Abstract
This work provides a method that combines graphene oxide coating and self-image theory to improve the sensitivity of optical sensors. The sensor is designed specifically to measure the amount of glucose present quantitatively in aqueous solutions that replicate the range of glucose concentrations found in human saliva. COMSOL Multiphysics 6.0 was used to simulate the self-imaging phenomenon using a coreless silica fiber (CSF). For high-quality self-imaging, the second and fourth self-imaging points are usually preferred because of their higher coupling efficiency, which increases the sensor sensitivity. However, managing the fourth self-image is more difficult because it calls for a longer CSF length. As a result, the first and second self-image points were the focus of the simulation in this work. After the simulation, using the Layerby-Layer method, the sensor was constructed to a length that matched the second self-image point (29.12 mm) and coated with an 80 mu m/mL graphene oxide layer. When comparing uncoated and graphene oxide-covered sensors to measure glucose in liquids ranging from 25 to 200 mg/dL, one bilayer of polyethyleneimine/graphene demonstrated an eight-fold improvement in sensitivity. The final sensor, built on graphene oxide, showed stability with a low standard deviation of 0.6 pm/min. It also showed sensitivity at 10.403 +/- 0.004 pm/(mg/dL) with a limit of detection of 9.15 mg/dL.

Abstract
Raman technology offers a cutting-edge approach to measuring glucose solutions, providing precise and non-invasive analysis. By probing the vibrational energy levels of molecular bonds, Raman technology generates a unique spectral fingerprint that allows for the accurate determination of glucose concentrations. This study proposes the use of Raman spectroscopy to identify different glucose concentrations through the detection of Raman fingerprints. As expected, higher concentrations of glucose in the solution conducted to higher peak bands, indicating more glucose molecules interacting with light and consequently increasing the magnitude of inelastic scattering. This non-destructive approach preserves sample integrity and facilitates rapid analysis, making it suitable for various applications in biomedical research, pharmaceutical development, and food science.

Abstract
This work proposes a signal processing algorithm to analyse the optical signal from a Low Coherence Interferometric (LCI) system. The system uses a Mach-Zehnder (MZ) interferometer to interrogate a Fabry-Perot cavity, working as an optical sensor. This algorithm is based on the correlation and convolution operations, which allows the signal to be reconstructed based on itself, as well as, on the linearization of the signal phase, allowing the non-linearities of the actuator incorporated on the MZ interferometer to be compensated. The results show a noise reduction of 30 dB in the signal acquired. As a result, a reduction of 8.2 dB in the uncertainty of the measurement of the physical measurand is achieved. It is also demonstrated that the phase linearization made it possible to obtain a coefficient of determination (namely, R-squared) higher than 0.999.

Abstract
Optical fiber sensors were implemented to measure in-situ temperature variations in an oscillatory flow crystallizer operating in continuous. The sensors were fabricated by cleaved in the middle 8 mm-length fiber Bragg gratings, forming tips with a Bragg grating of 4 mm inscribed at the fiber ends. The geometry of the sensors fabricated, with a diameter of 125 mu m, allowed the temperature monitorization of the process flow, inside the crystallizer, at four different points: input, two intermediate points, and output. The results revealed that the proposed technology allows to perform an in-situ and in line temperature monitorization, during all the crystallization process, as an alternative to more expensive and complex technology.

Abstract
The aim of this work is to introduce a novel digital signal processing method for data acquired using low coherence interferometry (LCI) with a 1-kHz actuator oscillation frequency. Convolution and correlation operations are employed as efficient filters, reducing computational complexity for multilayer filtering. An envelope filtering technique is developed to address discrepancies in peak signal determination caused by nonlinear actuator motion. Additionally, a phase linearization method is presented to normalize the peak position relative to the actuator signal. Experimental results demonstrate a significant signal-to-noise ratio (SNR) improvement of 50 dB. Long-term measurements reveal an 11-dB noise reduction for frequencies below 1 mHz. This research enables LCI implementation at sampling rates of at least 1 kHz and expands its applicability to extreme measurement conditions.

Abstract
This paper presents a new type of phase-shifted Fiber Bragg Grating (FBG): the sliced-FBG (SFBG). The fabrication process involves cutting a standard FBG inside its grating region. As a result, the last grating pitch is shorter than the others. The optical output signal consists of the overlap between the FBG reflection and the reflection at the fiber-cleaved tip. This new fiber optic device has been studied as a vibration sensor, allowing for the characterization of this sensor in the frequency range of 150 Hz to 70 kHz. How the phase shift in the FBG can be controlled by changing the length of the last pitch is also shown. This device can be used as a filter and a sensing element. As a sensing element, we will demonstrate its application as a vibration sensor that can be utilized in various applications, particularly in monitoring mechanical structures.