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  1. Current commercially available robotic minimally invasive surgery (RMIS) platforms provide no haptic feedback of tool interactions with the surgical environment. As a consequence, novice robotic surgeons must rely exclusively on visual feedback to sense their physical interactions with the surgical environment. This technical limitation can make it challenging and time-consuming to train novice surgeons to proficiency in RMIS. Extensive prior research has demonstrated that incorporating haptic feedback is effective at improving surgical training task performance. However, few studies have investigated the utility of providing feedback of multiple modalities of haptic feedback simultaneously (multi-modality haptic feedback) in this context, and these studies have presented mixed results regarding its efficacy. Furthermore, the inability to generalize and compare these mixed results has limited our ability to understand why they can vary significantly between studies. Therefore, we have developed a generalized, modular multi-modality haptic feedback and data acquisition framework leveraging the real-time data acquisition and streaming capabilities of the Robot Operating System (ROS). In our preliminary study using this system, participants complete a peg transfer task using a da Vinci robot while receiving haptic feedback of applied forces, contact accelerations, or both via custom wrist-worn haptic devices. Results highlight the capability of our system in running systematic comparisons between various single and dual-modality haptic feedback approaches. 
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  2. We report on the collective behavior of active particles in which energy is continuously supplied to rotational degrees of freedom. The active spinners are 3D-printed disks, 1 cm in diameter, that have an embedded fan-like structure, such that a sub-levitating up-flow of air forces them to spin. Single spinners exhibit Brownian motion with a narrow Gaussian velocity distribution function, P ( v ), for translational motion. We study the evolution of P ( v ) as the packing fraction and the average single particle spin speeds are varied. The interparticle hydrodynamic interaction is negligible, and the dynamics is dominated by hyperelastic collisions and dissipative forces. As expected for nonequilibrium systems, P ( v ) for a collection of many spinners deviates from Gaussian behavior. However, unlike translationally active systems, phase separation is not observed, and the system remains spatially homogeneous. We then search for a near-equilibrium counterpart for our active spinners by measuring the equation of state. Interestingly, it agrees well with a hard-sphere model, despite the dissipative nature of the single particle dynamics. 
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