Minghui Li¹, Hongbo Li^1,*, Jiaqi Zhu², Xupeng Zhang¹

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072406 - 12 January 2026

Abstract To address the challenge of real-time detection of unauthorized drone intrusions in complex low-altitude urban environments such as parks and airports, this paper proposes an enhanced MBS-YOLO (Multi-Branch Small Target Detection YOLO) model for anti-drone object detection, based on the YOLOv8 architecture. To overcome the limitations of existing methods in detecting small objects within complex backgrounds, we designed a C2f-Pu module with excellent feature extraction capability and a more compact parameter set, aiming to reduce the model’s computational complexity. To improve multi-scale feature fusion, we construct a Multi-Branch Feature Pyramid Network (MB-FPN) that employs a… More >

Yuanyuan Wang^1,*, Yemeng Zhu¹, Xiuchuan Chen¹, Tongtong Yin¹, Shiwei Su²

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072404 - 12 January 2026

Abstract To solve the false detection and missed detection problems caused by various types and sizes of defects in the detection of steel surface defects, similar defects and background features, and similarities between different defects, this paper proposes a lightweight detection model named multiscale edge and squeeze-and-excitation attention detection network (MSESE), which is built upon the You Only Look Once version 11 nano (YOLOv11n). To address the difficulty of locating defect edges, we first propose an edge enhancement module (EEM), apply it to the process of multiscale feature extraction, and then propose a multiscale edge enhancement… More >

Qian Yu^1,2, Gui Zhang^2,*, Ying Wang¹, Xin Wu², Jiangshu Xiao², Wenbing Kuang¹, Juan Zhang²

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072172 - 12 January 2026

Abstract Detecting small forest fire targets in unmanned aerial vehicle (UAV) images is difficult, as flames typically cover only a very limited portion of the visual scene. This study proposes Context-guided Compact Lightweight Network (CCLNet), an end-to-end lightweight model designed to detect small forest fire targets while ensuring efficient inference on devices with constrained computational resources. CCLNet employs a three-stage network architecture. Its key components include three modules. C3F-Convolutional Gated Linear Unit (C3F-CGLU) performs selective local feature extraction while preserving fine-grained high-frequency flame details. Context-Guided Feature Fusion Module (CGFM) replaces plain concatenation with triplet-attention interactions to… More >

Oncology Research Editorial Office

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.077270 - 30 December 2025

Abstract This article has no abstract. More >

Oncology Research Editorial Office

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.077269 - 30 December 2025

Abstract This article has no abstract. More >

Se Ha Jang^1,2,#, Hyung Seok Kim^3,#, Jung Woo Eun^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.072240 - 30 December 2025

Abstract Hepatocellular carcinoma (HCC) remains one of the most prevalent and lethal malignancies worldwide. Long non-coding RNAs (lncRNAs) have emerged as crucial regulators of gene expression and cancer progression, yet the functional diversity of RP11-derived lncRNAs—originally mapped to bacterial artificial chromosome (BAC) clones from the Roswell Park Cancer Institute—has only recently begun to be appreciated. This mini-review aims to systematically synthesize current findings on RP11-derived lncRNAs in HCC, outlining their genomic origins, molecular mechanisms, and biological significance. We highlight their roles in metabolic reprogramming, microRNA network modulation, and tumor progression, as well as their diagnostic and More >

Dongchi Cai^1,2,#, Jialin Ji^3,#, Chunhui Yang^1,*, Hong Cai^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.071152 - 30 December 2025

Abstract Metabolic reprogramming involving branched-chain amino acids (BCAAs)—leucine, isoleucine, and valine—is increasingly recognized as pivotal in cancer progression, metastasis, and immune modulation. This review comprehensively explores how cancer cells rewire BCAA metabolism to enhance proliferation, survival, and therapy resistance. Tumors manipulate BCAA uptake and catabolism via high expression of transporters like L-type amino acid transporter 1 (LAT1) and enzymes including branched chain amino acid transaminase 1(BCAT1), branched chain amino acid transaminase 2 (BCAT2), branched-chain alpha-keto acid dehydrogenase (BCKDH), and branched chain alpha-keto acid dehydrogenase kinase (BCKDK). These alterations sustain energy production, biosynthesis, redox homeostasis, and oncogenic… More >

Lv Ling^1,#, Minying Lu^2,#, Ling Ye³, Yuanhang Chen², Sheng Lin², Jun Yang², Yu Rong^2,*, Guixiong Wu^4,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.069889 - 30 December 2025

Abstract Background: A significant proportion of patients still cannot benefit from existing targeted therapies and immunotherapies, making the search for new treatment strategies extremely urgent. In this study, we combined integrate public data analysis with experimental validation to identify novel prognostic biomarkers and therapeutic targets for lung adenocarcinoma (LUAD). Methods: We analyzed RNA and protein databases to assess the expression levels of cytochrome C oxidase 5B (COX5B) in LUAD. Several computational algorithms were employed to investigate the relationship between COX5B and immune infiltration in LUAD. To further elucidate the role of COX5B in LUAD, we utilized… More > Graphic Abstract

Dike Chen^1,2,3, Zhiyong Qin², Ji Zhang², Hongyuan Wang^1,2,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-17, 2026, DOI:10.32604/cmc.2025.072494 - 09 December 2025

Abstract To address the challenges of small target detection and significant scale variations in unmanned aerial vehicle (UAV) aerial imagery, which often lead to missed and false detections, we propose Multi-scale Feature Fusion YOLO (MFF-YOLO), an enhanced algorithm based on YOLOv8s. Our approach introduces a Multi-scale Feature Fusion Strategy (MFFS), comprising the Multiple Features C2f (MFC) module and the Scale Sequence Feature Fusion (SSFF) module, to improve feature integration across different network levels. This enables more effective capture of fine-grained details and sequential multi-scale features. Furthermore, we incorporate Inner-CIoU, an improved loss function that uses auxiliary More >

Jay Barach^*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-23, 2026, DOI:10.32604/cmc.2025.071705 - 09 December 2025

Abstract Human Resource (HR) operations increasingly rely on cloud-based platforms that provide hiring, payroll, employee management, and compliance services. These systems, typically built on multi-tenant microservice architectures, offer scalability and efficiency but also expand the attack surface for adversaries. Ransomware has emerged as a leading threat in this domain, capable of halting workflows and exposing sensitive employee records. Traditional defenses such as static hardening and signature-based detection often fail to address the dynamic requirements of HR Software as a Service (SaaS), where continuous availability and privacy compliance are critical. This paper presents a Moving Target Defense… More >