超声换能器检测方法的研究

超声检测技术广泛使用在无损检测领域中,而换能器是超声工程中极其重要的技术和分支领域。超声换能器是一种电声能量转换器件,是超声检测技术中的关键,直接影响无损检测结果的可靠性,本文阐述了超声换能器的原理和测量接触换能器的检测方法,分析了A型换能器脉冲回波灵敏度校准的不确定度。     

In-situ synthesis of TiO2 nanostructures on Ti foil for enhanced and stable photocatalytic performance

TiO_2 nanostructures with strong interfacial adhesion and diverse morphologies have been in-situ grown on Ti foil substrate through a multiple-step method based on conventional plasma electrolytic oxidation(PEO) technology, hydrothermal reaction and ion exchange process. The PEO process is critical to the formation of TiO_2 seeding layer for the nucleation of Na_2Ti_3O_7 and H_2Ti_3O_7 mediates that are strongly attached to the Ti foil. An ion exchange reaction can finally lead to the formation of H_2Ti_3O_7 nanostructures with diverse morphologies and the calcination process can turn the H_2Ti_3O_7 nanostructures into TiO_2 nanostructures with enhanced crystallinity. The morphology of the TiO_2 nanostructures including nanoparticles(NP), nanowhiskers(NWK), nanowires(NW) and nanosheets(NS) can be easily tailored by controlling the NaOH concentration and reaction time during hydrothermal process. The morphology, composition and optical properties of TiO_2 photocatalysts were analyzed using scanning electron microscope(SEM), X-ray diffraction(XRD), photoluminescence(PL) spectroscopy and UV–vis absorption spectrum. Photocatalytic tests indicate that the TiO_2 nanosheets calcined at 500?C show good crystallization and the best capability of decomposing organic pollutants. The decoration of Ag cocatalyst can further improve the photocatalytic performance of the TiO_2 nanosheets as a result of the enhanced charger separation efficiency. Cyclic photocatalytic test using TiO_2 nanostructures grown on Ti foil substrate demonstrates the superior stability in the photodegradation of organic pollutant, suggesting the promising potential of in-situ growth technology for industrial application.     

Computational Parametric Analysis of Cellular Solids with the Miura-Ori Metamaterial Geometry under Quasistatic Compressive Loads

Origami-based metamaterials have widespread application prospects in various industries including aerospace, automotive, flexible electronics, and civil engineering structures. Among the wide range of origami patterns, the fourfold tessellation known as Miura-ori is of particular attraction to engineers and designers. More specifically, researchers have proposed different 3D structures and metamaterials based on the geometric characteristics of this classic origami pattern. Herein, a computational modeling approach for the design and evaluation of 3D cellular solids with the Miura-ori metamaterial geometry which can be of zero or nonzero thicknesses is presented. To this end, first, a range of design alternatives generated based on a numerical parametric model is designed. Next, their mechanical properties and failure behavior under quasistatic axial compressive loads along three perpendicular directions are analyzed. Then, the effects of various geometric parameters on their energy absorption behavior under compression in the most appropriate direction are investigated. The findings of this study provide a basis for future experimental investigations and the potential application of such cellular solids for energy-absorbing purposes.     

Escherichia coli prlC gene encodes a trypsin-like proteinase regulating the cell cycle

BACKGROUND AND PURPOSE: Mood disorders are common after stroke and may impede physical, functional, and cognitive recovery, making early identification and treatment of potential importance. We aimed to compare the accuracy of the General Health Questionnaire (GHQ-30) and the Hospital Anxiety and Depression (HAD) Scale in detecting psychiatric morbidity after stroke and to determine the most suitable cutoff points for different purposes. METHODS: One hundred five hospital-referred stroke patients completed both the GHQ-30 and HAD Scale 6 months after onset before a blinded psychiatric assessment in which the Schedule for Affective Disorders and Schizophrenia with some supplementary questions was used to determine a DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) diagnosis. Measures were compared in terms of sensitivity, specificity, and receiver operating characteristic curves. RESULTS: No significant differences were found between the GHQ-30 and the HAD Scale in identifying those patients with any DSM-IV diagnosis (P=0.95), grouped depression (P=0.56), or anxiety (P=0.25) disorders. The previously recommended cutoff points for identifying "cases" for the GHQ (4/5) and for the HAD Scale (8/9 and 11/12) were found to be suboptimal in this population. CONCLUSIONS: The GHQ-30 and HAD scale exhibited similar levels of sensitivity and specificity. Data are presented, taking into account the "cost" of false-positives and negatives, to allow a choice of cutoff points suitable for differing situations.     

A relativistic extension of the complex scaling method using oscillator basis functions

We develop the complex scaling method within the relativistic framework by expanding the Dirac spinors in the complete set of eigensolutions of a harmonic oscillator potential, and present the theoretical formalism of describing the discrete bound and resonant states on the same footing. Based on a well established and frequently used model, we demonstrate the utility and applicability of the extended method and examine the stability of the results with respect to the variations of the parameters of the model. Satisfactory agreements are found for all the calculated results in comparison with some other calculations in references. Especially, the present calculation in the nonrelativistic limit gives a consistent result with that in the nonrelativistic calculation.     

基于无线网络技术的燃气集抄系统设计

针对燃气行业人工抄表费时费力等问题,提出一种基于GPRS和无线多跳网络技术的燃气无线抄表系统,在分析传统抄表系统的结构以及传输方式优缺点的基础上介绍了系统的总体结构、工作原理以及各部分组成和功能。采用计算机网络和数据库等技术,使得该系统具有功能强大、使用方便、可扩展性好等特点,可实现对整个燃气输配系统的监控,有效提高燃气公司的管理水平和服务效率。     

A two-level strategy for segmenting center of interest from pictures

Segmenting center of interests (COIs) from pictures is an important but highly challenging problem for researchers in computer vision and image processing. The capability of understanding the meanings of pictures by computers can lead to breakthroughs in a wide range of applications including Web image search and online picture-sharing communities. In this paper, a two-level strategy is presented, which consists of a rough segmentation stage and a fine segmentation stage. In the first level, a picture is partitioned into four regions by using a block clustering method based on color and texture features, and the COI within the picture is distinguished from the background according to the principles of photographic composition. This stage aims to determine the approximate region of the target. In the second level, a novel active contour model is established based on shape information and vector method, where the image energy is defined by a hue gradient and the external energy is generated from either a triangular inner force or a supplementary force. This stage tries to extract the boundary of the target accurately. Experimental results on photos downloaded from the Internet show the feasibility and effectiveness of the proposed method.     

基于网络的智能辅导模式研究与系统设计

针对目前辅导行业的现状,为解决课后辅导的自动化、实时化的问题,分析了学生课后学习掌握知识的过程,提出了一个基于学生课后学习规律的辅导模型,建立了面向问题的多层面知识辅导新模式,构建了基于此模式的网络智能家教系统的框架结构。该系统采用基于知识的自动推理技术使得推理过程得以完整保存来分析后续的多层面辅导信息,采用资源模型分解知识粒度保证抽象度,采用网络服务模式满足用户的实时使用。以学生提出的几何问题为实例,展示了多层面辅导过程,实验结果表明了该模式和系统设计的可行性。     

Performance Analysis of Gradient Neural Network Exploited for Online Time-Varying Matrix Inversion

This technical note presents theoretical analysis and simulation results on the performance of a classic gradient neural network (GNN), which was designed originally for constant matrix inversion but is now exploited for time-varying matrix inversion. Compared to the constant matrix-inversion case, the gradient neural network inverting a time-varying matrix could only approximately approach its time-varying theoretical inverse, instead of converging exactly. In other words, the steady-state error between the GNN solution and the theoretical/exact inverse does not vanish to zero. In this technical note, the upper bound of such an error is estimated firstly. The global exponential convergence rate is then analyzed for such a Hopfield-type neural network when approaching the bound error. Computer-simulation results finally substantiate the performance analysis of this gradient neural network exploited to invert online time-varying matrices.     

一种基于组策略的过滤式特征选择算法

MRMR算法具有快速、高效等优势,在处理高维数据方面较为流行。基于此,提出一种基于组策略的MRMR改进算法（MRMRE）,该算法不仅考虑单个特征属性的相关性与冗余性,同时针对特征组间的相互关系进行研究。算法以MRMR算法为框架,以CCA作为度量基准,选择SVMs作为基分类器,使其特征选择效果提升。在UCI机器学习数据库中图像与基因序列数据集上的大量实验表明：与MRMR算法相比,所提出的算法其特征选择结果具有更高的结果稳定性与分类精度。