Tootfinder

#rijeka #croatia
https://ostblog.hypotheses.org/8288

#Windows zu #Linux von einem nicht-technichen Wissenschaftler

Por que é hora de colocar a ética e a humanidade no centro da educação em engenharia
#etica #filosofia

Por que é hora de colocar a ética e a humanidade no centro da educação em engenharia
Milad Haghani, Stephan Winter e Abbas Rajabifard HAGHANI, Milad; WINTER, Stephan; RAJABIFARD, Abbas. Por que é hora de colocar a ética e a humanidade no centro da educação em engenharia. (trad. Marcio Miotto e...

Das Wiener Amerlinghaus feiert heute seinen Fünfziger – ich gratuliere mit dem kurzen Hinweis auf eine noch offene Hausnummernfrage: https://nummer.hypotheses.org/651

QuantumBoost: A lazy, yet fast, quantum algorithm for learning with weak hypotheses
Amira Abbas, Yanlin Chen, Tuyen Nguyen, Ronald de Wolf
https://arxiv.org/abs/2510.05089 https…

QuantumBoost: A lazy, yet fast, quantum algorithm for learning with weak hypotheses
The technique of combining multiple votes to enhance the quality of a decision is the core of boosting algorithms in machine learning. In particular, boosting provably increases decision quality by combining multiple weak learners-hypotheses that are only slightly better than random guessing-into a single strong learner that classifies data well. There exist various versions of boosting algorithms, which we improve upon through the introduction of QuantumBoost. Inspired by classical work by Bar…

Unifying Deductive and Abductive Reasoning in Knowledge Graphs with Masked Diffusion Model
Yisen Gao, Jiaxin Bai, Yi Huang, Xingcheng Fu, Qingyun Sun, Yangqiu Song
https://arxiv.org/abs/2510.11462

Unifying Deductive and Abductive Reasoning in Knowledge Graphs with Masked Diffusion Model
Deductive and abductive reasoning are two critical paradigms for analyzing knowledge graphs, enabling applications from financial query answering to scientific discovery. Deductive reasoning on knowledge graphs usually involves retrieving entities that satisfy a complex logical query, while abductive reasoning generates plausible logical hypotheses from observations. Despite their clear synergistic potential, where deduction can validate hypotheses and abduction can uncover deeper logical patte…

Two-cardinal Kurepa Hypotheses
Fanxin Wu
https://arxiv.org/abs/2510.08860 https://arxiv.org/pdf/2510.08860

Two-cardinal Kurepa Hypotheses
We consider the two-cardinal Kurepa Hypothesis $\mathsf{KH}(κ,λ)$. We observe that if $κ\leqλ<μ$ are infinite cardinals then $\lnot\mathsf{KH}(κ,λ)\land\mathsf{KH}(κ,μ)\rightarrow\mathsf{KH}(λ^+,μ)$, and show that in some sense this is the only $\mathsf{ZFC}$ constraint. The case of singular $λ$ and its relation to Chang's Conjecture and scales is discussed. We also extend an independence result about Kurepa and Aronszajn trees due to Cummings to the case of successors of singular c…

A doubly composite Chernoff-Stein lemma and its applications
Ludovico Lami
https://arxiv.org/abs/2510.06342 https://arxiv.org/pdf/2510.06342

A doubly composite Chernoff-Stein lemma and its applications
Given a sequence of random variables $X^n=X_1,\ldots, X_n$, discriminating between two hypotheses on the underlying probability distribution is a key task in statistics and information theory. Of interest here is the Stein exponent, i.e. the largest rate of decay (in $n$) of the type II error probability for a vanishingly small type I error probability. When the hypotheses are simple and i.i.d., the Chernoff-Stein lemma states that this is given by the relative entropy between the single-copy p…

Asymptotic distributions of four linear hypotheses test statistics under generalized spiked model
Zhijun Liu, Jiang Hu, Zhidong Bai, Zhihui Lv
https://arxiv.org/abs/2510.04185 h…

Asymptotic distributions of four linear hypotheses test statistics under generalized spiked model
In this paper, we establish the Central Limit Theorem (CLT) for linear spectral statistics (LSSs) of large-dimensional generalized spiked sample covariance matrices, where the spiked eigenvalues may be either bounded or diverge to infinity. Building upon this theorem, we derive the asymptotic distributions of linear hypothesis test statistics under the generalized spiked model, including Wilks' likelihood ratio test statistic U, the Lawley-Hotelling trace test statistic W, and the Bartlett-Nand…

AI Agents as Universal Task Solvers
Alessandro Achille, Stefano Soatto
https://arxiv.org/abs/2510.12066 https://arxiv.org/pdf/2510.12066

AI Agents as Universal Task Solvers
AI reasoning agents are already able to solve a variety of tasks by deploying tools, simulating outcomes of multiple hypotheses and reflecting on them. In doing so, they perform computation, although not in the classical sense -- there is no program being executed. Still, if they perform computation, can AI agents be universal? Can chain-of-thought reasoning solve any computable task? How does an AI Agent learn to reason? Is it a matter of model size? Or training dataset size? In this work, w…

Inference in pseudo-observation-based regression using (biased) covariance estimation and naive bootstrapping
Simon Mack, Morten Overgaard, Dennis Dobler
https://arxiv.org/abs/2510.06815

Inference in pseudo-observation-based regression using (biased) covariance estimation and naive bootstrapping
We demonstrate that the usual Huber-White estimator is not consistent for the limiting covariance of parameter estimates in pseudo-observation regression approaches. By confirming that a plug-in estimator can be used instead, we obtain asymptotically exact and consistent tests for general linear hypotheses in the parameters of the model. Additionally, we confirm that naive bootstrapping can not be used for covariance estimation in the pseudo-observation model either. However, it can be used for…

Mephisto: Self-Improving Large Language Model-Based Agents for Automated Interpretation of Multi-band Galaxy Observations
Zechang Sun, Yuan-Sen Ting, Yaobo Liang, Nan Duan, Song Huang, Zheng Cai
https://arxiv.org/abs/2510.08354

Mephisto: Self-Improving Large Language Model-Based Agents for Automated Interpretation of Multi-band Galaxy Observations
Astronomical research has long relied on human expertise to interpret complex data and formulate scientific hypotheses. In this study, we introduce Mephisto -- a multi-agent collaboration framework powered by large language models (LLMs) that emulates human-like reasoning for analyzing multi-band galaxy observations. Mephisto interfaces with the CIGALE codebase (a library of spectral energy distribution, SED, models) to iteratively refine physical models against observational data. It conducts …

How Internal Structure Shapes the Metallicity of Giant Exoplanets
Lorenzo Peerani, Saburo Howard, Ravit Helled
https://arxiv.org/abs/2510.08280 https://arx…

How Internal Structure Shapes the Metallicity of Giant Exoplanets
The composition and internal structure of gas giant exoplanets encode key information about their formation and subsequent evolution. We investigate how different interior structure assumptions affect the inferred bulk metallicity and its correlation with planetary mass. For a sample of 44 giant exoplanets (0.12-5.98 MJ), we compute evolutionary models with CEPAM and retrieve their bulk metallicities under three structural hypotheses: Core+Envelope (CE), Dilute Core (DC), and Fully Mixed (FM). …

Generalized Pseudo-Hopf Bifurcation: Limit Cycle Position and Period
Lucas Queiroz Arakaki, Douglas Novaes, Paulo Santana
https://arxiv.org/abs/2510.05269 https://

Generalized Pseudo-Hopf Bifurcation: Limit Cycle Position and Period
We investigate planar piecewise-smooth vector fields with a discontinuity line, focusing on the bifurcation of crossing limit cycles that arise when one of the vector fields is translated along the discontinuity set. We establish topological conditions under which such bifurcations occur and, under additional generic hypotheses, derive precise asymptotic expressions for both the position and the period of the resulting limit cycle in terms of the perturbation parameter. Our results extend the c…

First experimental measurements of biophotons from Astrocytes and Glioblastoma cell cultures
L. De Paolis, E. Pace, C. Mazzanti, M. Morelli, F. Di Lorenzo, L. Tonello, C. Curceanu, A. Clozza, M. Grandi, I. Davoli, A. Gemignani, P. Grigolini, M. Benfatto
https://arxiv.org/abs/2510.05792

First experimental measurements of biophotons from Astrocytes and Glioblastoma cell cultures
Biophotons are non-thermal and non-bioluminescent ultraweak photon emissions, first hypothesised by Gurwitsch in 1924 as a regulatory mechanism in cell division, and then experimentally observed in living organisms. Today, two main hypotheses explain their origin: stochastic decay of excited molecules and coherent electromagnetic fields produced in biochemical processes. Recent interest focuses on the role of biophotons in cellular communication and disease monitoring. This study presents the f…

On the Possibility of Melting Water Ice during the Recent Past of Mars. Application to the Formation of Gullies
Lucas Lange, Francois Forget
https://arxiv.org/abs/2510.06154 htt…

On the Possibility of Melting Water Ice during the Recent Past of Mars. Application to the Formation of Gullies
The formation of gullies on Mars has often been attributed to the melting of (sub)surface water ice. However, melting-based hypotheses generally overlook key processes: (1) sublimation cooling by latent heat absorption, (2) the non-stability of ice where melting conditions can be reached, and (3) the particular microclimates of gullied slopes. Using state-of-the-art climate simulations, we reassess ice melting scenarios over the past four million years (obliquity $\le$35\textdegree)), beyond th…

A Mixed-Methods Analysis of Repression and Mobilization in Bangladesh's July Revolution Using Machine Learning and Statistical Modeling
Md. Saiful Bari Siddiqui, Anupam Debashis Roy
https://arxiv.org/abs/2510.06264

A Mixed-Methods Analysis of Repression and Mobilization in Bangladesh's July Revolution Using Machine Learning and Statistical Modeling
The 2024 July Revolution in Bangladesh represents a landmark event in the study of civil resistance. This study investigates the central paradox of the success of this student-led civilian uprising: how state violence, intended to quell dissent, ultimately fueled the movement's victory. We employ a mixed-methods approach. First, we develop a qualitative narrative of the conflict's timeline to generate specific, testable hypotheses. Then, using a disaggregated, event-level dataset, we employ a m…