Numerical reconstruction of the spatial component in the source term of a time-fractional diffusion equation

In this article, we are concerned with the analysis on the numerical reconstruction of the spatial component in the source term of a time-fractional diffusion equation. This ill-posed problem is solved through a stabilized nonlinear minimization system by an appropriately selected Tikhonov regularization. The existence and the stability of the optimization system are demonstrated. The nonlinear optimization problem is approximated by a fully discrete scheme, whose convergence is established under a novel result verified in this study that the $H^1$-norm of the solution to the discrete forward system is uniformly bounded. The iterative thresholding algorithm is proposed to solve the discrete minimization, and several numerical experiments are presented to show the efficiency and the accuracy of the algorithm.Comment: 17 pages, 2 figures, 2 table

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Quadratic convergence of Levenberg-Marquardt method for elliptic and parabolic inverse robin problems

We study the Levenberg-Marquardt (L-M) method for solving the highly nonlinear and ill-posed inverse problem of identifying the Robin coefficients in elliptic and parabolic systems. The L-M method transforms the Tikhonov regularized nonlinear non-convex minimizations into convex minimizations. And the quadratic convergence of the L-M method is rigorously established for the nonlinear elliptic and parabolic inverse problems for the first time, under a simple novel adaptive strategy for selecting regularization parameters during the L-M iteration. Then the surrogate functional approach is adopted to solve the strongly ill-conditioned convex minimizations, resulting in an explicit solution of the minimisation at each L-M iteration for both the elliptic and parabolic cases. Numerical experiments are provided to demonstrate the accuracy, efficiency and quadratic convergence of the methods

Simulation of geological uncertainty using coupled Markov Chain: A case study at a manually filled Loess Site

Stratigraphic variability contributes significantly to the deformation and stability of geotechnical structures. In this case study, the stratigraphic variability of a typical deep manually filled site in Lanzhou New District, Gansu Province, China is simulated. By applying Walther’s law, the relationship between vertical and horizontal transition counting matrices is established to calculate the vertical and horizontal state-transition probability matrices using a coupled Markov chain model. The Monte Carlo simulation method is used to predict the distribution of soil layers. Based on borehole data, the effects of different borehole layout schemes on the estimation of the transfer probability matrix and prediction of the soil layer distribution are investigated. The results indicate that to obtain accurate estimations for the state transition probability matrix and predictions for the soil layer distribution, more evenly distributed borehole data should be selected. When the values of the diagonal elements in the matrix are high, the sensitivity of the transition probability matrix estimation to the borehole layout scheme is low. Multiple predictions of soil layer distributions using the same borehole layout scheme yield different results primarily because of the significant spacing between the boreholes