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.
摘要：
<jats:title>Abstract</jats:title><jats:p>The present study investigates residual contagion of the recent two international crises under the dual functions of “herd effect” and “alarm effects in informatization, focusing on emerging markets. Both the impulse response method and dynamic conditional correlation MGARCH model are used to capture residual contagion from developed markets to emerging markets during the period 2000–2016. The results show that the level of volatility in emerging stock markets was greater than that of developed markets, such as the US and the EU, although they are less integrated with the world. Emerging stock markets are significantly subjected to residual contagion during the US subprime mortgage crisis and Europe’s protracted debt crisis. Moreover, the residual contagion effects of these two crises are noticeably heterogeneous in emerging markets.</jats:p>
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.
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.
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.
