cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10565496
title: KPSS Trend Stationary Files

description: KPSS Trend Stationary Files contain the comma delimited time series data file as well as all the raw stationarity test result files.
DOI: 10.5281/zenodo.10565497
title: KPSS Trend Stationary Files

description: KPSS Trend Stationary Files contain the comma delimited time series data file as well as all the raw stationarity test result files.
DOI: 10.5281/zenodo.10575711
title: Burke/Superior - REMs, Cross Sections, Lowest Elevation

description: Superior (sup) and Burke (bur) files. All data are zipped. Shapefiles included are cross sections and lowest elevation generated with REM tools. Superior's edited valleyline is included as well since this was used to generate these REMs. Additionally, Superior site has a smaller AOI included (shp and REM) which might be used to avoid massive elevation changes; these files are designated with "_smaller" suffix. The original Superio AOI REM is included as well. REMs (RelativeDEMs) are included for review: 2 for Superior (full AOI and smaller AOI) and 1 for Burke.
DOI: 10.5281/zenodo.10575712
title: Burke/Superior - REMs, Cross Sections, Lowest Elevation

description: Superior (sup) and Burke (bur) files. All data are zipped. Shapefiles included are cross sections and lowest elevation generated with REM tools. Superior's edited valleyline is included as well since this was used to generate these REMs. Additionally, Superior site has a smaller AOI included (shp and REM) which might be used to avoid massive elevation changes; these files are designated with "_smaller" suffix. The original Superio AOI REM is included as well. REMs (RelativeDEMs) are included for review: 2 for Superior (full AOI and smaller AOI) and 1 for Burke.
DOI: 10.5281/zenodo.10565491
title: KPSS Level Stationary Files

description: KPSS Level Stationary Files contain the comma delimited time series data file as well as all the raw stationarity test result files.
DOI: 10.5281/zenodo.10565492
title: KPSS Level Stationary Files

description: KPSS Level Stationary Files contain the comma delimited time series data file as well as all the raw stationarity test result files.
DOI: 10.5281/zenodo.10565480
title: Henon Files

description: Henon Data Files contain the comma delimited time series data file as well as all the raw stationarity test result files.
DOI: 10.5281/zenodo.10565481
title: Henon Files

description: Henon Data Files contain the comma delimited time series data file as well as all the raw stationarity test result files.
DOI: 10.5281/zenodo.10565468
title: Explosion 6 P Wave Files

description: Explosion 6 P Wave Files contain the comma delimited time series data file as well as all the raw stationarity test result files.
DOI: 10.5281/zenodo.10565469
title: Explosion 6 P Wave Files

description: Explosion 6 P Wave Files contain the comma delimited time series data file as well as all the raw stationarity test result files.
DOI: 10.5281/zenodo.10565336
title: Earthquake 5 P Wave Files

description: Earthquake 5 P Wave Files contain the comma delimited time series data file as well as all the raw stationarity test result files.
DOI: 10.5281/zenodo.10565337
title: Earthquake 5 P Wave Files

description: Earthquake 5 P Wave Files contain the comma delimited time series data file as well as all the raw stationarity test result files.
DOI: 10.25430/researchdata.cab.unipd.it.00001183
title: BISF (Brief Index of Sexual Functioning)

description: DATA base and descritpion
DOI: 10.34740/kaggle/dsv/7489435
title: FF | 2023 12 12 | Multi-Modal Dataset [3/6]
DOI: 10.5281/zenodo.10575732
title: Data archive for paper "Assessment of tropospheric ozone products from downscaled CAMS reanalysis and  CAMS daily forecast using urban air quality monitoring  stations in Iran"

description: This archive contains data to reproduce results as included in Kaffashzadeh and Aliakbari Bidokhti (2024).
DOI: 10.5281/zenodo.10575733
title: Data archive for paper "Assessment of tropospheric ozone products from downscaled CAMS reanalysis and  CAMS daily forecast using urban air quality monitoring  stations in Iran"

description: This archive contains data to reproduce results as included in Kaffashzadeh and Aliakbari Bidokhti (2024).
DOI: 10.34740/kaggle/dsv/7490484
title: FF | 2023 12 12 | Multi-Modal Dataset [4/6]
DOI: 10.5517/ccdc.csd.cc2h3xh1
title: CCDC 2297673: Experimental Crystal Structure Determination

description: Related Article: Brandon A. Wright, Alessio Regni, Nattawadee Chaisan, Richmond Sarpong|2024|J.Am.Chem.Soc.|146|1813|doi:10.1021/jacs.3c12953
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.cc2h3xj2
title: CCDC 2297674: Experimental Crystal Structure Determination

description: Related Article: Brandon A. Wright, Alessio Regni, Nattawadee Chaisan, Richmond Sarpong|2024|J.Am.Chem.Soc.|146|1813|doi:10.1021/jacs.3c12953
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.cc2h3xk3
title: CCDC 2297675: Experimental Crystal Structure Determination

description: Related Article: Brandon A. Wright, Alessio Regni, Nattawadee Chaisan, Richmond Sarpong|2024|J.Am.Chem.Soc.|146|1813|doi:10.1021/jacs.3c12953
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.cc2h3xl4
title: CCDC 2297676: Experimental Crystal Structure Determination

description: Related Article: Brandon A. Wright, Alessio Regni, Nattawadee Chaisan, Richmond Sarpong|2024|J.Am.Chem.Soc.|146|1813|doi:10.1021/jacs.3c12953
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.cc2h3xm5
title: CCDC 2297677: Experimental Crystal Structure Determination

description: Related Article: Brandon A. Wright, Alessio Regni, Nattawadee Chaisan, Richmond Sarpong|2024|J.Am.Chem.Soc.|146|1813|doi:10.1021/jacs.3c12953
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.cc2h3xn6
title: CCDC 2297678: Experimental Crystal Structure Determination

description: Related Article: Brandon A. Wright, Alessio Regni, Nattawadee Chaisan, Richmond Sarpong|2024|J.Am.Chem.Soc.|146|1813|doi:10.1021/jacs.3c12953
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.cc2hb68b
title: CCDC 2303711: Experimental Crystal Structure Determination

description: Related Article: Ali H. Alawadhi, Saumil Chheda, Gautam D. Stroscio, Zichao Rong, Daria Kurandina◇, Ha L. Nguyen, Nakul Rampal, Zhiling Zheng, Laura Gagliardi, Omar M. Yaghi|2024|J.Am.Chem.Soc.|146|2160|doi:10.1021/jacs.3c11947
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.cc2hdrqd
title: CCDC 2306174: Experimental Crystal Structure Determination

description: Related Article: Brandon A. Wright, Alessio Regni, Nattawadee Chaisan, Richmond Sarpong|2024|J.Am.Chem.Soc.|146|1813|doi:10.1021/jacs.3c12953
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: 10.25345/c58s4k09t
title: MassIVE MSV000093938 - GNPS_ S. rapamycin sample different medium 01.26.24
title: The bacterial strain was cultured in different mediums and looked for new metabolite identification through GNPS analysis.
DOI: 10.25345/c5542jk6b
title: MassIVE MSV000093939 - GNPS of Streptomyces lactacystin strain for the metabolite identification 01.26.24
title: The bacterial strain was cultured in different medium and looking for the new metabolite identification through GNPS analysis.
DOI: 10.25345/c51c1ts3p
title: MassIVE MSV000093940 - GNPS CNQ samples for GNPS analysis
title: The biosynthetic gene cluster was cultured and expressed to see the metabolite profiling in GNPS analysis.
DOI: 10.5281/zenodo.10575672
title: YUTO MMS Dataset, Sequence C, Images, Part3
DOI: 10.5281/zenodo.10575673
title: YUTO MMS Dataset, Sequence C, Images, Part3
DOI: 10.5281/zenodo.10575676
title: YUTO MMS Dataset, Sequence C, Images, Part4
DOI: 10.5281/zenodo.10575677
title: YUTO MMS Dataset, Sequence C, Images, Part4
DOI: 10.5281/zenodo.10575289
title: Dataset for the paper: Temporal true and surrogate fitness landscape analysis for expensive bi-objective optimisation

description: Fitness landscape analysis can provide valuable insight about key characteristics of a problem. Many real-world problems have expensive-to-compute fitness functions and are multi-objective in nature. Surrogate-assisted evolutionary algorithms are often used to tackle such problems. Despite this, literature about analysing the fitness landscapes induced by surrogate models is limited, and even non-existent for multi-objective problems. This study addresses this critical gap by comparing landscapes of the real fitness function with those of surrogate models for multi-objective functions. Moreover, it does so temporally by examining landscape features at different points in time during optimisation, in the vicinity of the population at that point in time. We consider the well-known BBOB bi-objective benchmark functions in our experiments and employ a reference-vector guided surrogate-assisted evolutionary algorithm. The results of the landscape analysis on the real fitness landscape reveal significant distinctions between features at different time points during optimisation, and between real and surrogate landscape features. Furthermore, the study demonstrates that both surrogate and real landscape features are of importance when predicting algorithm performance, and that the outcome of an algorithm can be forecast to a decent standard by sampling these during evolution. The results could help to facilitate the design of surrogate switching approaches to improve performance in multi-objective optimisation.  

This dataset contains data for static fitness landscape analyses as well as temporal analyses, focusing on five different surrogates: IDW, IDWR, KNN, LR-KNN, and No-Struct. The dataset comprises six ZIP files in total.

## Folder Descriptions

- idw/: Data related to the temporal analysis using the IDW surrogate.- idwr/: Data related to the temporal analysis using the IDWR surrogate.- knn/: Data related to the temporal analysis using the KNN surrogate.- lr-knn/: Data related the temporal analysis using to the LR-KNN surrogate.- no-struct/: Data related the temporal analysis using to the No-Struct surrogate.- static/: Data related to the static analysis.

## Contents per folder

Each analysis is structured into three main folders:

- Samples: Contains all the solutions for true and surrogate fitness landscape feature extraction,  including the performance metric.- Features: Contains all the true and surrogate features for each repeat of the BBOB-BIOBJ problem.- Performance: Contains all the performance (hv) for each repeat of the BBOB-BIOBJ problem.
DOI: 10.5281/zenodo.10575290
title: Dataset for the paper: Temporal true and surrogate fitness landscape analysis for expensive bi-objective optimisation

description: Fitness landscape analysis can provide valuable insight about key characteristics of a problem. Many real-world problems have expensive-to-compute fitness functions and are multi-objective in nature. Surrogate-assisted evolutionary algorithms are often used to tackle such problems. Despite this, literature about analysing the fitness landscapes induced by surrogate models is limited, and even non-existent for multi-objective problems. This study addresses this critical gap by comparing landscapes of the real fitness function with those of surrogate models for multi-objective functions. Moreover, it does so temporally by examining landscape features at different points in time during optimisation, in the vicinity of the population at that point in time. We consider the well-known BBOB bi-objective benchmark functions in our experiments and employ a reference-vector guided surrogate-assisted evolutionary algorithm. The results of the landscape analysis on the real fitness landscape reveal significant distinctions between features at different time points during optimisation, and between real and surrogate landscape features. Furthermore, the study demonstrates that both surrogate and real landscape features are of importance when predicting algorithm performance, and that the outcome of an algorithm can be forecast to a decent standard by sampling these during evolution. The results could help to facilitate the design of surrogate switching approaches to improve performance in multi-objective optimisation.  

This dataset contains data for static fitness landscape analyses as well as temporal analyses, focusing on five different surrogates: IDW, IDWR, KNN, LR-KNN, and No-Struct. The dataset comprises six ZIP files in total.

## Folder Descriptions

- idw/: Data related to the temporal analysis using the IDW surrogate.- idwr/: Data related to the temporal analysis using the IDWR surrogate.- knn/: Data related to the temporal analysis using the KNN surrogate.- lr-knn/: Data related the temporal analysis using to the LR-KNN surrogate.- no-struct/: Data related the temporal analysis using to the No-Struct surrogate.- static/: Data related to the static analysis.

## Contents per folder

Each analysis is structured into three main folders:

- Samples: Contains all the solutions for true and surrogate fitness landscape feature extraction,  including the performance metric.- Features: Contains all the true and surrogate features for each repeat of the BBOB-BIOBJ problem.- Performance: Contains all the performance (hv) for each repeat of the BBOB-BIOBJ problem.
DOI: 10.6084/m9.figshare.25076150
title: IFN SCC Horse Data

description: A study determining the utility of perilesional IFN treatment for equine periocular squamous cell carcinoma.
DOI: 10.6084/m9.figshare.25076150.v1
title: IFN SCC Horse Data

description: A study determining the utility of perilesional IFN treatment for equine periocular squamous cell carcinoma.
DOI: 10.34740/kaggle/dsv/7493603
title: Full TMDb TV Shows Dataset 2024 (150K Shows)
DOI: 10.5517/ccdc.csd.cc2hxw9m
title: CCDC 2321661: Experimental Crystal Structure Determination

description: Related Article: Jiahao Zhao, Jiajun Chang, Shangyu Li, Yajie Chou，Zhenjie Ni, Hanlin Wang|2024|CSD Communication|||
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: 10.34740/kaggle/dsv/7488228
title: Full TMDB Movies Dataset 2024 (985K Movies)
DOI: 10.6084/m9.figshare.25093676
title: Supplementary files

description: Supplementary files
DOI: 10.6084/m9.figshare.25093676.v1
title: Supplementary files

description: Supplementary files
DOI: 10.25345/c5wm1449z
title: MassIVE MSV000093941 - PFAS in Dried Blood Spots acquired on 6546 from US Population 2000s
title: PFAS in DBS from 2000s from a population in Berkley, CA, USA, run in DDA mode.
DOI: 10.34740/kaggle/dsv/7493570
title: FF | 2023 12 12 | Multi-Modal Dataset [5/6]
DOI: 10.6084/m9.figshare.25093703
title: PostAI_Stroke

description: This sheet has the data and time stamps for patients with acute stroke in the post AI period.
DOI: 10.6084/m9.figshare.25093703.v1
title: PostAI_Stroke

description: This sheet has the data and time stamps for patients with acute stroke in the post AI period.
DOI: 10.6084/m9.figshare.25093733
title: AI_scores_Dx accuracy

description: This sheet has the scores generated by AI for each of the target findings.
DOI: 10.6084/m9.figshare.25093733.v1
title: AI_scores_Dx accuracy

description: This sheet has the scores generated by AI for each of the target findings.
DOI: 10.6084/m9.figshare.25093709
title: Radioreports_coded_Dxaccuracy

description: This sheet has the radiologists' reports coded for presence or absence of each target findings.
DOI: 10.6084/m9.figshare.25093697
title: PreAI_Stroke

description: This data sheet has data on time stamps and other variables for acute stroke patients from the 3 months before AI deployment.
DOI: 10.7910/dvn/uwo6ty
title: Replication Data for: Banning Products with Low Energy Efficiency: Market Response and Adjustment Cost

description: Code and programs for the empirical analysis of regulation that banned washing mashines with a low Energy Efficiency Index from EU market for appliances.
DOI: 10.5519/qd.e7jmd5ah
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (49 records)
DOI: 10.5517/ccdc.csd.cc2j3vgz
title: CCDC 2327401: Experimental Crystal Structure Determination

description: Related Article: Fang Changzhen|2024|CSD Communication|||
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: 10.5519/qd.rzm6h36y
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (883 records)
DOI: 10.5281/zenodo.10292581
title: CoqPyt: Proof Navigation in Python in the Era of LLMs

description: Replication package with code and CompCert dataset accompanying the paper "CoqPyt: Proof Navigation in Python in the Era of LLMs".The file provided here is a Docker image. To use it, follow the steps:
 
1. docker load < coqpyt.tar
2. docker run -it --name coqpyt -d coqpyt /bin/bash
3. docker attach coqpyt 
After these steps, see the README.
DOI: 10.5281/zenodo.10576042
title: CoqPyt: Proof Navigation in Python in the Era of LLMs

description: Replication package with code and CompCert dataset accompanying the paper "CoqPyt: Proof Navigation in Python in the Era of LLMs".The file provided here is a Docker image. To use it, follow the steps:
 
1. docker load < coqpyt.tar
2. docker run -it --name coqpyt -d coqpyt /bin/bash
3. docker attach coqpyt 
After these steps, see the README.
DOI: 10.5519/qd.y2io4b5l
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1669 records)
DOI: 10.25345/c5rv0db5t
title: MassIVE MSV000093942 - European River Monitoring Study
title: River water collected across 31 European countries with 45 participating research laboratories. Between 3 to 16 rivers and creeks sampled in each country during the spring period March-April 2023. The 302 samples were frozen and shipped for nontarget analysis at Aarhus University, Denmark. River water samples were cleaned and enriched 30 times using hydrophilic-lipophillic balanced (HLB) solid-phase extraction and analyzed using nanoLC-nanoelectrospray-HRMS/MS.
DOI: 10.6084/m9.figshare.25093790
title: Raw Data for: Photochromic webbing structures for monitoring UV-induced mechanical strength degradation

description: This dataset contains the colorimetric measurements of the photochromic webbing structures acquired in the true-color image acquisition chamber using a Nikon D5600 camera. Data acquired on different hours/days following the onset of the QUV experiment are saved in different subfolders, with the subfolder name corresponding to the duration of UV irradiation.
DOI: 10.6084/m9.figshare.25093790.v1
title: Raw Data for: Photochromic webbing structures for monitoring UV-induced mechanical strength degradation

description: This dataset contains the colorimetric measurements of the photochromic webbing structures acquired in the true-color image acquisition chamber using a Nikon D5600 camera. Data acquired on different hours/days following the onset of the QUV experiment are saved in different subfolders, with the subfolder name corresponding to the duration of UV irradiation.
DOI: 10.5281/zenodo.10576081
title: Dataset and videos for the hydraulic fracturing tests using the transparent true triaxial cell developed at Los Alamos National Laboratory

description: This upload includes the dataset (boundary stresses, injection rate, injection pressure) and experiment video recordings of the hydraulic fracturing tests using the transparent true triaxial cell developed at Los Alamos National Laboratory. The dataset is intended to support journal pulications to document our recent findings which demonstrate hydraulic fractures can curve and branch in homogeneous porous rocks under 3D stress conditions.
DOI: 10.5281/zenodo.10576158
title: Data for Scanning Nitrogen-Vacancy Magnetometry of Focused-Electron-Beam-Deposited Cobalt Nanomagnets

description: Data for Scanning Nitrogen-Vacancy Magnetometry of Focused-Electron-Beam-Deposited Cobalt Nanomagnets
DOI: 10.5281/zenodo.10576159
title: Data for Scanning Nitrogen-Vacancy Magnetometry of Focused-Electron-Beam-Deposited Cobalt Nanomagnets

description: Data for Scanning Nitrogen-Vacancy Magnetometry of Focused-Electron-Beam-Deposited Cobalt Nanomagnets
DOI: 10.5281/zenodo.10569816
title: How Professionals Rank Specification Strategies Confronting Utility and Usability
DOI: 10.5281/zenodo.10569817
title: How Professionals Rank Specification Strategies Confronting Utility and Usability
DOI: 10.5281/zenodo.10576213
title: NAR_data
DOI: 10.5281/zenodo.10576214
title: NAR_data