Search Results (1,156)

As a next-generation automotive display technology, Augmented Reality Head-Up Display (AR-HUD) has demonstrated immense potential in reshaping driving safety and enhancing the human–computer interaction experience. To address the challenges of barrel distortion and perspective distortion inherent in HUD systems, we propose a joint-learning-based dual-path pre-correction method. This approach employs a shared encoder to extract image features, which are then decoupled into two parallel branches: a classification branch and a distortion flow prediction branch. Building upon this architecture, a model-fitting method is introduced to estimate the distortion model parameters in the parameter space using the predicted distortion types and flows, thereby reconstructing a refined distortion flow. Finally, image rectification is achieved through a resampling method. On the ARHDD dataset, the proposed method achieves a PSNR of 24.617 dB (barrel) and 25.062 dB (perspective), an SSIM of 0.845 and 0.873, and an NRMSE of 0.163 and 0.157, respectively. On the Places 365 dataset, it achieves a PSNR of 23.914 dB (barrel) and 21.870 dB (perspective), an SSIM of 0.812 and 0.748, and an NRMSE of 0.174 and 0.211, respectively. Both quantitative and qualitative comparative experiments against other state-of-the-art methods demonstrate that the proposed approach achieves superior correction performance for both types of distortion. Finally, the simulation verification of the HUD system proved that this correction method demonstrated excellent potential, but further verification is still needed in a real or semi-real environment. Full article

Rechargeable zinc-based batteries (ZBBs) have attracted considerable attention for use in large-scale energy storage systems due to their inherent high safety, low cost, and environmental friendliness. However, the practical applicability of ZBBs is limited by challenges related to the anode—such as uncontrollable zinc dendritic growth, the hydrogen evolution reaction (HER), and corrosion—which lead to significant polarization, capacity degradation, and unsatisfactory Coulombic efficiency of the ZBBs. Polyacrylamide (PAM)-based hydrogels have emerged as promising electrolyte materials to address these challenges due to their superior mechanical properties, flexibility, high ionic conductivity, and structural designability. Considering the rapid increase in research attention regarding this topic, we comprehensively summarize recent progress in PAM-based hydrogels as electrolytes for ZBBs in this study. First, we discuss the key challenges associated with Zn anodes in ZBBs, together with corresponding optimization strategies. Next, we detail the fundamental structure, properties, and synthesis of PAM-based hydrogels. Then, the relationships among synthetic methods, nano/microstructures, and electrochemical properties are systematically reviewed and discussed. Finally, prospects for the rational design and application of PAM-based hydrogels in ZBBs are summarized. Full article

Background/Objectives: The accuracy and reliability of automated clinical analyzers are fundamental to patient safety and effective medical decision-making. Traditional quality control (QC) methods, which rely on periodic manual calibration and reactive maintenance, are inherently limited by high latency and labor costs; furthermore, they fail to provide continuous, real-time monitoring. This paper introduces a novel hybrid ensemble learning framework for the automated quality inspection of medical devices through the analysis of time-series reaction curves. Methods: Our system integrates three heterogeneous anomaly detection paradigms: an Enhanced Dynamic Time Warping (DTW) detector for robust non-linear pattern matching, a Shape Template Matching (STM) detector that mimics expert clinical logic by analyzing morphological features in a normalized shape space, and a specialized Time-series Variational Autoencoder (TimeVAE) for deep representation learning. The outputs of these detectors are fused using a weighted ensemble strategy, which is specifically designed to prioritize the minimization of false negatives—a critical requirement in medical diagnostics. Results: We evaluate our framework on a comprehensive, multi-center real-world dataset comprising seven distinct biochemical assays. Experimental results demonstrate that our proposed method achieves superior performance, attaining a $0\%$ false negative rate on CRE and DBIL assays and outperforming all baseline methods on the other five datasets. An ablation study confirms the model’s robustness even with limited training data, and a comparative analysis against eight state-of-the-art baseline methods further validates the effectiveness of our domain-optimized ensemble approach. Conclusions: The system provides a robust, interpretable, and highly automated solution for transitioning from reactive maintenance to proactive, real-time quality assurance in clinical laboratories. Full article

This paper presents a comprehensive numerical investigation into the transient thermo-structural response of axial bellows during start-up and shutdown cycles in long-distance heating pipelines. Using ANSYS-based transient thermal–structural coupling finite element analysis under the pure linear elasticity and constant internal pressure, the spatio-temporal evolution mechanisms of temperature fields, axial deformation, and equivalent stress are systematically analyzed. The results demonstrate the highly synchronized evolution between temperature and deformation fields, with maximum axial deformation and equivalent stress consistently concentrated at the convolution root and transition arcs. Under steady-state high-temperature conditions (130 °C), the maximum equivalent stress reaches 332.78 MPa. However, after complete cooling and unloading, minimal residual deformation (≤0.001 mm) and residual stress (8.86 MPa) are observed, satisfying the pressure vessel shakedown criteria and confirming the inherent self-limiting nature of thermal secondary stresses. A specific decoupling phenomenon is revealed during the high-temperature steady-state holding period, where the deformation stabilizes while the stress undergoes secondary redistribution. The comparative analysis of different temperature change rates indicates that the fast start-up/shutdown (0.55 °C/s) induces severe transient temperature gradients, causing a nearly 50% increase in the maximum equivalent stress compared to the slow start-up/shutdown (0.275 °C/s). This study provides theoretical foundations for the service safety assessment of axial bellows and recommends gradual heating/cooling operation strategies (≤0.3 °C/s) to mitigate structural thermal shock risks. Full article

With the rapid development of the hydrogen economy, Type IV composite pressure vessels have emerged as the core components of on-board hydrogen storage systems. However, accurate fatigue life prediction remains a critical bottleneck limiting their design optimization and safe operation. Existing methods often exhibit prediction errors exceeding ±50% due to the inherent scatter, anisotropy, and complex service environments of composites. This study proposes an improved simulation method for fatigue life prediction of Type IV cylinders. Systematic tension–tension fatigue tests were conducted on carbon fiber-reinforced polymer (CFRP) laminates at four ply angles (0°, ±15°, ±30°, ±45°) and PA6 liner at three temperatures (−30 °C, 25 °C, 82 °C) to establish comprehensive S-N curve databases. The results reveal that ply angle is the predominant factor governing CFRP fatigue performance, while temperature significantly influences PA6 behavior, and failure mode transitions from fiber fracture to matrix-dominated damage as ply angle increases. A fatigue analysis model was developed in nCode, incorporating the ply fatigue Algorithm to characterize the anisotropic fatigue behavior of CFRP overwraps. Full-scale validation on Type IV cylinders under cyclic pressure (2–87.5 MPa) confirmed the method’s effectiveness, achieving prediction errors of 11.5% and 35.3% for the two failed specimens, with failure locations well predicted. This study provides a rapid and reliable engineering calculation method and data support for the anti-fatigue design, safety assessment, and life management of Type IV cylinders. Full article

Network latency remains a fundamental bottleneck in vehicle teleoperation, inducing instability and performance degradation in conventional control methods, while predictive techniques like the Smith Predictor offer a theoretical solution, their efficacy is often compromised by unmodelled dynamics and real-world disturbances. This paper presents the first experimental validation of the Successive Reference-Pose Tracking (SRPT) architecture. By streaming future reference poses rather than direct steering commands, SRPT leverages an onboard Nonlinear Model Predictive Controller to compute optimal vehicle actions while inherently accounting for dynamic constraints and network delays. Real-world human-in-the-loop experiments were conducted with four drivers on a test track featuring cornering, double lane-change, and slalom manoeuvres. Quantitative comparisons at 10 km/h across four modes—manual driving, direct teleoperation, a Smith Predictor, and SRPT—demonstrate that SRPT significantly outperforms other teleoperation methods, reducing cross-track error by up to 66% and yielding smoother, more stable control inputs. Furthermore, SRPT uniquely maintained stability during a proof-of-concept trial at 13 km/h, where it proactively moderated vehicle speed to respect actuator limits—a critical safety behavior absent in other modes. This work provides the first tangible evidence that SRPT is a robust and superior framework for delay-resilient vehicle teleoperation in real-world conditions. Full article

As core structural components for deep-sea oil and gas exploitation, deep-sea risers are continuously subjected to wind, wave, and current loads, which readily induce vortex-induced vibration (VIV) and further trigger structural fatigue damage. Furthermore, the progressive exploitation of deepwater and ultra-deepwater oil and gas resources has exacerbated the complexity and risk of riser VIV, rendering it a critical engineering problem that urgently requires effective solutions. This paper presents a comprehensive review of numerical studies on deep-sea riser VIV, systematically elaborating the fundamental principles, research advances, and application scenarios of three mainstream numerical approaches: semi-empirical models, computational fluid dynamics (CFD) models, and computational structural dynamics (CSD) models. The respective accuracy advantages and inherent limitations of each numerical method are thoroughly analyzed. Additionally, this review focuses on key research hotspots and challenging issues, including VIV responses of flexible risers, dynamic fluid–structure boundary coupling, internal–external flow coupling effects, wake interference of multi-riser systems, efficient VIV prediction, and vibration suppression optimization. The current technical bottlenecks in existing research are clarified. This study aims to provide a systematic theoretical framework and methodological reference for subsequent numerical investigations and engineering applications of riser VIV, and offer technical support for the optimal structural design and safety risk prevention of deep-sea riser systems. Full article

Accurate characterization of mining-induced surface subsidence is essential for safety assessment in mining areas; however, single monitoring techniques have inherent limitations. Spaceborne interferometric synthetic aperture radar (InSAR) provides large-area coverage but suffers from low signal-to-noise ratio in the subsidence center, whereas terrestrial laser scanning offers high accuracy but limited spatial coverage. To achieve physically consistent quantitative fusion, a multi-source subsidence fusion framework based on variational data assimilation is proposed. By constructing an objective function that incorporates a background prior, D-InSAR-derived boundary constraints, TLS observations, spatial smoothness constraints, and gradient penalty terms, multi-source data are integrated into a unified optimization framework. The results show that, compared with RTK observations, the fused subsidence field achieves an RMSE of 0.12 m and an RRMSE of 2.4% approximately. Parameter sensitivity analysis indicates that the smoothing strength has the greatest influence on fusion accuracy, whereas the observation weight and gradient penalty coefficient exhibit relatively wide stable intervals, and the background constraint has a minor effect on the results. Parameter interaction analysis further demonstrates that the coupling between smoothing strength and observation weight is the most significant. The proposed method provides a physically consistent and parameter-controllable framework for multi-source deformation data fusion in mining subsidence monitoring. Full article

Aquatic recreation significantly enhances well-being; however, individuals experiencing functional limitations remain frequently marginalized from this form of tourism due to infrastructural and environmental barriers. This study investigates the perceived operational risks and apprehensions encountered by users with specific accessibility needs during yacht sailing, aiming to inform inclusive vessel design aligned with the social dimension of sustainable development. A survey of 277 participants with diverse, officially certified functional limitations was conducted to evaluate their maritime experiences and safety concerns. Participants identified a mean of 11 pre-voyage apprehensions out of 19 distinct risk categories. The most prevalent concerns included stumbling, slipping, or falling on board (79%), the risk of falling overboard (73%), and seasickness (70%), with an overall moderate severity ($\overline{X}$ = 2.2 on a 4-point scale). Crucially, severe safety concerns (e.g., vessel sinking or falling overboard) were significantly mitigated following practical sailing experience. Conversely, everyday functional and ergonomic challenges—such as moving between the deck and crew quarters ($\overline{X}$ = 2.6), operating rigging ($\overline{X}$ = 2.7), embarkation ($\overline{X}$ = 2.6), and utilizing sanitary facilities ($\overline{X}$ = 2.1)—persisted irrespective of experience level. Statistical analysis revealed that gender and age had negligible effects on concern levels. Extensive maritime experience reduced apprehensions regarding balance and swimming competencies, while concurrently increasing awareness of communication and comfort-related operational challenges. This study highlights a distinct divergence between initial psychological anxiety—which is largely mitigated by experience—and persistent architectural barriers inherent in standard yacht design. The results underscore that achieving meaningful inclusivity in water tourism requires prioritizing interior spatial layouts, accessible sanitary facilities, and barrier-free vertical circulation in naval architecture, rather than focusing exclusively on emergency safety systems. These insights directly support the advancement of Sustainable Development Goal 10 and the integration of universal and human-centered design principles within the maritime recreation sector. Full article

Background: Alcohol use disorder (AUD) is a grave mental health condition that can result in significant health and social consequences. The medications Naltrexone and Nalmefene are indicated for the treatment of AUD, with Naltrexone having received the most extensive research attention. Methods: The majority of papers assessing universal measures of alcohol consumption employed two primary metrics: total alcohol consumption (TAC) and the number of days per month where individuals engaged in heavy drinking (HDD). Indicators pertaining to the maintenance of complete abstinence were excluded due to the absence of sufficient data. The safety of both substances was also assessed, as were the frequency of side effects and independent patient dropout. The study also incorporated practical factors of the therapy, such as the route of administration, dosage regimen, and the drug’s patient convenience, which can have a significant impact on adherence to therapy. Results: Nalmefene, administered in an “as needed” regimen, demonstrated statistically significant activity in reducing HDD and total alcohol consumption (TAC) among patients with AUD, particularly those with elevated World Health Organization (WHO) DRL risk. Preliminary findings from the ESENSE1 (Efficacy of Nalmefene in Alcohol Dependence; the first phase III study), ESENSE 2 (Efficacy of Nalmefene in Alcohol Dependence, the second phase III study), and SENSE (the final phase III long term-safety and cost-effectiveness study) studies indicate a substantial decrease in HDD and TAC following the initial month of treatment. These effects persist throughout the subsequent follow-up period. Several Japanese studies have corroborated the effectiveness of Nalmefene, demonstrating its efficacy across both short-term and long-term applications. Furthermore, these studies have substantiated its safety profile, indicating that there is no inherent risk of addiction or the emergence of withdrawal symptoms. The mild nature of adverse events (most commonly nausea and dizziness) led to a relatively low discontinuation rate of Nalmefene treatment. A subsequent study, employing a recognized methodology, corroborated the efficacy of psychosocial support in enhancing treatment outcomes. Meta-analyses demonstrate that Naltrexone exhibits comparable efficacy in reducing the frequency and severity of alcohol consumption. In select populations, the injectable form (LAI) of this pharmaceutical agent facilitates less frequent dosing, which is advantageous for the treatment process. A comparison of Nalmefene and Naltrexone reveals that the latter does not demonstrate a significant impact on the likelihood of individuals returning to heavy alcohol consumption. Conclusions: In the treatment of AUD, both naltrexone and nalmefene have been shown to yield positive outcomes, particularly in terms of reducing the HDD and TAC. According to the World Health Organization (WHO) classification, Nalmefene is indicated for individuals with a high risk of developing serious conditions. It has been demonstrated to produce rapid and sustained results while exhibiting a favorable safety profile, characterized by the absence of significant adverse effects. Naltrexone is a medication that has proven to be effective. LAI may have a positive impact on the efficacy of treatment. Full article

Cyber–Physical Systems (CPSs) are increasingly vulnerable to Distributed Denial-of-Service (DDoS) attacks, which can disrupt critical operations and compromise system safety. Although deep learning (DL) techniques are widely adopted for cyberattack detection, conventional DL-based classifiers often struggle to handle the uncertainty and ambiguity inherent in network traffic data. To address this limitation, this paper proposes an AI-driven hybrid framework, termed LSTM–Fuzzy–CPS, for adaptive DDoS detection in CPS environments. Unlike prior LSTM–Fuzzy approaches that are primarily restricted to SDN settings, the proposed framework is adapted for CPS environments and introduces continuous risk scoring, reduced false positives for safety-critical operation, and proportional mitigation mechanisms. The framework consists of a detection module and a conceptual mitigation module. The detection module, named LSTM–Fuzzy–Detector, integrates an LSTM network with a Mamdani-type fuzzy inference system that maps LSTM outputs into a continuous risk score using triangular membership functions (Low, Medium, High) and centroid defuzzification. The mitigation module is designed as a rule-based conceptual framework that translates risk levels into adaptive response actions; however, its experimental implementation is left for future work. The proposed detector is evaluated on the CICIoT2023 dataset and achieves an accuracy of 99.83% with a false-positive rate of 0.12%, demonstrating strong robustness against complex and evolving attack patterns. These results indicate that the proposed framework provides an effective, interpretable, and scalable solution for intelligent threat detection in CPS environments. Full article

To date, lithium–ion batteries (LIBs) are considered one of the most promising and market-leading energy storage systems due to their high theoretical capacity and energy density. However, poor thermal and cyclic stability, low electrolyte uptake, and the possibility for frequent short circuits of typical separators and evolution of several gases during long cycle operation pose several problems for LIBs. Metal-organic frameworks (MOFs) have attracted widespread interest as a promising material for improving the cycle stability and safety of rechargeable batteries due to their inherent surface and structural properties such as high specific surface area, high porosity, and ionic conductivity. In this work, the aim is to provide detailed descriptions of the synthesis routes and parameters for obtaining various MOFs such as Zr-MOF-808 and Ni-MOF-74 nanoparticles and the fabrication of those MOF-integrated separators. To optimize the crystallinity, morphological and compositional characteristics, and several material characterizations such as XRD, SEM, and EDX have been applied. Afterwards, the synthesized MOF-integrated glass fiber (GF) separators have been developed for lithium–ion battery (LIB) applications. To investigate the electrochemical performance and the effect of MOF integration into the separators, electrochemical studies in the form of galvanostatic charge–discharge (GCD), electrochemical impedance spectroscopy (EIS) have been evaluated by preparing CR2032-type half-coin cells. This MOFs-integrated GF-separators and synthesized LiNi_0.6Mn_0.2Co_0.2O₂ (NMC622) cathode materials-based coin cell LIB exhibited higher cycle stability than bare GF-separator based LIB. This novel approach and extensive research suggest that development of MOF-integrated separators could significantly improve cycle stability by reducing the internal cell degradation for next generation energy storage devices. Full article

Recent advances in roadside sensing technologies, including camera-based systems, radar, and LiDAR, have enabled high-resolution sampling of vehicle trajectories, overcoming the temporal and spatial limitations of traditional data collection methods. Among these, LiDAR sensing has been widely adopted for traffic monitoring and surrogate safety analysis due to its high spatial accuracy and temporal resolution. However, sensor noise and occlusion in roadside LiDAR frequently introduce tracking point offsets and trajectory discontinuities, reducing the reliability of vehicle counts, traffic state estimation, and conflict analysis. To address these challenges, this study proposes a post-processing method based on time–space analysis to detect and correct occlusion-induced trajectory discontinuities. By exploiting the inherent spatiotemporal consistency of vehicle movements, the proposed approach identifies fragmented trajectories, reconstructs continuous vehicle paths, and recovers realistic traffic patterns. Validated on real-world LiDAR data collected at an urban intersection in Reno, Nevada, across four 30 min traffic periods covering AM and PM peak conditions on weekdays and weekends, the proposed method achieves an average precision of 0.989 and an average F1-score of 0.948, outperforming IMM, GNN-RM, and HMM + Viterbi benchmark methods. Count accuracy improved from 85.5% to 97.4% across all evaluated periods, confirming the method’s effectiveness under occlusion conditions. Full article

The transition to automated vehicles (AVs) introduces complex human factors and system-level challenges across Society of Automotive Engineers (SAE) Levels 0–5, with profound implications for the long-term viability of future transport infrastructure. Drawing on a synthesis of socio-technical, cognitive, and behavioural adaptation theories, this study develops an integrated framework to analyse the evolving relationships among driving automation, human behaviour, system risks, and urban sustainability. The findings demonstrate that human-factor risks are inherently nonlinear, meaning they do not decrease proportionally as technology advances; instead, risk profiles peak significantly at intermediate automation levels (SAE 2–3) due to supervisory fatigue and delayed takeovers, introducing severe traffic flow volatility and localised micro-congestion that directly compromise the environmental efficiency of sustainable transport systems. As these risks reconfigure into institutional and digital infrastructure dependencies at higher levels (SAE 4–5), the primary constraint shifts toward network readiness. Through an analysis of real-world AV deployment case studies and a structured narrative literature review, this paper identifies critical operational discontinuities and mixed-traffic complexities that threaten urban grid resilience. This study proposes a conceptual framework that translates these cross-level socio-technical insights into actionable deployment pathways, providing policymakers with adaptive governance models, transportation planners with mixed-traffic management strategies aimed at preserving network efficiency, infrastructure agencies with physical and digital readiness criteria for long-term asset sustainability, and AV developers with human–machine interface optimisation frameworks to secure human-centric safety within sustainable smart city networks. Full article

Background/Objectives: Intraoperative fluorescence imaging (FI) with tumor-targeted tracers offers a promising approach to improve surgical precision in cancer surgery. cRGD-ZW800-1, an integrin-targeted fluorescent tracer, has previously demonstrated safety, tumor specificity, and utility in detecting inadequate margins in oral cancer. During this study, we observed variability in background fluorescence between different subsites of the oral cavity. Therefore, this study aimed to systematically evaluate intraoperative in vivo and ex vivo mucosal contrast ratios across various oral cavity subsites using FI with cRGD-ZW800-1. Methods: Thirty-one patients with oral squamous cell carcinoma underwent intraoperative FI following intravenous injection of cRGD-ZW800-1 at least 18 h preoperatively. In vivo imaging was performed using the Quest Spectrum platform. In addition, ex vivo FI of the resected specimen was performed using the Pearl Trilogy Small Animal Imaging System. As these ex vivo images were obtained under uniform and controlled acquisition conditions, they allow for direct comparison with the intraoperative fluorescence signals. Fluorescence intensities and tumor-to-background ratios (TBRs) were assessed per oral subsite using manually drawn regions of interest (ROIs) on the tumor and adjacent healthy mucosa using Quest’s Spectrum Software, version 4.8.2, (in vivo images) and the Pearl’s integrated software ImageStudio version 6.2 (ex vivo images). A TBR ≥ 1.5 was considered sufficient. Results: Under uniform imaging settings, all samples exhibited adequate contrast (TBR ≥ 2.3), allowing clear tumor visualization and precise evaluation of mucosal margins on final histopathology. Notably, intraoperative in vivo contrast in the posterior located maxillary alveolar process was comparatively lower, which was attributable to suboptimal imaging conditions and subsite-specific background fluorescence. Conclusions: Our findings indicate that, although contrast varies across different oral subsites, all specimens exhibited sufficient ex vivo mucosal contrast to allow reliable tumor delineation. As in vivo imaging may be affected by subsite-specific background fluorescence and inherent limitations of intraoperative imaging geometry, fluorescence signals should be interpreted in conjunction with standard visual and tactile assessment. Due to anatomical constraints, different oral subsites may appear within the same field of view, which can influence perceived signal intensity. Therefore, intraoperative ex vivo fluorescence evaluation is recommended for signal interpretation. Full article