Kohat University of Science and Technology

Daraz U., Bojnec Š., Khan Y.

The agricultural sector faces challenges such as water scarcity, energy inefficiency, and declining productivity, particularly in arid regions. Traditional irrigation methods contribute to resource depletion and environmental impacts. Solar-powered smart irrigation systems integrate precision irrigation with renewable energy, improving water use and productivity. In Pakistan, where agriculture contributes 19% of gross domestic product and employs 40% of the workforce, these challenges are severe, especially in water-scarce areas like the Cholistan Desert. This study examines the impact of solar-powered smart irrigation on agricultural productivity, water conservation, and energy efficiency in the Cholistan Desert. Using a quantitative cross-sectional design, data were collected from 384 farmers via structured questionnaires. Statistical analyses, including multiple linear regression, paired sample t-tests, and Structural Equation Modeling (SEM), were conducted. Findings show significant improvements in crop yield (from 3.0 to 4.8 tons/hectare) and reductions in water and energy consumption. Regression analysis highlighted strong positive effects on yield and efficiency, while SEM confirmed reduced environmental impact and operational costs. The study concludes that solar-powered irrigation enhances productivity, conserves resources, and promotes sustainability. Policymakers should provide financial incentives, invest in renewable infrastructure, and implement training programs to support adoption. Collaborative efforts are essential for sustainable agriculture in arid regions.

Said K., Rauf M., Khan S.A., Hussain A., Alhegaili A.S., Hussain S., Ali S., Hamayun M.

Introduction: Dryopteris ramosa is a high-altitude plant of moist and shady habitat. Its aerial parts are edible and orally administered as an antibiotic and effective aphrodisiac. They are also used as pesticides, astringents, and febrifuges. AIM: The present study aimed to elucidate the plant's medicinal potential as an anticancer agent. Extracts of Dryopteris ramosa were examined for cytotoxic effects against AGS, A549, and HCT116 cell lines. The project also aimed to evaluate the phytochemical constitutents of the plant. For this purpose, GC-ToF-MS analysis was executed to identify the bioactive compounds in the aerial parts extract of Dryopteris ramosa. As a result, 93 different phytochemicals were identified from the spectral properties of GC-ToF-MS which contain 19 compounds of high peaks having reported anti-inflammatory, Anti-diabetic, Antibacterial, Analgesic, and antioxidant potential. Methods: Three different cell lines have been treated against Ethanol, Methanol, Ethyl acetate, Water, Chloroform, Acetone, and n-hexane extracts from the aerial parts of Dryopteris ramosa. These cell lines were checked and were ranked in lethality based on IC50 value. The extract samples were processed as serial dilution from high concentrations (500 ug/ml). All the three cell lines were treated for 48 hours. Results: Extracts showed a significant effect in different cell lines (based on IC50 less than 200 ug/ml). Performing the in-vitro anticancer activity against the three different cell lines in Ethyl Acetate, Methanol, nhexane, Chloroform and Acetone extract of Dryopteris indicated that anticancer activity of the plant is high against AGS and A549 cell line while less prominent in HTC116 cell lines through MTT Assay. Insilico drug-likeness and ADMET analysis were studied of the compounds, that exhibit considerable drug likenesses, phytochemical medicinal chemistry, and a promising ADMET score and no toxicity. The candidate compounds were chosen for further elucidation by Molecular Docking and dynamic simulations. Employing the molecular docking approach for virtual screening of the phytochemicals it was found that the compounds Germacrene showed remarkable results towards BCL2 with -7Kcal/Mol and a-D-(+)-Xylopyranose showed significant docking results towards 5P21 with -7.1Kcal/Mol. Conclusion: For multi-scale frames structural aberrations and fluctuations identification of the docked complexes, a molecular dynamics analysis was performed for a 100 ps simulation run by accessing the online tool of MDweb simulations. These molecular docking and simulation analyses also revealed that both the phytochemicals have a stable interaction with the cancer-related proteins BCL2 and 5P21. result: As a result, 93 different phytochemicals were identified from the spectral properties of GC-ToF-MS which contain 19 compounds of high peaks having reported anti-inflammatory, Anti diabetic, Anti bacterial, Analgesic and antioxidant potential. Three different cell lines have been treated against Ethanol, Methanol, Ethyl acetate, Water, Chloroform, Acetone and n-Hexane extracts from the aerial parts of Dryopteris ramosa. These cell lines were checked and were ranked its lethality based on IC50 value. The extract samples processed as serial dilution from high concentration (500ug/ml). All the three cell lines were treated for 48 hours. Extracts showed a significant effect in different cell lines (based on IC50 less than 200ug/ml). By performing the in-vitro anticancer activity against the three different cell lines in Ethyl Acetate, Methanol, n-Hexane, Chloroform and Acetone extract of Dryopteris clearly indicated that anticancer activity of the plant is high against AGS and A549 cell line while less prominent in HTC116 cell lines through MTT Assay. Insilico drug likeness and ADMET analysis were studied of the compounds, those exhibit considerable drug likenesses, phytochemical medicinal chemistry, and a promising ADMET score and no toxicity the candidate compounds were chosen for further elucidation by Molecular Docking and dynamic simulations. Employing the molecular docking approach for virtual screening of the phytochemicals it was found that the compounds Germacrene showed remarkable result towards BCL2 with -7Kcal/Mol and a-D-(+)-Xylopyranose showed significant docking result towards 5P21 with -7.1Kcal/Mol. For multi-scale frames structural aberrations and fluctuations identification of the docked complexes, a molecular dynamics analysis was performed out for a 100 ps simulation run by accessing the online tool of MDweb simulations.

Yao H., Ullah A., Ikramullah, Widyan A.M., Althobaiti A., Khalifa H.A.

AbstractWe examine a new model for the Casson fluid (CF) migration near a thin needle. The needle is moving along the free stream with constant velocity. The impacts of nonlinear thermal radiation, Joule heating, magnetic fields, and viscous dissipation are considered in the flow. The flow is modeled with the basic equations, whose complexity is reduced with the similarity transformations. We introduced the artificial neural network (ANN) to tackle the first‐order system of equations. ANN is trained with the numerical methods (bvp4c) solution that uses the Levenberg‐Marquardt algorithm by choosing the best possible weights. A comprehensive graphical description is provided with varying heating parameters, Eckert number, radiation parameter, velocity ratio parameter, Prandtl number, and the size of the thin needle. The rise in the needle size and velocity ratio reduce the velocity flux and increases the thermal transport. The CF parameter increases the velocity gradient. The Eckert number and radiation parameter increase the thermal profile with their increasing values. The regression plots display that data is utilized in the curve fitting, while the error histograms depict the minimal zero error. Furthermore, the mean square error and performance validation for each varying parameter are presented. For validation, the present numerical results are compared in tabular form with the published literature, where the current approach is validated.

Khan R., Mehmood A., Song H., Maple C.

Jemai R., Ahmed Z., Hajji M., Kamoun O., Ben Haj Amara A., Ben Rhaiem H.

Han X., Ai Y., Wang L., Liu T., Badshah A., Hu X., Huang Z., Mansoor A., Sun W.

Bisphenol A (BPA) exposure poses significant health risks, making its analysis essential. This study presents a portable electrochemical sensing platform using copper nanoparticles (CuNPs) decorated on a laser‐induced graphene (LIG) electrode (CuNPs@LIGE). The platform is created through a one‐step laser‐induced synthesis that combines polyimide and metal precursors, resulting in a three‐dimensional porous structure. The sensor utilizes linear scan voltammetry for BPA detection with a smartphone‐connected electrochemical workstation. The presence of CuNPs in LIG enhances electrical conductivity and response signals. Under optimal conditions, the sensor achieves a detection range from 0.1 μmol/L to 10.0 mmol/L and a low detection limit of 0.033 μmol/L (3σ), demonstrating good stability and selectivity. Additionally, it shows recovery rates between 95.71% and 99.17% for BPA detection in seawater samples, making it a strong candidate for rapid BPA monitoring applications.

Khattak S., Waseem, Ullah A., Ikramullah, Althobaiti A., Khalifa H.A., Al‐Rajeh M.A.

AbstractA time‐dependent mixed convective hybrid nanofluid (HNF) ( /Engine oil) flow between two spinning disks is considered. The physical problem is modeled and transformed into a non‐dimensional ordianary differential equation system to reduce the complexity. A modified Devi and Devi's model is utilized for the nanofluid properties. The cylindrical shape nanoparticles are considered for the analysis of the various pertinent parameters. The base fluid is considered as the engine oil to briefly explain its thermal behavior. One of the famous optimization algorithms Levenberg–Marquardt is used to train the artificial neural network with the data achieved from the numerical results to analyze the various states of the HNF. The results for the state variables as well as nanoparticle shapes are displayed through graphs and tables. The enhancement of the expansion parameter () causes to augment, then drop and augment again the velocity gradient with the increasing distance between the disks. The temperature of the fluid initially drop and then enhances with the rising strength of (). The rising concentration of the nanomaterial associated with the higher values of volume fraction parameter () enhances the temperature distribution of the HNF. The results obtained show that the smaller nanoparticles concentration will keep the engine at a lower state of temperature. The results are validated through graphs in each case by providing the validation and absolute error graphs.

Ullah K., Almutairi M.H., Abbas M.N., Wahab A., Nayab S., Fozia F., Khan M.A., Shah Z.A., Ahmad I., Almutairi B.O., Ziaullah Z.

Introduction: Alzheimer's disease (AD) is a progressive neurological disorder for which no effective cure currently exists. Research has identified β-Secretase (BACE1) as a promising therapeutic target for the management of AD. BACE1 is involved in the rate-limiting step and produces toxic amyloid-beta (Aβ) peptides that lead to deposits in the form of amyloid plaques extracellularly, resulting in AD. Method: In this connection, 60 small peptides were evaluated for their in-silico studies to predict the bonding orientation with BACE1. Next, 5 peptides (12, 20, 21, 51, and 52) were selected based on high scoring of Vander Waal interactions with the catalytic site of the enzyme. Results: The identified hit peptides were synthesized using Solid-Phase Peptide Synthesis (SPPS), and Electrospray Ionization Mass Spectrometry (ESI-MS) elucidated their structures and 1 1 HNMR spectroscopy. According to their In-vitro BACE1 inhibitory study, peptides 21 having high Vander Waal forces showed significant BACE1 inhibition with IC50 = 4.64 ± 0.1μM). Moreover, the kinetic study revealed that peptide 21 is a mixed-type inhibitor and can interact at the active site and the allosteric site of BACE1. Conclusion: According to the cytotoxicity study, peptide 21 was found to be noncytotoxic at 4.64 μM, 10 μM and 20 μM. The forthcoming target of this study is to evaluate further the effect of peptide 21 in an in-vivo mice model.

Khan J., Lawati D.R., Dutta A., Almutairi F.N., Ayari-Akkari A.

The structural, electronic, elastic, and optical properties of Half Heusler YSbPd and YSbPt were investigated with PBE and RPBE functions using GGA implemented with Density Functional Theory (DFT). Structural stability was verified using the Birch–Murnaghan equation of states for optimization. The obtained lattice parameters match previous literature data. The Elastic stability is computed the Elastic constants by using the Code version: 2024.03.15 (running on Python 3.11.2). Our results show that both compounds are ductile in nature. The Calculated the Band structures of half-Heusler YSbPd and YSbPt show direct band gaps of approximately 0.154 and 0.412 eV, respectively, which indicate a semiconducting nature. The Sb and Pd/Pt states are mainly responsible for the conduction state, as evidenced by the density of states (DOS) plot. Optical properties such as dielectric function, reflectivity, refractive index, conductivity, and loss function were investigated in the energy range of 0–10 eV. The maximum absorption and low loss indicate that YSbPd and YSbPt are potential candidates for optoelectronic device applications.

Ullah I., Aldhafeeri T.R., Haider A., Wu X., Ullah Z., Chang S., Innayat A., Begum N., Pope M.A., Sher F., Rehman H.U., Hussain I.

Ishaq S., Habib O., Tahir R., Afzal S., Ikram H., Li Z., Malik S.I., Ullah A., Alshaya D.S., Eldeen M.A.

Prevotella copri is a prominent constituent of the human gastrointestinal microbiome, and its fluctuating abundance has been linked with positive and negative influences on diseases such as Parkinson’s disease and rheumatoid arthritis. Prevotella copri demonstrates flexibility against drugs. There is presently no vaccine approved by the FDA against prevotella copri,and treatment options are restricted. Hence, this research work was designed to create an in silico-based vaccine for prevotella copri.The protein sequences of two distinct strains ofprevotella copriwere retrieved from NCBI. The T-cell and B-cell epitopes were obtained and then analyzed for antigenicity, allergenicity, docking and simulation. The peptide comprises linear B-cell and T-cell epitopes from proteins identified as potential novel vaccine candidates. The molecular dynamics (MD) simulations and protein-protein docking results revealed that the vaccine exhibits strong and Sustained interaction with Toll-like receptor 4 (TLR4). The constructed sequence was integrated into the pET-30a (+) biological vehicle (vector) for subsequent analysis expression in E. coli through the SnapGene server. The constructed multi-epitopic vaccine candidate was assessed for its structural, physicochemical and immunological properties. The results demonstrated solubility, stability, antigenicity and nonallergenicity and showed a strong affinity for its target receptors. The in silico study represents a significant step forward in designing a vaccine that could effectively eliminate Prevotella copri globally.

Ullah A., Ali F., Ullah F., Sadozai S.K., Khan S.A., Hussain S., Alrefaei A.F., Ali S.

The development of resistance to traditional antifungal therapies has necessitated the exploration of alternative treatment strategies to effectively manage fungal infections, particularly those induced by Candida albicans (C. albicans). This research investigates the possibility of integrating silver nanoparticles (AgNPs) with Terbinafine to improve antifungal effectiveness. Terbinafine, while potent, faces challenges with specific fungal strains, highlighting the need for strategies to enhance its treatment efficacy. Silver nanoparticles were produced through a light-activated, gelatin-based method, resulting in particle sizes ranging from 56.8 nm to 66.2 nm, confirmed by dynamic light scattering and scanning electron microscopy. Stability studies indicated that AgNPs produced with 30 mg of silver nitrate (AgNO₃) exhibited the greatest stability over 60 days across different temperature conditions. The analysis through UV-visible spectrophotometry revealed a notable shift in the absorption spectra as AgNO₃ concentrations increased, which was associated with a strengthening of plasmon resonance. The effectiveness of the AgNPs and Terbinafine combination was assessed against three strains of C. albicans (ATCC 10231, ATCC 90028, and ATCC 18804). Terbinafine demonstrated strong antifungal properties with minimum inhibitory concentrations (MIC) values ranging from 2–4 µg/mL, whereas AgNPs on their own displayed moderate effectiveness. The integrated formulation notably enhanced effectiveness, especially against strain ATCC 90028, revealing a synergistic effect (FIFi = 0.369). These results were complemented by the findings of the time-to-kill assay, where the same strain showed a 3.2 log₁₀ CFU/mL decrease in viable cell count. The process by which AgNPs boost activity entails the disruption of the fungal cell membrane and its internal components, probably as a result of silver ion release and the generation of free radicals. The results indicate that the combination of Terbinafine and AgNPs may act as a powerful alternative for addressing resistant fungal infections, presenting an encouraging direction for future antifungal treatments.

Mehboob M., Rehman A., Naz I., Shuja M.N., Farooq A.S., Khattak B.

Noor A., Ahmad N., Ali A., Ali M., Iqbal M., Khan M.N., Laila M.B., Shah S.N., Kaplan A., Ercişli S., Elshikh M.S.

ABSTRACTOne of the main difficulties in nanotechnology is the development of an environmentally friendly, successful method of producing nanoparticles from biological sources. Silver‐doped zinc oxide nanoparticles (Ag‐ZnO NPs), with antibacterial and antioxidant properties, were produced using Adiantum venustum extract as a green technique. Fresh A. venustum plants were gathered, then their bioactive elements were extracted with cold water and processed into nanoparticles. The main goal was to develop Ag‐ZnO NPs (nanoparticles) for medical applications, especially with regard to their antifungal and antibacterial properties. Pathogens such as Fusarium oxysporum, Escherichia coli, and Staphylococcus aureus were tested against the synthesized nanoparticles. While FTIR spectroscopy revealed functional groups, X‐ray diffraction validated the crystalline structure. The scanning electron microscope analysis revealed that the Ag‐ZnO NPs had an average size of 30.16 nm and an irregular shape. Additionally, energy dispersive X‐ray analysis) confirmed the elemental composition. The bioactive compounds present in A. venustum significantly stabilized the nanoparticles. Strong antioxidant and antibacterial activity of the Ag‐ZnO nanoparticles was demonstrated. In particular, this work shows that the Ag‐ZnO nanoparticles produced by green synthesis could be used in biomedical drug delivery and therapy.

Sagheer M., Asif Jan M., Shah Z., Mashwani W.K., Adeeb Khanum R., Shutaywi M.

Meta-heuristics are utilized to handle challenging optimization problems, since conventional optimization techniques for such problems often fail or become stuck in the local optimum. Teaching-learning based optimization algorithm (TLBO) is a prominent meta-heuristic that mimics the teaching-learning process. It is initially employed to tackle unconstrained optimization problems. The main obstacle to meta-heuristics is premature convergence. The strategy of forming groups of students is introduced in the teaching-learning process for mutual discussions and joint projects. Along with some advantages, like increased creativity, diversity of ideas, access to new information, and more critical thinking, the group discussion strategy also has few disadvantages, such as disagreements over ideas, group size sensitivity, dependency on others, and lengthened the completion time. If properly implemented, the strategy can be a useful tool in the teaching-learning process. To increase an algorithm local search capabilities and to produce solutions of diverse nature, it is essential to have sufficient knowledge about the optimum solution with enough population diversity. Through group discussion sufficient information with diverse views about the solution of the problem is obtained. Therefore, in this work, the group discussion strategy is embedded to the learner phase of TLBO to enhance it. In the strategy, the group of randomly selected individuals correspond to each candidate solution is made to minimize the happening of premature convergence. This strategy depends on the group size parameter; for which the sensitivity analysis is also performed to obtain the right/optimal value. The suggested algorithm is known as GTLBO, and the group size parameter sensitivity analysis generates its four versions, referred to as GTLBO2–GTLBO5, where the digits 2–5 represent the group size value. The performance of the proposed algorithms is evaluated by the unconstrained benchmark problems of CEC 2017. The comparison of the obtained simulations’ results of the newly designed and some state-of-the-art algorithms on the tested problems exhibits that the suggested algorithms take the first, third, fourth, and fifth ranks in the top five ranks, which highlights the importance of the introduced strategy in the sense of enhancing TLBO.