Results 211 to 220 of about 527,546 (285)

Psychosocial impact and self-esteem in patients seeking dental aesthetic treatment: a cross-sectional study using PIDAQ and RSES. [PDF]

Front Psychol
Gumus Ayaz S, Kececi G, Kokoz Citaker O.
europepmc   +1 more source

Laser Stabilized to a Fiber Interferometer With Close‐To‐Zero Temperature Sensitivity

Laser &Photonics Reviews, EarlyView.
A laser stabilized to a hollow‐core fibre interferometer is presented. The interferometer is designed to have near‐zero temperature phase‐sensitivity. Laser stabilized to this interferometer put in a non‐vacuum environment achieves ±550 kHz frequency variation over 100 h and an Allan deviation of 2 × 10−14τ, which is comparable to miniature ULE ...
Bo Shi, Irene Barbeito Edreira, Meng Ding, Zitong Feng, Win Indra, Francesco Poletti, Giuseppe Marra, Radan Slavík   +7 more
wiley   +1 more source

Perception of Smile Attractiveness Based on Upper Dental Midline Shift and Gingival Display Among Dental Professionals and General Population: A Questionnaire-Based Study. [PDF]

Cureus
P R H, R N G R, Kondody R, M K A, K R.
europepmc   +1 more source

Benchmarking Large Language Models for Polymer Property Predictions

Macromolecular Rapid Communications, EarlyView.
Large language models (LLMs) are fine‐tuned on polymer thermal property datasets to directly predict glass transition, melting, and decomposition temperatures from SMILES inputs. Compared to state‐of‐the‐art models such as Polymer Genome, polyGNN, and polyBERT, LLMs achieve competitive yet lower accuracy.
Sonakshi Gupta, Akhlak Mahmood, Shivank Shukla, Rampi Ramprasad   +3 more
wiley   +1 more source

Role of High Fidelity Vs. Low Fidelity Experimental Data in Machine Learning Model Performance for Predicting Polymer Solubility

Macromolecular Rapid Communications, EarlyView.
The performance of machine learning models for classifying polymer solubility improves when a high‐fidelity experimental dataset is used compared to a low‐fidelity experimental dataset. This has important implications for justifying the value of spending additional time and resources preparing detailed experimental datasets.
Mona Amrihesari, Manali Banerjee, Raul Olmedo, Blair Brettmann   +3 more
wiley   +1 more source

Analyzing how personality factors influence the perception of smile aesthetics across diverse dental educational backgrounds and lay audiences. [PDF]

Prog Orthod
Al-Bitar Z, Attari N, Abu Arqub S, Al-Omiri M.   +3 more
europepmc   +1 more source

Uncovering Key Characteristics of Antibacterial Peptides through Machine Learning

Macromolecular Rapid Communications, EarlyView.
Machine‐learning (ML) techniques using random forest classification models revealed key characteristics that predict effective antimicrobial peptides (AMPs) targeting Gram‐negative bacteria, Gram‐positive bacteria, and mycobacteria. The ideal cLogP (<$ < $−6) and net‐charge (≤+4) threshold was the same for all three targets with variations in the ...
Jooyoung Roh, Cyrille Boyer, Priyank V. Kumar   +2 more
wiley   +1 more source

High-resolution biomechanical mapping of SMILE and SMILE with CXL using Brillouin microscopy: Insights into localized corneal stiffness preservation. [PDF]

PLoS One
Jeong J, Bae M, Kim DW, Kim HJ, Kim Y.
europepmc   +1 more source

Structure‐Aware Machine Learning for Polymers: A Hierarchical Graph Network for Predicting Properties From Statistical Ensembles

Macromolecular Rapid Communications, EarlyView.
This work presents a structure‐aware graph convolutional network that models polymers as statistical ensembles to predict macroscopic properties. By combining topologically realistic graphs generated via kinetic Monte Carlo simulations with explicit molar mass distributions, the framework achieves high accuracy in classifying architectures and ...
Julian Kimmig, Yannik Köster, Timo Koswig, Punith Raviswamy, Subhash V. S. Ganti, Stefan Zechel, Christopher Kuenneth, Ulrich S. Schubert   +7 more
wiley   +1 more source