Jingcheng Zhang¹, Xingjian Zhou¹, Dong Shen¹, Qimeng Yu¹, Lin Yuan^2,*, Yingying Dong³

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 745-762, 2024, DOI:10.32604/phyton.2024.049734

Abstract As an important rice disease, rice bacterial leaf blight (RBLB, caused by the bacterium Xanthomonas oryzae pv. oryzae), has become widespread in east China in recent years. Significant losses in rice yield occurred as a result of the disease’s epidemic, making it imperative to monitor RBLB at a large scale. With the development of remote sensing technology, the broad-band sensors equipped with red-edge channels over multiple spatial resolutions offer numerous available data for large-scale monitoring of rice diseases. However, RBLB is characterized by rapid dispersal under suitable conditions, making it difficult to track the disease at a regional scale with… More >

Biying Qiu^1,2, Niwu Te², Lin Song², Yuan Shi², Chuan Qiu², Xiaoan Zuo³, Qiang Yu⁴, Jianqiang Qian⁵, Zhengwen Wang², Honghui Wu^6,7, Wentao Luo^2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 831-841, 2024, DOI:10.32604/phyton.2024.047560

Abstract The responses of ecosystem nitrogen (N) and phosphorus (P) to drought are an important component of global change studies. However, previous studies were more often based on site-specific experiments, introducing a significant uncertainty to synthesis and site comparisons. We investigated the responses of vegetation and soil nutrients to drought using a network experiment of temperate grasslands in Northern China. Drought treatment (66% reduction in growing season precipitation) was imposed by erecting rainout shelters, respectively, at the driest, intermediate, and wettest sites. We found that vegetation nutrient concentrations increased but soil nutrient concentrations decreased along the aridity gradient. Differential responses were… More >

Meng Huang, Honglei Wei^*, Xianyi Zhai

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 531-547, 2024, DOI:10.32604/cmc.2024.048510

Abstract In pursuit of cost-effective manufacturing, enterprises are increasingly adopting the practice of utilizing recycled semiconductor chips. To ensure consistent chip orientation during packaging, a circular marker on the front side is employed for pin alignment following successful functional testing. However, recycled chips often exhibit substantial surface wear, and the identification of the relatively small marker proves challenging. Moreover, the complexity of generic target detection algorithms hampers seamless deployment. Addressing these issues, this paper introduces a lightweight YOLOv8s-based network tailored for detecting markings on recycled chips, termed Van-YOLOv8. Initially, to alleviate the influence of diminutive, low-resolution markings on the precision of… More >

Yiwei Liu¹, Yingnan Zhao^1,*, Yi Chen¹, Zheng Hu¹, Min Xia²

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 909-926, 2024, DOI:10.32604/cmc.2024.047901

Abstract Scene text detection is an important task in computer vision. In this paper, we present YOLOv5 Scene Text (YOLOv5ST), an optimized architecture based on YOLOv5 v6.0 tailored for fast scene text detection. Our primary goal is to enhance inference speed without sacrificing significant detection accuracy, thereby enabling robust performance on resource-constrained devices like drones, closed-circuit television cameras, and other embedded systems. To achieve this, we propose key modifications to the network architecture to lighten the original backbone and improve feature aggregation, including replacing standard convolution with depth-wise convolution, adopting the C2 sequence module in place of C3, employing Spatial Pyramid… More >

Xiaohui Yang, Peiyin Zhao^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1521-1538, 2024, DOI:10.32604/cmc.2024.047666

Abstract Electronic medical records (EMR) facilitate the sharing of medical data, but existing sharing schemes suffer from privacy leakage and inefficiency. This article proposes a lightweight, searchable, and controllable EMR sharing scheme, which employs a large attribute domain and a linear secret sharing structure (LSSS), the computational overhead of encryption and decryption reaches a lightweight constant level, and supports keyword search and policy hiding, which improves the high efficiency of medical data sharing. The dynamic accumulator technology is utilized to enable data owners to flexibly authorize or revoke the access rights of data visitors to the data to achieve controllability of… More >

Zenglun Guan^1,2, Murad S. Alfarzaeai^1,3,*, Eryi Hu^1,3,*, Taqiaden Alshmeri⁴, Wang Peng³

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 279-306, 2024, DOI:10.32604/cmc.2024.047159

Abstract In the coal mining industry, the gangue separation phase imposes a key challenge due to the high visual similarity between coal and gangue. Recently, separation methods have become more intelligent and efficient, using new technologies and applying different features for recognition. One such method exploits the difference in substance density, leading to excellent coal/gangue recognition. Therefore, this study uses density differences to distinguish coal from gangue by performing volume prediction on the samples. Our training samples maintain a record of 3-side images as input, volume, and weight as the ground truth for the classification. The prediction process relies on a… More >

Liang Chen¹, Jingbo Zhang¹, Linjie Wu¹, Xingjuan Cai^1,2,*, Yubin Xu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 363-383, 2024, DOI:10.32604/cmes.2024.049044

Abstract The large-scale multi-objective optimization algorithm (LSMOA), based on the grouping of decision variables, is an advanced method for handling high-dimensional decision variables. However, in practical problems, the interaction among decision variables is intricate, leading to large group sizes and suboptimal optimization effects; hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables (MOEAWOD) is proposed in this paper. Initially, the decision variables are perturbed and categorized into convergence and diversity variables; subsequently, the convergence variables are subdivided into groups based on the interactions among different decision variables. If the size of a group surpasses the set… More >

Zhong Qu^1,*, Guoqing Mu¹, Bin Yuan²

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 255-273, 2024, DOI:10.32604/cmes.2024.048175

Abstract Automatic crack detection of cement pavement chiefly benefits from the rapid development of deep learning, with convolutional neural networks (CNN) playing an important role in this field. However, as the performance of crack detection in cement pavement improves, the depth and width of the network structure are significantly increased, which necessitates more computing power and storage space. This limitation hampers the practical implementation of crack detection models on various platforms, particularly portable devices like small mobile devices. To solve these problems, we propose a dual-encoder-based network architecture that focuses on extracting more comprehensive fracture feature information and combines cross-fusion modules… More > Graphic Abstract

Kai Wang¹, Biao He^2,*, Pijush Samui³, Jian Zhou⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 229-253, 2024, DOI:10.32604/cmes.2024.047569

Abstract Rock bursts represent a formidable challenge in underground engineering, posing substantial risks to both infrastructure and human safety. These sudden and violent failures of rock masses are characterized by the rapid release of accumulated stress within the rock, leading to severe seismic events and structural damage. Therefore, the development of reliable prediction models for rock bursts is paramount to mitigating these hazards. This study aims to propose a tree-based model—a Light Gradient Boosting Machine (LightGBM)—to predict the intensity of rock bursts in underground engineering. 322 actual rock burst cases are collected to constitute an exhaustive rock burst dataset, which serves… More >

LIJUAN ZHANG^1,#, QINGYIN MENG^2,#, LI ZHUANG¹, QUAN GONG¹, XIANDA HUANG³, XUEQIN LI¹, SHIJUAN LI¹, GUOQIN WANG⁴, XICAI WANG^5,*

BIOCELL, Vol.48, No.4, pp. 581-590, 2024, DOI:10.32604/biocell.2024.047260

Abstract Background: Lung adenocarcinoma is a very pervasive histological form of lung cancers, and inhibiting metastasis is crucial for effective treatment. In this investigation, we explored the functional interaction of miR-30a-5p and the putative transcription factor 2 of the homeodomain (PHTF2) in dictating the aggressiveness and metastasis of lung adenocarcinoma. Method: We collected clinical samples to evaluate the expression patterns of miR-30a-5p and PHTF2 in lung adenocarcinoma along with normal tissues. Cellular experiments including cell count kit (CCK)-8 growth assay, apoptosis analysis, migration and invasion examinations were performed to assess the aggressiveness of lung adenocarcinoma cells. Furthermore, we examined tumorigenesis and… More > Graphic Abstract