Results 71 to 80 of about 807,314 (352)

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Surface Subsidence Prediction Method for Coal Mines with Ultrathick and Hard Stratum

Advances in Civil Engineering, 2019
Overburden conditions consisting of ultrathick and hard stratum (UTHS) are widespread in China and other countries, but existing surface subsidence prediction methods ignore the strong impact of UTHS on surface subsidence.
Hongkai Han, Jialin Xu, Xiaozhen Wang, Jianlin Xie, Yantuan Xing   +4 more
doaj   +1 more source

Optimization of satellite insar techniques for monitoring of subsidence in the surroundings of Karvina mine: Lazy plant [PDF]

, 2013
This paper deals with issues related to convenient monitoring of subsidence due to longtime mining activities of Czech Karviná Mine: Lazy plant, using satellite SAR interferometry (InSAR) techniques.
Jiránková, Eva, Lazecký, Milan
core   +1 more source

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

Monitoring of surface subsidence disasters and evolution laws caused by multiple mining activities in coal mines based on SBAS-InSAR

Geohazard Mechanics
In underground coal mining, surface subsidence disasters are likely to be induced. Especially, under the condition of multi-seam mining, the movement characteristics of the overlying strata are more complex.
Jianyang Yu, Jiachen Cao, Siqi Gao, Ying Wang, Yihong Liu, Shuai Liu, Lufang Wang, Zhengqing Wang   +7 more
doaj   +1 more source

Accuracy verification and evaluation of small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) for monitoring mining subsidence

European Journal of Remote Sensing, 2021
This study investigated the role of the number of differentialinterferograms and coherent threshold values on the accuracy of SBAS InSAR (small baseline subset interferometric synthetic aperture radar) results for specific applications in Jiyang Coal ...
Qiuxiang Tao, Fengyun Wang, Zaijie Guo, Leyin Hu, Chen Yang, Tongwen Liu   +5 more
semanticscholar   +1 more source

Analyzing kinetics of deformation of boundary rocks of mine workings [PDF]

, 2018
Purpose is to analyze nature of rock deformation and to estimate experimentally state of mine workings being supported under the conditions of areas disturbed by coal mining. Methods. The studies involved field instrumental observations within measuring
Nehrii, S, Nehrii, T, Sakhno, I, Sakhno, S   +3 more
core   +1 more source

Harnessing Phase Dynamics Across Diverse Frequencies with Multifrequency Oscillatory Neural Networks

Advanced Intelligent Discovery, EarlyView.
Oscillatory Neural Networks (ONNs) are an emerging computing paradigm that encodes information in the phases of coupled oscillators. Traditionally, ONNs have been investigated using homogeneous frequency oscillators. However, physical hardware implementations are inherently subject to frequency mismatches, device variability, and nonuniformities.
Nil Dinç, Filip Sabo, Aida Todri‐Sanial   +2 more
wiley   +1 more source

Introduction for the Special Issue on Beyond the Hypes of Geospatial Big Data: Theories, Methods, Analytics, and Applications [PDF]

, 2019
We live in the era of ‘Big Data’. In particular, Geospatial data, whether captured through remote sensors (e.g., satellite imagery) or generated from large-scale simulations (e.g., climate change models) have always been significantly large in size. Over
Kealy, Allison, Wang, Qianxing, Zhai, Shengjie   +2 more
core   +2 more sources

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source