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349 results for “comparative method”
Comparing eDNA collection methods for sampling community composition on marine infrastructure
<p>Raw de-multiplexed data accompanying the manuscript "Comparing eDNA collection methods for sampling community composition on marine infrastructure "Comparing eDNA collection methods for sampling community composition on marine infrastructure".</p>
Supplementary material 2 from: Thiel R, Knebelsberger T (2016) How reliably can northeast Atlantic sand lances of the genera Ammodytes and Hyperoplus be distinguished? A comparative application of morphological and molecular methods. ZooKeys 617: 139-164. https://doi.org/10.3897/zookeys.617.8866
Table S2 : Explanation note: Museum IDs and collection data for specimens of Ammodytes tobianus used for morphological analyses only.
Supplementary material 1 from: Thiel R, Knebelsberger T (2016) How reliably can northeast Atlantic sand lances of the genera Ammodytes and Hyperoplus be distinguished? A comparative application of morphological and molecular methods. ZooKeys 617: 139-164. https://doi.org/10.3897/zookeys.617.8866
Table S1 : Explanation note: Supplementary metadata for specimens used for both morphological and genetic analyses; Museum and Sample IDs are specimen identifiers, BOLD Process IDs are unique codes automatically generated for each record on BOLD, GenBank Accession NOs represent sequence identifiers.
Data and code used for 'Thigh-Worn Accelerometry: A Comparative Study of Two No-Code Classification Methods for Identifying Physical Activity Types'
<p>This repository contains all data necessary to reproduce the results for the manuscript titled 'Thigh-Worn Accelerometry: A Comparative Study of Two No-Code Classification Methods for Identifying Physical Activity Types'.</p> <p> </p> <h2><strong>File structure</strong></h2> <p><strong>- analysis</strong></p> <p>The analysis subfolder contains all R scripts used for the study:</p> <p>1. Sample size estimation<br>2. Synchronisation of the timestamps<br>3. Processing of the raw data<br>4. Calculating the interrater agreement<br>5. Calculating all performance metrics and producing the plots</p> <p>In addition, the two subfolders contain the plots and result tables produced when running the scripts.</p> <p> </p> <p><strong>- data</strong></p> <p>The data folder contains all raw data as well as the processed data. A subfolder for each subject contains the video annotations (.eaf), the raw acceleration data (.csv) and the SENS motion classification data (.csv).</p> <p>The ActiPASS subfolder contains the raw acceleration files in binary file format as well as the ActiPASS output.</p> <p>The shiny subfolder contains the R code used for running the shiny app during data collection as well as the logged data and timestamps.</p> <p> </p> <p><span><strong><span>- documents</span></strong></span></p> <p><span>This folder contains any additional documents used in the study.</span></p> <p> </p> <h2><strong><span>Requirements</span></strong></h2> <p>The data processing and analysis was performed in R (Version 4.3.2). To run the full analysis in R, the following packages need to be installed:</p> <ul> <li>tidyverse</li> <li>xml2</li> <li>lubridate</li> <li>here</li> <li>dygraphs</li> <li>hms</li> <li>irr</li> <li>yardstick</li> <li>cowplot</li> <li>gt</li> </ul>
Database of research methods in the educational field. Bibliometric analysis: comparative study between Scopus and WoS
<p>Data package on research methods in the educational field in the Web of Science and Scopus databases between 2000 and 2023</p>
Comparative study on the effects of various drying methods on antioxidant and sensory profiles of Sambung Nyawa (Gynura precumbens) tea
<p>Comparative study on the effects of various drying methods on antioxidant activity (% DPPH Inhibition), total phenolics, total tannins, total flavonoids, moisture content, color, overall liking, and sensory profiles of Sambung Nyawa (Gynura precumbens) tea.</p>
Towards the conservation of Brazilian legumes: Summary, land cover and use analytics, and a comparative analysis of locations count methods (curated vs. automated [buffer-dissolution])
<p>This dataset presents key findings from the study "<strong>Automating and Enhancing Species Extinction Risk Assessments with Historical Land Use and Land Cover Data</strong>."</p> <p>The file `<em>summary-threatened-legume-species.ods</em>` provides a summary of all threatened species of the Leguminosae family native to Brazil, including IUCN category and criteria, location counts, and the year of the latest assessment, sourced from official records. Additionally, it includes calculated values for Area of Occupancy (AOO) and Extent of Occurrence (EOO), along with trend data indicating natural area change rates (decline [positive number, red] or growth [negative number, green]) within both AOO and EOO. Location counts are further detailed across various buffer radii (1-5 km), utilizing a buffer-dissolution method for automated location counting. Each buffer radius is analyzed to assess AOO and EOO decline, where '1' indicates a species is threatened and '0' indicates it is not. This data provides an efficient method for screening threatened species under criterion B of the IUCN Red List guidelines.</p> <p>The file `<em>overlay-analysis.ods</em>` contains overlay analysis results for AOO and EOO of each species using MapBiomas land use and land cover (LULC) data (specifically MapBiomas Brazil, collection 7.1) from 1985 to 2021, covering all threatened legume species. This file provides both absolute area in square kilometers and percentages for each LULC class. The overlay analysis results support estimates of growth and decline trends for each LULC class.</p> <p>The file `<em>trend-analysis.ods</em>` presents results of annual rate estimates from trend analysis across LULC classes, and including both natural and anthropic groupings. A complete JSON database with p-values and R² values is provided in `<em>trend-analysis.json</em>`.</p> <p>This approach, combining all results for each species in a comprehensive, merged dataset, allows for effective filtering and ranking of the most threatened species as well as identification of their primary threats.</p> <p>We recommend opening the ODS files with LibreOffice, as Microsoft Excel may experience issues parsing decimal formats accurately.</p> <p>More detailed maps and graphs are available at <a title="LULC-MapBiomas-Leguminosae" href="https://github.com/lsbjordao/LULC-MapBiomas-Leguminosae" target="_blank" rel="noopener">https://github.com/lsbjordao/LULC-MapBiomas-Leguminosae</a>.</p>
Data from: Extant-only comparative methods fail to recover the disparity preserved in the bird fossil record
Most extant species are in clades with poor fossil records, and recent studies of comparative methods show have low power to infer even highly simplified models of trait evolution without fossil data. Birds are a well-studied radiation, yet their early evolutionary patterns are still contentious. The fossil record suggests that birds underwent a rapid ecological radiation after the end-Cretaceous mass extinction, and several smaller, subsequent radiations. This hypothesized series of repeated radiations from fossil data is difficult to test using extant data alone. By uniting morphological and phylogenetic data on 604 extant genera of birds with morphological data on 58 species of extinct birds from 50 million years ago, the "halfway point" of avian evolution, I have been able to test how well extant-only methods predict the diversity of fossil forms . All extant-only methods underestimate the disparity, although the ratio of within to between clade disparity does suggest high early rates. The failure of standard models to predict high early disparity suggests that recent radiations are obscuring deep time patterns in the evolution of birds. Metrics from different models can be used in conjunction to provide more valuable insights than simply finding the model with the highest relative fit.
Data from: Phylogenetic comparative methods for evaluating the evolutionary history of function-valued traits
Phylogenetic comparative methods offer a suite of tools for studying trait evolution. However, most models inherently assume fixed trait values within species. Although some methods can incorporate error around species means, few are capable of accounting for variation driven by environmental or temporal gradients, such as trait responses to abiotic stress or ontogenetic trajectories. Such traits, often referred to as function-valued or infinite-dimensional, are typically expressed as reaction norms, dose–response curves, or time plots and are described by mathematical functions linking independent predictor variables to the trait of interest. Here, I introduce a method for extending ancestral state reconstruction to incorporate function-valued traits in a phylogenetic generalized least squares (PGLS) framework, as well as extensions of this method for testing phylogenetic signal, performing phylogenetic analysis of variance (ANOVA), and testing for correlated trait evolution using recently proposed multivariate PGLS methods. Statistical power of function-valued comparative methods is compared to univariate approaches using data simulations, and the assumptions and challenges of each are discussed in detail.
Data from: Seeing is believing? comparing plant-herbivore networks constructed by field co-occurrence and DNA barcoding methods for gaining insights into network structures
Plant-herbivore interaction networks provide information about community organization. Two methods are currently used to document pairwise interactions among plants and insect herbivores. One is the traditional method that collects plant-herbivore interaction data by field observation of insect occurrence on host plants. The other is the increasing application of newly developed molecular techniques based on DNA barcodes to the analysis of gut contents. The second method is more appealing because it documents realized interactions. To construct complete networks, each technique of network construction is urgent to be assessed. We addressed this question by comparing the effectiveness and reliability of the two methods in constructing plant-Lepidoptera larval network in a 50 ha subtropical forest in China. Our results showed that the accuracy of diet identification by observation method increased with the number of observed insect occurrences on food plants. In contrast, the molecular method using three plant DNA markers were able to identify food residues for 35.6% larvae and correctly resolved 77.3% plant (diet) species. Network analysis showed molecular networks had three-fold more unique host plant species but fewer links than the traditional networks had. The molecular method detected plants that were not sampled by the traditional method, e.g., bamboos, bryophytes and lianas in the diets of insect herbivores. The two networks also possessed significantly different structural properties. Our study indicates the traditional observation of co-occurrence is inadequate, while molecular method can provide higher species resolution of ecological interactions.
Comparing Pain Relief Between Two Methods of Freezing Injections in Children Having Their Appendix Removed
ClinicalTrials.gov study NCT06945263. IPD Sharing: NO. Countries: 1. Publications: 17.
Comparing the Effectiveness of Different Appointment Reminder Methods
ClinicalTrials.gov study NCT06767423. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Compare the Efficacy of Different Laryngeal Mask Size Selection Methods in General Anesthesia in Children
ClinicalTrials.gov study NCT03845998. IPD Sharing: NO. Countries: 1. Publications: 2.
Comparing Body Composition Assessment Methods
ClinicalTrials.gov study NCT04610918. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Prospective Study Comparing Methods of Obtainment of Specimen After EUS-FNA in Patients With Peri-pancreatic Mass
ClinicalTrials.gov study NCT01354795. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Comparing Two Methods of Subacromial Space Injection
ClinicalTrials.gov study NCT03692091. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
An Open Label, Blinded Assessor, Trial Comparing Odor Levels Due to Different Hygiene Methods With PrePexTM
ClinicalTrials.gov study NCT02153658. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Comparing Methods for Tracking Health Information at Home After Lung Transplant
ClinicalTrials.gov study NCT00818025. IPD Sharing: Not stated. Countries: 1. Publications: 15.
Comparing Different Methods of Patient Education on Preeclampsia
ClinicalTrials.gov study NCT02765906. IPD Sharing: NO. Countries: 1. Publications: 11.
Comparing Platelet-Rich Plasma (PRP) Centrifugation Methods on Thrombocyte Concentration and Clinical Improvement of Androgenetic Alopecia
ClinicalTrials.gov study NCT05681897. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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.