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11,506 results for “Dynamics”
Aligned and curated mtDNA sequences from: Ancient DNA reveals interstadials as a driver of common vole population dynamics during the last glacial period
<p><strong><span>Aim: </span></strong><span>Many species experienced population turnover and local extinction during the Late Pleistocene. In the case of megafauna, it remains challenging to disentangle climate change and the activities of Palaeolithic hunter-gatherers as the main cause. In contrast, the impact of humans on rodent populations </span><span>is likely to be negligible. This study investigated which climatic and/or environmental factors affect the population dynamics of the common vole. </span><span>This temperate rodent is widespread across Europe and was one of the most abundant small mammal species throughout the Late Pleistocene.</span></p> <p><span><strong>Location:</strong> </span><span>Europe</span></p> <p><strong><span>Taxon: </span></strong><span>Common vole (<em>Microtus arvalis</em>)</span></p> <p><strong><span>Methods: </span></strong><span>We generated a dataset comprised of a 4.2-kb-long fragment of mitochondrial DNA (mtDNA) from 148 ancient and 51 modern specimens sampled from multiple localities across Europe and covering the last 60 thousand years (ka). We used Bayesian inference to reconstruct their phylogenetic relationships and to estimate the age of the specimens that were not directly dated.</span></p> <p><span><strong>Results:</strong> </span><span>We estimated the time to the most recent common ancestor of all last glacial and extant common vole lineages to be 90 ka ago and the divergence of the main mtDNA lineages present in extant populations to between 55 and 40 ka ago, which is earlier than previous estimates. </span><span>We detected several lineage turnovers in Europe during the period of high climate variability at the end of Marine Isotope Stage 3 (MIS 3; 57–29 ka ago) in addition to those found previously around the Pleistocene/Holocene transition.</span><span> </span><span>In contrast, data from the Western Carpathians suggest continuity throughout the Last Glacial Maximum (LGM), even at high latitudes.</span></p> <p><strong><span>Main conclusions: </span></strong><span>The main factor affecting the common vole populations during the last glacial period was the decrease in open habitat during the interstadials, whereas </span><span>climate </span><span>deterioration </span><span>during</span><span> the LGM had little impact on population dynamics. This suggests that the rapid environmental change rather than other factors was the major force shaping the histories of the Late Pleistocene faunas.</span></p>
Change Detection in Dynamic Environments by Means of a Robotic Swarm - Digital Appendix
<p>Digital Appendix for my thesis Change Detection in Dynamic Environments by Means of a Robotic Swarm.</p> <p>In the zip-file you find a README that guides you through the structure and where to find the plots for the respective experiments.</p> <p><strong>Change Detection of Dynamic Environments by Means of a Robotic Swarm - Digital Appendix</strong></p> <p>The following folder structure holds all research data of my conducted experiments(h5-logfiles and plots). The Python-Script "show_h5.py" can be used to read out the logfile in h5-format (<em>$python3 show_h5.py expample_logfilename.h5</em>). However, this shouldn't be necessary because all plots are already generated.</p> <p>To find the results you want to see, this is a small guide through the structure:</p> <ol> <li> <p>First the trials are divided into the respective methods (BOCPD, PELT, DBB, DBBCPD). In the folders you find the experiments for the specific method.</p> </li> <li> <p>In the folders of BOCPD and PELT you find the results for the different feedback types and their combinations. The id for each feedback is noted in parentheses (e.g. XX_(id)_feedback_description). Feedback combinations have their ids added up (e.g. XX_(id1+...+idn)_feedback_description).</p> </li> <li> <p>In the folder to each feedback type the different test trials can be found. This means varying environment difficulties and parameter settings. In the name of the folders this information can be found (e.g. XX_method_environmentdifficulty_parametersetting).</p> </li> </ol> <p>All experiments follow the same procedure as long as it is stated otherwise. Each trial consists of 20 individual runs with a duration of 6000 seconds. At half time (3000 s) a change to the opposite fill ratio occurs (fill ratio of 1.0 defines a completely white and one of 0.0 a completely black environment).</p> <p><strong>Environment difficulty</strong></p> <ul> <li> <p>0901 --> easy environment, fill ratio changed from 0.9 to 0.1</p> </li> <li> <p>0703 --> easy environment, fill ratio changed from 0.7 to 0.3</p> </li> <li> <p>0604 --> easy environment, fill ratio changed from 0.6 to 0.4</p> </li> <li> <p>055045 --> easy environment, fill ratio changed from 0.55 to 0.45</p> </li> </ul> <p><strong>Parameter Setting</strong></p> <p>The setting is in the name of the folder composed of: feedbackID: intervalLength amountNeighbors</p> <ul> <li> <p>3c:50s3n --> feedback 3c with a 50s interval and 3 neighbors</p> </li> </ul> <p>In these folders all plots of the respective runs can be found showing a Boxplot of all 20 runs and for each run the swarm belief, the decision distribution and the reset histogram (before/after the change)</p>
Dataset and code for "Tiltable objective microscope visualizes selectivity for head motion direction and dynamics in zebrafish vestibular system", Nat Commun 13, 7622 (2022). https://doi.org/10.1038/s41467-022-35190-9
<p>Dataset and code for "Tiltable objective microscope visualizes selectivity for head motion direction and dynamics in zebrafish vestibular system", Tanimoto, Watakabe, and Higashijima.</p> <p> </p> <p>The spreadsheet files contain source data for the figures.</p> <p>The file named "register_rotated_images_demo.zip" contains the MATLAB code, example image data, and instruction text data. To use the code, unzip the file and follow the instructions in the "readme.txt" file. The file named "register_rotated_images_demo_output.zip" contains expected output image data.</p> <p> </p>
Figure 1 in Dynamic of fish trophic guilds in the plateau-plain gradient in the Paraguay River, Northern Pantanal
Figure 1. The sampling sites along the Paraguay River, state of Mato Grosso, Brazil.
Structural dynamics of DNA strand break sensing by PARP-1 at a single-molecule level
<p><span>Single-stranded breaks (SSBs) are the most frequent DNA lesions threatening genomic integrity. A highly kinked DNA structure in complex with human PARP-1 domains led to the proposal that SSB sensing in Eukaryotes relies on dynamics of both the broken DNA double helix and PARP-1's multi-domain organization. Here, we directly probe this fundamental yet poorly understood process at the single-molecule level. Quantitative smFRET and structural ensemble calculations reveal how PARP-1's N-terminal zinc fingers convert DNA SSBs from a largely unperturbed conformation, via an intermediate state into the highly kinked DNA conformation. Our data suggest an induced fit mechanism via a multi-domain assembly cascade that drives SSB sensing and stimulates an interplay with the scaffold protein XRCC1 orchestrating subsequent DNA repair events. Interestingly, a clinically used PARP-1 inhibitor Niraparib shifts the equilibrium towards the unkinked DNA conformation, whereas the inhibitor EB47 stabilizes the kinked state. </span></p>
Supplemental information for "Single-Molecule Dynamics of Surface Lipoproteins in Bacteroides Indicate Similarities and Cooperativity"
<p>Supplemental Movies 1 - 3</p> <p><strong>SI Movie S1 - Representative movie of SusG-HT dynamics in <em>Bt</em> cells grown in amylopectin.</strong> The <em>Bt</em> cell outlines (white) are determined from the corresponding phase-contrast image. The single-molecule localization fits (circles) and corresponding trajectories (lines) are overlaid with the same colors as in Figure 1c. Below the scale bar is the date of the experiment, the movie number, the number of the photo-activation pulse that the sequence follows (in parentheses), and the frame number. These indicators are displayed in green during the imaging frames and in red during the photo-activation pulse. Scale bar: 1 µm; imaging rate: 20 ms/frame.</p> <p><strong>SI Movie S2 - Representative movie of SusG-HT dynamics in <em>Bt</em> cells grown in maltose.</strong> The <em>Bt</em> cell outlines (white) are determined from the corresponding phase-contrast image. The single-molecule localization fits (circles) and corresponding trajectories (lines) are overlaid with the same colors as in Figure 1c. Below the scale bar is the date of the experiment, the movie number, the number of the photo-activation pulse that the sequence follows (in parentheses), and the frame number. These indicators are displayed in green during the imaging frames and in red during the photo-activation pulse. Scale bar: 1 µm; imaging rate: 20 ms/frame.</p> <p><strong>SI Movie S3 - Representative movie of SusG-HT dynamics in <em>Bt</em> cells grown in glucose.</strong> The <em>Bt</em> cell outlines (white) are determined from the corresponding phase-contrast image. The single-molecule localization fits (circles) and corresponding trajectories (lines) are overlaid with the same colors as in Figure 1c. Below the scale bar is the date of the experiment, the movie number, the number of the photo-activation pulse that the sequence follows (in parentheses), and the frame number. These indicators are displayed in green during the imaging frames and in red during the photo-activation pulse. Scale bar: 1 µm; imaging rate: 20 ms/frame.</p>
Simulation input files and analysis scripts for "Optimal bond-constraint topology for molecular dynamics simulations of cholesterol"
<p>Simulation input files and analysis scripts for "Optimal bond-constraint topology for molecular dynamics simulations of cholesterol".</p> <p>See ... for details.</p>
Effects of El Niño drought on seedling dynamics in a seasonally dry tropical forest in northern Thailand
<p><span>As El Niño is predicted to become stronger and more frequent in the future, it is crucial to understand how El Niño-induced droughts will affect tropical forests. Although many studies have focused on tropical rainforests, there is a paucity of studies on them, particularly in Asia, and few studies have focused on seedling dynamics, which are expected to be strongly affected by drought. Seedlings in seasonally dry tropical forests (SDTFs) are generally more drought-tolerant than those in the rainforests, and the effects of El Niño-induced droughts may differ between SDTF and tropical rainforests. In this study, we explored the impact of El Niño-induced drought at an SDTF in northern Thailand by monitoring the seedling dynamics at monthly intervals for seven years, including a period of strong El Niño. The effects were compared between two forest types in an SDTF: a </span><span>deciduous dipterocarp forest (DDF)</span><span>, dominated by deciduous species, and an adjacent </span><span>lower montane forest</span><span> (LMF) with more evergreen species. El Niño-induced drought increased seedling mortality in both forest types. The effect of drought was stronger in evergreen than in the deciduous species, resulting in higher mortality in the LMF during El Niño. However, El Niño increased seedling recruitment only in the DDF, mainly because of the massive recruitment of the deciduous oak, <em>Quercus brandisiana</em> (Fagaceae), which compensated for the mortality of seedlings in the DDF. As a result, El Niño increased seedling density in the DDF and decreased it in the LMF. This is the first long-term study to identify the differences in the impacts of El Niño on seedlings between the two forest types, DDF and LMF, and two leaf habits, evergreen and deciduous, in Southeast Asia. Our findings suggest that future climate change may alter the species composition and spatial distribution of seedlings in Asian SDTFs.</span></p>
Supporting Data for "Disruption of energetic and dynamic base pairing cooperativity in DNA duplexes by an abasic site"
<p>Temperature-jump IR spectroscopy data and coarse-grained molecular dynamics trajectories for three DNA sequences with and without an abasic site.</p>
Dataset for "Attosecond Dynamics of sp-Band Photoexcitation"
<p>Dataset for: </p> <p>"Attosecond Dynamics of sp-Band Photoexcitation</p> <p>Johann Riemensberger, Stefan Neppl, Dionysios Potamianos, Martin Schäffer, Maximilian Schnitzenbaumer, Marcus Ossiander, Christian Schröder, Alexander Guggenmos, Ulf Kleineberg, Dietrich Menzel, Francesco Allegretti, Johannes V. Barth, Reinhard Kienberger, Peter Feulner, Andrei G. Borisov, Pedro M. Echenique, and Andrey K. Kazansky</p> <p>Phys. Rev. Lett. <strong>123</strong>, 176801 – Published 21 October 2019"</p> <p> </p> <p>DOI: https://doi.org/10.1103/PhysRevLett.123.176801</p>
Microbial community dynamics during decomposition of insect exuviae and frass in soil
<p><span>As the mass-rearing industry of insects for food and feed is expected to grow, </span><span>residual streams associated with this activity will become increasingly available. Before these residues can be used as organic amendments, more knowledge on the decomposition and dynamics of the involved microbial communities is needed. </span><span>This study investigated decomposition, N-mineralization, and fungal/bacterial community composition during 16 weeks of incubation of exuviae and frass of </span><span>black soldier fly, mealworm, and house cricket in arable soil</span><span>. Decomposition of insect residues in litterbags was rapid, with more than 50% weight loss in 2 weeks. Accumulation of mineral-N from insect materials distributed in the soil was also highest during the first 2 weeks, but</span><span> it was more profound for exuviae than their frass counterparts. </span><span>Soil amendment with insect residues enriched soil microbial inhabitants belonging to Gammaproteobacteria, Bacilli, Actinobacteria, and Mortierellomycetes. Comparison of microbial community composition in soil amended with sterilized and nonsterilized mealworm exuviae indicated that the presence of </span><span>microbial propagules in the exuviae had no significant influence on the composition of bacterial decomposers and a minor, but significant impact on fungal community composition. Overall, our results reveal a good prospect of using insect residual streams as soil amendment.</span></p>
Alien plants and flower visitors disrupt the seasonal dynamics of mutualistic networks - Dataset
<p>Dataset associated with the manuscript "Alien plants and flower visitors disrupt the seasonal dynamics of mutualistic networks" (Arroyo-Correa et al. 2019)</p>
A Multi-Scale Spatial Model of Hepatitis-B Viral Dynamics
<p>Dataset related to an accepted manuscript:</p> <p>A Multi-Scale Spatial Model of Hepatitis-B Viral Dynamic. Cangelosi Q., Means S., Ho H. PLOS One</p> <p>Dataset documented in a ReadMe file.</p>
Ligand Field Molecular Dynamics Simulation of Pt(II)-Phenanthroline Binding to N-Terminal Fragment of Amyloid-beta Peptide
<p>DL_POLY Classic input and output files for 10 MD simulations: 5 of free peptide, 5 with Pt(phen)</p>
Polyhedral-based Dynamic Loop Pipelining for High-Level Synthesis
<p>This data set contains the results presented in the paper "Polyhedral-based Dynamic Loop Pipelining for High-Level Synthesis", to be published in the IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD).</p>
Supplementary Data:Risk Analysis for Real-time Flood Control Operation of a Multi-reservoir System Using a Dynamic Bayesian Network
<p>The files in this record contain data for risk analysis for real-time flood control operation of a multi-reservoir system using a dynamic bayesian network considered for publication in Water Resources Research.</p> <p>The files consist of:</p> <ul> <li>Reservoir data and river flood routing parameters</li> <li>Flood data</li> <li>Code and results of the Monte Carlo simulations</li> <li>Code and results of the Bayesian network</li> </ul>
Time series used in the manuscript "Causal dependences between the coupled ocean-atmosphere dynamics over the Tropical Pacific, the North Pacific and the North Atlantic"
<p>These 6 files contain time series built using reanalyses datasets of the ECMWF as discussed in the manuscript "Causal dependences between the coupled ocean-atmosphere dynamics over the Tropical Pacific, the North Pacific and the North Atlantic" submitted for discussion in the journal "Earth System Dynamics".</p>
The Data for Gaseous Dynamical Friction on Elliptical Keplerian Orbits
<p>The results for the the changing orbital elements of single perturbers and equal mass binaries due to Gaseous Dynamical Friction. The arrays ecc0, Mp represent the eccentricities and Mach numbers over which the change in semi-major axis (adot) eccentricity (edot) and precession (omegadot) are calculated. </p>
Probing homogenous catalysts and pre-catalysts in solution by exchange mediated Overhauser dynamic nuclear polarization NMR
<p>This is the raw data set for the publication </p> <p><span>Probing homogenous catalysts and pre-catalysts in solution by exchange mediated Overhauser dynamic nuclear polarization NMR </span><span>Authors: Yu Rao, Federico De Biasi, Ran Wei, Christophe Copéret and Lyndon Emsley </span><span>DOI for the publication:</span><span> doi.org/10.1021/jacs.4c01570 </span></p>
Benchmarking Dynamic Binary Value Problems with IOHprofiler -- Reproducibility files
<div> <div>This repository contains the code, data and scripts to reproduce the results from the paper "<span>Empirical Analysis of the Dynamic Binary Value Problem </span><span>with IOHprofiler</span>".</div> <br> <div>The files are split into 3 parts:</div> </div> <h3><br>Part 1: Data collection</h3> <div> <div>The data can be collected using the data_collection.py file. In its default state, this will collect the full set of experimental data used in the paper. This can be modified by adjusting the main to only execute the relevant parts of the experiments. Note that the data location and number of parallell processes can be adjusted at the top of this file.</div> <br> <div>To run the data collection, the only requirement is to install multiprocessing (any version from pip) and iohexperimenter. The version of ioh should be installed from github https://github.com/IOHprofiler/IOHexperimenter/tree/dynamic-bin-val (installation instructions can be found on the github page). Alternatively, the future pip-release 0.3.16 will include these changes as well.</div> </div> <div><br> <h3>Part 2: Data</h3> <div>Instead of rerunning the full experimental data collection, the results of this have also been made available. Each set of experiments is provided as a 'SetX.zip' file.</div> <br> <h3>Part 3: Visualization</h3> <div>To analyze and visualize the data, the provided notebook can be used. This notebook takes the data from either step 1 or 2 and uses it to create the figures presented in the paper (plus some variations).</div> <div>The resulting figures are also provided on Figshare: doi.org/10.6084/m9.figshare.25592904</div> </div> <p> </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.