Effect of Sintering Temperature on Magnetic and Electrical Properties of GdBaCo<Subscript>2</Subscript><Emphasis Type="Italic">O</Emphasis><Subscript>5 + <Emphasis Type="Italic">δ</Emphasis></Subscript>

In this study, we report the results of an investigation into the sintering temperature dependence of magnetic and transport properties for GdBaCo₂ O _{5 + δ} synthesized through a sol-gel method. The lowering of sintering temperature leads to the increase of oxygen content and the reduction of grain size. The increase of oxygen content results in the enhancement of magnetic interactions and the weakening of Coulomb repulsion effect, while the reduction of grain size improves the magnetoresistance effect. Metal-insulator transition accompanied with spin-state transition is observed in all samples.     

The interlaminar shear failure characteristics of asphalt pavement coupled heating cables

Nowadays, heating cables are used as heat sources for heating pavements in practical engineering. However, there is a contradiction between the snow melting function and the interlaminar stability of heating pavement. In order to solve the contradiction, the interlaminar failure behavior of asphalt mixture coupled heating cables specimen (AMCS) was researched, through experiments and the finite element method. Under the different conditions of heating cables and rolling times, a series of direct shear tests was performed at the interface of AMCS, to compare the interlaminar stability of three different AMCS. Meanwhile, based on the bilinear cohesive zone model and coulomb friction model a 2D finite element model was established, to simulate this shear failure processes and make up for the limitations of the experiment. According to above test and simulation results, the failure mechanism and the weakest interface in AMCS were found, and the influence of the heating cable’s diameter and embedded spacing on the interlaminar shear strength were found. Then, a modified coulomb theorem model was proposed to predict the shear strength of the AMCS. This research enriches the design theory of the heating pavement and it has great significance for its structural design of heating asphalt pavement.     

A facile synthesis of supported amorphous iron oxide with high performance for Cr(Ⅵ) removal from aqueous solution under visible light irradiation

A series of supported iron oxide nanoparticles were prepared by impregnation with Fe(NO_3)_3 supported on TiO_2,followed by low-temperature calcination. Scanning electron microscopy(SEM), X-ray diffraction(XRD), X-ray photoelectron spectroscopy(XPS), UV–vis diffuse reflectance spectra and BET have been used to characterize the samples. These iron oxide-impregnated TiO_2 were examined for photocatalytic reduction of Cr(Ⅵ). The experiments demonstrated that Cr(Ⅵ) in aqueous solution was more efficiently reduced using Fe_2O_3/TiO_2 heterogeneous photocatalysts than either pure Fe_2O_3 or TiO_2 under visible light irradiation. All TiO_2 supported samples were somewhat active for visible light photoreduction. With an optimal mole ratio of 0.05-Fe/Ti, the highest rate of Cr(Ⅵ) reduction was achieved under the experimental conditions. We also compared the photoreactivity of TiO_2 supported iron oxide samples with that supported on Al_2O_3 and ZrO_2. It can be noted that iron oxide nanoparticles deposited on high surface area supports to increase the solid-liquid contact area renders it considerably more active. Noticeably,iron oxide cluster size and dispersion are important parameters in synthesizing active, supported Iron oxide nanoparticles. In addition, the interaction between iron oxide and TiO_2 was proposed as the source of photoactivity for Cr(Ⅵ) reduction.     

Physics-Informed Multistage Machine Learning Strategy for the Nanomachining-Induced Plastic Deformation Behavior

The evolution of the dislocation density induced by the nanomachining process dominates the plastic deformation behaviors of materials, thus affecting the mechanical properties significantly. However, a challenging topic related to how to establish an accurate model for predicting the dislocation density based on the limited simulations and experiments arises due to the complicated thermal–mechanical coupling mechanism during the machining process. Herein, a multistage method integrating machine learning, physics, and high-throughput atomic simulation is proposed to investigate the effect of cutting speed on the dislocation behavior in polycrystal copper. Compared with the traditional one-step machine learning method, the constraint of physical features effectively improves the accuracy and generalization ability of the model. The results indicate that the dislocation behaviors depend on the competition between the cutting force and temperature. In the low-cutting speed, the predominated role of the cutting temperature leads to a rapid decline of the dislocation density. In contrast, the dislocation density tends to be stable under a high-speed cutting process due to the dynamic balance between the effects of the cutting force and temperature. Notably, the proposed strategy provides a new and universal framework to design the machining parameters to obtain high-quality products.     

Modified HSS iteration methods for a class of complex symmetric linear systems

In this paper, we introduce and analyze a modification of the Hermitian and skew-Hermitian splitting iteration method for solving a broad class of complex symmetric linear systems. We show that the modified Hermitian and skew-Hermitian splitting (MHSS) iteration method is unconditionally convergent. Each iteration of this method requires the solution of two linear systems with real symmetric positive definite coefficient matrices. These two systems can be solved inexactly. We consider acceleration of the MHSS iteration by Krylov subspace methods. Numerical experiments on a few model problems are used to illustrate the performance of the new method.     

一种安全有效的基于身份的门限签密方案

签密是一种将加密和数字签名技术结合在一起的思想,它比采用先签名后加密的方法具有更高的效率.基于双线性对技术,提出了一种新的基于身份的门限签密方案.它利用决策双线性Diffie-Hellman(DBDH)问题的困难性在随机预言模型下给出了方案的语义安全性证明,并利用计算Diffie-Hellman(CDH)问题的困难性证明了方案的不可伪造性,同时指出方案具有较高的效率.     

An axiom system for sequence-based specification

This paper establishes an axiomatic foundation and a representation theorem for the rigorous, constructive process, called sequence-based specification, of deriving precise specifications from ordinary (informal) statements of functional requirements. The representation theorem targets a special class of Mealy state machines, and algorithms are presented for converting from the set of sequences that define the specification to the equivalent Mealy machine, and vice versa. Since its inception, sequence-based specification has been effectively used in a variety of real applications, with gains reported in quality and productivity. This paper establishes the mathematical foundation independently of the process itself.     

基于LDA模型的新闻话题的演化

新闻话题及演化的研究可以帮助人们快速了解和获取新闻内容。提出了一种挖掘新闻话题随时间变化的方法,通过话题抽取和话题关联实现话题的演化。首先应用LDA(Latent Dirichlet Allocation Model)对不同时间段的文集进行话题的自动抽取,话题数目在不同时间段是可变的;计算相邻时间段中任意两个话题的分布距离实现话题的关联。实验结果证明该方法不但可以描述同一个话题随时间的演化过程,还可以描述话题内容随时间的变化,反映了话题(或子话题)之间多对多的演化关系。     

一种基于可信度矩阵的多传感器目标识别方法

为了解决多传感器目标识别中不同等级信息源数据的融合问题,在研究DSmT证据理论的基础上,引入证据可信度矩阵.依据可信度矩阵对证据进行转化,使之可以用传统的方法进行证据融合.将这种方法应用到等级不同的多传感器目标识别中,可以解决传统证据理论只能进行相同等级传感器目标识别的难题.仿真实验表明,该方法提高了目标识别的准确性和有效性.