Results 131 to 140 of about 534,560 (282)

A Rational Optimization Approach for the Development of a Multiplexed Lateral Flow Immunoassay: Detection of Nonepithelial Ovarian Cancer Markers in Human Serum

Advanced Science, EarlyView.
This study outlines the developmental pipeline of a multiplexed nanozyme‐based lateral flow immunoassay for the purpose of ovarian germ cell tumor detection. It demonstrates the application of a design of experiments optimization approach for nanozyme probe conjugate development.
Aida Abdelwahed, Carl E. Eskildsen, Luca Panariello, André Shamsabadi, Christy J. Sadler, Edmund H. Wilkes, Federico Galvanin, Yuxi Cheng, Sara Carvalho, Srdjan Saso, Molly M. Stevens   +10 more
wiley   +1 more source

Using Covariance Factor in Genetic Parameter Estimation

Veterinary Sciences and Practices, 2022
Ömer ELTAS, Mehmet TOPAL
doaj   +1 more source

Deciphering the Evolution Pattern of Structural Variations Overlapped With Repetitive Sequence During Cattle Evolution

Advanced Science, EarlyView.
The authors complement bovine pan‐SV with massive novel structural variations (SVs) identified through long‐read sequencing of 83 globally distributed cattle breeds. Repetitive sequence‐mediated SVs (rep‐SV) exhibit distinct dynamic patterns throughout cattle sub‐speciation and/or domestication processes, including uneven distribution between chr‐X and
Zhifan Guo, Jinxiu Li, Adeniyi C. Adeola, Xueyan Jiang, Juntao Ma, Jian Xiao, Dexiang Hu, Kaixing Qu, Haihong Wu, Junren Chen, Zhanxing He, Tingting Yin, Ali Esmailizadeh, Jing Luo, Olivier Hanotte, Ya‐Ping Zhang, Yan Li   +16 more
wiley   +1 more source

Bias-free estimation of the covariance function and the power spectral density from data with missing samples including extended data gaps

EURASIP Journal on Advances in Signal Processing
Nonparametric estimation of the covariance function and the power spectral density of uniformly spaced data from stationary stochastic processes with missing samples is investigated.
Nils Damaschke, Volker Kühn, Holger Nobach   +2 more
doaj   +1 more source

Robust Kalman Filter with Recursive Measurement Noise Covariance Estimation Against Measurement Faults

International Journal of Prognostics and Health Management
A new innovation-based recursive measurement noise covariance estimation method is proposed. The presented algorithm is used for Kalman filter tuning, as a result, the robust Kalman filter (RKF) against measurement malfunctions is derived.
Chingiz Hajiyev
doaj   +1 more source

FDD Channel Estimation via Covariance Estimation in Wideband Massive MIMO Systems. [PDF]

Sensors (Basel), 2020
González-Coma JP, Suárez-Casal P, Castro PM, Castedo L.   +3 more
europepmc   +1 more source

Robustness Analysis Of Covariances Matrix Estimates

, 2010
Publication in the conference proceedings of EUSIPCO, Aalborg, Denmark ...
Mahot, Mélanie, Forster, Philippe, Ovarlez, Jean-Philippe, Pascal, Frédéric   +3 more
openaire   +2 more sources

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

An Introduction to Shrinkage Estimation of the Covariance Matrix: A Pedagogic Illustration

Spreadsheets in Education, 2011
Shrinkage estimation of the covariance matrix of asset returns was introduced to the finance profession several years ago. Since then, the approach has also received considerable attention in various life science studies, as a remedial measure for ...
Clarence C. Y. Kwan
doaj  

A singular spectrum analysis: problems and solutions

St. Petersburg Polytechnical University Journal: Physics and Mathematics
The paper has examined various aspects of the singular spectrum analysis (SSA) method. The original purpose of the method is to optimize harmonic (spectral) analysis of time series.
Pichugin Yury, Pichugina Nika
doaj   +1 more source