Conghao Niu^1,*, Dezhi Han¹, Bing Han², Zhongdai Wu²

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1723-1748, 2024, DOI:10.32604/csse.2024.056736 - 22 November 2024

Abstract The high coverage and all-weather capabilities of Synthetic Aperture Radar (SAR) image ship detection make it a widely accepted method for maritime ship positioning and identification. However, SAR ship detection faces challenges such as indistinct ship contours, low resolution, multi-scale features, noise, and complex background interference. This paper proposes a lightweight YOLOv8 model for small object detection in SAR ship images, incorporating key structures to enhance performance. The YOLOv8 backbone is replaced by the Slim Backbone (SB), and the Delete Medium-sized Detection Head (DMDH) structure is eliminated to concentrate on shallow features. Dynamically adjusting the… More >

Monirah Al-Ajlan^*, Mourad Ykhlef

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2053-2076, 2024, DOI:10.32604/cmc.2024.055891 - 18 November 2024

Abstract The ever-growing network traffic threat landscape necessitates adopting accurate and robust intrusion detection systems (IDSs). IDSs have become a research hotspot and have seen remarkable performance improvements. Generative adversarial networks (GANs) have also garnered increasing research interest recently due to their remarkable ability to generate data. This paper investigates the application of (GANs) in (IDS) and explores their current use within this research field. We delve into the adoption of GANs within signature-based, anomaly-based, and hybrid IDSs, focusing on their objectives, methodologies, and advantages. Overall, GANs have been widely employed, mainly focused on solving the More >

WEITAO ZHENG¹, DONG JIANG², SONGEN CHEN¹, MEILING WU¹, BAOQI YAN², JIAHUI ZHAI², YUNQIANG SHI², BIN XIE¹, XINGWANG XIE², KANGHONG HU^1,*, WENXUE MA^3,*

Oncology Research, Vol.32, No.12, pp. 1837-1850, 2024, DOI:10.32604/or.2024.056565 - 13 November 2024

Abstract Objectives: The Kirsten rat sarcoma virus (KRAS) G12D oncogenic mutation poses a significant challenge in treating solid tumors due to the lack of specific and effective therapeutic interventions. This study aims to explore innovative approaches in T cell receptor (TCR) engineering and characterization to target the KRAS G12D_7-16 mutation, providing potential strategies for overcoming this therapeutic challenge. Methods: In this innovative study, we engineered and characterized two T cell receptors (TCRs), KDA11-01 and KDA11-02 with high affinity for the KRAS G12D_7-16 mutation. These TCRs were isolated from tumor-infiltrating lymphocytes (TILs) derived from tumor tissues of patients More >

SAM SON¹, AKSHAAR BRAHMBHATT¹, KEN ZHAO¹, BRETT MARINELLI¹, JAMES HARDING², WILLIAM JARNAGIN³, GHASSAN K. ABOU-ALFA², HOOMAN YARMOHAMMADI^1,*

Oncology Research, Vol.32, No.12, pp. 1831-1836, 2024, DOI:10.32604/or.2024.052985 - 13 November 2024

Abstract Background: This article aims to present the single-institution outcomes of patients with Fibrolamellar Carcinoma (FLC) treated with liver-directed therapies (LDT). Methods: In this single-center retrospective study, all patients diagnosed with FLC who underwent LDT were identified. Between July 2012 and July 2023, six patients were identified. One patient was excluded due to bleeding. Demographic and clinical parameters were recorded. Complications within 30 days of the LDT were evaluated. Radiological treatment responses at 1, 6, and 12 months were assessed per mRECIST. Results: A total of five patients, which included three females and two males, were reviewed.… More >

Qingrong Zeng, Xiaochen Liu, Xuefeng Zhu^*, Xiangkui Zhang, Ping Hu

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2065-2085, 2024, DOI:10.32604/cmes.2024.052620 - 31 October 2024

Abstract Traditional topology optimization methods often suffer from the “dimension curse” problem, wherein the computation time increases exponentially with the degrees of freedom in the background grid. Overcoming this challenge, we introduce a real-time topology optimization approach leveraging Conditional Generative Adversarial Networks with Gradient Penalty (CGAN-GP). This innovative method allows for nearly instantaneous prediction of optimized structures. Given a specific boundary condition, the network can produce a unique optimized structure in a one-to-one manner. The process begins by establishing a dataset using simulation data generated through the Solid Isotropic Material with Penalization (SIMP) method. Subsequently, we More >

Laviza Falak Naz¹, Rohail Qamar^2,*, Raheela Asif¹, Muhammad Imran², Saad Ahmed³

Intelligent Automation & Soft Computing, Vol.39, No.5, pp. 855-887, 2024, DOI:10.32604/iasc.2024.055074 - 31 October 2024

Abstract Domain shift is when the data used in training does not match the ones it will be applied to later on under similar conditions. Domain shift will reduce accuracy in results. To prevent this, domain adaptation is done, which adapts the pre-trained model to the target domain. In real scenarios, the availability of labels for target data is rare thus resulting in unsupervised domain adaptation. Herein, we propose an innovative approach where source-free domain adaptation models and Generative Adversarial Networks (GANs) are integrated to improve the performance of computer vision or robotic vision-based systems in… More >

Hossam S. El-Beltagi^1,2,*, Mohamed Fathi El-Nady³, Adel A. Rezk^1,4, Abdelaziz M. Tahoon⁵, Mohammed I. Al-Daej¹, Dina Abdulmajid⁶, Mohamed M. El-Mogy⁷, Elsayed Abd Elmaksoud Abomarzoka⁸, Sherif Mohamed El-Ganainy^7,9, Metwaly Mahfouz Salem Metwaly³

Phyton-International Journal of Experimental Botany, Vol.93, No.10, pp. 2535-2556, 2024, DOI:10.32604/phyton.2024.056734 - 30 October 2024

Abstract Rice (Oryza sativa L.) is one of the most important cereal crops in the world. Bakanae disease is a significant rice disease widely distributed in rice-growing regions worldwide. Therefore, the present investigation aimed to assess the optimal concentrations of paclobutrazol (PBZ) as a treatment for rice grains (cv. Sakha 108) to control bakanae disease, also evaluating its impact on grain germination, seedling growth parameters as well as disease index. Paclobutrazol concentrations had no significant impact on seed germination, regardless of whether the seeds were incubated with Fusarium fujikuroi or not. Application of PBZ, either alone or in… More >

Oncology Research Editorial Office

Oncology Research, Vol.32, No.11, pp. 1815-1815, 2024, DOI:10.32604/or.2024.056890 - 16 October 2024

Abstract This article has no abstract. More >

LICHEN XU^1,2, PAN ZHANG^3,*, GUIQI ZHANG², ZHAOLIANG SHEN⁴, XIZHUANG BAI^1,3,*

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 >

Lechan Yang^1,*, Li Li², Shouming Ma³

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1471-1489, 2024, DOI:10.32604/cmc.2024.056379 - 15 October 2024

Abstract Accurate geospatial data are essential for geographic information systems (GIS), environmental monitoring, and urban planning. The deep integration of the open Internet and geographic information technology has led to increasing challenges in the integrity and security of spatial data. In this paper, we consider abnormal spatial data as missing data and focus on abnormal spatial data recovery. Existing geospatial data recovery methods require complete datasets for training, resulting in time-consuming data recovery and lack of generalization. To address these issues, we propose a GAIN-LSTM-based geospatial data recovery method (TGAIN), which consists of two main works:… More >