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@playinprogress@assemblag.es
2025-06-12 06:08:35

#photography #bloomScrolling #red

horizontal closeup of three deep red poppy flowers against a light background, illuminated by diffuse daylight from behind
horizontal closeup of three deep red poppy flowers against a light background, illuminated by diffuse daylight from behind, with one of them taking up most of the picture space and showing its black inner markings
horizontal closeup of two deep red poppy flowers, illuminated by diffuse daylight from the left, with the left one showing its dark patterned insides
closeup of two deep red poppy flowers illuminated by diffuse daylight against a vague grey background, with the image focusing on the foremost edges of the petals closest to the camera
@EgorKotov@datasci.social
2025-08-10 23:26:51

Get 9-30x speed doing areal-weighted interpolation with my new {𝐝𝐮𝐜𝐤𝐬𝐟} #rstats package compared to {sf}/{areal}. Experimental, but tested against both {areal} and {sf}. github.com/e-kotov/ducksf . Despite…

Benchmark scatter plot comparing areal-weighted interpolation runtimes (seconds) vs. peak memory use (MB) for three R package backends. {ducksf} with DuckDB backend is fastest (8.3s, 240MB, bottom left, green). {geosareal} with GEOS backend is mid-range (35.2s, 623MB, center, blue). {areal} with sf backend is slowest (230.7s, 1546MB, top right, orange). Ducksf logo in top-left corner.
Benchmark scatter plot comparing areal-weighted interpolation runtimes (seconds) vs. peak memory use (MB) for three R package backends. {ducksf} with DuckDB backend is fastest (8.3s, 240MB, bottom left, green). {geosareal} with GEOS backend is mid-range (35.2s, 623MB, center, blue). {areal} with sf backend is slowest (230.7s, 1546MB, top right, orange). Ducksf logo in top-left corner.
Benchmark scatter plot comparing areal-weighted interpolation runtimes (seconds) vs. peak memory use (MB) for three R package backends. {ducksf} with DuckDB backend is fastest (30.6s, 240MB, bottom left, green). {geosareal} with GEOS backend is mid-range (35.9s, 623MB, center, blue). {areal} with sf backend is slowest (284.1s, 1581MB, top right, orange). Ducksf logo in top-left corner.
@DominikDammer@mastodon.gamedev.place
2025-06-12 17:45:48

OH MY GOD!
There will be a second Spaceballs movie!!!
msn.com/en-us/video/peopleandp

@jamie@boothcomputing.social
2025-08-09 23:21:14

The table's final dry fit. It's almost perfectly level which was one thing I was worried about.
Also, the glue up with shims.
Tomorrow, the finishing goes on and it should be ready to attach the top
#woodworking
#inprogress

table dry fitted with a level across the front legs showing it is level.
table dry fitted with a level across the right side legs showing it is level.
final image of the table dry fit standing iny garage.
table with glue applied and shims in place. it's ready to dry overnight.
@stefan@gardenstate.social
2025-07-12 14:35:45

Find the lie.
tumblr.com/hashtagloveloses/78

hashtagloveloses there's something to be said about movies like kpop demon hunters, turning red, encanto, over the moon, and sinners, which combine music and cultural specificity into engaging storytelling. you don't need to just take "inspiration" from a culture. you can tell a specific story about it that everyone will be able to relate to even if they are unfamiliar with the specifics, because there are human elements we can all relate to in well-told stories.
@arXiv_csLO_bot@mastoxiv.page
2025-08-12 08:29:53

A Rule-Based Approach to Specifying Preferences over Conflicting Facts and Querying Inconsistent Knowledge Bases
Meghyn Bienvenu, Camille Bourgaux, Katsumi Inoue, Robin Jean
arxiv.org/abs/2508.07742

A Rule-Based Approach to Specifying Preferences over Conflicting Facts and Querying Inconsistent Knowledge Bases
Repair-based semantics have been extensively studied as a means of obtaining meaningful answers to queries posed over inconsistent knowledge bases (KBs). While several works have considered how to exploit a priority relation between facts to select optimal repairs, the question of how to specify such preferences remains largely unaddressed. This motivates us to introduce a declarative rule-based framework for specifying and computing a priority relation between conflicting facts. As the express…

@arXiv_csPL_bot@mastoxiv.page
2025-09-12 07:57:29

Dependent-Type-Preserving Memory Allocation
Paulette Koronkevich, William J. Bowman
arxiv.org/abs/2509.09059 arxiv.org/pdf/2509.09059

Dependent-Type-Preserving Memory Allocation
Dependently typed programming languages such as Coq, Agda, Idris, and F*, allow programmers to write detailed specifications of their programs and prove their programs meet these specifications. However, these specifications can be violated during compilation since they are erased after type checking. External programs linked with the compiled program can violate the specifications of the original program and change the behavior of the compiled program -- even when compiled with a verified comp…

@hynek@mastodon.social
2025-07-12 09:49:42

ep2025.europython.eu/session/w

Ralph Wiggum *chuckles* I’m in danger.
@macandi@social.heise.de
2025-08-12 10:13:00

Add-on in Alu: Zwei Thunderbolt-5-SSDs für Mac Studio und Mac mini M4
Beelink, bekannt für seine PC-Nachbauten des Mac mini, hat neue SSD-Docks für zwei Desktop-Macs vorgestellt – mit interessanten Spezifikationen.

Add-on in Alu: Zwei Thunderbolt-5-SSDs für Mac Studio und Mac mini M4
Beelink, bekannt für seine PC-Nachbauten des Mac mini, hat neue SSD-Docks für zwei Desktop-Macs vorgestellt – mit interessanten Spezifikationen.

@kurt@nelson.fun
2025-08-11 22:50:03

For anyone who is getting fed-up with the "e-bike" riding couriers who make all cyclists look horrible, turns out the main company leasing them is HMP Bikes and is trying to call them Class 2s when they have stubby little pedals you basically can't use. They are taking advantage of immigrants.

Yes, San Francisco Does Have an E-bike Problem. But It’s Specific to a Type of Bike (and Rider)
Food app delivery drivers on their glorified e-mopeds have brought a certain danger to San Francisco's bike lanes.