Search Results (258)

The growing penetration of distributed photovoltaic (PV) systems presents significant operational challenges for power grids, driven by the scarcity of historical data and the high spatiotemporal variability of PV generation. To address these challenges, we propose Generative Reconstruction and Adaptive Identification via Latents (GRAIL), a unified, end-to-end framework that integrates generative modeling with adaptive clustering to discover latent structures and representative scenarios in PV datasets. GRAIL operates through a closed-loop mechanism where clustering feedback guides a cluster-aware data generation process, and the resulting generative augmentation strengthens partitioning in the latent space. Evaluated on a real-world, multi-site PV dataset with a high missing data rate of $45.4\%$, GRAIL consistently outperforms both classical clustering algorithms and deep embedding-based methods. Specifically, GRAIL achieves a Silhouette Score of 0.969, a Calinski–Harabasz index exceeding $4.132\times {10}^6$, and a Davies–Bouldin index of $0.042$, demonstrating superior intra-cluster compactness and inter-cluster separation. The framework also yields a normalized entropy of $0.994$, which indicates highly balanced partitioning. These results underscore that coupling data generation with clustering is a powerful strategy for expressive and robust structure learning in data-sparse environments. Notably, GRAIL achieves significant performance gains over the strongest deep learning baseline that lacks a generative component, securing the highest composite score among all evaluated methods. The framework is also computationally efficient. Its alternating optimization converges rapidly, and clustering and reconstruction metrics stabilize within approximately six iterations. Beyond quantitative performance, GRAIL produces physically interpretable clusters that correspond to distinct weather-driven regimes and capture cross-site dependencies. These clusters serve as compact and robust state descriptors, valuable for downstream applications such as PV forecasting, dispatch optimization, and intelligent energy management in modern power systems. Full article

This study investigates the causal impact of board governance structures on firm profitability. We develop the Board Structure Influence (BSI) index, a composite metric that captures board independence, diversity, and role distribution—which we conceptualize as three structural pillars of Separation, Variety, and Disparity—to provide a comprehensive measure of governance effectiveness. Using a Difference-in-Differences (DiD) framework centered on the COVID-19 pandemic as an exogenous shock, we identify firms with strong governance and top BSI quartiles and compare their financial performance—measured by net profit margin—against firms with weaker board structures. Our results demonstrate that firms with higher BSI scores experience a statistically significant increase in profitability post-COVID-19. A Causal Forest analysis further reveals that this positive effect is heterogeneous, with the largest firms benefiting most significantly from strong board governance. Robustness checks—including placebo tests, parallel trends validation, and a SUTVA test—affirm the credibility of our findings. This research highlights the strategic importance of board structure for firm resilience during crises. It provides management insights for corporate leaders, investors, and policymakers aiming to align governance reform with financial profitability. Full article

This study investigates the multifaceted impact of digitalization on economic performance across the 27 European Union member states from 2017 to 2023. Using a comprehensive panel dataset, the analysis moves beyond aggregate metrics to dissect how specific digital levers contribute to trade performance and national income. A two-way fixed effects (FEs) regression model is employed to rigorously control for unobserved country-specific heterogeneity and common time-based shocks, with diagnostic tests confirming the suitability of this specification. The results reveal a complex and often counter-intuitive set of relationships. One key finding is a statistically significant negative association between the EU’s headline Digital Economy and Society Index (DESI) and goods exports, a paradox that emerges in the model once specific business-level digital tools are accounted for. This suggests that composite indices can be misleading for granular policy analysis. The marginal benefit of cloud adoption diminishes significantly in countries with higher levels of public investment in Research and Development (R&D), indicating a substitution rather than a complementary relationship between these two innovation channels. Full article

Driving wheel slippage in agricultural tractors is influenced by soil moisture, density, and penetration resistance. These surface variations reflect post-tillage composition, enabling dynamic mapping via Remotely Piloted Aircraft (RPAs). This study evaluated ballast recommendations based on soil surface data and slippage percentages, correlating added wheel weights at different speeds for a tractor-reversible plow system. Six 94.5 m² quadrants were analyzed for slippage monitored by RPA (Mavic3M-RTK) pre- and post-agricultural operation overflights and soil sampling (moisture, density, penetration resistance). A 2 × 2 factorial scheme (F-test) assessed soil-surface attribute correlations and slippage under varying ballasts (52.5–57.5 kg/hp) and speeds. Results showed slippage ranged from 4.06% (52.5 kg/hp, fourth reduced gear) to 11.32% (57.5 kg/hp, same gear), with liquid ballast and gear selection significantly impacting performance in friable clayey soil. Digital Elevation Model (DEM) and spectral indices derived from RPA imagery, including Normalized Difference Red Edge (NDRE), Normalized Difference Water Index (NDWI), Bare Soil Index (BSI), Green–Red Vegetation Index (GRVI), Visible Atmospherically Resistant Index (VARI), and Slope, proved effective. The approach reduced tractor slippage from 11.32% (heavy ballast, 4th gear) to 4.06% (moderate ballast, 4th gear), showing clear improvement in traction performance. The integration of indices and slope metrics supported ballast adjustment strategies, particularly for secondary plowing operations, contributing to improved traction performance and overall operational efficiency. Full article

This paper presents the development of a high-resolution composite index to monitor and quantify climate-related risks across Italy. The country’s complex climatic variability, extensive coastline, and low insurance penetration highlight the urgent need for robust, locally calibrated tools to bridge the climate protection gap. Building on the methodological framework of existing actuarial climate indices, previously adapted for France and the Iberian Peninsula, the index integrates six standardised indicators capturing warm and cool temperature extremes, heavy precipitation intensity, dry spell duration, high wind frequency, and sea level change. It leverages hourly ERA5-Land reanalysis data and monthly sea level observations from tide gauges. Results show a clear upward trend in climate anomalies, with regional and seasonal differentiation. Among all components, sea level is most strongly correlated with the composite index, underscoring Italy’s vulnerability to marine-related risks. Comparative analysis with European indices confirms both the robustness and specificity of the Italian exposure profile, reinforcing the need for tailored risk metrics. The index can support innovative risk transfer mechanisms, including climate-related insurance, regulatory stress testing, and resilience planning. Combining scientific rigour with operational relevance, it offers a consistent, transparent, and policy-relevant tool for managing climate risk in Italy and contributing to harmonised European frameworks. Full article

This study introduces the Normalized Difference Gamma Ray Index (NDGRI), a novel spectral composite derived from Sentinel 2 imagery for mapping elevated natural gamma radiation in semi-arid and arid basins. We hypothesized that water-sensitive spectral indices correlate with gamma-ray hotspots in arid regions of Mongolia, where natural radionuclide distribution is influenced by hydrological processes. Leveraging historical car-borne gamma spectrometry data collected in 2008 across the Sainshand and Zuunbayan uranium project areas, we evaluated twelve spectral bands and five established moisture-sensitive indices against radiation heatmaps in Naarst and Zuunbayan. Using Pearson and Spearman correlations alongside two percentile-based overlap metrics, indices were weighted to yield a composite performance score. The best performing indices (MI—Moisture Index and NDSII_1—Normalized Difference Snow and Ice Index) guided the derivation of ten new ND constructs incorporating SWIR bands (B11, B12) and visible bands (B4, B8A). The top performer, NDGRI = (B4 − B12)/(B4 + B12) achieved a precision of 62.8% for detecting high gamma-radiation areas and outperformed benchmarks of other indices. We established climatological screening criteria to ensure NDGRI reliability. Validation at two independent sites (Erdene, Khuvsgul) using 2008 airborne gamma ray heatmaps yielded 76.41% and 85.55% spatial overlap accuracy, respectively. Our results demonstrate that NDGRI effectively delineates gamma radiation hotspots where moisture-controlled spectral contrasts prevail. The index’s stringent acquisition constraints, however, limit the temporal availability of usable scenes. NDGRI offers a rapid, cost-effective remote sensing tool to prioritize ground surveys in uranium prospective basins and may be adapted for other radiometric applications in semi-arid and arid regions. Full article

The objective of this study was to assess the changes in adiponectin concentrations and inflammatory markers in men with abdominal obesity following physical exercise and exercise combined with dietary intervention. This study included 44 males with abdominal obesity (mean age 34.7 ± 5.5 years, waist circumference [WC] 110.3 ± 8.5, BMI 32.0 ± 3.9), who were randomly assigned to three groups: a control group without interventions (CG, n = 12), an experimental group engaging in aerobic-resistance exercise (EG, n = 16) and a group engaging in aerobic-resistance exercise combined with an ad libitum high-protein, low-glycemic index carbohydrate diet (EDG, n = 16). Body composition metrics: the body fat-, fat-free mass-, and abdominal fat-to body mass (BF/BM, FFM/BM, ABD/BM) indexes and the body adiposity index (BAI), along with biochemical blood analyses—adiponectin (ADIPO), interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), Castelli-II Index (CRI II) and fasting glucose–insulin (FG/I) ratio—were measured at baseline and after the intervention. The effects of the interventions on the analyzed variables across groups were assessed using mixed ANOVA tests with post hoc comparisons. Effect size (ES) was also calculated using partial eta squared (ηp²). The exercise intervention (EG) resulted in a significant reduction in the BAI (p < 0.01), insulin resistance FG/I (p < 0.02), and IL-6 concentrations (p < 0.01) and initiated an increase in ADIPO secretion (p = 0.03). The combined intervention (EDG) reduced the insulin resistance FG/I (p = 0.02) and atherogenic index CRI II (p = 0.01), decreased inflammatory markers IL-6 (p = 0.01) by 48% and hs-CRP (p = 0.04) by 30%, and simultaneously increased the ADIPO (p = 0.02) concentration by 15%. These effects were accompanied by significant changes in body composition: reductions in visceral fat ABD/BM (p < 0.01), total fat BF/BM (p < 0.01), and BAI (p = 0.02) and an increase in FFM/BM (p < 0.01). A crucial role in achieving these outcomes was played by dietary modifications, i.e., the inclusion of low-glycemic index carbohydrates (p < 0.01), a 23% increase in protein intake (p < 0.01), and a 50% increase in dietary fiber intake (p < 0.01), which consistently deepened the energy deficit (p < 0.01) and reduced fat intake (p < 0.01). These findings underscore that short-term interventions, whether exercise alone or combined with dietary modifications, can effectively reduce inflammation and lower insulin resistance in men with visceral obesity. However, the combined intervention, involving both exercise and dietary modifications, resulted in more pronounced beneficial changes in both body composition and concentrations of adipokines, inflammatory markers, and atherogenic indices and insulin resistance. Full article

This review provides a comprehensive synthesis of the coupled effect of temperature and solar radiation on photovoltaic (PV) module performance and lifespan. Although numerous investigations have examined these stressors in themselves, this research addresses their interrelationship and evaluates the way climatic conditions affect short-term performance fluctuation and long-term degradation mechanisms. The assessment consolidates outcomes from model strategies, laboratory tests, and field monitoring studies. Through the presentation of these findings in a narrative form, the paper identifies recurring difficulties in terms of the absence of shared assessment metrics and the low level of standardisation of long-term test regimes. Second, it underlines the importance of predictive modelling and live monitoring as important management tools for coupled stressors. Finally, the review points out research gaps and underscores future research avenues, including ongoing work towards the development of a coupling index, a composite measure being piloted in individual studies, and advancements in materials technology, predictive methodology, and durability testing. Full article

The acceleration of global population aging has driven a surge in demand for health monitoring among older adults. However, traditional mobility assessment methods mostly rely on invasive measurements or laboratory-grade equipment, making it difficult to achieve continuous monitoring in daily scenarios. This study investigated the correlation between dynamic gait characteristics and static body metrics to enhance the understanding of elderly mobility and overall health. A sensor-based framework was implemented, which utilizes the Short Physical Performance Battery (SPPB), combined with PoseNet (a vision-based sensor) for dynamic gait analysis, and the InBody bioelectrical impedance device for static body composition assessment. Key variables comprised the dynamic metric mean directional shift and static metrics, including skeletal muscle index (SMI), skeletal muscle mass (SMM), body fat percentage (PBF), visceral fat area (VFA), and intracellular water. Nineteen elderly participants aged 60–89 years underwent assessments; among them, 16 were males (84.21%), and 3 were females (15.79%), 50% were in the 80–89 age group, 95% did not live alone, and 90% were married. Dynamic gait data were analyzed for center displacement and horizontal directional shifts. A Pearson correlation analysis revealed that the mean directional shift positively correlated with SMI ($\rho =0.561$, $p<0.01$), SMM ($\rho =0.496$, $p<0.01$), and intracellular water ($\rho =0.497$, $p<0.01$), highlighting the role of muscle strength in movement adaptability. Conversely, negative correlations were found with PBF ($\rho =-0.256$) and VFA ($\rho =-0.342$, $p<0.05$), suggesting that greater fat mass impedes dynamic mobility. This multimodal integration of dynamic movement patterns and static physiological metrics may enhance health monitoring comprehensiveness, particularly for early sarcopenia risk detection. The findings demonstrate the framework’s potential, indicating mean directional shift as a valuable dynamic health indicator. Full article

First-principles density-functional theory (PBE, Quantum ESPRESSO) was employed to quantify how Fe substitution modulates the structural, elastic, electronic, and optical behaviour of cubic fluorite Fe_xZr_1−xO₂ (x = 0.00–1.00). The fluorite FeO₂ end member was treated as a hypothetical ambient-pressure limit to trace trends across the solid solution (experimental FeO₂ being stabilized in the high-pressure pyrite phase). Mechanical stability was verified via the cubic Born criteria, and composition-dependent stiffness and anisotropy were assessed through Voigt–Reuss–Hill moduli, Pugh ratio, and elastic indices. A strong band-gap narrowing was found—from 3.41 eV (x = 0) to ≈0.02 eV (x = 0.50)—which was accompanied by a visible–NIR red-shift, large absorption (α ≈ 10⁵ cm⁻¹ at higher x), and enhanced refractive index and permittivity; metallic-like response was indicated at high Fe content. Spin-polarized calculations converged to zero total and absolute magnetization, indicating a non-magnetic ground state at 0 K within PBE. The effect of oxygen vacancies (V₀)—expected under Fe³⁺ charge compensation—was explicitly considered: V₀ is anticipated to influence lattice metrics, elastic moduli (B, G, G/B), and sub-gap optical activity, potentially modifying stability and optical figures of merit. Stoichiometric (formal Fe⁴⁺) predictions were distinguished from V₀-rich scenarios. Absolute band gaps may be underestimated at the PBE level. Full article

Background/Objectives: Cardiopulmonary exercise testing (CPET) is a well-established tool for risk stratification in patients with heart failure (HF); however, its utility is limited in routine clinical practice due to the associated cost and technical demands. The hemodynamic gain index (HGI), a non-metabolic parameter derived from systolic blood pressure and heart rate changes during exercise, has been demonstrated to play a promising role in HF populations. In this study, we aimed both to validate the prognostic value of the HGI and to evaluate a novel metric, heart hemodynamic reserve (HHR), in patients with HF and left ventricular ejection fraction (LVEF) below 50%. Methods: We retrospectively enrolled 479 consecutive patients with HF and reduced or mildly reduced LVEF who underwent maximal, symptom-limited CPET at three Italian university hospitals between 2012 and 2024. The HGI and HHR were computed using resting and peak exercise hemodynamic data. HHR is defined as the product of systolic blood pressure and heart rate reserve with exercise, normalized for the age-predicted maximum heart rate. The primary endpoint was a composite of cardiovascular death, urgent heart transplantation (HTx), or left ventricular assist device (LVAD) implantation. Prognostic associations were assessed using multivariable Cox regression and area under the receiver operating characteristic curves (AUCs). Results: During a median follow-up of 3.25 years, the composite outcome occurred in 56 patients (11.5%). Both the HGI and HHR were independently associated with the prespecified endpoint (HGI HR: 0.41, 95% CI: 0.20–0.83, p = 0.013; HHR HR: 0.89, 95% CI: 0.83–0.96, p = 0.004), with HHR showing a slightly higher prognostic accuracy than the HGI (AUC 0.78 vs. 0.74; p = 0.033). Conclusions: Both the HGI and HHR are independent prognostic markers in HF patients with LVEF < 50%. Their non-metabolic derivation makes them valuable tools for risk stratification in settings where CPET is unavailable. Full article

Tropical cyclones (TCs) over the Arabian Sea pose significant threats to coastal populations and result in substantial economic losses, yet their variability in response to major climate modes remains insufficiently understood. This study examines the relationship between the El Niño–Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and the Indo-Pacific Warm Pool (IPWP) with TC activity over the Arabian Sea from 1982 to 2021. Utilizing the India Meteorological Department (IMD)’s best-track data, reanalysis datasets, and composite analysis, we find that ENSO and IOD phases affect TC activity differently across seasons. The pre-monsoon season shows a limited association between TC activity and both ENSO and IOD, with minimal variation in frequency, intensity, and energy metrics. However, during the post-monsoon season, El Niño enhances TC intensity, resulting in a higher frequency of intense storms, leading to increased accumulated cyclone energy (ACE) and power dissipation index (PDI) in a statistically significant way. In contrast, La Niña favors the development of weaker TC systems and an increased frequency of depressions. While negative IOD (nIOD) phases tend to suppress TC formation, positive IOD (pIOD) phases are associated with increased TC activity, characterized by longer durations and higher ACE and PDI (statistically significant). Genesis sites shift with ENSO: El Niño favors genesis in the eastern Arabian Sea, causing westward or northeastward tracks, while La Niña shifts genesis toward the central-western basin, promoting northwestward movement. Composite analysis indicates that higher sea surface temperatures (SSTs), reduced vertical wind shear (VWS), increased mid-tropospheric humidity, and lower sea level pressure (SLP) during El Niño and pIOD phases create favorable conditions for TC intensification. In contrast, La Niña and nIOD phases are marked by drier mid-level atmospheres and less favorable SST patterns. The Indo-Pacific Warm Pool (IPWP), particularly its westernmost edge in the southeastern Arabian Sea, provides a favorable thermodynamic environment for genesis and exhibits a moderate positive correlation with TC activity. Nevertheless, its influence on interannual variability over the basin is less significant than that of dominant large-scale climate patterns like ENSO and IOD. These findings highlight the critical role of SST-related teleconnections (ENSO, IOD, and IPWP) in regulating Arabian Sea TC activity, offering valuable insights for seasonal forecasting and risk mitigation in vulnerable areas. Full article

Background and Objectives: Relapsed or refractory germ cell tumors are commonly treated with HDCT/ASCT, but robust predictors of hematopoietic recovery are limited. Quantitative CT-based metrics of body composition are readily available, but their prognostic value for post-transplant engraftment remains uncertain. We investigated whether muscle and fat indices derived from routine CT scans are associated with the pace of hematologic recovery after HDCT/ASCT. Materials and Methods: This retrospective study analyzed a single-center cohort (n = 43) with relapsed/refractory GCT undergoing HDCT/ASCT. CT within 6 months pre-HDCT/ASCT was analyzed at L3 to derive the Skeletal muscle index, Psoas muscle index, Subcutaneous fat area, Visceral fat area, Total fat area, Visceral-to-subcutaneous fat area ratio. Primary endpoint: The engraftment time post-ASCT. Spearman’s ρ was used for univariable associations; multivariable linear regressions were adjusted for age, Hb, weight, and BSA to evaluate the independent effects. The significance was set at p < 0.05. Results: The median hematologic engraftment duration was 12.0 days, and the engraftment duration was positively correlated with age and negatively with hemoglobin. According to the multivariable analysis, older age and lower hemoglobin independently predicted longer engraftment; body weight and BSA were not significant. Among the morphometrics, only the VFA/SFA ratio was associated with delayed engraftment. The SMI, PMI, and TFA were not significant. As expected, after HDCT, grade 4 neutropenia and thrombocytopenia occurred in all patients. Conclusions: In relapsed/refractory GCT treated with HDCT/ASCT, older age and lower post-transplant hemoglobin independently predicted a prolonged engraftment. Beyond traditional muscle/fat areas, a higher VFA/SFA ratio—reflecting visceral adiposity—is also associated with delayed recovery, suggesting that fat distribution may influence hematopoietic regeneration. These variables may support pre-transplant risk stratification and individualized supportive care. Full article

Background. Sex-based disparities in chronic obstructive pulmonary disease (COPD) diagnosis remain underexplored, particularly in primary care settings. This study assessed sex differences in clinical burden, diagnostic delay, and missed diagnostic opportunities using conventional and composite metrics. Methods. A cross-sectional analysis was conducted in 166 newly diagnosed COPD patients (76 women, 90 men) from Spanish primary care. Clinical severity, healthcare use, and diagnostic timing were compared using Mann–Whitney and chi-squared tests. Composite indices included the Symptom Intensity Score, Diagnostic Inertia Indices, DOSE Index, and Diagnosis Complexity Score. Multivariable regressions evaluated independent associations. Results. At diagnosis, women showed a greater clinical and functional burden (FEV₁ % predicted: 50.4% vs. 61.4%, p < 0.001; symptom intensity z-score: 0.13 vs. −0.67, p < 0.001), higher diagnostic complexity (Diagnosis Complexity Score: 403.5 vs. 272.0, p < 0.001), and longer diagnostic delay (median: 133.0 vs. 66.5 days, p < 0.001). Stratified and composite analyses confirmed consistent sex-based asymmetries. In adjusted models, being female independently predicted a longer diagnostic delay (β = 0.888, p = 0.005), but was not significantly associated with the burden of missed diagnostic opportunities (MDOs) (β = 0.112, p = 0.395). Conclusions. Women with newly diagnosed COPD experience greater symptom burden and longer diagnostic delays. Composite metrics may improve the identification of diagnostic disparities in routine clinical settings. Full article

Landscape patterns serve as important drivers of macroinvertebrate biodiversity. However, the mechanisms through which landscape dynamics influence biodiversity across different elevation gradients in undammed rivers remain poorly understood. Here, this study investigated macroinvertebrate communities in the Chishui River, which represents the only undammed tributary maintaining a natural flow regime in the upper Yangtze River. We documented 97 macroinvertebrate taxa (3 phyla, 16 orders, and 57 families) with a mean density of 314.93 ind./m². NMDS and PERMANOVA analyses revealed significant spatial heterogeneity in macroinvertebrate community composition, but no overall seasonal variation. However, functional diversity indices (e.g., FRic) exhibited seasonal fluctuations across the river system. Furthermore, we assessed nine landscape metrics to capture heterogeneity, complexity, and fragmentation effects. Random forest modeling with nine predictors revealed that landscape heterogeneity primarily drove functional diversity in the upstream areas, whereas landscape fragmentation was the dominant factor in the downstream areas. Functional diversity, which reflects trait-based ecological roles, provides more direct insights into ecosystem processes than taxonomic diversity alone. Notably, the taxonomic diversity indices (Margalef richness, Shannon–Wiener diversity, Simpson diversity, and Pielou evenness index) showed no significant correlations with landscape metrics. These findings highlight the critical role of functional diversity in evaluating landscape-mediated ecological effects. For effective conservation, management strategies should prioritize reducing anthropogenic disturbances in downstream areas while preserving natural landscape heterogeneity. Full article