Ali Abdelmoteleb¹, Daniel Gonzalez-Mendoza^2,*, Ahmed Mohamed Elbaalawy³

Phyton-International Journal of Experimental Botany, Vol.91, No.1, pp. 21-32, 2022, DOI:10.32604/phyton.2022.016227

Abstract The salinity stress is one of the most relevant abiotic stresses that affects the agricultural production. The present study was performed to study the improvement of the salt tolerance of tomato plants which is known for their susceptibility to salt stress. The present study aimed to assess to what extent strain Azospirillum brasilense (N040) and Saccharomyces cerevisiae improve the salt tolerance to tomato plants treated with different salt concentration. The inoculant strain A. brasilense (N040) was previously adapted to survive up to 7% NaCl in the basal media. A greenhouse experiment was conducted to evaluate the effect of this inoculation… More >

Alejandro Ibarra-Sánchez, Juan Enrique Rodríguez-Pérez, Aureliano Peña-Lomelí, Clemente Villanueva-Verduzco, Jaime Sahagún-Castellanos^*

Phyton-International Journal of Experimental Botany, Vol.91, No.1, pp. 33-43, 2022, DOI:10.32604/phyton.2022.016136

Abstract Synthetic varieties (SVs) are populations generated by randomly mating their parents. They are a good alternative for low-input farmers who grow onions, maize, and other allogamous crops since the seed produced by a SV does not change from one generation to the next. Although SV progenitors are commonly pure lines, in this case a synthetic (Syn_TC) whose parents are t three-way line crosses, a very common type of maize hybrid grown in Mexico, is studied. The aim was to develop a general and exact equation for the inbreeding coefficient of a Syn_TC Syn_TC because of its relationship with… More >

Yaoyi Zhang, Xiangyin Ni, Jing Yang, Siyi Tan, Shu Liao, Dingyi Wang, Kai Yue, Fuzhong Wu^*

Phyton-International Journal of Experimental Botany, Vol.91, No.1, pp. 185-196, 2022, DOI:10.32604/phyton.2022.016117

Abstract High rainfall in subtropical regions can leach cation elements from ecosystems, which may limit plant growth. Plants often develop efficient resorption patterns to recycle elements, but there is relatively little available information on this topic. In February 2012, a common garden was established in a subtropical forest by planting dominant trees from the area. Green and senescent leaves were sampled from 11 tree species. The concentrations of potassium (K), calcium (Ca), sodium (Na) and magnesium (Mg) were determined, and the resorption efficiencies were calculated. The results showed significant K, Na and Mg resorption in most of the investigated tree species,… More >

Chunxue Peng^1,2, Fang Gao^1,2, Hao Wang^1,2, Iraida Nikolaevna Tretyakova³, Alexander Mikhaylovich Nosov^4,5, Hailong Shen^1,2,*, Ling Yang^1,2,*

Phyton-International Journal of Experimental Botany, Vol.91, No.1, pp. 223-238, 2022, DOI:10.32604/phyton.2022.015523

Abstract Korean pine is an important afforestation tree species in Northeast China, which has a high ecological and economic value. Although regeneration of somatic embryogenesis using immature zygotic embryos of Korean pine as explants has been successful, it cannot be applied to automation and large-scale production. Therefore, we urgently need a method that can increase the output of somatic embryos (SEs) to meet the needs of large-scale production. We used Korean pine 1–1 and 1–100 cell lines as research materials to evaluate the effects of inoculum-density, culture time, orbiting speed, vessel volume, plant growth regulator (PGR) concentration, and carbon source on… More >

Yuanyuan Liu, Zhen Li, Lie Xu, Qiang Fu^*, Yongjian Wang

Phyton-International Journal of Experimental Botany, Vol.91, No.1, pp. 115-128, 2022, DOI:10.32604/phyton.2022.015395

Abstract A key scientific challenge relating to the threat of invasive plants on agriculture at the region level is to understand their adaptation and evolution in functional traits. Leaf functional traits, related to growth and resource utilization, might lead to adaptation of invasive plants to the geographical barriers (region or elevation). In the field experiment, we discussed the effects of region and elevation on leaf functional traits on invasive plant Erigeron annuus in farmland habitats in China. We compared leaf size, coefficient of variation (CV) of leaf traits, and fluctuating asymmetry (FA) of E. annuus from three regions (east vs. center… More >

Jiaming Mao^1,*, Mingming Zhang¹, Mu Chen², Lu Chen², Fei Xia¹, Lei Fan¹, ZiXuan Wang³, Wenbing Zhao⁴

Computer Systems Science and Engineering, Vol.39, No.3, pp. 373-390, 2021, DOI:10.32604/csse.2021.018086

Abstract The rapidly increasing popularity of mobile devices has changed the methods with which people access various network services and increased network traffic markedly. Over the past few decades, network traffic identification has been a research hotspot in the field of network management and security monitoring. However, as more network services use encryption technology, network traffic identification faces many challenges. Although classic machine learning methods can solve many problems that cannot be solved by port- and payload-based methods, manually extract features that are frequently updated is time-consuming and labor-intensive. Deep learning has good automatic feature learning capabilities and is an ideal… More >

Zhipin Gu¹, Liangzhong He², Peiyan Li¹, Peng Sun³, Jiangyong Shi¹, Yuexiang Yang^1,*

Computer Systems Science and Engineering, Vol.39, No.3, pp. 307-320, 2021, DOI:10.32604/csse.2021.017969

Abstract Federated learning is an ideal solution to the limitation of not preserving the users’ privacy information in edge computing. In federated learning, the cloud aggregates local model updates from the devices to generate a global model. To protect devices’ privacy, the cloud is designed to have no visibility into how these updates are generated, making detecting and defending malicious model updates a challenging task. Unlike existing works that struggle to tolerate adversarial attacks, the paper manages to exclude malicious updates from the global model’s aggregation. This paper focuses on Byzantine attack and backdoor attack in the federated learning setting. We… More >

M.J. Huntul^*

Computer Systems Science and Engineering, Vol.39, No.3, pp. 415-429, 2021, DOI:10.32604/csse.2021.017924

Abstract The aim of this paper is to find the time-dependent term numerically in a two-dimensional heat equation using initial and Neumann boundary conditions and nonlocal integrals as over-determination conditions. This is a very interesting and challenging nonlinear inverse coefficient problem with important applications in various fields ranging from radioactive decay, melting or cooling processes, electronic chips, acoustics and geophysics to medicine. Unique solvability theorems of these inverse problems are supplied. However, since the problems are still ill-posed (a small modification in the input data can lead to bigger impact on the ultimate result in the output solution) the solution needs… More >

Heming Jia^1,2,*, Yao Li², Kangjian Sun², Ning Cao¹, Helen Min Zhou³

Computer Systems Science and Engineering, Vol.39, No.3, pp. 321-335, 2021, DOI:10.32604/csse.2021.017536

Abstract In this paper, a hybrid model based on sooty tern optimization algorithm (STOA) is proposed to optimize the parameters of the support vector machine (SVM) and identify the best feature sets simultaneously. Feature selection is an essential process of data preprocessing, and it aims to find the most relevant subset of features. In recent years, it has been applied in many practical domains of intelligent systems. The application of SVM in many fields has proved its effectiveness in classification tasks of various types. Its performance is mainly determined by the kernel type and its parameters. One of the most challenging… More >

Amrul Faruq¹, Aminaton Marto², Shahrum Shah Abdullah^3,*

Computer Systems Science and Engineering, Vol.39, No.3, pp. 297-306, 2021, DOI:10.32604/csse.2021.017468

Abstract The rainstorm is believed to contribute flood disasters in upstream catchments, resulting in further consequences in downstream area due to rise of river water levels. Forecasting for flood water level has been challenging, presenting complex task due to its nonlinearities and dependencies. This study proposes a support vector machine regression model, regarded as a powerful machine learning-based technique to forecast flood water levels in downstream area for different lead times. As a case study, Kelantan River in Malaysia has been selected to validate the proposed model. Four water level stations in river basin upstream were identified as input variables. A… More >