Search Results (2,169)

Near-surface ozone (O₃) pollution is a growing environmental concern, particularly in the Beijing–Tianjin–Hebei (BTH) region, one of China’s most densely populated megacity clusters experiencing increasingly severe O₃ episodes. Existing data-driven forecasting models systematically underestimate high-concentration events and offer limited lead times. To reveal the meteorological drivers of extreme O₃ episodes, we conducted composite anomaly analysis over 2019–2023 and identified the dominant meteorological mechanism as a coupled pattern of mid-tropospheric anticyclonic circulation with high temperature, low humidity, and deep subsidence inversion, which suppresses vertical diffusion while southerly advection drives rapid near-surface O₃ accumulation. Motivated by meteorological diagnostics, we proposed ARC-Net, a Transformer-encoder-based Adaptive Residual Correction Network that ingests numerical weather prediction data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and air quality observations to produce hourly O₃ forecasts up to 240 h (10 days) ahead. The model features a dual-branch regression-classification architecture enhancing feature discrimination at high concentrations and an Adaptive Residual Correction module that dynamically calibrates outputs through a triple-gating mechanism conditioned on pollution-level priors. In independent forecast tests for the year 2023 across 13 cities in the BTH region, ARC-Net achieved R² = 0.879 and a root mean square error (RMSE) of 17.03 μg/m³ at 0–24 h, retaining R² = 0.749 and RMSE = 24.57 μg/m³ at 0–240 h. For extreme episodes (maximum daily 8 h average ozone (MDA8_O₃) ≥ 215 μg/m³), the Critical Success Index improved by 63.9% over the baseline, and RMSE decreased by 33.15% within the 215–265 μg/m³ range in a representative case. These results indicate that meteorology-guided predictors combined with adaptive residual correction can partially alleviate high-O₃ underestimation and provide practically useful medium-range warning skill. Full article

Source identification in confined underground ventilation systems is essential for hazardous-gas monitoring, and uranium-mine radon provides a representative case in which release locations and strengths must be inferred from limited concentration measurements. This presents an underdetermined, ill-posed inverse problem whose solvability under different sparse-regression strategies and roadway configurations remains poorly understood. In this study, a computational fluid dynamics (CFD) forward model is coupled with sparse regression. The ventilation flow field and radon advection–diffusion process are solved in OpenFOAM to construct a source–sensor contribution matrix, and source recovery is formulated as a sparse linear inverse problem. Four methods—LASSO, LASSO with non-negative least-squares (NNLS) refitting, Elastic Net, and Elastic Net with NNLS refitting—are compared, and the contribution matrix is characterized by its mutual coherence, condition number, and singular-value spectrum. Numerical tests were conducted for single- and multiple-source scenarios in single-main and main–branch roadway models. The results indicate that inversion performance depends on the spatial information and local identifiability provided by the sensor configuration rather than on sensor number alone. LASSO and Elastic Net exhibited varying degrees of source-strength shrinkage or dispersion, whereas NNLS refitting reduced these effects when the first-stage support contained the dominant source candidates. In the prescribed three-source case, denser sensor coverage improved dominant-source localization and reduced the post hoc condition number of the prescribed-source submatrix, although the full-matrix condition number increased. This finding indicates improved local identifiability for the tested source combination rather than a general sensor-count effect. Because the synthetic observations and the inversion operator were derived from the same CFD response matrix, the results represent a controlled model-consistent proof of concept rather than an estimate of field-level performance. Full article

Structural fractures and karst cavities are widely developed in deep and ultra-deep carbonate reservoirs, providing preferential pathways for rapid fluid migration while increasing the risk of severe drilling fluid loss. To investigate the lost-circulation mechanism in fractured-vuggy formations, a hydro-mechanically coupled gas–liquid two-phase seepage model was established by considering the multiple-media characteristics of matrix, fractures and cavities, as well as rock deformation and fluid compressibility. We hypothesize that gas–liquid property differences and hydro-mechanical changes in conductivity jointly control drilling fluid loss, with the gas–liquid property contrast exerting the stronger effect under the simulated conditions. In the model, flow in the matrix and fractures is described by Darcy’s law, while high-velocity flow in cavities is characterized using the Forchheimer non-Darcy equation. The coupling between the seepage field and stress field is achieved by incorporating the effective stress relationship, using the Kozeny–Carman porosity–permeability evolution model and the Goodman fracture deformation model. The coupled equations were implemented in COMSOL. Model validation confirms the reliability of the proposed model in predicting drilling fluid loss. The fracture–vug system significantly enhances fluid exchange between the wellbore and formation. Pressure propagates rapidly along fractures and vugs at the early stage and subsequently diffuses into the surrounding matrix, while the loss rate generally decreases with time. After 120 min, hydro-mechanical coupling increased the loss rate from 1.15 × 10⁻³ to 1.23 × 10⁻³ m³/s and the cumulative loss volume from 11.41 to 12.06 m³. Compared with the single-phase model, the gas–liquid two-phase model predicted a 4.82-fold higher loss rate. Fracture aperture, vug size, bottomhole pressure differential, and rock mechanical properties are the principal factors controlling loss intensity and pressure propagation. Through effective stress variations, hydro-mechanical coupling modifies porosity, permeability, and fracture aperture, thereby affecting formation conductivity and dynamic loss behavior. These results provide theoretical guidance for lost-circulation mechanism analysis, risk assessment, and plugging optimization in deep fractured-vuggy carbonate formations. Full article

We introduce a deterministic class of constraint-coupled reaction–diffusion systems in which an internally generated field modulates transport and reaction processes while being regenerated by the same dynamics that it regulates. This feedback structure provides a minimal mathematical framework for studying dynamically consequential endogenous regulation in spatially extended non-equilibrium systems; the presence of a causal loop alone is not identified with organizational autonomy. The model is formulated as a quasilinear parabolic system on a bounded domain. Positivity, boundedness, viability, equilibrium stability, and spatial localization are treated as distinct mathematical properties. Under structural assumptions on the diffusion and reaction terms, we establish local classical well-posedness, preservation of non-negativity, and global existence under boundedness or forward-invariant-region conditions. Viability is formulated as forward invariance of subsets of an infinite-dimensional phase space rather than as a local pointwise balance. A minimal three-field realization, consisting of a resource field, an organizing field, and a constraint field, is then analyzed. We derive conditions for the existence of positive homogeneous equilibria, obtain sufficient criteria for homogeneous and full modal stability, and characterize stationary and oscillatory spatial instability thresholds through a mode-dependent dispersion relation. We complement the analysis with conservative two-dimensional finite-volume simulations. Below the predicted spatial-instability threshold, perturbations decay, whereas above threshold a persistent heterogeneous state forms with a dominant scale consistent with the dispersion relation. Constraint level sets, occupied fraction, connected components, and concentration indices quantify the resulting dynamically generated localization. Feedback-ablation controls show that, for the representative parameter set, removing either transport or reaction feedback eliminates the finite-wavenumber instability, while alternative bounded monotone constitutive laws preserve spatial patterning. The framework therefore distinguishes externally imposed regulation, passive outputs, and dynamically consequential endogenous feedback, and provides a basis for investigating bounded self-maintenance and localization without equating loop topology with autonomy. Full article

Polarity reversal changes not only the instantaneous electric field in a needle–plane air gap but also the subsequent field–particle coupling through the charged-particle distribution established before reversal. For a configuration in which the grounded needle and grounded lower plate share the same return path, it remains unclear to what extent this local history-dependent state is transferred to the complete grounded conductor and its externally measurable current. Here, a two-dimensional axisymmetric electrostatic model (ES) and a drift–diffusion–reaction–Poisson–discharge-fluid model (EDIS) were established for a 50 mm needle–plane air gap. Positive-to-negative (P2N)/negative-to-positive (N2P) reversals and history-retained/history-reset (H/R) controls were used to separate the effects of reversal path and pre-existing charged-particle state. Over the tested 0–2τ reset-hold range, the representative near-tip electron density in H remained approximately 15–16% higher than that in the corresponding R case, whereas the H/R conductor-integrated response of the complete common-ground assembly was indistinguishable at the present numerical resolution. Outer-domain analysis further showed that for the representative 15 kV case in the 300 mm reference domain, the EDIS and ES common-ground integrated responses differed by approximately 3.3%. Experimentally, P2N and N2P reversals were repeated at 5, 10, and 15 kV, yielding 120 events. The main common-ground current pulse increased with voltage magnitude and maximum voltage slew rate, and the median event-level Pearson correlation with signed dV/dt was approximately 0.989. Different capacitance-baseline constructions yielded central residual-integral levels of approximately 18–19%; after multiplicity correction, the 15 kV fixed-window absolute integral was the direction-sensitive terminal metric with the strongest statistical support. Under the investigated conditions—a nominal 0.5 mm tip radius, 50 mm gap, approximately 3 ms reversal time, and weak-discharge regime—the reversal path and particle history primarily reorganize the near-tip charged-particle state, whereas the dominant scale of the common-ground transient remains closely associated with the applied-voltage variation and the capacitive response of the system. Full article

In porous media grouting, highly viscous non-Newtonian fluids often trigger viscous fingering (Saffman–Taylor instability) due to adverse mobility ratios, creating fractal-like preferential channels that severely weaken the reinforcement volume. To overcome this, a novel swirl-driven grouting method is proposed. A 2.5D swirl seepage model is established to derive the analytical solution for tangential velocity spatial decay. Integrating the Capillary Bundle and Herschel–Bulkley models elucidates the nonlinear coupling mechanism of centrifugal force and shear-thinning. The swirl flow creates an in situ centrifugal pump, reshaping pressure gradients and triggering a sudden viscosity plunge via extremely high comprehensive shear rates. Furthermore, a modified Saffman–Taylor dispersion relation is constructed and validated via indoor sandbox experiments. Theoretical analysis yields a conditional critical Swirl Number threshold of approximately 0.6 under the tested parameters to suppress the fractal-like evolution of fingering. Experiments demonstrate that exceeding this threshold transitions the grout from preferential seepage to uniform isotropic diffusion. The measured isotropic index is closely enveloped within the 10% theoretical error band. Consequently, the effective projected area experiences a substantial leap of 83.3% due to synergistically enhanced driving forces and reduced medium resistance. This mechanism fundamentally overcomes viscous fingering and suppresses the fractal-like growth tendency of the displacement front, providing a solid theoretical basis for controlling grout diffusion morphology in underground engineering. Full article

Soil acidification threatens agroecosystems, yet the coupled, soil-specific proton-buffering mechanisms in permanent-charge soils (PCSs) and variable-charge soils (VCSs) remain insufficiently quantified. This study systematically investigated surface cation exchange, vacant site H⁺ sorption, and mineral dissolution, using batch and kinetic incubation experiments. Results showed that H⁺ buffering in PCSs was dominated by rapid, stoichiometric surface ion exchange, whereas approximately 42% of the total exchangeable acidity increment in VCSs originated from specific H⁺ sorption on vacant, high-affinity surface sites. VCSs exhibited ~10-fold-higher Langmuir proton sorption affinity and Temkin acid-buffering capacity than PCSs, driven by their more homogeneous, pH-dependent surface properties favoring inner-sphere coordination. Base cation release followed Ca²⁺ ≫ Mg²⁺ ≫ Na⁺ ≈ K⁺ across all soils; VCSs showed a twofold-higher Mg²⁺ pseudo-second-order rate constant and a strong Mg²⁺-Mn²⁺ positive correlation (R² > 0.804, p < 0.0001), exposing them to dual risks of Mn phytotoxicity and Mg deficiency during acidification. The well-fitted parabolic diffusion model for Al³⁺ and Mn²⁺ release further indicated prolonged, diffusion-limited metal toxicity risk in VCSs. A critical soil organic carbon (SOC) threshold of 8.1 g kg⁻¹ was identified, exceeding this value effectively retarded acidification via enhanced cation exchange capacity (CEC) and base retention. These findings provided a mechanistic framework for developing soil-specific strategies to manage and mitigate agricultural soil acidification. Full article

Conductive polymer nanocomposites (CPC) are widely investigated as chemo-resistive materials for the detection of volatile organic compounds (VOC). However, the physical mechanisms governing their transient electrical response remain only partially understood, limiting the development of predictive models and highly selective sensors. In this work, the chemo-resistive behaviour of carbon nanoparticle-filled poly(ethylene-co-ethyl acrylate) (EEA-CNP) was investigated through a multiphysics experimental approach combining simultaneous measurements of solvent uptake, dimensional changes, temperature and electrical resistance during toluene sorption and desorption. Thick specimens were deliberately employed to amplify transient diffusion phenomena and enable direct observation of the coupling between mass transport, polymer swelling and conductive network evolution. The results demonstrate that electrical resistance cannot be interpreted solely from the average solvent concentration within the material. Instead, the transient response is primarily governed by solvent concentration gradients, which continuously modify the connectivity of the conductive nanoparticle network during diffusion. This mechanism explains the pronounced hysteresis observed between sorption and desorption, the transient resistance overshoot during sorption, and the absence of a unique relationship between resistance and solvent content under dynamic conditions. A dedicated quasi-static desorption protocol was therefore developed to minimise concentration gradients and establish the intrinsic correlation between electrical resistivity and solvent fraction. The experiments further show that a solvent content of approximately 6 wt% is sufficient to completely disrupt the conductive percolation network. These findings provide new insights into the multiphysics mechanisms governing chemo-resistive sensing and establish an experimental basis for the development and validation of predictive models for conductive polymer nanocomposites. The proposed methodology is expected to contribute to the optimisation of next-generation VOC sensors and electronic noses with improved selectivity and predictive capability. Full article

Psoriatic arthritis (PsA) is a chronic immune-mediated arthropathy characterized by synovitis, enthesitis, and coupled bone erosion and pathological new-bone formation. Although biologics have improved outcomes, incomplete or lost response and safety constraints motivate the search for complementary multi-target candidates. Here, herb–compound records from OASIS; compound–target interactions from DrugBank, TTD, and STITCH; and curated PsA disease genes from DisGeNET were integrated into a multiscale interactome, and a biased random walk with restart was applied to prioritize herbs and constituents. Herbs were ranked by diffusion-profile similarity to PsA together with disease–target overlap. The prioritized set comprised three literature-supported comparator herbs and six candidate herbs without prior PsA evidence. Enrichment of the shared targets against PsA-relevant KEGG pathways returned IL-17 signaling, TNF signaling, Th17-cell differentiation, and osteoclast differentiation, while integrated network analyses—rather than pathway enrichment alone—identified TRAF3IP2 and RUNX2, together with BMP4, as recurrent nodes linking inflammation to bone remodeling. Compound-resolved subnetworks nominated constituent-level mechanisms, and site-resolved docking identified α-asarone as the most ligand-efficient molecule within the tested candidate panel and, provisionally, iNOS as the target with the most consistently favorable ligand efficiency in that panel. These convergent computational findings are hypothesis-generating and define candidates for experimental evaluation. Full article

The present study investigates the physicochemical behavior of the first-line anti-tuberculosis drugs isoniazid (INH) and ethambutol, in the form of dihydrochloride (E·(HCl)₂), in aqueous solutions containing the synthetic macrocyclic resorcinarene, C-tetra(propyl)resorcin[4]tetrasulfonate (Na₄PRA) at 298.15 K. Taylor dispersion experiments were conducted to determine the ternary diffusion coefficients of these systems, offering valuable insights into their transport properties. Non-zero cross-diffusion coefficients (${\mathit{D}}_{12}$ and ${\mathit{D}}_{21}$) demonstrate significant coupled transport, collectively indicating interactions between these antibiotics and the resorcinarene host. This behavior is highly consistent with the formation of a host–guest complex. These diffusion measurements were complemented by NMR spectroscopy, which confirmed the formation of host–guest complexes between the respective drugs and this resorcinarene, Na₄PRA. Full article

Package-level hygrothermal simulations commonly represent drying at epoxy molding compound (EMC) surfaces using idealized boundary conditions, which may not fully capture the coupled effects of bulk moisture diffusion and surface evaporation during reflow soldering and thermal cycling. This study developed a diffusion- and evaporation-based hygrothermal mechanical model for quad-flat no-lead (QFN) packages by incorporating an evaporation boundary formulation with moisture transport parameters obtained from independent moisture absorption and desorption experiments. The mass transfer Biot number S was introduced to quantify the relative roles of bulk moisture diffusion and surface evaporation in package desorption. Comparative simulations demonstrated that S influenced surface moisture removal kinetics and moisture retention during thermal loading, resulting in variations in predicted hygrothermal stress evolution. The proposed approach provides an experimentally calibrated and physically representative treatment of desorption boundaries for reliability analysis of plastic encapsulated packages. Full article

In contemporary online environments, the dynamics of the attention economy drive payoff-seeking, irresponsible information diffusion, resulting in severe discourse polarization. This study defines the primary objective function for society as the maintenance of “Informational Hygiene.” To capture these dynamics, we propose an Adaptive Co-evolution model that integrates incomplete information games with bounded rationality and evolutionary opinion dynamics. We incorporate a subjective expected payoff function, based on information asymmetry, into a scale-free network model. The interaction between agents’ internal states (infection degree, psychological damage, resilience) and network topology changes (edge deletion and rewiring) is formulated as a hybrid dynamical system of coupled ordinary differential equations and discrete topological updates. Extended computational experiments evaluate the coupled dynamics of autonomous edge deletion (structural bypass) and global propagation suppression (circuit breakers). The simulation results demonstrate that “subtractive interventions”—creating discriminatory boundaries by completely severing ties with contamination sources—can halt information spread but tend to fragment the social network irreversibly. Depending on inherent resilience parameters, this structural collapse conditionally isolates agents from social buffering mechanisms, causing a “Paradox of Isolation” characterized by strong hysteresis, where internal damage diverges. To ensure informational hygiene and prevent irreversible polarization, we suggest that platforms must implement “reasonable accommodation.” Specifically, “additive interventions”—comprising autonomous rewiring to healthy nodes to maintain inclusive boundaries (weak ties) and foster the complex contagion of resilience—are mathematically optimal prerequisites for next-generation intervention platforms. Full article

The negative differential resistance (NDR) effect provides nonlinear control over ionic current and has important potential in ion sensing and information storage. A multiphys-ics numerical model is established using COMSOL Multiphysics 6.3, coupling the Poisson−Nernst−Planck and Navier−Stokes equations to investigate the effects of solution concentration gradient, pore length, pore diameter, and surface charge density on NDR effect. The results indicate that the NDR effect occurs only in the negative voltage range, where concentration gradient diffusion competes with electric field driven migration. The characteristic voltage window stabilizes between −0.2 V and −0.5 V, and the total current reaches a local extremum near −0.2 V. Electromigration dominates in this range and sup-presses Cl⁻ ion diffusion, while K⁺ transport is less affected, resulting in decreased total ionic current. Under baseline conditions, the total current decreases by 26.19%, from −0.42 nA to −0.31 nA. Increasing the concentration gradient, shortening the pore length, enlarging the pore diameter, and reducing the surface charge density enhance local vortices or maintain Cl⁻ diffusion pathways, thereby strengthening NDR characteristics. This study reveals the regulation mechanisms of NDR effect by solution conditions, macropore structures, and surface properties, providing theoretical guidance for tunable ionic current devices. Full article

This study presents a physics-informed, climate-responsive model for predicting carbonation depth and compressive strength degradation in conventional and sustainable cementitious composites under real environmental exposure. The Semi-Theoretical Predictive Degradation (STPD) model couples hourly temperature, relative humidity, and CO₂ concentration data with two-dimensional diffusion–reaction equations implemented in FEniCS. The model accounts for humidity-sensitive diffusivity, temperature-activated carbonation kinetics, and CO₂ consumption via Langmuir decay. Experimental validation was performed on ordinary Portland cement (OPC) concrete specimens exposed for 30 days to climate profiles representative of Portugal (average 14.2 °C, RH 74%, CO₂ ~417 ppm) and Slovakia (average 4.7 °C, RH 80%, CO₂ ~414 ppm). Carbonation depth increased from 0 to 0.30 mm in Portugal and up to 0.15 mm in Slovakia, with corresponding predicted reductions in compressive strength relative to the corresponding uncarbonated reference of up to 25% and 14%, respectively. The STPD model accurately reproduced these trends, achieving RMSE values of 0.008 mm for carbonation depth and 1.55 MPa for compressive strength in OPC concrete. To assess the broader applicability of the framework, simulations were extended to fly ash/slag-blended, geopolymer, and biochar-containing concretes using material-specific parameters. Among the simulated systems, geopolymer concrete showed the highest predicted durability, with carbonation depths below 1 mm and strength loss below 10%. A degradation index combining carbonation depth and strength loss mapped high-risk zones near the exposed surface, particularly under warm and fluctuating climatic conditions. The model provides a transferable framework for climate-informed durability assessment, material selection, and the design of sustainable cementitious composites. Full article

Medium-resolution building-footprint mapping is limited by two coupled problems: 10 m optical pixels mix roofs with roads and bare surfaces, and SAR observations are degraded by speckle and viewing geometry. We present ACBDT, a Sentinel-1/2 framework that encodes each modality separately, learns a diffusion-inspired time-step-conditioned fused teacher representation, transforms it through a Cross-Modal Distillation Bridge (CMDB), and refines the output with a Student Refinement Decoder. The time-step variable is used only as a stochastic conditioning index; ACBDT does not implement a forward noising schedule, reverse diffusion, or iterative diffusion sampling. Training and evaluation used 2680 paired 256 × 256 patches over eight Yangtze River Delta cities with a spatially disjoint block partition. In three independent runs on the held-out test partition, ACBDT achieved 85.61 ± 0.32% building IoU, 92.24 ± 0.19% F1, and 83.74 ± 0.34% dataset-level boundary F1, compared with 83.21 ± 0.24% IoU for the strongest baseline, FTransUNet. Repeated-seed ablation showed 79.01 ± 0.42% IoU without CMDB and 84.53 ± 0.20% IoU without time-step conditioning. The separate density diagnostic retained a positive full-minus-optical IoU difference across all five building-density strata. Conclusions are limited to this Yangtze River Delta evaluation; city-held-out and cross-season transfer were not tested. Full article