Dynamics of intra- and inter-regional activities of the auditory 'Where' pathway during sound localization: An fMRI study.

Higher-order derivative-constrained univalent conformal maps for complex potential flow simulation

Soil-borne plant parasites and pathogens in agricultural landscapes can persist and disperse over time, yet their movement across habitat boundaries remains an underexplored but ecologically important process. While edge effects and cross-boundary movement have been widely studied in above-ground systems, below-ground dynamics-shaped by soil structure, host distribution and seasonal cycles-have received far less attention. In this review, we synthesize current knowledge on below-ground spillover, define key ecological mechanisms influencing its dynamics and propose a framework for understanding how soil-borne pests move, survive and interact across space and time-focusing on soil-borne parasites. We emphasize the role of habitat boundaries, edge permeability and seasonal feedback, integrating insights from landscape ecology, plant pathology and movement theory. To capture these dynamics, we introduce the Soil Spillover Framework (SSF), a multi-variable model incorporating persistence potential, trophic interactions, vector pathways, dispersal cost, buffering effects and biotic flow. We argue that buffer zones, soil structure and connectivity shape spillover probabilities in ways that are often nonlinear and temporally delayed. By conceptualizing below-ground boundaries as filters or amplifiers of spillover, this synthesis offers a foundation for predictive modelling and integrated management. Understanding how soil-borne pests move and persist across boundaries is critical for managing crop diseases, conserving biodiversity and designing resilient agroecosystems in a fragmented world. This article is part of the theme issue 'Wild plant pathosystems'.

ABSTRACT In this study, an analytical solution for the potential flow past two unequal circular cylinders is derived using the bipolar degenerate kernel within the boundary integral equation. The analytical solution for the two identical cylinders was shown to agree well with the results of Lebedev, Skalskaya, and Uflyand (1965) and Morse and Feshbach (1953). For the unequal cylinder case, the analytical results were also compared with those in Morse and Feshbach’s book. We identified three noteworthy points. First, the velocity potential obtained by the present formulation is different from the constant term, although it does not have any effect on the velocity. Second, both formulas were found to differ by a sign, which can be explained by the different conventions used to define the angular coordinates in the bipolar coordinates. Third, even when employing the same definition of angular coordinates in our numerical tests, we find that the sign in Morse and Feshbach’s book, as well as in Lebedev, Skalskaya, and Uflyand (1965), is still incorrect. To verify these three points, numerical results for the finite series terms were obtained. The velocity distribution for different angles of attack was plotted in bipolar coordinates for the case of two unequal circular cylinders.

Turing patterns are a well-studied model of reaction-diffusion equationsfor developmental patterning. Their applicability has often been limited by the difficulty in identifying candidate molecules that satisfy the requisite criteria for patterning. Here, we build on recent work on geometric models to describe Turing patterning as a potential flow. We show how the universal dynamics of Turing patterning is described by a landscape, largely independent of the underlying reaction-diffusion equations. We apply our framework to three-component systems and demonstrate that we can accurately capture the dynamics of any given component. We extend our framework to larger networks and to models of Turing patterns coupled with external morphogens that provide positional information. We provide a quantitative description of the dynamics of chosen markers and apply it to the dynamics of SOX9 expression during digit patterning.

An efficient two-way coupling approach for viscous and potential flows in free-surface hydrodynamic simulations

Multi-objective optimization to explore the potential optimal thermal and flow performance of a packed bed humidifier

Abstract An accurate track forecast for tropical cyclones (TCs) is critical for disaster prevention and mitigation. Although various models, including statistical, numerical, and artificial intelligence (AI) based, have demonstrated good skill in TC track forecasting, they have not ever been (and will not ever be) perfect, resulting in large uncertainties among them. To reduce the uncertainties, the Spatiotemporal Integrated Forecast Network (ST-IFNet), an integrated model, is developed using deep learning techniques and the track forecasts from seven operational agencies. ST-IFNet utilizes agency-time dual-branch attentions to dynamically adjust the weights of each agency at each time step and concurrently mines the physical trends of the changes in TC movement by the incorporation of environmental data. Experimental results show that ST-IFNet outperforms the operational forecast from any of the agencies as well as a simple average of them, especially in the medium-term (36–48 h) and long-term (60–120 h) TC track forecasts, achieving a track position error (TPE) as low as 62.89, 78.93, 123.96, 139.91, and 177.69 km for 24, 48, 72, 96, and 120 h, respectively. Further analysis reveals that large-scale potential height fields (≥1000 km) and mesoscale flow fields (200–1000 km) obtained from scale separation provide the most valuable guidance for ST-IFNet. This work builds a bridge between numerical forecasts and artificial intelligence techniques and provides a useful and efficient tool for operational TC track forecasts in the future. Significance Statement This study develops Spatiotemporal Integrated Forecast Network (ST-IFNet), an integrated forecast model, based on deep learning techniques to forecast tropical cyclone (TC) tracks. It effectively utilizes multiagency forecasts of TC tracks as well as the corresponding environmental data to achieve higher accuracy of track forecast with minimal computational costs, significantly enhancing the TC track forecast in the South China Sea. In particular, the large-scale potential height fields (≥1000 km) and flow fields that span 200–1000 km are found to provide the most valuable guidance for ST-IFNet.

Design and dynamic response analysis of a 15 MW semi-submersible floating wind turbine

Abstract. Fire affects soil and vegetation, which in turn can promote the initiation and growth of runoff-generated debris flows in steep watersheds. Postfire hazard assessments often focus on identifying the most likely watersheds to produce debris flows, quantifying rainfall intensity-duration thresholds for debris flow initiation, and estimating the volume of potential debris flows. This work seeks to expand on such analyses and forecast downstream debris flow runout and peak flow depth. Here, we report on a high-fidelity computational framework that enables debris flow simulation over two watersheds and the downstream alluvial fan, although at significant computational cost. We then develop a Gaussian Process surrogate model, allowing for rapid prediction of simulator outputs for untested scenarios. With a modest training of debris flow simulations, this surrogate is able to approximate peak flow depth with a mean squared error that is generally in the range of 0.1–0.2 m. We utilize this framework to explore model sensitivity to rainfall intensity and sediment availability as well as parameters associated with saturated hydraulic conductivity, hydraulic roughness, grain size, and sediment entrainment. Simulation results are most sensitive to hydraulic roughness and grain size. Further, we use this approach to examine variations in debris flow inundation patterns at different stages of postfire recovery, and we find that the area inundated by postfire flows decreases substantially over a time period as short as 9 months. In this case, we also see that temporal changes in hydraulic roughness and grain size following fire would be particularly beneficial for forecasting debris flow runout throughout the postfire recovery period. The emulator methodology presented here also provides a means to compute the probability of a debris flow inundating a specific downstream region, consequent to a forecast or design rainstorm. This workflow could be employed in prefire scenario-based planning or postfire hazard assessments.

Background/Objectives: A known disadvantage of extracardiac Fontan is the absence of growth potential and potential late flow stagnation compared to lateral tunnel Fontan. This study investigates the differences in changes in the cross-sectional area and impact on liver fibrosis. Methods: The anteroposterior and lateral diameters of the Fontan pathways were measured using angiograms. Cross-sectional area and the indexed cross-sectional area were calculated, and their relation to Fibrosis-4 index was analyzed. Results: A total of 334 angiograms of 224 patients (212 extracardiac and 12 lateral tunnel Fontan) were evaluated. The median age at Fontan was 2.2 (Interquartile Range: 1.8-2.9) years. The median period from Fontan to angiogram was 3.3 (0.04-10.8) years. Cross-sectional areas remained unchanged in extracardiac Fontan patients and increased in lateral tunnel Fontan patients. The indexed cross-sectional areas in extracardiac Fontan patients decreased over time. The smallest indexed-cross-sectional areas were 200 mm2/m2 in extracardiac Fontan patients at 10 years postoperatively, whereas indexed cross-sectional areas in lateral tunnel Fontan patients were larger and more variable. Fibrosis-4 index increased time-dependently in both groups. Indexed cross-sectional area at the smallest level <156 mm2/m2 was identified as a risk factor for liver fibrosis. Conclusions: The Fontan pathway expanded in patients after lateral tunnel Fontan, whereas indexed cross-sectional area decreased over time after extracardiac Fontan. Importantly, in patients after extracardiac Fontan, narrowing of the Fontan pathway might be one of the risk factors for progression of liver fibrosis.

Thermal and mass management is one of the major components of material processing in various productive industries. A significant predictive analytical way is presented in this workto predict the heat and mass exchange during many industrial processes. More specifically, this work is very relevant to exploring the physics of ternary hybrid nanofluid (THNF), induced magnetic field, first-order chemical reaction, Darcy Forchheimer effects, suction/injection, modified heat and mass fluxes effects. The convective surface constraints are imposed to address the surface behavior of the dynamic disk. The typical potential Homann-type flow equations and the thermal and mass balance aspects are mathematically expressed via a set of nonlinear flow, thermal, mass, and induced magnetic field equations. However, the material composition is based on the effective inclusion of nanoparticles, CoFe2O4, ZnO and Au in the base liquid ethylene glycols. The influence of such physical factors is described through explicit graphical and numerical tables, while using the modified collocation method. Moreover, the valid behaviors of each controlling parameter are presented through the THNF temperature, concentration, velocity, resistive forces, and induced magnetic field. The ratio of stress and strain caused a significant enhancement in the flow components of the material. The thermal expansion factor reduced the material temperature significantly away from the surface. The Darcy and non-Darcy Forchiemer factors both cause a reduction in the flow speed of the composite THNF materials. The ratio of strain rate and disk linear deformation enhanced the flow speed, and a reduction is noted for the higher Eckert and thermal relaxation factor. The Biot number appeared in the surface condition, which decreased the thermal trend of the material. The time relaxation for the mass fraction factor diminished the material concentration, and the same is enhanced via the first chemical reaction factor. An authentic and justified comparison is generated to show the validity of the numerical method.

Genetically modified (GM) plants have been commercially grown for 30 years, and their acceptance depends on a thorough risk assessment. Environmental Risk Assessment (ERA) evaluates potential impacts of releasing GM plants into the environment, whether through cultivation or import for food, feed, and processing. A key component is assessing potential gene flow to crop wild relatives or non-GM crops. For gene flow to significantly affect the environment, transferred genes must provide a selective advantage. Since most GM plants are engineered for herbicide tolerance, insect resistance, or stacked traits, evaluating such advantages is relatively straightforward. New genomic techniques (NGTs) can generate plants with a wider range of traits, including tolerance to biotic and abiotic stress. Although still considered GM in the EU, their genomic changes can complicate detection, identification, and ERA, especially when such traits may offer advantages under stress conditions. This scoping review focuses on gene flow in two crops: oilseed rape (canola) (Brassica napus L.) and potato (Solanum tuberosum L.). In canola, transgene movement can increase weediness, fitness, herbicide resistance, or genetic diversity in feral or related populations. Gene flow in potato is less studied, with concerns centered on contamination risks in the Andean diversity center. Limited data exist for NGT plants, though many are expected to resemble conventionally bred varieties, suggesting comparable environmental impacts.

Rapidly and quantitatively assessing potential catastrophic debris flow risks over a regional scale is crucial for early-stage risk prevention and control. However, significant differences in the developmental conditions of various debris flow catchments pose considerable challenges to regional risk assessment. To address this, this study proposes a method for the rapid quantitative estimation of the population threatened by debris flows in the Bailong River Basin, aiming to identify potential sites of catastrophic debris flows. First, the SCS hydrological model is used to predict the peak discharge and maximum outflow volume of debris flows under a designed rainfall scenario. Including the innovative application of machine learning to construct a sediment supply prediction model. Then, an empirical formula for debris flow deposition fans in the region is applied to estimate the potential hazard area. Finally, this potential hazard area is overlaid with spatially gridded population distribution data to estimate the number of people potentially threatened by each debris flow catchment. Utilizing publicly available fundamental data, this method constructs a comprehensive estimation process for debris flows, covering rainfall-runoff-outflow volume-hazard area-threatened population. It provides a robust and scalable solution for the rapid quantitative assessment of regional catastrophic debris flow risks.

Abstract Debris‐flow disasters triggered by extreme rainfall have posted high risks in mountainous areas. However, the hazard of potential debris flows remains difficult to assess given the context of climate change. For this purpose, a novel quantitative framework for assessing the impact of climate change on debris flow hazard was proposed in this study. It can indicate how the hazard degree of a debris flow will change with a changing climate over different periods. The Changzhoucun (CZC) debris flow hazard in Tianjin of north China was selected as a case study. We analysed the evolution trends of extreme rainfall events versus time windows based on rain gauge data from 1951 to 2017. Four distribution functions were examined and compared, thus defining four different rainfall scenarios (full history, far history, mid history, near history). A physically‐based model named FSLAM was employed to compute stability in initiation areas and peak discharge in the channel. The FLO‐2D code was applied to simulate runout characteristics of the debris flow to conduct hazard mapping. We observed an increase in the extreme rainfall frequency in the summers of the region. The near history presented the largest rainfall level, whereas the full history was the smallest. Under the return period of 20 years, the projected difference in 48 h extreme rainfall and runoff between full history and near history reached 4.4% and 5.4%, respectively. In addition, the debris flow magnitude, characterized by depth, velocity and impact force, was also projected to increase, but these changes were unevenly distributed throughout the catchment. The results can contribute to better predicting debris flow development at catchment scales and provide a basis for the government to identify and manage high‐risk areas.

This study carries out a boundary element analysis to numerically investigate the hydrodynamic performance of a pile-supported oscillating water column breakwater wave energy converter subjected to obliquely incident waves, within the framework of linear potential flow theory. A bottom undulation effect, created by varying water depths on the lee and seaward sides, is adopted as an effective strategy to enhance wave power extraction under obliquely incident waves. Key hydrodynamic parameters, including optimal efficiency, wave reflection, transmission, wave loads, damping characteristics, diffraction flux, and optimal power exerted, are systematically investigated. Besides, the key hydrodynamic parameters are formulated and validated against the newly derived Haskind relation for obliquely incident waves. The findings reveal that an optimal chamber width ratio (b/h1=0.15) and front wall submergence (a1/h1=0.15), combined with a rear wall draft of a2/h1=0.40 maximize the energy capture while maintaining structural balance. Additionally, moderate oblique wave angles (30° and 45°) significantly enhance resonance and power output. Furthermore, a lower water depth ratio (h2/h1=0.55) effectively broadens resonance bandwidth and minimizes wave transmission, improving both efficiency and resilience. The study also demonstrates that seabed non-uniformity and concave bottom profiles can significantly enhance energy extraction compared to a conventional stepped seabed by amplifying the wave propulsion of the incident wave within the water column.

The Madelung equationsoffer a hydrodynamic description of quantum systems, from single particles to quantum fluids. In this formulation, the probability density is mapped onto the fluid density and the phase is treated as a scalar potential generating the velocity field. As examples of potential flows, quantum fluids described in this way are inherently irrotational, but quantum vortices may arise at discrete points where the phase is undefined. In this paper, starting from this irrotational description of a quantum fluid, a coarse-graining procedure is applied to arrive at a macroscopic description of the quantum fluid in terms of a hierarchy of moments in which the role of velocity is played by a Favre average of the microscopic velocity field. This hierarchy is truncated using an explicit closure derived from an expansion in a finite length scale. The resulting coarse-grained fields are shown to allow for finite vorticity at any point in the fluid. Furthermore, it is shown that this vorticity obeys a similar equationto the vorticity equationin classical hydrodynamics and includes a vortex-stretching term. The particular closure employed here also gives rise to a novel stress term in the fluid equations, which in the appropriate limit appears analogous to an artificial viscous stress from computational fluid dynamics.

A theoretical study is made of steady, subcritical (Froude number $F \lt 1$ ) two-dimensional free-surface flow due to a uniform stream flowing over smooth, locally confined bottom topography of large horizontal extent ( $L \gg 1$ ) and finite peak height ( $\varepsilon = O(1)$ ). In earlier work, this flow was analysed based on the nonlinear shallow-water equations which neglect the effects of dispersion altogether. This so-called hydraulic theory predicts a steady disturbance confined in the vicinity of the topography if $\varepsilon$ is below a critical value $\varepsilon _{\textit{crit}}(F)$ . The present asymptotic analysis of the full potential flow equations focuses on how dispersive effects (controlled by $\mu = 1/L \ll 1$ ) influence this steady state, particularly in regard to a steady short-scale radiating wave downstream that is ignored by hydraulic theory. Utilizing exponential asymptotics, it is shown that as $\varepsilon$ is increased this dispersive wave, whose amplitude is formally exponentially small with respect to $\mu$ , grows sharply and ultimately it becomes comparable with the hydraulic wave disturbance when $\varepsilon$ approaches $\varepsilon _{\textit{crit}}$ . Thus, the nonlinear shallow-water equations break down in the vicinity of $\varepsilon _{\textit{crit}}$ regardless of $\mu \ll 1$ . The asymptotic results are supported by numerical solutions of the full potential flow theory, which also reveal a limiting $\varepsilon$ , $\varepsilon _{\textit{lim}} \approx \varepsilon _{{ crit}}$ , above which steady wave responses cannot be computed. For $\varepsilon$ just below $\varepsilon _{\textit{lim}}$ , the downstream wave resembles a steep steady Stokes periodic wave, while for $\varepsilon$ slightly above $\varepsilon _{\textit{lim}}$ unsteady computations suggest that the downstream disturbance steepens and breaks.

This paper presents a computational study of wave–bathymetry and wave–structure interaction problems using advanced numerical techniques based on high-fidelity, two-phase Navier–Stokes (TpNS) flow and reduced-order, fully nonlinear potential flow models. For high-fidelity simulations, the TpNS equations are discretized using the finite-element method, with free-surface evolution captured through a hybrid level-set (LS) and volume-of-fluid (VOF) formulation. A monolithic, phase-conservative LS equation is introduced to mitigate mass loss and interface smearing, combined with a semi-implicit projection scheme. Hydrodynamic forces are resolved using a high-order, phase-resolving cut finite-element method (CutFEM), which enables the representation of complex solid geometries within a fixed background mesh. An equivalent polynomial of Heaviside and Dirac distributions ensures accurate evaluation of surface and volume integrals. Hence, no explicit generation of cut cell meshes, adaptive quadrature, or local refinement is required. For reduced-order modeling, a fast regularized boundary integral method (RBIM) is employed to solve the fully nonlinear potential flow. Singular and near-singular integrals are treated using a subtract-and-addition technique based on auxiliary functions derived from Stokes’ theorem, allowing direct application of high-order quadrature without conventional boundary element discretization. An arbitrary Lagrangian–Eulerian (ALE) formulation is adopted to enforce free-surface boundary conditions while avoiding excessive mesh distortion. The proposed approaches are applied to investigate highly nonlinear wave transformation over complex bathymetry and wave-induced dynamics of floating structures, including eddy-making damping effects. Numerical results are validated against experimental measurements. These two modeling approaches represent complementary levels of physical fidelity and computational efficiency, and their systematic comparison clarifies the trade-offs between computational accuracy, efficiency, and cost for practical marine problems.

Over 125 years ago, Henry Selby Hele-Shaw realised that the depth-averaged flow in thin-gap geometries can be closely approximated by two-dimensional (2-D) potential flow, in a surprising marriage between the theories of viscous-dominated and inviscid flows. Hele-Shaw approximation allows visualisation of potential flows over 2-D aerofoils and also undergirds important discoveries in the dynamics of interfacial instabilities and convection, yet it has found little use in modelling flows in microfluidic devices, although these devices often have thin-gap geometries. Here, we derive a Hele-Shaw approximation for the flow in the kinds of thin-gap geometries created within microfluidic devices. Using the method of weighted residuals, we reinterpret the Hele-Shaw approximation as the leading term of an orthogonal polynomial expansion that can be systematically extended to higher-order corrections. The resulting leading-order equation coincides with the previously derived 2-D approximations, but our derivation is shorter and more direct. By extending the expansion beyond leading order, we obtain a new reduced model that captures non-parabolic gapwise velocity profiles and out-of-plane flow effects. We provide substantial numerical evidence showing that approximate equations can successfully model real microfluidic and inertial-microfluidic device geometries. By reducing three-dimensional flows to 2-D models, our validated model will allow for accelerated device modelling and design.