Background: Gastric cancer is a global health issue, and efforts are being made to discover new compounds that can be used to treat or prevent this disease. Clove (Syzygium aromaticum) contains eugenol and other bioactive compounds that have antioxidant and anticancer effects. The use of nanoemulsion technology can help to improve the solubility, stability, and bioavailability of these natural compounds, which in turn may enhance their therapeutic ability. Objective: This study aimed to compare the chemical composition and anticancer activity of clove oil nanoemulsions and alcoholic clove extract against human gastric cancer cells. Methods: Both clove oil nanoemulsion and alcoholic extract were prepared using standardized methods, with 50% ethanol employed for the extraction of active compounds. The samples were characterized by dynamic light scattering (DLS) for particle size analysis and Fourier-transform infrared spectroscopy (FTIR) for identification of functional groups and structural features. Their anticancer activity was evaluated using the MTT assay on a gastric cancer cell line by testing multiple concentrations and assessing effects on cell viability. Results: FTIR analysis revealed the presence of key functional groups in both the nanoemulsion and the alcoholic extract, such as phenolic hydroxyl groups (O–H) and aromatic bonds (C=C), confirming the presence of eugenol as the main active ingredient in both preparations. However, the nanoemulsion exhibited higher spectral intensity and a better distribution of nonpolar compounds, indicating improved solubility and stability of the active compounds. Both samples demonstrated antioxidant activity and the ability to inhibit the growth of gastric cancer cells. The nanoemulsion was found to have significantly higher potency compared to the alcoholic extract, with an IC50 value of 36.30±1.47 μg/mL compared to 41.67±1.53 μg/mL for the extract. Conclusions: This difference is attributable to enhanced solubility, stability and cellular uptake of the active compounds in the nanoemulsion. The results suggest that clove oil nanoemulsions exhibit superior antioxidant properties and anticancer activity compared to conventional alcoholic extracts indicating that nanotechnology and traditional methods together present a unique opportunity for improving bioactivity and bioavailability of natural anticancer agents, which could lead to the development of effective therapies as treatment options for gastric cancer.
Background: The pathogen “Pseudomonas aeruginosa (P. aeruginosa)” is extremely hazardous for people with weak immune systems because it has several virulence factors and can resist antibiotics. Objective: To isolate and molecularly identify P. aeruginosa from burn and wound infections and to evaluate its antimicrobial resistance patterns, ESBL production, and virulence characteristics. Methods: A total of 150 burn and wound samples were collected from patients at Erbil West Emergency Hospital and processed immediately. P. aeruginosa was isolated using selective media and confirmed molecularly by PCR targeting rpoB and oprL genes. Virulence genes (nan1, plcH, exoT, toxA, aprA) were detected by PCR. Antimicrobial susceptibility testing was performed against 14 antibiotics using the disk diffusion method. ESBL production was detected using the Double Disc Synergy Test (DDST). Hemolytic and proteolytic activities were evaluated using blood agar and skim milk agar, respectively, while pigment production was assessed on cetrimide agar. Results: Out of 150 samples, 40 P. aeruginosa isolates were identified. Imipenem showed the highest efficacy, while complete resistance was observed against AMP, CTX, P, AMC, and C. Resistance rates were ATM (32.5%), MEM (42.5%), TOB, AK, and CN (45%), CIP (62.5%), CAZ (67.5%), and TE (80%). ESBL production was detected in 26 isolates (65%). β-hemolysis was observed in 25 isolates (62.5%), and strong proteolytic activity was detected in 35 isolates (87.5%). Typical pigment production was observed on cetrimide agar. Conclusions: The study reveals a high prevalence of MDR and ESBL-producing P. aeruginosa with considerable virulence potential in burns and wounds. Imipenem still holds its position as the most promising therapeutic agent; this emphasizes the need for continuous surveillance and proper antibiotic use.
Background: Transformer-based foundation models have achieved state-of-the-art results in various natural language inference benchmarks, but their decision-making processes remain largely unexplainable. Addressing the ’explainability gap’ is crucial for responsible AI adoption in highrisk industries that require transparency and trustworthiness. Furthermore, the combination of neural pattern matching with structured symbolic reasoning in resource-constrained scenarios is an important open problem. Objective: This study aims to present a memory-optimized probabilistic neuro-symbolic hybrid architecture that unifies transformer-based neural networks with logic-based symbolic reasoning systems. Methods: We use the e-SNLI dataset that provides human-written natural language explanations and reasoning highlights as training targets, and finetune the BERT transformer-based language model with an emphasis on gradient checkpointing, mixed-precision (FP16) training, and layer freezing for optimal resource utilization/reasoning tradeoffs. All experiments were performed on an NVIDIA GPU with 8–12 GB VRAM and CUDA-compatible hardware. Results: The proposed framework achieves 80.6% accuracy on 3-way NLI classification (contradiction, entailment, and neutral) with 0.806 precision, recall, and F1 scores on each class, and detailed class-level analysis shows high performance on entailment recognition (F1 = 0.912) and contradiction detection (F1 = 0.902), but slightly lower performance on neutral cases (F1 = 0.864). Ablation studies and confidence distributions of the model predictions indicate that memory-optimized models can maintain competitive performance and be deployed on resource-constrained devices, reducing GPU memory usage by ~60%. Conclusions: The results indicate that neuro-symbolic systems within memory-constrained systems can achieve both explanation needs and foundation models’ performance requirements, representing an important step in creating more trustworthy AI for NLP.
Background: Burn and wound infections represent a significant public health burden in Iraq, contributing to high rates of morbidity and mortality. Decades of armed conflict, economic instability and deteriorating healthcare infrastructure have severely compromised the capacity of Iraqi hospitals to prevent and manage these infections effectively. Objective: This comprehensive review consolidates scientific literature to evaluate the epidemiology, antimicrobial resistance patterns, pathogenic mechanisms and clinical outcomes associated with bacterial wound and burn infections across Iraqi hospitals and healthcare systems. Methods: A systematic search identified studies on bacterial isolates from wound and burn infections across Iraqi hospitals, with data drawn primarily from Sulaymaniyah, Baghdad and Misan provinces as geographically and demographically representative samples rather than a comprehensive national survey. Results: Pseudomonas aeruginosa, Staphylococcus aureus and Acinetobacter baumannii collectively account for the majority of wound and burn infections. Multidrug-resistant (MDR) pathogens are highly prevalent, including MRSA rates approaching 87%, ESBL-producing Enterobacteriaceae and carbapenem-resistant Gram-negative organisms. Nosocomial transmission is the predominant route of spread, driven by overcrowding, poor infection control and contaminated environments. Burn patient mortality ranges from 13–28%, with sepsis responsible for 44–65% of burn-related deaths. Virulence factors, biofilm formation and bacterial adaptation to wound environments contribute to treatment failure and infection persistence. Conclusions: Urgent improvements are required in antibiotic stewardship, infection prevention, epidemiologic surveillance and evidence-based treatment protocols across Iraqi healthcare facilities. Inter-hospital collaboration and investment in regional microbiological diagnostic capacity are essential to addressing this growing public health crisis.
Background: Cancer remains a major global health burden that significantly affects human populations. The ongoing need for innovative therapeutic strategies to both manage and prevent this life-threatening disease is paramount. The quest for creative and less toxic cancer therapies has led to a vast exploration of plant-derived compounds. Objective: This study investigated the anticancer potential of phytochemicals extracted from Antiaris africana (A. africana), a traditional medicinal plant used in ethnomedicine in West Africa, through molecular docking studies. Methods: The stem bark extract, prepared via maceration with methanol, was analyzed by gas chromatography mass spectrometry (GC-MS), revealing 36 bioactive compounds. In silico evaluations, including molecular docking, ADME prediction, and toxicity assessments, were carried out to identify inhibitory effects on cyclin-dependent kinases 8 (CDK8) and 13 (CDK13), key regulators of cancer progression. Results: GC-MS analysis of the methanolic extract of A. africana revealed 36 phytochemicals with possible anticancer potential. Notable phytochemicals, such as bis(2-ethylhexyl) phthalate and campesterol, exhibited significant binding affinities to CDK8 and CDK13, with high Glide scores and favorable pharmacokinetic profiles, adhering to Lipinski’s five rule. ADME analyzes highlighted the druglikness and minimal toxicity of the compound, supporting its potential as an orally bioavailable therapeutic. In silico studies revealed bis(2-ethylhexyl) phthalate, 2,6,10,15,19,23-hexamethyl-tetracosa-2,10,14,18,22-pentaene-6,7-diol and 3-12-formyl-digoxigenin as lead compounds, which offered promising insights into the anticancer potential of the compounds. Conclusions: This study underscores A. africana as a promising source of lead compounds for targeted cancer therapies. Further in vitro and in vivo studies are recommended to validate these findings and explore the therapeutic landscape of these bioactive molecules.
Background: Iraq experienced a severe dust event that occurred in mid-May 2022, disrupting daily life with adverse health impacts. Objective: This study aims to investigate the triggering weather systems, and examine the variations in meteorological factors during the event with a specific focus on Basrah station in southern Iraq. Methods: Ground-based meteorological observations and satellite imagery. In addition to the atmospheric composition forecast data from the copernicus atmosphere monitoring service (CAMS), including meteorological and optical properties for different levels. Applying statistical evaluations for CAMS data against observed data, including correlation coefficients, coefficient of determination, and error metrics (MBE and MAE). Results: The dust event was driven by a deep upper air cut-off low over the eastern Mediterranean region, coinciding with a southern intrusion of the polar jet stream. This situation led to baroclinic instability and the developing frontal cyclonic system over southern Turkey, Syria, Jordan, western Iraq to northern Saudi Arabia. Satellite images showed dense dust clouds swept and transported towards the east and southeast due to the front passage, which is simulated well in the CAMS model with a value exceeding 2.5 of optical depth. In Basrah station, the dust event led to a notable reduction in visibility, lower temperature by 4° C, and surface solar radiation of 15%. Wind speed, extinction coefficient, and humidity levels increase by about 2.2, 2, and 1.4 times respectively. 12% reduction in boundary layer height during daytime hours of a dust event, and an 8% increment during nighttime. The statistical assessment shows a strong correlation for temperature and humidity, moderate for wind speed, and weak for wind direction. The model overestimates temperature and wind direction, while underestimating humidity and wind speed. Errors are low for most variables but notably higher for wind direction. Conclusions: The May 2022 dust event was driven by a deep frontal cyclone, reaching central and southern Iraq, in which Basrah station witnessed reduced visibility, lower temperature and solar radiation, and increased wind speed, humidity, and extinction coefficient. Boundary layer height decreased during the day and rose at night, highlighting the atmospheric instability during the event.
Background: Youth unemployment presents a significant threat to Nigeria’s socioeconomic stability, resulting in widespread issues such as poverty, insecurity, banditry, inequality, and robbery. Objective: In this paper, mathematical modelling for the control of unemployment in Nigeria incorporating vocational education and apprenticeship was formulated. The model equilibrium points were obtained and the local stability analysis was carried out. Methods: The basic reproduction number Re was computed using the Next Generation Matrix technique and used to determine whether unemployment will persist or be eradicated in Nigeria. Sensitivity analysis was carried out to determine the most sensitive parameters. Results: Numerical simulations were presented in a graphical form to show the effects of sensitive parameters on the reproduction number. The stability analysis shows that unemployment will be eradicated in Nigeria if Re ≤ 1. It was revealed from the sensitivity analysis that the theoretical education graduate employment rate, γ is the most sensitive parameter with −0.9883 and the rate of transition of becoming highly skilled due to vocational education, β is the least sensitive parameter with −0.0409. Conclusions: It was shown from the sensitivity analysis and the graphical presentation that the theoretical education graduate employment rate, γ is the most sensitive negative parameter which will decrease the reproduction number. This implies that when employment is created for the graduates from the higher institutions the unemployment rate will reduce drastically from the society. It is recommended that the government and the private sector owners should create more job for the graduates. Optimal control analysis is recommended for future research to determine the minimal cost for the increase graduate employment rate and motivation of vocational education.
Background: Bacterial infections, particularly those in medical devices such as urinary catheters, are a significant clinical challenge due to structural differences between Gram-positive and Gram-negative bacteria influencing their susceptibility to antimicrobial agents. As antibiotic resistance increases, core/shell nanoparticles are being explored as potential alternatives. Objective: This study investigates the antibiofilm properties of MgO/ZnO and CuO/ZnO nanoparticles at concentrations of 10 and 40 µg/mL, respectively, against common bacterial pathogens, specifically Klebsiella pneumoniae, Escherichia coli, and Staphylococcus aureus, and their potential to sterilize urinary catheters. Methods: A 96-well microtiter plate was used to determine sublethal dosage levels (Sub-MIC) and minimum inhibitory concentrations (MIC) to evaluate antibacterial activity. Antibiofilm performance was evaluated by measuring biofilm reduction, while antiadhesion assays were conducted on urinary catheters to determine the ability of nanoparticles to prevent E. coli attachment. Results: The nanoparticles exhibited strain-dependent antibacterial effects. S. aureus and showed high sensitivity to CuO/ZnO NPs, while E. coli and K. pneumoniae were less susceptible. Notably, Gram-negative pneumococci demonstrated resistance to MgO/ZnO and CuO/ZnO nanoparticles. In terms of biofilm inhibition, MgO/ZnO NPs were slightly more effective against S. aureus and E. coli, whereas CuO/ZnO NPs showed superior activity against K. pneumoniae. Biofilm formation was reduced by up to 56.32% at sub-MIC concentrations. In catheter adhesion assays, MgO/ZnO NPs inhibited E. coli adhesion by 64.59%, compared to 60.92% for CuO/ZnO NPs. This development refers to the effective adhesion of CuO/ZnO NPs to the catheter surface. The study also presented an efficient, feasible and simple procedure of coatings of MgO/ZnO and CuO/ZnO NPs to prevent biofilm adhesion to catheter surfaces. Conclusions: MgO/ZnO and CuO/ZnO nanoparticles demonstrated potent anti-biofilm activity, inhibiting bacterial growth, biofilm formation, and catheter adhesion. However, more research is needed on cytotoxicity, biocompatibility, and long-term effects.
Background: This study investigates the existence and uniqueness of solutions for a class of nonlinear fractional differential systems governed by Caputo derivatives. Such systems are effective in modeling dynamic processes with hereditary behaviors and anomalous responses, which are commonly observed in socio-economic, biological, and engineering contexts. Traditional integer-order differential models fail to capture these features, motivating the use of fractional-order formulations. Objective: The primary goal is to establish rigorous mathematical conditions ensuring the well-posedness of nonlinear fractional systems involving coupled variables. By proving existence and uniqueness, the study provides a solid theoretical foundation for analysis, simulation, and application of fractional-order models to complex systems with hereditary dynamics. Methods: The fractional differential system is transformed into an equivalent integral formulation using Riemann–Liouville fractional integral operators. Within a Banach space, two operators are defined: one is continuous and compact, while the other is contractive. The existence of solutions is established via Krasnoselskii’s fixed point theorem, and the boundedness and Lipschitz continuity of the nonlinear terms ensure uniqueness through Banach’s contraction principle. The system admits a unique solution confined to a closed, invariant subset of the function space, providing a rigorous framework for analytical and numerical investigations. Results: Analytical results confirm that the proposed fractional-order system satisfies conditions for existence and uniqueness of solutions. The integral representation demonstrates the well-posedness of the model and validates its ability to capture hereditary dynamics accurately. Operator-based analysis ensures stability and supports convergence of numerical methods, making the model practically applicable for simulations of socio-economic and biological processes. Conclusions: This work establishes a rigorous theoretical foundation for nonlinear fractional differential systems with Caputo derivatives. By addressing existence, uniqueness, and stability, it provides a reliable framework for modeling systems where past states influence current behavior. The findings facilitate both analytical and numerical studies of fractional-order dynamics, expanding the applicability of fractional calculus in diverse fields, including economics, population dynamics, control theory, and material science.
Background: Titanium dioxide nanoparticles (TiO2 NPs) have widespread use in industrial and biological fields owing to their distinctive physicochemical characteristics. Nonetheless, their growing prevalence raises concerns over their possible toxicological impacts, especially on the functionality of essential organs. Objective: The present work examines the subacute toxicity of TiO2 nanoparticles on hepatic and renal function and modifications in the lipid profile in a mouse model. Methods: Forty-eight adult female albino mice were divided randomly into three groups (n=16 each). Two groups were treated intraperitoneally with TiO2 NPs at 100 mg/kg and 400 mg/kg, respectively, while the control group was treated with distilled water. The animals were sacrificed after 7 and 21 days of treatment. Serum levels of urea, creatinine, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and lipid profile parameters (cholesterol, HDL, LDL) were estimated. Results: Both treated groups showed significant rises in urea, creatinine, AST, and ALT levels (p<0.0001) compared to the control. These were more pronounced at higher concentrations and longer exposure durations. Cholesterol level fell after 21 days, with significant drops in HDL and rises in LDL (p<0.0001). Conclusions: TiO2 NPs induce dose- and time-related alteration of liver and kidney function, and lipid metabolism in mice. These findings highlight that further toxicological research on nanoparticle exposure in environmental and biomedical applications is needed.
Background: The regular use of connected devices on the internet by users of social media generates a large quantity of multimedia data every second, and the data concerned may be of a variable nature, such as text data, color images, video, and audio. We can confirm that online security is becoming an area that is increasingly being explored by researchers around the world to guarantee and ensure the authenticity and confidentiality of exchanged data. Objective: The goal of this article is to introduce a new dynamic cryptosystem for encrypting color images, using elliptic curves and chaotic functions. Methods: This new system serves to generate the coefficients of the curve, create the encryption keys, and create the prime number of the curve. The new system utilizes the length of the encryption keys, which encompasses all points on the curve and relates to the discrete logarithm problem of elliptic curves, thereby justifying the difficulty in uncovering hidden information. Results: The results were obtained with the assistance of several analyses, including histogram analysis, correlation coefficient analysis, differential attack analysis, and key space analysis. The results obtained confirm the robustness and reliability of the proposed cryptographic system. Conclusions: By combining the two systems (elliptic curves and chaotic functions), we obtain a new hybrid system capable of operating with reduced encryption key lengths and random values, which makes our new system sensitive to initial conditions.
Background: Phishing is a common cybercrime attack, and it is also considered a social crime that has been going on for more than two decades. Phishing aims to trick users into revealing their private information, including banking information, passwords, and account credentials. Phishing remains a real threat and usually occurs via instant messages, email, or phone calls. Objective: Used shape analysis on the system to uncover the most important features that contribute to phishing detection. A set of key features was identified. Many phishing detection methods have been used recently, but they do not provide a complete understanding of the impact of different features on predictions. Methods: Several machine learning strategies based on SHAP (Shappley Additive Explanations) were applied, which enhanced the classification model. This paper proposes a fast model based on a set of contemporary machine learning techniques. Results: Experiments showed that the proposed model achieved a maximum accuracy of 99.1% for K-NN and 98.5% for XGBoost on the Phishing_Legitimate_full dataset. K-NN has demonstrated superior performance and interpretability, which is critical for security-critical applications. Conclusions: The results highlight the balance between predictive performance and interpretability. This provides valuable transparency into the decision-making process. This makes it a more practical choice for real-world phishing detection systems, where reliability and interpretability are critical.
Background: Alzheimer’s disease (AD) shows distinct differences between women and men in prevalence, disease progression, and therapeutic response. Women express a greater risk of AD onset, influenced by increased longevity and hormonal factors, and typically experience faster cognitive decline along with heightened susceptibility to AD-associated depression and anxiety. Current therapies—primarily cholinesterase inhibitors and memantine—offer only symptomatic relief without modifying disease progression. Objective: To review sex-specific differences in Alzheimer’s disease and evaluate the current understanding of therapeutic response variations between men and women, with an emphasis on identifying opportunities for sex-tailored interventions. Methods: A narrative review of the literature on AD prevalence, progression, and treatment outcomes across sexes was conducted. Particular attention was given to pharmacological therapies (cholinesterase inhibitors, memantine), lifestyle factors, and sex-specific risk determinants such as cardiovascular health and hormonal fluctuations. Results: Evidence suggests that women are more vulnerable to AD onset and progression compared to men. Limited studies indicate potential therapeutic advantages of specific medications for women, though robust, sex-stratified clinical trials remain lacking. Non-pharmacological strategies, including lifestyle adjustments in diet, exercise, and cognitive engagement, show promise in alleviating symptoms for both sexes. Conclusions: Sex differences significantly influence AD onset, clinical course, and therapeutic response. While current treatment remains largely non-disease-modifying, emerging sex-specific findings underscore the need for personalised medicine approaches. Further research is required to clarify sex specific mechanisms, optimise therapeutic strategies, and address disparities in care access, ultimately improving management of AD in both women and men.
Background: Finding an analytical solution to Volterra integro-differential equations (VIDEs), especially nonlinear types, often poses serious difficulties and is many times impossible, thus the need to provide a semi-analytical solution. Objective: This research focuses on the solutions of systems of linear and nonlinear fractional-order integro-differential equations with difference kernels. To achieve this, we exploited the advantage of integral transforms and one of the existing semi-analytical methods to develop the desired method of solution. Methods: One of the recently developed integral transforms, the Shehu transform, which generalizes Laplace and Sumudu transforms, is systematically integrated into the well-known Adomian Decomposition Method (ADM) to obtain a simplified approach to solving the class of problems considered. The Shehu transform is first applied to both sides of the given VIDEs with difference kernels, followed by the application of the convolution theorem. The ADM is then employed to handle the nonlinearities encountered. Results: The proposed method, the Modified Semi-analytical Method (MSM), is applied to selected problems in the literature and produces comparatively good results. The method also produces the exact solution whenever the solution is in closed form. The results are presented in tabular and 2D or 3D graphical forms for easy comparison. All computations are carried out using Mathematica 13.3, with the fractional-order derivative interpreted in the Caputo sense. Conclusions: Since MSM has been successfully used to solve linear and nonlinear VIDEs with difference kernels, the scope of the method can be expanded to cover Volterra-Fredholm integro-differential equations (VFIDEs) in future studies.
Background: FGFBP-3 plays a role in metabolic syndrome in mice by regulating fat and glucose metabolism. The FGFBP3 protein is secreted by adipose tissue and also functions in the central nervous system, similar to thyroid hormone. Thyroid dysfunction is the second most common endocrine disorder after diabetes mellitus (DM). Objective: This study evaluates FGFBP-3 levels in patients with hyperthyroidism, both with and without DM. Methods: The study included 90 participants divided into three groups: 30 patients with hyperthyroidism and DM, 30 patients with hyperthyroidism without DM, and 30 healthy individuals as controls. Thyroid hormones (TSH, total T3, and total T4) were measured using the Minividas device. FGFBP-3 levels were estimated by the enzyme-linked immunosorbent assay (ELISA) sandwich method. Additionally, lipid profile parameters (total cholesterol, triglycerides, HDL, LDL, and VLDL) were determined using enzymatic colorimetric methods. Results: The study found that TSH and HDL levels were significantly lower in both hyperthyroidism groups compared to controls. Conversely, FGFBP3, HbA1c, free T4, free T3, total cholesterol, triglycerides, LDL, and VLDL levels were significantly elevated in both hyperthyroidism groups relative to the healthy group. There were no significant differences in lipid profile levels between the hyperthyroidism with DM group and the hyperthyroidism without DM group. High serum FGFBP3 levels were observed in hyperthyroid patients regardless of DM status, whereas the control group exhibited lower FGFBP3 levels. Receiver operating characteristic (ROC) analysis indicated that FGFBP3 could serve as a biomarker for monitoring hyperthyroidism with and without DM. Conclusions: This study demonstrates a strong association between FGFBP3 levels and hyperthyroidism, irrespective of the presence of diabetes mellitus.
Background: CR-39 nuclear track detectors are widely used in various fields, including science, technology, astronomy, and environmental preservation, to detect and register heavy ions, neutrons, and alpha particles. Objective: This study aims to determine the optimal etching duration for CR-39 nuclear track detectors by comparing etching methods: The wet etching (using a water bath) and the dry etching technique (using dielectric barrier discharge (DBD) plasma). Methods: The traditional etching method involved immersing CR-39 detectors in a sodium hydroxide (NaOH) solution at 70 °C for varying durations. The dry etching method employed employs a non-thermal DBD plasma system to etch solid-state nuclear track detectors (SSNTDs) without the use of chemical solutions. Results: Photomicrographs revealed that tracks from chemical etching became clearly visible after 1 hour and developed at 5 hours. In contrast, the dry etching technique was significantly faster; tracks began to appear after just 1 minute of DBD plasma etching and were fully developed at 5 minutes. The optimum track density for DBD plasma was 20340±56 tracks/mm2 at 3 minutes, whereas the traditional water bath method achieved an optimum track density of 5238.0±5.7 tracks/mm2 at 2 hours. The shorter etching duration in the dry method likely facilitates the emergence of latent tracks without overlap. Conclusions: The bulk etch rate (VB) for CR-39 detectors using the dry DBD plasma etching technique was faster compared to the traditional chemical etching method. This demonstrates the efficacy of the dry etching process in significantly reducing etching time required for etching SSNDs.
Background: Anemia is a widespread global health issue affecting millions of individuals worldwide. Early and accurate diagnosis is essential for effective treatment. Traditional diagnostic approaches rely on complete blood count (CBC) parameters, which provide valuable clinical insights but may require advanced tools to enhance diagnostic accuracy. Objective: This study aims to develop and evaluate machine learning models for classifying different anemia subtypes using CBC data. The goal is to assess the performance of individual models and ensemble methods in improving diagnostic accuracy. Methods: Five machine learning algorithms were implemented for the classification task: Decision tree, random forest, XGBoost, gradient boosting, and neural networks. In addition to evaluating individual models, ensemble techniques-including hard voting, soft voting, and stacking-were applied to enhance model performance. Results: Experimental results demonstrated that ensemble methods significantly outperformed individual models in classification accuracy. Among them, the stacking ensemble achieved the highest accuracy of 98.44%, indicating superior performance in distinguishing anemia subtypes. Conclusions: This study demonstrates that ensemble learning methods, particularly stacking, can substantially improve the performance of machine learning models in anemia classification based on CBC data. These findings suggest the potential integration of such ensemble techniques into clinical decision-support systems to assist healthcare providers in making efficient and timely diagnoses.
Background: Chalcone derivatives are well-known for their versatile pharmacological properties, particularly their antimicrobial and antioxidant activities. Their simple chemical structure and ease of synthesis make them attractive candidates for drug discovery, especially in combating microbial resistance and oxidative stress-related disorders. Objective: The study aimed to synthesize and characterize a series of new chalcone derivatives and evaluate their antimicrobial and antioxidant activities, alongside molecular docking studies to assess their potential as therapeutic agents. Methods: Six new chalcone derivatives were synthesized via Claisen–Schmidt condensation of two methyl ketones (p-aminoacetophenone and cyclopropyl methyl ketone) with p-substitutedphenyl aldehydes under mild conditions. Structural elucidation was performed using FT-IR, 1H-NMR, 13C-NMR, and GC-MS spectroscopy. Antimicrobial activities were tested against five microbial strains: Staphylococcus aureus, Staphylococcus epidermidis, Escherichia coli, Klebsiella pneumoniae, and Candida albicans, using the agar well-diffusion method. Antioxidant activity was evaluated using the standard DPPH radical scavenging assay. Molecular docking studies were conducted using PyRx software to investigate the binding interactions of the synthesized chalcones with the active site of glucosamine-6-phosphate (GlcN-6-P) synthase, a target enzyme for antimicrobial agents. Results: The synthesized chalcone derivatives were successfully characterized and exhibited varying levels of antimicrobial activity against the tested strains, with some compounds demonstrating significant inhibitory effects. Antioxidant assays revealed promising radical scavenging capabilities for several synthesized chalcones. Docking studies showed favorable binding affinities between the identified compounds and the GlcN-6-P synthase active site, supporting the experimental bioactivity results. Conclusions: This study demonstrates that the newly synthesized chalcone derivatives possess both antimicrobial and antioxidant activities. Their effective interaction with GlcN-6-P synthase suggests potential for further development as lead compounds in antimicrobial drug research.
Background: There is great interest in developing plant-based nanoparticles due to their unique chemical and physical properties, which make them an excellent alternative to chemical drugs that fight bacteria and protect cells from damage. Objective: Green synthesis of silver nanoparticles using cinnamon, characterization and evaluation of them as antioxidants, and investigation of their effect on the HepG-2 cell line. Methods: The study involved the green synthesis of Ag NPs/cinnamon, its characterization using XRD, TEM, and GC-MS techniques, and the evaluation of its activity as DPPH antioxidants as well as activity against the HepG-2 cell line. Results: During analysis, it was found that the diameter of the nanoparticles ranged from approximately 19 to 100 nm. The results indicated that the crystal sizes ranged from 12.68 to 29.76 nm, with an average crystal size of 22.335 nm. Cinnamon contains 25 chemical compounds with high antioxidant activity, such as 3-phenyl-(cinnamaldehyde), coumarin, cis-calamine, trans-calamine, oleic acid, (Z)-9-octadecenoic acid, and octadecenoic-9-enoic acid. The nanoparticles inhibited 62% of free radicals, confirming that Ag NPs/cinnamon has good free radical scavenging activity at low concentrations and can function as antioxidants. The results showed that Ag NPs/cinnamon induced greater damage to HepG-2 hepatocytes than to HFF hepatocytes. At a concentration of 1 mg/ml, silver nanoparticles inhibited cytotoxicity and increased cell viability. Compared with the control group (HFF), the IC50 value was 48.41 mg/ml, and the toxicity was 105.1 mg/ml, respectively. Conclusions: Silver nanoparticles combined with cinnamon exhibited significant antioxidant properties, indicating their potential as promising free radical scavengers. Additionally, the synthesized Ag NPs/cinnamon exhibited notable activity against the HepG-2 cell line.
Background: El NIÑO phenomenon is a global climate phenomenon that occurs as a result of the interaction between the surface of the Pacific Ocean and the atmosphere directly above it. Objective: This study investigates whether El NIÑO 3.4 affects some of the climatic parameters in some Iraqi cities. Methods: A record surface data (2007-2017) of relative humidity, maximum and minimum air temperature was used from the Iraqi meteorological and seismology organization for seven selected meteorological stations, sea surface temperature anomalies from the royal Netherlands meteorological institute, and the reanalysis data of air temperature (1980-2022) from the national centers for environmental prediction and national center for atmospheric research. The climatic parameters data for seasonal and mean monthly are analyzed to understand the general trend, and the statistical relationships are investigated. Results: The result shows a decrease in relative humidity for Kirkuk and Nasiriya stations. Also, there is an increase in the general trend of the maximum and minimum temperatures for Kirkuk, Nasiriya, Basra, Baghdad, Al-Hay, and Mosul stations. The influence of the NIÑO 3.4 index on Iraq's climate, temperature, and relative humidity was minimal. The impact of the NIÑO 3.4 index on the maximum and minimum temperatures within the daily and monthly values, in general, was a weak positive correlation. The correlation between the NIÑO 3.4 index and the maximum and minimum temperatures during the spring and winter seasons is positive, while it is a negative correlation in the summer and autumn seasons. Conclusions: The main conclusion illustrated that the effect of the NIÑO 3.4 has a limited impact on the surface values of relative humidity and maximum and minimum air temperatures because there is a lag time in the response when the change of sea surface temperature anomalies starts to happen; it takes a month or more time until its impacts reach Iraq.
