53 research outputs found
QCD and strongly coupled gauge theories : challenges and perspectives
We highlight the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment. We discuss how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as to searches for physics beyond the Standard Model. We also discuss how success in describing the strong interaction impacts other fields, and, in turn, how such subjects can impact studies of the strong interaction. In the course of the work we offer a perspective on the many research streams which flow into and out of QCD, as well as a vision for future developments.Peer reviewe
Almost sure exponential stability of an explicit stochastic orthogonal Runge-Kutta-Chebyshev method for stochastic delay differential equations
Analysis of the masses and decay constants of the heavy-light mesons with QCD sum rules
In this article, we calculate the contributions of the vacuum condensates up to dimension-6 including the corrections to the quark condensates in the operator product expansion, then we study the masses and decay constants of the pseudoscalar, scalar, vector, and axial-vector heavy-light mesons with the QCD sum rules in a systematic way. The masses of the observed mesons , , ,
, can be well reproduced, while the predictions for the masses of and can be confronted with the experimental data in the future. We obtain the decay constants of the pseudoscalar, scalar, vector, and axial-vector heavy-light mesons, which have many phenomenological applications in studying the semi-leptonic and leptonic decays of the heavy-light mesons
Development of a Three Dimensional Multiscale Computational Model of the Human Epidermis
Transforming Growth Factor (TGF-β1) is a member of the TGF-beta superfamily ligand-receptor network. and plays a crucial role in tissue regeneration. The extensive in vitro and in vivo experimental literature describing its actions nevertheless describe an apparent paradox in that during re-epithelialisation it acts as proliferation inhibitor for keratinocytes. The majority of biological models focus on certain aspects of TGF-β1 behaviour and no one model provides a comprehensive story of this regulatory factor's action. Accordingly our aim was to develop a computational model to act as a complementary approach to improve our understanding of TGF-β1. In our previous study, an agent-based model of keratinocyte colony formation in 2D culture was developed. In this study this model was extensively developed into a three dimensional multiscale model of the human epidermis which is comprised of three interacting and integrated layers: (1) an agent-based model which captures the biological rules governing the cells in the human epidermis at the cellular level and includes the rules for injury induced emergent behaviours, (2) a COmplex PAthway SImulator (COPASI) model which simulates the expression and signalling of TGF-β1 at the sub-cellular level and (3) a mechanical layer embodied by a numerical physical solver responsible for resolving the forces exerted between cells at the multi-cellular level. The integrated model was initially validated by using it to grow a piece of virtual epidermis in 3D and comparing the in virtuo simulations of keratinocyte behaviour and of TGF-β1 signalling with the extensive research literature describing this key regulatory protein. This research reinforces the idea that computational modelling can be an effective additional tool to aid our understanding of complex systems. In the accompanying paper the model is used to explore hypotheses of the functions of TGF-β1 at the cellular and subcellular level on different keratinocyte populations during epidermal wound healing
Numerical schemes for integro-differential equations with Erdélyi-Kober fractional operator
Stability Analysis of Explicit and Semi-implicit Euler Methods for Solving Stochastic Delay Differential Equations
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