The STEM Lab 101
“All models are wrong, but some are useful.” — George E. P. Box
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“All science is nothing more than the refinement of everyday thinking.”
— Albert Einstein​
“Any sufficiently advanced technology is indistinguishable from magic.”
— Arthur C. Clarke
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“Biology today is the science of the 21st century. Engineering it will be the art.”
— Leroy Hood
​Approach​
We create our own insights and models while providing comprehensive meta-analyses to synthesize findings across studies. Our goal is to offer robust, evidence based conclusions that advance understanding and guide future research.
Mission​
Human progress is shaped by scientific exploration. At TheSTEMLab101, we aim to inspire and expand scientific research and knowledge. We focus on applied math, epidemiology, physics, and biochemistry, disciplines fundamental to human advancement. With artificial intelligence dominating global research, these fields risk being overshadowed. Our mission is to reinforce their importance by fostering scientific curiosity, education and inquiry.
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Modified COVID-19 SIR Model
This paper applies the Susceptible Infected Recovered (SIR) model to COVID-19 data in Taiwan. While the standard model explained early outbreaks in other nations, the model only aligned with Taiwan's data after 2022 due to unique delays from strong interventions and changing medical protocols. Using Python, Taiwan's early case data was fitted to a basic SIR curve, which poorly matched observed trends. The SIR was modified to account for government interventions and healthcare changes. The updated model produced a curve that closely fitted Taiwan’s epidemic pattern, offering a more accurate picture of how policy and science shape public health outcomes.
Optimization of PET Hydrolysis Using Response Surface Methodology
Response Surface Methodology (RSM) was used to model and optimize the enzymatic activity of TfCut2, a thermostable cutinase enzyme (Barth et al. 2015). Under varying temperature and pH conditions, nano absorbance at 260 nm (A260), the response variable, was recorded to evaluate catalytic performance during PET film hydrolysis. Using a second-order polynomial model, the effects of the factors temperature and pH were analyzed, and 3D response surfaces were generated using RStudio to visualize the effects caused by the factors. The RSM model predicted an optimal pH of approximately 7.5 and an optimal temperature of 51°C, showing that TfCut2 exhibits maximal catalytic efficiency under moderately basic and moderate heat conditions. This study focuses on the mathematical theory behind RSM, applied to optimizing biocatalytic parameters while minimizing experimental trials.
Mathematical Model:
Lang Lang Analysis
(New Changes Published on 11/6)
Why are ProV1s so Good?
(New Changes Published on 11/6)
Our work is inspired by platforms and educators that make knowledge open and useful. arXiv.org, MIT OpenCourseWare, ScienceOpen, and Wirecutter all show how academic and educational content can be shared clearly and accessibly. We also take inspiration from Organic Chemistry Tutor and 3Blue1Brown, whose ability to break down complex ideas and engage audiences inspires our approach to STEM cultivation and education.
