Zobrazeno 1 - 10
of 2 534 170
pro vyhledávání: '"ALI, A."'
Inhaled dry powder liposomal azithromycin for treatment of chronic lower respiratory tract infection
Autor:
Dallal Bashi, Y.H., Ali, A., Al Ayoub, Y., Assi, Khaled H., Mairs, R., McCarthy, H.O., Tunney, M.M., Kett, V.L.
Yes
A dry powder inhaled liposomal azithromycin formulation was developed for the treatment of chronic respiratory diseases such as cystic fibrosis and bronchiectasis. Key properties including liposome size, charge and encapsulation efficiency p
A dry powder inhaled liposomal azithromycin formulation was developed for the treatment of chronic respiratory diseases such as cystic fibrosis and bronchiectasis. Key properties including liposome size, charge and encapsulation efficiency p
Externí odkaz:
http://hdl.handle.net/10454/20085
Publikováno v:
Novel Research in Microbiology Journal, Vol 7, Iss 5, Pp 2138-2151 (2023)
This investigation was conducted to evaluate the activity of some essential oils emulsions and a biocide (Bio-Cure F) for controlling Fusarium wilt disease of marjoram (Majorana hortensis) caused by Fusarium oxysporum. The fungal filtrate of F. oxysp
Externí odkaz:
https://doaj.org/article/9f85b98d2626492a82df82594c2800f6
Yes
A fuzzy neural Petri Nets (FNPN) controller is utilized for controlling a three-links robot arm which considers a nonlinear dynamic system. The incorporation of the classical FNN with a Petri net (PN) has been suggested to produce a new repr
A fuzzy neural Petri Nets (FNPN) controller is utilized for controlling a three-links robot arm which considers a nonlinear dynamic system. The incorporation of the classical FNN with a Petri net (PN) has been suggested to produce a new repr
Externí odkaz:
http://hdl.handle.net/10454/19283
Autor:
Eli, Aimina Ali, Ali, Abida
Medical image analysis has emerged as an essential element of contemporary healthcare, facilitating physicians in achieving expedited and precise diagnosis. Recent breakthroughs in deep learning, a subset of artificial intelligence, have markedly rev
Externí odkaz:
http://arxiv.org/abs/2410.14131
Autor:
Ali, Parvez, Baby, Annmaria, Xavier, D. Antony, A, Theertha Nair, Ali, Haidar, Kirmani, Syed Ajaz K.
For a graph $\mathbb{Q}=(\mathbb{V},\mathbb{E})$, the transformation graphs are defined as graphs with vertex set being $\mathbb{V(Q)} \cup \mathbb{E(Q)}$ and edge set is described following certain conditions. In comparison to the structure descript
Externí odkaz:
http://arxiv.org/abs/2410.09122
Autor:
Qian, Cheng, Shi, Xianglong, Yao, Shanshan, Liu, Yichen, Zhou, Fengming, Zhang, Zishu, Akram, Junaid, Braytee, Ali, Anaissi, Ali
We present a refined approach to biomedical question-answering (QA) services by integrating large language models (LLMs) with Multi-BERT configurations. By enhancing the ability to process and prioritize vast amounts of complex biomedical data, this
Externí odkaz:
http://arxiv.org/abs/2410.12856
Autor:
Ahmed, Fatimaelzahraa Ali, Yousef, Mahmoud, Ahmed, Mariam Ali, Ali, Hasan Omar, Mahboob, Anns, Ali, Hazrat, Shah, Zubair, Aboumarzouk, Omar, Ansari, Abdulla Al, Balakrishnan, Shidin
Applying deep learning (DL) for annotating surgical instruments in robot-assisted minimally invasive surgeries (MIS) represents a significant advancement in surgical technology. This systematic review examines 48 studies that and advanced DL methods
Externí odkaz:
http://arxiv.org/abs/2410.07269
Autor:
Taghinejad, Hossein, Taghinejad, Mohammad, Abdollahramezani, Sajjad, Li, Qitong, Woods, Eric V., Tian, Mengkun, Eftekhar, Ali A., Lyu, Yuanqi, Zhang, Xiang, Ajayan, Pulickel M., Cai, Wenshan, Brongersma, Mark L., Analytis, James G., Adibi, Ali
Achieving deterministic control over the properties of low-dimensional materials with nanoscale precision is a long-sought goal. Mastering this capability has a transformative impact on the design of multifunctional electrical and optical devices. He
Externí odkaz:
http://arxiv.org/abs/2410.06181
Coding theory plays a crucial role in ensuring data integrity and reliability across various domains, from communication to computation and storage systems. However, its reliance on trust assumptions for data recovery poses significant challenges, pa
Externí odkaz:
http://arxiv.org/abs/2410.05540
Automating the design of microstrip antennas has been an active area of research for the past decade. By leveraging machine learning techniques such as Genetic Algorithms (GAs) or, more recently, Deep Neural Networks (DNNs), a number of work have dem
Externí odkaz:
http://arxiv.org/abs/2410.02474