Search Results (5,416)

Artificial intelligence, digital payments and platform-based services are reshaping the operating conditions of Africa’s informal economy and micro-enterprise sector. While mobile money, digital marketplaces, app-mediated logistics and algorithmic scoring systems are commonly presented as instruments of financial inclusion and enterprise modernisation, their effects on informal traders remain uneven, conditional and under-governed. This systematic review synthesises recent peer-reviewed evidence on AI-mediated digitalisation pathways for informal and micro-enterprises in Africa, with particular attention to mobile money, platform payments, app-based logistics, digital credit, algorithmic management and platform governance. Following PRISMA-informed systematic review procedures, this review analyses 60 peer-reviewed, DOI-bearing articles published between April 2022 and June 2026 through a mechanism–outcome synthesis approach. The final corpus was selected through database searching, duplicate removal, title-and-abstract screening, full-text eligibility assessment, quality appraisal and mechanism–outcome coding. The findings show that digitalisation can expand market access, reduce cash-handling risks, create transaction histories, strengthen customer reach, improve operational continuity and support household resilience. However, the same digital infrastructures may also intensify livelihood vulnerability through opaque scoring, unexplained account freezes, fee shocks, exclusionary verification procedures, algorithmic ranking losses, data extraction and weak dispute-resolution mechanisms. The review therefore argues that informal enterprise digitalisation should not be understood only as a technology adoption issue, but as a socio-technical systems governance challenge. The article contributes a governance-and-risk framework linking local infrastructure, platform and payment design, AI (artificial intelligence) mediation, adoption conditions and livelihood outcomes. It further identifies minimum policy and design protections required for inclusive and resilient participation, including transparent fees, proportionate verification, human appeal channels, explainable restrictions, data-use consent, timely settlement and contingency mechanisms during digital outages or erroneous flags. The review concludes that sustainable digital inclusion for African informal micro-enterprises depends not merely on access to digital tools, but on the fairness, transparency, recoverability and accountability of the systems through which traders participate. Full article

Despite growing interest in artificial intelligence (AI) applications in the construction industry, the literature still lacks a consolidated understanding of how AI functions across the full spectrum of construction supply chain processes. Existing studies are dispersed across different technologies, project stages, and application contexts, making it difficult to identify the intellectual structure of this field, the main areas of AI application, and the barriers that continue to constrain practical implementation. To address this gap, this study conducts a systematic review of AI applications in construction supply chains by combining scientometric analysis with qualitative content synthesis. A total of 212 journal articles retrieved from Scopus were analyzed using VOSviewer-based scientometric analysis and qualitative content synthesis. The scientometric analysis maps annual publication trends, keyword co-occurrence patterns, co-cited sources, influential documents, and collaboration networks. The qualitative synthesis further examines how AI supports construction supply chain management across three broad themes: procurement and production optimization, logistics and material management, and collaborative decision-making for resilience and sustainability. The findings show that AI has been primarily applied to demand forecasting, resource optimization, logistics coordination, contract and document processing, computer vision-based monitoring, and multi-agent decision support. However, its practical diffusion remains constrained by fragmented and low-quality data, limited empirical validation, high implementation costs, algorithmic opacity, cybersecurity risks, and unresolved governance and liability issues. Based on these findings, this study proposes a data-centric and phased research agenda that emphasizes benchmark datasets, human–AI collaboration, lifecycle economic evaluation, explainable AI, and multi-stakeholder governance. The study contributes to the literature by integrating fragmented AI-related research into a structured knowledge map and by clarifying future pathways for developing intelligent, transparent, and resilient construction supply chains. Full article

Biochar has emerged as one of the most promising nature-based strategies for improving soil quality, enhancing crop productivity and supporting climate-smart agriculture. However, the agronomic performance of biochar remains highly variable because its effects are governed by complex interactions among feedstock characteristics, pyrolysis conditions, soil properties and management practices. This review synthesizes recent advances in biochar research (2019–2026), examining how production variables determine biochar physicochemical properties and how these properties subsequently influence soil functioning, plant performance and long-term agricultural sustainability. The review integrates evidence on feedstock selection, pyrolysis technologies, biochar modification strategies and the relationships between biochar properties and soil physical, chemical and biological processes. Particular attention is given to crop productivity, nutrient use efficiency, stress mitigation, contaminant immobilization, greenhouse gas mitigation and long-term soil resilience. Across the literature, the most consistent agronomic benefits were observed when biochar was applied to degraded or resource-limited soils and integrated with complementary management practices, whereas responses were often limited under fertile soils, low application rates or short experimental periods. Rather than identifying a universally superior biochar, the evidence indicates that agronomic performance depends on matching biochar characteristics to specific production objectives and environmental conditions. Based on these findings, this review proposes a transition from generalized biochar application towards optimized deployment strategies supported by standardized characterization, long-term multi-site validation and integrated environmental and economic assessments. This synthesis provides a comprehensive framework for guiding future research and facilitating the effective implementation of biochar within sustainable and regenerative agricultural systems. Full article

Background/Objectives: Contemporary secondary students increasingly learn in technology-rich classrooms characterized by digital stimulation, multitasking demands, compressed pacing, platform switching, and persistent attentional competition. Established scholarship on cognitive load, multimedia learning, self-regulated learning, disciplinary literacy, attentional control, and environmental restoration identifies mechanisms relevant to these conditions, but these mechanisms are often examined at different levels of analysis. This conceptual review develops the Cognitive Ecology of Learning Framework (CELF) as an applied, classroom-level framework for examining how disciplinary cognitive demand, attentional fragmentation conditions, and restoration opportunities may interact during sustained secondary science learning. Methods: An integrative conceptual-review and theory-synthesis design was used. Iterative searches conducted from January through May 2026 identified theoretical, empirical, and review literature across education, psychology, attentional science, digital learning, environmental psychology, and secondary science education. Sources were selected purposively according to their relevance to the research questions and synthesized through cross-domain comparison. Results: The synthesis proposes CELF as a hypothesis-generating framework organized around three classroom-level dimensions: Disciplinary Cognitive Demand, Attentional Fragmentation Conditions, and Restoration Opportunities. The framework also proposes cognitive malnourishment and cognitive endurance as context-sensitive constructs requiring empirical validation. Cognitive malnourishment describes a possible ecological mismatch in which substantial informational or disciplinary demand coincides with persistent fragmentation and insufficient opportunities for elaboration, reflection, consolidation, and coherent reengagement. Cognitive endurance refers to the context-sensitive capacity to sustain attention, conceptual processing, and disciplinary reasoning during extended, cognitively demanding work. Preliminary indicators, measurement approaches, and testable propositions are presented for future classroom-based research. Conclusions: CELF organizes selected task-level, learner-level, disciplinary, attentional, and environmental constructs within a bounded framework for technology-rich secondary science classrooms. It does not revise or replace the foundational theories from which these constructs are drawn, nor does it claim causal validation. Instead, CELF provides a structure for investigating how classroom conditions may support or constrain attentional continuity, conceptual persistence, restoration, and sustained disciplinary engagement. Full article

Background: Relative energy deficiency in sport (REDs) is a multi-system syndrome precipitated by sustained low energy availability (LEA) and known to perturb bone, muscle, adipose, endocrine, and fluid–electrolyte homeostasis in athletic populations. Research question: How does chronic exercise-induced LEA modify the four principal compartments of body composition—bone mineral density, skeletal muscle mass, adipose (total and visceral) tissue, and hydration status—and to what extent do these modifications differ across endurance, strength, and aesthetic sporting disciplines? Objective: The objective of this narrative review was to synthesise the post-2000 peer-reviewed literature addressing this question, to delineate sex- and sport-specific patterns of compositional change, and to appraise the evidence base underpinning current nutritional and screening recommendations. Methods: A structured search of PubMed, Web of Science, Scopus, and Google Scholar (January 2000–June 2026) was performed; 85 sources specific to REDs, body composition, and athletes met the pre-specified inclusion criteria and informed the synthesis (104 references are cited in total, including background and methodological sources), the reporting of which was guided by the SANRA framework. Scope: The review integrates physiological, endocrine, and nutritional evidence across both sexes, contrasts REDs risk across endurance, ultra-endurance, weight-category/aesthetic, speed–power, and team disciplines and addresses practical implications for screening, interdisciplinary care, and future research. Full article

Precision agriculture (PA) has emerged as a transformative approach for improving agricultural productivity, resource-use efficiency, and environmental sustainability through the integration of digital technologies, including Global Positioning Systems (GPSs), Geographic Information Systems (GISs), remote sensing, the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), and autonomous systems. Although previous reviews have primarily emphasized technological innovation, adoption trends, or environmental outcomes, they have provided limited synthesis of the economic mechanisms linking technology adoption, resource allocation, production efficiency, investment performance, and long-term sustainability. A structured narrative–systematic review was conducted using peer-reviewed research retrieved from Scopus, Web of Science, and Google Scholar, covering studies published between 2004 and 2026. An integrated analytical framework combining technology adoption theory, resource economics, and production-efficiency models was employed to explain how digital technologies generate economic value while identifying methodological limitations, geographical bias, unresolved research questions, and future research priorities. The review demonstrates that GPS-guided machinery, variable-rate technologies, smart irrigation systems, AI-driven decision-support tools, and integrated digital platforms improve water- and nutrient-use efficiency, labor productivity, production efficiency, and farm profitability. However, economic performance remains highly context-dependent, varying according to farm size, crop type, climatic conditions, institutional support, digital infrastructure, resource scarcity, and policy environments. Methodological inconsistencies in return on investment (ROI), net present value (NPV), lifecycle costing, ecosystem-service valuation, and environmental externality assessment reduce comparability among studies and complicate evidence-based policymaking. The review further identifies a pronounced geographical concentration of evidence in North America, Europe, and Australia, with comparatively limited understanding of PA economics in China, India, Brazil, Sub-Saharan Africa, and Southeast Asia. Persistent challenges include high capital costs, unequal access among smallholder farmers, data governance concerns, interoperability limitations, uncertainty in long-term investment performance, and limited integration of agricultural insurance, climate-risk management, and digital finance. By integrating economic theory, methodological comparison, geographical analysis, sustainability valuation, and policy perspectives within a unified conceptual framework, this review highlights the need for standardized economic evaluation methodologies, broader geographical representation, and interdisciplinary research to support evidence-based policy and the sustainable digital transformation of global agriculture. Full article

Hydrogen (H₂) has emerged as a promising sustainable energy vector due to its scalability, high energy density, and its ability to enable sector coupling across electricity, heating, transportation, and industry. There remains a huge technical challenge to overcome. The economic implications of low round-trip efficiency, high capital costs, the limited lifespan of fuel cells and electrolyzers, and infrastructure constraints on H₂’s relative competitiveness have not been comprehensively studied. In a comparative assessment against other storage options such as batteries, pumped hydro, and compressed air energy storage (CAES), we highlight the potential of H₂ as a grid-scale storage solution. The novelty of this paper is that it compares H₂ as a competing option with other storage technologies and highlights its unique suitability for seasonal and grid-scale applications where others fall short. The paper also discusses the technological opportunities for AI and other digital technologies in the H₂ grid. Unlike general reviews, this work emphasizes the engineering performance of H₂’s production cost and economic viability, electrolyzer technology maturity, infrastructure readiness, safety and lifecycle considerations, and provides critical synthesis and implications. With this, the paper extends beyond the theoretical capacity for H₂ and gives an engineering-focused analysis that informs the drive toward sustainable and resilient power grids. Full article

Biochar has attracted increasing attention for aquatic pollution control, particularly due to its capacity to accelerate the rate-limiting steps of denitrification in wastewater treatment. While early research primarily focused on the adsorption capacity of biochar, recent studies have increasingly investigated its role as a redox-active mediator that facilitates electron transfer. This review critically synthesizes the multifaceted mechanisms of biochar-enhanced denitrification, establishing a link between synthesis parameters (feedstock, pyrolysis kinetics) and physicochemical functionalities (pore architecture, redox-active functional groups). Specifically, we elucidate how precise regulation of pyrolysis temperature dictates the dominant electron transfer pathway: low-temperature biochar (<500 °C) facilitates electron shuttling via oxygen-containing functional groups (e.g., quinone moieties), whereas high-temperature biochar (>700 °C) promotes direct interspecies electron transfer (DIET) through graphitic conduction. We systematically decouple biochar-mediated electron transfer into three pathways: functional group-driven shuttling, solid-state conductive matrix transfer via conjugated π-electrons, and material-assisted DIET. Crucially, we emphasize that validating true DIET requires direct biological evidence of electroactive machinery. Furthermore, the review details how biochar modulates the biological microenvironment, upregulating key denitrification genes (narG, nirS/K, nosZ) and enriching functional microbial consortia. By integrating advances in surface modification—such as heteroatom doping and metal loading—we propose strategies to engineer biochar for optimized nitrate-to-nitrogen conversion. Future perspectives underscore the need for balancing electron-donating capacity with structural stability, developing low-energy functionalization techniques, and conducting life-cycle assessments to facilitate the scale-up of sustainable, high-efficiency nitrogen removal systems. Full article

The accelerating digital transformation of urban economies is reshaping labor markets at unprecedented speed, generating skills mismatches, employment volatility, and widening inclusion gaps that current smart city governance frameworks are insufficiently equipped to address. While the smart city literature has advanced substantially in the areas of digital infrastructure, mobility, and e-government services, the governance of labor market transitions in data-driven urban environments remains conceptually underdeveloped. In particular, no integrated analytical framework currently links smart city governance, labor market intelligence, and workforce resilience into a coherent tool for assessing urban preparedness for technology-driven employment change. This study addresses that gap by developing the Urban Workforce Readiness Framework (UWRF)—an integrated conceptual model designed to evaluate how prepared urban labor markets are for accelerating digital and technological transformation. Methodologically, the framework is constructed through a structured synthesis of peer-reviewed scholarship published between 2015 and 2025 across five domains—smart city governance, labor market regulation, human capital development, workforce resilience, and data-driven public administration—complemented by a thematic review of policy documents issued by the OECD, ILO, European Commission, and World Bank. On this basis, the UWRF identifies five interdependent dimensions of urban workforce readiness: (i) digital infrastructure capacity, (ii) labor market intelligence and analytics, (iii) workforce skills adaptability, (iv) institutional governance capacity, and (v) social inclusion mechanisms. A multi-criteria operationalization is proposed, enabling comparative diagnostic assessment across cities and supporting evidence-based prioritization of policy interventions. The analysis demonstrates that institutional governance capacity and real-time labor market intelligence function as critical mediators within the system: in their absence, even substantial investments in digital infrastructure fail to produce resilient, inclusive, or sustainable labor market outcomes. Theoretically, the study extends data-driven governance scholarship beyond service delivery into the domain of workforce management, thereby integrating three traditionally separate research streams—smart city studies, labor market governance, and digital public administration—under a single analytical architecture. Practically, the UWRF provides policymakers, municipal authorities, labor market institutions, and urban planners with a structured diagnostic instrument for aligning digital transformation strategies with sustainable and equitable employment outcomes, and offers a replicable foundation for future empirical validation across diverse urban contexts. Full article

Sustaining learner motivation remains a persistent challenge in higher education Japanese-language e-learning, where learners often study with limited social presence and personalized encouragement. This paper proposes a preliminary Design Framework for Motivational Robots in E-Learning (DFMRE), derived through a retrospective, theory-guided synthesis of two previously published empirical studies on robot-assisted Japanese-language learning. The synthesis interprets the prior findings through Self-Determination Theory and self-efficacy theory and formulates five candidate design principles: human-affine compact hardware, multi-level learner-selectable gestures, calibrated vocal encouragement, learner-initiated interaction protocol, and content-independent system integration. To provide an initial external check, nine domain experts with diverse backgrounds in education, educational technology, human–robot interaction, and related fields provided a preliminary appraisal of the principles in terms of clarity, feasibility, transferability, and overall usefulness. The framework received broadly favorable ratings, including a mean overall usefulness score of 4.33 on a 5-point scale, while expert comments highlighted the need for clearer operational definitions and flexible interaction modes. Because the empirical base consists of two small-sample Japanese-language learning studies conducted at one institution using one robot platform, DFMRE should be read as an early, context-grounded, falsifiable proposal rather than as a confirmed model for higher education e-learning in general. Full article

The escalating challenge of managing vector-borne pathologies necessitates the advancement of vector control strategies that are both highly potent and environmentally benign. This research evaluates the insecticidal efficacy and environmental plasticity of three Bacillus thuringiensis subsp. israelensis (Bti) H14 strains 33, 87/1, and 7-1/3 against laboratory and wild mosquito populations. In controlled laboratory assays, cultures with a spore density of 4.0–4.4 × 10⁹ spores/mL demonstrated significant larvicidal activity against larvae of all instars (L₁–L₄) of Aedes aegypti. The median lethal concentration (LC₅₀) was established between 1.15 and 1.48 µL/L, resulting in cumulative mortality rates of 95–96% within a 48 h exposure window. Proteomic profiling via SDS-PAGE and Western blotting validated the robust synthesis of the signature δ-endotoxin complex, specifically verifying the presence of Cry4Aa, Cry4Ba, Cry11Aa, and Cyt1Aa. Field applications in specific forest (Polissya) and steppe (Forest–Steppe) aquatic biotopes of Ukraine—characterized by distinct physicochemical profiles (differing significantly in light exposure, water hardness, salinity, and suspended solids)—substantiated the stability of the liquid formulations, achieving larval suppression rates of 95–100% within 48 h against wild Aedes-dominated assemblages at application rates of 0.25–1.0 mL/m² (equivalent to 2.5–10.0 L/ha). The demonstrated environmental adaptability suggests these novel strains are viable candidates for broad-spectrum ecological engineering applications. Their integration into sustainable vector control strategies offers a mechanism to enhance biosecurity without compromising the ecological balance of local biocenoses. Full article

Background: Artificial intelligence (AI) is increasingly entering hospital practice through diagnostic, predictive, workflow, operational, and generative applications. Hospitals often govern these systems as procurement or information-technology projects rather than as clinical–organizational interventions requiring indication, evaluation, monitoring, accountability, and withdrawal. Objective: To refine the concept of an “AI Hospital Formulary” as an operational, proportional, and accountable framework for the safe, equitable, and sustainable adoption of hospital AI. Design and Methods: This is a perspective article using a structured, non-systematic narrative synthesis and conceptual framework development. Targeted literature and policy sources were identified through purposive searches and citation chaining through 20 July 2026. The synthesis compares the formulary with existing oversight approaches, maps its lifecycle gates to regulatory and risk management duties, and applies the framework to a worked example based on published evaluations of the Epic Sepsis Model. The EQUATOR reporting-guideline selection tool was consulted, and SANRA was used to strengthen the narrative synthesis component. Framework: The revised framework combines a hospital-wide AI register, a standardized formulary monograph, six lifecycle gates, proportional review pathways, governance-of-governance safeguards, cloud and data-sovereignty controls, continuous monitoring of technical and behavioral feedback loops, and explicit renewal or deprescribing criteria. The worked example shows how version-specific evidence can lead to local validation, controlled implementation, restriction, suspension, or renewal rather than automatic adoption. Conclusions: Hospitals should not merely purchase, install, and update AI systems. They should prescribe, monitor, audit, renew, restrict, and, when necessary, deprescribe them. The AI Hospital Formulary is proposed as a complementary institutional layer that converts external standards and existing governance approaches into documented portfolio decisions at the hospital level. Full article

Dietary protein is essential for poultry performance, influencing egg production, growth, immunity, and physiological functions. However, the high cost and environmental impact of soybean meal has encouraged the development of reduced crude protein (CP) diets supplemented with crystalline amino acids (AAs), coupled with the reduced cost and improved availability of synthetic AA. This strategy enables precise AA balancing, improves nitrogen utilization, and reduces nitrogen excretion and ammonia emissions. Among these strategies, supplementation with arginine (Arg), an indispensable AA in chickens, is particularly important due to its critical roles in protein synthesis, reproductive function, and eggshell formation. In addition, functional Arg precursors, such as guanidinoacetic acid (GAA) and citrulline (Cit), can further enhance Arg availability while supporting energy metabolism and hormonal regulation. Despite these benefits, excessive protein reduction without adequate AA balance can impair laying performance, particularly in aged hens. Furthermore, nutrient digestibility remains a key limitation in reduced protein (RP) diets, as non-starch polysaccharides present in cereal-based feeds can reduce nutrient availability. The inclusion of exogenous enzymes, such as xylanase and β-glucanase, can improve digestibility, while phytase supplementation further enhances nutrient utilization by increasing phosphorus availability and mitigating the anti-nutritional effects of phytate; however, responses are often inconsistent. Another critical factor is maintaining an optimal energy-to-protein ratio, as imbalances may lead to increased fat deposition and reduced productive performance. While supplementation of key limiting AAs (lysine, methionine, and threonine) supports protein reduction, other AAs, such as Arg, isoleucine, and valine, may become limiting in RP diets. Hence, this review explores developments toward RP diets by highlighting three key strategies: enzyme supplementation to enhance nutrient digestibility, inclusion of functional Arg sources to improve performance and bone quality, and optimization of the energy–protein ratio in RP diets through precise AA formulation, with the overall aim to improve the sustainability of the poultry industry. Full article

Background/Objectives: Green antibacterial synthesis is a natural alternative to chemical methods, aligning with the Sustainable Development Goals by being beneficial to the environment and contributing to new therapies to combat antibiotic resistance. In this research, a simple method was developed for producing nanosystems with natural extracts of Ginger (Zingiber officinale) or Galangal (Alpinia galanga) with gold. Then, their antibacterial efficacy was evaluated and compared against strains of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). Methods: After optimizing the systems, the core size of the nanosystems was determined using transmission electron microscopy (TEM), and the presence of gold was confirmed with EDS. Stability control was measured using spectrometry, and the systems were characterized by measuring zeta potential and dynamic light scattering (DLS). Finally, to verify the antibacterial effect, minimum inhibitory concentration (MIC) assays were performed. Results: The analysis of the MIC experiments confirmed that the Galangal nanosystem (Au@Galangal showed better results against both bacteria. In the case of the Ginger nanosystem (Au@Ginger), the most evident results were against E. coli. Internalization studies demonstrated the antibacterial efficacy of all the nanosystems analyzed. Conclusions: The results suggest that nanosystems obtained entirely by green methods have great potential as alternative antimicrobial agents, especially against resistant strains, representing a major advance in the development of sustainable bactericidal nanosystems. Full article

Sugarcane molasses (SCM) is an abundant agro-industrial waste and a renewable carbon source for obtaining functional materials and chemicals. This work presents a one-pot strategy for converting SCM into bifunctional metal oxide–carbon catalysts for the production of 5-hydroxymethylfurfural (HMF). Catalysts were synthesised by hydrothermal carbonisation of SCM in the presence of SnCl₂·2H₂O or Al(NO₃)₃·9H₂O, enabling the in situ formation of the carbon support and incorporation of metal oxide phases. The effects of NaOH addition and thermal treatment under N₂ or CO₂ on catalyst structure and performance in the microwave-assisted conversion of sucrose to HMF in water were investigated. Al-containing hydrochars exhibited higher apparent Brønsted acidity (A_tot = 3.1–3.4 mmol H⁺·g⁻¹) than the Sn-containing materials (A_tot = 2.2–2.7 mmol H⁺·g⁻¹), while NH₃-TPD indicated a higher concentration of accessible acid sites after thermal treatment under CO₂. NaOH favoured the formation of poorly crystalline or amorphous Al-containing phases, whereas CO₂ activation significantly enhanced the texture of the catalysts. The highest HMF yield (36%) was achieved over the CO₂-treated, NaOH-derived Al-containing catalyst, demonstrating the importance of controlling catalyst acidity and textural properties for efficient HMF production from sucrose. Full article