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308 results for “Dynamical system”
REMODEL. WP4. Vision-Based Perception. T4-2. Dynamic environment reconstruction. Data related to a paper presented at 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2021)
<p>Dataset with evaluation results of the paper "New Metrics for Industrial Depth Sensors Evaluation for Precise Robotic Applications", DOI <a href="https://doi.org/10.1109/IROS51168.2021.9636322">10.1109/IROS51168.2021.9636322</a></p>
Optimal Dynamic Service Restoration of Distribution Networks Considering Energy Storage System Data
<p>The power distribution system presented is composed with 53 node and 61 branches and can be employed in multi-time service restoration problem, islading operation and energy storage system optimal operation. The system was designed based on a 53 node system (available <a href="https://ieee-dataport.org/documents/optimal-service-restoration-active-distribution-networks-considering-microgrid-formation">here</a>). The dataset was modified to include 6 photovoltaic generation, 3 energy storage system and time-changing demand load nodes.</p>
Data for: Age structure eliminates the impact of coinfection on epidemic dynamics in a freshwater zooplankton system
<p>Parasites often coinfect host populations, and, by interacting within hosts, might change the trajectory of multi-parasite epidemics. However, host-parasite interactions often change with host age, raising the possibility that within-host interactions between parasites might also change, influencing the spread of disease. We measured how heterospecific parasites interacted within zooplankton hosts and how host age changed these interactions. We then parameterized an epidemiological model to explore how age-effects altered the impact of coinfection on epidemic dynamics. In our model, we found that in populations where epidemiologically relevant parameters did not change with age, the presence of a second parasite altered epidemic dynamics. In contrast, when parameters varied with host age (based on our empirical measures), there was no longer a difference in epidemic dynamics between singly and coinfected populations, indicating that variable age structure within a population eliminates the impact of coinfection on epidemic dynamics. Moreover, infection prevalence of both parasites was lower in populations where epidemiologically relevant parameters changed with age. Given that host-population age structure changes over time and space, these results indicate that age-effects are important for understanding epidemiological processes in coinfected systems and that studies focused on a single age group could yield inaccurate insights.</p>
Research data supporting: "Detecting dynamic domains and local fluctuations in complex molecular systems via timelapse neighbors shuffling"
<p>This repository contains the set of data shown in the paper "Detecting dynamic domains and local fluctuations in complex molecular systems via timelapse neighbors shuffling" published on PNAS (DOI: 10.1073/pnas.2300565120).</p>
Airflow dynamics and aeolian sand transport across a beach-climbing dune-clifftop dune system
<p>This study presents an analysis of wind flow and sediment transport from the beach, up a 50m high, long (130m), steep (mean slope 26°) climbing dune and across a 1.5 m high max, 85 m long and 17.5 m wide clifftop dune 30km south of Dakhla in Morocco, NW Africa during highly oblique incident wind conditions. Multiple 2D sonic and cup/vane anemometers and sand traps were utilised for measurements. Flow steering was significant on the upper climbing dune. Flow deceleration occurred near the dune toe, and topographic forcing of flow was considerable on the upper slopes of the climbing dune. Near-surface flow steadiness (CV<sub>U1</sub>, CV<sub>U0.25</sub>) on the climbing dune straight slope segment was low and constant The distance upslope over which the airflow reached the speed comparable to that on the beach increases as the incident wind speed increases. The greatest flow acceleration and speed-up was observed at the cliff edge reaching 250% at 1m height and 220% at 0.25m height for the lowest incident wind speed class (4-5 m/s). The sand transport rate declined from the beach to the climbing dune toe and lower slope, but at the uppermost section of the climbing dune was 4 times higher than at the beach for the 7-8m/s incident wind speed. Sand in aeolian transport was generally finer than surface sand with mean grain size increasing up the slope. A comparison of the sand transport data collected with sand transport models, and the effects of slope on aeolian transport are also examined.</p>
Susceptible and infectious states for both vector and host in a dynamic pathogen-vector-host system
<p>Deformed wing virus (DWV) is a resurgent insect pathogen of honey bees that is efficiently transmitted by vectors and through host social contact. Continual transmission of DWV between hosts and vectors is required to maintain the pathogen within the population, and this vector-host-pathogen system offers unique disease transmission dynamics for pathogen maintenance between vectors and a social host. In a series of experiments, we measured vector-vector, host-host and host-vector transmission routes and show how these maintain DWV in honey bee populations. We found co-infestations on shared hosts allowed for movement of DWV from mite to mite. Additionally, two social behaviors of the honey bee, trophallaxis and cannibalization of pupae, provide routes for horizontal transmission from bee to bee. Circulation of the virus solely amongst hosts through communicable modes provides a reservoir of DWV for naïve Varroa to acquire and subsequently vector the pathogen. Our findings illustrate the importance of community transmission between hosts and vector transmission. We use these results to highlight the key avenues used by DWV during maintenance and infection and point to similarities with a handful of other infectious diseases of zoonotic and medical importance.</p>
Host controls of within-host disease dynamics: insight from an invertebrate system
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Machine learning reveals dynamic controls of soil nitrous oxide (N2O) emissions from diverse long-term cropping systems
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Susceptible and infectious states for both vector and host in a dynamic pathogen-vector-host system
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Leak-resilient enzyme-free nucleic acid dynamical systems through shadow cancellation
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Data for: Age structure eliminates the impact of coinfection on epidemic dynamics in a freshwater zooplankton system
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Environmental drivers of biseasonal anthrax outbreak dynamics in two multi-host savanna systems
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Supplementary data for "Molecular dynamics study of confined water in the periclase-brucite system under conditions of reaction-induced fracturing"
<p>In this dataset you can find sample data from periclase and brucite simulations and python scripts that can be used to confirm the plots in the paper.</p> <ul> <li>"bruciteSimualtions" and "periclaseSimualtions" contains the simulations where the mineral in contact with water is either brucite or periclase. Within each of these two folders, there are two subfolders, "waterProperties" and "waterThickness". <ul> <li>The data in "waterProperties" is used to calculate water properties. Each folder inside "simulations" represent one simulation.</li> <li>The data in "waterThickness" is used to calculate the change in water film thickness with time under different conditions. The simulations are run for either 3 ns or 10 ns. Each folder inside "simulations_Xns" represent one simulation.</li> </ul> </li> <li>For each folder containing one simulations, we provide: <ul> <li>NAME.run: The input script</li> <li>NAME.data: The input data</li> <li>job.sh: Script to run the simulation</li> <li>log.lammps: Thermodynamic output from the simulation</li> <li>Note that the pressures given in the folder names and in the simulations are in atm, not MPa.</li> </ul> </li> </ul> <p> </p> <ul> <li>"bruciteSimulations" and "periclaseSimualtions" are in zip containers. In order to use them, please unzip them and leave the resulting folders in the same directory as this README file. </li> </ul> <p> </p> <ul> <li>The python scripts shows how to extract the relevant data from the lammps log files, which enables reproduction of the figures in the paper. See instructions below to use the scripts.</li> </ul> <p><br> Installation instructions to make the python plot scripts working, assuming you already have numpy and matplotlib:</p> <p>> pip3 install git+https://github.com/henriasv/regex-file-collector.git</p> <p>> pip3 install git+https://github.com/henriasv/lammps-logfile.git<br> </p> <p>If this does not work, please contact Marthe Grønlie Guren, m.g.guren@geo.uio.no</p>
Simple muscle-lever systems are not so simple: The need for dynamic analyses to predict lever mechanics that maximize speed
<p><span>Here we argue that quasi-static analyses are insufficient to predict the speed of an organism from its skeletal mechanics alone (i.e. lever arm mechanics). Using a musculoskeletal numerical model we specifically demonstrate that 1) a single lever morphology can produce a range of output velocities, and 2) a single output velocity can be produced by a drastically different set of lever morphologies. These two sets of simulations quantitatively demonstrate that it is incorrect to assume a one-to-one relationship between lever arm morphology and organism maximum velocity. We then use a statistical analysis to quantify what parameters are determining output velocity, and find that muscle physiology, geometry, and limb mass are all extremely important. Lastly we argue that the functional output of a simple lever is dependent on the dynamic interaction of two opposing factors: those decreasing velocity at low mechanical advantage (low torque and muscle work) and those decreasing velocity at high mechanical advantage (muscle force-velocity effects). These dynamic effects are not accounted for in static analyses and are inconsistent with a force-velocity tradeoff in lever systems.</span> <span>Therefore, we advocate for a dynamic, integrative approach that takes these factors into account when analyzing changes in skeletal levers.</span></p>
Data from: Long-term population dynamics of dreissenid mussels (Dreissena polymorpha and D. rostriformis): a cross-system analysis
Dreissenid mussels (including the zebra mussel Dreissena polymorpha and the quagga mussel D. rostriformis) are among the world's most notorious invasive species, with large and widespread ecological and economic effects. However, their long‐term population dynamics are poorly known, even though these dynamics are critical to determining impacts and effective management. We gathered and analyzed 67 long‐term (>10 yr) data sets on dreissenid populations from lakes and rivers across Europe and North America. We addressed five questions: (1) How do Dreissena populations change through time? (2) Specifically, do Dreissena populations decline substantially after an initial outbreak phase? (3) Do different measures of population performance (biomass or density of settled animals, veliger density, recruitment of young) follow the same patterns through time? (4) How do the numbers or biomass of zebra mussels or of both species combined change after the quagga mussel arrives? (5) How does body size change over time? We also considered whether current data on long‐term dynamics of Dreissena populations are adequate for science and management. Individual Dreissena populations showed a wide range of temporal dynamics, but we could detect only two general patterns that applied across many populations: (1) Populations of both species increased rapidly in the first 1–2 yr after appearance, and (2) quagga mussels appeared later than zebra mussels and usually quickly caused large declines in zebra mussel populations. We found little evidence that combined Dreissena populations declined over the long term. Different measures of population performance were not congruent; the temporal dynamics of one life stage or population attribute cannot generally be accurately inferred from the dynamics of another. We found no consistent patterns in the long‐term dynamics of body size. The long‐term dynamics of Dreissena populations probably are driven by the ecological characteristics (e.g., predation, nutrient inputs, water temperature) and their temporal changes at individual sites rather than following a generalized time course that applies across many sites. Existing long‐term data sets on dreissenid populations, although clearly valuable, are inadequate to meet research and management needs. Data sets could be improved by standardizing sampling designs and methods, routinely collecting more variables, and increasing support.
Data from: Age-structure and transient dynamics in epidemiological systems
Mathematical models of childhood diseases date back to the early twentieth century. In several cases, models that make the simplifying assumption of homogeneous time-dependent transmission rates give good agreement with data in the absence of secular trends in population demography or transmission. The prime example is afforded by the dynamics of measles in industrialized countries in the pre-vaccine era. Accurate description of the transient dynamics following the introduction of routine vaccination has proved more challenging, however. This is true even in the case of measles which has a well-understood natural history and an effective vaccine that confers long-lasting protection against infection. Here, to shed light on the causes of this problem, we demonstrate that, while the dynamics of homogeneous and age-structured models can be qualitatively similar in the absence of vaccination, they diverge subsequent to vaccine roll-out. In particular, we show that immunization induces changes in transmission rates, which in turn reshapes the age distribution of infection prevalence, which effectively modulates the amplitude of seasonality in such systems. To examine this phenomenon empirically, we fit transmission models to measles notification data from London that span the introduction of the vaccine. We find that a simple age-structured model provides a much better fit to the data than does a homogeneous model, especially in the transition period from the pre-vaccine to the vaccine era. Thus, we propose that age structure and heterogeneities in contact rates are critical features needed to accurately capture transient dynamics in the presence of secular trends.
Dataset of paper: Supervised and Dynamic Neuro-Fuzzy Systems to Classify Physiological Responses in Robot-Assisted Neurorehabilitation (PLOS One)
<p>The data set contains number of user, user's physiological signals (Pulse, SCL, SCR, Respiration rate, Skin temperature), Label, Difficulty level from relax to stress. Label is codified from 1 to 5 corresponding to the Difficulty level.</p>
Learning stochastic process-based models of dynamical systems from knowledge and data - Libraries, incomplete models and data
<p>The archive contains all libraries of domain knowledge, the incomplete models and the data used in the experiments described in the manuscript titled "Learning stochastic process-based models of dynamical systems from knowledge and data" pubilshed in BMC Systems Biology</p>
Research data supporting: "Non-trivial stimuli-responsive collective behaviours emerging from microscopic dynamic complexity in supramolecular polymer systems"
<p>Contains the relevant simulation data and input files. See "readme.txt" for information.</p>
Supplementary material for the article "The Crystal Cargo Provides a Chronicle of Pre-Caldera Dynamics in Mafic Volcanic Systems: Insights from Colli Albani"
<p>This repository contains the data and supplementary material associated with the manuscript: Ágreda-López M., Musu A., Jorgenson C., Sǎla M., Giordano G., Caricchi L., Stremtan C., Petrelli M. "<strong>The Crystal Cargo Provides a Chronicle of Pre-Caldera Dynamics in Mafic Volcanic Systems: Insights from Colli Albani</strong>".<em> S</em>ubmitted to the Journal<em> Bulletin of Volcanology.</em></p> <div> </div> <p> </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.