Find research datasets worth reusing

Molecular dynamics dataset of barnase-barstar

This dataset contains all-atom molecular dynamics trajectories of barnase with its inhibitor barstar. All details regarding the molecular dynamics setup are given in reference [1]. The dataset consists of three parts and comes with a time step of 1 ns. amber-adaptive.tar: adaptive MD trajectories using Amber ff99SB. Cumulative length of about 0.3 ms. amber-gpugrid,.tar: longer simulations computed on GPUgrid, using Amber ff99SB. Cumulative length of about 1.7 ms. charmm-adaptive.tar: adaptive MD trajectories using CHARMM36. Cumulative length of about 0.5 ms. [1] Plattner, N.; Doerr, S.; Fabritiis, G. D.; Noé, F. Complete Protein–Protein Association Kinetics in Atomic Detail Revealed by Molecular Dynamics Simulations and Markov Modelling. Nature Chemistry 2017, 9 (10), 1005. <a href="https://doi.org/10.1038/nchem.2785">https://doi.org/10.1038/nchem.2785</a>.

opencc-by-4.0Jul 2022View details →

Zr–O Ab Initio Training Data Created by Molecular Dynamics, Contour Exploration, and Dimer Searches

These density functional theory calculations span a diverse set of structures in the Zr–O system which was used as machine-learned interatomic potential (MLIP) training data. This data set was used to benchmark different structural evolution methods (molecular dynamics, contour exploration, and dimer searches) for the quality and accuracy of MLIPs trained on them. The data is provided in the .traj format from ASE. Along with data set used in our publication, we provide a large set of extra unused data and a small Python script example for parsing the data set. The set contains 120,068 structures which contain a total of 3,154,158 atoms. For more details, please see our paper: Michael J Waters and James M Rondinelli,  J. Phys.: Condens. Matter 34 385901(2022) (<a href="https://dx.doi.org/10.1088/1361-648X/ac7f73">https://dx.doi.org/10.1088/1361-648X/ac7f73</a>)

Data used in the study: "The impact of landfast sea ice buttressing on ice dynamic speedup in the Larsen-B Embayment, Antarctica" by Surawy-Stepney et al, 2023.

Calving front and sea ice front positions, mean speed and speed trend (pre and post sea ice evacuation) maps, timeseries of ice speed shown on Hektoria, Green, Evans, Crane Glaciers, freeboard and associated uncertainty point data over the Larsen-B Embayment, maps of thickness and bed topography used in the model simulations, basal melt rates over the Scar Inlet, and shapefiles used for the extraction of speed, modelled speed and sensitivity data.

Dataset for the paper: Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers

Dataset This dataset contains the input and output examples used in the publication described below. The hyperspectral folder contains the first example and use case. The spatiotemporal folder contains the second example use case. Contents data/ ├── hyperspectral │   ├── VeloxTest-Membranes.emd │   └── example_output │       ├── simulator-0-VeloxTest-Membranes.emd │       ├── simulator-0-VeloxTest-Membranes.json │       └── simulator-0-VeloxTest-Membranes.png └── spatiotemporal     ├── 2023081040-700kx MultiFrams 991ms 600F Counting & FFI mode Falcon 700 kx 1819.emd     ├── best-yolo.pt     └── example_output         ├── prediction-simulator-17-2023081040-700kx MultiFrams 991ms 600F Counting & FFI mode Falcon 700 kx 1819.mp4         ├── simulator-17-2023081040-700kx MultiFrams 991ms 600F Counting & FFI mode Falcon 700 kx 1819.emd         ├── simulator-17-2023081040-700kx MultiFrams 991ms 600F Counting & FFI mode Falcon 700 kx 1819.json         └── simulator-17-2023081040-700kx MultiFrams 991ms 600F Counting & FFI mode Falcon 700 kx 1819.mp4   Source Code Our code is hosted on GitHub at the following link: <a href="https://github.com/ramanathanlab/PicoProbeDataFlow/tree/main">https://github.com/ramanathanlab/PicoProbeDataFlow/tree/main</a> Paper Name Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers Paper Abstract The Dynamic PicoProbe at Argonne National Laboratory is undergoing upgrades that will enable it to produce up to 100s of GB of data per day. While this data is highly important for both fundamental science and industrial applications, there is currently limited on-site infrastructure to handle these high-volume data streams. We address this problem by providing a software architecture capable of supporting large-scale data transfers to the neighboring supercomputers at the Argonne Leadership Computing Facility. To prepare for future scientific workflows, we implement two instructive use cases for hyperspectral and spatiotemporal datasets, which include: (i) off-site data transfer, (ii) machine learning/artificial intelligence and traditional data analysis approaches, and (iii) automatic metadata extraction and cataloging of experimental results. This infrastructure supports expected workloads and also provides domain scientists the ability to reinterrogate data from past experiments to yield additional scientific value and derive new insights.

opencc-by-4.0Jun 2021View details →

Data set used in article: Model Predictive Control for Wake Redirection in Wind Farms: a Koopman Dynamic Mode Decomposition Approach

Step-wise yaw deflection in 2 wind turbines in SOWFA. More information in the article.

Fig. 3 in Canopy isotopic investigation reveals different water uptake dynamics of maples and oaks

Fig. 3. Leaf level measurements of assimilation (A), stomatal conductance (gs), and transpiration (T) of maples and oaks. Species were compared using a one-way ANOVA, significance was set to 0.05 and denoted using the letters placed above the box plots. The right hand panels are frequency distribution plots of measured A, gs, and T for maples and oaks on DOY 243, 248, 250, 269, and 271 of 2017.

Fig. 4. A in Canopy isotopic investigation reveals different water uptake dynamics of maples and oaks

Fig. 4. A diagram summarizing the soil water isotope gradient and water source utilization for maples and oaks during the study period. Arrow size indicates the relative contribution of each soil water pool to the isotopic composition of canopy transpiration.

Fig. 2 in Canopy isotopic investigation reveals different water uptake dynamics of maples and oaks

Fig. 2. Fluctuations in vapor pressure deficit (VPD), soil moisture (soil moisture), and transpiration isotope signatures (δT) for maples (δTm) and oaks (δTo) displayed with precipitation amounts for each day of the study period (2017). Error bars shown are 1 standard deviation of the mean.

Fig. 1 in Canopy isotopic investigation reveals different water uptake dynamics of maples and oaks

Fig. 1. Graphical representation (A) and field photos (B–D) of the equipment used to measure the stable isotopic composition of plant transpiration. The labeled items in panel A are as follows: 1. Triple water vapor isotope analyzer, 2. External pump, 3. Leaf chamber, 4. Flow path of air in the system. For more details, please reference section 4.

opennotspecifiedJun 2020View details →

Fig. 5 in Study of two isoforms of lipoxygenase by kinetic assays, docking and molecular dynamics of a specialised metabolite isolated from the aerial portion of Lithrea caustica (Anacardiaceae) and its synthetic analogs

Fig. 5. Active site of molecular dynamics between 3-pentadecylcatechol (2) (A), (Z)-3-(pentadec-10′-enyl)-catechol (1) (B), and arachidonic acid with 5-hLOX and fluctuation of catechol distances during simulation time (10 ns).

opencc-by-4.0Jun 2023View details →

Data set for Dynamic Service Restoration of Distribution Networks with Volt-Var Devices, Distributed Energy Resources, and Energy Storage Systems

Data for three power distribution systems are presented in this document. The first system consists of 53 nodes and 61 branches. The second is composed of 217 nodes and 219 branches. Finally, the third system consists of 404 nodes and 430 branches. Both distribution systems offer extensive applications in problems related to multi-time service restoration, Volt/Var devices, and distributed energy resource operation.

Chiral-Induced Spin Selectivity in Photo-Induced Electron Transfer: investigating charge and spin dynamics in a master equation framework. Open data set

Data supporting the original figures 2, 3, 4 and 5 of the related publication.

opencc-zeroAug 2023View details →

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Meta-model for Patagonian grass steppe dynamics - library of transition matrices for steppe dynamics under sheep grazing

One of the central problems in ecology is how to scale from small-scale observations and experiments to large-scale patterns and processes. One approach to such upscaling is to use dynamic simulation models, but their application to large scales relevant for management is limited by computational costs, and their outputs are difficult to analyse without a systematic strategy. Our general objective is to propose such a strategy. The idea is to approximate the dynamics of detailed simulation models through a set of states, external drivers, and transition matrices, and then use Markov chain and network analysis of the resulting transition matrices to gain insights into the dynamics of the underlying detailed model. We used the individual-based model COIRON, which simulates the dynamics of semiarid grass steppes in Patagonia (Argentina) under alternative grazing management, as example. Our specific objectives are to identify pathways of degradation and rehabilitation, as well as critical grazing thresholds and early-warning vegetation states to guide sustainable grazing management in these steppes. Our results indicate nonlinear effects of stocking rate and grazing season on steppe dynamics. Markov chain analysis suggests benefits of seasonal over continuous grazing at intermediate stocking rates, and network analysis of recovery and degradation trajectories shows that intermediate stocking rates maximize differences between grazing seasons. Finally, our analysis identified specific vegetation states as early warning signals that indicate a high risk of irreversible vegetation changes. Patagonian grass steppes should ideally be managed with multi-paddock grazing at moderate stocking rates around 0.5 sheep·ha-1. The transition matrices summarize the relevant key features of the detailed model for larger scales, and applying Markov and network theory provides a systematic strategy to analyse its dynamics to respond to biological questions, both are often difficult to obtain by direct analysis of the detailed model.

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Discordant spatio-temporal dynamics of functional and phylogenetic diversity of rotiferan communities exposed to aquaculture effluent

The growth of the human population brought about the global intensification of aquacultural production, and aquaculture became the fastest growing animal husbandry sector. Effluent from aquaculture is an anthropogenic environmental burden, containing organic matter, nutrients, and suspended solids that affect water quality, especially in water bodies of high biodiversity and conservation value. Water quality assessment often relies on bioindicators, analysing changes in taxonomic diversity of various freshwater organismal groups. Stepping beyond taxon diversity, we used functional and phylogenetic diversities of rotifers to identify factors affecting their community organization in response to an aquaculture effluent gradient in the largest oxbow lake in the Carpathian Basin, Hungary. Sampling was carried out three times per season at five points along a 3.5 km section of the oxbow lake, including the point of effluent inflow. We used eight traits to evaluate functional diversity: body size, trophi type, feeding mode, protection type, body wall type, corona type, habitat preference, and tolerance level. Functional and phylogenetic distances among the 24 species identified indicated trait conservatism. Rotiferan diversity increased with increasing distance from the point of influx in spring and summer. Among the factors affecting community organization in spring and summer, we find examples of environmental filtering, while in autumn the role of biotic interaction is more frequent. Under nutrient-rich conditions in spring and summer, organisms belonging to the same functional group were dominant, while under oligotrophic conditions more diverse but less abundant groups were present. Considering functional and phylogenetic traits allowed us to identify organising forces of rotifer communities in the largest oxbow lake of the Hungarian Lowland.

opencc-zeroAug 2023View details →

opencc-by-4.0Sep 2023View details →

Molecular dynamics dataset of Trypsin-Benzamidine

This dataset contains all-atom molecular dynamics trajectories of Trypsin-Benzamidine. All details regarding the molecular dynamics setup are given in references [1, 2]. The dataset consists of two parts and comes with a time step of 100 ps. long-trajs.tar: cumulative of 100 µs of MD data in trajectories of 48 x 2 µs and 4 x 1 µs. Generated and used in [1]. gpugrid-trajs.tar: cumulative of 49.5 µs of MD data in trajectories of 495 x 100 ns. Generated for [2] and used in [1, 2]. [1] Plattner, N.; Noé, F. Protein Conformational Plasticity and Complex Ligand-Binding Kinetics Explored by Atomistic Simulations and Markov Models. Nature Communications 2015, 6, 7653. <a href="https://doi.org/10.1038/ncomms8653">https://doi.org/10.1038/ncomms8653</a>.  [2] Buch, I.; Giorgino, T.; De Fabritiis, G. Complete Reconstruction of an Enzyme-Inhibitor Binding Process by Molecular Dynamics Simulations. Proc. Natl. Acad. Sci. U.S.A. 2011, 108 (25), 10184–10189. <a href="https://doi.org/10.1073/pnas.1103547108">https://doi.org/10.1073/pnas.1103547108</a>.

Research data supporting "Dynamic Local Structure in Caesium Lead Iodide: Spatial Correlation and Transient Domains"

This is research data associated with "Dynamic Local Structure in Caesium Lead Iodide: Spatial Correlation and Transient Domains", accepted to Small.  The repository contains the trajectories which support the conclusions of the paper, the MLIP parameters, and some additional visualizations.

opencc-by-4.0Aug 2022View details →

Inverted S-wave velocity model for "Anomalous radial anisotropy and its implications for upper mantle dynamics beneath South China from multimode surface wave tomography"

# Instructions for the South China velocity model dataset from multi-mode surface-wave inversion.   1. The detailas can be found at the paper: Tang Q, Sun W, Yoshizawa K, et al. Anomalous radial anisotropy and its implications for upper mantle dynamics beneath South China from multimode surface wave tomography. Journal of Geophysical Research: Solid Earth, 2022, 127(8): e2021JB023485.   2. The relative SV-wave and SH-wave velocity models at different depths (from 0 to 300 km) are stored in the "data" foder. Each file follows the name convention: shear_{SV/SH}.{depth}.dat representing SV or SH velocity at a given depth.   3. In each velocity file, each line have three columns: longitude (deg) latitude (deg) relative_velocity (%)   4. The reference velocity can be found in the two files "SV_velocity" and "SH_velocity", depth and velocity.   5. The relative velocity is calculated from (absolute-reference)/reference*100%. Thus one can have the absolute velocity via absolute = relative * (1+relative/100).

opencc-by-4.0Dec 2022View details →

Dynamics and maintenance of categorical responses in primary auditory cortex during task engagement

Source data used in the paper: "Dynamics and maintenance of categorical responses in primary auditory cortex during task engagement" (BiorXiv, 2022), Chillale RK, Shamma S, Ostojic S, Boubenec Y. (doi: https://doi.org/10.1101/2022.12.19.521141) This data repository contains following folders:  - Pelardon (Ferret-P) and Timanoix(Ferret-T) as described in the figures of the paper - Each folder contains sub-folders 1. Spike_soring and 2. TrialStructures and Channels_all.mat and SessionsInfo_AllSess.mat - This data can used to generate figures in the paper using publicly available code (https://github.com/rupeshjnu/A1-Category)  - Spike_sorting folder contains recording sessions corresponding to SessionInfo_AllSess.mat file  with the session number mentioned in the code - Each Spike_sorting folder contains files - TrialStructure folders corresponds to behavioral files corresponding to the recording sessions

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Data for: The kinetic Ising model encapsulates essential dynamics of land pattern change

A land pattern change represents a globally significant trend with implications for the environment, climate, and societal well-being. While various methods have been developed to predict land change, our understanding of the underlying change processes remains inadequate. To address this issue, we investigate the suitability of the 2D kinetic Ising model (IM), an idealized model from statistical mechanics, for simulating land change dynamics. We test the IM on a variety of patterns, each with different focus land type. Specifically, we investigate four sites characterized by distinct patterns, presumably driven by different physical processes. Each site is observed on eight occasions between 2001 and 2019. Given the observed pattern at the time $t_i$ we find two parameters of the IM such that the model-evolved land pattern at $t_{i+1}$ resembles the observed land pattern at that time. The data supports simulating seven such transitions per site. Our findings indicate that the IM produces approximate matches to the observed patterns in terms of layout, composition, texture, and patch size distributions. Notably, the IM simulations even achieve a high degree of cell-scale pattern accuracy in two of the sites. Nevertheless, the IM has certain limitations, including its inability to model linear features, account for the formation of new large patches, and handle pattern shifts.

opencc-zeroSep 2023View details →