Single- and Double-Comb Tilted Fibre Bragg Grating Refractive Index Demodulation Methods with Fourier Transform Pre-Processing

Active imaging through dense fog by utilizing the joint polarization defogging and denoising optimization based on range-gated detection

Imaging through the scattering medium, such as fog, is important for military and civilian applications. However, the fog concentration restricts the current defogging methods; the image will be seriously degraded in dense fog scenes. Here, an imaging technique by developing joint active polarization defogging and denoising optimization methods based on range-gated detection is proposed for the target in fog conditions. The range-gated imaging method shields the scattering light from outside the selected region to improve the signal intensity. The properties of signal light, backscattering light, and forward scattering light in the range-gated imaging way are analyzed experimentally and theoretically. Thus the elimination method of backscattering light is developed in terms of polarization differences in the degree of polarization and angle of polarization, and the block-matching with 3D transform-domain collaborative filtering (BM3D) algorithm is developed to remove the effect of the forward scattering light on the image. By adopting the proposed defogging method, the clear imaging of the target under fog with an optical thickness of up to 5 is realized, and the target contour and detail information are successfully recovered. Compared with the complete failure of the current defogging method, this method can recover targets with high contrast and signal-to-noise ratio in dense fog scenes, which exhibits widespread application potential for target detection and recognition in severe weather and turbid underwater environment.

A Wavelet Derivative Spectrum Length Method of TFBG Sensor Demodulation

Fibre optic sensors using tilted fibre Bragg grating (TFBG) have high sensitivity for refractive index measurements. In order to achieve good metrological parameters of the measurement, an appropriate method of spectrum demodulation must be used. The method proposed in the article is an improvement of the spectral length algorithm. The spectral length parameter is treated as the sum of the derivative filter responses. In the original version, the first difference of spectrum elements was used, while this article proposes to use the wavelet transform to calculate the numerical derivative approximation. The advantage of this solution is an easy way to select the level of smoothing filtration by changing the scale parameter. The derivation is appropriate even for a relatively low signal-to-noise level. The approximation of the spectral length by the derivative calculated using the wavelet transform eliminates the high-frequency noise of the optical signal. The absolute value of determined spectral derivatives after significant smoothing can be used to estimate the wavelength of the decay of modes. After analyzing experimental data and performing calculations, it turns out that this is a linear method with better resolution than the contour length algorithm.

Adaptive Savitzky–Golay Filters for Analysis of Copy Number Variation Peaks from Whole-Exome Sequencing Data

Copy number variation (CNV) is a form of structural variation in the human genome that provides medical insight into complex human diseases; while whole-genome sequencing is becoming more affordable, whole-exome sequencing (WES) remains an important tool in clinical diagnostics. Because of its discontinuous nature and unique characteristics of sparse target-enrichment-based WES data, the analysis and detection of CNV peaks remain difficult tasks. The Savitzky–Golay (SG) smoothing is well known as a fast and efficient smoothing method. However, no study has documented the use of this technique for CNV peak detection. It is well known that the effectiveness of the classical SG filter depends on the proper selection of the window length and polynomial degree, which should correspond with the scale of the peak because, in the case of peaks with a high rate of change, the effectiveness of the filter could be restricted. Based on the Savitzky–Golay algorithm, this paper introduces a novel adaptive method to smooth irregular peak distributions. The proposed method ensures high-precision noise reduction by dynamically modifying the results of the prior smoothing to automatically adjust parameters. Our method offers an additional feature extraction technique based on density and Euclidean distance. In comparison to classical Savitzky–Golay filtering and other peer filtering methods, the performance evaluation demonstrates that adaptive Savitzky–Golay filtering performs better. According to experimental results, our method effectively detects CNV peaks across all genomic segments for both short and long tags, with minimal peak height fidelity values (i.e., low estimation bias). As a result, we clearly demonstrate how well the adaptive Savitzky–Golay filtering method works and how its use in the detection of CNV peaks can complement the existing techniques used in CNV peak analysis.

Determination of the Highly Sensitive Carboxyl-Graphene Oxide-Based Planar Optical Waveguide Localized Surface Plasmon Resonance Biosensor

This study develops a highly sensitive and low-cost carboxyl-graphene-oxide-based planar optical waveguide localized surface plasmon resonance biosensor (GO-OW LSPR biosensor), a system based on measuring light intensity changes. The structure of the sensing chip comprises an optical waveguide (OW)-slide glass and microfluidic-poly (methyl methacrylate) (PMMA) substrate, and the OW-slide glass surface-modified gold nanoparticle (AuNP) combined with graphene oxide (GO). As the GO has an abundant carboxyl group (–COOH), the number of capture molecules can be increased. The refractive index sensing system uses silver-coated reflective film to compare the refractive index sensitivity of the GO-OW LSPR biosensor to increase the refractive index sensitivity. The result shows that the signal variation of the system with the silver-coated reflective film is 1.57 times that of the system without the silver-coated reflective film. The refractive index sensitivity is 5.48 RIU⁻¹ and the sensor resolution is 2.52 ± 0.23 × 10⁻⁶ RIU. The biochemical sensing experiment performs immunoglobulin G (IgG) and streptavidin detection. The limits of detection of the sensor for IgG and streptavidin are calculated to be 23.41 ± 1.54 pg/mL and 5.18 ± 0.50 pg/mL, respectively. The coefficient of variation (CV) of the repeatability experiment (sample numbers = 3) is smaller than 10.6%. In addition, the affinity constants of the sensor for anti-IgG/IgG and biotin/streptavidin are estimated to be 1.06 × 10⁷ M⁻¹ and 7.30 × 10⁹ M⁻¹, respectively. The result shows that the GO-OW LSPR biosensor has good repeatability and very low detection sensitivity. It can be used for detecting low concentrations or small biomolecules in the future.