Abstract: This study examines how an educational intervention about domestic personal care and perfume products can foster patriotism (cinta tanah air) among Indonesian high school students. A qualitative field study was conducted with 12 female students from four public high schools in Surabaya. Researchers delivered interactive educational sessions and gathered data through observation and interviews. We report that all participants used personal care products daily, yet only a small fraction chose domestic brands. After the educational program, students showed increased awareness and pride in local products. The findings suggest that aligning everyday consumer choices with national values can internalize patriotic sentiments among youth.

Abstract: This study examined the effectiveness of technology-integrated instruction in enhancing EFL students’ critical reading skills within an Indonesian university context. Grounded in concerns about students’ limited critical literacy and the growing emphasis on digital learning in higher education, the research aimed to identify how technology-supported activities could improve students’ ability to analyze arguments, evaluate evidence, and construct informed interpretations of academic texts. Using a qualitative design, the study involved university students engaged in a technology-enhanced reading module that incorporated digital annotation tools, multimedia explanations, and guided online discussions. Data were collected through classroom observations, student reflections, and semi-structured interviews, and analyzed thematically to capture recurring patterns of learning behavior and student perceptions. The findings indicated that technology-integrated instruction provided meaningful scaffolding that fostered deeper engagement with texts and promoted higher-order thinking. Students reported increased motivation and clarity in understanding complex materials when supported by interactive features. However, the results also revealed that some learners required additional time and pedagogical guidance to fully utilize digital tools. Overall, the study contributes to the growing body of research on technology-enhanced literacy by demonstrating the potential of digital platforms to strengthen critical reading skills in EFL settings. The implications suggest the need for intentional instructional design and ongoing digital literacy support to maximize the benefits of technology integration in reading instruction.

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This study develops and validates a psychometric instrument to measure entrepreneurial intention (EI) among secondary school students in Chile. Grounded in the Theory of Planned Behavior, the instrument integrates attitudinal and contextual factors adapted to the school context. Data from 1,402 students were subjected to confirmatory factor analysis, reliability estimation (Cronbach's alpha, composite reliability), and validity procedures (convergent and discriminant validity, variance inflation factor). Results support the instrument's factorial structure and internal consistency, enabling robust assessment of entrepreneurial intention and related educational interventions. The instrument demonstrates solid psychometric properties across most constructs, identifies items for future refinement, and provides practical guidelines for its application in school-based entrepreneurial programs and structural equation modeling. This work contributes a validated tool for both research and evidence-based practice in entrepreneurship education, with direct implications for evaluating and improving educational initiatives targeting entrepreneurial competencies in adolescents.

Abstract: The development of cross-border hydrogen energy value chains involves complex interactions between technological, regulatory, and logistical subsystems. Static assessment models often fail to capture the dynamic response of these coupled systems to external perturbations. This study addresses this gap by proposing the Dual Carbon Cooperation Index (DCCI), a data-driven framework designed to quantify the synergy efficiency of the China-Korea hydrogen ecosystem. We construct a dynamic state estimation model integrating three coupled dimensions—Technology Synergy, Regulatory Alignment, and Supply Chain Resilience—utilizing an adaptive weighting algorithm (Triple Dynamic Response). Based on multi-source heterogeneous data (2020–2024), the model employs Natural Language Processing (NLP) for vectorizing unstructured regulatory texts and incorporates an exogenous signal detection mechanism (GRI). Empirical results reveal that the ecosystem's composite synergy score recovered from 0.38 to 0.50, driven by robust supply chain resilience but constrained by high impedance in technological transfer protocols. Crucially, the novel dynamic weighting algorithm significantly reduces state estimation error during high-volatility periods compared to static linear models, as validated by bootstrapping analysis (1,000 resamples). The study provides a quantitative engineering tool for monitoring ecosystem coupling stability and proposes a technical roadmap for reducing system constraints through secure IP data architectures and synchronized standard protocols.

Abstract: Smartphones have become the backbone of the connected society, reshaping social interactions in a period of adolescence marked by a neuropsychology vulnerability that is sensitive to intensive technological mediation. This study analyzes the relationship between the problematic use of mobile phones and the social and assertiveness skills of adolescents. Through a cross-cutting design, the answers of 1864 adolescents aged between 11 and 21 years old from education centers located in Cordoba (Spain) were analyzed, through a questionnaire that collected sociodemographic variables, the MPPUSA scale, to measure the inadequate use of mobile phones, and the ADCA-1 to assess social skills and assertiveness. The results revealed inadequate levels of mobile phone use and low levels of social skills, with nomophobia and negative consequences as the main risk factors, with the cluster analysis confirming the latter as the main predictor of the level of social development. The findings point to a concerning situation, in which not only does the usage time, but also the quality, have an influence on the psychosocial development of this population group. The application of preventive and educational interventions that address literacy, management of emotions, and the promotion of face-to-face social skills are therefore necessary.

Abstract: Background: Youth from Malaysia’s low socioeconomic communities frequently face chronic instability, limited parental involvement, and restricted access to developmental support. Within such conditions, coaches often assume relational roles extending beyond technical instruction. Methods: This autoethnographic study draws on 20 weeks of longitudinal coaching, reflective journals, and fieldnotes to examine how the coach–athlete relationship evolved into a form of “social fathering” for one low-income youth athlete, Derrick, and how this contrasted with the developmental trajectory of Chia, an athlete from a more stable socioeconomic background. Guided by Nasheeda et al.’s three-layered narrative framework, the analysis integrates personal narrative, thematic interpretation, and sociocultural discourse. Results: Structured adversity—deliberately designed challenges embedded within a trusting relationship—served as a key mechanism for cultivating grit, resilience, and moral reasoning. Father-like practices such as boundary-setting, moral guidance, and life-navigation support compensated for socioeconomic gaps in Derrick’s home environment, whereas Chia’s growth reflected a faster transition toward self-regulated grit due to his more stable support structures. Conclusions: Coaching within disadvantaged contexts functions as relational labour that provides youths with social capital, emotional stability, and developmental resources otherwise inaccessible to them. Implications highlight the need for culturally informed coach-education programmes that integrate relational ethics, adversity-based pedagogy, and contextual awareness of poverty-related challenges.

Abstract: Urban Green Space Per Capita (UGSPC) is one of the oldest and most widely applied indicators in urban planning, providing a measure of green areas in relation to the population size. Despite its century-long application and decades of research, no global systematic review has previously synthesized how UGSPC has been applied, interpreted, and evolved across different contexts. This study aims to fill that gap by conducting the first comprehensive systematic review, following PRISMA guidelines, examining the usage, trends, and effectiveness of UGSPC in both developed and developing countries. Thematic analysis revealed that most studies were published in journals focused on sustainability and environmental science. The results show a surge in publications following the COVID-19 pandemic, reflecting a growing recognition of the importance of urban green spaces for public health and livability. Moreover, 67% of the studies were conducted in developing countries, while 30% of the publications were in developed countries. Higher UGSPC values are generally found in developed cities; however, this was not a rule. Time series studies showed a decline in UGSPC in some developed and developing countries, influenced by factors such as population density, urbanization stage, climate, and economic conditions. Although UGSPC is widely used, most municipalities typically develop their plans based on this measurement. 95% of the included research incorporated additional measurements, including accessibility, social equity, spatial patterns, ecological services, ecosystem benefits, and human health. This study suggests that UGSPC is still used as an indicator in urban planning and policy and integrating it with other indicators can serve as contemporary indicators to capture better equity, functionality, and sustainability in urban environments.

Abstract: This paper introduces the Sextuple Helix Innovation Model as an extension of the Quintuple Helix Innovation Model by Carayannis and Campbell. It considers the understanding of generative AI (GenAI) as a sixth helix of knowledge production in sustainable innovation ecosystems. Accordingly, the knowledge economy of GenAI will be discussed in the context of innovation processes of cultural and creative industries. While GenAI is largely described in social discourses as a tool that potentially replaces human creativity and thus destroys jobs, this paper discusses GenAI as an entity with a specific knowledge economy that contributes to creative innovation processes in exchange with the five established helices of science, politics, economy, the media- and culture-based public and the natural environment of societies. With the help of a scoping review, a comprehensive evaluation of academic literature from the fields of creative industries, cultural policy, and innovation research, based on a constructivist epistemological approach and knowledge economy theory, confirmed that the positioning of GenAI as an epistemic actor in the Sextuple Helix Innovation Model reframes and redefines discourses beyond the prevailing narratives of disruption and regulation.

Abstract: Background: The rapid integration of digital technologies into everyday life has raised widespread concerns regarding the psychological consequences of prolonged screen exposure. While prior studies have shown associations between screen time and mental health issues, findings have often been inconsistent, largely due to simplistic linear models and limited behavioral contextualization. This study aims to address these gaps by evaluating how various forms of screen use, lifestyle behaviors, and psychological indicators jointly influence mental wellness in a population of digitally active individuals. Methods: We analyzed a self-reported dataset of 400 participants containing detailed metrics on screen use (mobile, TV, laptop), sleep quality, stress, productivity, mood, and other lifestyle behaviors. Statistical analyses included Pearson correlation, multivariate linear regression, and K-means clustering with Principal Component Analysis (PCA) to uncover behavioral subtypes. Predictors of mental wellness were identified through standardized regression coefficients, and clusters were interpreted based on their psychological and digital usage profiles. Results: Stress emerged as the strongest negative predictor of mental wellness (β = −10.69), followed by sleep quality (β = +5.92) and productivity (β = +4.72). Contrary to prevailing assumptions, total screen time and leisure screen use had minimal direct impact on wellness once mediating variables were included. Clustering revealed three distinct digital behavior phenotypes: (1) Balanced and Active Users, (2) Leisure-Heavy High-Stress Users, and (3) Burnout-Prone Professionals. These profiles showed differing wellness outcomes sharply and validated the multidimensional nature of digital health risk. Conclusion: Mental wellness in digital contexts is best understood through a multivariable lens that accounts for stress, sleep, and self-regulatory behaviors rather than raw screen time alone. These findings challenge traditional screen time metrics and highlight the need for personalized, context-aware interventions. This study offers a replicable computational framework for identifying behavioral risk profiles and supports a paradigm shift from screen avoidance to digital self-optimization.

Abstract: This conceptual paper proposes a purpose-driven experiential marketing framework for film-inspired destinations, integrating sustainability and emotional engagement into destination management. The model comprises five interconnected dimensions — integrated experience, branding, people, emotional touchpoints and processes — articulated through purpose-driven marketing principles and aligned with relevant Global Reporting Initiative (GRI) indicators. This alignment reinforces the model’s capacity to support ethical, transparent, and sustainability-oriented destination strategies. The framework was developed through an interdisciplinary literature review and is illustrated with insights from an exploratory case study of Monsanto, a rural Portuguese village recently featured in HBO's House of the Dragon. Semi-structured interviews were conducted with a purposive sample of local stakeholders, including tourists, residents, entrepreneurs, and institutional representatives, and analysed thematically to assess the model’s relevance and practical applicability. The findings suggest that emotional engagement, co-creation, and territorial authenticity play a central role in shaping memorable, film-related tourism experiences that align with the destination’s purpose and value creation. The study also highlights the strategic importance of storytelling, audiovisual narratives and stakeholder collaboration in strengthening place identity and achieving sustainable differentiation. Although the study is exploratory in scope, the framework offers practical guidance for destination management organisations (DMOs), cultural programmers, and creative industry actors. The article concludes by identifying avenues for future research, including cross-regional validation, digital experimentation, and the quantitative assessment of experience dimensions.

Abstract: This study investigates the impact of the Slow Food movement on sustainability and local gastronomy in North Cyprus. After reviewing key concepts such as sustainable gastronomy, local food heritage and regional practices, the research focuses on the five Cittaslow regions of North Cyprus and the development of Slow Food activities since 2013. Using a qualitative design with purposive sampling, semi-structured interviews were conducted with twelve participants, including local producers, chefs and regional administrators. The study identifies the challenges faced by local businesses, the role of Slow Food in promoting sustainable practices and the ways regional actors contribute to cultural and environmental preservation. Findings highlight both progress and gaps, offering practical recommendations and outlining areas for future research. As one of the few studies examining Slow Food in North Cyprus, the research provides valuable insights and contributes significantly to the existing literature.

Abstract: The aim of this study is to evaluate science teacher candidates' knowledge and views on biotechnology education. The research was conducted with the phenomenology pattern, one of the qualitative research designs. In the study, quantitative data were collected using the "biotechnology knowledge scale" data collection tool, while qualitative data were collected using the "semi-structured interview form". The sample of the study was science teaching students studying in the fall semester of the 2024-2025 academic year. While the "biotechnology knowledge scale" was ap-plied to a total of 283 students, the “semi-structured interview form" was applied to 36 students. As a result of the research, most of the participants answered yes to the question asked about getting biotechnology education. To the question asked about whether science teacher candidates find biotechnology useful, most of the participants answered that they find it useful. Among the answers to the question asked about the benefits of biotechnology, benefits in the field of health, benefits in the field of agriculture and animal husbandry, quality of life and I do not find useful answers to the question, most of the participants answered in the field of health. Among the answers given to the questions about the harms of biotechnology, ethical issues, biological weapons, ecosystem degradation, threatening health and most of the participants answered the question as ethical issues. Among the answers given to the question asked to evaluate the views of science teacher candidates on the importance of educating teachers-biologists in biotechnology education, professional ethics and responsibility, increasing quality, and training qualified teachers, most of the participants answered the question as professional ethics and responsibility.

Abstract: Background: While Behavioral Activation (BA) is a validated and widely used treatment for depression, a subset of cases exhibits a paradoxical failure: patients demonstrate insight, express motivation, and engage in therapy but fail to initiate any behavioral change. Existing behavioral and cognitive models offer limited structural explanations for such ignition failure. Objective: This paper applies Cognitive Drive Architecture (CDA), an emerging structural field grounded in Lagunian Dynamics and governed by Lagun’s Law of Primode and Flexion Dynamics, to reinterpret a well-documented BA treatment failure. The goal is not to critique BA but to examine whether ignition failure may reflect deeper architectural misalignment rather than motivational deficit. Method: Using secondary analysis, the clinical case of “Karen” (Hopko et al., 2011) is reinterpreted through the CDA framework. Six structural variables (Primode, CAP, Flexion, Anchory, Grain, and Slip) were mapped to observed behaviors, therapeutic responses, and contextual factors. Latent Task Architecture (LTA), a domain-specific extension of Lagunian Dynamics, is used to model task readiness and resistance layering. Results: Karen’s persistent non-initiation is structurally explained by a configuration of near-zero Primode, low CAP, poor Flexion, weak Anchory, high Grain, and minimal Slip. This Drive profile mathematically predicts near-zero behavioral output despite motivation or understanding, resolving the paradox without pathologizing the patient. Conclusion: CDA reframes treatment nonresponse not as resistance or noncompliance, but as a predictable structural outcome under specific internal configurations. This suggests a future direction in which therapeutic approaches are selected based on drive architecture assessment rather than symptom profiles alone. Implications for pre-intervention calibration, clinical modeling, and the structural classification of treatment resistance are discussed.

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This article identifies a terminological misrepresentation in the expression “small gatherings cancellation”—ranked by Haug et al. as the most effective non-pharmaceutical intervention during the COVID-19 pandemic. Corpus-based and theoretical analyses demonstrate that small gathering conventionally denotes a planned or spontaneous social event, while the predicate cancellation reinforces this event-based frame. Consequently, the phrase fails to capture the intended reference to restrictions on simultaneous presence in commercial or professional settings. Drawing on cognitive-linguistic theory and institutional usage from the WHO and CDC, this paper shows how such misrepresentation may trigger unintended conceptual frames, leading to interpretive ambiguity in both scholarly and policy contexts. Three alternatives are proposed to achieve better semantic alignment and enhance terminological precision and communicative clarity in future public-health discourse.

Abstract: Industry 5.0 challenges higher education to integrate human-centred and sustainable uses of artificial intelligence, yet current deployments rarely connect generative AI, neuroadaptive sensing and governance in a single framework. This article introduces Nested Learning as a neuro-adaptive ecosystem design in which generative AI agents, IoT infrastructures and multimodal deep learning orchestrate instructional support while preserving student agency and a “pedagogy of hope”. We present an exploratory two-phase mixed-methods study as an early empirical illustration of this proposal. First, a neuro-experimental calibration with 18 undergraduate students used mobile EEG while they interacted with ChatGPT in problem-solving tasks. Second, a field implementation at a university in Madrid involved 380 participants (300 students and 80 lecturers), embedding the Nested Learning ecosystem into regular courses. Data sources included EEG (P300) signals, interaction logs, self-report measures of self-regulated learning, emotional experience and ethical concerns, and semi-structured interviews. In the lab phase, P300 dynamics aligned with key instructional events, providing preliminary evidence that the neuro-adaptive pipeline is sensitive enough to justify larger-scale studies. In the field phase, 87% of students reported higher engagement and 73% perceived improved learning outcomes, while qualitative data highlighted greater clarity, adaptive support and cognitive safety, alongside concerns about privacy and data sovereignty. Perceived Nested Learning and neuro-adaptive adjustments were moderately associated with enhanced self-regulatory strategies (correlations up to r=0.57, p<0.001). We argue that, under robust ethical, data-protection and sustainability frameworks, Nested Learning can strengthen academic resilience, learner autonomy and human-centred uses of AI in higher education.

Abstract: Human-AI collaboration requires a shared set of operational concepts that can be interpreted across biological and artificial substrates. Traditional terms used to describe cognitive or emotional states - such as "meaning", "anxiety", or "motivation" - lack computable grounding, producing a structural gap that prevents reliable joint inference, alignment, and action selection. Recent developments in information theory, predictive processing, and network control theory show that many of these psychological descriptors correspond to measurable features of information flow: prediction error topology, information bottlenecks, state-space curvature, and metastable coordination regimes. These convergences indicate that subjective vocabulary can be replaced with substrate-independent structural variables. This paper introduces an operational language patch for the Operational Coherence Framework (OCOF), defining five such variables: Structural Magnitude (SM), Structural Predictive Fluctuation (SPF), Structural Suppression (SS), Structural Gain Rate (SGR), and Human-AI Coherence (HA-C). Each variable is grounded in information mechanics and provides a computable signal for analyzing cross-substrate coordination. By translating subjective terminology into structural variables that can be estimated, perturbed, and optimized, this framework aims to establish a rigorous lexicon for describing the coupling dynamics between human and artificial agents. The proposed patch enables reproducible analysis and forms the basis for OCOF v1.2's expanded operational semantics.

Abstract: Developing mental health apps is a complex task that requires co-design, creativity, and reconciliation between clinical and technological priorities, while facing barriers related to ethics, privacy, costs, and team limitations. This work proposes a structured framework derived from the authors’ experience in developing the webapp “Psychosocial Rehab App”, created and validated by specialists, with high usability, and led by mental health professionals. This is a critical-reflective experience report based on SQUIRE, referring to a doctoral project initiated in 2023, with partial completion in 2025 and final implementation expected in 2027. The accumulated know-how enabled the construction of the Framework for the Development of the webapp “Psychosocial Rehab App”: Actions and Recommendations, composed of: Planning, Requirements Gathering, Prototyping, Prototype, Development with Alpha Validation, Beta Validation, Implementation, and Gold Validation. Thus, this work consolidates a methodological and practical trajectory that can guide professionals and researchers in creating robust, safe, and effective clinical technologies, contributing to the advancement of digital mental health.

Abstract: In recent years, Zhu Zhengfu, a deputy to the National People's Congress, has consistently advocated for issues such as ‘abolishing the crime of provoking trouble’, ‘sealing minor criminal records’, and ‘sealing public security violation records for drug use’. His proposals have generated significant influence in both public discourse and legislative debates. On the surface, these proposals appear to champion ‘rights protection’ and ‘humanitarian concerns.’ However, when re-examined within the frameworks of Marxist jurisprudence, Xi Jinping Thought on the Rule of Law, and the overall national security outlook, they reveal a series of concerning issues in their logical structure, value orientation, and security perspective. This paper, while clarifying online rumours and adhering to factual foundations, focuses solely on Zhu Zhengfu's publicly available and verifiable legal propositions for analysis. It critiques these from three dimensions: logical reasoning, national security implications, and ideological roots. Furthermore, it proposes a tiered reform pathway for optimising the crime of provoking trouble and the systems governing prior convictions and records under the comprehensive national security outlook. The article contends that several of Zhu Zhengfu's assertions exhibit dualistic reasoning in logic, display pronounced formal liberal rights-centrism in values, and underestimate systemic risks within complex social structures in security perspectives. His discourse system is highly isomorphic with Western legal liberalism, creating significant tension with the path of socialist rule of law with Chinese characteristics in the new era. Subjecting the rule-of-law discourse of NPC deputies to public scrutiny from the perspectives of the people's stance and national security is essential to upholding the people's congress system and the overall national security outlook.

Abstract: Under ongoing climate change, environmental conditions in complex global arid and semi-arid ecosystems are rapidly deteriorating. According to NASA observations, the average annual air temperature in the northeastern regions of Kazakhstan and the Republic of Uzbekistan has increased by +1.03°C over the past 40 years (1984–2024). Forecasts derived from a linear regression model indicate that if the current warming trend continues, by 2070 the average annual temperature is expected to rise by an additional +1.47°C, reaching approximately 7.00°C. This projected warming suggests further intensification of environmental challenges in arid regions, including groundwater depletion, soil salinization (degradation), and heightened risks to food security. Consequently, equipping younger generations with high-quality knowledge based on clear analytical algorithms, and integrating complex ecological issues with modern educational technologies, requires innovative and effective methodological approaches. This study responds to this need by introducing the Eco-Decision Spiral Model (EDSM). Empirical findings show that students’ acquisition and practical application of relevant knowledge through the EDSM reached an average of 87.04%, while the comparative WSWNW model demonstrated a more limited effectiveness of 75.48%. The model’s integration with Benjamin Bloom’s classic cognitive taxonomy, STEM and inquiry-based learning principles, Herbert Simon’s bounded rationality and Scientific Decomposition approach, Howard T. Odum’s systems ecology concept, and several other foundational educational frameworks plays a significant role in strengthening learners’ ability to understand, critically analyze, and independently make decisions regarding complex ecological systems. Moreover, the model is highly aligned with international standards such as UNESCO ESD, OECD Education 2030/2040, and the NGSS. This compatibility not only supports the applicability of EDSM in global environmental education and scientific research, but also demonstrates its methodological value in advancing the goals defined within these international initiatives.

Abstract: Urban renewal research has long relied on expert-led assessments and fragmented indicators, yet lacks scalable, perception-aware frameworks that can translate street-level conditions into interpretable renewal strategies. To bridge these gaps, this study proposes a vision–language model (VLM) based method to identify the potentially renewable areas across the Hongshan Central District of Urumqi, China. Specifically, we collected 4,215 panoramas and used multiple VLMs to measure six perceptual scores (i.e., safety, liveliness, beauty, wealthiness, depressiveness, and boringness) together with textual descriptions. The best-performing model, selected by correlation with a 500-respondent perception survey, was used as the final analysis to identify the renewal area. Then, we conducted spatial statistics and text mining (eight semantic themes) to reveal the spatial patterns and semantic topics for proposing renewal strategies. The results show that: 1) VLMs have a high consistency with humans in evaluating the spatial perception of six dimensions; 2) four renewal priority tiers were identified, with high-score areas concentrated on Tianshan District Government Residential Quarter, Mashi Community, Heping South Road, etc.; and 3) Semantically, low-score areas such as Hongshan Road, Binhe Middle Road, Wuxing South Road, Huhuo Line, etc. emphasize infrastructure, safety, street level and order. We conclude that VLMs add value not only via scalable assessment but also through explanatory language evidence that directly supports tiered renewal and public communication. This work provides a data-driven and interpretable evaluation framework for urban renewal decision-making, facilitating precision-oriented and intelligent regional urban regeneration.