MSA Repository "MSAR"

MSAR University's Digital Repository is a documentation and digitization of all university outcomes that are of effective value in the scientific and academic community and reflects the university's image, work, and effective contribution to society Through MSAR Digital Repository, the university managed to collect, store, archive and publish digital content - including documents, audio files, images and data sets - all in a safe place. MSAR is one of the strongest University Digital Repositories in Egypt and documented in the DSPACE community with its latest versions.

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RESEARCH & LANGUAGES CENTERS 18

Recent Submissions

Comparative performance evaluation of meta-heuristic optimization algorithms for tuning PID gains in dual-axis solar tracking systems
(SAGE Publications Ltd, 2026-04-08) Mohamed Ibrahem Taha; Mohamed A. Kamel; Ehab Said; Wael Elmayyah
This work addresses the growing need for energy-efficient and accurate control in solar tracking systems, where precise alignment with the sun must be achieved without excessive actuator energy consumption. To this end, a novel proportional-integral-derivative (PID) controller tuning framework is proposed based on a dual-objective cost function that simultaneously minimizes both the integral time-weighted absolute error (ITAE) and the control effort, where the first objective is a measure of tracking accuracy, and the latter serves as a normalized approximation of control energy consumption. First, a complete model of the dual-axis solar tracking system is presented. Then, a PID controller is applied to minimize the tracking error. Next, the PID gains tuning is formulated as a multi-objective optimization problem, and five recent metaheuristic algorithms are applied to solve this problem. These algorithms are the Grey Wolf optimizer (GWO), the Aquila Optimizer (AO), the Manta Ray foraging optimization (MRFO), the Harris Hawks Optimization (HHO), and the gradient-based optimizer (GBO). All these algorithms are applied under consistent settings and benchmarked using 50 Monte Carlo simulations. Besides, they are compared based on their ability to achieve the best and mean solutions, standard deviation, computational effort, number of iterations, and convergence behavior. From the perspective of controller performance, the evaluation includes overshoot, settling time, steady-state error, and control energy consumption. Under these criteria, the GWO achieved the best cost values. All algorithms, however, exhibited overshoot limited to below 0.06% and settling times under 2 s. While from the perspective of algorithm performance, AO demonstrated the fastest average run-time and GWO was the lowest standard deviation, while MRFO achieved the lowest overshoot and GBO achieved the minimum energy consumption. The proposed framework outperforms existing approaches by integrating actuator energy into the control objective and validating statistical robustness through extensive simulation, thus offering a reliable, energy-aware strategy for real-time solar tracking deployment.
Response to Letter to the Editor regarding, “Advancements in artificial intelligence algorithms for dental implant identification”
(The Journal of Prosthetic Dentistry, 2026-04-02) Ahmed Yaseen Alqutaibi; Radhwan S. Algabri; Dina Elawady; Wafaa Ibrahim Ibrahim
Our conclusions were deliberately cautious and forward-looking, emphasizing the need for larger, more diverse datasets, external validation, and methodological standardization in future AI research on implant identification. We also noted that with continued advancements in technology and research design, AI models have the potential to accurately identify dental implant systems from radiographs and enhance patient care. We fully agree that future studies should include subgroup analyses by imaging modality and implant brand, as well as real-world clinical validation, to further strengthen the evidence base for AI integration in implant dentistry.
Seeing differently: (De)Constructing cultural narratives of blindness in al-Kīt Kāt and Scent of a Woman
(BioMed Central Ltd, 2026-04-02) Samar Abdelsalam; Noha F. Abdelmotagally
While disability studies have significantly evolved over the past few decades, cinematic representations of people with disabilities, particularly in Egypt, still remains an understudied area. Thus, the present paper uses the cultural model of disability to comparatively analyse two culturally diverse films that feature visually impaired protagonists; namely, the Egyptian al-Kīt Kāt (1991) and the American Scent of a Woman (1992). The study investigates the lives of two males who experience blindness after having been sighted, and analyses their culturally-constructed impairment, submission to/subversion of mainstream stereotypes, control (or lack thereof) of the metanarrative of blindness, and the effect of their impairment on the quality of their lives and the lives of those around them. It concludes that the films contribute to deconstructing dominant ableist narratives critiqued within disability studies, offering representations of blindness that are empathetic, multidimensional, and resistant to cultural stereotypes.
Artifcial Intelligence-Guided Optimization of Hyaluronic Acid-Coated Liposomal Linagliptin for Targeted Management of Polycystic Ovary Syndrome
(Springer Science and Business Media Deutschland GmbH, 2026-04-02) Marwa H. S. Dawoud; Aml H. Zaghloul; Karen S. Zakhari; Mai I. Mahmoud; Zeinab M. Elnagdy; Nyera H. El‑Shafei; Mai A. Zaafan
Linagliptin, a DPP-4 inhibitor commonly used in the management of diabetes mellitus, has shown potential activity in polycystic ovary syndrome (PCOS). Linagliptin’s therapeutic effectiveness is limited by its poor membrane permeability and low oral bioavailability. This study aimed to formulate hyaluronic acid-coated liposomal linagliptin optimized through I-optimal design and AI-based entrapment efficiency (EE%) prediction. The effects of hyaluronic acid and drug concentrations on particle size (PS), polydispersity index (PDI), zeta potential (ZP), and EE% were systematically evaluated to develop an optimized delivery system for PCOS management. The optimized formulation (O1) demonstrated a PS of 152.5 nm, PDI of 0.373, ZP of –19.92 mV, and an EE% of 89.43%. The integrated AI-based predictive model achieved 89.8% accuracy, confirming its reliability for rational formulation design. In-vitro dissolution studies revealed a sustained drug release over 72 h from O1, in contrast to complete release within 3 h from unformulated linagliptin. In the PCOS-induced rat model, treatment with both unformulated linagliptin and O1 significantly improved insulin sensitivity and normalized lipid profiles. Notably, O1 markedly restored ovarian redox balance through modulation of the Keap1/Nrf2 pathway, indicating a mechanistic basis for the amelioration of PCOS-associated oxidative stress and metabolic dysfunction. Overall, the optimized HA-coated liposomal formulation demonstrated superior therapeutic efficacy and bioavailability compared to unformulated linagliptin, supporting its potential as a targeted repurposed nanocarrier-based therapy for PCOS management, where AI and response surface design are efficient tools for accelerating pharmaceutical formulation development and predicting formulation performance.
Alleviation of nonalcoholic steatohepatitis induced by tetracycline in rats by Coffee Arabica extract through autophagy signals (mTOR/LC3-B)
(Nature Research, 2026-03-27) Merehan Alaa-ElDin Mohamed; Said S. Moselhy; Shaimaa Rihan; Mustafa M. M. Elbakry
The autophagy mechanism is a key point for liver protection against nonalcoholic steatohepatitis (NASH). By specifically selecting Coffea arabica, this study leverages its high concentration of chlorogenic acid to modulate autophagy, a critical cellular recycling process that is typically suppressed during the development of NASH-related liver damage. We investigated the impact of Coffea Arabica methanolic extract (CAME) on autophagy-related markers (mTOR and LC3-B) mediated abrogation of tetracycline (TET) induced NASH in rats. Sixty male albino rats weighing 150 ± 10 g were equally divided into six groups: group 1 (control) received a chow diet; group 2 (NASH) received TET orally (1 g/kg bw) for 8 days; group 3 (CAME) received Coffea Arabica methanolic extract (CAME) orally (100 mg/kg bw) for 28 days; group 4 (treatment) received TET then CAME treatment for 28 days; group 5 (preventive) received CAME (100 mg/kg) for 28 days then TET orally (1 g/kg) for 8 days; and group 6 (protective) received both TET and CAME orally for 8 days. ELISA technique was used to measure mTOR and LC3-B content in liver tissue homogenate. Moreover, transmission electron microscope analysis carried out to detect pathological alterations in liver tissue. Also, molecular docking analysis was done. Coffea Arabica methanolic extract analysis by GC/MS revealed that CAME contained the highest percentage of chlorogenic acid (12.7963%). The biochemical data obtained pointed out that the mTOR level was significantly increased (~71.62%) while LC3-B decreased (~28.08%) in the NASH group compared with control. Administration of CAME abrogated these abnormalities. Liver examination by electron microscope indicated improvement abnormalities caused by TET in treatment with CAME. Docking study showed that chlorogenic acid has binding energy − 7.554 favorable to mTOR than ATP-γS. We concluded that CAME stimulated a protective mechanism against NASH via LC3B and mTOR modulation which should attract further research to confirm our results and fully understand its mechanism of induction.