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4,694 results for “data analysis”
Data from: Combined analysis of extant Rhynchonellida (Brachiopoda) using morphological and molecular data
Independent molecular and morphological phylogenetic analyses have often produced discordant results for certain groups which, for fossil-rich groups, raises the possibility that morphological data might mislead in those groups for which we depend upon morphology the most. Rhynchonellide brachiopods, with more than 500 extinct genera but only 19 extant genera represented today, provide an opportunity to explore the factors that produce contentious phylogenetic signal across datasets, as previous phylogenetic hypotheses generated from molecular sequence data bear little agreement with those constructed using morphological characters. Using a revised matrix of 66 morphological characters, and published ribosomal DNA sequences, we performed a series of combined phylogenetic analyses to identify conflicting phylogenetic signals. We completed a series of parsimony-based and Bayesian analyses, varying the data used, the taxa included, and the models used in the Bayesian analyses. We also performed simulation-based sensitivity analyses to assess whether the small size of the morphological data partition relative to the molecular data influenced the results of the combined analyses. In order to compare and contrast a large number of phylogenetic analyses and their resulting summary trees, we developed a measure for the incongruence between two topologies, and simultaneously ignore any differences in phylogenetic resolution. Phylogenetic hypotheses generated using only morphological characters differed amongst each other, and with previous analyses, while molecular-only and combined Bayesian analyses produced extremely similar topologies. Characters historically associated with traditional classification in the Rhynchonellida have very low consistency indices on the topology preferred by the combined Bayesian analyses. Overall, this casts doubt on the use of morphological systematics to resolve relationships among the crown rhynchonellide brachiopods. However, expanding our dataset to a larger number of extinct taxa with intermediate morphologies is necessary to exclude the possibility that the morphology of extant taxa is not dominated by convergence along long branches.
Compositional Data Analysis (CoDA) of Clinopyroxene from Abyssal Peridotites
<ol> <li> <p>Additional supporting information includes data, R script, and QGIS file supporting the main text:</p> <p><strong>CSV (Data Set)</strong></p> <ul> <li> <p>residual_abyssal_peridotites.csv: Compilations of residual abyssal peridotites (n = 1162) and depleted MORB-mantle (n = 1)</p> </li> <li> <p>residual_abyssal_peridotites_coda_results.csv: Filtered data and results of PCA and k-means clustering (n = 267)</p> </li> <li> <p>model_cpx.csv: Clinopyroxene compositions obtained by open-system melting model</p> </li> <li> <p>test.csv: csv file for testing new data<br> <br> <strong>R</strong></p> </li> <li> <p>abyssal_cpx_pca.Rproj</p> </li> <li> <p>coda.R: R script implemented in this study</p> </li> <li> <p>test_your_data.R: R script to test new data comparing to abyssal clinopyroxenes</p> <p>and modeled clinopyroxenes</p> <p><strong>QGIS</strong></p> </li> <li> <p>residual_abyssal_peridotites.qgz: QGIS using residual_abyssal_peridotites.csv and residual_abyssal_peridotites_coda_results.csv for Figure 1 and Figure S7</p> </li> <li> <p>color_etopo1_ice_low_modified.tiff: ETOPO1 is a 1 arc-minute global relief model of Earth's surface that integrates land topography and ocean bathymetry from NOAA</p> </li> </ul> </li> </ol> <p> </p> <p>2. Instruction</p> <p>We prepared an R script to compare new (your) clinopyroxene data with clinopyroxene from abyssal peridotites. New data will be plotted using the principal components derived from the natural clinopyroxene database presented in this paper.</p> <p>The procedure is as follows:</p> <p>1. add data below the second row in test.csv<br> * Do not change the file name<br> * Do not change the first row<br> * Add clinopyroxene data (10 elements) and its label replacing under 2nd row * Label of data can be sample name, lithology, locality etc.</p> <p>2. Open abyssal_cpx_pca.Rproj by R studio (double click) 3. Open test_your_data.R (double click)<br> 4. Implement test_your_data.R.</p> <p>To use test_your_data.R, first press cmd+A (ctrl+A) and press Run/cmd+enter (ctrl+enter).</p> <p>5. Results files<br> 5-1. abyssalcpx_vs_test.csv: PC1&PC2 values using abyssal clinopyroxene PC coordinates<br> 5-2. plot1.pdf: abyssal clinopyroxene (cluster) vs. test data plot<br> 5-3. plot2.pdf: modeled clinopyroxene vs. test data plot<br> 5-4. spider_cl1.pdf: PM-normalized trace elements patterns of cluster 1 from abyssal peridotites 5-5. spider_cl2.pdf: PM-normalized trace elements patterns of cluster 2 from abyssal peridotites 5-6. spider_cl3.pdf: PM-normalized trace elements patterns of cluster 3 from abyssal peridotites 5-7. spider_cl4.pdf: PM-normalized trace elements patterns of cluster 4 from abyssal peridotites 5-8. spider_test.pdf: PM-normalized trace elements patterns of new data (your data)<br> 5-9. plot3.pdf: Discrimination diagram for clinopyroxene trace elements compositions. PM normalized Sr/Nd ratio vs. Ce/Yb ratio of clinopyroxenes from abyssal peridotites vs. test data</p>
Funding Covid-19 research: Insights from an exploratory analysis using open data infrastructures - Supplementary material
<p>This dataset contains supplementary material for the paper 'Funding Covid-19 research: Insights from an exploratory analysis using open data infrastructures' by Alexis-Michel Mugabushaka, Nees Jan van Eck, and Ludo Waltman.</p> <ul> <li>supplementary_material_1_dataset.ods: Dataset of Covid-19 publications.</li> <li>supplementary_material_2_sample.ods: Samples of publications used to assess the accuracy of funding data in the different databases.</li> <li>supplementary_material_3_tables_and_figures.ods: Statistics underlying the tables and figures presented in the paper.</li> </ul>
Supporting Information for "Data analysis of the unsteadily accelerating GPS and seismic records at Campi Flegrei caldera from 2000 to 2021". Data Set S1. Extended dataset of all the analyses
<p>This compressed folder contains supporting information related to the Figures in the manuscript: "Data analysis of the unsteadily accelerating GPS and seismic records at Campi Flegrei caldera from 2000 to 2021".</p> <p>Files and folders labeled with G1…n are related to the GPS data, those labeled with H1…n are related to the seismic data.</p> <p>In particular: <br> Subfolder 1_DATA supports Figure 3 – the vertical and the horizontal moduli of ground displacement at all analyzed GPS stations; the logarithmic plots of all seismic events and of their energy. It also shows the complete plot leveling data from 1905 to 2010 (modified from del Gaudio et al., 2010). It also includes Figure 2 and Figure 6a-c.</p> <p>Subfolder 2_AnnualRate supports Figure 4 - the annual rate of the vertical and horizontal moduli of ground displacement at all analyzed GPS stations; the annual rate of all seismic events and of their energy. These detail the 2-year, the 6-month, and the 30-day average results. It also supports Figure 5 with similar data concerning 2018-2020.</p> <p>Subfolder 3_InverseRate supports Figure S3 - the inverse rate of the vertical and the horizontal moduli of ground displacement at all analyzed GPS stations; the inverse rate of all seismic events and of their energy. These detail the 2-year, 6-month, and 30-day average results, including detailed plots of 2018-2020.</p> <p>Subfolder 4_RateChange supports Figure S2 - the daily rate change of the vertical and horizontal moduli of ground displacement at all analyzed GPS stations; the daily rate change of all seismic events and of their energy. These detail the 2-year, the 6-month, and the 30-day average results, including detailed plots of 2018-2020.</p> <p>Subfolder 5_FourierCoef supports Figure 6 - the Fourier spectrum of the vertical and the horizontal moduli of ground displacement at all analyzed GPS stations. These detail the 2-year, 6-month, and 30-day average results obtained in 2000-2020, 2011-2020, 2018-2020. Also, additional plots that detail other combinations of time domain and part of the Fourier spectrum, thus testing the sensitivity of the main harmonics on the time domain selected.</p> <p>Subfolder 6_ FFM_WaitTime supports Figure 11 – waiting time examples based on vertical and horizontal moduli of ground displacement at all analyzed GPS stations; all seismic events, and their energy. These detail the 2-year, 6-month, and 30-day average rate results, and the 10-year, 5-year and 3-year regressions.</p> <p>Subfolder 7_FFM_FailTime also supports Figure 11 – all the results expressed in terms of the failure time t<sub>f</sub> instead of in terms of the waiting time [t<sub>f</sub>(t) - t].</p> <p>Subfolder 8_pFFM_Regression supports Figure 9 - the pFFM examples based on the vertical and the horizontal moduli of ground displacement at all analyzed GPS stations; all seismic events and of their energy. These detail the 2-year, 6-month, and 30-day average rate results, and the 10-year, 5-year and 3-year regression.</p> <p>Subfolder 9_pFFM_Probability supports Figure S4 - pFFM examples based on vertical and horizontal moduli of ground displacement at all analyzed GPS stations; all seismic events, and their energy. These detail the 2-year, 6-month, and 30-day average rates, and the 10-year, 5-year and 3-year regressions.</p> <p>Subfolder 10_BarplotProb supports Figure S5 - results expressed in terms of the mean failure time probability at 2, 5, 10, and 25 years.It also supports Figure S6 - examples based on 6-month, and 30-day average rate results.</p> <p>Subfolder 11_BarplotWaitTime supports Figure S6 - all the results expressed in terms of the waiting time (t<sub>f</sub> – t) barplot. It also includes Figure S5.</p>
Research Data supporting "3D Tomographic Analysis of the Order-Disorder Interplay in the Pachyrhynchus congestus mirabilis Weevil"
<p>This data and the descriptions below should be read in conjunction with the manuscript and “Supporting Info”, both of which may be found at the following DOI: https://doi.org/10.1002/advs.202202145.</p>
Data from: Improving governance outcomes for water quality: insights from participatory social network analysis for chalk stream catchments in England
<p>Globally important chalk streams in England are in poor ecological health, in part due to inadequate water quality. Addressing this issue requires an understanding of the governance systems that surround water quality. The complexity and uncertainty inherent in hydrological systems has led to the emergence of integrated and adaptive forms of governance. In these multi-actor governance systems, the structure of the relationships between actors (the social network) has been shown to affect governance processes and outcomes.</p> <p>Using participatory social network analysis, we mapped and analysed the social networks for the River Test and River Itchen in Hampshire, UK, to identify actors and their roles, determine the network characteristics, and identify interventions to improve governance.</p> <p>Although the results suggest a well connected network of actors from the state, private sector and civil society, we find that decision making is not decentralised. Bureaucratic governance by central state actors dominates. However, trust in these central state actors and private actors in the networks is low, which undermines collaboration and co-ordination in the network.</p> <p>Devolving authority to local actors, building trust in the networks, and improving connections to important actors could help to improve governance outcomes for water quality.</p>
Research Data Supporting "Coupling Lipid Nanoparticle Structure and Automated Single Particle Composition Analysis to Design Phospholipase Responsive Nanocarriers"
<p>Raw research data supporting Barriga, Pence, et al. 2022, Advanced Materials. <a href="https://doi.org/10.1002/adma.202200839">https://doi.org/10.1002/adma.202200839</a></p>
RNAseq data and analysis results from hippocampus of IVH+ICP, IVH, and sham control rats
<p>Supporting data from the RNAseq experiments appearing in the original manuscript "Sustained ICP Elevation Is a Driver of Spatial Memory Deficits After Intraventricular Hemorrhage and Leads to Activation of Distinct Microglial Signaling Pathways" accepted to Translational Stroke Research on June 24, 2022 (published July 12, 2022). Full experimental and technical details are available at <a href="https://doi.org/10.1007/s12975-022-01061-0">https://doi.org/10.1007/s12975-022-01061-0</a>. </p>
cost-benefit analysis data of the Wuxikou water control project
<p>A cost-benefit analysis (CBA) data for evaluating the long-term profitability and economic benefits of Wuxikou Water Control Project.</p>
Technology transfer from Nordic capital parenting companies to Lithuanian and Estonian subsidiaries or joint capital com-panies: the analysis of the obtained primary data
<p>Scientific literature describes various factors influencing knowledge transfer and successful adoption, assimilation, transformation, and exploitation. These four components are mostly related to the absorptive capacity of the company. However, more factors influence both developments of innovations or patents and the lack of ability to use external and internal information (knowledge).<strong> </strong>Using external knowledge is often associated with previous experience or even a point of view towards investment in innovation or developing patents. Thus, the companies might be divided into innovators and imitators. The research addresses several problems (questions). What external factors are influencing knowledge transfer and further development of innovation? What factors are influencing absorptive capacity? What factors are essential in cooperation and knowledge transfer to switch from a linear to a circular economy? To collect data, a computer-assisted telephone interviewing method was used. The survey was addressed to subsidiaries, joint companies, Lithuanian-Nordic, Estonian-Nordic capital companies, or companies in close collaboration with the Nordic countries. 158 companies from Estonia and Lithuania agreed to answer all questions. The survey involves companies of various sizes and ages from different business sectors. Reliability was denoted as Cronbach's alpha has been estimated. KMO test was used to measure whether data is suitable for principal component analysis.</p> <p> Additionally, PCA was performed. PCA reduced the number of variables into an extracted number of components. The separate row of the component defined a linear composite of the component score that would be the expected value of associated variable. The data set may be used to develop interlinkages among the research mentioned above questions, and results of introducing innovation, the company's size, and age might be used as control variables. The article aims to analyze factors determining innovation development and their interlinkages while technology is transferred from Nordic parenting companies to the subsidiaries. The article's results contribute to the interdisciplinary knowledge transfer, innovations, and internationalization field.</p>
Analysis of Data Consistency of Howells' Craniometric Data Sets
<p>Derived data and R scripts for analyzing the data consistency of Howells' craniometric data sets.</p>
Sintering of alumina nanoparticles: comparison of interatomic potentials, molecular dynamics simulations, and data analysis
<p>This is the dataset for the publication in MSMSE 2022 containing all plot scripts and data for reproducing all figures. The dataset is a snapshot of the repository https://gitlab.com/computational-materials-science/public/publication-data-and-code/2022_MSMSE_Roy_et_al_MD-sintering (SHA 7ad2f421deb055f3384c00ba29f2fb1acd0e78ea) that might contain additional/newer data and scripts.</p>
Global offshore wind turbine analysis with Sentinel-1 - supplementary data
<p>Gloabl offshore wind turbine analysis with Sentinel-1 - supplementary data</p> <p>The files are supplementary data of the publication:</p> <p>Global dynamics of the offshore wind energy sector monitored with Sentinel-1: Turbine count, installed capacity and site specifications</p> <p>which is currently under review in the International Journal of Applied Earth Observation and Geoinformation</p> <p>supplementary_data_B_OWT_height_capacity.csv holds 50 pairs of offshore wind turbine hub heights and the corresponding installed capacities along with the offshore wind farm project name, the number of turbines of this wind farm, and the source the information originates from.</p> <p>supplementary_data_B_DeepOWT_1_21_2_plus.geojson is the extended version of the DeepOWT data set (https://zenodo.org/record/5933967) with all of the derived attributes in the respective publication e.g. OWT hub height and installed capacity.</p>
Biotechnology data analysis training with Jupyter Notebooks
<p>Biotechnology has experienced innovations in analytics and data processing. As the volume of data and its complexity grows, new computational procedures for extracting information are developed. However, the rate of change outpaces the adaptation of biotechnology curricula, necessitating new teaching methodologies to equip biotechnologists with data analysis abilities. To simulate experimental data, we created a virtual organism simulator (<em>silvio</em>) by combining diverse cellular and sub-cellular microbial models. With the <em>silvio </em>Python package, we constructed a computer-based instructional workflow to teach growth curve data analysis, promoter sequence design, and expression rate measurement. The instructional workflow is a Jupyter Notebook with background explanations and Python-based experiment simulations combined. The data analysis is either conducted within the Notebook in Python or externally with Excel. This instructional workflow was separately implemented in two distance courses for Master's students in biology and biotechnology with assessment of the pedagogic efficiency. The concept of using virtual organism simulations that generate coherent results across different experiments can be used to construct consistent and motivating case studies for biotechnological data literacy.</p> <p>Here, the supplementary material is provided.</p> <table> <tbody> <tr> <td>2207_BLS-RecExpSim.mbz</td> <td>Moodle backup file for import as new moodle function.</td> </tr> <tr> <td>BLS_RecExpSim_PerformanceEvaluation Rubric.docx</td> <td>Expected learning outcomes with associated performance levels.</td> </tr> <tr> <td>BLS_SurveryQuestions.docx</td> <td>Survey questions to evaluate the educational approach.</td> </tr> <tr> <td>RecExpSim.html</td> <td>Html-Export of the Jupyter Notebook to teach biotechnology data analysis. This only serves as visual impression of the course because the dynamic Python-evaluations are not functioning.</td> </tr> <tr> <td>RecExpSim_Lecture.pdf</td> <td>Static pdf of preparatory lecture to cover the theoretical aspects in the simulations and to get student on comparable level.</td> </tr> <tr> <td>RecExpSim_Lecture.pptx</td> <td>Adjustable pptx of preparatory lecture to cover the theoretical aspects in the simulations and to get student on comparable level.</td> </tr> </tbody> </table> <p> </p> <p> </p>
Some original, intermediate, and result data in the papar entited "Highway marking extraction and degradation analysis by using MLS point clouds"
<p>Some original, intermediate, and result data in the papar entited "Highway marking extraction and degradation analysis by using MLS point clouds"</p>
Data and analysis for the paper "Nonlocal measurement of quasiparticle charge and energy relaxation in proximitized semiconductor nanowires using quantum dots"
<p>This repository contains the raw data and analysis code used to generate the figures in the manuscript <em>Nonlocal measurement of quasiparticle charge and energy relaxation in proximitized semiconductor nanowires using quantum dots</em>. </p> <p><a href="https://journals.aps.org/prb/abstract/10.1103/PhysRevB.106.064503">Link to publication</a></p> <p><a href="https://arxiv.org/abs/2110.05373">Link to arXiv</a></p>
Data for meta-analysis of the soil greenhouse gas emissions
<p><span>Exploring the </span><span>responses of greenhouse gases (GHGs) emissions to land use conversion or reversion is significant for taking effective land use measures to alleviate global warming.</span> <span>A global meta-analysis was conducted to analyze the responses of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) emissions to land use conversion or reversion, and determine their temporal evolution, driving factors and potential mechanisms. Our results showed that CH4 and N2O responded positively to land use conversion while CO2 responded negatively to the changes from natural herb and secondary forest to plantation. By comparison, CH4 responded negatively to land use reversion and N2O also showed negative response to the reversion from agricultural land to forest. The conversion of land use weakened the function of natural forest and grassland as CH4 sink and the artificial nitrogen (N) addition for plantation increased N source for N2O release from soil, while the reversion of land use could alleviate them to some degree. Besides, soil carbon would impact CO2 emission for a long time after land use conversion, and secondary forest reached the methane uptake level similar to that of primary forest after over 40 years. N2O responses had negative relationships with time interval under the conversions from forest to plantation, secondary forest and pasture. In addition, meta-regression indicated that CH4 had correlations with several environmental variables, and carbon-nitrogen ratio had contrary relationships with N2O emission responses to land use conversion and reversion.</span> <span>And the importance of driving factors displayed that CO2, CH4 and </span><span>N2O</span><span> response to land use conversion and reversion were easily affected by NH4+ and soil moisture, </span><span>mean annual temperature</span><span> and NO3-, total nitrogen and </span><span>mean annual temperature</span><span>, respectively.</span> <span>This study would provide enlightenment for scientific land management and reducing of GHG emissions.</span></p>
Oservational data for sfdda nudging analysis in WRF model over China during 2017
<p>Oservational data for sfdda nudging analysis in WRF model over China during 2017.</p>
Raw data: Association and functional analysis of angiotensin-converting enzyme 2 gene genetic variants with the pathogenesis of pre-eclampsia
<p class="MsoNormal"><span>These data were generated to investigate the association and functional analysis of angiotensin-converting enzyme 2 genetic variants with the pathogenesis of pre-eclampsia(PE). This study conducted a case-control study involving 327 PE patients and 591 healthy pregnant women to explore the associations between candidate variants in the ACE2 gene variants and the pathogenesis of PE.This study collected clinical samples and data, and used logistic regression, false positive report rate, multi factor dimension reduction, functional analysis and other analysis methods to process the research data. </span>Potential functional ACE2 gene variants (rs2106809 A>G, rs6632677 G>C, and rs2074192 C>T) were selected and genotyped using kompetitive allele-specific PCR. The strength of the associations between the studied genetic variants and the risk of PE were evaluated using odds ratios (ORs) and corresponding 95% confidence intervals (CIs).<span> Finally,it showed that the rs2106809 A>Gis significantly associated with the risk of PE via individual locus effects and/or complex gene-gene and gene-environment interactions.</span><span> </span></p>
Data from: First application of dental microwear texture analysis to infer theropod feeding ecology
<p>Theropods were the dominating apex predators in most Jurassic and Cretaceous terrestrial ecosystems. Their feeding ecology has always been of great interest, and new computational methods have yielded more detailed reconstructions of differences in theropod feedings behaviour. Many approaches however rely on well-preserved skulls. Dental microwear texture analysis (DMTA) is potentially applicable to isolated teeth, and here employed for the first time to investigate dietary ecology of theropods. In particular, we test whether tyrannosaurids show DMT associated with more hard-object feeding than compared to Allosaurus – which would be a sign for higher levels of osteophagy, as has often been suggested. We find no significant difference in complexity and roughness of enamel surfaces between Herrerasaurus, Allosaurus, and tyrannosaurids, which conflicts with inferences of more frequent osteophagic behaviour in Tyrannosaurus as compared to other theropods. Orientation of wear features reveals a more pronounced bi-directional puncture-and-pull feeding mode in Allosaurus than in tyrannosaurids. Our results further indicate ontogenetic niche shift in theropods and crocodylians, significantly larger height parameters in juvenile theropods might indicate frequent scavenging, resulting in more bone-tooth contact during feeding. Overall, DMTA is found to be very similar between theropods and extant large, broad-snouted crocodylians and shows great similarity in feeding ecology of theropod apex predators throughout the Mesozoic.</p>
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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.