cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e242311v1
title: Emmanuel Alayande University of Education 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542

description: Emmanuel Alayande University of Education 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542
DOI: 10.3886/e242312v1
title: Kogi State University, Kabba 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542

description: Kogi State University, Kabba 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542
DOI: 10.3886/e242313v1
title: AbdulKadir Kure University 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542

description: AbdulKadir Kure University 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542
DOI: 10.3886/e242314v1
title: Benue State University of Agriculture Science and Technology 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542

description: Benue State University of Agriculture Science and Technology 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542
DOI: 10.3886/e242315v1
title: Abubakar Tafawa Balewa University 2026/2027 Diploma Form, Direct-Entry Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542

description: Abubakar Tafawa Balewa University 2026/2027 Diploma Form, Direct-Entry Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542
DOI: 10.3886/e242306v1
title: Lagos State University of Science and Technology 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542

description: Lagos State University of Science and Technology 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542
DOI: 10.3886/e242307v1
title: Lagos State University of Education 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542

description: Lagos State University of Education 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542
DOI: 10.3886/e242305v1
title: Imo State University of Agriculture and Environmental Sciences 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542

description: Imo State University of Agriculture and Environmental Sciences 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542
DOI: 10.3886/e242308v1
title: Shehu Shagari University of Education 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542

description: Shehu Shagari University of Education 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542
DOI: 10.3886/e242304v1
title: Bamidele Olumilua University of Science and Technology Ikere 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542

description: Bamidele Olumilua University of Science and Technology Ikere 2026/2027 Pre-Degree Form, Part-time Form Is Out Call 07076040542 To Apply and further admission assistance. Call Prof. Ben +2347076040542
DOI: 10.5281/zenodo.18022714
title: A Normalized Incremental Divergence Functional for Instability Onset in Representative Nonlinear Systems

description:  

This repository contains supplementary data and code for the manuscript titled "

A Normalized Incremental Divergence Functional for Instability

Onset in Representative Nonlinear Systems

"

 

Files include: CSV output from the main test, Python scripts for all 8 tests, and figures referenced in the Results section of the manuscript.
description: This repository contains Python code, output CSV, and figure supporting "

A Normalized Incremental Divergence Functional for Instability

Onset in Representative Nonlinear Systems

"All variables and methods are described in the main manuscript.
DOI: 10.5281/zenodo.18109306
title: A Normalized Incremental Divergence Functional for Instability Onset in Representative Nonlinear Systems

description:  

This repository contains supplementary data and code for the manuscript titled "

A Normalized Incremental Divergence Functional for Instability

Onset in Representative Nonlinear Systems

"

 

Files include: CSV output from the main test, Python scripts for all 8 tests, and figures referenced in the Results section of the manuscript.
description: This repository contains Python code, output CSV, and figure supporting "

A Normalized Incremental Divergence Functional for Instability

Onset in Representative Nonlinear Systems

"All variables and methods are described in the main manuscript.
DOI: 10.17632/fjfc23mmx2.1
title: QTNano - Unveiling the impact of organic cation passivation on structural and optoelectronic properties of two-dimensional perovskites thin films, Applied Surface Science, 678, 161098 (2024)

description: Raw data of the published paper - https://doi.org/10.1016/j.apsusc.2024.161098
DOI: 10.5281/zenodo.14907324
title: AI Adoption Survey (Responses)

description:  This dataset provides the raw, individual‐level answers for Questions 1–12 from the survey, with all personally identifying information removed to protect respondent confidentiality. Each record reflects a single participant’s responses, allowing researchers to conduct secondary analyses while ensuring privacy and adherence to ethical guidelines.
DOI: 10.5281/zenodo.14907325
title: AI Adoption Survey (Responses)

description:  This dataset provides the raw, individual‐level answers for Questions 1–12 from the survey, with all personally identifying information removed to protect respondent confidentiality. Each record reflects a single participant’s responses, allowing researchers to conduct secondary analyses while ensuring privacy and adherence to ethical guidelines.
DOI: 10.15468/dl.yx8yxn
title: Occurrence Download

description: A dataset containing 7389 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Opheodrys vernalis (Harlan, 1827)"
 ]
}

 The dataset includes 7389 records from 80 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000555-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14907322
title: Assessment of economic efficiency
DOI: 10.5281/zenodo.14907323
title: Assessment of economic efficiency
DOI: 10.5281/zenodo.14809924
title: Replication Package for "SeBS-Flow: Benchmarking Serverless Cloud Function Workflows"

description: This artifact contains the implementation of SeBS-Flow, data, and analysis scripts. We provide the following components:



sebs-flow-artifact: Benchmarking results obtained for the paper together with Python plotting and analysis scripts used for data analysis. See separate README. 

sebs-flow-implementation: We provide the implementation of SeBS-Flow integrated within the serverless benchmarking suite SeBS. To setup SeBS, please refer to information given in the original README inside the implementation folder. Our workflow benchmarks are provided in the benchmarks folder (`benchmarks/600.workflows`). Please refer to `docs/workflows.md` regarding the required setup for workflow execution. 


We obtained the results presented in the paper using the `perf-cost` experiment. To execute the experiment, set the desired properties in the config json and execute the following command:

./sebs.py experiment invoke perf-cost --config {path/to/config.json} --workflow True --output-dir {path/to/output-dir} --verbose

We provide the configurations used for execution of the benchmarks as in the paper for each platform as part of the artifact (`sebs-flow-artifact/benchmark-configs`).
DOI: 10.5281/zenodo.14809925
title: Replication Package for "SeBS-Flow: Benchmarking Serverless Cloud Function Workflows"

description: This artifact contains the implementation of SeBS-Flow, data, and analysis scripts. We provide the following components:



sebs-flow-artifact: Benchmarking results obtained for the paper together with Python plotting and analysis scripts used for data analysis. See separate README. 

sebs-flow-implementation: We provide the implementation of SeBS-Flow integrated within the serverless benchmarking suite SeBS. To setup SeBS, please refer to information given in the original README inside the implementation folder. Our workflow benchmarks are provided in the benchmarks folder (`benchmarks/600.workflows`). Please refer to `docs/workflows.md` regarding the required setup for workflow execution. 


We obtained the results presented in the paper using the `perf-cost` experiment. To execute the experiment, set the desired properties in the config json and execute the following command:

./sebs.py experiment invoke perf-cost --config {path/to/config.json} --workflow True --output-dir {path/to/output-dir} --verbose

We provide the configurations used for execution of the benchmarks as in the paper for each platform as part of the artifact (`sebs-flow-artifact/benchmark-configs`).
DOI: 10.5281/zenodo.14810035
title: Replication Package for "SeBS-Flow: Benchmarking Serverless Cloud Function Workflows"

description: This artifact contains the implementation of SeBS-Flow, data, and analysis scripts. We provide the following components:



sebs-flow-artifact: Benchmarking results obtained for the paper together with Python plotting and analysis scripts used for data analysis. See separate README. 

sebs-flow-implementation: We provide the implementation of SeBS-Flow integrated within the serverless benchmarking suite SeBS. To setup SeBS, please refer to information given in the original README inside the implementation folder. Our workflow benchmarks are provided in the benchmarks folder (`benchmarks/600.workflows`). Please refer to `docs/workflows.md` regarding the required setup for workflow execution. 


We obtained the results presented in the paper using the `perf-cost` experiment. To execute the experiment, set the desired properties in the config json and execute the following command:

./sebs.py experiment invoke perf-cost --config {path/to/config.json} --workflow True --output-dir {path/to/output-dir} --verbose

We provide the configurations used for execution of the benchmarks as in the paper for each platform as part of the artifact (`sebs-flow-artifact/benchmark-configs`).
DOI: 10.5281/zenodo.14851707
title: Replication Package for "SeBS-Flow: Benchmarking Serverless Cloud Function Workflows"

description: This artifact contains the implementation of SeBS-Flow, data, and analysis scripts. We provide the following components:



sebs-flow-artifact: Benchmarking results obtained for the paper together with Python plotting and analysis scripts used for data analysis. See separate README. 

sebs-flow-implementation: We provide the implementation of SeBS-Flow integrated within the serverless benchmarking suite SeBS. To setup SeBS, please refer to information given in the original README inside the implementation folder. Our workflow benchmarks are provided in the benchmarks folder (`benchmarks/600.workflows`). Please refer to `docs/workflows.md` regarding the required setup for workflow execution. 


We obtained the results presented in the paper using the `perf-cost` experiment. To execute the experiment, set the desired properties in the config json and execute the following command:

./sebs.py experiment invoke perf-cost --config {path/to/config.json} --workflow True --output-dir {path/to/output-dir} --verbose

We provide the configurations used for execution of the benchmarks as in the paper for each platform as part of the artifact (`sebs-flow-artifact/benchmark-configs`).
DOI: 10.5281/zenodo.14858804
title: Replication Package for "SeBS-Flow: Benchmarking Serverless Cloud Function Workflows"

description: This artifact contains the implementation of SeBS-Flow, data, and analysis scripts. We provide the following components:



sebs-flow-artifact: Benchmarking results obtained for the paper together with Python plotting and analysis scripts used for data analysis. See separate README. 

sebs-flow-implementation: We provide the implementation of SeBS-Flow integrated within the serverless benchmarking suite SeBS. To setup SeBS, please refer to information given in the original README inside the implementation folder. Our workflow benchmarks are provided in the benchmarks folder (`benchmarks/600.workflows`). Please refer to `docs/workflows.md` regarding the required setup for workflow execution. 


We obtained the results presented in the paper using the `perf-cost` experiment. To execute the experiment, set the desired properties in the config json and execute the following command:

./sebs.py experiment invoke perf-cost --config {path/to/config.json} --workflow True --output-dir {path/to/output-dir} --verbose

We provide the configurations used for execution of the benchmarks as in the paper for each platform as part of the artifact (`sebs-flow-artifact/benchmark-configs`).
DOI: 10.5281/zenodo.14872056
title: Replication Package for "SeBS-Flow: Benchmarking Serverless Cloud Function Workflows"

description: This artifact contains the implementation of SeBS-Flow, data, and analysis scripts. We provide the following components:



sebs-flow-artifact: Benchmarking results obtained for the paper together with Python plotting and analysis scripts used for data analysis. See separate README. 

sebs-flow-implementation: We provide the implementation of SeBS-Flow integrated within the serverless benchmarking suite SeBS. To setup SeBS, please refer to information given in the original README inside the implementation folder. Our workflow benchmarks are provided in the benchmarks folder (`benchmarks/600.workflows`). Please refer to `docs/workflows.md` regarding the required setup for workflow execution. 


We obtained the results presented in the paper using the `perf-cost` experiment. To execute the experiment, set the desired properties in the config json and execute the following command:

./sebs.py experiment invoke perf-cost --config {path/to/config.json} --workflow True --output-dir {path/to/output-dir} --verbose

We provide the configurations used for execution of the benchmarks as in the paper for each platform as part of the artifact (`sebs-flow-artifact/benchmark-configs`).
DOI: 10.5281/zenodo.14888559
title: Replication Package for "SeBS-Flow: Benchmarking Serverless Cloud Function Workflows"

description: This artifact contains the implementation of SeBS-Flow, data, and analysis scripts. We provide the following components:



sebs-flow-artifact: Benchmarking results obtained for the paper together with Python plotting and analysis scripts used for data analysis. See separate README. 

sebs-flow-implementation: We provide the implementation of SeBS-Flow integrated within the serverless benchmarking suite SeBS. To setup SeBS, please refer to information given in the original README inside the implementation folder. Our workflow benchmarks are provided in the benchmarks folder (`benchmarks/600.workflows`). Please refer to `docs/workflows.md` regarding the required setup for workflow execution. 


We obtained the results presented in the paper using the `perf-cost` experiment. To execute the experiment, set the desired properties in the config json and execute the following command:

./sebs.py experiment invoke perf-cost --config {path/to/config.json} --workflow True --output-dir {path/to/output-dir} --verbose

We provide the configurations used for execution of the benchmarks as in the paper for each platform as part of the artifact (`sebs-flow-artifact/benchmark-configs`).
DOI: 10.5281/zenodo.14907321
title: Replication Package for "SeBS-Flow: Benchmarking Serverless Cloud Function Workflows"

description: This artifact contains the implementation of SeBS-Flow, data, and analysis scripts. We provide the following components:



sebs-flow-artifact: Benchmarking results obtained for the paper together with Python plotting and analysis scripts used for data analysis. See separate README. 

sebs-flow-implementation: We provide the implementation of SeBS-Flow integrated within the serverless benchmarking suite SeBS. To setup SeBS, please refer to information given in the original README inside the implementation folder. Our workflow benchmarks are provided in the benchmarks folder (`benchmarks/600.workflows`). Please refer to `docs/workflows.md` regarding the required setup for workflow execution. 


We obtained the results presented in the paper using the `perf-cost` experiment. To execute the experiment, set the desired properties in the config json and execute the following command:

./sebs.py experiment invoke perf-cost --config {path/to/config.json} --workflow True --output-dir {path/to/output-dir} --verbose

We provide the configurations used for execution of the benchmarks as in the paper for each platform as part of the artifact (`sebs-flow-artifact/benchmark-configs`).
DOI: 10.15468/dl.e3v26k
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is Italy",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Coscinodon cribrosus (Hedw.) Spruce"
 ]
}

 The dataset includes 14 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000556-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14907294
title: AMPERE Summary Plot Movies (2020-Jun)

description: 2020-Jun AMPERE summary plot movies. See included zenodo_summary_plot_movie_description document for details.
DOI: 10.5281/zenodo.14907295
title: AMPERE Summary Plot Movies (2020-Jun)

description: 2020-Jun AMPERE summary plot movies. See included zenodo_summary_plot_movie_description document for details.
DOI: 10.15468/dl.7kvck5
title: Occurrence Download

description: A dataset containing 449 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "GadmGid is COL.25_2",
 "TaxonKey is Chiroptera",
 "Year 2000-2025"
 ]
}

 The dataset includes 449 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000557-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14907347
title: SmartPLS Analysis Report

description: This repository includes an Excel file containing the fully cleaned dataset used in our analyses, along with essential PLS‐SEM outputs such as path coefficients, bootstrapping results, and model fit indicators. Researchers can replicate or extend the study’s structural equation modeling steps with the provided data and outputs.
DOI: 10.5281/zenodo.14907348
title: SmartPLS Analysis Report

description: This repository includes an Excel file containing the fully cleaned dataset used in our analyses, along with essential PLS‐SEM outputs such as path coefficients, bootstrapping results, and model fit indicators. Researchers can replicate or extend the study’s structural equation modeling steps with the provided data and outputs.
DOI: 10.5517/ccdc.csd.cc28wwjl
title: CCDC 2112170: Experimental Crystal Structure Determination

description: Related Article: Fatma M. Elantabli, Samir M. El-Medani, Abdulaziz Al-Anazi, Mohamed R. Shehata, Matti Haukka, Rania G. Mohamed|2025|J.Mol.Struct.|1330|141511|doi:10.1016/j.molstruc.2025.141511
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fkprg
title: CCDC 2251336: Experimental Crystal Structure Determination

description: Related Article: Fei Liu, Qin Li, Yongqi Li, Hong Liao, Weiguang Sun, Jianguo Li, Chunmei Chen, Yonghui Zhang, Hucheng Zhu|2025|Phytochemistry|233|114414|doi:10.1016/j.phytochem.2025.114414
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fkpsh
title: CCDC 2251337: Experimental Crystal Structure Determination

description: Related Article: Fei Liu, Qin Li, Yongqi Li, Hong Liao, Weiguang Sun, Jianguo Li, Chunmei Chen, Yonghui Zhang, Hucheng Zhu|2025|Phytochemistry|233|114414|doi:10.1016/j.phytochem.2025.114414
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2kcztr
title: CCDC 2365015: Experimental Crystal Structure Determination

description: Related Article: Zhen Jiang, Qiyin Chen, Chao Shi, Jie Su, Feiyang Li, Kaishun Ye, Zhigang Zhao, Qiuxia Li, Aihua Yuan, Guohua Xie|2025|Dyes Pigm.|236|112681|doi:10.1016/j.dyepig.2025.112681
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2kxkhk
title: CCDC 2380939: Experimental Crystal Structure Determination

description: Related Article: Connor S. Durfy, Michelle Huang, Joseph A. Zurakowski, Paul D. Boyle, Marcus W. Drover|2025|Chem.Commun.|61|3323|doi:10.1039/D4CC06176D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2kxkjl
title: CCDC 2380940: Experimental Crystal Structure Determination

description: Related Article: Connor S. Durfy, Michelle Huang, Joseph A. Zurakowski, Paul D. Boyle, Marcus W. Drover|2025|Chem.Commun.|61|3323|doi:10.1039/D4CC06176D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.