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757 results for “twinning”
Non-identical moire twins in bilayer graphene revealed by valley Hall effect measurements
<p>The superlattice obtained by aligning a monolayer graphene and boron nitride (BN) inherits from the hexagonal lattice a sixty degrees periodicity with the layer alignment. It implies that, in principle, the properties of the heterostructure must be identical for 0$^{\circ}$ and 60$^{\circ}$ of layer alignment. Here, we demonstrate, using dynamically rotatable van der Waals heterostructures, that the moir\'e superlattice formed in a bilayer graphene/BN has different electronic properties at 0$^{\circ}$ and 60$^{\circ}$ of alignment. Although the existence of these non-identical moir\'e twins is explained by different relaxation of the atomic structures for each alignment, the origin of the observed valley Hall effect remains to be explained. A simple Berry curvature argument do not hold to explain the hundred and twenty degrees periodicity of this observation. Our results highlight the complexity of the interplay between mechanical and electronic properties on moir\'e structure and the importance of taking into account atomic structure relaxation to understand its electronic properties.</p>
Numerical simulations and experimental measurements of the ULB semi-industrial furnace for the development of a Digital Twin
<p>This dataset contains the numerical and experimental data used to build the Digital Twin in Aversano et al. (https://doi.org/10.1016/j.proci.2020.06.045) and the adaptive Digital Twin in Procacci et al. (https://doi.org/10.1016/j.proci.2022.07.029).</p> <p>The directory "Numerical_data" includes 45 text files containing the data coming from the CFD simulations of the ULB furnace. <br> In each file, for each computational cell the features reported are: <br> - the cell's position in x, y, z coordinates and in meters.<br> - the cell's temperature in K. <br> - the cell's species mass fraction of NO (mf-pollut-pollutant-0), CO, OH, H2, H2O, CO2, O2, CH4.<br> The details of the setup of the numerical simulations are reported in Aversano et al.</p> <p>The numerical simulations have been computed for different values of the equivalence ratio (phi), blend of H2-CH4 (H2) and <br> inlet diameter (D).<br> The simulations for different inlet diameter where computed using different meshes, with slightly different numbers of cells.<br> In the file 'cases_parameters.csv', the value of the parameters is reported for of each simulation. There is a <br> discrepancy between the naming of the simulations in Aversano et al. and the one used in naming the files, so both are reported.</p> <p>The experimental measurements used to validate the numerical simulations can be found in the directory "Experimental_data". Each<br> file contains the value of the measured temperature along with the position in x and z in meters (y being 0). The temperature is<br> in K. The experimental uncertainty is estimated at 10 K.</p> <p>The file 'grid.vtu' contains the computational grid used to solve the CFD simulations. It can be opened using VTK-based software <br> such as Paraview or Pyvista.</p> <p>Changelog:</p> <p>- In version V1, some simulations were corrupted during data export.<br> - Added the grid file in V3</p>
Greenhouse Gas and Water Chemistry Data from Ponds in the Twin-Cities area of Minnesota, 2021
Freshwaters are significant contributors of greenhouse gases to the atmosphere, including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Small waterbodies such as ponds are now recognized to have disproportionate greenhouse gas emissions relative to their size, but recorded emissions from ponds have varied by several orders of magnitude. To assess drivers of variation in pond greenhouse gas dynamics, this study measured concentrations and emissions of CO2, CH4, and N2O across 26 ponds in Minnesota, USA during the ice-free season. The studied ponds ranged in land-use, from urban stormwater ponds to natural forested ponds. Water chemistry variables were measured with sonde profiles as well as surface water samples. Greenhouse gas emsisions of CO2 and CH4 were measured with a floating chamber at three locations on each pond, and gas concentrations of CO2, CH4, and N2O were measured using a headspace equilibrium technique in both the surface waters and bottom waters of each pond.
Dataset for Superconducting 'twin qubit' , PRB 102, 115422 (2020)
<p>Dataset for manuscript "Superconducting 'twin qubit'", Phys. Rev. B 102, 115422 (2020). Dataset includes experimental data text files of Fig. 2 and Fig. 7 in the manuscript. The dataset describes energy spectrum of superconducting 'twin qubit' (Fig. 2) and its Rabi oscillations (Fig. 7). The paper studies the superconducting double loop system, 'twin qubit'.</p>
Early postzygotic mutations contribute to de novo variation in a healthy monozygotic twin pair.
<p>Human de novo single-nucleotide variation (SNV) rate is estimated to range between 0.82-1.70×10(-8) mutations per base per generation. However, contribution of early postzygotic mutations to the overall human de novo SNV rate is unknown.</p> <p>METHODS:</p> <p>We performed deep whole-genome sequencing (more than 30-fold coverage per individual) of the whole-blood-derived DNA samples of a healthy monozygotic twin pair and their parents. We examined the genotypes of each individual simultaneously for each of the SNVs and discovered de novo SNVs regarding the timing of mutagenesis. Putative de novo SNVs were validated using Sanger-based capillary sequencing.</p> <p>RESULTS:</p> <p>We conservatively characterised 23 de novo SNVs shared by the twin pair, 8 de novo SNVs specific to twin I and 1 de novo SNV specific to twin II. Based on the number of de novo SNVs validated by Sanger sequencing and the number of callable bases of each twin, we calculated the overall de novo SNV rate of 1.31×10(-8) and 1.01×10(-8) for twin I and twin II, respectively. Of these, rates of the early postzygotic de novo SNVs were estimated to be 0.34×10(-8) for twin I and 0.04×10(-8) for twin II.</p> <p>CONCLUSIONS:</p> <p>Early postzygotic mutations constitute a substantial proportion of de novo mutations in humans. Therefore, genome mosaicism resulting from early mitotic events during embryogenesis is common and could substantially contribute to the development of diseases.</p>
Twin test 1: Effect of vegetation on urban flows. PIV data from NTUA WT experiment and LDV from KIT WT experiment
<p>The first Twin Test (TW1) of the TWEET-IE project (<a href="http://www.tweet-ie.eu">www.tweet-ie.eu</a>) involved measurements of the flow past a surface mounted cube with openings, representing a building exposed to an atmospheric boundary layer. Tests were performed for smooth building walls but also with modelled vegetation covering the windward façade and the roof of the building. The measurements were performed both at Karlsruhe Institute of Technology (KIT) and the National Technical University of Athens (NTUA), in wind tunnels, at common locations around the building. Laser Doppler Anemometry (LDA) was used at KIT and Particle Image Velocimetry (2C-2D and 3C-2D PIV) at NTUA. In the present data set shows the effect of vegetation on the flow velocities and a comparison of the twin wind tunnel measurements. </p>
TWIN2PIPSA - Twinning for strategic networking and impactful research and innovation in Biomedicine and Biotechnology
<p>Presentation by Prof. Cláudio M. Gomes at the 5<sup>th</sup> edition of Ciências Research & Innovation Day.</p>
Supplementary material for: Calibrating coordinate system alignment in a scanning transmission electron microscope using a digital twin.
<h1>Calibrating coordinate system alignment in a scanning transmission electron microscope using a digital twin.</h1> <h2>Supplementary material</h2> <p>This deposition contains supplementary material for a paper on coordinate system calibration in 4D STEM. A preprint of the paper is available at <a href="https://arxiv.org/abs/2403.08538">https://arxiv.org/abs/2403.08538</a>.</p> <h2>Contents</h2> <div> <div><code>20221025_154811.zip</code>: Overfocused 4D STEM test dataset</div> <div> </div> <div><code>overfocus.sif</code>: Apptainer image with complete software stack. <code>apptainer run --writable overfocus.sif</code> to execute. It starts a Jupyterlab instance with two notebooks, one to genreate test data and the other to perform the interactive adjustment. This documents the software version that was used for the figures in the paper.</div> <div> </div> <div><code>requirements.txt</code>: Python package versions of dependencies in <code>overfocus.sif</code>. </div> <div> </div> <div><code>COM - Jupyter Notebook - Google Chrome 2023-01-25 12-40-07_processed.mp4</code>: Screen capture video with explanation of the first live calibration with an early prototype.</div> <div> </div> <div><code>video description.docx</code>: Explanation of the plots and adjustment process in the screen capture video.</div> <div> </div> <div><code>Microscope-Calibration.tar.gz</code>: Repository archive of the software and examples for calibration in the version used in the paper.</div> <div> </div> <div><code>TemGym.tar.gz</code>: Repository archive of TemGym Basic in the version used in the paper.</div> </div>
Digital Twins - from industrial management to healthcare practice
<p>A guest seminar offered by SCImPULSE Foundation CTO Taghi Aliyev for the University of Parma (IT) master "ARTE" https://www.masterarte-unipr.it/</p>
Fig. 1 in Interspecific Interactions as a Factor of Limitation of Geographical Distribution: Evidence Obtained by Modeling Home Ranges of Vole Twin Species Microtus Arvalis – M. Levis (Rodentia, Microtidae)
Fig. 1. Potential distribution of the Common vole Microtus arvalis. White circles are georeferenced occurrences of genetically identified individuals; black indicates areas of maximum habitat suitability, white are areas of lowest suitability.
Twin prime countings up to 5.9*10^8
<p>One file contains all the sets of of calculations including f(x)/g(x), the other is just the twin prime counts every 100 units.</p>
Twin Prime Conjecture data for Bortolomasi et al
<p>dakini@Kairos:~/Documents/Marco2022/ZenodoFiles$ head p2_HLC_001.txt<br> "gx[x_]:=Sqrt[x]/Log[x] "<br> {"n= ", " p2= ", " HLCconj= ", " fx->|p2-HLC|= ", "f(x)/g(x)"}<br> {100, 8, 13.53, 5.53, 2.54}<br> {200, 15, 18.86, 3.86, 1.44}<br> {300, 19, 23.20, 4.20, 1.38}<br> {400, 21, 27.06, 6.06, 1.81}<br> {500, 24, 30.60, 6.60, 1.83}<br> {600, 26, 33.92, 7.92, 2.06}<br> {700, 30, 37.07, 7.07, 1.75}<br> {800, 30, 40.08, 10.08, 2.38}</p> <p>dakini@Kairos:~/Documents/Marco2022/ZenodoFiles$ head p2_HLC_002.txt<br> "gx[x_]:=Sqrt[x]/Log[x] "<br> {"n= ", " p2= ", " HLCconj= ", " fx->|p2-HLC|= ", "f(x)/g(x)"}<br> {590139000, 2134457, 2.13*^6, 771.94,<br> 0.64}<br> {590144000, 2134473, 2.13*^6, 772.13,<br> 0.64}<br> {590149000, 2134490, 2.13*^6, 771.31,<br> 0.64}<br> {590154000, 2134500, 2.13*^6, 777.50,<br> 0.64}</p> <p>dakini@Kairos:~/Documents/Marco2022/ZenodoFiles$ head p2_HLC_003.txt<br> "gx[x_]:=Sqrt[x]/Log[x] "<br> {"n= ", " p2= ", " HLCconj= ", " fx->|p2-HLC|= ", "f(x)/g(x)"}<br> {9999999000, 27412677, 2.74*^7, 1262.71,<br> 0.29}<br> {10000009000, 27412691, 2.74*^7, 1251.81,<br> 0.28}<br> {10000019000, 27412720, 2.74*^7, 1255.91,<br> 0.28}<br> {10000029000, 27412748, 2.74*^7, 1259.01,<br> 0.28}</p> <p> </p> <p> </p>
Data for RAPPPID: Towards Generalisable Protein Interaction Prediction with AWD-LSTM Twin Networks
<p>Data for RAPPPID, a method for the Regularised Automative Prediction of Protein-Protein Interactions using Deep Learning.</p> <p>These datasets are in a format that RAPPPID is ready to read.<br> <br> <strong>Comparatives Dataset</strong><br> These datasets were derived from the STRING v11 <em>H. sapiens</em> dataset, according to the C1, C2, and C3 procedures outlined by Park and Marcotte, 2012. Negative samples are sampled randomly from the space of proteins not known to interact. See <a href="https://doi.org/10.1101/2021.08.13.456309">Szymborski & Emad</a> for details.<br> <br> <strong>Repeatability Datasets</strong><br> The following datasets are all derived from STRING in the manner as the comparatives dataset, but three different random seeds are used for drawing proteins.<br> <br> <strong>References</strong><br> Park,Y. and Marcotte,E.M. (2012) Flaws in evaluation schemes for pair-input computational predictions. Nat Methods, 9, 1134–1136.</p> <p>Szklarczyk, D., Gable, A. L., Lyon, D., Junge, A., Wyder, S., Huerta-Cepas, J., Simonovic, M., Doncheva, N. T., Morris, J. H., Bork, P., Jensen, L. J., and Mering, C. (2019). String v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Research, 47(D1), D607–D613.<br> <br> Szymborski,J. and Emad,A. (2021) RAPPPID: Towards Generalisable Protein Interaction Prediction with AWD-LSTM Twin Networks. bioRxiv https://doi.org/10.1101/2021.08.13.456309</p>
Sparsified Model Zoo Twins: A Dataset of Sparsified Populations of Neural Network Models - MNIST
<p><strong>Abstract</strong></p> <p>In the last years, neural networks have evolved from laboratory environments to the state-of-the-art for many real-world problems. Our hypothesis is that neural network models (i.e., their weights and biases) evolve on unique, smooth trajectories in weight space during training. Following, a population of such neural network models (refereed to as “model zoo”) would form topological structures in weight space. We think that the geometry, curvature and smoothness of these structures contain information about the state of training and can be reveal latent properties of individual models. With such zoos, one could investigate novel approaches for (i) model analysis, (ii) discover unknown learning dynamics, (iii) learn rich representations of such populations, or (iv) exploit the model zoos for generative modelling of neural network weights and biases. Unfortunately, the lack of standardized model zoos and available benchmarks significantly increases the friction for further research about populations of neural networks. With this work, we publish a novel dataset of model zoos containing systematically generated and diverse populations of neural network models for further research. In total the proposed model zoo dataset is based on six image datasets, consist of 27 model zoos with varying hyperparameter combinations are generated and includes 50’360 unique neural network models resulting in over 2’585’360 collected model states. Additionally, to the model zoo data we provide an in-depth analysis of the zoos and provide benchmarks for multiple downstream tasks as mentioned before.</p> <p><strong>Dataset</strong></p> <p>This dataset is part of a larger collection of model zoos and contains the sparsified twins of models trained on MNIST. The original population is made available at https://doi.org/10.5281/zenodo.6632086. Sparsification is done using Variational Dropout, starting from the last epoch of the original population. The zip file contains the sparsification trajectory for 25 epochs for all 1000 models. All zoos with extensive information and code can be found at www.modelzoos.cc.</p> <p> </p>
Sparsified Model Zoo Twins: A Dataset of Sparsified Populations of Neural Network Models - SVHN
<p><strong>Abstract</strong></p> <p>In the last years, neural networks have evolved from laboratory environments to the state-of-the-art for many real-world problems. Our hypothesis is that neural network models (i.e., their weights and biases) evolve on unique, smooth trajectories in weight space during training. Following, a population of such neural network models (refereed to as “model zoo”) would form topological structures in weight space. We think that the geometry, curvature and smoothness of these structures contain information about the state of training and can be reveal latent properties of individual models. With such zoos, one could investigate novel approaches for (i) model analysis, (ii) discover unknown learning dynamics, (iii) learn rich representations of such populations, or (iv) exploit the model zoos for generative modelling of neural network weights and biases. Unfortunately, the lack of standardized model zoos and available benchmarks significantly increases the friction for further research about populations of neural networks. With this work, we publish a novel dataset of model zoos containing systematically generated and diverse populations of neural network models for further research. In total the proposed model zoo dataset is based on six image datasets, consist of 27 model zoos with varying hyperparameter combinations are generated and includes 50’360 unique neural network models resulting in over 2’585’360 collected model states. Additionally, to the model zoo data we provide an in-depth analysis of the zoos and provide benchmarks for multiple downstream tasks as mentioned before.</p> <p><strong>Dataset</strong></p> <p>This dataset is part of a larger collection of model zoos and contains the sparsified twins of models trained on SVHN. The original population is made available at https://doi.org/10.5281/zenodo.6632120. Sparsification is done using Variational Dropout, starting from the last epoch of the original population. The zip file contains the sparsification trajectory for 25 epochs for all 1000 models. All zoos with extensive information and code can be found at www.modelzoos.cc.</p>
SICIL extractions of eNATL60 twin simulations
<p>This repository describes the SICIL extractions of the <a href="https://github.com/ocean-next/eNATL60">eNATL60</a> twin simulations : how to get it and how to reproduce it.</p>
Data from: Digital twin mathematical models suggest individualized hemorrhagic shock resuscitation strategies
<p><strong>Background:</strong> Optimizing resuscitation to reduce inflammation and organ dysfunction following human trauma-associated hemorrhagic shock is a major clinical hurdle. This is limited by the short duration of pre-clinical studies and the sparsity of early data in the clinical setting.</p> <p><strong>Methods:</strong> We sought to bridge this gap by linking preclinical data in the porcine model with clinical data from patients from the Prospective, Observational, Multicenter, Major Trauma Transfusion (PROMMTT) study via a three-compartment ordinary differential equation model of inflammation and coagulation.</p> <p><strong>Results:</strong> The model accurately predicts physiologic, inflammatory, and laboratory measures in both the porcine model and patients, as well as the outcome and time of death in the PROMMTT cohort. Model simulation suggests that resuscitation with plasma and red blood cells outperformed resuscitation with crystalloid or plasma alone, and that earlier plasma resuscitation reduced injury severity and increased survival time.</p> <p><strong>Conclusions:</strong> This workflow may serve as a translational bridge from pre-clinical to clinical studies in trauma-associated hemorrhagic shock and other complex disease settings.</p>
Mothers of twins had higher old-age survival than mothers of singletons in Estonian 19th-century birth cohorts
<p><strong><span>Study question:</span></strong><span> Do the mothers of twins and singletons differ regarding post-partum and old-age mortality?</span></p> <p><span> </span><strong><span>Summary answer:</span></strong><span> M</span><span>others of twins had twice as high post-partum mortality as mothers of singletons; survival of twinners was higher than survival of the mothers of singletons after the 67<sup>th </sup>lifespan percentile.</span></p> <p><strong><span>What is known already:</span></strong><span> Twinning is typically associated with higher post-partum maternal mortality. The evidence about whether twinning incurs long-term survival costs of reproduction or is a trait pertinent to long-lived women is scarce and contradictory.</span></p> <p><strong><span>Study design, size, duration:</span></strong><span> The study is based on the data of the Estonian Family Register (operating from 1926-43) and involves 5 565 mothers of twins and 119 613 mothers of singletons born between 1850-99. The subset for comparing maternal lifespans included 1 703 – 1 884 mothers of twins and </span><span>19 747 </span><span>– 36 690 mothers of singletons.</span></p> <p><strong><span>Participants/materials, setting, methods:</span></strong><span> Post-partum maternal mortality was analysed in the whole sample (including mothers of a single child) by logistic regression. Most of the analyses were performed in samples where each mother of twins was matched against mothers of singletons based on parity, urban versus rural origin, whether their lifespan was known, date of birth and age at first birth. Quantile regression was used to analyse age-dependent variations in maternal mortality rates. Lifespans were compared in linear mixed models. All models were adjusted for relevant biodemographic covariates.</span></p> <p><strong><span>Main results and the role of chance:</span></strong><span> The twinning rate in the whole sample was 4.4%. During the year after giving birth, maternal mortality for multiple gestations was 0.75% (17/2 273) and 0.37% (</span><span>449</span><span>/</span><span>122 750)</span><span> for single gestations (OR = 2.05, 95% CI = 1.21 – 3.23). The association between twinning and post-natal maternal mortality remained significant in a model controlling for parity and age of first and last birth. The life spans of the mothers of twins and singletons did not differ in matched samples. Past the 67<sup>th</sup> lifespan percentile, the odds of survival were significantly higher for mothers of twins than mothers of singletons, as indicated by non-overlapping 95% confidence intervals.</span></p> <p><strong><span>Limitations, reasons for caution: </span></strong><span>Relatively low number of individuals (22 802) with known age at death due to discontinuation of the register after 1943.</span></p>
Dataset for digital twins for managing bridge climate change adaptation
<p><span>This is the dataset for embedding in the novel digital twin driven by</span><span> BIM technology to manage the climate change adaptation measures for the bridges. A 6D BIM model has been established and embeded with change adaptation measures, timeline schedule, climate change adaptation cost estimation, and carbon emission estimation.</span></p>
Dataset: Twin Vee Powercats Co. (VEEE) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
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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.