Results 191 to 200 of about 1,925,109 (294)
Adsorption Mechanisms and AI‐Driven Discovery of Biomass‐Based CO2 Sorbents
This review analyzes recent advances in biomass‐derived activated carbons for CO2 capture. It highlights the influence of precursors, activation methods, and surface modifications on adsorption performance. The integration of AI‐driven approaches for material optimization is discussed.
Faezeh Hajiali +6 more
wiley +1 more source
Beyond Euclid: an illustrated guide to modern machine learning with geometric, topological, and algebraic structures. [PDF]
Papillon M +10 more
europepmc +1 more source
On the security of short McEliece keys from algebraic andalgebraic geometry codes with automorphisms
Élise Barelli
openalex +1 more source
Morphogenetic Metals through Topology‐Driven Stiffness Changes and Electrochemical Activation
Morphogenesis in metals is achieved through reversible, electrochemically driven topological changes, which switch stainless‐steel lattices between compliant and stiff states (1.1 MPa–2.6 GPa) at room temperature and with minimal energy input. These topological transitions also allow programmable vibration control and auxetic behavior, establishing a ...
Jungtaek Kim +4 more
wiley +1 more source
On Hodge polynomials for nonalgebraic complex manifolds. [PDF]
Katzarkov L +3 more
europepmc +1 more source
Abstract This study examines the time‐dependent behavior of reinforced and prestressed concrete structures using integral‐ and rate‐type formulations, applying the concrete creep and steel relaxation models from the fib Model Code 2020. The stress–strain law for aging concrete is expressed by a second‐order differential equation, but a single rate‐type
Mauro Schulz
wiley +1 more source
Maximum likelihood estimation of log-affine models using detailed-balanced reaction networks. [PDF]
Henriksson O +3 more
europepmc +1 more source
Enhancing generalized spectral clustering with embedding Laplacian graph regularization
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang +5 more
wiley +1 more source
VLWE: Variety-based Learning with Errors for Vector Encryption through Algebraic Geometry [PDF]
Dongfang Zhao
openalex +1 more source
ABSTRACT Digital twin is considered the key technique for real‐time monitoring and life‐cycle management of electric equipment. To construct the digital twin model of electric equipment, a multi‐parameter electromagnetic analysis is needed to generate a large amount of high fidelity data under various working condition.
Ze Guo, Zuqi Tang, Zhuoxiang Ren
wiley +1 more source

