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16 results for “Dwell Time”
Extensive crowdsourced dataset of in-situ evaluated binaural soundscapes of private dwellings containing subjective sound-related and situational ratings along with person factors to study time-varying influences on sound perception — research data
<p><strong>Abstract:</strong></p> <p>The soundscape approach highlights the role of situational factors in sound evaluations; however, only a few studies have applied a multi‐domain approach including sound‐related, person‐related, and time‐varying situational variables. Therefore, we conducted a study based on the Experience Sampling Method to measure the relative contribution of a broad range of potentially relevant acoustic and non‐auditory variables in predicting indoor soundscape evaluations. Here we present the comprehensive dataset for which 105 participants reported temporally (rather) stable trait variables such as noise sensitivity, trait affect, and quality of life. They rated 6.594 situations regarding the soundscape standard dimensions, perceived loudness, and the saliency of its sound components and evaluated situational variables such as state affect, perceived control, activity, and location. To complement these subject‐centered data, we additionally crowdsourced object‐centered data by having participants make binaural measurements of each indoor soundscape at their homes using a low‐(self‐)noise recorder. These recordings were used to compute (psycho‐)acoustical indices such as the energetically averaged loudness level, the A‐weighted energetically averaged equivalent continuous sound pressure level, and the A‐weighted five‐percent exceedance level. This complex hierarchical data can be used to investigate time‐varying non‐auditory influences on sound perception and to develop soundscape indicators based on the binaural recordings to predict soundscape evaluations.</p> <p><strong>Content:</strong></p> <ul> <li><a href="https://zenodo.org/record/7858848/files/01%20StudyDescription.pdf">01 StudyDescription.pdf </a> <ul> <li>Description of the field study.</li> <li>Information about the methods and materials used.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/02%20Dataset.csv">02 Dataset.csv</a> <ul> <li>The dataset, consisting of 93 variables describing 6594 observations taken by 105 participants.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/03%20VariableDescriptions_EnglishPersonQuestionnaire.pdf">03 VariableDescriptions_EnglishPersonQuestionnaire.pdf</a> <ul> <li>Descriptions of all variables, their measurement scale, scale ranges and levels.</li> <li>Questions and task descriptions of the Experience Sampling Method questionnaire in German language with an English translation.</li> <li>English translations of questions asked in the person questionnaire.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/04%20ESM-Questionnaire.pdf">04 ESM-Questionnaire.pdf</a> <ul> <li>Screenshots of the original Experience Sampling Method questionnaire with English translations.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/05%20PersonQuestionnaire_OriginalGermanVersion.pdf">05 PersonQuestionnaire_OriginalGermanVersion.pdf</a> <ul> <li>Original version of the person questionnaire in German language.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/06%20HelpTexts.pdf">06 HelpTexts.pdf</a> <ul> <li>Descriptions of the study task.</li> <li>Explanations of the scales used in the questionnaire.</li> <li>Explanations of the sound categories and the soundscape composition.</li> <li>Explanation of the operation of the recording device.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_README.md">AcousticFeatures_README.md</a> <a href="https://zenodo.org/api/files/3d784540-c0f4-412f-8742-df1db6f5401d/TimeSeries_and_Spectrograms_README.md?versionId=9291496c-d2c6-4151-96f1-a2ad99e1a540"> </a> <ul> <li>Descriptions of the structure of the AcousticFeatures_xxx.csv and .zip files.</li> <li>Analyis settings used in Artemis Suite to generate the acoustic features.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_SingleValues.csv">AcousticFeatures_SingleValues.csv</a> <ul> <li>All acoustic features, aggregated to single values per feature, recording, and channel.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_Spectra.csv">AcousticFeatures_Spectra.csv</a> <ul> <li>Time-averaged 1/3 octave spectra of each channel of each recording, A-weichted and un-weighted.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_Spectrograms.zip">AcousticFeatures_Spectrograms.zip</a> <ul> <li>13188 .csv files with un-weighted spetrograms of each channel of each recording.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_TimeSeries.zip">AcousticFeatures_TimeSeries.zip</a> <ul> <li>A .csv file containing LAeq and LZeq time series of each channel of each recording.</li> </ul> </li> </ul> <p><strong>Publications refering to this dataset:</strong></p> <p>Versümer, Siegbert; Steffens, Jochen; Weinzierl, Stefan (currently under review): "The role of loudness predictions, personal and situational factors in day-to-day loudness assessments of indoor soundscapes."</p> <p><strong>Funding:</strong></p> <p>This study was sponsored by the German Federal Ministry of Education and Research. “FHprofUnt” funding code: 13FH729IX6. </p> <p><strong>License: </strong></p> <p>CC 4.0 BY, <a href="https://creativecommons.org/licenses/by/4.0/legalcode">https://creativecommons.org/licenses/by/4.0/legalcode</a></p> <p><strong>Version history:</strong></p> <p>Details can be found in the <a href="https://zenodo.org/api/files/a15d6a91-1a35-4b5e-a7ec-da8a9bcbee2b/Changelog.md">Changelog.md</a> file.</p> <ul> <li> V.01.0. March 7, 2023: Initial publication. <a href="https://doi.org/10.5281/zenodo.7193938">https://doi.org/10.5281/zenodo.7193938</a></li> <li> V.01.1. April 25, 2023. <a href="https://doi.org/10.5281/zenodo.7858848">https://doi.org/10.5281/zenodo.7858848</a></li> </ul>
Single molecule experimental data for dwell time histogram in Gilburt et al, Angewandte Chemie 2017
<p>Raw and partially processed data for the dwell time histogram in the following publication:</p> <p>James A H Gilburt, Hajrah Sarkar, Peter Sheldrake, Julian Blagg, Liming Ying, Charlotte A Dodson (2017) Dynamic equilibrium of the Aurora-A kinase activation loop revealed by single molecule spectroscopy. <em>Angewandte Chemie</em></p> <p><strong><em>Please cite our publication in any use of this data</em></strong></p>
Emergence and return times in a colonial, cave-dwelling bat: age and sex differences driven by reproductive cycle
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Bi-objective optimization for last-train coordination planning with dwell time adjustment strategy
<p><span><span><span><span>In the design of last-train coordination plan, adjusting (extending/reducing) dwell time can balance economic and service goals for operation company and late-night passengers, especially when transfer-passenger flow is uncertain. For this purpose, we first develop</span></span><span><span> a </span></span><span><span>bi-objective</span></span> <span><span>scenario-based</span></span> <span><span>stochastic programming model for</span></span> <span><span>last-train coordination planning problem combined with</span></span><span><span> the </span></span><span><span>dwell time adjustment strategy. Then, we</span></span> <span><span>develop a two-phase approach, wherein the first phase we adopt the varepsilon-constraint method to reformulate the original model to a modified single-objective one. This is followed by the second phase using the branch-and-bound algorithm implemented by</span></span><span><span> the </span></span><span><span>CPLEX solver to obtain</span></span> <span><span>Pareto-optimal solutions (frontier). Finally, we demonstrate the advantage of the proposed model through comparison with the corresponding model without dwell time strategy and the max-min robust model over a randomly generated small-scale network. Moreover, we also illustrate the application of the proposed model by a real-world case study on the large-scale Beijing subway network.</span></span></span></span></p>
Bi-objective optimization for last-train coordination planning with dwell time adjustment strategy
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Optimal Feeding Tube Dwell Time in VLBW Infants to Reduce Feeding Tube Contamination
ClinicalTrials.gov study NCT03728608. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Modeling ribosome dwell times and relationship with tRNA loading and codon usage in mammals (Ribosome Profiling)
GEO Series GSE126383. Mus musculus. 11 samples. Type: Other.
NORTH-REG Dwell-Time Study
ClinicalTrials.gov study NCT04701151. IPD Sharing: NO. Countries: 3. Publications: 0.
Validity and Reliability of the Self-administered Timed Up and Go Test: a Promising Telehealth Resource for Monitoring the Risk of Falls in Community-dwelling Older Adults
ClinicalTrials.gov study NCT06481384. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Random Selection of Patients From the SENTRY Study Who Have a Bioconverted Sentry IVC Filter in Situ With a Minimum Dwell Time of 24 Months From a Single Center Follow up
ClinicalTrials.gov study NCT04208139. IPD Sharing: NO. Countries: 1. Publications: 0.
Comparison of Dwell Time of Open Versus Closed Type Peripheral Intravenous Cannula
ClinicalTrials.gov study NCT07182877. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
A Comparative, Retrospective Chart Review of Intended Dwell Time of a PICC Line
ClinicalTrials.gov study NCT04656548. IPD Sharing: NO. Countries: 1. Publications: 0.
Evaluation of Performance Over Dwell Time and Safety of the Central-venous Catheters Certofix® Paed
ClinicalTrials.gov study NCT05124821. IPD Sharing: NO. Countries: 2. Publications: 0.
Modeling ribosome dwell times and relationship with tRNA loading and codon usage in mammals (tRNA Profiling)
GEO Series GSE126382. Mus musculus. 24 samples. Type: Non-coding RNA profiling by high throughput sequencing.
The Effect of Catheter Protector on Catheter Dwell Time and Complications
ClinicalTrials.gov study NCT06675786. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Robust landscapes of ribosome dwell times and aminoacyl-tRNAs in response to nutrient stress in liver
GEO Series GSE126384. Mus musculus. 35 samples. Type: Non-coding RNA profiling by high throughput sequencing; Other.
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