Abstract
The Theory of General Relativity is currently the most accepted model to describe gravity, and although many experiments and observations continue to validate it, recent astrophysical and cosmological observations require to include new forms of matter and energy (dark matter and dark energy), to be consistent. Modified theories of gravity with non-minimal coupling between curvature and matter are extensions of the Theory of General Relativity and have been proposed to address these shortcomings. Interestingly, matter at large scales behaves as a fluid and under certain approximations, the field equations can be approximated to a generalized Schrodinger-Newton system of equations. This model is largely found in the nonlinear optical systems, in particular to describe light propagating in nonlinear and nonlocal optical materials and also as a base model for the development of many optical analogues. Due to this, there are a wide variety of numerical methods developed to tackle this type of mathematical models, and that can be used to study these alternative gravity models. In this work, we explore the application of these numerical techniques based on GPGPU supercomputing, initially developed to study light propagating in nonlinear optical systems, to explore a particular non-minimal coupled gravity model. This model, in the nonrelativistic limit, modifies the hydrodynamic equations with the introduction of an attractive Yukawa potential and a repulsive one proportional to the matter density. We used the Schrodinger-Newton formalism to numerically study this model and, through the imaginary-time propagation method, we found stationary solutions that were sustained by the repulsive potential introduced by the non-minimal coupled model, even in the absence of a pressure term. We developed an analytical study in the Thomas-Fermi approximation and compared the predictions with numerical solutions. Finally, we explored how this gravity model may be emulated in the laboratory as an optical analogue.

Abstract
The last years saw the emergence of nonlinear optical materials, with local and nonlocal nonlinearities, as experimentally accessible systems to implement optical analogues of quantum fluids. In these systems, a light beam propagating in the nonlinear medium can be interpreted as a fluid, where the diffraction in the transverse plane to the propagation gives the effective mass of the fluid and the medium nonlinearity mediates the required interactions between the photons. This fluid interpretation and its application have been extensively studied, from the creation of superfluid-like flows and the study of phenomena associated with this effect to the implementation of gravity analogues. Furthermore, many optical materials have been considered, with a special interest in the ones that offer tunable mechanisms that allow to easily control the system properties to better explore and emulate the different phenomena. Recently, nematic liquid crystals have been proposed as an interesting tunable material capable of supporting superfluids of light. These systems have a nonlocal character and offer external mechanisms that can be used to tailor the nonlinearity to better emulate the desired analogue system. Indeed, through the application of an external electric field perpendicular to the direction of propagation, is it possible to control the nonlocal length of the nonlinearity. This mechanism offers interesting opportunities in the present context. In this work, through numerical methods based on GPGPU supercomputing, we explore the possibility of observing superfluid effects in defocusing nematic liquid crystals. In particular, we explore the possibility of observing the drag force cancellation and the emission of quantized vortices, which are two manifestations of a superfluid flow. Furthermore, we also discuss the possibility of using these systems for creating an analogue of quantum turbulence with these materials. These studies constitute a stepping-stone towards the implementation of gravity analogues with nematic liquid crystals.

Abstract
The need for faster and energy-efficient computing technologies has recently pushed for major developments on alternative computing paradigms to the common von Neumann architecture. Amongst those, reservoir computing framework is an emerging concept that leverages a simple training process and eases transference to hardware implementations, allowing any given nonlinear physical system to act as a computing platform. In this work, we explore how we can make use of a discrete chain of solitons to create an effective reservoir computing framework, investigating not only the ability to learn data but also to predict models depending on the strength of the nonlinear interaction of the media. Probing the role of the nonlinear separation for tasks involving nonlinear separable data, these results open new possibilities for a multitude of physical implementations in the context of optical sciences, from optical fibers to nonlinear crystals.

Abstract
Fluids of light is an emergent topic in optical sciences that exploits the fluid-like properties of light to establish controllable and experimentally accessible physical analogues of quantum fluids. In this work we explore this concept to generate and probe quantum turbulence phenomena by using the fluid behavior of light propagating in a defocusing nonlinear media. The proposal presented makes use of orthogonal polarizations and incoherent beam interaction to establish a theoretical framework of an analogue two-component quantum fluid, a physical system that features a modified Bogoliubov-like dispersion relation for the perturbative excitations featuring regions of instability. We demonstrate that these unstable regions can be tuned by manipulating the relative angle of incidence between the two components, allowing to define an effective range of energy injection capable of exciting turbulent phenomena. Our numerical investigations confirm the theory and show evidence of direct and inverse turbulent cascades expected from weak wave turbulence theories. The works end on a discussion concerning its possible experimental realization, allowing the access to quantum turbulence in regimes beyond those previously explored by making use of the controllable aspects of tabletop fluids of light experiments.

Abstract
Surface plasmon resonance (SPR) and localized surface plasmon resonance (LSPR) are among the most common and powerful label-free refractive index-based biosensing techniques available nowadays. Focusing on LSPR sensors, their performance is highly dependent on the size, shape, and nature of the nanomaterial employed. Indeed, the tailoring of those parameters allows the development of LSPR sensors with a tunable wavelength range between the ultra-violet (UV) and near infra-red (NIR). Furthermore, dealing with LSPR along optical fiber technology, with their low attenuation coefficients at NIR, allow for the possibility to create ultra-sensitive and long-range sensing networks to be deployed in a variety of both biological and chemical sensors. This work provides a detailed review of the key science underpinning such systems as well as recent progress in the development of several LSPR-based biosensors in the NIR wavelengths, including an overview of the LSPR phenomena along recent developments in the field of nanomaterials and nanostructure development towards NIR sensing. The review ends with a consideration of key advances in terms of nanostructure characteristics for LSPR sensing and prospects for future research and advances in this field.

Abstract
Optical fiber sensing systems have been widely developed for several fields such as biomedical diagnosis, food technology, military and industrial applications and civil engineering. Nowadays, the growth and advances of optical fiber sensors (OFS) are focused on the development of novel sensing concepts and transducers as well as sensor cost reduction. This review provides an overview of the state-of-the-art of OFS based on sol-gel materials for diverse applications with particular emphasis on OFS for structural health monitoring of concrete structures. The types of precursors used in the development of sol-gel materials for OFS functionalization to monitor a wide range of analytes are debated. The main advantages of OFS compared to other sensing systems such as electrochemical sensors are also considered. An interdisciplinary review to a broad audience of engineers and materials scientists is provided and the relationship between the chemistry of sol-gel material synthesis and the development of OFS is considered. To the best of the authors' knowledge, no review manuscripts were found in which the fields of sol-gel chemistry and OFS are correlated. The authors consider that this review will serve as a reference as well as provide insights for experts into the application of sol-gel chemistry and OFS in the civil engineering field.