cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22010048.v2
title: OSER assay in HeLa cells

description: Randomly picked images of HeLa cells expressing Cyt-ERM fusion, used for OSER assay. See barcoding for corresponding protein. Complete dataset available upon request. Recent progress in fluorescent protein development has generated a large diversity of near-infrared fluorescent proteins, which are rapidly becoming popular probes for a variety of imaging applications. To assist end-users with a selection of the right near-infrared fluorescent protein for a given application, we conducted a quantitative assessment of intracellular brightness, photostability, oligomeric state, and cytotoxicity of 22 near-infrared fluorescent proteins in cultured HEK cells and primary mouse neurons. The top-performing proteins were further validated for <em>in vivo</em> imaging of neurons in <em>C. elegans</em>, zebrafish, and mice as well as in liver of mice. We also assessed the applicability of the selected NIR FPs for multi-color imaging of fusions, expansion microscopy, and two-photon imaging.
DOI: 10.6084/m9.figshare.22010048.v1
title: OSER assay in HeLa cells

description: Randomly picked images of HeLa cells expressing Cyt-ERM fusion, used for OSER assay. See barcoding for corresponding protein. Complete dataset available upon request. Recent progress in fluorescent protein development has generated a large diversity of near-infrared fluorescent proteins, which are rapidly becoming popular probes for a variety of imaging applications. To assist end-users with a selection of the right near-infrared fluorescent protein for a given application, we conducted a quantitative assessment of intracellular brightness, photostability, oligomeric state, and cytotoxicity of 22 near-infrared fluorescent proteins in cultured HEK cells and primary mouse neurons. The top-performing proteins were further validated for <em>in vivo</em> imaging of neurons in <em>C. elegans</em>, zebrafish, and mice as well as in liver of mice. We also assessed the applicability of the selected NIR FPs for multi-color imaging of fusions, expansion microscopy, and two-photon imaging.
DOI: 10.6084/m9.figshare.22010099.v1
title: NIR FP brightness in C elegans

description: Complete dataset of brightness imaging in C elegans. See barcoding file for corresponding protein. Recent progress in fluorescent protein development has generated a large diversity of near-infrared fluorescent proteins, which are rapidly becoming popular probes for a variety of imaging applications. To assist end-users with a selection of the right near-infrared fluorescent protein for a given application, we conducted a quantitative assessment of intracellular brightness, photostability, oligomeric state, and cytotoxicity of 22 near-infrared fluorescent proteins in cultured HEK cells and primary mouse neurons. The top-performing proteins were further validated for <em>in vivo</em> imaging of neurons in <em>C. elegans</em>, zebrafish, and mice as well as in liver of mice. We also assessed the applicability of the selected NIR FPs for multi-color imaging of fusions, expansion microscopy, and two-photon imaging.
DOI: 10.6084/m9.figshare.22010126.v2
title: NIR FPs photostability C elegans

description: Randomly picked photostability imaging of one C elegans line in Cy5-LP and Cy5.5. Complete dataset available upon request. Recent progress in fluorescent protein development has generated a large diversity of near-infrared fluorescent proteins, which are rapidly becoming popular probes for a variety of imaging applications. To assist end-users with a selection of the right near-infrared fluorescent protein for a given application, we conducted a quantitative assessment of intracellular brightness, photostability, oligomeric state, and cytotoxicity of 22 near-infrared fluorescent proteins in cultured HEK cells and primary mouse neurons. The top-performing proteins were further validated for <em>in vivo</em> imaging of neurons in <em>C. elegans</em>, zebrafish, and mice as well as in liver of mice. We also assessed the applicability of the selected NIR FPs for multi-color imaging of fusions, expansion microscopy, and two-photon imaging.
DOI: 10.6084/m9.figshare.22010126.v1
title: NIR FPs photostability C elegans

description: Randomly picked photostability imaging of one C elegans line in Cy5-LP and Cy5.5. Complete dataset available upon request. Recent progress in fluorescent protein development has generated a large diversity of near-infrared fluorescent proteins, which are rapidly becoming popular probes for a variety of imaging applications. To assist end-users with a selection of the right near-infrared fluorescent protein for a given application, we conducted a quantitative assessment of intracellular brightness, photostability, oligomeric state, and cytotoxicity of 22 near-infrared fluorescent proteins in cultured HEK cells and primary mouse neurons. The top-performing proteins were further validated for <em>in vivo</em> imaging of neurons in <em>C. elegans</em>, zebrafish, and mice as well as in liver of mice. We also assessed the applicability of the selected NIR FPs for multi-color imaging of fusions, expansion microscopy, and two-photon imaging.
DOI: 10.6084/m9.figshare.22013591.v1
title: MSA of Actinomycetota ClpIb

description: Multiple sequence alignment in FASTA format of ClpIb sequences from Actinomycetota.
DOI: 10.6084/m9.figshare.22013591
title: MSA of Actinomycetota ClpIb

description: Multiple sequence alignment in FASTA format of ClpIb sequences from Actinomycetota.
DOI: 10.6084/m9.figshare.22013519
title: MSA of Actinomycetota ClpIa

description: Multiple sequence alignment in FASTA format of ClpIa enzymes from Actinomycetota
DOI: 10.6084/m9.figshare.22013519.v1
title: MSA of Actinomycetota ClpIa

description: Multiple sequence alignment in FASTA format of ClpIa enzymes from Actinomycetota
DOI: 10.6084/m9.figshare.22013180
title: MSA of Actinomycetota ClpC

description: Multiple sequence alignment in FASTA format of clpC enzymes from Actinomycetota
DOI: 10.6084/m9.figshare.22013180.v1
title: MSA of Actinomycetota ClpC

description: Multiple sequence alignment in FASTA format of clpC enzymes from Actinomycetota
DOI: 10.6084/m9.figshare.22013162
title: MSA of Actinomycetota ClpB

description: Multiple sequence alignment in FASTA format of ClpB enzymes from Actinomycetota
DOI: 10.6084/m9.figshare.22013162.v1
title: MSA of Actinomycetota ClpB

description: Multiple sequence alignment in FASTA format of ClpB enzymes from Actinomycetota
DOI: 10.6084/m9.figshare.22013201.v2
title: Barcoding

description: Plasmid barcoding used during experiments, so that experimentators were blinded to the proteins' identity. Recent progress in fluorescent protein development has generated a large diversity of near-infrared fluorescent proteins, which are rapidly becoming popular probes for a variety of imaging applications. To assist end-users with a selection of the right near-infrared fluorescent protein for a given application, we conducted a quantitative assessment of intracellular brightness, photostability, oligomeric state, and cytotoxicity of 22 near-infrared fluorescent proteins in cultured HEK cells and primary mouse neurons. The top-performing proteins were further validated for <em>in vivo</em> imaging of neurons in <em>C. elegans</em>, zebrafish, and mice as well as in liver of mice. We also assessed the applicability of the selected NIR FPs for multi-color imaging of fusions, expansion microscopy, and two-photon imaging.
DOI: 10.6084/m9.figshare.22013201.v1
title: Barcoding

description: Plasmid barcoding used during experiments, so that experimentators were blinded to the proteins' identity. Recent progress in fluorescent protein development has generated a large diversity of near-infrared fluorescent proteins, which are rapidly becoming popular probes for a variety of imaging applications. To assist end-users with a selection of the right near-infrared fluorescent protein for a given application, we conducted a quantitative assessment of intracellular brightness, photostability, oligomeric state, and cytotoxicity of 22 near-infrared fluorescent proteins in cultured HEK cells and primary mouse neurons. The top-performing proteins were further validated for <em>in vivo</em> imaging of neurons in <em>C. elegans</em>, zebrafish, and mice as well as in liver of mice. We also assessed the applicability of the selected NIR FPs for multi-color imaging of fusions, expansion microscopy, and two-photon imaging.
DOI: 10.6084/m9.figshare.22013216.v2
title: Support Materials

description: Support Materials
DOI: 10.6084/m9.figshare.22013216
title: Support Materials

description: Support Materials
DOI: 10.6084/m9.figshare.22013216.v1
title: Support Materials

description: Support Materials
DOI: 10.6084/m9.figshare.22014203.v1
title: Indo-Pacific region data.xlsx

description: We survey the Indo-Pacific understanding of QUAD members using data taken from defence white papers or defence strategy reports from Australia, India, Japan, and the U.S. The data cover from the first mention of the Indo-Pacific to the last published one. In this scope, analyze Australia’s 2013, 2016 Defence White Papers, and 2020 Strategic Updates; India’s 2015-2016, 2016-2017, 2017-2018, 2018-2019, 2019-2020 Ministry of Defence’s Annual Reports; Japan’s 2018, 2019, 2020, 2021 and 2022 Defence of Japan Documents[1], and the U.S’, 2017 National Security Strategy, 2018 and 2022 National Defence Strategy Documents. We used a mixed method during the data collection. [1] References are not included in the calculation of the Japanese defence paper.
DOI: 10.6084/m9.figshare.15172410
title: Relationships between cognitive pattern recognition and specific mathematical domains in mathematics education

description: The understanding of the relationships between pattern recognition and mathematical abilities is important for students in their learning of mathematics and mathematics teachers in the design of their teaching pedagogies. This study examines the connections between pattern recognition and mathematical abilities of students from four Singapore private schools (52.7% male and 47.3% female) in arithmetic, algebra and geometry. Two validated instruments are used to measure the cognitive skills. At the end of the study, it is found that the students have moderate mastery levels of pattern recognition and mathematical ability. The study also discovers that most of the correlations between pattern recognition and mathematical abilities in the domains of arithmetic, algebra, and geometry are statistically significant. This lent support to not only the results from recent studies but also indicates that the long-standing relationships between these two cognitive abilities remain valid.
DOI: 10.6084/m9.figshare.15172410.v1
title: Relationships between cognitive pattern recognition and specific mathematical domains in mathematics education

description: The understanding of the relationships between pattern recognition and mathematical abilities is important for students in their learning of mathematics and mathematics teachers in the design of their teaching pedagogies. This study examines the connections between pattern recognition and mathematical abilities of students from four Singapore private schools (52.7% male and 47.3% female) in arithmetic, algebra and geometry. Two validated instruments are used to measure the cognitive skills. At the end of the study, it is found that the students have moderate mastery levels of pattern recognition and mathematical ability. The study also discovers that most of the correlations between pattern recognition and mathematical abilities in the domains of arithmetic, algebra, and geometry are statistically significant. This lent support to not only the results from recent studies but also indicates that the long-standing relationships between these two cognitive abilities remain valid.
DOI: 10.6084/m9.figshare.22014203
title: nondata

description: We survey the Indo-Pacific understanding of QUAD members using data taken from defence white papers or defence strategy reports from Australia, India, Japan, and the U.S. The data cover from the first mention of the Indo-Pacific to the last published one. In this scope, analyze Australia’s 2013, 2016 Defence White Papers, and 2020 Strategic Updates; India’s 2015-2016, 2016-2017, 2017-2018, 2018-2019, 2019-2020 Ministry of Defence’s Annual Reports; Japan’s 2018, 2019, 2020, 2021 and 2022 Defence of Japan Documents[1], and the U.S’, 2017 National Security Strategy, 2018 and 2022 National Defence Strategy Documents. We used a mixed method during the data collection. [1] References are not included in the calculation of the Japanese defence paper.
DOI: 10.6084/m9.figshare.22014203.v2
title: Indo-Pacific region data.xlsx

description: We survey the Indo-Pacific understanding of QUAD members using data taken from defence white papers or defence strategy reports from Australia, India, Japan, and the U.S. The data cover from the first mention of the Indo-Pacific to the last published one. In this scope, analyze Australia’s 2013, 2016 Defence White Papers, and 2020 Strategic Updates; India’s 2015-2016, 2016-2017, 2017-2018, 2018-2019, 2019-2020 Ministry of Defence’s Annual Reports; Japan’s 2018, 2019, 2020, 2021 and 2022 Defence of Japan Documents[1], and the U.S’, 2017 National Security Strategy, 2018 and 2022 National Defence Strategy Documents. We used a mixed method during the data collection. [1] References are not included in the calculation of the Japanese defence paper.
DOI: 10.5281/zenodo.7608492
title: Data for "Mega forest fires intensify floods"

description: Data for the manuscript entitled "Mega forest fires intensify floods".
DOI: 10.5281/zenodo.7608706
title: Data for "Mega forest fires intensify floods"

description: Data for the manuscript entitled "Mega forest fires intensify floods".
DOI: 10.5281/zenodo.7178175
title: Data for "Mega forest fires intensify floods"

description: Data for the manuscript entitled "Mega forest fires intensify floods".
DOI: 10.5281/zenodo.7608667
title: Shock Induced Dilation - Validation data

description: Input files needed for running shock simulations in LIGGGHTS as well as the results of a single granular shock run. Full description is provided in Frizzell and Hartzell, 2023 - Simulation of Shock Induced Inertial Dilation at the Surface of an Unconfined Granular Assembly
DOI: 10.6084/m9.figshare.22014344
title: AJIAdata.xlsx

description: to be edited later
DOI: 10.6084/m9.figshare.22014344.v1
title: AJIAdata.xlsx

description: to be edited later
DOI: 10.5281/zenodo.6355086
title: Training and Testing Data, Associated Code, and WRF Code for ML-based nonhydrostatic alternative scheme in dynamical core of atmosphere

description: Data and codes for a nonhydrostatic alternative scheme (NAS) in dynamical core of atmosphere based on machine learning. In this new version, the randomly sampled training data samples testing data samples from nonhydrostatic simulations in WRF baraclinic wave test are provided. They are processed into a new data structure, which can be directly utilized in training and testing. Follow the instructions in README.txt and download the training and testing data, and the associated codes. Here we provide 3 parts of data and codes: 1, Training and testing data from WRF; 2, Training and testing codes for two machine learning emulators: machine learning and neural network 3, WRF application.
DOI: 10.5281/zenodo.6355085
title: Training and Testing Data, Associated Code, and WRF Code for ML-based nonhydrostatic alternative scheme in dynamical core of atmosphere

description: Data and codes for a nonhydrostatic alternative scheme (NAS) in dynamical core of atmosphere based on machine learning. In this new version, the randomly sampled training data samples testing data samples from nonhydrostatic simulations in WRF baraclinic wave test are provided. They are processed into a new data structure, which can be directly utilized in training and testing. Follow the instructions in README.txt and download the training and testing data, and the associated codes. Here we provide 3 parts of data and codes: 1, Training and testing data from WRF; 2, Training and testing codes for two machine learning emulators: machine learning and neural network 3, WRF application.
DOI: 10.6084/m9.figshare.22014332
title: Lab Package - Secondary Study on TDM Technologies

description: This package a set of analyzed data in the Secondary Study about TDM Technologies. It includes: (i) the list of selected papers in this review; (i) worksheet with detailed information about the TDM selected in this review. It support us in the data analysis. <br> This study was performed in February 2017. <br>
DOI: 10.6084/m9.figshare.22014332.v1
title: Lab Package - Secondary Study on TDM Technologies

description: This package a set of analyzed data in the Secondary Study about TDM Technologies. It includes: (i) the list of selected papers in this review; (i) worksheet with detailed information about the TDM selected in this review. It support us in the data analysis. <br> This study was performed in February 2017. <br>
DOI: 10.5281/zenodo.7608719
title: Australian collecting events for Robert Mesibov, 1973-2020

description: Dates, georeferenced locations and associated data for 3840 unique collecting events in Australia with Robert Mesibov as sole, primary or associated collector from 1973 to 2020. Version 2 adds several events and corrects and annotates my collections near Savage River, Tasmania in 1973 and 1974. Version 3 corrects the georeference for REM-event-2140. Version 4 corrects the date for REM-event-1950 and adds two "new" records (from 1994 and 1998). Version 5 adds two "new" records (from 1984 and 1991). Version 6 deletes REM-event-1946, which duplicated REM-event-1787. Version 7 is (I hope!) the final version. It adds some "new" records previously overlooked, corrects the georeferences for events 0042, 0244 and 0081, and deletes the "fieldNumber" field (which really only applied to samples, not events). Background: Mesibov RE (2021) An Australian collector's authority file, 1973–2020. Biodiversity Data Journal 9: e70463. https://doi.org/10.3897/BDJ.9.e70463
description: Tab-separated table with 23 fields and 3841 lines, UTF-8 encoded
DOI: 10.5281/zenodo.4990402
title: Australian collecting events for Robert Mesibov, 1973-2020

description: Dates, georeferenced locations and associated data for 3840 unique collecting events in Australia with Robert Mesibov as sole, primary or associated collector from 1973 to 2020. Version 2 adds several events and corrects and annotates my collections near Savage River, Tasmania in 1973 and 1974. Version 3 corrects the georeference for REM-event-2140. Version 4 corrects the date for REM-event-1950 and adds two "new" records (from 1994 and 1998). Version 5 adds two "new" records (from 1984 and 1991). Version 6 deletes REM-event-1946, which duplicated REM-event-1787. Version 7 is (I hope!) the final version. It adds some "new" records previously overlooked, corrects the georeferences for events 0042, 0244 and 0081, and deletes the "fieldNumber" field (which really only applied to samples, not events). Background: Mesibov RE (2021) An Australian collector's authority file, 1973–2020. Biodiversity Data Journal 9: e70463. https://doi.org/10.3897/BDJ.9.e70463
description: Tab-separated table with 23 fields and 3841 lines, UTF-8 encoded
DOI: 10.5519/qd.8pltm9zn
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (80 records)
DOI: 10.6084/m9.figshare.22014413
title: milled rice stored at low temperature

description: These data are the fungal growth, quality and volatiles changes of Yanfeng rice with moisture content of 15.6% at three low temperatures of 16, 18, and 20 °C storaged for a long term storage.
DOI: 10.6084/m9.figshare.22014413.v1
title: milled rice stored at low temperature

description: These data are the fungal growth, quality and volatiles changes of Yanfeng rice with moisture content of 15.6% at three low temperatures of 16, 18, and 20 °C storaged for a long term storage.
DOI: 10.6084/m9.figshare.22014491.v1
title: dft computational data.rar

description: The relevant QTAIM and NCI analysis files and the corresponding Gaussian 09 output files for the key intermediates and transition states
DOI: 10.6084/m9.figshare.19890313.v2
title: Amphibian color paper data and analysis code

description: Amphibian color dataset and analyses code for R. AmphiData.csv: Datafile MCCtree.nwk: the maximum clade credibility tree file. output.nex: 1,000 trimmed trees that we extracted from VertLife.com Analysis code.zip: analysis code in R format.
DOI: 10.5281/zenodo.7042354
title: How do CONTRIBUTING files support newcomers in Open Source projects?

description: Welcome to the replication package for the paper entitled "Do CONTRIBUTING files provide information about OSS newcomers' onboarding barriers?" <strong>Repository Structure </strong><br> Our package is divided in folders and it is organized as follows: <strong>app</strong>: This folder contains the implementation of our streamlit application, used to demonstrate the capabilities of our classification model. <strong>data</strong>: If you are looking for the data we have used for classification, this is the folder where it is located. This folder also contains the raw contributing files of each project analyzed, and the spreadsheets qualitatively analyzed by the authors. <strong>results</strong>: This folder contains all the files related to our results section. From the analysis of our classification model to the results of our online questionnaire. <strong>scripts</strong>: If you want to see the code we wrote during the whole classification process, including but not limited to the classification process, this is the folder you are looking for. <strong>survey</strong>: instrument used in the survey, raw answers and a spreadsheet with analyzed data. <strong>misc</strong>: This folder contains miscellaneous files that were not used in this paper, but support the statements of it (e.g. a screenshot of the top ten languages used on GitHub from the Octoverse website). <em>Each folder has its specific README.md with more specific details about their content.</em> <strong>I want to use your model!</strong><br> We are glad you are interested in our classification model. The final model is available as a `classification_model.sav` file inside the `app` folder that you can load using Pickle. If you are not familiar with Pickle or don't know how to load a model, we recommend you to take a look at our code implementation inside the `app` folder (`classify_content.py` is a good starting point).<br>