Search Results (359)

Rising global demand for food and fibre requires more efficient and sustainable fertilizer strategies. Biochar mineral complexes (BMC) are being developed for use as an organic alternative to conventional synthetic fertilizers, or to supplement conventional fertilizers applied at lower rates. Biochar can change electrochemical properties such as zeta potential (ZP) that influence nutrient use efficiency. However, the impact of BMCs on the ZP of plant roots remains unknown. This study investigated the effects of BMC on root zeta potential, nutrient leaching, and yield in an intensive protected cropping system. A novel BMC was developed and tested in four treatments: synthetic fertilizer, organic fertilizer, BMC with half-rate organic fertilizer, and BMC alone. Organic fertilizer significantly increased negative root ZP compared with other treatments, largely due to higher concentrations of –COOH and –OH functional groups on the potting media. Treatments containing organic fertilizer also increased pH and cation exchange capacity (CEC), enhancing nutrient availability and retention relative to synthetic fertilizer. Yield was greatest with synthetic fertilizer; however, BMC combined with half-rate organic fertilizer achieved similar yields to full-rate organic fertilizer. This indicates that BMC co-applied with half-rate organic fertilizer should be considered by farmers to be a viable alternative to full-rate organic fertilizer regimes to reduce net inputs and risk of negative environmental impacts from over-fertilization. Full article

Background: Sickle cell disease (SCD) is a hereditary hemoglobinopathy associated with life-threatening complications such as acute chest syndrome (ACS), which may necessitate extracorporeal membrane oxygenation (ECMO) in refractory cases. Despite growing use, ECMO in SCD remains challenging due to risks of hemolysis, thrombosis, and anticoagulation complications. This systematic review consolidates existing evidence on ECMO outcomes in SCD, focusing on indications, complications, and survival. Methods: A systematic search of MEDLINE, Cochrane CENTRAL, and Google Scholar was conducted up to January 2025, identifying case reports/series on ECMO use in SCD. Studies reporting venovenous (VV) or venoarterial (VA) ECMO for acute cardiopulmonary failure were included. Data on demographics, laboratory findings, management, and outcomes were extracted. Quality assessment was performed using the Joanna Briggs Institute checklist. Results: Sixteen case reports (23 patients) were included. Most patients were female (65.2%), with ACS (47.8%) and pulmonary embolism (13.0%) as common ECMO indications. VV-ECMO (69.6% of cases) was primarily used for respiratory failure, with a 69% survival rate, while VA-ECMO (30.4%) had a 29% survival rate, often due to cardiogenic shock or cardiac arrest. Complications included hemorrhage (26.1%), neurological injury (21.7%), and thrombosis (13.0%). Exchange transfusion was frequently employed (43.5%), with post-ECMO echocardiography showing improved right ventricular function in survivors. Conclusions: VV-ECMO demonstrates favorable outcomes in SCD-related respiratory failure, whereas VA-ECMO carries higher mortality risks. Careful patient selection, anticoagulation management, and multidisciplinary coordination are essential. Larger prospective studies are needed to refine ECMO utilization in this high-risk population. Full article

Urban pluvial waterlogging has become a major challenge for densely populated cities due to increasingly extreme rainfall events and the rapid expansion of impervious surfaces. In response to the growing demand for localized waterlogging risk assessments, an automated evaluation framework is proposed that integrates high-resolution digital elevation models (DEMs), rainfall scenarios, and classified building data within a GIS-based modeling system. The methodology consists of four modules: (i) design of rainfall scenarios and runoff estimation, (ii) waterlogging depth simulation based on volume-matching algorithms, (iii) construction of depth–damage curves for residential and commercial buildings, and (iv) building-level economic loss estimation though differentiated depth–damage functions for residential/commercial assets—a core innovation enabling sector-specific risk precision. A case study was conducted in the Lixia District, Jinan City, China, involving 15,317 buildings under a 50-year return period rainfall event. The total economic losses were shown to reach approximately USD 327.88 million, with residential buildings accounting for 88.6% of the total. The model achieved a mean absolute percentage error within 5% for both residential and commercial cases. The proposed framework supports high-precision, building-level urban waterlogging damage assessment and demonstrates scalability for use in other high-density urban areas. Note: all monetary values were converted from Chinese Yuan (CNY) to U.S. Dollars (USD) using an average exchange rate of 1 USD = 7.28 CNY. Full article

This paper examines the relationship between currency misalignment and income inequality across 70 countries from 1998 to 2021. Currency misalignment occurs when the actual exchange rate diverges significantly from the equilibrium exchange rate. Using fixed-effects and random-effects regressions, we find that currency overvaluation is associated with higher income inequality, while undervaluation is linked to lower income inequality. These findings are strongest in emerging markets and upper-middle-income countries, where undervalued currencies may be associated with stronger tradable-sector activity and narrower income gaps. In contrast, lower-income countries experience increasing levels of inequality during the early stages of development, even with growth, which is consistent with the Kuznets hypothesis. For advanced markets and higher-income nations, currency misalignment is not statistically related to income inequality, which is likely due to the presence of stronger financial systems and more stable institutions that reduce the effects of currency misalignment. The results are robust across the two grouping methods—development level (IMF) and income level (World Bank). Overall, the study highlights that while undervaluation may be associated with equitable growth in emerging markets, its benefits likely depend on a country’s development stage and are more likely when accompanied by appropriate social and economic policies to mitigate potential risks. Full article

Objectives: To clarify the need for a kidney exchange program (KEP) in Japan by conducting a questionnaire survey on KEPs and simulated KEPs by virtual cross-matching based on past cases of transplantation avoidance. Methods: In addition to the content regarding KEPs, an electronic survey was conducted to investigate the number of cases of kidney transplant abandonment due to “immunological” reasons over the past 10 years (2012–2021). Virtual cross-matching was conducted to simulate the feasibility of avoiding immunological risks and enabling kidney transplantation in patients who were previously unable to undergo the procedure. Results: The survey received responses from 107 facilities (response rate: 81.7%). In response to the question about the necessity of a KEP in Japan, 71 facilities (66.4%) indicated that KEPs are necessary. In addition, 251 living-donor kidney transplants were abandoned for “immunological” reasons over the past decade (2012–2021). Among the 80 pairs for which detailed information was available, virtual cross-matching simulations showed that 37/80 pairs (46.3%) were donor-specific antibody (DSA)-negative for blood type-matched combinations, and 41/80 pairs (51.3%) were DSA-negative for blood type-incompatible transplants. Conclusions: The need for a KEP in Japan and its potential usefulness were demonstrated. Full article

International organizations have highlighted the importance of consistent and reliable environment, social and governance (ESG) disclosure and metrics to inform business strategy and investment decisions. Greater corporate disclosure is a positive signal to investors who prioritize sustainable investment. In this study, economic and climate sentiment are extracted from the integrated and sustainability reports of the top 40 corporates listed on the Johannesburg Stock Exchange, employing domain-specific natural language processing. The intention is to clarify the complex interactions between climate risk, corporate disclosures, financial performance and investor sentiment. The study provides valuable insights to regulators, accounting professionals and investors on the current state of disclosures and future actions required in South Africa. A time series analysis of the sentiment scores indicates a noticeable change in the corporates’ disclosures from climate-related risks in the earlier years to climate-related opportunities in recent years, specifically in the banking and mining sectors. The trends are less pronounced in sectors with good ESG ratings. An exploratory regression study reveals that climate and economic sentiments contain information that explain stock price movements over the longer term. The results have important implications for asset allocation and offer an interesting direction for future research. Monitoring the sentiment may provide early-warning signals of systemic risk, which is important to regulators given the impact on financial stability. Full article

Economic stability in emerging market economies is increasingly shaped by the interplay between global financial integration, domestic monetary dynamics, and asset price fluctuations. Yet, early detection of financial market disruptions remains a persistent challenge. This study constructs a Financial Stress Index (FSI) for Pakistan, utilizing monthly data from 2005 to 2024, to capture systemic stress in a globalized context. Using Principal Component Analysis (PCA), the FSI consolidates diverse indicators, including banking sector fragility, exchange market pressure, stock market volatility, money market spread, external debt exposure, and trade finance conditions, into a single, interpretable measure of financial instability. The index is externally validated through comparisons with the U.S. STLFSI4, the Global Economic Policy Uncertainty (EPU) Index, the Geopolitical Risk (GPR) Index, and the OECD Composite Leading Indicator (CLI). The results confirm that Pakistan’s FSI responds meaningfully to both global and domestic shocks. It successfully captures major stress episodes, including the 2008 global financial crisis, the COVID-19 pandemic, and politically driven local disruptions. A key understanding is the index’s ability to distinguish between sudden global contagion and gradually emerging domestic vulnerabilities. Empirical results show that banking sector risk, followed by trade finance constraints and exchange rate volatility, are the leading contributors to systemic stress. Granger causality analysis reveals that financial stress has a significant impact on macroeconomic performance, particularly in terms of GDP growth and trade flows. These findings emphasize the importance of monitoring sector-specific vulnerabilities in an open economy like Pakistan. The FSI offers strong potential as an early warning system to support policy design and strengthen economic resilience. Future modifications may include incorporating real-time market-based metrics indicators to better align the index with global stress patterns. Full article

Cryptocurrency is often viewed as a hedge against economic instability, yet the extent to which economic risk drives digital asset adoption remains unclear. This study asks to what extent does economic risk shape global cryptocurrency adoption? To address this question, the research investigates how variables such as inflation, corruption, unemployment, and exchange rate volatility influence adoption patterns. Using panel data from 41 countries between 2019 and 2024, the study employs country fixed-effects regression models and Principal Component Analysis. A novel Regulatory Permissiveness Index is introduced to evaluate the role of national regulatory environments. The findings show that cryptocurrency adoption is primarily associated with structural enablers such as GDP per capita, internet penetration, and regulatory clarity. Among the economic risk indicators, higher corruption and lower unemployment significantly predict adoption. Other economic factors, such as inflation and exchange rate volatility, are not consistently significant. The results suggest that economic development and digital infrastructure, rather than reactive responses to economic crises, are the main drivers of cryptocurrency adoption. Nonetheless, the significance of corruption highlights the role of institutional dissatisfaction in adoption behaviour, even in economically stable settings. Full article

This paper investigates the dynamics of volatility spillovers in the South African foreign exchange market across calm and crisis periods, with particular attention paid to the pre- and post-COVID-19 eras. Employing daily exchange rate returns from 2015 to 2025, we apply a Quantile Vector Autoregression (QVAR) model to uncover asymmetries in spillover transmission across the distribution of returns. We evaluate the implications of these spillovers for portfolio performance under three canonical strategies: risk parity, tangency, and naïve equal-weighting. Our findings indicate that the COVID-19 shock intensified volatility spillovers and exacerbated their asymmetry, especially in the lower tail, while the pre-COVID period portrayed higher volatility compared to the post-COVID period under calm market conditions. While risk-based strategies dominate in tranquil markets, equal-weighted portfolios exhibit superior downside resilience under stress, although they ignore risk exposure. These results underscore the importance of accounting for tail-risk-driven interconnectedness in portfolio construction and risk management. This study contributes to the growing literature on volatility spillovers and offers practical insights for managing currency exposure in emerging markets under nonlinear dependence structures. Full article

The current study focuses on a preliminary evaluation of the use of solid residues produced from the distillation of selected medicinal and aromatic plants (MAP) as fertilizers for alkaline soils. Specifically, the residues of hemp (Cannabis sativa L.), helichrysum (Helichrysum Italicum (Roth) G. Don), lavender (Lavandula angustifolia Mill.), oregano (Origanum vulgare L.), rosemary (Rosmarinus officinalis L.) and sage (Salvia officinalis L.) were added in an alkaline and calcareous soil at the rates of 0 (control), 1, 2, 4 and 8%, in three replications (treatments), and the treated soils were analyzed. The results showed that upon application of the residues, soil electrical conductivity (EC), organic C, total N and the C/N ratio significantly increased, especially at the 4 and 8% rates. The same was found for soil available P, K, B, Cu and Mn. The effects of the residues on soil pH, cation exchange capacity (CEC) and available Zn and Fe were rather inconclusive, whereas soil available N significantly decreased, which was somewhat unexpected. From the different application rates tested, it seems that all residues could improve soil fertility (except N?) when they were applied to soil at rates of 2% and above, without exceeding the 8% rate. The reasons for the latter statement are soil EC and available Mn: the doubling of EC upon application of the residues and the excessive increase in soil available Mn in treatments with 8% residues raise concerns of soil salinization and Mn phytotoxicity risks, respectively. This work provides the first step towards the potential agronomic use of solid residues from MAP distillation in alkaline soils. However, for the establishment of such a perspective, further research is needed in respect to the effect of residues on plant growth and soil properties, by means of at least pot experiments. Based on the results of the current study, the undesirable effect of residues on soil available N should be investigated in depth, since N is the most important essential element for plant growth, and possible risks of micronutrient phytotoxicities should also be studied. In addition, application rates between 2 and 4% should be studied extensively in order to recommend optimum application rates of residues to producers. Full article

In this paper a new state model is introduced, an adaptative state model in a binary temporal representation (ASMBRT) as well as its application in constructing an algorithmic trading system. The presented model uses the binary temporal representation, which allows for a precise analysis of exchange rates without losing any informative value of the data. The basis of the model is the trajectory analysis for the ensuing changes in price quotations and dependencies between the duration of each change. The main advantage of the model is to eliminate the threshold analysis, used in existing state models. This solution allows for a more accurate identification of investor behavior patterns, which translates into a reduction of investment risk. In order to verify obtained results in practice, the paper presents a concept of creating an algorithmic trading system and an analysis of its financial effectiveness for the exchange rate most popular among investors, namely EUR/USD. Full article

This study examines the impact of geopolitical risk (GPR) on the connectedness dynamics among the sovereign bonds of the emerging seven (E7) and the Group of Seven (G7) countries. Initially, a quantile-based vector-autoregressive (Q-VAR) connectedness approach is used to calculate the total connectedness index (TCI) among sovereign bonds under different market states. Then, the impact of GPR on the TCI at the median and tails is estimated to examine if GPR affects the TCI among sovereign bonds. Using daily yields from 30 January 2012, to 17 June 2024, the findings show that the GPR is one of the significant determinants of the TCI among sovereign bonds during normal and extreme market conditions. Other determinants of the TCI include yields on Treasury bills (T-bills), the exchange rate, and the financial market volatility index. The impact of GPR on the TCI varies significantly during different GPR episodes and bond market conditions. The effect of GPR on the TCI among sovereign bonds yields is higher during war times and when bond yields are average. These findings can be utilized by investors seeking to achieve international diversification and policymakers aiming to mitigate the effects of heightened geopolitical risk on financial stability. Furthermore, GPR can be used as an early signal tool for systematic tail risk spillovers among sovereign bonds. Full article

Understanding the price dynamics of oil futures is crucial for advancing green finance strategies and supporting sustainable energy transitions. This study investigates the macroeconomic and energy market determinants of oil futures prices through Granger causality, cointegration analysis, and the error correction model, using daily data. It focuses on the influence of economic development levels, exchange rate fluctuations, and inter-energy price linkages. The empirical findings indicate that (1) oil futures prices exhibit strong correlations with other energy prices, macroeconomic factors, and exchange rate variables; (2) economic development significantly affects oil futures prices, while exchange rate impacts are statistically insignificant based on the daily data analyzed; (3) there exists a stable long-term equilibrium relationship between oil futures prices and variables representing economic activity, exchange rates, and energy market trends; (4) oil futures prices exhibit significant short-term dynamics while adjusting steadily toward a long-run equilibrium driven by macroeconomic and energy market fundamentals. By enhancing the accuracy of oil futures price forecasting, this study offers practical insights for managing financial risks associated with fossil energy markets and contributes to the formulation of low-carbon investment strategies. The findings provide a valuable reference for integrating energy pricing models into sustainable finance and climate-aligned portfolio decisions. Full article

This study investigates the relationship between sovereign credit rating transitions and domestic equity market performance, focusing on Greece from 2004 to 2024. Although credit ratings are central to sovereign risk assessment, their immediate influence on financial markets remains contested. This research adopts a multi-method analytical framework combining algebraic combinatorics and time-series econometrics. The methodology incorporates the construction of a directed credit rating transition graph, the partially ordered set representation of rating hierarchies, rolling-window correlation analysis, Granger causality testing, event study evaluation, and the formulation of a reward matrix with optimal rating path optimization. Empirical results indicate that credit rating announcements in Greece exert only modest short-term effects on the Athens Stock Exchange General Index, implying that markets often anticipate these changes. In contrast, sequential downgrade trajectories elicit more pronounced and persistent market responses. The reward matrix and path optimization approach reveal structured investor behavior that is sensitive to the cumulative pattern of rating changes. These findings offer a more nuanced interpretation of how sovereign credit risk is processed and priced in transparent and fiscally disciplined environments. By bridging network-based algebraic structures and economic data science, the study contributes a novel methodology for understanding systemic financial signals within sovereign credit systems. Full article

The impact of Environmental, Social, and Governance (ESG) scores on financial performance remains a subject of debate, as the literature reports mixed evidence regarding their effect on stock returns. This research aims to examine the relationship between ESG ratings and the change in ESG scores, or ESG Momentum, concerning both returns and risk of a large sample of stocks traded on U.S. exchanges. The study examined a sample of 3856 stocks traded on U.S. exchanges, considering 20 years of quarterly data from December 2002 to December 2022. We applied multi-factor models and tested them through pooled ordinary, fixed effects, and random effects panel regression methods. Our results show negative relationships between ESG scores and stock returns and between ESG Momentum and volatility. Contrarily, we find positive associations between ESG Momentum and returns and between ESG scores and volatility. Although high ESG scores are generally associated with lower long-term stock returns, an increase in a company’s ESG rating tends to translate into immediate positive returns and reduced risk. Accordingly, investors may benefit from strategies that focus on companies actively improving their ESG performance, while firms themselves stand to gain by signaling continuous advancement in ESG-related areas. Full article