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56 results for “mechanical performance”
Design of Multifunctional Composites: New Strategy to Save Energy and Improve Mechanical Performance
<p>dataset on </p> <p>Dynamic Mechanical Analysis, Electro-Mechanical Measurement, Dynamic Light Scattering</p> <p>FTIR spectroscopy, Thermogravimetric analysis, Differential Scanning Calorimetry,</p> <p>Electro-Temperature Measurement, Thermal Image Camera, Water sorption measurement,</p> <p>Transmission Electron Microscopy and Stress Strain</p>
Acquired data necessary to perform the control algorithm introduced in the scientific paper: "Multilevel control of an anthropomorphic prosthetic hand for grasp and slip prevention" (Advances in Mechanical Engineering, 2016, vol. 8, pp. 1-13)
<p>Acquired data necessary to perform the control algorithm introduced in this paper.</p> <p>a) Figure 6: Calibration data for the three FSRs placed on the prosthetic hand and covered with silicon caps.<br> b) Figure 9: Data for the cost during the learning of two grasping tasks of an egg: bi-digital grasp and tri-digital grasp.<br> c) Figure 10 and Figure 11: Data for the experimental results with the plastic cup and with the highlighter shown in the paper.<br> </p> <p> </p>
Dataset of "PEMFC performance decay during real-world automotive operation: evincing degradation mechanisms and heterogeneity of ageing"
<p>This is the underlying dataset of "PEMFC performance decay during real-world automotive operation: evincing degradation mechanisms and heterogeneity of ageing"</p>
Performance of Advanced Ambu Bag System among Adult Patients with Mechanical Ventilation: A Mixed-Effects Analysis
<p>We conducted the study at the Department of Stroke Care of the Can Tho Central General Hospital, Vietnam. There are eight intensive care beds for critical illness. The study was performed according to the Helsinki Declaration and approved by the Can Tho Central General Hospital ethics committee. All patients gave written informed consent by a legal surrogate. We enrolled patients with mechanical ventilation between November 2022 and September 2023. The inclusion criteria were: (1) patients aged 16 years and older, (2) pulse rate less than 120 times per minute, (3) systolic blood pressure from 110 to 160 mmHg, (4) peripheral oxygen saturation (SpO<sub>2</sub>) greater than 90%, (5) spontaneous breathing rate less than 28 times per minute, (6) end-tidal carbon dioxide (EtCO<sub>2</sub>) from 20 to 45 mmHg, (7) secretion required suction less than one time per hour, (8) positive end-expiratory pressure less than or equal to 5 cmH<sub>2</sub>O, (9) fraction of inspired oxygen less than or equal to 60%, (10) minute ventilation less than 15 liters per minute, (11) diameter of a tracheal or tracheostomy tube greater than or equal to 7.0 mm, (12) no usage of sedation, (13) normal ST wave in the electrocardiogram. Patients were excluded from the trial if they had one of the following conditions: (1) acute myocardial infarction, (2) acute pulmonary embolism, or (3) new dangerous arrhythmias appeared in this episode (multiform ventricular ectopy, bigeminy or trigeminy ventricular ectopy, coupled ventricular ectopy, R-on-T ventricular ectopy, high-grade atrioventricular heart block, supraventricular tachycardia, atrial fibrillation, atrial flutter, ventricular tachycardia, ventricular fibrillation), (4) using vasopressors or inotropic agents. Patients could withdraw from the study at any time without giving any reason. Besides, the patient stopped the trial of the advanced Ambu bag system immediately when one of the signs appeared, such as (1) the peripheral oxygen saturation lower than 90% prolonging more than 1 minute, (2) the end-tidal carbon dioxide greater than 45 mmHg or less than 15 mmHg prolonging more than 10 minutes, (3) pulse rate greater than 120 times per minute or less than 60 times per minute prolonging more than 10 minutes, (4) systolic blood pressure greater than 170 mmHg prolonging more than 10 minutes, (5) appearing dangerous arrhythmias, (6) progressive cognitive impairment (based on Grady coma scale), or (7) any abnormal sign that the physician evaluated the patient required respiratory support immediately with conventional mechanical ventilation.</p> <p> The following is the meaning of the variables in the study:</p> <p>age: Age of study participants.</p> <p>gender: Gender of study participants (0: Woman, 1: Man).</p> <p>day1: Day of admission to the hospital</p> <p>day2: Intervention day.</p> <p>dia1: Major disease.</p> <p>dia2: Cause of respiratory failure.</p> <p>nihss1: National Institute of Health Stroke Scale on admission</p> <p>hsg: Severity of cerebral hemorrhage (0: No hemorrhagic stroke, hi1: Scattered small petechiae, no mass effect, hi2: Confluent petechiae, no mass effect, ph1: Hematoma within infarcted tissue, occupying <30%, no substantive mass effect, ph2: Hematoma occupying 30% or more of the infarcted tissue, with obvious mass effect, 3a: Parenchymal hematoma remote from infarcted brain tissue, 3b: Intraventricular hemorrhage, 3c: Subarachnoid hemorrhage, 3d: Subdural hemorrhage)</p> <p>aspects1: Alberta stroke program early CT score of anterior circulation on CTscan</p> <p>aspect2: Alberta stroke program early CT score of anterior circulation on DWI- Diffusion-weighted Imaging.</p> <p>aspects3: Alberta stroke program early CT score of posterior circulation on CTscan</p> <p>aspects4: Alberta stroke program early CT score of posterior circulation on DWI- Diffusion-weighted Imaging.</p> <p> </p> <p>nihss2: National Institute of Health Stroke Scale before intervention</p> <p>grady: Grady coma scale before intervention</p> <p> </p> <p>rtpa: Use alteplase (0: No, 1: Yes)</p> <p>thromb: Thrombectomy (0: No, 1: Yes)</p> <p>crani: Craniectomy (0: No, 1: Yes).</p> <p>coil: Endovascular coiling (0: No, 1: Yes)</p> <p> </p> <p>mode: Ventilation mode</p> <p>mv: Mechanical ventilation (L/min)</p> <p>fio2: Fraction of inspired oxygen (%)</p> <p>peep: Positive end-expiratory pressure (cmH<sub>2</sub>O)</p> <p>sc: Static compliance (mL/cmH<sub>2</sub>O)</p> <p>alv: Pulmonary consolidation (0: No, 1: ¼ lung, 2: ½ lung, 3: ¾ lung, 4: Complete lung)</p> <p>sf: spo2/fio2 ratio.</p> <p> </p> <p>p13a: Number of pulse beats at time -13 (conventional mechanical ventilation stage)</p> <p>s13a: Systolic blood pressure at time -13 (conventional mechanical ventilation stage)</p> <p>d13a: Diastolic blood pressure at time -13 (conventional mechanical ventilation stage)</p> <p>sp13a: SpO<sub>2</sub> at time -13 (conventional mechanical ventilation stage)</p> <p>e13a: EtCO<sub>2</sub> at time -13 (conventional mechanical ventilation stage)</p> <p> </p> <p>p12a: Number of pulse beats at time -12 (conventional mechanical ventilation stage)</p> <p>s12a: Systolic blood pressure at time -12 (conventional mechanical ventilation stage)</p> <p>d12a: Diastolic blood pressure at time -12 (conventional mechanical ventilation stage)</p> <p>sp12a: SpO<sub>2</sub> at time -12 (conventional mechanical ventilation stage)</p> <p>e12a: EtCO<sub>2</sub> at time -12 (conventional mechanical ventilation stage)</p> <p> </p> <p>p11a: Number of pulse beats at time -11 (conventional mechanical ventilation stage)</p> <p>s11a: Systolic blood pressure at time -11 (conventional mechanical ventilation stage)</p> <p>d11a: Diastolic blood pressure at time -11 (conventional mechanical ventilation stage)</p> <p>sp11a: SpO<sub>2</sub> at time -11 (conventional mechanical ventilation stage)</p> <p>e11a: EtCO<sub>2</sub> at time -11 (conventional mechanical ventilation stage)</p> <p> </p> <p>p10a: Number of pulse beats at time -10 (conventional mechanical ventilation stage)</p> <p>s10a: Systolic blood pressure at time -10 (conventional mechanical ventilation stage)</p> <p>d10a: Diastolic blood pressure at time -10 (conventional mechanical ventilation stage)</p> <p>sp10a: SpO<sub>2</sub> at time -10 (conventional mechanical ventilation stage)</p> <p>e10a: EtCO<sub>2</sub> at time -10 (conventional mechanical ventilation stage)</p> <p> </p> <p>p9a: Number of pulse beats at time -9 (conventional mechanical ventilation stage)</p> <p>s9a: Systolic blood pressure at time -9 (conventional mechanical ventilation stage)</p> <p>d9a: Diastolic blood pressure at time -9 (conventional mechanical ventilation stage)</p> <p>sp9a: SpO<sub>2</sub> at time -9 (conventional mechanical ventilation stage)</p> <p>e9a: EtCO<sub>2</sub> at time -9 (conventional mechanical ventilation stage)</p> <p> </p> <p>p8a: Number of pulse beats at time -8 (conventional mechanical ventilation stage)</p> <p>s8a: Systolic blood pressure at time -8 (conventional mechanical ventilation stage)</p> <p>d8a: Diastolic blood pressure at time -8 (conventional mechanical ventilation stage)</p> <p>sp8a: SpO<sub>2</sub> at time -8 (conventional mechanical ventilation stage)</p> <p>e8a: EtCO<sub>2</sub> at time -8 (conventional mechanical ventilation stage)</p> <p> </p> <p>p7a: Number of pulse beats at time -7 (conventional mechanical ventilation stage)</p> <p>s7a: Systolic blood pressure at time -7 (conventional mechanical ventilation stage)</p> <p>d7a: Diastolic blood pressure at time -7 (conventional mechanical ventilation stage)</p> <p>sp7a: SpO<sub>2</sub> at time -7 (conventional mechanical ventilation stage)</p> <p>e7a: EtCO<sub>2</sub> at time -7 (conventional mechanical ventilation stage)</p> <p> </p> <p>p6a: Number of pulse beats at time -6 (conventional mechanical ventilation stage)</p> <p>s6a: Systolic blood pressure at time -6 (conventional mechanical ventilation stage)</p> <p>d6a: Diastolic blood pressure at time -6 (conventional mechanical ventilation stage)</p> <p>sp6a: SpO<sub>2</sub> at time -6 (conventional mechanical ventilation stage)</p> <p>e6a: EtCO<sub>2</sub> at time -6 (conventional mechanical ventilation stage)</p> <p> </p> <p>p5a: Number of pulse beats at time -5 (conventional mechanical ventilation stage)</p> <p>s5a: Systolic blood pressure at time -5 (conventional mechanical ventilation stage)</p> <p>d5a: Diastolic blood pressure at time -5 (conventional mechanical ventilation stage)</p> <p>sp5a: SpO<sub>2</sub> at time -5 (conventional mechanical ventilation stage)</p> <p>e5a: EtCO<sub>2</sub> at time -5 (conventional mechanical ventilation stage)</p> <p> </p> <p>p4a: Number of pulse beats at time -4 (conventional mechanical ventilation stage)</p> <p>s4a: Systolic blood pressure at time -4 (conventional mechanical ventilation stage)</p> <p>d4a: Diastolic blood pressure at time -4 (conventional mechanical ventilation stage)</p> <p>sp4a: SpO<sub>2</sub> at time -4 (conventional mechanical ventilation stage)</p> <p>e4a: EtCO<sub>2</sub> at time -4 (conventional mechanical ventilation stage)</p> <p> </p> <p>p3a: Number of pulse beats at time -3 (conventional mechanical ventilation stage)</p> <p>s3a: Systolic blood pressure at time -3 (conventional mechanical ventilation stage)</p> <p>d3a: Diastolic blood pressure at time -3 (conventional mechanical ventilation stage)</p> <p>sp3a: SpO<sub>2</sub> at time -3 (conventional mechanical ventilation stage)</p> <p>e3a: EtCO<sub>2</sub> at time -3 (conventional mechanical ventilation stage)</p> <p> </p> <p>p2a: Number of pulse beats at time -2 (conventional mechanical ventilation stage)</p> <p>s2a: Systolic blood pressure at time -2 (conventional mechanical ventilation stage)</p> <p>d2a: Diastolic blood pressure at time -2 (conventional mechanical ventilation stage)</p> <p>sp2a: SpO<sub>2</sub> at time -2 (conventional mechanical ventilation stage)</p> <p>e2a: EtCO<sub>2</sub> at time -2 (conventional mechanical ventilation stage)</p> <p> </p> <p>p1a: Number of pulse beats at time -1 (conventional mechanical ventilation stage)</p> <p>s1a: Systolic blood pressure at time -1 (conventional mechanical ventilation stage)</p> <p>d1a: Diastolic blood pressure at time -1 (conventional mechanical ventilation stage)</p> <p>sp1a: SpO<sub>2</sub> at time -1 (conventional mechanical ventilation stage)</p> <p>e1a: EtCO<sub>2</sub> at time -1 (conventional mechanical ventilation stage)</p> <p> </p> <p>p0a: Number of pulse beats at time 0 (conventional mechanical ventilation stage)</p> <p>s0a: Systolic blood pressure at time 0 (conventional mechanical ventilation stage)</p> <p>d0a: Diastolic blood pressure at time 0 (conventional mechanical ventilation stage)</p> <p>sp0a: SpO<sub>2</sub> at time 0 (conventional mechanical ventilation stage)</p> <p>e0a: EtCO<sub>2</sub> at time 0 (conventional mechanical ventilation stage)</p> <p> </p> <p>p1b: Number of pulse beats at time +1 (advanced Ambu bag system stage)</p> <p>s1b: Systolic blood pressure at time +1 (advanced Ambu bag system stage)</p> <p>d1b: Diastolic blood pressure at time +1 (advanced Ambu bag system stage)</p> <p>sp1b: SpO<sub>2</sub> at time +1 (advanced Ambu bag system stage)</p> <p>e1b: EtCO<sub>2</sub> at time +1 (advanced Ambu bag system stage)</p> <p> </p> <p>p2b: Number of pulse beats at time +2 (advanced Ambu bag system stage)</p> <p>s2b: Systolic blood pressure at time +2 (advanced Ambu bag system stage)</p> <p>d2b: Diastolic blood pressure at time +2 (advanced Ambu bag system stage)</p> <p>sp2b: SpO<sub>2</sub> at time +2 (advanced Ambu bag system stage)</p> <p>e2b: EtCO<sub>2</sub> at time +2 (advanced Ambu bag system stage)</p> <p> </p> <p>p3b: Number of pulse beats at time +3 (advanced Ambu bag system stage)</p> <p>s3b: Systolic blood pressure at time +3 (advanced Ambu bag system stage)</p> <p>d3b: Diastolic blood pressure at time +3 (advanced Ambu bag system stage)</p> <p>sp3b: SpO<sub>2</sub> at time +3 (advanced Ambu bag system stage)</p> <p>e3b: EtCO<sub>2</sub> at time +3 (advanced Ambu bag system stage)</p> <p> </p> <p>p4b: Number of pulse beats at time +4 (advanced Ambu bag system stage)</p> <p>s4b: Systolic blood pressure at time +4 (advanced Ambu bag system stage)</p> <p>d4b: Diastolic blood pressure at time +4 (advanced Ambu bag system stage)</p> <p>sp4b: SpO<sub>2</sub> at time +4 (advanced Ambu bag system stage)</p> <p>e4b: EtCO<sub>2</sub> at time +4 (advanced Ambu bag system stage)</p> <p> </p> <p>p5b: Number of pulse beats at time +5 (advanced Ambu bag system stage)</p> <p>s5b: Systolic blood pressure at time +5 (advanced Ambu bag system stage)</p> <p>d5b: Diastolic blood pressure at time +5 (advanced Ambu bag system stage)</p> <p>sp5b: SpO<sub>2</sub> at time +5 (advanced Ambu bag system stage)</p> <p>e5b: EtCO<sub>2</sub> at time +5 (advanced Ambu bag system stage)</p> <p> </p> <p>p6b: Number of pulse beats at time +6 (advanced Ambu bag system stage)</p> <p>s6b: Systolic blood pressure at time +6 (advanced Ambu bag system stage)</p> <p>d6b: Diastolic blood pressure at time +6 (advanced Ambu bag system stage)</p> <p>sp6b: SpO<sub>2</sub> at time +6 (advanced Ambu bag system stage)</p> <p>e6b: EtCO<sub>2</sub> at time +6 (advanced Ambu bag system stage)</p> <p> </p> <p>p7b: Number of pulse beats at time +7 (advanced Ambu bag system stage)</p> <p>s7b: Systolic blood pressure at time +7 (advanced Ambu bag system stage)</p> <p>d7b: Diastolic blood pressure at time +7 (advanced Ambu bag system stage)</p> <p>sp7b: SpO<sub>2</sub> at time +7 (advanced Ambu bag system stage)</p> <p>e7b: EtCO<sub>2</sub> at time +7 (advanced Ambu bag system stage)</p> <p> </p> <p>p8b: Number of pulse beats at time +8 (advanced Ambu bag system stage)</p> <p>s8b: Systolic blood pressure at time +8 (advanced Ambu bag system stage)</p> <p>d8b: Diastolic blood pressure at time +8 (advanced Ambu bag system stage)</p> <p>sp8b: SpO<sub>2</sub> at time +8 (advanced Ambu bag system stage)</p> <p>e8b: EtCO<sub>2</sub> at time +8 (advanced Ambu bag system stage)</p> <p> </p> <p>p9b: Number of pulse beats at time +9 (advanced Ambu bag system stage)</p> <p>s9b: Systolic blood pressure at time +9 (advanced Ambu bag system stage)</p> <p>d9b: Diastolic blood pressure at time +9 (advanced Ambu bag system stage)</p> <p>sp9b: SpO<sub>2</sub> at time +9 (advanced Ambu bag system stage)</p> <p>e9b: EtCO<sub>2</sub> at time +9 (advanced Ambu bag system stage)</p> <p> </p> <p>p10b: Number of pulse beats at time +10 (advanced Ambu bag system stage)</p> <p>s10b: Systolic blood pressure at time +10 (advanced Ambu bag system stage)</p> <p>d10b: Diastolic blood pressure at time +10 (advanced Ambu bag system stage)</p> <p>sp10b: SpO<sub>2</sub> at time +10 (advanced Ambu bag system stage)</p> <p>e10b: EtCO<sub>2</sub> at time +10 (advanced Ambu bag system stage)</p> <p> </p> <p>p11b: Number of pulse beats at time +11 (advanced Ambu bag system stage)</p> <p>s11b: Systolic blood pressure at time +11 (advanced Ambu bag system stage)</p> <p>d11b: Diastolic blood pressure at time +11 (advanced Ambu bag system stage)</p> <p>sp11b: SpO<sub>2</sub> at time +11 (advanced Ambu bag system stage)</p> <p>e11b: EtCO<sub>2</sub> at time +11 (advanced Ambu bag system stage)</p> <p> </p> <p>p12b: Number of pulse beats at time +12 (advanced Ambu bag system stage)</p> <p>s12b: Systolic blood pressure at time +12 (advanced Ambu bag system stage)</p> <p>d12b: Diastolic blood pressure at time +12 (advanced Ambu bag system stage)</p> <p>sp12b: SpO<sub>2</sub> at time +12 (advanced Ambu bag system stage)</p> <p>e12b: EtCO<sub>2</sub> at time +12 (advanced Ambu bag system stage)</p> <p> </p> <p>p13b: Number of pulse beats at time +13 (advanced Ambu bag system stage)</p> <p>s13b: Systolic blood pressure at time +13 (advanced Ambu bag system stage)</p> <p>d13b: Diastolic blood pressure at time +13 (advanced Ambu bag system stage)</p> <p>sp13b: SpO<sub>2</sub> at time +13 (advanced Ambu bag system stage)</p> <p>e13b: EtCO<sub>2</sub> at time +13 (advanced Ambu bag system stage)</p> <p> </p> <p>p14b: Number of pulse beats at time +14 (advanced Ambu bag system stage)</p> <p>s14b: Systolic blood pressure at time +14 (advanced Ambu bag system stage)</p> <p>d14b: Diastolic blood pressure at time +14 (advanced Ambu bag system stage)</p> <p>sp14b: SpO<sub>2</sub> at time +14 (advanced Ambu bag system stage)</p> <p>e14b: EtCO<sub>2</sub> at time +14 (advanced Ambu bag system stage)</p>
The Mechanical Performance of Permanent and Bioabsorbable Metal Stents: Supporting Data
<p>Materials including scripts, finite element models and experimental data that were created during the Phd work toward 'The Mechanical Performance of Permanent and Bioabsorbable Metal Stents' http://hdl.handle.net/10379/3744 but wasn't ultimately used in the thesis or publications.</p>
Microstructure and mechanical performance of cold spray Cr coatings
<p>This dataset includes the data associated with the publication titled "Microstructure and mechanical performance of cold spray Cr coatings", published in Journal of Nuclear Materials (https://doi.org/10.1016/j.jnucmat.2024.155492). The zip folder contains the following items:</p> <ol> <li>Data for producing the grain size distribution plots.</li> <li>Microhardness data for the reported values.</li> <li>Nanohardness data.</li> <li>SEM images that were analysed to produce the porosity distribution plot.</li> <li>SEM images that were used to quantify the interfacial roughness and thickness variation of the two coatings.</li> <li>XRD data for measuring residual stresses in the coatings.</li> <li>In-situ DIC data to quantify the crack density and average strain in the coatings after in-situ tensile testing.</li> <li>A jupyter lab notebook to analyse and produce the plots that were presented in the publication.</li> </ol>
Microstructure and mechanical performance of cold spray Cr coatings
<p>This dataset includes the data associated with the publication titled "Microstructure and mechanical performance of cold spray Cr coatings", published in Journal of Nuclear Materials (https://doi.org/10.1016/j.jnucmat.2024.155492). The zip folder contains the following items:</p> <ol> <li>Data for producing the grain size distribution plots.</li> <li>Microhardness data for the reported values.</li> <li>Nanohardness data.</li> <li>SEM images that were analysed to produce the porosity distribution plot.</li> <li>SEM images that were used to quantify the interfacial roughness and thickness variation of the two coatings.</li> <li>XRD data for measuring residual stresses in the coatings.</li> <li>In-situ DIC data to quantify the crack density and average strain in the coatings after in-situ tensile testing.</li> <li>A jupyter lab notebook to analyse and produce the plots that were presented in the publication.</li> </ol>
Input data for performing chemistry coupled PALM model system 6.0 simulations with different chemical mechanisms
<p>The data presented here comprised of input files that have been used to run chemistry coupled PALM model system 6.0 simulations for the article entitled "Development of an atmospheric chemistry model coupled to the PALM model system 6.0: Implementation and first applications". In this article we describe the implementation of an online-coupled gas-phase chemistry model in the turbulence resolving PALM model system 6.0.</p> <p>List of the input data required for performing chemistry model simulations with different chemical mechanisms is given below. A text file comprised of measured concentrations of NO, NO<sub>2</sub> and O<sub>3</sub> is also added.</p> <ol> <li>Fortran parameter (PARIN) files for four mechanisms and one meteorology-only simulation.</li> <li>Static file</li> <li>Dynamic file</li> <li>Two files (shortwave and longwave input data) for rrtmg radiation model</li> <li>Observation from two air quality stations in Berlin, Germany .</li> <li>PALM model source code revision 4450 (palm_trunk_rev-4450.tar.gz)</li> <li>PALM model source code revision 4601 (palm_trunk_rev-4601.tar.gz)</li> </ol> <p>The PALM model system 6.0 revision 4451 and 4601 (for chemistry flux profiles only) have been used for these simulations. </p>
Impact of intercept trap type on plume structure: a potential mechanism for differential performance of intercept trap designs for Monochamus species
<p>Studies have demonstrated that semiochemical-baited intercept traps differ in their performance for sampling insects, but we have an incomplete understanding of how and why intercept trap design effects vary among insects. This can significantly delay both the development of new and optimization of existing survey and detection tools. The development of a mechanistic understanding of why trap performance varies within and among species would mitigate this delay. The primary objective of this study was to develop methods to characterize and compare the odor plumes associated with intercept traps that differ in their performance for forest Coleoptera. We released CO<sub>2</sub> and measured fluctuations of this tracer gas from 175-point locations arranged in a 2-by-3-by-2-m grid cuboid downwind of a standard multiple-funnel, a modified multiple-funnel, a panel, a canopy malaise trap, and a blank control (i.e., no trap) in a greenhouse. Significant differences in trapping efficacy between these different trap designs were observed for <i>Monochamus scutellatus</i> (Say) and <i>Monochamus notatus</i> (Drury) in a field trial. Significant differences were also observed in how CO<sub>2</sub> accumulated in time at different positions downwind among these different trap designs. Turbulent dispersion is the dominant force structuring odor plumes and creates intermittency in the odor plume that is important for sustained upwind flight in insects. Methodological and instrumental limitations resulted in the inability to determine instantaneous plume structures and vortex shedding frequencies for different intercept trap designs. Although we observed differences in the odor plumes emanating downwind of the different intercept trap designs, we were unable to reconcile these differences with capture rates of the different trap designs for <i>M. scutellatus</i> and <i>M. notatus</i>.</p>
Dataset for publication Reaction Mechanism and Performance of Innovative 2D Germanane-Silicane Alloys SixGe1−xH Electrodes in Lithium-Ion Batteries
<p>A dataset for publication Datase for publication Reaction Mechanism and Performance of Innovative 2D Germanane-Silicane Alloys SixGe1−xH Electrodes in Lithium-Ion Batteries including all relevant data used in the manuscript. Information on how to use the dataset are included in the readme file.</p>
Mechanisms of enhanced cardiorespiratory performance under hyperoxia differ with exposure duration in yellowtail kingfish
<p>Hyperoxia has been shown to expand the aerobic capacity of some fishes, although there have been very few studies examining the underlying mechanisms and how they vary across different exposure durations. Here, we investigated cardiorespiratory function of yellowtail kingfish (<em>Seriola lalandi</em>) acutely (~20 hours) and chronically (3-5 weeks) acclimated to hyperoxia (~200 % air saturation). Our results show that aerobic performance of kingfish is limited in normoxia and increases with environmental hyperoxia. Aerobic scope was elevated in both hyperoxia treatments driven by a ~33% increase in maximum O<sub>2</sub> uptake (MO<sub>2max</sub>), although the mechanisms differed across treatments. Fish acutely transferred to hyperoxia primarily elevated tissue O<sub>2</sub> extraction, while increased stroke volume-mediated maximum cardiac output was the main driving factor in chronically acclimated fish. Still an improved O<sub>2</sub> delivery to the heart in chronic hyperoxia was not the only explanatory factor as such. Here, maximum cardiac output only increased in chronic hyperoxia compared to normoxia when plastic ventricular growth occurred, as increased stroke volume was partly enabled by an ~8-12% larger relative ventricular mass. Our findings suggest that hyperoxia may be used long-term to boost cardiorespiratory function potentially rendering fish more resilient to metabolically challenging events and stages in their life-cycle.</p>
Data from: Divergent mechanisms of reduced growth performance in Betula ermanii saplings from high-altitude and low-latitude range edges
<p><span>The reduced growth performance of individuals from range edges is a common phenomenon in various taxa, and considered to be an evolutionary factor that limits the species' range. However, most studies did not distinguish between two mechanisms that can lead to this reduction: genetic load and adaptive selection to harsh conditions. This study investigated the climatic and genetic factors underlying the growth performance of <em>Betula ermanii</em> saplings transplanted from 11 populations including high-altitude edge and low-latitude edge population using RAD-seq analysis.</span></p> <p>For 11 B. ermanii populations in wide-latitude range of Japan, we estimated gene diversity, nucleotide diversity, <span>the coefficients of linkage disequilibrium, genetic differentiation between populations, population structure as well as the relatedness coefficient from SNPs. As a result, the low-latitude edge population exhibited a high level of linkage disequilibrium, low genetic diversity, a distinct genetic composition from the other populations, and a high relatedness coefficient.</span></p> <p><span>This data contains two SNPs datas (vcf files) used in these analysis. We analyzed SNPs data separately for 8 planting sites. Then each tarball contains 8 separate vcf files. One tarball named "vcfAfterFiltering" contains vcf files after SNP filtering steps used for the calculation of the coefficients of linkage disequilibrium. Another tarball named "vcfAfterLDPruning" contains vcf files after SNP filtering and before LD-based pruning used for the calculation of other genetic parameters.</span></p>
Data from: Selection for functional performance in the evolution of cuticle hardening mechanisms in insects
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Data from: Divergent mechanisms of reduced growth performance in Betula ermanii saplings from high-altitude and low-latitude range edges
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Mechanisms of enhanced cardiorespiratory performance under hyperoxia differ with exposure duration in yellowtail kingfish
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Impact of intercept trap type on plume structure: a potential mechanism for differential performance of intercept trap designs for Monochamus species
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Data for Performance-Portable Solid Mechanics via Matrix-Free p-Multigrid
<p>Data, scripts to make the figures, and tex source for the paper: https://arxiv.org/abs/2204.01722</p>
Data from: How biological attention mechanisms improve task performance in a large-scale visual system model
How does attentional modulation of neural activity enhance performance? Here we use a deep convolutional neural network as a large-scale model of the visual system to address this question. We model the feature similarity gain model of attention, in which attentional modulation is applied according to neural stimulus tuning. Using a variety of visual tasks, we show that neural modulations of the kind and magnitude observed experimentally lead to performance changes of the kind and magnitude observed experimentally. We find that, at earlier layers, attention applied according to tuning does not successfully propagate through the network, and has a weaker impact on performance than attention applied according to values computed for optimally modulating higher areas. This raises the question of whether biological attention might be applied at least in part to optimize function rather than strictly according to tuning. We suggest a simple experiment to distinguish these alternatives.
Hygro-thermo-mechanical model for concrete pavement from an early age to a long-term performance
<p>A new 3D hygro-thermo-mechanical model for a concrete pavement slab is formulated, capturing its behavior from casting to long-term drying. The model includes a microprestress-solidification viscoelastic model for concrete ageing creep. Calibrations and validations are based on lab experiments and a four year continuous monitoring of a real highway slab. The results show that slab drying leads to the highest principal tensile stress on the surface as high as 3.5 MPa. Simulated temperature cycles and traffic loading yield smaller stresses. In this regard, concrete crack resistance during drying should be considered in material and structural design.</p>
Mechanical Ventilation Controlled by the Electrical Activity of the Patient's Diaphragm - Effects on Cardiac Performance
ClinicalTrials.gov study NCT00647361. IPD Sharing: Not stated. Countries: 1. Publications: 2.
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.