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<a class="navigation__link" href="#20">7 References</a> | <a class="navigation__link" href="#20">7 References</a> | ||
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<div class="page-section hero" id="1"> | <div class="page-section hero" id="1"> | ||
− | <h1>1 Introduction</h1> | + | <h1>1. Introduction</h1> |
<p> | <p> | ||
− | Our goal in the dry lab this year was to create four different models that allow our wet lab team to characterize their results, and allow future researchers to benchmark their results creating standard measures in the field of cellular flotation. First, we created a generic differential bioreactor model that allowed our team to predict the effectiveness of our | + | Our goal in the dry lab this year was to create four different models that allow our wet lab team to characterize their results, and allow future researchers to benchmark their results creating standard measures in the field of cellular flotation. First, we created a generic differential bioreactor model that allowed our team to predict the effectiveness of our <i>E. coli</i> cells to clean waste-waters if coupled with any surface binding method. We performed a complete sensitivity analysis on this model to allow future researchers to reuse this model with completely different parameters, strains of bacteria and object of waste. Then we created an algorithm that can track cellular flotation from frame to frame, and characterize exactly how the cells float; previously, we could only tell whether they floated or not. This coupled with our ODE buoyancy model allows us to define a maximum carrying capacity for each strain. Both of these models allowed our team to benchmark their results and will allow future researchers to quantify the performance of flotation as well. </br></br> |
{Note:} In the very end of this paper, we included a nomenclature defining all the variables used. | {Note:} In the very end of this paper, we included a nomenclature defining all the variables used. | ||
</p> | </p> | ||
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<div class="page-section" id="2"> | <div class="page-section" id="2"> | ||
− | <h1>2 A Differential Bioreactor Model</h1> | + | <h1>2. A Differential Bioreactor Model</h1> |
</div> | </div> | ||
<div class="page-section" id="3"> | <div class="page-section" id="3"> | ||
− | <h1>Goals</h1> | + | <h1>2.1 Goals</h1> |
<p> | <p> | ||
• Explore a possible application for our genetically engineered E. coli biomass that utilizes flota-tion. </br> | • Explore a possible application for our genetically engineered E. coli biomass that utilizes flota-tion. </br> |
Revision as of 21:27, 15 October 2018
1. Introduction
Our goal in the dry lab this year was to create four different models that allow our wet lab team to characterize their results, and allow future researchers to benchmark their results creating standard measures in the field of cellular flotation. First, we created a generic differential bioreactor model that allowed our team to predict the effectiveness of our E. coli cells to clean waste-waters if coupled with any surface binding method. We performed a complete sensitivity analysis on this model to allow future researchers to reuse this model with completely different parameters, strains of bacteria and object of waste. Then we created an algorithm that can track cellular flotation from frame to frame, and characterize exactly how the cells float; previously, we could only tell whether they floated or not. This coupled with our ODE buoyancy model allows us to define a maximum carrying capacity for each strain. Both of these models allowed our team to benchmark their results and will allow future researchers to quantify the performance of flotation as well. {Note:} In the very end of this paper, we included a nomenclature defining all the variables used.
2. A Differential Bioreactor Model
2.1 Goals
• Explore a possible application for our genetically engineered E. coli biomass that utilizes flota-tion. • Develop a generic bioreactor that can be reused in many different conditions and for a varietyof purposes.