Results 181 to 190 of about 741,105 (343)

Electronic Nose for Indoor Mold Detection and Identification

Advanced Sensor Research, EarlyView.
This study explores the potential of a SnO2 nanowire‐based chemiresistive electronic nose not only to detect but also to identify two common indoor mold species, Stachybotrys chartarum and Chaetomium globosum on two different growth substrates. In a laboratory setup, the electronic nose displays high classification performance using optimized linear ...
Hankun Yang, Martin Sommer, Stephanie Bauer, Uli Lemmer   +3 more
wiley   +1 more source

Performance Evaluation of a Proposed Machine Learning Model for Chronic Disease Datasets Using an Integrated Attribute Evaluator and an Improved Decision Tree Classifier [PDF]

, 2020
Sushruta Mishra, Pradeep Kumar Mallick, Hrudaya Kumar Tripathy, Akash Kumar Bhoi, Alfonso González‐Briones   +4 more
openalex   +1 more source

Techno‐Economic Analysis of Polylactic Acid from Corn Stover: Understanding Uncertainty and Variability via Artificial Intelligence Tools

Advanced Sustainable Systems, EarlyView.
This study analyses the uncertainty and variability existing in the economic performance of polylactic acid (PLA) production, via integrating techno‐economic analysis with process models and Monte Carlo simulation enabled by artificial intelligence. The results show that the minimum selling price varies from $2,107 to $3076/t PLA.
Yinqiao Wang, Jiawei Huang, Chuan Xu, Sipan Liu, Junwei Li, Kai Lan   +5 more
wiley   +1 more source

Distill2Explain: Differentiable decision trees for explainable reinforcement learning in energy application controllers [PDF]

Gargya Gokhale, Seyed Soroush Karimi Madahi, Bert Claessens, Chris Develder   +3 more
openalex   +1 more source

Data‐Driven Multi‐Objective Optimization of Large‐Diameter Si Floating‐Zone Crystal Growth

Advanced Theory and Simulations, EarlyView.
This study presents a surrogate‐based Multi‐Objective Optimization framework for Floating Zone silicon crystal growth. An ensemble of Neural Networks is trained on simulation data and combined with Genetic Algorithms to explore trade‐offs in process parameters.
Lucas Vieira, Milena Petković, Robert Menzel, Natasha Dropka   +3 more
wiley   +1 more source

First‐Principles Structure–Activity Relationship Insights Into Phenolic Scaffolds: QSAR Modeling and Drug‐Likeness Screening

Advanced Theory and Simulations, EarlyView.
Integrated machine learning framework for phenolic derivatives: classification (toxicity) and regression (logP) models identify top drug‐like compounds. Random Forest outperformed for toxicity, while Linear Regression best predicted logP. A weighted scoring approach prioritized five safe, lipophilicity‐optimized candidates, supporting rational ...
Houria Nacer, Sridhar Priyankha, Gopal Hema, Anouar Zerouali, Hamza Haddag, Muneerah Mogren Al Mogren, Muthuramalingam Prakash, Majdi Hochlaf   +7 more
wiley   +1 more source

Searches for the BSM scenarios at the LHC using decision tree based machine learning algorithms: A comparative study and review of Random Forest, Adaboost, XGboost and LightGBM frameworks [PDF]

Arghya Choudhury, Arpita Mondal, Subhadeep Sarkar   +2 more
openalex   +1 more source

VDLIN: A Deep Learning‐Based Platform for Methylcobalamin‐Inspired Immunomodulatory Compound Screening

Advanced Science, EarlyView.
Using the convolutional neural network model VDLIN, Co7 is identified as a promising therapeutic candidate. Co7 demonstrates distinct advantages over MCB by effectively balancing anti‐inflammatory and immune‐stimulatory functions, making it a potential novel approach for immune modulation.
Xuefei Guo, Yang Zhao, Xianle Rong, Chenxi Niu, Shiyu Hu, Qiang Liu, Fuping You   +6 more
wiley   +1 more source

Intrusion detection using search-based learning optimized ensemble tree classifier model. [PDF]

PLoS One
Alhassan AM, Altmami NI.
europepmc   +1 more source

Modifying Glucose Metabolism Reverses Memory Defects of Alzheimer's Disease Model at Late Stages

Advanced Science, EarlyView.
Using spatial transcriptomics, we show that ferul enanthate (SL‐ZF‐01) reverses episodic‐like memory deficits in aged, but not young, Alzheimer’s disease (AD) mice. SL restores glucose metabolism and Glucose Transporter 1/3 expression via an ‘Aging‐AD‐Rescue’ pattern, rescuing deficits seen in aged AD mice.
Fang Liu, Yiyu‐Li Tang, Zong‐Bo Zhang, Ya‐Hong Tan, Si‐Hui Lin, Ni‐Ya Wang, Jin‐Nan Li, Zhi‐Jie Pan, Jian‐Feng Li, Jing‐Fei Huang, Yu‐Qiang Ding, Chun‐Ming Guo, Lin Xu, Cheng Peng, Qi‐Xin Zhou   +14 more
wiley   +1 more source