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
Putnam-Fuglede theorem and the range-kernel orthogonality of derivations
Let ℬ(H) denote the algebra of operators on a Hilbert space H into itself. Let d=δ or Δ, where δAB:ℬ(H)→ℬ(H) is the generalized derivation δAB(S)=AS−SB and ΔAB:ℬ(H)→ℬ(H) is the elementary operator ΔAB(S)=ASB−S. Given A,B,S∈ℬ(H), we say that the pair (A,B)
B. P. Duggal
doaj +1 more source
Hulls and kernels from topological dynamical systems and their applications to homeomorphism $C^{*}$ -algebras [PDF]
Jun Tomiyama
openalex +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
Tensor algebras and displacement structure. IV. Invariant kernels [PDF]
T. Banks+2 more
openalex +1 more source
Approximate‐Guided Representation Learning in Vision Transformer
ABSTRACT In recent years, the transformer model has demonstrated excellent performance in computer vision (CV) applications. The key lies in its guided representation attention mechanism, which uses dot‐product to depict complex feature relationships, and comprehensively understands the context semantics to obtain feature weights.
Kaili Wang+4 more
wiley +1 more source
Model‐Free Local Partial Correlation
ABSTRACT In the simple linear regression context, partial correlation measures the linear association between two variables, with the linear effects of a third control variable removed. In this paper, we investigate the local partial correlation using a kernel smoothing approach.
Li‐Shan Huang+2 more
wiley +1 more source
From farms to tables: Quantifying the effect of emissions pricing on Canadian food prices
Abstract We examine the effect of emissions pricing on the cost of Canadian food. We describe emissions pricing policies relevant to the agriculture and food sectors and the differing design details of various provincial systems and the federal Greenhouse Gas Pollution Pricing Act.
Trevor Tombe, Jennifer Winter
wiley +1 more source
Farmers’ share of the consumer food dollar in Canada: What input‐output data from 1997–2021 show us
Abstract This article uses Canadian input–output data from 1997–2021 to explore the consumer food dollar in terms of its distribution between farmers (i.e., farm share) and post‐farm gate industries. We have adopted the method developed by Canning (2011), which is based on a type one Input‐Output multiplier model.
Solomon Aklilu+4 more
wiley +1 more source
Variance Matrix Priors for Dirichlet Process Mixture Models With Gaussian Kernels
Summary Bayesian mixture modelling is widely used for density estimation and clustering. The Dirichlet process mixture model (DPMM) is the most popular Bayesian non‐parametric mixture modelling approach. In this manuscript, we study the choice of prior for the variance or precision matrix when Gaussian kernels are adopted.
Wei Jing+2 more
wiley +1 more source