@kurtsh@mastodon.social2025-12-27 05:21:46
Imagine a "Darwin Awards" for Texans - particularly the ultra-right wing & Elon Musk.
This may be the best article you read this week.
☑️ The 2026 Bum Steer Awards
https://www.texasmonthly.com/being-texan/bum-steer-awards-2026/
@NFL@darktundra.xyz2026-01-27 21:26:14
Vikings announcer apologizes for comments critical of Minneapolis ICE protesters https://www.nytimes.com/athletic/7002163/2026/01/27/paul-allen-vikings-ice-protesters-comments/
@wrog@mastodon.murkworks.net2025-12-28 00:30:23
(yes, I'm avoiding a link to Failbook):
@Techmeme@techhub.social2025-12-23 18:35:52
A federal judge grants a temporary injunction blocking a Texas law requiring mobile app stores to verify users' ages from taking effect on January 1 (Lauren Feiner/The Verge)
https://www.theverge.com/news/849752/texas-app-store-accounta…
@arXiv_physicsoptics_bot@mastoxiv.page2025-11-25 11:06:23
Experimental insights into data augmentation techniques for deep learning-based multimode fiber imaging: limitations and success
Jawaria Maqbool, M. Imran Cheema
https://arxiv.org/abs/2511.19072 https://arxiv.org/pdf/2511.19072 https://arxiv.org/html/2511.19072
arXiv:2511.19072v1 Announce Type: new
Abstract: Multimode fiber~(MMF) imaging using deep learning has high potential to produce compact, minimally invasive endoscopic systems. Nevertheless, it relies on large, diverse real-world medical data, whose availability is limited by privacy concerns and practical challenges. Although data augmentation has been extensively studied in various other deep learning tasks, it has not been systematically explored for MMF imaging. This work provides the first in-depth experimental and computational study on the efficacy and limitations of augmentation techniques in this field. We demonstrate that standard image transformations and conditional generative adversarial-based synthetic speckle generation fail to improve, or even deteriorate, reconstruction quality, as they neglect the complex modal interference and dispersion that results in speckle formation. To address this, we introduce a physical data augmentation method in which only organ images are digitally transformed, while their corresponding speckles are experimentally acquired via fiber. This approach preserves the physics of light-fiber interaction and enhances the reconstruction structural similarity index measure~(SSIM) by up to 17\%, forming a viable system for reliable MMF imaging under limited data conditions.
toXiv_bot_toot
@burningbecks@social.tchncs.de2025-12-23 15:20:47
Hatte die Band schon fast abgeschrieben - und dann kommt noch ein Album mit DIESEM Ohrwurmpotenzial... 🤘
#ThrashMetal
@brichapman@mastodon.social2025-11-25 02:59:56
This is awesome!! Thanks for sharing 🫶
https://flipping.rocks/@sunguramy/115607959076156137
@cdarwin@c.im2026-01-23 15:47:02
This week, in the space of a few hours at the World Economic Forum's annual meeting in Davos,
Trump first ruled out taking Greenland by force
and then removed the threat of new tariffs on eight European states standing in his way
- hailing instead an imaginary deal for the Arctic island with NATO chief Mark Rutte.
European leaders believe Trump backed down in part because
- in contrast to their more accommodating stance in last year's tariff negotiation…
@UP8@mastodon.social2025-11-04 01:51:16
🔬 Optical imaging technique unlocks hidden glycemic history for diabetes and cancer research
https://medicalxpress.com/news/2025-10-optical-imaging-technique-hidden-glycemic.html
@sean@scoat.es2026-01-23 15:39:07
I love taking the train, but the weaponized incompetence of VIA Rail makes wish I'd taken another type of transportation, nearly every time.
Current status: “I, like the other two agents you spoke to, can't actually help you in any way, but I assure you that once you're on the train, the staff will be able to help. It's *the algorithm* not us!”