Search Results (243)

Cross-border Fifth Generation Mobile Communication (5G) roaming requires secure N32 connections between network operators via Security Edge Protection Proxy (SEPP) interfaces, but current Transport Layer Security (TLS) 1.3 implementations face a critical trade-off between connection latency and security guarantees. Standard TLS 1.3 optimization modes either compromise Perfect Forward Secrecy (PFS) or suffer from replay vulnerabilities, while full handshakes impose excessive latency penalties for time-sensitive roaming services. This research introduces Zero Round Trip Time Forward Secrecy (0-RTT FS), a novel protocol extension that achieves zero round-trip performance while maintaining comprehensive security properties, including PFS and replay protection. Our solution addresses the fundamental limitation where existing TLS 1.3 optimizations sacrifice security for performance in international roaming scenarios. Through formal verification using ProVerif and comprehensive performance evaluation, we demonstrate that 0-RTT FS delivers 195.0 $\mathsf{\mu }$s handshake latency (only 17% overhead compared to insecure 0-RTT) while providing full security guarantees that standard modes cannot achieve. Security analysis reveals critical replay vulnerabilities in all existing standard TLS 1.3 optimization modes, which our proposed approach successfully mitigates. The research provides operators with a decision framework for configuring sub-millisecond secure handshakes in next-generation roaming services, enabling both optimal performance and robust security for global 5G connectivity. Full article

Perfect absorbers operating in the terahertz (THz) band are key enablers for next-generation wireless systems. However, conventional metal–dielectric designs suffer from Ohmic losses and limited reconfigurability. Here, we propose an all-dielectric indium antimonide (InSb) cylindrical pillar metasurface that achieves near-unity absorption at $f_0=1.83$ THz with a high quality factor of $Q=72.3$. Critical coupling between coexisting electric and magnetic dipoles enables perfect impedance matching, while InSb’s low damping minimizes energy loss. The resonance is tunable via temperature and magnetic bias at sensitivities of $S_T\approx 2.8\mathrm{GHz}·{\mathrm{K}}^{-1}$, $S_B^{\mathrm{TE}}\approx -132.7\mathrm{GHz}·{\mathrm{T}}^{-1}$, and $S_B^{\mathrm{TM}}\approx -34.7\mathrm{GHz}·{\mathrm{T}}^{-1}$, respectively, without compromising absorption strength. At zero magnetic bias ($B=0$), the metasurface is polarization-independent under normal incidence; under magnetic bias ($B\ne 0$), it maintains near-unity absorbance for both TE and TM, while the resonance frequency becomes polarization-dependent. Additionally, the 90% absorptance bandwidth ($\Delta f_{A\ge 0.9}$) can be modulated from 8.3 GHz to 3.3 GHz with temperature, or broadened from 8.5 GHz to 14.8 GHz under magnetic bias. This allows gapless suppression of up to 14 consecutive 1 GHz-spaced channels. This standards-agnostic bandwidth metric illustrates dynamic spectral filtering for future THz links and beyond-5G/6G research. Owing to its sharp selectivity, dual-mode tunability, and metal-free construction, the proposed absorber offers a compact and reconfigurable platform for advanced THz filtering applications. Full article

Power converters play an important role in incorporating renewable energy sources into power systems. Among different converter designs, Buck and Boost converters are popular, as they use fewer components and deliver cost savings and high efficiency. However, Boost converters are known as non–minimum phase systems, imposing harder constraints for designing a robust converter. Developing an efficient controller for these topologies can be difficult since they exhibit nonlinearity and distortion in high frequency modes. The Lyapunov-based Adaptive Backstepping Control (ABSC) technology is used to regulate suitable outputs for these structures. This approach is an updated version of the technique that uses the stability Lyapunov function to produce increased stability and resistance to fluctuations in real-world circumstances. However, in real-time situations, disturbances with larger ranges such as supply voltage changes, parameter variations, and noise may have a negative impact on the operation of this strategy. To increase the controller’s flexibility under more difficult working settings, the most appropriate first gains must be established. To solve these concerns, the ABSC’s performance is optimized using the Reinforcement Learning (RL) adaptive technique. RL has several advantages, including lower susceptibility to error, more trustworthy findings obtained from data gathering from the environment, perfect model behavior within a certain context, and better frequency matching in real-time applications. Random exploration, on the other hand, can have disastrous effects and produce unexpected results in real-world situations. As a result, we choose the Deep Deterministic Policy Gradient (DDPG) approach, which uses a deterministic action function rather than a stochastic one. Its key advantages include effective handling of continuous action spaces, improved sample efficiency through off-policy learning, and faster convergence via its actor–critic architecture that balances value estimation and policy optimization. Furthermore, this technique uses the Grey Wolf Optimization (GWO) algorithm to improve the initial set of gains, resulting in more reliable outcomes and quicker dynamics. The GWO technique is notable for its disciplined and nature-inspired approach, which leads to faster decision-making and greater accuracy than other optimization methods. This method considers the system as a black box without its exact mathematical modeling, leading to lower complexity and computational burden. The effectiveness of this strategy is tested in both modeling and experimental scenarios utilizing the Hardware-In-Loop (HIL) framework, with considerable results and decreased error sensitivity. Full article

As extensions of circular symmetric vortex beams, elliptical vortex beams with more diverse field forms are worthy of attention. In this paper, we investigate the mode propagation characteristics of an elliptical perfect optical vortex (EPOV) beam in oceanic turbulence. The theoretical model is constructed to analyze the detection probability of orbital angular momentum mode and average capacity at the receiver. The results reveal that the self-focusing property of the EPOV beam is able to improve propagation performance. By changing the elliptical scaling factor and the ratio of ring radius to width, the self-focusing effect is adjustable. The smaller elliptical scaling factor and ring radius to width ratio are beneficial for short-range transmission, while the larger ones are better for long-range transmission. Furthermore, the impacts of oceanic temperature and salinity in wide variation ranges are analyzed by use of the oceanic turbulence optical power spectrum. Higher capacity is obtained when the EPOV beam propagates in low-temperature and low-salinity oceanic channel. The research is referable for the design of underwater communication systems. Full article

With the wide application of battery energy storage systems (BESSs) in DC microgrids, BESSs are facing increasingly severe cyber threats, among which, false data injection attacks (FDIAs) seriously undermine the accuracy of battery state estimation by tampering with sensor measurement data. To address this problem, this paper proposes an improved generative adversarial network (WGAN-GP)-based detection and defence method for FDIAs in battery energy storage systems. Firstly, a more perfect FDIA model is constructed based on the comprehensive consideration of the dual objectives of circumventing the bad data detection (BDD) system of microgrid and triggering the effective deviation of the system operating state quantity; subsequently, the WGAN-GP network architecture introducing the gradient penalty term is designed to achieve the efficient detection of the attack based on the anomalous scores output from the discriminator, and the generator reconstructs the tampered measurement data. Finally, the state prediction after repair is completed based on Gaussian process regression. The experimental results show that the proposed method achieves more than 92.9% detection accuracy in multiple attack modes, and the maximum reconstruction error is only 0.13547 V. The overall performance is significantly better than that of the traditional detection and restoration methods, and it provides an effective technical guarantee for the safe and stable operation of the battery energy storage system. Full article

Against the background of traffic conflicts arising due to the highly concentrated population in high-density cities, this study aims to systematically identify the core transport needs of patients awaiting medical treatment; based on the theory of the Kano model, we construct a measurement system relating to patient transport needs when awaiting medical treatment that encompasses multiple levels. Taking 10 large general hospitals in Guangzhou as samples, this study collected data through questionnaires and auxiliary interviews, using the importance–sensitivity analysis method to accurately measure the degree of patient needs for each influencing factor of the transport environment for medical treatment. The study found that, among the primary needs (core basic needs), the perfection of public transport (which directly affects the convenience of medical care) is the core need with the highest degree of demand. Among the second-level needs (refined categorised demand levels), specifically relating to important attributes (essential needs), priority attention should be given to patient diversion, hospital–city connection, and corridor settings. As concerns the high value-added one-dimensional attributes (desired needs), focus should be placed on controlling health and safety distances and guiding the flow of medical treatment, while for high glamour attributes (glamour needs), primary consideration should be given to crowd distribution, stopping and resting, and direct access to the ground floor. The group difference analysis (grouped by emotional state, transport mode, and group type) showed that the first-level demand sensitivity ranking was highly consistent, and the second-level demand for urban connectivity, convenient transfer, and direct underground access were also common priorities. This study is the first to introduce the Kano model into the analysis of high-density urban healthcare transport systems, providing a clear basis for the grading of demand for the design of the transport environment for patients’ medical care. This is of great practical value for alleviating congestion and improving the resilience of emergency response in mega-cities in relation to medical care. Full article

Secure autonomous secret key distillation (SKD) systems traditionally depend on external common randomness (CR) sources, which often suffer from instability and limited reliability over long-term operation. In this work, we propose a novel SKD architecture that synthesizes CR by combining a keystream of a shared-key keystream generator $KSG\left(K_G\right)$ with locally generated binary Bernoulli noise. This construction emulates the statistical properties of the classical Maurer satellite scenario while enabling deterministic control over key parameters such as bit error rate, entropy, and leakage rate (LR). We derive a closed-form lower bound on the equivocation of the shared-secret key $K_G$ from the viewpoint of an adversary with access to public reconciliation data. This allows us to define an admissible operational region in which the system guarantees long-term secrecy through periodic key refreshes, without relying on advantage distillation. We integrate the Winnow protocol as the information reconciliation mechanism, optimized for short block lengths ($N=8$), and analyze its performance in terms of efficiency, LR, and final key disagreement rate (KDR). The proposed system operates in two modes: ideal secrecy, achieving secret key rates up to 22% under stringent constraints (KDR < 10⁻⁵, LR < 10⁻¹⁰), and perfect secrecy mode, which approximately halves the key rate. Notably, these security guarantees are achieved autonomously, without reliance on advantage distillation or external CR sources. Theoretical findings are further supported by experimental verification demonstrating the practical viability of the proposed system under realistic conditions. This study introduces, for the first time, an autonomous CR-based SKD system with provable security performance independent of communication channels or external randomness, thus enhancing the practical viability of secure key distribution schemes. Full article

Estradiol (E2) plays an important role in cell proliferation and certain brain functions. To reveal its mechanism of action, its detectability is essential. Only a few fluorescent-labeled hormonally active E2s exist in the literature, and their mechanism of action usually remains unclear. It would be of particular interest to develop novel labeled estradiol derivatives with retained biological activity and improved optical properties. Due to their superior optical characteristics, aza-BODIPY dyes are frequently used labeling agents in biomedical applications. E2 was labeled with the aza-BODIPY dye at its phenolic hydroxy function via an alkyl linker and a triazole coupling moiety. The estrogenic activity of the newly synthesized fluorescent conjugate was evaluated via transcriptional luciferase assay. Docking calculations were performed for the classical and alternative binding sites (CBS and ABS) of human estrogen receptor α. The terminal alkyne function was introduced into the tetraphenyl aza-BODIPY core via selective formylation, oxidation, and subsequent amidation with propargyl amine. The conjugation was achieved via Cu(I)-catalyzed azide–alkyne click reaction of the aza-BODIPY-alkyne with the 3-O-(4-azidobut-1-yl) derivative of E2. The labeled estrogen induced a dose-dependent transcriptional activity of human estrogen receptor α with a submicromolar EC₅₀ value. Docking calculations revealed that the steroid part has a perfect overlap with E2 in ABS. In CBS, however, a head-tail binding deviation was observed. A facile, fluorescent labeling methodology has been elaborated for the development of a novel red-emitting E2 conjugate with substantial estrogenic activity. Docking experiments uncovered the binding mode of the conjugate in both ABS and CBS. Full article

Sitagliptin is an orally bioavailable selective DPP4 inhibitor that reduces blood glucose levels without significant increases in hypoglycemia. The aim of this study was to design and validate an innovative, rapid, and highly sensitive LC–MS/MS assay for the precise measurement of sitagliptin concentrations in human plasma. This analytical method, utilizing sitagliptin-d4 as the internal standard, is performed using only 100 μL of plasma and a liquid–liquid extraction procedure based on methyl tert-butyl ether (MTBE). Chromatographic separation is expertly achieved with a Kinetex^® C18 column under isocratic elution, employing a perfect 1:1 blend of 5 mM ammonium acetate (with 0.04% formic acid) and acetonitrile, and maintaining an efficient flow rate of 0.2 mL/min. Detection occurs in positive ionization mode through multiple reaction monitoring, precisely targeting transitions of m/z 408.2 → 193.0 for sitagliptin and 412.2 → 239.1 for the IS. The total runtime of this assay is under 2 min. Comprehensive validation in line with MFDS and FDA criteria demonstrates outstanding linearity (5–1000 ng/mL, r² > 0.998), alongside impressive levels of accuracy, precision, recovery and sample stability. Due to its minimal sample requirement and high-throughput capability, the validated approach is highly appropriate for pharmacokinetic and bioequivalence assessments involving sitagliptin. Full article

The precise control of thermal–kinetic parameters governs epitaxial perfection in functional oxide heterostructures. Herein, using Iridium/MgO(100) as a model system, the traditional “low-speed/high-temperature” paradigm is revolutionized through the combination of ab initio calculations, multiscale simulations, and subsequent deposition experiments. First-principles modeling reveals the mechanisms of Volmer–Weber (VW, island growth mode) nucleation at low coverage and Stranski–Krastanov (SK, layer-plus-island growth) transitions driven by interface metallization, stress release, and energy reduction, which facilitates coherent monolayer formation by lowering the energy barrier by ~34%. Molecular dynamics simulations demonstrate that the strategic co-optimization of substrate temperature (T_sub) and deposition rate (V_dep) induces an abrupt cliff-like drop in mosaic spread. Experimental validations confirm that this T-V synergy achieves unprecedented interfacial coherence, whereby AFM roughness reaches 0.34 nm (RMS) and the XRC-FWHM of 0.13° approaches single-crystal benchmarks. Notably, our novel “accelerated heteroepitaxy” protocol reduces growth time without compromising quality, addressing the efficiency–quality paradox in industrial-scale diamond substrate fabrication. These findings establish universal thermal–kinetic design principles applicable to refractory metal/oxide heterostructures for next-generation quantum sensors and high-power electronic devices. Full article

The defects in zinc oxide crystals are of crucial importance for their usability in many applications and are not yet fully understood. Here, we demonstrate that dioxygen species are present as defects in the grown ZnO, resulting in a bending of the atom layers that lie perpendicular to the c-axis. In the Raman spectra, these defects cause the appearance of bands different from the known bands of perfect ZnO crystals allowed by symmetry. These additional Raman bands, which have been frequently reported for ZnO in the past, can thus be fully explained by the presence of dioxygen species, and the widespread assumption of second-order modes for the assignments of these bands is not necessary. Furthermore, the Raman spectrum belonging to perfect zinc oxide in the ideal wurtzite structure is presented, obtained from small domains in ZnO(0001) crystals exposed to pressures up to 2 GPa. The dependence of the O-O stretching modes on the applied pressure proves the presence of dioxygen species in ZnO, which is also confirmed by phonon calculations of structure models with embedded dioxygen species. The surface quality of the ZnO crystals studied is also reflected in the Raman spectra and is included in the analysis. Full article

Multimodal transport refers to the integrated transportation in a logistics system in the form of multiple transportation modes, such as highway, railway, waterway, etc. In recent years, the deep integration of electric trucks and route optimization has significantly improved the cost-effectiveness and operational efficiency of multimodal transportation. It has provided strong support for the sustainable development of the logistics system. Based on whether to consider low-carbon requirements, uncertainty, and special cargo transportation, the literature is divided into five areas: traditional multimodal transport path optimization, multimodal transport path optimization considering low-carbon requirements, multimodal transport path optimization considering uncertainty, multimodal transport path optimization considering low-carbon requirements and uncertainty, and multimodal transport path optimization considering special transport needs. In this paper, we searched the literature on multimodal path optimization after 2016 in WOS (Web of Science) and CNKI (China National Knowledge Infrastructure), and found that the number of publications in 2024 is three times that in 2016. We collected 130 relevant studies to summarize the current state of research. Finally, with the development of multimodal transport to collaborative transport and the improvement of the application of in-depth learning in different fields, the research mainly focuses on two future research directions: collaborative transport and the use of in-depth learning to solve uncertain problems, and combining it with the problem of multimodal transport route optimization to explore more efficient and perfect transport solutions. Full article

Vehicles exhibit complex failure modes and mechanisms because of their extreme service environments and severe external loads. The increasing level of integration in these vehicles is also driving more stringent reliability requirements, but conventional methods for reliability analysis require significant calculations, necessitating the use of surrogate models. At present, in the field of the reliability analysis of vehicle dust extraction impellers, although there are various research methods, the research on using surrogate models for relevant analysis is still not perfect. In particular, there are few studies specifically focused on dust extraction impellers. This study established a three-dimensional finite element parametric model of one such fan to simulate the impeller blade stress output for 500 parameter sets. The feedback neural network, backpropagation neural network, and quadratic polynomial response surface were subsequently used as surrogate models to learn the relationship between the parameters and output responses in these data. Comparisons of the results indicated that the feedback neural network exhibited the highest accuracy when predicting the stress responses of the dust extraction fan impeller to changes in parameter values. Through a comparative analysis of multiple surrogate models, this study determined the advantages of the feedback neural network in predicting the impeller stress response. It provides a more efficient and accurate method for reliability analysis in this field and helps to promote the development of reliability research on vehicle filtration systems. Full article

This research investigates the structural behavior of high-strength concrete beams reinforced with carbon fiber-reinforced polymer (CFRP) bars and varying percentages of recycled concrete aggregate (RCA). The study examined 15 reinforced concrete beams (200 × 250 × 2000 mm) constructed with different RCA proportions (0%, 25%, 50%, 75%, and 100%) and tested at three shear span-to-depth ratios ($a/d$ = 1.5, 2.5, and 3.5), addressing a critical knowledge gap in sustainable structural engineering. Specimens exhibited compressive strengths of 55–67 MPa and reached ultimate load capacities of up to 198.4 kN. Notably, beams with 75% RCA achieved 35.7% higher capacity than control specimens at $a/d$ = 1.5, challenging conventional expectations about RCA performance. Failure modes transitioned from shear-dominated at $a/d$ = 1.5 to flexure-dominated at $a/d$= 3.5, with optimal ductility indices (up to 2.75) observed at $a/d$ = 2.5. Statistical analysis revealed significant correlations between $a/d$ ratio and performance metrics, with a perfect parabolic relationship for the ductility index (R² = 1.0, $p<0.001$). Comparison with ACI 440.1R15 predictions showed generally conservative estimates (mean experimental-to-predicted ratio = 1.02, COV = 16.9%). The findings demonstrate that high-strength concrete can successfully incorporate substantial RCA quantities (up to 75%) without compromising performance when using CFRP reinforcement, potentially reducing virgin material consumption by approximately 33% for sustainable construction applications. Full article

The evaluation of the acoustic quality of sound-emitting appliances is primarily conducted by measuring psychoacoustic parameters or by means of a jury study through subjective evaluation by respondents. This article aims to validate the developed model for evaluating the acoustic quality of washing machines. Three top-loading washing machines were used in three operating modes for validation. The measurement of the psychoacoustic parameters of these washing machines was carried out. Subsequently, in the evaluation process, a developed quality index was used, based on which a ranking of washing machines in terms of sound quality was determined. Subsequently, the results were validated using a questionnaire. By comparing the results of the evaluation of the questionnaire method and the application of the developed sound quality evaluation model based on the sound quality index, an almost perfect agreement is evident in determining the ranking of washing machines using both methods, as confirmed by statistical analysis. Developed a model for the evaluation of psychoacoustic quality and its application to the measured psychoacoustic parameters that can substitute the time-consuming methods of assessing sound quality through questionnaire surveys. The application of the developed method significantly reduces the evaluation time. Full article