Tootfinder

from my link log —
Async Rust in ScyllaDB: performance, pitfalls, profiling.
https://www.scylladb.com/2022/01/12/async-rust-in-practice-performance-pitfalls-profiling/
saved 2022-01-13

Async Rust in Practice: Performance, Pitfalls, Profiling
Learn how our developers used flamegraphs to diagnose and resolve performance issues in our Tokio framework based Rust driver.

Filings: Meta's board agreed to a $190M settlement with investors over claims that Zuckerberg and other board members mishandled the Cambridge Analytica scandal (Jef Feeley/Bloomberg)
https://www.bloomberg.com/news/articles/20

hmm i thought rachelbythebay.com has a complaint about colleagues not following a “make before break” rule when changing things
but i can’t find a post along those lines
i wonder if she used a different term for the idea or if i’m just remembering wrong

Estimating Spatially Resolved Radiation Fields Using Neural Networks
Felix Lehner, Pasquale Lombardo, Susana Castillo, Oliver Hupe, Marcus Magnor
https://arxiv.org/abs/2512.17654 https://arxiv.org/pdf/2512.17654 https://arxiv.org/html/2512.17654
arXiv:2512.17654v1 Announce Type: new
Abstract: We present an in-depth analysis on how to build and train neural networks to estimate the spatial distribution of scattered radiation fields for radiation protection dosimetry in medical radiation fields, such as those found in Interventional Radiology and Cardiology. Therefore, we present three different synthetically generated datasets with increasing complexity for training, using a Monte-Carlo Simulation application based on Geant4. On those datasets, we evaluate convolutional and fully connected architectures of neural networks to demonstrate which design decisions work well for reconstructing the fluence and spectra distributions over the spatial domain of such radiation fields. All used datasets as well as our training pipeline are published as open source in separate repositories.
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