Baghdad Science Journal

Using 1H-, 13C-, and 119Sn-nuclear magnetic resonance (NMR) spectroscopies in addition to Fourier transform infrared
spectroscopy (FTIR) for structural identification, we synthesized and studied three tin complexes of Ibuprofen in this
study. To improve poly(vinyl chloride) (PVC)’s photo-stability, the produced complexes were mixed one at a time. FTIR
techniques were employed to evaluate their effectiveness, and the results indicated the formation of new groups inside
the polymer structure following exposure to ultraviolet radiation. We also investigated the weight loss of the polymer
under irradiation and calculated the average molecular weight by comparing the viscosity before and after exposure.
Additionally, a variety of methods were used to investigate the surface morphology of PVC before and after radiation.
After irradiation, PVC treated with Ibuprofen tin complexes showed less cracks and spots and a smoother surface than
untreated PVC, according to optical and scanning electron microscopy (SEM) data. The modified polymers showed
increased resistance to photodegradation and had lower roughness factor, weight reduction, surface damages, and small
fragments generated compared to the blank PVC. This shows that the Ibuprofen tin compounds that were produced may
work extremely well as photo-stabilizers for PVC. Complex 1 performed better than the other stabilizers, which can be
due to its large conjugation system.

The coumarin scaffold was combined with nitrogen containing heteroatom molecule known as pyrazoline to increase
its biological activity, and it demonstrated a wide range of activity. The study involved the synthesis of a new compound
bycondensationmethod,andthestructuralstructuresofthepreparedcompoundswerecharacterizedusingspectroscopic
and analytical studies FT-IR, 1H-NMR,13CNMR, and mass spectrometry, through which it was proven that pyrazoline
ring through the appearance of protons of the methylene group in different coupling constants. On the other hand, the
proton of C11’, adapts to two different adjacent angles for the two protons of the methylene group, so the coupling
constant of the protons adjacent to each other is different, and the bidirectional angle between the protons can be
related to the karplus relationship with the adjacent proton coupling constant. The biological activity of the prepared
compounds was studied using the principle of ABTS• assay depended on the generation of the blue/green ABTS•
chromophore by the reaction between ABTS and potassium persulfate at about 734 nm, as the results of its effectiveness
showed the results show that coumarin-pyrazoline derivatives are characterized by high antioxidant activity that is
superior to ascorbic acid, especially the dimethylamine derivative

CyanoCobalamin (Vitamin B12) was determined using a simple, reliable, and affordable colorimetric method. According to this method, excess Ferrous sulfate (FeSO4.7H2O, or FS) is used to reduce vitamin B12, and the excess FS reacts with the reagent 1,10-phenanthroline to produce a soluble red color complex. The greatest wavelength of the spectrum of this complex was 510 nm. The concentration linearity range was 5-100 µg/mL. The RSD% values were 0.107-0.259% for intraday and 1.085-0.1378% for interday, while the Rec% values ranged from 95 to 100.833%. LOD and LOQ values were respectively 0.016 µg/mL and 0.053 µg/mL. The method was used to determine the presence of vitamin B12 in medicinal preparations with success.

The biomarker significance of chemokine (Cartilage Oligomeric Matrix Protein) was evaluated in the sera of 80 rheumatoid arthritis (RA) patients and 40 control men and women. A test ELISA kit was used in the Human Reader HS apparatus to measure the serum COMP, CRP, and RF. The Nihon Kohden Europes (MEK-6550K) analyzer apparatus was used for the testing of Complete Blood Count and the erythrocyte sedimentation rate (ESR), The Westergren device was used in this evaluation. The results demonstrated that COMP, CRP, RF, and ESR showed a significantly increased median in RA patients compared to control (COMP:104.79±1.95 vs. 47.79±1.34 ng/ml; CRP: 2442.09±172.32 vs. 1271.41±35.14 pg/ml; RF: 0.92±0.03 vs. 0.34±0.024 ng/ml; ESR: 33.81±2.52 vs. 15.53±1.13 MM/H). Binary logistic regression analysis revealed that COMP was a significant predictor of RA. The ROC curve analysis also revealed that COMP recorded an area under the curve of 1.00 in RA patients. In conclusion, serum COMP is a reliable diagnostic parameter that may accurately distinguish between those with active RA and control individuals.

The target of this work included synthesis of several new derivatives (B-B17) from Ciprofloxacin drug and evaluating antibacterial activities for some derivatives. The analogs were synthesized, designed, and characterized by 1HNMR, and FTIR. The first step involved the preparation of a 2-Chloroacetyl Ciprofloxacin drug from the reaction of Ciprofloxacin with chloroacetyl chloride in the presence of triethylamine. Then, the yield B with 2-aminobenzothiazole in the presence of glacial acetic acid as a catalyst to produce derivatives (B1-B8), Potassium phthalimide or Succinimide was used to prepared (B9-B12) compounds , and the (B13-B17) compounds were synthesis from 4-acetyl ciprofloxacin (B).The antibacterial and antifungal activity showed effectiveness against Gram-positive bacteria (Staphylococcus), Gram-negative bacteria (Pseudomonas aeruginosa), and fungi (Candida Albicans).

This study, carried out over six months at an Indonesian hospital, explores the benefits of standardizing medical record data and integrating health information systems for healthcare delivery. Utilizing a quantitative research approach, it focuses on the impact of precise data mining extraction on data analysis and the advantages of an integrated system for accessing patient records. Advanced data mining methods were employed for feature extraction, selection, and dataset reduction to enhance data classification accuracy. Findings revealed a direct correlation between the accuracy of data extraction and the reliability of data classification, highlighting the significant role of dataset reduction in improving analysis precision. The introduction of the XRP Model, a new predictive tool for assessing disease likelihood, marked a notable advancement, demonstrating high accuracy rates in predicting diabetes and heart disease (96.8% and 88%, respectively). The model\\'s consistent performance across various outcome scenarios underscores its potential in healthcare decision-making. This research evidences the value of advanced data mining and dataset reduction in refining data classification, thus facilitating better healthcare decisions. The XRP Model\\'s success in disease prediction suggests considerable benefits for healthcare services, offering insights crucial for the development and optimization of health information systems. These findings have the potential to influence healthcare policy and practice, advocating for a new standard in healthcare data management.

This study sought to examine the removal of some heavy metal ions from an aqueous media utilizing an adsorbent made from waste materials Cyperus papyrus and nano Cyperus papyrus. Because of their abundance of (OH) groups, Cyperus papyrus biomaterials are promising adsorbents for removing heavy metals. Therefore, this study proposed removing Al, Fe, Pb, and Cd from aqueous solutions using dried Cyperus papyrus. The effectiveness of removal was determined to be in this sequence Fe >Pb> Cd>Al. In another method, some of the cyperus papyrus was converted to nanopowder and used to investigate the elimination of Pb and Cd from aqueous solutions, and the results showed that the nano cyperus papyrus is more effective than normal cyperus papyrus. Normal cyperus papyrus was applied into two samples; the first was a sewage water sample, and the other was ground water. The Freundlich isothermal adsorption method worked better for the adsorption of Al, Fe, Pb, and Cd using Cyperus papyrus, and it also demonstrated an ion exchange process that took place in the adsorption surface layer that is uneven. Cyperus papyrus had a high affinity for adsorbing heavy metals Al, Fe, Pb, and Cd without additional chemicals. The results revealed that the used adsorbent had been a promising material for treating some contaminants and was eco-friendly.

Complexes of Vanadyl, Copper, Zinc, Cadmium, and Aureate with their double valence and Aureate with its triple valence were prepared using the azo dye (2,4,6-trihydroxy-3-((3-hydroxyphenyl) dixenyl)phenyl)ethane-1-one prepared newly from diazonium salt With 2,4,6-trihydroxyacetophenone, after isolation. The prepared materials were identified by available spectroscopic methods and diagnostic techniques for C.H.N, IR, UV-Vis, 1H&13C-NMR, Mass, thermogravimetric analysis curve, differential scanning calorimetry, and complexes, these techniques included as well as determining the metal percentage, determining the chlorine content, magnetic susceptibility, and molar conductivity. The results showed that the ligand is anionic (negative) tetradentate when coordinated with Vanadyl, Copper, Zinc, Cadmium through the phenolic oxygen atom, the carbonyl oxygen atom, and the azo nitrogen atom. It was tridentate e when it coordinated with Aureate through the phenolic oxygen atom and the azo nitrogen atom, giving the planar square shape (neutral) while the zinc and cadmium were (neutral) octahedral containing two coordinated water molecules and copper was tetrahedral shape (neutral) and Vanadyl complex give trigonal bipyramidal shape (neutral). Then the potential of these prepared compounds as antioxidants was determined by inhibiting free radicals using DPPH as a free radical and vitamin C as a reference to determine The Radical scavenging activities gave the results (Au-complex > H4L >Ascorbic acid>Zn-complex >Cu-complex >Cd-complex >V-complex).

The genus Usnea was reported to synthesize the bioactive secondary metabolites, including cytotoxic and antibacterial activities. To continue our study on bioactive compounds from Usnea sp, we studied secondary metabolites and their bioactivities of Usnea sp. The aim of this study was to determine the chemical constituents of lichen Usnea sp. Methanol extract of Usnea sp. was prepared by solid liquid extraction followed by fractionation and purification of the crude extract by several chromatographic techniques using n-hexane and ethyl acetate as solvents to obtain two pure compounds (1 and 2). The structures of both secondary metabolites were analyzed by 1D and 2D (one and two-dimensional) NMR spectroscopy and identified as 2,6-dihydroxy-4-methylbenzoic acid (1) and (-)-placodiolic acid (2). Cytotoxic activity of compounds against MCF-7 cells was evaluated using the MTT assay (IC50 = 554.82 and 5.10 µM, respectively). Both compounds were also assayed for their antibacterial activity using disc diffusion method. Inhibition zones of compound 1 against S. aureus, E. coli, and S. pyogenes were 6.37 ± 0.21, 7.57 ± 0.15, and 5.43 ±0.12 mm, respectively. In addition, compound 2 inhibited the growth of S. aureus, E. coli, and S. pyogenes bacteria (Inhibition zones = 10.43 ± 0.25, 11.63 ± 0.21, and 10.63 ± 0.21). The result of biological activities demonstrated that 2 exhibited stronger cytotoxic activity against MCF-7 cells as well as antibacterial activity than compound 1. Based on the theses results, compound 2 could be a promising candidate of antibiotics in the near future.

The purpose of this study is to find out the optimal substitution ratio for lead with yttrium through the structural properties of the prepared compounds. The superconductor compound (Y1−xPbxBa2Cu2.85La0.15O6+δ) was prepared by the solid state reaction (SSR) method. The effect of partial substitution for the lead on the compound\\'s structural characteristics has been studied. The variation of (x) is (0, 0.05, 0.1, 0.15, 0.20, 0.25). With a pressure of 7 tons per square centimeter, the combined powder was formed into a disc with a thickness of (about 0.2 cm). The samples were sintered for a while (24 hours ) at a rate that changed from room temperature (27°C) to (850°C). Based on the X-ray diffraction (XRD) study. All samples were discovered to contain an orthorhombic structure. It was established that variations in the lead concentrations in each of our samples result in variations in parameters for a lattice (a,b,c),(c/a), dm, Tc, and energy gap. Its best values were recorded at a concentration (x = 0.1), where the values of the lattice constants in angstrom units (a, b, c) were (3.807346, 3.886549, and 11.70871) respectively, the highest value for (Tc) was (112.1). The density value (dm) was (6.42604 gm/cm3), the highest percentage was (c/a =3.075295) and the highest energy gap was (Eg = 0.03384 eV). So, it can be considered the optimal replacement ratio under the conditions of this work. Scanning electron microscopy(SEM) was used to analyze microscopic pictures of the compounds prepared with different substitution ratios in addition to the pure sample at very high magnifications (SEM) at a degree of magnification (5μm,200nm).

Endometrial receptivity is the limiting phase in the success of IVF treatment, Invasion of human trophoblast cells to the endometrial is regulated by many factors such as EDN1 and IL-1β. This study aims to verify the relationship between polymorphism and gene expression of EDN1 and IL-1β genes with embryo implantation in infertile women under the IVF program. The peripheral blood samples were collected on the day of embryo transfer an hour after embryo transfer, after approval from 60 women, and divided according to the outcome of embryo implantation outcomes, the failure implantation group included 35 women, and the success implantation group included 25 women. The results of sequencing revealed two genetic variants in the EDN1 gene, SNP rs2070699 showed no association with the embryo implantation outcome in infertility women according to Fisher probability. SNP rs2070699 shows a higher frequency of genotypes GG and TT than the GT genotype in the study groups. Variant No.7196T>G on exon 2 shows that the TT genotype had the highest frequency in the success group, while the TG genotype recorded the highest frequency in the failure group. The results of EDN1 and IL-1β gene expression fold change showed non-significant differences between groups. The correlation between EDN1, and IL-1β gene expression showed a significant positive relationship. In conclusion, Genetic variants of the SNPs rs2070699 and No.7196 in EDN1 do not affect the gene expression level in infertility women under the IVF program. EDN1 and IL-1β gene expression have a significant positive relationship in the luteal phase and both are upregulated in women with successful implantation.

Cystic echinococcosis (CE) is an endemic disease that causes serious disease and economic loss in the majority of countries around the world. MiRNAs are an epigenetic factor that is essential to the regulation of the immune response by interfering with cytokine expression; one such miRNA is microRNA-146a. The aim of the present study was to assess if we could use microRNA 146a as a biomarker for the detection of CE and to determine the relationship between microRNA 146a gene expression and IL-17 in patients with CE. The study included 50 CE patients who were admitted to the hospital in Baghdad, Iraq, for CE removal surgery and 50 healthy controls. The serum was collected from September 2022 to June 2023. The sample’s age range was 20–55 years. Rural patients were infected at a higher rate than urban patients (74.00% and 42.00%, respectively), The lung was the most affected organ (74%), followed by the liver (18%), then the liver and lung together (8%). CE patients had significantly higher miRNA-146a fold expression than control group members (4.33 ± 1.01 and 1.00 ± 0.23, respectively). The serum level of IL-17 was significantly higher in the control group, at 129.15 ± 4.73ng/L, than in patients, at 105.99 ± 5.81ng/L. According to our findings, miRNA-146a is upregulated in the sera of CE patients, which leads to the development of novel biomarkers for echinococcosis and it is associated negatively with IL-17 levels. This may interfere with their immune system\\'s inflammatory response and contribute to the pathogenesis of CE.

The aim of this study was to evaluate the levels of urinary Hydroxyproline, urinary Malondialdehyde, urinary Creatinine, and urinary Albumin as potential biomarkers for air pollution in two distinct sites: Site 1, an industrial area and Site 2, a non-industrial area, also measuring the urine albumin-to-creatinine ratio (UACR) to further investigate the effects of air pollution. The study employed a cross-sectional design with 90 participants. Site 1 had 56 participants (42 adults, 14 children, 11.2% of the total population), while Site 2 had 34 participants (23 adults, 11 children, 11.3% of the total population). The findings of the study indicated that the concentrations of Hydroxyproline and Malondialdehyde were significantly higher at Site 1 for both adults and children compared to Site 2. Biomarkers indicate more sensitive to industrial air pollution exposure. On the other hand, the concentrations of Creatinine and Albumin were found to be higher at Site 1; however, the difference was not statistically significant when compared to Site 2 for both adults and children. UACR values were measured at Site 1 and Site 2. For adults, the UACR values were 10.093 and 8.870 mg/g, respectively, while for children, they were 11.061 and 9.882 mg/g, respectively. All values were within the normal range, suggesting that air pollution did not significantly impact kidney function in this study. Elevated hydroxyproline levels indicate collagen alterations, which could be caused by air pollution-induced tissue injury. Increased malondialdehyde and urine albumin levels indicate oxidative stress and renal impairment caused by exposure to air pollution.

Salt stress has adverse impacts on chili pepper (Capsicum annuum L.) growth, development and production. Plant tolerance must be increased to be able to adapt to salinity stress conditions. A factorial experiment with three factors according to Randomized Complete Blocks Design (RCBD) was conducted with three replicates. Polyamine P0, P1, P2 (0, 2, 3 mg L-1 Polyamine), salicylic acid A0, A1, A2 (0, 75, 150 mg L-1), sodium chloride S0, S1, S2 (0, 2000, 4000 ppm) with their interactions were investigated. Salinity had a significant negative effect on the phenotypic characteristics and yield. Polyamine P2, salicylic acid A2 and their interaction (P2A2) were superior, as the highest value was recorded in many of the studied characteristics in comparison to the control. Interaction P2A2S0 gave the highest value compared to other parameters for all processing methods. In summary, this result indicates that the application of polyamine and salicylic acid can effectively reduce the harmful effect of salt stress in chili pepper.

The presence of nitrate in water has become a concern for many environmentalists because it has reduced the quality of water used to meet people\\'s clean water needs. The study of the temporal variation of nitrate in water flow is expected to provide a complete understanding of the influencing factors that need to be managed to control the nitrate concentration in water. This study aims to analyze the temporal variations in the nitrate concentration at the Guntur Spring, one of the springs in the Gunungsewu Karst Area that plays a role in the provision of clean water. The data used in this research include data on nitrate concentration in spring water, rainfall, and spring discharge. Sampling was carried out every two weeks from February 2018 to March 2019 to understand the temporal variation in nitrate concentrations. Discharge and rainfall data were obtained from automatic recording during the same period as water sampling for nitrate analysis. The result shows that the nitrate concentration throughout the year in the Guntur Spring does not exceed the quality standard. The good water quality is caused by the natural filtration process that is still going well due to the low level of karstification that is still dominated by fissure flows. In addition, this research has found that the most influential variation in nitrate concentration in the spring flow at Guntur Spring is the cropping pattern in the area.

In this paper we made a comparison between the theoretical results of one and two components of partial level density Ericson\'s formulae with the experimental results. In the frame work of equidistant spacing model. It is noticed that the values of one - component partial level density formula increases with increasing the exciton number. the excitons numbers is taken 3, 5, 7 and 9. The same excitons number is substituted in two-component partial level density formula, but the increase in partial level density values in case of two components with the excitons numbers is slight and this change is so small that it cannot be seen. Therefore one can say that the increase in exciton number effects on the one-component partial level density value and lead to an increase them. But in the case of two-components the partial level density value doesn\'t affect by the change in exciton number values because the energy distributed on particles more than in case of one- component and this makes partial level density less than in case of one-component and the effect of change in exciton number doesn\'t appear. In case of one-component when the exciton numbers is n=3 the theoretical partial level density curve lies below the experimental curve and when n=5 the theoretical curve become more close to the experimental curve. And at n = 7 the theoretical curve intersect with the experimental curve at E = 5 MeV, So when n=9 the theoretical curve intersect with the experimental curve at 4 MeV.

The role of nanotechnology in remediating organic pollutants is substantial, considering the significant environmental consequences arising from the extensive agricultural use of pesticides. Consequently, nano adsorbents have attracted particular attention due to their exceptional properties and capacity to effectively degrade and eliminate various organic pollutants, including pesticides. Here, an attempt was made to fabricate and characterize silver nanoparticles (Ag NPs) using orange peel extract as a reducing agent. Transmission Electron Microscopy (TEM) images confirm the quasi-spherical shape of the Ag NPs, with average sizes of 40 nm, 30 nm, and 20 nm corresponding to different silver nitrate concentrations (0.5, 1, and 2 moles). UV-VIS Spectroscopy analysis revealed absorption peaks at 427 nm, 429 nm, and 437 nm for sizes of 20 nm, 30 nm, and 40 nm, respectively, highlighting the correlation between size and optical characteristics reveals that there is a noticeable redshift in absorption peaks as size increases. Zeta potential analysis indicated moderate stability for the fabricated nanoparticles, with values of -26.6 mV, -25 mV, and -24 mV for nanoparticles of sizes 20 nm, 30 nm, and 40 nm, respectively. X-ray diffraction (XRD) analysis confirmed the presence of a polycrystalline structure with a cubic crystal phase of fabricated Ag NPs with crystallite sizes of approximately 11.0839 nm, 11.0694 nm, and 10.2993 nm for 20 nm, 30 nm, and 40 nm nanoparticles, respectively. Fourier-transform infrared (FTIR) analysis exhibited functional groups from the orange peel extract on the nanoparticles\' surfaces, enhancing their stability and bioactivity. Additionally, the interaction between Ag NPs and three different pesticides (Cypermethrin, Lambda-cyhalothrin, and Methomyl) was studied, indicating the potential for Ag NPs to degrade halocarbon pesticides through electron transfer processes. The study provides valuable insights into the green synthesis of Ag NPs and their potential applications in various fields, including environmental remediation and agriculture.

The study investigates the influence of incorporating carbon nanoparticles (CNP) and polypropylene fibers into epoxy composites on their mechanical properties, focusing on the elastic modulus and hardness. The results show that an increase in the weight percentage of polypropylene fibers leads to a corresponding rise in the elastic modulus of the epoxy composites. The presence of nanocarbon black (CNP) in various concentrations did not have a clear effect on the elastic modulus. On the other hand, the elastic modulus increased linearly with increasing the percentage of hybrid filler (CNP/PP). Regarding to hardness test that was achieved using the shore D tester, lubrication properties improved with increasing weight percentages of CNP, while the hardness decreased a lot with increasing the weight percentage of polypropylene fibers. the results of the recovery test revealed that the CNP plays a major role in a preference for healing along the width axis of the groove, while the addition of polypropylene fiber makes the epoxy matrix favor healing along the depth axis, When using hybrid filler (CNP/PP) the recovery behavior was almost equal in both the transverse and depth axes. The above results shed light on the recovery behavior of hybrid composites and the possibility of their self-healing while at the same time improving their mechanical properties and thus increasing the requirements they perform in various engineering applications.

Within the framework of the shell model, the single-particle wave functions of Hartree-Fock approximation adopted with Skyrme interactions like Skxtb, Skxs25, Sly4 and Bsk9 to get the thickness of the neutron skin, the mirror radii and the charges mirror radii for 18Ne-18O pair mirror nucleus. The wave functions were calculated using the NuShellX@MSU shell model code. The computed values of root -mean - square -radii are influenced by the type of interaction employed. The symmetry energy and its slope at nuclear saturation density and the mirror energy displacement were also determined. Comparisons between theoretical and experimental data were made and it was concluded that the data are well described in of this pair mirror nucleus.

The current investigation concentrated on even-even nuclei forms to isotopes that have masses number less than 100 (A>100) to ((_28^(58-68))Ni )elements . This includes a look at deformation parameters 〖(β〗_2) derived from reduced electric transition probability (E2)↑ as well as distortions parameters(δ) derived by intrinsic electric quadrupole moment(Q_0). A Roots mean square Radius〖<r^2>〗^(1/2 ) We studied the most important deformation parameters (,2) , and major and minor of ellipsoid axes (a,b) in addition to the difference between these axes (R) All these parameters were calculated using the deformed shell model equations and applied theoretically in a special program. Differences in nuclei forms were observed for selected isotopes via drawing two 2- dimensional shapes. According to the current findings. Thus the distortion coefficients decrease as the number of neutrons approaches the magic number. Thus it was observed that the most distorted and inclined isotopes of the elliptical shape are the isotopes with numbers of protons and neutrons far from the magic numbers Also, the obtained results were compared with the theoretical results from Raman source by \\"single-shell Asymptotic Nilsson Model \\"(SSANM), and noticed that was little change in the results. Also observed from the results that ((_28^58)Ni) is the most stable isotope and has a clear spherical shape because (Z) is equal to (28) a magic number and (N) is equal to (30) a number close to the magic number.

Shape recognition is an essential task in machine vision applications. Many techniques have been adopted for shape recognition all of them distributed according to two directions of shape features belonging to boundary or region, in many categories of applications in addition to recognition like shape simplification, restoration classification and retrieving. This paper presents a proposed testing algorithm for shape recognition according to boundary or global base features where the approximated contour of the shape is derived by the Douglas Peucker line simplification approach. The initial diversity value starts with fixit value according to an undetermined number of iterations until reaching to target set of approximated points for testing, where in each iteration the diversity value increases gradually with the fixit interval. This algorithm evaluates the state, “Is there an optimal number of approximated points as features vector can be adopted that satisfy the maximum recognition rate”. Before learning and testing stat the features vector derived after applied a distance matrix among the approximated set. The recognition process experiments on the MPEG-7 dataset when classified using Support Vector Machine (SVM) through different kernel functions. However, the experiment results show the proposed testing recognition achieved to high rate about 0.961 according to a specific number of approximated datasets when adopting a radial basis function (RBF) as kernel function based on Matlab testing environment.

This paper aims to analyze the M/M(a,b)/1 multiple working vacations queuing model with a breakdown. Instead of the server being fully idle during the vacation period, the server serves at a different rate during multiple working vacations. The system has only one server, and the service rate varies depending on the arrival state. Customers’ enter the system to get service with parameter λ_v following the Poisson distribution. The server provides service for customers’ in regular busy periods with parameter μ and under multiple working vacations, the server provides service with parameter μ_v with the exponential distribution. In this model, batches of customers are served as a group under the general bulk service rule, which was introduced by Neuts. In the batch service process, the service times for each customer within a batch may be independent and random variables. The number of customers’ in each batch can also vary. Thus, each batch of service contains a minimum of ’a’ units and a maximum of ’b’ units of customers’. Suppose that the number of customers waiting in the queue is less than ’a’ server begins a vacation random variable V with parameter η, the breakdown β_v occurs during the busy state. This paper analyzed the steady-state equation, steady-state solutions, and measures of system performance. Specifically, various performance analyses, namely the mean length and other characteristics like the probability that the server is idle, regular busy and working vacation periods are analyzed. Finally, this paper computed the results with the working vacation and the classical multiple working vacation models.

In this paper, the algorithm (Stochastic Gradient Descent) SGD, which is one of the most famous optimization algorithms, was hybridized with genetic algorithms in finding the roots of non-linear equations, which is one of the most important mathematical problems due to its application in all sciences. Genetic algorithms are used here to find the optimal primary root of SGD algorithm and its application in reducing the studied objective function. Some famous algorithms need initial point to reach the solution in terms of stability. The proposed algorithm is tested on several standard functions and the results are compared with the famous algorithms, and the results show the efficiency of the proposed algorithm through tables and figures.

Molecular similarity, governed by the principle that "similar molecules exhibit similar properties," is a pervasive concept in chemistry with profound implications, notably in pharmaceutical research where it informs structure-activity relationships. This study focuses on the pivotal role of molecular similarity techniques in identifying sample molecules akin to a target molecule while differing in key features. Within the realm of artificial intelligence, this paper introduces a novel hybrid system merging Swarm Intelligence (SI) behaviors (Aquila and Termites) with Neural Networks. Unlike previous applications where Aquila or Termites were used individually, this amalgamation represents a pioneering approach. The objective is to determine the most similar sample molecule in a dataset to a specific target molecule. Accuracy assessments reveal a manual evaluation accuracy of 70.58%, surging to 90% with the incorporation of Neural Networks. Additionally, a three-dimensional grid elucidates the Quantitative Structure-Activity Relationship (QSAR). The Euclidean and Manhattan Distance metrics quantify differences between molecules. This study contributes to molecular similarity assessment by presenting a hybrid approach that enhances accuracy in identifying similar molecules within complex datasets.

Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on recurrent neural network (proposed long short term memory(LSTM) model). The proposed LSTM architecture is designed and trained with inefficient optimizer, tuned hyperparameters and a good choice dropout ratio to avoid overfitting. The aim of this article is to conduct an experimental comparison between the classical machine learning approach (J48 & logistic regression) and deep learning represented by LSTM. The experimental results show that the proposed approach of LSTM outperforms other approaches with the two datasets in predicting the price and movement of the stock market.

Due to the extraordinary development in the production and exchange of multimedia across unprotected networks, there is a greater need to develop reliable secure, and effective cryptographic algorithms. This paper proposes a new lightweight encryption algorithm combining SALSA20 and password-based Key Derivation Function2 (PBKDF2) for the encryption of color images. Due to the PBKDF2 characteristics such as strengthening the security of the password by applying multiple rounds of a pseudorandom function (PRF) to generate the key, Salt usage adds additional randomness to the key derivation process, therefor it is used to enhance SALSA20. By offering a large key space, the recommended lightweight image encryption has demonstrated robustness against brute force attacks. Additionally, the suggested algorithm capable of protecting against statistical cracking, differential attack, and image security is good based on the histogram, correlation, NPCR, UACI, and Entropy criteria. Encryption time for test images is very short, ranging from one to one and a half seconds, so it is close to being run in real time.

Communication impairments have a broad spectrum of medical causes, such as speech disorders, hearing loss, brain injury, stroke, and physical impairments. As a result, communication disorders can affect social development and interpersonal relationships. Speech impairments can benefit from early speech treatments; however, the majority of rehab facilities across the world still carry out this process manually. A wide range of studies has been conducted on speech processing for various human languages. Machine learning and deep learning have been applied to the medical and healthcare industry to enhance rehabilitation by utilizing the new technology. This study analyzed the classification accuracy of the designed network and other pre-trained models (VGG-Net, AlexNet, and Inception) and performed a complete comparative analysis to assess the classification accuracy of several pre-trained models. The sound is converted to the image as a new way to see them in the neural network via a newly proposed concept named image-profiled data. These image-profiled datasets that used a spectrogram and a Mel-frequency cepstral coefficient (MFCC) produced this study\'s best results and accuracy. This project aims to develop a new neural network that can successfully distinguish between the vowels from the voices of normal people, patients with speech disorders and the mix from the prior two groups using the six and twelve classes of Malay vowels. The designed network model, which used 6 batch sizes, 20 epochs, and ADAM as the optimizer, this study presented and achieved the maximum accuracy values of both classes for image-profiled audio data in analyses conducted.

Tahfiz education is popular and accepted in Malaysia. Today, tahfiz centres and modern institutions offer it. Since these Islamic entities fulfil sacred religious obligations, good governance and accountability are essential. Modern Malaysian Islamic education requires innovative technology for Tahfiz education and administration. Tahfiz learning management is hampered by a lack of resources, infrastructure, and facilities. No model has been implemented to organise tahfiz institutions for better management. This study evaluates the Integrated Management Model of Malaysian Private Tahfiz Centres (I3M-Tahfiz) for practical education satisfaction efficiency. User satisfaction will be prioritised when implementing the I3M-Tahfiz Model at a random Malaysian Tahfiz institution. The framework implementation uses the subjective approach algorithm to calculate user Mean Opinion Score (MOS) from a user acceptability review study. A Tahfiz institution that prioritises QoE will likely gain community support and engagement. This can boost enrollment, donations, and word-of-mouth, expanding the institution's reach. After establishing MOS and Resource, linear regression is used to determine the relationship between user acceptability and a major tahfiz efficiency factor. MOS results show 78% relationship between user acceptability and I3M-Tahfiz frameworks. In conclusion, I3M-Tahfiz encompasses spiritual growth, efficient memorization, customised instruction, community support, long-term student effects, technology integration, flexibility, global competency, and education leadership.

The modulus of smoothness is essential for modern analysis and its applications. Is a versatile tool in approximation theory that helps in understanding the properties of approximation methods, characterizing function spaces, and analyzing the convergence and accuracy of numerical algorithms. It helps in determining the optimal number of terms or the optimal choice of basic functions to achieve the desired level of accuracy in approximation of a function and rate of convergence. The smoothness modulus has many applications, including its applications in numerical analysis, particularly in the analysis of numerical methods for solving differential equations, optimization problems, and integral equations. Many papers introduced the ordinary modulus of smoothness with one variable. However, few researchers have tried to approximate functions with multiple variables and mixed modulus. This paper tries to fill in that gap introducing a new k -mixed modulus of smoothness for measurable functions 〖f∈L〗_p (〖[0,2π]〗^d ),0