Results 221 to 230 of about 16,443 (322)
Are we underestimating exposures from NORM dust? [PDF]
Hewson GS, Ralph MI, Cattani M.
europepmc +1 more source
This work introduces a novel framework for identifying non‐small cell lung cancer biomarkers from hundreds of volatile organic compounds in breath, analyzed via gas chromatography‐mass spectrometry. This method integrates generative data augmentation and multi‐view feature selection, providing a stable and accurate solution for biomarker discovery in ...
Guancheng Ren +10 more
wiley +1 more source
Biosorption of thorium onto Chlorella Vulgaris microalgae in aqueous media. [PDF]
Cheng K +5 more
europepmc +1 more source
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source
Editorial for the Special Issue "Preparation and Application of Advanced Functional Membranes". [PDF]
Gugliuzza A, Boi C.
europepmc +1 more source
Crater Observing Bioinspired Rolling Articulator (COBRA)
Crater Observing Bio‐inspired Rolling Articulator (COBRA) is a modular, snake‐inspired robot that addresses the mobility challenges of extraterrestrial exploration sites such as Shackleton Crater. Incorporating snake‐like gaits and tumbling locomotion, COBRA navigates both uneven surfaces and steep crater walls.
Adarsh Salagame +4 more
wiley +1 more source
Preparation of Quaternary Ammonium Separation Material based on Coupling Agent Chloromethyl Trimethoxysilane (KH-150) and Its Adsorption and Separation Properties in Studies of Th(IV). [PDF]
Wang Z +6 more
europepmc +1 more source
This study presents a multitask strategy for plastic cleanup with autonomous surface vehicles, combining exploration and cleaning phases. A two‐headed Deep Q‐Network shared by all agents is traineded via multiobjective reinforcement learning, producing a Pareto front of trade‐offs.
Dame Seck +4 more
wiley +1 more source

