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11,506 results for “Dynamics”
Cortical mechanisms of smooth eye movements revealed by dynamic covariations of neural and behavioral responses
<p>Neural activity in the frontal eye fields controls smooth pursuit eye movements, but the relationship between single neuron responses, cortical population responses, and eye movements is not well understood. We describe an approach to dynamically link trial-to-trial fluctuations in neural responses to parallel variations in pursuit and demonstrate that individual neurons predict eye velocity fluctuations at particular moments during the course of behavior, while the population of neurons collectively tiles the entire duration of the movement. The analysis also reveals the strength of correlations in the eye movement predictions derived from pairs of simultaneously recorded neurons and suggests a simple model of cortical processing. These findings constrain the primate cortical code for movement, suggesting that either a few neurons are sufficient to drive pursuit at any given time or that many neurons operate collectively at each moment with remarkably little variation added to motor command signals downstream from the cortex.</p>
The dynamics of bi-directional exchange flows: implication for morphodynamic change within estuaries and sea straits
<p>Environmental and geophysical flows, including dense bottom gravity currents in the ocean and buoyancy-driven exchange flows in marginal seas,<br> are strongly controlled by topographic features.<br> These are known to exert significant influence on both internal mixing and secondary circulations generated by these flows.<br> In such cases, uni-directional or bi-directional exchange flows develop when horizontal density differences<br> and/or pressure gradients are present between adjacent water bodies connected by a submerged channel.<br> The flow dynamics of the dense lower layer depend primarily on the volumetric flux and channel cross-sectional shape,<br> while the stratified interfacial flow mixing characteristics, leading to fluid entrainment/detrainment,<br> are also dependent on the buoyancy flux and motion within the upper (lower density) water mass.<br> For submerged channels that are relatively wide compared to the internal Rossby radius of deformation,<br> Earth rotation effects introduce geostrophic adjustment of these internal fluid motions,<br> which can suppress turbulent mixing generated at the interface and result in the development of Ekman layers that induce secondary,<br> cross-channel circulations, even within straight channels.<br> Moreover, recent studies of dense, gravity currents generated in rotating and non-rotating systems,<br> respectively, indicated that the V-shaped channel topography had a strong influence on both flow distribution<br> and associated interfacial mixing characteristics along the channel.<br> However, such topographic controls on the interfacial mixing and secondary circulations generated by bi-directional exchange flows<br> are not yet fully understood and remain to be investigated thoroughly in the laboratory.<br> Also the effect of mobile bed for bi-directional exchange flows generated in deformable channels along with the physical interactions<br> between the lower dense water flow and the erodible bed sediments<br> will have a strong influence in (re-)shaping the overall channel bed topography (i.e. bed morphodynamics).<br> Consequently, the resulting temporal changes in cross-sectional channel bathymetry (i.e. through erosion and deposition processes)<br> would also be expected to have associated feedbacks on transverse asymmetries in the bi-directional exchange flow structure,<br> as well as on the internal flow stability.</p>
Dataset from: Transport and water age dynamics in soils: a comparative study of spatially-integrated and spatially-explicit models
<p>This dataset contains high-resolution vegetated lysimeter experimental dataset carried out in EPFL, Lausanne, Switzerland in March-August 2016. The lysimeter is 100 cm long with a diameter of 120 cm. During this experiment, a simultaneous spike injection of five different solutes (2,5-DFBA, 2-TFMBA, 3,4-DFBA, 2,6-DFBA, 3-TFMBA) took place on the 3rd of March 2016 at 14:00 in an hour. The solutes' mass recovery at the bottom of lysimeter was observed for these solutes.</p> <p>This dataset contains three files which are described in the following:</p> <ul> <li>"hydrologic_data.dat" contains the hourly fluxes (precipitation, irrigation, evapotranspiration measured from load cells, and the water draining at the bottom of lysimeter ) in mm/hr between the 19th of Feb-the 1st of Sep 2016.</li> <li>"tracer_data.dat" contains the tracer concentration observed at the bottom of lysimeter in mg/L. These samples are collected at variable frequencies with an approximate average of 1.5 samples per day.</li> <li>"additional_data.dat" informs you on dry mass and soil volume in the lysimeter, vegetation type, and volume of injection per solute.</li> </ul> <p> </p>
Enhanced Synthetic Texas 2,000 bus (ACTIVSg2000) test case w/synthesized dynamic parameters of wind generation and protective devices
<p>Enhanced Synthetic Texas 2,000 bus (ACTIVSg2000) test case w/synthesized dynamic parameters of wind generation and protective devices<br> Compatible with PowerWorld v21, adapted from ACTIVSg2000.pwb (<a href="https://electricgrids.engr.tamu.edu/electric-grid-test-cases/activsg2000/">https://electricgrids.engr.tamu.edu/electric-grid-test-cases/activsg2000/</a>)<br> <br> Used as a test case for the paper: `Electrical Grid Resilience Metric with Uncertainty.' Power Systems Computation Conference, under review. </p> <p>Wind Dynamic Parameters:<br> Machine models:<br> -REGC_A: Renewable Energy Generator/Converter.</p> <p> Machine governors:<br> -WTGT_A: Wind Turbine Generator Drive-train Model.</p> <p> Machine excitation system:<br> -REEC_A: Renewable Energy Electrical Control Model.</p> <p>Protective relays:<br> -DLSH: Rate of Frequency Load Shedding Model (used on all loads in network).<br> -LVSH: Undervoltage Load Shedding Model (used on all loads in network).<br> -TIOCR1: Time inverse overcurrent relay (used on all lines in network).<br> -FRQTPAT: Under frequency generator trip relay (used on all machines).<br> -LHVRT: Low/High Voltage Ride through Generator Protection (used on all machines).</p> <p> </p> <p>This research was completed by Idaho National Laboratory with funding<br> from the U.S. Department of Energy Wind Energy Technologies Office. Idaho National Laboratory is operated<br> by Battelle Energy Alliance under contract No. DE AC07-05ID14517.</p>
Striking differences in virulence, transmission, and sporocyst growth dynamics between two schistosome populations
<p>Dataset (v2) associated with the accepted publication in Parasites & Vectors - Striking differences in virulence, transmission, and sporocyst growth dynamics between two schistosome populations.</p>
Speed Prediction in Large and Dynamic Traffic Sensor Networks
<p>Aggregated traffic sensor data from Fortaleza (Brazil) in 2014.</p> <p>Please cite the following paper when using the dataset:</p> <p>R.P. Magalhaes, F. Lettich, J.A. Macedo, F.M. Nardini, R. Perego, C. Renso, R. Trani., <strong>Speed prediction in large and dynamic traffic sensor networks</strong>, Information Systems (2019) 101444, <a href="https://doi.org/10.1016/j.is.2019.101444">https://doi.org/10.1016/j.is.2019.101444</a></p> <p>You can also check details regarding the dataset in the paper.</p>
Dataset used in the article: Cunico, G., Aivazidou, E., Mollona, E. (2019), "European Cohesion Policy performance and citizens' awareness: A holistic System Dynamics framework", Investigaciones Regionales – Journal of Regional Research (In Press)
<p>In the context of the abovementioned article, interviews with experts about EU funding, as well as a workshop, were performed to find any missing factors or links in the conceptual model developed. This dataset provides detailed information about the interviews and the workshop. The related research is conducted in the context of the Horizon 2020 project PERCEIVE (www.perceiveproject.eu).</p>
Molecular dynamics simulations of the interaction of mutant human CYP2J2 (R111A) with arachidonic acid (POSES 1-3)
<p><strong>Description of files in this dataset:</strong></p> <p><strong>MD_mutR111A_CYP2J2_AA_StateX_repeatY.zip</strong> : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the R111A mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose). </p> <p>Each directory contains the following sub-directories:</p> <p>001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands</p> <p>002.min : Minimisation stage</p> <p>003.heat : Heating stage</p> <p>004.equil: Equilibration stage</p> <p>005.md : Production stage</p> <p>006.analysis : Basic energy graphs</p> <p>007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)</p>
Molecular dynamics simulations of the interaction of the double mutant human CYP2J2 (R117A and R111A) with arachidonic acid (POSES 4-6)
<p><strong>Description of files in this dataset:</strong></p> <p><strong>MD_mutR111A_R117A_CYP2J2_AA_StateX_repeatY.zip</strong> : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the double R111A + R117A mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose). </p> <p>Each directory contains the following sub-directories:</p> <p>001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands</p> <p>002.min : Minimisation stage</p> <p>003.heat : Heating stage</p> <p>004.equil: Equilibration stage</p>
VPS: Excavating High-Level C++ Constructs from Low-Level Binaries to Protect Dynamic Dispatching - (Evaluation Data)
<p>Evaluation data of the published paper: "VPS: Excavating High-Level C++ Constructs from Low-Level Binaries to Protect Dynamic Dispatching". The paper was published at the Annual Computer Security Applications Conference (ACSAC) 2019.</p> <p>The paper is available at: https://www.syssec.ruhr-uni-bochum.de/research/publications/VPS/</p> <p> </p> <p>Ab­stract</p> <p>Po­ly­mor­phism and in­heri­t­an­ce make C++ sui­ta­ble for wri­ting com­plex soft­ware, but si­gni­fi­cant­ly in­crea­se the at­tack sur­face be­cau­se the im­ple­men­ta­ti­on re­li­es on vir­tu­al func­tion ta­bles (vta­bles). These vta­bles con­tain func­tion poin­ters that at­ta­ckers can po­ten­ti­al­ly hi­jack and in prac­tice, vta­ble hi­ja­cking is one of the most im­portant at­tack vec­tor for C++ bi­na­ries. In this paper, we pre­sent VTa­ble Poin­ter Se­pa­ra­ti­on (VPS), a prac­tical bi­na­ry-le­vel de­fen­se against vta­ble hi­ja­cking in C++ ap­p­li­ca­ti­ons. Un­li­ke pre­vious bi­na­ry-le­vel de­fen­ses, which rely on un­sound sta­tic ana­ly­ses to match clas­ses to vir­tu­al call­si­tes, VPS achie­ves a more ac­cu­ra­te pro­tec­tion by re­stric­ting vir­tu­al call­si­tes to va­lidly crea­ted ob­jects. More spe­ci­fi­cal­ly, VPS en­su­res that vir­tu­al call­si­tes can only use ob­jects crea­ted at valid ob­ject con­struc­tion sites, and only if those ob­jects can reach the call­si­te. Mo­re­over, VPS ex­pli­cit­ly prevents false po­si­ti­ves (fal­se­ly iden­ti­fied vir­tu­al call­si­tes) from brea­king the bi­na­ry, an issue exis­ting work does not hand­le cor­rect­ly or at all. We eva­lua­te the pro­to­ty­pe im­ple­men­ta­ti­on of VPS on a di­ver­se set of com­plex, re­al-world ap­p­li­ca­ti­ons (Mon­goDB, MySQL ser­ver, Node.js, SPEC CPU2017/CPU2006), show­ing that our ap­proach pro­tects on aver­a­ge 97.8% of all vir­tu­al call­si­tes in SPEC CPU2006 and 97.4% in SPEC CPU2017 (all C++ bench­marks), with a mo­de­ra­te per­for­mance over­head of 11% and 9% geo­me­an, re­spec­tive­ly. Fur­ther­mo­re, our eva­lua­ti­on re­veals 86 false ne­ga­ti­ves in VTV, a po­pu­lar sour­ce-ba­sed de­fen­se which is part of GCC.</p>
Speciation data for "Pressure-induced coordination changes in a pyrolitic silicate melt from ab initio molecular dynamics simulations"
<p>With <em>ab initio</em> molecular dynamics simulations on pyrolite melt, we examine the detailed changes in elemental coordination as a function of pressure and temperature. We consider the average coordination as well as the proportion and distribution of coordination environments at pressures and temperatures encompassing the conditions at which molten silicates may exist in present-day Earth and those of the Early Earth's magma ocean. At ambient pressure and 2000 K, we find that the average coordination of cations with respect to oxygen is 4.0 for Si-O, 4.0 for Al-O, 3.7 for Fe-O, 4.6 for Mg-O, 5.9 for Na-O and 6.2 for Ca-O. Although the coordination for iron with respect to oxygen is underestimated, the coordination number for all other cations are consistent with experiments. At the base of the upper mantle (~15 GPa and 2000 K), the average coordination for Si-O remains at 4.0, but increases to 4.1 for Al-O, 4.2 for Fe-O, 4.9 for Mg-O, 8.0 for Na-O and 6.8 for Ca-O. The coordination environment for Na-O remains approximately constant up to core-mantle boundary conditions (135 GPa and 4000 K), but increases to about 6 for Si-O, 6.5 for Al-O, 6.5 for Fe-O, 8 for Mg-O, 9.5 for Ca-O. Our results have implications for melt properties, such as viscosity, transport coefficients, thermal conductivities and electrical conductivities, and will help interpret experimental results on silicate glasses.</p> <p>Detailed speciation statistics for pyrolite melt were determined using <em>a</em><em>b initio</em> molecular dynamics simulations with the Vienna Ab Initio Simulation Package (VASP) (Kresse and Furthmuller, 1996). Simulations were performed with a time step of 0.5-2 femtoseconds for 10-50 picoseconds, depending on the temperature and density. The composition of the Bulk Silicate Earth was modeled with a pyrolite melt with the stoichiometry NaCa<sub>2</sub>Fe<sub>4</sub>Mg<sub>30</sub>Al<sub>3</sub>Si<sub>24</sub>O<sub>89</sub>. Bond distances were determined from the pair distribution functions, which describe the probability of finding an atom type at a given distance from the reference atom. We used the first peak in the pair distribution function to approximate the average bond length; the distance at which the first minimum occurs marks the radius of the first coordination sphere of atoms that are directly bonded to the reference atom. We used this value to define the bond criterion between two atom types. Additional computational details can be found in the manuscript.</p>
An exploratory study (with and without time pressure) using mouse dynamics to detect faking-good behavior in the MMPI-2 and PPI-R validity scales
<p>Please find here the dataset generated and analyzed during the study entitled "Can mouse dynamics detect faking-good behavior in personality questionnaires? An exploratory study (with and without time pressure) using the MMPI-2 and PPI-R validity scales". Moreover, here you can find the source code of the experiment to execute the task using MouseTracker software, the code of the statistical analysis and a file containing the instructions to replicate ML model results reported in the original paper.</p>
Testing Dynamically Adaptive Systems: A Preliminary Literature Review
<p><strong>Context.</strong> Dynamically Adaptive Systems (DAS) encompasses a large class of systems that adapt their behaviours in response to changes in their context and/or predefined optimisation goals. Advanced software architectures support these adaptations robustly and efficiently at runtime. Yet, testing such architectures remains challenging as tests also need to cope with contextual and behavioural changes (addition, modification or removal) to be useful and prevent undesired behaviours to be deployed.<br> <strong>Objective.</strong> The objective of this study is to identify what strategies are used to test DAS and raise evidence on techniques and tools that achieve high defect detection even in unpredictable contexts.<br> <strong>Method.</strong> We performed a literature review of 389 studies published from the year 2001 until 2019. These studies cover the testing of Dynamic Software Product Lines, Context-Aware Systems and Dynamically Adaptive Systems.<br> <strong>Results.</strong> Our analysis comprised three fundamental aspects of testing strategies for DAS: executing the test cases, the test methods, and the test tools. Our preliminary findings indicate that the literature offers a large number of strategies to cope with such aspects. However, the studies analyzed do not show how to design or execute the test cases in practice.</p>
Phase portrait of the dynamical system for the mKdV equation
<p>Phase portrait of ion-acoustic waves for the dynamical system of the mKdV equation. There are three types of wave trajectories namely, nonlinear periodic trajectory (NPT) and nonlinear homoclinic trajectory (NHT) enclosing one equilibrium point with no separatrix, and supernonlinear periodic trajectory (SNPT) enclosing three equilibrium points with one separatrix. </p>
lingpy/sign-language-evolution-paper: Evolutionary Dynamics in the Dispersal of Sign Languages
<p>Supplement for study on Manual Alphabet evolution.</p>
Figure 1 in Surveillance of population dynamics and breeding habitat diversity of Anopheles subpictus in different areas of Odisha, East Central India
Figure 1. Map showing (circle marks) study areas.
Data for "Neural space-time model for dynamic multi-shot imaging"
<p>Data for "Neural space-time model for dynamic multi-shot imaging"</p> <p>Link to preprint: <a href="https://www.biorxiv.org/content/10.1101/2024.01.16.575950">https://www.biorxiv.org/content/10.1101/2024.01.16.575950</a></p> <p>Code: <a href="https://github.com/rmcao/nstm">https://github.com/rmcao/nstm</a></p> <p> </p> <p>Raw images from structured illumination microscopy (SIM):</p> <ul> <li>beads.tif: a dense microbead sample with vibrating motion (Fig.2)</li> <li>mito.tif: a live RPE-1 cell expressing StayGold-tagged mitochondrial matrix protein (Fig.3)</li> <li>er.tif: a RPE-1 cell expressing StayGold-tagged endoplasmic reticulum (Fig.4)</li> <li>f-actin.tif: a live RPE-1 cell tagged with F-Actin Halo-JF585 (Extended Data Fig.6)</li> <li>f-actin_extradelay.tif: a live RPE-1 cell tagged with F-Actin Halo-JF585 with extra time delay between rotations (Extended Data Fig.6)</li> </ul> <p> </p> <p>Baseline reconstruction:</p> <ul> <li>beads_fairSIM.tif: conventional reconstruction of the dense microbead sample using fairSIM software (https://www.fairsim.org)</li> <li>mito_cudasirecon.tif: conventional reconstruction for a mitochondria-labeled cell (mito.tif) using cuda-accelerated SIM reconstruction software (https://github.com/scopetools/cudasirecon)</li> <li>er_cudasirecon.tif: conventional reconstruction for an endoplasmic reticulum-labeled cell (er.tif) using cuda-accelerated SIM reconstruction software</li> <li>f-actin_cudasirecon.tif: conventional reconstruction for a F-Actin Halo-JF585 labeled cell (f-actin.tif) using cuda-accelerated SIM reconstruction software</li> <li>f-actin_extradelay_cudasirecon.tif: conventional reconstruction for a F-Actin Halo-JF585 labeled cell with extra delay (f-actin_extradelay.tif) using cuda-accelerated SIM reconstruction software</li> </ul>
Figure 1 in Spider assemblages and dynamics on a seasonal island in the Pripyat River, Belarus
Figure 1. Location of the study area – Belarus, the Turov Meadows at the Pripyat River (●).
Molecular dynamics simulation input files: Dynamics of amphiphilic poly($\varepsilon$-caprolactone) micelles with doxorubicin and transition temperature predictions using all-atom molecular dynamics simulation
<p>The files uploaded contain the input files for simulations:<br><br>1) P10_Solv: Input files for drug-free micelles.<br>2) Micelle_Solv: Input files for drug-loaded micelles.</p>
Supplementary Data for "DNA hairpin base-flipping dynamics drives APOBEC3A recognition and selectivity"
<p>Contains CSV-formatted files with RMSD and Sugar Pucker averages and standard deviations for 3- and 4-nt hairpin loop simulations as described in the manuscript "DNA hairpin base-flipping dynamics drives APOBEC3A recognition and selectivity".</p>
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.