Encyclopedia doi: 10.3390/encyclopedia6100212

Authors: Askhat Makhmetov Arstan Satanov Assel Myrzakhmetova Yevgeniya Matorina

Civic education has expanded from nationally bounded instruction about institutions and participation into a diverse field encompassing global citizenship, sustainability, digital life, and identity formation. Yet the international indexes through which this expansion is commonly mapped may reproduce geographic and linguistic inequalities. This bibliometric review maps 4954 records retrieved from the Web of Science Core Collection for 1975 to 24 August 2026 examines Central Asia’s visibility within that English-dominant corpus. Performance analysis and thematic mapping were conducted in R using Bibliometrix and Biblioshiny. Because exported cited-reference metadata were incomplete, conceptual change was examined through author keywords and title terms rather than citation networks. Publication output grew at an annual rate of 12.94%, with marked acceleration after 2005; the United States and the United Kingdom were the most frequently represented countries in author-affiliation metadata. A manual screening identified 12 records with Central Asian institutional affiliations, but distinguished that only eight of these substantively focused on the region. Thematic evolution indicated increasing attention to global citizenship, education for sustainable development, and digital citizenship, alongside continuing concern with participation, identity, students, and schools. Central Asian country names and regional identity terms did not appear among the displayed trend topics. This pattern indicates limited visibility in the retrieved corpus, not an absence of regional knowledge. Future research should use multilingual, multi-database corpus construction and comparative school-level studies that bring Central Asian experience into international theory and evidence.

Encyclopedia doi: 10.3390/encyclopedia6100211

Authors: Rungthip Kunthom Ploypailin Milin Saengdet Upsorn Boonyang Sakchai Laksee Masafumi Unno

The repair of critical bone defects remains a substantial clinical challenge. A regenerative material must support osteogenesis, provide appropriate mechanical function, and degrade at a rate compatible with tissue formation. Hydroxyapatite (HA) is osteoconductive and chemically similar to bone mineral, but its brittleness and slow resorption limit its use as a stand-alone load-bearing material. Silsesquioxanes, particularly polyhedral oligomeric silsesquioxanes (POSS), provide molecularly defined silicon–oxygen frameworks with modifiable organic substituents. These can be incorporated as fillers or covalent network components. This review critically evaluates silsesquioxane-based biomaterials for bone regeneration. It distinguishes direct evidence from HA-containing systems from mechanistic analogues. These analogues include silicate-substituted HA, bioactive glass, dental POSS composites, and related polymer–POSS materials. Sol–gel processing, in situ mineralisation, particle incorporation, surface grafting, and network formation are assessed in relation to interfacial bonding, apatite nucleation, mechanical behaviour, and degradation. Current evidence indicates that reinforcement depends on cage functionality, dispersion, loading, matrix chemistry, and interfacial integration. Direct evidence that implanted HA–POSS systems release orthosilicic acid at biologically active concentrations remains unavailable. Cross-system comparisons further show that reported mechanical values cannot be ranked without accounting for physical form, porosity, test mode, and environmental conditions. The principal translational barriers are (i) the scarcity of load-bearing in vivo studies, (ii) uncertain degradation-product fate, and (iii) sterilisation sensitivity in some POSS-modified polymers. Further barriers are (iv) limited manufacturing standardisation and (v) the absence of clinically validated HA–POSS implants. The most defensible rationale for these hybrids is therefore their capacity for multifunctional interfacial design rather than universal mechanical superiority.

Encyclopedia doi: 10.3390/encyclopedia6100210

Authors: Marcos Komodromos

Digital entrepreneurship has increasingly become an ecosystem phenomenon in which digital infrastructure, human capital, innovation capacity, institutional support, finance, internationalization, sustainability, and digital resilience interact to shape entrepreneurial development. However, existing research remains fragmented and provides limited guidance for systematically assessing the maturity of national digital entrepreneurial ecosystems, particularly in small economies. This study develops the Digital Entrepreneurship Ecosystem Assessment Framework (DEEAF), a multidimensional conceptual framework integrating eight interconnected dimensions into a unified model for assessing ecosystem maturity. The authors developed the framework through a structured synthesis of the literature on entrepreneurial ecosystems, digital entrepreneurship, innovation systems, institutional economics, digital transformation, sustainability, and resilience. The study also proposes using the Analytic Hierarchy Process (AHP) to establish dimension weights and the Digital Entrepreneurship Ecosystem Index (DEEI) to support future empirical assessment and benchmarking. Cyprus is used as an illustrative small-economy context through which the framework’s relevance and practical applicability are examined. The conceptual analysis indicates that digital entrepreneurial performance cannot be understood through isolated indicators because weaknesses in infrastructure, skills, finance, innovation, institutions, internationalization, sustainability, or resilience can constrain the wider ecosystem. DEEAF contributes to the literature by integrating these dimensions within a single assessment architecture and by linking conceptual ecosystem analysis to a future measurement mechanism. The framework remains conceptual and requires empirical validation, expert-based AHP weighting, and implementation using national-level indicators.

Encyclopedia doi: 10.3390/encyclopedia6100209

Authors: Carla Giuliana Guanilo Pareja Lidia Ysabel Pareja Pera Andrés Arias Lizares Lupe Marilu Huanca Rojas Henri Emmanuel López Gómez Zoila Rosa Díaz Tavera Clara Patricia Almonte Andrade Fernando Martin Ramirez Wong Wanda Marina Román-Santana Carmen Mata-de-Salcedo Judith Martínez-Alonzo

Generative artificial intelligence is increasingly being adopted in doctoral education to support writing, literature synthesis, translation, feedback, research planning, and administrative work. While emerging scholarship has examined generative AI in higher education, academic integrity, and student writing, its specific implications for doctoral supervision remain comparatively underexplored. This review argues that generative AI should not be understood merely as a technical aid, but as a socio-technical force that may reshape ethical boundaries, feedback practices, doctoral student agency, and supervisory relationships. Drawing on literature from doctoral education, supervision studies, academic writing, feedback literacy, and AI-mediated learning, the review examines three interrelated thematic areas of AI-augmented doctoral supervision. First, it considers ethical issues related to authorship, originality, academic integrity, transparency, privacy, confidentiality, bias, data protection, and overdependence. Second, it analyses how generative AI may influence feedback preparation, interpretation, timing, and dialogic use in doctoral writing and research development. Third, it explores implications for supervisory relationships, particularly trust, power, responsibility, emotional support, and autonomy. The review also discusses institutional implications, including AI literacy, supervisor development, doctoral policy, and responsible use guidelines, and positions generative AI as a human-centred support mechanism rather than a substitute for supervisory judgement, ethical responsibility, or relational mentoring.

Encyclopedia doi: 10.3390/encyclopedia6100208

Authors: Alev Erarslan

Rural cultural landscapes are shaped by the long-term interaction between natural environmental conditions and human activities, reflecting local settlement patterns, architectural traditions, production practices, and socio-cultural values. The rural cultural landscape of Gökçeada (Imbros) is represented particularly by its five historic Orthodox Christian Greek villages—Tepeköy (Agridia), Zeytinliköy (Aya Todori), Eski Bademli (Gliki), Dereköy (Skinudi), and Kaleköy (Kastro). Their landscape character is defined by the interrelationship between the island’s natural setting, compact hillside settlements, vernacular stone architecture, agricultural and productive landscapes, public and communal spaces, and continuing socio-cultural practices.

Encyclopedia doi: 10.3390/encyclopedia6100207

Authors: Matthias Ripp Rayee Metha

Emotions are relatively brief, object-directed affective episodes that arise when a person appraises an event, place, object, or memory as relevant to their concerns, and that unfold across several coordinated components: cognitive appraisal, physiological change, motivational and action tendencies, motor expression, and subjective feeling. Emotion is distinguished from the broader, longer-lasting and often objectless state of mood, from core affect (the elementary, always-present feeling of pleasantness and activation), and from feeling (the conscious, subjective component of an emotional episode). In relation to cultural heritage, “emotions and emotion-related values” denote (i) the affective responses that people have to heritage places, objects, and practices, and (ii) the dimensions of heritage significance—variously termed social, communal, spiritual, and associative value—that are constituted through, and cannot be assessed independently of, those affective bonds. On this view, heritage is not an inert set of material remains whose value is intrinsic and expert-determined; it is an active, meaning-making and emotionally charged cultural process through which individuals and communities relate to the past in the present.

Encyclopedia doi: 10.3390/encyclopedia6090206

Authors: Evelyn Wu

Educational AI auditing is the systematic, evidence-based examination of artificial intelligence systems used in formal, non-formal, and informal education to determine whether they are technically reliable, pedagogically valid, developmentally appropriate, equitable, accessible, safe, and institutionally accountable. Its object is not only a model but the situated arrangement through which models, data, interfaces, people, policies, and organizational routines redistribute educational opportunities, judgments, labor, and risk. Unlike benchmarking, an audit does not stop at task performance; unlike prospective impact assessment, it tests claims with empirical evidence; and unlike compliance review, it can ask whether a lawful use is educationally defensible. A stage-sensitive audit asks what educational work is delegated to AI, whether that delegation expands or displaces learners’ and educators’ capabilities, how effects differ across contexts and social positions, and who can contest or remedy harmful outcomes. The framework presented here combines four system levels, seven audit domains, five lifecycle gates, and a burden of evidence that rises with decision stakes, opacity, developmental dependence, and the persistence or irreversibility of consequences.

Encyclopedia doi: 10.3390/encyclopedia6090205

Authors: Yasmany García-Ramírez

Artificial intelligence (AI) and machine learning (ML) are increasingly applied to road traffic congestion prediction, but heterogeneous outcomes, models, horizons, and evaluation practices limit comparability. The objective of this study was to synthesize methods, applications, validation, explainability, and reproducibility in AI/ML-based road traffic congestion prediction and forecasting. Following PRISMA 2020, Scopus, Web of Science Core Collection, and IEEE Xplore were searched through 5 July 2026 for English-language journal articles and full conference papers published from 2000 to 2026. Two external reviewers independently screened 734 unique records and assessed the retrieved full texts, while the author resolved disagreements against the predefined eligibility criteria. Study characteristics, prediction tasks, congestion indicators, model families, metrics, explainability, validation, and data/code availability were synthesized descriptively and narratively. Of 1131 records identified, 397 duplicates were removed and 734 records were screened. Full-text retrieval was sought for 339 reports; 195 could not be retrieved, 144 were assessed for eligibility, and 129 were included. Congestion level was the main prediction task, while traffic flow and speed were the most frequent indicators. Heterogeneity and the absence of verified numerical performance values precluded meta-analysis or model ranking. Explainability was limited, and external validation, transferability, and reproducibility were insufficiently documented. Progress requires standardized outcomes, transparent validation, reproducible workflows, explainable models, and independent testing across networks and cities.

Encyclopedia doi: 10.3390/encyclopedia6090204

Authors: Mustafa Akpinar Usman Khan Durrani Asif Malik Jinane Mounsef Ahmed Mostafa Omar Abdul Latif Ghazi Al-Naymat Milan Dordevic Ibrahim Delibasoglu

Recent educational research has increasingly examined the interaction between three complementary instructional approaches: Problem-Based Learning (PBL), gamification, and Keller’s ARCS model of motivation. Rather than attempting a comprehensive review of each framework independently, this paper presents a focused integrative review of empirical studies that explicitly examine their combined application. Thirty rigorously selected studies published between 2018 and 2026 were synthesised to examine how these approaches have been operationalised across diverse educational settings and what evidence exists regarding their collective impact on learner motivation, engagement, and educational outcomes. The corpus includes both studies that explicitly integrate all three frameworks and studies that examine meaningful combinations of two of the three; only a minority of the included studies implement all three simultaneously, a distinction maintained throughout the review. Across the reviewed literature, integrated implementations were consistently associated with positive outcomes; individual studies reported effect sizes ranging from Cohen’s d = 0.8 to 1.2, particularly where authentic problem-solving, carefully aligned game mechanics and systematic motivational design were implemented together. Because these estimates are drawn from heterogeneous samples, interventions, and outcome measures rather than a formal meta-analysis, they should be read as indicative of the range reported across studies rather than as a precise estimate of a single common effect. At the same time, the review identifies important limitations within the existing evidence base, including methodological heterogeneity, relatively small and context-specific samples, inconsistent outcome measures, and limited longitudinal evaluation. These findings suggest that although the integrated PBL–gamification–ARCS approach offers considerable promise, stronger comparative and long-term empirical studies remain necessary before broad generalisations can be made. By deliberately concentrating on studies situated at the intersection of these three frameworks, this review provides a coherent synthesis of current evidence while identifying priorities for future research and instructional practice.

Encyclopedia doi: 10.3390/encyclopedia6090203

Authors: Maria Antuna-Casal Marta Rios Maria Rios-Antuna Juan Carlos Rios-Fernandez

Professional education asks learners to act under consequential uncertainty while judgment and professional identity are still developing. Scholarship on emotion, identity formation, reflection, psychological safety, ethics, and agency has expanded, yet these literatures seldom explain how affectively charged experience becomes accountable professional action. This critical integrative review develops INTEGRAL (INTegrated Emotional Growth for Responsible Agency and Leadership), a cross-professional framework for health sciences and engineering education. A purposive, theory-led synthesis of 47 peer-reviewed sources was assembled through targeted searches, citation tracing, abductive construct comparison, negative-case analysis, and contrastive examination of two consequential professional fields; the retained corpus comprised 25 health-sciences sources, 13 engineering sources, and 9 cross-disciplinary, general-education, or methodological sources. Because the iterative search was not an exhaustive database export, no valid total-hit denominator was generated, and this reporting boundary is stated explicitly. INTEGRAL distinguishes event-in-context exposure (D1) from learner appraisal and identity-relevant processing (D2). Structured curricular scaffolding (D3) is specified as a multilevel configuration that shapes the exposure learners encounter, influences early processing, and moderates whether D2 becomes observable, reason-giving, accountable action under constraint (D4). Leadership and stewardship (D5) are repositioned as a conditional long-term extension rather than a mandatory stage. The framework is theoretical, identifies rival explanations and disconfirmation conditions, and derives testable propositions and multi-source indicators without treating adversity as inherently beneficial or emotional display as competence.

Encyclopedia doi: 10.3390/encyclopedia6090202

Authors: Sareen Kaur Bhar

Workplace language proficiency functions as career capital because it shapes whose expertise is heard, trusted, and converted into developmental assignments, networks, promotion, and mobility. Generative artificial intelligence (GenAI) disrupts the assumed correspondence between employee-held language competence and observable communicative performance by enabling linguistic capability to be technologically accessed. This critical integrative review synthesises 41 substantive sources across language and careers, AI-mediated communication, multilingual model performance, workplace productivity, identity, attribution and signalling, sociotechnical work, and AI literacy. Sources were classified by evidentiary proximity to career outcomes, from model benchmarks and simulated tasks to workplace processes and direct mobility evidence. Evidence indicates task-level and workplace-process benefits alongside uneven cross-language performance and unresolved attribution and legitimacy concerns, but no study in the reviewed set directly links GenAI-supported multilingual communication with promotion, pay growth, lateral mobility, or access to strategic assignments. Integrating career-capital theory, attribution and signalling processes, and sociotechnical perspectives, the article distinguishes employee-owned competence, technologically accessed capability, AI-mediated communicative performance, organisationally recognised performance, and career-convertible capital. LANA provides the multilevel organising framework for a conversion model explaining how mediated performance may, or may not, become career value. Two conditional pathways theorise how GenAI may flatten language ceilings through improved performance, participation, learning, and visibility, or re-stratify work through unequal access, verification burdens, cross-language error, and legitimacy penalties. Five testable propositions are advanced. GenAI therefore changes not only communicative performance but the mechanisms through which capability is attributed, recognised, and converted into career advantage.

Encyclopedia doi: 10.3390/encyclopedia6090201

Authors: Elfrieda H. Hiebert

English has a large and historically layered lexicon. The usual approach to vocabulary instruction, finding the unfamiliar words in an assigned passage and teaching them, improves comprehension of that passage but transfers poorly to broader measures. The problem has not been a lack of theory about which words merit instruction; frameworks for principled word selection have been well developed for more than a decade. What was lacking was a way for educators to apply those criteria, with the necessary corpus, morphological, and psycholinguistic analyses largely confined to research databases and the expertise of specialists. This review argues that large language models do not change what makes a word worth teaching, but rather they change what is now available to apply those criteria. Educators can now apply the criteria to a particular text and grade level using ordinary language. Drawing on four texts about hurricanes that hold the subject constant while varying genre and grade, the review develops three applications: domain-structured selection for informational text, semantic-cluster mapping for narrative, and the identification of a text’s latent lexicon that is particularly germane to narrative texts. It closes with the limits of these tools and identifies the points where teacher judgment is still required and the validation studies they still need.

Encyclopedia doi: 10.3390/encyclopedia6090200

Authors: Esabella Pounraj Aravind Banumathi Rajamanickam

The escalating environmental crisis has intensified scholarly attention on literature that inquiries into the relationship between humans and nature. This study addresses an existing gap in ecocritical research by applying Deep Ecology to selected passages from Easterine Kire’s novels, Son of the Thundercloud (2016), Don’t Run, My Love (2017), A Respectable Woman (2019), and Spirit Nights (2022), to analyse the portrayal of nature’s intrinsic value and biodiversity. Through close analysis of selected passages, the analysis investigates how Easterine Kire’s narratives represent landscapes, plants, animals, and ecological relationships as living, primary factors. The selected passages question anthropocentric perspectives by foregrounding the interconnectedness of all life forms and advocating an ecocentric worldview. The study highlights how Kire’s Fiction represents profound ecological ethics and sustainable human–environment relationships through culturally grounded ecological perspectives.

Encyclopedia doi: 10.3390/encyclopedia6090199

Authors: Lingkai Kong Zeyuan Wang

The natural law tradition offers two fundamentally opposed answers to the question of how a political body emerges. The first, exemplified by Hobbes, treats natural law as a pre-political condition of deficiency and conflict that the political body must transcend through a single contractual leap establishing an unlimited sovereign. The second, exemplified by Althusius, treats natural law as the normative foundation from which political order gradually grows through multi-layered association, beginning with the family. These two poles are analytical reconstructions of a broader contrast rather than an exhaustive classification of the tradition. This entry examines the structural tension between them through the case of Pufendorf, who departs from Hobbes by grounding natural law in sociability and granting priority to horizontal association, but ultimately returns to absolute sovereignty. His unfinished departure reveals the difficulty of sustaining the pole of generation, once political unity is identified with an absolute adjudicative center. This entry argues that the historical marginalization of the pole of generation stems from a centralization presupposition within the natural law tradition, the post-1648 consolidation of the sovereign state system, and the historiographical exclusion of the scholastic inheritance. This tension does not disappear when the vocabulary of natural law gives way to later theories of political order.

Encyclopedia doi: 10.3390/encyclopedia6090198

Authors: Lingting Jiang Linna Shi Nan Zhou

Artificial intelligence (AI) refers to a set of computational techniques, including machine learning, natural language processing, deep learning, and generative AI, that enable systems to perform tasks traditionally requiring human intelligence, such as prediction, pattern recognition, and decision-making. The rapid diffusion of AI into business organizations is transforming how information is processed, decisions are made, and knowledge-intensive work is performed, creating both new opportunities for economic value and new challenges for human judgment, organizational governance, and accountability. The growing adoption of AI across accounting, finance, and management makes it increasingly important to understand not only what AI can do, but also how and under what conditions it affects individuals, organizations, and markets. This paper provides a comprehensive review of the rapidly growing literature on artificial intelligence across these three disciplines. We synthesize existing research to examine how AI is transforming information processing, decision-making, governance, and organizational performance. In accounting, AI enhances auditing, financial reporting, and fraud detection while raising concerns regarding transparency and professional judgment. In finance, AI improves asset pricing, risk assessment, and trading strategies by leveraging large-scale structured and unstructured data. In management, AI reshapes organizational design, human capital, strategic decision-making, and innovation through increasingly sophisticated human–AI collaboration. Across these disciplines, we organize the literature around several unifying themes, including information asymmetry, automation versus augmentation, decision quality, interpretability, and governance. We further identify important research gaps concerning whether AI’s predictive and analytical advantages translate into meaningful economic and organizational outcomes, how AI reshapes human judgment and skills, the emerging risks, and the need for stronger research designs. By integrating evidence across three major business disciplines, this review provides a unified framework for understanding AI’s transformative role in organizations and offers a roadmap for future interdisciplinary research on the economic, behavioral, organizational, and governance consequences of AI.

Encyclopedia doi: 10.3390/encyclopedia6090197

Authors: Maaz A. Khan César M. A. Vasques Adélio M. S. Cavadas

Automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) are among the key enabling technologies driving intelligent logistics and industrial automation. Despite their widespread adoption and rapid technological evolution, the literature often addresses AGV and AMR systems in a fragmented manner, lacking a structured methodological perspective that highlights their architectural foundations, levels of autonomy, and technological maturity. This paper presents a methodological survey of AGV and AMR technologies, focusing on system-level architectures and core functional components rather than isolated algorithms. The survey systematically analyzes key technological dimensions, including sensing and perception, localization and positioning strategies, navigation and path-planning approaches, communication infrastructures, and multi-robot coordination mechanisms. A clear distinction is drawn between classical AGV systems, which rely on fixed infrastructure and predefined routes, and AMR systems, which exhibit adaptive, perception-driven, and self-configuring behaviors enabled by artificial intelligence techniques. Rather than proposing new algorithms, this paper organizes existing approaches into a coherent framework that highlights technological transitions from infrastructure-dependent guidance to autonomous, data-driven navigation. Recent trends such as cloud–edge integration, learning-based navigation, scalable fleet management architectures, and cooperative multi-robot systems are reviewed and discussed from a methodological standpoint, emphasizing their role in increasing flexibility, robustness, and operational efficiency in industrial and logistics environments. The survey also addresses cross-cutting challenges, including system transparency, safety and certification, interoperability, and sustainability. Finally, this paper outlines research directions aligned with the principles of Industry 5.0, highlighting the need for human-centered, resilient, and scalable AMR and AGV systems capable of safe and explainable operation in complex industrial contexts.

Encyclopedia doi: 10.3390/encyclopedia6090196

Authors: Alam Ahmad

Digital money has transformed from a technological experiment into a central concern of monetary economics, financial regulation, and public policy. Despite rapid growth in cryptocurrencies, stablecoins, central bank digital currencies (CBDCs), and tokenized deposits, the literature remains fragmented across disciplines, with limited cross-cutting synthesis. This article adopts a scoping–integrative review methodology, combining systematic database (Scopus and Web of Science) searches with targeted retrieval of policy and institutional sources (BIS, IMF, Financial Stability Board (FSB), ECB, and national central bank repositories), covering the period 2008–2025, with integrative synthesis of academic, policy, and regulatory sources following PRISMA-ScR reporting principles. The review identifies four competing trust mechanisms underpinning digital money: algorithmic trust associated primarily with cryptocurrencies, private reserve backing trust (stablecoins), sovereign trust underpinning CBDCs, and regulated institutional intermediation supporting tokenized deposits. The proposed digital money ecosystem taxonomy (DMET) classifies digital money instruments across fourteen institutional, governance, technological, monetary, and regulatory dimensions, enabling systematic comparison of cryptocurrencies, stablecoins, CBDCs, and tokenized deposits. Future monetary systems will be hybrid, combining public and private digital money within layered governance arrangements. Interoperability, privacy, programmability, and cross-border governance represent the most critical unresolved policy and research challenges.

Encyclopedia doi: 10.3390/encyclopedia6090195

Authors: Emese Beáta Berei

Family life education (FLE) is a social support and educational practice that encompasses all efforts to equip individuals, families, or community members with information, resources, skills, and examples of best practices to ensure the healthy functioning of families and prevent or minimize problems. It is grounded in social science, specifically family sciences, but evidence-based research exists in multidisciplinary or interdisciplinary studies across many other domains. Family life educators are professional helpers who focus on supporting, educating, and teaching the community to empower families and improve the quality of personal and family life. Studies state that FLE is a transdisciplinary or global field, it should sustain the quality of families’ lives: subjective well-being, optimism, health, and standard of living, while reducing aspects of family deprivation and maintaining a work–life balance. FLE should integrate educational knowledge and practices for a simple way of living in families and society.

Encyclopedia doi: 10.3390/encyclopedia6090194

Authors: Maaz A. Khan César M. A. Vasques Adélio M. S. Cavadas

Computer vision (CV) systems driven by artificial intelligence (AI) are increasingly replacing manual and conventional rule-based inspection procedures in industrial quality inspection, enabling automated, real-time, and data-driven decision-making based on visual data. Conventional inspection procedures are usually limited in terms of scalability, human-related errors, and high operational costs, which drives the increasing reliance on smart vision-based technologies. A practical, practice-oriented review of AI-based computer vision systems for industrial quality control is provided in this paper, with emphasis on real-world deployment issues and performance aspects. Two representative industrial case studies are examined. The first investigates real-time extrusion monitoring in robotic building construction, where geometric deviations, bead-width variation, surface irregularities, and process inconsistencies are detected during material deposition using vision-based monitoring and image-processing pipelines. The second case study focuses on automated inspection of bolts and screws in manufacturing lines, addressing presence detection, orientation recognition, and defect classification under high-speed production conditions. In both cases, widely adopted vision and AI techniques, including image-processing pipelines, convolutional neural networks, and edge-computing hardware, are discussed and compared. The analysis shows that AI-enabled computer vision systems can outperform traditional rule-based or manual solutions in terms of inspection accuracy, consistency, and throughput when they are supported by reliable acquisition, representative data, and robust industrial integration. Nevertheless, challenges related to dataset quality, model generalization, lighting variability, and real-time computational constraints remain critical in industrial environments. In conclusion, AI-based computer vision plays a central enabling role in intelligent quality inspection within the context of Industry 5.0. Future research should focus on adaptive model capabilities, tighter integration with cyber-physical systems, and scalable deployment strategies to achieve reliable and autonomous inspection across diverse industrial sectors.

Encyclopedia doi: 10.3390/encyclopedia6090193

Authors: Said Gaci Youcef Abchi

This review provides an integrative synthesis of the R&D performance measurement literature and introduces the Beyond Traditional Metrics (BTM) framework as a multi-criteria reference model for R&D performance evaluation in the petroleum sector. Research and Development (R&D) constitutes a strategic pillar of the petroleum industry, where technological innovation supports competitiveness, operational efficiency, and the transition toward more sustainable energy systems. However, evaluating the performance of R&D projects remains a major challenge because their outcomes are often uncertain, intangible, long-term, and multidimensional. Commonly used Key Performance Indicators (KPIs)—such as cost, time, and number of deliverables—therefore provide only a partial representation of R&D effectiveness. R&D performance assessment must therefore consider the intrinsic diversity of innovation activities. Reverse engineering emphasizes replication and adaptation of existing technologies, while innovation-driven R&D seeks to create novel knowledge, technological capabilities, and strategic learning. Accordingly, the selection of performance indicators should be adapted according to project type, technological maturity, and strategic objectives. To avoid biased evaluation, the approach integrates principles derived from the Multi-Criteria Decision Analysis (MCDA) approach, enabling prioritization of criteria aligned with each project’s objectives, complexity, and organizational priorities. To move beyond simple cost and time metrics, this study revisits the meaning of “performance” in R&D and explores a multidimensional evaluation perspective capable of capturing both tangible and intangible forms of value creation by integrating five complementary dimensions: Knowledge Creation and Diffusion, Innovation Velocity, Dynamic Strategic Alignment, Team and Organizational Health, and Resilience and Robustness under technological, regulatory, operational, and market uncertainty. The framework is illustrated through an exploratory application to a hypothetical portfolio of petroleum-sector R&D projects, demonstrating its potential usefulness for benchmarking, portfolio prioritization, and multidimensional innovation assessment under conditions of uncertainty.

Encyclopedia doi: 10.3390/encyclopedia6090192

Authors: Noëlle Fabre-Mitjans Gregorio Jiménez-Valverde Salvador Viciana Ferran Crespo i Torres

Learning from errors (LFE) constitutes a complex, multilevel process whose pedagogical value depends on how errors are elicited, interpreted, and corrected. This narrative review critically synthesizes research on LFE and its implications for science instruction in school and higher education. The reporting of the purposive, non-exhaustive search was strengthened with reference to the Scale for the Assessment of Narrative Review Articles (SANRA) criteria. The synthesis traces the historical transition from error avoidance to conditional error-as-resource perspectives and integrates five complementary lenses: error type, negative knowledge, cognitive load and prior knowledge, affective and self-regulatory processes, and the Generating Errors/Detecting and Correcting Errors model. It then evaluates instructional approaches including productive failure, erroneous examples, peer instruction, formative feedback, conceptual-change strategies, Predict–Observe–Explain, refutation texts, and gamification. Evidence is strongest when errors are embedded in structured cycles of manageable challenge, explanation, feedback, and revision; however, effects are heterogeneous and moderated by learner expertise, task demands, feedback design, classroom error climate, and safety constraints. Domain-specific evidence is most developed in physics, chemistry, biology, and health-professions simulation, whereas Earth and climate sciences and teacher professional development remain comparatively underexamined. The review concludes with an integrative framework and actionable design principles for science teacher education, while identifying methodological, cultural, and empirical gaps for future research.

Encyclopedia doi: 10.3390/encyclopedia6090191

Authors: Elsa Simões

Storytelling in advertising is an organising principle through which narrative meaning can be constructed at different but interconnected levels, from individual advertisements to campaigns and more enduring brand narratives across changing media environments. It provides the narrative logic through which individual advertisements can function as narratives in their own right while also contributing to broader narrative structures, allowing audiences to interpret them within wider cultural frameworks. Although its forms have evolved with successive developments in advertising media, storytelling continues to rely on the narrative processes through which meaning is constructed. The distinction between the narrative content (tale) and its modes of expression (telling) explains how similar stories may be communicated differently as advertising adapts to new media. Storytelling therefore encompasses a wide range of narrative strategies while preserving its underlying narrative function. The emergence of generative artificial intelligence marks the latest stage in this historical development. Narrative production is increasingly distributed across human creators and computational systems. The construction of narrative meaning nevertheless continues to depend on human judgement, which remains central to advertising storytelling.

Encyclopedia doi: 10.3390/encyclopedia6090190

Authors: Zhipeng Liao Abusaleh Jabir Guangyu Xue Zohreh Hajiabadi Vihirthan Ravitharan Sridhar Chandrasekaran Firman M. Simanjuntak

As computational demands from artificial intelligence increase, traditional von Neumann architectures face memory wall bottlenecks while CMOS technology approaches physical limitations defined by Moore’s law and Dennard scaling. This entry examines memristor-based logic circuits as potential solutions to overcome these computing constraints. We systematically analyse various memristor-based logic implementation approaches by reviewing and comparing stateful methods, including Material Implication (IMPLY) and Memristor-Aided Logic (MAGIC), as well as non-stateful techniques such as Memristor-Ratioed Logic (MRL) and Scouting Logic (SL). Each approach demonstrates unique capabilities for implementing fundamental logic operations, with progressive improvements in efficiency documented across multiple research studies. We discuss that while memristor-based logic shows promise, significant limitations exist: crossbar arrays can only integrate specific gates (NOT, NOR), MAGIC architecture struggles with multilevel cascade and large fan-out circuits, IMPLY requires numerous operational steps, and MRL faces challenges integrating CMOS-based inverters into crossbars.

Encyclopedia doi: 10.3390/encyclopedia6090189

Authors: Williams Jiménez-García

Criminal ecosystems are durable social systems in which differentiated criminal functions become recurrently interdependent across organizations, networks, illicit markets, institutional actors, financial facilitators, territorial brokers, and social environments. The concept applies when coercion, illicit accumulation, political protection, territorial regulation, and other specialized capacities depend on one another over time and become structurally coupled with institutional, sociocultural, spatial, or technological conditions. A criminal ecosystem is therefore not defined by the presence of a particular organization, market, or territory, nor by resilience itself. It is identified by functional differentiation, recurrent interdependence, structural coupling, and temporal reproduction. Complex adaptive systems theory explains how decentralized interactions can generate adaptation, substitution, and emergent order, while autopoietic social systems theory explains how recurring communications stabilize expectations and reproduce boundaries. Digital infrastructure can mediate financial and transnational functions without constituting a separate operational dimension in the present framework. This distinction allows resilience, reconfiguration, displacement, and decline to be examined as empirical outcomes rather than assumed properties of the ecosystem.

Encyclopedia doi: 10.3390/encyclopedia6090188

Authors: Luca Cerniglia Silvia Cimino

Executive dysfunction (EFD) represents a transdiagnostic construct encompassing deficits in inhibitory control, working memory, and cognitive flexibility, mediated primarily by the prefrontal cortex (PFC). Despite a robust neurobiological literature, the psychodynamic dimensions of EFD remain undertheorized and clinically underutilized. Moreover, the implications of EFD for the parent–child relationship, both when the deficit resides in the child and when it characterizes the parent, have received insufficient integrative attention. This paper adopts an integrative neuro-psychodynamic framework, examining EFD across three clinical presentations, namely Attention-Deficit/Hyperactivity Disorder (ADHD), Major Depressive Disorder (MDD), and chronic procrastination, and exploring their neurobiological substrates in parallel with their psychoanalytic correlates. A dedicated section examines the bidirectional relationship between EFD and the quality of the parent–child dyad, drawing on developmental neuroscience, attachment theory, and object-relational thinking. Evidence suggests that top-down regulatory failures, indexed by disrupted PFC-amygdala circuitry, may be conceptually mapped onto classical psychoanalytic constructs including Hartmann’s ego functions, Bion’s container-contained model, and Freudian theories of narcissistic withdrawal. The parent–child relationship emerges as a critical bidirectional system in which executive capacities and relational quality mutually regulate one another: parental EFD compromises the scaffolding function essential to the child’s developing self-regulation, while the child’s EFD severity independently predicts elevated parental stress and dysfunctional interactional patterns. An integrated neuro-psychodynamic model of EFD offers clinicians a richer diagnostic and therapeutic framework. Awareness of the neurobiological underpinnings of EFD may meaningfully inform treatment sequencing, particularly regarding the timing of psychodynamic interventions relative to the structural and regulatory capacity of the patient’s ego apparatus. The family system emerges as a primary unit of clinical attention, inasmuch as EFD rarely operates in isolation but rather within, and in recursive interaction with, the relational field.

Encyclopedia doi: 10.3390/encyclopedia6090187

Authors: António R. Teixeira José Vasconcelos Ferreira Ana Luísa Ramos

Artificial-intelligence-enabled agri-food entrepreneurship is the creation of new ventures and the entrepreneurial renewal of existing firms, whose value propositions and business models are built around learning-based computational systems applied across the food value chain, from primary production and processing to distribution, consumption, and the recovery of losses and by-products. The core enabling technologies are machine learning and computer vision, generative artificial intelligence (AI) and large language models, and AI-enabled robotics and predictive analytics, deployed with complementary digital infrastructure such as the Internet of Things, big data, cloud and edge computing, blockchain, and digital twins. The concept is broader than technology adoption because its subject is the entrepreneur: how opportunities are recognised or created, how business models convert them into revenue, and why so few technically capable solutions become durable businesses. This entry makes four contributions: It specifies a mechanism—because AI lowers the cost of prediction but not of judgement, opportunities concentrate in decisions that are prediction-intensive, recurrent, and attached to an outcome that the customer already measures. It provides a taxonomy of business-model archetypes that separates value creation from value capture. It establishes the boundary conditions under which digital-entrepreneurship theory transfers to food systems—seasonality, fixed adoption costs, contested data governance, and liability. Finally, it converts the synthesis into seven testable propositions and an evidence calibration separating controlled benchmarks, field pilots, and commercial deployment.

Encyclopedia doi: 10.3390/encyclopedia6090186

Authors: Alexandros Garefalakis

Green accounting is an extension of conventional accounting that incorporates environmental considerations into economic measurement and reporting. It examines the relationships between economic activity and the natural environment by identifying environmental costs, resource use, ecological impacts and related responsibilities. Green accounting may be applied within organisations to support management and reporting or at the national level to assess how economic development affects natural resources and environmental quality. Its main purpose is to provide a broader understanding of performance by showing that economic value cannot be evaluated independently of environmental sustainability. In this way, it supports more responsible decision-making, greater accountability and long-term planning.

Encyclopedia doi: 10.3390/encyclopedia6090185

Authors: Klara Sauanova Zhanar Bidakhmet Gulnar Omarova Sholpan Sagyndykova Marina Vorogushina

Research on teacher digital competence has expanded sharply over the past decade. However, the field’s development, thematic structure, and underlying terminological characteristics have remained under-examined. The rapid integration of artificial intelligence has compounded this challenge, introducing new competence-related constructs and reshaping the field’s conceptual landscape. In the context of Sustainable Development Goal (SDG) targets 4.4 (developing digital skills) and 4.c (ensuring a supply of qualified teachers), this raises the question of whether the knowledge base is developing coherently. To address this question, we analyse a corpus of 4097 Scopus-indexed publications retrieved through a broad search on teacher digital competence, published between 2015 and 2025, using longitudinal bibliometric analysis and science mapping. The analysis reveals marked terminological variability: a high Pielou’s evenness index (J′ = 0.86) indicates that occurrences are distributed relatively evenly across 8567 normalised terms, suggesting the absence of a strongly dominant terminological core at the corpus level, while singleton terms account for a large share of the vocabulary (76%), pointing to substantial fragmentation. Against this fragmented backdrop, an AI-oriented strand accounts for 10.4% of the corpus and rises to 26.1% of annual output by 2025; rather than displacing established competence-related concepts, AI-related concepts form an emerging technological layer within teacher digital competence research. These thematic patterns are accompanied by uneven publication activity and international collaboration. Taken together, these findings indicate that the conceptual boundaries of teacher digital competence research are shaped by substantial terminological variability and ongoing thematic expansion. They further highlight the importance of transparent search strategies and greater terminological clarity and consistency for improving the comparability, reproducibility, and cumulative development of research in this field.

Encyclopedia doi: 10.3390/encyclopedia6090184

Authors: Carlos Ledezma Vicenç Font Alicia Sánchez Alexandre Cortés

Practical argumentation refers to a form of argumentation oriented towards action. Unlike theoretical argumentation, which primarily concerns the truth or acceptability of propositions, or mathematical argumentation, which is mainly concerned with the production, justification, and validation of mathematical claims, practical argumentation includes an action, decision, or course of conduct as a central component of the argument. Practical argumentation has attracted growing interest in fields such as political science, critical discourse analysis, argumentation theory, and education. In educational contexts, it is especially relevant for analysing how teachers justify pedagogical decisions in relation to learning objectives, classroom circumstances, available means, professional values, and anticipated consequences. Within mathematics education, analytical tools have been developed to structure and represent practical arguments made by prospective and practising teachers during episodes of teaching reflection on practice, for instance through schemes that connect argumentation models with didactical criteria for analysing mathematics teaching and learning. Practical argumentation thus provides a conceptual and analytical tool for making visible the reasons underlying teachers’ decision-making, particularly in situations characterised by tensions between mathematical, didactical, and classroom-management considerations.

Encyclopedia doi: 10.3390/encyclopedia6090183

Authors: Satavat Malaisri Warakorn Seeyo Sayam Chuangprakhon

In science, technology, engineering, arts, and mathematics (STEAM)-based music education, sound serves as a shared object of listening, inquiry, design, representation, and artistic expression. Sound is approached as musical material, a physical phenomenon, a technological object, a design problem, and a mathematical structure. Learners investigate vibration, pitch, loudness, timbre, duration, rhythm, melody, and acoustic experience; use digital tools to record, replay, visualize, arrange, and create sound; and apply design processes to plan, test, revise, and present sound-based products or performances. Musical understanding is developed through singing, movement, instrumental performance, composition, improvisation, and reflection, while mathematical reasoning is supported through beat, duration, sequence, proportion, pattern, and timing. In this approach, music provides an integrated context in which learners connect sensory experience with conceptual understanding. It is relevant across general music education contexts because it supports listening, discrimination, comparison, organization, creation, performance, and reflection, with activities adapted to learners’ ages, prior musical experience, and educational levels.

Encyclopedia doi: 10.3390/encyclopedia6090182

Authors: Clotilde Cicatiello Paolo Fusco

Gender bias in generative artificial intelligence (GenAI) is both a technical and a social phenomenon: it emerges from historically patterned data, model design, and interactions in institutional use, and it cannot be understood by engineering or by social critique alone. This critical integrative review develops a more differentiated account. It connects feminist epistemology, Science and Technology Studies, critical AI scholarship, natural language processing, and governance research to examine five levels: historical knowledge production, technical representation and generation, benchmark evaluation, institutional deployment, and accountability. The review explains tokenization, next-token prediction, transformers, and the transition from static embeddings to contemporary language models before assessing evidence from standard fairness tests—coreference tests (WinoBias), sentence-pair tests (CrowS-Pairs), and stereotype tests (StereoSet)—as well as open-ended generation, multilingual testing, and text-to-image systems. It shows that measured bias varies with task, prompt, language, model version, and metric. What a test records and what that record means are therefore distinct questions: measurements are situated and depend on the instrument, and their interpretation draws on theory rather than following from the numbers alone. Evidence from employment, education, healthcare, and translation further indicates that the relevant unit of analysis is the model-in-context—the model together with the institution and workflow in which its outputs are used. Technical mitigation can reduce specific harms but does not repair unequal criteria, incomplete evidence bases, or weak institutional accountability. The review proposes a multilevel governance approach combining technical evaluation, documentation, professional and community oversight, appeals, remedies, and public-interest knowledge infrastructure. Its distinctive contribution is to connect three observations usually kept apart—how bias is measured, how generative systems concentrate epistemic authority, and how statistical learning is oriented toward past data—and to show why democratic and feminist governance can keep alternative technological futures open.

Encyclopedia doi: 10.3390/encyclopedia6080181

Authors: Vera Bijelić

Architecture design studios are complex learning environments in which knowledge develops through critique, collaboration, individual reflection, material exploration, and increasingly digital forms of practice. Although the physical organization of these spaces influences how such activities unfold, research on furniture arrangement remains fragmented across ergonomics, learning environments, educational research, technology-enhanced education, and participatory design. This structured integrative review examined the mechanisms reported between furniture arrangement, related physical spatial configurations, and learning processes in architecture design studios and relevant adjacent educational settings. It also investigated the pedagogical, ergonomic, technological, and cultural conditions under which these mechanisms were reported as supportive or restrictive. Scopus, Web of Science All Databases, and ScienceDirect were searched on 7 August 2026. The searches identified 64 source-level records: 26 from Scopus, 19 from Web of Science, and 19 from ScienceDirect. Eight duplicate records were identified within the ScienceDirect results. Following cross-source deduplication, title and abstract screening, and full-text eligibility assessment, 15 publications were included in the integrative synthesis. Study characteristics, methodological quality, contextual relevance, furniture-related conditions, pedagogical activities, reported outcomes, explanatory mechanisms, evidentiary directness, and transferability were examined through an integrative, mechanism-oriented synthesis. The resulting relationships were subsequently organized through an abductive framework-development process into the provisional Adaptive Studio Learning Ecosystem (ASLE) framework. ASLE comprises five interrelated dimensions: spatial flexibility, ergonomic responsiveness, pedagogical mediation, technological support, and cultural–participatory fit. The synthesis supports activity–layout alignment rather than a universally optimal furniture configuration and indicates that spatial adaptability becomes educationally meaningful only when supported by appropriate pedagogical practices, ergonomic conditions, technological integration, and patterns of user participation. Because the evidence base includes a limited number of direct architecture-studio studies and relies partly on mechanisms transferred from adjacent settings, ASLE should be treated as a provisional, review-derived framework requiring empirical validation.

Encyclopedia doi: 10.3390/encyclopedia6080180

Authors: Nikolaos Voudrislis

Spatial literacy and spatial thinking are fundamental skills for understanding space, interpreting geographical phenomena, and enabling active citizenship in a society increasingly driven by geospatial information. This review examines how digital tools and geospatial technologies contribute to cultivating spatial literacy and thinking within primary geography education. Following an integrative, PRISMA-informed review methodology combining searches of Scopus, Web of Science, and ERIC (n = 1373 records identified), this study draws on a corpus of 141 studies—comprising an original set of sources supplemented by newly identified, priority-ranked literature—examining digital maps, Geographic Information Systems (GIS), Web GIS, StoryMaps, collaborative mapping, digital games, and augmented and virtual reality in geography teaching. This review proposes an explicit conceptual model clarifying the hierarchical and complementary relationships among spatial skills, spatial thinking, critical spatial thinking, spatial literacy, and spatial citizenship, together with a four-dimensional typology distinguishing technological platforms, representational formats, pedagogical approaches, and learning activity types; both are proposed as synthesizing heuristics for organizing the reviewed evidence and are offered as a basis for future empirical validation rather than as established models. The findings suggest that pedagogically grounded digital integration strengthens spatial skills, shifts learning toward active, participatory models, and helps cultivate spatial citizenship, though the strength of this evidence varies considerably by tool and by educational level, with primary-specific support remaining comparatively limited for higher-order outcomes such as critical spatial thinking. Crucially, the effective integration of these technologies depends on structured teacher training—addressing self-efficacy and confidence-related barriers alongside technical skills—and the adoption of innovative instructional approaches. Ultimately, digital tools provide effective means of deepening geographical learning and strengthening spatial literacy in primary schools. Realizing this potential, however, depends on matching the selection and use of each tool to the specific dimension of spatial learning it is evidenced to support.

Encyclopedia doi: 10.3390/encyclopedia6080179

Authors: José Antonio González Pizarro

This examines the development of the saltpeter industry in Chile after the War of the Pacific (1879–1883), a conflict between Chile and a Bolivian–Peruvian alliance. Chile’s victory meant the annexation of the territories of Antofagasta and Tarapacá, effectively controlling the production of sodium nitrate and the global saltpeter monopoly. Industrial development was reflected through changes in foreign and Chilean capitals, technologies, and work practices. In Tarapacá, the most important investments in the 19th century were British and German. In Antofagasta, Chilean, English, German, and Croatian investments were prominent in the 19th and 20th centuries. And since 1926, American capitals have occupied the spotlight. The dominant technologies were the Shanks system between 1880–1926, the Guggenheim from 1926–1954, and the introduction of Solar Evaporation in the 1950s. Work evolved from manual artisanal labor without legal protection to mechanization under social laws. Saltpeter represented, in the social and economic history of Chile, the rise of the proletariat, communal social movements, a strong labor press, and a series of strikes and massacres. From the saltpeter era sprouted powerful literature, poetry, and music throughout the 20th century until today. The nitrate industry reached its peak between 1881 and 1917. During this period, it had to confront competition from synthetic nitrate and ceased to be the main source of revenue for the national treasury of Chile. This was followed by a period of decline and crisis from 1918 to 1931, the latter intertwined with the global financial crisis. Various state and business measures made it possible for a small number of nitrate oficinas (processing plants and settlements) in Tarapacá and Antofagasta to continue operating until the nationalization of the nitrate industry in 1971. The nitrate industry took place during the first globalization of liberalism, one that brought flows of capital, migration from Europe to the American Continent, changes to marine navigation, and the opening of various markets in Asia, Europe, and Africa. Nitrate became the most effective fertilizer for agriculture and replaced guano in crop production. In order to analyze this topic, we will utilize the results of the main monographic studies, texts used for historical and political context, and works with interpretative theses about specific periods of nitrate production.

Encyclopedia doi: 10.3390/encyclopedia6080178

Authors: Adriaan De Man Amare Wondirad

As an expression of cultural identity, food is rooted in social transformation and, in the area of the Pearl River Delta, the cuisines of Macau and Hong Kong have been shaped by global interactions. Despite a geographical adjacency, both Special Administrative Regions (SARs) display unique foodways. While typical Macanese cuisine integrates not only Portuguese and Chinese but also African and Indian fusions, the Cantonese gastronomy of Hong Kong is heavily based on street food culture and the hybridity of cha chaan teng dishes. This encyclopedia entry looks at local food traditions from colonial culinary practice to globalized consumption. It illustrates a continuous adaptiveness in the wake of socioeconomic change, as well as the resilience needed for preserving heritage.

Encyclopedia doi: 10.3390/encyclopedia6080177

Authors: Paula Cristina Nunes Figueiredo Vandana Mohanty

Employee experience management (EXM) is a strategic and systematic approach through which organisations design, coordinate, and continuously improve the structural conditions, organisational mechanisms, and interactions in the workplace. These interactions shape the experiences lived by employees throughout their professional trajectory. Based on organisational psychology, human resource management (HRM), organisational behaviour, human-centred design, and technological studies, EXM seeks to understand how employees perceive, interpret, and attribute meaning to their interactions with organisational environments. Employee experience (EX) thus emerges from the dynamic interaction between structural conditions, organisational mechanisms, and the psychological interpretation that employees make of their experiences in the workplace, influencing well-being, engagement, performance, and organisational sustainability.

Encyclopedia doi: 10.3390/encyclopedia6080176

Authors: Ivan Veselov Georgiy Shakhgildyan Kirill Tregubov Daniil Vinogradov Vladimir Sigaev

Glass-ceramics are inorganic, non-metallic materials obtained by controlled crystallization of glasses through different processing routes; they contain at least one functional crystalline phase together with a residual glass, and the crystallized fraction may range from trace levels to nearly complete crystallization. Transparent glass-ceramics (TGCs) constitute the optically transparent subset of this class and combine a controlled crystalline microstructure with a residual amorphous matrix. Their transparency distinguishes them from conventional opaque glass-ceramics and is achieved by minimizing light scattering through careful control of crystallite size, volume fraction, spatial distribution, and refractive-index mismatch between the crystalline and glassy phases. Unlike conventional sintered ceramics, TGCs retain many of the processing advantages of glass while incorporating crystalline phases that can enhance mechanical, thermal, optical, or functional properties. Depending on their composition and microstructure, TGCs may exhibit improved hardness, fracture toughness, thermal stability, chemical durability, luminescence, nonlinear optical response, or ion-exchange strengthening capability. These features make TGCs attractive for applications requiring both optical clarity and advanced performance, including protective cover glass, transparent armour, precision optical substrates, laser and photonic components, optical sensors, and multifunctional host materials for rare-earth ions and nanoparticles.

Encyclopedia doi: 10.3390/encyclopedia6080175

Authors: Dan Valeriu Voinea

Synthetic media are digital artifacts (image, video, audio, text, or multimodal content) that are wholly or partly generated or materially manipulated by artificial intelligence (AI), particularly by deep-learning models. In consequence, their form, source, identity signal, or evidentiary relation to recorded events becomes partly or wholly artificial. A deepfake is the best-known subclass: AI-generated or AI-manipulated image, audio, or video content (including audio-only voice clones and still images) that realistically depicts an existing or fictitious person, object, place, or event and could falsely appear to be authentic. Contemporary scholarly and legal usage defines deepfakes by their technological origin and their capacity to deceive rather than by the creator’s intent, so disclosed and beneficial applications (accessibility, dubbing, entertainment, and research) are synthetic media as well. They are distinguished from cheapfakes (or shallowfakes), which achieve deception through conventional, non-AI editing such as selective cropping, slowing, or recontextualization. The social significance of synthetic media is not intrinsic but depends on consent, context, disclosure, and distribution, and on the institutional conditions under which audiences judge authenticity across the expanding volume of AI-generated content (AIGC) in the digital society.

Encyclopedia doi: 10.3390/encyclopedia6080174

Authors: Chun-Lin Lee Tzu-Ming Pan

Monascus yellow pigments, including monascin, ankaflavin, and the derivative monascinol, are azaphilone secondary metabolites produced by Monascus species. They have attracted attention as candidate functional-food ingredients because experimental studies indicate activity in pathways relevant to lipid and glucose metabolism. Available evidence, however, is heterogeneous and is derived predominantly from in vitro and animal studies; the human evidence is limited to small, short-term studies of Monascus-fermented preparations rather than isolated pigments. Reported associations with PPAR-α/γ and AMPK signaling, and with gut–liver-axis outcomes, should therefore be interpreted as mechanistic or preclinical observations. Monascus yellow pigments may offer a promising safety profile relative to monacolin K-containing preparations, but their long-term efficacy, dose standardization, and safety require confirmation in adequately powered human trials. Monascus-fermented products are being investigated beyond their traditional use as colorants and sources of monacolin K, partly because monacolin K has statin-like safety concerns. This review summarizes the structural diversity, biosynthetic pathways, and reported pharmacological activities of monascin, ankaflavin, and monascinol. Preclinical studies suggest that these azaphilones may influence PPAR-α/γ-, AMPK-, oxidative-stress-, and inflammation-related pathways and may affect lipid and glucose metabolism. Evidence for gut-microbiota modulation by monascinol is currently derived mainly from animal and mechanistic studies. Human data remain limited, including a small, short-duration trial of a Monascus-fermented preparation enriched in monascin and ankaflavin; these findings support short-term investigation but do not establish long-term clinical efficacy or comparative safety. Accordingly, Monascus yellow pigments should be regarded as promising candidate functional ingredients whose composition, bioavailability, dose, long-term safety, and clinical applicability require further rigorous evaluation.

Encyclopedia doi: 10.3390/encyclopedia6080173

Authors: Sayam Tarikul Islam Sakil Mahmud Subrata Chandra Das

Environmental sustainability of natural and synthetic fibers used in textiles and composites depends on their impacts throughout production, use, and end-of-life (EoL) stages. Natural fibers are renewable and biodegradable but may require substantial water and agricultural inputs, whereas synthetic fibers contribute to fossil resource depletion, microplastic pollution, and persistent waste generation. Natural fibers are often regarded as more sustainable alternatives to synthetic fiber; however, evidence from a life cycle assessment (LCA) reveals a more nuanced reality. As demand for fiber-based materials increases across textile and composite applications, a deeper understanding of the environmental implications of both natural and synthetic options becomes essential. This review compares these fiber categories from a life cycle perspective, examining carbon footprint, energy demands, resource consumption, and EoL pathways. Natural fibers such as cotton, flax, jute, hemp, sisal, banana, coir, and emerging plant-based alternatives offer advantages including biodegradability and carbon sequestration during cultivation. Nevertheless, agricultural practices and subsequent industrial processing require substantial land, water, and chemical inputs. Synthetic fibers, predominantly derived from fossil resources, provide a long service life and consistent performance but are associated with high greenhouse gas (GHG) emissions, dependence on non-renewable feedstocks, microplastic pollution, and broader environmental impacts. By presenting a comprehensive life cycle-based comparison, this review identifies the conditions under which each fiber type may offer environmental benefits, supporting informed material selection for sustainable development.

Encyclopedia doi: 10.3390/encyclopedia6080172

Authors: Emmanuel Udekwe Chux Gervase Iwu Chidi Chinedu Udekwe Nana Agyeman-Prempeh Lucky Sibanda Robertson Khan Tengeh Tendai Makwara

Entrepreneurship Education (EE) is acknowledged for developing entrepreneurial skills, ideas, and knowledge to support individuals and foster independence, thereby promoting economic growth and national sustainability. Digitised EE has been proposed as a means to strengthen entrepreneurial effectiveness and economic transformation. This literature review classifies studies on digitised EE, emphasises how it supports entrepreneurial effectiveness, and suggests guidelines for digitised EE performance in Tertiary Institutions (TIs). A search strategy was used to identify publications in databases such as Scopus, ScienceDirect, DOAJ, WOS, IEEE, and Cochrane. The publication range spanned from 2012 to 2024. A total of 912 publications were identified in the database, of which 43 met the inclusion criteria. Digitised EE requires considerable study to determine its impact on reducing unemployment, economic development through TIs, and the Sustainable Development Goals (SDGs). A descriptive research design was adopted; the themes selected were acknowledged in the research and discussed based on data extracted from the included criteria. Additionally, most of the included criteria are recent publications, with journals the most frequently identified and quantitative methods the most commonly applied. The lack of improved EE deprives the realisation of entrepreneurial effectiveness, which is attributed to Artificial Intelligence (AI), entrepreneurial knowledge, competitiveness, and strategic decisions. It is imperative to research digitised EE practices for entrepreneurial effectiveness and efficiency in the education sector for a country’s growth. Recommendations for related studies are provided in the review.

Encyclopedia doi: 10.3390/encyclopedia6080171

Authors: Mihail Kolev Krasimir Kolev

High-entropy alloys (HEAs), complex concentrated alloys (CCAs), medium-entropy alloys (MEAs), and multi-principal element alloys (MPEAs) are compositionally complex material classes in which design is based on multiple principal elements present in substantial, often comparable, fractions rather than on a single dominant constituent. In this Entry, the discussion focuses primarily on metallic alloy systems within this broader framework. HEAs are commonly described as alloys containing five or more principal elements and relatively high ideal configurational entropy; CCAs represent a broader, phase-agnostic category of chemically complex alloys in which multiple elements occupy significant fractions and can form solid solutions, ordered phases, intermetallic compounds, or multiphase microstructures; MEAs generally refer to systems containing fewer principal elements or lower configurational entropy than typical HEAs; and MPEAs describe alloys designed around multiple principal elements without requiring a specific entropy threshold. These terms overlap and are not universally hierarchical, and their use depends on composition, phase constitution, and research context. The large compositional space enabled by these materials provides opportunities for designing face-centered cubic, body-centered cubic, hexagonal close-packed, ordered, eutectic, refractory, interstitially alloyed, and precipitation-strengthened alloy systems. Their properties are governed by the complex interactions among composition, phase stability, chemical ordering, processing route, microstructure, and service environment. This Entry summarizes the fundamental concepts, design approaches, structural characteristics, processing methods, modeling strategies, properties, candidate engineering applications, limitations, and future perspectives of HEAs and related compositionally complex alloys.

Encyclopedia doi: 10.3390/encyclopedia6080170

Authors: Meryem Müzeyyen Fındıkgil Ilke Ciritci Semih Göksel Yıldırım

This review examines non-Muslim cemeteries in Istanbul as multicultural urban heritage landscapes, using the Feriköy Protestant Cemetery as its principal case. Rather than treating cemeteries solely as religious or funerary spaces, it conceptualizes them as material archives of urban memory, minority presence, spatial displacement, and heritage governance. Drawing on a literature review, historical documentation, spatial mapping, and field observation, the article first traces the transformation of non-Muslim cemeteries from the Ottoman period to the Republican period, with particular attention to their relocation, disappearance, and reuse within processes of urban modernization. It then analyses the Feriköy Protestant Cemetery in terms of its establishment, multinational governance structure, architectural and funerary features, transferred memorial elements, digitisation practices, and conservation initiatives. The case illustrates the layered relationships among urban development, multicultural identity, and sustainable conservation. The article argues that Istanbul’s surviving non-Muslim cemeteries should be understood as living spaces of memory and cultural landscapes whose protection requires documentation, public awareness, and multi-actor heritage governance.

Encyclopedia doi: 10.3390/encyclopedia6080169

Authors: Duygu Büyükköse Merve Nur Sarıyer Temelli

Children with hearing loss increasingly participate in inclusive educational settings; however, many continue to experience difficulties in language development, communication access, and classroom participation. This narrative review examines school-based speech–language therapy (SLT) services for children with hearing loss in inclusive educational settings, focusing on language development, service delivery models, and intervention practices. The reviewed literature suggests that language development in children with hearing loss is multidimensional and influenced by multiple interacting factors. Evidence further indicates that intervention outcomes are shaped not only by intervention approaches but also by educational context, classroom communication environments, collaboration among professionals, and students’ individual needs. Interventions tailored to students’ individual needs and implemented within meaningful educational contexts may support communication access, classroom participation, and the functional use of language. At the same time, the available evidence remains heterogeneous, suggesting that service delivery decisions should be guided by students’ individual needs and educational contexts. Overall, the reviewed literature suggests that school-based SLT may contribute not only to children’s language development but also to communication access, classroom participation, and interdisciplinary collaboration in inclusive educational settings. The review also identifies implications for clinical practice and priorities for future research.

Encyclopedia doi: 10.3390/encyclopedia6080168

Authors: Michalis Ioannou Natalia Spyropoulou Achilles Kameas

Competence frameworks function as structured knowledge codification systems: authoritative, domain-wide representations of professional knowledge that define what counts as competence within a field and how it should be organised. As such, they constitute a form of professional knowledge encyclopaedia, structured to comprehensively map an emerging or established knowledge domain. This paper examines how eight EU and international competence frameworks codify AI-related knowledge for STEAM educators, using a dual analytical lens comprising AI-TPACK and STEAMCompEdu. Read through this dual lens, the cross-framework analysis identifies four knowledge dimensions insufficiently addressed in the existing landscape: interdisciplinary pedagogical knowledge, creative-aesthetic AI knowledge, ethics as embedded disciplinary practice, and inquiry-oriented AI pedagogy. Based on these findings, the paper proposes three emerging theoretical extensions to AI-TPACK to address the identified lacunae and discusses implications for the design of structured professional knowledge codification systems that better represent complex, interdisciplinary, and rapidly evolving knowledge domains.

Encyclopedia doi: 10.3390/encyclopedia6080167

Authors: Heru Agung Saputra Muhammad Hanif Amrulloh Nadiya Ayu Astarini Fathan Bahfie David Candra Birawidha Kyeong-Deok Seo Yuanhui Huang Widi Astuti Yeni Wahyuni Hartati

Ion-imprinted polymers (IIPs) are advanced adsorbents featuring selective recognition cavities for targeted metal ion capture, offering a promising route to high-efficiency separation in extractive metallurgy. In the present work, the evolution, design principles, synthesis strategies, separation mechanisms, and practical applicability of IIPs for metal recovery from complex aqueous matrices are overviewed. Key material components, including functional monomers, crosslinkers, template ions, initiators, solvents, and support materials, are discussed in relation to adsorption capacity, selectivity, kinetics, stability, and recyclability. Major preparation routes, such as surface imprinting, bulk polymerization, in situ polymerization, and sol–gel methods, are critically compared to clarify their advantages and limitations. Recent applications for base metals, precious metals, and rare-earth elements demonstrate that IIPs can achieve high specificity and rapid equilibrium under optimized conditions. However, their translation from simulated solutions to real leachates remains constrained by interfering ions, organic contaminants, mass transfer resistance, incomplete template removal, and matrix complexity. Mitigation strategies, including sample pretreatment, improved polymer architecture, and hybrid supports, are therefore emphasized. Additionally, chemometric modelling, machine learning, or artificial intelligence-assisted design may be implemented to advance the prospects of IIPs in industry. Conclusively, IIPs represent a strong separation platform, yet industrial deployment requires robust validation with real feed streams and scalable regeneration protocols during column operation, as well as under chemically aggressive conditions at scale.

Encyclopedia doi: 10.3390/encyclopedia6080166

Authors: João Marôco

The University Student Engagement Inventory (USEI) is a multidimensional self-report instrument designed to assess student engagement in higher education through three interrelated dimensions: behavioral, emotional, and cognitive engagement. Developed within a hierarchical framework, the USEI provides both dimension-specific scores and an overall indicator of student engagement, supporting research, institutional assessment, and educational quality evaluation across diverse cultural and educational contexts. Student engagement is widely recognized as a key determinant of academic success, persistence, and educational quality in higher education. The University Student Engagement Inventory (USEI) was developed to provide a theoretically grounded and psychometrically sound measure of engagement that captures students’ behavioral, emotional, and cognitive involvement in learning activities. This encyclopedia entry reviews the conceptual foundations, development process, factorial structure, psychometric properties, and applications of the USEI. Evidence from multiple studies indicates that the instrument exhibits satisfactory reliability, construct validity, predictive validity, and measurement invariance across different countries, languages, and educational settings. The USEI has been translated and adapted for use in diverse cultural contexts and has been employed extensively in research examining academic performance, well-being, persistence, and learning environments, including online and blended education. Its brevity, multidimensional structure, and cross-cultural validation have supported its use in educational research and institutional assessment. Overall, the USEI represents a robust and versatile instrument for evaluating student engagement and supporting evidence-based improvements in higher education.

Encyclopedia doi: 10.3390/encyclopedia6080165

Authors: Alexandros Gazis Efstathios Karypidis Kleanthi Santamouri Theodoros Vavouras Nikos E. Mastorakis Stylianos Pappas

Deepfakes, synthetic audiovisual content produced by deep generative models, have escalated into a critical threat across civilian and military domains, enabling identity fraud, disinformation campaigns, and evidence fabrication. In high-stakes environments, ranging from journalism and finance to healthcare and legal contexts, the consequences extend to severe misinformation, market manipulation, identity fraud, and the erosion of institutional trust. This entry explores how modern visual intelligence and computer-vision techniques are used to detect deepfakes. It outlines key deepfake generation models, such as GANs, autoencoders, neural rendering, and diffusion systems, while also explaining how adversarial methods enhance realism and challenge existing detectors. The overview highlights visual artifacts, digital patterns, and physiological cues commonly leveraged in detection and reviews major CNN, transformer, and frequency-based approaches. It also summarizes evaluation practices and the difficulty of achieving strong generalization. Finally, it identifies emerging directions, including modern intelligence techniques for civilian and military content verification. This survey covers generation architectures (GANs, latent diffusion, neural rendering, video synthesis), the spatial, temporal, frequency-domain, and physiological artifacts they produce, and the detector families that exploit them. We examine evaluation benchmarks and protocols, highlighting cross-generator generalization as the field’s central open challenge. Beyond detection, we discuss cryptographic provenance standards, watermarking, and regulatory frameworks (EU AI Act, DSA, GDPR). We conclude that effective deepfake governance requires defense in depth integrating forensic detection, verifiable provenance, and institutional accountability.

Encyclopedia doi: 10.3390/encyclopedia6080164

Authors: Sebastián Eustaquio Martín Pérez Carmen Lucía Hernández Stender Aday Infante Guedes Paulino Vico Rodríguez Marta Cano Orihuela Ana María González Martín Antonio Bernal Suárez Isidro Miguel Martín Pérez

Virtual Reality is an interactive technology that creates immersive, computer-generated three-dimensional environments for therapeutic and rehabilitative purposes. In neurorehabilitation, it has been increasingly adopted to support motor, cognitive, emotional, and functional recovery via task-oriented, multisensory, and feedback-driven interventions. Originally developed for exposure-based therapies, its applications have expanded to neurological conditions such as stroke, traumatic brain injury, Parkinson’s disease, multiple sclerosis, spinal cord injury, and chronic pain. Its therapeutic rationale is thought to rely on mechanisms including neuroplasticity, multisensory integration, motor learning, embodiment, and adaptive feedback. Despite the fact that standardized clinical protocols are still evolving, VR is considered a complement to conventional neurorehabilitation, with advances in artificial intelligence and wearable technologies expected to further enhance its clinical applications.

Encyclopedia doi: 10.3390/encyclopedia6080163

Authors: Michelle R. Eades-Baird Emily Hayden

Disciplinary literacy refers to the specialized practices of reading, writing, and reasoning that are unique to each academic discipline—the distinct ways in which scientists, historians, mathematicians, and literary scholars construct, communicate, and critique knowledge within their fields. Although disciplinary literacy is relevant across the lifespan and across all phases of education, its demands become most salient as learners advance through schooling and encounter increasingly specialized texts and discourse conventions. It is distinguished from content-area literacy, which applies general study and comprehension strategies across subjects, and from the foundational literacy skills emphasized in the early-grades Science of Reading. Where foundational literacy concerns the components by which children learn to read (phonemic awareness, phonics, fluency, vocabulary, and comprehension), disciplinary literacy concerns how learners read, write, and think as participants in a discipline once those foundations are largely in place. In secondary teacher preparation specifically, disciplinary literacy denotes both a body of pedagogical knowledge and a set of instructional competencies that content-area teacher candidates are increasingly expected to demonstrate—including the capacity to make discipline-specific reading and writing practices visible and teachable for their students. Its theoretical foundations lie in scholarship documenting that literacy demands become more specialized, rather than more general, as students advance through schooling. As educator preparation systems, particularly in the United States, formally integrate Science of Reading principles into program requirements, disciplinary literacy has emerged as the established, though comparatively less codified, extension of that movement into the secondary content areas, where disciplinary reading and writing instruction have historically received limited systematic attention.

Encyclopedia doi: 10.3390/encyclopedia6080162

Authors: Chaima ElHichou-Ahmed Pedro R. Gil-Monte Hugo Figueiredo-Ferraz

Occupational burnout has become a major topic in occupational health psychology because of its implications for employee well-being, mental health, and organizational functioning. Although the scientific literature has grown steadily, the field still requires an integrated picture of its development, collaboration patterns, and thematic structure. This study examined the evolution, collaboration patterns and thematic structure of occupational burnout research through a bibliometric analysis of publications indexed in the Web of Science Core Collection between 2000 and 2025. A total of 3227 publications were retrieved using a topic-based search focused specifically on occupational burnout terminology. Bibliometric analyses used VOSviewer to map and visualize trends in scientific production, co-authorship networks, country/region collaboration, keyword co-occurrence, and journal citation patterns. The findings indicate an accelerating increase in publication output, from 17 publications in 2000 to 454 in 2025. The period 2020–2025 alone accounted for 2142 publications, representing 66.4% of the corpus. Collaboration analyses revealed an increasingly international field involving 122 countries/regions, with the United States occupying a highly connected position and collaboration clusters emerging in Europe and Asia. Spain also appeared to connect European and Latin American research communities. Thematic mapping showed that burnout is closely associated with organizational variables, psychological distress, healthcare settings, and measurement-related issues. Overall, occupational burnout research has become an internationalized and multidisciplinary field, shaped by the growing relevance of psychosocial risks, mental health, and work-related well-being.

Encyclopedia doi: 10.3390/encyclopedia6080161

Authors: Nathan Tetteh Masa Noguchi

The authors would like to make the following corrections to the published paper [...]

Encyclopedia doi: 10.3390/encyclopedia6070160

Authors: Vincenzo Maria Romeo

Digital dependence and substance use may co-occur in post-digital cohorts when platform design, peer norms, stress exposure, and individual vulnerabilities converge to reinforce dysregulated patterns of reward seeking, self-regulation failure, and affective coping. This Entry defines their co-occurrence as a multidetermined phenomenon in which digital environments, including algorithmic feeds, notifications, social comparison, and variable rewards, interact with developmental vulnerabilities such as identity formation, impulsivity, reward sensitivity, and emotional dysregulation. Psychiatric comorbidities, particularly depression, anxiety, Attention-Deficit/Hyperactivity Disorder, and personality pathology, may increase susceptibility, while socioeconomic disadvantage and unequal access to care can intensify harm. Current evidence suggests that problematic digital use and substance use are more strongly related to functional impairment, coping motives, peer norms, and contextual stressors than to screen time alone. This Entry therefore organizes the available evidence around structural determinants, individual mechanisms, mental-health mediators, and prevention strategies, with emphasis on proportionate regulation, digital literacy, culturally adapted interventions, and integrated clinical pathways.

Encyclopedia doi: 10.3390/encyclopedia6070159

Authors: Thomas I. Wilkes

Pharmaceuticals are essential to modern healthcare but increasingly represent a pervasive and biologically active class of environmental contaminants. Following administration, many drugs are incompletely metabolised in the human body and are excreted as parent compounds or active metabolites, subsequently entering municipal wastewater treatment plants (WWTPs). Conventional treatment processes only partially remove many pharmaceuticals, resulting in chronic sub-therapeutic exposure of microbial communities which act as both functional agents of biodegradation and sensitive ecological targets. Such exposure alters microbial structure and function, reduces biotransformation capacity, promotes the persistence of recalcitrant compounds such as carbamazepine and diclofenac, and drives the selection and dissemination of antibiotic resistance genes. These effects may propagate across aquatic, terrestrial, agricultural, and food systems via treated effluents and biosolids, linking human medical practices to environmental and public health outcomes. By integrating Pharmaceutical science, wastewater engineering, microbiome ecology, and antimicrobial resistance research, this work frames pharmaceutical pollution as a closed-loop OneHealth challenge.

Encyclopedia doi: 10.3390/encyclopedia6070158

Authors: José Luis Aparicio-Herguedas Miriam Molina-Soria Teresa Fuentes-Nieto Víctor M. López-Pastor

The use of Artificial Intelligence (AI) in Formative and Shared Assessment (F&SA) processes refers to the application of AI-based technologies to support formative and continuous assessment in Higher Education (HE). F&SA systems involve the ongoing monitoring of students’ learning, the provision of feedback that enables them to regulate and improve their performance, and the collection of information that informs the continuous improvement of teaching practice. In this context, AI can serve a dual purpose: when orientated towards students, it enhances learning outcomes; when directed at educators, it supports the development of their pedagogical expertise through tools designed to assist in the creation of assessment instruments, the generation of automated feedback, the analysis of learning data, and the design of simulation environments that foster the development of professional competencies. The integration of AI into F&SA practices holds considerable potential to transform traditional assessment approaches by enabling more personalised, adaptive, and timely feedback for both students and educators. In this shared assessment framework, students may likewise draw on AI applications to support specific dimensions of their learning, including academic writing, knowledge organisation, and the generation of educational content, thereby becoming active participants in their own assessment processes. However, the incorporation of AI into F&SA also requires careful consideration of the pedagogical, ethical, and institutional challenges it entails, particularly those related to academic integrity, cognitive offloading, and the responsible use of AI tools. It is therefore essential to promote AI literacy in HE among both faculty members and students, fostering a critical and informed engagement with these technologies that ensures the pedagogical relationship, along with the shared, formative nature of assessment, remains at the core of meaningful learning processes.

Encyclopedia doi: 10.3390/encyclopedia6070157

Authors: Özden Şengül Özge Can Aran

This article aims to inform the scholarly debate on curriculum research in science education through a systematic scoping review of 140 empirical articles from four leading science education journals. Scoping review methodology was selected to map the breadth, nature, and thematic landscape of curriculum research rather than to evaluate intervention effectiveness or establish evidence hierarchies. Data were retrieved through database searches and thematic content analysis of articles published in 2009 through 2025. Based on formulations of scientific literacy framework, the analytic framework was used to conceptualize curriculum research. The review identified seven themes: nature of science and policy; inquiry-based learning; curriculum standards, materials and assessment; scientific practices; context-based and socioscientific issues education; teacher professional development; and equity and social justice. Categories focusing on standards, materials, and content leaned toward Vision I. Categories emphasizing practices, inquiry, and contexts tended to bridge Visions I and II. Categories focusing on social issues and equity tended to cross and link Vision II and III. While the category centered on teacher professional development uniquely encompassed all three visions, Vision II perspectives (science as related to society) remained dominant but increasingly aligned with Vision III frameworks, such as critical engagement, social and political engagement, and transformative education. The review emphasized the critical role of teacher pedagogical design capacity in addressing the implementation differences between intended and actual curricula.

Encyclopedia doi: 10.3390/encyclopedia6070156

Authors: Narcis Eduard Mitu

Artificial intelligence (AI) may raise productivity by automating tasks, augmenting human work and reducing information-processing costs. Yet productivity gains are not necessarily converted into broadly shared purchasing capacity or fully absorbed output. This conceptual review develops the notion of the Distributional Absorption Threshold of AI-Induced Productivity, defined as the point at which AI-related productivity growth outpaces the growth of broadly distributed real purchasing power and household consumption. The framework links AI-induced productivity to labour income, income distribution, prices, investment, fiscal redistribution, external demand and effective demand. It distinguishes a favourable transmission path, in which productivity gains support wages, disposable income, consumption and output absorption, from a critical path, in which weak distributive transmission may generate absorption tension. The review formulates conceptual propositions and preliminary operational indicators for future empirical research while treating the threshold as an analytical construct rather than a fixed empirical constant. Its contribution is theoretical: it reframes the AI productivity debate beyond both technological optimism and automation anxiety by connecting technological change, distribution and demand-side realisation.

Encyclopedia doi: 10.3390/encyclopedia6070155

Authors: Sergio Da Silva Patricia Bonini

Revealed preference is an approach in consumer theory that infers preferences from observed choices rather than treating preferences or utility as directly given. If a consumer chooses one bundle when another bundle is also affordable, the chosen bundle is said to be revealed preferred to the alternative. The theory asks under what conditions such observed choices can be rationalized by a preference relation or a utility function. Observed choices may satisfy local consistency by avoiding direct reversals while still failing to support a single complete and transitive ordering. Stronger acyclicity conditions can restore rationalizability, although finite choice data may still leave the underlying preference ordering underdetermined rather than uniquely identified.

Encyclopedia doi: 10.3390/encyclopedia6070154

Authors: Sayam Chuangprakhon Akapong Phulaiyaw Arthit Khamhongsa Warakorn Seeyo Weerayut Seekhunlio Narongruch Woramitmaitree

The Isan Orchestra is a large-scale homogeneous contemporary musical ensemble in Thailand that systematically integrates traditional Northeastern Thai (Isan) folk instruments using the formal structural, compositional, and architectural frameworks of a Western symphony orchestra. Consisting of 40 traditional Isan folk instruments without Western instrumentation, this ensemble achieves a multi-tonal orchestral dimension by balancing the modal melodies and unique acoustic textures of regional instruments such as the Phin (plucked lute), Whode (circular panpipe), Khaen (free-reed mouth organ), and Pong Lang (log xylophone). The ensemble achieves a multi-tonal orchestral dimension without Western instrumentation. Compositional concepts rely on extracting melodic motifs from traditional folk tunes, transforming them through Western contrapuntal methods, polyphonic textures, and harmonic voice-leading. This entry systemizes the programmatic suite architecture, orchestration grids, and physical seating layouts required to achieve acoustic balance. Through this systemization, this study achieves a fully verified, replicable prototype that successfully transitions orally transmitted regional repertoire into standardized notation. The implications of this model offer a strategic, decolonial framework for institutional safeguarding, enabling Indigenous musical traditions to achieve structural parity and international visibility within higher education.

Encyclopedia doi: 10.3390/encyclopedia6070153

Authors: Lydiah Nganga

Multicultural education remains a foundational yet contested area of teacher preparation in increasingly diverse, unequal, and politically polarized educational contexts. This conceptual review examines multicultural education through culturally responsive, critical, and democratic approaches by synthesizing foundational scholarship and recent research published between 2023 and 2026. Although these traditions have been widely examined, they are often treated as separate perspectives, limiting the development of a coherent framework for teacher preparation across diverse educational settings. Guided by the question of how multicultural education is conceptualized, enacted, and sustained within teacher preparation programs, the review argues that multicultural education is most effective when embedded throughout curriculum, assessment, clinical practice, and program design rather than confined to stand-alone diversity courses. The synthesis demonstrates that implementation remains predominantly fragmented or additive, acknowledging diversity without systematically advancing equity. To address this limitation, the article proposes an integrative conceptual framework organized around three complementary pedagogical orientations—culturally responsive, critical, and democratic—operationalized through reflective practice, curriculum transformation, community and contextual engagement, and pedagogical translation. The framework further incorporates contemporary scholarship on intercultural education, culturally sustaining pedagogy, democratic citizenship, Indigenous education, and decolonizing perspectives, extending existing conceptualizations of multicultural teacher preparation. The review concludes by identifying persistent challenges related to institutionalization, faculty capacity, policy contexts, and assessment while outlining directions for future research and program development across diverse national and sociocultural contexts. By integrating recent scholarship within a unified conceptual framework, the article offers teacher educators, researchers, and policymakers a comprehensive model for designing coherent, equity-oriented teacher preparation programs.

Encyclopedia doi: 10.3390/encyclopedia6070152

Authors: Christian Stary

Transhumanism subsumes system developments extending human capabilities, whereas posthumanism includes developments beyond actors and processes in human life. It affects agency and identity development, bringing into play ‘more-than-human-centered design’ of technology-based artefacts. Transhumanism uses science and technology to expand human capabilities, in particular intellect and health. Posthumanism addresses the co-existence of human and artificial actors while decentering human actors. It examines how technology has already and is still influencing agency and identity without necessarily requiring physical extensions. Both approaches affect (future) system development. Socio-technical system design can contribute to the respective discourse. Key issues relevant for transhumanist concerns are the dynamics of socio-technical system design, the functional, communication, and interaction capabilities of networked system elements (including human support), and learning infrastructures. Considering this structure and these capabilities lays the ground for approaching posthuman system design issues in terms of representing networked entities and their behavior albeit their different nature of actors. Implementation of a respective framework requires enabling infrastructures for the (dynamic) reconfiguration of heterogeneous networked components. The entry finally discusses how such a design framework could inform future research at the intersection of design theory, human–technology integration, and critical futures studies.

Encyclopedia doi: 10.3390/encyclopedia6070151

Authors: Nicolas Lainé

Anthropology in One Health refers to the use of anthropological concepts, methods and field-based approaches to analyse health problems at the intersections of humans, animals, plants, microbes and environments. It examines how disease, risk, care, surveillance and prevention are understood, negotiated and organised in specific social and ecological settings. Its contribution is not simply to add a “social dimension” to biological problems already defined elsewhere. It also asks how a health problem is framed in the first place, whose observations are recognised as evidence, and how different ways of describing a situation shape the interventions that become possible. In this entry, One Health is approached primarily as a collaborative field of practice rather than as a single theoretical concept, bringing together ethnography, medical anthropology, political ecology, multispecies approaches, ethnobiology and studies of Indigenous and local knowledge.

Encyclopedia doi: 10.3390/encyclopedia6070150

Authors: Mihail Kolev

Machine learning (ML) in materials science refers to computational methods that learn statistical, structural, or physics-informed relationships from experimental, computational, and literature-derived materials data. These methods are used to predict materials properties, identify structure–property and process–structure–property–performance relationships, discover candidate materials, optimize synthesis and processing routes, and guide functional applications. ML is narrower than artificial intelligence (AI), which also includes broader reasoning, planning, search, and automation capabilities. It is also distinct from materials informatics, which is the wider data-centered framework that includes databases, descriptors, metadata, workflows, visualization, and knowledge management. ML can complement high-throughput computation by building surrogate models from density functional theory, finite-element simulation, molecular dynamics, or experimental data, but it is not identical to high-throughput screening itself. Unlike conventional physics-based modeling, which begins with explicit governing equations or mechanistic assumptions, ML usually infers predictive relationships from data; modern approaches increasingly combine both perspectives through physics-informed features, uncertainty quantification, and human expertise.

Encyclopedia doi: 10.3390/encyclopedia6070149

Authors: Fernando Sánchez

The Misery Index (MI), also known as the Economic Discomfort Index, is a macroeconomic gauge originally proposed by Arthur M. Okun. It is defined as the unweighted sum of inflation and unemployment rates. This indicator attempts to synthesize the main factors generating economic malaise and collective discomfort, although it has been criticized for being an oversimplification of the economic problems faced by average citizens. Consequently, researchers have modified this index by incorporating variables associated with informality, interest rates, and economic growth, among others. Despite its simplicity, the MI has been utilized to describe the behavior of numerous social phenomena, such as suicide, the inclination to gamble, and tourism. However, the index has also been criticized for the inherent difficulty of associating its behavior with specific policy actions. This paper presents the main criticisms that this index has received, as well as its main applications and the various modifications it has undergone over time.

Encyclopedia doi: 10.3390/encyclopedia6070148

Authors: Amir M. Horr

Data science methodologies are playing an increasingly important role in advancing manufacturing systems, enabling improvements in efficiency, energy usage, cost reduction, product quality, and predictive maintenance capabilities. This raises a fundamental question: to what extent can data models reshape manufacturing processes, and what limitations prevent their full-scale adoption? Recent developments show a growing integration of data models within digital twin and digital shadow architectures, facilitating real-time monitoring and decision-making. Nonetheless, the complexity of industrial processes and the scarcity of high-quality, well-structured datasets pose significant challenges, particularly in terms of model robustness, interpretability, and scalability. Importantly, the effectiveness of such models depends more on data quality and representativeness than on data quantity alone. This review presents a structured analysis of data modeling techniques for manufacturing applications, with emphasis on data generation, sampling, preprocessing, and modeling approaches across diverse operational regimes, including steady, transient, and generative processes.

Encyclopedia doi: 10.3390/encyclopedia6070147

Authors: Antonio Cicchella Zhenyu Li

The scientific foundations of sport-training methodology are commonly attributed to physiological principles; however, the extent to which these principles directly inform practical training models remains unclear. This narrative review examines the historical development of training theory—from early adaptology and integrative physiology to contemporary molecular discoveries in muscle biology—and evaluates their relevance to strength development. Strength expression is shown to be highly variable, influenced by neural, mechanical, technical, and psychological factors, challenging the traditional reliance on fixed percentages of maximal strength for training prescription. Additional complexities arise from individual response variability, performance plateaus, and the interference between molecular pathways activated by strength and endurance training. Emerging artificial intelligence systems offer new opportunities for individualized training optimization, injury prediction, and motor-learning analysis, while advances in brain decoding technologies highlight the potential role of willpower and cognitive processes in strength expression. Overall, current training methodologies remain heterogeneous and incomplete, although recent evidence increasingly supports modality-specific prescription principles based on load, contraction velocity, movement intent, and athlete training status. So, substantial research is required to more clearly connect physiological mechanisms with practical training applications.

Encyclopedia doi: 10.3390/encyclopedia6070146

Authors: Nuno da Silva Jorge

Public Relations (PR) is the strategic role of communication between an organization or public actor and the publics on whose recognition, trust and consent its operation depends. The field encompasses media relations, internal and employee communication, public affairs and government relations, crisis and reputation management, community relations and corporate social responsibility, investor relations, marketing communications, political communication, digital and platform engagement, and the communication of activist and non-governmental organizations. PR scholarship draws on sociology, political philosophy, organizational studies, rhetoric and media studies to examine how organizations construct, sustain and contest their legitimacy in the public sphere. The dominant theoretical framework of the late twentieth century, the Excellence Theory developed by James Grunig and colleagues, defined PR as the symmetrical management of relationships with strategic publics; the field has since broadened to include relational, dialogic, rhetorical, situational, contingent and critical approaches, alongside frameworks grounded in stakeholder theory, institutional analysis and emerging work on public legitimacy. Contemporary PR operates within a hybrid media environment shaped by digital platforms, algorithmic visibility, generative artificial intelligence and the structural erosion of institutional trust. It is simultaneously a professional industry of significant global economic scale and a contested civic function whose democratic role, ethical foundations and disciplinary boundaries remain the subject of active scholarly debate.

Encyclopedia doi: 10.3390/encyclopedia6070145

Authors: Miguel Juárez-Marín Francisco José López-Avilés Luis Tortosa-Díaz Jorge Saura-Martínez Ginés Benito Martínez-Hernández Asunción M. Hidalgo Antonio López-Gómez Fulgencio Marín-Iniesta

Paprika is a spice obtained from the dehydration and grinding of red pepper fruits, primarily from the Capsicum annuum species. Its etymology comes from Slavic Balkanian languages and was adopted in Hungarian. The crop originated in America, where it was domesticated by pre-Columbian civilizations over 6000 years ago (specifically in present-day Mexico) for medicinal and culinary purposes. Following the Spanish arrival in the Americas in the 15th century, pepper was introduced first in Spain (Sevilla, Extremadura and Murcia) and later in the rest of the Old World. The agroclimatic conditions of different Mediterranean regions made it an essential crop, turning these regions into centers of production and giving this spice a sense of cultural identity. The purpose of this study lies in the technological and nutritional significance of paprika in the modern food industry, where it is demanded as a natural colorant, preservative and source of bioactive compounds, such as antioxidants and carotenoids. Despite its prevalence, the existing literature is often fragmented into specific disciplines. This article distinguishes itself by proposing a holistic approach expanding the study from its historical evolution to its socioeconomic impact, including its agronomic characteristics and industrial-scale production. It is recommended that the research community and producers focus on the sustainability of processing methods while preserving cultural authenticity, ensuring the preservation of the functional and culinary relevance of this spice.

Encyclopedia doi: 10.3390/encyclopedia6070144

Authors: Vlad Glăveanu Maire Dee Muhammad Saiful Islam Hasrizal Andreea Tofan Conor Nolan

Possibility Studies are an emerging interdisciplinary field concerned with how individuals, groups and societies engage with possibilities, including imagined futures, unrealised alternatives and transformative forms of action. Drawing on psychology, sociology, anthropology, philosophy, creativity research, futures studies and related disciplines, it examines how possibilities are perceived, constructed, negotiated, constrained and enacted within cultural, social and material contexts. Central topics include imagination, agency, anticipation, creativity, counterfactual thinking, hope and social transformation. What distinguishes Possibility Studies is their focus on possibility itself as an object of inquiry. Rather than concentrating on a single domain such as creativity, innovation, futures, identity or social change, the field investigates the conditions under which alternatives become imaginable, the factors that enable or constrain them, and the processes through which they are explored and realised. Possibility Studies therefore serve as a cross-disciplinary framework for understanding how people and societies engage with uncertainty, openness and the not-yet-realised dimensions of life. Although the term is relatively recent, the field builds on longer intellectual traditions concerned with imagination, becoming, human potential and the open-ended nature of social reality. It has gained increasing relevance in response to contemporary challenges such as ecological crisis, technological transformation and political uncertainty, all of which raise fundamental questions about alternative futures and the capacity to shape them.

Encyclopedia doi: 10.3390/encyclopedia6070143

Authors: Lorena Espina-Romero Jorge Izaguirre Olmedo Angélica Ochoa-Díaz Omar El Kadi Janbeih Karla Rojas Jimenez Hugo Benzaquen Hinope

Digital transformation and artificial intelligence are reshaping nursing education by changing how students access information, complete academic tasks, and engage with technology-mediated learning. However, evidence on digital competencies, AI-related constructs, mediating mechanisms, and academic performance remains fragmented and methodologically uneven. This systematic review of empirical studies synthesized how digital competencies and AI-related constructs are associated with academic performance and learning-related outcomes in nursing education. Following PRISMA 2020 guidelines adapted to social science research, searches were conducted in Scopus and Web of Science Core Collection in March 2026, covering 2022–2026. Twenty-five empirical studies were included: 18 quantitative, 4 qualitative, and 3 mixed-methods studies. The evidence was concentrated in the Middle East and North Africa, Asia, and Europe. Findings suggest that digital competencies are associated with academic and learning-related outcomes mainly through self-efficacy, academic motivation, cognitive presence, and learning flow. AI-related evidence remains emerging, mixed, and context-dependent. Although some AI-assisted interventions reported favorable outcomes, one experimental study found greater knowledge gains with traditional text-based study than with ChatGPT-assisted learning. Therefore, AI integration should not be considered universally beneficial, but contingent on pedagogical design, task type, teacher guidance, AI literacy, responsible use, and critical verification.

Encyclopedia doi: 10.3390/encyclopedia6070142

Authors: Adriaan De Man Mohamed Khater

Artificial Intelligence (AI) in heritage management refers to the use of computational systems for tasks conventionally associated with human intelligence. These range from pattern recognition to prediction and language processing, among other dimensions such as image analysis or decision support, across the cultural and creative industries. AI applications are commonly applied in daily settings, namely for site management and visitor experience enhancement. Beyond its multiple technical functions, AI acts as a mediating infrastructure that influences how heritage knowledge is produced. Consequently, AI raises epistemological, ontological, ethical, and political questions for the future of heritage management. This entry takes into account the interconnected concepts of authenticity, authority, representation, and participation.

Encyclopedia doi: 10.3390/encyclopedia6070141

Authors: Nicolo John L. Bernaldo Felicity S. Pogenio Alexa T. Anicete Justine G. Baje Sheenah Kate V. Fetalvero Paul Dexter T. Tiquez Arnel O. Rendon Ace Bryan Sotelo Cabal Huai-Ying Huang Po-Hua Wu Kuo-Pin Chuang Brian Harvey Avanceña Villanueva

This scoping review evaluates the role of vector-associated dissemination in contaminating the Philippine food supply chain with antimicrobial-resistant (AMR) Salmonella, an emerging infectious disease threat, using a One Health perspective to map the mechanisms through which insects and rodents bridge environmental reservoirs to human food systems. This scoping review was conducted and reported in accordance with the PRISMA-ScR guidelines. From 1969 records identified through systematic database searches, 52 studies met the inclusion criteria. These comprised 21 primary Philippine studies, 28 non-Philippine studies (including ASEAN-based historical baseline reports), and 3 policy/gray literature studies, prioritized to reflect tropical ecological and agricultural settings. Results suggest that intensive swine and poultry farming may contribute to the emergence of multidrug resistance (MDR) linked to genes such as blaTEM and qnr. Evidence suggests that Salmonella persists in environmental matrices, such as manure and irrigation water, and that synanthropic vectors, including Rattus rattus and various fly species, potentially serve as biological and mechanical bridges in transmission. Clinical data reveal an alarming trend toward invasive non-typhoidal salmonellosis (iNTS) showing reduced susceptibility to cephalosporins and fluoroquinolones. Despite these findings, major evidence gaps remain, particularly regarding the prevalence of vector-borne Salmonella in pre-harvest produce. Consequently, mitigation requires a One Health framework that integrates non-antibiotic interventions, pest management to disrupt transmission pathways, and rapid diagnostic tools, such as loop-mediated isothermal amplification (LAMP), to enhance market surveillance.

Encyclopedia doi: 10.3390/encyclopedia6070140

Authors: Klára Czimre

Cross-border cooperation (CBC) is defined as the structured, institutionalized, or informal collaboration between adjacent regional and local authorities, economic actors, and civil society groups across international state borders. Within contemporary border studies, CBC has transitioned from traditional top-down, state-centric diplomatic containment toward bottom-up, grassroots territorial integration. This entry synthesizes the multidisciplinary evolution of CBC across geography, economics, jurisprudence, sociology, and political science, structuring the analysis around four core dimensions: spatial, political, economic, and socio-cultural. It categorizes diverse territorial and governance mechanisms of cooperation, ranging from localized town twinnings to formalized Euroregions and European Groupings of Territorial Cooperation (EGTCs), and introduces quantitative performance metrics such as the Cross-Border Activity Index (CBAI). Examining how these structures operate along both the internal and external borders of the European Union, this entry analyzes the cyclical, non-linear dynamics of the bordering–debordering–rebordering framework. By evaluating diverse theoretical models across varying geopolitical contexts, it identifies the universal characteristics of contemporary border dynamics, conceptualizing borders not merely as physical or political demarcations, but as analytical lenses reflecting broader processes of globalization, regionalization, and territorial resilience.

Encyclopedia doi: 10.3390/encyclopedia6070139

Authors: Mihail Kolev

Metal matrix composites (MMCs) are engineered multiphase materials in which a continuous metallic matrix contains deliberately introduced reinforcing phases. Their properties arise from the combined effects of the matrix, reinforcement, interface, processing route and spatial architecture. The matrix provides metallic continuity, plastic deformation capacity, processability and thermal or electrical conduction, whereas the reinforcement is selected to modify stiffness, strength, hardness, wear resistance, thermal stability, corrosion response or functional behavior. From a practical interpretation standpoint, MMC performance should not be ascribed solely to the reinforcement fraction, but rather to the coupled effects of reinforcement distribution, interfacial bonding, porosity, residual stress, heat-treatment state, and architecture.

Encyclopedia doi: 10.3390/encyclopedia6060138

Authors: Cèlia Llurba Gabriela Fretes Antoni Martínez-Ballesté Ramon Palau

The integration of Artificial Intelligence (AI) into smart classrooms (SCs) has accelerated in recent years, fostering new forms of interaction, personalization, and data-driven educational decision-making. Despite this growing interest, the literature remains conceptually fragmented, particularly regarding how AI is integrated across the technological, pedagogical, and environmental dimensions of SCs. This systematic literature review aims to provide a structured synthesis of how AI is integrated into SC contexts, their main functions, their relation to these three dimensions, and the teacher’s role in the system. Following PRISMA guidelines, peer-reviewed studies published between 2021 and 2026 were selected from Web of Science and Scopus, yielding a final corpus of 29 studies. The findings showed that AI integration is mostly concentrated in the technological dimension. The pedagogical dimension is linked to personalization, active learning, formative assessment, and instructional adaptation, while the environmental dimension is less developed. Teachers remain central actors who integrate technological tools, interpret the generated data, and mediate pedagogical decisions. Overall, AI-supported SCs are not only defined by technology but also by pedagogical use and teacher mediation.

Encyclopedia doi: 10.3390/encyclopedia6060137

Authors: Hakan Öntaş Harun Çiğdem

Generative Artificial Intelligence (GenAI) in cardiac surgery refers to the integration of advanced computational models, such as Large Language Models (LLMs), to automate and enhance clinical decision-making, preoperative risk assessment, and surgical education. In the context of surgical training, it functions as a personalized pedagogical tool that supports various learning activities, ranging from information acquisition and clinical inquiry to procedural practice, while requiring rigorous human oversight to ensure patient safety and clinical accuracy. (1) Background: Generative Artificial Intelligence (GenAI) is increasingly integrated into health professions education, offering new opportunities for learning; however, its specific application and pedagogical mapping in high-stakes fields such as cardiac surgery remain underexplored. This systematic review investigates how GenAI is utilized in cardiac surgery and surgical education, aligning these uses with Laurillard’s six learning types. (2) Methods: Following the PRISMA 2020 guidelines, we searched the Web of Science Core Collection for studies on GenAI in cardiac surgery, resulting in 42 studies that met the inclusion criteria. Study quality was appraised using the Medical Education Research Study Quality Instrument (MERSQI). (3) Results: GenAI applications most frequently supported clinical inquiry (93.8%) and practice (68.8%), demonstrating expanding efficiency across commercial and open-source models (including ChatGPT-4o, Gemini AI, and emerging reasoning architectures such as DeepSeek) for knowledge acquisition and medical production. While it significantly improves individualized learning and preoperative assessment workflows, its practical role in Discussion and Collaboration remains heavily underutilized, highlighting a distinct shift toward individualized solo professional workflows. (4) Conclusions: GenAI provides a transformative and scalable approach to cardiac surgical training by offering personalized and accessible knowledge retrieval. However, clinical educators and governance bodies must deliberately balance these immediate productivity benefits with long-term concerns regarding structural “hallucinations,” data verifiability, and the preservation of collaborative competencies within modern multidisciplinary Heart Teams.

Encyclopedia doi: 10.3390/encyclopedia6060136

Authors: Jerred Junqi Wang

Background: This scoping review examines how schedule-related load affects athletic and team performance in professional sport, an issue that has received less systematic attention than training and competition load despite its clear implications for recovery, injury risk, and performance. Methods: Following PRISMA-ScR guidelines, Web of Science, SPORTDiscus, Scopus, and MEDLINE were searched for relevant publications (1993–2025) examining schedule-related load in professional sport. Five theoretical frameworks (Fitness-Fatigue, Circadian Disruption, Allostatic Load, Training-Injury Prevention, and Conservation of Resources) were used to interpret underlying mechanisms. Results: Seventy-two sources were included. At the athlete level, schedule-related load degrades physical performance, impairs sleep and recovery, increases injury risk, and disrupts circadian function. At the team level, it deteriorates game outcomes, alters offensive and defensive strength, and constrains lineup management. Six research gaps were identified involving measurement, interaction effects, advanced metrics, player heterogeneity, integration with training load, and longitudinal analysis. Conclusions: The findings position schedule design as a measurable performance variable and highlight the need for more rigorous sport analytics research to support evidence-based optimization of competition calendars and workload management.

Encyclopedia doi: 10.3390/encyclopedia6060135

Authors: Andrés González Novoa María Lourdes C. González Luís Pedro Perera Méndez María Daniela Martín Hurtado

Strategic Autobiographical Narrative is a pedagogical concept designating the deliberate and structured use of self-narration as a tool for learning, identity reconstruction and community engagement in contexts of social exclusion. Its strategic dimension lies in the conscious articulation of memory, language and transformative action: converting lived experience into pedagogical material capable of resignifying biographical trajectories, sustaining the openness of identity to new readings, and projecting possible futures from a critical and communal perspective. The concept operates through three synchronic registers: as temporal mediation, reopening biographical time where institutions tend to freeze it; as identity mediation, sustaining the mobility of the self against classificatory fixation; and as relational mediation, creating the conditions for the intersubjective event of recognition within a space of non-judgmental listening. Against the disciplinary institution’s tendency to fix identity under a single classificatory reading, the concept recovers the subject’s capacity to reinscribe their past within an open narrative and project a future not prefigured by their carceral present. Its operational methodology is structured around the ELCEN method—listen, read, converse, write and narrate—and deploys diverse autobiographical pathways oriented toward both the reconstruction of the subject’s identity and the community’s sensibilisation in the process of social reintegration. At its core lies a conviction safeguarded by oral tradition for millennia before anyone theorised it: to narrate is to coexist.

Encyclopedia doi: 10.3390/encyclopedia6060134

Authors: Mihail Kolev Tatiana Simeonova

Digital tools in aluminum alloy processing are computational, sensing-based, and data-driven methods used to understand, predict, monitor, optimize, and control how aluminum alloys are transformed into components. They support decisions across casting, deformation processing, heat treatment, welding, surface engineering, and additive manufacturing by linking processing conditions with geometry, microstructure, defects, properties, and service performance. In technical use, the term includes finite element method (FEM), computational fluid dynamics (CFD), CALculation of PHAse Diagrams (CALPHAD), microstructure models, machine-learning regressors, surrogate models, nondestructive digital inspection, image-analysis tools, and digital twins. These tools are most effective when they establish links among controllable processing variables, underlying metallurgical mechanisms, measurable quality indicators, and service-relevant performance outcomes.

Encyclopedia doi: 10.3390/encyclopedia6060133

Authors: Nii A. Tawiah Alberta N. A. Aryee

West African cuisine is among the world’s most complex and historically significant culinary traditions, shaped by diverse ecosystems, centuries of trans-regional trade, and the cultural heritage of more than three hundred distinct ethnic groups spanning the Atlantic coast and the Sahel. West African cuisine has undergone a significant cultural and culinary transformation in the American food landscape, moving from relative obscurity to mainstream visibility. This entry examines the rise of West African cuisine in the United States, with particular attention to jollof as a cultural symbol of identity, diaspora, and culinary diplomacy. Drawing on academic scholarship, food journalism, and primary cultural sources, the entry traces the historical roots of West African foodways through the transatlantic slave trade and their enduring influence on American culinary traditions. It further explores how contemporary chefs, restaurateurs, and food writers of West African descent, including Eric Adjepong, Pierre Thiam, and Kwame Onwuachi, have elevated the cuisine within American fine dining and popular culture. The entry also addresses the role of social media, particularly the viral “Jollof Wars,” in amplifying West African culinary culture globally, culminating in UNESCO’s recognition of Senegalese jollof rice as an element of intangible cultural heritage. Questions of structural barriers, authenticity, and representation are critically examined. The entry argues that while West African cuisine is experiencing unprecedented visibility in America, its mainstream acceptance remains mediated by cultural filters that risk diluting its complexity and richness. Ultimately, this entry positions West African cuisine not merely as a culinary trend but as a living expression of diasporic identity, cultural resilience, and global influence.

Encyclopedia doi: 10.3390/encyclopedia6060132

Authors: Stelios Pantazidis

The terms democracy and the pedagogy of the possible name an approach imagining schools as sites where more just, inclusive and participatory collective life can be practised, particularly in early childhood. The entry brings three traditions into dialogue. (a) Critical pedagogy, particularly in its post-structuralist, Foucauldian, and post-Marxist readings, engages with Rancièrian critiques of pedagogical mastery and offers a vocabulary for examining how power, knowledge, subjectivity, and hegemony are produced and contested within educational life. (b) Freinet pedagogy, extended through Fernand Oury’s Institutional Pedagogy, contributes a politically grounded, practice-first repertoire of cooperative techniques, classroom institutions, and democratic forms of organisation. (c) Educational commons approaches frame knowledge, space, time, and pedagogical relations as shared goods, collectively produced, cared for, and democratically governed by a community of teachers, children, and families. In this perspective, the child is approached as a commoner and agent in the here and now. The educator, in turn, is understood as a fellow commoner and reflexive practitioner, capable of acting beyond the logics of both the state and the market. Together, they co-shape the everyday life of education. Eight shared dimensions, namely the relational, the political, praxis, agency, anti-enclosure, prefiguration, community, and the schoolized mind, traverse all three traditions, with care as their transversal thread. The framework is conceived as a hospitable theoretical and practical space, not as a self-contained doctrine. It is heuristic in orientation, bringing these traditions into conversation because each contributes a complementary layer to democratic educational life.

Encyclopedia doi: 10.3390/encyclopedia6060131

Authors: Ahmed Hashim Azeez Harshitha Vallabhaneni Adhith Theyver Sreesha Phani Durga Rithika Kodamanchili Taha Kassim Dohadwala Vraj JigarKumar Rangrej Yan Leyfman Chandler Park

Sickle Cell Disease (SCD) is a pervasive monogenic disorder characterized by chronic hemolytic anemia, unpredictable vaso-occlusive crises, and progressive multi-organ damage, representing a significant global health burden. Driven by a point mutation in the β-globin gene, the resulting abnormal Hemoglobin S (HbS) polymerizes under deoxygenated conditions, leading to erythrocyte sickling and systemic endothelial dysfunction. While supportive therapies such as hydroxyurea and transfusions manage symptoms, the mandate for definitive curative therapies is urgent. Historically, allogeneic hematopoietic stem cell transplantation (HSCT) utilizing matched sibling donors (MSD) has been the sole curative option, offering high survival rates but constrained by limited donor availability and the risk of graft-versus-host disease (GVHD). Consequently, alternative donor sources, including matched unrelated donors, umbilical cord blood, and haploidentical donors, have expanded patient access, particularly with the integration of post-transplant cyclophosphamide (PTCy) to mitigate alloreactivity. Concurrently, the advent of autologous gene therapy, encompassing lentiviral gene addition (Lyfgenia) and CRISPR-Cas9 gene editing (Casgevy) offers a revolutionary donor-independent approach that eliminates GVHD risk. Lyfgenia employs a lentiviral vector to introduce an anti-sickling βT87Q hemoglobin variant into autologous hematopoietic stem cells, while Casgevy employs CRISPR-Cas9 to disrupt the erythroid-specific enhancer of the BCL11A transcription factor, derepressing γ-globin expression and elevating fetal hemoglobin. This review synthesizes the pathophysiological mechanisms of SCD, evaluates the clinical outcomes and limitations of both allogeneic HSCT and autologous gene therapies, and outlines the clinical decision-making paradigms and future innovations required to achieve equitable global access to these transformative treatments.

Encyclopedia doi: 10.3390/encyclopedia6060130

Authors: Darren K. Griffin Rebecca E. O’Connor Luciano C. Pozzobon Worapong Singchat Kornsorn Srikulnath Denis M. Larkin Rafael Kretschmer Michael N. Romanov

Contemporary iterations of avian phylogenies based on multiple genome sequence assemblies assign three major clades: Palaeognathae (mostly ratite birds), Galloanseres (land and waterfowl) and the largest group—Neoaves. The latter two are sister clades representing subdivisions of Neognathae, while Neoaves further subdivide into Columbaves (pigeons/doves/cuckoos/bustards, etc.), Mirandornithes (flamingos/grebes), Telluraves (“higher land birds”, including finches) and the newly recognized Elementaves (e.g., penguins/pelicans/hummingbirds/swifts/cranes/shorebirds). Molecular studies provide clade information, likely divergence timings and a framework from which gross genomic (chromosomal) changes may be mapped. In this review, we consider the patterns of chromosome change that have occurred throughout all avian clades thus far examined, citing studies from standard karyotyping through molecular cytogenetics to whole genome assemblies. Standard karyotyping led to the realization that most chromosomes (particularly the microchromosomes and dot chromosomes) could not be distinguished by classical means. Indeed, cross-species comparisons were difficult, even among the macrochromosomes, because of indistinct banding patterns. Based on fluorescence (or fluorescent) in situ hybridization (FISH), comparative genomics was thence progressed considerably by cross-species chromosome painting (Zoo-FISH) for the macrochromosomes and interspecific mapping of bacterial artificial chromosome (BAC) probes for the microchromosomes. A key finding was that the most studied species, the chicken, fortuitously, has a genomic organization somewhat akin to that of the ancestral karyotype and tends to be the standard from which all others are measured. A notable exception is the fusion of basal chromosome 4 with a smaller chromosome that convergently appears in some other Galliformes, at least one goose and one dove species. While some groups such as Falconiformes (falcons, etc.) and Psittaciformes (parrots, etc.) underwent extensive interchromosomal change, most, broadly speaking, retain a basic karyotype that differs little from bird to bird. Many, e.g., Passeriformes (finches, songbirds, etc.) and Columbiformes (pigeons, doves), do this despite multiple intrachromosomal rearrangements. The complete karyotype and fully established chromosome-level genome assembly of the chicken allow full integration of DNA sequence assembly with karyotype. They further permit cytogenetic studies to be performed using genome assemblies alone alongside cutting-edge long-read sequencing and optical mapping without the need for chromosome preparation. The classic ZW sex-determination system of birds is easily visible in most Neognathae species, but intrachromosomal change in the sex chromosomes is faster than in the autosomes; indeed, there are numerous examples of autosomal fusions and new sex chromosomes formed. Sex chromosomes aside, the classic avian karyotype represents a very successful mode of genome organization established before the emergence of the dinosaurs and perpetuated to this day in their only living descendants.

Encyclopedia doi: 10.3390/encyclopedia6060129

Authors: Sheng-Ping Yang

This review examines the relationship among foreign direct investment (FDI), trade openness, and economic growth, with emphasis on the channels through which external integration influences development outcomes. The literature generally suggests that FDI can raise growth through capital accumulation, technology transfer, productivity gains, and stronger linkages with domestic firms, while trade openness can promote growth by expanding market access, increasing competition, and improving resource allocation. However, the evidence is not uniform: some studies report that trade openness is the main driver of growth, while others find that FDI has a stronger effect, or that both variables matter only under favorable macroeconomic, institutional, and financial conditions. This review synthesizes theoretical arguments and empirical findings, identifies major transmission mechanisms and conditional factors, and highlights the policy environment needed for FDI and trade liberalization to translate into sustained economic growth.

Encyclopedia doi: 10.3390/encyclopedia6060128

Authors: Jose Israel Cardenas-Jimenez Diógenes de Jesus Ramirez-Ramirez Cristian David Correa-Álvarez

Bamboo as a functional gradient biomaterial refers to the understanding of bamboo culms as naturally hierarchical, anisotropic, and radially heterogeneous lignocellulosic structures whose mechanical, chemical, and conversion properties vary across the wall thickness. Gradients in fiber volume fraction, vascular bundle distribution, moisture, density, mineral content, and silica deposition influence stiffness, strength, durability, permeability, surface hardness, and thermal conversion behavior. This entry treats bamboo not only as a renewable plant resource, but also as a biologically organized material platform for structural components, engineered composites, and carbon-rich products such as biochar and activated carbon. A gradient-based view helps connect bamboo characterization with layer-aware processing, feedstock classification, and circular bio-based material design.

Encyclopedia doi: 10.3390/encyclopedia6060127

Authors: Inmaculada Martínez-García Hans De Witte Francisco Javier Cano-García Jesús García-Martínez

Doctoral student wellbeing refers to the perceived state of psychological, physical, and social health experienced by a person during the process of completing a doctoral thesis. From a eudaimonic and salutogenic perspective, this construct goes beyond the mere absence of distress and incorporates dimensions such as meaning and purpose in life, personal growth, autonomy, feelings of mattering, and the quality of academic and personal relationships. It is a multidimensional construct shaped by the interaction between personal variables, including prior psychological history, personality traits, and task motivation, among others, and contextual variables, such as funding conditions, quality of supervision, departmental culture, family and personal circumstances, and social and institutional support networks. Doctoral wellbeing is therefore dynamic: it evolves throughout the different phases of the doctoral process and is influenced by conditions specific to this population that distinguish it from other groups of students or workers. It has emerged as a critical concern in higher education research, driven by evidence of high rates of psychological difficulties among this population. This entry paper offers a narrative and conceptual review of the current state of knowledge on doctoral student wellbeing, identifying the main challenges facing this group, the factors that influence their wellbeing, and the pathways forward in terms of intervention and future research.

Encyclopedia doi: 10.3390/encyclopedia6060126

Authors: Cherry Canovan

Science Festivals are public events focused on showcasing science, technology, engineering, and mathematics in a celebratory and engaging setting similar in atmosphere to an arts or music event. Aimed at the general public, science festivals vary widely in form and duration, lasting from anywhere between a day and several weeks, and featuring interactive activities such as hands-on workshops, live demonstrations, lectures, and performances. Many include dedicated programming for schools, but they differ from school-based science fairs, which are aimed primarily at students and parents and are typically held on school premises. Their aims include sparking curiosity, promoting scientific literacy, enabling visitors to interact with working scientists, and making science fun and accessible. Festivals are distinct from other informal science engagement formats due to their temporary, joyful nature and diversity of offerings. The modern science festival concept originated in Edinburgh in 1989 and has since experienced rapid global spread. Hundreds of events now take place annually throughout Europe and North America, and to a lesser extent other parts of the world, supported by associations such as the UK Science Festivals Network, the European Science Engagement Association, and, in the USA and Canada, the Science Festival Alliance. Some of the largest festivals see attendance figures in the hundreds of thousands, and across the world, millions of people participate every year. An emerging body of research literature, situated within a variety of social science disciplines and lenses, suggests that festivals are greatly enjoyed by their attendees, and succeed in boosting science interest, increasing knowledge, and improving perceptions of science among visitors, making them a potential asset for societies that place a high value on scientific activity among the population. However, the events have also attracted criticism for their limited audience diversity, with visitors being disproportionately drawn from highly educated and affluent groups, prompting suggestions that they are ‘preaching to the converted’. In response, some festivals have introduced targeted initiatives such as community outreach and partnerships to attract audiences from underrepresented communities. Despite these ongoing challenges, science festivals continue to evolve and grow as platforms for inspiring curiosity and fostering meaningful public dialogue around key scientific topics.

Encyclopedia doi: 10.3390/encyclopedia6060125

Authors: Yuval Reiser Luka Marković Ivica Pelivan Ana Ivanišević Dragana Gabrić

The term “periapical lesion” refers to a pathological change in the tissues surrounding the apex of a tooth root, defined by its anatomical location rather than a distinct disease entity. Periapical lesions may be of endodontic origin, most commonly resulting from microbial infection of the root canal system following pulp necrosis due to caries, trauma, or other insults, or of non-endodontic origin, such as developmental cysts, benign and malignant odontogenic and non-odontogenic tumors, and fibro-osseous lesions. Accurate diagnosis requires a systematic approach combining patient history, clinical examination, pulp vitality testing, and radiographic assessment; histopathological evaluation is indicated when clinical and radiographic findings are inconsistent or suspicious. The pathophysiology of these lesions involves dynamic interactions between root canal microorganisms and the host immune-inflammatory response. The primary management for endodontic periapical lesions is root canal treatment, which aims to reduce or eliminate root canal microorganisms through mechanical debridement and chemical disinfection. Persistent or extensive endodontic lesions and non-endodontic lesions may require surgical intervention. Molecular and inflammatory biomarkers have been investigated as adjunctive tools for assessing disease activity and prognosis; however, these remain largely investigational and are not yet part of routine clinical practice. Future developments in artificial intelligence, advanced imaging, molecular diagnostics, and personalized therapies may enhance the diagnosis and management of periapical lesions, although further clinical validation is required.

Encyclopedia doi: 10.3390/encyclopedia6060124

Authors: Dris Soulaimani

Script reforms are socially motivated actions undertaken by institutions or communities that intentionally select, modify, or standardize writing systems. Although scripts are often analyzed as technical ways of writing, designed to enhance literacy and facilitate communication, this is not how script users typically perceive them. Beyond their linguistic function, scripts acquire deep social significance through their critically intertwined relations with issues of identity, political ideologies, and linguistic differentiation. This study analyzes such ideological underpinnings within script use and discusses the social ramifications of language codification. The study draws on different orthographic debates from Africa, Asia, and beyond, to demonstrate the social nature of script. The outcome of this study has implications for communities confronting orthographic decisions and competing script choices.

Encyclopedia doi: 10.3390/encyclopedia6060123

Authors: André Rui Graça

Entrepreneurship education in film and the creative industries refers to a set of pedagogical approaches, curricula, and institutional frameworks designed to foster entrepreneurial mindsets, competencies, and practices among students and professionals operating within the cultural and creative industries (CCIs). Going well beyond conventional business training, entrepreneurship education in this context encourages learners to identify opportunities for value creation—cultural, social, and economic—to develop sustainable modes of creative practice, and to engage critically with the markets, institutions, and communities that constitute the contemporary creative economy. Within film studies and adjacent disciplines such as media production, design, music, and the visual arts, entrepreneurship education plays an increasingly prominent role in preparing graduates for careers characterised by self-employment, project-based work, portfolio careers, and the continuous negotiation of artistic autonomy with the imperatives of professional sustainability. This entry aims to compile and organise existing knowledge on entrepreneurship education as it applies to the CCIs, with particular attention to the film and audiovisual sector, drawing on academic literature, European policy frameworks, and empirical industry evidence. The entry uses a narrative literature review approach, synthesising scholarly works from the fields of education, cultural economics, and creative industry research alongside institutional documentation and policy instruments, in order to provide a systematic and accessible account of the current state of knowledge in this area.

Encyclopedia doi: 10.3390/encyclopedia6060122

Authors: Melita Stavrou

The present entry focuses on definiteness agreement patterns in Modern Greek by exploring the function of the definite article in structures that involve a head noun and a modifier—typically an adjective, but not only—that is also accompanied by the definite article. Such structures have been variously dubbed polydefinite noun phrases/Determiner Phrases (or, simply, polydefinites), appositions, (pseudo)partitives, and evaluative appositives in the numerous studies that have been put forward to account for them over the past four decades or so. The peculiarity of these structures is the very presence of the second definite article that shows up whenever the modified noun itself is definite; at first sight, this ‘second’ article seems redundant, or expletive. Polydefiniteness has earned a privileged position in the literature, as has been discussed extensively and in depth over the past thirty years or so. The aim of this entry is to provide i. a description of the patterns that involve a noun and a modifier accompanied by its own definite article, and ii. a comprehensive survey of the relevant literature by highlighting commonalities and differences across the basic studies that have been written about polydefiniteness.

Encyclopedia doi: 10.3390/encyclopedia6060121

Authors: John Jairo Salazar-Buitrago Jaider Albeiro Figueroa-Flórez Cristian David Correa-Álvarez

Systemic educational change in Colombia refers to coordinated transformation across policy, teaching, curriculum, assessment, school leadership, teacher professionalization, data use, and community participation, oriented toward improving learning quality, equity, citizenship, and transitions to further study and work. This entry treats systemic change as a continuous, context-sensitive process rather than as a single reform event. Its success depends on the alignment of national direction, territorial implementation, institutional capacity, teacher agency, family and community engagement, and reliable feedback on whether students are developing the knowledge, skills, dispositions, and opportunities needed for social and labor participation.

Encyclopedia doi: 10.3390/encyclopedia6060120

Authors: Albrecht Classen

From the early Middle Ages, but mostly the late twelfth century, the love story involving Tristan and Isolde (also Yseut) attracted much attention, originating in the Celtic world but fully developed first by the Old French poet Béroul (ca. 1160) and Thomas of England, of Britain, or of Brittanny, around 1170. It was rendered into virtually every European language since then and has also appealed to artists and musicians throughout time. We know, for example, of tiles, tapestry, sculptures, paintings, musical tunes, manuscript illuminations, and other visual representations of the intense but highly problematic relationship between these two young people. In essence, while Yseult is married to the King of Cornwall, Mark/Marke, a love potion, a metaphorical symbol of their deep feelings, bonds her with Tristan for the rest of their lives (a limited number of years in the earlier versions). Ultimately, at least in most versions, they are destined to die because of their love, which is incompatible with the social norms of their time, and this Romantic theme has hence also played a huge role in the nineteenth and twentieth centuries, and is perhaps highly important also today, as expressed by modern movies and music engaging with this love story. This study first traces in rough brushstrokes the history of the reception of this literary theme from the twelfth to the twenty-first century; then, it returns to the various medieval versions to investigate the critical issues contained in this highly popular story, which has never lost its relevance and attraction for audiences throughout time. Since the focus rests on the history of reception, less on comparative literature, the main tradition to be traced will be the German one.

Encyclopedia doi: 10.3390/encyclopedia6060119

Authors: Erika María López-López Osnamir Elias Bru-Cordero Cristian David Correa-Álvarez

Generative artificial intelligence in higher education refers here to the use of computational systems that produce text, code, explanations, feedback-like responses, images, and other outputs from user prompts in university learning, coursework, assessment, and student study practices. This entry focuses on how students use generative AI while studying, preparing assignments, seeking explanations, revising work, programming, brainstorming, or responding to assessment tasks. It defines such use as a situated educational practice shaped by disciplinary expectations, assessment design, AI literacy, study habits, and academic integrity norms. From this perspective, the same AI-supported action may be acceptable as learning support in one course, ambiguous in another, and inappropriate when it conceals authorship, fabricates evidence, or substitutes for independent academic performance.

Encyclopedia doi: 10.3390/encyclopedia6060118

Authors: Juan Manuel Garcia-Manso Alejandro Leiva-Arcas Antonio Sánchez-Pato Juan Alfonso Garcia-Roca

Addition of an Author [...]

Encyclopedia doi: 10.3390/encyclopedia6060117

Authors: Yang Liu Sayam Chuangprakhon Warakorn Seeyo Akapong Phulaiyaw Arthit Khamhongsa

Zhao’s Guzheng: Traditional Chinese Performance Techniques refers to a comprehensive pedagogical and performance framework within the Shandong–Northeast lineage of the Guzheng (Chinese plucked zither). This system is historically rooted in a 200-year family tradition that underwent a pivotal transition in 1953, when it migrated from Shandong Province to the Shenyang Conservatory of Music in Northeast China. It is formally defined by three primary evolutionary pillars: the physical transition from 16-string silk-string folk instruments to standardized 21-string S-shaped academic models; a rigorous right-hand symbolic codification system that serves as a technical grammar for practitioners; and its status as recognized Intangible Cultural Heritage. The tradition represents a sophisticated synthesis of regional folk esthetics, noted for its robust, vigorous acoustic identity and structured conservatory training. By bridging the gap between oral folk apprenticeships and formal institutional pedagogy, the Zhao lineage maintains its specific stylistic authenticity, known as Yun Wei (musical flavor), ensuring that the technical soul of the school remains reproducible within the modern global musical landscape.

Encyclopedia doi: 10.3390/encyclopedia6060116

Authors: Vassilios Makrakis

This entry focuses on an Aristotelian approach to contemporary discourses about the implications of Artificial Intelligence (AI) regarding what it teaches and learns, with special regard to virtue or arete, practical wisdom or phronesis, and human flourishing or eudaimonia. Even though AI technologies provide new options for personalized learning, adaptive assessment, and data-driven instruction, their increasing entrenchment in the education ecosystem raises fundamental philosophical questions about the essence of teaching and learning, and about how we become better people. Aristotle’s distinction between intellectual and moral virtues can help us determine whether AI meaningfully contributes to the cultivation of good judgment, ethical character, and responsible agency. While AI is not completely antithetical to virtue formation, its knowledge and skill acquisition cannot replace the social, experiential, and habituated processes through which virtues are grown. AI should be designed and deployed as a “technological partner” to support (not replace) the teacher’s moral and pedagogical role. Guided by Aristotle’s view of eudaimonia and the common good, this analysis suggests that education should be structured to promote human flourishing in the age of AI, ensuring that learners develop their capacities for ethical reasoning, autonomy, and co-responsible participation to build a more sustainable and just society.

Encyclopedia doi: 10.3390/encyclopedia6060115

Authors: Seung B. Lee Danielle P. Espino

Research communities refer to the learning and social environments within which members engage in scholarly activities. Consisting of diverse actors involved in research processes, research communities provide opportunities for doctoral students to become familiar with the shared norms, values and cultures that are particular to each group. Research communities not only allow members to access pertinent knowledge, information and resources, but also offer social support and foster a sense of belonging in academia, helping students to develop into independent scholars. During their studies, doctoral students often participate in various research communities, ranging from the research lab at their institution to international networks connecting researchers from different countries. This paper focuses on ways to guide doctoral students into research communities, both within and outside of their institutions. In addition, it examines the formal and informal processes that facilitate their integration into these communities.

Encyclopedia doi: 10.3390/encyclopedia6060114

Authors: Antonio Cicchella Zhenyu Li

There is a lack of clarity on the isokinetic testing of professional female soccer players (PFSPs) concerning the proper use of isokinetic testing, and the existing data, useful for rehabilitation purposes, are confusing. This review aims to highlight the main methodological issues and provide guidance for performing reliable isokinetic strength (IS) based on evidence data. Following the PRISMA guidelines, we selected 18 out of 98 papers dealing with healthy PFSPs surveying four databases. It emerged that there is a large difference between subjects even in comparable test conditions (e.g., usage of the same isokinetic device). The more reliable testing speed ranges from 60°/s to 180°/s. Employing lower or higher velocities does not add information to test results. Interlimb differences in healthy PFSP are confirmed to be approximately 10 percent. The H/Q ratio does not differ through the different calculation methods, considering eccentric values or not, in any considered menstrual cycle phase. It emerged that more methodological rigor is necessary in PFSP isokinetic testing.

Encyclopedia doi: 10.3390/encyclopedia6050113

Authors: Chuanjie He Sharizal Bin Hashim

This study explores how internal and external brand management synergistically construct employee brand equity in contemporary organizations. Drawing on social identity theory, brand equity theory, and relationship quality theory, we conducted a systematic literature review of research published from 2019 to 2024 to analyze the cognitive, emotional, and behavioral mechanisms underlying this process. Our findings reveal that internal brand management activities (brand-oriented HR practices, brand communication) and external initiatives (CSR, marketing strategies) jointly shape employees’ brand cognition, while brand relationship quality mediates emotional connections through brand commitment, trust, and advocacy. These elements ultimately manifest in behavioral expressions including brand citizenship behavior, loyalty, retention intention, and positive word-of-mouth. This research provides organizations with an integrated framework for strategically aligning internal and external brand activities to enhance employee brand support, thereby strengthening competitive advantage through consistent brand delivery across all stakeholder touchpoints.