Abstract
Subwavelength cells of metallic nanorods arrayed in a dielectric background, termed "metamaterials", present bulk properties that are useful to control and manipulate surface plasmon resonances. Such feature finds tremendous potential in providing a broad manifold of applications for plasmonic optical sensors. In this paper, we propose a surface-plasmon-resonance-based sensor with spectral response tunable by the volume fraction of silver present in a metamaterial layer deposited on a D-shaped photonic crystal fiber. Using computational simulations, we show that sensitivity and resolution can be hugely altered by changing the amount of constituents in the metamaterial, with no further modifications in the structure of the sensor. Moreover, the designed sensor can also be applied to label the average volume fraction of silver in the metamaterial layer and then to estimate its effective constitutive parameters.

Abstract
Optical tweezers use light to trap and manipulate mesoscopic scaled particles with high precision making them a useful tool in a plethora of natural sciences, with emphasis on biological applications. In principle, the Brownian-like dynamics reflect trapped particle properties making it a robust source of information. In this work, we exploit this information by plotting histogram based images of 250ms of position or displacement used as input to a Convolution Neural Network. Results of 2-fold stratified cross-validation show satisfying classifications between sizes or types of particles: Polystyrene and Polymethilmethacrylate thus highlighting the potential of CNN approaches in faster and non-invasive applications in intelligent opto and microfluidic devices using optical trapping tools.

Abstract
Extreme learning machines (ELMs) are a versatile machine learning technique that can be seamlessly implemented with optical systems. In short, they can be described as a network of hidden neurons with random fixed weights and biases, that generate a complex behaviour in response to an input. Yet, despite the success of the physical implementations of ELMs, there is still a lack of fundamental understanding about their optical implementations. This work makes use of an optical complex media to implement an ELM and introduce an ab-initio theoretical framework to support the experimental implementation. We validate the proposed framework, in particular, by exploring the correlation between the rank of the outputs, H, and its generalization capability, thus shedding new light into the inner workings of optical ELMs and opening paths towards future technological implementations of similar principles.

Abstract
The use of concrete has been widespread in our society in housing and infrastructure, despite the environmental cost associated with its production. Its decay poses a social, economic, and environmental problem. Currently, the carbonation of cement paste is monitored through the measurement of its pH, with several optical fiber sensors (OFS) have been produced for this purpose. In the current work the focus is, also, on the carbonation monitoring of cement paste through an OFS, but not through pH measurements. Single fiber reflectance spectroscopy, previously employed to measure cement paste durability, is used to monitor the discoloration of cement paste caused by carbonation. As the carbonation front reaches the fiber tip embedded in the cement paste, the signal reflected onto the fiber increases. The accelerated carbonation of two limestone cement paste samples in an atmosphere of 100% CO2 was successfully monitored. The applicability of the sensor for operational use with ambient CO2 was confirmed through the measurement of carbonation at 3% CO2. The cross interference from water ingress and egress was also evaluated, and it didn't hinder the measurements of carbonation. Therefore, a novel OFS capable of measuring cement paste carbonation and durability, was achieved. © Published under licence by IOP Publishing Ltd.

Abstract
A strain gauge sensor based on Fiber Bragg Grating (FBG) for diameter measurement is proposed and experimentally demonstrated. The sensor is easily fabricated inserting the FBG on the strain gauge-it was fabricated using a 3D printer-and fixing the FBG in two points of this structure. The idea is to vary the diameter of the structure. We developed two experimental setups, the first one is used to evaluate the response of the FBG to strain and the second one to assess the possibility of using the structure developed to monitor the desired parameter. The results demonstrated that the structure can be used as a way to monitor the diameter variation in some applications. The sensor presented a sensitivity of 0.5361 nm/mm and a good linear response of 0.9976 using the Strain Gauge with FBG and fused taper.

Abstract
Power transformers are central elements of power transmission systems and their deterioration can lead to system failures, causing major disruptions in service. Catastrophic failures can occur, posing major environmental hazards due to fires, explosions, or oil spillage. Early fault detection can be accomplished or estimated using electrical sensors or a chemical analysis of oil or gas samples. Conventional methods are incapable of real-time measurements with a low electrical noise due to time-consuming analyses or susceptibility to electromagnetic interference. Optical fiber sensors, passive elements that are immune to electromagnetic noise, are capable of structural monitoring by being enclosed in power transformers. In this work, optical fiber sensors embedded in 3D printed structures are studied for vibration monitoring. The fiber sensor is encapsulated between two pressboard spacers, simulating the conditions inside the power transformer, and characterized for vibrations with frequencies between 10 and 800 Hz, with a constant acceleration of 10 m/s(2). Thermal aging and electrical tests are also accomplished, aiming to study the oil compatibility of the 3D printed structure. The results reported in this work suggest that structural monitoring in power transformers can be achieved using optical fiber sensors, prospecting real-time monitoring.