Search Results (9,151)

The rapid expansion of information and communication technology (ICT) alongside sustained economic growth poses a critical policy challenge for hydrocarbon-based economies seeking to reconcile digital development with environmental sustainability. This study examines both the short- and long-term relationships between per capita CO₂ emissions, GDP per capita, and the adoption of ICT in Saudi Arabia, using annual time-series data for 1995–2024. Methodologically, we employ the ARDL bounds test, an error correction model (ECM), and Granger causality analysis to test the EKC hypothesis. Additionally, we use the Zivot–Andrews test to detect structural breaks, accounting for these through dummy variables. Long-run cointegration among the three variables is validated by the bounds test results. GDP is the dominant long-run driver of internet-based ICT adoption, while CO₂ emissions and GDP are strongly cointegrated through the 2010 structural break and the EKC mechanism. No direct causal link is found between ICT and CO₂ emissions in either direction. The long-run validity of the EKC hypothesis is confirmed, with an estimated income turning point of approximately USD 26,021 per capita, a level reached during the latter part of the sample period. These findings suggest that Saudi Arabia’s internet adoption has yet to generate an independent decarbonization dividend, underscoring the need for policies that couple ICT investment with clean energy deployment under Vision 2030. Full article

The objective of this study was to predict seed and oil yields in safflower (Carthamus tinctorius L.) using UAV-based multispectral imagery and machine learning algorithms. The study was conducted during the 2024 growing season under varying irrigation levels, fertilization practices, and applications of plant growth-promoting rhizobacteria. The experiment included four irrigation levels, fertilized and unfertilized conditions, and bacterial treatments consisting of Bacillus pumilus, Bacillus albus, their mixture, and a non-bacterial control. Sixty-two vegetation indices were calculated from multispectral images acquired during the harvest maturity period and used to predict seed and oil yields. To identify the most informative features, Mutual Information, Recursive Feature Elimination, and LASSO feature selection methods were applied; subsequently, Linear Regression, Decision Tree, Random Forest, Support Vector Regression, K-Nearest Neighbors, and XGBoost regression algorithms were compared. The results showed that Linear Regression combined with Mutual Information-based feature selection was the most successful approach for predicting both seed and oil yields. According to the 5-fold cross-validation results, average values of $R=0.8600$, $MAE=0.2870$, and $RMSE=0.3765$ were obtained for seed yield prediction, while average values of $R=0.8710$, $MAE=0.0876$, and $RMSE=0.1101$ were obtained for oil yield prediction. Full article

Tomato leaf mold, caused by Passalora fulva, is one of the most destructive fungal diseases affecting greenhouse tomato production and can cause substantial yield losses under conditions of high relative humidity and moderate temperatures that favor pathogen infection and disease development. This study evaluated the in vitro antifungal activity of a commercial fungicide formulation, Priori Top^® (azoxystrobin + difenoconazole), and three essential oils derived from Eucalyptus globulus, Artemisia herba-alba, and Mentha pulegium against two monoconidial isolates of P. fulva. Unlike previous studies, which have mainly focused on mycelial growth, the present work simultaneously evaluated the effects of the tested products on mycelial growth, sporulation, and conidial germination, providing a comprehensive assessment of antifungal efficacy across three key developmental stages of the pathogen. Antifungal activity was quantified by estimating IC₅₀ and IC₉₀ values using Probit regression analysis. The azoxystrobin–difenoconazole formulation consistently exhibited the highest antifungal activity across all evaluated parameters and showed the lowest estimated IC₅₀ and IC₉₀ values for both fungal isolates. Among the tested essential oils, Artemisia herba-alba exhibited the greatest antifungal activity, reducing mycelial growth by 83% and 78% at 500 ppm for isolates 1 and 2, respectively, and consistently outperforming Mentha pulegium and Eucalyptus globulus. Differences in sensitivity were observed between the two fungal isolates, indicating intraspecific variability in their response to the tested treatments. These findings demonstrate the strong antifungal efficacy of the azoxystrobin–difenoconazole formulation against P. fulva and identify A. herba-alba essential oil as the most promising botanical treatment for integrated management of tomato leaf mold. Further greenhouse and field studies are required to validate these findings, optimize formulation strategies, and evaluate the practical application of A. herba-alba essential oil under commercial production conditions. Full article

Understanding the pricing of climate risks in bond markets is relevant to financial stability. The real estate sector, characterized by geographically fixed and long-duration assets, exhibits high exposure to environmental shocks; yet, empirical matching between specific climate channels and real estate bond pricing remains sparse. This analysis examines the impact of climate risks on corporate bond credit spreads within the real estate sector by constructing three thematic indicators: transition risk (CTRI), chronic physical risk (ChroCPRI), and acute physical risk (AcuCPRI). Initial feature selection via machine learning suggests all three risk categories as predictive covariates for bond pricing. Subsequent regression estimations indicate that climate transition risk and acute physical risk expand credit spreads, whereas chronic physical risk compresses them—with these statistical patterns being more pronounced among state-owned enterprises (SOEs). Mechanism analyses yield threefold insights: first, transition risk elevates spreads by tightening financing constraints and restricting corporate asset growth, a channel concentrated in short-term tranches and low-liquidity firms; second, the counterintuitive spread-compressing effect of chronic risk is localized among firms with lower credit ratings and lower profitability, consistent with institutional climate support frameworks and strategic green adaptations; third, acute physical risk widens spreads by compressing operational cash flows and exacerbating financing friction, particularly for smaller enterprises. These channels align with the structural attributes of SOEs, which are characterized by larger asset scales, superior capital liquidity, and a higher propensity to secure state guarantees. Full article

Salinity poses a major threat to sustainable agriculture and coastal ecosystems, resulting in a substantial loss of plant productivity and biodiversity. Although some coastal grass species exhibit natural adaptation to saline conditions, the physiological mechanisms underlying salt tolerance remain incompletely understood, particularly regarding the contribution of plant-associated microorganisms. In a previous study, a commercial cultivar of red fescue (Festuca rubra ssp. rubra cv. Rafael) was shown to be salt sensitive when grown hydroponically, whereas wild populations of F. rubra commonly occur in coastal salt marshes (possibly ssp. litoralis). We hypothesized that this difference in salt tolerance is partly associated with beneficial fungal plant interactions. To test this hypothesis, we investigated whether inoculation with a fungal isolate designated Fusarium sp. 1 and isolated from F. rubra growing on a salt marsh along the Dutch Wadden Sea coast could improve the salinity tolerance of the commercial cultivar. The results showed that inoculation with Fusarium sp. 1 alleviated the salt-induced growth inhibition. At 100 mM NaCl, shoot and root biomass were partially restored relative to non-inoculated controls, accompanied by a significant increase in the shoot-to-root ratio. To investigate the physiological basis of this response, we applied the Microelectrode Ion Flux Estimation (MIFE) technique to quantify Na⁺ -induced K⁺ efflux in roots. Inoculated plants exhibited improved K⁺ homeostasis, characterized by a reduced instantaneous Na⁺-induced K⁺ efflux and a faster recovery of root fluxes. Moreover, inoculated plants grown at 50 and 100 mM NaCl displayed 333% and 397% greater net K⁺ influx, respectively, compared with non-inoculated controls. Our results indicated that inoculation with Fusarium sp. 1 improves the salinity tolerance of F. rubra, likely through enhanced root K⁺ retention. These findings suggest that commercial F. rubra cultivars remain responsive to beneficial microbial associations and highlight the potential of exploring plant–microbe interactions from naturally salt-adapted environments to improve salinity resilience in grasses and potentially other crops. Full article

This study investigates the relationship between economic growth, trade openness, energy intensity, and carbon dioxide (CO₂) emissions in South Africa within the Environmental Kuznets Curve (EKC) framework over the period 1970–2022. Using quarterly time series data and the Autoregressive Distributed Lag (ARDL) modelling approach, the study examines both the short-term and long-term dynamics between economic activity and environmental degradation. Descriptive statistics, correlation analysis, unit root tests, ARDL bounds testing, error-correction modelling, Granger causality analysis, and diagnostic tests were employed to ensure robust empirical results. The Augmented Dickey–Fuller (ADF) and Phillips–Perron (PP) tests indicate that all variables are integrated of order one, I(1), thereby satisfying the conditions for ARDL estimation. The ARDL bounds test confirms the existence of a long-term cointegrating relationship among carbon emissions, economic growth, trade openness, and energy intensity. The long-term results reveal a statistically significant negative coefficient for economic growth and a positive coefficient for the squared income term, indicating a U-shaped relationship between income and carbon emissions. Consequently, the conventional Environmental Kuznets Curve hypothesis is not supported for South Africa. The findings suggest that economic growth initially reduces environmental degradation; however, beyond a certain income threshold, further economic expansion increases carbon emissions. Trade openness and energy intensity exert positive and statistically significant effects on carbon emissions in the long run, implying that increased integration into global markets and continued dependence on energy-intensive production contribute to environmental degradation. The Error-Correction Model (ECM) reveals a negative and highly significant adjustment coefficient (−0.928), indicating that approximately 92.8% of short-term disequilibrium is corrected within one period. Granger causality results further show a unidirectional causal relationship running from trade openness to carbon emissions, while no significant causal relationship is found between economic growth and carbon emissions. The study concludes that economic growth alone is insufficient to achieve environmental sustainability in South Africa. Policy efforts should therefore focus on promoting renewable energy adoption, improving energy efficiency, strengthening environmental regulations, encouraging cleaner production technologies, and integrating environmental considerations into trade and industrial policies. These measures are essential for achieving sustainable economic development while meeting national climate-change-mitigation objectives. Full article

Consumption is a basic driver of economic growth and a key part of the new development paradigm centered on the dual circulation of domestic and international markets. Treating the establishment of National E-Commerce Demonstration Cities as a quasi-natural experiment, this paper employs a multi-period difference-in-differences (DID) model and draws on panel data from Chinese prefecture-level cities spanning 2009 to 2023 to estimate the impact of the demonstration city policy on residents’ consumption levels and its transmission mechanisms. The findings are as follows: First, the National E-Commerce Demonstration City Policy significantly promotes residents’ consumption. Compared with the control group, consumption levels in demonstration cities increased by approximately 6.6%, and this result is robust to various specification checks. Second, mechanism analysis shows that the policy boosts consumption through three channels: stimulating urban entrepreneurship, upgrading smart logistics, and improving digital infrastructure. These channels together help build a more efficient consumption system. Third, heterogeneity analysis indicates that the policy effect is stronger in large cities, central and western regions, non-old industrial base cities, and cities with higher urbanization rates. These findings provide theoretical insights and practical implications for refining the e-commerce demonstration policy, tailoring it to local conditions, and unlocking consumption potential. Full article

Background/Objectives: Resting energy expenditure (REE) rises during critical illness, but its determinants and prognostic relevance remain incompletely characterized. Identifying a circulating signal that tracks REE could provide a bedside surrogate for metabolic demand where indirect calorimetry is unavailable. This prospective pilot study described longitudinal trajectories of indirect calorimetry-measured REE, Sequential Organ Failure Assessment (SOFA) score, serum cortisol and insulin-like growth factor-1 (IGF-1) over two weeks in the intensive care unit (ICU), examined whether the REE trajectory was attenuated by adjustment for these variables, and generated preliminary effect-size and variance estimates for mortality. Methods: This single-center pilot study enrolled 39 critically ill adults at Evangelismos General Hospital (Athens, Greece); sample size was pragmatic, not based on an a priori power calculation. REE (Q-NRG metabolic monitor), cortisol and IGF-1 were measured at admission and days 5–7, 10–11 and 13–14, alongside SOFA. Trajectories were modeled with linear mixed-effects models using all available repeated measures. Confounding was assessed by adding SOFA, cortisol and IGF-1 as covariates and evaluating attenuation of the time effect; no formal mediation analysis was performed. Causes of missing data were quantified and a completers-only sensitivity analysis was undertaken. Mortality was analyzed by Cox regression with ICU length of stay as the time variable. Estimation was emphasized throughout; point estimates and 95% confidence intervals (CIs) are reported in preference to significance testing. Results: Mean age was 54.6 ± 18.1 years; 69.2% were male; median admission SOFA was 6 (IQR 3–9). ICU and 28-day mortality were 20.5% (8/39) and 10.3% (4/39). REE/kg rose from 25.3 ± 3.7 to a peak of 27.2 ± 4.2 kcal/kg/day by days 10–11 (likelihood-ratio χ² = 17.2, p = 0.0006). Attrition was driven predominantly by discharge alive (18 of 23 patients missing at days 13–14) rather than death (n = 2), and the trajectory was preserved in a completers-only sensitivity analysis (χ² = 9.13, p = 0.028). Cortisol declined (21.1 to 13.4 μg/dL) and IGF-1 rose (80.0 to 105.4 ng/mL); SOFA was essentially unchanged. REE did not correlate with SOFA, cortisol or IGF-1 at any time-point, and the time effect was not attenuated by adjustment for them. Admission REE was not associated with ICU mortality (HR 1.00, 95% CI 1.00–1.00). Higher admission REE was associated with a longer ICU stay, and this persisted after adjustment for body mass index (p = 0.026) and fat-free mass (p = 0.001). Age (HR 1.04, 95% CI 1.00–1.09) and admission SOFA (HR 1.18, 95% CI 0.98–1.44) were the covariates most associated with ICU mortality. Conclusions: REE rose progressively over the first 10–11 days of critical illness. Its trajectory was not attenuated by adjustment for SOFA, cortisol or IGF-1, which is compatible with—but does not establish—independence from the adrenal and somatotropic markers measured here. Neither REE nor these hormones were associated with mortality; age and disease severity remained the dominant prognostic factors, supporting a larger confirmatory study. Full article

This paper develops a parameterized generalized transform framework for nonlinear differential models. The method combines a generalized Laplace-type transform, Adomian decomposition, Chebyshev–Padé rational reconstruction, and a $\mu$-scaled generalized transform to construct admissible semi-analytical approximations. The framework treats the transform geometry as part of the approximation process, allowing the transformed domain to be adjusted while preserving an explicit analytical structure. The theoretical analysis establishes admissibility conditions, existence of admissible minimizers, characterization of the admissible region for the parametric kernel, interior optimality conditions, inverse and residue inversion formulas, and fixed-point consistency with a first-order truncation estimate. The method is illustrated on a logistic–Allee tumor-growth model using experimental data. The resulting compact representations remain real-valued and admissible on the full data interval and produce errors comparable to standard numerical reference solutions. Full article

Background/Objective: Most weight estimation formulae developed for children from skeletal measurements are based on 20 individuals from the Denver Growth Study. This limitation is mainly due to the availability of data. The formulae produced using these data are limited to a small range of variation in weight, which may result in reduced applicability. This study develops new weight estimation formulae relying on a larger and more diverse sample of deceased children (n = 77) of known age and weight from the New Mexico Decedent Image Database. Methods: A classical calibration regression approach was used to generate weight estimation equations from virtual metaphyseal breadths, epiphyseal breadths, and torsional rigidity (J) of the femur and tibia. Equations were developed separately for the two sexes, two BMI categories, and three age categories. Results: Midshaft femoral J values (45.5% of the total diaphyseal length) and proximal tibial J values (75% of the total diaphyseal length) correlate most highly with body weight and when used to develop weight estimation formulae produce the least amount of error. In general, the breadth measures were less correlated and had larger error than the J values, though the distal femoral metaphyseal breadth produced the highest coefficients of determination and lowest error of the breadth formulae. Conclusions: While these formulae are based on a sample of modern children, the variation that they encompass and the different equations provided allow users to apply them in a variety of circumstances. However, weight estimation may have limited value due to large prediction errors. Full article

Most studies involving genomic data in animal breeding use only the effects of autosomal chromosome markers, excluding the sex chromosomes. However, the X chromosome is the second-largest chromosome in the bovine genome, and several economically important traits are sexually dimorphic, such as those related to growth. Therefore, the objective of this study was to evaluate whether there are predictive advantages for genetic parameters when including genomic markers from the X chromosome for yearling weight (YW) and postweaning gain (PWG) in Nellore cattle. Genetic parameter estimates were obtained under three scenarios: (1) only pedigree and phenotypic information; (2) pedigree, phenotypes, and autosomal chromosome markers; and (3) pedigree, phenotypes, autosomal chromosome markers, and X chromosome markers. Analyses were carried out using Bayesian inference with BLUPF90 family software version 2025. The heritability estimates obtained and their respective standard errors were 0.41 ± 0.004 for YW and 0.21 ± 0.004 for PWG. No differences were observed among the three scenarios tested for either trait. Therefore, the inclusion of the X chromosome did not influence the estimates of genetic parameters for these growth traits in Nellore cattle. Nevertheless, further molecular and genomic studies on the bovine X chromosome are still needed to explain the genetic effects and biological functions associated with this chromosome and with different traits of economic interest, as well as to justify whether to include the X chromosome in genomic prediction analyses. Full article

Specialized firms face a strategic tension between extending established capabilities into new applications and preserving the coherence that underpins their competitive advantage. Integrating dynamic capability theory with research on managerial time orientation, this study examines whether disclosed action-based managerial long-term orientation is associated with subsequent product-application extension and whether such extension remains related to the firm’s existing capability base. The analysis uses an unbalanced retrospective cohort of 1272 firm-year observations from 325 listed Chinese firms that subsequently attained specialized, refined, distinctive, and innovative (SRDI) Little Giant status in the first three national batches. A change from the 10th to the 90th percentile of the raw long-term-orientation score (2 to 3) is associated with a 0.050 increase in the extension score (95% confidence interval: 0.021–0.080), equivalent to 1.25% of the full coding range and 10.9% of the outcome standard deviation. Firm fixed-effects and Mundlak estimates locate this modest association primarily in persistent differences across firms. A direct coefficient comparison favors related product-application extension, although the rarity of unrelated-expansion events limits the precision of this contrast. Digital-depth interactions vary across specifications, and extension is not significantly associated with sales growth or return on assets over the available horizons. These findings refine dynamic-capability theory by locating capability redeployment within persistent firm-level configurations and extend research on strategic time orientation by linking managerial horizons to the direction of product-application extension. Full article

Tourism development in coastal Mediterranean regions has posed a significant pressure on water local resources, particularly the extensive use of water-intensive recreational infrastructures. This study investigates the spatial distribution and water consumption of public and private swimming pools in the Kassandra peninsula, Halkidiki, Greece. Using Geographic Information Systems (GIS) and high-resolution satellite imagery from 2016 and 2024, the research quantified changes in pool density and estimated associated water losses from evaporation and filter backwashing. Our findings reveal a significant increase in swimming pools and related water demand, intensifying water scarcity during the tourist season. Growth was particularly strong among small private and tourism-related pools, which increased by 192.4% overall and by more than 400% in some districts. This trend reflects a shift from mass hotel-based tourism toward decentralized and flexible tourism models. Furthermore, cartographic outputs and thematic mapping highlight spatial concentrations of water consumption near environmentally sensitive coastal zones. The applied geospatial approach identifies interactions between tourism infrastructure and vulnerable ecosystems, offering an integrated geographic perspective on environmental pressures in coastal areas. Our results emphasize the urgent need for sustainable water management policies, including water reuse practices and strategies to improve the resilience of tourism-dependent regions under climate stress. Full article

The study evaluated the effect of an Ascophyllum nodosum-based biofertilizer applied under three treatments: foliar (FA, 0.5 g/L every 15 days), root (RA, 0.5 g/L every 30 days), and combined (F&RA, 0.5 g/L, Foliar every 15 days and Root every 30 days) compared to a control (C) in aeroponic cultivation of Phaseolus vulgaris L. var. Opus. Environmental conditions were continuously monitored using an IoE-based system, ensuring consistent microclimatic characterization throughout the experimental period. A non-parametric statistical approach was applied due to non-normal data distribution. Most growth and yield variables did not show statistically significant differences; however, significant treatment effects were observed for leaf temperature, root temperature, calcium, iron, and manganese. Significant differences among treatments (α = 0.05) were identified using Kruskal–Wallis test for calcium (p = 0.0002), iron (p = 0.0067), and manganese (p = 0.0439), while other micronutrients showed no statistical differences. Descriptive statistics indicated moderate shifts in central tendency, particularly for calcium and iron, with higher values observed in the combined treatment (F&RA). Effect size analysis using Cliff’s delta (δ) revealed moderate to large differences for calcium, iron, and manganese, although these estimates were interpreted cautiously given the unequal replication among treatments. Spearman correlation analysis showed moderate to strong associations, although none were statistically significant (p > 0.05). Overall, results indicate limited effects of the biofertilizer on growth and yield variables but treatment-associated changes in selected nutritional components, suggesting element-dependent responses to biofertilizer application. Full article

Background/Objectives: Korea has undergone rapid epidemiological transitions in cancer incidence over the past two decades. Using a 25-year nationwide dataset (1999–2023), we characterize long-term trends for 61 cancer types, examine inter-cancer correlations, and forecast incidence to 2028. Methods: Annual incidence counts, crude rates, and age-standardized incidence rates (ASIRs) stratified by sex were obtained from the Korea Central Cancer Registry (KCCR) via the Korean Statistical Information Service (KOSIS). Annual percent change (APC) was estimated using log-linear regression. Pearson correlation coefficients were computed among cancer-specific ASIRs, with false-discovery-rate (FDR) correction for multiple comparisons. Multiple and hierarchical regression evaluated the statistical association of individual cancer types with the overall cancer rate, and variance inflation factors (VIFs) were used to quantify multicollinearity. Time series forecasting used damped Holt–Winters exponential smoothing; forecast accuracy was assessed with rolling-origin cross-validation (RMSE, MAE, MAPE) and benchmarked against ARIMA. A sensitivity analysis excluding the pandemic years (2020–2021) tested the robustness of trend estimates. Five-year prevalence data (2007–2023) were analyzed from the KCCR prevalence module. Results: Total cancer incidence increased from 101,854 in 1999 to 288,613 in 2023, a 183% increase. The overall ASIR rose from 402.7 to 522.9 per 100,000 (2020 standard population). The three fastest-growing cancers were thyroid (APC +7.56%, p < 0.001), prostate (+6.98%, p < 0.001), and breast (+5.03%, p < 0.001). Stomach (APC −2.20%) and liver (−2.90%) cancers showed significant declines. Hierarchical regression showed that adding thyroid, breast, and prostate to lung and stomach increased explained variance from R² = 0.449 to 0.997; however, high VIF values (up to ~263) indicate substantial multicollinearity and compositional dependence, so these coefficients should not be read as independent causal contributions. Holt–Winters and ARIMA produced comparable accuracy (mean MAPE 4.6% vs. 4.7%). The five-year cancer prevalence pool reached 1,035,107 in 2023. Forecasting projects a total incidence of approximately 319,000 by 2028. Conclusions: Korean cancer epidemiology is undergoing a transition from infection-related cancers toward hormone-sensitive and screening-detectable malignancies. These findings support strategic resource allocation for high-growth cancers while maintaining vigilance over rising pancreatic and other emerging cancers. Full article