Centre Tecnologic De Telecomunicacions De Catalunya

The growing complexity of Cyber-Physical Systems (CPS) in industrial and manufacturing environments calls for more sophisticated methods to represent heterogeneous assets and processes. In response, hierarchical Digital Twins (DTs)–virtual representations of physical, taxonomy-based processes–offer transparent, layered modeling of diverse data sources. This layered structure fuels renewed interest in intelligent engines capable of extracting meaningful insights and mapping them within the stratified DT ecosystem. While current Intelligent Digital Twin (I-DT) engines based on Deep Learning are computationally demanding, lightweight alternatives like Reservoir Computing (RC) offer efficient solutions with low training costs and fast inference for modeling causal dynamics. This inherent trade-off between performance and practicality underscores the limitations of evaluating I-DTs on accuracy alone. To address this gap, this work introduces a novel metric, Fidelity , designed to provide a comprehensive evaluation. Unlike traditional approaches, Fidelity also accounts for maintainability and deployability, especially in contexts involving time-varying and hierarchical data dynamics. Extensive experiments on two multimodal datasets demonstrate the competitiveness of our RC-based engine and highlight the value of introducing Fidelity for effectively profiling I-DTs. Specifically, our RC-based engine, identified as optimal through a higher Fidelity score, consumes an order of magnitude less energy and achieves up to 39 % higher accuracy (about 10 % increase on average) compared to both canonical and other RC-based alternatives.

The exponential advancement of quantum computing poses an unprecedented threat to blockchain technology and emerging Sixth Generation (6G) networks, necessitating an urgent transition to post-quantum cryptographic solutions. This comprehensive review proposed post-quantum Cryptography (PQC) integration within Blockchain Enabled 6G (BE6G) architectures, highlighting vulnerabilities by Shor’s and Grover’s algorithms according to existing cryptographic standards, including Rivest-Shamir-Adleman (RSA), Elliptic Curve Digital Signature Algorithm (ECDSA), and Elliptic-Curve Cryptography (ECC). The paper addresses quantum computing fundamentals and blockchain security implications, exploring quantum-resistant cryptographic schemes including lattice-based, hash-based, code-based, and multivariate approaches. Through systematic examination of post-quantum threats, this review shows vulnerabilities affecting nearly 25% of existing cryptocurrency assets, presenting how quantum computers can break public-key systems in polynomial time. The study proposes solutions for implementing quantum-resistant blockchain architectures throughout 6G components, including Radio Access Network (RAN), edge computing, and core transport networks, while meeting ultra-low latency and scalability requirements. Key findings elaborate that hybrid cryptographic approaches combining classical and quantum-resistant algorithms provide promising directions. Lattice-based algorithms, particularly CRYSTALS-kyber and CRYSTALS-dilithium, are identified as primary deployment candidates. The review concludes that successful Quantum-Resistant Security deployment for BE6G Networks requires unprecedented coordination among telecommunication operators, blockchain developers, equipment manufacturers, and regulatory bodies. The ”harvest now, decrypt later” threat model creates sudden implementation, valuable for long-term digital infrastructure security.

Abstract Climate change profoundly affects well‐being in complex and interconnected ways. However, the relationship between climate change and well‐being has been explored in only a handful of settings, most of which are industrialized. Here, we investigate the association between perceived climate change impacts, their severity and subjective well‐being (measured as life satisfaction) using cross‐culturally comparable first‐hand reports from 2488 participants across 14 nature‐dependent communities. We find a negative association between site‐aggregated life satisfaction and different metrics of climate change: perceptions of local impacts, reported severity and instrumental measurements. Within sites, individual‐level associations between perceived severity of climate change impacts and life satisfaction are weak or absent. Further analysis suggests that site‐level characteristics play a crucial role in shaping these patterns. This could indicate that it is the overall vulnerability and exposure of a community to climate change impacts, rather than individual experiences that matters most. Our findings offer a nuanced understanding of how climate change impacts relate to well‐being, emphasizing the multidimensional character of climate change impacts and underscoring the importance of local context in shaping these relationships. Read the free Plain Language Summary for this article on the Journal blog.

The aim of this contribution is to define active customer relationships within the renewable-based energy communities in the EU, and, namely, in Catalonia [...]