Expanding the state space of the Susceptible-Infectious-Susceptible model on networks gives nodes a memory of susceptibility, providing more accurate estimates of the epidemic threshold and quasi-stationary distribution.
đź”— go.aps.org/4uzNdFR
ALT Figure with two graphs showing the fraction infected on the Y axis and the infection rate on the X axis. The top graph is for 3-regular random graphs and shows a green curve for K=1, a pink curve for K=8, and black dots indicating the simulation. The bottom graph is for 4-regular random graphs and appears very similar. The black dots closely follow the pink line in both cases, showing a compelling improvement in predictions.
The #WorldCup is underway, but soccer is more than goals and glory — it’s a complex network.
#APSNews interviewed two researchers who used statistical physics and network science to uncover hidden patterns in “the beautiful game”: go.aps.org/3QbAtH9
This study finds that in biomolecular #Condensates, the process of aging emerges from basic physical principles — a potential mechanism that could explain why these droplets, which are initially fluid, gradually solidify over time.
Learn more: go.aps.org/4dWUZoe
ALT A graph showing the estimated storage modulus, labeled G′ and shown as a solid black line, and loss, labeled G′′ and shown as a dashed black line, using the intermediate scattering function measured after different lag times. Slopes characteristics of Maxwell viscoelastic gel are displayed as reference.
Direct measurements of persistent surfactant accumulation in a foam liquid and direct quantifications of micelle concentrations show an increase in micellar concentration with foam height and age.
Read the Letter: go.aps.org/4oetw4X
ALT Graph showing small-angle neutron scattering data for a foam aged eight hours at nine centimeters above the liquid surface. Insets point to different lines on the graph and show schematics of liquid channels, thin liquid films, and a micelle in foam liquid. A blue line with a negative slope shows liquid channels. An orange line that curves down sharply in multiple dips shows thin liquid films. and a micelle in foam liquid. A red lines that also has several dips down shows a micelle in foam liquid.
Using a finite-cell model of tumor evolution under drug-induced selection, this study details a Q-learning approach for identifying chemotherapy dosing schedules that balance therapeutic effectiveness with the evolutionary dynamics of drug resistance.
đź”— go.aps.org/4ue2vzN
ALT A graph showing time [steps] on the x axis and tumor volume on the y axis. The graph shows different values for background fitness, g: 2.0 in blue, 2.1 in orange, 2.2 in green, and 2.3 in red. The plots show that tumor volume decreases most sharply for higher background fitness values.
Bacteria can propel themselves like a corkscrew by wrapping their flagella around their body. How do they do it? A new study in Physical Review E suggests they take advantage of motor-induced buckling instability to perform this method of locomotion.
đź”— go.aps.org/4eZvYtm
ALT Animated GIF of a device meant to mimic the flagellum of a bacterium. There is a thin black line hanging from a ball-shaped structure that rotates. As the animation plays, the thin line forms a helix that twirls and whirls in the tank.
How do opinions form? đź’
Using a network-based approach, physicists showed how local dynamics and community structure allow minority opinions to persist by gaining dominance in localized areas.
đź”— go.aps.org/4uku0HT
ALT Graphic showing an overview of the model. Agents are shown as blue or yellow dots. Each color represents one of two competing opinions. Two pathways show how opinions form on each node. One shows spontaneous opinion flipping. The other shows how opinions adjust due to influence of others, shown by one blue and two yellow dots that then become three yellow dots. At the bottom are more dots that show the change in proportion of yellow and blue to show the distribution of opinions at the end.
The work was done by Tim Mauch and Thilo Gross at the Helmholtz Institute for Functional Marine Biodiversity, Carl-von-Ossietzky University, and Alfred-Wegener Institute.
How do natural killer cells conduct reconnaissance? Using binary cell mixtures, researchers find two distinct strategies: they either swarm and kill cancer cells, or quietly patrol and watch fibroblasts.
đź”— go.aps.org/3PZCjLm
ALT A series of sequential microscopic images of natural killer cells and cancer cells in culture. The top row of four images displays natural killer cells alone in culture at four time points: 0 hours, 2 hours, 20 hours, and 40 hours. The middle row displays cancer cells alone in culture at the same time points. The bottom row displays natural killer cells cultured with cancer cells at the same time points. As time progresses, both cell groups gradually aggregate in all three culture conditions, but with different clustering behaviors.
Researchers developed a model that describes how the copolymer P(VDF-TrFE) switches between ferroelectric and paraelectric phases, then used it to calculate hysteresis loops and dielectric permittivity of a real semicrystalline polymer.
Read their paper: go.aps.org/4voxDh2
ALT Four square plots showing red hysteresis loops for a single crystal for four values of temperature. E(10^8 V/m) is on the X axis from -2 to 2, and P (D) is on the y axis from -2 to 2. 600 K shows a wide vertical rectangle with an extending line at each end, 650 K shows a narrow vertical rectangle with an extending line at each end, 670 K shows a diagonal line with four bends, and 700 K shows a very slightly curved diagonal line.
Vadim V. Atrazhev, Dmitry V. Dmitriev, and Vadim I. Sultanov from the N. M. Emanuel Institute of Biochemical Physics of the Russian Academy of Science authored the study.
Maybe “shoot for the moon” isn’t the best strategy after all? 🌙
A model suggests the optimal level of ambition is slightly above average: ambitious enough to reach better opportunities, but not so high you waste time chasing impossible goals. Read more in @PhysRevE: go.aps.org/4wXLEnA
ALT A grid of six graphs titled "Landscape properties" comparing fitness landscape dynamics (Reward over Time) on the left with their corresponding distributions (Frequency over Reward) on the right. From top to bottom: a "Smooth landscape" shows a steadily increasing reward line paired with a "Left skew" distribution (peaking at high rewards); an "Intermediate landscape" features a fluctuating but upward-trending reward line paired with a symmetrical "No skew" distribution; and a "Rugged landscape" displays highly volatile, erratic reward spikes paired with a "Right skew" distribution (peaking at low rewards).
A new study suggests that motion of #BiomolecularCondensates is different from that of colloidal particles. Externally-controlled dynamic states, such as condensate motion, lead to polarization and dipole force fields.
đź”— go.aps.org/4x8sds4
ALT Graphic comparing the motion of a condensate and a colloidal particle moving with a velocity of v. On the left is the condensate, which is moving with a chemical potential gradient. On the right is the colloidal particle, which is moving with a hydrodynamic pressure gradient. The gradient of each is shown by arrows with higher values in red and lower values in blue.