Results 201 to 210 of about 1,209,483 (310)

Monte Carlo and Quasi-Monte Carlo Sampling [PDF]

, 2009
openaire   +1 more source

Cartolina illustrata. Carlo Betocchi a Carlo Bo, 2 novembre 1959

, 1959
Betocchi, Carlo
core  

Flooding‐Driven Greenhouse Gas Emissions From Global Upland Croplands

Advanced Science, EarlyView.
Temporary flooding of upland croplands releases nitrous oxide, carbon dioxide, and methane. Field measurements combined with a global literature synthesis yield a global estimate of 63.3 teragrams of carbon dioxide equivalent per year for diffusive emissions from flooded upland croplands.
Shuilian Bi, Zhifeng Yan, Zhengkui Ge, Si‐Liang Li, Guirui Yu, Cong‐Qiang Liu, Hanqin Tian, Pete Smith   +7 more
wiley   +1 more source

An AI‐Driven Framework for Directed Self‐Assembly Toward Design‐Technology Co‐Optimization

Advanced Science, EarlyView.
An artificial intelligence (AI)‐driven closed‐loop framework integrates experiment, three‐dimensional physics‐based simulation, and template design for directed self‐assembly (DSA). Guided by experimental data, AI‐assisted calibration accelerates model optimization, supports morphology prediction, and identifies template windows.
Caiwei Shang, Yanting Xu, Yue Zhang, Yan Zhang, Jianfeng Li, Ming Li, Longlin Lei, Wenda Bao, Weixuan Zeng, Shisheng Xiong   +9 more
wiley   +1 more source

An Exploratory Randomized Clinical Trial to Assess the Effects of Vitamin D and Leucine-Enriched Whey Protein Supplementation on Inflammaging and Gut Eubacterial Biomass in Cardiac Rehabilitation Patients. [PDF]

Biomolecules
Gheri CF, Luisi MLE, Lucarini L, Biffi B, Madiai S, Roccotelli A, Zipoli R, Sgambellone S, Provensi G, Macchi C, Masini E, Ceccherini MT.   +11 more
europepmc   +1 more source

An Explainable Multimodal Deep‐Learning Model Using Histopathological Image and Clinical Information for Prognosis Prediction in Colorectal Cancer: A Multi‐Center Cohort Study

Advanced Science, EarlyView.
This study develops a multimodal deep‐learning model that integrates clinical variables and histopathological images to predict survival outcomes in colorectal cancer. The multimodal model effectively stratifies patients into low‐ and high‐risk groups, demonstrating superior accuracy and generalizability across multiple independent cohorts.
Zhihan Jiang, Xiangchao Shi, Chenghan Su, Yao Ma, Rui Li, Menglei Chen, Jianxin Cui, Nicholas Hawkins, Robyn Ward, Xiangzhi Bai, Jitendra Jonnagaddala, Wei Fu, Xin Zhou   +12 more
wiley   +1 more source

Faster Hamiltonian Monte Carlo by learning leapfrog scale: an offline randomized solution. [PDF]

Stat Comput
Wu C, Pudlo P, Robert CP, Stoehr J.
europepmc   +1 more source

Biglietto. Giancarlo De Carlo a Carlo Bo, dicembre 2000

, 2000
De Carlo, Giancarlo
core