Results 191 to 200 of about 86,959 (305)
Mapping the “Supply–Demand–Flow” of Ecosystem Services for Ecosystem Management in China
This study develops a “supply–demand–flow” framework clarifies how ecosystem services move between regions by distinguishing potential and actual supply and demand. Using integrated biophysical–socioeconomic modeling, nine services in China were mapped.
Yikun Zhang +3 more
wiley +1 more source
RBM10 deficiency promotes anti‐PD‐1 resistance in lung adenocarcinoma by altering STING alternative splicing, which enhances CCL7 secretion and CCR2‐dependent M2 macrophage polarization. A positive feedback loop via mitochondrial transfer sustains this immunosuppression.
Weitong Gao +14 more
wiley +1 more source
Legendre polynomial transformation and energy-weighted random forests for sequential data classification. [PDF]
Olaniran OR +5 more
europepmc +1 more source
Correction: Analysis of epidemiological association patterns of serum thyrotropin by combining random forests and Bayesian networks. [PDF]
Becker AK +9 more
europepmc +1 more source
Streaming Random Forests [PDF]
Hanady M. Abdulsalam +2 more
openaire +1 more source
Bone cancer pain and depression share a common origin: astrocytic A2‐to‐A1 transition in the posterior piriform cortex. This phenotypic shift disrupts the ATP–adenosine–A2AR–norepinephrine axis, simultaneously driving nociceptive and affective dysfunction.
Jiang‐Ping Liu +14 more
wiley +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Utilising random forests in the modelling of Eragrostis curvula presence and absence in an Australian grassland system. [PDF]
Brown J, Merchant A, Ingram L.
europepmc +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source

