Results 111 to 120 of about 1,355,935 (279)

Systematic Deciphering of ATBC Nephrotoxicity Mechanisms via Machine Learning and Single‐Cell Analysis

Medicine Bulletin, EarlyView.
This study elucidates the nephrotoxic mechanism of acetyl tributyl citrate (ATBC) by integrating network toxicology, machine learning, and single‑cell multi‑omics analysis to systematically decipher the molecular mechanisms and cell‑type‑specific regulatory networks underlying ATBC‑induced kidney injury. First, a protein‑protein interaction network was
Yimao Wu, Yalun Liang, Jintao Liang, Wenlong Sun, Qian Zhang, Meng‐Yao Li   +5 more
wiley   +1 more source

Neural networks and support vector machines based bio-activity classification [PDF]

, 2006
Classification of various compounds into their respective biological activity classes is important in drug discovery applications from an early phase virtual compound filtering and screening point of view. In this work two types of neural networks, multi
Salim, Naomie, Zeb Shah, Jehan
core  

Prediction of the Mechanical Properties of the Additive Friction Stir‐Deposited Al2219 Using Machine Learning

Materials Genome Engineering Advances, EarlyView.
In this work, three prediction machine learning (ML) models (MLP, RBF, BP) are developed to predict the ultimate tensile strength (UTS) and elongation (EL) of the AFSDed Al2219 samples. ABSTRACT Additive friction stir deposition (AFSD) is an effective method for fabricating high‐performance deposits, with process parameters directly influencing the ...
Chan Wa Tam, Qian Qiao, Xiaowei Chen, Wai I Lam, Xiumei Gong, Yongyong Lin, Hongchang Qian, Dawei Guo, Dawei Zhang, Chi Tat Kwok, Lap Mou Tam   +10 more
wiley   +1 more source

A system for monitoring NO2 emissions from biomass burning by using GOME and ATSR-2 data [PDF]

, 2002
In this paper, we propose a system for monitoring abnormal NO2 emissions in troposphere by using remote-sensing sensors. In particular, the system aims at estimating the amount of NO2 resulting from biomass burning by exploiting the synergies between the
Bruzzone, Lorenzo, Casadio, S., Cossu, Roberto, Sini, Francesco, Zehner, Claus   +4 more
core  

Ellipsoid‐Based Interval‐Type Uncertainty Model Updating Based on Riemannian Manifold and Gaussian Process Model

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Modern engineering systems require advanced uncertainty‐aware model updating methods that address parameter correlations beyond conventional interval analysis. This paper proposes a novel framework integrating Riemannian manifold theory with Gaussian Process Regression (GPR) for systems governed by Symmetric Positive‐Definite (SPD) matrix ...
Yanhe Tao, Qintao Guo, Jin Zhou, Cheng Yi   +3 more
wiley   +1 more source

A neuro-fuzzy approach as medical diagnostic interface [PDF]

, 2010
In contrast to the symbolic approach, neural networks seldom are designed to explain what they have learned. This is a major obstacle for its use in everyday life.
Brause, Rüdiger W., Friedrich, F.
core  

Experimental Modal Analysis‐Driven Gaussian Process Regression Modeling of Rectangular Steel Beams With Various Hole Geometries

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Understanding the dynamic behavior of structural components is crucial for optimizing performance and ensuring structural integrity. This study presents a new method that combines a systematic experimental investigation of four distinct hole geometries (circular, square, compact rectangular, and long rectangular) with varying hole counts, all ...
Amir Hossein Rabiee, Majid Rajaei, Mohammad Hossein Mahdavi Nasab, Parsa Shafiei   +3 more
wiley   +1 more source

Research on price forecasting method of China's carbon trading market based on PSO-RBF algorithm

Systems Science & Control Engineering, 2019
The forecasting of carbon emissions trading market price is the basis for improving risk management in the carbon trading market and strengthening the enthusiasm of market participants. This paper will apply machine learning methods to forecast the price
Yuansheng Huang, Jianjun Hu, Hui Liu, Shijian Liu   +3 more
doaj   +1 more source

Using Support Vector Machine for Prediction Dynamic Voltage Collapse in an Actual Power System [PDF]

, 2008
—This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines. Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation
Hussain, Aini, Mohamed , Azah, Nizam , Muhammad   +2 more
core  

Using deep learning to assess the toxicological effects of sublethal exposure of a novel green pesticide in a stored‐product beetle

Pest Management Science, EarlyView.
This study employs an AI‐driven multidisciplinary approach to increase our understanding of the toxicological effects of sublethal concentrations of carlina oxide on Prostephanus truncatus. Sublethal exposure to the carlina oxide induced changes in motor patterns and thigmotaxis, highlighting its potential role in integrated pest management strategies.
Anita Casadei, Maria C. Boukouvala, Gianluca Manduca, Nickolas G. Kavallieratos, Filippo Maggi, Marta Ferrati, Eleonora Spinozzi, Cesare Stefanini, Antonio DeSimone, Donato Romano   +9 more
wiley   +1 more source