Search Results (48)

Recent underwater and remote sensing surveys identified, located, and documented the wreck of a Liberty-class cargo ship, SS Samuel J. Tilden, which sank during the German raid of Bari in December 1943. The use of remote sensing technologies (MBES, ROVs) and the photogrammetric acquisition for the creation of 3D models were central for a comprehensive analysis of the wreck site. The analysis of remote sensing and photogrammetric data indicates a well-preserved wreck, as previously noted in avocational underwater surveys, and a complex maritime landscape. By applying remote sensing and non-invasive technologies to conflict archaeology remains, this paper provides a basis for future studies on World War II wrecks in Italy. Full article

Drought significantly disrupts rice productivity under increasing climate volatility. Identifying robust molecular determinants for resilience remains a critical priority for crop improvement. Following the PRISMA guidelines, we performed a large-scale, dual-platform meta-analysis of RNA-Seq and microarray datasets to elucidate the robust transcriptomic landscape of Oryza sativa underwater deficit. Tissue-specific regulatory pathways were identified using STRING, g:Profiler, and PANTHER. Our analysis resolved distinct functional divergence, where shoots prioritize photosynthetic adjustment while roots emphasize transcriptional and chromatin reprogramming. Beyond validating core ABA signaling, we uncover a novel metabolic pivot: the activation of glyoxylate and dicarboxylate metabolism to mitigate drought-induced carbon starvation. We further identify specialized transport systems for ions and electrons across organelle membranes, alongside cellular reorganization driven by autophagy and actin-dependent cytoskeleton remodeling. These findings highlight a sophisticated network of survival strategies governing energy conservation and structural adaptation. By synthesizing heterogeneous transcriptomics, this study reveals robust pathways that are overlooked in single-platform investigations. This work provides a prioritized roadmap for utilizing functional validation and precision breeding to accelerate the development of climate-resilient rice cultivars. Full article

Underwater cultural heritage represents a fragile and largely unexplored component of historical landscapes, particularly in dynamic fluvial and coastal environments. Despite increasing international attention to its protection, the spatial identification of submerged heritage remains methodologically challenging. This study proposes a geo-historical approach that integrates historical cartography and Geographic Information Systems (GIS) to identify areas of high archaeological potential in underwater contexts. Focusing on the Douro River in Porto (Portugal), a UNESCO World Heritage city with a long maritime and fluvial history, the research analyses a set of key historical maps from the eighteenth and nineteenth centuries, complemented by documentary and archaeological sources. These cartographic materials were georeferenced and critically assessed in QGIS, enabling the digitisation of features associated with land–water interaction, navigation hazards, port infrastructures, and military defences. The resulting spatial dataset was used to generate an interpretative map and a kernel density model highlighting potential underwater heritage hotspots along the riverbed and riverbanks. The findings identify several priority zones, including the river mouth, historic quays, former shipbuilding areas, and sectors linked to nineteenth-century defensive structures. While the study does not include in situ verification, it demonstrates the value of historical maps as predictive tools for guiding targeted underwater surveys and proposes a transferable, cost-effective framework for heritage prospection and management in historically active fluvial–estuarine settings. Full article

Accurately predicting the long-term behavior of complex dynamical systems is a central challenge for safety-critical applications like autonomous navigation. Mechanistic models are often brittle, relying on difficult-to-measure parameters, while standard deep learning models are black boxes that fail to generalize, producing physically inconsistent predictions. Here, we introduce a physics-informed framework that learns the continuous-time dynamics of an Autonomous Underwater Vehicle (AUV) by discovering its underlying energy landscape. We embed the structure of Port-Hamiltonian mechanics into a neural ordinary differential equation (NODE) architecture, learning not to imitate trajectories but rather to identify the system’s Hamiltonian and its constituent physical matrices from observational data. Geometric consistency is enforced by representing rotational dynamics on the SE(3) manifold, preventing numerical error accumulation. Experimental validation reveals a stark performance divide. While a state-of-the-art black-box model matches our accuracy in simple, interpolative maneuvers, its predictions fail catastrophically under complex controls. Quantitatively, our physics-informed model maintained a mean 10 s position error of a mere 3.3 cm, whereas the black-box model’s error diverged to 5.4 m—an over 160-fold performance gap. This work establishes that the key to robust, generalizable models lies not in bigger data or deeper networks but in the principled integration of physical laws, providing a clear path to overcoming the brittleness of black-box models in critical engineering simulations. Full article

The objective of this article is to provide a critical analysis of maritime heterotopia as a category for reinterpreting ships, shipwrecks and maritime landscapes between the 16th and 18th centuries. Through an interdisciplinary approach combining history, underwater archaeology, heritage theory and literary analysis, it explores the ways in which maritime spaces, especially ships and shipwrecks, functioned as ‘other spaces’–following Foucault’s concept of heterotopia–in the articulation of imperial projects, power relations, experiences of transit and narratives of memory. A particular focus has been placed on the examination of shipwreck accounts, which are regarded as microhistories of human behaviour in contexts of crisis. These accounts have been shown to offer insights into alternative social structures, dynamics of authority, and manifestations of violence or solidarity. A review of the legal framework and practices related to shipwrecks in the Spanish Carrera de Indias is also undertaken, with particular emphasis on their impact on maritime legislation and international law. This article proposes a reading of maritime heritage as a symbolic and political device in constant dispute, where material remains and associated narratives shape collective memories, geopolitical tensions and new forms of cultural appropriation. Shipwrecks thus become sites of rupture and origin, charged with utopian, dystopian and heterotopic potential. Full article

Agricultural drainage canals provide critical habitats for fish species that are highly sensitive to agricultural practices. However, conventional monitoring methods such as capture surveys are invasive and labor-intensive, which means they can disturb fish populations and hinder long-term ecological assessment. Therefore, there is a strong need for effective and non-invasive monitoring techniques. In this study, we developed a practical method using the YOLOv8n deep learning model to automatically detect and quantify fish occurrence in underwater images from a canal in Ibaraki Prefecture, Japan. The model showed high performance in validation (F1-score = 91.6%, Precision = 95.1%, Recall = 88.4%) but exhibited reduced performance under real field conditions (F1-score = 61.6%) due to turbidity, variable lighting, and sediment resuspension. By correcting for detection errors, we estimated that approximately 7300 individuals of Pseudorasbora parva and 80 individuals of Cyprinus carpio passed through the observation site during a seven-hour monitoring period. These findings demonstrate the feasibility of deep learning-based monitoring to capture temporal patterns of fish occurrence in agricultural drainage canals. This approach provides a promising tool for sustainable aquatic ecosystem management in agricultural landscapes and emphasizes the need for further improvements in recall under turbid and low-visibility conditions. Full article

This study explores a submerged architectural strategy for data center deployment in coal mining subsidence water bodies, aiming to simultaneously address the underutilization of post-mining landscapes, the high-carbon operation of data centers, and the implementation challenges of China’s dual carbon goals. The proposed structure integrates wall-mounted plate heat exchangers into the façades of underwater data halls, using the natural convection of surrounding water as a low-grade heat sink to replace conventional cooling towers and achieve passive, low-carbon cooling. A thermal exchange model was developed based on heat transfer principles and validated by comparing outputs from TRNSYS simulations and MATLAB-based parameterized calculations, showing a deviation of less than 3% under all test conditions. The model was then used to estimate energy consumption, PUE, and carbon emissions under typical IT load scenarios. Results indicate a 42.5–64.3% reduction in cooling energy use and a 37.7–75.1% reduction in carbon emissions compared to conventional solutions, while a PUE range of 1.06–1.15 is maintained. The system also offers strong spatial adaptability and scalability, presenting a sustainable solution for redeveloping subsidence zones that supports ecological restoration and digital transformation in resource-depleted urban regions. Full article

The classification of submarine topography and geomorphology is essential for marine resource exploitation and ocean engineering, with wide-ranging implications in marine geology, disaster assessment, resource exploration, and autonomous underwater navigation. Submarine landscapes are highly complex and diverse. Traditional visual interpretation methods are not only inefficient and subjective but also lack the precision required for high-accuracy classification. While many machine learning and deep learning models have achieved promising results in image classification, limited work has been performed on integrating backscatter and bathymetric data for multi-source processing. Existing approaches often suffer from high computational costs and excessive hyperparameter demands. In this study, we propose a novel approach that integrates pruning-enhanced ConDenseNet with label smoothing regularization to reduce misclassification, strengthen the cross-entropy loss function, and significantly lower model complexity. Our method improves classification accuracy by 2% to 10%, reduces the number of hyperparameters by 50% to 96%, and cuts computation time by 50% to 85.5% compared to state-of-the-art models, including AlexNet, VGG, ResNet, and Vision Transformer. These results demonstrate the effectiveness and efficiency of our model for multi-source submarine topography classification. Full article

Tainan’s Cigu, located on Taiwan’s southwestern coast, is a prominent aquaculture hub known for its extensive ponds, tidal flats, and lagoons. This study explored the novel integration of kayaking within aquavoltaic (APV) aquaculture ponds, creating a unique hybrid tourism landscape that merges industrial land use (aquaculture and energy production) with nature-based recreation. We investigated the relationships among facility maintenance and safety professionalism (FM), the perceived value of kayaking training (PV), and green energy and sustainable development recognition (GS) within these APV systems in Cigu, Taiwan. While integrating recreation with renewable energy and aquaculture is an emerging approach to multifunctional land use, the mechanisms influencing visitors’ sustainability perceptions remain underexplored. Using data from 613 kayaking participants and structural equation modeling, we tested a theoretical framework encompassing direct, mediated, and moderated relationships. Our findings reveal that FM significantly influences both PV (β = 0.68, p < 0.001) and GS (β = 0.29, p < 0.001). Furthermore, PV strongly affects GS (β = 0.56, p < 0.001). Importantly, PV partially mediates the relationship between FM and GS, with the indirect effect (0.38) accounting for 57% of the total effect. We also identified significant moderating effects of APV coverage, guide expertise, and operational visibility. Complementary observational data obtained with underwater cameras confirm that non-motorized kayaking causes minimal ecological disturbance to cultured species, exhibiting significantly lower behavioral impacts than motorized alternatives. These findings advance the theoretical understanding of experiential learning in novel technological landscapes and provide evidence-based guidelines for optimizing recreational integration within production environments. Full article

The North American Great Lakes offer a dynamic case study of inundated cultural landscapes. These bodies of water and the life around them have never been static. While submerged lands offer avenues for archaeological research, it is essential to first understand that these cultural landscapes have also been flooded with invasive power dynamics through settler colonialism. For example, the land and water systems in Anishinaabe Akiing (the northern Great Lakes) have fundamentally shifted from flourishing life systems to poisoned areas and now struggle to deal with invasive species. When seeking to learn from or otherwise engage Indigenous knowledge, it is essential to work from a perspective that takes all these changes into consideration. There are Indigenous communities who are interested in these inundated landscapes, and in this research, but a pause, naandamo, is needed to ethically consider the ongoing process of settler colonialism and Indigenous perspectives. Here we address ethical considerations for researchers participating in, or interested in participating in, submerged site research. By incorporating settler colonialism as a methodology of understanding, we will provide an ethical starting place for working with Indigenous communities and inundated landscapes. Full article

The application of artificial intelligence (AI) in monitoring and managing ocean waste reveals considerable promise for improving sustainable strategies to combat marine pollution. This study performs a bibliometric analysis to examine research trends, knowledge frameworks, and future directions in AI-driven sustainable ocean waste management. This study delineates key research themes, prominent journals, influential authors, and leading nations contributing to the field by analysing scientific publications from major databases. Research from citation networks, keyword analysis, and co-authorship patterns highlights significant topics such as AI algorithms for waste detection, machine learning models for predictive mapping of pollution hotspots, and the application of autonomous drones and underwater robots in real-time waste management. The findings indicate a growing global focus on utilising AI to enhance environmental monitoring, optimise waste reduction methods, and support policy development for sustainable marine ecosystems. This bibliometric study provides a comprehensive analysis of the current knowledge landscape, identifies research gaps, and underscores the importance of AI as a crucial enabler for sustainable ocean waste management, offering vital insights for researchers, industry leaders, and environmental policymakers dedicated to preserving ocean health. Full article

The ocean, covering 71% of Earth’s surface, remains largely unexplored due to the challenges of the marine environment. This study focuses on the Kuźnica Deep in the Baltic Sea, aiming to develop an automatic seabed mapping methodology using multibeam echosounders (MBESs) and machine learning. The research integrates various scientific fields to enhance understanding of the Kuźnica Deep’s underwater landscape, addressing sediment composition, backscatter intensity, and geomorphometric features. Advances in remote sensing, particularly, object-based image analysis (OBIA) and machine learning, have significantly improved geospatial data analysis for underwater landscapes. The study highlights the importance of using a reduced set of relevant features for training models, as identified by the Boruta algorithm, to improve accuracy and robustness. Key geomorphometric features were crucial for seafloor composition mapping, while textural features were less significant. The study found that models with fewer, carefully selected features performed better, reducing overfitting and computational complexity. The findings support hydrographic, ecological, and geological research by providing reliable seabed composition maps and enhancing decision-making and hypothesis generation. Full article

This review focuses on touching-based underwater robotic perception and manipulation, and provides a comprehensive overview of the current research landscape. We begin by examining underwater tactile sensors, discussing their basic types and recent advancements that have facilitated their integration into underwater robotic manipulation. Additionally, we explore the development of force control algorithms for underwater manipulators and grippers, emphasizing their critical role in underwater environments. Furthermore, we analyze the application of force control algorithms in underwater robotic manipulation, considering different autonomy levels, basic manipulation tasks, and specific operational scenarios. Through this investigation, we identify existing limitations and propose future research directions aimed at enhancing the operational capabilities of underwater vehicle manipulator systems (UVMS) and expanding their application range. Finally, this review highlights key challenges and outlines pathways for advancing the field. Full article

Conventional methodologies often struggle in accurately positioning underwater habitats and elucidating the complex interactions between terrestrial and aquatic environments. This study proposes an innovative methodology to bridge the gap between these domains, enabling integrated 3D mapping and underwater positioning. The method integrates UAV (Uncrewed Aerial Vehicles) photogrammetry for terrestrial areas with underwater photogrammetry performed by a snorkeler. The innovative aspect of the proposed approach relies on detecting the snorkeler positions on orthorectified images as an alternative to the use of GNSS (Global Navigation Satellite System) positioning, thanks to an image processing tool. Underwater camera positions are estimated through precise time synchronization with the UAV frames, producing a georeferenced 3D model that seamlessly joins terrestrial and submerged landscapes. This facilitates the understanding of the spatial context of objects on the seabed and presents a cost-effective and comprehensive tool for 3D coastal mapping, useful for coastal management to support coastal resilience. Full article

According to EuroStat data, the recorded landings of fisheries products from European waters were estimated at about 6 million tons in 2001, down to 3.2 million tons in 2022. This gradual decline slowed after the entering into force of the reform of the European Common Fisheries Policy (CFP) at the end of 2013, but was followed by a steeper decline after 2018. This is reflected in the last assessment of the Scientific Technical and Economic Committee for Fisheries (STEPF), noting that despite progress in the NE Atlantic management, 41% of the assessed stocks in 2022 were outside safe biological limits, down from 80% in 2003. Improvements in the Mediterranean are significantly slower. A warming ocean provokes the measurable poleward migration of species and adds stress to predator–prey relations in all European seas. Within this general picture, the broad-brush landscape is influenced by policy applications more in favour of industrial exploitation and regulatory and market environments, making it very hard for many small-scale fishers (SSFs) to remain in business, let alone attract younger successors for generational transition. In crowded marine spaces, it is a challenge to allocate access rights fairly between fisheries, exclusion zones for resource and habitat protection and much-needed ecosystem recovery, platforms for fossil exploitation, wind farms, underwater cables and recreational uses. Two examples of local initiatives with faunal recovery potential in the Mediterranean are briefly presented as a bottom-up complement to more top-down management approaches. They are spearheaded by artisanal fishers, who seek to restore spawning grounds and other coastal habitats as a way to procure enough fish and other complementary activities to secure their livelihoods in the future. They are supported by local scientists and nature conservation organisations. While promising, this is still rather the exception. Here, it is argued that trust-building between artisanal fishers, conservationists and scientists, and greater systemic support to SSFs by governments, increase chances for the urgently needed structural shifts that deliver the reversal in the ongoing decline in biodiversity and ocean productivity that all aspire to, to ensure sustained social and economic benefits. Full article