Results 181 to 190 of about 659,868 (301)

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Structural Characterizations of MCM-41 Synthesized from Coal Gasification Slag: Effect of Metal Impurities

ACS Omega
Shuo Yao, Wei Du, Changshuai Chen, Yinhai Pan, Weijie Meng, Zhen Zhang, Haijun Zhang, Quanzhi Tian   +7 more
doaj   +1 more source

Genome-guided discovery and computational prioritization of next generation drug development from <i>Streptomyces</i> sp. VITGV156 (MCC 4965). [PDF]

Front Microbiol
Pattapulavar V, Shah M, Bell I PJ, Ramanujam S, Subburaj S, Arumugam S, Muniyan R, Christopher JG.   +7 more
europepmc   +1 more source

Automatic Determination of Quasicrystalline Patterns from Microscopy Images

Advanced Intelligent Discovery, EarlyView.
This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender, Marco Corrias, Cesare Franchini   +2 more
wiley   +1 more source

A robust framework for evaluating green mines towards sustainable development. [PDF]

Sci Rep
Sayed E, Ali AM, Alrashdi I, Sallam KM, Abdel-Basset M, Ismail MM.   +5 more
europepmc   +1 more source

Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces

Advanced Intelligent Discovery, EarlyView.
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali, Lachlan Caulfield, Eric Sauter, Alexei Nefedov, Chengwu Yang, Christof Wöll   +5 more
wiley   +1 more source

Toward microbiome-assisted remediation: Vanadium-titanium magnetite mining reshapes cropland soil chemistry and rhizosphere microbiomes. [PDF]

Crop Health
Liu B, Huang X, Chang C, Wan X, Liu M, Li R, Li J, Li Q, Tao Y.   +8 more
europepmc   +1 more source

Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites

Advanced Intelligent Discovery, EarlyView.
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir, Miguel Hernández‐del‐Valle, Christina Schenk, De‐Yi Wang, Maciej Haranczyk   +4 more
wiley   +1 more source

Emergence of artemisinin-based combination therapy resistance markers in <i>Plasmodium falciparum</i> from the Brazilian tri-border region of the Guiana Shield. [PDF]

Antimicrob Agents Chemother
Salazar YEAR, Rezende AM, Puça MCSB, Louzada J, Mascarenhas MEP, Lagström S, Fletcher D, Oliveira-Ferreira J, Gil JP, de Sousa TN.   +9 more
europepmc   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source