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841 results for “vibrations”
Data from: Food vibrations: Asian spice sets lips trembling
Szechuan pepper, a widely used ingredient in the cuisine of many Asian countries, is known for the tingling sensation it induces on the tongue and lips. While the molecular mechanism by which Szechuan pepper activates tactile afferent fibres has been clarified, the tingling sensation itself has been less studied, and it remains unclear which fibres are responsible. We investigated the somatosensory perception of tingling in humans to identify the characteristic temporal frequency and compare this to the established selectivity of tactile afferents. Szechuan pepper was applied to the lower lip of participants. Participants judged the frequency of the tingling sensation on the lips by comparing this with the frequencies of mechanical vibrations applied to their right index finger. The perceived frequency of the tingling was consistently at around 50 Hz, corresponding to the range of tactile RA1 afferent fibres. Furthermore, adaptation of the RA1 channel by prolonged mechanical vibration reliably reduced the tingling frequency induced by Szechuan pepper, confirming that the frequency-specific tactile channel is shared between Szechuan pepper and mechanical vibration. Combining information about molecular reactions at peripheral receptors with quantitative psychophysical measurement may provide a unique method for characterizing unusual experiences by decomposing them into identifiable minimal units of sensation.
Figure 6 in The Behavioral Ecology of Insect Vibrational Communication
Figure 6. Frequency spectra of vibrational signals (a through f) predicted to evolve in response to different combinations of receiver frequency selectivity and average substrate filtering properties. For example, when the substrate filtering is unpredictable or flat, use of signals containing a broad range of frequencies may ensure that some energy reaches the signaler (a). However, this strategy will only be successful if receivers are also broadly tuned; if receivers are selective for a narrow band of frequencies, signals should likewise be narrowly tuned (b). Use of hosts with different filtering properties (such as lowpass vs. bandpass filters, or bandpass filters with different best frequencies) may favor the evolution of different signals, a process that could contribute to speciation.
Figure 5 in The Behavioral Ecology of Insect Vibrational Communication
Figure 5. Female preference curve for signal frequency compared with the amplitude spectrum of a male advertisement signal for a treehopper (a member of the Enchenopa binotata species complex occurring on the host plant Ptelea trifoliata in central Missouri). (a) Amplitude spectrum of a male advertisement signal that closely matches the mean frequency for the population. The waveform of that signal is shown above. (b) Proportion of females (n = 15) that responded to digitally generated signals that varied in carrier frequency while keeping all other traits at the mean value for the population. Playback stimuli were delivered by means of a magnet attached to the host plant stem and an electromagnet placed 2 millimeters away from the magnet. The stimuli and the female response calls were monitored with a PCB U352B65 accelerometer and U480E09 amplifier connected to a recording computer. Playback intensity was set to the median peak acceleration of the signals of nine males recorded on the playback plant.
Figure 4 in The Behavioral Ecology of Insect Vibrational Communication
Figure 4. Examples of complex vibrational signaling environments. (a) A male treehopper (Heteronotus trinodosus) producing advertisement signals in alternation with another male on the same stem. (b, c) Field recordings from two herbaceous plants in Soberanía National Park, Panama. Each recording contains signals of approximately four insect species, with one species signaling continuously (indicated with number 1 in panel b and number 3 in panel c). Scale bars = 1 second. It is difficult to gain from figures like these the impression one gets, when listening to vibrational signals in plants in the field, of an encounter with a mysterious and alien world of sound.
Figure 1 in The Behavioral Ecology of Insect Vibrational Communication
Figure 1. Prevalence of various signaling modalities among insects that use mechanical communication (categories from Greenfield 2002). The pie chart above shows an estimate obtained by tallying the number of families for which evidence of signaling in any given modality exists. The chart below shows a more speculative estimate obtained by counting the number of species for which such evidence is available; for groups in which reports suggest the use of a modality is widespread, or for which few reports exist but all have found use of a particular modality, we tallied the total number of described species in the group. We excluded instances of detection of incidental cues produced by conspecifics (e.g., we did not count detection of water surface vibrations by gyrinid beetles or of near-field vibrations by culicids and chironomids). We also excluded instances in which the vibration might be perceived through direct bodily contact (e.g., during copulatory courtship). Files with the references used to generate this figure are available on request from the authors. The distribution of signaling modalities among insect orders (phylogenetic tree from Gullan and Cranston 2000) suggests that the use of substrate vibrations for communication may be ancestral for at least some insect groups at the supraordinal level.
Figure 3 in The Behavioral Ecology of Insect Vibrational Communication
Figure 3. Wind as an agent of selection on insect vibrational communication through plants. (a) Hourly wind speeds, averaged over one month, recorded at a weather station in Corvallis, Oregon. Wind speeds were consistently lower in the morning. Wind-speed data were obtained from the AgriMet Program of the US Bureau of Reclamation, Pacific Northwest Region (www.usbr.gov/pn/agrimet/ webagdayread.html). (b) Short-term variation in the amplitude of wind-induced vibrations in a petiole of a black walnut tree, Juglans nigra. (c, d) Amplitude spectra (x ⎯ ± standard deviation) of wind-induced vibrations in petioles of two tree species, J. nigra and Robinia pseudoacacia, showing the predominance of low frequencies and the gradual roll-off at higher frequencies. Wind noise recordings were made at typical positions of treehoppers (Enchenopa binotata) on the two host plants, using a PCB U352B65 accelerometer attached to the leaf petiole and a PCB U480E09 amplifier connected to a Macintosh G3 laptop computer. Maximum wind velocity for these recordings, measured with a handheld anemometer, varied from 1 to 2 meters per second (n = 1 petiole per tree for 10 trees of each species).
Vibrational Probe at the Electrochemical Interface: Dependence on Plasmon Coupling and Potential on the Lineshape in Two-Dimensional Infrared Spectroscopy
<p>These files contain the data presented in the research article: Vibrational Probe at the Electrochemical Interface: Dependence on Plasmon Coupling and Potential on the Lineshape in Two-Dimensional Infrared Spectroscopy by Melissa Bodine, Vepa Rozyyev, Jeffrey W. Elam, Andrei Tokmakoff and Nicholas H. C. Lewis J. Phys. Chem. Lett., (2023)</p>
Data for "Neutron scattering and neural-network quantum molecular dynamics investigation of the vibrations of ammonia along the solid-to-liquid transition"
<p>Data for "Neutron scattering and neural-network quantum molecular dynamics investigation of the vibrations of ammonia along the solid-to-liquid transition".</p> <p>neutron_data.zip --> neutron data in .nxspe form. S(Q,E) calculated using the DAVE software. Includes logbook spreadsheet. </p> <p>Training_Data.xyz --> xyz file containing training data used to generate Allegro machine learning forcefield in the paper</p> <p>nh3_pimd.deploy --> Trained Allegro model to that can be used in LAMMPS and RXMD software a ML forcefield </p> <p>POSCAR_UNIT_CELL_AMMONIA --> NH3 unit cell in solid phase in POSCAR format that can be read by the VASP software used to perform the DFT simmulations.</p>
Supplementary material S2: Video evidence of vibrational traces originating from an individual Varroa mite walking.
<p>A video demonstrating an individual mite walking, together with the measured vibrations in spectrogram form. The logged coordinates of mite movement allow the individual to be tracked within the field of view which is continuously updated. The right-hand side panel detects the changes between two consecutive images of the original cropped video panel. When motionless the mite remains dark blue in the said panel, but the pixels flash red when the mite is walking. The synchronicity between mite movement and the vibrational traces seen on the top spectrogram panel can clearly be seen. This movie soundtrack, which is the accelerometer signal, also demonstrates the audible ‘clicking’ of mite walking vibrations, which are also synchronous with the movement and spectrogram traces. The spectrogram of the accelerometer data is shown with respect to time, with acceleration magnitude in logarithmic (to the base 10) format, with dark red always forced to be 6x10<sup>-3 </sup>m/s<sup>2</sup> (for ease of viewing the walking traces) as the highest point of magnitude at any point in time and dark blue as 1/50 of the maximum. This movie and its corresponding audio track are slowed from the original 50 to 25 frames per second for better viewing.</p>
Cavity-Enabled Enhancement of Ultrafast Intramolecular Vibrational Redistribution over Pseudorotation
<p>This file contains the data and codes for the paper, 'Cavity-Enabled Enhancement of Ultrafast Intramolecular Vibrational Redistribution over Pseudorotation'. </p>
Computational data for "Measurement of Coherent Vibrational Dynamics with X-ray Transient Absorption Spectroscopy Simultaneously at the Carbon K- and Chlorine L$_{2,3}$- Edges"
<p>Contains:<br><br>1. Code for and results from, time-dependent Schroedinger equation simulations for the molecular normal modes under strong electric fields inducing impulsive stimulated Raman processes.</p> <p>2. Molecular orbitals obtained from ROKS calculations for the C 1s and Cl 2p excited states (with spin-free one-electron X2C). </p>
Data for "Thermodynamic stability and vibrational properties of multi-alkali antimonides"
<p>Input and output files of the calculations presented in the publication <em>"Thermodynamic stability and vibrational properties of multi-alkali antimonides</em>".</p> <p>All the DFT-relaxation and supercell calculations necessary to obtain the phonon properties are included. For Cs3Sb, K3Sb, and Na3Sb, additional calculations for each exchange-correlation functional are provided.</p>
Dataset and analyses for: Force-field perturbations and muscle vibration strengthen stability-related foot placement responses during steady-state gait in healthy adults
<p>We have collected kinematic data (heel and pelvis markers) from healthy adults during treadmill walking, whilst force-field perturbations and timed muscle vibrations were applied. We assessed the (after-)effects of these two interventions by evaluating foot placement control through outcome measures derived from a regression model which predicts foot placement based on the center-of-mass kinematic state. The data and analyses provided belong to the scientific publication: "Force-field perturbations and muscle vibration strengthen stability-related foot placement responses during steady-state gait in healthy adults". In the manuscript we place these analyses in the context of stability control and speculate on how these trainining interventions may improve stability control in patient populations.</p>
Accurate prediction of the solid-state region of the Ni-Al phase diagram including configurational and vibrational entropy and magnetic effects
<p>Documentation for the Dataset used in the publication entitled "Accurate prediction of the solid-state region of the Ni-Al phase diagram including configurational and vibrational entropy and magnetic effects" <br>** These datasets comprise all configurations uesd in Ni-Al system and their formation enthalpies at different temperatures, where fcc Al and fcc Ni were used as reference state. **<br>** More details about the methodology can be found in the paper "Wei Shao, José Manuel Guevara-Vela, Antonio Fernández-Caballero, Sha Liu, Javier LLorca, Accurate prediction of the solid-state region of the Ni-Al phase diagram including configurational and vibrational entropy and magnetic effects, Acta Materialia, 2023"**</p> <p>1. bcc-Ni-Al.zip<br>- Description: bcc-Ni-Al.zip is a compressed folder. It contains Al1-xNix configurations with bcc lattice used to fit the cluster expansion (CE). Each folder contains a POSCAR file that corresponds to a configuration. The POSCAR can be opened with Notepad and visualized with VESTA software.</p> <p><br>2. bcc-with-vacancies-Ni-Al.zip<br>- Description: bcc-with-vacancies-Ni-Al.zip is a compressed folder. It contains (AlVa)x(AlNi)1-x configurations with bcc-with-vacancies lattice used to fit the CE. Each folder contains a POSCAR file that corresponds to a configuration. The POSCAR can be opened with Notepad and visualized with VESTA software.</p> <p><br>3. fcc-Ni-Al.zip<br>- Description: fcc-Ni-Al.zip is a compressed folder. It contains Al1-xNix configurations with fcc lattice used to fit the CE. Each folder contains a POSCAR file that corresponds to a configuration. The POSCAR can be opened with Notepad and visualized with VESTA software.</p> <p><br>4. Formation enthalpies of bcc-Ni-Al.xlsx<br>- Description: Formation enthalpies of bcc lattice in Ni-Al system at different temperatures, which includes the effect of lattice vibration. The fcc Al and fcc Ni were used as reference states.</p> <p>- Variable description by columns:<br> 1-(Folder name) - type: numerical (integer)<br> Description: Each folder name in the bcc-Ni-Al.zip corresponds to a configuration<br> 2- (at. fraction of Ni (%)) - type: numerical (float)<br> Description: The atomic fraction of Ni in each configuration<br> 3- (H_f^(conf)(DFT) (eV/atom) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 0 K calculated by density functional theory (DFT).<br> 4- (H_f^(conf)(CE)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 0 K fitted by CE. <br> 6- (at. fraction of Ni (%)) - type: numerical (float)<br> Description: The atomic fraction of Ni in each configuration<br> 7- (H_f^(conf+vib) (DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 300 K calculated by DFT and bond length vs. bond stiffness relationship (L-S).<br> 8- (H_f^(conf+vib) (CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 300 K fitted by CE. <br> 10- (at. fraction of Ni (%)) - type: numerical (float)<br> Description: The atomic fraction of Ni in each configuration<br> 11- (H_f^(conf+vib) (DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 600 K calculated by DFT and L-S.<br> 12- (H_f^(conf+vib) (CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 600 K fitted by CE. <br> 14- (at. fraction of Ni (%)) - type: numerical (float)<br> Description: The atomic fraction of Ni in each configuration<br> 15- (H_f^(conf+vib) (DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 900 K calculated by DFT and L-S.<br> 16- (H_f^(conf+vib) (CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 900 K fitted by CE.<br> 18- (at. fraction of Ni (%)) - type: numerical (float)<br> Description: The atomic fraction of Ni in each configuration<br> 19- (H_f^(conf+vib) (DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1200 K calculated by DFT and L-S.<br> 20- (H_f^(conf+vib) (CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1200 K fitted by CE.</p> <p><br>5. Formation enthalpies of bcc-with-vacancies-Ni-Al.xlsx<br>- Description: Formation enthalpies of bcc lattice with vacancies in Ni-Al system at different temperatures, which includes the effect of lattice vibration and magnetism. The fcc Al and fcc Ni were used as reference states.</p> <p>- Variable description by columns:<br> 1-(Folder name) - type: numerical (integer)<br> Description: Each folder name in the bcc-with-vacancies-Ni-Al.zip corresponds to a configuration.<br> 2- (at. fraction of AlVa (%)) - type: numerical (float)<br> Description: The atomic fraction of Ni in each configuration<br> 3- (H_f^(conf)(DFT) (eV/atom) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 0 K calculated by DFT.<br> 4- (H_f^(conf)(CE)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 0 K fitted by CE. <br> 6- (at. fraction of AlVa (%)) - type: numerical (float)<br> Description: The atomic fraction of Ni in each configuration<br> 7- (H_f^(conf+vib) (DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 300 K calculated by DFT and L-S.<br> 8- (H_f^(conf+vib) (CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 300 K fitted by CE. <br> 10- (at. fraction of AlVa (%)) - type: numerical (float)<br> Description: The atomic fraction of Ni in each configuration<br> 11- (H_f^(conf+vib) (DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 600 K calculated by DFT and L-S.<br> 12- (H_f^(conf+vib) (CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 600 K fitted by CE. <br> 14- (at. fraction of AlVa (%)) - type: numerical (float)<br> Description: The atomic fraction of Ni in each configuration<br> 15- (H_f^(conf+vib) (DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 900 K calculated by DFT and L-S.<br> 16- (H_f^(conf+vib) (CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 900 K fitted by CE.<br> 18- (at. fraction of AlVa (%)) - type: numerical (float)<br> Description: The atomic fraction of Ni in each configuration<br> 19- (H_f^(conf+vib) (DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1200 K calculated by DFT and L-S.<br> 20- (H_f^(conf+vib) (CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1200 K fitted by CE.</p> <p><br>6. Formation enthalpies of fcc-Ni-Al.xlsx<br>- Description: Formation enthalpies of fcc lattice in Ni-Al system at different temperatures, which includes the effect of lattice vibration. The fcc Al and fcc Ni were used as reference states.<br>- Variable descriptions by columns are the same as those of Formation enthalpies of bcc-Ni-Al.xlsx.</p> <p><br>7. ECIs of bcc-Ni-Al at different temperatures.txt<br>- Description: ECIs of bcc lattice in Ni-Al system from 0 to 2000 K with increment step of 10 K. The ECIs at different temperatures are separated by blank lines. ECIs at 0 K means that only configurational contribution was considered. ECIs at finite temperature means that both configurational and vibrational contributions were considered.</p> <p><br>8. ECIs of bcc-with-vacancies-Ni-Al at different temperatures.txt<br>- Description: ECIs of bcc lattice with vacancies in Ni-Al system from 0 to 2000 K with increment step of 10 K. The ECIs at different temperatures are separated by blank lines. ECIs at 0 K means that only configurational contribution was considered. ECIs at finite temperature means that both configurational and vibrational contributions were considered.</p> <p><br>9. ECIs of fcc-Ni-Al at different temperatures.txt<br>- Description: ECIs of hcp lattice in Ni-Al system from 0 to 2000 K with increment step of 10 K. The ECIs at different temperatures are separated by blank lines. ECIs at 0 K means that only configurational contribution was considered. ECIs at finite temperature means that both configurational and vibrational contributions were considered.</p> <p><br>10. Clusters of bcc-Ni-Al.txt<br>- Description: Cluster information of bcc lattice in Ni-Al system. Each cluster is separated by a blank line. Each cluster contains: multiplicity; Length of the longest pair within the cluster; number of points in cluster; coordinates of point. They are arranged in a row.</p> <p><br>11. Clusters of bcc-with-vacancies-Ni-Al.txt<br>- Description: Cluster information of bcc lattice with vacancies in Ni-Al system. Each cluster is separated by a blank line. Each cluster contains: multiplicity; Length of the longest pair within the cluster; number of points in cluster; coordinates of point. They are arranged in a row.</p> <p><br>12. Clusters of fcc-Ni-Al.txt<br>- Description: Cluster information of fcc lattice in Ni-Al system. Each cluster is separated by a blank line. Each cluster contains: multiplicity; Length of the longest pair within the cluster; number of points in cluster; coordinates of point. They are arranged in a row.</p>
Vibration data of rotating machines subjected to different failure conditions
<p>These data were used for implementing a project on the analysis of failures in rotating machines, using a combined approach of exploratory data analysis and convolutional neural networks (CNNs).</p>
Collected Data on Bending, Vibration, and Push-out Tests of Shallow Steel-Timber Composite Beams – Nordic System
Open the record for dataset details and reuse information.
Raw data for "Signatures of Intra- and Intermolecular Vibrational Coupling in Halogenated Liquids Revealed by Two-Dimensional Raman-Terahertz Spectroscopy"
<p>Raw data for "Signatures of Intra- and Intermolecular Vibrational Coupling in Halogenated Liquids Revealed by Two-Dimensional Raman-Terahertz Spectroscopy"</p>
Data for Collision Induced Spin-Orbit Relaxation of Highly Vibrationally Excited NO Near 1 K
<p>Data for "<strong>Collision Induced Spin-Orbit Relaxation of Highly Vibrationally Excited NO Near 1 K" published in Natural Sciences</strong></p>
VBL-VA001: Lab-scale vibration analysis dataset
<p>This dataset is a collection of vibration data (x, y, z) from four machine conditions: normal, bearing fault, misalignment, and unbalance. There are 4000 files, each folder contains 1000 CSV files.</p> <p>Specification:</p> <ul> <li>Machine: Panasonic GP –129JXK</li> <li>Sensor: enDAQ LOG-0002-100G-DC-8GB-PC Shock & Vibration Sensor</li> <li>Length: 5 seconds per CSV file</li> <li>Sampling rate: 20 kHz.</li> </ul> <p>Repository for baseline methods: <a href="https://github.com/bagustris/vbl-va001">https://github.com/bagustris/vbl-va001</a>.</p> <p>Refer to our paper for detail: <a href="https://link.springer.com/article/10.1007/s42417-023-00959-9">https://link.springer.com/article/10.1007/s42417-023-00959-9</a></p> <p>The preprint is also available at ArXiv: <a href="https://arxiv.org/abs/2212.14732">https://arxiv.org/abs/2212.1473</a>.</p>
Buckling Metamaterials for Extreme Vibration Damping
<p>This dataset belongs to the article "Buckling Metamaterials for Extreme Vibration Damping". This dataset can be used to reproduce all data reported in this article.</p> <p><strong>Abstract</strong></p> <p>Damping mechanical resonances is a formidable challenge in an increasing number of applications. Many of the passive damping methods rely on using low stiffness dissipative elements, complex mechanical structures or electrical systems, while active vibration damping systems typically add an additional layer of complexity. However, in many cases, the reduced stiffness or additional complexity and mass render these vibration damping methods unfeasible. Here, we introduce a method for passive vibration damping by allowing buckling of the primary load path, which sets an upper limit for vibration transmission: the transmitted acceleration saturates at a maximum value, no matter what the input acceleration is. This nonlinear mechanism leads to an extreme damping coefficient tan delta ~0.23 in our metal metamaterial|orders of magnitude larger than the linear damping of traditional lightweight structural materials. We demonstrate this principle experimentally and numerically in free-standing rubber and metal mechanical metamaterials over a range of accelerations, and show that bi-directional buckling can further improve its performance. Buckling metamaterials pave the way towards extreme vibration damping without mass or stiffness penalty, and as such could be applicable in a multitude of high-tech applications, including aerospace structures, vehicles and sensitive instruments.</p> <p> </p>
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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.