Abstract
Extreme Learning Machines (ELMs) are a versatile Machine Learning (ML) algorithm that features as the main advantage the possibility of a seamless implementation with physical systems. Yet, despite the success of the physical implementations of ELMs, there is still a lack of fundamental understanding in regard to their optical implementations. In this context, this work makes use of an optical complex media and wavefront shaping techniques to implement a versatile optical ELM playground to gain a deeper insight into these machines. In particular, we present experimental evidences on the correlation between the effective dimensionality of the hidden space and its generalization capability, thus bringing the inner workings of optical ELMs under a new light and opening paths toward future technological implementations of similar principles.

Abstract
The growing demand for multiparameter sensors includes compact devices accompanied by simple calibration processes to distinguish the outputs from each other. This paper evaluates a scheme to determine multiple parameters of a medium using localized surface plasmon resonances (SPR) excited on a Dshaped photonic crystal fiber (PCF) partially covered by two gold layers of different thicknesses. We demonstrate that the proposed sensing platform, once customized to characterize the possible dispersive profiles of the refractive index of the analyte, also allows interrogating the temperature of a sample from a linear relationship. Since the plasmonic resonances are excited at separated and low crosstalk spectral channels, different sensing responses can be obtained simultaneously in the same location of the D-shaped PCF. These features turn out the SPR sensor a suitable tool for simultaneous monitoring of optical dispersion and temperature. © 2023 SBMO/SBMag.

Abstract

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
Water vapor sorption is a powerful tool for the analysis of cement paste, one of the most used substances by mankind. The monitoring of cementitious materials is fundamental for the improvement of infrastructure resilience, which has a deep impact on the economy, the environment, and on society. In this work, a multimode fiber was embedded in cement paste for real-time monitoring of cement paste water vapor sorption. Changes in the reflected light intensity due to the build-up of water in the cement paste's pores were exploited for this purpose. The sample was 7-day moist cured, and the relative humidity was controlled between 8.9% and 97.6%. Reflected light intensity was converted into a specific surface area of cement paste (133 m(2)/g) and thickness of water through the Brunauer-Emmett-Teller (BET) method and into a pore size distribution through the Barret-Joyner-Halenda (BJH) method. The results achieved through reflected light intensity agree with those found in the literature, validating the usage of this setup for the monitoring of water vapor sorption, breaking away from standard gravimetric measurements.

Abstract
Biochemical-chemical sensing with plasmonic sensors is widely performed by tracking the responses of surface plasmonic resonance peaks to changes in the medium. Interestingly, consistent sensitivity and resolution improvements have been demonstrated for gold nanoparticles by analyzing other spectral features, such as spectral inflection points or peak curvatures. Nevertheless, such studies were only conducted on planar platforms and were restricted to gold nanoparticles. In this work, such methodologies are explored and expanded to plasmonic optical fibers. Thus, we study-experimentally and theoretically-the optical responses of optical fiber-doped gold or silver nanospheres and optical fibers coated with continuous gold or silver thin films. Both experimental and numerical results are analyzed with differentiation methods, using total variation regularization to effectively minimize noise amplification propagation. Consistent resolution improvements of up to 2.2x for both types of plasmonic fibers are found, demonstrating that deploying such analysis with any plasmonic optical fiber sensors can lead to sensing resolution improvements.