Search Results (6)

In the context of the “Dual Carbon” goals, achieving synergistic development between digitalization and green transformation in the coal power industry is essential for ensuring a just and sustainable energy transition. The core scientific problem addressed is the lack of a robust quantitative tool to evaluate the comprehensive performance of diverse transition scenarios in a complex environment characterized by multi-objective trade-offs and high uncertainty. This study establishes a sustainability-oriented four-dimensional performance evaluation system encompassing 22 indicators, covering Synergistic Economic Performance, Green-Digital Strategy, Synergistic Governance, and Technology Performance. Based on this framework, a Fuzzy DEMATEL–MultiMOORA–Borda integrated decision model is proposed to evaluate seven transition scenarios. The computational framework utilizes the Interval Type-2 Fuzzy DEMATEL (IT2FS-DEMATEL) method for robust causal analysis and weight determination, addressing the inherent subjectivity and vagueness in expert judgments. The model integrates MultiMOORA with Borda Count aggregation for enhanced ranking stability. All model calculations were implemented using Matlab R2022a. Results reveal that Carbon Price and Digital Hedging Capability (C13) and Digital-Driven Operational Efficiency (C43) are the primary drivers of synergistic performance. Among the scenarios, P3 (Digital Twin Empowerment and New Energy Co-integration) achieves the best overall performance (score: 0.5641), representing the most viable pathway for balancing industrial efficiency and environmental stewardship. Robustness tests demonstrate that the proposed model significantly outperforms conventional approaches such as Fuzzy AHP (Analytic Hierarchy Process) and TOPSIS under weight perturbations. Sensitivity analysis further identifies Financial Return (C44) and Green Transformation Marginal Economy (C11) as critical factors for long-term policy effectiveness. This study provides a data-driven framework and a robust decision-support tool for advancing the coal power industry’s low-carbon, intelligent, and resilient transition in alignment with global sustainability targets. Full article

School connectedness, belonging, and engagement are linked to improved academic, social, and emotional outcomes, yet no prior systematic review or meta-analysis has synthesised interventions targeting these constructs in secondary schools. This review evaluated randomised controlled trials identified through systematic searches of CINAHL, Medline, ERIC, and PsycINFO (last searched: June 2024). Studies included school-based interventions measuring connectedness, belonging, or engagement with validated tools. Methodological quality was assessed via the Cochrane Risk of Bias Tool, and effectiveness was analysed using meta-analysis (Hedges’ g). Sixteen trials (N = 35,451) met the inclusion criteria, with eleven providing sufficient data for meta-analysis. Overall, interventions significantly improved connectedness, belonging, and engagement (Hedges’ g = 1.056, within-group; 0.642, between-group). Multi-tier programs yielded the largest effects (0.781), with ecological (0.613) and environmental (0.636) approaches; behavioural and intrapersonal strategies were non-significant, possibly due to the small sample sizes. Interventions frequently overlapped in content but differed in theoretical frameworks. Future research should develop more distinctive, multi-tiered interventions and use consistent, theoretically robust measures. The findings underscore the potential of targeting environmental factors and interpersonal techniques to foster connectedness, belonging, and engagement in secondary schools. These results highlight the importance of clarifying the conceptual frameworks and measurement tools to strengthen future interventions’ design and interpretation. Full article

We present a semi-static replication algorithm for Bermudan swaptions under an affine, multi-factor term structure model. In contrast to dynamic replication, which needs to be continuously updated as the market moves, a semi-static replication needs to be rebalanced on just a finite number of instances. We show that the exotic derivative can be decomposed into a portfolio of vanilla discount bond options, which mirrors its value as the market moves and can be priced in closed form. This paves the way toward the efficient numerical simulation of xVA, market, and credit risk metrics for which forward valuation is the key ingredient. The static portfolio composition is obtained by regressing the target option’s value using an interpretable, artificial neural network. Leveraging the universal approximation power of neural networks, we prove that the replication error can be arbitrarily small for a sufficiently large portfolio. A direct, a lower bound, and an upper bound estimator for the Bermudan swaption price are inferred from the replication algorithm. Additionally, closed-form error margins to the price statistics are determined. We practically study the accuracy and convergence of the method through several numerical experiments. The results indicate that the semi-static replication approaches the LSM benchmark with basis point accuracy and provides tight, efficient error bounds. For in-model simulations, the semi-static replication outperforms a traditional dynamic hedge. Full article

In order to improve the utilization rate of water resources in the flood season of the reservoir effectively and promote wind power consumption, this paper proposes an optimization model for the combined dispatching of wind power and hydropower based on the hedging theory. First, the conflicting relationship between the water storage benefits of hydropower stations, flood control risks, and the joint output of hydropower and wind power in joint dispatching is studied. The introduction of hedging theory divides the combined dispatching of wind power and hydropower into a two-stage dispatching problem including the decision-making stage and the remaining stage; Second, considering the uncertainty of water forecasting and wind power forecasting, a multi-objective optimal dispatching model of hydropower and wind power based on hedging theory is constructed. This model aims to minimize flood control risks, maximize water storage benefits, and minimize wind power and hydropower combined power output volatility. Finally, the non-dominated sorting genetic algorithm (NSGA2) is used to solve the specific examples. The results show that the model built in the article controls the flood control risk at each time period not to be higher than 1.63 × 10⁻³ (the flood control standard corresponding to the flood control risk in 50 years is 0.006). Additionally, the water level of the reservoir increased from the flood limit water level (583.00 m) to 583.70 m. It greatly increases the water storage capacity and effectively improves the utilization rate of water resources. At the same time, the optimized scheduling scheme reduced the peak-valley difference of joint output from 125.00 MW to 35.66 MW, and the peak-valley difference was greatly reduced. It effectively improves the volatility of wind power. The validity of the model is verified, and the obtained scheme can provide decision-making for the joint dispatch scheme of hydropower and wind power. Full article

Pace bowlers must often perform extended bowling spells with maximal ball release speed (BRS) while targeting different delivery lengths when playing a multi-day match. This study investigated the effect of an eight over spell upon pace bowling biomechanics and performance at different delivery lengths. Nine male bowlers (age = 18.8 ± 1.7 years) completed an eight over spell, while targeting different lengths (short: 7–10 m, good: 4–7 m, full: 0–4 m from the batter’s stumps, respectively) in a randomized order. Trunk, knee and shoulder kinematics and ground reaction forces at front foot contact (FFC), as well as run-up velocity and BRS were measured. Paired sample t-tests (p ≤ 0.01), Hedges’ g effect sizes, and statistical parametrical mapping were used to assess differences between mean variables from the first and last three overs. No significant differences (p = 0.05–0.98) were found in any discrete or continuous variables, with the magnitude of difference being trivial-to-medium (g = 0.00–0.73) across all variables. Results suggest pace bowlers sustain BRS through a single eight over spell while tolerating the repeatedly high whole-body biomechanical loads as suggested by maintaining the kinematics or technique at the assessed joints during FFC. Practically, the findings are advantageous for bowling performance and support current bowling load monitoring practices. Full article

The purpose of this study was to examine potential moderators of school-based physical activity interventions on cariorespiratory endurance in primary school-aged children using meta-regression. An Internet search with several databases was employed, extracting school-based pediatric physical activity intervention studies published within the past 30 years. Studies were included if there was a control or comparison group, if the study sample included primary school-aged children, if the targeted outcome of cardiorespiratory endurance was objectively assessed, if the intervention was at least partially school-based, and if the effect estimate’s variability was reported. An inverse-variance random effects meta-regression was employed using the primary predictors of component number (single component or multi-component) and intervention length using 20 extracted studies with 23 total effects. The overall pooled effect on cardiorespiratory endurance was statistically significant (Hedges’ g = 0.30, 95% C.I.: 0.19–0.40; p < 0.001). Using random effects meta-regression, neither component number (b = −0.09, 95% C.I.: −0.40–0.23; p = 0.560) or intervention length (b = 0.001, 95% C.I.: −0.002–0.004; p = 0.427) yielded a significant modifying effect on cardiorespiratory endurance. School-based physical activity interventions have a significant pooled effect on cardiorespiratory endurance in primary school-aged children. Component number and intervention length does not modify this effect, suggesting other sources for between-study heterogeneity. Full article