Between Readiness and Reality: EFL Teachers’ Deep Learning Implementation in Indonesia’s Merdeka Curriculum Amid Remote-Region Constraints

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This study investigates the readiness of EFL teachers in Toraja, a geographically remote region of South Sulawesi, Indonesia, to implement the Deep Learning approach within Indonesia’s Merdeka Curriculum, and examines the systemic, pedagogical, student-related, and infrastructural challenges they encounter during implementation.A sequential explanatory mixed-methods design was employed, involving six purposively selected junior secondary school EFL teachers. Quantitative data were collected through a validated 20-item questionnaire measuring four readiness dimensions (pedagogical, technological, psychological, and institutional) on a five-point Likert scale, analyzed using descriptive statistics. Qualitative data were gathered through in-depth semi-structured interviews and analyzed using reflexive thematic analysis within Miles and Huberman’s interactive framework. Quantitative results revealed Very High overall teacher readiness (M = 4.28, SD = 0.470), with pedagogical and psychological readiness achieving Very High categorization (M = 4.40 each) and technological and institutional readiness achieving High categorization (M = 4.20 and 4.13 respectively). Four of six teachers (66.7%) were classified as Very High readiness. However, qualitative analysis identified four major challenge themes that systematically constrain implementation: (1) systemic institutional constraints inadequate sporadic professional development, rigid curriculum structures, and heavy administrative burden; (2) pedagogical instructional difficulties severe time constraints, challenges implementing inquiry and reflection phases, and authentic assessment design gaps; (3) student-related barriers uneven readiness, limited EFL vocabulary, passive learning habits, and cultural deference norms; and (4) infrastructure and technological limitations limited shared devices, unstable internet, and forced pedagogical regression reducing deep learning quality by up to 50%. This study reveals a critical readiness-reality gap: teachers demonstrate high internal readiness, yet face substantial external constraints that systematically undermine implementation quality. The findings contribute evidence-based insights to the emerging literature on Deep Learning implementation in under-resourced Indonesian EFL contexts and offer targeted recommendations for teachers, school leaders, district authorities, and national policymakers to achieve sustainable implementation in Toraja and comparable remote regions.​

Integrating Ethnopedagogical Approaches in English Vocabulary Learning: A Qualitative Study from Toraja, Indonesia

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learning and identifies the challenges teachers face in implementing these culturally responsive approaches in the Toraja context, Indonesia. Employing a qualitative research design with thematic analysis following the Miles and Huberman interactive model, data were collected through in-depth interviews with English teachers regarding the integration of ethnopedagogical approaches in vocabulary instruction. Findings reveal that ethnopedology significantly enhances student motivation across eight dimensions: increased learning attractiveness and information retention, enhanced overall motivation, greater active participation, increased confidence, improved long-term vocabulary retention, stronger sense of ownership and cultural pride, increased perseverance, and fostered independent learning habits. Teachers face ten substantial implementation challenges, including limited competence in integrating local wisdom, insufficient contextual materials, absence of evaluation standards, time constraints, difficulty balancing cultural content and linguistic targets, and assessment difficulties. Despite these challenges, teachers employ ten effective strategies including the use of authentic cultural objects, storytelling, discovery learning, cultural portfolios, and collaboration with community experts. This study contributes to the growing body of literature on culturally responsive language teaching by providing empirical evidence from an under-researched Indonesian context, offering practical implications for teachers, curriculum developers, and policymakers.

Characterization and Comparison of Interaction of Capsaicin with Hemoglobin and Bovine Serum Albumin Using Circular Dichroism

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Capsaicin, the primary pungent compound in chili peppers (Capsicum species), exhibits a wide range of pharmacological and biological activities. Investigating its interaction with proteins is crucial for understanding its behaviour in biological systems and potential physiological effects. This study explores the binding of capsaicin with two model proteins, hemoglobin (Hb) and bovine serum albumin (BSA), using circular dichroism (CD) spectroscopy to evaluate structural changes induced by ligand interaction. Far-UV CD spectra of Hb and BSA reveals characteristic negative bands around 208 nm and 222 nm, consistent with their predominantly α-helical secondary structures. Upon titration with capsaicin, significant changes in the intensity of these bands were observed, indicating partial alterations in α-helical content and conformational adjustments in both proteins. These structural modifications suggest that capsaicin binds to Hb and BSA, likely through hydrophobic interactions and potential hydrogen bonding with specific amino acid residues. Comparative analysis showed differences in the extent of conformational change between Hb and BSA, reflecting variations in their binding affinity and interaction modes with capsaicin. The results highlight the impact of capsaicin on protein stability and secondary structure and demonstrate the utility of CD spectroscopy as an effective tool for probing protein–ligand interactions. This study provides valuable insights into the molecular mechanisms of capsaicin–protein binding, which may inform its physiological and therapeutic relevance.

Ikigai and Entrepreneurship: A Systematic Literature Review of Purpose-Driven Ventures and Sustainable Performance

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This systematic literature review examines the convergence of Ikigai — the Japanese philosophical notion of purposeful living — with entrepreneurship, integrating evidence from peer-reviewed journals, practitioner literature, and multidatabase academic sources from 2016 to 2026. The review utilises a PRISMA-adapted protocol on a final corpus of 42 key sources, incorporating additional citations from Scopus, Google Scholar, and CrossRef databases to delineate the current state of knowledge in this nascent field. The analysis reveals three predominant thematic clusters: (1) the psychological underpinnings of Ikigai and their implications for entrepreneurial resilience and well-being; (2) the strategic incorporation of Ikigai principles into organisational management and sustainable performance; and (3) persistent conceptual discussions regarding cultural portability, measurement validity, and definitional limits. The evidence collectively indicates that purpose-driven founders, aligned with Ikigai principles, exhibit significantly greater psychological resilience, lower operational volatility, and more sustainable financial trajectories than their solely profit-driven counterparts. The review identifies a substantial gap in founder-centric, psychometrically sound empirical research and proposes three testable hypotheses to guide subsequent scholarly investigations. Quality appraisal was conducted using the Mixed Methods Appraisal Tool (MMAT), ensuring that all 42 included sources met a minimum threshold of methodological rigour. The results have direct implications for entrepreneurial educators, startup ecosystems, and policymakers seeking to encourage more sustainable, people-centred approaches to new venture creation.

Themes, Topics, and Structure of Chivalrous Detective Novels in Southern Vietnam during the Early 20th Century

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This study examines the distinctive features of theme, content, and narrative structure in early 20th-century South Vietnamese knightly detective novels. The question posed is: how are theme, content, and narrative structure expressed? The study primarily employs a careful reading of texts, combined with systematic classification and analysis of relevant texts. Furthermore, a synthetic analysis method is applied to generalize key patterns and identify specific structural and thematic characteristics of the genre. The results show that South Vietnamese knightly detective novels exhibit a unique convergence of Western detective novel models and indigenous moral traditions, particularly the chivalrous and generous spirit of the South Vietnamese people in the early 20th century. Their themes and content often revolve around justice, morality, and social order, while the narrative structure integrates both traditional and modern elements. In short, this genre represents a fusion of indigenous and Western traditional genres and cultures. This demonstrates that the spirit of learning without hesitation is a recurring spirit throughout the Vietnamese tradition.

Integrating Social-Emotional Education (SEL) into Steam Education to Develop Empathy in 5-6 Years Old Preschool Children

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The rapid development of artificial intelligence and digital transformation is placing new demands on early childhood education; the goal of early childhood education is not only to develop cognitive abilities but also to comprehensively develop humanistic qualities and competencies in children, in which empathy is considered a core component of socio-emotional competence. However, in reality, the development of these competencies in early childhood education still faces many limitations and lacks systematic and effective integrated approaches. This article aims to analyze the theoretical basis and clarify the mechanism for developing empathy in 5-6 years old preschool children through the integration of socio-emotional education (SEL) in STEAM education. The study uses a method of analyzing and synthesizing literature from the fields of developmental psychology, socio-emotional education, and STEAM education to build an integrated theoretical framework. The research results show that empathy can be effectively formed and developed through three main mechanisms: experiential learning, social interaction, and human-centered problem-solving in STEAM activities. Simultaneously, the research also points to the strong link between SEL and STEAM in the holistic development of children’s abilities. This paper contributes to supplementing the theoretical basis for integrating SEL into STEAM education and proposes directions for organizing activities to enhance the effectiveness of empathy development in preschool children in the current educational context.

TRAINER – A Content-Based Recommender System of Training Workouts and Nutritional Diets for Fitness Enthusiasts

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The TRAINER system is a personalized health and fitness solution developed for the Fitness Zone Fitness Center in Antipolo, Philippines, to address the shortcomings of generic, “one-size-fits-all” training programs. By utilizing a content-based recommender system driven by machine learning, the platform integrates individual user profiles—including fitness levels, personal goals, and dietary preferences—with a curated repository of workouts and nutritional plans. The system features a web-based interface for real-time data collection and progress tracking, employing a continuous feedback loop to ensure recommendations remain dynamic and adaptive. Ultimately, TRAINER seeks to enhance client adherence and health outcomes by providing data-driven, context-aware guidance that bridges the gap between limited instructor availability and the diverse needs of fitness enthusiasts.

Exemplary Model of AI-Supported Adaptive Optimization Energy Flow Control in Smart City Microgrids: A Simulation-Based Scenarios

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The paper focuses on the possibilities for developing a model for adaptive control of electricity flows in urban microgrids using AI support into the Internet of Things networks.  The goal is the requirement for smarter, more adaptive and sustainable methods in controlling local energy systems. This is critical for distributed generation and the growing incorporation of renewable energy resources. The study is conceptual in nature and aims to develop an integrated model that combines physical energy infrastructure, IoT-based data acquisition, the analytical capabilities of artificial intelligence, and a logic for adaptive real-time decision-making. It is analyzed the theoretical foundations of adaptive management in microgrids, the design of model development of multilayered architecture, and the interaction between physical and information flows. Particular attention is given to the role of intelligent monitoring devices, forecasting and optimization algorithms, as well as the coordination between local generation, storage, consumption, and exchange with the main grid. The proposed model is analyzed through comparison with traditional, optimization-based, and AI-driven models discussed in the scientific literature, and it is argued that the integration of AI and IoT enables higher adaptability, improved load balancing, more efficient use of local energy resources, and better integration of renewable energy sources in the urban energy environment. The proposed model provides a conceptual framework for the intelligent management of electricity flows in urban microgrids, emphasizing its potential for further development and application in sustainable energy systems.

Decarbonization of the Cheese Making Industry on the Island of Crete, Greece

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Cheese making is a well-developed activity in the island of Crete, Greece since a long time ago. It is mainly based on local sheep’ and goats’ milk while the small-scale cheese making plants in Crete use conventional energy sources to meet their heat and electricity demand. However, solar energy and solid biomass are abundant in the island and they are currently used for heat and power generation. Elimination of carbon emissions in cheese making plants in Crete can be achieved with the replacement of grid electricity and fossil fuels used with local renewable energies such as solar energy and solid biomass. It has been estimated that complete elimination of the operational carbon emissions due to energy use in a small-size cheese making plant in Crete with annual capacity 120 tons cheese can be achieved with the installation of a solar photovoltaic system at 88 kWp for electricity generation and the annual use of 62.86 tons of olive kernel wood for heat production. Additionally, solar thermal systems and high efficiency heat pumps can be used for heat and cooling production. The abovementioned sustainable energy sources and technologies are mature, reliable, cost-efficient and they are currently used in Crete in various sectors. The results of the present study could be useful to all stakeholders of the cheese making industry in the island.

Hydrometallurgical Recovery of Rare Earth Elements from Metallurgical Slags (2020–2026): A Critical Review

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Metallurgical slags generated from ironmaking, steelmaking, ferroalloy production, and molten salt electrolysis are increasingly recognized as secondary resources for critical raw materials, particularly rare earth elements (REEs) such as scandium, yttrium, and light REEs, which are incorporated into complex silicate, aluminate, and fluoride phases formed at high temperatures. This review critically evaluates hydrometallurgical routes for REE recovery across a wide range of slag systems, including blast furnace, basic oxygen furnace, electric arc furnace, bauxite residue–derived, FCC catalyst, and molten salt electrolytic slags, covering direct leaching approaches (acidic, alkaline, and ammoniacal), hybrid roast–leach processes (sulfation, chlorination, and alkali roasting), and downstream separation techniques such as selective precipitation and solvent extraction. Particular emphasis is placed on the role of slag mineralogy, phase assemblage, and glassy matrices in controlling leaching kinetics, selectivity, and impurity co-dissolution, with silicate-rich slags identified as the most challenging systems due to their polymerized structure, which limits reagent accessibility and often requires thermal pretreatment to achieve recoveries above 80–90%, typically at high reagent consumption (>50–300 kg/t). Comparative evaluation reveals that reported performance is frequently dominated by recovery metrics, while key parameters such as selectivity, reagent intensity, and process integration remain underreported, such that high extraction efficiencies do not necessarily translate into industrial feasibility. The main limitations across existing approaches include silica gel formation, extensive co-dissolution of matrix elements, and the generation of secondary residues, all of which negatively impact process stability and economic viability; moreover, most reported systems remain constrained by poor selectivity, high reagent intensity, and lack of continuous pilot-scale validation, limiting their industrial transferability. Future progress, therefore, depends on shifting from isolated process optimization to integrated, mineralogy-driven process design, supported by reduced reagent consumption, simplified separation flowsheets, and validation under industrially relevant conditions, positioning metallurgical slags as strategic secondary resources capable of supporting diversified and resilient REE supply chains within circular economy systems.