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  • Open Access

    ARTICLE

    Glycogen metabolism-mediated intercellular communication in the tumor microenvironment influences liver cancer prognosis

    YANG ZHANG1,2,#, NANNAN QIN5,#, XIJUN WANG6,#, RUI LIANG7, QUAN LIU4, RUOYI GENG8, TIANXIAO JIANG8, YUNFEI LIU8,*, JINWEI LI3,4,*

    Oncology Research, Vol.32, No.3, pp. 563-576, 2024, DOI:10.32604/or.2023.029697

    Abstract Glycogen metabolism plays a key role in the development of hepatocellular carcinoma (HCC), but the function of glycogen metabolism genes in the tumor microenvironment (TME) is still to be elucidated. Single-cell RNA-seq data were obtained from ten HCC tumor samples totaling 64,545 cells, and 65 glycogen metabolism genes were analyzed by a nonnegative matrix factorization (NMF). The prognosis and immune response of new glycogen TME cell clusters were predicted by using HCC and immunotherapy cohorts from public databases. HCC single-cell analysis was divided into fibroblasts, NT T cells, macrophages, endothelial cells, and B cells, which… More >

  • Open Access

    ARTICLE

    RPL-Based IoT Networks under Decreased Rank Attack: Performance Analysis in Static and Mobile Environments

    Amal Hkiri1,*, Mouna Karmani1, Omar Ben Bahri2, Ahmed Mohammed Murayr2, Fawaz Hassan Alasmari2, Mohsen Machhout1

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 227-247, 2024, DOI:10.32604/cmc.2023.047087

    Abstract The RPL (IPv6 Routing Protocol for Low-Power and Lossy Networks) protocol is essential for efficient communication within the Internet of Things (IoT) ecosystem. Despite its significance, RPL’s susceptibility to attacks remains a concern. This paper presents a comprehensive simulation-based analysis of the RPL protocol’s vulnerability to the decreased rank attack in both static and mobile network environments. We employ the Random Direction Mobility Model (RDM) for mobile scenarios within the Cooja simulator. Our systematic evaluation focuses on critical performance metrics, including Packet Delivery Ratio (PDR), Average End to End Delay (AE2ED), throughput, Expected Transmission Count More >

  • Open Access

    ARTICLE

    Real-Time Detection and Instance Segmentation of Strawberry in Unstructured Environment

    Chengjun Wang1,2, Fan Ding2,*, Yiwen Wang1, Renyuan Wu1, Xingyu Yao2, Chengjie Jiang1, Liuyi Ling1

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1481-1501, 2024, DOI:10.32604/cmc.2023.046876

    Abstract The real-time detection and instance segmentation of strawberries constitute fundamental components in the development of strawberry harvesting robots. Real-time identification of strawberries in an unstructured environment is a challenging task. Current instance segmentation algorithms for strawberries suffer from issues such as poor real-time performance and low accuracy. To this end, the present study proposes an Efficient YOLACT (E-YOLACT) algorithm for strawberry detection and segmentation based on the YOLACT framework. The key enhancements of the E-YOLACT encompass the development of a lightweight attention mechanism, pyramid squeeze shuffle attention (PSSA), for efficient feature extraction. Additionally, an attention-guided… More >

  • Open Access

    ARTICLE

    Novel Rifle Number Recognition Based on Improved YOLO in Military Environment

    Hyun Kwon1,*, Sanghyun Lee2

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 249-263, 2024, DOI:10.32604/cmc.2023.042466

    Abstract Deep neural networks perform well in image recognition, object recognition, pattern analysis, and speech recognition. In military applications, deep neural networks can detect equipment and recognize objects. In military equipment, it is necessary to detect and recognize rifle management, which is an important piece of equipment, using deep neural networks. There have been no previous studies on the detection of real rifle numbers using real rifle image datasets. In this study, we propose a method for detecting and recognizing rifle numbers when rifle image data are insufficient. The proposed method was designed to improve the… More >

  • Open Access

    ARTICLE

    Einstein Hybrid Structure of q-Rung Orthopair Fuzzy Soft Set and Its Application for Diagnosis of Waterborne Infectious Disease

    Rana Muhammad Zulqarnain1, Hafiz Khalil ur Rehman2, Imran Siddique3, Hijaz Ahmad4,5, Sameh Askar6, Shahid Hussain Gurmani1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1863-1892, 2024, DOI:10.32604/cmes.2023.031480

    Abstract This research is devoted to diagnosing water-borne infectious diseases caused by floods employing a novel diagnosis approach, the Einstein hybrid structure of q-rung orthopair fuzzy soft set. This approach integrates parts of fuzzy logic and soft set theory to develop a robust alternative for disease detection in stressful situations, especially in areas affected by floods. Compared to the traditional intuitionistic fuzzy soft set and Pythagorean fuzzy soft set, the q-rung orthopair fuzzy soft set (q-ROFSS) adequately incorporates unclear and indeterminate facts. The major objective of this investigation is to formulate the q-rung orthopair fuzzy soft… More >

  • Open Access

    ARTICLE

    Person Re-Identification with Model-Contrastive Federated Learning in Edge-Cloud Environment

    Baixuan Tang1,2,#, Xiaolong Xu1,2,#, Fei Dai3, Song Wang4,*

    Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 35-55, 2023, DOI:10.32604/iasc.2023.036715

    Abstract Person re-identification (ReID) aims to recognize the same person in multiple images from different camera views. Training person ReID models are time-consuming and resource-intensive; thus, cloud computing is an appropriate model training solution. However, the required massive personal data for training contain private information with a significant risk of data leakage in cloud environments, leading to significant communication overheads. This paper proposes a federated person ReID method with model-contrastive learning (MOON) in an edge-cloud environment, named FRM. Specifically, based on federated partial averaging, MOON warmup is added to correct the local training of individual edge… More >

  • Open Access

    REVIEW

    Carbon Monoxide Modulates Auxin Transport and Nitric Oxide Signaling in Plants under Iron Deficiency Stress

    Kaiyue Hong1,2, Yasmina Radani2, Waqas Ahmad2, Ping Li3, Yuming Luo1,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.1, pp. 45-61, 2024, DOI:10.32604/phyton.2023.046389

    Abstract Carbon monoxide (CO) and nitric oxide (NO) are signal molecules that enhance plant adaptation to environmental stimuli. Auxin is an essential phytohormone for plant growth and development. CO and NO play crucial roles in modulating the plant’s response to iron deficiency. Iron deficiency leads to an increase in the activity of heme oxygenase (HO) and the subsequent generation of CO. Additionally, it alters the polar subcellular distribution of Pin-Formed 1 (PIN1) proteins, resulting in enhanced auxin transport. This alteration, in turn, leads to an increase in NO accumulation. Furthermore, iron deficiency enhances the activity of… More >

  • Open Access

    ARTICLE

    Variation Characteristics of Root Traits of Different Alfalfa Cultivars under Saline-Alkaline Stress and their Relationship with Soil Environmental Factors

    Tian-Jiao Wei1, Guang Li1, Yan-Ru Cui1, Jiao Xie1, Xing-Ai Gao1, Xing Teng1, Xin-Ying Zhao1, Fa-Chun Guan1,*, Zheng-Wei Liang2,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.1, pp. 29-43, 2024, DOI:10.32604/phyton.2023.046078

    Abstract Soil salinization is the main factor that threatens the growth and development of plants and limits the increase of yield. It is of great significance to study the key soil environmental factors affecting plant root traits to reveal the adaptation strategies of plants to saline-alkaline-stressed soil environments. In this study, the root biomass, root morphological parameters and root mineral nutrient content of two alfalfa cultivars with different sensitivities to alkaline stress were analyzed with black soil as the control group and the mixed saline-alkaline soil with a ratio of 7:3 between black soil and saline-alkaline… More >

  • Open Access

    REVIEW

    The IDD Transcription Factors: Their Functions in Plant Development and Environmental Response

    Jing Liu1,*, Defeng Shu1, Zilong Tan1, Mei Ma1, Huanhuan Yang1, Ning Guo1,2, Shipeng Li1, Dayong Cui1,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.1, pp. 63-79, 2024, DOI:10.32604/phyton.2023.045940

    Abstract INDETERMINATE-DOMAIN proteins (IDDs) are a plant-specific transcription factor family characterized by a conserved ID domain with four zinc finger motifs. Previous studies have demonstrated that IDDs coordinate a diversity of physiological processes and functions in plant growth and development, including floral transition, plant architecture, seed and root development, and hormone signaling. In this review, we especially summarized the latest knowledge on the functions and working models of IDD members in Arabidopsis, rice, and maize, particularly focusing on their role in the regulatory network of biotic and abiotic environmental responses, such as gravity, temperature, water, and More >

  • Open Access

    ARTICLE

    Repair of Second-Generation Recycled Fine Aggregate of Waste Concrete from Freeze-Thaw Environment by Carbonation Treatment

    Jie Huang*, Rongbin Jiang, Xiaobo Sun, Yingyong Shuai

    Journal of Renewable Materials, Vol.12, No.1, pp. 187-201, 2024, DOI:10.32604/jrm.2023.044232

    Abstract The reuse of waste recycled concrete from harsh environments has become a research hotspot in the field of construction. This study investigated the repair effect of carbonation treatment on second-generation recycled fine aggregate (SRFA) obtained from recycled fine aggregate concrete (RFAC) subjected to freeze-thaw (FT) cycles. Before and after carbonation, the properties of SRFA were evaluated. Carbonated second-generation recycled fine aggregate (CSRFA) at five substitution rates (0%, 25%, 50%, 75%, 100%) to replace SRFA was used to prepare carbonated second-generation recycled fine aggregate concrete (CSRFAC). The water absorption, porosity and mechanical properties of CSRFAC were More >

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