Automatic Clustering and Classification of Coffee Leaf Diseases Based on an Extended Kernel Density Estimation Approach. [PDF]
Hasan RI +3 more
europepmc +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
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 +3 more
wiley +1 more source
Nonstationary Density Estimation and Kernel Autoregression [PDF]
An asymptotic theory is developed for the kernel density estimate of a random walk and the kernel regression estimator of a nonstationary first order autoregression.
Joon Y. Park, Peter C.B. Phillips
core
A spatial obesity risk score for describing the obesogenic environment using kernel density estimation: development and parameter variation. [PDF]
Präger M +4 more
europepmc +1 more source
Multi‐omics analyses uncover breed‐specific cis‐regulatory landscapes and higher‐order chromatin architectural differences that underlie early postnatal muscle fiber divergence in pigs. A super‐enhancer upstream of PPP3CB recruits MEF2C to activate PPP3CB transcription, while the PPP3CB–MEF2C positive feedback loop promotes oxidative muscle fiber ...
Shuailong Zheng +8 more
wiley +1 more source
Enhancing Broiler Weight Prediction via Preprocessed Kernel Density Estimation
Accurate broiler weight estimation in commercial farms is hindered by noisy scale data and multi-broiler occupancy. To address this challenge, we propose a KDE-based framework enhanced with systematic preprocessing, including coefficient of variation (CV)
Sangmin Yoo, Yumi Oh, Juwhan Song
doaj +1 more source
Nonparametric Density Estimation for Linear Processes with Infinite Variance [PDF]
We consider nonparametric estimation of marginal density functions of linear processes by using kernel density estimators. We assume that the innovation processes are i.i.d. and have infinite-variance.
Honda, Toshio
core
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv +11 more
wiley +1 more source
Identification of the associations between genes and quantitative traits using entropy-based kernel density estimation. [PDF]
Yee J, Park T, Park M.
europepmc +1 more source
Temporal Interference Stimulation Enhances Neural Regeneration
Temporal interference (TI) stimulation is proposed as a non‐invasive approach to enhance neural regeneration in the deep brain. Theta‐band TI modulation selectively promotes neural progenitor cell differentiation in vitro and augments hippocampal neurogenesis in amouse model of Alzheimer's disease‐like amyloidosis.
Sofia Peressotti +15 more
wiley +1 more source

