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917 results for “Theorie”
An information theory-based machine learning approach to detecting functionally conserved and coordinated protein dynamics
<p>The application of machine learning classification to the molecular dynamics of the functional states of protein allows for application of an information theoretic framework familiar to traditional bioinformatics. The functional states of proteins involving binding interactions with partners comprised of protein, DNA or small molecules can first be defined in a binary fashion (i.e. bound vs unbound), subsequently simulated in molecular dynamics software, and then employed as a comparative training set for a binary machine learning classifier capable of discerning the complex dynamical consequences of binding interaction. This learner can subsequently be deployed on new simulations of the functionally bound state to validate its ability to recognize the molecular motions that are supporting binding function. Regions of proteins with functionally conserved dynamics will induce significant local correlations in learning performance across independent validation runs. Through case studies of Rbp subunit 4/7 interaction in RNA Pol II and DNA-protein interactions of TATA binding protein, we demonstrate this method of detecting functionally conserved protein dynamics. We also demonstrate how Shannon information, relative entropy and mutual information can be applied to these binary classification states of dynamic simulations in order to compare dynamics and identify concerted motions involved in dynamic interactions across sites.</p>
Data and simulations files for the article "Quasinormal-mode perturbation theory for dissipative and dispersive optomechanics".
<p>Data and simulations files for the article "Quasinormal-mode perturbation theory for dissipative and dispersive optomechanics".</p>
Raw Data to "Density functional theory study of CO formation through reactions of polycyclic aromatic hydrocarbons with atomic oxygen (O(3P))"
<p>This data is a supplement to the publication <a href="https://doi.org/10.1016/j.fuel.2018.12.047">https://doi.org/10.1016/j.fuel.2018.12.047</a>. The data includes Turbomole input and output files. The calculations are performed using DFT/TPSSh-D3/TZVP method and Turbomole version 7.2. The equilibrium structures for the reactions of polyaromatics are named as following:<br> C<sub>X</sub>H<sub>Y</sub> (<strong>S1</strong>) + O -> C<sub>X</sub>H<sub>Y</sub>O (<strong>S2</strong>) -> C<sub>X</sub>H<sub>Y-1</sub>O (<strong>S3</strong>) + H (i) O addition and H abstraction<br> C<sub>X</sub>H<sub>Y-1</sub>O (<strong>S3</strong>) [-> <strong>S4</strong> -> <strong>S5</strong> ] -> CX-1HY-1 (<strong>S6</strong>) + CO (ii) Single, two, or three step CO elimination</p> <p>The transition state structures are named according to the naming of the corresponding reactant and product. For example, the transition state connecting the structure S3 to S5 is named as T35. Under some of the transition state directories, intrinsic reaction coordinate calculation output can be found under the directories named as "IRC".<br> <br> </p> <p><br> The LibreOffice Calc spreadsheet "SUPPINFO.ods" includes the activation and reaction energies to the reaction steps.</p>
Nonperturbative infrared finiteness in super-renormalisable scalar quantum field theory -- data release
<p>This submission contains the Markov-Chain Monte Carlo data required to reproduce central results of the paper "Nonperturbative infrared finiteness in super-renormalisable scalar quantum field theory" (<a href="https://arxiv.org/abs/2009.14768">https://arxiv.org/abs/2009.14768</a>). </p> <p>The Python code required to read and analyse the data can be found under https://github.com/andreasjuettner/Finite-Size-Scaling-Analysis (the relevant release is attached to 10.5281/zenodo.4290508).</p> <p>For any questions please get in touch: juettner@soton.ac.uk.</p>
Standard Model effective field theory global fit using electroweak data
<p>These are files that can be used to reproduce the fit results in 10.1007/JHEP09(2016)157 and arXiv:1610.01783<strong>.</strong></p> <p> </p>
Searchlight and bucket theory of mind (K. Popper)
<p>Drawing illustrating the bucket and the searchlight theories of mind as described by Karl Popper in <em>Objective Knowledge</em> (1972). The image does not appear in the book, but is based on it.</p>
Attentional Bias for Uncertain Cues of Shock in Human Fear Conditioning: Evidence for Attentional Learning Theory
<p>Eye tracking data and statistical analysis of:</p> <p>Koenig, S., Uengoer, M., & Lachnit, H. (2017). Attentional bias for uncertain cues of shock in human fear conditioning: Evidence for attentional learning theory. Frontiers in Human Neuroscience. doi: 10.3389/fnhum.2017.00266.</p> <p>Abstract: We conducted a human fear conditioning experiment in which three different color cues were followed by an aversive electric shock on 0, 50, and 100% of the trials, and thus induced low (L), partial (P), and high (H) shock expectancy respectively. The cues differed with respect to the strength of their shock association (L < P < H) and the uncertainty of their prediction (L < P > H). During conditioning we measured pupil dilation and ocular fixations to index differences in the attentional processing of the cues.<br> After conditioning, the shock-associated colors were introduced as irrelevant distracters during visual search for a shape target while shocks were no longer administered and we analyzed the cues’ potential to capture and hold overt attention automatically.<br> Our findings suggest that fear conditioning creates an automatic attention bias for the conditioned cues that depends on their correlation with the aversive outcome. This bias was exclusively linked to the strength of the cues’ shock association for the early<br> attentional processing of cues in the visual periphery, but additionally was influenced by the uncertainty of the shock prediction after participants fixated on the cues. These findings are in accord with attentional learning theories that formalize how associative learning shapes automatic attention.</p>
Data from: warming and top-down control of stage-structured prey: linking theory to patterns in natural systems
<p>Warming has broad and often nonlinear impacts on organismal physiology and traits, allowing it to impact species interactions like predation through a variety of pathways that may be difficult to predict. Predictions are commonly based on short-term experiments and models, and these studies often yield conflicting results depending on the environmental context, spatiotemporal scale, and the predator and prey species considered. Thus, the accuracy of predicted changes in interaction strength, and their importance to the broader ecosystems they take place in, remain unclear. Here, we attempted to link one such set of predictions generated using theory, modeling, and controlled experiments to patterns in the natural abundance of prey across a broad thermal gradient. To do so, we first predicted how warming will impact a stage-structured predator-prey interaction in riverine rock pools between Pantala spp. dragonfly nymph predators and Aedes atropalpus mosquito larval prey. We then described temperature variation across a set of hundreds of riverine rock pools (n = 775) and leveraged this natural gradient to look for evidence for or against our model's predictions. Our model's predictions suggested that warming should weaken predator control of mosquito larval prey by accelerating their development and shrinking the window of time that aquatic dragonfly nymphs could consume them in. This was consistent with data collected in rock pool ecosystems, where the negative effects of dragonfly nymph predators on mosquito larval abundance were weaker in warmer pools. Our findings provide additional evidence to substantiate our model-derived predictions, while emphasizing the importance of assessing similar predictions using natural gradients of temperature whenever possible.</p>
Perturbative effective field theory expansions for cosmological phase transitions, dataset
<p>This dataset is the work of Oliver Gould and Tuomas V.I. Tenkanen. It collects the numerical data from the paper <a href="https://arxiv.org/abs/2309.01672">"Perturbative effective field theory expansions for cosmological phase transitions"</a> (2023). It primarily contains data from perturbative calculations of the thermal evolution of the real-triplet extended Standard Model at two benchmark parameter points.</p><p>In addition, for comparison to the perturbative results, we have included data of the scalar quadratic condensates as a function of temperature from the lattice Monte-Carlo simulations of Lauri Niemi, Michael J. Ramsey-Musolf, Tuomas V.I. Tenkanen and David J. Weir, from the paper <a href="https://doi.org/10.1103/PhysRevLett.126.171802">"Thermodynamics of a Two-Step Electroweak Phase Transition"</a> (2020). We thank the authors for granting permission to reproduce this data here.</p><p>Everything is contained within the archive file <a href="https://zenodo.org/api/records/10353066/draft/files/triplet_two_step_data.tar.gz/content">triplet_two_step_data.tar.gz</a>, a tarball compressed with Gzip. For further details and for the context of this dataset, see the above papers. Details of the conventions used in the dataset can be found in the accompanying README.md file.</p>
Supplementary data and code for: Non-Abelian Hyperbolic Band Theory from Supercells
<p>This data and code collection contains all necessary code and data required to reproduce the results of the accompanied publication. To run the code contained in this collection GAP, the HyperCells package, Mathematica, the NCAlgebra (version >= 6.0) and the HyperBloch package are required. Please refer to the included Readme file and the links therein for more details.</p> <p>Changes: add NCAlgebra to list of dependencies.</p>
Costless renewable energy distribution model based on cooperative game theory for energy communities considering its members' active contributions
<p>This dataset was used in the case study of the following publication:</p> <p> - Luis Gomes, Zita Vale, "Costless renewable energy distribution model based on cooperative game theory for energy communities considering its members’ active contributions," Sustainable Cities and Society, Volume 101, 2024, 105060, ISSN 2210-6707, <a href="https://doi.org/10.1016/j.scs.2023.105060">https://doi.org/10.1016/j.scs.2023.105060</a> </p> <p><em>(if you used this dataset in your publications, please send us your information so we can add your publication to the list above)</em></p> <p> </p> <p>The dataset is composed by energy generation, consumption, and forecast (for generation, and for consumption) expressed in Wh. The data considers an energy community of 10 prosumers in 30 days.</p> <p>The dataset also has energy prices that have been collected from MIBEL (Iberian Electricity Market).</p> <p> </p> <p>We would be grateful if you could acknowledge the use of this dataset in your publications. Please use the Zenodo publication to cite this work.</p>
Lattice investigations of the chimera baryon spectrum in the Sp(4) gauge theory---Data Release
<p>This release contains the analysis workflow used to prepare the publication <a href="https://arxiv.org/abs/2311.14663" target="_blank" rel="noopener">Lattice investigations of the chimera baryon spectrum in the Sp(4) gauge theory</a>.</p> <p>A Python code for performing the analysis and generating the plots and tables is <a href="https://doi.org/10.5281/zenodo.10929539" target="_blank" rel="noopener">uploaded to Zenodo</a>. See the README therein for details on running the code.</p> <p>For details on the data formats, see the relevant README.md files.</p> <h2>Content of directories and files:</h2> <ul> <li>README.md: This contains general information on the content of the release.</li> <li>raw_data.zip: This compressed file contains all the raw data utilized in the research outlined in arXiv:2311.14663. These data were crucial in generating the results showcased in the paper.</li> <li><span>data.h5: An HDF5 file housing the correlators derived from the raw data through the processing code, <code>generate/transform_h5.py</code>.</span></li> <li><span>metadata.zip: This archive furnishes essential metadata such as ensemble information, fitting intervals, and smearing parameters crucial for extracting masses.</span></li> <li><span>F_meson.csv: Presents the fundamental meson masses extracted via the <code>analysis/analysis_F.py</code> script.</span></li> <li><span>AS_meson.csv: Presents the antisymmetric meson masses extracted via the <code>analysis/analysis_AS.py</code> script.</span></li> <li><span>CB_mass.csv: Presents the chimera baryon masses extracted via the <code>analysis/analysis_CB.py</code> script.</span></li> <li><span>FIT_mass.csv: Offers the AIC scan results conducted through the <code>analysis/analysis_AIC.py</code> script.</span></li> <li><span>FIT_cross_fixAS.csv and FIT_cross_fixF.csv: These files provide cross-check results computed by the</span> <span><code>analysis/analysis_cross.py</code> script, specifically for fixing antisymmetric and fundamental masses, respectively.</span></li> </ul>
Simulation and laboratory eddy current testing data - modelling compound defects via perturbation theory
<p>This dataset serves to fit and validate a perturbation approach to the modelling eddy current signals of compound defects. It was obtained during the AIFRI project (Artificial Intelligence for Rail Inspection). The simulation data was generated with the Faraday software by INTEGRATED Engineering Software, using its BEM Solver. The simulation data is supplied as csv. The laboratory data was gathered by Rainer Pohl in the eddy current laboratory of BAM, section 8.4. It is supplied in the DICONDE data format. The first frame of the pixel array in the DICONDE files corresponds to the real part and the second frame corresponds to the imaginary part of the signal. The data set is analyzed in an upcoming article.</p> <p><span> </span></p>
Data from: Metacommunity theory review and its application in community assembly of soil animals
<p>We were interested in community assembly of soil animals and performed a literature study to find out what is known about soil metacommunities. We aimed to study keywords co-occurrence relationships of scientific journal articles in the field of "metacommunity" research from 1992-2017 as a whole. We also investigated the co-occurrence of the top 20 most frequent keywords in five 5-year time periods.</p> <p> </p> <p> </p> <p>In September 2017 we searched the Web of Science with ‘metacommunity’ as the only keyword, and found 1226 English papers published in international journals between January 1992 and September 2017. And we exported these papers from Web of Science as a plain text file (.txt) with the option ‘Full Record and Cited References’, which is archived here. The text file thus contains full records and cited references (in a concise format, so without the titles of the cited papers), and each field is prefaced by a two-character field tag. Afterwards we used the software ‘Citespace’ to create Table 1 and Figure 2 in Guo et al. (2018). We created that Figure 2 using the following settings in Citespace: we choose the “co-occurrence” function and “keyword” as node types, then created keywords co-occurrence relationships (Figure 2). Next, we created lists of the top 20 keywords in different periods, which can reveal the research hotspots (Table 1). The method for extracting the top 20 most frequent keywords was as follows: We use the Web of Science database to retrieve scientific papers from 1992 to 2017, taking into account the relationship between citation and publication time. We calculated the percentage of 200 most cited papers published in each of the 5-year periods. To do so we followed the following steps:</p> <p>Step1: we selected the 200 most cited papers from the entire datset (1226 in the 1992-2017 period).</p> <p>Step 2: we calculated the percentage of those 200 papers published each 5-year period.</p> <p>Step 3: we also calculated an correction coefficient by taking, for each 5-year period, the number of top-200 most cited papers published in that period, and dividing that number by the total number of papers (out of the 1226 selected papers) published in that period.</p> <p>Step 4 Last, we calculate the real keyword frequency by multiplying the keyword frequency in specific 5-year periods with the correction coefficient.</p>
Treatise on Hearing: The Temporal Auditory Imaging Theory Inspired by Optics and Communication (Supplementary Audio Demo Files)
<p>Audio files that supplement "Treatise on Hearing: The Temporal Auditory Imaging Theory Inspired by Optics and Communication". Please refer to the manuscript (preprint) for additional details.</p>
Dataset for an application example of a unified theory for 3D Gear and Thread Metrology
<p>The evaluation of this dataset is presented in Stein et al. (2021) as an example for the advantages of the suggested novel approach. We propose a unified theory for the metrological treatment of helical machine elements such as cylindrical and conical gears, worms, and screw threads. The main idea is to introduce a universal 3D geometry model for threaded components that provides for distinct parameterization using a unique set of geometry parameters and that offers and a functional description of the transverse profile. Using modern 3D coordinate measuring technology, a holistic evaluation algorithm yields the actual geometry as the result of a high dimensional best-fit procedure and form deviations as corresponding residuals. All determinants and evaluation parameters can then be calculated from the set of actual geometry parameters. By applying certain constraints to the model to be fitted, the novel method can be reduced to the established 2D methods and hence meets demands for the comparison of the two procedures. The results of the novel approach have proven to be very stable and they enable the evaluation of areal measurements with no loss of information.</p>
Coevolutionary theory of hosts and parasites
<p>Host and parasite evolution are closely intertwined, with selection for adaptations and counter-adaptations forming a coevolutionary feedback loop. Coevolutionary dynamics are often difficult to intuit due to these feedbacks and are hard to demonstrate empirically in most systems. Theoretical models have therefore played a crucial role in shaping our understanding of host-parasite coevolution. Theoretical models vary widely in their assumptions, approaches and aims, and such variety makes it difficult, especially for non-theoreticians and those new to the field, to: (1) understand how model approaches relate to one another; (2) identify key modelling assumptions; (3) determine how model assumptions relate to biological systems and (4) reconcile the results of different models with contrasting assumptions. In this review, we identify important model features, highlight key results and predictions and describe how these pertain to model assumptions. We carry out a literature survey of theoretical studies published since the 1950s (n=219 papers) to support our analysis. We identify two particularly important features of models that tend to have a significant qualitative impact on the outcome of host-parasite coevolution: population dynamics and the genetic basis of infection. We also highlight the importance of other modelling features, such as stochasticity and whether time proceeds continuously or in discrete steps, that have received less attention but can drastically alter coevolutionary dynamics. We finish by summarising recent developments in the field, specifically the trend towards greater model complexity, and discuss likely future directions for research.</p>
A comparative analysis testing Werner's theory of complex life cycles
<p>A popular theoretical model for explaining the evolution of complex life cycles was provided by Earl Werner. The theory predicts the size at which an individual should switch stages to maximise growth rate relative to mortality rate across the life history. </p> <p>Werner's theory assumes that body size does not change during the transition from one phase to another (e.g. from larva to adult)—a key assumption that has not been tested systematically but could alter the predictions of the model. </p> <p>We quantified how growth rate and mass change across larval stages and metamorphosis for 105 species of fish, amphibians, insects, crustaceans and molluscs Across all taxonomic groups, we found support for Werner's assumption that growth rates are maintained or increase around transitions. We found that changes in growth and mass were greatest during metamorphosis, and change in growth correlated with development time. Importantly, most species either gained or lost mass when switching to a new stage—a direct contradiction of Werner's assumption. When we explored the consequences of energy loss and gain in a numerical model, we found that individuals should switch stages at a larger and smaller size, respectively, relative to what Werner's standard theory predicts.</p> <p>Our results suggest that while there is support for Werner's assumption regarding growth rates, mass changes profoundly alter the timing of transitions that are predicted to maximise fitness, and therefore the original model omits an important component that may contribute to the evolution of complex life cycles. Future studies should test for conditions that alter the costs of transitions, so that we can have a better understanding of how mass loss or gain affects fitness.</p>
Influence of conspiracy theories and distrust of community health volunteers on adherence to COVID-19 guidelines and vaccine uptake in Kenya
<p>This cross-sectional study collected data between 25 May –27 June 2021 n=447. It involved all registered community health volunteers (CHVs) who had participated in the COVID-19 vaccine hesitancy study. This data was collected as part of an Epidemic Ethics/WHO initiative that FCDO/Wellcome Grant 214711/Z/18/Z has supported. WHO’s specific grant number was 2020/1077878-0). The funders had no role in study design, data collection and analysis, decision to publish, or manuscript preparation. No authors received a salary from the funders.</p>
How nitrogen and phosphorus supply to nutrient-limited autotroph communities affects herbivore growth: testing stoichiometric and co-limitation theory across trophic levels
<p><span>Primary producer communities are often growth-limited by essential nutrients such as nitrogen (N) and phosphorus (P). The magnitude of </span><span>limitation and whether N, P, or both elements are limiting autotroph </span><span>growth depends on the supply and ratios of these essential nutrients. </span><span>Previous studies identified single, serial or co-limitation as predominant </span><span>limitation outcomes in autotroph communities by factorial nutrient </span><span>additions. Little is known about potential consequences of such scenarios </span><span>for herbivores and whether their growth is primarily affected by changes </span><span>in autotroph quantity or nutritional quality. We grew a community of </span><span>phytoplankton species differing in various food quality aspects in </span><span>experimental microcosms at varying N and P concentrations resulting in </span><span>three different N:P ratios. At carrying capacity, N, P, both nutrients or </span><span>none were added to reveal which nutrients were limiting. The nutrient supplied </span><span>communities were fed to the generalist herbivorous rotifer </span><span>Brachionus calyciflorus to investigate how changing phytoplankton </span><span>biomass and community composition affect herbivore abundance. We </span><span>found phytoplankton being growth-limited either by N alone (single </span><span>limitation) or serially, i.e. primarily by N and secondarily by P, altering </span><span>available food quantity for rotifers. Rotifer growth showed a different </span><span>response pattern compared to phytoplankton, suggesting that apart from </span><span>food quantity food quality aspects played a substantial role in the </span><span>transfer from primary to secondary production. The combined addition of </span><span>N and P to phytoplankton had generally a positive effect on herbivore </span><span>growth, whereas adding non-limiting nutrients had a rather detrimental </span><span>effect probably due to stoichiometrically imbalanced food in terms of </span><span>nutrient excess. Our experiment shows that adding various nutrients to </span><span>primary producer communities will not always lead to increased </span><span>autotroph and herbivore growth, and that differences between autotroph </span><span>and herbivore responses under co-limiting conditions can be partly well </span><span>explained by concepts of ecological stoichiometry theory.</span></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.