Search Results (1,980)

In the presented research, aluminum-doped zinc oxide (AZO) thin films were synthesized on high-power transmission lines using the RF magnetron sputtering process. The impact of deposition power (160 W to 280 W) and deposition pressure (2 Pa to 5 Pa), on key characteristics like material composition, wettability, anti-icing behavior, and average crystal size were analyzed. The optimization of wettability and anti-icing performance was carried out using two-factor, four-level design of the Taguchi method to study the combined effects of multiple parameters rather than the effect of a single parameter. Considerable variation in the water contact angle, from 92.3° to 123.6°, has been observed, suggesting an enhancement in hydrophobic nature with optimized condition. Anti-icing tests demonstrated that the coated surface delayed ice accumulation by approximately 4.56 times compared to the uncoated surface. X-ray diffraction (XRD) analysis was carried out to confirm notable changes in the intensity of the (002) peak along the c-axis, directly correlating with grain size modification. The change in surface roughness was studied using AFM and the results were compared to establish a relationship between surface roughness and average grain size. Overall, the findings highlight the critical role of deposition parameters and their interactions in modifying the surface and structural properties of AZO thin films, which demonstrates their potential application for improving the anti-icing performance of transmission lines. Full article

With the rapid development of unmanned surface vessels (USVs), a vector thruster was designed in this paper to meet their evolving operational demands. The anti-impact capability of the vector thruster, in which the universal joint plays a critical role in attenuating impact loads, directly governs the stability and security of power transmission in USVs. A mechanical model of the vector thruster with a universal joint was established, incorporating length and stiffness ratio coefficients to characterize its key dynamics. Based on this model, numerical simulation using the Newmark method was conducted to systematically evaluate the thruster’s mechanical characteristics, particularly the dynamic variation of the inclination angle, under various working conditions and impact loads. The results indicate that an increase in stiffness ratio amplifies the angular displacement amplitude of the driven shaft but shortens the vibration stabilization time. During the operation of the vector thruster, an increase in the inclination angle leads to greater vibration amplitude. Furthermore, systems with a higher, longer ratio exhibit a more pronounced tendency for amplitude growth as the inclination angle increases. Finally, the theoretical model was validated through a test bench, and the variation pattern of dynamic thrust under impact load was revealed. These results emphasize that the stiffness and dimensional parameters must be carefully considered in the design and control optimization of vector thrusters to ensure reliable performance under demanding operational conditions. Full article

Johne’s disease (JD) is a chronic infection of cattle that undermines herd productivity and profitability. While test-and-cull programs are commonly proposed for control, their effectiveness and economic feasibility remain uncertain in beef production systems. This study used an updated agent-based model (ABM) to simulate JD transmission in a representative 300-cow Western Canadian beef herd, coupled with a partial budget model to evaluate net present value (NPV) over a 10-year time horizon. Seven diagnostic test-and-cull strategies were compared, varying in test type (ELISA, individual PCR, and pooled PCR), sampling frequency (6, 12, or 24 mo), and risk-based sampling protocols. Results showed that, under baseline assumptions (6% starting prevalence; 1% prevalence in purchased stock), all strategies reduced JD prevalence relative to no testing, and six of seven yielded higher NPVs. Annual individual PCR testing provided the best balance between prevalence reduction and profitability, whereas semi-annual PCR most effectively reduced prevalence but at greater economic cost. Failure to implement control measures resulted in increasing prevalence and long-term economic losses. Sensitivity analyses demonstrated that strategy performance was consistent across variations in market conditions, cost of production, and replacement female management, although profitability declined substantially when JD prevalence in externally sourced stock was high (i.e., 10%). Collectively, these findings indicate that JD can be controlled economically in beef herds, with long-term application of various test-and-cull strategies offering robust options adaptable to management preferences. Full article

The early detection of plant diseases is critical to improving agricultural productivity and ensuring food security. However, conventional centralized deep learning approaches are often unsuitable for large-scale agricultural deployments, as they rely on continuous data transmission to cloud servers and require high computational resources that are impractical for Internet of Things (IoT)-based field environments. In this article, we present a distributed deep learning framework based on Federated Learning (FL) for the diagnosis of plant diseases in IoT sensor networks. The proposed architecture integrates multiple IoT nodes and an edge computing node that collaboratively train an EfficientNet B0 model using the Federated Averaging (FedAvg) algorithm without transferring local data. Two training pipelines are evaluated: a standard single-model pipeline and a hierarchical pipeline that combines a crop classifier with crop-specific disease models. Experimental results on a multicrop leaf image dataset under realistic augmentation scenarios demonstrate that the hierarchical FL approach improves per-crop classification accuracy and robustness to environmental variations, while the standard pipeline offers lower latency and energy consumption. Full article

Bioaerosols are a major source of airborne microbial contamination in intensive poultry production systems. Their concentration and community structure can profoundly influence animal health, public health, and the overall safety of the farming environment. However, the dynamic characteristics of bacterial aerosols in enclosed poultry houses during winter remain insufficiently studied. Using Taihang chickens as a model, this study investigated three key production stages—brooding (15 days), growing (60 days), and laying (150 days)—under winter cage-rearing conditions. A six-stage Andersen sampler was employed alongside culture-dependent enumeration and 16S rRNA high-throughput sequencing to analyze variations in bacterial aerosol concentration, particle size distribution, and community succession patterns. The results revealed a significant increase in the concentration of culturable airborne bacteria with bird age, rising from 8.98 × 10³ colony-forming unit (CFU)/m³ to 2.89 × 10⁴ CFU/m³ (p < 0.001). The particle size distribution progressively shifted from larger, settleable particles (≥4.7 μm) toward smaller, respirable particles (<4.7 μm). Microbial sequencing indicated a continuous increase in bacterial alpha diversity across the three stages (Chao1 and Shannon indices, p < 0.05), while beta diversity exhibited stage-specific clustering, reflecting clear differences in community assembly. The composition of dominant bacterial genera transitioned from potentially pathogenic taxa such as Acinetobacter and Corynebacterium during the brooding stage to a greater abundance of beneficial genera, including Bacteroides, Lactobacillus, and Ruminococcus, in later stages. This shift suggests a potential ecological link between aerosolized bacterial communities and host development, possibly related to the aerosolization of gut microbiota. Notably, several zoonotic bacterial species were detected in the poultry house air, indicating potential public health and occupational exposure risks under winter confinement conditions. This study is the first to elucidate the ecological succession patterns of airborne bacterial aerosols in Taihang chicken houses across different growth stages during winter. The findings provide a scientific basis for optimizing winter ventilation strategies, implementing stage-specific environmental controls, and reducing pathogen transmission and occupational hazards. Full article

Existing salient object detection methods for optical remote sensing images still face certain limitations due to complex background variations, significant scale discrepancies among targets, severe background interference, and diverse topological structures. On the one hand, the feature transmission process often neglects the constraints and complementary effects of high-level features on low-level features, leading to insufficient feature interaction and weakened model representation. On the other hand, decoder architectures generally rely on simple cascaded structures, which fail to adequately exploit and utilize contextual information. To address these challenges, this study proposes a Hierarchical Semantic Interaction Module to enhance salient object detection performance in optical remote sensing scenarios. The module introduces foreground content modeling and a hierarchical semantic interaction mechanism within a multi-scale feature space, reinforcing the synergy and complementarity among features at different levels. This effectively highlights multi-scale and multi-type salient regions in complex backgrounds. Extensive experiments on multiple optical remote sensing datasets demonstrate the effectiveness of the proposed method. Specifically, on the EORSSD dataset, our full model integrating both CA and PA modules improves the max F-measure from 0.8826 to 0.9100 (↑2.74%), increases maxE from 0.9603 to 0.9727 (↑1.24%), and enhances the S-measure from 0.9026 to 0.9295 (↑2.69%) compared with the baseline. These results clearly demonstrate the effectiveness of the proposed modules and verify the robustness and strong generalization capability of our method in complex remote sensing scenarios. Full article

This study investigates underwater acoustic propagation patterns under mesoscale eddy conditions through numerical modeling and parametric analysis. A mathematical model of mesoscale eddies was developed, and acoustic transmission loss was computed using the BELLHOP ray-tracing model. Systematic simulations were conducted to examine the effects of source depth, eddy polarity (cold/warm), eddy intensity, and seabed topography. The results reveal distinct acoustic behaviors: cold-core eddies shift convergence zones forward, reduce their width, elevate their depth, and enhance convergence gain within certain ranges. In contrast, warm-core eddies displace convergence zones backward, broaden their width, and can induce surface duct formation. Furthermore, seabed topography exerts minimal influence on acoustic propagation under cold-core eddies but significantly modulates propagation under warm-core eddies, with different topographies producing markedly distinct effects. These findings provide valuable insights for marine scientific research and engineering applications leveraging mesoscale eddy phenomena. Full article

Conventional thresholding methods for rotorcraft Health and Usage Monitoring Systems (HUMS) often neglect flight-condition variability, resulting in frequent false alarms. To address this, a flight-state-driven threshold optimization framework that explicitly incorporates flight parameters and operational context is proposed. The proposed method combines proactive spike filtering with Principal Component Analysis (PCA) of flight parameters to distinguish flight-state-driven Condition Indicator (CI) variations from spike-like artifacts, and then re-estimates thresholds from the filtered CI distribution. The framework is evaluated using HUMS data collected from in-service rotorcraft, focusing on vibration- and fatigue-sensitive transmission components. Quantitative results show that the framework significantly reduces the Background Alarm Rate (BAR) to approximately 0.030 compared to the baseline of 0.202, while maintaining a high In-window Alarm Concentration (IAC) comparable to conventional methods. These validation results using real fault cases confirm the practical applicability of the approach to operational rotorcraft environments, indicating that the framework effectively reduces unnecessary alarms and enhances the stability and reliability of fault detection compared with conventional methods. The proposed framework offers an explainable, consistent, and operationally grounded basis for periodic threshold reviews in HUMS. It complements existing practices in Condition-Based Maintenance (CBM), providing a practical pathway to enhance confidence in vibration-based diagnostics under diverse flight conditions. Full article

In recent years, the scientific community has increasingly focused on state-of-the-art techniques, such as MIMO and mmWave transmission, aimed at enhancing the performance of telecommunication channels both quantitatively and qualitatively through various approaches. These efforts often rely on channel models designed to more accurately represent real-world conditions, thereby ensuring that the results are objective and practically applicable. In the present study, we employ one of the most scientifically reliable system- level simulators, Vienna SLS Simulator, to evaluate the performance of a wireless channel that we configure based on the latest standards (3GPP TR 36.873). We take into account the well-known non-symmetrical behavior of mMIMOs, where m stands for microwave MIMOs, in wireless communication systems and analyze the resulting changes in key performance metrics including average cell throughput, average user spectral efficiency and signal-to-interference-plus-noise ratio (SINR). We vary specific parameters such as transmission power, antenna polarization, ratio of indoor to outdoor users, and others with the aim of validating or challenging existing scientific assumptions. Particular attention is given to studying how variations in the aforementioned factors affect channel geometry and spatial uniformity, emphasizing the role of antenna geometry, polarization and user distribution in shaping channel asymmetries in mmWave MU-MIMO systems. Overall, this study provides insights into designing more balanced and efficient wireless systems in realistic urban environments. Full article

Based on existing models, this paper incorporates some key ecological factors, thereby obtaining a class of eco-epidemiological models that can more objectively reflect natural phenomena. This model simultaneously integrates disease dynamics within the prey population and the Beddington–DeAngelis functional response, thus achieving an organic combination of ecological dynamics, epidemic transmission, and spatial movement under time-varying environmental conditions. The proposed framework significantly enhances ecological realism by simultaneously accounting for spatial dispersal, predator–prey interactions, disease transmission within prey species, and seasonal or temporal variations, providing a comprehensive mathematical tool for analyzing complex eco-epidemiological systems. The theoretical results obtained from this study can be summarized as follows: Firstly, the existence and uniqueness of globally positive solutions for any positive initial data are rigorously established, ensuring the well-posedness and biological feasibility of the model over extended temporal scales. Secondly, analytically tractable sufficient conditions for uniform population persistence are derived, which elucidate the mechanisms of species coexistence and biodiversity preservation even under sustained epidemiological pressure. Thirdly, by employing innovative applications of differential inequalities and fixed point theory, the existence and uniqueness of a positive spatially homogeneous periodic solution in the presence of time-periodic coefficients are conclusively demonstrated, capturing essential rhythmicities inherent in natural systems. Fourthly, through a sophisticated combination of the upper and lower solution method for parabolic partial differential equations and Lyapunov stability theory, the global asymptotic stability of this periodic solution is rigorously established, offering a powerful analytical guarantee for long-term predictive modeling. Beyond theoretical contributions, these research findings provide actionable insights and quantitative analytical tools to tackle pressing ecological and public health challenges. They facilitate the prediction of thresholds for maintaining ecosystem stability using real-world data, enable the analysis and assessment of disease persistence in spatially structured environments, and offer robust theoretical support for the planning and design of wildlife management and conservation strategies. The derived criteria support evidence-based decision-making in areas such as controlling zoonotic disease outbreaks, maintaining ecosystem stability, and mitigating anthropogenic impacts on ecological communities. A representative numerical case study has been integrated into the analysis to verify all of the theoretical findings. In doing so, it effectively highlights the model’s substantial theoretical value in informing policy-making and advancing sustainable ecosystem management practices. Full article

This paper presents a 3-bit transmissive intelligent surface (TIS) using a novel technique that employs a unit cell comprising loaded semi-loop dipole resonators. The two resonators are anti-symmetrically oriented along the H-plane, functioning as transmitter and receiver on opposite sides of the TIS. The unit cell, with 13.2 mm periodicity, achieves 360° phase variation in 45° steps while maintaining insertion loss below 2 dB at 10 GHz. A 17 × 17 array TIS is designed using ray tracing and phase shift compensation techniques, with phase profiles distributed across eight discrete varactor states. The implemented TIS demonstrates a 10.8 dB gain enhancement for a horn antenna source at 10 GHz while preserving antenna matching, polarization, and radiation efficiency. The design achieves beam steering capabilities up to 60° with ±2° precision across elevation, azimuth, and inclined angles, maintaining an average steering gain loss of 3 dB over a 400 MHz bandwidth. These characteristics make the proposed design particularly effective for modern wireless coverage extension and tracking applications. Full article

The global shift to digital terrestrial television broadcasting (DTTB) from the conventional analogue has significantly transformed television culture, necessitating comprehensive technical and infrastructural evaluations. This study addresses the limitations of existing path-loss models for accurately predicting path loss in digital terrestrial television broadcasting in the UHF bands, motivated by the need for reliable, location-specific models that account for seasonal, meteorological, and topographical variations in Abeokuta, Nigeria. The study focuses on path-loss prediction in the UHF band using Ogun State Television (OGTV), Abeokuta, Nigeria, as the transmission source. Eight receiving sites, spaced 2 kilometers apart, were selected along a 16.7 km transmission contour. Daily measurements of received signal strength (RSS) and weather conditions were collected over one year. Seasonal path-loss models ${PL}_{wet}$ for the wet season and ${PL}_{dry}$. For the dry season, models were developed using multiple regression analysis and further optimized using least squares (LS) and gradient descent (GD) techniques, resulting in six refined models: ${PL}_{wet}$, ${PL}_{dry}$, ${PL}_{wet-LS}$, ${PL}_{dry-LS}$, ${PL}_{wet-GD}$, and ${PL}_{dry-GD}$. Model performance was evaluated using Mean Absolute Error, Root Mean Square Error, Coefficient of Correlation, and Coefficient of Multiple Determination. Results indicate that the Okumura model provided the closest approximation to measured RSS for all the receiving sites, while the Hata and COST-231 models were unsuitable. Among the developed models, ${PL}_{wet}$ ($RMSE- 1.2633$, $MAE - 0.9968$, $MSE - 1.5959$, $R - 0.9935$, $R^2 - 0.9871$) and ${PL}_{dry-LS}$($RMSE- 1.1884$, $MAE - 0.7692$, $MSE - 1.4124$, $R - 0.9942$, $R^2 - 0.9883$) were found to be the most suitable models for the wet and dry seasons, respectively. The major influence of location-based elevation and meteorological data on path-loss prediction over digital terrestrial television broadcasting communication lines in Ultra-High-Frequency bands was evident. Full article

This paper presents a voltage controller for an alternating current microgrid, where the nonlinear optimization problem of voltage regulation is transformed into a linear one by employing a linear predictor based on an online extended dynamic mode decomposition algorithm. This approach enables an online finite-dimensional representation of the Koopman operator. The voltage regulator operates online by updating the state matrix with past and current measurements. The system dynamics are updated in real time using the most recent data pair, with a regularization term included to prevent ill-posedness. Furthermore, this paper proposes an online data-driven control scheme for voltage regulation in a microgrid, which leverages model predictive control to handle transmission line faults and load variations, while ensuring conditions for convergence and stability. The main results are validated by simulation in a 14-node IEEE testbed microgrid. Full article

The efficient conversion of free fatty acids (FFAs) to fatty acid methyl esters via esterification is a crucial step in biodiesel production from low-cost high-FFA feedstocks, which supports global efforts toward renewable energy and reduced dependence on fossil fuels. However, this esterification process is hindered by slow reaction kinetics, high energy demand, and low catalyst efficiencies. This study investigates tungsten disulfide (WS₂) as a heterogeneous catalyst for the esterification of a mixture of oleic and linoleic acids with methanol under ultrasonic activation, aiming to improve catalytic performance, reaction efficiency, and enhance process sustainability. Four commercial WS₂ powders from various suppliers, varying in particle size (2 μm and 90 nm), were characterized using X-ray diffraction, scanning electron microscopy, and transmission electron microscopy. Micron-sized WS₂ exhibited higher catalytic activity than nano-scaled WS₂ due to a higher density of edge defects and abundance of catalytically active edge sites. Variation in reaction parameters demonstrated that the ester yield increases from 7% to 53% as the catalyst loading rises from 2% to 32% and reaches a 95% yield at an FFAs-to-methanol molar ratio of 1:15 under ultrasonic activation at 75 °C for 1 h. Comparative experiments confirmed that ultrasound treatment increases the yield of esterification compared to thermal activation. The results suggest WS₂ as a heterogeneous catalyst appropriate for efficient sonochemical esterification in biodiesel production. These kinetic and catalytic data are valuable for future process design, scalability assessments, and techno-economic evaluations of sustainable biodiesel production. Full article

Molten salt, as a phase change heat storage material, can be used to mitigate the volatility of clean energy. Increasing the specific heat of molten salts can help to increase heat storage density and reduce costs. In this study, nanoparticles with different potentials were prepared and doped into Solar Salt (NaNO₃-KNO₃). The modification results of the nanoparticles were evaluated by transmission electron microscopy, energy dispersive X-ray spectroscopy and infrared spectroscopy, and the modification process was analyzed by density functional theory. The specific heat, thermal diffusion coefficient, melting point, latent heat of the composites and their variation mechanism were analyzed using synchronized thermal analyzer, laser flash analyzer and scanning electron microscope. It was found that acidification was able to modify the SiO₂ nanoparticles and that the higher the acidity, the more the negative charge of the nanoparticles was neutralised. A 25.8% decrease in zeta potential to −23.17 mV was observed for the nano-SiO₂ after treatment with HCl at pH 1, compared to the non-acidified sample. The microelectric field generated by the charged nanoparticles affects the thermophysical properties such as the specific heat of the molten salt-nanoparticle composites, with one of the samples having the largest specific heat (1.79 J/(g·K)) and thermal diffusion coefficient (0.94 mm²/s), which were increased by 13.3% and 14.6%, respectively, compared to the Solar Salt. This study attributes the alterations in thermophysical properties to the variation in ion separation distance induced by the charge on nanoparticles. Full article