Zhengyang Zhang^#, Weixue Liu^#, Yinran Huang^*, Ping Li^*

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1263-1274, 2024, DOI:10.32604/phyton.2024.050755

Abstract Plant antifreeze proteins (AFPs) are special proteins that can protect plant cells from ice crystal damage in low-temperature environments, and they play a crucial role in the process of plants adapting to cold environments. Proteins with these characteristics have been found in fish living in cold regions, as well as many plants and insects. Although research on plant AFPs started relatively late, their application prospects are broad, leading to the attention of many researchers to the isolation, cloning, and genetic improvement of plant AFP genes. Studies have found that the distribution of AFPs in different species… More >

Yuting Zhou¹, Xuemei Yang¹, Junping Yin^2,3,4,*, Shiqi Liu¹

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5313-5333, 2024, DOI:10.32604/cmc.2024.052060

Abstract Gliomas have the highest mortality rate of all brain tumors. Correctly classifying the glioma risk period can help doctors make reasonable treatment plans and improve patients’ survival rates. This paper proposes a hierarchical multi-scale attention feature fusion medical image classification network (HMAC-Net), which effectively combines global features and local features. The network framework consists of three parallel layers: The global feature extraction layer, the local feature extraction layer, and the multi-scale feature fusion layer. A linear sparse attention mechanism is designed in the global feature extraction layer to reduce information redundancy. In the local feature… More >

Xiaofang Jin¹, Yuying Yang^1,*, Yinan Wu¹, Ying Xu²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5225-5242, 2024, DOI:10.32604/cmc.2024.050384

Abstract The emergence of new media in various fields has continuously strengthened the social aspect of social media. Netizens tend to express emotions in social interactions, and many people even use satire, metaphors, and other techniques to express some negative emotions, it is necessary to detect sarcasm in social comment data. For sarcasm, the more reference data modalities used, the better the experimental effect. This paper conducts research on sarcasm detection technology based on image-text fusion data. To effectively utilize the features of each modality, a feature reconstruction output algorithm is proposed. This algorithm is based… More >

Jing Gao^*, Mingxuan Ji, Hongjiang Wang, Zhongxiao Du

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5017-5030, 2024, DOI:10.32604/cmc.2024.050158

Abstract With the continuous advancement of China’s “peak carbon dioxide emissions and Carbon Neutrality” process, the proportion of wind power is increasing. In the current research, aiming at the problem that the forecasting model is outdated due to the continuous updating of wind power data, a short-term wind power forecasting algorithm based on Incremental Learning-Bagging Deep Hybrid Kernel Extreme Learning Machine (IL-Bagging-DHKELM) error affinity propagation cluster analysis is proposed. The algorithm effectively combines deep hybrid kernel extreme learning machine (DHKELM) with incremental learning (IL). Firstly, an initial wind power prediction model is trained using the Bagging-DHKELM… More >

Xueping Song^1,*, Jianming Yang¹, Shuyu Zhang¹, Jicun Zhang^1,2,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4551-4572, 2024, DOI:10.32604/cmc.2024.049446

Abstract To address the shortage of public datasets for customs X-ray images of contraband and the difficulties in deploying trained models in engineering applications, a method has been proposed that employs the Extract-Transform-Load (ETL) approach to create an X-ray dataset of contraband items. Initially, X-ray scatter image data is collected and cleaned. Using Kafka message queues and the Elasticsearch (ES) distributed search engine, the data is transmitted in real-time to cloud servers. Subsequently, contraband data is annotated using a combination of neural networks and manual methods to improve annotation efficiency and implemented mean hash algorithm for… More >

Jicai Guo^1,2, Xiaowen Song^1,2,*, Chang Liu^1,2, Yanfeng Zhang^1,2, Shijie Guo^1,2, Jianxin Wu^1,2, Chang Cai³, Qing’an Li^3,*

Energy Engineering, Vol.121, No.7, pp. 1739-1758, 2024, DOI:10.32604/ee.2024.048854

Abstract In winter, wind turbines are susceptible to blade icing, which results in a series of energy losses and safe operation problems. Therefore, blade icing detection has become a top priority. Conventional methods primarily rely on sensor monitoring, which is expensive and has limited applications. Data-driven blade icing detection methods have become feasible with the development of artificial intelligence. However, the data-driven method is plagued by limited training samples and icing samples; therefore, this paper proposes an icing warning strategy based on the combination of feature selection (FS), eXtreme Gradient Boosting (XGBoost) algorithm, and exponentially weighted… More >

Yang Xiong^1,2, Jianxin Liu^1,2,*, Xianhao Yi², Bangyan Xiao², Dan Wu², Biao Wu², Chunyu Gao²

Energy Engineering, Vol.121, No.7, pp. 1759-1780, 2024, DOI:10.32604/ee.2024.048536

Abstract In the heterogeneous reservoirs, CO₂ flooding easily leads to CO₂ gas channeling, which can seriously affect sweeping efficiency and reduce oil recovery. After thoroughly investigating the advantages and shortcomings of various CO₂ plugging technologies, this paper focuses on the feasibility of improving conventional water-alternating gas (WAG) through CO₂-responsive gel materials. Based on the different chemical reaction mechanisms between the unique chemical structure and CO₂, changes in the material’s physical and chemical properties can respond to CO₂. The feasibility of utilizing these property changes for CO₂-responsive plugging is explored. Various CO₂-responsive gels and gel nanoparticles have been extensively researched in More >

Yue Cao^1,2, Longsheng Bao¹, Xiaowei Zhang^1,*, Zhanfei Wang¹, Bingqian Li¹

Structural Durability & Health Monitoring, Vol.18, No.4, pp. 485-503, 2024, DOI:10.32604/sdhm.2024.049698

Abstract This study addresses the issue of inaccurate single damage fingerprint recognition during the process of bridge damage identification. To improve accuracy, the proposed approach involves fusing displacement mode difference and curvature mode difference data for single damage identification, and curvature mode difference and displacement mode wavelet coefficient difference data for two damage identification. The methodology begins by establishing a finite element model of the cable-stayed bridge and obtaining the original damage fingerprints, displacement modes, curvature modes, and wavelet coefficient differences of displacement modes through modal analysis. A fusion program based on the D-S evidence theory… More > Graphic Abstract

LINGLI ZHANG^1,2,#, YAN LI^1,#, JINGXIN MAO^1,*

BIOCELL, Vol.48, No.6, pp. 905-922, 2024, DOI:10.32604/biocell.2024.050396

Abstract Hepatocellular carcinoma (HCC) remains a prevalent and challenging malignancy globally, characterized by its numerous causal factors and generally unfavorable prognosis. In the relentless pursuit of effective treatment modalities, natural products have emerged as a promising and relatively non-toxic alternative, garnering significant interest. The integration of natural products with contemporary medical research has yielded encouraging therapeutic outcomes in the management of HCC. This review offers a comprehensive overview of the causal factors underlying HCC, and the diverse treatment options available, and highlights the advancements made by natural products in anti-HCC research. Particularly, we provide an outline More >

Xiaorui Cui¹, Shan Wang^2,*

International Journal of Mental Health Promotion, Vol.26, No.5, pp. 407-416, 2024, DOI:10.32604/ijmhp.2023.030135

Abstract Research motivation: Through the 12 weeks dance therapy intervention for children with autism, the purpose is to explore the intervention model of dance therapy for children with autism and the changes in motor ability, social ability, and communication ability of children with autism after dance therapy intervention. The results of the research are expected to expand the intervention mode of dance therapy in my country and provide practical reference for rehabilitation intervention of children with autism. Research methods: 24 autistic boys aged 6 to 12 with mild to moderate symptoms were recruited and screened through the Internet… More >