cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7695738
title: Data for manuscript "Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting"

description: The tar file contains the input files for RADICAL augmented MDFF implementation (R-MDFF) for two protein systems, Adenylate Kinase (ADK) and Carbon Monoxide Dehydrogenase (CODH). These examples demonstrate the implementation of R-MDFF using RADICAL-Cybertools to flexibly fit biomolecules in cryo-EM density maps with on-the-fly decision making. All molecular simulations were performed using CUDA enabled NAMD 2.14 installed on OLCF Summit HPC resource. The CHARMM36 force field parameters were used for the proteins. Synthetic density maps were prepared at 1.8, 3 and 5 Å for ADK and 1.8 and 3 Å for CODH using VMD 1.9.3 software installed on OLCF Summit HPC resource. During the analysis stage, the cross correlation coefficients between density maps and atomic model were computed using VMD 1.9.3 on Summit HPC as part of the R-MDFF workflow. The source code is publicly available on GitHub: https://github.com/radical-collaboration/MDFF-EnTK The preprint of this research is submitted on bioRxiv, doi: https://doi.org/10.1101/2021.12.07.471672 To obtain maximum compression of the data, the tar command used to generate this tarball was: <pre><code class="language-bash">GZIP=-9 tar --exclude='last.pdb' --exclude='*last_from_prev_iter.pdb' --exclude='*old' --exclude='*log' --exclude='*coor' --exclude='*vel' --exclude='*xsc' --exclude='*dcd' --exclude='lastframepdbs_fix' --exclude='*out' --exclude='*sl' --exclude='*rs' --exclude='*prof' --exclude='*err' --exclude='*dx' --exclude='*grid.pdb' --exclude='*txt' -cvzf rmdffv2.tar.gz rmdff-zenodo/</code></pre>
DOI: 10.5281/zenodo.7695737
title: Data for manuscript "Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting"

description: The tar file contains the input files for RADICAL augmented MDFF implementation (R-MDFF) for two protein systems, Adenylate Kinase (ADK) and Carbon Monoxide Dehydrogenase (CODH). These examples demonstrate the implementation of R-MDFF using RADICAL-Cybertools to flexibly fit biomolecules in cryo-EM density maps with on-the-fly decision making. All molecular simulations were performed using CUDA enabled NAMD 2.14 installed on OLCF Summit HPC resource. The CHARMM36 force field parameters were used for the proteins. Synthetic density maps were prepared at 1.8, 3 and 5 Å for ADK and 1.8 and 3 Å for CODH using VMD 1.9.3 software installed on OLCF Summit HPC resource. During the analysis stage, the cross correlation coefficients between density maps and atomic model were computed using VMD 1.9.3 on Summit HPC as part of the R-MDFF workflow. The source code is publicly available on GitHub: https://github.com/radical-collaboration/MDFF-EnTK The preprint of this research is submitted on bioRxiv, doi: https://doi.org/10.1101/2021.12.07.471672 To obtain maximum compression of the data, the tar command used to generate this tarball was: <pre><code class="language-bash">GZIP=-9 tar --exclude='last.pdb' --exclude='*last_from_prev_iter.pdb' --exclude='*old' --exclude='*log' --exclude='*coor' --exclude='*vel' --exclude='*xsc' --exclude='*dcd' --exclude='lastframepdbs_fix' --exclude='*out' --exclude='*sl' --exclude='*rs' --exclude='*prof' --exclude='*err' --exclude='*dx' --exclude='*grid.pdb' --exclude='*txt' -cvzf rmdffv2.tar.gz rmdff-zenodo/</code></pre>
DOI: 10.5517/ccdc.csd.cc1ln6bs
title: CCDC 1479175: Experimental Crystal Structure Determination

description: Related Article: Maissa P. Belcina, Bahar Farhadpour, Nada Y. Tashkandi, Andrew T. Henry, Jeremy L. Bourque, Kim, M. Baines|2022|Can.J.Chem.|101|126|doi:10.1139/cjc-2021-0331
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.cc297cxv
title: CCDC 2122257: Experimental Crystal Structure Determination

description: Related Article: Maissa P. Belcina, Bahar Farhadpour, Nada Y. Tashkandi, Andrew T. Henry, Jeremy L. Bourque, Kim, M. Baines|2022|Can.J.Chem.|101|126|doi:10.1139/cjc-2021-0331
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.cc2b5893
title: CCDC 2150014: Experimental Crystal Structure Determination

description: Related Article: Meng Chen Wang, Wei Wei Cao, Li Tian|2023|Cryst.Growth Des.|23|1868|doi:10.1021/acs.cgd.2c01362
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: 10.6084/m9.figshare.22099679
title: Tweet Emotion Data

description: <em>Dataset containing tweets and meta data information for multiclass prediction for emotion of tweet.</em><br> <br> <em>The data has 4653 tweet records with 5 features and a multiclass target column, referring to the emotion of the tweet.</em><br> <br> <em>This dataset is an extension of Hugging Face's tweet_eval dataset,</em><br> <em>For additional details about the dataset, please refer to the original source: https://huggingface.co/datasets/tweet_eval</em>
DOI: 10.6084/m9.figshare.22122968
title: ROB2_Consensus form (1).xlsm

description: Details on the risk of bias assessment consensus of the systematic review: <strong>Digital technology for delivering and monitoring exercise programs for people with cystic fibrosis</strong>
DOI: 10.6084/m9.figshare.22122968.v2
title: ROB2_Consensus form (1).xlsm

description: Details on the risk of bias assessment consensus of the systematic review: <strong>Digital technology for delivering and monitoring exercise programs for people with cystic fibrosis</strong>
DOI: 10.6084/m9.figshare.22122968.v3
title: ROB2_Consensus form (1).xlsm

description: Details on the risk of bias assessment consensus of the systematic review: <strong>Digital technology for delivering and monitoring exercise programs for people with cystic fibrosis</strong>
DOI: 10.6084/m9.figshare.22059416
title: Predictors of feeling of threat caused by COVID-19 pandemic, the distinctive effects of automatic vs reflective emotions - database

description: Database for the research article "Predictors of feeling of threat caused by COVID-19 pandemic, the distinctive effects of automatic vs reflective emotions".
DOI: 10.6084/m9.figshare.22059416.v1
title: Predictors of feeling of threat caused by COVID-19 pandemic, the distinctive effects of automatic vs reflective emotions - database

description: Database for the research article "Predictors of feeling of threat caused by COVID-19 pandemic, the distinctive effects of automatic vs reflective emotions".
DOI: 10.5281/zenodo.7626042
title: Data for: Representation of rewards differing in their hedonic valence in the caudate nucleus correlates with the performance in a problem-solving task in dogs (Canis familiaris)

description: Abstract We have investigated dogs’ (<em>Canis familiaris</em>) abilities in associating different sounds with food rewards of different incentive value. The establishment of the association was tested in a problem-solving behavioural paradigm, as well as in an fMRI study on the same subjects (N=20). The aim was to show behavioural, as well as parallel neural effects of the association formation between the two sounds and two different associated food rewards.<br> The latency of solving the problem was considered as an indicator of motivational state. In our behaviour study we found that dogs were quicker in solving a problem upon hearing the sound associated with food higher in reward value, suggesting that they have successfully associated the sounds with the corresponding food value. In the fMRI study, the cerebral response to the two sounds was compared both before and after the associative training. Two bilateral regions of interest were explored: the caudate nucleus and the amygdala. After the associative training the response in the caudate nucleus was higher to the sound related to a higher reward value food than to the sound related to a lower reward value food, which difference was not present before the associative training. We found an increase in the amygdala response to both sounds after the training. In a whole-brain representational similarity analysis, we found that cerebral patterns in the caudate nucleus to the two sounds were different only after the training. Moreover, we found a positive correlation between the dissimilarity index in the caudate nucleus for activation responses to the two sounds and the difference in latencies to solve the behavioural task: the quicker the dog solved the behavioural task the greater the difference in the neural representation of the two sounds was. In summary, family dogs’ brain activation patterns reflected their expectations based on what they learned about the relationship between two sounds and their associated rewards. This dataset contains Raw data (four functional runs n = 20) Dog brain template ROI results (Caudate nucleus and amygdala percentage of BOLD signal change and caudate nucleus response to sounds during the two post-training runs adding or not the Inter-scan interval as a covariate in the GLM model n = 20,) RSA results ( Dissimilarity change between sounds (post-training &gt; pre-training) and dissimilarity index per participant n = 20)
DOI: 10.5281/zenodo.7626041
title: Data for: Representation of rewards differing in their hedonic valence in the caudate nucleus correlates with the performance in a problem-solving task in dogs (Canis familiaris)

description: Abstract We have investigated dogs’ (<em>Canis familiaris</em>) abilities in associating different sounds with food rewards of different incentive value. The establishment of the association was tested in a problem-solving behavioural paradigm, as well as in an fMRI study on the same subjects (N=20). The aim was to show behavioural, as well as parallel neural effects of the association formation between the two sounds and two different associated food rewards.<br> The latency of solving the problem was considered as an indicator of motivational state. In our behaviour study we found that dogs were quicker in solving a problem upon hearing the sound associated with food higher in reward value, suggesting that they have successfully associated the sounds with the corresponding food value. In the fMRI study, the cerebral response to the two sounds was compared both before and after the associative training. Two bilateral regions of interest were explored: the caudate nucleus and the amygdala. After the associative training the response in the caudate nucleus was higher to the sound related to a higher reward value food than to the sound related to a lower reward value food, which difference was not present before the associative training. We found an increase in the amygdala response to both sounds after the training. In a whole-brain representational similarity analysis, we found that cerebral patterns in the caudate nucleus to the two sounds were different only after the training. Moreover, we found a positive correlation between the dissimilarity index in the caudate nucleus for activation responses to the two sounds and the difference in latencies to solve the behavioural task: the quicker the dog solved the behavioural task the greater the difference in the neural representation of the two sounds was. In summary, family dogs’ brain activation patterns reflected their expectations based on what they learned about the relationship between two sounds and their associated rewards. This dataset contains Raw data (four functional runs n = 20) Dog brain template ROI results (Caudate nucleus and amygdala percentage of BOLD signal change and caudate nucleus response to sounds during the two post-training runs adding or not the Inter-scan interval as a covariate in the GLM model n = 20,) RSA results ( Dissimilarity change between sounds (post-training &gt; pre-training) and dissimilarity index per participant n = 20)
DOI: 10.6084/m9.figshare.21667583
title: Synodontis cannibalism

description: Primary data and R code used to test the importance of cannibalism in cuckoo catfish early development. (Zimmermann et al. 2023)
DOI: 10.6084/m9.figshare.21667583.v2
title: Synodontis cannibalism

description: Primary data and R code used to test the importance of cannibalism in cuckoo catfish early development. (Zimmermann et al. 2023)
DOI: 10.6084/m9.figshare.21667583.v1
title: Synodontis cannibalism

description: Primary data used to test the importance of cannibalism in cuckoo catfish early development.
DOI: 10.5517/ccdc.csd.cc29xsgh
title: CCDC 2142827: Experimental Crystal Structure Determination

description: Related Article: Meng Chen Wang, Wei Wei Cao, Li Tian|2023|Cryst.Growth Des.|23|1868|doi:10.1021/acs.cgd.2c01362
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: 10.5281/zenodo.7699966
title: FT16 H. Grenser (1) 5-key fagottino: partial measurements

description: Description: Dataset of FT16 H. Grenser (1) 5-key fagottino containing partial measurements, based on third-party sketch
DOI: 10.5281/zenodo.7699965
title: FT16 H. Grenser (1) 5-key fagottino: partial measurements

description: Description: Dataset of FT16 H. Grenser (1) 5-key fagottino containing partial measurements, based on third-party sketch
DOI: 10.21227/6yka-v482
title: TopoData

description: We used the traceroute tool to measure the routing of IPs in some areas. This dataset is the measured results.
DOI: 10.6084/m9.figshare.20222724
title: SuicideBD: A Suicidal Dataset for Bangladesh

description: This dataset contains individual details who committed suicide in Bangladesh during the Pandemic between February, 2020 to November, 2020. This dataset includes details of every individuals who committed suicide like personal details, family & social life, profession, financial condition, methods of committing suicide, location and weather info. The dataset is freely available. The major fields included in this dataset are: age group, age, gender, profession group, reason, method, suicide date & time, addiction status, mental status, economic condition, marital status, family details, academic qualification, weather. Apart from the above data this dataset also contains a CSV file of a Bengali wordcloud built on social media posts of the suicide victims. <br> <strong>The access to the dataset files is kept restricted. Fill up the below form (link in the References section) to request the data.</strong>
DOI: 10.6084/m9.figshare.20222724.v1
title: SuicideBD: A Suicidal Dataset for Bangladesh

description: This dataset contains individual details who committed suicide in Bangladesh during the Pandemic between February, 2020 to November, 2020. This dataset includes details of every individuals who committed suicide like personal details, family & social life, profession, financial condition, methods of committing suicide, location and weather info. The dataset is freely available. The major fields included in this dataset are: age group, age, gender, profession group, reason, method, suicide date & time, addiction status, mental status, economic condition, marital status, family details, academic qualification, weather. Apart from the above data this dataset also contains a CSV file of a Bengali wordcloud built on social media posts of the suicide victims. <br> <strong>The access to the dataset files is kept restricted. Fill up the below form (link in the References section) to request the data.</strong>
DOI: 10.6084/m9.figshare.22122374
title: Raw data and Analysis

description: The raw data on behavior and physical fitness. The behavior for sampling worker before joining WE is on sheet behavior 31 and 62 Then, we show all data for behavior and physical fitness.
DOI: 10.6084/m9.figshare.22122374.v3
title: Raw data and Analysis

description: The raw data on behavior and physical fitness. The behavior for sampling worker before joining WE is on sheet behavior 31 and 62 Then, we show all data for behavior and physical fitness.
DOI: 10.34740/kaggle/dsv/5111131
title: Nigerian Presidential Election 2023 Tweets
DOI: 10.5281/zenodo.7700129
title: Effects of Charring on Squash (Cucurbita L ) Seed Morphology and Compression Strength: Implications for Paleoethnobotany Metric Data

description: Metric data resulting from a series of charring experiments on seeds from three species of squash: <em>Cucurbita pepo</em>, <em>Cucurbita moschata</em>, and <em>Cucurbita maxima</em>.
DOI: 10.5281/zenodo.7700128
title: Effects of Charring on Squash (Cucurbita L ) Seed Morphology and Compression Strength: Implications for Paleoethnobotany Metric Data

description: Metric data resulting from a series of charring experiments on seeds from three species of squash: <em>Cucurbita pepo</em>, <em>Cucurbita moschata</em>, and <em>Cucurbita maxima</em>.
DOI: 10.5281/zenodo.7669533
title: datasets for A systematic approach to study protein-substrate specificity enables the identification of Ssh1 substrate range

description: datasets for A systematic approach to study protein-substrate specificity enables the identification of Ssh1 substrate range
DOI: 10.5281/zenodo.7669532
title: datasets for A systematic approach to study protein-substrate specificity enables the identification of Ssh1 substrate range

description: datasets for A systematic approach to study protein-substrate specificity enables the identification of Ssh1 substrate range
DOI: 10.6084/m9.figshare.21268512
title: Vodoprovodnoye Lake_Bosmina longirostris abundance and demography

description: The datasets contain input data on Bosmina longirostris abundance and demographic characteristics for the Bosmina longirostris population inhabiting the Vodoprovodnoye lake (66°33' N, 33°06' E) during the study season in 2012 and 2013. Two additional files (Conts_VOD_BL_2012 and Conts_VOD_BL_2013) containing the results of contribution analysis, i.e. the ratios of the absolute values of contributions of proportion of adults and fecundity into the change of birth rate calculated for consecutive intervals between samples, have also been uploaded.
DOI: 10.6084/m9.figshare.21268512.v1
title: Vodoprovodnoye Lake_Bosmina longirostris abundance and demography

description: The two datasets contains input data on Bosmina longirostris abundance and demographic characteristics for the population inhabiting the Vodoprovodnoye lake (66°33' N, 33°06' E) during the study season in 2012 and 2013
DOI: 10.5281/zenodo.7265755
title: Malawi probabilistic seismic hazard analysis (PSHA) using the Malawi Seismogenic Source Model (MSSM). Supplementary Files v1.1

description: Updated (October 2022) version of supplementary files for running probabilistic seismic hazard analysis (PSHA) MATLAB codes for Malawi. The PSHA codes themselves (v1.0) are available at: https://doi.org/10.5281/zenodo.7265781and the most recent version will be available on GitHub at: https://github.com/jack-williams1/Malawi_PSHA. Note the variables stored here are not stored on GitHub due to the file size. Includes both input files for performing PSHA and output ground motions for plotting PSHA results. Files are: malawi_Vs30_active.txt: Input USGS slope-based Vs30 values for Malawi (Wald and Allen 2007) EQCAT_comb.mat: MSSM Direct catalog for all possible rupture weightings (stored as MATLAB variable) GM_MSSM_em_20221027: Ground motions for plotting PSHA maps (stored as MATLAB variable) GM_MSSM_20221021.mat: Ground motions needed for plotting PSHA-site analysis figures (stored as MATLAB variable) mssm_comb.mat: Matlab file for combined MSSM Direct and Adapted MSSM catalogs (stored as MATLAB variable) MSSM_Catalog_Adapted_em.mat: Adapated MSSM event catalog (stored as MATLAB variable) syncat_bg.mat: Areal source stochastic event catalog (stored as MATLAB variable) Further descriptions of these files and how to use them are provided on Github. An open-access manuscript describing the PSHA is available at: Williams J. N., Werner M. J., Goda K., Wedmore L. N. J., De Risi R., Biggs J., Mdala H., Dulanya Z., Fagereng Å, Mphepo F., Chindandali P. (2023). Fault-based probabilistic seismic hazard analysis in regions with low strain rates and a thick seismogenic layer: a case study from Malawi, Geophysical Journal International, Volume 233, Issue 3, June 2023, Pages 2172–2206, https://doi.org/10.1093/gji/ggad060 Please reference this publication along with this repository when using these data. USGS vs30 value compilation described in: Allen, T. I., and Wald, D. J., 2009, On the use of high-resolution topographic data as a proxy for seismic site conditions (Vs30), Bulletin of the Seismological Society of America, 99, no. 2A, 935-943.
DOI: 10.5281/zenodo.6350792
title: Malawi probabilistic seismic hazard analysis (PSHA) using the Malawi Seismogenic Source Model (MSSM). Supplementary Files v1.1

description: Updated (October 2022) version of supplementary files for running probabilistic seismic hazard analysis (PSHA) MATLAB codes for Malawi. The PSHA codes themselves (v1.0) are available at: https://doi.org/10.5281/zenodo.7265781and the most recent version will be available on GitHub at: https://github.com/jack-williams1/Malawi_PSHA. Note the variables stored here are not stored on GitHub due to the file size. Includes both input files for performing PSHA and output ground motions for plotting PSHA results. Files are: malawi_Vs30_active.txt: Input USGS slope-based Vs30 values for Malawi (Wald and Allen 2007) EQCAT_comb.mat: MSSM Direct catalog for all possible rupture weightings (stored as MATLAB variable) GM_MSSM_em_20221027: Ground motions for plotting PSHA maps (stored as MATLAB variable) GM_MSSM_20221021.mat: Ground motions needed for plotting PSHA-site analysis figures (stored as MATLAB variable) mssm_comb.mat: Matlab file for combined MSSM Direct and Adapted MSSM catalogs (stored as MATLAB variable) MSSM_Catalog_Adapted_em.mat: Adapated MSSM event catalog (stored as MATLAB variable) syncat_bg.mat: Areal source stochastic event catalog (stored as MATLAB variable) Further descriptions of these files and how to use them are provided on Github. An open-access manuscript describing the PSHA is available at: Williams J. N., Werner M. J., Goda K., Wedmore L. N. J., De Risi R., Biggs J., Mdala H., Dulanya Z., Fagereng Å, Mphepo F., Chindandali P. (2023). Fault-based probabilistic seismic hazard analysis in regions with low strain rates and a thick seismogenic layer: a case study from Malawi, Geophysical Journal International, Volume 233, Issue 3, June 2023, Pages 2172–2206, https://doi.org/10.1093/gji/ggad060 Please reference this publication along with this repository when using these data. USGS vs30 value compilation described in: Allen, T. I., and Wald, D. J., 2009, On the use of high-resolution topographic data as a proxy for seismic site conditions (Vs30), Bulletin of the Seismological Society of America, 99, no. 2A, 935-943.