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8,460 results for “MONITORING”
Land use information and NO2 observations of environmental monitoring stations in China
<p>The land use information for environmental monitoring stations in China is stored in the "<i>site_lu.csv" </i>file. The monthly NO2 observations from 2015 to 2017 are stored in the "<i>NO2_ground.csv</i>" file.</p>
For the people by the people: citizen science web interface for real-time monitoring of tick risk areas in Finland
<p>Ticks and tick-borne diseases (TBDs) form a significant and growing threat to human health and well-being in Europe, with increasing numbers of tick-borne encephalitis (TBE) and Lyme borreliosis cases being reported during the past few decades. Increasing knowledge of tick risk areas and seasonal activity remains the primary method for preventing TBDs. Crowdsourcing provides the best alternative for rapidly obtaining data on tick occurrence on a national level.</p> <p>In order to produce and share up-to-date data about tick risk areas in Finland, an online platform, Punkkilive (www.punkkilive.fi/en), was launched in April 2021. On the website, users can submit and browse tick observations, report tick numbers and hosts, and upload pictures of ticks.</p> <p>Here, we looked at trends in the crowdsourced data from 2021, assessed the effect of local tick species on seasonality of observations, and examined sampling bias in the data.</p> <p>The high number of tick observations (n=78 837) highlights that there was demand for such a service. Approximately 97% of 5573 uploaded pictures represented ticks. Seasonal patterns of tick observations varied across Finland, highlighting variability in the risk associated with the two human-biting tick species <em>Ixodes ricinus</em> and <em>I. persulcatus</em>, the latter having a shorter, unimodal activity peak in late spring–early summer. Tick numbers were low and the proportion of new sightings was high in northern Finland, as may be expected near the latitudinal distribution limits of both species. While the number of inhabitants generally explained the number of tick observations well, geographically weighted regression models also identified areas that deviated from this general pattern.</p> <p>This study offers a prime example of how crowdsourcing can be applied to track vectors of zoonotic diseases, to the benefit of both researchers and the public. Areas with more or fewer observations than predicted based on number of inhabitants were revealed, wherein more specific analyses may reveal factors contributing to lower or higher risk levels that may be used in increasing awareness. We hope that the success of Punkkilive serves to highlight the usefulness of citizen science in the prevention of vector-borne diseases.</p>
GNSS-IR data for "Real-time water levels using GNSS-IR: a potential tool for flood monitoring"
<p>Organised SNR data used for GNSS-IR analysis in the article "Real-time water levels using GNSS-IR: a potential tool for flood monitoring" by David Purnell, Natalya Gomez, William Minarik and Gregory Langston.</p><p> </p><p>The directories 'rv3s' and 'sjdlr' contain SNR data corresponding to sites Trois-Rivières and Saint-Joseph-de-la-Rive, respectively.</p><p> </p><p>Software for processing the data can be found at: https://github.com/purnelldj/gnssir_rt</p><p> </p><p>SNR data is given as text files in the format specified here except for columns 4+:</p><p>https://gnssrefl.readthedocs.io/en/latest/pages/file_structure.html#the-snr-data-format</p><p>columns:</p><p>1. sat PRN with an offset such that GLONASS satellites are between 100-200 and Galileo are between 200-300</p><p>2. satellite elevation (degrees)</p><p>3. azi is satellite azimuth (degrees)</p><p>4. GPS time (seconds since 1980)</p><p>5. L1 SNR</p>
Screen-Printed Piezoelectric Sensors on Tattoo Paper Combined with All-Printed High Performance Organic Electrochemical Transistors for Electrophysiological Signal Monitoring
<p>Dataset of the journal article "Screen-Printed Piezoelectric Sensors on Tattoo Paper Combined with All-Printed High Performance Organic Electrochemical Transistors for Electrophysiological Signal Monitoring" published in <i>ACS Applied Materials & Interfaces</i>, 28 November 2023, <a href="https://eur05.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1021%2Facsami.3c10299&data=05%7C01%7Cpeter.andersson.ersman%40ri.se%7Cbabb1e939a0d4fa7a40908dbeb5e3902%7C5a9809cf0bcb413a838a09ecc40cc9e8%7C0%7C0%7C638362562144125762%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=pwQmN%2BZMzDOvXQcJ1B4gpHf1S5TEKXtjslPldL%2F9kYQ%3D&reserved=0">https://doi.org/10.1021/acsami.3c10299</a></p>
Raw Data and Codes for the Article "Ultrafast and persistent photoinduced phase transition at room temperature monitored by streaming powder diffraction"
<p>Dataset for the article "Ultrafast and persistent photoinduced phase transition at room temperature monitored by streaming powder diffraction", containing:</p><ul><li>The data and the codes used to generate the figures</li><li>The raw data used for the study, and the codes to analyze it, from raw diffraction images to refinement parameters</li></ul>
Supplement of "Algorithm for continual monitoring of fog life cycles based on geostationary satellite imagery as a basis for solar energy forecasting"
<p>The file uploaded here is an animation that visually illustrates the outputs of the a newly developed machine learning based FLS (<strong>F</strong>og and <strong>L</strong>ow <strong>S</strong>tratus) detection algorithm for the SEVIRI (<strong>S</strong>pinning <strong>E</strong>nhanced <strong>V</strong>isible and <strong>I</strong>nfra<strong>R</strong>ed <strong>I</strong>mager) instrument onboard the MSG (<strong>M</strong>eteosat <strong>S</strong>econd <strong>G</strong>eneration) geo-stationary satellites over the 24hr cycle of the day for the day of <strong>02/March/2021</strong> and compares them with the corresponding raw channel values observed by SEVIRI. The proposed algorithm classifies each SEVIRI pixel as "clear-sky", "FLS", or "non-FLS-cloud" (identified with Khaki, Red, and Blue in the animation) based on the SEVIRI pixel values of BT12.0, BT8.7 - BT12.0, BT10.8 - BT12.0, and BT12.0 - BT13.4 plus the standard deviation of each of these variables in a spatial window sized 3x3 pixels with the central pixel being the target pixel. </p><p><br>In this animation, the left-hand panel shows a false-color RGB image constructed based on the SEVIRI raw channel data with the red, green, and blue channels being BT12.0- BT13.4, BT8.7 - BT12.0, and BT10.8 - BT12.0, respectively. In this panel, the green color represents the high clouds, and the light and dark red colors represent the clear-sky and FLS, respectively. The right-hand panel of this animation also shows the outputs of the ML FLS detection algorithm developed in the present study.</p>
Monitoring of large-scale archaeological excavations using photogrammetric techniques - Nea Paphos case study
<p>Photogrammetric data (images) for five contexts from a single archaeological trench from the Paphos Agora Project (Excavations conducted in Nea Paphos Archaeological Site by Jagiellonian Unversity in Krakow - under the direction of Prof. Ewdoksia Papuci-Władyka). Images for photogrammetric modelling of all contexts were taken in 2015 with the NIKON D7100 camera (24 Mpx resolution), with the number of images per model varying from 25 to 41. For photogrammetric processing, the Agisoft PhotoScan and Reality Capture were used. </p><p>The data (images) were uploaded together with project files from Agisoft Metashape and RealityCapture, exported results (3D models, orthoimages and DEMs) and reference data - point clouds from terrestrial laser scanner measurements are available as supplementary material for the article in Journal of Archaeological Science: Reports. Also, data for one layer below and above, which do not include reference point clouds, have been added.</p>
Discharge of springs monitored during the WABEsense project
<p>Water discharge and temperature of the springs monitored during the <a href="https://www.aramis.admin.ch/Grunddaten/?ProjectID=47484">WABEsense project (UTF 642.21.20)</a>.</p><p>The data corresponding to the all field measurements performed between Feb. 2021 and Dec 2023. Data for each spring might not cover the whole period.</p><p>For each spring there are two files: *.csv and *.meta. The .csv file contains the recorded data. The .meta fiel contains further information about the spring (e.g. location) and the data.</p><p>## List of springs:</p><p>- Bonaduz BS Paliu Fravi<br>- Bonaduz BS Salums Friedrich<br>- Bonaduz BS Salums Leo<br>- Bonaduz SS Leo Friedrich<br>- Bregaglia BS Acqua d'Balz 1<br>- Bregaglia BS Acqua d'Balz 2<br>- Hergiswil BS Rossmoos<br>- Hergiswil SS Muesli<br>- Oberriet SS Ulrika<br>- Schiers BS Chalta Wasser<br>- Schiers BS Grapp rechts<br>- Susch BS Prada bella suot<br>- Susch BS Prada bella sura<br>- Zernez BS Sarsura<br>- Zug SS Nidfuren</p><p>More details about each spring is given in the corresponding .meta file.</p><p>We are very grateful for the work of the operators responsible for collecting the data.</p><p>## Files formats</p><p>All files are plain text. The .csv files are UTF-8 encoded and separated by ";" (semi-colon) . The .meta files follow the YAML format.</p><p>An example of loading the data in python using pandas is given below:</p><p>import pandas as pd data = pd.read_csv("Bonaduz.BS.Paliu_Fravi_discharge.csv", encoding="utf-8", sep=";")</p><p> </p>
Data files for Sheehan et al. 2023 'City Scale Traffic Monitoring Using WorldView Satellite Imagery and Deep Learning: A Case Study of Barcelona' DOI: https://doi.org/10.3390/rs15245709
<p>Data files for Sheehan et al. (2023) City Scale Traffic Monitoring Using WorldView Satellite Imagery and Deep Learning: A Case Study of Barcelona. Remote Sensing. 15(24) DOI: <a href="https://doi.org/10.3390/rs15245709">https://doi.org/10.3390/rs15245709</a></p> <p>Description of contents: </p> <p>xView-YOLOv3_Model6_Barcelona_weights.pt</p> <p>This file contains the pre-trained weights for the xView-YOLOv3 model (model code available here: https://github.com/ultralytics/xview-yolov3). These weights were trained on a manually created training data set of vehicles present in WorldView 2/3 imagery covering the city of Barcelona. The weights relate to Model 6 set up: a single vehicle class (parked, static and moving), RGB imagery, Barcelona training data set derived anchor boxes, 1500 x 1500 pixel sized images and to 1000 epochs. </p> <p> </p>
[Data] Real-time monitoring and quality assurance for laser-based directed energy deposition: integrating co-axial imaging and self-supervised deep learning framework
<p>The experimental setup utilized a co-axial color Charged Couple Device (CCD) camera, integrated into the laser deposition head. This camera operates at a frame rate of 30 frames per second and captures the morphology of the process area. The captured images consist of three RGB channels with a 640 × 480 pixels resolution. To enable the camera to capture the radiation from the process zone, a beam splitter is installed on Precitec's laser applicator head. An optical notch filter within the 650–675 nm range also blocks the laser wavelengths.</p> <p>The dataset consists of four categories that covers the process map of DED process [.rar file].<br>The dataset consist of around 48,000 images that are labelled into 4 categories [P1-P2-P3-P4]. The images correspond to DED process zone captured co-axially<br>The categories are function of linear laser energy deposited. The folder is already split into Train and Test.</p>
Quantum Material-Based Self-Propelled Microrobots for the Optical "On-the-Fly" Monitoring of DNA
<p>Quantum dot-based materials have been found to be excellent platforms for biosensing and bioimaging applications. Herein, self-propelled microrobots made of graphene quantum dots (GQD–MRs) have been synthesized and explored as unconventional dynamic biocarriers toward the optical “on-the-fly” monitoring of DNA. As a first demonstration of applicability, GQD–MRs have been first biofunctionalized with a DNA biomarker (i.e., fluorescein amidite-labeled, FAM-L) via hydrophobic π-stacking interactions and subsequently exposed toward different concentrations of a DNA target. The biomarker–target hybridization process leads to a biomarker release from the GQD–MR surface, resulting in a linear alteration in the fluorescence intensity of the dynamic biocarrier at the nM range (1–100 nM, <em>R</em><sup>2</sup> = 0.99), also demonstrating excellent selectivity and sensitivity, with a detection limit as low as 0.05 nM. Consequently, the developed dynamic biocarriers, which combine the appealing features of GQDs (e.g., water solubility, fluorescent activity, and supramolecular π-stacking interactions) with the autonomous mobility of MRs, present themselves as potential autonomous micromachines to be exploited as highly efficient and sensitive “on-the-fly” biosensing systems. This method is general and can be simply customized by tailoring the biomarker anchored to the GQD–MR’s surface.</p>
Monitoring genome-wide diversity over contemporary time with new indicators applied to Arctic charr populations
<p>Genetic diversity is fundamental to the adaptive potential and survival of species. Although its importance has long been recognized in science, it has a history of neglect within policy – until now. The new Global Biodiversity Framework recently adopted by the Convention on Biological Diversity, states that genetic diversity must be maintained at levels assuring adaptive potential of populations, and includes metrics for systematic monitoring of genetic diversity in so called indicators. Similarly, indicators for genetic diversity are being developed at national levels. Here, we apply new indicators for Swedish national use to one of the northernmost salmonid fishes, the Arctic charr (<em>Salvelinus alpinus</em>). We sequence whole genomes to monitor genetic diversity over four decades in three landlocked populations inhabiting protected alpine lakes in central Sweden. We find levels of genetic diversity, inbreeding and load to differ among lakes but remain stable over time. Effective population sizes are generally small (<500), suggesting a limited ability to maintain adaptive variability if genetic exchange with nearby populations became eliminated. We identify genomic regions potentially shaped by selection; SNPs exhibiting population divergence exceeding expectations under drift and a putative selective sweep acting within one lake to which the competitive brown trout was introduced during the sampling period. Identified genes appear involved in immunity and salinity tolerance. Present results suggest that genetically vulnerable populations of Arctic charr have maintained neutral and putatively adaptive genetic diversity despite small effective sizes, attesting the importance of continued protection and assurance of gene flow among populations.</p>
Monitoring mobility in older adults using a global positioning system (GPS) smartwatch and accelerometer: A validation study
<p><strong>Background</strong></p> <p>There is interest in identifying the most reliable method for detecting early mobility limitations. Accelerometry and Global Positioning System (GPS) could provide insight into declines in mobility, but few studies have used this multi-sensor approach to monitor mobility in older adults. </p> <p><strong>Methods</strong></p> <p>Thirty-two volunteers (66.2±6.3 years) agreed to participate in our validation study. We conducted two experiments to determine the validity of the TicWatch S2 and Pro 3 Ultra GPS models against the Qstarz receiver in measuring life-space mobility, trip frequency, duration, and mode. We also assessed the accuracy of the TicWatch in measuring step count and agreement with the ActiGraph wGT3X-BT for activity counts and sedentary behavior. Participants wore devices simultaneously for three consecutive days and recorded activity and trip information.</p> <p><strong><span>Results</span></strong></p> <p>The TicWatch Pro 3 Ultra GPS performed better than the S2 model and was similar to the Qstarz in all tested trip-related measures, and it was able to estimate both passive and active trip modes. Both models showed similar results to the Qstarz in life-space-related measures. The TicWatch S2 demonstrated good to excellent overall agreement with the ActiGraph algorithms for the time spent in sedentary and non-sedentary activities, with 84% and 87% agreement rates, respectively. Under supervised conditions, the TicWatch Pro 3 Ultra GPS measured step count consistently with the gold standard observer, with a bias of 0.4 steps. The thigh-worn ActiGraph algorithm accurately classified sitting and lying postures (97%) and standing postures (90%).</p> <p><strong>Conclusion</strong></p> <p>Our multi-sensor approach to monitoring mobility has the potential to capture both accelerometer-derived movement data and trip/life-space data only available through GPS. In this study, we found that the TicWatch models are valid devices for capturing GPS and raw accelerometer data, making them useful tools for assessing real-world mobility in older adults and advancing our knowledge of early mobility decline.</p>
Data from: Large-scale bioacoustic monitoring to elucidate the distribution of a non-native katydid
<p>For animals that produce species-specific audible sounds, environmental recordings combined with automated acoustic monitoring software (passive acoustic monitoring, PAM) may be an effective monitoring tool because it allows audio data from many, widely distributed autonomous recording units (ARUs) to be processed in a relatively short period of time. Males of many insect species produce loud, species-specific mating songs, yet acoustic insects have received less attention from PAM relative to vertebrates.</p> <p>We evaluated the use of PAM to monitor, <em>Roeseliana roeselii</em> (Orthoptera, Tettigoniidae), an acoustic insect that has expanded its range to Alberta, Canada far outside its naturalized North American range. We analyzed environmental recordings from ARUs: 1) at two control sites known to be occupied by <em>R. roeselii</em>, and 2) across Alberta established by the Alberta Biodiversity Monitoring Institute (ABMI) to search for new populations.</p> <p>PAM successfully detected <em>R. roeselii</em> at the two control sites, but not at any of the 74 ABMI sites that we analyzed. Despite the failure to detect new locations of <em>R. roeselii</em>, our analysis of ABMI environmental recordings detected several other species of acoustic insects, including <em>Orchelimum gladiator</em>, <em>Gryllus</em> sp. and <em>Allonemobius</em> spp.</p> <p>Our results add to the growing body of work showing the feasibility of using PAM for acoustic insects. We make suggestions for how to maximize the effectiveness of this monitoring tool for the conservation and management of singing insects in North America.</p>
Data from: environmental DNA reveals temporal variation in mesophotic reefs of the Humboldt upwelling ecosystems of central Chile: towards a baseline for biodiversity monitoring of unexplored marine habitats
<p>Temperate mesophotic reef ecosystems (TMREs) are among the least known marine habitats. Information on their diversity and ecology is geographically and temporally scarce, especially in highly productive large upwelling ecosystems. Lack of information remains an obstacle to understanding the importance of TMREs as habitats, biodiversity reservoirs and their connections with better-studied shallow reefs. Here, we use environmental DNA (eDNA) from water samples to characterize the community composition of TMREs on the central Chilean coast generating the first baseline for monitoring the biodiversity of these habitats. We analyzed samples from two depths (30 and 60m) over four seasons (spring, summer, autumn, and winter) and at two locations approximately 16 km apart. We used a panel of three metabarcodes, two that target all eukaryotes (18S rRNA and mitochondrial COI) and one specifically targeting fishes (16S rRNA). All panels combined encompassed eDNA assigned to 42 phyla, 90 classes, 237 orders, and 402 families. The highest family richness was found for the phyla Arthropoda, Bacillariophyta and Chordata. Overall, family richness was similar between depths but decreased during summer, a pattern consistent at both locations. Our results indicate that the structure (composition) of the mesophotic communities varied predominantly with seasons. We analyzed further the better-resolved fish assemblage and compared eDNA with other visual methods at the same locations and depths. We recovered eDNA from nineteen genera of fish, six of these have also been observed on towed underwater videos, while thirteen were unique to eDNA. We discuss the potential drivers of seasonal differences in community composition and richness. Our results suggest that eDNA can provide valuable insights for monitoring TMRE communities but highlight the necessity of completing reference DNA databases available for this region.</p>
Data from: Evaluating genotyping-in-thousands by sequencing as a genetic monitoring tool for a climate sentinel mammal using non-invasive and archival samples
<p>Genetic tools for wildlife monitoring can provide valuable information on spatiotemporal population trends and connectivity, particularly in systems experiencing rapid environmental change. Though many DNA sequencing approaches still require high quality and quantity of DNA obtained from traditional sources (e.g. blood and tissue), rapid genotyping tools such as Genotyping-in-Thousands by sequencing (GT-seq) have improved our ability to make use of degraded and less concentrated DNA commonly obtained from non-invasive and archival samples. Here, we developed a multi-purpose GT-seq panel (307 single nucleotide polymorphisms) for a climate sentinel mammal (the American pika, <em>Ochotona princeps</em>) for use as a genetic tool for monitoring populations in the Canadian Rocky Mountains. We optimized the panel using contemporary tissue samples (n = 77) and subsequently applied it to archival tissue (n = 17) and contemporary fecal pellet samples (n = 129) to evaluate its effectiveness at identifying individuals and sex, estimating relatedness, and inferring population structure. The panel demonstrated high efficacy with contemporary and archival tissue samples (94.7% and 90.5% genotyping success, respectively) and negligible genotyping error (0.001% and 0.0%, respectively). Despite relatively high genotyping success for fecal pellet samples (79.7%), high genotyping error (28.4%) limited its power as a monitoring tool to assess genetic variation using non-invasive samples and highlighted the need for further optimization around sample and data collection.</p>
Shark-dust: Application of high-throughput DNA sequencing of processing residues for trade monitoring of threatened sharks and rays
<p>Data repository accompanying manuscript titled of "Shark-dust: Application of high-throughput DNA sequencing of processing residues for trade monitoring of threatened sharks and rays."</p> <p>Prasetyo, A. P., Murray, J. M., Kurniawan, M. F. A. K., Sales, N. G., McDevitt, A. D., & Mariani, S. (2023). Shark-dust: Application of high-throughput DNA sequencing of processing residues for trade monitoring of threatened sharks and rays. Conservation Letters, 16, e12971. https://doi.org/10.1111/conl.12971</p>
Figure 4 in Natural regeneration in Atlantic Forest Fragments: using ants (Hymenoptera: Formicidae) for monitoring a conservation unit
Figure 4. Camponotus cillae recorded for the RPPN Botujuru: (A) front view; (B) dorsal view; (C) side view.
Data to "Cardiopulmonary exercise testing complements both spirometry and nuclear imaging for assessing sarcoidosis disease stage and for monitoring disease activity"
<p>This record contains analysis scripts (written in Matlab) as well as raw and processed data to reproduce the results shown in:</p> <p>Torregiani, C., Reale, M., Confalonieri, M., Dore, F., Crisafulli, C., Baratella, E., ... & Maiello, G. (2024). Cardiopulmonary exercise testing complements both spirometry and nuclear imaging for assessing sarcoidosis stage and for monitoring disease activity. <em>Sarcoidosis, Vasculitis, and Diffuse Lung Diseases</em>, 41(1), e2024017-e2024017. https://doi.org/10.36141/svdld.v41i1.15125</p>
Supporting Materials for: The calm before the (next) storm: no third outburst in 2019--2020, and ongoing monitoring of the transient AGN IC 3599
<p>This deposit contains supporting materials for the article "The calm before the (next) storm: no third outburst in 2019--2020, and ongoing monitoring of the transient AGN IC 3599" by Grupe, Komossa, and Wolsing (2024), ApJ. </p> <p>The deposit has the following machine-readable tables:</p> <p><a href="../api/records/10899673/draft/files/MRT_longterm_xray_fig1.txt/content" target="_blank" rel="noopener noreferrer">MRT_longterm_xray_fig1.txt</a>: contains the data used to create Figure 1. These are 0.2-2.0 keV fluxes of IC 3599 fromm ROSAT, Chandra, and Swift observations. </p> <div> </div> <div><a href="../api/records/10899673/draft/files/MRT_swift_observations.txt/content" target="_blank" rel="noopener noreferrer">MRT_swift_observations.txt </a>: contains the information about the Swift XRT and UVOT observations, including the Target ID, segement, start and end times in UT, the MJD of the middle of the exposure times in the XRET and each of the UVOT filters. This table is Table 1 in the Appendix of the paper</div> <div> </div> <div> </div> <div><a href="../api/records/10899673/draft/files/MRT_Swift_results.txt/content" target="_blank" rel="noopener noreferrer">MRT_Swift_results.txt</a> : contains the fluxes measured in the XRT and UVOT filters. These results were used to create Figures 2 - 7. This table is Table 3 in the Appendix of the paper. </div> <div> </div> <p>The deposit conatins the UV W2 image that was use to create Figure 10. This is <a href="../api/records/10899673/draft/files/uvw2_sum_low_2013_2023.fits/content" target="_blank" rel="noopener noreferrer">uvw2_sum_low_2013_2023.fits</a></p> <p> </p> <p>The files <a href="../api/records/10899673/draft/files/arf_pc_2013_2023.fits/content" target="_blank" rel="noopener noreferrer">arf_pc_2013_2023.fits</a> , <a href="../api/records/10899673/draft/files/backgr_spec_pc_2013_2023.fits/content" target="_blank" rel="noopener noreferrer">backgr_spec_pc_2013_2023.fits</a> , <a href="../api/records/10899673/draft/files/source_spec_pc_2013_2023.fits/content" target="_blank" rel="noopener noreferrer">source_spec_pc_2013_2023.fits </a>were used for the X-ray spectral analysis of the low state data between 2013-2023. This low state spectrum is displayed in Figures 8 and 9, and was used for the</p> <p>spectral energy distribution in Fugure 11. </p> <p> </p> <p>The files <span><a href="../api/records/10899673/draft/files/arf_pc_high_2010.fits/content" target="_blank" rel="noopener noreferrer">arf_pc_high_2010.fits</a></span> , <span><a href="../api/records/10899673/draft/files/backgr_spec_high_2010.fits/content" target="_blank" rel="noopener noreferrer">backgr_spec_high_2010.fits</a></span> , <span><a href="../api/records/10899673/draft/files/source_spec_high_2010.fits/content" target="_blank" rel="noopener noreferrer">source_spec_high_2010.fits</a></span> were used to do the X-ray spectral</p> <p>analysis of the 2010 high state data. This spectrum is displayed in Figure 9 and was used in Figure 11 to show the spectral energy distribution. </p> <p> </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.