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  • Open Access

    RETRACTION

    Retraction: Downregulation of microRNA-135 promotes sensitivity of non-small cell lung cancer to gefitinib by targeting TRIM16

    Oncology Research Editorial Office

    Oncology Research, Vol.32, No.11, pp. 1813-1813, 2024, DOI:10.32604/or.2024.056888 - 16 October 2024

    Abstract This article has no abstract. More >

  • Open Access

    COMMENTARY

    Redefining the tumor microenvironment with emerging therapeutic strategies

    SULING XU1, XIAO LI2, WENXUE MA3,*

    Oncology Research, Vol.32, No.11, pp. 1701-1708, 2024, DOI:10.32604/or.2024.055161 - 16 October 2024

    Abstract The environment surrounding a tumor, known as the tumor microenvironment (TME), plays a role in how cancer progresses and responds to treatment. It poses both challenges and opportunities for improving cancer therapy. Recent progress in understanding the TME complexity and diversity has led to approaches for treating cancer. This perspective discusses the strategies for targeting the TME, such as adjusting networks using extracellular vesicles to deliver drugs and enhancing immune checkpoint inhibitors (ICIS) through combined treatments. Furthermore, it highlights adoptive cell transfer (ACT) therapies as an option for tumors. By studying how components of the More >

  • Open Access

    ARTICLE

    MiR-150-5p inhibits cell proliferation and metastasis by targeting FTO in osteosarcoma

    LICHEN XU1,2, PAN ZHANG3,*, GUIQI ZHANG2, ZHAOLIANG SHEN4, XIZHUANG BAI1,3,*

    Oncology Research, Vol.32, No.11, pp. 1777-1789, 2024, DOI:10.32604/or.2024.047704 - 16 October 2024

    Abstract Background: Osteosarcoma (OS), recognized as the predominant malignant tumor originating from bones, necessitates an in-depth comprehension of its intrinsic mechanisms to pinpoint novel therapeutic targets and enhance treatment methodologies. The role of fat mass and obesity-associated (FTO) in OS, particularly its correlation with malignant traits, and the fundamental mechanism, remains to be elucidated. Materials and Methods: 1. The FTO expression and survival rate in tumors were analyzed. 2. FTO in OS cell lines was quantified utilizing western blot and PCR. 3. FTO was upregulated and downregulated separately in MG63. 4. The impact of FTO on the… More >

  • Open Access

    ARTICLE

    LQTTrack: Multi-Object Tracking by Focusing on Low-Quality Targets Association

    Suya Li1, Ying Cao1,*, Hengyi Ren2, Dongsheng Zhu3, Xin Xie1

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1449-1470, 2024, DOI:10.32604/cmc.2024.056824 - 15 October 2024

    Abstract Multi-object tracking (MOT) has seen rapid improvements in recent years. However, frequent occlusion remains a significant challenge in MOT, as it can cause targets to become smaller or disappear entirely, resulting in low-quality targets, leading to trajectory interruptions and reduced tracking performance. Different from some existing methods, which discarded the low-quality targets or ignored low-quality target attributes. LQTTrack, with a low-quality association strategy (LQA), is proposed to pay more attention to low-quality targets. In the association scheme of LQTTrack, firstly, multi-scale feature fusion of FPN (MSFF-FPN) is utilized to enrich the feature information and assist… More >

  • Open Access

    ARTICLE

    Adversarial Defense Technology for Small Infrared Targets

    Tongan Yu1, Yali Xue1,*, Yiming He1, Shan Cui2, Jun Hong2

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1235-1250, 2024, DOI:10.32604/cmc.2024.056075 - 15 October 2024

    Abstract With the rapid development of deep learning-based detection algorithms, deep learning is widely used in the field of infrared small target detection. However, well-designed adversarial samples can fool human visual perception, directly causing a serious decline in the detection quality of the recognition model. In this paper, an adversarial defense technology for small infrared targets is proposed to improve model robustness. The adversarial samples with strong migration can not only improve the generalization of defense technology, but also save the training cost. Therefore, this study adopts the concept of maximizing multidimensional feature distortion, applying noise… More >

  • Open Access

    ARTICLE

    Path Planning of Multi-Axis Robotic Arm Based on Improved RRT*

    Juanling Liang1, Wenguang Luo1,2,*, Yongxin Qin1

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1009-1027, 2024, DOI:10.32604/cmc.2024.055883 - 15 October 2024

    Abstract An improved RRT* algorithm, referred to as the AGP-RRT* algorithm, is proposed to address the problems of poor directionality, long generated paths, and slow convergence speed in multi-axis robotic arm path planning. First, an adaptive biased probabilistic sampling strategy is adopted to dynamically adjust the target deviation threshold and optimize the selection of random sampling points and the direction of generating new nodes in order to reduce the search space and improve the search efficiency. Second, a gravitationally adjustable step size strategy is used to guide the search process and dynamically adjust the step-size to… More >

  • Open Access

    ARTICLE

    Cross-Target Stance Detection with Sentiments-Aware Hierarchical Attention Network

    Kelan Ren, Facheng Yan, Honghua Chen, Wen Jiang, Bin Wei, Mingshu Zhang*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 789-807, 2024, DOI:10.32604/cmc.2024.055624 - 15 October 2024

    Abstract The task of cross-target stance detection faces significant challenges due to the lack of additional background information in emerging knowledge domains and the colloquial nature of language patterns. Traditional stance detection methods often struggle with understanding limited context and have insufficient generalization across diverse sentiments and semantic structures. This paper focuses on effectively mining and utilizing sentiment-semantics knowledge for stance knowledge transfer and proposes a sentiment-aware hierarchical attention network (SentiHAN) for cross-target stance detection. SentiHAN introduces an improved hierarchical attention network designed to maximize the use of high-level representations of targets and texts at various… More > Graphic Abstract

    Cross-Target Stance Detection with Sentiments-Aware Hierarchical Attention Network

  • Open Access

    ARTICLE

    Obstacle Avoidance Capability for Multi-Target Path Planning in Different Styles of Search

    Mustafa Mohammed Alhassow1,*, Oguz Ata2, Dogu Cagdas Atilla1

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 749-771, 2024, DOI:10.32604/cmc.2024.055592 - 15 October 2024

    Abstract This study investigates robot path planning for multiple agents, focusing on the critical requirement that agents can pursue concurrent pathways without collisions. Each agent is assigned a task within the environment to reach a designated destination. When the map or goal changes unexpectedly, particularly in dynamic and unknown environments, it can lead to potential failures or performance degradation in various ways. Additionally, priority inheritance plays a significant role in path planning and can impact performance. This study proposes a Conflict-Based Search (CBS) approach, introducing a unique hierarchical search mechanism for planning paths for multiple robots.… More >

  • Open Access

    ARTICLE

    An Aerial Target Recognition Algorithm Based on Self-Attention and LSTM

    Futai Liang1,2, Xin Chen1,*, Song He1, Zihao Song1, Hao Lu3

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1101-1121, 2024, DOI:10.32604/cmc.2024.055326 - 15 October 2024

    Abstract In the application of aerial target recognition, on the one hand, the recognition error produced by the single measurement of the sensor is relatively large due to the impact of noise. On the other hand, it is difficult to apply machine learning methods to improve the intelligence and recognition effect due to few or no actual measurement samples. Aiming at these problems, an aerial target recognition algorithm based on self-attention and Long Short-Term Memory Network (LSTM) is proposed. LSTM can effectively extract temporal dependencies. The attention mechanism calculates the weight of each input element and… More >

  • Open Access

    ARTICLE

    Data-Driven Decision-Making for Bank Target Marketing Using Supervised Learning Classifiers on Imbalanced Big Data

    Fahim Nasir1, Abdulghani Ali Ahmed1,*, Mehmet Sabir Kiraz1, Iryna Yevseyeva1, Mubarak Saif2

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1703-1728, 2024, DOI:10.32604/cmc.2024.055192 - 15 October 2024

    Abstract Integrating machine learning and data mining is crucial for processing big data and extracting valuable insights to enhance decision-making. However, imbalanced target variables within big data present technical challenges that hinder the performance of supervised learning classifiers on key evaluation metrics, limiting their overall effectiveness. This study presents a comprehensive review of both common and recently developed Supervised Learning Classifiers (SLCs) and evaluates their performance in data-driven decision-making. The evaluation uses various metrics, with a particular focus on the Harmonic Mean Score (F-1 score) on an imbalanced real-world bank target marketing dataset. The findings indicate… More >

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