Graphical Interface

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Videos on Extracting Valuable Parameters from Multiple Experimental Dataset(s):

 

1) Extracting rate constants for the non-competitive inhibition of an enzymatic reaction system utilizing Kintecus.

This is using one dataset with missing data and uneven data spacing or gridding
(please click full screen mode to clearly see video text):

 

2) Kintecus Enzyme MultiData Fit with a Non-competitive Inhibition of An Enzymatic Reaction System

This multidata fit examples shows how to regress or fit several experimental datasets against a chemical model.
In this case, rate constants for the non-competitive inhibition of an enzymatic reaction system.
This is using many datasets with missing data, missing data columns(!!) and uneven data spacing or gridding.
(please click full screen mode to clearly see video text):

 

3) Kintecus Enzyme MultiData Fit with a Non-competitive Inhibition of An Enzymatic Reaction System
WITH different initial conditions.

This multidata fit examples shows how to regress or fit several experimental datasets against a chemical model.
 In this case, rate constants for the non-competitive inhibition of an enzymatic reaction system.
This is using many datasets with missing data, missing data columns(!!) and uneven data spacing or
gridding and with DIFFERENT initial conditions.
(please click full screen mode to clearly see video text)

 

4) Kintecus Enzyme MultiData Fit with a Non-competitive Inhibition of An Enzymatic Reaction System
WITH Equation Constraints
This multidata fit examples shows how to regress or fit several experimental datasets against a chemical model.
In this case, rate constants for the non-competitive inhibition of an enzymatic reaction system.
In this example shows you how to constrain reverse rate constants, kb, against the respective equilibrium constant
 while fitting the forward rate-constants using fit_links. See the model worksheet and the O_fit_links.txt worksheet
(please click full screen mode to clearly see video text):


 

5) Kintecus Combustion Fit MultiData

This multidata fit examples shows how to regress or fit several experimental datasets against a combustion model. In this case, energy of activations (Ea) for a reaction set.
This example utilizes different initial conditions (like temperature, initial concentrations). See the "O_initconditions.txt" worksheet on setting initial conditions for each dataset.


 


 

Here are some screen shots and movies of the Graphical Interface for Kintecus:

*** NEW Plots from KintecusV3.8!! ***

scan_h2_concs.gif (80799 bytes)

scan_h2_temp.gif (65512 bytes)

H2_O2_sensit1_example.gif (36334 bytes)

bootstrapped_rate_constants.gif (26797 bytes)

 

*** NEW Plots from KintecusV3.7!! ***

An extremely important new feature is the capability to calculate model uncertainty
in order to answer questions such as:

What is the maximum dosage the patient can take?
What is the chance that the boiler/CSTR/PFR might explode or have low yield?
Why does the engine knock in real conditions, but does not do so under simulations
that use nominal values?
Why do some atmospheric simulations show high [OH] when experimental data shows
low [OH] concentrations or visa-versa ?

enzymeavg.gif (18534 bytes)

combavgrunHOX.gif (22923 bytes)

combavgtemp.gif (18564 bytes)

 

enzymemaxminzoom1.gif (16519 bytes)


 

Kintecus V3.7 Excel Macros now have the capability
to read the output from the "-o:y:y:y:y" switch:

 

 

Species_flux.gif (59532 bytes)

Reactions_flux.gif (65545 bytes)

Sysout.gif (37614 bytes)

thermout.gif (13590 bytes)

Temp_flux.gif (11884 bytes)

 

enzyme_Species_flux.gif (19278 bytes)

 

fit_plot.gif (24373 bytes)
enyzme_data.gif (29918 bytes)
H2_O2_plot.gif (21235 bytes)
temperat_plot.gif (16802 bytes)

etemp.jpg (295238 bytes)

ctemp.jpg (273372 bytes)

ttemp.jpg (217796 bytes)

 

 

The Kintecus Workbench :

Questions or problems regarding this web site should be directed to jianni10[el atto]gmail.com .
Copyright 2020  James C. Ianni. All rights reserved. Kintecus is a registered trademark.