Abstract
Reinforced concrete structures are prevalent in infrastructure and are of significant economic and social importance to humanity. However, they are prone to decay from cement paste carbonation. pH sensors have been developed to monitor cement paste carbonation, but their adoption by the industry remains limited. This work introduces two new methods for monitoring cement paste carbonation in real time that have been validated through the accelerated carbonation of cement paste samples. Both configurations depart from traditional pH monitoring. In the first configuration, the carbonation depth of a cement paste sample is measured using two CO2 optical fiber sensors. One sensor is positioned on the surface of the sample, while the other is embedded in the middle. As the carbonation depth progresses and reaches the embedded CO2 sensor, the combined response of the sensors changes. In the second configuration, a multimode fiber is embedded within the paste, and its carbonation is monitored by observing the increase in reflected light intensity (1.6-18%) resulting from the formation of CaCO3. Its applicability in naturally occurring carbonation is tested at concentrations of 3.2% CO2, and the influence of water is positively evaluated; thus, this setup is suitable for real-world testing and applications.

Abstract
The sensitivity of one-dimensional Bloch surface wave (BSW) sensors to external refractive index variations using Kretschmann's configuration is calculated analytically by employing first-order perturbation theory for both TE and TM modes. This approach is then validated by com- parison with both transfer matrix method simulations and experimental results for a chosen photonic crystal structure. Experimental sensitivities of (8.4 +/- 0.2)x102 and (8.4 +/- 0.4)x102 nm/RIU were obtained for the TE and TM BSW modes, corresponding to errors of 0.02% and 4%, respectively, when comparing with the perturbation the- ory approach. These results provide interesting insights into photonic crystal design for Bloch surface wave sensing by casting light into the important parameters related with sen- sor performance.(c) 2023 Optica Publishing Group

Abstract
This study presents the dependence of strain sensitivity on cavity length in conventional Fabry-Perot (F-P) sensors. A high number of F-P sensors were required and to ensure their reproducibility, a manufacturing process was developed to obtain similar sensors but with different types of lengths. A hollow-core silica tube was used to fabricate several F-P cavities by fusion splicing it between two sections of SMF28 fiber. The fabricated F-P has a varying length ranging from 15 to 2500 mu m. The cavities were measured under a microscope and the reflected spectrum was acquired for each one. Strain measurements were performed for a maximum strain of 1000 mu epsilon. The strain sensitivity showed a highly linear correlation with increment lambda(FSR). Small length variations for short cavities heavily affect the FSR value. The smallest and longest cavities present sensitivities of 8.71 and 2.68 pm/mu epsilon, respectively. Thermal characterization for low- and high-temperature regimes was also performed and is constant for tested sensors.

Abstract
This work addresses the fabrication of straight silica-core liquid-cladding suspended waveguides inside a microfluidic channel through fs-laser micromachining. These structures enable the reconfiguration of the waveguide's mode profile and enhance the evanescent interaction between light and analyte. Further, their geometry resembles a tapered optical fiber with the added advantage of being monolithically integrated within a microfluidic platform. The fabrication process includes an additional post-processing thermal treatment responsible for smoothening the waveguide surface and reshaping it into a circular cross-section. Suspended waveguides with a minimum core diameter of 3.8 mu m were fabricated. Their insertion losses can be tuned and are mainly affected by mode mismatch between the coupling and suspended waveguides. The transmission spectrum was studied and it was numerically confirmed that it consists of interference between the guided LP01 mode and uncoupled light and of modal interference between the LP01 and LP02 modes.

Abstract
A new sensing platform based on long-period fiber gratings (LPFGs) for direct, fast, and selective detection of human immunoglobulin G (IgG; Mw = 150 KDa) was developed and characterized. The transducer's high selectivity is based on the specific interaction of a molecularly imprinted polymer (MIPs) design for IgG detection. The sensing scheme is based on differential refractometric measurements, including a correction system based on a non-imprinted polymer (NIP)-coated LPFG, allowing reliable and more sensitive measurements, improving the rejection of false positives in around 30%. The molecular imprinted binding sites were performed on the surface of a LPFG with a sensitivity of about 130 nm/RIU and a FOM of 16 RIU-1. The low-cost and easy to build device was tested in a working range from 1 to 100 nmol/L, revealing a limit of detection (LOD) and a sensitivity of 0.25 nmol/L (0.037 mu g/mL) and 0.057 nm.L/nmol, respectively. The sensor also successfully differentiates the target analyte from the other abundant elements that are present in the human blood plasma.

Abstract
The estimation of the spectral absorption coefficient of biological tissues provides valuable information that can be used in diagnostic procedures. Such estimation can be made using direct calculations from invasive spectral measurements or though machine learning algorithms based on noninvasive or minimally invasive spectral measurements. Since in a noninvasive approach, the number of measurements is limited, an exploratory study to investigate the use of artificial generated data in machine learning techniques was performed to evaluate the spectral absorption coefficient of the brain cortex. Considering the spectral absorption coefficient that was calculated directly from invasive measurements as reference, the similar spectra that were estimated through different machine learning approaches were able to provide comparable information in terms of pigment, DNA and blood contents in the cortex. The best estimated results were obtained based only on the experimental measurements, but it was also observed that artificially generated spectra can be used in the estimations to increase accuracy, provided that a significant number of experimental spectra are available both to generate the complementary artificial spectra and to estimate the resulting absorption spectrum of the tissue. © 2022 Journal of Biomedical Photonics & Engineering. © J-BPE.