WTF
lol we're promising them 324 billion dollars?
It's like six years of their government's entire budget,
including offsets for petro sales lmfao.
We'd be paying their government to exist through Inauguration day 2033
https://bsky.app/profile/shipwreck75.b…
Working on tempolocus, a tool that analyses time-series activity patterns to infer a user’s likely location.
In @…, we work with a large volume of social-network time series. Estimating users’ locations from these patterns is often a manual task.
I prototyped a Python module that combines potential locations with yearly activity …
Whenever I see these obvious offsets in #OpenStreetMap, I have this itch to move them so they align with each other. But since I am not a local, I won’t do so and will leave it to Greek OpenStreetMappers to reconcile. But yeah, the 100-meter offset looks bad.
Island of Skopelos, #Greece 🇬🇷:
Kitty Terminal Security PSA
If you are using the kitty terminal @…, go get your security update!
"The handle_compose_command() function in kitty/graphics.c performs bounds validation on composition offsets using unsigned 32-bit arithmetic that is subject to integer wrapping. An attacker who can write escape sequences to a kitty termin…
Holy. Fucking. Fuckballs.
This exploit is... insane.
> An unprivileged local user can write 4 controlled bytes into the page cache of any readable file on a Linux system, and use that to gain root
https://copy.fail/
Fun engineering problem I am currently facing: Generate a very long sine wave in ngscopeclient, accurately and in parallel, using only single-precision floating point and 32-bit integer math.
The current implementation, used in both the "sine" and "downconvert" filter, looks basically like (pseudocode with some stuff like scaling and offsets removed for simplicity)
double rate;
uint depth;
for GPU thread i in 0...depth-1
double tmp = (i * ra…
Enhanced nondipole momentum offsets in triple ionization of atoms driven by mid-infrared laser fields
Samuel James Praill, Georgios Petros Katsoulis, Daria Romero Torres, Agapi Emmanouilidou
https://arxiv.org/abs/2606.10837
MORSE-PI -- Flexible and artefact-free image reconstruction for structural and functional QSM and other phase-critical imaging applications
Barbara Dymerska, Oliver Josephs, Benjamin James, Vahid Malekian, Nadine N. Graedel, Martina F. Callaghan
https://arxiv.org/abs/2606.21336 https://arxiv.org/pdf/2606.21336 https://arxiv.org/html/2606.21336
arXiv:2606.21336v1 Announce Type: new
Abstract: Phase imaging applications such as QSM are highly sensitive to noise amplifications, phase singularities, and other artefacts, particularly in challenging scenarios such as ultra-high field (7T), under-sampled or single-echo acquisitions. We present a novel image reconstruction method, MORSE-PI, designed to produce high-SNR, artefact-free, and singularity-free phase images for both structural and functional phase-based brain imaging. MORSE-PI extends our previous approach, MORSE, by introducing a Virtual Reference Coil (VRC). The VRC is constructed as a linear combination of coil sensitivity maps, with correlations enhanced between coil elements using the noise covariance matrix. Such a VRC ensures robust signal support across the entire brain and is used to correct phase offsets in the MORSE-derived coil sensitivity estimates, resulting in artefact-free, high SNR phase. Compared to GRAPPA with ASPIRE phase correction, MORSE-PI demonstrates greater robustness to artefacts such as noise amplification and aliasing, and shows improved reproducibility in structural imaging at both 3T and 7T. Unlike ESPIRiT and GRAPPA combined with adaptive coil combination methods, MORSE-PI yields singularity-free phase maps. MORSE-PI enables high-SNR reconstructions even for the most challenging scenarios, such as single-echo EPI at 7T. Its efficient, containerised implementation using the Gadgetron framework supports deployment on the MRI scanner console during measurements. MORSE-PI offers a flexible and computationally efficient solution for generating high-SNR, artefact- and singularity-free phase images in both single- and multi-echo GRE and EPI acquisitions. This makes it particularly well-suited for structural and functional QSM, as well as other phase-based MRI applications. Its robustness and rapid computational time facilitate efficient deployment on scanners across field strengths.
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