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8,460 results for “MONITORING”
Modern phenotypic typing technologies for monitoring and evaluating heterogeneity in bacterial populations
<p>Modern phenotypic typing technologies for monitoring and evaluating heterogeneity in bacterial populations</p> <p>Современные технологии фенотипического типирования для мониторинга и оценки гетерогенности бактериальных популяций</p>
Data for "Advanced Structural Health Monitoring Method by Integrated Isogeometric Analysis and Distributed Fiber Optic Sensing"
<p>This dataset includes the experiment and simulation data of a new structural health monitoring system using distributed fiber optic sensing (DFOS) and Isogeometric Analysis (IGA).</p> <p>The experiment setup was a 5mm thick PVC pipe with a fiber optic cable wrapped around the outer surface of the pipe. The PVC pipe was subjected to an applied deformation and the distributed strains along the optical fiber was measured with a Neubrescope (NBX7031) instrument using Rayleigh backscattering technology.</p> <p>The simulation was performed using the in-house code JWRIAN-IGA developed in Joining and Welding Research Institute, Osaka University. The simulated data includes deformation, stress and strain distributions of the pipe, and projected one-dimensional fiber strains. The visualization files are post-processed with ParaView software.</p>
Dataset of EPR-monitored-redox potentiometries performed with distinct CrFdx isoforms and variants
<p>The zip-folder contains the raw EPR data and data necessary for construction of the Nernst fits that appear in:</p> <p>Melanie Heghmanns, Alexander Günzel, Dörte Brandis, Yury Kutin, Vera Engelbrecht, Martin Winkler, Thomas Happe, Müge Kasanmascheff, "Fine-tuning of FeS Proteins Monitored via Pulsed EPR Redox Potentiometry at Q-band", Biophysical Reports, 2021, https://doi.org/10.1016/j.bpr.2021.100016.</p> <p>A brief explanation of the files and samples can be found in “Readme.docx”. <br> The relevant data obtained are compiled in “Summary_data.xlsx”. <br> Other experimental details can be found in the paper.</p>
Dataset of "Triggering and propagation of exogeneous sediment pulses in mountain channels: insights from flume experiments with seismic monitoring"
<p>Dataset of "Triggering and propagation of exogeneous sediment pulses in mountain channels: insights from flume experiments with seismic monitoring".</p>
DiaMOS Plant Dataset: A Dataset for Diagnosis and Monitoring Plant Disease
<p>DiaMOS Plant, is a dataset for diagnosis and monitoring plant disease, collected in the field, consisting of 3505 images, depicting 4 leaf diseases with 4 level of severity and 4 fruit stages.</p> <p> </p> <p>Cite as:</p> <p>Fenu, G.; Malloci, F.M. DiaMOS Plant: A Dataset for Diagnosis and Monitoring Plant Disease. Agronomy 2021, 11, 2107. https://doi.org/10.3390/agronomy11112107</p>
Monitoring vertebrate biodiversity of a protected coastal wetland using eDNA metabarcoding
<p>Monitoring plans using environmental DNA have the potential to offer a standardized and cost-efficient method to survey biodiversity in aquatic ecosystems. Among these ecosystems, coastal wetlands are key elements that serve as transition zones between marine and freshwater ecosystems and are today the target of many conservation and restoration efforts. In this sense, eDNA monitoring could provide a rapid and efficient tool for studying and generating baseline biodiversity information to guide coastal wetland management programs. Here we test an eDNA metabarcoding assay as a tool to characterize vertebrate biodiversity in one of the largest coastal wetlands of Chile, the Rio Cruces Wetland, a Ramsar designated site since 1981. We sampled surface water from 49 sites along the entire wetland. Our eDNA approach detected 91 genera of vertebrates including amphibians, fishes, mammals, and birds, as well as identified several cryptic, exotic, and endangered species. Our results also indicated that the spatial distribution of eDNA from different species is spatially structured despite the complex hydrodynamics inherent in this wetland due to the influence of daily tidal regimes. For amphibians and fishes, the number of taxa detected with eDNA was higher in the periphery of the wetland, and increased with proximity to the ocean, a pattern consistent with small-scale spatial sensitivity for some species and eDNA accumulation downstream for others. Birds and mammals showed somewhat more idiosyncratic distributions. Taken together our results add to the growing body of evidence showing eDNA can serve as a rapid cost-effective tool to characterize vertebrate communities in protected coastal wetlands, where visual surveys are difficult and animal collections are often prohibited. The use of multiple primer sets is also recommended as it facilitates the detection of ephemeral terrestrial organisms and resident aquatic organisms that make use of these wetlands.</p>
Data from: Predicting bushmeat biomass from species composition captured by camera traps: implications for locally-based wildlife monitoring
<p>The 'StatAnalysis.zip' contains the data and model files. We used it for the four analyses below.</p> <p>First, we estimated population densities, the mean body mass and camera-trap capture rates of five main bushmeat targets in a rainforest of southeast Cameroon: Peters's duikers (<em>Cephalophus callipygus</em>), bay duikers (<em>C. dorsalis</em>), blue duikers (<em>Philantomba monticola</em>), brush-tailed porcupines (<em>Atherurus africanus</em>) and Emin's pouched rats (<em>Cricetomys emini</em>). Second, on the basis of the density and body mass estimates, we estimated bushmeat biomass—the total biomass of the five bushmeat species—and its spatial variation. Third, we calculated six bushmeat indicators based on the capture rate estimates. Lastly, we examined the correlation between bushmeat biomass and the indicators.</p> <p>The ZIP file consists of 16 R script files, three CSV files (in the 'data' subfolder) and 135 stan files (in the 'stan' subfolders). It also has two empty folders, 'figure' and 'res', where the figures and R objects of model results will be stored following the analyses. Please see the document 'README.txt' before performing the analysis. This text file gives the ZIP file structure and brief descriptions of the files.</p>
PUDL Raw EPA Hourly Continuous Emission Monitoring System (CEMS)
<p>US EPA hourly Continuous Emissions Monitoring System (CEMS) data. Hourly CO2, SO2, NOx emissions and gross load. Archived from <a href="https://campd.epa.gov/">https://campd.epa.gov/</a></p><p>This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by <a href="https://catalyst.coop">Catalyst Cooperative</a>. It is organized into <a href="https://specs.frictionlessdata.io/data-package/">Frictionless Data Packages</a>. For additional information about this data and PUDL, see the following resources:</p><ul><li><a href="https://github.com/catalyst-cooperative/pudl">The PUDL Repository on GitHub</a></li><li><a href="https://catalystcoop-pudl.readthedocs.io">PUDL Documentation</a></li><li><a href="https://zenodo.org/communities/catalyst-cooperative/">Other Catalyst Cooperative data archives</a></li></ul><p>In order to enable more regular CEMS updates, this dataset replaces a prior PUDL EPA CEMS archive that pulled one annual file for each state. That archive is no longer updated but can be found <a href="https://zenodo.org/doi/10.5281/zenodo.4127054">here</a>.</p>
Transitioning from microsatellites to SNP-based microhaplotypes in genetic monitoring programs: lessons from a 20-year time series of paired data.
<p>Many long-term genetic monitoring programs began before next-generation sequencing became widely available. Older programs can now transition to new marker systems usually consisting of 1000s of SNP loci, but there are still important questions about comparability, precision, and accuracy of key metrics estimated using SNPs. Ideally, transitioned programs should capitalize on new information without sacrificing continuity of inference across the time series. We combined existing microsatellite-based genetic monitoring information with SNP-based microhaplotypes obtained from archived samples of Rio Grande silvery minnow (<em>Hybognathus amarus</em>) across a 20-year time series to evaluate point estimates and trajectories of key genetic metrics. Demographic and genetic monitoring bracketed multiple collapses of the wild population, and included cases where captive-born repatriates comprised the majority of spawners in the wild. Even with smaller sample sizes, microhaplotypes yielded comparable and in some cases more precise estimates of variance genetic effective population size, multilocus heterozygosity and inbreeding compared to microsatellites because many more microhaplotype loci were available. Microhaplotypes also recorded shifts in allele frequencies associated with population bottlenecks. Trends in microhaplotype-based inbreeding metrics were associated with the fraction of hatchery-reared repatriates to the wild, and should be incorporated into future genomic monitoring. Although differences in accuracy and precision of some metrics were observed between marker types, biological inferences and management recommendations were consistent.</p>
Source Data for Crowdsourcing Bridge Dynamic Monitoring with Smartphone Vehicle Trips
<p>This data accompanies the study "Crowdsourcing Bridge Dynamic Monitoring with Smartphone Vehicle Trips" published in (Nature) Communications Engineering. This paper focuses on using large and inexpsensive datasets for obtaining information on the dynamics of bridges. In this study, data is collected by smartphones in moving vehicles as the cross over a bridge, in three distinct applications. Smartphone data was collected in controlled field experiments and uncontrolled Uber rides on a long-span suspension bridge in the USA (The Golden Gate Bridge) and an analytical method was developed to accurately recover modal properties. The method was also successfully applied to partially-controlled crowdsourced data collected on a short-span highway bridge in Italy. The results suggest that larve and inexpensive datasets collected by smartphones could play a role in monitoring the health of existing transportation infrastructure.</p> <p>The data provided includes the source data for the figures in the publication as well as the "controlled data" referenced in the study.</p>
Country‐wide genetic monitoring over 21 years reveals lag in genetic recovery despite spatial connectivity in an expanding carnivore (Eurasian otter, Lutra lutra) population
<p>Numerous terrestrial mammal species have experienced extensive population declines during past centuries, due largely to anthropogenic pressures. For some species, including the Eurasian otter (<em>Lutra lutra</em>), environmental and legal protection has more recently led to population growth and recolonisation of parts of their historic ranges. While heralded as conservation successes, only a few such recoveries have been examined from a genetic perspective, i.e. whether genetic variability and connectivity have been restored. We here use large-scale and long-term genetic monitoring data from UK otters, whose population underwent a well-documented population decline between the 1950s to 1970s, to explore the dynamics of a population re-expansion over a 21-year period. We genotyped otters from across Wales and England at five time points between 1994 and 2014 using 15 microsatellite loci. We used this combination of long-term temporal and large-scale spatial sampling to evaluate 3 hypotheses relating to genetic recovery; that (i) gene flow between sub-populations would increase over time, (ii) genetic diversity of previously isolated populations would increase, and that (iii) genetic structuring would weaken over time. Although we found an increase in inter-regional gene flow and admixture levels among subpopulations, there was no significant temporal change in either heterozygosity or allelic richness. Genetic structuring among the main sub-populations hence remained strong and showed a clear historical continuity. These findings highlight an underappreciated aspect of population recovery of endangered species, that genetic recovery may often lag behind the processes of spatial and demographic recovery. In other words, the restoration of physical connectivity of populations does not necessarily lead to genetic connectivity. Our findings emphasise the need for genetic data as an integral part of conservation monitoring, to enable the potential vulnerability of populations to be evaluated.</p>
Geochemical, timescales data in orthopyroxenes from Kizimen 2010 eruption and database of studies linking diffusion timescales with monitoring signals.
<p>This dataset comprises the geochemical data on whole rock analysis, melt inclusions, residual glasses, magnetites and orthopyroxenes in samples from the 2010 eruption of Kizimen volcano (Kamchatka), as well as the timescales modelled in the orthopyroxenes and a database of studies linking diffusion timescales with monitoring signals, associated with the publication: Ostorero, L., Balcone-Boissard, H., Boudon, G. <em>et al.</em> Correlated petrology and seismicity indicate rapid magma accumulation prior to eruption of Kizimen volcano, Kamchatka. <em>Commun Earth Environ</em> <strong>3</strong>, 290 (2022). https://doi.org/10.1038/s43247-022-00622-3</p> <p> </p>
Monitoring the Internet Computer (Artifact)
<p>This artifact accompanies the paper <em>Monitoring the Internet Computer</em>, which will be presented at the 25th International Symposium on Formal Methods (FM 2023). It provides the policy formulas described in Section 3.2 of the paper, the raw log files that were used in the evaluation, and all tools necessary to reproduce the experimental results, specifically those reported in Table 2 and Figure 5 in the paper.</p> <p>See README.md for additional information and instructions.</p> <p><strong>Erratum</strong> (August 14, 2023): Unlike stated in Table 1 of the paper, the block-validation-latency policy included in this artifact does not contain a future operator. The operator was present in an earlier version of the policy. It was removed because it was not required given the structure of the log data. The future operator can be added by inserting</p> <pre>EVENTUALLY [0,0]</pre> <p>at the end of line 50 of the file policy-monitoring/mfotl-policies/block_validation_latency/formula.mfotl. We did not observe a meaningful change in the results when we repeated the experiments using both the included and the modified policy.</p>
Quantitative monitoring of diverse fish communities on a large scale combining eDNA metabarcoding and qPCR
<p>eDNA metabarcoding is an effective method for studying fish communities but allows only an estimation of relative species abundance (density / biomass). Here, we combine metabarcoding with an estimation of the total abundance of eDNA amplified by our universal marker (teleo) using a qPCR approach to infer the absolute abundance of fish species. We carried out a 2,850 km eDNA survey within the Danube catchment using a spatial integrative sampling protocol coupled with traditional electrofishing for fish biomass and density estimation. Total fish eDNA concentrations and total fish abundance were highly correlated. The correlation between eDNA concentrations per taxon and absolute specific abundance was of comparable strength when all sites were pooled and remained significant when the sites were considered separately. Furthermore, a non-linear mixed model showed that species richness was underestimated when the amount of teleo-DNA extracted from a sample was below a threshold of 0.65.106 copies of eDNA. This result, combined with the decrease in teleo-DNA concentration by several orders of magnitude with river size, highlights the need to increase sampling effort in large rivers. Our results show a comprehensive description of longitudinal changes in fish communities and underline our combined metabarcoding/qPCR approach for biomonitoring and bioassessment surveys when a rough estimate of absolute species abundance is sufficient.</p>
Genova - Rain monitoring network
<p>This dataset is published into the Genova Open Data Portal and imported in the UNaLab Open Data to monitor weather data from Genova city</p>
Tampere KPIs (from City Performance Monitor)
<p>This dataset contains all the Tampere KPIs monitored through the Tampere Performance Monitor and exported in JSON format.</p>
Genova KPIs (from City Performance Monitor)
<p>This dataset contains all the GEnova KPIs monitored through the City Performance Monitor and exported in JSON format.</p>
Eindhoven KPIs (from City Performance Monitor)
<p>This dataset contains all the Eindhoven KPIs monitored through the CIty Performance Monitor and exported in JSON format.</p>
Raw data: Wildbee Monitoring along two elevational gradients in Germany
<p><a name="_Hlk94689048"></a><span>Global warming is assumed to restructure mountain insect communities in space and time. Theory and observations along climate gradients predict that insect abundance and richness, especially of small-bodied species, will increase with increasing temperature</span>.<span> However, the specific responses of single species to rising temperatures, such as spatial range shifts, may weaken such prediction, asking for intensive monitoring of real-world communities over time. Here, we examined the temporal and spatial change in wild bee communities and its drivers along two largely well-protected elevational gradients (alpine grassland vs. prealpine forest), each resampled within the last decade. Along both gradients, we detected clear upward shifts in bee communities,</span> with cold-adapted bumblebee species<em> </em><span>reacting particularly sensitive, demonstrating the speed with which mobile organisms can respond to climatic changes. Mean annual temperature (MAT) was identified as the main driver of species richness in both regions. Accordingly, and in large overlap with expectations under climate warming, we detected an increase in bee richness and abundance, and an increase of small-bodied species in low- and mid-elevations along the grassland gradient. While changes in upward shifts, species richness, abundance and body size in the prealpine forest gradient were partly consistent with the alpine grassland system, they were generally weaker, which could be due to a much less severe warming trend than in the alpine grassland system or due to the variable and possibly confounding effect of canopy cover. Our study highlights the use of <a name="_Hlk94772843"></a>accurate assessed abundance data revealing rapid changes in bee communities over only one decade. We conclude, that in well-protected temperate regions, small-bodied bees may initially profit from warming temperatures, by getting more abundant and diverse.</span></p>
Flash drought monitor (FDM) datasets
<p>Flash drought monitor (FDM) is the first near-real time monitoring system for operational tracking of flash drought conditions in Spain (<a href="https://flash-drought.csic.es/">https://flash-drought.csic.es</a>). FDM is based on Standardized Precipitation Evapotranspiration Index (SPEI) at short time scale (1-month) and high spatial (1.21 km<sup>2</sup>) and temporal (weekly) resolution data. Flash drought events were identified following the methodology suggested by Noguera et al. (2020). Thus, we defined a flash drought event as: (i) a minimum length of 4 weeks in the development phase; (ii) a ΔSPEI equal to or <−2 z-units; and (iii) a final SPEI value equal to or <−1.28 z-units (corresponding to return periods of 10 years). See additional details in Noguera et al. (2020).</p> <p>Here, we provide the datasets used by FDM to monitor flash drought conditions in Spain for the period 1961-2021. We include the SPEI (1-month time scale) dataset used for flash drought identification, as well as meteorological datasets required for SPEI calculation [i.e., precipitation and reference evapotranspiration (ETo)]. Likewise, we include the dataset with the flash drought conditions recorded in Spain for the period 1961-2021, indicating the number of weeks elapsing from the onset of a flash drought by means of the following encoding: value = 0 (no flash drought), value = 1 (flash drought onset), value = 2 (1st week from onset), value = 3 (2nd week from onset), value = 4 (3rd week from onset). All datasets are provided in netCDF (network Common Data Form) format, and contain high spatial (1.21 km<sup>2</sup>) and temporal (weekly) resolution data for the period 1961-2021.</p> <p>The precipitation and ETo datasets were created using all daily observational information of precipitation, maximum and minimum air temperature, relative humidity, sunshine duration (as a surrogate of solar radiation) and wind speed from the National Spanish Meteorological Service (AEMET). FAO-56 Penman–Monteith equation (Allen et al., 1998) was used to calculate the reference evapotranspiration (ETo), which is a spatially and temporally comparable metric for the atmospheric evaporative demand (AED). Employing precipitation and ETo data we computed SPEI at a 1-month time scale following the methodology proposed by Vicente-Serrano et al. (2010). Additional details of the datasets development and validation are available in Vicente-Serrano et al. (2017).</p> <p><strong>References:</strong></p> <p>Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements.</p> <p>Noguera, I., Domínguez-Castro, F., & Vicente-Serrano, S. M. (2020). Characteristics and trends of flash droughts in Spain, 1961–2018. Annals of the New York Academy of Sciences, 1472(1), 155– 172. https://doi.org/10.1111/nyas.14365</p> <p>Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010). A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index. Journal of Climate, 23(7), 1696–1718. https://doi.org/10.1175/2009JCLI2909.1</p> <p>Vicente-Serrano, S. M., Tomas-Burguera, M., Beguería, S., Reig, F., Latorre, B., Peña-Gallardo, M., et al. (2017). A High Resolution Dataset of Drought Indices for Spain. Data, 2(3), 22. https://doi.org/10.3390/data2030022</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.