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6,467 results for “process”
Online Appendix and Cetacean Datasets for: The Occurrence Birth-Death Process for combined-evidence analysis in macroevolution and epidemiology
<p>Phylodynamic models generally aim at jointly inferring phylogenetic relationships, model parameters, and more recently, the number of lineages through time, based on molecular sequence data. In the fields of epidemiology and macroevolution these models can be used to estimate, respectively, the past number of infected individuals (prevalence) or the past number of species (paleodiversity) through time. Recent years have seen the development of "total-evidence" analyses, which combine molecular and morphological data from extant and past sampled individuals in a unified Bayesian inference framework. Even sampled individuals characterized only by their sampling time, i.e. lacking morphological and molecular data, which we call occurrences, provide invaluable information to reconstruct the past number of lineages.</p> <p>Here, we present new methodological developments around the Fossilized Birth-Death Process enabling us to (i) incorporate occurrence data in the likelihood function; (ii) consider piecewise-constant birth, death and sampling rates; and (iii) reconstruct the past number of lineages, with or without knowledge of the underlying tree. We implement our method in the RevBayes software environment, enabling its use along with a large set of models of molecular and morphological evolution, and validate the inference workflow using simulations under a wide range of conditions.</p> <p>We finally illustrate our new implementation using two empirical datasets stemming from the fields of epidemiology and macroevolution. In epidemiology, we infer the prevalence of the COVID-19 outbreak on the Diamond Princess ship, by taking into account jointly the case count record (occurrences) along with viral sequences for a fraction of infected individuals. In macroevolution, we infer the diversity trajectory of cetaceans using molecular and morphological data from extant taxa, morphological data from fossils, as well as numerous fossil occurrences. The joint modeling of occurrences and trees holds the promise to further bridge the gap between between traditional epidemiology and pathogen genomics, as well as paleontology and molecular phylogenetics.</p>
CESM model results - Effect of nitrogen limitation and soil processes on Holocene greening of the Sahara
<p>The model results are made in EAPL, Yonsei University, South Korea (https://eapl.yonsei.ac.kr). The purpose of the simulations were to find out the effect of nitrogen limitation and soil processes on Holocene greening of the Sahara. CESM model v1.2 was used for this simulation.</p>
Processed data and models in support of manuscript "Deciphering the state of the lower crust and upper mantle with multi-physics inversion"
<p>Data and model files in original format used in the manuscript "Deciphering the state of the lower crust and upper mantle with multi-physics inversion". These files are accompanied by a set of python scripts to reproduce several of the figures in the Manuscript. Please refer to the Manuscript and the included files for further information on data origin and how to use the scripts. A link will be added upon acceptance.</p>
Supplementary Data for "Sequencing the Pandemic: Rapid and High-Throughput Processing and Analysis of COVID-19 Clinical Samples for 21st Century Public Health"
<p>Supplementary material for F1000 methods manuscript. Includes raw sequencing metrics for two COVID sequencing methodologies, as well as a complete cost breakdown for each methodology.</p>
Compositional discovery of architecture-aware and sound process models from event logs of multi-agent systems: experimental data.
<p>This repository contains the experimental data used for the evaluation of the compositional approach to the discovery of process models from event logs of multi-agent systems, where agents interact according to specific patterns of synchronous and asynchronous interactions.</p> <p>According to the experiment plan, there is the folder for each interface pattern containing:</p> <ol> <li>The reference model (Petri net encoded in PNML-file)</li> <li>The event log obtained by simulating the behavior of the reference model (XES-file)</li> <li>The model discovered directly from the generated event log (Petri net encoded in PNML-file)</li> <li>The model discovered by composing the agent model w.r.t. the interface pattern (Petri net encoded in PNML-file)</li> </ol>
Copernicus Global Land Service: Global biome cluster layer for the 100m global land cover processing line
<p><strong>A map of 73 global biome clusters, geographic areas that were grouped to optimize the global 100m land cover processing.</strong></p> <p>In order to group Earth Observation data for faster processing or adaptation of algorithms to specific regions, the 100m global land cover (CGLS-LC100) algorithm uses a Global Biome Cluster layer. The term <em>biome cluster</em> hereby refers to a geographic area which has similar bio-geophysical parameters and, therefore, can be grouped for processing. In other words, the biome cluster layer can be seen as an ecological regionalisation which outlines areas of similar environmental conditions, ecological processes, and biotic communities (Coops et al., 2018). There are already several global regionalisation layers existing, e.g. Ecoregions 2017 global dataset (Dinerstein et al., 2017), Geiger-Koeppen global ecozones after Olofsson update (Olofsson et al., 2012), Global ecological zones for FAO forest reporting with update 2010 (FAO, 2012). But several tests in the CGLS-LC100 workflow have shown that the existing layers did not provide the required global and continental classification accuracy. These findings go along with Coops et al. (2018) who stated that "<em>Most regionalisations are made based on subjective criteria, and cannot be readily revised, leading to outstanding questions with respect to how to optimally develop and define them."</em></p> <p>Therefore, we decided to develop a customized ecological regionalisation layer which performs best with the given PROBA-V remote sensing data and the specifications of the CGLS-LC100 product. It groups spectral similar areas and helps to optimize the later classification/regression to regional patterns. Input into the layer creation were well-known existing datasets which were combined, re-grouped and advanced based on prior CGLS-LC100 classification results and local mapping knowledge of the workflow developer. To ensure that this layer is clearly separable from other existing regionalisations and not mistakenly interpreted as an eco-region layer, we decide to call it <em>biome clusters</em> <em>layer</em>.</p> <p>The following steps outline the global biome clusters layer generation:</p> <ul> <li>Spatial union of Ecoregions 2017 dataset (Dinerstein et al., 2017), Geiger-Koeppen dataset (Olofsson et al., 2012) and Global FAO eco-regions datasets (FAO, 2012);</li> <li>Regrouping and dissolving by using experience from first global CGLS-LC100 mapping results and subjective mapping experience of the developer;</li> <li>Refinement of the biome clusters in the High North latitudes via incorporation of a Global tree-line layer (Alaska Geobotany Center, 2003);</li> <li>Manual improvement of borders between biome clusters to reduce classification artefacts by using a DEM and mapping experience from previous projects and continental test runs;</li> <li>Usage of a global land/sea mask, the Sentinel-2 tiling grid and PROBA-V imaging extent to extend the borders of the biome clusters into the sea to make sure that also small islands on the coastline are correctly processed.</li> </ul> <p>When developing a regionalisation, the definition of the clusters and the boundaries that delineate them in time and space is the key challenge. Overall, the map distinguishes <strong>73 global biome clusters</strong>.</p>
All data of the manuscript "A self-sustained charge neutrality lightning model containing the channel decay and reactivation process" submitted to Geophysical Research Letters
<p>The data supports the manuscript entitled "A self-sustained charge neutrality lightning model containing the channel decay and reactivation process”. Microsoft Notepad can open the *.txt files, they contain the channel information of two intracloud flashes (IC1 and IC2) and the channel elctrical parameters at the first fork of positive or negative leader channels. A normal video player software can open Movies S1.avi, and it shows the entire development process of IC1 discharge.</p> <p>The data can be used freely for scientific purposes with the appropriate citation.</p>
Data of Self-Weight Consolidation Process of Water-Saturated Deltas on Mars and Earth
<p><strong>Data of the paper "Self-Weight Consolidation Process of Water-Saturated Deltas on Mars and Earth".</strong> This dataset includes five tables. <strong>Table S1</strong> is the original data of the measurements of the moisture content <em>w</em><sub>0</sub>, <strong>Table S2</strong> is the original data of the pycnometer test, which was conducted to obtain the specific gravity <em>G</em><sub>s</sub> of our samples, <strong>Table S3</strong> is the original data of the consolidation experiments, <strong>Table S4</strong> is the original data of the permeability experiments, and <strong>Table S</strong><strong>5</strong> is the martian global delta relief obtained by us based on MOLA data, which is used as the maximum thickness of a delta.</p> <p><strong>Table S1.</strong> The original data of the measurements of the moisture content <em>w</em><sub>0</sub>. The initial void ratio is calculated by equation (1). <em>A'</em> is the inner area of the consolidation container.</p> <p><strong>Table S2.</strong> The original data of the pycnometer test, which was conducted to obtain the specific gravity <em>G</em><sub>s</sub> of our samples. The specific gravity <em>G</em><sub>s </sub>can be derived from <em>m</em><sub>d</sub><em>G</em><sub>wT</sub> /(<em>m</em><sub>bw+</sub><em>m</em><sub>d+</sub><em>m</em><sub>bws</sub>), where <em>m</em><sub>d </sub>is the samples’ dry mass, <em>m</em><sub>bw </sub>is the total mass of the pycnometer and water,<em> m</em><sub>bws </sub>is the total mass of the pycnometer, water and samples, and <em>G</em><sub>wT</sub> is the specific gravity of pure water at<em> T </em>℃.</p> <p><strong>Table S3.</strong> The original data of consolidation experiments of our samples. The void ratio is calculated by equation (2).</p> <p><strong>Table S4. </strong>The original data of permeability experiments of our samples. The hydraulic conductivity <em>K </em>was calculated by equations (3) and (4). The inner area of the consolidation container is 30 cm<sup>2</sup>, the cross-sectional area<em> a' </em>of the water pipe is 0.89286 cm<sup>2</sup>, and the seepage path length <em>L</em> equals the sample initial height <em>h</em><sub>0</sub> minus the accumulated height <em>Σ</em>Δ<em>h</em><sub>i</sub>. <em>t</em>1 and <em>t</em>2<sub> </sub>are the first and the second test results of time-taken for water dropping from <em>H</em><sub>1</sub> to <em>H</em><sub>2</sub>, respectively. <em>t</em> is the average of <em>t</em>1 and <em>t</em>2. <em>T</em><em>’</em> is the temperature during the experiments. Note: we only test the <em>T</em><em>’</em> of the third group and here we used the average of <em>T’ </em>(=12.5℃) to represent the temperature of all three parallel groups during the experiments. It’s acceptable because <em>T’</em> varies slightly throughout the experiments, whose fluctuations hardly affect the order of magnitude of the hydraulic conductivity <em>K</em>. The seepage velocity <em>v</em>=<em>Q</em>/<em>A’t</em>, in which <em>Q</em> is the volume of water that seeps out of the samples.</p> <p><strong>Table S5.</strong> The delta relief of a delta. The locations of martian deltas are based on the database of Wilson et al. (2021)</p> <p> </p> <p> </p>
Patient-specific processed data, code and visualisations for "Fluctuations in EEG band power at subject-specific timescales over minutes to days explain changes in seizure evolutions"
<p>Processed data and code for reproducing the main results and figures of the paper "<strong>Fluctuations in EEG band power at subject-specific timescales over minutes to days explain changes in seizure evolutions</strong>".</p> <p>We analysed publicly available data from subjects with drug-resistant focal epilepsy. A total of 2656 hours of long-term intracranial electroencephalography (iEEG) from 18 subjects was obtained using the "The SWEC-ETHZ iEEG Database and Algorithms" (available at <a href="http://ieeg-swez.ethz.ch">http://ieeg-swez.ethz.ch</a>) (Burrello et al., 2019).</p> <p>Reference<br> A. Burrello, L. Cavigelli, K. Schindler, L. Benini, A. Rahimi, <strong>‘‘</strong>Laelaps: An Energy-Efficient Seizure Detection Algorithm from Long-term Human iEEG Recordings without False Alarms<strong>’’</strong> <em>in proceedings of the</em> <em>ACM/IEEE Design, Automation, and Test in Europe Conference (DATE)</em>, Florence, Italy, March 25-29, 2019. </p>
Hubble eXtreme Deep Field that has been clipped and processed for ML applications
<p>This is a set of FITS files downloaded from https://archive.stsci.edu/ .</p> <p> </p> <p>The *.npy file has been clipped to the 99.99th percentile and then minmax normalised along each channel.</p>
Pitfalls of ignoring trait resolution when drawing conclusions about ecological processes
<p><strong>Aim:</strong> Understanding how ecological communities are assembled remains a grand challenge in ecology with direct implications for charting the future of biodiversity. Trait-based methods have emerged as the leading approach for quantifying functional community structure (convergence, divergence) but their potential for inferring assembly processes rests on accurately measuring functional dissimilarity among community members. Here, we argue that trait resolution (from finest-resolution continuous measurements to coarsest-resolution binary categories) remains a critically overlooked methodological variable, even though categorical classification is known to mask functional variability and inflate functional redundancy among species or individuals.</p> <p><strong>Innovation:</strong> We present the first detailed predictions of trait resolution biases and demonstrate, with simulations, how the distortion of signal strength by increasingly coarse-resolution traits can fundamentally alter functional structure patterns and the interpretation of causative ecological processes (e.g., abiotic filters, biotic interactions). We show that coarser trait data impart different impacts on the signals of divergence and convergence, implying that the role of biotic interactions may be underestimated when using coarser traits. Furthermore, in some systems, coarser traits may overestimate the strength of trait convergence, leading to erroneous support for abiotic processes as the primary drivers of community assembly or change.</p> <p><strong>Main conclusions:</strong> Inferences of assembly processes must account for trait resolution to ensure robust conclusions, especially for broad-scale studies of comparative community assembly and biodiversity change. Despite recent improvements in the collection and availability of trait data, great disparities continue to exist among taxa in the number and availability of continuous traits, which are more difficult to acquire for large numbers of species than coarse categorial assignments. Based on our simulations, we urge the consideration of trait resolution in the design and interpretation of community assembly studies and suggest a suite of practical solutions to address the pitfalls of trait resolution biases.</p>
Process Controls on Flood Seasonality in Brazil - link to data and plots
<p>This data set and plots of circular histograms accompany the paper "Process Controls on Flood Seasonality in Brazil" at Geophysical Research Letters (<a href="https://doi.org/10.1029/2021GL096754">https://doi.org/10.1029/2021GL096754</a>). In this paper, we investigate the relationship between the seasonality of floods, maximum annual rainfall, and maximum annual soil moisture data of 886 basins in Brazil for 1980-2015 to shed light on process controls of flood generation.</p>
Age, sex, length (mm), weight (g), and plasma sex steroid concentrations (ng/ml) of greater amberjack Seriola dumerili reared in sea cages during the process of sex differentiation
<p>The dataset contains an excel file with the age, sex, total length (mm), wet weight (g) and plasma concentrations (ng/ml) of the following sex steroids, measured with the use of liquid chromatography/tandem mass spectrometry (LC-MS/MS): adrenosterone (Ad), androstenedione (Δ4), 11-ketotestosterone (11ΚΤ), testosterone (Τ), estradiol (Ε2), progesterone (P4) and 17,20β-dihydroxy-4-pregnen-3-one (17,20βP).</p>
Rupture Process of the 2017 Mw 6.3 Earthquake in Jinghe, Northwest China Constrained by GNSS, InSAR and teleseismic waveforms
<p>This dataset include:</p> <p>1. Slip model of 2017 Mw 6.3 Jinghe earthquake invert with GNSS, InSAR and teleseismic waveforms.</p> <p>2. InSAR LOS offsets caused by the mainshock (The file named by sar.static )</p> <p>3. Aftershocks locations relocated with hypoDD</p> <p> </p>
CSV files and R script: writing process data of typed picture description by 15 cognitively impaired patients and 15 healthy controls
<p>Writing process data of 15 cognitively impaired patients and 15 age- and gender-matched healthy controls were obtained. Each of them completed two typed picture description tasks that were logged with Inputlog, a keystroke logging tool. Variables included time on task; number of characters, pauses and Pause-bursts per minute; proportion of pause time; duration of Pause-bursts; and pause time between words. For pause time between words, also the effect of pauses preceeding specific word categories was analyzed.</p> <p>The data were used to explore if the observation of writing behavior can assist in the screening and follow-up of mild cognitive impairment (MCI) and mild dementia due to Alzheimer’s disease (AD). This data set contains the CSV files that were used for the analyses and the corresponding R script.</p>
ATAC-seq processing resources for the GRCh38 (hg38) assembly of the human genome
<p>A collection of publicly available, but preprocessed, reference data for the analysis of ATAC-seq samples using the GRCh38 (hg38) assembly of the human genome using the <a href="https://doi.org/10.5281/zenodo.6323634">Ultimate ATAC-seq Data Processing & Analysis Pipeline</a> (details in the documentation on GitHub).</p>
Supplementary GIS data - Potential and implications of automated pre-processing of LiDAR-based digital elevation models for large-scale archaeological landscape analysis
<p>A supplementary dataset related to the paper discussing preparation of a digital elevation model derived from DMR 5G (LiDAR-based DEM of the Czech Republic) cleaned of modern artificial features. It includes data used as a clipping mask and data produced during the testing phase.</p> <p>Contents:</p> <ul> <li>..\clipping_buffers.gdb\ - Clipping buffers based on ZABAGED dataset used for masking the original data stored as ESRI geodatabase.</li> <li>..\drainages\ - Drainages with Strahler order higher than four (potential watercourses) for the original and filtered DEMs. <ul> <li>drainages_filtered - Drainges identified in the filtered DEM stored as GeoTIFF.</li> <li>drainages_original - Drainges identified in the original DEM stored as GeoTIFF. </li> </ul> </li> <li>..\LSC\ - Locations with significant land surface curvature for the original and filtered DEMs. <ul> <li>LSC_filtered - Significant LSC identified in the filtered DEM stored as GeoTIFF. </li> <li>LSC_original - Significant LSC identified in the original DEM stored as GeoTIFF. </li> </ul> </li> <li>..\visibility\ - Viewsheds computed over the original and filtered DEMs. <ul> <li>Libice\ - Sample viewsheds computed for the early medieval hillfort of Libice. <ul> <li>Libice_visibility_filtered - Viewshed based on the filtered DEM stored as GeoTIFF. </li> <li>Libice_visibility_original - Viewshed based on the original DEM stored as GeoTIFF. </li> <li>observer_points - Observer points used for calculating the viewsheds.</li> </ul> </li> <li>regular_grid\ - Cumulative viewsheds calculated for regularly spaced points in a 10 x 10 km grid with a visibility radius of 5 km and an observer height of 2 m; a total of 574 viewsheds. <ul> <li>visibility_filtered - Cumulative viewshed for the filtered DEM stored as GeoTIFF.</li> <li>visibility_original - Cumulative viewshed for the original DEM stored as GeoTIFF. </li> <li>visibility_test_buffers - Buffers used for the viewshed calculations stored as ESRI shapefile.</li> <li>visibility_test_observers - Observer points used for the viewshed calculations stored as ESRI shapefile.</li> </ul> </li> </ul> </li> </ul> <p> </p> <p>Preprint version of the related paper:</p> <p>Novák, David and Pružinec, Filip, Potential and Implications of Automated Pre-Processing of Lidar-Based Digital Elevation Models for Large-Scale Archaeological Landscape Analysis. Available at SSRN: <a href="https://ssrn.com/abstract=4063514">https://ssrn.com/abstract=4063514</a></p>
Microassembly process - pick and release of ø25µm stainless balls - H2020 UWIPOM2 PROJECT
<p>Microassembly process - Pick and release of ø25µm stainless balls</p> <p>https://www.youtube.com/watch?v=xCu9CqVDltk&ab_channel=Prof.Efr%C3%A9nD%C3%ADezJim%C3%A9nez-UniversidaddeAlcal%C3%A1</p>
Data and code from: Geomorphological processes shape plant community traits in the Arctic
<p><strong>Aim</strong></p> <p>Geomorphological processes profoundly affect plant establishment and distributions, but their influence on functional traits is insufficiently understood. Here, we unveil trait-geomorphology relationships in Arctic plant communities.</p> <p> </p> <p><strong>Location</strong></p> <p>High-Arctic Svalbard, low-Arctic Greenland, and sub-Arctic Fennoscandia.</p> <p> </p> <p><strong>Time period</strong></p> <p>2011-2018</p> <p> </p> <p><strong>Major taxa studied</strong></p> <p>Vascular plants</p> <p> </p> <p><strong>Methods</strong></p> <p>We collected field-quantified data on vegetation, geomorphological processes, microclimate, and soil properties from 5280 plots and 200 species across the three Arctic regions. We combined these data with database trait records to relate local plant community trait composition to dominant geomorphological processes of the Arctic, namely cryoturbation, deflation, fluvial processes, and solifluction. We investigated the relationship between plant functional traits and geomorphological processes using hierarchical generalised additive modelling.</p> <p> </p> <p><strong>Results</strong></p> <p>Our results demonstrate that community-level traits are related to geomorphological processes, with cryoturbation most strongly influencing both structural and leaf economic traits. These results were consistent across regions, suggesting a coherent biome-level trait response to geomorphological processes.</p> <p> </p> <p><strong>Main conclusions</strong></p> <p>The results indicate that geomorphological processes shape plant community traits in the Arctic. We provide empirical evidence for the existence of generalisable relationships between plant functional traits and geomorphological processes. The results indicate that the relationships are consistent across these three distinct tundra regions and that geomorphological processes should be considered in future investigations of functional traits.</p> <p> </p> <p>Kemppinen, Niittynen, Happonen, le Roux, Aalto, Hjort, Maliniemi, Karjalainen, Rautakoski & Luoto. Provisionally accepted. Geomorphological processes shape plant community traits in the Arctic. Global Ecology and Biogeography.</p> <p>These are the data and code from Kemppinen et al. (Provisionally accepted).</p>
Spontaneous parthenogenesis in the parasitoid wasp Cotesia typhae: low frequency anomaly or evolving process?
<p>Raw data linked to the manuscript, including phenotyping and genotyping results for all Cotesia typhae females analyzed in this study.</p>
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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.