Toy model of matter that exhibits phase transition in dimension 2 and greater. It does not provide numerically exact results by itself, but can serve as a tool to theorize existing and new phase transitions.
As mentioned at: stanford.edu/~jeffjar/statmech/intro4.html some systems which can be seen as modelled by it include:
- the spins direction (up or down) of atoms in a magnet, which can undergo phase transitions depending on temperature as that characterized by the Curie temperature and an externally applied magnetic fieldNeighboring spins like to align, which lowers the total system energy.
- the type of atom at a lattice point in a 2-metal alloy, e.g. Fe-C (e.g. steel). TODO: intuition for the neighbor interaction? What likes to be with what? And aren't different phases in different crystal structures?
Also has some funky relations to renormalization TODO.
Bibliography:
The Ising Model in Python by Mr. P Solver
. Source. The dude is crushing it on a Jupyter Notebook.The hard part then is how to make any predictions from it:
- 2024 www.nature.com/articles/d41586-024-02935-z Fly-brain connectome helps to make predictions about neural activity. Summary of "Connectome-constrained networks predict neural activity across the fly visual system" by J. K. Lappalainen et. al.
2024: www.nature.com/articles/d41586-024-03190-y Largest brain map ever reveals fruit fly's neurons in exquisite detail
As of 2022, it had been almost fully decoded by post mortem connectome extraction with microtome!!! 135k neurons.
- 2021 www.nytimes.com/2021/10/26/science/drosophila-fly-brain-connectome.html Why Scientists Have Spent Years Mapping This Creature’s Brain by New York Times
That article mentions the humongous paper elifesciences.org/articles/66039 elifesciences.org/articles/66039 "A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection" by a group from Janelia Research Campus. THe paper is so large that it makes eLife hang.
Subtle is the Lord by Abraham Pais (1982) page 85:so it is quite cool to see that organic chemistry is one of the things that pushed atomic theory forward. Because when you start to observe that isomers has different characteristics, despite identical proportions of atoms, this is really hard to explain without talking about the relative positions of the atoms within molecules!
However, it became increasingly difficult in chemical circles to deny the reality of molecules after 1874, the year in which Jacobus Henricus van't Hoff and Joseph Achille Le Bel independently explained the isomerism of certain organic substances in terms of stereochemical properties of carbon compounds.
Ciro Santilli supports full legalization of all drugs, because he feels that it would be better overall for the world to have cheaper drugs and more drug addicts, but way, way less organized crime.
These should be extremely controlled of course, with extremely high taxes that puts their price just below the current illegal market, and a complete ban on any positive advertising.
Ciro believes that maybe the government could even go as far as giving free drugs to drug addicts so they don't have to rob to get a fix.
This is notably considering that drug-led organized crime completely dominates and corrupts the politics of many production and trafficking zones, which are already generally poor fucked up places to start with:Ciro's experiences in Brazil such as mentioned at São Remo, the favela next to USP, although much less extreme than the above, also come to mind.
Drug traffic corrupts everything. It prevents development of honest people. It is a cancer, which we have failed time and time a gain to cure. The only cure is to accept the other less insidious of addiction.
Bibliography:
- How to Fix a Drug Scandal (2020) gives a good sense of the relentlessness of the drug war, and how it affects people who are already poor the most
In the context of tensors , we use raised indices to refer to members of the dual basis vs the underlying basis:The dual basis vectors are defined to "pick the corresponding coordinate" out of elements of V. E.g.:By expanding into the basis, we can put this more succinctly with the Kronecker delta as:
Note that in Einstein notation, the components of a dual vector have lower indices. This works well with the upper case indices of the dual vectors, allowing us to write a dual vector as:
This is the one where French Nobel Prizes come from: en.wikipedia.org/wiki/List_of_École_normale_supérieure_people#Nobel_laureates
The conventional starting point is not at the E. Coli K-12 MG1655 origin of replication.
biocyc.org/ECOLI/NEW-IMAGE?type=EXTRAGENIC-SITE&object=G0-10506 explains:If it is a bit hard to understand what they mean by "origin of transfer" though, as that term is usually associated with the origin of transfer of bacterial conjugation.
This site is the origin of replication of the E. coli chromosome. It contains the binding sites for DnaA, which is critical for initiation of replication. Replication proceeds bidirectionally. For historical reasons, the numbering of E. coli's circular chromosome does not start at the origin of replication, but at the origin of transfer during conjugation.
In the 2010's/2020's, many people got excited about getting children in to electronics with cheap devboards, notably with Raspberry Pi and Arduino.
While there is some potential in that, Ciro Santilli always felt that this is very difficult to do, while also keeping his sacred principle of backward design in mind.
The reason for this is that "everyone" already has much more powerful computers at hand: their laptops/desktops and even mobile phones as of the 2020s. Except perhaps if you are thing specifically about poor countries.
Therefore, the advantage using such devboards for doing something that could useful must come from either:
- their low cost. This would be an important consideration if you were to mass produce your product, but that is not going to be the case for learners, at least initially.
- their portability, and closely linked their ability to act as sensors
- their ability to act as actuators, which is often missing from regular computers
- them having hardware accelerators that are not normally present in regular computers, e.g. FPGAs or AI accelerators. And then the demo project must demonstrate that the project is able to do something significantly faster/cheaper on the devboard than on a desktop computer.
And most important of all: you should not start learning phenomena by reading the from first principles derivation.
Instead, you should see what happens in experiments, and how matches some known formula (which hopefully has been derived from first principles).
Only open the boxes (understand from first principles derivation) if the need is felt!
E.g.:
- you don't need to understand everything about why SQUID devices have their specific I-V curve curve. You have to first of all learn what the I-V curve would be in an experiment!
- you don't need to understand the fine details of how cavity magnetrons work. What you need to understand first is what kind of microwave you get from what kind of input (DC current), and how that compares to other sources of microwaves
- lasers: same
Physics is all about predicting the future. If you can predict the future with an end result, that's already predicting the future, and valid.
This is a pre-requisite of Section "Students must have a flexible choice of what to learn".
If the choice of what to learn depend on a years long dependency graph of other obligations, which currently are the increasingly interlinked:you end up without much choice at all.
- passing the University entry exam
- getting your undergrad degree
- getting your PhD
The lock-in periods must be much more fluid and shorter term than those, otherwise it makes the almost inevitable pivots to success impossible.
This is something that Ciro Santilli has heard from several people at the end of their undergrad/PhD degrees. Some online mentions:
NCBI taxonomy entry: www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=511145 This links to:
- Interactively browse the sequence on the browser viewer: "Reference genome: Escherichia coli str. K-12 substr. MG1655" which eventually leads to: www.ncbi.nlm.nih.gov/nuccore/556503834?report=graphIf we zoom into the start, we hover over the very first gene/protein: the famous (just kidding) e. Coli K-12 MG1655 gene thrL, at position 190-255.The second one is the much more interesting e. Coli K-12 MG1655 gene thrA.
- Gene list, with a total of 4,629 as of 2021: www.ncbi.nlm.nih.gov/gene/?term=txid511145
20 minutes in optimal conditions, with a crazy multiple start sites mechanism: E. Coli starts DNA replication before the previous one finished.
Otherwise, naively, would take 60-90 minutes just to replicate and segregate the full DNA otherwise. So it starts copying multiple times.
- biology.stackexchange.com/questions/30080/how-can-e-coli-proliferate-so-rapidly
- stochasticscientist.blogspot.co.uk/2012/02/how-e-coli-grows-so-fast.html
- www.ncbi.nlm.nih.gov/pmc/articles/PMC2063475/ Organization of sister origins and replisomes during multifork DNA replication in Escherichia coli by Fossum et al (2007)
github.com/CovertLab/WholeCellEcoliRelease is a whole cell simulation model created by Covert Lab and other collaborators.
The project is written in Python, hurray!
But according to te README, it seems to be the use a code drop model with on-request access to master. Ciro Santilli asked at rationale on GitHub discussion, and they confirmed as expected that it is to:
- to prevent their publication ideas from being stolen. Who would steal publication ideas with public proof in an issue tracker without crediting original authors? Academia is broken. Academia should be the most open form of knowledge sharing. But instead we get this silly competition for publication points.
- to prevent noise from non-collaborators. But they only get like 2 issues as year on such a meganiche subject... Did you know that you can ignore people, and even block them if they are particularly annoying? Much more likely is that no one will every hear about your project and that it will die with its last graduate student slave.
The project is a followup to the earlier M. genitalium whole cell model by Covert lab which modelled Mycoplasma genitalium. E. Coli has 8x more genes (500 vs 4k), but it the undisputed bacterial model organism and as such has been studied much more thoroughly. It also reproduces faster than Mycoplasma (20 minutes vs a few hours), which is a huge advantages for validation/exploratory experiments.
The project has a partial dependency on the proprietary optimization software CPLEX which is freeware, for students, not sure what it is used for exactly, from the comment in the
requirements.txt the dependency is only partial.This project makes Ciro Santilli think of the E. Coli as an optimization problem. Given such external nutrient/temperature condition, which DNA sequence makes the cell grow the fastest? Balancing metabolites feels like designing a Factorio speedrun.
There is one major thing missing thing in the current model: promoters/transcription factor interactions are not modelled due to lack/low quality of experimental data: github.com/CovertLab/WholeCellEcoliRelease/issues/21. They just have a magic direct "transcription factor to gene" relationship, encoded at reconstruction/ecoli/flat/foldChanges.tsv in terms of type "if this is present, such protein is expressed 10x more". Transcription units are not implemented at all it appears.
Everything in this section refers to version 7e4cc9e57de76752df0f4e32eca95fb653ea64e4, the code drop from November 2020, and was tested on Ubuntu 21.04 with a docker install of
docker.pkg.github.com/covertlab/wholecellecolirelease/wcm-full with image id 502c3e604265, unless otherwise noted.- www.linkedin.com/in/howelzy/Epic.
Might know a thing or two about landfills.
- www.independent.co.uk/news/uk/home-news/lost-bitcoin-crypto-james-howells-b2406517.htmlThe bizarre saga started in 2013 when Mr Howells, put the hardware from an old laptop that contained 8,000 bitcoins, the world’s leading cryptocurrency, in a black bag in his hallway.
- www.bbc.co.uk/news/uk-wales-67297013
Run output is placed under
out/:Some of the output data is stored as
.cpickle files. To observe those files, you need the original Python classes, and therefore you have to be inside Docker, from the host it won't work.We can list all the plots that have been produced under Plots are also available in SVG and PDF formats, e.g.:
out/ withfind -name '*.png'The output directory has a hierarchical structure of type:where:
./out/manual/wildtype_000000/000000/generation_000000/000000/wildtype_000000: variant conditions.wildtypeis a human readable label, and000000is an index amongst the possiblewildtypeconditions. For example, we can have different simulations with different nutrients, or different DNA sequences. An example of this is shown at run variants.000000: initial random seed for the initial cell, likely fed to NumPy'snp.random.seedgenereation_000000: this will increase with generations if we simulate multiple cells, which is supported by the model000000: this will presumably contain the cell index within a generation
We also understand that some of the top level directories contain summaries over all cells, e.g. the
massFractionSummary.pdf plot exists at several levels of the hierarchy:./out/manual/plotOut/massFractionSummary.pdf
./out/manual/wildtype_000000/plotOut/massFractionSummary.pdf
./out/manual/wildtype_000000/000000/plotOut/massFractionSummary.pdf
./out/manual/wildtype_000000/000000/generation_000000/000000/plotOut/massFractionSummary.pdfEach of thoes four levels of
plotOut is generated by a different one of the analysis scripts:./out/manual/plotOut: generated bypython runscripts/manual/analysisVariant.py. Contains comparisons of different variant conditions. We confirm this by looking at the results of run variants../out/manual/wildtype_000000/plotOut: generated bypython runscripts/manual/analysisCohort.py --variant_index 0. TODO not sure how to differentiate between two different labels e.g.wildtype_000000andsomethingElse_000000. If-vis not given, a it just picks the first one alphabetically. TODO not sure how to automatically generate all of those plots without inspecting the directories../out/manual/wildtype_000000/000000/plotOut: generated bypython runscripts/manual/analysisMultigen.py --variant_index 0 --seed 0./out/manual/wildtype_000000/000000/generation_000000/000000/plotOut: generated bypython runscripts/manual/analysisSingle.py --variant_index 0 --seed 0 --generation 0 --daughter 0. Contains information about a single specific cell.
E. Coli Whole Cell Model by Covert Lab Source code overview Updated 2025-07-11 +Created 1970-01-01
Let's try to understand some interesting looking, with a special focus on our understanding of the tiny E. Coli K-12 MG1655 operon thrLABC part of the metabolism, which we have well understood at Section "E. Coli K-12 MG1655 operon thrLABC".
reconstruction/ecoli/flat/compartments.tsvcontains cellular compartment information:"abbrev" "id" "n" "CCO-BAC-NUCLEOID" "j" "CCO-CELL-PROJECTION" "w" "CCO-CW-BAC-NEG" "c" "CCO-CYTOSOL" "e" "CCO-EXTRACELLULAR" "m" "CCO-MEMBRANE" "o" "CCO-OUTER-MEM" "p" "CCO-PERI-BAC" "l" "CCO-PILUS" "i" "CCO-PM-BAC-NEG"CCO: "Celular COmpartment"BAC-NUCLEOID: nucleoidCELL-PROJECTION: cell projectionCW-BAC-NEG: TODO confirm: cell wall (of a Gram-negative bacteria)CYTOSOL: cytosolEXTRACELLULAR: outside the cellMEMBRANE: cell membraneOUTER-MEM: bacterial outer membranePERI-BAC: periplasmPILUS: pilusPM-BAC-NEG: TODO: plasma membrane, but that is the same as cell membrane no?
reconstruction/ecoli/flat/promoters.tsvcontains promoter information. Simple file, sample lines:corresponds to E. Coli K-12 MG1655 promoter thrLp, which starts as position 148."position" "direction" "id" "name" 148 "+" "PM00249" "thrLp"reconstruction/ecoli/flat/proteins.tsvcontains protein information. Sample line corresponding to e. Coli K-12 MG1655 gene thrA:so we understand that:"aaCount" "name" "seq" "comments" "codingRnaSeq" "mw" "location" "rnaId" "id" "geneId" [91, 46, 38, 44, 12, 53, 30, 63, 14, 46, 89, 34, 23, 30, 29, 51, 34, 4, 20, 0, 69] "ThrA" "MRVL..." "Location information from Ecocyc dump." "AUGCGAGUGUUG..." [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 89103.51099999998, 0.0, 0.0, 0.0, 0.0] ["c"] "EG10998_RNA" "ASPKINIHOMOSERDEHYDROGI-MONOMER" "EG10998"aaCount: amino acid count, how many of each of the 20 proteinogenic amino acid are thereseq: full sequence, using the single letter abbreviation of the proteinogenic amino acidsmw; molecular weight? The 11 components appear to be given atreconstruction/ecoli/flat/scripts/unifyBulkFiles.py:so they simply classify the weight? Presumably this exists for complexes that have multiple classes?molecular_weight_keys = [ '23srRNA', '16srRNA', '5srRNA', 'tRNA', 'mRNA', 'miscRNA', 'protein', 'metabolite', 'water', 'DNA', 'RNA' # nonspecific RNA ]23srRNA,16srRNA,5srRNAare the three structural RNAs present in the ribosome: 23S ribosomal RNA, 16S ribosomal RNA, 5S ribosomal RNA, all others are obvious:- tRNA
- mRNA
- protein. This is the seventh class, and this enzyme only contains mass in this class as expected.
- metabolite
- water
- DNA
- RNA: TODO
rnavsmiscRNA
location: cell compartment where the protein is present,cdefined atreconstruction/ecoli/flat/compartments.tsvas cytoplasm, as expected for something that will make an amino acid
reconstruction/ecoli/flat/rnas.tsv: TODO vstranscriptionUnits.tsv. Sample lines:"halfLife" "name" "seq" "type" "modifiedForms" "monomerId" "comments" "mw" "location" "ntCount" "id" "geneId" "microarray expression" 174.0 "ThrA [RNA]" "AUGCGAGUGUUG..." "mRNA" [] "ASPKINIHOMOSERDEHYDROGI-MONOMER" "" [0.0, 0.0, 0.0, 0.0, 790935.00399999996, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] ["c"] [553, 615, 692, 603] "EG10998_RNA" "EG10998" 0.0005264904halfLife: half-lifemw: molecular weight, same as inreconstruction/ecoli/flat/proteins.tsv. This molecule only have weight in themRNAclass, as expected, as it just codes for a proteinlocation: same as inreconstruction/ecoli/flat/proteins.tsvntCount: nucleotide count for each of the ATGCmicroarray expression: presumably refers to DNA microarray for gene expression profiling, but what measure exactly?
reconstruction/ecoli/flat/sequence.fasta: FASTA DNA sequence, first two lines:>E. coli K-12 MG1655 U00096.2 (1 to 4639675 = 4639675 bp) AGCTTTTCATTCTGACTGCAACGGGCAATATGTCTCTGTGTGGATTAAAAAAAGAGTGTCTGATAGCAGCTTCTGreconstruction/ecoli/flat/transcriptionUnits.tsv: transcription units. We can observe for example the two different transcription units of the E. Coli K-12 MG1655 operon thrLABC in the lines:"expression_rate" "direction" "right" "terminator_id" "name" "promoter_id" "degradation_rate" "id" "gene_id" "left" 0.0 "f" 310 ["TERM0-1059"] "thrL" "PM00249" 0.198905992329492 "TU0-42486" ["EG11277"] 148 657.057317358791 "f" 5022 ["TERM_WC-2174"] "thrLABC" "PM00249" 0.231049060186648 "TU00178" ["EG10998", "EG10999", "EG11000", "EG11277"] 148promoter_id: matches promoter id inreconstruction/ecoli/flat/promoters.tsvgene_id: matches id inreconstruction/ecoli/flat/genes.tsvid: matches exactly those used in BioCyc, which is quite nice, might be more or less standardized:
reconstruction/ecoli/flat/genes.tsv"length" "name" "seq" "rnaId" "coordinate" "direction" "symbol" "type" "id" "monomerId" 66 "thr operon leader peptide" "ATGAAACGCATT..." "EG11277_RNA" 189 "+" "thrL" "mRNA" "EG11277" "EG11277-MONOMER" 2463 "ThrA" "ATGCGAGTGTTG" "EG10998_RNA" 336 "+" "thrA" "mRNA" "EG10998" "ASPKINIHOMOSERDEHYDROGI-MONOMER"reconstruction/ecoli/flat/metabolites.tsvcontains metabolite information. Sample lines:In the case of the enzyme thrA, one of the two reactions it catalyzes is "L-aspartate 4-semialdehyde" into "Homoserine"."id" "mw7.2" "location" "HOMO-SER" 119.12 ["n", "j", "w", "c", "e", "m", "o", "p", "l", "i"] "L-ASPARTATE-SEMIALDEHYDE" 117.104 ["n", "j", "w", "c", "e", "m", "o", "p", "l", "i"]Starting from the enzyme page: biocyc.org/gene?orgid=ECOLI&id=EG10998 we reach the reaction page: biocyc.org/ECOLI/NEW-IMAGE?type=REACTION&object=HOMOSERDEHYDROG-RXN which has reaction IDHOMOSERDEHYDROG-RXN, and that page which clarifies the IDs:so these are the compounds that we care about.- biocyc.org/compound?orgid=ECOLI&id=L-ASPARTATE-SEMIALDEHYDE: "L-aspartate 4-semialdehyde" has ID
L-ASPARTATE-SEMIALDEHYDE - biocyc.org/compound?orgid=ECOLI&id=HOMO-SER: "Homoserine" has ID
HOMO-SER
- biocyc.org/compound?orgid=ECOLI&id=L-ASPARTATE-SEMIALDEHYDE: "L-aspartate 4-semialdehyde" has ID
reconstruction/ecoli/flat/reactions.tsvcontains chemical reaction information. Sample lines:"reaction id" "stoichiometry" "is reversible" "catalyzed by" "HOMOSERDEHYDROG-RXN-HOMO-SER/NAD//L-ASPARTATE-SEMIALDEHYDE/NADH/PROTON.51." {"NADH[c]": -1, "PROTON[c]": -1, "HOMO-SER[c]": 1, "L-ASPARTATE-SEMIALDEHYDE[c]": -1, "NAD[c]": 1} false ["ASPKINIIHOMOSERDEHYDROGII-CPLX", "ASPKINIHOMOSERDEHYDROGI-CPLX"] "HOMOSERDEHYDROG-RXN-HOMO-SER/NADP//L-ASPARTATE-SEMIALDEHYDE/NADPH/PROTON.53." {"NADPH[c]": -1, "NADP[c]": 1, "PROTON[c]": -1, "L-ASPARTATE-SEMIALDEHYDE[c]": -1, "HOMO-SER[c]": 1 false ["ASPKINIIHOMOSERDEHYDROGII-CPLX", "ASPKINIHOMOSERDEHYDROGI-CPLX"]catalized by: here we seeASPKINIHOMOSERDEHYDROGI-CPLX, which we can guess is a protein complex made out ofASPKINIHOMOSERDEHYDROGI-MONOMER, which is the ID for thethrAwe care about! This is confirmed incomplexationReactions.tsv.
reconstruction/ecoli/flat/complexationReactions.tsvcontains information about chemical reactions that produce protein complexes:The"process" "stoichiometry" "id" "dir" "complexation" [ { "molecule": "ASPKINIHOMOSERDEHYDROGI-CPLX", "coeff": 1, "type": "proteincomplex", "location": "c", "form": "mature" }, { "molecule": "ASPKINIHOMOSERDEHYDROGI-MONOMER", "coeff": -4, "type": "proteinmonomer", "location": "c", "form": "mature" } ] "ASPKINIHOMOSERDEHYDROGI-CPLX_RXN" 1coeffis how many monomers need to get together for form the final complex. This can be seen from the Summary section of ecocyc.org/gene?orgid=ECOLI&id=ASPKINIHOMOSERDEHYDROGI-MONOMER:Fantastic literature summary! Can't find that in database form there however.Aspartate kinase I / homoserine dehydrogenase I comprises a dimer of ThrA dimers. Although the dimeric form is catalytically active, the binding equilibrium dramatically favors the tetrameric form. The aspartate kinase and homoserine dehydrogenase activities of each ThrA monomer are catalyzed by independent domains connected by a linker region.
reconstruction/ecoli/flat/proteinComplexes.tsvcontains protein complex information:"name" "comments" "mw" "location" "reactionId" "id" "aspartate kinase / homoserine dehydrogenase" "" [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 356414.04399999994, 0.0, 0.0, 0.0, 0.0] ["c"] "ASPKINIHOMOSERDEHYDROGI-CPLX_RXN" "ASPKINIHOMOSERDEHYDROGI-CPLX"reconstruction/ecoli/flat/protein_half_lives.tsvcontains the half-life of proteins. Very few proteins are listed however for some reason.reconstruction/ecoli/flat/tfIds.csv: transcription factors information:"TF" "geneId" "oneComponentId" "twoComponentId" "nonMetaboliteBindingId" "activeId" "notes" "arcA" "EG10061" "PHOSPHO-ARCA" "PHOSPHO-ARCA" "fnr" "EG10325" "FNR-4FE-4S-CPLX" "FNR-4FE-4S-CPLX" "dksA" "EG10230"
In this section we list charitable organizations that support education or research:
- elifesciences.org/labs by eLife
- www.digital-science.com/investment/catalyst-grant/ by Shuttleworth Foundation.
- en.wikipedia.org/wiki/PLOS
- www.chanzuckerberg.com/ Zuck has already invested in education previously:
- openuk.uk/
- Sir Peter Lampl, Education Endowment Foundation and Sutton Trust
- Jacobs Foundation, by German-Swiss coffee mogul Klaus Johann Jacobs
- joint-research-centre.ec.europa.eu/what-open-education_en
- www.non-trivial.org/ "Launch Your Own Impactful Project CHOOSE YOUR CAUSE. GET EXPERT GUIDANCE. FIND A SOLUTION AND MAKE IT HAPPEN."
- by United States Government:
- FY 2024 Education Innovation and Research:
- Education Innovation and Research (EIR) Notices Inviting Applications
- oese.ed.gov/offices/office-of-discretionary-grants-support-services/innovation-early-learning/education-innovation-and-research-eir/fy-2024-competition/
- www.federalregister.gov/documents/2024/05/06/2024-09797/applications-for-new-awards-education-innovation-and-research-eir-program-early-phase-grants
- FY 2024 Education Innovation and Research:
Huge interest overlap with Ciro Santilli, e.g. he's into
- molecular biology in general: I should have loved biology by James Somers
- JCVI-syn3.0: www.newyorker.com/magazine/2022/03/07/a-journey-to-the-center-of-our-cells
- cryo-EM: www.newyorker.com/magazine/2022/03/07/a-journey-to-the-center-of-our-cells
- David Goodsell: www.newyorker.com/magazine/2022/03/07/a-journey-to-the-center-of-our-cells
- History of Google: www.newyorker.com/magazine/2018/12/10/the-friendship-that-made-google-huge
Whenever Ciro Santilli walks in front of a school and sees the tall gates it makes him sad. Maybe 8 year olds need gates. But do we need to protect 15 year olds like that? Students should be going out to see the world, both good and evil not hiding from it! We should instead be guiding them to the world. But instead, we are locking them up in brainwashing centers.
Video "The Purpose of Education by Noam Chomsky (2012)" puts it well, education can be either be:He has spoken about that infinitely, e.g. from when he was thin: www.youtube.com/watch?v=JVqMAlgAnlo
- a brainwashing to make people comply with The Establishment
- a way to get people genuinely interested and help them to reach their life goals
Bibliography:
- www.youtube.com/watch?v=ts7CEFQM2bE How Education Became Indoctrination: Dr Stephen Hicks (2021) Interview by www.youtube.com/c/KnowlandKnows Interesting channel. "Are you sick of woke-washing in education? Free speech distinguishes education from indoctrination" and "I taught at Eton College before I was fired because 'The Patriarchy Paradox' caused offence.".
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