State-of-the-Art Review of High-Throughput Statistical Spatial-Mapping Characterization Technology and Its Applications

Macroscopic materials are heterogeneous,multi-elementary,and complex.No material is homogeneous or isotropic at a certain small scale.Parts of the material that differ from one another can be termed"natural chips."At different spots on the material,the composition,structure,and properties vary slightly,and the combination of these slight differences establishes the overall material performance.This article presents a state-of-the-art review of research and applications of high-throughput statistical spatialmapping characterization technology based on the intrinsic heterogeneity within materials.Highthroughput statistical spatial-mapping uses a series of rapid characterization techniques for analysis from the macroscopic to the microscopic scale.Datasets of composition,structure,and properties at each location are obtained rapidly for practical sample sizes.Accurate positional coordinate information and references to a point-to-point correspondence are used to set up a database that contains spatialmapping lattices.Based on material research and development design requirements,dataset spatialmapping within required target intervals is selected from the database.Statistical analysis can be used to select a suitable design that better meets the targeted requirements.After repeated verification,genetic units that reflect the material properties are determined.By optimizing process parameters,the assembly of these genetic unit(s)is verified at the mesoscale,and quantitative correlations are established between the microscale,mesoscale,macroscale,practical sample,across-the-scale span composition,structure,and properties.The high-throughput statistical spatial-mapping characterization technology has been applied to numerous material systems,such as steels,superalloys,galvanization,and ferrosilicon alloys.This approach has guided the composition and the process optimization of various materials.

The Formation of Anthocyanic Vacuolar Inclusions in Arabidopsis thaliana and Implications for the Sequestration of Anthocyanin Pigments

Anthocyanins are flavonoid pigments that accumulate in the large central vacuole of most plants. Inside the vacuole, anthocyanins can be found uniformly distributed or as part of sub-vacuolar pigment bodies, the Anthocyanic Vacuolar Inclusions （AVIs）. Using Arabidopsis seedlings grown under anthocyanin-inductive conditions as a model to un- derstand how AVIs are formed, we show here that the accumulation of AVIs strongly correlates with the formation of cyanidin 3-glucoside （C3G） and derivatives. Arabidopsis mutants that fail to glycosylate anthocyanidins at the 5-0 position （Sgt mutant） accumulate AVIs in almost every epidermal cell of the cotyledons, as compared to wild-type seedlings, where only a small fraction of the cells show AVIs. A similar phenomenon is observed when seedlings are treated with vanadate. Highlighting a role for autophagy in the formation of the AVIs, we show that various mutants that interfere with the autophagic process （atg mutants） display lower numbers of AVIs, in addition to a reduced accumulation of anthocyanins. Interestingly, vanadate increases the numbers of AVIs in the atg mutants, suggesting that several pathways might participate in AVl formation. Taken together, our results suggest novel mechanisms for the formation of sub-vacuolar compartments capable of accumulating anthocyanin pigments.

脾肾分流术与断流术治疗门静脉高压症疗效的对比研究

目的比较脾肾分流术和传统断流术治疗门静脉高压症的临床疗效。方法回顾性分析2012年1月至2021年11月于南通大学附属医院行脾肾分流术和传统断流术109例乙肝肝硬化门静脉高压症患者的临床资料。结果分流组手术时间长于断流组,差异有统计学意义[(208±43)min比(172±53)min,t=-3.677,P<0.05];分流组与断流组术中出血量和术后住院时间相比差异均无统计学意义[(131±89)ml比(164±109)ml,t=1.621,P>0.05;(21±6)d比(21±8)d,t=-0.403,P>0.05]。术后两组中重度腹水、腹腔出血和肝性脑病发生率差异均无统计学意义(χ^(2)=0.973、0.830、0.095,均P>0.05)。分流组术后再出血率低于断流组,差异有统计学意义(5%比28%,χ^(2)=5.280,P<0.05)。手术方式是再出血的独立预测因素。分流组1、2、3、5年的累积生存率分别为95%、94%、91%、88%,断流组分别为95%、88%、85%、73%。再出血是影响生存率的独立危险因素。结论脾肾分流术比传统断流术在降低门静脉高压症患者术后再出血率和提高生存率方面有明显的优势。

Differentiability of dividends function on jump-diffusion risk process with a barrier dividend strategy

We consider a dividends model with a stochastic jump perturbed by diffusion. First, we prove that the expected discounted dividends function is twice continuously differentiable under the condition that the claim distribution function has continuous density. Then we show that the expected discounted dividends function under a barrier strategy satisfies some integro-differential equation of defective renewal type, and the solution of which can be explicitly expressed as a convolution formula. Finally, we study the Laplace transform of ruin time on the modified surplus process.