Search Results (3,680)

Accurately monitoring terrestrial water storage (TWS) variations is essential due to global climate change and growing water demands. This study investigates TWS changes in Oregon, USA, using Global Navigation Satellite System (GNSS) data from the Nevada Geodetic Laboratory, Gravity Recovery and Climate Experiment (GRACE) level-3 mascon data from the Jet Propulsion Laboratory (JPL), and Noah model data from the Global Land Data Assimilation System (GLDAS) data. The results show that the GNSS inversion offers superior spatial resolution, clearly capturing a water storage gradient from 300 mm in the Cascades to 20 mm in the basin and accurately distinguishing between mountainous and basin areas. However, the GRACE data exhibit blurred spatial variability, with the equivalent water height amplitude ranging from approximately 100 mm to 145 mm across the study area, making it difficult to resolve terrestrial water storage gradients. Moreover, GLDAS exhibits limitations in mountainous regions. The GNSS can provide continuous dynamic monitoring, with results aligning well with seasonal trends seen in GRACE and GLDAS data, although with a 1–2 months phase lag compared to the precipitation data, reflecting hydrological complexity. Future work may incorporate geological constraints, region-specific elastic models, and regularization strategies to improve monitoring accuracy. This study demonstrates the strong potential of GNSS technology for monitoring TWS dynamics and supporting environmental assessment, disaster warning, and water resource management. Full article

Cities are the growth engines responsible for shaping the global economy, major contributors to climate change, and are significantly affected by it. However, the United Nations adopted the Sustainable Development Goals (SDGs) to make these cities and human settlements inclusive, safe, resilient, and sustainable. Yet, the rapid and unplanned urban expansion exacerbates various environmental challenges and reduces green cover in urban areas. To address these issues and meet the SDGs, stakeholders need to emphasise and optimise urban spaces. This study investigates the borough-level analysis of green spaces and human exposure to green spaces across London using satellite-derived datasets on vegetation and socio-economic factors to examine the variations in urban vegetation cover and urban population exposure to vegetation cover between 2017 and 2024. This study highlights the spatial disparity in green space coverage and exposure to green space between the inner and outer boroughs of London. The methodology used here suggests an average loss of approximately 11 and 9 percent in green space coverage and green space exposure to population, respectively, between 2017 and 2024 across London boroughs. Full article

The Alpine Periglacial Weathering Zone (APWZ) is a critical transitional belt between alpine vegetation and glaciers, and a highly sensitive region to climate change. Its dynamic variations profoundly reflect the surface environment’s response to climatic shifts. Taking Gongga Mountain as the study area, this study utilizes summer Landsat imagery from 1986 to 2024 and constructs a remote sensing method based on NDVI and NDSI indices using the Otsu thresholding algorithm on the Google Earth Engine platform to automatically extract the positions of the upper limit of vegetation and the snowline. Results show that over the past four decades, the APWZ in Gongga Mountain has exhibited a continuous upward shift, with the mean elevation rising from 4101 m to 4575 m. The upper limit of vegetation advanced at an average rate of 17.43 m/a, significantly faster than the snowline shift (3.9 m/a). The APWZ also experienced substantial areal shrinkage, with an average annual reduction of approximately 13.84 km², highlighting the differential responses of various surface cover types to warming. Spatially, the most pronounced changes occurred in high-elevation zones (4200–4700 m), moderate slopes (25–33°), and sun-facing aspects (east, southeast, and south slopes), reflecting a typical climate–topography coupled driving mechanism. In the upper APWZ, glacier retreat has intensified weathering and increased debris accumulation, while the newly formed vegetation zone in the lower APWZ remains structurally fragile and unstable. Under extreme climatic disturbances, this setting is prone to triggering chain-type hazards such as landslides and debris flows. These findings enhance our capacity to monitor alpine ecological boundary changes and identify associated disaster risks, providing scientific support for managing climate-sensitive mountainous regions. Full article

The Jidong Oilfield No. 2 Underground Gas Storage (UGS), located in an active fault zone in Northern China, is a key facility for ensuring natural gas supply and peak regulation in the Beijing–Tianjin–Hebei region. To evaluate the effectiveness of a combined surface and shallow borehole monitoring system under deep reservoir conditions, a 90-day microseismic monitoring trial was conducted over a full injection cycle using 16 surface stations and 1 shallow borehole station. A total of 35 low-magnitude microseismic events were identified and located using beamforming techniques. Results show that event frequency correlates positively with wellhead pressure variations instead of the injection volume, suggesting that stress perturbations predominantly control microseismic triggering. Events were mainly concentrated near the bottom of injection wells, with an average location error of approximately 87.5 m and generally shallow focal depths, revealing limitations in vertical resolution. To enhance long-term monitoring performance, this study recommends deploying geophones closer to the reservoir, constructing a 3D velocity model, applying AI-based phase picking, expanding array coverage, and developing a microseismic-injection coupling early warning system. These findings provide technical guidance for the design and deployment of long-term monitoring systems for deep reservoir conversions into UGS facilities. Full article

Climate change intensifies hydrological cycles, leading to an increased variability in terrestrial water storage anomalies (TWSAs) and a heightened drought risk. Understanding the spatiotemporal dynamics of TWSAs and their driving factors is crucial for sustainable water management. While previous studies have primarily attributed TWSAs to regional factors, this study employs wavelet coherence, partial correlation analysis, and multiple linear regression to comprehensively analyze TWSA dynamics and their drivers in the Hengduan Mountains (HDM) region from 2003 to 2022, incorporating both regional and global influences. Additionally, dry–wet variations were quantified using the GRACE-based Drought Severity Index (GRACE-DSI). Key findings include the following: The annual mean TWSA showed a non-significant decreasing trend (−2.83 mm/y, p > 0.05), accompanied by increased interannual variability. Notably, approximately 36.22% of the pixels in the western HDM region exhibited a significantly decreasing trend. The Nujiang River Basin (NRB) (−17.17 mm/y, p < 0.01) and the Lancang (−17.17 mm/y, p < 0.01) River Basin experienced the most pronounced declines. Regional factors—particularly precipitation (PRE)—drove TWSA in 59% of the HDM region, followed by potential evapotranspiration (PET, 28%) and vegetation dynamics (13%). Among global factors, the North Atlantic Oscillation showed a weak correlation with TWSAs (r = −0.19), indirectly affecting it via winter PET (r = −0.56, p < 0.05). The decline in TWSAs corresponds to an elevated drought risk, notably in the NRB, which recorded the largest GRACE-DSI decline (slope = −0.011, p < 0.05). This study links TWSAs to climate drivers and drought risk, offering a framework for improving water resource management and drought preparedness in climate-sensitive mountain regions. Full article

Using graphs as a data structure is a simple way to represent relationships between objects. Consequently, it has raised the need for algorithms to process, analyze, and extract meaningful information from graphs. Therefore, frequent subgraph mining (FSM) algorithms have been reported in the literature to discover interesting, unexpected, and useful patterns in graph databases. Frequent subgraph mining involves discovering subgraphs that appear no less than a user-specified threshold; this can be performed exactly or approximately. Although several algorithms for mining frequent approximate subgraphs exist, mining this type of subgraph in graph collections has scarcely been addressed. Thus, we propose AGCM-SLV, an algorithm for mining frequent approximate subgraphs within a graph collection that allows structural and label variations. Unlike other FSM approaches, our proposed algorithm tracks subgraph occurrences and their structural dissimilarities, allowing user-defined partial similarities between node and edge labels, and captures frequent approximate subgraphs (patterns) that would otherwise be overlooked. Experiments on real-world datasets demonstrate that our algorithm identifies more patterns than the most similar state-of-the-art algorithm with a shorter runtime. We also present experiments in which we add white noise to the graph collection at different levels, revealing that over 99% of the patterns extracted without noise are preserved under noisy conditions, making the proposed algorithm noise-tolerant. Full article

For the airfoil in freestream, the pressure difference between the upper and lower surfaces and the variations in pressure gradients are significant at its leading edge area. Under reasonable deflections, the active leading edge can effectively change airfoil aerodynamic loads, which helps to improve the rotor aerodynamic performance. In this paper, a modeling method for an airfoil with an active leading edge was developed to calculate its aerodynamic loads. The pitch motion of the rotor blade and the leading edge deflections were taken into account. Firstly, simulations of steady and unsteady flow for the airfoil with an active leading edge were conducted under different boundary conditions and with different leading edge deflection movement. Secondly, the rational function approximation (RFA) was employed to establish the relationship between aerodynamic loads and airfoil/active leading edge deflections. Then, coefficient matrices of the RFA approach were identified based on a limited number of high-fidelity computational fluid dynamics (CFD) results. Finally, an aerodynamic model of the airfoil with an active leading edge was developed, and its accuracy was validated by comparing it to the high-fidelity CFD results. Comparative results reveal that the developed model can calculate the aerodynamic loads of an airfoil with an active leading edge accurately and efficiently when applied appropriately. The modeling method can be used in aerodynamic load calculations and the aeroelastic coupling analysis of a rotor with active control devices. Full article

To investigate the slope instability caused by differential frost heaving mechanisms from the slope crest to the toe during frost heave processes, this study takes a typical silty clay slope in Xinjiang, China, as the research object. Through indoor triaxial consolidated undrained shear tests, eight sets of natural and frost-heaved specimens were prepared under confining pressure conditions ranging from 100 to 400 kPa. The geotechnical parameters of the soil in both natural and frost-heaved states were obtained, and a spatiotemporal thermo-hydro-mechanical coupled numerical model was established to reveal the dynamic evolution law of anchor rod axial forces and the frost heave response mechanism between the frame and slope soil. The analytical results indicate that (1) the frost heave process is influenced by slope boundaries, resulting in distinct spatial variations in the temperature field response across the slope surface—namely pronounced responses at the crest and toe but a weaker response in the mid-slope. (2) Under the coupled drive of the water potential gradient and gravitational potential gradient, the ice content in the toe area increases significantly, and the horizontal frost heave force exhibits exponential growth, reaching its peak value of 92 kPa at the toe in February. (3) During soil freezing, the reverse stress field generated by soil arching shows consistent temporal variation trends with the temperature field. Along the height of the soil arch, the intensity of the reverse frost heave force field displays a nonlinear distribution characteristic of initial strengthening followed by attenuation. (4) By analyzing the changes in anchor rod axial forces during frost heaving, it was found that axial forces during the frost heave period are approximately 1.3 times those under natural conditions, confirming the frost heave period as the most critical condition for frame anchor design. Furthermore, through comparative analysis with 12 months of on-site anchor rod axial force monitoring data, the reliability and accuracy of the numerical simulation model were validated. These research outcomes provide a theoretical basis for the design of frame anchor support systems in seasonally frozen regions. Full article

The U.S. Environmental Protection Agency (EPA) developed the concept of Water Quality Volume (WQv) as a Best Management Practice (BMP) to treat the first 25.4 mm of rainfall in urban areas, aiming to capture approximately 90% of annual runoff. However, applying this urban-based standard—designed for areas with over 50% imperviousness—to rural regions with higher infiltration and pervious surfaces may result in overestimated facility capacities. In Korea, a uniform WQv criterion of 5 mm is applied nationwide, regardless of land use or hydrological conditions. This study examines the suitability of this 5 mm standard in rural catchments using the Hydrological Simulation Program–Fortran (HSPF). Eight sub-watersheds in the target area were simulated under varying cumulative runoff depths (1–10 mm) to assess pollutant loads and runoff characteristics. First-flush effects were most evident below 5 mm, with variation depending on land cover. Nature-based treatment systems for constructed wetlands were modeled for each sub-watershed, and their effectiveness was evaluated using Flow Duration Curves (FDCs) and Load Duration Curves (LDCs). The findings suggest that the uniform 5 mm WQv criterion may result in overdesign in rural watersheds and highlight the need for region-specific standards that consider local land-use and hydrological variability. Full article

The ionospheric response to the major geomagnetic storm (SYM-H = −518 nT) of 10–11 May 2024 was investigated using total electron content (TEC) observations from the Central Asian (CAR) and East Asian (EAR) regions. In the CAR region, shortly after the storm sudden commencement (SC) (17:05 UT on 10 May), during a rapid decrease in SYM-H, a significant TEC decrease (~70%) and a subsequent formation of a prolonged TEC depletion phase on 11 May were observed. The duration of the phase’s maximum intensity seemed to agree with the duration of southward interplanetary magnetic field (IMF) Bz activity. The total duration of the negative phase exceeded 3 days and correlated with the duration of the Auroral Electrojet (AE) index activity. The ionospheric response in the EAR region differed significantly, exhibiting a secondary, deeper TEC decrease (termed “phase 2”) on 12 May, which occurred during a period of reduced AE and IMF Bz activity. The analysis of latitudinal TEC variations in the EAR region revealed that “phase 2” occurred across a geographic latitude range of 31.4° N to 43.9° N (approximately 21° N to 34° N dipole latitude). These results are discussed in the context of potential longitudinal variations in thermospheric composition and meridional circulation during the geomagnetic storm. Full article

This study investigates the influence of cerium nitrate (Ce(NO₃)₃·6H₂O) content on the performance of Ce(III)/CF/BN/EPN coatings intended for heat exchangers. A series of Ce(III)/carbon fibre (CF)/boron nitride (BN)/epoxy phenolic (EPN) coatings are fabricated with varying concentrations of Ce(NO₃)₃·6H₂O. The results of SEM and EDS show that the dissolution of cerium nitrate in acetone due to the particulate form causes it to be distributed in a diffuse state in the coating. This diffuse distribution does not significantly alter the porosity or structural morphology of the coating. With the increase in cerium nitrate content, both the EIS test results and mechanical damage tests indicate a progressive improvement in the corrosion resistance and self-healing properties of the coatings, while the thermal conductivity (TC) remains largely unaffected. The Ce in the coating reacts with the water molecules penetrating into the coating to generate Ce₂O₃ and CeO₂ with protective properties to fill the permeable pores inside the coating or to form a passivation film at the damaged metal–coating interface, which enhances the anticorrosive and self-repairing properties of the coating. However, the incorporation of Ce(NO₃)₃·6H₂O does not change the distribution structure of the filler inside the coating. As a result, the phonon propagation path, rate, and distance remain unchanged, leading to negligible variation in the thermal conductivity. Therefore, at a cerium nitrate content of 2.5 wt%, the coating exhibits the best overall performance, characterised by a |Z|_0.1Hz value of 6.08 × 10⁹ Ω·cm² and a thermal conductivity of approximately 1.4 W/(m·K). Full article

Over the past few decades, occurrences of extreme climatic events have escalated significantly, with severe repercussions for global ecosystems and socio-economics. northern China (NC), characterized by its complex topography and diverse climatic conditions, represents a typical ecologically vulnerable region where vegetation is highly sensitive to climate change. Therefore, monitoring vegetation dynamics and analyzing the influence of extreme climatic events on vegetation are crucial for ecological conservation efforts in NC. Based on extreme climate indicators and the Normalized Difference Vegetation Index (NDVI), this study employed trend analysis, Ensemble Empirical Mode Decomposition, all subsets regression analysis, and random forest to quantitatively investigate the spatiotemporal variations in historical and projected future NDVI trends in NC, as well as their responses to extreme climatic conditions. The results indicate that from 1982 to 2018, the NDVI in NC generally exhibited a recovery trend, with an average growth rate of 0.003/a and a short-term variation cycle of approximately 3 years. Vegetation restoration across most areas was primarily driven by short-term high temperatures and long-term precipitation patterns. Future projections under different emission scenarios (SSP245 and SSP585) suggest that extreme climate change will continue to follow historical trends. However, increased radiative forcing is expected to constrain both the rate of vegetation growth and its spatial expansion. These findings provide a scientific basis for mitigating the impacts of climate anomalies and improving ecological quality in NC. Full article

Gearbox failure represents one of the most time-consuming maintenance challenges in wind turbine operations. Abnormal temperature variations in the gearbox high-speed shaft (GHSS) serve as reliable indicators of potential faults. This study proposes a Spatio-Temporal Attentive (STA) synergistic architecture for GHSS fault detection and early warning by utilizing the in situ monitoring data from a wind farm. This comprehensive architecture involves five modules: data preprocessing, multi-dimensional spatial feature extraction, temporal dependency modeling, global relationship learning, and hyperparameter optimization. It was achieved by using real-time monitoring data to predict the GHSS temperature in 10 min, with an accuracy of 1 °C. Compared to the long short-term memory (LSTM) and convolutional neural network and LSTM hybrid models, the STA architecture reduces the root mean square error of the prediction by approximately 37% and 13%, respectively. Furthermore, the architecture establishes a normal operating condition model and provides benchmark eigenvalues for subsequent fault warnings. The model was validated to issue early warnings up to seven hours before the fault alert is triggered by the supervisory control and data acquisition system of the wind turbine. By offering reliable, cost-effective prognostics without additional hardware, this approach significantly improves wind turbine health management and fault prevention. Full article

Peste des petits ruminants virus (PPRV) has been classified into four lineages based on the nucleocapsid and fusion genes, with lineage IV strains being the most widely distributed. In Africa, recent epidemiological data revealed that PPRV lineage IV is increasingly displacing other lineages in prevalence, suggesting a competitive advantage in viral transmission and adaptability. Moreover, a lineage IV strain was the only confirmed strain in Europe and Asia. In this study, a one-step Taqman quantitative real-time reverse transcription polymerase chain reaction (RT-qPCR) assay for lineage IV PPRV was established by targeting the hemagglutinin (H) gene. The results indicated that this method could detect approximately six copies of PPRV RNA, indicating high sensitivity. No cross-reactions with related viruses or other lineages of PPRV were observed. The results of a repeatability test indicated that the coefficient of variation values were low in both the inter-assay and intra-assay experimental groups. Detection of field samples indicated that all positive samples could be detected successfully using the developed method. This RT-qPCR assay provides a valuable tool to facilitate targeted surveillance and rapid differential diagnosis in regions with active circulation of PPRV lineage IV, enabling timely epidemiological investigations and strain-specific identification. Full article

Sperm membrane potential (Em) hyperpolarization during capacitation is a functional hallmark of fertilizing ability and has been proposed as a predictive biomarker for conventional in vitro fertilization (IVF) success. However, it is unclear whether Em remains stable across ejaculates over time and can reliably guide assisted reproductive technology (ART) decisions in advance. Thus, we aimed to evaluate the temporal consistency of human sperm Em within individuals and assess its utility as a prognostic marker when measured days or weeks prior to IVF procedures. Em was assessed in capacitated and non-capacitated sperm from normospermic donors at three time points over 28 days, using a fluorometric assay. Capacitated values were compared to a −48.6 mV threshold previously associated with successful fertilization. Intra-donor Em variability and coefficients of variation (CV) were analyzed statistically. Our results showed that Em values exhibited significant intra-donor variability over time (p = 0.007), with approximately half of the donors crossing the −48.6 mV functional threshold across sessions. Capacitated sperm samples showed significantly greater variability than non-capacitated ones, with several donors exceeding a 30% CV cutoff. No consistent correlation was found between CV and mean Em values. While Em remains a promising functional marker when assessed on the day of IVF, its temporal variability undermines its reliability as a predictive tool for ART decisions made in advance. These findings underscore the importance of timing in functional sperm assessments and call for further studies to identify the physiological factors influencing Em stability. Full article