cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24006048
title: Apatite (U-Th)/He thermochronology data

description: Apatite (U-Th)/He thermochronology data, measured from Senonian sandstone grains
DOI: 10.6084/m9.figshare.24005997
title: K/Ar age data from fault gauge samples

description: K/Ar age data from fault gauge samples collected from the shear zone of the Nekézseny Thrust
DOI: 10.6084/m9.figshare.24005997.v1
title: K/Ar age data from fault gauge samples

description: K/Ar age data from fault gauge samples collected from the shear zone of the Nekézseny Thrust
DOI: 10.5281/zenodo.10101651
title: Data and R-Code from: How to account for behavioral states in step-selection analysis: a model comparison

description: This repository provides the R-code and data used for the simulation and case study of the research paper: "How to account for behavioral states in step-selection analysis: a model comparison".
The folder "Pohle_et_al_2023_BehavioralStates_iSSA_Data" contains the landscape rasters used for data generation in the simulation study, and the bank vole (Myodes glareolus) movement data used in the case study on bank vole interactions:

landscape10.RData and landscape50.RData: Landscape rasters for the simulation study.
Vole_case_control.rds: Case-control bank vole data for the case study.
Info_replicates.rds: Information about bank vole indiviuals and corresponding replicates for the case study.
Codebook_case_study.xlsx: Codebook for the case study data sets.
Read_me.txt
The folder "Pohle_et_al_2023_BehavioralStates_iSSA_RCode" contains the R-scripts for the simulation and case study:

Functions.R: Functions to apply HMMs, TS-iSSAs, and HMM-iSSAs to movement data; used for the simulation and case study.
Simulation_study.R: R-Code to run the simulation study. Parallel computation is used.
Results_simulation_study.R: R-Code to create the result figures and tables for the simulation study.
Case_study.R: R-Code to run the bank vole interaction case study. Parallel computation is used.
Results_case_study.R: R-Code to create the result figures and tables for the case study.
Read_me.txt
Besides the simulation and case study from the paper, the included functions (Functions.R) can generally be used to perform an HMM-iSSA analysis.
For the bank vole movement data without control locations, see: Schlägel, U.E. et al. (2019). Data from: Estimating interactions between individuals from concurrent animal movements [Dataset]. Dryad. https://doi.org/10.5061/dryad.rt535m8.
Acknowledgements
We thank Sophie Eden, Angela Puschmann and Pauline Lange for help with the bank vole data collection and maintenance of the outdoor enclosures.
DOI: 10.5281/zenodo.10101650
title: Data and R-Code from: How to account for behavioral states in step-selection analysis: a model comparison

description: This repository provides the R-code and data used for the simulation and case study of the research paper: "How to account for behavioral states in step-selection analysis: a model comparison".
The folder "Pohle_et_al_2023_BehavioralStates_iSSA_Data" contains the landscape rasters used for data generation in the simulation study, and the bank vole (Myodes glareolus) movement data used in the case study on bank vole interactions:

landscape10.RData and landscape50.RData: Landscape rasters for the simulation study.
Vole_case_control.rds: Case-control bank vole data for the case study.
Info_replicates.rds: Information about bank vole indiviuals and corresponding replicates for the case study.
Codebook_case_study.xlsx: Codebook for the case study data sets.
Read_me.txt
The folder "Pohle_et_al_2023_BehavioralStates_iSSA_RCode" contains the R-scripts for the simulation and case study:

Functions.R: Functions to apply HMMs, TS-iSSAs, and HMM-iSSAs to movement data; used for the simulation and case study.
Simulation_study.R: R-Code to run the simulation study. Parallel computation is used.
Results_simulation_study.R: R-Code to create the result figures and tables for the simulation study.
Case_study.R: R-Code to run the bank vole interaction case study. Parallel computation is used.
Results_case_study.R: R-Code to create the result figures and tables for the case study.
Read_me.txt
Besides the simulation and case study from the paper, the included functions (Functions.R) can generally be used to perform an HMM-iSSA analysis.
For the bank vole movement data without control locations, see: Schlägel, U.E. et al. (2019). Data from: Estimating interactions between individuals from concurrent animal movements [Dataset]. Dryad. https://doi.org/10.5061/dryad.rt535m8.
Acknowledgements
We thank Sophie Eden, Angela Puschmann and Pauline Lange for help with the bank vole data collection and maintenance of the outdoor enclosures.
DOI: 10.21338/ess9mtmme03
title: ESS9 - test data (MTMM), edition 3.0
DOI: 10.21338/ess9timee02
title: ESS9 - interview time data, edition 2.0
DOI: 10.15151/esrf-es-1338642281
title: Operando Photoelectrochemical XAFS analysis of mixed Co-Fe co-catalysts on WO3/BiVO4 photoanodes.

description: Metal oxides photoanodes, such as WO3/BiVO4 heterostructures, represent the state of the art towards photoelectrochemical (PEC) water splitting, but their efficiency is still hampered by the sluggish oxygen evolution reaction (OER) kinetics and limited charge separation efficiency. Mixed Cobalt-Iron co-catalysts proved to be effective to temper such issues, however, a full comprehension of the catalytic cycle underlying such enhancement is yet to be achieved. To address this issue, we request beamtime to perform operando PEC-XAFS measurements, as a follow-up study to a previous beamtime at ESRF beamtime LISA BM-08. This experiments highlighted a structure-dependent response of the Co – Kedge upon bias and light stimuli, requiring further investigation. The present proposal aims to strenghten the understanding of the physical properties of this photocatalyst in real operating conditions, focusing on the Fe – Kedge behaviour and the dependence on the illumination source power.
DOI: 10.21338/ess9cfe03
title: ESS9 - data from Contact forms, edition 3.0
DOI: 10.21338/ess9roe01
title: ESS9 - Romania (participating on pilot basis)
DOI: 10.21338/ess9ale01
title: ESS9 - Albania (interview quality issues)
DOI: 10.6084/m9.figshare.21803727
title: EASE2023_rapid_review

description: This is the online appendix for the paper entitled "A Rapid Review of Responsible AI frameworks: How to guide the development of ethical AI", published on EASE 2023
DOI: 10.6084/m9.figshare.21803727.v1
title: EASE2023_rapid_review

description: This is the online appendix for the paper entitled "A Rapid Review of Responsible AI frameworks: How to guide the development of ethical AI", published on EASE 2023
DOI: 10.5281/zenodo.10123621
title: Rapid discovery of high-affinity antibodies via massively parallel sequencing, ribosome display and affinity screening

description: Deep screening datasets for experiments conducted in Porebski et al., (2023) Rapid discovery of high-affinity antibodies via massively parallel sequencing, ribosome display and affinity screening. Nat. Biol. Eng., doi: 10.1038/s41551-023-01093-3.


Datasets are made available under a CC BY-NC-ND 4.0 licence.
DOI: 10.5281/zenodo.8241732
title: Rapid discovery of high-affinity antibodies via massively parallel sequencing, ribosome display and affinity screening

description: Deep screening datasets for experiments conducted in Porebski et al., (2023) Rapid discovery of high-affinity antibodies via massively parallel sequencing, ribosome display and affinity screening. Nat. Biol. Eng., doi: 10.1038/s41551-023-01093-3.


Datasets are made available under a CC BY-NC-ND 4.0 licence.
DOI: 10.5281/zenodo.8241733
title: Rapid discovery of high-affinity antibodies via massively parallel sequencing, ribosome display and affinity screening

description: Deep screening datasets for experiments conducted in Porebski et al., (2023) Rapid discovery of high-affinity antibodies via massively parallel sequencing, ribosome display and affinity screening. <em>Nat. Biol. Eng., doi: 10.1038/s41551-023-01093-3</em>. Datasets are made available under a CC BY-NC-ND 4.0 licence.
DOI: 10.21338/ess8timee01
title: ESS8 - interview time data, edition 1.0
DOI: 10.21338/ess8cfe03
title: ESS8 - data from Contact forms, edition 3.0
DOI: 10.5281/zenodo.10031326
title: Ecological filtering shapes the impacts of agricultural deforestation on biodiversity

description: This dataset and associated code are for the manuscript titled "Ecological filtering shapes the impacts of agricultural deforestation on biodiversity", which is due to be published in the journal Nature Ecology & Evolution (accepted on September 20, 2023). The abstract of this manuscript is as follows:
 
The biodiversity impacts of agricultural deforestation vary widely across regions. Previous efforts to explain this variation have focused exclusively on the landscape features and management regimes of agricultural systems, neglecting the potentially critical role of ecological filtering in shaping deforestation tolerance of extant species assemblages at large geographical scales via selection for functional traits. Here we provide a large-scale test of this role using a global database of species abundance ratios between matched agricultural and native forest sites that comprises 71 avian assemblages reported in 44 primary studies, and a companion database of ten functional traits for all 2,647 species involved. Using meta-analytic, phylogenetic, and multivariate methods, we show that beyond agricultural features, filtering by the extent of natural environmental variability and the severity of historical anthropogenic deforestation shapes the varying deforestation impacts across species assemblages. For assemblages under greater environmental variability – proxied by drier and more seasonal climates under greater disturbance regime – and longer deforestation histories, filtering has attenuated the negative impacts of current deforestation by selecting for functional traits linked to stronger deforestation tolerance. Our study provides a heretofore largely missing piece of knowledge in understanding and managing the biodiversity consequences of deforestation by agricultural deforestation.
DOI: 10.5281/zenodo.10031327
title: Ecological filtering shapes the impacts of agricultural deforestation on biodiversity

description: This dataset and associated code are for the manuscript titled "Ecological filtering shapes the impacts of agricultural deforestation on biodiversity", which is due to be published in the journal Nature Ecology & Evolution (accepted on September 20, 2023). The abstract of this manuscript is as follows:
 
The biodiversity impacts of agricultural deforestation vary widely across regions. Previous efforts to explain this variation have focused exclusively on the landscape features and management regimes of agricultural systems, neglecting the potentially critical role of ecological filtering in shaping deforestation tolerance of extant species assemblages at large geographical scales via selection for functional traits. Here we provide a large-scale test of this role using a global database of species abundance ratios between matched agricultural and native forest sites that comprises 71 avian assemblages reported in 44 primary studies, and a companion database of ten functional traits for all 2,647 species involved. Using meta-analytic, phylogenetic, and multivariate methods, we show that beyond agricultural features, filtering by the extent of natural environmental variability and the severity of historical anthropogenic deforestation shapes the varying deforestation impacts across species assemblages. For assemblages under greater environmental variability – proxied by drier and more seasonal climates under greater disturbance regime – and longer deforestation histories, filtering has attenuated the negative impacts of current deforestation by selecting for functional traits linked to stronger deforestation tolerance. Our study provides a heretofore largely missing piece of knowledge in understanding and managing the biodiversity consequences of deforestation by agricultural deforestation.
DOI: 10.21338/ess8sddfe01_1
title: ESS8 - sample data (SDDF), edition 1.1
DOI: 10.21338/ess8mce02
title:  ESS8 - data from Media claims, edition 2.0
DOI: 10.5281/zenodo.10102437
title: When cheating turns into a stabilizing mechanism of plant-pollinator communities

description: This repository is a complete update to the one linked to our preprint (https://zenodo.org/records/8272889). It includes:

R codes to reproduce simulations, empirical analyses and figures
results of theoretical simulations (data_for_analyses.txt in simulations_results)
empirical data to reproduce analyses (traits_data.csv & empirical_data.csv in empirical_data folder)
results of simulations calibrated by empirical networks (equilibriums_analyse_empir.txt in simulations_results)
results of simulations for randomized empirical cheating patterns (equilibriums_analyse_empir_null.txt in simulations_results)
R (v. 4.3.0) codes are also available here: https://github.com/f-duchenne/Cheating_in_mutualistic_networks
DOI: 10.5281/zenodo.10102438
title: When cheating turns into a stabilizing mechanism of plant-pollinator communities

description: This repository is a complete update to the one linked to our preprint (https://zenodo.org/records/8272889). It includes:

R codes to reproduce simulations, empirical analyses and figures
results of theoretical simulations (data_for_analyses.txt in simulations_results)
empirical data to reproduce analyses (traits_data.csv & empirical_data.csv in empirical_data folder)
results of simulations calibrated by empirical networks (equilibriums_analyse_empir.txt in simulations_results)
results of simulations for randomized empirical cheating patterns (equilibriums_analyse_empir_null.txt in simulations_results)
R (v. 4.3.0) codes are also available here: https://github.com/f-duchenne/Cheating_in_mutualistic_networks
DOI: 10.21338/ess8mtmme02
title: ESS8 - test data (MTMM), edition 2.0
DOI: 10.6084/m9.figshare.19738237
title: 2023_TechDebt_SonarQubeFortify

description: This is the online appendix for the paper entitled "Resolving Security Issues via Quality-Oriented Refactoring: A User Study", published on TechDebt 2023
DOI: 10.6084/m9.figshare.19738237.v1
title: 2023_TechDebt_SonarQubeFortify

description: This is the online appendix for the paper entitled "Resolving Security Issues via Quality-Oriented Refactoring: A User Study", published on TechDebt 2023
DOI: 10.21338/ess8inte02
title: ESS8 - data from Interviewer's questionnaire, edition 2.0
DOI: 10.6084/m9.figshare.24559180
title: Table S3. Gene annotation and transcription for Fungal-type DNA-binding domain.

description: Fungal comparative genomics.
DOI: 10.6084/m9.figshare.24559180.v1
title: Table S3. Gene annotation and transcription for Fungal-type DNA-binding domain.

description: Fungal comparative genomics.
DOI: 10.6084/m9.figshare.24559195
title: Table S4. <b>Orthogroups in which Mycena species are enriched.</b>

description: Mycena comparative genomics.
DOI: 10.6084/m9.figshare.24559195.v1
title: Table S4. <b>Orthogroups in which Mycena species are enriched.</b>

description: Mycena comparative genomics.
DOI: 10.18112/openneuro.ds004513.v1.0.3
title: The energetic costs of the human connectome
DOI: 10.21338/ess7alce02
title: ESS7 - alcohol consumption variables, edition 2.0
DOI: 10.21338/ess7sddfe1_2
title: ESS7 - sample data (SDDF), edition 1.2
DOI: 10.5281/zenodo.10123611
title: Òmnibus de dades cadastrals del nord del barri de Point Breeze, a Filadèlfia

description: El dataset inclou tota la informació disponible a través del portal Property relatiu a totes les finques dins la zona nord del barri de Point Breeze, que es correspon al polígon delimitat pels carrers Washington Avenue, al nord, Wharton Street, al sud, South Broad Street, a l'est, i South 25th Street, a l'oest. Els mapes de la pàgina següent il.lustren l'abast geogràfic de la captura. L'horitzó temporal de les dades capturades es correspon a la segona meitat d'octubre i la primera meitat de novembre de 2023.
DOI: 10.5281/zenodo.10123612
title: Òmnibus de dades cadastrals del nord del barri de Point Breeze, a Filadèlfia

description: El dataset inclou tota la informació disponible a través del portal Property relatiu a totes les finques dins la zona nord del barri de Point Breeze, que es correspon al polígon delimitat pels carrers Washington Avenue, al nord, Wharton Street, al sud, South Broad Street, a l'est, i South 25th Street, a l'oest. Els mapes de la pàgina següent il.lustren l'abast geogràfic de la captura. L'horitzó temporal de les dades capturades es correspon a la segona meitat d'octubre i la primera meitat de novembre de 2023.
DOI: 10.21338/ess7timee01
title: ESS7 - interview time data, edition 1.0
DOI: 10.6084/m9.figshare.24559249
title: Table S6. Orthologs of Neurospora genome maintenance genes identified in Mycena and non-Mycena species examined here.

description: Mycena comparative genomics.
DOI: 10.6084/m9.figshare.24559249.v1
title: Table S6. Orthologs of Neurospora genome maintenance genes identified in Mycena and non-Mycena species examined here.

description: Mycena comparative genomics.
DOI: 10.18167/dvn1/o9tjeo
title: Phenotypic data of the CNA6 population from cycle 3 to cycle 7

description: The CNA6 population, evaluated over five cycles (3 to 7) of selection, including 20 field trials, was used to assess the realized genetic gain. The experimental data used in this study was generated in multisite trials conducted on S0:2 families from five cycles of recurrent selection in the CNA6 population. The following traits were analyzed: grain yield (YLD, kg‧ha−1), days to flowering (FLW, days) and plant height (PHT, cm).
DOI: 10.5525/gla.researchdata.1482
title: A nanoplasmonic sensor array for optical inline drinking water assessment: a pilot study with rural Scottish water treatment works

description: This dataset contains raw data associated with the aforementioned paper.
DOI: 10.6084/m9.figshare.24559252
title: <b>Table S7. Significant results of correlation analyses between DNA transposons, genome size, LTR elements, unclassified genes, and gene counts of SSPs, lipases, proteases, and CAZyme classes.</b>

description: Mycena comparative genomics.
DOI: 10.6084/m9.figshare.24559252.v1
title: <b>Table S7. Significant results of correlation analyses between DNA transposons, genome size, LTR elements, unclassified genes, and gene counts of SSPs, lipases, proteases, and CAZyme classes.</b>

description: Mycena comparative genomics.
DOI: 10.21338/ess7mce01
title: ESS7 - data from Media claims, edition 1.0
DOI: 10.5281/zenodo.3872436
title: Instrument response files for seismic stations in South Korea (accelerometer)

description: A paper related to this dataset will be submitted. Examples to deconvolve the instrument response from raw data are below, using the Seismic Analysis Code (SAC, version sac-101.6a). 1. A unit of output is 'm/s2' <pre><code class="language-bash">r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 w acc.sac q</code></pre> 2. A unit of output is 'm/s' <pre><code class="language-bash">r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 TRANS FROM ACC TO VEL w vel.sac q</code></pre> 3. A unit of output is 'm' <pre><code>r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 TRANS FROM ACC TO VEL rtr rmean taper TRANS FROM VEL TO NONE w disp.sac q</code></pre> Note that the unit of the output is incoherent with the SAC header 'IDEP'. <strong>Others</strong> Velocity seismometer https://doi.org/10.5281/zenodo.3700312<br> Accelerometer https://doi.org/10.5281/zenodo.3872436
DOI: 10.5281/zenodo.3872435
title: Instrument response files for seismic stations in South Korea (accelerometer)

description: To do
[1.01] I have found something wrong in poles and zeros for the KG and KN networks. Please do not use them until update. I am sorry for it. (14 November 2023)
 
Example 1 (Seismic Analysis Code)
Examples to deconvolve the instrument response from raw data are below, using the Seismic Analysis Code (SAC, version sac-101.6a). 
 
1. A unit of output is 'm/s2'
r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 w acc.sac q
 
2. A unit of output is 'm/s'
r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 TRANS FROM ACC TO VEL w vel.sac q
 
3. A unit of output is 'm'
r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 TRANS FROM ACC TO VEL rtr rmean taper TRANS FROM VEL TO NONE w disp.sac q
 
Note that the unit of the output is incoherent with the SAC header 'IDEP'.
Example 2 (StationXML with obspy)
#this is same as the code for the velocity seismometers.
 
Update notes

[1.01]

Typo at INPUT UNIT for KG is modified (M/S -> M/S**2)
Stations KS.CE2A, KS.HA2B are added
StationXML file is added (ksgn.xml)
[1.00] The files for the KG network are made based on the logs until 12 April 2019 (personal communication with the Korea Institute of Geoscience and Mineral Resources).
Others
Velocity seismometer https://doi.org/10.5281/zenodo.3700312Accelerometer https://doi.org/10.5281/zenodo.3872436
 
License
This distribution follows the Creative Commons Attribution 4.0 International. You are free to modify and redistribute the files.
DOI: 10.5281/zenodo.5748671
title: Instrument response files for seismic stations in South Korea (accelerometer)

description: To do
[1.01] I have found something wrong in poles and zeros for the KG and KN networks. Please do not use them until update. I am sorry for it. (14 November 2023)
 
Example 1 (Seismic Analysis Code)
Examples to deconvolve the instrument response from raw data are below, using the Seismic Analysis Code (SAC, version sac-101.6a). 
 
1. A unit of output is 'm/s2'
r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 w acc.sac q
 
2. A unit of output is 'm/s'
r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 TRANS FROM ACC TO VEL w vel.sac q
 
3. A unit of output is 'm'
r $input rtr rmean taper TRANS FROM POLEZERO S $pzfile TO none FREQ 0.05 0.1 1.5 3.0 TRANS FROM ACC TO VEL rtr rmean taper TRANS FROM VEL TO NONE w disp.sac q
 
Note that the unit of the output is incoherent with the SAC header 'IDEP'.
Example 2 (StationXML with obspy)
#this is same as the code for the velocity seismometers.
 
Update notes

[1.01]

Typo at INPUT UNIT for KG is modified (M/S -> M/S**2)
Stations KS.CE2A, KS.HA2B are added
StationXML file is added (ksgn.xml)
[1.00] The files for the KG network are made based on the logs until 12 April 2019 (personal communication with the Korea Institute of Geoscience and Mineral Resources).
Others
Velocity seismometer https://doi.org/10.5281/zenodo.3700312Accelerometer https://doi.org/10.5281/zenodo.3872436
 
License
This distribution follows the Creative Commons Attribution 4.0 International. You are free to modify and redistribute the files.
DOI: 10.21338/ess7cfe02_1
title: ESS7 - data from Contact forms, edition 2.1
DOI: 10.21338/ess7inte02_1
title: ESS7 - data from Interviewer's questionnaire, edition 2.1
DOI: 10.21338/ess7mtmme2_1
title: ESS7 - test variables from Supplementary questionnaire, edition 2.1
DOI: 10.5281/zenodo.10118347
title: Repos Type4Py

description: dataset.zip contains folders with repositories divided by project topics.
all_repos.zip contains .json files with links and other meta information about all repositories which were found and analysed during our work.
filtered_repos.zip contains subset of all_repos.zip files. We filtered out repositories with rules described in our paper. json files in filtered_repos.zip correspond to dataset.zip
DOI: 10.5281/zenodo.10118348
title: Repos Type4Py