Journal of university of Anbar for Pure science

Curcumin, a polyphenol extracted from turmeric rhizomes, has shown promising effects in several biological systems, including model organisms. This study investigated the effects of curcumin and nanocurcumin on weight, negative geotaxis, total protein, protein profiling via sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS- PAGE), and lifespan in Drosophila melanogaster as a model organism. Curcumin and nanocurcumin were individually added to the Drosophila melanogaster medium at concentrations of 0.5, 1, 5, and 10 mg/g of media, alongside a control group, with three replicates for each concentration. ANOVA and Tukey’s post hoc test were performed for statistical analysis. The study revealed that curcumin and nanocurcumin had statistically significant effects on multiple parameters, with nanocurcumin showing a greater impact than curcumin and the control group, suggesting that the nano form has higher biological effectiveness and better cellular interaction. As evidenced by an extended Drosophila melanogaster lifespan (P < 0.001) and increased weight (P < 0.01), negative geotaxis (P
< 0.01), and total protein (P < 0.002), an increase in negative geotaxis indicates improved neuromuscular coordination, while increases in weight, total protein, and lifespan may reflect better metabolic activity or nutrient absorption. In addition, curcumin and nanocurcumin significantly altered the SDS-PAGE protein profile, suggesting a potential impact on protein expression that may be linked to gene regulation. These findings demonstrate that curcumin and nanocurcumin have a pronounced impact on physiological and biochemical parameters, with nanocurcumin exerting a stronger effect, making them promising options for biological applications.

The increasing accumulation of heavy metals in aquatic environments poses a persistent threat to both environmental sustainability and public health. Conventional water treatment technologies often suffer from drawbacks such as high operational cost, limited selectivity, and poor regeneration efficiency. In recent years, biopolymer-based hydrogels have gained attention as efficient, eco-friendly, and tunable adsorbents for the removal of heavy metal ions from aqueous systems, owing to their high-water retention capacity, surface functional versatility, biodegradability, and environmental compatibility. Despite significant research efforts, current findings remain scattered, and the lack of a unified framework for evaluating hydrogel performance presents a challenge for practical implementation. This review provides a comprehensive and critical synthesis of recent progress in the design, functionalization, and application of natural biopolymers, particularly cellulose, starch, and chitosan, in hydrogel fabrication for water purification. Special emphasis is placed on chemical modification strategies, including carboxymethylation, graft copolymerization, and sulfonation, that introduce or enhance reactive functional groups responsible for metal ion binding. The mechanisms underlying metal ion removal, such as ion exchange, electrostatic interaction, coordination, and chelation, are discussed in detail. The role of crosslinking methods in controlling hydrogel structure, porosity, stability, and recyclability is also addressed. In addition, the integration of nanomaterials and biochar into hydrogel matrices for performance enhancement is highlighted. Finally, the review outlines key challenges and future directions in translating these materials from laboratory-scale studies to practical, scalable, and sustainable water treatment solutions.

Rheumatoid arthritis (RA) is a persistent inflammatory autoimmune disease that impacts joints and leads to gradual deterioration. Cytokines like IL-17 and IL-21 are associated with the etiology of rheumatoid arthritis due to their involvement in fostering inflammation and autoimmunity. This study investigated the association between single- nucleotide polymorphisms (SNPs) in IL-17F (rs2397084 and rs11465553) and IL-21 (rs2221903) genes and susceptibility to rheumatoid arthritis in an Iraqi cohort. The case-control study included 90 participants (50 RA patients and 40 healthy controls) from Ramadi, Al-Anbar, between November 2023 and January 2024. Genomic DNA was extracted from blood samples, and SNP genotyping was conducted using AS-PCR and ARMS-PCR techniques. Results showed a significant association between the C allele of IL-17F rs2397084 and RA susceptibility (frequency: 0.31 in patients vs. 0.16 in controls, ????2 = 5.235, ???? = 0.022), with genotype distributions of T/T (0.48), T/C (0.42), and C/C (0.10) in patients compared with 0.72, 0.22, and 0.05 in controls (p=0.063). The dominant model (T/C + C/C) indicated increased risk (OR=7.71, 95% CI: 1.43-41.53, p=0.008). For rs11465553, the A allele was more frequent in patients (0.38 vs. 0.06, ????2 = 24.641, ???? < 0.001), with genotype distributions of A/A (0.30), G/A (0.16), and G/G (0.54) in patients compared with 0.02, 0.08, and 0.90 in controls (????2 = 14.881, ???? = 0.001). The dominant (OR=6.28, 95% CI: 1.43- 27.60, p=0.0097) and recessive models (OR=11.64, 95% CI: 1.21-111.53, p=0.0095) confirmed this association. For IL-21 rs2221903, the T allele was more prevalent (71 in patients vs. 44 in controls,????2 = 6.378, ???? = 0.012), with genotype distributions of T/T (n=23), T/C (n=25), and C/C (n=2) in patients compared with T/C (n=28), C/C (n=4), and T/T (n=8) in controls (????2 = 46.586, ???? < 0.001). However, genetic model analysis showed no significant associations (e.g., dominant model OR=0.30, p=0.095). Deviations from Hardy-Weinberg equilibrium were observed for rs11465553 in patients (p<0.0001) and rs2221903 in controls (p=0.023), possibly reflecting disease effects or sample size limitations. These findings suggest that IL-17 and IL-21 genetic variations may contribute to RA susceptibility in the Iraqi population. Further studies in larger, multiethnic cohorts are warranted to confirm these associations and elucidate underlying mechanisms.

The study investigates the prevalence of multidrug-resistant (MDR), extensively drug-resistant (XDR), and pan-drug-resistant (PDR) profiles among ESKAPE pathogens. It examines the role of biofilm formation in the development of antimicrobial resistance. This cross-sectional study, conducted between May 2024 and March 2025, analyzed 546 clinical specimens collected from patients aged 1–85 years (mean ± SD = 36.07 ± 18.97) who were admitted to intensive care, ENT, internal medicine, gynecology, surgery, and burn units across several Iraqi hospitals, including Ramadi, Al-Fallujah, Heet, Ghazi Al-Hariri, Burns Specialist, Al-Yarmouk, and Al-Hakeem. Bacterial identification was performed using the VITEK 2 Compact system, and antimicrobial susceptibility testing was performed according to CLSI (2024). Biofilm formation was assessed qualitatively using the microtiter plate method and quantitatively using sodium alginate beads. Of the 546 isolates, 331 (60.62%) were identified as ESKAPE pathogens; among these, 51.0% were MDR, 32.9% were XDR, and 9.4% were PDR. Biofilm formation was observed in 86.9% of the isolates. Notably, Staphylococcus aureus showed a significant association between MDR and strong biofilm formation (OR = 6.04, p = 0.018), whereas Klebsiella pneumoniae exhibited a weaker correlation (OR = 0.77, p = 0.015). The microtiter plate method (86.9%) demonstrated higher sensitivity than the alginate bead assay (82.4%), particularly for Enterobacter spp. (p = 0.002). The findings highlight the high prevalence of MDR, XDR, and PDR ESKAPE pathogens, particularly A. baumannii and K. pneumoniae, in Iraqi hospitals, underscoring the need to integrate antimicrobial resistance profiling and biofilm evaluation into infection control and therapeutic management.

A pot experiment for the 2024–2025 agricultural season was conducted using a completely randomized design to evaluate the effectiveness of Trichoderma harzianum in the biological control of Alternaria solani, the cause of early blight on tomato plants, in vivo and in vitro. The bioactivity of the 15-day culture filtrate extracted from T. harzianum was assessed against pathogenic A. solani fungi. The dual culture assay (DCA) was calculated to evaluate the efficacy of T. harzianum on the pathogenic fungus in vitro. Chitinase and ????-glucanase enzymes in T. harzianum were measured to determine their role in fungal cell degradation. To understand the role of T. harzianum filtrate in stimulating defensive enzymes in plants (in vivo), the activities of phenylalanine ammonia lyase (PAL), polyphenol oxidase (PPO), peroxidase (POD), and catalase (CAT) were measured in tomato plants after treatment with T. harzianum filtrate.
The results showed that, in the dual culture assay, the largest mean diameter of Trichoderma was (80.00 ± 0.71) in 7 days (168 hr), while A. solani showed the largest diameter (25.00±0.71) in 4 days and then decreased to the lowest diameter (10.20±0.66) in 7 days. The age of Trichoderma filtrate and the incubation period had significant differences (???? ≤ 0.05) in A. solani colonies. The 15-day extracts of T. harzianum had significant cytotoxic effects toward A. solani. The results of chitinase and ????-glucanase enzymes extracted from the culture medium of T. harzianum showed 2.87 and 1.68 Units/mL, respectively, compared with the control (non-Trichoderma cultured medium), which gave 0.021 and 0.013 Units/mL, respectively. The results also showed that the defensive enzymes in tomato plants (PAL, PPO, POD, and CAT) showed higher levels in plants treated with Trichoderma filtrate than in untreated plants, further supporting the role of Trichoderma filtrate in stimulating plant resistance. In vitro findings using several methodologies indicate that T. harzianum was the most effective in suppressing A. solani growth. It may serve as a possible biocontrol agent in the future.

This study aimed to investigate the wound healing properties and antimicrobial activity of silver nanoparticles, hyaluronic acid, and their combination in animal models. Twenty rabbits were divided into five groups (n = 4): group 1, the control group; group 2, the induction group; group 3, the group treated with 1% silver nanoparticle ointment (1% SNO); group 4, the group treated with hyaluronic acid ointment (HAO); and group 5, the combination-treated group. Skin wounds were induced in the latter four groups, contaminated with multidrug-resistant Pseudomonas aeruginosa, and treated for 15 days. The healing process was evaluated based on gross and histopathological findings. Histopathological scoring was used to compare the groups. Results showed that wound healing improved in all treated groups compared with the induction group. The 1% SNO-treated group showed better results than the HAO-treated group in reducing inflammation, while the HAO-treated group also showed improvement compared with the induction group. The 1% SNO group showed a greater reduction in inflammation, whereas the HAO group exhibited better epidermal regeneration. The most significant acceleration of wound healing was observed in the combination-treated group (group 5). It was also noted that this group had the lowest score (0) for inflammation and granulation tissue formation and the highest scores (4) for the regeneration of skin appendages, collagen deposition, and re-epithelialization compared with other groups. In conclusion, combining HAO and SNO may be more effective than using either treatment alone. To our knowledge, this is the first study to use a combination of SNO and HAO for treating skin wounds.

Vitamin D deficiency has been implicated in disturbances of thyroid function and iron metabolism, but data from Iraqi clinical populations remain limited. We performed a hospital-based cross-sectional study (August 2024-January 2025) of 99 adults (15-45 years; 49 males, 50 females) attending Mosul General Hospital to examine associations between serum 25-hydroxyvitamin D status and two biochemical markers: thyroid-stimulating hormone (TSH) and ferritin. Participants were classified as vitamin Ddeficient (≤10 ng/mL, n = 37), insufficient (11-20 ng/mL, n = 31), or sufficient (>20 ng/mL, n = 31). Mean TSHwashighest in the deficient group (5.09 ± 0.77 µIU/mL) and lowest in the sufficient group (1.90 ± 0.13 µIU/mL; p < 0.001). Mean ferritin was lowest in the deficient group (42.8 ± 3.07 ng/mL) and higher in the sufficient group (60.26 ± 7.3 ng/mL; p = 0.03). Correlation analysis showed a significant inverse association between vitamin D and TSH (r =-0.488, p < 0.001) and a positive association between vitamin D and ferritin (r = 0.212, p = 0.035). These findings indicate that lower vitamin D status is associated with higher TSH and lower iron stores in this hospital cohort. Consideration of vitamin D and iron status may aid the interpretation of abnormal TSH values and warrants prospective investigation to test whether nutritional correction modifies thyroid-related outcomes.

Antibiotic resistance (ABR) has emerged as a critical global health challenge, posing considerable threats to effective infection management and public health. Antibiotics are increasingly ineffective against a wide range of pathogens because of the rising rate of microbial resistance. Misuse and overuse of antibiotics in both clinical and agricultural settings have contributed to the proliferation of resistant strains. A substantial number of deaths are attributable to drug-resistant infections, underscoring the urgency of addressing this crisis. This review aims to inform stakeholders in mitigating the impact of antibiotic resistance on global health. It focuses on the multifaceted nature of ABR, highlighting mechanisms by which bacteria avoid antibiotic action, including horizontal gene transfer, genetic mutations, and biofilm formation. The review also emphasizes the need for an integrated, modern approach to reduce antibiotic resistance, incorporating advances in diagnostic techniques and novel therapeutic strategies to protect public health.

ThisstudyusedtendifferentOleaeuropaeaL.genotypes, includingAshrasi, Bashiqa, Manzanilla, Dakel, Al-Khudairi, Darmalali, Sorani, Qaisi, Nabali, and Ascolano. The genotypes were selected from seven sites representing the major areas of olive production and cultivation in Iraq. Genetic relationships among the 10 examined olive cultivars were determined using ISSR analysis, which revealed that 10 primers were highly efficient, generating 98 bands, 64 of which were polymorphic, yielding a mean polymorphism rate of 64.7%. These findings reveal significant genetic differentiation among the olive cultivars under study. Genetic similarity coefficients ranged from 0.11 to 0.83, indicating a broad spectrum of diversity. The Ashrasi cultivar was the most genetically distinct, suggesting it may be useful for enriching genetic diversity. In contrast, high genetic similarity was observed between Qaisi and Dakel, and between Darmalali and Al-Khudairi. These results were also supported by the dendrogram, which separated the cultivars into two major groups: one with higher similarity and the other with greater evolutionary distance, with Ascolano forming a separate branch, indicating its unique genetic identity.

Chronic occupational exposure to heavy metals is among the most significant health risks faced by workers in environmentally hazardous industries, particularly in welding. These elements are associated with cumulative toxic effects on the immune and renal systems, as well as redox balance, often leading to long-term chronic health disorders. Across-sectional study was conducted in Ramadi, Iraq, from January 1 to February 1, 2024, including 40 welders exposed to metal fumes and a control group of 20 healthy, unexposed individuals. Participants were aged 25–60 years, with welding work ranging from 5 to 30 years, stratified into four groups with 5-year exposure intervals. Blood and urine samples were collected from all subjects to assess immunoglobulins (IgE) and cytokines (IL-5), neutrophil gelatinase-associated lipocalin (NGAL), oxidative stress biomarkers (GSH-PX), and blood metal levels (Pb, Cd, Cr). Significant increases in mean ± SD IgE levels were observed, rising from 86.2 ± 22.7 IU/mL (5 years exposure) to 139.8 ± 39.0 IU/mL (25–30 years), compared with 66.9 ± 21.7 IU/mL in controls (p < 0.001). The mean ± SD IL-5 increased numerically from 12.8 ± 3.1 to 17.2 ± 5.1 pg/mL, compared with 9.2 ± 2.7 pg/mL in controls, but did not reach statistical significance (p = 0.088). Urinary NGAL mean ± SD rose significantly from 120.8 ± 21.3 to 191.6 ± 39.2 ng/mL, compared with 104.5 ± 23.3 ng/mL in controls (p = 0.001), suggesting progressive tubular kidney damage. GSH-PX mean ± SDactivity decreased markedly from 45.2 ± 9.2 to 26.7 ± 9.1 units/mL, against 47.6 ± 11.6 units/mL in controls (p = 0.002), indicating diminished antioxidant defense. Lead and cadmium blood levels showed linear increases, with mean ± SD Pb rising from 25.7 ± 9.1 to 66.1 ±13.7µg/dLandmean±SDCdrisingfrom3.2±1.1to8.0±2.4µg/L, while chromium remained elevated but not statistically significant. The study reveals a clear cumulative impact of chronic heavy metal exposure in welding environments on workers’ immune, renal, and oxidative systems, with severity increasing alongside years of service, notably beyond 10 years. These findings support the urgent need for enhanced preventive measures and ongoing medical surveillance among long-term exposed workers to curb progressive health risks.

The rapid rise of antimicrobial resistance has weakened the clinical value of many antibiotics and complicated the management of burn wound infections. This study investigated bacterial pathogens recovered from burn wounds in Ramadi City and evaluated wastewater-derived bacteriophages as a targeted option against drug-resistant isolates. A total of 100 burn wound swabs were collected from patients (12-65 years) at Ramadi City Hospital between September 15, 2024, and January 17, 2025. Isolates were cultured on selective media, identified by microscopy and biochemical testing, and confirmed using the VITEK_2 Compact system. Antimicrobial susceptibility was assessed by the Kirby–Bauer disk diffusion method using 12 antibiotic disks interpreted according to CLSI 2024. Biofilm production was screened, and molecular confirmation wasperformedusingconventionalPCRtargetingthe16SrRNAgenewithelectrophoretic visualization and sequencing for verification. Environmental wastewater samples from a local wastewater filling station were used for phage enrichment, isolation by the double agar layer method, plaque purification, and morphological characterization by transmission electron microscopy (TEM). Eighty-six bacterial isolates were obtained from the 100 samples; 14samplesshowed no growth. Staphylococcus aureus was the predominant organism (54%), followed by Pseudomonas aeruginosa (9%), Klebsiella pneumoniae (7%), Escherichia coli (5%), Enterobacter aerogenes (4%), and Serratia marcescens (3%), with several species detected as single isolates. Lytic bacteriophages were recovered only against S. aureus; no lytic activity was observed against E. coli, P. aeruginosa, or K. pneumoniae under the conditions tested. TEM revealed tailed phage particles consistent with common staphylococcal bacteriophages. Overall, wastewater-derived phages showed strong host specificity for S. aureus, supporting further work to optimize isolation conditions, expand host-range screening, and evaluate combined phage-antibiotic strategies for burn wound infections.

Uterine fibroids are the most common benign tumors in women of childbearing age. Fibroids are made of muscle cells and other tissues that grow in and around the wall of the uterus (womb). This study aimed to examine the relationship between uterine f ibroids and women’s age. This study included 30 patients of different ages (25–50) who were suspected to be diagnosed with uterine fibroids. Patients were recruited from Al-Rrazy private hospital and private laboratories. Patient information, including name and age, was recorded. Pathological fibroid samples were collected postoperatively and fixed in 10% formalin for histopathological analysis. The present work revealed a significant difference in uterine fibroids with increasing age; 80% of phase 1 showed a substantial increase in women aged 40–50. Histopathological findings in phase 1 showed cellular leiomyoma with mitotic figures, sheets of smooth muscle cells arranged in parallel, and no stromal collagen. In conclusion, the incidence and prevalence rates of uterine fibroids in the normal population of Al-Ramadi city are comparable to those reported in other parts of the globe. Rates of uterine fibrosis ranged between age groups and reached 35% of women. The most affected cases were between 40 and 50 years of age in phase 1.

ATP-bindingcassettetransporter A1(ABCA1)isacrucialproteinthathelpspromote cholesterol efflux and HDL synthesis. ABCA1 defects can cause type 2 diabetes, insulin resistance, and difficulties with fat metabolism. The aims of this study were to establish blood ABCA1 levels in Iraqi patients with recent-onset type 2 diabetes and prediabetes and to evaluate their correlations with clinical and metabolic characteristics and smoking status. In this case-control study, serum ABCA1 levels were measured in prediabetes (n = 40), newly diagnosed type 2 diabetes (n = 56), and control groups (n = 40). Samples collected from January 15, 2024, to November 5, 2024, were used to measure diabetes parameters and lipid profiles. As a result, newly diagnosed type 2 diabetes showed a slight but statistically insignificant reduction in serum ABCA1 levels compared with prediabetes and controls. LDL-C, VLDL-C, total cholesterol, and triglycerides were inversely correlated with ABCA1 in patient groups. ABCA1 correlated positively with HDLin patients with newly diagnosed diabetes mellitus but negatively in those with prediabetes. All groups had significantly lower ABCA1 levels according to smoking status. The negative correlation between HOMA-???? and ABCA1, along with the positive correlations between HOMA-IR and insulin and ABCA1 concentration, reveal the role of these factors in pancreatic function. The main conclusion is that smokers with prediabetes or newly diagnosed diabetes mellitus showed decreased ABCA1 levels, suggesting a complex regulatory system involving genes, metabolism, and environmental factors.

Wastewater from various sources can release large amounts of chemical pollutants and related substances into the environment. There is an immediate need for methods to purge water and wastewater of contaminants; one possible strategy is to employ matrix-stabilized nanoparticles for adsorption-based pollutant removal. Mesoporous silica (mSiO2) can be derived from natural sources as a cost-effective alternative to industrial products. Natural minerals such as porcelainite, kaolinite, shale, and diatomite contain silicon dioxide (SiO2), making them promising raw materials for the manufacture of mesoporous silica. Mesoporous silica is characterized by a highly ordered pore structure, with diameters ranging from 2 to 50 nm, an excellent surface area, and a slimming structure. Recent studies have demonstrated the adsorption capacity of mSiO2, particularly modified varieties, for removing toxic metal ions such as lead (Pb2+), cadmium (Cd2+), and chromium (Cr3+), even at low concentrations. These ions pose significant environmental risks due to their bioaccumulative nature and persistence in aquatic environments. Therefore, in simple terms, matsorption is a cost-effective, simple, and efficient method that is comparable to other techniques such as reverse osmosis, membrane filtration, precipitation, oxidation-reduction, and ion exchange. The mesoporous silica (mSiO2) was characterized using FTIR, FESEM, and XRD analyses. Fourier transform infrared (FTIR) spectroscopy has been widely used to characterize the functional properties of both tattoo chemicals and the distinctive features of military compounds. A strong short-duration stretching band at 1000 cm-1, attributed to silicon-oxygen vibrations, is the bandgap location of silicon dioxide. This demonstrates the fineness of the prepared material. The XRD pattern of pure silica (mSiO2) showed a strong stretch at 2???? = 2.2◦ (100), spanning two stretches at 2???? = 3.7◦ (110) and 4.3◦ (200). These lines indicate the hexagonal mesoporous structure of mSiO2. FESEMimages showed that mSiO2 has a uniform surface composed of densely packed spherical particles. The test materials were evaluated for the removal of Pb2+, Cd2+, and Cr3+ ions, with removal efficiencies of 97.8% for Pb2+, 98% for Cd2+, and 99.6% for Cr3+ ions. Manufactured silica effectively decomposes water under various conditions, with optimal elimination achieved at pH 8, a contact time of 60 minutes, and a temperature of 298.

Hydrophilic surfaces modified with polymer brushes have attracted significant attention due to their applications in biomedical fields, particularly for reducing nonspecific protein adsorption. In the current study, different concentrations of thiolpoly(ethylene glycol)-acetic acid (thiol-PEG-acetic acid) were used to modify gold surfaces using surface plasmon resonance (SPR), aiming to reduce non-specific protein adsorption. Different grafting densities were obtained by using different concentrations of thiol-PEG-acetic acid, and the results showed that the highest concentration of thiol-PEG-acetic acid produced a high thiol-PEG-acetic acid grafting density. All modified surfaces were characterized using advanced analytical techniques, including X-ray photoelectron spectroscopy (XPS), SPR, and water contact angle measurements. Furthermore, all surfaces were tested in a bovine serum albumin (BSA) solution. The study found that a low grafting density of thiol-PEG-acetic acid resulted in high protein adsorption on the modified gold surface.

Thyroid disorders and diabetes mellitus frequently occur and disrupt metabolic balance. Vitamin D, leptin, and asprosin contribute to metabolic regulation, and alterations in lipid profiles can further complicate this condition. To investigate relationships among asprosin, leptin, and other biomarkers in diabetic patients with hypothyroidism or hyperthyroidism, a cross-sectional study was conducted with 130 participants divided into three groups: diabetes with hypothyroidism (n = 50), diabetes with hyperthyroidism (n = 50), and diabetes with normal thyroid function (n = 30). Participants were recruited from Al-Yarmouk Hospital in Baghdad, Iraq, between July 2024 and May 2025. Thyroid hormone levels (TSH, free T3, free T4) and vitamin D were measured using an enzyme-linked fluorescence assay. Lipid profile and HbA1c levels were assessed using a spectrophotometer. Levels of asprosin and leptin were determined by enzyme-linked immunosorbent assay. Patients with hypothyroidism showed significantly higher leptin and asprosin levels and lower vitamin D comparedwith the other groups. Hypothyroid diabetics also had less favorable lipid profiles, including increased LDL and total cholesterol. Free T3 showed negative correlations with total cholesterol and positive correlations with HbA1c and vitamin D. Triglycerides and BMI showed positive correlations with TSH. Thyroid dysfunction significantly affects metabolic markers in diabetes. Hypothyroidism is associated with increased asprosin and leptin. Monitoring these markers may improve management.

This study addresses the synthesis and characterization of seven new complexes of a hydrazone ligand derived from a non-steroidal anti-inflammatory drug (ibuprofen) via condensation with p-nitroacetophenone, followed by reaction with cobalt(II), nickel(II), copper(II), zinc(II), and cadmium(II) chloride and nitrate salts. All complexes were prepared in a 1:2 metal-to-ligand molar ratio. The ligand and its complexes were characterized using FTIR, UV–Vis, 1H NMR, magnetic susceptibility measurements, molar conductivity, powder XRD, density functional theory (DFT), molecular docking, and bacteriological activity assays. Based on the physicochemical measurements and infrared spectral data, the ligand behaves as a neutral bidentate chelator, coordinating through the azomethine nitrogen and the amide oxygen. The combined evidence indicates the formation of hexa- and tetracoordinate complexes, consistent with octahedral, squareplanar, or tetrahedral geometries.The research aims to prepare new ibuprofen-derived hydrazone complexes with potential applications in multiple fields. In pharmacological contexts, the prepared complexes may exhibit antimicrobial activity, as such compounds can interact with essential enzymes or disrupt bacterial cell walls. They may also show anti-inflammatory effects if part of the parent drug’s activity is retained, potentially with improved efficacy or reduced side effects. In addition, hydrazone complexes containing metals such as cobalt(II) and copper(II) have been reported in multiple studies to interact with DNA or inhibit enzymes linked to cancer cell proliferation. Some complexes may also act as electron donors, enabling free radical scavenging and reducing oxidative stress associated with several diseases. In coordination chemistry and analytical applications, these complexes can serve as models for understanding drug-metal interactions in vivo, supporting the design of new metallodrugs or improved drug absorption. Some complexes also exhibit fluorescence or visible spectral changes upon binding to specific molecules, enabling their use as sensors for ions or biomolecules. In organic chemistry, certain nickel- or copper-containing complexes can act as catalysts in oxidation and addition reactions.

One promising approach for developing multifunctional hybrid nanocomposite films is the incorporation of hybrid nanoparticles into conductive polymer blends. In this work, a 50:50 polypyrrole/polyethylene oxide (PPy/PEO) blend doped with graphene oxide (GO) and silver nitrate (AgNO3) nanoparticles at different concentrations (3–12 wt%) was examined to explore structural and morphological changes in the film matrix. The effects of nanoparticle incorporation on crystallinity, phase compatibility, and surface behavior were investigated: structural properties by XRD, chemical properties by FTIR, and morphology and surface features by FESEM and AFM examinations. At 12 wt% loading, GO’s oxygenated groups anchor AgNO3 nanoparticles, enabling uniform dispersion and interfacial bridging between PPy’s rigid domains and PEO’s flexible matrix. XRD revealed a reduction in PEO crystallinity (up to 40% at 12 wt%), attributed to GO’s disruption of molecular ordering. FESEM images confirmed phase-separated morphologies, with GO sheets forming wrinkled networks in PEO-rich regions and Ag nanoparticles aggregating in PPy domains. AFM surface roughness trends (RMS: 4.22 nm at 3 wt% to 1.61 nm at 12 wt%) highlight nanoparticle-induced smoothing at higher concentrations.

Photonuclear reactions were studied for the samarium isotopes 144Sm, 148Sm, 150Sm, 152Sm, and 154Sm over an energy range of 8–22 MeV using the EMPIRE 3.2.2 nuclear reaction code. Total photoabsorption cross sections, particularly the Giant Dipole Resonance (GDR), were analyzed by considering contributions from both compound-nucleus and pre-equilibrium mechanisms. The Hauser–Feshbach model was employed to describe the compound-nucleus contribution, while the exciton model was used for the pre-equilibrium process. The results showed that the compound-nucleus mechanism is dominant across the studied energy range, although pre-equilibrium effects become more noticeable at higher energies. Furthermore, the influence of various gamma-ray strength function models, including MLO and EGLO, was evaluated. It was observed that different MLO variants yield consistent results, whereas the EGLO model fails to reproduce the double-peaked GDR structure characteristic of deformed samarium isotopes. These findings contribute to a better understanding of photonuclear reaction mechanisms and the applicability of gamma-ray strength function models in nuclear structure studies.

V2O5/PANI nanocomposites were created using a hydrothermal method at 180 °C and 200 °C and then coated on p-type silicon substrates for photodetectors. The 180 °C sample showed better crystallinity with smaller crystals, more evenly distributed nanoparticles, and a more uniform surface than the 200 °C sample. FESEM and atomic force microscopy (AFM) analyses indicated enhanced surface homogeneity, distinct nanostructures, and improved charge-separation efficiency in the 180 °C sample. Raman spectra suggested better structural organization, while PL measurements revealed increased light-emission efficiency. The photodetectors were active in the 500–680 nm range, optimizing photodetection performance. The sample fabricated at 180 °C exhibited improved results compared to the one at 200 °C, with a photoresponse of 0.14 A/W, a detectivity of 1.58 × 1020 Jones, and an external quantum efficiency (EQE) of 55.41%. It also had a faster rise time and a steadier photoresponse, highlighting the importance of synthesis temperature in improving the structure and function of V2O5/PANI nanocomposite photodetectors.

In this work, copper-doped zinc ferrite CuxZn1−xFe2O4 thin films with x ranging from 0 to 0.09 were synthesized by electric-field-enhanced spray pyrolysis, a novel and successful technique for depositing this cubic-structured material system. The films’ structural, morphological, and optoelectronic properties were characterized in detail by X-ray diffraction (XRD), photoluminescence (PL) spectroscopy, field-emission scanning electron microscopy (FE-SEM) imaging, and current–voltage (I-V) measurements to assess their overall suitability as visible-light photodetectors. XRD analyses confirmed a polycrystalline cubic spinel structure. Blue-to-near-infrared emission peaks were observed in PL spectra, and shifts associated with variations in crystallite size and defect states were considered. I-V measurements confirmed improved photoconductivity under illumination, with the best performance at x = 0.05, showing the highest photosensitivity (50.6%) and responsivity (3.39×10−4 A/W). Although high doping caused agglomeration and cracking, FE-SEM images showed improved particle uniformity at lower copper concentrations. The films were better suited for detecting blue light, showing theirhighest sensitivity at 420 nm. By optimizing composition to improve performance, these results highlight the potential of Cu-doped zinc ferrite thin films for optoelectronic devices, particularly photodetection. This work also describes how copper doping enhances the structural and functional characteristics of spinel ferrites for advanced technological applications.

Date seeds are a viable biomass resource for pyrolysis due to their organic content; however, using them directly without pretreatment may lead to poor yields and product quality, especially in uncontrolled and uncatalyzed environments. Therefore, this research aims, for the first time, to use the cetyltrimethylammonium bromide surfactant (CTAB) as a novel treatment for date seeds and to investigate its effects on yield, characteristics, and the composition of the resulting pyrolysis products. The feedstock was pretreated with CTABat different concentrations (1–2%) to modify surface properties and enhance biomass porosity for improved mass and heat transfer, as well as reaction efficiency. Pyrolysis experiments were carried out at moderate temperatures (300-400 °C) with different feedstock particle sizes under a nitrogen atmosphere. A bio-oil yield higher than 50 wt.% was obtained at pyrolysis temperatures higher than 350 °C. In contrast, higher biochar yields of more than 30 wt.% were obtained at the lower temperature (300 °C) and decreased as the temperature increased. Results also indicated that CTAB pretreatment, along with varying date seed particle sizes, had considerable effects on product yield and quality, with mitigation of secondary undesirable reactions. The products demonstrated notable characteristic features. This research presents an innovative solution for managing agricultural residues by converting them into energy and other useful resources, addressing both waste management and renewable energy strategies. The finding that date seed residues can serve as a resource for biofuel production and activated carbon manufacture aligns with circular economy concepts.

Zones in the vicinity of the Fermi hole were studied for the 1????22????2 state over the atomic-number range 4 ≤ ???? ≤ 12. Calculations were performed using the Hartree–Fock method. The results showed that the hole becomes narrower and deeper as the atomic number increases. The shift in the Fermi hole for neighboring elements in the series shows a significant shrinkage due to increasing nuclear charge. The investigation also revealed the existence of a second hole, and the results show that a shift occurs in this second hole as well. Similarly, the second hole decreased in size as the nuclear charge increased. Across the series, the shifts in both holes were reduced. In addition, the electron–electron repulsion energy was reported for each shell.

Ensuring security for vehicle access control in vital institutions, factories, and residential complexes has become a pressing concern. To address this, leading global logistics companies have focused on enhancing security infrastructure through vehicle license plate recognition systems. This research employs two algorithms: Region-based Convolutional Neural Network (RCNN) and Convolutional Neural Network (CNN). Both deep learning models are essential and are widely applied for vehicle detection and license plate recognition in image processing tasks. The system integrates an Arduino microcontroller, an ultrasonic sensor, and a computer-connected camera to capture images of vehicles at checkpoints. These images are then compared with a database of authorized vehicles. Arduino provides an efficient and adaptable platform for object detection and classification across different domains, including robotics, surveillance, and automation, enabling the development of more advanced systems in the future. The system achieved an accuracy rate of over 98%, demonstrating its reliability and effectiveness. This study makes a significant contribution by providing a robust security strategy.

Optimizing CPU task scheduling is crucial for increasing system performance, particularly in multi-core environments. Traditional algorithms, such as first-come, firstserved (FCFS), shortest-job-first (SJF), and Round Robin (RR), have become inefficient and fail to efficiently reduce waiting times or adapt to changes in the system. To address these issues, we introduce the Adaptive Mountain Gazelle Optimizer (AMGO), a modified version of the Mountain Gazelle Optimizer. It has the ability to dynamically balance exploration and exploitation, assigning tasks according to expected processing times, priorities, and deadlines. Its performance was compared with metaheuristic algorithms such as PSO, GWO, and MGO, as well as traditional algorithms. The results showed that the IMGO reduced waiting time by 30.6%, improved makespan completion time by 9.9%, and reduced total cost by 23.1% when examined on 150 tasks distributed across four cores over 100 iterations. These results demonstrate how IMGO improves real-time task scheduling performance. It has become a contemporary alternative to traditional methods in advanced computing systems for its ability to achieve a balance between exploration and exploitation.

Phishing attacks have been among the latest cybersecurity threats as they exploit people’s weaknesses and compromise critical information. Traditional methodologies of phishing detection practices based on machine learning have generally been unsuccessful in offering high performance due to limited generalizability and very high false positive rates. In this paper, a novel hybrid deep learning model is proposed that incorporates Bidirectional Encoding Representation from Transformers (BERT) with Bidirectional Long Short-TermMemory (BLSTM) to increase the detection of suspicious emails within the framework of the proposed model. The model utilizes the contextual understanding of texts from BERT and sequential learning from BLSTM to enhance classification accuracy. Experimental results using an available phishing email dataset show that the proposed approach significantly outperforms the baseline models in F1-score, recall, and precision metrics. Those results highlight the advantages of combining transformerbased embedding and recurrent architectures in phishing detection, providing avenues towards a more robust framework for email security enhancement.

The vast growth in email communications has resulted in an overwhelming increase in unsolicited email, making it challenging to filter properly. This study proposes a novel spam detection approach called SCDNN, which adapts spectral clustering and deep neural networks for precise spam identification. The aim of the study is to engineer an enhanced filtering model capable of delivering precise spam detection while minimizing false alarms and strengthening the system’s adaptability against evolving deceptive techniques. Firstly, SCDNN partitions the corpus according to neighborhoods centered around clustering centroids. Next, deep neural networks estimate spam by gauging distances between test and training data points using likelihood metrics. Experiments on several email datasets, such as the expansive Enron collection, Spam Assassin corpus, and UCI Mail Spam benchmark, indicate that SCDNN outperforms traditional techniques like backpropagation neural networks, support vector machines, random forests, and Bayesian logic with respect to precision, recall, mean accuracy, and F1 score. For instance, SCDNN achieved 96.3% accuracy on the Enron Email Corpus versus 94.7% for convolutional neural networks, and 91.6% accuracy on Spam Assassin compared to 93.0% for long short-term memory networks. The findings suggest that SCDNN exhibits superior generalization against ever-shifting spam tactics across diverse evaluation sets. It is this scalable methodology that enables large-scale filtering analysis and holds great promise for widespread application. SCDNN can mitigate the spam load, enhance user efficiency, and lower the risks associated with spam, including phishing and malware.

In shortwave self-organizing networks, periodic messaging can consume significant channel resources, increase network control overhead, and waste limited bandwidth, leading to a sharp decline in network communication performance. In order to solve these problems, an Enhanced Optimized Link State Routing (E-OLSR) protocol for a shortwave ad hoc network with low delay is put forward in this paper. The E-OLSR protocol combines an adaptive control message scheduling and a load-aware routing method by modifying the OLSR to enhance the process of route discovery and the MultiPoint Relay (MPR) selection algorithm. The protocol minimizes unnecessary overhead by adapting control message intervals to network conditions and by prioritizing critical updates messages. Meanwhile, load-aware routing is used for traffic balancing, congestion avoidance, and delay reduction. The proposed E-OLSR was experimented extensively on various network sizes ranging from 10 to 50 nodes. Simulation results demonstrate that the E-OLSR yields substantial improvements in terms of control overhead, packet delivery success rate, end-to-end delay, and throughput. Specifically, E-OLSR reduces control overhead by approximately 15% compared to II-OLSR and 25% compared to OLSR in a network with 50 nodes. Also, it achieves an 8-15% higher packet delivery success rate, decreases end-to-end delay by 30-40%, and improves throughput by 20-30% across varying network sizes. These results highlight the efficiency and reliability of E-OLSR in addressing the challenges of low-latency shortwave networks.

As steganographic techniques advance and object data are increasingly generated in various domains, detecting concealed data embedded in digital media has become more challenging; thus, image steganalysis plays an important role. Conventional detection techniques are becoming less effective against these evolving strategies, which calls for better solutions. In this paper, we present RGV-Stega, a new high-level structure that combines Reinforcement Learning (RL), Generative Adversarial Networks (GANs), and Vision Transformers (ViTs) to further enhance the detection of steganographic contents in images. Artificial intelligence techniques such as RL, GANs, and ViTs play significant roles in current steganalysis work: RL helps an agent learn optimal feature extraction strategies, GANs yield rich steganographic samples for strong training, and ViTs help capture long-range dependencies in image data, thereby boosting top-1 accuracy. On benchmark datasets such as BOSSBase and BOWS, our method RGV-Stega achieves up to 93% accuracy, comparable to conventional CNN- and ViT-based models. Findings show that combining RL, GANs, and ViTs is an effective approach to addressing issues arising from advances in steganographic techniques. This improves steganalysis’s ability to identify hidden content.

The present study is an investigation of the effects of non-locality and dual-phase-lags in a thermoelastic half-space subjected to thermomechanical loading. A homogeneous isotropic nonlocal thermoelastic diffusive half space with dual phase lag is explored.The governing equations are solved with the help of harmonic vibration analysis in collaboration with Fourier transform techniques. The distributed sources are considered to demonstrate practical relevance. Further, they are categorized as uniformly distributed sources and linearly distributed sources for mechanical, thermal, and chemical potential excitations. Numerical simulations are performed using software MATLAB (R2016a) to evaluate displacements, stresses, temperature variations, and chemical potential, where the results are presented graphically for proper clarity. Moreover, the particular limiting cases are also examined to validate the model and highlight key behaviors. The study is applicable in order to predict thermal and mechanical responses in electronics, MEMS/NEMS devices, aerospace components, and energy systems subjected to timeharmonic loads.

This study aimed to analyze the problems faced by international students in the science and engineering departments at Karabük University, Turkey, with a focus on academic and social issues. A semi structured interview model was used as the primary tool within a field survey research design. The participants included 152 international students, and their academic and social challenges were analyzed using questionnaires that examined several variables, such as the relationship between gender and mathematics grades and the effect of Turkish language proficiency on course evaluation. Statistical analyses were conducted in SPSS, including the chi-square test and Cramer’s V correlation coefficient, to assess the presence and strength of relationships among variables. The results indicated that the relationships between gender and mathematics grades, employment status and perceived exam difficulty, Turkish language proficiency and language course evaluation, and scholarships and the choice of Karabük University were weak to moderate, suggesting no strong association among these variables. Therefore, the findings suggest that these variables do not have a significant impact on the academic and social issues international students experience.

Water quality is a crucial factor affecting human health in arid and semi-arid regions. The Al-Habbaniyah area includes two important sources of surface water: Lake Habbaniyah and the Euphrates River. To assess water quality, surface-water samples were collected and analyzed. Relative precision and deviation (E%, T%) were adopted for interpretation. Physical properties that significantly influence water quality, including color, odor, taste, temperature, pH, total dissolved solids, and electrical conductivity, were analyzed. Most water samples (R1, R2, R3, L1, L2, L3, Ch1, Ch2) were grouped into three categories according to the USDA irrigation water-quality assessment diagrams. The results demonstrated that most natural water sources contain cations and anions in chemical equilibrium. The study concludes that surface water is suitable for irrigation and drinking, provided that drinking water is treated to remove naturally occurring iron and manganese ions. Irrigation water requires management to control sodium and salinity risks. Integrated management of surface water for drinking and irrigation purposes is recommended to address water problems. Additionally, the Piper diagram indicated that all samples belong to Class I, Category V.

Scientific evidence suggests that intelligence is shaped by various biological factors and is among the most prominent cognitive abilities influencing academic performance. This study aimed to investigate neurochemical influences on intelligence among school-aged students. A total of 90 male students from three types of schools (public, distinguished, and high-achieving) participated. The Standard Progressive Matrices (SPM) test was used to assess mental age and IQ before any intervention, while both SPM and Advanced Progressive Matrices (APM) were administered before and after a 15-day nutritional intervention involving walnuts and dark chocolate. Dopamine and beta-endorphin levels were also measured to assess physiological influences. Before the intervention, significant differences were observed among the three groups in both mental age and IQ. Post-intervention results showed a notable improvement in the public school group, particularly in APM scores. The distinguished group improved mainly in the SPM test, while the high-achievers group showed no significant changes. Dopamine levels differed significantly among the groups, with higher levels in distinguished and high-achieving students than in public school students. In contrast, beta-endorphin levels did not differ significantly. Overall, the findings indicate that biological factors, particularly dopamine, may contribute to differences in cognitive performance among student groups. Moreover, the nutritional intervention appeared to improve performance among students with initially lower cognitive scores, especially in public schools.