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139 results for “parameter estimation”
Data for: Estimation of genetic parameters for the implementation of selective breeding in commercial insect production
<p><strong>Background</strong></p> <p>There is a burgeoning interest in using insects as a sustainable source of food and feed, particularly by capitalising on various waste materials and by-products that are typically considered of low value. Enhancing the commercial production of insects can be achieved through two main approaches: optimising environmental conditions and implementing selective breeding strategies. In order to successfully target desirable traits through selective breeding, having a thorough understanding of the genetic parameters pertaining to those traits is essential. In this study, a full-sib half-sib mating design was used to estimate variance components and heritabilities for larval size and survival at day seven of development, development time and survival from egg to adult, and to estimate correlations between these traits, within an outbred population of house flies (<em>Musca domestica</em>), using high-throughput phenotyping for data collection.</p> <p><strong>Results</strong></p> <p>The results revealed low to intermediate heritabilities and positive genetic correlations between all traits except development time and survival to day seven of development and from egg to adulthood. Surprisingly, larval size at day seven exhibited a comparatively low heritability (0.10) in contrast to development time (0.25), a trait that is believed to have a stronger association with overall fitness. A decline in family numbers resulting from low mating success and high overall mortality reduced the amount of available data which resulted in large standard errors for the estimated parameters. Environmental factors made a substantial contribution to the phenotypic variation, which was overall high for all traits.</p> <p><strong>Conclusions</strong></p> <p>There is potential for genetic improvement in all studied traits and estimates of genetic correlations indicate a partly shared genetic architecture among the traits. All estimates have large standard errors. Implementing high-throughput phenotyping is imperative for the estimation of genetic parameters in fast developing insects, and facilitates age synchronisation, which is vital in a breeding population. In spite of endeavours to minimise non-genetic sources of variation, all traits demonstrated substantial influences from environmental components. This emphasises the necessity of thorough attention to the experimental design before breeding is initiated in insect populations.</p>
Improving estimations of life history parameters of small animals in mesocosm experiments: A case study on mosquitoes
<p>We used an experimental setup with 48 aquatic mesocosms, each with twenty first instar mosquito (<em>Culex pipiens</em>) larvae and under one of twelve treatments with varying temperatures and nutrient concentrations. We took daily subsamples of the aquatic life stages as well as counting the emerging adults. We developed a method to estimate the survival and development probabilities at each life stage, based on optimising a matrix population model. We used two different approaches, one calculating the difference between predictions and observations based on a normal distribution, and the other using a combination of a normal and a multinomial distribution. For each approach, the resulting optimisation problem had around 100 parameters, making conventional gradient descent ineffective with our limited number of data points. We solved this by computing the formal derivatives of our matrix model.</p>
Smart Battery Management System for Electric Vehicles: Selflearning Algorithms for Simultaneous State and Parameter Estimation, and Stress Detection
<p>The project proposes to develop parameter-varying SOH-coupled models for lithium-ion battery and self-learning algorithms to learn the model for simultaneous state and parameter estimation and fault detection. The traditional battery models use constant parameters, limiting their accuracy for predicting the state of the charge and health over the complete life-cycle. In practice, the battery parameters vary with the change in the state of charge and state of health. SOH-coupled models can be used to estimate the state of charge and health accurately. Further, obtaining the model parameters is also a challenging task for designing filters or observers for state estimation. A self-learning algorithm can eliminate the requirement of the model parameters. In this project, three SOH-coupled models are proposed and validated experimentally. The models are also used to design extended Kalman filters (EKF) for the state of charge, state of health, core and surface temperature, and internal resistance estimation. The results showed that the SOHcoupled models are more effective when compared to the uncoupled models in the literature. Further, it was found that EKFs based state estimation errors were within 1%. The self-learning algorithm using a two-layer neural network showed the ability to learn the models in real-time. However, the state estimation errors are higher for the self-learning scheme compared to the EKF based approaches. This is due to the limited measurement and online training schemes utilized to train neural networks. This requires further investigation in hyper-parameter tuning for implementation. Finally, a model-based fault detection scheme was proposed to detect internal thermal fault at its onset. The SOHcoupled model is reformulated to incorporate the internal resistance as a state. The EKF is used as a fault detection observer. The proposed fault detection scheme is validated using numerical simulation. It was observed that the fault detection scheme with SOH coupled electro-thermal-aging model could effectively detect a thermal fault at its incipient state.</p>
Parameter variability across different timescales in the energy balance-based model and its effect on evapotranspiration estimation
<p>Our dataset is for the manuscript "Parameter variability across different timescales in the energy balance-based model and its effect on evapotranspiration estimation". It includes the instantaneous and daily <em>z<sub>0m</sub></em>, <em>z<sub>0h</sub></em>, <em>g<sub>s</sub></em>, and <em>EBR</em>, which are derived from FLUXNET2015 dataset. The training and test datasets for building the data-driven parameter models are also uploaded.</p>
New parameter estimates for exogenous organic materials including biochar for the Rothamsted carbon model
<p><span>This parameter set has been established within the EJP Soil project Carboseq and is fully explained in the corresponding report (Leifeld, J., Hardy, B., Budai, A., Elsgaard, L., Keel, S.G., Levavasseur, F., Liang, Z., Mondini, C., Plaza, C., Rodrigues, L. 2024. Soil organic carbon sequestration potential of agricultural soils in Europe. Final report EJP Soil CarboSeq work package 3 – Biochar and other organic amendments).</span></p>
Forward Asteroseismic Modeling of Stars with a Convective Core from Gravity-mode Oscillations: Parameter Estimation and Stellar Model Selection
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/arXiv:1806.06869">Aerts et al. (2018)</a>. MESA version 10108.</p> <p>Publication DOI: <a href="https://doi.org/10.3847/1538-4365/aaccfb">10.3847/1538-4365/aaccfb</a></p>
Stellar Parameter Estimation for Half a Million M Dwarfs based on Cycle-StarNet
Open the record for dataset details and reuse information.
Parameter estimation data repository - "Spatial discordances between mRNAs and proteins in the intestinal epithelium"
<p>The repository contains data associated with the estimation of protein translation and decay rates in the manuscript "Spatial discordances between mRNAs and proteins in the intestinal epithelium". Specifically, it includes MCMC-chains approximating the posterior parameter distribution and figures showing the model's fit to the data for each gene as well as a summary table of all fit results for two different models, the constant translation-rate model ("constant_rate_model") and the declining translation-rate model ("declining_rate_model") as explained in the manuscript.</p> <p>Code associated with the parameter estimation is available at https://github.com/LiBuchauer/spatial_MP_discordances .</p>
Three dimensional localization refinement and motion model parameter estimation for confined single particle tracking under low-light conditions: Simulation datasets
<p><span>The datasets store both motion and observation information of a single fluorescent sub-diffraction limit-sized particle moving in a three-dimensional confined environment. The confined motion is following a nonlinear model driven by non-Gaussian noise, the observation is formed by engineered Double-helix (DH) point spread function (PSF) and captured by scientific complementary metal-oxide semiconductor (sCMOS) camera. Based on our prior computationally efficient application of Sequential Monte Carlo - Expectation Maximization (SMC-EM), we extended it to handle the DH-PSF for encoding the three-dimensional position of the particle in two-dimensional image plane of the camera. We focus on studying the datasets at low signal and low signal-to-background ratio (SBR). Based on the datasets across different SBR and confinement lengths, a quantitative comparison is conducted to show that in the low signal regime, the SMC-EM approach outperforms the other methods while at higher signal-to-background levels, SMC-EM and the MLE-based methods perform equally well and both are significantly better than fitting to the MSD. In addition, our results indicate that at smaller confinement lengths where the nonlinearities dominate the motion model, the SMC-EM approach is superior to the alternative approaches. </span></p>
Optimizing parameters for using the parallel auditory brainstem response (pABR) to quickly estimate hearing thresholds
<p><b>Objectives: </b>Timely assessments are critical to providing early intervention and better hearing and spoken language outcomes for children with hearing loss. To facilitate faster diagnostic hearing assessments in infants, the authors developed the parallel auditory brainstem response (pABR), which presents randomly timed trains of tone pips at five frequencies to each ear simultaneously. The pABR yields high-quality waveforms that are similar to the standard, single-frequency serial ABR but in a fraction of the recording time. While well-documented for standard ABRs, it is yet unknown how presentation rate and level interact to affect responses collected in parallel. Furthermore, the stimuli are yet to be calibrated to perceptual thresholds. Therefore, this study aimed to determine the optimal range of parameters for the pABR and to establish the normative stimulus level correction values for the ABR stimuli.</p> <p><b>Design: </b>Two experiments were completed, each with a group of 20 adults (18 – 35 years old) with normal hearing thresholds (≤ 20 dB HL) from 250 to 8000 Hz. First, pABR electroencephalographic (EEG) responses were recorded for six stimulation rates and two intensities. The changes in component wave V amplitude and latency were analyzed, as well as the time required for all responses to reach a criterion signal-to-noise ratio of 0 dB. Second, behavioral thresholds were measured for pure tones and for the pABR stimuli at each rate to determine the correction factors that relate the stimulus level in dB peSPL to perceptual thresholds in dB nHL.</p> <p><b>Results:</b> The pABR showed some adaptation with increased stimulation rate. A wide range of rates yielded robust responses in under 15 minutes, but 40 Hz was the optimal singular presentation rate. Extending the analysis window to include later components of the response offered further time-saving advantages for the temporally broader responses to low frequency tone pips. The perceptual thresholds to pABR stimuli changed subtly with rate, giving a relatively similar set of correction factors to convert the level of the pABR stimuli from dB peSPL to dB nHL.</p> <p><b>Conclusions: </b>The optimal stimulation rate for the pABR is 40 Hz, but using multiple rates may prove useful. Perceptual thresholds that subtly change across rate allow for a testing paradigm that easily transitions between rates, which may be useful for quickly estimating thresholds for different configurations of hearing loss. These optimized parameters facilitate expediency and effectiveness of the pABR to estimate hearing thresholds in a clinical setting.</p>
Parameter estimation and identifiability analysis for a bivalent analyte model of monoclonal antibody-antigen binding
<p>Data for non-regenerative bivalent analyte binding interaction between CH505 transmitted founder gp120 and CH31 monoclonal antibody, an HIV-1 mAb with CD4-binding site specificity.</p> <p>This data set is submitted as part of the manuscript titled "Parameter estimation and identifiability analysis for a bivalent analyte model of monoclonal antibody-antigen binding"</p>
Estimated parameters for Bayesian Multilevel Models of KM and kcat values
<p>RData (.rds) files containing brmsfit model objects estimated with the brms R package from KM and kcat values reported in BRENDA and SABIO-RK.</p> <p>These models are used by the ENKIE python package to predict kinetic parameter values and uncertainties.</p>
Parameter estimation and species tree rooting using ALE and GeneRax
<p>Some output files associated with the analyses in an article (currently) entitled "Parameter estimation and species tree rooting using ALE and GeneRax"</p> <p>The outputs were obtained by running ALEml_undated either with default (maximum likelihood) estimation of the delta, tau, and lambda parameters, or with delta:tau fixed to a pre-defined ratio. The option to fix delta:tau (or other parameter combinations) was recently added to ALE (https://github.com/ssolo/ALE).</p> <p>The .ale files used as input for these analyses (for the bacterial dataset) are available from the data repository for the original 2021 paper here: https://doi.org/10.6084/m9.figshare.12651074.v12</p> <p> </p>
Estimation of best-fitting force, moment tensor, and depth for the 2022 Hunga-Tonga submarine volcanic eruption: Misfit plots in model parameter space
<p>Supporting documents for the correction of the publication <em>Multi‐Event Explosive Seismic Source for the 2022 Mw 6.3 Hunga Tonga Submarine Volcanic Eruption, </em>published in The Seismic Record (<a href="https://doi.org/10.1785/0320220027">https://doi.org/10.1785/0320220027</a>).</p>
CARLA dataset for monocular depth estimation with varying camera parameters
<p>Dataset contains images and corresponding ground truth depths in CARLA simulator. Dataset has been collected within urban, rural, and highway environments across 8 different maps <em>Town01 - Town07</em> and <em>Town10HD. </em>Each image is created with different camera parameters (camera pitch, camera height and focal length) sampled from uniform distribution.</p>
Data from: An ASC-based unitary matrix pencil method for parameter estimation of group target
<p><span>The unitary matrix pencil (UMP) method has been successfully applied to antenna array optimization. In this work, the UMP method is applied to the parameter estimation of target detection based on the attributed scattering center (ASC) model. This method can accurately estimate the number of arbitrary group targets in the space. Firstly, the radar cross section (RCS) is reconstructed based on the ASC model. Since the unitary matrix can be used to process the parameter estimation of the echo with 'sum of attenuation exponents', the unitary matrix is constructed by the samples from this reconstructed RCS. Moreover, the stronger scattering center can be characterized via the larger singular values, and the number of group targets can be obtained by solving the number of large singular values. Then, singular value decomposition (SVD) is performed on this unitary matrix, and some larger singular values are screened by setting an appropriate threshold. The higher estimation accuracy can be obtained by fusing the echoes from multiple frequencies and angles. Besides, the estimation accuracies of this proposed method in this work are discussed under different signal-to-noise ratios (SNR) considering the noise in the actual scene. Simulation results show that this method can effectively and accurately estimate the number of group targets, and it shows strong robustness. <span>In this data file, the simulation results obtained by commercial software FEKO and MATLAB are listed.</span></span></p>
Data from Preliminary estimates of genetic parameters and familial selection for non-native poplars show good potential for genetic gains on growth, cold hardiness, trunk quality and Sphaerulina musiva susceptibility
<p>Data from Preliminary estimates of genetic parameters and familial selection for non-native poplars show good potential for genetic gains on growth, cold hardiness, trunk quality and <em>Sphaerulina musiva</em> susceptibility</p> <p><br> Abstract<br> Genetic parameters for growth, trunk quality and susceptibility to frost and <em>Sphaerulina musiva</em> attack was estimated from 34 half-sib families of hybrid poplar from the crossing of non-native parents, <em>Populus maximowiczii</em> A. Henry and <em>Populus trichocarpa</em> Torr. & Gray, 3 and 6 years after planting. The use of spatial analysis proved to be the best method for quantitative growth data. The proportion of the among-family variance to the total (phenotypic) variance as well as the high heritabilities of growth and susceptibility to frost and <em>Spaherulina musiva</em> showed a high potential for selection for these traits while the quality traits were under low genetic control. Some families showed gains for several traits, suggesting the possibility of developing a selection index to obtain superior families that show gain for not only growth but quality and adaptive traits as well. Type B correlations were high, suggesting that families responded in the same way regardless of the site. High type A correlation between growth traits at 3 and 6 years showed early selection potential, although these relationships should be confirmed with future measurements to evaluate this effect at maturity. These results can be integrated into the strategy for improving hybrid poplar parental populations and, in the longer term, will make it possible to optimize the selection of individuals with traits of interest for the operational deployment of hybrid poplar clones.</p>
Parameter estimation data release for paper "Waveform systematics in identifying gravitationally lensed gravitational waves: Posterior overlap method"
<p>This is a second data release for the paper "Waveform systematics in identifying gravitationally lensed gravitational waves: Posterior overlap method", which is available on <a href="https://arxiv.org/abs/2306.12908">https://arxiv.org/abs/2306.12908</a>.</p> <p>This data release contains posterior samples and configuration files for parameter estimation runs performed for the paper. For the lensing hypothesis tests results see the other <a href="https://doi.org/10.5281/zenodo.8409635">data release</a> for the same paper.</p> <p>For each event that we have run parameter estimation for, we provide a tar.gz file that includes the configurations, the priors and the results for each run, typically with several different waveforms. All runs were performed with <a href="https://lscsoft.docs.ligo.org/parallel_bilby/">parallel bilby</a> with different versions as described in section 6.1 of the paper. The input data is available from <a href="https://gwosc.org/">GWOSC</a>.</p> <p>The results for IMRPhenom* waveforms (runs with parallel bilby version 1.0.1) are in json format, while for SEOBNRv5PHM and NRSur7dq4 (run with parallel bilby version 2.0.2) some of the results are in hdf5 and others in json, depending on whether multiple runs were merged together. These should be readable with bilby or <a href="https://lscsoft.docs.ligo.org/pesummary/">pesummary</a>.</p> <p>We provide the "complete" configuration files processed by bilby. These can be used for reproducing the runs, but the prior file information needs to be added with a syntax like the following `prior-file=ProdF4.prior`. Generally most runs use the same prior file, with the labels `Prod*.prior`, taken from the LVK analyses. The priors used for the aligned-spin waveforms have the label `_AS`. For the NRSur7dq4 waveform we use a restricted prior with the label `_NR_Sur_constrMtot`. For GW190527 we also use a different prior for IMRPhenomXP and IMRPhenomTPHM, which has the label `_restricted`.</p> <p>Also note that for the result file GW190527_NRSur7dq4_N4096_nact50_fmin0_nparallel3_merged_result.hdf5 this was merged from the results obtained with the config GW190527_NRSur7dq4_N4096_nact50_fmin0_nparallel3_config_complete.ini together with the fourth chain of identical configuration.</p>
Improving estimations of life history parameters of small animals in mesocosm experiments: A case study on mosquitoes
Open the record for dataset details and reuse information.
Optimizing parameters for using the parallel auditory brainstem response (pABR) to quickly estimate hearing thresholds
Open the record for dataset details and reuse information.
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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.