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Bibliography:
- www.comuseum.com/ some good galleries
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Mitchell and Webb Updated 2025-07-16
They do have some really good ones.
It is interesting that in different episodes they often switch the dominant/passive roles, so it's not fixed as in Laurel and Hardy.
Are we the Baddies? by Mitchell and Webb
. Source. See also: cirosantilli.com/china-dictatorship/nazi.Discoverer by Mitchell and Webb
. Source. Makes fun of the many terrible naming choices British navigators have made while discovering/rediscovering new lands. Perforce Updated 2025-07-16
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CIA 2010 covert communication websites 2013 DNS census SOA records Updated 2025-07-16
Same as 2013 DNS census NS records basically, nothing came out.
CIA 2010 covert communication websites 2013 DNS Census virtual host cleanup Updated 2025-07-16
We've noticed that often when there is a hit range:and that this does not seem to be that common. Let's see if that is a reasonable fingerprint or not.
- there is only one IP for each domain
- there is a range of about 20-30 of those
Note that although this is the most common case, we have found multiple hits that viewdns.info maps to the same IP.
First we create a table The
u (unique) that only have domains which are the only domain for an IP, let's see by how much that lowers the 191 M total unique domains:time sqlite3 u.sqlite 'create table t (d text, i text)'
time sqlite3 av.sqlite -cmd "attach 'u.sqlite' as u" "insert into u.t select min(d) as d, min(i) as i from t where d not like '%.%.%' group by i having count(distinct d) = 1"not like '%.%.%' removes subdomains from the counts so that CGI comms are still included, and distinct in count(distinct is because we have multiple entries at different timestamps for some of the hits.Let's start with the 208 subset to see how it goes:OK, after we fixed bugs with the above we are down to 4 million lines with unique domain/IP pairs and which contains all of the original hits! Almost certainly more are to be found!
time sqlite3 av.sqlite -cmd "attach 'u.sqlite' as u" "insert into u.t select min(d) as d, min(i) as i from t where i glob '208.*' and d not like '%.%.%' and (d like '%.com' or d like '%.net') group by i having count(distinct d) = 1"This data is so valuable that we've decided to upload it to: archive.org/details/2013-dns-census-a-novirt.csv Format:The numbers of the first column are the IPs as a 32-bit integer representation, which is more useful to search for ranges in.
8,chrisjmcgregor.com
11,80end.com
28,fine5.net
38,bestarabictv.com
49,xy005.com
50,cmsasoccer.com
80,museemontpellier.net
100,newtiger.com
108,lps-promptservice.com
111,bridesmaiddressesshow.comTo make a histogram with the distribution of the single hostname IPs:Which gives the following useless noise, there is basically no pattern:
#!/usr/bin/env bash
bin=$((2**24))
sqlite3 2013-dns-census-a-novirt.sqlite -cmd '.mode csv' >2013-dns-census-a-novirt-hist.csv <<EOF
select i, sum(cnt) from (
select floor(i/${bin}) as i,
count(*) as cnt
from t
group by 1
union
select *, 0 as cnt from generate_series(0, 255)
)
group by i
EOF
gnuplot \
-e 'set terminal svg size 1200, 800' \
-e 'set output "2013-dns-census-a-novirt-hist.svg"' \
-e 'set datafile separator ","' \
-e 'set tics scale 0' \
-e 'unset key' \
-e 'set xrange[0:255]' \
-e 'set title "Counts of IPs with a single hostname"' \
-e 'set xlabel "IPv4 first byte"' \
-e 'set ylabel "count"' \
-e 'plot "2013-dns-census-a-novirt-hist.csv" using 1:2:1 with labels' \
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X-ray crystallography Updated 2025-07-16
One of its main applications is to determine the 3D structure of proteins.
Sometimes you are not able to crystallize the proteins however, and the method cannot be used.
Crystallizing is not simple because:
Cryogenic electron microscopy can sometimes determine the structures of proteins that failed crystallization.
AI alignment Updated 2025-07-16
As highlighted e.g. at Human Compatible by Stuart J. Russell (2019), this AI alignment intrinsically linked to the idea of utility in economy.
Algebraic geometry Updated 2025-07-16
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