Results 51 to 60 of about 2,287,103 (299)
Consistency checks for particle filters [PDF]
, 2006 An "inconsistent" particle filter produces - in a statistical sense - larger estimation errors than predicted by the model on which the filter is based. Two test variables are introduced that allow the detection of inconsistent behavior.
Heijden, F. van der
core +3 more sources
Peptide‐based ligand antagonists block a Vibrio cholerae adhesin
FEBS Letters, EarlyView.The structure of a peptide‐binding domain of the Vibrio cholerae adhesin FrhA was solved by X‐ray crystallography, revealing how the inhibitory peptide AGYTD binds tightly at its Ca2+‐coordinated pocket. Structure‐guided design incorporating D‐amino acids enhanced binding affinity, providing a foundation for developing anti‐adhesion therapeutics ...
Mingyu Wang +9 more
wiley +1 more source
Using lexical variables to predict picture-naming errors in jargon aphasia
Frontiers in Psychology, 2015 Introduction Individuals with jargon aphasia produce fluent output which often comprises high proportions of non-word errors (e.g., maf for dog). Research has been devoted to identifying the underlying mechanisms behind such output.
Catherine Godbold
doaj +1 more source
CO-REGISTRATION OF 3D POINT CLOUDS BY USING AN ERRORS-IN-VARIABLES MODEL [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Co-registration of point clouds of partially scanned objects is the first step of the 3D modeling workflow. The aim of co-registration is to merge the overlapping point clouds by estimating the spatial transformation parameters. In the literature, one of
U. Aydar +3 more
doaj +1 more source
A General Solution for the Errors in Variables (EIV) Model with Equality and Inequality Constraints
Applied Sciences, 2022 Targeting the adjustment of the errors-in-variables (EIV) model with equality and inequality constraints, a general solution that is similar to the classical least square adjustment is proposed based on the penalty function and the weight in measurement.
Dengshan Huang, Yulin Tang, Qisheng Wang
doaj +1 more source
The role of histone modifications in transcription regulation upon DNA damage
FEBS Letters, EarlyView.This review discusses the critical role of histone modifications in regulating gene expression during the DNA damage response (DDR). By modulating chromatin structure and recruiting repair factors, these post‐translational modifications fine‐tune transcriptional programmes to maintain genomic stability.
Angelina Job Kolady, Siyao Wang
wiley +1 more source
Regression quantiles with errors-in-variables [PDF]
, 2003 In a lot of situations, variables are measured with errors. While this problem has been previously studied in the kontext of kernel regression, no work has been done in quantile regression. To estimate this function we use deconvoluting kernel estimators.
Ioannides, D. A., Matzner-Lober, E.
core
Error-in-variables modelling for operator learning.
Proposed for presentation at the MSML22 in ,, 2022 Deep operator learning has emerged as a promising tool for reduced-order modelling and PDE model discovery. Leveraging the expressive power of deep neural networks, especially in high dimensions, such methods learn the mapping between functional state variables. While proposed methods have assumed noise only in the dependent variables, experimental and
Patel, Ravi G. +3 more
openaire +2 more sources
Multiple ETS family transcription factors bind mutant p53 via distinct interaction regions
FEBS Letters, EarlyView.Mutant p53 gain‐of‐function is thought to be mediated by interaction with other transcription factors. We identify multiple ETS transcription factors that can bind mutant p53 and found that this interaction can be promoted by a PXXPP motif. ETS proteins that strongly bound mutant p53 were upregulated in ovarian cancer compared to ETS proteins that ...
Stephanie A. Metcalf +6 more
wiley +1 more source
Self-Consistent Density Estimation in the Presence of Errors-in-Variables
Abstract and Applied Analysis, 2014 This paper considers the estimation of the common probability density of independent and identically distributed variables observed with additive measurement errors.
Junhua Zhang, Yuping Hu, Sanying Feng
doaj +1 more source