Search Results (688)

Transcranial direct current stimulation (tDCS) can modulate cortical excitability in a polarity-specific manner, yet identical protocols often produce inconsistent outcomes across sessions or individuals. This narrative review proposes that much of this variability arises from the brain’s intrinsic temporal landscape. Integrating evidence from chronobiology, sleep research, and non-invasive brain stimulation, we argue that tDCS produces reliable, polarity-specific after-effects only within a circadian–homeostatic “window of efficacy”. On the circadian (Process C) axis, intrinsic alertness, membrane depolarisation, and glutamatergic gain rise in the late biological morning and early evening, whereas pre-dawn phases are marked by reduced excitability and heightened inhibition. On the homeostatic (Process S) axis, consolidated sleep renormalises synaptic weights, widening the capacity for further potentiation, whereas prolonged wakefulness saturates plasticity and can even reverse the usual anodal/cathodal polarity rules. Human stimulation studies mirror this two-process fingerprint: sleep deprivation abolishes anodal long-term-potentiation-like effects and converts cathodal inhibition into facilitation, while stimulating at each participant’s chronotype-aligned (phase-aligned) peak time amplifies and prolongs after-effects even under equal sleep pressure. From these observations we derive practical recommendations: (i) schedule excitatory tDCS after restorative sleep and near the individual wake-maintenance zone; (ii) avoid sessions at high sleep pressure or circadian troughs; (iii) log melatonin phase, chronotype, recent sleep and, where feasible, core temperature; and (iv) consider mild pre-heating or time-restricted feeding as physiological primers. By viewing Borbély’s two-process model and allied metabolic clocks as adjustable knobs for plasticity engineering, this review provides a conceptual scaffold for personalised, time-sensitive tDCS protocols that could improve reproducibility in research and therapeutic gain in the clinic. Full article

The objective of this research was to conduct a comprehensive review of rainbow trout (Oncorhynchus mykiss) culture in recirculating aquaculture systems (RAS), identify knowledge gaps, and propose strategies oriented towards intelligent and sustainable aquaculture. A systematic review and bibliometric analysis of 387 articles published between 1941 and 2025 in the Scopus database was carried out. Since 2011, there has been a sustained growth in scientific production, with the United States, Denmark, Finland, and Germany standing out as the main contributors. The journals with the highest number of publications were Aquacultural Engineering, Aquaculture, and Aquaculture Research. The conceptual analysis revealed the following three thematic clusters: experimental studies on physiology and metabolism; research focused on nutrition, growth, and yield; and technological developments for water treatment in RAS. This evolution reflects a transition from basic approaches to applied technologies oriented towards sustainability. There was also evidence of a thematic transition toward molecular tools such as proteomics, transcriptomics, and real-time PCR. However, there is still limited integration of smart technologies such as the IoT. It is recommended to incorporate self-calibrating multi-parametric sensors, machine learning models, and autonomous systems for environmental regulation in real time. Full article

This paper introduces a unified and systematic design methodology for robotic systems that is generalizable across a wide range of applications. It integrates rigorous mathematical formalisms such as kinematics, dynamics, control theory, and optimization with advanced simulation tools, ensuring that each design decision is grounded in provable theory. The approach defines clear phases, including mathematical modeling, virtual prototyping, parameter optimization, and theoretical validation. Each phase builds on the previous one to reduce unforeseen integration issues. Spanning from conceptualization to deployment, it offers a blueprint for developing mathematically valid and robust robotic solutions while streamlining the transition from design intent to functional prototype. By standardizing the design workflow, this framework reduces development time and cost, improves reproducibility across projects, and enhances collaboration among multidisciplinary teams. Such a generalized approach is essential in today’s fast-evolving robotics landscape where rapid innovation and cross-domain applicability demand flexible yet reliable methodologies. Moreover, it provides a common language and set of benchmarks that both novice and experienced engineers can use to evaluate performance, facilitate knowledge transfer, and future-proof systems against emerging application requirements. Full article

The article examines the application of collaborative robots (cobots) as a modern engineering tool for the transformation of the food industry following the principles of Industry 5.0. A conceptual engineering model has been developed that integrates collaborative robots with IoT systems, digital twins, and predictive analytics to increase the flexibility, safety, and sustainability of production processes. The proposed model is validated through a practical case study focused on a yogurt packaging line in the dairy sector, where cobot systems demonstrate a significant improvement in operational efficiency and process safety. A step-by-step strategic roadmap is presented to guide industrial enterprises through the various stages of implementation, from the initial assessment to the full-scale integration of solutions. Additionally, a comparative analysis has been performed between traditional automated systems and the integrated approach with collaborative robots, which highlights the technological, economic, and human-oriented advantages of the latter. The results of the study confirm that collaborative robotics offers an effective and applicable path for transforming the food and beverage industry towards a sustainable, adaptive, and human-centered manufacturing ecosystem characteristic of Industry 5.0. Full article

Ontologies are essential tools for representing, organizing, and sharing knowledge across various domains. This study presents a methodology for ontology construction supported by large language models (LLMs), with an initial application in the automotive sector. Specifically, a user preference ontology for adaptive interfaces in autonomous machines was developed using ChatGPT-4o. Based on this case study, the results were generalized into a reusable methodology. The proposed workflow integrates classical ontology engineering methodologies with the generative and analytical capabilities of LLMs. Each phase follows well-established steps: domain definition, term elicitation, class hierarchy construction, property specification, formalization, population, and validation. A key innovation of this approach is the use of a guiding table that translates domain knowledge into structured prompts, ensuring consistency across iterative interactions with the LLM. Human experts play a continuous role throughout the process, refining definitions, resolving ambiguities, and validating outputs. The ontology was evaluated in terms of logical consistency, structural properties, semantic accuracy, and inferential completeness, confirming its correctness and coherence. Additional validation through SPARQL queries demonstrated its reasoning capabilities. This methodology is generalizable to other domains, if domain experts adapt the guiding table to the specific context. Despite the support provided by LLMs, domain expertise remains essential to guarantee conceptual rigor and practical relevance. Full article

Urban flooding presents a growing challenge amid rapid urbanization, climate variability, and fragmented governance. Although simulation and risk assessment tools have advanced considerably, their integration into urban planning remains limited. This study utilized a comprehensive bibliometric analysis of 1293 articles from the Scopus database, selected through a PRISMA-guided workflow, to examine the temporal, structural, and conceptual evolution of simulation, flood risk, and planning in urban flood research from 1980 to 2025. The findings reveal a thematic progression from engineering-centric approaches to broader discourses on resilience, adaptation, and systemic risk. However, disciplinary fragmentation persists, with technical modeling, infrastructure planning, and governance still weakly connected. Despite a shared vocabulary around climate risk and resilience, practical integration into decision-making frameworks remains underdeveloped. The study highlights the need for more cohesive research-practice linkages and calls for frameworks that better align simulation outputs with urban planning imperatives. Full article

A longstanding ambiguity surrounds the operationalization of consciousness in artificial systems, complicated by the philosophical and cultural weight of subjective experience. This work examines whether cognitive architectures may be designed to support a functionally explicit form of artificial consciousness, focusing not on the replication of phenomenology, but rather on measurable, technically realizable introspective mechanisms. Drawing on a critical review of foundational and contemporary literature, this study articulates a conceptual and methodological shift: from investigating the experiential perspective of agents (“what it is like to be a bat”) to analyzing the informational, self-regulatory, and adaptive structures that enable purposive behavior. The approach combines theoretical analysis with a comparative review of major cognitive architectures, evaluating their capacity to implement access consciousness and internal monitoring. Findings indicate that several state-of-the-art systems already display core features associated with functional consciousness—such as self-explanation, context-sensitive adaptation, and performance evaluation—without invoking subjective states. These results support the thesis that cognitive engineering may progress more effectively by focusing on operational definitions of consciousness that are amenable to implementation and empirical validation. In conclusion, this perspective enables the development of artificial agents capable of autonomous reasoning and self-assessment, grounded in technical clarity rather than speculative constructs. Full article

Artisanal and small-scale gold mining (ASGM) in Burkina Faso increasingly relies on cyanide, intensifying concerns about environmental contamination and human exposure. This study assessed free cyanide levels in water and soil across three ASGM sites—Zougnazagmiline, Guido, and Galgouli. Water samples (surface and groundwater) and topsoil (0–20 cm) were analyzed using the pyridine–pyrazolone method. Data were statistically and spatially processed using SPSS version 29.0 and the Google Earth Engine in conjunction with QGIS version 3.34, respectively. A site conceptual model (SCM) was also developed, based on the literature review, field observations, and validation by multidisciplinary experts in public health, toxicology, ecotoxicology, environmental engineering, and the mining sector, through a semi-structured survey. The results showed that 9.26% of the water samples exceeded the WHO guideline (0.07 mg/L), with peaks of 1.084 mg/L in Guido and 2.42 mg/L in Galgouli. At Zougnazagmiline, the water type differences were significant (F = 64.13; p < 0.001), unlike the other sites. In the soil, 29.36% of the samples exceeded 0.5 mg/kg, with concentrations reaching 9.79 mg/kg in Galgouli. A spatial analysis revealed pollution concentrated near the mining areas but spreading to residential and agricultural zones. The validated SCM integrates pollution sources, transport mechanisms, exposure routes, and vulnerable populations, offering a structured tool for environmental monitoring and health risk assessment in cyanide-impacted mining regions. Full article

The objective of this study is to design, develop, and analyze a tri-wheeled trolley integrated with a motor that incorporates adjustable and foldable features. The purpose of a trolley is to allow users to easily transport items from one place to another. However, problems arise when transporting objects across challenging surfaces, such as up a flight of stairs, using a conventional cart. This innovation uses multiple engineering skills to determine and develop the best possible design for a stair-climbing trolley. A tri-wheel mechanism is integrated into its motorized design, meticulously engineered for adjustability, ensuring compatibility with a wide range of staircase dimensions. The designed trolley was constructed considering elements and processes such as a literature review, conceptual design, concept screening, concept scoring, 3D modelling, engineering design calculations, and simulations. The trolley was tested, and the measured pulling force data were compared with the theoretical calculations. A graph of the pulling force vs. load was plotted, in which both datasets showed similar increasing trends; hence, the designed trolley worked as expected. The development of this stair-climbing trolley can benefit people living in rural areas or low-cost buildings that are not equipped with elevators and can reduce injuries among the elderly. The designed stair-climbing trolley will not only minimize the user’s physical effort but also enhance safety. On top of that, the adjustable and foldable features of the stair-climbing trolley would benefit users living in areas with limited space. Full article

Uniquely rooted in regenerative leadership and complemented by Complexity Leadership Theory (CLT), this conceptual essay offers a theoretical exploration of how educational institutions can act as dynamic systems that catalyze adaptive, community-led responses to anthropocentric socio-environmental crises. Rather than sustaining existing structures, educational leadership for regeneration seeks to restore ecological balance and nurture emergent capacities for long-term resilience. Positioned as key sites of influence, educational institutions are explored as engines of innovation capable of mobilizing students, educators, and communities toward collective environmental action. CLT offers a valuable lens for understanding how leadership emerges from nonlinear, adaptive processes within schools, enabling the development of innovative, collaborative, and responsive strategies required for navigating complexity and leading planetary-positive change. Drawing on a synthesis of the recent global literature, this paper begins by outlining the need to go beyond sustainability in envisioning regenerative futures, followed by an introduction to regenerative principles. It then examines the current and evolving role of educational leadership, the relevance in enabling whole-institution transformation, and how this relates to regenerative practices. The theoretical frameworks of systems thinking and CLT are introduced before noting their application within regenerative educational leadership. The final sections identify implementation challenges and offer practical recommendations, including curriculum innovation, professional development, and youth-led advocacy, before concluding with a call for education as a vehicle for cultivating planetary-conscious citizens and systemic change. This work contributes a timely and theoretically grounded model for reimagining educational leadership in an era of global turbulence. Full article

Teaching of embedded systems, including communication protocols such as SMBus, is commonly faced with difficulties providing the students with interactive and personalized, practical learning experiences. To overcome these shortcomings, this report presents a new conceptual framework that exploits generative artificial intelligence (GenAI) via customized DV-GPT. Coupled with prepromises techniques, DV-GPT offers timely targeted support to students and engineers who are studying SMBus protocol design and verification. In contrast to traditional learning, this AI-based tool dynamically adjusts feedback based on the users’ activities, providing greater insight into challenging concepts, including timing synchronization, multi-master arbitration, and error handling. The framework also incorporates the industry de facto standard UVM practices, which helps narrow the gap between education and the professional world. We quantitatively compare with a baseline GPT-4 and show significant improvement in accuracy, specificity, and user satisfaction. The effectiveness and feasibility of the proposed GenAI-enhanced educational approach have been empirically validated through the use of structured student feedback, expert judgment, and statistical analysis. The contribution of this research is a scalable, flexible, interactive model for enhancing embedded systems education that also illustrates how GenAI technologies could find applicability within specialized educational environments. Full article

This paper explores the potential and implications arising from the convergence of virtual reality, the metaverse, and digital twins in translating a real-world commemorative event into a virtual environment. It emphasizes how such integration influences digital transformation processes, particularly in reshaping models of social interaction. Virtual reality is conceptualized as an immersive technology, enabling advanced multisensory experiences within persistent virtual spaces, such as the metaverse. Furthermore, this study delves into the concept of digital twins—high-fidelity virtual representations of physical systems, processes, and objects—highlighting their application in simulation, analysis, forecasting, prevention, and operational enhancement. In the context of virtual events, the convergence of these technologies is examined as a means to create interactive, adaptable, and scalable environments capable of accommodating diverse social groups and facilitating global accessibility. As a practical application, a digital twin of the Ferrándiz and Carbonell buildings—the most iconic architectural ensemble on the Alcoi campus—was developed to host a virtual event commemorating the 50th anniversary of the integration of the Alcoi School of Industrial Technical Engineering into the Universitat Politècnica de València in 1972. The virtual environment was subsequently evaluated by a sample of users, including students and faculty, to assess usability and functionality, and to identify areas for improvement. The digital twin achieved a score of 88.39 out of 100 on the System Usability Scale (SUS). The findings underscore the key opportunities and challenges associated with the adoption of these emerging technologies, particularly regarding their adaptability in reconfiguring digital environments for work, social interaction, and education. Using this case study as a foundation, this paper offers insights into the strategic role of the metaverse in extending environmental perception and its transformative potential for the future digital ecosystem through the implementation of digital twins. Full article

Decentralized desalination systems driven by renewable energy sources have surfaced as a feasible way to alleviate water scarcity in arid and rural areas. This bibliometric study aims to clarify the research trends, conceptual frameworks, and cooperative dynamics in the scientific literature on decentralized renewable-powered desalination techniques. Using a thorough search approach, 1354 papers were found. Duplicates, thematically unrelated works, and entries with poor information were removed using the PRISMA 2020 framework. A selected 832 relevant papers from a filtered dataset were chosen for in-depth analysis. Quantitative measures were obtained by means of Bibliometrix; network visualisation was obtained by means of VOSviewer (version 1.6.19) and covered co-authorship, keyword co-occurrence, and citation structures. Over the previous 20 years, the data show a steady rise in academic production, especially in the fields of environmental science, renewable energy engineering, and water treatment technologies. Author keyword co-occurrence mapping revealed strong theme clusters centred on solar stills, thermoelectric modules, reverse osmosis, and off-grid systems. Emphasizing current research paths and emerging subject borders, this paper clarifies the intellectual and social structure of the field. The outcomes are expected to help policy creation, cooperative projects, and strategic planning meant to hasten innovation in sustainable and decentralized water desalination. Full article

Native forest timber supplies are declining, and industry needs to do more with less to meet growing demand for wood products. An Australian-based, vertically integrated timber manufacturing business is commissioning a spindleless lathe to produce engineered wood products from small logs. The literature on innovation in timber manufacturing was found to generally focus on technical innovation, with relatively little use of market-oriented concepts and theory. This was particularly true in the Australian context. Using a market-oriented case study approach, this research assessed innovation in the business. It aimed to inform industry-wide innovation approaches to meet market demand in the face of timber supply challenges. Interviews were conducted with key personnel at the firm. Data and outputs were produced to facilitate comparison to existing research and conceptual frameworks. The business was found to empower key staff and willingly access knowledge, information and data from outside its corporate domain. It was also found to prioritise corporate goals outside of traditional goals of profit and competitive advantage. This was shown to increase willingness to try new things at the mill and increase the chances that new approaches would succeed. Thinking outside of the corporate domain was shown to allow access to resources that the firm could not otherwise count on. It is recommended that wood processing businesses seek to emulate this element of the case study, and that academia and the broader sector examine further the potential benefits of using enterprise and market-oriented lenses to better utilise available resources and maintain progress towards corporate goals. Full article

In the current context, where environmental concerns are gaining increased attention, the transition toward sustainable urban mobility stands out as a necessary and responsible step. Technological advancements over the past decade have brought private autonomous vehicles, particularly those defined by the Society of Automotive Engineers Levels 4 and 5, into focus as promising solutions for mitigating road congestion and reducing greenhouse gas emissions. However, the extent to which Autonomous Vehicles can fulfill this potential depends largely on user acceptance, patterns of use, and their integration within broader green energy and sustainability policies. The present paper aims to develop an integrated conceptual model that links behavioral determinants to environmental outcomes, assessing how individuals’ intention to adopt private autonomous vehicles can contribute to sustainable urban mobility. The model integrates five psychosocial determinants—perceived usefulness, trust in technology, social influence, environmental concern, and perceived behavioral control—with contextual variables such as energy source, infrastructure availability, and public policy. These components interact to predict users’ intention to adopt AVs and their perceived contribution to urban sustainability. Methodologically, the study builds on a narrative synthesis of the literature and proposes a framework applicable to empirical validation through structural equation modeling (SEM). The model draws on established frameworks such as Technology Acceptance Model (TAM), Theory of Planned Behavior, and Unified Theory of Acceptance and Use of Technology, incorporating constructs including perceived usefulness, trust in technology, social influence, environmental concern, and perceived behavioral control, constructs later to be examined in relation to key contextual variables, including the energy source powering Autonomous Vehicles—such as electricity from mixed or renewable grids, hydrogen, or hybrid systems—and the broader policy environment (regulatory frameworks, infrastructure investment, fiscal incentives, and alignment with climate and mobility strategies and others). The research provides relevant directions for public policy and behavioral interventions in support of the development of clean and smart urban transport in the age of automation. Full article