Iraqi Journal of Science (IJS) is a blind peer-reviewed open access journal issued by the College of Science at the University of Baghdad. It is a monthly journal that publishes original research articles in a wide range of subjects. The prestigious interdisciplinary editorial board in the journal reflects the diversity of subjects covered in the journal. The journal is being published since 1956. The journal is basically self-financed by applying fees on the researcher's work published in the journal. However, the journal is also supported by the college of science at the University of Baghdad.
College of Science - University of Baghdad
Geophysical Study to the Role of Salt in Creating BuzurganOilfield Structure, Southeast of Iraq.
This paper is an attempt to study the relation between the creation of Buzurgan oilfield structures and the role of salt in forming these structures. The study depends on the available surface geophysical data, namely; seismic reflection, gravity and magnetic data. Seismic reflection profiles show clearly how the salt of Al-Fatha Formation (evaporite) plays a clear role in creating the relatively shallow anticlinal structures of Buzurgan oilfield, in addition to the effect of the lateral stresses resulted from the collision between Arabian and Iranian plates. Gravity and magnetic data interpretations indicate that there are similar probable anticlinal structures may occur in deeper formations due to the effect of Gotnia and Hormuz salt, where these salts are piercing upward by buoyant forces resulting from the density contrast between these formations and the heavier rocks above them. Depth of the basement rocks are found to be ranged between 11.7 to 12.4 Km measured from gravity and magnetic data respectively.
Copyright (c) 2026 Iraqi Journal of Science https://creativecommons.org/licenses/by-nc/4.0
Immunological Consequences of rs5742621 Variant and IGF-1 in Modulating MIF, IL-27, and CXCL12 Expression in Individuals with Prostate Cancer
Prostate cancer (PCa) is the second most common cancer among men worldwide. Immunological biomarkers play a crucial role in disease diagnosis, progression, and treatment. This study aimed to investigate the relationship between the rs5742621 (A>G) genetic variant and serum levels of insulin-like growth factor 1 (IGF-1) and other cytokines in patients with PCa compared to healthy controls. A total of 204 patients with PCa (aged 48–80) and 196 healthy controls were enrolled. Blood samples were collected to genotype the rs5742621 variant using the tetra-primer amplification refractory mutation system-polymerase chain reaction (ARMS-PCR). Serum levels of IGF1, macrophage migration inhibitory factor (MIF), CXC motif chemokine ligand 12 (CXCL12), and interleukin-27 (IL-27) were measured using a sandwich immunoassay. The heterozygous GA genotype of rs5742621 was more prevalent among patients with PCa, while the AA genotype was more prevalent in healthy controls. Additionally, serum IGF-1 levels were significantly elevated in PCa patients (median: 110 pg/mL) compared to healthy controls (median: 65 pg/mL; p < 0.001). Similarly, MIF levels were higher in PCa patients (85 pg/mL vs. 45 pg/mL; p < 0.001), as were CXCL12 concentrations (140 pg/mL vs. 40 pg/mL; p < 0.001). In contrast, IL-27 levels were lower in PCa patients (40 pg/mL) than in controls (65 pg/mL; p < 0.001). ROC curve analysis demonstrated that CXCL12 and MIF both achieved perfect diagnostic accuracy (AUC = 1.0), while IGF1 showed excellent diagnostic performance (AUC = 0.979) and IL-27 showed good performance (AUC = 0.903). The GA genotype of rs5742621 was significantly associated with elevated IGF-1 levels and increased PCa risk, promoting cell proliferation, inhibiting apoptosis, and accelerating tumor growth. IGF-1 and related immunological markers may serve as promising diagnostic biomarkers and potential therapeutic targets for prostate cancer.
Novel Nitric Oxide-Releasing Polyvinyl Alcohol Films for Disrupting Pseudomonas aeruginosa Biofilms
Novel nitric oxide (NO)-releasing polyvinyl alcohol (PVA) films were prepared by blending sodium nitroprusside (SNP), which serves as an NO donor, into a PVA solution. The microtiter plate (MTP) was used to measure the biofilm-forming capacity of eight Pseudomonas aeruginosa isolates on PVA film-coated MTP, MTP coated with nitric oxide-releasing PVA films, and catheters coated with NO-releasing PVA films. The qPCR was employed to determine the effect of PVA, nitric oxide, and NO mixed with PVA on the gene expressions of pslA, pelA, algD, nirS, and bdlA genes. All isolates developed strong biofilms on uncoated MTP, with a highly significant decrease on NO- releasing-PVA film-coated MTP and catheters coated with NO-releasing-PVA film compared to PVA film-coated MTP and uncoated MTP. Significant downregulation of pelA and pslA expression was determined upon exposure to the SNP-PVA and SNP alone. However, algD displayed insignificant downregulation after exposure to the SNP-PVA blend and SNP alone versus the PVA solution. Furthermore, nirS and bdlA exhibited insignificant upregulation after exposure to SNP-PVA and SNP alone versus the PVA solution.
A Novel Image Decomposition Employing Gaussian Curvature based Edge preserving Filter for Brain Tumor Detection through Image Fusion
The process of combining images from multiple medical imaging sources without any distortion or loss of information is known as medical image fusion. It improves the usefulness of medical imaging for the diagnosis and treatment of medical issues by maintaining every feature in the fused image. Recent years have seen the introduction of many image fusion techniques that show the significant progress in the field of medical diagnosis. However, the fusion performance of these contemporary methods is prone to distortion, noise, and blurring. To address these drawbacks of the current methods, this work presents a novel fusion methodology for a visually pleasing appearance. Using Gaussian curvature and guided filters, a new decomposition technique with an edge-preserving smoother is firstly described. The primary objective of this approach is to preserve edge haloes while recovering the structural information. The "weighted average" technique is used to merge source images based on the weights that were computed based on significant edge details. This technique can enhance contrast and highlight significant details in the fused image. We evaluate our proposed methodology on multiple pairs of publically available medical imaging datasets. The quantitative evaluation indicates that the suggested fusion strategy for multimodal image fusion improves the average IE by 5.8, MI by 34.8%, MSSIM by 31%, and QAB/F by 40% over the current methods, making it appropriate for usage in the medical area for correct diagnosis.
Gaussian curvature, Guided filter, Medical image fusion,Weighted average, Qualitative, Quantitative evaluation
Copyright (c) 2025 Iraqi Journal of Science https://creativecommons.org/licenses/by-nc/4.0
Pharmacological Evaluation of Najas gracillima from the Bay of Bengal Coastal Regions: In Vitro and In Silico Studies
Najas gracillima is a green seaweed commonly found in North America and East Asia. This study explored its phytochemical composition and assessed its antioxidant activity using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assays, along with α-amylase inhibition and cytotoxicity evaluations via the brine shrimp lethality bioassay (BSLB) and the HeLa cancer cell line. The acetone extract of Najas gracillima (ANG) showed a total phenolic content of 14.26 ± 1.86 mg GAE/g extract and a total flavonoid content of 10.27 ± 2.24 mg QUE/g extract. ANG demonstrated strong antioxidant activity (IC₅₀ for DPPH: 14.57 ± 0.93 µg/mL; IC₅₀ for ABTS: 32.17 ± 1.35 µg/mL) and moderate α-amylase inhibition (IC₅₀: 54.97 ± 3.36 µg/mL). While it showed mild cytotoxicity in the BSLB assay (LC₅₀: 673.08 μg/mL), no cytotoxic effects were observed against HeLa cells. Molecular docking analysis revealed that the identified compounds exhibited strong binding affinities to relevant drug target proteins associated with the observed biological activities. These findings suggest that N. gracillima may serve as a valuable source of bioactive compounds with potential applications in managing oxidative stress and diabetes.
Estimating the levels of Vitamin D, Interleukin-17A, Interleukin-22, and Interleukin-34 in Women with Polycystic Ovary Syndrome.
Polycystic ovarian syndrome (PCOS) is the most prevalent endocrine disorder affecting women during their reproductive period. The study aims to estimate the concentrations of interleukins (IL-17A, IL-34, and IL-22) and vitamin D levels, besides some hormonal indices in blood serum, and to explain their roles in PCOS pathogenicity in women. This study included ninety samples categorized into two groups: sixty samples from patients with PCOS and thirty samples from a healthy control group. Participants' ages ranged from 19 to 39 years. The PCOS diagnosis is made by a specialist doctor. Blood samples were collected from each woman, both patients and healthy controls, during the menstrual cycle (days 3 and 4) to measure hormonal profile levels of estradiol, testosterone, Anti-Müllerian Hormone (AMH) and vitamin D using a mini VIDAS device. The ELISA technique was used to determine the concentrations of serum IL-17A, IL-34, and IL-22. The results indicated a significant elevation (P <0.05) in testosterone and Anti-Müllerian Hormone (AMH) levels in patients with PCOS compared to the healthy control group. In contrast, estradiol had a significant decrease in PCOS patients. The vitamin D levels in patients with PCOS were lower than those in the healthy control group, without statistical significance. IL-17A and IL-34 exhibited no significant differences between women with PCOS and the healthy group. IL-22 concentrations were reduced in the patients compared to the healthy control group. Furthermore, it is noteworthy that a weak negative correlation was observed between IL-17A and testosterone (r = -0.25), as well as between IL-34 and other variables, including estradiol (r = 0.27) and testosterone (r = 0.28). In contrast, a weak positive correlation was identified between IL-22 and testosterone (r = 0.26). It can be concluded that there are no statistically significant changes in the levels of vitamin D, IL-17A, or IL-34 between patients and healthy controls. However, there was a notable decrease in the levels of IL-22 in patients with PCOS. A drop in IL-22, likely caused by hormonal changes and immune dysregulation, such as chronic low-grade inflammation, may help prevent and treat PCOS.
Effect of Moringa Leaves Water Extract Combined with Collagen and Vitamin C on Malondialdehyde Levels in Rats Exposed to Oxidative Stress
The increasing prevalence of free radical-related diseases has led to a greater reliance on herbal medicines, such as Moringa oleifera (ML), as antioxidants. However, limited evidence exists regarding the combined effect of herbal and conventional antioxidants on malondialdehyde (MDA) levels. This research assessed simplisia characterization, phytochemical screening, antioxidant activity of ML water extract (ML-WE), and serum MDA levels in animal models using ELISA. Forty-two Wistar rats were randomly divided into seven groups: a negative control, a positive control, and five treatment groups. All treatment groups were exposed to lead for seven days, followed by supplementation with either ML-WE (200 mg/kg BW), vitamin C (36 mg/kg BW), collagen (27 mg/kg BW), or their combinations. ML-WE showed strong antioxidant activity (IC50: 81.761 ppm). MDA levels differed significantly among groups (p < 0.001). Combining ML-WE with collagen reduced MDA levels more than ML-WE alone (14.65 ± 0.66 vs 21.32 ± 0.95 nmol/mL, p < 0.05) but was less effective than collagen monotherapy. Similarly, ML-WE combined with vitamin C showed no statistically significant improvement. These results indicate that while ML-WE has strong antioxidant properties, no synergistic effects were observed in combination therapies.
Modulation of BarA/UvrY Two-Component System Expression in Escherichia coli Induced by Ceftazidime Treatment
Uropathogenic Escherichia coli (UPEC) remains the most common etiologic agent of community-acquired urinary tract infections (UTIs), largely due to its extensive virulence arsenal and adaptive regulatory mechanisms. In this study, we examined the phenotypic regulation of major virulence factors—hemolysin production, biofilm, swarming motility, and adhesion—under exposure to sub-inhibitory concentrations of Ceftazidime, an extended-spectrum β-lactam antibiotic. The transcriptional response of the BarA/UvrY two-component regulatory system was also examined to unravel its role in response to antibiotic stress. Using an extensive range of microbiological, molecular, and phenotypic tests, we unveiled differential profiles of virulence traits. Exposure to sub-MICs Ceftazidime markedly diminished hemolytic activity, biofilm formation, and adhesive capacity, with swarming motility exhibiting almost complete inhibition. Moreover, quantitative real-time PCR (qRT-PCR) analysis revealed variable transcriptional responses of BarA and UvrY in the tested isolates, with the recovery of BarA expression noted after prolonged exposure to antibiotics. These findings emphasize the dynamic expression of UPEC's stress response mechanisms and outline the central role of Bar/UvrY in modulating pathoadaptive mechanisms under antibiotic stress.
A Morphological and Histological Study of the Skin in the Bufo viridis Frog in Iraq
This research was carried out to identify the layers of the skin of Bufo viridis. Ten adult frogs were used in the study, which was conducted in the histology and embryology laboratory at the College of Education for Pure Science (Ibn Al-Haitham), University of Baghdad. The skin was dissected and fixed in 10% formalin, then dehydrated, cleared, infiltrated, and embedded. The sections were stained with hematoxylin and eosin. The histological structure of the skin revealed that it is composed of two layers. The epidermis layer is composed of stratified squamous epithelial tissue and consists of three strata: the Corneum, Spinosum, and Germinativum. There are no papillae in the epidermis. The dermis layer is composed of loose connective tissue with blood vessels and consists of two layers: the spongy and compact layers. The spongy tissue consists of alveolar glands, both mucous and granular. The dorsal skin and the dermis consisted of pigment cells. The skin tissue consists of a two-layered structure: the epidermis, composed of stratified squamous epithelium, and the dermis, composed of loose connective tissue. Pigment cells are present in both layers, suggesting that they serve a role as coloration or UV radiation protection.
Expression Variation of Serine Protease Autotransporters Genes of Uropathogenic E. coli in Response to Tea Tree Essential Oil (Melaleuca alternifolia) and its Polymer
In this study, the antibacterial activity of tea tree essential oil and its polymer on Uropathogenic E. coli was determined. In addition to their effect on the gene expression of two serine protease autotransporter genes, sat and vat. Five hundred clinical urine samples have been collected from individuals aged between 15 and ≥65 years old with urinary tract infections in Babylon. One hundred E. coli isolates were collected and isolated using selective and differential culture media, then verified by polymerase chain reaction (PCR). The minimum inhibitory concentration (MIC) was determined using the agar dilution method to assess the antibacterial activity of tea tree essential oil and its polymer. The MIC values of tea tree essential oil was 10000 ppm for 2 strains (3.3%), 5000 ppm for 51 strains (85%), and 2500 ppm for 7 strains (11.7%), while MIC of the polymer was 20000 ppm for 58 strains (96.7%), and 10000 ppm for 2 strains (3.3%). Gene expression was measured using the RT-qPCR method. Tea tree essential oil and its polymer were highly effective antibacterial agents against E. coli bacteria, and their effect on decreasing gene expression of the sat gene was more pronounced than that of the vat gene. This effect indicates the potential of tea tree essential oil and its polymer as alternative antibacterial agents that target bacterial virulence, providing a strategy for combating antibiotic resistance and pathogenicity.
Predictive Role of Immunological Markers sCD14-ST and Interleukin-6 in Assessing Severity and Recovery Outcomes in COVID-19 Patients
The soluble cluster of differentiation CD14 subtype (sCD14-ST) acts as a cofactor, increasing pattern recognition receptor (PRR) activity through some infections. Interleukin-6 (IL-6) has a critical clinical role in infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing a cytokine storm that eventually leads to acute respiratory distress syndrome (ARDS). During the coronavirus disease 2019 (COVID-19) pandemic, various investigations found that IL-6 and sCD14-ST are predictive biomarkers for disease prognosis and severity. This study strives to investigate the immunological role of IL-6 and sCD14-ST in predicting COVID-19 outcomes. A case-control study involving 180 participants was divided into three groups: a severe group (with a particular focus on intensive care unit (ICU) patients), a mild-moderate group, with 60 patients, and a control group consisting of 60 healthy participants. ELISA was utilized to quantify IL-6 and sCD14-ST. The results exhibited a statistically significant increase (p-value ≤0.001) in median serum levels of IL-6 and sCD14-ST among patient groups compared to the control group. The Spearman correlation demonstrates a positive and substantial association between patient indicators. According to the findings, high levels of IL-6 and sCD14-ST associated with COVID-19 severity could be used as predictive markers for disease progression, particularly in ICU patients. In contrast, the low levels of these biomarkers in both control and mild-moderate infections may reflect inflammation resolution and infection recovery.
Gold Mineralisation in Metamorphic Rocks on Buru Island, Indonesia: Rock Facies, Geochemistry, Alterations, Mineralisation, and Types of Ore Deposits
Indonesia is a country rich in natural resources, one of which is gold deposits scattered across several locations, including the islands of Sumatra, Java, Sulawesi, Maluku, Nusa Tenggara and Papua. This study aims to (1) determine the type of alteration contained in the research area based on the altered mineral set resulting from the alteration process and the characteristics of gold deposits in metamorphic rocks in the study area, (2) determine the mineralisation characteristics of gold deposits by conducting geochemical analysis, (3) determine the type of metamorphic facies in host-rocks Gold deposits in the research area, (4) explain how the distribution of gold content from the results of geochemical analysis, (5) explain the genetic characteristics of gold deposits in the study area based on geochemical analysis and petrographic analysis. This study involved a field survey and random rock sampling at Mount Botak, Buru Regency, Maluku Province, Indonesia. Rock samples were analysed by petrographic analysis, XRD (X-ray Diffraction) analysis, XRF (X-ray fluorescence) analysis, ICP-OES (inductively coupled plasma-optical emission spectrometry) analysis, and AAS (atomic absorption spectrometry) analysis. The study results indicate that the host rock of gold deposits on Buru Island is a metamorphic rock formed by greenschist facies. The types of alterations are silicic, sericitization, argilic, and chloritization. The mineralisation is generally in quartz veins with a crustiform texture and a slight vein stockwork. Au levels ranged from 0.23 to 5.9 g/ton, which was not accompanied by Ag enrichment. Based on the analysis of gold deposits in the research area, it is an orogenic-type of deposit formed in a mesozonal environment, typically at a depth of 5-10 km. The implications of the research results can be applied to gold exploration purposes in Indonesia, particularly for gold deposits that have metamorphic host rocks.
The Potential Role of Asprosin and Irisin in Colorectal Cancer Diagnosis in Iraqi Patients
Background: Colorectal cancer (CRC) ranks among the top causes of cancer mortality worldwide, yet early detection remains challenging. Although carcinoembryonic antigen (CEA) is routinely used, the roles of adipocytokines such as Asprosin (ASP) and Irisin (Ir) in CRC diagnosis and prognosis are not well defined. Objective: This study aims to determine the diagnostic and prognostic value of serum ASP and Ir levels in Iraqi CRC patients, with analyses stratified by gender, body mass index (BMI), and age. Materials and Methods: In a nine‑month case-control study, 102 individuals (62 histologically confirmed CRC patients and 40 healthy volunteers) were recruited. Serum CEA was quantified by electrochemiluminescence, while Asprosin and Irisin concentrations were measured using ELISA. Statistical comparisons (unpaired t-test, ANOVA) and receiver-operating characteristic (ROC) curve analyses were performed to evaluate the biomarker's performance and correlation with BMI, gender, and age. Results: Compared to controls, CRC patients exhibited significantly lower ASP (mean ± SD: 1.85 ± 0.45 vs. 2.32 ± 0.50 pg/mL; P< 0.001) and higher Ir levels (3.15 ± 0.70 vs. 2.48 ± 0.60 ng/mL; P < 0.001). ASP positively correlated with BMI (r = 0.42; P = 0.002) and was elevated in males and patients > 60 years. In contrast, Irisin inversely correlated with BMI (r = –0.35; P = 0.008) and was lower in patients < 50 years. ROC analysis yielded AUCs of 0.7801 for ASP (cut‑off 2.098 pg/mL; 83.9% sensitivity and 60.0% specificity) and 0.7571 for Ir (cut‑off 2.232 ng/mL; 72.2% sensitivity and 67.7% specificity). Conclusion: Serum ASP and Ir display distinct expression patterns in CRC and demonstrate good diagnostic potential, influenced by BMI, age, and gender. These adipocytokines may complement existing biomarkers to enhance early detection of CRC and risk stratification; larger studies are warranted to validate these findings and explore the underlying mechanisms.
Analyzing Materials and Determining their Physical Properties Using Spectral Sensing Technology from Satellite Images: Methodology and Applications
The spectral remote sensor technology was used to study the Kurdistan region of Iraq to determine the characteristics of surface minerals and by analyzing satellite images across multiple spectral ranges, distinctive spectral signatures were specified for several metals such as zinc (ZN), Lead (PB), and Parium (BA), as well as the use of thermal infrared to detect free abnormalities and the results were verified through field measurements and admonitory, where the selection accuracy was 85% according to the absolute error (MAPE) and 0.045 for RMSé and the results showed that spectral signatures for metals were distributed in nearby and remote IR ranges, helping to determine mineral sediments such as zinc and lead in carbonate rocks and infrared data and it also revealed a surface temperature between 20°C and 35°C, with thermal anomaly indicating metal concentrations and the study confirms the effectiveness of spectral remote sensing as an inexpensive and accurate tool for minerals, which enhances sustainable resource management strategies in Iraq.
The Antioxidant and Anticancer Efficacy of Tea Tree (Melaleuca alternifolia) Oil and Casein Polymer Against Melanoma Skin Cancer
One of the most widespread global health problems is cancer, specifically skin cancer. These problems are attributed to environmental and immunological causes and can be associated with other disease conditions. According to the statistical increase of the disease, the need has become urgent to reach an alternative formula for chemotherapy due to its side effects on the body's organs. One of the most important anticancer agents is essential oils, especially tea tree oil, which has been extracted from the plant's dry leaves using the steam distillation method by Clevenger apparatus, then analysed using gas chromatography mass technique which revealed the presence of many important compounds such as (4-terpineol 22.45%, cymene 14.10%, γ-terpinene 6.69%, α-pinene 5.79%, α-terpineol 3.48%, sabinene 2.54% and α-terpinolene 2.33%); the oil was polymerized with casein to compare its effectiveness as an antioxidant and anticancer agent. The study proved that casein polymer compared to ascorbic acid scored highest inhibitory activity at concentration 100 (mg/ml) (34.34±11.92 and 54.08±15.89) and 80 (mg/ml) (27.15±10.92 and 38.77±12.83) and lowest inhibitory activity at concentration 40 (mg/ml) (14.26±4.98 and 20.91±8.92) and 20 (mg/ml) (14.89±6.29 and 18.36±6.87); meanwhile tea tree oil scored highest anticancer activity at doses 0, 31.25, and 62.5 µg/ml (100 ± 1.92, 92.20 ± 1.98, and 91.96 ± 1.95) and lowest anticancer activity at doses 250 and 500 µg/ml (53.6 ± 1.80 and 10.37 ± 2.86), while casein scored highest anticancer activity at doses 0, 7.81 and 31.25 µg/ml (100 ± 4.09, 89.94 ± 0.66 and 89.35 ± 3.30) and lowest anticancer activity at doses 250 µg/ml (74.09 ± 1.78) which considered the highest skin anticancer value for the polymer.
Role of Date Palm Seeds Extract in Modulating Inflammatory Mediators, Apoptotic Pathways, and Cellular Signaling in Alloxan-Induced Diabetic Male Rats
Hyperglycaemia is a result of genetic, environmental, and immunological factors. These factors lead to the destruction of pancreatic beta cells, resulting in insulin deficiency. This study aimed to investigate the effect of date seed extract on inflammatory, cellular, and tissue changes in male rats with alloxan-induced diabetes. Thirty rats were housed in the College of Veterinary Medicine at Tikrit University and divided into five groups. The control group was given distilled water, the second group was the diabetes induction group, while the third and fourth groups were induction groups treated with date seed extract and metformin, respectively. As for the fifth group, they were given only date seed extract. The results showed a significant increase in the levels of caspase-3, fetuin-A, IL-6, and STAT-3, with a decrease in IL-12 levels in the diabetic group compared to the control group. In contrast, the diabetic rats treated with date seed extract showed a reduction in the levels of caspase-3, fetuin-A, IL-6, and STAT-3, and an increase in the level of IL-12. Alloxan also showed detrimental effects on liver tissue, manifested in the infiltration of inflammatory cells, congestion of the central vein, and haemolysis. The chemical analysis of date seeds revealed the presence of phenols, flavonoids, and tannins, which possess antioxidant and anti-inflammatory properties. The current study demonstrated the vital role of date seed components in reducing levels of Caspase-3 and Fetuin-A, as well as inflammatory mediators, and improving the liver tissue structure in diabetic-induced rats.
Nonlinear optical characteristics of Nile blue films doped with the polymers PMMA, PVC and their blend by using z-scan technique
The nonlinear optical characteristics of the laser dye Nile blue doped with Polyvinyl chloride (Nb /PVC), poly methylmethacrylate Nb/ (PMMA) and their blend N /(blend of PMMA 50 %+PVC 50%) was studded. Free-casting technique method was used for deposited the films. The nonlinear properties of the films studded by using Z- scan technique .Z-scan experiment was performed using continuous wave (CW) diode laser at 650 nm in two parts with power of 50 mw . The first part was done using a closed-aperture placed in front of the detector to measure the nonlinear refractive index ,with the second part; the aperture in front the detector was removed (open aperture) to measure the nonlinear absorption coefficient. The open-aperture curve exhibits a normalized transmittance (valley), indicating the presence of induced absorption. The observed nonlinearity is found to be of the third order, as it fits to two photon absorption process (TPA). The closed-aperture curve exhibits a peak to valley shape, indicating a negative value of the nonlinear refractive index n2. The effective values of the nonlinear refractive index n2, the nonlinear absorption coefficient β2, real and imaginary parts of the third-order optical nonlinearity, χ(3) for Nb/PMMA+PVC films comparatively with that of Nb/PMMA and Nb/PVC has much lower optical transmittance value obtained shows that these films can be used as efficient optical limiters.
Copyright (c) 2021 Iraqi Journal of Science https://creativecommons.org/licenses/by-nc/4.0
Non-Calibrated Camera-Based Robot Arm for Pick and Place Tasks
The integration of robotic systems with machine learning and computer vision has become increasingly critical in automating systems. This is specifically essential to accomplish complex and different tasks, hence enabling intelligent systems to operate with minimal human intervention. These tasks include object recognition, classification, and manipulation. However, accurate object localization and manipulation pose challenges for robotic systems relying on non-calibrated cameras due to positional inaccuracies. This paper introduces a new non-calibrated camera mapping technique to enhance precision in robotic pick-and-place operations. To this end, a robotic arm controller is implemented to pick and place objects using efficient machine learning and computer vision techniques. The proposed approach is used to pick and place different objects that are identified and labeled by certain classes and sorted accordingly. The location of the objects is found using a proposed non-calibrated camera approach. This approach eliminates the need for expensive calibration procedures while maintaining high accuracy. The proposed method is evaluated by comparing actual object locations with those found using the camera mapping, resulting in a 2.458% error rate. In addition, a comparison with other non-calibrated camera approaches demonstrated that the proposed method achieved higher accuracy and lower errors. These results show promise for applications in industrial automation and robotics systems.
Enhanced Brain Tumor Classification Using EfficientNetB0 and Hybrid Machine Learning Approaches
The classification of brain tumors has remained a strong area of research in the medical field, and this has been caused by the high number of cases of brain tumors reported all over the world. The incidence rate of brain tumors in India in 2023 was found to be more than 38,000 new cases. This is one of the widespread cancers, with fewer than 34,000 deaths occurring. The opposing issues in the classification of brain tumors using machine learning (ML) include the small scale of the data, feature selection, and significant classification errors. Although deep learning (DL) methods are continually evolving, this research will provide solutions using a hybrid scheme that combines mixed ML and DL methods. The models examined in this paper are: Convolutional Neural Networks (CNN), CNN with Support Vector Machine (SVM), Random Forest (RF), Logistic Regression (LR), and EfficientNetB0. Four types of measures were taken to establish the accuracy of the results and to compare the five types of models applied in the study. The outcome indicated that EfficientNetB0 was the best model, with an accuracy of 99.80%, a precision of 99.90%, a recall of 99.80%, and an F1-score of 99.80%. The CNN, CNN-SVM, CNN-RF, and CNN-LR models, on the other hand, provided accuracies in the range of 89% to 91%. This outcome demonstrates that EfficientNetB0 outperforms other models in detecting brain tumors, as well as its ability to enhance diagnostic capabilities in clinical settings. The paper presented the performance of each tumour class (Glioma, Meningioma, Pituitary Tumor, No Tumor) in each model. It also employed statistical validation methods, including cross-validation and significance testing, to support the results.
Equilibrium points and their stability of food - chain prey - predator model involving fear and toxin
This paper presents and analyses a food chain eco-toxicant model involving one prey and two predators, incorporating a fear with linear and nonlinear harvesting, utilizing two distinct functional responses (Lotka-Volterra and Sokol-Howell). Prey species are directly exposed to environmental toxins, while first and second predators encounter these toxins through consumption. The model's boundedness and uniqueness have been established. All the equilibrium points of this model have been found. All requisite conditions for achieving the local stability of equilibrium points have been identified, leading to in the conclusion that all points where are locally stable. Additionally, a global stability study has been conducted using appropriate Lyapunov functions. Ultimately, numerical simulations for a one set of parameters and varying initial conditions have been conducted to validate the analytical results and to assess the effect of fear, toxins, linear and nonlinear harvesting on the dynamics of the proposed model.
Evaluation of the Heavy Metals Concentration Upon Occupational Workers at Several Petrol Filling Stations in Baghdad City, Iraq
Several heavy metals emitted from car petrol may accumulate in occupational workers at elevated concentrations, resulting in various impacts on these workers. The current work was designed to assess the blood content of Zn, Cu, and Pb in occupationally exposed workers. Four car filling stations situated within Baghdad city, Iraq, and 40 occupational workers were subjected to this study; in addition, a sample of 20 individuals away from these examined fuel stations was selected to act as a control sample during November 2023. From both occupational workers and control samples, 4 ml of blood from each individual was taken and placed in a gel tube for coagulation. Each blood sample was centrifuged for 40 min at 3000 rpm to separate blood serum. The serum of each sample was placed into glass tubes and kept in a refrigerator at 20º C and then used to assess blood Zn, Cu, and Pb content. Also, the ages of both control and workers samples and the working period of only occupational workers were recorded. The obtained data has shown that the mean of examined blood heavy metals content was significantly lower in the control sample than those detected in occupational workers where control sample had a mean value of Zn of 65.15 ± 11.0, Cu of 101.3 ± 14.57 and Pb of 14.625 ± 2.52 µg/dl while worker sample gave mean value of 98.03 ± 23.07, 123.26 ± 40.96 and 57.68 ±14.33 µg/dl for Zn, Cu, and Pb respectively. Also, this work has found that there were insignificant (P < 0.05) effects of age on blood heavy metals whilst a significant effect of working period (P < 0.001) on blood heavy metal content of examined workers was recorded. Also, t-test analysis has revealed significant differences (P < 0.05) between the mean values of control and occupational workers for all examined blood heavy metals content.
Construction of the 1,3,4-Oxadiazole Rings at C-5 of Benzotriazole and Investigation of Its Biological Activities
This study reports the synthesis of novel benzotriazole-substituted 1,3,4-oxadiazole rings 4-17 through a four-step reaction sequence. Initially, benzotriazole-5-carboxylic acid (1) was converted to its acid chloride derivative 2 via treatment with thionyl chloride. Subsequently, nucleophilic addition of hydrazine hydrate yielded 89% of hydrazide 3. The desired compounds 4-17 were then obtained via condensation of compound 3 with different aromatic aldehydes, followed by an oxidative cyclization reaction using I2/K2CO3. The target compounds 4-17 were obtained in yields ranging from 65 to 90%. The structures were confirmed using FT-IR and 1H NMR spectroscopy. Additionally, the antioxidant and antibacterial properties of a few of these products were investigated.
Enhancing the Performance of Cyberattack Detection Model on AWS Using Stacked Feature Selection and Hybrid Classification
One of the essential technologies worldwide is cloud computing. Increasing demand for its various Amazon Web Services (AWS) services make it more vulnerable to different types of attacks, such as DoS, DDoS, Infiltration, and others). The full list of attack types used in this study is presented in the classification section. Protecting cloud systems and their data mainly depends on various security technologies, including intrusion detection systems that monitor network traffic to detect suspicious activity or potential threats. This research proposes a model to contribute to solving the problem of identifying malicious activities in cloud networks. This model has three stages: the initial stage is pre-processing, encompassing data cleaning, normalization, and labelling. Stage two involved intersecting the outputs of the correlation and Information Gain methods to obtain a set of common features. Then these features were further filtered using the Chi-square method to identify the most relevant features. Lastly, a proposed classification technique was used utilizing (CNN -XGBoost) to classify traffic in the network into normal and abnormal. Experiment results on CSE-CIC-IDS2018 dataset showed that the proposed model achieved an accuracy of 99.3%, outperforming traditional filter-based feature selection.
Stability and Bifurcation in Fractional Order Derivatives of a Tri-Trophic Food Chain with Harvesting
This paper primarily focuses on the study of an ecological model in which fractional differential equations (FDEs) are utilized to construct the model rather than using traditional first order differential equations. A model of tri-trophic food chain is explored using the Beddington–DeAngelis (BD) functional response with harvesting in each species. The impact of harvesting on the system’s behaviour is observed, that brings about the occurrence of both bifurcations, Transcritical and Hopf bifurcation, which depends not only on fractional order derivative parameters, but also on the harvesting parameters. The existence, uniqueness, non-negativity, and boundedness of the solutions are explored. Next, the stability of all feasible equilibrium points is determined locally. Additionally, sufficient conditions are established to make certain the global asymptotic stability of each point of equilibrium, except the trivial equilibrium point, by selecting an appropriate Lyapunov function. Finally, numerical simulations are given to illustrate the outcomes of our dynamical analysis of the model.
Gene Expression of clfA , clfB, and SdrC Genes of Staphylococcus aureus Under Probiotic Stress
The significant factor that participated in virulence and pathogenesis for Gram-positive pathogen Staphylococcus aureus is biofilm development. In hospital settings, biofilm construction on medical equipment is quite concerning since it is a permanent source of infection. The infection results from S. aureus biofilm, which was considered a serious problem due to the difficulty in treating it with traditional antibiotics. In recent years, the medical community has been using probiotic bacteria to suppress biofilm development. The current work aims to investigate the impact of cell-free supernatant (CFS) of lactobacillus acidophilus on biofilm generation and gene expression of some key adhesion genes (clfA, clfB, and SdrC) in S. aureus clinical isolates. The CFS was extracted from Lactobacillus. acidophilus, and minimum inhibitory concentration was estimated. The colorimetric method was carried out to detect the impact of sub-minimum inhibitory concentrations of the CFS extracts on biofilm construction in thirty-three S. aureus isolates. Moreover, the expression level of some associated biofilm genes (clfA, clfB, and SdrC) was determined quantitatively before and after CFS treatment using real-time PCR for three isolates forming a strong biofilm. The result indicated that most isolates formed mostly strong and moderate biofilm with 42.42% and 48.48%, respectively, while 6.06% and 3.03% of isolates were weak and non-biofilm former. Regarding the clfA gene, gene expression was only detected in two isolates by which one isolate showed downregulation with a fold change value (0.0883) and another isolate showed upregulation with a fold change value (5.7134) after treatment of isolates with CFS. However, clfB and sdrC revealed a decrease in expression in two isolates, while the third isolate showed upregulation after treatment of isolates with CFS. The above result indicates that clfA, clfB, and sdrC expressed downregulation under the effect of CFS. In conclusion, the ability to produce biofilm plays a significant role in pathogenicity and antibiotic resistance in S. aureus isolates, especially when most isolates produce strong and moderate biofilm. Furthermore, the highly inhibitory effect of CFS from lactobacillus acidophilus in the reduction of biofilm activity and the drop in expression of key biofilm genes in S. aureus isolates highlights the capacity to use CFS as an alternative strategy to eliminate infection related to biofilm in this pathogen.
Cytotoxic Effects of Prodigiosin Pigment from Serratia marcescens on Tumor Cell Lines
Prodigiosin is a secondary metabolite with red pigmentation produced by Serratia marcescens. Prodigiosin has been described for several biological activities, including antitumor. The study aimed to isolate S. marcescens that produces the prodigiosin pigment, purify it, and evaluate its activity against three human cancer cell lines, MM.1S, TP-53, and HL-60, with the HdFn normal cell line as a control. 145 urinary tract infection (UTI) samples and 35 soil samples were collected, and only 16 isolates were identified as S. marcescens using the VITEK system. The isolates were tested under primary and secondary screening to select the best prodigiosin-producing isolate. Isolate S2 had the highest productivity of the pigment (0.1704g/l). The pigment was purified by column chromatography, identified, and characterized using FTIR and UV-VIS spectroscopy. The pigment corresponded to prodigiosin, with a maximum absorption at 535 nm and a structural formula C20H25N3O. High cytotoxic effects of prodigiosin were observed against TP-53 and HL-60 cell lines. The MM.1s were more pigment resistant. The cytotoxic activity showed IC50 of 94.59 and 57.96 against HL-60 and TP-53 cell lines, respectively, and did not affect the normal cell line at all. Prodigiosin pigment exhibits cytotoxic effects on tumor cell lines and is safe for normal cell lines.
ADL: A New Dataset of Select Arabic-Derived Letters for Handwritten Character Recognition
Arabic text and characters recognition are among the most challenging problems in the field of optical character recognition (OCR) due to the complex nature of the letters and their variance in forms. This paper presents a new ADL dataset of the Arabic derived letters: Che (چ), Ngain (ڠ), Pe (پ), Ve (ڤ), Zhe (ژ), and the three versions of Gaf (گ, ڭ, and ݣ). This dataset consists of 55,440 images from scanned handwritten papers made by 30 participants of different ages, thus ensuring demographic and stylistic diversity. The dataset has been evaluated on three different models: a Support Vector Machine (SVM), a Convolutional Neural Network (CNN), and a Vision Transformer (ViT) to demonstrate its practical usability. Several forms for different alphabet positions are used to represent each letter: isolated, initial, medial, and final, to reflect its real-world usage, which increases the value of the dataset for machine learning applications. The dataset was enriched using data augmentation techniques based on random rotation, horizontal shift, and zooming with nearest neighbor interpolation to fill empty pixels, which allowed for representing each character in a balanced way while preserving the essential structural elements. The dataset, as the first structured resource on some derived letters of the Arabic language, aims to fill a crucial gap in datasets focused on Arabic script and to advance research on handwritten character recognition. This dataset has important implications for linguistic research, practical applications, and advances in automated text processing systems by supporting better recognition of these non-original derived letters, especially in optical character recognition (OCR) systems.
Enhancing Steganography System Using Deep Learning and Hyperparameter Optimization
Steganography plays a vital role in secure message transmission, embedding information imperceptibly within cover images. This research addresses the challenge of creating stego images visually indistinguishable from originals, while enhancing resistance to steganalysis. We propose a novel steganographic system based on Generative Adversarial Networks (GANs) with hyperparameter tuning to enhance imperceptibility and security. Multi-scale feature extraction via Inception modules within the encoder facilitates efficient embedding with minimal distortion. A new combined metric, incorporating MSE, PAD, and MAE alongside PSNR and SSIM, provides a more comprehensive performance evaluation, addressing limitations of relying solely on PSNR/SSIM. For instance, while RMSprop achieved a PSNR of 57.32 dB, its combined metric score was 16.37, reflecting its weaknesses in error metrics. Conversely, SGD, with a PSNR of 59.55 dB, achieved a combined metric score of 34.73, demonstrating its balanced performance. Multiple optimization algorithms, including Adadelta, Adam, Nosadam, SparseAdam, Adamp, L-BFGS, RAdamplus, Tadam, RMSprop, Nadam, Ftrl, AdaGrad, AdamW, Adamwt, SGD, RAdam, and Naturalgrad, were evaluated. Nadam and Adadelta achieved the highest combined metric scores (36.71 and 34.61, respectively), correlating with superior PSNR and SSIM values, thus ensuring higher image fidelity and imperceptibility. The system effectively impedes steganalysis by reducing statistical discrepancies and utilizes tanh activation functions for enhanced security. This system achieves robust steganographic performance with minimal distortion and improved security, offering significant advancements in secure image communication. The new combined metric provides a nuanced performance assessment, guiding optimal algorithm selection.
Enhanced Intelligent System Model for Managing Anxiety in In-Vitro Fertilization (IVF) Patients
In vitro fertilization (IVF) program patients have elevated anxiety levels. Therefore, they immediately contact fertility doctors through existing communication media to get treatment. However, fertility doctors cannot respond quickly due to high workloads. The intelligent health system that implements the Case-Based Reasoning (CBR) model is widely used to assist doctors in handling patient complaints. However, the system provides opportunities for modification so that the performance of the CBR model increases and further assists fertility doctors in handling IVF patient anxiety. This study modified the CBR model by integrating several previous research results (CCBR similarity formula, combination of CBR with Rule-Based Reasoning, the role of patient feedback, and the application of a minimum standard value of 80%). Measurement of the coefficient matrix to assess system performance using the Chris Case-Based Reasoning (CCBR) similarity formula produced an accuracy value of 52.58%, and the performance of the combination of the CBR model with the Rule-Based Reasoning model increased the accuracy value by 47.42%, so it can be stated that the CCBR model is a better intelligent system model for handling IVF patient anxiety.
GIS-MCDA Based Land Capability Analysis for Sustainable Food Production in the Kurdistan Region of Iraq
Food production is vital to global food security, entailing significant social, economic, and environmental implications. The Kurdistan Region of Iraq (KRI) possesses abundant natural and human resources essential for agriculture, including extensive agricultural land, water resources, and a favorable climate. However, challenges such as population growth, displacement of large numbers of residents from other provinces to the Kurdistan Region, unplanned urban expansion encroaching on agricultural areas, useless land accumulation, and agricultural land degradation pose substantial threats to sustainable food production (SFP). The study's primary objective is to assess and map the potential for SFP in the region, enabling stakeholders to formulate strategies for sustainability and ensure food security. The methodology involved classifying land capability using Geographic Information System - Multi-Criteria Decision Analysis GIS-MCDA approaches, including the fuzzy analytical hierarchy process-hybrid model (F-AHP) and fuzzy analytical network process F-ANP. The dataset encompassed variables related to land capability for food production, categorized into six main groups: topography, climate elements, water resources, land use-landcover (LULC), geology, and soil characteristics, each with about eighteen sub-factors. Results from F-AHP and F-ANP indicated consistent findings across factor weights and land capability classifications in KRI, showing no significant disparities. Only 10.72% of the region's total land 4245.7 km2 exhibited high capability, while 28.68%, 11355 km2, 34.18%, 13534 km2, and 18.1%, 7168 km2, were moderately capable, low capability, and limited capable land, respectively. An 8.32%, 3295.4 km2 of Kurdistan's land was deemed unsuitable for SFP. The study's insights are crucial for experts, planners, governments, and stakeholders, facilitating the assessment of current food production. Based on these findings, appropriate plans and strategies can be developed to uphold long-term food security in the Kurdistan region.