Congratulations, and keep enjoying the research journey!! 🚀
Congratulations, and keep enjoying the research journey!! 🚀
Yesterday we had the pleasure of attending her talk on control mechanisms to eliminate Diaphorina citri, super interesting!!!
Yesterday we had the pleasure of attending her talk on control mechanisms to eliminate Diaphorina citri, super interesting!!!
Importantly, this abrupt behavior disappears in the pairwise limit, highlighting the destabilizing effect of group interactions.
Importantly, this abrupt behavior disappears in the pairwise limit, highlighting the destabilizing effect of group interactions.
Big congrats to @pvalganon.bsky.social for a superb PhD thesis!
It has been great to have you with us these years and wish you a vibrant and exciting scientific journey ahead. 🚀
Congrats also to the supervisors @sorianopanos.bsky.social & @gomezgardenes.bsky.social
Big congrats to @pvalganon.bsky.social for a superb PhD thesis!
It has been great to have you with us these years and wish you a vibrant and exciting scientific journey ahead. 🚀
Congrats also to the supervisors @sorianopanos.bsky.social & @gomezgardenes.bsky.social
We find that they precipitate a transition from localized outbreaks (confined to vulnerable patches) to a widespread propagation.
🧭 This drastically shifts the spatial epidemic landscape.
We find that they precipitate a transition from localized outbreaks (confined to vulnerable patches) to a widespread propagation.
🧭 This drastically shifts the spatial epidemic landscape.
We show that transit-based infections reshape this boundary, modifying the critical conditions under which mobility boosts or suppresses epidemic outbreaks.
We show that transit-based infections reshape this boundary, modifying the critical conditions under which mobility boosts or suppresses epidemic outbreaks.
We show that neglecting in-transit infections leads to a serious underestimation of epidemic severity and population vulnerability. A hidden risk that standard models miss 🧩
We show that neglecting in-transit infections leads to a serious underestimation of epidemic severity and population vulnerability. A hidden risk that standard models miss 🧩
🚌 But what about infections acquired on the move?
We extended our MIR framework introducing infections that happen while commuting, in particular on public transport, key in urban settings.
🚌 But what about infections acquired on the move?
We extended our MIR framework introducing infections that happen while commuting, in particular on public transport, key in urban settings.
Agents with low exploratory behavior spend less time in new places, reducing the spread window and raising the required mobility to generate a global epidemic.
Agents with low exploratory behavior spend less time in new places, reducing the spread window and raising the required mobility to generate a global epidemic.
Interestingly, it depends on how frequently agents return versus how much they roam:
Random-walk–dominated dynamics (low return, high mobility) typically yield a higher threshold for 🦠 to spread!
Interestingly, it depends on how frequently agents return versus how much they roam:
Random-walk–dominated dynamics (low return, high mobility) typically yield a higher threshold for 🦠 to spread!
High return → more commuting 🚌 (agents quickly go back), low return → more exploration 🧭 (random walks).
High return → more commuting 🚌 (agents quickly go back), low return → more exploration 🧭 (random walks).
☑️ Large hyperedge overlap hinders synchronizability. In particular, large intra-order overlap can fragment structures, making global synchronization impossible!
☑️ On the other hand, large overlap promotes local synchronization
☑️ Large hyperedge overlap hinders synchronizability. In particular, large intra-order overlap can fragment structures, making global synchronization impossible!
☑️ On the other hand, large overlap promotes local synchronization
Inter-order overlap can promote the mesoscale localization (large overlap) or distort it (low overlap).
There is a hierarchy 🥇🥈🥉, the larger the interaction order, the stronger these effects!!!
Inter-order overlap can promote the mesoscale localization (large overlap) or distort it (low overlap).
There is a hierarchy 🥇🥈🥉, the larger the interaction order, the stronger these effects!!!
☑️ Intra-order hyperedge overlap (shared nodes within same-order groups).
☑️ Inter-order hyperedge overlap (shared nodes across different-order groups).
☑️ Intra-order hyperedge overlap (shared nodes within same-order groups).
☑️ Inter-order hyperedge overlap (shared nodes across different-order groups).
How does hyperedge overlap affect synchronization stability itself?
How does hyperedge overlap affect synchronization stability itself?
Congrats Alex on the CSS award, you rock!!!
Congrats Alex on the CSS award, you rock!!!