Results 141 to 150 of about 133,461 (264)

Sequence-Derived and Molecular Descriptors for Interpretable Modeling of Molecular Systems: Insights from Peptide Hemolysis. [PDF]

J Chem Inf Model
Medvedeva A, Kolomeisky K, Vasnetsov C, Reed A, Bodganova A, Kolomeisky AB.   +5 more
europepmc   +1 more source

Ensemble‐based soil liquefaction assessment: Leveraging CPT data for enhanced predictions

Civil Engineering Design, Volume 7, Issue 1, Page 23-35, March 2025.
Abstract This study focuses on predicting soil liquefaction, a critical phenomenon that can significantly impact the stability and safety of structures during seismic events. Accurate liquefaction assessment is vital for geotechnical engineering, as it informs the design and mitigation strategies needed to safeguard infrastructure and reduce the risk ...
Arsham Moayedi Far, Masoud Zare
wiley   +1 more source

Porous Carbon Materials for Carbon Dioxide Capture

Carbon Energy, EarlyView.
This work aims to address the current status and challenges associated with the regulation of pore structures, as well as the influence of pore structures on CO2 capture. Systematic quantitative analysis of structure–property relationships, combined with machine learning approaches, can effectively evaluate the contributions of structural ...
Zhifu Liu, Chuhan Fu, Tao Qi, Hui Zhou, Guangping Hao, Yalou Guo, Guoping Hu   +6 more
wiley   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Development and validation of a machine learning-based risk prediction model for cancer-related fatigue in ovarian cancer patients. [PDF]

Front Oncol
Feng R, Fan Z, Pang Y, Ding Q, Yue Q, Wei S.   +5 more
europepmc   +1 more source

Artificial intelligence in enzyme catalysis: Emerging trends and applications in biocatalyst engineering

The Canadian Journal of Chemical Engineering, EarlyView.
Schematic representation of artificial intelligence approaches in enzyme catalysis, integrating bibliometric analysis, emerging research trends, and machine learning tools for enzyme design, prediction, and industrial biocatalytic applications. Abstract This study systematically explores the applications of artificial intelligence (AI) in enzyme ...
Misael Bessa Sales, Francisco Izaias da Silva Aires, Paulo Gonçalves de Sousa Junior, Calebe Da Rocha Silva, Emanuel Lino Rodrigues, Maria Cristiane Martins de Souza, José C. S. dos Santos   +6 more
wiley   +1 more source

Explainable Supervised Learning Classification Model Using Diffusion Tensor Imaging Predicts Postoperative Outcomes in Cervical Spondylotic Myelopathy: A Preliminary Study. [PDF]

JOR Spine
Peng Y, Zhang Z, Zhang Z, Shi K, Wang R, Liu Y, Zhang L.   +6 more
europepmc   +1 more source

Extended batch adsorber analogue model (e‐BAAM) for rapid evaluation of CO2 capture pressure swing adsorption cycles

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract This work presents a simplified extended‐batch adsorber analogue model (e‐BAAM) to quantify key performance metrics such as purity, recovery, and energy trends for various pressure swing adsorption (PSA) process cycles for CO2$$ {\mathrm{CO}}_2 $$ capture.
Gwyneth Liske, Arvind Rajendran
wiley   +1 more source

Ocular myopathy

Indian Journal of Ophthalmology, 1979
Surya Rao SVM, Anjaneyulu C, Vengal Rao K   +2 more
doaj  

Hidden in the Pangenome? Machine Learning-Driven Discovery of Antimicrobial Potential in <i>Corynebacterium glutamicum</i>. [PDF]

Bioinform Biol Insights
Islam SI, Shahed K, Parvin MM, Sanjida S.   +3 more
europepmc   +1 more source