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Rolling bearings are prone to failure, meaning that research on intelligent fault diagnosis is crucial in relation to this key transmission component in rotating machinery. The application of deep learning (DL) has significantly advanced the development of intelligent fault diagnosis. This paper proposes a novel method for rolling bearing fault diagnosis based on the fractional constant Q non-stationary Gabor transform (FCO-NSGT) and VMamba-Conv. Firstly, a rolling bearing fault experimental platform is established and the vibration signals of rolling bearings under various working conditions are collected using an acceleration sensor. Secondly, a kurtosis-to-entropy ratio (KER) method and the rotational kernel function of the fractional Fourier transform (FRFT) are proposed and applied to the original CO-NSGT to overcome the limitations of the original CO-NSGT, such as the unsatisfactory time–frequency representation due to manual parameter setting and the energy dispersion problem of frequency-modulated signals that vary with time. A lightweight fault diagnosis model, VMamba-Conv, is proposed, which is a restructured version of VMamba. It integrates an efficient selective scanning mechanism, a state space model, and a convolutional network based on SimAX into a dual-branch architecture and uses inverted residual blocks to achieve a lightweight design while maintaining strong feature extraction capabilities. Finally, the time–frequency graph is inputted into VMamba-Conv to diagnose rolling bearing faults. This approach reduces the number of parameters, as well as the computational complexity, while ensuring high accuracy and excellent noise resistance. The results show that the proposed method has excellent fault diagnosis capabilities, with an average accuracy of 99.81%. By comparing the Adjusted Rand Index, Normalized Mutual Information, F1 Score, and accuracy, it is concluded that the proposed method outperforms other comparison methods, demonstrating its effectiveness and superiority. Full article

To address the central cracking problem in continuous casting slabs of 38CrMoAl steel, high-temperature tensile tests were performed using a Gleeble-3800 thermal simulator to characterize the hot ductility of the steel within the temperature range of 600–1200 °C. The phase transformation behavior was computationally analyzed via the Thermo-Calc software, while the microstructure, fracture morphology, and precipitate characteristics were systematically investigated using a metallographic microscope (MM), a field-emission scanning electron microscope (FE-SEM), and transmission electron microscopy (TEM). Additionally, the effects of different holding times and cooling rates on the microstructure and precipitates of 38CrMoAl steel were also studied. The results show that the third brittle temperature region of 38CrMoAl steel is 645–1009 °C, and the fracture mechanisms can be classified into three types: (I) in the α single-phase region, the thickness of intergranular proeutectoid ferrite increases with rising temperature, leading to reduced hot ductility; (II) in the γ single-phase region, the average size of precipitates increases while the number density decreases with increasing temperature, thereby improving hot ductility; and (III) in the α + γ two-phase region, the precipitation of proeutectoid ferrite promotes crack propagation and the dense distribution of precipitates at grain boundaries causes stress concentration, further deteriorating hot ductility. Heat treatment experiments indicate that the microstructures of the specimen transformed under water cooling, air cooling, and furnace cooling conditions as follows: martensite + proeutectoid ferrite → bainite + ferrite → ferrite. The average size of precipitates first decreased, then increased, and finally decreased again with increasing holding time, while the number density exhibited the opposite trend. Therefore, when the holding time was the same, reducing the cooling rate could increase the average size of the precipitates and decrease their number density, thereby improving the hot ductility of 38CrMoAl steel. Full article

For the precise description of gas physical processes in high-voltage direct current (HVDC) transmission, an advanced and robust numerical framework for the simulation of transient particle densities in the course of corona discharges is developed in this work. The aim is the scalable and consistent modeling of the space charge density under realistic conditions. The core component of the framework is a discontinuous Galerkin method that ensures the conservative properties of the underlying hyperbolic problem. The space charge density at the electrode surface is imposed as a dynamic boundary condition via Lagrange multipliers. To increase the numerical stability and convergence rate, a homotopy approach is also integrated. For the experimental validation, a measurement concept was realised that uses a subtraction method to specifically remove the displacement current component in the signal and thus enables an isolated recording of the transient ion current with superimposed voltage stresses. The experimental results on a small scale agree with the numerical predictions and prove the quality of the model. On this basis, the framework is transferred to hybrid HVDC overhead line systems with a bipolar design. In the event of a fault, significant transient space charge densities can be seen there, especially when superimposed with new types of voltage waveforms. The framework thus provides a reliable contribution to insulation coordination in complex HVDC systems and enables the realistic analysis of electrohydrodynamic coupling effects on an industrial scale. Full article

This paper presents an electromechanical coupling model integrating an equivalent magnetic network (EMN) model of a dual three-phase permanent magnet synchronous motor (DTP-PMSM) with the dynamic model of a helical planetary gear transmission system. Using this model, this study analyzes the dynamic characteristics of an electric drive system, specifically motor phase current, electromagnetic torque, and gear meshing force, under self-fault-tolerant control strategies. Simulation and experimental results demonstrate that the self-fault-tolerant control strategy enables rapid fault tolerance during open-phase faults, significantly reducing system fault recovery time. Meanwhile, compared to the open-phase faults conditions, the self-fault-tolerant control effectively suppresses most harmonic components within the system; only the second harmonic amplitude of the electromagnetic torque exhibited an increase. This harmonic disturbance propagates to the gear system through electromechanical coupling, synchronously amplifying the second harmonic amplitude in the gear system’s vibration response. This study demonstrates that self-fault-tolerant control strategies significantly enhance the dynamic response performance of the electric drive system under open-phase faults conditions. Furthermore, this study also investigates the electromechanical coupling mechanism through which harmonics generated by this strategy affect the gear system’s dynamic response, providing theoretical support for co-optimization electromechanical coupling design and fault-tolerant control in high-reliability electric drive transmission systems. Full article

Rabies remains a significant global public health concern, causing an estimated 59,000–69,000 human fatalities annually. Despite being entirely preventable through vaccination, rabies continues to impose substantial economic burdens worldwide. This study presents a scoping review of the economic research on rabies to determine overlaps and gaps in knowledge and inform future research strategies. We selected 150 studies (1973–2024) to analyze. The review categorizes the literature based on geographic distribution, species focus, and type of study. Findings indicate that economic studies are disproportionately concentrated in developed countries, such as the United States and parts of Europe, where rabies risk is low, while high-risk regions, particularly in Africa and Asia, remain underrepresented. Most studies focus on dog-mediated rabies, reflecting its dominant role in human transmission, while fewer studies assess the economic impacts of wildlife and livestock-mediated rabies. Case studies and modeling approaches dominate the literature, whereas cost–benefit and cost–effectiveness analyses—critical for informing resource allocation—are limited. The review highlights the need for more economic evaluations in rabies-endemic regions, expanded research on non-dog reservoirs, and broader use of economic methods. Addressing these gaps will be crucial for optimizing rabies control and supporting global initiatives to eliminate dog-mediated rabies by 2030. Full article

Background/Objectives: Mumps remains a relevant vaccine-preventable disease globally, especially in settings where immunization coverage fluctuates or vaccine-induced immunity wanes. This study aimed to assess long-term trends in mumps incidence, vaccination coverage, clinical outcomes, and demographic characteristics in the Autonomous Province of Vojvodina (AP Vojvodina), Serbia, over a 47-year period. Methods: We conducted a retrospective observational study using surveillance data from the Institute of Public Health of Vojvodina. Analyses included annual mumps incidence rates (1978–2024), coverage with mumps-containing vaccines (MuCVs; 1986–2024), monthly case counts, and individual-level case data for the 1997–2024 period. Variables analyzed included age, month of notification, gender, vaccination status, presence of clinical complications, and the method used for case confirmation. Results: Following the introduction of MuCV in 1986, the mumps incidence markedly declined, with limited resurgences in 2000, 2009, and 2012. Between 1997 and 2024, a total of 1358 cases were reported, with 62.7% occurring in males. Over time, the age distribution shifted, with adolescents and young adults being increasingly affected during the later (2011–2024) observed period. In 2012, the highest age-specific incidence was observed among individuals aged 10–19 and 20–39 years (49.1 and 45.5 per 100,000, respectively). Vaccination coverage for both MuCV doses was suboptimal in several years. The proportion of unvaccinated cases decreased over time, while the proportion with unknown vaccination status increased. Mumps-related complications—such as orchitis, pancreatitis, and meningitis—were rare and predominantly affected unvaccinated individuals: 84.2% of orchitis, 40.0% of pancreatitis, and all meningitis cases. Only two pancreatitis cases (40.0%) were reported after one MMR dose, while fully vaccinated individuals (two doses) had one orchitis case (5.3%) and no other complications. Laboratory confirmation was applied more consistently from 2009 onward, with 49.6% of cases confirmed that year (58 out of 117), and, in several years after 2020, only laboratory-confirmed cases were reported, indicating improved diagnostic capacity. Conclusions: Despite substantial progress in controlling mumps, gaps in vaccine coverage, waning immunity, and incomplete vaccination records continue to pose a risk for mumps transmission. Strengthening routine immunization, ensuring high two-dose MuCV coverage, improving vaccination record keeping, and enhancing laboratory-based case confirmation are critical. Consideration should be given to booster doses in high-risk populations and to conducting a seroepidemiological study to estimate the susceptible population for mumps in AP Vojvodina. Full article

Investigating the coevolution between ecosystem services (ES) and human well-being (HWB) holds significant implications for achieving the sustainable operation of human–environment systems. However, limited research has focused on ES-HWB interactions in ecotourism-dominated counties. To address this gap, this study takes Chun’an County in Zhejiang Province, China, as a case study, with the research objective of exploring the processes, patterns, and mechanisms of the coevolution between ecosystem services (ES) and human well-being (HWB) in ecotourism-dominated counties. By integrating multi-source heterogeneous data, including land use data, the normalized difference vegetation index (NDVI), and statistical records, and employing methods such as the dynamic equivalent factor method, the PLUS model, the coupling coordination degree model, and comprehensive evaluation, we analyzed the synergistic evolution of ES-HWB in Chun’an County from 2000 to 2020. The results indicate that (1) the ecosystem service value (ESV) fluctuated between 30.15 and 36.85 billion CNY, exhibiting a spatial aggregation pattern centered on the Qiandao Lake waterbody, with distance–decay characteristics. The PLUS model confirms ecological conservation policies optimize ES patterns. (2) The HWB index surged from 0.16 to 0.8, driven by tourism-led economic growth, infrastructure investment, and institutional innovation, facilitating a paradigm shift from low to high well-being at the county level. (3) The ES-HWB interaction evolved through three phases—disordered, antagonism, and coordination—revealing tourism as a key mediator driving coupled human–environment system sustainability via a pressure–adaptation–synergy transmission mechanism. This study not only advances the understanding of ES-HWB coevolution in ecotourism-dominated counties, but also provides a transferable methodological framework for sustainable development in similar regions. Full article

Serial block-face scanning electron microscopy (SBEM) is a powerful technique for three-dimensional ultrastructural analysis of biological samples, though its application to in vitro cultured human cells remains underutilized. In this study, we present an optimized SBEM sample preparation protocol using human dermal fibroblasts and induced pluripotent stem cells (iPSCs). The method includes key modifications to the original protocol, such as using only glutaraldehyde for fixation and substituting the toxic cacodylate buffer with a less hazardous phosphate buffer. These adaptations result in excellent preservation of cellular ultrastructure, with high contrast and clarity, as validated by transmission electron microscopy (TEM). The loss of natural cell morphology resulted from fixation during passage, when cells formed a precipitate, rather than from fixation directly within the culture medium. The protocol is time-efficient, safe, and broadly applicable to both stem cells and differentiated cells cultured under 2D conditions, providing a valuable tool for ultrastructural analysis in diverse biomedical research settings. Full article

Carbon flow tracking and spatial pattern optimization at the scale of urban functional zones are key scientific challenges in achieving carbon neutrality. However, due to the complexity of carbon metabolism processes within urban functional zones, related studies remain limited. To address these scientific challenges, this study, based on the “source–sink–flow” ecosystem services framework, develops an integrated analytical approach at the scale of urban functional zones. The carbon balance is quantified using the CASA model in combination with multi-source data. A network model is employed to trace carbon flow pathways, identify critical nodes and interruption points, and optimize the urban spatial pattern through a low-carbon land use structure model. The research results indicate that the overall carbon balance in Hangzhou exhibits a spatial pattern of “deficit in the center and surplus in the periphery.” The main urban area shows a significant carbon deficit and relatively poor connectivity in the carbon flow network. Carbon sequestration services primarily flow from peripheral areas (such as Fuyang and Yuhang) with green spaces and agricultural functional zones toward high-emission residential–commercial and commercial–public functional zones in the central area. However, due to the interruption of multiple carbon flow paths, the overall carbon flow transmission capacity is significantly constrained. Through spatial optimization, some carbon deficit nodes were successfully converted into carbon surplus nodes, and disrupted carbon flow edges were repaired, particularly in the main urban area, where 369 carbon flow edges were restored, resulting in a significant improvement in the overall transmission efficiency of the carbon flow network. The carbon flow visualization and spatial optimization methods proposed in this paper provide a new perspective for urban carbon metabolism analysis and offer theoretical support for low-carbon city planning practices. Full article

In multi-user wireless communication scenarios, signal degradation caused by channel fading and co-channel interference restricts system capacity, while traditional enhancement schemes face challenges of high coordination complexity and hardware integration. This paper proposes an electromagnetic focusing method using a single-layer transmissive passive metasurface. A high-efficiency metasurface array is fabricated based on PCB technology, which utilizes subwavelength units for wide-range phase modulation to construct a multi-user energy convergence model in the WiFi band. By optimizing phase gradients through the geometric phase principle, the metasurface achieves collaborative wavefront manipulation for multiple target regions with high transmission efficiency, reducing system complexity compared to traditional multi-layer structures. Measurements in a microwave anechoic chamber and tests in an office environment demonstrate that the metasurface can simultaneously create signal enhancement zones for multiple users, featuring stable focusing capability and environmental adaptability. This lightweight design facilitates deployment in dense networks, providing an effective solution for signal optimization in indoor distributed systems and IoT communications. Full article

Terahertz (THz) communication is regarded as a key technology for achieving high-speed data transmission and wireless communication due to its ultra-high frequency and large bandwidth characteristics. In this study, we focus on a single-carrier THz communication system and propose a two-stage deep learning-based time-domain equalization method, specifically designed to mitigate the nonlinear distortions in such systems, thereby enhancing communication reliability and performance. The method adopts a progressive learning strategy, whereby global characteristics are initially captured before progressing to local levels. This enables the effective identification and equalization of channel characteristics, particularly in the mitigation of nonlinear distortion and random interference, which can otherwise negatively impact communication quality. In an experimental setting at a frequency of 230 GHz and a channel distance of 2.1 m, this method demonstrated a substantial reduction in the system’s bit error rate (BER), exhibiting particularly noteworthy performance enhancements in comparison to before equalization. To validate the model’s generalization capability, data collection and testing were also conducted at a frequency of 310 GHz and a channel distance of 1.5 m. Experimental results show that the proposed time-domain equalizer, trained using the two-stage DL framework, achieved significant BER reductions of approximately 92.15% at 230 GHz (2.1 m) and 83.33% at 310 GHz (1.5 m), compared to the system’s performance prior to equalization. The method exhibits stable performance under varying conditions, supporting its use in future THz communication studies. Full article

Static Priority-based Multiple Access (SPMA) is an emerging and promising wireless MAC protocol which is widely used in Unmanned Aerial Vehicle (UAV) networks. UAV (Unmanned Aerial Vehicle) networks, also known as drone networks, refer to a system of interconnected UAVs that communicate and collaborate to perform tasks autonomously or semi-autonomously. These networks leverage wireless communication technologies to share data, coordinate movements, and optimize mission execution. In SPMA, traffic arriving at the UAV network node can be divided into multiple priorities according to the information timeliness, and the packets of each priority are stored in the corresponding queues with different thresholds to transmit packet, thus guaranteeing the high success rate and low latency for the highest-priority traffic. Unfortunately, the multi-priority queue scheduling of SPMA deprives the packet transmitting opportunity of low-priority traffic, which results in unfair conditions among different-priority traffic. To address this problem, in this paper we propose the method of Adaptive Credit-Based Shaper with Reinforcement Learning (abbreviated as ACBS-RL) to balance the performance of all-priority traffic. In ACBS-RL, the Credit-Based Shaper (CBS) is introduced to SPMA to provide relatively fair packet transmission opportunity among multiple traffic queues by limiting the transmission rate. Due to the dynamic situations of the wireless environment, the Q-learning-based reinforcement learning method is leveraged to adaptively adjust the parameters of CBS (i.e., idleslope and sendslope) to achieve better performance among all priority queues. The extensive simulation results show that compared with traditional SPMA protocol, the proposed ACBS-RL can increase UAV network throughput while guaranteeing Quality of Service (QoS) requirements of all priority traffic. Full article

In the era of Industry 5.0, future wireless networks are increasingly shifting from traditional symmetric architectures toward heterogeneous and asymmetric paradigms, driven by the demand for diversified and dynamic services. This architectural evolution gives rise to complex and asymmetric flows, such as the coexistence of periodic and burst flows with varying latency, jitter, and deadline constraints, posing new challenges for deterministic transmission. Traditional time-sensitive networking (TSN) is well-suited for periodic flows but lacks the flexibility to effectively handle dynamic, asymmetric traffi. To address this limitation, we propose a two-stage asymmetric flow scheduling framework with dynamic deadline control, termed A-TSN. In the first stage, we design a Deep Q-Network-based Dynamic Injection Time Slot algorithm (DQN-DITS) to optimize slot allocation for periodic flows under varying network loads. In the second stage, we introduce the Dynamic Deadline Online (DDO) scheduling algorithm, which enables real-time scheduling for asymmetric flows while satisfying flow deadlines and capacity constraints. Simulation results demonstrate that our approach significantly reduces end-to-end latency, improves scheduling efficiency, and enhances adaptability to high-volume asymmetric traffic, offering a scalable solution for future deterministic wireless networks. Full article

Background: The long-term success of total knee arthroplasty (TKA) is often compromised by stress shielding, which can lead to bone resorption and even implant loosening. This study employs finite element analysis (FEA) to compare the stress-shielding effects of a knee prosthesis made from polyether ether ketone (PEEK) with a traditional titanium Ti6Al4V implant on an osteoporotic tibial bone model. Methods: Stress distribution and the stress-shielding factor (SSF) were evaluated at seven critical points in the proximal tibia under physiological loading conditions. Results: Results indicate that the PEEK prosthesis yields a more uniform stress transmission, with von Mises stress levels within the optimal 2–3 MPa range for bone maintenance and consistently negative or near-zero SSF values, implying minimal stress shielding. Conversely, titanium implants exhibited significant stress shielding with high positive SSF values across all points. Additionally, stress concentrations on the polyethylene liner were lower and more evenly distributed in the PEEK model, suggesting reduced wear potential. Conclusions: These findings highlight the biomechanical advantages of PEEK in reducing stress shielding and preserving bone integrity, supporting its potential use to improve implant longevity in TKA. Further experimental and clinical validation are warranted. Full article

The orthogonal time frequency space (OTFS) is a modulation designed to transmit data in high Doppler channels where the usage of the orthogonal frequency division multiplexing (OFDM) is challenging. The random padded OTFS (RP-OTFS) modulation, introduced recently, is an OTFS-like waveform optimized for more precise estimation of channel state information (CSI) and, in the case of integrated sensing and communication (ISAC), for radar detection as well. One of the main drawbacks of the RP-OTFS is the high level of interference between carriers (the inter-carrier interference—ICI) of Doppler-delay (DD) grid. In the article, we optimize the RP-OTFS waveform in terms of reducing the level of pilot-to-data interference and also offer a way to reduce the data carrier interference. The reduction in the pilot-to-data interference is achieved due to the introduction of the following: (1) redistributing interferences along the DD grid, and (2) special DD grid configuration. In turn, the reduction in data carrier interference is achieved by extrapolating the estimate of channel state information. The proposed approach allows us to reduce the influence of the interference component and, as a result, to improve the probability of correct demodulation in the ISAC RP-OTFS system. Various DD grid configurations for different use cases from a radar point of view are considered in the article. The questions of choosing appropriate values of the DD grid parameters depending on the operating environment are also discussed here. In simulations, the ICI-reduced RP-OTFS is compared with its predecessor, the regular RP-OTFS, and classical modulations: OFDM and zero-padded OTFS, and benefits of its usage are shown: lower bit error rate (BER) of the transmission and higher detection probability of the radar detection. Full article