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917 results for “Theorie”
Dataset to "Hydrogen in tungsten trioxide by membrane photoemission and density functional theory modeling"
<p>Dataset to "Hydrogen in tungsten trioxide by membrane photoemission and density functional theory modeling" as published in Physical Review B, 103 (2021), 205304</p>
Functional traits and metacommunity theory reveal that habitat filtering and competition maintain bird diversity in a human shared landscape
<p>Human shared landscapes cover much of Earth, yet their conservation value is contested. This controversy may persist because previous studies have examined species diversity, rather than the processes through which such diversity is maintained. For example, a site exhibiting high diversity may not actually bolster populations if the diversity is only maintained through net immigration. Recent research has begun to isolate the processes that maintain metacommunities and develop functional trait methods to identify these processes. However, the processes underlying bird communities remain obscure. Here, we leverage metacommunity theory, functional trait partitioning, and a Bayesian multispecies abundance model to assess whether a shared landscape – woody perennial polyculture farms – bolsters bird diversity. Such farms grow multiple species of food-producing woody perennials together with vegetative groundcover. We surveyed birds and their <em> in situ </em> functional traits across the US Midwest in traditional agriculture, woody perennial polyculture, prairie, and woods. We found that woody perennial polycultures exhibited the highest bird diversity and were the most preferred by many species (including threatened ones). Moreover, our functional trait analysis suggests that this diversity is maintained through habitat filtering and competition, rather than merely immigration. Thus, shared landscapes can likely conserve birds by providing a distinct habitat. These results suggest that woody perennial polyculture farms offer substantial potential to support bird populations in the US Midwest. Our study demonstrates the utility of <em> in situ </em> functional trait partitioning within a Bayesian framework to unmask ecological processes and help assess the conservation value of landscapes.</p>
The theory of planned behavior and the prediction of pre-service biology teachers' intention to teach evolution
<p>We developed the project to identify and analyze variables that promote or hinder prospective biology teachers’ intentions to teach evolution. We adopted the model of the theory of planned behavior (TPB). We extended it to include additional variables described by teacher education research as key determinants of behavioral intention to teach evolution. We initially hypothesized that attitudes toward teaching evolution, subjective norms, perceived behavioral control, personal religious beliefs, perceived usefulness, and knowledge about evolution would determine a person’s behavioral intentions. To test the hypotheses, we developed an online questionnaire and conducted a quantitative cross-sectional survey in the field of teacher education. The data included information on <em>N</em> = 309 participants. Because we initially analyzed the data using a two-stage structural equation model (SEM), we uploaded two data files that were created in subprocesses of our original analyses (for more information, see the original publication). The dataset “data3” contains 77 variables and has missing values. Since we wanted to use complete data for the SEM, we trimmed the data set “data3” to include only the 67 variables necessary for the SEM, then applied an expectation-maximum (EM) algorithm with multiple imputations, and obtained the data set “data4”. </p>
StorAge Selection theory: a visual introduction
<p>This short video provides an introduction to the theory of StorAge Selection, or SAS. SAS is used to simulate material transport through complex systems, like rain water through a watershed and into a stream.</p> <p>The animations in this video were produced using mesas.py: https://github.com/charman2/mesas/</p>
Data for Survival probabilities of atmospheric particles: comparison based on theory, cluster population simulations, and observations in Beijing
<p>Data for<em> Survival probabilities of atmospheric particles: comparison based on theory, cluster population simulations, and observations in Beijing </em>(https://doi.org/10.5194/acp-2022-484)</p> <p>Contact Santeri Tuovinen (santeri.tuovinen@helsinki.fi) for more details.</p>
Dataset for "Solving deep-learning density-functional theory via variational autoencoder"
<p>The dataset contains the ground state energies, the ground state density profiles, and the external potentials of a 3D single particle system with a Gaussian-like external potential.<br>The number of grid points for each dimension is \(N_g=18\), the linear length of the box is \(L=a_0\) with \(a_0\) the unit of length. The unit of energy is \(E_0=\frac{ \hbar^2}{(m a_0^2)}\).</p> <p> </p> <p> </p> <p>The dataset is zip file of a Python npz file with the following keys:</p> <p>- "density" that corresponds to the ground state density profile.<br>- "potential" is the external potential.<br>-"energy" is the ground state energy.</p> <p><br>The number of instances is 36000. </p> <p>-3D_gaussian.zip -> 3D_gaussian.npz</p> <p> a dictionary with three keys -density, potential, energy-.<br> The dimension of both potential and density is \([N_d,N_g,N_g,N_g]\).<br> The shape of energy is \([N_d]\).<br> \(N_d=36000\)</p> <p>-3D_gaussian_transfer_test_1.npz</p> <p> a dictionary with three keys -density, potential, energy-.<br> The dimension of both potential and density is \([N_d,N_g,N_g,N_g]\).<br> The shape of energy is \([N_d]\).<br> \(N_d=500\)</p> <p>-3D_gaussian_transfer_test_2.npz</p> <p> a dictionary with three keys -density, potential, energy-.<br> The dimension of both potential and density is \([N_d,N_g,N_g,N_g]\).<br> The shape of energy is \([N_d]\).<br> \(N_d=500\)</p>
Microscopic understanding of NMR signals by dynamic mean-field theory for spins
<p>Data collection for several plots of the article <a href="https://doi.org/10.1016/j.ssnmr.2024.101936">Microscopic understanding of NMR signals by dynamic mean-field theory for spins</a>. Each hdf5-file contains one or several datasets of a specific figure. The datasets are described by the attribute "description".</p>
AI Tool Use and Adoption in Software Development by Individuals and Organizations: A Grounded Theory Study
<div> <p>This data represents four artifacts from our research in studying what impacts AI adoption and use in SE. It includes our interview questions, the codebook with example quotes, survey questions, and table with the code to category generation.</p> <p>This page includes supplementary materials associated with our paper entitled "<span>AI Tool Use and Adoption in Software Development by </span><span>Individuals and Organizations: A Grounded Theory Study</span>".</p> </div>
Density functional theory calculations of 1D hybrid nanoobjects composed of alternating polycyclic hydrocarbon regions and double carbon chains
<p>It has been proposed recently based on molecular dynamics simulations that electron irradiation of graphene nanoribbons of alternating width can lead to creation of 1D hybrid nanoobjects composed of alternating double carbon chains and polycyclic hydrocarbon regions [1]. We have performed density functional theory calculations of such 1D hybrid nanoobjects using Quantum ESPRESSO [2]. Semi-local exchange and correlation functional of Perdew, Burke and Ernzerhof [3] and screened exchange hybrid density functional of Heyd, Scuseria and Ernzerhof [4] were used. The dependences of structure, magnetic and electronic properies on the length of chains and type of the polycyclic hydrocarbon region were studied.</p> <p>I.V.L acknowledges the IKUR HPC project "First-principles simulations of complex condensed matter in exascale computers" funded by MCIN and by the European Union NextGenerationEU/PRTR-C17.I1, as well as by the Department of Education of the Basque Government through the collaboration agreement with nanoGUNE within the framework of the IKUR Strategy, computer resources at MareNostrum and the technical support provided by Barcelona Supercomputing Center (RES grant nos. FI-2022-1-0023, FI-2022-2-0035, FI-2022-3-0048 and FI-2023-1-0037). A.M.P., and Y.E.L. acknowledge the support by the Russian Science Foundation grant No. 23-42-10010, https://rscf.ru/en/project/23-42-10010/. S.A.V. and N.A.P. acknowledge support by the Belarusian Republican Foundation for Fundamental Research (Grant No. F23RNF-049) and by the Belarusian National Research Program "Convergence-2025".</p> <p>[1] A. S. Sinitsa, I. V. Lebedeva, Y. G. Polynskaya, D. G. de Oteyza, S. V. Ratkevich, A. A. Knizhnik, A. M. Popov, N. A. Poklonski, and Y. E. Lozovik, “Transformation of a graphene nanoribbon into a hybrid 1D nanoobject with alternating double chains and polycyclic regions,” Phys. Chem. Chem. Phys. 23, 425–441 (2021).</p> <p>[2] P. Giannozzi et al., “Advanced capabilities for materials modelling with Quantum ESPRESSO,” J. Phys.: Condens. Matter 29, 465901 (2017).</p> <p>[3] J. P. Perdew, K. Burke, and M. Ernzerhof, “Generalized gradient approximation made simple,” Phys. Rev. Lett. 77, 3865–3868 (1996).</p> <p>[4] J. Heyd, G. E. Scuseria, and M. Ernzerhof, “Hybrid functionals based on a screened Coulomb potential,” J. Chem. Phys. 118, 8207–8215 (2003).</p>
Understanding Electrochemical Reversibility using Density Functional Theory: Bridging Theoretical Scheme of Squares and Experimental Cyclic Voltammetry
<p>#<strong> Scheme of Squares</strong></p> <p>## <strong>Overview</strong></p> <p>The `SchemeOfSquares.tar` archive contains essential data and examples related to our research on redox reactions. The contents are organized into two primary subfolders: `datasets` and `examples`.</p> <p>##<strong> Getting Started</strong></p> <p>### <em><strong>Extracting the Archive</strong></em></p> <p>To extract the contents of the `SchemeOfSquares.tar` file, use the following command in a Linux environment:</p> <p>```sh<br>tar -xvf SchemeOfSquares.tar<br>```</p> <p>### <strong><em>Directory Structure</em></strong></p> <p>After extracting, you will find the following structure:</p> <p>- **datasets/**<br> - **ET/**: Contains Gaussian input and output files for electron transfer (ET) redox reactions.<br> - **PET/**: Contains Gaussian input and output files for proton-coupled electron transfer (PET) redox reactions.<br> <br>- **examples/**: Includes sample cases discussed in the main paper, along with the corresponding scaling code.</p> <p>## <strong>Details</strong></p> <p>### <em><strong>Datasets</strong></em></p> <p>- **ET Subfolder**: Houses all the data files related to electron transfer reactions. Each file here represents a specific reaction and contains Gaussian input and output data.<br>- **PET Subfolder**: Contains data files for proton-coupled electron transfer reactions, similarly structured with Gaussian input and output data.</p> <p>### <em><strong>Examples</strong></em></p> <p>- The `examples` folder provides illustrative samples that were elaborated upon in the main research paper. This includes the scaling code necessary for replicating the results.</p> <p>## <strong>References</strong></p> <p>For a comprehensive understanding of the data and examples provided, please refer to the main paper associated with this repository.</p> <p>## <strong>Contact</strong></p> <p>For any questions or further information, please contact Amir Mahdian / Arsalan Hahsemi at firstname.lastname@aalto.fi.</p>
Constraining the dense matter equation of state with new NICER mass-radius measurements and new chiral effective field theory constraints: prior and posterior samples and scripts for generating plots
<p>Full reproduction package accompanying the paper: <em>Constraining the dense matter equation of state with new NICER mass-radius measurements and </em><em>new chiral effective field theory inputs</em></p> <p> </p> <p><em>*Note, the changes made from version to version are made visible in the CHANGELOG.rst file</em></p>
Figure 4. Main elements of a face, according to the feature-based processing theories-Gestalt Processing in Human-Robot Interaction: A Novel Account for Autism Research
<p>In 1980 Peter Thompson proposed a new experimental paradigm for investigation of<br> perception, called “face thatcherization” (also named “Thomson illusion”) (Thompson, 1980).<br> Imagine that the following face, depicted in figure 4, is a photo of the then UK Prime Minister<br> Margaret Thatcher.</p>
Figure 1.Flowchart of the CoDOA.-Realizing an Optimization Approach Inspired from Piaget's Theory on Cognitive Development
<p>The objective of this paper is to introduce an artificial intelligence based optimization<br> approach, which is inspired from Piaget’s theory on cognitive development. The approach has been<br> designed according to essential processes that an individual may experience while learning<br> something new or improving his / her knowledge. These processes are associated with the Piaget’s<br> ideas on an individual’s cognitive development. The approach expressed in this paper is a simple<br> algorithm employing swarm intelligence oriented tasks in order to overcome single-objective<br> optimization problems. For evaluating effectiveness of this early version of the algorithm, test<br> operations have been done via some benchmark functions. The obtained results show that the<br> approach / algorithm can be an alternative to the literature in terms of single-objective optimization.<br> The authors have suggested the name: Cognitive Development Optimization Algorithm (CoDOA)<br> for the related intelligent optimization approach.</p>
Data of the PhD thesis "Merge-and-Shrink Abstractions for Classical Planning: Theory, Strategies, and Implementation"
<p>This data set contains raw data and parsed data of all experiments [1] run for the PhD thesis. They were generated using lab (see https://doi.org/10.5281/zenodo.399255).</p> <p>The raw data files (sievers-phd2017-raw-data-part*.tar.gz) contain a subdirectory for each experiment, each containing a subdirectory for each planner run of the experiment, distributed over the directories runs-*. For each run, there are the input PDDL files, domain.pddl and problem.pddl, the compressed output as generated by the translator component of Fast Downward (output.sas.xz), the run log file "run.log" (stdout), possibly also a run error file "run.err" (stderr), and the run script "run" used to start the experiment. The latter cannot be directly used, however, because the directory containing source code and build (compiled object files) have been removed for space reasons. The code is publicly available under https://doi.org/10.5281/zenodo.1163381. The (lab) scripts for parsing run.log are also available in the main directory of each experiment. All other scripts and a corresponding lab version are available on request.</p> <p>For each raw data experiment, the parsed data file (sievers-phd2017-parsed-data.tar.gz) also contains a directory of the same name, with "-eval" appended. It contains a single file called "properties" that combines all of the experiment's parsed data (which can be and was generated from the raw data using lab and the parser scripts). They are in the json format and can be used for easy manipulation of the data. The directories with the prefix "paper-" and "talk-" are combinations of other directories (using the "fetch" mechanism of lab). It is recommended to use these, because due to technical errors, the original eval directories do not contain all runs of all planners (to be more precise: they contain all runs, but a subset of the planner have not been started in these experiments for technical errors and thus considered not solving the task). The missing ones have been run separately, see the directories with "missing-runs" in their name. This is also the reason some of these directories ("paper-", "talk-") contain files named "old-properties" and "fixed-properties" besides the actual "properties". "old-properties" are those with missing/faulty runs, "fixed-properties" are as "old-properties", however with the data of faulty runs removed, and "properties" are as "fixed-properties", however with the addition of the fixed missing runs (in fact, these always contain *all* fixed missing runs of all experiments, for technical reasons).</p> <p>The file sievers-phd2017-parsed-data-all-and-random-merge-strategies.tar.gz contains parsed data of earlier experiments (see [1]), for which no raw data has been archived. The directories contain properties files in the json format.</p> <p>[1] except raw data for the parsed data "sota-symba-spmas-eval" (which in the meantime was added to a separate data set available under https://doi.org/10.5281/zenodo.1189912) and all re-used experiments from the paper "An Analysis of Merge Strategies for Merge-and-Shrink Heuristics" (Silvan Sievers, Martin Wehrle and Malte Helmert, ICAPS 2016), for which the raw data was too large to be archived.</p>
Equation-of-Motion Coupled-Cluster Theory based on the 4-component Dirac--Coulomb(--Gaunt) Hamiltonian. Energies for single electron detachment, attachment and electronically excited states: Dataset
<p>This dataset collects the unprocessed (= outputs from calculations) and processed (= outputs from fits for obtaining spectroscopic constants) results discussed in the paper titled "Equation-of-Motion Coupled-Cluster Theory based on the 4-component Dirac--Coulomb(--Gaunt) Hamiltonian. Energies for single electron detachment, attachment and electronically excited states", by Avijit Shee, Trond Saue, Lucas Visscher and Andre Severo Pereira Gomes.</p>
Predictive simulations of ionization energies of solvated halide ions with relativistic embedded Equation of Motion Coupled-Cluster Theory: Dataset
<p>This dataset collects the unprocessed (= outputs from calculations) and processed (= plots, average values for ionization energies) results discussed in the paper titled "Predictive simulations of ionization energies of solvated halide ions with relativistic embedded Equation of Motion Coupled-Cluster Theory", by Yassine Bouchafra, Avijit Shee, Florent Réal, Valérie Vallet and André Severo Pereira Gomes.</p> <p>In each archive file there is a README explaining how to use the bundled scripts to process the data.</p>
Supplementary data for "Stability and flexibility of Heterometallic Formate Perovskites with the Dimethylammonium Cation: Pressure-induced Phase transitions and Density Functional Theory Calculations"
<p>Optimized structures for DMANaCr, DMAKCr and DMAZn.</p> <p>For each structure there is a zip-file containing the force constants used for the phonon calculation, the phonon frequencies at the gamma point, the calculated thermal properties and the phonon partial density of states.</p> <p>For further information see the associated paper.</p>
Density Functional Theory Calculations of Segregation Tendency of Cu and Zn in Al3Zr Dispersoid Particles
<p>The .zip archive contains data related to DFT calculations published in the paper:</p> <p>Dispersoid Composition in Zirconium Containing Al-Zn-Mg-Cu (AA7010) Aluminium Alloy<br> A.M. Cassell, J. D. Robson, C. P. Race, A. Eggeman, T. Hashimoto, M. Besel.</p> <p>Submitted to Acta Materialia.</p> <p>Archive contains a set of .txt files, each of which contains the total energies of a series of simulations along with several other output fields and descriptive fields.</p> <p>The Archive also contains a .ipynb Jupyter (Python) Notebook, which contains descriptions of the .txt files, the code required to import them and the analysis required to produce the figure in the published paper.</p>
Data and code for Nettle and Frankenhuis, 'The evolution of life history theory'
<p>Data and code for 'The evolution of life history theory: Bibliometric analysis of an interdisciplinary research area', by Daniel Nettle and Willem E Frankenhuis.</p> <p>Version of March 4 2019</p> <p>This archive contains the raw data (Web of Science records), plus VOS Viewer files and R code for performing the analyses and making the bibliometric maps.</p> <p>Please see 'Files read me.txt' for explanation of the different files.</p>
Fig. 5 in The Alvarez impact theory of mass extinction; limits to its applicability and the "great expectations syndrome"
Fig. 5. Evolving timing of the multi−ring Woodleigh impact structure, manifested in purported causal connection with the P–T and F–F mass extinctions, as a reflection of variously dated processes. Age constraints still range from post−Middle Devonian to pre−Early Jurassic, but the connection with the D–C global event seems to be most likely (Glikson et al. 2005).
ScienceDex guides
Understand access before you commit
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.