日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Experimental and numerical analysis of pGFRP and wood cross-arm in latticed tower: a comprehensive study of mechanical deformation and flexural creep

对格构塔中pGFRP和木质横臂进行实验和数值分析:力学变形和弯曲蠕变的综合研究。

Latif, Amir Abd; Ishak, Mohamad Ridzwan; Razman, Muhammad Rizal; Yidris, Noorfaizal; Mohd Zuhri, Mohamed Yusoff; Rizal, Muhammad Asyraf Muhammad; Ramli, Zuliskandar

Infraorbital nerve block for pain management in pediatric cleft lip surgery in resource-limited areas of Indonesia: A case series

在印度尼西亚资源匮乏地区,采用眶下神经阻滞术进行儿童唇裂手术疼痛管理:病例系列研究

Islam, Ahmad Nur; Utariani, Arie; Andriyanto, Lucky; Ahmad, Muhammad Ramli; Faruk, Muhammad

Levulinic Acid Production from Waste Corncob Biomass Using an Environmentally Benign WO(3)-Grafted ZnCo(2)O(4)@CeO(2) Bifunctional Heterogeneous Catalyst

利用环境友好的WO(3)接枝ZnCo(2)O(4)@CeO(2)双功能非均相催化剂,从废弃玉米芯生物质中生产乙酰丙酸

Perveen, Fouzia; Farooq, Muhammad; Ramli, Anita; Naeem, Abdul; Khan, Ihtisham Wali; Saeed, Tooba; Khan, Jehangeer

Pulsed Radiofrequency Decreases pERK and Affects Intracellular Ca2+ Influx, Cytosolic ATP Level, and Mitochondrial Membrane Potential in the Sensitized Dorsal Root Ganglion Neuron Induced by N-Methyl D-Aspartate

脉冲射频降低 pERK 并影响 N-甲基 D-天冬氨酸诱导的致敏背根神经节神经元细胞内 Ca2+ 流入、细胞浆 ATP 水平和线粒体膜电位

Ristiawan Muji Laksono, Handono Kalim, Mohammad Saifur Rohman, Nashi Widodo, Muhammad Ramli Ahmad, Willy Halim

Quantitative and Qualitative Analysis of 18 Deep Convolutional Neural Network (CNN) Models with Transfer Learning to Diagnose COVID-19 on Chest X-Ray (CXR) Images

利用迁移学习对18个深度卷积神经网络(CNN)模型进行定量和定性分析,以诊断胸部X光片(CXR)图像中的COVID-19感染。

Chow, Li Sze; Tang, Goon Sheng; Solihin, Mahmud Iwan; Gowdh, Nadia Muhammad; Ramli, Norlisah; Rahmat, Kartini

Modeling and Molecular Dynamic Simulation of F(ab')(2) Fragment of Nimotuzumab for Lung Cancer Diagnostics

尼妥珠单抗F(ab')(2)片段在肺癌诊断中的建模和分子动力学模拟

Sastyarina, Yurika; Firdaus, Ade Rizqi Ridwan; Nafisah, Zuhrotun; Hardianto, Ari; Yusuf, Muhammad; Ramli, Martalena; Mutalib, Abdul; Soedjanaatmadja, Ukun Ms