Search Results (182,611)

Background/Objectives: To evaluate the diagnostic performance of ultrasound-guided attenuation parameter (UGAP) for the assessment of hepatic steatosis in a population at risk for metabolic dysfunction-associated steatotic liver disease (MASLD), using MRI proton density fat fraction (PDFF) as the reference standard, and to also derive optimal population-specific diagnostic thresholds. Methods: In this single-center prospective study, 64 adults at risk for MASLD underwent UGAP measurement and MRI-PDFF. UGAP was performed according to standardized manufacturer-recommended protocols and standardized on the right hepatic lobe. Hepatic steatosis was staged using established MRI-PDFF thresholds. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis. Cohort-UGAP cut-offs were derived using the Youden index. Associations between UGAP and clinical parameters were assessed using correlation and regression analyses. Results: UGAP correlated strongly with MRI-PDFF (ρ = 0.82, p < 0.001). The areas under the ROC curve (AUCs) for detecting mild, moderate, and severe steatosis were 0.86, 0.96, and 0.96, respectively. Right-lobe acquisitions outperformed left-lobe measurements, while four-region averaging yielded the highest diagnostic performance. UGAP values were associated with BMI, waist circumference, and liver enzymes. Conclusions: UGAP provides an accurate noninvasive assessment of hepatic steatosis, demonstrating high overall diagnostic agreement with MRI-PDFF. Right-lobe acquisition and multi-regional averaging further improve its performance. While cohort-specific threshold optimization may enhance clinical applicability, larger studies are needed to fully confirm its accuracy in advanced stages. Full article

Full-physics reservoir simulation for CO₂ storage becomes computationally expensive when many operational schedules must be screened, motivating machine-learning (ML) surrogates that reduce simulation burden while preserving the essential physics-driven response. We propose an activity-based partitioning methodology that produces an interpretable applicability map, identifying regions where surrogate substitution is expected to be reliable and regions where highly active dynamics make it unsafe. In this work, we focus exclusively on the slow-varying region and develop proxy models for pressure and saturation time derivatives in that domain. The fast-varying region is intentionally excluded, and no fully coupled hybrid simulator is claimed at this stage. The partition is constructed from temporal changes in derivative signals and aggregated across multiple schedules to obtain a conservative, scenario-robust delineation. For slow cells, local stencil-based neural proxies leverage overlapping time windows and features describing the local state, schedule forcing, and injector influence. Because saturation derivatives in the slow region are strongly zero-inflated, with many cells remaining outside the advancing CO₂ plume for long periods, a two-stage strategy is adopted: first detecting whether meaningful change occurs and then predicting the derivative magnitude only when active, with additional smoothing to suppress near-zero artifacts. The framework also supports selective surrogate deployment over user-selected time windows. The objective is therefore to establish a conservative zone of applicability for derivative-based ML updates, rather than to demonstrate full simulator replacement or end-to-end coupled acceleration. In the case study, 5914 of the 8243 grid blocks evaluated by the proxy workflow were classified as slow-varying, corresponding to 71.7% of the evaluated proxy-analysis domain. For the blind schedule, full-rollout pressure reconstruction produced mean absolute errors of 5.34, 3.69, and 2.80 psi over early, middle, and late time-window groups, respectively. In a future coupled implementation using the same partition, these 5914 cells could be advanced by the ML proxy, while the remaining dynamically active or unsupported cells would remain under full-physics treatment. This would reduce the full-physics active-cell count from 9212 to 3298 in the future coupled setting, although direct wall-clock acceleration remains to be quantified after simulator integration. Full article

Determining the internal oceanic gravity corresponds to solving for the Earth’s internal gravitational potential, for which traditional geodetic theories (Stokes’ and Molodenskii’s theorems) are not directly applicable. To overcome this constraint, the concept of “seawater layer” is introduced. The first original global three-dimensional internal oceanic gravity field model WHU-IOGM was constructed using four key methods: (1) sliding-window Newtonian integration, (2) multi-node parallel computing on a high-performance supercomputing platform, (3) an ellipsoidal harmonic expansion algorithm with improved convergence properties, and (4) a spherical-to-ellipsoidal harmonic coefficient transformation algorithm. Compared with underwater gravity measurement continuation, the “seawater layer” method has more advantages in theoretical rigor and accuracy. The theoretical systematic error of WHU-IOGM was evaluated, with the global RMSE of about 6.28 mGal and a mean error of about 0.19 mGal. Based on the WOA18 deep stratification framework, we added a grid layer corresponding to the actual seabed depth, expanding the original 102-layer system to a total of 103 layers. The inclusion enhances the model’s conformity with actual seabed topography. This structural refinement enables a more accurate and detailed representation of the ocean’s internal gravity field, providing a theoretical basis and algorithmic models for underwater gravity measurement and underwater navigation. Full article

Gastrointestinal (GI) cancers account for a quarter of all cancer cases worldwide and are responsible for a third of cancer deaths. One of the characteristic features of GI tissue is its multilayered structure, which, in addition to multiple scattering, complicates optical spectral analysis. The use of spectroscopic diagnostics and photodynamic therapy for the detection and treatment of GI cancer is a rapidly developing field. The method proposed in this paper for layer-by-layer optical properties assessment, suitable for real-time clinical application to the walls of hollow organs, allows us to calculate the absorbed dose layer by layer. This paper proposes a method for recording spectral data in two geometries, diffuse reflectance and transmission, using light delivery from both the external and internal surfaces of the gastrointestinal tract wall. Layer-by-layer assessment of optical properties was performed using a developed algorithm based on the inverse adding–doubling method with initial optical properties values determined using the modified two-stream Kubelka–Munk model with the accuracy equal to 86 ± 13%. The method was approved in clinical conditions. Based on the results of the work, the developed method for assessing the optical properties of multilayered biological tissues exhibited sufficient speed and accuracy for in vivo application to personalize laser-induced therapy by correction of the laser dose. Full article

Tsunami fragility modeling plays a central role in probabilistic coastal risk assessment; however, representing structural vulnerability under near-field tsunami conditions remains challenging due to complex hydrodynamic loading, strong spatial variability, and the presence of pre-existing earthquake damage. This paper advances near-field tsunami fragility modeling through three specific contributions, each bridging simulation-based methods and empirical damage survey observations. First, it demonstrates how a successive earthquake–tsunami simulation framework can generate conditional fragility surfaces that explicitly account for pre-existing seismic damage without relying on statistically intractable probabilistic decompositions. Second, it develops and validates a distance-dependent intensity-shifting approach—derived from analysis of the 2011 Great East Japan tsunami survey dataset—that adapts baseline fragility curves to near-field and near-coast conditions in a physically interpretable and practically deployable manner. Third, it establishes an explicit cross-validation pathway between simulation-derived fragility surfaces and empirical damage observations through machine-learning-assisted feature importance analysis, a connection largely absent from prior literature. Together, these contributions provide a physically consistent and data-informed foundation for near-field tsunami fragility modeling that is directly applicable—as a methodological framework—to loss and resilience estimation platforms such as IN-CORE and HAZUS and to risk-informed coastal infrastructure design in subduction-zone regions, subject to typology-specific calibration; the simulation results are demonstrated for a US Reinforced Concrete (RC) moment-frame archetype and the empirical results for Japanese wood-frame construction, so direct quantitative application to other structural typologies requires recalibration of the respective model components. Full article

Background: Ultrasonography during medical procedures allows for real-time assessment of the target structure. This design feature could be more advantageous than radiological “snapshot” imaging. Technically, the image resolution of endoscopic ultrasound (EUS) is noticeably higher than that of transesophageal echocardiography (TOE). The benefits of investigating cardiovascular structures using this mode of high-resolution EUS are unknown. Materials and Methods: We present clinical applications in the diagnosis of cardiovascular structures, demonstrated during routine gastrointestinal endosonographic procedures. In some cases, these diagnoses led to changes in management strategies. Results and Discussion: The introduction of high-resolution EUS into cardiology allows for the accurate definition of variable cardiovascular anatomy and early detection of asymptomatic cardiac pathologies. It also prevents double investigations for patients and operators, reduces the risk of esophageal trauma, and highlights the benefits of interdisciplinary teamwork. In addition, the high spatial resolution of EUS facilitates detailed tissue characterization for guiding biopsies, thereby extending the applicability of elastography across various echocardiographic domains. Moreover, the precision of using EUS when targeting and inserting a needle into adjacent organs could facilitate the development of EUS indications for cardiac-based interventions. Conclusions: The use of EUS in cardiology provides high-resolution real-time assessments of cardiovascular anatomy and may facilitate the development of EUS indications for cardiac-based interventions. However, large cohort studies are required. Full article

Surface functionalization of metallic implants is widely explored to enhance their performance and functionality. In this study, multifunctional hydrogel coatings based on poly(vinylpyrrolidone) and polyethylene glycol were developed and functionalized with a taxifolin (TAX) inclusion complex and collagen to introduce bioactive features. TAX, a naturally occurring flavonoid with antioxidant and anti-inflammatory properties, was incorporated using β-cyclodextrin to improve its stability and enable controlled release. The coatings were applied to titanium-hydroxyapatite composites and titanium sheet substrates to evaluate their applicability across surfaces with varying morphologies, ranging from porous to relatively smooth. The ceramic phase was modified with magnesium ions to enhance its bioactivity and better mimic the composition of natural bone tissue. FTIR and SEM analyses confirmed hydrogel formation and effective surface coverage. Degradation and incubation studies in simulated physiological environments demonstrated the material’s stability, while UV–Vis analysis indicated TAX release, highlighting the system’s potential as a carrier for flavonoid-based compounds. Indirect cytotoxicity studies using MC3T3-E1 preosteoblasts indicated low cytotoxicity and a favorable biological response of collagen- and taxifolin-modified systems. The developed coatings represent a versatile platform for surface modification of titanium-based biomaterials and demonstrate potential for application across substrates with diverse surface characteristics. Further studies are required to assess their biological potential. Full article

Hydraulic fracturing in naturally fractured rock is governed by complex interactions between fluid flow, rock deformation, fracture propagation, and induced seismicity. In this study, a fully coupled hydro-mechanical framework based on the FDEM is developed to investigate fracture evolution and seismic responses during fluid injection in fractured rock masses. Three representative horizontal stress ratios (R = 1.0, 1.5, and 2.0) were considered to investigate the influence of stress anisotropy on fracture propagation and induced seismicity. The results demonstrate that stress anisotropy exerts a dominant control on fracture propagation patterns, fluid pressure diffusion, and induced seismicity. Under low stress ratios, fracture propagation is diffuse and strongly influenced by pre-existing fractures, whereas higher stress ratios promote localized, directional fracture growth controlled primarily by the stress field. Fluid pressure becomes increasingly concentrated with increasing stress ratio, leading to higher injection pressures and more pronounced pressure fluctuations. The spatial and temporal evolution of mean stress and volumetric strain closely follows that of fluid pressure, indicating that fluid pressurization directly controls effective stress reduction and associated deformation. Seismic analysis reveals a systematic decrease in the Gutenberg–Richter b-value with increasing stress ratio, indicating a transition from distributed micro-fracturing to more coherent fracture reactivation and larger seismic events. Under quasi-steady injection pressure conditions, fracture propagation is found to be episodic and unstable, as evidenced by pronounced positive and negative spikes in the fracture volume change rate and associated pressure fluctuations; these are accompanied by intermittent fracture opening and closure, stress redistribution, and temporary reductions in cumulative seismic moment. These findings provide new insights into the coupled mechanisms governing hydrofracturing-induced seismicity and have important implications for the assessment and mitigation of seismic risks in subsurface engineering applications. Full article

Mechanical damage remains a major constraint in low-damage harvesting and handling of the Korla fragrant pear, owing to its cultivar-specific bruise-sensitive traits (BSTs), namely its thin peel, crisp flesh, smooth epidermis, and high bruise sensitivity. This review synthesizes evidence from the Korla fragrant pear, other pear cultivars, apple, and related fresh produce to clarify damage mechanisms and engineering strategies for damage control. The reviewed studies show that injury is mainly governed by impact energy, compression load, contact stiffness, friction, fruit velocity, spacing, and transfer trajectory. Quasi-static compression and drop-impact tests provide essential thresholds, including elastic modulus, rupture force, absorbed energy, bruise area, and bruise volume, but Korla-specific data remain insufficient. Nondestructive techniques are complementary: RGB machine vision supports rapid surface screening, hyperspectral imaging improves early bruise detection, X-ray computed tomography quantifies internal bruising, and scanning electron microscopy verifies cellular damage mechanisms. FEM and DEM can predict stress distribution, deformation, collision behavior, and equipment-induced injury when calibrated with cultivar-specific parameters. Overall, apple- or general pear-based technologies require recalibration before application to the Korla fragrant pear. Future work should establish Korla-specific damage thresholds and validate detection, simulation, and conveying systems under real orchard and packing-line conditions. Full article

Rapeseed is one of the most important oil crops in the world. Its yield and quality are severely restricted by biotic stress and abiotic stress. Rapeseed seeds play a crucial role in the propagation process, and the microorganisms in the seeds can be vertically passed on to the next generation, which greatly affects the quality, yield and growth of rapeseed. However, from a group perspective, there is currently a lack of systematic research on the composition of seed-associated microbiome within rapeseed seeds. This study utilized the transcriptome data of 218 rapeseed seeds that have been published, focusing on analyzing and comparing the dynamic changes and functional differences in the composition of seed-associated microbiome in rapeseed seeds under normal growth and development, biologic stress and abiotic stress conditions. Since we used public transcriptome data without surface sterilisation control, we refered to the detected microorganisms as seed-associated microbiome. The advantage of this study lies in its application of this method to a large-scale sample of rapeseed populations, which systematically revealed the response characteristics of seed-associated microbiome under different stress conditions. Interestingly, some widely distributed genera were not detected, while rare taxa were found under specific conditions, warranting further verification. Since these microorganisms originated from the seeds, their compatibility with plants and colonization ability may far exceed those of soil-derived agents. In the future, high-throughput screening of strains with excellent antagonistic or repellent effects against major diseases and pests of rapeseed can be conducted from these unique seed-associated microbiome. These strains that were confirmed by culture-based, amplicon or metagenomic approaches can then be used to develop seed coating agents or soil inoculants. Full article

The calculation of costs for a complex edge–cloud platform operated by a telecommunications provider, which both manages networks and delivers communication and cloud services, is of fundamental importance. This work systematically addresses the evaluation of CapEx and OpEx, and thus the total cost of ownership, from a multi-period perspective for fully on-premises or hybrid edge–cloud platforms, including multi-cloud options. It also considers the computation of hourly costs of elementary resource units (e.g., vCPU), enabling cost allocation to applications and supporting service pricing. The proposed model and methods are general and adaptable to different contexts, requiring only the population of the data model and, as a next step, the platform instantiation for specific cases. The approach enables comparative analyses of multi-period deployment alternatives, including different degrees of decentralization, varying shares of public cloud resources, and sensitivity analyses on key parameters, particularly infrastructure costs. This work is developed within the IPCEI-CIS TIM Edge–Cloud Continuum project and currently is in the research phase, without application in TIM’s operational or commercial domains. Full article

Modeling thermal environments across scales is crucial for climate-adaptive design and energy management. Traditional numerical methods (e.g., CFD) offer high accuracy and physical consistency, but they are computationally expensive. In contrast, purely data-driven models, though efficient, lack physical consistency and generalization capability. This review systematically examines Physics-Informed Neural Networks (PINNs), a hybrid paradigm in which physical prior knowledge is embedded directly into the neural network training process. A structured keyword search of the Web of Science Core Collection was performed, and 94 peer-reviewed journal articles were analyzed. The evolution from numerical simulations and data-driven surrogate models to PINNs is outlined. PINN methods are classified according to the stage at which physical prior information is integrated (i.e., dataset development, model construction, or loss function formulation). Current research remains heavily focused on loss function constraints, whereas systematic integration into data augmentation and model construction remains limited. Application domains span indoor environments, outdoor environments, and building systems, with each domain exhibiting unique prior integration strategies tailored to specific problems. Future PINN modeling should evolve toward multi-physics coupling, adaptive loss balancing, cross-scenario transfer learning, and unified evaluation benchmarks. PINNs in this field are promising but remain at an early stage, especially for complex urban-scale deployment. This review synthesizes existing research around the three stages of dataset development, model construction, and loss function formulation, summarizes the prior integration strategies adopted in the domain of building thermal environments, and provides a practical workflow for embedding physical prior knowledge at different stages of model development. Full article

We propose a Bayesian kernel machine regression (BKMR) framework for count outcomes with dynamic spatiotemporal dependence. The proposed model, termed Negative Binomial BKMR with spatiotemporal effects (NB-BKMR), integrates (i) a negative binomial likelihood to accommodate overdispersion, (ii) a kernel-based exposure–response surface for complex mixtures, (iii) hierarchical group-wise variable selection and (iv) a dynamic spatiotemporal random effect structure based on a Leroux conditional autoregressive (CAR) prior evolving over time. Posterior inference is conducted in a fully Bayesian framework using Polya-Gamma data augmentation. Through simulation studies, under varying nonlinear exposure–response functions, correlation structures, and spatiotemporal dependence patterns, we show that NB-BKMR yields well-calibrated uncertainty quantification and robust identification of dominant mixture drivers, even when exposures are highly correlated. An application to the U.S. state-level traffic fatality counts (1982–1988) illustrates how the model uncovers nonlinear effects and interactions among socioeconomic and behavioral predictors while improving predictive performance relative to generalized additive models with spatiotemporal smooths. This work extends existing BKMR methodology by unifying mixture modeling, count outcomes, and dynamic spatial dependence in a single coherent framework, with particular relevance for areal public health surveillance data. Full article

Due to fractures in young and mature people, combined with aging and other factors increasing year by year, there is a demand for new materials to efficiently address fracture-healing-related issues. There are designs of new biodegradable Zn-based alloys whose chemical composition provides new opportunities to manufacture medical devices for supporting and assisting bones in their healing processes. To achieve this goal, it is well known that a strength–ductility balance and appropriate degradation are required. In this context, it is vital to know and understand how the addition of elements modifies the as-cast microstructure, which is the basis of further processing steps such as heat treatment and thermomechanical processing. In the present work, a broad characterization was performed of two as-cast hypoperitectic Zn-Ag-based alloys with Mg and Cu additions. First, cooling curves were presented, and a dissertation regarding the temperature appearance of their secondary phases was made. Also, XRD and SEM-EDS techniques were performed, and their mechanical and corrosion performance was analyzed to elucidate which third element is the best option for intended orthopedic applications. Full article

Atmospheric CO₂ concentrations have reached significant levels during the industrial era, necessitating the implementation of effective carbon dioxide removal (CDR) technologies. Enhanced Rock Weathering (ERW) using basalt has emerged as a high-potential strategy, leveraging its mafic composition to sequester CO₂ as stable carbonates. This review analyzes ERW’s geochemical processes, application methods, and multifaceted co-benefits, such as restoring “background fertility” and improving soil structure. The literature indicates that while small-scale applications range from 1.5 to 6 Mg·ha⁻¹·yr⁻¹, intensive agricultural rates typically reach 40–100 Mg·ha⁻¹·yr⁻¹. Global models estimate a sequestration potential of up to 4.9 × 10⁹ Mg CO₂·yr⁻¹ for basalt, although field-scale results vary significantly, reaching uptake rates of up to 4 Mg CO₂·ha⁻¹ depending on pedological conditions and crop types. Despite this promise, transitioning to large-scale deployment faces critical hurdles, including operational difficulties in mechanized spreading and a scarcity of audited, long-term field data. Future research must prioritize standardized protocols and comprehensive economic analyses to bridge the gap between theoretical models and empirical evidence. Ultimately, ERW represents a multifaceted solution for climate stabilization and sustainable food security, provided that sequestration efficacy and environmental safety are rigorously verified through high-application field trials. Full article