Search Results (387)

This paper’s goal was to determine the state of green financing and reveal the main aspects of its regulation and influence on environmental risk management in the conditions of the growth of global uncertainty. Based on the sample that contains the top 10 countries of the world with a higher level of green economic capabilities in 2024, by the assessment for developed and developing countries in isolation, we performed regression analysis of the following: (1) Dependence of environmental costs of GDP on the volume of green investments; (2) Dependence of the volume of green investments on the application of the measures of state regulation of green finance. As a result, we proved that in developed countries, the growth of the activity of green investing in the economy leads to a reduction in the environmental costs of GDP, and in developing countries, an increase in the environmental costs of GDP. Unlike developed countries, in which green investments are not determined by the influence of the factors of state regulation, the implementation of the measures of state regulation of green finance in developing countries ensures the inflow of green investments into the economy. This paper’s novelty, compared to the existing literature, is that it discloses previously unknown differences in the character of the influence of the factors of state regulation of green finance on green investments in the economy and differences in the consequences of the activity of investing for environmental risks in different categories of countries (in particular, differences between developed and developing countries) and at different phases of the economic cycle (in the conditions of relative stability and in the conditions of global instability). The established regularities of the development of green finance under the influence of state regulation measures in developed and developing countries will raise the precision of forecasting and planning of this development in support of green economic growth and decarbonization. The revealed differences between developed and developing countries will allow forming a strategy of development of green finance in each category of countries, given their specifics, and thus, achieving the growth of these strategies’ effectiveness. The proposed policy implications for the reduction in environmental risks through the improvement of state regulation of green finance in developed and developing countries, given their revealed specifics, have practical significance. Full article

Cultured meat is an emerging innovation with the potential to contribute to sustainable animal production by reducing the environmental and ethical challenges associated with conventional animal farming. In Romania, this new source of protein is viewed with both interest and scepticism, reflecting broader consumer uncertainties about food innovations. Market data indicates that Romania faces a significant deficit in animal protein supply (exceeding 65% for pork, as well as notable deficits in fish and beef), while also recording one of the largest overall trade deficits in pet food. In this context, the present study explored the openness of respondents in northeastern Romania to the consumption of cultivated meat, taking into account both personal diet and pet nutrition. The results showed that 33.2% of participants were fully willing to feed their pets cultured meat products, and 70% supported its introduction to the market, provided that regulatory frameworks ensure product safety and quality. Although Romania does not currently have the legal and technological infrastructure necessary to integrate cultured meat into the food system, these findings highlight the potential role of consumer acceptance in shaping future nutritional strategies aimed at sustainable, high-quality protein alternatives for humans and pets alike. Full article

Supply chain financing offers advantages over traditional channels such as bank loans and equity financing, including greater flexibility, lower transaction costs, and simplified approval procedures. However, when a firm’s sustainability faces uncertainty, access to supply chain financing may become constrained by multiple factors, including the risk tolerance of supply chain partners, market transparency, and corporate reputation. ESG, representing Environmental, Social, and Governance standards, is a critical framework for assessing corporate sustainability performance. Given that divergent ESG evaluations reflect disparate market assessments of a firm’s sustainable development capabilities, such divergence may affect supply chain financing by altering stakeholder trust dynamics. This research examines A-share listed firms in China (2016–2022) and reveals that divergence in ESG evaluations significantly inhibits firms’ access to supply chain financing. Mechanism validation suggests that divergent ESG evaluations amplify informational opacity, operational risks, and negative reputation, thereby influencing supply chain partners’ risk perceptions and trust levels. Heterogeneity analysis shows that corporate governance quality, regional trust levels, and ESG awareness modulate the negative impact of divergent ESG evaluations on supply chain financing. The asymmetric effects of divergent ESG evaluations on supply chain financing are further confirmed, with distinct manifestations between upstream suppliers and downstream customers. By bridging gaps in existing research on divergent ESG evaluations and supply chain finance, this work offers regulatory guidelines, operational recommendations for firms, and investment decision frameworks. Full article

Air pollution poses major risks to public health, driving the adoption of low-cost sensor (LCS) networks for fine-grained and real-time monitoring. However, the variable accuracy of LCS data compared with reference instruments necessitates robust quality control (QC) frameworks. Over the past decade, machine learning (ML) has emerged as a powerful tool to calibrate sensors, detect anomalies, and mitigate drift in large-scale deployment. This survey reviews advances in three methodological categories: traditional ML models, deep learning architectures, and hybrid or unsupervised methods. We also examine spatiotemporal QC frameworks that exploit redundancies across time and space, as well as real-time implementations based on edge–cloud architectures. Applications include personal exposure monitoring, integration with atmospheric simulations, and support for policy decision making. Despite these achievements, several challenges remain. Traditional models are lightweight but often fail to generalize across contexts, while deep learning models achieve higher accuracy but demand large datasets and remain difficult to interpret. Spatiotemporal approaches improve robustness but face scalability constraints, and real-time systems must balance computational efficiency with accuracy. Broader adoption will also require clear standards, reliable uncertainty quantification, and sustained trust in corrected data. In summary, ML-based QC shows strong potential but is still constrained by data quality, transferability, and governance gaps. Future work should integrate physical knowledge with ML, leverage federated learning for scalability, and establish regulatory benchmarks. Addressing these challenges will enable ML-driven QC to deliver reliable, high-resolution data that directly support science-based policy and public health. Full article

The new financial standards, IFRS S1 and S2, have not only modified the way financial reporting is presented to diverse stakeholders but have also increased uncertainty. These changes make traditional valuation methods inadequate. This article proposes the development of a valuation framework using Real Options Valuation (ROV), which incorporates the disclosures required by S1 and S2 as inputs to the valuation model. The framework proposes a quarterly decision rule for deferring investments, parameters aligned with the new sustainability disclosures, and notes in the financial statements proposed as voluntary reporting. The results show that, under regulatory uncertainty and its associated implications, the deferral option is a more effective technique than the Net Present Value method. For professionals responsible for the valuation process, the proposed model serves as a practical guide for applying the ROV within the capital budgeting process. For investors, it provides an additional element of transparency through disclosure and alignment with other existing accounting standards. This work lays the groundwork for future empirical applications as companies adapt to the implementation of new accounting standards and their associated reporting. Full article

This study distinguishes between observed, uncertain, and stochastic uncertain firm growth. Observed firm growth is measured via historical growth of fixed assets scaled by growth of sales revenue. Uncertain firm growth is the volatility of unobserved (estimated error terms) firm growth. The latter is simulated using nonuniform Monte Carlo to generate stochastic uncertain firm growth. The objective of this study is to examine the relationships among the firm specific, economic, and institutional factors that affect the uncertain and stochastic uncertain growth of a firm. The sample includes the nonfinancial firms listed in the DJIA30 and NASDAQ100, covering quarterly data from 1996Q1 to 2022Q4 for 121 companies. The results reveal that (a) sales growth, profitability, cash flow, and long-term financing help reduce a firm’s uncertain growth, (b) high involvement in exporting exposes firms to higher geopolitical uncertainty, (c) institutional quality (especially political stability and regulatory quality) paradoxically contribute to uncertain firm growth. This study contributes to related studies via offering perspectives to firm managers and policy makers about the factors that help manage the uncertainties of firm growth. Full article

Mexico holds significant potential for wind energy development, owing to its strategic geographic location and extensive coastlines. This review article systematically explores the technical, environmental, and economic aspects of wind energy in five different climatic zones in Mexico, reviewing potential zones for wind energy development, with the focus on the key case studies, ongoing project, and wind power performance metrics. It also critically examines the key challenges and opportunities within Mexico’s wind energy portfolio, with a focus on social, economic, environmental, and regulatory dimensions that influence the sector’s development and long-term sustainability. The results indicate that Oaxaca leads Mexico’s onshore wind potential with a power density of 761 W/m², followed by strong resources in Tamaulipas and Baja California, where wind speeds exceed 6 m/s. For offshore wind potential, Isthmus of Tehuantepec demonstrates outstanding offshore potential, with wind power densities exceeding 1000 W/m² and wind speeds above 8 m/s. Major challenges include inconsistent or unclear governmental policies regarding renewable energy incentives, regulatory uncertainties, and social resistance from local communities concerned about environmental impacts and land use. These obstacles underline the need for integrated, transparent policies and inclusive engagement strategies to carry out the full potential of wind energy in Mexico. Full article

Background: Three-dimensional (3-D) printing paired with tissue-engineering strategies promises to overcome the volume, contour, and donor-site limitations of traditional breast reconstruction. Patient-specific, bioabsorbable constructs could enable one-stage procedures that better restore aesthetics and sensation. Methods: A narrative review was conducted following a targeted PubMed search (inception—April 2025) using combinations of “breast reconstruction,” “tissue engineering,” “3-D printing,” and “scaffold.” Pre-clinical and clinical studies describing polymer-based chambers or scaffolds for breast mound or nipple regeneration were eligible. Data was extracted on scaffold composition, animal/human model, follow-up, and volumetric or histological outcomes. Results: Forty-three publications met inclusion criteria: 35 pre-clinical, six early-phase clinical, and two device reports. The predominant strategy (68% of studies) combined a vascularized fat flap with a custom 3-D-printed chamber to guide adipose expansion. Poly-lactic acid, poly-glyceric acid, poly-lactic-co-glycolic acid, poly-4-hydroxybutyrate, polycarbonate, and polycaprolactone were the principal polymers investigated; only poly-4-hydroxybutyrate and poly-lactic acid have been tested for nipple scaffolds. Bioabsorbable devices supported up to 140% volume gain in large-animal models, but even the best human series (≤18 months) achieved sub-mastectomy volumes and reported high seroma rates. Mechanical testing showed elastic moduli (5–80 MPa) compatible with native breast tissue, yet long-term load-bearing data are scarce. Conclusions: Current evidence demonstrates biocompatibility and incremental adipose regeneration, but clinical translation is constrained by small sample sizes, incomplete resorption profiles, and regulatory uncertainty. Standardized large-animal protocols, head-to-head polymer comparisons, and early human feasibility trials with validated outcome measures are essential next steps. Nevertheless, the convergence of 3-D printing and tissue engineering represents a paradigm shift that could ultimately enable bespoke, single-stage breast reconstruction with superior aesthetic and functional outcomes. Full article

Hernia repair is among the most frequent procedures in general surgery, traditionally performed with synthetic meshes such as polypropylene. While effective in reducing recurrence, these materials are biologically inert and often trigger chronic inflammation, fibrosis, pain, and impaired abdominal wall function, with a significant impact on long-term quality of life. A comprehensive literature search was conducted in PubMed, Web of Science, and Scopus databases, and relevant preclinical, clinical, and review articles were synthesized within a narrative review framework. Recent advances in tissue engineering propose a shift from passive reinforcement to regenerative strategies based on biomimetic scaffolds, nanomaterials, and nanocomposites that replicate the extracellular matrix, enhance cell integration, and provide controlled drug delivery. Nanotechnology enables localized release of anti-inflammatory, antimicrobial, and pro-angiogenic agents, while electrospun nanofibers and composite scaffolds improve strength and elasticity. In parallel, 3D printing allows for patient-specific implants with tailored architecture and regenerative potential. Although preclinical studies show encouraging results, clinical translation remains limited by cost, regulatory constraints, and long-term safety uncertainties. Overall, these innovations highlight a transition toward personalized and regenerative hernia repair, aiming to improve durability, function, and patient quality of life. Full article

The integration of renewable energy into the grid has led to problems such as low utilization rate of energy storage resources (“underutilization after construction”) and insufficient system stability. This paper studied the co-evolution mechanism of power market entities empowered by shared energy storage. Based on the interaction among power generation enterprises, power grid operators, and government regulatory agencies, this paper constructed a three-party evolutionary game model. The model introduced a dynamic reward and punishment mechanism as well as a random interference mechanism, which makes it more in line with the actual situation. The stability conditions of the game players were analyzed by using stochastic differential equations, and the influences of key parameters and incentive mechanisms on the stability of the game players were investigated through numerical simulation. The main research results showed the following: (1) The benefits of shared energy storage and opportunistic gains had a significant impact on the strategic choices of power generation companies and grid operators. (2) The regulatory efficiency had significantly promoted the long-term stable maintenance of the system. (3) Dynamic incentives were superior to static incentives in promoting cooperation, while the deterrent effect of static penalties is stronger than that of dynamic penalties. (4) The increase in the intensity of random disturbances led to strategy oscillation. This study suggested that the government implement gradient-based dynamic incentives, maintain strict static penalties to curb opportunism, and enhance regulatory robustness against uncertainty. This research provided theoretical and practical inspirations for optimizing energy storage incentive policies and promoting multi-subject coordination in the power market. Full article

Background: The incorporation of biosensors into orthopedic implants, particularly tibial components in total knee arthroplasty (TKA), marks a new era in personalized joint replacement. These smart systems aim to provide real-time physiological and mechanical data, enabling dynamic postoperative monitoring and enhanced surgical precision. Objective: This narrative review synthesizes the current landscape of electrochemical biosensor-embedded tibial implants in TKA, exploring technical mechanisms, clinical applications, challenges, and future directions for translation into clinical practice. Methods: A comprehensive literature review was conducted across PubMed and Google Scholar. Articles were thematically categorized into technology design, integration strategies, preclinical and clinical evidence, regulatory frameworks, ethical considerations, and strategic recommendations. Findings were synthesized narratively and organized to support forward-looking system design. Results: Smart tibial implants have demonstrated feasibility in both bench and early clinical settings. Key advances include pressure-sensing intraoperative tools, inertial measurement units for remote gait tracking, and chemical biosensors for infection surveillance. However, the field remains limited by biological encapsulation, signal degradation, regulatory uncertainty, and data privacy challenges. Interdisciplinary design, standardized testing, translational funding, and ethical oversight are essential to scaling these innovations. Conclusions: Biosensor-enabled tibial components represent a promising convergence of orthopedics, electronics, and data science. By addressing the technological, biological, regulatory, and ethical gaps outlined herein, this field can transition from prototype to widespread clinical reality—offering new precision in arthroplasty care. Full article

Open-source generative AI technologies offer transparent and customizable alternatives to proprietary AI systems, the concept of which closely aligns with the principles of open innovation. Organizations with strong open-source orientations may have greater absorptive capacity to adopt open-source generative AI technologies. However, adopting such technologies into the organizations is not always guaranteed because ethical, privacy, and regulatory concerns on open-source generative AI usage create normative uncertainty that can reduce organizations’ willingness to adopt the technology, particularly when it is used in customer-facing products or services rather than integrated into internal processes. This study draws on organizational learning theory and open innovation literature to examine how open-source orientation affects open-source generative AI adoption under normative uncertainty, and how this relationship depends on organizational exploiting and exploring behaviors. Using global survey data from the Linux Foundation, we test our hypotheses with ordered logistic regression and interaction effects. The results show that open-source oriented organizations are more likely to adopt open-source generative AI, but this effect weakens when normative uncertainty is high, especially in product-related use cases. These findings extend absorptive capacity theory by highlighting ethical ambiguity as a key moderating factor and provide practical insights into how organizations can responsibly approach open-source generative AI adoption. Full article

Premature infants are an especially vulnerable group that often needs extended intensive care. Prematurity naturally hampers the development of the immune system, significantly increasing the risk of infections. In the Neonatal Intensive Care Unit (NICU), antibiotic treatment is often a crucial, life-saving measure. For parents, the birth of a very preterm infant (before 32 weeks of gestation) turns what should be a happy event into a period filled with deep uncertainty and distress. Maintaining hope amid these difficulties relies heavily on maintaining regular communication with and trusting the medical team. Clinical realities in the NICU include a high risk of infection that requires multiple medications, including antibiotics. There is an inverse relationship between gestational age and pharmaceutical exposure. Parents worry about the amount of medication their child receives and the potential long-term effects on development. Over the past thirty years, initiatives such as antimicrobial stewardship programs have worked to reduce antibiotic use and treatment duration in the NICU, emphasizing proper care for premature infants worldwide. This article examines the ethical landscape from the perspectives of three primary stakeholders: parents, healthcare providers, and regulatory bodies. The key ethical question is whether these groups achieve meaningful cooperation or if institutional and professional priorities overshadow clinical practice. In the NICU, decision-making responsibility mainly lies with the medical team, as parents often have limited influence over treatment decisions, and regulatory oversight usually occurs indirectly. This concentration of authority underscores the complex and critical nature of neonatal intensive care. Full article

Controlling air pollution from sea-going vessels is crucial to the sustainable development of maritime transportation. However, emissions of intermediate volatility organic compounds (IVOCs), an emerging aerosol precursor, remain poorly understood. This study developed a ship-type-, fuel-, and operating-mode-specific IVOC emission factor dataset based on existing real-world vessel measurements, and a ship-call-based IVOC inventory methodology tailored for regulatory applications. We quantified IVOC emissions from sea-going ships (excluding fishing and military vessels) entering or departing from the ports in the Economic Zone on the West Coast of the Taiwan Straits in 2014. The total IVOC emissions were 481.4 ± 220.0 t, with Xiamen Port contributing the highest share. Cargo and passenger ships accounted for 65% and 21% of emissions, respectively. While switching to low-sulfur and ultra-low-sulfur fuels increased IVOC emissions by 87% and 49% compared to high-sulfur fuels, the greater reductions in particulate matter and SO₂ emissions still yielded net environmental benefits. The ship IVOC emissions might have become more important in recent years due to enhanced port activity and fuel switching. Uncertainty analysis emphasizes the urgent need for IVOC emission testing on more vessel types. By providing a high-resolution profile of IVOC emissions from selected ports, this study underscores the urgency of adopting shore power and zero-emission vessels to mitigate organic aerosol pollution and offers a foundation for refining environmental impact assessments and efficient emission control policies to achieve sustainability in maritime transportation. Full article

Understanding generational differences in herding behavior is crucial for policymakers, financial educators, and market regulators, particularly in emerging markets where retail investor participation is rapidly growing. This study investigates the influence of herding behavior on investment decision-making among Generations X, Y, and Z in Indonesia, as well as the moderating role of investment experience. Using a multi-group structural equation modeling (SEM) approach with data from 1293 retail investors, the research compares behavioral tendencies across cohorts. Results reveal that herding behavior has a positive and significant impact on investment decision-making in all generations, with the strongest effect observed in Generation X, followed by Generation Z and Generation Y. Investment experience significantly weakens herding behavior’s influence for Generation X but shows no significant moderating effect for Generations Y and Z, suggesting that psychological and social influences, particularly from digital platforms, may outweigh experiential learning in younger cohorts. These findings align with behavioral finance theory, which explains herding as a cognitive and emotional bias heightened by market uncertainty. The results provide practical implications for designing targeted financial education programs and regulatory measures to promote independent decision-making and reduce susceptibility to biased market information, especially among younger generations in digitally driven investment environments. Full article