A brief review on α-zirconium phosphate intercalation compounds and nano-composites

The layer structured zirconium phosphate(Zr P) can be intercalated with atoms, molecules, small organic groups and even polymers. The structures and properties of the Zr P intercalation compounds can be deliberately tuned, leading to promising potential applications in many fields. This article provides a brief review on the experimental results of the Zr P intercalation compounds, with the focus on the polymer/a-zirconium phosphate (α-Zr P) nano-composites. The computer simulations of the Zr P intercalation compounds at the atomic level play a significant role in designing and understanding the properties of Zr P, and in the promotion of the applications of compounds.     

Influence of Cryomilling on the Morphology and Composition of the Oxide Scales Formed on HVOF CoNiCrAlY Coatings

Commercially available, gas-atomized CoNiCrAlY powder was cryomilled to produce powder with nanocrystalline grains. The cryomilled powder and conventional gas-atomized powder were thermally sprayed using the HVOF process to prepare two coatings with fine-grain (～15 nm) and coarse-grain (～1 μm) microstructure, respectively. The two coatings were isothermally oxidized in air at 1000° C for up to 330 hr. The morphology and composition of the oxide scales formed on the two coatings were compared with each other. The results indicate that, while a fine-grain microstructure can promote the formation of a pure alumina layer on the coating by increasing the Al diffusion rate toward the surface, it can also accelerate the Al depletion by increasing the Al diffusion rate toward the substrate, which results in the formation of non-alumina oxides after long-term oxidation. The mechanisms governing the oxide formation are discussed in terms of atomic diffusion and thermodynamic stability.     

Microstructural Investigation of Protective and Non-Protective Oxides on 11% Chromium Steel

FIB, SEM and STEM/EDX were used to investigate X20 stainless-steel samples exposed to dry O₂, or O₂ containing 40% H₂O, with a flow velocity of 0.5 cm/s or 5 cm/s, for 168 hr or 336 hr at 600°C. Thin protective Cr-rich (Cr,Fe)₂O₃ was maintained on the samples exposed to dry O₂, even after 336 hr, and on the sample exposed to O₂/H₂O mixture with the low-flow velocity (0.5 cm/s) for 168 hr. The oxide scale formed in the latter environment contained less Cr, due to Cr loss through CrO₂(OH)₂ evaporation. Breakaway oxidation occurred on the samples exposed in high-gas-flow velocity for shorter time (168 hr) or in low-gas-flow velocity (0.5 cm/s) for longer time (336 hr). The breakaway scales featured a two-layered structure: an outward-growing oxide “island” consisting of almost pure hematite (α-Fe₂O₃), and an inward-growing oxide “crater” consisting of (Cr,Fe)₃O₄. The transition from a thin protective (Cr,Fe)₂O₃ scale to a non-protective thick scale on this martensitic/ferritic steel originated locally and was followed by rapid oxide growth, resulting in a thick scale that covered the whole sample surface.     

A modular designed bolt tightening shaft based on adaptive fuzzy backstepping control

This paper presents a modular designed autonomous bolt tightening shaft system with an adaptive fuzzy backstepping control approach developed for it. The bolt tightening shaft is designed for the autonomous bolt tightening operation, which has huge potential for industry application. Due to the inherent nonlinear and uncertain properties, the bolt tightening shaft and the bolt tightening process are mathematically modeled as an uncertain strict feedback system. With the adaptive backstepping and approximation property of fuzzy logic system, the controller is recursively designed. Based on the Lyapunov stability theorem, all signals in the closed-loop system are proved to be uniformly ultimately bounded and the torque tracking error exponentially converges to a small residue. And the effectiveness and performance of the proposed autonomous system are verified by the simulation and experiment results on the bolt tightening shaft system.     

新时期中职体育礼仪教育的实施策略

体育是文化的重要组成部分,不管是在世界,还是在国内,都已经成为了人们日常生活的一部分,也影响着人们的生活。中职的体育教学是培养人才的重要手段,蕴含着丰富的教育功能。在中职体育教学中,通过体育礼仪的教育可以提高中职学生的礼仪修养,进而促进学生整体思想水平和境界的提升。     

中央一号文件出台背景及政策要点

一、一号文件出台的背景1.兴水利除水害是治国安邦的头等大事在前不久一次会议上,一位中央领导同志指出,水的问题对中国来讲,历来都是一个大事。党的十五届三中全会决定中也有类似的论述。这次一号文件更是鲜明地提出,水旱     

Testing the equality of proportions for correlated otolaryngologic data

In otolaryngologic (or ophthalmologic) studies, each subject usually contributes information for each of two ears (or eyes), and the values from the two ears (or eyes) are generally highly correlated. Statistical procedures that fail to take into account the correlation between responses from two ears could lead to incorrect results. On the other hand, asymptotic procedures that overlook small sample designs, sparse data structures, or the discrete nature of data could yield unacceptably high type I error rates even when the intraclass correlation is taken into consideration. In this article, we investigate eight procedures for testing the equality of proportions in such correlated data. These test procedures will be implemented via the asymptotic and approximate unconditional methods. Our empirical results show that tests based on the approximate unconditional method usually produce empirical type I error rates closer to the pre-chosen nominal level than their asymptotic tests. Amongst these, the approximate unconditional score test performs satisfactorily in general situations and is hence recommended. A data set from an otolaryngologic study is used to illustrate our proposed methods.     

Utilize bootstrap in small data set learning for pilot run modeling of manufacturing systems

If the production process, production equipment, or material changes, it becomes necessary to execute pilot runs before mass production in manufacturing systems. Using the limited data obtained from pilot runs to shorten the lead time to predict future production is this worthy of study. Although, artificial neural networks are widely utilized to extract management knowledge from acquired data, sufficient training data is the fundamental assumption. Unfortunately, this is often not achievable for pilot runs because there are few data obtained during trial stages and theoretically this means that the knowledge obtained is fragile. The purpose of this research is to utilize bootstrap to generate virtual samples to fill the information gaps of sparse data. The results of this research indicate that the prediction error rate can be significantly decreased by applying the proposed method to a very small data set.