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52 results for “matrix model”
Non-perturbative phase structure of the bosonic BMN matrix model --- data release
<p>This HDF5 file collects data and analysis results for non-perturbative lattice calculations investigating the phase structure of the bosonic part of the Berenstein--Maldacena--Nastase matrix model. See the README for further information.</p>
Trained Models from "General Cross-Architecture Distillation of Pretrained Language Models into Matrix Embeddings"
<p>Trained models from the paper:</p> <p>Lukas Galke, Isabell Cuber, Christoph Meyer, Henrik Ferdinand Noelscher, Angelina Sonderecker, and Ansgar Scherp: <strong>General Cross-Architecture Distillation of Pretrained Language Models into Matrix Embeddings</strong>, in: <em>International Joint Conference on Neural Networks (IJCNN), </em>2022.</p> <ul> <li>File seq2mat_hybrid_bidirectional_sbertlike-100p-bsz512 holds the model from pretraining</li> <li>File ws2020_transformer_final_models holds the fine-tuned models for each task of the GLUE benchmark</li> </ul>
SI Figure 1: Dispersion values (a boxplot using distance to centroids based on Bray Curtis distance matrix) of external and internal bacterial microbiome composition for different hosts. In a mixed linear model, microinvertebrates did not significantly impact dispersion (P=0.44), but microbiome type did (P=0.03). Pairwise contrasts show that while external microbiomes of P. murrayi and Tardigrada are more variable than their internal microbiomes, E. antarcticus external and internal microbiomes are equally variable. in External and internal microbiomes of Antarctic nematodes are distinct, but more similar to each other than the surrounding environment
SI Figure 1: Dispersion values (a boxplot using distance to centroids based on Bray Curtis distance matrix) of external and internal bacterial microbiome composition for different hosts. In a mixed linear model, microinvertebrates did not significantly impact dispersion (P=0.44), but microbiome type did (P=0.03). Pairwise contrasts show that while external microbiomes of P. murrayi and Tardigrada are more variable than their internal microbiomes, E. antarcticus external and internal microbiomes are equally variable.
Figure 1. Markov Chain Model&Figure 2. Transition matrix-Study of a Random Navigation on the Web Using Software Simulation
<p>For a good simulation it is very important to find methods for<br> navigating through the web (Levene and Wheeldon, 2004). John Kemeny and Laurie Snell have<br> proposed the use of Markov models for web simulations (Kemeny and Snell, 1960). Cadez et al. (2000)<br> used Markov models for classifying the sessions into different categories for browsers. Some other<br> proposed techniques choose to combine different order Markov models for obtaining low state<br> complexity and improving accuracy, as Deshpande and Karypis (2004). Dongshan and Junyi (2002)<br> used for predicting the access providing good scalability and high coverage a hybrid-order tree-like<br> Markov model. As an alternative to the Markov model Pitkow proposed a longest subsequence model<br> (Pitkow and Pirolli, 1999), also for predicting the next page accessed by the user Sarukkai chose<br> Markov models (Sarukkai, 2000).<br> Transitions are simulated using the Markov Chain nodes, Google matrix and an arbitrary initial<br> probability distribution. Examples can be seen in Figure 1 and Figure 2.</p>
WP6 SIA Model Matrix dataset
<p>There is no single right answer as to which model might be most appropriate for assessing the impact of Maker initiatives. Instead, we discuss the different parameters that are relevant for choosing the appropriate SIA model and provide a matrix of 69 SIA models with their respective approaches and parameters in this dataset and in deliverable <a href="http://make-it.io/deliverables/d6-2-societal-impact-analysis-and-sustainability-scenarios/">D6.2</a>.</p> <p>See also: <a href="http://make-it.io/open-data-api/">http://make-it.io/open-data-api/</a></p>
A guide to using a multiple-matrix animal model to disentangle genetic and nongenetic causes of phenotypic variance
<p>Simulated data associated with the paper "A guide to using a multiple-matrix animal model to disentangle genetic and nongenetic causes of phenotypic variance".</p> <p>The main dataset is contained within the mermaids.csv, with columns explained within the associated README file. Epigenetic and social network information are contained within the other two datasets</p>
Figure. The phylogenetic tree showing the relationship among Brevibacillus parabrevis strains SA2.2 and TJ2.3, Bacillus licheniformis MG4.2, and their phylogenetically closest type strains. The GenBank accession numbers of the type strains and studied strains are shown following species names. Distance matrix was calculated by Kimura's 2-parameter model. The scale bar indicates 0.02 substitutions per nucleotide position. Alicyclobacillus pohliae AJ564766 served as an out-group. in Distribution of extracellular enzyme-producing bacteria in the digestive tracts of 4 brackish water fish species
Figure. The phylogenetic tree showing the relationship among Brevibacillus parabrevis strains SA2.2 and TJ2.3, Bacillus licheniformis MG4.2, and their phylogenetically closest type strains. The GenBank accession numbers of the type strains and studied strains are shown following species names. Distance matrix was calculated by Kimura's 2-parameter model. The scale bar indicates 0.02 substitutions per nucleotide position. Alicyclobacillus pohliae AJ564766 served as an out-group.
Data for Coupling Covariance Matrix Adaptation with Continuum Modeling for Determination of Kinetic Parameters Associated with Electrochemical CO2 Reduction
<p>This data set contains digitized and tagged polarization and partial current density data for 18 datasets of CO<sub>2</sub> reduction to H<sub>2</sub> and CO over Ag catalysts, as well as 8 datasets of CO<sub>2</sub> reduction to HCOO<sup>-</sup>, CO, and H<sub>2</sub> over Sn catalysts. We analyze this data using a coupled continuum modeling and covariance matrix adaptation approach for which the codebase is provided in DOI: 10.5281/zenodo.7866195.</p>
A mathematical model to predict network growth in physarum polycephalum as a function of extracellular matrix viscosity, measured by a novel viscometer
Open the record for dataset details and reuse information.
Real-time benchmark dynamics of the Ohmic Spin-Boson Model computed with Time-Dependent Variational Matrix Product States. (TDVMPS) coupling strength and temperature parameter space
<p>Data describing the complete propagators (maps) for the evolution of the Ohmic Spin-Boson Model are made available, here. Using a time-dependent variotnal matrix product states (TDVMPS) respresentation of the complete spin-environment wave function, non -perturbative results are presented over a wide range of coupling strengths, temperatures and initial conditions. The results in this repository are associated with the article: </p> <p>https://www.preprints.org/manuscript/202012.0016/v1 </p> <p>A mathematica notebook that allows the data to be visualised and manipulated is also provided. </p>
Exact Spin-Boson-Model Tunneling Dynamics with Time Dependent Variation Matrix Product States (TDVMPS). Barrier height and temperature parameter space
<p>Spin-Boson tunnelling data acquired using the T-TEDOA method for Time-Dependent-Variational-Matrix-Product-States (TDVMPS) accompanying the paper <a href="https://doi.org/10.3389/fchem.2020.600731">https://doi.org/10.3389/fchem.2020.600731</a>.</p> <p> </p>
Simulation data for paper "Evaluation of Fendiline Treatment in VP40 System with Nucleation-Elongation Process: A Computational Model of Ebola Virus Matrix Protein Assembly"
<p>This is the original simulation data sets for paper "Evaluation of Fendiline Treatment in VP40 System with Nucleation-Elongation Process: A Computational Model of Ebola Virus Matrix Protein Assembly".</p>
Connectivity matrix of the internal connectivity of a SSCX model
<p>This is a simplified view of the <i>internal</i> synaptic connectivity of the model deposited under <a href="https://zenodo.org/records/8026353">https://zenodo.org/records/8026353.</a></p><p>While in this view a lot of data is lost compared to the detailed representation linked above (such as the pre- and postsynaptic locations of synaptic contacts and their physiology), it can still be used for structural connectomics analyses.</p><p>The data is in a format that can be loaded using our <a href="https://github.com/BlueBrain/ConnectomeUtilities"><i>Connectome_Utilities</i></a> package. We have converted the internal connectivity of the <a href="https://www.microns-explorer.org/">MICrONS</a> dataset into the same format (<a href="https://zenodo.org/records/8364070">found here</a>), allowing researchers to easily run the same analysis scripts on both datasets.</p>
Assessing Heavy Metal Contamination in Agricultural Soils: A Predictive Model Integrating GIS Tools and Probability-Risk Matrix – Case Study: Guarda Region, Portugal
<p>In these files we can find the final risk map of heavy metal contamination for the guarding area in Portugal obtained according to the methodology explained in the paper "Assessing Heavy Metal Contamination in Agricultural Soils: A Predictive Model Instegrating GIS Tools and Probability-Risk Matrix - Case Study: Guarda Region (Portugal)</p> <p>Final Risk Equal.tiff: GeoTiff with a pixel size of 30m. EPSG:3763 - ETRS89 / Portugal TM06</p> <p>Also attached is the symbolisation for the image in .qml (Quantum GIS Layer Style File) format.</p> <p>A file called RISK RECLASS is also available, where you can find the risk classification maps for each of the studied factors: </p> <ul> <li>Proximity to roads</li> <li>Proximity to industrial areas</li> <li>Ph</li> <li>Soil organic content</li> <li>Slope</li> <li>Soil texture</li> <li>Mining extraction areas </li> <li>Drainage</li> </ul> <p>finally a DATABASE file where the data of the 360 points for the calculation of the risk maps can be found. </p>
Dataset for Modeling scattering matrix containing evanescent modes for wavefront shaping applications in disordered media
<h3>About the data set</h3> <p>The zipped folder contains the saved computational run data of the Matlab code packages associated with our manuscript titled "Modeling scattering matrix containing evanescent modes for wavefront shaping applications in disordered media". Two .mat data files "saved-data-Code-Package-1.mat" and "saved-data-Code-Package-2.mat" are available within the zipped folder which are associated with the Matlab code packages hosted in the <a href="https://github.com/michaelraju/Generalized-S-Matrix.git" target="_blank" rel="noopener">Github repository</a> . One may add the data files "saved-data-Code-Package-1.mat" and "saved-data-Code-Package-2.mat" to the <a href="https://github.com/michaelraju/Generalized-S-Matrix.git" target="_blank" rel="noopener">Github repository</a> code package folders "Code-Package-1" and "Code-Package-2" respectively. Loading the saved run data (by setting <em>new_run_flag=0</em> in the main.m file contained in the Github repository) helps to visualize the results presented in the paper, without actually performing a new computational run from scratch. On the other hand, setting the flag <em>new_run_flag=1</em> yields a fresh computational run, initializing a new disorder.</p> <div> <h3>Contribution</h3> </div> <p>The dataset, the associated code packages and the analytical and numerical formulations were developed by Michael Raju as part of his <a href="https://hdl.handle.net/10468/14107" target="_blank" rel="noopener">PhD thesis</a>. Baptiste Jayet and Prof. Stefan Andersson-Engels were involved in the PhD supervision. </p>
Improved dual-permeability model for characterizing the mass transfer process inside matrix blocks
<p>The dual-permeability model (DPM) is highly efficient for describing bimodal transport in heterogeneous porous media. However, it uses only one domain to describe the matrix blocks, and it therefore ignores the impact of the mass transfer process inside the matrix blocks at the microscale. Therefore, in this study, to investigate the effect of the mass transfer process in dual-permeability media and the computational accuracy when considering it, the dual-permeability model with a transition domain (DPMTD) is proposed based on the DPM. Comparison of the DPMTD with the DPM by applying them to a sand column experiment with the same concept as the model reveals that the DPMTD captures the bimodal transport (especially the first peak) more effectively because it calculates the rapid exchange of solute in the early stage more accurately. Subsequently, the same conclusion is reached when both models are applied to a reported solute displacement experiment for an Andisol. In short, we suggest that the mass transfer process inside matrix blocks needs to be characterized in the model to achieve higher accuracy and provides a new approach for modeling the solute transport of preferential flow.</p>
Dataset: Modular Impedance Matrix Method for Transient Modeling in Pipe Network Systems
<p>Unsteady flow is an important engineering problem in urban pipe network systems, requiring pressure and flow rate management analyses and reliable drinking water quality maintenance. Efficiently solving the hyperbolic partial differential equation and integrating it with various boundary conditions under the complex layout scenarios of pipe networks is a challenging issue for pipeline modelers. Frequency-domain modeling with a time-domain response was developed as an alternative to the traditional method of characteristics. However, this solution requires a substantial array size for large pipe network systems, significantly affecting applicability in field pipe network systems. This study proposes an innovative transient analysis method, the modular impedance matrix method, to solve the most labor- and cost-intensive computational issues affecting the unsteady flow analysis of large, complicated pipe networks. This method was applied to a field pipe network system and its performance compared to existing approaches. The algorithm of the proposed method fundamentally solved the computational problems associated with other methods, and its modular scheme allowed feasible integration with an analytical formulation that can be tailored to the modeler's preferences. The modular impedance matrix method's strength can be amplified according to the size and complexity of the pipe network system owing to its unique complementary validation capability. </p>
Improved dual-permeability model for characterizing the mass transfer process inside matrix blocks
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Targeting cell-matrix induced chemoresistance with regorafenib in a 3D model of osteosarcoma
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Embeddings from "CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix-Space Model"
<p>This item holds the learned embeddings from the paper:</p> <p>Mai, Florian, Lukas Galke, and Ansgar Scherp. “CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space Model.” In <em>International Conference on Learning Representations</em>, 2019. <a href="https://openreview.net/forum?id=H1MgjoR9tQ">https://openreview.net/forum?id=H1MgjoR9tQ</a>.</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.