Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

         The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp

The accurate determination of nuclear radius is fundamental to understanding nuclear structure and interactions. The present study conducts a comprehensive theoretical analysis of nuclear radius measurements using various nuclear structure models, including the empirical mass-number scaling model, the Hartree-Fock approach, and the relativistic mean-field (RMF) theory. These models are systematically compared against experimental nuclear radii to evaluate their predictive accuracy and assess their strengths and limitations. The study also incorporates an uncertainty analysis to quantify the reliability of theoretical predictions, employing Monte Carlo simulations and Bayesian inference techniques to refine estimations. The results r

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

    Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data.  This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −

Background: The treatment of moderate-to-severe psoriasis has advanced significantly with the use of biologic treatments. Objective: To compare the effectiveness, safety, and impact on quality of life of biologic therapies versus conventional systemic therapies for moderate-to-severe psoriasis, using evidence from 2015 to 2025, focusing on the implications for understudied regions such as Iraq and the Middle East. Methods: Data was collected using "Embase," "MEDLINE," "PubMed," and "Cochrane Central Register." The study includes 45 randomized controlled trials. Additionally, 25 key real-world evidence studies were included for qualitative synthesis to provide context on long-term drug survival, quality of life, and regional applicab

This search include the synthesis of some new 1,3-oxazepine derivatives have been prepared, starting from reaction of L-ascorbic acid with dry acetone in presence of dry hydrogen chloride afforded the acetal (I). Treatment of the latter with p-nitrobenzoyl chloride in dry pyridine yielded the ester (II) which was dissolved in (65%) acetic acid in absolute ethanol yielded the glycol (III). The reaction of the glycol (III) with sodium periodate in distilled water at room temperature produced the aldehyde (IV). The compound (V) [2-amino-5-mercapato-1,3,4-thiadiazole] was prepared through the reaction of thiosemicarbazide with carbon disulphide (CS2) in entity of anhydrous (Na2CO3) in (abs. ethanol ). Compound (VI) [2-(5-mercapto-1,3,4-thiadiaz

4-amino-3-(4-(((4-hydroxy-3, 5dimethoxybenzyl) oxy) methyl) phenyl)-1, 2, 4-triazole-5-thione was synthesized by to method the first one from melt reaction of 4-(((4-hydroxy-3, 5-dimethoxybenzyl) oxy) methyl) benzoic acid with Thiocarbonyldihydrazide, the second method from convert the corresponded acid hydrazide to potassium 2-(4-(((4-hydroxy-3, 5-dimethoxybenzyl) oxy) methyl) benzoyl) hydrazinecarbodithioate salt then react with hydrazine hydrate. Newly Schiff base (7a-7f) were synthesized from reaction the 4-amino-1, 2, 4-triazol with substituted hydroxybenzaldehyde. The resulting compounds were characterized by IR, 1H-NMR, 13C-NMR, and HRMS data. 2, 2-Diphenyl-1-picrylhydrazide (DPPH) and ferric reducing antioxidant power (FRAP) assays

Abdominal fat synthesizes a variety of adipokines, including vaspin and chemerin, that affect the resistance to insulin. This research was conducted to demonstrate the effect of pioglitazone, one insulin sensitizer used to decrease insulin resistance, on these adipokines in   obese patients with polycystic ovary (PCOS). Twenty-five obese women with PCOS were treated with pioglitazone 15mg/bid for 12 weeks. Modifications in fasting blood glucose (FBG), serum fasting insulin (FSI), chemerin and vaspin serum levels, follicle stimulation hormone (FSH), luteinizing hormone (LH), testosterone (T), and in baseline and post-therapy were assessed. Body mass index decreased without any substantial variance after 12 weeks of piogl