Search Results (250)

This study proposes an intelligent patrol planning framework that leverages reinforcement learning, spatiotemporal crime forecasting, and simulated sensor telemetry to optimize autonomous vehicle (AV) navigation in urban environments. Crime incidents from Washington DC (2024–2025) and Seattle (2008–2024) are modeled as a dynamic spatiotemporal graph, capturing the evolving intensity and distribution of criminal activity across neighborhoods and time windows. The agent’s state space incorporates synthetic AV sensor inputs—including fuel level, visual anomaly detection, and threat signals—to reflect real-world operational constraints. We evaluate and compare three learning strategies: Deep Q-Network (DQN), Double Deep Q-Network (DDQN), and Proximal Policy Optimization (PPO). Experimental results show that DDQN outperforms DQN in convergence speed and reward accumulation, while PPO demonstrates greater adaptability in sensor-rich, high-noise conditions. Real-map simulations and hourly risk heatmaps validate the effectiveness of our approach, highlighting its potential to inform scalable, data-driven patrol strategies in next-generation smart cities. Full article

As a key tropospheric photochemical pollutant, ground-level ozone (O₃) poses significant threats to ecosystems through its strong oxidative capacity. With China’s rapid industrialization and urbanization, worsening O₃ pollution has emerged as a critical environmental concern. This study examines O₃’s impacts on forest ecosystems in Southwestern China (Yunnan, Guizhou, Sichuan, and Chongqing), which harbors crucial forest resources. We analyzed high-resolution monitoring data from over 200 stations (2019–2023), employing spatial interpolation to derive the regional maximum daily 8 h average O₃ (MDA8-O₃, ppb) and accumulated O₃ exposure over 40 ppb (AOT40) metrics. Through AOT40-based exposure–response modeling, we quantified the forest relative yield losses (RYL), economic losses (ECL) and ECL/GDP (GDP: gross domestic product) ratios in this region. Our findings reveal alarming O₃ increases across the region, with a mean annual MDA8-O₃ anomaly trend of 2.4% year⁻¹ (p < 0.05). Provincial MDA8-O₃ anomaly trends varied from 1.4% year⁻¹ (Yunnan, p = 0.059) to 4.3% year⁻¹ (Guizhou, p < 0.001). Strong correlations (r > 0.85) between annual RYL and annual MDA8-O₃ anomalies demonstrate the detrimental effects of O₃ on forest biomass. The RYL trajectory showed an initial decline during 2019–2020 and accelerated losses during 2020–2023, peaking at 13.8 ± 6.4% in 2023. Provincial variations showed a 5-year averaged RYL ranging from 7.10% (Chongqing) to 15.85% (Yunnan). O₃ exposure caused annual ECL/GDP averaging 4.44% for Southwestern China, with Yunnan suffering the most severe consequences (ECL/GDP averaging 8.20%, ECL averaging CNY 29.8 billion). These results suggest that O₃-driven forest degradation may intensify, potentially undermining the regional carbon sequestration capacity, highlighting the urgent need for policy interventions. We recommend enhanced monitoring networks and stricter control methods to address these challenges. Full article

The Moxi area in the Sichuan Basin hosts abundant deep geothermal resources, but their thermal regime and accumulation mechanisms remain poorly understood. Using 2D/3D seismic data, drilling records, and temperature measurements (DST), we analyze deep thermal fields, reservoir–caprock systems, and structural features. The following are our key findings: (1) Heat transfer is conduction-dominated, with thermal anomalies in Late Permian–Early Cambrian strata. Four mudstone/shale caprocks and three carbonate reservoirs occur, with the Longtan Formation as the key seal. Reservoir geothermal gradients (25.05–32.55 °C/km) exceed basin averages. (2) Transtensional strike-slip faults form E-W/NE/NW networks; most terminate at the Permian Longtan Formation, with few extending into the Lower Triassic while penetrating the Archean–Lower Proterozoic basement. (3) Structural highs positively correlate with higher geothermal gradients. (4) The deep geothermal reservoirs and thermal accumulation mechanisms in the Moxi area are jointly controlled by crustal thinning, basement uplift, and structural architecture. Mantle-derived heat converges at basement uplift cores, generating localized thermal anomalies. Fault networks connect these deep heat sources, facilitating upward fluid migration. Thick Longtan Formation shale seals these rising thermal fluids, causing anomalous heating in underlying strata and concentrated thermal accumulation in reservoirs—enhanced by thermal focusing effects from uplift structures. This study establishes a theoretical framework for target selection and industrial-scale geothermal exploitation in sedimentary basins, highlighting the potential for repurposing oil/gas infrastructure. Full article

DNA is inherently unstable and is susceptible to damage from both endogenous sources (such as reactive oxygen species) and exogenous factors (including UV, ionizing radiation, and chemicals). The accumulation of DNA damage manifests as genetic mutations, chromosomal instability, and the stalling of DNA replication and transcription processes. Accumulated DNA damage influences apoptosis and cell cycle checkpoints, serving as one of the key triggers for the manifestation of the senescent phenotype. Both aging and cancer are associated with the accumulation of mutations in somatic cells. Disruption of cell cycle control and uncontrolled proliferation are fundamental characteristics of any cancer cell, with the majority of anticancer drugs acting as inhibitors of cyclin-dependent kinases, thereby inducing a transition of cells into a senescent state. Consequently, disturbances in the dynamics and regulation of inflammatory responses, oxidative stress, cell proliferation, DNA damage repair, and epigenetic anomalies, along with the influence of retroviruses and transposons, lead to the accumulation of senescent cells within the human body, characterized by blocked replication and cell cycle, as well as a distinct secretory phenotype. The age-related or disease-associated accumulation of these senescent cells significantly alters the physiology of tissues and the organism as a whole. Many secondary metabolites of higher plants exhibit senolytic and senomorphic activities, although most of them are not fully characterized. In this review, we will explore the principal signaling pathways in mammalian cells that govern the cell cycle and cellular senescence, with a particular emphasis on how their dynamics, expression, and regulation have been modified through the application of senotherapeutic compounds. The second section of the review will identify key target genes for the metabolic engineering, primarily aimed at enhancing the accumulation of plant secondary metabolites with potential therapeutic benefits. Lastly, we will discuss the rationale for utilizing liver cells as a model system to investigate the effects of senolytic compounds on human physiology and health, as well as how senotherapeutic substances can be leveraged to improve gene therapy approaches based on CRISPR/Cas9 and prime-editing technologies. Full article

Anomaly detection methods for industrial control networks using multivariate time series usually adopt deep learning-based prediction models. However, most of the existing anomaly detection research only focuses on evaluating detection performance and rarely explains why data is marked as abnormal and which physical components have been attacked. Yet, in many scenarios, it is necessary to explain the decision-making process of detection. To address this concern, we propose an interpretable method for an anomaly detection model based on gradient optimization, which can perform batch interpretation of data without affecting model performance. Our method transforms the interpretation of anomalous features into solving an optimization problem in a normal “reference” state. In the selection of important features, we adopt the method of multiplying the absolute gradient by the input to measure the independent effects of different dimensions of data. At the same time, we use KSG mutual information estimation and multivariate cross-correlation to evaluate the relationship and mutual influence between different dimensional data within the same sliding window. By accumulating gradient changes, the interpreter can identify the attacked features. Comparative experiments were conducted on the SWAT and WADI datasets, demonstrating that our method can effectively identify the physical components that have experienced anomalies and their changing trends. Full article

Wire Arc Additive Manufacturing (WAAM), a specific type of Directed Energy Deposition (DED) additive manufacturing, has recently gained widespread attention for manufacturing industrial components. WAAM has many advantages compared to other metal AM processes such as powder bed fusion. It is not only cost-efficient and easily accessible, but also capable of manufacturing large-scale industrial components in a short period of time. However, due to the inherent layered nature of the process and significant heat accumulation, parts can experience severe warping, often leading to part rejection. Predicting these anomalies prior to manufacturing would allow for process parameter adjustments to reduce or eliminate residual stresses and large deformations. In this study, we develop a simulation-based model capable of accurately predicting final deformations and unintended warpages. A Johnson–Cook plasticity model with isotropic hardening is implemented through a UMAT user subroutine in Abaqus. The proposed model is then utilized to predict the residual stresses and deformations in WAAM-fabricated parts. Simple wall geometries with 4, 8, and 20 layers deposited on build plates of varying thicknesses, are tested to assess the performance of the model. Combined Johnson–Cook plasticity and isotropic hardening for the WAAM process were implemented for the first time in this study, and the model was validated against experimental data, showing a maximum deviation of 4%. Thermal analysis of a four-layer-high wall took 12 min, while structural analysis using the proposed model took 1 h and 40 min. In comparison, thermo-mechanical analysis of the same geometry reported in the literature takes 14 h. The results demonstrate that the proposed model is not only highly accurate in predicting warpage but also significantly faster than other methodologies reported in the literature. Full article

Underground longwall mining conducted in the vicinity of the barrier pillars in the KWK ROW Ruch Marcel mine has led to volume changes in the rock mass. As the longwalls progressed, a gradual increase in stress occurred in the goaf overburden, as a result of which this part of the rock mass increased in density in relation to the surrounding strata. Seismic events occurring during mining as a result of elastic energy accumulation led to the relaxation of the medium and local decreases in its bulk density. The microgravimetric method is sensitive to variations in this physical parameter of rock. The most transparent effects of the differences in rock mass density can be observed by performing periodic local gravity field surveys and analysing their spatial and temporal variability. This paper analyses the relationship between ground deformations and the spatial and temporal gravity field distribution changes observed on the surface in the context of the safety of barrier pillars F1 and F2 in Marklowice (the GSB-GFO testing ground of project EPOS-PL+). Relative gravimetric surveys, referenced to the determined absolute values of g, were performed in 7 series over the period of 2021–2023. The collected data made it possible to chart differential maps of gravity field changes and anomalies with Bouguer reduction. The differential anomaly distributions between successive survey series and the reference series were analysed. This served as the basis for assessing the safety of the barrier pillars maintained by the mine and the possibility of ground deformation occurrence on the surface. Full article

The South China Block hosts extensive sedimentary phosphorites that offer valuable insights into both paleoenvironmental reconstruction and rare earth element (REE) resource potential. However, the mechanisms governing REE enrichment in these deposits remain poorly understood. This study investigates two distinct phosphorite layers from the Lower Cambrian Zhujiaqing (ZJQ) Formation in the Bailongtan (BLT) area of the Yangtze Platform using integrated analyses including petrology, XRD, major and trace elements, δ¹³C and δ¹⁸O isotopes, and LA-ICP-MS. The lower thin-bedded phosphorite, composed of finer phosphatic grains (<300 μm), exhibits significantly higher REE concentrations (883.6 ± 160.9 ppm; n = 48) compared to the upper thick-bedded phosphorite (303.2 ± 82.7 ppm; n = 64), which is dominated by larger, reworked grains (300–600 μm). Intervening strata consist of laminated phosphate-bearing carbonates interbedded with quartz, dolomite, and pyrite. PAAS-normalized REE patterns display MREE–HREE enrichment, negative Ce anomalies (avg. 0.60 ± 0.18; n = 18), and positive Y anomalies—indicative of oxic depositional conditions. The elevated REE content in the lower layer, coupled with the lowest δ¹³C values (−4.59‰), suggests enrichment linked to organic matter degradation. A proposed two-stage depositional model links REE enrichment to proximity with REE-rich deep-shelf waters, underscoring the critical role of redox and depositional dynamics in phosphorite-hosted REE accumulation. Full article

The ability to predict the volume of methane outbursts in coal mines is critical for the prevention of methane outburst accidents and the assurance of coal-mine safety. This paper’s central argument is that existing prediction models are limited in several ways. These limitations include the complexity of the models and their poor ability to generalize. The paper proposes a methane outburst volume-prediction and early-warning method. This method is based on a secondary decomposition and improved TSMixer model. First, data smoothing is achieved through an STL decomposition–adaptive Savitzky–Golay filtering–reconstruction framework to reduce temporal complexity. Second, a CEEMDAN-Kmeans-VMD secondary decomposition strategy is adopted to integrate intrinsic mode functions (IMFs) using K-means clustering. Variational mode decomposition (VMD) parameters are optimized via a novel exponential triangular optimization (ETO) algorithm to extract multi-scale features. Additionally, a refined TSMixer model is proposed, integrating reversible instance normalization (RevIn) to bolster the model’s generalizability and employing ETO to fine-tune model hyperparameters. This approach enables multi-component joint modeling, thereby averting error accumulation. The experimental results demonstrate that the enhanced model attains RMSE, MAE, and R² values of 0.0151, 0.0117, and 0.9878 on the test set, respectively, thereby exhibiting a substantial improvement in performance when compared to the reference models. Furthermore, we propose an anomaly detection framework based on STL decomposition and dual lonely forests. This framework improves sensitivity to sudden feature changes and detection robustness through a weighted fusion strategy of global trends and residual anomalies. This method provides efficient and reliable dynamic early-warning technology support for coal-mine gas disaster prevention and control, demonstrating significant engineering application value. Full article

The Chaoshan Depression, situated in the northern South China Sea, is a Mesozoic residual depression beneath the Cenozoic Pearl River Mouth Basin. Borehole LF35-1-1 has confirmed the existence of marine Jurassic layers rich in organic carbon within this depression. However, the understanding of petroleum geology in this area is limited due to the complex interplay of Mesozoic and Cenozoic tectonic activities and the poor quality of seismic imaging from previous surveys, which have obstructed insights into the characteristics of Mesozoic reservoirs and the processes of oil and gas accumulation. Recent quasi-3D seismic data have allowed for the identification of Mesozoic bioherms and carbonate platforms in the Middle Low Uplift of the Chaoshan Depression. This research employs integrated geophysical data (MCS, gravity, magnetic) and well data to explore the factors that influenced Middle Jurassic reef development and their implications for reservoir formation. The seismic reflection patterns of reefs and carbonate platforms are primarily characterized by high-amplitude discontinuous to chaotic reflections, with occasional blank reflections or weak, sub-parallel reflections, as well as significant high-velocity, high Bouguer gravity and low reduced-to-pole (RTP) magnetic anomalies. Atolls, stratiform reefs, and patch reefs are located on the local topographic highs of the platform. Three vertical evolutionary stages have been identified based on the size of atolls and fluctuations in relative sea level: initiation, growth, and submergence. The location of bioherms and carbonate platforms was influenced by paleotectonic topography, while their horizontal distribution was affected by variations in relative sea level. Furthermore, the reef limestone reservoirs from the upper member of the Middle Jurassic, combined with the mudstone source rocks from the Lower Jurassic and the lower section of the Middle Jurassic, as well as the bathyal mudstone caprocks from the lower part of the Late Jurassic, create highly favorable conditions for hydrocarbon accumulation. Full article

On 23 January 2024, a M_S7.1 earthquake struck Wushi County, Xinjiang Uygur Autonomous Region, marking the largest seismic event in the Southern Tianshan (STS) region in the past century. This study investigates the relationship between hydrothermal fluid circulation and seismic activity by analyzing the chemical composition and origin of fluids in natural hot springs along the Maidan Fracture (MDF). Results reveal two distinct hydrochemical water types (Ca-HCO₃ and Ca-Mg-Cl). The δD and δ¹⁸O values indicating spring water are influenced by atmospheric precipitation input and altitude. Circulation depths (621–3492 m) and thermal reservoir temperatures (18–90 °C) were estimated. Notably, the high ³He/⁴He ratios (3.71 Ra) and mantle-derived ³He content reached 46.48%, confirming that complex gas–water–rock interactions occur at fracture intersections. Continuous monitoring at site S13 (144 km from the epicenter of the Wushi M_S7.1 earthquake) captured pre-and post-seismic hydrogeochemical fingerprints linked to the Wushi MS7.1 earthquake. Stress accumulation along the MDF induced permeability changes, perturbing hydrogeochemical equilibrium. At 42 days pre-Wushi M_S7.1 earthquake, δ¹³C DIC exceeded +2σ thresholds (−2.12‰), signaling deep fracture expansion and CO₂ release. By 38 days pre-Wushi M_S7.1 earthquake, Na⁺, SO₄²⁻, and δ¹⁸O surpassed 2σ levels, reflecting hydraulic connection between deep-seated and shallow fracture networks. Ion concentrations and isotope values showed dynamic shifts during the earthquake, which revealed episodic stress transfer along fault asperities. Post-Wushi M_S7.1 earthquake, fracture closure reduced deep fluid input, causing δ¹³C DIC to drop to −4.89‰, with ion concentrations returning to baseline within 34 days. Trace elements such as Be and Sr exhibited anomalies 12 days before the Wushi M_S7.1 earthquake, while elements like Li, B, and Rb showed anomalies 24 days after the Wushi M_S7.1 earthquake. Hydrochemical monitoring of hot springs captures such critical stress-induced signals, offering vital insights for earthquake forecasting in tectonically active regions. Full article

The interplay between terrestrial water storage and vegetation dynamics in arid regions is critical for understanding ecohydrological responses to climate change and human activities. This study examines the coupling between total water storage anomaly (TWSA) and vegetation greenness changes in the Hexi Corridor, an arid region in northwestern China consisting of three inland river basins—Shule, Heihe, and Shiyang—from 2002 to 2022. Utilizing TWSA data from GRACE/GRACE-FO satellites and MODIS Enhanced Vegetation Index (EVI) data, we applied a trend analysis and partial correlation statistical techniques to assess spatiotemporal patterns and their drivers across varying aridity gradients and land cover types. The results reveal a significant decline in TWSA across the Hexi Corridor (−0.10 cm/year, p < 0.01), despite a modest increase in precipitation (1.69 mm/year, p = 0.114). The spatial analysis shows that TWSA deficits are most pronounced in the northern Shiyang Basin (−600 to −300 cm cumulative TWSA), while the southern Qilian Mountain regions exhibit accumulation (0 to 800 cm). Vegetation greening is strongest in irrigated croplands, particularly in arid and hyper-arid regions of the study area. The partial correlation analysis highlights distinct drivers: in the wetter semi-humid and semi-arid regions, precipitation plays a dominant role in driving TWSA trends. Such a rainfall dominance gives way to temperature- and human-dominated vegetation greening in the arid and hyper-arid regions. The decoupling of TWSA and precipitation highlights the importance of human irrigation activities and the warming-induced atmospheric water demand in co-driving the TWSA dynamics in arid regions. These findings suggest that while irrigation expansion cause satellite-observed greening, it exacerbates water stress through increased evapotranspiration and groundwater depletion, particularly in most water-limited arid zones. This study reveals the complex ecohydrological dynamics in drylands, emphasizing the need for a holistic view of dryland greening in the context of global warming, the escalating human demand of freshwater resources, and the efforts in achieving sustainable development. Full article

Mercury is naturally present in soils at trace concentrations, but its cycle is increasingly disrupted by anthropogenic activities, which affect its distribution and behavior. Due to its toxic nature, mercury has become a significant focus in environmental and public health policies. Following the detection of mercury anomalies during groundwater quality monitoring at the Pays de Caux study site (France), a comprehensive multidisciplinary research effort was initiated. This included geological and hydrogeological studies aimed at tracking mercury concentrations in piezometric wells and identifying the sources of these anomalies. This study seeks to assess the groundwater quality and characteristics from ten hydrogeological wells. The evaluation will focus on key hydrogeological parameters, including pH, redox potential (Eh), suspended solids, and groundwater levels, as well as a detailed geochemical analysis of elements such as Hg, Fe, Mn, Zn, Pb, and Cu. The mobilization of mercury and other metallic traces elements is strongly governed by environmental factors. Hydrochemical analyses highlight the complex interplay of various parameters that influence the chemical forms and behavior of mercury in both soil and groundwater. The results from the piezometric measurement campaigns (Pz1 to Pz7) have provided crucial insights, enabling the development of hypotheses about mercury’s behavior in the chalk aquifer. It is hypothesized that impermeable areas may trap groundwater for extended periods, leading to the accumulation and abnormal concentration of mercury. This could cause mercury to be intermittently released, potentially affecting the surrounding environment. Mercury concentrations in groundwater are highly sensitive to pH and redox potential (Eh), with low pH and reducing conditions promoting mercury mobilization and the formation of toxic methylated species. The study suggests the chalk aquifer is generally in equilibrium with mercury, but fluctuations in mercury levels between Pz7 and Pz4 are likely due to the heterogeneity of the clay and geological factors such as mineral composition and fracturing. This research provides insights into mercury transfer in heterogeneous environments and emphasizes the need for continuous hydrogeological monitoring, including piezometer readings, to manage mercury dispersion in the aquifer. Full article

This study examines speleothems, sediments, rock, and water to assess geochemical and mineralogical processes in deep karst systems. Focusing on Slovačka jama cave (−1320 m deep) and the Velebita cave system (−1026 m deep), we identify elemental and mineralogical anomalies that provide valuable records of element transport, mineral formation, and paleoenvironmental changes. Heavy metal anomalies (Al, B, Co, Mn, Na, Tl, Ba, Be, Cr, Cu, Fe, K, Pb, Rb, Ti, U, Zn) at 300–400 m of depth in Slovačka jama indicate a complex interplay of geological conditions, geomorphological processes, atmospheric deposition, and potential anthropogenic influences. Factor analysis reveals two elemental associations: (1) Fe, Pb, Cu, and Zn, linked to terrigenous aluminosilicates, and (2) Cd, Cr, Mo, and Ni, suggesting airborne or geological sources. Mineralogical analysis confirms the dominance of calcite, with quartz, clay minerals, feldspars, magnetite, and goethite also detected. High magnetic susceptibility values in sediment-rich samples suggest Fe-rich mineral inputs from weathering, biogenic activity, or industrial sources. Ba anomalies in feldspar-rich samples and Sr accumulation at depth indicate distinct geochemical processes. These findings enhance our understanding of deep karst geochemistry, crucial for paleoenvironmental reconstructions and groundwater protection. Full article

Sulfamethoxazole (SMX), a commonly used sulfonamide antibiotic, poses a threat to aquatic life due to its widespread presence in the environment. This study aims to investigate the specific effects of SMX on the development of marine medaka (Oryzias melastigma) embryos and larvae. Marine medaka embryos were exposed to SMX at concentrations of 0 (solvent control group, SC group), 1 μg/L (low concentration group, L group), 60 μg/L (middle concentration group, M group), and 1000 μg/L (high concentration group, H group). The results indicated that SMX exposure significantly accelerated the heart rate of embryos (p < 0.0001) and shortened the hatching time while also causing anomalies such as reduced pigmentation, smaller eye size, spinal curvature, and yolk sac edema. SMX also led to a decrease in the total length of the larvae. The M group and the H group exhibited a significant increase (p < 0.05) in lipid accumulation in the visceral mass of the larvae. In the L group and the M group, there was a significant increase (p < 0.0001) in the swimming distance of the larvae. At the molecular level, SMX exposure affected the transcript levels of the genes involved in the cardiovascular system (ahrra, arnt2, atp2a1, and cacan1da), antioxidant and inflammatory systems (cat, cox-1, gpx, pparα, pparβ, and pparγ), nervous system (gap43, gfap, α-tubulin), intestinal barrier function (claudin-1), detoxification enzymes (ugt2c1-like), and lipid metabolism (rxraa) in the embryos to larval stage. The microbiome analysis showed that at the phylum level, exposure to SMX resulted in an increase in the abundance of Proteobacteria. Additionally, the abundance of Actinobacteriota significantly increased in the L group (p < 0.05). At the genus level, the abundance of Bifidobacterium significantly increased in the L group (p < 0.05), while the abundance of Vibrio significantly increased in the H group (p < 0.05). The alpha diversity analysis revealed a significant decrease in the Chao1 index in the L and H groups, indicating a reduction in microbial richness. The beta diversity analysis showed differences in the microbial communities of marine medaka larvae among different SMX exposure groups. This study elucidates the negative impacts of SMX on the development of marine medaka embryos and larvae and their microbial composition, providing a scientific basis for assessing the risks of SMX in marine ecosystems. Full article