Search Results (208)

Background and Clinical Significance: Osteonevus of Nanta is a rare histological phenomenon characterized by bone formation within a benign melanocytic nevus, most commonly in intradermal nevi of the head and neck. Although osteonevus of Nanta is rare, ossification in a cellular blue nevus is even more uncommon. To date, only one case of a cellular blue nevus with ossification has been documented. This case report adds to the limited literature and emphasizes the clinical importance of recognizing this rare phenomenon, as osteonevus of Nanta has been potentially associated with malignant melanoma. Case Presentation: A 72-year-old woman presented with an asymptomatic, pigmented scalp lesion that had recently increased in size. On clinical examination, the tumor appeared as a well-demarcated, firm, and nodular mass with dark blueish to violet pigmentation that measured 15 × 12 × 7 mm. To ensure a definitive diagnosis and rule out malignancy, the lesion was excised with narrow margins. Histological examination revealed a cellular blue nevus with prominent osseous metaplasia. Due to the absence of clear margins, a wider re-excision was performed. No residual tumor was found, and the patient remained asymptomatic with no recurrence. Conclusions: This case represents only the second published example of a cellular blue nevus with ossification. While osteonevus of Nanta is benign, its potential association with malignant melanoma, as well as its clinical resemblance to malignant entities such as nodular melanoma, malignant blue nevus, and pigmented basal cell carcinoma, underscores the need for thorough clinical and histopathologic evaluation. Full article

This study investigates the predictive performance of financial indicators in forecasting stock prices within the automotive sector using an adaptive neuro-fuzzy inference system (ANFIS). In light of the growing complexity of global financial markets and the increasing demand for automated, data-driven forecasting models, this research aims to identify those financial ratios that most accurately reflect price dynamics in this specific industry. The model incorporates four widely used financial indicators, return on assets (ROA), return on equity (ROE), earnings per share (EPS), and profit margin (PM), as inputs. The analysis is based on real financial and market data from automotive companies, and model performance was assessed using RMSE, nRMSE, and confidence intervals. The results indicate that the full model, including all four indicators, achieved the highest accuracy and prediction stability, while the exclusion of ROA or ROE significantly deteriorated model performance. These findings challenge the weak-form efficiency hypothesis and underscore the relevance of firm-level fundamentals in stock price formation. This study’s sector-specific approach highlights the importance of tailoring predictive models to industry characteristics, offering implications for both financial modeling and investment strategies. Future research directions include expanding the indicator set, increasing the sample size, and testing the model across additional industry domains. Full article

This article investigates the macroeconomic and labor market conditions that shape the adoption of artificial intelligence (AI) technologies among large firms in Europe. Based on panel data econometrics and supervised machine learning techniques, we estimate how public health spending, access to credit, export activity, gross capital formation, inflation, openness to trade, and labor market structure influence the share of firms that adopt at least one AI technology. The research covers all 28 EU members between 2018 and 2023. We employ a set of robustness checks using a combination of fixed-effects, random-effects, and dynamic panel data specifications supported by Clustering and supervised learning techniques. We find that AI adoption is linked to higher GDP per capita, healthcare spending, inflation, and openness to trade but lower levels of credit, exports, and capital formation. Labor markets with higher proportions of salaried work, service occupations, and self-employment are linked to AI diffusion, while unemployment and vulnerable work are detractors. Cluster analysis identifies groups of EU members with similar adoption patterns that are usually underpinned by stronger economic and institutional fundamentals. The results collectively suggest that AI diffusion is shaped not only by technological preparedness and capabilities to invest but by inclusive macroeconomic conditions and equitable labor institutions. Targeted policy measures can accelerate the equitable adoption of AI technologies within the European industrial economy. Full article

China’s national strategies emphasize both achieving carbon peaking and neutrality (“dual carbon” objectives) and fostering high-quality economic development. This dual focus highlights the critical importance of the Green and Low-Carbon Transition (GLCT) of the economy and the development of New Quality Productive Forces (NQPF). Firms are central actors in this transformation, prompting the core research question: How does corporate engagement in GLCT contribute to the formation of NQPF? We investigate this relationship using panel data comprising 33,768 firm-year observations for A-share listed companies across diverse industries in China from 2012 to 2022. Corporate GLCT is measured via textual analysis of annual reports, while an NQPF index, incorporating both tangible and intangible dimensions, is constructed using the entropy method. Our empirical analysis relies primarily on fixed-effects regressions, supplemented by various robustness checks and alternative econometric specifications. The results demonstrate a significantly positive relationship: corporate GLCT robustly promotes the development of NQPF, with dynamic lag structures suggesting delayed productivity realization. Mechanism analysis reveals that this effect operates through three primary channels: improved access to financing, stimulated collaborative innovation and enhanced resource-allocation efficiency. Heterogeneity analysis indicates that the positive impact of GLCT on NQPF is more pronounced for state-owned enterprises (SOEs), firms operating in high-emission sectors, those in energy-efficient or environmentally friendly industries, technology-intensive sectors, non-heavily polluting industries and companies situated in China’s eastern regions. Overall, our findings suggest that corporate GLCT enhances NQPF by improving resource-utilization efficiency and fostering innovation, with these effects amplified by specific regional advantages and firm characteristics. This study offers implications for corporate strategy, highlighting how aligning GLCT initiatives with core business objectives can drive NQPF, and provides evidence relevant for policymakers aiming to optimize environmental governance and foster sustainable economic pathways. Full article

Background/Objectives: Platelet transfusions are administered to preterm neonates with thrombocytopenia prophylactically to decrease their bleeding risk. The amplitude difference between the extrinsic rotational thromboelastometry (EXTEM) and the fibrinogen rotational thromboelastometry (FIBTEM) assays is considered an index of platelet contribution to clot strength, guiding transfusion management. The difference in maximum clot elasticity (MCE) (namely the platelet contribution to clot elasticity—MCEplatelet) is considered highly accurate. Limited data exist to specify the contribution of platelets and fibrinogen in clot formation during sepsis in neonates with thrombocytopenia. We investigated the potential of MCFplatelet (platelet contribution to clot firmness) and MCEplatelet in reflecting platelet count and function in septic preterm neonates. We simultaneously assessed the contribution of both platelets and fibrinogen to clot strength during sepsis. Methods: We compared 28 preterm neonates with sepsis born (gestational age 24⁺¹-34⁺³) with 30 healthy counterparts by using rotational thromboelastometry (ROTEM) and platelet flow cytometry. Results: MCEplatelet showed a higher association with platelet count in the sepsis group than MCFplatelet (R² = 47.66% vs. R² = 18.79%). MCEplatelet (AUC = 0.81) had better discrimination capability than MCFplatelet (AUC = 0.78) in platelet count <100 × 10³/L. MCEplatelet was poorly associated with platelet function. The contribution of platelets was significantly lower (MCEplatelet = 84.03 vs. 89.21; p < 0.001) compared with fibrinogen (36.9 vs. 25.92; p < 0.001) in the sepsis group. Conclusions: MCEplatelet has a better predictive value than MCFplatelet. In clinical practice, the elasticity difference between EXTEM and FIBTEM may replace the amplitude difference. The higher contribution of fibrinogen in clot strength during neonatal sepsis results in higher MCF, even in neonates with thrombocytopenia. Full article

A Cournot triopoly is a type of oligopoly market involving three firms that produce and sell homogeneous or similar products without cooperating with one another. In Cournot models, firms’ decisions about production levels play a crucial role in determining overall market output. Compared to duopoly models, oligopolies with more than two firms have received relatively less attention in the literature. Nevertheless, triopoly models are more reflective of real-world market conditions, even though analyzing their dynamics remains a complex challenge. A reaction–diffusion system of PDEs generalizing a nonlinear triopoly model describing a master–slave Cournot game is introduced. The effect of diffusion on the stability of Nash equilibrium is investigated. Self-diffusion alone cannot induce Turing pattern formation. In fact, linear stability analysis shows that cross-diffusion is the key mechanism for the formation of spatial patterns. The conditions for the onset of cross-diffusion-driven instability are obtained via linear stability analysis, and the formation of several Turing patterns is investigated through numerical simulations. Full article

Firmware vulnerabilities in embedded devices have caused serious security incidents, necessitating similarity analysis of binary program instruction embeddings to identify vulnerabilities. However, existing instruction embedding methods neglect program execution semantics, resulting in accuracy limitations. Furthermore, current embedding approaches utilize independent computation across models, where the lack of standardized interaction information between models makes it difficult for embedding models to efficiently detect firmware vulnerabilities. To address these challenges, this paper proposes a firmware vulnerability detection scheme based on statistical inference and code similarity fuzzy matching analysis for resource-constrained vehicular network environments, helping to balance both accuracy and efficiency. First, through dynamic programming and neighborhood search techniques, binary code is systematically partitioned into normalized segment collections according to specific rules. The binary code is then analyzed in segments to construct semantic equivalence mappings, thereby extracting similarity metrics for function execution semantics. Subsequently, Google Protocol Buffers (ProtoBuf) is introduced as a serialization format for inter-model data transmission, serving as a “translation layer” and “bridging technology” within the firmware vulnerability detection framework. Additionally, a ProtoBuf-based certificate authentication scheme is proposed to enhance vehicular network communication reliability, improve data serialization efficiency, and increase the efficiency and accuracy of the detection model. Finally, a vehicular network simulation environment is established through secondary development on the NS-3 network simulator, and the functionality and performance of this architecture were thoroughly tested. Results demonstrate that the algorithm possesses resistance capabilities against common security threats while minimizing performance impact. Experimental results show that FirmPB delivers superior accuracy with 0.044 s inference time and 0.932 AUC, outperforming current SOTA in detection performance. Full article

This paper investigates sustainable decision systems within green E-business models by analyzing how different O2O (online-to-offline) fulfillment structures affect emission-reduction efforts and pricing strategies in a two-tier supply chain consisting of a manufacturer and a new retailer. Three practical sales formats—package self-pickup, nearby delivery, and hybrid—are modeled using Stackelberg game frameworks that incorporate key factors such as inconvenience cost, logistics cost, processing fees, and emission-reduction coefficients. Results show that the manufacturer’s emission-reduction decisions and both parties’ pricing strategies are highly sensitive to cost conditions and consumer preferences. Specifically, higher inconvenience and abatement costs consistently reduce profitability and emission efforts; the hybrid model exhibits threshold-dependent advantages over single-mode strategies in terms of carbon efficiency and economic returns; and consumer green preference and distance sensitivity jointly shape optimal channel configurations. Robustness analysis confirms the model’s stability under varying parameter conditions. These insights provide theoretical and practical guidance for firms seeking to develop adaptive, low-carbon fulfillment strategies that align with sustainability goals and market demands. Full article

This paper examined whether regional differences in Poland affect the use of various tools for supporting local entrepreneurship. It also verified whether there is a universal set of tools that accounts for the level at which local entrepreneurship support tools are used by municipalities. This study was based on a survey conducted among 882 Polish municipalities. Analyses were carried out using classical measures of descriptive statistics, supplemented by the Mann–Whitney U test and Kruskal–Wallis rank. The results reveal that the likelihood of municipalities with a local spatial development plan (LSDP) use more support instruments is statistically significant. For municipalities, having an LSDP also correlates with higher levels of local entrepreneurship. Moreover, the presence of an LSDP contributes not only to increased local entrepreneurship, but also aligns with long-term, sustainable, spatial and economic development goals. It was concluded that municipalities should be encouraged to create comprehensive development plans and, above all, to develop and implement local spatial development plans. Local decision-makers should must be made aware of the role of the plan and its importance for the level of entrepreneurship in the area. More attention should also be focused on the use of tools aimed at direct cooperation with entrepreneurs. Full article

In the context of increasing consumer demand for high-quality, residue-free fruits and the growing emphasis on sustainable postharvest technologies, identifying effective, eco-friendly treatments to maintain grape quality during storage has become a critical focus in modern viticulture. Over the course of this study, we examined the influence of seaweed extract (derived from Ascophyllum nodosum) and ethanol-based postharvest treatments on the postharvest quality of the ‘Tarsus Beyazı’ grape. The seaweed extract was applied at six specific phenological stages according to the BBCH scale: BBCH 13 (3rd–4th leaf stage, 0.40%), BBCH 60 (first flower sheath opening, 0.50%), BBCH 71 (fruit set, 0.50%), BBCH 75 (chickpea-sized berries, 0.50%), BBCH 81 (start of ripening, 0.60%), and BBCH 89 (harvest maturity, 0.60%). After harvest, grape clusters were subjected to four different postharvest treatments: untreated control, control + ethanol (20% ethanol immersion for 10 s), seaweed extract alone (preharvest applications only), and seaweed extract + ethanol (combining both preharvest and postharvest treatments). Grapes were stored at 0–1 °C and 90–95% RH for three weeks, followed by a shelf-life evaluation period of three days at 20 °C and 60–65% RH. The findings revealed that seaweed treatments, especially when applied during cluster formation and berry development, effectively mitigated physiological deterioration, preserving stem turgidity and enhancing berry firmness. In contrast, ethanol showed variable responses, occasionally exerting negative effects, with only marginal benefits observed when applied at optimal developmental stages. Both the type and timing of application emerged as critical determinants of key quality attributes such as weight loss, decay incidence, and must properties (TSS, pH, TA). Correlation and heat map analyses indicated the interrelationships among these parameters and the differential impacts of treatments. These results suggest that phenological-stage-specific seaweed applications hold significant potential as a sustainable strategy to extend the storage life and maintain the market quality of ‘Tarsus Beyazı’ grapes. Full article

Considering the rapid increase in mobile payment usage, numerous big tech companies have added mobile payment to the primary services that their platforms offer. However, extant research predominantly treats this added service as a standalone offering and investigates user adoption and behavior for this service independent of the primary services. Recognizing this gap in the literature, this study considers the added service as part of an extended ecosystem and examines different motivations for using the primary service. Therefore, this study examines how different motivations for using social networking services (SNSs) shape trust in the extended payment service and ultimately influence behavioral intentions. Drawing on the schema congruity theory, we conceptualize trust as a multidimensional construct—distinguished between cognitive and emotional trust—and explore the impact of trust in the primary service on the use of an added service. Specifically, we analyze survey data of 478 users of South Korea’s leading SNS. The results reveal that both hedonic and utilitarian motivations positively influence emotional and cognitive trust, which, in turn, drive behavioral intention. However, hedonic (utilitarian) motivation exerts a stronger effect on emotional (cognitive) trust. Overall, the findings enhance the knowledge regarding trust formation in extended service ecosystems and offer insights for tech firms integrating financial services into their platforms. Full article

Environmental variability modifies forest structure through interactions among soil properties, topography, and climate. These factors influence the occurrence of contrasting forest types in northern Amazonia (Brazil), such as forests in highlands (Terra Firme) and forests under regular flooding (Várzea). Flooding regimes influence soil formation and modify soil geochemistry, nutrient distribution, and organic matter accumulation, shaping forest structure and composition. The objective was to determine the relationships between structure and soil characteristics in non-flooded and flooded tropical forests. We compared forest structure and soil characteristics at both conditions (n = 2 treatments × 20 replicas = 40 plots) using univariate and multivariate analyses. We found significant differences in most of the studied variables between forest types, both chemical and physical properties. Our results showed that flooding defines forest structure and composition (e.g., tree density, height, and volume) and influences soil nutrient characteristics. Floodplain forests exhibited higher soil nutrient concentration and organic carbon content, likely due to periodic litter accumulation, sediments, and reduced decomposition rates. In contrast, non-flooded forests were characterized by lower nutrient levels, higher sand content, and greater forest structure values (e.g., height, basal area, and volume). These insights contribute to understanding the functioning of both forest ecosystems. Full article

Managing risk, matching resources efficiently, and ensuring fair allocation are fundamental challenges in both finance and decision-making processes. In many scenarios, participants contribute unequally to collective outcomes, raising the question of how to distribute costs, benefits, or opportunities in a justifiable and optimal manner. This paper applies the Shapley value—a solution concept from cooperative game theory—as a principled tool in the following two specific financial settings: first, in tax cooperation games; and second, in assignment markets. In tax cooperation games, we use the Shapley value to determine the equitable tax burden distribution among three firms, A, B, and C, which operate in two countries, Italy and Poland. Our model ensures that countries participating in coalitions face a lower degree of tax evasion compared to non-members, and that cooperating firms benefit from discounted tax liabilities. This structure incentivizes coalition formation and reveals the economic advantage of joint participation. In assignment markets, we use the Shapley value to find the optimal pairing in a four-buyers and four-sellers housing market. Our findings show that the Shapley value provides a rigorous framework for capturing the relative importance of participants in the coalition, leading to more balanced tax allocations and fairer market transactions. Our theoretical insights with computational techniques highlights the Shapley value’s effectiveness in addressing complex allocation challenges across financial management domains. Full article

The present study focuses on how various firm characteristics influence their dividend payout policies. The study finds empirical evidence with regard to primarily two aspects of corporate dividend decisions—dividend increase and decrease, whose exploration is inadequate in the past literature. The random effect logistic regression has been considered in order to analyze the panel dataset from 2001–2002 to 2021–2022 including 3739 listed Indian firms. The empirical models are formatted based on the relevant dividend-related theories in the Indian context such as the residual theory, transaction cost theory, signalling theory, etc. Further, additional tests are conducted regarding the robustness of the reported results. The empirical results document that firm size, profitability, promoter holdings, cash holdings, and life cycle have a favourable influence on the propensity of both increasing and decreasing dividend payouts. In contrast, earnings volatility, leverage, and free cash flow reduce firms’ tendency to increase and decrease dividend payments. These results indicate that higher liquidity and ownership concentration provide firms with greater financial flexibility to adjust their dividend policies as per their prevailing opportunities. The findings of the study offer insightful information about how to arrange dividend policies with firm-specific traits which will be helpful for managers and investors to make better decisions. Full article

The COVID-19 pandemic not only caused considerable disruptions in the capital markets, but also threatened firm sustainability. There are quite a few proxies that can measure a company’s sustainability, but information asymmetry is a representative one. Hence, we use information asymmetry to analyze whether the disruptions caused by changes in the corporate environment during the COVID-19 pandemic fostered significant differences in the sustainability of firms. The findings reveal the following: First, in the full sample, information asymmetry significantly increased during the pandemic. This suggests that the pandemic may have led to capital market disruptions, and thus, low sustainability of firms. Second, analyzing industry variations in information asymmetry during the pandemic reveals that information asymmetry does not significantly increase in the pharmaceutical and information technology industries. In contrast, it significantly increases in the samples belonging to the manufacturing and construction industries. This study provides the empirical evidence of the effects of COVID-19 on company’s sustainability. Based on this study, it should focus on finding way to reduce in-formation asymmetry in the capital market to increase the sustainability of firms in the long run. Full article