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2,649 results for “Optical”
Database of optical parameters for the simulation of perovskite/silicon solar cells
<p>This dataset contains a set of representative optical parameters, i.e. the wavelength dependent complex refractive index (n+ik), for common materials used in perovskite-silicon tandems. In particular: SnO2, Spiro-MEOTAD, CH3NH3PbI2, a-Si:H, undoped c-Si, MgF.<br> The data are stored in the ASCII file “<em>nk_MaterialParameters.txt</em>”, where for each material, we report three data columns: wavelength (in µm), refractive index <em>n</em> and extinction coefficient <em>k</em>.</p>
X-Shooting ULLYSES: Massive Stars at low metallicity - II. DR1: Advanced optical data products for the Magellanic Clouds
<p>Xshooter optical spectroscopic data of Magellanic Clouds targets observed by the ESO Large Program X-Shooting ULLYSES: Massive Stars at low metallicity (PI: Vink; Porgram ID: 106.2011Z). <br><br>This version is identical to the previous version but includes the LMC and SMC atlases and the static calibration files with the new flux models (all arms) and spline anchor points (only UVB).</p>
Quantitative comparison of camera technologies for cost-effective Super-resolution Optical Fluctuation Imaging (SOFI) [raw datasets]
<p>Raw datasets accompanying the analysis in "Quantitative comparison of camera technologies for cost-effective Super-resolution Optical Fluctuation Imaging (SOFI)"</p> <p>The datasets contain raw fluorescence microscopy images aimed to be processed in a SOFI analysis. They are acquired with different camera technologies, allowing for direct comparison of an industry-grade CMOS detector with both a scientific-grade sCMOS and emCCD detector.</p>
Composite X-EUV + optical model spectrum of the planet-hosting star HIP 67522 (HD 120411)
<p>Composite spectrum of HIP 67522 obtained by joining a Phoenix photospheric spectrum with the X-EUV spectrum synthesized from the reconstructed plasma Emission Measure Distribution (EMD) vs. temperature in chromosphere, transition region, and corona. The FITS file contains 3 extensions with the spectrum, the EMD, and the plasma chemical abundances, derived from the analysis of X-ray and FUV high-resolution spectra, obtained with simultaneous observations with XMM-Newton and HST.</p> <p>In the attached figure, the upper panel shows the specific flux at Earth, while the bottom panel is the photon flux at a distance of 1 AU. In green the Phoenix spectrum resampled to a wavelength resolution of 1 Angstrom, down to 1700 A; the XUV spectrum in the range 1-1700 A instead has a resolution of 0.01 A. The green and blue segments in the upper panel, at about 200 nm, mark the Phoenix model flux and the observed flux integrated over the OM UVM2 band.</p>
An Acoustic and Optical Dataset for the Perception of Underwater Unexploded Ordnance (UXO)
<p>We present a dataset for acoustic and optical sensing of unexploded ordnance (UXO) underwater.</p> <p>UXO in the sea pose an environmental problem and a challenge for the growing offshore economy. It is best practice to perform the recovery of ammunition without explosions to protect anthropogenic structures and marine mammals. During explosive ordnance disposal (EOD), experts often rely on optical images. However, visibility underwater may be limited in harbor areas, after storm events or in waters with very mobile sediments. Thus, visual inspection is not always possible. EOD experts therefore use high-frequency sonars with large vertical apertures like the ARIS Explorer 3000 for acoustic imaging. While efforts have been made to use the available information for 3D reconstruction, existing solutions can be limited to predefined motion patterns. </p> <p>The topic is inherently sensitive, and most of the data is acquired by and for private companies and not made available to the public, which impedes research in this area. Additionally, in-situ data often lacks sufficient pose information. To facilitate further research, we created a validation dataset that was recorded in a controlled experimental environment. It has the following properties:</p> <ul> <li>Close to 100 recordings of 3 different UXO.</li> <li>More than 74000 matched and annotated imaging sonar and camera frames.</li> <li>UXO ground truths in the form of photogrammetric 3D models.</li> <li>Precise position and attitude sensor data with respect to the targets.</li> <li>Realistic motion trajectories achievable in non-experimental environments.</li> </ul> <p>This dataset allows quantitative analysis with different algorithms. 3D models and trajectories can be compared against each other to evaluate different solutions.</p> <p> </p> <p><strong>The accompanying paper is:</strong></p> <blockquote> <p>@INPROCEEDINGS{dahn2024uxo,<br> author={Dahn, Nikolas and Firvida, Miguel Bande and Sharma, Proneet and Christensen, Leif and Geisle, Oliver and Mohrmann, Jochen and Frey, Torsten and Kumar Sanghamreddy, Prithvi and Kirchner, Frank},<br> booktitle={OCEANS 2024 - Halifax}, <br> title={An Acoustic and Optical Dataset for the Perception of Underwater Unexploded Ordnance (UXO)}, <br> year={2024},<br> doi={10.1109/OCEANS55160.2024.10754316}}</p> </blockquote> <p>The paper is available on <a href="https://www.researchgate.net/publication/386124306_An_Acoustic_and_Optical_Dataset_for_the_Perception_of_Underwater_Unexploded_Ordnance_UXO">researchgate</a>.</p> <p> </p> <p><strong>Notes:</strong></p> <ul> <li>Labels have been (unfortunately) generated for the SD camera frames. To get the correct coordinates on the included FHD images, multiply all coordinates by 3.</li> </ul> <p> </p> <p><strong>Files</strong>:</p> <ul> <li>data_export_recordings.7z: main dataset</li> <li>data_export_polar.7z: contains only the polar-transformed sonar frames</li> <li>data_export_3dmodels.7z: 3d models of the UXO</li> <li>data_processed.7z: extracted and cut unmatched raw data</li> </ul>
Seeing nanoscale electrocatalytic reactions at individual MoS2 particles under an optical microscope: probing sub-mM oxygen reduction reaction
<p><span>Data in this repository include raw iSCAT optical microscopy movies for the operando monitoring of oxygen reduction reaction at bare ITO and MoS2-coated ITO electrodes in KCl solution in the presence or absence of La<sup>3+</sup> with their respective electrochemical data (voltammograms). </span></p>
Data associated with following publication: "In situ optical sub-wavelength thickness control of porous anodic aluminum oxide"
<p>Data associated with following publication: "In situ optical sub-wavelength thickness control of porous anodic aluminum oxide" (DOI: <a href="https://doi.org/10.3762/bjnano.15.12" target="_blank" rel="noopener">https://doi.org/10.3762/bjnano.15.12</a>)</p>
Data for "a cavity-based optical antenna for color centers in diamond"
<p>An efficient atom-photon-interface is a key requirement for the integration of solid-state emitters such as color centers in diamond into quantum technology applications. Just like other solid state emitters, however, their emission into free space is severely limited due to the high refractive index of the bulk host crystal. In this work, we present a planar optical antenna based on two silver mirrors coated on a thin single crystal diamond membrane, forming a planar Fabry-Pérot cavity that improves the photon extraction from single tin vacancy (SnV) centers as well as their coupling to an excitation laser. Upon numerical optimization of the structure, we find theoretical enhancements in the collectible photon rate by a factor of 60 as compared to the bulk case. As a proof-of-principle demonstration, we fabricate single crystal diamond membranes with sub-µm thickness and create SnV centers by ion implantation. Employing off-resonant excitation, we show a 6-fold enhancement of the collectible photon rate, yielding up to half a million photons per second from a single SnV center. At the same time, we observe a significant reduction of the required excitation power in accordance with theory, demonstrating the functionality of the cavity as an optical antenna.<br> Due to its planar design, the antenna simultaneously provides similar enhancements for a large number of emitters inside the membrane. Furthermore, the monolithic structure provides high mechanical stability and straightforwardly enables operation under cryogenic conditions as required in most spin-photon interface implementations.</p>
Spatial and Temporal Availability of Cloud-free Optical Observations in the Tropics
<p>These data comprise three layers describing the spatial and temporal distribution of cloud-free optical observations over the tropics. The test datasets shared here are derived from the combination of Landsat and Sentinel-2 satellite data and represent a portion of the full datasets. The test data correspond to year 2020 over Mesoamerica. </p> <ul> <li>Spatial data: the Meso2020_validObs contains one band 'valid_obs' indicating the number of cloud-free observations at the pixel level. </li> <li>Temporal data: the maximumWaitDate2020 contains two bands 'max' and 'maxDay' corresponding to the number of maximum consecutive days without data in a year and final date in which the maximum number of consecutive days without data occurred, respectively.</li> </ul>
Dataset for manuscript "Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations"
<p>This is the long-term satellite retrieval dataset of dust aerosol optical depth at 10 μm (DAOD<sub>10μm</sub>) and dust coarse mode effective diameter (D<sub>eff</sub>) based on collocated MODIS and CALIOP observations from July 2006 to August 2018. The full description is in the manuscript "<strong>Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations" </strong>by Zheng, Jianyu, et al. The readme file for the data is in "readme_dust_aod_size_product.txt". The variable list of Level-2 data is in "variable_list_L2.txt". The variable list of Level-3 data is in "variable_list_L3.txt".</p>
A Pan-European, Quantile Machine learning (QML) based, Total, Fine-Mode and Coarse-Mode Aerosol Optical Depth dataset (QML AOD))
<p>The V 1.1.0 product is an improved Aerosol Optical Depth (AOD) product based on Gap-filled MAIAC AOD, which provide first full-coverage, high-resolution monitoring of fine-mode and coarse-mode aerosols in Europe from 2003-20. This dataset has successfully rectified the previously identified issue of weak associations between satellite AOD and PM2.5 in Europe, which was primarily attributable to current limitations of AOD data. Our innovative approach has yielded stronger correlations with PM10, PM2.5, and PMcoarse than previous AOD product, laying a critical groundwork for improving PM10, PM2.5, and PMcoarse predictions in further epidemiological studies or environmental monitoring.</p> <p>We have uploaded three QML AOD datasets in Geotiff format, covering the region from -27° to 72° latitude and from -25° to 45° longitude. These datasets will be useful for researchers and policymakers to better understand the impacts of aerosols on the environment and human health.</p> <p> Note: v1.0.0 product do not include MAIAC AOD in their models.</p> <p>Please read more details in our paper </p> <h1><span>Estimation of pan-European, daily total, fine-mode and coarse-mode Aerosol Optical Depth at 0.1° resolution to facilitate air quality assessments</span></h1> <p><a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.scitotenv.2024.170593" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.scitotenv.2024.170593</span></a></p>
Data - Low-Noise Phase-Sensitive Optical Parametric Amplifier with Lossless Local Pump Generation using a Digital Dither Optical Phase-Locked Loop
<p>This dataset contains measurement data and processing code for the results published in "Low-Noise Phase-Sensitive Optical Parametric Amplifier with Lossless Local Pump Generation using a Digital Dither Optical Phase-Locked Loop". The Pyrpl code change used in the work is also attached.</p> <p>This work was funded by the Swedish Research Council (grant VR-2015-00535).</p>
Interstitial null-distance time-domain diffuse optical spectroscopy using a superconducting nanowire detector
<p>We demonstrate a novel realization of Interstitial fiber, broadband, Time Domain Diffuse Optical Spectroscopy (TD-DOS) in Null Source-Detector separation (NSDS) approach without temporal gating, by using a Superconducting Nanowire single photon detector (SNSPD) for acquisition. As per the MEDPHOT protocol, we test experimentally, the absorption linearity of the system on tissue-equivalent liquid phantoms, and demonstrate the scattering-independent retrieval of the absorption spectrum of water using Intralipid phantoms in the wavelength range of 600-1100 nm.</p> <p>This work has been published in the Journal of Biomedical Optics - https://doi.org/10.1117/1.JBO.28.12.121202. Here, we present the dataset containing the acquired data pertaining to the aforementioned publication, including a brief overview, the tools to read it and the analysis corresponding to the figures in the article.</p>
Limnological data from nearly 400 lakes across the Americas and New Zealand with a focus on vertical profiles of temperature, UV radiation, and optical properties
Two and a half decades of limnological data have been collected from nearly 400 lakes, encompassing a wide range of systems and a broad range of geography. This data set comprises one of the largest and most complete sets of measurements of underwater ultraviolet (UV) transparency available in the world. The data include a suite of 36 variables, with a focus on the optical characteristics. Lakes range from pristine natural lakes to manmade reservoirs. The systems represented in this data set are largely located in North America, from the northeastern United States to Alaska, and alpine and subalpine lakes in the Rocky Mountains of the United States and Canada. Lakes included range from iconic Lake Tahoe, and Castle Lake in northern California, to lakes in the South American Patagonian region, as well as New Zealand. Data were most often collected during the summer, and in some lakes span multiple years (with year-round data since 2006 in Lake Tahoe). The data here are contained in four files, including LakeData.csv, SiteInformation.csv, Methods.csv, and Variables.csv. The main data are in LakeData.csv. SiteInformation.csv, Methods.csv, and Variables.csv support the main data file with descriptions of the sampling sites, methods by which samples were processed, and descriptions of the variables that were measured, respectively. This data set complements the site-intensive limnological data that we published in EDI on 30+ years of data from 3 lakes in the Poconos Mountains region of Pennsylvania, USA. This complementary data set can be accessed at https://portal.edirepository.org/nis/mapbrowse?scope=edi&identifier=186
MCR LTER: Coral Reef: Optical parameters and SST from SeaWiFS and MODIS, ongoing since 1997 and AVHRR-derived SST from 1985 to 2009
Monthly averages of the Sea Surface Temperature (SST), the Sub-surface chlorophyll-a concentration (Chl), the colored dissolved and detrital organic materials at 443 nm (acdm[443]) and the particulate backscattering coefficient at 443 nm (bbp[443]) around Moorea are obtained or derived from satellite data (SST from AVHRR and MODIS-Aqua; Chl, acdm[443] and bbp[443] from SeaWiFS and MODIS-AQUA). The satellite data are averaged over a 1 month period for geographic areas of 16S-19S/147W-151W (SeaWiFS and MODIS-AQUA) and 15S-20S/145W-155W for AVHRR. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2022). This work represents a contribution of the Moorea Coral Reef (MCR) LTER Site.
Cyclist Actions: Optical Flow Sequences and Trajectories
<p>The dataset consists of over 1.1 million samples of labeled cyclists actions. Every sample consists of two optical flow sequences, recorded over the past second (9 optical flow images each), from two different cameras, the past trajectory of the cyclist of the last second (50 past positions), and a label of the currently performed action.</p> <p>The samples were extracted from 1,639 video sequences of cyclists moving across an urban intersection at the University of Applied sciences in Aschaffenburg: <a href="https://www.th-ab.de/ueber-uns/organisation/labor/kooperative-automatisierte-verkehrssysteme/ausstattung/">https://www.th-ab.de/ueber-uns/organisation/labor/kooperative-automatisierte-verkehrssysteme/ausstattung/</a></p> <p>The uploaded files consist of an archive containing 27 numpy files, a single numpy file containing trajectories only, and a json file containing 5-fold cross validation/test split.</p> <p>The numpy files consist of python dictionaries with scenes of the form:</p> <pre><code class="language-python">{SCENE_NAME: 'of_hk1/2': [...], # zip compressed, python pickled optical flow sequences of cameras 1/2 'x/y/z_tracked': [...], # tracked cyclists positions in x/y/z directions, 'x/y/z_smoothed': [...], # smoothed (by rts smoother) cyclists positions in x/y/z directions, 'orientation': [...], # orientation of the cyclists estimated by kalman filters 'ts': [...], # utc timestamps in micro seconds LABEL_NAME: [...], # labels of different actions (0 or 1)}</code></pre> <p>The manually created labels are:</p> <ul> <li>straight: cyclists is moving and not turning</li> <li>tr/tl: cyclist is turning left/right</li> <li>move: cyclist is moving with nearly constant velocity and not turning</li> <li>start: cyclist was standing and starts moving</li> <li>starting_movement: first movement of cyclist before starting</li> <li>stop: cyclist was moving/starting and slows down to a halt</li> <li>wait: cyclist is standing</li> <li>hand_signal_left/right: cyclist indicates a turn by hand signal</li> <li>shoulder_check_left/right: cyclist looks over left/right shoulder</li> <li>out_of_saddle: cyclist is standing</li> </ul> <p>The optical flow sequences were created using PWC-Net [1].</p> <p>To extract the zipped/pickled optical flow sequences:</p> <pre><code class="language-python">import cv2 as cv import zlib import pickle import numpy as np # visualize flow def vis_of(of): hsv = np.zeros([of.shape[0], of.shape[1], 3], dtype=np.uint8) hsv[..., 1] = 255 mag, ang = cv.cartToPolar(of[..., 0].astype(np.float32), of[..., 1].astype(np.float32)) hsv[..., 0] = ang * 180 / np.pi / 2 hsv[..., 2] = cv.normalize(mag, None, 0, 255, cv.NORM_MINMAX) bgr = cv.cvtColor(hsv, cv.COLOR_HSV2BGR) return bgr # load npy file from dataset npy_path = 'of_dataset_0.npy' data = np.load(npy_path, allow_pickle=True).item() scene = data[list(data.keys())[0]] # extract optical flow sequence ofs = pickle.loads(zlib.decompress(scene['of_hk1'][i])).astype(np.float16) * 2.0 / 255.0 - 1.0 # show of images in sequence for j in range(len(ofs)): # create bgr image from 2 channel optical flow bgr = vis_of(ofs[j]) cv.imshow("of", bgr) </code></pre> <p>Python code and a description to read the dataset can be found in our GitHub: <a href="https://github.com/CooperativeAutomatedTrafficSystemsLab/CyclistActionRecognition">https://github.com/CooperativeAutomatedTrafficSystemsLab/CyclistActionRecognition</a></p> <p>[1] D. Sun, X. Yang, M. Liu, and J. Kautz, “PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, June 2018, pp. 8934–8943.</p> <p> </p> <p>This work results from the project DeCoInt 2, supported by the German Research Foundation (DFG) within the priority program SPP 1835: "Kooperativ interagierende Automobile", grant numbers DO 1186/1-2, FU 1005/1-2, and SI 674/11-2. Additionally, the work is supported by "Zentrum Digitalisierung Bayern".</p> <p>Due to privacy laws in germany, we are not permitted to publish image sequences.</p>
Data files for: Comparison of high-speed optical observations of a lightning flash from space and the ground
<p>This dataset accompanies the paper in the AGU open acces journal <em>Earth and Space Science</em>, special section "A New Era of Lightning Observations From Space"<em> </em>and contains data of the lightning flash in Colombia detected by:</p> <ul> <li>Geostationary Lightning Mapper (GLM) </li> <li>Lightning Imaging Sensor on the International Space Station (ISS-LIS) </li> <li>Atmosphere-Space Interactions Monitor - Modular Multi-spectral Imaging Array (ASIM MMIA)</li> <li>High-speed intensified Phantom V7.3 camera fielded in Cartagena, Colombia.</li> </ul> <p>The high-speed video .cine files can be read by (free) CineViewer and PCC software of Vision Research Inc. which can convert to avi files. For any questions, contact the first author.</p>
Matlab code for a multipolar decomposition of optical forces
<p>This dataset supplements Figure 5 from the publication "Multipolar Origin of the Unexpected Transverse<br> Force Resulting from Two-Wave Interference*" by Karim Achouri, Andrei Kiselev, and Olivier J. F. Martin. Here, we provide the code for the multipolar analysis of the optical force based on the vector spherical harmonic decomposition. Based on the Mie solution, electric fields can be obtained numerically in the far-field by using the software developed by Dr. Karim Achouri https://github.com/kachourim/MieScatteringPEC. This code analyzes the far-field scattered by a perfect electric conductor sphere placed in vacuum for different sphere radii. In the framework of the Maxwell stress tensor, we find the optical force acting on a sphere along the z-direction in the illumination configuration presented in Figure 1*. The use of the vector spherical decomposition allows to observe contributions from different multipolar interactions. In this code,we analyze the force appearing as a result of the interaction between electric dipole aligned along x, px, and electric quadrupole with components xz, Qexz and compare it with the total force along the z-axis appearing as a result of interaction between all multipoles supported by the sphere with given radius.</p>
Demonstration of 100 Gbit/s active measurements in dynamically provisioned optical paths
<p>New techniques, based on Software-Defined Networks, are used to deploy optical paths dynamically. This demonstration shows how active measurements at 100 Gbit/s are performed to check before operation that the performance requirements are met in terms of capacity, delay or packet loss.</p>
Crossed graphene nanoribbons as beam splitters and mirrors for electron quantum optics
<p>OPEN DATA related to the research publication:</p> <p>S. Sanz, P. Brandimarte, G. Giedke, D. Sánchez-Portal, and T. Frederiksen, <em>Crossed graphene nanoribbons as beam splitters and mirrors for electron quantum optics</em>, Phys. Rev. B <strong>102</strong>, 035436 (2020) [arXiv:2005.11391]</p> <p>Abstract: We analyze theoretically 4-terminal electronic devices composed of two crossed graphene nanoribbons (GNRs) and show that they can function as beam splitters or mirrors. These features are identified for electrons in the low-energy region where a single valence or conduction band is present. Our modeling is based on <em>pz</em> orbital tight-binding with Slater-Koster type matrix elements fitted to accurately reproduce the low-energy bands from density functional theory calculations. We analyze systematically all devices that can be constructed with either zigzag or armchair GNRs in AA and AB stackings. From Green's function theory the elastic electron transport properties are quantified as a function of the ribbon width. We find that devices composed of relatively narrow zigzag GNRs and AA-stacked armchair GNRs are the most interesting candidates to realize electron beam splitters with a close to 50-50 ratio in the two outgoing terminals. Structures with wider ribbons instead provide electron mirrors, where the electron wave is mostly transferred into the outgoing terminal of the other ribbon, or electron filters where the scattering depends sensitively on the wavelength of the propagating electron. We also test the robustness of these transport properties against variations in intersection angle, stacking pattern, lattice deformation (uniaxial strain), inter-GNR separation, and electrostatic potential differences between the layers. These generic features show that GNRs are interesting basic components to construct electronic quantum optical setups.</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.