cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22194397
title: Design of a Line-of-Sight Fluorescence-Based Imaging Diagnostic for Classification of Microbe Species

description: This data set contains corrected two-color fluorescence intensity image data from 44 bacterial smears presented in the associated journal article, along with summary statistics, fluorescence spectra, and fluorescence intensity ratio histograms. <br> <strong>Article: </strong>Herzog et al 2023 <em>Meas. Sci. Technol.</em> https://doi.org/10.1088/1361-6501/acd711 <br> The individual files are as files: <br> <strong>Corrected two-color fluorescence image data</strong> B.cereus.tif B.subtilis.tif E.coli.tif M.luteus.tif Mold.tif P.fluorescens.tif R.rubrum.tif S.marcescens.tif <br> Each file contains three-channel, 16-bit per sample image stacks. The Red and Blue image channels contain the corrected Red- and Blue-band fluorescence intensity data, respectively. Images were registered and corrected for LED intensity profile variation before storing. Each image corresponds to a different microbial smear. Image data is stored as 16-bit integers, although the raw data range is only 10-bit; typical intensity values are on the order of 1000. <br> It is recommended that ImageJ or a similar viewer be used to view the red and blue color channels independently with an appropriate scale. <br> <strong>Summary data</strong> Summary.xlsx <br> This file contains a table of summary statistics from each of the 44 analyzed microbial smears. The columns are as follows: <br> Species: Name of the microbial species Exposure: Exposure duration (UV LED and camera) in ms Ratio: Most common ratio value (i.e., the mode of the ratio histogram) Red: Median corrected red-band fluorescence intensity in counts Blue: Median corrected blue-band fluorescence intensity in counts R_fwhm: Full-width at half maximum of the ratio PDF sR: Standard deviation of the corrected red-band fluorescence intensity in counts sB: Standard deviation of the corrected blue-band fluorescence intensity in counts R0: Median raw red-band fluorescence intensity in counts B0: Median raw blue-band fluorescence intensity in counts sR0: Standard deviation of the raw red-band fluorescence intensity in counts sB0: Standard deviation of the raw blue-band fluorescence intensity in counts <br> <strong>Histogram data</strong> Histogram.csv <br> Comma-separated histogram data, smoothed using a 7-bin wide 2nd order Savitzky-Golay filter. Each histogram is stored as a separate block with the format: <br> [Name] [Comma-separated ratio bin values] [Comma-separated smoothed count values] <br> <strong>Spectroscopy data</strong> Spectra.csv <br> Comma-separated fluorescence spectra data, smoothed using a 10.5 nm wide 1st order Savitzky-Golay filter. Data was corrected for background and relative spectral response, then normalized by its integral and scaled by a factor of 100. Each histogram is stored as a separate block with the format: <br> [Species name] [Comma-separated wavelength values] [Comma-separated normalized corrected intensity values x 100]
DOI: 10.6084/m9.figshare.22194397.v1
title: Design of a Line-of-Sight Fluorescence-Based Imaging Diagnostic for Classification of Microbe Species

description: This data set contains corrected two-color fluorescence intensity image data from 44 bacterial smears presented in the associated journal article, along with summary statistics, fluorescence spectra, and fluorescence intensity ratio histograms. <br> <strong>Article: </strong>Herzog et al 2023 <em>Meas. Sci. Technol.</em> https://doi.org/10.1088/1361-6501/acd711 <br> The individual files are as files: <br> <strong>Corrected two-color fluorescence image data</strong> B.cereus.tif B.subtilis.tif E.coli.tif M.luteus.tif Mold.tif P.fluorescens.tif R.rubrum.tif S.marcescens.tif <br> Each file contains three-channel, 16-bit per sample image stacks. The Red and Blue image channels contain the corrected Red- and Blue-band fluorescence intensity data, respectively. Images were registered and corrected for LED intensity profile variation before storing. Each image corresponds to a different microbial smear. Image data is stored as 16-bit integers, although the raw data range is only 10-bit; typical intensity values are on the order of 1000. <br> It is recommended that ImageJ or a similar viewer be used to view the red and blue color channels independently with an appropriate scale. <br> <strong>Summary data</strong> Summary.xlsx <br> This file contains a table of summary statistics from each of the 44 analyzed microbial smears. The columns are as follows: <br> Species: Name of the microbial species Exposure: Exposure duration (UV LED and camera) in ms Ratio: Most common ratio value (i.e., the mode of the ratio histogram) Red: Median corrected red-band fluorescence intensity in counts Blue: Median corrected blue-band fluorescence intensity in counts R_fwhm: Full-width at half maximum of the ratio PDF sR: Standard deviation of the corrected red-band fluorescence intensity in counts sB: Standard deviation of the corrected blue-band fluorescence intensity in counts R0: Median raw red-band fluorescence intensity in counts B0: Median raw blue-band fluorescence intensity in counts sR0: Standard deviation of the raw red-band fluorescence intensity in counts sB0: Standard deviation of the raw blue-band fluorescence intensity in counts <br> <strong>Histogram data</strong> Histogram.csv <br> Comma-separated histogram data, smoothed using a 7-bin wide 2nd order Savitzky-Golay filter. Each histogram is stored as a separate block with the format: <br> [Name] [Comma-separated ratio bin values] [Comma-separated smoothed count values] <br> <strong>Spectroscopy data</strong> Spectra.csv <br> Comma-separated fluorescence spectra data, smoothed using a 10.5 nm wide 1st order Savitzky-Golay filter. Data was corrected for background and relative spectral response, then normalized by its integral and scaled by a factor of 100. Each histogram is stored as a separate block with the format: <br> [Species name] [Comma-separated wavelength values] [Comma-separated normalized corrected intensity values x 100]
DOI: 10.6084/m9.figshare.23146127
title: Data in the article "Determination of the Unknown Eddy Diffusion in the Venus Clouds from the VeRa Sulfuric Acid Observations"

description: This is the data for the figures in the article "Determination of the Unknown Eddy Diffusion in the Venus Clouds from the VeRa Sulfuric Acid Observations".
DOI: 10.6084/m9.figshare.23146127.v1
title: Data in the article "Determination of the Unknown Eddy Diffusion in the Venus Clouds from the VeRa Sulfuric Acid Observations"

description: This is the data for the figures in the article "Determination of the Unknown Eddy Diffusion in the Venus Clouds from the VeRa Sulfuric Acid Observations".
DOI: 10.5281/zenodo.7966521
title: Petty bribery, pluralistic ignorance, and the collective action problem

description: Corruption in the form of bribery for access to public goods and services remains a widespread and seemingly innocuous practice which disproportionately targets the poor and helps keep them poor. Furthermore, the aggregate effects of bribery in the form of small payments erode the legitimacy of government institutions and their capacity to fairly administer public goods and services as well as protection under the law. Drawing on original evidence using social norms methodology, this research tests underlying beliefs and expectations which sustain persistent forms of bribery and draws attention to its association with pluralistic ignorance and consequent collective action problems. With examples focused on bribery in traffic law enforcement, healthcare, and education – three critical areas where bribery is often identified as an entrenched and systematic practice – this paper contributes new evidence of: i) the presence of pluralistic ignorance, a common social comparison error, in bribe-giving behaviour; ii) differing social evaluations of bribe-solicitation and finally, iii) how this context might exacerbate collective action problems. This empirical case study of Nigeria shows that even though more people are likely to be directly affected by bribery during routine interactions with public officials and institutions and many believe this practice is wrong, most people incorrectly believe that others in their community tolerate or even accept bribery behaviour.
DOI: 10.5281/zenodo.7966520
title: Petty bribery, pluralistic ignorance, and the collective action problem

description: Corruption in the form of bribery for access to public goods and services remains a widespread and seemingly innocuous practice which disproportionately targets the poor and helps keep them poor. Furthermore, the aggregate effects of bribery in the form of small payments erode the legitimacy of government institutions and their capacity to fairly administer public goods and services as well as protection under the law. Drawing on original evidence using social norms methodology, this research tests underlying beliefs and expectations which sustain persistent forms of bribery and draws attention to its association with pluralistic ignorance and consequent collective action problems. With examples focused on bribery in traffic law enforcement, healthcare, and education – three critical areas where bribery is often identified as an entrenched and systematic practice – this paper contributes new evidence of: i) the presence of pluralistic ignorance, a common social comparison error, in bribe-giving behaviour; ii) differing social evaluations of bribe-solicitation and finally, iii) how this context might exacerbate collective action problems. This empirical case study of Nigeria shows that even though more people are likely to be directly affected by bribery during routine interactions with public officials and institutions and many believe this practice is wrong, most people incorrectly believe that others in their community tolerate or even accept bribery behaviour.
DOI: 10.6084/m9.figshare.23057276
title: tree_all.nwk

description: Phylogenetic tree for "The predictive power of phylogeny on growth rates in soil bacterial communities" by J. Walkup et al. 2023.
DOI: 10.6084/m9.figshare.23145542
title: Bacterial relative growth rates and taxonomic identities

description: Dataset for "The predictive power of phylogeny on growth rates in soil bacterial communities" by J. Walkup et al. 2023. This dataset includes bacterial growth rates and taxonomic identities of organisms observed in this study.
DOI: 10.6084/m9.figshare.21764185.v1
title: Comparison of SMOS, SMAP and <i>In Situ</i> Sea Surface Salinity in the Gulf of St. Lawrence

description: The Gulf of St. Lawrence (GSL) is an Eastern Canada semi-enclosed sea under the influence of the freshwater discharge from the Great Lakes – St. Lawrence River drainage basin. Studying the variability of oceanographic conditions in the GSL under a changing climate is important for ecosystem and fisheries management. To supplement the available <i>in situ</i> sea surface salinity (SSS) measurements with satellite SSS data, this study compares all available years of Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active and Passive (SMAP) satellite SSS to <i>in situ</i> SSS observations. Despite the relatively cold water and proximity to land and sea ice, the satellite SSS is able to capture the interannual variability and annual cycle of SSS in the GSL, with correlations ranging from 0.80 to 0.85 in the Southern GSL, and 0.22 to 0.77 in the Northern GSL. All satellite SSS data products were able to detect the very low salinity year of 2017 in the Southern GSL.
DOI: 10.34740/kaggle/dsv/5765292
title: Nigerian Presidential Election 2023 Tweets
DOI: 10.5281/zenodo.7966559
title: CRT23-data

description: Data associated with Cattiaux, Ribes and Thompson (2023), Searching for the most extreme temperature events in recent history, submitted to BAMS.
DOI: 10.5281/zenodo.7966558
title: CRT23-data

description: Data associated with Cattiaux, Ribes and Thompson (2023), Searching for the most extreme temperature events in recent history, submitted to BAMS.
DOI: 10.6084/m9.figshare.23146064
title: Development of Innovation Districts: A Performance Assessment

description: Global challenges demand more competitiveness from cities, calling for quick adaptation to changes brought about by the current knowledge economy. Innovation Districts (ID) stand out as the most favourable ecosystems to create economic, urban, social and governance solutions proactively and at the speed demanded by this rapid renewal of knowledge. Effective assessment is important in these areas to ensure efforts are guided to achieve the objectives set. Following validation by a panel of 17 experts through an international Fuzzy Delphi survey, and 15 experts in the DEMATEL multi-criteria decision-making approach, this study builds a conceptual framework in four dimensions (Urban, Economic, Social and Governance), with a set of 37 indicators identified as relevant to assess performance in ID and the power of influences among them. The resulting multidimensional innovation assessment framework is a powerful tool, being useful in determining the key impact indicators of existing innovation districts.
DOI: 10.6084/m9.figshare.23146064.v1
title: Development of Innovation Districts: A Performance Assessment

description: Global challenges demand more competitiveness from cities, calling for quick adaptation to changes brought about by the current knowledge economy. Innovation Districts (ID) stand out as the most favourable ecosystems to create economic, urban, social and governance solutions proactively and at the speed demanded by this rapid renewal of knowledge. Effective assessment is important in these areas to ensure efforts are guided to achieve the objectives set. Following validation by a panel of 17 experts through an international Fuzzy Delphi survey, and 15 experts in the DEMATEL multi-criteria decision-making approach, this study builds a conceptual framework in four dimensions (Urban, Economic, Social and Governance), with a set of 37 indicators identified as relevant to assess performance in ID and the power of influences among them. The resulting multidimensional innovation assessment framework is a powerful tool, being useful in determining the key impact indicators of existing innovation districts.
DOI: 10.5281/zenodo.7958518
title: Data for 'CFL Optimized Forward-Backward Runge-Kutta Schemes for the Shallow Water Equations'

description: The data generated for 'CFL Optimized Forward-Backward Runge-Kutta Schemes for the Shallow Water Equations' submitted to the Monthly Weather Review. This includes the model output used to generate vorticity plots, model output to generate convergence plots, and log files from CFL performance experiments.
DOI: 10.5281/zenodo.7958517
title: Data for 'CFL Optimized Forward-Backward Runge-Kutta Schemes for the Shallow Water Equations'

description: The data generated for 'CFL Optimized Forward-Backward Runge-Kutta Schemes for the Shallow Water Equations' submitted to the Monthly Weather Review. This includes the model output used to generate vorticity plots, model output to generate convergence plots, and log files from CFL performance experiments.
DOI: 10.6084/m9.figshare.23146826
title: Dataset for Goodreads investigation project

description: Investigating Goodreads reviews to perform sentiment analysis and keyword extraction about popular books.
DOI: 10.6084/m9.figshare.23059934
title: Labeler's vote and Kappa calculation

description: <strong>A Study on Classifying Stack Overflow Questions Based on Difficulty<br> by Utilizing Contextual Features</strong> <br> All Rater's Label: Consist of all the labels given by the rater's Fleiss Kappa: The kappa value calculation on the rater's inter-agreeability.
DOI: 10.6084/m9.figshare.23059934.v1
title: Labeler's vote and Kappa calculation

description: <strong>A Study on Classifying Stack Overflow Questions Based on Difficulty<br> by Utilizing Contextual Features</strong> <br> All Rater's Label: Consist of all the labels given by the rater's Fleiss Kappa: The kappa value calculation on the rater's inter-agreeability.
DOI: 10.5281/zenodo.7966824
title: Dataset of Flow Velocity Prediction in Vegetated Alluvial Channels Comparing Empirical and State-of-the-art Hybrid Machine Learning Models

description: We compiled 447 datasets from different sources and lab- and field-based measurements. These datasets included Einstein and Banks (1950), Fenzl (1962), Kouwen et al. (1969), Ree and Crow (1977), Murota (1984), Tsujimoto and Kitamura (1990), Tsujimoto (1991), Tsujimoto (1993), Shimizu (1994), Dunn et al. (1996), Ikeda and Kanazawa (1996), Meijer (1998), Jarvela (2002), Rowinski and Kubrak (2002), Stone and Shen (2002), Poggi et al. (2004), Carollo et al. (2005), and Murphy et al. (2007).
DOI: 10.5281/zenodo.7966823
title: Dataset of Flow Velocity Prediction in Vegetated Alluvial Channels Comparing Empirical and State-of-the-art Hybrid Machine Learning Models

description: We compiled 447 datasets from different sources and lab- and field-based measurements. These datasets included Einstein and Banks (1950), Fenzl (1962), Kouwen et al. (1969), Ree and Crow (1977), Murota (1984), Tsujimoto and Kitamura (1990), Tsujimoto (1991), Tsujimoto (1993), Shimizu (1994), Dunn et al. (1996), Ikeda and Kanazawa (1996), Meijer (1998), Jarvela (2002), Rowinski and Kubrak (2002), Stone and Shen (2002), Poggi et al. (2004), Carollo et al. (2005), and Murphy et al. (2007).
DOI: 10.48567/hmwz-2w31
title: Marble Point Automatic Weather Station, 1996 quality-controlled observational data.
DOI: 10.5517/ccdc.csd.cc28jg9l
title: CCDC 2101189: Experimental Crystal Structure Determination

description: Related Article: Hui-Lin Hu, Xiaoyu Ren, Jiajia He, Lixiang Zhu, Siqiang Fang, Zhishan Su, Tianli Wang|2022|Sci.China.Chem.|65|2500|doi:10.1007/s11426-022-1337-3
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.7966830
title: Functional Near-Infrared Spectroscopy Reveals Delayed Hemodynamic Changes in the Primary Motor Cortex During Fine Motor Tasks and Decreased Interhemispheric Connectivity in Parkinson's Disease Patients

description: This dataset contains functional near-infrared spectroscopy (fNIRS) data from 20 patients with Parkinson’s disease and 20 age- and sex-matched healthy subjects without movement disorders. There are 3 folders, each corresponding to a different task: a 10-second finger-tapping task, a 2-minute walking task, and a 6-minute resting-state
DOI: 10.5281/zenodo.7896751
title: Accident dataset RUSSIA 2022-2023

description: some big description
DOI: 10.5281/zenodo.7896750
title: Car crash dataset RUSSIA 2022-2023

description: Car crash dataset RUSSIA 2022-2023 is a big driving video dataset that contains over 545 high-resolution videos of various driving scenarios. The dataset was created to aid the development and testing of autonomous driving systems and other related technologies. It includes videos from Russia, captured from a diverse set of locations, weather conditions, and lighting conditions, each video lasting about 10 seconds. The videos are annotated with bounding boxes around objects such as different types of cars, pedestrians, and cyclists, as well as traffic signs, and traffic lights. Additionally, the dataset includes metadata information for each video. For each video there is a json file, which includes labelling of this video. Also,there are csv files, which include framing for an accident. Car crash dataset RUSSIA 2022-2023 is considered to be one of the few datasets from Russia on this topic. Created by 7 students from Moscow, MIEM HSE. First version published on 4th May, 2023.
DOI: 10.5281/zenodo.7901387
title: Accident dataset RUSSIA 2022-2023

description: some big description
DOI: 10.5281/zenodo.7901493
title: Car crash dataset RUSSIA 2022-2023

description: Car crash dataset RUSSIA 2022-2023 is a big driving video dataset that contains over 500 high-resolution videos of various driving scenarios. The dataset was created to aid the development and testing of autonomous driving systems and other related technologies. It includes videos from Russia, captured from a diverse set of locations, weather conditions, and lighting conditions, each video lasting about 10 seconds. The videos are annotated with bounding boxes around objects such as different types of cars, pedestrians, and cyclists, as well as traffic signs, and traffic lights. Additionally, the dataset includes metadata information for each video.Car crash dataset RUSSIA 2022-2023 is considered to be one of the few datasets from Russia on this topic. Created by 7 students from Moscow, MIEM HSE. First version published on 4th May, 2023.
DOI: 10.5281/zenodo.7904820
title: Car crash dataset RUSSIA 2022-2023

description: Car crash dataset RUSSIA 2022-2023 is a big driving video dataset that contains over 545 high-resolution videos of various driving scenarios. The dataset was created to aid the development and testing of autonomous driving systems and other related technologies. It includes videos from Russia, captured from a diverse set of locations, weather conditions, and lighting conditions, each video lasting about 10 seconds. The videos are annotated with bounding boxes around objects such as different types of cars, pedestrians, and cyclists, as well as traffic signs, and traffic lights. Additionally, the dataset includes metadata information for each video. For each video there is a json file, which includes labelling of this video. Also,there are csv files, which include framing for an accident. Car crash dataset RUSSIA 2022-2023 is considered to be one of the few datasets from Russia on this topic. Created by 7 students from Moscow, MIEM HSE. First version published on 4th May, 2023.
DOI: 10.5281/zenodo.7920737
title: Car crash dataset RUSSIA 2022-2023

description: Car crash dataset RUSSIA 2022-2023 is a big driving video dataset that contains over 545 high-resolution videos of various driving scenarios. The dataset was created to aid the development and testing of autonomous driving systems and other related technologies. It includes videos from Russia, captured from a diverse set of locations, weather conditions, and lighting conditions, each video lasting about 10 seconds. The videos are annotated with bounding boxes around objects such as different types of cars, pedestrians, and cyclists, as well as traffic signs, and traffic lights. Additionally, the dataset includes metadata information for each video. For each video there is a json file, which includes labelling of this video. Also,there are csv files, which include framing for an accident. Car crash dataset RUSSIA 2022-2023 is considered to be one of the few datasets from Russia on this topic. Created by 7 students from Moscow, MIEM HSE. First version published on 4th May, 2023.
DOI: 10.6084/m9.figshare.23147468
title: Questionnaire data from "Comparative study of attitudes and perceptions of university students in Business Administration and Management and in Education towards Artificial Intelligence".

description: Questionnaire data from "Comparative study of attitudes and perceptions of university students in Business Administration and Management and in Education towards Artificial Intelligence".
DOI: 10.5517/ccdc.csd.cc2b5d1z
title: CCDC 2150130: Experimental Crystal Structure Determination

description: Related Article: Yusuke Ano, Sakura Takahashi, Naoto Chatani|2023|Org.Lett.|25|3266|doi:10.1021/acs.orglett.3c01008
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.