Results 81 to 90 of about 78,135 (298)
When Biology Meets Medicine: A Perspective on Foundation Models
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu +3 more
wiley +1 more source
Стимулювання інновацій та підприємництва в розумному виробництві. Аналітична записка. [PDF]
Ця аналітична записка була підготовлена в рамках проєкту SMILE (Інновації, навчальні лабораторії та підприємництво у сфері розумного виробництва) Європейського інституту інновацій і технологій в програмі “Horizon Europe” і призначена для освітніх ...
консорціум SMILE EIT HEI Innovate
core +1 more source
Evaluating smile aesthetic satisfaction and related smile characteristics in dental students
Aim: This study aimed to assess the association between self-rated smile satisfaction and the smile dimensions among dental students. Method: An analytical cross-sectional study was conducted on 216 Vietnamese dental students.
Vy Thi Nhat Nguyen +3 more
doaj +1 more source
Why do we smile? On the determinants of the implied volatility function. [PDF]
We report simple regressions and Granger causality tests in order to understand the pattern of implied volatilities across exercise prices. We employ all calls and puts transacted between 16:00 and 16:45 on the Spanish IBEX-35 index from January 1994 to ...
Rubio, Gonzalo +2 more
core
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary +1 more
wiley +1 more source
Smile analysis following orthognathic surgery
is study compared the different views between orthodontists and oral maxillofacial surgeons, as for smile analysis in patients subjected to orthognathic surgery.
Gabriel Ramalho Ferreira, Leonardo Perez Faverani, Gustavo Augusto Grossi de Oliveira, André Luis da Silva Fabris, Cláudio Maldonado Pastori, Omar Gabriel da Silva Filho
core
Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha +2 more
wiley +1 more source
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
This research demonstrates that the combination of domain knowledge–based multiple regression, multi‐objective Bayesian optimization, and generative models is a suitable prediction tool for candidates of high refractive index polymers, even with the constraints in the model trained on limited data. The experimental validation can reproduce the proposed
Takuya Yokoo +3 more
wiley +1 more source
Quasigroup Representation of Some Feistel and Generalized Feistel Ciphers
There are several block ciphers designed by using Feistel networks or their generalization, and some of them allow to be represented by using quasigroup transformations, for suitably defined quasigroups. We are interested in those Feistel ciphers and
Markovski, Smile, Mileva, Aleksandra
core +2 more sources

