AIMC Topic: Hydrogen-Ion Concentration
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AI-enabled alkaline-resistant evolution of protein to apply in mass production.
eLife
Feb 19, 2025
Artificial intelligence (AI) models have been used to study the compositional regularities of proteins in nature, enabling it to assist in protein design to improve the efficiency of protein engineering and reduce manufacturing cost. However, in indu...
Extraction of polysaccharides from Camellia oleifera leaves by dual enzymes combined with deep eutectic solvents screened by ANN and COSMO-RS.
International journal of biological macromolecules
Feb 16, 2025
Camellia oleifera leaves were byproduct of the C. oleifera industry which was rich in polysaccharides. Deep eutectic solvent-dual enzyme system (DES-dEAE) was established to achieve the simultaneous hydrolysis reaction of dual enzymes and DES extract...
UNET-FLIM: A Deep Learning-Based Lifetime Determination Method Facilitating Real-Time Monitoring of Rapid Lysosomal pH Variations in Living Cells.
Analytical chemistry
Feb 4, 2025
Lifetime determination plays a crucial role in fluorescence lifetime imaging microscopy (FLIM). We introduce UNET-FLIM, a deep learning architecture based on a one-dimensional U-net, specifically designed for lifetime determination. UNET-FLIM focuses...
Machine learning integrated with in vitro experiments for study of drug release from PLGA nanoparticles.
Scientific reports
Feb 4, 2025
This paper investigates delivery of encapsulated drug from poly lactic-co-glycolic micro-/nano-particles. Experimental data collected from about 50 papers are analyzed by machine learning algorithms including linear regression, principal component an...
KaMLs for Predicting Protein p Values and Ionization States: Are Trees All You Need?
Journal of chemical theory and computation
Jan 30, 2025
Despite its importance in understanding biology and computer-aided drug discovery, the accurate prediction of protein ionization states remains a formidable challenge. Physics-based approaches struggle to capture the small, competing contributions in...
Optimizing gelation time for cell shape control through active learning.
Soft matter
Jan 29, 2025
Hydrogels are popular platforms for cell encapsulation in biomedicine and tissue engineering due to their soft, porous structures, high water content, and excellent tunability. Recent studies highlight that the timing of network formation can be just...
An exploration of RSM, ANN, and ANFIS models for methylene blue dye adsorption using Oryza sativa straw biomass: a comparative approach.
Scientific reports
Jan 23, 2025
This study focused on simulating the adsorption-based separation of Methylene Blue (MB) dye utilising Oryza sativa straw biomass (OSSB). Three distinct modelling approaches were employed: artificial neural networks (ANN), adaptive neuro-fuzzy inferen...
The application of design of experiments and artificial neural networks in the evaluation of the impact of acidic conditions on cloud point extraction.
Journal of chromatography. A
Jan 17, 2025
This study aimed to analyze the impact of acidic conditions on the recovery of ciprofloxacin and levofloxacin for cloud point extraction with the Design of Experiments and Artificial Neural Networks. The design included 27 experiments featuring three...
Cooking loss estimation of semispinalis capitis muscle of pork butt using a deep neural network on hyperspectral data.
Meat science
Jan 10, 2025
This study evaluated the performance of a deep-learning-based model that predicted cooking loss in the semispinalis capitis (SC) muscle of pork butts using hyperspectral images captured 24 h postmortem. To overcome low-scale samples, 70 pork butts we...
Quantifying the contributions of factors to bioaccessible Cd and Pb in soil using machine learning.
Journal of hazardous materials
Jan 2, 2025
The bioaccessibility of cadmium (Cd) and lead (Pb) in the gastrointestinal tract is crucial for health risk assessments of contaminated soils. However, variability in In vitro analytical conditions and soil properties introduces bias and uncertainty ...
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