Search Results (649)

This study investigates the impact of corporate governance factors and environmental, social, and governance (ESG) regulations on environmental performance and emissions in Saudi Arabian companies to explore whether these companies are in line with the Sustainable Development Goals (SDGs). Using a pooled panel data approach for 51 Saudi-listed firms over the period from 2016 to 2023, the study examines the role of various governance mechanisms, such as audit committees, internal audits, audit quality, and leverage, in influencing companies’ environmental outcomes. The results indicate that ESG regulations have a promotive and statistically significant impact on reducing environmental emissions and improving environmental performance, particularly when supported by robust governance audit mechanisms. The results show that audit committee expertise, internal auditing, and audit tenure after ESG regulations exhibit a positive and significant effect on reducing environmental emissions and improving environmental performance. The findings have important policy, managerial, and theoretical implications, emphasizing the role of government regulations in shaping corporate sustainability practices, the need for improved corporate governance, and the theoretical link between governance and environmental performance. The study bridges an existing gap in the context of the impact of ESG regulations in emerging economies. The study contributes to the growing body of knowledge on ESG practices in emerging markets, particularly in the context of Saudi Arabia’s regulatory landscape. Full article

Background/Objectives: This systematic review evaluates unconventional mammalian models from wild, agricultural, and urban/domestic ecosystems for genotoxicity assessment under the One Health framework. Non-human primates (NHPs), cattle, and domestic dogs are analyzed as sentinel species due to their distinct environmental niches, unique human interactions, and species-specific traits. In conjunction with this, evidence is presented about the in vitro use of cells of these mammals for the genotoxicological evaluation of different chemical substances, such as veterinary drugs, environmental pollutants, and pesticides. The synthesis focuses on standardized genetic toxicology assays (e.g., chromosomal aberrations, micronucleus, comet assay) aligned with Organization for Economic Cooperation and Development (OECD) guidelines. Methods: A structured search of international literature identified studies employing OECD-compliant genotoxicity assays in NHPs, cattle, dogs, and others not listed in OECD. Data was categorized by species, assay type, chemical class evaluated, environmental context (wild, agricultural, urban), and merits of the papers. Results: NHPs, despite their phylogenetic proximity to humans, show limited genotoxicity data in contrast to biomedical research, which has been constrained by ethical concerns and fieldwork logistics. Cattle emerge as robust models in agricultural settings due to the abundance of studies on the genotoxic capacity of pesticides, veterinary drug, and environmental biomonitoring, with direct implications for food safety. Domestic dogs are recognized as powerful sentinels for human health due to shared exposomes, physiological similarities (e.g., shorter cancer latency), and reduced lifestyle confounders; however, genotoxicity studies in dogs remain sparse compared to chemical exposure monitoring or cancer research. Conclusions: This review advocates for expanded, integrated use of these models to address genotoxic threats across ecosystems, which would benefit both animal and human health. In the application of biomonitoring studies with sentinel animals, a critical gap persists: the frequent lack of integration between xenobiotic quantification in environmental and biological samples, along with genotoxicity biomarkers evaluation in sentinel populations, which hinders comprehensive environmental risk assessment. Full article

This study examined the impact of tax avoidance on firm value. Further, it investigated whether ESG disclosure moderates this relationship. This study examined the top 100 non-financial firms listed in the S&P/EGX ESG index over the period from 2018 to 2022. The sample contained 80 companies with 400 firm-year observations. Statistical analysis was conducted using pooled ordinary least squares (OLS) and fixed effects regression models. The statistical analysis revealed a negative and significant impact of tax avoidance on firm value. Further, ESG disclosure was found to have a negative moderating impact as it eliminated the negative impact of the effect of tax avoidance on firm value, leading to a positive overall effect. These results carry important implications for regulators, investors, and shareholders in Egypt and other emerging markets, underscoring ESG disclosure’s pivotal role in enhancing firm value and reducing tax avoidance practices within the Egyptian market. To the best of our knowledge, this study represents one of the earliest empirical explorations into the moderating effect of ESG disclosure on the relationship between tax avoidance and firm value in an emerging market. By presenting empirical evidence from the Egyptian market, this research broadens the existing literature on tax avoidance and firm value, offering fresh perspectives on the influence of ESG disclosure. Early studies have primarily focused on the direct effect of ESG disclosure on firm value. Full article

Corporate social responsibility (CSR) and sustainability have proliferated the corporate boardroom agenda and companies’ leadership teams are trying to find ways to improve their social and environmental performance and enhance their corporate governance management systems. This paper investigates the main CSR and sustainability-related standards that modern corporations use. To do so, it uses a sample of the 60 companies listed in the ATHEX ESG index. Firstly, a content analysis of those companies’ sustainability reports is conducted. The 60 companies are categorized into sectors according to the Global Industry Classification Standard (GICS). The sustainability standards used by each sector are grouped into four categories, namely environmental, social, governance, and reporting. Furthermore, an attempt is made to establish a link between the standards used and both the sectors they belong to and the material topics of each sector as they emerge from each company’s materiality analysis. Our research shows that our sample companies predominantly utilize reporting standards regardless of their sector. We did not establish a definitive relation between the prioritized material topics and the relative standards employed by the companies. We may have recognized certain pairings such as environmental material topics with relative environmental management systems, but not in a rigid manner or across all material topic categories. Full article

In recent years, China has actively advanced the new energy vehicle industry to achieve its “dual carbon” objectives via a green revolution. The growth of green technical innovation by new energy vehicle enterprises has emerged as a significant national support project, and it has implemented a number of new energy vehicle promotion policies. Therefore, it is essential to investigate if promotional policies encourage the development of green technologies in businesses. China’s 2016 “New Energy Vehicle Promotion Catalogue” serves as the policy’s temporal shock point, and data from Chinese-listed new energy vehicle companies from 2011 to 2022 are used in this study. The effect and mechanism of the new energy vehicle promotion strategy on developing green technologies in businesses are investigated using a double difference model. As per the research, the promotion policy substantially enhances the green technological innovation of new energy vehicle firms. It can augment the level of R&D investment and alleviate financing constraints for enterprises, and enterprises’ social responsibility can act as a positive moderator for the promotion policy and enterprise green technological innovation. Finally, it has a more apparent positive impact on the green technological innovation of major companies and non-state-owned enterprises compared to state-owned firms. Additionally, it is more evident that enterprises are raising green technology innovation in the eastern and central regions. Full article

This study investigates the properties of financial markets that arise from the multi-scale structure of volatility, particularly intermittency, by employing robust theoretical tools from nonequilibrium thermodynamics. Intermittency in velocity fields along spatial and temporal axes is a well-known phenomenon in developed turbulence, with extensive research dedicated to its structures and underlying mechanisms. In turbulence, such intermittency is explained through energy cascades, where energy injected at macroscopic scales is transferred to microscopic scales. Similarly, analogous cascade processes have been proposed to explain the intermittency observed in financial time series. In this work, we model volatility cascade processes in the stock market by applying the framework of stochastic thermodynamics to a Langevin system that describes the dynamics. We introduce thermodynamic concepts such as temperature, heat, work, and entropy into the analysis of financial markets. This framework allows for a detailed investigation of individual trajectories of volatility cascades across longer to shorter time scales. Further, we conduct an empirical study primarily using the normalized average of intraday logarithmic stock prices of the constituent stocks in the FTSE 100 Index listed on the London Stock Exchange (LSE), along with two additional data sets from the Tokyo Stock Exchange (TSE). Our Langevin-based model successfully reproduces the empirical distribution of volatility—defined as the absolute value of the wavelet coefficients across time scales—and the cascade trajectories satisfy the Integral Fluctuation Theorem associated with entropy production. A detailed analysis of the cascade trajectories reveals that, for the LSE data set, volatility cascades from larger to smaller time scales occur in a causal manner along the temporal axis, consistent with known stylized facts of financial time series. In contrast, for the two data sets from the TSE, while similar behavior is observed at smaller time scales, anti-causal behavior emerges at longer time scales. Full article

Background/Objectives: Acute kidney injury (AKI) is a significant global health issue with a high morbidity and mortality. The Kidney Disease: Improving Global Outcomes (KDIGO) guidelines identify various exposures and susceptibilities as risk factors for AKI. However, the predictive significance of these factors in heterogeneous emergency department (ED) populations remains unclear. We hypothesized that assessing KDIGO-listed exposures and susceptibilities for AKI, alone and in combination, would provide an insight into their predictive value for AKI. Furthermore, we investigated whether adding biomarkers, plasma neutrophil gelatinase-associated lipocalin (pNGAL) and C-reactive protein (CRP), could enhance AKI risk prediction. Methods: Data were analyzed from the prospective longitudinal “NGAL study” conducted at North Zealand University Hospital in Denmark. A total of 344 ED patients were included, with AKI diagnosed using KDIGO’s creatinine-based criteria. Patient data, including medical history, exposures, and susceptibilities, were extracted and analyzed. Predictive performance was evaluated using a receiver operating characteristic (ROC) analysis on individual and combined risk factors. Additional models incorporated pNGAL and CRP to assess their impact on prediction accuracy. Results: Individual exposures and susceptibilities showed a poor predictive performance, with nephrotoxic drugs and advanced age demonstrating the highest sensitivity but a low positive predictive value (PPV). Combining multiple risk factors improved AKI prediction, with models clustering into those optimizing sensitivity or PPV. The inclusion of pNGAL significantly enhanced predictive performance, achieving the highest combined sensitivity and PPV. Although less than pNGAL, CRP also improved prediction, while requiring fewer variables than pNGAL-inclusive models. Conclusions: No individual KDIGO-listed exposure or susceptibility could reliably predict AKI in the ED setting. Combining multiple exposures and susceptibilities improved the predictive accuracy, but the models excelled either at screening or confirmation, not both. The addition of pNGAL and CRP significantly enhanced AKI prediction, emphasizing the need for biomarker integration in risk stratification models. These findings highlight the limitations of clinical parameters alone and underscore the importance of a multifaceted approach to AKI risk assessment. Full article

Seed production of common vetch (Vicia sativa L.) and sweet white lupine (Lupinus albus L.) is risky due to weed infestation as few herbicides are permitted for use in crops. Our aim was to test herbicides in these crops in order to expand the list of available herbicides. Various pre- and post-emergence herbicides were tested for their phytotoxicity and weed-control activity in field cultures of the common vetch (cv. Emma) and sweet white lupine (cv. Nelly). After the application of herbicides, phytotoxicity was monitored visually. Data collection involved the Normalized Difference Vegetation Index (NDVI), the plant height, the number of weeds, yield, and its contamination. Additionally, 1000-seed-weight measurements were taken for lupine. Summarizing the phytotoxicity and efficacy results in common vetch, the agents S-metolachlor, flumioxazin, and clomazone can be recommended for further pre-emergence testing, while metazachlor + quinmerac, chlorotoluron, and flumioxazin can be recommended for further post-emergence testing. In sweet white lupine, pre-emergence applications of flumioxazin, pendimethalin, dimethenamid-P, pethoxamid, clomazone, metobromuron, and diflufenican were found to be effective without any significant phytotoxicity. Further post-emergence testing of flumioxazin, chlorotoluron, carfentrazone-ethyl, and diflufenican can also be recommended, as well as the application of halauxifen-methyl and sulfosulfuron at low doses (0.4 L ha⁻¹; 13.0 g ha⁻¹). Additional evaluations of these treatments are recommended, including in different soil and weather conditions. Full article

Under the pressure of the global low-carbon transition, green initiatives have gradually emerged as a critical direction for outward foreign direct investment (OFDI). In the context of China’s high-level opening up, environmental, social, and governance (ESG) performance can promote sustainable development of firms. However, there is lack of research on the influence of ESG performance from the perspective of corporate green OFDI. This study examines the impact mechanism of ESG performance on corporate green OFDI in terms of its propensity and depth, using a sample of Chinese A-share listed firms from 2009 to 2023. The findings indicate that ESG performance promotes corporate green OFDI, a result that remains robust after a series of endogeneity and robustness tests. The internal mechanism analysis reveals that ESG performance enhances corporate green OFDI by reducing financing constraints and managerial myopia and by promoting risk-taking and foreign institutional investors’ shareholdings. The external mechanism analysis verifies that ESG institutional constraints in the home country and ESG locational advantages in host countries strengthen the positive effect of ESG performance on corporate green OFDI. Further analysis shows that ESG performance facilitates corporate green innovation development through collaborative and independent innovation by promoting corporate green OFDI. By extending the theoretical understanding of the impact of ESG performance on the process of corporate green OFDI, this study provides strategic guidance for the sustainable development of firms in China and other similar developing countries. Full article

The United States is facing outbreaks of highly pathogenic avian influenza H5N1 in birds and dairy cattle, along with threats of African swine fever, classical swine fever, and foot-and-mouth disease. While the National Animal Health Laboratory Network (NAHLN) depends on high-throughput testing, the KingFisher Duo Prime, IndiMag 48s, and IndiMag 2 are viable alternatives to aid in outbreak assessments. This study evaluates extraction platforms and the IndiMag Pathogen Kit for detecting the previous listed pathogens. Samples and reference materials were extracted using the MagMAX Viral RNA Isolation Kit, MagMAX CORE Nucleic Acid Purification Kit, and IndiMag Pathogen Kit. Real-time RT-PCR was performed following NAHLN protocols to assess analytical and diagnostic performance. Comparable limits of detection across extraction chemistries, instrumentation, and pathogens were demonstrated, with PCR efficiency ranging between 82.5% and 107.6%. The precision variability was low, with the coefficient of variation ranging from 0.16% to 1.76%. Diagnostic sensitivity and specificity were 100%, with a kappa coefficient of 1.0, indicating strong agreement between methods. These findings support the KingFisher Duo Prime, IndiMag 48s, IndiMag 2, and IndiMag Pathogen Kits as reliable options for NAHLN-approved testing, increasing equipment and reagent alternatives to enhance diagnostic resilience and improve response capabilities to emerging animal health threats. Full article

Fifth-Generation (5G) cellular networks extensively utilize subscriber identifiers throughout the protocol stack, thereby linking subscribers to their activities on the network. With the inherent use of linked identifiers comes the potential capability to track subscribers’ location and behavior, which poses critical challenges for user identity protections and privacy in sensitive applications like military or healthcare operating over public 5G infrastructure. The reliance on such personal identifiers threatens a user’s right to privacy and brings to light the importance of proper mechanisms to mitigate these risks for current and future cellular network technologies. In this paper, we explore the 5G specifications to understand the most important list of identifiers and their use across Virtual Network Functions (VNF), and points of exposure within the Core Network (CN). We also examine the existing literature regarding identity protections and efforts to mitigate privacy concerns targeted in the CN. Findings include the need for a trust relationship between users and their network providers to protect and safeguard their identity. While 5G technology has greater user identity protections compared to previous cellular generations, our analysis shows that several areas of concern remain, particularly in the exchange of subscriber metadata. This work also finds that new technologies adopted in 5G networks add further complexity to maintaining a strict posture for safeguarding user identity and privacy protections. This paper also reviews the scientific community’s proposed enhancements for future 6G networks’ user identity and privacy protections, with a focus on emerging Artificial Intelligence (AI) and Machine Learning (ML) applications. The ethical implications of private or anonymous communications are also carefully weighed and examined to understand the multifaceted nature of this topic. Our work is concluded by proposing important further research to reduce the prevalence and reliance on personal identifiers such as the SUPI (Subscription Permanent Identifier) within 5G Core operations to help better protect user identity. We also propose replacing the widespread use of the SUPI between VNFs with ephemeral identifiers, building upon efforts by 3GPP aiming for 5G to protect the SUPI from eavesdroppers. Full article

This study examines the feasibility of using financial ratios and non-financial variables to predict audit opinions (qualified or unqualified) for firms listed on the Athens Exchange (ATHEX) from 2018 to 2022. Using 450 firm-year observations from 90 non-financial firms, we applied a logit regression model to analyze the relationship between 11 financial ratios and non-financial factors, such as auditor quality, auditor turnover, and corporate performance. While the results indicate that auditor characteristics, particularly auditor quality, have significant explanatory power, the predictive strength of financial ratios varies, suggesting that audit opinions in Greece may be influenced by broader governance and institutional factors rather than financial indicators alone. The study provides empirical insights that contribute to the development of predictive models for audit opinion assessment. These findings are particularly relevant in emerging economies like Greece, where audit risk and firm failures are heightened due to economic and regulatory challenges. By identifying key determinants of audit opinions, the study enhances understanding of audit risk assessment and its alignment with International Standards on Auditing (ISA 520). However, its findings are limited by the sample size and Greece’s unique regulatory environment. Future research should explore the integration of additional governance and institutional variables and assess the model’s applicability in larger and more developed markets. Full article

Background: Optimizing organ preservation techniques is imperative in the face of donor kidney shortage and high waiting list mortality. Hypothermic machine perfusion (HMP) has emerged as an effective method to improve graft function post-transplantation, particularly for deceased donor kidneys, prone to ischemia reperfusion injury (IRI). The perfusion solution includes glucose to support kidney metabolism; however, its effect on mitochondrial function remains unclear. The present study investigated the effect of glucose supplementation during 24 h of oxygenated HMP on mitochondrial function in porcine kidneys. Methods: After 30 min of warm ischemia, porcine slaughterhouse kidneys were preserved for 24 h using HMP with one of the following three solutions: the standard HMP preservation solution, University of Wisconsin machine perfusion (UW-MP) solution, which contains glucose; the solution used for static cold storage, University of Wisconsin cold storage (UW-CS) solution, which lacks glucose; or the UW-CS supplemented with 10 mmol/L glucose. Tissue and perfusate samples were collected before, during, and after perfusion for further analysis. Results: ATP production, mitochondrial respiration, and oxidative stress markers were not significantly different between groups. Glucose was released into the perfusion solution even from kidneys without exogenous glucose supplementation in the perfusate. Conclusions: These results suggest that kidney mitochondrial respiration does not depend on the presence of glucose in the HMP perfusion solution at the start of perfusion, underscoring the need for further exploration of nutrient supplementation and mitochondrial function in organ preservation strategies. Full article

Immediately following the emergency use authorizations of COVID-19 vaccines, governments around the world made these products available to their populations and later started implementing differential rules for vaccinated and unvaccinated citizens regarding mobility and access to venues and services. The Oxford COVID-19 Government Response Tracker (OxCGRT) is a time series database that reflects the extent of public health measures in each country. On the basis of the OxCGRT Containment and Health Index, we calculated a corresponding discrimination index by subtracting the daily index values for vaccinated and unvaccinated individuals. The resulting metric provides a cursory quantification of the discrimination experienced by unvaccinated individuals throughout 2021 and 2022. Patterns in the index data show a high degree of discrimination with great numeric and temporal differences between jurisdictions. Around 90% of countries in Europe and North and South America discriminated against their unvaccinated citizens at some point during the pandemic. The least amount of discrimination was found for countries in Central America and Africa. In order to move towards sustainable post-pandemic recovery and prevent discriminatory public health policies in the future, we recommend that human rights protections be expanded and the prohibition of discrimination be extended beyond a limited list of grounds. Full article

In this paper, we investigated the role of generative AI in education in academic publications extracted from Web of Science (3506 records; 2019–2024). The proposed methodology included three main streams: (1) Monthly analysis trends; top-ranking research areas, keywords and universities; frequency of keywords over time; a keyword co-occurrence map; collaboration networks; and a Sankey diagram illustrating the relationship between AI-related terms, publication years and research areas; (2) Sentiment analysis using a custom list of words, VADER and TextBlob; (3) Topic modeling using Latent Dirichlet Allocation (LDA). Terms such as “artificial intelligence” and “generative artificial intelligence” were predominant, but they diverged and evolved over time. By 2024, AI applications had branched into specialized fields, including education and educational research, computer science, engineering, psychology, medical informatics, healthcare sciences, general medicine and surgery. The sentiment analysis reveals a growing optimism in academic publications regarding generative AI in education, with a steady increase in positive sentiment from 2023 to 2024, while maintaining a predominantly neutral tone. Five main topics were derived from AI applications in education, based on an analysis of the most relevant terms extracted by LDA: (1) Gen-AI’s impact in education and research; (2) ChatGPT as a tool for university students and teachers; (3) Large language models (LLMs) and prompting in computing education; (4) Applications of ChatGPT in patient education; (5) ChatGPT’s performance in medical examinations. The research identified several emerging topics: discipline-specific application of LLMs, multimodal gen-AI, personalized learning, AI as a peer or tutor and cross-cultural and multilingual tools aimed at developing culturally relevant educational content and supporting the teaching of lesser-known languages. Further, gamification with generative AI involves designing interactive storytelling and adaptive educational games to enhance engagement and hybrid human–AI classrooms explore co-teaching dynamics, teacher–student relationships and the impact on classroom authority. Full article