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11,506 results for “Dynamics”
Data from: Structure of the rare archaeal biosphere and seasonal dynamics of active ecotypes in surface coastal waters
Marine Archaea are important players among microbial plankton and significantly contribute to biogeochemical cycles, but details regarding their community structure and long-term seasonal activity and dynamics remain largely unexplored. In this study, we monitored the inter-annual archaeal community composition of abundant and rare biospheres in northwestern Mediterranean Sea surface waters by pyrosequencing 16S rDNA and rRNA. A detailed analysis of the rare biosphere structure showed that the rare archaeal community was composed of three distinct fractions. One contained the rare Archaea that became abundant at different times within the same ecosystem; these cells were typically not dormant, and we hypothesize that they represent a local seed bank that is specific and essential for ecosystem functioning through cycling seasonal environmental conditions. The second fraction contained cells that were uncommon in public databases and not active, consisting of aliens to the studied ecosystem and representing a non-local seed bank of potential colonizers. The third fraction contained Archaea that were always rare but actively growing; their affiliation and seasonal dynamics were similar to the abundant microbes and could not be considered a seed bank. We also showed that the major archaeal groups, Thaumarchaeota Marine Group-I (MGI) and Euryarchaeota Group-II.B (MGII.B) in winter and Euryarchaeota Group-II.A (MGII.A) in summer, contained different ecotypes with varying activities. Our findings suggest that archaeal diversity could be associated with distinct metabolisms or life strategies, and that the rare archaeal biosphere is composed of a complex assortment of organisms with distinct histories that affect their potential for growth.
Data for `Field-mediated locomotor dynamics on highly deformable surfaces'
<p>This dataset is for `Field-mediated locomotor dynamics on highly deformable surfaces.'</p>
Data from: Microbial expansion-collision dynamics promote cooperation and coexistence on surfaces
Microbes colonizing a surface often experience colony growth dynamics characterized by an initial phase of spatial clonal expansion followed by collision between neighboring colonies to form potentially genetically heterogeneous boundaries. For species with life cycles consisting of repeated surface colonization and dispersal, these spatially-explicit "expansion-collision dynamics" generate periodic transitions between two distinct selective regimes, "expansion competition" and "boundary competition", each one favoring a different growth strategy. We hypothesized that this dynamic could promote stable coexistence of expansion- and boundary-competition specialists by generating time-varying, negative frequency-dependent selection that insulates both types from extinction. We tested this experimentally in budding yeast by competing an exo-enzyme secreting "cooperator" strain (expansion-competition specialists) against non-secreting "defectors" (boundary-competition specialists). As predicted, we observed cooperator-defector coexistence or cooperator dominance with expansion-collision dynamics, but only defector dominance otherwise. Also as predicted, the steady-state frequency of cooperators was determined by colonization density (the average initial cell-cell distance) and cost of cooperation. Lattice-based spatial simulations give good qualitative agreement with experiments, supporting our hypothesis that expansion-collision dynamics with costly public goods production is sufficient to generate stable cooperator-defector coexistence. This mechanism may be important for maintaining public-goods cooperation-and-conflict in microbial pioneer species living on surfaces.
Chaotic Dynamics in a Two-Droplet Pilot Wave System: A Numerical Simulation
<p>Data set and results for our university modeling project.</p>
Basket-type G-Quadruplex with Two Tetrads in the Presence of TMAO and Urea: A Molecular Dynamics Study
<p>Molecular Dynamics simulation trajectories of basket-type DNA G-quadruplex (PDB: 2KF7). The structures have been simulated in the temperatures 300 K and 360 K in pure water, 1 M TMAO solution, 2 M urea solution and the mixture of 1 M TMAO and 2 M urea.</p> <p> </p>
A mid-infrared lab-on-a-chip for dynamic reaction monitoring
<p>This file contains the as measured source data of the above-mentioned manuscript. </p>
Figure 1 in Population dynamics and reproductive biology of the sandhopper Atlantorchestoidea brasiliensis (Amphipoda: Talitridae) of a sandy beach in Southwestern Atlantic Coast
Figure 1. Location of study area, Sossego Beach, Rio de Janeiro, Brazil.
Laboratory evidence supporting a mechanical model describing the dynamic formation of fault damage asymmetry [DATA]
<p>Data and metadata for the publication "Laboratory evidence supporting a mechanical model describing the dynamic formation of fault damage asymmetry", published in Geophysical Research Letters.</p>
Data for: Quantifying patch-specific seed dispersal and local population dynamics to estimate population spread of an endangered plant species
<p>Dataset on seed dispersal and population spread for the paper</p> <p class="Default"><span><b>Quantifying patch-specific seed dispersal and local population dynamics to estimate population spread of an endangered plant species</b></span></p> <p>Jinlei Zhu<sup>1, 2,</sup> *, Karolína Hrušková<sup>1, 3</sup>, Hana Pánková<sup>1</sup>, Zuzana Münzbergová<sup>1, 3</sup></p> <p><sup>1</sup>Institute of Botany, Czech Academy of Sciences, Průhonice, Czech Republic</p> <p class="Default"><span><sup>2</sup>Institute of Landscape and Plant Ecology, University of Hohenheim, Stuttgart, Germany</span></p> <p class="Default"><span><sup>3</sup>Department of Botany, Faculty of Science, Charles University, Prague, Czech Republic</span></p> <p class="Default"><span>*Corresponding author: jinlei.zhu@uni-hohenheim.de</span></p> <p>Institute of Landscape and Plant Ecology</p> <p>University of Hohenheim</p> <p>Ottilie-Zeller-Weg 2, 70599 Stuttgart, Germany</p>
Locus Coeruleus firing patterns selectively modulate brain activity and dynamics
<p>This dataset supports the manuscript entitled 'Locus Coeruleus firing patterns selectively modulate brain activity and dynamics' (https://doi.org/10.1101/2022.08.29.505672). Please refer to this manuscript for detailed information. </p> <p>The dataset contains a total of 81 functional (GE-BOLD) and 30 anatomical (T1-weighted) scans of ChR2-expressing C57BL/6-Tg(<em>Dbh</em>-iCre)1Gsc mice in NIFTI format, multiplied by 10. Mice were optogenetically stimulated with blue light in the right Locus Coeruleus in a 3Hz tonic, 5Hz tonic, and 15Hz burst pattern. Sham stimulation entailed red light stimulation at a 5Hz tonic frequency. The 'StimulationProtocol' text file specifies the precise onset (in seconds, minus 10 seconds for dummy scans) and duration (in seconds) of the different optogenetic stimulation protocols during a 1440 seconds functional scan. The 'SubjectDetails' file lists the subject IDs, their gender, their genotype, the stimulation type of functional scans, and their associated anatomical scan.</p>
Data_of_Temporal_dynamics_of_the_sensorimotor_convergence_underlying_voluntary_limb_movement
<p>Software and dataset used in a manuscript.</p>
Dynamic equilibrium at the HCOOH-saturated TiO2(110)-water interface
<p>Experimental and computational, archived in a single zip file</p>
Analysis of future heatwaves in the Pearl River Delta through CMIP6-WRF dynamical downscaling
<p>Heatwave datasets</p>
Area-Efficient Memory Scheduling for Dynamically Scheduled High-Level Synthesis
<p>Dataset for Area-Efficient Memory Scheduling for Dynamically Scheduled High-Level Synthesis</p>
Isotope constraints on nitrogen dynamics in the upper water column of the South China Sea
<p>ds01-All water sample data supporting this study are summed in ds01.</p> <p>ds02-All CTD data supporting this study are summed in ds02.</p>
Dynamic viscosity of liquid gallium at different temperatures
<p><strong>Dynamic viscosity of liquid gallium at different temperatures</strong></p> <p>Junjie Chen</p> <p>Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com</p> <p> </p> <p>Gallium is a chemical element, metal of main Group 13 of the periodic table. It liquefies just above room temperature. Gallium does not occur free or concentrated in independent minerals. It is extracted as a by-product from zinc blende, iron pyrites, bauxite, and germanite. Gallium is silvery white and soft enough to be cut with a knife. It takes on a bluish tinge because of superficial oxidation. Unusual for its low melting point, gallium also expands upon solidification and supercools readily, remaining a liquid at temperatures as low as 0 degrees Celsius. Gallium remains in the liquid phase over a temperature range of about 2,000 degrees Celsius, with a very low vapour pressure up to about 1,500 degrees Celsius, the longest useful liquid range of any element. The liquid metal clings to glass and similar surfaces. The crystal structure of gallium is orthorhombic. Natural gallium consists of a mixture of two stable isotopes: gallium-69 and gallium-71. Gallium has been considered as a possible heat-exchange medium in nuclear reactors, although it has a high neutron-capture cross section. The metal gallium is stable in dry air. Somewhat similar to aluminum chemically, gallium slowly oxidizes in moist air until a protective film forms. On burning in air or oxygen, it forms the white oxide. This oxide can be reduced to the metal when heated at high temperatures in hydrogen. Gallium is amphoteric, reacting with sodium and potassium hydroxide solutions to yield a gallate and hydrogen gas. The halogens attack it vigorously.</p> <p>Temperature (degrees Celsius), Dynamic viscosity (grams per meter per second)</p> <p>350 1.369</p> <p>400 1.158</p> <p>450 1.016</p> <p>500 0.915</p> <p>550 0.840</p> <p>600 0.783</p> <p>650 0.737</p> <p>700 0.700</p> <p>750 0.669</p> <p>800 0.643</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com, Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p>
Dynamic Covalent Michael Acceptors to Penetrate Cells: Thiol-Mediated Uptake with Tetrel-Centered Exchange Cascades, Assisted by Halogen-Bonding Switche
<p>Original data</p> <p>1. Synthesis and Characterization</p> <p>Compounds <strong>7</strong>, <strong>9</strong>, <strong>10</strong>, <strong>11</strong>, <strong>13</strong>, <strong>14</strong>, <strong>16</strong>, <strong>33</strong>, <strong>34</strong>, <strong>36</strong></p> <ul> <li>Lab Book Page; <sup>1</sup>H and <sup>13</sup>C NMR; IR; HRMS</li> </ul> <p>Compound <strong>10 </strong>Stability Test</p> <ul> <li>Lab Book Page</li> <li>UV-Vis Absorption Spectra of <strong>10</strong> and <strong>41</strong> in PBS</li> <li>UV- Vis Absorption Spectra of <strong>10</strong> in Buffer After 72 h</li> <li>Kinetics 10 h in PBS; and in AMPSO Buffer</li> </ul> <p>Compound <strong>22</strong></p> <ul> <li>Lab Book Page</li> </ul> <p>Compounds <strong>47</strong>, <strong>48</strong>, <strong>53</strong>, <strong>55</strong>, <strong>56</strong></p> <ul> <li>Lab Book Pages; <sup>1</sup>H and <sup>13</sup>C NMR; IR</li> </ul> <p>2. Automated High-Content High-Throughput Screening</p> <ul> <li>Lab Book Pages and Data</li> </ul> <p>2.1. Inhibitor Screening with OPS Reporter</p> <p>2.2. Cellular Uptake of MAC Reporters</p> <p>2.3. Inhibitor Screening with MAC and CTO Reporters</p> <p>3. Protein Uptake</p> <p>3.1. Preparation and Cellular Uptake of Streptavidin Complexes</p> <ul> <li>Lab Book Page and Data</li> </ul>
Supplemental Material: Dynamic Team Heterogeneity in Cooperative Coevolutionary Algorithms
<p>Supplemental videos for the paper "Dynamic Team Heterogeneity in Cooperative Coevolutionary Algorithms".</p> <p>multirover_720.mp4: Best solutions evolved for the multi-rover task.</p> <p>soccer_720.mp4: Best solutions evolved for the soccer task.</p>
Supplementary material 2 from: Standovár T, Horváth S, Aszalós R (2017) Temporal changes in vegetation of a virgin beech woodland remnant: stand-scale stability with intensive fine-scale dynamics governed by stand dynamic events. Nature Conservation 17: 35-56. https://doi.org/10.3897/natureconservation.17.12251
Map showing canopy trees in the study area. :
Supplementary material 1 from: Standovár T, Horváth S, Aszalós R (2017) Temporal changes in vegetation of a virgin beech woodland remnant: stand-scale stability with intensive fine-scale dynamics governed by stand dynamic events. Nature Conservation 17: 35-56. https://doi.org/10.3897/natureconservation.17.12251
Map showing the position of sampling plots in 1996 and 2013 :
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.