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349 results for “comparative method”
Data from: Model sensitivity and use of the comparative finite element method in mammalian jaw mechanics: mandible performance in the Gray Wolf
Finite Element Analysis (FEA) is a powerful tool gaining use in studies of biological form and function. This method is particularly conducive to studies of extinct and fossilized organisms, as models can be assigned properties that approximate living tissues. In disciplines where model validation is difficult or impossible, the choice of model parameters and their effects on the results become increasingly important, especially in comparing outputs to infer function. To evaluate the extent to which performance measures are affected by initial model input, we tested the sensitivity of bite force, strain energy, and stress to changes in seven parameters that are required in testing craniodental function with FEA. Simulations were performed on FE models of a Gray Wolf (Canis lupus) mandible. Results showed that unilateral bite force outputs are least affected by the relative ratios of the balancing and working muscles, but only ratios above 0.5 provided balancing-working side joint reaction force relationships that are consistent with experimental data. The constraints modeled at the bite point had the greatest effect on bite force output, but the most appropriate constraint may depend on the study question. Strain energy is least affected by variation in bite point constraint, but larger variations in strain energy values are observed in models with different number of tetrahedral elements, masticatory muscle ratios and muscle subgroups present, and number of material properties. These findings indicate that performance measures are differentially affected by variation in initial model parameters. In the absence of validated input values, FE models can nevertheless provide robust comparisons if these parameters are standardized within a given study to minimize variation that arise during the model-building process. Sensitivity tests incorporated into the study design not only aid in the interpretation of simulation results, but can also provide additional insights on form and function.
Data from: More than skin and bones: comparing extraction methods and alternative sources of DNA from avian museum specimens
Next-generation sequencing has greatly expanded the utility and value of museum collections by revealing specimens as genomic resources. As the field of museum genomics grows, so does the need for extraction methods that maximize DNA yields. For avian museum specimens, the established method of extracting DNA from toe pads works well for most specimens. However, for some specimens, especially those of birds that are very small or very large, toe pads can be a poor source of DNA. In this study, we apply two DNA extraction methods (phenol-chloroform and silica column) to three different sources of DNA (toe pad, skin punch, and bone) from ten historical avian museum specimens. We show that a modified phenol-chloroform protocol yielded significantly more DNA than a silica column protocol (e.g., Qiagen DNeasy Blood & Tissue Kit) across all tissue types. However, extractions using the silica column protocol contained longer fragments on average than those using the phenol-chloroform protocol, likely a result of loss of small fragments through the silica column. While toe pads yielded more DNA than skin punches and bone fragments, skin punches proved to be a reliable alternative source of DNA and might be especially appealing when toe pad extractions are impractical. Overall, we found that historical bird museum specimens contain substantial amounts of DNA for genomic studies under most extraction scenarios, but that a phenol-chloroform protocol consistently provides the high quantities of DNA required for most current genomic protocols.
Maintaining an open landscape: a 15-year multi-site experiment comparing seven management methods for semi-natural grasslands
<p>The data and publications presented here stems from a field trial started in Sweden ca 1972 (at one site still running in 2023). The purpose of the trial was to compare traditional management of semi-natural grasslands by grazing or annual mowing with five alternative management methods. At <strong>e</strong>leven locations in southern Sweden, block experiments were conducted evaluating seven treatments in 5 m * 20 m plots: grazing, annual mowing, annual spring burning, mowing every third year, mechanical removal of woody plants, herbicide control of woody plants, and untreated control. After approximately 13 years, trends for woody plants and species richness, and the occurrence of management-dependent plant species, low-grown species, and pollinator-attracting plant species were analysed. Overall, the annual mowing and grazing treatments resulted in fewer woody plants, the highest species richness, and more management-dependent, low-grown, and pollinator-attracting species. The untreated control plots showed the opposite effect, whereas less intense management (annual burning, mowing every third year, and mechanical and chemical treatments of woody plants) showed mixed and often intermediate effects. </p><p>On this ZENODO-page, one can find all the orginal publication, most in Swqedish. An article summarizing much of results can be found here: <a href="https://doi.org/10.1016/j.gecco.2023.e02721">https://doi.org/10.1016/j.gecco.2023.e02721</a></p>
Stimulus classification with electrical potential and impedance of living plants: comparing discriminant analysis and deep-learning methods
<p>The physiology of living organisms, such as living plants, is complex and particularly difficult to understand on a macroscopic, organism-holistic level. Among the many options for studying plant physiology, electrical potential and tissue impedance are arguably simple measurement techniques that can be used to gather plant-level information. Despite the many possible uses, our research is exclusively driven by the idea of phytosensing, that is, interpreting living plants’ signals to gather information about surrounding environmental conditions. As ready-to-use plant-level physiological models are not available, we consider the plant as a blackbox and apply statistics and machine learning to automatically interpret measured signals. In simple plant experiments, we expose <em>Zamioculcas zamiifolia</em> and <em>Solanum lycopersicum</em> (tomato) to four different stimuli: wind, heat, red light and blue light. We measure electrical potential and tissue impedance signals. Given these signals, we evaluate a large variety of methods from statistical discriminant analysis and from deep learning, for the classification problem of determining the stimulus to which the plant was exposed. We identify a set of methods that successfully classify stimuli with good accuracy, without a clear winner. The statistical approach is competitive, partially depending on data availability for the machine learning approach. Our extensive results show the feasibility of the blackbox approach and can be used in future research to select appropriate classifier techniques for a given use case. In our own future research, we will exploit these methods to derive a phytosensing approach to monitoring air pollution in urban areas.</p> <p>Data repository for our paper " <em>Stimulus classification with electrical potential and impedance of living plants: comparing discriminant analysis and deep-learning methods</em> ", submitted to the journal Bioinspiration & Biomimetics . Please refer to the paper for more information.</p> <p> </p> <p><strong>Contents of this repository</strong></p> <ul> <li><em>mu_interface:</em> Code for our data collection plant experiments, based on Raspberry Pis and the <a href="http://cybertronica.co/?q=products/phytosensor">Cybertronica phytosensing and phytoactuating system</a>.</li> <li><em>SupplementaryCode</em>: Includes the discriminant analysis classifier, raw datasets, calculated features, test-train split and the corresponding code.</li> <li><em>dl-4-tsc:</em> Deep learning framework developed by <a href="https://doi.org/10.1007/s10618-019-00619-1">Fawaz et. al (Deep learning for time series classification: a review)</a> and adapted to our use case. </li> <li><em>DeepClassifier: </em>Trained deep learning time series classifier.</li> <li><em>classification_results.xlsx: </em>Overview of the results from the deep learning framework (accuracy, precision, recall, training time, confusion matrix) and the achieved accuracies using discriminant analysis with sequential forward section (further evaluation metrics of the discriminant analysis can be found in SupplementaryCode.</li> </ul>
Figure 2 in Comparing the effectiveness of pitfall traps and active sampling methods for ants and spiders in a Chromolaena odorata invaded site
Figure 2. Ant species richness collected using active and passive sampling techniques in Buffelsdraai Conservancy [AHC = aerial hand collection above the knee; AHC CRYPTIC = aerial hand collection below the knee cryptic; AHC OBV = aerial hand collection below the knee noticeable or non-cryptic; BB = vegetation beating].
Data from: A novel Bayesian method for inferring and interpreting the dynamics of adaptive landscapes from phylogenetic comparative data
Our understanding of macroevolutionary patterns of adaptive evolution has greatly increased with the advent of large-scale phylogenetic comparative methods. Widely used Ornstein-Uhlenbeck (OU) models can describe an adaptive process of divergence and selection. However, inference of the dynamics of adaptive landscapes from comparative data is complicated by interpretational difficulties, lack of identifiability among parameter values and the common requirement that adaptive hypotheses must be assigned a priori. Here we develop a reversible-jump Bayesian method of fitting multi-optima OU models to phylogenetic comparative data that estimates the placement and magnitude of adaptive shifts directly from the data. We show how biologically informed hypotheses can be tested against this inferred posterior of shift locations using Bayes Factors to establish whether our a priori models adequately describe the dynamics of adaptive peak shifts. Furthermore, we show how the inclusion of informative priors can be used to restrict models to biologically realistic parameter space and test particular biological interpretations of evolutionary models. We argue that Bayesian model-fitting of OU models to comparative data provides a framework for integrating of multiple sources of biological data–such as microevolutionary estimates of selection parameters and paleontological timeseries–allowing inference of adaptive landscape dynamics with explicit, process-based biological interpretations.
Figure 4 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
Figure 4 - Plot of all analysed Ammodytes and Hyperoplus specimens onto the first and second discriminant functions based on a set of 19 morphometric characters. Circles include 95% of specimens in each species.
Figure 3 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
Figure 3 - Plot of all analysed Ammodytes and Hyperoplus specimens onto the first and second discriminant functions based on a set of eight meristic characters. Circles include 95% of specimens in each species.
Figure 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
Figure 2 - Radiograph of Common sand eel Ammodytes tobianus (Linnaeus, 1758) indicating the meristic characters evaluated from X-ray pictures. Depicted specimen: ZMH 26098-3, standard length 128.1 mm.
Figure 5 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
Figure 5 - NJ dendrogram based on K2P pairwise genetic distances. Values at nodes indicate the result of the bootstrap test (10.000 pseudo replicates). Only values ≥ 50 are shown. For Ammodytes tobianus (grey box) and Hyperoplus lanceolatus all analysed individuals are shown. In case of Ammodytes marinus and Hyperoplus immaculatus the number of specimens is given in brackets.
Comparing Between XP Endo Finisher and Conventional Irrigation Method On Post-Operative Flare Ups In Necrotic Teeth
ClinicalTrials.gov study NCT02952326. IPD Sharing: NO. Countries: 0. Publications: 2.
This Study Compares Two Different Ways of Cleaning and Shaping Root Canals During Root-canal Treatment: the Step-down Technique and the Step-back Technique. Iu Want to Find Out Which Method Causes Les
ClinicalTrials.gov study NCT07290192. IPD Sharing: NO. Countries: 1. Publications: 0.
Hernia Prevention. Effectiveness of Reinforced Tension Line (RTL) Technique Compared With the Conventional Method
ClinicalTrials.gov study NCT02136628. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Measuring Cardiovascular Performance and Blood Flow Using Common But Never Compared Methods.
ClinicalTrials.gov study NCT04553484. IPD Sharing: NO. Countries: 1. Publications: 0.
Comparing Jaw Tracking and Traditional Methods for Measuring Bite Accuracy in Patients With Teeth
ClinicalTrials.gov study NCT07203703. IPD Sharing: YES. Countries: 0. Publications: 6.
Comparing Through-the-Needle With Suture-Method Catheter Designs for Popliteal Nerve Blocks
ClinicalTrials.gov study NCT03442036. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Comparing Hearing Aid Fitting Methods in Blast-exposed Veterans
ClinicalTrials.gov study NCT06309264. IPD Sharing: YES. Countries: 1. Publications: 0.
Comparative Analysis of SUV Measurements Using Different Correction Methods in Oncological PET/CT Imaging.
ClinicalTrials.gov study NCT07306975. IPD Sharing: YES. Countries: 0. Publications: 2.
Pilot Study Comparing the Effectiveness of Two Different Methods of Acoustic Stimulation
ClinicalTrials.gov study NCT03600194. IPD Sharing: NO. Countries: 1. Publications: 0.
A Comparative Assessment of Orthodontic Treatment Outcomes Using the Quantitative Light-Induced Fluorescence Method
ClinicalTrials.gov study NCT03738839. IPD Sharing: UNDECIDED. Countries: 0. Publications: 8.
ScienceDex guides
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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.