The hydrolysis of starch is a key factor for controlling the glycemic index (GI). Slow digestion properties of starch lead to slower glucose release and lower glycemic response. Food with high resistant starch (RS) possesses great value for controlling the GI. To elucidate the factors that play a role in slow digestibility, seven rice mutants different in RS contents were selected for comparative studies. The degree of hydrolysis showed highly significant correlation with RS, apparent amylose content (AAC), lipid content (LC), and other starch physiochemical properties in all these materials with different RS contents. The rate of in vitro digestible starch correlated positively with RS, whereas digestibility was affected mostly by lipid content for those mutants with similar RS. Starch-lipid complexes and short chains with degrees of polymerization (DP) of 8-12 strongly influenced starch digestion. The integrity of aggregated starch and the number of round starch granules might influence the digestibility of starch directly.

A hybrid algorithm, combining analytic Kirchhoff approximation (KA) and numerical method of moments (MoMs), is developed to solve the coupling electric-field integral equations (EFIEs) of scattering from a perfect electric conducting (PEC) object above a randomly rough PEC surface under TE-polarized plane-wave incidence. The MoM with the conjugate gradient approach is used to first solve the EFIE of the object. The surface fields on the rough surface are analytically expressed using the KA method, and large memory and computations for those fields are greatly reduced. An iterative approach of the surface fields induced on both object and rough surface is then utilized to take into account interactions between the object and underlying rough surface. Convergence of this hybrid algorithm is numerically validated. Making use of Monte Carlo realization, bistatic scattering from a 2-D PEC cylindrical object above a PEC rough surface is well simulated by this hybrid KA-MoM algorithm.Index Terms-Hybrid algorithm, iteration, Kirchhoff approximation (KA), method of moments (MoMs), object and rough surface.

Low phytic acid grains can provide a solution to dietary micronutrient deficiency and environmental pollution. A low phytic acid 1-1 (lpa1-1) barley mutant was identified using forward genetics and the mutant gene was mapped to chromosome 2HL. Comparative genomic analysis revealed that the lpa1-1 gene was located in the syntenic region of the rice Os-lpa-MH86-1 gene on chromosome 4. The gene ortholog of rice Os-lpa-MH86-1 (designated as HvST) was isolated from barley using polymerase chain reaction and mapped to chromosome 2HL in a doubled haploid population of Clipper×Sahara. The results demonstrate the collinearity between the rice Os-lpa-MH86-1 gene and the barley lpa1-1 region. Sequence analysis of HvST revealed a single base pair substitution (C→T transition) in the last exon of the gene in lpa1-1 (M422), which resulted in a nonsense mutation. These results will facilitate our understanding of the molecular mechanisms controlling the low phytic acid phenotype and assist in the development of a diagnostic marker for the selection of the lpa1-1 gene in barley.

To select a better kind of feature for radar specific emitter identification, the unintentional frequency and phase modulation features are compared through theoretic analysis and experimental verification with 104 real radar instances. Results show that the unintentional phase modulation feature outperforms the unintentional frequency modulation feature.

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[1] A new hybrid analytical-numerical iterative algorithm, which combines the Kirchhoff approximation (KA) and the Method of Moment (MoM), is developed for computing the electromagnetic scattering from a three-dimensional (3-D) perfect electric conducting (PEC) target above a 2-D infinite randomly rough dielectric surface. The equations of difference scattering due to the target presence above the rough surface are derived. The induced difference fields on the rough surface due to the interactions between the target and the rough surface are calculated by using the KA method. The excitation term on the right-hand-side (RHS) of target's surface integral equation (SIE), which contains the difference scattering of the rough surface, is then updated for calculating new target currents with the Conjugate Gradient (CG) procedure. Then the target currents are used to compute the difference field induced on the rough surface with the KA method. Multiple iterations take account of the multiorder interactions between the target and the underlying rough surface. Numerical quadrature upon the rough surface is performed only once to compute the coupling scattering field from the rough surface to the target, and it takes N steps (N is the discretized mesh number of rough surface). By using this hybrid KA-MoM algorithm, the requirements of memory and CPU time can be reduced significantly. Moreover, the validity conditions and the convergence performance of this hybrid algorithm are also discussed. With Monte-Carlo generations of randomly rough surfaces, bistatic scattering from different-shaped targets above a Gaussian rough surface is numerically simulated. Finally, dependence of bistatic scattering pattern on the surface dielectric property and the target geometry is discussed.

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In this paper, we give attention to the robustness of the Cyber-Physical System, which consists of interdependent physical resources and computational resources. Numerous infrastructure systems can evolve into the Cyber-Physical System, e.g., smart power grids, traffic control systems, and wireless sensor and actuator networks. These networks depend on their interdependent networks, which provide information or energy to function. In a Cyber-Physical System, a small failure could trigger serious cascading failures within the entire interdependent networks. In this paper, we try to alleviate these cascading failures between interdependent networks to reduce losses. We discuss the robustness of systems for random attacks by calculating the size of functioning components in entire networks. We change the inter-links topology of the coupled networks to enhance the reliability of the entire system. Then we get the most effective swapping strategy in enhancing the robustness of the Cyber-Physical System compared to previous studies. Different systems' structures would influence the performance of swap inter links strategies on improving the reliability of networks. Moreover, our work could guide how to optimize a Cyber-Physical System topology by reducing the influence of cascading failures. INDEX TERMS Cyber-physical system, interdependent networks, cascading failures, swap inter-links strategy, robustness, giant component.