Search Results (1,119)

Karst piedmont fault overflow springs are widely developed in structurally controlled, basin-margin settings, where basin-bounding faults obstruct regional groundwater flow. However, the coupled fault blocking, fault conduction, and caprock sealing mechanisms governing their genesis remain insufficiently quantified. This study investigates the Shentou Spring system in Shanxi Province, North China—a typical piedmont fault overflow spring—to develop a three-dimensional genetic model characterised by coupled blocking, conduction, and overflow processes. Integrating borehole datasets, multi-year groundwater level monitoring records, hydrochemical and isotopic measurements, and detailed structural mapping, this study identifies three key controlling mechanisms. First, spatial variations in the throw of the Mayi Fault control fault blocking efficiency, partitioning the fault zone into complete barrier and semi-permeable segments, which underpins the incomplete drainage behaviour of the spring system. Second, the Gengzhuang Fault intersects the high-permeability Qilihe and Yuanzihe groundwater flow zones, acting as the primary conduit that transports groundwater from distant recharge areas to the discharge zone. Third, the Quaternary caprock in the discharge area features a critical thickness threshold of approximately 30 m; confined karst groundwater breaches the overlying caprock and forms spring outlets where caprock thickness falls below this threshold. The proposed tripartite coupled model provides a semi-quantitative framework for interpreting the genesis of piedmont fault overflow springs. In practical terms, it supports the delineation of fault-conduit protection zones and the design of long-term water-quality monitoring networks along fault-controlled flow paths. Full article

To meet the demands for high-density integration and broadband RF performance in next-generation electronic equipment, this paper investigates the structural design and process sensitivity of vertical interconnects in three-dimensional stacked system-in-package (3D-SiP). Based on quasi-coaxial matching and low-impedance compensation techniques, three typical vertical interconnect structures are designed: the PCB-BGA-SiP microstrip structure achieves S₁₁ better than −15 dB and S₂₁ < 0.3 dB within 2–20 GHz; the lower stripline–BGA–upper microstrip structure achieves S₁₁ better than −27 dB; the lower microstrip–BGA–upper microstrip structure achieves S₁₁ better than −18 dB within 1–23 GHz. Isolation simulation shows that the isolation between adjacent channels exceeds 55 dB within 25 GHz. For process sensitivity evaluation, physical samples of gold wire bonding parameters (length, diameter, number) were fabricated and tested for S₁₁, confirming that the dual-wire topology extends the effective bandwidth to 2–20 GHz (a 54% improvement over single wire), the third-wire marginal gain is only ~5%, and 25 μm diameter offers the best overall performance. For BGA ball radius and pad pitch, parametric sensitivity analysis via Ansys HFSS was performed (not experimentally validated process variation results), identifying the optimal BGA radius as 0.245 mm with an allowable variation of ±0.015 mm, and the pad center-to-center distance should be controlled near 0.8 mm. Based on these findings, process control strategies are proposed: low-loop wire bonding (loop height < 50–80 μm) with statistical process control; substrate warpage controlled through symmetric copper filling, a thick-middle dielectric stack-up, and distributed symmetric cavity layout, combined with eutectic pressure of 1.5 kPa, validated on 10 fabricated substrates with peak warpage consistently < 80 μm, void rate 4.75%, and solder overflow 94%; and BGA soldering using high-precision vision alignment and controlled collapse (20–35%). This work provides a theoretical basis and practical process pathway for transitioning 3D-SiP vertical interconnects from ideal design to mass production. Full article

In most railway divisions the results of scheduled inspections of automation and telemechanics field devices are still recorded on paper. Such records reach engineering management with a delay, are easy to lose, and are difficult to verify. This paper examines the data transmission core of a digital inspection complex in which passive RFID tags identify both the equipment and the personnel, and the inspection record is delivered to a cloud server over a hybrid cellular architecture combining a failure-prone GSM channel with a reliable CDMA channel. To quantify the stability of such a system, a continuous-time Markov chain model is constructed in which the link is represented as an M/M/2/K queue with one unreliable server: both channels carry traffic in parallel, and during a GSM outage the CDMA channel alone sustains service. Records already admitted are preserved across a channel switch; only records arriving at a full shared buffer are rejected. This residual overflow loss stays below 0.1% at routine load with a buffer of m ≥ 5 and reaches about 2.8% only under post-incident overload. The model parameters were measured on an operating ESP32-based scanner complex piloted at Hamza station on 46 point machines. Calculations for three load scenarios show that increasing the local buffer beyond m = 5 yields diminishing returns while the delay grows, and that resilience is governed primarily by the presence of the redundant channel and adequate buffering, with the primary-channel recovery rate a secondary factor. Full article

Battery-powered IoT sensor nodes require energy-efficient Medium Access Control (MAC) protocols to extend network lifetime while supporting priority-sensitive traffic. This paper proposes a Priority-Aware Packet Aggregation/Piggybacking-Based (Priority + Packet Aggregation) Hybrid Energy-Efficient MAC ($P^2$A-HMAC) protocol that integrates bit-mapped priority signaling with lightweight packet aggregation/piggybacking to reduce control overhead. The protocol classifies traffic into emergency, buffer-overflow, priority, and normal categories, providing guaranteed access to delay-sensitive data while minimizing radio activity, idle listening, and contention. A mathematical energy model is developed for both priority- and contention-based operations. MATLAB-based evaluation demonstrates that $P^2$A-HMAC consistently achieves lower energy consumption than TDMA, EA-TDMA, ASHMAC, E-BMA, and $P^2$A-HMAC across varying network sizes, packet sizes, and event-generation probabilities. The proposed protocol provides substantial energy savings, particularly in large-scale and moderate-traffic networks, while maintaining priority-aware communication and QoS, making it suitable for low-power IoT and wireless sensor network applications. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a systemic disorder shaped by interorgan crosstalk: dynamic, bidirectional communication through which the liver and endocrine organs, gut, adipose tissue, brain, kidney, skeletal muscle, bone, and heart exchange signals to coordinate metabolism, immunity, and tissue homeostasis. Across these axes, neural circuits, hormones, cytokines, adipokines, hepatokines, myokines, osteokines, bile acids, microbial metabolites, lipids, extracellular vesicles, and microRNAs integrate nutrient handling, insulin action, immunity, mitochondrial function, and tissue remodeling. Perturbation of these networks converts physiological homeostasis into self-reinforcing loops of substrate overflow, endocrine dysregulation, dysbiosis, inflammation, and fibrogenesis, while hepatic dysfunction propagates renal, neurocognitive, cardiometabolic, and musculoskeletal complications. This framework helps explain why individuals with comparable steatosis show divergent trajectories of metabolic dysfunction-associated steatohepatitis (MASH), fibrosis, extrahepatic disease, and treatment response. It also highlights tractable points of intervention, including restoration of adipose buffering, modulation of gut microbial and bile-acid signaling, correction of endocrine drivers, preservation of muscle and bone, and integrated cardio–kidney–liver risk reduction across different disease stages and clinical phenotypes. We argue that precision hepatology should move beyond isolated assessment of liver fat and fibrosis towards multidimensional phenotyping of dominant crosstalk mechanisms. Longitudinal multi-omic studies and trials incorporating outcomes across organs are now required to distinguish causal signals from disease correlates, define clinically actionable endotypes, and test whether targeting one node can restore durable metabolic and functional resilience throughout the interconnected MASLD network, while improving patient-centered outcomes across the disease course. Full article

Volcanic reservoirs exhibit strong lithological heterogeneity and complex seismic responses, making lithofacies prediction between wells challenging, particularly in the Yingcheng Formation of the Songliao Basin. To address this issue, this study proposes an integrated workflow for volcanic lithofacies prediction based on Principal Component Analysis (PCA)-optimized multi-attribute seismic clustering. Seismic facies are first identified from reflection configuration and external geometry, and three types—chaotic, layered, and shield-like facies—are established and calibrated using well logs and core data. PCA is then applied to reduce attribute redundancy and optimize the attribute set. The selected attributes, including root mean square (RMS) amplitude, energy half-life, and gradient magnitude, are used for multi-attribute clustering. The results indicate that eruption facies dominate the study area and correspond to favorable reservoirs, accounting for the majority of high-quality reservoir zones. In contrast, overflow and volcanic sedimentary facies show comparatively lower reservoir potential. The predicted lithofacies distribution shows strong spatial consistency with well observations, demonstrating the method’s reliability. Overall, the proposed workflow improves lithofacies prediction accuracy and provides an effective tool for reservoir characterization and well deployment in complex volcanic settings. Full article

Urban drainage resilience assessments emphasize hydraulic performance or pollutant discharges at outfalls, with limited attention paid to street-level contamination following sewer surcharge and overflow. This study developed an event-based framework to quantify surface pollution exposure resilience. An integrated 1D pipe network–2D surface hydraulic-water quality model was implemented in InfoWorks ICM for Xiamen Island, China. Spatial analysis revealed a mismatch between inundation extent and pollutant concentration distributions, demonstrating that severe flooding does not necessarily coincide with high pollution exposure and hydraulic indicators alone cannot adequately represent pollution exposure risk. Therefore, an event-based performance function integrating overflow nodes, pollution exposure area, and exposure intensity under different designed storms was proposed. Results showed that hydraulic failure occurred rapidly after rainfall onset, whereas pollutant accumulation and spatial expansion exhibited delayed responses, reflecting different controlling mechanisms of drainage failure and pollution exposure. Sensitivity analysis indicated that hydraulic failure dominated resilience sensitivity to rainfall intensity, with node-focused weighting causing the largest decline (0.733 to 0.662), whereas pollution exposure determined the magnitude of overall resilience loss, which was consistently lowest under exposure area-focused weighting. These findings highlight the necessity of integrating hydraulic and pollution perspectives to understand urban drainage behavior and provide a scientific basis for targeted resilience-oriented management and urban renewal. Full article

The “climate bathtub,” originated by Linda Booth Sweeney and John Sterman in 2001, has provided an elegant metaphor for the physical problem of climate change for 25 years. In this metaphor, as long as inflows of water into a bathtub from a faucet (greenhouse gas emissions) exceed outflows through a drain (removals), then the stock of water in the bathtub (atmospheric concentrations) will rise, with eventual consequences when the bathtub overflows. This bathtub metaphor is simple, relatable, urgent, and apt. But climate change is a social problem, not just a physical problem. By adding four new elements to the climate bathtub—multiple faucets; multiple drains; multiple damage thresholds; and multiple people—the climate bathtub metaphor can illuminate a wide range of social challenges related to climate change. This expanded climate bathtub metaphor offers insights on how individuals prioritize climate actions; why collective disagreements emerge; and hierarchical levels of climate cooperation. It suggests heuristics that policymakers, practitioners, and future climate professionals can use to evaluate potential climate actions. This more complex, but more versatile, version of the climate bathtub can supplement the original metaphor as a public communications tool and motivator for climate action. Full article

γ-photon tomography provides a non-contact approach for reconstructing and visualizing flow-field parameters. However, the resulting grayscale images often exhibit blurred boundaries and weak texture features, causing conventional colorization methods such as DeOldify to produce cross-region color diffusion and boundary color overflow. To address this, this paper proposes a γ-photon flow-field image colorization algorithm based on the Hybrid Swin Colorization Network (HSCN). A hybrid dual-stream encoder composed of a Swin Transformer semantic stream and a central difference convolution (CDC) gradient branch is combined with cross-stage gradient injection and a spatially gated adaptive fusion mechanism to enhance the perception of high-frequency structures at flow-field boundaries and suppress color overflow. The effectiveness of the algorithm is evaluated in terms of colorization quality and flow-field temperature-parameter inversion using γ-photon flow-field images of two CFD-simulated flow patterns, a large-scale vortical wake and a horizontal wake. The proposed method achieves PSNR, SSIM, FID, and MAE values of 38.7422, 0.9372, 10.7344, and 0.0085, respectively. Compared with DeOldify, PSNR and SSIM are improved by 24.30% and 11.89%, while FID and MAE are reduced by 42.98% and 60.47%, respectively. In addition, HSCN achieved a MAPE of 12.65% across 15 boundary and temperature-transition locations in three representative samples, compared with 31.24% for DeOldify and 28.70% for DDColor. Full article

Closed droplet contours provide the geometric basis for area estimation in vision-based droplet observation. In OLED inkjet printing, droplets are deposited into pixel wells with predefined geometry; projected area is therefore a primary geometric quantity for assessing whether the deposited liquid sufficiently fills the well or risks overflow. This work formulates closed-contour sampling under a fixed sampling budget as an area-driven sampling problem. A leading-order analysis of the local arc–chord area error shows that the dominant cubic term depends jointly on curvature and segment length. Minimization of the resulting leading-order area-error functional yields an asymptotically optimal area-driven sampling density proportional to the cube root of curvature, together with a sampling-budget estimate under a target area-error tolerance. The derived sampling density is implemented on the fitted closed contour through cumulative-weight inversion. Experiments on random closed curves and the droplet dataset provide a systematic quantitative comparison with representative methods under identical fixed-budget settings, complemented by statistical analysis and evaluations of geometric fidelity, sensitivity, and computational efficiency. The proposed method achieves lower area estimation error under the tested sampling budgets, with the improvement being most pronounced at lower sampling budgets, while the reported geometric-fidelity metrics show no disproportionate degradation of contour fidelity. These results demonstrate the effectiveness of area-driven sampling for closed-contour area estimation under limited sampling budgets. Full article

Dense medium cyclone (DMC) separation offers a potential route for the pre-concentration of spodumene ores prior to downstream grinding and flotation. In this study, the effects of dense medium suspension density and feed pressure on spodumene pre-concentration were investigated through actual ore separation tests combined with CFD simulations. Under the optimal conditions of a feed pressure of 150 kPa and a medium density of 2200 kg/m³, the Li₂O grade increased from 1.30% in the feed to 5.72% in the concentrate, with a Li₂O recovery of 77.23% and a separation efficiency of 60.42%. CFD results showed that the optimal operating conditions produced a relatively stable flow field with lower turbulent kinetic energy. Excessively high medium density or feed pressure increased the probability of fine spodumene particles reporting to the overflow, resulting in lithium losses, whereas insufficient medium density or feed pressure promoted the misplacement of gangue minerals into the concentrate. These results clarify the effects of key operating parameters on spodumene separation in a DMC and provide a basis for optimizing the pre-concentration of hard-rock lithium ores. Full article

Urban stormwater poses a threat to urban safety and development. The systematic spatial planning of low-impact development (LID) facilities is increasingly recognized as a sustainable approach to enhancing urban flood resilience. Previous studies have largely focused on empirically-based design approaches or have employed uncoupled computational methods, resulting in a lack of accuracy in flood simulation results. In this study, a novel framework was proposed. The Non-dominated Sorting Genetic Algorithm II was employed to perform multi-objective optimization of the spatial layout of LID facilities, and a coupled model of SWMM and TELEMAC was developed to simulate surface flooding based on the optimized schemes. Under three rainfall scenarios, three schemes on the Pareto Front—representing the lowest cost, the optimal compromise and the least overflow—were selected to investigate how scheme parameters and overflow are influenced by rainfall intensity and design preferences. The results indicate that scheme parameters and node overflow show greater variation under the influence of different design preferences than under different rainfall conditions. Taking the schemes selected in this study as examples, under the lowest-cost scheme, LID coverage was less than 10%, resulting in a limited reduction in node overflow; but when ‘minimum overflow’ was set as the design preference, node overflow was virtually eliminated, with peak water levels at flood-prone locations reduced to 0.05 m, 0.08 m and 0.10 m under 50-year, 100-year and 200-year storm conditions, respectively. The framework for urban flooding simulation and flood control scheme design proposed in this study is potentially applicable to comparable settings, subject to similar data availability and physical conditions, serving as a reference for enhancing urban resilience to flooding. Full article

The Weibei Plain, characterized by its complex stratified aquifer system and extensive brine resources, faces severe groundwater salinization. Unraveling the precise evolutionary mechanisms of diverse hydrochemical types across varying depths and geomorphological zones remains a significant challenge. This study synthesizes a multi-batch hydrochemical dataset with multi-isotopic tracers (δ²H, δ¹⁸O, δ¹¹B, δ⁸¹Br, δ³⁷Cl) to establish a comprehensive groundwater evolutionary model from the piedmont plain to the coastal marine plain. The results indicate distinct hydrochemical zonation governed by geographic geomorphology and historical marine transgressions. Salinization in transitional waters is primarily driven by physical mixing and reverse cation exchange rather than extreme evaporative fractionation. Crucially, isotopic mass balance definitively reveals that deep brine (depth > 60 m) originates not from modern seawater intrusion, but from the extreme surface evaporation of ancient paleo-seawater. This paleo-brine underwent profound isotopic exchange during its gravity-driven downward migration, evidenced by intense clay mineral adsorption (yielding extreme δ¹¹B enrichment up to 64.42‰) and secondary evaporite dissolution. Furthermore, the regional cone of depression formed by intensive brine extraction has profoundly altered deep hydrodynamics, inducing overflow and membrane ultrafiltration across massively thick clay aquitards. This process distinctly drives the isotopic fractionation observed in deep brackish waters. The analysis process in this study combines the isotope method with the regional geomorphological zoning, which can provide a reference for the analysis of groundwater evolution characteristics in other coastal aquifers. Full article

With the continuous advancement of deep and ultra-deep well drilling technologies, formations with complex pressure windows are becoming increasingly common. During casing running operations, it is necessary to ensure both leak prevention in loss-prone formations and pressure stabilization in high-pressure formations, demanding increasingly higher accuracy in wellbore pressure calculation. This study establishes a wellbore pressure calculation model for managed pressure casing (MPC) running in deep wells, specifically addressing the scenario where a multi-density gradient drilling fluid column exists in the annulus after tripping out. The model’s novelty lies in integrating transient surge pressure calculation with a dynamic fluid column structure model that tracks the displacement of multi-density drilling fluid layers during casing running. The governing equations based on one-dimensional unsteady flow theory are solved using the method of characteristics with adaptive time stepping and a grid independence study confirming the discretization scheme. Quantitative analysis reveals that casing running speed is the dominant factor affecting surge pressure; when the speed increases from 0.5 m/s to 1.5 m/s, the surge pressure increases from approximately 1.2 MPa to 3.5 MPa at a 2000 m depth. Drilling fluid properties also significantly influence surge pressure: increasing the density from 2.0 g/cm³ to 2.22 g/cm³ results in a surge pressure increase of approximately 0.6 MPa; increasing the yield value from 2.85 Pa to 15 Pa leads to an increase of about 1.1 MPa; the surge pressure shows a clear increasing trend with both the consistency coefficient and flow behavior index. Casing running depth affects the buffering effect of the bottomhole flow channel; when the casing is run to 7000 m, the surge pressure is approximately 0.5 MPa higher than at 2000 m. Taking a typical deep well (8578 m) with a negative pressure window of −0.008 g/cm³ as an example, three casing running speed plans were designed and evaluated. Plan 1 was selected with running speeds ranging from 0.16 m/s in the upper section to 0.115 m/s in the lower section, maintaining the equivalent circulating density (ECD) within the safe density window throughout the entire operation. Field application of this plan proceeded smoothly without any occurrences of lost circulation or overflow. This provides a practical basis for MPC running technology in deep wells with narrow or negative pressure windows. Full article

Driven by the vision of sixth-generation (6G) communication networks, Space–Air–Ground Integrated Vehicular Networks (SAGVNs) address the connectivity blind spots inherent in traditional networks by integrating unmanned aerial vehicles (UAVs) as highly mobile relay nodes. However, the high bit error rates (BERs) and prolonged propagation delays characteristic of satellite links, coupled with the highly dynamic topologies and multi-hop transmission nature of UAVs and terrestrial vehicles, present significant challenges to reliable end-to-end data streaming. To mitigate the performance degradation caused by link asymmetries in heterogeneous networks, this paper proposes a reliable transmission optimization scheme for UAV-relayed SAGVNs. By comprehensively modeling the transmission dynamics of long-delay, high-BER satellite links and mobile multi-hop UAV networks, the proposed scheme introduces an enhanced slow-start mechanism to accelerate throughput growth, thereby mitigating the startup lag induced by extensive propagation delays. Furthermore, an accurate packet loss differentiation model is established during the congestion avoidance phase. This model effectively decouples non-congestion packet losses—triggered by random channel errors or topology handovers due to high-speed node mobility—from genuine congestion-induced losses caused by buffer overflows at bottleneck nodes. Simulation results demonstrate that the proposed adaptive scheme demonstrates notable improvements over classical loss-based and delay-based baselines in reducing queuing delays at UAV relay nodes, enhances the transmission efficiency of multi-hop terminals, and effectively maintains end-to-end goodput stability in high-latency environments. Full article