#topology — Public Fediverse posts

I'm Anthony, a #math phd candidate at George Mason University! I like to think about stochastic #topology, #probability, random #algorithms, and quantitative justice. let me know if you're going to the AMS Eastern Sectional at GWU in October, I'd love to say hi :)

The nuclear pore complex (7R5J & 7R5K) – one of the largest molecular machines in biology.

The nuclear pore complex is the gatekeeper of the cell nucleus – controlling everything that enters or leaves. We captured it in two states: open (dilated) and closed (constricted).

961665 quantum records

https://www.exxogen.hu/

​#StructuralBiology #Biophysics #Bioinformatics #Topology #InformationTheory #DNAFolding #ComputationalBiology #ComplexSystems #Genomics #OpenScience #EXXOGEN

Users Are Too Dependent on Centralized Techno-Fascist Corporate Structure to Ever Leave Discord

I’m watching people scatter into countless real-time chat alternatives to Discord after Discord started pulling the age-verification and age-gating card.

https://techcrunch.com/2026/02/09/discord-to-roll-out-age-verification-next-month-for-full-access-to-its-platform/

It’s very frustrating because people are entirely missing the point of a community and how social networks work. Real-time platforms and social media networks only work well when a large number of people share the same space at the same time. If everyone creates separate servers or competing apps, the result is fragmentation that makes it unviable.

One reason why Bluesky became so successful is the invitation and starter-pack move. It essentially allowed people to move collectively as cliques. Bluesky used invitations and starter packs to move groups of friends together. This kept communities intact. Moving as cliques preserves network structure, whereas random scattering does not. People aren’t do not seem to intend to move as cliques or subgraphs of networks off of Discord. And the whole reason people were on Discord was to host their communities, so an alternative becomes pointless if your community doesn’t remain intact.

Instead of an active, strongly connected, possibly distributed network, you get dozens of small pockets. I am referring to a potential distributed network rather than a single centralized platform, because Matrix is an example of a decentralized chat protocol. Not all alternatives have to be centralized like Discord. Technically, many older chat protocols, such as XMPP and IRC, are examples of federated real-time synchronous messaging. They allowed communication between users on different, independently operated servers. Federation means that multiple servers can interconnect so that users from separate networks can exchange messages with one another seamlessly.

Decentralized alternatives would not be a problem if people moved to the same distributed network as cohesive groups. However, what I am seeing is that people move in disconnected and stochastic ways to entirely separate distributed networks, so communities are not kept intact. For example, when people move to XMPP servers or Matrix servers, it bifurcates and disconnects social networks. Notice I said XMPP or Matrix, which logically means people are on Matrix but not XMPP, or they are on XMPP but not Matrix. That implies a person would need to be on both Matrix and XMPP to speak to their original community from Discord if it split down the middle. To synchronize conversations in chats, there would need to be a bridge. It’s a pretty complicated solution.

The likely outcome is that people will remain on the dominant platform because of its scale and structure. The deeper irony is that while people may want independence from corporate platforms, they often struggle to organize effectively without the centralized structure those platforms provide. They’ve become so dependent on corporate structures to support their communities that they have no clue how to organize their own social networks in a sustainable way.

I’ve always been an internet nerd, but most of my social life has been offline. I view my interactions with the social app layer of the internet as a game, so losing that domain of the Internet is not devastating to me.

I’ll give you an example. This is a WordPress site. You hear this insincere nostalgia from Millennials and Gen X for a simulacrum that never was, especially concerning forums. Check this out: when you go into the plugin installation section of WordPress, this is on the second row you see:

https://bbpress.org/

That means any WordPress site has the capability to host a forum. They’re nostalgic for a setup where you can use a simple install script on any hosting service to install WordPress. After that, you can then just add a plugin to turn it into a forum. Hell, they can do this on WordPress.com if they don’t want to self-host.

You can make a forum, but no one will use it because they’d rather use a centralized platform like Reddit. Users have become so dependent on corporations to structure and organize communities that they can’t do it themselves. It’s sort of like the cognitive debt that accrues when people outsource their thinking to AI.

The issue is not that forums are hard to host or create; rather, the issue is that people have become so dependent on centralized corporate structures that they can’t maintain or organize their own communities, which is why everyone ends up on Reddit or Discord. A reason I keep hearing for why people don’t want to leave Discord is that it’s hard to recreate the community structure that Discord’s features provide. They claim that they want independence from corporate platforms, but rely on the centralized structure those platforms provide to function socially.

People say they want decentralized freedom, but in practice they depend on centralized platforms to maintain social cohesion. Stochastically scattering to the digital winds of the noosphere destroys the very communities they’re trying to preserve.

Your BlueSky Feed Is Porn You Didn’t Ask For Because Your Friends Are Gooners With a Severe Porn Addiction

A common complaint I see people make on Bluesky is: why am I being served so much porn or things I am not interested in? They will incorrectly believe that the algorithm is broken. It’s not broken. You didn’t know the people you knew as well as you thought you did. Porn addiction is a thing, and porn addiction is especially common with weebs. You’re seeing deranged shit because people you follow have porn addictions and are into deranged shit. So, though you may not be consuming porn, people in your network are. That activity kicks into your feeds.

The issue I have with that is that it essentially normalizes being sex pests in a space on the Internet. That sets the expectation that it is good—attractive, even—to act like that elsewhere. That expectation alienates relationships. Bluesky creates a cultural space that offers an unrealistic, bizarre representation of social relationships, which isolates and alienates the users who stay on there consuming erotica and porn like they do.

So, user repos in Bluesky have a property for likes. Bluesky’s underlying AT Protocol stores likes as first-class structured records in each user’s AT Protocol repository. In the AT Protocol lexicon, a like is an app.bsky.feed.like record type. Unlike a simple boolean flag on a post, it is its own record with a creation timestamp and a subject field that holds a strong reference to the liked record.

That strong reference is composed of an AT-URI and a CID. The AT-URI identifies the exact record in the network by DID, collection, and record key. The CID is a cryptographic content identifier that uniquely identifies the exact content of that liked record.

These like records exist under the app.bsky.feed.like namespace in the user’s repo. Bluesky’s repo model is built so that these repos are hosted on a user’s Personal Data Server and are publicly readable through the AT Protocol APIs. Because of that, the like record and its fields can be fetched, indexed, and used by any client or service that can query the protocol.

The protocol exposes operations like getLikes. This returns all of the like records tied to a particular subject’s AT-URI and CID. It also exposes getActorLikes. This returns all of the subject references a given actor has liked. Those API calls return structured like objects with timestamps and subject references directly from the public repository data.

Various feeds hosted by different PDSs use the likes property to construct the feeds that you see. Since the likes of people you follow are included in your social graph, along with your own likes, you’re going to get served the porn they are consuming. Because likes are public and anyone can write an algorithm to see everyone’s likes, you can clearly see just how much porn people are consuming.

Honestly, what started to turn my stomach about the people on Bluesky is how they behave across different contexts. If you look through the records of the posts they interact with, you’ll see them engaging with political posts in the replies like a normal person. Then, when you look through their AT Protocol records, you see hours and hours of them interacting with every kind of porn imaginable. I am not exaggerating. Hours of likes for porn posts within 1–10 minutes of each other. Am I sex-negative? A prude? No, this site is filled with furry, gay bara porn, lol. You can have a drink without being an alcoholic. The problem with these people is like people who can’t have one drink without drinking the whole fucking day; they can’t consume porn in healthy ways.

I think people assume that their feed is customized for them and based on their likes. No—feeds are generalized based on what everyone likes and then served to your subgraph. It’s not just about who you follow; it’s about who they follow. So if you follow someone who follows a lot of people with porn addictions, you will see porn. Bluesky isn’t weighting the algorithm to do this. Basically, it’s the people in your social network with furry, hentai, or trans porn addictions who are driving it.

BlueSky’s Solution To Moderating Is Moderating Without Moderating via Social Proximity

I have noticed a lot of people are confused about why some posts don’t show up on threads, though they are not labeled by the moderation layer. Bluesky has begun using what it calls social neighborhoods (or network proximity) as a ranking signal for replies in threads. Replies from people who are closer to you in the social graph, accounts you follow, interact with, or share mutual connections with, are prioritized and shown more prominently. Replies from accounts that are farther away in that network are down-ranked. They are pushed far down the thread or placed behind “hidden replies.”

Each person gets their own unique view of a thread based on their social graph. It creates the impression that replies from distant users simply don’t exist. This is true even though they’re still technically public and viewable if you expand the thread or adjust filters. Bluesky is explicitly using features of subgraphs to moderate without moderating. Their reasoning is that if you can’t see each other, you can’t harass each other. Ergo, there is nothing to moderate.

Bluesky mentions that here:

https://bsky.social/about/blog/10-31-2025-building-healthier-social-media-update

As a digression, I’m not going to lie: I really enjoyed working on software built on the AT protocol, but their fucking users are so goddamn weird. It’s sort of like enjoying building houses, but hating every single person who moves into them. But, you don’t have to deal with them because you’re just the contractor. That is how I feel about Bluesky. I hate the people. I really like the protocol and infrastructure.

I sort of am a sadist who does enjoy drama, so I do get schadenfreude from people with social media addictions and parasocial fixations who reply to random people on Bluesky, because they don’t realize their replies are disconnected from the author’s thread unless that person is within their network. They aren’t part of the conversation they think they are. They’re algorithmically isolated from everyone else. Their replies aren’t viewable from the author’s thread because of how Bluesky handles social neighborhoods.

Bluesky’s idea of social neighborhoods is about grouping users into overlapping clusters based on real interaction patterns rather than just the follow graph. Unlike Twitter, it does not treat the network as one big public square. Instead, it models networks of “social neighborhoods” made up of people you follow, people who follow you, people you frequently interact with, and people who are closely connected to those groups. They’re soft, probabilistic groupings rather than strict labels.

Everyone does not see the same replies. Bluesky is being a bit vague with “hidden.” Hidden means your reply is still anchored to the thread and can be expanded. There is another way Bluesky can handle this. Bluesky uses social neighborhoods to judge contextual relevance. Replies from people inside or near your social neighborhood are more likely to be shown inline with a thread, expanded by default, or served in feeds. Replies from outside your neighborhood are still public and still indexed, but they’re treated as lower-context contributions.

Basically, if you reply to a thread, you will see it anchored to the conversation, and everyone will see it in search results, as a hashtag, or from your profile, but it will not be accessible via the thread of the person you were replying to. It is like shadow-banning people from threads unless they are strongly networked.

Because people have not been working with the AT Protocol like I have, they assume they are shadow-banned across the entire Bluesky app view. No—everyone is automatically shadow-banned from everyone else unless they are within the same social neighborhood. In other words, you are not part of the conversation you think you are joining because you are not part of their social group.

Your replies will appear in profiles, hashtag feeds, or search results without being visually anchored to the full thread. Discovery impressions are neighborhood-agnostic: they serve content because it matches a query, tag, or activity stream. Once the reply is shown, the app then decides whether it’s worth pulling in the rest of the conversation for you. If the original author and most participants fall outside your neighborhood, Bluesky often chooses not to expand that context automatically.

Bluesky really is trying to avoid having to moderate, so this is their solution. Instead of banning or issuing takedown labels to DIDs, the system lets replies exist everywhere, but not in that particular instance of the thread.

I find this ironic because a large reason why many people are staying on Bluesky and not moving to the fediverse—thank God, because I do not want them there—is discoverability, virality, and engagement.

In case anyone is asking how I know so much about how these algorithms work: I was a consultant on a lot of these types of algorithms, so I certainly hope I’d know how they work, lol. No, you get no more details about the work I’ve done. I have no hand in the algorithm Bluesky is using, but I have proposed and implemented that type of algorithm before.

I have an interest in noetics and the noosphere. A large amount of my ontological work is an extension of my attempts to model domains that have no spatial or temporal coordinates. The question is how do you generalize a metric space that has no physically, spatial properties. I went to school to try to formalize those ideas. Turns out they’re rather useful for digital social networks, too. The ontological analog to spatial distance, when you have no space, is a graph of similarities.

"#TheGarden is the web as #topology. The web as space. It’s the integrative web, the iterative web, the web as an arrangement and rearrangement of things to one another.
Things in the Garden don’t collapse to a single set of relations or canonical sequence, and that’s part of what we mean when we say “the web as topology”. Every walk through the garden creates new paths, new meanings, and when we add things to the garden we add them in a way that allows many future, unpredicted relationships."

"Encode #spatial data as #topology in #Python!

With #topojson it is possible to reduce the size of your spatial data. Mostly by orders of magnitude."

https://mattijn.github.io/topojson/

#geopython #geospacial #GIS #computationalGeometry

The following list identifies the longest escarpments on the planet. Escarpments are defined as follows:

Escarpment: “A steep slope or long cliff that results from erosion or faulting and separates two relatively level areas of differing elevations.”

Source: The American Heritage® Dictionary of the English Language, 5th Edition

If you have ever driven along the Ohio Turnpike near Cleveland, you have gone up/down the Portage Escarpment. Similarly, between Toronto and London Ontario, one would have to cross the Niagara Escarpment. In fact, Niagara Falls, on the New York/Ontario border, are literally a part of the Niagara Escarpment. The falls are where the elevation drops dramatically between Lake Erie (571 feet above sea level) on the upper side and Lake Ontario (243 feet above sea level) on the lower side of the escarpment. The Welland Canal was specifically built to bypass the falls and cross the escarpment.

Similar examples of lengthy escarpments can be found worldwide on every continent including Antarctica. And the steepness/sheerness of them can vary too, as the Cody Scarp in northern Florida is comparatively quite mild. However, most escarpments are quite bold, rapidly rising to elevations well above the surrounding terrain. The sharp change can often be measured in hundreds or thousands of feet.

In several cases, hiking trails or scenic byways have been developed along or near the rim of these magnificent natural features, providing amazing visiting fr those trekking them. Blue Ridge Parkway, Mogollon Rim Road and Skyline Drive are examples of scenic byways while the Knobstone Trail in Indiana and the developing Mogollon Rim Trail in Arizona are hiking routes.

For proposes of this post a minimum length of 10 miles was required and escarpments which are primarily situated underwater (ocean/sea/lake, etc.) are not included. Those shown in italics the author has seen or traveled across. Peace!

1. Great Escarpment of Southern Africa = 3,107 miles/5,000 km

2. Great Escarpment (Oceania) = 2,200 miles/3,600 km

3. Grande Escarpa do Brasil (South America) = 1,600 miles/2,600 km

4. Niagara Escarpment (North America) = 1,000 miles/1609 km

5. Atlantic Seaboard Fall Line (North America) = 900 miles/1,400 km

6. Portage Escarpment (North America) ~ 653 miles/1051 km

7-8. Darling Scarp (Oceania) and Madagascar East Coast Escarpment (Africa) = 620 miles/1,000 km

9. Blue Ridge Escarpment (North America) = 550 miles/885 km

10. Tuwaiq Escarpment (Asia) = 500 miles/800 km

11. Zambezi Escarpment (Africa) = 497 miles/800 km

12. Manitoba/Pembina Escarpment (North America) = 419 miles/675 km

13-14. Sierra Escarpment (North America) = 400 miles/644 km Balcones Escarpment (North America) ~ 400 miles/644 km

15. Book Cliffs Escarpment (North America) = 250 miles/402 km *longest continuous escarpment in the world

16-17. Caprock Escarpment (North America) and Mogollon Rim (North America) = 200 miles/320 km

18. Usas Escarpment (Antarctica) = 199 miles/320 km

19. Roan Cliffs Escarpment (North America) = 190 miles/306 km – separate escarpment atop the Book Cliffs Escarpment

20. Allegheny Front (North America) = 180 miles/290 km

21. Western Andean Escarpment (South America) = 155 miles/250 km

22. North Downs Chalk Escarpment = 153 miles/246 km

23. Knobstone Escarpment (North America) = 150 miles/241 km

24. Nullarbor Scarp (Oceania) = 130 miles/210 km

25. Missouri Escarpment (North America) = 100 miles/161 km

26-27. Bandiagara Escarpment (Africa) and Vermillion-Echo Cliffs Escarpment (North America) = 90 miles/160 km

28. South Downs Chalk Escarpment (Europe) = 68 miles/110 km

29. Onondaga Escarpment (North America) = 62 miles/100km

30. Illawarra Escarpment (Oceania) = 57 miles/92 km

31-32. Lincoln/Trent Cliff (Europe) and Mescalero Ridge (North America) = 50 miles/80 km

33. Chiltern Escarpment (Europe) = 45 miles/72 km

34. Côte d’Or (Europe) = 30 miles/48 km

35. Catskills Escarpment (North America) = 24 miles/38 km

36. Palisades Escarpment (North America) = 20 miles/34 km

37. Wenlock Edge (Europe) = 19 miles/31 km

38. Chinese Wall Escarpment (North America) = 12 miles/19 km

39-40. Duluth Escarpment (North America) and Black Mountain Escarpment (Europe) = 11 miles/18 km

Other Escarpments – More Information Needed

• Cody Scarp (North America)
• Elgeyo Escarpement (Africa)
• Eardley Escarpment (North America) = 40+ km
• Kaimai Escarpment (Oceania)
• Muldraugh Hill Escarpment (North America)
• Pottsville/Cumberland Escarpment (North America)
• Sharon Escarpment (Asia)
• Gotland–Saaremaa Klint (Europe) = 180+ km
• Wulian Feng (Asia)

SOURCES:

• https://en.wikipedia.org/wiki/Escarpment
• https://www.britannica.com/place/Niagara-Escarpment
• https://www.britannica.com/place/Serra-do-Mar
• https://www.dmr.nd.gov/ndgs/ndnotes/pembina/Pembina.htm
• personal knowledge
• https://www.manitoba.ca/iem/geo/mgstracker/images/region6/2010_fieldtrip.pdf
• https://www.greatnortherncatskills.com/how-thru-hike-escarpment-trail
• https://en-academic.com/dic.nsf/enwiki/4787527
• https://falzguy.com/escarp-niag-onon.html#:~:text=The%20Onondaga%20Escarpment%20begins%20at,600%20feet%20above%20sea%20level.
• https://www.geneseo.edu/sites/default/files/2023-08/Brett%20and%20Brett%20SDS%202023%20Part%201%20-%20Niagara%20Frontier.pdf
• https://oldleacounty.com/2021/07/13/mescalero-ridge/
• https://www.sciencedirect.com/science/article/pii/S0040195101002128
• https://en.wikipedia.org/wiki/Tuwaiq
• https://www.researchgate.net/profile/Nigel-Barker-2/publication/234834352_The_Great_Escarpment_of_Southern_Africa_A_New_Frontier_for_Biodiversity_Exploration/links/0fcfd510128f337795000000/The-Great-Escarpment-of-Southern-Africa-A-New-Frontier-for-Biodiversity-Exploration.pdf
• https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2022JF007001#:~:text=Eastern%20Madagascar%20is%20characterized%20by,et%20al.%2C%202021).
• https://en.wikipedia.org/wiki/Bunda_Cliffs
• https://kentdowns.org.uk/north-downs-way/#:~:text=Passing%20through%20153%20miles%20of,life%2Dchanging%20long%20distance%20walk.
• https://www.blackmountainswalking.co.uk/the-black-mountains-magic
• https://thevinofiles.typepad.com/the_vino_files/2008/09/burgundy-2.html#:~:text=For%20all%20its%20notoriety%2C%20the,past%20Santenay%20in%20the%20south.
• https://www.looduskalender.ee/klint/eng/5.html
• https://www.neilyworld.com/neilyworld/eegpnw.htm
• https://www.swimdrinkfish.ca/lake-ontario-waterkeeper/blog/19870
• https://en.wikipedia.org/wiki/The_Palisades_(Hudson_River)
• https://suwa.org/multimedia/map/book-cliffsdesolation-canyon-region/#:~:text=Winding%20for%20250%20miles%20across,continuous%20escarpment%20in%20the%20world.
• https://en.wikipedia.org/wiki/Roan_Cliffs#:~:text=Stretching%20nearly%20190%20miles%20(310,the%20Carbon%E2%80%91Duchesne%20county%20line.
• https://duluthmn.gov/media/7719/skyline_map.pdf
• https://www.lakesuperiorstreams.org/understanding/geology.html
• https://falzguy.com/escarp-niag-onon.html
• https://howardfalls.org/2023/08/24/the-portage-escarpment/
• https://janelcurry.com/blog1/understanding-western-new-york
• https://scholarsmine.mst.edu/cgi/viewcontent.cgi?article=3134&context=geosci_geo_peteng_facwork

https://panethos.wordpress.com/2024/01/11/natures-sheer-cliffs-the-worlds-longest-escarpments/

#bluffs #cliffs #ecology #ecosystems #environment #escarpments #geology #hiking #history #landUse #mountains #planning #rims #topology #travel

`It is also called the #Cantor ternary #function, the #Lebesgue function, Lebesgue's singular function..the Devil's staircase, the Cantor #staircase function, and the Cantor–Lebesgue function. Georg Cantor (1884) introduced the Cantor function and mentioned that Scheeffer pointed out that it was a counterexample to an extension of the fundamental #theorem of #calculus claimed by Harnack.`

https://en.wikipedia.org/wiki/Cantor_function

#devilsStaircase #fractal #cantorSet #topology #analysis

Exploring the #topology of a fused #latentspace , made of two fine-tuned #stablediffusion models – my #solarpunk model, and my 'gold' #portrait model.

Working in this way means letting go, prompting at a higher-level of abstraction, and discovering the characters who inhabit this mysterious #manifold

✨

#introduction

Part of the Migration. Moved from @[email protected]

Interested in #topology (for fun and #TDA )
#GraphicalLinearAlgebra and similar notations like string diagrams and #ExistentialGraphs
#CurryHowardIsomorphism
#Semantics for humans and computers
#topoi
#CategoryTheory
#WordEmbeddings (in #NLP )
#language
#logic
#SFF
#History of science, math, societies
etc.

Trans rights are human rights; blm; workers solidarity; native rights; and all the various other ways of not being vile to people