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3,688 results for “Computer”
Data from: Computed tomographic analysis of dental system of three Jurassic ceratopsians: implications for the evolution of the tooth replacement pattern and diet in early-diverging ceratopsians
<p><span>T</span><span>he </span><span>dental system of ceratops</span><span>ids is among the most specialized structure in Dinosauria</span><span>, and includes high angled wear surfaces, split tooth roots, and multiple teeth in each tooth family. However, the early evolution of this unique dental system is generally poorly understood due to a lack of knowledge of the dental morphology and development in early-diverging ceratopsians.</span><span> Here we study the dental system of </span><span>three</span><span> of the earliest-diverging Chinese ceratopsians</span><span>: </span><em><span>Yinlong</span></em><span> and <em>Hualianceratops</em> from the early Late Jurassic of Xinjiang</span><span>,</span><span> and <em>Chaoyangsaurus</em> from the Late Jurassic of Liaoning. By using micro-computed tomographic analyses, our study has revealed significant new information regarding the dental system of these early ceratopsians, including </span><span>no</span><span> more than five replacement teeth in each jaw quadrant; at most one generation of replacement teeth in each alveolus; nearly full resorption of the functional tooth root during tooth replacement; and occlusion with low-angled, concave wear facets that differs significantly from the shearing occlusal system seen in ceratopsids. <em>Yinlong</em> displays an increase in the number of maxillary tooth alveoli and a decrease in the number of replacement teeth during ontogeny as well as the retention of remnants of functional teeth in the largest individual.</span> <span>Early-diverging ceratopsians thus display a relatively slow tooth replacement rate compared to late-diverging ceratopsians.</span> <span>Combined with paleobotany and palaeoenvironment data, <em>Yinlong</em> likely uses gastroliths to triturate foodstuffs, and t</span><span>he difference in diet strategy might have influenced the pattern of tooth replacement in later-diverging ceratopsians.</span></p>
Processed FDG-PET data from: A computational model of neurodegeneration in Alzheimer's disease
<p>Disruption of mental functions in Alzheimer's disease (AD) and related disorders is accompanied by selective degeneration of brain regions. These regions comprise large-scale ensembles of cells organized into systems for mental functioning, however the relationship between clinical symptoms of dementia, patterns of neurodegeneration, and functional systems is not clear. We developed a model of the association between dementia symptoms and degenerative brain anatomy using F18-fluorodeoxyglucose (FDG) PET and dimensionality reduction techniques patients with AD. This data and code package contains preprocessed FDG-PET images from 423 subjects across the Alzheimer's disease spectrum and the MATLAB code to produce eigenbrains from this data.</p>
R20_006_Computer_Prelude_Risset_TEST
<p>Sketch of the Score Code from Risset's Little boy.</p> <p>Copyright: Fonds Risset, PRISM, CNRS Marseille</p>
Example data for "Calibration of X-ray computed tomography for surface topography measurement using metrological characteristics"
<p>Example raw data used to create figures during the conference paper "<a href="https://www.euspen.eu/knowledge-base/ICE21165.pdf"><em>Calibration of X-ray computed tomography for surface topography measurement using metrological characteristics</em></a>", presented at euspen’s 21st International Conference & Exhibition 2020</p> <p>Data in the ".datx" format are acquired using a ZYGO NexView NX2 coherence scanning interferometer.</p> <p>Data in the ".stl" format are acquired using a Nikon MCT 225 X-ray computed tomography instrument.</p>
Computational Data for Weaker interdomain interactions in FimH30 from multidrug-resistant Escherichia coli ST131 mediate longer lasting interactions with mannose and enhanced adhesin function
<p>Input files for the MD simulations and the resulting trajectories. A representative trajectory is provided for the R and T state of each allele. </p>
Does automated reassesment & relearning improve math performance in comparison to traditional computer adaptive practice alone?
<p>Scholarly interest in the notion on how students learn and retain learned skills is vast. Cognitive psychologists have recommended various techniques used to increase retention. One technique, spaced retrieval practice, involves extending opportunities to retrieve course content beyond a customarily short window following the initial learning process. Our preregistered counterbalanced randomised control trial investigated whether an online tutor with an Automated Reassessment and Relearning System (ARRS) improves retention for individual students across specific mathematical skills. While our findings revealed a null result, in part due to the small number of participants, we feel this experimental design could be used in future studies with more favourable results. Additionally, we feel ARRS could be used to support low prior knowledge students and Students With Interrupted or Limited Formal Education (SLIFE), a growing population in schools that is often overlooked in academic research.</p>
Research compendium for 'Practical and technical aspects for the 3D scanning of lithic artefacts using micro-computed tomography techniques and laser light scanners for subsequent geometric morphometric analysis. Introducing the StyroStone protocol'
<p><strong>Abstract:</strong></p> <p>Here, we present a new method to scan a large number of lithic artefacts using three-dimensional (3D) scanning technology. Despite the rising use of high-resolution 3D surface scanners in archaeological sciences, no virtual studies have focused on the 3D digitization and analysis of small lithic implements such as bladelets, microblades, and microflakes. This is mostly due to difficulties in creating reliable 3D meshes of these artefacts resulting from several inherent features (i.e., size, translucency, and acute edge angles), which compromise the efficiency of structured light or laser scanners and photogrammetry. Our new protocol <em>StyroStone</em> addresses this problem by proposing a step-by-step procedure relying on the use of micro-computed tomographic technology, which is able to capture the 3D shape of small lithic implements in high detail. We tested a system that enables us to scan hundreds of artefacts together at once within a single scanning session lasting a few hours. As also bigger lithic artefacts (i.e., blades) are present in our sample, this protocol is complemented by a short guide on how to effectively scan such artefacts using a structured light scanner (Artec Space Spider). Furthermore, we estimate the accuracy of our scanning protocol using principal component analysis of 3D Procrustes shape coordinates on a sample of meshes of bladelets obtained with both micro-computed tomography and another scanning device (i.e., Artec Micro). A comprehensive review on the use of 3D geometric morphometrics in lithic analysis and other computer-based approaches is provided in the introductory chapter to show the advantages of improving 3D scanning protocols and increasing the digitization of our prehistoric human heritage.</p> <p><strong>Content List:</strong></p> <ul> <li><strong>S1. </strong>Step-by-step protocol entitled ‘StyroStone: A protocol for scanning and extracting three-dimensional meshes of stone artefacts using Micro-CT scanners’. Also available on protocols.io (dx.doi.org/10.17504/protocols.io.bzbfp2jn);</li> <li><strong>S2. </strong>Dataset with all raw semilandmark coordinate data (in .xlsx format) used in the validation study;</li> <li><strong>S3. </strong>AGMT3D project. The file “Validation Protocol-MorphoProject.mat” can be used to open the project in the software AGMT3D;</li> <li><strong>S4. </strong>Dataset in .csv format of the principal component score data of the validation study;</li> <li><strong>S5.</strong> R script used to create Figure 2 using the R package ggplot2;</li> <li><strong>S6. </strong>3D models of the experimental bladelets obtained with the Micro-CT scanner used in the validation study. Both .ply and .wrl formats are provided;</li> <li><strong>S7. </strong>3D models of the experimental bladelets obtained with the Artec Micro scanner used in the validation study. Both .ply and .wrl formats are provided.</li> </ul>
Data from: Correcting a bias in the computation of behavioral time budgets that are based on supervised learning
<p>Supervised learning of behavioral modes from body-acceleration data has become a widely used research tool in Behavioral Ecology over the past decade. One of the primary usages of this tool is to estimate behavioral time budgets from the distribution of behaviors as predicted by the model. These serve as the key parameters to test predictions about the variation in animal behavior. In this paper we show that the widespread computation of behavioral time budgets is biased, due to ignoring the classification model confusion probabilities. Next, we introduce <em>the confusion matrix correction for time budgets</em> -- a simple correction method for adjusting the computed time budgets based on the model's confusion matrix. Finally, we show that the proposed correction is able to eliminate the bias, both theoretically and empirically in a series of data simulations on body acceleration data of a fossorial rodent species (Damaraland mole-rat, <em>Fukomys damarensis</em>). Our paper provides a simple implementation of <em>the confusion matrix correction for time budgets</em>, and we encourage researchers to use it to improve accuracy of behavioral time budget calculations.</p>
Images of Public Streetlights with Operational Monitoring using Computer Vision Techniques
<p>This dataset consists of ~350k JPEG images of streetlight columns installed on a public road infrastructure located in the city of Bristol, UK.</p> <p>Each streetlight is photographed by a Raspberry Pi Camera Module v1, installed on each lamppost, providing a unique camera placement, photographic angle, and distance from the streetlight. Several streetlights are partially obstructed by vegetation or are outside the Field of View (FoV) of the Raspberry Pi camera. Finally, the cameras facing the sky are susceptible to weather conditions (e.g., rain, snow, direct sunlight, etc.) that can partially or entirely alter the quality of the images taken.</p> <p>The above provides a unique and diverse dataset of images that can be used for training tools and machine learning models for inspection, monitoring and maintenance use-cases within Smart Cities applications.</p>
JCSP: Joint Caching and Service Placement for Edge Computing Systems
<p>The archives include the research data associated with the paper <strong><em>JCSP: Joint Caching and Service Placement for Edge Computing Systems</em></strong>. The paper is accepted in IEEE IWQoS 2022.</p> <p>The research data includes the validation dataset for the generalized LQN model that corresponds to section V of the paper. The validation model contains two layers. In the upper layer, the underlying processor adopts the processor sharing strategy. While in the lower layer, the capacity of the cache-task is set as 1 with a total number of 3 items. All the items obey discrete uniform distribution and take the random replacement strategy. </p> <p> </p>
X-ray computed tomography aided engineering approach for non-crimp fabric reinforced composites [Data set]
<p>The finite element models behind the publication</p> <p>Auenhammer, R.M., Jeppesen, N., Mikkelsen, L.P., Dahl, V.A., Blinzler, B.J., Asp, L.E. Robust numerical analysis of fibrous composites from X-ray computed tomography image data enabling low resolutions, <em>Composites Science and Technology, </em><strong>224</strong>, 109458, <a href="https://doi.org/10.1016/j.compscitech.2022.109458">https://doi.org/10.1016/j.compscitech.2022.109458</a>, 2022. </p> <p>The x-ray scan data which the model is based on can be found in the following publication:</p> <p>Jeppesen, N., V.A. Dahl, A.N. Christensen, A.B. Dahl, L.P. Mikkelsen, Characterization of the fiber orientations in non-crimp glass fiber reinforced composites using structure tensor. IOP Conf. Ser.: Mater. Sci. Eng. 942, 012037, <a href="https://doi.org/10.1088/1757-899X/942/1/012037">https://doi.org/10.1088/1757-899X/942/1/012037</a> 2020</p> <p>and data-set</p> <p>Jeppesen N, Dahl V A, Christensen A N, Dahl A B and Mikkelsen L P 2020 Characterization of the fiber orientations in non-crimp glass fiber reinforced composites using structure tensor [data set] Zenodo. <a href="http://dx.doi.org/10.5281/zenodo.3877522">http://dx.doi.org/10.5281/zenodo.3877522.</a></p> <p> </p>
Data from: Determining ground-state phase diagrams on quantum computers via a generalized application of adiabatic state preparation
<p>Quantum phase transitions materialize as level crossings in the ground-state energy when the parameters of the Hamiltonian are varied. The resulting ground-state phase diagrams are straightforward to determine by exact diagonalization on classical computers, but are challenging on quantum computers because of the accuracy needed and the near degeneracy of competing states close to the level crossings. In this work, we use a local adiabatic ramp for state preparation to allow us to directly compute ground-state phase diagrams on a quantum computer via time evolution. This methodology is illustrated by examining the ground states of the XY model with a magnetic field in the z-direction in one dimension. We are able to calculate an accurate phase diagram on both two and three site systems using IBM quantum machines.</p>
Figure 2 from: Keller D., Radivojević N., Lazzarini V. (2022). Issues in ubimus archaeology: Beyond pure computing and precision during the analogue-digital transition
<p><strong>Figure2_W20_003_2_P92</strong></p> <p><strong>Fonds Jean-Claude Risset, Laboratoire PRISM (UMR 7061 – France). The copyright applies to documents digitized by the PRISM laboratory.</strong></p>
Figure 3 from: Keller D., Radivojević N., Lazzarini V. (2022). Issues in ubimus archaeology: Beyond pure computing and precision during the analogue-digital transition
<p><strong>Figure3. W20_003_3_P10</strong><br> <strong>Fonds Jean-Claude Risset, Laboratoire PRISM (UMR 7061 – France). The copyright applies to documents digitized by the PRISM laboratory</strong></p>
Figure 1 from: Keller D., Radivojević N., Lazzarini V. (2022). Issues in ubimus archaeology: Beyond pure computing and precision during the analogue-digital transition
<p><strong>Figure 1. W20_003_2_P20</strong><br> <strong>Fonds Jean-Claude Risset, Laboratoire PRISM (UMR 7061 – France). The copyright applies to documents digitized by the PRISM laboratory</strong></p>
A computational toolbox to investigate the metabolic potential and resource allocation in fission yeast
<p>Computational models and figure data for the publication "A computational toolbox to investigate the metabolic potential and resource allocation in fission yeast" (preprint on <a href="https://doi.org/10.1101/2022.05.04.490403"><em>bioRxiv</em></a>). Data put together by Pranas Grigaitis, p.grigaitis [at] vu.nl.</p> <p> </p> <p><em>Abstract</em></p> <p>The fission yeast <em>Schizosaccharomyces pombe</em> is a popular eukaryal model organism for cell division and cell cycle studies. With this extensive knowledge of its cell and molecular biology, <em>S. pombe</em> also holds promise for use in metabolism research and industrial applications. However, unlike the baker’s yeast <em>Saccharomyces cerevisiae</em>, a major workhorse in these areas, cell physiology and metabolism of <em>S. pombe</em> remain less explored. One way to advance understanding of organism-specific metabolism is construction of computational models and their use for hypothesis testing. To this end, we leverage existing knowledge of <em>S. cerevisiae</em> to generate a manually-curated high-quality reconstruction of <em>S. pombe’s</em> metabolic network, including a proteome-constrained version of the model. Using these models, we gain insights into the energy demands for growth, as well as ribosome kinetics in <em>S. pombe</em>. Furthermore, we predict proteome composition and identify growth-limiting constraints that determine optimal metabolic strategies under different glucose availability regimes, and reproduce experimentally determined metabolic profiles. Notably, we find similarities in metabolic and proteome predictions of <em>S. pombe</em> with <em>S. cerevisiae</em>, which indicate that similar cellular resource constraints operate to dictate metabolic organization. With these use cases, we show, on the one hand, how these models provide an efficient means to transfer metabolic knowledge from a well-studied to a lesser-studied organism, and on the other, how they can successfully be used to explore the metabolic behaviour and the role of resource allocation in driving different strategies in fission yeast.</p>
Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed Tomography-based Latent Traits: A Deep Learning Approach
<p>Around nine million people had been exposed to toxic humidifier disinfectants (HDs) in Korea. HD-exposure may lead to HD-associated lung injuries (HDLI). However, many people who claimed HD exposure were not diagnosed of HDLI but still felt discomfort possibly due to the unknown effects of HD. Therefore, this study examined HD-exposed subjects with normal appearing lungs as well as unexposed subjects in clusters (subgroups) with distinct characteristics classified by deep-learning-derived computed-tomography (CT)-based tissue-pattern latent traits. Among the major clusters, cluster 0 (C0) and cluster 5 (C5) were dominated by HD-exposed and unexposed subjects, respectively. C0 was characterized by features attributable to lung inflammation or fibrosis compared with C5. The computational fluid and particle dynamics (CFPD) analysis suggested that the smaller airway sizes observed in the C0 subjects led to greater airway resistance and particle deposition in the airways. Accordingly, women appeared more vulnerable to HD-associated lung abnormality than men.</p>
Chanalyzer: a computational geometry approach for the analysis of protein channel shape and dynamics
<p>Dataset of molecular dynamics trajectories described in the "Chanalyzer: a computational geometry approach for the analysis of protein channel shape and dynamics" work.</p> <p>Trajectories of differently functionalized MscL channel forms. </p> <p>The *_xyzr.tar.gz files contain the processed frames in the xyzr format, which is a compatible input for NanoShaper</p> <p>The conf.prm file is the parameter file that has been used for the NanoShaper tool</p>
On the computational reproducibility of molecular phylogenies
<p>Reports on the lack of computational reproducibility of molecular phylogenies, produced in multiple runs of the same program or by different programs, cast a long shadow on downstream research using these phylogenies and on efforts to build the tree of life. We show that this irreproducibility does not decrease the accuracy of the reconstructed evolutionary relationships. Also, we find inferred molecular phylogenies to have log-likelihoods comparable to or better than the true phylogeny. Therefore, the lack of computational reproducibility of molecular phylogenies is not a problem for evolutionary studies.</p>
Computational models from: Allele-specific activation, enzyme kinetics, and inhibitor sensitivities of EGFR exon 19 deletion mutations in lung cancer
<p>Computational models, compressed molecular dynamics (MD) simulation trajectories, and sample input files for "Allele-specific activation, enzyme kinetics, and inhibitor sensitivities of EGFR exon 19 deletion mutations in lung cancer". An early version of this manuscript is available as a preprint here: https://www.biorxiv.org/content/10.1101/2022.03.16.484661v1</p>
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.