摘要：
Watermelon is a crop susceptible to diseases. Rapid and effective detection of watermelon diseases is of great significance to ensure the yield of watermelon. Aiming at the interference of the environment and obstacles in the natural environment, resulting in low target detection accuracy and poor robustness, this paper takes watermelon leaves as the research object, considering anthracnose, leaf blight, leaf spot and normal leaves as examples. A disease recognition method based on deep learning is proposed. This paper has improved the pre-selected box setting formula of the SSD model and tested it in multiple SSD models. Experiments show that the average accuracy of the final SSD768 model is 92.4%, and the average accuracy of the IOU is 88.9%. It shows that this method can be used to detect watermelon diseases in natural environment.
期刊：
COMMUNICATIONS IN MATHEMATICAL SCIENCES,2020年18(7):2059-2074 ISSN：1539-6746
通讯作者：
Wang, Yong;Xu, Jiankai
作者机构：
[Tan, Zhong] Xiamen Univ, Sch Math Sci, Xiamen 361005, Fujian, Peoples R China.;[Wang, Yong] South China Normal Univ, South China Res Ctr Appl Math & Interdisciplinary, Guangzhou 510631, Guangdong, Peoples R China.;[Xu, Jiankai] Hunan Agr Univ, Coll Informat Sci & Technol, Changsha 410128, Hunan, Peoples R China.
通讯机构：
[Wang, Yong] S;[Xu, Jiankai] H;South China Normal Univ, South China Res Ctr Appl Math & Interdisciplinary, Guangzhou 510631, Guangdong, Peoples R China.;Hunan Agr Univ, Coll Informat Sci & Technol, Changsha 410128, Hunan, Peoples R China.
关键词：
Axis-symmetric kernel;Integral equation;Non-existence of radial solutions;Regularity lifting lemma
期刊：
Frontiers in Genetics,2020年10:488214 ISSN：1664-8021
通讯作者：
Chen, Yuan
作者机构：
[Zhang, Haojian; Jiang, Heling; Yuan, Zheming; Chen, Yuan; Wang, Qifei; Liang, Yuqing] Hunan Agr Univ, Hunan Engn & Technol Res Ctr Agr Big Data Anal &, Changsha, Peoples R China.;[Tan, Siqiao] Hunan Agr Univ, Sch Informat Sci & Technol, Changsha, Peoples R China.;[Luo, Feng] Clemson Univ, Sch Comp, Clemson, SC USA.
通讯机构：
[Chen, Yuan] H;Hunan Agr Univ, Hunan Engn & Technol Res Ctr Agr Big Data Anal &, Changsha, Peoples R China.
关键词：
RNA sequencing;Maximal information coefficient;Differential expressed gene;Gene selection;normalized differential correlation
摘要：
For precision medicine, there is a need to identify genes that accurately distinguish the physiological state or response to a particular therapy, but this can be challenging. Many methods of analyzing differential expression have been established and applied to this problem, such as t-test, edgeR, and DEseq2. A common feature of these methods is their focus on a linear relationship (differential expression) between gene expression and phenotype. However, they may overlook nonlinear relationships due to various factors, such as the degree of disease progression, sex, age, ethnicity, and environmental factors. Maximal information coefficient (MIC) was proposed to capture a wide range of associations of two variables in both linear and nonlinear relationships. However, with MIC it is difficult to highlight genes with nonlinear expression patterns as the genes giving the most strongly supported hits are linearly expressed, especially for noisy data. It is thus important to also efficiently identify nonlinearly expressed genes in order to unravel the molecular basis of disease and to reveal new therapeutic targets. We propose a novel nonlinearity measure called normalized differential correlation (NDC) to efficiently highlight nonlinearly expressed genes in transcriptome datasets. Validation using six real-world cancer datasets revealed that the NDC method could highlight nonlinearly expressed genes that could not be highlighted by t-test, MIC, edgeR, and DEseq2, although MIC could capture nonlinear correlations. The classification accuracy indicated that analysis of these genes could adequately distinguish cancer and paracarcinoma tissue samples. Furthermore, the results of biological interpretation of the identified genes suggested that some of them were involved in key functional pathways associated with cancer progression and metastasis. All of this evidence suggests that these nonlinearly expressed genes may play a central role in regulating cancer progression.
通讯机构：
[Xu, Jian] H;Huazhong Univ Sci & Technol, Sch Math & Stat, Wuhan 430074, Peoples R China.
摘要：
In the one-dimensional Diophantine approximation, by using the continued fractions, Khintchine's theorem and Jarnik's theorem are concerned with the growth of the large partial quotients, while the improvability of Dirichlet's theorem is concerned with the growth of the product of consecutive partial quotients. This paper aims to establish a complete characterization on the metric properties of the product of the partial quotients, including the Lebesgue measure-theoretic result and the Hausdorff dimensional result. More precisely, for anyx is an element of [0, 1), letx=[a(1),a(2), horizontal ellipsis ] beits continued fraction expansion. The size of the following set, in the sense of Lebesgue measure and Hausdorff dimension,E-m(phi):= {x is an element of [0, 1):a(n)(x) MIDLINE HORIZONTAL ELLIPSISa(n+m-1)(x) >=phi(n) for infinitely manyn is an element of N}, are given completely, wherem >= 1 is an integer and phi: N -> Double-struck capital R(+)is a positive function.
作者机构：
[Cao Xiao-lan; Deng Meng-jie] Hunan Agr Univ, Coll Informat Sci & Technol, Changsha 410128, Hunan, Peoples R China.;[Cao Xiao-lan; Cui Guo-xian] Hunan Agr Univ, Ramie Res Inst, Changsha 410128, Hunan, Peoples R China.
通讯机构：
[Cui Guo-xian] H;Hunan Agr Univ, Ramie Res Inst, Changsha 410128, Hunan, Peoples R China.
关键词：
苎麻;高光谱;主成分分析;判别分析
摘要：
苎麻(Boehmeiria nivea L)是我国的特产,作为一种传统的纤维作物,一直有着较高的经济地位。开发一种基于高光谱的、新型高效的苎麻品种识别方法,有利于苎麻栽种、种质资源开发利用,为实现苎麻高产优质及麻田精准管理提供关键技术支撑,对提高苎麻产量和品质有重要意义。为了将高光谱技术应用于苎麻品种识别,采集了9个不同基因型苎麻品种,利用地物光谱仪测定苎麻叶片高光谱反射率,共1 458个叶片高光谱数据,利用主成分分析(PCA)对高光谱数据进行降维,探讨PCA最佳主因子个数的确定方法,比较不同主因子个数与不同判别分析(DA)方法———即线性判别分析(LDA)、二次判别分析(QDA)和马氏距离判别分析(MD-DA)组合,在建立基于叶片高光谱的苎麻品种识别模型中效果。对全波段的数据样本进行主成分分析之后,以2~20个主成分作为特征变量,分别建立LDA,QDA和MD-DA三种品种判别模型进行预测,以预测集正确率为评价标准,比较各种组合的效果。结果表明,若以累积贡献率≥85%为标准,选择2个主成分时,LDA,QDA和MD-DA三种判别模型预测集正确率分别为32.92%,38.48%和33.54%;以特征值≥1为标准,选择11个主成分时,三种判别模型预测集正确率分别为68.72%,87.04%和83.54%;若以预测集正确率为优先考虑标准,将主成分个数增加至20个时,三种判别模型正确率有较大提高,分别为84.98%,95.68%和95.27%。由此,得到如下结论:①利用PCA组合DA方法建立基于苎麻叶片高光谱的品种识别模型是可行的,但因子数不同、DA判别标准不同、组合方法不同效果差异非常大;②主因子个数对识别结果的影响较为明显,适当增加主成分个数可以显著提高模型判别正确率,因此不应局限于PCA特征值和方差累积贡献率的选择方法;③主因子个数相同时,三种判别标准中,QDA效果最好, LDA效果最差;④最佳组合是20个主成分+QDA方法,其数据维度大大降低(由全波段的2 031维降低20维),而预测集正确率为95.68%。 <&wdkj&>Ramie(Boehmeiria nivea L)is a special and traditional fiber crop in China,having higher economic status.Determining the hyperspectral reflectance of ramie leaves with the spectrometer and developing a hyperspectrum-based method of ramie variety identification of high efficiency will be beneficial for the cultivation of ramie,the development and utilization of germplasm resources as well as the provision of critical technological supports to realize the top quality and high production of ramie and the accurate management of ramie croplands,which are significant for improving ramie yield and quality.In order to apply the hyperspectral technology for identifying ramie varieties,total 1458hyperspectral data on the ramie leaves coming from nine ramie varieties of different genotypes were collected.According to these data,we explored the using of the Principal Components Analysis(PCA)to reduce dimensions of the hyperspectral data and how to determine the best appropriate number of principal factors in the PCA.Further,we compared different combinations constituted by different principal factors and different Discriminant Analysis approaches,and the results of the ramie variety identifying models based on the hyperspectrum of ramie leaves were established.After the principal component analysis of the full-band data sample,with 2~20principal components as the feature variables,we applied three discriminant models,namely the Linear Discriminant analysis(LDA),the Quadratic Discriminant Analysis(QDA),and the Mahalanobis Distance Discriminant Analysis,(MD-DA),to create variety discriminant models and used them to predict,and with the accuracy of the prediction set as the evaluation criteria,the effects of various combinations were compared.The results showed that when we used the cumulative contribution rate(≥85%)as the criteria and selected two principal components,the accuracies for the LDA,the QDA and the MD-DA prediction sets were respectively 32.92%, 38.48%and 33.54%;but,when we used the feature value(≥1)as the criteria,and selected eleven principal components,the accuracies for the prediction sets of above discriminant models were respectively 68.72%,87.04%and 83.54%;and further, when we considered the accuracy of the prediction set as the preferential criteria and selected twenty principal components,the accuracies for above discriminant models were all significantly improved and were respectively 84.98%,95.68%and 95.27%. Therefore,we can draw the following conclusions:(1)it is feasible to establish the ramie leaf-based hyperspectral variety identification model by combining the PCA and the DA,but there are big differences between results due to different numbers of factors, different DA criterias and different combination approaches;(2)The impact of the number of principal factors on the identification results are significant,and the appropriate adding of the principal components can notably improve the accuracies of corresponding models,thus it is not confined to how to select the feature values of the PCA and the accumulative variance contribution rate;(3)When the numbers of principal factors are the same,among above three discriminant criteria,the effect of the QDA is the best while that of the LDA is the worst;(4)Twenty principal components and the QDA approach constitute the best combination,which makes data dimensions be hugely reduced,from 2031dimensions of the full-band down to 20dimensions, and the accuracy of the prediction set is 95.68%.
摘要：
Fractional-order gene regulatory networks with time delay (DFGRNs) have proven that they are more suitable to model gene regulation mechanism than integer-order. In this paper, a novel DFGRN is proposed. The existence and uniqueness of the equilibrium point for the DFGRN are proved under certain conditions. On this basis, the conditions on the global asymptotic stability are established by using the Lyapunov method and comparison theorem for the DFGRN, and the stability conditions are dependent on the fractional-order q. Finally, numerical simulations show that the obtained results are reasonable.
摘要：
The assembly of the HIV-1 immature capsid (HIC) is an essential step in the virus life cycle. In vivo, the HIC is composed of [Formula: see text] hexameric building blocks, and it takes 5-6 min to complete the assembly process. The involvement of numerous building blocks and the rapid timecourse makes it difficult to understand the HIC assembly process. In this work, we study HIC assembly in vivo by using differential equations. We first obtain a full model with 420 differential equations. Then, we reduce six addition reactions for separate building blocks to a single complex reaction. This strategy reduces the full model to 70 equations. Subsequently, the theoretical analysis of the reduced model shows that it might not be an effective way to decrease the HIC concentration at the equilibrium state by decreasing the microscopic on-rate constants. Based on experimental data, we estimate that the nucleating structure is much smaller than the HIC. We also estimate that the microscopic on-rate constant for nucleation reactions is far less than that for elongation reactions. The parametric collinearity investigation testifies the reliability of these two characteristics, which might explain why free building blocks do not readily polymerize into higher-order polymers until their concentration reaches a threshold value. These results can provide further insight into the assembly mechanisms of the HIC in vivo.
摘要：
In this study, the complete mitochondrial genome (mitogenome) of Gibbovalva kobusi was at first sequenced by high-throughput sequencing. As a circular DNA molecule, the complete mitogenome is 15,717 bp in length (GeneBank accession number: MK956103) and consists of 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA) genes, 2 ribosomal RNA (rRNA) genes, and an AT-rich region. The nucleotide composition is A (41.0%), C (11.6%), G (7.9%), and T (39.5%). Based on the sequences of complete mitogenome from 11 species as ingroups and 3 superfamily Tineoidea species as outgroups, the phylogenetic trees were constructed. The family Gracilariidae as a monophyletic clade is strongly supported by the bootstrap value of 100%.
作者机构：
[Wu, Guochun] Huaqiao Univ, Fujian Prov Univ Key Lab Computat Sci, Sch Math Sci, Quanzhou 362021, Fujian, Peoples R China.;[Tan, Zhong] Xiamen Univ, Sch Math Sci, Xiamen 361005, Fujian, Peoples R China.;[Tan, Zhong] Xiamen Univ, Fujian Prov Key Lab Math Modeling & Sci Comp, Xiamen 361005, Fujian, Peoples R China.;[Xu, Jiankai] Hunan Agr Univ, Coll Informat Sci & Technol, Changsha 410128, Hunan, Peoples R China.
通讯机构：
School of Mathematical Sciences and Fujian Provincial Key Laboratory on Mathematical Modeling and Scientific Computing, Xiamen University, Xiamen, China
摘要：
We study the heat flow of equation of H-surface with non-zero Dirichlet boundary in the present article. Introducing the “stable set”
$$\mathfrak{M}_2$$
and “unstable set”
$$\mathfrak{M}_1$$
, we show that there exists a unique global solution provided the initial data belong to
$$\mathfrak{M}_2$$
and the global solution converges to zero in H1 exponentially as time goes to infinity. Moreover, we also prove that the local regular solution must blow up at finite time provided the initial data belong to
$$\mathfrak{M}_1$$
.
摘要：
A depth map and a full focus image can be obtained by using the image sequence and the image evaluation function. The depth map obtained by gradient operator as the evaluation function has good resolution but is also affected by the deviation value. This kind of noise is different from common salt-and-pepper noise and Gaussian noise, so the median filter or mean filter cannot play a very good role. In order to improve the effect of 3D modeling, it is necessary to eliminate the deviation and retain and highlight the depth information. In this paper, an adaptive image enhancement method based on mode cooperative filtering is proposed. This method uses the general level of mode data to express the data, and uses the method of cooperative filtering to form the centralized balance and isolated deviation around the mode. Compared with other filters, the results show that it can achieve better results.
摘要：
Crowd density estimation is one of the critical issues in social activities. The traditional solution to this problem is to leverage video surveillance to monitor a crowd. However, this is not accurate for crowd density estimation because it is still hard to identify people from background. In the past few years, more and more people use Wi-Fi enabled smartphones. Smartphones can send Wi-Fi request packets periodically, even when they are not connected to access points. This gives another promising solution to the crowd density estimation even for the public environment. In this paper, we first develop a Wi-Fi monitor detection that can capture smartphone passive Wi-Fi signal information including MAC address and received signal strength indicator. Then, we propose a positioning algorithm based on smartphone passive Wi-Fi probe and a dynamic fingerprint management strategy. In real-world public social activities, a person may have zero, one, two, or multiple smartphones with variant Wi-Fi signals. Therefore, we design a method of computing the probability of a user generating one Wi-Fi signal to identify people population. Finally, we propose a crowd density estimation solution based on Wi-Fi probe packets positioning algorithm. Experiments were conducted in an indoor laboratory class and three public social activities, clearly demonstrated that the proposed solution can effectively and accurately estimate crowd density.
摘要：
Recently, computational Grids have proven to be a good solution for processing large-scale, computation intensive problems. However, the heterogeneity, dynamics of resources and diversity of applications requirements have always been important factors affecting their performance. In response to these challenges, this work first builds a Grid job scheduling architecture that can dynamically monitor Grid computing center resources and make corresponding scheduling decisions. Second, a Grid job model is proposed to describe the application requirements. Third, this paper studies the characteristics of commercial interconnection networks used in Grids and forecast job transmission time. Fourth, this paper proposes an application-aware job scheduling mechanism (AJSM) that includes periodic scheduling flow and a heuristic application-aware deadline constraint job scheduling algorithm. The rigorous performance evaluation results clearly demonstrate that the proposed application-aware job scheduling mechanism can successful schedule more Grid jobs than the existing algorithms. For successful scheduled jobs, our proposed AJSM method is the best algorithm for job average processing time and makespan.
