A carbuncle cure for the Harten-Lax-van Leer contact (HLLC) scheme using a novel velocity-based sensor

A hybrid numerical flux scheme is proposed by adapting the carbuncle-free modified Harten-Lax-van Leer contact (HLLCM) scheme to smoothly revert to the Harten-Lax-van Leer contact (HLLC) scheme in regions of shear. This hybrid scheme, referred to as the HLLCT scheme, employs a novel, velocity-based shear sensor. In contrast to the non-local pressure-based shock sensors often used in carbuncle cures, the proposed shear sensor can be computed in a localized manner meaning that the HLLCT scheme can be easily introduced into existing codes without having to implement additional data structures. Through numerical experiments, it is shown that the HLLCT scheme is able to resolve shear layers accurately without succumbing to the shock instability.

Shear sensor mechano-signaling determines tendon stiffness and human jumping performance

Tendons enable movement by transferring muscle forces to the skeleton, and athletic performances critically rely on mechanically-optimized tendons. How load-bearing structures of tendon sense and adapt to physical demands is an open question of central importance to musculoskeletal medicine and human sports performance. Here, with calcium imaging in tendon explants and primary tendon cells we characterized how tenocytes detect mechanical forces and determined collagen fiber-sliding-induced shear stress as a key stimulus. CRISPR/Cas9 screening in human and rat tenocytes identified PIEZO1 as the crucial shear sensor. In rodents, elevated mechano-signaling increased tendon stiffness and strength both in vitro by pharmacological channel activation and in vivo by a Piezo1 gain-of-function mutation. Strikingly, humans carrying the PIEZO1 gain-of-function E756del mutation revealed a 16% average increase in normalized jumping height, with more effective storage of potential energy released during dynamic jumping maneuvers. We propose that PIEZO1-mediated mechano-signaling regulates tendon stiffness and impacts human athletic performance.

Highly Sensitive Tactile Shear Sensor Using Spatially Digitized Contact Electrodes

In this article, we report on a highly sensitive tactile shear sensor that was able to detect minute levels of shear and surface slip. The sensor consists of a suspended elastomer diaphragm with a top ridge structure, a graphene layer underneath, and a bottom substrate with multiple spatially digitized contact electrodes. When shear is applied to the top ridge structure, it creates torque and deflects the elastomer downwards. Then, the graphene electrode makes contact with the bottom spatially digitized electrodes completing a circuit producing output currents depending on the number of electrodes making contact. The tactile shear sensor was able to detect shear forces as small as 6 μN, detect shear direction, and also distinguish surface friction and roughness differences of shearing objects. We also succeeded in detecting the contact slip motion of a single thread demonstrating possible applications in future robotic fingers and remote surgical tools.

A preliminary study on characterisation of finger interface kinetics using a pressure and shear sensor system

Background: Our hands constantly handle objects throughout our lives, where a crucial component of this interaction is the detection of grasping (pressure) and slipping (shear) of the object. While there have been a large amount of studies using pressure sensors for grasping detection, synchronised pressure and shear detection at the finger/object interface is still needed. Objectives: This study aims to assess the feasibility of a sensor system designed to detect both pressure and shear at the fingertip/object interface via a single subject test. Study design: Descriptive study, proof of concept. Methods: One healthy subject participated in the study and was asked to perform a single finger test protocol and a simple hand test protocol. The corresponding multidirectional loads at the fingertip/object interface were measured in real time using a pressure and shear sensor system. Results: Results from the finger test protocol show peak values of up to approximately 50 kPa (5 N) and 30 kPa (3 N) of pressure for each test, respectively. Results from the hand test protocol show a pressure and shear profile that shows a large increase in grip force during the initial grasping of the object, with a peak pressure of approximately 50 kPa (5 N). The pressure and shear profile demonstrates that the load is not evenly distributed across all digits. Conclusion: This study provides evidence that the reported sensor system has sufficient resolution, dynamic response and load capability to capture biomechanical information during basic protocols and hand-grasping tasks. Clinical relevance The presented sensor system could be potentially used as a tool for measuring and evaluating hand function and could be incorporated into a prosthetic hand as a tactile feedback system.