Hasil untuk "Ocean engineering"

Benjamin D. Goffin, Alfonso Fernandez, Jordi Etchanchu et al.

Wildfires, exacerbated by climate change, land-use alterations, and extreme weather conditions, can have catastrophic impacts on both people and ecosystems. Recent research highlights the role of Soil Moisture (SM) as a predisposing factor to large fires, yet critical thresholds remain poorly characterized across different data sources. Volumetric SM measurements differ in magnitude and dynamic range across large spatial extents and satellite products, making direct comparisons challenging. To address this, we calculated the Fraction of Available Water (FAW), which ranges from 0 to 1 as SM varies from wilting point to field capacity. Using satellite observations from the Soil Moisture and Ocean Salinity (SMOS), Advanced Microwave Scanning Radiometer 2 (AMSR2), Soil Moisture Active Passive (SMAP), and the Climate Change Initiative (CCI) programs, we explored antecedent conditions in south-central Chile that favored an extreme fire spread in early February 2023, when over 240 000 ha burned in just four days. Our analysis showed that FAW was low—not only in the days immediately before the fires, but throughout the preceding month. Critical thresholds emerged across multiple satellite products, revealing plant stress (FAW < 0.50) and extreme drought (FAW < 0.20). Even drier conditions (FAW < 0.10) were widespread, affecting both burned and nonburned areas and reducing moisture constraints across the region. Our findings demonstrate that FAW thresholds derived from multiple satellite products, including SMOS, SMAP, and CCI, provide a robust framework for identifying SM levels that may predispose areas to wildfire danger.

Sharifah Altalhi, Júnia Schultz, Tahira Jamil et al.

Abstract Background Hydrothermal vents along mid-ocean ridges host diverse microbial communities and are crucial to global elemental cycling. The Red Sea, known for its unique environmental conditions—including low nutrient levels, high year-round temperatures, bottom-water temperatures of 21 °C, and elevated salinity—hosts recently discovered active low-temperature hydrothermal vent fields at the axial Hatiba Mons volcano. These vents, characterized by large iron oxide mounds and abundant microbial mats, offer an extreme environment for studying the diversity and functions of prokaryotes involved in elemental cycling in this system. In this study, we used 16S rRNA sequencing and shotgun metagenomics to examine the microbial diversity and metabolic capabilities of precipitates and microbial mats from five vent sites. Results We recovered 314 non-redundant metagenome-assembled genomes (MAGs), including 250 bacterial and 64 archaeal MAGs, representing 34 bacterial and 11 archaeal phyla. Functional annotations revealed diverse nutrient and metal cycling potentials, with notable enrichment in iron redox genes. Key players include Bathyarchaeia and Chloroflexi in the precipitates (contributing to carbon, nitrogen, sulfur, and metal cycling potentials) and Pseudomonadota members in the microbial mats and upper precipitates (involved in iron and sulfur metabolism and carbon fixation through the CBB cycle). Carbon fixation in precipitate potentials primarily occurs through the Wood–Ljungdahl pathway. Sulfur and nitrogen cycling genes are distributed across various genomes, indicating collaborative cycling. Conclusion Our genome-resolved analysis positions the Hatiba Mons vents as an iron-rich system that provides new insights into oligotrophic hydrothermal environments, with potential relevance for understanding novel metabolic pathways, extremophilic adaptations, and their roles in element cycling and biotechnological applications.

Kyung-Hoon Han, Jaehoon Jeong, Sungwook Hong

This study proposes an infrared-to-rain (IR2Rain) model to enhance the accuracy of the geostationary (GEO) weather satellite Geo-Kompsat-2A (GK-2A) rain rate (RR) product. The IR2Rain model is built upon a conditional generative adversarial network, taking GK-2A brightness temperatures as inputs and Integrated MultisatellitE Retrievals for Global Precipitation Measurement (IMERG) Final RRs as target values. To address the distinct physical characteristics and ranges of the input and target datasets, IR2Rain employs preprocessing for normalization and postprocessing for denormalization. The IR2Rain model is developed and validated using the paired input and output datasets collected between September 2019 and December 2022, encompassing a broad region across Asia and Oceania. This study compares the performance of IR2Rain-derived RRs against IMERG RR, GK-2A RR, and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network dynamic infrared (IR) rain rate-now products. The results demonstrated a probability of detection of 0.607, a critical success index of 0.482, a root-mean-square error of 0.759 mm/h, and a correlation coefficient of 0.671. By combining the high temporal resolution of GEO satellite observations with the reliability of IMERG Final data, the IR2Rain model produces a robust near-real-time IMERG-like precipitation product. Despite smoothing effects and the tendency to underestimate intense rainfall, IR2Rain improves the performance relative to RR products based on the same GK-2A IR data, mitigates the latency encountered in IMERG data generation, and provides timely and accurate precipitation information on intensity and distribution. These products are particularly valuable for operational weather forecasting and public end users in Asia and Oceania, supporting disaster preparedness and hydrological applications.

Donglai Zhou, Donglai Zhou, Wenhao Zhong et al.

This study investigated the effects of dietary supplementation of mulberry leaf oligosaccharides (MLO) on the growth performance, serum biochemistry, glucose and lipid metabolism, antioxidant activity, liver health, and virus resistance in largemouth bass (Micropterus salmoides). The fish were fed with CK (basal diet), MLOL (basal diet supplemented with 0.5%MLO), and MLOH (basal diet supplemented with 1.0% MLO) for 80 days, and then subjected to a 21-day viral challenge experiment. The results showed that MLO supplementation had no adverse effect on the weight gain rate, specific growth rate, feed intake, and condition factor (P > 0.05), but significantly decreased the feed conversion rate and viscerosomatic index (P< 0.05). Moreover, the MLOL and MLOH group had significantly lower contents of triglyceride, blood glucose, and malondialdehyde and activities of serum alanine aminotransferase and aspartate aminotransferase, while significantly higher levels of serum and liver total superoxide dismutase and lower levels of glutathione than the CK group (P< 0.05). MLO supplementation significantly up-regulated the relative expression of glycolytic genes gk and pfk and lipid catabolism genes ppar-α and cpt-1, while obviously down-regulated that of acc, fas, and dgat related to fatty acid synthesis in the liver tissue (P< 0.05). In terms of liver health, MLO supplementation significantly up-regulated the relative expression of anti-inflammatory cytokines il-10 and tgf-β, while decreased that of pro-inflammatory cytokines nf-κb, il-8, and tnf-α in the liver tissue (P< 0.05). The viral challenge test showed that MLO supplementation significantly improved the survival rate of M. salmoides after largemouth bass ranavirus (LMBV) infection. Dietary MLO supplementation promoted liver glucose and lipid metabolism, and improved the immunity and resistance of M. salmoides to LMBV by regulating the PPAR signaling way and inhibiting the NF-kB signaling pathway. The appropriate addition amount of MLO to the diet was determined to be 1.0%.

Liam Magargal, Parisa Khodabakhshi, Steven Rodriguez et al.

This paper presents the development of a graph autoencoder architecture capable of performing projection-based model-order reduction (PMOR) using a nonlinear manifold least-squares Petrov–Galerkin (LSPG) projection scheme. The architecture is particularly useful for advection-dominated flows modeled by unstructured meshes, as it provides a robust nonlinear mapping that can be leveraged in a PMOR setting. The presented graph autoencoder is constructed with a two-part process that consists of (1) generating a hierarchy of reduced graphs to emulate the compressive abilities of convolutional neural networks (CNNs) and (2) training a message passing operation at each step in the hierarchy of reduced graphs to emulate the filtering process of a CNN. The resulting framework provides improved flexibility over traditional CNN-based autoencoders because it is readily extendable to unstructured meshes. We provide an analysis of the interpretability of the graph autoencoder’s latent state variables, where we find that the Jacobian of the decoder for the proposed graph autoencoder provides interpretable mode shapes akin to traditional proper orthogonal decomposition modes. To highlight the capabilities of the proposed framework, which is named geometric deep least-squares Petrov–Galerkin (GD-LSPG), we benchmark the method on a one-dimensional Burgers’ model with a structured mesh and demonstrate the flexibility of GD-LSPG by deploying it on two test cases for two-dimensional Euler equations that use an unstructured mesh. The proposed framework is more flexible than using a traditional CNN-based autoencoder and provides considerable improvement in accuracy for very low-dimensional latent spaces in comparison with traditional affine projections.

Jingxin Zhou, Yeqi Hu, Yuan Rao et al.

Accurate depth estimation is fundamental for underwater applications such as robotics and marine exploration. However, underwater imaging suffers from severe degradation due to light attenuation, scattering, and geometric distortion, which is compounded by the scarcity of real stereo data. To address these challenges, we propose Joint Dual-Branch Denoising (JDBD), which is a plug-in framework embedded within dual-branch depth estimation networks. JDBD performs task-aware denoising via bidirectional refinement between a monocular and a stereo pathway: the monocular branch combines Adaptive White Balance and a Red Inverse Channel Prior for color correction and haze suppression, while the stereo branch applies Joint Bilateral Filtering to reduce scattering and preserve edges. Trained on the synthetic UWStereo dataset and evaluated on the real-world SQUID dataset as well as a subset of UWStereo, JDBD achieves high depth estimation accuracy and visual fidelity in underwater scenes, demonstrating robust and adaptable performance across diverse conditions.

E. Ruvinov, Smadar Cohen

Yu Xie, Zhihui Zhong, Bingyi Li et al.

In the realm of real-time spaceborne synthetic aperture radar (SAR) imaging, the accurate and swift phase factors calculation (PFC) holds significant importance. This article introduces an innovative advanced RISC machines (ARM) field-programmable gate array (FPGA) hybrid acceleration technique designed to expedite the phase factor computation process of SAR imaging. By combing the strengths of ARM and FPGA, our approach achieves optimal performance. The proposed methodology strategically allocates the initial and intermediate calculations to ARM, while delegating the intricate exponential functions to FPGA. By incorporating a parallel four-channel coordinated rotation digital computer (CORDIC) structure and redundancy-based fault tolerant modules with error correction codes, the protection of soft errors is realized and the reliability is improved. By utilizing a modified three-tiered reconfigurable processing elements exchange network for fault tolerant CORDIC processors, the acceleration of computing time is realized and hardware overhead is reduced. A comprehensive prototype verification illustrates the method's efficacy for PFC in spaceborne SAR imaging. The evaluation of computational time and resource utilization unveils ARM's suitability for the initial two levels, while the complexities and precision of the third level warrant FPGA computing acceleration. Overall, this research advances a novel ARM-FPGA hybrid strategy that elevates phase factor computation in spaceborne SAR imaging, opening up avenues for efficient and dependable radar imaging applications.

Xiaoteng Xiao, Xiaoteng Xiao, Yufeng Zhang et al.

Seawater salt is constantly supplied from the marine environment to coastal underground brine deposits, meaning that brine has the potential for continuous extraction. There is currently a lack of information about the processes that drive the fluxes of seawater salt to underground brine deposits in tidal-driven brine mining areas. We chose the Yangkou salt field on the southern coast of Laizhou Bay, a brine mining area, as our study site. We monitored the spatial and temporal distribution of the underground brine reserve and the changes in water level and salinity in the mining area and adjacent tidal flats using electrical resistivity tomography and hydrogeological measurements. We monitored cross-sections along two survey lines and observed that the underground brine reserve receives a stable supply of seawater salt, and calculated that the rate of influx into the brine body in the mining area near the boundary of the precipitation funnel was 0.226−0.232 t/h. We calculated that a total salt flux of approximately 5.50 t enters the underground brine body every day through a 150 m long shoreline and a 1322.3 m2 window, which is sufficient to sustain the daily extraction of one brine well. During tidal cycles, there are two peaks in the salinity of the water supplied to the underground brine reserve, which means that the brine supply is from at least two high-salinity salt sources in different tidal stages. The first salinity peak occurs during the initial stage of the rising tide after seawater inundates the tidal flat. At this time, seawater, which is a solution and carries a large amount of evaporated salt, is transported into the brine layer through highly permeable areas or biological channels and replenishes the brine in the mining area. The second salinity peak occurs during the early stage of the falling tide. Influenced by hysteresis-driven tidal pumping, high-salinity brine from the lower intertidal zone is rapidly transported into the mining area, thereby increasing the salinity of the underground brine.

Hajar F. Ismael, Harivan R. Nabi, Tukur Abdulkadir Sulaiman et al.

In this study, we focus on the (3+1)-dimensional generalized B-type Kadomtsev–Petviashvili (gBKP) equation in fluid dynamics, which is useful for modeling weakly dispersive waves transmitted in quasi media and fluid mechanics. As a general matter, this paper examines the gBKP equation including variable coefficients of time that are widely employed in plasma physics, marine engineering, ocean physics, and nonlinear sciences to explain shallow water waves. Using Hirota’s bilinear approach, one-, two, and three-soliton solutions to the problem are constructed. By employing a long-wave method, 1-M-, 2-M, and 3-M-lump solutions are derived. In addition, interaction phenomena of one-, and two-soliton solutions with one-M-lump wave are revealed. Moreover, an interaction solution between a two-M-lump wave and a one-soliton solution is also offered. The planes that M-lump waves travel among them are derived. We believe that our findings will help improve the dynamical properties of (3+1)-dimensional BKP-type equation.

Zhenyue Liu, Pengyan Zhang, Guanghui Li et al.

Ecosystems offer a wide array of benefits to support human livelihoods and enhance the quality of life. Quantitative evaluation of ecosystem services (ESs) is crucial for achieving the goal of sustainable development. The Yellow River Basin has a large population, and there are contradictions and conflicts in ecological protection, resource utilization, and economic development, among which the downstream region is the most prominent. However, the ESs selected in the existing research are not comprehensive enough, and there are also few studies that further focus on the effects of urbanization on this basis. This article calculated seven types of ESs based on the InVEST model and related methods, and then constructed a composite ecosystem service index (CESI), and studied its spatiotemporal evolution and response to urbanization indicators through bivariate spatial autocorrelation and spatial metrological models. We found that from 1990 to 2020, the CESI fluctuated and decreased with time, with a significant positive spatial correlation but showed a weakening trend. There were differences in the evolution process of the spatial correlation between the CESI and population density, economic density, and land development degree, but ultimately the spatial correlation changed from positive to negative. In terms of spatial spillover effect, population density had a significant positive effect on the CESI, land development had a significant negative effect, and economic density had a weak spillover effect. This article provides a certain reference basis for governments at all levels to formulate relevant strategies for environmental protection and economic development.

Chaosheng Song, Feihong Zhu, Xinzi Li et al.

Abstract A three-dimensional conjugate tooth surface design method for Harmonic Drive with a double-circular-arc tooth profile is proposed. The radial deformation function of the flexspline (FS), obtained through Finite Element (FE) analysis, is incorporated into the kinematics model. By analyzing the FS tooth enveloping process, the optimization of the overlapping conjugate tooth profile is achieved. By utilizing the hobbing process, the three-dimensional machinable tooth surface of FS can be acquired. Utilizing the coning deformation of the FS, simulations are conducted to analyze the multi-section assembly and meshing motion of the machinable tooth surface. The FE method is utilized to analyze and compare the loaded contact characteristics. Results demonstrate that the proposed design method can achieve an internal gear pair consisting of a circular spline with a spur gear tooth surface and the FS with a machinable tooth surface. With the rated torque, approximately 24% of the FS teeth are engaged in meshing, and more than 4/5 of the tooth surface in the axial direction carries the load. The contact patterns, maximum contact pressure, and transmission error of the machinable tooth surface are 227.2%, 40.67%, and 71.24% of those on the spur gear tooth surface, respectively. It clearly demonstrates exceptional transmission performance.