Facile synthesis of flake-like dihydrate zinc oxalate particles

Monodispersed dihydrated zinc oxalate(ZnC_2O_4·2H_2O) particles with characteristic morphology were synthesized by aging a mixed solution of zinc nitrate(Zn(NO_3)_2) and sodium oxalate(Na_2C_2O_4) in the presence of a citrate ligand, with an average flat size of approximately 10–15 μm. The important parameters, including the solution pH values and the concentration of the zinc ions and citrate ligand, were investigated using a series of experiments. It is verified that the citrate ligand significantly affects the morphology of zinc oxalate particles, probably via its multiple roles of chelating, dispersing, and selective absorption. Thermodynamic equilibrium of the distribution of zinc species in an aqueous solution of Zn(Ⅱ)-citrate-oxalate-H_2O was estimated to explain the experimental results and to clarify the size and morphological evolution mechanism of the precipitated particles.     

Secure Two-Party Distance Computation Protocol Based on Privacy Homomorphism and Scalar Product in Wireless Sensor Networks

Numerous privacy-preserving issues have emerged along with the fast development of the Internet of Things. In addressing privacy protection problems in Wireless Sensor Networks(WSN), secure multi-party computation is considered vital, where obtaining the Euclidian distance between two nodes with no disclosure of either side’s secrets has become the focus of location-privacy-related applications. This paper proposes a novel Privacy-Preserving Scalar Product Protocol(PPSPP) for wireless sensor networks. Based on PPSPP, we then propose a Homomorphic-Encryption-based Euclidean Distance Protocol(HEEDP) without third parties. This protocol can achieve secure distance computation between two sensor nodes. Correctness proofs of PPSPP and HEEDP are provided, followed by security validation and analysis. Performance evaluations via comparisons among similar protocols demonstrate that HEEDP is superior; it is most efficient in terms of both communication and computation on a wide range of data types, especially in wireless sensor networks.     

基于GUI图形化设计的古建筑声学信号发生器

古建筑声学现象具有重要的文化价值,其测量和分析均依赖现场采集的数据,实验室使用的信号发生器便携性较差,价格比较高不适用于室外测量,具有强大数据分析和处理能力的Matlab软件成为最佳选择.本文介绍基于声卡和matlab设计的虚拟图形化信号发生器,其具有生成建筑声学需求的特殊频率信号能力,提供频率自定义和脉冲调制功能,可实现白噪声发生功能.本文给出了具体实现方法和实际采集的波形结果.     

Ion flux dropout observed near dipolarization front

An ion flux dropout near the dipolarization front （DF） at around XGSM =- 11 RE in the Earth＇ s plasma sheet was observed by Time History of Events and Macroscale Interaction during substorms （THEMIS） on March 31, 2009. The ion differential energy fluxes at energies from 450 eV to 150 keV measured by the ESA and SST instruments from THC began to decrease about 2 s before the detection of the DF and reached a local minimum 6 s later. Then, the ion fluxes gradually increased to form a dropout around the DF. The spatial extent of the dropout was about 4,000 km. For energies above 20 keV, the ion fluxes after the dropout are greater than those before it, contrary to the fluxes at energies below 20 keV. The associated ion density variation indicates that the ion flux dropout coincides with the ion density dropout. Taking advantage of multipoint observations, THD, THC, and THE detected the same DF consecutively. Only THC detected an obvious ion flux dropout; THD observed an indistinct one about 2 s before THC; no high-energy （E 〉 30 keV） ion flux dropout was observed by THE. Our study suggests that the ion flux dropout may evolve with the earthward-propagating DF, and its properties can depend on locations relative to the DF.     

Some open problems related to creative telescoping

Creative telescoping is the method of choice for obtaining information about definite sums or integrals. It has been intensively studied since the early 1990s, and can now be considered as a classical technique in computer algebra. At the same time, it is still a subject of ongoing research. This paper presents a selection of open problems in this context. The authors would be curious to hear about any substantial progress on any of these problems.     

The distributed representation for societal risk classification toward BBS posts

The risk classification of BBS posts is important to the evaluation of societal risk level within a period. Using the posts collected from Tianya forum as the data source, the authors adopted the societal risk indicators from socio psychology, and conduct document-level multiple societal risk classification of BBS posts. To effectively capture the semantics and word order of documents, a shallow neural network as Paragraph Vector is applied to realize the distributed vector representations of the posts in the vector space. Based on the document vectors, the authors apply one classification method KNN to identify the societal risk category of the posts. The experimental results reveal that paragraph vector in document-level societal risk classification achieves much faster training speed and at least 10% improvements of F-measures than Bag-of-Words. Furthermore, the performance of paragraph vector is also superior to edit distance and Lucene-based search method. The present work is the first attempt of combining document embedding method with socio psychology research results to public opinions area.     

太原市民营经济开发区地电场观测系统运行评测

详细介绍了太原市民营经济开发区地电场观测系统的运行情况,从数据的完整率和图形曲线变化等方面对仪器观测系统进行了全方位的综合评价,结果表明:该区地电场观测仪器系统运行平稳可靠,能够有效记录民营区范围内地电场的相关变化,为该区地震预测预报提供一定的依据。