We studied in this research how to find a method of estimating the quantity (Kinetically) of three kinds of Insecticide and their mixture, which are used in agriculture. The extracted insecticide from the polluted samples with these insect from air, soil, and the leaves of trees, have be used into the reaction with H2O2 and benzedine. The kinetic study of this reaction was formed in basic medium,( pH= 8.6), using UV. Spectra at (?= 420nm). The study showed that the reaction is the first order, and the speed of the reaction was used to estimate the concentration of insecticide in solution and mixture. The experiments of this study indicated that this method has the speed and efficiency for quantitatively estimating these

Water pollution as a result of contamination with dye-contaminating effluents is a severe issue for water reservoirs, which instigated the study of biodegradation of Reactive Red 195 and Reactive Blue dyes by E. coli and Bacillus sp. The effects of occupation time, solution pH, initial dyes concentrations, biomass loading, and temperature were investigated via batch-system experiments by using the Design of Experiment (DOE) for 2 levels and 5 factors response surface methodology (RSM). The operational conditions used for these factors were optimized using quadratic techniques by reducing the number of experiments. The results revealed that the two types of bacteria had a powerful effect on biodegradable dyes. The regression analysis reveale

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The experiment was carried out in the green house of botanical garden belong to Department of Biology/College of Education for Pure Science Ibn AL-Haitham, University of Baghdad for growing season 2017-2018 to evaluate effect of lead stress with concentrations (0, 50, 100, 150) mg.L -1 and Selenium concentrations (0, 15, 30) mg.L-1 on growth of dill plant using pots. The experiment was designed according to completely randomized design (CRD) with three replications. Result indicated that dill plants subjected to lead stress with height concentrations caused decrease in plant parameters (plant height, no. of branches. plant-1, root length, shoot dry weight, the content of nitrogen, phosphorus and potassium, protein concentration, no. of umbe

Folic acid modulates several disorders in humans, pregnancy mostly because of the mitochondria-rich placenta, is a condition that favors oxidative stress.Transitional metals, especially iron, which are particularly abundant in the placenta, are important in the production of free radicals. Adenosine deaminase (ADA), an enzyme essential for the differentiation of lymphoid cells, has been used for monitoring diseases with altered immunity. In the present study we investigated the effect of regular and irregular administered folic acid in the first and second trimester of pregnancy to be compared with non-pregnant women ,and also the effect of regular and irregular using of folic acid  supplement on  oxidative stress parameters an

To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim

An accurate assessment of the pipes’ conditions is required for effective management of the trunk sewers. In this paper the semi-Markov model was developed and tested using the sewer dataset from the Zublin trunk sewer in Baghdad, Iraq, in order to evaluate the future performance of the sewer. For the development of this model the cumulative waiting time distribution of sewers was used in each condition that was derived directly from the sewer condition class and age data. Results showed that the semi-Markov model was inconsistent with the data by adopting ( 2 test) and also, showed that the error in prediction is due to lack of data on the sewer waiting times at each condition state which can be solved by using successive conditi

Aspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Proce

Imaging by Ultrasound (US) is an accurate and useful modality for the assessment of gestational age (GA), estimation fetal weight, and monitoring the fetal growth during pregnancy, is a routine part of prenatal care, and that can greatly impact obstetric management. Estimation of GA is important in obstetric care, making appropriate management decisions requires accurate appraisal of GA. Accurate GA estimation may assist obstetricians in appropriately counseling women who are at risk of a preterm delivery about likely neonatal outcomes, and it is essential in the evaluation of the fetal growth and detection of intrauterine growth restriction. There are many formulas are used to estimate fetal GA in the world, but it's not specify fo