12,170 research outputs found

    T Cell Responses during Acute Respiratory Virus Infection

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    This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.The T cell response is an integral and essential part of the host immune response to acute virus infection. Each viral pathogen has unique, frequently nuanced, aspects to its replication, which affects the host response and as a consequence the capacity of the virus to produce disease. There are, however, common features to the T cell response to viruses, which produce acute limited infection. This is true whether virus replication is restricted to a single site, for example, the respiratory tract (RT), CNS etc., or replication is in multiple sites throughout the body. In describing below the acute T cell response to virus infection, we employ acute virus infection of the RT as a convenient model to explore this process of virus infection and the host response. We divide the process into three phases: the induction (initiation) of the response, the expression of antiviral effector activity resulting in virus elimination, and the resolution of inflammation with restoration of tissue homeostasis

    Electromagnetically controlled multiferroic thermal diode

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    We propose an electromagnetically tunable thermal diode based on a two phase multiferroics composite. Analytical and full numerical calculations for prototypical heterojunction composed of Iron on Barium titanate in the tetragonal phase demonstrate a strong heat rectification effect that can be controlled externally by a moderate electric field. This finding is of an importance for thermally based information processing and sensing and can also be integrated in (spin)electronic circuits for heat management and recycling.Comment: Accepted in Phys. Rev.

    Scaling in directed dynamical small-world networks with random responses

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    A dynamical model of small-world network, with directed links which describe various correlations in social and natural phenomena, is presented. Random responses of every site to the imput message are introduced to simulate real systems. The interplay of these ingredients results in collective dynamical evolution of a spin-like variable S(t) of the whole network. In the present model, global average spreading length \langel L >_s and average spreading time _s are found to scale as p^-\alpha ln N with different exponents. Meanwhile, S behaves in a duple scaling form for N>>N^*: S ~ f(p^-\beta q^\gamma t'_sc), where p and q are rewiring and external parameters, \alpha, \beta, \gamma and f(t'_sc) are scaling exponents and universal functions, respectively. Possible applications of the model are discussed.Comment: 4 pages, 6 Figure

    Quantum discord dynamical behaviors due to initial system-cavity correlations

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    We analyze the roles of initial correlations between the two-qubit system and a dissipative cavity on quantum discord dynamics of two qubits. Considering two initial system-cavity states, we show that the initial system-cavity correlations not only can initially increase the two-qubit quantum discord but also would lead to a larger long-time quantum discord asymptotic value. Moreover, quantum discord due to initial correlations is more robust than the case of the initial factorized state. Finally, we show the initial correlations' importance for dynamics behaviors of mutual information and classical correlation

    Adiabatic Theory of Nonlinear Evolution of Quantum States

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    We present a general theory for adiabatic evolution of quantum states as governed by the nonlinear Schrodinger equation, and provide examples of applications with a nonlinear tunneling model for Bose-Einstein condensates. Our theory not only spells out conditions for adiabatic evolution of eigenstates, but also characterizes the motion of non-eigenstates which cannot be obtained from the former in the absence of the superposition principle. We find that in the adiabatic evolution of non-eigenstates, the Aharonov-Anandan phases play the role of classical canonical actions.Comment: substantial revision, 5 pages and 3 figure

    How to project a bipartite network?

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    The one-mode projecting is extensively used to compress the bipartite networks. Since the one-mode projection is always less informative than the bipartite representation, a proper weighting method is required to better retain the original information. In this article, inspired by the network-based resource-allocation dynamics, we raise a weighting method, which can be directly applied in extracting the hidden information of networks, with remarkably better performance than the widely used global ranking method as well as collaborative filtering. This work not only provides a creditable method in compressing bipartite networks, but also highlights a possible way for the better solution of a long-standing challenge in modern information science: How to do personal recommendation?Comment: 7 pages, 4 figure

    Mutual selection in network evolution: the role of the intrinsic fitness

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    We propose a new mechanism leading to scale-free networks which is based on the presence of an intrinsic character of a vertex called fitness. In our model, a vertex ii is assigned a fitness xix_i, drawn from a given probability distribution function f(x)f(x). During network evolution, with rate pp we add a vertex jj of fitness xjx_j and connect to an existing vertex ii of fitness xix_i selected preferentially to a linking probability function g(xi,xj)g(x_i,x_j) which depends on the fitnesses of the two vertices involved and, with rate 1−p1-p we create an edge between two already existed vertices with fitnesses xix_i and xjx_j, with a probability also preferential to the connection function g(xi,xj)g(x_i,x_j). For the proper choice of gg, the resulting networks have generalized power laws, irrespective of the fitness distribution of vertices.Comment: ws-ijmpc.te
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