Optical whispering gallery mode (WGM) microresonators have attracted great attention due to their remarkable properties such as extremely high quality factor, small mode volume, tight confinement of modes, and strong evanescent field. All these properties of WGM microresonators have ensured their great potentials for applications, such as physical sensors, bio/chemical sensors and microlasers. In this mini-review, the key parameters and coupling conditions of WGM microresonators are firstly introduced. The geometries of WGM optical microcavities are presented based on their fabrication methods. This is followed by the discussion on the state-of-the-art applications of WGM microresonators in sensors and microlasers.
Background. The purpose of this study is to investigate the influence of transverses abdominis and lumbar multifidus thickness activation and electromyogram signal characteristics after core stability training monitored by rehabilitative ultrasound imaging and surface electromyogram. Methods. 60 healthy volunteers were allocated randomly into two groups, one of which received monitoring training and the other participated identical training without monitoring. Ultrasound image and surface electromyogram signal were collected at 0, 4, and 8 weeks during training. The muscle thickness activation ratio value and integrated electromyogram value were then extracted. During the training, the monitoring group was monitored by real-time rehabilitative ultrasound imaging and surface electromyogram while the control group was not. Results. There are no differences in performance of local core muscles between both groups before training (p>0.05). Compared with the control group, the thickness contraction ratio value and integrated electromyogram value of core muscles in the monitoring group were higher after 8 weeks’ training (p<0.05). Conclusion. Together, the core stability training monitored by rehabilitative ultrasound imaging and surface electromyogram can markedly activate and enhance local core muscles in healthy people, providing a potential strategy to treat low back pain more effectively.
In quasi-distributed fiber Bragg grating (FBG) sensor networks, challenges are known to arise when signals are highly overlapped and thus hard to separate, giving rise to substantial error in signal demodulation. We propose a multi-peak detection deep learning model based on a dilated convolutional neural network (CNN) that overcomes this problem, achieving extremely low error in signal demodulation even for highly overlapped signals. We show that our FBG demodulation scheme enhances the network multiplexing capability, detection accuracy and detection time of the FBG sensor network, achieving a root-mean-square (RMS) error in peak wavelength determination of < 0.05 pm, with a demodulation time of 15 ms for two signals. Our demodulation scheme is also robust against noise, achieving an RMS error of < 0.47 pm even with a signal-to-noise ratio as low as 15 dB. A comparison on our high-performance computer with existing signal demodulation methods shows the superiority in RMS error of our dilated CNN implementation. Our findings pave the way to faster and more accurate signal demodulation methods, and testify to the substantial promise of neural network algorithms in signal demodulation problems.
Combination of anti‐resonant hollow‐core fiber (HCF) and semiconductor nanomaterial is an effective strategy to obtain high‐performance gas sensors with exceptional sensitivity and low power consumption. However, controlling the semiconductor morphology onto HCF is a major challenge to achieve the desired gas sensor with the enhanced sensitivity. Here, a ZnO‐Bi2O3 nanosheets (NSs) heterostructure is grown in situ on the surface of HCF by sol–gel and hydrothermal methods. ZnO‐Bi2O3 NSs serving as electron acceptors trap electrons after acetone adsorption and then change the refractive index of the surface of HCF. Benefiting from the unique sheet structure and the synergetic effects for multi‐component, the resulting ZnO‐Bi2O3 NSs enabled HCF gas sensor exhibits high sensitivity, selectivity, and repeatability for detecting acetone at room temperature, particularly in the low concentration range, with the theoretical limit of detection down to 140 parts‐per‐billion. Meanwhile, the successful application of the ZnO‐Bi2O3 NSs enabled HCF gas sensor to distinguish the exhaled breath from the healthy individuals and simulated diabetic cases is demonstrated, which paves the way to achieve non‐invasive, ultra‐sensitivity gas sensing at room temperature for the early diagnosis of diabetes.
The growing demand for intelligent equipment has greatly inspired the development of flexible devices. Thus, disparate flexible multifunctional devices, including pressure sensitive flexible/stretchable displays, have drawn worldwide research attention. Electrodes maintaining conductivity and mechanical strength against deformations are indispensable components in all prospective applications. In this work, a flexible pressure mapping sensor array is developed based on patterned Ag-nanofibers (Ag-NFs) electrode through electrospinning and lithography. The metallic Ag layer is sputtered onto the electrospinning polyvinyl alcohol (PVA) NFs. A uniform and super conductive electrode layer with outstanding mechanical performance is thus formed after dissolving PVA. Followed by the traditional lithography method, a patterned electrode array (4 × 4 sensors) is obtained. Based on the newly developed triboelectric nanogenerator (TENG) technology, a flexible pressure-mapping sensor with excellent stability towards bending deformations is further demonstrated. Moreover, a letter “Z” is successfully visualized by this pressure sensor array, encouraging more human–machine interactive implementations, such as multi-functional tactile screens.
It has been demonstrated recently that the absolute nodal coordinate formulation (ANCF) can be used to develop lower-order consistent rotation-based formulations (CRBF) that employ finite rotation parameters as nodal coordinates without the need for interpolating the rotation field. The objective of this study is to develop new planar shear-deformable ANCF/CRBF beam elements and demonstrate their use. A cubic ANCF/CRBF shear deformable beam element is first developed starting with the ANCF kinematic description that employs position vector gradients as nodal coordinates. The transverse position vector gradients at the nodes are expressed in terms of finite rotation parameters, leading to a lower-dimensional beam element model that captures the shear deformation, ensures continuity of the stresses and rotations at the nodes, allows for an arbitrary large displacement, and has a kinematic description consistent with geometry methods and suitable for systematically modeling curved structures. The results, obtained using the new planar ANCF/CRBF shear deformable beam element, are compared with the original and more general ANCF shear deformable beam element. Another lower-dimension bilinear CRBF beam element which has three coordinates at each node, two translation coordinates and one rotation parameter, is also developed in this investigation. The formulations of the three finite elements, including the ANCF finite element, considered in this investigation are compared. Numerical results are presented in order to demonstrate the use of the new formulations and test their performances in the analysis of large displacements and deformations. While the ANCF/CRBF assumptions are evaluated numerically, the results obtained show, in general, a good agreement between the elements considered in this study. The results also show that the CRBF finite elements, which have nonlinear mass matrix, can be more efficient for smaller meshes. As the mesh size and the number of finite elements increase, the original higher order ANCF finite elements, which have constant mass matrix and zero Coriolis and centrifugal forces, become more efficient. The ANCF/CRBF approach clearly demonstrates that there is no need for introducing an independent rotation field to capture the shear effect.
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