Iraqi Journal of Science

This research aimed to explore the potential involvement of oxidative stress in the onset of migraines. The primary objective was to assess the concentrations of malondialdehyde (MDA), which serves as an indicator of oxidative stress, as well as nitric oxide (NO), a marker for nitrosative stress, and asymmetric dimethylarginine (ADMA), an indicator of endothelial dysfunction. Ninety (90) participants were recruited in this research work from the neurology department's outpatient headache clinic at Al Jumhury Teaching Hospital in Erbil city, the study consisted of (60) patients and (30) as controls. In the migraine group, there were (45) females and (15) males, while the control group was comprised of (20) females and (10) males with age and sex matching. The study was granted ethical approval by the Human Research Ethics Committee (HREC) at the Department of Biology, College of Science, Salahaddin University-Erbil, on February 6th, 2022.The study showed that the migraine patients had significantly greater levels of MDA, NO and ADMA than the control group. Additionally, the number of headache days experienced per month by migraine patients was positively correlated with the serum concentrations of MDA, NO, and ADMA. Specifically, as the frequency of monthly headache days increased, levels of the oxidative stress markers MDA and NO, as well as the endothelial dysfunction marker ADMA, also tended to be higher.

In this work, new Schiff bases of quinazolinone derivatives (Q1-Q5) were synthesized from methyl anthranilate. The synthesis involved three steps. In the first step, methyl anthranilate was reacted with isothiocyanatobenzene, producing the thiourea derivative K1. The second step entailed reacting K1 with hydrazine hydrate, synthesizing 3-amino-2-(phenylamino) quinazolin-4(3H)-one (K2). The third step involved reaction of K2 with various aromatic aldehydes, yielding the Schiff bases derivatives Q1-Q5. The chemical structures of these compounds were identified by FT-IR,1H NMR and 13C NMR spectroscopy. The newly synthesized derivatives (Q1-Q5) were subjected to rigorous evaluation to assess their efficacy as corrosion inhibitors for carbon steel in an acidic environment (1M HCl). Weight loss measurements were employed, and the concentration of the compounds was varied to gauge their performance at ambient temperature. Among the array of compounds tested, Q1 exhibited remarkable performance, particularly when employed at a concentration of 0.5 M. The corrosion inhibition properties of compound Q1 were evaluated. It exhibited excellent inhibition efficiency, reaching a peak of 93% according to the investigation. Further dynamic polarization analysis revealed some interesting relationships between inhibition efficiency, concentration, and temperature. Specifically, higher concentrations and lower temperatures led to enhanced inhibition by Q1.

This study evaluated the effect of two different types of amino group-containing pharmacological inhibitors on titanium corrosion under acidic conditions. The first inhibitor examined was the antibiotic trimethoprim. The second inhibitor studied was the nonsteroidal anti-inflammatory drug voltaren. The results showed that titanium had a high corrosion current in the absence of a corrosion inhibitor, however, trimethoprim notably enhanced corrosion resistance and protection percentages of titanium (%IE) at higher concentrations by adhering to the metal surface, as evidenced by improved protection percentages. Furthermore, the results showed that as Voltaren concentration was increased, both corrosion resistance and inhibition efficiency decreased. This demonstrates that less Voltaren was absorbed onto the metal surface as compared to trimethoprim.

This study synthesized polyacetal from the reaction of polyvinyl alcohol with para-nitrobenzaldehyde. Polyacetal/polyvinylpyrrolidone polymer blends were prepared using solution casting. Gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were biosynthesized using onion peel extract as the reducing agent. Nanocomposites were fabricated by blending polyacetal/PVP with AuNPs and AgNPs at different ratios. XRD and FESEM characterized the AuNPs and AgNPs. FTIR, FESEM, TGA, and DSC characterized the polyacetal, polymer blends, and nanocomposites. DSC and TGA confirmed the improved thermal stability of the polymer blends and nanocomposites. Nanocomposites demonstrated higher efficacy in inhibiting lung cancer cell lines compared to the blends alone.

The new azo dye was synthesized via the reaction of the diazonium salt form of 3-aminophenol with 2-hydroxyquinoline. This dye was then used to access a series of complexes with the chlorides of manganese, iron, zinc, cadmium, and vanadium sulfate. The prepared ligand and its complexes were characterized by FT-IR spectroscopy, UV-visible spectroscopy, mass spectrometry, thermogravimetric analysis, differential scanning calorimeter, and microelemental analysis. Conductivity, magnetic susceptibility, metal content, and chlorine content of the complexes were also measured. The ligand and cadmium complex were identified using1H NMR and 13C NMR spectroscopy. The results showed that the shape of the ligand is a trigonal planner, and the complex shapes are tetrahedral, except for vanadium, which isa square-based pyramid. Additionally, the findings demonstrated that the complexes include water inside the coordination field and that each and every one of them is a non-electrolyte. The dye used the complexes prepared from it to determine their ability to inhibit free radicals by measuring their ability as antioxidants using DPPH as a free radical.D-ascorbic acid was employed as a standard substance in determining the value of IC50, as it was found that the ligand had a high ability to inhibit free radicals. The ability to inhibit the complexes varied according to the value of IC50, and the results are as follows: H2L ˃ D-ascorbic acid ˃Zn-complex ˃Fe-complex ˃ V-complex ˃Cd-complex ˃ Mn-complex .

The purpose of this study was to assess the diagnostic value of the immunohistochemical expression of Special AT-rich sequence binding protein (SATB2) alone and in combination with the caudal type homeobox 2 (CDX2) in colorectal cancers (CRCs) in Iraqi patients. This study's samples collection for tissue and practical work spanned twelve months, 20 December 2021 to 20 December 2022. A total of 80 male and female participants (41 CRC, 19 severe colitis and 20 controls) were examined. For each case, at least two 4-μm-thick tissue sections were cut for immunohistochemical staining with CDX2 and SATB2 immunohistochemical markers. According to the current study results all samples of CRC patients showed positive expression for STAB2 and CDX proteins with significantly higher (p< 0.001) frequencies of expression recorded in score 3, 78.05% and 99.9% respectively, in comparison to other study groups. A positive correlation between the two studied markers was found and both could be used as diagnostic markers for CRC.

This study included investigating red lead oxide effects on the bodies of laboratory animals (Albino mice) and how to remove or reduce the effect of this pollutant that was dosed orally using the ethanolic extract of the Moringa oleifera (MO) plant. In the study, 40 adult male mice were used. At an average age of 8-10 weeks and with 21-29 grams average weight, the animals were randomly distributed among four groups with 10 mice/group. The first group M1 was the control group, the second group M2 was treated with red lead oxide only [1.25 mg/kg], while the third group M3 was treated with red lead oxide + Moringa oleifera [C1 = 8.4 mg/kg], and the last group M4 was treated with red lead oxide + Moringa oleifera [C2 = 9 mg/kg]. The results showed a significant difference increase in the growth rates of laboratory mice (p≤0.05) for all studied groups, while the results of animals exposed to red lead oxide and treated with MO extract and those exposed to red lead oxide only showed a significant difference increase (p≤0.01) compared to the control group. In addition, the results of the FBS analysis showed that there was a highly significant increased (p≤0.01) among the four groups that were mentioned earlier and when compared to the control group. The histological examination sections showed different changes in the tissues of the liver, pancreas and kidneys of the mice. The results of this study indicated that an extract of MO, is important to reduce the adverse effects of exposure to red lead oxide toxicity. The administration of MO returned some parameters to control, especially histological sections. It showed that red lead oxide had a harmful effect on tissue sections, while MO plant extract reduced the toxicity of red lead oxide for the M3 and M4 groups.

Fusarium wilt is one of the most important diseases that affects various plants and is caused by the fungus Fusarium oxysporum. Fusarium wilts in tomato plants are caused by Fusarium oxysporum f. sp. lycopersici (FOL), whether in fields or greenhouses. The tomato plant is considered one of the most important plants. This disease, however, affects its agricultural production. The current research aimed to diagnose Fusarium species that were isolated from infected tomato plants from different regions in Iraq by using molecular and morphological methods and to study the evolutionary relationship between the studied species, as twenty Fusarium isolates were obtained from infected tomato plants. Genomic DNA was amplified, using primers ITS1 and ITS4 to amplify ITS region, as there were differences between the results of the morphological diagnosis, which were based on the study of morphological features, and the molecular diagnosis which was based on the ITS region. Depending on the morphological features, F7 and F8 isolates were diagnosed as F. oxysporum, while the molecular diagnosis of the ITS regions showed that they were F.incarnatum and F.proliferatum respectively. For the rest of the isolates, the morphological and molecular diagnoses were consistent with Fusarium oxysporum. All isolates were recorded in the Gen Bank, and were given their accession numbers. An evolutionary tree was also made for the studied isolates to know the degree of genetic convergence and divergence between them. The current study concluded that the tomato plants in the field and greenhouse from different regions in Iraq were infected with different Fusarium species, with Fusarium oxysporum f. sp. lycopersici, being the most common species, was widely spreading among the identified isolates. Conventional methods based on morphological features take time and may result in incorrect identification of closely related species. Henceforth, Fusarium species may be correctly identified by using molecular methods based on ITS sequences.

Infectious toxoplasmosis, caused by an obligate intracellular protozoan Toxoplasma gondii, is a prevalent zoonotic disease that affects humans and warm-blooded animals. Cytokines are a class of signaling molecules that are widely employed in cellular communication; cells produce them, and they have an impact on how other cells interact. The aim of this study was to clarify the relationship between serum levels and gene expression of interleukin18 in miscarried women with toxoplasmosis. A Total of 200 blood samples from patients and controls were collected from Baghdad, Iraq between November 2021 and March 2022 which were used to measure gene expression of IL-18 using real-time PCR. Enzyme-linked immunosorbent assay was used to detect the level of IL-18. The findings of this investigation showed that the IL-18 serum concentration elevated significantly in healthy pregnant women compared to women with recurrent miscarriage and toxoplasmosis, recurrent miscarriage without toxoplasmosis and healthy women. Also, women who had recurrent miscarriage with toxoplasmosis showed significant differences compared with women who had recurrent miscarriage as well as healthy women (p< 0.005). Additionally, significant differences between patient and control were revealed by gene expression data. Also, there was statistically positive correlation between toxoplasmosis and IL-18 gene expression in the patient group. The IL-18 gene expression provided sensitive and precise toxoplasmosis diagnosis. Summing everything it can be concluded that serum level and gene expression of IL-18 elevated in recurrent miscarriage women infected with toxoplasmosis in comparison with other studied groups. Thus, the expression of IL-18 gene could serve as an indicator for women with miscarriage and toxoplasmosis.

This study investigated the role of probiotics in treating echinococcosis, considering three time periods (3, 5, and 7 months) and three bacterial dilutions. Mice were injected subperitoneally before and after primary infection with the rudiments. Before infection, the mice were injected with the Pro-30Max probiotics twice, with 48 hours interval. On the fifth day, they were infected with protoscoleces, and after 48 hours they were treated with the bacteria. The injections continued every 72 hours for all periods. A decrease in the number and weight of hydatid cysts was recorded reaching the value of 0.00 mg. Whereas a decrease in the weight of the liver and spleen and their inflation factors were recorded after 7, 5 and 3 months. The lowest weight of the liver and spleen reached 1.2869 and 0.196 grams, and their lowest inflation factors were 36.106 and 7.118, respectively, when treated with a dilution of 18 × 108 compared with the control group. At the same dilution, the percentage reduction of hydatid cysts increased after 7 months, reaching 100% compared with the control group.

Flavonoids, a wide range of phenolic compounds produced as secondary metabolites in plants, bacteria and fungi, have highly potent activities. In this study, the fungus Gymnoascus dankaliensis was isolated in spring from sheep dung samples, and itsability to produce a secondary metabolite was investigated. The fungal secondary metabolite was extracted, and the antimicrobial and antioxidant activitis were tested. The results showed that Gymnoascusdankaliensis, thefirst ever isolated fungus from dung in Basrah, could produce a secondary metabolite that were produced using a Solid State Ferementation SSF medium after 40 days of incubation. The bioactive compounds were extracted from the solid media by using ethyl acetate. The chemical identification of the extracted bioactive compound indicated that the isolated compound belonged to the flavonoid group. The isolated flavonoid compound tested as an antimicrobial agent against three clinical isolates of bacteria,Escherichia coli , Staphylococcus aureus and and Bacillus subtilis, was also tested against two yeast isolates Candida albicans and C. tropicalis. The results recorded the largest inhibition zone in S.aureus. Whereas C.albicans was found to be more sensitive toward the isolated flavonoid compound than C. tropicalis. The antioxidant activity of the isolated compound was investigated using DPPH (1,1-diphenyl-2-picrylhydrazyl) method where it showed moderate antioxidant activity compared to ascorbic acid.

Despite the widespread use of zinc oxide nanoparticles (ZnO NPs) in various fields, there have been a growing number of reports regarding their toxicity. However, there is insufficient research available regarding the insecticidal effects of ZnO nanoparticles. Using leaves of the river oak tree (Casuarina cunninghamiana Miq., 1848), this study aimed to produce ZnO NPs utilizing a simple and eco-friendly biological process to evaluate the toxic effects of zinc oxide nanoparticles on the mealworm (Tenebrio molitor Fabricius, 1792), the superworm (Zophobas atratus Fabricius, 1775) and the red flour beetle (Tribolium castaneum Herbst, 1797). The produced zinc oxide nanoparticles were characterized using X-ray diffraction (XRD), transmission electron microscopy (TEM) and UV-visible spectroscopy .The laboratory study was conducted by feeding larvae with leaves immersed in a solution of different concentrations of zinc oxide nanoparticles. The lethal effects of the nanoparticles on the three studied insects were recorded at different time intervals. The outcomes of the statistical analysis displayed important differences in the mean mortality rate according to the composition of the zinc particles and the insects. The highest overall average larval mortality rate was 31.6%
among the studied insects with 51.40% being the overall average adult emergence success rate of the studied insect larvae. The LC50 values of the extracted zinc oxide nanoparticles from the used plant, on the other hand, showed varying effects on the mealworm larvae, with a value of 396.27 parts per million (ppm). While the values for the super worm larvae were 6760.83 ppm and that for the red flour beetle larvae the values were 977.23 ppm. These results suggested that the synthesized zinc oxide nanoparticles from river oak tree leaves possess lethal properties against larvae and adults, making them an alternative to synthetic insecticides in insect control stages and environment friendly. Therefore, biologically derived zinc oxide nanoparticles can be used as a potential agent for insect control.

Ankylosing spondylitis (AS) is a form of arthritis that predominantly affects the spine and is characterized by immune and skeletal disorders causing deterioration in structural integrity, functional capability, and overall quality of life. This study aimed to estimate IL-40 serum level in Iraqi men who had AS. Blood samples were obtained from 100 patients (with AS) and 100 men (controls group). The enzyme-linked immune sorbent assay was used to measure the IL-40 level in blood samples. The investigation's findings showed that the typical patient’s age was 40.56 ± 10.19 years old. While the control group's average age was 38.76 ± 10.52 years. The results found that the duration of the disease was< 5 years in 44% of cases, 5-10 years in 50% and >10 years in 6% of cases. Patients without HLA-B27 had higher IL-40 levels, on average than those with HLA-B27 (p = 0.0001). Analysis of the receiver operating characteristic (ROC) curve suggested that a serum IL-40 level of 14.18 pg/mL (AUC = 0.93; p= 0.0001) was optimal which was considered the point at which a person was either affected or not. The differences in the interleukin level in serum between patients and controls were included. The results for levels of IL-40 appeared higher significant differences in patients as contrasted to healthy controls (19.10 ± 5.07 vs 9.13 ± 4.03 pg/ml; p<0.001). Also, the results showed that IL-40 was not substantially correlated with BASFI, BASDAI, Erythrocyte sedimentation, white blood cell count, disease duration, hemoglobin, urea, C-reactive protein or creatinine. While age had a significant positive association with IL-40 serum levels. In conclusion, IL-40 levels in the serum of AS patients were significantly higher than those of healthy controls which indicated that it could play an important pathogenetic role in AS.

This work aimed to select a safe and bacteriocin-producing isolate of Lactobacillus to use it as a probiotic for treating Pseudomonas aeruginosa associated with burn infections. For this purpose, 151 burn wound swabs were collected from patients to isolate the most common multi-drug resistance Pseudomonas aeruginosa that could be used as an indicator. In addition, thirty-six Lactobacillus isolates were collected from different sources and subjected to a screening program to evaluate their antagonism activities against MDR P. aeruginosa. Based on results, the isolate Lactobacillus HLB12 showed a highest bacteriocin production which was further characterized as Limosilactobacillus fermentum through 16s ribosomal RNA. Several tests were performed to study the properties of Limosilactobacillus fermentum HLB12, particularly its biosafety and suitability to be a successful probiotic. Results showed that L. fermentum HLB12 was resistant to β-lactams group such as ticarcillin/clavulanate. Whereas it was sensitive to amikacin, ciprofloxacin and levofloxacin. Moreover, the results confirmed that L. fermentum HLB12 was safe as a probiotic without any health impacts as it has no hemolytic activity. Furthermore, results revealed that this bacterium was strongly adherent and good biofilm producer, had high auto-aggregation capability and high ability of adhering with Pseudomonas aeruginosa. Limosilactobacillus fermentum cells were successfully incorporated into a gel base formula. The results revealed that cells kept their viability over 21 days with an ability to produce and release the bacteriocin. The formula was tested in vitro and results showed a high antagonistic activity against Pseudomonas aeruginosa. Next, the formula was tested in vivo to treat rabbit models with full-thickness skin burn. Upon examining the healing process, results showed signs of remodeling stage by day four and scar tissue formation by day nine. The results supported the idea of using probiotic as an alternative method for the treatment with antibiotics.

In this study, the indium tin oxide (ITO) electrode was modified, physical and electrochemical characterization were studied to be used in some biosensor applications. Using the drop-casting method, functionalized Multiwall Carbon Nanotubes, Polypyrrole, and gold nanoparticles (f-MWCNTs-AuNP-PPy) were efficiently coated on the surface of an ITO electrode. Fourier transform of infrared radiation (FTIR) and field emission scanning electron microscopy (FE-SEM) were utilized to describe the microscopic structure and morphogenesis of the generated films at the ITO electrode's surface. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were used to assess the electroanalytical performance of electrodes after modification. The f-MWCNTs-AuNPs-PPy distribution on the ITO electrode was improved by studying the effect of adding gold nanoparticles and varying polymer concentrations on the film distribution. Electrodes were tested with bare ITO electrodes as well as electrodes modified with f-MWCNTs, f-MWCNTs-PPy, and f-MWCNTs-AuNPs-PPy. The results revealed that nanoparticles distributed on the surface of the modified electrode reduced its impedance by roughly 40% for f-MWCNTs, 75% for f-MWCNTs-PPy, and 95% for f-MWCNTs-PPy-AuNPs. The equivalent circuit was appropriately matched in three situations (f-MWCNTs, f-MWCNTs-PPy, and f-MWCNTs-PPy-AuNPs). The transmission line model, which shows the impedance sensitivity of a diffusion process was utilized to describe the film properties. Nanoparticles enhance electrochemical performance by increasing electrochemical active surface area and allowing electron transport from the redox probe (Ferrocene/ Ferrocenium) to the ITO electrode.

Iron oxide (Fe3O4) nanoparticles were synthesized via an eco-friendly green approach by adding Phoenix dactylifera extract to the aqueous solution of ferric chloride. The effect of annealing temperature (Ta) (100-150) °C on particle size was studied. X-ray diffraction (XRD), UV-visible spectroscopy, atomic force microscopy (AFM), and field emission scanning electron microscopy (FESEM) were used to evaluate the produced nanoparticles. According to XRD spectra, the crystallite size of the samples was determined using the Scherrer formula. AFM and FE-SEM were used to determine surface morphology. A UV-Vis optical spectroscopic examination was carried out to determine the band gap energy of the iron oxide nanoparticles. It was found that with the increased temperature from 100 to 150 oC, the band gap energy of the produced Fe3O4 NPs decreased. The size of the produced particles increased with increasing temperature, as evidenced by AFM and XRD spectra.

Short-range effect on C2, C3, C4 and C5 form factors in the 90Zr atomic nucleus
was scrutinized. The charge density of the 90Zr was as well as scrutinized via the 1-
and 2-body parts of cluster expansion in collaboration with harmonic functions of
single particle. To incorporate the short-range effect in the 2-body part of cluster
expansion, the Jastrow formula was used. Here, the core-polarization and model
space participations are what lead to the form factors in 90Zr. The transition density
of core polarization was calculated using the Tassie form, relying on the charge
density. The elements of one body density matrix were determined by performing
shell model computations using the computer code OXBASH together with the
N50J interaction. The oscillator parameter b and correlation parameter  were
applied to the existing calculations, where b and  are autonomously produced
for each distinct nucleus by matching between the predicted and actual elastic form
factors. A single value for each of b and  must be given for computing the
density, elastic and inelastic form factors for diverse states in 90Zr. This work
provides confirmation that the short-range effect substantially dominates existing
computations, where taking this effect into account appears to be crucial to creating
an important modification to the predicated findings which eventually leads to a
noteworthy interpretation of the data across all assumed momentum transfers.

Heavy metals and metalloids can accumulate in the soil, cause severe risks to human health and the ecosystem, and threaten the sustainable use and management of soil resources. This study investigated the Distribution and levels of heavy metals in soils of different lands in Abu-Ghraib (AGP), Baghdad, Iraq. Twenty-seven samples from cultivated soil and two uncultivated soil samples were collected during February 2023 from the surface layer (0–30 cm depth) and analyzed for major oxides and heavy metals. Different parameters were utilized to investigate the naturality of studied soils, including grain size analysis, pH, total dissolved solids (TDS), electrical conductivity (EC), and trace elements (TEs) concentration. Analysis of grain size indicated that all soil samples were silty clay. The mean pH of the collected soils was 7.9, indicating its alkaline nature. Also, the mean of EC and the TDS of the studied soils was 801.55 μS/cm and 0.80155dS/m, respectively, referring to their non-salinity. Mineralogical analysis by XRD indicated the presence of non-clay minerals, such as calcite, quartz, feldspar, and dolomite, and clay minerals, such as illite, kaolinite, and palygorskite. Levels of Al2O3, CaO, Fe2O3, K2O, MgO, P2O5, and SiO2 were interchangeably found high in both types of soils, with CaO (19.84ppm), MgO (7.18ppm), and TiO2 (0.78ppm) being slightly higher in the uncultivated soils. TE concentrations followed a descending order of Mn> Cr>
Ni> V> Zn> Cu> Pb> Co> Mo> As> Th> Cd> U> Se in the cultivated soils and Mn> Cr> Ni> V> Zn> Co> Cu> Pb> Mo> Th> As> Cd> U> Se in the uncultivated soils. The results also showed that the concentrations of Cr (262.36> 200ppm), Mo (10.87> 10ppm), Ni (190.24> 150ppm), and V (157.68> 150ppm) acceded the maximum allowable concentrations. Such elevated concentrations of TEs in Abu-Ghraib soils are concerning and may lead to abnormal plant growth, reduced biodiversity, and increased risk of human health problems.

Many important archaeological sites in Iraq still need to be preserved. Some of these sites were subjected to destruction and negligence. So, exploring these sites represents a priority for its protection. A 2D Electrical Resistivity Imaging (ERI) as a non-invasive geophysical survey method was implemented at a part of the Borsippa archaeological site near Babylon to search for the subsurface archaeological artefacts/structures. Electrical resistivity measurements were carried out using a Dipole-Dipole array. Steps were taken to process and filter using Horizontal profiles, forward modelling, and 2D inverse models to analyze the resistivity measurements. The ERI inversion results show that the superficial conductive zone produced variations in ERI inverse models. The low resistivity caused by the relatively high conductivity was observed due to rainwater leaking into the topsoil zone. The ERI sections revealed a coherent depth of approximately 7 meters and the anomalies geometry and semi-layering soil. These changes can be attributed to the high resistivity contrast between the relatively high-resistivity anomalies and the surrounding intact soil. The soil types include dry silty and clayey soils and crushed refractory materials such as broken bricks and ruins mixed with rock pulp. These materials have resulted in the collapse of walls due to weathering and erosion. Based on the identified patterns, shallow-depth high-resistive anomalies are present and extend throughout some parts of the study area. These anomalies are represented in a SW-NE trend of the mound area. At the bottom of this zone is another zone with low resistance values and variable thickness, which varies from place to place within the study area. The results proved the efficiency of the ERI technique in detecting archaeological wall-like artefacts, which represents a data bank for any future archaeological prospection.

The upward continuation was used to obtain the residual RTP magnetic maps at elevations 2, 12, 16 and 22 km. These maps are processed by the Total Horizontal Derivative (THD) technique to detect the main lineaments that represent the boundary of subsurface sources or fractures. The high background of THD in the central part of the study area supports the presence of a group of faults between the western and eastern parts of the area. The obtained lineaments trends were represented on the rose diagram, as were the main trends in the study area. The predominant lineaments (faults) trends in the western part in descending are N55W, N35W, N05W, N65W, N45W, N25W, N05E, N15E, and N35E, respectively, for the four considered upward elevations. The lineament in eastern part found trending N55W, N35W, N35E, N45W, N45E, N05E, N25E, and N05W, respectively. The lineaments of the western and eastern parts indicate that the main trend in shallow sources is NW-SE, which coincides with the Najd fault system (540-620 Ma) in the Arabian Plate. The deep-level lineaments are trending N-S, which coincides with the Nabitah fault system (680-640 Ma).

In this work, the Banach contraction principle is generalized to a new formula. Then, it is used to give the guarantee conditions for the existence of common fixed point for set valued mappings defined on complete partial b-metric spaces. In addition, some results in connection with the existence of a fixed point for a set-valued mapping defined on a partial b-metric space are given. Some examples are established to illustrate our results.

The significance of media alerts in influencing public perception and response during disease outbreaks is of paramount importance. This research investigates how media alerts affect the epidemiological model by taking into account both asymptomatic and symptomatic cases. Media alerts serve as a powerful tool for raising awareness about the disease, driving people to undergo testing and diagnosis, and promoting adherence to public health measures. This, in turn, contributes to better reporting and surveillance of cases, leading to a more accurate representation of disease spread in the model. The proposed model introduces a five-dimensional compartment system that includes susceptible, asymptomatic, symptomatic, recovered populations and media. This research addresses various aspects of the model, such as its uniqueness, boundedness, and existence of solutions. The determination of all possible model equilibrium points is thoroughly explored. To study the global dynamics of the proposed models, appropriate Lyapunov functions are employed. Additionally, numerical simulation is also carried out to investigate the influence of parameters affecting the dynamics of the model and to support the gathered analytical findings of the model.

In this paper, an ecological model with stage-structure in prey population, fear, anti-predator and harvesting are suggested. Lotka-Volterra and Holling type II functional responses have been assumed to describe the feeding processes . The local and global stability of steady points of this model are established. Finally, the global dynamics are studied numerically to investigate the influence of the parameters on the solutions of the system, especially the effect of fear and anti-predation.

In this paper, a new proper generalization of small monoform modules, namely ????-Small monoform modules is introduced and studied. An ????-module ???? is called ????-small monoform module (ZSM module; for short), if every non-zero partial endomorphism of ???? has ????-small kernel.

The module ???? is cofinitely rationally closed weak supplemented module (denoted by CRCWS-module) if every cofinite rationally closed submodule of ???? has weak supplement submodule in ????. The CRCWS- module is stronger generalize of closed cofinitely weak supplemented modules. In addition, we present a rationally closed weak supplemented modules (denoted by RCWS-module) which is a stronger generalize of closed weak supplemented modules. The relationships of our concepts to other related concepts was discussed and studied, and we give the conditions that make them equivalent were given. And also, we gave the necessary condition that makes the direct sum of RCWS-module (or CRCWS-module) is RCWS-module (CRCWS-module).

The presented study investigates the scheduling regarding ???? jobs on a single machine. Each ???? job is processed with no interruptions and becomes available for processing at time 0. The aim is to find a processing order with regard to jobs, minimizing “multi-criteria and multi-objective” for two problems. The first problem considers the summation completion time Σ????????, summation late work Σ????????, and maximal tardiness ????????????????, while the second problem considers the total completion time Σ????????, total earliness Σ????????, and maximum tardiness ????????????????. In addition, a sub-problem is presented for each problem and denoted by 1// Σ????????+Σ????????+???????????????? and 1// Σ????????+Σ????????+???????????????? for the first and second problems, respectively, which is an NP-hard problem. Two meta-heuristics methods “particle swarm optimization (PSO) and bee algorithm (BA)” were applied to acquire the optimal or near-optimal solution. Meta-heuristics methods solve problems of up to ????=4000 jobs. Finally, in an attempt to increase the overall search efficiency, a hybrid algorithm was created by combining two algorithms, a hybrid between BA and PSO was created to create an alternative search method that incorporates the best properties that each method offers during problem-solving. Moreover, by comparing the performance of local search methods with a hybrid strategy, the hybrid strategy method outperforms BA and PSO. In addition, it can solve problems up to ????=8000 jobs. Arithmetic results are calculated by coding (programming) algorithms using (MATLAB 2019a).

Many operators are introduced for the approximation of real functions, but little for the approximation of complex functions. These studies are for analytic functions.
In this article, we define a new type of Szasz-Mirakjan operator. Then we estimate the degree of approximation using this modified complex Szasz-Mirakjan operators to integrable functions on compact disks along with a quantitative estimation. Using quantitative methods, we also obtain an upper estimate in the simultaneous approximation by ????????(????,????)(ƒ) and exact degrees of approximation estimation for these operators' Stancu-type generalization.

This study introduces a novel topological space named the nano Ɽ-space, which is based on the principles of nano topological spaces. Thus, the reconstruction of this space and their properties are demonstrated and explored, accompanied by illustrative examples to aid in understanding its nature. Furthermore, the investigation of the practical implications of the nano Ɽ-space through a series of case studies involving pediatric patients diagnosed with leukemia. Then, by examining the symptoms exhibited by these patients and their impact on the equivalence relations within the nano Ɽ-space, the elucidate the applied aspect of this novel topological framework. the findings indicate that the presence of unexplained bruises on the body emerges as a fundamental and indispensable symptom, allowing us to definitively diagnose the presence of leukemia in a patient.

Let ꭆ be a 2-torsion-free prime ring, ???? be non-zero square closed Lie ideal of ꭆ, ???? and ???? be automorphisms of ꭆ.A mapping .

The digital image is considered one of the most heavily attacked and targeted data types because of its various applications and sensitive visual data. Many security techniques have been introduced to cover various image security needs, such as watermarking and steganography for intellectual property protection, authentication, and cryptography techniques for confidentiality and secrecy. In this paper, we present a technique that introduces enhancements to encryption quality and employs chaos theory to augment system robustness. The approach involves the generation of pseudo-random sequences through the utilization of the four-dimensional Lorenz system. These sequences serve a dual purpose: firstly, they facilitate image preprocessing by applying a scrambling and diffusion technique to eliminate intrinsic relationships between adjacent pixels. Secondly, a DNA-based codebook method is incorporated to further elevate encryption quality during the final step. This entails the utilization of the LUC public encryption algorithm, along with one of the generated pseudo-random sequences, as the encryption keys for safeguarding the image. The findings regarding encryption quality and the perceptibility of the resulting image yield promising outcomes. In terms of encryption quality, notably high values were attained. In regard to entropy, the achieved entropy for the encrypted images exceeded 7.9. Additionally, the range of PSNR between the plain and encrypted images remained below 8.7.

Traditional surveillance systems rely on human attention, limiting their effectiveness. This study employs convolutional neural networks and transfer learning to develop a real-time computer vision system for automatic handgun detection. A comprehensive analysis of online handgun detection methods is conducted, emphasizing reducing false positives and learning time. Transfer learning is demonstrated as an effective approach. Despite technical challenges, the proposed system achieves a precision rate of 84.74%, demonstrating promising performance comparable to related works, enabling faster learning and accurate automatic handgun detection for enhanced security. This research advances security measures by reducing human monitoring dependence, showcasing the potential of transfer learning-based approaches for efficient and reliable handgun detection.

The compression system typically comprises two fundamental categories: compression and decompression. Within the realm of compression, there exist two primary types: lossy compression and lossless compression. In this research, a novel lossless digital image encoding technique is presented. This method depends on performing a series of iterative mathematical transformations. The methodology of performing this method is similar to the process of performing the fractal compression algorithm, with an essential difference: the fractal pressure is classified as lossy compression, but this new method is lossless compression. It is well known that lossless compression methods produce higher-quality images than lossy methods, but they do not achieve as high a compression ratio as lossy methods. This research has overcome this problem. A high compression ratio has been obtained with images retrieved entirely according to the original (lossy). Lossless compression holds immense significance across a spectrum of applications, especially in critical domains such as healthcare, where the imperative is to retrieve images that are indistinguishable from the originals

The lifespan of WSNs is crucial, and it primarily relies on the energy efficiency of the sensors, as their power source is often non-rechargeable and non-replaceable batteries. Addressing this issue involves carefully designing of a routing protocol that considers energy saving. This article presents a heterogeneity-aware routing protocol based on the Stable Election Protocol SEP for heterogeneous WSNs to extend the lifespan of the WSN by reducing energy consumption. The proposal employs the Time Difference of Arrival (TDoA) in the cluster-forming process to determine the shortest distance between the cluster head (CH) and sensor nodes in that cluster, thereby minimizing power consumption in all later communication operations. The proposal has been evaluated and compared to three protocols which are SEP, Zonal-SEP (Z-SEP), and Improved Z-SEP (IZ-SEP). The results depicts that the proposed protocol outperforms the three protocols in terms of the largest number of alive nodes in all evaluation rounds and exhibited a greater average of residential energy in nodes by about 90%, 10%, and 5% more than SEP, Z-SEP, and IZ-SEP respectively.

Predicting stock prices is a challenging task due to the numerous factors that impact them. The dataset used for analyzing stock prices often displays complex patterns and high volatility, making the generation of accurate predictions difficult. To address these challenges, this study proposes a hybrid prediction model that combines the salp-swarm algorithm and the artificial neural network (SSA-ANN). The SSA is used to optimize the weights and biases in the ANN, resulting in more reliable and accurate predictions. Before training, the dataset is normalized using the min-max normalization technique to reduce the influence of noise. The effectiveness of the SSA-ANN model is evaluated using the Yahoo stock price dataset. The results show that the SSA-ANN model outperforms other models when applied to normalized data. Additionally, the SSA-ANN model is compared with other two hybrid models: the ANN optimized by the Whale Optimization Algorithm (WOA-ANN) and Moth-Flame Optimizer (MOA-ANN), as well as a single model, namely the Autoregressive Integrated Moving Average (ARIMA). The study’s findings indicate that the SSA-ANN model performs better in predicting the dataset based on the evaluation criteria used.

In the realm of online information retrieval, Arabic web content presents unique challenges due to the complexity of the Arabic language and the varying quality of available materials. These complexities often confound search engines, hindering precise web page classification. This research addresses these challenges with a streamlined approach to effective online Arabic web page classification. Our strategy involves two key components: First, we employ a comprehensive text mining approach to extract valuable insights from a corpus of documents. This begins with text extraction from the online web page after providing the URL and the removal of stop words to enhance data quality. Additionally, we leverage Natural Language Processing (NLP), specifically lemmatization, to normalize text and reduce linguistic variations, ensuring consistent and meaningful representation. To complete the text mining process, we use the Bag of Words (BoW) model to transform preprocessed text data into a numerical format, capturing word frequencies. Second, we harness the power of the Artificial Bee Colony (ABC) optimization algorithm, inspired by bees' foraging behavior, as a pivotal element in our decision-making process. This algorithm provides a robust framework for optimizing classification tasks. Empirical results affirm the effectiveness of our approach, achieving an impressive 95.349% accuracy rate. This advancement bridges the gap between the intricacies of the Arabic language and efficient web content organization, promising a more informative Arabic web landscape

A Weather Wireless Sensor Network (WWSN) has many limitations related to node throughput (NT), node power (P), and node energy (E). To address the limitations of WWSN, a mixed-byte LZW scheme is proposed. Mixed-Byte reduces the size of the sensed data by merging every two readings of data from the sensor into a single byte. The merged bytes would be highly frequent, which made them appropriate for compression by the Lempel Ziv Welsh (LZW) scheme. The result shows that the proposed Mixed-Byte-LZW gives the best compression ratio (CR) (0.01) for humidity and the best saving compressing rate (SR) (99%) for humidity and pressure. The simulated result shows that the Mixed-Byte-LZW scheme gives the best NT (580 Kbps) for humidity, the highest power saving (PS) (15.98 Kw) for pressure, and the lowest E (0.39 Kj) for transferring humidity data.

The privacy, confidentiality, and integrity of user information are very important
concerns; therefore, cryptography is the solution to keep and satisfy these objectives.
Encryption is the most important policy that is used to make transmitted messages
have a high level of security and be so difficult to crack by attackers. The main aim
of this research is divided into two parts: The aim of Part 1 is to obtain the highest
level of complexity against the attacker by applying six classical cryptography
algorithms to the same plain-text message. These six algorithms are Vigenère, Porta,
Autokey, Beaufort, Trithemuis, and Gronsfeld. Also, in this part, several analysis
tools are used to evaluate the performance of the six algorithms: entropy, histogram,
and autocorrelation. Part 2 of this research aims to apply the results of Part 1 by
using the best algorithm among these six algorithms (Vigenère) to improve the
security level of the Data Encryption Standard (DES) algorithm by applying two
experiments for two hybrid ciphering models. Each experiment has three cases. The
first experiment included three cases: the first case included ciphering plain text by
using only the Vigenère algorithm, the second case included ciphering plain text by
using only the ECB DES algorithm, and the third case included multilevel ciphering
plain text by using Vigenère and then ECB DES algorithms, while the second
experiment for the second hybrid ciphering model included the same cases as the
first experiment but applied CBC DES, another type of DES algorithm. The results
of this research indicated different efficiency levels of six classical algorithms, and
the Vigenère algorithm is the best and offers the highest level of complexity among
the used algorithms. In addition, the Vigenère algorithm can be used to enhance the
security level of cryptography algorithms and increase the complexity of cracking
ciphertext when combined with another algorithm like the DES algorithm.

The main objective of recommender systems is to assist users in overcoming the issue of information overload by providing them with a carefully selected list of items that they are likely to find useful or relevant. Recommender systems may face many limitations and challenges, such as the cold start problem, which occurs when there is insufficient or no information about a new user or item. This leads to a decline in the performance of the recommender system. In this paper, we propose a recommendation system based on textual reviews and the deep learning method (RS-TRDL) to alleviate the user cold-start problem. Our RS-TRDL model can extract the important aspects and underlying sentiment polarity classification from the review text using NLP techniques and a deep learning method. These are then fused into collaborative filtering techniques to improve the RS and alleviate the user cold-start problem. The proposed method consists of two components: (i) An aspect-based sentiment analysis module that aims to extract aspects from the review text with its polarity; (ii) A recommendation generation component that uses the aspects as additional information with the numeric ratings. It also employs an important feature in the dataset, namely, the helpfulness to finally infer the overall rating prediction. Extensive experiments were conducted by the proposed system on two Amazon datasets. The experimental results show that the proposed RS-TRDL model exceeded all literature-reviewed comparison methods in the cold-start problem alleviation task.

Stability in the atmosphere is the most important factor in the transport and
dispersion of air pollutants. There are a number of complicated methods for
determining stability. The majority of these methods are based on the amount of
convective and mechanical turbulence in atmospheric motions, such as the
Richardson number, Monin-Obukhov length, Pasquill-Gifford stability
classification, and Pasquill-Turner stability classification. Pasquill utilized surfaceaccessible
meteorological information like breeze speed, sun-based radiation, and
surface darkness to portray air steadiness. Baghdad territory was separated into a
gathering of focuses as indicated by scope and longitude; six focuses were chosen
and conveyed in a manner that addresses all districts of Baghdad territory through
the diurnal hourly information (6, 9, 12, 15, 18) for the months (January, April, July,
October) for the year 2018, and find the spatial and fleeting circulation of relative
recurrence RF% dependability classes as per consolidating the Pasquill-Turner
strategy. The pattern of conditions necessary for atmospheric stability can be derived
from two distinct categories. First, the patterns for the month and the season are
calculated. The results show that in April, the relative frequency (RF%) of the (A)
and (B) classes is highest in the northeast of Baghdad province and has an inverse
relationship with average wind speed (R = - 0.62, - 0.90). During July, the relative
frequency RF percentages of the (C) and (D) classes are highest in the west and
northeast of Baghdad province, respectively, and they are positively correlated with
average wind speed (R = 0.91, 0.78, respectively). The spatial and worldly
conveyance of relative recurrence RF% steadiness classes as per joining the
Pasquill-Turner strategy prompts a feeble relationship or an absence of clarity in the
relationship because of the impact of affecting elements (non-direct variety) (the
Pasquill-Turner Technique (PTM) in extra factors of the Pasquill strategy). Second,
monthly and seasonal patterns are calculated. The Pasquill method reveals that the
stability class (C) has the highest relative frequency (RF%) in January (28.72
percent), the stability class (B) has the highest relative frequency (RF%) in April
(33.98 percent), the stability class (C) has the highest relative frequency (RF%) in
July (64.74 percent), and the stability class (C) has the highest relative frequency
(RF%) in October (35.48 percent).

Due to its commercial and economic significance and its adjacency to Iraq's
largest university, the Al-Jadriya area in Baghdad holds vital importance. This
region exhibits high population density, diverse land uses, and a wide range of land
cover types. Therefore, accurately classifying the land features in this area is crucial
to support decision-making and facilitate infrastructure development. This study
aims to utilize remote sensing techniques and a high-resolution satellite image to
classify the region. To achieve this, GIS and QGIS programs and a software package
encompassing various classification methods were employed to accurately classify
the features and determine the most practical classification methods for this data
type. The results indicated that deep learning algorithms utilizing artificial
intelligence were the most effective classification method; it achieved an 81.66%
classification accuracy for the region, surpassing other techniques.

The change in land cover eventually occurs as the population increases, resulting
in high human activities. Monitoring this change can be beneficial for territorial
planning and ecosystem monitoring. Therefore, this study aimed to evaluate the
spatial-temporal patterns and rates of land cover change in Nampula City,
Mozambique, over the past three decades (1989-2020). For this purpose, data from
the Landsat-5 TM and Landsat-8 OLI / TIRS satellites were applied as input to two
classification systems: (1) thresholding-NDVI and MNDWI and (2) supervised
classification. The results showed that the supervised classification method
performed better than the thresholding system, with an overall accuracy of 92.4%
and a kappa coefficient of 0.89. Estimates pointed to a reduction of 0.04% in the
water area and 20.3% in cultivated land. In contrast, barren rock and urban areas
experienced an increase of 18.2%, while shrubs and grasslands showed a growth of
2.1% of their area. The results showed a considerable change over the study period
and that the spatial dynamics of crop and barren rock and urban areas resulting from
human interventions require special consideration. This study provides an
opportunity for further studies on the spatial dynamics of land cover change in
Nampula City, facilitating effective land management and sustainable development
strategies in the region.

The ecological interaction, human, geomorphological, and climatological factors lead to basin morphometry; morphometric aspects could be used as evidence for understanding the nature of these factors in terms of active dominant factors within the basin area. Quantitative morphometric analysis based on remote sensing imageries and GIS techniques is the best way to determine these aspects. In this research, a new approach was submitted: using Google Maps to track the Horan Valley path and region that passes through, delineating the main basins in the region, and then neglecting all basins that involve the valley only. The obtained results showed that the Horan region is a four-order basin with 213 1st-order streams, 89 2nd-order streams, 35 3rd-order streams, and 84 4th-order streams, and its area is 12947 km2, the average bifurcation ratio is (1.784) indicating the flood risk in the basin during rain generally, while the sub-ratios between two successive orders refer to this risk absence in the main order streams. Dd was 0.201 km-1, revealing the area's desertification and increased soil permeability. Fs was 0.0325 stream/ km2, meaning an alluvial basin formed mainly by sediments during rainstorms. T was 0.0611 km-1, proving the region's soil's high porosity and permeability. Re was 0.289, indicating semi-rectangle basin shape and geological structures equivalence. C was 0.086, revealing that lineaments control the basin drainage pattern model, and Rf was 0.069, meaning a youth geomorphological stage and length of the water drainage period till arriving at the basin end during the rain.

This research proposed a 5.0 MW wind power project at the Al-Shihabi site in Iraq. The wind speed was collected from the Al-Shehabi metrological station at heights 10, 30, 50, and 52 m with 10-minute time intervals; then those data were compared with the hourly wind speed measured at 50 m for one year above the ground level obtained from the NASA site. The data were modeled using the Weibull distribution function for all wind power heights. Three methods were used to estimate Weibull parameters: Maximum Likelihood, Least Squares, and WAsP, which were executed to determine the numerical values of Weibull shape parameter (k), scale parameter (c), and mean wind speed. It is concluded that the annual mean wind speeds and the annual mean wind power densities of the measured data at 10, 30, 50, and 52 m heights were 4.607m/s, 144.0W/m2, 6.068 m/s, 257.0 W/m2, 6.673m/s, 346.0 W/m2, 6.91m/s, 359.0W/m2 respectively, as 3rd class (Gentle Breeze), while the results of wind data from NASA at 50 m were 5.241m/s and 126 W/m2 as 2nd (Light breeze). The predicted power density was analyzed using ten wind energy system models of rated capacity 10, 25, 50, 60, 100, 330, 500, 850, and 900 kW.

Exploring the performance of supervised machine learning algorithms for specific classification tasks is essential to enhance the accuracy and reliability of thematic maps generated from remote sensing data, ultimately supporting informed decision-making in land use management and environmental monitoring. This paper evaluates the classification performance of supervised machine learning algorithms within a specific region of Baghdad, Iraq, primarily focusing on utilizing SENTINEL-2A imagery. The crucial initial step involves data preprocessing, meticulously executed through the application of SNAP software, setting the foundation for a comprehensive analysis of the algorithms' effectiveness. Maximum Likelihood (ML), Minimum Distance (MD), Random Forest (RF), K-Nearest Neighbor (KNN), and KD Tree KNN (KD-KNN) models are applied to produce Landuse maps of five classes. Finally, a confusion matrix is implemented to examine the classification accuracy. The results revealed the superiority of the RF classifier with an overall accuracy of 83.33%. Followed by KNN and KD-KNN with an accuracy of 80% each. Bare lands scored the highest rating in most of the applied algorithms. The reported findings raise awareness regarding selecting suitable algorithms for specific classification tasks.