Search Results (843)

The maritime sector’s transition to sustainable energy is critical for achieving global carbon neutrality, with container terminals representing a key focus due to their high energy consumption and emissions. This study explores the potential of hydrogen energy as a decarbonization solution for port operations, using the Chuanshan Port Area of Ningbo Zhoushan Port (CPANZP) as a case study. Through a comprehensive analysis of hydrogen production, storage, refueling, and consumption technologies, we demonstrate the feasibility and benefits of integrating hydrogen systems into port infrastructure. Our findings highlight the successful deployment of a hybrid “wind-solar-hydrogen-storage” energy system at CPANZP, which achieves 49.67% renewable energy contribution and an annual reduction of 22,000 tons in carbon emissions. Key advancements include alkaline water electrolysis with 64.48% efficiency, multi-tier hydrogen storage systems, and fuel cell applications for vehicles and power generation. Despite these achievements, challenges such as high production costs, infrastructure scalability, and data integration gaps persist. The study underscores the importance of policy support, technological innovation, and international collaboration to overcome these barriers and accelerate the adoption of hydrogen energy in ports worldwide. This research provides actionable insights for port operators and policymakers aiming to balance operational efficiency with sustainability goals. 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

Precipitation, as a key input in the water cycle, directly influences the formation and change process of runoff. Meanwhile, the return runoff intuitively reflects the available quantity of water resources in a river basin. An in-depth analysis of the evolution laws and response relationships between precipitation and return runoff over a long time scale serves as an important support for exploring the evolution of hydrometeorological conditions and provides an accurate basis for the scientific planning and management of water resources. Taking Lanzhou Station on the upper Yellow River as a typical case, this study proposes the VSSL (LSTM Fusion Method Optimized by SSA with VMD Decomposition) deep learning precipitation element series extension method and the SSVR (SVR Fusion Method Optimized by SSA) machine learning runoff element series extension method. These methods achieve a reasonable extension of the missing data and construct 100-year precipitation and return runoff series from 1921 to 2020. The research results showed that the performance of machine learning and deep learning methods in the precipitation and return runoff test sets is better than that of traditional statistical methods, and the fitting effect of return runoff is better than that of precipitation. The 100-year precipitation and return runoff series of Lanzhou Station from 1921 to 2020 show a non-significant upward trend at a rate of 0.26 mm/a and 0.42 × 10⁸ m³/a, respectively. There is no significant mutation point in precipitation, while the mutation point of return runoff occurred in 1991. The 100-year precipitation series of Lanzhou Station has four time-scale alternations of dry and wet periods, with main periods of 60 years, 20 years, 12 years, and 6 years, respectively. The 100-year return runoff series has three time-scale alternations of dry and wet periods, with main periods of 60 years, 34 years, and 26 years, respectively. During the period from 1940 to 2000, an approximately 50-year cycle, precipitation and runoff not only have strong common-change energy and significant interaction, but also have a fixed phase difference. Precipitation changes precede runoff, and runoff responds after a fixed time interval. Full article

Pore defects are one of the most common defects in the aluminum alloy electron beam welding process. In this paper, research on the pore defects and related mechanisms of the electron beam welding of dissimilar aluminum alloys was carried out with 1060 and 2A12 aluminum alloys. Under the test conditions, the pore defects of the aluminum alloy joint were related to the penetration status, the porosity of the critically penetrated joint was low, and the porosity of the beam joint increased when it was slightly penetrated. When the welding speed changed from 300 mm/min to 1200 mm/min, the porosity in the critically penetrated joint first increased and then decreased. When the welding speed was set to 300 mm/min and the beam current was set to 26 mA, the porosity of the joints reached its minimum value at 0.23%. Based on the actual process of electron beam welding, a flow simulation model was established to study the aluminum alloy welding process. The stability of the keyhole was related to the electron beam energy density reaching the inner keyhole, so increasing the electron beam for the fully penetrated joints was advantageous for reducing the pore defects. Full article

This research proposes optimizing the thermal pattern in the sintering bed by manipulating the air supply. The impact of the air supply on the distribution of heat in the upper and lower layers of the material bed is investigated based on a numerical simulation model. An optimized air supply scheme is proposed to enhance the thermal distribution of the sintering bed. The simulation results suggest that decreasing the air supply during sintering in the upper layer leads to an increase in bed temperature and an extension of the melting zone thickness from 5 mm to 16 mm. Similarly, reducing the air supply during sintering of the lower layer prevents over-melting of the sintering material by reducing heat accumulation. However, both decrease the speed of vertical sintering. To optimize the sintering process, it is suggested to decrease the air supply during the early and late stages and increase it during the middle stage. This optimized air supply leads to a uniform temperature distribution, with a 30 °C decrease in the gap between the highest temperatures. Additionally, the melting zone thickness in the early sintering stage increases from 0 mm to 14 mm, and the average vertical sintering speed remains comparable. Full article

In order to improve the microstructure and corrosion resistance of entropy alloy in the FeCrNi system, laser melting deposition technology was used as a preparation method to study the effects of different contents of Al and Ti on the microstructure and corrosion resistance of entropy alloy in FeCrNi(AlTi)_x (x = 0.17, 0.2, and 0.24). The results show that the addition of Al and Ti elements can change the phase structure of the alloy from a single FCC phase structure to an FCC + BCC biphase structure. The BCC phase volume fraction of FeCrNi(AlTi)_0.2 is the highest among the three alloys, reaching 37.5%. With the addition of Al and Ti content, the grain of the alloy will be refined to a certain extent. In addition, the dual-phase structure will also improve the corrosion resistance of the alloy. In 3.5 wt.% NaCl solution, the increase of Al and Ti content can effectively improve the protection of the passivation film on the surface of the entropy alloy in FeCrNi(AlTi)_x, effectively inhibit the large-scale corrosion phenomenon on the alloy surface, and thus improve the corrosion resistance of the alloy. In a certain range, increasing the content of Al and Ti elements in the FeCrNi(AlTi)_x system can improve the corrosion resistance of the alloy. Full article

In order to improve the durability of loess-based composite coal gangue porous planting concrete (LCPC), the effects of fly ash and slag powder content on the durability and microstructure of LCPC were studied. In this paper, fly ash and slag powder were mixed into LCPC, and freeze-thaw cycle and dry-wet cycle tests were carried out. The compressive strength, dynamic elastic modulus, and mass change were used as evaluation indices to determine the optimal mix ratio for LCPC durability. Scanning electron microscopy (SEM) was performed, and the experimental design was carried out with the water–cement ratio, fly ash, and slag powder content as variables. The microstructure characteristics of LCPC were analyzed. The results show that the maximum number of freeze-thaw cycles can reach 35 times and the maximum number of dry-wet cycles can reach 50 when 5% fly ash and 20% slag powder are used. With an increase in the water-cement ratio, the skeleton of the loess gradually became complete, and its structure became more compact. In the micro-morphology diagram, the mixed fly ash and slag powder particles are not obvious, but with an increase in dosage, the size of the cracks and pores gradually decreases. The incorporation of fly ash and slag powder can play a positive role in the durability of LCPC and improvement of its microstructure. The results of this study are crucial for improving the application performance of ecological restoration, soil improvement, and long-term stability of structures, and can provide a scientific basis for the sustainable development of environmentally friendly building materials. Full article

(1) Background: The provision of monofunctional or inadequately distributed services in urban park green spaces often constrains residents’ opportunities and diversity for outdoor activities, particularly limiting access and participation for specific age groups or activity preferences. However, functional nodes with temporal and spatial flexibility demonstrate high-quality characteristics of resilient and shared services through integrated development. Accurately identifying user demand provides a solid basis for optimizing the functional configuration of urban parks. (2) Methods: This study took the old city area of Zhengzhou, Henan Province, China, as a case study. By collecting and integrating various types of data, such as geographic spatial data, field investigation data, and behavioral observations, we developed a population demand quantification method and a modular analysis approach for park service functions. This framework enabled correlation analysis between diverse user needs and park services. The study further classified and combined park functions into modular units, quantifying their elastic and shared service capabilities—namely, the adaptive flexibility and shared utilization capacity of park services. Additionally, we established a demand-responsive evaluation system for identifying and diagnosing problem areas in park services based on multi-source data. (3) Results: The demand response index and diagnostic results indicate that the supply of fitness facilities—particularly equipment-based installations—is insufficient within the old urban district of Zhengzhou. Among the three user groups—children, young and middle-aged adults, and the elderly—the elderly population exhibited the lowest demand response index, revealing a significant gap in meeting their specific needs. (4) Conclusions: Based on the research findings, a three-tier optimization strategy is proposed: A. improve green space connectivity to expand the service coverage of parks; B. implement multifunctional overlay and coordinated integration in spatial design based on site characteristics and demand diagnostics; and C. increase the total supply of facilities to enhance spatial efficiency in parks. By integrating the demand assessment data and diagnostic results, this approach enabled a data-driven reorganization of service types and targeted allocation of resources within existing park infrastructure, offering a practical tool and reference for the planning of urban outdoor activity spaces. Full article

Liver, the center of substance metabolism, plays a vital role in the hibernation of mammals, a topic arousing increasing interest from researchers around the world. However, it remains unclear how the liver regulates energy metabolism during the hibernation of mammals. Metabolic disorders in the liver are closely associated with numerous diseases. In this research on chipmunks (Tamias sibiricus), we compared histological changes in the liver and energy source between the conditions for hibernation and room temperature, and subsequently conducted transcriptome sequencing analysis. The results demonstrate that lipid metabolism becomes a significant energy source during hibernation via the retinol signaling pathway and PPAR signaling pathway, thereby suggesting the importance of the liver in maintaining homeostasis when facing hypothermia. Furthermore, the result provides us with a novel perspective to obtain an insight into liver metabolic reprogramming and potential therapeutic strategies for metabolic disease in the liver. Full article

Against the backdrop of the increasing penetration rate of new energy year by year, power systems face a continuously growing demand for flexibility. Under the structure of such a new power system, it is essential not only to introduce diverse flexible power sources but also to explore the flexible regulation capabilities of existing conventional power sources. To fully utilize the flexibility of thermal power units (TPUs), this study proposes a real-time optimal scheduling strategy for a wind–thermal energy-storage integrated system with an adaptive time division and variable objectives. Based on the evaluation results of the real-time flexible supply–demand relationship within a regional power grid, the operation modes of TPUs are categorized into three types: economic mode, peak shaving mode, and coordination mode. For each operation mode, corresponding optimization objectives are defined, and an energy storage control strategy is developed to assist in the peak shaving of TPUs. While effectively harnessing the flexibility of TPUs, the proposed method reduces both the frequency and capacity of TPUs entering deep peak shaving. Using data from a province in Northwest China as a case study, simulation calculations and analyses demonstrate that the proposed method increases renewable energy consumption by 314.37 MWh while decreasing system economic benefits by CNY 129,000. Compared with traditional scheduling methods for TPUs to accommodate renewable energy, the system benefit increases by CNY 297,000, and an additional 13.53 MWh of peak wind power is accommodated. These results confirm that the proposed scheduling strategy can significantly enhance the system’s ability to integrate new energy while maintaining its economic efficiency. Full article

Autoimmune CD8⁺ T cell-driven melanocyte destruction constitutes a key pathogenic mechanism in the development of vitiligo. Therefore, the pharmacological inhibition of CD8⁺ T cell effector functions and skin trafficking is a clinically viable therapeutic strategy. This study investigates leflunomide (LEF), an immunomodulatory drug with established safety in autoimmune diseases, for its therapeutic potential in a tyrosine-related protein (TRP) 2-180-induced vitiligo mouse model. Through flow cytometry, immunofluorescence, ELISA, and histopathological analyses, we systematically evaluated LEF’s effects on T cell regulation, chemokine expression, and cytokine profiles. Key findings demonstrated that LEF (20 mg/kg/day) significantly attenuated depigmentation by reducing CD8⁺ T cell infiltration and suppressing the IFN-γ-driven expression of CXCL9/10. Furthermore, LEF restored CD4⁺/CD8⁺ T cell homeostasis and rebalanced pro-inflammatory (IFN-γ, TNF-α, IL-2) and anti-inflammatory (IL-4, IL-10) cytokines, inducing a shift from Th1 to Th2. These results position LEF as an effective immunomodulator that disrupts the IFN-γ-CXCL9/10 axis and re-establishes immune balance, offering a promising repurposing strategy for halting vitiligo progression. Full article

Background/Objectives: Breast milk provides essential nutrition and immune protection to support infant growth and development. However, insufficient breast milk remains a serious issue, and bioactive peptides represent a potential strategy to promote lactation. In this study, we investigated the impact of a methionine-containing dipeptide, EM, on MCF-10A mammary epithelial cells. Methods: MCF-10A cells were treated with EM, and cell proliferation and the expression of key milk protein genes were assessed. Integrated transcriptomic and untargeted metabolomic analyses were performed to identify EM-induced changes in metabolic and gene expression pathways. Results: EM treatment significantly enhanced cell proliferation and upregulated the expression of key milk protein genes (CSN1S1 (casein alpha-S1, encoding alpha-S1 casein), CSN2 (casein beta, encoding beta-casein), and CSN3 (casein kappa, encoding kappa-casein)) at both transcriptional and protein levels compared to controls. Integrated transcriptomic and metabolomic analyses revealed that EM reprogrammed amino acid metabolism, lipid biosynthesis, and nutrient transport pathways. Core genes such as SLC7A11, APOE, and ABCA1 were identified as critical nodes linking metabolic and transcriptional networks. Conclusions: These findings indicate that EM may promote lactogenic activity by modulating metabolic and transcriptional networks in vitro, highlighting the potential of dipeptide-based nutritional interventions, which warrants further in vivo validation. Full article

Due to the limitations of the sowing machine performance and rice seed germination rates, missing seedlings inevitably occur after rice is sown in large fields. This phenomenon has a direct impact on the rice yield. In the field environment, the existing methods for detecting missing seedlings based on unmanned aerial vehicle (UAV) remote sensing images often have unsatisfactory effects. Therefore, to enable the fast and accurate detection of missing rice seedlings and facilitate subsequent reseeding, this study proposes a UAV remote-sensing-based method for detecting missing rice seedlings in large fields. The proposed method uses an improved PCERT-DETR model to detect rice seedlings and missing seedlings in UAV remote sensing images of large fields. The experimental results show that PCERT-DETR achieves an optimal performance on the self-constructed dataset, with an mean average precision (mAP) of 81.2%, precision (P) of 82.8%, recall (R) of 78.3%, and F₁-score (F₁) of 80.5%. The model’s parameter count is only 21.4 M and its FLOPs reach 66.6 G, meeting real-time detection requirements. Compared to the baseline network models, PCERT-DETR improves the P, R, F₁, and mAP by 15.0, 1.2, 8.5, and 6.8 percentage points, respectively. Furthermore, the performance evaluation experiments were carried out through ablation experiments, comparative detection model experiments and heat map visualization analysis, indicating that the model has a strong detection performance on the test set. The results confirm that the proposed model can accurately detect the number of missing rice seedlings. This study provides accurate information on the number of missing seedlings for subsequent reseeding operations, thus contributing to the improvement of precision farming practices. Full article

This paper presents a model predictive control (MPC)-enabled disturbance-rejection controller approach for a pneumatic manipulator system subjected to complex nonlinear terms within the system. To facilitate the handling of the complex nonlinear terms, they are modeled as disturbances. To address these disturbances, a receding-horizon-based extended state observer (RH-ESO) incorporating a decision variable is developed. The optimal disturbance estimation error is determined through a receding-horizon optimization procedure, which provides the best estimate of the disturbance. Using this optimal estimate, the MPC-enabled disturbance-rejection controller is proposed for the pneumatic manipulator system to achieve angle tracking control. Moreover, the proposed approach ensures both the recursive feasibility of the optimization problem and the uniform boundedness of the closed-loop system. The simulation results further demonstrate the effectiveness and validity of the proposed methodology. Full article

Recent advances in hyperspectral image (HSI) classification have demonstrated the effectiveness of hybrid architectures that integrate convolutional neural networks (CNNs) and Transformers, leveraging CNNs for local feature extraction and Transformers for global dependency modeling. However, existing fusion approaches face three critical challenges: (1) insufficient synergy between spectral and spatial feature learning due to rigid coupling mechanisms; (2) high computational complexity resulting from redundant attention calculations; and (3) limited adaptability to spectral redundancy and noise in small-sample scenarios. To address these limitations, we propose HyperTransXNet, a novel CNN-Transformer hybrid architecture that incorporates adaptive spectral-spatial fusion. Specifically, the proposed HyperTransXNet comprises three key modules: (1) a Hybrid Spatial-Spectral Module (HSSM) that captures the refined local spectral-spatial features and models global spectral correlations by combining depth-wise dynamic convolution with frequency-domain attention; (2) a Mixture-of-Experts Routing (MoE-R) module that adaptively fuses multi-scale features by dynamically selecting optimal experts via Top-K sparse weights; and (3) a Spatial-Spectral Tokens Enhancer (SSTE) module that ensures causality-preserving interactions between spectral bands and spatial contexts. Extensive experiments on the Indian Pines, Houston 2013, and WHU-Hi-LongKou datasets demonstrate the superiority of HyperTransXNet. Full article