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    A hybrid scaffold of gelatin glycosaminoglycan matrix and fibrin as a carrier of human corneal fibroblast cells

    , Article Materials Science and Engineering C ; Volume 118 , 2021 ; 09284931 (ISSN) Hajian Foroushani, Z ; Mahdavi salimi, S ; Abdekhodaie, M. J ; Baradaran Rafii, A ; Tabatabei, M. R ; Mehrvar, M ; Sharif University of Technology
    Elsevier Ltd  2021
    A hybrid scaffold of gelatin-glycosaminoglycan matrix and fibrin (FGG) has been synthesized to improve the mechanical properties, degradation time and cell response of fibrin-like scaffolds. The FGG scaffold was fabricated by optimizing some properties of fibrin-only gel and gelatin-glycosaminoglycan (GG) scaffolds. Mechanical analysis of optimized fibrin-only gel showed the Young module and tensile strength of up to 72 and 121 KPa, respectively. Significantly, the nine-fold increase in the Young modulus and a seven-fold increase in tensile strength was observed when fibrin reinforced with GG scaffold. Additionally, the results demonstrated that the degradation time of fibrin was enhanced... 

    Ring- DVFS: reliability-aware reinforcement learning-based DVFS for real-time embedded systems

    , Article IEEE Embedded Systems Letters ; October , 2020 , Page:1-1 Yeganeh Khaksar, A ; Ansari, M ; Safari, S ; Yari Karin, S ; Ejlali, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Dynamic Voltage and Frequency Scaling (DVFS) is one of the most popular and exploited techniques to reduce power consumption in multicore embedded systems. However, this technique might lead to a task-reliability degradation because scaling the voltage and frequency increases the fault rate and the worst-case execution time of the tasks. In order to preserve taskreliability at an acceptable level as well as achieving power saving, in this letter, we have proposed an enhanced DVFS method based on reinforcement learning to reduce the power consumption of sporadic tasks at runtime in multicore embedded systems without task-reliability degradation. The reinforcement learner takes decisions based...