Current Issue

Sana'a University Journal of Applied Sciences and Technology

Vol. 4 No. 6 (2026)

2026-06-28

10 Articles

The fourth volume – the sixth issue in the Sana'a University Journal of Applied Sciences and Technology

Article

8 Articles

UV-Vis absorption spectra of the TAC-FBRC complex and the reagent blank.

Determination Standardization and Validation of Optimized Spectrophotometric Assays for Total Antioxidant, Polyphenol, and Flavonoid Determination: A Kinetic and Methodological Framework

Anass A. Alnedhary, Fatima A. Murshed, Maher A. Almaqtari, Amal A. S. AL Huzaim, Fadhailah A. Al-herdy Al-herdy

2166-2177

2026-06-28

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DOI: 10.59628/jast.v4i6.2774

Abstract

This study addresses persistent methodological inconsistencies in phytochemical assays by developing a harmonized, high-sensitivity framework for TAC, TPC, and TFC. Using the Ferric Bipyridyl Reducing Capacity (FBRC), Folin-Ciocalteu, and Aluminum Chloride methods, critical parameters—including maximum wavelength (λ_max), temperature, kinetics, pH, and stoichiometry—were systematically re-evaluated and optimized. The novelty of this work lies in the transition from empirical "snapshot" measurements to kinetically optimized and AOAC-validated protocols that ensure inter-laboratory reproducibility. Optimized conditions for TAC were established at 520 nm, pH 4, and 30 minutes at 50°C. TPC was optimized at 750 nm (20 min at 50°C), while TFC achieved stability at 430 nm after 10 minutes at ambient temperature. Unlike conventional methods that often suffer from baseline drift, these refined protocols achieved superior sensitivity. Comprehensive validation in accordance with AOAC guidelines confirmed high precision, with repeatability (%RSD) ranges of 0.82–5.68% (TAC), 0.85–6.22% (TPC), and 0.29–5.09% (TFC). Linearity was established over concentration ranges of 0.2–5 ppm for TAC (ascorbic acid equivalent), 1–10 ppm for TPC (gallic acid equivalent), and 2–20 ppm for TFC (quercetin equivalent). All methods demonstrated excellent linearity (R2 = 0.9978) and significantly lower limits of detection (LODs: 0.027, 0.164, and 0.065 ppm) than those reported in the literature. These protocols offer a rapid, cost-effective, standardized alternative to expensive chromatography. By resolving the kinetic and chemical variables that typically cause discrepancies in research, this study provides a validated "gold-standard" approach that ensures the global comparability of phytochemical data across diverse plant matrices.

Keywords

Spectrophotometry Total antioxidant capacity Phytochemicals Validation Kinetic optimization

Interactive Effects of Limestone/Basalt Mineral Fillers and Dry-Processed Crumb Rubber on Hot Mix Asphalt Performance

Ali Abdullah Dahmash, Abdullah Ahmed Al-Mswari, Ali Mohammed Rajeh

2178- 2197

2026-06-28

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DOI: 10.59628/jast.v4i6.2990

Abstract

Road networks in developing regions such as Yemen suffer from premature deterioration for many reasons, including the use of basalt asphalt mixtures in the design of pavement layers; however, these mixtures exhibit poor resistance to rutting and moisture damage, particularly under excessive axle loads. This study investigates the performance of hot mix asphalt (HMA) modified with crumb rubber (CR) from scrap tires using the dry mixing technique, with a focus on the influence of mineral filler type and rubber gradation. Two locally sourced fillers- limestone and basalt-were evaluated using three CR gradations (coarse, fine, and powder) at concentrations of 0%, 5%, 10%, 15%, 20%, and 25% by weight of the asphalt binder. A total of 210 Marshall specimens were tested. The results showed that the limestone reference mixture exhibited critically low voids in mineral aggregate (VMA=12.40%), below the 13% specification requirement, while excessive stability suggested susceptibility to premature aging. The addition of 15% fine crumb rubber to the limestone mixture yielded optimal performance: a stability of 14.7 kN, a VMA of 14.8%, and an optimum asphalt content of 4.0% at 4% air voids, satisfying the Marshall mix design criteria for a heavy-traffic wearing course. In contrast, the basalt mixture showed continuous performance degradation upon crumb rubber addition. A two-way ANOVA confirmed a significant interaction between filler type and rubber content (p < 0.001). The study concludes that the optimal formulation-limestone filler with 15% fine crumb rubber -offers a practical solution for sustainable pavement infrastructure development in Yemen.

Keywords

Crumb Rubber Dry Process Hot Mix Asphalt Filler Type Rubber Gradation Tire Recycling Marshall properties Moisture susceptibility (TSR).

XRD pattern for 96.3Sn -0.1 Ag -3.6 Cu alloy.

Studying Structural analysis by (X-ray and SEM) of (96.5-2x)Sn-(x)Ag-(3.5+x)Cu alloy with x=0.1,0.2,0.3,0.4 and 0.5 wt%

Hend. Q.A. Al-hubaishi, A.H. Al-Hammadi, Ibrahim G.H. Loqman, Ahmed. M.A. Haider, Abdulmalek Mansoor N. Hulif

2198-2208

2026-06-28

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DOI: 10.59628/jast.v4i6.2754

Abstract

In the pursuit of developing high-performance, lead-free solder alloys with enhanced reliability and environmental compliance, this study investigates the structural effects of incorporating the alloy (x)Ag–(3.5+x)Cu into the near-eutectic (96.5–2x)Sn system. The objective is to evaluate the influence of varying Ag and Cu concentrations on phase formation and microstructural evolution. Five alloy compositions were synthesized with x values of 0.1, 0.2, 0.3, 0.4, and 0.5 using conventional melting and casting techniques. The samples were characterized using X-ray diffraction (XRD) to identify crystalline phases and scanning electron microscopy (SEM) to analyze microstructural features. X-ray diffraction (XRD) analysis confirmed that all alloy samples predominantly consist of a single-phase tetragonal β-Sn structure. The incremental addition of silver and copper to the tin matrix enhanced the particle size refinement of the near-eutectic Sn–Ag–Cu ternary alloy. The introduction of the (x)Ag–(3.5+x)Cu alloy into the (96.5–2x)Sn system at varying concentrations (x = 0.1, 0.2, 0.3, 0.4, 0.5) resulted in noticeable shifts in diffraction peak positions (2θ), indicating lattice distortion and compositional changes. The calculated lattice parameters closely matched the standard peaks listed in JCPDS PDF No. 04-0673, and no new phases were detected within the ternary systems. Scanning electron microscopy (SEM) revealed distinct grayscale variations corresponding to differences in chemical composition and electron density across the microstructure. Notably, even minimal additions of Ag (x = 0.1) significantly improved the microstructural uniformity, which is critical for understanding the structural integrity and potential reliability of Sn–Ag–Cu solder joints in electronic interconnects.

Keywords

Sn-Ag-Cu alloy lead-free solder Structural Properties Phases of interphase (XRD) (SEM) (SEI)

Co0.5Zn0.3Mn0.2Fe2O4 nanoparticle preparation steps via Sol-gel method

Tuning Structural and Optical Properties of Co₀.₅Mn₀.₅₋ₓZnₓFe₂O₄ Nanoferrites via Zn Substitution for Optoelectronic Applications

Yousef A. Alsabah, Abdelrahman A. Elbadawi, Ibrahim Alsuqia, Olfat Humaid, A .A. Al-Muntaser

2209-2218

2026-06-28

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DOI: 10.59628/jast.v4i5.2925

Abstract

Ferrite nanoparticles are interesting materials due to their rich and unique physical and chemical properties. They find applications in catalysis, bio-processing, medicine, magnetic recording, adsorption, devices, so nanoferrite materials had been synthesized to produce new alternate substance for reducing the rare or high cost of industrial materials. Therefore,Co_0.5Mn_0.5-xZn_xFe₂O₄nanoferrite compositions (x=0,0.1,0.2,0.3,0.4) were successfully synthesized via the citrate-nitrate sol-gel auto-combustion technique. A comprehensive investigation of structural and optical, properties was conducted using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and UV–Vis diffuse reflectance spectroscopy (DRS). XRD analysis confirmed the formation of a single-phase cubic spinel structure with space group Fd-3m, without detectable secondary phases, indicating the successful incorporation of Zn²⁺ and Mn²⁺ ions into the cobalt ferrite lattice. The crystallite size was found to vary between 8.017 and 10.130 nm depending on Zn substitution. Rietveld refinement further verified the structural stability with a lattice parameter of a = 8.370 Å and satisfactory fit (x² = 0.15). Microstructural parameters such as dislocation density, microstrain, and stacking fault probability were found to increase with decreasing crystallite size. The FTIR spectroscopy confirmed the formation of spinel ferrite and spectra exhibited characteristic metal–oxygen vibration bands at approximately 585 cm⁻¹ and 415 cm⁻¹, corresponding to tetrahedral and octahedral sites of the spinel structure. UV–Vis DRS analysis revealed strong absorption in the UV–visible region, with the optical band gap decreasing from 2.96 to 2.81 eV as the Zn concentration increased, demonstrating tunable electronic properties. The absorption coefficient, extinction coefficient, imaginary dielectric constant, and optical conductivity increased with Zn substitution, whereas the refractive index and real dielectric constant showed an opposite trend, with a maximum refractive index observed near 2.6 eV (475 nm). The enhanced optical conductivity around 3.6 eV was attributed to interband transitions and charge-transfer processes such as O^2- → Fe³⁺ and Fe²⁺ ↔ Fe³⁺. These results demonstrate that Zn substitution effectively tailors the optical response of Co–Mn ferrites, highlighting their potential for optoelectronic and photonic applications.

Keywords

Nanoferrites Sol-Gel Spinel Structure Optical Properties XRD

Biological Study on Alternaria alternata isolated from infected Vegetables in Sana’a, Yemen

Huda Sultan Al-Shaif, Ebtesam Hassan Lutf Alhamzi, Saeed M. Alghalibi

2219-2229

2026-06-28

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DOI: 10.59628/jast.v4i6.2686

Abstract

Alternaria alternata, the causal agent of early blight, is one of the most destructive pathogens affecting tomato and potato crops in Yemen, with documented yield losses of up to 80%. The traditional reliance on synthetic fungicides has led to environmental degradation and the emergence of resistant strains, necessitating the development of sustainable, eco-friendly alternatives. This study aimed to isolate and identify A. alternata from infected crops in the Sana’a Governorate and evaluate the in vitro antifungal efficacy of essential oils (EOs) derived from Cupressus macrocarpa leaves. Of the 41 initial isolates, 19 were identified as A. alternata based on morphological and microscopic characterization. Pathogenicity assays revealed significant variability in virulence, with isolate 1T1 (from tomato) exhibiting the highest disease severity (56%). Gas Chromatography-Mass Spectrometry (GC-MS) analysis identified the major chemical constituents, including monoterpenes (4-terpineol, γ-terpinene, and α-terpinene) and fatty acid esters. In vitro assays demonstrated potent fungicidal activity; at concentrations of 0.2%, 0.4%, and 0.6%, the EO achieved up to 97% mycelial growth inhibition at the highest concentration. This efficacy was comparable to that of the synthetic fungicide difenoconazole (0.1%). These findings suggest that C. macrocarpa essential oil is a promising biofungicide candidate for sustainable management of Alternaria blight.

Keywords

Alternaria alternata Early blight potato and tomato diseases Cupressus macrocarpa Essential oils Antifungal Activity biofungicide

English Dataset Class Distribution (651,191 URLs)

A Hybrid Deep Learning Ensemble for Multi-Class Malicious URL Detection in Arabic and English

Nagi Ali Abdullah Al-shaibany

2230-2243

2026-06-28

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DOI: 10.59628/jast.v4i6.2961

Abstract

Malicious URLs serve as primary vectors for cyber-attacks, facilitating phishing, malware, and defacement. While conventional systems focus on binary classification, security operations require granular threat identification. Furthermore, literature exhibits a significant bias toward English content, leaving Arabic speaking populations disproportionately exposed to localized threats. This study proposes a hybrid stacked ensemble architecture integrating CNN-BiLSTM with an Attention mechanism, Random Forest, and XGBoost. The methodology incorporates 27 lexical features for English URLs and 23 specialized features tailored to Arabic linguistic structures and Punycode-encoded domains. The model was evaluated on 651,191 English and 20,329 Arabic URLs. The architecture achieved a peak accuracy of 99.43% on English data and 89.07% on the Arabic dataset, outper-forming baseline configurations. Feature correlation analysis demonstrated that class imbalance inflates feature importance, with average correlation coefficients decreasing by 0.214 post-balancing. Comparative experiments utilizing a unified cross-language model yielded inferior results (91.2% English, 82.5% Arabic), confirming that language-specific optimization is essential. This research establishes the first multi-class baseline for Arabic URL detection, providing a robust, scalable framework for regional threat intelligence.

Keywords

Malicious URL Detection Ensemble Methods Arabic URL Classification Hybrid Models Stacked Generalization

snapshot from the WHO dashboard highlighting the state of nutrition in Yemen after applying DHIS2, December 2022 [16]

Conceptual Readiness for DHIS2 Adoption in Yemen’s NCD Program: SWOT, PESTEL.

Roqiah Atef, Mansoor N.Ali

2244-2253

2026-06-28

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DOI: 10.59628/jast.v4i6.2796

The X-ray density (Dx) and bulk density (Db ) as a function of Cu Content.

Effect of the Cu additions on the structure of the soldered (96.5- x)Sn - (3.5)Ag -(x)Cu alloy with x=0.2, 0.4, 0.6, 0.8 and 1 wt % There is none

Amtalsabowr A.AL-Thamari, A.H.Al-Hammadi, Ibrahim G.H. Loqman, Ahmed.M.A.Haider

2254-2264

2026-06-28

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DOI: 10.59628/jast.v4i6.2827

Review

2 Articles

Evolution of pattern mining techniques from 2021 to 2025

A A Dynamic Mining of Interesting Web Usage Patterns for Personalized E-Learning: A Systematic Review

Emad Mahmoud Al-Azazi, Ahmed Sultan Al-Hegami

2265-2283

2026-06-28

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DOI: 10.59628/jast.v4i6.2980

Abstract

Personalized e-learning adapts educational materials and learning paths to individual learner characteristics. This adaptation is often supported by analyzing learner interactions through Web Usage Mining. The present survey reviews research from 2010 to 2025 that addresses dynamic web usage pattern mining for personalized e-learning environments. Four main contributions stand out. First, a hierarchical classification organizes approaches across five interconnected levels: data sources, preprocessing, pattern discovery, dynamic mining, and recommendation systems. A comparison then follows between static and dynamic mining approaches—tracing temporal and incremental methodologies, something earlier surveys often overlooked. Third, the analysis turns to recommendation mechanisms: collaborative filtering and content-based methods. Finally, ongoing challenges are identified and future directions suggested. Static algorithms such as Apriori and FP-Growth, according to the review’s conclusion, are increasingly giving way to dynamic techniques—incremental mining and sliding window analysis, for instance. Dynamic methods capture the evolution of learner behavior more effectively. Several research gaps remain. Despite their proven effectiveness, deploying these dynamic techniques in real-world educational settings continues to face obstacles, with scalability and latency being the most prominent. More critically, metrics for evaluating pattern interestingness based on educational impact remain underdeveloped.

Keywords

Web Usage Mining Sequential pattern mining Dynamic pattern mining Stream mining Incremental mining.

Natural Photosynthesis vs Artificial Photosynthesis

A A Short Review of Recent Advances in ArtificialP hotosynthesis Chemistry

Amir Alqahm

2284-2291

2026-06-28

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DOI: 10.59628/jast.v4i6.2751

Abstract

Artificial photosynthesis has emerged as a promising strategy for sustainable solar-to-chemical energy conversion by mimicking natural photosynthetic processes to produce fuels from water and carbon dioxide. In recent years, significant chemical advances have been achieved in light-harvesting materials, molecular and heterogeneous catalysts, and integrated photoelectrochemical systems. Progress in self photosensitizing molecular catalysts, metal-organic and covalent organic frameworks, and earth-abundant water oxidation and CO₂ reduction catalysts has enhanced charge separation, catalytic efficiency, and product selectivity. Meanwhile, artificial leaf architectures and hybrid systems have demonstrated improved solar-to-chemical conversion efficiencies under increasingly practical conditions. Notably, several laboratory scale photoelectrochemical (PEC) systems have recently reported solar-to-hydrogen conversion efficiencies approaching 10% (unassisted, AM 1.5G illumination), reaching the threshold for commercial viability. Despite these advances, challenges related to long-term catalyst stability, efficiency losses, and large-scale implementation remain. This review summarizes key chemical developments from the past 3–5 years (2020–2025), highlighting emerging design strategies and integrated approaches that are shaping the future of scalable and sustainable artificial photosynthesis.

Keywords

Solar fuel generation Water splitting Carbon dioxide conversion Molecular complexes Photoelectrochemistry Heterojunctions Metal-organic frameworks MOFs Covalent organic frameworks COF Solar-to-hydrogen efficiency Charge separation.

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Effect of the Cu additions on the structure of the soldered (96.5- x)Sn - (3.5)Ag -(x)Cu alloy with x=0.2, 0.4, 0.6, 0.8 and 1 wt % There is none

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