Search Results (311)

Existing research predominantly focuses on the preservation or renewal models of the physical forms of historic cultural districts, with limited exploration of their roles in stimulating tourists’ cognitive, affective resonance, and behavioral interactions. This study addresses historic cultural districts by evaluating the space quality and its impact on tourist experiences through the “cognition-affect-behavior” framework, integrating GIS, street view semantic segmentation, VR eye-tracking, and web crawling technologies. The findings reveal significant multidimensional differences in how space quality influences tourist experiences: the impact intensities of functional diversity, sky visibility, road network accessibility, green visibility, interface openness, and public facility convenience decrease sequentially, with path coefficients of 0.261, 0.206, 0.205, 0.204, 0.201, and 0.155, respectively. Additionally, space quality exerts an indirect effect on tourist experiences through the mediating roles of cognitive, affective, and behavioral dimensions, with a path coefficient of 0.143. This research provides theoretical support and practical insights for empowering cultural heritage space governance with digital technologies in the context of cultural and tourism integration. Full article

The growing need for secure and privacy-preserving identity management in industrial environments has exposed the limitations of traditional, centralized authentication systems. In this context, SIBERIA was developed as a modular solution that empowers users to control their own digital identities, while ensuring robust protection of critical services. The system is designed in alignment with European standards and regulations, including EBSI, eIDAS 2.0, and the GDPR. SIBERIA integrates a Self-Sovereign Identity (SSI) framework with a decentralized blockchain-based infrastructure for the issuance and verification of Verifiable Credentials (VCs). It incorporates multi-factor authentication by combining a voice biometric module, enhanced with spoofing-aware techniques to detect synthetic or replayed audio, and a behavioral biometrics module that provides continuous authentication by monitoring user interaction patterns. The system enables secure and user-centric identity management in industrial contexts, ensuring high resistance to impersonation and credential theft while maintaining regulatory compliance. SIBERIA demonstrates that it is possible to achieve both strong security and user autonomy in digital identity systems by leveraging decentralized technologies and advanced biometric verification methods. Full article

Background: Vaccine hesitancy (VH) represents a growing concern among healthcare professionals and students, potentially undermining public health efforts. Nursing, pediatric nursing, and midwifery students are future vaccinators and educators, making it essential to understand their attitudes, knowledge, and confidence toward vaccination. This study aims to assess vaccine-related perceptions and behaviors among these student populations in an Italian university. Methods: A cross-sectional survey was conducted between November 2022 and February 2024 at the University of Rome “Tor Vergata”. A structured, anonymous questionnaire, including the Vaccination Attitudes Examination (VAX) scale, vaccine knowledge items, and sources of information, was administered to students in nursing (n = 205), pediatric nursing (n = 46), and midwifery (n = 21). Statistical analyses included descriptive statistics, ANOVA, post hoc tests, and Mann–Whitney U tests. Results: Among the 272 participants, 20.6% reported refusing at least one recommended vaccine, and 18.4% delayed vaccination for non-medical reasons. Vaccine knowledge and confidence increased significantly with academic progression (p < 0.001). Midwifery students showed both the highest concern for long-term vaccine effects and the greatest confidence in vaccine safety. Institutional and scientific sources were the most trusted, though traditional and non-institutional media also influenced perceptions, particularly among midwifery students. Conclusions: Despite high COVID-19 vaccine uptake, VH persists among health professional students. Discipline-specific patterns highlight the need for early, targeted educational strategies to enhance vaccine literacy and reduce hesitancy. Tailored training may empower future professionals to become informed and credible advocates for vaccination. Full article

In nature, organisms often rely on the integration of local sensory information and prior experience to flexibly adapt to complex and dynamic environments, enabling efficient path selection. This bio-inspired mechanism of perception and behavioral adjustment provides important insights for path planning in mobile robots operating under uncertainty. In recent years, the introduction of deep reinforcement learning (DRL) has empowered mobile robots to autonomously learn navigation strategies through interaction with the environment, allowing them to identify obstacle distributions and perform path planning even in unknown scenarios. To further enhance the adaptability and path planning performance of robots in complex environments, this paper develops a deep reinforcement learning framework based on the Soft Actor–Critic (SAC) algorithm. First, to address the limited adaptability of existing transfer learning methods, we propose an action-level fusion mechanism that dynamically integrates prior and current policies during inference, enabling more flexible knowledge transfer. Second, a bio-inspired radar perception optimization method is introduced, which mimics the biological mechanism of focusing on key regions while ignoring redundant information, thereby enhancing the expressiveness of sensory inputs. Finally, a reward function based on ineffective behavior recognition is designed to reduce unnecessary exploration during training. The proposed method is validated in both the Gazebo simulation environment and real-world scenarios. Experimental results demonstrate that the approach achieves faster convergence and superior obstacle avoidance performance in path planning tasks, exhibiting strong transferability and generalization across various obstacle configurations. Full article

The rapid spread of artificial intelligence (AI) in education means that students need to master both AI literacy and personal agency. This study situates a sample of 425 Slovenian secondary technical students within a three-tier framework that maps psychological empowerment onto AI literacy outcomes within a cultural–historical activity system. The agency competence assessments yielded four profiles of student agency, ranging from fully empowered to largely disempowered. The cluster membership explained significant additional variance in AI literacy scores, supporting the additive empowerment model in an AI-rich vocational education and training context. The predictive modeling revealed that while self-efficacy, mastery-oriented motivations, and metacognitive self-regulation contributed uniquely—though small—to improving AI literacy, an unexpectedly negative relationship was identified for internal locus of control and for behavioral self-regulation focused narrowly on routines, with no significant impact observed for grit-like perseverance. These findings underscore the importance of fostering reflective, mastery-based, and self-evaluative learning dispositions over inflexible or solely routine-driven strategies in the development of AI literacy. Addressing these nuanced determinants may also be vital in narrowing AI literacy gaps observed between diverse disciplinary cohorts, as supported by recent multi-dimensional literacy frameworks and disciplinary pathway analyses. Embedding autonomy-supportive, mastery-oriented, student-centered projects and explicit metacognitive training into AI curricula could shift control inward and benefit students with low skills, helping to forge an agency-driven pathway to higher levels of AI literacy among high school students. The most striking and unexpected finding of this study is that students with a strong sense of competence—manifested as high self-efficacy—can achieve foundational AI literacy levels equivalent to those possessing broader, more holistic agentic profiles, suggesting that competence alone may be sufficient for acquiring essential AI knowledge. This challenges prevailing models that emphasize a multidimensional approach to agency and has significant implications for designing targeted interventions and curricula to rapidly build AI literacy in diverse learner populations. Full article

With the rise of live-streaming services on e-commerce platforms, AI-powered virtual idols have demonstrated tremendous application potential and thus possess high commercial value. From the perspective of psychological distance, this study adopts the Stimulus–Organism–Response (S–O–R) theoretical framework to construct a research model of “AI-powered virtual idols–psychological distance–impulsive buying intention”. The model aims to explore how AI-powered virtual idols promote digital natives’ impulsive buying intention in the context of e-commerce live streaming. Furthermore, this study examines the moderating effect of technology readiness on the relationship between AI-powered virtual idols and psychological distance. The findings reveal that the level of intelligence of AI-powered virtual idols—including interactivity, anthropomorphism, homogeneity, and reputation—enhances digital natives’ impulsive buying intention by reducing psychological distance. For digital natives with lower technology readiness, the effect of AI-powered virtual idols in narrowing psychological distance is more pronounced. These findings enrich AI-driven consumer behavior models from a theoretical perspective and offer theoretical support and practical insights for developing AI-empowered digital marketing strategies tailored to the psychological traits and technological adaptability of digital natives. Full article

In the context of accelerating digital transformation and growing sustainability imperatives, entrepreneurial ecosystems increasingly rely on open innovation and strategic collaboration to foster resilient, knowledge-driven growth. This study aims to examine how leadership behaviors and strategic alliances interact as enablers of sustainable innovation across macro (systemic), meso (organizational), and micro (individual) levels. To achieve this, this study employs a literature review, supported by bibliometric analysis, as its core methodological approach. Drawing on 86 influential publications from 1992 to 2024, two major thematic streams emerge: leadership dynamics in entrepreneurial settings and the formation and governance of strategic alliances as vehicles for innovation. The findings underscore the pivotal role of transformational and ethical leadership in cultivating trust-based inter-organizational relationships, facilitating digital knowledge sharing, and catalyzing sustainable value creation. Simultaneously, strategic alliances enhance organizational agility and innovation capacity through co-creation mechanisms, digital platforms, and crowdsourcing, especially in small and medium-sized enterprises (SMEs). This paper highlights a mutually reinforcing relationship: effective leadership strategies empower alliances, while alliance participation enhances leadership capabilities through experiential learning in diverse, digitalized environments. By bridging leadership theory, open innovation practices, and digital transformation, this study offers critical insights for entrepreneurs, managers, and policymakers seeking to drive inclusive and sustainable innovation within interconnected global markets. Therefore, this study provides practical guidance for business leaders aiming to strengthen alliance performance through adaptive leadership and for policymakers seeking to foster innovation ecosystems through supportive regulatory and institutional frameworks. Full article

Childhood cancer survivors (CCSs) are at increased risk for chronic health issues due to late effects of cancer and its treatment. We address the impact of environmental exposures, such as air pollution, tobacco smoke, extreme weather events, and pesticides, on the health and survival of CCSs. These environmental hazards have been associated with worsening health outcomes and decreased survival among CCSs on a global scale. We also highlight that providers at a major pediatric cancer center in the United States have limited knowledge and practical skills about environmental risk factors and how to reduce exposures. Our survey results show that pediatric oncology providers would find an environmental referral service helpful and useful in their department. Integrating environmental health into pediatric cancer care can empower patients and families, promote healthier behaviors, and potentially reduce morbidity and mortality in this vulnerable population. Full article

Reducing carbon dioxide emissions within carbon-intensive industries is a critical strategy to effectively combat global warming. The accelerated cultivation and enhancement of new quality productivity has created new momentum directed towards industrial low-carbon transformation. Using data from a sample of Chinese provinces and enterprises between 2011 and 2022, this study quantifies, evaluates, and explores the influence and mechanisms of new quality productivity on the low-carbon transformation of carbon-intensive industries. The research findings show that: (1) Fostering new quality productivity effectively promotes the low-carbon transformation of carbon-intensive industries and plays a positive, empowering role. Industrial innovation, digital stimulation, technological innovation, and green empowerment all support the low-carbon transformation of carbon-intensive industries, with their respective impacts gradually decreasing in turn. (2) Mechanism analysis confirms a chain transmission mechanism of “new quality productivity—environmental protection investment—green innovation—the transformation of carbon-intensive industries” at the macro-provincial level. In micro-level carbon-intensive enterprises, a positive U-shaped relationship between new quality productivity and low-carbon transformation of carbon-intensive industries is evident, and the main pathways include increasing low-carbon, energy-saving investment and improving the ESG performance of high-carbon emission enterprises. (3) Advancing transformation is more pronounced in central and western areas, high-carbon areas, non-carbon trading pilot areas, and non-energy-rich ecologically fragile areas. The government and enterprises should take advantage of the development opportunities of new quality productivity and adopt low-carbon behaviors to promote transformational development. Full article

Background: Nutrition literacy, defined as “the skills to comprehend and implement nutrition information into everyday practice”, is a new area of study. Preschool teachers affect children’s perception of nutrition and health and contribute to their nutrition literacy skills. Objective: This cross-sectional study aimed to assess the level of nutrition literacy (NLS-Gr) of preschool teachers. Methods: The research included two stages of cluster sampling in a sample of kindergarten teachers in Greece (Rhodes Island). Nutrition literacy was assessed with the NLS-Gr, the Greek version of the NLS, and adherence to a Mediterranean diet with the MedDiet score. Results: The mean NLS-Gr score was 25.87 (SD ± 2.2) and is considered adequate. The correct answers range from 65.1% to 100%. The MedDiet score was calculated at 33.94 (SD ± 3.8), and no correlation was found between the MedDiet score and the NLS-Gr. The NLS-Gr score of kindergarten teachers was adequate, higher than that of previous research on different populations. Conclusions: The study concluded that adherence to the Mediterranean diet requires improvement, and food waste needs to be reduced. Educators should be empowered through targeted educational interventions to improve their dietary habits and, therefore, enhance students’ health and nutritional behaviors. Further research is needed to contribute to formulating nutrition strategies and policies in kindergarten. Full article

Background: The aging population is increasing, leading to a greater need for home care for older adults, often provided by informal caregivers (ICs). These caregivers face numerous challenges, requiring adequate training and support. Objectives: This study aimed to map the main interventions performed by the Rehabilitation Nursing Specialist in empowering ICs of older adults at home. Methods: A scoping review was conducted following the Joanna Briggs Institute methodology. The search included seven articles published between 2019 and 2024, in Portuguese, English, and Spanish, available in the PubMed e CINHAL Ultimate databases. The descriptors used were (Rehabilitation Nursing) AND (Informal Caregivers OR Caregivers) AND (Elderly OR Aged) AND (mentoring OR Training. Results: The RNS interventions focused on training caregivers in technical skills (e.g., positioning, transfers, hygiene care, feeding, medication administration), preventing caregiver burden, managing behavioral and psychological symptoms of dementia, promoting self-care, and emotional support. Educational programs and the use of technologies (telehealth) were identified as effective strategies. Conclusions: RNS interventions are crucial for enhancing the skills and well-being of ICs, improving the quality of care provided to older adults at home, and reducing caregiver burden. Person-centered care, continuous support, and recognizing the caregiver’s role are fundamental aspects of these interventions. Full article

Blockchain technology empowers decentralized transactions in smart grids, but existing consensus algorithms face efficiency and security bottlenecks under Byzantine attacks. This article proposes the RVR consensus algorithm, which innovatively integrates dynamic reputation evaluation, verifiable random function (VRF), and a weight-driven probability election mechanism to achieve (1) behavior-aware dynamic adjustment of reputation weights and (2) manipulation-resistant random leader election via VRF. Experimental verification shows that under a silence attack, the maximum latency is reduced by 37.88% compared to HotStuff, and under a forking attack, the maximum throughput is increased by 50.66%, providing an efficient and secure new paradigm for distributed energy trading. Full article

Software as a service (SaaS) is a major service model for delivering software to end users through the cloud. SaaS platforms provide their users with cost-efficient, flexible and scalable services that can be available on demand, anytime, and anywhere. Moreover, SaaS empowers software providers to establish recurring revenue and create profitable businesses. However, SaaS can endure high customer turnover due to reasons such as serving a wide range of customers, intense competition and rapid evolution of technology. Maintaining a regular customer base and keeping users engaged is crucial for the survival of a SaaS business. Thus, it is crucial for SaaS providers to identify both the reasons behind users’ engagement and churn of their app towards taking proper actions to retain them in the long term. SaaS data regarding user behavior, subscriptions and system performance can be utilized for deriving insights and identifying patterns to support decision-making for SaaS providers. To this end, the aim of this survey is to review research in data-driven decision support systems in SaaS, identifying current gaps and challenges and highlighting directions for future improvements towards the development of more efficient and intelligent systems. Full article

This paper introduces a novel methodology for subsurface characterization in mineral exploration, through the simultaneous joint inversion of seismic and geoelectrical data. By combining complementary information provided by multidisciplinary geophysical data, the joint inversion yields a more accurate and consistent representation of subsurface properties. Furthermore, the joint inversion algorithm is empowered by dynamic hyperparameter self-adjustment. Hyperparameters are settings or configuration values that control the behavior of the inversion algorithm but are not directly learned from the data. Examples include regularization weights, coupling parameters, learning rates (if using gradient-based methods), and number of iterations. In traditional approaches, these values must be manually selected or tuned, often through trial and error, which is time-consuming and may lead to suboptimal results. Instead, in the approach here introduced, a self-adaptive mechanism monitors the evolution of the cost function and optimization performance, automatically tuning hyperparameters to enhance convergence toward an optimal (global) solution. For the purposes of this preliminary study, the method is tested on synthetic 2D geophysical scenarios featuring resistivity and seismic velocity anomalies representative of potential mineral targets. Results show the effectiveness of the approach in accurately identifying these subsurface anomalies. Finally, we show that this joint inversion technique holds significant promise for mineral exploration, particularly in detecting geological features such as ore bodies and mineralized zones, which can manifest as contrasts in seismic velocity and resistivity. Full article

This narrative review examines adolescents’ perceptions of sustainable dietary characteristics, including local eating, plant-based diets, organic food, and food waste, and how these influence their understanding and behavior. Evidence indicates that adolescents often have simplified conceptions of these practices, which leads to misconceptions. Local food is frequently perceived as inherently more sustainable despite complex factors such as seasonality, production methods, and transportation. Although reducing meat consumption is crucial for environmental impact, adolescents may struggle to understand sustainable protein sources and animal-based foods in various contexts. Although viewed positively, the benefits and limitations of organic food remain poorly understood. Food waste is recognized as significant; however, adolescents often focus on individuals rather than on systemic drivers. Schools play a pivotal role in the promotion of food literacy and sustainable dietary habits. Educational interventions that integrate sustainability into curricula, provide hands-on learning, and engage families can help adolescents to develop critical thinking skills and make informed food choices. Strategies such as promoting a plant-based diet, sourcing local produce, incorporating organic options, and implementing waste reduction programs can create environments that support sustainable eating habits. These efforts must be context-sensitive, culturally relevant, and grounded in understanding food systems. By empowering adolescents to question assumptions, recognize complexities, and take action, schools can cultivate a generation capable of leading the transition towards healthier and more sustainable diets. Full article