Search Results (215)

Despite the growing use of FLNG in offshore gas development, LNG hose safety during tandem offloading remains a critical challenge. Existing studies often analyze mooring dynamics and hose mechanics separately, lacking a unified framework that integrates multiple failure modes. This fragmented approach leads to unclear safety boundaries and inadequate risk control. Therefore, this study proposes a multi-parameter safe operating zone threshold method based on coupled dynamic analysis. First, a three-dimensional time-domain dynamic analysis model is developed using OrcaFlex, which integrates the floating bodies, hoses, and mooring system into a unified coupling framework based on hydrodynamic theory, simulating the dynamic response of the offloading system under combined wind, wave, and current actions. Second, tension, bending moment, and curvature are selected as safety evaluation parameters. These three parameters correspond to the core criteria of typical failure modes, namely axial overload failure, ultimate bending failure, and local joint failure, respectively. By comparing them with their allowable values, the safety status of the hose under various operating conditions is determined. Finally, a coupled safety threshold analysis method incorporating both “sea state return period” and “operational vessel distance” is proposed. The results indicate that, at a fixed vessel distance, the dynamic response of the hose increases significantly with worsening sea states. Tension satisfies the safety factor requirements under most sea conditions. However, the bending moment first exceeds the limit starting from the 5-year return period, making it the primary failure control indicator. Curvature exceeds the limit notably under the 50-year return period and beyond, becoming the main risk source under extreme sea states. The safe operational vessel distances under different sea states are also calculated, systematically revealing the response patterns and failure sequences of tension, curvature, and bending moment of the LNG hose under combined wind, wave, and current actions. Furthermore, by integrating safety margin calculations, an operational classification standard comprising a safe zone, a warning zone, and a danger zone is proposed, along with the upper limits of safe vessel distance and operational windows for each sea state. The threshold determination method established in this paper can provide effective engineering support for FLNG offloading operation planning, hose selection, and operational risk management. Full article

Rapidly deployable floating bridges face coupled challenges in compact deployment, structural load-bearing, and controllable module maneuvering, which cannot be fully evaluated through a single-stage structural or hydrodynamic assessment. To close this gap, this study proposes a rigid–flexible hybrid floating bridge composed of rigid deck plates, inflatable buoyancy bladders, scissor linkages, and integrated waterjet propulsors. A multi-stage assessment was conducted through inflation and calm-water maneuvering tests, gas–solid coupled finite-element analysis, and hydrodynamic and mooring simulations. The inflation experiment revealed three stages in the inflation process of the rigid–flexible specimen, including filling, transition, and pressurization stages. A remotely controlled scale model completed longitudinal, lateral, rotational, and compound motions, demonstrating the feasibility of module-level maneuvering under manual remote control. The finite-element results showed that increasing the initial internal pressure improved the load-bearing capacity and reduced local plastic deformation of the upper deck, while further improvement became limited above 70 kPa. Under the specified wave–current conditions, the ten-module assembly exhibited maximum mooring tension, horizontal displacement, and rotation of 34.7 kN, 0.276 m, and 5.525°, respectively. These results demonstrate the potential of the proposed configuration for bearing capacity, rapid deployment, and resistance to the investigated current and wave conditions while providing a multi-stage framework for further engineering design. Full article

This paper presents a mathematical model to investigate how waves and currents interact with a flexible perforated floating membrane in finite water depth within the framework of linear wave theory. The perforated flexible membrane is modeled based on Darcy’s law and the one-dimensional string equation. The complex dispersion relation in the presence of current velocity is derived from the Green’s function technique using a fundamental source potential solution. The dispersion curve is analyzed by comparing the phase and group velocities for different water depths. Further, a physical model associated with the effect of current on a moored finite floating perforated flexible membrane integrated with a vertical wall is formulated. Then, the theoretical solution of a physical boundary value problem near a vertical rigid wall is obtained using the matching technique and the roots of the dispersion relation derived from the Green’s function technique. Numerical simulations are provided to verify the convergence of the series solution and the accuracy of the obtained analytical findings are evaluated against previously published analytical and experimental datasets. Further, several numerical results on the membrane deflection, hydrodynamic coefficients, and horizontal force on the wall for various structural parameters, mooring stiffness, and current velocities are analyzed. It is observed that the present analysis with this perforated membrane breakwater will be helpful to coastal and marine engineers to understand the influence of current velocity. Full article

HY–4A is China’s first ocean salinity remote-sensing satellite, launched into orbit in November 2024 and currently in operational service. The LASMR (L-Band Aperture Synthesis Microwave Radiometer) is the L-band synthetic aperture radiometer onboard the HY–4A satellite. This study validates the LASMR Level-2 SSS (sea surface salinity) product using in situ salinity observations from Argo floats, covering the period from November 2024 to December 2025. Global analysis indicates that the LASMR SSS retrieval uncertainties show a distinct zonal distribution, which primarily reflects the impact of sea surface temperature (SST) and sea surface wind speed on SSS retrieval accuracy. A lower SST reduces the sensitivity of brightness temperature (TB) to SSS variations, and a high wind speed degrades the sea surface roughness correction. Both factors lead to increasing uncertainties in SSS retrieval. Furthermore, atmospheric parameters including water vapor content and precipitation also affect the SSS retrieval uncertainty. The influence of water vapor may originate from its coupling with SST/wind speed and inherent uncertainties in the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data. The effect of precipitation is more complex: it increases ocean TB through rain-induced surface freshening and additional rain-induced roughening, which aliases into the satellite signal. Moreover, precipitation-enhanced vertical salinity gradients amplify the vertical representativeness error arising from the depth difference between satellite sensing and Argo measurements. Meanwhile, impacted by land brightness temperature contamination and radio-frequency interference (RFI), the SSS retrieval accuracy of HY–4A decreases significantly in coastal waters compared with the open ocean. Since the traditional buoy–satellite dual-matching method tends to overestimate uncertainties in satellite data, an Argo/HY–4A/SMAP (Soil Moisture Active Passive) triple-collocation dataset is used to estimate the LASMR SSS retrieval uncertainties. The triple-collocation method yields robust uncertainty estimates for both satellites (HY–4A and SMAP) over the global ocean and high-salinity-variability regions. In conclusion, the global uncertainty of the HY–4A LASMR SSS product is 0.35 psu. These results provide a reference for future product refinement and improvements in HY–4A SSS retrieval algorithms. Full article

Accurate brain tumor segmentation in multimodal magnetic resonance imaging (MRI) scans is essential for quantitative neuro-oncology analysis, treatment planning, and longitudinal disease monitoring. However, automatic delineation remains challenging because glioma subregions exhibit heterogeneous appearance across T1-weighted (T1), contrast-enhanced T1-weighted (T1ce), T2-weighted (T2), and fluid-attenuated inversion recovery (FLAIR) sequences; weak and irregular lesion boundaries; and severe scale variation between edema, tumor core, and enhancing tumor regions. This paper presents NeuroSPFNet, a vision–language semantic prior-guided frequency-enhanced segmentation framework for tumor subregion delineation in multimodal MRI volumes. NeuroSPFNet integrates four complementary components: a Clinical Vision–Language Prior Component (CVLPC) for category-level semantic guidance; a Frequency-Enhanced Boundary Module (FEBM) for boundary-sensitive representation learning; a Multi-Scale Lesion-Dominated Fusion Module (MLDFM) for hierarchical lesion aggregation; and a Lesion-Semantic Boundary Consistency Loss (LSBCL) for jointly constraining region overlap, boundary quality, and semantic alignment. The task-specific contribution lies in the closed coupling of shared BraTS-region semantic prototypes, gated frequency responses, lesion-weighted multiscale features, and semantic-boundary supervision within one volumetric segmentation pipeline. On the Brain Tumor Segmentation (BraTS) 2021 benchmark, NeuroSPFNet achieved Dice scores of 91.94%, 88.84%, and 85.38% for whole tumor, tumor core, and enhancing tumor, respectively, with a mean Dice of 88.72% and a mean 95th-percentile Hausdorff distance (HD95) of 3.58 mm. Ablation studies show distinct effects across subregions and metrics: semantic priors primarily strengthen tumor-core and enhancing-tumor discrimination, whereas frequency and boundary constraints primarily reduce contour error. NeuroSPFNet also attains competitive performance under the current setting, with moderate computational overhead of 42.58 million parameters, 78.60 billion floating-point operations (GFLOPs), and 265 ms per volume. Full article

This article examines the extent to which it is possible to reconstruct part of the technical knowledge employed in pre-Hispanic Andean constructions. Drawing on chronicles, colonial representations, linguistic studies, ethnography and direct architectural analysis, it demonstrates that Andean societies possessed specialised trades and a wider repertoire of tools than is commonly recognised. A central finding is the identification of gaveras—wooden moulds for making adobe bricks—whose recognition here shows that carpentry techniques were more developed than has been assumed. The poor documentation of these objects—several of them miscatalogued in Peruvian museums—has reinforced the mistaken assumption that complex construction tools were not used in ancient Peru. The study combines three approaches: direct observation of the built fabric (marks, imprints and textures that reveal construction processes), review of the Quechua vocabulary associated with tools and trades—drawn from three sixteenth- and seventeenth-century dictionaries consulted in the Langas repository of the CNRS—and comparison with current practices in Andean communities. This is complemented by a comparison with records from other cultures and a systematic search of the database of the Ministry of Culture of Peru, where plumb bobs, floats, shovels, axes, chisels and other instruments rarely analysed from a constructive perspective were located. Taken together, the article demonstrates that pre-Hispanic architecture was neither intuitive nor improvised, but the outcome of a technical tradition carried out by specialists, tools that are little known today, and construction methods based on measurement, alignment control, mortar transfer and careful surface finishing. Full article

Floating offshore wind turbines (FOWTs) have become an important structural configuration for deep-water offshore wind energy development. However, existing studies have mainly focused on towing experience for conventional offshore structures and static stability assessment, while a systematic understanding of the multi-body coupled dynamic response characteristics and hazardous response factors of large-scale FOWTs under combined wind, wave, and current loads remains limited. To address the insufficient understanding of critical hazardous response indicators in existing studies, a 10 MW semi-submersible floating wind turbine was investigated in this study. Variations in environmental loads, towline constraints, and FOWT responses during towing were incorporated into a multi-body coupled analysis framework, and the key hazardous response indicators governed by different dominant environmental factors were identified. The results indicate that increasing wind speed significantly amplifies the pitch response, with the extreme pitch angle reaching approximately −7.17° under the 24 m/s wind condition. Variations in current velocity have limited influence on response amplitudes. Wave height has the most pronounced effect on heave motion and nacelle acceleration. Under the 6.5 m wave height condition, their extreme values reach approximately −1.37 m and 1.15 m/s², respectively. Under the single-tug towing configuration, the 45° and 90° environmental directions induce pronounced lateral and yaw offsets, indicating insufficient path-keeping capability under unfavorable environmental directions. Comprehensive analysis demonstrates that pitch motion should be regarded as the primary hazardous response indicator under high wind speed conditions, while nacelle acceleration and heave motion require particular attention under high wave height conditions. Full article

Uzbekistan has rapidly expanded solar photovoltaic (PV) capacity as part of its transition toward a low-carbon energy system, supported by guaranteed purchase tariffs and an evolving regulatory framework. This paper evaluates the economic feasibility of solar PV investments in Uzbekistan through a combined ex post and ex ante analysis, focusing on both commercial-scale rooftop installations and a proposed large utility-scale floating photovoltaic (FPV) project. Ex post performance data from four commercial rooftop PV systems in Tashkent (20–304 kW) over the period 2024–2025 are analyzed using lifecycle investment appraisal metrics, including the Equivalent Uniform Annual Cost (EUAC)/LCOE framework, Net Present Value (NPV), and Internal Rate of Return (IRR), to benchmark real operating outcomes against modeled expectations. These results are subsequently used to calibrate ex ante simulations for a 491 MW FPV installation planned on the Sardoba reservoir, assessed using RETScreen Expert and a bespoke three-statement financial model incorporating detailed tax, financing, and operational assumptions. The findings indicate that commercial-scale rooftop PV projects in Tashkent operate close to the financial break-even point, with EUAC-based levelized costs of energy broadly aligned with current guaranteed purchase prices for PV electricity, resulting in near-zero NPVs. In contrast, the large-scale Sardoba FPV project demonstrates moderate but positive financial viability, with nominal IRRs of approximately 14–16% and payback periods under ten years at the prevailing tariff levels. Importantly, the monetized value of environmental externalities—primarily avoided CO₂ emissions—amounts to roughly from one quarter to a third of initial capital expenditure, materially enhancing the project’s overall economic value. The results suggest that while large-scale solar projects in Uzbekistan generate limited private financial rents, their societal benefits justify continued policy support, stopping short of additional direct subsidy disbursements but conducive to lower cost-of-capital measures. Full article

Solidago canadensis L. is a regulated invasive alien species in China and was first recorded in the wild in Jiangsu Province. Despite widespread concern regarding its distribution and ecological associations, province-wide information on its current invasion status and associated plant community patterns in Jiangsu remains limited. To fill this gap, we conducted field surveys at 165 sites across Jiangsu Province and combined hierarchical clustering, plant-community diversity analysis, species-level analysis of accompanying-plant composition, redundancy analysis, and MaxEnt modeling to evaluate invasion-intensity patterns, associated environmental and anthropogenic factors, and plant-community responses in invaded communities. Solidago canadensis was recorded throughout the province, but invasion intensity was highest in southern Jiangsu. Hierarchical clustering classified the 165 sampling sites into three invasion-intensity groups. Group A (74 sites), concentrated in southern Jiangsu, was classified as the severe invasion group and showed generally lower plant diversity within the invaded-site dataset. Group B (60 sites) represented moderate invasion. Group C (31 sites), mainly distributed in northern and coastal Jiangsu, represented light invasion and retained relatively higher accompanying-plant diversity. Within S. canadensis-invaded communities, we documented 183 accompanying plant species from 43 families. Asteraceae and Poaceae were the most species-rich families, and annual or biennial herbs were the dominant life-form category. Species-level analysis further showed that accompanying-plant composition varied significantly along the invasion-intensity gradient (PERMANOVA, R² = 0.035), suggesting that differences in S. canadensis dominance were associated with detectable shifts in local plant assemblages. Redundancy analysis indicated latitude, transportation route density, and floating population density were closely associated with variation in S. canadensis invasion indicators and associated community variables, with soil pH, precipitation of the driest month, GDP, and motor vehicle ownership also contributing to the observed pattern. MaxEnt modeling identified southern and central Jiangsu as the main climatically suitable areas. This pattern was broadly consistent with the concentration of higher invasion intensity in southern Jiangsu. Nevertheless, field records in northern Jiangsu suggest that areas with lower predicted climatic suitability should also remain under continued monitoring. These findings suggest the need for coordinated management, particularly along major transportation corridors and in highly disturbed urban habitats. Control efforts should combine zoning management, source control, repeated removal, and habitat restoration tailored to local conditions. Full article

Introduction: The most common indication of chronic kidney disease (CKD) is a sudden deterioration of renal function. At that point, the only reliable test determining disease progression is the histopathological evaluation of material obtained during kidney biopsy. Although biopsy is currently the gold standard of diagnosis, the procedure is associated with a number of complications that further burden kidney function. The aim of this work is to evaluate the potential of multiparametric magnetic resonance image (MRI) in the assessment of the renal parenchyma state. Material and Methods: The study is based on kidney MRI examinations of healthy volunteers (group 1, n = 11) and patients suffering from CKD in the active phase (group 2, n = 29) or the non-active phase (group 3, n = 14), as confirmed by kidney biopsy. The T1-weighted images, T2-weighted images and DWI images were extracted and used to create algorithms, based on Support Vector Machine and Sequential Floating Forward Search, aimed to differentiate defined groups. Results: The final algorithms obtained the following metrics: for T1-weighted images, analysis–precision 91.5%, sensitivity 89.6%, specificity 94.8%; for T2-weighted images, analysis–precision 80.2%, sensitivity 79.0%, specificity 89.5%; for DWI images, analysis–precision 82.3%, sensitivity 82.1%, specificity 91.0%; and for multiparametric MRIs, analysis–precision 90.9%, sensitivity 90.4%, specificity 95.2%. Conclusions: Texture analysis of multiparametric MRI seems to have diagnostic potential in CKD and its development may reduce the frequency of invasive procedures such as kidney biopsy. Full article

Since 2011, massive strandings of pelagic Sargassum have become a recurrent environmental hazard across the tropical Atlantic and Caribbean archipelago, creating an urgent need for reliable short-term drift forecasts to support coastal risk management. This study evaluates key sources of uncertainty in operational Sargassum drift forecasting by analyzing the sensitivity of Lagrangian simulations to the representation of floating material and to environmental forcing fields. The analysis uses two complementary observational datasets: trajectories of four GPS-tracked Sargassum mats deployed near Puerto Rico and thirteen 24 h displacement vectors derived from sequential Sentinel-3 satellite detections across the tropical North Atlantic. Drift simulations were performed with the MOTHY model under multiple configurations, testing two material parameterizations, different atmospheric forcings, and several ocean circulation products and vertical current integration strategies. The results indicate that the best agreement with observed trajectories is obtained for partially immersed structures, highlighting the importance of balancing wind exposure and hydrodynamic drag. Sensitivity experiments further show that ocean circulation forcing dominates trajectory skill, while higher-resolution atmospheric forcing provides limited improvement under offshore conditions. Overall, the study confirms the importance of accurately representing upper-ocean transport processes and provides observational support for several operational choices implemented in the Météo-France Sargassum forecasting system. Full article

Federal post-quantum cryptography migration is scoped around three categories of cryptographic assets: libraries, protocols, and key stores. We argue that this scoping is incomplete. Cryptographic functions and key material can be realized in the parameters of machine-learning models, and the current open-source serialization-focused scanners we evaluated do not detect them. We provide an existence proof: a 30-layer feed-forward ReLU network that realizes AES-128 exactly, with the master key and all eleven round keys resident directly in the layer bias vectors and recoverable by parsing. The construction validates bit-exactly against FIPS 197 and the NIST CAVP AESAVS known-answer subsets across 10⁴ random plaintext-key pairs, including under float32 quantization. We argue analytically—by a sizing analysis rather than empirical construction—that ML-KEM and ML-DSA private keys hide more comfortably in modern weight tensors than AES keys do. The basis is twofold: larger key sizes amortize the construction’s fixed parameter overhead, and the lattice arithmetic underlying these primitives admits more architectural variation than the rigid AES key schedule. Under the harvest-now-decrypt-later threat model, the consequence is direct: any long-lived cryptographic key embedded in an open-weights model artifact distributed today is recoverable by any future party with knowledge of the embedding scheme, with no quantum capability required. We propose an audit primitive—a parameter-space cryptographic recognizer—that screens model artifacts at ingestion through four stages: structural matching against cipher fingerprints, a parametric analysis for bias-and-sign coupling signatures, functional probing for cryptographic input–output behavior, and the integration with cryptographic bill-of-materials tooling as a parameter-resident cryptographic content emission class extending the MBOM-PQC schema. The recognizer is defense-in-depth: it closes the gap for known constructions and architectural fingerprints without claiming completeness against adaptive adversaries. We make no claim that any deployed model contains such an embedding; the contribution is the existence of the capability, the absence of detection in the scanners we evaluated, and the migration-scope consequence. Full article

Given South Korea’s acute land constraints and ambitious renewable energy targets, floating solar farms (FSFs) on multi-purpose dam reservoirs offer a sustainable land-sparing solution for advancing the water-energy nexus and climate adaptation. This study estimates households’ willingness to pay (WTP) for a tariff premium supporting FSFs on multi-purpose dam reservoirs—a bundled sustainability attribute encompassing land-sparing deployment, water-energy nexus synergies (90% evaporation reduction, hydropower complementarity), and avoided land-use conflicts—relative to equivalent electricity from land-based solar farms (LSFs). The valuation scenario explicitly frames FSFs as an integrated policy package, not an isolated engineering characteristic, with balanced disclosure of location-specific trade-offs. The study highlights the sustainability value of land-sparing water-energy nexus solutions in South Korea. The analysis draws on a nationwide contingent valuation survey of 1000 households conducted from mid-April to mid-May 2025. Employing the one-and-one-half-bound dichotomous choice format with a spike model to handle zero WTP responses, we estimate a mean tariff premium of KRW 26.8 (USc 1.9) per kWh—17% of the residential rate. This exceeds the current FSF-LSF levelized cost differential (KRW 19 per kWh), despite 49% zero bids largely from protest responses. Socioeconomic factors (education, income, female gender, metropolitan residence, policy awareness) significantly shape acceptance probabilities. These findings affirm meaningful support for FSF deployment, contributing to long-term sustainability by integrating renewable energy with water resource management and reducing land-use conflicts. They also inform sustainable energy transition policies by showing that consumers are willing to fund multifunctional infrastructure synergies. Full article

A hydroelastic theoretical model is formulated, and an analytical solution is obtained to investigate the interaction between wave-opposing current loading with compression and a moored floating flexible platform within the framework of Timoshenko–Mindlin beam theory based on the linearized wave and small structural response. By employing the matching technique and orthogonal mode-coupling relation, the closed-form analytical solutions for structural displacement, as well as shear force and bending moment, are obtained. The wave blocking and buckling limit in the presence of compressive force against an opposing current is determined via group and phase velocities from the dispersion relation in the context of the Timoshenko–Mindlin beam theory. Further, the combined influence of opposing current, compressive loading, and key structural design parameters on the hydroelastic response are examined. The results demonstrate that opposing currents and compressive forces can significantly alter the hydroelastic response, highlighting their critical role in structural engineering analysis. The current analysis provides a comprehensive analytical framework that can support the design and optimization of floating flexible platforms in the presence of opposing currents and compressive loads in complex marine environments. Full article

Optimization Modulo Theory (OMT) is an important extension of Satisfiability Modulo Theory (SMT), aiming to find models that satisfy constraints while optimizing objective functions. OMT naturally arises in program analysis and formal methods, making OMT solving an important and challenging task. OptiMathSAT is currently the state-of-the-art OMT solver supporting floating-point theories. It incrementally calls an SMT solver to prune the search space step by step until the optimal objective value is found. However, this frequent invocation of the SMT solver is highly inefficient. Therefore, this paper proposes a novel hybrid method consisting of two stages: coarse search and precise search. The coarse search stage quickly finds an approximate optimal model using an optimization search algorithm. The precise search stage then performs an SMT-based binary search starting from the approximate model to find the true optimal model (the OMT solution). Evidently, this hybrid approach reduces computational cost by rapidly shrinking the search space, thereby improving overall solving performance. We evaluated our method on benchmarks derived from SMT-LIB2 and real-world programs. Experimental results show that our method outperforms the current state-of-the-art in both effectiveness and efficiency. Full article