Abstract Age influences behavior, survival, and reproduction; hence, variation in population age structure can affect population-level processes. The extent of spatial age structure may be important in driving spatially variable demography, particularly when space use is linked to reproduction, yet it is not well understood. We use long-term data from a wild bird population to quantify covariance between territory quality and age and examine spatial age structure. We find associations between age and aspects of territory quality, but little evidence for spatial age structure compared with the spatial structure of territory quality and reproductive output. We also report little between-year repeatability of spatial age structure compared with structure in reproductive output. We suggest that high breeding site fidelity among individuals that survive between years, yet frequent territory turnover driven by high mortality and immigration rates, limits the association between age and territory quality and weakens overall spatial age structure. Greater spatial structure and repeatability in reproductive output compared with age suggests that habitat quality may be more important in driving spatially variable demography than age in this system. We suggest that the framework developed here can be used in other taxa to assess spatial age structure, particularly in longer-lived species, where we predict from our findings there may be greater structure.

Geodesic acoustic modes (GAMs), the high-frequency branch of zonal flows, play a crucial role in regulating turbulence and the associated anomalous transport in tokamaks. Although often treated as electrostatic oscillations, GAMs intrinsically possess an electromagnetic component, manifested as magnetic field perturbations. This component is essential for GAM's interaction with electromagnetic turbulence and for the existence of global GAM eigenmodes. However, a long-standing discrepancy exists between magnetohydrodynamic (MHD) and gyro-kinetic theories regarding the three-dimensional (3D) structure of these perturbations. MHD models consistently predict a full 3D structure, with dominant $m=2$ components in the radial and poloidal magnetic field perturbations and dominant $m=1$ component in the toroidal magnetic field perturbation, where $m$ denotes the poloidal wavenumber. In contrast, most gyro-kinetic studies, adopting the conventional parallel vector potential approximation ($\delta\vec{A} \approx \delta A_\|\vec{b}$), are restricted to describing only the $m=2$ poloidal component while systematically neglecting the radial and parallel (toroidal) components. This limitation has created a theoretical gap, preventing a unified understanding of the electromagnetic nature of GAMs.<br>To address this issue, we employ a self-consistent electromagnetic gyro-kinetic model without invoking the parallel vector potential approximation. Starting from the linear electromagnetic gyro-kinetic equation, we describe the perturbed distribution functions of both ions and electrons. The model is closed with a self-consistent set of field equations—including the quasi-neutrality condition and both the parallel and perpendicular components of Ampère’s law—which determine the evolution of the electrostatic potential $\delta\phi$, the parallel vector potential $\delta A_\|$, and the parallel magnetic perturbation $\delta B_\|$ (associated with the perpendicular vector potential $\delta A_\perp$). By retaining the full perturbed magnetic vector potential $\delta\vec{A}$, the framework naturally incorporates both parallel current perturbations (linked to $\delta A_\|$) and diamagnetic effects (linked to $\delta B_\|$). Analytical solutions are obtained in the long-wavelength limit for a large-aspect-ratio, circular tokamak, including first-order finite-Larmor-radius (FLR) and finite-orbit-width (FOW) effects.<br>For the first time within a gyro-kinetic framework, our analysis yields the complete 3D magnetic perturbation structure of the electromagnetic GAM. The results explicitly demonstrate that the radial ($\delta B_r$) and poloidal ($\delta B_\theta$) perturbations exhibit a dominant $m=2$ standing-wave structure, while the parallel perturbation ($\delta B_\|$) exhibits a dominant $m=1$ structure. This spatial structure is in excellent qualitative agreement with the predictions of ideal MHD theory, thereby resolving the long-standing discrepancy between the two theoretical approaches. Moreover, the gyro-kinetic model provides a refined physical picture beyond the reach of single-fluid MHD. The analytical expressions reveal distinct roles of ions and electrons: the $m=2$ radial and poloidal magnetic field perturbations, associated with parallel currents, are more strongly influenced by the ion thermal pressure, whereas the $m=1$ parallel magnetic field perturbation, linked to diamagnetic effects, receives a relatively larger contribution from the electron thermal pressure. These results not only unify the theoretical description of GAM magnetic perturbations but also advance our understanding of their kinetic physics, offering a more accurate foundation for experimental diagnostics and numerical simulation.

Functional ligand-mediated tailoring of size and spatial architecture in metal-organic framework/polymer hybrids for photothermal applications.

Genetic differentiation of habitat-forming kelp Ecklonia radiata across an urban estuary.

Mesh generation and geometric characteristics of multi-surface spatial structures based on surface partitioning and unfolding

DGTO: Derivable geodesics-coupled topology optimization for multi-axis 3D printing of continuous fiber-reinforced spatial structures

Stochastic congestion pricing and urban spatial structure in a monocentric city: A risk-adjusted equilibrium model

Environmental DNA as a tool for detecting ocean outfall impacts and environmental gradients in coastal ecosystems.

Spatial structure of a radio-frequency magnetron plasma at various Ar gas pressures for hydrophobic film preparation with a fluoropolymer PFA target

Placement of dedicated lanes for autonomous vehicles considering the changes of urban spatial structure

A novel simplified structure model for accurate and flexible simulation of radiation-induced DNA damage.

Human action understanding serves as a foundational pillar in the field of intelligent motion perception.Skeletons serve as a modality- and device-agnostic representation for human modeling, and skeleton-based action understanding has potential applications in humanoid robot control and interaction. However, existing works often lack the scalability and generalization required to handle diverse action understanding tasks. There is no skeleton foundation model that can be adapted to a wide range of action understanding tasks. This paper presents a Unified Skeleton-based Dense Representation Learning (USDRL) framework, which serves as a foundational model for skeleton-based human action understanding. USDRL consists of a Transformer-based Dense Spatio-Temporal Encoder (DSTE), Multi-Grained Feature Decorrelation (MG-FD), and Multi-Perspective Consistency Training (MPCT). The DSTE module adopts two parallel streams to learn temporal dynamic and spatial structure features. The MG-FD module collaboratively performs feature decorrelation across temporal, spatial, and instance domains to reduce dimensional redundancy and enhance information extraction. The MPCT module employs both multi-view and multi-modal self-supervised consistency training. The former enhances the learning of high-level semantics and mitigates the impact of low-level discrepancies, while the latter effectively facilitates the learning of informative multimodal features. We perform extensive experiments on 25 benchmarks across across 9 skeleton-based action understanding tasks, covering coarse prediction, dense prediction, and transferred prediction. Our approach significantly outperforms the current state-of-the-art methods. We hope that this work would broaden the scope of research in skeleton-based action understanding and encourage more attention to dense prediction tasks.

Multi-Agent Reinforcement Learning With Spatial Structure Awareness for Topological Map-Based Path-Finding

Adaptive spatial feature extraction and graphical feature awareness for robust point cloud registration.

Mechanisms of enhanced synergistic pollution reduction and carbon fixation induced by microalgal-bacterial interactions within different biofilm structures.

Abstract. Accurate registration of photogrammetric point clouds is essential for reliable geometric monitoring of slope instabilities. Although low-cost imagery provides an easy and inexpensive option for data acquisition, it often suffers from doming and drift-induced errors during reconstruction, resulting in geometric distortions within the point cloud. To mitigate these effects, a method for improving point cloud registration based on an segment-wise Iterative Closest Point (ICP) algorithm is presented. The approach subdivides the point cloud into small, locally rigid segments that are each aligned individually with a reference model. To ensure smooth transitions between neighboring segments, an interpolation of the local transformations is applied. The method is evaluated using data from Mt. Hochvogel, where several video sequences of the summit area are captured with low-cost cameras. For registration and reference, terrestrial laser scanning (TLS) data and a photogrammetric point cloud from an earlier epoch are used. The latter is used for change analysis based on M3C2 distance computation. The results demonstrate that the described distortions can be substantially reduced, particularly in comparison to a single global ICP registration, providing an effective means of improving registration accuracy for low-cost photogrammetric monitoring, especially when ground control point (GCP) measurements are not feasible. The overall registration quality depends strongly on the reconstruction quality and the chosen part size. Segments that are too small may not provide sufficient spatial structure to ensure a stable ICP solution in all three dimensions, whereas larger segments limit the local adaptability.

ABSTRACT In corridor-led urbanization, historic small towns risk a mismatch between spatial structure and local memory. Using Guoyang, China, as a diachronic case, this study reconstructs 1923/1966/2023 street networks and integrates Muratorian School, space syntax, and structured free recall into a framework centered on the Memory – Morphology Index (MMI) with LISA. Structural advantage shifts from the historical matrix route to a highway belt; system-wide, the median MMI is negative, indicating mild structure-leading, memory-lagging. Generational slices show young cohorts form an “old core and new axis” dual core, while overall migration is limited. These findings refine Cataldi’s “double urban life cycle” and motivate a dual-track strategy: structural optimization and memory gain.

ABSTRACT Traditional indoor space modelling in complex geometric environments faces challenges such as incomplete point cloud data, low accuracy in spatial topology identification, and limited automation. This paper proposes an indoor space topology modelling method based on 3D point cloud reconstruction and an improved PointNet++ algorithm to enable automated design generation. Indoor 3D point cloud data are first preprocessed through noise filtering, segmentation, and semantic annotation to enhance data quality. The PointNet++ framework is then improved by optimising hierarchical sampling and feature aggregation, incorporating multi-scale feature fusion and attention mechanisms to better capture spatial structures. A geometric constraint matrix and topology graph generation module are introduced, and a Graph Neural Network (GNN) is used to construct editable indoor space topology. Finally, the output is mapped to BIM parameters to achieve automatic design generation and optimisation. Compared with the traditional PointNet++ method, spatial recognition accuracy is improved to approximately 94%, topology modelling time is reduced by 23.9%, and the automatically generated design schemes achieve 98% consistency in spatial topology connectivity. These results demonstrate the effectiveness, efficiency, and scalability of the proposed method for complex indoor environments.

Falling Down (1993), directed by Joel Schumacher and starring Michael Douglas, follows a white, middle-class man whose attempt to regain control over his life leads to escalating violence and collapse. The protagonist, Foster embodies the crisis of hegemonic masculinity and the dismantling of traditional male identity. Each encounter he has with characters from different ethnic, social, and economic backgrounds descends him into chaos. In this context, his violent journey across Los Angeles is a symbolic repudiation of the Melting Pot and a stark indictment of the unfulfilled promises of the American Dream. This study discusses white masculinity within the ideological frameworks of the American Dream and the Melting Pot ideal by intertwining Connell’s insights on hegemonic masculinity, Arthur Miller’s essay on tragic hero, and Bourdieu’s masculine dominance. With ideological and formal film analysis, this essay argues how Falling Down (1993) depicts a crisis of masculinity through its use of space, visual composition, and character encounters. While the film has often been discussed in terms of masculinity in crisis, this study argues that the crisis extends beyond personal or psychological dimensions which is rooted in the spatial and symbolic structure of the film. The analysis concludes that these illusory promises collapse under social and cultural fragmentation.

The Poynting vector provides a rigorous framework for understanding electromagnetic energy flow, revealing that power is transported by fields in space rather than conductors. Although central to Maxwell’s equations, its physical interpretation in everyday circuits is often overlooked. This paper revisits the Poynting vector’s theoretical basis—energy density, Poynting’s theorem, and applicability in static and dynamic regimes—and applies it to three representative systems: a battery–resistor circuit, a coaxial cable, and a circular loop. Using a field-based analytical approach supported by peer-reviewed studies, each case demonstrates how electric and magnetic field configurations govern the paths of energy transfer. Calculations and visualizations confirm that the total Poynting flux matches conventional circuit-theoretic power, while exposing the spatial structure of energy distribution that circuit models cannot capture. The findings highlight the Poynting vector’s value as both a conceptual and practical tool. Clarifying fundamental misconceptions, informing high-frequency circuit design, and improving electromagnetic system analysis.