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57 results for “light scattering”
Supporting experimental data for "Z-average and Polydispersity Index of Dynamic Light Scattering" by Bazzoni et al.
<p>Data (auto-correlation functions used for preparing Figure 5-8) accompanying manuscript "Z-average and Polydispersity Index of Dynamic Light Scattering" by Bazzoni et al.</p> <p> </p> <p>1. “<strong>Figure 5_ACFs.zip</strong>” Large sets of autocorrelation functions (ASCII format) recorded to demonstrate heteroscedastic and angle-dependent uncertainties. Each file may list the basic parameters, instrument’s estimation of Z-average (not evaluated and not used by us), the auto-correlation function, and a low temporal-resolution trace of the scattering intensity. Figure 5 is based on the analyses of subsets of this data set.</p> <p>2. “<strong>Figure 6 & 7_ACFs.zip</strong>” Large sets of autocorrelation functions (ASCII format) recorded to demonstrate the impact of uncertainty on precision, and the impact of duration and photon counting rate on the signal-to noise ratio. Each file may list the basic parameters, instrument’s estimation of Z-average (not evaluated and not used by us), the auto-correlation function, and a low temporal-resolution trace of the scattering intensity. Figure 6 and 7 are based on the analyses of subsets of this data set.</p> <p>3. “<strong>Figure 8_ACFs.zip</strong>” Large sets of autocorrelation functions (ASCII format) recorded to demonstrate the positive impact of data averaging on precisions. Each file may list the basic parameters, instrument’s estimation of Z-average (not evaluated and not used by us), the auto-correlation function, and a low temporal-resolution trace of the scattering intensity. Figure 8 is based on the analyses of subsets of this data set.</p>
Wavenumber-dependent dynamic light scattering optical coherence tomography measurements of collective and self-diffusion
<p>This repository contains raw data and analysis routines of the publication <strong>“<em>Wavenumber-dependent dynamic light scattering optical coherence tomography measurements of collective and self-diffusion</em>”</strong> in Optics Express (doi.org/10.1364/OE.521702)<em>. </em>The reader is free to use the scripts and data in this depository if the manuscript is correctly cited in their work. For further questions, feel free to contact the corresponding author. Python 3.11 was used for programming. Kindly note that simulating autocorrelation functions from extensive time series data, especially with a high repetition rate, can be time-consuming, often requiring more than 20-30 minutes. Despite parallelized processing routines for the measurement data, the full analysis may still take up to an hour. Please restart the kernel and run the code again if the parallelization fails. Also, keep in mind the significant RAM usage.</p> <p>We've conducted measurements using both a custom-built OCT system and the Thorlabs OCT system. The custom setup specifically focused on measuring diffusion in concentrated suspensions, while the Thorlabs OCT system was used to analyze both concentrated and dilute suspensions. To analyze the data from the custom setup, we require an additional dark measurement file. Conversely, analyzing the Thorlabs measurements necessitates a chirp interpolation file. All filenames, whether for raw data or analysis files, are sufficiently descriptive. Files obtained with the Thorlabs OCT system are easily identifiable as they contain “Thorlabs” in their names. To conduct the analysis of Thorlabs measurements, it's essential to have information regarding the time series length (number of A-scans), the number of repeats (B-scans), and the acquisition rate. The results are plotted at the end of our analysis routines, with the parameters displayed as a function of depth or wavenumber. Raw measurement files and analysis routines are described below.</p> <div> <table> <tbody> <tr> <td> <p><strong>Name</strong></p> </td> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Parameters</strong></p> </td> </tr> <tr> <td> <p>10050, 10 us.mat</p> </td> <td> <p>Interference intensity from the custom setup for the concentrated Kostrosöl 10050 sample.</p> </td> <td> <p>Na=8192, Nb=20, 4.5 kHz</p> </td> </tr> <tr> <td> <p>CS50-28, 10 us.mat</p> </td> <td> <p>Interference intensity from the custom setup for the concentrated Levasil CS50-28 sample.</p> </td> <td> <p>Na=8192, Nb=20, 4.5 kHz</p> </td> </tr> <tr> <td> <p>Mix, 10 us.mat</p> </td> <td> <p>Interference intensity from the custom setup for the concentrated mixed sample.</p> </td> <td> <p>Na=8192, Nb=20, 4.5 kHz</p> </td> </tr> <tr> <td> <p>Dark, 10 us.mat</p> </td> <td> <p>Background interference intensity from a custom setup.</p> </td> <td> <p>Na=2048, Nb=5, 4.5 kHz</p> </td> </tr> <tr> <td> <p>Concentrated 8050, Thorlabs.oct</p> </td> <td> <p>Interference intensity from the Thorlabs OCT for the concentrated Kostrosöl 8050 sample.</p> </td> <td> <p>Na=65536, Nb=10, 36 Khz</p> </td> </tr> <tr> <td> <p>Concentrated 9550, Thorlabs.oct</p> </td> <td> <p>Interference intensity from the Thorlabs OCT for the concentrated Kostrosöl 9550 sample.</p> </td> <td> <p>Na=65536, Nb=10, 36 Khz</p> </td> </tr> <tr> <td> <p>Concentrated mix, Thorlabs.oct</p> </td> <td> <p>Interference intensity from the Thorlabs OCT for the concentrated mixed sample.</p> </td> <td> <p>Na=65536, Nb=10, 36 Khz</p> </td> </tr> <tr> <td> <p>Dilute 8050, Thorlabs.oct</p> </td> <td> <p>Interference intensity from the Thorlabs OCT for the dilute Kostrosöl 8050 sample.</p> </td> <td> <p>Na=32768, Nb=20, 36 Khz</p> </td> </tr> <tr> <td> <p>Dilute 9550, Thorlabs.oct</p> </td> <td> <p>Interference intensity from the Thorlabs OCT for the dilute Kostrosöl 9550 sample.</p> </td> <td> <p>Na=32768, Nb=20, 36 Khz</p> </td> </tr> <tr> <td> <p>Dilute mix, Thorlabs.oct</p> </td> <td> <p>Interference intensity from the Thorlabs OCT for the dilute mixed sample.</p> </td> <td> <p>Na=32768, Nb=20, 36 Khz</p> </td> </tr> <tr> <td> <p>Chirp.data</p> </td> <td> <p>File containing k-interpolation data for the Thorlabs OCT measurements.</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>ReadOCTFile.py</p> </td> <td> <p>Written by Jos de Wit, this module reads and imports spectra from raw Thorlabs OCT files.</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Data_processing.py</p> </td> <td> <p>This module contains all analysis functions.</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Custom_concentrated.py</p> </td> <td> <p>The script is for analyzing raw concentrated measurement files from the custom setup.</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Thorlabs_concentrated.py</p> </td> <td> <p>The script is for analyzing raw concentrated measurement files from the Thorlabs setup.</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Thorlabs_dilute.py</p> </td> <td> <p>The script is for running analysis of raw dilute measurement files from the Thorlabs setup.</p> </td> <td> <p> </p> </td> </tr> </tbody> </table> </div> <p> </p>
The laboratory experiment for the light scattering on 3D printed lunar surface simulants at the small phase angles
<p>Data from a study submitted to JGR-Planets about a laboratory experiment of lunar fairy castle structures printed using a 3D printer. (last update: 2024.07.23)<br><br></p> <p>1. data.xlsx<br> * Each Excel sheet corresponds to the data of the sample used in the experiment.<br>(e.g., 80-40-10: sheet for the experimental data of sample "80-40-10")</p> <p>2. luna16_distant.csv and luna20_distant.csv<br>* These files contain data obtained by digitizing Figures 4 and 8 from Velichko et al. (2022) (doi: 10.1016/j.pss.2022.105475). <br>* The data obtained from distant locations of each Luna 16 and Luna 20 landing sites (See Velichko et al. (2022)).</p> <p>3. velikodsky_param.csv<br>*This file contains parameters described in Table 3 of Velikodsky et al. (2011) (doi: 10.1016/j.icarus.2011.04.021)</p> <p>4. readme.txt</p> <p>* Description of each file in detail.</p>
Differential static light scattering (DSLS) of full-length huntingtin samples of different polyQ lengths (Q19, Q23, Q42 and Q54) – 2018/05/09
<p><strong>Project</strong> - Huntingtin structure-function open lab notebook. </p> <p><strong>Experiment</strong> - Differential static light scattering (DSLS) of full-length huntingtin samples of different polyQ lengths (Q19, Q23, Q42 and Q54) – 2018/05/09. To investigate how increased polyQ length of the huntingtin protein affects its biophysical properties. </p> <p> </p>
A time-course analysis using Differential Static Light Scattering (DSLS) of purified HTT1-3144 Q23 - 2019/01/28
<p><strong>Project: </strong>Biophysical investigation of purified HTT protein samples</p> <p><strong>Experiment: </strong>A time-course analysis using Differential Static Light Scattering (DSLS) of purified HTT<sup>1-3144</sup>Q23 </p> <p><strong>Date completed:­ </strong>2019/01/28</p> <p><strong>Rationale: </strong>Time and resources in the HD field have been primarily focussed on understanding HTT aggregation looking as caspase cleavage products spanning aa. 1-586 or exon 1 spanning aa. 1-90. However, we know that HTT protein purified in its apo form is able to self-associate into larger oligomeric species and that monomer, dimer and larger species are found following FLAG-affinity chromatography as determined by size-exclusion chromatography (SEC) and SEC-multi-angle light scattering (SEC-MALS). This experiment aimed to begin to investigate how HTT self-associates and aggregates over time in a range of different conditions. </p>
Multi-angle light scattering (MALS) analysis of HTT1-3144 Q54 HAP401-371 samples purified from Sf9 insect cells - 2018/12/03
<p><strong>Project: </strong>Biophysical investigation of purified HTT protein samples</p> <p><strong>Experiment: </strong>Multi-angle light scattering (MALS) analysis of HTT<sup>1-3144 </sup>Q54 HAP40<sup>1-371</sup>samples purified from Sf9 insect cells</p> <p><strong>Date completed:­ </strong>2018/12/03</p> <p><strong>Rationale: </strong>Apo HTT<sup>1-3144 </sup>Q23 and HTT<sup>1-3144 </sup>Q23 HAP40<sup>1-371</sup>complex samples have been analysed by MALS revealing HTT-HAP40 complex samples to be monodisperse. PolyQ expanded HTT constructs have been expressed as HAP40 complexes but the monodispersity has not been assessed beyond analytical gel filtration. </p>
Implementation of Aerosol Mie Scattering in POSEIDON with Application to the hot Jupiter HD 189733 b's Transmission, Emission, and Reflected Light Spectrum - Supplementary Material
<p>Supplementary material to 'Implementation of Aerosol Mie Scattering in POSEIDON with Application to the hot Jupiter HD 189733 b’s Transmission, Emission, and Reflected Light Spectrum'</p> <p>This zenodo repository corresponds to the updates to POSEIDON presented in Mullens et al 2024, as well as the benchmark retrievals preformed on archival HD 189733 b. </p> <p>In the upper level of the repository we have data products mentioned in the paper:</p> <p>aersosol_database.pdf <br>Aerosol-Database-Readme.txt<br>aerosol_database.hdf5</p> <p>There are then three directories (here as zip files): </p> <p>Aerosol-Datbase<br>- This folder contains the aerosol properties for aerosols in Table 1 in the paper. It contains the aerosol-database.hdf5 which contains the precomputed aerosol properties that POSEIDON utilizes in forward models and retrievals, a folder containing the npy files that have individual precomputed aerosol properties (used to generate the hdf5 file), a pdf containing the refractive indices + precomputed aerosol properties for each aerosol in the database (png versions of these figures are available in the Aerosol-Optical-Properties-Pngs folder), the refractive index txt files for each aerosol, and a readme file that contains information on each aerosol in the database (such as aerosol name, polymorph, crystalline or amorphous, crystal shape, information on samples used in refractive index references, and exoplanet/planetary science specific references). </p> <p>HD-189733b-Retrievals<br>- Contains retrieval scripts and retrieval results for the transmission, emission, and emission+reflection retrievals in the paper. Also has the notebooks used to make the figures in the paper.</p> <p>POSEIDO-V1-2<br>- Contains the POSEIDON module used to run retrievals and generate figures, and corresponds to POSEIDON version 1.2. Also contains a folder containing tutorial notebooks for new features introduced into POSEIDON version 1.2. Included in this repository for posterity.</p>
Dynamic light scattering data
<p>The upload archive consists of all the obtained results based on DLS measurements ( commonly known as dynamic light scattering) . More detain you could find in the cited article above.</p>
Observation of mutual extinction and transparency in light scattering
<p>The basic publication is:<br> A. Rates, A. Lagendijk, O. Akdemir, A.P. Mosk, and W.L. Vos, "Observation of mutual extinction and transparency in light scattering", Phys. Rev. A <strong>104</strong>, 043515. DOI: 10.1103/PhysRevA.104.043515.<br> <br> We have uploaded to the Zenodo database all data enabling everyone to reuse our data, and to reproduce all the figures of our paper.</p> <p>The upload contains the file "Metadata.txt" explaining the content of the upload.</p>
data for "Probing molecular crowding in compressed tissues with Brillouin light scattering"
<p>Data for the paper entitled "Probing molecular crowding in compressed tissues with Brillouin light scattering" published in PNAS</p>
Raw data on dynamic light scattering assessment of small cellular particles isolated from conditioned culture media of Dunaliella tertiolecta and Phaeodactylum tricornutum. Effect of Triton X-100 and temperature
<p>Raw data on dynamic light scattering assessment of small cellular particles isolated from conditioned culture media of microalgae <em>Dunaliella tertiolecta</em> (<em>D. tertiolecta</em>)<em> </em>and <em>Phaeodactylum tricurnutum</em> (<em>P. tricornutum</em>)<em> </em>by dynamic light scattering are presented. The project contains spreadsheet files with the measured dependencies of g2 function on time. We collected several g2 functions for each setting (3 for <em>D. tertiolecta</em> samples, 5 for <em>D. tertiolecta</em> with added TX100, 3 for <em>P. tricornutum</em> samples, 3 for <em>P. tricornutum</em> with added TX100). Curves were analyzed independently and compared with the respective averaged curve fitted by the inverse Laplace transform program CONTIN (freely available at: <a href="http://s-provencher.com/index.shtml">http://s-provencher.com/index.shtml</a>, the code was accessed 25. 1. 2011). The correlation curves were fitted with up to 50 exponents.</p> <p>For analysis of stability of small cellular particles with respect to temperature change, we have overall reports for each microalgae type and reports on the size distribution function, data for the g2 function and dependence of scattered light intensity on time for each temperature measured. There were 14 temperatures chosen for each type of microalgae. The files are marked with respective temperatures.</p> <p>The samples were prepared as described below:</p> <p><strong>Cultivation of the algae:</strong> Cultures of <em>D. tertiolecta</em> CCAP 19/22 and <em>P. tricornutum</em> CCAP 1052/1A from the Culture Collection of Algae and Protozoa (CCAP) of SAMS (Oban, Scotland) were grown in artificial seawater (Reef Crystals, Aquarium Systems, France). 22 g of salt was dissolved in one litre of distilled water, sterile filtered (0.2-micron cellulose filters, ref. 11107-47-CAN, Sartorius Stedim Biotech GmbH, Germany), autoclaved, and supplemented with Guillard’s (F/2) Marine Water Enrichment Solution (ref. G0154, Sigma Aldrich, USA). Cultures were grown in a respirometer (Echo, Slovenia) in 0.5-L borosilicate bottles, at 20 °C and 20 % illumination (approximately 250 μmol/m2s) with a 14-hour light / 10-hour dark cycle, with aeration of 0.2 L/min.</p> <p><strong>Isolation of small cellular nanoparticles:</strong> Small cellular particles were isolated by differential centrifugation, using a protocol widely used for the isolation of extracellular vesicles (Théry C, Amigorena S, Raposo G, Clayton A. Isolation and Characterization of Exosomes from Cell Culture Supernatants and Biological Fluids. Current Protocols in Cell Biology. 2006;30(1). doi:10.1002/0471143030.cb0322s30). Microalgal cells were removed by low-speed centrifugation (300 g, 10 min, 4°C, centrifuge Centric 260R with rotor RA 6/50 (Domel, Slovenia)), using 50 mL conical centrifuge tubes (ref. S.078.02.008.050, Isolab Laborgeräte GmbH, Germany); and 2000 g, 10 min, 4°C (Centric 400R centrifuge with rotor RS4/100 (Domel, Slovenia)), using 15 mL conical centrifuge tubes (ref. S.078.02.001.050, Isolab Laborgeräte GmbH, Germany). Each step was repeated twice. Then, the cell-depleted medium was centrifuged twice at 10 000g and 4°C for 30 min (Beckman L8-70M ultracentrifuge, rotor SW55Ti (Beckman Coulter, USA)), using thin-wall polypropylene centrifuge tubes (ref. 326819, Beckman Coulter, USA) to remove larger cell debris. Finally, small cellular particles were pelleted by centrifugation at 118 000 g and 4°C, for 70 min in the same type of ultracentrifuge and ultracentrifuge tubes. The isolate obtained from about 30 mL of conditioned media was not visible to the eye.</p> <p>For treatment with Triton X-100, the sample was incubated with Triton X-100 at concentration of 0.1%.</p> <p><strong>Dynamic light scattering (DLS): </strong>The average hydrodynamic radius (<em>R</em><sub>h</sub>) of NPs and the average intensity of scattered light (<em>I</em>) were assessed for characterization of small cellular particles by DLS. The value of <em>I</em> was interpreted as a measure of small cellular particles concentration (in the case of preserved particle size distribution) or as a topological change (in the case of altered particle size distribution)(Paterna A, Rao E, Adamo G, et al. Isolation of Extracellular Vesicles From Microalgae: A Renewable and Scalable Bioprocess. <em>Front Bioeng Biotechnol</em>. 2022;10:836747. doi:10.3389/fbioe.2022.836747; Brown W, ed. <em>Dynamic Light Scattering: The Method and Some Applications</em>. Clarendon Press ; Oxford University Press; 1993). For analysis of the samples we used Instrument 3D-DLS-SLS cross-correlation spectrometer from LS Instruments GmbH (Fribourg, Switzerla nd) with a 100 mW DPSS laser (Cobolt Flamenco, Cobolt AB, Sweden) having a wavelength λ<sub>0</sub> = 660 nm. Before measurements, samples were equilibrated in a decalin bath at 25 °C for 15 min. The scattered light was measured at an angle <em>θ</em> = 90° for 120 s. The correlation functions and integral time-averaged intensities <em>I</em>(<em>θ</em>)≡ <em>I</em>(<em>q</em>) (where <em>q</em> is the scattering vector, defined as <em>q</em> =(4π<em>n</em><sub>0</sub>/λ<sub>0</sub>)sin(<em>θ</em>/2), with <em>n</em><sub>0</sub> the refractive index of the medium, in our case estimated by the corresponding value for water, i.e. <em>n</em><sub>0</sub> = 1.33 at 25°C), were recorded simultaneously. The <em>R</em><sub>h</sub> values of small cellular particles were obtained from the diffusion coefficients (<em>D</em>) that were assessed from the correlation function of the scattered electric field (<em>g</em><sub>1</sub>(<em>t</em>)). The <em>g</em><sub>1</sub>(<em>t</em>) function was calculated from the measured correlation function of the scattered light intensity <em>g</em><sub>2</sub>(<em>t</em>) by applying Siegert’s relation (Schärtl W. <em>Light Scattering from Polymer Solutions and Nanoparticle Dispersions</em>. Springer; 2007; Shurer CR, Kuo JCH, Roberts LM, et al. Physical Principles of Membrane Shape Regulation by the Glycocalyx. <em>Cell</em>. 2019;177(7):1757-1770.e21. doi:10.1016/j.cell.2019.04.017).</p> <p>To convert <em>D</em> to <em>R</em><sub>h</sub>, the Stokes-Einstein equation was used (<em>R</em><sub>h</sub> = <em>kT</em>6π<em>ηD</em>, where <em>k</em> is the Boltzmann constant, <em>T</em> is the absolute temperature, and <em>η</em> is the viscosity of the medium in which the particles diffuse). It was assumed that particles have a spherical shape. The viscosity of the medium was not known. We approximated the viscosity value to that of of water at 25°C.To test the effect of Triton X-100 on the samples, 0.1% (V/V) of Triton X-100 was added to the sample before the measurement. The change in <em>R</em><sub>h</sub> distribution and the change of scattered light intensity (Δ<em>I = I</em><sub>sample </sub><em>- I</em><sub>sample<em>+</em>0.1%.TX100</sub>) was determined.</p> <p>The analysis was made with an in-house created software based on the inverse Laplace transform program CONTIN (freely available at: <a href="http://s-provencher.com/index.shtml">http://s-provencher.com/index.shtml</a>, the code was accessed 25. 1. 2011). We collected several intensity correlation functions for each setting. Curves were analyzed independently and compared with the averaged curve. The correlation curves were fitted with up to 50 exponents.</p> <p>To test the effect of Triton X-100 on NPs, 0.1% (V/V) of Triton X-100 was added to the sample before the measurement. The change in <em>R</em><sub>h</sub> distribution and the change of scattered light intensity (Δ<em>I = I</em><sub>sample </sub><em>- I</em><sub>sample<em>+</em>0.1%.TritonX-100</sub>) was determined.</p> <p>Thermal stability analysis was performed using the LitesizerTM 500 instrument (Anton Paar GmbH). Samples were heated from 15 °C to 80 °C in 5 °C steps. When the target temperature was reached, the samples were equilibrated for another 5 minutes before 10 measurements of 20 s duration were performed. The size distributions were determined from the mean correlation function using the Anton Paar Kalliope Professional; Version 2.16.0. (Anton Paar GmbH), <a href="https://www.anton-paar.com/corp-en/products/details/software-for-particle-analysis-kalliopetm/">https://www.anton-paar.com/corp-en/products/details/software-for-particle-analysis-kalliopetm/</a>, applying the CONTIN approach. A new version of Kalliope<sup>TM </sup>4.12.0 <a href="https://www.kalliope.com/2021/05/03/versione-firmware-4-12-0/?lang=en">https://www.kalliope.com/2021/05/03/versione-firmware-4-12-0/?lang=en</a> is freely available online.</p>
Data for: Diagnostic potential of blood plasma longitudinal viscosity measured using Brillouin light scattering
<p>Data for "Diagnostic potential of blood plasma longitudinal viscosity measured using Brillouin light scattering"</p>
Metabolic light absorption, scattering and emission (MetaLASE) microscopy
<p>The uploaded scripts and data generate the figures of the manuscript "Metabolic light absorption, scattering and emission (MetaLASE) microscopy".</p>
Figures data for "Pauli blocking of light scattering in degenerate fermions" (arXiv:2103.06921)
<p>Figures data for "Pauli blocking of light scattering in degenerate fermions" (arXiv:2103.06921)</p> <p>Excel spreadsheet file.</p>
Controllable Light Scattering on Fiber Bragg Gratings in Multimode Fibers: Tailoring Angular Emission for Advanced Fiber-Based Light
<p>The dataset consists of angular scattering patterns and transmission spectra for two fiber Bragg gratings. The scattering data is represented as 2-D arrays (images). The arrays are rectangular, where the longer side corresponds to the phi angle (azimuth) ranging from 0 to 2pi, and the shorter side represents the theta angle (polar angle) ranging from 0 to pi. To get the angle in rad per pixel just divide the corresponding arc length (p, 2pi) by the number of pixels on the axis.</p>
Dataset for "Improving data quality of low-cost light-scattering PM sensors: Towards automatic air quality monitoring in urban environments"
<p>The dataset contains the data used in the article "Improving data quality of low-cost light-scattering PM sensors: Towards automatic air quality monitoring in urban environments".</p> <p>A low-cost monitoring system composed of 14 monitoring stations was positioned at the official monitoring station of Torino Rubino in the city of Turin (Italy). The official station is managed by the environmental agency ARPA Piemonte.</p> <p>Each low-cost station contains four low-cost light-scattering PM sensors (Honeywell HPMA115S0-XXX), one temperature and relative humidity sensor (DHT22), and one atmospheric pressure sensor (BME/BMP280).<br>The sampling time of the PM sensors was set to one second, while the other sensors generated measurements every 3-4 seconds.</p> <p>The official monitoring station uses both a gravimetric and a beta attenuation instrument for measuring PM.</p> <p>The data contained in this dataset was collected from October 2020 to November 2021. It contains the PM2.5, relative humidity, and temperature measurements of the low-cost monitoring system and the official measurements of the beta attenuation device.</p> <p>Measurements of low-cost sensors are expressed in UTC, while official measurements are expressed in UTC+1.</p> <p>Official PM measurements can be also found at https://aria.ambiente.piemonte.it/qualita-aria/dati.</p>
Dynamic light scattering size distribution, ζ-potential data, and fluorescence spectra
Open the record for dataset details and reuse information.
Observation of Pauli blocking in light scattering from quantum degenerate fermions
<p>The experimental data and code required to calculate the modelling results. </p>
Differential static light scattering (DSLS) of huntingtin-HAP40 complex samples of different polyQ lengths (Q23 and Q54) – 2018/10/13
<p>Project - Huntingtin structure-function open lab notebook. </p> <p>Experiment - Differential static light scattering (DSLS) of huntingtin-HAP40 complex samples of different polyQ lengths (Q23 and Q54) - 2018/10/13. To investigate how increased polyQ length of the huntingtin protein and complex formation of HAP40 might affect thermal aggregation properties of the samples. </p>
Size-exclusion chromatography (SEC) - multi-angle light scattering (MALS) analysis of HTT and HTT-HAP40 complex samples – 2018/11/27
<p>Project - Huntingtin structure-function open lab notebook. </p> <p>Experiment - Size-exclusion chromatography (SEC) - multi-angle light scattering (MALS) analysis of HTT and HTT-HAP40 complex samples – 2018/11/27. To investigate how monodispersity of HTT and HTT-HAP40 samples. </p>
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.