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40 results for “Polarisation”
Spin-SILC cosmic microwave background (CMB) polarisation maps R1 of Planck PR2 data
<p>Clean maps of the CMB linear polarisation <em>E</em>/<em>B</em> and Stokes <em>Q</em>/<em>U</em> fields (as measured by Planck; public data release PR2). They are constructed with a novel internal linear combination (ILC) algorithm using spin, directional, scale-discretised wavelets – Spin, Scale-discretised, directional wavelet ILC or Spin-SILC.</p>
Videos of the processed microscope images and time series of the petrophysical parameters from image processing and geochemical simulation and of the measured induced polarisation [Video][Dataset]
<p>Supporting Information for the manuscript <em>Microfluidics and spectral induced polarization for direct observation and petrophysical modeling of calcite dissolution</em> published in Geophysical Research Letters</p> <ul> <li><strong>Data Set S1.</strong> Porosity, water saturation, and calcite sample perimeter from image<br>processing.</li> <li><strong>Data Set S2.</strong> Porosity, water conductivity, and pH from geochemical simulation.</li> <li><strong>Data Set S3.</strong> Real and imaginary components of the complex electrical conductivity at<br>2.5 Hz and CEC from petrophysical modeling.</li> <li><strong>Movie S1.</strong> Dissolution of the calcite sample with the detected contour superimposed in<br>white on the grayscale images. Time, length scale, and flow direction are indicated. In<br>case of problems launching the file, we recommend using VLC Media Player software.</li> <li><strong>Movie S2.</strong> Segmented images of the CO2 bubbles produced by the calcite dissolution.<br>Time, length scale, and flow direction are indicated. In case of problems launching the<br>file, we recommend using VLC Media Player software.</li> </ul>
Dataset for "Helicity proxies from linear polarisation of solar active regions"
<p>The <span class="math-tex">\(\alpha\)</span> effect is believed to play a key role in the generation of the solar magnetic field. A fundamental test for its significance in the solar dynamo is to look for magnetic helicity of opposite signs in the two hemispheres, and at small and large scales. However, measuring magnetic helicity is compromised by the inability to fully infer the magnetic field vector from observations of solar spectra, caused by what is known as the <span class="math-tex">\(\pi\)</span> ambiguity of spectropolarimetric observations. We decompose linear polarisation into parity-even and parity-odd <em>E</em> and <em>B</em> polarisations, which are not affected by the <span class="math-tex">\(\pi \)</span> ambiguity. Furthermore, we study whether the correlations of spatial Fourier spectra of <em>B</em> and parity-even quantities such as <em>E </em>or temperature <em>T</em> are a robust proxy for magnetic helicity of solar magnetic fields. We analyse polarisation measurements of active regions observed by the Helioseismic and Magnetic Imager on board the Solar Dynamics observatory. Theory predicts the magnetic helicity of active regions to have, statistically, opposite signs in the two hemispheres. We then compute the parity-odd <em>EB</em> and <em>TB</em> correlations, and test for systematic preference of their sign based on the hemisphere of the active regions. We find that: (i) <em>EB</em> and <em>TB</em> correlations are a reliable proxy for magnetic helicity, when computed from linear polarisation measurements away from spectral line cores, and (ii) <em>E</em> polarisation reverses its sign close to the line core. Our analysis reveals Faraday rotation to not have a significant influence on the computed parity-odd correlations. The <em>EB</em> decomposition of linear polarisation appears to be a good proxy for magnetic helicity independent of the <span class="math-tex">\(\pi\)</span> ambiguity. This allows us to routinely infer magnetic helicity directly from polarisation measurements.</p> <p>The full article can be found at https://arxiv.org/abs/2001.10884</p>
Supplementary files for "Pressure-enhanced ferroelectric polarisation in polar perovskite-like [C2H5NH3]Na0.5Cr0.5(HCOO)3 metal-organic framework"
<p>DFT optimised structures for the paper: Pressure-enhanced ferroelectric polarisation in polar perovskite-like [C2H5NH3]Na0.5Cr0.5(HCOO)3 metal-organic framework. See the paper for additional information on the computational setup.</p> <p>Files are named HP or LP for high-pressure and low-pressure phases, followed by the pressure as calculated by DFT. The HP structure was optimized in two different space groups and are labelled accordingly. The DFT optimized structure without volume restrictions is found in opt-vol.POSCAR</p> <p> </p>
Tutorial Photonics Explorer Module 5: Polarisation
<p>Photonics Austria (PhAu) has conducted Teacher Training Programmes - the Photonics Explorer- about Photonics in order to promote the potential of photonics to enliven physics lessons. This video is concerned with the topic polarisation and optical activity. </p>
◂Fig. 3 Gynoecium of C. crenata %yellow frames), C. cf. grandicalyx %blue frames) and C. sinensis %pink frames; A, B stack shot images; C–K light microscopy; G polarised light; TS in horizontal orientation). A, B Anthetic female flower, calyx and corolla partly removed. B LS of gynoecium. C LS of functionally female flower %note strongly stained peripheral tissue of corolla, anther and gynoecium). D LS of gynoecium. E, F TS of functionally female flower %note strongly stained, peripheral tissue). G TS of functionally female flower %note crystal deposition). H LS of ovule %note stalked embryo sac). J TS of functionally male flower with non-functional ovules. K LS of functionally male flower %style lacking, original position indicated by an asterisk) %LS, longisection; TS, transverse section; a,anther; bs, basal septum; c, calyx; car, carpel; co, corolla; db, dorsal bundles; es, embryo sac; fs, false septum; lb, lateral bundles; o, ovule; stg, stigma; sty, style; t, trichomes; tt, transmission tissue; ut, peripheral, strongly stained tissue; vb, ventral bundles; vs, ventral slit) in Observations on flower and fruit anatomy in dioecious species of Cordia (Cordiaceae, Boraginales) with evolutionary interpretations
◂Fig. 3 Gynoecium of C. crenata %yellow frames), C. cf. grandicalyx %blue frames) and C. sinensis %pink frames; A, B stack shot images; C–K light microscopy; G polarised light; TS in horizontal orientation). A, B Anthetic female flower, calyx and corolla partly removed. B LS of gynoecium. C LS of functionally female flower %note strongly stained peripheral tissue of corolla, anther and gynoecium). D LS of gynoecium. E, F TS of functionally female flower %note strongly stained, peripheral tissue). G TS of functionally female flower %note crystal deposition). H LS of ovule %note stalked embryo sac). J TS of functionally male flower with non-functional ovules. K LS of functionally male flower %style lacking, original position indicated by an asterisk) %LS, longisection; TS, transverse section; a,anther; bs, basal septum; c, calyx; car, carpel; co, corolla; db, dorsal bundles; es, embryo sac; fs, false septum; lb, lateral bundles; o, ovule; stg, stigma; sty, style; t, trichomes; tt, transmission tissue; ut, peripheral, strongly stained tissue; vb, ventral bundles; vs, ventral slit)
Electrocatalysis at the Polarised Interface between Two Immiscible Electrolyte Solutions (dataset)
<p>This is a dataset used to prepare Figure 4 in the review "<strong>Electrocatalysis at the Polarised Interface between Two Immiscible Electrolyte Solutions</strong>", prepared for the journal Current Opinion in Electrochemistry.</p>
Light intensity reflected from PAAO containing samples (AoI 45 deg., 60 deg., two polarisations)
<p>The file contains raw intensity data measured in reflection mode for various material combinations: porous anodized aluminium oxide (PAAO), gold nanoparticles (Au NPs), diamond-like carbon with silver nanoparticles composite (DLC:Ag), quartz, and silicon.</p> <p>List of investigated samples:</p> <table> <thead> <tr> <th scope="col">Sample name</th> <th scope="col">Sample description</th> </tr> </thead> <tbody> <tr> <td>AJ1</td> <td>Aluminium substrate, ~241 nm thickness PAAO (anodized in 0.3 mol/L oxalic acid at 40 V for 3 min 16 s), 60 nm diameter Au NPs (dip-coated at a speed of 1 μm/s)</td> </tr> <tr> <td>AJ2</td> <td>Aluminium substrate, ~259 nm thickness PAAO (anodized in 0.3 mol/L oxalic acid at 40 V for 3 min 37 s), 60 nm diameter Au NPs (dip-coated at a speed of 1 μm/s)</td> </tr> <tr> <td>AJ3</td> <td>Aluminium substrate, ~293 nm thickness PAAO (anodized in 0.3 mol/L oxalic acid at 40 V for 4 min 8 s), 60 nm diameter Au NPs (dip-coated at a speed of 1 μm/s)</td> </tr> <tr> <td>AJ4</td> <td>Aluminium substrate, ~317 nm thickness PAAO (anodized in 0.3 mol/L oxalic acid at 40 V for 4 min 30 s), 60 nm diameter Au NPs (dip-coated at a speed of 1 μm/s)</td> </tr> <tr> <td>AJ5</td> <td>Aluminium substrate, ~345 nm thickness PAAO (anodized in 0.3 mol/L oxalic acid at 40 V for 4 min 57 s), 60 nm diameter Au NPs (dip-coated at a speed of 1 μm/s)</td> </tr> <tr> <td>AJ6</td> <td>Aluminium substrate, ~276 nm thickness PAAO (anodized in 0.3 mol/L oxalic acid at 40 V for 3 min 42 s), ~55 nm thickness, 20 V.% Ag concentration DLC:Ag (magnetron sputtered using silver target, 80 sccm argon gas flow, 5.4 sccm C<sub>2</sub>H<sub>2</sub> gas flow, 405 V voltage, 0.09-0.10 A current, 7·10<sup>-3</sup> mbar work pressure, 2 minutes 32 seconds process duration)</td> </tr> <tr> <td>AJ7</td> <td>Aluminium substrate, ~316 nm thickness PAAO (anodized in 0.3 mol/L oxalic acid at 40 V for 4 min 25 s), ~55 nm thickness, 20 V.% Ag concentration DLC:Ag (magnetron sputtered using silver target, 80 sccm argon gas flow, 5.4 sccm C<sub>2</sub>H<sub>2</sub> gas flow, 405 V voltage, 0.09-0.10 A current, 7·10<sup>-3</sup> mbar work pressure, 2 minutes 32 seconds process duration)</td> </tr> <tr> <td>AJ8</td> <td>Aluminium substrate, ~345 nm thickness PAAO (anodized in 0.3 mol/L oxalic acid at 40 V for 5 min 4 s), ~55 nm thickness, 20 V.% Ag concentration DLC:Ag (magnetron sputtered using silver target, 80 sccm argon gas flow, 5.4 sccm C<sub>2</sub>H<sub>2</sub> gas flow, 405 V voltage, 0.09-0.10 A current, 7·10<sup>-3</sup> mbar work pressure, 2 minutes 32 seconds process duration)</td> </tr> <tr> <td>Q140</td> <td>Quartz substrate, ~55 nm thickness, 20 V.% Ag concentration DLC:Ag (magnetron sputtered using silver target, 80 sccm argon gas flow, 5.4 sccm C<sub>2</sub>H<sub>2</sub> gas flow, 405 V voltage, 0.09-0.10 A current, 7·10<sup>-3</sup> mbar work pressure, 2 minutes 32 seconds process duration)</td> </tr> <tr> <td>Si140</td> <td>Silicon substrate, ~55 nm thickness, 20 V.% Ag concentration DLC:Ag (magnetron sputtered using silver target, 80 sccm argon gas flow, 5.4 sccm C<sub>2</sub>H<sub>2</sub> gas flow, 405 V voltage, 0.09-0.10 A current, 7·10<sup>-3</sup> mbar work pressure, 2 minutes 32 seconds process duration)</td> </tr> </tbody> </table> <p>The file also contains data for lamp and dark spectra. Images are for illustrative purposes and contain measured sample intensity minus dark intensity.</p> <p>The spectra were collected by a custom-made computer-controlled motorized goniometer set-up with an incandescent lamp light source and an AvaSpec-2048 (Avantes) spectrometer covering a wavelength range of 360–860 nm with 1.2 nm resolution.</p> <p>Notations inside the file: AoI - angle of incidence (45 deg. or 60 deg.), AoD - angle of detection (90 deg. is mirror reflection from 45 deg. incidence, while 120 deg. is the same for 60 deg.), pol - angle of the polarizing prism (0 deg. or 90 deg., light intensity was lower for the 0 deg.).</p>
Polarisation camera movie of single SYTOX Orange molecules on a cover glass
<p>This image dataset is a movie of the fluorescence of single SYTOX Orange molecules (S34861, Invitrogen) dispersed on a cover glass. The data was collected on a fluorescence microscope (Ti-U, Nikon) with a polarisation camera (CS505MUP, Thorlabs). The molecules were excited with a 532 nm diode laser with a measured power density at the sample plane of 0.36 kW/cm^2. An exposure time of 100 ms was used. The following filters were used: dichroic (Di03-R532-t1, Semrock) and emission filter (FF01-582/64, Semrock).</p>
Polarisation camera movies of T cells on a cover glass
<p>The plasma membrane of live T cells (J8 LFA-1) was labelled using the Nile red-derivative NR4A, and 3D movies were recorded using a polarisation camera. Two unprocessed datasets are included here:</p> <ul> <li><strong>Tcell_NR4A_EPI_stack</strong>: A 3D stack of a single T cell, imaged with the excitation in EPI configuration.</li> <li><strong>Tcell_NR4A_HILO_stack_movie</strong>: A 3D movie of live T cells interacting with an OKT3 antibody-coated cover glass, imaged with the excitation in HILO configuration.</li> </ul> <p>For each .tif file, the corresponding Micro-Manager metadata file is included.</p> <p><strong>Optical setup:</strong></p> <p>Imaging was performed on a widefield microscope equipped with a polarisation camera (CS505MUP, Thorlabs). The sample was excited using a 515 nm laser, coupled into a square-core multi-mode fiber (M97L02, Thorlabs) with a custom vibration-motor-based mode scrambler. The measured power density at the image plane was on the order of 0.004 kW/cm^2. A dichroic (Di03-R514-t1, Semrock) was used to seperate fluorescence from the excitation. The emission was filtered using a long-pass filter (FF01-515/LP, Semrock) and bandpass filter (FF01-650/200, Semrock) before detection.</p> <p><strong>Sample preparation:</strong></p> <p>J8 LFA-1 cells were incubated overnight (~18 h) in complete-RPMI (StableCell RPMI-1640 media (Sigma) supplemented with 10 % (v/v) fetal calf serum (FCS), 1 % (v/v) HEPES buffer, and 1 % (v/v) pen/strep antibiotics. 1 mL of cells were collected by centrifugation and resuspended in phenol-red free RPMI supplemented with 1 % HEPES.</p> <p>Round coverslips were rinsed with IPA, MilliQ, dried, and Ar-plasma cleaned for 20 minutes. Grace Bio-Labs CultureWells were attached, and the slide was incubated with OKT3 antibody (provided by the Human Immunology Unit, WIMM, Oxford) for 30 minutes. The slide was washed 5 times with phenol-red free RPMI supplemented with 1 % HEPES and a final wash with phenol-red free RPMI supplemented with 1 % HEPES and 200 nM NR4A before imaging.</p>
Generating spatiotemporal patterns of linearly polarised light at high frame rates for insect vision research
<p><strong>Electrophysiology dataset for the work presented in:</strong></p> <p>Supple et al., (2022) Generating spatiotemporal patterns of linearly polarised light at high frame rates for insect vision research. J. Exp. Biol. 225, jeb244087. doi:10.1242/jeb.244087</p> <p><strong>Analysis code available at:</strong> https://github.com/jacksupple/Supple22_JEB_PolDevice_DataAnalysisScripts</p> <p>Download, select all, and extract files. Navigate to the assembled folder to re-run the analysis code.</p> <p><em>Argynnis paphia</em> butterfly intracellular photoreceptor traces are located in "\Photoreceptor_data". Results of the analysed data are found in "\photoreceptor_results"</p> <p><em>Calliphora vicina</em> blowfly extracellular lobula plate tangential cell (LPTC) recordings are located in "\LPTC_data". Results of the analysed data are found in "\LPTC_results".</p> <p>"\DualDLP_Stim" contains parameter files for the rotating dot stimuli, which are used during analysis.</p>
Convolution of individual and group identity: self-reliance increases polarisation in basic opinion model
<p>Data for the manuscript</p> <p><strong>Convolution of individual and group identity: self-reliance increases polarisation in basic opinion model</strong></p> <p><strong>Quante, L.*, Stechemesser A.*, Hödtke, D. and Levermann, A. </strong></p> <p><strong>*These authors contributed equally.</strong></p> <p><strong><em>Humanit Soc Sci Commun</em> 11, 838 (2024)</strong></p> <p><a href="https://doi.org/10.1057/s41599-024-03359-w" target="_blank" rel="noopener"><strong><span>https://doi.org/10.1057/s41599-024-03359-w</span></strong></a></p> <p>Reproduction of data and figures is described in the corresponding github repository <br><a href="https://github.com/lquante/social_agent_based_modelling/tree/bf33be685547db739387a41820e8b3b7ea16cf26" target="_blank" rel="noopener">https://github.com/lquante/social_agent_based_modelling/tree/bf33be685547db739387a41820e8b3b7ea16cf26</a>.</p>
Animated plots of the spectrum and polarisation of Cassiopeia A based on a 24 hour observation with LOFAR Station IE613 (LBA)
<p>This collection of animated plots over time of the variation in channel flux for the linear polarisation channels XX, XY and YY and Stokes Parameters U, V, I and Q against frequency for Cassiopeia A as observed at LOFAR station SE607 between 2018-04-06 and 2018-04-07 using the LBA</p>
Animated plots of the spectrum and polarisation of Cassiopeia A based on a 24 hour observation with LOFAR Station IE613 (LBA)
<p>This collection of animated plots over time of the variation in channel flux for the linear polarisation channels XX, XY and YY and Stokes Parameters U, V, I and Q against frequency for Cassiopeia A as observed at LOFAR station IE613 between 2018-04-06 and 2018-04-07 using the LBA</p>
Reducing social media engagement with affectively polarised content via inoculation
<p>Datasets for validation study and experiments one - six.</p>
Dataset of phantom images captured using a multi-flash and a cross polarised probe.
<p>Data captured using two micro camera based imaging probes. One uses a multi-flash technique to eliminate specular reflections. The other uses a cross polarisation technique to overcome specular reflections. Images of embedded features in a multi-layer tissue mimicking phantom are captured using different illumination wavelengths at different depths. </p>
A Single-cell Perturbation Landscape of Colonic Stem Cell Polarisation
<p>Cancer cells are regulated by oncogenic mutations and microenvironmental signals, yet these processes are often studied separately. To functionally map how cell-intrinsic and cell-extrinsic cues co-regulate cell-fate in colorectal cancer (CRC), we performed a systematic single-cell analysis of 1,107 colonic organoid cultures regulated by 1) CRC oncogenic mutations, 2) microenvironmental fibroblasts and macrophages, 3) stromal ligands, and 4) signalling inhibitors. Multiplexed single-cell analysis revealed a stepwise epithelial differentiation landscape dictated by combinations of oncogenes and stromal ligands, spanning from fibroblast-induced Clusterin (CLU)<sup>+</sup> revival colonic stem cells (revCSC) to oncogene-driven LRIG1<sup>+</sup> hyper-proliferative CSC (proCSC). The transition from revCSC to proCSC is regulated by decreasing WNT3A and TGF-β-driven YAP signalling and increasing KRAS<sup>G12D</sup> or stromal EGF/Epiregulin-activated MAPK/PI3K flux. We find APC-loss and KRAS<sup>G12D</sup> collaboratively limit access to revCSC and disrupt stromal-epithelial communication -- trapping epithelia in the proCSC fate. These results reveal that oncogenic mutations dominate homeostatic differentiation by obstructing cell-extrinsic regulation of cell-fate plasticity.</p>
Potentiodynamic polarisation curves and pitting descriptors of 316L stainless steel in NaCl electrolyte
<div>This deposit contains all data and code supporting the analysis in:</div> <div> </div> <div>Identifying stable pitting pathways in 316L stainless steel via fractal-inspired PCA-based clustering</div> <div>Coelho L.B., Amand T., Torres D., Olivier M., Ustarroz J. (accepted 21 April 2025, npj Materials Degradation)</div> <div> </div> <div>Included files</div> <div> </div> <div>calculated_epit_data.csv – the ML-estimated critical pitting potentials (Epit)</div> <div> </div> <div>calculated_logipit_data.csv – the ML-estimated log(jₚᵢₜ) values corresponding to Epit</div> <div> </div> <div>calculated_epass_data.csv – the ML-estimated passive potentials (Epass) and log(jₚₐₛₛ)</div> <div> </div> <div>calculated_epit_df_meta_data.csv – manually curated Epit values just before stable pit growth</div> <div> </div> <div>calculated_logipit_df_meta_data.csv – manually curated log(jₚᵢₜ) values just before stable pit growth</div> <div> </div> <div>Critical-descriptor definitions</div> <div> </div> <div>The critical pitting potentials (Epit) and passive potentials (Epass) were estimated using the machine learning (ML) model described previously [1].</div> <div>The files calculated_epit_df_meta_data.csv and calculated_logipit_df_meta_data.csv contain the last metastable-pitting descriptors—manually identified—immediately prior to the onset of stable pit growth.</div> <div> </div> <div>Experimental methods</div> <div>The macro-scale potentiodynamic polarization (PP) tests were performed at varying NaCl concentrations (0.005 M, 0.01 M and 0.05 M). Using an SP-300 (Bio-Logic) potentiostat inside a Faraday cage, the cell comprised:</div> <div> </div> <div>WE: 316L SS specimen (~1 cm² exposed area)</div> <div> </div> <div>RE: Ag/AgCl/KCl_sat inside a Luggin capillary</div> <div> </div> <div>CE: platinum foil</div> <div> </div> <div>After 60 min immersion to stabilize the open-circuit potential (OCP), polarization scans ran from –30 mV to +900 mV vs. OCP at 0.5 mV/s, matching our previous macro PP study on the same sample [2]. Each NaCl concentration was tested 28 times (84 curves total).</div> <div> </div> <div>References</div> <div> </div> <div>[1] L.B. Coelho, D. Torres, V. Vangrunderbeek, M. Bernal, G.M. Paldino, G. Bontempi, J. Ustarroz, Estimating pitting descriptors of 316 L stainless steel by machine learning and statistical analysis, Npj Mater Degrad 7 (2023) 82. https://doi.org/10.1038/s41529-023-00403-z.</div> <div> </div> <div>[2] L. B. Coelho, S. Kossman, A. Mejias, X. Noirfalise, A. Montagne, A. Van Gorp, M. Poorteman, M. G. Olivier, “Mechanical and corrosion characterization of industrially treated 316L stainless steel surfaces,” Surf. Coat. Technol. 382 (2020) 125175. https://doi.org/10.1016/j.surfcoat.2019.125175</div> <div> </div> <div> </div>
Polarisation camera dSTORM datasets of actin in fixed HeLa cells labeled with phalloidin-Alexa Fluor 488
<p>Polarisation camera dSTORM dataset of the actin of fixed HeLa cells labeled with phalloidin-Alexa Fluor 488.</p> <p><strong>Image acquisition was performed as follows:</strong></p> <p>Imaging was performed on a widefield microscope equipped with a polarisation camera (CS505MUP, Thorlabs). The sample was excited using a 488 nm laser at quasi-TIRF, with a measured power density at the image plane of <span>5.04 kW/cm^2</span>. A single long-pass dichroic (Di02-R488, Semrock) was used to seperate fluorescence from the excitation. The emission was filtered using a long-pass (BLP01-488R, Semrock) and a bandpass filter (FF01-582/64, Semrock) before detection. An exposure time of 30 ms was used.</p> <p><strong>Samples were prepared as follows:</strong></p> <p><span>Cell culture: </span>HeLa TDS cells were cultured in DMEM (Gibco, Invitrogen) supplemented with 10 % Fetal Bovine Serum (FBS, Life Technologies), 1 % penicillin/streptomycin (Life Technologies), and 1 % glutamine (Life Technologies) at 37 °C + 5 % CO_2. Cells were periodically tested for mycoplasma contamination and passaged 3 times per week. Cells were plated at low density on high-precision glass coverslips (MatTek, P35G-0.170-14-C) 1 day prior to fixation for dSTORM experiments.</p> <p><span>Labeling:</span> Cells were simultaneously fixed and permeabilized in cytoskeleton buffer (CBS, 10 mM MES, 138 mM KCl, 3 mM MgCl_2, 2 mM EGTA, 4.5 % sucrose w/v, pH 7.4), + 4 % paraformaldehyde (PFA) and 0.2 % Triton for 6 minutes at 37 °C, and further fixed in CBS + 4 % PFA for 14 minutes at 37 °C. Post-fixation, cells were washed x3 in PBST (PBS supplemented with 0.1 % Tween) and permeabilized a second time in PBS + 0.5 % Triton for 5 minutes at room temperature. The samples were then washed 3 times in PBST and blocked for 30 minutes in 5 % BSA. Cells were washed x3 in PBST and then incubated with Alexa Fluor™ 488 Phalloidin (A12379, Invitrogen, 1:50 in PBS) for 1 h in the dark, followed by x2 washes in PBS. Prior to dSTORM imaging, PBS was replaced with dSTORM imaging buffer (base buffer consisting of 0.56 M glucose, 50 mM Tris (pH 8.5), and 10 mM NaCl supplemented with 5 U/mL pyranose oxidase (Sigma, P4234), 10 mM cysteamine (Sigma, 30070), 40 µg/mL catalase (Sigma, C100) and 2 mM cyclooctatetraene (Sigma, 138924).</p>
Polarisation camera TAB-PAINT dataset of alpha-synuclein fibrils using Nile red
<p>Alpha-synuclein fibrils were deposited on PLL-coated and argon plasma-cleaned coverslides. A low concentration of Nile Red (~1 nM) was added for PAINT imaging, and fluorescent beads for post-acquisition drift correction.</p> <p>The data was collected on a fluorescence microscope (Eclipse Ti-U, Nikon) with a polarisation camera (CS505MUP, Thorlabs). The molecules were excited with a 515 nm laser using epi-illumination with a measured power density at the sample plane of 6.08 kW/cm^2. An exposure time of 50 ms was used. The following filters were used: dichroic (Di03-R514-t1, Semrock) and emission filter (FF01-515/LP and FF01-650/200, Semrock). A 60x oil-immersion objective (Plan Apo, 60xA/1.40 Oil, DIC H, inf/0.17 WD 0.21, Nikon) was used for detection.</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.