Search Results (3,198)

Integrating Wire Arc Additive Manufacturing (WAAM) into the Selective Paste Intrusion (SPI) process enables the fully additive fabrication of reinforced concrete structures with complex geometries. Previous investigations have demonstrated that the thermal impact of the WAAM process can adversely affect the SPI process. Thus, dedicated cooling strategies are required. One proposed approach increases the vertical distance between the welding point and the particle bed by introducing a defined vertical protrusion of the reinforcement bar. This configuration may give rise to shadowing effects, here understood as a process-induced disturbance of material deposition in the vicinity of the protruding bar. Two distinct manifestations are considered in parallel. The first is a geometrically projected shadowed region within the particle bed, depending on bar diameter and inclination. The second is a layer-wise modification of the contact zone along the lower half of the bar surface within the bond length, largely independent of inclination. To isolate the geometric component from thermal effects, the present study focuses on controlled reinforcement configurations with constant vertical protrusion. Two hypotheses are tested: bond decreases with increasing bar diameter (H1), and, at constant diameter, with decreasing inclination angle (H2), the latter being the signature of the projected shadow. To assess these effects, reinforcement bars with a constant vertical protrusion of 40$\mathrm{m}$$\mathrm{m}$ and varying inclination angles were embedded into the particle bed, and concrete specimens were produced above them using the SPI process. Bar diameters of 8$\mathrm{m}$$\mathrm{m}$, 16$\mathrm{m}$$\mathrm{m}$, and 25$\mathrm{m}$$\mathrm{m}$ and inclination angles from 0 to 90 in 15 increments were investigated systematically. Bond strength was determined using push-through tests derived from RILEM RC6, and the bond response was evaluated against both a quantitative measure of the projected shadowed area and a process-based indicator of the affected contact zone. The bar diameter dominates the bond response, most pronounced at the developed-interlock and capacity levels. The inclination angle produces no monotonic trend from 0 to 90, and individual angle contrasts remain largely within the experimental scatter. The projected shadowed area cannot consistently explain the observed behaviour and is at most a secondary factor, whereas the layer-wise contact-zone disturbance along the lower bar surface is the most probable interpretation of the data. The findings identify shadowing as a boundary condition for reinforcement integration in SPI: the observed bond reduction at the developed-interlock and capacity levels is attributed to the layer-wise contact-zone disturbance rather than to the projected shadowed area, an attribution that remains a hypothesis until the contact zone has been verified directly. Full article

Automatic license-plate recognition (ALPR) systems typically rely on a two-stage pipeline that combines object detection with optical character recognition (OCR), whereas recent vision–language models (VLMs) enable direct image-level recognition without task-specific training. This paper presents a comprehensive comparison between these paradigms under limited target-domain data availability. We evaluate a plate-specific YOLO11x detector combined with four OCR backends and five locally hosted open-weight VLMs, without training or fine-tuning on a study-specific Serbian dataset containing 435 images and 643 visible license plates, annotated with image-level plate counts, registration transcriptions, and plate-level bounding boxes. Performance is assessed using strict end-to-end success, exact-match accuracy, character error rate, readable-plate recall, plate-count accuracy, and inference speed. The comparison is further validated on the OpenALPR-EU and UC3M-LP benchmarks. Finally, we investigate the effect of increasing target-domain annotation budgets by incrementally fine-tuning the YOLO detector on UC3M-LP to determine when a conventional detector–OCR pipeline overtakes zero-shot VLMs. The results demonstrate complementary strengths rather than a universal winner. YOLO11x combined with FastPlateOCR achieves the highest transcription accuracy and is approximately 13× faster than the best-performing VLM; the three general-purpose OCR backends collapse on identical detections, so these figures characterize the strongest available plate-specific recognizer rather than detector–OCR pipelines in general, while Qwen3-VL provides superior image-level plate-count accuracy in the zero-shot setting, an advantage concentrated in single-plate scenes. The annotation-budget study shows that a few hundred labeled localization annotations substantially improve the conventional pipeline, enabling it to surpass zero-shot VLMs in character recovery, although VLMs retain an advantage in image-level plate counting. These findings provide practical guidance for selecting ALPR systems according to annotation availability, deployment constraints, and application objectives. Full article

Large-scale ecological restoration has greatly boosted carbon sequestration across China’s Loess Plateau, yet the long-term sustainability of restoration-fueled carbon growth remains unclear. This study constructs a dynamic carbon stock mapping framework integrating GEDI LiDAR, Landsat time-series data and the dynamic InVEST model for ecosystem carbon accounting to analyze carbon accumulation trends from 2000 to 2025. Regional total carbon storage rose from 8088.65 Tg C to 9269.54 Tg C, with a net gain of 1180.89 Tg C, but carbon growth slowed markedly. The share of regions with notable carbon growth dropped sharply from 77.92% (2000–2013) to merely 1.50% (2013–2025). Logistic modeling shows 2025 carbon storage hit roughly 96.3% of its estimated saturation threshold, meaning room for fast carbon accumulation is shrinking. SHAP analysis identifies SWIR1 (31.1%) and NDVI (15.9%) as primary predictors contributing to biomass carbon variation, with nonlinear relationships proving moisture and vegetation jointly shape carbon accumulation. PLUS model simulations show ecological priority land-use scenarios deliver stronger carbon storage capacity than cropland protection or natural development schemes, though future carbon increments will be far smaller than historical gains. Ultimately, this study confirms that the Loess Plateau carbon sink is transitioning from restoration-facilitated rapid expansion to environmentally constrained slow growth, with current carbon storage approaching 96.3% of the regional ecohydrological carrying capacity. Full article

This paper develops a finite-horizon stochastic optimal harvesting model that links constrained Hamilton-Jacobi-Bellman (HJB) control with a nonlinear Feynman-Kac/BSDE representation. Harvesting effort is bounded, yielding a projected feedback policy with lower-bound, interior, and upper-saturation regimes. Under appropriate regularity conditions, the HJB and BSDE formulations characterize the same value function and optimal feedback through the Markovian relation $Z_s=\sigma X_s{J}_X^{\ast }(s,X_s)$. Numerically, the HJB equation is solved using a monotone implicit upwind Bellman scheme with policy iteration, while the associated BSDE is approximated independently by Monte Carlo conditional-expectation regression, permitting an ex post assessment of numerical consistency. The framework is illustrated using annual capture fisheries production data for the United States, Japan, China, and Indonesia. Country-specific drift and multiplicative volatility are estimated from normalized state-relative increments. The empirical state is interpreted as a normalized capture-production index rather than a biological stock, providing a data-informed illustration of constrained harvesting under stochastic dynamics and uncertainty. Full article

Background: Ischemic heart disease (IHD) diagnosis is complicated by anatomical-functional dissociation, where morphological stenosis severity fails to reliably predict hemodynamic significance. This diagnostic gap necessitates a shift toward integrated physiological and structural phenotyping, a role increasingly fulfilled by Cardiovascular Magnetic Resonance (CMR). Objective: To systematically evaluate the incremental diagnostic and prognostic value of CMR across the clinical spectrum of IHD, defining its evidence-based integration into multimodal pathways, particularly for diagnostically indeterminate cases. Methods: A systematic review was conducted in accordance with the PRISMA guidelines. A structured literature search of PubMed, Web of Science, and Scopus retrieved peer-reviewed articles published between January 2021 and April 2026. Methodological quality was appraised using the Newcastle–Ottawa Scale and AMSTAR 2, while evidence certainty was evaluated via the GRADE framework. Results: Thirty studies were included in the qualitative synthesis. Current evidence demonstrates that stress perfusion CMR provides superior diagnostic accuracy compared with traditional tests (e.g., SPECT, stress ECG), although it may be outperformed by advanced CT-derived fractional flow reserve in specific post-CCTA cohorts. In indeterminate presentations such as MINOCA, CMR accurately reclassified the underlying etiology in approximately 68% of cases. Furthermore, multiparametric assessment—integrating late gadolinium enhancement (LGE), microvascular obstruction (MVO), and global longitudinal strain (GLS)—refined post-infarction short- and medium-term risk stratification beyond LVEF alone, though the independent prognostic value of MVO attenuates in long-term follow-up (>6 years). Emerging data support the non-inferiority of accelerated stress-only protocols and the utility of artificial intelligence-driven analytics. Conclusions: CMR is a critical modality for resolving anatomical-functional mismatches and providing robust risk stratification. However, evidence does not support its use as a universal first-line test due to operational costs, scan duration, and patient contraindications. Expanding its clinical impact relies strictly on standardizing protocols and adopting AI-assisted, accelerated sequences to mitigate logistical barriers. Full article

Geopolitical uncertainty may affect financial markets, but its incremental value for forecasting emerging-market stock returns remains unclear. Using monthly data from January 1990 to July 2026, this study compares ARIMA-GARCH and ARIMAX-GARCH benchmarks with Random Forest, XGBoost, LightGBM, and a zero-return benchmark across 1-, 3-, 6-, and 12-month horizons. Forecasts are generated with a target- and predictor-leakage-safe expanding-window design: training targets never exceed the forecast origin, and no realized future predictor values are used. Econometric forecasts are conditional on fixed ARIMA and ARIMAX orders selected during full-sample diagnostics. Among the estimated models, XGBoost achieves the lowest RMSE and MAE at three months, Random Forest has the lowest RMSE at one and six months, and ARIMA-GARCH performs best at twelve months. Nevertheless, the zero-return benchmark records the lowest RMSE at every horizon, while Diebold–Mariano tests generally do not reject equal predictive accuracy, and the Model Confidence Set retains multiple competitive models. Rolling SHAP analysis ranks geopolitical risk first among 16 predictors in the three-month XGBoost model, accounting for 14.38% of aggregate mean absolute attribution. Thus, geopolitical risk provides model-specific short-horizon conditioning information, but its standalone accuracy gain is modest, statistically insignificant, and absent at twelve months. Full article

GNSS cycle-slip diagnostics require thresholds that transfer across receivers and observation conditions. We combine causal dual-frequency phase–Doppler innovations (PDI), current-epoch common-mode subtraction, trailing robust normalization, worst-source quantile calibration, and half-cycle-grid ambiguity-increment repair. Three IGS source stations and an expanded station-disjoint target cohort of five stations supplied four separated 15 min blocks per station at native 1 s and decimated 5 s sampling. Two targets were usable from the original list; three were added after the primary run but before their data were inspected. Threshold calibration is source-only, whereas score normalization uses the causal target-stream history. At 1 s and the 1% source budget, PDI produced a 1.114% unmodified-background alarm rate (UBAR), 98.68% detection, and 98.34% exact dual-frequency repair over 3184 seeded event epochs. A post hoc fixed-score audit reduced UBAR from pooled calibration’s 1.284% without changing event success. A stronger covariance-weighted GF/MW integer-search control repaired 96.86% on the half-cycle grid; PDI’s paired five-station repair-gain interval was 0.19–2.97 percentage points. On integer-only events the control slightly exceeded PDI, and at 5 s it repaired 81.97% versus PDI’s 54.99%. Thus, the large advantage over componentwise GF/MW rounding does not extend to all classical repair estimators. The sampling-rate comparisons use separately generated, identically specified injection ensembles rather than paired physical events. The contribution is source-only threshold calibration with causal target-stream normalization, not universal repair superiority. UBAR includes unlabeled natural events; moving-receiver transfer and downstream positioning benefit remain unvalidated. Full article

Background: Metabolic age (Met-Age), a bioelectrical impedance analysis (BIA)-derived index based on basal metabolic rate (BMR) and body composition, has been associated with cardiometabolic risk. However, its relationship with body mass index (BMI)-defined obesity severity in individuals with type 2 diabetes mellitus (T2DM) remains unclear. This study investigated the association between obesity severity and Met-Age and identified factors associated with Met-Age. Methods: In this retrospective observational study, 683 adults with T2DM were classified into five BMI categories: normal weight, overweight, and class I, II, and III obesity. Anthropometric, laboratory, and BIA-derived body composition data were analyzed using correlation and sex-stratified multivariable linear regression analyses. Results: Although chronological age did not differ significantly across groups, Met-Age increased progressively with increasing obesity severity (p < 0.001). The Jonckheere–Terpstra test confirmed a significant ordered increase in Met-Age across BMI categories. BMI, fat mass, and waist-to-height ratio (WHtR) also increased progressively with increasing obesity severity. In the multivariable regression analyses, chronological age and WHtR were positively associated with Met-Age in both sexes, whereas muscle mass showed a weak inverse association with Met-Age only in female participants. No significant correlations were found between Met-Age and fasting blood glucose (FBG) or hemoglobin A1c (HbA1c) levels (all p > 0.05). Conclusions: In individuals with T2DM, greater obesity severity was associated with higher BIA-derived Met-Age. WHtR was positively associated with Met-Age in both sexes, whereas muscle mass showed a weak inverse association among female participants. Met-Age may serve as a descriptive index reflecting body composition and metabolic characteristics; however, its incremental clinical value beyond BMI and WHtR remains unproven. Full article

Background/Objectives: Published estimates of artificial-intelligence (AI) accuracy for dental caries differ in imaging modality, lesion threshold, observational unit, reference standard, and validation design. We mapped the clinical composition and credibility of this evidence and summarized clinician-plus-AI studies separately. Methods: Five databases were searched through 10 June 2026. Eligible diagnostic-accuracy studies used clinically acquired human dental data. QUADAS-3 and a structured GRADE-DTA assessment were applied. Because the studies did not address a common clinical question, no pooled operating point was estimated. Results: A total of 29 reports representing 28 studies were included. Overall risk of bias was high for all 28 estimates; only five studies used external validation. Twelve standalone-AI reports supplied exact, coherent 2 × 2 data. Their sensitivity ranged from 0.360 to 0.940 and specificity from 0.700 to 0.983. The exact-data subset was an availability sample, and most nominal uncertainty estimates could not account for clustering. Two controlled reader studies reported higher sensitivity with AI assistance, accompanied by lower specificity in one study and more invasive treatment decisions in the other. Certainty was very low for both standalone accuracy and incremental clinician benefit. Conclusions: The evidence does not support a transferable accuracy benchmark or a conclusion of net clinical benefit. Locked-model external validation and paired prospective evaluations with patient-relevant outcomes are needed. Full article

Long-term lake storage monitoring remains challenging in data-scarce high-elevation regions because continuous water-level records and bathymetric data are often unavailable. Annual Landsat-derived areas of Xiao Qaidam Lake from 1996 to 2025 were combined with DEM-based height–area–volume (H–A–V) relationships to reconstruct DEM-referenced relative water-level anomalies and DEM scenario-based relative volume anomalies. Sentinel-2, three DEMs, ICESat-2 ATL13, uncertainty propagation, and buffer tests were used for evaluation. All three DEM scenarios showed long-term increases but different magnitudes. FABDEM contained a 91.04 km² low-elevation platform, 99.9% of which overlapped the 2011–2015 water-mask union, consistent with source-period water-body flattening or gap filling. Lake area increased from 78.42 to 126.63 km². Across the three DEM scenarios, the 2025 DEM-referenced relative water-level anomalies ranged from 3.29 to 3.99 m, and the 2025 DEM scenario-based relative volume anomalies ranged from 3.46 to 4.14 × 10⁸ m³. Without bathymetric validation, the magnitude of ΔV remains DEM scenario-dependent. During 2019–2025, DEM-referenced relative water-level anomalies were consistent with ATL13 relative water-level anomalies (r = 0.885; RMSE = 0.195 m). Annual relative volume increments were positively associated with climatic water balance. The framework provides a DEM-aware approach for monitoring relative water-level and volume anomalies in data-scarce closed basins. Full article

Although perfectionism has received considerable attention from organizational scholars, research on how it enhances employee creativity remains limited. Drawing on the model of proactive motivation and trait activation theory, this study investigates the relationship between employees’ self-oriented perfectionism and creativity (including both radical and incremental creativity), with job crafting as a mediating mechanism. In addition, we incorporate work stress as a moderator and propose a moderated mediation model. Multi-wave survey data were collected from employees in several Chinese organizations. The results show that self-oriented perfectionism is positively associated with both radical and incremental creativity, and that job crafting mediates these relationships. Furthermore, work stress moderates the mediated relationships, such that the positive indirect associations are stronger when work stress is higher. Theoretical and practical implications are discussed. Full article

Background: Accurate sales forecasting supports inventory planning, resource allocation, revenue management, and operational decision-making. However, the incremental predictive value of external factors such as weather, beyond historical sales information, remains important to assess. This study evaluates an interpretable forecasting framework for daily-location sales revenue and examines the relative contributions of historical and weather information. Methods: Daily sales data were integrated with weather observations and temporal lag features. Random Forest, Extreme Gradient Boosting, CatBoost, and Stacked Long Short-Term Memory (LSTM) models were used for forecasting. Performance was assessed using mean absolute error, root mean squared error, symmetric mean absolute percentage error, and R². Results: Stacked LSTM achieved the strongest overall test performance (MAE = 28.50, RMSE = 57.04, sMAPE = 5.82%, R² = 0.972). Feature-importance analysis indicated that historical sales, particularly one-day sales lag, provided a stronger predictive signal than individual weather variables. Conclusions: Historical sales information was the primary predictive signal, while weather provided supplementary information. From a practical perspective, the framework can support revenue-oriented forecasting and help assess the additional value of incorporating weather information. This study also contributes to forecasting research by distinguishing the predictive role of historical sales patterns from the incremental contribution of external contextual variables. Full article

To address current-density ramping, cell-voltage increase, and elevated operating stress in anion exchange membrane water electrolyzers (AEMWEs) under fluctuating wind and photovoltaic (PV) power inputs, this study develops a dynamic AEMWE model that couples voltage losses, thermal dynamics, and water-management states. A forecast-assisted reference governor based on short-term power prediction and dynamic constraints is further proposed. Using German Open Power System Data (OPSD) wind and PV, the effects of power-command correction on current density, voltage efficiency, specific energy consumption (SEC), voltage-limit exceedance, and a degradation-related stress proxy are analyzed. The steady-state benchmark distinguishes a separate 21-point empirical polarization fit (same-set RMSE 0.0059 V and MAPE 0.292%) from the mechanistic voltage-loss model actually used in the dynamic simulations (same-set RMSE 0.5063 V and MAPE 28.42%); consequently, the dynamic results are treated as model-conditioned rather than experimentally validated. In the 24 h case, explicit state-constrained smoothing reduced the maximum cell voltage from 2.2479 to 2.1501 V and SEC from 59.4755 to 58.1968 kWh kg⁻¹, but hydrogen yield and renewable-energy utilization decreased from 1.51997 to 0.54293 kg d⁻¹ and from 99.52% to 34.78%, respectively. The forecast envelope did not bind on the selected smooth day; across 30 representative days it reduced the stress proxy relative to the no-look-ahead state-constrained baseline on only 3–6 days depending on wind–PV composition, while in a diagnostic ramp-down case it activated 10 times and reduced cumulative ramping by 6.7% at the cost of a 16.9% hydrogen-yield loss. These results provide model-based exploratory evidence and separate the benefit of state projection from the incremental value of prediction. Full article

Heart transplantation remains the gold-standard therapy for selected patients with end-stage heart failure, yet acute rejection and cardiac allograft vasculopathy (CAV) continue to limit long-term survival. While endomyocardial biopsy and coronary angiography remain the reference standards for diagnosing rejection and CAV, respectively, echocardiography offers a non-invasive, repeatable tool for the longitudinal surveillance of heart transplant recipients. This review summarizes the expected echocardiographic findings following orthotopic heart transplantation according to surgical technique (biatrial versus bicaval) and describes the echocardiographic features of early graft dysfunction, acute allograft rejection, and late graft failure due to cardiac allograft vasculopathy. We also discuss the incremental value of newer echocardiographic techniques—including speckle-tracking-derived strain, myocardial work, and three-dimensional echocardiography—in detecting subclinical left ventricular and right ventricular dysfunction that may precede changes detectable by conventional parameters. No single echocardiographic parameter reliably diagnoses rejection or vasculopathy in isolation; an integrated, multiparametric approach combined with clinical data is required. Emerging techniques hold promise for reducing reliance on invasive surveillance, although further validation in larger, multicenter cohorts is needed. This review aims to provide echocardiographers and transplant cardiologists with a practical, imaging-based framework for the follow-up of heart transplant recipients across the early postoperative period and long-term surveillance. Full article

The stability of engineering structures in frozen regions is primarily governed by the coupled evolution of temperature, moisture migration, and stress fields driven by freeze–thaw cycles. In this study, a typical embankment section in Heilongjiang Province, a seasonally frozen region of China, is selected as a case study. To investigate the influence of river operating water levels on the spatiotemporal evolution of temperature and deformation fields in freeze–thaw cycles, this study establishes a thermo-hydro-mechanical (THM) numerical analysis framework through Python 3.8.10.-based ABAQUS secondary development. A representative annual ground-surface temperature boundary derived from ERA5-Land reanalysis data is adopted as the continuous thermal boundary condition. Two middle-drainage water states, namely water-filled drainage and water-free drainage, are considered. Design and check water levels are applied to evaluate the evolution of the temperature field, freezing depth, and deformation in freeze–thaw cycles for the embankment section soil. The predicted temperatures show seasonal trends consistent with ERA5-Land soil-temperature reanalysis data at depths of 0, 25, and 50 cm. The maximum freezing depth at the representative location on the left slope is 1.66 m, which falls within the field-measured freezing-depth range of 1.5–2.0 m. These comparisons indicate that the temperature-field and freezing-depth simulations are reasonable. Under all operating conditions, soil deformation accumulates with freeze–thaw cycles and shows a stabilization trend characterized by rapid early growth and small later increments. After the ninth cycle, the maximum deformations under the water-filled/design-level, water-filled/check-level, water-free/design-level, and water-free/check-level conditions are 15.49, 15.95, 17.81, and 18.48 mm, respectively; these values are far smaller than the reserved settlement allowance of 18 cm. Compared with the water-filled case, the deformation for the water-free case increases by approximately 15.0% under the design water level and 15.9% under the check water level. The results indicate that the condition of water-filled drainage is a dominant factor in freeze–thaw deformation, and water level fluctuation is another influencing factor. Full article