A new strategy for controlling invasive weeds: selecting valuable native plants to defeat them

To explore replacement control of the invasive weed Ipomoea cairica, we studied the competitive effects of two valuable natives, Pueraria lobata and Paederia scandens, on growth and photosynthetic characteristics of I. cairica, in pot and field experiments. When I. cairica was planted in pots with P. lobata or P. scandens, its total biomass decreased by 68.7% and 45.8%, and its stem length by 33.3% and 34.1%, respectively. The two natives depressed growth of the weed by their strong effects on its photosynthetic characteristics, including suppression of leaf biomass and the abundance of the CO 2 -fixing enzyme RUBISCO. The field experiment demonstrated that sowing seeds of P. lobata or P. scandens in plots where the weed had been largely cleared produced 11.8-fold or 2.5-fold as much leaf biomass of the two natives, respectively, as the weed. Replacement control by valuable native species is potentially a feasible and sustainable means of suppressing I. cairica

Validation of Material Algorithms for Femur Remodelling Using Medical Image Data

The aim of this study is the utilization of human medical CT images to quantitatively evaluate two sorts of “error-driven” material algorithms, that is, the isotropic and orthotropic algorithms, for bone remodelling. The bone remodelling simulations were implemented by a combination of the finite element (FE) method and the material algorithms, in which the bone material properties and element axes are determined by both loading amplitudes and daily cycles with different weight factor. The simulation results showed that both algorithms produced realistic distribution in bone amount, when compared with the standard from CT data. Moreover, the simulated L-T ratios (the ratio of longitude modulus to transverse modulus) by the orthotropic algorithm were close to the reported results. This study suggests a role for “error-driven” algorithm in bone material prediction in abnormal mechanical environment and holds promise for optimizing implant design as well as developing countermeasures against bone loss due to weightlessness. Furthermore, the quantified methods used in this study can enhance bone remodelling model by optimizing model parameters to gap the discrepancy between the simulation and real data