Tootfinder

De VS kan natuurlijk niet onze "vriend" en bondgenoot blijven als alle basisprincipes van democratie en rechtstaat worden geschonden. Naast dat de VS Putin helpt waar ze kan.
https://www.nu.nl/verkiezingen-vs/6369782/

Trump eist dat justitie politieke vijanden vervolgt: 'We kunnen niet wachten'
De Amerikaanse president Donald Trump heeft zijn minister van Justitie Pam Bondi zaterdag via sociale media opgedragen zijn politieke vijanden te vervolgen. In een post op Truth Social met de aanhef "Pam" zei hij: "We kunnen niet langer wachten."

A variational phase-field model for anisotropic fracture accounting for multiple cohesive lengths
Angela Maria Fajardo Lacave, Francesco Vicentini, Fabian Welschinger, Laura De Lorenzis
https://arxiv.org/abs/2510.11309

A variational phase-field model for anisotropic fracture accounting for multiple cohesive lengths
We propose a novel variational phase-field model for fracture in anisotropic materials. The model is specifically designed to allow a more flexible calibration of crack nucleation than existing anisotropic fracture formulations, while avoiding the introduction of multiple damage variables. In addition to the classical components of anisotropic phase-field models based on a single damage variable -- namely, anisotropic elasticity and the extension of the fracture energy density via a second-orde…

Robust Measurement of Stellar Streams Around the Milky Way: Correcting Spatially Variable Observational Selection Effects in Optical Imaging Surveys
K. Boone, P. S. Ferguson, M. Tabbutt, K. Bechtol, T. -Y. Cheng, A. Drlica-Wagner, C. E. Mart\'inez-V\'azquez, B. Mutlu-Pakdil, T. M. C. Abbott, O. Alves, F. Andrade-Oliveira, D. Bacon, S. Bocquet, D. Brooks, R. Camilleri, A. Carnero Rosell, L. N. da Costa, M. E. da Silva Pereira, T. M. Davis, J. De Vicente, S. Desai, P. Doel, S. Ev…

Robust Measurement of Stellar Streams Around the Milky Way: Correcting Spatially Variable Observational Selection Effects in Optical Imaging Surveys
Observations of density variations in stellar streams are a promising probe of low-mass dark matter substructure in the Milky Way. However, survey systematics such as variations in seeing and sky brightness can also induce artificial fluctuations in the observed densities of known stellar streams. These variations arise because survey conditions affect both object detection and star-galaxy misclassification rates. To mitigate these effects, we use Balrog synthetic source injections in the Dark …

Recovering Individual-Level Activity Sequences from Location-Based Service Data Using a Novel Transformer-Based Model
Weiyu Luo, Chenfeng Xiong
https://arxiv.org/abs/2508.02734 …

Recovering Individual-Level Activity Sequences from Location-Based Service Data Using a Novel Transformer-Based Model
Location-Based Service (LBS) data provides critical insights into human mobility, yet its sparsity often yields incomplete trip and activity sequences, making accurate inferences about trips and activities difficult. We raise a research problem: Can we use activity sequences derived from high-quality LBS data to recover incomplete activity sequences at the individual level? This study proposes a new solution, the Variable Selection Network-fused Insertion Transformer (VSNIT), integrating the In…

Mooi voorbeeld wat ChatGPT prima kan , waarom Athene niet zo'n mooi stadscentrum heeft en Rome wel, alle factoren op een rijtje. Dat er wellicht kleine onbetrouwbaarheden in zitten is op vakantie geen ramp 😃
https://chatgpt.com/s/t_6890df7e038c8191b0599cbdfc821e9e

ChatGPT - Desigualdad y frustración global
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A Stability-Driven Framework for Long-Term Hourly Electricity Demand Forecasting
Soumyadeep Dhar, Ayushkumar Parmar, Haifeng Qiu, Juan Ramon L. Senga, S. Viswanathan
https://arxiv.org/abs/2507.15001

A Stability-Driven Framework for Long-Term Hourly Electricity Demand Forecasting
Long-term electricity demand forecasting is essential for grid and operations planning, as well as for the analysis and planning of energy transition strategies. However, accurate long-term load forecasting with high temporal resolution remains challenging, as most existing approaches focus on aggregated forecasts, which require accurate prediction of numerous variables for bottom-up sectoral forecasts. In this study, we propose a parsimonious methodology that employs t-tests to verify load sta…

Boolean and Free Symmetrization of Bernoulli Laws
Sukrit Chakraborty
https://arxiv.org/abs/2508.17112 https://arxiv.org/pdf/2508.17112

Boolean and Free Symmetrization of Bernoulli Laws
We revisit the notion of \emph{symmetrizers} for Bernoulli random variables, originally studied in the classical convolution setting by Harremoës and Vignat \cite{HarremoesVignat2008} and later refined in Dossani \cite{Dossani2008}. In the classical case, an asymmetric Bernoulli distribution is \emph{symmetry resistant}: any independent symmetrizer must have variance at least $pq$, where $p$ is the Bernoulli parameter and $q=1-p$. We prove an analogous result for \emph{Boolean convolution}, sh…

Lung Cancer Survival Prediction Using Machine Learning and Statistical Methods
Varun Vishwanathan Nair, Victor Miranda Soberanis
https://arxiv.org/abs/2510.01267 https://…

Lung Cancer Survival Prediction Using Machine Learning and Statistical Methods
Lung cancer remains one of the leading causes of cancer-related mortality, yet most survival models rely only on baseline factors and overlook posttreatment variables that reflect disease progression. To address this gap, we applied Cox Proportional Hazards and Random Survival Forests, integrating baseline features with post-treatment predictors such as progression-free interval (PFI.time) and residual tumor status. The Cox model achieved a concordance index (C-index) of 0.90, while the RSF mod…