AIMC Topic: Bioreactors
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Modelling the removal of volatile pollutants under transient conditions in a two-stage bioreactor using artificial neural networks.
Journal of hazardous materials
Mar 8, 2016
A two-stage biological waste gas treatment system consisting of a first stage biotrickling filter (BTF) and second stage biofilter (BF) was tested for the removal of a gas-phase methanol (M), hydrogen sulphide (HS) and α-pinene (P) mixture. The biore...
Gross parameters prediction of a granular-attached biomass reactor by means of multi-objective genetic-designed artificial neural networks: touristic pressure management case.
Environmental science and pollution research international
Nov 17, 2015
The Artificial Neural Networks by Multi-objective Genetic Algorithms (ANN-MOGA) model has been applied to gross parameters data of a Sequencing Batch Biofilter Granular Reactor (SBBGR) with the aim of providing an effective tool for predicting the fl...
Characteristics of pellets with immobilized activated sludge and its performance in increasing nitrification in sequencing batch reactors at low temperatures.
Journal of environmental sciences (China)
Oct 28, 2015
Immobilized pellets obtained by means of entrapping activated sludge in waterborne polyurethane were successfully adapted in ammonium (NH4(+)-N) synthetic wastewater. Its physicochemical characteristics were determined using scanning electron microsc...
The potential of random forest and neural networks for biomass and recombinant protein modeling in Escherichia coli fed-batch fermentations.
Biotechnology journal
Aug 11, 2015
Product quality assurance strategies in production of biopharmaceuticals currently undergo a transformation from empirical "quality by testing" to rational, knowledge-based "quality by design" approaches. The major challenges in this context are the ...
Artificial neural network associated to UV/Vis spectroscopy for monitoring bioreactions in biopharmaceutical processes.
Bioprocess and biosystems engineering
Jan 1, 2015
Currently, mammalian cells are the most utilized hosts for biopharmaceutical production. The culture media for these cell lines include commonly in their composition a pH indicator. Spectroscopic techniques are used for biopharmaceutical process moni...
Prediction and quantifying parameter importance in simultaneous anaerobic sulfide and nitrate removal process using artificial neural network.
Environmental science and pollution research international
Dec 20, 2014
The present investigation deals with the prediction of the performance of simultaneous anaerobic sulfide and nitrate removal in an upflow anaerobic sludge bed (UASB) reactor through an artificial neural network (ANN). Influent sulfide concentration, ...
Intelligent FA/FNA alternating strategy for nitrite-oxidizing bacteria inhibition: Data-driven prediction and process control.
Journal of environmental management
Jun 1, 2025
Alternating treatment with free ammonia (FA) and free nitrous acid (FNA) is an effective strategy to inhibit nitrite-oxidizing bacteria (NOB) in partial nitrification (PN) process. However, the current alternating treatment relies on manual assessmen...
Machine learning assisted media optimization for enhanced insulin production in Pseudomonas fluorescens cell factory and scale-up studies.
International journal of biological macromolecules
Jun 1, 2025
Diabetes mellitus, a chronic metabolic disorder, is characterized by high blood glucose levels. External insulin administration, along with diet and exercise, is recommended to the patients. The increase in the number of diabetics and the adoption of...
Recognizing the state of aerobic granular sludge over its life-cycle in a continuous-flow membrane bioreactor with an artificial intelligence approach.
Journal of environmental management
Jun 1, 2025
The continuous-flow aerobic granular sludge-membrane bioreactor (AGS-MBR) system represents an efficient and sustainable technology for wastewater treatment. AGS, a spherical or ellipsoidal granular sludge formed through microbial self-aggregation un...
Deep-learning-assisted medium optimization improves hyaluronic acid production by Streptococcus zooepidemicus.
Journal of bioscience and bioengineering
Jun 1, 2025
To improve the efficiency of hyaluronic acid production by Streptococcus zooepidemicus, the growth medium was optimized with a pipeline involving a deep learning (DL) algorithm. To train the DL model, the initial training dataset (OA01-18) was design...
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