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Abstract Extremely rare topologically protected acoustic energy sink is presented in this article. Acoustic topological phenomena are generally described using quantum anomalous hall effects (QAHE), quantum valley hall effects (QVHE), and quantum spin hall effects (QSHE) where spin orbit coupling is predominant. Topological edge states are demonstrated by bulk-boundary distinction when the bulk is insulated. In this article topological acoustic conductor and its phenomena are theoretically demonstrated where the boundaries are insulated. This is exactly opposite to the behavior of a topological acoustic insulator. Phenomena presented in this article could not be explained by any of the trio Quantum Hall effects. To explain the phenomenon phononic crystals or PnCs were designed to obtain accidental triple degeneracies, resulting a Dirac-like cone at the Γ point ( $$\overrightarrow{k}=0$$ k → = 0 ). The phenomenon is microarchitecture and microrotation field independent. Here time reversal symmetry or the space inversion symmetry is not broken, and the degenerated ‘Deaf band’ dominates the local dispersion with a syncline top band. This scenario results in continuously changing ‘up spin’ and ‘down spin’ of the wave energy in the media and remain trapped without specific preferential direction of wave transport. The spin was found to generate the spin angular momentum, causing the switching in geometric phase from $$0-2\pi$$ 0 - 2 π in cyclic pattern, keeping the energy trapped inside the bulk media.

The ever-changing technology landscape has seen a significant breakthrough with the introduction of edge computing. This innovation has revolutionized various domains, and one of its critical applications is in the domain of accident detection. Edge computing can help enhance road safety and emergency response by enabling real-time processing and analysis of sensory information from onboard sensors, cameras, and other connected devices. By integrating edge computing into accident detection systems, we can overcome the limitations of conventional centralized cloud-based methods and create a safer transportation network. In this article, we have proposed an accident detection framework using Deep Learning (DL) in the edge cloud environment. For accident detection, we have used a Convolutional Neural Network (CNN)- based DL model. The DL model detects the accident in the edge node which is near the data source. The proposed framework provides low latency, minimal network usage, and lower execution time as compared to only cloud-based deployment. Additionally, the proposed accident detection model is accurate up to 95.91% with Precision 0.9574, Recall 0.9574 and F1 score 0.9574 in the cloud-edge environment.

This study examined the impact of personalizing muscle vibration parameters on trunk control. We assessed how altered trunk extensor muscle (TEM) proprioception affects seated trunk control in healthy controls (HCs). To explore the link between altered TEM proprioception and impaired trunk control in chronic low back pain (cLBP), we performed equivalence testing between HCs undergoing TEM vibration and cLBP without vibration. Twenty HCs performed active joint reposition error (AJRE) testing to determine personalized vibration parameters. Each participant maintained balance on an unstable chair with eyes open and closed, with and without TEM vibration. We compared trunk control between HCs and twenty age- and sex-matched cLBP participants, using mean velocity and 95% confidence ellipse area of center-of-pressure changes to quantify trunk postural control. Equivalence was examined by comparing mean difference scores to minimal detectable change values and calculating between-group effect sizes. Personalized vibration parameters led to larger lumbopelvic repositioning errors (d = 0.89) than any single vibration frequency (d = 0.31–0.36). In healthy adults with no back pain, vision had large effects on postural control (ηp2 = 0.604–0.842), but TEM vibration had no significant effects (p > 0.105) or interactions with vision (p > 0.423). Between-group effect sizes (d = 0.32–0.51) exceeded our threshold for performance equivalence (d < 0.2). Muscle vibration altered position sense during AJRE testing, and personalizing parameters amplified this effect. However, TEM vibration had minimal impact on seated trunk postural control in adults with no back pain and did not lead to performance degradation comparable to that in cLBP.

The article presents the design concept of a surface acoustic wave (SAW)-based lab-on-a-chip sensor with multifrequency and multidirectional sensitivity. The conventional SAW sensors use delay lines that suffer from multiple signal losses such as insertion, reflection, transmission losses, etc. Most delay lines are designed to transmit and receive continuous signal at a fixed frequency. Thus, the delay lines are limited to only a few features, like frequency shift and change in wave velocity, during the signal analysis. These facts lead to limited sensitivity and a lack of opportunity to utilize the multi-directional variability of the sensing platform at different frequencies. Motivated by these facts, a guided wave sensing platform that utilizes simultaneous tone burst-based excitation in multiple directions is proposed in this article. The design incorporates a five-count tone burst signal for the omnidirectional actuation. This helps the acquisition of sensitive long part of the coda wave (CW) signals from multiple directions, which is hypothesized to enhance sensitivity through improved signal analysis. In this article, the design methodology and implementation of unique tone burst interdigitated electrodes (TB-IDT) are presented. Sensing using TB-IDT enables accessing multiple frequencies simultaneously. This results in a wider frequency spectrum and allows better scope for the detection of different target analytes. The novel design process utilized guided wave analysis of the substrate, and selective directional focused interdigitated electrodes (F-IDT) were implemented. The article demonstrates computational simulation along with experimental results with validation of multifrequency and multidirectional sensing capability.