Tootfinder

Beyond Accessibility: How Intelligent Assistive Technologies Improve Activities of Daily Life for Visually Impaired People in South Africa
Ronaldo Nombakuse, Nils Messerschmidt, Pitso Tsibolane, Muhammad Irfan Khalid
https://arxiv.org/abs/2510.05998

Beyond Accessibility: How Intelligent Assistive Technologies Improve Activities of Daily Life for Visually Impaired People in South Africa
Our study explores how intelligent assistive technologies (IATs) can enable visually impaired people (VIPs) to overcome barriers to inclusion in a digital society to ultimately improve their quality of life. Drawing on the Social Model of Disability (SMD), which frames disability as a consequence of social and institutional barriers rather than individual impairments, we employ semi-structured interviews and an online qualitative survey with n=61 VIPs in South Africa. Using descriptive statisti…

Viscosity and dynamic surface tension measurement: A guideline for appropriate measurement
Vivek Kumar, JSM Quintero, Aleksey Baldygin, Paul Molina, Thomas Willers, Prashant R. Waghmare
https://arxiv.org/abs/2510.05481

Viscosity and dynamic surface tension measurement: A guideline for appropriate measurement
Dynamic surface tension measurements play a critical role in interfacial activities for liquids with varying viscosities. Understanding the rate at which the interface attains the equilibrium, for surface tension measurements, after the formation of a new interface is of significant interest. Although surface tension is independent of viscosity, the time required for a new surface to form (equilibrium/relaxation time) is influenced by viscosity. The measured surface tension value is accurate on…

Open-Access Scientific Game-Theory Paper Shows Religion Worth a Damn
Fear of supernatural PUNISHMENT can harmonize human societies with nature: an evolutionary game-theoretic approach
https://www.nature.com/articles/s41599-025-05734-7?ref=404media.co
…

Fear of supernatural punishment can harmonize human societies with nature: an evolutionary game-theoretic approach - Humanities and Social Sciences Communications
Human activities largely impact the natural environment negatively and radical changes in human societies would be required to achieve their sustainable relationship with nature. Although frequently overlooked, previous studies have suggested that supernatural beliefs can protect nature from human overexploitation via beliefs that supernatural entities punish people who harm nature. Studies of folklore and ethnology have shown that such supernatural beliefs are widely found. However, it remains…

China’s coastal cities are sinking as seas rise at record speed #China

China’s coastal cities are sinking as seas rise at record speed
Sea levels are rising faster than at any time in 4,000 years, scientists report, with China’s major coastal cities at particular risk. The rapid increase is driven by warming oceans and melting ice, while human activities like groundwater pumping make it worse. In some areas, the land itself is sinking faster than the ocean is rising. Still, researchers see progress as cities like Shanghai adopt new technologies to stabilize the ground and prepare for the future.

Trump administration prepares sweeping crackdown on leftist networks
Thursday marks a first deadline,
set this month in a memo from Attorney General Pam Bondi,
for all federal law enforcement agencies to “coordinate delivery”
to the FBI of their intelligence files
on “Antifa” and “Antifa-related” activities.
Bondi has tasked the FBI with using those files to draw up lists of Americans and foreigners to investigate
as part of a campaign directed by …

Trump administration prepares sweeping crackdown on leftist networks
The Justice Department’s program to root out violent “Antifa” extremism is raising First Amendment concerns.

looks like there'll be a #NoKings event at Sunset Dunes! cool crossover
https://www.mobilize.us/nokings/event/847587/
main march in SF here:

NO KINGS Ocean Beach, San Francisco · No Kings
**In America, we don’t put up with would-be kings.** Join us for No Kings Day Ocean Beach! Saturday, October 18 • 12:00 PM • Sunset Dunes (Upper Great Highway & Judah), SF Be part of a fun, family-friendly Resistance Festival on the westside of San Francisco. Together we’ll celebrate community and resistance with: 🎨 Art and creative expression 🎶 Live music and performances 📚 Information tables on Bay Resistance, Prop 50, voter registration and more 🤝 Family-friendly ac…

PromoGuardian: Detecting Promotion Abuse Fraud with Multi-Relation Fused Graph Neural Networks
Shaofei Li, Xiao Han, Ziqi Zhang, Minyao Hua, Shuli Gao, Zhenkai Liang, Yao Guo, Xiangqun Chen, Ding Li
https://arxiv.org/abs/2510.12652

PromoGuardian: Detecting Promotion Abuse Fraud with Multi-Relation Fused Graph Neural Networks
As e-commerce platforms develop, fraudulent activities are increasingly emerging, posing significant threats to the security and stability of these platforms. Promotion abuse is one of the fastest-growing types of fraud in recent years and is characterized by users exploiting promotional activities to gain financial benefits from the platform. To investigate this issue, we conduct the first study on promotion abuse fraud in e-commerce platforms MEITUAN. We find that promotion abuse fraud is a g…

Prototyping Multimodal GenAI Real-Time Agents with Counterfactual Replays and Hybrid Wizard-of-Oz
Frederic Gmeiner, Kenneth Holstein, Nikolas Martelaro
https://arxiv.org/abs/2510.06872

Prototyping Multimodal GenAI Real-Time Agents with Counterfactual Replays and Hybrid Wizard-of-Oz
Recent advancements in multimodal generative AI (GenAI) enable the creation of personal context-aware real-time agents that, for example, can augment user workflows by following their on-screen activities and providing contextual assistance. However, prototyping such experiences is challenging, especially when supporting people with domain-specific tasks using real-time inputs such as speech and screen recordings. While prototyping an LLM-based proactive support agent system, we found that exis…

Leveraging Large Language Models for Cybersecurity Risk Assessment -- A Case from Forestry Cyber-Physical Systems
Fikret Mert G\"ultekin, Oscar Lilja, Ranim Khojah, Rebekka Wohlrab, Marvin Damschen, Mazen Mohamad
https://arxiv.org/abs/2510.06343

Leveraging Large Language Models for Cybersecurity Risk Assessment -- A Case from Forestry Cyber-Physical Systems
In safety-critical software systems, cybersecurity activities become essential, with risk assessment being one of the most critical. In many software teams, cybersecurity experts are either entirely absent or represented by only a small number of specialists. As a result, the workload for these experts becomes high, and software engineers would need to conduct cybersecurity activities themselves. This creates a need for a tool to support cybersecurity experts and engineers in evaluating vulnera…

Extreme events scaling in self-organized critical models
Abdul Quadir, Haider Hasan Jafri
https://arxiv.org/abs/2510.08733 https://arxiv.org/pdf/2510.08733…

Extreme events scaling in self-organized critical models
We study extreme events of avalanche activities in finite-size two-dimensional self-organized critical (SOC) models, specifically the stochastic Manna model (SMM) and the Bak-Tang-Weisenfeld (BTW) sandpile model. Employing the approach of block maxima, the study numerically reveals that the distributions for extreme avalanche size and area follow the generalized extreme value (GEV) distribution. The extreme avalanche size follows the Gumbel distribution with shape parameter $ξ=0$ while in the …

Prismo: A Decision Support System for Privacy-Preserving ML Framework Selection
Nges Brian Njungle, Eric Jahns, Luigi Mastromauro, Edwin P. Kayang, Milan Stojkov, Michel A. Kinsy
https://arxiv.org/abs/2510.09985

Prismo: A Decision Support System for Privacy-Preserving ML Framework Selection
Machine learning has become a crucial part of our lives, with applications spanning nearly every aspect of our daily activities. However, using personal information in machine learning applications has sparked significant security and privacy concerns about user data. To address these challenges, different privacy-preserving machine learning (PPML) frameworks have been developed to protect sensitive information in machine learning applications. These frameworks generally attempt to balance desi…

Effect of modeling subject-specific cortical folds on brain injury risk prediction under blunt impact loading
Anu Tripathi, Alison Brooks, Traci Snedden, Peter Ferrazzano, Christian Franck, Rika Wright Carlsen
https://arxiv.org/abs/2510.08379

Effect of modeling subject-specific cortical folds on brain injury risk prediction under blunt impact loading
Purpose: Computational head models are essential tools for studying the risk of mild traumatic brain injury (mTBI) under different activities and across populations. However, different computational models incorporate varied levels of anatomical details, such as cortical folds. In this study, we aim to determine the effect of modeling cortical folds on mTBI risk assessment. Methods: We compared the gyrencephalic (with cortical folds) and lissencephalic (without cortical folds) FE models of 18…

ExPrESSO: Zero-Knowledge backed Extensive Privacy Preserving Single Sign-on
Kaustabh Barman, Fabian Piper, Sanjeet Raj Pandey, Axel Kuepper
https://arxiv.org/abs/2510.08355 http…

ExPrESSO: Zero-Knowledge backed Extensive Privacy Preserving Single Sign-on
User authentication is one of the most important aspects for secure communication between services and end-users over the Internet. Service providers leverage Single-Sign On (SSO) to make it easier for their users to authenticate themselves. However, standardized systems for SSO, such as OIDC, do not guarantee user privacy as identity providers can track user activities. We propose a zero-knowledge-based mechanism that integrates with OIDC to let users authenticate through SSO without revealing…

Exposing LLM User Privacy via Traffic Fingerprint Analysis: A Study of Privacy Risks in LLM Agent Interactions
Yixiang Zhang, Xinhao Deng, Zhongyi Gu, Yihao Chen, Ke Xu, Qi Li, Jianping Wu
https://arxiv.org/abs/2510.07176

Exposing LLM User Privacy via Traffic Fingerprint Analysis: A Study of Privacy Risks in LLM Agent Interactions
Large Language Models (LLMs) are increasingly deployed as agents that orchestrate tasks and integrate external tools to execute complex workflows. We demonstrate that these interactive behaviors leave distinctive fingerprints in encrypted traffic exchanged between users and LLM agents. By analyzing traffic patterns associated with agent workflows and tool invocations, adversaries can infer agent activities, distinguish specific agents, and even profile sensitive user attributes. To highlight th…