Search Results (365)

Matched-field processing localizes underwater acoustic targets by measuring the degree of correlation between the acoustic field and replica fields. The intrusion of mesoscale eddies can induce sound speed mismatch in the matched-field process. Therefore, it is essential to investigate the impact of mesoscale eddies on matched-field localization errors. In this study, the typical vertical structure of mesoscale eddies in a certain region of the Northwestern Pacific was synthesized using the mesoscale eddy dataset META 2.0 and Argo float data. Furthermore, by employing both an idealized eddy model and composite-analysis structure of eddy, the performance of the localization algorithm was evaluated under the influence of mesoscale eddies with different structures and in different regions. The results show that under specific conditions, the distribution of localization errors exhibits certain patterns, which is beneficial for inverting eddy parameters via matched-field processing. Finally, the mechanism behind the systematic distribution of localization errors is discussed and analyzed. In the simulations, the source frequency was swept from 50 to 75 Hz with a 1 Hz step, and a circular array was employed as the receiving aperture. These findings indicate that, in the absence of small-scale interference and within a certain range of sound speed mismatch, the localization error of underwater acoustic targets increases with the strengthening of mesoscale eddy disturbances. Full article

The dynamic evolution of dissolved oxygen (DO) concentration is critical for aquatic ecosystem stability and biodiversity, serving as an important water quality indicator. Predicting DO distribution is challenging due to complex hydrodynamic conditions and environmental disturbances. While traditional experimental methods provide accurate short-term data, they are limited in spatial coverage, costly, and lack real-time predictive capabilities. Computational fluid dynamics (CFD) simulations, though beneficial for mechanism modeling, suffer from high computational costs and reduced accuracy in long-term, nonlinear predictions. This study addresses these limitations by developing an LSTM-GRU Hybrid Model for predicting DO concentration in Shenzhen Bay. Combining Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU), the model enhances time-memory capabilities and parameter efficiency. Results show that the LSTM-GRU Hybrid Model outperforms single neural networks with a correlation coefficient close to 0.99 and RMSE below 0.04 gO₂/m³. This study not only introduces a novel methodology for modeling dissolved oxygen in Shenzhen Bay, but also contributes to advancing predictive capabilities in earth systems environment and offers methodological insights applicable to similar semi-enclosed marine environments. Full article

Numerous industries have begun using cloud computing. Among other things, this presents a plethora of novel security and dependability concerns. Thoroughly verifying cloud solutions to guarantee their correctness is beneficial, just like with any other computer system that is security- and correctness-sensitive. While there has been much research on distributed system validation and verification, nobody has looked at whether verification methods used for distributed systems can be directly applied to cloud computing. To prove that cloud computing necessitates a unique verification model/architecture, this research compares and contrasts the verification needs of distributed and cloud computing. Distinct commercial, architectural, programming, and security models necessitate distinct approaches to verification in cloud and distributed systems. The importance of cloud-based Service Level Agreements (SLAs) in testing is growing. In order to ensure service integrity, users must upload their selected services and registered services to the cloud. Not only does the user fail to update the data when they should, but external issues, such as the cloud service provider’s data becoming corrupted, lost, or destroyed, also contribute to the data not becoming updated quickly enough. The data saved by the user on the cloud server must be complete and undamaged for integrity checking to be effective. Damaged data can be recovered if incomplete data is discovered after verification. A shared resource pool with network access and elastic extension is realized by optimizing resource allocation, which provides computer resources to consumers as services. The development and implementation of the cloud platform would be greatly facilitated by a verification mechanism that checks the data integrity in the cloud. This mechanism should be independent of storage services and compatible with the current basic service architecture. The user can easily see any discrepancies in the necessary data. While cloud storage does make data outsourcing easier, the security and integrity of the outsourced data are often at risk when using an untrusted cloud server. Consequently, there is a critical need to develop security measures that enable users to verify data integrity while maintaining reasonable computational and transmission overheads. A cryptography-based public data integrity verification technique is proposed in this research. In addition to protecting users’ data from harmful attacks like replay, replacement, and forgery, this approach enables third-party authorities to stand in for users while checking the integrity of outsourced data. This research proposes a Cloud Integrity Verification and Validation Model using the Double Token Key Distribution (CIVV-DTKD) model for enhancing cloud quality of service levels. The proposed model, when compared with the traditional methods, performs better in verification and validation accuracy levels. Full article

To fabricate thermoelectric generators (TEGs) with high mechanical strength using single-walled carbon nanotubes (SWCNTs), we combined SWCNTs, poly(3, 4-ethylenedioxythiophene):poly(4-styrenesulfonate) (PEDOT:PSS), and sodium alginate (SA) to synthesize flexible SWCNT/PEDOT:PSS/SA composite yarns via wet spinning. The composite yarns were flexible and dense, with a diameter of approximately 290 µm. Their tensile strength and breaking strain were 151 MPa and 12.7%, respectively, which were approximately 10 and 4 times those of the SWCNT films. However, the thermoelectric properties of the composite yarns were inferior to those of the SWCNT films. The temperature distribution and output voltage of the fabricated TEG with composite yarns were measured at a heater temperature of 100 °C. The temperature difference generated by the TEG with composite yarns was approximately 75% of that generated by the TEG with SWCNT films because the composite yarn had a smaller specific surface area. The output voltage of the TEG with two composite yarns (0.21 mV) was lower than that of the TEG with two SWCNT films. However, arranging the composite yarns at a high density resulted in an output voltage exceeding that for the TEGs with SWCNT films. These findings are highly beneficial for yarn-based TEGs used in wearable sensors. Full article

Nowadays, most of the heavy oil fields around the world have entered difficult exploiting stages, with problems regarding high viscosity and poor fluidity. However, there has been little previous research on the accurate identification and distribution of remaining oil with different levels of steam dryness. Therefore, this paper proposes a new nuclear magnetic resonance (NMR) interpretation method, as well as a new samples analysis method for remaining oil in the core. We conducted core displacement experiments using different methods. The nuclear magnetic resonance (NMR) tests and analysis of core thin sections after steam flooding were used to study the effect of different steam dryness levels on the migration and sedimentation mechanisms of heavy oil components. The results showed that the viscosity of crude oil and the permeability of rock cores are both sensitive to steam dryness; therefore, the improvement of steam dryness is beneficial for improving oil recovery. Heavy oil is mainly distributed in the medium pores of 10–50 μm and the small pores of 1–10 μm. However, with the decrease in steam dryness, the dynamic amount of crude oil in both medium and small pores decreases, and the bitumen in crude oil stays in the pores in the form of stars, patches, and envelopes, which leads to a decline in oil displacement efficiency. Thus, our study provides a micro-level understanding of remaining oil which lays the foundation for the further enhancement of oil recovery in heavy oilfields. Full article

In view of the problems existing in the application of greenhouse pesticides in China, this paper developed a swing-arm sprayer for greenhouse high-stem crops through field research and a literature review. Static and dynamic simulations of the swing-arm mechanism were carried out to verify the rationality of the structure. The average contact angle between the water and tomato leaves was 49.39°, while the contact angle of the auxiliary solution on the tomato leaves decreased to 40.98°. An indoor atomization test platform was designed to accurately test the particle size and spray performance. The relative span (RS) of droplet distribution showed that the RS values of nozzles 015, 02, and 03 were relatively small, while the RS value of nozzle 04 was about 1.734. With the addition of additives, the RS value of nozzle 02 decreased from 1.305 to 1.021. The field tests showed that the deposition of fog droplets on the front of tomato leaves was in the order of middle > lower > ground > upper (3.622 μL/cm², 3.005 μL/cm², 2.977 μL/cm², and 2.931 μL/cm², respectively). The results indicate that adding additives or increasing the swing-arm angle is beneficial for improving the uniformity of canopy droplet deposition. The front fog droplet coverage of the lower canopy of tomatoes was the lowest, with an average of 26.00%, while the middle and upper canopies had the highest, with an average of 50.58% and 50.72%, respectively. The research found that the spray coverage rate on the front and back sides of tomato leaves was relatively uniform, indicating that the swing-arm greenhouse sprayer designed in this paper could meet the spray quality requirements for tomato pest control. Full article

The suspension arm is a crucial connecting component in the automotive powertrain system, required to withstand various working condition loads, thus necessitating high mechanical performance. With the continuous development of forming processes, the forming method of suspension arms has gradually shifted from traditional gravity casting to squeeze casting. Along with the demand for automotive lightweighting, there is an urgent need for lightweight requirements in suspension arm components. This study employs a multi-condition topology optimization method, incorporating the forming requirements of the squeeze casting process, to conduct lightweight design of a certain mounting bracket. The filling and solidification processes were numerically simulated using Anycasting, followed by mechanical property testing and microstructure analysis of the product. The results revealed that the topology-optimized suspension arm met the strength and stiffness requirements under all working conditions, with a mass reduction of approximately 54.7% compared to the pre-optimized version. Based on the forming process analysis of the suspension arm, the design of its squeeze casting mold was completed. Using AnyCasting software (AnyCasting 6.7), numerical simulations of the filling and solidification processes of the suspension arm were conducted. Combined with theoretical calculations, the forming process parameters for the suspension arm were finally determined as follows: extrusion speed of 15 cm/s-10 cm/s-5 cm/s (multi-stage speed), pouring temperature of 690 °C, mold temperature of 250 °C, extrusion pressure of 81.4 MPa, and holding time of 45 s. Through T6 heat treatment, the tensile strength, yield strength, and elongation after fracture of the suspension arm reached 326.05 MPa, 276.87 MPa, and 9.68%, respectively. Metallographic analysis showed that the eutectic silicon in the T6 heat-treated specimens was primarily spherical in shape, uniformly distributed without significant clustering. The reason for this difference may be that heat treatment affects the boundary dissolution degree of alloying elements. For eutectic Al-Si alloys, the boundary dissolution and diffusion of alloying elements are accelerated, which is beneficial for improving the mechanical properties of the alloy. Finally, in order to quantitatively analyze the microstructural properties of the material after heat treatment, analyses of secondary dendrite arm spacing and porosity were conducted, leading to the conclusion that the microstructure after heat treatment is more uniform and dense. Full article

Enargite (Cu₃AsS₄), a copper–arsenic sulfosalt, represents a critical challenge in copper mineral processing due to its high arsenic content, which poses significant environmental, metallurgical, and economic issues. Its flotation behavior closely resembles that of other copper sulfides such as chalcopyrite and chalcocite, complicating selective separation at early beneficiation stages. This review presents a comprehensive examination of enargite’s surface chemistry and electrochemical behavior, focusing on the influence of oxidation, pH, and pulp potential on surface reactivity, charge distribution (zeta potential), and hydrophobicity. Detailed insights into the formation of surface oxidation layers, passivation mechanisms, and contact angle variations are provided to elucidate collector-mineral interactions. Advances in selective flotation techniques are also discussed, including the use of depressant reagents, controlled redox environments, and reagent conditioning strategies. Special attention is given to flotation in seawater, where ionic strength and multivalent ions significantly influence mineral-reagent interactions and flotation outcomes. Galvanic interactions between enargite and other sulfide minerals are identified as critical factors affecting floatability and selectivity. The review consolidates findings from recent experimental and electrochemical studies, highlighting promising approaches to enhance enargite rejection and copper concentrate purity. It concludes with perspectives on future research aimed at optimizing flotation processes and developing sustainable solutions for processing arsenic-bearing copper ores. Full article

The design of cycloidal reducers requires a detailed knowledge of the intensity and character of load, as well as the maximum von Mises stresses on critical components. In the available literature, the load distribution and the stress–strain state of the cycloidal reducer elements are typically determined based on factors such as cycloidal disc tooth profile modifications, contact deformations, and internal clearances, whereas the influence of thermal stresses is most often neglected. To address this research gap, an innovative numerical–analytical methodology has been developed, which, for the first time, enables the prediction of the distribution of temperature fields and the quantification of the influence of temperature on the contact forces and the stress–strain state of key elements of the cycloidal reducer. Furthermore, the proposed methodology can be adapted for application within a broader context of mechanical engineering. From a practical perspective, it is expected to be beneficial to companies engaged in the design of power transmission gearboxes, as valuable practical guidelines for engineering applications are provided. This study also provides new insights into the dominant sources of heat generation and offers a clearer understanding of how thermal energy is transferred from internal heat sources to the outer surface of the housing. Full article

Food-derived carbon dots (F-CDs) are a novel class of carbon-based nanomaterials unintentionally generated during common thermal food processing techniques, such as baking, roasting, frying, and caramelization. These nanostructures exhibit unique optical and chemical properties, including photoluminescence, high aqueous solubility, and tunable surface functionality, making them increasingly relevant to both food science and biomedical research. Recent studies have highlighted their ability to interact with biological systems, particularly the gut microbiota, a critical determinant of host metabolism, immunity, and overall health. This review critically summarizes the current understanding of F-CDs, including their mechanisms of formation, analytical detection methods, and physicochemical properties. It explores their biological fate in the gastrointestinal tract, encompassing absorption, distribution, metabolism, and excretion, with a focus on their stability and cellular uptake. Special attention is given to the interaction between F-CDs and the gut microbiota, where evidence suggests both beneficial (e.g., anti-inflammatory, antioxidant) and detrimental (e.g., dysbiosis, inflammatory signaling) effects, depending on the CD type, dose, and exposure context. Additionally, this review addresses toxicological concerns, highlighting gaps in long-term safety data, standardized detection methods, and regulatory oversight. The dual role of F-CDs—as potential modulators of the microbiota and as emerging dietary nanomaterials with uncharted risks—underscores the need for further interdisciplinary research. Future efforts should aim to refine detection protocols, assess chronic exposure outcomes, and clarify structure–function relationships to enable the safe and responsible application of these nanomaterials in food and health contexts. Full article

Baicalin is a natural flavonoid that has anti-apoptotic and anti-inflammatory effects. It shows some beneficial effects on muscle atrophy. However, its effects on age-related muscle atrophy are poorly understood. In this paper, we investigated whether baicalin exerts protective effect against skeletal muscle atrophy and its underlying mechanisms in aged mice using the grip strength test, histological analysis, and Western blots. Baicalin increased total muscle mass and strength in aged mice. Consistently, the cross-sectional area of quadriceps (QD) muscle significantly increased in both baicalin-administrated groups. Moreover, baicalin induced a shift in muscle fiber size distribution toward large fibers in both groups of mice. Expression levels of muscle atrophic factors, such as myostatin (MSTN) and atrogin-1, as well as pro-inflammatory cytokines, including tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), were elevated in aged mice, but these increases were reduced by baicalin. While mitochondrial fission regulator, dynamin-related protein 1 (DRP-1), and apoptosis-related protein (apoptotic protease activating factor 1 (Apaf-1)) expressions were higher in aged mice than young mice, and their expression were downregulated following baicalin administration. The comprehensive results of this study suggest that baicalin provides beneficial effects on the treatment of sarcopenia not only by suppressing muscle atrophic factor expression and inflammation but also attenuating DRP-1-mediated mitochondrial fission and apoptosis. Full article

Strontium, a key trace element regulating bone development and cardiovascular function, has seen growing research interest in its groundwater accumulation and resource potential. The unique geological structure of the northern Lushan Mountain slope provides an ideal setting to investigate strontium migration and enrichment. We systematically collected 21 groundwater samples and analyzed strontium occurrence characteristics and formation mechanisms using hydrochemical analysis, PHREEQC simulations, Gibbs diagrams, and cation exchange adsorption models. Analysis revealed that 71.4% of samples (15 groups) exceeded the GB 8537-2018 standard (≥0.4 mg/L), significantly higher than typical groundwater systems. Spatial distribution showed marked geological differentiation: average strontium concentration in Cambrian-Ordovician fractured-karst water reached 2.79 mg/L (range: 0.207–12.41 mg/L), 109.8% higher than in bedrock fissure water (1.33 mg/L). Structural control was evident, with samples near fault zones exhibiting generally higher concentrations than non-fault areas. Multivariate statistics indicated significant positive correlations between Sr²⁺ and TDS, Na⁺, Ca²⁺, and SO₄²⁻, suggesting synergistic enrichment mechanisms. Hydrogeochemical simulations confirmed that multiphase leaching of strontium-bearing silicate rocks provides the primary source, while rock weathering-driven ion exchange reactions constitute the key enrichment mechanism. This study elucidates the structural-lithological coupling-controlled hydrogeochemical cycle of strontium, providing theoretical support for delineating high-quality mineral water targets and developing health-beneficial geo-resources in the Lushan region. Full article

Making full utilisation of the synergies that exist among the various stages of industrial green production is beneficial to the realisation of the dual-carbon goal. However, the synergistic effects among the three stages of industrial green production have not yet been explored in depth from a microscopic perspective. Based on the analytic hierarchy process, the entropy weighting method, the coupled synergy degree model, the spatial autocorrelation test, and the geographically weighted regression model (GWR), the spatiotemporal evolution characteristics and driving mechanism of the synergistic effects among the three stages of industrial green production were explored by utilising the relevant data of industrial enterprises in 30 provinces of China from 2012 to 2022. The results showed that the synergistic effect of industrial green production exhibited an upward trend over time, and displayed a regional distribution characteristic of decreasing from east to west. The spatial differences in the synergistic effects of industrial green production gradually narrowed and the number of provinces with high–high (H-H) agglomerations increased. The level of digital economy development, the urbanisation level, the optimisation of industrial structure, the level of green credit, and the intensity of environmental regulation were the main driving factors for the synergistic effects of industrial green production, and there were significant spatial differences. This study provides a basis for the formulation of differentiated regional green development policies from the perspective of synergizing the various stages of industrial green production. Full article

To address the limitation of generalization of federated learning under non-independent and identically distributed (Non-IID) data, we propose FedDFPA, a personalized federated learning framework that integrates dynamic parameter fusion and prototype alignment. We design a class-wise dynamic parameter fusion mechanism that adaptively fuses global and local classifier parameters at the class level. It enables each client to preserve its reliable local knowledge while selectively incorporating beneficial global information for personalized classification. We introduce a prototype alignment mechanism based on both global and historical information. By aligning current local features with global prototypes and historical local prototypes, it improves cross-client semantic consistency and enhances the stability of local features. To evaluate the effectiveness of FedDFPA, we conduct extensive experiments on various Non-IID settings and client participation rates. Compared to the average performance of state-of-the-art algorithms, FedDFPA improves the average test accuracy by 3.59% and 4.71% under practical and pathological heterogeneous settings, respectively. These results confirm the effectiveness of our dual-mechanism design in achieving a better balance between personalization and collaboration in federated learning. Full article

Electromigration (EM) is a critical reliability concern in electronic solder joints due to increasing current densities in modern electronic packaging. EM-induced failures often manifest as void formation and microstructural degradation, particularly at the cathode interface. To address this issue, composite solder joints with elemental additions have been explored to enhance performance under high current stress. This study investigates the effect of Zn addition on the electromigration behavior and mechanical performance of eutectic Sn-Bi solder joints on copper (Cu) and nickel-coated copper (Ni/Cu) substrates. The solder alloys 58Sn-42Bi and Zn-modified Sn-Bi were prepared and reflowed onto the substrates. Electromigration testing was performed under a constant current of 1000 mA at room temperature, with applied voltages of 5 V, 12 V, and 24 V over a 10-day period per sample. Shear tests were conducted at a crosshead speed of 0.1 mm/min to evaluate joint strength. The results revealed that Zn addition influenced the distribution of Bi within the solder matrix, reducing Bi depletion at the cathode and mitigating accumulation at the anode, suggesting improved EM resistance. Zn-containing solder joints also demonstrated enhanced shear strength compared to unmodified Sn-Bi joints. These findings highlight the potential of Zn as a beneficial alloying element for improving the reliability of lead-free solder joints and form a foundation for future studies incorporating phase analysis and predictive EM lifetime modelling. Full article