Abstract
Combining data from different sensing modalities has been a promising research topic for building better and more reliable data-driven models. In particular, it is known that multimodal spectral imaging can improve the analytical capabilities of standalone spectroscopy techniques through fusion, hyphenation, or knowledge distillation techniques. In this manuscript, we focus on the latter, exploring how one can increase the performance of a Laser-induced Breakdown Spectroscopy system for mineral classification problems using additional spectral imaging techniques. Specifically, focusing on a scenario where Raman spectroscopy delivers accurate mineral classification performance, we show how to deploy a knowledge distillation pipeline where Raman spectroscopy may act as an autonomous supervisor for LIBS. For a case study concerning a challenging Li-bearing mineral identification of spodumene and petalite, our results demonstrate the advantages of this method in improving the performance of a single-technique system. LIBS trained with labels obtained by Raman presents an enhanced classification performance. Furthermore, leveraging the interpretability of the model deployed, the workflow opens opportunities for the deployment of assisted feature discovery pipelines, which may impact future academic and industrial applications.

Abstract
In this paper we present results on the normalized temperature sensitivity of UV- and fs-induced fiber Bragg gratings in a singlemode fiber with similar to 4.7 mol% GeO2 and having an Ormocer coating. In the 1500-1600 nm wavelength range, the former shows an almost constant value of 6.165x10(-6) K-1, whilst the fs-induced present some variation not related with the strength of the grating but probably due to induced birefringence. The average value obtained was 6.191x10(-6) K-1 which is higher than the former. For the UV-induced gratings in the Corning SMF-28 fiber (3.67 mol% GeO2) the value obtained was 6.143x10(-6) K-1. The achieved values are compatible with the use of Corning 7980 silica-based cladding fiber. Preliminary results also show no measurable impact of the hydrogenation process or the strength of the grating on the normalized temperature sensitivity.

Abstract
A semi-distributed optical fiber bending extensometer system based on OTDR is proposed, consisting of N-loops designed to enable different maximum extension measurements and sensitivities. This system offers a low-cost solution for monitoring landslides and similar civil structures. Tests conducted at 1625 nm demonstrate that different series of sensors can be independently measured with elongation errors typically within +/- 0.25 cm across a range from 0 to 9 cm.

Abstract
A flexible wearable sensor utilizing a balloon-shaped interferometer structure, created from a bent standard single-mode fiber and a 3D-printed piece, was introduced and shown for respiratory monitoring. The interferometer is a compact, cost-effective, and easily fabricated sensor. The fiber's curvature causes interference between the core and cladding modes, which in turn results in the sensor operation. In the balloon-shaped curving section, light traversing the core partially escapes and interacts with the cladding. The preliminary results demonstrate an average displacement of 9.3 nm and the capability to evaluate breathing rate.

Abstract
A sensor based on the fiber Bragg grating (FBG) and additive manufacturing for diameter variation measurement is proposed and experimentally demonstrated in this work. Two designs were proposed: a FBG alone and a FBG in series with a spring. Three tests were developed for each design, and at the end, the statistical treatment was performed. The designs were fabricated using a 3D printer, and the FBG sensor is embedded. The results demonstrated that the structures proposed in this work can be used to monitor diameter variation, among other applications. The sensors, with and without spring in series, presented sensitivities of 0.0671 nm/mm and 0.5116 nm/mm, respectively, with a good linear response greater than 0.99.

Abstract
A refractive index sensor was designed using a novel approach to sensing based on a cleaved standard fiber Bragg grating (FBG) at the grating region, which enables the FBG to interact with its surrounding environment. The sliced-FBG (SFBG) exhibits a variable phase shift in the reflection response due to the length of the last grating's pitch, which differs from the rest. At the SFBG, the signal is the result of interference between the reflected wave from the grating and the transmitted spectrum returned due to Fresnel reflection at the final pitch, and the intensity of this signal depends on the refractive index of the surrounding medium. Based on this phenomenon, an intensity-based refractive index sensor with self- referencing technique was employed in this experiment, whereby the grating peak maximum point served as the signal reference, while the minimum of the Fresnel peak from each measurement functioned as the signal input. The proposed sensor demonstrated the ability to measure refractive indices within the range of 1.333-1.339, with a resolution of approximate to 10(-3), and a minimum detectable value of 6x10(-4) RIU (the data yielded a linear response with R-2=0.990). This study presents an innovative data sensing approach compared to existing techniques found in literature, which typically employ wavelength variation in the reflected wave to extract the desired information.