Tootfinder

High-Speed Event Vision-Based Tactile Roller Sensor for Large Surface Measurements
Akram Khairi, Hussain Sajwani, Abdallah Mohammad Alkilany, Laith AbuAssi, Mohamad Halwani, Islam Mohamed Zaid, Ahmed Awadalla, Dewald Swart, Abdulla Ayyad, Yahya Zweiri
https://arxiv.org/abs/2507.19914

High-Speed Event Vision-Based Tactile Roller Sensor for Large Surface Measurements
Inspecting large-scale industrial surfaces like aircraft fuselages for quality control requires capturing their precise 3D surface geometry at high resolution. Vision-based tactile sensors (VBTSs) offer high local resolution but require slow 'press-and-lift' measurements stitched for large areas. Approaches with sliding or roller/belt VBTS designs provide measurements continuity. However, they face significant challenges respectively: sliding struggles with friction/wear and both approaches are…

Physics-informed conditional diffusion model for generalizable elastic wave-mode separation
Shijun Cheng, Xinru Mu, Tariq Alkhalifah
https://arxiv.org/abs/2506.23007

Physics-informed conditional diffusion model for generalizable elastic wave-mode separation
Traditional elastic wavefield separation methods, while accurate, often demand substantial computational resources, especially for large geological models or 3D scenarios. Purely data-driven neural network approaches can be more efficient, but may fail to generalize and maintain physical consistency due to the absence of explicit physical constraints. Here, we propose a physics-informed conditional diffusion model for elastic wavefield separation that seamlessly integrates domain-specific physi…

Theoretical modeling and quantitative research on aquatic ecosystems driven by multiple factors
Haizhao Guan, Yiyuan Niu, Chuanjin Zu, Ju Kang
https://arxiv.org/abs/2507.19553 h…

Theoretical modeling and quantitative research on aquatic ecosystems driven by multiple factors
Understanding the complex interactions between water temperature, nutrient levels, and chlorophyll-a dynamics is essential for addressing eutrophication and the proliferation of harmful algal blooms in freshwater ecosystems algal. However, many existing studies tend to oversimplify thse relationships often neglecting the non-linear effects and long-term temporal variations that influence chlorophyll-a growth. Here, we conducted multi-year field monitoring (2020-2024) of the key environmental fa…

AraHealthQA 2025 Shared Task Description Paper
Hassan Alhuzali, Farah Shamout, Muhammad Abdul-Mageed, Chaimae Abouzahir, Mouath Abu-Daoud, Ashwag Alasmari, Walid Al-Eisawi, Renad Al-Monef, Ali Alqahtani, Lama Ayash, Nizar Habash, Leen Kharouf
https://arxiv.org/abs/2508.20047

AraHealthQA 2025 Shared Task Description Paper
We introduce {AraHealthQA 2025}, the {Comprehensive Arabic Health Question Answering Shared Task}, held in conjunction with {ArabicNLP 2025} (co-located with EMNLP 2025). This shared task addresses the paucity of high-quality Arabic medical QA resources by offering two complementary tracks: {MentalQA}, focusing on Arabic mental health Q\&A (e.g., anxiety, depression, stigma reduction), and {MedArabiQ}, covering broader medical domains such as internal medicine, pediatrics, and clinical decision…

Spin Correlations in Recirculating Multipass Alkali Cells for Advancing Quantum Magnetometry
Qian Ling Kee, Lingyi Zhao, Ruvi Lecamwasam, Biveen Shajilal, Xinan Liang, Joel K Jose, Yao Chen, Ping Koy Lam, Tao Wang
https://arxiv.org/abs/2506.14160

Spin Correlations in Recirculating Multipass Alkali Cells for Advancing Quantum Magnetometry
Multipass cells are critical components in a variety of quantum technologies, including atomic magnetometers and optical quantum memories, due to their ability to achieve long optical paths within compact volumes. In optical magnetometry, increasing the optical depth through multipass geometries enhances sensitivity by reducing photon shot noise and enabling quantum nondemolition (QND) detection. In this work, we present a novel recirculating multipass alkali cell that improves the active-to-ce…

A Bayesian Additive Regression Trees Model for zero and one inflated data for Predicting Individual Treatment Effects in Alcohol Use Disorder Trials
Pamela Solano, M Lee Van Horn, Kyle Walters, Philipp Besendorfer, Alena Kuhlemeier, Manel Mart\'inez-Ram\'on, Thomas Jaki
https://arxiv.org/abs/2507.19848

A Bayesian Additive Regression Trees Model for zero and one inflated data for Predicting Individual Treatment Effects in Alcohol Use Disorder Trials
Alcohol Use Disorder (AUD) treatment presents high individual-level heterogeneity, with outcomes ranging from complete abstinence to persistent heavy drinking. This variability-driven by complex behavioral, social, and environmental factors-poses major challenges for treatment evaluation and individualized decision-making. In particular, accurately modeling bounded semicontinuous outcomes and estimating predictive individual treatment effects (PITEs) remains methodologically demanding. For th…

Adam Subhas has been leading the LOC-NESS project
—short for Locking away Ocean Carbon in the Northeast Shelf and Slope
—since 2023.
The ongoing research initiative is evaluating the effectiveness and environmental impact of a marine carbon dioxide removal approach called "ocean alkalinity enhancement" (OAE). 
This method of marine carbon dioxide removal involves adding alkaline substances to the ocean
to boost its natural ability to neutralize acids p…

The LOC-NESS Project
Locking away Ocean Carbon in the Northeast Shelf and Slope

🍸 'Super alcohol' created in space-like lab reveals cosmic secrets
#chemistry

'Super alcohol' created in space-like lab reveals cosmic secrets
University of Hawaiʻi at Mānoa researchers in the Department of Chemistry have created a molecule once thought too unstable to exist called methanetetrol using extreme, space-like conditions. The discovery could reshape our understanding of chemistry in the universe and shed light on the complex reactions happening in deep space.

This is a trend of my desire to not drink alcohol over the last few days. Purely coincidentally, this is also a graph of the state of charge of my solar battery array over the last few days.
I think I'm like one of those lizards that has to recharge in the sun to have any desire to live. No wonder I love the desert. No wonder I don't love Ireland.

A Novel Monte-Carlo Compressed Sensing and Dictionary Learning Method for the Efficient Path Planning of Remote Sensing Robots
Alghalya Al-Hajri, Ejmen Al-Ubejdij, Aiman Erbad, Ali Safa
https://arxiv.org/abs/2507.18462

A Novel Monte-Carlo Compressed Sensing and Dictionary Learning Method for the Efficient Path Planning of Remote Sensing Robots
In recent years, Compressed Sensing (CS) has gained significant interest as a technique for acquiring high-resolution sensory data using fewer measurements than traditional Nyquist sampling requires. At the same time, autonomous robotic platforms such as drones and rovers have become increasingly popular tools for remote sensing and environmental monitoring tasks, including measurements of temperature, humidity, and air quality. Within this context, this paper presents, to the best of our knowl…