浅谈表面处理新技术一无铬达克罗

介绍了达克罗技术的涂层结构，从环保的角度考虑详细阐述了无铬达克罗的开发与应用、防腐机理、性能特点、环境效益，并展望了无铬达克罗技术的发展前景。     

两步法合成2-氨基-5-硝基苯酚

以邻氨基苯酚和尿素为原料,将传统环合-硝化-水解三步法工艺改为环合硝化-水解两步法合成了2-氨基-5-硝基苯酚(ANP);研究了影响环合硝化反应和水解反应的因素;优化了反应条件。环合硝化反应的最优条件为:n(邻氨基苯酚)∶n(尿素)=1.00∶1.20、环合时间6h、硝酸用量40.2g、硫酸用量20g、硝化时间3h、硝化温度70℃,在此条件下中间产物6-硝基苯并噁唑酮的收率为90.2%;水解反应的最优条件为:体积分数95%的乙醇为溶剂、n(6-硝基苯并噁唑酮)∶n(氢氧化钠)=1.0∶3.3、水解温度80℃、水解时间15h,在此条件下ANP收率为81.2%。两步反应ANP的总收率为73.2%。对产品进行了元素分析和红外光谱表征,确认终产物为ANP。该方法成本低,ANP总收率高,溶剂可回收,三废量少。     

ASRNet: Adversarial Segmentation and Registration Networks for Multispectral Fundus Images

Multispectral imaging (MSI) technique is often used to capture images of the fundus by illuminating it with different wavelengths of light. However, these images are taken at different points in time such that eyeball movements can cause misalignment between consecutive images. The multispectral image sequence reveals important information in the form of retinal and choroidal blood vessel maps, which can help ophthalmologists to analyze the morphology of these blood vessels in detail. This in turn can lead to a high diagnostic accuracy of several diseases. In this paper, we propose a novel semi-supervised end-to-end deep learning framework called “Adversarial Segmentation and Registration Nets” (ASRNet) for the simultaneous estimation of the blood vessel segmentation and the registration of multispectral images via an adversarial learning process. ASRNet consists of two subnetworks: (i) A segmentation module S that fulfills the blood vessel segmentation task, and (ii) A registration module R that estimates the spatial correspondence of an image pair. Based on the segmention-driven registration network, we train the segmentation network using a semi-supervised adversarial learning strategy. Our experimental results show that the proposed ASRNet can achieve state-of-the-art accuracy in segmentation and registration tasks performed with real MSI datasets.     

游规矩于准绳之内 寄妙理于法度之外——宋以前古代界画的发展特点

界画是中国古代绘画十三科中的一种,作为传统绘画的重要组成部分,虽然在魏晋到明清漫长的发展历程中,一直受到文人画家的轻视和排斥,但仍在宋元时期达到了艺术创作的顶峰阶段,明清渐趋衰落,近代从事界画创作的画家更是凤毛麟角。完其原因除了界画绘制需要直尺界笔的辅助,一笔一划皆须合乎规矩准绳,限制了文人画家个人情感的自由抒发和宣泄外,还有就是界画常与工匠、匠气和庸俗联系在一起。本文试从界画达到顶峰的宋元前几个历史阶段中,界画所呈现出的艺术特最进行分析比较,以呈现界画早期的发展概况,顺便求教于大家。     

硅酸盐富锌（水性）防腐涂料的研究

通过分析比较，找出制备硅酸盐富锌涂料的理想配方。试验检测表明：该涂层具有良好的附着力，较强防腐性能等。是一种很有发展潜力的防腐蚀涂料。     

基于落锤激励的某新型减振扣件减振性能分析

采用落锤激励,对某新型减振扣件进行现场测试,从传递率、传递损失率、传递损失及Z振级等四个方面对其减振性能进行分析。结果表明,在4~200 Hz范围内,传递率基本都在2.5%以下;传递损失率基本都在97.5%以上;传递损失基本都在32 dB以上;道床垂向振动加速度经过计算后,其Z振级为86.15 dB;跟普通减振扣件相比,新型扣件的综合减振性能有了明显地提高。试验表明,落锤激励法操作方便,行之有效,是测试扣件减振性能的优良方法。     

基于WebGIS的渤海渔业服务系统设计与开发

面对日益恶化的海洋环境和不断减少的海洋资源,科学、规范地管理各种海洋资源对于渔业资源的可持续发展十分重要。结合地理信息系统利用渔业空间数据建立渔业分析模型,可为合理开发海洋渔业资源提供基本依据。介绍了在ArcGIS Server平台发布渔业空间数据和渔业分析模型服务,实现渤海渔业管理系统设计和开发的方法与过程,系统采用B/S架构基于Flex环境开发。通过要素服务和地理处理服务在客户端实现渔业数据的在线编辑及调用渔业分析模型,同时采用BlazeDS开源库和JavaScript语言,在Tomcat服务器的支持下实现服务器与客户端的数据通信,最终实现高效的渔业数据查询、可视化以及鱼群分布的分析和模拟。     

A projection-based decomposition for the scalability of evolvable hardware

Scalability is a main and urgent problem in evolvable hardware (EHW) field. For the design of large circuits, an EHW method with a decomposition strategy is able to successfully find a solution, but requires a large complexity and evolution time. This study aims to optimize the decomposition on large-scale circuits so that it provides a solution for the EHW method to scalability and improves the efficiency. This paper proposes a projection-based decomposition (PD), together with Cartesian genetic programming (CGP) as an EHW system namely PD-CGP, to design relatively large circuits. PD gradually decomposes a Boolean function by adaptively projecting it onto the property of variables, which makes the complexity and number of sub-logic blocks minimized. CGP employs an evolutionary strategy to search for the simple and compact solutions of these sub-blocks. The benchmark circuits from the MCNC library, \(n\)-parity circuits, and arithmetic circuits are used in the experiment to prove the ability of PD-CGP in solving scalability and efficiency. The results illustrate that PD-CGP is superior to 3SD-ES in evolving large circuits in terms of complexity reduction. PD-CGP also outperforms GDD+GA in evolving relatively large arithmetic circuits. Additionally, PD-CGP successfully evolves larger \(n\)-even-parity and arithmetic circuits, which have not done by other approaches.     

词性对中英文文本聚类的影响研究

不同词性特征在文本聚类中有不同的贡献度。该文对四组有代表性的中英文数据集,利用三种聚类算法验证了四种主要词性及其组合对中英文文本聚类的影响。实验结果表明,在中文和英文两种语言中,名词均是表征文本内容的最重要词性,动词、形容词和副词均对文本聚类结果有帮助,仅选择名词作为特征聚类的结果与保留所有词性聚类的结果相近,但可大大降低文本的维度;选用名词为文本特征不能实现最好的聚类效果;相对其他词性组合和单一词性,采用名词、动词、形容词和副词的组合特征往往可以实现更好的聚类效果。在词性所占的比例以及单一词性聚类的结果上,同一词性在中英文文本聚类中呈现出较大差异。相对于英文,不同词性特征及其组合在中文文本聚类中呈现的差异更为稳定。     

Leaf movement simulation

This paper presents a method for the animation of leaf movement.Leaves are classified into two classes:moveable and non-moveable.For moveable leaves,their movements consist of two parts:leafstalk rotation and leaf surface rotation.For each rotation,a movement model was constructed and the movement was computed based on each model,respectively.The final leaf movements were obtained by superposition of these two rotations.The method‘s principle is simple and easy to use.