A low cost, wearable textile-based respiratory sensing system is proposed and experimentally demonstrated. A highly sensitive D-shaped plastic optical fiber (POF) sensor that responds to bending is integrated into an elastic band structure to form a respiratory sensing system. The curvature sensing experiments were conducted on the D-shaped POF sensor, which has a coefficient of determination (R ² ) of 0.9977. The system can be used to monitor not only the respiratory rate (RR) of the human body under different movement states (resting, walking, and running) but also the RR of steady and unsteady respiratory signals due to different physiological states. In addition, using the proposed signal processing technique, the interference of motion noise can be removed and the influence of body movement on the sensor response can be eliminated. The advantages of the system are its low cost, compactness, and simplicity in design. Thus, the application of the proposed respiratory sensing system provides a simple and inexpensive optical solution for wearable health.

A new double-taper microfiber Mach-Zehnder interferometer (MZI) biosensor is applied for Staphylococcus aureus ( S. aureus ) detection. The microfiber MZI structure is fabricated by creating two tapers along a traditional single mode fiber (SMF) firstly and tapering the SMF sandwiched between two tapers into very small diameter (in the order of micrometers). The measured refractive index (RI) sensitivity of the microfiber MZI is up to 2731.1 nm/RIU in the RI range of 1.34 when the taper waist diameter was $10.2 ~\mu \text{m}$ , which is in good agreement with numerical simulation results by using the beam propagation method (BPM). The microfiber MZI functionalized with pig immunoglobulin (pig IgG) could be used to specifically binding to S. aureus . In experiment, the maximum wavelength shift of 1.408 nm was achieved when the microfiber biosensors were immersed into S. aureus with concentration of $7\times 10^{1}$ CFU/mL. The limit of detection (LoD) of the microfiber biosensor for S. aureus is calculated as low as 11 CFU/mL. The proposed microfiber MZI biosensor has advantages of simple structure configuration, high sensitivity, good repeatability and specificity, wide detection range and fast detection response time (< 30 minutes) and thus was demonstrated a good application prospect in food safety inspection, biochemical sensing, diseases and medical diagnostics.

Brillouin-based LiDAR is an alternative remote sensing technique for measuring the distribution profiles of temperature, salinity, and sound speed in the upper ocean mixed layer. Its principle is based on the dependence of Brillouin frequency shift on the temperature, salinity, and depth of ocean. Therefore, it is necessary to investigate the effect of various seawater parameters on Brillouin frequency shift for ocean remote sensing by using the Brillouin LiDAR. Here we theoretically and experimentally investigate the influence of temperature, salinity, and pressure (depth) of seawater on Brillouin frequency shift in the upper ocean for the first time. Numerical simulations of the distribution profiles of temperature, salinity, and Brillouin frequency shift in the upper-ocean mixed layers of East China Sea and South China Sea were performed, respectively, by employing the Brillouin equations and the World Ocean Atlas 2018 (WOA18). A special ocean simulation system was designed to carry out the stimulated Brillouin scattering (SBS) experiments for validating the numerical simulations. The results show that the seawater temperature is the most important factor for the Brillouin frequency shift in the upper-ocean mixed layer compared with the salinity and pressure. At the same salinity and pressure, the frequency shift increases by more than 10 MHz for every 1 °C increase in temperature. Also, the differences of Brillouin frequency shift between experimental and theoretical values at the same parameter conditions were analyzed. The experimental results coincide well with the theoretical simulations. This work is essential to future applications of Brillouin LiDAR in remote sensing of the temperature, salinity, or sound velocity profiles of ocean.

This work aims to depth-resolved quantitatively analyze the effect of different stromal ablation amounts on the corneal biomechanical properties during small incision lenticule extraction (SMILE) using optical coherence elastography (OCE). A 4.5-MHz ultrasonic transducer was used to excite elastic waves in the corneal tissue. The OCE system combined with the antisymmetric Lamb wave model was employed to achieve a high-resolution, high-sensitivity, and depth-resolved quantitative detection of the corneal Young’s modulus. Eighteen rabbits were randomly divided into three groups; each group had six rabbits. The first and second groups underwent -3D and -6D SMILE surgeries, and the third group was the control group, respectively. Young’s modulus of the corneal cap and residual stromal bed (RSB) were both increased after SMILE, which shared the stress under intraocular pressure (IOP). Furthermore, the Young’s modulus of both the corneal cap and RSB after 3D SMILE group were significantly lower than that in the -6D group, which indicated that the increases in the post-operative corneal Young’s modulus were positively correlated with the amount of stromal ablation. The OCE system for quantitative spatial characterization of corneal biomechanical properties can provide useful information on the extent of safe ablation for SMILE procedures.

Vegetable oils provide some important components and health benefits for human nutrition and In this work, we have investigated the potential of laser-induced fluorescence (LIF) spectroscopy combined with the principal component analysis (PCA) method and partial least squares (PLS) model as a tool for the identification and quantification of vegetable oils adulterated with waste frying oil. Four types of vegetable oils (rapeseed, olive, peanut, and corn) were selected as the original oil samples, and a total of 210 sets samples were measured. By employing a PLS model, the values of prediction linearity greater than 0.995 were obtained when four types of vegetable oils were adulterated with waste frying oil with a mean square error less than 2%. The results indicate that the method proposed in this work is feasible for the detection and quantification of vegetable oil adulteration with waste frying oil.