Comparisons of Several Similarity Coefficients for Cluster Analysis of Hot Pepper Germplasm Resources

An appropriate genetic similarity coefficient is particularly important for accurately estimating the genetic similarity and phylogenetic relationship between individuals and evaluating the genetic diversity of populations. In this study, five genetic similarity coefficients were compared for analysis of phylogenetic relationship among 31 hot pepper inbred lines based on SRAP. The applicability of different genetic similarity coefficient was investigated by means of SRAP data of hot pepper inbred lines. According to the experimental results, the variation ranges of Nei ＆ Li, Jaceard, Sorensen, Simple matching and Yule coefficients were 0. 598 - 0. 973, 0. 427 - 0. 947, 0. 598 - 0. 973, 0.427 - 0. 947 and 0. 133 - 0. 997, respectively. Results of cluster analysis based on different similarity coefficients varied greatly. To be specific, clustering results based on Nei ＆ Li, Jaccard and Sorensen coefficients were consistent; clustering with Simple matching and Yule coef ficients led to consistent classification of category in different order and slightly different classification of subcategory. Comprehensively comparing the results of cluster analysis and the dendrograms of hot pepper inbred lines, Yule coefficient is suitable for SRAP analysis of hot pepper.

INTS-MFS:A novel method to predict microRNA-disease associations by integrating network topology similarity and microRNA function similarity

Identifying associations between microRNAs(miRNAs)and diseases is very important to understand the occurrence and development of human diseases.However,these existing methods suffer from the following limitation:first,some disease-related miRNAs are obtained from the miRNA functional similarity networks consisting of heterogeneous data sources,i.e.,disease similarity,protein interaction network,gene expression.Second,little approaches infer disease-related miRNAs depending on the network topological features without the functional similarity of miRNAs.In this paper,we develop a novel model of Integrating Network Topology Similarity and MicroRNA Function Similarity(INTS-MFS).The integrated miRNA similarities are calculated based on miRNA functional similarity and network topological characteristics.INTS-MFS obtained AUC of 0.872 based on five-fold cross-validation and was applied to three common human diseases in case studies.As a results,30 out of top 30 predicted Prostatic Neoplasm-related miRNAs were included in the two databases of dbDEMC and PhenomiR2.0.29 out of top 30 predicted Lung Neoplasm-related miRNAs and Breast Neoplasm-related miRNAs were included in dbDEMC,PhenomiR2.0 and experimental reports.Moreover,INTS-MFS found unknown association with hsa-mir-371a in breast cancer and lung cancer,which have not been reported.It provides biologists new clues for diagnosing breast and lung cancer.

SIMILARITY REDUCTIONS FOR 2+1-DIMENSIONAL VARIABLE COEFFICIENT GENERALIZED KADOMTSEV-PETVIASHVILI EQUATION

With the aid of MATHEMATICA, the direct reduction method,vas extended and applied in 2 + 1-dimensional variable coefficient generalized Kadomtsev-Petviashvili equation( VCGRPE). As a result, several kinds of similarity reductions for VCGKPE are obtained which contain Painleve I, Painleve II and Painleve ni reductions.

Improvement of Similarity Measure： Pearson Product-Moment Correlation Coefficient

Aim To study the reason of the insensitiveness of Pearson preduct-moment correlation coefficient as a similarity measure and the method to improve its sensitivity. Methods Experimental and simulated data sets were used. Results The distribution range of the data sets influences the sensitivity of Pearson product-moment correlation coefficient. Weighted Pearson product-moment correlation coefficient is more sensitive when the range of the data set is large. Conclusion Weighted Pearson product-moment correlation coefficient is necessary when the range of the data set is large.

Feasibility of similarity coefficient map for improving morphological evaluation of T_2* weighted MRI for renal cancer

The purpose of this paper is to investigate the feasibility of using a similarity coefficient map（SCM） in improving the morphological evaluation of T2＊ weighted（T2＊W） magnatic resonance imaging（MRI） for renal cancer.Simulation studies and in vivo 12-echo T2＊W experiments for renal cancers were performed for this purpose.The results of the first simulation study suggest that an SCM can reveal small structures which are hard to distinguish from the background tissue in T2＊W images and the corresponding T2＊ map.The capability of improving the morphological evaluation is likely due to the improvement in the signal-to-noise ratio（SNR） and the carrier-to-noise ratio（CNR） by using the SCM technique.Compared with T2＊ W images,an SCM can improve the SNR by a factor ranging from 1.87 to 2.47.Compared with T2＊ maps,an SCM can improve the SNR by a factor ranging from 3.85 to 33.31.Compared with T2＊W images,an SCM can improve the CNR by a factor ranging from 2.09 to 2.43.Compared with T2＊ maps,an SCM can improve the CNR by a factor ranging from 1.94 to 8.14.For a given noise level,the improvements of the SNR and the CNR depend mainly on the original SNRs and CNRs in T2＊W images,respectively.In vivo experiments confirmed the results of the first simulation study.The results of the second simulation study suggest that more echoes are used to generate the SCM,and higher SNRs and CNRs can be achieved in SCMs.In conclusion,an SCM can provide improved morphological evaluation of T2＊W MR images for renal cancer by unveiling fine structures which are ambiguous or invisible in the corresponding T2＊W MR images and T2＊ maps.Furthermore,in practical applications,for a fixed total sampling time,one should increase the number of echoes as much as possible to achieve SCMs with better SNRs and CNRs.

Linear-fitting-based similarity coefficient map for tissue dissimilarity analysis in T2^＊-w magnetic resonance imaging

Similarity coefficient mapping（SCM） aims to improve the morphological evaluation of T＊2weighted magnetic resonance imaging（T＊2-w MRI）. However, how to interpret the generated SCM map is still pending. Moreover, is it probable to extract tissue dissimilarity messages based on the theory behind SCM？ The primary purpose of this paper is to address these two questions. First, the theory of SCM was interpreted from the perspective of linear fitting. Then, a term was embedded for tissue dissimilarity information. Finally, our method was validated with sixteen human brain image series from multiecho T＊2-w MRI. Generated maps were investigated from signal-to-noise ratio（SNR） and perceived visual quality, and then interpreted from intra- and inter-tissue intensity. Experimental results show that both perceptibility of anatomical structures and tissue contrast are improved. More importantly, tissue similarity or dissimilarity can be quantified and cross-validated from pixel intensity analysis. This method benefits image enhancement, tissue classification, malformation detection and morphological evaluation.

Similarity identification method on formational interfaces and application in general granite

An instrumented drilling system can be applied for the acquisition of drilling process parameters. The system can provide continuous and huge data for geotechnical engineering. However, due to the complexity of ground strata, the variation in the drilling parameters with stratigraphical characteristics is great and the correlation between likely comparable parameters is not high, which limits the use of conventional correlation approaches in this field. How to use the data for engineering and how to get a reasonable interpretation for the relationships among the drilling parameters, as well as between a drilling parameter and formational characteristics, become a technical choke point for the development and application of the instrumented drilling system. Based on similarity criteria, the extraction of sample data and characteristics, the pretreatment of data and feature matching algorithms have been analyzed and an approach of slope coefficient searching identification has been established. A case study was carried out for the similarity between the rotational speed of the drill bit, flushing pressure, and effective thrust force graphics in general weathered granite. The result shows that the similarity coefficients between the rotational speed of the drill bit, flushing pressure, and effective thrust force are 0.72 and 0.83, respectively. Although there are differences between the distances of the graphics, the curves of both rotational speed and flushing pressure agree with the effective thrust curve in shape, which provides a possible method for the identification of various formations by use of the similarity between feature drilling parameters.

Fuzzy-Weighted Similarity Measures for Memory-Based Collaborative Recommender Systems

Memory-based collaborative recommender system (CRS) computes the similarity between users based on their declared ratings. However, not all ratings are of the same importance to the user. The set of ratings each user weights highly differs from user to user according to his mood and taste. This is usually reflected in the user’s rating scale. Accordingly, many efforts have been done to introduce weights to the similarity measures of CRSs. This paper proposes fuzzy weightings for the most common similarity measures for memory-based CRSs. Fuzzy weighting can be considered as a learning mechanism for capturing the preferences of users for ratings. Comparing with genetic algorithm learning, fuzzy weighting is fast, effective and does not require any more space. Moreover, fuzzy weightings based on the rating deviations from the user’s mean of ratings take into account the different rating scales of different users. The experimental results show that fuzzy weightings obviously improve the CRSs performance to a good extent.

New computing method of weighted coefficients for tracking a maneuvering target using PDAF in the presence of clutter

To avoid or reduce the influence of unpredictable motion mode on data association, a new computing method of weighted coefficients of measurements for PDAF is presented in which it is assumed that the current turn rate of a maneuvering target changes within a limited range and its turn may be in arbitrary direction during data association. Thus, the predicted center for computing the weighted coefficients is a curved surface in 3-D space, which differs from the predicted center for setting up a validation gate, namely, a point in 3-D space. The distance between a measurement and the curved surface is used to compute its weighted coefficient. To reduce the computational complexity of weighted coefficients, the formulas for computing the maneuvering direction angle and turn rate corresponding to a measurement are presented. Simulation results show the proposed method reduces the percentage of lost tracks and improves the state estimation accuracy in tracking a maneuvering target using PDAF in the presence of clutter.

Similarity Analysis of Beetle Communities in Jiuzhaigou,Xiaozhaizigou, Caopo, Ma'anshan and Baihe Nature Reserves of Sichuan Province,China

In this study, beetle communities in Jiuzhaigou, Xiaozhaizigou, Caopo, Ma＇anshan and Baihe nature reserves of Sichuan Province were compared and analyzed. F index, G index and G-F index of beetle communities in five nature reserves were analyzed to calculate the similarity coefficient C between these five na- ture reserves. According to the results, beetle communities exhibited high dissimilarity between Jiuzhaigou and Xiaozhaizigou, Caopo and Jiuzhaigou, Caopo and Xiaozhaizigou, Ma＇anshan and Xiaozhaizigou, Ma＇anshan and Jiuzhaigou, Baihe and Xiaozhaizigou, Baihe and Caopo, Baihe and Ma＇anshan; beetle communities exhibited moderate dissimilarity between Ma＇anshan and Caopo, Baihe and Jiuzhaigou.

Personalized Recommendation Algorithm Based on Rating System and User Interest Association Network

In most available recommendation algorithms, especially for rating systems, almost all the high rating information is utilized on the recommender system without using any low-rating information, which may include more user information and lead to the accuracy of recommender system being reduced. The paper proposes a algorithm of personalized recommendation (UNP algorithm) for rating system to fully explore the similarity of interests among users in utilizing all the information of rating data. In UNP algorithm, the similarity information of users is used to construct a user interest association network, and a recommendation list is established for the target user with combining the user interest association network information and the idea of collaborative filtering. Finally, the UNP algorithm is compared with several typical recommendation algorithms (CF algorithm, NBI algorithm and GRM algorithm), and the experimental results on Movielens and Netflix datasets show that the UNP algorithm has higher recommendation accuracy.

A Quantum Tanimoto Coefficient Fidelity for Entanglement Measurement

Fidelity plays an important role in quantum information processing,which provides a basic scale for comparing two quantum states.At present,one of the most commonly used fidelities is Uhlmann-Jozsa(U-J)fidelity.However,U-J fidelity needs to calculate the square root of the matrix,which is not trivial in the case of large or infinite density matrices.Moreover,U-J fidelity is a measure of overlap,which has limitations in some cases and cannot reflect the similarity between quantum states well.Therefore,a novel quantum fidelity measure called quantum Tanimoto coefficient(QTC)fidelity is proposed in this paper.Unlike other existing fidelities,QTC fidelity not only considers the overlap between quantum states,but also takes into account the separation between quantum states for the first time,which leads to a better performance of measure.Specifically,we discuss the properties of the proposed QTC fidelity.QTC fidelity is compared with some existing fidelities through specific examples,which reflects the effectiveness and advantages of QTC fidelity.In addition,based on the QTC fidelity,three discrimination coefficients d_(1)^(QTC),d_(2)^(QTC),and d_^(3)^(QTC)are defined to measure the difference between quantum states.It is proved that the discrimination coefficient d_(3)^(QTC)is a true metric.Finally,we apply the proposed QTC fidelity-based discrimination coefficients to measure the entanglement of quantum states to show their practicability.

井地过渡带对聚合物驱油剂性能影响研究

利用井地过渡带剪切模拟实验装置,以疏水缔合聚合物AP-P4为研究对象,研究不同吸水强度条件下,剪切后聚合物溶液的表观黏度、流变性、阻力和残余阻力系数、微观结构以及水动力学半径的变化情况。结果表明,经井地过渡带剪切后,随着吸水强度的增大,聚合物AP-P4溶液的黏度损失率高达61.4%,建立阻力系数和残余阻力系数的能力降低40.0%以上,但其建立残余阻力系数能力的降低幅度要比建立阻力系数能力的降低幅度小。聚合物溶液的储能模量和损耗模量降低,微观结构被破坏的越严重,水动力学半径越小。

考虑关联波段特性的光谱相似图像分类方法

光谱相似图像分类性能过差会增加光谱信息冗余度,降低地物勘探与军事防御等多种领域的光谱探测效率。为了多元素匀质区分光谱信息与光谱曲线,提出考虑关联波段特性的光谱相似图像分类方法。该方法首先利用光谱匹配消除光谱相似图像白色光源过曝现象。然后提取优化图像的关联波段,并将其作为聚类特征输入支持向量机中。最后根据支持向量机的输出结果,实现光谱相似图像分类。实验结果表明,所提方法分类结果清晰度较高,分类误差或像素块填色错误小,混淆矩阵中同行同列矩形块的分类精度较高。

基于碳汇潜力的碳排放空间关联网络结构特征及影响因素——以长江中游城市群为例

考虑碳汇潜力的碳排放空间关联是促进城市群协同减排的重要基础,更是实现碳中和的有力抓手。以长江中游城市群为研究区,对传统引力模型进行修正,构建兼具碳汇潜力的碳排放空间关联网络,采用社会网络分析(SNA)和二次指派程序方法(QAP)探究长江中游城市群碳排放空间关联网络的时空特征与影响因素。结果表明:①研究期间长江中游城市群碳排放网络关联关系数、网络密度和网络关联度呈增长趋势,网络效率和网络等级度不断下降,且网络等级度在2010年后始终为0,表明碳排放空间关联网络日益稠密、网络通达性较强,存在多重叠加的溢出渠道,但等级结构并不森严。基于碳汇潜力的长江中游城市群碳排放空间关联网络从“双核化”向“多极化、多线程”网络形态发展,核心城市的扩散作用不断增强。此外,以抚州、宜昌、鹰潭、上饶和吉安等为代表的高碳生态承载力地区,在碳排放空间关联网络中的受益关联性大于溢出关联性。②2020年,长江中游城市群碳排放空间关联网络形成四大板块,相较于板块内部成员间的碳排放空间关联效应,板块间的碳排放空间关联效应更为明显,即板块间的“碳排放转移”效应较为普遍。净溢出板块主要分布在武汉都市圈、宜荆荆都市圈和长株潭城市群外围城市,处于网络核心圈层位置;净受益板块主要分布在环鄱阳湖城市群东部,“碳排放避难所”效应显著。经纪人板块集中在环鄱阳湖城市群西部,板块间表现出“净溢出板块→经纪人板块→净受益板块”的碳排放传递路径,呈现出明显的“梯度转移”特征。双向溢出板块主要位于长江中游城市群西部,对净溢出和净受益板块都存在碳排放的空间溢出。研究期内,净溢出板块的成员虽然有所变化但总数保持不变,经纪人板块的成员有所增加,而净受益和双向溢出板块的成员均减少,环鄱阳湖城市群的“碳排放避难所”效应有所弱化。③地理邻近关系能够促进城市间碳排放关联关系的建立,而城市间的经济集聚程度、土地利用强度和经济发展水平上的互补性,促使碳排放空间关联网络随着城市间分工与协作的加强而呈现出千里“碳缘”一线牵的特点。

不同级别肿瘤中心医师对鼻咽癌调强放疗靶区和危及器官勾画差异比较

目的:评估不同级别肿瘤中心医师对鼻咽癌调强放疗计划靶区和危及器官勾画的个体化差异,为多中心放疗临床试验的质量控制提供数据参考。方法:随机抽取12例不同TMN分期的鼻咽癌患者,3名同一市级肿瘤中心医师以手工方式勾画每例患者的靶区(GTVnx)和危及器官(OAR)。以国家区域级肿瘤中心放疗专家手工修改和确认的靶区(GTVnx)和OAR勾画结构作为标准勾画。采用绝对体积差异比(△V_diff)、体积最大/最小比(MMR)、离散系数(CV)和体积相似性指数(DSC)分别比较不同级别肿瘤中心(市级与国家区域级)医师之间和市级肿瘤中心3名医师之间的器官勾画差异,并进一步比较不同级别肿瘤中心医师对不同TMN分期的鼻咽癌放疗计划器官的勾画差异。结果:不同级别肿瘤中心(市级与国家区域级)医师之间勾画GTVnx体积差异明显,3名医生中的最大△V_diff、MMR和CV分别为97.23%±83.45%、2.19±0.75和0.31±0.14,平均DSC<0.7。同时,他们之间对于左右视神经、视交叉、脑垂体等小体积OAR勾画差异也较大,平均MMR>2.8,CV>0.37,DSC<0.51;但对于脑干、脊髓、左右眼球、左右下颌骨等大体积OAR的勾画差异相对较小,平均的△V_diff<42%,MMR<1.55,DSC>0.7。相比于不同级别肿瘤中心医师之间的勾画差异,市级肿瘤中心3名医生勾画差异有一定的减小。另外,不同级别肿瘤中心医师之间对不同分期的鼻咽癌靶区勾画也存在差异,相对早期患者(I或II期)的靶区勾画,他们之间在对晚期患者(III或IV期)靶区勾画的差异更小,平均△V_diff和DSC值分别为(98.31%±67.36%vs 69.38%±72.61%, P<0.05)和(0.55±0.08 vs 0.72±0.12, P<0.05)。结论:不同级别肿瘤中心医师勾画鼻咽癌放疗计划靶区和OAR存在差异,尤其对早期患者靶区(GTVnx)和小体积OAR的勾画。为确保多中心临床试验的准确性,建议对不同级别医师进行统一培训并审核其勾画结果,以减少差异对治疗结果的影响。

基于融合距离的极化SAR图像非局部均值滤波

在极化合成孔径雷达(synthetic aperture radar,SAR)图像降噪领域,常见的非局部均值滤波仅依靠像素间的统计距离进行相似性度量,忽略了像素点的空间信息。本文结合极化SAR数据统计特性和图像空间特征作为像素间的相似性度量,提出了一种利用融合距离来计算相邻窗口权重的方法——基于融合距离的非局部均值滤波器。融合距离的引入使得滤波器能够更全面的评估像素间的相似性,从而得到更合适的像素权重。此外,本方法还引进变异系数对邻域窗口的权重进行评估,通过该参数可以控制滤波的程度。在多幅极化SAR图像上的实验结果表明,所提出的滤波器能够在有效抑制斑点噪声的同时保留较为完整的图像边缘信息和极化散射特性。

基于余弦相似度和TSO-BP的短期光伏预测方法

对光伏出力的精准预测在配电网安全稳定运行中起着至关重要的作用。因此,提出了一种基于余弦相似度和TSO-BP(金枪鱼群优化-反向传播)神经网络的短期光伏预测方法。首先,利用余弦相似度算法筛选出与预测日具有强相似度的历史数据作为训练样本;然后,采用TSO算法寻找BP神经网络的最优初始权值与阈值,训练TSO-BP短期光伏预测模型;最后,利用TSO-BP模型分别预测平缓天气与波动天气下的光伏出力。仿真结果表明:在平稳和波动两种不同天气情况下,该方法相较于传统预测方法精度更高。

基于高阶信息的网络相似性比较方法

量化复杂网络之间的结构相似性是网络科学中一个基本且具有挑战性的问题,在医学、社会学等多个领域发挥了至关重要的作用.传统的网络比较方法通常基于简单的结构特征,例如节点度分布、最短路径长度等,这些方法可能无法充分捕捉网络的全局结构信息,导致得到的网络相似性不精准.本文提出了一种基于高阶信息的网络相似性比较方法,该方法同时考虑了网络的全局结构和局部结构.具体而言,通过构建网络节点的高阶聚类系数分布和节点间距离分布,并利用基于这两个分布的Jensen-Shannon散度来量化网络之间的相似性.实验结果表明,相较于其他基线方法,本文提出的方法不仅能高效地比较不同网络的相似性,且在对真实网络进行扰动的过程中也表现出鲁棒性.