Search Results (608)

This research investigates the integration of green cores as central biophilic elements in residential architecture, proposing a climate-responsive design methodology grounded in architectural optimization. The study begins with the full-scale refurbishment of a compact urban apartment, wherein interior partitions, fenestration and material systems were reconfigured to embed vegetated zones within the architectural core. Light exposure, ventilation potential and spatial coherence were maximized through data-driven design strategies and structural modifications. Integrated planting modules equipped with PAR-specific LED systems ensure sustained vegetation growth, while embedded environmental infrastructure supports automated irrigation and continuous microclimate monitoring. This plant-centered spatial model is evaluated using quantifiable performance metrics, establishing a replicable framework for optimized indoor ecosystems. Photosynthetically active radiation (PAR)-specific LED systems and embedded environmental infrastructure were incorporated to maintain vegetation viability and enable microclimate regulation. A programmable irrigation system linked to environmental sensors allows automated resource management, ensuring efficient plant sustenance. The configuration is assessed using measurable indicators such as daylight factor, solar exposure, passive thermal behavior and similar elements. Additionally, a post-occupancy expert assessment was conducted with several architects evaluating different aspects confirming the architectural and spatial improvements achieved through the refurbishment. This study not only demonstrates a viable architectural prototype but also opens future avenues for the development of metabolically active buildings, integration with decentralized energy and water systems, and the computational optimization of living infrastructure across varying climatic zones. Full article

This study presents a comprehensive dataset developed to monitor coastal water quality in the south-central region of Vietnam, focusing on Nha Trang Bay. Environmental data were collected from four research cruises conducted between 2013 and 2024. Water samples were taken at two depths: surface samples at approximately 0.5–1.0 m below the water surface, and bottom samples 1.0 to 2.0 m above the seabed, depending on site-specific bathymetry. These samples were analyzed for key water quality parameters, including biological oxygen demand (BOD₅), dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus (DIP), and Chlorophyll-a (Chl-a). The data establish a valuable baseline for assessing both spatial and temporal patterns of water quality, and for calculating eutrophication index to evaluate potential environmental degradation. Importantly, it also demonstrates practical applications for environmental management. The dataset can support assessments of how seasonal tourism peaks contribute to nutrient enrichment, how aquaculture expansion affects dissolved oxygen dynamics, and how water quality trends evolve under increasing anthropogenic pressure. These applications make it a useful resource for evaluating pollution control efforts and for guiding sustainable development in coastal areas. By promoting open access, the dataset not only supports scientific research but also strengthens evidence-based management strategies to protect ecosystem health and socio-economic resilience in Nha Trang Bay. Full article

The integrated assessment of watershed ecosystems is increasingly critical for sustainable water resource management amid global environmental change. Multi-source data integration—encompassing in situ monitoring, remote sensing, and model-based observations—has significantly expanded the spatial and temporal scales at which watershed processes can be analyzed. Concurrently, advances in model coupling strategies, ranging from loose to embedded architectures, have enabled more dynamic and holistic representations of interactions among hydrology, water quality, and ecological systems. However, a unifying operational framework that links multi-source data, cross-scale coupling, and rigorous uncertainty propagation to actionable, real-time decision support is still missing, largely due to gaps in interoperability and stakeholder engagement. Addressing these limitations demands the development of intelligent, adaptive modeling frameworks that leverage hybrid physics-informed machine learning, cross-scale process integration, and continuous real-time data assimilation. Open science practices and transparent model governance are essential for ensuring reproducibility, stakeholder trust, and policy relevance. The recent literature indicates that loose coupling predominates, physics-informed ML tends to generalize better in data-sparse settings, and uncertainty communication remains uneven. Building on these insights, this review synthesizes methods for data harmonization and cross-scale integration, compares coupling architectures and data assimilation schemes, evaluates uncertainty and interoperability practices, and introduces the Smart Integrated Watershed Eco-Assessment Framework (SIWEAF) to support adaptive, real-time, stakeholder-centered decision-making. Full article

As an integrated socio-technical system linking information technology with industrial infrastructure, the Industrial Internet is increasingly central to urban digital transformation. However, current research largely centers on national or sectoral scales, lacking systematic analysis at the city level—particularly regarding system structure, enabling mechanisms, and region-specific pathways. This study takes Dalian, a city with a strong industrial base and urgent digital transformation needs, leveraging the Industrial Internet Development Index (IIDI), employing a “system structure–mechanism–pathway” analytical framework, we conducted a comprehensive assessment of the spatiotemporal relationship between industrial structure and Industrial Internet performance in Dalian from 2020 to 2022. The study finds that, during the research period, Dalian’s Composite IIDI increased from 0.31 to 0.65, with substantial improvements in platform infrastructure, resource coordination, and data application capacity—providing key support for enterprise digitalization and intelligent consumption. A strong correlation (R² = 0.85) between industrial structure and Industrial Internet performance underscores the structural foundation’s critical role. However, comparative analysis reveals that Dalian still faces structural deficiencies in platform openness, international interface integration, and ecosystem synergy. The study introduces a systemic pathway for empowering Industrial Internet capabilities and offers actionable insights for policymakers seeking to foster regionally adapted digital transformation. Full article

Fish stocks and their management are paramount for sustainable fisheries under the ongoing changes in atmosphere–sea interactions. The Aegean Sea, one of the composite seas influenced by different water masses, is characterized by a diverse ecosystem. Small pelagic fish are abundant and tend to form schools that vary in size. One of the most efficient and rapid techniques for sampling fish schools over a large area is the use of acoustic methods. Therefore, an acoustic survey was conducted in the coastal areas along the entire Turkish Aegean waters between June and August 2024, using a scientific quantitative echosounder equipped with a split-beam transducer operating at 206 kHz. During the survey, environmental parameters, including water physics, optics, and bathymetry, were measured at 321 stations. Additionally, satellite data were used to obtain water primary production levels for each sampling month across the entire study area. Using a custom computer algorithm written during the present study in MATLAB (2021a), fish schools were automatically detected to measure various morphological and acoustic features. Through a series of statistical analyses, three optimal clusters, validated with the total silhouette sum of distances (1317.38), were identified, each characterized by specific morphological, acoustic, and environmental variables associated with different areas of the study. School morphology and acoustic properties also varied with bottom depth. Cluster 1 was mostly found in open and relatively deep waters. Cluster 2 appeared in areas impacted by anthropogenic sources. Principal Component Analysis (PCA) revealed that the first component (PCA1) was correlated with school height from the bottom (HFB) and overall school height (SH), followed by minimum depth (MnD), maximum depth (MxD), and volume backscattering strength at the school edge (SvE). The second component (PCA2) was associated with school width (SW) and area (A). Cluster 1 was characterized by schools with large SW and A, and relatively high HFB and SH. Cluster 2 showed low HFB and SH, while Cluster 3 had high MnD and MxD and low SvE. Based on the descriptors for these clusters, each cluster could be attributed to fish species at different life stages inferred based on target strength (TS), namely sardine, horse mackerel, and chub mackerel, distributed along the entire Turkish Aegean coast. Full article

Delegation of authority remains a critical yet insufficiently addressed capability in Self-Sovereign Identity (SSI) systems. Building on an existing delegation model that introduced the concept of a Verifiable Mandate (VM) for expressing authority and access rights, this paper extends the approach with a rigorous formalization of delegation semantics, enabling unambiguous reasoning over roles, grants, and constraints. The formal model is aligned with standards from the World Wide Web Consortium (W3C), and its constructs are embedded into an extended credential schema that preserves compatibility with the Verifiable Credentials (VC) data model while introducing delegation-specific attributes. A generalized VM schema is defined, supporting both generic and business-specific instantiations, and ensuring structural and semantic interoperability. Policy compliance is operationalized through a policy-based enforcement architecture, where rules are authored in the Rego language and evaluated at runtime by the Open Policy Agent (OPA). The architecture incorporates trusted registries for schema and policy distribution, allowing verifiers to define and enforce context-specific delegation rules in a modular and interoperable manner. Validation through realistic scenarios, such as postal service and academic use cases, demonstrates how formal semantics, schema validation, and language-based policy enforcement can be combined to enable secure, verifiable, and context-aware delegation in SSI ecosystems. Full article

The accurate prediction of atmospheric low-visibility events due to fog, haze or atmospheric pollution is an extremely important problem, with major consequences for transportation systems, and with alternative applications in agriculture, forest ecology and ecosystems management. In this paper, we provide a comprehensive literature review and analysis of AI-based methods applied to fog and low-visibility events forecasting. We also discuss the main general issues which arise when dealing with AI-based techniques in this kind of problem, open research questions, novel AI approaches and data sources which can be exploited. Finally, the most important new AI-based methodologies which can improve atmospheric visibility forecasting are also revised, including computational experiments on the application of ordinal classification approaches to a problem of low-visibility events prediction in two Spanish airports from METAR data. Full article

Interoperability between Building Information Modeling (BIM) and Facility Management (FM) depends on open, vendor-neutral standards. Yet, operational uptake remains constrained by fragmented workflows, incompatible schemas, and non-standardized delivery. This critical review synthesizes OpenBIM pathways—within the buildingSMART ecosystem (Industry Foundation Classes (IFC), Construction–Operations Building information exchange (COBie), Information Delivery Specification (IDS) v1.0, buildingSMART Data Dictionary (bSDD)) and the Level of Information Need (ISO 7817-1:2024)—across technical, managerial, and strategic dimensions. We searched major databases and used guided snowballing to screen a core corpus. Technically, persistent semantic inconsistencies and limited real-time, bidirectional exchange remain; open standards enable machine-checkable deliverables and API-friendly serializations. Managerially, weak Organizational Information Requirements (OIR) → Asset Information Requirements (AIR) → Exchange Information Requirements (EIR) alignment and unclear acceptance criteria undermine FM readiness. Strategically, procurement and risk management should mitigate vendor lock-in. We highlight gaps in FM ontologies and BIM–IoT synchronization and outline an agenda for Digital Twins, automation, and verifiable FM data quality within OpenBIM ecosystems. Full article

The rapid evolution of the metaverse is driving the development of new digital design tools that integrate Computer-Aided Design (CAD) and Building Information Modeling (BIM) technologies. Core technologies such as Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) are increasingly combined with BIM to enhance collaboration and innovation in design and construction workflows. However, current BIM–VR integration often remains limited to isolated tasks, lacking persistent, multi-user environments that support continuous project collaboration. This study proposes a BIM-based Virtual World (VW) framework that addresses these limitations by creating an immersive, real-time collaborative platform for the Architecture, Engineering, and Construction (AEC) industry. The system enables multi-user access to BIM data through avatars, supports direct interaction with 3D models and associated metadata, and maintains a persistent virtual environment that evolves alongside project development. Key functionalities include interactive design controls, real-time decision-making support, and integrated training capabilities. A prototype was developed using Unreal Engine and supporting technologies to validate the approach. The results demonstrate improved interdisciplinary collaboration, reduced information loss during design iteration, and enhanced stakeholder engagement. This research highlights the potential of BIM-based Virtual Worlds to transform AEC collaboration by fostering an open, scalable ecosystem that bridges immersive environments with data-driven design and construction processes. Full article

Atmospheric aerosols significantly influence photosynthetically active radiation (PAR), critical for plant photosynthesis and ecosystem functioning. This study systematically reviewed recent research (2021–2025) on aerosol–PAR interactions. Using targeted keywords, 22 open-access articles from Scopus and Google Scholar were analyzed via VOSviewer for thematic, methodological, and geographic trends. Analysis revealed a strong concentration in Earth and Environmental Sciences, showcasing significant advances in radiative transfer modeling, remote sensing, and machine learning for estimating aerosol impacts on PAR. Studies primarily utilized satellite data and models (e.g., DART, SCOPE) to assess diffuse/direct radiation changes. The literature consistently demonstrates how aerosols modulate PAR, influencing canopy light penetration and photosynthetic efficiency. However, critical gaps persist, including limited field validation in tropical biomes (e.g., Amazon, Cerrado, Pantanal) and a lack of studies differentiating aerosol types like black and brown carbon. This synthesis underscores the need for expanded monitoring and integrated modeling efforts to improve understanding of aerosol–PAR interactions, particularly in underrepresented tropical regions. Full article

The increasing demand for decentralized and user-controlled cryptographic key management in blockchain ecosystems has created interest in alternative entropy sources that do not rely on dedicated hardware. This study investigates whether commercial smartwatches can generate sufficient entropy for secure local key generation by utilizing their onboard sensors. An open-source Wear OS application was developed to harvest sensor data in two acquisition modes: still mode, where the device remains stationary, and shake mode, where data collection is triggered by motion events exceeding a predefined acceleration threshold. A total of 4800 still-mode and 4800 shake-mode samples were collected, each producing 11,400 bits of sensor-generated data. Entropy was evaluated using statistical metrics commonly employed in entropy analysis, including Shannon entropy, min-entropy, Markov dependency analysis, and compression-based redundancy estimation. The shake mode achieved Shannon entropy of 0.997 and min-entropy of 0.918, outperforming the still mode (0.991 and 0.851, respectively) and approaching the entropy levels of software-based random number generators. These results demonstrate that smartwatches can act as practical entropy sources for cryptographic applications, provided that appropriate post-processing, such as cryptographic hashing, is applied. The method offers a low-cost, transparent, and user-friendly alternative to specialized hardware wallets, aligning with the principles of decentralization and self-sovereign identity. Full article

In the era of digital–real integration, open-source collaboration has become a strategic pathway for accelerating the innovation catch-up of China’s industrial software. This study employs an exploratory multi-case design, focusing on the China Automotive Operating System open-source project and the FastCAE open-source domestic CAE software integrated development platform to examine how open-source strategies shape collaborative mechanisms and innovation outcomes. The analysis reveals that firms adopt both formal (behavioral and outcome coordination) and informal (relationship and empowerment coordination) strategies, fostering high-level complementary collaboration in data, technology, institution, and human resources. These mechanisms significantly enhance R&D efficiency and quality, drive technological innovation, and create new market innovation, thereby improving collaborative performance. The study contributes to theory by linking open-source-driven digital–real integration with industrial software innovation catch-up and offers practical governance recommendations for strengthening China’s industrial software autonomy and ecosystem sustainability. Full article

Algal blooms are ecological phenomena with long-lasting effects on the ecosystem and on the climate. Often, they reduce the oxygen level underwater, creating adverse circumstances for aquatic species’ survival, development, and reproduction. In this article, the mapping of algal bloom incidents and their daily monitoring is automated using Python script and the Earthdata website. The automation is carried out in eight separate modules and then integrated. Test site dictionary, configuration, query data, download MODIS data, open image data, clip data, implementing a novel Normalized Difference MODIS Algae Index (NDMAI), and threshold are the eight modules used for automating the extraction and daily monitoring. This automation requires two inputs: firstly, the bounding box, i.e., lower left coordinate (LLC) and upper right coordinate (URC) of the test site, and secondly, the date range. In this article, eight test sites are used to extract algal bloom incidents, and a ninth test site is used for the extraction and daily monitoring, which are reported by the NASA Earth Observatory (NEO). The proposed framework automates the process of enhancing algal bloom features in MODIS imagery, and daily monitoring is successfully accomplished, and the results perfectly match the algal bloom region in the test sites reported by the NEO. Full article

This work draws on the principles of Environmental Education as a framework for designing meaningful teaching interventions that foster a critical understanding of socio-environmental issues. The proposal focuses on the specific case of plastic pollution and its impact on marine ecosystems, adopting an integrative perspective that connects animal, environmental, and human health. To this end, the One Health approach is incorporated, highlighting the close interdependence between the health of ecosystems, animals, and people, which allows the issue to be analyzed from a systemic and global perspective. The intervention is grounded in the principles of Transformative Environmental Education—a pedagogical orientation that seeks to promote deep changes in how students understand their environment and engage with the challenges of today’s world. This approach encourages ethical reflection, critical thinking, and the ability to imagine sustainable futures, as well as the development of competencies for action and civic engagement. The teaching proposal takes the form of a learning experience designed and implemented in three 7th-grade classrooms (1º ESO) in Cádiz, Spain, through a mixed-methods approach with 79 students (12–13 years old), structured around an escape box activity. This is a variation of the escape room format in which students, working in teams, must open a series of boxes by solving a sequence of puzzles. In this case, the escape box is set in a marine context. Through a gamified narrative, students receive a suitcase containing objects, clues, and materials that require the application of scientific knowledge about ocean acidification, biodiversity loss, and types of plastics. Data were collected through field notes, student artifacts, and a final questionnaire. The proposal is designed to foster critical environmental literacy, a holistic vision of environmental challenges, and the capacity to propose collective solutions from a One Health perspective. The results revealed high levels of motivation, engagement with the storyline, and a solid understanding of the link between marine plastic pollution and its effects on animal and human health, aligned with the One Health perspective. Full article

The Euphrates–Tigris Basin is experiencing significant environmental transformations due to climate change, Land Use and Land Cover Change (LULCC), and anthropogenic pressures. This study employs Earth Map, an open-access remote sensing platform, to comprehensively assess climate trends, vegetation dynamics, water resource variability, and land degradation across the basin. Key findings reveal a geographic shift toward aridity, with declining precipitation in high-altitude headwater regions and rising temperatures exacerbating water scarcity. While cropland expansion and localized improvements in land productivity were observed, large areas—particularly in hyperarid and steppe zones—show early signs of degradation, increasing the risk of dust source expansion. LULCC analysis highlights substantial wetland loss, irreversible urban growth, and agricultural encroachment into fragile ecosystems, with Iraq experiencing the most pronounced transformations. Climate projections under the SSP245 and SSP585 scenarios indicate intensified warming and aridity, threatening hydrological stability. This study underscores the urgent need for integrated water management, Land Degradation Neutrality (LDN), and climate-resilient policies to safeguard the basin’s ecological and socioeconomic resilience. Earth Map is a vital tool for monitoring environmental changes, offering rapid insights for policymakers and stakeholders in this data-scarce region. Future research should include higher-resolution datasets and localized socioeconomic data to improve adaptive strategies. Full article