Search Results (2,295)

This paper shifts the research perspective from “Buddhist monasteries” to “monastic Buddhism,” using Nālandā Mahāvihāra as a micro-level case to illuminate the broader support mechanism of Indian Buddhist monasteries, with particular focus on the concept of “non-exhaustible endowment”. Drawing on epigraphic evidence, Vinaya texts, and Chinese pilgrims’ records, it finds that major donors supported monasteries through religious rituals, land grants, and cash investments, primarily in the form of landed property and gold and silver currency, which were designated as non-exhaustible endowments. Monasteries then engaged in agriculture, handicrafts, building industry, commerce, and lending, transforming static assets into a non-exhaustible cycle of capital that benefited both monastics and laity. Systems such as Yizhi (robe funds) and Gongfu zhi Zhuang (robe-providing estates) reveal mature financial services that not only liberated monks from economic constraints but also stimulated the cotton textile trade between India and China. The wealth possessed by monasteries was not static but perpetually engaged in a dynamic cycle of capital. Major Buddhist monasteries thus emerged as regional economic engines, which became the core value for continuous royal patronage, as well as the key incentive for their violent destruction by Turkic Muslims. However, the transformation of the religious landscape and economic network in late medieval Bihār was not a simplistic process. Faced with a changing political and religious environment over time, Sufi saints, Jain followers, Shaiva ascetics and other religious communities, each grounded in their own faiths, landholdings, commercial networks and educational systems, gradually displaced, restructured and undermined the Buddhist monastery-centered endowment mechanism, causing Buddhism to progressively lose its regional dominance as an institutionalized religion. Full article

This article analyses trading-performance patterns in a stock market simulation conducted with 134 second-year students at the University of Mons (Belgium) on 11 December 2025. Participants had a virtual capital of 100,000 euros and were free to trade CAC 40 securities without any restrictions on the number or volume of transactions. An academic incentive scheme, combining a participation bonus and bonuses for the three best portfolios, created a tournament-style environment with continuous ranking feedback. This feature is considered as part of the experimental context rather than as a separately identified causal mechanism. We estimate a quadratic model linking performance to activity, measured by the number of mean-centered transactions to reduce the collinearity between the first-degree term and its square, and control exposure via the average percentage of cash in the portfolio, portfolio variability (measured as the standard deviation of portfolio value) and the average trade size. Breusch–Pagan and White tests indicate heteroscedasticity, justifying a robust inference. The results highlight a convex relationship between activity and performance: the marginal association is initially negative but becomes positive above a model-implied upper-tail level corresponding to approximately 46 transactions. This value should not be interpreted as a behavioral level or as a trading rule. The percentage of cash in the portfolio and the average trade size are negatively associated with performance, while the portfolio variability does not show a statistically significant association with performance. Overall, the results indicate heterogeneous trading patterns rather than a single activity–performance profile. Full article

The valorization of phosphogypsum (PG), a byproduct of phosphoric acid production, along with waste glass (WG) and silica fume (SF) into value-added materials has attracted growing attention in recent years. The present study aims to synthesize three types of porous geopolymers (GD, GDP, and GDG) using Tunisian clay and locally available mineral wastes, and to investigate their potential as low-cost adsorbents for the removal of methylene blue (MB) dye from aqueous solutions. The physicochemical characteristics of the raw precursors and the resulting porous geopolymers were analyzed using various techniques, including FTIR, XRD, BET, and SEM. Variations in Si/Al, Na/Al, and Ca/Al ratios play a critical role in the geopolymer structure. The high Ca/Al ratio in GDP (porous geopolymer from calcined clay and phosphogypsum) promotes the formation of C-A-S-H, leading to increased macroporosity, which favors adsorption capacity despite the presence of a more heterogeneous morphology. The results indicated that the maximum adsorption capacity (Qmax) for MB dye was obtained for the GDP sample, reaching 68 mg/g. Adsorption experiments revealed the successful removal of MB dye by geopolymers, with the Langmuir isotherm and pseudo-second-order kinetic models adequately describing the adsorption process. The MB uptake by geopolymers was facilitated by weak physicochemical interactions, including electrostatic attraction, hydrogen bonding, and π–π interactions. This study proposes a simple and effective alkali activation strategy that combines different industrial wastes within a single geopolymer system, resulting in improved porosity and adsorption efficiency. Overall, the findings highlight the potential of these waste-derived geopolymers as promising and sustainable adsorbents for wastewater treatment applications. Full article

Magnesium–rich environments are frequently encountered in cementitious systems, including the use of high–Mg raw materials in clinker production, cement–clay interfaces relevant to nuclear waste disposal, and exposure of cement–based materials to seawater, where progressive decalcification can substantially alter the structure and durability of calcium aluminosilicate hydrate (C–A–S–H) phases. In this study, density functional theory (DFT) calculations were employed to investigate the combined effects of interlayer and intralayer partial decalcification, Mg²⁺ substitution, and reinforcement with epoxy– and hydroxyl–functionalized reduced graphene oxide (rGO) on the structural stability and elastic properties of alkali charge–balanced C–A–S–H under dry and hydrated conditions. Adsorption–energy calculations reveal thermodynamically favorable interactions between functionalized rGO and silicate hydrate species in the presence of Mg²⁺, with hydroxyl/rGO promoting stronger interfacial stabilization and epoxy/rGO preserving greater graphene lattice integrity. The results demonstrate that Mg²⁺ substitution together with rGO intercalation generally enhances the mechanical response of partially decalcified structures through structural densification and interfacial cohesion. Relative to dry systems, hydration further improves elastic performance, increasing Young’s modulus and bulk modulus by 1–11% and 4–19%, respectively, for interlayer decalcified nanocomposites, while intralayer configurations exhibit stronger but model–dependent enhancements of up to ≈22% and ≈33%. Compared with untreated systems, rGO–treated nan–composites exhibit enhanced stiffness, with Young’s modulus and bulk modulus increasing by up to ≈22% and ≈15%, respectively. Overall, these findings provide atomistic insights into stabilization mechanisms in partially decalcified alkali charge–balanced C–A–S–H systems and identify Mg²⁺–rGO incorporation as a promising strategy for mitigating decalcification–induced degradation in durable low–carbon cementitious nanocomposites. Full article

This study investigates the determinants and predictability of stock return volatility by integrating firm-specific financial characteristics with advanced econometric and volatility modeling techniques. Using an unbalanced panel dataset comprising 1596 firms and 19,752 firm-year observations from MENA stock markets over the period 2010–2024, the analysis employs fixed-effects panel regression models, conditional volatility models, and machine learning-based forecasting approaches. Following extensive diagnostic testing, including tests for heteroskedasticity, serial correlation, cross-sectional dependence, and model specification, a two-way fixed-effects model with Driscoll–Kraay standard errors is adopted as the preferred estimation framework. The results indicate that liquidity ratio, cash ratio, sales growth, firm age, lagged volatility, and lagged returns are significant determinants of stock return volatility, whereas leverage, tangibility, board independence, firm size, Tobin’s Q, and profitability do not exhibit statistically significant effects after controlling for firm-specific and time-specific heterogeneity. The volatility analysis reveals substantial persistence in stock return volatility, with the EGARCH-t specification providing the best fit among the competing GARCH-family models according to the Akaike Information Criterion. The estimated asymmetry parameters indicate that volatility responds differently to positive and negative shocks, supporting the presence of asymmetric volatility dynamics and the suitability of asymmetric volatility models. The forecasting analysis shows that advanced machine learning and deep learning models achieve competitive predictive performance; however, differences in predictive accuracy across models are generally modest. Full article

Climate change and low-carbon transition policies affect sustainable development by changing firms’ financing costs and investors’ capital allocation. This paper investigates whether and how climate-related information is priced in China’s equity market, focusing on firm-level carbon intensity and exposure to climate policy uncertainty (CPU). First, univariate-sorted portfolio tests confirm the existence of a carbon premium, as firms with high carbon intensity earn significantly higher average returns. However, the unconditional relation between CPU exposure and stock returns is insignificant. Bivariate-sorted portfolios reveal a strong interaction between the carbon premium and the CPU premium. The carbon premium is higher for firms with high exposure to CPU, whereas a significant and negative CPU premium appears among low-carbon firms and, in sector-level tests, is concentrated in non-energy firms. Further analysis demonstrates clear differences between energy and non-energy sectors, which may be attributable to cash flow risks and uncertainty in growth options. The findings contribute to climate-related asset pricing and sustainable finance research by showing that transition-risk pricing depends on the interaction between carbon exposure and policy uncertainty. Full article

A central question in contemporary bail reform is whether the different forms of monetary release used in large U.S. jurisdictions, commercial surety bonds, deposit bonds, full cash bonds, and property bonds, produce systematically different pretrial outcomes. The commercial bail industry has long defended its role on the grounds that bondsman-supervised release produces superior pretrial outcomes through a private enforcement function not available under alternative mechanisms. The present study tests this claim using data from the 2009 State Court Processing Statistics program on 5271 felony defendants released on financial conditions in 35 large urban counties. Logistic regression models with county fixed effects and cluster-robust standard errors estimate the association between release mechanism and two outcomes, pretrial rearrest and failure to appear (FTA), net of bail amount, prior criminal record, seriousness of offense, criminal justice status at arrest, time from arrest to release, type of legal representation, and demographic characteristics. Three findings emerge. First, defendants released on deposit bonds exhibit substantially lower odds of pretrial rearrest than otherwise comparable defendants released on commercial surety bonds, a finding that is robust across a battery of sensitivity analyses. Second, defendants released on full cash bonds exhibit substantially lower odds of FTA than otherwise comparable defendants released on commercial surety bonds, although this finding is somewhat sensitive to specification choice and is partly mediated by bail amount. Third, no specification supports the public-safety claim made on behalf of commercial bail because surety bonds do not outperform the alternatives for either outcome. These findings indicate that the principal empirical justification for the commercial bail industry is not supported by nationally representative data, and that a shift away from commercial bail toward court-administered alternatives is unlikely to impose behavioral costs and may produce modest public-safety gains. Full article

The proliferation of Unmanned Aerial Vehicles (UAVs) in various applications has created a pressing need for robust and efficient communication systems. Fifth-generation (5G) networks can support UAV connectivity through high bandwidth and low-latency communication; however, rapid three-dimensional UAV mobility creates handover-management challenges that can increase signalling overhead, service interruption, and Quality of Service (QoS) degradation. This paper presents an integrated framework that combines LSTM-based multi-UAV trajectory prediction with proactive handover optimization using an Advantage Actor–Critic (A2C) Deep Reinforcement Learning (DRL) agent. The LSTM predictor is evaluated on a real-world UAV trajectory dataset and reports a root mean square error (RMSE) of 4.37 m over a 5 s prediction horizon after conversion to a local East–North–Up coordinate frame. A lightweight simulation-level coordination mechanism is included to reduce simultaneous target-cell contention among multiple UAVs; it is not claimed as a new standardized 3GPP signalling procedure. Handover performance is evaluated by replaying 180 held-out flight trajectories in a controlled 5G simulation across ten independent random seeds. Under these stated assumptions, the proposed framework achieves a handover success rate of $94.2\pm 0.8$%, an average SINR of $15.8\pm 0.2$ dB, a handover delay of $45.2\pm 1.1$ ms, and a handover frequency of $0.85\pm 0.05$ HOs/min, outperforming the tuned 3GPP A3, reactive SINR, and CASH baselines in the reported simulation results (Wilcoxon signed-rank test, $p<0.01$, Bonferroni-corrected). The experimental setup is described in detail to support methodological transparency and facilitate future replication, but the handover results should be interpreted as simulation-based evidence rather than live-network validation. Full article

Traditional olive groves are widely recognised as providers of landscape, environmental and cultural public goods in Mediterranean rural areas, but their long-term economic viability remains uncertain. This study assesses the income gap between traditional, intensive and super-high-density (SHD) olive-growing systems in a representative hill olive-growing area in Tuscany (central Italy), characterised by physical and structural conditions typical of traditional Mediterranean systems. Using a discounted cash-flow framework, the analysis compares long-term financial performance through standard investment appraisal indicators and uses the Equivalent Annual Value (EAV) as a policy-relevant benchmark for calibrating support. The results reveal a clear structural divergence: while intensive and SHD systems achieve higher profitability and faster capital recovery, the traditional system exhibits a persistent income disadvantage under market conditions. The estimated EAV gap amounts to approximately 950 €/ha relative to the intensive system and 3104 €/ha relative to the SHD system—values that represent the additional annual support required to preserve traditional olive groves and prevent abandonment. These values can also be interpreted as the annual private opportunity cost of maintaining traditional olive landscapes rather than converting them to more financially competitive systems. Break-even analysis further shows that the traditional system requires an oil price of at least 9.6 €/kg to achieve economic viability without public support, compared to 6.97 €/kg and 4.13 €/kg for the intensive and SHD systems, respectively. The findings highlight a structural misalignment between private profitability and social value, suggesting that the conservation of traditional olive landscapes cannot rely on market mechanisms alone and requires targeted, evidence-based policy instruments. Full article

E-commerce has reshaped short-term financial management by altering transaction speed, payment structures, and supply chain coordination. This study examines how large publicly listed e-commerce firms, viewed as complex digital business systems, adjusted their working capital policies during and after the COVID-19 shock. The sample is based on the 100 largest e-commerce companies worldwide by market capitalization, as reported by CompaniesMarketCap (February 2026), and is reduced to 76 firms from 23 countries due to data availability, yielding 802 firm-year observations. Firm-level data are obtained from LSEG Datastream, while macroeconomic variables are sourced from the World Bank. The analysis distinguishes between two dimensions of working capital: flow-based operational adjustment, measured by the cash conversion cycle (CCC), and stock-based balance-sheet adjustment, captured by net working capital relative to total assets (WC/TA). Fixed-effects models with firm-clustered standard errors are employed. The results indicate a substantial contraction of the CCC during the pandemic, followed by partial persistence of that contraction rather than a return to pre-pandemic norms. In contrast, WC/TA remains broadly stable during the crisis but declines in the post-pandemic period, suggesting a delayed balance-sheet adjustment. Business-model heterogeneity is not statistically significant, which may reflect a common system-level response across e-commerce firm types. Leverage and supply-chain pressures are associated with working capital intensity (WC/TA), while inflation shapes operate cycle duration (CCC). The findings are consistent with a two-stage adaptive response to systemic disruption. Full article

Against the background of global climate change and China’s dual-carbon strategic goal, agricultural carbon emission reduction and low-carbon transformation have become urgent practical issues. As an important characteristic cash crop in China, apple cultivation faces significant carbon emission pressure, and an obvious spatial imbalance exists in carbon productivity across major producing areas. Using the Dagum Gini coefficient, kernel density estimation, and Markov-chain analysis, this study analyzes regional differences in and the dynamic distribution of carbon productivity in China’s main apple-growing provinces from 2008 to 2024. The results indicate the following: (1) Overall, carbon productivity in China’s apple industry shows an upward trend, with a “rising–declining–rising–declining” M-shaped evolution during the study period. (2) The main reason for the overall differences is variation between regions, which shows a continuous inverted V-shaped change pattern of “rising–declining–rising–declining–rising–declining–rising.” (3) High-carbon-productivity areas have a positive effect on surrounding areas, while low-productivity areas have a negative effect. Therefore, to improve carbon productivity in apple cultivation, it is essential to not only understand regional differences and their causes but also leverage the positive effects of neighboring high-carbon-productivity areas to positively influence local conditions. This will help achieve cross-regional collaborative improvement in carbon productivity in China’s main apple-producing provinces. Full article

This study introduces a fractional optimal control model for managing cash balances, emphasizing the critical factor of long-term memory, particularly in the context of multiple investments. Leveraging the Caputo-type fractional derivative, our model captures memory effects, providing a nuanced perspective on financial dynamics. In contrast to single-degree-of-freedom fractional models, our approach assigns distinct parameters to represent memory in cash and investment behavior within a multi-degree-of-freedom framework. These parameters reflect the varying influence strengths of historical states on their corresponding current states. By doing so, we enhance the model’s flexibility and accuracy, enabling it to more faithfully depict real-world complexities. Our results reveal that introducing long-term memory yields smoother fluctuations in both cash and investment. Furthermore, the interplay of memory effects within this multi-degree-of-freedom context significantly impacts changes in enterprise cash balance. Notably, if we tentatively view memory as decision-makers’ reliance on historical data regarding cash and various investments, the magnitude of the memory parameter may be associated with the degree of historical dependence. A smaller value indicates stronger historical dependence. However, this is only a heuristic interpretation; establishing a rigorous link between memory parameters and decision-making behavior requires further empirical investigation. While our study primarily addresses straightforward cash balance problems, the clarity of our model construction and resulting insights holds broader implications. These findings can be extended to other contexts, providing meaningful conclusions for financial decision-makers. Full article

While Peribacillus simplex has been reported to alleviate abiotic stress-induced damage in diverse plant species, its precise functional mechanism in mediating salt tolerance in asparagus remains unclear. The present study sought to uncover the molecular regulatory mechanisms through which strain P10 enhances the salt adaptability of asparagus seedlings. We investigated physiological responses, as well as transcriptomic and metabolomic alterations, in P10-inoculated asparagus seedlings grown under saline conditions. The results demonstrated that P10 inoculation alleviated salt-induced physiological damage by enhancing antioxidant enzyme activities and promoting the accumulation of osmotic regulatory substances. Comparative transcriptomic and metabolomic analyses identified 1659 differentially expressed genes (DEGs) and 128 differentially accumulated metabolites (DAMs) between P10-inoculated and non-inoculated seedlings under salt stress. These DEGs were primarily associated with multiple biological pathways, including phenylpropanoid biosynthesis, nitrogen metabolism, and flavonoid biosynthesis pathways (flavone, flavonol, and total flavonoid synthesis). Metabolomic profiling indicated that organic acids constituted the most abundant class of DAMs, followed by amino acids and their derivatives, and flavonoids. Integrated transcriptomic and metabolomic analyses suggested that P10 optimized the amino acid metabolic network under salt stress by upregulating genes involved in nitrogen assimilation, glutathione biosynthesis, and polyamine biosynthesis, thereby promoting amino acid accumulation and enhancing glutathione and polyamine levels. In addition, P10 markedly stimulated flavone and flavonol biosynthesis while maintaining elevated anthocyanin levels. Overall, P10 mitigated salt stress injury in asparagus by regulating amino acid metabolism to improve osmotic balance and growth stability, while simultaneously redirecting phenylpropanoid flux toward flavone and flavonol biosynthetic pathways to fine-tune stress responses. Full article

The economic resilience of agricultural enterprises is increasingly relevant for maintaining processing continuity and food quality in highly perishable agro-food chains. This study examines the associations between financial knowledge, financial management competency, business liquidity, and operational food-processing continuity in Türkiye’s tea sector. A quantitative cross-sectional design was employed, using structured survey data from 203 senior managers across 86 public and private tea-processing firms in Rize Province. The data were analysed using Ordinary Least Squares regression, mediation analysis, exploratory factor analysis, and robustness checks in accordance with OECD/INFE guidelines. Results indicate a significant deficit in theoretical financial knowledge (mean score: 4.47/10) alongside widespread overconfidence among 85% of managers. Applied financial management competency is positively associated with perceived business liquidity (β = 0.336, p < 0.001), suggesting that practical budgeting, cash-flow planning, and financial decision-making capabilities are relevant to maintaining operational funding capacity. In contrast, cash-flow difficulties are not significantly explained by firm-level financial knowledge, managerial competency, liquidity, or ownership structure (R² = 0.014, p = 0.722), indicating that these difficulties may reflect broader seasonal and sector-wide financing constraints. The findings challenge the assumption of a linear relationship between theoretical financial knowledge and managerial outcomes. They suggest a dual policy approach that combines applied financial management training with structural financing mechanisms to ensure the continuity of fresh leaf procurement and processing. While the study does not directly measure food safety, post-harvest losses, or SDG outcomes, the results have potential implications for reducing processing disruptions and supporting more resilient agro-food processing systems. Full article

In this study, three types of industrial solid waste—granulated blast furnace slag (GBFS), fly ash, and desulfurization gypsum (DG)—are utilized to collaboratively prepare low-carbon cementitious materials. The effects of steam curing temperature, constant temperature time, and fly ash content on the mechanical properties of multi-source solid waste cementitious materials are systematically investigated, and the optimal mix proportion ratio for low-carbon cementitious materials is determined. The results indicate that as steam curing temperature and constant temperature time increase, the compressive strength of the ternary cementitious material generally shows an upward trend, while the fly ash content exhibits a negative correlation. When the steam curing temperature is 70 °C, the constant temperature time is 10 h, the fly ash content is 20%, and the strength can reach 24 MPa, with both its engineering performance and economic benefits meeting the requirements of practical applications. Meanwhile, the steam curing temperature shows a tendency of first decreasing and then increasing shrinkage rate after 28 d, with the lowest shrinkage rate at 70 °C. Extending the constant temperature time can slightly reduce shrinkage, and the addition of 20–30% fly ash can optimize shrinkage performance. Moreover, the TG/DTG and SEM-EDS microscopic testing demonstrates that the ternary system achieves synergistic activation by accelerated mineral dissolution, ion release and enhanced alkalinity under steam curing, which jointly promotes the formation of AFt and C-A-S-H gel to refine microstructure and improve compactness. This study can not only reduce the consumption of cement, but also facilitate the recycling of industrial waste, providing theoretical support for the application of multi-source solid waste low-carbon materials in practical engineering. Full article