Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Methods of Medium Optimization01:28

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
Response Surface Methodology01:16

Response Surface Methodology

Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Bioreactor Design and Operational System01:29

Bioreactor Design and Operational System

Bioreactors are engineered vessels designed to cultivate microorganisms under controlled conditions for industrial bioprocessing. They maintain sterility and allow precise regulation of pH, temperature, oxygen, and nutrient levels to optimize microbial growth and metabolite production. Bioreactors range from small laboratory units of 1 liter to industrial systems holding up to 500,000 liters, though only about 75% of their volume is actively used for fermentation. The remaining headspace...
Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Diagnostic performance of an automated plasma p-tau217 chemiluminescent assay for detecting Aβ pathology in a Chinese memory clinic cohort.

The journal of prevention of Alzheimer's disease·2026
Same author

Clinical, neuroimaging, and biomarker profiling of four Alzheimer's disease pedigrees caused by pathogenic APP variants.

Alzheimer's research & therapy·2026
Same author

Efficacy and application potential of purified hydrocolloid coatings sprayed onto maize seeds subjected to anti-aging.

Environmental research·2025
Same author

Distribution characteristics of sulfonamide antibiotics between water and extracellular polymeric substances in municipal sludge.

Environmental research·2024
Same author

Occurrence and mechanism of sulfamethoxazole in alginate-like extracellular polymers from excess sludge.

Bioresource technology·2024
Same author

Concentration properties of biopolymers via dead-end forward osmosis.

International journal of biological macromolecules·2024

Related Experiment Video

Updated: Jun 14, 2026

Optimization of Processing Technology for Tiebangchui with Zanba Based on CRITIC Combined with Box-Behnken Response Surface Method
09:16

Optimization of Processing Technology for Tiebangchui with Zanba Based on CRITIC Combined with Box-Behnken Response Surface Method

Published on: May 12, 2023

[Making optimal operation for a BNR process: modeling prediction and experimental verification].

Xiao-di Hao1, Yuan-sheng Hu, Ke-wei Wan

  • 1The R & D Center for Sustainable Environmental Biotechnology, Beijing University of Civil Engineering and Architecture, Beijing 100044, China. haoxiaodi@bucea.edu.cn

Huan Jing Ke Xue= Huanjing Kexue
|April 3, 2010
PubMed
Summary

Modeling and experiments confirm optimal parameters for Biological Nutrient Removal (BNR) systems, specifically the BCFS process. These findings enable efficient wastewater treatment by identifying key operational settings for improved effluent quality.

More Related Videos

Optimization of the Epimedii Folium Mutton-Oil Processing Technology and Testing Its Effect on Zebrafish Embryonic Development
06:00

Optimization of the Epimedii Folium Mutton-Oil Processing Technology and Testing Its Effect on Zebrafish Embryonic Development

Published on: March 17, 2023

High-Throughput Metabolic Profiling for Model Refinements of Microalgae
11:07

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

Related Experiment Videos

Last Updated: Jun 14, 2026

Optimization of Processing Technology for Tiebangchui with Zanba Based on CRITIC Combined with Box-Behnken Response Surface Method
09:16

Optimization of Processing Technology for Tiebangchui with Zanba Based on CRITIC Combined with Box-Behnken Response Surface Method

Published on: May 12, 2023

Optimization of the Epimedii Folium Mutton-Oil Processing Technology and Testing Its Effect on Zebrafish Embryonic Development
06:00

Optimization of the Epimedii Folium Mutton-Oil Processing Technology and Testing Its Effect on Zebrafish Embryonic Development

Published on: March 17, 2023

High-Throughput Metabolic Profiling for Model Refinements of Microalgae
11:07

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

Area of Science:

  • Wastewater treatment technologies
  • Environmental engineering
  • Biotechnology

Context:

  • Biological Nutrient Removal (BNR) systems are crucial for managing wastewater effluent quality.
  • Optimizing BNR operational parameters is essential for efficient and cost-effective treatment.
  • The BCFS process model provides a framework for predicting system performance.

Purpose:

  • To predict the effects of operational parameters on effluent quality using a BCFS process model.
  • To validate model predictions through lab-scale experiments.
  • To determine optimal operational parameters for BCFS systems.

Summary:

  • Modeling and experimental results showed strong agreement, validating the BCFS process model for optimizing operation.
  • Bio-P removal was independent of biomass in the anaerobic tank at rA ≥ 1.5. rA did not significantly correlate with COD and N removal.
  • TN removal efficiency plateaued above rB = 2. COD and TP removals were unaffected by rB variations. rC had minimal impact on removals. COD and TP removal were stable within DO(R5) of 1-2.5 mg/L, but NH4+-N increased below DO(R5) of 2 mg/L.

Impact:

  • The study provides a reliable modeling approach for optimizing BNR systems at various scales.
  • Identified optimal operational parameters (rA=2, rB=2-2.5, rC=0, DO(R5)=2-2.5 mg/L) for enhanced BCFS performance.
  • Contributes to achieving higher effluent quality and more sustainable wastewater treatment practices.