Results 181 to 190 of about 36,481,271 (303)

Prediction of hydraulic support pressure in a coal longwall face by integrating multi-head attention and temporal feature learning. [PDF]

Sci Rep
Deng C, Ding Z.
europepmc   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

Advanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song, Xinmin Li, Hongbo Yu, Le Xiong, Guixia Liu, Weihua Li, Yun Tang   +6 more
wiley   +1 more source

A novel fine-scale identification method for coal mining subsidence basin based on TS-InSAR and subsidence curve characteristics. [PDF]

Sci Rep
Huang S, Zhang Y, Yan Y, Guo L, Hu J, Zhang X, Chen R.   +6 more
europepmc   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

Advanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian‐Marco Rignanese, Janine George   +6 more
wiley   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

Deep learning-based intelligent prediction of strata pressure in a steeply inclined fully mechanized longwall face. [PDF]

Sci Rep
Ding Z, Xu N, Su C.
europepmc   +1 more source

Generative and Experimental Validation of High Refractive Index Polymers via Domain Knowledge Approach with Small Data

Advanced Intelligent Discovery, EarlyView.
This research demonstrates that the combination of domain knowledge–based multiple regression, multi‐objective Bayesian optimization, and generative models is a suitable prediction tool for candidates of high refractive index polymers, even with the constraints in the model trained on limited data. The experimental validation can reproduce the proposed
Takuya Yokoo, Seigo Watanabe, Hana Matsunaga, Kenichi Oyaizu   +3 more
wiley   +1 more source

Robots in mine search and rescue operations: a review of platforms and design requirements. [PDF]

Front Robot AI
Bakzadeh R, Androulakis V, Khaniani H, Shao S, Hassanalian M, Roghanchi P.   +5 more
europepmc   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source