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122 results for “Bending”
Suppression of Bend deformation in Active Nematics by Magnetic Field
<p>In the presence of an external magnetic field (1.8T) applied horizontally along the shear-aligned direction of the active nematic within a cuboidal channel, flows perpendicular to the field are hindered (time<6 min). This suppression arises because the active stress that distorts the nematic alignment encounters resistance from nematic elasticity and the externally applied magnetic field. When the magnetic field is switched off (time>6 min) (indicated by spikes in PIV vector magnitude due to sample holder movement), the nematic undergoes a bend deformation, initiating flows perpendicular to the field direction. This observation suggests that the magnetic field's influence lies in aligning the liquid crystal rather than disrupting the active stress through interference with motor proteins.</p>
Bending mode data for Rubin Observatory Simonyi Survey Telescope
<p>Bending mode data for Rubin Observatory Simonyi Survey Telescope</p> <p>Bending modes sags are represented as sums of Zernike polynomials and a bicubic spline for each mirror.</p> <p>Source of bending mode data is: https://github.com/bxin/ZEMAX_FEMAP/tree/main</p> <p>To resolve an extrapolation error in previous legacy bending modes, new modes were created by:</p> <ol> <li>Reading original unit load cases</li> <li>Weighting unit load case forces to match previously determined bending mode forces</li> <li>Applying above weights to unit load surface deviations</li> <li>Decomposing into Zernikes + bicubic splines</li> </ol> <p>The corresponding actuator forces for these bending modes can be found in:</p> <ul> <li>https://github.com/bxin/ZEMAX_FEMAP/tree/main/0M1M3Bending/2bendingModes</li> <li>https://github.com/bxin/ZEMAX_FEMAP/tree/main/1M2Bending/2bendingModes</li> </ul> <p>Representative files:</p> <ul> <li> <p><strong>M1M3_bend_zk.fits.gz</strong>: Zernike coefficients (in meters) for M1M3 sag perturbations. 20 modes x 29 coefficients</p> </li> <li> <p><strong>M1M3_bend_forces.fits.gz</strong>: Forces on each actuator for each bending mode. 20 modes x 156 actuators</p> </li> <li> <p><strong>M1M3_actuator_table.fits.gz</strong>: IDs and locations of actuators.</p> </li> <li> <p><strong>M1_bend_coords.fits.gz</strong>: Grid coordinates for bicubic spline nodes on M1. 2 dimensions x 204 points</p> </li> <li> <p><strong>M1_bend_grid.fits.gz</strong>: Bicubic spline coefficients on M1. First dimension is split into z, dz/dx, dz/dy, dz^2/dxdy. Second dimension is 20 bending modes. Third and fourth dimensions are x and y grid locations.</p> </li> <li> <p><strong>bend.yaml</strong>: YAML file indicating which grid coordinates, grid, and Zernikes to use for each mirror. Also indicates inner and outer radii of annuli for Zernike components, and the ordering of modes to use inside of the batoid_rubin package.</p> </li> </ul> <p>Additional files for M2 or M1 and M3 separately follow the same pattern described above.</p>
PTT-subtracted Bending mode data for Rubin Observatory Simonyi Survey Telescope
<p>Piston/Tip/Tilt-subtracted bending mode data for Rubin Observatory Simonyi Survey Telescope</p> <p>Bending modes sags are represented as sums of Zernike polynomials and a bicubic spline for each mirror.</p> <p>Piston, Tip, and Tilt terms have been removed from each mirror in this dataset.</p> <p>Source of bending mode data is: https://github.com/bxin/ZEMAX_FEMAP/tree/main</p> <p>To resolve an extrapolation error in previous legacy bending modes, new modes were created by:</p> <ol> <li>Reading original unit load cases</li> <li>Removing piston/tip/tilt from unit load surface deviations</li> <li>Weighting unit load case forces to match previously determined bending mode forces</li> <li>Applying above weights to unit load surface deviations</li> <li>Decomposing into Zernikes + bicubic splines</li> </ol> <p>The corresponding actuator forces for these bending modes can be found in:</p> <ul> <li>https://github.com/bxin/ZEMAX_FEMAP/tree/main/0M1M3Bending/2bendingModes</li> <li>https://github.com/bxin/ZEMAX_FEMAP/tree/main/1M2Bending/2bendingModes</li> </ul> <p>Representative files:</p> <ul> <li> <p><strong>M1M3_bend_zk.fits.gz</strong>: Zernike coefficients (in meters) for M1M3 sag perturbations. 20 modes x 29 coefficients</p> </li> <li> <p><strong>M1M3_bend_forces.fits.gz</strong>: Forces on each actuator for each bending mode. 20 modes x 156 actuators</p> </li> <li> <p><strong>M1M3_actuator_table.fits.gz</strong>: IDs and locations of actuators.</p> </li> <li> <p><strong>M1_bend_coords.fits.gz</strong>: Grid coordinates for bicubic spline nodes on M1. 2 dimensions x 204 points</p> </li> <li> <p><strong>M1_bend_grid.fits.gz</strong>: Bicubic spline coefficients on M1. First dimension is split into z, dz/dx, dz/dy, dz^2/dxdy. Second dimension is 20 bending modes. Third and fourth dimensions are x and y grid locations.</p> </li> <li> <p><strong>bend.yaml</strong>: YAML file indicating which grid coordinates, grid, and Zernikes to use for each mirror. Also indicates inner and outer radii of annuli for Zernike components, and the ordering of modes to use inside of the batoid_rubin package.</p> </li> </ul> <p>Additional files for M2 or M1 and M3 separately follow the same pattern described above.</p>
Legacy bending mode data for Rubin Observatory Simonyi Survey Telescope
<p>Legacy bending mode data for Rubin Observatory Simonyi Survey Telescope</p> <p>Bending modes sags are represented as sums of Zernike polynomials and a bicubic spline for each mirror.</p> <p>Source of bending mode data is: https://github.com/bxin/ZEMAX_FEMAP/tree/main/2senM/0bendingModeGridFiles</p> <p>The corresponding actuator forces for these bending modes can be found in:</p> <ul> <li>https://github.com/bxin/ZEMAX_FEMAP/tree/main/0M1M3Bending/2bendingModes</li> <li>https://github.com/bxin/ZEMAX_FEMAP/tree/main/1M2Bending/2bendingModes</li> </ul> <p>Representative files:</p> <ul> <li> <p><strong>M1M3_bend_zk.fits.gz</strong>: Zernike coefficients (in meters) for M1M3 sag perturbations. 20 modes x 29 coefficients</p> </li> <li> <p><strong>M1M3_bend_forces.fits.gz</strong>: Forces on each actuator for each bending mode. 20 modes x 156 actuators</p> </li> <li> <p><strong>M1M3_actuator_table.fits.gz</strong>: IDs and locations of actuators.</p> </li> <li> <p><strong>M1_bend_coords.fits.gz</strong>: Grid coordinates for bicubic spline nodes on M1. 2 dimensions x 204 points</p> </li> <li> <p><strong>M1_bend_grid.fits.gz</strong>: Bicubic spline coefficients on M1. First dimension is split into z, dz/dx, dz/dy, dz^2/dxdy. Second dimension is 20 bending modes. Third and fourth dimensions are x and y grid locations.</p> </li> <li> <p><strong>bend.yaml</strong>: YAML file indicating which grid coordinates, grid, and Zernikes to use for each mirror. Also indicates inner and outer radii of annuli for Zernike components, and the ordering of modes to use inside of the batoid_rubin package.</p> </li> </ul> <p>Additional files for M2 or M1 and M3 separately follow the same pattern described above.</p>
Data from: Origins of mammalian vertebral function revealed through digital bending experiments
Open the record for dataset details and reuse information.
Defect tolerance of lead-halide perovskite (100) surface relative to bulk: band bending, surface states, and characteristics of vacancies (dataset)
<p>This repository contains an input data set as well as the output data that were used in a study of surface and bulk defects in cubic CsPbI<sub>3</sub>. using a Vienna ab initio simulation package (VASP) and PyDEF 2 package for processing of defect calculations. More details about organization of the dataset can be found within REDME.txt files</p>
Data for: Experiment on hydrodynamic characteristics of plunging flows in bedrock canyon bends
<p>The dataset is about the hydrodynamic characteristics of plunging flows in bedrock bends. The dataset includes raw data of bed topography of the Ciping Reservoir canyon section of Jinghe River and the bed of the flume experiments, flow field along the center profiles of plain- and undulating-beds conditions, and the bed shear stress of plain- and undulating-beds conditions.</p>
Bacterial histone HBb from Bdellovibrio bacteriovorus compacts DNA by bending
<p>This repository contains the DNA affinity purification sequencing (DAP-seq) data, for two biological replicates, as used in the following manuscript:<br><br>Yimin Hu, Samuel Schwab, Silvia Deiss, Pedro Escudeiro, Joe D. Joiner, Marcus D. Hartmann, Andrei N. Lupas, Birte Hernandez Alvarez, Vikram Alva, and Remus T. Dame. 'Bacterial Histone HBb from <i>Bdellovibrio Bacteriovorus</i> Compacts DNA by Bending'. bioRxiv, 27 September 2023. https://doi.org/10.1101/2023.02.26.530074.<br><br>There are four types of data in this repository:</p><ul><li>Paired-end FASTQ files, containing the raw Illumina reads (<i>raw_reads</i> folder).</li><li>Raw read QC reports, generated by the nf-core/chipseq pipeline (<i>fastqc</i> folder).</li><li>BAM files, generated by the nf-core/chipseq pipeline (<i>bam</i> folder).</li><li>bigWig files, generated by the nf-core/chipseq pipeline (<i>bigwig</i> folder).</li></ul><p>Abstract:<br>Histones are essential for genome compaction and transcription regulation in eukaryotes, where they assemble into octamers to form the nucleosome core. In contrast, archaeal histones assemble into dimers that form hypernucleosomes upon DNA binding. Although histone homologs have recently been identified in bacteria, their DNA-binding characteristics remain largely unexplored. Our study reveals that the bacterial histone HBb is indispensable for the survival of <i>Bdellovibrio bacteriovorus</i>, suggesting critical roles in DNA organization and gene regulation. We also elucidate the crystal structure of the HBb dimer at 1.06 Å resolution and employ various biophysico-chemical approaches to show its ability to bind and compact DNA in a sequence-independent manner. This binding induces DNA bending, similar to that observed with bacterial HU/IHF family proteins. Finally, using DNA affinity purification and sequencing, we reveal that HBb binds along the entire genomic DNA of <i>B. bacteriovorus</i> without sequence specificity. These unique DNA-binding properties of bacterial histones, distinct from their archaeal and eukaryotic counterparts, highlight the diverse roles that histones can play in DNA organization across the domains of life.<br><br>To whom correspondence should be addressed (E-mail):<br>birte.hernandez@tuebingen.mpg.de, or vikram.alva@tuebingen.mpg.de, or rtdame@chem.leidenuniv.nl</p>
Spatial Data Recovery and Resilience of Oyster Reefs in the Big Bend of Florida
<p><strong>Project:</strong> Recovery and Resilience of Oyster Reefs in the Big Bend of Florida</p> <p><a href="https://wec.ifas.ufl.edu/oysterproject/">https://wec.ifas.ufl.edu/oysterproject/</a></p> <p><strong>Lone Cabbage Reef Restoration Spatial Data (2017-2023) Repository:</strong></p> <p><a href="../communities/lonecabbagereef">https://zenodo.org/communities/lonecabbagereef</a></p> <p><strong>Contact:</strong> Joe Aufmuth, University of Florida, George A. Smathers Libraries, Academic Research and Consulting Services Department, <a href="mailto:mapper@ufl.edu">mapper@ufl.edu</a>, (352) 273-0371.</p> <p><strong>Clarifying Publication: </strong>Aufmuth, Moore, Pine, and Ennis (2024 in progress), An Oyster’s Pearl: Restoring the Elevation of Lone Cabbage Reef, Florida.</p> <p>The repository contains ArcGIS Map Packages (v3.2.0) that are listed in the repository file Descriptions_Lone_Cabbage_Reef_map_package_list_xls. </p> <p><strong>Purpose:</strong> Data collected varies in scale as well as positional and attribute accuracy. It is the responsibility of the user to verify that the data are appropriate for their project. No warranties or guarantees are made that the data are appropriate for uses other than the Recovery and Resilience of Oyster Reefs in the Big Bend of Florida project.</p> <p><strong>Data Collection:</strong> Elevation data was collected through professional certified surveyors (Lone Cabbage Reef 2017, 2018, and 2021) as well as through field data collection efforts using Trimble survey grade GPS equipment (University of Florida 2019). Oyster count data locations were collected through field efforts and mapped to field transects using Juniper GPS survey equipment (2018, 2019, 2020, 2021, 2022, 2023). Other spatial data layers included in this data set are credited in the layouts that produce the individual maps in the map packages.</p>
Data from "Bending the course of evolution: how mutualistic interactions affect macroevolutionary dynamics of diversification in mimetic Ithomiini butterflies"
<p>Data and codes for the analyses from Chazot et al. "Bending the course of evolution: how mutualistic interactions affect macroevolutionary dynamics of diversification in mimetic Ithomiini butterflies". Check README for more information about the files. </p>
Light-driven multidirectional bending in artificial muscles dataset
<h1>General Description</h1> <p>This dataset accompanies our research on the development of programmable artificial muscles. By integrating photothermal components into shape memory polymer actuators, we have created a system that exhibits on-command multidirectional bending, controlled by illumination intensity and the chirality of the actuators. The dataset showcases the rapid response of these artificial muscles, with reaction times significantly faster than natural heliotropic systems.</p> <p>The Python code that processes shared data can be found at <a href="https://github.com/p3d2/LTCAM">https://github.com/p3d2/LTCAM</a>.</p> <h1>About Dataset</h1> <p>The folder "data" (inside data.zip) contains thermal videos and recordings of yarns for photothermal actuation measurements. Zahra Madani produced and extruded the filaments, Maija Vaara and Laura Koskelo twisted and winded the filaments, Susobhan Das, and Camilo Arias made the photoactivation recordings and Pedro Silva made the measurements. Samples names can be found in the table below and measurements were performed not sequentially. The "Materials Characterization.zip" contains DMA, DSC, FTIR, Rheology, Tensile, and TGA measurements. The following information in this readme considers the documents inside the data folder only. </p> <h3>Folders, Files & File formats</h3> <p>If the data includes images or audio, you can mention the file format eg.(.svg, .png, .mpeg)</p> <ul> <li>LTCAM:<br>- 14 npy pixel data with temperatures (mat files)<br>- 14 npy time data (time files)<br>- Supplementary images of samples and experimental setup</li> <li>Butterfly: <br>- 2 npz pixel with temperatures and time data<br>- 2 mp4 recordings of the activation of wings</li> <li>Rotating:<br>- 6 npz pixel with temperatures and time data<br>- 6 mp4 recordings of activation of samples in a rotating platform</li> </ul> <h3>Optical parameters setup for 'LTCAM' experiments</h3> <ul> <li><strong>Laser specification</strong>: Ultrafast laser with pulse width 230 fs and repetition rate 2kHz. (Spectra-Physics, TOPAS)</li> <li>Incident wavelength: 800nm (Horizontal polarization)</li> <li>Beam Diameter: 5 mm</li> <li>Average Power: tunable based on experimental need</li> <li>Beam Diameter is larger than the width of the sample. Therefore, to calculate the effective incident power, it has to be the fraction of the total power based on the area of the sample exposed.</li> <li><strong>Lens System</strong>: A part of experiment is done under the focused light condition with a lens of 100mm focal length.</li> <li><strong>Power Meter</strong>: Thorlab Power meter (Model No. S401C) is used to measure the incident power on the sample.(Wavelength range: 190nm to 20000nm). <br>- Setup photo:<br><br><br></li> </ul> <h3>Optical parameters setup for 'Butterfly' and 'Rotating' experiments</h3> <ul> <li>Laser: Cobolt 06-MLD | 808 nm | max power = 100 mW</li> <li>Setup photo:</li> </ul> <h1>LTCAM Samples details</h1> <p>Pictures of samples:</p> <p>| Name in the article | Sample No. | Mandrel Dia (mm) | Original length (cm) | Twisting (rounds) | Twists/cm | Twisting Direction | coiling direction |<br>| ---------- | ---------- | ----------- | ---------------- | ------------- | -------- | ------------- | ------------ |<br>| ZSØ1A | M733 | 1 | 50 | 260 | 5.20 | z | s |<br>| ZSØ2A | M734 | 2 | 50 | 301 | 6.02 | z | s |<br>| ZSØ1B | M781 | 1 | 50 | 258 | 5.16 | z | s |<br>| ZSØ1C | M782 | 1 | 50 | 262 | 5.24 | z | s |<br>| ZSØ2B | M783 | 2 | 48 | 270 | 5.63 | z | s |<br>| ZSØ2C | M784 | 2 | 50 | 227 | 4.54 | z | s |<br>| ZZØ2A | M785 | 2 | 50 | 339 | 6.78 | s | s |<br>| ZZØ2B | M786 | 2 | 50 | 226 | 4.52 | s | s |</p> <h3>Experiments 'LTCAM'</h3> <p>| Filename | Sample name | Laser power (mW) | Time ON (s) | Time OFF (s) | Cycles |<br>|-------------------|----------------|---------------------|---------------|---------------|--------|<br>| 230414_112622 | ZSØ2A | 50 | 60 | 30 | 1 |<br>| 230414_112851 | ZSØ2A | 100 | 60 | 30 | 1 |<br>| 230414_113149 | ZSØ2A | 150 | 60 | 30 | 1 |<br>| 230414_113420 | ZSØ2A | 200 | 60 | 30 | 1 |<br>| 230414_113656 | ZSØ2A | 250 | 60 | 30 | 1 |<br>| 230414_113955 | ZSØ2A | 300 | 60 | 30 | 1 |<br>| 230414_114838 | ZSØ1B | 300 | 30 | 30 | 3 |<br>| 230414_115518 | ZSØ1C | 300 | 30 | 30 | 3 |<br>| 230414_120115 | ZSØ2B | 300 | 30 | 30 | 3 |<br>| 230414_120714 | ZSØ2C | 300 | 30 | 30 | 3 |<br>| 230414_121714 | ZZØ2B | 300 | 30 | 30 | 3 |<br>| 230414_122255 | ZZØ2A | 300 | 30 | 30 | 3 |<br>| 230414_122808 | ZSØ2A | 300 | 30 | 30 | 3 |<br>| 230414_123244 | ZSØ1A | 300 | 30 | 30 | 3 |</p> <h3>Experiments 'Butterfly'</h3> <p>| Filename (Recording) | Filename (IR video) | Laser power (mW) | Time ON (s) | Time OFF (s) | Cycles | Obs. |<br>|---------------------------|----------------------|---------------------|---------------|---------------|--------|------------------------|<br>| 20231002_134454162 | 231002_164924 | 100 | 1 | 1 | 100 | Left wing activation |<br>| 20231002_135842563 | 231002_170312 | 100 | 1 | 1 | 100 | Right wing activation |</p> <h3>Experiments 'Rotating'</h3> <p>| Filename (Recording) | Filename (IR video) | Laser power (mW) | Time ON (s) | Rotation deg/s (measured) |<br>|---------------------------|-----------------------|---------------------|-------------|--------------------------------|<br>| 20231003_073512244 | 231003_103940 | 100 | 120 | -28.0 |<br>| 20231003_073755982 | 231003_104223 | 100 | 120 | -6.6 |<br>| 20231003_074535766 | 231003_105003 | 100 | 120 | -15.3 |<br>| 20231003_085141041 | 231003_115608 | 100 | 120 | 5.2 |<br>| 20231003_085417756 | 231003_115845 | 100 | 120 | 27.3 |<br>| 20231003_085716949 | 231003_120144 | 100 | 120 | 12.8 |</p> <p> </p>
PMMA 3 point bending test until failure loaded in displacement
<p>This document present the 3 point bending test results for PMMA. Digital Image Correlation (DIC) was used to measure displacements during the test. Results obtained provide the force-strain plot over time. Such results could be compared with simulation results or used as part of an experimental dataset.<br> Raw results and a complete dataset are provided with this data package.</p>
In situ clamped beam bending of accumulative roll bonded Cu/Nb with 16 nm individual layer thickness
<p>In situ scanning electron microscope (SEM) videos of clamped beam bending of Cu/Nb ARB nanolaminates with 16 nm layer thickness. Each video contains the video captured with SEM and the corresponding measured load vs. displacement curve.</p> <p>The beams were fabricated using focused ion beam (FIB) milling from bulk Cu/Nb sample produced in Los Alamos National Lab, USA. The sample was made using accumulative roll bonding (ARB) process, described in ref. [1]. </p> <p>All the beam lengths are aligned with rolling direction (RD) of the sample. Each beam has a rectangular notch located in the center of the beam length. Each notch spans through the beam width. Owing to limited accuracy of FIB, the notch depth was not always same at the front and rear sides of the beam (typically, smaller at the rear sides)</p> <p>Beam geometries:</p> <p>Id | Length, µm | Width, µm | Thickness, µm | Notch depth (front), nm | Notch width (front), nm</p> <p>ARBRD1 | 40 | 4.9 | 4.2 | 800 | 180</p> <p>ARBRD2 | 40 | 5.1 | 2.4 | 350 | 160</p> <p>All the beams were loaded using Hysitron PI85 picoindenter with truncated cone shape (5 µm diameter). The indenter tip was aligned with the notch location and the middle of beam width. </p> <p>All the beams were loaded under displacement control with displacement rates between 2nm/s to 10nm/s until failure.</p> <p>The SEM videos were captured using JEOL JSM-7600F SEM. </p> <p>[1] Irene J Beyerlein et al. “Interface-driven microstructure development and ultra high strength of bulk nanostructured Cu-Nb multilayers fabricated by severe plastic deformation”. In: Journal of materials research 28.13 (2013), pp. 1799–1812</p>
In situ clamped beam bending of physical vapor deposited Cu/Nb nanolaminate with 20 nm individual layer thickness
<p>In situ scanning electron microscope (SEM) videos of clamped beam bending of Cu/Nb PVD nanolaminate with 20 nm layer thickness and 42+-10 nm grain size at the surface layer. Each video contains the video captured with SEM and the corresponding measured load vs. displacement curve.</p> <p>The beams were fabricated using focused ion beam (FIB) milling from the Cu/Nb sample produced in Los Alamos National Lab, USA. The sample was made using magnetron sputtering, described in ref. [1]. </p> <p>Each beam has a rectangular notch located in the center of the beam length. Each notch spans through the beam width. Owing to limited accuracy of FIB, the notch depth was not always same at the front and rear sides of the beam (typically, smaller at the rear sides)</p> <p>Beam geometries:</p> <p>Id | Length, µm | Width, µm | Thickness, µm | Notch depth (front), nm | Notch width (front), nm</p> <p>PVD1 | 29 | 5 | 1.6 | 380 | 120</p> <p>PVD2 | 29 | 5 | 1.5 | 290 | 305</p> <p>All the beams were loaded using Hysitron PI85 picoindenter with truncated cone shape (5 µm diameter). The indenter tip was aligned with the notch location and the middle of beam width. </p> <p>All the beams were loaded under displacement control with displacement rates between 2nm/s to 10nm/s until failure.</p> <p>The SEM videos were captured using JEOL JSM-7600F SEM. </p> <p>[1] D. Bhattacharyya et al. “Transmission electron microscopy study of the deformation behavior of Cu/Nb and Cu/Ni nanoscale multilayers during nanoindentation”. In: Journal of Materials Research 24.3 (2009), pp. 1291-1302. </p>
BIR-MicroED: TEM image series revealing bend contour motion in static microcrystals (biotin, Zn(II)-methionine, Co(II)-porphyrin, AVAAGA) and diffraction patterns acquired from the same crystals at 200 kV
<p>This deposition contains a series zip files each containing TEM image series and electron diffraction images in .mrc file format. Each folder collects data acquired from crystals of a particular compound under the same conditions (electron energy, temperature). Zip files are named according to the format: <em>"CompoundName</em>_bendcontour_imageseries_<em>AcceleratingVoltage</em>_<em>Temperature</em>.zip"</p> <p>Data is further divided into sub-directories according to the particular crystal studied (crystal1, crystal2, crystal3), each containing a TEM image series (name format: "<em>CompoundName</em>_static_imageseries_<em>AcceleratingVoltage</em>_<em>Temperature</em>_crystal#.mrc") and 10 diffraction snapshots (2 frames each, each convering 1 second of electron beam exposure) acquired at equally spaced time intervals throughout the image series. These are named according to the format:</p> <p>"CompoundName_bendcontour_crystal#_diffraction_snap#.mrc"</p>
BEND Dataset Revised
<p>Data from the BEND dataset (https://arxiv.org/abs/2311.12570)</p> <p>HDF5 files and bed files were combined into single parquet files. </p>
Seeing the piles of the velvet bending under our finger sliding over a tactile stimulator improves the feeling of the fabric
<p>Using friction modulation to simulate fabrics with a tactile stimulator (i.e. virtual surface) is not<br>sufficient to render fabric touch and even more so for hairy fabrics. We hypothesized that seeing<br>the pile of the velvet darken or lighten depending on changes in the finger movement direction<br>on the virtual surface should improve the velvet fabric rendering.</p> <p><strong>Experiment 1</strong> : Participants actively rubbed a tactile device or a velvet fabric looking at a screen that showed a synthesized image of a velvet which either remained static (V-static) or darkening/lightening with the direction of touch (V-moving). We showed that in V-moving condition, the touched surface was always perceived rougher, which is a descriptor of a real velvet<strong>.</strong></p> <p><em>Files : data_brutes.csv</em> and <em> ordre_xx_c.csv</em> for data,<em> Calculus_data_expe1.Rmd</em> for code</p> <p><strong>Experiment 2</strong> : Using electroencephalography and sources localization analyses, we found increased activity in the occipital and inferiorparietal lobes when seeing dark and shinning traces during back and forth finger<br>movements over the virtual surface. This suggests that these two posterior cortical regions work<br>together to evaluate visuo-tactile congruence between the seen and the felt (tactile). The visuotactile binding, evidenced by neural synchronization (specifically, theta band [5-7 Hz] oscillation) in the left inferior posterior parietal lobule, is consistent with enhanced integration of information and likely contributed to the emergence of a more realistic velvet representation. </p> <p><em>Files </em>: <em>EEG time frequency individual data.xlsx</em> and all <em>.eeg</em></p>
Studying gastrulation by invagination: the bending of a cell sheet by mechanical cell properties using 3D deformable cell based simulations
<p>This dataset contains the scripts and end results of invagination simulation experiments.<br>The data are the results of a 3D cell based model that was used to investigate invagination: the bending of a cell sheet, and uses cell-cell adhesion, apical constriction, cell volume conservation, collision detection and handeling.</p>
Bending and Looping of long DNA by Polycomb repressive complex 2 revealed by AFM imaging in liquid
<p><span>Polycomb repressive complex 2 (PRC2) is a histone methyltransferase that methylates histone H3 at Lysine 27. PRC2 is critical for epigenetic gene silencing, cellular differentiation, and the formation of facultative heterochromatin. It can also promote or inhibit oncogenesis. Despite this importance, the molecular mechanisms by which PRC2 compacts chromatin are relatively understudied. Here, we visualized the binding of PRC2 to naked DNA in liquid at the single-molecule level using atomic force microscopy. Analysis of the resulting images showed PRC2, consisting of 5 subunits (EZH2, EED, SUZ12, AEBP2, and RBBP4), bound to a 2.5-kbp DNA with an apparent dissociation constant (<em>K</em><sub>d</sub><sup>App</sup>) of 150 ± 12 nM. PRC2 did not show sequence-specific binding to a region of high GC content (76%) derived from a CpG island embedded in such a long DNA substrate. At higher concentrations, PRC2 compacted DNA by forming DNA loops typically anchored by two or more PRC2 molecules. Additionally, PRC2 binding led to a 3-fold increase in the local bending of DNA's helical backbone and no evidence of DNA wrapping around the protein. We suggest that the bending and looping of DNA by PRC2, independent of PRC2's methylation activity, may contribute to heterochromatin formation and therefore epigenetic gene silencing. </span></p>
Bending strain in 3D topological semi-metals
<p>We present an experimental set-up for the controlled application of strain gradients by mechanical piezoactuation on 3D crystalline microcantilevers that were fabricated by focused ion beam machining. A simple sample design tailored for transport characterization under strain at cryogenic temperatures is proposed. The topological semi-metal Cd<sub>3</sub>As<sub>2</sub> serves as a test bed for the method, and we report extreme strain gradients of up to 1.3%μm<sup>−1</sup> at a surface strain value of≈0.65% at 4K. Interestingly, the unchanged quantum transport of the cantilever suggests that the bending cycle does not induce defects via plastic deformation. This approach is a first step towards realizing transport phenomena based on structural gradients, such as artificial gauge fields in topological materials.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.