Results 251 to 260 of about 2,440,522 (332)

Risks and Benefits of Feeding Enterostomy Creation During Minimally Invasive Esophagectomy: A Propensity‐Weighted Analysis Using the Japanese National Clinical Database

Annals of Gastroenterological Surgery, EarlyView.
Feeding enterostomy during MIE was evaluated in 19 054 patients from the Japanese NCD using propensity weighting. Enterostomy was associated with higher reoperation and respiratory complications, but lower delayed gastric emptying and deep vein thrombosis, with no significant difference in overall bowel obstruction.
Eisuke Booka, Shinya Hirakawa, Hisateru Tachimori, Koji Tanaka, Hideki Ueno, Yasue Kimura, Ken Shirabe, Hiroya Takeuchi   +7 more
wiley   +1 more source

Generation of NADPH and the formation of lipofuscin fluorophore precursors in human rod photoreceptors. [PDF]

J Biol Chem
Adler L, Chen C, Boyer NP, Koutalos Y.
europepmc   +1 more source

Dokument 366-380 [PDF]

, 2013
openaire   +1 more source

Real‐time fault detection in multicomponent nuclear‐waste slurries through data fusion of spectroscopic sensors

AIChE Journal, EarlyView.
Abstract Three instruments–Raman spectroscopy, attenuated total reflectance–Fourier transform infrared spectroscopy, and focused beam reflectance measurement–were used to detect sensor faults, mixing faults, and unanticipated chemistry in a system of multicomponent slurries.
Steven H. Crouse, Ronald W. Rousseau, Martha A. Grover   +2 more
wiley   +1 more source

Microstructure-Dependent Creep Mechanisms in Heat-Treated CZ1 Zr Alloy at 380 °C. [PDF]

Nanomaterials (Basel)
Shi H, Wang J, Chen M, Liu P, Xia Z, Lu C, Gao R, Li W, Zhang Y, Su Z, Hu J.   +10 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Predicted T-Cell and B-Cell Epitopes of NIS: Where Do Sjögren's Syndrome and Hashimoto's Thyroiditis Converge? [PDF]

Int J Mol Sci
Talotta R, Cammaroto G, Ruggeri RM, Postorino E, Cannavò S, Aragona P.   +5 more
europepmc   +1 more source

Interpretable Machine Learning for Solvent‐Dependent Carrier Mobility in Solution‐Processed Organic Thin Films

Advanced Intelligent Discovery, EarlyView.
This work establishes a correlation between solvent properties and the charge transport performance of solution‐processed organic thin films through interpretable machine learning. Strong dispersion interactions (δD), moderate hydrogen bonding (δH), closely matching and compatible with the solute (quadruple thiophene), and a small molar volume (MolVol)
Tianhao Tan, Lian Duan, Dong Wang
wiley   +1 more source

Evaluating adherence to COVID-19 quarantine protocols at two international ground crossings in Savannakhet Province, Lao PDR. [PDF]

Trop Med Health
Xaylovong K, Adjei-Gyamfi S, Pongvongsa T, Moji K, Aiga H.   +4 more
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source