Highly regioselective construction of spirocycles via phosphine-catalyzed [3 + 2]-cycloaddition

A direct entry to spirocycles with low to moderate regioselectivity was achieved by triphenylphosphine-catalyzed [3 + 2]-cycloaddition of active exo-methylenecycles (1) and ethyl 2,3-butadienoate (2). The regioselectivity of the reaction was greatly improved by using the bulky tert-butyl ester of the 2,3-butadienoate (5). The regioselectivity of the reaction was further enhanced by using the tert-butyl 2-butynoate as the substrate. This protocol provided an efficient entry to the skeleton of spirocarbocycles, especially spiro[4.n]alkanes.     

Ca(1)(-)(x)Na(2)(x)Al(2)B(2)O(7): a structure with tunable density of Na(+) vacancies

A series of samples with the composition Ca(1)(-)(x)Na(2)(x)Al(2)B(2)O(7) (0 < x < or = 1) was investigated and a hexagonal structure with unusually large range of homogeneity (at least from x = 0.01 to 0.95) was revealed. The hexagonal phase consists of [Al(2)B(2)O(7)](infinity)(2)(-) lamellae stacked along the c axis, as in CaAl(2)B(2)O(7) and Na(2)Al(2)B(2)O(7). Nevertheless, the configuration and stacking sequence of the [Al(2)B(2)O(7)](infinity)(2)(-) lamellae are different in these three structures. In the hexagonal structure of Ca(1)(-)(x)()Na(2)(x)()Al(2)B(2)O(7), Ca and half Na cations (Na1) statistically occupy the same crystallographic site which is located between the [Al(2)B(2)O(7)](infinity)(2)(-) lamellae, the other half Na cations (Na2) distribute in the planes bisecting the [Al(2)B(2)O(7)](infinity)(2)(-) lamellae. Depending on the composition, the site occupation factor of Na2 site can vary in the same range as x, leading to a tunable density of Na(+) vacancies in the structure. The AlO(4) tetrahedra and BO(3) triangles in the structure tilt in appropriate ways to improve the bond valence sum of Na2 cations which are not sufficiently bonded to the anions.     

三重四极杆电感耦合等离子体质谱(ICP-MS)法测定氧化铕中13种稀土杂质元素

稀土杂质元素直接影响高纯单金属稀土材料的整体性能,是高科技领域许多材料的重要组成部分。通过考察最佳的消解酸量、温度、时间、氧气反应气流量、稀释气流量,建立了基于三重四极杆电感耦合等离子体质谱仪(ICP-MS/MS)直接测定氧化铕中13种稀土杂质元素分析方法。该方法采用0.1%基体直接进样,可以很大程度提高前处理分析效率。利用碰撞模式测定氧化铕稀土中的Y、La、Pr、Nd、Sm、Gd、Tb、Dy、Ho、Er、Yb、Lu元素,氧气质量转移模式测定氧化铕中的Tm,两种模式结合可以有效去除多原子干扰,实现氧化铕的稳定测试分析。通过对氧化铕标准物质（GBW02902）直接测定分析,结果表明,在碰撞和氧气质量转移模式下,各元素线性相关系数（r）均大于 0.9999,方法检出限为0.001~0.023 mg/kg,测试精密度优于1.99%,13种元素的测试值都在认定值的不确定度范围之内。该分析方法操作简单,测试稳定,效率高,为实验室进行氧化铕材料中REE杂质的准确测试分析提供思路和借鉴。     

微区X射线荧光光谱成像法分析历史文物建筑混凝土材料成分及工艺

历史文物建筑修复与保护的首要步骤是对建材构件进行成分解析。但成型的混凝土构件成分复杂,传统技术难以直接分析。微区X射线荧光光谱具有速度快、无需前处理、可获得大面积高分辨的元素成像等优势,可用于此类混合物的原位分析。本文采用束斑为20μm的微区X射线荧光光谱仪,扫描成型混凝土构件以获得混合成分的元素分布图,结合基本参数定量法,对上海地区典型历史建筑混泥土构件进行元素定量。分析结果有效地解析了混凝土构建中骨料和凝胶材料的成分和含量,鉴别了涂层成分,解析了拌混工艺,鉴别了局部污染元素和致劣元素并分析致劣原因,为历史建筑修复材料选配、拌混工艺选择、除污及保护性预防劣化提供了科学的数据支撑。     

Joint Optimization of Control Strategy and Energy Consumption for Energy Harvesting WSAN

With the rapid development of wireless sensor technology, recent progress in wireless sensor and actuator networks (WSANs) with energy harvesting provide the possibility for various real-time applications. Meanwhile, extensive research activities are carried out in the fields of efficient energy allocation and control strategy design. However, the joint design considering physical plant control, energy harvesting, and consumption is rarely concerned in existing works. In this paper, in order to enhance system control stability and promote quality of service for the WSAN energy efficiency, a novel three-step joint optimization algorithm is proposed through control strategy and energy management analysis. First, the optimal sampling interval can be obtained based on energy harvesting, consumption, and remaining conditions. Then, the control gain for each sampling interval is derived by using a backward iteration. Finally, the optimal control strategy is determined as a linear function of the current plant states and previous control strategies. The application of UAV formation flight system demonstrates that better system performance and control stability can be achieved by the proposed joint optimization design for all poor, sufficient, and general energy harvesting scenarios.     

KEADA: Identifying Key Classes in Software Systems Using Dynamic Analysis and Entropy-Based Metrics

Software maintenance is indispensable in the software development process. Developers need to spend a lot of time and energy to understand the software when maintaining the software, which increases the difficulty of software maintenance. It is a feasible method to understand the software through the key classes of the software. Identifying the key classes of the software can help developers understand the software more quickly. Existing techniques on key class identification mainly use static analysis techniques to extract software structure information. Such structure information may contain redundant relationships that may not exist when the software runs and ignores the actual interaction times between classes. In this paper, we propose an approach based on dynamic analysis and entropy-based metrics to identify key classes in the Java GUI software system, called KEADA (identifying KEy clAsses based on Dynamic Analysis and entropy-based metrics). First, KEADA extracts software structure information by recording the calling relationship between classes during the software running process; such structure information takes into account the actual interaction of classes. Second, KEADA represents the structure information as a weighted directed network and further calculates the importance of each node using an entropy-based metric OSE (One-order Structural Entropy). Third, KEADA ranks classes in descending order according to their OSE values and selects a small number of classes as the key class candidates. In order to verify the effectiveness of our approach, we conducted experiments on three Java GUI software systems and compared them with seven state-of-the-art approaches. We used the Friedman test to evaluate all approaches, and the results demonstrate that our approach performs best in all software systems.     

A Fault Detection Method for Electrohydraulic Switch Machine Based on Oil-Pressure-Signal-Sectionalized Feature Extraction

A turnout switch machine is key equipment in a railway, and its fault condition has an enormous impact on the safety of train operation. Electrohydraulic switch machines are increasingly used in high-speed railways, and how to extract effective fault features from their working condition monitoring signal is a difficult problem. This paper focuses on the sectionalized feature extraction method of the oil pressure signal of the electrohydraulic switch machine and realizes the fault detection of the switch machine based on this method. First, the oil pressure signal is divided into three stages according to the working principle and action process of the switch machine, and multiple features of each stage are extracted. Then the max-relevance and min-redundancy (mRMR) algorithm is applied to select the effective features. Finally, the mini batch k-means method is used to achieve unsupervised fault diagnosis. Through experimental verification, this method can not only derive the best sectionalization mode and feature types of the oil pressure signal, but also achieve the fault diagnosis and the prediction of the status of the electrohydraulic switch machine.     

An Encryption Algorithm for Region of Interest in Medical DICOM Based on One-Dimensional eλ-cos-cot Map

Today, with the rapid development of the Internet, improving image security becomes more and more important. To improve image encryption efficiency, a novel region of interest (ROI) encryption algorithm based on a chaotic system was proposed. First, a new 1D eλ-cos-cot (1D-ECC) with better chaotic performance than the traditional chaotic system is proposed. Second, the chaotic system is used to generate a plaintext-relate keystream based on the label information of a medical image DICOM (Digital Imaging and Communications in Medicine) file, the medical image is segmented using an adaptive threshold, and the segmented region of interest is encrypted. The encryption process is divided into two stages: scrambling and diffusion. In the scrambling stage, helical scanning and index scrambling are combined to scramble. In the diffusion stage, two-dimensional bi-directional diffusion is adopted, that is, the image is bi-directionally diffused row by column to make image security better. The algorithm offers good encryption speed and security performance, according to simulation results and security analysis.