Results 61 to 70 of about 2,329,699 (248)

Empirical likelihood for quantile regression models with response data missing at random

Open Mathematics, 2017
This paper studies quantile linear regression models with response data missing at random. A quantile empirical-likelihood-based method is proposed firstly to study a quantile linear regression model with response data missing at random.
Luo S., Pang Shuxia
doaj   +1 more source

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 more
wiley   +1 more source

VDAC1 Upregulation Induces Hyperexcitability of Nociceptive Sensory Neurons Via Enhanced Mitochondrial Atp Efflux in Neuropathic Pain

Advanced Science, EarlyView.
The mechanism diagram of VDAC1 mediating neuronal excitability and neuropathic pain. Briefly, VDAC1 is expressed in DRG neurons and is upregulated following CCI‐induced neuropathic pain. This upregulation enhances ATP transport from mitochondria to the cytoplasm in sensory neurons, leading to increased neuronal excitability and pain behavior.
Fengrun Sun, Ning Yu, Liang Yu, Xiaofen Tian, Yujia Ma, Yikuan Xie, Tao Wang, Chao Ma   +7 more
wiley   +1 more source

Nonparametric estimation of an additive quantile regression model [PDF]

, 2004
This paper is concerned with estimating the additive components of a nonparametric additive quantile regression model. We develop an estimator that is asymptotically normally distributed with a rate of convergence in probability of n^{-r/(2+10)} when ...
Joel L. Horowitz, Horowitz, J., Lee, S., Horowitz, Joel L., Lee, Sokbae, Sokbae (Simon) Lee   +5 more
core   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source

Simulation Study The Implementation of Quantile Bootstrap Method on Autocorrelated Error

Cauchy: Jurnal Matematika Murni dan Aplikasi, 2018
Quantile regression is a regression method with the approach of separating or dividing data into certain quantiles by minimizing the number of absolute values from asymmetrical errors to overcome unfulfilled assumptions, including the presence of ...
Ovi Delviyanti Saputri, Ferra Yanuar, Dodi Devianto   +2 more
doaj   +1 more source

A New Quantile Regression Model and Its Diagnostic Analytics for a Weibull Distributed Response with Applications

Mathematics, 2021
Standard regression models focus on the mean response based on covariates. Quantile regression describes the quantile for a response conditioned to values of covariates.
Luis Sánchez, Víctor Leiva, Helton Saulo, Carolina Marchant, José M. Sarabia   +4 more
doaj   +1 more source

Censored Quantile Regression Forest

CoRR, 2019
Random forests are powerful non-parametric regression method but are severely limited in their usage in the presence of randomly censored observations, and naively applied can exhibit poor predictive performance due to the incurred biases. Based on a local adaptive representation of random forests, we develop its regression adjustment for randomly ...
Li, Alexander Hanbo, Bradic, Jelena
openaire   +7 more sources

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

Advanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio, Wei Xuan Wilson Loo, Yan Shan Loo, Wen Xin Tan, Hui Xuan Lim, Huitao Liu, Chen Seng Ng   +6 more
wiley   +1 more source