Abstract: Many geometries of plant organs can be described by the Gielis equation, a polar coordinate equation extended from the superellipse equation, . Here, r is the polar radius corresponding to the polar angle φ; m is a positive integer that determines the number of angles of the Gielis curve when φ ∈ [0 to 2π); and the rest of the symbols are parameters to be estimated. The pentagonal radial symmetry of calyxes and corolla tubes in top view is a common feature in the flowers of many eudicots. However, prior studies have not tested whether the Gielis equation can depict the shapes of corolla tubes. We sampled randomly 366 flowers of Vinca major L., among which 360 had five petals and pentagonal corolla tubes, and six had four petals and quadrangular corolla tubes. We extracted the planar coordinates of the outer rims of corolla tubes (in top view) (ORCTs), and then fitted the data with two simplified versions of the Gielis equation with k = 1 and m = 5: (Model 1), and (Model 2). The adjusted root mean square error (RMSEadj) was used to evaluate the goodness of fit of each model. In addition, to test whether ORCTs are radially symmetrical, we correlated the estimates of n2 and n3 in Model 1 on a log-log scale. The results validated the two simplified Gielis equations. The RMSEadj values for all corolla tubes were smaller than 0.05 for both models. The numerical values of n2 and n3 were demonstrated to be statistically equal based on the regression analysis, which suggested that the ORCTs of V. major are radially symmetrical. It suggests that Model 1 can be replaced by the simpler Model 2 for fitting the ORCT in this species. This work indicates that the pentagonal or quadrangular corolla tubes (in top view) can both be modeled by the Gielis equation and demonstrates that the pentagonal or quadrangular corolla tubes of plants tend to form radial symmetrical geometries during their development and growth.

Abstract: This study presents a novel method for the detection and quantification of atmospheric corrosion products on carbon steel. Using hyperspectral imaging (HSI) in the short-wave infrared range (SWIR) (900-1700 nm), we are able to identify the most common corrosion minerals such as: alpha-FeO(OH) (goethite), gamma-FeO(OH) (lepidocrocite), and gamma-Fe2O3 (maghemite). Six carbon steel samples were artificially corroded in a salt spray chamber, each sample with a different duration (between 1 h and 120 hours). These samples were analysed by scanning X-ray diffraction (XRD) and also using a SWIR HSI system. The XRD data is used as baseline data. A random forest regression algorithm is used for training on the combined XRD and HSI data set. Using the trained model, we can predict the abundance map based on the HSI images alone. Several image correlation metrics are used to assess the similarity between the original XRD images and the HSI images. The overall abundance is also calculated and compared for XRD and HSI images. The analysis results show that we are able to obtain visually similar images, with error rates ranging from 3.27 to 13.37%. This suggests that hyperspectral imaging could be a viable tool for the study of corrosion minerals.

Abstract: A quasi 3D modelling approach was developed by integrating a crop growth (LINGRA-N) and a hydrological model (Hydrus-1D) to simulate and visualize water flow, soil-water storage, water stress and crop yield over a heterogeneous sandy field. We assessed computational efficiency and uncertainty with low to high-spatial resolution input factors (soil-hydraulic properties, soil-layer thickness and groundwater level) and evaluated four irrigation scenarios (no, current, optimized and triggered) to find the optimal and cost-effective irrigation scheduling. Numerical results showed that the simulation uncertainty was reduced when using the high-resolution information while a fast performance was maintained. The approach accurately determined the field scale irrigation requirements, taking into account spatial variations of input information. Optimal irrigation scheduling is obtained by triggered-irrigation resulting in saving up to similar to 300% water as compared to the current-irrigation, while yield increased similar to 1%. Overall, the approach can be useful to help decision makers and applicants in precision farming. (C) 2017 Published by Elsevier Ltd.

Abstract: Quasiparticle physics underlies our understanding of the microscopic dynamical behaviors of materials that govern a vast array of properties, including structural stability, excited states and interactions, dynamical structure factors, and electron and phonon conductivities. Thus, understanding band structures and quasiparticle interactions is foundational to the study of condensed matter. Here we advance a 'twist' dynamical description of quasiparticles (including phonons and Bloch electrons) in nonsymmorphic chiral and achiral materials. Such materials often have structural complexity, strong thermal resistance, and efficient thermoelectric performance for waste heat capture and clean refrigeration technologies. The twist dynamics presented here provides a novel perspective of quasiparticle behaviors in such complex materials, in particular highlighting how non-symmorphic symmetries determine band crossings and anti-crossings, topological behaviors, quasiparticle interactions that govern transport, and observables in scattering experiments. We provide specific context via neutron scattering measurements and first-principles calculations of phonons and electrons in chiral tellurium dioxide. Building twist symmetries into the quasiparticle dynamics of non-symmorphic materials offers intuition into quasi particle behaviors, materials properties, and guides improved experimental designs to probe them. More specifically, insights into the phonon and electron quasiparticle physics presented here will enable materials design strategies to control interactions and transport for enhanced thermoelectric and thermal management applications. (C) 2021 Published by Elsevier Ltd.