Results 51 to 60 of about 121,066 (260)
ABSTRACT Wetlands constitute Earth's largest natural methane (CH4) source, yet projections of their climate feedback remain uncertain due to poorly constrained temperature sensitivity (Q10‐CH4) of microbial methanogenesis. While water table dynamics have been demonstrated to regulate wetland methanogenesis by altering key soil conditions such as ...
Shuying Qiu +6 more
wiley +1 more source
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin +12 more
wiley +1 more source
This study establishes a CT‐based radiomics framework to quantify intratumoral heterogeneity (ITH) in HNSCC. Using unsupervised clustering, tumor ROIs and VOIs are analyzed to calculate 2D/3D ITH scores. The score shows strong predictive value for prognosis and immunotherapy response, and is associated with tumor metabolism and immune microenvironment,
Xinwei Chen +15 more
wiley +1 more source
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen +7 more
wiley +1 more source
A New Kibria-Lukman-Type Estimator for Poisson Regression Models
One of the most important models for the analysis of count data is the Poisson Regression Model (PRM). The parameter estimates of the PRM are obtained by the Maximum Likelihood Estimator (MLE).
Cemal Çiçek, Kadri Ulaş Akay
doaj +1 more source
Correlation between independent variables in multiple linear regression model called multicollinearity. One of the assumptions of multiple linear regression free from multicollinearity problem. Principal Component Analysis (PCA) method in this study aims
Fita Mega Kusuma, Arief Wibowo
doaj +1 more source
This study applied AI to quantify multidimensional body composition from CT images in gastric cancer and healthy controls. Distinct sex‐specific patterns and disease‐related alterations were identified and were associated with survival. Higher muscle and fat measures were linked to improved outcomes.
Tianxiang Li +13 more
wiley +1 more source
Genetic divergence of common bean lines for agronomic traits by hierarchical methods considering multicollinearity [PDF]
Genetic divergence for agronomic traits in common bean lines can be analyzed with and without multicollinearity and by different hierarchical methods, which can lead to errors in the interpretation of results obtained from dendrograms.
Nerinéia Dalfollo Ribeiro +5 more
doaj +1 more source
An optimized single‐cell transcriptomic framework profiles over 60 000 cells to map the ovine rumen microbiome, partitioning the ecosystem into seven cross‐species functional clusters. In heat‐resistant hosts, a lineage‐specific metabolic shift in Anaerovibrio lipolyticus toward a highly glycolytic phenotype contributes to a “nutritional sparing ...
Sanbao Zhang +8 more
wiley +1 more source
Caspofungin heteroresistance is prevalent in clinical Candida glabrata isolates and depends on calcineurin‐mediated stress adaptation. This transient phenotype serves as a reservoir for resistance evolution, enabling the emergence of stable resistant descendants under prolonged drug pressure.
Yanyu Su +7 more
wiley +1 more source

