May 2026

(1) Background. Food sovereignty and local sustainability are ensured by large agro-industrial holdings and small-scale farms; this is synergy forms a complementary model of the agrifood system. Maintaining this model’s balance requires the creation of a unified digital ecosystem that integrates all suppliers and consumers into production chains, thereby eliminating unnecessary intermediaries. (2) Methods. This study employs a comprehensive methodological framework, including systems analysis and mathematical modeling, to develop service algorithms. Object-oriented design and software engineering methods facilitated […]

Ver mais

This post is a practical companion to It’s 2026, Just Use Postgres. That post makes the architectural case for consolidating on Postgres. This one shows you how. Below are working SQL examples for each use case. Every extension listed here is available on Tiger Cloud with no additional setup. If you’re self-hosting, each section links to the extension’s repo. What you’ll be able to do after reading this: Set up Postgres extensions for full-text search, vector search, time-series, caching, message queues, document […]

Ver mais

Hi, I’m interested in geometric deep learning (due to Michael M. Bronstein’s book and Maurice Weiler’s PhD thesis), and in order not to write projects to nowhere, I decided to keep a technical blog. I started with a short note about machine learning on spherical manifolds, but it’s a pretty simple thing. Is there a list of some open problems on the topic of GDL, or maybe some of you are doing something in this direction and can […]

Ver mais

At RSA Conference this year there were 650+ security vendors. All of them were selling security products. Almost none of them were selling security practices. This distinction sounds academic. It isn’t. A security product gives you a tool and a dashboard. A security practice gives you a discipline that gets embedded into how your engineers work every day. The security industry has spent 30 years optimising for selling products. The result: organisations with extraordinary tooling and catastrophic outcomes. […]

Ver mais

grep finds things. cut and tr shape what you do with them. Most practitioners pick these up by accident — copy a one-liner from somewhere, it works, move on. But understanding what cut and tr actually do changes how you build pipelines. You stop reaching for awk when cut is enough. You stop writing substitution logic by hand when tr handles it in seconds. This article covers both tools from the ground up — what they do, every […]

Ver mais

AI does not make security impossible. It makes slow, static and periodic security obsolete. This is a long-form strategy article about how enterprise security changes when AI compresses the time between vulnerability discovery, exploit development, attack execution, remediation and validation. The core idea is simple: Post-AI Security starts by shrinking the time between detection, decision, remediation and validation. The starting point can be ugly and simple: better inventory, existing scanners, available live patching, ownership, and common sense in […]

Ver mais

arXiv:2605.19122v1 Announce Type: new Abstract: Tensor-valued data arise naturally in neuroimaging, genomics, climate science, and spatiotemporal networks, where multilinear dependencies across modes carry information that is destroyed under vectorization. Existing approaches either impose a single low-rank structure, which can miss localized signal, or treat the tensor as a long vector, which discards its multiway geometry. We propose a *Dual-Channel Tensor Neural Network* (DC-TNN) that decomposes each tensor input into a low-rank core and a sparse refinement, and processes […]

Ver mais

arXiv:2605.19052v1 Announce Type: new Abstract: Lagrangian Relaxation (LR) is a powerful technique for solving large-scale Mixed Integer Linear Programming (MILP), particularly those with decomposable structures, such as vehicle routing or unit commitment problems. By relaxing the coupling constraints, LR enables parallel subproblem solving and often yields tighter dual bounds than standard linear programming relaxations, which is crucial for efficient branch-and-bound pruning. While recent empirical work has shown promising results using machine learning to predict these multipliers, a theoretical […]

Ver mais

arXiv:2605.19024v1 Announce Type: new Abstract: Split conformal prediction provides finite-sample marginal coverage under exchangeability, but this guarantee averages over the random calibration sample. We study instead the law of the calibration-conditional coverage induced by a realized conformal threshold. In the continuous i.i.d. setting this law is exactly $Beta(k,n+1-k)$, so the usual marginal guarantee corresponds to its mean. We take this beta law as a finite-sample reference object and quantify departures from it using Wasserstein distances on $[0,1]$. The […]

Ver mais