Tootfinder

Blowing up NATO's foundation, right before its Summit:
"Trump refused to give a clear commitment to NATO’s Article 5 — its collective defense clause — as he departed for The Hague, raising fresh concerns about his stance on one of NATO’s core principles."
https://

Trump casts doubt on NATO defense pledge as alliance confronts Russian threat
Although Article 5 is central to NATO’s security framework, U.S. President Donald Trump has previously expressed skepticism about honoring it, often criticizing member states for not contributing enough to shared defense efforts.

Ransomware attack contributed to patient’s death, says Britain’s NHS
https://therecord.media/ransomware-attack-contributed-patient-death-uk-nhs

Ransomware attack contributed to patient’s death, says Britain’s NHS
A cybercrime group's attack against a London-based pathology service last year was one of the "contributing factors" in the death of a patient, U.K. officials said.

Adding equatorial-asymmetric effects for spin-precessing binaries into the SEOBNRv5PHM waveform model
H\'ector Estell\'es, Alessandra Buonanno, Raffi Enficiaud, Cheng Foo, Lorenzo Pompili
https://arxiv.org/abs/2506.19911

Adding equatorial-asymmetric effects for spin-precessing binaries into the SEOBNRv5PHM waveform model
Gravitational waves from spin-precessing binaries exhibit equatorial asymmetries absent in non-precessing systems, leading to net linear momentum emission and contributing to the remnant's recoil. This effect, recently incorporated into only a few waveform models, is crucial for accurate recoil predictions and improved parameter estimation. We present an upgrade to the SEOBNRv5PHM model -- SEOBNRv5PHM_w/asym -- which includes equatorial asymmetric contributions to the l=m<=4 waveform modes in t…

Nowhere left to hide: revealing realistic gravitational-wave populations in high dimensions and high resolution with PixelPop
Sofia Alvarez-Lopez, Jack Heinzel, Matthew Mould, Salvatore Vitale
https://arxiv.org/abs/2506.20731

Nowhere left to hide: revealing realistic gravitational-wave populations in high dimensions and high resolution with PixelPop
The origins of merging compact binaries observed by the LIGO-Virgo-KAGRA gravitational-wave detectors remain uncertain, with multiple astrophysical channels possibly contributing to the merger rate. Formation processes can imprint nontrivial correlations in the underlying distribution of source properties, but current understanding of the overall population relies heavily on simplified and uncorrelated parametric models. In this work, we use PixelPop-a high-resolution Bayesian nonparametric mod…

Electronic conduction in copper-graphene composites with functional impurities
Kishor Nepal, Ridwan Hussein, Yahya Al-Majali, David Drabold
https://arxiv.org/abs/2506.20912

Electronic conduction in copper-graphene composites with functional impurities
Coal-derived graphene-like material and its addition to FCC copper are investigated using ab initio plane wave density functional theory (DFT). We explore ring disorder in the sp2 carbon, and functional impurities such as oxides (-O), and hydroxides (-OH) that are common in coal-derived graphene. The electronic density of states analysis revealed localized states near the Fermi level, with functional groups contributing predominantly to states below the Fermi level, while carbon atoms in non-he…

This is a great initiative. Please check the GitHub link on the attached post if you use Linux on Tablet PC.
From: @…
https://floss.social/@kde/114745104649286…

Association between optically identified galaxy clusters and the underlying dark matter halos
DES Collaboration, Shulei Cao, Hao-Yi Wu, Matteo Costanzi, Arya Farahi, Sebastian Grandis, David H. Weinberg, August E. Evrard, Eduardo Rozo, Andr\'es N. Salcedo, Chun-Hao To, Lei Yang, Conghao Zhou
https://arxiv.org/abs/2506.17526

Association between optically identified galaxy clusters and the underlying dark matter halos
Clusters of galaxies trace massive dark matter halos in the Universe, but they can include multiple halos projected along lines of sight. We study the halos contributing to clusters using the Cardinal simulation, which mimics the Dark Energy Survey data. We use the red-sequence-based cluster finding algorithm redMaPPer as a case study. For each cluster, we identify the halos hosting its member galaxies, and we define the main halo as the one contributing the most to the cluster's richness ($λ$…

Automattic says it will resume contributing to the WordPress project, after announcing a pause in April (Sarah Perez/TechCrunch)
https://techcrunch.com/2025/05/30/automattic-says-it-will-start-contributing-to-wordpress-a…

Automattic says it will start contributing to WordPress again after pause | TechCrunch
WordPress.com parent company Automattic is changing direction... again.

Ransomware attack contributed to patient’s death, says Britain’s NHS https://therecord.media/ransomware-attack-contributed-patient-death-uk-nhs

Subtooting since people in the original thread wanted it to be over, but selfishly tagging @… and @… whose opinions I value...
I think that saying "we are not a supply chain" is exactly what open-source maintainers should be doing right now in response to "open source supply chain security" threads.
I can't claim to be an expert and don't maintain any important FOSS stuff, but I do release almost all of my code under open licenses, and I do use many open source libraries, and I have felt the pain of needing to replace an unmaintained library.
There's a certain small-to-mid-scale class of program, including many open-source libraries, which can be built/maintained by a single person, and which to my mind best operate on a "snake growth" model: incremental changes/fixes, punctuated by periodic "skin-shedding" phases where make rewrites or version updates happen. These projects aren't immortal either: as the whole tech landscape around them changes, they become unnecessary and/or people lose interest, so they go unmaintained and eventually break. Each time one of their dependencies breaks (or has a skin-shedding moment) there's a higher probability that they break or shed too, as maintenance needs shoot up at these junctures. Unless you're a company trying to make money from a single long-lived app, it's actually okay that software churns like this, and if you're a company trying to make money, your priorities absolutely should not factor into any decisions people making FOSS software make: we're trying (and to a huge extent succeeding) to make a better world (and/or just have fun with our own hobbies share that fun with others) that leaves behind the corrosive & planet-destroying plague which is capitalism, and you're trying to personally enrich yourself by embracing that plague. The fact that capitalism is *evil* is not an incidental thing in this discussion.
To make an imperfect analogy, imagine that the peasants of some domain have set up a really-free-market, where they provide each other with free stuff to help each other survive, sometimes doing some barter perhaps but mostly just everyone bringing their surplus. Now imagine the lord of the domain, who is the source of these peasants' immiseration, goes to this market secretly & takes some berries, which he uses as one ingredient in delicious tarts that he then sells for profit. But then the berry-bringer stops showing up to the free market, or starts bringing a different kind of fruit, or even ends up bringing rotten berries by accident. And the lord complains "I have a supply chain problem!" Like, fuck off dude! Your problem is that you *didn't* want to build a supply chain and instead thought you would build your profit-focused business in other people's free stuff. If you were paying the berry-picker, you'd have a supply chain problem, but you weren't, so you really have an "I want more free stuff" problem when you can't be arsed to give away your own stuff for free.
There can be all sorts of problems in the really-free-market, like maybe not enough people bring socks, so the peasants who can't afford socks are going barefoot, and having foot problems, and the peasants put their heads together and see if they can convince someone to start bringing socks, and maybe they can't and things are a bit sad, but the really-free-market was never supposed to solve everyone's problems 100% when they're all still being squeezed dry by their taxes: until they are able to get free of the lord & start building a lovely anarchist society, the really-free-market is a best-effort kind of deal that aims to make things better, and sometimes will fall short. When it becomes the main way goods in society are distributed, and when the people who contribute aren't constantly drained by the feudal yoke, at that point the availability of particular goods is a real problem that needs to be solved, but at that point, it's also much easier to solve. And at *no* point does someone coming into the market to take stuff only to turn around and sell it deserve anything from the market or those contributing to it. They are not a supply chain. They're trying to help each other out, but even then they're doing so freely and without obligation. They might discuss amongst themselves how to better coordinate their mutual aid, but they're not going to end up forcing anyone to bring anything or even expecting that a certain person contribute a certain amount, since the whole point is that the thing is voluntary & free, and they've all got changing life circumstances that affect their contributions. Celebrate whatever shows up at the market, express your desire for things that would be useful, but don't impose a burden on anyone else to bring a specific thing, because otherwise it's fair for them to oppose such a burden on you, and now you two are doing your own barter thing that's outside the parameters of the really-free-market.

Students' Reliance on AI in Higher Education: Identifying Contributing Factors
Griffin Pitts, Neha Rani, Weedguet Mildort, Eva-Marie Cook
https://arxiv.org/abs/2506.13845

Students' Reliance on AI in Higher Education: Identifying Contributing Factors
The increasing availability and use of artificial intelligence (AI) tools in educational settings has raised concerns about students' overreliance on these technologies. Overreliance occurs when individuals accept incorrect AI-generated recommendations, often without critical evaluation, leading to flawed problem solutions and undermining learning outcomes. This study investigates potential factors contributing to patterns of AI reliance among undergraduate students, examining not only overreli…

Join Andrew Musselman and Trevor Grant as they present the latest developments in Mahout's new quantum compute layer, Qumat. They will provide an overview of the project, explain why Qumat was developed, and demonstrate its current capabilities. They will also present a demo of Qumat in action and conclude with calls to action for researchers and engineers who are interested in using and contributing to the project.
Learn more:

Today was the Neos Contribution Day right after #NeosCon in Karlsruhe. The idea is that members of the @… Neos Team help interested people getting started with contributing to #NeosCMS

Learning from the Storm: A Multivariate Machine Learning Approach to Predicting Hurricane-Induced Economic Losses
Bolin Shen, Eren Erman Ozguven, Yue Zhao, Guang Wang, Yiqun Xie, Yushun Dong
https://arxiv.org/abs/2506.17964

Learning from the Storm: A Multivariate Machine Learning Approach to Predicting Hurricane-Induced Economic Losses
Florida is particularly vulnerable to hurricanes, which frequently cause substantial economic losses. While prior studies have explored specific contributors to hurricane-induced damage, few have developed a unified framework capable of integrating a broader range of influencing factors to comprehensively assess the sources of economic loss. In this study, we propose a comprehensive modeling framework that categorizes contributing factors into three key components: (1) hurricane characteristics…

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction
Shigan Liu, Guannan Geng, Yanfei Xiang, Hejun Hu, Xiaodong Liu, Xiaomeng Huang, Qiang Zhang
https://arxiv.org/abs/2506.18018

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction
Air pollution remains a leading global health threat, with fine particulate matter (PM2.5) contributing to millions of premature deaths annually. Chemical transport models (CTMs) are essential tools for evaluating how emission controls improve air quality and save lives, but they are computationally intensive. Reduced form models accelerate simulations but sacrifice spatial-temporal granularity, accuracy, and flexibility. Here we present CleanAir, a deep-learning-based model developed as an eff…

Park Discovery 🏞️
公园探险 🏞️
📷 Nikon FE
🎞️Lucky SHD 400
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Yiding Cao Geld mit PayPal.Me senden
Folgen Sie dem Link PayPal.Me/dingsterdingster und geben Sie den Betrag ein. Es ist bequem und sicher. Sie haben noch kein PayPal-Konto? Kein Problem.

The libxml2 maintainer is basically shrugging his shoulders and saying "deal with your own fucking security issues; libxml was never meant to be used in your projects" to google and the rest of the giant corporations that are using his labor without contributing back. I'm totally on board with that.
https://

Triaging security issues reported by third parties (#913) · Issues · GNOME / libxml2 · GitLab
I have to spend several hours each week dealing with security issues reported by third parties. Most of these issues aren't critical but it's still a lot of...

Millions of non-producing oil and gas wells around the world are leaking methane and other contaminants,
contributing to increased greenhouse gas emissions and polluting our water, soil, and air.
The total annual methane emissions from non-producing wells in Canada is 7 times higher than estimated in Canada’s National Inventory Report
The U.S. no longer even estimates it's methane emissions

SimSpark: Interactive Simulation of Social Media Behaviors
Ziyue Lin, Yi Shan, Lin Gao, Xinghua Jia, Siming Chen
https://arxiv.org/abs/2506.14476 https://

SimSpark: Interactive Simulation of Social Media Behaviors
Understanding user behaviors on social media has garnered significant scholarly attention, enhancing our comprehension of how virtual platforms impact society and empowering decision-makers. Simulating social media behaviors provides a robust tool for capturing the patterns of social media behaviors, testing hypotheses, and predicting the effects of various interventions, ultimately contributing to a deeper understanding of social media environments. Moreover, it can overcome difficulties assoc…

#linktipp
They Looted Companies — Now They're Looting the Government
Most executives are no longer rewarded for building durable businesses or contributing to the real economy—they’re rewarded for how efficiently they extract value from the companies that they control.
“Because these people have gotten away with looting corporations, they’ve come to believe it’s their right …

Neutrino Portal to Extra Dimensions: Unified Origin of Dark Radiation, Dark Matter, and Neutrino Decay
Arnab Chaudhuri
https://arxiv.org/abs/2506.15485 htt…

Neutrino Portal to Extra Dimensions: Unified Origin of Dark Radiation, Dark Matter, and Neutrino Decay
We propose a unified framework based on sterile neutrinos propagating in large extra dimensions (LED) and coupled to a pseudo-Nambu-Goldstone boson (Majoron) arising from spontaneous lepton number violation. In this setup, the lightest Kaluza-Klein (KK) sterile neutrino serves as warm dark matter, higher KK modes decay invisibly producing a relativistic Majoron contributing to the effective number of neutrino species (Delta Neff), and active neutrinos undergo invisible decay. This model address…

A good counter-explanation from @…, although it’s not entirely consistent with the data: if this were merely aging vehicles, we’d expect to see a slow, steady decline. But we don’t; we see a •very• sharp turnaround that coincides precisely with Musk’s fascism entering full public view, and not with any sort of sudden aging event in the vehicles.
But yes, surely normal depreciation is a contributing factor as well.
https://mstdn.ca/@alessandro/114637425697204963

In West-Nordamerika ist der Einfluss des Menschen auf das #Feuerwetter (heißes, trockenes, windreiches Wetter) jetzt messbar.
Zwischen 81 % und 188 % des Anstiegs in den letzten 50 Jahren gehen auf menschgemachte #Klimaveränderungen zurück.
Temperatur,

Fingerprint of anthropogenic climate change detected in long-term western North American fire weather trends - Communications Earth & Environment
Anthropogenic climate change has been the dominant driver of increasing fire weather trends in western North America over the past 50 years, contributing 81–188% of the observed linear trends, according to regional optimal fingerprinting applied to large ensembles of high-resolution climate models.

Mobility to Campus -- a Framework to Evaluate and Compare Different Mobility Modes
Helena Fehler, Marco Pruckner, Marie Schmidt
https://arxiv.org/abs/2506.13574

Mobility to Campus -- a Framework to Evaluate and Compare Different Mobility Modes
The transport sector accounts for about 20% of German CO2 emissions, with commuter traffic contributing a significant part. Particularly in rural areas, where public transport is inconvenient to use, private cars are a common choice for commuting and most commuters travel alone in their cars. Consolidation of some of these trips has the potential to decrease CO2 emissions and could be achieved, e.g., by offering ridesharing (commuters with similar origin-destination pairs share a car) or ridepo…

XDoppler axial velocity estimation using row-column arrays
Henri Leroy, Adrien Bertolo, Guillaume Goudot, Mickael Tanter, Thomas Deffieux, Mathieu Pernot
https://arxiv.org/abs/2506.15469

XDoppler axial velocity estimation using row-column arrays
Accurate volumetric velocity estimation in ultrasound imaging is crucial for applications in diagnostic and therapeutic medicine. Traditional ultrasound systems, while effective in two-dimensional imaging, face significant challenges in achieving 3D imaging due to hardware and computational demands. Row-column addressed (RCA) ultrasound probes present a promising alternative, reducing hardware complexity, thus contributing to bridge the gap between research and clinical systems. Yet, this usual…

Code-Switching and Syntax: A Large-Scale Experiment
Igor Sterner, Simone Teufel
https://arxiv.org/abs/2506.01846 https://arxiv.org/pd…

Code-Switching and Syntax: A Large-Scale Experiment
The theoretical code-switching (CS) literature provides numerous pointwise investigations that aim to explain patterns in CS, i.e. why bilinguals switch language in certain positions in a sentence more often than in others. A resulting consensus is that CS can be explained by the syntax of the contributing languages. There is however no large-scale, multi-language, cross-phenomena experiment that tests this claim. When designing such an experiment, we need to make sure that the system that is p…

A theoretical basis for model collapse in recursive training
Vivek Shripad Borkar
https://arxiv.org/abs/2506.09401 https://arxiv.org/…

A theoretical basis for model collapse in recursive training
It is known that recursive training from generative models can lead to the so called `collapse' of the simulated probability distribution. This note shows that one in fact gets two different asymptotic behaviours depending on whether an external source, howsoever minor, is also contributing samples.

The power of SKA to Constrain cosmological gravitational-wave backgrounds below the astrophysical foreground noise
Chengjie Fu, Jing Liu
https://arxiv.org/abs/2506.14366

The power of SKA to Constrain cosmological gravitational-wave backgrounds below the astrophysical foreground noise
The inspirals of supermaissive black hole binaries provide a convinced gravitational wave background in the nHz band, serving as the fiducial model of the recent gravitational wave signal reported by the PTA experiments. The uncertainties of the number of binaries contributing to each frequency bin introduce a foreground noise in the nHz and $μ$Hz bands against the observation of the underlying gravitational wave backgrounds of the cosmological origin. In this work, we investigate a new method…

Speech Neurophysiology in Realistic Contexts: Big Hype or Big Leap?
Giovanni M. Di Liberto, Emily Y. J. Ip
https://arxiv.org/abs/2506.05494 https://…

Speech Neurophysiology in Realistic Contexts: Big Hype or Big Leap?
Understanding the neural basis of speech communication is essential for uncovering how sounds are translated into meaning, how that changes with development, ageing, and speech-related deficits, as well as contributing to brain-computer interfaces research. While traditional neurophysiological studies have relied on simplified, controlled paradigms, recent advances have shifted the field toward more ecologically-valid approaches. Here, we examine the impact of continuous speech research and dis…

Predicting Postoperative Stroke in Elderly SICU Patients: An Interpretable Machine Learning Model Using MIMIC Data
Tinghuan Li, Shuheng Chen, Junyi Fan, Elham Pishgar, Kamiar Alaei, Greg Placencia, Maryam Pishgar
https://arxiv.org/abs/2506.03209

Predicting Postoperative Stroke in Elderly SICU Patients: An Interpretable Machine Learning Model Using MIMIC Data
Postoperative stroke remains a critical complication in elderly surgical intensive care unit (SICU) patients, contributing to prolonged hospitalization, elevated healthcare costs, and increased mortality. Accurate early risk stratification is essential to enable timely intervention and improve clinical outcomes. We constructed a combined cohort of 19,085 elderly SICU admissions from the MIMIC-III and MIMIC-IV databases and developed an interpretable machine learning (ML) framework to predict in…

This https://arxiv.org/abs/2410.21844 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Optimizing Perishable and Non-Perishable Product Assignment to Packaging Lines in a Sustainable Manufacturing System: An AUGMECON2VIKOR Algorithm
Identifying appropriate manufacturing systems for products can be considered a pivotal manufacturing task contributing to the optimization of operational and planning activities. It has gained importance in the food industry due to the distinct constraints and considerations posed by perishable and non-perishable items in this problem. Hence, this study proposes a new mathematical model according to knowledge discovery as well as an assignment model to optimize manufacturing systems for perisha…

Understanding Self-Regulated Learning Behavior Among High and Low Dropout Risk Students During CS1: Combining Trace Logs, Dropout Prediction and Self-Reports
Denis Zhidkikh, Ville Isom\"ott\"onen, Toni Taipalus
https://arxiv.org/abs/2506.09178

Understanding Self-Regulated Learning Behavior Among High and Low Dropout Risk Students During CS1: Combining Trace Logs, Dropout Prediction and Self-Reports
The introductory programming course (CS1) at the university level is often perceived as particularly challenging, contributing to high dropout rates among Computer Science students. Identifying when and how students encounter difficulties in this course is critical for providing targeted support. This study explores the behavioral patterns of CS1 students at varying dropout risks using self-regulated learning (SRL) as the theoretical framework. Using learning analytics, we analyzed trace logs a…

Can LLMs and humans be friends? Uncovering factors affecting human-AI intimacy formation
Yeseon Hong, Junhyuk Choi, Minju Kim, Bugeun Kim
https://arxiv.org/abs/2505.24658

Can LLMs and humans be friends? Uncovering factors affecting human-AI intimacy formation
Large language models (LLMs) are increasingly being used in conversational roles, yet little is known about how intimacy emerges in human-LLM interactions. Although previous work emphasized the importance of self-disclosure in human-chatbot interaction, it is questionable whether gradual and reciprocal self-disclosure is also helpful in human-LLM interaction. Thus, this study examined three possible aspects contributing to intimacy formation: gradual self-disclosure, reciprocity, and naturalnes…

Cardiovascular function changes following lung resection: a computational model to compare afterload increase and contractility loss mechanisms
Shiting Huang, Sanjay Pant, Sean McGinty, Richard Good, Ben Shelley, Ankush Aggarwal
https://arxiv.org/abs/2505.01264

Cardiovascular function changes following lung resection: a computational model to compare afterload increase and contractility loss mechanisms
Functional limitation after lung resection surgery has been consistently documented in clinical studies, and right ventricle (RV) dysfunction has been hypothesized as a contributing reason. However, the mechanisms of RV dysfunction after lung resection remain unclear, particularly whether change in afterload or contractility is the main cause. This study is the first to employ a lumped parameter model to simulate the effects of lung resection. The implementation of a computational model allowed…

This https://arxiv.org/abs/2410.21844 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Optimizing Perishable and Non-Perishable Product Assignment to Packaging Lines in a Sustainable Manufacturing System: An AUGMECON2VIKOR Algorithm
Identifying appropriate manufacturing systems for products can be considered a pivotal manufacturing task contributing to the optimization of operational and planning activities. It has gained importance in the food industry due to the distinct constraints and considerations posed by perishable and non-perishable items in this problem. Hence, this study proposes a new mathematical model according to knowledge discovery as well as an assignment model to optimize manufacturing systems for perisha…

Understanding Stability Mechanisms in Single-Atom Alloys with Theory-infused Deep Learning
Yang Huang, Shih-Han Wang, Shuyi Cao, Luke E. K. Achenie, Hongliang Xin
https://arxiv.org/abs/2506.03031

Understanding Stability Mechanisms in Single-Atom Alloys with Theory-infused Deep Learning
We present an interpretable deep learning model that enhances the prediction of cohesive energy in transition metal alloys (TMAs) by incorporating cohesion theory into a graph neural network (GNN) framework. The model not only predicts the total cohesive energy-an indicator of crystal stability-but also disentangles its various contributing factors and underlying physical parameters. The physics insights extracted from the model clarify the stability trends of transition metal surfaces across t…

High-order anisotropic flow and nonlinear hydrodynamic responses
Owen Horecny, Chun Shen
https://arxiv.org/abs/2506.02930 https://arx…

High-order anisotropic flow and nonlinear hydrodynamic responses
In this work, we study the charged hadron anisotropic flow coefficients $v_n$ (up to $n = 12$) using high-statistics event-by-event simulations of Pb+Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$ and $5.36$~TeV, employing the IP-Glasma + MUSIC + UrQMD hybrid approach. The power spectra of anisotropic flow coefficients ($v_n\{2\}$ vs. $n$) are compared with the ALICE measurements from central to 50% centrality. To understand the various sources contributing to the high-order $v_n$ coefficients,…