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11,506 results for “Dynamics”
Dataset: Capturing dynamical correlations using implicit neural representations
<p>Dataset of Linear Spin Wave Theory simulations accompanying the manuscript: Capturing dynamical correlations using implicit neural representations. </p>
Population dynamics and seasonal migration patterns of Spodoptera exigua in northern China based on 11 years of monitoring data
<p>The beet armyworm, <em>Spodoptera exigua </em>(Hübner) is an important migratory pest worldwide that has caused serious economic losses in the main crop-producing areas of China. To effectively monitor and control this pest, it is necessary to investigate its interannual and seasonal migration patterns in northern China. In this study, we weekly monitored the population dynamics of <em>S. exigua</em> using sex pheromone traps in Shenyang, Liaoning Province from 2012 to 2022 and simulated the migration trajectories using the HYSPLIT model. Overall, the migration numbers varied significantly among years, with large migrations in 2018 and 2020 that resulted in a total catch of more than 2000 individuals. </p>
Identification of Potential JNK3 Inhibitors Through Virtual Screening, Molecular Docking And Molecular Dynamics Simulation as Therapeutics for Alzheimer's Disease
<p>Alzheimer's disease (AD) is a complex neurological disorder without effective treatment. One factor in its development is c-Jun N-terminal kinases (JNKs), a type of protein related to brain function. JNK3, found mainly in the brain, contributes to AD by promoting brain abnormalities. Current research aims to create new JNK3 inhibitors for AD treatment using a virtual screening method. A database of compounds was filtered, and five potential compounds were identified with better scores than a reference. These compounds underwent simulations and energy calculations, showing stability and potential as JNK3 inhibitors.</p>
Data set used in article: On the Potential of Reduced Order Models for Wind Farm Control: A Koopman Dynamic Mode Decomposition Approach
<p>Step-wise pitch simulation of two wind turbines interacting using SOWFA. More information in the paper.</p>
Data underpinning "Unraveling long-time quantum dynamics using flow equations"
<p>The study of many-body quantum dynamics in strongly-correlated systems is extremely challenging. To date few numerical methods exist which are capable of simulating the non-equilibrium dynamics of two-dimensional quantum systems, in part reflecting complexity theoretic obstructions. In this work, we present a new technique able to overcome this obstacle, by combining continuous unitary flow techniques with the newly developed method of scrambling transforms. We overcome the prejudice that approximately diagonalizing the Hamiltonian cannot lead to reliable predictions for relatively long times. To the contrary, we show that the method works well in both localized and delocalized phases, and makes reliable predictions for a number of quantities including infinite-temperature autocorrelation functions. We complement our findings with rigorous incremental bounds on the truncation error. This approach shows that in practice, the exploration of intermediate-scale time evolution may be more feasible than is commonly assumed, challenging near-term quantum simulators.</p>
MDCC: A Multimodal Dynamic Dataset for Donation-based Crowdfunding Campaigns
<p>This is the repository of MDCC: A Multimodal Dynamic Dataset for Donation-based<br> Crowdfunding Campaigns. For details, please refer: https://github.com/Jiayang-L1/mdcc</p> <p><br> V2: We added json and csv files for easier use and renamed it with standard name. Specifically, the "comment_cor_time" column in new files means the corresponding donation time of each comment.</p>
Mapped data: Transcription factor stoichiometry, motif affinity and syntax regulate single cell chromatin dynamics during fibroblast reprogramming to pluripotency
<p>This record contains mapped sequencing data for the paper "Transcription factor stoichiometry, motif affinity and syntax regulate single cell chromatin dynamics during fibroblast reprogramming to pluripotency" by Nair, Ameen <em>et al</em>. It contains single-cell RNA-seq (scRNA) and single-cell ATAC-seq (scATAC) data from a time course of human dermal fibroblasts induced with Yamanaka factors OSKM using a Sendai virus based delivery system. The scRNA and scATAC data is performed at days 0, 2, 4, 6, 8, 10, 12, 14 and the final iPSCs. The experiment was re-performed and single-nucleus multiome (ATAC+RNA) was collected on days 1 and 2. </p> <p>The data is as follows:</p> <p><strong>scATAC</strong>: We used Chromap (commit <a href="https://github.com/haowenz/chromap/tree/6e97125b9">https://github.com/haowenz/chromap/tree/6e97125b9</a>, <a href="https://doi.org/10.1038/s41467-021-26865-w">https://doi.org/10.1038/s41467-021-26865-w</a>) to perform barcode correction, alignment and filtering for each of our samples. The corresponding fragment files (tab separated file containing mapped fragments with columns: chr, start, end, barcode, number of reads) and their tabix indices are available for each sample.</p> <p><strong>scRNA</strong>: We used cellranger v6.0.2 for read mapping and quantification to obtain the counts matrix. We used the GRCh38 2020-A reference. For each sample, the raw and filtered counts matrices are provided. E.g. `D0/raw_feature_bc_matrix.h5` contains an HDF5 object containing gene counts for each barcode and associated metadata for the Day 0 sample. Similarly, the files in `D0/raw_feature_bc_matrix/` contain the same gene x barcode matrix, with the counts matrix in Matrix Market format (`matrix.mtx.gz`), and gene (`features.tsv.gz`) and barcode names (`barcodes.tsv.gz`). </p> <p><strong>multiome</strong>: The ATAC and RNA components are separately processed using the same tools as mentioned above for scATAC and scRNA. Outputs are in the `snATAC` and `snRNA` subdirectories respectively. In addition, the `ATAC.RNA.bc.map.tsv` file contains a map to link snATAC barcodes to snRNA barcodes. </p>
Molecular dynamics simulation trajectories for the GB99dms implicit solvent force field
<p>Molecular dynamics simulation trajectories used in training and validating the GB99dms implicit solvent protein force field. See the paper:</p> <ul> <li>Greener JG. Differentiable simulation to develop molecular dynamics force fields for disordered proteins, <a href="https://doi.org/10.1039/D3SC05230C" target="_blank" rel="noopener">Chemical Science</a> 15, 4897-4909 (2024)</li> </ul> <p>For more information, including structure files for these trajectories, see https://github.com/greener-group/GB99dms.</p>
Source Data for the publication: "How Orange Carotenoid Protein controls the excited state dynamics of Canthaxanthin"
<p>This dataset contains the raw data for the results shown in the paper, in plain text format. The first line of each file describes the content of the columns.</p> <p>Contents:</p> <ul> <li>ocp_adiabatic_energies.txt - Energies of the adiabatic states (A.U.) for all SH trajectories of CAN in OCP</li> <li>ocp_bla.txt - Values of the BLA coordinate (Angstrom) for all SH trajectories of CAN in OCP</li> <li>ocp_dihedrals.txt - Values of the CAN dihedrals ) degrees for all SH trajectories of CAN in OCP</li> <li>ocp_populations.txt - Calculated adiabatic populations of CAN in OCP</li> <li>vac_adiabatic_energies.txt - Energies of the adiabatic states (A.U.) for all SH trajectories of CAN in gas phase</li> <li>vac_bla.txt - Values of the BLA coordinate (Angstrom) for all SH trajectories of CAN in gas phase</li> <li>vac_dihedrals.txt - Values of the CAN dihedrals ) degrees for all SH trajectories of CAN in gas phase</li> <li>vac_populations.txt - Calculated adiabatic populations of CAN in gas phase</li> </ul> <p><br> </p> <p> </p> <p> </p>
ChromBPNet models and data: Transcription factor stoichiometry, motif affinity and syntax regulate single cell chromatin dynamics during fibroblast reprogramming to pluripotency
<p>This record contains ChromBPNet models and data used to train the models for the paper "Transcription factor stoichiometry, motif affinity and syntax regulate single cell chromatin dynamics during fibroblast reprogramming to pluripotency" by Nair, Ameen <em>et al</em>.</p> <p>`data` contains bigwigs and regions (peaks + non-peaks) used for training each of the models. See `data/README.txt` for more details.</p> <p><strong>Models:</strong></p> <p><em>Loading the model:</em></p> <p>The models were trained using tf1.14. The models are provided in h5 format for tf1.14 (py3.7) and SavedModel format for tf2.X. tf2.X tested only for py3.8-11, tf2.8-13.</p> <p>To load the models in tf1.14:</p> <pre><code class="language-python">model = tf.keras.models.load_model("path/to/model.h5")</code></pre> <p>In tf2:</p> <pre><code class="language-python">model = tf.keras.models.load_model("path/to/model_dir")</code></pre> <p>If all fails, you can load the architecture as provided in `model_arch.py` with default parameters (`bpnet_seq` for bias model and `chrombpnet` for chrombpnet model), and then load the weights using `model.load_weights` from the weights provided in the `weights` directory.</p> <p> </p> <p><em>Usage:</em></p> <p>The bias models take as input one-hot sequence of length 2000. It has 2 outputs, a vector of logits of length 2000, and 1 logcounts scalar:</p> <pre><code class="language-python"># seq_one_hot of length B x 2000 x 4 out_bias_logits, out_bias_logcounts = bias_model.predict(seq_one_hot) # out_bias_logits: B x 2000 # out_bias_logcounts: B x 1</code></pre> <p>The ChromBPNet model takes as input a one-hot sequence of length 2000, bias logits of length 2000 and bias log-counts scalar. It has the same output types as the bias model. To run the chrombpnet model to obtain predictions:</p> <pre><code class="language-python">pred_profile, pred_logcounts = chrombpnet_model.predict([seq_one_hot, out_bias_logits, out_bias_logcounts]) # pred_profile: B x 2000 # pred_logcounts: B x 1 </code></pre> <p>If you wish to obtain the "de-biased" predictions (see Methods), simply pass in zeros instead of the bias model predictions as:</p> <pre><code class="language-python">pred_profile_debiased, pred_logcounts_debiased = chrombpnet_model.predict([seq_one_hot, np.zeros((seq_one_hot.shape[0], 2000)), np.zeros((seq_one_hot.shape[0], 1))])</code></pre> <p>To obtain predicted per-base predicted counts (with or without bias):</p> <pre><code class="language-python">pred_per_base_counts = scipy.special.softmax(pred_profile, axis=-1) * (np.exp(pred_logcounts)-1) # pred_per_base_counts: B x 2000 </code></pre> <p>Note that in general predicted counts can't be compared across models as they are not corrected for sequencing depth.</p> <p> </p> <p><em>Note:</em></p> <p>All bias models used across folds are identical, except for the final intercept term in the counts output (see Methods), that is specific to each cell state, fold combination.</p> <p> </p> <p><em>Folds:</em></p> <p>The splits used for training the different folds are as below:</p> Fold Test Chromosomes Validation Chromosomes 0 chr1 chr8, chr10 1 chr2, chr19 chr1 2 chr3, chr20 chr2, chr19 3 chr6, chr13, chr22 chr3, chr20 4 chr5, chr16, chrY chr6, chr13, chr22 5 chr4, chr15, chr21 chr5, chr16, chrY 6 chr7, chr18, chr14 chr4, chr15, chr21 7 chr11, chr17, chrX chr7, chr18, chr14 8 chr9, chr12 chr11, chr17, chrX 9 chr8, chr10 chr9, chr12 <p>Remaining chromosomes were used as the training chromosome for each fold.</p>
The dynamic matrix predicts population response to long-term experimental forest fragmentation
<div><strong>Context</strong></div> <div> </div> <div>Earth's forests are fragmented. Species' long-term persistence depends on their conservation in fragmented landscapes with remnants embedded in a matrix of human land use. This matrix influences species' persistence in fragments by determining their degree of isolation and the extent to which edge effects alter habitat. Matrix habitat is often dynamic, so its impact on persistence of remnant species changes over time.</div> <div> </div> <div><strong>Objectives</strong></div> <div> </div> <div>Previous research showed that the abundance response of predatory beetle species to matrix habitat predicted their response in fragments with a log-response ratio of about 0.5. When abundance declined in the matrix, there was a smaller but predictable decline in fragments. However, the predictive utility of a fragment:matrix log-response ratio needs testing with functionally different species, more detailed data, and a focus on mechanism.</div> <div> </div> <div><strong>Methods</strong></div> <div> </div> <div>In the Wog Wog habitat fragmentation experiment, we follow a detritivorous amphipod 27 years after forest fragmentation.</div> <div> </div> <div><strong>Results</strong></div> <div> </div> <div>The amphipod's response in habitat fragments was predicted by its response in the matrix with a log-response ratio of about 0.5, similar to predatory beetles. The amphipod's response was explained by its abiotic niche. The amphipod's short-term response did not predict its long-term response.</div> <div> </div> <div><strong>Conclusions</strong></div> <div> </div> <div>The log-response ratio might generalize across the invertebrate food web. For two groups within the Wog Wog experiment, a species' dynamic response in matrix habitat predicted its persistence in fragments. Future work should explore the generality of this finding. With knowledge of projected land use of matrix habitat, a species' matrix response could be used for management planning.</div>
Data supplement for "Stick-slip Dynamics in the Forced Wetting of Polymer Brushes"
<p>This dataset contains supplementary data for the following publication:</p> <p>Greve, D., Hartmann, S. & Thiele, U.<br> Stick-slip Dynamics in the Forced Wetting of Polymer Brushes<br> Soft Matter, 2023, 19, 4041-4061</p> <p>We provide the source files and data for all figures as well as a video of the stick-slip motion of a liquid front on a polymer brush substrate corresponding to the data shown in Figs. 10 & 11 of the paper.</p>
Data and Code Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"
<p>Code and Data Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"<br> ===========================================================</p> <p>This directory contains the data and scripts used to create the plots from our publication as well as the source<br> code modifications necessary to run this test case within the CESM and MPAS models.</p> <p>Generating Plots<br> ---------------</p> <p>The `netcdf` directory contains the nominal half-degree runs necessary to generate nearly all of the plots from the paper. The one plot which is not reproducible from these data is the volume-integrated Eddy Kinetic Energy in the Spectral Element model. Storing high-resolution 4D wind fields requires a prohibitive amount of space. These data can be provided by the corresponding author, O.K. Hughes (owhughes@umich.edu). However, because this is several hundred GB of data I would strongly recommend generating these high-resolution runs yourself on your local system if you need them. Using 288 Intel Skylake cores (that is, 8 nodes each with two 18C processors) ran on the order of an hour.</p> <p><em>In order to generate the plots from the paper, you need only install NCL and then run</em> run.bash. Instructions for installing NCL<br> can be found in the `run.bash` script.</p> <p>Source Code Modifications<br> ----------------</p> <p><strong>CESM</strong><br> The `src` subdirectory contains the files `user_nl_cam` and `ic_baroclinic.F90`. Create a case using `--compset=FKESSLER` and `--run-unsupported` options when running `create_newcase`. If your case is located at `${CASE_DIR}`, then from within the directory containing this README, run `cp user_nl_cam ${CASE_DIR}/user_nl_cam`, and then run `cp ic_baroclinic.F90 ${CASE_DIR}/SourceMods/src.cam/`. Then build and run the model using the usual workflow.</p> <p><strong>MPAS</strong></p> <p>The MPAS code was run using a branch of the MPAS model provided by the model developers to the authors. While the source code modifications are provided in the `src` directory, I would strongly recommend contacting the corresponding author if you wish to run this test case in the MPAS codebase.</p>
Attack time analysis in dynamic attack trees via integer linear programming
<p>Matlab code for the experiments of the paper "Attack time analysis in dynamic attack trees via integer linear programming" by Milan Lopuhaä-Zwakenberg & Mariëlle Stoelinga.</p> <p>The code can be accessed either via the virtual machine in Artifact_MILPforDATs_revised.zip, or through the code directly in Matlab_code.zip. The results are in Paper_results.zip.</p> <p>To run the code, installations of Matlab and Gurobi are required.</p>
Implementation of the novel Duo-Grid in GFDL's FV3 Dynamical Core - Code and simulations files
<p>Supporting simulation files and code for the JAMES technical paper: Implementation of the novel Duo-Grid in GFDL’s FV3 Dynamical Core. This study tests the Duo-Grid implementation in FV3 through idealized 2D and 3D simulations to address the issue of cubed sphere grid imprinting. Please note that the provided code is still a test version. It is compiled with the FMS version tag 2020.04.</p>
Invasion dynamics of the European Collared-Dove are explained by combined effects of habitat and climate
<p>Global biodiversity is increasingly threatened by the spread of invasive species. Understanding the mechanisms influencing the initial colonization and persistence of invaders is therefore needed if conservation actions are to prevent new invasions or strive to slow their spread. The Eurasian collared-dove (<em>Streptopelia decaocto</em>, EUCO) is one of the most successful avian invasive species in North America; however, to our knowledge, no study has simultaneously examined the role that climate-matching, human activity, directional propagation, and local density have in this invasion process. Our research expands upon a cellular-automata-based hierarchical model developed to assess directional invasion dynamics to further quantify the impacts of climate, elevation, and land cover type on the spread of EUCO in North America. Our results suggest that EUCO's dispersal patterns can largely be explained by the effects of habitat, climate, and environmental conditions at different stages of the invasion process rather than some innate preferred north-westerly spread. Specifically, EUCO initially colonized warm and wet grassland habitats and tended to persist in urban areas. We also found that while EUCO were more likely to spread to the northeast of existing habitats, directional preference did not drive persistence and recolonization events. These findings highlight the importance of incorporating both neighbourhood effects and environmental factors in the modelling of range-expanding species, adding to the toolset available to researchers to model invasive species spread. Further, our research demonstrates that historical records of invasive species occurrences from citizen science projects can provide the data resources needed to disentangle the characteristics driving species invasion and enable predictions that are of critical importance to resource managers.</p>
Data from: hibernation telomere dynamics in a shifting climate: insights from wild greater horseshoe bats
<p>Hibernation is linked with various hypotheses to explain the extended lifespan of hibernating mammals compared with their non-hibernating counterparts. Studies on telomeres, markers of ageing and somatic maintenance, suggest telomere shortening slows during hibernation and lengthening may reflect self-maintenance with favourable conditions. Bats in temperate zones adjust body temperatures during winter torpor to conserve energy and exploit mild conditions for foraging. Climate change may impact the hibernation cycle of bats, but more research is needed regarding the role of telomeres in understanding their response to a changing climate. Here relative telomere length (rTL) was measured in the long-lived greater horseshoe bat<em> Rhinolophus ferrumequinum</em> (n = 223 individuals) over three winters, considering climatic conditions. Cross-sectional analyses revealed between-individual variation in rTL with a strong year effect, likely linked to varying weather conditions and foraging success. Additionally, within-individual increases of rTL occurred in 51% of consecutive measurements, with evidence of increasing telomerase expression during hibernation in this species. These findings highlight the beneficial effects of hibernation on telomeres and potential consequences of changing climatic conditions for long-lived temperate bats. Understanding the interplay between hibernation, telomeres, and climate can provide insights into the adaptive capacity and survival of bat populations facing environmental challenges.</p>
Sims et al. A Tale of Two Pools: The Dynamic Influence of Subsurface Geological Processes on the Assembly and Diversification of Thermophilic Microbial Communities in Hydrothermal Systems - Supplementary Datasets
<p>These datasets comprise the supplementary datasets found in Sims et al. A Tale of Two Pools: The Dynamic Influence of Subsurface Geological Processes on the Assembly and Diversification of Thermophilic Microbial Communities in Hydrothermal Systems, <strong><em>Geochimica et Cosmiochimica Act </em></strong></p>
Identifying the variety of jovian X-ray auroral structures: tying the morphology of X-ray emissions to associated magnetospheric dynamics
<p>The data used in Weigt et al., study <strong><em>"Identifying the variety of jovian X-ray auroral structures: tying the morphology of X-ray emissions to associated magnetospheric dynamics"</em>.</strong> The README.pdf explains what data is used to produce each Figure in the article with links to the Chandra archive and other data repositories. Pipeline to analyse data can be found here: </p> <pre><a href="https://doi.org/10.5281/zenodo.7380282">https://doi.org/10.5281/zenodo.7380282</a> </pre>
The effects of sex on extinction dynamics of Chlamydomonas reinhardtii depend on the rate of environmental change
<p>The continued existence of sex, despite many the costs it entails, still lacks an adequate explanation, as previous studies demonstrated that the effects of sex are environment-dependent: sex enhances the rate of adaptation in changing environments, but the benefits level off in benign conditions. To the best of our knowledge, the potential impact of different patterns of environmental change on the magnitude of these benefits received less attention in theoretical studies. In this paper, we begin to explore this issue by examining the effect of the rate of environmental deterioration (negatively correlated with population survival rate), on the benefits of sex.</p> <p>To investigate the interplay of sex and the rate of environmental deterioration, we carried out a long-term selection experiment with a unicellular alga (<em>Chlamydomonas</em> <em>reinhardtii</em>), by manipulating mode of reproduction (asexual, facultative or obligate sexual) and the rate of environmental deterioration (an increase of salt concentration). We monitored both the population size and extinction dynamics.</p> <p>The results revealed that the relative advantage of sex increased at the intermediate rate and plateaued at the highest rate of environmental deterioration. Obligate sexual populations had the slowest extinction rate under the intermediate rate of environmental deterioration, while facultative sexuality was favoured under the high rate-treatment.</p> <p>To the best of our knowledge, our study is the first to demonstrate that the interplay of sex and the rate of environmental deterioration affects the probability of survival, which indicates that mode of reproduction may be an important determinant of survival of the anthropogenic-induced environmental change.</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.