[1] P. J. Landrigan, J. J. Stegeman, L. E. Fleming. Human health and ocean pollution. Ann. Glob. Health, 86, 151(2020).

[2] Z. H. Wang, X. X. Lu, K. Zhang. Distribution and contamination of metals and biogenic elements in sediments from Zhifu Bay of the Yellow Sea, China. J. Environ. Sci., 41, 6-15(2016).

[3] Y. F. Guo, Y. Q. Sun, Z. H. Li. Detection, detoxification, and removal of multiply heavy metal ions using a recyclable probe enabled by click and declick chemistry. J. Hazard. Mater., 423, 127242(2022).

[4] R. Min, Z. Y. Liu, L. Pereira. Optical fiber sensing for marine environment and marine structural health monitoring: a review. Opt. Laser Technol., 140, 107082(2021).

[5] J. del Castillo-Nicolau, H. J. Hufschmidt. Reversible poisoning of nerve fibers by heavy-metal ions. Nature, 167, 146-147(1951).

[6] H. Kanwal, A. Raza, M. S. Zaheer. Transformation of heavy metals from contaminated water to soil, fodder and animals. Sci. Rep., 14, 11705(2024).

[7] A. Badeenezhad, H. Soleimani, S. Shahsavani. Comprehensive health risk analysis of heavy metal pollution using water quality indices and Monte Carlo simulation in R software. Sci. Rep., 13, 15817(2023).

[8] I. López-García, J. J. Marín-Hernández, M. Hernández-Córdoba. Speciation of chromium in waters using dispersive micro-solid phase extraction with magnetic ferrite and graphite furnace atomic absorption spectrometry. Sci. Rep., 10, 5268(2020).

[9] T. Van Acker, S. Theiner, E. Bolea-Fernandez. Inductively coupled plasma mass spectrometry. Nat. Rev. Methods Primers, 3, 52(2023).

[10] K. Tsukagoshi, M. Hashimoto, R. Nakajima. Application of microchip capillary electrophoresis with chemiluminescence detection to an analysis for transition-metal ions. Anal. Sci., 16, 1111-1112(2000).

[11] R. Y. Ding, Y. H. Cheong, A. Ahamed. Heavy metals detection with paper-based electrochemical sensors. Anal. Chem., 93, 1880-1888(2021).

[12] Y.-L. Chen, Y.-H. Hu, X. Yang. Plasmon-enhanced fluorescence of gold nanoparticle/graphene quantum dots for detection of Cr³⁺ ions. Photonics Res., 11, 1781-1790(2023).

[13] H. Y. Meng, W. Shen, G. B. Zhang. Fiber Bragg grating-based fiber sensor for simultaneous measurement of refractive index and temperature. Sens. Actuators B Chem., 150, 226-229(2010).

[14] W. L. Zheng, B. Han, Y. N. Zhang. Reflective optical fiber SPR sensor with DNA modification for high-sensitive Hg²⁺ concentration measurement. Microchem. J., 203, 110861(2024).

[15] X. Y. Fan, Y. Guo, L. F. Wang. Chitosan/polyacrylic acid film based on a tapered fiber structure for the ultrasensitive detection of Cu²⁺ concentration. Measurement, 235, 114923(2024).

[16] O. Zhernovaya, O. Sydoruk, V. Tuchin. The refractive index of human hemoglobin in the visible range. Phys. Med. Biol., 56, 4013-4021(2011).

[17] K. M. Mayer, J. H. Hafner. Localized surface plasmon resonance sensors. Chem. Rev., 111, 3828-3857(2011).

[18] H. Ahmad, M. J. M. Makhfuz, N. Yusoff. The effect of Ti₂C MXene on the performance of optical fiber-based surface plasmon resonance sensor towards lead detection. Mater. Sci. Eng. B, 302, 117232(2024).

[19] L. S. Laxmeshwar, M. S. Jadhav, J. F. Akki. Elemental analysis of wastewater effluent using highly sensitive fiber Bragg grating sensor. Opt. Laser Technol., 105, 45-51(2018).

[20] S. Ghosh, K. Dissanayake, S. Asokan. Lead (Pb²⁺) ion sensor development using optical fiber gratings and nanocomposite materials. Sens. Actuators B Chem., 364, 131818(2022).

[21] S. Y. Tan, S. C. Lee, T. Okazaki. Detection of mercury (II) ions in water by polyelectrolyte-gold nanoparticles coated long period fiber grating sensor. Opt. Commun., 419, 18-24(2018).

[22] F. Liu, T. Guo, J. G. Liu. High-sensitive and temperature-self-calibrated tilted fiber grating biological sensing probe. Chin. Sci. Bull., 58, 2611-2615(2013).

[23] T. B. Zhu, M. Loyez, K. Chah. Gold-coated tilted fiber Bragg gratings for lead ion sensing. Opt. Express, 31, 32478-32487(2023).

[24] Z. Q. Ren, Z. L. Huang, F. X. Wang. Tilted fiber Bragg grating surface plasmon resonance based optical fiber cadmium ion trace detection. Sens. Actuators B Chem., 393, 134247(2023).

[25] Y. C. Lu, R. Geng, C. C. Wang. Polarization effects in tilted fiber Bragg grating refractometers. J. Lightwave Technol., 28, 1677-1684(2010).

[26] N. J. Alberto, C. A. Marques, J. L. Pinto. Three-parameter optical fiber sensor based on a tilted fiber Bragg grating. Appl. Opt., 49, 6085-6091(2010).

[27] S. Cieszczyk, D. Harasim, P. Kisala. A novel simple TFBG spectrum demodulation method for RI quantification. IEEE Photonics Technol. Lett., 29, 2264-2267(2017).

[28] Z. X. Huang, N. Yang, J. W. Xie. Improving accuracy and sensitivity of a tilted fiber bragg grating refractometer using cladding mode envelope derivative. J. Lightwave Technol., 41, 4123-4129(2023).

[29] A. Bekmurzayeva, M. Shaimerdenova, Y. Abukhanov. Detection of tilted fiber Bragg grating fiber-optic sensors with short-term KLT: towards low-cost biosensors. IEEE Sensors, 1-4(2018).

[30] M. Lobry, C. Guyot, D. Kinet. Plasmonic biosensing with tilted fiber Bragg gratings interrogated using a 512-pixel spectrometer. Opt. Lett., 48, 976-979(2023).

[31] E. Chubchev, K. Tomyshev, I. Nechepurenko. Machine learning approach to data processing of TFBG-assisted SPR sensors. J. Lightwave Technol., 40, 3046-3054(2022).

[32] Z. H. Cao, T. T. Xia, S. Q. Zhang. Improved spectral interrogation of tilted fiber Bragg grating refractometer using residual convolutional neural networks. J. Lightwave Technol., 40, 7403-7411(2022).

[33] C. X. Li, H. C. Qi, X. Han. Ultrahigh-speed phase demodulation of a Fabry-Perot sensor based on fiber array parallel spectral detection. Opt. Lett., 49, 714-717(2024).

[34] Z. Z. Yue, D. Zheng, X. H. Zou. Large dynamic range interrogation technique for fiber-optic interferometric sensor based on AWG and deep learning algorithm. IEEE Sens. J., 24, 278-286(2024).

[35] Z. Z. Yue, W. B. Li, D. Zheng. Performance enhancement of arrayed waveguide grating-based fibre Bragg grating interrogation assisted by random forest. Electron. Lett., 59, e12682(2023).

[36] S. F. Ren, S. C. Chen, J. L. Yang. High-efficiency FBG array sensor interrogation system via a neural network working with sparse data. Opt. Express, 31, 8937-8952(2023).

[37] S. C. Chen, F. F. Yao, S. F. Ren. Cost-effective improvement of the performance of AWG-based FBG wavelength interrogation via a cascaded neural network. Opt. Express, 30, 7647-7663(2022).

[38] T. Erdogan. Fiber grating spectra. J. Lightwave Technol., 15, 1277-1294(1997).

[39] T. Erdogan. Cladding-mode resonances in short- and long-period fiber grating filters. J. Opt. Soc. Am. A, 14, 1760-1773(1997).

[40] Y. F. Zhou, Y. N. Zhang, Q. Yu. Application of machine learning in optical fiber sensors. Measurement, 228, 114391(2024).

[41] G. Huang, Z. Liu, L. van der Maaten. Densely connected convolutional networks. 30th IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2261-2269(2017).

[42] M. Kikuchi, T. Ogasawara, S. Fujii. Application of machine learning for improved accuracy of simultaneous temperature and strain measurements of carbon fiber-reinforced plastic laminates using an embedded tilted fiber Bragg grating sensor. Composites Part A, 161, 107108(2022).

[43] K. A. Tomyshev, E. S. Manuilovich, D. K. Tazhetdinova. High-precision data analysis for TFBG-assisted refractometer. Sens. Actuator A Phys., 308, 112016(2020).

[44] H. Fasseaux, M. Loyez, C. Caucheteur. Machine learning unveils surface refractive index dynamics in comb-like plasmonic optical fiber biosensors. Commun. Eng., 3, 34(2024).

[45] X. Quan, E. S. Fry. Empirical equation for the index of refraction of seawater. Appl. Opt., 34, 3477-3480(1995).