Search Results (409)

Fixed automated (unmanned) above-water radiometric measurements are subject to unavoidable sky conditions and surface perturbations, leading to significant uncertainties in retrieved water surface remote sensing reflectances (R_rs(λ), sr⁻¹). This study evaluates various above-water R_rs(λ) glint correction methods using a comprehensive dataset collected at the Royal Netherlands Institute for Sea Research (NIOZ) Jetty Station located in the Marsdiep tidal inlet of the Dutch Wadden Sea, the Netherlands. The dataset includes in-situ water constituent concentrations (2006–2020), inherent optical properties (IOPs) (2006–2007), and above-water hyperspectral (ir)radiance observations collected every 10 min (2006–2023). The bio-optical models were validated using in-situ IOPs and utilized to generate glint-free remote sensing reflectances, R_rs,ref(λ), using a robust IOP-to-R_rs forward model. The R_rs,ref(λ) spectra were used as a benchmark to assess the accuracy of glint correction methods under various environmental conditions, including different sun positions, wind speeds, cloudiness, and aerosol loads. The results indicate that the three-component reflectance model (3C) outperforms other methods across all conditions, producing the highest percentage of high-quality R_rs(λ) spectra with minimal errors. Methods relying on fixed or lookup-table-based glint correction factors exhibited significant errors under overcast skies, high wind speeds, and varying aerosol optical thickness. The study highlights the critical importance of surface-reflected skylight corrections and wavelength-dependent glint estimations for accurate above-water R_rs(λ) retrievals. Two showcases on chlorophyll-a and total suspended matter retrieval further demonstrate the superiority of the 3C model in minimizing uncertainties. The findings highlight the importance of adaptable correction models that account for environmental variability to ensure accurate R_rs(λ) retrieval and reliable long-term water quality monitoring from hyperspectral radiometric measurements. Full article

This study was realized in the frame of an IAEA Coordinated Research Project for the evaluation of sediment dynamics, applying in-situ radiometric methods accompanied with a theoretical model. The in-situ methods were validated using lab-based high-resolution gamma-ray spectrometry. Sediment dynamics assessments were performed based on the measured and mapped activity concentrations of specific ²³⁸U progenies (²¹⁴Bi or ²¹⁴Pb), ²³²Th progenies (²⁰⁸Tl and ²²⁸Ac), and ⁴⁰K along the shoreline of the beach. The maps of the activity concentrations of natural radionuclides were produced rapidly using software tools (R language v4.5). The sediment dynamics of the studied area were also investigated through numerical simulations, applying an open source model considering land–sea interactions and meteorological conditions and the corresponding sediment processes. The assessments, which were conducted utilizing the detailed data from the natural radioactivity maps, were validated by the simulation results, since both were found to be in agreement. Generally, it was confirmed that the distribution of radionuclides reflects the selective transport processes of sediments, which are related to the corresponding processes that occur in the study area. Legrena Beach in Attica, Greece, served as a pilot area for the comparative analysis of methods and demonstration of their relevance and applicability for studying coastal processes. Full article

Recent catastrophic bridge fire incidents have highlighted the critical need for effective post-fire assessment of bridges, thereby challenging the dominant practice of complete replacement following these destructive events. This study investigates the post-fire performance of bare, isolated, and Carbon Fiber Reinforced Polymer (CFRP)-repaired Reinforced Concrete (RC) bridge columns under single-unit truck impact followed by air blast. This extreme loading scenario was deliberately selected given the increased vulnerability of bridge columns to this loading scenario in the recent few years. Three-dimensional Finite Element (FE) models of the structural system and surrounding environment were developed and validated in LS-DYNA. The effectiveness of two in-situ retrofitting schemes in mitigating damage and enhancing structural integrity of three column diameters under the selected multi-hazards was assessed. Results demonstrated that wrapping the bottom half of the column height prevents shear failure and significantly reduces the damage under the coupled impact and blast. In contrast, employing a combination of CFRP bars and externally bonded sheets showed limited enhancement on post-fire impact and blast performance. This study provides critical insights into the feasibility and efficacy of retrofitting bridge columns that have experienced fire, thus laying the groundwork for the reconsideration of current design and rehabilitation protocols. Full article

Hyperspectral remote sensing is crucial due to its continuous spectral information, especially in the quantitative remote sensing (QRS) field. Surface reflectance (SR), a fundamental product in QRS, can play a pivotal role in application accuracy and serves as a key indicator of sensor performance. However, the distinctive spectral characteristics of a hyperspectral image (HSI) make it particularly susceptible to noise during the process of imaging, which inevitably degrades data quality and reduces SR accuracy. Moreover, the validation of hyperspectral SR faces challenges due to the scarcity of reliable validation data. To address these issues, aiming at fast and efficient processing of Chinese domestic ZY1-02D hyperspectral level-1 data, this study proposes a comprehensive processing framework: (1) To address the low efficiency of traditional bad line detection by visual examination, an automatic bad line detection method based on the pixel grayscale gradient threshold algorithm is proposed; (2) A spectral correlation-based interpolation method is developed to overcome the poor performance of adjacent-column averaging in repairing wide bad lines; (3) A reliable validation method was established based on the spectral band adjustment factors method to compare hyperspectral SR with multispectral SR and in-situ ground measurements. The results and analysis demonstrate that the proposed method improves the accuracy of ZY1-02D SR and the method ensures high processing efficiency, requiring only 5 min per scene of ZY1-02D HSI. This study provides a technical foundation for the application of ZY1-02D HSIs and offers valuable insights for the development and enhancement of next-generation hyperspectral sensors. Full article

Colorectal cancer (CRC) progression occurs through three stages: adenoma (pre-cancerous lesion), carcinoma in situ (CIS) and adenocarcinoma, with tumor stage playing a pivotal role in the prognosis and treatment outcomes. Despite therapeutic advancements, the lack of stage-specific biomarkers hinders the development of accurate diagnostic tools and effective therapeutic strategies. This study aims to identify stage-specific gene expression profiles and key molecular mechanisms in CRC providing insights into molecular alterations across disease progression. Our methodological approach integrates the use of absolute gene set enrichment analysis (absGSEA) on formalin-fixed paraffin-embedded (FFPE)-derived transcriptomic data, combined with large-scale clinical validation and experimental confirmation. A comparative whole transcriptomic analysis (RNA-seq) was performed on FFPE samples including adenoma (n = 10), carcinoma in situ (CIS) (n = 8) and adenocarcinoma (n = 11) samples. Using absGSEA, we identified significant cellular pathways and putative molecular biomarkers associated with each stage of CRC progression. Key findings were then validated in a large independent CRC patient cohort (n = 1926), with survival analysis conducted from 1336 patients to assess the prognostic relevance of the candidate biomarkers. The key differentially expressed genes were experimentally validated using real-time PCR (RT-qPCR). Pathway analysis revealed that in CIS, apoptotic processes and Wnt signaling pathways were more prominent than in adenoma samples, while in adenocarcinoma, transcriptional co-regulatory mechanisms and protein kinase activity, which are critical for tumor growth and metastasis, were significantly enriched compared to adenoma. Additionally, extracellular matrix organization pathways were significantly enriched in adenocarcinoma compared to CIS. Distinct gene signatures were identified across CRC stages that differentiate between adenoma, CIS and adenocarcinoma. In adenoma, ARRB1, CTBP1 and CTBP2 were overexpressed, suggesting their involvement in early tumorigenesis, whereas in CIS, RPS3A and COL4A5 were overexpressed, suggesting their involvement in the transition from benign to malignant stage. In adenocarcinoma, COL1A2, CEBPZ, MED10 and PAWR were overexpressed, suggesting their involvement in advanced disease progression. Functional analysis confirmed that ARRB1 and CTBP1/2 were associated with early tumor development, while COL1A2 and CEBPZ were involved in extracellular matrix remodeling and transcriptional regulation, respectively. Experimental validation with RT-qPCR confirmed the differential expression of the candidate biomarkers (ARRB1, RPS3A, COL4A5, COL1A2 and MED10) across the three CRC stages reinforcing their potential as stage-specific biomarkers in CRC progression. These findings provide a foundation to distinguish between the CRC stages and for the development of accurate stage-specific diagnostic and prognostic biomarkers, which helps in the development of more effective therapeutic strategies for CRC. Full article

The reserves of hot dry rock (HDR) geothermal resources are huge. The main method used to develop HDR geothermal resources is called an enhanced geothermal system (EGS), and this generally uses hydraulic fracturing. After nearly 50 years of research and development, more and more countries have joined the ranks engaged in the exploration and development of HDR in the world. This paper summarizes the base technologies, key technologies, and game-changing technologies used to promote the commercialization of HDR geothermal resources. According to the present situation of the exploration, development, and utilization of HDR at home and abroad, the evaluation and site selection, efficient and low-cost drilling, and geothermal utilization of HDR geothermal resources are defined as the base technologies. Key technologies include the high-resolution exploration and characterization of HDR, efficient and complex fracture network reservoir creation, effective microseismic control, fracture network connectivity, and reservoir characterization. Game-changing technologies include downhole liquid explosion fracture creation, downhole in-situ efficient heat transfer and power generation, and the use of CO₂ and other working fluids for high-efficient power generation. Most of the base technologies already have industrial applications, but future efforts must focus on reducing costs. The majority of key technologies are still in the site demonstration and validation phase and have not yet been applied on an industrial scale. However, breakthroughs in cost reduction and application effectiveness are urgently needed for these key technologies. Game-changing technologies remain at the laboratory research stage, but any breakthroughs in this area could significantly advance the efficient development of HDR geothermal resources. In addition, we conducted a comparative analysis of the respective advantages of China and the United States in some key technologies of HDR development. On this basis, we summarized the key challenges identified throughout the discussion and highlighted the most pressing research priorities. We hope these technologies can guide new breakthroughs in HDR geothermal development in China and other countries, helping to establish a batch of HDR exploitation demonstration areas. In addition, we look forward to fostering collaboration between China and the United States through technical comparisons, jointly promoting the commercial development of HDR geothermal resources. Full article

The valuation of the benefits to humans of ecosystem services (ESs) provided by nature has become increasingly important. A current challenge is the measurement of the range of benefits which are not traded in the marketplace and are generally considered intangible, with further challenges to even classify them formally, e.g., as cultural ecosystem services (CESs). Previous studies have emphasized a related challenge: the strong need for engagement of not just experts but ’ordinary people’. Approaches using participatory approaches and less formal communication pathways to draw out local CES values have been reported. However, critical reflections of those studies reported significant differences in understanding between ’outsider researchers’ and ’locals’, calling validity deeply into question. Even deliberative approaches backfired by significantly modifying local social constructs during elicitation. In this study, we demonstrate a fundamentally different kind of approach, developed from the bottom–up sustainability indicator development process called WeValue InSitu. It focuses not on improving deeper top–down ‘engagement’ of a specific topic, but instead on improving local articulation of existing envelopes of in situ human shared values, naturally integrated. The WeValue InSitu output is a framework of separate but interlinked concise Statements of local shared values. Some of these Statements may refer to values concerning ecosystems, but situated amongst others. Here, we analyze the outputs from 23 convenience groups in three sites in Nigeria and investigate the shared values found empirically against existing economics-based MEA classifications. The findings include hybrid values which span existing CES sub-categories and even across into market-based categories. This opens a discussion as to whether future ES valuation frameworks might evolve more usefully with foundations built on empirically derived typologies of human values, rather than bolt-on modifications to financially based economics concepts. It also raises questions about the validity of current valuations made which cannot capture empirically found human values. Full article

The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is one of the most urbanized and industrialized coastal regions in China, where intense human activities contribute to substantial terrestrial sediment discharge into the adjacent marine environment. However, complex hydrodynamic conditions and high spatiotemporal variability pose challenges for accurate suspended sediment concentration (SSC) retrieval. Developing water quality retrieval models based on different classifications of water bodies could enhance the accuracy of SSC inversion in coastal waters. Therefore, this study classified the coastal waters of the GBA into clear and turbid zones based on Hue angle α, and established retrieval models for SSC using a single-scattering approximation model for clear zones and a secondary-scattering approximation model for turbid zones based on radiative transfer processes. Model validation with in-situ data shows a coefficient of determination (R²) of 0.73, a root mean square error (RMSE) of 8.30, and a mean absolute percentage error (MAPE) of 42.00%. Spatial analysis further reveals higher SSC in the waters around Qi’ao Island in the Pearl River Estuary (PRE) and along the coastline of Guanghai Bay, identifying these two areas as priorities for attention. This study aims to offer valuable insights for SSC management in the coastal waters of the GBA. Full article

Industrially applied bioelectrochemical systems require long-term stable operation, and hence the control of biofilm accumulation on the electrodes. An optimized application of biofilm control mechanisms presupposes on-line, in-situ monitoring of the accumulated biofilm. Heat transfer sensors have successfully been integrated into industrial systems for on-line, non-invasive monitoring of biofilms. In this study, a mathematical model for the description of the sensitivity of a heat transfer biofilm sensor was developed, incorporating the hydrodynamic conditions of the fluid and the geometrical properties of the substratum. This model was experimentally validated at different flow velocities by integrating biofilm sensors into cylindrical pipes and planar mesofluidic flow cells with a carbonaceous substratum. Dimensionless sensor readings were correlated with the mean biovolume measured gravimetrically, and optical coherence tomography was used to determine the sensors’ sensitivity. The biofilm sensors applied in the planar flow cells revealed an increase in sensitivity by a factor of 6 compared to standard stainless steel pipes, as well as improved sensitivity at higher flow velocities. Full article

Arsenic contamination in groundwater threatens public health, particularly in small, low-income communities lacking affordable treatment solutions. This study investigated the field implementation of novel air cathode assisted iron electrocoagulation (ACAIE) technology for arsenic removal in Allensworth, California, where groundwater arsenic concentrations exceeded 250 µg/L. Over four months, a pilot-scale ACAIE system, operating at 600 L/h, consistently reduced arsenic levels to below the EPA’s maximum contaminant level of 10 µg/L. Laboratory experiments informed the optimization of charge dosage and flow rates, which were validated during field testing of the ACAIE 600 L/h system. The in-situ generation of hydrogen peroxide at the cathode speeded up the reaction kinetics, ensuring high arsenic removal efficiency while allowing high throughput, even with a compact reactor size. An economic analysis demonstrated a treatment cost of USD 0.02/L excluding labor, highlighting the system’s affordability compared to conventional methods. Adding labor costs increased the treatment cost to USD 0.09/L. The regeneration of air cathodes extended their operational life, addressing a key maintenance challenge, thus reducing the costs slightly. Intermittent challenges were encountered with filtration and secondary contaminant removal; these issues highlight opportunities for further operational improvements. Despite these challenges, ACAIE’s low operational complexity, scalability, and cost-effectiveness make it a promising solution for underserved small communities. These findings provide critical insights into deploying sustainable arsenic remediation technologies that are tailored to the needs of rural, low-resource communities. Full article

Coastal zones, particularly sandy beaches, are highly dynamic environments subject to a variety of natural and anthropogenic forcings. Instantaneous shoreline is a widely used indicator of beach changes in image-based applications, and it can display undulations at different spatial and temporal scales. Megacusps, periodic seaward and landward shoreline perturbations, are an example of such undulations that can significantly modify beach width and impact its usability. Traditionally, the study of these phenomena relied on video monitoring systems, which provide high-frequency imagery but limited spatial coverage. Instead, this study explored the potential of employing multispectral satellite-derived shorelines, specifically from Sentinel-2 (S2) and PlanetScope (PLN) platforms, for characterizing and monitoring megacusps’ formation and their dynamics over time. First, a tool was developed and validated to guarantee accurate shoreline detection, based on a combination of spectral indices, along with both thresholding and unsupervised clustering techniques. Validation of this shoreline detection phase was performed on three micro-tidal Mediterranean beaches, comparing with high-resolution orthomosaics and in-situ GNSS data, obtaining a good subpixel accuracy (with a mean absolute deviation of 1.5–5.5 m depending on the satellite type). Second, a tool for megacusp characterization was implemented and subsequent validation with reference data proved that satellite-derived shorelines could be used to robustly and accurately describe megacusps. The methodology could not only capture their amplitude and wavelength (of the order of 10 and 100 m, respectively) but also monitor their weekly–daily evolution using different potential metrics, thanks to combining S2 and PLN imagery. Our findings demonstrate that multispectral satellite imagery provides a viable and scalable solution for monitoring shoreline megacusp undulations, enhancing our understanding and offering an interesting option for coastal management. Full article

The degree of rock mass discontinuity is crucial for evaluating surrounding rock quality, yet its accurate and rapid measurement at construction sites remains challenging. This study utilizes fractal dimension to characterize the geometric characteristics of rock mass discontinuity and develops a data-driven surrounding rock classification (SRC) model integrating machine learning algorithms. Initially, the box-counting method was introduced to calculate the fractal dimension of discontinuity from the excavation face image. Subsequently, crucial parameters affecting surrounding rock quality were analyzed and selected, including rock strength, the fractal dimension of discontinuity, the discontinuity condition, the in-situ stress condition, the groundwater condition, and excavation orientation. This study compiled a database containing 246 railway and highway tunnel cases based on these parameters. Then, four SRC models were constructed, integrating Bayesian optimization (BO) with support vector machine (SVM), random forest (RF), adaptive boosting (AdaBoost), and gradient boosting decision tree (GBDT) algorithms. Evaluation indicators, including 5-fold cross-validation, precision, recall, F1-score, micro-F1-score, macro-F1-score, accuracy, and the receiver operating characteristic curve, demonstrated the GBDT-BO model’s superior robustness in learning and generalization compared to other models. Furthermore, four additional excavation face cases validated the intelligent SRC approach’s practicality. Finally, the synthetic minority over-sampling technique was employed to balance the training set. Subsequent retraining and evaluation confirmed that the imbalanced dataset does not adversely affect SRC model performance. The proposed GBDT-BO model shows promise for predicting surrounding rock quality and guiding dynamic tunnel excavation and support. Full article

Ice–water interaction is a critical issue of engineering studies in polar regions. This paper proposes a methodology to simulate fluid–ice interactions by employing a structure modeled using ordinary state-based peridynamics (OSB-PD) within a smoothed particle hydrodynamics (SPH) framework, effectively representing a deformable moving boundary. The forces at the fluid–structure interface are delineated by solving the fluid motion equations for normal forces exerted by the fluid on the structure, grounded in the momentum conservation law. Upon validating the PD and SPH methods, a dam break flowing through an elastic gate was simulated. When compared with experimental results, the model exhibited discrepancies of 3.8%, 0.5%, and 4.6% in the maximum horizontal displacement, maximum vertical displacement, and the waterline deviation (W = 0.05 m), respectively. Moreover, the method demonstrated a high degree of accuracy in simulating the fracture of in-situ cantilever ice beams, with deflection closely matching experimental data and a 7.4% error in maximum loading force. The proposed PD-SPH coupling approach demonstrates its effectiveness in capturing the complex fluid–structure interactions and provides a valuable tool for studying the deformation and fracture of structures under the influence of fluid forces. Full article

This paper proposes an efficient productivity-aware optimization framework that utilizes hybrid machine learning with parallel global search to timely and appropriately adjust the critical control parameters (CCPs) of a cutter suction dredger (CSD) during construction. This optimization framework consists of three main parts. First, a hybrid Jaya–multilayer perceptron (MLP) algorithm was developed to rapidly construct a model that captures the interaction between construction parameters and slurry concentration. Next, the preliminary coarse results for the CCPs are determined through multi-parameter sensitivity analysis. Finally, the proposed resilient-zone parallel global search algorithm was employed to further optimize the CCPs, yielding more precise optimization results. To validate the proposed optimization framework and implement the in-situ service, it is applied to a real-world case study involving “Tianda” CSD construction. The results demonstrated that the average optimization duration is 6.7 s, which is shorter than the data acquisition interval of 8 s. Our approach improves the computational efficiency by 9.4 times compared with traditional optimization control methods. Additionally, there is a significant increase in the slurry concentration, with the maximum growth rate reaching 81.64%. Full article

Trophic state index (TSI) is a critical ecological and environmental issue in water resource management that has garnered significant attention. Given the complexity of optical characteristics in aquatic environments, this study employs fuzzy classification methods (FCM) and composite nutrient status indices to meticulously classify in-situ remote sensing reflectance data, aiming to develop evaluation models for different nutrient status categories to facilitate the assessment of the Daihai River in Inner Mongolia, China. Subsequently, we applied this model to MSI data to analyze the nutrient status of Daihai Lake from 2016 to 2021. Furthermore, a structural equation model (SEM) was utilized to explore the primary driving factors influencing nutrient status. The results indicated that the water bodies in Daihai Lake can be broadly classified into three categories, with the nutrient status models demonstrating robust performance for each category (R² = 0.80, R² = 0.83, and R² = 0.74). Comparisons were made between nutrient status accuracies obtained through the NCM and FCM based on measured data, yielding R² values of 0.74 and 0.85, respectively. Furthermore, the TSI results derived from MSI inversion were validated, with NCM achieving an R² of 0.49, RMSE of 6.88, and MAPE of 10.36%, while FCM exhibited an R² of 0.55, RMSE of 8.89, and MAPE of 13.18%. An SEM–based analysis revealed that over the long term, human activities exerted a more substantial impact on eutrophication in Daihai Lake, while climatic factors played an accelerating and reinforcing role. These results are consistent with prior research in the Daihai area, indicating a state of mild eutrophication and the potential of the fuzzy classification method and comprehensive trophic status index method in eutrophication assessment. Full article