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Belowground responses to altered precipitation regimes in two semi-arid grasslands
Predicted climate change extremes, such as severe and prolonged drought, may profoundly impact biogeochemical processes like carbon and nitrogen cycling in water-limited ecosystems. To increase our understanding of how extreme climate events impact belowground ecosystem processes, we investigated the effects of five years of severe growing season drought and two-month delay in monsoon precipitation on belowground productivity and biogeochemical processes in two semi-arid grasslands. This experiment takes place during the fifth year of the Extreme Drought in Grassland Experiment (EDGE) at the Sevilleta National Wildlife Refuge (SNWR), a Long-Term Ecological Research in central New Mexico, USA. The two grassland sites a Chihuahuan Desert grassland dominated by Bouteloua eriopoda and Great Plains grassland dominated by B. gracilis are ~5km apart in the SWNR. The EDGE platform was established in the spring of 2012 (pre-treatment). Each site contains three treatments (ten replicates): ambient rainfall, extreme growing season drought, and delayed monsoon. The extreme drought treatment reduces growing season rainfall (April through September) each year by 66%, which equates to a 50% reduction of annual precipitation while maintaining natural precipitation patterns. There are 10 replicates per treatment within each site. All plots are 3 x 4 m in size and are paired spatially into blocks with treatments assigned randomly within a block. We measured an array of belowground and biogeochemical variables. Each variable was measured either once, twice, or three times (specific information on sampling scheme for each measured variable in methods section). Belowground net primary productivity, standing crop root biomass, total organic carbon, and total nitrogen were measured once. Extractable organic carbon, extractable total nitrogen, microbial biomass carbon, microbial biomass nitrogen and extracellular enzymes were measured twice. Available soil nitrate, available soil ammonium,
Consumer Front Plant Trait Sampling in Two Virginia Coast Salt Marshes, 2018
A consumer front forms when dense aggregations of herbivores form at the edge of a resource. The front then propagates through the ecosystem in search of additional resources. In U.S. Atlantic salt marshes, the purple marsh crab, Sesarma reticulatum, creates consumer fronts as it grazes the smooth cordgrass, Spartina alterniflora. Sesarma fronts typically form at the heads of tidal creeks and create distinct zonation between the low marsh, tall-form Spartina zones and the high marsh, short-form Spartina zones, with a denuded band of mudflat in between. Over time, Sesarma consumer fronts are moving directionally inland towards the short-form zone and away from the tall-form zone. This movement inland allows for tall-form Spartina to revegetate, preventing further marsh loss. However, it remains unknown why these consumer fronts are moving inland. To test the hypothesis that plant traits (i.e., nutritional quality, palatability) are driving the Sesarma consumer front inland, we collected Spartina from consumer fronts at 8 unique creekheads across two marsh systems on the Eastern Shore of Virginia (4 consumer fronts at Upper Phillips Creek and 4 at Upshur Creek). Spartina was collected from 15 replicate quadrats (0.0625m^2) from the tall-form low marsh zones (TSA) and from the short-form low marsh zones (SSA) at each creekhead. The short-form zone was delineated into two additional zones, an interior (SSA-I) and an exterior (SSA-E), to assess if there were any differences in plant traits between Spartina being actively grazed (SSA-E, adjacent to consumer front) and those that have not been grazed (SSA-I, 2 meters from consumer front). Collected Spartina plants were then processed for a series of plant traits that can influence herbivore preference.
Two-minute averaged net community production in seawater estimated along the Antarctic Circumnavigation Expedition during the austral summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>During the Antarctic Circumnavigation Expedition (ACE) in the austral summer of 2016/2017, seawater O2/Ar ratios were measured underway from the ship's flow-through seawater system. High-resolution net community production (NCP) in units of mmol O2 m-2 day-1 was derived from delta O2/Ar and National Centers for Environmental Prediction (NCEP) reanalysis winds followed by a linear correction for sea-ice.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_ncp_linear_correction.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> <li>change_log.txt, metadata, text</li> </ul> <p><strong>Change log</strong></p> <p>v1.1 - data reprocessed using different version of sea ice.</p> <ul> <li>data file reprocessed</li> <li>README updated to reflect change in processing</li> <li>change log added to dataset</li> </ul> <p>v1.0 - initial release of dataset</p>
Curlie Enhanced with LLM Annotations: Two Datasets for Advancing Homepage2Vec's Multilingual Website Classification
<h3>Advancing Homepage2Vec with LLM-Generated Datasets for Multilingual Website Classification</h3> <p>This dataset contains two subsets of labeled website data, specifically created to enhance the performance of Homepage2Vec, a multi-label model for website classification. The datasets were generated using Large Language Models (LLMs) to provide more accurate and diverse topic annotations for websites, addressing a limitation of existing Homepage2Vec training data.</p> <p><strong>Key Features:</strong></p> <ul> <li><strong>LLM-generated annotations:</strong> Both datasets feature website topic labels generated using LLMs, a novel approach to creating high-quality training data for website classification models.</li> <li><strong>Improved multi-label classification:</strong> Fine-tuning Homepage2Vec with these datasets has been shown to improve its macro F1 score from 38% to 43% evaluated on a human-labeled dataset, demonstrating their effectiveness in capturing a broader range of website topics.</li> <li><strong>Multilingual applicability:</strong> The datasets facilitate classification of websites in multiple languages, reflecting the inherent multilingual nature of Homepage2Vec.</li> </ul> <p><strong>Dataset Composition:</strong></p> <ul> <li><strong>curlie-gpt3.5-10k:</strong> 10,000 websites labeled using GPT-3.5, context 2 and 1-shot</li> <li><strong>curlie-gpt4-10k:</strong> 10,000 websites labeled using GPT-4, context 2 and zero-shot</li> </ul> <p><strong>Intended Use:</strong></p> <ul> <li>Fine-tuning and advancing Homepage2Vec or similar website classification models</li> <li>Research on LLM-generated datasets for text classification tasks</li> <li>Exploration of multilingual website classification</li> </ul> <p><strong>Additional Information:</strong></p> <ul> <li><strong>Project and report repository:</strong> https://github.com/CS-433/ml-project-2-mlp</li> </ul> <p><strong>Acknowledgments:</strong></p> <p>This dataset was created as part of a project at EPFL's Data Science Lab (DLab) in collaboration with <a href="https://people.epfl.ch/robert.west">Prof. Robert West</a> and <a href="https://tizianopiccardi.github.io/" rel="nofollow">Tiziano Piccardi.</a></p>
Data Associated with Chemical Cartography with APOGEE: Two-process Parameters and Residual Abundances for 288,789 Stars from Data Release 17
<p>Stellar abundance measurements are subject to systematic errors that induce extra scatter and artificial correlations in elemental abundance patterns. We derive empirical calibration offsets to remove systematic trends with surface gravity log(g) in 17 elemental abundances of 288,789 evolved stars from the SDSS APOGEE survey. We fit these corrected abundances as the sum of a prompt process tracing core-collapse supernovae and a delayed process tracing Type Ia supernovae, thus recasting each star's measurements into the amplitudes A_cc and A_Ia and the element-by-element residuals from this two-parameter fit. Here we present the log(g)-calibrated abundances, fit parameters, process amplitudes, and element-by-element abundance residuals of 288,789 stars (310,427 spectra) in APOGEE DR17 that accompany <a href="https://arxiv.org/abs/2403.08067" target="_blank" rel="noopener">the paper</a>.</p> <p>calibration_values_final.dat contains all derived calibration offsets, including the grids of log(g) calibration offsets and zero-point offsets for two-process model analysis. The first five rows of this catalog are reproduced in Table 2 of the paper.</p> <p>logg_calib_example.ipynb is a Jupyter notebook containing Python code to load calibration_values_final.dat, extract the log(g) calibration offsets for specific element, and apply calibration offsets to 10 sample stars.</p> <p>2process_residual_abund_catalog_final.fits is the catalog of 310,427 APOGEE DR17 spectra (288,789 unique stars) containing calibrated abundances, two-process fit parameters, and abundance residuals. A full listing of columns in this catalog is given in Table 5 of the paper.</p> <p>catalog_examples.ipynb is a Jupyter notebook containing Python code to load 2process_residual_abund_catalog_final.fits, cross match with other catalogs (using AstroNN and the APOGEE DR17 Globular Cluster Value-Added Catalog as examples), and make some example plots utilizing the cross-matched data.</p>
Two Wearable Sensor Datasets recording the Countermovement Jump
<p>These datasets come from two independent studies using wearable inertial sensors to estimate countermovement jump performance. The participants were healthy sports science students, free of injury, all of whom had given their prior written consent. Ethical approval was given by the governing institutions’ ethics committees, which included further analysis of the data.</p> <ul> <li><strong>Smartphone Dataset:</strong> <ul> <li>119 valid jumps</li> <li>Peak power 40.7 +/- 8.9 W/kg</li> <li>22 males, 10 females (26.5 +/- 4.1 yrs; standing height 1.74 +/- 0.08 m; body mass 70.0 +/- 10.9 kg)</li> <li>Redmi 9T phone (Xiaomi Technology, Beijing, China)</li> <li>128 Hz sampling frequency</li> <li>Accelerometer & gyroscope</li> <li>Handheld at sternum level</li> <li>Mascia, G.; De Lazzari, B.; Camomilla, V. Machine learning aided jump height estimate democratization through smartphone measures. Frontiers in Sports and Active Living 2023, 5, 1112739. <a href="https://doi.org/10.3389/fspor.2023.1112739">https://doi.org/10.3389/fspor.2023.1112739</a>.</li> </ul> </li> <li><strong>Accelerometer Dataset:</strong> <ul> <li>347 valid jumps</li> <li>Peak power 45.1 +/- 7.6 W/kg</li> <li>48 males, 25 females (21.6 +/- 3.3 yrs; standing height 1.75 +/- 0.10 m; body mass 71.2 +/- 15.1 kg)</li> <li>Trigno sensor (Delsys Inc, MA, USA)</li> <li>250 Hz sampling frequency</li> <li>Accelerometer</li> <li>Taped to lower back (L4)</li> <li>White, M.G.E.; Bezodis, N.E.; Neville, J.; Summers, H.; Rees, P. Determining jumping performance from a single body-worn accelerometer using machine learning. PLOS ONE 2022, 17, e0263846. <a href="https://doi.org/10.1371/journal.pone.0263846">https://doi.org/10.1371/journal.pone.0263846</a></li> </ul> </li> </ul> <p>MATLAB .mat files</p> <p>This repository was used by the paper currently under review for the open journal Mathematics:</p> <p>White, M.; De Lazzari, B.; Bezodis, N., Camomilla, V. Title. Mathematics 2024, 1, 0. Wearable Sensors for Athletic Performance: A Comparison of Discrete and Continuous Feature Extraction Methods for Prediction Models</p>
Simulated heating energy demand for two residential neighbourhoods
<p>The large-scale and comprehensive artificial dataset introduced in this research reflects the energy demands of two neighbourhoods and with some reasonable limitations mimics monitoring campaigns otherwise collected on-site from buildings in use. The monitoring campaigns are created using white-box simulation models for single-family houses representing typical neighbourhoods in Flanders. The datasets are generated using Dymola and the IDEAS package embedded in TEASER. Each house varies in geometry, size, envelope properties, occupancy schedules, and installed gas heating systems. In this research, two datasets are created, one reflecting the properties of a low-performing building stock dating before the introduction of the EPBD (2006), and the other reflecting properties of a well-performing stock built after 2006. The envelope properties for older houses are allocated using EPC data grouped in four construction periods, while for newly built houses the properties are based on EPB reports, both were collected in Flanders. The datasets include heavy-weight houses in a detached, semi-detached, or terraced typology. Furthermore, the houses are simulated as one or two-zone buildings, depending on the number of floors which range from one to three floors. In the simulations, a natural infiltration model is implemented as well as a stochastic occupant behaviour model mimicking gains from occupants and appliances. Due to the complexity of the large-scale simulation, the heating system is post-processed in a data-driven approach and the heat source for both datasets are gas-fired heating systems. In total six system configurations are considered including condensing and non-condensing boilers with three types of domestic hot water (DHW) sub-systems (no integrated DHW, direct and with a storage tank). For all configurations, a variable production efficiency is considered dependent on the load ratio. The urban-scale simulation is carried out at a 10-minute frequency for the weather data assuming the location of Heverlee (Belgium) in the year 2016.<br>The original purpose of this dataset was the development of statistical tools for the assessment of the heat loss coefficient of the building fabric. However, the generated artificial datasets provide a large spectre of usually difficult-to-measure inputs suitable to assess the importance of different components in the overall energy balance. Even though the original work looked into individual building behaviour, the datasets can be also used from an urban perspective for energy planning purposes.</p>
Analysis of two Methods for Aircraft Fuel Requirement Calculations in the Context of a novel Methodological Framework for LCA of Sustainable Aviation
<p>This Microsoft Excel file contains equations to compare different approaches to calculate fuel efficiency ("energy use" in [MJ/t*km]) of aircraft over a specific distance at a specific payload. </p> <p>Two approaches are compared: A novel approach by <a href="10.1016/j.scitotenv.2023.163881" target="_blank" rel="noopener">Su-ungkavatin et al.</a> and the more established approach well documented by eg. <a href="https://www.fzt.haw-hamburg.de/pers/Scholz/arbeiten/TextBurzlaff.pdf" target="_blank" rel="noopener">Burzlaff</a> or <a href="http://www.aircraftmonitor.com/uploads/1/5/9/9/15993320/aircraft_payload_range_analysis_for_financiers___v2.pdf" target="_blank" rel="noopener">Ackert</a>.</p> <p>This work augments a Letter to the Editor we submitted to the journal <a href="https://www.sciencedirect.com/journal/science-of-the-total-environment" target="_blank" rel="noopener">Science of the Total Environment</a>.</p>
Two-bubble simulation and gravitational wave spectrum codes and data
<p><span>Code and data used in the paper with title</span><a href="https://doi.org/10.1103/PhysRevD.104.075039"><span> <em>Vacuum bubble collisions: from microphysics to gravitational waves </em>by Oliver Gould, Satumaaria Sukuvaara, and David Weir</span></a><span> [</span><a href="https://arxiv.org/abs/2107.05657"><span>arXiv:2107.05657</span></a><span>]. </span></p> <p><span>The field simulation and gravitational wave spectrum calculation codes are based on Gravitational radiation from colliding vacuum bubbles by Arthur Kosowsky, Michael S. Turner and Richard Watkins [</span><a href="https://inspirehep.net/literature/324187"><span>Inspire</span></a><span>].</span></p> <p><span>Contains files:</span></p> <ul> <li> <p><span>two_bubbles_code-v1.0.1.zip is a snapshot of a</span><a href="https://version.helsinki.fi/two_bubbles/two_bubbles_code/"><span> git repository</span></a><span>, corresponding to</span><a href="https://version.helsinki.fi/two_bubbles/two_bubbles_code/-/tree/v1.0.1?ref_type=tags"><span> commit v1.0.1</span></a><span>. Contains the codes with which the majority of the data was produced.</span><span><br><br></span></p> </li> <li> <p><span>two_bubbles_data-v1.0.1.zip is a snapshot of a</span><a href="https://version.helsinki.fi/two_bubbles/two_bubbles_data/"><span> git repository</span></a><span>, corresponding to</span><a href="https://version.helsinki.fi/two_bubbles/two_bubbles_data/-/tree/v1.0.1?ref_type=tags"><span> commit v1.0.1</span></a><span>. It contains the majority of data used in the paper. Note however that the simulation pickle files are examples run on a coarser lattice due to Zenodo file size restrictions. Apart from few exceptions, the data in this file was produced by the codes in two_bubbles_code-v1.0.1.zip.</span><span><br><br></span></p> </li> </ul> <p><span>README.md files, specifying and explaining the contents and usage, are included within. The v1.0.1 of</span><a href="https://version.helsinki.fi/two_bubbles/two_bubbles_code/-/blob/v1.0.1/README.md?ref_type=tags"><span> </span><span>code README.md</span></a><span> and the</span><a href="https://version.helsinki.fi/two_bubbles/two_bubbles_data/-/blob/v1.0.1/README.md?ref_type=tags"><span> </span><span>data README.md</span></a><span> can be found from the repositories as well.</span></p> <p><span>The update v1.0.1 updates the README and fixes a small error in the calculation of the gravitational wave spectrum. We thank Toby Opferkuch for pointing this out. The error in the code does not affect the results in two_bubbles_data-v1.0.0.zip or the paper as they were produced with a slightly earlier version of the code, before the appearance of this error. The version two_bubbles_data-v1.0.1 updates the README, clarifying some points.</span></p>
A laser-plasma platform for photon-photon physics: the two photon Breit-Wheeler process, and Bounding elastic photon-photon scattering at $\sqrt s \approx 1$\,MeV using a laser-plasma platform
<p>The data contained in this repository was used in the production of the publication "A laser-plasma platform for photon-photon physics: the two photon Breit-Wheeler process" (<a href="https://doi.org/10.1088/1367-2630/ac3048">https://doi.org/10.1088/1367-2630/ac3048</a>) and "Bounding elastic photon-photon scattering at $\sqrt s \approx 1$\,MeV using a laser-plasma platform" (<a href="https://doi.org/10.1016/j.physletb.2025.139247">https://doi.org/10.1016/j.physletb.2025.139247</a>).</p>
Comparative plot about two sequences of integers very similar to each other: A348960 vs A127034
<p>This is the behavior comparison graph between the integer sequences registered in OEIS (The On-Line Encyclopedia of Integer Sequences) with codes: A348960 & A127034 respectively.</p> <p><strong>1)</strong> The sequence A348960 obeys the formula: </p> <p> <span class="math-tex">\(a_{n }=\lfloor(log(\pi n!)\rfloor. \)</span> For any non-negative integer such that <span class="math-tex">\(n\geq0\)</span></p> <p><strong>2) </strong>The sequence A127034 obeys the formula:</p> <p><span class="math-tex">\(a_{n}=\lfloor log(n!)/log(11)\rfloor.\)</span> For any non-negative integer such that <span class="math-tex">\(n\geq0\)</span></p> <p>In this particular case we're conducting the study for the following n-values: i<span class="math-tex">\(1\leq n\leq 60.\)</span> </p> <p> </p>
Nonlinear two-level dynamics of quantum time crystals
<p>Dataset for the manuscript titled "AC Josephson effect between two superfluid time crystals" by the same authors.</p>
Past and future effects of climate on the metapopulation dynamics of a NorthEast Atlantic seabird across two centuries
<p>Datasets required to run code for contribution:</p> <p>Past and future effects of climate on the metapopulation dynamics of a NorthEast Atlantic seabird across two centuries</p> <p>Jana WE Jeglinski, Holly I Niven, Sarah Wanless, Robert T. Barrett, Mike P. Harris, Jochen Dierschke and Jason Matthiopoulos</p> <p>Extension of a Bayesian metapopulation model fit to colony census data for all Northeast Atlantic colonies of the Northern gannet (<em>Morus bassanus</em>) described in Jeglinski et al. (2023) to investigate mechanistic relationships with climate and forecast metapopulation dynamics under two climate scenarios. </p>
Web Experience in Mobile Networks: Lessons from Two Million Page Visits
<p>Measuring and characterizing web page performance is a challenging task.</p> <p>When it comes to the mobile world, the highly varying technology characteristics coupled with the opaque network configuration make it even more difficult.</p> <p>Aiming at reproducibility, we present a large scale measurements study of web page performance collected in eleven commercial mobile networks spanning four countries.</p> <p>We build a dataset of nearly two million web browsing sessions to we shed light on the impact of different web protocols, browsers, and mobile technologies on the web performance.</p> <p>We find that the impact of mobile broadband access is sizeable.</p> <p>For example, the median page load time using mobile broadband increases by a third compared to wired access.</p> <p>Mobility clearly stresses the system, with handover causing the most evident performance penalties.</p> <p>Contrariwise, our measurements show that the adoption of HTTP/2 and QUIC has practically negligible impact.</p> <p>Our work highlights the importance of large-scale measurements.</p> <p>Even with our controlled setup, the complexity of the mobile web ecosystem is challenging to untangle.</p> <p>For this, we are releasing the dataset as open data for validation and further research.</p> <p>We also release together with the datasets we collected the scripts we use to produce the analysis we present in the paper. Please use plot_all.sh script to generate the plots in the paper, using the separate scripts from the "scripts" archive. </p> <p>Should you use any of these resources, please also make an attribution using the following reference (provided here in bibtex format):</p> <pre>@inproceedings{rajiullah2019web, title={{Web Experience in Mobile Networks: Lessons from Two Million Page Visits}}, author={Rajiullah, Mohammad and Lutu, Andra and Khatouni, Ali Safari and Fida, Mah-Rukh and Mellia, Marco and Brunstrom, Anna and Alay, Ozgu and Alfredsson, Stefan and Mancuso, Vincenzo}, booktitle={The World Wide Web Conference}, pages={1532--1543}, year={2019}, organization={ACM}, address = {San Francisco, CA, USA}, keywords = {Web Experience, HTTP2, QUIC, TCP, Mobile Broadband, Measurements} }</pre>
Costal operating wind farms: two datasets with concurrent SCADA, LiDAR and turbulent fluxes
<p>This data collection consists of two datasets from a micrometeorological experiment conducted in two distinct operating wind farms in a coastal area of the northeast region of Brazil, called Pedra do Sal Wind Farm (UEPS) and Beberibe Wind Farm (UEBB). These wind farms are located on the northeast coast of Brazil where meteorological conditions are strongly influenced by trade winds and sea breeze. Both datasets represent a full-year of measurements from August/2013 to July/2014.</p> <p>On both operating wind farms it was commissioned a fully instrumented IEC-compliant 100m met mast, with five levels of first-class calibrated cup anemometers and one level (100m) with 3D sonic anemometer. Additionally at UEPS there's an extra 3D sonic at 20m height on the met mast, as well as a VAISALA LEOSPHERE Windcube8 doppler wind lidar with a range up to 500m height and located 2.5D upwind of one of the wind turbines.</p> <p>The Pedra do Sal wind farm (UEPS) has an installed capacity of 18MW, with 20 Enercon E-44 installed at 55m a.g.l. At Beberibe wind farm (UEBB) there are 32 Enercon E-48 wind turbines installed at 75m a.g.l. The dataset includes 10min SCADA data for all wind turbines on both wind farms.</p> <p>This dataset has a high-quality combination of meteorological, SCADA and turbulent flux data of two operating wind farms in Brazil. During a full-year of measurements both datasets had a high data recovery rate (see attached tables). The dataset has already been used to assess the impact of atmospheric stability on the wind farm performance, as well as the effect of mesoscale patterns on the wind profile and wind farm power production. Recirculation of the sea breeze and the development of an internal boundary layer upwind the wind turbines were also characterized.</p> <p>For more details on the experimental layout, wind turbine locations, meso and microcale wind conditions and any other information not stated in the NetCDF4 files, please refer to the reference material or contact one of the authors.</p> <p> </p>
Barchan Swarm Simulations Using the Two-Flank Agent-Based Model v3
<p>This archive contains several animations of barchan swarms simulated using the Two-Flank Agent-Based model which was introduced in following article: </p> <p> </p> <p>Robson, Dominic T., and Andreas CW Baas. "A Simple Agent‐Based Model That Reproduces All Types of Barchan Interactions." Geophysical Research Letters 50.19 (2023): e2023GL105182. </p> <p> </p> <p>which is Open Access and available at https://doi.org/10.1029/2023GL105182</p> <p> </p> <p>The Two-Flank Agent-Based Model has been developed openly on GitHub by Dominic T Robson and Andreas CW Baas. All the necessary source files together with an example run file can be found at:</p> <p> </p> <p>https://github.com/DTRobson/TwoFlankABModel/releases/tag/TFABM</p> <p> </p> <p>The following model parameters and initial conditions were used for these simulations:</p> <p> </p> <p> simwidth = 9000 or 15000 #(m)</p> <p> simlength = 10000 #(m)</p> <p> fieldwidth = 3000 or 5000 #(m)</p> <p> </p> <p> qsatinit = 79 #(m^2 year^{-1})</p> <p> q0 = 0.25 #(q_sat)</p> <p> dt = 1/8 #(years) </p> <p> collson = True</p> <p> inject = True</p> <p> injectdist = Uniform </p> <p> periodic = False</p> <p> </p> <p> lambda1 = 1.</p> <p> lambda2 = 1.8</p> <p> lambda3 = 1/3</p> <p> alpha = 0.05</p> <p> delta = 4.6 #(m)</p> <p> a = 0.45</p> <p> b = 0.1</p> <p> </p> <p> </p> <p> eqw = 0.5 * delta/(q0 - alpha)</p> <p> injectparams = [2*eqw, 2*eqw]</p> <p> lws = [eqw]</p> <p> rws = [eqw]</p> <p> xs = [fieldwidth*1.5] </p> <p> ys = [simlength - 1]</p> <p> </p> <p> c = 45. </p> <p> </p> <p> w0 = 16.6 #(m)</p> <p> </p> <p> outfluxmode = 'Hersen' or 'Duran' #Hersen for unscaled outflux, Duran for scaled outflux</p> <p> plottinghornflux = False</p> <p> </p> <p> keep_coll_rec = True</p> <p> </p> <p> helpplotting = True</p> <p> </p> <p> </p> <p>The remaining model parameters varied across the different runs and took the values shown in the filenames. Where the filename does not list the angular separation of the secondary wind mode (thetab) simulations were unidirectional. The primary mode was normally distributed with mean 270degrees and standard deviation theta_sd. The list of all values used are shown here:</p> <p> </p> <p> initdensity = 12 or 24 or 37#(km^{-2}) this sets the rate at which dunes are injected into the model</p> <p> qshift = 0. or 0.05 or 0.1 or 0.15#(q_sat)</p> <p> thetab = 22.5 or 45 or 67.5 #(degrees)</p> <p> theta_sd = 3 #(degrees) </p> <p> </p> <p>In bimodal simulations the secondary mode angle was normally distributed with mean 270+thetab and standard deviation theta_sd. Each year (12 iterations) the first 9 iterations had wind direction taken from the primary mode and the final 3 iterations were from the secondary mode i.e. the 3:1 seasons of primary:secondary wind direction. Note that, in the simulations the primary mode 270deg means that dunes migrate in the negative y-direction, to produce the plots and revert to the convention of the primary wind being in the x-direction, the dunes were then rotated.</p> <p>The simulations were performed by Dominic T Robson using a 12th Gen Intel(R) Core(TM) i7-1255U 1.70 GHz processor and 16.0GB of RAM.</p> <p> </p> <p> </p>
Two decades of body length measurements in size-structured larval and juvenile fish populations in English rivers.
<p>Long term ecological datasets are valuable in providing context and understanding to complex ecological processes that occur over broad temporal scales, and provide a baseline for analysing change. Monitoring of fish populations in UK waterbodies and elsewhere is typically through measuring the length of individual fish caught in surveys. Through this method, the age structure of fish populations can be determined, as well as over winer survival rates and future recruitment success and cohort sizes can be predicted. The larval and juvenile period are when fish are considered most vulnerable to predation, competition, disease and environmental perturbations. </p> <p><br>This study presents the first long-term larval and juvenile fish lengths dataset for 67 survey sites over two decades (1999-2018) from the rivers Ancholme, Warwickshire Avon, Don, Trent, and Yorkshire Ouse (including the Swale, Ure, Nidd and Wharfe) in the United Kingdom. These rivers represent a range of topographical and biotopical characteristics. For the majority of this study, surveys were conducted on a monthly or fortnightly basis making both annual and seasonal analyses of size structure, growth and body length possible. Although there is some variation in the sampling frequency and some locations varied throughout the study according to requirements. In total, more than 380,000 larval or juvenile fish of 30 species were measured, likely representing one of the most comprehensive datasets of its type.</p> <p>Surveys were conducted in river margins, where the velocity was slowest and larval and juvenile fish tend to aggregate. Fish were captured using a 25 x 3 m micromesh (3 mm mesh size) seine net that was set in a rectangle parallel to the bank. This net capture fish as small as 5 mm and is the most appropriate method of catching larvae and juvenile fish, although occasionally some larger adult fish may have also been captured and measured as part of this dataset for completeness. All fish were identified to species and measured to standard length (mm) and released at the point of capture. The exception was the smallest larvae, which were euthanised with an overdose of methanesulphonate (MS-222) and preserved in 4% formalin solution for microscopic examination.</p> <p><br>The dataset contains 384,090 rows and 13 columns. Each row corresponds to a single fish that was measured at each site and date. Associated site information (site name, location, area fished (m<sup>2</sup>) and survey date) is reported for each row. When only a fraction of the catch was processed, the sub-sample size was reflected in the Count column (e.g. when half the sample was processed, the numbers of fish measured or only counted were multiplied by two). This enables accurate densities to be calculated as the total number of both measured and unmeasured fish is recorded.</p> <p>Description of columns found in the dataset:</p> <p> </p> <table> <tbody> <tr> <td> <p><strong>Column heading</strong></p> </td> <td> <p><strong>Column description</strong></p> </td> <td> <p><strong>Data type</strong></p> </td> <td> <p><strong>Units</strong></p> </td> </tr> <tr> <td> <p>Fish _Catchment</p> </td> <td> <p>The river catchment/basin location of each fish site</p> </td> <td> <p>Text</p> </td> <td> <p>n/a</p> </td> </tr> <tr> <td> <p>Fish_River</p> </td> <td> <p>The river/watercourse location of each fish site.</p> </td> <td> <p>Text</p> </td> <td> <p>n/a</p> </td> </tr> <tr> <td> <p>Fish_SiteName</p> </td> <td> <p>The name of each fish site</p> </td> <td> <p>Text</p> </td> <td> <p>n/a</p> </td> </tr> <tr> <td> <p>Fish_Latitude</p> </td> <td> <p>The latitude of each fish site (WGS 1984)</p> </td> <td> <p>Integer</p> </td> <td> <p>Decimal degrees</p> </td> </tr> <tr> <td> <p>Fish_Longitude</p> </td> <td> <p>The longitude of each fish site (WGS 1984)</p> </td> <td> <p>Integer</p> </td> <td> <p>Decimal degrees</p> </td> </tr> <tr> <td> <p>Fish_Area</p> </td> <td> <p>Area of fish site surveyed</p> </td> <td> <p>Integer</p> </td> <td> <p>m<sup>-2</sup></p> </td> </tr> <tr> <td> <p>Fish_SurveyDate</p> </td> <td> <p>Date fish survey was carried out</p> </td> <td> <p>Integer</p> </td> <td> <p>dd/mm/yyyy</p> </td> </tr> <tr> <td> <p>Fish_Year</p> </td> <td> <p>Year fish survey was carried out</p> </td> <td> <p>Integer</p> </td> <td> <p>yyyy</p> </td> </tr> <tr> <td> <p>Common_Name</p> </td> <td> <p>The common/vernacular name of each fish taxon recorded in the dataset.</p> </td> <td> <p>Text</p> </td> <td> <p>n/a</p> </td> </tr> <tr> <td> <p>Latin_Name</p> </td> <td> <p>The scientific name of each fish taxon recorded in the dataset</p> </td> <td> <p>Text</p> </td> <td> <p>n/a</p> </td> </tr> <tr> <td> <p>Net_Number</p> </td> <td> <p>The net number the fish in a given survey were caught on</p> </td> <td> <p>Integer</p> </td> <td> <p>n/a</p> </td> </tr> <tr> <td> <p>Length_mm</p> </td> <td> <p>Length of individual fish caught</p> </td> <td> <p>Integer</p> </td> <td> <p>mm</p> </td> </tr> <tr> <td> <p>Count</p> </td> <td> <p>Count of fish caught accounting for sub- sampling</p> </td> <td> <p>Integer</p> </td> <td> <p>Number of fish</p> </td> </tr> </tbody> </table> <p> </p>
Geochemistry of soils and eroded suspended sediments from two large rural catchments in southern Brazil for studies on Suspended Sediment Fingerprinting
<p> <strong>1. Introduction</strong></p> <p>This dataset comes from a research project entitled "Water and pollutants, from cropfields to cities: evaluation and improved of soil management technologies in a catchment network " supported by the Foundation for Research Support of the State of Rio Grande do Sul (FAPERGS) and National Council for Scientific and Technological Development (CNPq) (process n°10/0034-0). The project was carried out between 2010 and 2014 under the coordination of José Miguel Reichert and Danilo Rheinheimer dos Santos, professors at the Federal University of Santa Maria. One of the aims of this project was to understand the main pollutant transfer process from hillslopes to fluvial systems in large rural catchments representative of the agricultural production system in Southern Brazil. In this context, the Suspended Sediment Fingerprinting (SSF) was extremely useful for quantifying the origin of the sediment yield monitored at the outlet of these catchments. Among the various works carried out in this project, we highlight Tales Tiecher's doctoral thesis (Tiecher, 2015) that explored the SSF in many catchments, including the Conceição and Guaporé river basins.</p> <p><strong>2. Material and Methods</strong></p> <p>The catchments represent the magnitude of erosive and hydrological processes representative of Southern Brazil. The Conceição catchment has a drainage area of 804 km<sup>2</sup> (28°27′22″S and 53°58′24″ W). According to Köppen, the climate is Cfa type, with an annual rainfall between 1,750 and 2,000 mm. Geology is riodacithe basalt, with a formation of deep and highly weathered soils (Oxisols, Ultisols, and Alfisols). The relief is characterized by gentle slopes (6–9 %) on top and hillside slopes and higher steepness (10–14%) near the drainage channels. Farming based on the production of soybeans (<em>Glycine max</em>) in summer and wheat (<em>Triticumspp.</em>), oats (<em>Avena strigosa</em>), and ryegrass (<em>Lolium multiflorum</em>) in winter. The Guaporé catchment has a drainage area of 1,980 km<sup>2</sup> (28°54′41″S and 51°57′10″W), it covers part of the meridional plateau border. The climate is classified as Cfa, with annual rainfall varies between 1,400 and 2,000 mm. Geology is characterized by volcanic lava flows, and topography is undulating to hilly. Due to variations in landscape, several classes of soils (Entisols, Luvisol, Cambisol, Oxisol, Ultisol, and Chernosol). The land use is highly heterogeneous. In the upper third of the catchment, there is a predominance of soybean cultivated under no-tillage soil management. In the other two-thirds (middle and lower parts), land use and soil management are very heterogeneous. The main land uses are tobacco (<em>Nicotiana tabacum</em>) and maize (<em>Zea mays</em>) crops, Eucalyptus (<em>Eucalyptus</em> spp.), as well as pastures for dairy cattle. The contribution of unpaved roads is relevant to the sediment yield in both catchments (Didoné et al., 2014). Composite samples of potential sediment sources (cropland, unpaved roads, and stream channel banks) were collected. Sediment source samples were taken from the surface soil layer (0–0.05 m) of cropland and unpaved roads and on exposed sites located along the river channel network. Each sample was composed of at least 10 subsamples. To obtain representative samples of suspended sediment transported in the catchment’s outlet were used three strategies: (1) to collect flood suspended sediments (FSS) through the manual sampling (USDH-48) at different periods during the rising and falling stages of floods; (2) to deploy time-integrated suspended sediment samplers (TISS), by installing the device developed by Phillips et al. (2000) at different sites within the catchments; to collect fine-bed sediment (FBS) with a suction stainless sampler limiting the loss of fine material at the bed river. Source and sediment samples were oven‐dried at 50 °C, gently disaggregated using a pestle and mortar, and then sieved to 62,5 μm. The geochemical tracers evaluated were total organic carbon estimated by wet oxidation (K<sub>2</sub>Cr<sub>2</sub>O<sub>7</sub> + H<sub>2</sub>SO<sub>4</sub>) and the total concentration of Al, Ba, Be, Ca, Co, Cr, Cu, Fe, K, La, Li, Mg, Mn, Na, Ni, P, Pb, Sr, Ti, V, and Zn using inductively coupled plasma optical emission spectrometry after microwave‐assisted digestion with concentrated HCl and HNO<sub>3</sub> (ratio 3:1) for 9.5 min at 182 °C (Tiecher, 2015; Tiecher et al. 2017, 2018).</p> <p> <strong>3. Final remarks</strong></p> <p> The SSF results provided by this dataset (Tiecher, 2015) combined with sediment yield monitoring were very important for the assessment and modeling studies in these two catchments that took place after that (Didoné et al., 2015; 2017). In addition, other studies have explored the same sample bank, expanding upon the array of tracer properties and increasing our understanding about the mechanisms of sediment and pollutant transfer in these catchments (Le Gall et al. 2017; Zafar et al., 2017; Ramon et al., 2020).</p> <p> <strong>4. References</strong></p> <p> Didoné, E. J., Minella, J. P. G., Reichert, J. M., Merten G. H., Dalbianco, L., Barros, C. A. P., Ramon, R. (2014) Impact of no-tillage agricultural systems on sediment yield in two large catchments in southern Brazil. J Soils Sediments 14:1287–1297.</p> <p>Didoné, E.J., Minella, J.P.G., Evrard, O. (2017). Measuring and modelling soil erosion and sediment yields in a large cultivated catchment under no-till of Southern Brazil. Soil Tillage Res. 174, 24-33. https://doi.org/10.1016/j.still.2017.05.011</p> <p>Didoné, E. J.; Minela, J. P. G.; Merten, G. H. (2015). Quantifying soil erosion and sediment yield in a catchment in southern Brazil and implications for land conservation. J. Soils Sediments 11, 2334-2346. https://doi.org/10.1007/s11368-015-1160-0</p> <p>le Gall, M., Evrard, O., Dapoigny, A., Tiecher, T., Zafar, M., Minella, J. P. G., Laceby, J. P., & Ayrault, S. (2017). Tracing sediment sources in a subtropical agricultural catchment of southern Brazil cultivated with conventional and conservation farming practices. Land Degradation and Development, 28(4). https://doi.org/10.1002/ldr.2662</p> <p>Ramon, R., Evrard, O., Laceby, J. P., Caner, L., Inda, A. v., Barros, C. A. P., Minella, J. P. G., & Tiecher, T. (2020). Combining spectroscopy and magnetism with geochemical tracers to improve the discrimination of sediment sources in a homogeneous subtropical catchment. Catena, 195, 104800. https://doi.org/10.1016/j.catena.2020.104800</p> <p>Tiecher, T. (2015). Fingerprinting sediment sources in agricultural catchments in Southern Brazil. Doctoral Dissertation in Soil Science. Universidade Federal de Santa Maria, Santa Maria, RS.</p> <p>Tiecher, T., Minella, J. P. G., Caner, L., Evrard, O., Zafar, M., Capoane, V., le Gall, M., & Santos, D. R. D. (2017). Quantifying land use contributions to suspended sediment in a large cultivated catchment of Southern Brazil (Guaporé River, Rio Grande do Sul). Agriculture, Ecosystems and Environment, 237. https://doi.org/10.1016/j.agee.2016.12.004</p> <p>Tiecher, T., Minella, J. P. G., Evrard, O., Caner, L., Merten, G. H., Capoane, V., Didoné, E. J., & dos Santos, D. R. (2018). Fingerprinting sediment sources in a large agricultural catchment under no-tillage in Southern Brazil (Conceição River). Land Degradation and Development, 29(4). https://doi.org/10.1002/ldr.2917.</p> <p>Zafar, M., Tiecher, T., Capoane, V., Troian, A., dos Santos, D.R. (2017). Characteristics, lability and distribution of phosphorus in suspended sediment from a subtropical catchment under diverse anthropic pressure in Southern Brazil. Ecol. Eng. 100, 28–45.</p>
Two-probe macaque monkey auditory LFP
<p>Dataset accompanying paper Klein, N., Siegle, J.H., Teichert, T., Kass, R.E. (2021) "Cross-population coupling of neural activity based on Gaussian process current source densities". </p> <p>Auditory local field potential (LFP) recordings and evoked multi-unit activity (MUA) from two 24-electrode linear probes (V-Probes from Plexon) inserted in primary auditory cortex of a macaque monkey. The probes were arranged parallel to the iso-frequency bands in primary auditory cortex (A1), and had similar tonal response fields with preferred frequencies close to 1000 Hz. The first probe (which we call the lateral probe) was located centrally in A1, while the second probe (which we call the medial probe) was located more medially and closer to the boundary of A1 with the medio-lateral belt. The medial probe had lower response threshold, shorter MUA latencies, and overall stronger current sinks and sources than the lateral probe. The spacing between electrodes on each probe was 100 microns so that the probe spanned 2,300 microns. The treatment of the animals was in accordance with the guidelines set by the U.S. Department of Health and Human Services (NIH) for the care and use of laboratory animals, and all methods were approved by the Institutional Animal Care and Use Committee at the University of Pittsburgh.</p> <p>See README.txt for precise description of data files.</p>
Topography drives microgeographic adaptations of closely-related species in two tropical tree species complexes
<p>Combining LiDAR-derived topography, tree inventories, and single nucleotide polymorphisms (SNPs) from gene capture experiments, we explored genome-wide population genetic structure, covariation of environmental variables, and genotype-environment association to assess microgeographic adaptations to topography within the species complexes <em>Symphonia</em> (Clusiaceae), and <em>Eschweilera</em> (Lecythidaceae) with three species per complex and 385 and 257 individuals genotyped, respectively.</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.