Center for Theoretical Biological Physics

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    73752 research outputs found

    Multi-Patch Epidemic Models with General Exposed and Infectious Periods

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    We study multi-patch epidemic models where individuals may migrate from one patch to another in either of the susceptible, exposed/latent, infectious and recovered states. We assume that infections occur both locally with a rate that depends on the patch as well as “from distance” from all the other patches. The migration processes among the patches in either of the four states are assumed to be Markovian, and independent of the exposed and infectious periods. These periods have general distributions, and are not affected by the possible migrations of the individuals. The infection “from distance” aspect introduces a new formulation of the infection process, which, together with the migration processes, brings technical challenges in proving the functional limit theorems. Generalizing the methods in Pang and Pardoux [Ann. Appl. Probab. 32 (2022) 1615–1665], we establish a functional law of large number (FLLN) and a function central limit theorem (FCLT) for the susceptible, exposed/latent, infectious and recovered processes. In the FLLN, the limit is determined by a set of Volterra integral equations. In the special case of deterministic exposed and infectious periods, the limit becomes a system of ODEs with delays. In the FCLT, the limit is given by a set of stochastic Volterra integral equations driven by a sum of independent Brownian motions and continuous Gaussian processes with an explicit covariance structure

    Pion, kaon, and (anti)proton production in U+U collisions at √sNN=193 GeV measured with the STAR detector

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    We present the first measurements of transverse momentum spectra of π±, K±, p(¯p) at midrapidity (|y|<0.1) in U+U collisions at √sNN= 193 GeV with the STAR detector at the Relativistic Heavy Ion Collider (RHIC). The centrality dependence of particle yields, average transverse momenta, particle ratios and kinetic freeze-out parameters are discussed. The results are compared with the published results from Au+Au collisions at √sNN= 200 GeV in STAR. The results are also compared to those from A Multi-Phase Transport (ampt) model

    Higher-order cumulants and correlation functions of proton multiplicity distributions in √sNN=3 GeV Au+Au collisions at the RHIC STAR experiment

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    We report a measurement of cumulants and correlation functions of event-by-event proton multiplicity distributions from fixed-target Au+Au collisions at √sNN = 3 GeV measured by the STAR experiment. Protons are identified within the rapidity (y) and transverse momentum (pT) region −0.9<y<0 and 0.4<pT<2.0 GeV/c in the center-of-mass frame. A systematic analysis of the proton cumulants and correlation functions up to sixth order as well as the corresponding ratios as a function of the collision centrality, pT, and y are presented. The effect of pileup and initial volume fluctuations on these observables and the respective corrections are discussed in detail. The results are compared to calculations from the hadronic transport UrQMD model as well as a hydrodynamic model. In the most central 5% collisions, the value of proton cumulant ratio C4/C2 is negative, drastically different from the values observed in Au+Au collisions at higher energies. Compared to model calculations including lattice QCD, a hadronic transport model, and a hydrodynamic model, the strong suppression in the ratio of C4/C2 at 3 GeV Au+Au collisions indicates an energy regime dominated by hadronic interactions

    Quantitative unique continuation for the elasticity system with application to the kinematic inverse rupture problem

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    We obtain explicit estimates on the stability of the unique continuation for a linear system of hyperbolic equations. In particular, our result applies to the elasticity system and also the Maxwell system. As an application, we study the kinematic inverse rupture problem of determining the jump in displacement and the friction force at the rupture surface, and we obtain new features on the stable unique continuation up to the rupture surface

    Evaluating bone marrow dosimetry with the addition of bone marrow structures to the medical internal radiation dose phantom

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    Background Reliable estimates of radiation dose to bone marrow are critical to understanding the risk of radiation-induced cancers. Although the medical internal radiation dose phantom is routinely used for dose estimation, bone marrow is not defined in the phantom. Consequently, methods of indirectly estimating bone marrow dose have been implemented based on dose to surrogate volumes or average dose to soft tissue. Methods In this study, new bone marrow structures were implemented and evaluated to the medical internal radiation dose phantom in Geant4, offering improved fidelity. The dose equivalent to the bone marrow was calculated across medical, occupational, and space radiation exposure scenarios, and compared with results using prior indirect estimation methods. Conclusion Our results show that bone marrow dose may be overestimated by up to a factor of three when using the traditional methods when compared with the improved fidelity medical internal radiation dose method, specifically at clinical x-ray energies

    Human Schistosomiasis Vaccines as Next Generation Control Tools

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    Human schistosomiasis remains one of the most important yet neglected tropical diseases, with the latest estimates from the Global Burden of Disease Study indicating that over 140 million people are infected with schistosomes [...

    Enhanced Electron Correlation and Significantly Suppressed Thermal Conductivity in Dirac Nodal-Line Metal Nanowires by Chemical Doping

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    Enhancing electron correlation in a weakly interacting topological system has great potential to promote correlated topological states of matter with extraordinary quantum properties. Here, the enhancement of electron correlation in a prototypical topological metal, namely iridium dioxide (IrO2), via doping with 3d transition metal vanadium is demonstrated. Single-crystalline vanadium-doped IrO2 nanowires are synthesized through chemical vapor deposition where the nanowire yield and morphology are improved by creating rough surfaces on substrates. Vanadium doping leads to a dramatic decrease in Raman intensity without notable peak broadening, signifying the enhancement of electron correlation. The enhanced electron correlation is further evidenced by transport studies where the electrical resistivity is greatly increased and follows an unusual TT\sqrt T dependence on the temperature (T). The lattice thermal conductivity is suppressed by an order of magnitude via doping even at room temperature where phonon-impurity scattering becomes less important. Density functional theory calculations suggest that the remarkable reduction of thermal conductivity arises from the complex phonon dispersion and reduced energy gap between phonon branches, which greatly enhances phase space for phonon–phonon Umklapp scattering. This work demonstrates a unique system combining 3d and 5d transition metals in isostructural materials to enrich the system with various types of interactions

    Conditional Injective Flows for Bayesian Imaging

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    Most deep learning models for computational imaging regress a single reconstructed image. In practice, however, ill-posedness, nonlinearity, model mismatch, and noise often conspire to make such point estimates misleading or insufficient. The Bayesian approach models images and (noisy) measurements as jointly distributed random vectors and aims to approximate the posterior distribution of unknowns. Recent variational inference methods based on conditional normalizing flows are a promising alternative to traditional MCMC methods, but they come with drawbacks: excessive memory and compute demands for moderate to high resolution images and underwhelming performance on hard nonlinear problems. In this work, we propose C-Trumpets—conditional injective flows specifically designed for imaging problems, which greatly diminish these challenges. Injectivity reduces memory footprint and training time while low-dimensional latent space together with architectural innovations like fixed-volume-change layers and skip-connection revnet layers, C-Trumpets outperform regular conditional flow models on a variety of imaging and image restoration tasks, including limited-view CT and nonlinear inverse scattering, with a lower compute and memory budget. C-Trumpets enable fast approximation of point estimates like MMSE or MAP as well as physically-meaningful uncertainty quantification

    Investigation of the structure and elemental composition of 2D Interfaces in Transition Metal Dichalcogenides

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    The electronics boom happened with the invention of semiconductor materials with Si becoming the number one in the race. But now, since Si electronics seems to be reaching its limit, the researchers are switching their attention to 2D materials because of their unique electrical, mechanical, or optical properties. Transition metal dichalcogenides (TMDs) are semiconductor materials from this family that show promise to be the next generation of nanoelectronics as well as give possibility to improve energy or informational storage. However, for maintaining high efficiency, the structure of TMDs should have minimum number of defects, misfits, or inclusions of other elements. This indicates a need to understand the structural and elemental composition of the 2D materials to atomic scales, and this is where techniques like (scanning) transmission electron microscopy (S)TEM and energy-dispersive x-ray spectroscopy (EDX) come to aid. In this study, we will discuss sample preparation and analysis techniques for of SnSe, MoS2, WS2, WSe2, and graphene/Al heterostructures on silicon wafer and sapphire substrates, the methods of uncovering the elemental and layer composition of these materials and provide image and signal processing approaches to increase the signal-to-noise ratio of the currently employed techniques. All of these will help us reach a conclusion about atomic structure and elemental composition of the materials and show the possible traps and pitfalls that a microscopist might encounter during similar analysis for either TMDs or other types of 2D materials

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