Chinese family name distributions in multiple scales

The distribution of Chinese family names is investigated based on data of the fifth national census of China in 2000, including 7329 Chinese family names and 1.28 billion people. The cumulative distribution function (CDF) of family name in multiple scales is presented and the correlation between distribution and scale is discussed. The fitting results show that CDFs at the scales of country, province, city and county all follow stretched exponential truncated power law, while the fitting parameters vary greatly. A characteristic index is proposed to measure the extent the distribution is stretched-exponential-like. The index increases as the scale goes down, indicating that the distribution at lower scale is more stretched-exponential-like, and the distribution at higher scale is more power-law-like. Such correlation between distribution and scale is verified by investigating how the distribution changes as the scale is expanded county by county. Furthermore, the correlation is qualitatively explained by artificially constructing multiple scales with a partition process.     

Rapid Discrimination and Prediction of Ginsengs from Three Origins Based on UHPLC-Q-TOF-MS Combined with SVM

Ginseng, which contains abundant ginsenosides, grows mainly in the Jilin, Liaoning, and Heilongjiang in China. It has been reported that the quality and traits of ginsengs from different origins were greatly different. To date, the accurate prediction of the origins of ginseng samples is still a challenge. Here, we integrated ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) with a support vector machine (SVM) for rapid discrimination and prediction of ginseng from the three main regions where it is cultivated in China. Firstly, we develop a stable and reliable UHPLC-Q-TOF-MS method to obtain robust information for 31 batches of ginseng samples after reasonable optimization. Subsequently, a rapid pre-processing method was established for the rapid screening and identification of 69 characteristic ginsenosides in 31 batches ginseng samples from three different origins. The SVM model successfully distinguished ginseng origin, and the accuracy of SVM model was improved from 83% to 100% by optimizing the normalization method. Six crucial quality markers for different origins of ginseng were screened using a permutation importance algorithm in the SVM model. In addition, in order to validate the method, eight batches of test samples were used to predict the regions of cultivation of ginseng using the SVM model based on the six selected quality markers. As a result, the proposed strategy was suitable for the discrimination and prediction of the origin of ginseng samples.     

基于超高效液相色谱-紫外检测定量指纹图谱结合化学模式识别的复方金钱草颗粒质量评价

复方金钱草颗粒具有利尿、抑制泌尿系结石形成、抗炎、抗氧化作用,且具有较大的市场需求。因此,采用超高效液相色谱-紫外检测(UPLC-UV)法建立定量指纹图谱,并结合化学模式识别技术对不同年份的复方金钱草颗粒进行质量评价,可为其质量控制提供依据。采用聚类分析(HCA)和主成分分析(PCA)等化学模式识别技术对35批复方金钱草颗粒样品的指纹图谱数据进行分析,筛选出质量差异标志物芒果苷和异芒果苷,并对二者进行含量测定。在复方金钱草颗粒指纹图谱中共指认出12个共有峰,且35批样品的相似度均在0.952以上。在HCA中,将35批样品分为了两类,其中2018年和2019年的样品为一类,2020年和2021年的样品为一类。此外,PCA结果显示了与聚类分析相同的聚类趋势。在此基础上,进一步通过正交偏最小二乘法分析 (OPLS-DA)筛选出了导致2018年、2019年与2020年、2021年的样品产生差异的差异标志物芒果苷和异芒果苷。以两个差异标志物芒果苷和异芒果苷为指标进行含量测定,结果显示色谱峰的分离度良好,线性关系良好,平均加标回收率分别为101.7%~105.6%和103.4%~105.5%,且相对标准偏差(RSD)均低于1.43%。在35批样品中,2020年、2021年的样品与2018年、2019年的样品相比,芒果苷与异芒果苷含量更高且波动范围更小。该研究建立了准确、可靠的复方金钱草颗粒质控方法,实现了对不同年份的复方金钱草颗粒样品合理、有效的质量评价,可为建立更系统、更全面的质量控制标准提供借鉴与参考。     

JFNK方法在S N输运计算中的应用

JFNK(Jacobian-free Newton-Krylov)方法是一种求解非线性方程的高效迭代算法.传统输运计算中的负通量修正与k-特征值迭代使得原本线性的输运计算转变为非线性问题数值求解.为提高非线性输运问题的计算效率,将这两类非线性问题离散成残差形式的非线性方程组,并采用JFNK方法对其进行迭代求解.分析不同...     

Preparation of Small‐Diameter Tissue‐Engineered Vascular Grafts Electrospun from Heparin End‐Capped PCL and Evaluation in a Rabbit Carotid Artery Replacement Model

Aiming to construct small diameter (ID <6 mm) off‐the‐shelf tissue‐engineered vascular grafts, the end‐group heparinizd poly(ε‐caprolactone) (PCL) is synthesized by a three‐step process and then electrospun into an inner layer of double‐layer vascular scaffolds (DLVSs) showing a hierarchical double distribution of nano‐ and microfibers. Afterward, PCL without the end‐group heparinization is electrospun into an outer layer. A steady release of grafted heparin and the existence of a glycocalyx structure give the grafts anticoagulation activity and the conjugation of heparin also improves hydrophilicity and accelerates degradation of the scaffolds. The DLVSs are evaluated in six rabbits via a carotid artery interpositional model for a period of three months. All the grafts are patent until explantation, and meanwhile smooth endothelialization and fine revascularization are observed in the grafts. The composition of the outer layer of scaffolds exhibits a significant effect on the aneurysm dilation after implantation. Only one aneurysm dilation is detected at two months and no calcification is formed in the follow‐up term. How to prevent aneurysms remains a challenging topic.     

求解α本征值的k-α迭代方法误差估计

分析求解α本征值的k-α迭代方法,指出迭代法中参数的选择影响使用标准差的平均值估计出来的α误差.如果参数选取不当,实际估计误差可能和真实估计误差相差很大.MCNP4C程序中使用的参数给出的误差估计通常和真实估计误差有一定的偏差.本文给出一个新的参数选择办法,能够让实际估计误差几乎等于真实估计误差,并用数值实验进行验证.     

Adapting the Hill estimator to distributed inference: dealing with the bias

Extremes - The distributed Hill estimator is a divide-and-conquer algorithm for estimating the extreme value index when data are stored in multiple machines. In applications, estimates based on the...     

基于TMS320DM642的矿用数字化扩音电话系统设计

通过分析目前的矿用扩音电话系统的现状,为解决矿井下语音通信中高噪声强干扰问题,提出一种基于数字处理器TMS320DM642和嵌入式TCP/IP协议的矿用数字化扩音电话系统的设计方案;采用音频编解码芯片TLV320AIC23B实现语音处理以达到矿井下语音质量的要求,并利用物理层芯片Intel LXT971与TMS320DM642的无缝连接,实现基于嵌入式TCP/IP协议栈的数字语音传输;系统软件采用RF5框架开发,基于DSP/BIOS实现语音采集,语音处理,网络传输等任务;通过对各关键模块测试与分析,系统运行稳定可靠,实现矿用数字化扩音电话的高质量,远距离和稳定的语音通信。     

A semi-supervised learning approach for detection of phishing webpages

This paper proposes a new phishing webpage detection approach based on a kind of semi-supervised learning method-transductive support vector machine (TSVM). Firstly the features of web image are extracted for complementing the disadvantage of phishing detection only based on document object model (DOM); they include gray histogram, color histogram, and spatial relationship between subgraphs. Then the features of sensitive information are examined by using page analysis based on DOM objects. In contrast to the drawback of support vector machine (SVM) algorithm which simply trains classifier by learning little and poor representative labeled samples, this method introduces the TSVM to train classifier that it takes into account the distribution information implicitly embodied in the large quantity of the unlabeled samples, and have better performance than SVM. The experimental results show that the proposed method not only achieves better classification accuracy, but also has strong applicability as the independent method of phishing detection.