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4,276 results for “Estimation”
Datasets used in 'Streambed hydraulic conductivity estimated by spectral induced polarization imaging can help to improve groundwater modeling'
<p>These datasets pertain to the manuscript entitled 'Streambed hydraulic conductivity estimated by spectral induced polarization imaging can help to improve groundwater modeling', which is currently submitted for revision in Water Resources Research. They comprise raw data from measurements taken in the field at 2 sites in terms of (1) pressure time series during the performed slug tests, (2) impedance from spectral induced polarization, (3) submersion levels of the used electrodes below the top of the water column, and (4) three-dimensional Cartesian coordinates relating the measurements spatially. The coordinates have been projected to a local coordinate system for each site, to comply with a non-disclosure agreement of the measurement locations. The projection of the coordinates still allows to fully reproduce the presented results, if using the methods described in the manuscript. The naming convention throughout the datasets is consistent with site labels used in the manuscript. All data is given as comma-separated values with intuitive file names and self-explanatory headers containing a list of field names. The slug test data includes multiple repetitions of the same measurement, and the impedance measurements contain normal as well as reciprocal readings – as described in the manuscript.</p> <p>The data is separated into two compressed file archives, named according to the site names given in the manuscript. Each file pertaining to slug tests at a certain location, in the subfolder “slugTestRecordings” has the following naming convention: “<locationTag>_<finalDepth>.csv”, where <locationTag> corresponds to the local coordinates given in “coordinates.txt”, and where <finalDepth> is an integer describing the largest depth in cm at which a slug test was performed according to the protocol described in the manuscript. Each file pertaining to impedance measurements at a certain profile, in the subfolder “SIPRecordings”, has the following naming convention: “<locationTag>_<frequency>.dat”, where <locationTag> corresponds to the local coordinates given in “coordinates.txt”, and where <frequency> is a zero-padded integer describing the measurement frequency in Hz at which the measurement was performed according to the protocol described in the manuscript. Submersion levels of the electrodes below the top of the stream’s water column are given in m in the file “submersionLevels.txt”, corresponding to the local coordinates given in “coordinates.txt”. The local coordinates given in m in “coordinates.txt” have the following convention for the column “locationTag”: “<profileTag>-<electrodeNumber>, where <profileTag> pertains to a name of the electrical array and <electrodeNumber”> is a continuous number for the electrode. Slug tests were exclusively perfomed at the location of electrodes and files are, thus, as described above, named accordingly.</p>
FCA-estimated wind using EAR spaced antenna
<p>Dataset for horizontal wind estimation using EAR spaced antenna from configuration 1, 2, 3, 4, and 5.</p> <p>These are the output from FCA method. </p>
Tables of MTZ results and estimated lithospheric thickness beneath the Cenozoic Okavango rift zone and adjacent Precambrian provinces
<p>This file provides tables S1 and S2 on the MTZ observations and estimated lithospheric thickness of each circular bin, respectively, for the paper of "<strong>Topography of the 410 and 660 km discontinuities beneath the Cenozoic Okavango rift zone and adjacent Precambrian provinces" </strong>in JGR 2020.</p> <p>Table S1 is the resulting apparent depths of the d410 and d660 and MTZ thickness of each circular bin.</p> <p>Table S2 is estimated mean upper mantle P wave velocity anomaly and lithospheric thickness derived from the resulting apparent depth of the d410 for each bin. </p>
Collected data on early estimates of global fossil CO2 emissions
<p>This dataset collects together a number of early estimates made of global emissions of fossil CO2, starting with Arvid Högbom in 1894. Microsoft Excel files for original data sources where these are time series, including images of the tables from the original sources, in addition to one CSV file of CO2 emissions from all sources. Sources that only reported emissions for a short period are not included in the Excel collection, but are included in the CSV file. In addition the original United Nations energy data used by several sources is included as UN1956.xlsx.</p>
Supplementary data for article 'Estimating and abstracting the 3D structure of feline bones using neural networks on X-ray (2D) images'
<p>3D DICOM volumes (CT scans) of feline femora, PNGs generated from them as DRRs using MeVisLab, and STLs generated from the DICOM volumes with MIMICS or MeshLab. Software to work with these files can be found at http://doi.org/10.5281/zenodo.3829423</p>
Automatic image-based identication and biomass estimation of invertebrates
<p>Dataset containing images of macroinvertebrates from updated BIODISCOVER (2019). The task of the image collection was to determine optimal camera settings, from 2 parameters: Exposure time and Aperture.</p> <p>A combination of 3 exposure time and aperture settings was tested (total of 9 combinations of settings):</p> <p>Exposure time: 1000, 1500, 2000</p> <p>Aperture: 3.8, 8, 16</p> <p> </p> <p>All images contained within the dataset are separated by camera settings, species and sample number. Samples containing several specimen within one sample number are indexed (example: 10023_1, 10023_2, 10023_3). Further labeling and information can be found within "setup data.csv".</p> <p> </p>
Air-flow distortion bias factors of the port and starboard anemometers of the Akademik Tryoshnikov estimated during the Antarctic Circumnavigation Expedition (ACE) legs 0-4 undertaken during the austral summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>This data set contains the air-flow distortion bias factors of the port and starboard anemometers of the Akademik Tryoshnikov estimated during the Antarctic Circumnavigation Expedition (ACE) legs 0-4 undertaken during the austral summer of 2016/2017. The data are provided over overlapping wind direction secotors of 5(10) degree width stepped by 1(2) degrees relative wind direction. These bias factors can be used to correct the observed wind speeds for air-flow distortion on a sample by sample basis. For details see Landwehr et al. (2019; DOI: https://doi.org/10.5194/amt-2019-366).</p> <p><strong>Dataset contents</strong></p> <ul> <li>flow_distortion_bias_sensor1.csv, data file, comma-separated values</li> <li>flow_distortion_bias_sensor2.csv, data file, comma-separated values</li> <li>data_file_header, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This dataset of air-flow distortion factors is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Data from: Can light-saturated photosynthesis in lowland tropical forests be estimated by one light level?
Leaf-level net photosynthesis (An) estimates and associated photosynthetic parameters are crucial for accurately parameterizing photosynthesis models. For tropical forests such data are poorly available and collected at variable light conditions. To avoid over- or underestimation of modelled photosynthesis, it is critical to know at which photosynthetic photon flux density (PPFD) photosynthesis becomes light saturated. We studied the dependence of An on PPFD in two tropical forests in French Guiana. We estimated the light saturation range, including the lowest PPFD level at which Asat (An at light saturation) is reached, as well as the PPFD range at which Asat remained unaltered. The light saturation range was derived from photosynthetic light-response curves, and within-canopy and interspecific differences were studied. We observed wide light saturation ranges of An. Light saturation ranges differed among canopy heights, but a PPFD level of 1000 µmol/m²/s was common across all heights, except for pioneer trees species that did not reach light saturation below 2000 µmol/m²/s. A light intensity of 1000 µmol/m²/s sufficed for measuring Asat of climax species at our study sites, independent of the species or the canopy height. Because of the wide light saturation ranges, results from studies measuring Asat at higher PPFD levels (for upper canopy leaves up to 1600 µmol/m²/s) are comparable with studies measuring at 1000 µmol/m²/s.
Data from: Estimating transmission dynamics and serial interval of the first wave of COVID-19 infections under different control measures: A statistical analysis in Tunisia from February 29 to May 5, 2020
<p>Background: Describing transmission dynamics of the outbreak and impact of intervention measures are critical to planning responses to future outbreaks and providing timely information to guide policy makers decision. We estimate serial interval (SI) and temporal reproduction number (R<sub>t</sub>) of SARS-CoV-2 in Tunisia.</p> <p>Methods: We collected data of investigations and contact tracing between March 1, 2020 and May 5, 2020 as well as illness onset data during the period February 29-May 5, 2020 from National Observatory of New and Emerging Diseases of Tunisia. Maximum likelihood (ML) approach is used to estimate dynamics of R<sub>t</sub>.</p> <p>Results: 491 of infector-infectee pairs were involved, with 14.46% reported pre-symptomatic transmission. SI follows Gamma distribution with mean 5.30 days [95% CI 4.66-5.95] and standard deviation 0.26 [95% CI 0.23-0.30]. Also, w<span>e estimated large changes in </span>R<sub>t</sub><span> in response to the combined lockdown interventions. The </span>R<sub>t</sub><span> moves from </span>3.18 [95% CI 2.73-3.69] <span>to 1.77 [95% CI 1.49-2.08] with </span>curfew<span> prevention measure, and under the epidemic threshold (0.89 </span>[95% CI 0.84-0.94]) by national lockdown measure<span>.</span></p> <p><span>Conclusions: </span>Overall, our findings highlight contribution of <span>interventions</span> to interrupt transmission of SARS-CoV-2 in Tunisia.</p>
Data from: Estimating fish population abundance by integrating quantitative data on environmental DNA and hydrodynamic modeling
<p>Molecular analysis of DNA left in the environment, known as environmental DNA (eDNA), has proven to be a powerful and cost-effective approach to infer occurrence of species. Nonetheless, relating measurements of eDNA concentration to population abundance remains difficult because detailed knowledge on the processes that govern spatial and temporal distribution of eDNA should be integrated to reconstruct the underlying distribution and abundance of a target species. In this study, we propose a general framework of abundance estimation for aquatic systems on the basis of spatially replicated measurements of eDNA. The proposed method explicitly accounts for production, transport, and degradation of eDNA by utilizing numerical hydrodynamic models that can simulate the distribution of eDNA concentrations within an aquatic area. It turns out that, under certain assumptions, population abundance can be estimated via a Bayesian inference of a generalized linear model. Application to a Japanese jack mackerel (<em>Trachurus japonicus</em>) population in Maizuru Bay revealed that the proposed method gives an estimate of population abundance comparable to that of a quantitative echo sounder method. Furthermore, the method successfully identified a source of exogenous input of eDNA (a fish market), which may render a quantitative application of eDNA difficult to interpret unless its effect is taken into account. These findings indicate the ability of eDNA to reliably reflect population abundance of aquatic macroorganisms; when the "ecology of eDNA" is adequately accounted for, population abundance can be quantified on the basis of measurements of eDNA concentration.</p>
Estimating leaf nitrogen concentration based on the combination with fluorescence spectrum and first-derivative
Leaf nitrogen concentration (LNC) is a major indicator in the estimation of the crop growth status which has been diffusely applied in remote sensing. Thus, it is important to accurately obtain LNC by using passive or active technology. Laser-induced fluorescence (LIF) can be applied to monitor LNC in crops through analyzing the changing of fluorescence spectral information. Thus, the performance of fluorescence spectrum (FS) and first-derivative fluorescence spectrum (FDFS) for paddy rice (Yangliangyou 6 and Manly Indica) LNC estimation was discussed, and then the proposed FS+FDFS was used to monitor LNC by multivariate analysis. The results showed that the difference between FS (R2=0.781, SD=0.078) and FDFS R2=0.779, SD=0.097) for LNC estimation by using the artificial neural network (ANN) is not obvious. The proposed FS+FDFS can improved the accuracy of LNC estimation to some extent (R2=0.813, SD=0.051). Then, principal component analysis was used in FS and FDFS, and extracted the main fluorescence characteristics. The results indicated that the proposed FS+FDFS exhibited higher robustness and stability for LNC estimation (R2=0.851, SD=0.032) than that only using FS (R2=0.815, SD=0.059) or FDFS (R2=0.801, SD=0.065).
Data from: Are skyline plot-based demographic estimates overly dependent on smoothing prior assumptions?
<p>In Bayesian phylogenetics, the coalescent process provides an informative framework for inferring changes in the effective size of a population from a phylogeny (or tree) of sequences sampled from that population. Popular coalescent inference approaches such as the Bayesian Skyline Plot, Skyride and Skygrid all model these population size changes with a discontinuous, piecewise-constant function but then apply a smoothing prior to ensure that their posterior population size estimates transition gradually with time. These prior distributions implicitly encode extra population size information that is not available from the observed coalescent data i.e. the tree. Here we present a novel statistic, Ω, to quantify and disaggregate the relative contributions of the coalescent data and prior assumptions to the resulting posterior estimate precision. Our statistic also measures the additional mutual information introduced by such priors. Using Ω we show that, because it is surprisingly easy to over-parametrise piecewise-constant population models, common smoothing priors can lead to overconfident and potentially misleading inference, even under robust experimental designs. We propose Ω as a useful tool for detecting when posterior estimate precision is overly reliant on prior choices.</p>
Data from: Sonar estimation of summer chum and pink salmon in the Anvik River, Alaska, 2018
Dual-frequency identification sonar (DIDSON) was used to estimate adult summer chum salmon Oncorhynchus keta and pink salmon O. gorbuscha passage in the Anvik River from June 15 to July 26, 2018. Apportionment to species was determined using data collected from tower counts. A total of 305,098 (SE 5,926) summer chum and 1,122,346 (SE 7,588) pink salmon were estimated to have passed the sonar site. A beach seine sample fishery was conducted to collect age, sex, and length information. Both sonar systems functioned well with minimal interruptions to operation. Range of ensonification was considered adequate for most fish that migrated upstream.
Re-evaluating deep neural networks for phylogeny estimation: the issue of taxon sampling
Deep neural networks (DNNs) are powerful machine learning models that are widely used for classification problems, and have been recently proposed for quartet tree phylogeny estimation (Survorov et al. Systematic Biology 2020 and Zou et al. Molecular Biology and Evolution 2020). Here we present a study evaluating recently trained DNNs (from Zou et al., MBE 2020) in comparison to a collection of standard phylogeny estimation methods, including UPGMA, neighbor joining, maximum parsimony, and maximum likelihood, on a heterogeneous collection of 20-sequence datasets simulated under the same models that were used to train the DNNs, and also under similar conditions but with higher rates of evolution. Our study shows that using DNNs with quartet amalgamation (to combine quartet trees into a tree on the full dataset) is only more accurate than UPGMA, and otherwise is less accurate than all standard phylogeny estimation methods we explore (maximum likelihood, neighbor joining, and maximum parsimony). We further find that while DNNs can provide good quartet tree accuracy, some standard phylogeny estimation methods match or improve on DNNs for quartet accuracy, especially, but not exclusively, when used in a global manner (i.e., the tree on the full dataset is computed and then the induced quartet trees are extracted from the full tree). Thus, our study provides evidence that a major challenge impacting the utility of current DNNs for phylogeny estimation is their restriction to estimating quartet trees which must subsequently be combined into a tree on the full dataset: in contrast, global methods -- i.e., those that estimate trees from the full set of sequences -- are able to benefit from taxon sampling, and hence have higher accuracy on large datasets.
Plastic Packaging Market Estimates and Forecast, by Type, 2014 - 2025
<p>Estimates of historical (2014-2018) and forecast (2019-2025) size of the global market for rigid and flexible plastic packaging.</p>
Data from: Age and sex prevalence estimate of Joubert Syndrome in Italy
Objective: To estimate the prevalence of Joubert syndrome (JS) in Italy applying standards of descriptive epidemiology, and to provide a molecular characterization of the described patients cohort. Methods: We enrolled all patients with a neuroradiologically confirmed diagnosis of JS and resident in Italy in 2018, and calculated age and sex prevalence, assuming a Poisson distribution. We also investigated the correlation between proband chronological age and age at diagnosis, and performed Next-Generation Sequencing (NGS) analysis on probands' DNA when available. Results: We identified 284 JS patients: the overall, female- and male-specific population-based prevalence rates were 0.47 (95% CI 0.41-0.53), 0.41 (95% CI 0.32-0.49) and 0.53 (95% CI 0.45-0.61) per 100,000 population, respectively. When considering only patients in the age range from 0 to 19 years, the corresponding population-based prevalence rates rose to 1.7 (95% CI 1.49-1.97), 1.62 (95% CI 1.31-1.99) and 1.80 (95% CI 1.49-2.18) per 100,000 population. NGS analysis allowed identifying the genetic cause in 131 out of 219 screened probands. Age at diagnosis was available for 223 probands, with a mean of 6.67 ± 8.10 years, and showed a statistically significant linear relationship with chronological age (r2=0.91; p<0.001). Conclusions: We estimated for the first time the age and sex prevalence of JS in Italy, and investigated their genetic profile. The obtained population-based prevalence rate was approximately 10 times higher than that available in literature for children population.
data for [Magnetostratigraphic evidence for post-depositional disruption of osmium isotopic records in pelagic clay and its implications for mineral flux estimates]
<p>Data produced in <em>Magnetostratigraphic evidence for post-depositional disruption of osmium isotopic records in pelagic clay and its implications for mineral flux estimates</em></p>
Data and code for paper "A gray-box model for a probabilistic estimate of regional ground magnetic perturbations: Enhancing the NOAA operational Geospace model with machine learning"
<p>Simulation results from the NOAA/SWPC Geospace model used in the paper Camporeale et al. (2020) "A gray-box model for a probabilistic estimate of regional ground magnetic perturbations: Enhancing the NOAA operational Geospace model with machine learning" published in J. Geophys. Res. (2020)</p> <p>MATLAB code is provided to train process the data and train the machine learning model and plot results.</p> <p>Manuscript available on <a href="https://arxiv.org/abs/1912.01038">https://arxiv.org/abs/1912.01038</a></p>
Estimating survival for elusive juvenile pond‐breeding salamanders
<p>Juvenile vital rates have important effects on population dynamics for many species, but this demographic is often difficult to locate and track. As such, we frequently lack reliable estimates of juvenile survival, which are necessary for accurately assessing population stability and potential management approaches to conserve biodiversity. We empirically estimated survival rates for elusive juveniles of 3 complex lifecycle species of salamanders (ringed salamander [<i>Ambystoma annulatum</i>]<i>, </i>spotted slamander<i> </i>[<i>A. maculatum</i>]<i>, </i>and small-mouthed slamander [<i>A. texanum</i>]) using 2 approaches. First, we conducted an 11-month mark-recapture study within semi-natural enclosures and used Bayesian Cormack-Jolly-Seber models to estimate survival and recapture probabilities. Second, we inferred the expected annual juvenile survival rate given published vital rates for pre-metamorphic and adult ambystomatids assuming stable population growth. For all 3 species, juvenile survival probabilities were constant across recapture occasions, while recapture probability estimates were time-dependent. Further, survival and recapture probabilities among study species did not significantly differ. Post-study sampling revealed that the initial study period median estimate of annual survival probability (0.39) underestimated the number of salamanders known alive at 11 months. We therefore appended approximately 1 year of opportunistic data, which produced a median annual survival probability of 0.50, encompassing salamanders that we knew to have been alive. Calculation from literature values suggested a mean annual terrestrial juvenile ambystomatid survival probability of 0.45. Similar results among our approaches indicated that juvenile survival estimates for the study species were robust and likely comparable to rates in nature. These estimates can now be confidently applied to research, monitoring, and management efforts for the study species and ecologically similar taxa. Our data indicated that similarly robust vital rate estimates for subsets of ecologically and phylogenetically similar species can provide reasonable surrogate demographic information to advance conservation efforts for data-deficient species.</p>
Apresentação para Sessão Oral - CBEB2020: Evaluation of the Motor Performance of People with Parkinson's Disease through the Autocorrelation Function Estimated from Sinusoidal Drawings
<p>The objective of this work was to use the autocorrelation function to assess the fine motor performance of a healthy control group (CG) and people with Parkinson's disease (PD), whose fluctuations caused by the disease compromise motor skills, performed mainly by the hands and fingers essential for daily activities such as dressing, carrying objects and taking care of personal hygiene. For this, accelerometer signals were collected while the volunteers drew a sinusoidal pattern. The correlogram was estimated and two features were calculated from it: (i) the normalized area under the curve (𝑨𝒖𝑪); (ii) the difference between matching peaks and valleys from the reference and estimated correlograms (𝒗𝒎𝒎). These features allowed for the discrimination between drawing patterns of CG (𝒗𝒎𝒎= 0.154±0.063, 𝑨𝒖𝑪 = 0.204±0.040) and PD (𝒗𝒎𝒎 = 0.239±0.085, 𝑨𝒖𝑪 = 0.179±0.033) groups. Following the verification of normality (Shapiro-Wilk, p > 0.05), the t-test was applied to confirm the significant differences between groups (p < 0.05). The Cohen’s d effect size (p < 0.05) was medium (0.730) for 𝑨𝒖𝑪 and large (1.252) for 𝒗𝒎𝒎. This further confirms the differences between the features extracted from the groups. Therefore, the features 𝑨𝒖𝑪 and 𝒗𝒎𝒎 estimated from the autocorrelation function are effective for the assessment of the motor performance of healthy individuals and people with PD. </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.