Stabilizing Redox-Active Hexaazatriphenylene in a 2D Conductive Metal–Organic Framework for Improved Lithium Storage Performance

Organic redox-active materials are promising electrode candidates for lithium-ion batteries by virtue of their designable structure and cost-effectiveness. However, their poor electrical conductivity and high solubility in organic electrolytes limit the device's performance and practical applications. Herein, the π-conjugated nitrogen-containing heteroaromatic molecule hexaazatriphenylene (HATN) is strategically embedded with redox-active centers in the skeleton of a Cu-based 2D conductive metal–organic framework (2D c-MOF) to optimize the lithium (Li) storage performance of organic electrodes, which delivers improved specific capacity (763 mAh g⁻¹ at 300 mA g⁻¹), long-term cycling stability (≈90% capacity retention after 600 cycles at 300 mA g⁻¹), and excellent rate performance. The correlation of experimental and computational results confirms that this high Li storage performance derives from the maximum number of active sites (CN sites in the HATN unit and CO sites in the CuO₄ unit), favorable electrical conductivity, and efficient mass transfer channels. This strategy of integrating multiple redox-active moieties into the 2D c-MOF opens up a new avenue for the design of high-performance electrode materials.     

Lightweight deep learning methods for panoramic dental X-ray image segmentation

Neural Computing and Applications - Dental X-ray image segmentation is helpful for assisting clinicians to examine tooth conditions and identify dental diseases. Fast and lightweight segmentation...     

Teachers cooperation: team-knowledge distillation for multiple cross-domain few-shot learning

Although few-shot learning (FSL) has achieved great progress, it is still an enormous challenge especially when the source and target set are from different domains, which is also known as cross-domain few-shot learning (CD-FSL). Utilizing more source domain data is an effective way to improve the performance of CD-FSL. However, knowledge from different source domains may entangle and confuse with each other, which hurts the performance on the target domain. Therefore, we propose team-knowledge distillation networks (TKD-Net) to tackle this problem, which explores a strategy to help the cooperation of multiple teachers. Specifically, we distill knowledge from the cooperation of teacher networks to a single student network in a meta-learning framework. It incorporates task-oriented knowledge distillation and multiple cooperation among teachers to train an efficient student with better generalization ability on unseen tasks. Moreover, our TKD-Net employs both response-based knowledge and relation-based knowledge to transfer more comprehensive and effective knowledge. Extensive experimental results on four fine-grained datasets have demonstrated the effectiveness and superiority of our proposed TKD-Net approach.     

Complex and flexible data access policy in attribute-based encryption

The Journal of Supercomputing - With the development of cloud computing application, attribute-based encryption (ABE) with flexibly fine-grained data access control is widely adopted. However,...     

Avoiding negative elastic moduli when using Lagrange interpolation for material grading in finite element analysis

Polynomial interpolations, one of the most common interpolations used in finite element methods (FEMs), are a workhorse of many FEM codes. These interpolations are readily available for all kinds of elements, and using them for modeling the variation of elastic moduli in graded elements is thus both convenient and natural. Yet, like all polynomial interpolations, they can be prone to oscillations that can result in regions of negative elastic modulus in the element, even with only positive nodal values of elastic moduli. The result of these negative modulus regions, even if the region is small, can be unexpected singularities in the solution. This defeats the purpose of using polynomial interpolations for capturing material grading in the element. We demonstrate the issue using three-node quadratic Lagrange interpolations of material grading in otherwise isoparametric p-type elements and show how to avoid this problem.     

远程勘验取证分析软件开发与实现

远程勘验分析技术是计算机取证技术的一个重要分支,而如何实现自动、智能远程勘验分析目标网站是一项重要研究课题。文章简要介绍了远程勘验取证分析软件＂网际无痕特种兵＂基本原理和功能,进行了实证性分析并取得了积极的成果。     

TMS-RFID: Temporal management of large-scale RFID applications

In coming years, there will be billions of RFID tags living in the world tagging almost everything for tracking and identification purposes. This phenomenon will impose a new challenge not only to the network capacity but also to the scalability of event processing of RFID applications. Since most RFID applications are time sensitive, we propose a notion of Time To Live (TTL), representing the period of time that an RFID event can legally live in an RFID data management system, to manage various temporal event patterns. TTL is critical in the “Internet of Things” for handling a tremendous amount of partial event-tracking results. Also, TTL can be used to provide prompt responses to time-critical events so that the RFID data streams can be handled timely. We divide TTL into four categories according to the general event-handling patterns. Moreover, to extract event sequence from an unordered event stream correctly and handle TTL constrained event sequence effectively, we design a new data structure, namely Double Level Sequence Instance List (DLSIList), to record intermediate stages of event sequences. On the basis of this, an RFID data management system, namely Temporal Management System over RFID data streams (TMS-RFID), has been developed. This system can be constructed as a stand-alone middleware component to manage temporal event patterns. We demonstrate the effectiveness of TMS-RFID on extracting complex temporal event patterns through a detailed performance study using a range of high-speed data streams and various queries. The results show that TMS-RFID has a very high throughput, namely 170,000–870,000 events per second for different highly complex continuous queries. Moreover, the experiments also show that the main structure to record the intermediate stages in TMS-RFID does not increase exponentially with the number of events. These results demonstrate that TMS-RFID not only supports high processing speeds, but is also highly scalable.     

GPS导航数据提取的设计与研究

为解决盲用定位模块在嵌入式平台下实现的问题,根据串口通信同步方式实现WindowsCE 5.0操作系统下GPS导航数据的提取,并对获得的数据提出一种格式转换的方法.以PXA270嵌入式系统平台实现系统原型,在有限硬件条件下验证了系统的功能及可行性.实验结果表明,该系统运行稳定,实验数据可靠有效,可以有效结合电子地图数据提取出周边的位置信息.