AIMC Topic: Hydrogen-Ion Concentration
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Machine learning-based prediction of cadmium pollution in topsoil and identification of critical driving factors in a mining area.
Environmental geochemistry and health
Jul 13, 2024
Mining activities have resulted in a substantial accumulation of cadmium (Cd) in agricultural soils, particularly in southern China. Long-term Cd exposure can cause plant growth inhibition and various diseases. Rapid identification of the extent of s...
AttenGpKa: A Universal Predictor of Solvation Acidity Using Graph Neural Network and Molecular Topology.
Journal of chemical information and modeling
Jul 9, 2024
Rapid and accurate calculation of acid dissociation constant (p) is crucial for designing chemical synthesis routes, optimizing catalysts, and predicting chemical behavior. Despite recent progress in machine learning, predicting solvation acidity, es...
A DNA robotic switch with regulated autonomous display of cytotoxic ligand nanopatterns.
Nature nanotechnology
Jul 1, 2024
The clustering of death receptors (DRs) at the membrane leads to apoptosis. With the goal of treating tumours, multivalent molecular tools that initiate this mechanism have been developed. However, DRs are also ubiquitously expressed in healthy tissu...
Infusion of active compound into sliced button mushrooms through vacuum impregnation to improve functionality: Comparing response surface methodology and artificial neural network.
Journal of food science
Jun 26, 2024
The present study explores the infusion of active compounds (ascorbic acid and calcium lactate) into sliced button mushrooms (Agaricus bisporus) to increase the nutritional value and reduce the browning effect of sliced mushrooms using the vacuum imp...
Application of artificial intelligence in modeling of nitrate removal process using zero-valent iron nanoparticles-loaded carboxymethyl cellulose.
Environmental geochemistry and health
Jun 26, 2024
This study explores nitrate reduction in aqueous solutions using carboxymethyl cellulose loaded with zero-valent iron nanoparticles (Fe-CMC). The structures of this nano-composite were characterized using various techniques. Based on the characteriza...
Comparative studies on modeling and optimization of fermentation process conditions for fungal asparaginase production using artificial intelligence and machine learning techniques.
Preparative biochemistry & biotechnology
Jun 19, 2024
The L-asparaginase is commercial enzyme used as chemotherapeutic agent in cancer treatment and food processing agent in backed and fried food industries. In the present research work, the artificial intelligence and machine learning techniques were e...
The use of artificial neural network for modelling adsorption of Congo red onto activated hazelnut shell.
Environmental monitoring and assessment
Jun 19, 2024
Activated hazelnut shell (HSAC), an organic waste, was utilized for the adsorptive removal of Congo red (CR) dye from aqueous solutions, and a modelling study was conducted using artificial neural networks (ANNs). The structure and characteristic fun...
Artificial neural network modeling for the oxidation kinetics of divalent manganese ions during chlorination and the role of arsenite ions in the binary/ternary systems.
Water research
Jun 3, 2024
This study investigated the coexistence and contamination of manganese (Mn(II)) and arsenite (As(III)) in groundwater and examined their oxidation behavior under different equilibrating parameters, including varying pH, bicarbonate (HCO) concentratio...
Machine-Learning-Assisted Rational Design of Si─Rhodamine as Cathepsin-pH-Activated Probe for Accurate Fluorescence Navigation.
Advanced materials (Deerfield Beach, Fla.)
May 31, 2024
High-performance fluorescent probes stand as indispensable tools in fluorescence-guided imaging, and are crucial for precise delineation of focal tissue while minimizing unnecessary removal of healthy tissue. Herein, machine-learning-assisted strateg...
Machine learning-driven prediction of phosphorus removal performance of metal-modified biochar and optimization of preparation processes considering water quality management objectives.
Bioresource technology
May 18, 2024
Developing an optimized and targeted design approach for metal-modified biochar based on water quality conditions and management is achievable through machine learning. This study leveraged machine learning to analyze experimental data on phosphate a...
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