Search Results (2,277)

Diabetes-related pathophysiological processes contribute to endothelial dysfunction, arterial stiffening (AS), hypertension, vascular remodeling, and impaired myocardial perfusion. This study aimed to assess the relationship between arterial wall parameters and sST2 concentration as potential risk factors in type 2 diabetes (T2DM) and investigate sex-related differences. To achieve this, we enrolled 100 patients with suspected or exacerbated coronary artery disease (CAD) and divided them into a T2DM group (n = 58) and a control group (n = 42). Endothelial reactivity (lnRHI), ABI, sST2 levels, and carotid–femoral (cfPWV) and carotid–radial pulse wave velocity (crPWV) were assessed. Coronary angiography was performed in every patient, and epicardial flow and myocardial perfusion were evaluated using QuBE and FLASH. Our results showed that the coronary angiographic findings were similar in both groups. However, T2DM patients had a significantly higher central AS (cfPWV 10.8 ± 2 vs. 9.9 ± 2.7 m/s, p < 0.05) and vascular age (70.0 ± 12.3 vs. 61.3 ± 15.4 years, p < 0.05), while peripheral AS, RHI, and ABI showed no differences. CfPWV correlated with renal function; higher HbA1c and sST2 levels were additionally associated with advanced vascular age. Notably, central AS and vascular age were higher in men with T2DM but not in women. These findings indicate that T2DM patients exhibit increased central AS and vascular aging, influenced by sST2 levels, suggesting fibrosis as a target for precision medicine in T2DM. Full article

Air–sea interactions play a pivotal role in shaping cyclone development and evolution. In this context, this study investigates the role of ocean optical properties and solar radiation penetration in modulating subsurface heat content and their subsequent influence on the intensity of Mediterranean cyclones. Using a regional coupled ocean–wave–atmosphere model, we conducted sensitivity experiments for Storm Daniel (2023) comparing two solar radiation penetration schemes in the ocean model component: one with a constant light attenuation depth and another with chlorophyll-dependent attenuation based on satellite estimates. Results show that the chlorophyll-driven radiative heating scheme consistently produces warmer sea surface temperatures (SSTs) prior to cyclone onset, leading to stronger cyclones characterized by deeper minimum mean sea-level pressure, intensified convective activity, and increased rainfall. However, post-storm SST cooling is also amplified due to stronger wind stress and vertical mixing, potentially influencing subsequent local atmospheric conditions. Overall, this work demonstrates that ocean bio-optical processes can meaningfully impact Mediterranean cyclone behavior, highlighting the importance of using appropriate underwater light attenuation schemes and ocean color remote sensing data in coupled models. Full article

The Mid-Piacenzian Warm Interval (MPWI) is marked by warmer temperatures and higher atmospheric CO₂ levels than today, making it an analogue for late-21st-century-warming, whereas the early Pleistocene cooling is more like today. We compare seasonal growth temperatures derived from oxygen isotope ratios (δ¹⁸O) and clumped isotopes (∆₄₇) in Mercenaria. Modern shells were previously collected from coastal NC. The fossil shells are from the Duplin (MPWI) and Waccamaw Formations (early Pleistocene), NC. Oxygen isotope ratios range from −2.2‰ to 2.3‰ (modern), −0.9‰ to 2.4‰ (MPWI), and −0.9‰ to 2.9‰ (early Pleistocene). The values of Δ₄₇ range from 0.576‰ to 0.639‰ (modern), 0.566‰ to 0.621‰ (MPWI), and 0.581‰ to 0.615‰ (early Pleistocene). We show that Mercenaria do not require a species-specific ∆₄₇ calibration. Modern and MPWI ∆₄₇-derived summer/winter temperatures (SST_∆47) and seasonal amplitudes are indistinguishable from δ¹⁸O-derived temperatures. The early Pleistocene summer SST_∆47 is indistinguishable from δ¹⁸O-derived temperatures, but the winter SST_∆47 is warmer by 5 °C and may reflect within-shell time averaging. The modern summer/winter SST_∆47 are indistinguishable from the MPWI, but the MPWI has a lower seasonal amplitude by 5 °C. Compared to our calculated δ¹⁸O_sw values, modeled values for the MPWI are within error but are much lower, and they are not within error for the early Pleistocene. Full article

Heart failure (HF) poses a substantial global burden due to its high morbidity, mortality, and healthcare costs. Accurate prognostication is crucial for optimizing treatment, resource allocation, and patient counseling. Prognostic tools range from simple clinical scores such as ADHERE and MAGGIC to more complex models incorporating biomarkers (e.g., NT-proBNP, sST2), imaging, and artificial intelligence techniques. In acute HF, models like EHMRG and STRATIFY aid early triage, while in chronic HF, tools like SHFM and BCN Bio-HF support long-term management decisions. Despite their utility, most models are limited by poor generalizability, reliance on static inputs, lack of integration into electronic health records, and underuse in clinical practice. Novel approaches involving machine learning, multi-omics profiling, and remote monitoring hold promise for dynamic and individualized risk assessment. However, these innovations face challenges regarding interpretability, validation, and ethical implementation. For prognostic models to transition from theoretical promise to practical impact, they must be continuously updated, externally validated, and seamlessly embedded into clinical workflows. This review emphasizes the potential of prognostic models to transform HF care but cautions against uncritical adoption without robust evidence and practical integration. In the evolving landscape of HF management, prognostic models represent a hopeful avenue, provided their limitations are acknowledged and addressed through interdisciplinary collaboration and patient-centered innovation. Full article

Background/Objectives: To investigate acute caffeine (CAF: 375 mg, ≈4.8 mg/kg body mass) effects on energy expenditure (EE) and substrate kinetics during high-intensity interval exercise in individuals with high (HBAT) versus low (LBAT) brown adipose tissue activity using time-trend polynomial modeling. Methods: This is a randomized, double-blind crossover study in which 35 highly-trained males [HBAT-CAF, HBAT-PLA (Placebo), LBAT-CAF, LBAT-PLA] performed 30-min treadmill HIIE. Infrared thermography (IRT) assessed BAT activity by measuring supraclavicular skin temperature (SST). Breath-by-breath ergospirometry measured EE (kcal/min) and carbohydrate (CHO), lipid (LIP), and protein (PTN) oxidation. We applied second- and third-order polynomial regression models to depict the temporal trajectories of metabolic responses. Results: HBAT groups showed 25% higher sustained EE versus LBAT (p < 0.001), amplified by CAF. CHO oxidation exhibited biphasic kinetics: HBAT had 40% higher initial rates (0.75 ± 0.05 vs. 0.45 ± 0.04 g/min; p < 0.001) with accelerated decline (k = −0.21 vs. −0.15/min; p = 0.01). LIP oxidation peaked later in LBAT (40 vs. 20 min in HBAT), with CAF increasing oxidation by 18% in LBAT (p = 0.01). HBAT-CAF uniquely showed transient PTN catabolism (peak: 0.045 g/min at 10 min; k = −0.0033/min; p < 0.001). Conclusions: BAT status determines EE magnitude and substrate-specific kinetic patterns, while CAF exerts divergent modulation, potentiating early glycogenolysis in HBAT and lipolysis in LBAT. The HBAT-CAF synergy triggers acute proteolysis, revealing BAT-mediated metabolic switching. Full article

Typhoon Yagi (2024) was a rapidly moving storm that lasted for eight days and made landfall in three locations, producing heavy rainfall over Hainan and Vietnam. This study aims to investigate the dynamical processes contributing to the heavy rainfall, concentrating on enthalpy flux (EF) and moisture flux (MF). The results indicate that both EF and MF increased significantly during the typhoon’s intensification stage and were high at the time of landfall. Before landfalling at Hainan, latent heat flux (LHF) reached 600 W/m², while sensible heat flux (SHF) was recorded as 80 W/m². Landfall at Hainan resulted in a decrease in LHF and SHF. LHF and SHF subsequently increased to 700 W/m² and 100 W/m², respectively, as noted prior to the landfall in Vietnam. The increased LHF led to higher evaporation, which subsequently elevated moisture flux (MF) following the landfall in Vietnam, while the region’s topography further intensified the rainfall. The mean daily rainfall observed over Philippines is 75 mm on 2 September (landfall and passing through), 100 mm over Hainan (landfall and passing through) on 6 September, and 95 mm at over Vietnam on 7 September (landfall and after), respectively. Heavy rainfall was observed over the land while the typhoon was passing and during the landfall. This research reveals that Typhoon Yagi’s intensity was maintained by a well-organized and extensive circulation system, supported by favorable weather conditions, including high sea surface temperatures (SST) exceeding 30.5 °C, substantial low-level moisture convergence, and elevated EF during the landfall in Vietnam. Full article

Extreme surface winds and wave heights of tropical cyclones (TCs)—pose serious threats to coastal community, infrastructure and environments. In recent decades, progress in numerical wave modeling has significantly enhanced the ability to reconstruct and predict wave behavior. This review offers an in-depth overview of TC-related wave modeling utilizing different computational schemes, with a special attention to WAVEWATCH III (WW3) and Simulating Waves Nearshore (SWAN). Due to the complex air–sea interactions during TCs, it is challenging to obtain accurate wind input data and optimize the parameterizations. Substantial spatial and temporal variations in water levels and current patterns occurs when coastal circulation is modulated by varying underwater topography. To explore their influence on waves, this study employs a coupled SWAN and Finite-Volume Community Ocean Model (FVCOM) modeling approach. Additionally, the interplay between wave and sea surface temperature (SST) is investigated by incorporating four key wave-induced forcing through breaking and non-breaking waves, radiation stress, and Stokes drift from WW3 into the Stony Brook Parallel Ocean Model (sbPOM). 20 TC events were analyzed to evaluate the performance of the selected parameterizations of external forcings in WW3 and SWAN. Among different nonlinear wave interaction schemes, Generalized Multiple Discrete Interaction Approximation (GMD) Discrete Interaction Approximation (DIA) and the computationally expensive Wave-Ray Tracing (WRT) A refined drag coefficient (C_d) equation, applied within an upgraded ST6 configuration, reduce significant wave height (SWH) prediction errors and the root mean square error (RMSE) for both SWAN and WW3 wave models. Surface currents and sea level variations notably altered the wave energy and wave height distributions, especially in the area with strong TC-induced oceanic current. Finally, coupling four wave-induced forcings into sbPOM enhanced SST simulation by refining heat flux estimates and promoting vertical mixing. Validation against Argo data showed that the updated sbPOM model achieved an RMSE as low as 1.39 m, with correlation coefficients nearing 0.9881. Full article

Skipjack tuna constitutes a crucial fishery resource in the Western and Central Pacific Ocean (WCPO) purse seine fishery, with high economic value and exploitation potential. It also serves as an essential subject for studying the interaction between fishery resource dynamics and marine ecosystems, as its resource abundance is significantly influenced by marine environmental factors. Skipjack tuna can be categorized into unassociated schools and associated schools, with the latter being predominant. Overfishing of the associated schools can adversely affect population health and the ecological environment. In-depth exploration of the spatial distribution responses of these two fish schools to environmental variables is significant for the rational development and utilization of tuna resources and for enhancing the sustainability of fishery resources. In sparsely sampled and complex marine environments, geographic similarity methods effectively predict tuna resources by quantifying local fishing ground environmental similarities. This study introduces geographical similarity theory. This study focused on 1° × 1° fishery data (2004–2021) released by the Western and Central Pacific Fisheries Commission (WCPFC) combined with relevant marine environmental data. We employed Geographical Convergent Cross Mapping (GCCM) to explore significant environmental factors influencing catch and variations in causal intensity and employed a Geographically Optimal Similarity (GOS) model to predict the spatial distribution of catch for the two types of tuna schools. The research findings indicate that the following: (1) Sea surface temperature (SST), sea surface salinity (SSS), and net primary productivity (NPP) are key factors in GCCM model analysis, significantly influencing the catch of two fish schools. (2) The GOS model exhibits higher prediction accuracy and stability compared to the Generalized Additive Model (GAM) and the Basic Configuration Similarity (BCS) model. R² values reaching 0.656 and 0.649 for the two types of schools, respectively, suggest that the geographical similarity method has certain applicability and application potential in the spatial prediction of fishery resources. (3) Uncertainty analysis revealed more stable predictions for unassociated schools, with 72.65% of the results falling within the low-uncertainty range (0.00–0.25), compared to 52.65% for associated schools. This study, based on geographical similarity theory, elucidates differential spatial responses of distinct schools to environmental factors and provides a novel approach for fishing ground prediction. It also provides a scientific basis for the dynamic assessment and rational exploitation and utilization of skipjack tuna resources in the Pacific Ocean. Full article

Change in sea level (SL) is an important indicator of global warming, since it reflects alterations in several components of the climate system at once. The main factors behind this phenomenon are the melting of glaciers and thermal expansion of ocean water, with the latter contributing about 40% to the overall rise in SL. Rising SL indirectly indicates an increase in ocean heat content and, consequently, its surface temperature. Previous studies have found that tropical sea surface temperature (SST) is critical to regulating the Earth’s climate and weather patterns in high and mid-latitudes. For this reason, SST and SL in the tropics can be considered as precursors of both global climate change and the emergence of climate anomalies in extratropical latitudes. Although SST has been used in this capacity in a number of studies, similar research regarding SL had not been conducted until recently. In this paper, we examine the links between SL in the tropical North Atlantic and North Pacific Oceans and surface air temperature (SAT) at mid- and high latitudes, with the aim of assessing the potential of SL as a predictor in forecasting SAT anomalies. To identify similarities between the variability of tropical SL and SST and that of SAT in high- and mid-latitude regions, as well as to estimate possible time lags, we applied factor analysis, clustering, cross-correlation and cross-spectral analyses. The results reveal a structural similarity in the internal variability of tropical SL and extratropical SAT, along with a significant lagged relationship between them, with a time lag of several years. Full article

Temperature affects the morphology, physiology, and distribution of marine macroalgae, as supported by studies that used long-term data from herbaria. In the present study, sea surface temperature (SST), latitudinal distribution, and La Niña or El Niño years were correlated to the morphology of two macroalgal species of the Mexican Pacific: Ceratodictyon tenue and C. variabile. Twenty-four morphological characteristics were evaluated, and 95 samples from 1965 to 2013 in the Escuela Nacional de Ciencias Biológicas herbarium were reviewed. In 2017, 2023, and 2024, 12 specimens were sampled at three locations. Low positive correlations were found between thallus diameter and SST for C. tenue, while low positive correlations were detected for thallus length and medullary cell diameter vs. SST and medullary cell length vs. year for C. variabile. Significant relationships were found between the thallus length and cortical cell diameter of C. variabile with latitude and SST. It is concluded that SST contributes to changes in morphology, but is not the only factor that affects them. For the first time in a tropical area, the present study explores whether there is a relationship between SST, latitudinal distribution, and El Niño and La Niña years and the morphology of a genus of red algae. Full article

This study examines the performance of two diffuser configurations—a trumpet-shaped and a semi-diagonal design—for application in micro gas turbine engines, aiming to assess their suitability in terms of efficiency and operational flexibility. Both diffusers were initially evaluated using steady-state CFD simulations with the k-omega SST turbulence model, followed by experimental testing on an actual engine across the start-up sequence from idle to 70% of nominal speed. Performance was mapped over four constant-speed lines for each configuration. Results showed that the trumpet-shaped diffuser offered a greater choke margin but suffered from increased aerodynamic losses, whereas the semi-diagonal diffuser demonstrated higher efficiency but required closer alignment with the target operating point. The k-omega SST model showed strong predictive accuracy, with 5.13% agreement across all instrumented parameters for all investigated speed lines. These findings suggest that while the trumpet diffuser provides better stability, the semi-diagonal design is more efficient when properly targeted. Future work will focus on extending the analysis to higher speed ranges and transient regimes using harmonic balance CFD methods and enhanced data acquisition techniques. Full article

This study investigates the flow dynamics and local scour around a Reef Cube^® artificial reef deployed in Torbay, UK, using computational fluid dynamics. The flow is modelled using Reynolds-Averaged Navier–Stokes (RANS) equations with a k-ω SST turbulence model. A novel hydro-morphodynamic model employing the generalized internal boundary method in HELYX (OpenFOAM-based) is used to simulate scour development. Model performance was validated against experimental data for flow fields, bed shear stress, and local scour. Flow simulations across various scenarios demonstrated that parameters such as the orientation angle and arrangement of Reef Cubes significantly influence flow patterns, bed shear stress, and habitat suitability. The hydro-morphodynamic model was used to simulate scouring around a reef cube in the Torbay marine environment. Results indicate that typical tidal flow velocity flow in the region is barely sufficient to initiate sediment motion, whereas extreme flow events, represented by doubling the mean flow velocity, significantly accelerate scour development, producing holes up to ten times deeper. These findings underscore the importance of considering extreme flow conditions in scour analyses due to their potential impact on the stability and failure risk of AR projects. Full article

The long-term trend of coastal upwelling under global warming has been a research focus in recent years. Based on datasets including sea surface temperature (SST), sea surface wind, air–sea heat fluxes, ocean currents, and sea level pressure, this study explores the long-term trend and underlying mechanisms of the Oman coastal upwelling intensity in summer during 1993–2018. The results indicate a persistent decrease in SST within the Oman upwelling region during this period, suggesting an intensification trend of Oman upwelling. This trend is primarily driven by the strengthened positive wind stress curl (WSC), while the enhanced net shortwave radiation flux at the sea surface partially suppresses the SST cooling induced by the strengthened positive WSC, and the effect of horizontal oceanic heat transport is weak. Further analysis revealed that the increasing trend in the positive WSC results from the nonuniform responses of sea level pressure and the associated surface winds to global warming. There is an increasing trend in sea level pressure over the western Arabian Sea, coupled with decreasing atmospheric pressure over the Arabian Peninsula and the Somali Peninsula. This enhances the atmospheric pressure gradient between land and sea, and consequently strengthens the alongshore winds off the Oman coast. However, in the coastal region, wind changes are less pronounced, resulting in an insignificant trend in the alongshore component of surface wind. Consequently, it results in the increasing positive WSC over the Oman upwelling region, and sustains the intensification trend of Oman coastal upwelling. Full article

In response to the increasing demand for high-precision navigation of satellites operating in the cislunar space, this study introduces an onboard orbit determination algorithm considering both convergence and computational efficiency, referred to as the Sliding-Window Batch Processing (SWBP) algorithm. This algorithm combines the strengths of data batch processing and the sequential processing algorithm, utilizing measurement data from multiple historical and current epochs to update the orbit state of the current epoch. This algorithm facilitates rapid convergence in orbit determination, even in instances where the initial orbit error is large. The SWBP algorithm has been used to evaluate the navigation performance in the Distant Retrograde Orbit (DRO) and the Earth–Moon transfer orbit. The scenario involves a low-Earth-orbit (LEO) satellite establishing satellite-to-satellite tracking (SST) links with both a DRO satellite and an Earth–Moon transfer satellite. The LEO satellite can determine its orbit accurately by receiving GNSS signals. The experiments show that the DRO satellite achieves an orbit determination accuracy of 100 m within 100 h under an initial position error of 500 km, and the transfer orbit satellite reaches an orbit determination accuracy of 600 m within 3.5 h under an initial position error of 100 km. When the Earth–Moon transfer satellite exhibits a large initial orbital error (on the order of hundreds of kilometers) or the LEO satellite’s positional accuracy is degraded, the SWBP algorithm demonstrates superior convergence speed and precision in orbit determination compared to the Extended Kalman Filter (EKF). This confirms the proposed algorithm’s capability to handle complex orbital determination scenarios effectively. Full article

The development in coastal engineering and maritime transport demands accurate wave height prediction. In this study, hybrid deep learning models, including CNN-LSTM, CNN-BiLSTM, CNN-GRU, and CNN-BiGRU, are employed to develop regional multivariate wave prediction models that incorporate multiple features, such as wave height, wind stress, water depth, pressure, and sea surface temperature (SST), for the entire Bay of Bengal area. Sensitivity analysis is performed to evaluate the accuracy using statistical metrics, such as the correlation coefficient, RMSE, and MAE. The findings demonstrate that regional multivariate models offer satisfactory results for the entire Bay of Bengal region. The multivariate model performs better compared to the univariate model as the forecast horizon increases. Performance assessment of each environmental factor, employing the integrated gradient method, reveals that sea surface temperature has the most significant influence, while wind stress is the least dominant factor in the wave prediction model. Among the tested models, the CNN-BiGRU has superior performance with a correlation of 0.9872, an RMSE of 0.1547, and an MAE of 0.1005 for the 3 h prediction and is proposed as the optimal model. This study contributes to assessing the contribution of each environmental feature and improving the accuracy of regional wave prediction. Full article