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| 1 | Preparation and biological characterization of cellulose graft copolymers显示文摘 | Dahou W Ghemati D Oudia A | 2010 | Biochemical Engineering Journal2010，，48： | 1 |
| 2 | Experimental and numerical investigations on transient creep of porous chalk显示文摘 | A Dahou J F Shao M Bederiat | 1995 | Mechanics of Materials1995，，21： | 1 |
| 3 | Experimental and numerical investigations on transient creep of porous chalk显示文摘 | A Dahou J F Shao M Bederiat | 1995 | Mechanics of Materials1995，，21： | 1 |
| 4 | Experimental and Numerical Investigations on Transient Creep of Porous Chalk显示文摘 | Dahou A Shao J F Bederiat M | 1995 | Mechanics of Materials1995，21，2： | 1 |
| 5 | 查看详情显示文摘 | Cattin L Dahou F Lare Y | | 0，，： | 1 |
| 6 | Preparation and biological characterization of cellulose graft copolymers显示文摘 | Dahou W Ghemati D Oudia A | 2010 | Biochemical Engineering Journal2010，，2： | 1 |
| 7 | Preparation and biological characterization of cellulose graft copolymers 显示文摘 | DAHOU W GHEMATI D OUDIA A | 2010 | Biochemical Engineering Journal2010，，48： | 1 |
| 8 | Preparation and Bio- logical Characterization of Cellulose Graft Copolyrners显示文摘 | Dahou W Ghemati D Oudia A | 2010 | BiochemEngJ2010，48，2： | 1 |
| 9 | Experimental and numerical investigations on transient creep of porous chalk显示文摘 | Dahou A Shao J F Bederiat M | 1995 | Mechanics of Materials1995，21，1： | 1 |
| 10 | MoO3 surface passivation of the transparent anode in organic solar cells using ultrathin films 显示文摘 | Cattin L Dahou F Lare Y | 2009 | Journal of Applied Physics2009，105，3： | 1 |
| 11 | Experimental study on the strength and ductility of steel tubular columns filled with steel-reinforced concrete 显示文摘 | WANG Qingxiang ZHAO Dahou GUAN Ping | 2004 | Journal of Engineering Structures2004，26，2： | 1 |
| 12 | Experimental and numerical investigations on transient creep of porous chalk 显示文摘 | Dahou A Shao J F Bederiat M | 1995 | Mechanics of Materials1995，21，： | 1 |
| 13 | Secretive derived from hypoxia preconditioned mesenchymal stem cells promote cartilage regeneration and mitigate joint inflammation via extracellular vesicles显示文摘Secretome derived from mesenchymal stem cells (MSCs) have profound effects on tissue regeneration, which could become the basis of future MSCs therapies. Hypoxia, as the physiologic environment of MSCs, has great potential to enhance MSCs paracrine therapeutic effect. In our study, the paracrine effects of secretome derived from MSCs preconditioned in normoxia and hypoxia was compared through both in vitro functional assays and an in vivo rat osteochondral defect model. Specifically, the paracrine effect of total EVs were compared to that of soluble factors to characterize the predominant active components in the hypoxic secretome. We demonstrated that hypoxia conditioned medium, as well as the corresponding EVs, at a relatively low dosage, were efficient in promoting the repair of critical-sized osteochondral defects and mitigated the joint inflammation in a rat osteochondral defect model, relative to their normoxia counterpart. In vitro functional test shows enhancement through chondrocyte proliferation, migration, and matrix deposition, while inhibit IL-1β-induced chondrocytes senescence, inflammation, matrix degradation, and pro-inflammatory macrophage activity. Multiple functional proteins, as well as a change in EVs’ size profile, with enrichment of specific EV-miRNAs were detected with hypoxia preconditioning, implicating complex molecular pathways involved in hypoxia pre-conditioned MSCs secretome generated cartilage regeneration. | Yanmeng Yang Yingnan Wu Dahou Yang Shu Hui Neo Nurul Dinah Kadir Doreen Goh Jian Xiong Tan Vinitha Denslin Eng Hin Lee Zheng Yang | 2023 | Bioactive Materials2023，，9： | 0 |
| 14 | Terrorism Attack Classification Using Machine Learning: The Effectiveness of Using Textual Features Extracted from GTD Dataset显示文摘One of the biggest dangers to society today is terrorism, where attacks have become one of the most significantrisks to international peace and national security. Big data, information analysis, and artificial intelligence (AI) havebecome the basis for making strategic decisions in many sensitive areas, such as fraud detection, risk management,medical diagnosis, and counter-terrorism. However, there is still a need to assess how terrorist attacks are related,initiated, and detected. For this purpose, we propose a novel framework for classifying and predicting terroristattacks. The proposed framework posits that neglected text attributes included in the Global Terrorism Database(GTD) can influence the accuracy of the model’s classification of terrorist attacks, where each part of the datacan provide vital information to enrich the ability of classifier learning. Each data point in a multiclass taxonomyhas one or more tags attached to it, referred as “related tags.” We applied machine learning classifiers to classifyterrorist attack incidents obtained from the GTD. A transformer-based technique called DistilBERT extracts andlearns contextual features from text attributes to acquiremore information from text data. The extracted contextualfeatures are combined with the “key features” of the dataset and used to perform the final classification. Thestudy explored different experimental setups with various classifiers to evaluate the model’s performance. Theexperimental results show that the proposed framework outperforms the latest techniques for classifying terroristattacks with an accuracy of 98.7% using a combined feature set and extreme gradient boosting classifier. | Mohammed Abdalsalam Chunlin Li Abdelghani Dahou Natalia Kryvinska | 2024 | Computer Modeling in Engineering & Sciences2024，138，2： | 0 |
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