Search Results (2,372)

Accurate mapping of hurricane-induced damage is essential for guiding rapid disaster response and long-term recovery planning. This study evaluates the Three-Dimensional Multi-Attributes, Multiscale, Multi-Cloud (3DMASC) framework for semantic classification of pre- and post-hurricane Light Detection and Ranging (LiDAR) data, using Mexico Beach, Florida, as a case study following Hurricane Michael. The goal was to assess the framework’s ability to classify stable landscape features and detect damage-specific classes in a highly complex post-disaster environment. Bitemporal topo-bathymetric LiDAR datasets from 2017 (pre-event) and 2018 (post-event) were processed to extract more than 80 geometric, radiometric, and echo-based features at multiple spatial scales. A Random Forest classifier was trained on a 2.37 km² pre-hurricane area (Zone A) and evaluated on an independent 0.95 km² post-hurricane area (Zone B). Pre-hurricane classification achieved an overall accuracy of 0.9711, with stable classes such as ground, water, and buildings achieving precision and recall exceeding 0.95. Post-hurricane classification maintained similar accuracy; however, damage-related classes exhibited lower performance, with debris reaching an F1-score of 0.77, damaged buildings 0.58, and vehicles recording a recall of only 0.13. These results indicate that the workflow is effective for rapid mapping of persistent structures, with additional refinements needed for detailed damage classification. Misclassifications were concentrated along class boundaries and in structurally ambiguous areas, consistent with known LiDAR limitations in disaster contexts. These results demonstrate the robustness and spatial transferability of the 3DMASC–Random Forest approach for disaster mapping. Integrating multispectral data, improving small-object representation, and incorporating automated debris volume estimation could further enhance classification reliability, enabling faster, more informed post-disaster decision-making. By enabling rapid, accurate damage mapping, this approach supports sustainable disaster recovery, resource-efficient debris management, and resilience planning in hurricane-prone regions. Full article

It might be difficult in many countries to find extended time series of measurements related to parameters of lakes' hydrology and their interactions with catchments. Nowadays, the combined use of satellite imagery and spatially distributed hydrological models may contribute substantially to this direction. In this study, in order to assess for a long period of years a lake’s surface elevation (LSE) and its water balance components, Lake Kastoria and its catchment, under Greece’s dry-thermal conditions, were selected as the case study. This research employed the MIKE SHE coupled with the MIKE HYDRO River (MHR) hydrological modeling system, fed with precipitation and leaf area index (LAI) data coming from a ground weather station, typical values of LAI for the specific area, and satellite products from NASA for the precipitation and from Copernicus Global Land Service for the LAI. In all cases where satellite data were used, the simulation of the long-term LSE was very satisfactory, with minor to medium changes to the inflow and outflow components of the water balance in both the catchment (from 0.32 to 7.36%) and the lake (from 1.47 to 11.3%). The above changes were also reflected in the runoff coefficients. In conclusion, the above satellite products can adequately be used for the prediction of the LSE. Furthermore, a plethora of quantified information in relation to the catchment’s water balance can be extracted and used in decision-making processes. Full article

Background: Atherosclerosis is the pathological basis for lethal cardio-cerebral vascular diseases, such as coronary artery disease and stroke. Fructus Choerospondiatis (FC) has demonstrated cardiac protective effects in multiple ethnomedicine. Whether these protective effects are attributed to the prevention of vascular atherosclerosis, however, remains unknown. We aim to examine the anti-atherosclerotic effect of FC aqueous extract and elucidate the underlying mechanism. Methods: FC was separated into peel and pulp, and the aqueous extract was obtained separately by boiling in water to mimic decocting. Atherosclerosis model was established in ApoE^−/− mice fed with a high-fat diet, and histological analysis were utilized to evaluate the development of atherosclerosis. Various inflammatory models were constructed in mice to evaluate the anti-inflammatory effect of FC extract systemically, including acute local inflammation induced by traumatic injury (ear/foot swelling), acute systemic inflammation triggered by pathogenic infection (LPS- and POLY (I:C)-induced), as well as chronic inflammatory conditions associated with oxidative stress (D-galactose-induced), metabolic disorder (db/db mice), and aging. LC-MS and network pharmacology identified bioactive components and targets. Western blotting, ELISA, qPCR, and immunofluorescence were utilized to analyze the key genes involved in the mechanisms. Results: FC peel extract reduced serum IL-6 level, atherosclerotic plaque area, and macrophage content in the plaque, while pulp extract showed no protective effects. Peel extract exhibits anti-inflammatory effects in all models. The integrative application of LC-MS and network pharmacology identified ellagic acid as the major bioactive component and AKT as its target protein. Mechanistically, FC peel extract inhibits AKT phosphorylation, suppresses c-FOS expression and nuclear translocation, reduces IL-6 transcription and inflammation, and thus alleviates atherosclerosis. Conclusions: FC peel aqueous extract exerts anti-atherosclerotic effect by inhibiting inflammation through AKT/c-FOS/IL-6 axis. This study provides novel insights into the protective effects against atherosclerosis of FC peel and highlights its potential application in the prevention and treatment of coronary artery diseases. Full article

Moringa oleifera has been recognized for its adaptability, nutritional richness, and multipurpose potential, particularly in resource-limited regions. While most research has focused on its leaves, moringa seeds remain underutilized despite their broad applicability in the environmental, agricultural, and food sectors. This review systematically and critically examines recent scientific literature on the use of M. oleifera seeds across these fields, emphasizing their functional value, applications, and challenges for sustainable use. The review follows the SALSA methodology (Search, Appraisal, Synthesis, and Analysis), a structured and iterative framework designed to identify, evaluate, and integrate scientific evidence from diverse sources. The analysis encompasses three main areas: (i) water treatment, where moringa seed extracts have achieved turbidity removal efficiencies above 90% and effective adsorption of dyes and potentially toxic elements; (ii) agriculture, where seed-derived fertilizers improve soil fertility, nutrient availability, and crop yield compared to conventional inputs; and (iii) the food industry, where moringa seed derivatives enhance the nutritional, functional, and antioxidant properties of bakery, beverage, and oil-based products. Overall, M. oleifera seeds emerge as a versatile and sustainable resource with proven potential as a natural coagulant, biofertilizer, and nutraceutical ingredient. By integrating findings from both English and Spanish language studies, this work highlights their contribution to sustainable water management, agricultural productivity, and food innovation, while emphasizing the need for further safety evaluation and process optimization to support large-scale application. Full article

Invasive species are a recurring global problem, and the water hyacinth (Pontederia crassipes) is a well-known example. Various strategies have been explored to manage its spread, including its use as an agricultural amendment. However, when P. crassipes biomass is incorporated into soil and undergoes degradation, it may increase soil conductivity and promote metal leaching, potentially affecting soil biota, particularly microbiota. Saprophytic fungi play a key role in the decomposition and renewal of organic matter, and their resilience to stressors is crucial for maintaining soil function. Thus, the aim of this study was to evaluate the effects of P. crassipes biomass extracts on the saprophytic fungus Trametes versicolor by evaluating fungal growth and metabolic changes [including sugar content, phosphatase enzymatic activity, and reactive oxygen species (ROS) production]. The fungus was exposed for 8 days to a dilution series of extracts (100%—undiluted, to 3.13%) prepared from P. crassipes biomass collected at five locations in Portuguese wetlands. Two sites were in the south, within a Mediterranean climate (Sorraia and Estação Experimental António Teixeira), and three were in the north, within an Atlantic climate (São João de Loure, Pateira de Fermentelos, and Vila Valente), representing both agricultural-runoff–impacted areas and recreational zones. Extracts were used to simulate a worst-case scenario. All extracts have shown high conductivity (≥15.4 mS/cm), and several elements have shown a high soluble fraction (e.g., K, P, As, or Ba), indicating substantial leaching from the biomass to the extracts. Despite this, T. versicolor growth rates were generally not inhibited, except for exposure to the São João de Loure extract, where an EC₅₀ of 45.3% (extract dilution) was determined and a significant sugar content decrease was observed at extract concentrations ≥25%. Possibly due to the high phosphorous leachability, both acid and alkaline phosphatase activities increased significantly at the highest percentages tested (50% and 100%). Furthermore, ROS levels increased with increasing extract concentrations, yet marginal changes were observed in growth rates, suggesting that T. versicolor may efficiently regulate its intracellular redox balance under stress conditions. Overall, these findings indicate that the degradation of P. crassipes biomass in soils, while altering chemical properties and releasing soluble elements, may not impair and could even boost microbiota, namely saprophytic fungi. This resilience highlights the potential ecological benefit of saprophytic fungi in accelerating the decomposition of invasive plant residues and contribution to soil nutrient cycling and ecosystem recovery. Full article

This study presents the results on the composition of hydro-distilled essential oils and the antioxidant properties of extracts isolated with different polarity solvents from the leaves (GLEO) and roots (GREO) of wild-grown Lithuanian goutweed (Aegopodium podagraria L.). The yields of GLEO and GREO were 0.22% and 0.04%. The identified compounds numbered 117 and 88, which constituted 99.4 and 99.2% of the total integrated peak area, respectively. The major GLEO constituents were sesquiterpenes germacrene D (17.53%), (E)-β-bergamotene (11.75%), (E,E)-α-farnesene (7.23%), and (E)-caryophyllene (5.29%), while monoterpene α-pinene (19.24%) was quantitatively dominant in GREO, followed by sesquiterpenes germacrene B (4.59%), (E)-caryophyllene (4.51%), β-barbatene (4.26%), and β-bazzanene (4.10%). Polyacetylene (Z)-falcarinol, which is an important bioactive compound, constituted 4.60% in GREO. The antioxidant characteristics of water, methanol, and acetone extracts were evaluated by the TPC, DPPH^•/ABTS^•+ scavenging, and ORAC assays. The water and methanol extracts of the leaves were the strongest antioxidants; their TPC and ORAC values were 62.12 and 56.84 mg GAE/g, and 1426 and 1293 µM TE/g, respectively; the EC₅₀ values of DPPH^• and ABTS^•+ scavenging were 1.18 and 2.48, and 2.45 and 3.57 mg/mL, respectively. The results obtained may assist in developing antioxidants, cosmeceuticals, nutraceuticals, and other health-beneficial preparations from A. podagraria extracts. Full article

Across the Baltic Sea region, areas situated in climate-sensitive water zones are increasingly exposed to environmental and socio-economic challenges. Gdańsk, Poland, is a prominent example where the rising threat of climate-related hazards, particularly connected with flooding, coincides with growing demand for resilient and adaptive housing solutions. Located in the Vistula Delta, the city’s vulnerability is heightened by its low-lying terrain, polder-based land systems, and extensive waterfronts. These geographic conditions underscore the urgent need for flexible, climate-responsive design strategies that support long-term adaptation while safeguarding the urban fabric and the well-being of local communities. This study provides evidence-based guidance for adaptive housing solutions tailored to Gdańsk’s waterfronts. It draws on successful architectural and urban interventions across the Baltic Sea region, selected for their environmental, social, and cultural relevance, to inform development approaches that strengthen resilience and social cohesion. To achieve this, an exploratory case study methodology was employed, supported by desk research and qualitative content analysis of strategic planning documents, academic literature, and project reports. A structured five-step framework, comprising project identification, document selection, qualitative assessment, data extraction, and analysis, was applied to examine three adaptive housing projects: Hammarby Sjöstad (Stockholm), Kalasataman Huvilat (Helsinki), and Urban Rigger (Copenhagen). Findings indicate measurable differences across nine sustainability indicators (1–5 scale): Hammarby Sjöstad excels in environmental integration (5/5 in carbon reduction and renewable energy), Kalasataman Huvilat demonstrates strong modular and human-scaled adaptability (3–5/5 across social and housing flexibility), and Urban Rigger leads in climate adaptability and material efficiency (4–5/5). Key adaptive measures include flexible spatial design, integrated environmental management, and community engagement. The study concludes with practical recommendations for local planning guidelines. The guidelines developed through the Gdańsk case study show strong potential for broader application in cities facing similar challenges. Although rooted in Gdańsk’s specific conditions, the model’s principles are transferable and adaptable, making the framework relevant to water sensitivity, flexible housing, and inclusive, resilient urban strategies. It offers transversal value to both urban scholars and practitioners in planning, policy, and community development. Full article

Investigating the evolution mechanism of overlying strata fractures during mining and identifying the key factors that influence the development height of water-conducting fracture zones (WCFZs) are essential for preventing roof water inrush disasters, protecting mine water resources, and ensuring safe and sustainable mine development. To investigate the height of WCFZs and the evolution law of roof water inflow in a syncline structure working face under high-confined aquifer conditions, the 203 working face of Gaojiapu Coal Mine in Binchang Coalfield is selected as the engineering case. This paper analyzes the characteristics and control mechanisms of roof water inflow in a syncline structure mining area using UDEC 7.0 and COMSOL Multiphysics 6.0 multiphysics numerical simulation software. The results indicate that under different mining heights and advancing speeds, the height of the WCFZ in the overlying strata of a syncline structure working face continuously increases during the downward mining stage and in areas below the axis, and decreases thereafter, eventually stabilizing after reaching its maximum value at the initial stage of upward mining. When the WCFZ communicates with the strong aquifer of the Cretaceous Luohe Formation during the mining process, roof water inflow into the working face increases abruptly. The effectiveness of controlling water inflow by adjusting mining height is superior to that of controlling mining speed. Based on the response relationship between mining height, mining speed, and roof WCFZ, an on-site drainage prevention strategy was implemented involving reduced mining height and increased mining speed. Consequently, the roof water inflow at the working face has decreased from an initial rate of 950 m³/h to 360 m³/h. This study is of great significance for the safe and efficient extraction of coal seams under high-confined aquifers in the Binchang Coalfield, supporting the efficient development of coal resources while safeguarding regional water resources, thereby offering considerable engineering and practical value in promoting green mining and sustainable mining practices in large-scale coal production bases with similar geological conditions. Full article

Accurate shoreline determination is essential for the study of coastal and inland water processes, hydrography, and the monitoring of aquatic and terrestrial environments. This study compares two modern remote sensing technologies: MLS conducted with a USV and photogrammetry using a UAV. The research was carried out on Lake Kłodno, characterised by a complex shoreline with vegetation and hydrotechnical structures. Both approaches satisfied the accuracy requirements of the IHO Special Order for shoreline extraction (≤5 m at the 95% confidence level). For the UAV-derived orthophoto, the error within which 95% of shoreline points were located (corresponding to 2.45·σ) was 0.05 m for the natural shoreline and 0.06 m for the variant including piers, both well below the IHO threshold. MLS achieved a 95% error of 1.16 m, which also complies with the Special Order criteria. UAV data enable clear interpretation of the land–water boundary, whereas MLS provides complete three-dimensional spatial information, independent of lighting conditions, and allows surveys of vegetated or inaccessible areas. The results demonstrate the complementarity of the two approaches: UAV is well suited to highly accurate shoreline mapping and the identification of hydrotechnical structures, while MLS is valuable for analysing the nearshore zone and for surveying vegetated or inaccessible areas. The findings confirm the value of integrating these approaches and highlight the need to extend research to other types of waterbodies, to consider seasonal variability, and to develop methods for the automatic extraction of shorelines. Full article

In controlled environment agriculture (CEA), CO₂ enrichment can promote photosynthesis while simultaneously reducing evapotranspiration, but the optimal settings vary depending on crop type, growth stage, and microclimate. This study presents a near-field remote sensing framework that fuses RGB image features with environmental variables to predict the CO₂ uptake/respiration dynamics of five leafy vegetables grown in a hydroponic culture system and evaluate their impact on resource efficiency under CO₂ control. A hybrid deep model incorporating You Only Look Once version 11 (YOLOv11) and a Residual Network with 50 layers (ResNet50) extracts growth-related visual cues and integrates them with tabular features (CO₂, temperature, and light conditions) to predict chamber CO₂ dynamics. Performance was evaluated by Mean Absolute Error (MAE)/Mean Squared Error (MSE) on withheld data, and the system-level impacts on water use (ET), pumping energy, and relative yield were analyzed using a conventional greenhouse model. The model exhibited high accuracy (MAE = 0.95; MSE = 1.62). Scenario analysis results showed that increasing ambient CO₂ concentration from 400 to 1200 ppm reduced modeled water demand by approximately 11%, increased modeled yield by approximately 9%, and resulted in a corresponding reduction in pumping energy per unit area. Unlike conventional single-crop, table-based approaches, this study demonstrates multi-crop generalization and image-environment fusion for CO₂ dynamic prediction, establishing proximity sensing as a viable decision-making layer for CEA. While yield/ET results were simulated rather than measured in long-term trials, and leaf area normalization was not available, the proposed framework provides a viable path for data-driven CO₂ control in indoor farms by linking image-based monitoring with operational optimization. Full article

The aim of this research was to identify the challenges and opportunities associated with the Water-Food-Ecosystem (WFE) Nexus approach in coastal river basins in Northeastern Pará and Eastern Amazonia. The methodology considered Sustainable Development Goals (SDGs) axes 2, 6, 8, 10 and 13 through a Nexus indicator matrix. It involved a statistical analysis of distribution and correlation coefficients. The coefficient indicates the strength of the relationship and the presence of positive or negative correlations. The final distribution of the variables discussed was to zone the region into areas of higher and lower potential for water sustainability. The results showed significant variability in consumptive use along the water axis. Castanhal had the highest level of consumptive use due to its public water supply, which increased in line with population growth between 2000 and 2022 (r = 0.76), in accordance with SDG 6. In the food axis, fishing and aquaculture activities were prevalent in the coastal municipalities of Maracanã and São Caetano de Odivelas (SDGs 2 and 8). In the ecosystem axis, significant deforestation was observed (39.45% to 86.88%), accompanied by low environmental compliance. Regarding the relationship between water and food, only the proportion of rural properties with irrigation and temporary crops showed a significant negative correlation (r = −0.62). The results indicate the consolidation of measures pertaining to water security in the region, exerting a direct influence on food security and strategies employed for the administration of ecosystems imperative for the sustenance of multiple extractive communities in the region. The Nexus approach highlighted various challenges in the region, including poor environmental compliance, overuse of water and forest resources, degraded pastures, and underdeveloped socioeconomic indicators. Full article

Tidal flats play a vital role in coastal ecosystems by supporting biodiversity, mitigating natural hazards, and functioning as blue carbon reservoirs. However, monitoring their geomorphological changes remains challenging due to high turbidity, shallow depths, and tidal variability. Conventional approaches—such as satellite remote sensing, acoustic sounding, and topographic LiDAR—face limitations in resolution, accessibility, or coverage of submerged areas. Airborne bathymetric LiDAR (ABL), which uses green laser pulses to detect reflections from both the water surface and seabed, has emerged as a promising alternative. Unlike traditional discrete-return data, full waveform analysis offers greater accuracy, resolution, and reliability, enabling more flexible point cloud generation and extraction of additional signal parameters. A critical step in ABL processing is waveform decomposition, which separates complex returns into individual components. Conventional methods typically assume fixed models with three returns (water surface, water column, bottom), which perform adequately in clear waters but deteriorate under shallow and turbid conditions. To address these limitations, we propose an adaptive progressive Gaussian decomposition (APGD) tailored to tidal flat environments. APGD introduces adaptive signal range selection and termination criteria to suppress noise, better accommodate asymmetric echoes, and incorporates a water-layer classification module. Validation with datasets from Korea’s west coast tidal flats acquired by the Seahawk ABL system demonstrates that APGD outperforms both the vendor software and the conventional PGD, yielding higher reliability in bottom detection and improved bathymetric completeness. At the two test sites with different turbidity conditions, APGD achieved seabed coverage ratios of 66.7–70.4% and bottom-classification accuracies of 97.3% and 96.7%. Depth accuracy assessments further confirmed that APGD reduced mean depth errors compared with PGD, effectively minimizing systematic bias in bathymetric estimation. These results demonstrate APGD as a practical and effective tool for enhancing tidal flat monitoring and management. Full article

Acoustic emission detection technology is widely employed for leakage detection in water supply systems. However, this approach heavily relies on extensive field data to develop feature extraction and analysis models. Since field data cannot comprehensively cover all operational conditions—such as variations in pressure, pipe diameter, and leakage size—the limited generalization capability of these models often results in high rates of false negatives and false positives. To address these issues, this study utilizes Large Eddy Simulation (LES) to analyze leakage flow fields, establishing correlations between diverse operating conditions and flow field characteristics, including the areas of negative pressure zones and pressure pulsations. Based on these flow field findings, Computational Aeroacoustics (CAA) is applied to analyze the acoustic radiation field at leakage locations, thus clarifying the sound generation mechanisms of leakage-related acoustic signals, demonstrating strong agreement between simulation results and experimental data. Furthermore, wavelet packet energy ratio, centroid frequency, and frequency entropy are extracted as key feature parameters. A leakage detection model based on Support Vector Machine (SVM) is subsequently developed, achieving an accuracy of 98.6% across a wide range of operating conditions. This research enhances the capability for high-accuracy leakage detection with limited field data, offering valuable technical insights for the development of low-computation and low-hardware-cost leakage detection systems. Full article

This paper introduces a novel approach to handwritten digit recognition based on directional flood simulation and topological feature extraction. While traditional pixel-based methods often struggle with noise, partial occlusion, and limited data, our method leverages the structural integrity of digits by simulating water flow from image boundaries using a modified breadth-first search (BFS) algorithm. The resulting flooded regions capture stroke directionality, spatial segmentation, and closed-area characteristics, forming a compact and interpretable feature vector. Additional parameters such as inner cavities, perimeter estimation, and normalized stroke density enhance classification robustness. For efficient prediction, we employ the Annoy approximate nearest neighbors algorithm using ensemble-based tree partitioning. The proposed method achieves high accuracy on the MNIST (95.9%) and USPS (93.0%) datasets, demonstrating resilience to rotation, noise, and limited training data. This topology-driven strategy enables accurate digit classification with reduced dimensionality and improved generalization. Full article

In order to explore the co-evolutionary relationship between the functions of microbial communities and the chemical composition of groundwater in a hyporheic zone affected by groundwater exploitation along riverbank, we have taken the Huangjia water source area on the Liao River main stream in Shenyang as an example. DNA was extracted from microorganisms in the hyporheic zone affected by groundwater exploitation along the riverbank, and we conducted high-throughput sequencing to select the dominant bacterial strains from the indigenous bacteria. They are classified as the Proteobacteria phylum, the Actinobacteria phylum, the Firmicutes phylum, the Bacteroidetes phylum, the Chloroflexi phylum, and the Acidobacteria phylum. The dominant bacteria have a good correlation with Fe, Mn, and environmental factors (such as DO—dissolved oxygen, Eh—oxidation-reduction potential, etc.) in the hyporheic zone. The functions and activities of the superior bacterial strains exhibit a feature of co-evolution with the water’s chemical environment, which has certain response characteristics to redox zoning. Studying the co-evolution relationship between the microbial community structure and function in the hyporheic zone and the chemical composition of the groundwater can provide a microbiological theoretical basis for the redox zonation. It also offers reference for understanding the process of Fe and Mn migration and transformation in the hyporheic zone under the hydrodynamic conditions of groundwater exploitation along the riverbank. Full article