Search Results (26,359)

During shale gas field production, wellhead throttle valves are prone to erosion caused by solid particles carried in the gas stream, posing significant safety risks. Existing studies on erosion primarily focus on simple structure like elbows and tees, while research on gas–solid two-phase flow erosion in needle throttle valves remains limited. This paper establishes a numerical model based on the CFD-DPM approach, integrating actual shale gas field production conditions to investigate the erosion behavior of needle throttle valves under varying openings, particle sizes, inlet velocities, and particle mass flow rates. The results show that the valve spool consistently exhibits the highest erosion rate among all components, with the most severe erosion localized at its front end. At a 1/4 opening, particles colliding with the spool exhibit significantly increased frequency and energy when re-entering the upstream pipeline, raising the risk of blockages. Furthermore, when the opening exceeds 2/4, the valve chamber experiences higher erosion rates than the upstream and downstream pipelines. This study provides critical insights for optimizing valve design and maintenance strategies, thereby enhancing service life and ensuring safe shale gas production. Full article

An ocean target electric field signal is an effective approach for analyzing the ocean environment and is widely used for detecting ocean targets, extracting their features, and tracking them. Low-frequency analysis and recording (LOFAR) is a commonly used time–frequency analysis tool that provides the time–frequency spectrum of a signal; however, its reliance on the Fourier transform (FT) results in a low frequency resolution and signal-to-noise ratio (SNR), which limits its target detection capabilities. To address this problem, we propose a method called low-frequency analysis and recording based on basis pursuit (LOFAR-BP) for analyzing and detecting ocean target electric field signals. LOFAR-BP uses basis pursuit (BP) with the L1 norm for frequency analysis, whereas LOFAR utilizes the FT. We demonstrate that the FT is the L2 norm mathematically. LOFAR-BP generates the time–frequency spectrum in the same way that LOFAR does. By extracting characteristic values from the time–frequency spectrum, targets can be detected using an appropriate threshold. Both simulation and ocean experiments showed that LOFAR-BP effectively enhances target signals and suppresses noise. Compared with LOFAR, LOFAR-BP improved the frequency resolution by 60% in both experiments and increased the SNR by 54.82 dB in the simulation experiment and by 39.59 dB in the ocean experiment. When applied to target detection, LOFAR-BP can detect targets 6 s earlier than LOFAR can. Full article

Driven by polymer processing–property data, machine learning (ML) presents an efficient paradigm in predicting the stress–strain curve. However, it is generally challenged by (i) the deficiency of training data, (ii) the one-to-many issue of processing–property relationship (i.e., aleatoric uncertainty), and (iii) the unawareness of model uncertainty (i.e., epistemic uncertainty). Here, leveraging a Bayesian neural network (BNN) and a recently proposed dual-architected model for curve prediction, we introduce a dual Bayesian model that enables accurate prediction of the stress–strain curve while distinguishing between aleatoric and epistemic uncertainty at each processing condition. The model is trained using a Taguchi array dataset that minimizes the data size while maximizing the representativeness of 27 samples in a 4D processing parameter space, significantly reducing data requirements. By incorporating hidden layers and output-distribution layers, the model quantifies both aleatoric and epistemic uncertainty, aligning with experimental data fluctuations, and provides a 95% confidence interval for stress–strain predictions at each processing condition. Overall, this study establishes an uncertainty-aware framework for curve property prediction with reliable, modest uncertainty at a small data size, thus balancing data minimization and uncertainty quantification. Full article

Multi-view graph clustering (MVGC) utilizes affinity graphs to efficiently obtain information between views. Although various excellent MVGC methods have been proposed, they still have many limitations. To surmount these limitations, this work develops a novel tensor-based unified and discrete multi-view projection clustering (TUDMPC) approach. Specifically, TUDMPC uses projection and the $L_{2,1}$-norm for feature selection to reduce the effects of redundancy and noise. Meanwhile, the differences among similar graphs are minimized through the tensor kernel norm to better leverage information across views and capture high-order correlations. In addition, the rank constraint is applied to keep the affinity graphs with a discrete cluster structure, and the clustering results are obtained directly in a unified joint framework. Finally, an efficient optimization algorithm is proposed to obtain the clustering results. Experiments are conducted to compare the clustering results of TUDMPC with seven baseline methods. The results show that TUDMPC outperforms the existing methods. Full article

Microbial-induced carbonate precipitation (MICP) is an eco-friendly soil stabilization technique. This study explores the synergistic effects of incorporating hydroxypropyl methylcellulose (HPMC) into the MICP process to enhance the disintegration and seepage resistance of loess. A series of disintegration, seepage, scanning electron microscopy (SEM), and mercury intrusion porosimetry (MIP) tests were conducted. The results show that HPMC forms protective membranes around calcium carbonate crystals produced by MICP and soil aggregates, which enhance cementation, reduce soluble salt dissolution, promote soil particle aggregation, and seal pore structures. At the optimal 0.4% HPMC dosage, the maximum accumulative disintegration percentage and the disintegration velocity decreased to zero. Additionally, HPMC-modified MICP reduced the amount, size, and flow velocity of seepage channels in loess. The integration of MICP with HPMC provides an efficient and sustainable solution for mitigating loess disintegration and seepage issues. Full article

Polar research was especially affected by the COVID-19 pandemic because of its reliance on travel for remote fieldwork, large-scale scientific infrastructure, ecologically stressed environments, and elevated health risks to remote communities. In this study, we seek to understand how the polar science community responded to these challenges. Our data employ formal documentary evidence from the U.S. National Science Foundation Office of Polar Programs (OPP) and semi-structured interviews with 21 academic polar scientists based in the United States. Combining on-the-ground experiences with real-time responses from a leading federal funding agency reveals impacts and highlights opportunities to support polar research and researchers in the coming years. Polar researchers and OPP were often able to respond to challenges plastically: increasing support for community engagement and onsite staffing, switching methods, pivoting to archival work, or building new theoretical or experimental capacity. That said, pandemic disruptions brought known problems in the field to the fore, such as the investments in time and other resources needed for knowledge co-production and fieldwork. Individual and policy-level strategies to address those problems point the way toward sustainable polar science, including recognition of the multiple methodologies and people needed for successful work; incorporation of technologies that enhance scientific capacity while expanding access and inclusion; and attention to career development, especially for early-career and community collaborators. Full article

The analysis of marine environmental parameters plays an important role in areas such as sea surface simulation modeling, analysis of sea clutter characteristics, and environmental monitoring. However, ocean observation remote sensing satellites typically deliver large volumes of data with limited spatial resolution, which often does not meet the precision requirements of practical applications. To overcome challenges in constructing high-resolution marine environmental parameters, this study conducts a systematic comparison of various interpolation techniques and deep learning models, aiming to develop a highly effective and efficient model optimized for enhancing the resolution of marine applications. Specifically, we incorporated adaptive global attention (AGA) mechanisms and a spatial gating unit (SGU) into the model. The AGA mechanism dynamically adjusts the weights of different regions in feature maps, enabling the model to focus more on critical spatial features and channel features. The SGU optimizes the utilization of spatial information by controlling the information transmission pathways. The experimental results indicate that for four types of marine environmental parameters from ERA5, our model achieves an overall PSNR of 44.0705, an SSIM of 0.9947, and an MAE of 0.2606 when the resolution is increased by a upscale factor of 2, as well as an overall PSNR of 35.5215, an SSIM of 0.9732, and an MAE of 0.8330 when the resolution is increased by an upscale factor of 4. These experiments demonstrate the model’s effectiveness in enhancing the spatial resolution of satellite-derived marine environmental parameters and its ability to be applied to any marine region, providing data support for many subsequent oceanic studies. Full article

DNA methylation is a critical mechanism for regulating gene expression in bacteria and plays an essential role in bacterial pathogenesis. A mutant, WC1535ΔhsdM, lacking hsdM encoding a DNA methyltransferase was constructed using homologous recombination technology. The growth, hemolytic activity, and capsule formation of the mutant were analyzed. The dynamic distribution of the wild-type (WT) and mutant strains in tilapia tissues after artificial infection was determined. The adhesion, invasion, anti-phagocytic, and whole-blood survival abilities of the WT and mutant strains were analyzed. Tilapia were intraperitoneally injected with the WT or mutant strains, and the LD₅₀ values were determined. The expression levels of the immune-related genes in tilapia were analyzed by qRT-PCR. The mutant showed faster growth during the logarithmic growth period (5~10 h) and lower hemolytic activity than the WT strain. Mutant loads in tilapia tissues were significantly lower than those of the WT strain. Mutant strain adhesion to epithelial cells was significantly reduced, it was more easily engulfed by macrophages, and it had decreased intracellular survival. The LD₅₀ of the mutant was 2.06 times higher than that of the WT strain, indicating decreased pathogenicity. Expression levels of immune-related genes IL-1β, IL-6, IFN-γ, and TNF-α in tilapia induced by the mutant were lower than those by the WT strain. In conclusion, the WC1535ΔhsdM mutant exhibited an increased growth rate and decreased hemolytic activity, tissue colonization, and pathogenicity, indicating that HsdM could regulate S. agalactiae growth and pathogenicity. This study provides new insights into the pathogenesis of piscine S. agalactiae. Full article

Marine zoning is a widely used spatial tool for managing ocean spaces, minimizing conflicts between uses, and maintaining ecosystem services. This review examines and profiles the use of marine zoning and its potential to support climate resilience and ecosystem services through a systematic PRISMA analysis of 121 articles. The findings highlight the importance of balancing sustainable resource use and human well-being with nature protection through well-tailored zoning objectives. The review underscores the need to expand research on underrepresented marine habitats such as seagrass and algae, which play a critical role in climate change mitigation. Additionally, it highlights the necessity of broadening the scope to consider human activities beyond fisheries, which are often the primary focus. Stakeholder engagement and public awareness are identified as crucial for effective marine zoning planning. A significant gap is noted in the integration of ecosystem services and natural capital into marine zoning research. Furthermore, despite marine zoning’s potential to address climate change challenges, the reviewed articles reveal limited attention to this topic, indicating an urgent need for further research. This review advocates for the incorporation of ecosystem service valuation and climate change considerations into marine zoning to ensure sustainable management that balances ecological preservation with human well-being. Full article

To develop safe and effective management policies, it is important to understand the physiologic effects of fishing interactions and scientific research methods on endangered marine species. In the present study, validated assays for plasma corticosterone, free thyroxine (fT4), and aldosterone were used to assess the endocrine status of 61 presumed healthy, wild Kemp’s ridley sea turtles (Lepidochelys kempii) that were captured for separate ecological studies using two capture methods (trawl net n = 40; manual capture n = 21). Plasma hormone concentrations were also assessed in relation to eight clinical plasma biochemical analytes. Corticosterone and aldosterone concentrations were moderately high after capture, with significantly higher concentrations in turtles captured by trawl net vs. manual capture. Free thyroxine concentrations were within previously published ranges for healthy individuals of this species. Clinical biochemical data revealed moderately elevated potassium and lactate concentrations in many individuals, with significantly greater lactate concentrations in trawl-captured turtles. Aldosterone concentrations were positively correlated with corticosterone. The results of the present study indicate that Kemp’s ridley sea turtles have robust adrenocortical activity immediately after capture, resulting in high plasma concentrations of corticosterone and aldosterone. Researchers who use such methods to access sea turtles can consider these results in planning careful and efficient field studies. Full article

Increases in the magnitude and frequency of extreme flood events are among the most impactful consequences of climate change. Coastal areas can potentially be affected by interactions among different flood drivers at the interface of terrestrial and marine ecosystems. At the same time, socio-economic processes of population growth and urbanization can lead to increases in local vulnerability to climate extremes in coastal areas. Within this context, research focusing on modelling and mapping rapid-onset coastal flooding is essential (a) to support flood risk management, (b) to design local climate adaptation policies and (c) to increase climate resilience of coastal communities. This systematic literature review delineates the state-of-the art of research on rapid-onset coastal flooding. It provides a comprehensive picture of the broad range of methodologies utilised to model flooding and highlights the commonly identified issues, both from a scientific standpoint and in terms of the policy implications of translating research outputs into actionable information. As flood maps represent fundamental instruments in the communication of research outcomes to support decision making and increase climate resilience, a focus on the spatial representation of coastal floods proposed in the literature is adopted in this review. Full article

High-performance fiber-reinforced concrete (HPFRC) offers exceptional strength, ductility, and durability, making it highly promising for electric power pipe jacking applications. However, limited research exists on the mechanical properties of HPFRC pipes, especially regarding reinforcement schemes. This study bridges this gap by using a combination of three-point testing, analytical calculations, and numerical simulations to investigate the mechanical behavior and performance of HPFRC pipes under various reinforcement configurations. The results show that the load–displacement curve of HPFRC pipes initially follows a linear elastic relationship, but as the load exceeds 200 kN/m, displacement increases and cracks form, with failure occurring at 410 kN/m. HPFRC pipes demonstrate significantly enhanced load-bearing and crack resistance capabilities, with reduced reinforcement and wall thickness compared to traditional materials, maintaining high load-bearing capacity even after damage. The three analysis methods generally align in terms of load-bearing and failure processes, though the analytical method reveals limitations in accurately predicting crack widths. The study also reveals that reinforcement schemes significantly affect the pipes’ structural performance, with double layer and inner layer reinforcement providing superior damage resistance. This study contributes new insights into HPFRC pipe performance and provides a basis for optimizing reinforcement designs in pipe jacking projects. Full article

Late Permian–Early Triassic basic rocks, which are widespread in the western margin of the Yangtze block (SW China), provide critical information for regional tectonic evolution. The Qiaoqi intrusion, distributed in the western margin of the Yangtze block, is selected as a representative for discussion in this paper. LA-ICP-MS zircon U-Pb dating results show that the Qiaoqi intrusion was formed at 245 ± 1 Ma. It belongs to the medium-K calc-alkaline and tholeiitic basalt series. It is characterized by high concentrations of Fe₂O₃^T (11.53 wt. % to 15.50 wt. %), TiO₂ (1.81 wt. % to 3.20 wt. %), Al₂O₃ (11.80 wt. % to 15.60 wt. %), and low concentrations of MgO (4.51 wt. % to 8.93 wt. %). The LREE and LILE (such as Cs, Rb, Ba and Th) are enriched, with insignificant Eu anomalies (Eu/Eu* = 0.92 to 1.13). The chondrite-normalized REE distribution diagram shows a right-leaning pattern, similar to ocean island basalts (OIB), displaying the geochemical characteristics of enriched mantle sources. The zircon εHf(t) values are relatively high (+12.7 to +15.5) and the single-stage Hf model ages are relatively young (t_DM = 272 to 386 Ma). Modeling further reveals that the parent magma was derived from 13% to 19% partial melting of garnet peridotite. Comprehensive analysis shows that the geochemical characteristics of the Qiaoqi intrusion bear resemblance to those of the Emeishan basalts, which are attributed to volumetrically minor melting of the fossil Emeishan plume head beneath the Yangtze crust following the eruption of the Emeishan Large Igneous Province (ELIP). This understanding further constrains the duration of the Emeishan Large Igneous Province and provides new support for understanding the formation, evolution and distribution of the Emeishan Large Igneous Province. Full article

This study investigates the spatiotemporal density aggregation and pattern distribution of vessel traffic amidst bustling maritime logistics scenarios. Firstly, a relatively new spatiotemporal segmentation and reconstruction method is proposed for ship AIS trajectories to address trajectory disruptions caused by berthing, anchorage, and other factors. Subsequently, a trajectory filtering algorithm utilizing time window panning is introduced to mitigate position jumps and deviation errors in trajectory points, ensuring that the dynamic trajectory adheres to the spatiotemporal correlations of ship motion. Secondly, to establish a geographical spatial mapping of dynamic trajectories, spatial gridding is applied to maritime traffic areas. By associating the geographical space of traffic activities with the temporal attributes of dynamic trajectories, a dynamic trajectory temporal density model is constructed. Finally, a case study is conducted to evaluate the effectiveness and applicability of the proposed method in identifying spatiotemporal patterns of maritime traffic and spatiotemporal density aggregation states. The results show that the proposed method can identify dynamic trajectory traffic patterns after the application of compression algorithms, providing a novel approach to studying the spatiotemporal aggregation of maritime traffic in the era of big data. Full article

This study presents a foam sandwich structure reinforced with carbon fiber columns (FSS-CFC), which exhibits strong mechanical and sound insulation properties. The FSS-CFC consists of two face-sheets and a polyvinyl chloride (PVC) core containing multiple CFC cylinders arranged in a periodic array. The sound transmission loss (STL) measured in acoustic tube experiments closely aligns with the finite element simulation results, validating the reliability of the present research. Through characteristic analyses, the study reveals the sound insulation mechanism of FSS-CFC, identifying three distinct sound insulation dips caused by the standing wave resonance of the core, column-driven same-direction bending vibrations, and column-constrained opposite-direction bending vibrations in the sheets. It is also demonstrated that the sound insulation performance of FSS-CFC is insensitive to hydrostatic pressure changes. Finally, the FSS-CFC is optimized by the genetic algorithm in MATLAB and COMSOL. The optimized FSS-CFC displays good improvements in both mechanical and acoustic performance compared to the initial structure. The average STL in the frequency of 500 Hz to 25,000 Hz has increased by 3 dB, representing an improvement of approximately 25%. The sound insulation mechanism in FSS-CFC could provide valuable insights for the development of a pressure-resistant acoustic structure for use on deep-water vehicles. Full article