cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e119191v1
title: Weather & Summer Spatial Behavior of U.S. National Park Visitors (Flickr data 2006 - 2018)

description: This dataset corresponds to a paper titled "Social media data reveal ecoregional variation in how weather influences visitor behavior in U.S. National Parks," which is currently under review. The paper is authored by Emily J. Wilkins, Peter D. Howe, and Jordan W. Smith.<br><br>In this paper, we investigate how daily temperature and precipitation in the summer influence visitors' spatial behavior in 110 U.S. National Park Service Units. We use Flickr data from 2006 - 2018 to uncover visitors locations within parks, and connect each geotagged point to the weather at the date the photo was taken (using Daymet data), as well as nearby infrastructure and environmental features (using OpenStreetMap data). <br><br>While we cannot provide the raw Flickr data due to privacy concerns, we include the final database we used after all data collection, cleaning, and processing (all_ecoregions_Flickr.csv). All personally identifiable information is deleted from this database. This database was used to run the statistical tests presented in the paper, as well as generate the maps (R code included). <br><br>We also include maps of each of the 110 study sites that show the general summer spatial distributions of Flickr posts in each park, and well as how the spatial distributions differ by hot and cold summer days.
description: web scraping; All data was collected by writing Python and R scripts to interact with APIs.
description: Any visitor to U.S. National Parks who has uploaded a photo to Flickr. .
description: We collected all Flickr data within the study sites, and filtered the dataset to only include one post per user, per day, within a 10 meter radius.
DOI: 10.14469/hpc/7177
title: Michael 1,4 addition, G =TS2 S-C formation, imino S-C TS G = -994.533884 IRC

description: Gaussian Calculation
DOI: 10.21227/vab6-et26
title: CALPA-NET

description: The supplementary files of our submitted TIFS paper: "CALPA-NET: Channel-pruning-assisted DeepResidual Network for Steganalysis of Digital Images".
DOI: 10.21227/dfwn-2k95
title: CALPA-NET

description: The supplementary files of our submitted TIFS paper: "CALPA-NET: Channel-pruning-assisted DeepResidual Network for Steganalysis of Digital Images".
DOI: 10.5281/zenodo.3813791
title: Dublin Trees GIS Database

description: <strong>Overview</strong> This dataset on trees covers Dublin City, Ireland. It indicates the locations of over 300,000 trees which were acquired using a point-and-click methodology using a high-quality aerial image (resolution of 12.5 cm) taken in June 2018. Each x,y location represents the tree canopy centre. The database also includes the estimated height of these trees based on a Digital Elevation Model (horizontal resolution of 1m, vertical resolution *m). This information is complemented with detailed information on individual trees, where available. This includes, for example, data on 2440 street trees (species and dimensions) gathered in 2008/2009. The dataset will be updated at regular intervals as information on individual trees is acquired. <em>* to be updated</em> <strong>Purpose</strong> Information on trees (location, species, age, and health) in urban areas is needed to assess the green infrastructure and the ecosystem, environmental and social services that they provide. These data were acquired to support greening strategies and actions in the Dublin City Council area. <em>Additional comments</em> The creation of the Dublin tree database was supported in part by a research grant from Ireland’s Environmental Protection Agency (EPA) and using databases acquired by the School of Geography at UCD. The tree database is part of the Mapping Green Dublin project and is being used by the Curio app, which allows citizens to add data on individual trees.
DOI: 10.5281/zenodo.3813792
title: Dublin Trees GIS Database

description: <strong>Overview</strong> This dataset on trees covers Dublin City, Ireland. It indicates the locations of over 300,000 trees which were acquired using a point-and-click methodology using a high-quality aerial image (resolution of 12.5 cm) taken in June 2018. Each x,y location represents the tree canopy centre. The database also includes the estimated height of these trees based on a Digital Elevation Model (horizontal resolution of 1m, vertical resolution *m). This information is complemented with detailed information on individual trees, where available. This includes, for example, data on 2440 street trees (species and dimensions) gathered in 2008/2009. The dataset will be updated at regular intervals as information on individual trees is acquired. <em>* to be updated</em> <strong>Purpose</strong> Information on trees (location, species, age, and health) in urban areas is needed to assess the green infrastructure and the ecosystem, environmental and social services that they provide. These data were acquired to support greening strategies and actions in the Dublin City Council area. <em>Additional comments</em> The creation of the Dublin tree database was supported in part by a research grant from Ireland’s Environmental Protection Agency (EPA) and using databases acquired by the School of Geography at UCD. The tree database is part of the Mapping Green Dublin project and is being used by the Curio app, which allows citizens to add data on individual trees.
DOI: 10.5281/zenodo.3818211
title: Detecting axisymmetric magnetic fields using gravity modes in intermediate-mass stars

description: Typical MESA and GYRE inlists associated with Van Beeck et al. (2020). MESA version 10398 and GYRE version 5.2. Context: Angular momentum (AM) transport models of stellar interiors require improvements to explain the strong extraction of AM from stellar cores that is observed with asteroseismology. One of the often invoked mediators of AM transport are internal magnetic fields, even though their properties, observational signatures and influence on stellar evolution are largely unknown. Aims: We study how a fossil, axisymmetric internal magnetic field affects period spacing patterns of dipolar gravity mode oscillations in main-sequence stars with masses of 1.3, 2.0 and 3.0 \(\mathrm{M}_{\odot}\) . We assess the influence of fundamental stellar parameters on the magnitude of pulsation mode frequency shifts. Methods: We compute dipolar gravity mode frequency shifts due to a fossil, axisymmetric poloidal-toroidal internal magnetic field for a grid of stellar evolution models, varying stellar fundamental parameters. Rigid rotation is taken into account using the traditional approximation of rotation and the influence of the magnetic field is computed using a perturbative approach. Results: We find magnetic signatures for dipolar gravity mode oscillations in terminal-age main-sequence stars that are measurable for a near-core field strength larger than 10<sup>5</sup> G. The predicted signatures differ appreciably from those due to rotation. Conclusions: Our formalism demonstrates the potential for the future detection and characterization of strong fossil, axisymmetric internal magnetic fields in gravity-mode pulsators near the end of core-hydrogen burning from Kepler photometry, if such fields exist. The publication date is the date of acceptance.
DOI: 10.34943/bc5bf185-4b4a-4533-963f-2d98dead60ad
title: Folger Pinnacle Fluorometer Turbidity Deployed 2016-04-20

description: The WET Labs ECO FLNTUS 895 was deployed on 2016-04-20 at Folger Pinnacle. Folger Pinnacle is an isolated pillar-like feature in Folger Passage, where biodiversity and coastal ecosystems are observed. This device is a Fluorometer Turbidity. Fluorometer Turbidity instruments measure chlorophyll fluorescence and turbidity within the same volume of seawater. The instrument uses a light emitting diode (LED) to provide an excitation source. The fluoresced light is received by a detector at a particular angle from the LED source, and uses an interference filter to discriminate against scattered excitation light. Turbidity is measured at the same time, by detecting scattered light from a LED, which is positioned at the same angle as the chlorophyll fluorescence. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Network Canada's Oceans 2.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.25345/c59h74
title: MassIVE MSV000085390 - Mitochondrial nucleoid organization and biogenesis of complex I require mTERF18/SHOT1 and ATAD3 in Arabidopsis thaliana_SHOT1-GFP IP-MS
title: IP-MS experiments to find interacting partner proteins of SHOT1-GFP using GFP-Trap (ChromoTek). MitoGFP: GFP targeted to mitochondria, negative control MK30: 35S::SHOT1-GFP MK108: native promoter driven SHOT1-GFP Bab: blocked agarose beads without GFP nanobody, negative control
DOI: 10.5281/zenodo.3818252
title: Linked COVID-19 Data: Johns Hopkins University (JHU) and European Centre for Disease Prevention and Control (ECDC)

description: Linked COVID-19 Data derived from <strong>Johns Hopkins University</strong> and <strong>European Centre for Disease Prevention and Control</strong> using the COVID-19 Ontology 10.5281/zenodo.3757828 developed for the Linked COVID-19 Data Dashboard: http://covid19data.link This files include data for covid19_jhu.ttl - COVID-19 data collected by the JHU covid19_ecdc.ttl - COVID-19 data collected by the ECDC This RDF files are based on https://pomber.github.io/covid19/timeseries.json https://opendata.ecdc.europa.eu/covid19/casedistribution/json/
DOI: 10.15161/oar.it/23644
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.25345/c55t4v
title: MassIVE MSV000085391 - Mitochondrial nucleoid organization and biogenesis of complex I require mTERF18/SHOT1 and ATAD3 in Arabidopsis thaliana_SHOT1 mitochondrial proteomics
title: To examine proteome changes resulting from defective SHOT1, we employed label-free quantitative proteomics on isolated mitochondria from shot1-2 and wild-type Columbia-0 (Col) plants (three biological replicates and three technical replicates).
DOI: 10.5281/zenodo.3818533
title: Jonesbc/Chiroxiphia_lanceolata_cort_dev: Chiroxiphia_lanceolata_cort_dev

description: Data release of "Testing the developmental hypothesis of the HPA axis in a tropical passerine: dampened corticosterone response and faster negative feedback in nestling lance-tailed manakins (Chiroxiphia lanceolata)."
DOI: 10.5281/zenodo.3818534
title: Jonesbc/Chiroxiphia_lanceolata_cort_dev: Chiroxiphia_lanceolata_cort_dev

description: Data release of "Testing the developmental hypothesis of the HPA axis in a tropical passerine: dampened corticosterone response and faster negative feedback in nestling lance-tailed manakins (Chiroxiphia lanceolata)."
DOI: 10.12751/g-node.df3de6
title: CRCNS Dataset: Spiking auditory network model and spectro-temporal receptive fields from auditory nerve, midbrain, thalamus and cortex

description: The accompanying neural data, sounds, and models are outlined in the publication: Fatemeh Khatami and Monty A. Escabí, Spiking network optimized for word recognition in noise predicts auditory system hierarchy. PLOS Comp. Bio (in press). The archive includes a MATLAB implementation of the auditory model from the above citation. The auditory model consists of a front end cochlear model that is connected to a hierarchical spiking neural network (HSNN). The HSNN contains inhibitory and excitatory connections between consecutive layers as outlined in the above manuscript. The original sounds used to test the network in a speech recognition task were derived from clean speech from the TIMIT Acoustic-Phonetic Continuous Speech Corpus (https://catalog.ldc.upenn.edu/LDC93S1). Here, edited speech sounds consisting of digits (“zero” to “nine”) that have added background noise and that were used in the study to test the network are included. The archive also includes neural data that was used to compare results from the auditory system to the auditory HSNN model. Neural data consists of recordings from auditory nerve (AN), inferior colliculus (IC), auditory thalamus (MGB) and cortex (A1).
description: IsSupplementTo: Fatemeh Khatami and Monty A. Escabí, Spiking network optimized for word recognition in noise predicts auditory system hierarchy. PLOS Comp. Bio (in press). IsSupplementTo: Fatemeh Khatami and Monty A. Escabí (2018) Spiking network optimized for noise robust word recognition approaches human-level performance and predicts auditory system hierarchy. BioRxiv (doi:10.1101/243915)
DOI: 10.5281/zenodo.3818005
title: Dataset used for detecting DNS over HTTPS by Machine Learning.

description: The dataset consists of three different data sources: DoH enabled Firefox DoH enabled Google Chrome Cloudflared DoH proxy The capture of of web browser data was made using the Selenium framework, which simulated classical user browsing. The browsers received command for visiting domains taken from Alexa's top 10K most visited websites. The capturing was performed on the host by listening on the network interface of the virtual machine. Overall the dataset contains almost 5,000 web-page visits by Mozzila and 1,000 pages visited by firefox. The Cloudflared DoH proxy was installed in raspberry and the IP address of the Raspberry was set as the default DNS resolver in two separate offices in our university. It was continuously capturing the DNS/DoH traffic created up to 20 devices for around three months. The dataset contains 1,128,904 flows from which is around 33,000 labeled as DoH. We provide it in the form of CSV file with the following datafields: <strong>Label </strong>(1 - Doh, 0 - regular HTTPS) Data source Duration Minimal Inter-Packet Delay Maximal Inter-Packet Delay Average Inter-Packet Delay A variance of Incoming Packet Sizes A variance of Outgoing Packet Sizes A ratio of the number of Incoming and outgoing bytes A ration of the number of Incoming and outgoing packets Average of Incoming Packet sizes Average of Outgoing Packet sizes The median value of Incoming Packet sizes The median value of outgoing Packet sizes The ratio of bursts and pauses Number of bursts Number of pauses Autocorrelation Transmission symmetry in the 1st third of connection Transmission symmetry in the 2nd third of connection Transmission symmetry in the last third of connection The observed network traffic does not contain privacy-sensitive information.
DOI: 10.17909/t9-94ka-p284
title: HST/COS data from Fox et al. 2020 ApJ Paper "Kinematics of the Magellanic Stream and Implications for its Ionization"

description: This data contains the 31 HST/COS Magellanic Sightlines used in the Fox et al. 2020 study of the kinematics of the Magellanic Stream and Leading Arm.
DOI: 10.21227/8dak-dy13
title: FooDD: Food Detection Dataset for Calorie Measurement Using Food Images

description: Images of various foods, taken in different conditions, as described below. Images can be used and to design and test Computer Vision techniques that can recognize foods and estimate their calories and nutrition.
DOI: 10.15468/7vsagd
title: Chapter 7: Linnaean Plant Names and their Types (part A)

description: This dataset contains the digitized treatments in Plazi based on the original book chapter Jarvis, Charlie (2007): Chapter 7: Linnaean Plant Names and their Types (part A). In: Order out of Chaos. Linnaean Plant Types and their Types. London: Linnaean Society of London in association with the Natural History Museum: 252-342, ISBN: 978-0-9506207-7-0, DOI: https://doi.org/10.5281/zenodo.291971
DOI: 10.5281/zenodo.3816968
title: Wikidata Dump Depressive disorders

description: RDF dump of wikidata produced with wdumps. Wikidata dumps<br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3817467
title: ConFire Model input/output for South America

description: ConFIRE input and output used in the submission of Kelley et al. "Low Climatic Influence found in 2019 Amazonia Fires". "input" dir including "amazon_inference_data-2002-MCDBA_obs-TERRA_M__T.csv", just contains a csv file of all common grid data in other "input" subdirectories, which can be used in "optimise_run_model/bayesian_inference.ipynb" notebook. The files in the subdirectories are then used to make gridded model output using "optimise_run_model/make_model_output.ipynb". Output, also provided, is summerized in the files in "outputs/sampled_posterior_ConFire_solutions/constant_post_2018_full_2002_BG2020/" The three files contain: fire_summary_frequancy_of_counts.nc - Contains one spatial variable (long name "firecount frequency of occurrence") is the probability of a fire count (along the model_level_number dimension) at a particular month (time dimension) according to the models full posterior, \(P(y_j)\)(see papers supplementary). All months start on Jan 2001. fire_summary_precentile.nc - Contains one spatial variable (long name "firecount at percentile"), the fire count at each percentile of the full posterior in 1% increments from 1-99% (along the model_level_number dimension). Note, by definition, the 0a nd 100% percentile is 0 and \(\infty \) . model_summary.nc - Summary of each variable of ConFire: "burnt_area": burnt area or fire count summary, described as percentiles as per "fire_summary_precentile", but this time just assessing parameter uncertainty, i.e \(P(\beta | Y_s)\) in supplementary of paper. All other variables describe different model controls in the same "burnt_area". Full information on how controls are constructed can be found in Kelley et al. (2019) with updates listed in supplementary of this paper. "fuel_continuity", "moisture_content", "ignitions", "suppression" are the actual values of the control "standard_&lt;&lt;control&gt;&gt;" is the standard limitation imposed by the control. "potential_&lt;&lt;control&gt;&gt; is the potential limitation "sensitivity_&lt;&lt;control&gt;&gt; is the senstivity of fire to a particular control.<br> <br> See Kelley et al. 2019 for the definition of limitation types and sensitivity Kelley, D.I., Bistinas, I., Whitley, R. <em>et al.</em> How contemporary bioclimatic and human controls change global fire regimes. <em>Nat. Clim. Chang.</em> <strong>9, </strong>690–696 (2019) doi:10.1038/s41558-019-0540-7
description: {"references": ["Kelley, D. I., Burton, C., Huntingford, C., J., B. M. A., Whitley, R. and Dong, N.: Low meteorological influence found in 2019 Amazonia fires, Biogeosciences, submitted.", "Kelley, D. I., Bistinas, I., Whitley, R., Burton, C., Marthews, T. R. and Dong, N.: How contemporary bioclimatic and human controls change global fire regimes, Nat. Clim. Chang., 9(9), 690\u2013696, 2019."]}
DOI: 10.5281/zenodo.3816967
title: Wikidata Dump Depressive disorders

description: RDF dump of wikidata produced with wdumps. Wikidata dumps<br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3816969
title: Wikidata Dump Depressive disorders

description: RDF dump of wikidata produced with wdumps. Wikidata dumps<br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3816970
title: Wikidata Dump Depressive disorders

description: RDF dump of wikidata produced with wdumps. Wikidata dumps<br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.6073/pasta/85e4ad99aeaded196f149d5c87c2f3b4
title: Water chemistry time series for Beaverdam Reservoir, Carvins Cove Reservoir, Falling Creek Reservoir, Gatewood Reservoir, and Spring Hollow Reservoir in southwestern Virginia, USA 2013-2019

description: Depth profiles of dissolved organic carbon and total and dissolved nitrogen and phosphorus were sampled from 2013 to 2019 in five drinking water reservoirs in southwestern Virginia, USA. These reservoirs are: Beaverdam Reservoir (Vinton, Virginia), Carvins Cove Reservoir (Roanoke, Virginia), Falling Creek Reservoir (Vinton, Virginia), Gatewood Reservoir (Pulaski, Virginia), and Spring Hollow Reservoir (Salem, Virginia). Beaverdam, Carvins Cove, Falling Creek, and Spring Hollow Reservoirs are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia, and Gatewood Reservoir is a drinking water source for the Town of Pulaski, Virginia. The dataset consists of depth profiles of water chemistry samples measured at the deepest site of each reservoir adjacent to the dam. Additional water chemistry samples were collected at a gauged weir on Falling Creek Reservoir’s primary inflow tributary, as well as surface samples at multiple upstream and inflow sites in Falling Creek Reservoir and Beaverdam Reservoir in summer of 2019. The water column samples were collected approximately fortnightly from March-April, weekly from May-October, and monthly from November-February at Falling Creek Reservoir and Beaverdam Reservoir, approximately fortnightly from May-August in most years at Carvins Cover Reservoir, and approximately fortnightly from 2014-2016 in Gatewood and Spring Hollow Reservoirs. Depth profiles of dissolved inorganic carbon were also collected in 2018 and 2019, but the analytical method for this analyte is still in development and these should be considered as preliminary data only.
DOI: 10.15468/ek36rv
title: Chapter 7: Linnaean Plant Names and their Types (part B)

description: This dataset contains the digitized treatments in Plazi based on the original book chapter Jarvis, Charlie (2007): Chapter 7: Linnaean Plant Names and their Types (part B). In: Order out of Chaos. Linnaean Plant Types and their Types. London: Linnaean Society of London in association with the Natural History Museum: 343-369, ISBN: 978-0-9506207-7-0, DOI: https://doi.org/10.5281/zenodo.291971
DOI: 10.5281/zenodo.3818580
title: IO Islamic 115. Bayân-i-Wâḳi', A History of Nâdirshâh, Muḥammadshâh, and Aḥmadshâh

description: IO Islamic 115. Bayân-i-Wâḳi’, A History of Nâdirshâh, Muḥammadshâh, and Aḥmadshâh
DOI: 10.5281/zenodo.3818581
title: IO Islamic 115. Bayân-i-Wâḳi', A History of Nâdirshâh, Muḥammadshâh, and Aḥmadshâh

description: IO Islamic 115. Bayân-i-Wâḳi’, A History of Nâdirshâh, Muḥammadshâh, and Aḥmadshâh