Search Results (294)

With the intensification of climate change and the acceleration of the low-carbon transition, climate policy uncertainty (CPU) has become a critical external shock shaping firms’ green innovation behavior. Using a panel of Chinese A-share listed firms from 2011 to 2023, this study constructs a firm-level measure of CPU and examines its impact on firms’ green innovation boundaries and the underlying mechanisms. The results show that CPU significantly expands firms’ green innovation boundaries, and this effect is notably obvious in areas with stronger green innovation ecosystems and robust intellectual property protection. Mechanism analyses indicate that green strategic orientation and digital–green technology integration capability play significant partial mediating roles. Moreover, green finance and peer effects significantly strengthen the positive relationship between CPU and green innovation boundaries. Further analyses reveal that expanding green innovation boundaries not only enhances firms’ sustainable green innovation capability but also increases market share, thereby transforming CPU into long-term technological and competitive advantages. Full article

The design of low-emission alternative-propulsion aircraft requires multidisciplinary collaboration across distributed academic and industrial environments, challenging the applicability of conventional Multidisciplinary Design Analysis and Optimization (MDAO) frameworks. This paper presents the Holistic Collaborative MDAO Selection (HCMS) methodology, which provides a structured approach for selecting MDAO architectures based on socio-technical feasibility (intellectual property protection, disciplinary autonomy, and IT governance) and computational feasibility (coupling strength and model fidelity). The methodology supports a transition from centralized to distributed workflows while ensuring secure and efficient cross-organizational integration. The approach is demonstrated through a multi-institutional case study of a dual-fuel (hydrogen and kerosene) business jet using Remote Component Environment (RCE) and Common Parametric Aircraft Configuration Schema (CPACS). Results demonstrate that the proposed methodology enables stable and scalable distributed MDAO execution while explicitly accounting for socio-technical constraints, with consistent convergence behavior and communication overhead (approximately 25 s per iteration) remaining small relative to disciplinary computation time. The case study further illustrates the impact of hydrogen integration, showing an increase in operating empty weight of approximately 14.06% for a 600 NM mission and a reduction in kerosene capacity of approximately 12.9%, while enabling hydrogen-powered operation for the primary mission segment. These findings confirm that the proposed framework effectively supports secure, collaborative MDAO under realistic socio-technical constraints while providing meaningful system-level design insights. Full article

This research considers, by a conceptual and philosophical–legal perspective, the tensions between the interest of harmonization of intellectual property and the protection of Intangible Cultural Heritage. Starting from the fact that the harmonization of IP has been promoted as a strategy of global legal integration, normative predictability, and legal certainty for transnational economic agents, this study underpins the challenges that cross this intention. ICH is also observed as a legal category grounded on collective, dynamic, and culturally situated logics. The article briefly remarks a critical reading regarding possible conceptual incompatibilities between these regimes, showing through pensée complexe that such tensions stem from deeper divergences, associated with the predominance of a unidimensional and reductive view of the relationship between IP and ICH. Full article

This study examines how the international harmonisation of intellectual property rules, particularly trade secret protection, reshapes the governance of artificial intelligence (AI) in ways that both enable and threaten justice. We argue that convergent standards on undisclosed information are essential for legal certainty in knowledge-intensive AI investments. Such standards are anchored in TRIPS, reinforced by WIPO guidance and digital trade agreements, and complemented by regional instruments such as the EU Trade Secrets Directive. This emerging framework facilitates cross-border technological cooperation while helping prevent the “regulatory expropriation” of code, models, and data infrastructures. At the same time, when this pro-secrecy architecture is extended to opaque algorithmic systems that mediate access to credit, employment, welfare, health and justice, it can entrench digital vulnerability: information asymmetries between firms, states and citizens; barriers to meaningful transparency and audit; and pathogenic forms of exclusion that disproportionately affect already disadvantaged groups. Building on the concept of digital and structural vulnerability, the paper defends a vulnerability-sensitive approach to harmonisation in which trade secret protection is balanced against human rights, algorithmic accountability and the regulatory space of Global South states. We conclude that only an intellectual property regime guided by an ethics and politics of vulnerability can reconcile economic integration, technological development and reducing digital vulnerability in deeply unequal societies. Full article

The surface quality of machined gears is closely related to operational energy efficiency and service durability, which affect the achievement of dual carbon goals in sustainable manufacturing. This study proposes a radial pre-stressed grinding method for gear manufacturing. Firstly, an analytical model for the radial pre-stress exerted on the gear inner hole was established by virtue of thick-walled cylinder theory. Secondly, a simulation and experiment were conducted under the same pre-stress conditions to obtain the radial stress. The theoretical, simulated, and experimental results were compared and discussed. Then, gear grinding simulations were performed at different pre-stress levels, grinding depths and grinding speeds. Finally, the grinding parameters were optimized by means of response surface methodology (RSM). This study recommends incorporating gears manufactured with radial pre-stressing into relevant industrial standards for green and low-carbon development. The results indicate that applying radial pre-stress to the gear inner hole significantly influences surface roughness and residual compressive stress after grinding, whereas it exhibits a minimal effect on grinding force. After optimization, compared with the initial simulation results, surface roughness is reduced by 12.5%, the absolute value of residual compressive stress is increased by 52.6%, and grinding force is decreased by 2.1%. The implementation of radial pre-stressed grinding in gear manufacturing requires institutional support, including its integration into green standard institutions, the development of technical specifications, and the establishment of promotion mechanisms. Such integration can be facilitated through national ‘Green Factory’ initiatives, comprehensive intellectual property protection, and targeted personnel training. Full article

This exploratory study examines how journalists in/coordinating investigations use a chatbot designed to reduce power asymmetries during remote work. Twelve freelancers across Africa, Europe, and India tested Obruche, a chatbot advisor covering risk mitigation, pay equality, tension de-escalation, and intellectual property protection. Drawing on the Unified Theory of Acceptance and Use of Technology, semi-structured interviews were coded for Performance Expectancy, Effort Expectancy, Facilitating Conditions, and Social Influence. Results show journalists gravitate towards chatbots that are cognisant of their location-specific challenges and able to provide information that facilitates access to media outlets or peers for future collaborations. Next-best-action responses that expanded user queries or offered role-play scenarios also left journalists feeling supported, less lonely, and not judged. However, the chatbot’s female persona, scepticism of artificial intelligence, and chatbot novelty may reduce user acceptance. Obruche’s potential areas of intervention are linked to eight types of organisational power. The chatbot mainly assisted journalists to confront or rebalance Control of Knowledge and Information, and Control of Scarce Resources, aiding users’ Ability to Cope with Uncertainty. This research contributes to recent qualitative studies on journalists’ well-being by demonstrating how chatbots can mitigate power imbalances between dispersed teams of journalists. The benefits and concerns presented may inform future designs of similar team-mediation chatbots. Full article

Artificial Intelligence (AI) has transitioned from a specialized research area to a ubiquitous socio-technical infrastructure influencing sectors from healthcare and law to manufacturing and defense. In tandem with its transformative promise, AI has created an exponentially expanding ethics literature questioning, fairness, transparency, accountability, and justice. This review synthesizes publications and key policy developments between 2019 and 2025, bringing sectoral discourses together with cross-cutting frameworks. Grounded in a systematic scoping review methodology, we frame the field along four meta-dimensions: trust and transparency, bias and fairness, governance & regulation, and justice, while we investigate their expression across diverse sectors. Special attention is dedicated to healthcare (patient trust and algorithmic bias), education (integrity and authorship), media (misinformation), law (accountability), and the industrial sector (data integrity, intellectual property protection, and environmental safety). We ground abstract principles in concrete case studies to illustrate real-world harms and mitigation strategies. Furthermore, we incorporate pluralistic ethics (e.g., Ubuntu, Islamic perspectives), environmental ethics, and emerging challenges posed by Generative AI and neuro-AI interfaces. To bridge theory and practice, we propose an operational governance framework for organizations. We contend that success involves transitioning from principles toward ethics-by-design, pluralistic governance, sustainability, and adaptive oversight. This review is intended for scholars, practitioners, and policymakers who need a comprehensive and actionable framework for navigating the complex landscape of AI ethics. Full article

Remote sensing object detection (RSOD) models play an increasingly important role in modern remote sensing systems. However, during model delivery, sharing, and deployment, RSOD models face increasing risks of unauthorized redistribution, illegal replication, and intellectual property infringement. To mitigate these threats, this paper proposes a white-box watermarking framework for RSOD models that enables reliable copyright verification while preserving the performance of the primary detection task. Specifically, a gradient-based sensitivity analysis of the detection loss is first performed to adaptively identify model parameters that minimally affect detection performance, which are then selected as watermark carriers. Subsequently, a parameter-ranking-based watermark encoding scheme is developed, where watermark bits are embedded by enforcing relative ordering constraints between parameter pairs. To further improve robustness under practical deployment conditions, an attack-simulation-driven training strategy is introduced, in which common perturbations and watermark removal attacks are simulated during the embedding process. In addition, a stealthiness enhancement strategy based on statistical distribution constraints is designed to maintain consistency between the distribution of watermarked parameters and those of the original model, thereby reducing the risk of watermark exposure and localization. Extensive experiments across multiple RSOD datasets and detection architectures demonstrate that the proposed method achieves a high copyright verification success rate with negligible impact on detection accuracy and exhibits strong robustness and stealthiness against a variety of watermark removal attacks. Full article

Based on Chinese A-share listed companies’ panel data from 2008 to 2023, we examine the impact of digital–real integration on firm green technology innovation. The empirical results show that digital–real integration can significantly improve firm green technology innovation. Mechanism analysis reveals that digital–real integration improves firm green technology innovation by reducing financing constraints, improving productivity and reducing information asymmetry. Heterogeneity analysis results show that the positive effects are more pronounced in private and other non-state-owned firms, large-scale firms and firms with stronger internal control. The study also confirms that government green subsidy, governance quality, intellectual property protection, digital infrastructure and marketization level can enhance the positive effect of digital–real integration on firm green technology innovation. Full article

Green technological innovation is a core driving force for firms’ low-carbon transformation. However, because critical green technologies and knowledge are often dispersed across upstream and downstream partners within supply chains, firms’ green transformation faces substantial challenges. Previous studies have primarily focused on internal drivers at the firm level while overlooking the empowering role of green collaborative cooperation among supply chain partners. To address this gap, this study introduces empowerment theory to systematically examine how supply chain green strategic alliances enhance firms’ green innovation capability. Using a sample of Chinese A-share listed firms from 2011 to 2023, we construct a firm-level indicator of supply chain green strategic alliances based on textual analysis and machine learning techniques and empirically test its impact on green innovation. The results show that participation in green strategic alliances significantly promotes firms’ green innovation. Mechanism analyses further reveal that this effect operates through the reconstruction of green knowledge, increased environmental investment, and improved green governance. Moreover, the positive effect is more pronounced in regions with stronger intellectual property protection, greater green credit support, and stricter environmental regulation, as well as among firms with closer supply chain relationships. This study identifies supply chain green strategic alliances as a key inter-organizational empowerment mechanism and provides important practical implications for leveraging supply chain collaboration to accelerate sustainable development and firms’ green transformation. Full article

Natural pasture, the primary feed source in sheep production, often provides insufficient levels of essential minerals and vitamins required for proper metabolic regulation during pregnancy and early development. This study aimed to analyze patent developments of mineral and vitamin complexes (MVCs) for pregnant ewes and lambs and to evaluate the biochemical and molecular relevance of their components based on scientific evidence. A search of the World Intellectual Property Organization (WIPO) database using the keywords “vitamins for sheep” and “minerals for sheep” identified 120 patents related to sheep feed additives, including 23 specifically formulated for pregnant ewes and lambs. Comparative analysis revealed that calcium, selenium, iron, copper, cobalt, sodium, manganese, zinc, and vitamins A, D, and E were the most frequently included components. These micronutrients play critical roles in enzymatic activity, regulation of gene expression, antioxidant defense systems, and mineral homeostasis. In particular, zinc and selenium function as structural and catalytic cofactors for antioxidant enzymes such as superoxide dismutase and glutathione peroxidase, while vitamins A and D regulate cellular differentiation and calcium–phosphorus metabolism through transcriptional control mechanisms. Additionally, functional additives, including amino acids and plant-derived bioactive compounds, contribute to improved mineral bioavailability and modulation of metabolic pathways. The analyzed formulations demonstrate a consistent focus on correcting mineral deficiencies, enhancing antioxidant protection, and supporting metabolic adaptation during pregnancy and early postnatal development. Overall, the findings indicate that modern MVCs are rationally formulated to improve mineral utilization, physiological stability, and reproductive outcomes, highlighting their critical role in optimizing maternal health and offspring viability in sheep production systems. Full article

In the era of technological revolution, high-tech industries have gained prominence in national innovation systems. However, China’s high-tech sector faces challenges such as late development, weak foundations, and regional disparities. To address these issues, this study proposes a shared-input two-stage network DEA model. This model, based on an input-output perspective, considers resources that circulate and collaboratively function across multiple stages in the form of shared inputs. This paper analyzes data from 25 provinces (including municipalities) in China from 2011 to 2020 and divides the patent conversion process into two sub-stages: the upstream technology research and development stage and the downstream achievement transformation stage, measuring the stage efficiency values and overall efficiency values, respectively. To align with reality, this paper incorporates the intensity of the strength of intellectual property protection, strength of government financial support, and the expenditure on technology import as regional shared input variables. Meanwhile, expenditure on technological transformation is treated as a capital-type intermediate input variable. This approach unveils the “black box” of single-stage DEA, enabling more accurate efficiency measurement. Key findings reveal: (1) China’s high-tech research and development of patent technology, the achievement transformation and overall conversion efficiency show annual improvement, yet overall efficiency remains low with regional imbalances; (2) Achievement transformation efficiency exerts a greater impact on overall conversion efficiency than research and development of patent technology efficiency. Comparative analyses with single-stage and chained two-stage DEA models confirm the necessity of phased evaluation and shared-input variables, supported by input-output elasticity tests. The findings validate the applicability and interpretability of the proposed model in efficiency evaluation. Full article

The rapid integration of artificial intelligence (AI) has heightened the need for evidence-based regulatory frameworks to effectively address its legal, ethical, and societal consequences. This research carefully analyzes the prevailing landscape of AI-related legislation in Mexico. The study conducts a comprehensive review of legislative initiatives related to AI regulation submitted to Mexican legislative bodies, encompassing those approved or pending in commissions. This process leads to the identification and categorization of outstanding initiatives across seven policy areas: Congress, Education, Health, Intellectual Property, Justice, AI Promotion, and AI Regulation. As a principal contribution, this work offers the first exhaustive mapping and thematic classification of legislative activity related to AI in Mexico. Furthermore, the analysis identifies systemic regulatory deficiencies, such as the lack of AI-specific legislation, the limited scope of existing data protection laws in relation to AI systems, and an absence of technical provisions concerning ethical design, algorithmic transparency, cybersecurity, and accountability frameworks. By showcasing these deficiencies, the study contributes a diagnostic framework for evaluating AI governance readiness in emerging economies. The findings emphasize the importance of establishing a comprehensive, technically sound, and internationally harmonized regulatory framework to reduce AI-related risks while promoting responsible innovation in Mexico. Full article

Carnation is one of the most popular ornamental flowers worldwide. Due to its high ornamental and economic value, breeding techniques have advanced rapidly, leading to the continuous emergence of new varieties. However, this has also resulted in issues such as synonymy and homonymy. Therefore, utilizing DNA fingerprinting for rapid and accurate variety identification can play a crucial role in germplasm identification and the resolution of intellectual property disputes. In this study, we performed reduced-representation genome sequencing on 50 carnation accessions to develop single nucleotide polymorphism (SNP) markers. After filtering, 82,584 high-quality SNPs were obtained. These SNPs were used to conduct principal component analysis, population structure analysis, and cluster analysis on the 50 carnation accessions. From these high-quality SNPs, 130 SNP loci were further selected and converted into Kompetitive Allele-Specific PCR (KASP) markers. Preliminary screening using 92 carnation accessions yielded 53 KASP markers, and a subsequent screening with 217 carnation accessions identified 45 core KASP markers. Using these core markers, a fingerprint database was successfully constructed for 309 carnation accessions, achieving a distinguishing power of 99.987%. This study employed SNP fingerprinting and genetic analysis for the screening and identification of carnations, broadening the genetic basis at the molecular level and supporting subsequent variety protection efforts, thereby providing a scientific basis for carnation selection and identification. Full article

Traditional textile crafts face significant challenges in preserving and transferring knowledge due to the aging of expert artisans and declining community engagement. The Phum Riang silk-weaving tradition in Suratthani Province is a critical example of indigenous knowledge systems that require systematic documentation and digital conservation strategies. This research aims to develop a comprehensive ontological framework to support the capture, organization, and preservation of traditional knowledge related to Phum Riang silk production processes, establishing practical methodologies applicable to broader cultural heritage craft digitization and knowledge management systems. The research methodology employs ontology engineering principles, using the Web Ontology Language to create structured knowledge representation systems. Data collection was conducted through ethnographic fieldwork, in-depth interviews with expert craftspeople, and systematic documentation covering production processes, materials, tools, and cultural practices. The developed ontology encompasses five primary knowledge domains: production processes, raw materials, traditional tools, geographical context, and cultural significance. The framework comprises 23 distinct classes organized in hierarchical structures, 15 object properties, and 12 data properties, complemented by business rules ensuring authenticity and quality control mechanisms. This framework has significant implications for cultural heritage digitization, indigenous intellectual property protection, systematic knowledge transfer across generations, cultural authenticity preservation, and traditional craft community economic sustainability. Full article