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1,742 results for “activity data”
Data collected for: The contrasted impacts of grasshoppers on soil microbial activities in function of ecosystem productivity and herbivore diet
<p>Herbivory can have contrasted impacts on soil microbes and nutrient cycling, which has stimulated the development of conceptual frameworks exploring the links between below- and aboveground processes. The "productivity model" predicts that herbivores stimulate microbial activities and accelerate nutrient mineralization in productive ecosystems, while they have an opposite effect in less productive ecosystems. In parallel, the "diet model" predicts that herbivores feeding on conservative plants accelerate nutrient cycling while those feeding on exploitative plants decelerate nutrient cycling, due to changes in litter inputs. Since these two frameworks can lead to conflicting predictions in some cases, experimental evidence combining herbivore diet and productivity is required.</p> <p>During two consecutive years, we conducted an experiment controlling the presence of three grasshopper species consuming either grasses, forbs or both in twelve natural and managed alpine grasslands of contrasted productivities. In order to assess the effects of herbivory on soil microbes, we measured their enzymatic activities, their biomass and the soil potential nitrogen mineralization (PNM). Soil and vegetation characteristics were also determined in order to test if they modulated the effects of herbivory on microbes.</p> <p>Contrary to the predictions of the diet model, the effects of herbivory on microbial characteristics did not depend on the herbivores diet but relied on ecosystem productivity. The most productive sites were characterized by exploitative plant species which depleted N resources in the soil, and by microbes producing relatively few extracellular enzymes, leading to a lower PNM. Herbivory increased microbial biomass and decreased the production of extracellular enzymes in those sites, possibly through the stimulation of root exudates produced by exploitative species. The least productive sites were characterized by conservative plants, which led to the sequestration of soil C, and by microbes having a resource acquisition strategy (more extracellular enzymes, higher PNM). Herbivory decreased microbial biomass and increased the production of extracellular enzymes in those sites. This pattern can be explained by the loss of carbon associated with insect respiration, which increases the need for microbes to acquire resources and by a lower production of root exudates by conservative species. Therefore, the effects of two years of herbivory on soil microbes were at odds with the productivity model, which focuses instead on longer term effects corresponding to herbivory-induced changes in plant species composition. This highlights the multidimensional feature of the impacts of herbivory on ecosystem functioning, both in space and time.</p>
Data and code for Barrett, Martin, and Shepherd (2022) "Manipulation-specific cortical activity as mice handle food"
<p>This dataset contains the tracking data, spiking data, and ethograms necessary to reproduce the results of Barrett, Martin, and Shepherd (2022) "Manipulation-specific cortical activity as mice handle food". Also included is Matlab and R code that generates all of the figures, tables, and stats in the aforementioned paper.</p>
Supplementary Simulation Data for "Conformational Selection of a Tryptophan Side Chain Drives the Generalized Increase in Activity of PET Hydrolases Through a Ser/Ile Double Mutation"
<p>Additional simulation data for "Conformational Selection of a Tryptophan Side Chain Drives the Generalized Increase in Activity of PET Hydrolases Through a Ser/Ile Double Mutation", which has been submitted as a preprint to ChemRxiv.</p>
Data from: Human avoidance, selection for darkness and prey activity explain wolf diel activity in a highly cultivated landscape
<p>Wildlife that share habitats with humans with limited options for spatial avoidance must either tolerate frequent human encounters or concentrate their activity on those periods with the least risk of encountering people. Based on 5,259 camera trap images of adult wolves from eight territories, we analyzed the extent to which diel activity patterns in a highly cultivated landscape with extensive public access (Denmark) could be explained by diel variation in darkness, human activity, and prey (deer) activity. A resource selection function that contrasted every camera observation (use) with 24 alternative hourly observations from the same day (availability), revealed that diel activity correlated with all three factors simultaneously with human activity having the strongest effect (negative), followed by darkness (positive) and deer activity (positive). A model incorporating these three effects had lower parsimony and classified use and availability observations just as well as a 'circadian' model that smoothed the use-availability ratio as a function of time of the day. Most of the selection for darkness was explained by variation in human activity, supporting the notion that nocturnality (proportion of observations registered at night vs. day at the equinox) is a proxy for temporal human avoidance. Contrary to our expectations, wolves were no more nocturnal in territories with unrestricted public access than in territories where public access was restricted to roads, possibly because wolves in all territories had few possibilities to walk more than a few hundred meters without crossing roads. Overall, Danish wolf packs were 6.5 (95% CI: 4.6-9.6) times more active at night than at daylight, which makes them amongst the most nocturnally active wolves reported so far. These results confirm the prediction that wolves in habitats with limited options for spatial human avoidance, invest more in temporal avoidance.</p>
Data for "Sintering activation energies of anisotropic layered and particle alumina/zirconia-based composites and their mechanical response"
<p>The dataset contains several folders that provide open data files for the manuscript "Sintering activation energies of anisotropic layered and particle alumina/zirconia-based composites and their mechanical response".</p>
Data from: Active restoration accelerates recovery of tropical forest bird assemblages over two decades
<p>Choosing effective methods to restore habitat for the diverse faunal assemblages of tropical forests is hampered by lack of long-term data comparing multiple restoration treatments. We conducted area counts of bird assemblages over 12 years (~5-17 years since restoration) in a blocked experiment with two active planted treatments (tree plantations and applied nucleation) and a passive restoration treatment (natural regeneration) replicated at 11 sites in Costa Rica. We also surveyed six pastures and five remnant forest sites to assess recovery of avian species richness, composition, forest specialists, and range-restricted species in restoration plots relative to degraded and reference systems. Restoration treatments showed increased resemblance of avian assemblages to remnant forest over time. Applied nucleation proved equally effective as plantation, despite a reduced planted area, whereas natural regeneration recovered more slowly. Assemblage-level trends in avian species richness and compositional similarity to reference forest are underpinned by reductions in use by pasture birds and by gradual increases in richness of forest-affiliated species. Because forest-affiliated species tend to have narrower distributions than the open-country species they replace, forest restoration can reduce biotic homogenization at the local scale. Restoration practitioners should consider applied nucleation as an alternative to standard plantations if seeking rapid recovery of bird assemblages. However, the ecological return on investment from natural regeneration increases over a couple of decades. Managers should monitor trends in forest-affiliated and range-restricted species to track the recovery of the full avian assemblages, since coarse metrics like species richness and overall compositional similarity may plateau relatively quickly.</p>
Effect of psychoactive substances on cardiac and locomotory activity-Procambarus virginalis-DATA
<p>This Effect of psychoactive substances on cardiac and locomotory activity<em>-Procambarus virginalis</em></p> <p>The associated dataset investigates the impact of environmentally relevant levels of psychoactive compounds on the early developmental stages of marbled crayfish (Procambarus virginalis). The compounds analyzed include sertraline, methamphetamine, and a mixture of citalopram, oxazepam, sertraline, tramadol, venlafaxine, and methamphetamine, each at a concentration of 1 μg L-1. The dataset assesses cardiac and locomotory activity on day four and day eight of exposure, respectively.</p> <p>it is a condition of the CENAKVA RI financing provider to record accesses to open data. Data can be requested at the following email: <strong>dubova@frov.jcu.cz</strong></p> <p>or visit the CENAKVA RI website:<br>https://www.frov.jcu.cz/en/faculty/faculty-parts/south-bohemian-research-centre-for-aquaculture-and-biodiversity-of-hydrocenoses-cenakva/large-research-infrastructure-cenakva</p>
Data from: Grazing herbivores reduce herbaceous biomass and fire activity across African savannas
<p>Fire and herbivory interact to alter ecosystems and carbon cycling. In savannas, herbivores can reduce fire activity by removing grass biomass, but the size of these effects and what regulates them remain uncertain. To examine grazing effects on fuels and fire regimes across African savannas, we combined data from herbivore exclosure experiments with remotely sensed data on fire activity and herbivore density. We show that, broadly across African savannas, grazing herbivores substantially reduce both herbaceous biomass and fire activity. The size of these effects was strongly associated with grazing herbivore densities and, surprisingly, was mostly consistent across different environments. A one-zebra increase in herbivore biomass density (~100 kg/km<sup>2</sup> of metabolic biomass) resulted in a ~53 kg/ha reduction in standing herbaceous biomass and a ~0.43 percentage point reduction in burned area. Our results indicate that fire models can be improved by incorporating grazing effects on grass biomass.</p>
Data from: Dissecting gene activation and chromatin remodeling dynamics in single human cells undergoing reprogramming
<p>During cell fate transitions, cells remodel their transcriptome, chromatin, and epigenome; however, it has been difficult to determine the temporal dynamics and cause-effect relationship between these changes at the single-cell level. Here, we employ the heterokaryon-mediated reprogramming system as a single-cell model to dissect key temporal events during early stages of pluripotency conversion using super-resolution imaging. We reveal that, following heterokaryon formation, the somatic nucleus undergoes global chromatin decompaction and removal of repressive histone modifications H3K9me3 and H3K27me3 without acquisition of active modifications H3K4me3 and H3K9ac. The pluripotency gene OCT4 (POU5F1) shows nascent and mature RNA transcription within the first 24 h after cell fusion without requiring an initial open chromatin configuration at its locus. NANOG, conversely, has significant nascent RNA transcription only at 48 h after cell fusion but, strikingly, exhibits genomic reopening early on. These findings suggest that the temporal relationship between chromatin compaction and gene activation during cellular reprogramming is gene context dependent. </p>
Data for "The Role of Mood and Stress in Physical Activity Engagement: Insights from Ecological Momentary Assessment
<p>Data collected in the SmartPA study in a joint effort from the Department of Psychology at the University of Salzburg (Jens Blechert) and the Ludwig Boltzmann Institute for Digital Health and Prevention Salzburg.</p>
Data for Non-Equilibrium Sensing of Volatile Compounds Using Active and Passive Analyte Delivery
<blockquote> <p>Version 2: Added missing files to <code>sniffing_data.zip</code></p> </blockquote> <p>See GitHub repository for data processing functions and examples: <a href="https://github.com/soerenbrandt/sniffing-sensor">https://github.com/soerenbrandt/sniffing-sensor</a></p> <p><strong>Abstract</strong>:<br>Sensor technologies have allowed us to outperform the human senses of sight, hearing, and touch; however, the development of artificial noses is significantly behind their biological counterparts. This is largely due to the complexity of natural olfaction, as it incorporates complex fluid dynamics within the nasal anatomy together with the response patterns of hundreds to thousands of unique molecular-scale receptors for odor interpretation. We designed a sensing approach to identify volatiles that exploits time-dependent information from a single sensor (here, the reflectance spectra from a mesoporous one-dimensional photonic crystal) by augmenting and accentuating differences in the non-equilibrium mass-transport dynamics of vapors stemming from their distinct physicochemical properties, thus obviating the need for a large sensor array. By training a machine learning algorithm on the sensor output, we clearly identify polar and nonpolar volatile organic compounds, determine the mixing ratios of binary mixtures, and accurately predict the boiling point, flash point, vapor pressure, and viscosity of several volatile liquids within those used for training as well as compounds unknown to the model. We further implement a bioinspired active sniffing approach, in which the fluid dynamics and patterns of analyte delivery are controlled, enabling an additional modality of differentiation and reducing the duration of data collection and analysis to seconds. These results outline a strategy to build accurate and rapid artificial noses for volatile liquids that can provide useful information on chemicals such as their composition and properties, and can be applied in a variety of fields, including disease diagnosis, hazardous waste management, and healthy building monitoring.</p>
Data and Reproducible Analysis For: "Fine-Scale Associations Between Land Cover Composition and the Oviposition Activity of Native and Invasive Aedes Vectors of La Crosse Virus"
<h1><strong>Data and Reproducible Analysis For: "Fine-Scale Associations Between Land Cover Composition and the Oviposition Activity of Native and Invasive Aedes Vectors of La Crosse Virus"</strong></h1> <p>This repository contains pre-processed data sets and code scripts to reproduce the data processing and analyses that are presented in the corresponding manuscript. Some minor pre-processing was completed before presenting this -- namely, the land cover raster was clipped to the study area of Knox County, Tennessee, USA, prior to placing in the repository to reduce the file size. </p> <h2><strong>How to use this repository to reproduce results </strong></h2> <p>This repository is designed to support the reproduction of analyses in the associated manuscript. The entire project can be downloaded and stored anywhere on your computer, as long as the file structure is not altered. The project contains folders with all data sets and code scripts necessary for analysis.</p> <p><strong>What you will need: </strong><br> - Installed R and RStudio for purely spatial cluster and global model analyses<br> - Basic understanding of how to open R and run code </p> <p><strong> You do NOT need:</strong><br> - To download or install R packages on your own; that is taken care of within this environment<br> - To write any code <br> - To set up any working directories in R </p> <h3><strong>Important: Using `renv`</strong></h3> <p>Short Version: When you open the R project, run `renv::restore()` and follow the prompts to install the necessary R packages. </p> <p>The R package `renv` was used to create a <strong>project library</strong>, which contains all R packages that are used by the project. The packages in the project library are <strong>the versions used during the original analysis</strong>. This means that if any packages are updated by developers in ways that would change the results of the analysis, this project can still produce the original results because of `renv`. When you open this project for the first time, `renv` will automatically download and install itself and ask you to run `renv::restore()`. <strong>You should run `renv::restore()` to automatically download and install all of the packages within this reproducible environment</strong>. </p> <h2><strong>## Basic step-by-step guide:</strong></h2> <p>- 1. Download the entire repository by clicking "Code -> Download ZIP" on GitHub or by downloading the ZIP file in Zenodo<br>- 2. Extract the ZIP file anywhere on your computer (do not change the structure of the files once extracted)<br>- 3. In RStudio, click *File -> Open Project* and browse to the location where you extracted the repository; in the repository file, open the knoxaedeslandcover R Project file <br>- 4. Open any of the R scripts in the `analysis/` folder<br>- 5. Run the code `renv::restore()` in the script or in the console and follow the prompt to install the packages <br> - Now you can run the R Scripts; start from the top with loading the packages and data, then work your way down line-by-line</p> <h3><strong># `analysis/` Folder</strong></h3> <p>The `analysis/` folder contains scripts for processing data and conducting analyses. Each file is an R script that should be opened in R studio. The first shows how to process and aggregate the various raw data files; if you are only interested in reproducing analyses from the manuscript, you can skip to the second file and work from there. </p> <p><strong><em>## Files within the `analysis/` folder</em></strong></p> <p>The files are numbered in the order that they were run for the original analysis. In this case, none of the analyses are dependent on the others, so they can technically be used in any order. The numbers associated with each file describe the order that the analyses would normally be run. </p> <p> - `(1)dataprep.R` contains the code for cleaning and combining the land cover, climate, and mosquito data -- this includes calculating the land cover percentages at different scales and calculating weekly and timelagged climate values<br> - `(2)summary_analysis.R` contains code for reproducing summary data and creating graphs from the manuscript<br> - `(3)variable_selection.R` contains code for asssessing collinearity and fitting models to identify the best fitting variables for each speceis<br> - `(4)finalmodels.R` contains code for fitting the final models using the selected variables for each species </p> <h3><strong># `data/` Folder</strong></h3> <p>This folder contains several datasets, including one that compiles them all for analyses (`knox_joined`). The raw data are included to show how the data was processed and aggregated, but the individual raw data files are not needed for analyses. See `data dictionary.txt` for a description of all attributes contained within each file. </p> <p><strong><em>## Files within the `data/` folder</em></strong></p> <p> - `knox22_joined.RDS` contains a cleaned and joined version of land cover, climate, and mosquito data in R Data Serialization format, which maintains predefined factor and numeric designations for columns. <br> - `knox22_joined.csv` contains a cleaned and joined version of land cover, climate, and mosquito data in CSV format -- identical to 'knox22_joined.RDS'<br> - `sites22.csv` contains the names, site codes, and coordinates of the study sites<br> - `aedes22_clean.csv` contains the raw mosquito collection data for the study without any climate or land cover information <br> - `NLCD_2019_landcover_clippedtoKnox.tif` contains the NLCD land cover data, already clipped to Knox County, TN, USA<br> - `knox22_temperature.csv` contains raw daily temperatures for the city of Knoxville in 2022<br> - `knox22_rainfall.csv` contains raw daily precipitation for the city of Knoxville watersheds in 2022<br> - `rainfall_stations.csv` contains the descriptions, approximate street addresses, and geographic coordinates for rainfall monitoring sites <br> - `data dictionary.txt` file that defines column names and other data attributes for every dataset </p> <h3><strong># `renv/` Folder</strong></h3> <p>The `renv/` folder contains bits and pieces needed for the `renv` package. Nothing should be altered in this folder. </p> <p> </p> <h2><strong>References for source data </strong></h2> <p> - Some of the data in this repository were originally obtained from open access sources. </p> <p> - Land cover data was obtained from the National Land Cover Database (NLCD) 2019 data product, specifically the "NLCD 2019 Land Cover (CONUS)" product. The original, unclipped raster can be freely downloaded here: https://www.mrlc.gov/data/nlcd-2019-land-cover-conus</p> <p> - Temperature data was downloaded from the United States National Oceanic and Atmospheric Administration (NOAA) weather station for Knoxville, Tennessee. The source data can be downloaded from this site: https://www.weather.gov/mrx/tysclimate</p> <p> - Rainfall data was obtained from the City of Knoxville rainfall data website, located here: https://www.knoxvilletn.gov/government/city_departments_offices/engineering/stormwater_engineering_division/rainfall_data</p> <p> - All mosquito collection data was collected directly by the manuscript authors</p>
Raw data to: Acetyl-CoA synthetase activity is enzymatically regulated by lysine acetylation using acetyl-CoA or acetyl-phosphate as donor molecule
<p>Initial configuration (PDB) and TIGER2hPE ensemble of all four simulations (R1-4) reported in this study in DCD trajectory format:</p> <ol> <li>AcuA + AcsA + Acetyl-CoA</li> <li>Acua + AcsA + Acetyl-CoA (AcuA:K549 deprotonated)</li> <li>AcuA + AcsA + CoA + AcP (Acetyl-Phosphate)</li> <li>AcuA + AcsA + Desulfo-CoA</li> </ol> <p> </p>
Data and code for: A standardised approach to quantifying activity in domestic dogs
<p>Objective assessment of activity via accelerometry can provide valuable insights into dog health and welfare. Common activity metrics involve using acceleration cut-points to group data into intensity categories and reporting the time spent in each category. Lack of consistency and transparency in cut-point derivation makes it difficult to compare findings between studies. We present an alternative metric for use in dogs: the acceleration threshold <em>(</em>as a fraction of standard gravity<em>,1g = 9.81m/s<sup>2</sup>)</em> above which the animal's X most active minutes are accumulated (MX<sub>ACC</sub>) over a 24-hour period. We report M2<sub>ACC,</sub> M30<sub>ACC</sub> and M60<sub>ACC</sub> data from a colony of healthy beagles (n=6) aged 3-13 months. To ensure that reference values are applicable across a wider dog population, we incorporated labelled data from beagles and volunteer pet dogs (n=16) of a variety of ages and breeds. The dogs' normal activity patterns were recorded at 200 Hz for 24-hours using collar-based Axivity-AX3 accelerometers. We calculated acceleration vector magnitude and MX<sub>ACC</sub> metrics. Using labelled data from both beagles and pet dogs, we characterise the range of acceleration outputs exhibited for a variety of behaviours, enabling meaningful interpretation of MX<sub>ACC</sub>. These metrics will help standardise measurement of canine activity, inform development of exercise guidelines and adherence monitoring, and serve as outcome measures for veterinary and translational research. This repository contains two files: 1) `LMM_input_data.csv`, a spreadsheet file containing the raw data used to explore the effect of modifying epoch length and sample frequency on aggregate activity metrics using linear mixed effects models as described in the manuscript. There is one row per dog per epoch length, sample frequency and age combination, and 2) `getMostActiveMinsThresh.m`, a MATLAB function used to compute the MX ACC outcome metrics that are explored in the manuscript.</p>
Fig.11 in The Experimental Data On Sun-Basking Activity Of European Pond Turtle Emys Orbicularis In Natural Climate In Latvia: Dynamics And Correlation With The Meteorological Factors
Fig.11. Ranking of meteorological factors by the quantity of significant positive or negative correlations with the number of sun-basking Emys orbicularis in the interval 8d"Nsbd"21.
Fig.3 in The Experimental Data On Sun-Basking Activity Of European Pond Turtle Emys Orbicularis In Natural Climate In Latvia: Dynamics And Correlation With The Meteorological Factors
Fig.3. Basic forms of sun-basking activity of Emys Fig.4. Basic forms of sun-basking activity of Emys orbicularis registered in the study: lying in the orbicularis registered in the study: heating under shadow. the sun in the shoal.
Figure 2 in Data on nocturnal activity of Darevskia rudis (Bedriaga, 1886) (Sauria: Lacertidae) in Central Black Sea Region, Turkey
Figure 2: The major nocturnal activities of Darevskia rudis. (a: leaving the shelter, b: mobility in its habitat, c: foraging, d: fronting to artificial light source and e: feeding).
Concise Synthesis of Pseudane IX, its N-Oxide and Novel Carboxamide Analogs with Antibacterial Activity - NMR Data
<p>This archive contains raw 1H/13C FIDs and associated data in Bruker-specific format that can be viewed with Bruker’s TopSpin or other appropriate NMR processing software. The subfolders are named in accordance with the compound numbering in the associated research paper (Concise Synthesis of Pseudane IX, its N-Oxide and Novel Carboxamide Analogs with Antibacterial Activity).</p> <p>Correspondence: angelov@uni-plovdiv.bg</p>
Data Sets "Modulation of electrical activity of proteinoid microspheres with chondroitin sulfate clusters"
<p>Data Sets "Modulation of electrical activity of proteinoid microspheres with chondroitin sulfate clusters"</p>
Data for: Activity of predators in seabird colonies decreases during the darkest compared to the brightest phase of the diel cycle below, but not above, the Arctic Circle
<p>The description of the data and how they were collected is in the associated open access publication: Huffeldt, N.P., F.M. van Beest, H.L. Kenyon, J. Danielsen, and T. Guilford. (2024) Activity of predators in seabird colonies decreases during the darkest compared to the brightest phase of the diel cycle below, but not above, the Arctic Circle. <em>Arctic, Antarctic, and Alpine Research</em> 56: 2367262. https://doi.org/10.1080/15230430.2024.2367262</p>
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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.