University of Diyala

A Neural Architecture Search-enhanced Dual Stage Attention Bidirectional Long Short-Term Memory (NAS-DSA-BiLSTM) model is proposed to capture nonlinear temporal hydrological patterns and is evaluated at three hydrological stations. The NAS-enhanced model achieved the best performance at Kaptanpasa, with the lowest MSE (11.249-16.224) and the highest R2 values, outperforming LSTM and DNN-LSTM models. Additional evaluations using NSE, sensitivity analysis, and Taylor diagrams confirmed stable and accurate predictions, particularly at Ulucami (NSE = 0.91) and Kaptanpasa (NSE = 0.80), demonstrating the model's robustness for streamflow forecasting. The proposed model improved MSE by 15-26%, demonstrating robust and reliable streamflow forecasting performance.

The present study aimed to synthesize suggested Cu-Ag Bimetallic (NPs) as antimicrobial agents for biomedical applications, using two-stages Nd: YAG laser ablation (maximum energy 800 mJ, 900 pulses, 1064 nm, 9 ns, 1 Hz) in dimethylformamide (DMF )solvent. The synthesized nanoparticles were further evaluated by molecular docking to investigate their potential inhibitory effects against bacterial targets. The prepared nanoparticles were characterized using (UV-Vis spectroscopy), Xray diffraction spectroscopy (XRD), Fourier transform infrared spectroscopy (FTIR), Transmission electron microscopy (TEM), Energy dispersive X-ray spectroscopy (EDX), Atomic force microscopy (AFM) and Zeta Potential (ZP). TEM analysis demonstrated semi-spherical nanostructures with average particle sizes of 25.5 nm for (AgNPs), 10.8 nm for (CuNPs), and 15 nm for suggested Cu-Ag Bimetallic NPs. The antimicrobial effect of different concentrations of the prepared NPs was tested on two types of bacteria; a gram-negative (Pseudomonas aeruginosa) and a gram-positive (Streptococcus mutans). At (100 ) μ g/mL concentration for AgNPs, CuNPs and Cu@AgNPs exhibited inhibition zones of (21.04 ± 0.10 mm, 20.07 ± 0.10 mm and 23.00 ± 0.10 mm) for (P. aeruginosa) bacteria and (31.04 ± 0.12 mm, 24.07 ± 0.12 mm and 32.21 ± 0.11 mm) for (S. mutans) bacteria respectively. The results indicate that suggested Cu-Ag BimetallicNPs exhibit enhanced antibacterial activity compared with monometallic Ag and Cu nanoparticles. Furthermore, biofilm inhibition assays demonstrated a higher capacity of Cu@Ag nanoparticles to suppress bacterial growth relative to the individual nanoparticle. Molecular docking was employed to evaluate the antibacterial potential of Cu, Ag, and core–shell Cu@Ag nanoparticles against Pseudomonas aeruginosa (PDB ID: 1IX1) and Streptococcus mutans (PDB ID: 3BJV). The copper-silver (Cu and Ag) monometallic nanoparticles exhibited moderate binding energies to their target proteins in bacteria. The binding energies to Pseudomonas aeruginosa ranged from − 5.44 to − 6.5 kcal/mol. Cu-Ag Bimetallic NPs exhibited higher binding energy (− 8.50 kcal/mol) with the same bacteria, indicating a stronger and more specific interaction within the binding site. Coordination interactions between silver and amino acid residues (ASN101, ASP103, and TYR147), along with π-donor interactions between copper and TYR147, demonstrate a genuine and stable chemical bond. For Streptococcus mutans, copper and silver particles exhibited relatively similar binding behavior with low binding energies.

Background: The parasite Echinococcus granulosus is still endemic in many nations worldwide, particularly in developing nations. The main organ where the parasite infests is the liver. is a significant zoonotic infection that mostly affects endemic areas and impacts millions of people globally. Techniques. A granulomatous tissue reaction is caused by an ongoing infection with an E. granulosus hydatid cyst, progressively establishing an immunological milieu marked by the buildup of monocytic and lymphocyte cells. IL-10-producing CD8+ T cells and CD4+ T-cell-mediated cellular immune responses are essential during the establishment phase of secondary E. granulosus s.s. infection. Methods: Liver samples (40 infected liver and 20 non-infected) from animals infected with hydatid cysts were collected from licensed governmental butchers and slaughterhouses located in local markets within the Diyala Governorate; no animals were harmed for this study, as the samples were from previously sacrificed animals. Results: The study examined clinical and histological alterations in liver tissue sections, with a focus on the impact of hydatid., The results of histological examination of liver sections showed that the infected livers contained increased sinusoid and central vein dilation; portal and central vein congestion; necrosis of hepatic tissue; atrophy; and increased inflammatory cell infiltration. compared to the noninfected livers, which had no histologic lesions. The current work involves assessing the expression of PD-L1, CD4, CD8 proteins in the liver infected with E. granulosus. Conclusion: In addition to increased inflammatory cell infiltration in the liver, a hydatid cyst infection results in a variety of clinical and biochemical alterations. These results open the door for further studies focused on early detection, prevention and focused treatment approaches for this common illness.

Early diagnosis of lung cancer greatly improves patient survival rates. This study used a large-scale dataset of 1000 patients with nine parameters. However, diagnosing lung cancer early remains a major challenge due to its impact on the human respiratory system. Currently, artificial intelligence techniques are among the most promising methods for diagnosing and detecting cancer. Various machine learning algorithms have been employed to identify lung cancer in patients. This paper evaluates the accuracy of nine classifiers: Decision Tree (DT), Quadratic Discriminant Analysis (QDA), Logistic Regression (LR), Naïve Bayes (NB), Support Vector Machine (SVM), K Nearest Neighbor (KNN), Ensemble Learner (EL), Artificial Neural Network (ANN), and Kernel machine for detecting lung cancer at its early stages, which leads to saving lives. The study’s results demonstrated that the Decision Tree algorithm (DT) achieved the highest accuracy of 93.5

This study investigates TIG welding current variations effects on 4 mm thickness AISI 304 stainless steel joint welded using Argon gas, and this process impacts on ferrite composition, structural properties and joint strength. Ferrite content control must be managed properly to prevent hot cracking while ensuring both material strength and corrosion resistance because improper management leads to deficits during welding operations. A set of welding currents starting at 100 A progressed to 150 A and ending at 190 A created welds which delivered heat inputs of 6 J/mm, 9 J/mm and 11.4 J/mm. Welds under each condition received full inspection using metal structure analysis, scanning electron microscopy (SEM) along with Ferritoscope ferrite measurement, Vickers hardness analysis and mechanical strength testing. Data showed that a rise in heat intensity led to more ferrite formation starting from 4% at 100 A up to 9% at 190 A. The welds with 150 A heat application produced the optimal combination of mechanical properties since they contained 6% ferrite and displayed peak tensile strength at 689 MPa and mid-range hardness from 160-170 HV along with increased resistance to hot cracking. The welding current at 100 A produced a high hardness level of 170-181 HV in the weld but lost strength because of excessive ferrite content. Meanwhile the weld at 190 A exhibited lower strength and reduced hardness (150-157 HV) due to its excessive ferrite formation. Because of its ability to achieve superior microstructure with desirable austenite-to-ferrite ratio the weld using 150A heat input delivers optimal weld quality. The current investigation establishes quantitative assessments about heat treatment effects on AISI 304 TIG welds which distinguishes itself from previous research. The integration of Schaeffler diagram modeling with direct ferrite evaluations paired with SEM verification leads to a superior method for welding process prediction and enhancement.