This paper introduces peri urban dislocation as a structural condition that complements existing sprawl metrics by capturing hierarchical misalignments between inner city and peripheral areas. Whereas conventional measures emphasise density, land-use mix, or fragmentation, peri-urban dislocation reflects deeper divergences in the core periphery relational functional organisation of urban systems. We operationalise this concept using percolation analysis of street networks, revealing hierarchical patterns via clustering maps and dendrograms, providing a relational structure between urban elements. Two case studies, Valdivia, Chile, and Boston, USA, demonstrate contrasting manifestations: a structural reversal in Valdivia, where a homogeneous residential periphery dominates the hierarchical clustering process, and peri-urban voids in Boston, where isolated parcellations persist despite metropolitan consolidation. These findings position peri-urban dislocation as a structural dimension linked to sprawl yet distinct from metrics based on density or peripherality; one that may occur independently or represent a previously unidentified structural signature of sprawl. Methodologically, we apply established percolation techniques to expose this previously unarticulated structural phenomenon, enabling the detection of hierarchical misalignments within urban systems. Conceptually, we introduce peri urban dislocation as a new dimension of urban structure, helping articulate debates on sprawl and peri urbanisation through a complexity informed lens and enabling core periphery diagnostics across diverse urban contexts.

Human behaviors, particularly non-pharmaceutical interventions (NPIs), are dynamically coupled with epidemic spreading. While prior studies mainly assume a linear interplay, real-world behavioral evolution is driven by nonlinear responses and social influence. Here, we incorporate these multifaceted mechanisms into a co-evolutionary model and analytically derive the critical thresholds. Notably, as the infection rate grows, NPI compliance initially rises but then abruptly drops to zero. This paradoxical decline indicates an emergent social dilemma: at high infection rates, abandoning NPIs is individually optimal but detrimentally triggers an explosive surge in epidemic prevalence. We further show that socially induced overestimation of the infection rate can counterintuitively prompt individuals to abandon NPIs. Moreover, the interplay with social influence induces periodic oscillations, reflecting a tragic cycle of recurrent epidemic waves. Furthermore, we validate the robustness of this NPI-abandonment dilemma in networked population. Our work illustrates rich emergent phenomena in the co-evolution of epidemic and behavior, challenging traditional views on this coupled dynamics.

We analyze five-neighbor particle cellular automata whose conventional two-dimensional fundamental diagrams are multivalued, but whose mean flow is uniquely determined by introducing a second density. We first consider binary rules for which the second density is conserved, and then examine rules for which the second density is not conserved but converges asymptotically. These examples give three-dimensional fundamental diagrams in which the mean flow is determined by the particle density and the second density. We then investigate whether this single-valued structure is preserved under real-valued max-plus extensions. There are some rules where two different max-plus extensions are introduced, and numerical simulations show that both extensions preserve the same single-valued three-dimensional fundamental diagram. These observations imply that, in constructing real-valued max-plus extensions, it is important to choose the flux function and the second density consistently.

Understanding how group interactions influence opinion dynamics is fundamental to the study of collective behavior. In this work, we propose and study a model of opinion dynamics on $d$-uniform hypergraphs, where individuals interact through group-based (higher-order) structures rather than simple pairwise connections. Each one of the two opinions $A$ and $B$ is characterized by a quality, $Q_A$ and $Q_B$, and agents update their opinions according to a general mechanism that takes into account the weighted fraction of agents supporting either opinion and the pooling error, $\alpha$, a proxy for the information lost during the interaction. Through bifurcation analysis of the mean-field model, we identify two critical thresholds, $\alpha_{\text{crit}}^{(1)}$ and $\alpha_{\text{crit}}^{(2)}$, which delimit stability regimes for the consensus states. These analytical predictions are validated through extensive agent-based simulations on both random and scale-free hypergraphs. Moreover, the analytical framework demonstrates that the bifurcation structure and critical thresholds are independent of the underlying topology of the higher-order network, depending solely on the parameters $d$, i.e., the size of the interaction groups, and the quality ratio. Finally, we bring to the fore a nontrivial effect: the large sizes of the interaction groups, could drive the system toward the adoption of the worst option.

Affective polarization and political sorting drive public antagonism around climate change and other issues at the science-policy nexus. We study cross-domain spillover of incivility in public engagements with climate change and public health on Twitter and Reddit using the COVID-19 period as a case study. We find strong evidence of the signatures of affective polarization surrounding COVID-19 spilling into the climate change domain. Across different social media systems, COVID-19 content is associated with incivility in climate discussions. These patterns of increased antagonism were responsive to pandemic events that made the link between science and public policy more salient. The observed spillover activated along pre-pandemic political cleavages, specifically anti-internationalist populist beliefs, that linked climate policy opposition to vaccine hesitancy. Our findings show how affective polarization in public engagement with science becomes entrenched across policy domains, which has implications for how the public engages with and communicates about issues such as climate change and public health.

We present a practical and effective method of planetary defense that allows for extremely short mitigation time scales if required as well as long time scale mitigation. This one system allows for virtually any required defense mode. In general, it uses much less launch mass with vastly shorter required response time than classical deflection techniques The method uses an array of small hypervelocity kinetic penetrators that pulverize and disassemble an asteroid or small comet. This approach works in both long warning time, as well as in short warning scenarios with intercepts of minutes to days before impact. In longer time intercept scenarios, the disassembled asteroid fragments largely miss the Earth. In short intercept scenarios, the asteroid fragments of maximum $\sim$10-meter diameter allow the Earth's atmosphere to act as a "beam dump" with fragment burn up and/or air burst, with the primary channel of energy going into spatially and temporally de-correlated shock waves. The effectiveness of the approach depends on the intercept time and size of the asteroid but allows for effective defense against asteroids in the 20-1000m diameter class and could virtually eliminate the threat. A 20m diameter asteroid ($\sim$0.5Mt, similar to Chelyabinsk) can be mitigated with a 100s prior to impact intercept with a 10m/s disruption. With ~1m/s internal disruption, a 5 hour prior to impact intercept of a 50m diameter asteroid ($\sim$10Mt yield, similar to Tunguska), a 1 day prior to impact intercept of 100m diameter asteroid ($\sim$100Mt yield), a 20 day prior to impact intercept of Apophis ($\sim$370m diameter, $\sim$4Gt yield). The use of active (explosive) penetrators including nuclear allows the same system to mitigate extremely large threats. A "single launcher" solution to planetary defense using existing launch vehicles that achieve positive C3 becomes a viable option.