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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

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

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

Biological extracellular vesicles in tear fluids, such as exosomes, are thought to have physiological functions in the management of healthy ocular surface epithelium, including corneal epithelium. However, the physiological roles of tear extracellular vesicles in the ocular surface remain unclear. In this study, we investigated the physiological function of tear extracellular vesicles in mouse tear fluids in the ocular surface epithelium in vitro. Morphological analysis of the isolated extracellular vesicles from mouse tear fluids was performed using nanoparticle tracking analysis and transmission electron microscopy. The identified particles were characterised by immunoblotting for exosomal markers. After confirming the uptake of tear exosomes in cultured corneal epithelial cells, gene expression changes in mouse cultured corneal epithelial cells after tear exosome treatment were analysed. Immunostaining analysis was performed to confirm cell proliferation in the cultured corneal epithelial cells with tear exosome treatment. Tear fluids from mice contain nanoparticles with exosome-like morphologies, which express the representative exosomal markers CD9 and TSG101. The extracellular vesicles can be taken up by cultivated murine corneal epithelial cells in vitro and induce expression changes in genes related to the cell cycle, cell membranes, microtubules, and signal peptides. Treatment with the tear extracellular vesicles promoted cell proliferation of cultured murine corneal epithelial cells. Our study provides evidence that murine tear fluids contain extracellular vehicles like exosomes and they may contribute to the maintenance of the physiological homeostatic environment of the ocular surface. Full article

The repeated occurrence of SARS-CoV-2 variants, largely driven by virus–host interactions, was and will remain a public health concern. Spike protein mutations shaped viral infectivity, transmissibility, and immune escape. From February 2022 to April 2024, a local genomic surveillance program in Verona, Italy, was conducted on 1333 SARS-CoV-2-positive nasopharyngeal swabs via next generation full-length genome sequencing. Spike protein mutations were classified based on their prevalence over time. Mutations were grouped into five categories: fixed, emerging, fading, transient, and divergent. Notably, some divergent mutations displayed a “Lazarus effect,” disappearing and later reappearing in new lineages, indicating potential adaptive advantages in specific genomic contexts. This two-year surveillance study highlights the dynamic nature of spike protein mutations and their role in SARS-CoV-2 evolution. The findings underscore the need for ongoing mutation-focused genomic monitoring to detect early signals of variant emergence, especially among mutations previously considered disadvantageous. Such efforts are critical for driving public health responses and guiding future vaccine and therapeutic strategies. Full article

Background: Influenza viruses are major pathogens responsible for respiratory infections and pose significant risks to densely populated urban areas. RT-qPCR has made substantial contributions in controlling virus transmission during previous COVID-19 epidemics, but it faces challenges in terms of detection time for large sample sizes and susceptibility to nucleic acid contamination. Methods: Our study designed loop-mediated isothermal amplification primers for three common influenza viruses: A/H3N2, A/H1N1, and B/Victoria, and utilized a 4-channel microfluidic chip to achieve simultaneous detection. The chip initiates amplification by centrifugation and allows testing of up to eight samples at a time. Results: By creating a closed amplification system in the microfluidic chip, aerosol-induced nucleic acid contamination can be prevented through physically isolating the reaction from the operating environment. The chip can specifically detect A/H1N1, A/H3N2, and B/Victoria and has no signal for other common respiratory viruses. The testing process can be completed within 1 h and can be sensitive to viral RNA at concentrations as low as 10⁻³ ng/μL for A/H1N1 and A/H3N2 and 10⁻¹ ng/μL for B/Victori. A total of 296 virus swab samples were further analyzed using the microfluidic chip method and compared with the classical qPCR method, which resulted in high consistency. Conclusions: Our chip enables faster detection of influenza virus and avoids nucleic acid contamination, which is beneficial for POCT establishment and has lower requirements for the operating environment. Full article

This paper proposes an intelligent power adaptation framework for Free-Space Optics (FSO) communication systems operating under different weather conditions exploiting a deep learning (DL) analysis of received eye diagram images. The system incorporates two Convolutional Neural Network (CNN) architectures, LeNet and Wide Residual Network (Wide ResNet) algorithms to perform regression tasks that predict received signal quality metrics such as the Quality Factor (Q-factor) and Bit Error Rate (BER) from the received eye diagram. These models are evaluated using Mean Squared Error (MSE) and the coefficient of determination (${\mathrm{R}}^2$ score) to assess prediction accuracy. Additionally, a custom CNN-based classifier is trained to determine whether the BER reading from the eye diagram exceeds a critical threshold of ${10}^{-4}$; this classifier achieves an overall accuracy of 99%, correctly detecting 194/195 “acceptable” and 4/5 “unacceptable” instances. Based on the predicted signal quality, the framework activates a dual-amplifier configuration comprising a pre-channel amplifier with a maximum gain of 25 dB and a post-channel amplifier with a maximum gain of 10 dB. The total gain of the amplifiers is adjusted to support the operation of the FSO system under all-weather conditions. The FSO system uses a 15 dBm laser source at 1550 nm. The DL models are tested on both internal and external datasets to validate their generalization capability. The results show that the regression models achieve strong predictive performance, and the classifier reliably detects degraded signal conditions, enabling the real-time gain control of the amplifiers to achieve the quality of transmission. The proposed solution supports robust FSO communication under challenging atmospheric conditions including dry snow, making it suitable for deployment in regions like Northern Europe, Canada, and Northern Japan. Full article

The ability of the neuropeptide oxytocin to affect glial cell function is receiving increasing attention. We previously reported that oxytocin at a low nanomolar concentration could inhibit both astrocytic Ca²⁺ signals and glutamate release. Here, we investigate the ability of oxytocin receptors to couple both inhibitory and stimulatory pathways in astrocytes, as already reported in neurons. We assessed the effects of oxytocin at concentrations ranging from low to high in the nanomolar range on intracellular Ca²⁺ signals and on the glutamate release in astrocyte processes freshly prepared from the striatum of adult rats. Our main findings are as follows: oxytocin could induce dual responses in astrocyte processes, namely the inhibition and facilitation of both Ca²⁺ signals and glutamate release; the inhibitory and the facilitatory response appeared dependent on activation of the G_i and the G_q pathway, respectively; both inhibitory and facilitatory responses were evoked at the same nanomolar oxytocin concentrations; and the biased agonists atosiban and carbetocin could duplicate oxytocin’s inhibitory and facilitatory response, respectively. In conclusion, due to the coupling of striatal astrocytic oxytocin receptors to different transduction pathways and the dual effects on Ca²⁺ signals and glutamate release, oxytocin could also play a crucial role in neuron–astrocyte bi-directional communication through a subtle regulation of striatal glutamatergic synapses. Therefore, astrocytic oxytocin receptors may offer pharmacological targets to regulate glutamatergic striatal transmission, which is potentially useful in neuropsychiatric disorders and in neurodegenerative diseases. Full article

With the rapid development of information technology and semiconductor technology, the iteration speed of electronic devices has accelerated in an unprecedented manner, and the market demand for miniaturized, highly integrated, and highly intelligent devices continues to rise. But when these electronic devices operate at high power, the electronic components generate a large amount of integrated heat. Due to the limitations of existing heat dissipation channels, the current heat dissipation performance of electronic packaging materials is struggling to meet practical needs, resulting in heat accumulation and high temperatures inside the equipment, seriously affecting operational stability. For electronic devices that require high energy density and fast signal transmission, improving the heat dissipation capability of electronic packaging materials can significantly enhance their application prospects. In order to improve the thermal conductivity of composite materials, hexagonal boron nitride (h-BN) was selected as the thermal filling material in this paper. The BMI resin was structurally modified through molecular structure design. The results showed that the micro-branched structure and h-BN synergistically improved the thermal conductivity and insulation performance of the composite material, with a thermal conductivity coefficient of 1.51 W/(m·K) and a significant improvement in insulation performance. The core mechanism is the optimization of the dispersion state of h-BN filler in the matrix resin through the free volume in the micro-branched structure, which improves the thermal conductivity of the composite material while maintaining high insulation. Full article

This paper presents the design, implementation, and experimental validation of a Condition Monitoring (CM) circuit for SiC-based Power Electronics Converters (PECs). The paper leverages in situ drain–source resistance (R_ds,on) measurements, interfaced with cloud connectivity for data processing and lifetime assessment, addressing key limitations in current state-of-the-art (SOTA) methods. Traditional approaches rely on expensive data acquisition systems under controlled laboratory conditions, making them unsuitable for real-world applications due to component variability, time delay, and noise sensitivity. Furthermore, these methods lack cloud interfacing for real-time data analysis and fail to provide comprehensive reliability metrics such as Remaining Useful Life (RUL). Additionally, the proposed CM method benefits from noise mitigation during switching transitions by utilizing delay circuits to ensure stable and accurate data capture. Moreover, collected data are transmitted to the cloud for long-term health assessment and damage evaluation. In this paper, experimental validation follows a structured design involving signal acquisition, filtering, cloud transmission, and temperature and thermal degradation tracking. Experimental testing has been conducted at different temperatures and operating conditions, considering coolant temperature variations (40 °C to 80 °C), and an output power of 7 kW. Results have demonstrated a clear correlation between temperature rise and R_ds,on variations, validating the ability of the proposed method to predict device degradation. Finally, by leveraging cloud computing, this work provides a practical solution for real-world Wide Band Gap (WBG)-based PEC reliability and lifetime assessment. Full article

Ion-conductive-hydrogel strain sensors demonstrate broad application prospects in the fields of flexible sensing and bioelectric signal monitoring due to their excellent skin conformability and efficient signal transmission characteristics. However, traditional preparation methods face significant challenges in enhancing adhesion strength, conductivity, and mechanical stability. To address this issue, this study employed a freeze–thaw cycling method, using polyvinyl alcohol (PVA) as the matrix material, tannic acid (TA) as the adhesion reinforcement material, and lithium chloride (LiCl) as the conductive medium, successfully developing an ion-conductive hydrogel with superior comprehensive performance. Experimental data confirm that the PVA-TA-0.5/LiCl-1 hydrogel achieves optimal levels of adhesion strength (2.32 kPa on pigskin) and conductivity (0.64 S/m), while also exhibiting good tensile strength (0.1 MPa). Therefore, this hydrogel shows great potential for use in strain sensors, demonstrating excellent sensitivity (GF = 1.15), reliable operational stability, as the ΔR/R₀ signal remains virtually unchanged after 2500 cycles of stretching, and outstanding strain sensing and electromyographic signal acquisition capabilities, fully highlighting its practical value in the fields of flexible sensing and bioelectric monitoring. Full article

The endoscopic capsule is a miniaturized device used for medical diagnosis, which is less invasive compared to traditional gastrointestinal endoscopy and can reduce patient discomfort. However, it faces challenges in communication transmission, such as high power consumption, serious signal interference, and low data transmission rate. To address these issues, this paper proposes an optimized modulation scheme that is low-cost, low-power, and robust in harsh environments, aiming to improve its transmission rate. The scheme is analyzed in terms of the in-body channel. The analysis and discussion for the scheme in wireless body area networks (WBANs) are divided into three aspects: bit error rate (BER) performance, energy efficiency (EE), and spectrum efficiency (SE), and complexity. These correspond to the following issues: transmission rate, communication quality, and low power consumption. The results demonstrate that the optimized scheme is more suitable for improving the communication performance of endoscopic capsules. Full article

To investigate the influence of different water quality conditions on the underwater transmission performance of laser communication signals, this paper systematically analyzes the absorption and scattering characteristics of the underwater laser communication channel, and constructs a transmission model of laser propagation in water, so as to explore the transmission influence mechanism under typical water quality environments. On this basis, a system of in situ measurements for underwater laser channel attenuation is designed and constructed, and several sets of experiments are carried out to verify the rationality and applicability of the model. The collected experimental data are denoised by the fusion of wavelet analysis and adaptive Kalman filtering (DWT-AKF in short) algorithm, and compared with the data measured by an underwater hyperspectral Absorption Coefficient Spectrophotometer (ACS in short), which shows that the channel attenuation coefficients of the model inversion and the measured values are in high agreement. The research results provide a reliable theoretical basis and experimental support for the performance optimization and engineering design of the underwater laser communication system. Full article

Satellite communications are pivotal to global Internet access, connectivity, and the advancement of information warfare. Despite these importance, the open nature of satellite channels makes them vulnerable to eavesdropping, making the enhancement of interception resistance in satellite communications a critical issue in both academic and industrial circles. Within the realm of satellite communications, polarization modulation and quadrature techniques are essential for information transmission and interference suppression. To boost electromagnetic countermeasures in complex battlefield scenarios, this paper integrates multi-parameter weighted-type fractional Fourier transform (MP-WFRFT) with directional modulation (DM) algorithms, building upon polarization techniques. Initially, the operational mechanisms of the polarization-amplitude-phase modulation (PAPM), MP-WFRFT, and DM algorithms are elucidated. Secondly, it introduces a novel variable polarization-amplitude-phase modulation (VPAPM) scheme that integrates variable polarization with amplitude-phase modulation. Subsequently, leveraging the VPAPM modulation scheme, an exploration of the anti-interception capabilities of MP-WFRFT through parameter adjustment is presented. Rooted in an in-depth analysis of simulation data, the anti-scanning capabilities of MP-WFRFT are assessed in terms of scale vectors in the horizontal and vertical direction. Finally, exploiting the potential of the robust anti-scanning capabilities of MP-WFRFT and the directional property of antenna arrays in DM, the paper proposes a secure transmission technique employing directional variable polarization modulation with MP-WFRFT. The performance simulation analysis demonstrates that the integration of MP-WFRFT and DM significantly outperforms individual secure transmission methods, improving anti-interception performance by at least an order of magnitude at signal-to-noise ratios above 10 dB. Consequently, this approach exhibits considerable potential and engineering significance for its application within satellite communication systems. Full article

This paper proposes a pseudo full-channel signal integrity (SI) simulation method tailored for high-bandwidth memory (HBM) interconnects. In this approach, real interconnect models are applied to selected portions of the channel, while the remaining sections are replaced with synchronized current loads that emulate the electrical behavior of actual signal transmission. This technique enables accurate modeling of the HBM interface under full-channel parallel data transfer conditions. In addition to the simulation methodology itself, this study focuses on three specific implementation schemes for the synchronized current loads and explores their practical applications. Comparative analysis demonstrates the necessity and effectiveness of using synchronized current loads as substitutes for real transmission loads, offering a viable and efficient solution for SI analysis in HBM interconnect systems. Full article