Search Results (1,596)

Low-cost sensors have demonstrated their advances in acquiring hyper-localized data compared to traditional, high-maintenance air quality monitoring stations. The study aims to leverage the mobility of participants equipped with low-cost wearable monitors (LWMs) by comparing their exposure to particulate matter (PM) across indoor-home, outdoor-walking, and hybrid-commuting micro-environments. The LWMs would be calibrated first through field co-location and the multiple linear regression models. The coefficient of determination (R²) of PM_1.0 and PM_2.5 increased to over 0.85 after calibration, along with the reduced root mean square error of 2.25 and 3.46 μg/m³, respectively. The 26-day PM data collection with geographic locations could identify individual exposure patterns, local source contributions, and hotspot maps. Commuting constituted a small fraction of daily time (4–8%) but contributed a disproportionate impact, accounting for 11% of individual PM exposure. Indoor-home PM_2.5 exposure varied significantly among the urban districts. Based on the PM_2.5 hotspot map, the elevated concentration was mainly concentrated in dense residential areas and historical industrial areas, as well as interchanges of major roads and the highway system. LWMs acting as non-regulatory instruments can complement monitoring stations to provide missing short-term and hyper-localized air pollution data. Future studies should integrate long-term monitoring and citizen science across seasons and geographical regions to address pollutant spatiotemporal variability for building and city sustainability. Full article

Nowadays, public buildings are clad on the outside, many with stone-clad facades. Energy requirements have changed a lot in the last 20–25 years, and the latest required value of the thermal conductivity of masonry is 0.24 W/m²K. The relevant requirements, available materials, and fastening technology options have changed significantly. Our research covers a comprehensive analysis of these systems, the selection of stone cladding materials, and the suitability and use of individual stone types for facade cladding, as well as an energy examination of layered wall systems and the development of fastening elements, including the material structure of the elements and possible design and fastening methods. In the original university research, we also developed an applied technology for several product manufacturing companies in order to obtain approval for industrial application. In this article, we summarize the results of our research, the building structure and building physics issues, the necessary fastening technology design, and the main aspects of selecting stone tiles regardless of the manufacturing companies. The goal of our university research was the introduction and structural development of assembled stone facade cladding in Hungary, a development that continues to this day. The assembled stone cladding system we developed has been used to cover the facades of thousands of buildings in Hungary. Full article

The discovery of Asgard archaea has reshaped our understanding of eukaryotic origins, supporting a two-domain tree of life in which eukaryotes emerged from Archaea. Building on this revised framework, we propose the Pre-prokaryotic Organismal Lifeforms Existing Today (POLET) hypothesis, which suggests that relic pre-prokaryotic life forms—termed POLETicians—may persist in deep, anoxic, energy-limited environments. These organisms could represent a living bridge to the RNA world and other origin-of-life models, utilizing racemic oligoribonucleotides and peptides, non-enzymatic catalysis, and mineral-assisted compartmentalization. POLETicians might instead rely on radical-based redox chemistry or radiolysis for energy and maintenance. These biomolecules may be racemic or noncanonical, eluding conventional detection. New detection methods are required to determine such life. We propose generalized nanopore sequencing of any linear polymer—including mirror RNAs, mirror DNAs, or any novel genetic material—as a potential strategy to overcome chirality bias in modern sequencing technologies. These approaches, combined with chiral mass spectrometry and stereoisomer-resolved analytics, may enable the detection of molecular signatures from non-phylogenetic primitive lineages. POLETicians challenge the assumption that all life must follow familiar biochemical constraints and offer a compelling extension to our search for both ancient and extant forms of life hidden within Earth’s most extreme environments. Full article

Reinforced concrete is the most widely utilized building material for bridges, buildings, and other infrastructure components, and its longevity is significantly influenced by corrosion or rust. Corrosion shortens reinforced concrete’s service life and safety, which raises maintenance expenses. Concrete is a porous material that allows air and water to pass through, and corrosion begins when the air and water reach the steel. This study evaluated the mechanical and corrosion resistance properties of reinforced concrete containing recycled and supplemented cementitious materials. The results showed that mixtures containing fine glass aggregate, glass powder, slag, fly ash, or silica fume significantly improved the compressive, tensile, and flexural strengths, but the 10% slag mix, and 5% glass aggregate with 10% glass powder with 10% fly ash mix produced the best results overall. In addition, the mixture containing 15% fly ash produced the best result against corrosion. The corrosion tests revealed that mixtures with 10% slag and 20% glass powder also significantly enhanced the corrosion resistance of steel with the same results, confirming their effectiveness in reducing the permeability and increasing the durability of reinforced concrete. Full article

This study investigates the integration of Large Language Models (LLMs) into supply chain workflow automation, with a focus on their technical, operational, financial, and socio-technical implications. Building on Dynamic Capabilities Theory and Socio-Technical Systems Theory, the research explores how LLMs can enhance logistics operations, increase workflow efficiency, and support strategic agility within supply chain systems. Using two developed prototypes, the Q inventory management assistant and the nodeStream© workflow editor, the paper demonstrates the practical potential of GenAI-driven automation in streamlining complex supply chain activities. A detailed analysis of system architecture and data governance highlights critical implementation considerations, including model reliability, data preparation, and infrastructure integration. The financial feasibility of LLM-based solutions is assessed through cost analyses related to training, deployment, and maintenance. Furthermore, the study evaluates the human and organisational impacts of AI integration, identifying key challenges around workforce adaptation and responsible AI use. The paper culminates in a practical roadmap for deploying LLM technologies in logistics settings and offers strategic recommendations for future research and industry adoption. Full article

In recent years, solar energy has emerged as a pillar of sustainable development. However, maintaining panel efficiency under extreme environmental conditions remains a persistent hurdle. This study introduces an automated defect detection pipeline that leverages deep learning and computer vision to identify five standard anomaly classes: Non-Defective, Dust, Defective, Physical Damage, and Snow on photovoltaic surfaces. To build a robust foundation, a heterogeneous dataset of 8973 images was sourced from public repositories and standardized into a uniform labeling scheme. This dataset was then expanded through an aggressive augmentation strategy, including flips, rotations, zooms, and noise injections. A YOLOv11-based model was trained and fine-tuned using both fixed and adaptive learning rate schedules, achieving a mAP@0.5 of 85% and accuracy, recall, and F1-score above 95% when evaluated across diverse lighting and dust scenarios. The optimized model is integrated into an interactive dashboard that processes live camera streams, issues real-time alerts upon defect detection, and supports proactive maintenance scheduling. Comparative evaluations highlight the superiority of this approach over manual inspections and earlier YOLO versions in both precision and inference speed, making it well suited for deployment on edge devices. Automating visual inspection not only reduces labor costs and operational downtime but also enhances the longevity of solar installations. By offering a scalable solution for continuous monitoring, this work contributes to improving the reliability and cost-effectiveness of large-scale solar energy systems. Full article

Accurate prediction and management of the service life of buildings and structural components are crucial for ensuring durability and economic efficiency. This paper investigates both discrete- and continuous-time Markov chains as probabilistic models for representing deterioration processes of building structures. Transition probabilities, fundamental matrices, and absorption times are computed to quantify expected lifespans and degradation pathways. Numerical simulations illustrate how state probabilities evolve, inevitably converging toward structural failure in the absence of maintenance interventions. Additionally, this study explicitly addresses uncertainties inherent in lifecycle predictions through the application of fuzzy set theory. A fuzzy Markov chain model is formulated to represent imprecise deterioration states and transition probabilities, which validate the predictable yet uncertain progression of structural deterioration through graphical analyses and fuzzy simulations. The proposed methodology, including fuzzy modeling, provides building managers and engineers with a robust analytical framework to optimize maintenance scheduling, refurbishment planning, and resource allocation for sustainable lifecycle management under uncertainty. Full article

This study explores the potential of National Spatial Data Infrastructure (NSDI) to strengthen governance and policy processes in Pakistan. Drawing on the UNESCAP principles of good governance and the EGU policy cycle model, this research applies a dual-method approach combining thematic document analysis of 23 national policy frameworks and a stakeholder survey (n = 28). The results reveal that while many policies reference spatial data conceptually, critical components such as standardised datasets, spatial dashboards, and institutional coordination mechanisms remain underdeveloped. Spatial references are largely confined to early policy stages, with limited integration in evaluation and maintenance, thereby limiting adaptive governance. Conversely, survey findings reflect strong recognition of NSDI’s value across governance principles, policy integration, and spatial awareness dimensions. The composite endorsement score highlights institutional demand for geospatial tools, data standards, and capacity-building platforms. The study concludes that embedding NSDI within policy and planning systems can bridge critical governance gaps, enhance implementation fidelity, and support inter-agency coordination for long-term policy effectiveness. Full article

This study evaluates the viability of a specific hybrid renewable energy system (HRES) installation designed for a remote community as a case study in Cuba. The system integrates solar, wind, and biomass resources to address localised challenges of energy insecurity and environmental degradation. Rather than offering a generalised evaluation of HRES technologies, this work focuses on the performance, impacts, and viability of this particular configuration within its unique geographical, social, and technical context. Using life cycle assessment (LCA) and input–output modelling, the research assesses environmental and socioeconomic impacts. The proposed HRES reduces greenhouse gas emissions by 60% (from 1.14 to 0.47 kg CO₂eq/kWh) and fossil energy consumption by 50% compared to diesel-based systems. Socioeconomic analysis reveals that the system generates 40.3 full-time equivalent (FTE) jobs, with significant employment opportunities in operation and maintenance. However, initial investments primarily benefit foreign suppliers due to Cuba’s reliance on imported components. The study highlights the potential for local economic gains through workforce training and domestic manufacturing of renewable energy technologies. These findings underscore the importance of integrating multiple renewable sources to enhance energy resilience and sustainability in Cuba. Policymakers should prioritise strategies to incentivise local production and capacity building to maximise long-term benefits. Future research should explore scalability across diverse regions and investigate policy frameworks to support widespread adoption of HRES. This study provides valuable insights for advancing sustainable energy solutions in Cuba and similar contexts globally. Full article

Digital Twin (DTw) technology is a cornerstone of Industry 4.0, enabling real-time monitoring, predictive maintenance, and performance optimization across diverse industries. A key requirement for effective DTw implementation is high geometric fidelity—ensuring the digital model accurately represents the physical counterpart. Fidelity metrics provide a quantitative means to assess this alignment in terms of geometry, behavior, and performance. Among these, 3D shape descriptors play a central role in evaluating geometric fidelity, offering computational tools to measure shape similarity between physical and digital entities. This paper presents a comprehensive review of 3D shape descriptor methods and their applicability to geometric fidelity assessment in DTw systems. We introduce a structured taxonomy encompassing classical, structural, texture-based, and deep learning-based descriptors, and evaluate each in terms of transformation invariance, robustness to noise, computational efficiency, and suitability for various DTw applications. Building upon this analysis, we propose a conceptual fidelity metric that maps descriptor properties to the specific fidelity requirements of different application domains. This metric serves as a foundational framework for shape-based fidelity evaluation and supports the selection of appropriate descriptors based on system needs. Importantly, this work aligns with and contributes to the emerging ISO 30138 standardization initiative by offering a descriptor-driven approach to fidelity assessment. Through this integration of taxonomy, metric design, and standardization insight, this paper provides a roadmap for more consistent, scalable, and interoperable fidelity measurement in digital twin environments—particularly those demanding high precision and reliability. Full article

With the advancement of refined urban governance and the construction of high-quality public spaces, street furniture design and usage face multiple challenges, including insufficient public participation and a neglect of actual user experience. These issues highlight the urgent need to establish a scientifically grounded user evaluation framework to inform design practices. This study focuses on Yangzhou Ecological Science and Technology New Town and, drawing on field investigation, grounded theory, and the Delphi method, develops a street furniture design evaluation framework encompassing three core dimensions: planning and configuration, environmental coordination, and operational management. Building on this framework, the Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation method are employed to conduct a holistic assessment of the street furniture and to identify critical design deficiencies. The results demonstrate that the proposed framework effectively identifies the strengths and weaknesses of street furniture and provides robust support for formulating targeted optimization strategies. The results reveal significant variations in the perceived importance of design factors among different user groups. Residents primarily emphasize practicality and convenience in daily use. Tourists value aesthetic expression and cultural resonance, whereas government officials focus on construction standardization and maintenance efficiency. In terms of satisfaction, all three groups reported relatively low scores, with the ranking as follows: “planning and configuration” > “management and operations” > “environmental coordination.” Based on these findings, the study proposes targeted design guidelines for future practice. The evaluation framework has been adopted by local authorities, incorporated into official street furniture design guidelines, and implemented in pilot projects—demonstrating its practical applicability and value. This research contributes to the theoretical advancement of street furniture design and provides empirical and methodological support for applications in other emerging urban areas and new town developments. Full article

This study reviews the methods and materials used in industry and ship maintenance to remove rust, marine deposits and paint from ships. It also reviews how this waste is transferred and repurposed into useful materials. The notion of recycling in this field of application represents the reuse of the waste blend of the abrasive grit material along with the mineral residues, antifouling agents and coatings removed in meaningful applications. They are used in building construction materials, road construction blends, insulation surfaces, renewed composites and coatings. The main concern of the experts is the presence of heavy metals that limit the applications of the waste mixes. Therefore, a thorough characterization of the waste stream is paramount to ensure its safety and suitability for repurposing. Furthermore, the study investigates the potential for upcycling these waste materials into higher-value products, moving beyond simple reuse to create new economic opportunities. Ultimately, the goal is to convert a former waste stream into a valuable resource, aligning with circular economic principles. Full article

Railway transportation systems have high accuracy and high integrity demands for safe localization. In the future, railway signaling is expected to rely on onboard sensors like Global Navigation Satellite Systems (GNSSs) in order to reduce installation and maintenance costs. GNSS position determination can, however, be highly degraded because of the presence of multipath on the train and railway environment. This paper tackles the characterization of multipath in code measurements caused exclusively by the antenna installation and derives a conservative error model of the antenna-installation-induced multipath and noise. First, we isolate multipath and noise from other GNSS errors using the Code-Minus-Carrier method. Second, an overbounding error model is derived. The limitation of modeling with restricted set of real data typically found in practice is discussed and we review methods that ensure the independence of samples. A new approach that creates separate data sets is ultimately proposed to derive an overbounding sigma. The presented methodology is supported by real measurements collected in an open-sky railway scenario. The derived models can be used as a reference nominal error models to build the null hypothesis of fault detection algorithms that detects the presence of excessive multipath in dynamic scenarios or as a part of a total error budget consideration. Full article

As cities grow faster and food systems grow more fragile, architects and planners are increasingly challenged to design spaces that not only house people but also support environmental and social well-being. This study investigates how vertical farming can be integrated into residential building facades in Egypt as a strategy to promote local food production and sustainable design. Focusing on a government housing project in Port Said, three façade-based design options were developed and assessed through structured surveys targeting two stakeholder groups: experts and residents. This research revealed a strong interest and awareness across both samples. While users prioritized benefits such as esthetics, air quality, and the ease of use, experts emphasized feasibility concerns, maintenance needs, and policy barriers. Both groups favored the second design option as the most balanced and applicable solution. By foregrounding stakeholder input, this study fills a gap in the existing literature on building-integrated agriculture and provides design and policy recommendations grounded in the local context. It advocates for inclusive design thinking, where technical viability and community values are considered together. While limited to single case and visual assessment methods, this research offers a foundation for further applied studies and broader sustainable design frameworks. Full article

Periphytic algae, as representative aquatic epiphytic communities, play a vital role in the material cycling and energy flow in rivers. Through physiological processes such as photosynthetic carbon fixation and nutrient absorption, they perform essential ecological functions in water self-purification, maintenance of primary productivity, and microhabitat formation. This study investigates the interaction mechanisms between these highly flexible organisms and the hydrodynamic environment, thereby addressing the limitations of traditional hydraulic theories developed for rigid vegetation. By incorporating the coupled effects of biological flexibility and water flow, an innovative nonlinear resistance model with velocity-dependent response is developed. Building upon this model, a coupled governing equation that integrates water flow dynamics, periphytic algae morphology, and layered Reynolds stress is formulated. An analytical solution for the vertical velocity distribution is subsequently derived using analytical methods. Through Particle Image Velocimetry (PIV) measurements conducted under varying flow velocity conditions in an experimental tank, followed by comprehensive error analysis, the accuracy and applicability of the model were verified. The results demonstrate strong agreement between predicted and measured values, with the coefficient of determination R² greater than 0.94, thereby highlighting the model’s predictive capacity in capturing flow velocity distributions influenced by periphytic algae. The findings provide theoretical support for advancing the understanding of ecological hydrodynamics and establish mechanical and theoretical foundations for river water environment management and vegetation restoration. Future research will build upon the established nonlinear resistance model to investigate the dynamic coupling mechanisms between multi-species periphytic algae communities and turbulence-induced pulsations, aiming to enhance the predictive modelling of biotic–hydrodynamic feedback processes in aquatic ecosystems. Full article