The packing of granular polymer chains

Rigid particles pack into structures, such as sand dunes on the beach, whose overall stability is determined by the average number of contacts between particles. However, when packing spatially extended objects with flexible shapes, additional concepts must be invoked to understand the stability of the resulting structure. Here we study the disordered packing of chains constructed out of flexibly-connected hard spheres. Using X-ray tomography, we find long chains pack into a low-density structure whose mechanical rigidity is mainly provided by the backbone. On compaction, randomly-oriented, semi-rigid loops form along the chain, and the packing of chains can be understood as the jamming of these elements. Finally we uncover close similarities between the packing of chains and the glass transition in polymers.Comment: 11 pages, 4 figure

Hypoconstrained Jammed Packings of Nonspherical Hard Particles: Ellipses and Ellipsoids

Continuing on recent computational and experimental work on jammed packings of hard ellipsoids [Donev et al., Science, vol. 303, 990-993] we consider jamming in packings of smooth strictly convex nonspherical hard particles. We explain why the isocounting conjecture, which states that for large disordered jammed packings the average contact number per particle is twice the number of degrees of freedom per particle (\bar{Z}=2d_{f}), does not apply to nonspherical particles. We develop first- and second-order conditions for jamming, and demonstrate that packings of nonspherical particles can be jammed even though they are hypoconstrained (\bar{Z}<2d_{f}). We apply an algorithm using these conditions to computer-generated hypoconstrained ellipsoid and ellipse packings and demonstrate that our algorithm does produce jammed packings, even close to the sphere point. We also consider packings that are nearly jammed and draw connections to packings of deformable (but stiff) particles. Finally, we consider the jamming conditions for nearly spherical particles and explain quantitatively the behavior we observe in the vicinity of the sphere point.Comment: 33 pages, third revisio

Random manifolds in non-linear resistor networks: Applications to varistors and superconductors

We show that current localization in polycrystalline varistors occurs on paths which are, usually, in the universality class of the directed polymer in a random medium. We also show that in ceramic superconductors, voltage localizes on a surface which maps to an Ising domain wall. The emergence of these manifolds is explained and their structure is illustrated using direct solution of non-linear resistor networks

Reproduction and optical analysis of Morpho-inspired polymeric nanostructures

The brilliant blue coloration of the Morpho rhetenor butterfly originates from complex nanostructures found on the surface of its wings. The Morpho butterfly exhibits strong short-wavelength reflection and a unique two-lobe optical signature in the incident (θ) and reflected (φ) angular space. Here, we report the large-area fabrication of a Morpho-like structure and its reproduction in perfluoropolyether. Reflection comparisons of periodic and quasi-random 'polymer butterfly' nanostructures show similar normal-incidence spectra but differ in the angular θ-φ dependence. The periodic sample shows strong specular reflection and simple diffraction. However, the quasi-random sample produces a two-lobe angular reflection pattern with minimal specular refection, approximating the real butterfly's optical behavior. Finite-difference time-domain simulations confirm that this pattern results from the quasi-random periodicity and highlights the significance of the inherent randomness in the Morpho's photonic structure

Smooth vortex precession in superfluid 4He

We have measured a precessing superfluid vortex line, stretched from a wire to the wall of a cylindrical cell. By contrast to previous experiments with a similar geometry, the motion along the wall is smooth. The key difference is probably that our wire is substantially off center. We verify several numerical predictions about the motion, including an asymmetry in the precession signature, the behavior of pinning events, and the temperature dependence of the precession.Comment: 8 pages, 8 figure

Classical electromagnetic field theory in the presence of magnetic sources

Using two new well defined 4-dimensional potential vectors, we formulate the classical Maxwell's field theory in a form which has manifest Lorentz covariance and SO(2) duality symmetry in the presence of magnetic sources. We set up a consistent Lagrangian for the theory. Then from the action principle we get both Maxwell's equation and the equation of motion of a dyon moving in the electro-magnetic field.Comment: 10 pages, no figure

A Novel, Orally Delivered Antibody Therapy and Its Potential to Prevent Clostridioides difficile Infection in Pre-clinical Models

Clostridioides difficile infection (CDI) is a toxin-mediated infection in the gut and a major burden on healthcare facilities worldwide. We rationalized that it would be beneficial to design an antibody therapy that is delivered to, and is active at the site of toxin production, rather than neutralizing the circulating and luminal toxins after significant damage of the layers of the intestines has occurred. Here we describe a highly potent therapeutic, OraCAb, with high antibody titers and a formulation that protects the antibodies from digestion/inactivation in the gastrointestinal tract. The potential of OraCAb to prevent CDI in an in vivo hamster model and an in vitro human colon model was assessed. In the hamster model we optimized the ratio of the antibodies against each of the toxins produced by C. difficile (Toxins A and B). The concentration of immunoglobulins that is effective in a hamster model of CDI was determined. A highly significant difference in animal survival for those given an optimized OraCAb formulation versus an untreated control group was observed. This is the first study testing the effect of oral antibodies for treatment of CDI in an in vitro gut model seeded with a human fecal inoculum. Treatment with OraCAb successfully neutralized toxin production and did not interfere with the colonic microbiota in this model. Also, treatment with a combination of vancomycin and OraCAb prevented simulated CDI recurrence, unlike vancomycin therapy alone. These data demonstrate the efficacy of OraCAb formulation for the treatment of CDI in pre-clinical models

A Method of Intervals for the Study of Diffusion-Limited Annihilation, A + A --> 0

We introduce a method of intervals for the analysis of diffusion-limited annihilation, A+A -> 0, on the line. The method leads to manageable diffusion equations whose interpretation is intuitively clear. As an example, we treat the following cases: (a) annihilation in the infinite line and in infinite (discrete) chains; (b) annihilation with input of single particles, adjacent particle pairs, and particle pairs separated by a given distance; (c) annihilation, A+A -> 0, along with the birth reaction A -> 3A, on finite rings, with and without diffusion.Comment: RevTeX, 13 pages, 4 figures, 1 table. References Added, and some other minor changes, to conform with final for

Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm

Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learning (ML) models to quantify intra-tumoral genetic heterogeneity for each patient. This capability holds great promise for enabling better therapeutic selection to improve patient outcomes. We proposed a novel Weakly Supervised Ordinal Support Vector Machine (WSO-SVM) to predict regional genetic alteration status within each GBM tumor using MRI. WSO-SVM was applied to a unique dataset of 318 image-localized biopsies with spatially matched multiparametric MRI from 74 GBM patients. The model was trained to predict the regional genetic alteration of three GBM driver genes (EGFR, PDGFRA, and PTEN) based on features extracted from the corresponding region of five MRI contrast images. For comparison, a variety of existing ML algorithms were also applied. The classification accuracy of each gene was compared between the different algorithms. The SHapley Additive exPlanations (SHAP) method was further applied to compute contribution scores of different contrast images. Finally, the trained WSO-SVM was used to generate prediction maps within the tumoral area of each patient to help visualize the intra-tumoral genetic heterogeneity. This study demonstrated the feasibility of using MRI and WSO-SVM to enable non-invasive prediction of intra-tumoral regional genetic alteration for each GBM patient, which can inform future adaptive therapies for individualized oncology.Comment: 36 pages, 8 figures, 3 table