title: Data for: Do improved pollination services outweigh farm-economic disadvantages of working in small- structured agricultural landscapes? – Development and application of a bio-economic model

description: This material encloses parts of our data (variable costs, yields and nutrient assumptions) as well as the R-script of our developed bio-economic model.
DOI: 10.7910/dvn/ikohap/cmu2gv
title: DIM_TRAINING_TERMS.tab

description: :unav
DOI: 10.7910/dvn/ikohap/q7zudi
title: DIM_PHASES.tab

description: :unav
DOI: 10.7910/dvn/ikohap/zzddsw
title: DIM_CRPS.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/7pvhuo
title: DIM_FLAGSHIPS.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/ezdfn5
title: DIM_PHASES.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/iduots
title: DIM_CRPS.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/nzinb0
title: DIM_STAGE_PROCESSES.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/rnn6ac
title: DIM_POLICIES_INFO.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/xabqv2
title: DIM_POLICY_INVESTMENT_TYPES.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/3ulec7
title: DIM_POLICIES_OWNERS.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/4wlyst
title: FACT_POLICIES.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/5tdcwc
title: DIM_LOCATIONS.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/bftcoc
title: DIM_GEO_SCOPES.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/h9pmju
title: DIM_SRF.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/k9zbxd
title: DIM_STG_MATURITIES.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/pqsomu
title: DIM_EXT_PARTNERS.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/sinfmo
title: DIM_SMO_ORG_TYPES.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/vhxkap
title: DIM_CCI.tab

description: :unav
DOI: 10.17632/dn6x9btbkx.1
title: Data for: Microarray-based detection of resistance and virulence factors in commensal Escherichia coli from livestock and farmers in Egypt

description: Raw microarray data obtained from the Kits E.coli PanType AS2 and ShigaType AS-1
DOI: 10.7910/dvn/kegeue/akhhsi
title: DIM_PARTNERSHIPS_MAIN_AREAS.tab

description: :unav
DOI: 10.7910/dvn/kegeue/iapmz1
title: DIM_CRPS.tab

description: :unav
DOI: 10.7910/dvn/kegeue/jzjfvo
title: DIM_PARNERSHIPS_2018_INFO.tab

description: :unav
DOI: 10.7910/dvn/kegeue/lxv4y0
title: DIM_PHASES.tab

description: :unav
DOI: 10.7910/dvn/kegeue/mqytaw
title: DIM_FLAGSHIPS.tab

description: :unav
DOI: 10.7910/dvn/kegeue/rvldk2
title: DIM_EXT_PARTNERS.tab

description: :unav
DOI: 10.7910/dvn/oxtlfn/ntx1jw
title: DIM_SDG.tab

description: :unav
DOI: 10.5281/zenodo.3553073
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Pirie, Michael, https://orcid.org/0000-0003-0403-4470. Claims were made on Bloodhound, https://bloodhound-tracker.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.6073/pasta/7696e20214fbf84f25d664ff7dc8050c
title: Marine turtles captured during haphazard at-sea surveys in Shark Bay, Australia from February 2008 to December 2013

description: This dataset provides information on marine turtles captured during long-term, haphazard surveys of our study site in Shark Bay, Western Australia. Taxon found in the study area include Chelonia mydas, Caretta caretta and Eretmochelys imbricata.
DOI: 10.7910/dvn/kegeue/goyz2v
title: FACT_PARTNERSHIP_2018.tab

description: :unav
DOI: 10.7910/dvn/nfnbzc/fnaa9n
title: DIM_CRPS.tab

description: :unav
DOI: 10.7910/dvn/nfnbzc/kxp9rg
title: DIM_INNOVATION_STG.tab

description: :unav
DOI: 10.7910/dvn/nfnbzc/zkqucl
title: DIM_RESEARCH_PHASES.tab

description: :unav
DOI: 10.7910/dvn/xzozgk/4uuqd0
title: Nicaragua 2017_JEPS replication.tab

description: :unav
DOI: 10.7910/dvn/xzozgk/pw6lto
title: JEPS_client mon vs benefits_clean.do

description: Do file that replicates all analyses
DOI: 10.7910/dvn/xzozgk/sjhtgm
title: README.rtf

description: :unav
DOI: 10.7910/dvn/nfnbzc/aaszck
title: DIM_SMO_ORG_TYPES.tab

description: :unav
DOI: 10.7910/dvn/nfnbzc/bcbnj1
title: DIM_PHASES.tab

description: :unav
DOI: 10.7910/dvn/nfnbzc/iwexut
title: DIM_GEO_SCOPES.tab

description: :unav
DOI: 10.7910/dvn/nfnbzc/ko61qf
title: DIM_CONTRIB_CRP.tab

description: :unav
DOI: 10.7910/dvn/nfnbzc/kxtsdy
title: DIM_DEGREE_INNOVATION.tab

description: :unav
DOI: 10.7910/dvn/nfnbzc/n0lmlu
title: FACT_INNOVATIONS.tab

description: :unav
DOI: 10.7910/dvn/nfnbzc/wsenu6
title: DIM_LOCATIONS.tab

description: :unav
DOI: 10.7910/dvn/nfnbzc/yefd66
title: DIM_DELIVERABLES_INFO.tab

description: :unav
DOI: 10.7910/dvn/nfnbzc/z7ohhx
title: DIM_INNOVATIONS_INFO.tab

description: :unav
DOI: 10.17632/whvphfzjry.1
title: Data for: The current strategies and parameters for the enhanced microbial production of 2,3-butanediol

description: 2,3-Butanediol (2,3-BD) is a propitious compound with many industrial uses ranging from rubber, fuels, and cosmetics to food additives. Its microbial production has especially attracted as an alternative way to the petroleum-based production. However, 2,3-BD production has always been hampered by low yields and high production costs. The enhanced production of 2,3-butanediol requires screening of the best strains and a systematic optimization of fermentation conditions. Moreover, the metabolic pathway engineering is essential to achieve the best results and minimize the production costs by rendering the strains to use efficiently low cost substrates. This review is to provide up-to-date information on the current strategies and parameters for the enhanced microbial production of 2,3-BD. .
DOI: 10.7910/dvn/nfnbzc/5gegfz
title: DIM_INNOVATION_TYPES.tab

description: :unav
DOI: 10.7910/dvn/nfnbzc/o7zher
title: DIM_OICS_METADATA.tab

description: :unav
DOI: 10.7910/dvn/wtayll/0rebcy
title: DIM_STG_MATURITIES.tab

description: :unav
DOI: 10.7910/dvn/wtayll/k7cxvc
title: DIM_EXT_PARTNERS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/liysuj
title: DIM_POLICY_INVESTMENT_TYPES.tab

description: :unav
DOI: 10.21227/8nfz-m523
title: Brain Signals and the Corresponding Hand Movement Signals Dataset (BS-HMS-Dataset)

description: BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer partcipants), and (2) Emotiv based Dataset (collected over several months in 2019). Neurosky based Dataset - Neurosky based dataset consists of EEG data recordings from neurosky headset and the corresponding hand movements recordings from SONY smartwatch's motions sensors. The users wore the smartwatch based on their personal preference of left or right hand.Emotiv based Dataset - Emotiv based dataset consists of EEG data recordings from Emotiv Epoc+ headset and the corresponding hand movements from both the hands of the user. The hand movement data was recorded using two SONY smartwatches which users wore in their hands, one in each hand. Both the datasets, Neurosky based Dataset and Emotiv based Dataset, were collected in two different sessions with an average gap of 6-7 days among the sessions. In each session the volunteer participants performed four different activities; (1) watching a happy video, (2) typing their response to the questions about the story in the watched happy video, (3) watching a sad video, and (4) typing their response to the questions about the story in the watched sad video. The users took a gap of ~5 minutes for rest between the different activities. The data was recorded separately for each activity. A more deatailed description of the data is given in BS-HMS-Dataset-README.pdf file.
DOI: 10.21227/e4q5-px89
title: Brain Signals and the Corresponding Hand Movement Signals Dataset (BS-HMS-Dataset))

description: BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer partcipants), and (2) Emotiv based Dataset (collected over several months in 2019). Neurosky based Dataset - Neurosky based dataset consists of EEG data recordings from neurosky headset and the corresponding hand movements recordings from SONY smartwatch's motions sensors. The users wore the smartwatch based on their personal preference of left or right hand.Emotiv based Dataset - Emotiv based dataset consists of EEG data recordings from Emotiv Epoc+ headset and the corresponding hand movements from both the hands of the user. The hand movement data was recorded using two SONY smartwatches which users wore in their hands, one in each hand. Both the datasets, Neurosky based Dataset and Emotiv based Dataset, were collected in two different sessions with an average gap of 6-7 days among the sessions. In each session the volunteer participants performed four different activities; (1) watching a happy video, (2) typing their response to the questions about the story in the watched happy video, (3) watching a sad video, and (4) typing their response to the questions about the story in the watched sad video. The users took a gap of ~5 minutes for rest between the different activities. The data was recorded separately for each activity. A more deatailed description of the data is given in BS-HMS-Dataset-README.pdf file.
DOI: 10.21227/m007-b259
title: Brain Signals and the Corresponding Hand Movement Signals Dataset (BS-HMS-Dataset))

description: BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer partcipants), and (2) Emotiv based Dataset (collected over several months in 2019). Neurosky based Dataset - Neurosky based dataset consists of EEG data recordings from neurosky headset and the corresponding hand movements recordings from SONY smartwatch's motions sensors. The users wore the smartwatch based on their personal preference of left or right hand.Emotiv based Dataset - Emotiv based dataset consists of EEG data recordings from Emotiv Epoc+ headset and the corresponding hand movements from both the hands of the user. The hand movement data was recorded using two SONY smartwatches which users wore in their hands, one in each hand. Both the datasets, Neurosky based Dataset and Emotiv based Dataset, were collected in two different sessions with an average gap of 6-7 days among the sessions. In each session the volunteer participants performed four different activities; (1) watching a happy video, (2) typing their response to the questions about the story in the watched happy video, (3) watching a sad video, and (4) typing their response to the questions about the story in the watched sad video. The users took a gap of ~5 minutes for rest between the different activities. The data was recorded separately for each activity. A more deatailed description of the data is given in BS-HMS-Dataset-README.pdf file.
DOI: 10.21227/my1k-dd23
title: Brain Signals and the Corresponding Hand Movement Signals Dataset (BS-HMS-Dataset))

description: BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer partcipants), and (2) Emotiv based Dataset (collected over several months in 2019). Neurosky based Dataset - Neurosky based dataset consists of EEG data recordings from neurosky headset and the corresponding hand movements recordings from SONY smartwatch's motions sensors. The users wore the smartwatch based on their personal preference of left or right hand. Emotiv based Dataset - Emotiv based dataset consists of EEG data recordings from Emotiv Epoc+ headset and the corresponding hand movements from both the hands of the user. The hand movement data was recorded using two SONY smartwatches which users wore in their hands, one in each hand. Both the datasets, Neurosky based Dataset and Emotiv based Dataset, were collected in two different sessions with an average gap of 6-7 days among the sessions. In each session the volunteer participants performed four different activities; (1) watching a happy video, (2) typing their response to the questions about the story in the watched happy video, (3) watching a sad video, and (4) typing their response to the questions about the story in the watched sad video. The users took a gap of ~5 minutes for rest between the different activities. The data was recorded separately for each activity. A more deatailed description of the data is given in BS-HMS-Dataset-README.pdf file.
DOI: 10.21227/p8cr-vn11
title: Brain Signals and the Corresponding Hand Movement Signals Dataset (BS-HMS-Dataset))

description: BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer partcipants), and (2) Emotiv based Dataset (collected over several months in 2019). Neurosky based Dataset - Neurosky based dataset consists of EEG data recordings from neurosky headset and the corresponding hand movements recordings from SONY smartwatch's motions sensors. The users wore the smartwatch based on their personal preference of left or right hand.Emotiv based Dataset - Emotiv based dataset consists of EEG data recordings from Emotiv Epoc+ headset and the corresponding hand movements from both the hands of the user. The hand movement data was recorded using two SONY smartwatches which users wore in their hands, one in each hand. Both the datasets, Neurosky based Dataset and Emotiv based Dataset, were collected in two different sessions with an average gap of 6-7 days among the sessions. In each session the volunteer participants performed four different activities; (1) watching a happy video, (2) typing their response to the questions about the story in the watched happy video, (3) watching a sad video, and (4) typing their response to the questions about the story in the watched sad video. The users took a gap of ~5 minutes for rest between the different activities. The data was recorded separately for each activity. A more deatailed description of the data is given in BS-HMS-Dataset-README.pdf file.
DOI: 10.21227/pv9q-rq48
title: Brain Signals and the Corresponding Hand Movement Signals Dataset (BS-HMS-Dataset))

description: BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer partcipants), and (2) Emotiv based Dataset (collected over several months in 2019). Neurosky based Dataset - Neurosky based dataset consists of EEG data recordings from neurosky headset and the corresponding hand movements recordings from SONY smartwatch's motions sensors. The users wore the smartwatch based on their personal preference of left or right hand. Emotiv based Dataset - Emotiv based dataset consists of EEG data recordings from Emotiv Epoc+ headset and the corresponding hand movements from both the hands of the user. The hand movement data was recorded using two SONY smartwatches which users wore in their hands, one in each hand. Both the datasets, Neurosky based Dataset and Emotiv based Dataset, were collected in two different sessions with an average gap of 6-7 days among the sessions. In each session the volunteer participants performed four different activities; (1) watching a happy video, (2) typing their response to the questions about the story in the watched happy video, (3) watching a sad video, and (4) typing their response to the questions about the story in the watched sad video. The users took a gap of ~5 minutes for rest between the different activities. The data was recorded separately for each activity. A more deatailed description of the data is given in BS-HMS-Dataset-README.pdf file.
DOI: 10.7910/dvn/wtayll/84zhfd
title: DIM_SRF_TARGETS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/fjz2yi
title: DIM_TAGS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/hhq4zm
title: BR_SRF_OICS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/hkjwn8
title: DIM_OICS_METADATA.tab

description: :unav
DOI: 10.7910/dvn/wtayll/ngecbj
title: DIM_CRPS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/ri66xs
title: BR_SRFTAR_OICS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/tpw5bm
title: BR_CCI_OICS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/txshyl
title: DIM_SMO_ORG_TYPES.tab

description: :unav
DOI: 10.21227/atyb-5p49
title: Brain Signals and the Corresponding Hand Movement Signals Dataset (BS-HMS-Dataset)

description: BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer partcipants), and (2) Emotiv based Dataset (collected over several months in 2019). Neurosky based Dataset - Neurosky based dataset consists of EEG data recordings from neurosky headset and the corresponding hand movements recordings from SONY smartwatch's motions sensors. The users wore the smartwatch based on their personal preference of left or right hand.Emotiv based Dataset - Emotiv based dataset consists of EEG data recordings from Emotiv Epoc+ headset and the corresponding hand movements from both the hands of the user. The hand movement data was recorded using two SONY smartwatches which users wore in their hands, one in each hand. Both the datasets, Neurosky based Dataset and Emotiv based Dataset, were collected in two different sessions with an average gap of 6-7 days among the sessions. In each session the volunteer participants performed four different activities; (1) watching a happy video, (2) typing their response to the questions about the story in the watched happy video, (3) watching a sad video, and (4) typing their response to the questions about the story in the watched sad video. The users took a gap of ~5 minutes for rest between the different activities. The data was recorded separately for each activity.
DOI: 10.21227/h697-sh97
title: Brain Signals and the Corresponding Hand Movement Signals Dataset (BS-HMS-Dataset)

description: BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer partcipants), and (2) Emotiv based Dataset (collected over several months in 2019). Neurosky based Dataset - Neurosky based dataset consists of EEG data recordings from neurosky headset and the corresponding hand movements recordings from SONY smartwatch's motions sensors. The users wore the smartwatch based on their personal preference of left or right hand.Emotiv based Dataset - Emotiv based dataset consists of EEG data recordings from Emotiv Epoc+ headset and the corresponding hand movements from both the hands of the user. The hand movement data was recorded using two SONY smartwatches which users wore in their hands, one in each hand. Both the datasets, Neurosky based Dataset and Emotiv based Dataset, were collected in two different sessions with an average gap of 6-7 days among the sessions. In each session the volunteer participants performed four different activities; (1) watching a happy video, (2) typing their response to the questions about the story in the watched happy video, (3) watching a sad video, and (4) typing their response to the questions about the story in the watched sad video. The users took a gap of ~5 minutes for rest between the different activities. The data was recorded separately for each activity.
DOI: 10.7910/dvn/wtayll/7xnsbz
title: DIM_GEO_SCOPES.tab

description: :unav
DOI: 10.7910/dvn/wtayll/dypz6q
title: BR_FLAGSHIP_OICS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/hvkqk7
title: BR_LOC_OICS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/m6zror
title: DIM_LOCATIONS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/rovxtx
title: BR_GEO_OICS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/s4bypc
title: DIM_SRF.tab

description: :unav
DOI: 10.7910/dvn/wtayll/wjjy9w
title: FACT_OICS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/wpofno
title: DIM_CCI.tab

description: :unav
DOI: 10.7910/dvn/wtayll/zw0gvq
title: DIM_PHASES.tab

description: :unav
DOI: 10.7910/dvn/wjlrlx/3e3wqw
title: DIM_FLAGSHIPS.tab

description: :unav
DOI: 10.7910/dvn/wjlrlx/3r9fr0
title: DIM_MILESTONE_STATUS_REASONS.tab

description: :unav
DOI: 10.7910/dvn/wjlrlx/3rsos3
title: FACT_MILESTONE_STATUS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/etf0ap
title: DIM_FLAGSHIPS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/jzseih
title: DIM_SDG.tab

description: :unav
DOI: 10.7910/dvn/wtayll/y55b9f
title: BR_SDG_OICS.tab

description: :unav
DOI: 10.7910/dvn/wtayll/yukdaf
title: DIM_STAGE_PROCESSES.tab

description: :unav
DOI: 10.21227/81fp-6c60
title: Brain Signals and the Corresponding Hand Movement Signals Dataset (BS-HMS-Dataset)

description: BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer partcipants), and (2) Emotiv based Dataset (collected over several months in 2019). Neurosky based Dataset - Neurosky based dataset consists of EEG data recordings from neurosky headset and the corresponding hand movements recordings from SONY smartwatch's motions sensors. The users wore the smartwatch based on their personal preference of left or right hand.Emotiv based Dataset - Emotiv based dataset consists of EEG data recordings from Emotiv Epoc+ headset and the corresponding hand movements from both the hands of the user. The hand movement data was recorded using two SONY smartwatches which users wore in their hands, one in each hand. Both the datasets, Neurosky based Dataset and Emotiv based Dataset, were collected in two different sessions with an average gap of 6-7 days among the sessions. In each session the volunteer participants performed four different activities; (1) watching a happy video, (2) typing their response to the questions about the story in the watched happy video, (3) watching a sad video, and (4) typing their response to the questions about the story in the watched sad video. The users took a gap of ~5 minutes for rest between the different activities. The data was recorded separately for each activity.
DOI: 10.7910/dvn/wjlrlx/8e1pzy
title: DIM_MILESTONE_STATUSES.tab

description: :unav
DOI: 10.7910/dvn/wjlrlx/agzzwn
title: DIM_PHASES.tab

description: :unav
DOI: 10.7910/dvn/wjlrlx/ihkid2
title: DIM_MILESTONE_STATUS_INFO.tab

description: :unav
DOI: 10.7910/dvn/wjlrlx/jqziul
title: DIM_CRPS.tab

description: :unav
DOI: 10.7910/dvn/wjlrlx/wsbyvt
title: DIM_MILESTONES.tab

description: :unav
DOI: 10.7910/dvn/wjlrlx/zdqmv4
title: DIM_CROSS_CUTTING_LEVELS.tab

description: :unav