Swelling of two-dimensional polymer rings by trapped particles

The mean area of a two-dimensional Gaussian ring of $N$ monomers is known to diverge when the ring is subject to a critical pressure differential, $p_c \sim N^{-1}$. In a recent publication [Eur. Phys. J. E 19, 461 (2006)] we have shown that for an inextensible freely jointed ring this divergence turns into a second-order transition from a crumpled state, where the mean area scales as $\sim N$, to a smooth state with $\sim N^2$. In the current work we extend these two models to the case where the swelling of the ring is caused by trapped ideal-gas particles. The Gaussian model is solved exactly, and the freely jointed one is treated using a Flory argument, mean-field theory, and Monte Carlo simulations. For fixed number $Q$ of trapped particles the criticality disappears in both models through an unusual mechanism, arising from the absence of an area constraint. In the Gaussian case the ring swells to such a mean area, $\sim NQ$, that the pressure exerted by the particles is at $p_c$ for any $Q$. In the freely jointed model the mean area is such that the particle pressure is always higher than $p_c$, and $$ consequently follows a single scaling law, $\sim N^2 f(Q/N)$, for any $Q$. By contrast, when the particles are in contact with a reservoir of fixed chemical potential, the criticality is retained. Thus, the two ensembles are manifestly inequivalent in these systems.Comment: 8 page

Law of corresponding states for osmotic swelling of vesicles

As solute molecules permeate into a vesicle due to a concentration difference across its membrane, the vesicle swells through osmosis. The swelling can be divided into two stages: (a) an "ironing" stage, where the volume-to-area ratio of the vesicle increases without a significant change in its area; (b) a stretching stage, where the vesicle grows while remaining essentially spherical, until it ruptures. We show that the crossover between these two stages can be represented as a broadened continuous phase transition. Consequently, the swelling curves for different vesicles and different permeating solutes can be rescaled into a single, theoretically predicted, universal curve. Such a data collapse is demonstrated for giant unilamellar POPC vesicles, osmotically swollen due to the permeation of urea, glycerol, or ethylene glycol. We thereby gain a sensitive measurement of the solutes' membrane permeability coefficients, finding a concentration-independent coefficient for urea, while those of glycerol and ethylene glycol are found to increase with solute concentration. In addition, we use the width of the transition, as extracted from the data collapse, to infer the number of independent bending modes that affect the thermodynamics of the vesicle in the transition region.Comment: 10 page

Why Monitor Violent Websites? A Justification

The authors argue that the international community should continue working together to devise rules for monitoring specific Internet sites, as human lives are at stake. Preemptive measures could prevent the translation of murderous thoughts into murderous actions. Designated monitoring mechanisms for certain websites that promote violence and seek adherents for the actualization of murderous thoughts could potentially prevent such unfortunate events. Our intention is to draw the attention of the international community' multi agents (law-enforcement agencies, governments, the business sector, including Internet Service Providers, websites administrators and owners, civil society groups) to the urgent need of developing monitoring schemes for certain websites, in order to prevent violent crime

Swelling of particle-encapsulating random manifolds

We study the statistical mechanics of a closed random manifold of fixed area and fluctuating volume, encapsulating a fixed number of noninteracting particles. Scaling analysis yields a unified description of such swollen manifolds, according to which the mean volume gradually increases with particle number, following a single scaling law. This is markedly different from the swelling under fixed pressure difference, where certain models exhibit criticality. We thereby indicate when the swelling due to encapsulated particles is thermodynamically inequivalent to that caused by fixed pressure. The general predictions are supported by Monte Carlo simulations of two particle-encapsulating model systems -- a two-dimensional self-avoiding ring and a three-dimensional self-avoiding fluid vesicle. In the former the particle-induced swelling is thermodynamically equivalent to the pressure-induced one whereas in the latter it is not.Comment: 8 pages, 6 figure

Smoothening Transition of a Two-Dimensional Pressurized Polymer Ring

We revisit the problem of a two-dimensional polymer ring subject to an inflating pressure differential. The ring is modeled as a freely jointed closed chain of N monomers. Using a Flory argument, mean-field calculation and Monte Carlo simulations, we show that at a critical pressure, $p_c \sim N^{-1}$, the ring undergoes a second-order phase transition from a crumpled, random-walk state, where its mean area scales as $\sim N$, to a smooth state with $\sim N^2$. The transition belongs to the mean-field universality class. At the critical point a new state of polymer statistics is found, in which $\sim N^{3/2}$. For $p>>p_c$ we use a transfer-matrix calculation to derive exact expressions for the properties of the smooth state.Comment: 9 pages, 8 figure

Asymptotic Behavior of Inflated Lattice Polygons

We study the inflated phase of two dimensional lattice polygons with fixed perimeter $N$ and variable area, associating a weight $\exp[pA - Jb ]$ to a polygon with area $A$ and $b$ bends. For convex and column-convex polygons, we show that $/A_{max} = 1 - K(J)/\tilde{p}^2 + \mathcal{O}(\rho^{-\tilde{p}})$, where $\tilde{p}=pN \gg 1$, and $\rho<1$. The constant $K(J)$ is found to be the same for both types of polygons. We argue that self-avoiding polygons should exhibit the same asymptotic behavior. For self-avoiding polygons, our predictions are in good agreement with exact enumeration data for J=0 and Monte Carlo simulations for $J \neq 0$. We also study polygons where self-intersections are allowed, verifying numerically that the asymptotic behavior described above continues to hold.Comment: 7 page

Electrostatic Interactions of Asymmetrically Charged Membranes

We predict the nature (attractive or repulsive) and range (exponentially screened or long-range power law) of the electrostatic interactions of oppositely charged and planar plates as a function of the salt concentration and surface charge densities (whose absolute magnitudes are not necessarily equal). An analytical expression for the crossover between attractive and repulsive pressure is obtained as a function of the salt concentration. This condition reduces to the high-salt limit of Parsegian and Gingell where the interaction is exponentially screened and to the zero salt limit of Lau and Pincus in which the important length scales are the inter-plate separation and the Gouy-Chapman length. In the regime of low salt and high surface charges we predict - for any ratio of the charges on the surfaces - that the attractive pressure is long-ranged as a function of the spacing. The attractive pressure is related to the decrease in counter-ion concentration as the inter-plate distance is decreased. Our theory predicts several scaling regimes with different scaling expressions for the pressure as function of salinity and surface charge densities. The pressure predictions can be related to surface force experiments of oppositely charged surfaces that are prepared by coating one of the mica surfaces with an oppositely charged polyelectrolyte

Linear Log-Normal Attention with Unbiased Concentration

Transformer models have achieved remarkable results in a wide range of applications. However, their scalability is hampered by the quadratic time and memory complexity of the self-attention mechanism concerning the sequence length. This limitation poses a substantial obstacle when dealing with long documents or high-resolution images. In this work, we study the self-attention mechanism by analyzing the distribution of the attention matrix and its concentration ability. Furthermore, we propose instruments to measure these quantities and introduce a novel self-attention mechanism, Linear Log-Normal Attention, designed to emulate the distribution and concentration behavior of the original self-attention. Our experimental results on popular natural language benchmarks reveal that our proposed Linear Log-Normal Attention outperforms other linearized attention alternatives, offering a promising avenue for enhancing the scalability of transformer models.Comment: 22 pages, 20 figures, 5 tables, submitted to ICLR202