A data collection protocol for real-time sensor applications

The nature of many sensor applications as well as continuously changing sensor data often imposes real-time requirements on wireless sensor network protocols. Due to numerous design constraints, such as limited bandwidth, memory and energy of sensor platforms, and packet collisions that can potentially lead to an unbounded number of retransmissions, timeliness techniques designed for real-time systems and real-time databases cannot be applied directly to wireless sensor networks. Our objective is to design a protocol for sensor applications that require periodic collection of raw data reports from the entire network in a timely manner. We formulate the problem as a graph coloring problem. We then present TIGRA (Timely Sensor Data Collection using Distributed Graph Coloring) — a distributed heuristic for graph coloring that takes into account application semantics and special characteristics of sensor networks. TIGRA ensures that no interference occurs and spatial channel reuse is maximized by assigning a specific time slot for each node. Although the end-to-end delay incurred by sensor data collection largely depends on a specific topology, platform, and application, TIGRA provides a transmission schedule that guarantees a deterministic delay on sensor data collection.     

高速可配置Rijndael算法的设计与实现

针对网络通信的安全要求,给出了在集成电路设计中实现Rijndael算法的高吞吐率解决方案。对算法实现进行了优化,具有支持密钥长度和数据长度的可变选择与组合配置,加密和解密工作通道完全独立,全双工安全高速通信等特点。已通过了FPGA的验证与电路实现。通过对比分析综合仿真结果,该实现相对于目前已知的实现方案在性能和速度上具有很大的优势。     

Cytotoxicity of aggregated fullerene C60 particles on CHO and MDCK cells

The cytotoxicity of fullerene C60 particles on two mammalian cell lines, i.e. the Chinese hamster ovary (CHO) cells and the Madin-Darby canine kidney (MDCK) cells, has been investigated. Although innate fullerene particles have a very low solubility in deionized (DI) water, these particles can be dissolved in the tetrahydrofuran (THF) solvent at a great value. Further, the dissolved fullerene particles in the THF solvent could be extracted into a DI water solution at a significantly increased solubility. The formation of fullerene particle aggregates is believed to be the cause of the increased solubility. Results presented here show that once the concentration of the fullerene aggregates reaches a certain level, the cells start to die. The lethal dosage LD50, which is defined as the lowest fullerene concentration that results in a 50% cell death within 24 h, has been determined. Furthermore, the percentage of cell mortality increased with increasing fullerene concentration and incubation time yielding a negative effect on cell viability. These results, illustrated by atomic force microscopy (AFM), dynamic light scattering (DLS) and other microscopic techniques, will help to better understand the side effects of fullerene particles in mammalian cells.     

CSE620R分切机退卷控制器参数调校的新方法

文章针对CSE620R分切机退卷张力控制系统过去使用过渡膜调校方法的不足,从理论上对各个需要调校的参数进行理论计算和曲线校对,并将计算结果对控制板进行设定和曲线校对.这既提高了调校精度又达到稳定生产的目的.避免了浪费大量的薄膜和能耗.     

Dijkstra算法在肾脏移植交换系统中的应用

在肾脏移植过程中,经常存在一个病人的亲属愿意将自己的一个肾脏捐赠给此病人,但是他们的肾脏匹配不够好,只能放弃的情况,这明显是一种资源的浪费.一个可行的方案就是肾脏交换系统.在这篇论文中,我们提出了两种解决方法,分别代表了解决此问题的两个解决方向.给一些相应的组织,如美国的OPTN,一定的改进建议,并对其他国家建立类似的组织起到一定的指导作用.     

In Situ Polymerizing Internal Encapsulation Strategy Enables Stable Perovskite Solar Cells toward Lead Leakage Suppression

Despite the outstanding power conversion efficiency (PCE) of perovskite solar cells (PSCs) achieved over the years, unsatisfactory stability and lead toxicity remain obstacles that limit their competitiveness and large-scale practical deployment. In this study, in situ polymerizing internal encapsulation (IPIE) is developed as a holistic approach to overcome these challenges. The uniform polymer internal package layer constructed by thermally triggered cross-linkable monomers not only solidifies the ionic perovskite crystalline by strong electron-withdrawing/donating chemical sites, but also acts as a water penetration and ion migration barrier to prolong shelf life under harsh environments. The optimized MAPbI₃ and FAPbI₃ devices with IPIE treatment yield impressive efficiencies of 22.29% and 24.12%, respectively, accompanied by remarkably enhanced environmental and mechanical stabilities. In addition, toxic water-soluble lead leakage is minimized by the synergetic effect of the physical encapsulation wall and chemical chelation conferred by the IPIE. Hence, this strategy provides a feasible route for preparing efficient, stable, and eco-friendly PSCs.     

Proximity-Induced Fully Ferromagnetic Order with Eightfold Magnetic Anisotropy in Heavy Transition Metal Oxide CaRuO3

Ferromagnetic materials with a strong spin-orbit coupling (SOC) have attracted much attention in recent years because of their exotic properties and potential applications in energy-efficient spintronics. However, such materials are scarce in nature. Here, a proximity-induced paramagnetic to ferromagnetic transition for the heavy transition metal oxide CaRuO₃ in (001)-(LaMnO₃/CaRuO₃) superlattices is reported. Anomalous Hall effect is observed in the temperature range up to 180 K. Maximal anomalous Hall conductivity and anomalous Hall angle are as large as ∼15 Ω⁻¹ cm⁻¹ and ∼0.93%, respectively, by one to two orders of magnitude larger than those of the typical 3d ferromagnetic oxides such as La_0.67Sr_0.33MnO₃. Density functional theory calculations indicate the existence of avoid band crossings in the electronic band structure of the ferromagnetic CRO layer, which enhances Berry curvature thus strong anomalous Hall effects. Further evidences from polarized neutron reflectometry show that the CaRuO₃ layers are in a fully ferromagnetic state (∼0.8 μ_B/Ru), in sharp contrast to the proximity-induced canted antiferromagnetic state in 5d oxides SrIrO₃ and CaIrO₃ (∼0.1 μ_B/Ir). More than that, the magnetic anisotropy of the (001)-(LaMnO₃/CaRuO₃) superlattices is eightfold symmetric, showing potential applications in the technology of multistate data storage.     

Editorial: Machine Learning and Intelligent Communications (MLICOM 2018)

Mobile Networks and Applications -     

Analysis of Internet Financial Risks Based on Deep Learning and BP Neural Network

Computational Economics - The study aims to analyze and forecast Internet financial risks based on the model based on deep learning and the Back Propagation Neural Network (BPNN). First, the theory...