Virtual Field Characterization for Ratcheting Effect Under Cyclic Loading

Experimental Mechanics - Ratcheting is an important mechanical behavior of metals and alloys, which is caused by the repeated accumulations of tensile and compressive strain in circle load....     

An Inexact Modified Newton Method for Viscc and Application in Grasping Force

Acta Mathematicae Applicatae Sinica, English Series - For the variational inequality with symmetric cone constraints problem, we consider using the inexact modified Newton method to efficiently...     

Solving probability reasoning based on DNA strand displacement and probability modules

In computation biology, DNA strand displacement technology is used to simulate the computation process and has shown strong computing ability. Most researchers use it to solve logic problems, but it is only rarely used in probabilistic reasoning. To process probabilistic reasoning, a conditional probability derivation model and total probability model based on DNA strand displacement were established in this paper. The models were assessed through the game “read your mind.” It has been shown to enable the application of probabilistic reasoning in genetic diagnosis.     

A novel feature selection for RNA-seq analysis

RNA-seq data are challenging existing omics data analytics for its volume and complexity. Although quite a few computational models were proposed from different standing points to conduct differential expression (D.E.) analysis, almost all these methods do not provide a rigorous feature selection for high-dimensional RNA-seq count data. Instead, most or even all genes are invited into differential calls no matter they have real contributions to data variations or not. Thus, it would inevitably affect the robustness of D.E. analysis and lead to the increase of false positive ratios.In this study, we presented a novel feature selection method: nonnegative singular value approximation (NSVA) to enhance RNA-seq differential expression analysis by taking advantage of RNA-seq count data's non-negativity. As a variance-based feature selection method, it selects genes according to its contribution to the first singular value direction of input data in a data-driven approach. It demonstrates robustness to depth bias and gene length bias in feature selection in comparison with its five peer methods. Combining with state-of-the-art RNA-seq differential expression analysis, it contributes to enhancing differential expression analysis by lowering false discovery rates caused by the biases. Furthermore, we demonstrated the effectiveness of the proposed feature selection by proposing a data-driven differential expression analysis: NSVA-seq, besides conducting network marker discovery.     

Edge agreement of second-order multi-agent system with dynamic quantization via the directed edge Laplacian

This work explores the edge agreement problem of second-order multi-agent systems with dynamic quantization under directed communication. To begin with, by virtue of the directed edge Laplacian, we propose a model reduction representation of the closed-loop multi-agent system depending on the spanning tree subgraph. Considering the limitations of the finite bandwidth channels, the quantization effects of second-order multi-agent systems under directed graph are considered. The static quantizers generally contain a fixed quantization interval and infinite quantization level, which are, to some extent, inefficient and impractical. To further reduce the bit depth (number of bits available) and to obtain better precision, the dynamic quantized communication strategy referring to zooming in-zooming out scheme is required. Based on the reduced model associated with the essential edge Laplacian, the asymptotic stability of second-order multi-agent systems under dynamic quantized effects with only finite quantization level can be guaranteed. Finally, the simulation of altitude alignment of micro air vehicles is provided to verify the theoretical results.     

Bounded invariant verification for time-delayed nonlinear networked dynamical systems

We present a technique for bounded invariant verification of nonlinear networked dynamical systems with delayed interconnections. The underlying problem in precise bounded-time verification lies with computing bounds on the sensitivity of trajectories (or solutions) to changes in initial states and inputs of the system. For large networks, computing this sensitivity with precision guarantees is challenging. We introduce the notion of input-to-state (IS) discrepancy of each module or subsystem in a larger nonlinear networked dynamical system. The IS discrepancy bounds the distance between two solutions or trajectories of a module in terms of their initial states and their inputs. Given the IS discrepancy functions of the modules, we show that it is possible to effectively construct a reduced (low dimensional) time-delayed dynamical system, such that the trajectory of this reduced model precisely bounds the distance between the trajectories of the complete network with changed initial states. Using the above results we develop a sound and relatively complete algorithm for bounded invariant verification of networked dynamical systems consisting of nonlinear modules interacting through possibly delayed signals. Finally, we introduce a local version of IS discrepancy and show that it is possible to compute them using only the Lipschitz constant and the Jacobian of the dynamic function of the modules.     

Methane conversion under cold plasma over Pd-containing ionic liquids immobilized on γ-Al2O3

Pd-containing ionic liquid（IL） 1-hexyl-3-methylimidazolium tetrafluoroborate（C₆MIMBF₄） immobilized on 7-Al₂O₃（Pd-IL/γ-Al₂O₃） was prepared and characterized by Fourier transform infrared spectroscopy（FTIR）,scanning electron microscopy（SEM） and Brunauer-Emmett-Teller （BET） analysis.The influences of C₆MIMBF₄ loading and Pd on methane conversion to C₂ hydrocarbons under cold plasma were investigated.FTIR and SEM analyses indicated that C₆MIMBF₄ had been successfully immobilized on 7-Al₂O₃ and the C₆MIMBF₄ showed excellent stability under cold plasma.The results of BET and methane conversion showed that with the increase in immobilization amount of C₆MIMBF₄ ontoγ-Al₂O₃,the specific surface area and pore volume of IL/γ-Al₂O₃ decreased,while the selectivity and yield of C₂ hydrocarbons increased.The selectivity of C₂ hydrocarbons was 94.6%when the loading of C₆MIMBF₄ was 40%,and the percentage of C₂H₄ in C₂ hydrocarbons was as high as 64%when using Pd-IL/γ-Al₂O₃ as a catalyst with no conventional thermal reduction treatment. Optical emission spectra（OES） from the cold plasma reactor during methane conversion were also studied.The results indicated that the intensity of the C₂,CH,H,and C active species from methane and hydrogen decomposition increased when IL/γ-Al₂O₃ or Pd-IL/γ-Al₂O₃ was introduced into the plasma system.Based on the analyses of the gas product and OES spectra,it can be concluded that the surface catalyzed reactions between plasma and ionic liquid were very important for the reduction of Pd²⁺ and the formation of C₂H₄.     

微波消解-毛细管电泳法测定茶叶中的生物碱

应用微波消解-毛细管电泳法测定3种茶叶中的咖啡因、腺嘌呤及儿茶素类化合物.优化了缓冲溶液体系、浓度、pH及分离电压等实验条件.在最佳实验条件下,以30 mmol/L硼砂-10 mmol/L β-环糊精为缓冲溶液,pH为9.0,分离电压为22 kV,检测波长为280 nm,电动进样20 kV×5s时,在7 min内同时分...     

TiO2-CoFe2O4磁性复合材料制备及太阳光催化性能

以四氯化钛、三价铁盐和二价钴盐为前驱体,采用超声波技术一步合成了TiO2-CoFe2O4新型复合光催化剂,运用VSM、XRD、TEM和UV-Vis技术进行了表征,以甲基橙为模拟污染物在太阳光照射下研究其光催化活性。结果表明:所制得的样品具有良好的顺磁性,其饱和磁化强度为212 Gs;样品中TiO2和CoFe2O4分别以锐钛矿相和尖晶石结构存在,粒径尺寸在40～50 nm之间;样品在紫外-可见区有很强的吸收。光催化结果表明复合催化剂具有较高的太阳光催化活性,循环使用3次,仍能保持良好的催化活性。     

Plakinidines生物碱的研究进展

Plakinidines是从海洋生物中分离得到的一种活性物质,也是人们首次发现具有吡咯[2,3,4-kl]吖啶骨架结构的天然产物,相应的生物活性探讨与合成工作也相继地展开.在本文中,结合本课题组的合成工作报道plakinidines的发现、生物活性以及相关的合成进展.