静电纺丝制备取向纳米纤维的研究进展

文章综述了采用静电纺丝法制备取向纳米纤维的研究进展,介绍了通过改变静电纺丝的装置,制备有序排列的纳米纤维的几种方式。     

小波变换的傅里叶变换算法

介绍信号小波变换的概念，讨论它与傅里叶变换的关系，并实现用傅里叶变换算法计算信号的连续小波变换，给出了算例。     

静电纺取向纳米纤维的制备及在组织工程中的应用进展

为拓展静电纺取向纳米纤维的应用领域,进一步提高收集静电纺取向纳米纤维的取向度和效率,综述了利用改变接收装置来制备取向纳米纤维的多种方法,根据接收装置的不同,主要分为旋转式收集法、水浴收集法和平行板收集法.简单分析了各种方法的基本原理和优缺点,阐述了取向纳米纤维在生物组织工程领域的重要应用,通过研究人员一系列的研究成果证...     

傅里叶变换在绝缘子污秽图像处理中的应用研究

通过对傅里叶变换在图像处理应用中的原理进行分析,并利用该原理对数字图像进行频谱分析,通过在时空域和频率域来回切换图像,对图像的信息特征进行提取和分析,把绝缘子图像与其污秽信息分离,从图像中提取有效信息,达到绝缘子污秽信息的识别目的。     

傅里叶变换近红外光谱分析技术在茶叶中的应用

利用傅里叶变换近红外光谱分析技术,通过建立茶叶中各主要组分和近红外光谱图对应模型,可快速、准确地测定茶叶的主要成分含量,判定茶叶品质优劣.     

傅里叶变换在数字图像处理中的教学方法探讨

信号与系统中离散信号的傅里叶变换完成了离散信号的空间域和频率域之间的转换,本文将数字图像处理中的频率域图像低通滤波过程实施到信号与系统的教学中,加强了学生对离散傅里叶变换的理解。     

静电纺纤网纤维取向分布的测量程序设计

在对静电纺丝网的扫描电镜图片进行滤波等预处理的基础上,使用LabVIEW软件编程,通过处理转动不同角度后的图片来对纤维的取向分布进行测量。所编测量程序可独立运行于个人计算机,具有方便、有效、直观等特点。     

用傅里叶变换计算单缝衍射的光强分布

现代光学和通讯理论由于引入了傅里叶变换的方法，使计算光学系统和通讯系统的物像的对应关系简洁、清晰。该文用傅氏变换计算长为２ａ、照度为Ａ的均匀缝光源在观察面上的光强分布为Ｉ（ｘ）＝│Ｅ（ｘ）│＾２＝ＡＡ＾２ａ＾２（ｓｉｎ２πｆａ／２πｆａ）此方法也可运用于矩形孔、圆孔等。     

静电纺取向纳米纤维制备技术的研究进展

传统的非取向静电纺纳米纤维微观结构杂乱,力学性能较差,其应用范围相对较小;而取向纳米纤维具有各向异性的结构和润湿性能,其力学性能、尺寸稳定性和导电率更高,因此,其应用前景更加广泛。系统介绍了近年来国内外制备取向纳米纤维的方法与技术,包括旋转辊轴收集装置、平行排列的电极装置、辅助电极装置和其他一些方法,并深入分析了各种方法的优缺点。分析结果表明,引入辅助电极控制射流的运动,再利用其他装置收集纳米纤维,是目前静电纺取向纳米纤维制备技术发展的方向。     

基于离散傅里叶变换的数字水印算法

提出了一种基于二重加密和离散傅里叶变换的数字水印算法:为保证安全性,水印在嵌入载体图像前先进行基于Logical映射的混沌置乱,又通过Arnold变换进一步实行加密;嵌入时,根据水印位的值对DFT系数的相位进行设定.实验结果证明,该算法具有较好的不可见性和鲁棒性.     

Weave pattern recognition by measuring fiber orientation with Fourier transform

An effective method based on measuring the fiber orientation of yarn floats with two-dimensional Fourier transform (2-D FFT) is proposed to recognize the weave pattern of yarn-dyed fabric in the high-resolution image. The recognition process consists of four main steps: 1. High-resolution image reduction, 2.Fabric image skew correction, 3.Yarn floats localization, 4. Yarn floats classification. Firstly, the high-resolution image is reduced by the nearest interpolation algorithm. Secondly, the skew of the fabric image is corrected based on Hough transform. Thirdly, the yarn floats in the fabric image is localized by the yarns segmentation method based on the mathematical statistics of sub-images. Fourthly, the high-resolution image is corrected and its yarns are segmented successively according to the inspection information of the reduced image. The fiber orientations are detected by 2-D FFT, and the yarn floats are classified by k-means clustering algorithm. Experimental results and discussions demonstrate that, by measuring the fiber orientation of yarn floats, the proposed method is effective to recognize the yarn floats and the weave pattern for yarn-dyed, solid color, and gray fabrics.     

窗口Fourier变换与小波变换

分析了从窗口Fourer变换到小波变换的有关问题.     

功能性纤维的静电纳米纺丝技术(二)

<正>(上接本刊2012年第1期第5页)3静电纺纤维的应用在纳米技术领域中,材料尺寸的减小会导致新性能的产生。如:金属粒子催化,当粒子尺寸减小到几纳米时,电子性能会发生变化;磁性材料,当磁性粒子尺寸为纳米级时,会看到超顺磁现象。静电纺纤维膜凭借其孔径小、比表面大等优良性能,如今已在生物和医学、传感器、过滤及个体防护等多个领域得到广泛的应用。     

近红外光谱应用于高粱中总淀粉、直链淀粉与支链淀粉的定量分析

酱香型白酒以高粱为主要原料发酵而成,高粱中的淀粉,尤其是支链淀粉的含量对于酱香型白酒的产品质量起着至关重要的作用,因此针对其总淀粉、直链淀粉与支链淀粉的检测手段研究也应受到人们高度的重视。傅里叶变换近红外光谱法因其准确性高、稳定性好以及快速无损检测等特点,在建立总淀粉、直链淀粉和支链淀粉同时定量分析模型方面得到了较为成功的应用。结果表明,总淀粉、直链淀粉以及支链淀粉的定量分析模型相关系数分别达到0.954 9、0.923 6和0.940 1,交互验证均方根误差分别为1.027 1、0.088 5和1.264 6。可见,基于近红外光谱技术的定量分析方法可适用于高粱中总淀粉、直链淀粉与支链淀粉的同时定量分析。     

基于傅里叶变换红外光谱法的红花药材质量分析

目的 建立傅里叶变换红外光谱法分析评价红花药材质量的分析方法。方法 采用傅立叶变换红外光谱法(Fourier transform infrared spectrometry, FTIR)对采集自新疆不同产地的20批红花药材进行测量, 建立指纹图谱; 运用聚类分析与主成分分析等统计学及化学模式识别技术, 对不同来源的红花药材进行红外光谱数据比较分析。结果 筛选出12个波数段, 形成了红花药材FTIR红外光谱指纹图谱共有模式; 精密度、稳定性和重复性实验结果表明, 共有峰波数的相对标准偏差(relative standard deviation, RSD)分别为0.00%~0.1%、0.00%~4.56%、0.32%~7.5%, 符合指纹图谱的要求; 20批样品相似度均大于95%, 大致可以分为3大类, 区域间差异较为明显。结论 本研究建立的方法简单、易行、快速, 不污染、样品耗量低, 为不同来源红花药材的鉴定、内在质量评价与质量控制提供了依据、奠定了基础。     

Application of Fourier transform infrared spectroscopy to legume seed flour analysis

The secondary structure of legume (Phaseolus vulgaris L. and Lens culinaris L.) proteins was investigated by studying the amide I infrared absorption band in whole seed flours, before and after dry heating and autoclaving thermal treatments. The analysis procedure, set up on 7S and different model proteins, shows that the content of β-sheet structures in lentil is higher than in common bean (47% vs. 32%). The dry heating does not appreciably affect secondary structures in lentil, while it causes a reduction of β-sheets (to 13%), an increase of aggregates, and the appearance of random coil structures in common bean. The autoclaving treatment produces high amounts of aggregates in both legumes. However, in lentil, random coil structures are lower than in common bean and some β-sheet structures are still detectable. These results indicate that multimeric heat-induced complexes of legume proteins have a high stability because of the high content in β-sheet structures, in particular in lentil, which may adversely affect protein utilization.     

菜籽油品质多样性与红外光谱特征的研究

为对菜籽油的品质监控和快速检测提供科学依据,测定49种菜籽油样品的质量指标和脂肪酸组成,分析其品质多样性,并考察其品质特征与傅里叶变换衰减全反射红外光谱的相关性。结果表明：49种菜籽油样品过氧化值和酸值的变异系数分别达63.20%和152.90%,所含主要脂肪酸中棕榈酸、油酸和亚油酸含量的变异系数均未超过21.38%,而花生一烯酸含量的变异系数高达127.09%;通过分类分析发现,油样的过氧化值、亚油酸含量和不饱和脂肪酸含量与其产地、加工工艺、品种、上架期和质量等级有关;采用化学计量学方法构建油样红外光谱的共有模式,以相关系数法分析各光谱的相似度介于0.68～0.98之间,并筛选出10个共有峰。以共有峰的峰高均值为自变量,构建脂肪酸(棕榈酸、油酸、亚油酸、花生一烯酸、不饱和脂肪酸和饱和脂肪酸)含量的多元线性回归模型均达显著水平(p＜0.05),但过氧化值和酸值的回归模型不显著(p＞0.05)。通过对30种热处理油样的验证实验发现,回归模型能准确预测其不饱和脂肪酸含量,预测值的相对误差介于-11.15%～10.95%之间。综上,红外光谱法可初步用于市售菜籽油的脂肪酸组成的快速分析。     

Selection for milk coagulation properties predicted by Fourier transform infrared spectroscopy in the Italian Holstein-Friesian breed

Milk coagulation is based on a series of physicochemical changes at the casein micelle level, resulting in formation of a gel. Milk coagulation properties (MCP) are relevant for cheese quality and yield, important factors for the dairy industry. They are also evaluated in herd bulk milk to reward or penalize producers of Protected Designation of Origin cheeses. The economic importance of improving MCP justifies the need to account for this trait in the selection process. A pilot study was carried out to determine the feasibility of including MCP in the selection schemes of the Italian Holstein. The MCP were predicted in 1,055 individual milk samples collected in 16 herds (66 ± 24 cows per herd) located in Brescia province (northeastern Italy) by means of Fourier transform infrared (FTIR) spectroscopy. The coefficient of determination of prediction models indicated moderate predictions for milk rennet coagulation time (RCT = 0.65) and curd firmness (a₃₀ = 0.68), and poor predictions for curd-firming time (k₂₀ = 0.49), whereas the range error ratio (8.9, 6.9, and 9.5 for RCT, k₂₀, and a₃₀, respectively) indicated good practical utility of the predictive models for all parameters. Milk proteins were genotyped and casein haplotypes (α_S1-, β-, α_S2-, and κ-casein) were reconstructed. Data from 51 half-sib families (19.9 ± 16.4 daughters per sire) were analyzed by an animal model to estimate (1) the genetic parameters of predicted RCT, k₂₀, and a₃₀; (2) the breeding values for these predicted clotting variables; and (3) the effect of milk protein genotypes and casein haplotypes on predicted MCP (pMCP). This is the first study to estimate both genetic parameters and breeding values of pMCP, together with the effects of milk protein genotypes and casein haplotypes, that also considered k₂₀, probably the most important parameter for the dairy industry (because it indicates the time for the beginning of curd-cutting). Heritability of predicted RCT (0.26) and k₂₀ (0.31) were close to the average heritability described in literature, whereas the heritability of a₃₀ was higher (0.52 vs. 0.27). The effects of milk proteins were statistically significant and similar to those obtained on measured MCP. In particular, haplotypes including uncommon variants showed positive (B-I-A-B) or negative (B-A¹-A-E) effects. Based on these findings, FTIR spectroscopy-pMCP is proposed as a potential selection criterion for the Italian Holstein.