Search Results (2,696)

This study presents a cross-cultural comparison of two fortified residences—Palazzo Farnese in Italy and Dong’s Fortified Compound in China—through a triadic analytical framework encompassing architectural form, symbolic ornamentation, and public perception. By combining field observation, iconographic interpretation, and digital ethnography, the research investigates how heritage meaning is constructed, encoded, and reinterpreted across distinct sociocultural contexts. Empirical materials include architectural documentation, decorative analysis, and a curated dataset of 4947 user-generated images and 1467 textual comments collected from Chinese and international platforms between 2020 and 2024. Methods such as CLIP-based visual clustering and BERTopic-enabled sentiment modelling were applied to extract patterns of perception and symbolic emphasis. The findings reveal contrasting representational logics: Palazzo Farnese encodes dynastic authority and Renaissance cosmology through geometric order and immersive frescoes, while Dong’s Compound conveys Confucian ethics and frontier identity via nested courtyards and traditional ornamentation. Digital responses diverge accordingly: international users highlight formal aesthetics and photogenic elements; Chinese users engage with symbolic motifs, family memory, and ritual significance. This study illustrates how historically fortified residences are reinterpreted through culturally specific digital practices, offering an interdisciplinary approach that bridges architectural history, symbolic analysis, and digital heritage studies. Full article

In response to the stress commonly experienced by young people in high-pressure daily environments, a music-based stress-relief interactive system was developed by integrating music-assisted care with emotion-sensing technology. The design principles of the system were established through a literature review on stress, music listening, emotion detection, and interactive devices. A prototype was created accordingly and refined through interviews with four experts and eleven users participating in a preliminary experiment. The system is grounded in a four-stage guided imagery and music framework, along with a static activity model focused on relaxation-based stress management. Emotion detection was achieved using a wearable EEG device (NeuroSky’s MindWave Mobile device) and a two-dimensional emotion model, and the emotional states were translated into visual representations using seasonal and weather metaphors. A formal experiment involving 52 users was conducted. The system was evaluated, and its effectiveness confirmed, through user interviews and questionnaire surveys, with statistical analysis conducted using SPSS 26 and AMOS 23. The findings reveal that: (1) integrating emotion sensing with music listening creates a novel and engaging interactive experience; (2) emotional states can be effectively visualized using nature-inspired metaphors, enhancing user immersion and understanding; and (3) the combination of music listening, guided imagery, and real-time emotional feedback successfully promotes emotional relaxation and increases self-awareness. Full article

The ongoing degradation of global forests has severely weakened ecosystem service functions, and traditional judicial remedies have struggled to quantify intangible ecological losses. China has become an important testing ground for restorative justice through the establishment of specialized environmental courts and the practice of environmental public interest litigation. Since 2015, China has actively explored and institutionalized the application of the concept of restorative justice in its environmental justice reform. This concept emphasizes compensating environmental damages through actual ecological restoration acts rather than relying solely on financial compensation. This shift reflects a deep understanding of the limitations of traditional environmental justice and an institutional response to China’s ecological civilization construction, providing critical support for forest ecosystem restoration and enabling ecological restoration activities, such as replanting and re-greening, habitat reconstruction, etc., to be enforced through judicial decisions. This study conducts a qualitative analysis of judicial rulings in forest restoration cases to systematically evaluate the effectiveness of restorative justice in compensating for losses in forest ecosystem service functions. The findings reveal the following: (1) restoration measures in judicial practice are disconnected from the types of ecosystem services available; (2) non-market values and long-term cumulative damages are systematically underestimated, with monitoring mechanisms exhibiting fragmented implementation and insufficient effectiveness; (3) management cycles are set in violation of ecological restoration principles, and acceptance standards lack function-oriented indicators; (4) participation of key stakeholders is severely lacking, and local knowledge and professional expertise have not been integrated. In response, this study proposes a restorative judicial framework oriented toward forest ecosystem services, utilizing four mechanisms: independent recognition of legal interests, function-matched restoration, application of scientific assessment tools, and multi-stakeholder collaboration. This framework aims to drive a paradigm shift from formal restoration to substantive functional recovery, providing theoretical support and practical pathways for environmental judicial reform and global forest governance. Full article

This study explores how corporate governance reforms can enhance financial reporting quality and organizational transparency, focusing on Greece’s transition from Law 3016/2002 to Law 4706/2020. The legislative reform aimed to modernize governance structures, align national practices with international standards, and strengthen investor protection in a post-crisis economic environment. Moving beyond a simple legal comparison, the study examines how Law 3016/2002’s formal compliance model contrasts with Law 4706/2020’s more substantive accountability framework. We hypothesize that Law 4706/2020 introduces substantively stronger governance mechanisms than its predecessor, thereby improving transparency and investor protection, while compliance with the new law imposes materially greater administrative and financial burdens, especially on small- and mid-cap firms. Methodologically, the research employs a narrative literature review and a structured comparative legal analysis to assess the administrative and financial implications of the new law for publicly listed companies, focusing on board composition and diversity, internal controls, suitability policies, and disclosure requirements. Drawing on prior comparative evidence, we posit that Law 4706/2020 will foster governance and disclosure improvements, enhanced oversight, and clearer board roles. However, these measures also impose compliance burdens. Due to the heterogeneity of listed companies and the lack of firm-level data following Law 4706/2020’s implementation, the findings are neither fully generalizable nor quantifiable; future quantitative research using event studies or panel data is required to validate the hypotheses. We conclude that Greece’s new framework is a critical step toward sustainable corporate governance and more transparent financial reporting, offering regulators, practitioners, and scholars examining legal reform’s impact on governance effectiveness and financial reporting integrity. Full article

Concept-cognitive learning reveals the principle of human cognition by simulating the brain’s process of learning and processing concepts. Nevertheless, for neighborhood similarity granules, the average information of objects regarding all attributes is not considered, which may lead to unbalanced acquisition of knowledge. On the other hand, there are some unnecessary concepts in the extension of fuzzy concepts, which results in poor classification learning. To tackle these challenges, we present a forgetting-based concept-cognitive learning model for classification in a fuzzy formal decision context. Firstly, the fuzzy concept space is established based on the the correlation coefficient matrix. Then, to delete unnecessary objects that are in the zone of proximal development, we construct the forgetting fuzzy concept space by selecting the concept corresponding to the maximum similarity. Subsequently, a forgetting-based fuzzy concept model (FCCLM) mechanism is proposed. In the end, experimental results on eight datasets validate the feasibility and efficiency of the proposed learning mechanism through classification performance assessment. Full article

Background: Thailand is rapidly transitioning into an aging society, creating an intergenerational caregiving gap that strains existing support systems. Objective: This study evaluated the effectiveness of “Young Care,” a community-based intervention designed to enhance youth knowledge, attitudes, and caregiving practices (KAP) toward older adults. Methods: A two-day structured training was conducted in Maha Sarakham Province in 2023 using a pre-post mixed-methods design. Middle and high school students participated in lectures, multimedia sessions, and experiential learning activities related to caregiving. Quantitative data were collected using validated KAP questionnaires, while qualitative insights were obtained from focus group discussions involving students, older persons, caregivers, and local leaders. Results: Post-intervention analysis revealed significant improvements in knowledge and attitudes (p < 0.001), accompanied by increased empathy, caregiving initiative, and a sense of moral responsibility among participants. Conclusions: The initiative fostered formal partnerships among schools, local governments, healthcare providers, and universities through memoranda of understanding. These collaborations enabled budgetary support and outreach to out-of-school youth, positioning “Young Care” as a scalable, youth-centered strategy to address Thailand’s long-term care challenges. Full article

Smart contracts and cryptocurrency wallets are foundational components of decentralized applications (dApps) on blockchain platforms such as Ethereum. While these technologies enable secure, transparent, and automated transactions, their integration also introduces complex security challenges. This study presents a security-oriented analysis of smart contract and wallet integration, focusing on BlockScribe—a decentralized Ethereum-based application for digital record certification. We systematically identify and categorize security risks arising from the interaction between wallet interfaces and smart contract logic. In particular, we analyze how user authorization flows, transaction design, and contract modularity affect the security posture of the entire dApp. To support our findings, we conduct an empirical evaluation using static analysis tools and formal verification methods, examining both contract-level vulnerabilities and integration-level flaws. Our results highlight several overlooked attack surfaces in wallet–contract communication patterns, including reentrancy amplification, permission mismanagement, and transaction ordering issues. We further discuss implications for secure dApp development and propose mitigation strategies that improve the robustness of wallet–contract ecosystems. This case study contributes to a deeper understanding of integration-layer vulnerabilities in blockchain-based systems and offers practical guidance for developers and auditors aiming to strengthen smart contract security. Full article

Background/Objectives: The extensive use of computed tomography (CT) has led to a significant increase in the detection of small and non-palpable pulmonary nodules, necessitating the use of invasive methods for definitive diagnosis. Video-assisted thoracoscopic surgery (VATS) has become the preferred procedure for nodule resections; however, intraoperative localization remains challenging, especially for deep or subsolid lesions. This study explores whether SPECT/CT improves the technical and clinical outcomes of radio-guided occult lesion localization (ROLL) before uniportal video-assisted thoracoscopic surgery (u-VATS). Methods: This is a retrospective study involving consecutive patients referred for the resection of pulmonary nodules who underwent CT-guided ROLL followed by u-VATS between September 2017 and December 2024. From January 2023, SPECT/CT was systematically added after planar imaging. The cohort was divided into a planar group and a planar + SPECT/CT group. The inclusion criteria involved nodules sized ≤ 2 cm, with ground glass or solid characteristics, located at a depth of <6 cm from the pleural surface. ^99mTc-MAA injected activity, timing, the classification of planar and SPECT/CT image findings (focal uptake, multisite with focal uptake, multisite without focal uptake), spillage, and post-procedure complications were evaluated. Statistical analysis was performed, with continuous data expressed as the median and categorical data as the number. Comparisons were made using chi-square tests for categorical variables and the Mann–Whitney U test for procedural duration. Cohen’s kappa coefficient was calculated to assess agreement between imaging modalities. Results: In total, 125 patients were selected for CT-guided radiotracer injection followed by uniportal-VATS. The planar group and planar + SPECT/CT group comprised 60 and 65 patients, respectively. Focal uptake was detected in 68 (54%), multisite with focal uptake in 46 (36.8%), and multisite without focal uptake in 11 patients (8.8%). In comparative analyses between planar and SPECT/CT imaging in 65 patients, 91% exhibited focal uptake, revealing significant differences in classification for 40% of the patients. SPECT/CT corrected the classification of 23 patients initially categorized as multisite with focal uptake to focal uptake, improving localization accuracy. The mean procedure duration was 39 min with SPECT/CT. Pneumothorax was more frequently detected with SPECT/CT (43% vs. 1.6%). The intraoperative localization success rate was 96%. Conclusions: SPECT/CT imaging in the ROLL procedure for detecting pulmonary nodules before u-VATs demonstrates a significant advantage in reclassifying radiotracer positioning compared to planar imaging. Considering its limited impact on surgical success rates and additional procedural time, SPECT/CT should be reserved for technically challenging cases. Larger sample sizes, multicentric and prospective randomized studies, and formal cost–utility analyses are warranted. Full article

Background: In a global panorama marked by a progressive rise in obesity, metabolic syndrome, and chronic non-communicable disease prevalence, nutrition education (NE) might play a pivotal role in restoring adoption and strengthening adherence to dietary patterns that protect human health. Therefore, the primary purpose of this work is to review the existing scientific literature studying NE programs aimed at schoolchildren in the decade 2014–2024 and evaluate the effectiveness of intervention tools. Methods: During the first phase of this research, a qualitative analysis was conducted to track similarity in intervention tools and strategies used in nutrition education programs. In the second phase, a quantitative analysis was carried out, extracting common parameters among studies and assessing their potential influence in improving adherence to the Mediterranean diet (MD). Results: A high degree of heterogeneity was observed in educational program designs and intervention tools, which were usually not properly described and justified. All studies that measured adherence to the MD registered an improvement after the intervention, in some cases even higher than 10%. However, this study found no relationship between common parameters (i.e., number of formal tools, number of non-formal tools, lesson duration, and program length) used in NE and the improvement in students’ adherence to MD. Conclusions: This research has contributed to outlining a general framework of NE and to promoting a systematic approach in this research field. Full article

The Industrial Internet of Things (IIoT), a key enabler of Industry 4.0, integrates advanced communication technologies with the industrial economy to enable intelligent manufacturing and interconnected systems. Secure and reliable identity authentication in the IIoT becomes essential as connectivity expands across devices, systems, and domains. Blockchain technology presents a promising solution due to its decentralized, tamper-resistant, and traceable characteristics, facilitating secure and transparent identity verification. However, current blockchain-based cross-domain authentication schemes often lack a lightweight design, rendering them unsuitable for latency-sensitive and resource-constrained industrial environments. This paper proposes a lightweight cross-domain authentication scheme that combines blockchain with Chebyshev chaotic mapping. Unlike existing schemes relying heavily on Elliptic Curve Cryptography or bilinear pairing, our design circumvents such computationally intensive primitives entirely through the algebraic structure of Chebyshev polynomials. A formal security analysis using the Real-Or-Random (ROR) model demonstrates the scheme’s robustness. Furthermore, performance evaluations conducted with Hyperledger Fabric and the MIRACL cryptographic library validate the method’s effectiveness and superiority over existing approaches in terms of both security and operational efficiency. Full article

Media organizations are experiencing ongoing transformation, increasingly driven by the advancement of AI technologies. This development has begun to link journalists with generative systems and synthetic technologies. Although newsrooms worldwide are exploring AI adoption to improve information sourcing, news production, and distribution, a gap exists between resource-rich organizations and those with limited means. Since ChatGPT 3.5 was released on 30 November 2022, Greek media and journalists have gained the ability to use and explore AI technology. In this study, we examine the use of AI in Greek newsrooms, as well as journalists’ reflections and concerns. Through qualitative analysis, our findings indicate that the adoption and integration of these tools in Greek newsrooms is marked by the lack of formal institutional policies, leading to a predominantly self-directed and individualized use of these technologies by journalists. Greek journalists engage with AI tools both professionally and personally, often without organizational guidance or formal training. This issue may compromise the quality of journalism due to the absence of established guidelines. Consequently, individuals may produce content that is inconsistent with the media outlet’s identity or that disseminates misinformation. Age, gender, and newsroom roles do not constitute limiting factors for this “experimentation”, as survey participants showed familiarity with this technology. In addition, in some cases, the disadvantages of specific tools regarding qualitative results in Greek are inhibiting factors for further exploration and use. All these points to the need for immediate training, literacy, and ethical frameworks. Full article

Collaborative business ecosystems (CBEs) are increasingly exposed to disruptive events (e.g., pandemics, supply chain breakdowns, cyberattacks) that challenge organizational adaptability and value creation. Traditional approaches to resilience and robustness often fail to capture the full range of systemic responses. This study introduces a unified mathematical framework to evaluate four crisis response modes—plasticity, resilience, transformative resilience, and antifragility—within complex adaptive networks. Grounded in complex systems and collaborative network theory, our model formalizes both internal organizational capabilities (e.g., adaptability, learning, innovation, structural flexibility) and strategic interventions (e.g., optionality, buffering, information sharing, fault-injection protocols), linking them to pre- and post-crisis performance via dynamic adjustment functions. A composite performance score is defined across four dimensions (Innovation, Contribution, Prestige, and Responsiveness to Business Opportunities), using capability–strategy interaction matrices, weighted performance change functions, and structural transformation modifiers. The sensitivity analysis and scenario simulations enable a comparative evaluation of organizational configurations, strategy impacts, and phase-transition thresholds under crisis. This indicator-based formulation provides a quantitative bridge between resilience theory and practice, facilitating evidence-based crisis management in networked business environments. Full article

Blockchain’s immutability, while enhancing transparency and trust, presents challenges when erroneous or sensitive content must be modified. To address this, we propose a novel cryptographic primitive called Time-Modifiable Chameleon Hash (TMCH), enabling controlled and time-modifiable data redaction in blockchain systems. TMCH enhances traditional chameleon hashes by embedding a time parameter into hash generation and verification, and it supports class-adaptive collision computation via a new Update algorithm. We formally define the security model for TMCH and analyze the relationships among uniqueness, indistinguishability (IND), and collision resistance (CR). This paper presents a concrete construction based on the Boneh–Boyen signature scheme and completes its security analysis and proof. Finally, the efficiency and practicality of the proposed scheme are validated through experimental comparisons with existing algorithms. Our results show that relaxing the uniqueness requirement does not compromise overall security, while enabling traceable and time-aware redactions. The proposed TMCH achieves strong security guarantees and practical efficiency, making it well suited for applications such as compliant data redaction and time-sensitive blockchain transactions. Full article

This study explores the interplay of climate vulnerability and social capital in two rural communities: Brajaballavpur, a high-climate-prone village in the Indian Sundarbans characterized by high ecological fragility, recurrent cyclones, and saline water intrusion affecting water access, livelihoods, and infrastructure; and Jemua, a low-climate-prone village in the land-locked district of Paschim Bardhaman, West Bengal, India, with no extreme climate events. A total of 85 participants (44 in Brajaballavpur, 41 in Jemua) were selected through purposive sampling. Using a comparative qualitative research design grounded in ethnographic fieldwork, data were collected through household interviews, Participatory Rural Appraisals (PRAs), Focus Group Discussions (FGDs), and Key Informant Interviews (KIIs), and analyzed manually using inductive thematic analysis. Findings reveal that bonding and bridging social capital were more prominent in Brajaballavpur, where dense horizontal ties supported collective action during extreme weather events. Conversely, linking social capital was more visible in Jemua, where participants more frequently accessed formal institutions such as the Gram Panchayat, local NGOs, and government functionaries that facilitated grievance redressal and information access, but these networks were concentrated among more politically connected individuals. The study concludes that climate vulnerability shapes the type, strength, and strategic use of social capital in village communities. While bonding and bridging ties are crucial in high-risk contexts, linking capital plays a critical role in enabling long-term social structures in lower-risk settings. The study contributes to both academic literature and policy design by offering a relational and place-based understanding of climate vulnerability and social capital. Full article

Calls for an “archaeology of climate change” highlight the interest in integrating human land use histories with the paleoenvironmental record. Shifts in land use patterns, observed via regional archaeological surveys, have been used in studies exploring the relationships between human and environmental systems, often via the Adaptive Cycle (AC). Recent work has combined datasets from separate surveys to examine macroregional patterns, which can then be integrated with environmental proxy data. However, efforts at aggregating archaeological data are often problematized due to projects’ differing collection methods and periodizations. This study ascribes the formal constructs of the AC to survey data to minimize data aggregation issues and maintain local integrity. Aoristic sum functions were performed individually on data from four projects in the northeastern Peloponnese to identify local patterns. These data were then aggregated, allowing for changes in land use to be observed at the macro and regional levels. Further measurements relating to land use abandonment, continuity, expansion, and potential serve as proxy data to identify the AC constructs of organization, exploitation, conservation, and release. The approach allows for cross-comparative regional analysis and the creation of an aggregated dataset that describes macroregional trends, essential to integrating human and paleoenvironmental narratives over time. Full article