Tootfinder

sp_high_school_new: High school dynamic contacts (2011-2012)
These datasets contain the temporal network of contacts between students in a high school in Marseilles, France. The first dataset gives the contacts of the students of three classes during 4 days in Dec. 2011, and the second corresponds to the contacts of the students of 5 classes during 7 days (from a Monday to the Tuesday of the following week) in Nov. 2012.
This network has 180 nodes and 45047 edges.
Tags: Soc…

Logistics in the technical sense (part of supply chain management) is a subset of logistics in the vernacular sense ("the handling of the details of an operation"). You can explore this second and more general sense, and thereby build an understanding of the first and more technical sense, by iteratively asking the question, "how does one make that happen" and follow questions from there.
A big part of organizing is figuring out the (vernacular) logistics (and helping others figure it out). You want to organize a seed swap? Ok. How does one make that happen? Well, you need seeds, people, a place, and perhaps a time. How does one make that happen? You can forage seeds or you can buy seeds for a garden and swap extras. How do you get people to come? Well, figure out where you want people to come from and choose an accessible place. What's the easiest thing to do? Get people from your neighborhood. How does one make that happen? Well, maybe put up flyers. How does one make that happen? Well, print them on your printer if you have one, or at a library, then go post them up. Etc.
Keep asking questions until you either find a roadblock that you can't find a way around, or you find things you can do yourself (one of those things you can do yourself is asking friends to help).
If you practice the exercise of thinking about how things happen, you can start to find things that you can do yourself. You can start to understand what exists now, and you can imagine what's possible. By thinking about logistics, you can figure out how to replace things when they collapse or are dismantled. You can also identify things that can't easily be replaced, and try to figure out alternatives.
This practice is good for figuring out how to build, but it can also be a valuable practice for figuring out how to resist. Concentration camps and ethnic cleansing also require logistics. Mass displacement means moving people. How does one do that? People are generally going to be moved in planes or buses. How does one do that? Well, people get loaded on to planes or buses in specific places. Planes and buses need fuel. Planes are fueled at their airports, which may well be the same places where people are loaded on to them. There is a fuel depo and a fuel truck that makes flying people out of a specific place possible. How does the fuel get to that fuel depo? Well, that fuel is probably also delivered by truck. Someone drives those trucks. Someone fuels those planes. Someone clears the planes for takeoff. Someone fuels those busses. Someone drives those busses. And so on.
Logistics networks can be highly complex. The more complex the operation, the more possible points of failure and more possible points where pressure can be applied, where operations can be disrupted. Ethnic cleansing is a complicated operation. The logistics of disrupting complicated things tend to be much less complicated than the logistics of the complicated things themselves.
The Right has exploited this fact for a long time. Centralized social services are logistically complex. Public infrastructure is logistically complex. By destroying these things, they can loot public resources by privatizing the infrastructure and functionality.
But the things that support the Right are even more logistically complex. Oil, cars, AI data centers, internal paramilitary, these are extremely complicated and fragile. There are numerous pressure points, all of which can respond to numerous strategies.
If we want to win, we should reduce the influence of politics over the things we care about. We should focus on building distributed mutual aid networks that don't rely on state funding and aren't subject to the whims of politicians. This is also known as "dual power." That is, creating counter-institutions outside of the dominant political system. The Right already does this in the form of churches and corporations.
As we reduce our complexity, we can then press our complexity advantage against the things for which the Right *needs* the state: the apparatus of violence needed to maintain capital and enforce the dominant order.

Urban Ridicules ❌
都市的愚弄 ❌
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If you like my work, Support by buying me a coffee or a roll of film from PayPal https://www.paypal.com/paypalme/ydcdingsite

Replaced article(s) found for physics.flu-dyn. https://arxiv.org/list/physics.flu-dyn/new
[1/1]:
- On the stability of an in-line formation of hydrodynamically interacting flapping plates
Monika Nitsche, Anand U. Oza, Michael Siegel
https://arxiv.org/abs/2410.04626 https://mastoxiv.page/@arXiv_physicsfludyn_bot/113270998236203403
- Side-wall wetting and linear stability of falling films
Hammam Mohamed, J\"orn Sesterhenn
https://arxiv.org/abs/2504.13300 https://mastoxiv.page/@arXiv_physicsfludyn_bot/114374794050144417
- An Omni-Temporal Theory for Hydrodynamic Dispersion and Reaction in Porous Media
Md Abdul Hamid, Kyle C. Smith
https://arxiv.org/abs/2505.06063 https://mastoxiv.page/@arXiv_physicsfludyn_bot/114493702701690116
- Confirming Wave Turbulence Predictions in Rotating Turbulence
Omri Shaltiel, Omri Gat, Eran Sharon
https://arxiv.org/abs/2510.25446 https://mastoxiv.page/@arXiv_physicsfludyn_bot/115462467154250733
- Using Physics Informed Neural Network (PINN) and Neural Network (NN) to Improve a $k-\omega$ Turb...
Lars Davidson
https://arxiv.org/abs/2511.12493 https://mastoxiv.page/@arXiv_physicsfludyn_bot/115570134553603649
- Oscillating Detonation of Liquid Ammonia
Wenhao Wang, Zongmin Hu, Peng Zhang
https://arxiv.org/abs/2511.14167 https://mastoxiv.page/@arXiv_physicsfludyn_bot/115575358542454196
- On the Poisson-Source Basis of Logarithmic Wall-Pressure-Variance Growth
Jonathan M. O. Massey, Joseph C. Klewicki, Beverley J. McKeon
https://arxiv.org/abs/2511.16776 https://mastoxiv.page/@arXiv_physicsfludyn_bot/115603689363840109
- Convolutional causal learning for aerodynamic flows
Ryo Koshikawa, Ryo Araki, Qiong Liu, Kai Fukami
https://arxiv.org/abs/2601.19104 https://mastoxiv.page/@arXiv_physicsfludyn_bot/115971839485449464
- Assessing engineering wake models against operational data: insights from the Lillgrund wind farm...
Siguenza-Alvarado, Harrison, Mohammadi, Vishwakarma, Bossanyi, Landberg, Bastankhah
https://arxiv.org/abs/2601.21035 https://mastoxiv.page/@arXiv_physicsfludyn_bot/115983015393462612
- Neural equilibria for long-term prediction of nonlinear conservation laws
Benitez, Hegazy, Guo, Dokmani\'c, Mahoney, de Hoop
https://arxiv.org/abs/2501.06933 https://mastoxiv.page/@arXiv_csLG_bot/113825452743912532
- Self-similar rupture of thin films of power-law fluid
Michael C Dallaston, Steven A Kedda, Scott W McCue
https://arxiv.org/abs/2509.05383 https://mastoxiv.page/@arXiv_condmatsoft_bot/115173629129170202
- Instability and self-propulsion of flexible autophoretic filaments
Ursy Makanga, Akhil Varma, Panayiota Katsamba
https://arxiv.org/abs/2509.10153 https://mastoxiv.page/@arXiv_condmatsoft_bot/115207443699020835
- Analytical response functions for a compressible thin fluid layer with odd viscosity
Abdallah Daddi-Moussa-Ider, Yuto Hosaka, Shigeyuki Komura
https://arxiv.org/abs/2602.18136 https://mastoxiv.page/@arXiv_condmatsoft_bot/116119064615788127
toXiv_bot_toot

Sources: CBS News anchor Tony Dokoupil is broadcasting from Taipei this week after failing to obtain a Chinese visa in time for the Trump-Xi summit in Beijing (Max Tani/Semafor)
https://www.semafor.com/article/05/13/2026

Exclusive: CBS’ Tony Dokoupil to broadcast from Taiwan after failing to get China visa in time
It was a stumble in the network’s efforts to play a leading role in this week’s dominant global story.

sp_high_school_new: High school dynamic contacts (2011-2012)
These datasets contain the temporal network of contacts between students in a high school in Marseilles, France. The first dataset gives the contacts of the students of three classes during 4 days in Dec. 2011, and the second corresponds to the contacts of the students of 5 classes during 7 days (from a Monday to the Tuesday of the following week) in Nov. 2012.
This network has 126 nodes and 28561 edges.
Tags: Soc…

City Silhouettes III 🏙️
城市轮廓线 III 🏙️
📷 Pentax 6x7
🎞️ Lucky SHD 400 (6x7)
If you like my work, Support by buying me a coffee or a roll of film from PayPal https://www.paypal.com/paypalme/ydcdingsite

I know Companies House doesn't verify anything, but I wonder how "dormant companies" can operate networks of thousands of IP addresses?
https://find-and-update.company-information.service.gov.uk/company/15891388/filing-history…

SKYDIGITAL TELECOM LTD filing history - Find and update company information - GOV.UK
SKYDIGITAL TELECOM LTD - Free company information from Companies House including registered office address, filing history, accounts, annual return, officers, charges, business activity

messal_shale: Messel Shale food web (2014)
A network of feeling links among taxa based on the 48 million years old uppermost early Eocene Messel Shale. Edge property 'certainty' denotes the certainty of the edge. Metadata include evidence, habitat, and trophic roles. The edge direction goes from consumer to resource.
This network has 700 nodes and 6444 edges.
Tags: Biological, Food Web, Uncertain, Weighted, Metadata

sp_high_school_new: High school dynamic contacts (2011-2012)
These datasets contain the temporal network of contacts between students in a high school in Marseilles, France. The first dataset gives the contacts of the students of three classes during 4 days in Dec. 2011, and the second corresponds to the contacts of the students of 5 classes during 7 days (from a Monday to the Tuesday of the following week) in Nov. 2012.
This network has 126 nodes and 28561 edges.
Tags: Soc…