Search Results (3,154)

AI-generated news is increasingly presented through combinations of text and visual content, making complete user-facing stimuli an important topic for credibility evaluation. This exploratory empirical evaluation examined perceived message credibility ratings across six implemented AI-generated news stimuli, organized by two selected stimulus domains—design industry and quantum computing—and three implemented presentation configurations: text only, an image with researcher-designated higher correspondence, and an image with researcher-designated lower correspondence. A total of 211 students from design-related disciplines evaluated all six stimuli in a fixed order, yielding 1266 ratings. Credibility ratings differed across the stimuli corresponding to the three implemented presentation configurations, F(1.95, 406.54) = 9.16, p < 0.001, partial η² = 0.042, and the pattern of ratings across the implemented configurations differed between the selected stimulus domains, F(1.94, 404.48) = 14.94, p < 0.001, partial η² = 0.067. Within the design-industry stimuli, the text-only stimulus was rated higher than the stimulus with a researcher-designated higher-correspondence image. Within the quantum-computing stimuli, both image-present stimuli were rated higher than the text-only stimulus, and the researcher-designated lower-correspondence image stimulus received the highest rating. The six implemented stimuli showed different credibility-rating patterns, underscoring the importance of considering visual attributes together with the content and presentation context in which they occur. Because story identity, presentation configuration, and serial position were not independently crossed, the findings describe the six implemented stimuli rather than isolated causal effects of visual presentation. Full article

Privacy is a major concern in the Internet Healthcare of Things (IoHT), where threat actors may intrude systems to access personally identifiable data. Federated Learning (FL) is a well suited Machine Learning (ML) approach to preserve confidentiality, availability, and integrity in such settings during data analysis. In this work, we introduce a Network of Quantum ML (N-QML) approach for IoHT intrusion detection, integrating quantum PCA (QPCA) with Quantum FL (QPCA+QFL), tested on a subset of the data set WUSTL-EHMS-2020 using classical and quantum computing experiments across three seeds, compared against conventional ML (CML) on three feature dimensions. Among CML techniques, the integration of PCA and ANN (PCA+ANN) attained the best mean accuracy, 76.6%, using two features. Among QML techniques, QPCA+QNN achieved the best centralized accuracy, 74.4%, when two features are used, while PCA+SVM outperformed QPCA+QSVM using ten features (70.1% versus 66.9%). As a result of the study, during federation of the quantum model, accuracy was realized to be reduced steadily from 62.9% to 54.7% as dimensionality changed and highest variance attainment occurred at the smallest dimension; this is a pattern that was not previously documented under matched, multi-seed validation. We attribute this to FedAvg interacting with the loss landscape of quantum-derived features on small client partitions, contributing this finding and the framework as groundwork for quantum-aware federated aggregation. Full article

Liquid organic hydrogen carriers (LOHC) have emerged as a promising technology for the safe, efficient, and reversible storage and transportation of hydrogen, offering a viable pathway toward the development of a hydrogen-based economy. Despite the rapid expansion of this research field, a comprehensive understanding of its scientific evolution, intellectual structure, and emerging research directions remains limited. This study presents a comprehensive bibliometric and thematic analysis of LOHC research based on 1140 publications indexed in the Scopus database between 2007 and 2025. Bibliometric indicators, scientific mapping, Bradford’s and Lotka’s laws, thematic evolution, and strategic thematic mapping were performed using VOSviewer and Bibliometrix/Biblioshiny. The results reveal an exponential increase in scientific production after 2016, reflecting the growing global interest in LOHC technologies. Bradford’s law identified a highly concentrated publication landscape dominated by a small core of specialized journals, whereas Lotka’s law demonstrated that scientific production is driven by a limited group of highly productive authors. Keyword network and thematic evolution analyses show a clear transition from fundamental hydrogen storage concepts toward advanced catalyst development, molecular design, quantum chemical calculations, machine learning, techno-economic assessment, and hydrogen transport applications. Strategic thematic mapping further indicates that computational methodologies and sustainability-oriented analyses are becoming emerging drivers of future research. Overall, this study provides a comprehensive overview of the conceptual, intellectual, and thematic evolution of LOHC research while identifying the principal scientific trends and technological opportunities expected to shape the next generation of hydrogen storage systems. Full article

Niels Bohr asserted both that (i) the properties of quantum systems are specifiable, in general, only in relation to mutually exclusive experimental arrangements which may be freely chosen by experimenters, and that (ii) observed physical behavior is objective. In a move that reduces the apparent tension between those two assertions, Bohr put forward an analogy between quantum complementarity (in effect, the dependence of property values on measurement apparatus configuration in quantum mechanics) and the principle of relativity (in effect, the dependence of property values on the inertial reference frame in special relativity). Here, Bohr’s analogy is considered in a theoretical context. The elements of quantum mechanics and special relativity involved are set side by side, the analogous elements are identified with their roles in the analogy spelled out, and a number of dissimilarities that impact the force of the analogy are indicated—for example, quantum value determination, in general, requires an uncontrollable interaction during measurement, whereas non-quantum relativistic value determination does not. These dissimilarities point to weaknesses in the analogy, which he did not highly develop, and suggest that any stronger such analogy involving the two theories must take these differences more fully into account. Full article

The relentless pursuit of higher information density and processing speed has driven photonic chips toward miniaturization, high performance, and multifunctional integration. Metasurfaces, composed of subwavelength artificial meta-atoms, have emerged as a revolutionary platform for manipulating light fields at the nanoscale, offering unprecedented control over amplitude, phase and polarization, as well as enabling frequency conversion through nonlinear processes. When seamlessly integrated with on-chip optical waveguides, metasurfaces provide a compelling solution for bridging guided waves and free-space waves, enabling compact, high-performance photonic devices with versatile light-manipulation capabilities. This review systematically surveys recent advances in on-chip metasurfaces for multifunctional light field manipulation, with a focus on guided-wave radiation control. We first elucidate the fundamental phase modulation mechanisms that collectively constitute a versatile toolbox for tailoring light fields at subwavelength scales. We then examine the three core application scenarios that define the operational framework of metasurface-integrated photonic systems: free-space-to-chip coupling, in-plane guided-wave manipulation, and guided-wave-to-free-space radiation. For each scenario, we highlight representative device architectures and their performance characteristics, tracing the evolution from single-mechanism modulation to multidimensional multiplexing and dynamic reconfigurability. We conclude by discussing remaining challenges including efficiency, dynamic tunability, and scalable fabrication, and outline future directions such as intelligent inverse design, on-chip quantum metasurfaces, and optical computing. Full article

Finding the global minimum of a function with many local extrema is well known to be a challenging computational task. We propose a hybrid quantum–classical algorithm for this optimisation problem, based on a combination of Grover quantum search and the classical Newton–Raphson method. The approach is tailored to situations with a large number of false minima. The main idea is to use quantum search to efficiently locate the vicinity of the true optimum, after which a classical algorithm can solve the problem in only a few iterations. We specifically address the nontrivial question of choosing the discretisation of the function domain, which is critical for quantum approaches to optimisation of continuous functions. While we do not expect that this method will always be superior, we identify a paradigmatic case of a function for which we demonstrate that, remarkably, our hybrid method quadratically outperforms a purely classical approach (measuring performance by the number of function/oracle calls). We evaluate key performance metrics of the algorithm in numerical experiments. We furthermore discuss its possible extensions as well as the potential relevance of hybrid approaches in the context of quantum cognition. Full article

Future sixth-generation (6G) Internet of Things (IoT) environments require scalable authentication for large populations of constrained devices while remaining resilient to quantum-capable adversaries. Quantum key distribution (QKD) can provide high-assurance key material between suitable infrastructure nodes, but direct QKD termination at every low-power endpoint is impractical and the secret-key supply is finite. This paper presents AQ-TESLA, an edge-assisted hybrid authentication architecture that combines infrastructure-facing QKD, ML-KEM fallback, quantum-derived TESLA epoch seeds, delayed key disclosure, authenticated edge synchronization, CoAP transport, and a runtime security controller. The controller jointly evaluates packet loss, attack evidence, congestion, device trust, message criticality, and QKD key-pool status to continue the current TESLA chain, shorten the disclosure interval, or trigger hybrid rekeying. A reproducible systems simulation generated 180,000 events across routine, dense-urban, industrial, emergency, and adversarial scenarios and compared AQ-TESLA with DTLS-CoAP, PQC-CoAP, classical TESLA-CoAP, and Static QKD-TESLA. AQ-TESLA achieved a mean authentication latency of 12.91 ms, P95 latency of 21.24 ms, attack rejection of 97.30%, and authentication success of 98.93%, while consuming 76.9% less QKD key material than static quantum rekeying in the reference workload. Ablation, threshold-sensitivity, bootstrap, and scalability analyses show that pool awareness and adaptive escalation reduce depletion and unnecessary quantum operations. These findings are systems-model results; they are not a physical QKD experiment, a 6G field trial, or a hardware security certification. Full article

Vehicular networks require privacy-preserving and secure authentication mechanisms to protect safety-critical communications against evolving cyber threats. Conventional authentication schemes relying on elliptic-curve cryptography (ECC) and RSA are vulnerable to quantum attacks, making them unsuitable for next-generation intelligent transportation systems. This paper proposes a unified post-quantum pseudonymous authentication and key establishment (UPQ-PAKE) scheme for secure vehicular networks. The proposed framework integrates dynamic pseudonymous identity construction, post-quantum digital signatures, and dual ephemeral key encapsulation into a single transcript-bound authenticated key exchange protocol. ML-DSA is employed for mutual authentication, while ML-KEM enables quantum-resistant session key establishment. Dynamic session-specific pseudonyms provide identity privacy and unlinkability. Furthermore, transcript binding, nonce freshness verification, and contributory dual-ephemeral session entropy strengthen the protocol against replay attacks, provide forward secrecy, and resist man-in-the-middle attacks under the quantum polynomial-time adversarial model. Formal security analysis demonstrates that the proposed scheme achieves authenticated key exchange security based on the IND-CCA security of ML-KEM and the EUF-CMA security of ML-DSA. Performance evaluation demonstrates that the proposed authentication technique maintains practical computational and communication overhead and provides post-quantum mutual authentication, dual-directional key establishment, and dynamic unlinkability, making it suitable for large-scale, real-time IoV deployments. Full article

Wireless sensor networks (WSNs) are pervasively employed in critical domains such as smart healthcare, industrial automation, and environmental surveillance, where secure access control is essential. User authentication protocols are vital for thwarting unauthorized intrusions, yet the vast majority of existing schemes rely on conventional public-key cryptography (such as ECC, RSA), which is provably insecure in the post-quantum era due to Shor’s algorithm. This motivates the design of post-quantum authentication that is also lightweight for resource-limited sensors. To address this challenge, we propose an efficient authentication and key agreement protocol based on Number Theory Research Unit (NTRU), a lattice-based cryptosystem offering proven resistance to quantum attacks. We have proven the correctness and security of our scheme through BAN logic and random oracle model and demonstrated through informal analysis that our scheme can resist various attack methods and possesses high security features. Moreover, we thoroughly evaluate our protocol against the most recent state-of-the-art schemes. The results indicate that our scheme has the lowest computational cost, and its communication cost is superior to that of most other schemes. Overall, our proposed protocol provides a robust, efficient, and future-proof authentication solution for WSNs, well-suited for deploying WSNs environments. Full article

The Berry phase plays a central role in modern electronics and acts as a foundation for a wide range of phenomena, from the anomalous Hall effect to topological insulators and valleytronics. However, in conventional analytical treatments, its geometric origin frequently stays abstract and unreachable. A thorough paradigm for computational visualization that clarifies the emergence and implications of the Berry phase in quantum electronic systems is presented in this paper. The simulation begins with a spin-½ model in a rotating magnetic field and uses real-time spin precession and field rotation tracking to demonstrate geometric phase accumulation on the Bloch sphere. Key ideas for comprehending tunable topological devices are revealed by the dynamic redistribution of Berry curvature and associated Berry-flux evolution when the framework is further extended to time-dependent Hamiltonians that reflect oscillating fields or shifting mass terms. Users can see local spin textures and phase progression within the Brillouin zone by mapping each k-point in momentum-space modules to a small Bloch sphere. Topology is linked to quantifiable device phenomena by a hybrid real- and momentum-space animation that links geometric phase evolution with observable transport behavior such as quantized Hall responses and Landau orbits. Together, these interconnected modules provide an interactive framework for exploring Berry-phase-related geometric and transport phenomena across complementary quantum-mechanical representations. Finally, these visualizations form an interactive and pedagogically rich toolset that unites geometric quantum theory with practical implications for next-generation electronic and spintronic devices. Full article

Offshore wind farms are representative unmanned energy systems whose operation relies heavily on remote information exchange between offshore substations and onshore centralized control centers. However, the cross-sea communication link is vulnerable to cyberattacks, including impersonation and message tampering, and these threats persist in the quantum computing era, potentially compromising operational decision-making and control. To address this problem, this paper proposes a privacy-preserving key agreement method based on the Ring Learning With Errors (RLWE) problem. First, identity privacy protection is integrated with post-quantum cryptography. An identity commitment function conceals the true identities of the communicating entities, while a pre-shared authentication factor and fresh random parameters enable mutual authentication and session key establishment. This design prevents identity disclosure and secures information exchange in offshore wind farms against quantum-capable adversaries. Second, confidentiality and unforgeability are formally established under the decisional and search RLWE assumptions. Finally, experiments validate the effectiveness of the proposed method. Compared with existing schemes, it reduces communication overhead by up to 43.75%, making it particularly suitable for resource-constrained offshore wind farm environments. Full article

The present work shows that E-hook fragments possess functional structural differences governed by electrostatic interactions and sequence composition. The acidic C-terminal tails of tubulin, known as E-hooks, play a central role in regulating interactions between microtubules and motor proteins, microtubule-associated proteins, and enzymatic modifiers. Despite their functional importance, the intrinsic structural properties of these peptide segments remain poorly characterized due to their intrinsically disordered nature. In this work, we present quantum-mechanically optimized structures of hexamer peptides derived from β-tubulin E-hook sequences. Density functional theory calculations were used to optimize peptide geometries using progressively larger basis sets. From the optimized geometries, we calculated theoretical Raman spectra, Ramachandran backbone dihedral distributions, and measured radii of gyration to resolve composition-dependent structural tendencies. The combined Raman and conformational analyses provide a systematic computational approach for comparing simulated and experimental Raman spectra of tubulin E-hooks and other intrinsically disordered proteins and offer insight into how E-hooks contribute to the recognition mechanisms underlying the tubulin code. Full article

The transition to post-quantum cryptography (PQC) presents significant challenges for modern computing environments due to increased computational overhead, communication latency, and implementation complexity. Existing evaluation methods typically focus on isolated cryptographic performance metrics and do not provide a unified framework for assessing the overall resilience of PQC deployments across heterogeneous systems. This paper introduces the Quantum Encryption Resilience Score (QERS), a novel system-level evaluation framework designed to quantify the resilience of post-quantum cryptographic implementations by integrating computational, network, and operational performance metrics into a single composite score. QERS provides a standardized methodology for comparing PQC algorithms across diverse deployment scenarios. In this study, the framework is experimentally evaluated using a heterogeneous ESP32-based embedded and IoT testbed with gateway-assisted post-quantum cryptographic processing. The proposed framework is validated through experimental implementations of the NIST-standardized ML-KEM key encapsulation mechanism and the ML-DSA digital signature algorithm under multiple communication protocols and heterogeneous hardware configurations. Experimental results demonstrate that QERS effectively distinguishes the trade-offs between security, computational efficiency, resource utilization, and communication performance, providing a practical decision-support framework for selecting appropriate PQC implementations. The proposed framework contributes a reproducible and extensible methodology for the system-level evaluation of post-quantum cryptography and establishes a foundation for future research into standardized resilience and trust assessment of quantum-resistant systems. Full article

Operational technology (OT) systems, such as power-grid controls and factory automation, are replacing cryptographic mechanisms vulnerable to future quantum computers with post-quantum (PQ) cryptography. However, older backups, standby systems, trust stores, and failover paths may retain weaker cryptography after the active system is upgraded. Legitimate recovery can reactivate these weaker states and allow them to regain privileged authority, reducing achieved protection. Existing work addresses PQ deployment, crypto-agility, secure recovery, rollback protection, attestation, and continuous authorization, but these mechanisms do not by themselves determine whether legitimate recovery can restore weaker cryptographic states that may regain privileged authority. We introduce PQReach-OT, which analyzes recovery paths before failure, keeps the required cryptographic protection level separate from the recoverable state, and requires fresh evidence before privileged authority is restored. We conducted a controlled mechanism-validation study using 570 deterministic recovery variants across 19 specified recovery scenario families. Seven configured mechanisms were exercised on the same variants, yielding 3990 primary records. The purpose of this matrix is to demonstrate and distinguish the registered recovery-security properties under controlled same-input cases, but it does not estimate the comparative effectiveness or weakness prevalence in operational OT deployments. Within these controlled cases, both PQReach-OT and the strong reactive experimental control satisfied post-transition grant safety. PQReach-OT additionally exercised the recovery-closure functions defined by the model: it identified all 510 current-compliant but recovery-unsafe variants before failure, selected a compliant alternative in all 390 applicable cases, rejected all 30 historical-floor replays, and detected all 30 exposures reachable only through multi-step recovery. Inventory completeness is an explicit assurance boundary: in the registered additive inventory-completion mutations, adding a compliant recovery state preserved Recovery-Closed Migration Coverage (RCMC) at 1.0, whereas adding a previously unrepresented below-floor state capable of regaining protected authority reduced RCMC from 1.0 to 0.0. Thus, RCMC is explicitly conditional on the represented recovery reachability: additive inventory completion can preserve the existing closure assessment or reveal an additional violation, but it cannot strengthen that assessment solely by enlarging the represented recovery space. These outcomes demonstrate the behavior and separability of the proposed recovery-closure mechanisms within the defined recovery semantics; evaluation in operational OT environments addresses the complementary question of external generalizability. Full article