Search Results (591)

Introduction: Estuaries are among the most productive ecosystems in the world, holding great ecological and economic importance. As transitional zones between rivers and the sea, they experience abrupt abiotic changes linked to the tidal cycle, as well as seasonal changes related to greater river discharge during periods of higher rainfall. Therefore, salinity and temperature are key factors in structuring communities. These estuarine areas are recognized as nursery grounds, offering an abundance of food and shelter from predators, which creates ideal conditions for juvenile growth. Objective: Intense heatwaves were recorded in northern Spain during 2021 and 2022. This study aimed to understand how environmental factors influence the daily and seasonal dynamics of epibenthic communities and to compare these results with those obtained 40 years ago. Methodology: The epibenthic community in the Minho River estuary was assessed between September 2021 and August 2022 during spring tides at both low tide and high tide. Five trawls were carried out at each tide using a 2-meter-wide beam trawl. Several physical and chemical parameters were evaluated during the sampling process. Results: A total of 10,527 demersal fish and epibenthic crustaceans belonging to 21 species were caught in the sampling area. The structure of epibenthic assemblages was heavily influenced by tidal regimes. Assemblages at low tide had a greater number of taxa. In contrast, high-tide assemblages exhibited significantly higher diversity and evenness. Significant differences were observed between the spring/summer and winter assemblages. A SIMPER analysis revealed that Carcinus maenas contributed most to assemblage dissimilarity, both seasonally and by tide. Furthermore, Echiichthys vipera and Platichthys flesus were the species that contributed most to assemblage dissimilarity in both 1982 and 2021–2022. Conclusions: Compared with historical data, the rise in temperature and salinity, coupled with reduced water flow, has caused a profound restructuring of benthopelagic communities. This is driven by a significant increase in the marine character of the habitat. Substantial taxonomic turnover is evident, characterized by reductions in abundance and increases in the number of taxa sampled, as well as in diversity and evenness. Full article

Accurate coastline extraction in muddy and macro-tidal environments is challenging due to tidal variability and complex coastal surfaces. The Jiangsu coast of China, characterized by extensive tidal flats, silty coastlines, and strong land–sea interactions, provides an ideal case for long-term coastline change analysis. This study investigates the spatiotemporal evolution of the Jiangsu coastline from 2018 to 2025 using multi-temporal Sentinel-2 imagery. A tide-independent coastline extraction framework was developed by integrating the Normalized Difference Water Index, Modified Normalized Difference Water Index, and Normalized Difference Vegetation Index for different coastal environments. An annual maximum spectral index composite was applied to approximate the highest water-level conditions without explicit tidal correction. Coastline dynamics were quantified using fractal dimension analysis and a transect-based method. The extracted coastlines yielded an average Root Mean Square Error (RMSE) of 13.14 m and an average Mean Absolute Distance Error (MADE) of 9.39 m. Results show that the total coastline length varied within 5% during the study period, with a maximum of 1079.84 km in 2022 and a minimum of 1004.99 km in 2018. Coastline change was dominated by erosion, accounting for 56.21% of the total coastline length. Land cover analysis revealed that accretion mainly occurred near river mouths and aquaculture areas, whereas erosion was more common at interfaces between forested land and engineered coastlines. The proposed framework provides an efficient and consistent approach for short-term coastline monitoring in muddy coastal environments. Full article

Red tide events pose substantial threats to marine ecosystems, aquaculture, and coastal public health. Timely and accurate delineation of red tide extent from satellite imagery is therefore essential for operational monitoring and early warning. However, existing deep learning-based semantic segmentation methods generally treat multispectral bands as homogeneous inputs and do not fully exploit the domain knowledge embodied in spectral indices commonly used in traditional remote sensing analysis. To address this limitation, this study proposes a spectral-index-guided network (SIG-Net) that explicitly incorporates spectral-index priors into deep feature extraction through a dual-branch architecture. SIG-Net comprises three components: a spectral encoder based on a Mix Vision Transformer (MiT-B2) that learns spatial-spectral representations from the original Sentinel-2 bands; a lightweight CNN-based index encoder that extracts discriminative features from four spectral indices, namely the red-green index (RGI), blue-green index (BGI), normalized difference vegetation index (NDVI), and the normalized difference Noctiluca index (NDNI) proposed in this study; and a spectral-index-guided fusion (SIGF) module that adaptively integrates multi-scale features from the two branches using spatial-reduction cross-attention and a gated fusion mechanism. Experiments on a Sentinel-2 red tide dataset show that SIG-Net outperforms single-branch baselines, including U-Net, DeepLabV3+, and SegFormer, as well as naive multi-source fusion strategies. Ablation studies further confirm the contributions of the SIGF module, the gating mechanism, and the proposed NDNI to performance improvements. The proposed method provides an effective framework for integrating domain knowledge with deep learning for red tide remote sensing monitoring. Full article

The UNESCO World Heritage coastal zone of Cinque Terre (Liguria, northern Italy) is increasingly threatened by ongoing sea-level rise. To assess expected sea levels up to 2150 CE under the IPCC Sixth Assessment Report (AR6), we carried out a first evaluation of potential coastal flooding for Monterosso and Vernazza under different Shared Socioeconomic Pathways (SSPs), integrating high-resolution topography and bathymetry, geodetic data, historical tide-gauge evidence, and storm-surge modeling. The historical sea-level analysis indicates a non-stationary rising trend for the Ligurian sector. Relative sea-level rise (RSLR) projections were computed for SSP1-2.6, SSP3-7.0 and SSP5-8.5, including local land subsidence, and were used to map the potential inundated areas for 2030, 2050, 2100, and 2150 CE. In 2150, projected RSLR is expected to range from 0.60 m to 1.17 m, corresponding to flooded surfaces of 9931 m² and 22,079 m² in the SSP1-2.6 and SSP5-8.5 scenarios, respectively. Because site-specific long-term run-up observations are not available for formal calibration at the two study sites, the storm-surge simulations are interpreted as scenario-based hazard envelopes. Even within this framework, storm surges with return times of 1 and 100 years in the SSP5-8.5 scenario cause maximum wave run-up in the range of 5.12 m and 13.36 m. The results show that narrow pocket beaches and low-elevation harbor areas are the most critical receptors and that adaptation measures should focus on quay elevation, drainage/backwater management, and the protection of transport and tourism infrastructures. Full article

Efficient in vitro production of rabies virus is essential for vaccine development and quality control applications. High-density cultivation systems offer practical advantages for rabies virus production but also create culture conditions in which nutrient depletion, waste accumulation, and progressive deterioration of host-cell condition may limit infectious virus output. In this study, we evaluated the effects of sodium pyruvate supplementation on rabies virus CVS-11 production in Vero and BSR cells cultivated in a high-density macrocarrier-based tide-motion culture system under serum-containing and serum-free conditions, with complementary comparative observations in conventional monolayer cultures of BHK cells. Cultures were infected at a multiplicity of infection of 0.01, and infectious virus production was assessed over time, together with cell density, glucose consumption, and pH dynamics. Sodium pyruvate supplementation was associated with significantly higher infectious virus titers, delayed culture deterioration, prolonged maintenance of viable cell populations, and higher peak infectious titers in both Vero and BSR cultures. The highest infectious titers were observed under serum-free pyruvate-supplemented conditions, reaching 7.5 log₁₀ FFU/mL in Vero cells and 7.2 log₁₀ FFU/mL in BSR cells. Across the tested conditions, serum-free cultivation and pyruvate supplementation were both associated with significantly higher peak infectious titers. In contrast, exploratory correlation analysis based on condition-level summary values indicated an inverse association between minimum culture pH and peak infectious titer. Together, these findings show that sodium pyruvate supplementation can improve infectious rabies virus yield and prolong the productive phase in high-density macrocarrier-based cultures, supporting its use as a practical culture-modulation strategy for CVS-11 production in adherent cell systems. Full article

The finless porpoise (Neophocaena asiaeorientalis) is a species frequently observed in Korean coastal waters that remains highly vulnerable to bycatch and habitat disturbance. To develop effective conservation strategies, it is essential to understand their acoustic behavior and environmental preferences. This study utilized Passive Acoustic Monitoring to investigate the acoustic characteristics and activity patterns of finless porpoises in coastal waters near cage aquaculture farms from September to October 2021. A total of 372,707 clicks and 175,119 click trains were identified. Mean acoustic parameters were peak frequency 122.0 ± 11.1 kHz, 3 dB bandwidth 15.4 ± 12.0 kHz, 10 dB bandwidth 45.3 ± 16.1 kHz, and ICI 39.0 ± 34.8 ms. Click activity exhibited a distinct diel pattern, with significantly higher activity during the early morning and nighttime. Generalized Additive Model analysis revealed significant non-linear relationships between click activity and tide, temperature, salinity, and hour. Specifically, click activity decreased with rising temperatures and lower salinity, while the effect of tide was relatively limited. These findings provide critical baseline data for the development of acoustic deterrent devices tailored to Korean marine environments and contribute to the management of bycatch mitigation and coastal ecosystem conservation. Full article

Modeling historically situated gender ideology remains challenging for language models, as contemporary embeddings struggle to reflect temporally specific semantic structures beyond surface lexical patterns. Although large language models exhibit extensive general-purpose performance, their direct use with history-specific semantic analysis is limited by the distributional mismatch between contemporary training data and historical linguistic patterns. These constraints encourage the distillation of temporally based semantic knowledge into small student architectures. To solve this issue, we propose Temporally Informed Distillation of Embedding Semantics (TIDES), which integrates continued pretraining on temporally specific corpora with feature-level distillation from large embedding teachers. We evaluate TIDES across teacher architectures with distinct pretraining objectives. While continued pretraining provides lexical and syntactic adaptation, our results show that improvements in ideological modeling cannot be attributed to additional training exposure alone. Rather, teacher–student structural alignment is also critical to transfer effectiveness. Contrastive, encoder-aligned teachers yield substantially more stable preservation of fine-grained, historically situated semantic distinctions. These findings suggest that temporal ideology transfer is representation-dependent: ideological meaning can be shaped by the geometry and training objectives of embedding spaces. By introducing TIDES and providing evidence that architectural compatibility can influence ideological inheritance, this study advances a representation-centered account of modeling ideology in temporally grounded semantic research. Full article

This study characterizes the structure and variability of baroclinic semidiurnal tidal currents at the head of the Biobio Submarine Canyon (BbC), off central Chile, based on Acoustic Doppler Current Profiler (ADCP) and moored thermistor-chain observations from two deployments conducted in 2013 and 2014 under contrasting stratification conditions. The results show that the head of the BbC is a dynamically active site of semidiurnal variability, with markedly stronger and more coherent baroclinic motions during the more stratified winter–spring 2014 period. During that deployment, semidiurnal baroclinic current amplitudes reached up to 17 cm s⁻¹, and the associated energy was concentrated near the surface and bottom. Rotary spectral analysis indicated that these semidiurnal baroclinic currents rotated anticyclonically and were closely aligned with the canyon axis. Empirical orthogonal function (EOF) analysis further showed that their vertical structure was dominated by a first baroclinic mode, which explained more than 70% of the semidiurnal baroclinic variance in 2014. In contrast, the 2013 deployment exhibited weaker and less coherent semidiurnal baroclinic variability. Taken together, these results indicate that stronger stratification favored the development of semidiurnal internal-tide-related motions over the canyon head and that the BbC provides a dynamically favorable setting for enhanced semidiurnal internal-tide activity and potentially elevated mixing, although direct turbulence or dissipation measurements were not available in this study. These findings have potential implications for local water-column structure, nutrient supply, and primary productivity in this highly productive coastal region. Full article

Since the 1960s, research on sea-level rise (SLR) and land subsidence has grown significantly; however, comprehensive syntheses remain limited. This study presents a systematic review of 2171 publications spanning 1964–2025, combining a global perspective with a regional focus on the Gulf of Guinea, a critically underrepresented region within the African continent. The results show a steady increase in publications, exceeding 80 per year since 2015. A combined bibliometric and content analysis approach was adopted, integrating large-scale metadata analysis with an in-depth evaluation of 166 full-text studies corresponding to 311 study sites. Bibliometric analyses highlight four main themes: (1) factors driving SLR and subsidence, including climate, geophysical, and human effects; (2) monitoring methods such as tide gauges, GPS, and InSAR-based land motion tracking; (3) impacts on coastal communities, and ecosystems; and (4) strategies for adaptation and mitigation. A comparative assessment of global research output and Low-Elevation Coastal Zone (LECZ) exposure reveals a marked spatial mismatch, with critically vulnerable regions, such as the Gulf of Guinea, remaining significantly underrepresented (44 studies). The synthesis identifies key conceptual, methodological, and practical research gaps. Addressing these gaps requires holistic frameworks that integrate SLR and subsidence, long-term monitoring networks, advanced modeling, and evidence-based adaptation strategies. By linking bibliometric evidence with the interpretation of research trends and gaps, this study provides an analytical basis for supporting monitoring strategies, coastal planning, and adaptive responses. Additionally, the results highlight priority directions for future research directions in the Gulf of Guinea region. Full article

Seaweeds are photosynthetic organisms with ecological, social, and economic significance, and they serve as effective bioindicators in marine ecosystems. This study assessed trace element concentrations in beach-cast seaweeds collected from four beaches along the Espírito Santo coast in southeastern Brazil—an area impacted by mining-related contamination. Samples of Zonaria tournefortii (J.V. Lamouroux) Montagne and Sargassum natans (Linnaeus) Gaillon, gathered during low tide (July–August 2022), were analyzed for 15 elements. Statistical analysis using the Kruskal–Wallis test revealed significant interspecific differences in the accumulation of several metals. Aluminum (Al), iron (Fe), and magnesium (Mg) were the most abundant (>100 mg/kg), while minor elements (<100 mg/kg) included barium (Ba), arsenic (As), zinc (Zn), vanadium (V), nickel (Ni), chromium (Cr), copper (Cu), lead (Pb), cobalt (Co), cadmium (Cd), silver (Ag), and mercury (Hg). Elemental profiles exceeded those reported in other global regions and closely resembled iron ore tailings. Most elements had relatively higher concentrations on the beaches of Imigrantes, in the north of the state. These findings are the first for beach-cast seaweeds in this region, suggesting that this contamination indicates the legacy of the mining industry from southeastern Brazil. Full article

Background: The chemokine CCL5 exhibits a complex role in cancer immunotherapy, yet its dual immunomodulatory functions in non-small cell lung cancer (NSCLC) remain poorly understood. Methods and Results: Based on a newly analyzed clinical cohort of 33 advanced NSCLC patients receiving anti-PD-1 therapy combined with platinum-based chemotherapy, we found that elevated baseline peripheral blood CCL5 levels significantly predicted shorter overall survival (27.6 months vs. not reached, HR = 2.779, p = 0.038) and a higher incidence of immune-related pneumonitis (p = 0.0072). These clinical observations were supported by the re-analysis of a previously published single-cell RNA sequencing (scRNA-seq) dataset (n = 8), which indicated that high CCL5 expression in peripheral blood T/NK cells was associated with a lower major pathological response (p = 0.029). To explore the underlying mechanisms, we conducted detailed analyses using a large, publicly available tumor scRNA-seq dataset (GSE243013, n = 234). These analyses revealed that high intratumoral CCL5 simultaneously promoted the recruitment of both immune effector cells (CD8⁺ T cells, NK cells) and immunosuppressive populations (Tregs, MDSCs). This paradoxical immune landscape correlated with elevated immune checkpoint expression and significantly higher TIDE scores (1.47 vs. 0.83, p < 0.001). CellChat and SCENIC network analyses identified intensified T cell–myeloid communication and key transcription factors (e.g., FOXP3, EOMES) mediating this dichotomy. Conclusions: This hypothesis-generating study raises the possibility that CCL5 orchestrates paradoxical immune responses and may serve as a biomarker in NSCLC. Further validation in larger prospective, independent cohorts is required. Full article

The ambiguous evolution of the depositional system in the Pinghu Formation of Block K, Xihu Depression, East China Sea Basin, has long constrained the accuracy of reservoir prediction in this area. Based on petrological analysis, sedimentary system identification, and depositional model reconstruction, this study systematically elucidates the sedimentary evolution of the Pinghu Formation in Block K. The results indicate that the Pinghu Formation exhibits diverse lithologies and multiple types of grain-size distribution, reflecting complex hydrodynamic conditions. The early stage was dominated by tidal processes with fluvial influence, transitioning to fluvial dominance in the late stage. The depositional system evolved through a complete sequence: the early stage (E2pSQ1) was characterized by a tide-dominated delta, the middle stage (E2pSQ2) by fluvial-tidal interaction, and the late stage (E2pSQ3) by an overwhelmingly fluvial-dominated system. This evolution was controlled by the combined effects of a persistently increasing sediment supply and episodic relative sea-level fall, with the transition mechanism primarily governed by tectonic-eustatic coupling. In the lowstand systems tract of the middle-upper section, a “high-supply, high-progradation” fluvial-dominated delta developed in the Kongbei fault-step zone, whereas a “low-supply, low-progradation” minor fluvial system formed in the Kongnan fault-step zone. Here, tidal reworking was weak, and tidal flats developed only locally. In contrast, the highstand systems tract in the middle-lower section was dominated by a tide-dominated delta in the Kongnan fault-step zone, while the Kongbei fault-step zone remained a “low-supply, low-progradation” minor fluvial system. The established depositional models provide a geological basis for reservoir prediction and hydrocarbon exploration in the Pinghu Formation of Block K. Full article

Under the dual carbon strategy and the sweeping tide of digital transformation in education, higher education confronts an urgent imperative: cultivating talent equipped with interdisciplinary skills and sustainable decision-making capabilities. To meet this critical challenge, this study pioneers the PAMD (Patient Capital–Accounting–Matrix–Development) interdisciplinary teaching framework. Rooted firmly in Education for Sustainable Development (ESD) principles, PAMD uniquely weaves together patient capital, carbon asset accounting, and linear algebra matrix modeling. Utilizing a quasi-experimental design with undergraduate business students, we implemented “Carbon Asset Accounting and Low-Carbon Transition Investment Analysis” as a case study. We rigorously evaluated teaching effectiveness across academic performance, competency, and cognitive attitude dimensions using Welch’s t-test, Hedges’ g, and ANCOVA. After controlling for baseline scores, the experimental group significantly surpassed the control group in comprehensive decision-making (81.22 vs. 72.41, g = 0.71) and matrix modeling competency (3.74 vs. 3.22, g = 0.77). The experimental cohort also demonstrated consistent gains in carbon accounting reporting precision and data representation clarity. Cognitive assessments revealed moderate effect sizes for both low-carbon investment literacy and interdisciplinary learning interest. These compelling results demonstrate that embedding a long-term value orientation into accounting representation and matrix modeling powerfully cultivates students’ ability to transfer interdisciplinary knowledge and make sound sustainable decisions within complex contexts. This study offers a robust, evidence-based, and replicable pathway for driving sustainability-oriented interdisciplinary reform within business education. Full article

Extreme sea levels along the Mexican coasts pose an increasing risk to coastal infrastructure and communities, particularly under the combined influence of tropical cyclones and ongoing sea-level rise. This study analyzes tide-gauge records from the Mexican Pacific and Gulf of Mexico–Caribbean coasts to characterize the statistical behavior and seasonal modulation of extreme sea-level residuals. Astronomical tides were removed through harmonic analysis to isolate the meteorological residual associated with storm-driven processes. Extreme events were evaluated using complementary extreme-value frameworks, including Generalized Extreme Value (GEV) distributions applied to monthly maxima and a Peaks-Over-Threshold (POT) approach applied to the continuous residual series with temporal declustering and Generalized Pareto Distribution (GPD) fitting. While both approaches consistently capture regional patterns, the POT–GPD framework is adopted as the primary basis for return-level estimation due to its explicit representation of event-scale extremes. The results reveal marked regional variability. Pacific stations exhibit bounded or near-Gumbel behavior (ξ ≈ −0.30 to −0.02) and a strong seasonal concentration of extremes during the tropical cyclone season. In contrast, Gulf of Mexico–Caribbean stations display higher absolute extremes and a broader seasonal footprint, with Veracruz showing a tendency toward heavier-tailed behavior (ξ ≈ 0.13). Return levels for a 25-year return period range from approximately 0.85–0.95 m in the Pacific to about 1.7 m in Veracruz. Longer return periods (e.g., 100 years) exceed 2.2 m in Veracruz but are associated with substantial uncertainty due to record-length limitations. The analysis of ENSO variability indicates that ENSO acts primarily as a secondary modulator of background sea-level variability rather than a deterministic driver of extreme events, with the largest anomalies typically associated with tropical cyclone activity. Overall, the results demonstrate that extreme sea levels along the Mexican coasts are governed by region-specific forcing and tail behavior requiring localized extreme-value modeling strategies. The proposed framework provides a robust and reproducible baseline for coastal hazard assessment and supports the integration of sea-level rise into future risk and design analyses. Full article

This study examines how assessments of coastal extreme sea levels depend on the separability and reconstructability of the astronomical tide in hourly sea-level records. Using a global tide-gauge network, it proposes an ensemble-learning correction framework that integrates a physical-baseline threshold with multi-criteria consistency testing to determine whether machine-learning enhancement is genuinely effective across stations and time windows. The analysis uses hourly records from 528 UHSLC tide gauges, with 31-day short sequences used to reconstruct 180-day sea-level variability. Taking the physical tidal model as the baseline, residuals are corrected using Extremely Randomized Trees, Random Forest, and Gradient Boosting. To avoid false improvement driven solely by error reduction, a hierarchical decision framework is established. Baseline model quality is first screened using NSE and the coefficient of determination, after which mathematical artefacts are identified through diagnostics of peak suppression and variance shrinkage. A five-level classification is then derived from the convergent evidence of twelve performance metrics and four statistical significance tests. The results show a consistent global pattern across all three algorithms. Approximately 57% of stations meet the criterion for genuine improvement, whereas about 42% are associated with an unreliable physical baseline, indicating that the dominant source of failure arises not from the ensemble-learning algorithms themselves, but from spatially varying limitations in the underlying physical baseline. Spatially, the credibility of machine-learning correction is strongly conditioned by baseline quality: stations with effective correction are more continuous along the eastern North Atlantic and European coasts, whereas stations with ineffective correction are more concentrated in the Gulf of Mexico, the Caribbean, and the marginal seas and archipelagic regions of the western Pacific. These results indicate that the observed spatial heterogeneity primarily reflects geographically varying physical and dynamical conditions that control baseline reliability and residual learnability, rather than a standalone difference in the intrinsic capability of ensemble learning itself. Full article