@mcdanlj@social.makerforums.info2026-06-19 17:42:51
More #FreeCADFriday now in Friday in my own time zone. I have a fan that I want to make a table stand for to use outside while operating #HamRadio. First I modeled the fan in a silly amount of detail, including the grill, which took some learning, and I'm still pretty sure I d…
@aredridel@kolektiva.social2026-05-19 15:01:11
Some of these are pretty reasonable! If you allow them for anyone, you probably make it so to compete at all requires everyone to follow suit. That's bad when those things have life-altering health implications.
But all of these things ultimately shape who is allowed to compete at the peak levels.
it's not always good! Honestly baseball is way less interesting to watch in the majors because everyone's great, all the plays are maximal capability, and it's kinda predictable. You don't end up with many of those "holy shit what just happened? that was awesome!" plays that are so much fun to watch. So as a spectator, these rules aren't always great. Sometimes you want to nerf the peak performance until the game is interesting. Sometimes you don't.
In F1, a huge part of the game is the nerding out about the rules and how to evade them cleverly to get peak performance. And the inside baseball on that is way more fun to watch than the race. The race is just cars going zoom and occasionally crashing, interrupted by amazing choreography in the pits.
There's a reason women's soccer is so much more fun for me to watch than men's. It's not been optimized so hard that the game isn't predictable in kind if not outcome. Plus the camaraderie shown is great.
But looking at all this, we gotta ask, what's sport's function in our societies? Why do we do this?
@PaulWermer@sfba.social2026-05-18 21:52:03
I keep seeing posts about how wonderful the Democratic Party is, how their polices are so good, their messaging is fine.
This does not accord with the latest NYTImes/Siena poll results, where 44% of DEMOCRATS are dissatisfied with the party. Overall voters, 70% are dissatisfied.
COMPARE TO GOP numbers: while #POTUS is not held in esteem by most, only 15% of GOP disapprove, and only 23% of…
@paulwermer@sfba.social2026-05-18 21:52:03
I keep seeing posts about how wonderful the Democratic Party is, how their polices are so good, their messaging is fine.
This does not accord with the latest NYTImes/Siena poll results, where 44% of DEMOCRATS are dissatisfied with the party. Overall voters, 70% are dissatisfied.
COMPARE TO GOP numbers: while #POTUS is not held in esteem by most, only 15% of GOP disapprove, and only 23% of…
@arXiv_physicsfludyn_bot@mastoxiv.page2026-05-19 08:22:29
Long-horizon prediction of three-dimensional wall-bounded turbulence with CTA-Swin-UNet and resolvent analysis
Bo Chen, Yitong Fan, Jie Yao, Weipeng Li
https://arxiv.org/abs/2605.17888 https://arxiv.org/pdf/2605.17888 https://arxiv.org/html/2605.17888
arXiv:2605.17888v1 Announce Type: new
Abstract: Long-horizon prediction of three-dimensional (3D) wall-bounded turbulence with machine-learning methods remains a challenging task, due to the rapid accumulation of autoregressive errors and the substantially computational cost. To address these challenges, we present a hybrid machine-learning framework, in which a channel-time-attention Swin-UNet (CTA-Swin-UNet) and a multi-time-scale fusion correction (MTFC) strategy are developed to predict the turbulent flow fields in a wall-parallel plane, with affordable computational cost. Then, 3D flow fields are reconstructed via a resolvent-based spectral linear stochastic estimation (SLSE), rooting from the predicted planar flow. Results show that the CTA-Swin-UNet outperforms the baseline models (LSTM, FNO and traditional Swin-UNet) in both single-step prediction and autoregressive rollouts, indicating the effectiveness of introducing the CTA module into the Swin-UNet architecture. At the same temporal interval, the CTA-Swin-UNet remains stable for approximately 150 rollout steps, while the baseline models fail within 20 to 50 rollout steps. After introducing the MTFC strategy, a longer horizon upto 300 steps is achieved. Using the resolvent-based SLSE reconstruction further recovers the 3D flow structures and energy spectral distributions from the predicted planar inputs, which demonstrates that the proposed framework provides an effective and computationally efficient approach for long-horizon autoregressive prediction of 3D wall-bounded turbulence.
toXiv_bot_toot
@davidaugust@mastodon.online2026-07-18 16:06:09
*sung as if Sublime’s Santeria*
♫ I don’t practice Trumporrhea
I don’t got explosive poops
But, if we had some public health
not just some stupid dupes
Then we could fine that Taylor
And then send their stock to hell
Well, I’d fed that bad CEO all the shit they sell ♫
#cyclospora
@Neybulot@pawb.fun2026-06-19 18:56:02
I like that Dutch Bros gives you a month to use the birthday drink, annoying that Starbucks makes you use it same day.
@hex@kolektiva.social2026-05-18 11:14:58
Here are some notes I've found also (not ours, but I think we distilled some ideas from these):
https://drive.google.com/file/d/1tz0mNWt01Fbc78m3waYzviM3exjDY2aj/view
This is related to FEMA stuff.
Edit:
Apologies in advance for the google link. It's not our doc. But also, we did use google drive. I wouldn't do that today.
@heiseonline@social.heise.de2026-06-15 19:51:00
@penguin42@mastodon.org.uk2026-04-19 16:47:43
My NVME performance rabbit hole is confusing; one of my two identical drives is half the performance in hdparm -T; I swapped the drives in the slots and the performance follows the drive not the slot. PCIe looks fine with the same link speed/width. NVMe features (nvme get-feature /dev/nvme. -f 0 -H) are the same on both.
Oddly the *latency* is much lower on the slower drive?!! wtf?!