Results 141 to 150 of about 35,702 (279)
Decoding Electroencephalography Signal Response by Stacking Ensemble Learning and Adaptive Differential Evolution. [PDF]
Sensors (Basel), 2023 Ribeiro MHDM +5 more
europepmc +1 more source
Magnetic Field‐Modulated Boolean Logic in Proteinoid‐ Fe3 O4 Hybrid Materials
Advanced Physics Research, EarlyView.Proteinoid‐Fe3O4${\rm Fe}_3{\rm O}_4$. nanoparticle composites exhibit spontaneous electrical oscillations that emulate Boolean logic gates (AND, OR, XOR, NAND, NOR, NOT) under magnetic field modulation. External fields of 65.103 mT tune oscillatory behavior: 84 mT enhances amplitude while 103 mT suppresses it.
Panagiotis Mougkogiannis +1 more
wiley +1 more source
StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens. [PDF]
BMC Bioinformatics, 2023 Charoenkwan P +2 more
europepmc +1 more source
Affinity Peptides With pH Sensitivity for the Enrichment of CD38+ Cells
Biotechnology and Bioengineering, EarlyView.ABSTRACT The selective enrichment of cell populations based on surface markers is critical for the advancement of gene and cell therapies. Current antibody‐based cell isolation methods, such as fluorescence‐ and magnetic‐activated cell sorting (FACS and MACS), offer high specificity but are limited by scalability, cost, and potential adverse effects on
Gabrielle Rusch +7 more
wiley +1 more source
Rumen Fermentation Parameters Prediction Model for Dairy Cows Using a Stacking Ensemble Learning Method. [PDF]
Animals (Basel), 2023 Wang Y +8 more
europepmc +1 more source
Prioritizing Feasible and Impactful Actions to Enable Secure AI Development and Use in Biology
Biotechnology and Bioengineering, EarlyView.ABSTRACT As artificial intelligence continues to enhance biological innovation, the potential for misuse must be addressed to fully unlock the potential societal benefits. While significant work has been done to evaluate general‐purpose AI and specialized biological design tools (BDTs) for biothreat creation risks, actionable steps to mitigate the risk
Josh Dettman +4 more
wiley +1 more source
Battery Energy, Volume 4, Issue 2, March 2025.Optimized ML framework for predicting RP and Dj phases in perovskite solar cells. ABSTRACT Two‐dimensional (2D) lead halide perovskites (LHPs) have captured a range of interest for the advancement of state‐of‐the‐art optoelectronic devices, highly efficient solar cells, next‐generation energy harvesting technologies owing to their hydrophobic nature ...
Basir Akbar, Kil To Chong, Hilal Tayara
wiley +1 more source
Carbon and Hydrogen, EarlyView.A machine‐learning framework integrating multimodel prediction, feature selection, and SHAP interpretability is developed to uncover structure–performance relationships of Cu‐based CO2‐to‐methanol catalysts. The optimized XGBoost model and an online prediction platform enable accurate selectivity prediction and data‐driven catalyst design.
Conglong Su +11 more
wiley +1 more source
Phase‐Pure 2D Interfacial Perovskite Passivation for Stable and Efficient Photovoltaics
Carbon Energy, EarlyView.Phase‐pure 2D interfacial passivation eliminates mixed‐phase energetic disorder, establishes favorable band alignment, and suppresses interfacial non‐radiative recombination. This review elucidates deterministic phase‐purity control, defect and lattice reconstruction mechanisms, and scalable manufacturing strategies, highlighting how phase‐pure 2D/3D ...
Ming‐Xin Li +9 more
wiley +1 more source
The Canadian Journal of Chemical Engineering, EarlyView.Abstract Carbon dioxide‐reduced hydrogen can be synthesized through various methods such as dry‐reforming (DRM), steam reforming (SMR), and partial oxidation (POX). Tri‐reforming of methane (TRM) is a promising technology which combines all the above‐mentioned processes for the simultaneous production of hydrogen and syngas with high energy efficiency.
Paulo A. L. de Souza +3 more
wiley +1 more source