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Related Concept Videos

SFG Algebra01:16

SFG Algebra

In Signal Flow Graph (SFG) algebra, the value a node represents is determined by the sum of all signals entering that node. This summed value is then transmitted through every branch leaving the node, making the SFG a powerful tool for visualizing and analyzing control systems.
Each node in an SFG corresponds to a variable, and the interactions between nodes are represented by branches with associated gains. When multiple branches lead into a node, the value at that node is the sum of the...
Gaussian Elimination: Problem Solving01:30

Gaussian Elimination: Problem Solving

Systems of linear equations in several variables are pivotal in modeling complex scenarios involving multiple unknowns and constraints. Such systems are widely used in various fields to represent relationships where several conditions must be simultaneously satisfied. Each variable in the system corresponds to an unknown quantity, while each equation imposes a linear constraint, leading to a structured approach for analyzing and solving real-world problems.A system of three equations with three...
Classification of Systems-I01:26

Classification of Systems-I

Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Signal Flow Graphs01:18

Signal Flow Graphs

Signal-flow graphs offer a streamlined and intuitive approach to representing control systems, providing an alternative to traditional block diagrams. These graphs use branches to symbolize systems and nodes to represent signals, effectively illustrating the relationships and interactions within the system.
In a signal-flow graph, branches denote the system's transfer functions, while nodes represent the signals. The direction of signal flow is indicated by arrows, with the corresponding...
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...
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...

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Related Experiment Videos

Towards future reference systems for GM analysis.

Stefanie Trapmann1, Philippe Corbisier, Heinz Schimmel

  • 1European Commission, Joint Research Centre, Institute for Reference Materials and Measurements (IRMM), Retieseweg 111, 2440 Geel, Belgium. stefanie.trapmann@ec.europa.eu

Analytical and Bioanalytical Chemistry
|December 5, 2009
PubMed
Summary
This summary is machine-generated.

Quantifying genetically modified organisms (GMOs) in food requires a standardized measurement. Copy number ratios offer a reliable reference system for GMO analysis, though further development is needed.

Related Experiment Videos

Area of Science:

  • Food science
  • Analytical chemistry
  • Biotechnology

Background:

  • International trade necessitates reliable quantification of genetically modified organisms (GMOs) in food and feed.
  • A universally agreed-upon measurement unit for GMO quantification is lacking in Europe.
  • Existing reference systems for GMO analysis face challenges in metrological traceability.

Purpose of the Study:

  • To present and discuss two reference systems for GMO quantification: mass fractions and copy number ratios.
  • To evaluate the metrological soundness of copy number ratios for GMO analysis.
  • To identify requirements for establishing a robust metrological system for GMO measurement.

Main Methods:

  • Comparative analysis of two reference systems: mass fractions vs. copy number ratios.
  • Examination of metrological traceability chains for each system.
  • Discussion of the implications for certified reference materials and uncertainty assessment.

Main Results:

  • Copy number ratios, when properly established and expressed, can form a metrologically sound reference system for GMO quantification.
  • This system allows for independent certified reference materials for calibration and quality control.
  • Uncertainty from calibration can be accurately incorporated into the overall GMO measurement uncertainty.

Conclusions:

  • A copy number ratio-based system offers a viable metrological framework for GMO analysis.
  • Further research and standardization efforts are crucial for the full establishment of this metrological system.
  • Standardized GMO measurement is essential for facilitating international trade and ensuring consumer safety.