High-rate capability of carbon-coated micron-sized hexagonal TT-Nb2O5 composites for lithium-ion battery

With excellent specific capacity, superior cycle stability, safety and strong practical, Nb₂O₅ has been considered as one of the prospective anode materials for lithium-ion batteries (LIBs). However, current study suggests that Nb₂O₅ electrode materials for LIBs still face the vital issues of low electrical conductivity and poor rate performance. Therefore, carbon-coated TT-Nb₂O₅ materials are designed and synthesized through solid state method in this work, which present high specific capacity (228 mA h g^?1 at 0.2C), satisfactory rate properties (107 mA h g^?1 at 20 C). The outstanding electrochemical property can not only give the credit to the pseudocapacitance effect of TT-Nb₂O₅, but also attribute to introduction of carbon. The homogeneous carbon-coated materials enhance the electrical conductivity, increase the electron transmission speed and alleviate particle crushing. This research not only offers a new method for preparing excellent electrode materials, but also provides a kind of excellent anode material with prospective application for LIBs.     

Study of haze emission efficiency based on new co-opetition data envelopment analysis

As haze intensifies in China, controlling haze emission has become the country's top priority for environmental protection. Because haze moves across different regions, it is necessary to develop a data envelopment analysis (DEA) model underpinned by both competition and cooperation to evaluate the haze emission efficiency in different provinces. This study innovatively adopts the spatial econometrics to construct the co-opetition matrices of Chinese provinces, then builds the co-opetition DEA model to evaluate the haze emission efficiency of them, and finally uses the haze data of 2015 as an example to assess the applicability of the model. The results of the study include the following: First, compared with the traditional CCR (A. Charnes & W. W. Cooper & E. Rhodes) model, this study constructs the co-opetition DEA cross-efficiency model that integrates haze's feature of cross-border moving; thus, it is more in line with the reality of haze emission and movement. Second, compared with the efficiency value gained from the CCR model, the haze emission efficiency values for Tianjin and Guangdong, two decision-making units, register greater variance when using the DEA model. The reason might lie in that they have a different spatial transportation relationship with their surrounding provinces. Third, the haze emission efficiency of provinces, according to the evaluation based on the co-opetition DEA method, varies greatly: Those with high efficiency are mostly inland provinces with slow economic growth and adverse climatic conditions, whereas many of the provinces with low efficiency are located in the relatively prosperous East China. The specific co-opetition DEA model constructed in this study enriches the research on the DEA model, which can be applied to the emission efficiency evaluation of similar pollutants around the world and can contribute empirical support to the haze reducing efforts of the government with its empirical results.     

Fair‐Weather Friends: Evidence of Lipoxin Dysregulation in Neurodegeneration

Lipoxins (LXs) are autacoids, specialized proresolving lipid mediators (SPMs) acting locally in a paracrine or autocrine fashion. They belong to a complex superfamily of dietary small polyunsaturated fatty acid (PUFA)–metabolites, which direct potent cellular responses to resolve inflammation and restore tissue homeostasis. Together, these SPM activities have been intensely studied in systemic inflammation and acute injury or infection, but less is known about LX signaling and activities in the central nervous system. LXs are derived from arachidonic acid, an omega‐6 PUFA. In addition to well‐established roles in systemic inflammation resolution, they have increasingly become implicated in regulating neuroinflammatory and neurodegenerative processes. In particular, chronic inflammation plays a central role in Alzheimer's disease (AD) etiology, and dysregulated LX production and activities have been reported in a variety of AD rodent models and clinical tissue samples, yet with complex and sometimes conflicting results. In addition, reduced LX production following retinal injury has been reported recently by the authors, and an intriguing direct neuronal activity promoting survival and homeostasis in retinal and cortical neurons is demonstrated. Here, the authors review and clarify this growing literature and suggest new research directions to further elaborate the role of lipoxins in neurodegeneration.     

Reducing the complexity of distance measurement methods for circular turbo codes that use structured interleavers

The knowledge of turbo code's minimum Hamming distance (d_min) and its corresponding codeword multiplicity (A_min) is of a great importance because the error correction capability of a code is strongly tied to the values of d_min and A_min. Unfortunately, the computational complexity associated with the search for d_min and A_min can be very high, especially for a turbo code that has high d_min value. This paper introduces some useful properties of turbo codes that use structured interleavers together with circular encoding. These properties allow for a significant reduction of search space and thus reduce significantly the computational complexity associated with the determination of d_min and A_min values. © 2014 The Authors. International Journal of Communication Systems published by John Wiley & Sons, Ltd.     

Wearing prediction of stellite alloys based on opposite degree algorithm

In order to predict the wearing of stellite alloys,the related methods of rare metals data processing were discussed. The method of opposite degree(OD) algorithm was put forward to predict the wearing of stellite alloys.OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation(BP) and radial basis function(RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.