Tootfinder

Un biais systémique vers le dogme de la "croissance robuste"

Une cécité organisée sur les patrimoines des plus riches

Le refus méthodique de chiffrer fidèlement les effets délétères de leurs propres politiques fiscales
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Le gouvernement fabrique délibérément les conditions du déficit et l'utilise comme justification de l'austérité sociale
Bref, une politique fiscale qui fait payer aux classes moyennes le coût de l'intouchabilité f…

Impôts : les mauvais comptes du gouvernement
TVA, contribution sur les hauts revenus, taxe sur les superprofits… : les gouvernements Macron accumulent depuis 2023 les erreurs de prévision sur les rentrées fiscales. Pas étonnant, dès lors, que les déficits publics soient élevés. 

D05 - Animals
CAPTAIN: One of our pursuit units engaged an unidentified planet hopper. They refused to obey a stand and be searched order and the pursuit commander opened fire.
SERVALAN: Why all the interest? What's one civilian cargo ship more or less?
https://blake.torpidity.net/m/405/97

Rust's Block Pattern
Here’s a little idiom that I haven’t really seen discussed anywhere, that I think makes Rust code much cleaner and more robust.
— by @…
🦀 https://notgull.net/block-pattern/<…

Another evening of filter refactoring and optimization, a few more nice performance jumps.
I've now done a first pass (remove deprecated method signatures, add explicit input location, add NVTX trace data, do easy GPU optimization if I see an obvious low effort win) on all filters A-F alphabetically plus a few later on that were priorities for one reason or other.
90 down (of which 23 were optimized and the rest just refactored), 115 to go.
Some of the remaining ones sh…

Revised January 8, 2026: Simulation of prosthetic vision with the PRIMA system and enhancement of face representation https://arxiv.org/abs/2503.11677 retinal implant

Simulation of prosthetic vision with PRIMA system and enhancement of face representation
Objective. Patients implanted with the PRIMA photovoltaic subretinal prosthesis in geographic atrophy report form vision with the average acuity matching the 100um pixel size. Although this remarkable outcome enables them to read and write, they report difficulty with perceiving faces. Despite the pixelated stimulation, patients see smooth patterns rather than dots. We present a novel, non-pixelated algorithm for simulating prosthetic vision, compare its predictions to clinical outcomes, and de…

Jš que colocaram três dias de desfile de escola de samba, poderiam colocar cinco escolas por dia. Hš espaço para 15 escolas no grupo especial, diminuindo o risco de escola gigantesca ser rebaixada ao menor tropeço.

Approximate Cartesian Tree Matching with Substitutions
Panagiotis Charalampopoulos, Jonas Ellert, Manal Mohamed
https://arxiv.org/abs/2602.08570 https://arxiv.org/pdf/2602.08570 https://arxiv.org/html/2602.08570
arXiv:2602.08570v1 Announce Type: new
Abstract: The Cartesian tree of a sequence captures the relative order of the sequence's elements. In recent years, Cartesian tree matching has attracted considerable attention, particularly due to its applications in time series analysis. Consider a text $T$ of length $n$ and a pattern $P$ of length $m$. In the exact Cartesian tree matching problem, the task is to find all length-$m$ fragments of $T$ whose Cartesian tree coincides with the Cartesian tree $CT(P)$ of the pattern. Although the exact version of the problem can be solved in linear time [Park et al., TCS 2020], it remains rather restrictive; for example, it is not robust to outliers in the pattern.
To overcome this limitation, we consider the approximate setting, where the goal is to identify all fragments of $T$ that are close to some string whose Cartesian tree matches $CT(P)$. In this work, we quantify closeness via the widely used Hamming distance metric. For a given integer parameter $k>0$, we present an algorithm that computes all fragments of $T$ that are at Hamming distance at most $k$ from a string whose Cartesian tree matches $CT(P)$. Our algorithm runs in time $\mathcal O(n \sqrt{m} \cdot k^{2.5})$ for $k \leq m^{1/5}$ and in time $\mathcal O(nk^5)$ for $k \geq m^{1/5}$, thereby improving upon the state-of-the-art $\mathcal O(nmk)$-time algorithm of Kim and Han [TCS 2025] in the regime $k = o(m^{1/4})$.
On the way to our solution, we develop a toolbox of independent interest. First, we introduce a new notion of periodicity in Cartesian trees. Then, we lift multiple well-known combinatorial and algorithmic results for string matching and periodicity in strings to Cartesian tree matching and periodicity in Cartesian trees.
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T1: One-to-One Channel-Head Binding for Multivariate Time-Series Imputation
Dongik Park, Hyunwoo Ryu, Suahn Bae, Keondo Park, Hyung-Sin Kim
https://arxiv.org/abs/2602.21043 https://arxiv.org/pdf/2602.21043 https://arxiv.org/html/2602.21043
arXiv:2602.21043v1 Announce Type: new
Abstract: Imputing missing values in multivariate time series remains challenging, especially under diverse missing patterns and heavy missingness. Existing methods suffer from suboptimal performance as corrupted temporal features hinder effective cross-variable information transfer, amplifying reconstruction errors. Robust imputation requires both extracting temporal patterns from sparse observations within each variable and selectively transferring information across variables--yet current approaches excel at one while compromising the other. We introduce T1 (Time series imputation with 1-to-1 channel-head binding), a CNN-Transformer hybrid architecture that achieves robust imputation through Channel-Head Binding--a mechanism creating one-to-one correspondence between CNN channels and attention heads. This design enables selective information transfer: when missingness corrupts certain temporal patterns, their corresponding attention pathways adaptively down-weight based on remaining observable patterns while preserving reliable cross-variable connections through unaffected channels. Experiments on 11 benchmark datasets demonstrate that T1 achieves state-of-the-art performance, reducing MSE by 46% on average compared to the second-best baseline, with particularly strong gains under extreme sparsity (70% missing ratio). The model generalizes to unseen missing patterns without retraining and uses a consistent hyperparameter configuration across all datasets. The code is available at https://github.com/Oppenheimerdinger/T1.
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The Associated Press has uncovered a pattern where Bangladeshi workers are enticed to Russia under false pretences of civilian employment, subsequently coerced into combat roles.
Many of these individuals faced threats of violence, imprisonment, or even death if they refused.
h…

Bangladeshi workers lured to Russia for jobs tricked into fighting the war in Ukraine
Workers claim they were threatened with 10-year jail terms and beaten

Spain is modernising its grid codes so that generation, demand and storage can cope more robustly with volatility and actively contribute to a more stable power grid. It can no longer wait for the delayed new European grid codes.
https://www.miteco.gob.es/es/energia/parti…