Results 181 to 190 of about 88,237 (314)
Observing the in-situ formation of the lead-free piezoceramic potassium sodium niobate (KNN) with SAED [PDF]
Rambaran Mark +3 more
doaj +1 more source
This research proposes an interpretable hybrid stacking ensemble framework, optimized by the Sparrow Search Algorithm, to enhance hard rock pillar stability prediction. By integrating six machine learning models—k‐nearest neighbors, support vector machines, random forests, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, and Light Gradient ...
Ning Wang +3 more
wiley +1 more source
Piezo-herbal microneedle patches enable wireless endometrial regeneration and fertility recovery. [PDF]
Zhao R, Ni S, Yang M, Gu Z, Zhu Y.
europepmc +1 more source
This work systematically reviews the key factors influencing the performance of low‐temperature NH3‐SCR. The mechanism and challenges of defect engineering strategies, such as oxygen vacancies, heteroatom doping, crystal facet exposure, and surface reconstruction, in controlling both activity and selectivity were analyzed.
Rongrong Kan +3 more
wiley +1 more source
Machine learning and mathematical modeling for comparative analysis of green-synthesized ZnO nanoparticles as seed nano-priming agents for linseed. [PDF]
Şavşatlı Y +4 more
europepmc +1 more source
Physics‐driven advances in optical nanobiosensors for rapid, miniaturized, and point‐of‐care diagnostics for next‐generation decentralized and personalized healthcare based on sensor intelligence. ABSTRACT Public health emergencies and the escalating burden of chronic diseases necessitate a paradigm shift from centralized laboratory testing to rapid ...
Vishal Chaudhary +5 more
wiley +1 more source
Identifying factors and predicting mental health issues in polypharmacy elderly using machine learning: a study based on the English longitudinal study of aging. [PDF]
Wang H +9 more
europepmc +1 more source
This study aims to introduce a novel‐designed structure of the colloidal aphron microbubbles reinforced by incorporating hydrophobic aerographene microparticles onto the hydrophobic outer shell. This results in the formation of a robust composite film and armored microbubble that offers exceptional ultrastability under elevated pressures of up to 400 ...
Mohammad Hossein Akhlaghi +4 more
wiley +1 more source
Development and internal validation of an interpretable machine-learning model for identifying comorbid atrial fibrillation in patients with diabetic kidney disease. [PDF]
Li X, Wang X, Wang S, Zhang X.
europepmc +1 more source
Abstract Objective Febrile seizures (FS) are the most common seizures in childhood, yet identifying children at risk of developing epilepsy after the first FS remains challenging. We aimed to evaluate the prognostic potential of machine learning (ML) algorithms applied to post‐febrile seizure electroencephalography (EEG) recordings.
Boran Şekeroğlu +7 more
wiley +1 more source

