Shafiul Islam, Lutful Hassan, Mohammad Anwar Hossain

Phyton-International Journal of Experimental Botany, Vol.91, No.1, pp. 97-114, 2022, DOI:10.32604/phyton.2022.017251

Abstract Tomato (Solanum lycopersicum L.) is called ‘the poor man’s orange’ due to its low price and improved nutritional values. An experiment was conducted to study the breeding potential of some exotic tomato lines by assessing various qualitative and quantitative traits conferring yield and quality attributes. Among the qualitative traits, greater variability was observed for growth type, stem hairiness, and fruit shape and size. A determinate growth habit was observed in the genotype AVTO9802 while the genotype AVTO0102 produced yellow color fruits. A significant (p ≤ 0.01) variation was also observed for the studied quantitative traits. Based on yield and traits… More >

Meifeng Wang^1,2, Wubliker Dessie², Hui Li^1,*

Journal of Renewable Materials, Vol.9, No.12, pp. 2119-2128, 2021, DOI:10.32604/jrm.2021.016811

Abstract Lignin is the most abundant heteropolymer based on aromatic subunits in nature. Large quantities of lignin are annually produced from pulping processes and biorefinery industries. Its unclearly defined structure and difficult biodegradation mainly limit its utilization. This work focused on the effect of hydroxylation of lignin on its microbial degradation. Butyloxy carbonyl-modified lignin, and hydroxylated-lignin were synthesized with di-tert-butyl dicarbonate and hydrogen peroxide, respectively, using lignin as raw material. The degradation of the modifiedlignins both by P. chrysosporium and B. subtilis were analyzed using UV-vis spectroscopy. Results revealed that the lignin degradation velocity raises with the increase hydroxylation level of… More > Graphic Abstract

Zhichao Hu¹, Xiangzhan Yu^1,*, Jiantao Shi¹, Lin Ye^1,2

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 695-711, 2021, DOI:10.32604/cmc.2021.017574

Abstract With the continuous development of network technology, various large-scale cyber-attacks continue to emerge. These attacks pose a severe threat to the security of systems, networks, and data. Therefore, how to mine attack patterns from massive data and detect attacks are urgent problems. In this paper, an approach for attack mining and detection is proposed that performs tasks of alarm correlation, false-positive elimination, attack mining, and attack prediction. Based on the idea of CluStream, the proposed approach implements a flow clustering method and a two-step algorithm that guarantees efficient streaming and clustering. The context of an alarm in the attack chain… More >

J. Hemalatha¹, S. Geetha², R. Geetha³, C. Balasubramanian⁴, Daniela Elena Popescu⁵, D. Jude Hemanth^6,*

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 283-300, 2021, DOI:10.32604/cmc.2021.017203

Abstract A novel image reversible data-hiding scheme based on primitive and varying radix numerical model is presented in this article. Using varying radix, variable sum of data may be embedded in various pixels of images. This scheme is made adaptive using the correlation of the neighboring pixels. Messages are embedded as blocks of non-uniform length in the high-frequency regions of the rhombus mean interpolated image. A higher amount of data is embedded in the high-frequency regions and lesser data in the low-frequency regions of the image. The size of the embedded data depends on the statistics of the pixel distribution in… More >

Peng Wei, Mingdao Lu, Xuehan Zhang, Yilei Teng^*

Journal of Quantum Computing, Vol.3, No.1, pp. 13-23, 2021, DOI:10.32604/jqc.2021.016324

Abstract Aviation service plays an indispensable role in the process of social and economic development. In this process, the problem of flight punctuality becomes more and more serious. Flight delay will bring a variety of implicit and explicit losses to individual passengers and airlines, so it is necessary to analyze the influencing factors of flight punctuality rate. Complex network can be used to study various objects with complex relations, obtain the relations of these objects and calculate the influence of different indicators on the objects. This article mainly has carried on the three aspects: Firstly, get the flight data from the… More >

Lei Guo^1,2,3,4, Pingping Chen¹, Lixia Guo^1,2,3,*, Zhilong Xue⁴, Zi Guan¹, Mingru Li¹

Journal of Renewable Materials, Vol.9, No.10, pp. 1805-1819, 2021, DOI:10.32604/jrm.2021.015140

Abstract In order to explore the relationship between the macroscopic properties and pore structure characteristics of baking-free slag-sludge bricks, the compressive strength and water absorption rate using aluminum industrial slag and sludge of different substitution rates were tested. Optical instruments and image analysis software were used to measure the parameters of the pore structure. Specifically, a fractal model was built based on the fractal theory, in which the fractal dimension was used as the characteristic index of the pore structure to analyze the correlation and interaction mechanism between the fractal dimension and the macroscopic mechanical properties. Based on this study, conclusions… More >

Shuo Qu¹, Yaolei Jiao², Lamboro Abraham², Piwu Wang^1,*

Phyton-International Journal of Experimental Botany, Vol.90, No.4, pp. 1177-1192, 2021, DOI:10.32604/phyton.2021.015206

Abstract The fatty acid dehydrogenase gene plays an important role in regulating the oleic acid content in soybean. Genome-wide association study screened out soybean oleic acid related gene Gm15G117700. A fragment size of 693bp was obtained by PCR amplification of the gene and, it was connected by seamless cloning technology to the pMD18T cloning vector. Based on the gene sequence cloned, bioinformatic analysis of gene protein was performed. The overexpression vector of Gm15G117700 and the CRISPR/Cas9 gene editing vector were constructed. The positive plants were obtained by Agrobacterium-mediated transformation of soybean cotyledon nodes and T₂ plants were identified by conventional PCR,… More >

Xiaoli Zhang^1,2,#, Xiaohong Yin^2,3,#, Jiana Chen^3,#, Fangbo Cao³, Yu Liu³, Zhengwu Xiao³, Liqin Hu³, Guanghui Chen³, Tianfeng Liang^1,2,*, Min Huang^3,*

Phyton-International Journal of Experimental Botany, Vol.90, No.4, pp. 1285-1292, 2021, DOI:10.32604/phyton.2021.014778

Abstract Protein in rice grains is an important source of nutrition for rice consumers. This study mainly aimed to identify the critical factors that determine grain protein concentration in rice. Accumulation parameters, including mean accumulation rate (R_mean) and active accumulation duration (D_active), for protein and non-protein components and their correlations with protein concentration in rice grains were investigated in field experiments conducted over two years with six rice cultivars. Results showed that grain protein concentration ranged from 9.6% to 11.9% across cultivars and years. Accumulation processes of protein and non-protein components were well fitted by the logistic equation for all six… More >

Zheng Zhang^*, Shu Zhou

Journal of New Media, Vol.3, No.2, pp. 73-80, 2021, DOI:10.32604/jnm.2021.018923

Abstract The development of various applications based on social network text is in full swing. Studying text features and classifications is of great value to extract important information. This paper mainly introduces the common feature selection algorithms and feature representation methods, and introduces the basic principles, advantages and disadvantages of SVM and KNN, and the evaluation indexes of classification algorithms. In the aspect of mutual information feature selection function, it describes its processing flow, shortcomings and optimization improvements. In view of its weakness in not balancing the positive and negative correlation characteristics, a balance weight attribute factor and feature difference factor… More >

Hongshuo Zhang¹, Bo Zhu^1,*, Kaimin Pang¹, Chunmei Chen¹, Yuwei Wan²

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 797-810, 2021, DOI:10.32604/iasc.2021.017232

Abstract Using machine learning method to recognize abnormal patterns covers the shortage of traditional control charts for autocorrelation processes, which violate the applicable conditions of the control chart, i.e., the independent identically distributed (IID) assumption. In this study, we propose a recognition model based on support vector machine (SVM) for the AR (1) type of autocorrelation process. For achieving a higher recognition performance, the cuckoo search algorithm (CS) is used to optimize the two hyper-parameters of SVM, namely the penalty parameter c and the radial basis kernel parameter g. By using Monte Carlo simulation methods, the data sets containing samples of… More >