Abstract
Distributed Acoustic Sensing (DAS) leverages the sensitivity of optical fibers to detect environmental vibrations. This study demonstrates the capability of DAS to identify and characterize the acoustic signatures of passing vessels, highlighting its potential to enhance maritime surveillance and monitoring. © 2025 Elsevier B.V., All rights reserved.

Abstract
The fabrication of Mach-Zehnder and Fabry-Perot interferometers in SMF-28e fibers by femtosecond laser direct writing is demonstrated. The feasibility and effectiveness of this technique in fabricating high-sensitivity fiber optic interferometers is highlighted. TiO2 coated Mach-Zehnder interferometers exhibit improved refractive index sensitivity compared to uncoated interferometers, while the dual-cavity intrinsic Fabry-Perot interferometers shows enhanced spectral response and sensitivity for measurement of gas pressure.

Abstract
Optical resonant structures, such as circular disks and optical microbubble resonators (OMBRs), are crucial for highresolution chemical and biochemical sensing. Both can be integrated into microfluidic systems: resonant disks can be fabricated within microfluidic channels, while OMBRs use thin silica capillary walls to confine fluid samples in a hollowcore cavity. Optical modes are typically excited using tapered optical fibers, which offer efficiency but lack robustness for functional devices. This work presents two femtosecond laser-written waveguide designs for exciting whispering gallery modes (WGMs) in these resonant structures. For resonant disks, suspended waveguides are fabricated tangentially between the microfluidic channel walls. For OMBRs, integrated waveguides are written on fused silica substrates to excite resonant modes. Both configurations provide stable and robust optical sensing solutions. The OMBR platform achieved a sensitivity of 45 nm/RIU with a resolution of 4.4x10(-5) RIU, while monolithically integrated disks reached 80 nm/RIU with a resolution of 7.0x10(-4) RIU. In both cases, the Q-factor exceeded 10(4) across the measurement range. These results confirm that femtosecond laser-written waveguides can efficiently excite resonant modes, offering promising platforms for chemical and biochemical sensing applications.

Abstract
This work studies the influence of an Erbium-Doped Fiber Amplifier (EDFA) on the phase variation of light in an optical fiber. To this end, the state of polarization (SOP) was measured as a function of optical power by adjusting the EDFA amplification, for two different laser output powers (2 dBm and 5 dBm). Results show that phase variation correlates with changes in optical power in both cases.

Abstract
Topological photonics, leveraging concepts from condensed matter physics, offers transformative potential in the design of robust optical systems. This study investigates the integration of topologically protected edge states into plasmonic nanostructures for enhanced optical sensing. We propose a toy model comprising two chains of metallic filaments forming a one-dimensional plasmonic crystal with diatomic-like unit cells, positioned on a waveguide. The system exhibits edge states localized at the boundaries and a central defect, supported by the Su-Schrieffer-Heeger (SSH) model. These edge states, characterized by significant electric field enhancement and topological robustness, are shown to overcome key limitations in traditional plasmonic sensors, including sensitivity to noise and fabrication inconsistencies. Through coupled mode theory, we demonstrate the potential for strong coupling between plasmonic and guided optical modes, offering pathways for improved interferometric sensing schemes. This work highlights the applicability of topological photonics in advancing optical sensors.

Abstract
This study explores the application of machine learning algorithms to optimize the geometry of the plasmonic layer in a surface plasmon resonance photonic crystal fiber sensor. By leveraging the simplicity of linear regression ( LR) alongside the advanced predictive capabilities of the gradient boosted regression (GBR) algorithm, the proposed approach enables accurate prediction and optimization of the plasmonic layer's configuration to achieve a desired spectral response. The integration of LR and GBR with computational simulations yielded impressive results, with an R-2 exceeding 0.97 across all analyzed variables. Moreover, the predictive accuracy demonstrated a remarkably low margin of error, epsilon < 10(-15). This combination of methods provides a robust and efficient pathway for optimizing sensor design, ensuring enhanced performance and reliability in practical applications.