Tootfinder

Best Practices for Machine Learning-Assisted Protein Engineering
Fabio Herrera-Rocha, David Medina-Ortiz, Fabian Mauz, Juergen Pleiss, Mehdi D. Davari
https://arxiv.org/abs/2507.07547

Best Practices for Machine Learning-Assisted Protein Engineering
Data-driven modeling based on Machine Learning (ML) is becoming a central component of protein engineering workflows. This perspective presents the elements necessary to develop effective, reliable, and reproducible ML models, and a set of guidelines for ML developments for protein engineering. This includes a critical discussion of software engineering good practices for development and evaluation of ML-based protein engineering projects, emphasizing supervised learning. These guidelines cover…

Best practices are contextual.
https://www.garfieldtech.com/blog/best-practices

Issue Tracking Ecosystems: Context and Best Practices
Lloyd Montgomery
https://arxiv.org/abs/2507.06704 https://arxiv.org/pdf/2507.06…

Issue Tracking Ecosystems: Context and Best Practices
Issue Tracking Systems (ITSs), such as GitHub and Jira, are popular tools that support Software Engineering (SE) organisations through the management of ``issues'', which represent different SE artefacts such as requirements, development tasks, and maintenance items. ITSs also support internal linking between issues, and external linking to other tools and information sources. This provides SE organisations key forms of documentation, including forwards and backwards traceability (e.g., Feature…

VerIF: Verification Engineering for Reinforcement Learning in Instruction Following
Hao Peng, Yunjia Qi, Xiaozhi Wang, Bin Xu, Lei Hou, Juanzi Li
https://arxiv.org/abs/2506.09942 …

VerIF: Verification Engineering for Reinforcement Learning in Instruction Following
Reinforcement learning with verifiable rewards (RLVR) has become a key technique for enhancing large language models (LLMs), with verification engineering playing a central role. However, best practices for RL in instruction following remain underexplored. In this work, we explore the verification challenge in RL for instruction following and propose VerIF, a verification method that combines rule-based code verification with LLM-based verification from a large reasoning model (e.g., QwQ-32B). …

Enhancing Quantum Software Development Process with Experiment Tracking
Mahee Gamage, Otso Kinanen, Jake Muff, Vlad Stirbu
https://arxiv.org/abs/2507.06990

Enhancing Quantum Software Development Process with Experiment Tracking
As quantum computing advances from theoretical promise to experimental reality, the need for rigorous experiment tracking becomes critical. Drawing inspiration from best practices in machine learning (ML) and artificial intelligence (AI), we argue that reproducibility, scalability, and collaboration in quantum research can benefit significantly from structured tracking workflows. This paper explores the application of MLflow in quantum research, illustrating how it enables better development pr…

This https://arxiv.org/abs/2406.14572 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

Bioptic B1: A Target-Agnostic Potency-Based Small Molecules Search Engine
Recent successes in virtual screening have been made possible by large models and extensive chemical libraries. However, combining these elements is challenging: the larger the model, the more expensive it is to run, making ultra-large libraries unfeasible. To address this, we developed a target-agnostic, efficacy-based molecule search model, which allows us to find structurally dissimilar molecules with similar biological activities. We used the best practices to design fast retrieval system, …

Deep Dive into #uv #Dockerfiles by #Astral: Image Size, Performance & Best Practices

If you’re interested in the best current practices for securing #SPA apps, then you should tune into our livestream today. Applies to #react #angular

TFW you build a site with @… and web platform standards (== semantic HTML, modern CSS, a little bit of JavaScript, and a dash of ARIA) and you look at Lighthouse for the first time …
Looks like industry best practices actually work. (Sorry for using my platform to ruin anyone’s day. 🥰) 🍋

Dredging up recollections of my experience as R6RS editor for my PLSS talk tomorrow.
https://2025.ecoop.org/details/plss-2025-papers/8/Do-Programming-Languages-Fulfill-Requirements-Should-They-

Don't Unwrap Options: There Are Better Ways #Rust
https://corrode.dev/blog/rust-option-handling-best-practices/

So #Gentoo #Python eclasses are pretty modern, in the sense that they tend to follow the best practices and standards, and eventually deal with deprecations. Nevertheless, they have a long history and carry quite some historical burden, particularly regarding to naming.
The key point is that the eclasses were conceived as a replacement for the old eclasses: "distutils" and "python". Hence, much like we revision ebuilds, I've named the matching eclasses "distutils-r1" and "python-r1". For consistency, I've also used the "-r1" suffix for the remaining eclasses introduced at the time: "python-any-r1", "python-single-r1" and "python-utils-r1" — even though there were never "r0"s.
It didn't take long to realize my first mistake. I've made the multi-impl eclass effectively the "main" eclass, probably largely inspired by the previous Gentoo recommendations. However, in the end I've found out that for the most use cases (i.e. where "distutils-r1" is not involved), there is no real need for multi-impl, and it makes things much harder. So if I were naming them today, I would have named it "python-multi", to indicate the specific use case — and either avoid designating a default at all, or made "python-single" the default.
What aged even worse is the "distutils-r1" eclass. Admittedly, back when it was conceived, distutils was still largely a thing — and there were people (like me) who avoided unnecessary dependency on setuptools. Of course, nowadays it has been entirely devoured by setuptools, and with #PEP517 even "setuptools" wouldn't be a good name anymore. Nowadays, people are getting confused why they are supposed to use "distutils-r1" for, say, Hatchling.
Admittedly, this is something I could have done differently — PEP517 support was a major migration, and involved an explicit switch. Instead of adding DISTUTILS_USE_PEP517 (what a self-contradictory name) variable, I could have forked the eclass. Why didn't I do that? Because there used to be a lot of code shared between the two paths. Of course, over time they diverged more, and eventually I've dropped the legacy support — but the opportunity to rename was lost.
In fact, as a semi-related fact, I've recognized another design problem with the eclass earlier — I should have gone for two eclasses rather than one: a "python-phase" eclass with generic sub-phase support, and a "distutils" (or later "python-pep517") implementing default sub-phases for the common backends. And again, this is precisely how I could have solved the code reuse problem when I introduced PEP517 support.
But then, I didn't anticipate how the eclasses would end up looking like in the end — and I can't really predict what new challenges the Python ecosystem is going to bring us. And I think it's too late to rename or split stuff — too much busywork on everyone.

Docker under Siege: Securing Containers in the Modern Era
Gogulakrishnan Thiyagarajan, Prabhudarshi Nayak
https://arxiv.org/abs/2506.02043 https://

Docker under Siege: Securing Containers in the Modern Era
Containerization, driven by Docker, has transformed application development and deployment by enhancing efficiency and scalability. However, the rapid adoption of container technologies introduces significant security challenges that require careful management. This paper investigates key areas of container security, including runtime protection, network safeguards, configuration best practices, supply chain security, and comprehensive monitoring and logging solutions. We identify common vulner…

The Protesters' Guide to #Smartphone #Security
https://www.

#7 🔍 Run regular security audits using #Larastan, #PHPStan and security checkers
https://

RewardBench 2: Advancing Reward Model Evaluation
Saumya Malik, Valentina Pyatkin, Sander Land, Jacob Morrison, Noah A. Smith, Hannaneh Hajishirzi, Nathan Lambert
https://arxiv.org/abs/2506.01937

RewardBench 2: Advancing Reward Model Evaluation
Reward models are used throughout the post-training of language models to capture nuanced signals from preference data and provide a training target for optimization across instruction following, reasoning, safety, and more domains. The community has begun establishing best practices for evaluating reward models, from the development of benchmarks that test capabilities in specific skill areas to others that test agreement with human preferences. At the same time, progress in evaluation has not…

How to secure your phone before joining a protest
✅ The Protesters' Guide to Smartphone Security
https://www.privacyguides.org/articles/2025/01/23/activists-guide-securing-your-smartphone/

The Protesters' Guide to Smartphone Security
Your phone is an essential tool, but it also represents a huge risk to your privacy and security. Understanding these best practices when it comes to securing your smartphone will help keep you and your data safe.

Our partner conference, MICES – Mix-Camp E-Commerce Search, takes place on June 18th at TUECHTIG in Berlin. Focusing on e-commerce search, MICES brings together experts from various fields such as IT, product management, UX design, search management, information retrieval, data science and search engine vendors to discuss challenges, share ideas, best practices and case studies in e-commerce search.
Register for free and learn more here:

Modeling the Mass Distribution and Gravitational Potential of Nearby Disk Galaxies: Implications for the ISM Dynamical Equilibrium
Vivek Vijayakumar, Jiayi Sun, Eve C. Ostriker, Enrico M. Di Teodoro, Konstantin Haubner, Chang-Goo Kim, Adam K. Leroy, Miguel Querejeta
https://arxiv.org/abs/2506.22381…

Modeling the Mass Distribution and Gravitational Potential of Nearby Disk Galaxies: Implications for the ISM Dynamical Equilibrium
We characterize stellar, gas, and dark matter mass distributions for 17 nearby massive disk galaxies from the PHANGS sample. This allows us to compute the gravitational potential that vertically confines the interstellar gas and determines its equilibrium scale height and weight. We first combine dynamical mass constraints from existing CO and HI rotation curves together with stellar and gas mass estimates from near-infrared, CO, and HI data. These estimates incorporate current best practices i…

Breaking Out from the TESSERACT: Reassessing ML-based Malware Detection under Spatio-Temporal Drift
Theo Chow, Mario D'Onghia, Lorenz Linhardt, Zeliang Kan, Daniel Arp, Lorenzo Cavallaro, Fabio Pierazzi
https://arxiv.org/abs/2506.23814

Breaking Out from the TESSERACT: Reassessing ML-based Malware Detection under Spatio-Temporal Drift
Several recent works focused on the best practices for applying machine learning to cybersecurity. In the context of malware, TESSERACT highlighted the impact of concept drift on detection performance and suggested temporal and spatial constraints to be enforced to ensure realistic time-aware evaluations, which have been adopted by the community. In this paper, we demonstrate striking discrepancies in the performance of learning-based malware detection across the same time frame when evaluated …

CI/CD #Pipeline #Architecture: Complete Guide to Building Robust CI and CD Pipelines
https://

Join Kevin Liang at this year's Berlin Buzzwords, where he will discuss how Apache Solr/Lucene builds dense vector indexes and talk about how he and his team optimised their dense vector setup, sharing the challenges they faced and the best practices they learned along the way.
Learn more: https…