cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7284/142620
title: TSG (Thermosalinograph) data collected during research cruise LMG1309 using a SeaBird SBE-45 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142621
title: TSG (Thermosalinograph) data collected during research cruise LMG1309 using a SeaBird SBE-45 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142612
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise LMG1310 using a Hawaii UHDAS instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142601
title: Fluorometer data collected during research cruise LMG1310 using a WETLabs ECO-FL instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142602
title: Meteorological Station data collected during research cruise LMG1310 using a USAP RVDAS Metstation instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142603
title: Oxygen data collected during research cruise LMG1310 using a AANDERAA Optode 3975 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.25345/c59882z0g
title: MassIVE MSV000092868 - ArreSTick Motif is Responsible for GPCR-B-Arrestin Binding Stability and Extends Phosphorylation-Dependent B-arrestin Interactions to Non-Receptor Proteins
title: The binding and function of B-arrestins are regulated by specific phosphorylation motifs present in G protein-coupled receptors (GPCRs). However, the exact arrangement of phosphorylated amino acids responsible for establishing a stable interaction remains unclear. To investigate this pattern, we employed a 1D sequence convolution model trained on a dataset of GPCRs that have established B-arrestin binding properties. This approach allowed us to identify the amino acid pattern required for GPCRs to form stable interactions with B-arrestins. This motif was named 'arreSTick.' Our data show that the model predicts the strength of the coupling between GPCRs and B-arrestins with high accuracy, as well as the specific location of the interaction within the receptor sequence. Furthermore, we show that the arreSTick pattern is not limited to GPCRs, and is also present in numerous non-receptor proteins. Using a proximity biotinylation assay and mass spectrometry analysis, we demonstrate that the arreSTick motif controls the interaction between numerous non-receptor proteins and B-arrestins. For example, the HIV-1 Tat Specific Factor 1 (HTSF1 or HTATSF1), a nuclear transcription factor, contains the arreSTick pattern, and our data show that its subcellular localization is influenced by its coupling to B-arrestin2. Our findings unveil a broader regulatory role for B-arrestins in phosphorylation-dependent interactions, extending beyond GPCRs to encompass non-receptor proteins as well.
DOI: 10.7284/142604
title: pCO2 (Partial Pressure of Carbon Dioxide) data collected during research cruise LMG1310 using a LDEO pCO2 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142600
title: Radiometer data collected during research cruise LMG1310 using a Biospherical GUV-2511 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142605
title: Singlebeam Echosounder data collected during research cruise LMG1310 using a Knudsen 3260 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142606
title: Water Temperature data collected during research cruise LMG1310 using a SeaBird SBE-38 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142607
title: TSG (Thermosalinograph) data collected during research cruise LMG1310 using a SeaBird SBE-45 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142608
title: TSG (Thermosalinograph) data collected during research cruise LMG1310 using a SeaBird SBE-45 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.15132/10000180
title: Court and Tax Records from the Early American Frontier

description: The data utilised in the book, Making the Frontier Man: Manhood, Violence, and Authority in the Early Western Backcountry, ca.1750-1815, was collected principally from archives in the United States, although some microfilm resources were also utilised. A full list of the sources of the data are listed in the ReadMe file. The principal sources utilised were the record books of the local county courts, most frequently the Court of Quarter Sessions or the Court of Common Pleas. For some counties, other archival material such as ended causes were also consulted to provide further detail of cases. The data was cross-referenced with tax records obtained from a range of published and archival resources, and also cross-referenced with a database constructed to explore ethnicity. The latter is not included here. Because of some simplification of the data, and the removal of some items for copyright issues, the data may not exactly match the tables in the book.

The study examined court records of cases of petty crime based on 6,500 indictments in fourteen different counties across the backcountry of Virginia, Pennsylvania, Ohio, and Kentucky, from the mid-eighteenth century to the early nineteenth century and investigates patterns of violent behaviour and petty crime.

Counties: Champaign OH, Christian KY, Cumberland PA, Fairfield OH, Frederick VA, Harrison KY, Lancaster PA, Mason KY, Muhlenberg KY, Rockbridge VA, Washington County PA and Washington OH.

Included are the raw court and tax data that were used for the project. Some materials have been redacted for copyright reasons, and also the tables have been edited to ensure consistency throughout.

Court and Tax Records from the Early American Frontier is made available under the Open Data Commons Attribution License: http://opendatacommons.org/licenses/by/1.0/

Keywords: Violence, Masculinity, Gun Culture, Warfare, Gender, Frontier.
DOI: 10.7284/142232
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise LMG1403 using a Hawaii UHDAS instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142235
title: Fluorometer data collected during research cruise LMG1403 using a WETLabs ECO-FL instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142236
title: Meteorological Station data collected during research cruise LMG1403 using a USAP RVDAS Metstation instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142237
title: Oxygen data collected during research cruise LMG1403 using a AANDERAA Optode 3975 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142238
title: pCO2 (Partial Pressure of Carbon Dioxide) data collected during research cruise LMG1403 using a LDEO pCO2 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142231
title: Radiometer data collected during research cruise LMG1403 using a Biospherical GUV-2511 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142239
title: Singlebeam Echosounder data collected during research cruise LMG1403 using a Knudsen 3260 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142240
title: Water Temperature data collected during research cruise LMG1403 using a SeaBird SBE-38 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142160
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise LMG1408 using a Hawaii UHDAS instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142161
title: Fluorometer data collected during research cruise LMG1408 using a WETLabs ECO-FL instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142162
title: Meteorological Station data collected during research cruise LMG1408 using a USAP RVDAS Metstation instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142163
title: Oxygen data collected during research cruise LMG1408 using a AANDERAA Optode 3975 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142164
title: pCO2 (Partial Pressure of Carbon Dioxide) data collected during research cruise LMG1408 using a LDEO pCO2 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142159
title: Radiometer data collected during research cruise LMG1408 using a Biospherical GUV-2511 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142165
title: Singlebeam Echosounder data collected during research cruise LMG1408 using a Knudsen 3260 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142166
title: Water Temperature data collected during research cruise LMG1408 using a SeaBird SBE-38 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.5281/zenodo.8349729
title: Dataset - Speeding up high-throughput characterization of materials libraries by active learning: autonomous electrical resistance measurements

description: With the trend towards multinary materials and the associated increase in measurement time, there is a clear need for increasing the efficiency of measurement procedures. In systems requiring long materials characterization times, the implementation of active learning can help decreasing the measurement duration significantly. This dataset is part of the publication in Digital Discovery under the same title and holds the algorithm as well as the data used to test its performance. The algorithm leverages an active learning approach with a Gaussian process model capable of selecting the next measurement area of a library of materials based on the highest uncertainty. Ten materials libraries were manufactured by magnetron sputtering, the composition was measured with EDX and the electrical resistance was measured using the described test stand. The code can also be found on Gitlab.
DOI: 10.5281/zenodo.8349728
title: Dataset - Speeding up high-throughput characterization of materials libraries by active learning: autonomous electrical resistance measurements

description: With the trend towards multinary materials and the associated increase in measurement time, there is a clear need for increasing the efficiency of measurement procedures. In systems requiring long materials characterization times, the implementation of active learning can help decreasing the measurement duration significantly. This dataset is part of the publication in Digital Discovery under the same title and holds the algorithm as well as the data used to test its performance. The algorithm leverages an active learning approach with a Gaussian process model capable of selecting the next measurement area of a library of materials based on the highest uncertainty. Ten materials libraries were manufactured by magnetron sputtering, the composition was measured with EDX and the electrical resistance was measured using the described test stand. The code can also be found on Gitlab.
DOI: 10.5281/zenodo.6448813
title: DeepLabCut network trained to track mouse 'back' body parts during rotarod running (back-view)

description: DeepLabCut (https://github.com/DeepLabCut/) (Mathis et al., 2018; Nath et al., 2019) was used for tracking body parts of mice in an open field arena or in the rotarod. DeepLabCut 2.1.8.2 (local version on Windows with CPU, using the GUI) and 2.1.10.2 (google colab to train the network) were used using default parameters and the pretrained resnet50 network with imgaug augmentation. Frames were extracted with the k-means method and outlier frames with the jump method. <em>Rotarod, back camera:</em> 20 images from 9 videos (10 fps) were extracted for a total of 180 labeled pictures. 5 body parts (2 paws, 2 ankles, tail base), 4 corners of the rotarod, 2 points on the rotarod wheels and 4 points in a flashing LED (indicating timestamps) were manually labeled. A neural network was trained using these images for 80K iterations. 20 images from 14 videos with different recording conditions were labeled. The network was trained to 200K iterations (from scratch) (train error: 3.00, test error: 3.75). Relevant videos were analyzed at each step, for a total of 152 videos. <em>Used to analyze videos for a publication (Labouesse et al., Nature Communications 2023)</em>
DOI: 10.5281/zenodo.6448812
title: DeepLabCut network trained to track mouse 'back' body parts during rotarod running (back-view)

description: DeepLabCut (https://github.com/DeepLabCut/) (Mathis et al., 2018; Nath et al., 2019) was used for tracking body parts of mice in an open field arena or in the rotarod. DeepLabCut 2.1.8.2 (local version on Windows with CPU, using the GUI) and 2.1.10.2 (google colab to train the network) were used using default parameters and the pretrained resnet50 network with imgaug augmentation. Frames were extracted with the k-means method and outlier frames with the jump method. <em>Rotarod, back camera:</em> 20 images from 9 videos (10 fps) were extracted for a total of 180 labeled pictures. 5 body parts (2 paws, 2 ankles, tail base), 4 corners of the rotarod, 2 points on the rotarod wheels and 4 points in a flashing LED (indicating timestamps) were manually labeled. A neural network was trained using these images for 80K iterations. 20 images from 14 videos with different recording conditions were labeled. The network was trained to 200K iterations (from scratch) (train error: 3.00, test error: 3.75). Relevant videos were analyzed at each step, for a total of 152 videos. <em>Used to analyze videos for a publication (Labouesse et al., Nature Communications 2023)</em>
DOI: 10.5281/zenodo.6448799
title: DeepLabCut network trained to track mouse 'front' body parts during rotarod running (front-view)

description: DeepLabCut (https://github.com/DeepLabCut/) (Mathis et al., 2018; Nath et al., 2019) was used for tracking body parts of mice in an open field arena or in the rotarod. DeepLabCut 2.1.8.2 (local version on Windows with CPU, using the GUI) and 2.1.10.2 (google colab to train the network) were used using default parameters and the pretrained resnet50 network with imgaug augmentation. Frames were extracted with the k-means method and outlier frames with the jump method. <em>Rotarod, front camera: </em>29 frames from 18 videos (10 fps) were extracted for a total of 520 labeled pictures. 12 body parts (left, right and mid snout, left/right top/bottom ears, left/right eyes, headmount, left/right foot), 4 corners of the rotarod and 4 points on the rotarod wheels were manually labeled and linked to each other using skeletons. A neural network was trained using these images for 225K iterations (train error: 1.58, test error: 1.63). 20 outlier frames were extracted from each video and relabeled. An additional 20 images from 20 new videos with different recording conditions were labeled. The network was then refined for 331K iterations (from scratch) (train error: 2.34, test error: 5.49). This process was repeated a second time when adding 20 new videos (400 frames) and the network trained to a final 402K (train error: 2.64, test error: 3.98). For this last batch, brightness/contrast were too low to detect body features; brightness/contrast were thus enhanced using custom-written Python scripts. Relevant videos were analyzed at each of the 3 steps, for a total of 152 videos. <em>Used to analyze videos for a publication (Labouesse et al., Nature Communications 2023).</em> <em>Network not included in the final publication.</em>
DOI: 10.5281/zenodo.6448798
title: DeepLabCut network trained to track mouse 'front' body parts during rotarod running (front-view)

description: DeepLabCut (https://github.com/DeepLabCut/) (Mathis et al., 2018; Nath et al., 2019) was used for tracking body parts of mice in an open field arena or in the rotarod. DeepLabCut 2.1.8.2 (local version on Windows with CPU, using the GUI) and 2.1.10.2 (google colab to train the network) were used using default parameters and the pretrained resnet50 network with imgaug augmentation. Frames were extracted with the k-means method and outlier frames with the jump method. <em>Rotarod, front camera: </em>29 frames from 18 videos (10 fps) were extracted for a total of 520 labeled pictures. 12 body parts (left, right and mid snout, left/right top/bottom ears, left/right eyes, headmount, left/right foot), 4 corners of the rotarod and 4 points on the rotarod wheels were manually labeled and linked to each other using skeletons. A neural network was trained using these images for 225K iterations (train error: 1.58, test error: 1.63). 20 outlier frames were extracted from each video and relabeled. An additional 20 images from 20 new videos with different recording conditions were labeled. The network was then refined for 331K iterations (from scratch) (train error: 2.34, test error: 5.49). This process was repeated a second time when adding 20 new videos (400 frames) and the network trained to a final 402K (train error: 2.64, test error: 3.98). For this last batch, brightness/contrast were too low to detect body features; brightness/contrast were thus enhanced using custom-written Python scripts. Relevant videos were analyzed at each of the 3 steps, for a total of 152 videos. <em>Used to analyze videos for a publication (Labouesse et al., Nature Communications 2023).</em> <em>Network not included in the final publication.</em>
DOI: 10.5519/qd.up6g7a1f
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (31 records)
DOI: 10.5281/zenodo.8342656
title: Quantifying the Incubation Period of Tuberculosis: A Systematic Review

description: Compiled dataset for the paper "Quantifying the Incubation Period of Tuberculosis: A Systematic Review"
DOI: 10.5281/zenodo.8342655
title: Quantifying the Incubation Period of Tuberculosis: A Systematic Review

description: Compiled dataset for the paper "Quantifying the Incubation Period of Tuberculosis: A Systematic Review"
DOI: 10.7284/142431
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise LMG1409 using a Hawaii UHDAS instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142433
title: Meteorological Station data collected during research cruise LMG1409 using a USAP RVDAS Metstation instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142434
title: Oxygen data collected during research cruise LMG1409 using a AANDERAA Optode 3975 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142435
title: pCO2 (Partial Pressure of Carbon Dioxide) data collected during research cruise LMG1409 using a LDEO pCO2 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142430
title: Radiometer data collected during research cruise LMG1409 using a Biospherical GUV-2511 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142436
title: Singlebeam Echosounder data collected during research cruise LMG1409 using a Knudsen 3260 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142437
title: Water Temperature data collected during research cruise LMG1409 using a SeaBird SBE-38 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142438
title: TSG (Thermosalinograph) data collected during research cruise LMG1409 using a SeaBird SBE-45 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142439
title: TSG (Thermosalinograph) data collected during research cruise LMG1409 using a SeaBird SBE-45 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142107
title: Expendable Probe data collected during research cruise LMG1503 using a Sippican MK21 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142100
title: Fluorometer data collected during research cruise LMG1503 using a WETLabs ECO-FL instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142099
title: Meteorological Station data collected during research cruise LMG1503 using a USAP RVDAS Metstation instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142101
title: Oxygen data collected during research cruise LMG1503 using a AANDERAA Optode 3975 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142102
title: pCO2 (Partial Pressure of Carbon Dioxide) data collected during research cruise LMG1503 using a LDEO pCO2 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142103
title: Singlebeam Echosounder data collected during research cruise LMG1503 using a Knudsen 3260 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142104
title: Water Temperature data collected during research cruise LMG1503 using a SeaBird SBE-38 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition