cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/8y0-x5l-a84
title: Phyllagathis Blume

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/dbw-8my-04p
title: Vitex trifolia L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/szn-80j-vjl
title: Callicarpa L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/ykf-la0-z0e
title: Kopsia fruticosa (Ker Gawl.) A. DC.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/hh1-h6f-54r
title: Melastomataceae Juss.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/xvf-mb9-dlm
title: Pinanga annamensis Magalon

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.5281/zenodo.18610649
title: Frequency-dependent gas opacity tables presented and used in the publication 'The role of detailed gas and dust opacities in shaping the evolution of the inner disc edge subject to episodic accretion' by Cecil et al. 2026 in the journal Astronomy & Astrophysics

description: Plese refer to the included ReadMe file (written according to CDS standards) for detailed information about the data files.
DOI: 10.5281/zenodo.18610648
title: Frequency-dependent gas opacity tables presented and used in the publication 'The role of detailed gas and dust opacities in shaping the evolution of the inner disc edge subject to episodic accretion' by Cecil et al. 2026 in the journal Astronomy & Astrophysics

description: Plese refer to the included ReadMe file (written according to CDS standards) for detailed information about the data files.
DOI: 10.15468/dl.zwgpav
title: Occurrence Download

description: A dataset containing 3323 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Observaciones de aves en el occidente de Boyacá, municipios de Quípama y Puerto Boyacá"
 ]
}

 The dataset includes 3323 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008686-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18018158
title: 6 channel raw sEMG signal recorded from biceps, triceps and trapezius during manual assembly operation (Sitting)

description: DescriptionThe dataset contains raw surface EMG signals recorded during a repeated assembly task. The trial is conducted while the operator was sitting while the forearms are rested on the work table. Signal DescriptionThe signal consists of 6 sEMG channels from biceps(Channel 2 and 3), triceps(Channel 4 and 5) and Upper Trapezeus Channel 6 and 7) muscles. Each sensor channel records at a frequency of 1000Hz. All 6 channels are synchronised. 

Data FormatData is  in the from of a list of JSON payloads each consisting of 200 data points each. Minimum Recomended data processing proceduresPre-Preperation --> Convert from JSON to DataFrameBand pass filter --> 20 - 450 HzNotch filter --> 50Hz (Power line frequency)





Acknowledgement



This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No's 101093069 (P2CODE) and 101120657(ENFIELD). Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commission. Neither the European Union nor the European Commission can be held responsible for them.

Citation The users of this dataset are kindly asked to cite the following paper:Syed, D.A., Quadrini, W., Rahmani Choubeh, N., Pinzone, M., Gusmeroli, S. (2025). Approaching Interoperability and Data-Related Processing Issues in a Human-Centric Industrial Scenario. In: Presser, M., Skarmeta, A., Krco, S., González Vidal, A. (eds) Global Internet of Things and Edge Computing Summit. GIECS 2024. Communications in Computer and Information Science, vol 2328. Springer, Cham. https://doi.org/10.1007/978-3-031-78572-6_2
DOI: 10.5281/zenodo.18018157
title: 6 channel raw sEMG signal recorded from biceps, triceps and trapezius during manual assembly operation (Sitting)

description: DescriptionThe dataset contains raw surface EMG signals recorded during a repeated assembly task. The trial is conducted while the operator was sitting while the forearms are rested on the work table. Signal DescriptionThe signal consists of 6 sEMG channels from biceps(Channel 2 and 3), triceps(Channel 4 and 5) and Upper Trapezeus Channel 6 and 7) muscles. Each sensor channel records at a frequency of 1000Hz. All 6 channels are synchronised. 

Data FormatData is  in the from of a list of JSON payloads each consisting of 200 data points each. Minimum Recomended data processing proceduresPre-Preperation --> Convert from JSON to DataFrameBand pass filter --> 20 - 450 HzNotch filter --> 50Hz (Power line frequency)





Acknowledgement



This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No's 101093069 (P2CODE) and 101120657(ENFIELD). Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commission. Neither the European Union nor the European Commission can be held responsible for them.

Citation The users of this dataset are kindly asked to cite the following paper:Syed, D.A., Quadrini, W., Rahmani Choubeh, N., Pinzone, M., Gusmeroli, S. (2025). Approaching Interoperability and Data-Related Processing Issues in a Human-Centric Industrial Scenario. In: Presser, M., Skarmeta, A., Krco, S., González Vidal, A. (eds) Global Internet of Things and Edge Computing Summit. GIECS 2024. Communications in Computer and Information Science, vol 2328. Springer, Cham. https://doi.org/10.1007/978-3-031-78572-6_2
DOI: 10.6084/m9.figshare.29106899
title: Figure3

description: In quantum networks, after passing through noisy channels or information processing, residual states may lack sufficient entanglement for further tasks, yet they may retain hidden quantum resources that can be recycled. Efficiently recycling these states to extract entanglement resources such as genuine multipartite entanglement or Einstein-Podolsky-Rosen pairs is essential for optimizing network performance. Here, we develop a tripartite entanglement distillation scheme using an eight-photon quantum platform, demonstrating entanglement superactivation phenomena which are unique to multipartite systems. We successfully generate a three-photon genuinely entangled state from two bi-separable states via local operations and classical communication, demonstrating superactivation of genuine multipartite entanglement.Furthermore, we extend our scheme to generate a three-photon state capable of extracting an Einstein-Podolsky-Rosen pair from two initial states lacking this capability, revealing a previously unobserved entanglement superactivation phenomenon. Our methods and findings offer not only practical applications for quantum networks, but also lead to a deeper understanding of multipartite entanglement structures.
DOI: 10.6084/m9.figshare.29106899.v1
title: Figure3

description: In quantum networks, after passing through noisy channels or information processing, residual states may lack sufficient entanglement for further tasks, yet they may retain hidden quantum resources that can be recycled. Efficiently recycling these states to extract entanglement resources such as genuine multipartite entanglement or Einstein-Podolsky-Rosen pairs is essential for optimizing network performance. Here, we develop a tripartite entanglement distillation scheme using an eight-photon quantum platform, demonstrating entanglement superactivation phenomena which are unique to multipartite systems. We successfully generate a three-photon genuinely entangled state from two bi-separable states via local operations and classical communication, demonstrating superactivation of genuine multipartite entanglement.Furthermore, we extend our scheme to generate a three-photon state capable of extracting an Einstein-Podolsky-Rosen pair from two initial states lacking this capability, revealing a previously unobserved entanglement superactivation phenomenon. Our methods and findings offer not only practical applications for quantum networks, but also lead to a deeper understanding of multipartite entanglement structures.
DOI: 10.15468/dl.k4n8zq
title: Occurrence Download

description: A dataset containing 67 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chamaecrista dentata",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 67 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008687-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mm6bkh
title: Occurrence Download

description: A dataset containing 71 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Agrostophyllum majus",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 71 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008688-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18502006
title: Baseline Dataset for the Translation-Prophet Interpretation Module
DOI: 10.5281/zenodo.18610738
title: Multiple Choice Questions: Reasoning Makes Large Language Models More Self- Confident, Especially When They Are Wrong

description: This repo provides the data and scripts for the paper: Multiple Choice Questions: Thinking Makes Large Language Models (LLMs) More Self-Confident Even When They are Wrong, IEEE Intelligent Systems (in press)

Repository Contents





MMLU: Contains the MMLU datasets from https://huggingface.co/datasets/cais/mmlu




Results: Include results under two types of prompts: one where the LLM directly generates an answer and another where the answer is generated after thinking. Each prompt contains two CSV files for each dataset, one for the original response and the other for the probabilities of the response options.




Figure: Outputs and visualizations derived from the analysis.




Code: The Python script used for analyzing and plotting the data in the Results folder.
DOI: 10.5281/zenodo.18610739
title: Multiple Choice Questions: Reasoning Makes Large Language Models More Self- Confident, Especially When They Are Wrong

description: This repo provides the data and scripts for the paper: Multiple Choice Questions: Thinking Makes Large Language Models (LLMs) More Self-Confident Even When They are Wrong, IEEE Intelligent Systems (in press)

Repository Contents





MMLU: Contains the MMLU datasets from https://huggingface.co/datasets/cais/mmlu




Results: Include results under two types of prompts: one where the LLM directly generates an answer and another where the answer is generated after thinking. Each prompt contains two CSV files for each dataset, one for the original response and the other for the probabilities of the response options.




Figure: Outputs and visualizations derived from the analysis.




Code: The Python script used for analyzing and plotting the data in the Results folder.
DOI: 10.5281/zenodo.18502005
title: Baseline Dataset for the Translation-Prophet Interpretation Module
DOI: 10.5281/zenodo.18021957
title: 6 channel raw sEMG signal recorded from biceps, triceps and trapezius during manual assembly operation (Standing)

description: DescriptionThe dataset contains raw surface EMG signals recorded during a repeated assembly task. This dataset was recorded while standing therefore the arms are unsupported putting additional strain on the operator.Signal DescriptionThe signal consists of 6 sEMG channels from biceps(Channel 2 and 3), triceps(Channel 4 and 5) and Upper Trapezeus Channel 6 and 7) muscles. Each sensor channel records at a frequency of 1000Hz. All 6 channels are synchronised. 

Data FormatData is  in the from of a list of JSON payloads each consisting of 200 data points each. Minimum Recomended data processing proceduresPre-Preperation --> Convert from JSON to DataFrameBand pass filter --> 20 - 450 HzNotch filter --> 50Hz (Power line frequency)





Acknowledgement



This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No's 101093069 (P2CODE) and 101120657(ENFIELD). Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commission. Neither the European Union nor the European Commission can be held responsible for them.

Citation The users of this dataset are kindly asked to cite the following paper:Syed, D.A., Quadrini, W., Rahmani Choubeh, N., Pinzone, M., Gusmeroli, S. (2025). Approaching Interoperability and Data-Related Processing Issues in a Human-Centric Industrial Scenario. In: Presser, M., Skarmeta, A., Krco, S., González Vidal, A. (eds) Global Internet of Things and Edge Computing Summit. GIECS 2024. Communications in Computer and Information Science, vol 2328. Springer, Cham. https://doi.org/10.1007/978-3-031-78572-6_2
DOI: 10.5281/zenodo.18021958
title: 6 channel raw sEMG signal recorded from biceps, triceps and trapezius during manual assembly operation (Standing)

description: DescriptionThe dataset contains raw surface EMG signals recorded during a repeated assembly task. This dataset was recorded while standing therefore the arms are unsupported putting additional strain on the operator.Signal DescriptionThe signal consists of 6 sEMG channels from biceps(Channel 2 and 3), triceps(Channel 4 and 5) and Upper Trapezeus Channel 6 and 7) muscles. Each sensor channel records at a frequency of 1000Hz. All 6 channels are synchronised. 

Data FormatData is  in the from of a list of JSON payloads each consisting of 200 data points each. Minimum Recomended data processing proceduresPre-Preperation --> Convert from JSON to DataFrameBand pass filter --> 20 - 450 HzNotch filter --> 50Hz (Power line frequency)





Acknowledgement



This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No's 101093069 (P2CODE) and 101120657(ENFIELD). Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commission. Neither the European Union nor the European Commission can be held responsible for them.

Citation The users of this dataset are kindly asked to cite the following paper:Syed, D.A., Quadrini, W., Rahmani Choubeh, N., Pinzone, M., Gusmeroli, S. (2025). Approaching Interoperability and Data-Related Processing Issues in a Human-Centric Industrial Scenario. In: Presser, M., Skarmeta, A., Krco, S., González Vidal, A. (eds) Global Internet of Things and Edge Computing Summit. GIECS 2024. Communications in Computer and Information Science, vol 2328. Springer, Cham. https://doi.org/10.1007/978-3-031-78572-6_2
DOI: 10.6084/m9.figshare.31315798
title: STRML

description: Salt tolerance phenotype prediction in rice
DOI: 10.6084/m9.figshare.31315798.v1
title: STRML

description: Salt tolerance phenotype prediction in rice
DOI: 10.25345/c51c1tv7h
title: MassIVE MSV000100802 - Proteomic insights on the bioactivity of Protium heptaphyllum essential oil against Moniliophthora perniciosa from cocoa plants
title: This research aims to evaluate the antifungal potential of amescla (Protium heptaphyllum) essential oils and assess protein modulation through the identification of differentially abundant proteins in the mycelium of M. perniciosa treated with amescla essential oil. Furthermore, it seeks to establish the functional organization of proteins in the mycelium of M. perniciosa treated with amescla essential oil within a protein-protein interaction network.
DOI: 10.6084/m9.figshare.31315579
title: PM2.5 and meteorological data

description: Mobile phase PM2.5 measurements and meteorological parameters collected in Lahore, Pakistan from January 2022 to 15 December 2024 for air quality forecasting study
DOI: 10.6084/m9.figshare.31315579.v1
title: PM2.5 and meteorological data

description: Mobile phase PM2.5 measurements and meteorological parameters collected in Lahore, Pakistan from January 2022 to 15 December 2024 for air quality forecasting study
DOI: 10.5281/zenodo.18497181
title: Exploratory EcoliBert and EcolimRNA-FM Dataset for Translation-Prophet Comparisons
DOI: 10.5281/zenodo.18497182
title: Exploratory EcoliBert and EcolimRNA-FM Dataset for Translation-Prophet Comparisons
DOI: 10.15468/dl.hbphcx
title: Occurrence Download

description: A dataset containing 185 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Apochloa euprepes",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 185 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008693-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29106902
title: Data_Fig.S5.xlsx

description: In quantum networks, after passing through noisy channels or information processing, residual states may lack sufficient entanglement for further tasks, yet they may retain hidden quantum resources that can be recycled. Efficiently recycling these states to extract entanglement resources such as genuine multipartite entanglement or Einstein-Podolsky-Rosen pairs is essential for optimizing network performance. Here, we develop a tripartite entanglement distillation scheme using an eight-photon quantum platform, demonstrating entanglement superactivation phenomena which are unique to multipartite systems. We successfully generate a three-photon genuinely entangled state from two bi-separable states via local operations and classical communication, demonstrating superactivation of genuine multipartite entanglement.Furthermore, we extend our scheme to generate a three-photon state capable of extracting an Einstein-Podolsky-Rosen pair from two initial states lacking this capability, revealing a previously unobserved entanglement superactivation phenomenon. Our methods and findings offer not only practical applications for quantum networks, but also lead to a deeper understanding of multipartite entanglement structures.
DOI: 10.6084/m9.figshare.29106902.v1
title: Data_Fig.S5.xlsx

description: In quantum networks, after passing through noisy channels or information processing, residual states may lack sufficient entanglement for further tasks, yet they may retain hidden quantum resources that can be recycled. Efficiently recycling these states to extract entanglement resources such as genuine multipartite entanglement or Einstein-Podolsky-Rosen pairs is essential for optimizing network performance. Here, we develop a tripartite entanglement distillation scheme using an eight-photon quantum platform, demonstrating entanglement superactivation phenomena which are unique to multipartite systems. We successfully generate a three-photon genuinely entangled state from two bi-separable states via local operations and classical communication, demonstrating superactivation of genuine multipartite entanglement.Furthermore, we extend our scheme to generate a three-photon state capable of extracting an Einstein-Podolsky-Rosen pair from two initial states lacking this capability, revealing a previously unobserved entanglement superactivation phenomenon. Our methods and findings offer not only practical applications for quantum networks, but also lead to a deeper understanding of multipartite entanglement structures.
DOI: 10.5281/zenodo.18022570
title: 8 channel raw sEMG signal recorded from biceps, triceps, trapezius, brachioradialis while performing pushups till failure

description: DescriptionThe dataset contains 3 sets of raw surface EMG signals recorded while performing pushups. The participant performed pushups till he could no longer continue. The three recordings were performed in 3 seperate instances seperated by sufficient time to allow for recovery. the numbering 1,2,3 is in temporal orderSignal DescriptionThe signal consists of 8 sEMG channels from  Upper Trapezeus (Channel 0 and 1),  triceps (Channel 2 and 6 ),  Brachioradialis (Channel 3 and 4)  and biceps ( channel 5 and 7) muscles. Each sensor channel records at a frequency of 1000Hz. All 8 channels are synchronised. 

Data FormatData is  in the from of a list of JSON payloads each consisting of 200 data points each. Minimum Recomended data processing proceduresPre-Preperation --> Convert from JSON to DataFrameBand pass filter --> 20 - 450 HzNotch filter --> 50Hz (Power line frequency)





Acknowledgement



This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No's 101093069 (P2CODE) and 101120657(ENFIELD). Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commission. Neither the European Union nor the European Commission can be held responsible for them.

Citation The users of this dataset are kindly asked to cite the following paper:Syed, D.A., Quadrini, W., Rahmani Choubeh, N., Pinzone, M., Gusmeroli, S. (2025). Approaching Interoperability and Data-Related Processing Issues in a Human-Centric Industrial Scenario. In: Presser, M., Skarmeta, A., Krco, S., González Vidal, A. (eds) Global Internet of Things and Edge Computing Summit. GIECS 2024. Communications in Computer and Information Science, vol 2328. Springer, Cham. https://doi.org/10.1007/978-3-031-78572-6_2