Efficiency and Sensitivity Analysis of Observation Networks for Atmospheric Inverse Modelling with Emissions

The controllability of advection-diffusion systems, subject to uncertain initial values and emission rates, is estimated, given sparse and error affected observations of prognostic state variables. In predictive geophysical model systems, like atmospheric chemistry simulations, different parameter families influence the temporal evolution of the system.This renders initial-value-only optimisation by traditional data assimilation methods as insufficient. In this paper, a quantitative assessment method on validation of measurement configurations to optimize initial values and emission rates, and how to balance them, is introduced. In this theoretical approach, Kalman filter and smoother and their ensemble based versions are combined with a singular value decomposition, to evaluate the potential improvement associated with specific observational network configurations. Further, with the same singular vector analysis for the efficiency of observations, their sensitivity to model control can be identified by determining the direction and strength of maximum perturbation in a finite-time interval.Comment: 30 pages, 10 figures, 5 table

HBV infection-induced liver cirrhosis development in dual-humanized mice with human bone mesenchymal stem cell transplantation

疾病动物模型是现代医学发展的基石，尤其是重大、突发传染病暴发时，适宜的疾病动物模型可为及时发现病原体、制定防控策略提供强大保障，原创的疾病动物模型已成为衡量一个国家生物医药科研水平的标志。我校夏宁邵教授团队和浙江大学附属第一医院李君教授团队历经5年的协同攻关，终于建立了国际上首个高度模拟人类乙肝病毒（HBV）自然感染诱发的慢乙肝肝硬化小鼠模型。厦门大学公共卫生学院袁伦志博士生、浙江大学医学院附属第一医院江静博士和厦门大学公共卫生学院刘旋博士生为该论文共同第一作者。厦门大学夏宁邵教授、浙江大学附属第一医院李君教授和厦门大学程通副教授为该论文共同通讯作者。【Abstract】Objective： Developing a small animal model that accurately delineates the natural history of hepatitis B virus (HBV) infection and immunopathophysiology is necessary to clarify the mechanisms of host-virus interactions and to identify intervention strategies for HBV-related liver diseases. This study aimed to develop an HBV-induced chronic hepatitis and cirrhosis mouse model through transplantation of human bone marrow mesenchymal stem cells (hBMSCs). Design： Transplantation of hBMSCs into Fah -/- Rag2 -/- IL-2Rγc -/- SCID (FRGS) mice with fulminant hepatic failure (FHF) induced by hamster-anti-mouse CD95 antibody JO2 generated a liver and immune cell dual-humanized (hBMSC-FRGS) mouse. The generated hBMSC-FRGS mice were subjected to assessments of sustained viremia, specific immune and inflammatory responses and liver pathophysiological injury to characterize the progression of chronic hepatitis and cirrhosis after HBV infection. Results： The implantation of hBMSCs rescued FHF mice, as demonstrated by robust proliferation and transdifferentiation of functional human hepatocytes and multiple immune cell lineages, including B cells, T cells, NK cells, dendritic cells (DCs) and immune cell lineages, including B cells, T cells, NK cells, dendritic cells (DCs) and viremia and specific immune and inflammatory responses and showed progression to chronic hepatitis and liver cirrhosis at a frequency of 55% after 54 weeks. Conclusion： This new humanized mouse model recapitulates the liver cirrhosis induced by human HBV infection, thus providing research opportunities for understanding viral immune pathophysiology and testing antiviral therapies in vivo.this work was supported by the national Science and technology Major Project (grant nos. 2017ZX10304402, 2017ZX10203201 and 2018ZX09711003-005-003), the national natural Science Foundation of china(grant nos. 81672023, 81571818 and 81771996), the Scientific research Foundation of the State Key laboratory of Molecular Vaccinology and Molecular Diagnostics (grant no 2016ZY005), Zhejiang Province and State's Key Project of the research and Development Plan of china (grant nos 2017c01026 and 2016YFc1101304/3).该研究获得了传染病防治国家科技重大专项、新药创制国家科技重大专项和国家自然科学基金的资助

The degree of freedom for signal assessment of measurement networks for joint chemical state and emission analysis

The Degree of Freedom for Signal (DFS) is generalized and applied to estimate the potential observability of observation networks for augmented model state and parameter estimations. The control of predictive geophysical model systems by measurements is dependent on a sufficient observational basis. Control parameters may include prognostic state variables, mostly the initial values, and insufficiently known model parameters, to which the simulation is sensitive. As for chemistry-transport models, emission rates are at least as important as initial values for model evolution control. Extending the optimisation parameter set must be met by observation networks, which allows for controlling the entire optimisation task. In this paper, we introduce a DFS based approach with respect to address both, emission rates and initial value observability. By applying a Kalman smoother, a quantitative assessment method on the efficiency of observation configurations is developed based on the singular value decomposition. For practical reasons an ensemble based version is derived for covariance modelling. The observability analysis tool can be generalized to additional model parameters

Optimal Control and Observation Locations for Time-Varying Systems on a Finite-Time Horizon

The choice of the location of controllers and observations is of great importance for designing control systems and improving the estimations in various practical problems. For time-varying systems in Hilbert spaces, the existence and convergence of the optimal locations based on the linear-quadratic control on a finite-time horizon is studied. The optimal location of observations for improving the estimation of the state at the final time, based on the Kalman filter, is considered as the dual problem to the linear-quadratic optimal problem of the control locations. Further, the existence and convergence of optimal locations of observations for improving the estimation of the initial state, based on the Kalman smoother, is discussed. The obtained results are applied to a linear advection-diffusion model with a special extension of emission rates.Read More: http://epubs.siam.org/doi/10.1137/15M101475