Tootfinder

Micro-Health Interventions: Exploring Design Strategies for 1-Minute Interventions as a Gateway to Healthy Habits
Zahra Hassanzadeh, David Haag, Lydia Chilton, Jan Smeddinck, Norman Farb, Joseph Jay Williams
https://arxiv.org/abs/2508.09312

Micro-Health Interventions: Exploring Design Strategies for 1-Minute Interventions as a Gateway to Healthy Habits
One-minute behavior change interventions might seem too brief to matter. Could something so short really help people build healthier routines? This work explores this question through two studies examining how ultra-brief prompts might encourage meaningful actions in daily life. In a formative study, we explored how participants engaged with one-minute prompts across four domains: physical activity, eating, screen use, and mental well-being. This revealed two common design approaches: Immediate…

Data-fused Model Predictive Control with Guarantees: Application to Flying Humanoid Robots
Davide Gorbani, Mohamed Elobaid, Giuseppe L'Erario, Hosameldin Awadalla Omer Mohamed, Daniele Pucci
https://arxiv.org/abs/2509.10353

Data-fused Model Predictive Control with Guarantees: Application to Flying Humanoid Robots
This paper introduces a Data-Fused Model Predictive Control (DFMPC) framework that combines physics-based models with data-driven representations of unknown dynamics. Leveraging Willems' Fundamental Lemma and an artificial equilibrium formulation, the method enables tracking of changing, potentially unreachable setpoints while explicitly handling measurement noise through slack variables and regularization. We provide guarantees of recursive feasibility and practical stability under input-outpu…

SpliDT: Partitioned Decision Trees for Scalable Stateful Inference at Line Rate
Murayyiam Parvez, Annus Zulfiqar, Roman Beltiukov, Shir Landau Feibish, Walter Willinger, Arpit Gupta, Muhammad Shahbaz
https://arxiv.org/abs/2509.00397

SpliDT: Partitioned Decision Trees for Scalable Stateful Inference at Line Rate
Machine learning (ML) is increasingly being deployed in programmable data planes (switches and SmartNICs) to enable real-time traffic analysis, security monitoring, and in-network decision-making. Decision trees (DTs) are particularly well-suited for these tasks due to their interpretability and compatibility with data-plane architectures, i.e., match-action tables (MATs). However, existing in-network DT implementations are constrained by the need to compute all input features upfront, forcing …

Agroseismology: unraveling the impact of farming practices on soil hydrodynamics
Qibin Shi, David R. Montgomery, Abigail L. S. Swann, Nicoleta C. Cristea, Ethan Williams, Nan You, Joe Collins, Ana Prada Barrio, Simon Jeffery, Paula A. Misiewicz, Tarje Nissen-Meyer, Marine A. Denolle
https://arxiv.org/abs/2509.09821

Agroseismology: unraveling the impact of farming practices on soil hydrodynamics
Farmed landscapes provide a natural laboratory to test how management reshapes near-surface hydrodynamics. Combining distributed acoustic sensing with physics-based hydromechanical modeling, we tracked minute-resolution, meter-scale changes across experimental fields with controlled tillage and compaction histories. We find that dynamic capillary effects, rate-dependent suction stresses during wetting and drying, govern transient stiffness and moisture redistribution in disturbed soils, produci…