Search Results (2,109)

This study investigates the integration of 3D laser scanning technology in the retrofitting of Ballast Water Treatment Systems (BWTS) on existing commercial vessels, addressing the global challenge of invasive aquatic species. The methodology combines a bibliometric analysis of keywords—indicating recent trends and knowledge gaps, a feasibility study, and detailed engineering design with on-site supervision. A case study is presented on a crude oil tanker, employing a multi-station 3D scanning strategy across the engine and pump rooms—performed using 63 and 45 scan positions, respectively. These data were processed with removal filters and integrated into specialized CAD software for detailed piping design. The implementation of high-fidelity point clouds served as the digital foundation for modeling the vessel’s existing piping infrastructure and retrofitting with the installation of an electrolysis-based BWTS. Results confirm that 3D scanning enables precise spatial analysis, minimizes retrofitting errors, reduces installation time, and ensures regulatory compliance with the IMO Ballast Water Management Convention. By digitally capturing complex onboard environments, the approach enhances accuracy, safety, and cost-effectiveness in maritime engineering projects. This work underscores the transition toward point cloud-based digital twins as a standard for sustainable and efficient ship conversions in the global shipping industry. Full article

CO₂ laser processing has emerged as an efficient dry-finishing technique capable of inducing controlled chemical and morphological transformations in cotton and denim textiles. The strong mid-infrared absorption of cellulose enables localised photothermal heating, leading to selective dye decomposition, surface oxidation, and micro-scale ablation while largely preserving the bulk fabric structure. These laser-driven mechanisms modify colour, surface chemistry, and topography in a predictable, parameter-dependent manner. Low-fluence conditions predominantly produce uniform fading through fragmentation and oxidation of indigo dye; in comparison, moderate thermal loads promote the formation of carbonyl and carboxyl groups that increase surface energy and enhance wettability. Higher fluence regimes generate micro-textured regions with increased roughness and anchoring capacity, enabling improved adhesion of dyes, coatings, and nanoparticles. Compared with conventional wet processes, CO₂ laser treatment eliminates chemical effluents, strongly reduces water consumption and supports digitally controlled, Industry 4.0-compatible manufacturing workflows. Despite its advantages, challenges remain in standardising processing parameters, quantifying oxidation depth, modelling thermal behaviour, and assessing the long-term stability of functionalised surfaces under real usage conditions. In this review, we consolidate current knowledge on the mechanistic pathways, processing windows, and functional potential of CO₂ laser-modified cotton substrates. By integrating findings from recent studies and identifying critical research gaps, the review supports the development of predictable, scalable, and sustainable laser-based cotton textile processing technologies. Full article

Lakes on the Qinghai–Tibet Plateau are important indicators of global climate change, and variations in their water storage strongly influence regional hydrological cycles and ecosystems. However, existing studies have largely focused on relative changes in lake volume, while the precise quantification of absolute water storage remains insufficient, largely due to the lack of long-term, high-accuracy water storage time series. Constrained by harsh natural conditions and limited in situ observations, conventional approaches struggle to achieve the accurate long-term monitoring of lake water storage across the Plateau. To address this challenge, we propose a DEM-based underwater topography extrapolation method. Under the assumption of continuity between surrounding onshore terrain and submerged lakebed morphology, nearshore DEM data are extrapolated to reconstruct lake bathymetry. By integrating multi-source remote sensing observations of lake area and water level, we estimate and reconstruct 30-year absolute water storage time series for 120 Plateau lakes larger than 50 km². This method does not require measured water depth data and is particularly suitable for data-scarce, topographically complex, high-altitude lake regions, effectively overcoming key limitations of conventional methods used for absolute water storage monitoring. Validation shows strong agreement between our estimates and an independent validation dataset, with an overall correlation coefficient of 0.95; the reconstructed time series are highly reliable, with correlation coefficients exceeding 0.6. During the study period, the total lake water storage of the Qinghai–Tibet Plateau exhibited a significant increasing trend, with a cumulative growth of approximately 137.297 billion m³, representing a 20.73% increase, and showing notable spatial heterogeneity. The water storage dataset constructed in this study provides reliable data support for research on water cycles, climate change assessment, and regional water resource management on the Qinghai–Tibet Plateau. Full article

Tilapia lake virus (TiLV) is a highly virulent pathogen that has caused substantial mortality in tilapia farms, particularly those with open-water systems. However, TiLV can also emerge and persist in closed environments, such as recirculating aquaculture systems (RAS), where environmental accumulation and repeated exposure may intensify infection and sustain outbreaks. In this case study, we conducted three field experiments to better understand TiLV dynamics among Nile tilapia in RAS. In experiment I, we quantified the TiLV levels in the fish, water, and sediment to compare outbreak and no-outbreak conditions and found that the TiLV concentrations in liver samples and the water were significantly higher in the outbreak ponds and positively correlated with increased fish mortality. In experiment II, we used a side-by-side field trial to evaluate the protective efficacy of a TiLV vaccine and its effects on the viral loads in the fish and aquatic environment during outbreaks. The vaccinated fish showed substantially lower cumulative mortality (16.7%) than the unvaccinated controls (37.7%), with a relative percent survival of 55.6%. Additionally, the TiLV concentrations in the pond water of the vaccinated group were significantly lower. In experiment III, we compared the TiLV patterns between RAS and non-RAS operations to determine how water recirculation influences viral accumulation and outbreak severity. The results revealed limited viral accumulation and shorter disease outbreak duration in the non-RAS. Overall, our findings showed that the TiLV levels in the rearing water were closely linked with disease severity in the RAS-based tilapia hatcheries. Continuous water recirculation allowed the virus to build up in the system, which led to more prolonged outbreaks, while the non-RAS conditions with regular water discharge showed lower viral loads and faster recovery. The vaccinated fish had better survival rates and released less virus into the water, which helped reduce infection pressure across the ponds. Together, these results suggest that combining vaccination with good water management and molecular monitoring can provide a practical, noninvasive way to detect and control TiLV outbreaks in intensive farming systems. Full article

Mega-event-led urban waterfront regeneration has played a key role in shaping public open spaces, particularly in newly developed areas within the Chinese context. However, public perceptions and their influence on the use of newly built open spaces created through mega-event-led regeneration have not been examined in existing research. To address this gap, this study establishes an integrated assessment framework to evaluate the quality of urban waterfront open spaces. A mixed methods approach was adopted, including direct observations and 770 online questionnaires collected between July and October 2024 at the South Bank of the Qiantang River (SBQR) in Hangzhou, China. Spatial analysis and Importance–Performance Analysis (IPA) were employed to determine priority improvement areas that should inform future waterfront regeneration strategies. The results indicate that inclusiveness emerged as the most important factor for enhancing waterfront open space quality, while spatial aesthetics ranked the lowest. Among the sub-sub factors, elements related to improving water accessibility, enhancing natural surveillance, providing artificial shelters and diverse seating options, introducing distinctive water features, and shaping collective memory through digital technologies are the key priorities for improvement in the future urban waterfront regeneration policies. Finally, the study highlights that the intangible legacies of the Asian Games and the adaptive reuse of informal built heritage have the potential to reshape a distinctive new city image and collective memory, even in the absence of tangible and formally recognised heritage buildings. Full article

The Iraqi coastline in the northern Persian Gulf is highly vulnerable to the impacts of future sea level rise. This study introduces a novel approach in the Arc Geographic Information System (ArcGIS) for inundation risk of the 58 km Iraqi coast of the northern Persian Gulf through a combination of multi-data sources, machine-learning predictions, and hydrological connectivity by Landsat. The Prophet/Neural Prophet time-series framework was used to extrapolate future sea level rise with 11 satellite altimetry missions that span 1993–2023. The coastline was obtained by using the Landsat-8 Operational Land Imager (OLI) imagery based on the Normalised Difference Water Index (NDWI), and topography was obtained by using the ALOS World 3D 30 m DEM. Global Land Use and Land Cover (LULC) projections (2020–2100) and population projections (2020–2100) were used as future inundation values. Two scenarios were compared, one based on an altimeter-based projection of sea level rise (SLR) and the other based on the National Aeronautics and Space Administration (NASA) high-emission scenario, Representative Concentration Pathway 8.5 (RCP8.5). It is found that, by the IPCC AR6 end-of-century projection horizon (relative to 1995–2014), 154,000 people under the altimeter case and 181,000 people under RCP8.5 will have a risk of being inundated. The highest flooded area is the barren area (25,523–46,489 hectares), then the urban land (5303–5743 hectares), and finally the cropland land (434–561 hectares). Critical infrastructure includes 275–406 km of road, 71–99 km of electricity lines, and 73–82 km of pipelines. The study provides the first hydrologically verified Digital Elevation Model (DEM)-refined inundation maps of Iraq that offer a baseline, in the form of a comprehensive and quantitative base, to the coastal adaptation and climate resilience planning. Full article

Shiqian County, located within a key geothermal fluids belt in Guizhou Province, China, has abundant underground hot water resources. Therefore, elucidating the hydrogeochemical characteristics and formation mechanisms of thermal mineral water in this area is essential for evaluating and sustainably utilizing regional geothermal fluids. This study focuses on the Shiqian Hot Spring Group and employs integrated analytical techniques, including rock geochemistry, hydrogeochemistry, isotope hydrology, digital elevation model (DEM) data analysis, remote sensing interpretation, geological surveys, mineral saturation index calculations, and PHREEQC-based inverse hydrogeochemical modeling, to elucidate its hydrogeochemical characteristics and formation mechanisms. The results show that strontium concentrations range from 0.06 to 7.17 mg/L (average 1.65 mg/L) and metasilicic acid concentrations range from 19.46 to 65.51 mg/L (average 33.64 mg/L). Most samples meet the national standards for natural mineral water and are classified as Sr-metasilicic acid type. Isotope analysis indicates that the geothermal water is recharged by meteoric precipitation at elevations between 911 m and 1833 m, mainly from carbonate outcrops and fracture zones on the southwestern slope of Fanjingshan, and discharges south of Shiqian County. The dominant hydrochemical types are HCO₃·SO₄-Ca·Mg and HCO₃-Ca·Mg. Strontium is primarily derived from carbonate rocks and celestite-bearing evaporites, whereas metasilicic acid mainly originates from quartz dissolution along the upstream groundwater flow path. PHREEQC-based inverse modeling indicates that, during localized thermal mineral water runoff in the middle-lower reaches or discharge areas, calcite dissolves while dolomite and quartz tend to precipitate, reflecting calcite dissolution-dominated water–rock interactions and near-saturation conditions for some minerals at late runoff stages. Full article

Freshwater availability is one of the most pressing environmental concerns in arid ecosystems. The use of free-standing water by raptors has been little studied, and in the context of climate change has become increasingly important as extended droughts are expected to become more frequent. We analyzed digital images from camera traps captured in the freshwater springs of Sierra El Mechudo, during summer to early autumn of 2023 and 2024 in Baja California Sur, Mexico. We recorded 165 detections of four raptor species. The Turkey Vulture (Cathartes aura) was the most frequently detected (n = 55), followed by the Great Horned Owl (Bubo virginianus) (n = 50), the Red-tailed Hawk (Buteo jamaicensis) (n = 45), and the Cooper’s Hawk (Astur cooperii), which was observed only in early autumn 2024 (n = 15). The Great Horned Owl exhibited a distinct detection pattern (mainly crepuscular, with the highest peak at 6 a.m.), in contrast with the other three species, which were detected mainly at midday and in the afternoon, during the hottest hours of the day. All raptors were recorded drinking water; however, species differed in the proportion of behaviors they exhibited at the freshwater springs. The Turkey Vulture showed the highest drinking activity (76.3%), whereas both hawks exhibited the same lowest proportions (26.6%) among all species detected. The proportion of behaviors remained constant across years. The time spent at the freshwater springs did not differ across species or years. The Red-tailed Hawk, the Great Horned Owl, and the Turkey Vulture increased their detections at the springs in 2024, when a severe and prolonged drought affected the southern peninsula. The results showed that the importance of freshwater springs for raptors extends beyond their use for drinking only; the surrounding habitat as a refuge and availability of prey in the area are evidently essential for these birds of prey. Further studies should extend research into the diverse use of springs and home ranges of raptors in the southern Baja California peninsula. Full article

Dry Eye Disease (DED) is a highly characterised multifactorial disease resulting in the loss of tear film homeostasis and associated with a major impact on patient quality of life. DED affects up to half of the global population, with modern lifestyle factors playing a critical role in disease development, particularly excessive use of digital devices. The ultimate treatment goal is restoration of tear film homeostasis and breaking the ‘vicious circle’ of DED. Today, the use of tear substitutes represents the main option for the treatment of DED. These topical formulations aim to provide lubrication, reduce osmolarity, and improve tear clearance. However, they do not interact with the ocular surface epithelium nor modulate ocular inflammation, and do not fully restore natural tear function. T-LysYal is the first supramolecular ocular surface modulator for DED. Studies demonstrate that T-LysYal promotes tissue repair, improves tear breakup time, restores corneal epithelial cell damage, and modulates inflammation processes, significantly reducing the severity of DED symptoms in patients. In addition, T-LysYal provides stability that prolongs activity and favours cell adhesion. Through its 3D nanotube structure, movement of water in the eye is retained and improved, enhancing ocular hydrodynamics. This narrative review introduces T-LysYal for DED whilst highlighting both its in vitro activity and clinical profile against hyaluronic acid, a mainstay of disease management. Full article

Digital twins (DTs) have seen widespread application across industries, enabling deep integration of cyber–physical systems. However, previous research has largely focused on domain-specific DTs and lacks a universal, cross-industry modeling framework, resulting in high development costs and low reusability. To address these challenges, this study proposes a DT modeling method based on hierarchical decoupling and topological connections. First, the system is decomposed top–down into three levels—system, subsystem, and component—through hierarchical functional decoupling, reducing system complexity and supporting independent component development. Second, a method for constructing component-level DTs using standardized information sets is introduced, employing the JSON-LD language to uniformly describe and encapsulate component information. Finally, a topological connection mechanism abstracts the relationships between components into an adjacency matrix and assembles components and subsystems bottom–up using graph theory, ultimately forming the system-level DT. The effectiveness of the proposed method was validated using a typical surface water purification system as a case study, where the system was decomposed into four functional subsystems and 12 types of components. Experimental results demonstrate that the method efficiently enables automated integration of DTs from standardized components to subsystems and the complete system. Compared with conventional monolithic modeling approaches, it significantly reduces system complexity, supports efficient component development, and accelerates system integration. For example, when the number of components exceeds 300, the proposed method generates topology connections 44.69% faster than direct information set traversal. Consequently, this approach provides a novel and effective solution to the challenges of low reusability and limited generality in DT models, laying a theoretical foundation and offering technical support for establishing a universal cross-industry DT modeling framework. Full article

The Australian public and broader society have little awareness of the seminal relationship between water supply and data usage/storage. Most data centers (DCs) consume large volumes of water to operate servers that supply digital society’s instantaneous 24/7 information communication systems. DC water consumption is a global issue that lacks transparency, sustainable management, and effective governance. This article analyzes current Australian legislation, policies, and industry sustainability plans to examine whether and in what ways the absence of clear water governance requirements for DC may contribute to state and national water insecurity. It shows how academic and applied discourses conceptualize, research, and respond to DC sustainability as an energy issue. This conceptualization masks the relevance of DC water usage/security. The results show that Australian legislation, policy, planning, and management lack sufficient transparency and state governance regarding the industry’s water use and accountability. Global and national DC certifications are discussed, and policy solutions are recommended to mitigate future DC pressure on water supply and related consequences. Our conclusions advocate the necessity of improving public awareness, industry accountability, and government management strategies (policy and legislation) for sustainable water practices in Australia, as artificial intelligence increases DC quantity and size, exacerbating supply and consumption in local environments that legislate against nuclear energy alternatives. Full article

Climate challenges, along with a projected global population increase of 2 billion by 2080, are intensifying pressures on agricultural systems, leading to biodiversity loss, land use constrains, soil fertility declining, and changes in water cycles, while crop yields struggle to meet the rising food demand. These challenges, coupled with evolving legislation and rapid technology advancements, require innovative sustainable agricultural solutions. By reshaping farmers’ daily operations, real-time data acquisition and predictive models can support informed decision-making. In this context, smart farming (SM) applied to plant breeding can improve efficiency by reducing inputs and increasing outputs through the adoption of digital and data-driven technologies. Examples include the investment on common ontologies and metadata standards for phenotypes and environments, standardization of HTP protocols, integration of prediction outputs into breeding databases, and selection workflows, as well in building multi-partner field networks that collect diverse envirotypes. This review outlines how AI and machine learning (ML) can be integrated in modern plant breeding methodologies, including genomic selection (GS) and genetic algorithms (GAs), to accelerate the development of climate-resilient and sustainably performing crop varieties. While many reviews address smart farming or smart breeding independently, herein, these domains are bridged to provide an understandable strategic landscape by enhancing breeding efficiency. Full article

AI enhances aquatic resource management by automating species detection, optimizing feed, forecasting water quality, protecting species interactions, and strengthening the detection of illegal, unreported, and unregulated fishing activities. However, these advancements are inconsistently employed, subject to domain shifts, limited by the availability of labeled data, and poorly benchmarked across operational contexts. Recent developments in technology and applications in fisheries genetics and monitoring, precision aquaculture, management, and sensing infrastructure are summarized in this paper. We studied automated species recognition, genomic trait inference, environmental DNA metabarcoding, acoustic analysis, and trait-based population modeling in fisheries genetics and monitoring. We used digital-twin frameworks for supervised learning in feed optimization, reinforcement learning for water quality control, vision-based welfare monitoring, and harvest forecasting in aquaculture. We explored automatic identification system trajectory analysis for illicit fishing detection, global effort mapping, electronic bycatch monitoring, protected species tracking, and multi-sensor vessel surveillance in fisheries management. Acoustic echogram automation, convolutional neural network-based fish detection, edge-computing architectures, and marine-domain foundation models are foundational developments in sensing infrastructure. Implementation challenges include performance degradation across habitat and seasonal transitions, insufficient standardized multi-region datasets for rare and protected taxa, inadequate incorporation of model uncertainty into management decisions, and structural inequalities in data access and technology adoption among smallholder producers. Standardized multi-region benchmarks with rare-taxa coverage, calibrated uncertainty quantification in assessment and control systems, domain-robust energy-efficient algorithms, and privacy-preserving data partnerships are our priorities. These integrated priorities enable transition from experimental prototypes to a reliable, collaborative infrastructure for sustainable wild capture and farmed aquatic systems. Full article

In this work, a 3D microfluidic paper-based analytical device (3D-µPAD) was developed for the smartphone-based colorimetric determination of phosphate in environmental samples. The assay relied on the formation of a blue-colored product (molybdenum blue) in the detection area of the 3D-µPAD upon reduction of the heteropolyacid H₃PMo₁₂O₄₀ formed in the presence of phosphate. A number of experimental parameters were optimized, including geometric aspects of 3D-µPADs, digitization and image processing conditions, the amount of chemicals deposited in specific areas of the 3D-µPAD, and the reaction time. In addition, the stability of the device was evaluated at three different storage temperatures. Under optimal conditions, the working range was found to be from 4 to 25 mg P/L (12–77 mg PO₄⁻³/L). The limits of detection (LOD) and quantification (LOQ) were 0.015 mg P/L and 0.05 mg P/L, respectively. The repeatability and intermediate precision of a 5 mg P/L standard were 4.8% and 7.1%, respectively. The proposed colorimetric assay has been successfully applied to phosphorous determination in various waters, soils, and sediments, obtaining recoveries in the range of 94 to 107%. The ready-to-use 3D-µPAD showed a greener profile than the standard method for phosphate determination, being affordable, easy-to-use, and suitable for citizen science applications. Full article

The textile sector provides essential goods, yet it remains environmentally and socially intensive, driven by high water use, pesticide dependent monocropping, chemical pollution during processing, and growing waste streams. This review examines credible pathways to sustainability by integrating emerging plant-based fibres from hemp, abaca, stinging nettle, and pineapple leaf fibre. These underutilised crops combine favourable agronomic profiles with competitive mechanical performance and are gaining momentum as the demand for demonstrably sustainable textiles increases. However, conventional fibre identification methods, including microscopy and spectroscopy, often lose reliability after wet processing and in blended fabrics, creating opportunities for mislabelling, greenwashing, and weak certification. We synthesise how advanced molecular approaches, including DNA fingerprinting, species-specific assays, and metagenomic tools, can support the authentication of fibre identity and provenance and enable linkage to Digital Product Passports. We also critically assess environmental Life Cycle Assessment (LCA) and social assessment frameworks, including S-LCA and SO-LCA, as complementary methodologies to quantify climate burden, water use, labour conditions, and supply chain risks. We argue that aligning fibre innovation with molecular traceability and harmonised life cycle evidence is essential to replace generic sustainability claims with verifiable metrics, strengthen policy and certification, and accelerate transparent, circular, and socially responsible textile value chains. Key research priorities include validated marker panels and reference libraries for non-cotton fibres, expanded region-specific LCA inventories and end-of-life scenarios, scalable fibre-to-fibre recycling routes, and practical operationalisation of SO-LCA across diverse enterprises. Full article