Search Results (481)

For offshore renewable energy planning and intelligent power management, access to long-term, high-resolution, and physically consistent meteorological and power generation records is essential. Such data supports a wide range of tasks, including resource assessment, hybrid system capacity sizing, grid operation planning, and data-driven forecasting model development. This article presents the construction of a 10-year continuous hourly dataset for 16 deep-sea grid sites in the Beibu Gulf, China, spanning from January 2016 to December 2025. The raw meteorological variables, including 10 m wind speed, wind direction, solar irradiance, and 2 m air temperature, were retrieved from the NASA POWER satellite database and subsequently cleaned using a 24 h periodic substitution algorithm designed to preserve the physical integrity of daily weather cycles. The dataset is organized into two sub-datasets, the Historical Weather Dataset and the Normalized Power Yield Dataset, with the latter providing normalized wind and solar power outputs on a 1.0 per-unit (p.u.) basis derived from a wind turbine power curve model and a PV thermodynamic model. All 32 CSV files are freely accessible online with UTF-8 encoding. The utility of the dataset is illustrated through two representative application cases including offshore site selection with hybrid capacity sizing and physics-informed deep learning forecasting, demonstrating its suitability for both engineering analysis and machine learning model development. Full article

The accessibility of flying drones (unmanned aerial vehicles) presents reproducible and cost-effective methods to monitor submerged aquatic vegetation. In particular, drone-borne topobathymetric LiDAR provides high-resolution (cm-scale), three-dimensional information about the geometry and structure of surveyed areas, allowing for quantification of vegetation volume in addition to bathymetry. For seagrasses, this information can advance research regarding the structure of canopies in relation to blue carbon storage and biodiversity. Here, we demonstrate how drone-borne LiDAR can be used to estimate the habitat volume of eelgrass (Zostera marina) within a sheltered bay in Norway. After classifying LiDAR points using a Random Forest model, we created a Digital Terrain Model of the sea floor and a Digital Surface Model of the eelgrass canopy. From these models, we showed that eelgrass canopy volume can be estimated (between 862 and 1099 m³ across the small study area) and the above-ground carbon stock in living tissue can be quantified (between 96 and 122 kg C). To our knowledge, this is the first study to utilise drone-borne LiDAR to quantify the habitat volume and carbon-storage potential of a marine habitat-forming species like eelgrass, demonstrating a novel methodology for providing reproducible and high-resolution data of submerged aquatic habitats. Full article

Coastal beach–dune systems along the Western Black Sea Coast represent geomorphologically complex and ecologically valuable environments that have been increasingly affected by long-term urbanisation and recreational pressure. This study examines the geomorphological settings, sedimentary connectivity and associated Natura 2000 dune habitats within two urbanised beach–dune systems, Pobeda (Burgas) and Asparuhovo (Varna), to improve their cadastral documentation and support objective conservation assessment. The analysis is based on high-resolution UAS-LiDAR surveys, complemented by UAS photogrammetry and field observations, allowing detailed three-dimensional characterisation of dune landforms, surface morphology and habitat patterns. The results identify foredune-dominated system architectures in both study areas, with the Pobeda (Burgas) and Asparuhovo (Varna) beach–dune systems comprising embryonic dunes, established foredune ridges and low-relief foredune plains, variably developed and spatially fragmented as a result of long-term urbanisation and recreational pressure, and spatially associated with dune habitats. Despite substantial anthropogenic modification, these elements remain recognisable, although locally fragmented and morphologically degraded. Subtle topographic changes related to trampling, informal access routes and surface compaction were detected, particularly affecting foredune crests and foredune plains, with implications for sediment transport continuity and habitat stability. The study shows that conventional habitat inventories alone are insufficient for capturing such changes. Integrated geomorphological and habitat analysis based on UAS-LiDAR provides a reliable framework for accurate mapping, conservation status assessment and informed consideration of coastal dune systems within the Natura 2000 network and related protection schemes. Full article

With the deployment and application of the Fifth-Generation (5G) mobile communication technologies and the ongoing research and development of the Sixth-Generation (6G) mobile communication technologies, the space–air–ground–sea integrated network has become the core development vision for future communications. As aerial nodes, Unmanned Aerial Vehicles (UAVs) can be applied in a wide range of scenarios, including emergency rescue, surveying and mapping, environmental monitoring, and communication coverage enhancement. In terms of communication coverage enhancement, the space–air–ground integrated network, with UAVs as a key component, can provide seamless communication coverage for the full-domain three-dimensional space such as remote areas, deserts, and oceans. Benefiting from advantages such as low cost and high flexibility, UAVs have become a critical research focus, and the one-hop Base Station (BS)–relay UAV–slave UAV architecture for communication coverage enhancement has emerged as an important development direction. However, the high mobility and wide coverage characteristics of UAVs also pose significant synchronization challenges. Aiming at the uplink synchronization problem on the sidelink between slave UAVs and the relay UAV, a two-step random-access scheme based on Asynchronous Non-Orthogonal Multiple Access (A-NOMA) is designed to mitigate the Doppler Frequency Offset (DFO), improve access efficiency, reduce resource consumption, and accommodate the asynchrony among different users. This scheme leverages the existing preamble sequences of the Physical Random Access Channel (PRACH) and realizes DFO estimation in combination with the pairing index. On this basis, a Successive Interference Cancellation (SIC) algorithm based on DFO and phase compensation is designed to complete the demodulation of user data. For the downlink synchronization problem on the sidelink between slave UAVs and the relay UAV, the frequency offset estimation performance is improved by redesigning the resource allocation scheme of the Sidelink Synchronization Signal Block (S-SSB). Meanwhile, considering the energy constraint of UAVs, a downsampling-based detection scheme is designed to reduce UAV power consumption, and a full-link algorithm is developed to support the practical implementation of the proposed scheme. Full article

The exploration of deep-sea microorganisms is transitioning from ex situ laboratory analysis to in situ real-time monitoring. While in situ technologies offer unprecedented access to microbial activities in their natural extreme habitats, they face a critical, yet often overlooked, bottleneck: the absence of a robust metrological framework. This lack of standardized calibration, traceability, and reference materials results in data that are often irreproducible, device-specific, and incomparable across studies, severely undermining scientific discovery and resource assessment. This review provides a systematic analysis of the current landscape of deep-sea microbial detection technologies, categorizing them by their operational principles and critically evaluating their performance, limitations, and metrological readiness. By synthesizing the technological challenges with the principles of metrology, we identify the fundamental gap between advanced sensing capabilities and the lack of in situ measurement standards. To bridge this gap, we propose an innovative “laboratory simulation–in situ detection–remote calibration” trinity calibration system. This framework establishes a complete metrological traceability chain tailored for extreme deep-sea conditions, aiming to transform isolated sensor data into globally comparable, scientifically robust, and industrially actionable information, thereby paving the way for precision deep-sea biology and governance. Full article

Viruses are abundant and widespread in extreme marine environments, such as sea ice, hydrothermal vents, and ocean trenches. They occur at temperatures up to 122 °C and down to −30 °C and pressures exceeding 100 MPa. Their distribution in these environments is closely correlated with that of their extremophile hosts, which are mostly bacteria, archaea, and microeukaryotes. Viruses have been shown to be capable of long-term survival in conditions simulating interstellar conditions. However, for them to reproduce, they would still need a host. Many recent astro-biological investigations have focused on habitability, specifically the ability of a planet to support the activity of at least one lifeform. The most likely candidates for extraterrestrial habitability in our solar system are the sea ice moons of Jupiter and Saturn, namely Europa and Enceladus. These are both thought to contain subsurface oceans of liquid water and potentially access to the necessary elements for microbial growth. If microorganisms were to be detected in these extraterrestrial environments, viruses might also be found coexisting with their host cells. Full article

In late Ming China, landscape (shanshui 山水) painting could function not only as a scenic representation but also as a pictorial means of making sacred space perceptible. This article examines Wu Bin’s hanging scroll Fanghu Tu 方壺圖 (1626; Palace Museum, Beijing) and asks how the painting renders Daoist sacred space visible through relations of distance, access, concealment, and uneven disclosure. To avoid treating “Daoist aesthetics” as a general label, the analysis uses schema and pictorial organization as limited descriptive terms for the structuring of spatial experience within the image. The close reading identifies two recurrent pictorial formations brought into relation in Fanghu Tu: a sea-boundary, distant-view configuration that emphasizes separation and delay, and a pavilion-centered enclosure that produces a more concentrated middle field. It then shows how layered waves and broken shoreline, cloud and mist, middle-zone enclosure, and the thinning legibility of the upper peaks prevent the scene from stabilizing into a single resolved destination. Read in relation to late Ming discussions of cultivated “strangeness” (qi 奇) in landscape painting, these features suggest that Daoist sacred space in Fanghu Tu takes shape as an uneven and mediated experience, structured through provisional concentration, interrupted visibility, and renewed distance. The article argues that late Ming landscape painting could render Daoist-inflected sacred spatial experience visible not only through iconography, but also through the pictorial distribution of visibility, access, and reorientation. Full article

Intelligent vessel navigation increasingly demands high-density bathymetric data. To resolve the limitations of traditional standards and overcome existing management bottlenecks, this study proposes a novel methodology for high-density bathymetric data modeling and system construction integrated with the S-100 framework. Centered on the International Hydrographic Organization (IHO) S-102 standard, this methodology pioneers a strongly correlated management paradigm for datasets, data, and metadata. Leveraging a relational database architecture and a three-level indexing mechanism, it enables the structured organization and efficient retrieval of data throughout its entire life cycle. At the data production stage, geometric feature constraints based on convex hulls are innovatively incorporated to facilitate the interpolation of high-density water depth data and the generation of grid arrays. A data organization and structured storage model based on the three-tier logical architecture of the Hierarchical Data Format version 5 (HDF5) is proposed, which couples the technologies of block-based storage and refined version control to achieve the synergistic optimization of storage costs and access efficiency for high-density water depth data. Validation via field measurements in selected sea areas of the East China Sea demonstrated that the generated S-102 bathymetric data complied with international specifications and achieved excellent terrain restoration accuracy. Meanwhile, the proposed HDF5-based storage strategy achieves a storage space reduction of 83.6%. This research provides authoritative and efficient data support for scenarios such as intelligent navigation and port digitalization, and contributes to the construction of an intelligent shipping ecosystem. Full article

Sea-surface reflections and wind–wave motion render maritime channels strongly time-varying and statistically non-stationary, while nearshore deployments face sparse infrastructure and co-channel multiuser interference. This study integrates reconfigurable intelligent surfaces (RISs) with rate-splitting multiple access (RSMA) for joint online resource allocation. A physics-inspired time-varying channel model is established by embedding fractional Brownian motion-driven slow statistical drift and reflection-phase perturbations. With imperfect, delayed channel state information (CSI) and discrete RIS phase quantization, a proportional-fairness utility maximization problem is formulated to jointly optimize shore base-station precoding, RIS phase shifts, and RSMA common-rate allocation. To cope with strong non-convexity, high dimensionality, mixed continuous–discrete coupling, and partial observability, a fractal-aware recurrent robust Actor–Critic (FRRAC) algorithm is developed. FRRAC encodes short observation histories using a gated recurrent unit and incorporates a lightweight Hurst-proxy estimator to capture slow channel statistics for robust value evaluation and policy learning. Truncated quantile critics and mixed prioritized–uniform replay further improve value robustness, training stability, and sample efficiency. Simulation results show that FRRAC converges faster and more stably under both conventional and fractal non-stationary channel modeling, and outperforms representative baselines across the objective and multiple statistical metrics, validating its effectiveness for joint resource optimization in maritime RIS–RSMA systems. Full article

Coastal cities are complex spatial systems shaped by intertwined economic, environmental, demographic, and governance pressures. This study develops a multidimensional comparative framework to analyze coastal cities in the Black Sea basin across five dimensions: physical–morphological structure, demographic scale, economic–functional profile, transportation and accessibility, and urban quality–governance. To address cross-country data heterogeneity, an ordinal (0–1–2) indicator system is employed and analyzed through multiple multivariate techniques, including Gower dissimilarity, NMDS, Ward hierarchical clustering, MCA, Spearman rank correlation, network analysis, and rank-transformed PCA. Findings indicate that Black Sea coastal cities do not form a single homogeneous typology but cluster around distinct structural patterns. A major axis of differentiation separates port–industrial production-oriented cities from tourism–service-oriented cities, while a considerable group of multifunctional and transitional cities exhibits moderate values across several dimensions. Results show that city typologies are shaped less by national planning regimes than by structural dynamics such as port scale, economic specialization, accessibility, and spatial pressure. By integrating non-metric and metric approaches, the study proposes a context-sensitive and multi-criteria comparative methodology. The findings highlight the need for multi-scalar and multidimensional planning perspectives to better understand structural differentiation in coastal urban systems within semi-enclosed marine regions such as the Black Sea. Full article

Unmanned Aerial Vehicle (UAV)-assisted mobile edge computing is pivotal for the Space–Air–Ground–Sea Integrated Network (SAGSIN) to support heterogeneous task offloading. However, the inherent resource constraints of UAVs limit their ability to support intensive and concurrent task processing in dynamic environments. In such complex scenarios, the dual requirements of discrete model partitioning and continuous bandwidth allocation make it difficult for traditional reinforcement learning algorithms to achieve optimal resource matching. Therefore, in this paper, we design a joint optimization framework based on Asynchronous Advantage Actor-Critic (A3C) and proximal policy optimization (PPO). Specifically, the model partitioning strategy is learned through PPO, which utilizes a clipped objective function to ensure training stability and generalization across complex Deep Neural Network (DNN) structures. Moreover, the framework leverages the asynchronous multi-threaded architecture of A3C to dynamically allocate bandwidth, effectively accommodating rapid fluctuations in terminal access. Finally, to prevent resource monopolization and ensure fairness, a weighted priority scheduling mechanism based on task urgency and computation time is introduced. Extensive simulations show that the proposed algorithm outperforms existing approaches in terms of task completion rate, task processing latency, and resource utilization under dynamic SAGSIN scenarios. Full article

Background: Quilombola communities, Afro-descendant Brazilian rural settlements with collectivistic culture, have suffered historical invasions and non-legalization of their territories, exposure to environmental degradation/hazards, and educational and health care deprivation by the government. Global climate changes have increased sea levels and the occurrence of floods. This study presents original empirical findings from ongoing qualitative fieldwork in Quilombola communities in Southern Brazil that were severely affected by the 2024 floods, focusing on post-disaster quality of life, health impacts, and community coping strategies. These dimensions remain underexamined in public health and environmental justice research. Methods: Guided by interdisciplinary frameworks of environmental racism, intersectionality, and critical disaster studies, flooding is analyzed not as a natural hazard, but as a socially produced risk shaped by racialized territorial exclusion, historical marginalization, and chronic governance failures. Data were generated by household testimonies, community observations, and assessments of governmental disaster responses. Results: Fragmented disaster management, unequal access to infrastructure, and limited participatory governance mechanisms intensified vulnerability, constrained adaptive capacity, and exacerbated health inequities among Quilombola populations. Despite these constraints, communities demonstrated strong resilience grounded in traditional knowledge, local solidarity networks, and collective agency. Conclusions: The study underscores the urgent need for equity-centered environmental governance and inclusive disaster risk reduction strategies to address healthy aging inequities. Full article

Public transport systems in rapidly urbanizing Gulf cities confront the simultaneous challenge of decreasing emissions while guaranteeing equal access for riders, many of whom rely on transit for economic reasons. Sustainable smart city development necessitates bus services that are both efficient and sensitive to rider needs in adverse weather conditions. This study develops and evaluates a wellbeing-focused planning framework for Dubai’s bus network, filling gaps in prior research that primarily focuses on temperate, choice-based transport environments. The study uses Generalized Structured Component Analysis (GSCA) to analyze how Service Efficiency and Accessibility (SEA), Physical Environment and Passenger Comfort (PEPC), and Service Operations and Assurance (SOA) impact overall journey wellbeing, based on a cross-sectional survey of 491 riders collected from July–August 2024. Data were collected during peak summer conditions, and the analysis followed a structured workflow that operationalized the proposed constructs into measurable indicators and estimated both the measurement and structural components of the GSCA model to find planning relevant wellbeing drivers. The model shows a strong fit (FIT = 0.684; GFI = 0.991; SRMR = 0.056), with SEA (β = 0.504) having the greatest influence on wellbeing, followed by SOA (β = 0.344) and PEPC (β = 0.070). Affordability and information quality are key SEA metrics, highlighting the necessity of economic access and multilingual, real-time communication. Overall, the findings indicate that wellbeing is most strongly shaped by accessibility-oriented service experience attributes particularly affordability and information quality followed by operational assurance, while comfort-related conditions remain significant under high heat exposure during waiting and transfers. On the other hand, the research indicates that operational reliability helps mitigate environmental discomfort in hyper-arid areas. The report suggests focusing on equal prices, digital information accessibility, dependable operations, and climate-adaptive infrastructure to promote sustainable mobility and long-term public transport use. Full article

The coelomic cavity of sea turtles is affected by congenital, developmental, traumatic, infectious, and organ- or system-specific disorders, making accurate anatomical knowledge essential for veterinary practice. This study presents an open-access, interactive two-dimensional (2D) anatomical atlas of the coelomic cavity of the loggerhead sea turtle (Caretta caretta), developed using images obtained from osteology, gross anatomical dissections, computed tomography (CT), and magnetic resonance imaging (MRI). The atlas comprises six osteology images, sixteen anatomical dissection images, eight transverse CT images acquired using bone and soft-tissue windows, six three-dimensional (3D) volume-rendered CT images, and fourteen MRI images (four transverse, five dorsal, and five sagittal), all provided in PNG format. Relevant anatomical structures were segmented and colour-coded for each figure using manual layer-based segmentation software. The Unity 3D platform was employed for image visualisation and assessment, supporting the development of interactive two-dimensional content. This atlas serves as a useful interactive tool for anatomical learning and clinical reference for professionals and students engaged in the conservation of loggerhead sea turtles. Full article

Very-high-resolution (VHR) satellite imagery has expanded the scale at which researchers can monitor marine mammals in remote regions and improved monitoring efforts in data-deficient areas. Relatively little is known about beluga whale (Delphinapterus leucas) distribution in their wintering grounds, due partly to the unpredictability of sea ice formation and limited accessibility. VHR satellite imagery has been used successfully to estimate the abundance of summering beluga whales; however, the feasibility of tasking VHR satellite imagery in the winter and determining the detectability of beluga whales amongst sea ice have not been formally assessed. Our objective was to assess the feasibility of acquiring VHR satellite imagery in the winter and whether beluga whales could be reliably distinguished from sea ice in the imagery. Our study focused on beluga whale populations that are winter residents within James Bay and Cumberland Sound, occupying nearshore open water and ice leads in the winter. Two images were collected in Cumberland Sound covering known beluga whale wintering grounds in February and March 2022 encompassing 745 km², with ice covering >75% of the image, and three images were acquired within James Bay from January to March 2024 spanning over 5700 km², with ice covering >86% of the survey area. We observed 0 certain and 294 uncertain detections, suggesting that current satellite imagery resolutions are too low for confidently detecting beluga whales amongst densely packed ice. High-definition sharpening to 15 cm reduced the number of uncertain detections, but we were still unable to identify any certain whales. Continued advancements in imagery resolution are required to distinguish beluga whales from sea ice and improve year-round beluga whale monitoring. Full article