Results 71 to 80 of about 110,431 (303)

Non-Probabilistic Uncertainty Quantification of Fiber-Reinforced Composite Laminate Based on Micro- and Macro-Mechanical Analysis

Applied Sciences, 2022
In this paper, the main aim is to study and predict macro elastic mechanical parameters of fiber-reinforced composite laminates by combining micro-mechanical analysis models and the non-probabilistic set theory.
Juxi Hu, Lei Wang, Xiaojun Wang
doaj   +1 more source

Finding novel vulnerabilities of hypomorphic BRCA1 alleles

Molecular Oncology, EarlyView.
Synthetic lethality screens performed to identify novel vulnerabilities often model complete gene loss, thereby overlooking patient‐derived hypomorphic mutations. In this study, we have performed genome‐wide CRISPR screens on BRCA1 hypomorphic mutations, showing BRCA1I26A behaves like wild‐type, while BRCA1R1699Q mimics deficiency. Furthermore, we have
Anne Schreuder, Klaas de Lint, Hồ Mỹ Phúc Võ, Mariana M. Góis, Rosalie A. Kampen, Marta San Martin Alonso, Ilse Nootenboom, Veronica Garzero, Tiemen J. Wendel, Rob M. F. Wolthuis, Sylvie M. Noordermeer   +10 more
wiley   +1 more source

Quantification and Evaluation of Parameter and Model Uncertainty for Passive and Active Vibration Isolation

, 2022
S.135-147Vibration isolation is a common method used for minimizing the vibration of dynamic load-bearing structures in a region past the resonance frequency, when excited by disturbances.
Platz, Roland, Lenz, Jonathan
core   +1 more source

A light‐triggered Time‐Resolved X‐ray Solution Scattering (TR‐XSS) workflow with application to protein conformational dynamics

FEBS Open Bio, EarlyView.
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei, Fredrik Orädd, Konstantinos Magkakis, Magnus Andersson   +3 more
wiley   +1 more source

Verification and validation for trustworthy scientific machine learning

Machine Learning: Science and Technology
Scientific machine learning (SciML) models are transforming many scientific disciplines. However, the development of good modeling practices to increase the trustworthiness of SciML has lagged behind its application, limiting its potential impact.
John D Jakeman, Lorena A Barba, Joaquim R R A Martins, Thomas O’Leary-Roseberry   +3 more
doaj   +1 more source

PCE-GPR: A toolbox for high-dimensional uncertainty quantification

This is the first official release of the PCE-GPR Toolbox, a MATLAB and UQLab-based toolbox for uncertainty quantification hybridizing Polynomial Chaos Expansion (PCE) and Gaussian Process Regression (GPR ...
Paolo Manfredi
core   +1 more source

Single‐molecule DNA flow‐stretch assays for high‐throughput DNA–protein interaction studies

FEBS Open Bio, EarlyView.
We describe an optimised single‐molecule DNA flow‐stretch assay that visualises DNA–protein interactions in real time. Linear DNA fragments are tethered to a surface and stretched by buffer flow for fluorescence imaging. Using λ and φX174 DNA, this protocol enhances reproducibility and accessibility, providing a versatile approach for studying diverse ...
Ayush Kumar Ganguli, Mohammad Nour Alsamsam, Ugnė Bagdonaitė, Van Truc Vu, Chun‐Jen Huang, Polina Kuzhir, Mindaugas Zaremba, Aurimas Kopūstas, Marijonas Tutkus   +8 more
wiley   +1 more source

Uncertainty Quantification in Computational Electromagnetics: The stochastic approach [PDF]

, 2013
Models in electromagnetism are more and more accurate. In some applications, the gap between the experience and the model comes from the deviation on input data of the model which are not perfectly known.
CLENET, Stephane
core  

Uncertainty Quantification of Michaelis-Menten Kinetic Rates and Its Application to the Analysis of CRISPR-Based Diagnostics

, 2022
Michaelis-Menten kinetics is an essential model to rationalize enzyme reactions. The quantification of Michaelis-Menten parameters can be very challenging as it is sensitive to even small experimental errors.
Juan G., Santiago, Alexandre S., Avaro
core   +1 more source

Screening and epitope characterization of Nidogen‐2‐specific nanobodies

FEBS Open Bio, EarlyView.
Camel immunization and phage display were employed to generate high‐affinity VHH nanobodies against Nidogen‐2. After library construction, biopanning, ELISA screening, sequencing, and recombinant expression, selected nanobodies were purified and characterized, leading to the preliminary exploration of a nanobody‐based sandwich ELISA for specific ...
Jianchuan Wen, Qianqian Cui, Zhongyun Lan, Yingjun Wang, Shuaiying Zhao, Wenxuan Feng, Yunfeng Liu, Qiting Huang, Dongna Zhang, Jianfeng Xu   +9 more
wiley   +1 more source