cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/efn3-ap19
title: Acoustic Force Elastography Microscopy

description: Hydrogel scaffolds have attracted attention to develop cellular therapy and tissue engineering platforms for regenerative medicine applications. Among factors, local mechanical properties of scaffolds drive the functionalities of cell niche. Dynamic mechanical analysis (DMA), the standard method to characterize mechanical properties of hydrogels, restricts development in tissue engineering because the measurement provides a single elasticity value for the sample, requires direct contact, and represents a destructive evaluation preventing longitudinal studies on the same sample. We propose a novel technique, acoustic force elastography microscopy (AFEM), to evaluate elastic properties of tissue engineering scaffolds. Results: AFEM can resolve localized and two-dimensional (2D) elastic properties of both transparent and opaque materials with advantages of being non-contact and non-destructive. Gelatin hydrogels, neat synthetic oligo[poly(ethylene glycol)fumarate] (OPF) scaffolds, OPF hydroxyapatite nanocomposite scaffolds and ex vivo biological tissue were examined with AFEM to evaluate the elastic modulus. These measurements of Young’s modulus range from approximately 2 kPa to over 100 kPa were evaluated and are in good agreement with finite element simulations, surface wave measurements, and DMA tests. Conclusion: The AFEM can resolve localized and 2D elastic properties of hydrogels, scaffolds and thin biological tissues. These materials can either be transparent or non-transparent and their evaluation can be done in a non-contact and non-destructive manner, thereby facilitating longitudinal evaluation. Significance: AFEM is a promising technique to quantify elastic properties of scaffolds for tissue engineering and will be applied to provide new insights for exploring elastic changes of cell-laden scaffolds for tissue engineering and material science.
DOI: 10.48420/20231004
title: Figure 6 and Figure S8 source data

description: Source data files for Figure 6 and Figure S8. <br> SPM files were from the AFM, XYZ files are the text outputs that were processed by a Python 3 script. <br> Raw QCM data is in a Microsoft Excel XML file. <br> Final worked up version of the figure is in the Unicode Origin Project file.
DOI: 10.48420/20231004.v1
title: Figure 6 and Figure S8 source data

description: Source data files for Figure 6 and Figure S8. <br> SPM files were from the AFM, XYZ files are the text outputs that were processed by a Python 3 script. <br> Raw QCM data is in a Microsoft Excel XML file. <br> Final worked up version of the figure is in the Unicode Origin Project file.
DOI: 10.13012/b2idb-5586647_v1
title: Data for Refining the role of nitrogen mineralization in mycorrhizal nutrient syndromes

description: This dataset includes data on soil properties, soil N pools, and soil N fluxes presented in the manuscript, "Refining the role of nitrogen mineralization in mycorrhizal nutrient syndromes". Please refer to that publication for details about methodologies used to generate these data and for the experimental design.
DOI: 10.48420/20231025
title: Figure S3 source data and processing

description: Raw data for Figure S3 as CSV files and the figure presentation as a Unicode Origin Project file
DOI: 10.48420/20231025.v1
title: Figure S3 source data and processing

description: Raw data for Figure S3 as CSV files and the figure presentation as a Unicode Origin Project file
DOI: 10.48420/20231052
title: Figure S4 data

description: source AFM data for plots shown in Figure S4.
DOI: 10.48420/20231052.v1
title: Figure S4 data

description: source AFM data for plots shown in Figure S4.
DOI: 10.5066/p9ucqud0
title: qPCR Results for An Assessment of Naegleria fowleri in Grand Teton National Park, Wyoming

description: In 2016, a multidisciplinary team from the U.S. Geological Survey Wyoming-Montana Water Science Center, National Park Service, The Centers for Disease Control and Prevention, and Montana State University?s Department of Microbiology and Immunology in cooperation with the Teton Conservation District, initiated a small study to document the presence or absence of Naegleria fowleri at several hot springs in Grand Teton National Park/John D. Rockefeller, Jr. Memorial Parkway. Over four sampling events in 2016-2017, Naegleria fowleri was detected in several of the Grand Teton National Park/John D. Rockefeller, Jr. Memorial Parkway hot springs for the first time. Additionally, the team found that the prevalence of Naegleria fowleri may be [...]
DOI: 10.48420/20231088.v1
title: Figure S7 source data and processing

description: Source data and Unicode Origin Project file for Figure S7.
DOI: 10.48420/20231088
title: Figure S7 source data and processing

description: Source data and Unicode Origin Project file for Figure S7.
DOI: 10.48420/20231103
title: Table S1

description: Table S1. DFT energies of the reaction cycle for benzyl cyanide.
DOI: 10.48420/20231103.v1
title: Table S1

description: Table S1. DFT energies of the reaction cycle for benzyl cyanide.
DOI: 10.48420/20231097
title: Figure S10 source data and processing

description: Source data and Unicode Origin Project for Figure S10
DOI: 10.48420/20231097.v1
title: Figure S10 source data and processing

description: Source data and Unicode Origin Project for Figure S10
DOI: 10.48366/r215005
title: German corpora for Named Entity Recognition (NER)

description: This comparison takes a comprehensive look at various corpora in German language that are available for the NLP/IE Named Entity Recognition (NER) task. The corpora are surveyed over all the various genre and domains of the underlying text as well as the encoded NER extraction objectives. German is most similar to other languages within the West Germanic language branch, including Afrikaans, Dutch, English, the Frisian languages, Low German, Luxembourgish, Scots, and Yiddish. It also contains close similarities in vocabulary to some languages in the North Germanic group, such as Danish, Norwegian, and Swedish. German is the second most widely spoken Germanic language after English which is also a West Germanic language.
DOI: 10.34740/kaggle/dsv/4144302
title: Elon Musk Tweets
DOI: 10.5281/zenodo.6379526
title: Data for nocturnal plant respiration is under strong non-temperature control

description: Data set contains 1- Annual output (2000-2018) of simulated plant respiration and net primary productivity from JULES with standard (Q10=2) and temperature dependent Q10 (TDQ<sub>10</sub>) with and without incorporation of nocturnal non-temperature control of respiration. Related readme file is included (Readme JULES output.txt). 2-Python code (manuscript-code.zip) and data sets (Source Data.zip) to produce all manuscript figures including supplementary material. Readme file is included within mansucript-code.zip.
DOI: 10.5281/zenodo.6379527
title: Nocturnal plant respiration is under strong non-temperature control

description: Data set contains 1- Annual output (2000-2018) of simulated plant respiration and net primary productivity from JULES with standard (Q10=2) and temperature dependent Q10 (TDQ<sub>10</sub>) with and without consideration of nocturnal non temperature control of respiration. 2-Python code and data sets to produce figure 1 and extended figures 1-4.
DOI: 10.5281/zenodo.7037530
title: Data for nocturnal plant respiration is under strong non-temperature control

description: Data set contains 1- Annual output (2000-2018) of simulated plant respiration and net primary productivity from JULES with standard (Q10=2) and temperature dependent Q10 (TDQ<sub>10</sub>) with and without incorporation of nocturnal non-temperature control of respiration. Related readme file is included (Readme JULES output.txt). 2-Python code (manuscript-code.zip) and data sets (Source Data.zip) to produce all manuscript figures including supplementary material. Readme file is included within mansucript-code.zip.
DOI: 10.18430/m37yzx
title: X-ray diffraction data for the scpA from Streptococcus pyogenes, D783A mutant. (7YZX)
DOI: 10.25574/54003
title: Chandra X-ray Observatory ObsId 54003
DOI: 10.25574/54008
title: Chandra X-ray Observatory ObsId 54008
DOI: 10.25574/54014
title: Chandra X-ray Observatory ObsId 54014
DOI: 10.25574/54020
title: Chandra X-ray Observatory ObsId 54020
DOI: 10.25574/54022
title: Chandra X-ray Observatory ObsId 54022
DOI: 10.25574/54043
title: Chandra X-ray Observatory ObsId 54043
DOI: 10.25574/54049
title: Chandra X-ray Observatory ObsId 54049
DOI: 10.25574/54054
title: Chandra X-ray Observatory ObsId 54054
DOI: 10.25574/54059
title: Chandra X-ray Observatory ObsId 54059
DOI: 10.25574/54065
title: Chandra X-ray Observatory ObsId 54065
DOI: 10.25574/54070
title: Chandra X-ray Observatory ObsId 54070
DOI: 10.25574/54082
title: Chandra X-ray Observatory ObsId 54082
DOI: 10.25574/54088
title: Chandra X-ray Observatory ObsId 54088
DOI: 10.25574/54094
title: Chandra X-ray Observatory ObsId 54094
DOI: 10.25574/54104
title: Chandra X-ray Observatory ObsId 54104
DOI: 10.25574/54111
title: Chandra X-ray Observatory ObsId 54111
DOI: 10.25574/54119
title: Chandra X-ray Observatory ObsId 54119
DOI: 10.25574/54126
title: Chandra X-ray Observatory ObsId 54126
DOI: 10.25574/54132
title: Chandra X-ray Observatory ObsId 54132
DOI: 10.25574/54143
title: Chandra X-ray Observatory ObsId 54143
DOI: 10.25574/54153
title: Chandra X-ray Observatory ObsId 54153
DOI: 10.25574/54160
title: Chandra X-ray Observatory ObsId 54160
DOI: 10.25574/54166
title: Chandra X-ray Observatory ObsId 54166
DOI: 10.25574/54172
title: Chandra X-ray Observatory ObsId 54172
DOI: 10.25574/54178
title: Chandra X-ray Observatory ObsId 54178
DOI: 10.25574/54185
title: Chandra X-ray Observatory ObsId 54185
DOI: 10.25574/54194
title: Chandra X-ray Observatory ObsId 54194
DOI: 10.25574/54204
title: Chandra X-ray Observatory ObsId 54204
DOI: 10.25574/54212
title: Chandra X-ray Observatory ObsId 54212
DOI: 10.25574/54214
title: Chandra X-ray Observatory ObsId 54214
DOI: 10.25574/54218
title: Chandra X-ray Observatory ObsId 54218
DOI: 10.25574/54223
title: Chandra X-ray Observatory ObsId 54223
DOI: 10.25574/54228
title: Chandra X-ray Observatory ObsId 54228
DOI: 10.25574/54230
title: Chandra X-ray Observatory ObsId 54230
DOI: 10.25574/54234
title: Chandra X-ray Observatory ObsId 54234
DOI: 10.25574/54239
title: Chandra X-ray Observatory ObsId 54239
DOI: 10.25574/54241
title: Chandra X-ray Observatory ObsId 54241
DOI: 10.5281/zenodo.7038455
title: Supplementary materials of the paper entitled: "Generating Natural Language Requirements via Adversarial Examples in Deep Learning"

description: Supplementary materials of the paper entitled: "Generating Natural Language Requirements via Adversarial Examples in Deep Learning" File A: Datasets (.txt) A1: Webex A2: Zoom A3: Teams A4: Word A5: PowerPoint A6: Excel File B: Python Code (Both ours and baseline) B1: adversarial_samples.ipynb B2: Baseline.ipynb FIle C: Result Tables (.xlsx) C1: Table of perturbed outputs in Webex C2: Table of perturbed outputs in Zoom C3: Table of perturbed outputs in Teams C4: Table of perturbed outputs in Word C5: Table of perturbed outputs in PowerPoint C6: Table of perturbed outputs in Excel (Excel) File D: Trend of Adversarial Shifts (Graphs) D1: Adversarial shifts of office suit (LSTM) D2: Adversarial shifts of video conferencing suit (LSTM) D3: Non-Adversarial shifts of office suit (LSTM) D4: Non-Adversarial shifts of video conferencing suit(LSTM) D5: Adversarial shifts of office suit (GRU) D6: Adversarial shifts of video conferencing suit (GRU) D7: Non-Adversarial shifts of office suit (GRU) D8: Non-Adversarial shifts of video conferencing suit(GRU) D9: Adversarial shifts of office suit (Bi-LSTM) D10: Adversarial shifts of video conferencing suit (Bi-LSTM) D11: Non-Adversarial shifts of office suit (Bi-LSTM) D12: Non-Adversarial shifts of video conferencing suit(Bi-LSTM) File E: Adversarial Examples (.pdf) E1: Adversarial vs original in Webex E2: Adversarial vs original in Zoom E3: Adversarial vs original in Teams E4: Adversarial vs original in Word E5: Adversarial vs original in PowerPoint E6: Adversarial vs original in Excel File F: Questionnaire
DOI: 10.5281/zenodo.7038454
title: Supplementary materials of the paper entitled: "Generating Natural Language Requirements via Adversarial Examples in Deep Learning"

description: Supplementary materials of the paper entitled: "Generating Natural Language Requirements via Adversarial Examples in Deep Learning" File A: Datasets (.txt) A1: Webex A2: Zoom A3: Teams A4: Word A5: PowerPoint A6: Excel File B: Python Code (Both ours and baseline) B1: adversarial_samples.ipynb B2: Baseline.ipynb FIle C: Result Tables (.xlsx) C1: Table of perturbed outputs in Webex C2: Table of perturbed outputs in Zoom C3: Table of perturbed outputs in Teams C4: Table of perturbed outputs in Word C5: Table of perturbed outputs in PowerPoint C6: Table of perturbed outputs in Excel (Excel) File D: Trend of Adversarial Shifts (Graphs) D1: Adversarial shifts of office suit (LSTM) D2: Adversarial shifts of video conferencing suit (LSTM) D3: Non-Adversarial shifts of office suit (LSTM) D4: Non-Adversarial shifts of video conferencing suit(LSTM) D5: Adversarial shifts of office suit (GRU) D6: Adversarial shifts of video conferencing suit (GRU) D7: Non-Adversarial shifts of office suit (GRU) D8: Non-Adversarial shifts of video conferencing suit(GRU) D9: Adversarial shifts of office suit (Bi-LSTM) D10: Adversarial shifts of video conferencing suit (Bi-LSTM) D11: Non-Adversarial shifts of office suit (Bi-LSTM) D12: Non-Adversarial shifts of video conferencing suit(Bi-LSTM) File E: Adversarial Examples (.pdf) E1: Adversarial vs original in Webex E2: Adversarial vs original in Zoom E3: Adversarial vs original in Teams E4: Adversarial vs original in Word E5: Adversarial vs original in PowerPoint E6: Adversarial vs original in Excel File F: Questionnaire
DOI: 10.5281/zenodo.6012866
title: Replication Data for: IQ, Expectations, and Choice

description: This package contains all the code necessary for reproducing the tables and figures in: D'Acunto, F, Hoang, D., Paloviita, M., and Weber. M. 2021. IQ. Expectations, and Choice. Review of Economic Studies, forthcoming. The package also provides information on how to access the raw data.
DOI: 10.5281/zenodo.6522336
title: Replication Data for: IQ, Expectations, and Choice

description: This package contains all the code necessary for reproducing the tables and figures in: D'Acunto, F, Hoang, D., Paloviita, M., and Weber. M. 2021. IQ. Expectations, and Choice. Review of Economic Studies, forthcoming. The package also provides information on how to access the raw data.
DOI: 10.5281/zenodo.6012865
title: Replication Data for: IQ, Expectations, and Choice

description: This package contains all the code necessary for reproducing the tables and figures in: D'Acunto, F, Hoang, D., Paloviita, M., and Weber. M. 2021. IQ. Expectations, and Choice. Review of Economic Studies, forthcoming. The package also provides information on how to access the raw data.
DOI: 10.5281/zenodo.6990966
title: Replication Data for: IQ, Expectations, and Choice

description: This package contains all the code necessary for reproducing the tables and figures in: D'Acunto, F, Hoang, D., Paloviita, M., and Weber. M. 2021. IQ. Expectations, and Choice. Review of Economic Studies, forthcoming. The package also provides information on how to access the raw data.
DOI: 10.34740/kaggle/dsv/4144391
title: Film Set Accidents
DOI: 10.5281/zenodo.7035667
title: Datasets for reproducing "Robust Modelling of Internet Delay and Smart Monitoring Schemes for the Automation of Overlay Networks"

description: This upload contains the datasets necessary to reproduce the figures and the results of my PhD thesis titled "Robust Modelling of Internet Delay and Smart Monitoring Schemes for the Automation of Overlay Networks" (2020). These datasets are derived from public sources: CAIDA MANIC and RIPE Atlas.
DOI: 10.5281/zenodo.7035666
title: Datasets for reproducing "Robust Modelling of Internet Delay and Smart Monitoring Schemes for the Automation of Overlay Networks"

description: This upload contains the datasets necessary to reproduce the figures and the results of my PhD thesis titled "Robust Modelling of Internet Delay and Smart Monitoring Schemes for the Automation of Overlay Networks" (2020). These datasets are derived from public sources: CAIDA MANIC and RIPE Atlas.
DOI: 10.5517/ccdc.csd.cc26mvg5
title: CCDC 2044867: Experimental Crystal Structure Determination

description: Related Article: Ruitao Li, Dafu Yuan, Mengqi Ping, Yuyi Zhu, Shaofei Ni, Ming Li, Lirong Wen, Lin-Bao Zhang|2022|Chemical Science|13|9940|doi:10.1039/D2SC01175A
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.cc26mw7z
title: CCDC 2044891: Experimental Crystal Structure Determination

description: Related Article: Ruitao Li, Dafu Yuan, Mengqi Ping, Yuyi Zhu, Shaofei Ni, Ming Li, Lirong Wen, Lin-Bao Zhang|2022|Chemical Science|13|9940|doi:10.1039/D2SC01175A
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.cc27hz80
title: CCDC 2070932: Experimental Crystal Structure Determination

description: Related Article: Xian Fei, San Zhang, Dong Zhai, Zhiwei Wang, Jin-Liang Lin, Qi Xiao, Chun-Lin Sun, Weiqiao Deng, Chunfeng Zhang, Wenping Hu, Hao-Li Zhang|2022|Chemical Science|13|9914|doi:10.1039/D2SC00263A
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.cc2bb0nc
title: CCDC 2154582: Experimental Crystal Structure Determination

description: Related Article: Lucile Hamon, Iryna Andrusenko, Aurelio Borzì, Michael Stiefel, Stephan Carl, Ruggero Frison, Antonio Cervellino, Mauro Gemmi, Gustavo Santiso-Quinones, Eric Hovestreydt, Antonia Neels, Ines E. Collings|2022|Mat.Advs.|3|6869|doi:10.1039/D2MA00389A
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.cc2bt56k
title: CCDC 2169138: Experimental Crystal Structure Determination

description: Related Article: Ethan J. Crace, Alexander C. Su, Hemamala I. Karunadasa|2022|Chemical Science|13|9973|doi:10.1039/D2SC02381D
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.cc2bt58m
title: CCDC 2169140: Experimental Crystal Structure Determination

description: Related Article: Ethan J. Crace, Alexander C. Su, Hemamala I. Karunadasa|2022|Chemical Science|13|9973|doi:10.1039/D2SC02381D
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.cc2bt59n
title: CCDC 2169141: Experimental Crystal Structure Determination

description: Related Article: Ethan J. Crace, Alexander C. Su, Hemamala I. Karunadasa|2022|Chemical Science|13|9973|doi:10.1039/D2SC02381D
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.cc2bt5bp
title: CCDC 2169142: Experimental Crystal Structure Determination

description: Related Article: Ethan J. Crace, Alexander C. Su, Hemamala I. Karunadasa|2022|Chemical Science|13|9973|doi:10.1039/D2SC02381D
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.cc2bt5cq
title: CCDC 2169143: Experimental Crystal Structure Determination

description: Related Article: Ethan J. Crace, Alexander C. Su, Hemamala I. Karunadasa|2022|Chemical Science|13|9973|doi:10.1039/D2SC02381D
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.cc2bt5dr
title: CCDC 2169144: Experimental Crystal Structure Determination

description: Related Article: Ethan J. Crace, Alexander C. Su, Hemamala I. Karunadasa|2022|Chemical Science|13|9973|doi:10.1039/D2SC02381D
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.cc2bt5fs
title: CCDC 2169145: Experimental Crystal Structure Determination

description: Related Article: Ethan J. Crace, Alexander C. Su, Hemamala I. Karunadasa|2022|Chemical Science|13|9973|doi:10.1039/D2SC02381D
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.cc2bwxsy
title: CCDC 2171791: Experimental Crystal Structure Determination

description: Related Article: Ruitao Li, Dafu Yuan, Mengqi Ping, Yuyi Zhu, Shaofei Ni, Ming Li, Lirong Wen, Lin-Bao Zhang|2022|Chemical Science|13|9940|doi:10.1039/D2SC01175A
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.