مجلة جامعة صنعاء للعلوم التطبيقية والتكنولوجيا

The matrix's complexity makes measuring acrylamide in food items challenging, requiring a time-consuming extraction technique and high method sensitivity. A homemade solid phase extraction (SPE) device and a gas chromatography/nitrogen phosphorus detector (GC/NPD) were used to establish a simple and inexpensive acrylamide detection method in fried fish. Optimization and validation were used to measure acrylamide concentrations in twelve fried fish samples, four of which were home-fried and eight from Sana'a, Yemen, restaurants. The validated technique has high linearity R² (0.995) in the 0.02–4 ppm range of acrylamide standards and good sensitivity with LOD (0.0062 ppm), substantially below the authorized level. The twelve samples had acrylamide values of 0.0583–0.4643 ppm. Due to variations in thermal treatments during frying, market-fried fish samples had greater acrylamide concentrations than home-fried fish samples.  In the current study, the improved simple extraction process and GC/NPD protocol were useful for acrylamide measurement and may be employed as a prescreening tool for food sector acrylamide quantification.

Arabic information retrieval is challenging due to the language's complex morphology and syntax. Preprocessing and stemming improve the accuracy and efficiency of Arabic information retrieval. This paper provides a comprehensive analysis of the existing literature on Arabic preprocessing and stemming techniques. The paper identifies the limitations and challenges of these techniques. The paper emphasizes the importance of preprocessing and stemming and underscores the need for further research to improve Arabic information retrieval. This study evaluates ten stemmers on a public dataset. The results show that root-based stemmers: Lucene, and khoja got the highest reduction rate 90.9%, and 85% respectively. The results emphasize that root-based stemmers have good conflating ability for similar terms, while light-based stemmers under-stem similar terms.

The emergence of antibiotic-resistant bacteria is a major global public health concern. Antibacterial agents are one of the most exciting areas for the use of nanoparticles and have shown great potential as alternative antibacterial agents due to their outstanding physical and chemical properties. The biosynthesis and antibacterial activities of Silver Nanoparticles (AgNPs) could contribute to the development of innovative antimicrobial drugs with potential for a variety of medical applications.

The X Ray Diffraction (XRD) results showed that the formed particles were pure silver nanoparticles with a cubic crystal structure and granular size. Fourier-transform infrared (FTIR) also showed that functional aggregates formed, and the thumb region confirmed the presence of silver nanoparticles. In addition, we investigated the Uv-Visible and biological activity of AgNPs. A study of the biological activity of gram-positive (Staphylococcus aureus) and gram-negative (Escherichia coli, and Klebsiella pneumonia) bacteria showed the importance of nano-silver particle biosynthesis.

The performance of a classification model in machine learning is affected by many factors, such as the type of machine learning technology used. Accuracy varies from method to method. This paper presents a comparison between the performance of different models in terms of the machine learning technique used (e.g. KNN, NB, SVM, DT, RF, MLP). Based on the data provided by the Tax Authority of Yemen, which is related to the commercial and industrial profits tax, which consists of 760 attributes, after the preprocessing of data. The dataset partition technique used k-fold validation. The paper shows that the e Naïve Bayes (NB) classifier gave the highest result in accuracy and other measures. Then KNN, SVM, and RF gave the same results in accuracy 99.87%, but in SVM, KNN the results were also the same in the rest measures, while in RF models the rest measures were 97.91%,99.95%, and 98.91% in Recall, Precision and F-score in order.  MLP gave 98.42 in accuracy with 66.62%, 64.21%, and 64.40 in the recall, Precision, and F-score, then DT gave 97.76% in accuracy with 57.006% ,99.24% and 72.41% in the recall, precision, and F-score.

Frequent set-item mining is a widely used technique in the field of data mining. The algorithm utilized in Association Rules constitutes the primary source of contention; this approach is memory-intensive and time-intensive. The extraction process for concealed patterns of frequent item sets, on the other hand, becomes more time-consuming as the volume of data grows. Therefore, the necessary algorithm for mining the patterns of frequently occurring concealed item sets must be memory-efficient and fast-running. By analyzing various algorithms for locating frequent item sets, this paper aims to contribute to the development of a more efficient algorithm in this domain. The paper will evaluate the efficiency of different algorithms by considering their memory usage and runtime. Additionally, it will explore potential improvements to existing algorithms to enhance their performance in mining frequently occurring concealed item sets.

The drug's stability, which is a prerequisite for good drug quality, cannot be simply established unless a reliable and trustworthy method for demonstrating stability is applied.   Creating such a method is a challenging task. In this work, we developed and validated a reversed-phase stability indicating liquid chromatographic technique with photo diode-array detection to analyze paracetamol (PCM), methylparaben (MP), propylparaben (PP), and their degradants in commercial oral suspension.  The compounds and their degradants were separated using a Phenomenex C8 column (250 mm x 4.6 mm, 5 µm) and a mobile phase of pH 4 consisting acetonitrile, potassium di-hydrogen ortho-phosphate, tri-ethylamine, and glacial acetic acid in a 40:58:1.5:0.5 ratio, at 1.2 mL/min. All chemicals separated in within 12 min.  The developed method followed the guidelines of the International Conference on Harmonization (ICH) and fulfilled all its requirements in terms of linearity, recovery, reproducibility, detection, and quantitation limits. The dependability of the developed method was shown by recoveries of 98.88% to 101.80% in 102 samples from 34 batches, indicating that it can be used in quality control step for paracetamol, methylparaben, and propylparaben in oral suspension products.

The presence of Hg in canned tuna flesh is a major source of customer concern. Thus, the primary goal of this investigation was to evaluate total mercury levels in Yemeni canned tuna. Thirty-one samples of seven popular locally canned tuna brands were acquired from local stores in Sana'a. A Direct Mercury Analyzer was used to determine the mercury content. The linearity of the method was tested by assessing a series of mercury standards in triplicates at concentrations ranging from 20 to 500 ppb. The correlation coefficient for this method was 0.9993. The repeatability of the procedure was measured as intra-day variation and given as the relative standard deviation, which did not exceed 4.45%. This indicated the excellent precision of the method. Mercury recoveries from spiked actual canned tuna samples were between 96.61% and 100.49%, demonstrating excellent accuracy and an acceptable procedure for mercury measurement. The limits of detection and quantitation were 1.62 ppb and 5.4 ppb, respectively. The mercury content in 31 canned tuna samples was less than the 500 ppb standard imposed by the Yemeni Organization for Standards Metrology and Quality Control (YSMO).

Pearl Millet (Pennisetum glaucum (L.) R. Br.) is an important crop plant cultivated in many countries, including Yemen, due to its high nutritional value. Landrace, temperatures, and rainfall are crucial factors when it comes to improving the cultivation of crops for the benefit of man and animals. Therefore, the aim of this study was to statistically evaluate the morphological (Plant height, Leaf area, area index and number, and inflorescence length) & physiological (Biomass, Grain Yield, and Seed weight) parameters of 20 Pearl Millet landraces that comply with the amount of rainfall to produce the best grain yielding and/or high biomass production when cultivated in the Al-Mawasit district, Taiz. The Grain Yield of landrace 25508 (mean grain yield of 3.1 t/ha) was found to be greater than the grain yield produced by the other studied landraces. Moreover, landraces 25366 and 25353 were found to give the greatest biomass (mean biomass of 6.7t/ha). 

Aluminum alloys are important in many industrial applications because of their light weight and good mechanical properties. In this study, the effect of copper addition with different percentages ( 0, 0.1, 0.2, 0.3wt. %) on  the  microstructure  and  mechanical  strength  of Al-Si alloy were studied using X-ray fluorescence (XRF), X-ray diffraction (XRD), scanning electron microscope (SEM) and Vickers hardness (Hv) tests. XRD and SEM analyses showed that the Al-Si alloy consisted of α-Al and Si phases. The intermetallic compound (IMC) CuAl₂ was detected with the addition of Cu. This IMC causes a change in the lattice constant and inter-atomic spacing (d_hkl). The distortion and dense of the microstructure are considered indications of the enhancement in the hardness of alloys. The Vickers hardness (Hv) was measured for the samples before and after sintering. The highest value was 28.755 Hv with 0.2wt. % Cu after sintering, whereas the smallest value was 11.643 Hv without Cu content before sintering. This improvement in hardness is attributed to the temperature that promotes the diffusion of Cu atoms into theAl lattices.

A linear analysis was performed to investigate the basic properties of waves propagating in different directions in magnetized quantam plasma consisting of classical warm ions and relativistic degenerate electrons. We employ a quantum magnetohydrodynamic approach considering quantum corrections, spin effects in addition to relativity, and a polytropic index to obtain a generalized dispersion relation of the regarded plasma system. The considered system supports three types of magnetohydrodynamic waves: Alfven, fast, and slow magnetosonic waves. The obtained modified Alfven and magnetosonic dispersion relations are affected by the obliqueness factor, spin magnetization, and plasma beta .The fast and slow modes were also altered owing to the Bohm potential and relativistic degenerate pressure impacts. Examination of the influences of these parameters revealed a significant modification of the phase velocity features of the magnetohydrodynamic waves. The results obtained may be applicable to relativistic magnetized quantum plasmas in astrophysical environments.