Search Results (905)

Elasmobranchs play a major role in shaping the structure and functioning of marine ecosystems through their position in food webs. The Lusitanian cownose ray Rhinoptera marginata, a benthopelagic species classified as Critically Endangered on the IUCN Red List, is frequently landed in fisheries off the Mauritanian coast, yet its trophic ecology remains poorly documented. We investigated the diet of R. marginata along the coast of Nouadhibou through stomach content analysis of 308 individuals sampled between March 2022 and August 2023; 135 stomachs (66 females and 69 males) contained identifiable prey and formed the basis of the analyses (disc width range 33–87 cm). Common dietary indices (frequency of occurrence, numerical and gravimetric percentages, Pinkas’ IRI, Hureau’s Q) were combined with multivariate approaches (PERMANOVA on Bray–Curtis dissimilarities, SIMPER, non-metric multidimensional scaling), measures of trophic niche breadth and specialization (Levins’ standardized index Bi, Shannon H′, Pielou’s J′, modified Costello plot), niche overlap (Pianka and Schoener indices), and ontogenetic modelling (generalized additive models). A total of 33 prey taxa were identified, dominated by Bivalvia (86.1% IRI), followed by Gastropoda (6.9%) and Crustacea (6.7%). The species exhibited a strongly specialized feeding strategy (Levins Bi = 0.06; Shannon H′ = 1.42) with high niche overlap between sexes (Pianka = 0.89). PERMANOVA detected significant compositional differences across seasons (pseudo-F = 6.98, p < 0.001) and size classes (pseudo-F = 4.98, p < 0.001) but not between sexes (pseudo-F = 1.87, p = 0.077). The proportion of bivalves significantly decreased with body size (R² = 0.176, p < 0.001), revealing a clear ontogenetic shift towards more diversified prey in larger individuals. The estimated trophic level (3.13) confirms a mesocarnivore benthic position. These results provide the first comprehensive description of the diet of R. marginata in West Africa and highlight its role as a specialized durophagous predator of bivalve molluscs, omnipresent along the northern Mauritanian coastal ecosystems. By identifying the principal prey, our findings provide a basis for identifying potentially important foraging habitats for this Critically Endangered species and informing future conservation and management strategies. Full article

Accurate short-term significant-wave-height forecasting is important for the safe and efficient operation of coastal and offshore activities. However, forecasting across sparse buoy networks remains challenging because wave conditions exhibit complex temporal variability and spatial dependence. This study proposes an Enhanced Crossformer, a dual-tower spatiotemporal framework that combines a Crossformer branch for modelling long-range inter-station dependencies with a Cheb–LSTM branch for capturing localised graph-based interactions. The framework was evaluated using 3-hourly significant-wave-height observations from 52 National Data Buoy Centre stations along the U.S. West Coast over the period 2020–2024. Missing observations were first estimated using a graph neural network imputation model, which achieved test-set $R^2$ values ranging from 0.85 to 0.95 on artificially masked observations. Forecasting performance was then assessed for lead times of 3–24 h and compared with LSTM, Transformer, Cheb–LSTM, and Crossformer baselines. The Enhanced Crossformer achieved the lowest MAE, MSE, and MAPE values and the highest $R^2$ and correlation values at all forecast steps. Relative to the strongest baseline, it reduced MSE by up to approximately 8.7% at short lead times and maintained positive improvements through the 24 h horizon. Forecast skill was strongest under low-to-moderate sea states but decreased for high-energy wave conditions and several sheltered stations in the Southern California Bight. These results demonstrate the potential of combining global attention with graph-based local recurrence for short-term multi-buoy wave forecasting. Full article

Research suggests that anxiety predicts student performance, and that this relationship is mediated at least in part through self-defeating behavior. However, the nature of this relationship has yet to be fully understood. While substantial research has characterized the ways that anxiety affects student performance directly, at the point where it occurs (e.g., test anxiety, stage anxiety), less research has addressed the ways anxiety affects student performance indirectly, as students prepare for a performance. The first type is commonly referred to as performance anxiety. We refer to the second as preparation anxiety, and suggest that it is a necessary counterpoint, and that the relationship between anxiety and student outcomes cannot be fully understood without it. In the present study, we seek to characterize preparation anxiety, distinguishing it from performance anxiety and developing a scale to measure it: The Preparation Anxiety Scale (PAS). We report three studies, each conducted with undergraduate students at a large west-coast university: In the first study, focus groups were conducted to generate items representing the preparation anxiety construct. In the second study, exploratory factor analysis identified a 32-item, three-factor solution, with factors assessing affective nerves (PAS-AN), behavioral avoidance (PAS-BA), and cognitive agitation (PAS-CA). The scale displayed good test–retest reliability and demonstrated adequate convergent and discriminant validity. In the third study, confirmatory factor analysis supported the three-factor solution and bifactor analysis indicated a strong general factor, supporting the use of a summary score. Further analyses demonstrated both criterion and incremental validity, showing that the PAS and its subscales predict relevant behaviors (procrastination), correlates (academic self-efficacy), and outcomes (GPA) beyond other constructs. Additionally, regression analysis reveals a suppressor relationship: When the PAS-BA and PAS-AN subscales are controlled for, the PAS-CA subscale emerges as a negative predictor of procrastination and a positive predictor of academic self-efficacy. Full article

This study investigated seasonal variation in tissue growth, reproductive status, energy reserves, and digestive tubule condition in the Pacific oyster, Magallana gigas, cultured in an off-bottom intertidal rack system in Garorim Bay on the west coast of Korea. Monthly samples of adult oysters were collected from February 2009 to December 2010. Condition index (CI), total carbohydrate content, reproductive stage, female reproductive effort estimated by indirect enzyme-linked immunosorbent assay (ELISA), and digestive tubule atrophy (DTA) were measured concurrently in individual oysters. Gametogenesis was largely synchronized between sexes and was strongly associated with seasonal sea surface temperature ($r=0.84$, $p<0.0001$). Carbohydrate content peaked in early spring and declined during the spawning season. In females, carbohydrate content was negatively correlated with gonad somatic index (GSI) ($r=-0.30$, $p<0.0001$), suggesting that oysters investing more heavily in egg production tended to have lower remaining carbohydrate reserves. GSI showed interannual variation in spawning timing, peaking at 37.9% in June 2009 and 37.0% in July 2010. DTA showed temporal variation, with relatively elevated values in late summer–early autumn 2009 and mid-winter 2010. The late-summer 2009 increase in DTA coincided with a marked decline in salinity; however, monthly mean analyses did not establish a causal relationship between salinity and DTA. Together, these results indicate that the seasonal physiological condition of intertidal rack-cultured oysters reflects a dynamic balance between reproductive investment, carbohydrate reserves, and digestive gland condition, with this balance potentially modified by seasonal environmental variability. These results provide a cross-sectional, multi-parameter baseline for seasonal monitoring of reproductive status, energy reserves, and digestive tubule condition in intertidal rack-cultured oysters in Garorim Bay. Full article

With increasing extreme rainfall, assessing whether emergency shelters remain accessible and functional during flood-constrained evacuation is essential for enhancing urban flood resilience. However, flood simulation, evacuation behavior, shelter suitability, and spatial accessibility are often examined separately, leaving the relationship between shelter reception performance and pre-disaster spatial support insufficiently clarified. This study evaluates emergency-shelter evacuation-support capacity in the Qingdao West Coast New Area under a 100-year, 24 h design rainstorm scenario. InfoWorks ICM was used to simulate two-dimensional surface inundation without explicitly resolving the sewer-pipe network, and hourly inundation depths were coupled with NetLogo to model evacuee movement, road passability, and shelter reception performance. An entropy-weighted TOPSIS model was applied within the 800 m road-network service areas of 20 shelters, comprising the 10 highest- and 10 lowest-arrival shelters. Results show that widespread shallow inundation coexisted with localized deep-water accumulation, and shelter reception performance varied substantially. Higher simulated arrivals did not necessarily indicate stronger evacuation-support capacity. Within the selected sample, parks and green spaces and intersection density received relatively higher weights. Four representative shelter cases were identified—core load-bearing, high-pressure risk, potential improvement, and inefficient vulnerable—providing a process-based basis for emergency shelter assessment and urban flood resilience enhancement. Full article

Ichthyoplankton provide critical insight into spawning activity, recruitment potential, and environmental drivers shaping fish populations. Despite their ecological importance, broad-scale ichthyoplankton studies in the Adriatic Sea remain limited. We analysed ichthyoplankton assemblages across the eastern Adriatic Sea, precisely five study areas—west coast of Istrian peninsula (I), Kvarner and Kvarnerić (K), northern middle Dalmatia (Z), wider area of Jabuka Pit (J), and southern Dalmatia (D), during two consecutive summers (2019–2020), combining plankton sampling using WP2 with DNA barcoding to improve taxonomic resolution. A total of 1382 eggs and 407 larvae were identified, representing 20 families and 34 species. Pelagic taxa dominated the assemblage, with anchovy (Engraulidae) accounting for more than 80% of ichthyoplankton. Spatial patterns revealed consistently higher abundances in Kvarner and Kvarnerić, the wider Jabuka Pit area, and southern Dalmatia—regions characterized by enhanced productivity, retentive circulation, or upwelling. Alpha biodiversity indices indicated high interannual similarity, while ANOSIM and SIMPER analyses confirmed significant differences (p < 0.05) among regions, driven primarily by Engraulidae and secondarily by Bothidae, Pomacentridae, Scombridae, Serranidae, and Sparidae. Redundancy analysis showed that temperature and chlorophyll-a were key environmental drivers influencing both pelagic and coastal taxa. These findings provide essential baseline information on ichthyoplankton dynamics in the eastern Adriatic Sea and highlight key spawning and nursery areas relevant for fisheries management. This study also demonstrates the value of integrating DNA barcoding with ecological analyses to strengthen ichthyoplankton monitoring in a rapidly changing marine environment. Full article

Objective: Despite most often used in research and medicine, it is unclear how well blood metabolite levels can reflect metabolic changes in tissues. Methods: We used untargeted metabolomic data from plasma, liver, gastrocnemius muscle, kidney, inguinal fat, and gonadal fat tissues from mice treated with lifespan-extending interventions: caloric restriction, rapamycin, canagliflozin, 17-α estradiol, and acarbose. Results: For each tissue, about 37% of the identified metabolites were also found in plasma and used for comparative analyses. We found that plasma metabolites do not primarily reflect the metabolome of a single tissue type. Caloric restriction caused the highest proportion of significantly altered metabolites detected in both organs and blood. Unsaturated triacylglycerols, diacylglycerols, amino acid-derivatives, and sphingomyelins had the most concordant overlaps between four tissues and plasma, followed by carbohydrates with three tissue/plasma intersections. Concordant plasma/tissue changes were found more pronounced in male mice than in female mice. Surprisingly, many compounds that responded similarly to lifespan-extending treatments in tissues and in plasma originated from dietary compounds, specifically, ergothioneine, DHA-containing fats, and diacylglycerides. Ergothioneine, previously associated with healthy aging in humans, showed concordant treatment responses in blood and all tissues except gonadal fat. DHA-containing fats showed consistent regulation between blood and inguinal and gonadal adipose tissue. The kidneys showed coherent trends with blood metabolite levels for LPC 15:0, LPC 17:0, and pinitol. Under treatments with strong life-extending effects, 1,5-anhydro-glucitol blood levels were co-regulated with both liver and kidney levels. Conclusions: Overall, plasma can only serve as limited proxy for tissue metabolism. Yet, several potential blood biomarkers were discovered as concordant in plasma and tissues in lifespan-extending interventions. Full article

Background: Inverted-bearing reverse total shoulder arthroplasty (rTSA), using a polyethylene glenosphere with a metal humeral liner, may reduce polyethylene wear, osteolysis, and scapular notching. This study evaluated long-term survivorship, complications, radiographic findings, and clinical outcomes of a large-glenosphere inverted-bearing rTSA design. Methods: A retrospective single-surgeon cohort included 394 primary rTSAs (363 patients; mean age 73.8 ± 8.5 years) performed between 2006 and 2018 using the same implant system. Clinical follow-up was available for 123 patients at a mean of 9.4 years. Outcomes included ASES, Oxford Shoulder Score (OSS), Subjective Shoulder Value (SSV), and pain VAS. Radiographs obtained at ≥8 years were assessed for scapular notching, glenoid loosening, and humeral osteolysis/stress shielding. Kaplan–Meier survival analysis was performed. Results: Thirty of the 257 rTSAs with revision follow-up (11.7%) underwent revision, most commonly for glenoid loosening or instability. Among patients with long-term radiographs, scapular notching occurred in 8.3% of all-polyethylene glenospheres and was limited to grade 1. Humeral osteolysis/stress shielding was present in 36%, although no humeral components were revised for loosening. Median final follow-up PROMs were ASES 75.8, OSS 42, SSV 78, and pain VAS 1. Conclusions: Large-glenosphere inverted-bearing rTSA demonstrated satisfactory long-term outcomes, low notching rates, and acceptable survivorship. The favourable notching profile should be interpreted in the context of the larger eccentric glenosphere design, which precludes attribution of this finding to bearing material alone. Full article

Emerging industrial agglomeration drives green transformation through knowledge spillovers and economies of scale. However, its effects exhibit pronounced nonlinearity and heterogeneity, shaped by spatial externalities and development stages. This paper investigates 19 Chinese urban agglomerations over the period 2014 to 2023. Kernel density estimation based on enterprise-level Point-of-Interest (POI) data is used to characterize spatial agglomeration patterns across eight emerging sectors. A two-stage dynamic network super-efficiency SBM model decomposes Green Transition Efficiency (GTE) into resource utilization and pollution control sub-stages. An XGBoost-SHAP-GEO analytical framework, combined with partial dependence analysis, then identifies nonlinear driving mechanisms. The main findings are as follows: First, emerging industrial agglomeration intensifies and polarizes toward the eastern coast, whereas GTE displays a “high-west, low-east” pattern. This produces a significant spatial mismatch, rooted in the near-saturation of environmental carrying capacity in eastern regions, where congestion effects exceed knowledge spillover dividends. Second, geographic characteristics constitute the primary factor shaping GTE and operate through nonlinear interactions with industrial agglomeration and R&D investment. Notably, their moderation direction is reversible, suggesting that geographic endowments should be understood as “conditional assets” rather than fixed advantages. Third, nonlinear patterns across sectors are highly heterogeneous. The bio-industry is the only sector to achieve a J-shaped positive breakthrough. Information technology and new materials exhibit persistent inhibition, while related services display an extremely narrow threshold window with the deepest negative reversal. Thus, “moderate agglomeration” is a multidimensional concept that shifts dynamically with industry type and regional endowment. Fourth, driving mechanisms display stage-dependent evolution. The incubation stage relies on natural endowments and basic industrial pull, with the green bottleneck residing in resource utilization efficiency. The growth stage faces multiple tensions from coexisting positive and negative effects. The optimization stage shifts toward R&D innovation and industrial greening, marking a qualitative transformation from MAR externalities to Jacobs externalities. In addition, the non-significant linear coefficient in the 2SLS instrumental variable test is consistent with the inverted U-shaped nonlinear finding, further validating the necessity of a nonlinear analytical framework. These findings provide differentiated governance evidence for balancing industrial agglomeration with green sustainable development. Full article

The spatial organization of public service facilities within transit-oriented development TOD blocks is closely related to residents’ daily travel conditions and travel-related carbon emissions. This study examined all 172 operating metro station areas in Qingdao using public service facility POIs, buildings, pedestrian road network and population data, field observations, and a resident travel survey. K-means clustering, spatial syntax analysis, Global Moran’s I, spatial regression, FDR-adjusted Pearson correlation analysis, and scenario simulation were jointly applied. Four facility layout types were identified: Spatially Balanced Type, Main-Road-Concentrated Type, Point-Concentrated Type, and Scattered-and-Disordered Type. The survey included 240 valid respondents distributed across all 41 station areas along Qingdao Metro Line 1. The Spatially Balanced Type had the lowest mean weekly per capita travel carbon emissions, followed by the Main-Road-Concentrated Type, whereas the Point-Concentrated and Scattered-and-Disordered types had similarly higher emission levels. The density and accessibility of Commercial and Entertainment facilities, Medical and Health facilities, and total facilities remained negatively associated with travel carbon emissions after FDR correction. Spatial syntax analysis showed that higher road network integration and connectivity were associated with stronger facility agglomeration. Facility density, road density, and population density exhibited significant positive network-based spatial autocorrelation, and the spatial error model provided the best fit, identifying positive associations of facility density with road density and population density. Based on these findings and field observations, three differentiated renewal pathways—node embedding, proximity coordination, and intensive integration—were proposed. Under the specified scenario, a 20% increase in facilities was associated with modeled reductions in aggregate weekly carbon emissions of 32.3% in Li Village, 28.1% in the University of Petroleum station area, and 33.0% in Jinggangshan Road. These results suggest that improving overall facility coverage may support lower-carbon travel across different facility layout contexts. This study connects facility layout typology, spatial structure, travel carbon emission associations, and differentiated renewal strategies at the TOD-block scale. Full article

Liquid chromatography–hydrogen/deuterium exchange–mass spectrometry (LC-HDX-MS) provides orthogonal structural information that complements conventional LC-MS and improves confidence in small-molecule structural elucidation. Although HDX-MS is well established in protein research, its application to small molecules remains less developed, and practical guidance for experimental implementation and data interpretation is limited. Here, we evaluate major LC-HDX-MS strategies, including post-column co-infusion, partial HDX, and full HDX approaches, and assess their analytical performance using reference standards and NIST SRM 1950 human plasma. The effects of deuterated mobile phases on background contamination, labeled/unlabeled signal ratios, retention-time shifts, adduct chemistry, and mass spectral interpretation are examined, and currently available software tools for LC-HDX-MS data processing are discussed. Full HDX provided the most complete deuterium incorporation, whereas deuterated mobile phases increased background signals and generally reduced analyte responses. Retention-time shifts were typically small but should be considered when matching features. HDX-derived information provides an additional experimental structural descriptor by defining the number of exchangeable hydrogen atoms and refining adduct assignments, thereby reducing ambiguity during structural annotation. These findings provide practical recommendations for implementing LC-HDX-MS in untargeted LC-MS workflows and demonstrate its value as an orthogonal tool for small-molecule structural elucidation. Full article

This paper studies the automatic berthing control of an unmanned surface vessel under cyber attacks. An adaptive neural-network-based fault-tolerant control method is developed. Unknown vessel dynamics, external disturbances, measurement noise, and cyber attacks are considered at the same time. First, the signal scaling, bias, and power-type distortion caused by cyber attacks are described by a unified nonlinear measurement model. The model has a known structure and unknown parameters. It converts different attack effects into structured uncertainties. Based on the corrupted position and attitude measurements, the tracking errors are defined. The vessel heading is reconstructed by integrating the unaffected yaw-rate signal. A Nussbaum-type function is introduced to handle the unknown gain in the measurement channel. A first-order filter is used to generate a smooth approximation of the virtual control signal. A neural network is then employed to approximate the unknown vessel dynamics. Adaptive laws are designed to estimate the composite uncertainties and external disturbances. Lyapunov analysis shows that all closed-loop signals remain bounded. The berthing tracking errors ultimately converge to a compact set around the origin. Finally, a berthing simulation with time-varying cyber attacks, measurement noise, and marine disturbances is conducted to evaluate the proposed method. Full article

Hypersaline semi-enclosed seas impose physiological constraints on marine bivalves by increasing osmotic regulation costs and limiting somatic growth. This study examined life-history variation in natural populations of the pearl oyster Pinctada radiata across contrasting salinity regimes along the eastern and western coasts of Bahrain in the Arabian Gulf. Environmental conditions, shell morphometrics, growth modeling, oocyte abundance, physiological condition indicators, and the production-to-biomass ratio (P:B) were assessed to determine whether high salinity constrains somatic growth while reproductive persistence is maintained. Monthly surveys were conducted from June 2021 to May 2022 at one pearl oyster bed on each coast, comprising 12 surveys per coast. The two coasts formed a salinity gradient, averaging approximately 42‰ in the east and 55‰ in the west. Oysters from the western coast were smaller, with a mean shell height decreasing from 63.12 ± 6.47 mm in the east to 45.88 ± 3.41 mm in the west. The Gompertz model indicated a lower asymptotic shell height in the more saline population. The population-level P:B ratio was 0.23 yr⁻¹ on the eastern coast and 7.46 yr⁻¹ on the western coast. Despite reduced shell size, western oysters maintained strong seasonal oocyte abundance. The higher biomass turnover in the west partly reflected greater oyster density. This pattern is consistent with osmoregulatory costs and constrained shell biomineralization under chronic hypersalinity. Reproductive activity followed a bimodal pattern on both coasts. These findings are consistent with a life-history trade-off in which pearl oysters exposed to chronic salinity stress maintain reproductive activity despite constrained growth. Overall, this study links environmental forcing, growth limitation, population-level biomass turnover, and reproductive activity, providing field-based evidence that chronic hypersalinity constrains somatic growth while reproductive persistence is maintained in a benthic bivalve inhabiting hypersaline coastal systems under climate-related stress. Full article

Black-sand mining is an under-studied anthropogenic pressure on arid coastal environments, where sparse vegetation and slow natural recovery limit conventional impact assessment. Despite the recent expansion of heavy-mineral extraction along the Mauritanian coast, no spatio-temporal analysis has quantified its effects on land cover and surface-water dynamics in the N’Diago region. We analysed the N’Diago–LGUWYCHICH coastal sector (south-western Mauritania) using three Landsat scenes (2014, 2020, and 2026) in QGIS (free and open-source Geographic Information System), four spectral indices (NDVI-Normalized Difference Vegetation Index, NDWI-Normalized Difference Water Index, BSI- Bare Soil Index, and CI -Coloration Index), supervised Support Vector Machine classification and a 30 m SRTM Digital Elevation Model over a 97.82 ha area of interest. Bare soil dominated the landscape at every date (92.6–95.7%) and vegetation stayed below 7%, indicating that canopy-based metrics underestimate disturbance in this setting. The clearest change was hydrological: an inland water body shrank from 1.02 ha in 2020 to 0.40 ha in 2026, a 60.6% loss. This individual inland water body, measured directly and independently from the NDWI index, is our primary hydrological observation: the wet feature was smaller in the 2026 image than in the 2020 image and was located near the mapped concession areas, but the available data do not establish the cause of this change. Similar bare-soil and colour index values (BSI ≈ 0.23, CI ≈ 0.79–0.80) were observed in the processed images, while residual seasonal and radiometric differences between the Landsat 8 and DOS-corrected Landsat 9 products cannot be excluded; BSI and CI are treated only as candidate or contextual spectral patterns, so any delineation of the disturbed footprint is provisional and requires confirmation from independent field data. This study illustrates a low-cost exploratory workflow that may support preliminary monitoring in data-scarce arid coastal settings, pending validation with denser time series and field observations. Full article

Seawater intrusion (SWI) represents an increasingly critical challenge for coastal groundwater systems, with particularly pronounced impacts observed along the Indian coastline. Coastal aquifers constitute a vital freshwater resource supporting domestic, agricultural, and industrial demands. This study evaluates SWI vulnerability along the entire Indian coast, extending from Gujarat to West Bengal, covering approximately 7517 km of shoreline and up to 100 km inland. The assessment applies the GALDIT vulnerability framework that combines several hydrogeological and hydrochemical criteria such as groundwater occurrence, aquifer hydraulic conductivity, depth to groundwater, distance from shoreline, hydrochemical data, and groundwater quality data. We also assessed the intrusion of existing seawater, shoreline location, and aquifer thickness. However, conventional vulnerability assessments are inherently static and often fail to capture anthropogenic influences. To address this limitation, the present study integrates multi-temporal land use and land cover (LULC) datasets derived from ESA WorldCover remote sensing data for the period 2017–2024. Incorporating LULC dynamics enables a more comprehensive evaluation of the impacts of urban expansion and agricultural intensification on coastal susceptibility to SWI. Accordingly, a modified GALDIT-LU framework is developed to assess the spatiotemporal evolution of coastal vulnerability. The outcomes suggest that huge parts of the Indian coastline are vulnerable to moderate or very high classes, with the very high vulnerability class growing from 13,295 km² in 2017 to 38,257 km² in 2024, a 188% increase in vulnerability over the course of seven years. Groundwater chloride concentrations from Central Ground Water Board (CGWB) monitoring well locations have been used for validation over the proposed assessment, and show good spatial agreement between areas identified as high vulnerability and the spatial distribution of groundwater salinity for all three assessment periods, lending support to the robustness and predictive power of the proposed groundwater salinity assessment. The findings carry direct implications for the United Nations 2030 Agenda, demonstrating that the identified vulnerability patterns intersect with critical targets related to clean water and sanitation, food security, public health, climate action, and poverty reduction along one of the world’s most densely populated coastlines. Full article