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Peter Sullivan discovers the issue scene from Margin Call

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Video 2.

Senior partners emergency meeting scene from Margin Call

. Source. God, Jeremy Irons is destroying it!!! And all others too.

Video 3.

Fire Sale of Mortgage Bonds scene from Margin Call

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Video 4.

Investment Analyst Explains Margin Call by The Plain Bagel

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The Big Short (2015) by

Ciro Santilli 37 Updated 2025-07-16

I'm Jacked to the Tits remix by The Big Short (2021)

Source.

Dot-com bubble by

Ciro Santilli 37 Updated 2025-07-16

Income distribution by

Ciro Santilli 37 Updated 2025-07-16

Wealth inequality by

Ciro Santilli 37 Updated 2025-07-16

Inflation by

Ciro Santilli 37 Updated 2025-07-16

One Million Dollars scene from Austin Powers

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Video 2.

100 Billion Dollars scene from Austin Powers

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Money creation by

Ciro Santilli 37 Updated 2025-07-16

E. Coli Whole Cell Model by Covert Lab / Other run variants by

Ciro Santilli 37 Updated 2025-07-16

Besides time series run variants, conditions can also be selected directly without a time series as in:

python runscripts/manual/runSim.py --variant condition 1 1

which select row indices from reconstruction/ecoli/flat/condition/condition_defs.tsv. The above 1 1 would mean the second line of that file which starts with:

"condition" "nutrients" "genotype perturbations" "doubling time (units.min)" "active TFs"
"basal" "minimal" {} 44.0 []
"no_oxygen" "minimal_minus_oxygen" {} 100.0 []
"with_aa" "minimal_plus_amino_acids" {} 25.0 ["CPLX-125", "MONOMER0-162", "CPLX0-7671", "CPLX0-228", "MONOMER0-155"]

so 1 means no_oxygen.

Authy by

Ciro Santilli 37 Updated 2025-07-16

Password by

Ciro Santilli 37 Updated 2025-07-16

Money creation vs tax by

Ciro Santilli 37 Updated 2025-07-16

politics.stackexchange.com/questions/73498/how-is-printing-money-different-from-taxing-people

To Ciro Santilli, a key observation is:

The rich are more easily able to avoid the harm than poor and middle-class people [...] they are more likely to have large amounts of non-cash assets to shield themselves from inflation.

Clearly the rich will be much, much more shielded by keeping large parts of their wealth in shares... from this point of view, it is insane to print money!!! Tax the rich instead...

Mentions:

Erik Finman: twitter.com/erikfinman/status/1446853065320112130

Renting by

Ciro Santilli 37 Updated 2025-07-16

Social inequality by

Ciro Santilli 37 Updated 2025-07-16

E. Coli Whole Cell Model by Covert Lab / Source code overview by

Ciro Santilli 37 Updated 2025-07-16

The key model database is located in the source code at reconstruction/ecoli/flat.

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".

We'll realize that a lot of data and IDs come from/match BioCyc quite closely.

reconstruction/ecoli/flat/compartments.tsv contains 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: nucleoid
- CELL-PROJECTION: cell projection
- CW-BAC-NEG: TODO confirm: cell wall (of a Gram-negative bacteria)
- CYTOSOL: cytosol
- EXTRACELLULAR: outside the cell
- MEMBRANE: cell membrane
- OUTER-MEM: bacterial outer membrane
- PERI-BAC: periplasm
- PILUS: pilus
- PM-BAC-NEG: TODO: plasma membrane, but that is the same as cell membrane no?
reconstruction/ecoli/flat/promoters.tsv contains promoter information. Simple file, sample lines:
```
"position" "direction" "id" "name"
148 "+" "PM00249" "thrLp"
```
corresponds to E. Coli K-12 MG1655 promoter thrLp, which starts as position 148.
reconstruction/ecoli/flat/proteins.tsv contains protein information. Sample line corresponding to e. Coli K-12 MG1655 gene thrA:
```
"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"
```
so we understand that:
- aaCount: amino acid count, how many of each of the 20 proteinogenic amino acid are there
- seq: full sequence, using the single letter abbreviation of the proteinogenic amino acids
- mw; molecular weight? The 11 components appear to be given at reconstruction/ecoli/flat/scripts/unifyBulkFiles.py:
  molecular_weight_keys = [ '23srRNA', '16srRNA', '5srRNA', 'tRNA', 'mRNA', 'miscRNA', 'protein', 'metabolite', 'water', 'DNA', 'RNA' # nonspecific RNA ]
  so they simply classify the weight? Presumably this exists for complexes that have multiple classes?
  - 23srRNA, 16srRNA, 5srRNA are 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 rna vs miscRNA
- location: cell compartment where the protein is present, c defined at reconstruction/ecoli/flat/compartments.tsv as cytoplasm, as expected for something that will make an amino acid
reconstruction/ecoli/flat/rnas.tsv: TODO vs transcriptionUnits.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" 0.0005264904
```
- halfLife: half-life
- mw: molecular weight, same as in reconstruction/ecoli/flat/proteins.tsv. This molecule only have weight in the mRNA class, as expected, as it just codes for a protein
- location: same as in reconstruction/ecoli/flat/proteins.tsv
- ntCount: nucleotide count for each of the ATGC
- microarray 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)
AGCTTTTCATTCTGACTGCAACGGGCAATATGTCTCTGTGTGGATTAAAAAAAGAGTGTCTGATAGCAGCTTCTG

reconstruction/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"] 148
```
- promoter_id: matches promoter id in reconstruction/ecoli/flat/promoters.tsv
- gene_id: matches id in reconstruction/ecoli/flat/genes.tsv
- id: matches exactly those used in BioCyc, which is quite nice, might be more or less standardized:
  - biocyc.org/ECOLI/NEW-IMAGE?object=TU0-42486
  - biocyc.org/ECOLI/NEW-IMAGE?type=OPERON&object=TU00178

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.tsv contains metabolite information. Sample lines:
```
"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"]
```
In the case of the enzyme thrA, one of the two reactions it catalyzes is "L-aspartate 4-semialdehyde" into "Homoserine".
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 ID HOMOSERDEHYDROG-RXN, and that page which clarifies the IDs:
- 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
so these are the compounds that we care about.

reconstruction/ecoli/flat/reactions.tsv contains 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 see ASPKINIHOMOSERDEHYDROGI-CPLX, which we can guess is a protein complex made out of ASPKINIHOMOSERDEHYDROGI-MONOMER, which is the ID for the thrA we care about! This is confirmed in complexationReactions.tsv.

reconstruction/ecoli/flat/complexationReactions.tsv contains information about chemical reactions that produce protein complexes:
```
"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"
1
```
The coeff is 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:
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.
Fantastic literature summary! Can't find that in database form there however.

reconstruction/ecoli/flat/proteinComplexes.tsv contains 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.tsv contains 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"

Why can't you collimate incoherent light as well as a laser? by

Ciro Santilli 37 Updated 2025-07-16

physics.stackexchange.com/questions/252393/why-cant-incoherent-light-be-collimated-as-well-as-laser-light-e-g-in-a-laser

You could put an LED in a cavity with a thin long hole but then, most rays, which are not aligned with the hole, will just bounce inside forever producing heat.

So you would have a very hot device, and very little efficiency on the light output. This heat might also behave like a black-body radiation source, so you would not have a single frequency.

The beauty of lasers is the laser cavity (two parallel mirrors around the medium) selects parallel motion preferentially, see e.g.: youtu.be/_JOchLyNO_w?t=832 from Video "How Lasers Work by Scientized (2017)"

Affirmative action by

Ciro Santilli 37 Updated 2025-07-16

Ciro Santilli is against all affirmative action, except for one: giving amazing free eduction to the poor.

Notably, Ciro is against university entry quotas.

Bounding box by

Ciro Santilli 37 Updated 2025-07-16

Equal opportunity by

Ciro Santilli 37 Updated 2025-07-16

Meritocracy by

Ciro Santilli 37 Updated 2025-07-16

Wealth distribution in the United States by

Ciro Santilli 37 Updated 2025-07-16

Grew tremendously since the 1990's, likely linked to the Internet.

www.cbpp.org/wealth-concentration-has-been-rising-toward-early-20th-century-levels-2 shows historical for top 1% and 0.5% from 1920 to 2010.

TODO why is it so hard to find a proper cumulative distribution function-like curve? OMG. This appears to be also called a Lorenz curve.

Wealth Inequality in America by politizane

. Source.

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