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Machine learning for manually-measured water quality prediction in fish farming.

PloS one
Monitoring variables such as dissolved oxygen, pH, and pond temperature is a key aspect of high-quality fish farming. Machine learning (ML) techniques have been proposed to model the dynamics of such variables to improve the fish farmer's decision-ma...

Prediction of population behavior of Listeria monocytogenes in food using machine learning and a microbial growth and survival database.

Scientific reports
In predictive microbiology, statistical models are employed to predict bacterial population behavior in food using environmental factors such as temperature, pH, and water activity. As the amount and complexity of data increase, handling all data wit...

Exploration of natural red-shifted rhodopsins using a machine learning-based Bayesian experimental design.

Communications biology
Microbial rhodopsins are photoreceptive membrane proteins, which are used as molecular tools in optogenetics. Here, a machine learning (ML)-based experimental design method is introduced for screening rhodopsins that are likely to be red-shifted from...

Artificial neural network modelling for biodecolorization of Basic Violet 03 from aqueous solution by biochar derived from agro-bio waste of groundnut hull: Kinetics and thermodynamics.

Chemosphere
In this study, Levenberg Marquardt back propagation algorithm was used to train the Artificial Neural Network (ANN) and to predict the adsorptive removal of cationic dye Basic Violet 03 (BV03) by biochar derived from biowaste of groundnut hull. The e...

Antibiofilm Activity of α-Amylase from Bacillus subtilis and Prediction of the Optimized Conditions for Biofilm Removal by Response Surface Methodology (RSM) and Artificial Neural Network (ANN).

Applied biochemistry and biotechnology
α-amylase is known to have antibiofilm activity against biofilms of both Gram positive and Gram-negative bacterial strains. Partially purified α-amylase from Bacillus subtilis was found to have inhibit biofilm formed by P. aeruginosa and S. aureus. T...

Application of machine learning methods to pathogen safety evaluation in biological manufacturing processes.

Biotechnology progress
The production of recombinant therapeutic proteins from animal or human cell lines entails the risk of endogenous viral contamination from cell substrates and adventitious agents from raw materials and environment. One of the approaches to control su...

Machine learning algorithms to predict seizure due to acute tramadol poisoning.

Human & experimental toxicology
INTRODUCTION: This study was designed to develop and evaluate machine learning algorithms for predicting seizure due to acute tramadol poisoning, identifying high-risk patients and facilitating appropriate clinical decision-making.

Machine Learning-Assisted Raman Spectroscopy for pH and Lactate Sensing in Body Fluids.

Analytical chemistry
This study presents the combination of Raman spectroscopy with machine learning algorithms as a prospective diagnostic tool capable of detecting and monitoring relevant variations of pH and lactate as recognized biomarkers of several pathologies. The...

Femtosecond laser programmed artificial musculoskeletal systems.

Nature communications
Natural musculoskeletal systems have been widely recognized as an advanced robotic model for designing robust yet flexible microbots. However, the development of artificial musculoskeletal systems at micro-nanoscale currently remains a big challenge,...