Thermodynamics Overview 

4:04-4:10 - zeroth law (not 'zero') 7:30-7:35 - the narrator misspoke "maximum" for "minimum"

I love what y'all are doing here! I have spoken as biological organisms as far-from-equilibrium systems with all the implications of dissipative systems (scaling, emergence, etc.) since I joined my PhD program. Needless to say, in a biological program, one still gets blank stares. Biologists still think with very reductionist points of view. This really is going to make it tough to transition to a more holistic view of biological systems in the future. I think what we need more than anything at this point are tools for understanding disease or other organismal processes by analyzing many different sources of data and integrating them together to form a more holistic picture. I'm essentially arguing for a marriage of a systems approach and an analytical approach. The major problem is that the tools we have in systems theory are far from adequate to model organisms with 2 billion nucleotides, 25000 protein-coding genes, and insanely complex interactions involved at all stages of the process (i.e. transcriptional and translational regulation and post-translational modifications). Modeling 10 covariates in a nonlinear system is difficult enough for numerical methods for solving ODEs and PDEs, but potentially millions of covariates? So being able to use data generated on genome, proteome, transcriptome, etc. scales, can help us to leverage our scientific abilities with our abilities to simplify systems into more interpretable results. As an example of this, we talk about ordered systems as ones that are less entropic. This being the case, even if they have a high number of important parameters, it should follow that less information is needed to represent the system. These are ideas used in information theoretical approaches to data compressing algorithms. What I'm getting at is the following. Is it possible that these highly complex systems can be collapsed to a much lower dimension of crucial/key features? And I'm not talking about an approach as simple as analyzing a genome, as that hasn't seemed to work all that well in understanding disease as of yet. The key features don't necessarily have to be 1 gene, 1 protein, or something so trivial. They could instead be a higher-order feature such as network topology, pathway perturbation, or other information that can be mined from data from multiple heterogeneous sources of data for your problem. And don't get me wrong, there are definitely people working on problems from this perspective. But I think what is mostly missing is a formalism that generalizes how highly complex systems can be represented in a more compact way that gives us both a more holistic picture and a way to understand them that can directly lead to clinical manifestations, I.e. a small molecule to target a process that seems to be awry, or a gene/set of genes/ etc. to edit to cure a person of a disease. Sorry for the long windedness, but I am definitely passionate about both systems theory and biology/bioinformatics. I just know that the most valuable thing for the future of biological understanding would be a way to bridge the gap between theory and generated data. Any insights would be very welcome!

"approximately 25% of the energy input will be destroyed in the process" I know what you meant by this, but perhaps for any lay-reader a correction of this can be posted on the video. Because as we know, energy can neither be created nor destroyed, but only converted, and in this case, lost to the atmosphere instead of harnessed in a form that can be used for human consumption.

So dissipative systems exist, let us say, in the staircase in the famous M.C. Escher's artwork, where the top of a building has ever-looping staircases. Right? Thanks for the videos. Hopefully I can make sense out of my terrible teachers with the support of your explanations :) PD: then, if I get this right, if (essentially) energy, entropy and temperature could be abstracted away from classical physical science and brought into a context of system dynamics, we could apply the theory of non-equilibrium ThDyn. to, say, a country's economy? Is that accurate? Thank you again for your videos!!

Обсуждение представленного материала следует после прочтения www.researchgate.net/publication/314187646_On_General_Physical_Principles_of_Biological_Evolution и просмотра ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-CYr1G5TZO50.html

Bro, you misspelled "systems."

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