Yuxin Zhao, Zhanxiang Tan, Yuying Li, Kaiyue Zhang, Lili Guo^*, Xiaogai Hou^*

Phyton-International Journal of Experimental Botany, Vol.94, No.4, pp. 1159-1176, 2025, DOI:10.32604/phyton.2025.063737 - 30 April 2025

Abstract Receptor-like cytoplasmic kinases (RLCKs) play a crucial role in the physiological processes of plant growth and development and stress response. To elucidate the characteristics and functions of the PBL gene family in tree peonies, the whole genome identification of PBL family members in tree peonies was conducted using a bioinformatics approach based on the published Arabidopsis thaliana PBL protein sequence. A total of 51 PoPBL members were identified, which were distributed unevenly on five chromosomes in the tree peony. PoPBL proteins were localized in the nucleus, cytoplasm, chloroplasts, and mitochondria, with most members of the same clade… More >

Can Hu¹, Shanqing Zhang^2,*, Kewei Tao², Gaoming Yang¹, Li Li²

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4913-4930, 2025, DOI:10.32604/cmc.2025.059770 - 06 March 2025

Abstract The surge of large-scale models in recent years has led to breakthroughs in numerous fields, but it has also introduced higher computational costs and more complex network architectures. These increasingly large and intricate networks pose challenges for deployment and execution while also exacerbating the issue of network over-parameterization. To address this issue, various network compression techniques have been developed, such as network pruning. A typical pruning algorithm follows a three-step pipeline involving training, pruning, and retraining. Existing methods often directly set the pruned filters to zero during retraining, significantly reducing the parameter space. However, this… More >

Caiping Huang^*, Zihan Huang, Wenfeng You

Structural Durability & Health Monitoring, Vol.18, No.3, pp. 299-320, 2024, DOI:10.32604/sdhm.2024.047850 - 15 May 2024

Abstract This paper presents an easily installed improved perfobond connector (PBL) designed to reduce the shear concentration of PBL. The improvement of PBL lies in changing the straight penetrating rebar to the Z-type penetrating rebar. To study the shear performance of improved PBL, two PBL test specimens which contain straight penetrating rebar and six improved PBL test specimens which contain Z-type penetrating rebars were designed and fabricated, and push-out tests of these eight test specimens were carried out to investigate and compare the shear behavior of PBL. Additionally, Finite Element Analysis (FEA) models of the PBL… More >

Anuruk Prommakhot, Jakkree Srinonchat^*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3313-3329, 2022, DOI:10.32604/cmc.2022.024417 - 29 March 2022

Abstract Image classification always has open challenges for computer vision research. Nowadays, deep learning has promoted the development of this field, especially in Convolutional Neural Networks (CNNs). This article proposes the development of efficiently scaled dilation of DropBlock optimization in CNNs for the fungus classification, which there are five species in this experiment. The proposed technique adjusts the convolution size at 35, 45, and 60 with the max-polling size 2 × 2. The CNNs models are also designed in 12 models with the different BlockSizes and KeepProp. The proposed techniques provide maximum accuracy of 98.30% for the training More >

Wei Sun^1,2,*, Xuan Chen³, Xiaorui Zhang^1,3, Guangzhao Dai², Pengshuai Chang², Xiaozheng He⁴

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3549-3561, 2021, DOI:10.32604/cmc.2021.021627 - 24 August 2021

Abstract Vehicle re-identification (ReID) aims to retrieve the target vehicle in an extensive image gallery through its appearances from various views in the cross-camera scenario. It has gradually become a core technology of intelligent transportation system. Most existing vehicle re-identification models adopt the joint learning of global and local features. However, they directly use the extracted global features, resulting in insufficient feature expression. Moreover, local features are primarily obtained through advanced annotation and complex attention mechanisms, which require additional costs. To solve this issue, a multi-feature learning model with enhanced local attention for vehicle re-identification (MFELA)… More >