Tootfinder

💢 Mental health benefits of retirement not evenly shared among different income levels, study says
https://phys.org/news/2025-09-mental-health-benefits-evenly-income.html

Mental health benefits of retirement not evenly shared among different income levels, study says
The impact of retirement on mental health depends on income level, the nature of the job left behind, and the age at which people leave the workforce, a study suggests.

#Wordle 1,510 3/6*
⬜🟨⬜🟨⬜ <1% of 218,639 (50)
🟩⬜🟨⬜🟨 0 of 5 (9)
🟩🟩🟩🟩🟩
WordleBot
Skill 84/99
Luck 58/99
Nice easy day today.
My starting word today was not one I'd expect to be a wordle answer, I just felt like using it.
Interesting, the bot would have chosen a different word w/ the same letters I did for the 3rd guess, and it would have distributed the remaining words more evenly.

"Quantum-enhanced nanodiamond rapid test advances early SARS-CoV-2 antigen detection in clinical diagnostics."
Imagine how this sentence would have had you scratching your head just 15 years ago.
The future truly is already here, and as the saying goes, just not evenly distributed.

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On The Road - To Xi’An 🗿
在路上 - 去西安 🗿
📷 Minolta Hi-Matic AF
🎞️Kentmere Pan 200
#filmphotography #Photography #blackandwhite

EvoMail: Self-Evolving Cognitive Agents for Adaptive Spam and Phishing Email Defense
Wei Huang, De-Tian Chu, Lin-Yuan Bai, Wei Kang, Hai-Tao Zhang, Bo Li, Zhi-Mo Han, Jing Ge, Hai-Feng Lin
https://arxiv.org/abs/2509.21129

EvoMail: Self-Evolving Cognitive Agents for Adaptive Spam and Phishing Email Defense
Modern email spam and phishing attacks have evolved far beyond keyword blacklists or simple heuristics. Adversaries now craft multi-modal campaigns that combine natural-language text with obfuscated URLs, forged headers, and malicious attachments, adapting their strategies within days to bypass filters. Traditional spam detection systems, which rely on static rules or single-modality models, struggle to integrate heterogeneous signals or to continuously adapt, leading to rapid performance degra…

Personality Matters: User Traits Predict LLM Preferences in Multi-Turn Collaborative Tasks
Sarfaroz Yunusov, Kaige Chen, Kazi Nishat Anwar, Ali Emami
https://arxiv.org/abs/2508.21628

Personality Matters: User Traits Predict LLM Preferences in Multi-Turn Collaborative Tasks
As Large Language Models (LLMs) increasingly integrate into everyday workflows, where users shape outcomes through multi-turn collaboration, a critical question emerges: do users with different personality traits systematically prefer certain LLMs over others? We conducted a study with 32 participants evenly distributed across four Keirsey personality types, evaluating their interactions with GPT-4 and Claude 3.5 across four collaborative tasks: data analysis, creative writing, information retr…

Evaluate Neighbor Search for Curve-based Vector Field Processing
Nguyen Phan, Guoning Chen
https://arxiv.org/abs/2509.00180 https://arxiv.org/pdf/2509.0018…

Evaluate Neighbor Search for Curve-based Vector Field Processing
Curve-based representations, particularly integral curves, are often used to represent large-scale computational fluid dynamic simulations. Processing and analyzing curve-based vector field data sets often involves searching for neighboring segments given a query point or curve segment. However, because the original flow behavior may not be fully represented by the set of integral curves and the input integral curves may not be evenly distributed in space, popular neighbor search strategies oft…

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