Search Results (573)

Artificial intelligence is being adopted across African public administration; health; education and finance; and the systems concerned act on a recorded or inferred gender value before they deliver anything at all. The problem this article addresses is that the categories operating in digital identity registers; automated facial analysis; biometric enrolment for social grants and language technologies are binary; anatomically grounded and administratively fixed; and that this specification reached the continent as a colonial import rather than as a description of how gendered standing is actually held. The article traces the descent of that binary; recovers from one southern African site a documented account of how gendered personhood is conferred and revised; and converts that account into design requirements. The design is conceptual and genealogical, reading three corpora against one another: the ethnographic record of the Balobedu of Bolobedu in Limpopo, South Africa; principally the Krige corpus and later commentary upon it; the technical and audit literature on gender classification; and South African identification law. Yoruba and Igbo scholarship is retained for comparison. Standing at the site is shown to be conferred through office; seniority; cattle and marriage rather than read from the body; so that a woman may hold the position of husband and a queenship may pass through a line of women. Systems in current use represent none of the properties by which such standing is held; and the article specifies thirteen changes to datasets; taxonomies; interfaces and procurement through which they could do so. Full article

Software-intensive organizations increasingly face the challenge of integrating ethical considerations into routine work practices while maintaining process quality and organizational performance. This study develops the Quality Value Driver (QVD) framework, a managerial approach for embedding ethical reflection into everyday organizational processes. The framework links ethical values, organizational drivers, and observable quality indicators, providing a structured mechanism through which ethical values can be operationalized and evaluated. Following constructive research methodology, the study introduces the framework and illustrates its application through a proof-of-concept case involving an Agile team developing an AI-based facial palsy classification system. In the demonstrated application, collaboration was selected as the target value, Balint Groups served as the organizational driver, and process-quality indicators were used to assess development outcomes. The findings do not establish causal effectiveness but illustrate the feasibility of operationalizing ethical values through routine organizational practices within the specific context examined. The study contributes a software-engineering perspective that conceptualizes ethical values as potential process-quality drivers and advances the Ethics by Design approach by integrating ethical reflection into everyday software-development decision-making. Full article

This critical assessment develops a mechanistic framework for plasma-engineered oxynitride thin films in photoelectrochemical (PEC) water splitting, moving beyond description to predictive understanding. Analyzing 30 peer-reviewed studies (2010–2025) via PRISMA 2020 and a structured reliability framework, we evaluate relationships between plasma conditions, film characteristics, and solar hydrogen generation. Results reveal that plasma power, gas composition, and substrate temperature collectively control nitrogen incorporation, crystallinity, and defect formation. Optimized plasma processing conditions were generally associated with improved photocurrent generation, hydrogen evolution performance, and operational stability relative to thermal synthesis routes across most of the reviewed studies, although the 30-study evidence base is still limited and the proposed power-domain classification should be treated as a preliminary framework requiring validation against additional studies. Mechanistic analysis indicates that moderate plasma energies provide sufficient activation for nitrogen incorporation while minimizing lattice damage and excessive defect formation. A unified conceptual framework is proposed relating plasma parameters, film properties, and PEC performance, providing mechanistic guidance for photoelectrode optimization and future process development. Quality assessment identifies that only 13.3% of studies provide high-confidence evidence (46.7% moderate, 40% low), with most lacking complete plasma diagnostics or long-term stability data, highlighting critical research gaps. The framework establishes that plasma engineering’s transformative potential lies in precise control over the composition–structure–property cascade, offering a reproducible route to high-performance oxynitride photoelectrodes for sustainable hydrogen production. Full article

The maternal–fetal interface functions as an integrated physiological unit whose homeostatic balance determines pregnancy success. Large-pore channels, composed of connexins (Cxs), pannexins (Panxs), calcium homeostasis modulators (CALHMs) and leucine-rich repeat-containing 8 (LRRC8) proteins, mediate direct intercellular communication, autocrine and paracrine release of ATP and other signaling molecules, and scaffold-based signal integration across this interface. In this review, we synthesize current knowledge on large-pore channel expression and their physiological and pathophysiological roles at the maternal–fetal interface, applying an explicit evidence-classification framework to distinguish established functions from emerging findings. We first map the large-pore channel repertoire of each cellular compartment—syncytiotrophoblast, cytotrophoblast, extravillous trophoblast, villous endothelium and decidual stroma—revealing that each compartment expresses a distinct combination of family members, with varying levels of evidence and gestational stage-dependent dynamics. We then analyze the three principal modes of large-pore channel operation in placental physiology: gap-junctional communication driving syncytialization, channel-mediated ATP release enabling paracrine purinergic signaling, and channel-independent scaffolding functions that integrate mechanical and biochemical signals. Next, we examine how each channel family becomes dysregulated in placental-related diseases. We conclude by outlining a targeted research roadmap with clear priorities: the most urgent need is protein-level validation of CALHM and LRRC8 expression in primary trophoblasts, followed by elucidation of gating mechanisms and testing for crosstalk among channel families. By providing both conceptual synthesis and practical guidance, this review aims to accelerate mechanistic understanding and therapeutic development targeting large-pore channels for pregnancy complications that currently lack mechanism-based treatments. Full article

Forensic age determination in presumed minors is affected by a structural tension between biological uncertainty, juridical thresholds, and the ethical duty to protect childhood. Conventional dental age estimation methods provide point estimates of chronological age but do not directly address the question central to legal proceedings: whether adult status can be affirmed with certainty. This short communication introduces MIDAS (Maturity Index for Determination of Adult Status), a certainty-based, hybrid human–AI framework for adult age determination. Two forensic odontologists independently assessed mandibular third-molar development (Radicular Completion Ratio, R₈; Apical Closure Index, A₈) in 180 anonymized orthopantomographs of individuals aged 14–25 years, complemented by an AI-assisted radiomorphometric module extracting root density relative to enamel (D₇) and trabecular texture homogeneity (T_m). These parameters were integrated into a continuous Integrated Dental Maturity Index (IMD). By raising the biological reference age to 20 years and excluding the 17–20-year interval from affirmative adult classification, the framework operationalizes the precautionary principle, interpreting residual uncertainty in favor of childhood protection. As a proof of concept, this study establishes the conceptual and operational architecture of MIDAS rather than its diagnostic accuracy. Formal validation on larger and more diverse populations is required before routine forensic and medico-legal application. Should such validation confirm its performance, MIDAS could offer an ethically grounded, legally coherent, and scientifically transparent complement to conventional methods of dental age estimation and adulthood determination. Full article

As financial institutions become increasingly reliant on similar foundational AI models, cloud infrastructure, data providers, and AI middleware platforms, diverse firms may begin to interpret and respond to market signals in increasingly similar ways. This paper examines model monoculture risk as a potential source of system-level exposure in banking and financial markets. Drawing on a structured, purposive conceptual review of the academic and regulatory literature, it develops the M³ Framework—Model, Market, and Middleware—to integrate three interacting mechanisms: Model Similarity, Market Synchronisation, and Middleware Concentration. Rather than treating these as a fixed causal sequence, the framework identifies their independent and cross-layer effects and distinguishes AI-mediated synchronisation from correlation arising from common exposures, conventional herding, and shared macroeconomic shocks. The paper further proposes the Model Monoculture Risk Index (MMRI) as a prototype index architecture and conceptual supervisory screening framework for characterising configurations of AI-related convergence, rather than as a calibrated quantitative measure of realised systemic risk. An illustrative application demonstrates how exposure classifications vary across alternative M³ configurations and attribution assumptions. The paper argues that governance should prioritise cross-institutional monitoring, dependency mapping, meaningful substitutability, and targeted stress testing rather than diversification by default. The framework provides a structured basis for future empirical research on AI-driven convergence and financial stability. Full article

Circular economy implementation is feasible through digital tracking of raw materials. The aim of this article is to analyze the possibilities for deploying blockchain or Ethereum as Distributed Ledger Technology (DLT) platforms. Various decision-selection algorithms were examined for choosing a suitable platform and network type (public, private). The article analyses the drawbacks and barriers to achieving a circular economy in accordance with sustainable development criteria. Based on the regulatory framework and operational projects, it is shown that digital technologies improve the efficiency of raw material processing and life cycle tracking. To build an effective network, a separator is proposed as a separate participant in addition to producers, processors, and consumers. Their functions are waste classification and sorting, and receiving and transmitting heterogeneous data streams while preserving the privacy of sensitive ones. Drawing on the specifics of circular economy implementation, selection criteria are proposed, including deployment cost, data immutability, energy consumption, need for new technology, and others. A superior decision support tree tailored to material recycling is proposed. Its advantage is fast decision-making and selection of an appropriate platform within the DLT landscape. The proposed conceptual framework is not a universal solution as it can be adapted to different recycling schemes, especially when the regulatory framework, technologies, materials, flows, scheme participants, stakeholders, or other factors change. Full article

Integrated management systems (IMSs) are currently experiencing a radical revolution triggered by digital technologies, sustainability issues, and human-centric management philosophies of Industry X.0. Even though there have been many advances in research about IMSs, our understanding of the evolution process and digital revolution of IMSs is still far from being comprehensive. In this research, a combination of bibliometric analysis and qualitative content analysis is used to explore the evolution of IMSs published in the scientific literature from 2015 to 2026. A set of 103 peer-reviewed publications, obtained through searches in the Scopus, Web of Science, and ScienceDirect databases, was analyzed following the PRISMA 2020 guidelines; of these, 59 full-text papers were selected for qualitative analyses. This bibliometric study discloses the ongoing advancement of IMSs, with major characteristics highlighting the increasing relevance of digital transformation, sustainability, artificial intelligence, and human-oriented management. According to the results of the bibliometric analysis, two theoretical contributions are made in this paper. First, a Digital Enabler Classification (DEC) taxonomy is proposed to classify IMS configurations according to their dominant digital enablers and associated management characteristics, comprising six analytical categories (DEC-0 to DEC-5). Second, a conceptual framework is proposed to provide a possible evolutionary interpretation of IMS transformation from standards-driven integration toward connected, intelligent, sustainable, and human-centric governance systems. The DEC taxonomy and its quantitative distribution across the six classes are derived directly from criterion-based coding of the 59 full-text articles; the evolutionary reading of the framework is a conceptual interpretation of this cross-sectional evidence rather than a longitudinally validated developmental sequence. Together, the contributions presented offer a structured view of the digital transformation process of IMSs and provide a foundation of theory and practice for the development of further research. Full article

Processing tubers such as potato, sweet potato, cassava, and yam, as well as legumes such as soybean, pea, chickpea, bean, and lentil, generates substantial quantities of peels, pulps, husks, and press cakes that retain considerable nutritional and functional value despite often being discarded. Microbial fermentation has emerged as a low-cost and scalable approach for valorising these residues into functional ingredients with improved digestibility and enhanced bioactive-compound content. This study synthesises the composition of major tuber and legume by-products, the solid-state and submerged fermentation systems employed for their bioconversion, and the biochemical and functional transformations achieved through fermentation, including improvements in antioxidant activity, prebiotic potential, antihyperglycaemic properties, and protein quality. The emerging applications of these fermented by-products in bakery products, dairy alternatives, snacks, nutraceuticals, and the conceptually related field of gut-microbiome-guided precision nutrition are also examined. Persistent challenges, including compositional variability, safety monitoring, and regulatory classification, are critically evaluated alongside strategies for addressing these limitations. Overall, fermentation-based valorisation of tuber and legume residues represents a scientifically credible and environmentally sustainable strategy for transforming agri-food waste streams into value-added, functional nutrition ingredients. Full article

Scapholunate (SL) instability is the most common form of carpal instability, and if untreated, it may progress through dorsal intercalated segment instability to scapholunate advanced collapse. Contemporary understanding emphasizes a dual stabilizing system in which the SL interosseous ligament (SLIL) acts as the intrinsic primary restraint, reinforced by extrinsic “critical” secondary stabilizers; isolated SLIL division does not by itself produce static malalignment until these secondary restraints are also compromised. Against this background, wrist arthroscopy has become a widely used reference standard for diagnosis and grading, allowing for graded assessment through the Geissler and the more granular European Wrist Arthroscopy Society (EWAS) classifications, while dry arthroscopy has reduced fluid-related morbidity and facilitated combined arthroscopic and mini-open procedures. Treatment has correspondingly shifted from open reconstruction toward arthroscopic and arthroscopic-assisted repair, capsulodesis, and ligamentoplasty, which are intended to preserve native capsuloligamentous structures and may offer potential advantages in limiting capsular disruption and postoperative stiffness. This narrative review synthesizes the literature identified through a selective search of PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar (final search 13 June 2026). The evidence consists mainly of small observational series and technique reports. The review stages the injury by arthroscopic grade (EWAS/Geissler) and organizing techniques by the target ligament(s), from partial and dynamic injuries through complete, reducible, and advanced deformities. We align each technique with the corresponding pattern of intrinsic and extrinsic ligament injury to clarify indications, summarize reported outcomes, and propose a stage-based conceptual treatment framework rather than a validated, evidence-based guideline. Current evidence derives largely from small, heterogeneous case series with variable classifications and outcome measures, underscoring the need for standardized staging and comparative studies. Full article

Background: This narrative concept-generating review proposes a theoretical and heuristic framework for conceptualizing established and emerging interventions for posttraumatic stress disorder (PTSD) including three categories: top-down/conscious (e.g., cognitive processing therapy, CPT), bottom-up/non-conscious (e.g., pharmacotherapy) and hybrid/conscious and non-conscious integration (e.g., eye movement desensitization and reprocessing, EMDR). The categorization offers a preliminary novel classification of well established and emerging interventions, while highlighting gaps in current treatment approaches. Methods: Clinical guidelines and review articles from 2008 through 2026 were used to create the framework; PubMed and Google Scholar databases were searched for relevant meta-analyses, systematic reviews, narrative reviews, and randomized clinical trials. A total of 27 treatment modalities were included presenting effect size data from 43 published articles. Results: Treatments across categories present mixed results for efficacy. While guideline recommended treatments offer more robust evidence, many understudied emerging interventions exhibit preliminary efficacy. At the intersection of conscious and non-conscious approaches, hybrid modalities may present unique potential benefits. However, superiority determinations between modalities cannot be made and further empirical validation of categorization is needed. Conclusions: The proposed framework highlights the need for increased investigation of treatments that address PTSD as an interconnected whole-body disorder to potentially expand care options. Full article

Commercialisation of research outcomes depends not only on technological quality but also on the competences through which research organisations identify market opportunities, coordinate stakeholders and translate knowledge into sustainable value. This study identifies and classifies commercialisation competences in research network organisations and develops a time-structured framework for operationalising their contribution to sustainability-oriented innovation (SOI). A structured review of Scopus and Web of Science publications, using predefined relevance criteria, yielded 129 competence formulations. Competence extraction was conducted by one author, while two authors independently synthesised the formulations into 25 conceptually distinct competences: five cognitive, eight functional, four personal and eight meta-competences. The 25 competences were then mapped against the triple bottom line, dynamic capabilities and ESG perspectives through a consensus-based expert assessment. Ten competences were classified as core sustainability-oriented, twelve as enabling and three as neutral. Because this classification is interpretative rather than empirically validated, it is intended as a transparent analytical proposition for subsequent testing. Each competence was linked to an Activity–Process Performance–Outcome (A–S–W) structure based on leading, diagnostic and lagging indicators, producing 75 illustrative indicators. The proposed numerical thresholds are heuristic calibration examples rather than universal benchmarks. The framework connects competence activation with process quality and commercialisation outcomes while incorporating economic, environmental and social dimensions and provides a basis for competence development, performance monitoring and future empirical validation. Full article

The city of Skopje faces persistent inefficiencies in waste management, characterised by rising waste generation and limited progress in sustainable treatment solutions. This paper addresses the need for a structured approach to identify barriers to implementing Waste-to-Energy (WtE) technology, focusing on incineration-based energy recovery as a potential option for improving waste management while generating energy. Interpretive Structural Modelling (ISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) were applied to six categories of implementation challenges: operational, technical, financial, regulatory, social, and environmental. ISM identified hierarchical relationships within each category, while MICMAC classified challenges according to their driving and dependence powers. The results revealed distinct structural patterns across categories, with underlying barriers including inadequate waste separation and collection, lack of integrated waste information, competitive renewable energy prices, regulatory preferences for waste reuse, recycling and reduction over WtE, institutional distrust, and combustion residue management. The findings reveal interconnected barriers with distinct structural roles, while conceptual mitigation measures and relevant SDG linkages are proposed based on the identified barriers and literature. The proposed ISM-MICMAC framework provides a structured approach for analysing WtE implementation barriers and can be adapted to other contexts following appropriate contextual and quantitative assessment. Full article

Introduction: COPD-OSA overlap syndrome (OVS) is defined by the coexistence of chronic obstructive pulmonary disease and obstructive sleep apnea syndrome in the same patient; it affects 28.3% of patients evaluated for either condition and is associated with significantly higher mortality compared to either pathology in isolation. Current therapeutic approaches, involving PAP therapy and bronchodilation, treat this syndrome as a homogeneous entity and ignore the biological heterogeneity of this patient population. Objectives: This review proposes a systematic framework for the endotypic classification of biological interactions between COPD and OSA, integrating current literature on the pathophysiological mechanisms underlying the OVS, clinically accessible biomarkers, and emerging therapies. Methods: A narrative review based on available literature, focusing on studies published between 2010 and 2026 identified via searches in PubMed, PMC, and Dove Medical Press using the terms: COPD-OSA overlap syndrome, endotype, precision medicine, phenotype, biomarker, dupilumab, and incretin-based therapies. Results: Four clinical phenotypes (obese-metabolic, emphysematous, bronchitic-hypoxemic, and hypercapnic) and three molecular endotypes (Th2/eosinophilic, neutrophilic/oxidative, and metabolic-adipokine) are proposed, each with distinct pathophysiological mechanisms and specific therapeutic implications. The interaction between the two conditions generates a unique, pronounced hypoxemic profile. We propose the “double-hit hypoxemia” model as a conceptual framework characterized by amplified systemic inflammation and increased cardiovascular risk compared to either pathology in isolation. This proposed model has not yet been prospectively validated. Dupilumab (approved for an inflammatory phenotype in COPD patients characterized by eosinophil counts ≥ 300 cells/μL) represents a promising option, though currently unsupported in the OVS population, that could nonetheless be relevant to the Th2/eosinophilic endotype of this syndrome and tirzepatide (which reduced the AHI by up to 23.8 events/hour versus placebo in the SURMOUNT-OSA trial, conducted in patients with obesity and moderate-to-severe OSA, rather than in patients with confirmed OVS) could represent a promising therapy for the metabolic-adipokine endotype of obese patients with OVS. A minimal biomarker panel, comprising blood eosinophils, FeNO, daytime PaCO₂, BMI, and T90, allows for a practical approach to identifying the dominant endotype. Conclusions: Endotyping of OVS may provide a framework for moving beyond a uniform therapeutic approach toward more individualized management based on the dominant underlying biological mechanism. Randomized clinical trials focusing on endotypic stratification and OVS cohorts remain research priorities. Full article

Rock bolt reinforcement governs underground excavation stability through the combined effects of embedment depth, installation pattern, and interaction with the evolving stress and structural environment. Despite substantial advances across mechanistic, empirical, numerical, discontinuum, dynamic, and field-based research traditions, no unified framework currently integrates these approaches across geological and stress regimes. Current practice, therefore, relies on design methods calibrated within specific contexts, producing optimisation outcomes that are model-dependent, metric-sensitive, and not reliably transferable across site conditions. This review critically synthesises evidence from 30 peer-reviewed studies organised into six analytical categories: mechanistic confinement frameworks, empirical classification systems, numerical parametric investigations, discontinuum- and discrete fracture network (DFN)-based optimisation studies, high-stress and dynamic performance analyses, and field-based performance evaluations. The synthesis establishes three principal findings. First, optimal bolt embedment is stress-regime-dependent; plastic-radius-based design logic is appropriate under moderate static conditions but becomes insufficient under high stress or dynamic loading, where energy absorption capacity and controlled yielding govern performance. Second, in discontinuous rock masses, joint geometry and spacing dominate reinforcement effectiveness, shifting optimisation from uniform length selection toward pattern-specific alignment and multi-length configurations that outperform equal-length grids under DFN-controlled conditions. Third, numerical optimisation outcomes are sensitive to the choice of objective metric and modelling paradigm, such that bolt length and spacing recommendations cannot be transferred across analytical frameworks without explicit mechanism comparison. To integrate these findings, a unified conceptual framework is proposed based on regime classification using three dimensionless indicators: the bolt penetration ratio (Π₁ = L/r_p), which relates embedment to plastic zone radius; the structural interception ratio (Π₂ = S/S_j), which relates bolt spacing to dominant joint spacing; and the stress intensity ratio (Π₃ = σ_in situ/σ_cm), which relates in situ stress to rock mass compressive strength. These indicators identify whether confinement-dominated, structure-dominated, or stress-dominated behaviour governs stability, and direct design logic accordingly. The framework does not prescribe universal geometric thresholds; rather, it provides a structured classification pathway that integrates mechanistic and empirical evidence into a coherent and transferable design logic. Probabilistic validation incorporating geological variability, stochastic fracture network modelling, and iterative field calibration is identified as the necessary development path toward a statistically robust optimisation methodology. Full article