Results 51 to 60 of about 2,329,699 (248)
Molecular Oncology, EarlyView.This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source
Prediction method of coal calorific value based on quantile regression
Gong-kuang zidonghua, 2022 At present, the traditional linear regression model is mainly used to predict the calorific value of coal. But it is difficult to express the complex relationship between independent variables and dependent variables.
ZHAO Xianzhi, CHEN Junlin
doaj +1 more source
Identifying Risk Factors for Severe Childhood Malnutrition by Boosting Additive Quantile Regression [PDF]
, 2009 Ordinary linear and generalized linear regression models relate the mean of a response variable to a linear combination of covariate effects and, as a consequence, focus on average properties of the response.
Kneib, Thomas +2 more
core +1 more source
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Postbuild annealing systematically modifies the phase fractions and morphology of EB‐PBF processed Mo–9Si–8B. Quantitative microstructure–property correlations reveal how controlled phase evolution enhances high‐temperature compressive strength and creep resistance.
Christopher Schmidt +5 more
wiley +1 more source
Prediction of composite indicators using locally weighted quantile regression
Nonlinear Analysis, 2018 The main goal of this paper is to improve the existing methods and tools used for solving penalized quantile regression problems. We modified the quantile regression method by implementing the extreme learning machine (ELM) algorithm and features of ...
Jurga Rukšenaitė +2 more
doaj +1 more source
Advanced Functional Materials, EarlyView.Lipoprotein‐mimicking nanoparticles (SL‐NPs), comprising Fe3O4@SiO2 cores coated with liposomal bilayers, selectively capture lipoproteins through protein corona formation. The resulting SL‐NP‐lipoprotein complexes can be removed by low‐speed centrifugation, thereby enhancing the purity of small extracellular vesicles (sEVs) isolated from human serum ...
Man‐Di Wang +7 more
wiley +1 more source
Two-step variable selection in quantile regression models
上海师范大学学报. 自然科学版, 2015 We propose a two-step variable selection procedure for high dimensional quantile regressions, in which the dimension of the covariates, pn is much larger than the sample size n.
FAN Yali
doaj +1 more source
Regression on Quantile Residual Life [PDF]
Biometrics, 2009 SummaryA time‐specific log‐linear regression method on quantile residual lifetime is proposed. Under the proposed regression model, any quantile of a time‐to‐event distribution among survivors beyond a certain time point is associated with selected covariates under right censoring.
Jung, Sin-Ho +2 more
openaire +3 more sources
LLM‐Integrated Human–Robot Interaction System for Microrobots
Advanced Robotics Research, EarlyView.This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley +1 more source