High-throughput low-delay MAC protocol for Tera Hertz ultra-high data-rate wireless networks

To address the problems of the present Tera Hertz medium access control(MAC) protocols such as not updating the time slot requests numbers in time, unreasonable superframe structures and not merging time slot requests from the same pair of nodes, high throughput low delay medium access control(HLMAC), a novel MAC protocol for Tera Hertz ultra-high data-rate wireless networks is proposed. It reduces the data access delay largely with a new superframe structure, from which nodes can get time slot allocation information immediately. The network throughput is also improved with the help of updating time slot requests number and merging time slot requests from the same pair of nodes. The theoretical analysis verifies the effectiveness of HLMAC, and the simulation results show that HLMAC improves the network throughput by 65.7% and decreases the access delay by 30%, as compared to energy and spectrum-aware medium access control(ES-MAC).     

原子吸收光谱法测定TG6钛合金中痕量铁不确定度的分析

通过对原子吸收光谱法测定TG6钛合金中痕量铁的不确定度的系统分析,阐述了测量结果不确定度主要来源于测量试液中铁的浓度、试液定容体积及样品质量产生的不确定度,并对这些分量进行了量化计算,最后计算出合成标准不确定度和扩展不确定度。同时通过评估,得出影响铁含量测定不确定度的主要因素是测量试液中铁浓度引起的不确定度。     

Effects of water molecules on the formation of transfer films and the occurrence of superlow friction

The establishment of superlow friction in moist air is very important for the engineering application of hydrogenated diamond-like carbon (H-DLC) films. Nevertheless, water molecules in the surrounding atmosphere always result in the failure of the near-frictionless state. This work aims to explore the effects of water molecules in the environment and the material of the counterparts on the tribological performance of a composite structure prepared by depositing MoS₂ on a H-DLC film. The results indicated that the existence of water molecules in the atmosphere is beneficial for achieving stable superlubricity for the material system because it helps retain the in-situ formed MoS₂ transfer film on the counterpart. In the presence of water molecules, the wear interface was replaced by a robust and incommensurate MoS₂ tribolayer/H-DLC sliding interface, which was responsible for the superlow friction achieved in this work. The results also revealed that the ZrO₂ counterpart was capable of retaining the as-formed MoS₂ transfer film and establishing long-lasting superlow friction even in dry air. The mechanisms behind this phenomenon are also discussed in this paper.     

Effect of crystal habit and superstructure on modulus of elasticity of isotactic polypropylene by AFM nanoindentation

In this study the effects of crystal habit, crystallinity and superstructure on the modulus of elasticity of isotactic polypropylene films were analyzed by atomic force microscope (AFM) nanoindentation. The modulus of elasticity, evaluated on the nanometer scale by AFM, showed a qualitatively similar dependence on the crystal habit, crystallinity and superstructure as the modulus of elasticity measured by dynamic-mechanical analysis and tensile testing. The observed values of both the surface stiffness measured by AFM and the macroscopic/bulk stiffness were distinctly larger in the presence of non-isometric lamellae organized in spherulite than in the presence of isometric nodular crystals, not organized in a spherulitic superstructure. The experimental data showed that the modulus of elasticity is not primarily influenced by the presence or absence of spherulite but by the molecular-deformation constraint associated to the crystal habit.     

克地坝陵河特大桥大直径深桩基断桩处理措施

结合沪昆高铁克地坝陵河特大桥桩基断桩处理实例,分析了造成断桩的原因,并详细介绍了处理及预防大直径深桩基断桩的主要技术措施,实践表明采用下沉钢护筒措施处理断桩是可行的。     

Hierarchical feature selection based on relative dependency for gear fault diagnosis

Feature selection is an important aspect under study in machine learning based diagnosis, that aims to remove irrelevant features for reaching good performance in the diagnostic systems. The behaviour of diagnostic models could be sensitive with regard to the amount of features, and significant features can represent the problem better than the entire set. Consequently, algorithms to identify these features are valuable contributions. This work deals with the feature selection problem through attribute clustering. The proposed algorithm is inspired by existing approaches, where the relative dependency between attributes is used to calculate dissimilarity values. The centroids of the created clusters are selected as representative attributes. The selection algorithm uses a random process for proposing centroid candidates, in this way, the inherent exploration in random search is included. A hierarchical procedure is proposed for implementing this algorithm. In each level of the hierarchy, the entire set of available attributes is split in disjoint sets and the selection process is applied on each subset. Once the significant attributes are proposed for each subset, a new set of available attributes is created and the selection process runs again in the next level. The hierarchical implementation aims to refine the search space in each level on a reduced set of selected attributes, while the computational time-consumption is improved also. The approach is tested with real data collected from a test bed, results show that the diagnosis precision by using a Random Forest based classifier is over 98 % with only 12 % of the attributes from the available set.     

Chinese Oil Companies Active in Latin America

Latin American region has become a focus area for the Chinese state-owned oil companies to expand their international presence in recent years. They are now operating in Venezuela, Brazil, Ecuador, Peru and Argentina in cooperation for oil and gas exploration and development.