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858 results for “monitoring data”
Data series of seismic events for the article "Seismic monitoring using the telecom fiber network"
<p>The file "catalog.h5" contains the catalog of seismic events analyzed in the paper "Seismic monitoring using the telecom fiber network" by S. Donadello et al., Commun Earth Environ 5, 178 (2024) <a href="https://doi.org/10.1038/s43247-024-01338-2">https://doi.org/10.1038/s43247-024-01338-2</a> (formerly "Earthquake observatory with coherent laser interferometry on the telecom fiber network" on arXiv preprint).</p> <p>The reported data correspond to raw recordings, acquired by coherent interferometry techniques on a telecommunication fiber (see also <a href="doi.org/10.1109/TIM.2023.3288255">https://doi.org/10.1109/TIM.2023.3288255</a>), and decimated to a lower sampling rate.</p> <p>The catalog is organized as about 900 seismic events in the period between June 19th, 2021 and Sept. 26th, 2022, between Feb. 6th and March 23th 2023, and between Nov. 9th, 2022 and Nov. 18th, 2022, according to the criteria described in the paper.</p> <p>A detailed description of the ".h5" file format is provided in "h5_file_description.txt".</p> <p>A Python3 script "h5_cat_parser.py" for data interpretation in terms of standard python structures is provided.</p>
Water level elevation data for monitoring wells and surface water gages at the Colorado State University Mountain Campus, 2019 – 2023
<p>This dataset contains groundwater and surface water levels measured between 2019 and 2023 at the Colorado State University Mountain Campus. The study site is situated within a formerly glaciated valley traversed by a modern perennial stream, the South Fork Cache la Poudre River, and occurs near the subalpine-montane ecosystem transition at an approximate elevation of 2,750 meters above sea level. Water levels were measured at two transects (the upstream and downstream transects). Each transect includes a surface water gage, two shallow hand-augered monitoring wells on the valley floor within the riparian zone, and a deeper water table observation well located on the adjacent terrace. Water levels were measured at a subhourly frequency using a combination of vented and non-vented pressure transducers. All data from non-vented transducers were corrected for barometric pressure fluctuations.</p>
Supporting data to "Open-source, low-cost, in-situ turbidity sensor for river network monitoring"
<p>This folder contains the Supporting Dataset that is part of the Manuscript "Open-source, low-cost, in-situ turbidity sensor for river network monitoring."</p>
Astra Memory Error and System Monitoring Data Sets
<p>Memory error events and system monitoring information gathered on Astra while it was operating from January 20, 2019 to September 14, 2019. See the dataset description files in the archive for additional details.</p>
Data from: Integrated wildlife monitoring, a pilot trial in Spain
<p>This study aims to report the implementation of the first nationwide pilot trial of balanced IWM in Europe, using a network of 11 pilot monitoring sites in Spain. The insights obtained in this pilot IWM trial will help to further develop a comprehensive IWM and serve as a reference for implementing IWM systems in other regions. For this purpose, a grid of 20 camera traps (Browning Strike Force HD ProX, Browning Arms Company®, Morgan, Utah, USA) was deployed for two months at each study site (n=11). REM was applied to wild boar (<em>Sus scrofa</em>), red deer (<em>Cervus elaphus</em>), and red fox (<em>Vulpes vulpes</em>) as the most frequently detected species. Relative abundance indexes, namely trapping rate and relative occupancy index, were calculated for the remaining, less frequently detected species.</p> <p>Files include the data necessary for the estimation of the population density by REM (DataREMZenodo.xlsx), data on indirect interactions recorded by camera traps at the pilot monitoring site level (DataIntZenodo.xlsx), and the metadata of the images (Metadata_imagesbyPP.xlsx).</p> <p> </p>
Data from: Genotyping-in-Thousands by Sequencing panel development and application for high-resolution monitoring of introgressive hybridization within sockeye salmon
<p>Stocking programs have been widely implemented to re-establish extirpated fish species to their historical ranges; when employed in species with complex life histories, such management activities should include careful consideration of resulting hybridization dynamics with resident stocks and corresponding outcomes on recovery initiatives. Genetic monitoring can be instrumental for quantifying the extent of introgression over time, however, conventional markers typically have limited power for the identification of advanced hybrid classes, especially at the intra-specific level. Here, we demonstrate a workflow for developing, evaluating, and deploying a Genotyping-in-Thousands by Sequencing (GT-seq) SNP panel with the power to detect advanced hybrid classes to assess the extent and trajectory of intra-specific hybridization, using the sockeye salmon (<em>Oncorhynchus nerka)</em> stocking program in Skaha Lake, British Columbia, as a case study. Previous analyses detected significant levels of hybridization between the anadromous (sockeye) and freshwater resident (kokanee) forms of <em>O. nerka</em>, but were restricted to assigning individuals to pure-stock or "hybrid". Simulation analyses indicated our GT-seq panel had high accuracy, efficiency and power (> 94.5%) of assignment to pure-stock sockeye salmon/kokanee, F<sub>1</sub>, F<sub>2</sub>, and B<sub>2</sub> backcross-sockeye/kokanee. Re-analysis of 2016/2017 spawners previously analyzed using TaqMan<span> </span>assays and otolith microchemistry revealed shifts in assignment of some hybrids to adjacent pure-stock or B<sub>2</sub>-backcross classes, while new assignment of 2019 spawners revealed hybrids comprised 31% of the population, ~74% of which were B<sub>2</sub>-backcross or F<sub>2</sub>. Overall, the GT-seq panel development workflow presented here could be applied to virtually any system where genetic stock identification and intra-specific hybridization are important management parameters.</p>
Рис. 1. Зонирование Амурской обΛасти на территории мониторинга попуΛяции ΑаΛьневосточного аиста. Синяя и зеΛеная зоны — учетные Αанные 2018 г., жеΛтая зона — учетные Αанные 2019 г., серая зона — опросные Αанные 2011–2017 гг. Fig. 1. Oriental stork monitoring zones in the Amur region. The blue and green zones are the 2018 survey, the yellow zone is the 2019 survey, the gray zone is the 2011–2017 survey data in Oriental stork (Ciconia boyciana Swinhoe) breeding population survey in the Amur region in 2018-2019
Рис. 1. Зонирование Амурской обΛасти на территории мониторинга попуΛяции ΑаΛьневосточного аиста. Синяя и зеΛеная зоны — учетные Αанные 2018 г., жеΛтая зона — учетные Αанные 2019 г., серая зона — опросные Αанные 2011–2017 гг. Fig. 1. Oriental stork monitoring zones in the Amur region. The blue and green zones are the 2018 survey, the yellow zone is the 2019 survey, the gray zone is the 2011–2017 survey data
Monitoring data of Zhujiatang landslide
<p>Data is for scientific research use only.</p>
Data from: Mapping canopy cover for municipal forestry monitoring: Using free Landsat imagery and machine learning
<p><strong>Paper Abstract:</strong></p> <p>Trees across the urban-rural continuum are recognized for their ecological importance and ecosystem services. Municipalities often utilize spatial canopy cover data for monitoring this resource. Monitoring frameworks typically rely on fine-scale maps derived from very high spatial resolution sensors, which are high quality but expensive and unwieldy for consistent wide-area monitoring. In this paper, we explore how free Landsat imagery, supported by very high-resolution imagery interpretation and/or digital hemispherical photographs, can be used to effectively map canopy cover at a scale appropriate for municipal monitoring. We compare linear models and random forest machine learning for predicting canopy cover across a landscape (general) and within specific land covers (specialized). We create 2018 canopy cover maps and track progress towards forestry objectives in a region of southern Ontario, Canada. Random forest models using all reference data perform best for general use (R<sup>2</sup>: 0.90, RMSE: 10.1%), separating non-canopy vegetation (e.g., agricultural fields) from tree canopy. Specialized models are useful in forest land cover patches, where hemispherical photographs relate with Landsat at a moderate strength (R<sup>2</sup>: 0.67, RMSE: 2.73%), and in residential areas, capturing the totality of canopy cover variation (R<sup>2</sup>: 0.85, RMSE: 5.66%). Accuracy was assessed with standard cross-validation, which is useful given limited resources. However, following best practice, an independent reference sample was also leveraged to assess the best general model (R<sup>2</sup>: 0.86, RMSE: 11.4%), indicating that cross-validation was slightly overoptimistic. Results show that Caledon, a rural-dominant municipality within the study area, is the greenest (34% canopy cover). The two cities (Brampton and Mississauga) have 15.9% and 17.5% canopy cover. Residential canopy criteria indicate “Good” performance in Caledon, “Moderate” in Mississauga, and “Low” in Brampton based on our 2018 assessment. The methods described here can provide municipalities with a low-cost approach for tree canopy monitoring across complex landscapes.</p> <p> </p> <p><strong>Data details:</strong></p> <p>See paper. </p>
FIGURE 8 in Novel analysis of locality data can inform better inventory and monitoring practices for paleontological resources at John Day Fossil Beds National Monument Oregon, USA
FIGURE 8. Boxplot of last yield over area index by hiatus length. Note the similar mean between all hiatus lengths.
FIGURE 4 in Novel analysis of locality data can inform better inventory and monitoring practices for paleontological resources at John Day Fossil Beds National Monument Oregon, USA
FIGURE 4. Aerial photograph with example measurements of T2.0" and L7.0". Fieldworkers recorded locality data by locating their place on the air photograph, measuring inches from the top and inches from the left, and writing the air photograph number and measurements in field notes.
FIGURE 5 in Novel analysis of locality data can inform better inventory and monitoring practices for paleontological resources at John Day Fossil Beds National Monument Oregon, USA
FIGURE 5. Map of field collection data for Test Area from 1999-2000. Each point represents one field number. Precise locality information is available to qualified researchers upon request from JODA's museum program.
FIGURE 2 in Novel analysis of locality data can inform better inventory and monitoring practices for paleontological resources at John Day Fossil Beds National Monument Oregon, USA
FIGURE 2. Map of Oregon showing the three park units (purple) and the extent of the majority of non-NPS sites worked by JODA paleontologists (green). There are museum collections at JODA from many sites in area highlighted in green. However, many of these sites have not been visited recently. Many of the sites with paleontological resources in the green area are found on lands administered or owned by partners and are scattered across the full area.
FIGURE 3 in Novel analysis of locality data can inform better inventory and monitoring practices for paleontological resources at John Day Fossil Beds National Monument Oregon, USA
FIGURE 3. Map of locality data for cataloged specimens by year collected in one of the five main collection areas. Years correspond to cyclic prospecting schedule outlined in Table 1. Note the overlap between 1993 and 1994 and 1997 and 1998 contrary to the schedule shown in Table 1. Precise locality information is available to qualified researchers upon request from JODA's museum program.
FIGURE 1 in Novel analysis of locality data can inform better inventory and monitoring practices for paleontological resources at John Day Fossil Beds National Monument Oregon, USA
FIGURE 1. Composite stratigraphic column of the John Day Formation with the Columbia River Basalt Group capping the section. Stratigraphic relationships and radiometric dates are based on Hunt and Stepleton (2004), Albright et al. (2008), and Fremd (2010). The black box encompasses the subunits that are considered lower Turtle Cove for the purposes of this study. Figure provided by the National Park Service.
Data for the paper: "A soundscape approach for a short-term acoustic monitoring of a Critically Endangered Cuban frog"
<p>This 4 excel sheets contain the data sets for the paper “A soundscape approach for a short-term acoustic monitoring of a Critically Endangered Cuban frog” . The data comprises the call rate informatione xtracted from te recordings and the Acoustical index data for descibing the soundscape of the area</p>
Figure 5 from: Assou D, Segniagbeto GH, Radji R, Akiti J, Pando F (2018) Monitoring data of marine turtles on the Togolese coast during 2012–2013. ZooKeys 779: 109-118. https://doi.org/10.3897/zookeys.779.26967
Figure 5 Sea turtle species considered in the survey: aLepidochelysolivaceabCheloniamydascDermochelyscoriacea.
System monitoring data
<p>This dataset contains the monitoring information in TeSLA systems.</p>
Continuous Digital Monitoring of Walking Speed in Frail Elderly Patients: Noninterventional Validation Study and Longitudinal Clinical Trial (Data for interventional clinical trial)
<p>Digital technologies and advanced analytics have drastically improved our ability to capture and interpret health relevant data from patients. However, to date, limited data and results have been published detailing real-world patient compliance, demonstrating accuracy in target indications or examining what novel insights and clinical value can be derived. Here we present novel, digital mobility data from two studies: an independent, non-interventional validation study with elderly, naturally slow walking subjects, and a global, multi-site phase IIb clinical trial involving patients with age-related muscle loss and slow walking speed (sarcopenia). Based on these data, we validate the accuracy of a novel algorithm for capturing in-clinic and real-world gait speed in frail, slow-walking adults. We demonstrate the feasibility of continuous monitoring with a wearable inertial sensor in elderly adults in real-world settings, and propose minimum thresholds for compliance required for robust capture of gait behaviors in this population. We also show how simple, inferred contextual information, describing the length of a given walking bout, can explain some of the variation in real-world gait speed, and use this information to demonstrate for the first time a relationship between in-clinic performance and real-world gait speed behavior. This work lays a foundation for exploration of the clinical relevance and value of such measures and is a first step in building a more complete chain of evidence between standardized physical performance assessment, real-world behavior, and subjective perceptions of mobility, independence and health.</p> <p>This dataset contains data collected during the interventional clinical trial: derived data from raw accelerometry data, and summary performance data.</p> <p>The full dataset, including raw accelerometry data, is available here: <a href="https://mueller-et-al-2019.s3.amazonaws.com/index.html">https://mueller-et-al-2019.s3.amazonaws.com/index.html</a></p>
Supporting data for "Simultaneous monitoring of crystalline active materials and resistance evolution in lithium-sulfur batteries"
<p>This is the dataset of electrochemical and operando X-ray diffracytion experiments for our publication "Simultaneous monitoring of crystalline active materials and resistance evolution in lithium-sulfur batteries". This archive contains the raw data and scripts written in R used in the analysis and presentation of the results in this manuscript.</p> <p><strong>Abstract for the manuscript:</strong></p> <p>Operando X-ray diffraction (XRD) is a valuable tool for studying secondary battery materials as it allows for the direct correlation of electrochemical behavior with structural changes of crystalline active materials. This is especially true for the lithium-sulfur chemistry, in which energy storage capability depends on the complex growth and dissolution kinetics of lithium sulfide (Li<sub>2</sub>S) and sulfur (S<sub>8</sub>) during discharge and charge, respectively. In this work, we present a novel development of this method through combining operando XRD with simultaneous and continuous resistance measurement using an Intermittent Current Interruption (ICI) method. We show that a coefficient of diffusion resistance, which reflects the transport properties in the sulfur/carbon composite electrode, can be determined from analysis of each current interruption. Its relationship to the established Warburg impedance model is validated theoretically and experimentally. We also demonstrate for an optimized electrode formulation and cell construction that the diffusion resistance increases sharply at the discharge end point, which is consistent with the blocking of pores in the carbon host matrix. The combination of XRD with ICI allows for a direct correlation of structural changes with not only electrochemical properties but also energy loss processes at a non-equilibrium state, and therefore is potentially highly valuable for the study of many other energy storage chemistries.</p>
ScienceDex guides
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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.