Results 141 to 150 of about 260,346 (290)

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
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]

open access: yes
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  

Multi‐Omics Insights Into the Mechanisms of Early Muscle Fiber Difference and Transformation Between Lean‐Type and Chinese Indigenous Pigs

open access: yesAdvanced Science, EarlyView.
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

open access: yesAgriculture
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]

open access: yes
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: A Multi‐Modal and Interpretable Co‐Attention Framework Integrating Property‐Aware Explanations and Memory‐Bank Contrastive Fusion for Blood–Brain Barrier Penetrating Peptide Discovery

open access: yesAdvanced Science, EarlyView.
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

Temporal Interference Stimulation Enhances Neural Regeneration

open access: yesAdvanced Science, EarlyView.
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

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