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A semi-distributed optical fiber bending extensometer system based on OTDR is proposed, consisting of N-loops designed to enable different maximum extension measurements and sensitivities. This system offers a low-cost solution for monitoring landslides and similar civil structures. Tests conducted at 1625 nm demonstrate that different series of sensors can be independently measured with elongation errors typically within +/- 0.25 cm across a range from 0 to 9 cm.

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Software businesses are continuously increasing their presence in the cloud. While cloud computing is not a new research topic, designing software for the cloud is still challenging, requiring engineers to invest in research to become proficient at working with it. Design patterns can be used to facilitate cloud adoption, as they provide valuable design knowledge and implementation guidelines for recurrent engineering problems. This work introduces a pattern language for designing software for the cloud. We believe developers can significantly reduce their R&D time by adopting these patterns to bootstrap their cloud architecture. The language comprises 10 patterns, organized into four categories: Automated Infrastructure Management, Orchestration and Supervision, Monitoring, and Discovery and Communication.

Abstract
Energy communities (EC) and collective self-consumption (CSC) systems can make a significant contribution to reducing dependence on fossil fuels and energy costs. They create mechanisms for the active participation of end-consumers in the energy system by becoming self-producers of renewable electricity and adapting their energy behavior to the needs of the system. CSC also alleviates energy poverty by reducing the energy costs of vulnerable members. The CSC is still in its early stages, and regulation is being developed in several countries along with pilot projects to test different rules and incentives. This chapter discusses the most relevant common definitions of CSC and EC so far, as well as the main challenges in relation to energy sharing rules and the management of EC and CSC. © 2025 Elsevier B.V., All rights reserved.

Abstract
Rendering on conventional computers is capable of generating realistic imagery, but the computational complexity of these light transport algorithms is a limiting factor of image synthesis. Quantum computers have the potential to significantly improve rendering performance through reducing the underlying complexity of the algorithms behind light transport. This article investigates hybrid quantum-classical algorithms for ray tracing, a core component of most rendering techniques. Through a practical implementation of quantum ray tracing in a 3D environment, we show quantum approaches provide a quadratic improvement in query complexity compared to the equivalent classical approach. Based on domain specific knowledge, we then propose algorithms to significantly reduce the computation required for quantum ray tracing through exploiting image space coherence and a principled termination criteria for quantum searching. We show results obtained using a simulator for both Whitted style ray tracing, and for accelerating ray tracing operations when performing classical Monte Carlo integration for area lights and indirect illumination.

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