Chi Zhang^1,#, Xi Huang^2,#, Cheng Hu¹, Bowen Tang¹, Jianjie Wu¹, Zhuolun Sun¹, Weian Zhu¹, Xiangfu Zhou¹, Hengjun Xiao^1,*, Hua Wang^1,*

Oncology Research, Vol.33, No.9, pp. 2331-2351, 2025, DOI:10.32604/or.2025.065119 - 28 August 2025

Abstract Background: U2AF homology motif kinase 1 (UHMK1) has been associated with RNA processing and protein phosphorylation, thereby influencing tumor progression. The study aimed to explore its regulatory mechanisms and biological functions in human prostate cancer (PCa). Methods: In this study, we systematically evaluated the expression and prognostic significance of UHMK1 in public databases, followed by validation through immunohistochemistry (IHC) in PCa specimens. Both gain-of-function and loss-of-function experiments were conducted to elucidate the role of UHMK1 in vitro and in vivo. Additionally, a series of molecular and biochemical assays were performed to investigate the regulatory mechanisms underlying UHMK1… More >

Chunlai Du^1,#, Xin Gu^1,#, Yanhui Guo^2,*, Siqi Guo³, Ziwei Pang³, Yi Du³, Guoqing Du^3,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3435-3450, 2025, DOI:10.32604/cmc.2025.060212 - 16 April 2025

Abstract Coronary artery disease is a highly lethal cardiovascular condition, making early diagnosis crucial for patients. Echocardiograph is employed to identify coronary heart disease (CHD). However, due to issues such as fuzzy object boundaries, complex tissue structures, and motion artifacts in ultrasound images, it is challenging to detect CHD accurately. This paper proposes an improved Transformer model based on the Feedback Self-Attention Mechanism (FSAM) for classification of ultrasound images. The model enhances attention weights, making it easier to capture complex features. Experimental results show that the proposed method achieves high levels of accuracy, recall, precision, F1 More >

Phan-Anh-Huy Nguyen^*, Luu-Luyen Than

Intelligent Automation & Soft Computing, Vol.40, pp. 221-234, 2025, DOI:10.32604/iasc.2025.058976 - 14 April 2025

Abstract The burgeoning e-commerce industry has made online customer reviews a crucial source of feedback for businesses. Sentiment analysis, a technique used to extract subjective information from text, has become essential for understanding consumer sentiment and preferences. However, traditional sentiment analysis methods often struggle with the nuances and context of natural language. To address these issues, this study proposes a comparison of deep learning models that figure out the optimal method to accurately analyze consumer reviews on women's clothing. CNNs excel at capturing local features and semantic information, while LSTMs are adept at handling long-range dependencies… More >

Min Liu¹, Qiliang Wu¹, Zhixin Li², Bo Zhao¹, Leiqi Zhang¹, Junhui Li², Xingxu Zhu^2,*

Energy Engineering, Vol.122, No.4, pp. 1403-1424, 2025, DOI:10.32604/ee.2025.060256 - 31 March 2025

Abstract To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms, an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is proposed. First, considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage, an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage system. Next, an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with… More >

Libo Han^1,2, Sha Tao^1,2, Wen Xia³, Weixin Sun³, Li Yan³, Wanlin Gao^1,2,3,*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2431-2449, 2025, DOI:10.32604/cmc.2024.057833 - 17 February 2025

Abstract At present, salient object detection (SOD) has achieved considerable progress. However, the methods that perform well still face the issue of inadequate detection accuracy. For example, sometimes there are problems of missed and false detections. Effectively optimizing features to capture key information and better integrating different levels of features to enhance their complementarity are two significant challenges in the domain of SOD. In response to these challenges, this study proposes a novel SOD method based on multi-strategy feature optimization. We propose the multi-size feature extraction module (MSFEM), which uses the attention mechanism, the multi-level feature… More >

Dianlang Wang¹, Qi Yin¹, Haifeng Wang¹, Jing Chen¹, Hong Miao², Yihan Chen^2,*

Energy Engineering, Vol.122, No.2, pp. 651-666, 2025, DOI:10.32604/ee.2025.057670 - 31 January 2025

Abstract As the penetration rate of distributed energy increases, the transient power angle stability problem of the virtual synchronous generator (VSG) has gradually become prominent. In view of the situation that the grid impedance ratio (R/X) is high and affects the transient power angle stability of VSG, this paper proposes a VSG transient power angle stability control strategy based on the combination of frequency difference feedback and virtual impedance. To improve the transient power angle stability of the VSG, a virtual impedance is adopted in the voltage loop to adjust the impedance ratio R/X; and the… More >

Jiawei Tian¹, Yu Zhou¹, Lirong Yin^2,*, Salman A. AlQahtani³, Minyi Tang⁴, Siyu Lu⁴, Ruiyang Wang⁴, Wenfeng Zheng^3,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 973-1019, 2025, DOI:10.32604/cmes.2024.057261 - 27 January 2025

Abstract Force feedback bilateral teleoperation represents a pivotal advancement in control technology, finding widespread application in hazardous material transportation, perilous environments, space and deep-sea exploration, and healthcare domains. This paper traces the evolutionary trajectory of force feedback bilateral teleoperation from its conceptual inception to its current complexity. It elucidates the fundamental principles underpinning interaction forces and tactile exchanges, with a specific emphasis on the crucial role of tactile devices. In this review, a quantitative analysis of force feedback bilateral teleoperation development trends from 2011 to 2024 has been conducted, utilizing published journal article data as the… More >

Jianwei Zhang^1,2,*, Zhishang Zhao³, Zengyu Cai³, Yuan Feng⁴, Liang Zhu³, Yahui Sun³

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 977-996, 2025, DOI:10.32604/cmc.2024.058438 - 03 January 2025

Abstract The rapid development of short video platforms poses new challenges for traditional recommendation systems. Recommender systems typically depend on two types of user behavior feedback to construct user interest profiles: explicit feedback (interactive behavior), which significantly influences users’ short-term interests, and implicit feedback (viewing time), which substantially affects their long-term interests. However, the previous model fails to distinguish between these two feedback methods, leading it to predict only the overall preferences of users based on extensive historical behavior sequences. Consequently, it cannot differentiate between users’ long-term and short-term interests, resulting in low accuracy in describing… More >

Xianju Gao^*, Huachun Zhou, Weilin Wang, Jingfu Yan

Computer Systems Science and Engineering, Vol.49, pp. 19-48, 2025, DOI:10.32604/csse.2024.058327 - 03 January 2025

Abstract The network security knowledge base standardizes and integrates network security data, providing a reliable foundation for real-time network security protection solutions. However, current research on network security knowledge bases mainly focuses on their construction, while the potential to optimize intelligent security services for real-time network security protection requires further exploration. Therefore, how to effectively utilize the vast amount of historical knowledge in the field of network security and establish a feedback mechanism to update it in real time, thereby enhancing the detection capability of security services against malicious traffic, has become an important issue. Our… More >

Musulmon Lolaev, Anand Paul^*, Jeonghong Kim

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4707-4726, 2024, DOI:10.32604/cmc.2024.058675 - 19 December 2024

Abstract Evaluating artificial intelligence (AI) systems is crucial for their successful deployment and safe operation in real-world applications. The assessor meta-learning model has been recently introduced to assess AI system behaviors developed from emergent characteristics of AI systems and their responses on a test set. The original approach lacks covering continuous ranges, for example, regression problems, and it produces only the probability of success. In this work, to address existing limitations and enhance practical applicability, we propose an assessor feedback mechanism designed to identify and learn from AI system errors, enabling the system to perform the More >