cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/bw3pn7m873.2
title: Data and program codes for the article in Analytica Chimica Acta "A new constraint to model background signals when processing chromatographic-spectral second-order data with multivariate curve resolution "

description: This set contains data and program codes for the article "A new constraint to model background signals when processing chromatographic-spectral second-order data with multivariate curve resolution", Carabajal, MD, Pellegrino Vidal, R, Arancibia, JA, Olivieri, AC, Anal. Chim. Acta 1266 (2023) 341354. Departamento de Química Analítica, Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Instituto de Química Rosario (CONICET-UNR), Suipacha 531 (2000) Rosario, Argentina
DOI: 10.7483/opendata.cms.zi4m.6wvd
title: /XtoAAto4G_X1500A30_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17632/7mshy2kcf3.2
title: Respiratory pressure and split flow data collection device with rapid expiratory shuttering

description: The venturi-based flow meter utilises split inspiratory and expiratory flow pathways, for greater configurability with additional respiratory monitoring or simulation devices, as well for ease of data processing. The venturi is designed to be integrated in series with respiratory circuitry, using standard 22mm male and female connections. In its current application the inspiratory input port (22mm male connection) is connected to a CPAP device using its accompanying circuitry (or is unconnected when CPAP is not required), the expiratory output port vents to atmosphere (22mm female connection), and the subject port (22mm male connection) is connected to a mouthpiece, filter, or mask. Differential Pressure Sensors were also upgraded (SSCDRRN001PD2A5) to capture larger flow ranges (seen in maximal breaths and panting).

Additionally, a modular expiratory shutter attachment is outlined for identification of passive respiratory mechanics. Specifically, the rapid expiratory shuttering allows for breath-wise identification of elastance and resistance during shutter instances. Thus, eliminating the issue of trade-off associated with the simultaneous fitting of elastance and resistance to expiratory profiles.

Ultimately, the device provides researchers with:

- Rapid expiratory occlusion for identification of passive lung mechanics 
- A low-cost alternative to commercial sensor systems 
- Individual inspiratory and expiratory flow pathways 
- Non-invasive data collection 
- A modular design with high customisability
DOI: 10.7483/opendata.cms.bu54.v1ck
title: /XtoAAto4G_X1500A30_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.zeem.fm2r
title: /XtoAAto4G_X1500A375_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.jf24.zp4b
title: /XtoAAto4G_X1500A375_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.hj5x.ao9k
title: /XtoAAto4G_X1500A37p5_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17632/vzgc98233x.1
title: LDHU3_14.1920

description: Protein of unknown function – conserved | WCB; Leishmania donovani (HU3 strain)
DOI: 10.5281/zenodo.8005474
title: Data for: A tool based on the Industry Foundation Classes standard for dynamic data collection and automatic generation of Building Automation Control Networks

description: This dataset shows the results obtained for a case study at TRL4 for the research paper title A tool based on the Industry Foundation Classes standard for dynamic data collection and automatic generation of Building Automation Control Networks, with DOI: https://doi.org/10.1016/j.jobe.2023.107625


This dataset is an enhanced IFC (Industry Foundation Classes) file with the creation of the BACN (Building Automation Control Network). This IFC file includes the devices created automatically by the BACN2BIM tool  (developed by CARTIF Technology Centre) for the case study validated at TRL4. The original IFC was obtained from the Institute for Automation and Applied Informatics (IAI) / Karlsruhe Institute of Technology (KIT) https://www.ifcwiki.org/images/e/e3/AC20-FZK-Haus.ifc, under an unrestricted license, as served as one of the case studies for this research.


*Depending on the IFC viewer used, the included sensors may not be represented correctly. In this case, it is recommended to try with another IFC viewer, for example xBIM explorer https://docs.xbim.net/downloads/xbimxplorer.html or BimCollab Zoom Free https://www.bimcollab.com/en/support/downloads/
DOI: 10.5281/zenodo.8005475
title: Data for: A tool based on the Industry Foundation Classes standard for dynamic data collection and automatic generation of Building Automation Control Networks

description: This dataset shows the results obtained for a case study at TRL4 for the research paper title A tool based on the Industry Foundation Classes standard for dynamic data collection and automatic generation of Building Automation Control Networks, with DOI: https://doi.org/10.1016/j.jobe.2023.107625


This dataset is an enhanced IFC (Industry Foundation Classes) file with the creation of the BACN (Building Automation Control Network). This IFC file includes the devices created automatically by the BACN2BIM tool  (developed by CARTIF Technology Centre) for the case study validated at TRL4. The original IFC was obtained from the Institute for Automation and Applied Informatics (IAI) / Karlsruhe Institute of Technology (KIT) https://www.ifcwiki.org/images/e/e3/AC20-FZK-Haus.ifc, under an unrestricted license, as served as one of the case studies for this research.


*Depending on the IFC viewer used, the included sensors may not be represented correctly. In this case, it is recommended to try with another IFC viewer, for example xBIM explorer https://docs.xbim.net/downloads/xbimxplorer.html or BimCollab Zoom Free https://www.bimcollab.com/en/support/downloads/
DOI: 10.48668/j40yug/ndctdy
title: Figure3.jpg

description: :unav
DOI: 10.7483/opendata.cms.hz4r.216r
title: /XtoAAto4G_X1500A37p5_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.17632/7x3yz9sn46.1
title: LDHU3_16.1170

description: Protein of unknown function - conserved; Leishmania donovani (HU3 strain)
DOI: 10.48668/j40yug/abqtsn
title: FigureS5.JPG

description: :unav
DOI: 10.48668/j40yug/exnwkl
title: FigureS4.JPG

description: :unav
DOI: 10.48668/j40yug/jcgopr
title: FigureS2.JPG

description: :unav
DOI: 10.48668/j40yug/jrkyqa
title: FigureS6.JPG

description: :unav
DOI: 10.48668/j40yug/l6mfqm
title: Figure4.jpg

description: :unav
DOI: 10.48668/j40yug/lqjhe7
title: FigureS1.JPG

description: :unav
DOI: 10.48668/j40yug/pumjkr
title: Figure5.jpg

description: :unav
DOI: 10.48668/j40yug/rvkmmv
title: FigureS7.JPG

description: :unav
DOI: 10.48668/j40yug/ti7a11
title: FigureS8.JPG

description: :unav
DOI: 10.48668/j40yug/wbkocm
title: Figure2.jpg

description: :unav
DOI: 10.48668/j40yug/xsqyab
title: FigureS3.JPG

description: :unav
DOI: 10.48668/j40yug
title: Figures

description: Figures and specimens photos of this study.
DOI: 10.48668/j40yug/0c4gkb
title: Figure4.jpg

description: :unav
DOI: 10.48668/j40yug/0kfw9t
title: Figure1.jpg

description: :unav
DOI: 10.48668/j40yug/jyjjp8
title: FigureS21.jpg

description: :unav
DOI: 10.48668/j40yug/lkwiv6
title: Figure1.jpg

description: :unav
DOI: 10.48668/j40yug/nrlvid
title: Supplementary Information.pdf

description: Supplementary Figures S1 to S21 with legends.
DOI: 10.48668/j40yug/tbfoey
title: Figure5.jpg

description: :unav
DOI: 10.48668/j40yug/wq5aly
title: Figure3.jpg

description: :unav
DOI: 10.17632/psh63mzc48.1
title: LDHU3_14.1960

description: Glutathione-S-transferase/glutaredoxin; Leishmania donovani (HU3 strain)
DOI: 10.7483/opendata.cms.e8ua.aacm
title: /XtoAAto4G_X1500A45_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.gf9v.f6en
title: /XtoAAto4G_X1500A45_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.5nln.qwpk
title: /XtoAAto4G_X1500A600_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.ciih.eyic
title: /XtoAAto4G_X1500A600_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.uj1i.m77d
title: /XtoAAto4G_X1500A75_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.p3d0.y5wi
title: /XtoAAto4G_X1500A75_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.jyo0.cf6r
title: /XtoAAto4G_X1500A7p5_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.qngo.6xsi
title: /XtoAAto4G_X1500A7p5_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.oywz.plqm
title: /XtoAAto4G_X2000A100_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.y41v.xi3y
title: /XtoAAto4G_X2000A100_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.idqt.qg12
title: /XtoAAto4G_X2000A10_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.gcrp.kp4l
title: /XtoAAto4G_X2000A10_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.cjx5.oea2
title: /XtoAAto4G_X2000A200_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.tc2m.9yoy
title: /XtoAAto4G_X2000A200_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.15468/dl.exfpa7
title: Occurrence Download

description: A dataset containing 63352 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pseudopleuronectes americanus (Walbaum, 1792)"
 ]
}

 The dataset includes 63352 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000087-250117103327516/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7483/opendata.cms.hwf6.6pic
title: /XtoAAto4G_X2000A20_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.aad7.9x48
title: /XtoAAto4G_X2000A20_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.m3tp.0jmf
title: /XtoAAto4G_X2000A30_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.5281/zenodo.14678414
title: COMBINING BLOCKCHAIN AND IOT FOR DECENTRALIZED HEALTHCARE DATA MANAGEMENT

description: Combining Blockchain and IoT for Decentralized Healthcare Data Management

 



Authors


Sajad Meisami1, Sadaf Meisami2, Melina Yousefi3 and Mohammad Reza Aref4, 1Illinois Institute of Technology, USA, 2Kharazmi University, Iran, 3Isfahan University of Technology, Iran, 4Sharif University of Technology, Iran

 



Abstract

The emergence of the Internet of Things (IoT) has resulted in a significant increase in research on e-health. As the amount of patient data grows, it has become increasingly challenging to protect patients' privacy. Patient data is commonly stored in the cloud, making it difficult for users to control and protect their information. Moreover, the recent rise in security and surveillance breaches in the healthcare industry has highlighted the need for a better approach to data storage and protection. Traditional models that rely on third-party control over patients' healthcare data are no longer reliable, as they have proven vulnerable to security breaches. To address these issues, blockchain technology has emerged as a promising solution. Blockchain-based protocols have the potential to provide a secure and efficient system for e-health applications that does not require trust in third-party intermediaries. The proposed protocol outlined in this paper uses a blockchain-based approach to manage patient data securely and efficiently. Unlike Bitcoin, which is primarily used for financial transactions, the protocol described here is designed specifically for e-health applications. It employs a consensus mechanism that is more suitable for resource constrained IoT devices, thereby reducing network costs and increasing efficiency. The proposed protocol also provides a privacy-preserving access control mechanism that enables patients to have more control over their healthcare data. By leveraging blockchain technology, the protocol ensures that only authorized individuals can access the patient's data, which helps prevent data breaches and other security issues. Finally, the security and privacy of the proposed protocol are analysed to ensure that it meets the necessary standards for data protection. The protocol's effectiveness and efficiency are tested under different scenarios to ensure that it can perform reliably and consistently. Finally, the protocol proposed in this paper shows that how blockchain can be used to provide a secure and efficient system that empowers patients to take control of their healthcare data.

Keywords

Internet of Things (IoT), Blockchain Technology, Healthcare data management, IoT e-health, privacy, access control, Security
DOI: 10.5281/zenodo.14678415
title: COMBINING BLOCKCHAIN AND IOT FOR DECENTRALIZED HEALTHCARE DATA MANAGEMENT

description: Combining Blockchain and IoT for Decentralized Healthcare Data Management

 



Authors


Sajad Meisami1, Sadaf Meisami2, Melina Yousefi3 and Mohammad Reza Aref4, 1Illinois Institute of Technology, USA, 2Kharazmi University, Iran, 3Isfahan University of Technology, Iran, 4Sharif University of Technology, Iran

 



Abstract

The emergence of the Internet of Things (IoT) has resulted in a significant increase in research on e-health. As the amount of patient data grows, it has become increasingly challenging to protect patients' privacy. Patient data is commonly stored in the cloud, making it difficult for users to control and protect their information. Moreover, the recent rise in security and surveillance breaches in the healthcare industry has highlighted the need for a better approach to data storage and protection. Traditional models that rely on third-party control over patients' healthcare data are no longer reliable, as they have proven vulnerable to security breaches. To address these issues, blockchain technology has emerged as a promising solution. Blockchain-based protocols have the potential to provide a secure and efficient system for e-health applications that does not require trust in third-party intermediaries. The proposed protocol outlined in this paper uses a blockchain-based approach to manage patient data securely and efficiently. Unlike Bitcoin, which is primarily used for financial transactions, the protocol described here is designed specifically for e-health applications. It employs a consensus mechanism that is more suitable for resource constrained IoT devices, thereby reducing network costs and increasing efficiency. The proposed protocol also provides a privacy-preserving access control mechanism that enables patients to have more control over their healthcare data. By leveraging blockchain technology, the protocol ensures that only authorized individuals can access the patient's data, which helps prevent data breaches and other security issues. Finally, the security and privacy of the proposed protocol are analysed to ensure that it meets the necessary standards for data protection. The protocol's effectiveness and efficiency are tested under different scenarios to ensure that it can perform reliably and consistently. Finally, the protocol proposed in this paper shows that how blockchain can be used to provide a secure and efficient system that empowers patients to take control of their healthcare data.

Keywords

Internet of Things (IoT), Blockchain Technology, Healthcare data management, IoT e-health, privacy, access control, Security
DOI: 10.7483/opendata.cms.n6p2.w4h7
title: /XtoAAto4G_X2000A30_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.9o87.wvbi
title: /XtoAAto4G_X2000A40_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.m232.fjf1
title: /XtoAAto4G_X2000A40_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.vwk6.h2oo
title: /XtoAAto4G_X2000A500_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.xuih.v8tx
title: /XtoAAto4G_X2000A500_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.17028/rd.lboro.28228292
title: Supplementary information files for "High‐impact jumping mitigates the short‐term effects of low energy availability on bone resorption but not formation in regularly menstruating females: A randomized control trial"

description: Supplementary files for article "High‐impact jumping mitigates the short‐term effects of low energy availability on bone resorption but not formation in regularly menstruating females: A randomized control trial" <br><br>Low energy availability (LEA) is prevalent in active individuals and negatively impacts bone turnover in young females. High‐impact exercise can promote bone health in an energy efficient manner and may benefit bone during periods of LEA. Nineteen regularly menstruating females (aged 18–31 years) participated in two three‐day conditions providing 15 (LEA) and 45 kcals kg fat‐free mass<sup>−1</sup>day<sup>−1</sup> (BAL) of energy availability, each beginning 3 ± 1 days following the self‐reported onset of menses. Participants either did (LEA+J, n = 10) or did not (LEA, n = 9) perform 20 high‐impact jumps twice per day during LEA, with P1NP, β‐CTx (circulating biomarkers of bone formation and resorption, respectively) and other markers of LEA measured pre and post in a resting and fasted state. Data are presented as estimated marginal mean ± 95% CI. P1NP was significantly reduced in LEA (71.8 ± 6.1–60.4 ± 6.2 ng mL−1, p &lt; 0.001, d = 2.36) and LEA+J (93.9 ± 13.4–85.2 ± 12.3 ng mL<sup>−1</sup>, p &lt; 0.001, d = 1.66), and these effects were not significantly different (time by condition interaction: p = 0.269). β‐CTx was significantly increased in LEA (0.39 ± 0.09–0.46 ± 0.10 ng mL<sup>−1</sup>, p = 0.002, d = 1.11) but not in LEA+J (0.65 ± 0.08–0.65 ± 0.08 ng mL<sup>−1</sup>, p &gt; 0.999, d = 0.19), and these effects were significantly different (time by condition interaction: p = 0.007). Morning basal bone formation rate is reduced following 3 days LEA, induced via dietary restriction, with or without high‐impact jumping in regularly menstruating young females. However, high‐impact jumping can prevent an increase in morning basal bone resorption rate and may benefit long‐term bone health in individuals repeatedly exposed to such bouts.<br>© The Authors, CC BY 4.0
DOI: 10.17028/rd.lboro.28228292.v1
title: Supplementary information files for "High‐impact jumping mitigates the short‐term effects of low energy availability on bone resorption but not formation in regularly menstruating females: A randomized control trial"

description: Supplementary files for article "High‐impact jumping mitigates the short‐term effects of low energy availability on bone resorption but not formation in regularly menstruating females: A randomized control trial" <br><br>Low energy availability (LEA) is prevalent in active individuals and negatively impacts bone turnover in young females. High‐impact exercise can promote bone health in an energy efficient manner and may benefit bone during periods of LEA. Nineteen regularly menstruating females (aged 18–31 years) participated in two three‐day conditions providing 15 (LEA) and 45 kcals kg fat‐free mass<sup>−1</sup>day<sup>−1</sup> (BAL) of energy availability, each beginning 3 ± 1 days following the self‐reported onset of menses. Participants either did (LEA+J, n = 10) or did not (LEA, n = 9) perform 20 high‐impact jumps twice per day during LEA, with P1NP, β‐CTx (circulating biomarkers of bone formation and resorption, respectively) and other markers of LEA measured pre and post in a resting and fasted state. Data are presented as estimated marginal mean ± 95% CI. P1NP was significantly reduced in LEA (71.8 ± 6.1–60.4 ± 6.2 ng mL−1, p &lt; 0.001, d = 2.36) and LEA+J (93.9 ± 13.4–85.2 ± 12.3 ng mL<sup>−1</sup>, p &lt; 0.001, d = 1.66), and these effects were not significantly different (time by condition interaction: p = 0.269). β‐CTx was significantly increased in LEA (0.39 ± 0.09–0.46 ± 0.10 ng mL<sup>−1</sup>, p = 0.002, d = 1.11) but not in LEA+J (0.65 ± 0.08–0.65 ± 0.08 ng mL<sup>−1</sup>, p &gt; 0.999, d = 0.19), and these effects were significantly different (time by condition interaction: p = 0.007). Morning basal bone formation rate is reduced following 3 days LEA, induced via dietary restriction, with or without high‐impact jumping in regularly menstruating young females. However, high‐impact jumping can prevent an increase in morning basal bone resorption rate and may benefit long‐term bone health in individuals repeatedly exposed to such bouts.<br>© The Authors, CC BY 4.0
DOI: 10.7483/opendata.cms.jkx2.sjpv
title: /XtoAAto4G_X2000A50_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.34740/kaggle/dsv/10496606
title: Forex Exchange Rates Since 2004 (Updated Daily)
DOI: 10.7483/opendata.cms.vz0m.2fk2
title: /XtoAAto4G_X2000A50_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.mc7j.bq0c
title: /XtoAAto4G_X2000A60_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.15468/dl.mbmh6e
title: Occurrence Download

description: A dataset containing 79 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pteragogus pelycus Randall, 1981"
 ]
}

 The dataset includes 79 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000088-250117103327516/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7483/opendata.cms.lqan.1c4a
title: /XtoAAto4G_X2000A60_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.mstl.vlhk
title: /XtoAAto4G_X2000A800_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.mnmo.xuru
title: /XtoAAto4G_X2000A800_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.qi9r.xbpo
title: /XtoAAto4G_X200A10_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.gobo.d3oa
title: /XtoAAto4G_X200A10_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.spqx.i72k
title: /XtoAAto4G_X200A1_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM