Mingguan Zhao^1,4, Lida Liao^2,*, Penglong Liang¹, Meng Li¹, Xinsheng Dong¹, Yang Yang¹, Hongxia Wang¹, Zhenhao Zhang³

Energy Engineering, Vol.121, No.8, pp. 2313-2330, 2024, DOI:10.32604/ee.2024.048261

Abstract The rapid growth of distributed renewable energy penetration is promoting the evolution of the energy system toward decentralization and decentralized and digitized smart grids. This study was based on energy blockchain, and developed a dual-biding mechanism based on the real-time energy surplus and demand in the local smart grid, which is expected to enable reliable, affordable, and clean energy supply in smart communities. In the proposed system, economic benefits could be achieved by replacing fossil-fuel-based electricity with the high penetration of affordable solar PV electricity. The reduction of energy surplus realized by distributed energy production More >

Lin Chen¹, Jiaming Zhu¹, Yuting Xu¹, Huanqin Zheng¹, Shen Su^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2373-2395, 2024, DOI:10.32604/cmes.2024.049996

Abstract In the information age, electronic documents (e-documents) have become a popular alternative to paper documents due to their lower costs, higher dissemination rates, and ease of knowledge sharing. However, digital copyright infringements occur frequently due to the ease of copying, which not only infringes on the rights of creators but also weakens their creative enthusiasm. Therefore, it is crucial to establish an e-document sharing system that enforces copyright protection. However, the existing centralized system has outstanding vulnerabilities, and the plagiarism detection algorithm used cannot fully detect the context, semantics, style, and other factors of the… More >

Tianyu Wang^1,2, Kongyang Chen^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2297-2314, 2024, DOI:10.32604/cmes.2024.049964

Abstract Crowdsourcing holds broad applications in information acquisition and dissemination, yet encounters challenges pertaining to data quality assessment and user reputation management. Reputation mechanisms stand as crucial solutions for appraising and updating participant reputation scores, thereby elevating the quality and dependability of crowdsourced data. However, these mechanisms face several challenges in traditional crowdsourcing systems: 1) platform security lacks robust guarantees and may be susceptible to attacks; 2) there exists a potential for large-scale privacy breaches; and 3) incentive mechanisms relying on reputation scores may encounter issues as reputation updates hinge on task demander evaluations, occasionally lacking… More >

Huang Zeng, Mingtian Zhang, Tengfei Liu, Anjia Yang^*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5125-5142, 2024, DOI:10.32604/cmc.2024.052846

Abstract Federated learning is an important distributed model training technique in Internet of Things (IoT), in which participant selection is a key component that plays a role in improving training efficiency and model accuracy. This module enables a central server to select a subset of participants to perform model training based on data and device information. By doing so, selected participants are rewarded and actively perform model training, while participants that are detrimental to training efficiency and model accuracy are excluded. However, in practice, participants may suspect that the central server may have miscalculated and thus… More >

Yuanyao Lu^1,*, Wei Chen², Zhanhe Yu¹, Jingxuan Wang¹, Chaochao Yang²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5051-5066, 2024, DOI:10.32604/cmc.2024.050865

Abstract With the rapid advancement of social economies, intelligent transportation systems are gaining increasing attention. Central to these systems is the detection of abnormal vehicle behavior, which remains a critical challenge due to the complexity of urban roadways and the variability of external conditions. Current research on detecting abnormal traffic behaviors is still nascent, with significant room for improvement in recognition accuracy. To address this, this research has developed a new model for recognizing abnormal traffic behaviors. This model employs the R3D network as its core architecture, incorporating a dense block to facilitate feature reuse. This… More >

Jane Kim¹, Soojin Lee¹, Chan Yeob Yeun², Seung-Hyun Seo^1,3,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3495-3518, 2024, DOI:10.32604/cmc.2024.050461

Abstract As big data, Artificial Intelligence, and Vehicle-to-Everything (V2X) communication have advanced, Intelligent Transportation Systems (ITS) are being developed to enable efficient and safe transportation systems. Electronic Toll Collection (ETC), which is one of the services included in ITS systems, is an automated system that allows vehicles to pass through toll plazas without stopping for manual payment. The ETC system is widely deployed on highways due to its contribution to stabilizing the overall traffic system flow. To ensure secure and efficient toll payments, designing a distributed model for sharing toll payment information among untrusted toll service… More >

Chunhui Li^1,*, Hua Jiang²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4491-4512, 2024, DOI:10.32604/cmc.2024.048431

Abstract In the context of enterprise systems, intrusion detection (ID) emerges as a critical element driving the digital transformation of enterprises. With systems spanning various sectors of enterprises geographically dispersed, the necessity for seamless information exchange has surged significantly. The existing cross-domain solutions are challenged by such issues as insufficient security, high communication overhead, and a lack of effective update mechanisms, rendering them less feasible for prolonged application on resource-limited devices. This study proposes a new cross-domain collaboration scheme based on federated chains to streamline the server-side workload. Within this framework, individual nodes solely engage in… More >

Tao Wang, Fan Shi, JiQuan Wang, Zi Liu, Jin Su

Oncology Research, Vol.25, No.5, pp. 809-817, 2017, DOI:10.3727/096504016X14799180778233

Abstract Kallistatin has been recognized as an endogenous angiogenesis inhibitor and exerts pleiotropic effects in inhibiting tumor growth, migration, apoptosis, and inflammation. The purpose of the present study was to investigate the potential role and mechanisms of kallistatin in cervical cancer. We demonstrated that kallistatin effectively inhibited cell proliferation and enhanced apoptosis in a dose-dependent manner. Additionally, kallistatin suppressed migration and invasion activities and markedly reduced the expression of matrix-degrading metalloproteinases, progelatinase (MMP-2), MMP-9, and urokinase-type PA (uPA). Kallistatin reversed the epithelial–mesenchymal transition (EMT) and caused the upregulation of epithelial markers such as E-cadherin and inhibited… More >

Xuyang Wen^*, Xiaoping He^†, Feng Jiao^‡, Chunhui Wang^§, Yang Sun^‡, Xuequn Ren^¶, Qianwen Li^*

Oncology Research, Vol.25, No.4, pp. 629-640, 2017, DOI:10.3727/096504016X14768383625385

Abstract Gastric cancer (GC) is one of the main causes of cancer death. The tumor microenvironment has a profound effect on inducing tumor growth, metastasis, and immunosuppression. Fibroblast activation protein-a (FAP) is a protein that is usually expressed in fibroblasts, such as cancer-associated fibroblasts, which are major components of the tumor microenvironment. However, the role of FAP in GC progression and treatment is still unknown. In this study, we explored these problems based on GC patient samples and experimental models. We found that high FAP expression was an independent prognosticator of poor survival in GC patients. More >

Xiaolin Miao^*1, Yiqi Chen^*1, Ke Hao^†1, Meiqin Zheng^‡, Bingyu Chen^†, Kaiqiang Li^†, Ying Wang^†, Wei Zhang^§, Yu Zhang^§, Xiaozhou Mou^§, Shanshan Jiang^¶, Zhen Wang^‡§

Oncology Research, Vol.26, No.2, pp. 173-182, 2018, DOI:10.3727/096504017X14841698396865

Abstract Glioblastoma is a lethal disease featuring a high proliferation of tumor cells, excessive angiogenesis, and heavy drug resistance. The overall survival of glioblastoma patients has been dismal, even with an intensive standard of care. Recent advances in immune checkpoint blockades are changing the treatment of cancers. However, the efficacy of immune checkpoint blockades in glioblastoma is still unclear. Here we investigated the roles of CD103⁺ cells in regulating the effect of immune checkpoint blockades in glioblastoma mouse models. Our findings indicated that the murine glioblastoma model was not sensitive to immune checkpoint blockades. Flt3L, a growth More >