Shugufta Parveen¹, Fayaz A. Mohiddin^2,*, M. Ashraf Bhat³, Zahoor Ahmed Baba⁴, Fehim Jeelani⁵, M. Anwar Bhat⁶, Sajad Un Nabi⁷, Burhan Hamid², Saba Bandey⁸, Farhanaz Rasool⁹, Zakir Amin¹, Ibrahim Al-Ashkar^10,*, Muhammad Adnan¹¹, Ayman El Sabagh¹²

Phyton-International Journal of Experimental Botany, Vol.92, No.11, pp. 3021-3041, 2023, DOI:10.32604/phyton.2023.030921

Abstract One hundred twenty-five endophytic microorganisms were isolated from the roots, stems, and leaves of four prominent rice cultivars growing in temperate regions. Their potential to combat rice blast disease and promote plant growth was investigated. The dual culture tests highlighted the strong antagonistic activity of five fungal (ranging from 89%–70%) and five bacterial (72%–61%) endophytes. Subsequent examination focused on volatile compounds produced by selected isolates to counter the blast pathogen. Among these, the highest chitinase (13.76 µg mL⁻¹) and siderophore (56.64%), was exhibited by Aspergillus flavus, and the highest HCN production was shown by Stenotrophomonas maltophilia (36.15 µM mL⁻¹). In… More >

Ziwei Li^1,2, Lifen Huang^1,2, Zhongyang Huo^1,2, Min Jiang^1,2,*

Phyton-International Journal of Experimental Botany, Vol.92, No.11, pp. 2999-3019, 2023, DOI:10.32604/phyton.2023.030627

Abstract The canopy temperature of rice is an important index that directly reflects the growth and physiological state of rice, and affects the yield of rice plants to a great extent. The correlation between the temperatures of different rice organs and canopy in different growth stages and the grain yield is complex. The stability and universality of these correlations must be verified. We conducted a pot experiment using two rice varieties and two temperature treatments (high temperature treatment was carried out at the beginning of heading stage for 10 days). We measured rice organ temperature during seven stages of growth using… More >

Ruoyan Li^1,2, Yijun Liu^1,*, Wenjing Ye²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09472

Abstract The boundary element method (BEM) for acoustic problems is a numerical method based on solving the discretized boundary integral equation (BIE) corresponding to the Helmholtz equation. A fast direct BEM for 3D acoustic problems is proposed in this paper, which is more suitable for broadband acoustic simulation of complex structures, such as in the design and analysis of acoustic metamaterials. The main idea of the fast direct solver is based on the hierarchical off-diagonal low-rank (HODLR) matrix, randomized interpolative decomposition and fast matrix inversion formula. Several numerical examples in solving both interior and exterior acoustic problems are presented in this… More >

Shehab Abdulhabib Alzaeemi¹, Saratha Sathasivam^2,*, Majid Khan bin Majahar Ali², K. G. Tay¹, Muraly Velavan³

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1471-1491, 2023, DOI:10.32604/csse.2023.037366

Abstract Rubber producers, consumers, traders, and those who are involved in the rubber industry face major risks of rubber price fluctuations. As a result, decision-makers are required to make an accurate estimation of the price of rubber. This paper aims to propose hybrid intelligent models, which can be utilized to forecast the price of rubber in Malaysia by employing monthly Malaysia’s rubber pricing data, spanning from January 2016 to March 2021. The projected hybrid model consists of different algorithms with the symbolic Radial Basis Functions Neural Network k-Satisfiability Logic Mining (RBFNN-kSAT). These algorithms, including Grey Wolf Optimization Algorithm, Artificial Bee Colony… More >

S. Kanmani^1,*, M. Murali²

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2583-2598, 2023, DOI:10.32604/csse.2023.037265

Abstract The introduction of new technologies has increased communication network coverage and the number of associating nodes in dynamic communication networks (DCN). As the network has the characteristics like decentralized and dynamic, few nodes in the network may not associate with other nodes. These uncooperative nodes also known as selfish nodes corrupt the performance of the cooperative nodes. Namely, the nodes cause congestion, high delay, security concerns, and resource depletion. This study presents an effective selfish node detection method to address these problems. The Price of Anarchy (PoA) and the Price of Stability (PoS) in Game Theory with the Presence of… More >

Fawad Ali Shah¹, Habib Akbar¹, Abid Ali^2,3, Parveen Amna⁴, Maha Aljohani⁵, Eman A. Aldhahri⁶, Harun Jamil^7,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1385-1413, 2023, DOI:10.32604/csse.2023.036144

Abstract The detection of rice leaf disease is significant because, as an agricultural and rice exporter country, Pakistan needs to advance in production and lower the risk of diseases. In this rapid globalization era, information technology has increased. A sensing system is mandatory to detect rice diseases using Artificial Intelligence (AI). It is being adopted in all medical and plant sciences fields to access and measure the accuracy of results and detection while lowering the risk of diseases. Deep Neural Network (DNN) is a novel technique that will help detect disease present on a rice leave because DNN is also considered… More >

Jing Yang^1,2, Yufeng Wang², Zhanghua Hu³, Xiaoping Chen⁴, Yanjun Dong^5,*, Sheng Teng^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.9, pp. 2649-2663, 2023, DOI:10.32604/phyton.2023.030710

Abstract Improvement of photosynthetic efficiency is a major approach to increase crop yield potential. Previously, we cloned a gene encoding the chloroplast-located putative monooxygenase TCD5, which is essential in plastid development under low temperature in rice (Oryza sativa L.). In this study, the effects of TCD5 on the photosynthesis and the yields were investigated in rice. Two sets of genetic materials with three levels of TCD5 expression, including tcd5 mutant or TCD5 RNAi transgenic lines and TCD5 over-expression transgenic lines in Jiahua1 and Nipponbare backgrounds, were used in the field trails of multi-locations and multi-years. TCD5 positively affected the panicle number… More >

Jintao Fu¹, Yong Zhou^1,*, Qian Qiu², Guangwei Xu³, Neng Wan³

Journal of Quantum Computing, Vol.4, No.3, pp. 147-163, 2022, DOI:10.32604/jqc.2022.038358

Abstract In the field of computer research, the increase of data in result of societal progress has been remarkable, and the management of this data and the analysis of linked businesses have grown in popularity. There are numerous practical uses for the capability to extract key characteristics from secondary property data and utilize these characteristics to forecast home prices. Using regression methods in machine learning to segment the data set, examine the major factors affecting it, and forecast home prices is the most popular method for examining pricing information. It is challenging to generate precise forecasts since many of the regression… More >

ZHENGHONG FENG¹, BING GAO¹, YU GAO², JIANHUI WU^1,*

BIOCELL, Vol.47, No.7, pp. 1571-1582, 2023, DOI:10.32604/biocell.2023.029106

Abstract Background:Potentilla sericea is a heavy metal hyperaccumulator landscaping plant. MYB transcription factors play an important role in regulating plant stress response to adversity. However, there are few studies on MYB transcription factors in stress tolerance in Potentilla sericea. In this study, the gene was successfully cloned from Potentilla sericea. Methods: Bioinformatic analysis and real-time quantitative PCR (qPCR) methods were used to evaluate this gene. The transgenic A. thaliana were obtained by flower dipping and the gene function was identified by determining physiological indicators under cadmium stress. Results: The open reading frame of is 942 bp, which encodes 313 amino acids… More >

Zhiwei Ye¹, Ziqian Fang¹, Zhina Song^1,*, Haigang Sui², Chunyan Yan¹, Wen Zhou¹, Mingwei Wang¹

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2019-2035, 2023, DOI:10.32604/iasc.2023.039949

Abstract Hyperparameters play a vital impact in the performance of most machine learning algorithms. It is a challenge for traditional methods to configure hyperparameters of the capsule network to obtain high-performance manually. Some swarm intelligence or evolutionary computation algorithms have been effectively employed to seek optimal hyperparameters as a combinatorial optimization problem. However, these algorithms are prone to get trapped in the local optimal solution as random search strategies are adopted. The inspiration for the hybrid rice optimization (HRO) algorithm is from the breeding technology of three-line hybrid rice in China, which has the advantages of easy implementation, less parameters and… More >