Abstract
The detection of volatile organic compounds is accomplished with a sensing device based on a long period fiber grating (LPFG) coated with a zinc oxide (ZnO) thin layer with self-temperature compensation. The ZnO coating structure was produced onto the cladding of the fiber by thermal oxidation of a metallic Zn thin film. The morphological characterization of ZnO thin films, grown at the same time on silicon substrates, was performed using X-ray diffraction, X-ray Photoelectron Spectroscopy and Scanning Electron Microscope which shows very good agreement. LPFGs with 290 nm thick ZnO coating were fabricated and characterized for the detection of ethanol and hexane in vapor phase. For ethanol a sensitivity of 0.99 nm / g.m(-3) was achieved when using the wavelength shift interrogation mode, while for hexane a much lower sensitivity of 0.003 nm / g.m(-3) was measured, indicating a semi-selectivity of the sensor with a spectral resolution better than 3.2 g.m(-3).

Abstract
Many optical systems based on surface plasmon resonance (SPR) have been developed for working as refractometers, chemical sensors or even for measuring the thickness of metal and dielectric thin films. Sensors based on SPR present very high sensitivity to refractive index (RI) variations when compared to the traditional RI sensors. However, these kinds of systems are usually large, expensive and therefore cannot be used for remote sensing. Optical fibre sensors based on SPR are usually implemented using multimode optical fibres cope with the requirements for remote sensing. In this section a new type of SPR sensor based in a single mode fibre (SMF) is proposed. A section of the SMF was chemically etched by emersion in a 48 % hydrofluoric acid solution, resulting in a tapering effect, with the cladding removing while the core is kept intact. Simulation results are in good agreement with the experimental spectral resonance dip attained around 1550 nm. Sensitivities of 3800 and 5100 nm/RIU were achieved for the reflection and for the transmission modes, respectively, for RI in the 1.33 to 1.37 range.

Abstract
We investigate spectroscopic imaging ellipsometry for monitoring biomolecules at surfaces of nanoparticles. For the modeling of polarimetric light scattering off surface-adsorbed core-shell nanoparticles, we employ an extension of the exact solution for the scattering by particles near a substrate presented by Bobbert and Vlieger, which offers insight beyond that of the Maxwell-Garnett effective medium approximation. Varying thickness and refractive index of a model bio-organic shell results in systematic and characteristic changes in spectroscopic parameters ? and ?. The salient features and trends in modeled spectra are in qualitative agreement with experimental data for antibody immobilization and fibronectin biorecognition at surfaces of gold nanoparticles on a silicon substrate, but achieving a full quantitative agreement will require including additional effects, such as nanoparticle-substrate interactions, into the model. © 2017 Optical Society of America.

Abstract
This paper presents an autonomous robotic system, IRIS, designed for lost fishing gear recovery. The vehicle was developed in the context of the NetTag project. This is a European Union project funded by EASME the Executive Agency for Small and Medium Enterprises addressing marine litter, and the reduction of quantity and impact of lost fishing gears in the ocean. NetTag intends to produce new technological devices for location and recovery of fishing gear and educational material about marine litter, raise awareness of fisheries industry and other stakeholders about the urgent need to combat marine litter and increase scientific knowledge on marine litter problematic, guaranteeing the engagement of fishers to adopt better practices to reduce and prevent marine litter derived from fisheries. The design of IRIS is presented in detail, addressing the mechanical design, hardware architecture, sensor system and navigation and control. Preliminary tests in tank and in controlled sea conditions are presented and ongoing developments on the recovery system are discussed.

Abstract
This work addresses the use of hyperspectral imaging systems for remote detection of marine litter concentrations in oceanic environments. The work consisted on mounting an off-the-shelf hyperspectral imaging system (400-2500 nm) in two aerial platforms: manned and unmanned, and performing data acquisition to develop AI methods capable of detecting marine litter concentrations at the water surface. We performed the campaigns at Porto Pim Bay, Fail Island, Azores, resorting to artificial targets built using marine litter samples. During this work, we also developed a Convolutional Neural Network (CNN-3D), using spatial and spectral information to evaluate deep learning methods to detect marine litter in an automated manner. Results show over 84% overall accuracy (OA) in the detection and classification of the different types of marine litter samples present in the artificial targets.

Abstract
This paper presents the development of a hyperbaric system able to collect, transport and maintain deep-sea species in controlled condition from the sea floor up to the surface (HiperSea System). The system is composed by two chambers coupled with a transference set-up. The first chamber is able to reach a maximum of 1km depth collecting both benthic and pelagic deep-sea species. The second chamber is a life support compartment to maintain the specimens alive at the surface, in hyperbaric conditions.