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50 results for “experimental methods”
Data for: Experimental and numerical methods to ensure comprehensible and replicable electrical stimulation experiments
<p>Replication data for "Experimental and numerical methods to ensure comprehensible and replicable electrical stimulation experiments".</p>
Novel Experimental Methods to Investigate the Effects of Plant Phytoliths on Tooth Enamel Wear
<p>Data of: Novel Experimental Methods to Investigate the Effects of Plant Phytoliths on Tooth Enamel Wear.</p>
Dataset supporting the manuscript "Establishment of a Newborn Lamb Gut-Loop Model to Evaluate New Methods of Enteric Disease Control and Reduce Experimental Animal Use" (Baillou, Kasal-Hoc et al, Veterinary Sciences, 2021)
<p>These are the data supporting reported results in the publication "Establishment of a Newborn Lamb Gut-Loop Model to Evaluate New Methods of Enteric Disease Control and Reduce Experimental Animal Use" (Baillou, A, Kasal-Hoc N. et al, Veterinary Sciences, 2021). DOI not yet available.</p>
Experimental and observation data used for the paper entitled "Method to constrain the complex refractive index of ambient black carbon aerosol from their observed distribution of the complex forward-scattering amplitude"
<p>The complex forward-scattering amplitude data used for Figure 6 and 7 of the paper entitled "Method to constrain the complex refractive index of ambient black carbon aerosol from their observed distribution of the complex forward-scattering amplitude" by N. Moteki et al.</p>
Data: Complementary Experimental Methods to Obtain Thermodynamic Parameters of Protein Ligand Systems
<p>Data, which are presented in the following publication: Mohanakumar, Shilpa; Lee, Namkyu; Wiegand, Simone (2022): Complementary Experimental Methods to Obtain Thermodynamic Parameters of Protein Ligand Systems. In: International Journal of Molecular Sciences 23 (22), S. 14198. DOI: 10.3390/ijms232214198.</p>
Experimental and analytical methods for thermal infrared spectroscopy of complex dust coatings in a simulated asteroid environment
<p>The spectral and thermophysical effects of thin-continuous, macro-discontinuous, and micro-discontinuous dust cover are not understood and require relevant laboratory analyses to be deconvolved in an orbital setting. We have constructed a custom environment chamber that enables the controlled deposition of size-regulated dust particles in coatings with varying continuity and thickness. TIR spectra of coated substrates acquired in a simulated asteroid environment (SAE) are used to investigate the extent to which dust coatings of different thicknesses and arrangements contribute to orbital spectral signatures of airless body surfaces. </p> <p>TIR (5-50 𝜇m) spectra of each sample are acquired under SAE conditions using the Planetary and Asteroid Regolith Spectroscopy Environmental Chamber (PARSEC) at Stony Brook University. PARSEC is designed to measure samples under environmental conditions typical of airless bodies. The chamber houses a sample wheel with six sample cups and a calibration target coated with Nextel black. There is also a black body target under the wheel. All sample cup and black body targets can be individually heated and rotated into position from outside of the chamber. Temperature is controlled through two Eurotherm Mini8 Loop Controllers and managed on an in-lab computer with the Eurotherm iTools interface. Samples are illuminated at 55° incidence by a quartz halogen lamp connected to a Bentham 610 power source. Surrounding the sample wheel is a cold shield actively cooled by the input of liquid nitrogen into an internal dewar to reach temperatures < 150 K. Pressure in the chamber is controlled by a Pfeiffer HiCube turbo vacuum pump to reach 10<sup>-6</sup> mbar. In line with the vacuum chamber is a pressure regulated tank of N<sub>2</sub> used for purging and ambient pressure measurements. The PARSEC chamber is connected to a Nicolet 6700 FTIR spectrometer equipped with a Cesium Iodide (CsI) beamsplitter and a deuterated L-alanine doped triglycine sulfate (DLaTGS) detector with a CsI window. The spectrometer is actively purged with air scrubbed of CO<sub>2</sub> and water vapor and sealed at the interface with PARSEC. A total of 256 scans from 2,200 to 400 cm<sup>-1</sup> are integrated for a 10-minute measurement period, using a spectral sampling of 2 cm<sup>-1</sup>. During each experimental session, all samples and the black body are measured under SAE conditions. Calibration measurements of the blackbody target at 70 and 100°C are acquired, then the integrated sample cup heaters and solar lamp are adjusted to achieve the desired sample brightness temperature of 80°C. Samples are allowed to reach temperature under the lamp for more than 45 minutes until the spectral maximum stabilizes and the calculated brightness temperature at the CF is within ~10 K of the target 353 K. This procedure is repeated for all samples while ensuring the chamber temperature remains stable under 150 K through continued addition of liquid nitrogen. The Radiance-to-emissivity conversion method used determines the maximum brightness temperature between 500 and 1700 cm-1 and divides the radiance by a Planck function of the same temperature. This assures the maximum brightness temperature is the kinetic temperature of the same, and its emissivity is unity at the frequency of this maximum. This dataset includes 15 different samples acquired under SAE and ambient pressure/temperature conditions. These samples range in layer thickness and continuity and are intended to test and demonstrate the range of the coating process.</p>
Experimental Results for the AAAI 2023 Paper "On Total-Order HTN Plan Verification with Method Preconditions -- An Extension of the CYK Parsing Algorithm"
<p>This is the collection of the experimental results reported in the paper "On Total-Order HTN Plan Verification with Method Preconditions -- An Extension of the CYK Parsing Algorithm". For a detailed explanation, please read the README.md file.</p>
Data from: Zooming in on mechanistic predator-prey ecology: integrating camera traps with experimental methods to reveal the drivers of ecological interactions
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Data from: An experimental evaluation of the effects of geolocator design and attachment method on between-year survival on whinchats Saxicola rubetra
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Data from: Head-to-head comparison of three experimental methods of quantifying competitive fitness in C. elegans
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Data from: Effect of detection heterogeneity in occupancy-detection models: an experimental test of time-to-first-detection methods
Imperfect detection can bias estimates of site occupancy in ecological surveys but can be corrected by estimating detection probability. Time-to-first-detection (TTD) occupancy models have been proposed as a cost-effective survey method that allows detection probability to be estimated from single site visits. Nevertheless, few studies have validated the performance of occupancy-detection models by creating a situation where occupancy is known, and model outputs can be compared with the truth. We tested the performance of TTD occupancy models in the face of detection heterogeneity using an experiment based on standard survey methods to monitor koala (Phascolarctos cinereus) populations in Australia. Known numbers of koala faecal pellets were placed under trees, and observers, uninformed as to which trees had pellets under them, carried out a TTD survey. We fitted five TTD occupancy models to the survey data, each making different assumptions about detectability, to evaluate how well each estimated the true occupancy status. Relative to the truth, all five models produced strongly biased estimates, overestimating detection probability and underestimating the number of occupied trees. Despite this, goodness-of-fit tests indicated that some models fitted the data well, with no evidence of model misfit. Hence, TTD occupancy models that appear to perform well with respect to the available data may be performing poorly. The reason for poor model performance was unaccounted for heterogeneity in detection probability, which is known to bias occupancy-detection models. This poses a problem because unaccounted for heterogeneity could not be detected using goodness-of-fit tests and was only revealed because we knew the experimentally determined outcome. A challenge for occupancy-detection models is to find ways to identify and mitigate the impacts of unobserved heterogeneity, which could unknowingly bias many models.
Experimental method for 3D reconstruction of Odonata wings (methodology and dataset)
Insect wings are highly evolved structures with aerodynamic and structural properties that are not fully understood or systematically modeled. Most species in the insect order Odonata have permanently deployed high aspect ratio wings. Odonata have been documented to exhibit extraordinary flight performance and a wide range of interesting flight behaviors that rely on agility and efficiency. The characteristic three-dimensional corrugated structures of these wings have been observed and modeled for a small number of species, with studies showing that corrugations can provide significant aerodynamic and structural advantages. Comprehensive museum collections are the most practical source of Odonata wing, despite the risk of adverse effects caused by dehydration and preservation of specimens. Museum specimens are not to be handled or damaged and are best left undisturbed in their display enclosures. We have undertaken a systematic process of scanning, modeling, and post-processing the wings of over 80 Odonata species using a novel and accurate method and apparatus we developed for this purpose. The method allows the samples to stay inside their glass cases if necessary and is non-destructive. The measurements taken have been validated against micro-computed tomography scanning and against similar-sized objects with measured dimensions. The resulting publicly available dataset will allow aeronautical analysis of Odonata aerodynamics and structures, the study of the evolution of functional structures, and research into insect ecology. The technique is useable for other orders of insects and other fragile samples.Insect wings are highly evolved structures with aerodynamic and structural properties that are not fully understood or systematically modeled. Most species in the insect order Odonata have permanently deployed high aspect ratio wings. Odonata have been documented to exhibit extraordinary flight performance and a wide range of interesting flight behaviors that rely on agility and efficiency. The characteristic three-dimensional corrugated structures of these wings have been observed and modeled for a small number of species, with studies showing that corrugations can provide significant aerodynamic and structural advantages. Comprehensive museum collections are the most practical source of Odonata wing, despite the risk of adverse effects caused by dehydration and preservation of specimens. Museum specimens are not to be handled or damaged and are best left undisturbed in their display enclosures. We have undertaken a systematic process of scanning, modeling, and post-processing the wings of over 80 Odonata species using a novel and accurate method and apparatus we developed for this purpose. The method allows the samples to stay inside their glass cases if necessary and is non-destructive. The measurements taken have been validated against micro-computed tomography scanning and against similar-sized objects with measured dimensions. The resulting publicly available dataset will allow aeronautical analysis of Odonata aerodynamics and structures, the study of the evolution of functional structures, and research into insect ecology. The technique is useable for other orders of insects and other fragile samples.
Data from: Experimental study on diesel engine EGR performance and Optimum EGR Rate Determination Method
In order to study deeply the Exhaust gas recirculation(EGR)performance of marine diesel engines,a venturi high-pressure exhaust gas recirculation device was established to overcome the exhaust gas reflow problem in a certain type turbocharged diesel engine. With the device, the EGR performance test is accomplished and an optimal EGR decision-making optimization method based on grey correlation coefficient modified is proposed. The results show that the venturi tube EGR can basically meet the injection requirements of high-pressure exhaust gas and makes good results to the diesel engine . Through the venturi tube EGR, the NOX emissions reduces significantly with the maximum drop of 30.6%. The explosive pressure in cylinder reduces with the EGR rate increases, and the cylinder pressure curve shows a single peak at low-speed conditions and double peaks at high-speed condition. However, the fuel consumption rate, NO, and smoke have been negatively affected. Due to small samples, the traditional evaluation method is difficult to determine the optimal EGR rate reasonably, while the proposed method can effectively solve this problem. It can weaken the shortcomings of subjective judgment and greatly improve the rationality of decision-making results.
An Automated, Experimenter-Free Method for the Standardised, Operant Cognitive Testing of Rats __ Data supplementing __
<p>These data supplement the article:</p> <p><strong>An Automated, Experimenter-Free Method for the Standardised, Operant Cognitive Testing of Rats</strong></p> <p><em>Marion Rivalan, Humaira Munawar, Anna Fuchs, York Winter (2017)</em></p> <ul> <li>Published: January 6, 2017</li> <li>http://dx.doi.org/10.1371/journal.pone.0169476</li> </ul> <p>Use is free for academic purposes, provided the aforementioned article is appropriately cited.</p> <p>The directory contains the following file: Pone_2016_DataSupplement-Zenodo.xlsx</p> <p>Explanations are within the document.</p>
Data from: A whole-ecosystem method for experimentally suppressing ants on a small scale
<p>Ant suppression experiments have emerged as a powerful method for assessing the role of ants in ecosystems. However, traditional methods have been limited to canopy ants, and not assessed the role of ants on and below ground. Recent advances have enabled whole-ecosystem ant suppression in large plots, but large-scale experiments are not always feasible. Here, we develop a small-scale, whole-ecosystem suppression method. We compare techniques for monitoring suppression experiments, and assess whether habitat complexity in oil palm influences our method's effectiveness.</p> <p>We conducted ant suppression experiments in oil palm agroforestry in Sumatra, Indonesia. We used targeted poison baits, a physical barrier, and canopy isolation to suppress ants in 4m-radius arenas around single palms. We sequentially tested three suppression methods that increased in intensity over 18 months. We sampled ant abundance before and after suppression by fogging, using pitfall traps, and extracting soil monoliths. We also monitored ants throughout the experiment by baiting. We tested the soil for residual poison and monitored other invertebrates (Araneae, Coleoptera, Orthoptera, and Chilopoda) to test for cross-contamination. Plots were established under four oil palm management treatments that varied in their habitat complexity: reduced, intermediate, and high understory complexity treatments in mature plantation, and a recently-replanted plantation.</p> <p>Post-treatment ant abundance was 92% lower in suppression than control plots. Only the most intensive suppression method, which ran for the final nine months, worked. Baiting rarely reflected the other monitoring methods. The treatment negatively affected Orthoptera, but not other taxa. We detected no residual poison in the soil. Coleoptera abundance increased in suppression plots post-treatment, potentially due to reduced competition with ants. Our findings were consistent across management treatments.</p> <p>We developed a whole-ecosystem method for suppressing ants on a small scale in oil palm plantations. Our method represents a significant advance; previous reductions in ant abundance have not exceeded 38%. We provide the first example of ants being experimentally suppressed belowground. Baiting is not adequate for assessing suppression effectiveness, and testing a range of taxa for confounding impacts is important. Our study acts as a blueprint for developing suppression methods for other taxa, which offer unique insights into community ecology.</p>
Screening and mechanism of novel angiotensin-I-converting enzyme inhibitory peptides in X. sorbifolium seed meal: A computer-assisted experimental study method
<p>本文档是补充材料</p>
Data from : Evaluating and Predicting the Audibility of Acoustic Alarms in the Workplace Using Experimental Methods and Deep Learning
<h2>Description</h2> <p>This repository serves as a complementary resource accompanying the academic paper titled "Evaluating and Predicting the Audibility of Acoustic Alarms in the Workplace Using Experimental Methods and Deep Learning" published in <em>Applied Acoustics </em>(available at: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.apacoust.2024.109955" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.apacoust.2024.109955</a>). It comprises a dataset containing the acoustic data, metadata, and perceptual annotations.</p> <p>In addition, we provide the .<em>h5</em> datasets and PyTorch model weights to run the code corresponding to the neural network section discussed in the paper (publicly accessible at: <a href="https://github.com/effajr/predicting_alarm_audibility">https://github.com/effajr/predicting_alarm_audibility</a>).</p> <p>The repository is composed of five .<em>zip</em> files:</p> <ul> <li><strong>source_audio </strong>: contains the source audio files used to generate the alarms and backgrounds present in the <strong>data</strong> file.</li> <li><strong>data</strong> : contains the audio files corresponding to the alarms and backgrounds, along with the perceptual annotations.</li> <li><strong>metadata</strong> : contains the metadata related to the alarms and backgrounds present in the <strong>data</strong> file, and to the source audio files contained in <strong>source_audio</strong>.</li> <li><strong>features </strong>: contains the .<em>h5</em> files representing the development and evaluation subsets (mel-spectrograms and perceptual labels) used in the deep learning approach presented in the paper.</li> <li><strong>trained_models </strong>: contains the PyTorch model weights for the 10 runs of model training mentionned in the paper.</li> </ul> <h2>How to use the data</h2> <p>To run the code present in the GitHub repository, we recommend extracting the files <strong>data</strong>.zip, <strong>features</strong>.zip and <strong>trained_models</strong>.zip in their corresponding folders in the "<strong>application</strong>" folder (see <a href="https://github.com/effajr/predicting_alarm_audibility">https://github.com/effajr/predicting_alarm_audibility</a>).</p> <h2>Content</h2> <p>Content of <strong>data</strong>.zip </p> <pre>annotations/ ├─ dev/ │ ├─ annotation_compilation_dev.csv : Compilation of all the listening conditions and <br>│ │ individual annotator responses for the development data.<br>│ ├─ dev_conditions.csv : Unique listening conditions (extracted from annotation_compilation_dev.csv). │ ├─ dev_labels.csv : All individual annotator responses for each <br>│ │ unique listening condition (extracted from annotation_compilation_dev.csv). │ ├─ dev_train_valid_split.csv : Random 80%/20% training/validation split used for development <br>│ │ in the experiments reported in the paper. ├─ eval/<br>│ ├─ annotation_compilation_eval.csv : Compilation of all the listening conditions and individual annotator <br>│ │ responses for the evaluation data.<br>│ │ The column 'clearly_audible_mean' represents individual annotator <br>│ │ binary responses evaluated for each listening condition.<br>│ │ The column 'clearly_audible_pf' represents individual annotator <br>│ │ psychometric functions evaluated for each listening condition.<br>│ │<br>│ ├─ eval_conditions.csv : Unique listening conditions (extracted from annotation_compilation_eval.csv). │ ├─ eval_labels_apf.csv : All individual annotator psychometric function values for each <br>│ │ unique listening condition (extracted from annotation_compilation_eval.csv). │ ├─ eval_labels_mv.csv : All individual annotator binary responses for each <br>│ │ unique listening condition (extracted from annotation_compilation_eval.csv)<br>│<br>audio/ : <em>.wav</em> files corresponding to the alarms and backgrounds for Development and <br> Evaluation subsets of the dataset. ├─ dev/ │ ├─ alarms/ │ ├─ backgrounds/ ├─ eval/ │ ├─ alarms/ │ ├─ backgrounds/<br><br><br>Content of <strong>metadata</strong>.zip <br><br>├─ audio_metadata.xlsx : Table of the alarms and background files with short descriptions, <br>│ source file names, and temporal information (in seconds). ├─ source_file_metadata.xlsx : Metadata table of the original files used to generate alarms and backgrounds. </pre>
Graphic Comparison between DualSPHysics and Experimental Method
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EXPERIMENTAL STUDY ON THE EFFECTIVENESS OF DEVELOPED METHODS FOR TEACHING CREATIVE WRITING
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Data from: Experimental study on diesel engine EGR performance and Optimum EGR Rate Determination Method
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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.