Search Results (985)

For more than seventy years, mathematics—particularly the calculus sequence—has defined both the rigor and the exclusivity of engineering education in the United States. While this structure was historically instrumental in professionalizing engineering, it has also produced unintended consequences: restricted access, misalignment with contemporary engineering practice, and persistent inequities in participation and degree attainment. This commentary argues that mathematics must be reimagined not as a barrier or filter, but as a gateway that enables engineering learning, persistence, and innovation. Building on The Engineering Mindset Report and decades of research in engineering education, learning sciences, and curricular reform, we examine how mathematics became a gatekeeping mechanism, assess its current impacts, and propose a framework for redesigning engineering mathematics around context, modularity, technology, and equity. We advocate for accessible, flexible, and technology-enabled pathways that emphasize modeling, data analysis, and conceptual understanding over procedural endurance. Such an approach has the potential to broaden participation, improve student success, and better align engineering education with the realities of 21st-century professional practice. Full article

In Latin America and the Caribbean, the circular economy approach is embedded in productive structures characterized by a dependence on natural resources and the persistence of informal economies. The general objective of this article is to analyze the circular economy as an approach to production and consumption in Latin America and the Caribbean through a bibliometric and qualitative analysis of scientific literature. This study adopted a mixed, descriptive, and analytical research design. International and regional databases (Scopus, Web of Science, SciELO, and Redalyc) were used to identify articles published between 2015 and 2025. The selection process followed the PRISMA protocol, resulting in a final qualitative analysis of 47 articles. The results reveal an accelerated and sustained growth in scientific production in the region, with a maximum increase of 250% in 2017, indicating a progressive consolidation of the field. The documentary corpus consists mainly of original articles (65%), with a clear preeminence of environmental sciences, engineering, and energy. Qualitatively, the literature shows a conceptual heterogeneity that adapts the circular economy to sustainable development and industrial ecology, uniquely incorporating grassroots recyclers and cooperatives into a “just transition.” However, there is evidence of an implementation gap: while large industries are making progress in eco-design and remanufacturing, adoption in SMEs and responsible consumption—especially in repair and reuse—remains at incipient levels due to structural and cultural limitations. Ultimately, the results suggest a growing concentration of circular economy research within selected Latin American institutions, indicating the emergence of regionally grounded research agendas that may differ in emphasis from dominant Global North framings. Full article

With the tightening of international environmental requirements for civil aviation and the implementation of initiatives aimed at reducing specific greenhouse gas emissions, the transition to hybrid power plants for regional aircraft is becoming increasingly relevant. This paper proposes an approach to the integrated energy assessment of a parallel hybrid turboprop power plant at the conceptual design stage while taking the aircraft mission profile into account. The considered power plant includes a gas turbine engine, a reversible electric machine located on the same shaft as the reduction gearbox and propeller, an electrical energy storage system, and power electronics. The mission profile is represented as a sequence of segments—takeoff, climb, cruise, descent, and approach/landing. For each segment, energy balances are formulated and allowable operating ranges for the gas turbine and electric subsystems are defined. The key parameter is the hybridization factor, which determines the share of power transmitted to the propeller from the electric machine in different mission segments. The primary integrated performance metric is the energy consumption per ton-kilometer of transported payload. The analysis shows that for ranges up to 500 km, the hybrid configuration reduces specific energy consumption per ton-kilometer by up to 9%. Full article

Healthy building concepts are increasingly recognized as important for improving occupant health and well-being, yet empirical evidence on their understanding and implementation in sub-Saharan African contexts remains limited. This study provides an exploratory assessment of construction professionals’ awareness and self-reported application of healthy building concepts in Gabon. Using a structured questionnaire survey of 45 construction professionals, including architects, engineers, and contractors, the study examines sources of awareness, patterns of application across project stages, and health-related dimensions prioritized in practice. The results indicate high levels of conceptual awareness within the surveyed group, but uneven and context-dependent application. Implementation is strongly concentrated at the design stage, while continuity during construction and operation remains limited. Professionals tend to prioritize tangible and measurable dimensions such as lighting, materials, air quality, and thermal comfort, whereas psychosocial and community-related aspects receive less attention. Based on these empirical patterns, the study proposes an empirically informed and context-sensitive framework structured around six strategic pillars to support the gradual integration of healthy construction practices in Gabon. Rather than offering a prescriptive model, the framework serves as an analytical reference to inform future research, professional capacity building, and policy dialog. Given the exploratory nature of the study and its reliance on self-reported data, the findings should be interpreted as indicative rather than generalizable. Full article

This paper presents FMECA-VR-0.1 Prototype, a Maintenance 4.0-oriented immersive Virtual Reality (VR)-based training platform that integrates tools in a digital and virtual environment with Failure Modes, Effects, and Criticality Analysis (FMECA) and the Qualitative Risk Criticality Matrix (QRCM) to enhance reliability-oriented maintenance training in the wind energy sector. The methodological framework is aligned with the Maintenance Management Model (MMM) developed by INGEMAN. It is applied to a VESTAS V100–2.0 MW wind turbine operating at the Valle de los Vientos Wind Farm in northern Chile. The study includes the definition of the operational context, subsystem-level criticality assessment, and a detailed FMECA of the blade subsystem, which are integrated as analytical layers within the immersive VR environment. The proposed platform enables users to visualize critical components, analyze physical failure modes, understand associated consequences, and review preventive and corrective maintenance strategies in an interactive 3D scenario. Preliminary qualitative feedback suggests potential improvements in user engagement and conceptual understanding; however, no formal experimental validation has been conducted at this stage. The FMECA-VR-0.1 prototype demonstrates a feasible path for incorporating risk-based engineering logic into immersive training ecosystems. It establishes the foundation for future developments involving digital twins, real-time monitoring data, multi-subsystem modeling, and quantitative assessment of learning performance. Full article

Negative capacitance (NC) has been reported across a wide range of physical systems, yet its interpretation has remained fragmented due to the lack of a unified conceptual framework. Existing explanations—spanning ferroelectric free-energy curvature, tunneling transport, plasmonic resonances, and electronic compressibility—have often been treated as unrelated or even contradictory. This review resolves these inconsistencies by showing that all manifestations of NC arise from non-synchronization between external excitation and internal response. We classify NC into three fundamental categories: temporal mismatch, originating from delays or inertia in charge or polarization dynamics; spatial mismatch, caused by nonuniform field or mode distributions; and quantitative mismatch, resulting from intrinsic parameter reversal such as negative curvature or negative compressibility. Despite their diverse physical origins, these mechanisms share the same mathematical signature (${\mathrm{C}}_{eff}=\partial \mathrm{Q}/\partial \mathrm{V}<0$). Organizing NC within this unified framework clarifies long-standing ambiguities, connects previously isolated research fields, and establishes a systematic foundation for engineering NC in electronic, photonic, and quantum devices. The framework further highlights tunnel-current-induced NC as a representative single-particle mechanism within the temporal mismatch category, expanding the scope of NC beyond ferroelectricity and collective modes. Overall, this work positions NC not as a singular anomaly but as a universal response class emerging from the interplay between excitation and internal dynamics. Full article

Wildfires are increasing in frequency, intensity, and duration, driving up suppression and damage costs and motivating a more coordinated use of aerial firefighting assets. Within this context, we extend the COLOSSUS Project’s X-Challenge System-of-Systems (SoS) simulation toolkit with an integrated aircraft sizing and fleet assessment methodology that links conceptual aircraft design with tactic selection. Two platforms are sized under 2035 technology assumptions—a 2000 kg payload electric Vertical Takeoff Landing (eVTOL) and a 3000 kg payload Single Engine Air Tanker (SEAT) using physics-based performance and parametric cost models. A Design of Experiments (DoE) workflow coupled with the SoS toolkit evaluates mixed fleets and tactic assignments in three representative regions. Effectiveness is quantified via a weighted, normalized Measure of Effectiveness that aggregates burnt area, emissions, and cost metrics into a single scalar. Results show that acquisition cost dominates overall effectiveness and that location-specific fleet compositions can outperform a single fixed fleet without degrading suppression outcomes, motivating future work on adaptive, region-specific fleet design and sensitivity analyses. Full article

Background: Macrophages were long regarded as passive executors of erythrophagocytosis responsible for systemic iron recycling. However, increasing evidence has reframed them as immunometabolic hubs that sense diverse environmental cues to modulate systemic iron homeostasis. Main body: This review examines the molecular architecture underlying macrophage iron metabolism and outlines how iron metabolic processes are dynamically regulated across spatial and temporal scales through the integration of mechanotransductive, mitochondrial, and epigenetic signaling pathways. Across disease contexts, macrophage iron handling displays marked heterogeneity, exemplified by contact-dependent iron transfer in tumors and ferroptosis-driven instability in cardiovascular disease. In cardiovascular pathologies, iron overload is associated with enhanced ferroptosis-related cascades that contribute to atherosclerotic plaque instability. Furthermore, at mucosal interfaces, host–pathogen competition over nutritional immunity highlights epigenetic strategies by which pathogens perturb host iron machinery. Conclusions: Linking these mechanistic insights to clinical translation, emerging therapeutic strategies are discussed that move beyond non-specific systemic iron chelation toward more targeted interventions. These include engineering macrophages for targeted drug delivery, exploiting nanomedicine-based redox modulation to influence macrophage phenotypes, and non-invasive regulation via the gut microbiota–epigenetic axis. Collectively, elucidating macrophage iron metabolic networks provides a conceptual framework for the development of precision approaches to inflammatory, metabolic, and malignant diseases. Full article

Generative artificial intelligence (AI), especially large language models (LLMs) that can write and debug code, is changing how students approach programming work in engineering education. Unlike more open-ended conceptual or modeling tasks, programming fits closely with what these systems do well: generating syntax, fixing errors, building procedural logic, and completing code structures. Hence, programming coursework may be one of the areas in which AI changes performance patterns in a measurable way. This study examines whether that shift appears in actual student outcomes. Using a retrospective pre/post design, it compares results from a pre-AI period (2021–2022) with results from a post-AI period (2023–2025), when generative AI tools became widely available to students. The focal assessment is a comprehensive programming project graded with the same rubric across multiple sections and terms. Performance is evaluated through descriptive statistics, distributional comparisons, and mastery thresholds (≥80%). The post-AI period shows a rise in overall scores, along with strong clustering near the top of the scale. Lower- and middle-range scores become much less common, most students fall in the highest score band, and overall variability declines. These results suggest that generative AI acts as a procedural equalizer in programming contexts, referring to the role of generative AI in reducing performance differences by assisting with rule-based, syntax-driven, and execution-oriented aspects of tasks, thereby raising baseline outcomes while compressing variation among students. It appears to raise lower-end performance and make outcomes more consistent, but it also narrows the spread among stronger students and creates a ceiling effect. That pattern raises questions about assessment validity, skill differentiation, and what “mastery” means when AI can handle much of the procedural work. Using multi-term data from authentic online courses, this study adds empirical evidence to the growing literature on AI in engineering education and identifies programming coursework as a setting where generative AI may have already changed performance dynamics in a structural way. Full article

This narrative conceptual review aims to examine how veterinary science intertwines with the different ontologies of resilience. As resilience has increasingly become an influential yet conceptually diverse framework, its different ontologies shape and are shaped by veterinary science thinking. This paper will begin with a brief overview of the origins of the resilience concept and its three major ontologies: engineering, psychological, and ecological resilience. Following these different ontologies, the paper then explores animal-level resilience, where engineering framings emphasise disease response and production stability, while welfare-oriented perspectives frame resilience in terms of the affective experience and the lived realities of animals. It then considers veterinary professional resilience, highlighting how emotional labour, workload pressures and structural constraints shape wellbeing across the profession. Finally, it analyses how veterinary science contributes to socio-ecological resilience through One Health approaches in public health, food systems and climate adaptation. Across these domains, resilience is often framed as a desirable attribute, yet it remains a value-laden concept that can obscure inequities or normalise preventable harms. This paper calls for critical, justice-oriented engagement with resilience to ensure it supports ethically grounded veterinary practice and promotes healthier, happier animals, more equitable systems, and sustainable professional environments. Full article

This paper advances a theoretical argument that generative AI is accelerating the democratization of computational thinking and, in turn, reshaping education, professional practice, and the nature of computing itself. Traditionally, computational thinking has been closely tied to learning to program, thereby limiting who could effectively employ it. The emergence of large language models (LLMs) challenges this linkage by decoupling many forms of computational problem solving from direct programming. In response to this shift, the paper explores the implications for curriculum design and workforce roles through a theoretical and interpretive lens. Drawing on prior literature, historical context, and illustrative examples from recent scholarship and practice, we develop a conceptual account of AI-augmented computing. We argue that LLMs lower barriers to entry by abstracting away much of manual coding and reallocating effort toward problem framing, prompt engineering, oversight, and validation. We further argue that this transition is redistributing computational skills across disciplines, positioning prompt engineering as an emerging engineering practice, and increasing pressure on universities to redesign curricula around AI literacy, fluency, and mastery. Full article

Advanced nanomaterials are becoming increasingly critical for improving the efficiency, durability, and sustainability of bioenergy systems, with applications spanning biomass conversion, catalysis, and bioelectrochemical energy generation. This systematic bibliometric and thematic review analyses Scopus-indexed literature from 2020 to 2025 to elucidate global research trends in nanomaterial characterisation and performance evaluation for bioenergy applications. Bibliometric mapping using VOSviewer version 1.6.18 reveals a rapidly growing research landscape structured around three dominant themes: nanocatalysts for biodiesel and bioethanol production, nanostructured enhancements in bioelectrochemical and anaerobic digestion systems, and surface-engineered materials for energy conversion and storage. The review highlights the pivotal role of structural and morphological characterisation techniques including SEM, TEM, AFM, and XRD in establishing structure–property–performance relationships that underpin catalytic activity, electron transfer efficiency, and system stability. Beyond short-term catalytic and electrochemical metrics, increasing attention is given to mechanical stability, durability, and long-term operational reliability, which are shown to be critical determinants of scalability. Emerging strategies such as additive manufacturing and hybrid material systems enable the integration of nanomaterials into architected, mechanically robust structures, mitigating degradation and enhancing sustained performance. A concise conceptual framework is presented to link nanomaterial classes, characterisation challenges, targeted bioenergy applications, and scalability constraints. Despite significant progress, gaps remain in standardised characterisation protocols, durability-focused testing, and life-cycle assessment. Addressing these challenges is essential for translating laboratory-scale advances into scalable, sustainable bioenergy technologies. Full article

Intelligent automation is a core component of Industry 4.0, enabling artificial intelligence (AI) systems to support or execute operational and managerial decisions in real time. In high-risk industrial environments such as mining and metallurgy, real-time decision-making improves efficiency but also raises critical challenges related to trust, explainability, human oversight, and institutional accountability. This study proposes PRIME–INSPECT, a two-layer socio-technical framework designed to support trustworthy AI-driven real-time decision-making. The PRIME (predict, regulate, interpret, mitigate, execute) layer formalizes the operational decision flow, embedding control mechanisms, uncertainty quantification, and explainability into the automation pipeline. The INSPECT (integrity, navigability, supervisory control, policy maturity, ethical compliance, collaboration, trust calibration) layer defines the organizational and governance conditions required for safe deployment. The framework is conceptually developed through a structured literature synthesis and supported by exploratory empirical grounding through stakeholder perceptions from IT and top management participants, alongside an illustrative industrial use case intended to demonstrate conceptual applicability rather than engineering performance validation. The findings highlight the importance of aligning operational AI processes with institutional safeguards to support calibrated trust and responsible automation. The empirical component is intended to provide conceptual and organizational grounding of framework dimensions rather than quantitative validation of predictive performance. PRIME–INSPECT provides a structured architecture for designing and governing AI-enabled real-time decision systems in high-risk industrial contexts. Full article

This study aims to identify key health and safety challenges and examine root causes while developing a conceptual framework to improve safety. Results of the study will be useful for policy makers, regulatory authorities, construction managers, safety professionals and researchers to improve regulations, safety practices, training programs and policy development. The emerging construction industry in Sri Lanka is facing significant safety challenges for workers, including poor practices, inappropriate conduct, and negative attitudes. The construction industry was selected for this study due to its labor-intensive nature and its consistently high exposure to occupational hazards compared to other industrial sectors. The underlying root causes of these health and safety challenges remain unclear, primarily due to a lack of comprehensive government regulations, which are currently limited to the outdated Factories Ordinance of 1942. Sri Lanka was chosen as the focus of this study because of its rapidly expanding construction sector and outdated regulatory framework; it is also a representative of underdeveloped countries. Several studies have identified contributing factors such as outdated legislation, a shortage of qualified officers, poor attitudes, lack of funding, negligence, and limited awareness. To address this research gap, the safety aspects of the Sri Lankan construction industry have been examined, revealing emerging challenges such as poor safety practices, the presence of foreign workers, and the inadequate use of personal protective equipment (PPE) by staff. A deeper examination of these challenges indicates that sufficient safety budgets reflect leadership attitudes toward preventing injuries, and that targeted safety training for different roles can help mitigate these issues. Accordingly, a conceptual safety framework has been developed. A qualitative, semi-structured interview comprising both open- and closed-ended questions was conducted to gain insights from 26 experts (including engineers, architects, human resource personnel, safety officers, and managers) regarding workplace safety challenges. The interview data was thematically categorized based on the identified safety challenges using NVivo analysis, to determine their root causes and develop strategies to improve workplace safety. To evaluate the emotional tone of participants’ response, sentiment analysis was conducted. Results highlighted participants’ optimism when discussing proactive or successful safety measures, neutrality in objective assessments, and concern or dissatisfaction when addressing safety challenges and organizational shortcomings. Experts recommended that safety education should be introduced in universities and vocational institutes. Firms can incorporate safety training through toolbox talks and induction sessions, and they can allocate a safety budget in their contracts. The study suggests developing a certificate-level safety training module for the construction industry and provides fresh insights into the underlying causes of safety issues in the Sri Lankan construction sector. Furthermore, the study has implications for delivering a health and safety framework for project risk management in developing countries that face budget constraints and limited training and development opportunities for enhancing construction skill sets. Full article

The production of pre-basic (G0) seed tubers underpins the certified potato value chain. However, the transition from in vitro laboratory conditions to the ex vitro greenhouse environment remains a persistent production constraint, with reported mortality rates of 50–70%. This systematic review, conducted in accordance with PRISMA 2020 guidelines, synthesizes data from 63 selected studies (spanning 2010–2026) to propose a conceptual “Physiological Competence Framework”. We introduce a conceptual hypothesis termed the “Nitrogen Paradox”, which suggests that excessive ammonium influx may inhibit lignin biosynthesis, explaining the structural vulnerability of the vitrotype. Our analysis proposes three pillars for acclimatization success: (1) Nutritional hardening and exogenous PGR modulation, characterized by reduced nitrogen and sucrose levels to mitigate hyperhydricity; (2) photo-autotrophic induction, where optimized LED spectra replace conventional lighting to stimulate stomatal functionality; and (3) rhizosphere engineering, utilizing bio-priming with Plant Growth-Promoting Rhizobacteria (PGPR) to create a biotic shield against transplant shock. Furthermore, we examine emerging evidence for nanoparticle-based stress priming (AgNPs, ZnNPs). The evidence supports replacing high-nitrogen multiplication media with reduced-nitrogen formulations, replacing fluorescent lamps with balanced Red–Blue LED spectra, and incorporating PGPR bio-priming before transplant. Full article