Search Results (474)

Cryptophyta are ecologically important microalgae in marine and brackish ecosystems, but their future habitat suitability and ballast-water-associated surveillance priorities under climate change remain insufficiently understood. Based on 136 georeferenced occurrence records from China’s coastal waters and 24 marine environmental variables, this study applied the Biomod2 ensemble modeling framework to predict the current and future potential distribution of Cryptophyta in the Bohai Sea, Yellow Sea, East China Sea, and South China Sea. The ensemble model showed high predictive performance (Kappa = 0.94, TSS = 0.94, AUC = 0.997), outperforming most individual algorithms. Annual mean temperature (bio22) and maximum salinity (bio15) were identified as the dominant environmental constraints, indicating that thermal and salinity regimes jointly shape habitat suitability. Under present conditions, suitable habitats were broadly distributed across China’s coastal and shelf waters. Future projections indicated that suitable habitats generally remained extensive under most climate scenarios, suggesting that future environmental changes may maintain or reshape potential recipient environments for Cryptophyta. However, this response was not linear with increasing emission intensity; under the high-emission scenario, suitable habitats declined in some regions and showed stronger spatial reorganization, implying that excessive warming or altered salinity may reduce broad-scale suitability. These findings suggest that climate change may alter the spatial pattern of Cryptophyta habitat suitability under different emission pathways. Given the role of ship ballast water in transporting planktonic microalgae, persistent or newly suitable habitats, especially those located near ports, estuaries, semi-enclosed bays, and aquaculture areas, should be regarded as habitat-suitability-based surveillance priorities. This study provides a basis for climate-informed monitoring, ballast-water-associated screening, and adaptive management of coastal microalgae in the China Seas. Full article

Background and Objectives: Water polo (WP) is a high-intensity, intermittent aquatic team sport that has been extensively investigated within sports science. While contemporary literature has examined the body composition and morphological characteristics of elite and international WP players, this study aimed to define the general body composition profile of world-class WP players and determine position-specific differences. Methods: The study involved 72 national team players from Serbia, Croatia, Greece, and Italy who participated in the Olympic Games, World Championships, or European Championships. Participants’ body composition was measured using the InBody 720 multichannel bioimpedance method. Ten different variables were examined to assess body structure regarding contractile and ballast components. Results: MANOVA revealed statistically significant differences in body composition across playing positions (Wilks’ lambda = 0.239, p < 0.000, η²_p = 0.402). The variables that had the greatest impact on the difference were: body mass, body fat and body mass index with the 47.0, 44.4, and 43.7% of explained total variance of the impact on the differences (p = 0.000), respectively. Conclusions: world-class WP players assigned to different playing positions differ significantly in body composition. These positional profiles should be considered in talent identification, selection procedures, training, and nutritional strategies to optimize performance models, considering the future evolution of the game at the highest competitive level. Coaches could use this information to initially select players for different specific positions based on anthropometric and body composition criteria. Full article

To address the risks of cross-border transmission of pathogenic microorganisms posed by the failure or non-compliance of shipboard ballast water treatment systems, ports urgently require efficient and flexible emergency response solutions. This study presents a novel, containerized, integrated ship-to-shore emergency response system specifically designed for the rapid inactivation of pathogenic microorganisms in ballast water. The core innovation lies in the integration of a three-degree-of-freedom (3-DOF) hydraulic robotic arm, a vision and positioning system, and a dynamic inflatable sealing structure designed for rapid, automated docking with a ship’s ballast water discharge outlet (DN250), thereby enhancing operational safety and efficiency. The system employs a purely physical treatment process of “ultrasound (US) pre-treatment + dual-stage ultraviolet (UV) disinfection,” allowing for reception and treatment without secondary chemical pollution. The integrated treatment train, consisting of US (30 kHz, 7.6–12 kW, minimum acoustic energy density ≥ 0.45 J/cm²) followed by dual-stage UV disinfection (minimum UV dose: 147 mJ/cm²), maintained effective microbial inactivation at turbidity levels of 15, 125, 250, and 500 NTU. US alone showed little direct bactericidal effect, whereas the first UV stage achieved log reduction values (LRVs) of 3.31–4.13, and the complete US + UV + UV process achieved total LRVs of 5.07–7.34 for Escherichia coli. The results showed that dual-stage UV disinfection was key to achieving high inactivation efficacy (p < 0.001), while ultrasound, despite its limited direct bactericidal effect, may have facilitated downstream UV disinfection within the sequential treatment train. This system not only fills a critical gap in port biosecurity emergency infrastructure but also provides an experimentally validated, efficient, environmentally friendly, and flexibly deployable shore-based solution. Full article

Introduction: Records of rare, deep-water, and non-indigenous fish species are of growing interest in marine biodiversity research because they refine regional inventories, improve taxonomic knowledge, and provide valuable evidence of ecological change. In regions supported by long-term monitoring programs, such findings are especially relevant, as they help detect unusual occurrences and document changes in species composition over time. Objective: The aim of this communication is to present recent records of fish species new to science and new to Spanish waters, together with a non-indigenous species, all from Galician and Cantabrian waters (northern Spain), while emphasizing the importance of scientific surveys and complementary local observations in their detection. Methodology: The material examined was collected during the annual demersal trawl surveys conducted by the Instituto Español de Oceanografía (IEO-CSIC) on the northern Spanish continental shelf (DEMERSALES), as well as during two multidisciplinary surveys carried out on the Galicia Bank in 2010 and 2011. An additional specimen was obtained from a local recreational fisher off Asturias. In all cases, species identification was based on an integrative taxonomic approach combining morphological examination and molecular analyses (COI barcoding). Results: Three species new to science were identified: Gaidropsarus gallaeciae (Gadiformes: Gaidropsaridae), Notacanthus arrontei (Notacanthiformes: Notacanthidae), and Neoscopelus serranoi (Myctophiformes: Neoscopelidae). In addition, Lyconus brachicolus (Gadiformes: Lyconidae) and Lipogenys hyalovelanum (Notacanthiformes: Notacanthidae) were recorded for the first time in Spanish waters. A specimen of Diapterus brevirostris (Perciformes: Gerreidae), native to the tropical and subtropical Pacific coast of America, was also identified off Asturias. Owing to its small size and to the proximity of the commercial port of Gijón, ballast water is considered the most plausible vector for its introduction into the Cantabrian Sea. Conclusions: These records illustrate the value of long-term oceanographic surveys for detecting rare and deep-water fishes and confirm the usefulness of integrative taxonomy for robust species identification. They also highlight the complementary role of fishers and citizen observers in documenting biodiversity change and detecting non-indigenous species in Spanish waters. Full article

The aim of this study is to provide a preliminary assessment of the feasibility of using a three-arm buoy as a small-scale point-absorber wave energy converter under the moderate hydrodynamic conditions of the Baltic Sea. The analysed concept combines an axisymmetric three-floater geometry with two energy-conversion pathways: an electric generator and a pneumatic energy-storage subsystem based on compressed air. The study defines the geometrical and buoyancy parameters of the structure and applies two complementary modelling levels: a simplified screening-level energy estimate and a first-order heave-response model. The extended analysis includes the influence of effective operational density, added mass, PTO damping, conversion-path efficiency, heave RAO and hydrostatic stability. The baseline screening estimate indicates that the total daily energy output may amount to approximately 0.409 kWh under average wave conditions and approximately 0.920 kWh for higher waves. The first-order heave-response model shows that, for an assumed electrical conversion efficiency of 10%, the daily electrical energy estimate ranges from approximately 0.88 kWh/day for the lightweight configuration to approximately 4.12 kWh/day for the most heavily ballasted analysed case. The RAO analysis indicates that increasing the operational mass shifts the natural period towards longer wave periods, although the system remains outside resonance tuning for the reference wave period of 6 s. The hydrostatic analysis indicates that the three-arm configuration increases the waterplane second moment of area compared with a single circular buoy of the same waterplane area and provides a more directionally balanced stability response. The results should be interpreted as conceptual and parametric estimates rather than experimentally validated wave-to-wire performance. Further work should include BEM/CFD-based hydrodynamic coefficients, irregular-wave modelling, multi-degree-of-freedom dynamics, mooring-system coupling and laboratory validation. Full article

To address the challenges of severe background interference and unstable grasping of irregular maintenance tools in complex railway ballast environments, this paper proposes a robotic system that integrates enhanced visual perception with bio-inspired soft grasping. The core components of the system include a lightweight detection network (RA-YOLO), asymmetric “Fin Ray” soft fingers, and a visual servoing control framework. By embedding the CBAM attention mechanism and incorporating Mosaic data augmentation, RA-YOLO achieves robust feature extraction under complex backgrounds. The fingertip topology is optimized using the Yeoh constitutive model and finite element analysis, thereby improving stiffness under heavy loads and overall adaptability. Experimental results demonstrate that proposed RA-YOLO achieved a mAP@0.5 of 93.6% on the standard test set with an inference speed of 105 FPS. The visual-servo localization experiment an average Euclidean positioning error of 1.03 mm, with the maximum component-wise absolute error remaining below 2.5 mm. In system-level grasping experiments involving five categories of irregular tools, the integrated system achieved an overall grasping success rate of 91.8%, indicating its potential for automated tool recovery in unstructured railway maintenance environments. Full article

This study evaluates the performance of hyperspectral imaging (HSI) as a non-contact method for assessing railroad ballast fouling. A severely degraded ballast sample was collected from a derailment site. Conventional fouling indices were measured, indicating extreme ballast deterioration and fouling. To establish a quantitative baseline for degradation severity, hyperspectral reflectance data in the Visible–Near Infrared (VNIR) and Near Infrared (NIR) ranges were acquired for field samples under fouled-wet (as-received), fouled-dry (oven-dried), and clean-dry (oven-dried and sieved) conditions. Field spectra were compared with laboratory-fabricated ballast mixtures containing clay and coal fouling agents to ensure the results were not skewed due to the sampling procedure. Spectral similarity analysis using the Spectral Angle Mapper (SAM) was employed to quantify differences across ballast conditions. The maximum SAM angle reached approximately 0.45 radians between the as-received and clean-dry states in the NIR range, reflecting the combined effects of fouling and moisture. Comparisons between field and laboratory-fabricated samples showed moderate similarity, with SAM angles below 0.30 radians, indicating general agreement between field and laboratory spectra while capturing differences related to fouling agents, moisture retention, and compositional variability. Full article

Accurate and rapid identification of microalgae in ship ballast water is critical for preventing the spread of invasive aquatic species and ensuring ecological security. However, traditional manual microscopic examination is labor-intensive and limited by challenges such as high intra-class morphological variability, frequent cell aggregation, and inter-class similarity among microalgae. This study proposes YOLO11-DBalgae, a specialized end-to-end object detection framework designed for fine-grained microalgae recognition in complex aquatic environments. Two key architectural innovations are introduced into the YOLO11n baseline—a Detail-enhanced Vanishing-prevention Block (DVB), which processes input features through a VoVGSCSP cross-stage aggregation module followed by parallel Conv and DSConv paths, preserving fine-grained boundary signals of morphologically diverse algal cells during repeated downsampling, and a Bidirectional Feature Pyramid Network (BiFPN), which employs learnable cross-scale weighting to optimize multi-scale feature fusion across the extreme size range of co-occurring microalgal targets. Experimental results demonstrate that YOLO11-DBalgae achieves an mAP@0.5 of 97.3%, representing an improvement of 7.0 percentage points over the baseline YOLO11n model. The model sustains an inference speed of 240 FPS with 2.83 M parameters, maintaining a lightweight and deployment-viable profile. Qualitative analysis via per-class precision–recall curves, detection visualization, and Grad-CAM attention maps confirms the model’s robustness in recovering near-invisible weak-feature targets, minimizing false detections within dense cell clusters, and accurately distinguishing morphologically convergent species. The proposed framework provides a practical and deployable solution for automated microalgae monitoring, offering maritime regulatory bodies an efficient and reliable tool for ballast water management. Full article

Rail infrastructure plays an important role in freight and passenger mobility, and the assessment of rail track structure depends critically on understanding how the rail interacts with the supporting foundation. When rail support degrades (e.g., due to ballast fouling, settlement, etc.), the rail exhibits greater localized deformation that can lead to serious deleterious conditions. Track modulus represents a fundamental diagnostic measure of rail support, encompassing the vertical stiffness characteristics of the foundation and its resistance against downward rail movement. Existing track modulus characterization methodologies typically comprise deflection measurements of railway track (e.g., tie deflections) under known loads. Track modulus estimations result from analyzing deflection and load under assumptions of a traditional Winkler foundation, which can oversimplify mechanic relationships. Specifically, in the context of rail–ballast–subgrade interaction, a tensionless foundation permits gap development which can occur as track structure separates from the supporting ballast; additionally, track modulus may vary along the track length as conditions vary spatially. This paper presents a general analytical solution of ballasted track support characterization based on an iterative algorithm for the static response of a finite beam resting on a tensionless Winkler foundation. The method relates to multiple loads (e.g., concentrated axle loads and distributed self-weight), deflection along the track, and track condition through singularity functions, superposition of discrete support springs, and moment–curvature relationships. The model estimates rail deflections, lift-off points and shear and moment diagrams along the track. The technique permits: (1) validations against benchmark solutions and previously published results, (2) estimations of track modulus from known loads and measured deflections, and ultimately, (3) a framework for designing and processing sensor data streams for use in analyses and evaluations of railway track structure. Full article

The prefabricated polyurethane-solidified track bed (PPSTB) combines the adjustability of ballasted tracks with the low maintenance requirements of slab tracks, offering a promising solution for railway sections on deformable foundations. This study investigates the interaction and mechanical behaviors of the polyurethane-solidified ballast (PSB) modules and bulk ballast under laboratory loading. A series of unconfined uniaxial tests, confined ballast box tests, and cyclic loading tests were conducted, complemented by discrete element method (DEM) simulations to analyze mesoscopic particle evolution. Under monotonic compression, the stress–strain curve exhibits three distinct stages with an average elastic modulus of 19.66 MPa, where the central aggregate framework acts as the primary load-bearing structure. Confinement increases the modulus by 33.57% and yields a nearly linear stress–strain relationship, attributed to a more compact and uniform contact distribution. Furthermore, under cyclic loading, the PSB shows enhanced energy dissipation and deformation resistance compared to conventional ballast. These findings provide a theoretical basis for the structural design and long-term performance assessment of the PPSTB. Full article

Ground penetrating radar (GPR), as an efficient non-destructive testing technique, plays a crucial role in the structural condition assessment and defect identification of railway ballast. Typical defects such as mud pumping generally exhibit characteristics in B-scan images including weak reflections, blurred boundaries, and irregular structures, which pose significant challenges for stable detection and precise localization using existing methods that rely primarily on spatial feature modeling. Most current deep learning approaches focus on modeling spatial or temporal information, while lacking effective utilization of frequency-domain features, thereby limiting their discriminative capability under complex electromagnetic environments. To address these issues, this paper proposes a single-stage object detection framework, termed YOLO-DGW, based on time-frequency collaborative modeling. Built upon YOLOv8, the proposed method introduces a structure-aware spatial enhancement module to improve the representation of continuous GPR echo structures. Meanwhile, frequency-domain information is incorporated as a modulation prior to guide spatial feature learning, enhancing the model’s sensitivity to weak reflections and complex-shaped targets. In addition, A-CIoU loss function is designed to improve localization accuracy and stability for defect regions of varying scales. Experimental results demonstrate that YOLO-DGW achieves an F1-score of 63.06% and an AP@0.50 of 62.07%, representing improvements of approximately 7.41% and 2.8%, respectively, over the strongest baseline method. Compared with several mainstream object detection models, the proposed approach exhibits superior performance in both detection accuracy and cross-region generalization capability. These findings indicate that integrating frequency-domain information into spatial feature learning through a modulation mechanism can effectively enhance the model’s ability to discriminate weak-reflection anomalies, providing a novel time-frequency collaborative modeling paradigm for railway GPR defect detection. Full article

Against the backdrop of global energy landscape restructuring, the advancement of the “dual-carbon” goals, and escalating external uncertainties, coal, as the “ballast stone” of China’s new energy system, faces new challenges in terms of supply chain stability and security. Therefore, scientifically assessing China’s coal supply chain resilience (CSCR) is of significant theoretical and practical importance for systematically identifying its supply vulnerabilities and ensuring energy supply security under extreme conditions. In the paper, we construct a composite evaluation indicator system using national statistical data from 2010 to 2024. We operationalize resilience across the following four capacities: resistance, absorption, recovery, and adaptive capacity. Annual resilience levels are measured using an integrated framework. This framework combines an improved entropy weight method, TOPSIS, and gray relational analysis (GRA). We then use the indicator contribution degree and obstacle degree models to identify the most influential factors. The results indicate that China’s CSCR followed a fluctuating upward, W-shaped trajectory during 2010–2024, with a marked acceleration after 2020. Resistance and absorption capacities display pronounced volatility. Recovery and adaptation capacities improve steadily. The dominant obstacle factors include the share of intelligent coal production capacity, labor productivity per employee, the scale of workforce security, and the working-capital turnover ratio. These findings provide empirical evidence and policy-relevant insights for strengthening China’s CSCR and reinforcing national energy security. Full article

Offshore wind energy is an important source of clean energy. Single-post platforms, due to their simple structure and strong stability, can adapt to deep water environments through buoyancy and ballast systems, have small motion responses, and have low construction and maintenance costs. They are suitable for offshore wind energy development in deep-sea areas and help expand the application of offshore wind power. This paper conducts a coupled response analysis of offshore wind turbine foundations and mooring systems, as well as an optimization study on the form and number of mooring lines. Under the premise of considering the safety and economy of floating wind turbines, the mooring lines have been optimally arranged. The study calculates frequency-domain responses, time-domain responses, and mooring line forces under the constraints of the original three-line mooring system. Based on this benchmark, the study further optimizes the mooring forms and numbers for the same platform, analyzing four, six, and eight single mooring lines, as well as three groups of single-line, double-line, and triple-line mooring configurations. Finally, using AQWA software (2024 R1), the responses and mooring line forces of different mooring configurations were calculated, and the preferred mooring arrangement for this stepped single-post platform was determined to be a three-group, three-line system (a total of nine mooring lines). The mooring line tension decreased substantially from the original 3.2 × 10⁶ N to 1.8 × 10⁶ N, while the dynamic response was reduced to one-sixth of its original level. Meanwhile, this study provides strong support for the utilization of offshore wind energy and the construction of offshore wind turbine platforms and mooring systems. Full article

The first golden mussel, Limnoperna fortunei (Dunker, 1857), specimens in North America were discovered on 17 October 2024 at the Port of Stockton on the lower San Joaquin River in California (United States). The golden mussel is native to southern China and is one of the highest-risk aquatic invasive species worldwide. Golden mussels colonize hard surfaces and cause significant biofouling, affecting vital infrastructure such as hydroelectric plants and water delivery systems. It spreads rapidly through hydrological connectivity and human-mediated transport, with water conveyance systems functioning as invasion highways. The Sacramento–San Joaquin River Delta is vital to endangered species and provides water to 30 million people and 790,000 ha of farmland in central and southern California, but faces severe ecological and economic threats from this invasion. The detection of golden mussels was received with concern due to their impact on ecosystems and infrastructure. One year after detection, the invasion front moved 545 km south of the initial detection site (in a straight line) into Silverwood Lake in San Bernardino County near Los Angeles. By April 2026, the invasion front had already advanced 707 km south to the Sweetwater Reservoir in San Diego County (detection date: 15 January 2026). The invasion path coincides with California’s major water delivery systems. Ballast water was the most likely introduction vector, further underscoring the inefficiency of well-intentioned ballast water management policies and the need to implement better ones. This article addresses five objectives: (1) document the introduction and current distribution; (2) highlight key invasive traits to guide management; (3) assess putative impacts in California; (4) review tested management strategies; and (5) propose an innovation-driven framework for golden mussel management. Full article

Pulsed electric field (PEF) extraction studies often report yield gains but less consistently translate them into purification-relevant metrics. This study re-analyzed a locked comparability tier of 56 solvent-matched control (CTR)-PEF contrasts from five leaf-biomass studies to map total phenolic content (TPC) uplift onto first-order downstream duty proxies. The tier was not designed as a field-wide survey, and audit logs plus dependence-aware analyses were used to reduce author bias. Across the 56 pairs, median ΔTPC% was 26.7% (IQR 12.1–35.0), with positive values in 55 of 56 contrasts. The strongest gains were concentrated at low specific energy (Wspec ≤ 0.15 kJ kg⁻¹ treated biomass) and 0–25% ethanol within this dataset. PLRI translated these uplifts into first-order processed-volume scaling at fixed capture criteria, and Pareto screening identified PLRI values of 1.18–1.73, corresponding to approximately 15–42% lower processed volume under the stated assumptions. Marker-level data were limited to two matrices (three paired observations), but SSF values > 1 (1.06–2.89) were consistent with possible composition steering. No new experiments were performed, and ballast, fouling, and downstream performance were not measured; conclusions are therefore limited to the operating envelope and are intended for screening, reporting standardization, and subsequent purification validation. Full article