Search Results (234)

Although carbon emissions trading systems are universally acknowledged as one of the most potent policy instruments for counteracting hazardous climate trends, and digitalization is seen as a favorable technological means to promote corporate green and low-carbon transformation, few studies have investigated the dark side of both. Using data on Chinese listed companies from 2011 to 2020 and adopting a multi-period DID methodology, this research reveals that, in response to the carbon emissions trading system, firms often adopt low-cost, strategic environmental governance behaviors—namely, carbon washing—to reduce compliance costs and maintain their reputation and image. Furthermore, the study reveals that the information advantages of digital transformation create conditions for the opportunistic manipulation of carbon disclosure. Digitalization amplifies the positive influence of the carbon trading system on corporate carbon washing behavior. Mechanism analysis confirms that the carbon emissions trading system increases the production costs of regulated firms, thereby increasing their carbon washing behavior. Economic consequence analysis confirms that firms engage in carbon washing to gain legitimacy and maintain their reputation and image, which may allow them to obtain opportunistic benefits in the capital market. Finally, this study suggests that the government should adopt supplementary policy tools, such as environmental subsidies, enhanced use of digital technologies to strengthen regulatory capacity, and increased media oversight, to mitigate the unintended consequences of the carbon trading system on corporate behavior. Full article

Yeast genetic improvement is entering a transformative phase, driven by the integration of artificial intelligence (AI), big data analytics, and synthetic microbial communities with conventional methods such as sexual breeding and random mutagenesis. These advancements have substantially expanded the potential for innovative re-engineering of yeast, ranging from single-strain cultures to complex polymicrobial consortia. This review compares traditional genetic manipulation techniques with cutting-edge approaches, highlighting recent breakthroughs in their application to beer and wine fermentation. Among the innovative strategies, adaptive laboratory evolution (ALE) stands out as a non-GMO method capable of rewiring complex fitness-related phenotypes through iterative selection. In contrast, GMO-based synthetic biology approaches, including the most recent developments in CRISPR/Cas9 technologies, enable efficient and scalable genome editing, including multiplexed modifications. These innovations are expected to accelerate product development, reduce costs, and enhance the environmental sustainability of brewing and winemaking. However, despite their technological potential, GMO-based strategies continue to face significant regulatory and market challenges, which limit their widespread adoption in the fermentation industry. Full article

Droplet microfluidics has emerged as a transformative technology that can substantially increase the throughput of antibody “hit” discovery. This review provides a comprehensive overview of the recent advances in this dynamic field, focusing primarily on the technological and methodological innovations that have enhanced the antibody discovery process. This investigation starts with the fundamental principles of droplet microfluidics, emphasizing its unique capabilities for precisely controlling and manipulating picoliter-volume droplets. This discussion extends to various assay types employed in droplet microfluidics, including binding assays, functional assays, Förster Resonance Energy Transfer (FRET) assays, internalization assays, and neutralization assays, each offering distinct advantages for antibody screening and characterization. A critical examination of methods to improve droplet encapsulation is presented, besides addressing challenges such as reducing the leakage of small molecules from droplets and explaining what a “hit” droplet looks like. Furthermore, we assess design considerations essential for implementing high-throughput fluorescence-activated droplet sorting (FADS) workstations and emphasize the need for automation. This review also delves into the evolving commercial landscape, identifying key market players and emerging industry trends. This review paper aims to catalyze further research and innovation, ultimately advancing the field towards more efficient and robust solutions for antibody identification and development. Full article

This study investigates how managers choose between alternative earnings management mechanisms among syndicated loan borrowers. Specifically, it examines the trade-off between accrual-based earnings management (AEM) and real activities manipulation (RAM) during the period leading up to syndicated loan origination. The study also explores whether lender monitoring mechanisms influence subsequent earnings management behavior. The syndicated loan market, positioned between the private and public fixed income markets, offers a distinctive context for analyzing these strategic decisions. Using a propensity score-matched sample of syndicated and bilateral loans issued between 1989 and 2005, the study finds that firms obtaining syndicated loans are more likely to engage in earnings manipulation beforehand, relying more heavily on AEM than on RAM. Further analysis reveals that monitoring mechanisms—such as lender reputation, the number of syndicate members, loan size, and loan maturity—are significantly associated with future changes in AEM but show a weaker relationship with changes in RAM. Full article

The Phalaenopsis genus, a horticulturally vital group within the Orchidaceae, dominates global floriculture markets through strategic cultivar innovation, scalable propagation, and data-driven cultivation. This review systematically examines the breeding, propagation, cultivation management, and potential applications of Phalaenopsis while providing insights into future research directions. The main contents include the following: Breeding innovations—This review outlines the taxonomy of the Phalaenopsis genus and highlights its intergeneric hybridization potential, which offers vast opportunities for developing novel horticultural varieties. By establishing clear breeding objectives, researchers employ diverse breeding strategies, including conventional crossbreeding and biotechnological approaches (e.g., mutation breeding, ploidy manipulation, genetic transformation, and CRISPR/Cas9 editing). Propagation and cultivation management—Analyses of Phalaenopsis tissue culture protocols covering explant selection, media optimization, and regeneration systems are summarized. Key factors for efficient cultivation are discussed, including temperature, light, water, nutrient management, cultivation medium selection, and integrated pest/disease management. Scientific environmental control ensures robust plant growth, synchronized flowering, and high-quality flower production. Emerging applications—Phalaenopsis exhibits promising applications in functional bioactive compound extraction (e.g., antioxidants and antimicrobial agents). This review summarizes current advancements in Phalaenopsis breeding, cultivation, and potential applications. Based on technological progress and market demands, future research directions are proposed to support the sustainable development of the Phalaenopsis industry. Full article

Fermentation is a promising food processing technique that has been used throughout history for its role in food preservation, the enhancement of nutritional content, and improvement of sensory attributes. Beyond the primary probiotic benefits, microorganisms in fermented foods play a functional role in increasing nutrient bioavailability, exhibiting antimicrobial properties, producing bioactive compounds, and removing antinutritional factors. This review explores microbial diversity and its role in the production of fermented foods across different regions of the world through a dynamic market analysis. It also highlights recent biotechnological advancements in fermentation, specifically the use of omics, multi-omics, and precision fermentation. Omics technologies have been found to provide a deeper insight into microbial diversity, deciphering their metabolic pathways and functional interactions, whereas precision fermentation is being used for the manipulation of microbial processes to optimize the fermentation process and produce the desired attributes in fermented foods. Various sustainable substrates have also been used in the production of fermented foods, apart from the conventional ones. Interestingly, this review discusses the growing role of artificial intelligence, machine learning, and the Internet of Things in food fermentation, focusing on their potential to optimize processes, predict microbial interactions, and improve quality control, supported by relevant successful examples. The review also examines the current challenges faced by the fermented food industry, offering various mitigation strategies to overcome these obstacles. Possible future prospects are also explored. Through a combination of traditional methods and modern biotechnological innovations, functional fermentation is bound to transform the global food industry. Full article

This study examines the relevance of the Fraud Pentagon Theory in detecting fraudulent financial reporting among companies listed on the Bucharest Stock Exchange. While financial reporting is essential for informed stakeholder decisions, requiring information to be accurate, reliable, and fairly presented and pressure to meet expectations can lead to manipulation. The Fraud Pentagon Theory identifies five potential drivers of such behavior: pressure, opportunity, rationalization, capability, and arrogance. This research contributes to the literature by empirically testing the theory in the Romanian context, an emerging market with limited prior analysis, using a sample of 62 listed companies over the 2017–2021 period. Regression analysis was applied, using the Dechow F-score, which combines accrual quality and financial performance to assess the likelihood of fraudulent financial reporting. The findings reveal that not all dimensions of the theory significantly affect the likelihood of fraudulent reporting. Specifically, pressure-related factors (financial performance and financial stability) were found to be statistically significant, while external pressure, opportunity (external auditor quality and nature of industry), rationalization (change of auditor), capability (change of director), and arrogance (number of CEO’s pictures) did not show significant influence in the Romanian framework. These results highlight the importance of contextual factors such as market structure, governance practices, and stakeholder expectations, suggesting that fraudulent reporting risk indicators may vary across different economic environments. Full article

This paper introduces a novel three-dimensional financial risk system that exhibits complex dynamical behaviors, including chaos, multistability, and a butterfly attractor. The proposed system is an extension of the Zhang financial risk model (ZFRM), with modifications that enhance its applicability to real-world economic stability assessments. Through numerical simulations, we confirm the system’s chaotic nature using Lyapunov exponents (LE), with values calculated as $L_1=3.5547,$ $L_2=0,$ $L_3=-22.5642$, indicating a positive Maximal Lyapunov Exponent (MLE) that confirms chaos. The Kaplan–Yorke Dimension (KYD) is determined as D_k = 2.1575, reflecting the system’s fractal characteristics. Bifurcation analysis (BA) reveals parameter ranges where transitions between periodic, chaotic, and multistable states occur. Additionally, the system demonstrates coexisting attractors, where different initial conditions lead to distinct long-term behaviors, emphasizing its sensitivity to market fluctuations. Offset Boosting Control (OBC) is implemented to manipulate the chaotic attractor, shifting its amplitude without altering the underlying system dynamics. These findings provide deeper insights into financial risk modeling and economic stability, with potential applications in financial forecasting, risk assessment, and secure economic data transmission. Full article

Gaze tracking is gaining relevance in collaborative robotics as a means to enhance human–machine interaction by enabling intuitive and non-verbal communication. This study explores the integration of human gaze into collaborative robotics by demonstrating the possibility of controlling a robotic manipulator with a practical and non-intrusive setup made up of a vision system and gaze-tracking software. After presenting a comparison between the major available systems on the market, OpenFace 2.0 was selected as the primary gaze-tracking software and integrated with a UR5 collaborative robot through a MATLAB-based control framework. Validation was conducted through real-world experiments, analyzing the effects of raw and filtered gaze data on system accuracy and responsiveness. The results indicate that gaze tracking can effectively guide robot motion, though signal processing significantly impacts responsiveness and control precision. This work establishes a foundation for future research on gaze-assisted robotic control, highlighting its potential benefits and challenges in enhancing human–robot collaboration. Full article

Using the PRISMA-ScR methodology, this scoping review systematically analyzes how EU laws and regulations influence the development, adoption, and deployment of AI-driven digital solutions in energy generation, transmission, distribution, consumption, and markets. It identifies key regulatory barriers such as stringent risk assessments, cybersecurity obligations, and data access restrictions, along with enablers like regulatory sandboxes and harmonized compliance frameworks. Legal uncertainties, including AI liability and market manipulation risks, are also examined. To provide a comparative perspective, the EU regulatory approach is contrasted with AI governance models in the United States and China, highlighting global best practices and alignment challenges. The findings indicate that while the EU’s risk-based approach to AI governance provides a robust legal foundation, cross-regulatory complexity and sector-specific ambiguities necessitate further refinement. This paper proposes key recommendations, including the integration of AI-specific energy sector guidelines, acceleration of standardization efforts, promotion of privacy-preserving AI methods, and enhancement of international cooperation on AI safety and cybersecurity. These measures will help strike a balance between fostering trustworthy AI innovation and ensuring regulatory clarity, enabling AI to accelerate the clean energy transition while maintaining security, transparency, and fairness in digital energy systems. Full article

With the growing popularity of cryptocurrencies, detecting potential market manipulation and fraudulent activities has become crucial for maintaining market integrity. In this study, we aim to detect anomalous Bitcoin transactions using an integrated approach by combining clustering techniques with statistical outlier detection. More specifically, anomalies were detected using three approaches: a distance-based method, flagging points with distances greater than the 95th percentile from their cluster centers; a statistical method, identifying transactions with any feature having an absolute Z-score greater than 3; and a hybrid approach, where transactions flagged by either method were considered anomalous. Using sample subset Bitcoin transaction data from 2015, our results showed that the combined approach was able to achieve the best performance with a total of 6492 (6.61%) detected anomalous transactions out of a total of 98,151 transactions. Full article

Firms frequently face a tradeoff between the advantages of upholding sustainability and ESG performance and the expenses associated with participating in ESG initiatives. This tension leads to an increase in greenwashing practices, which ultimately undermines genuine sustainability efforts and misleads stakeholders. Motivated by this trend, our study examines the influence of a macro-level factor, specifically local city-level governments’ GDP manipulation, on the extent of firms’ greenwashing, highlighting how government behavior can distort sustainable business practices. Using the data of the publicly traded Chinese manufacturing companies during the period of 2007–2019, we find a positive and significant relationship between the extent to which firms engage in greenwashing and the extent of local city-level governments’ GDP manipulation. Additional analysis reveals that firms’ financial constraints and external monitoring are the channels through which governments influence firms’ greenwashing. In addition, the finding of a positive association between firm greenwashing and government GDP manipulation is more pronounced in regions with a less developed marketization index, in periods before China’s anti-corruption campaign, in state-owned firms, and in firms at the business life cycle of the mature stage. Our study addresses a gap in the literature by demonstrating how government economic interventions influence firms’ sustainability performance. Full article

Ballota acetabulosa (L.) Benth. (syn. Pseudodictamnus acetabulosus (L.) Salmaki and Siadati), f. Lamiaceae, the Greek horehound, is a compact evergreen small shrub native to Greece, with hairy grey-green leaves, that bears small pink-purple flowers with green conical calyxes along its erect stems in late spring. The species stands out for its high resistance in xerothermic conditions and therefore it is advisable to promote its use in xeriscaping. The aim of this study was to develop an efficient protocol for in vitro propagation of B. acetabulosa for introduction into the horticultural and pharmaceutical industries. Shoot tip and single node explants derived from in vitro seedlings were cultured on MS medium with various cytokinin types and concentrations. Explants responded at almost 100% to produce high number of shoots on a medium with 1.0 mg L⁻¹ zeatin or 6-benzyladenine. However, there was intense hyperhydricity in the cultures, which was addressed in further experiments by increasing agar concentration from 8 to 12 g L⁻¹, preserving high multiplication indices (92% response, 10.2 shoots per explant). Microcuttings with 2–3 visible nodes, either from the apical part, including the apical meristem, or from the basal part of microshoots, as well as microshoot clusters, rooted 100% on full- or half-strength MS medium, respectively, regardless of the addition of indole-3-butyric acid (ΙΒA, 0.5–4.0 mg L⁻¹) in the rooting medium. However, middle level concentrations of IBA increased the number and length of roots produced, while the higher its concentration, the more and longer axillary shoots developed in the microcuttings during the rooting period. The acclimatization of all plantlets was completely successful (100%) in ex vitro conditions on peat/perlite substrate (1:1, v/v). Thus, efficient methods of producing propagation material to promote Ballota acetabulosa as a horticultural and medicinal plant were developed. In particular, rooting of microshoot clusters or microcuttings without the shoot tip, in the presence of 1.0 mg L⁻¹ IBA, leads to a plant of suitable shape for the floricultural market, without the need for further manipulation (pruning) in the nursery. Full article

The integration of artificial intelligence in interventional radiology is an emerging field with transformative potential, aiming to make a great contribution to the health domain. This overview of reviews seeks to identify prevailing themes, opportunities, challenges, and recommendations related to the process of integration. Utilizing a standardized checklist and quality control procedures, this review examines recent advancements in, and future implications of, this domain. In total, 27 review studies were selected through the systematic process. Based on the overview, the integration of artificial intelligence (AI) in interventional radiology (IR) presents significant opportunities to enhance precision, efficiency, and personalization of procedures. AI automates tasks like catheter manipulation and needle placement, improving accuracy and reducing variability. It also integrates multiple imaging modalities, optimizing treatment planning and outcomes. AI aids intra-procedural guidance with advanced needle tracking and real-time image fusion. Robotics and automation in IR are advancing, though full autonomy in AI-guided systems has not been achieved. Despite these advancements, the integration of AI in IR is complex, involving imaging systems, robotics, and other technologies. This complexity requires a comprehensive certification and integration process. The role of regulatory bodies, scientific societies, and clinicians is essential to address these challenges. Standardized guidelines, clinician education, and careful AI assessment are necessary for safe integration. The future of AI in IR depends on developing standardized guidelines for medical devices and AI applications. Collaboration between certifying bodies, scientific societies, and legislative entities, as seen in the EU AI Act, will be crucial to tackling AI-specific challenges. Focusing on transparency, data governance, human oversight, and post-market monitoring will ensure AI integration in IR proceeds with safeguards, benefiting patient outcomes and advancing the field. Full article

Spot Bitcoin Exchange Traded Products (ETPs) are financial instruments enabling Bitcoin to be traded on traditional brokerage platforms, reducing the risks associated with direct Bitcoin exposure while addressing fraud and market manipulation concerns. This study examines the adoption of Spot Bitcoin ETPs, emphasizing the roles of financial and digital literacy, market dynamics, and regulatory frameworks in influencing individual investor behavior. Based on a survey of 428 U.S. respondents, financial literacy and early adopter traits were found to significantly enhance adoption likelihood (β = 0.458, p < 0.001). Government factors, such as compliance guidelines and tax policies, improved investor confidence and adoption rates (β = 0.409, p < 0.001). Market factors, including volatility and sentiment, played a notable yet secondary role (β = 0.34, p < 0.001). Institutional investment mediated the effects of regulatory and market dynamics on individual adoption, legitimizing Spot Bitcoin ETPs and fostering trust (β = 0.298, p < 0.001). The findings emphasize the need for clear regulations, robust disclosure requirements, and investor education to enhance adoption. Policymakers should focus on regulatory transparency to build investor confidence, while financial institutions can advance adoption by promoting financial and digital literacy. This study contributes to understanding how individual, market, and regulatory factors collectively drive the integration of regulated cryptocurrency products into mainstream finance. Full article