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194 results for “R dataset”
Dataset and R-script for simple mechanistic model of Heracleum sosnowskyi seed dispersal by wind
<p>The dataset contains:</p> <p>- primary data about Heracleum sosnowskyi seeds traits (terminal velocity, mass, area, wing loading) and release heights for <em>H. sosnowskyi</em> populations from two geographically distant Russia regions;</p> <p>- results of experiments of model seeds launches under different wind speeds;</p> <p>- R script for exploratory statistical analysis, linear regressions and mechanistc models testing.</p> <p>The anemochorous seed dispersal was generalized with a number of empirical and mechanistic models of varying complexity. The aim of this work was to develop the simplest possible mechanistic model of <em>Heracleum sosnowskyi</em> that allows to determine the distance of seed dispersal by wind with an accuracy comparable to that of empirical measurements. We measured and compared the characteristics of the seeds (terminal velocity, mass, area, wing loading) as well as the release height for <em>H. sosnowskyi</em> populations from two geographically distant Russia regions. We tested two simplest mechanistic models: a ballistic model and a wind gradient model using identical artificial seeds with characteristics similar to those of real <em>H. sosnowskyi</em> seeds. The wind gradient model gave the best results, despite the fact that uniform in shape, weight and size artificial <em>H. sosnowskyi</em> seeds, when dropped simultaneously from the same height, fly off at different distances. This model provides an estimate of dispersal distances with an accuracy comparable to that of empirical measurements. We plan to use the presented model to develop an individual-based model that will allow us to calculate the flight distances of <em>H. sosnowskyi</em> propagules, taking into account real weather conditions in different years and in different parts of its invasion range. All primary data and R-scripts used are freely available at the Zenodo repository (https://doi.org/10.5281/zenodo.3766035).</p> <p> </p>
Dataset, Survey, and R Notebooks for "Does Surprisal Predict Code Comprehension Difficulty?"
<p>(Version 1.1 Update)</p> <p>- Removed anonymization after reviewing period ended and paper was accepted at Cogsci 2020.</p> <p>- Added Qualtrics Survey in exported form</p> <p>Dataset and R analysis scripts for the paper "Does Surprisal Predict Code Comprehension Difficulty?". For more details, see "ComprehensionREADME.md" in the included zip file.</p>
Collapse and Continuity: A multi-proxy reconstruction of settlement organization and population trajectories in the Northern Fertile Crescent during the 4.2kya Rapid Climate Change event (dataset and R scripts)
<p>The present digital archive is the outcome of the paper: <strong>Lawrence, D., Palmisano, A., and de Gruchy, M.W., 2021. <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0244871">Collapse and Continuity: A multi-proxy reconstruction of settlement organization and population trajectories in the Northern Fertile Crescent during the 4.2kya Rapid Climate Change event</a></strong><a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0244871">.</a> <em><strong>PLoS ONE</strong></em><strong>,</strong> <strong><em>16</em></strong>(1).</p> <p>The dataset included here provides a collection of <strong>920 </strong>radiocarbon dates and <strong>1070</strong> sites from archaeological surveys. In addition, the digital archive related to this paper provides reproducible analyses in the form of three scripts written in R statistical computing language.</p>
Holocene regional population dynamics and climatic trends in the Near East: a first comparison using archaeo-demographic proxies (dataset and R scripts)
<p>The present digital archive is the outcome of the paper: <strong>Palmisano, A., Lawrence, D., de Gruchy, M.W., Bevan, A., and Shennan, S., 2021. <a href="https://doi.org/10.1016/j.quascirev.2020.106739">Holocene regional population dynamics and climatic trends in the Near East: a first comparison using archaeo-demographic proxies</a>. <em>Quaternary Science Reviews</em>, <em>252</em></strong>.</p> <p>The dataset included here provides a collection of <strong>10,606</strong> radiocarbon dates, <strong>1884</strong> sites from archaeological surveys (1336 from Central Anatolia and 478 from Upper Mesopotamia) and <strong>16</strong> palaeoclimatic records for a period spanning between 14,000 and 2500 BP. In addition, the digital archive related to this paper provides reproducible analyses in the form of four scripts written in R statistical computing language.</p> <p>List of versions:</p> <ul> <li><strong>2.0.</strong> 15 December 2020 — Includes a few minor error corrections (the files 'References.txt' within the folder csv and the script 'radiocarbon.R').</li> <li><strong>1.0</strong> 28 November 2020 — First public release of the dataset on Zenodo.</li> </ul>
Really a nontraded commodity? A look at the international potato trade network (dataset and R code)
<p>This archive contains code and data for a social network analysis of international potato trade that was published at https://perspectivesandforesight.wordpress.com/2012/11/08/really-a-nontraded-commodity-a-look-at-the-international-potato-trade-network/ on 08 November, 2012.</p> <p>It can serve as a reference for understanding the analysis, and as a basis for replication of the results as well as for carrying out more detailed analyses of international potato trade.</p> <p>The following information and data is included:</p> <p>- The R code used for the social network analysis of international potato trade.</p> <p>- Data files with bilateral matrices of global trade in fresh, frozen and seed potatoes.</p> <p>- Data files with supplementary data used for the analysis.</p> <p>- A copy of the original blog post that was written using the data and code provided herewith.</p>
Illustrative dataset for the article: Vieira, R., McDonald, S., Araujo-Soares, V., Sniehotta, F., Henderson, R. (2017) "Dynamic modelling of n-of-1 data: Powerful and flexible data analytics applied to individualised studies"
<p>This dataset is supplementary material of the manuscript "Dynamic modelling of n-of-1 data: Powerful and flexible data analytics applied to individualised studies. McDonald et al. (2016) presents a series of novel n-of-1 studies that intended to explore the relationship between physical activity change during the retirement transition. The file contains the data of one participant. The column names correspond to the following variables:</p> <p>time: duration of follow-up (minutes);<br> minute: time of day (hours and minutes);<br> day_num: day since beginning of follow-up (the first two days were considered as adaptation phase and therefore removed); <br> PAscore: accelerometer raw score; <br> startBout: 1 (a bout of PA was initiated in this minute) or 0 (a bout of PA wasn't <br> initiated in this minute); <br> nPAbouts_day: number of PA bouts per day; <br> nPAbouts_day.l1: number of PA bouts in previous day (lag 1); <br> nPAbouts_day.l2: number of PA bouts two day before (lag 2); <br> nBoutsLast2hours: number of PA bouts in previous 2 hours; <br> retirement: 0 (before retirement) or 1 (after retirement)<br> weekday: 0 (workday) or 1 (weekend)<br> sleepLength: number of hours of sleep last night<br> sleepLength.l1: number of hours of sleep the night before<br> sleepLength.l2: number of hours of sleep two nights before<br> pers: personalised measure of partner's influence (scale 0-1)<br> periodDay: morning, evening or afternoon</p> <p>McDonald, S., Vieira, R., O'Brien, N., White, M., & Sniehotta, F. F. (2016). Does physical activity and sedentary behavior change during the retirement transition? Findings from a series of novel n-of-1 natural experiments. <em>International Journal of Behavioral Medicine, 23</em>, S261-S261.</p> <p> </p>
Dataset and full R script used in the data analysis of the paper "Overlooked and undervalued: Peripheral pollinators in an urban network"
<p>Dataset and full R script used in the data analysis of the paper "<strong>Overlooked and undervalued: Peripheral pollinators in an urban network</strong>".</p> <p>Summary:</p> <p>Since insect pollinators are essential for their ecological and agricultural roles, their conservation should be a priority, particularly in the remnant green spaces within highly urbanised cities. To gain insight into the occurrence of interactions between plants and often overlooked pollinators, and into their requirements for persistence over time in urban green spaces, we studied flower visitor diversity associated with a remnant of native vegetation in Cordoba (Argentina), one of the largest cities in South America. We recorded 198 insect species from six orders (Hymenoptera, Diptera, Lepidoptera, Coleoptera, Thysanoptera, and Hemiptera) interacting with the flowers of 94 plant species. The plant-pollinator interaction network was significantly modular, with 178 pollinators playing a peripheral role (i.e., it has a few links inside its own module and rarely any to other modules). We focused on the life history traits of these peripheral pollinators, which are often neglected in ecological studies. We classified their requirements to complete the life cycle and to persist over time into three broad categories: floral rewards, places to reproduce, and additional resources for food and nests. The life cycle requirements of peripheral pollinators differ significantly across insect orders. Hymenoptera and Lepidoptera have distinct life history requirements while Diptera and Coleoptera overlap in resource use. The three life history categories highlight how pollinators displayed different foraging behaviour, reproductive strategies of immature and adult stages, and the requirement of additional food resources used by larvae and adults beyond flower rewards to complete their life cycles. Knowledge about the requirements of neglected pollinators is a benchmark that can help to identify where efforts need to be made to conserve and maintain their biodiversity, even in small urban green spaces.</p>
Dataset and R code used in "Environmental filtering governs consistent vertical zonation in sedimentary microbial communities across disconnected mountain lakes"
<p>Dataset and R code used for the manuscript:</p> <p>Von Eggers, J. M., Wisnoski, N. I., Calder, J. W., Capo, E., Groff, D. V., Krist, A. C., & Shuman, B. (2024). Environmental filtering governs consistent vertical zonation in sedimentary microbial communities across disconnected mountain lakes. <em>Environmental Microbiology</em>, 26(3), e16607.</p> <p>This dataset and code are also available on GitHub (<a href="https://github.com/jvoneggers/WYLakeSedMicrobes">https://github.com/jvoneggers/WYLakeSedMicrobes</a>).</p>
Datasets and R codes used for the analyses in "Seasonal variation in home range size of White-Backed Woodpeckers"
<p><strong>Abstract</strong></p> <p>Knowing a species’ area requirements is fundamental for species conservation. For the nominate subspecies of the White-backed Woodpecker<em> Dendrocopos leucotos</em>, a species of high conservation concern in Europe, estimates of the seasonal and year-round area requirements based on telemetry are missing. In the present study, we radio-tracked adult White-backed Woodpeckers in Central Europe and investigated bi-monthly home range sizes based on three home range estimators in relation to season, sex, body weight, and year. Home range size of 49 radio-tracked individuals varied depending on the used home range estimator, with minimum convex polygons (MCP) and autocorrelated kernel density estimation (AKDE) producing 1.6 – 1.8 and 2 – 3.3 times larger seasonal home ranges than traditional kernel density estimation (KDE). Moreover, home range sizes varied between seasons. Home ranges were smallest in February/March (predicted median home range sizes ranged from 35 ha with KDE to 88 ha with AKDE) and April/May (KDE: 30 ha, AKDE: 55 ha) and larger during the rest of the year (KDE: 48 – 67 ha, AKDE: 136 – 184 ha). The mean home range size of six individuals tracked in all seasons (calculated with all locations per individual) was 116 ha with KDE, 304 ha with MCP and 350 ha with AKDE. Our results highlight the importance of considering the full annual cycle when addressing area requirements of White-backed Woodpeckers and likely also of other species. Furthermore, our study shows that using multiple methods for home range estimation may be useful to obtain results that are both comparable with those of other studies and capture the range in which the true home range size is likely to be. For the conservation of the White-backed Woodpecker, we conclude that at least 116 to 350 ha of forest should be present for a pair.</p>
Supplementary datasets, data analysis code, and R tutorials for: Phylogenetic analysis of adaptation in comparative physiology and biomechanics: overview and a case study of thermal physiology in treefrogs
<p>Comparative phylogenetic studies of adaptation are uncommon in biomechanics and physiology. Such studies require collecting data from many species, a challenge when data collection is experimentally intensive. Moreover, researchers struggle to employ the most biologically appropriate phylogenetic tools for identifying adaptive evolution. Here, we detail an established but greatly underutilized phylogenetic comparative framework—the Ornstein-Uhlenbeck process—that explicitly models long-term adaptation. We discuss challenges in implementing and interpreting the model, and we outline potential solutions. We demonstrate use of the model through studying the evolution of thermal physiology in treefrogs. Frogs of the family Hylidae have twice colonized the temperate zone from the tropics, and such colonization likely involved a fundamental change in physiology due to colder and more seasonal temperatures. However, which traits changed to allow colonization is unclear. We measured cold-temperature tolerance and characterized thermal performance curves in jumping for twelve species of treefrogs distributed from the Neotropics to temperate North America. We then conducted phylogenetic comparative analyses to examine how tolerances and performance curves evolved and to test whether that evolution was adaptive. We found that tolerance to low temperatures increased with the transition to the temperate zone. In contrast, jumping well at colder temperatures was unrelated to biogeography and thus did not adapt during dispersal. Overall, our paper shows how comparative phylogenetic methods can be leveraged in biomechanics and physiology to test the evolutionary drivers of variation among species.</p>
Affective, physiological, and attention restoration at a wooden desk: A pilot study (Datasets and R analysis code)
<p>This entry contains datasets and R processing and analysis code for the article <em>Affective, physiological, and attention restoration at a wooden desk: A pilot study.</em><br> <br> The analysis primarily investigates how people respond to the Mental Arithmetic Task (MAT) in terms of their affective states and physiological arousal, and how their cognitive performance changes between two task administrations. The analysis also checks whether affective, physiological, and cognitive responses differ between settings furnished with or without wood. We base our analysis on self-reported affective states, captured physiological (electrodermal and cardiovascular) activity, and results on the cognitive task (i.e., MAT).</p>
Dataset for the tutorial of supeRbaits R package
<p>Dataset for the tutorial of the R package "supeRbaits" (https://github.com/BelenJM/supeRbaits)</p>
Supplementary Material 1: Original dataset collected during the tracking and mark-release-recapture study and R script used to analyse the data
<p>The original dataset collected in northern Serbia during butterfly behavioural study on two species, <em>Phengaris teleius</em> and <em>Polyommatus icarus</em>. The dataset is provided in two separate CSV files for mark-release-recapture study and for butterfly tracking study. In addition, R script used to preopare the dataset and fit the models is given.</p>
Datasets and R code for: Brood as booty: The effect of colony size and resource value in social insect contests
<p><strong>From the Manuscript: </strong>Animals engage in contests for access to resources like food, mates, and space. Intergroup contests between groups of organisms have received little attention, and it remains unresolved what information groups might use collectively to make contest decisions. We staged whole-colony contests using ant colonies (<em>Temnothorax rugatulus</em>), which perceive conspecific colonies as both a threat and resource from which to steal brood. We recorded individual behaviors and used demographic characteristics as proxies for resource value (number of brood items) and fighting ability (number of workers). We found that ants altered their fighting effort depending on the relative number of workers of their opponent. While the proximate mechanism for this ability remains uncertain, we found that colonies increased fighting when their opponent had relatively more brood, but not if opposing colonies had relatively many more workers. This suggests that ant colonies can use information about opposing colonies that shapes contest strategies. Further, the behavior of opposing colonies were strongly correlated with each other despite colony size differences ranging from 4-51%, consistent with the hypothesis that colonies can use opponent information. The behavior of a distributed, collective system of many individuals, like a eusocial insect colony, thus fits several predictions of contest models designed for individuals if we consider the gain and loss of worker ants analogous to energetic costs accrued during typical dyadic contests.</p>
Datasets and R-codes complementing the Opinion of the Norwegian Scientific Committee for Food and Environment (VKM) "Risk-Benefit Assessment of Sunscreen"
<p>These datasets complement the Opinion of the Norwegian Scientific Committee for Food and Environment (VKM) "Risk-Benefit Assessment of Sunscreen". They contain:</p> <p>i) data on concentration of the UV filters bis-ethyl-hexyloxyphenol methoxyphenyl triazine (BEMT), butyl methoxydibenzoyl methane (BMDBM), 2-ethylhexyl salicylate (EHS), ethylhexyl triazone (EHT), octocrylene (OC), and titanium dioxide in nanoform (NP-TiO<sub>2</sub>) in commercially available sunscreens,</p> <p>ii) data on amount sunscreen used, and</p> <p>iii) data on dermal absorption of the UV filters bis-ethyl-hexyloxyphenol methoxyphenyl triazine (BEMT), butyl methoxydibenzoyl methane (BMDBM), 2-ethylhexyl salicylate (EHS), ethylhexyl triazone (EHT), octocrylene (OC), and titanium dioxide in nanoform (NP-TiO<sub>2</sub>).</p> <p>The data are used in the probabilistic exposure estimations in the Opinion. The data were retrieved from open sources.</p> <p>In addition, the R-codes used to perform the exposure estimation, are included.</p>
Dataset and R code: Effects of temperature and air pollution on emergency ambulance dispatches: a time series analysis in a medium-sized city in Germany
<p>Dataset and R script to replicate results in the manuscript "Effects of temperature and air pollution on emergency ambulance dispatches: a time series analysis in a medium-sized city in Germany", currently under review.</p>
R&D Dataset for LHC Olympics 2020 Anomaly Detection Challenge
<p>This is the first R&D dataset for the LHC Olympics 2020 Anomaly Detection Challenge. It consists of 1M QCD dijet events and 100k W'->XY events, with X->qq and Y->qq. The W', X, and Y masses are 3.5 TeV, 500 GeV and 100 GeV respectively. The events are produced using Pythia8 and Delphes 3.4.1, with no pileup or MPI included. They are selected using a single fat-jet (R=1) trigger with pT threshold of 1.2 TeV. </p> <p>The events are randomly shuffled together, but for the purposes of testing and development, we provide the user with a signal/background truth bit for each event. Obviously, the truth bit will not be included in the actual challenge.</p> <p>These events are stored as pandas dataframes saved to compressed h5 format. For each event, all Delphes reconstructed particles in the event are assumed to be massless and are recorded in detector coordinates (pT, eta, phi). More detailed information such as particle charge is not included. Events are zero padded to constant size arrays of 700 particles, with the truth bit appended at the end. The array format is therefore (Nevents=1.1M, 2101).</p> <p>For more information, including an example Jupyter notebook illustrating how to read and process the events, see the official LHC Olympics 2020 webpage.</p> <p><a href="https://lhco2020.github.io/homepage/">https://lhco2020.github.io/homepage/</a></p> <p><strong>UPDATE May 18 2020</strong></p> <p>We have uploaded a second signal dataset for R&D, consisting of 100k W'->XY with X,Y->qqq (i.e. 3-prong substructure). Everything else about this signal dataset (particle masses, trigger, Pythia configuration, detector simulation) is the same as the previous one described above. </p> <p><strong>UPDATE November 23 2020</strong></p> <p>We now include high-level feature files for the background and 2-prong signal (events_anomalydetection_v2.features.h5) and for the 3-prong signal (events_anomalydetection_Z_XY_qqq.features.h5). To produce the features, we have clustered every event into R=1 jets using the anti-kT algorithm. The features (calculated using fastjet plugins) are the 3-momenta, invariant masses, and n-jettiness variables tau1, tau2 and tau3 for the highest pT jet (j1) and the second highest pT jet (j2):</p> <p>'pxj1', 'pyj1', 'pzj1', 'mj1', 'tau1j1', 'tau2j1', 'tau3j1', 'pxj2', 'pyj2', 'pzj2', 'mj2', 'tau1j2', 'tau2j2', 'tau3j2'</p> <p>The rows (events) in each feature file should be ordered exactly the same as in their corresponding raw event file. For convenience, we have also included the label (1 for signal and 0 for background) as an additional column in the first feature file (events_anomalydetection_v2.features.h5).</p> <p><strong>UPDATE February 11 2021</strong></p> <p>We have included the Delphes detector card and the Pythia8 command files used to produce the R&D datasets.</p> <p><strong>UPDATE April 17 2022</strong></p> <p>It was brought to our attention that somehow the raw events file events_anomalydetection.h5 was never updated to v2, which had a lower generator-level pT threshold (PhaseSpace:pTHatMin = 500) for QCD events to minimize artificial trigger sculpting. This v2 is the version that the features file (events_anomalydetection_v2.features.h5) corresponds to, as well as the Pythia cmnd file (pythia_RnD_qcd.cmnd). Now the raw events file has been brought up to date as well. </p>
Long-term demographic trends and spatio-temporal distribution of past human activity in Central Europe: Comparison of archaeological and palaeoecological proxies (datasets and R scripts)
<p>This digital archive is an outcome of the paper Kolář J., Macek M., Tkáč P., Novák D. & V.Abraham: Long-term demographic trends and spatio-temporal distribution of past human activity in Central Europe: Comparison of archaeological and palaeoecological proxies. Quaternary Science Reviews, 2022</p>
DataSet & R code used for the analysis of "Mechanisms of mobbing call recognition: Exploring featural decoding in great tits"
<p>Data and R code used in a playback experiment exploring the mechanisms of mobbing call recognition in the great tit, Parus major. Accepted in Animal Behaviour (2024). </p> <p>This experiment aimed at testing the hypothesis of simple featural interpretation in the great tit (i.e., the fact that receivers can focus on specific acoustic features rather than complete note recognition). </p> <p>The experiment is organised with two parts: first, we test the response of great tits to artificial calls that possess either none or all of the characteristics present in their own calls (and shared with other Parids), and compare their level of response to natural mobbing calls. </p> <p>As the 'complete' treatment triggered the same level fo response than the natural calls, we then create artifical calls with only one of the four features used to create our artifical mobbing calls (large frequency range, low frequency, noise and harmonics). </p> <p> </p> <p>More information can be obtained by contacting Ambre SALIS (salis.ambre87[at]gmail.com)</p>
Dataset: Invesco BulletShares (R) 2025 Municipal Bond ETF (BSMP) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.