Search Results (62)

The rising popularity of in-vehicle information systems (IVIS) in China highlights the significance of Chinese character displays. A key design factor for text-rich in-vehicle human–machine interfaces (HMI) is Chinese text size (CTS). However, the impact of CTS on text legibility and driver distraction has not been extensively explored. The present study launches a simulator experiment and adopts several one-way repeated-measure analyses of variance to identify the optimal CTS that maximizes text legibility while minimizing driver distraction. The findings indicate that both text legibility and driver distraction improved progressively as the CTS increased, reaching a specific size of seven millimeters, at which they approached asymptotes. Subjective measures were more sensitive than objective measures. The analysis showed no significant impact of CTS on task completion time, number of errors, total glance duration, mean speed, or lane position variation. However, larger CTS led to more frequent, shorter glances, whereas smaller CTS resulted in fewer, longer glances. CTS below seven millimeters was associated with lower subjective preference and a higher perceived workload. Therefore, it is recommended that a CTS of seven millimeters or larger be used to promote the design of driver-friendly in-vehicle HMI, control IVIS-related distractions, and enhance road safety in China. Full article

The automatic detection of traffic accidents plays an increasingly vital role in advancing intelligent traffic monitoring systems and improving road safety. Leveraging computer vision techniques offers a promising solution, enabling rapid, reliable, and automated identification of accidents, thereby significantly reducing emergency response times. This study proposes an enhanced version of the YOLO11 architecture, termed YOLO11-AMF. The proposed model integrates a Mamba-Like Linear Attention (MLLA) mechanism, an Asymptotic Feature Pyramid Network (AFPN), and a novel Focaler-IoU loss function to optimize traffic accident detection performance under complex and diverse conditions. The MLLA module introduces efficient linear attention to improve contextual representation, while the AFPN adopts an asymptotic feature fusion strategy to enhance the expressiveness of the detection head. The Focaler-IoU further refines bounding box regression for improved localization accuracy. To evaluate the proposed model, a custom dataset of traffic accident images was constructed. Experimental results demonstrate that the enhanced model achieves precision, recall, mAP50, and mAP50–95 scores of 96.5%, 82.9%, 90.0%, and 66.0%, respectively, surpassing the baseline YOLO11n by 6.5%, 6.0%, 6.3%, and 6.3% on these metrics. These findings demonstrate the effectiveness of the proposed enhancements and suggest the model’s potential for robust and accurate traffic accident detection within real-world conditions. Full article

This research investigated the temporal dynamics of the anthropogenic impact of fishing pressure on the resilience of the fish species Sarotherodon melanotheron (Rüppel, 1858) in the African Lake Toho, located in southwest Benin. The sampling and analysis of monthly length frequency data were conducted from April 2002 to March 2003 and from April 2022 to March 2023 using the FAO-ICLARM Stock Assessment Tool (FiSAT II software program (version 1.2.2.). The analysis of the S. melanotheron population in Lake Toho revealed a significantly diminishing resilience potential, reflected mainly in general reductions in both the average size and weight of individuals. There was a notable reduction in the size of Sarotherodon melanotheron individuals caught between 2002–2003 and 2022–2023, reflecting the increased pressure on juvenile size classes. Catches are now concentrated mainly on immature fish, revealing increasing exploitation before sexual maturity is reached. An analysis of maturity stages showed a decrease in the percentage of mature individuals in the catches (69.27% in 2002–2003 compared to 55.07% in 2022–2023) and a reduction in the number of mega-spawners (4.53% in 2002–2003 compared to 1.56% in 2022–2023). Growth parameters revealed a decrease in asymptotic length (from 32.2 cm to 23.8 cm) and longevity (from 9.37 years to 7.89 years), while the growth coefficient slightly increased. The mean size at first capture and optimal size significantly declined, indicating increased juvenile exploitation. The total and natural mortalities increased, whereas the fishing mortality remained stable. The exploitation rate remained high, despite a slight decrease from 0.69 to 0.65. Finally, the declines in the yield per recruit, maximum sustainable yield, and biomass confirm the increasing fishing pressure, leading to growth overfishing, recruitment overfishing, reproductive overfishing, and, last but not least, a decreasing resilience potential. These findings highlight the growing overexploitation of S. melanotheron in Lake Toho, compromising stock renewal, fish population resilience, sustainability, and production while jeopardizing local food safety. Full article

Prefabricated unidirectional carbon fiber reinforced polymer (CFRP) composite strips are extensively used as a means of infrastructure rehabilitation through adhesive bonding to the external surface of structural concrete elements. Most data to date are from laboratory tests ranging from a few months to 1–2 years providing an insufficient dataset for prediction of long-term durability. This investigation focuses on the assessment of the response of three different prefabricated CFRP systems exposed to water, seawater, and alkaline solutions for 5 years of immersion in deionized water conducted at three temperatures of 23, 37.8 and 60 °C, all well below the glass transition temperature levels. Overall response is characterized through tensile and short beam shear (SBS) testing at periodic intervals. It is noted that while the three systems are similar, with the dominant mechanisms of deterioration being related to matrix plasticization followed by fiber–matrix debonding with levels of matrix and interface deterioration being accelerated at elevated temperatures, their baseline characteristics and distributions are different emphasizing the need for greater standardization. While tensile modulus does not degrade appreciably over the 5-year period of exposure with final levels of deterioration being between 7.3 and 11.9%, both tensile strength and SBS strength degrade substantially with increasing levels based on temperature and time of immersion. Levels of tensile strength retention can be as low as 61.8–66.6% when immersed in deionized water at 60 °C, those for SBS strength can be 38.4–48.7% at the same immersion condition for the three FRP systems. Differences due to solution type are wider in the short-term and start approaching asymptotic levels within FRP systems at longer periods of exposure. The very high levels of deterioration in SBS strength indicate the breakdown of the materials at the fiber–matrix bond and interfacial levels. It is shown that the level of deterioration exceeds that presumed through design thresholds set by specific codes/standards and that new safety factors are warranted in addition to expanding the set of characteristics studied to include SBS or similar interface-level tests. Alkali solutions are also shown to have the highest deteriorative effects with deionized water having the least. Simple equations are developed to enable extrapolation of test data to predict long term durability and to develop design thresholds based on expectations of service life with an environmental factor of between 0.56 and 0.69 for a 50-year expected service life. Full article

Altitude test facilities for aero-engines employ multi-chamber, multi-valve intake systems that require effective decoupling and strong disturbance rejection during transient tests. This paper proposes a coordinated active disturbance rejection control (ADRC) scheme based on external penalty functions. The chamber pressure safety limit is formulated as an inequality-constrained optimization problem, and an exponential penalty together with a gradient based algorithm is designed for dynamic constraint relaxation, with guaranteed global convergence. A coordination term is then integrated into a distributed ADRC framework to yield a multi-valve coordinated ADRC controller, whose asymptotic stability is established via Lyapunov theory. Hardware-in-the-loop simulations using MATLAB/Simulink and a PLC demonstrate that, under ±3 kPa pressure constraints, the maximum engine inlet pressure error is 1.782 kPa (77.1% lower than PID control), and under an 80 kg/s² flow-rate disturbance, valve oscillations decrease from ±27% to ±5%. These results confirm the superior disturbance rejection and decoupling performance of the proposed method. Full article

In the continuous drilling process of oil wells, to achieve the efficient screening of drilling fluids by the vibrating screen while ensuring the safety of the screening operation, an anti-resonance system driven by two exciters with triple-frequency (denoted as 3:1 frequency ratio) is proposed. Initially, differential motion equations are formulated utilizing Lagrange’s equation, followed by the definition of vibration isolation coefficients adopting ratios. Triple-frequency synchronization and stability criterion between two eccentric blocks are subsequently elucidated via the asymptotic method and Routh–Hurwitz criterion. Concurrently, the effects of structural parameters on vibration isolation capacity, steady-state trajectory, and the triple-frequency synchronization phase are investigated through numerical computation. Ultimately, the reliability of the theoretical study is corroborated by simulation analysis. Results indicate that under the allowable system parameters for the practical project, the amplitude of the vibration body can exceed three times that of the isolation body; the two solutions of the stable phase difference (SPD) are different by π, one of which is stable and the other is unstable, and the stability of phase difference is determined by the sign of the stability coefficient. This work is useful for developing new vibrating screens and other multi-frequency vibration machines. Full article

Traditional reliability methods using fixed removal plans often overlook withdrawal randomness, leading to biased estimates for asymmetric data. This study advances classical and Bayesian frameworks for the inverse Chen distribution, which is suited for modeling asymmetric data under adaptive progressively Type-II censoring with binomial removals. Here, removals post-failure follow a dynamic binomial process, enhancing a more realistic approach for reliability studies. Maximum likelihood estimates are computed numerically, with confidence intervals derived asymptotically. Bayesian approaches employ gamma priors, symmetric squared error loss, and posterior sampling for estimates and credible intervals. A simulation study validates the methods, while two asymmetric real-world applications demonstrate practicality: (1) analyzing diamond sizes from South-West Africa, capturing skewed geological distributions, and (2) modeling failure times of airborne communication transceivers, vital for aviation safety. The flexibility of the inverse Chen in handling asymmetric data addresses the limitations of symmetric assumptions, offering precise reliability tools for complex scenarios. This integration of adaptive censoring and asymmetric distributions advances reliability analysis, providing robust solutions where traditional approaches falter. Full article

This paper proposes a modular control framework for high-order nonlinear multi-agent systems (MASs) to achieve distributed finite-time formation tracking with a prescribed performance. The design integrates two modules to address uncertainties and safety constraints simultaneously. Module I—Prescribed Performance-Based Trajectory Generation: A virtual signal generator constructs collision/connectivity-aware reference trajectories by encoding time-varying performance bounds into formation errors. It ensures network rigidity and optimal formation convergence through dynamic error transformation. Module II—Anti-disturbance Tracking Control: A finite-time extended state observer (FTESO) estimates and compensates for uncertainties within a finite time, while a time-varying surface controller drives tracking errors into predefined performance funnels. This module guarantees rapid error convergence without violating the transient constraints from Module I. The simulations verified the accelerated formation reconfiguration under disturbances, and thus, demonstrated improved robustness and convergence over asymptotic approaches. The framework offers a systematic solution for safety-critical MAS coordination with heterogeneous high-order dynamics. Full article

Safety control based on barrier functions has gradually become one of the emerging and more important directions in the field of safety. Scholars are attempting to apply barrier functions to integer-order dynamical systems, such as general nonlinear systems, hybrid systems, linear systems, etc. Moreover, the introduction of barrier functions has even expanded the research approaches on safe reinforcement learning. However, there is very little research on the safety control problem of fractional-order dynamical systems. Based on our previous work, this article further explores, in depth, the problem of the transfer and adaptability of barrier functions for integer-order systems in fractional-order systems, and it also proposes the Caputo reciprocal barrier function and Caputo zeroing barrier function. And we established two theorems, which proved that we can also achieve uniform asymptotic stability or exponential stability with guaranteed safety. In the end, we created a new description for the definition of input-to-state safety under Caputo’s fractional-order systems, and we used this description and the above two Caputo barrier functions to construct two criteria of the Caputo input-to-state safety. Thus, we, finally, established the embryonic form of the theoretical framework of safety control based on barrier functions for fractional-order systems. Full article

Due to the difficulty in ensuring launch safety under unfavorable launch site conditions, restrictions regarding the selection of launch sites significantly weaken the maneuverability of the unsupported random vertical launch (URVL) mode. In this paper, a nonlinear robust control strategy is proposed to control the missile attitude by actively adjusting the oscillation of the launcher through the hydraulic actuator, enhancing the launching safety and the adaptability of the VMLS to the launching site. Firstly, considering the interaction among the launch canister, adapters, and missile, a 6-DOF dynamic model of the launch system is established, in combination with the dynamics of the hydraulic actuator. Then, in order to facilitate the nonlinear controller design, the seventh-order state-space equation is constructed, according to the dynamic model of the launch system. Subsequently, in view of the problem of “differential explosion” in the backstepping controller design of the seventh-order nonlinear system, a nonlinear dynamic surface control (DSC) framework is proposed. Meanwhile, the time delay estimation (TDE) technique is introduced to suppress the influence of the complex nonlinearities of the launch system on the missile attitude control, and a nonlinear robust control (NRC) is introduced to attenuate the TDE error. Both of these are integrated into the DSC framework, which can achieve asymptotic output tracking. Finally, numerical simulations are conducted to validate the superiority of the proposed control strategy in regards to missile launch response control. Full article

Making use of the well-known renormalization group (RG) scale dependences of the gravitational couplings in the framework of the two-parameter Einstein–Hilbert (EH) theory of gravity, the single scalar field-driven cosmological inflation is discussed in a spatially homogeneous, isotropic, and flat model universe. The inflaton field is represented by a one-component real, non-self-interacting, massive scalar field minimally coupled to gravity. Cases without and with the incorporation of the RG scaling of the inflaton mass are compared with each other and with the corresponding classical case. It is shown that the quantum improvement drastically alters the timing of the slow-roll inflation with the desirable number $\underset{,}{\mathrm{N}}\approx 60$ e-foldings, as compared with the classical case. Furthermore, accounting for the RG flow of the inflaton mass has an enormous effect on the timing of the desirable slow roll, too. Although providing the desirable slow-roll inflation, none of the versions of the investigated quantum-improved toy models provide a realistic value of the amplitude of the scalar perturbations. Full article

Meta-analysis aggregates information across related studies to provide more reliable statistical inference and has been a vital tool for assessing the safety and efficacy of many high-profile pharmaceutical products. A key challenge in conducting a meta-analysis is that the number of related studies is typically small. Applying classical methods that are asymptotic in the number of studies can compromise the validity of inference, particularly when heterogeneity across studies is present. Moreover, serious adverse events are often rare and can result in one or more studies with no events in at least one study arm. Practitioners remove studies in which no events have occurred in one or both arms or apply arbitrary continuity corrections (e.g., adding one event to arms with zero events) to stabilize or define effect estimates in such settings, which can further invalidate subsequent inference. To address these significant practical issues, we introduce an exact inference method for random effects meta-analysis of a treatment effect in the two-sample setting with rare events, which we coin “XRRmeta”. In contrast to existing methods, XRRmeta provides valid inference for meta-analysis in the presence of between-study heterogeneity and when the event rates, number of studies, and/or the within-study sample sizes are small. Extensive numerical studies indicate that XRRmeta does not yield overly conservative inference. We apply our proposed method to two real-data examples using our open-source R package. Full article

Autonomous driving has demonstrated impressive driving capabilities, with behavior decision-making playing a crucial role as a bridge between perception and control. Imitation Learning (IL) and Reinforcement Learning (RL) have introduced innovative approaches to behavior decision-making in autonomous driving, but challenges remain. On one hand, RL’s policy networks often lack sufficient reasoning ability to make optimal decisions in highly complex and stochastic environments. On the other hand, the complexity of these environments leads to low sample efficiency in RL, making it difficult to efficiently learn driving policies. To address these challenges, we propose an innovative Knowledge Distillation-Enhanced Behavior Transformer (KD-BeT) framework. Building on the successful application of Transformers in large language models, we introduce the Behavior Transformer as the policy network in RL, using observation–action history as input for sequential decision-making, thereby leveraging the Transformer’s contextual reasoning capabilities. Using a teacher–student paradigm, we first train a small-capacity teacher model quickly and accurately through IL, then apply knowledge distillation to accelerate RL’s training efficiency and performance. Simulation results demonstrate that KD-BeT maintains fast convergence and high asymptotic performance during training. In the CARLA NoCrash benchmark tests, KD-BeT outperforms other state-of-the-art methods in terms of traffic efficiency and driving safety, offering a novel solution for addressing real-world autonomous driving tasks. Full article

Laminated composite bolted joints are increasingly used in the aerospace field, and their damage and failure behavior has been studied in depth. In view of the complexity and stability requirements of laminated composite bolted structures, accurate prediction of damage evolution and failure behavior is significant to ensure the safety and reliability of the structures. In this paper, a novel asymptotic damage model is developed to predict the damage process and failure behavior of laminated composite bolted joints. In this model, the modified Puck criterion and the maximum shear stress criterion are used for fiber yarns. The parabolic yield criterion is adopted for the matrix, and the fiber fracture, inter-fiber fracture and matrix fracture are considered at the microscopic level. The pull-out strength and progressive failure behavior of countersunk and convex bolted joints structures are predicted by using the proposed model, and the corresponding experimental studies are carried out. The results show that the prediction results are in good agreement with the experimental data, which verifies the reliability of the model. Additionally, the effects of different structural parameters (thickness and aperture) on the progressive damage and failure behavior during pull-out is analyzed by the proposed model, and correction factors of pull-out strength are obtained, which provides a powerful tool for the design, analysis and progression of laminated composite bolted joint structures. Full article

In a recent contribution, we identified possible points of contact between the asymptotically safe and canonical approaches to quantum gravity. The idea is to start from the reduced phase space (often called relational) formulation of canonical quantum gravity, which provides a reduced (or physical) Hamiltonian for the true (observable) degrees of freedom. The resulting reduced phase space is then canonically quantized, and one can construct the generating functional of time-ordered Wightman (i.e., Feynman) or Schwinger distributions, respectively, from the corresponding time-translation unitary group or contraction semigroup, respectively, as a path integral. For the unitary choice, that path integral can be rewritten in terms of the Lorentzian Einstein–Hilbert action plus observable matter action and a ghost action. The ghost action depends on the Hilbert space representation chosen for the canonical quantization and a reduction term that encodes the reduction of the full phase space to the phase space of observables. This path integral can then be treated with the methods of asymptotically safe quantum gravity in its Lorentzian version. We also exemplified the procedure using a concrete, minimalistic example, namely Einstein–Klein–Gordon theory, with as many neutral and massless scalar fields as there are spacetime dimensions. However, no explicit calculations were performed. In this paper, we fill in the missing steps. Particular care is needed due to the necessary switch to Lorentzian signature, which has a strong impact on the convergence of “heat” kernel time integrals in the heat kernel expansion of the trace involved in the Wetterich equation and which requires different cut-off functions than in the Euclidian version. As usual we truncate at relatively low order and derive and solve the resulting flow equations in that approximation. Full article