Abstract
Spectral Imaging techniques such as Laser-induced Breakdown Spectroscopy (LIBS) and Raman Spectroscopy (RS) enable the localized acquisition of spectral data, providing insights into the presence, quantity, and spatial distribution of chemical elements or molecules within a sample. This significantly expands the accessible information compared to conventional imaging approaches such as machine vision. However, despite its potential, spectral imaging also faces specific challenges depending on the limitations of the spectroscopy technique used, such as signal saturation, matrix interferences, fluorescence, or background emission. To address these challenges, this work explores the potential of using techniques from conventional RGB imaging to enhance the dynamic range of spectral imaging. Drawing inspiration from multi-exposure fusion techniques, we propose an algorithm that calculates a global weight map using exposure and contrast metrics. This map is then used to merge datasets acquired with the same technique under distinct acquisition conditions. With case studies focused on LIBS and Raman Imaging, we demonstrate the potential of our approach to enhance the quality of spectral data, mitigating the impact of the aforementioned limitations. Results show a consistent improvement in overall contrast and peak signal-to-noise ratios of the merged images compared to single-condition images. Additionally, from the application perspective, we also discuss the impact of our approach on sample classification problems. The results indicate that LIBS-based classification of Li-bearing minerals (with Raman serving as the ground truth), is significantly improved when using merged images, reinforcing the advantages of the proposed solution for practical applications.

Abstract
Management and reuse of wood waste can be a challenging process due to the frequent presence of hazardous contaminants. Conventional detection methods are often limited by the need for excessive sample preparation and lengthy and expensive analysis. Laser-induced Breakdown Spectroscopy (LIBS) is a rapid and micro- destructive technique that can be a promising alternative, providing in-situ and real-time analysis, with minimal to no sample preparation required. In this study, LIBS imaging was used to analyze wood waste samples to determine the presence of contaminants such as As, Ba, Cd, Cr, Cu, Hg, Pb, Sb, and Ti. For this analysis, a methodology based on detecting three lines per element was developed, offering a screening method that can be easily adapted to perform qualitative analysis in industrial contexts with high throughput operations. For the LIBS experimental lines selection, control and reference samples, and a pilot set of 10 wood wastes were analysed. Results were validated by two different X-ray Fluorescence (XRF) systems, an imaging XRF and a handheld XRF, that provided spatial elemental information and spectral information, respectively. The results obtained highlighted LIBS ability to detect highly contaminated samples and the importance of using a 3-line criteria to mitigate spectral interferences and discard outliers. To increase the dataset, a LIBS large-scale study was performed using 100 samples. These results were only corroborated by the XRF-handheld system, as it provides a faster alternative. In particular cases, ICP-MS analysis was also performed. The success rates achieved, mostly above 88 %, confirm the capability of LIBS to perform this analysis, contributing to more sustainable waste management practices and facilitating the quick identifi- cation and remediation of contaminated materials.

Abstract
Spectral imaging is a broad term that refers to the use of a spectroscopy technique to analyze sample surfaces, collecting and representing spatially referenced signals. Depending on the technique utilized, it allows the user to reveal features and properties of objects that are invisible to the human eye, such as chemical or molecular composition. However, the interpretability and interaction with the results are often limited to screen visualization of two-dimensional representations. To surpass such limitations, augmented reality emerges as a promising technology, assisted by recent developments in the integration of spectral imaging datasets onto three-dimensional models. Building on this context, this work explores the integration of spectral imaging with augmented reality, aiming to create an immersive toolset to increase the interpretability and interactivity of the results of spectral imaging analysis. The procedure follows a two-step approach, starting from the integration of spectral maps onto a three-dimensional models, and proceeding with the development of an interactive interface to allow immersive visualization and interaction with the results. The approach and tool developed present the opportunity for a user-centric extension of reality, enabling more intuitive and comprehensive analyses with the potential to drive advancements in various research domains.

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.