Results 91 to 100 of about 406,470 (199)

Experimental validation of the RESPONSE framework against cyberattacks on cyber‐physical process systems

AIChE Journal, EarlyView.
Abstract This work experimentally validates the RESPONSE (Resilient Process cONtrol SystEm) framework as a solution for maintaining safe, continuous operation of cyber‐physical process systems under cyberattacks. RESPONSE implements a dual‐loop architecture that runs a networked online controller in parallel with a hard‐isolated offline controller ...
Luyang Liu, Pu Du, Zaman Sajid, Benjamin Wilhite, Costas Kravaris, Faisal Khan   +5 more
wiley   +1 more source

Cigarette smoking and SARS-CoV-2 infection: multivariable regression and Mendelian randomization analyses in the Norwegian Mother, Father and Child Cohort Study. [PDF]

BMC Infect Dis
Caspersen IH, Hernáez Á, Peña S, Shaaban AN, Magnus MC, Karvonen S, Galanti MR, Magnus P.   +7 more
europepmc   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

Super-twisting algorithm-based fuzzy sliding mode control for descriptor T-S fuzzy systems. [PDF]

Sci Rep
Li X, Zhang W, Yuan C.
europepmc   +1 more source

A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

Advanced Intelligent Discovery, EarlyView.
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar, Tiago L. P. Galvão, José D. Gouveia, José R. B. Gomes   +3 more
wiley   +1 more source

Correction to "Factors Associated With Depressive Symptoms Among Graduate Students in Science and Technology: A Cross-Sectional Study With Multivariable Analysis". [PDF]

Depress Anxiety
europepmc   +1 more source

Prevalence of HER2-low status and outcomes in early-stage HER2-negative breast cancer. [PDF]

NPJ Breast Cancer
Singareeka Raghavendra A, Liu DD, Pasyar S, Damodaran S, Shen Y, Mouabbi JA, Barcenas CH, Tripathy D.   +7 more
europepmc   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

Value of blended teaching in graduate tobacco medicine training: A prospective intervention study. [PDF]

Tob Induc Dis
Wang H, Zhang J, Xu X, Zhou J.
europepmc   +1 more source

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

Advanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source