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586 results on '"Alfaifi, Mohammad"'

12. Sustainable synthesis of zinc oxide nanoparticles using Piper betle petiole leaf extract: Antibacterial, antioxidant, and cytotoxic potential

Author

Mohan Krishana, G.K., Shivaramakrishna, Sahana, Sridhar, Sneha, Khan, Mansoor Ahmed, Kumar, Jajur Ramanna, Sai Chakith, M.R., Pradeep, Sushma, Kavana, C.P., Shreevatsa, Bhargav, Shati, Ali A., Alfaifi, Mohammad Y., Elbehairi, Serag Eldin I., Shivamallu, Chandan, Kumar, Dugganaboyana Guru, and Kollur, Shiva Prasad

Published
2024
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18. Author Correction: Integrated approach for studying bioactive compounds from Cladosporium spp. against estrogen receptor alpha as breast cancer drug target

Author

Anandan, Satish, Gowtham, Hittanahallikoppal Gajendramurthy, Shivakumara, C. S., Thampy, Anjana, Singh, Sudarshana Brijesh, Murali, Mahadevamurthy, Shivamallu, Chandan, Pradeep, Sushma, Shilpa, Natarajamurthy, Shati, Ali A., Alfaifi, Mohammad Y., Elbehairi, Serag Eldin I., Ortega‑Castro, Joaquín, Frau, Juan, Flores‑Holguín, Norma, Kollur, Shiva Prasad, and Glossman‑Mitnik, Daniel

Published
2023
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28. Machine Learning for Performance Prediction of Channel Bonding in Next-Generation IEEE 802.11 WLANs

Author

Wilhelmi, Francesc, Góez, David, Soto, Paola, Vallés, Ramon, Alfaifi, Mohammad, Algunayah, Abdulrahman, Martin-Pérez, Jorge, Girletti, Luigi, Mohan, Rajasekar, Ramnan, K Venkat, and Bellalta, Boris

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

With the advent of Artificial Intelligence (AI)-empowered communications, industry, academia, and standardization organizations are progressing on the definition of mechanisms and procedures to address the increasing complexity of future 5G and beyond communications. In this context, the International Telecommunication Union (ITU) organized the first AI for 5G Challenge to bring industry and academia together to introduce and solve representative problems related to the application of Machine Learning (ML) to networks. In this paper, we present the results gathered from Problem Statement~13 (PS-013), organized by Universitat Pompeu Fabra (UPF), which primary goal was predicting the performance of next-generation Wireless Local Area Networks (WLANs) applying Channel Bonding (CB) techniques. In particular, we overview the ML models proposed by participants (including Artificial Neural Networks, Graph Neural Networks, Random Forest regression, and gradient boosting) and analyze their performance on an open dataset generated using the IEEE 802.11ax-oriented Komondor network simulator. The accuracy achieved by the proposed methods demonstrates the suitability of ML for predicting the performance of WLANs. Moreover, we discuss the importance of abstracting WLAN interactions to achieve better results, and we argue that there is certainly room for improvement in throughput prediction through ML.

Published
2021

45. Antidiabetic activity of methanolic extract of Hibiscus sabdariffa Linn. fruit in alloxan-induced Swiss albino diabetic mice

Author

Akter Shahida, Ali Hanif, Shati Ali A., Alfaifi Mohammad Y., Elbehairi Serag Eldin I., Sayyed R. Z., and Yeasmin Tanzima

Subjects
hibiscus sabdariffa fruit, antioxidant activity, antidiabetic activity, alloxan, lipid profile, Agriculture, Agriculture (General), S1-972
Abstract

The majority of natural diabetic medications come from fruits and vegetables. These natural medications help protect humans from negative impacts of chemical antidiabetics by scavenging free radicals. The present study aimed to explore the antioxidant and antidiabetic properties of methanolic extract of fruits of Hibiscus sabdariffa Linn. (MEHSF) in alloxan-induced Swiss albino diabetic mice. The dried coarse powder of Hibiscus sabdariffa Linn. fruits was subjected to methanol extraction. The antidiabetic activity was determined by using alloxan-induced (80 mg/kg body weight) diabetic mice. Following a 15-day treatment period, serum biochemical parameters including total cholesterol (TC), triglyceride (TAG), LDL-cholesterol (LDL), HDL-cholesterol (HDL), serum glutamic pyruvic transaminase (SGPT), and serum glutamic-oxaloacetic transaminase (SGOT) enzymes were estimated. The antioxidant activity was evaluated through a DPPH and ABTS free radical scavenging assay. Total phenolic content and total flavonoid content were assessed using established methods. MESHF, containing polyphenolic and flavonoid compounds, exhibited antioxidant properties. A 100 and 200 mg/kg significantly (p < 0.05) lowered the blood glucose levels and improved biochemical parameters such as TC, TAG, LDL, and HDL in diabetic mice. Further, MESHF significantly (p < 0.05) reduced the activity of the SGPT and SGOT in diabetic mice compared to untreated diabetic mice. These results suggest that MEHSF with promising antioxidant and antidiabetic potentials can be considered to be a probable new resource of the antidiabetic agent.

Published
2024
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48. Integrated approach for studying bioactive compounds from Cladosporium spp. against estrogen receptor alpha as breast cancer drug target

Author

Anandan, Satish, Gowtham, Hittanahallikoppal Gajendramurthy, Shivakumara, C. S., Thampy, Anjana, Singh, Sudarshana Brijesh, Murali, Mahadevamurthy, Shivamallu, Chandan, Pradeep, Sushma, Shilpa, Natarajamurthy, Shati, Ali A., Alfaifi, Mohammad Y., Elbehairi, Serag Eldin I., Ortega-Castro, Joaquín, Frau, Juan, Flores-Holguín, Norma, Kollur, Shiva Prasad, and Glossman-Mitnik, Daniel

Published
2022
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