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182 results for “state dependence”
Classification of GTP-dependent K-Ras4B active and inactive conformational states
<p>Dataset for the paper: Classification of GTP-dependent K-Ras4B active and inactive conformational states.</p> <p>Cite as: J. Chem. Phys. 158, 000000 (2023); DOI: 10.1063/5.0139181<br> Submitted: 18 December 2022; Accepted: 13 February 2023; Published Online: 13 February 2023.</p> <p>All molecular dynamics and molecular docking data presented, analyzed, and discussed in this paper are available at reasonable<br> requests submitted to the corresponding author. The following data are also available online: (i) file KRas4B_pdbs.zip, a compressed<br> archive including coordinate (.pdb) and structure (.psf) files for KRas-4B WT and D33E proteins, (ii) KRas4B_WT_traj.zip,<br> a compressed archive including trajectory files (.trr) for the WT KRas-4B runs, including 120 "*.trr"-formatted trajectories each corresponding to 40 ns of MD simulation time, and (iii) a sample Python script to generate a free energy plot as shown in Fig. 2.</p>
Dataset for the article "Spatially coherent diffusion of human RNA Pol II depends on transcriptional state rather than chromatin motion" by Roman Barth and Haitham Shaban
<p>The data set comprises all raw microscopy images and DFCC analyses as presented in </p> <p><strong>Spatially coherent diffusion of human RNA Pol II depends on transcriptional state rather than chromatin motion</strong></p> <p>by Roman Barth and Haitham Shaban, published in Nucleus (https://doi.org/10.1080/19491034.2022.2088988)</p> <p>There are two folders for RNAPII and DNA each, one for the raw images and one for the processed DFCC data, supplied as .mat files.</p> <p>Every folder contains three sub-folders containing the data for the conditions: +Serum, -Serum, and +DRB.</p>
Data set for "State-dependent cell-type-specific membrane potential dynamics and unitary synaptic inputs in awake mice"
<p>Data set for: Pala A, Petersen CCH (2018) State-dependent cell-type-specific membrane potential dynamics and unitary synaptic inputs in awake mice. eLife 7: e35869. DOI: https://doi.org/10.7554/eLife.35869.</p> <p>There are 12 files in this data upload:</p> <p>1. '2018_Pala_eLife.pdf' - this is a pdf version of the online publication: Pala & Petersen (2018).</p> <p>2. 'data.mat' - this is a Matlab data structure, which contains all the data for the publication.</p> <p>3. 'DataViewer.m' - this is a Matlab code for viewing the data.</p> <p>4. 'DataViewer.fig' - this is a Matlab figure file, which is the GUI layout for 'DataViewer.m'.</p> <p>5. 'PalaPetersen_Plot.m' - this is a Matlab code, which plots the figures for Pala & Petersen (2018).</p> <p>6. 'PalaPetersen_Analysis.m' - this is a Matlab code, which analyses the data for the figures of Pala & Petersen (2018).</p> <p>7. 'blankAPs.m' - this is a Matlab code, which blanks action potentials from the membrane potential trace.</p> <p>8. 'lowpassfilt.m' - this is a Matlab code, which low pass filters the LFP.</p> <p>9. 'medianFiltAPs.m' - this is a Matlab code, which median filters the membrane potential trace to remove action potentials.</p> <p>10. 'remTrialswithAPs.m' - this is a Matlab code, which removes trials with action potentials.</p> <p>11. 'retrieveSegDur.m' - this is a Matlab code, which retrieves chunks of the recording of a given length.</p> <p>12. 'suptitleAP.m' - this is a Matlab code, which puts titles above subplots.</p>
Evidence for a by-product mutualism in a group hunter depends on prey movement state
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Data from: Whole-organism behavioral profiling reveals a role for dopamine in state-dependent motor program coupling in C. elegans.
<p>Animal behaviors are commonly organized into long-lasting states that coordinately impact the generation of diverse motor outputs such as feeding, locomotion, and grooming. However, the neural mechanisms that coordinate these diverse motor programs remain poorly understood. Here, we examine how the distinct motor programs of the nematode <i>C. elegans </i>are coupled together across behavioral states. We describe a new imaging platform that permits automated, simultaneous quantification of each of the main <i>C. elegans</i> motor programs over hours or days. Analysis of these whole-organism behavioral profiles shows that the motor programs coordinately change as animals switch behavioral states. Utilizing genetics, optogenetics, and calcium imaging, we identify a new role for dopamine in coupling locomotion and egg-laying together across states. These results provide new insights into how the diverse motor programs throughout an organism are coordinated and suggest that neuromodulators like dopamine can couple motor circuits together in a state-dependent manner. </p>
Real-time benchmark dynamics of the Ohmic Spin-Boson Model computed with Time-Dependent Variational Matrix Product States. (TDVMPS) coupling strength and temperature parameter space
<p>Data describing the complete propagators (maps) for the evolution of the Ohmic Spin-Boson Model are made available, here. Using a time-dependent variotnal matrix product states (TDVMPS) respresentation of the complete spin-environment wave function, non -perturbative results are presented over a wide range of coupling strengths, temperatures and initial conditions. The results in this repository are associated with the article: </p> <p>https://www.preprints.org/manuscript/202012.0016/v1 </p> <p>A mathematica notebook that allows the data to be visualised and manipulated is also provided. </p>
Exact Spin-Boson-Model Tunneling Dynamics with Time Dependent Variation Matrix Product States (TDVMPS). Barrier height and temperature parameter space
<p>Spin-Boson tunnelling data acquired using the T-TEDOA method for Time-Dependent-Variational-Matrix-Product-States (TDVMPS) accompanying the paper <a href="https://doi.org/10.3389/fchem.2020.600731">https://doi.org/10.3389/fchem.2020.600731</a>.</p> <p> </p>
Dataset accompanying publication: "Modulation of Cortical Oscillations by Low-Frequency Direct Cortical Stimulation is State-Dependent"
<p>Dataset accompanying publication:</p> <p>"Modulation of Cortical Oscillations by Low-Frequency Direct Cortical Stimulation is State-Dependent", Alagapan, Schmidt, Lefebvre, Hadar, Shin and Frohlich</p> <p>For questions, contact flavio_frohlich@med.unc.edu</p> <p>The mat file consists of the following Matlab variables</p> <ol> <li><strong>Electrode Distance</strong>: 3 x 1 cell array containing the arrays (trial x electrode) of distance from stimulating electrode to recording electrode for the three ECoG participants. (First array corresponds to P001, Second array corresponds to P005 and Third array corresponds to P008)</li> <li><strong>Spectra_Electrode_EC</strong>: 3 x 1 cell array consisting of nTrial x nFreq x nChannels x nEpochs matrices for each subject’s eyes-closed experiment. nTrial corresponds to number of trials, nFreq corresponds to frequencies at which spectral power is calculated, nChannels corresponds to number of electrodes in the analysis and nEpochs corresponds to “Before Stimulation”, “During Stimulation” and “After Stimulation” epochs.</li> <li><strong>Spectra_Electrode_EO</strong>: 3 x 1 cell array consisting of nTrial x nFreq x nChannels x nEpochs matrices for each subject’s eyes-open experiment. The dimensions are the same as above. The first array consists of task-engaged dataset from Participant P001.</li> <li><strong>MI_Summary</strong>: 8 x 1 cell array consisting of 3 x 1 cell arrays of modulation indexes for the three participants. The 8 arrays stand for the modulation indexes in different epochs and different frequencies. Refer <strong>MI_Summary_Names</strong></li> <li><strong>MI_Summary_Names</strong>: 8 x 1 cell array consisting of strings denoting the arrays in <strong>MI_Summary</strong>. <strong>During</strong> in text corresponds to “During Stimulation” epoch and <strong>After</strong> corresponds to “After Stimulation” epoch.</li> <li><strong>f</strong>: Frequencies at which spectral power was estimated.</li> <li><strong>NetworkModel</strong>: Matlab struct containing the time series generated by the network model and corresponding spectra. The <strong>timeseries</strong> consists of 4 columns – 1<sup>st</sup> column corresponds to time, 2<sup>nd</sup> column corresponds to task-engaged state data, 3<sup>rd</sup> column corresponds to eyes-open state data and 4<sup>th</sup> column corresponds to eyes-closed state data. The <strong>spectra </strong>struct consists of spectral powers estimated in the different epochs. 1<sup>st</sup> column of each epoch array corresponds to task-engaged state, 2<sup>nd</sup> column corresponds to eyes-open state and the 3<sup>rd</sup> column corresponds to eyes-closed state.</li> <li><strong>SummationModel</strong>: Matlab struct containing the time series generated by the summation model and the peak values in spectra before and during stimulation by varying the two strength parameters. The columns correspond to stimulation strength while rows correspond to oscillation strength. The oscillation strength parameter was varied from 0.5 to 50 in steps of 0.5 and the stimulation strength parameter was varied from 0.1 to 10 in steps of 0.1. </li> </ol> <p> </p>
Sex- and state-dependent covariation of risk-averse and escape behavior in a widespread lizard
<p>Mounting evidence has show<span>n</span> that personality and behavioral syndromes have a substantial influence on <span>interspecific interactions</span> and <span>individual </span>fitness. However, the stability of <span>covariation among multiple behavioral traits involved in antipredator responses</span> <span>has seldom been tested</span>. Here, we <span>investigate whether </span>sex, <span>gravidity</span>, and parasit<span>e infestations influence</span> <span>the covariation</span> <span>between</span> <span>risk-aversion</span> <span>(hiding time within a refuge) </span>and <span>escape</span> <span>response (immobility, escape distance)</span> using a viviparous lizard<span>,</span> <em>Zootoca vivipara</em><span> as a model system. Our results</span> <span>demonstrated a correlation between risk-averse and escape behavior at the among-individual level, but </span>only <span>in</span> <span>gravid</span> females<span>. We found no significant correlations in either males or neonates</span>. <span>A striking result was the loss of the association in post-parturition females. </span>Th<span>is</span> <span>suggests</span> that the <span>'risk-averse</span> – <span>e</span>scape<span>'</span> syndrome <span>is ephemeral and only emerges in response to constraints on locomotion driven by reproductive burden.</span> <span>Moreover</span>, parasites have the potential to disassociate the<span> correlations between</span> <span>risk-aversion and </span>escape <span>response</span> in <span>gravid</span> females, <span>yet the causal chain requires further examination</span>. <span>Overall, o</span>ur findings provide evidence of differences in the association <span>between</span> <span>behaviors within the life-time of an individual</span> and <span>indicate</span> that <span>individual states, sex and life stages can together</span> influence the stability of behavioral syndromes.</p>
Dataset for "Impacts and state-dependence of AMOC weakening in a warming climate" by Bellomo & Mehling
<p>This dataset allows the user to reproduce figures from the journal article "Impacts and state-dependence of AMOC weakening in a warming climate" by Bellomo & Mehling.</p>
Data underlying the article 'How nutrient retention and TN:TP ratios depend on ecosystem state in thousands of Chinese lakes'.
<div> <p>Here we share the data underlaying the publication 'How nutrient retention and TN:TP ratios depend on ecosystem<br>state in thousands of Chinese lakes' <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.scitotenv.2024.170690" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.scitotenv.2024.170690</a>.</p> </div> <div>In this study, we used data for analysis, models and R-scripts.</div> <div>The dataset contains data for the historic (2012) situation, and data for an economic-focused scenario and a sustainability-focused scenario for 2050.</div> <div> </div> <div>Raw input data originates from</div> <div>1) Climate scenario variables: HydroLAKES (Messager et al., 2016)</div> <div>2) Historic climate variables: https://doi.org/10.4121/13348004</div> <div>3) Nutrient losses to land for the SSP scenarios: Wang et al. 2020</div> <div> </div> <div>Model input and output data can be found in this database</div> <div>1) Simulated climate variables: folder 1</div> <div>2) Scenario specific parameter values: folder 1</div> <div>3) PCLake+ model output: folder 3</div> <div> </div> <div>R-scripts, as well as the used model (PCLake+), can be found in this database</div> <div>1) R-script to run PCLake+: folder 2 and 6</div> <div>2) R-script to process PCLake+ output data: folder 4</div> <div>3) PCLake+ software: folder 5: GNU LESSER GENERAL PUBLIC LICENSE, Version 3, 29 June 2007</div> <div> </div> <div>Data used for analysis can be found in this database</div> <div>1) ProcessedData.cvs: folder 4</div>
Velocity and temperature dependence of steady-state friction of natural gouge controlled by competing healing mechanisms
<p>The empirical rate- and state-dependent friction law is widely used to explain the frictional resistance of rocks. However, the constitutive parameters vary with temperature and sliding velocity, preventing extrapolation of laboratory results to natural conditions. Here, we explain the frictional properties of natural gouge from the San Andreas Fault, Alpine Fault, and the Nankai Trough from room temperature to $\sim300^\circ$C for a wide range of slip-rates with constant constitutive parameters by invoking the competition between two healing mechanisms with different thermodynamic properties. A transition from velocity-strengthening to velocity-weakening at steady-state can be attained either by decreasing the slip-rate or by increasing temperature. Our study provides a framework to understand the physics underlying the slip-rate and state dependence of friction and the dependence of frictional properties on ambient physical conditions. </p>
Fish resist temptation from junk food: State-dependent diet choice in reproductive Atlantic cod (Gadus morhua) facing seasonal fluxes of lipid-rich prey
<p>In ecological sciences, animal diets are often simplified to "resources" or "caloric quantities". However, in the present study, we investigated the optimal foraging strategy of Atlantic cod (Gadus morhua) when both macro- and micro-nutritional requirements are accounted for. Proteins cannot be synthesized from fatty acids, so the proteins for gonad development must come from other dietary sources. In addition, micronutrients are required in smaller quantities. For example, for cod, arachidonic acid (ARA) acts as a micronutrient precursor for prostaglandins, which is important for reproduction. We formulated a dynamic state-dependent model to make predictions about optimal diet choice and foraging behavior. We applied the model to a case study in the strait between Denmark and Sweden. The model predicted that energy acquired from dietary protein should be twice that acquired from lipids, with a small increase in the lipid requirements when gonads are growing. The model also predicted that the "energy sparing effect of lipids" made it beneficial to engage in risky foraging activity to supplement a lean diet with a little bit of fat. When we re-constructing the model to also optimize ARA uptake, the cod consumed relatively more ARA-rich crabs in the months prior to spawning, despite the otherwise poor energetic value of this prey. In support of the model predictions, field observations indicated that lipid stores reached a peak shortly after the arrival of the lipid-rich migrating herring and the fatty acid signal of these herring were evident in the liver of nearly all cod. Three month later, only half of the cod contained the herring-derived fatty acid signal, supporting the predicted shift in prey type prior to spawning. From these model predictions and field observations, we conclude that, also in the wild, nutritional requirements can be at least as important as pure energy acquisition.</p>
Raw experimental data and matlab codes for the paper "State-dependent driving : A route to non-equilibrium stationary states"
<p>Raw experimental data and matlab codes used for numerical simulation in the paper - "State-dependent driving : A route to non-equilibrium stationary states". The data and codes to generate figures 2, 3 and 5 are available in the folders named "Fig 2", "Fig 3" and "Fig 5" respectively.</p>
Loading-Dependent Structural Model of Polymeric Micelles Encapsulating Curcumin by Solid-State NMR Spectroscopy
<p>(Raw) experimental and calculation data, which was the basis for this publication.</p> <ul> <li>DOSY</li> <li>solid-state NMR</li> <li>PXRD</li> <li>Dissolution Rates</li> <li>GIPAW (CASTEP) calculations</li> </ul>
Dataset for "State-dependence of the equilibrium climate sensitivity in a clear-sky GCM" by Matthew Henry et al. (2023).
<p>Dataset for "State-dependence of the equilibrium climate sensitivity in a clear-sky GCM" by Matthew Henry, Geoffrey K. Vallis, Nicholas J. Lutsko, Jacob T. Seeley, and Brett A. McKim.</p>
Dataset:Female state and condition-dependent chemical signalling revealed by male choice of silk trails
<p class="MsoNormal"><span>We ask whether males of the nuptial gift-giving spider <em>Pisaura mirabilis</em> exert preferences for mates varying in their reproductive potential based on chemical information during mate search. Males were presented with binary trails consisting of silk lines and substrate-borne chemicals deposited while females were walking, from females varying in a) body condition (high vs. low), b) developmental state (subadult vs. adult) and c) mating state (unmated vs. mated). If female chemical signaling co-varies with individual state, we expect males to choose trails of females that are a) in higher body condition, indicating higher fecundity, b) adults, which can successfully reproduce, and c) unmated, to avoid sperm competition. </span><span>We show that female signaling is condition-dependent, with m</span><span>ales being</span><span> more likely to follow trails of higher body condition females, but not dependent on female mating state. Males also tended to prefer trails of adults over subadults. Choice did not depend on male individual body condition.</span></p>
Stochastic cell-cycle entry and cell-state-dependent fate outputs of injury-reactivated tectal radial glia in zebrafish
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Data from: Causes and consequences of individual variation: Linking state-dependent life histories to population performance
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Data from: Temperament, state-dependent behaviors, and their interplay in large herbivores: Lessons from a long-term study on mule deer, elk, and bighorn sheep
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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
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