Optimizing the Oxygen-Catalytic Performance of Zn–Mn–Co Spinel by Regulating the Bond Competition at Octahedral Sites

By using the more electro-negative Mn³⁺ ion to partially replace Co³⁺ at the octahedral site of spinel ZnCo₂O₄, i.e., forming ternary Zn–Mn–Co spinel oxide, the electrocatalytic oxygen reduction/evolution activity is found to be significantly increased. Considering the physical characterization and theoretical calculations, it demonstrated that the bond competition played a key role in regulating the cobalt valence state and the electrocatalytic activity. The partial replacement of octahedral-site-occupied Co³⁺ by Mn³⁺ can effectively modulate the adjacent Co–O bond and induce the Jahn–Teller effect, thus changing the originally stable crystal structure and optimizing the binding strength between the active center and reaction intermediates. Certainly, the Mn-substituted ZnMn_1.4Co_0.6O₄/NCNTs exhibit higher electrocatalytic oxygen reduction reaction (ORR) activity than that of ZnCo₂O₄/NCNTs and ZnMn₂O₄/NCNTs, supporting that the Co–O bond covalency determines the ORR activity of spinel ZnCo₂O₄. This study offers the competition between adjacent Co–O and Mn–O bonds via the B_Oh–O–B_Oh edge-sharing geometry. The ion substitution at octahedral sites by less electronegative cations can be a new and effective way to improve the electrocatalytic performance of cobalt-based spinel oxides.     

Social-path embedding-based transformer for graduation development prediction

As the education of students attracts more and more attention, the task of graduation development prediction has gradually become a hot topic in academia and industry. The task of graduation development prediction aims to predict the employment category of students in advance via academic achievement data, which can help administrators understand students’ learning status and set up a reasonable learning plan. However, existing research ignores the potential impact of social relationships on students’ graduation development choices. To fully explore social relationships among students, we propose a Social-path Embedding-based Transformer Neural Network (SPE-TNN) for the task of graduation development prediction in this paper. Specifically, SPE-TNN is divided into the Social-path selection layer, the Social-path embedding layer, the Transformer layer, and the Multi-layer projection layer. Firstly, the Social-path selection layer is designed to find social relationships that impact graduation development and embed them into the student’s performance features through the Social-path embedding layer. Secondly, the Transformer layer is adopted to balance the weights of the students’ features. Finally, the Multi-layer projection layer is used to achieve the student graduation development prediction. Experimental results on the real-world datasets show that SPE-TNN outperforms the existing popular approaches.

     

UV Photodetectors Based on BiOCl Nanosheet Arrays: The Effects of Morphologies and Electrode Configurations

A facile chemical bath method is adopted to grow bismuth oxychloride (BiOCl) nanosheet arrays on a piece of Cu foil (denoted as BiOCl‐Cu) and isolated BiOCl nanosheets are collected by ultrasonication. A self‐supporting BiOCl film is obtained by the removal of Cu foil. Photodetectors (PDs) based on these BiOCl materials are assembled and the effects of morphologies and electrode configurations on the photoelectric performance of these PDs are examined. The BiOCl nanosheet PD achieves high responsivities in the spectral range from 250 to 350 nm, while it presents quite a small photocurrent and slow response speed. The BiOCl film PD yields low photocurrents and near‐unity on–off ratios, demonstrating poor photoelectric performance. The photocurrent of the BiOCl‐Cu PD with both electrodes on the BiOCl film is much higher than those of these above‐mentioned PDs, and the response times are fast. Meanwhile, the BiOCl‐Cu PD with separate electrodes on the BiOCl film and Cu foil achieves even higher photocurrents and presents a self‐powering characteristic, depicting the improved photodetecting performances induced by the specific morphology and distinct electrode configuration. These results would promote the applications of BiOCl nanostructures in the photoelectric devices.     

Dynamic mix zone: location data sanitizing in assisted environments

Pervasive technology has been widely used in assistive environments and aware homes. The issue of how to preserve the privacy of patients being monitored has been attracting more public concerns. In assistive environments, location data of patients are collected through sensors for behavior patterns analysis, and they can also be shared among researchers for further research for early disease diagnosis. However, location information, even though de-identified, also introduces the risk of privacy leakage. A series of consecutive location samples can be considered as a trajectory of a single person, and this may leak private information if obtained by malicious users. This paper discusses this problem and proposes a location randomization algorithm to protect users’ location privacy. Two privacy metrics according to location privacy are defined and used to evaluate the proposed approach. A method using dynamic mix zones is proposed to confound trajectories of two or more persons.     

Diverse community: Demand differentiation in P2P live streaming

Peer-to-Peer (P2P) technology has become an attractive approach for enabling large-scale video streaming applications, but the factor of users’ subjective preferences is not paid enough attention in such networks. As users have various demand on video qualities, we can provide them with video streams at different resolutions without impairing their satisfaction. The adaptive streaming rate technique is a promising method. However, in providing adaptive streaming rate services, P2P live streaming design faces the following challenge: how to provide all users with uninterrupted video with their desired qualities in case that their demand dynamically changes? To shed more light on this problem, we first derive a model and formulate the problem as a resource demand vs supply problem. Then we present a framework to address the challenge via efficient bandwidth allocation and group cooperation. Through comprehensive simulations, we evaluate the effectiveness of the proposed framework, and conclude that it effectively helps existing solutions, such as Partial Participation Scheme (PPS), achieve better performance.     

Fast Algorithm for Walsh Hadamard Transform on Sliding Windows

This paper proposes a fast algorithm for Walsh Hadamard Transform on sliding windows which can be used to implement pattern matching most efficiently. The computational requirement of the proposed algorithm is about 1.5 additions per projection vector per sample, which is the lowest among existing fast algorithms for Walsh Hadamard Transform on sliding windows.     

新型锁相环在频率跟踪技术中的研究

在比较电力系统频率跟踪技术中软硬件同步优缺点的基础上,提出了一种基于FPGA的全数字锁相环(ADPLL)电路实现电力系统频率跟踪的技术;将FPGA技术运用于同步跟踪技术中,解决了软硬同步方法中的各个不足之处;全数字锁相环电路采用VHDL语言和FPGA设计,仿真波形和实验结果表明,该电路能够很好地跟踪电网频率的实时变化,相位误差仅为0.1%,频率测量误差仅为0.06%,实现了同频率同相位的锁定;速度快、精度高;对电网的谐波计算有较大的实际意义.     

基于Struts框架的Web应用研究与实现

Struts是目前Java Web领域使用最广泛的框架,研究了MVC设计模式以及Struts框架中的主要组件。详细描述了将Struts框架应用到实际项目中的过程。实践表明：利用Struts框架可以提高Web开发效率以及系统的可扩展性和维护性。     

Phase change materials in the ternary system NH4Cl+CaCl2+H2O

Solubility isotherms of the ternary system (NH₄Cl+CaCl₂+H₂O) were elaborately determined at T= (273.15 and 298.15) K by using the isothermal method. In the equilibrium phase diagram, there are two solubility branches corresponding to the solid phases CaCl₂⋅6H₂O and NH₄Cl. Invariant point compositions are 36.32 wt% CaCl₂ and 3.4 wt% NH₄Cl at 273.15 K, and 45.86 wt% CaCl₂ and 5.22 wt% NH₄Cl at 298.15 K. A Pitzer-Simonson-Clegg thermodynamic model was applied to represent the thermodynamic properties of this ternary system and to construct a partial phase diagram of the ternary system at temperatures between (273.15 and 323.15) K. It was found in the predicted solubility phase diagram that the double salt 2NH₄Cl⋅CaCl₂⋅3H₂O, found by other authors at (323.1 and 348.1) K, will disappear at temperatures below 298.15 K. Besides, it was found that there are two peritectic points in the ternary system with peritectic temperatures at 299.65 K and 298.15 K, and the former peritectic point falls just on the line between the composition points of NH₄Cl and CaCl₂⋅6H₂O. According to phase rule, a solution made of this point will begin to crystallize at 299.65 K and end at 298 K and therefore can be acted as a “pseudo eutectic” phase change material (PCM). A heat storing and releasing experiment of 50 grams of the PCM was carried out, obtaining a satisfying result.     

Induction of multiclass multifeature split decision trees from distributed data

The decision tree-based classification is a popular approach for pattern recognition and data mining. Most decision tree induction methods assume training data being present at one central location. Given the growth in distributed databases at geographically dispersed locations, the methods for decision tree induction in distributed settings are gaining importance. This paper describes one such method that generates compact trees using multifeature splits in place of single feature split decision trees generated by most existing methods for distributed data. Our method is based on Fisher's linear discriminant function, and is capable of dealing with multiple classes in the data. For homogeneously distributed data, the decision trees produced by our method are identical to decision trees generated using Fisher's linear discriminant function with centrally stored data. For heterogeneously distributed data, a certain approximation is involved with a small change in performance with respect to the tree generated with centrally stored data. Experimental results for several well-known datasets are presented and compared with decision trees generated using Fisher's linear discriminant function with centrally stored data.