An approach to characterization of the agricultural self-propelled machines stability

This paper presents an analytical algorithm with appropriate software specified for the approximation of the allowed critical slope of the solid flat terrain that guarantees static and/or dynamic stability of the specified self-propelled agricultural machines and their aggregates. This algorithm assumes machine as a rigid body, having 3 or 4 contact points (defined by wheels or crawlers), under uniform motion at different constant velocities and radii of curvature trajectories. Using this algorithm, based on the principles of theoretical mechanics combined with 3D analytical geometry, the computer program SSPM (stability of the self-propelled agricultural machines) has been coded. This software is intended to facilitate the analysis, comparison and optimization of different configurations of self-propelled agricultural machines in operation on horizontal and sloped flat terrains at constant velocities and radii of trajectory with respect to their static and dynamic stability. It calculates critical pitch and roll angles of the self-propelled machine and the maximum allowed slope of the flat terrain under the given conditions. The algorithm and the appropriate SSPM software were experimentally verified using the platform and low-scale tractor model. Average difference between calculated and experimental critical values of roll and pitch angles were about 4°     

Jordan–Cattaneo waves: Analogues of compressible flow

We review work of Jordan on a hyperbolic variant of the Fisher–KPP equation, where a shock solution is found and the amplitude is calculated exactly. The Jordan procedure is extended to a hyperbolic variant of the Chafee–Infante equation. Extension of Jordan’s ideas to a model for traffic flow are also mentioned. We also examine a diffusive susceptible–infected (SI) model, and generalizations of diffusive Lotka–Volterra equations, including a Lotka–Volterra–Bass competition model with diffusion. For all cases we show how a Jordan–Cattaneo wave may be analysed and we indicate how to find the wavespeeds and the amplitudes. Finally we present details of a fully nonlinear analysis of acceleration waves in a Cattaneo–Christov poroacoustic model.     

Mean field limits for nonlinear spatially extended Hawkes processes with exponential memory kernels

We consider spatially extended systems of interacting nonlinear Hawkes processes modeling large systems of neurons placed in ${\mathbb{R}}^d$ and study the associated mean field limits. As the total number of neurons tends to infinity, we prove that the evolution of a typical neuron, attached to a given spatial position, can be described by a nonlinear limit differential equation driven by a Poisson random measure. The limit process is described by a neural field equation. As a consequence, we provide a rigorous derivation of the neural field equation based on a thorough mean field analysis.     

Finest image sharpening by use of the modified mask filter dealing with highest spatial frequencies

We demonstrate a new finding that the filtering-mask with merely four coefficients in the vertical and horizontal directions could be the best choice to achieve finest image sharpening. The mask's merit to better magnify highest spatial frequencies is unveiled by employing the nonlinear transfer function, which has been proved liable to reduce the overshooting effect. By use of this chosen mask, the enhanced image is capable of manifesting extreme sharpness.     

Nonrigid image registration using similarity measure based on spatially weighted global probability distribution function

In nonrigid image registration, similarity measures including spatial information have been shown to perform better than those measures without spatial information. In this work, we provide new insight to the relationships among regional mutual information, regional probability distribution functions (PDFs) and global PDFs, and propose a novel nonrigid registration scheme with spatially weighted global probability distribution function (SWGPDF). Similarity measures based on SWGPDF (SWGPDFSM) are constructed. Three different spatial sub-region division methods are compared: the equally spaced sub-region (ESSR), the local binary pattern sub-region (LBPSR) and the gradient sub-region (GSR). The registration scheme applies B-spline based free form deformations (FFDs) as the transformation model. A Parzen window and linear interpolation are used to construct histograms. The SWGPDFSM registration scheme with ESSR space division is compared with the traditional global mutual information (gMI), the traditional global normalized mutual information (gNMI), regional mutual information and the SWGPDFSM with LBPSR or GSR space division. The test results show that SWGPDFSM scheme with ESSR space division outperforms the other schemes for elastically aligning images in the presence of big geometrical transformations, bias fields and illumination changes.     

MALDI Imaging Assisted Discovery of a Di-O-glycosyltransferase from Platycodon grandiflorum Root

A matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) assisted genome mining strategy was developed for the discovery of glycosyltransferase (GT) from the root of Platycodon grandiflorum. A di-O-glycosyltransferase PgGT1 was discovered and characterized that is capable of catalyzing platycoside E (PE) synthesis through the attachment of two β-1,6-linked glucosyl residues sequentially to the glucosyl residue at the C3 position of platycodin D (PD). Although UDP-glucose is the preferred sugar donor for PgGT1, it could also utilize UDP-xylose and UDP-N-acetylglucosamine as weak donors. Residues S273, E274, and H350 played important roles in stabilizing the glucose donor and positioning the glucose in the optimal orientation for the glycosylation reaction. This study clarified two key steps involved in the biosynthetic pathway of PE and could greatly contribute to improving its industrial biotransformation.     

Synthetic Matching of Complex Monoterpene Indole Alkaloid Chemical Space

Monoterpene indole alkaloids (MIAs) are endowed with high structural and spatial complexity and characterized by diverse biological activities. Given this complexity-activity combination in MIAs, rapid and efficient access to chemical matter related to and with complexity similar to these alkaloids would be highly desirable, since such compound classes might display novel bioactivity. We describe the design and synthesis of a pseudo-natural product (pseudo-NP) collection obtained by the unprecedented combination of MIA fragments through complexity-generating transformations, resulting in arrangements not currently accessible by biosynthetic pathways. Cheminformatic analyses revealed that both the pseudo-NPs and the MIAs reside in a unique and common area of chemical space with high spatial complexity-density that is only sparsely populated by other natural products and drugs. Investigation of bioactivity guided by morphological profiling identified pseudo-NPs that inhibit DNA synthesis and modulate tubulin. These results demonstrate that the pseudo-NP collection occupies similar biologically relevant chemical space that Nature has endowed MIAs with.