Wenjian Zeng¹, Xianglong Li², Hao Cai¹, Qingyu Zhou², Shuangshuang Sun², Pingping Li², Sunlong Li¹, Zhi Chen^2,*

Oncology Research, Vol.34, No.6, 2026, DOI:10.32604/or.2026.073934 - 21 May 2026

Abstract Objectives: Cisplatin resistance is a major obstacle in the treatment of renal cell carcinoma (RCC), severely compromising therapeutic efficacy and patient prognosis. This study aimed to clarify the role and molecular mechanism of cyclin-dependent kinase 4 (CDK4) in cisplatin resistance of RCC. Methods: Immunohistochemistry (IHC) was used to detect the expression of CDK4 in cisplatin-resistant RCC tissues. In RCC cells and their drug-resistant sublines, CDK4 overexpression/knockdown assays were performed to evaluate the effects on cisplatin resistance and malignant progression. An in vivo model was established, to verify the in vivo function of CDK4. Transcriptome sequencing (RNA-seq), Cleavage Under… More >

You-Yong Tang¹, Yong-Hao Liu², Dong-Yang Wei¹, Xiao-Wei Feng², Jose Campos e Matos³, David Hui⁴, Hua-Ping Wang^1,*

Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.075676 - 18 May 2026

Abstract Carbon fiber reinforced polymer (CFRP) laminates are widely used in aerospace, new energy, and transportation engineering due to their high specific strength and stiffness. However, interlaminar delamination damage can lead to sudden structural failure, and the occurrence and prediction of such hidden defects are difficult to identify and evaluate using conventional inspection methods. To address this, smart CFRP laminates integrated with fiber Bragg grating (FBG) sensors offer a new approach for real-time structural health monitoring (SHM). Nevertheless, the influence mechanisms of the two integration methods—embedded and surface-bonded FBG sensors—on the static strength and impact resistance… More >

Chirag Devendrakumar Parikh^*

Journal on Internet of Things, Vol.8, pp. 109-125, 2026, DOI:10.32604/jiot.2026.077412 - 12 May 2026

Abstract Secure IoT ecosystems are based on the notion that device authentication is reputable. Traditional approaches typically use software identifiers or stored cryptographic keys, which can be cloned, copied, or modified by physical access or supply-chain interference. The current paper presents a hardware fingerprinting system that is based on compliance to enhance the strength of the authentication of the IoT device, that is, to connect physical device properties with organized conformity practices. The tool exploits intrinsic electrical and manufacturing differences in parts to produce device-specific fingerprints and compares these fingerprints with compliance processes, including component validation, More >

Jianping Wu¹, Nian Li^2,*, Libin Dong³, Ping Zhang⁴

Journal on Artificial Intelligence, Vol.8, pp. 259-271, 2026, DOI:10.32604/jai.2026.075753 - 12 May 2026

Abstract This paper presents a static fusion framework that enhances object detection by integrating camera and LiDAR-based detection results. The proposed method focuses on associating 2D candidate bounding boxes from a camera detector with 3D candidate boxes from a LiDAR detector using an Intersection over Union (IoU)-based matching approach. To enhance the quality of 2D detection, we refine the baseline Cascade R-CNN detector by incorporating a dual self-attention mechanism into both the backbone and the region proposal network (RPN), resulting in the DA-Cascade R-CNN. This enhancement strengthens the network’s ability to detect small or distant objects More >

Feng Lv^*, Xin Xu, Cheng Yang, Yixuan Tang

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079917 - 08 May 2026

Abstract To ensure an effective disturbance response and maintain continuous production in hybrid flow shops, this paper focuses on the design of a rescheduling method. A rescheduling model is constructed that minimizes the makespan, total tardiness, and scheme deviation degree. A hybrid rescheduling driving mechanism based on the latest completion time is designed to effectively trigger rescheduling. The Whale Optimization Algorithm (WOA) is improved by integrating the good point set theory, nonlinear control parameter strategy, and Differential Evolution (DE) algorithm. Moreover, non-dominated sorting and a dynamic external archive mechanism based on crowding distance are introduced to More >

Linbin Li¹, Ruiyuan Xue^1,*, Juyin Zhang^2,*, Xueping Wang², Tiantian Chu¹

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079732 - 08 May 2026

Abstract The plastic strain accumulation results of the multi-layered wrapped pressure vessel liner during long-term service are an important basis for its safety performance evaluation. However, the complex welds distributed on the liner bring challenges to the calculation of plastic cumulative strain. To this end, a novel hybrid deep learning framework is proposed for the efficient and precise prediction of ratcheting behavior in the liner welds of multilayered pressure vessels. By employing a BiLSTM network to extract bidirectional temporal dependencies from the strain history and incorporating a Multi-Head Attention (MHA) mechanism for adaptive feature weighting, the… More >

Feng-Cheng Lin^*, Bo-Chiao Jan, Hui-An Wu

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079393 - 08 May 2026

Abstract With the increasing refinement of ornamental fish culture, understanding fish behavioral patterns has become critical. Fish movements not only reflect daily activity ranges but also reveal responses to environmental changes such as water currents and obstacles. However, traditional manual observation is limited by manpower and time, making it difficult to record fish behaviors over long periods stably. Existing automated tracking techniques often suffer from ID switches and track interruptions caused by rapid fish movement, occlusions, or intermingling, which in turn degrade the reliability of subsequent analyses. This paper proposes a deep learning-based multi-object fish tracking… More >

Chaobin Wang^1,2, Xianghong Tang^1,2,*, Jianguang Lu^1,2, Jing Yang^1,2, Panliang Yuan^1,2

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.078998 - 08 May 2026

Abstract Mobile Edge Computing (MEC) facilitates the rapid response and energy-efficient execution of tasks on mobile devices. However, determining whether and where to offload tasks remains a significant challenge due to the constantly changing character of workloads in MEC environments. To address this issue, this paper proposes PreAlloc-A2C—a deep reinforcement learning actor-critic-based framework that calculates allocation scores by leveraging both task features (task size, required completion time, and waiting time) and server features (queue length and historical workload). This design enables fully distributed task offloading decisions without centralized coordination. Additionally, a Long Short-Term Memory (LSTM) network More >

Wenfeng Wang^1,*, Wenjie Fan¹, Fang Dong¹, Bin Zeng¹, Wenxin Yu¹, Xiangping Deng²

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.078416 - 08 May 2026

Abstract Unmanned Aerial Vehicle (UAV) image object detection has been widely applied in many fields. However, compared with ordinary natural images, UAV images often exhibit complex backgrounds, a predominance of small objects, and significant variations in target scales, which cause traditional detection algorithms to easily suffer from missed or false detections with insufficient accuracy. To address these issues, this paper proposes a novel UAV image object detection algorithm named DMA-YOLO based on the YOLOv8s model, incorporating a deep diverse branch block and multi-scale auxiliary feature. First, a DF-C2f module integrating a deep diverse branch block and… More >

Shuqiu Tan, Chunsheng Tan, Yahui Liu^*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.077982 - 08 May 2026

Abstract Multimodal sentiment analysis aims to accurately identify emotional states by comprehensively utilizing information from multiple sources such as text, audio, and visual data. However, semantic heterogeneity and temporal differences exist between different modalities, limiting the effectiveness of feature fusion. To address this issue, this paper proposes a hierarchical joint cross-modal attention and gating mechanism (HJCAG) for multimodal sentiment analysis. This method introduces a hierarchical structure, dividing modal interactions into bimodal and trimodal layers to progressively model the semantic relevance between modalities. First, deep features are extracted from text, audio, and visual modalities using pre-trained models… More >