Schiff bases (Sh1-Sh3) have been synthesized (p-aminophenol) was condensed with different aromatic aldehyde in ethanol inthe presence of glacial acetic acid as catalyst. These Schiff bases on treatment with monochloroacetyl choride gave 3-chloro-1-(4-hydroxyphenyl)-4-(substituted)azetidin-2-one(Az4-Az6), with αmercaptoacetic acid gave 3-(4-hydroxyphenyl)-2-( substituted)thiazolidin-4-one (Th7-Th9) and with anthranilic acid gave 3-(4-hydroxyphenyl)-2(substituted)-2,3-dihydroquinazolin-4(1H)-one (Qu10-Qu12). The purity of the derivatives was confirmed by TLC. The some compoundsidentify by (FT-IR and1H, 13C-NMR) data. Some of derivatives were evaluated activity against several microbesto determine ability to inhibit bacterial in some h

The objective of this investigation was to study the effects of a mixture of three arbuscular mycorrhizae (Glomus etunicatum, G. leptotichum and Rhizophagus intraradices) on the development of fusarium wilt disease in tomato plants in the presence and absence of organic matter (peatmoss). Results indicated an increase in mycorrhizal root dry weight especially in the presence of the organic matter, on the other hand this parameter was significantly decreased when Fusarium oxysporum f. sp. Lycopersiciwas added simultaneously with the mycorrhiza, Moreover, mycorrhiza and organic matter significantly reduced the damping off seedling disease, disease severity and rate of infection of tomato leaves and roots caused by the pathogenic fungus, These

The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

The study focused on the treatment of real oilfield produced water from the East Baghdad field affiliated to the Midland Oil Company (Iraq) using an oil skimming process followed by a coagulation/flocculation process for zero liquid discharge system applications. Belt type oil skimmer was utilized for evaluating the process efficiency with various operating conditions such as temperature (17-40 °C) and time (0.5-2.5 hr.). Polyaluminum chloride (PAC) coagulant and polyacrylamide (PAM) flocculant was used to investigate the performance of the coagulation/flocculation process with PAC dosage (5-90 ppm) and pH (5-10) as operating conditions. In the skimming process, the oil content, COD, turbidity, and TSS decreased with an increase in tempera

When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

Abstract

The study aimed: To assess the level of trainers' knowledge about the application of strategies and to find out the relationship between Trainer's knowledge and their socio-demographic characteristics.

Methodology: Using the pre-experimental design of the current study, for one group of 47 trainers working at the private Autism Centers in Baghdad, data was collected from 8/January / 2022 to 13 /February /2022. Using non-probability samples (convenient samples), self-management technology in which trainers fill out the questionnaire form themselves was used in the data collection process; it was analyzed through descriptive and inference statistics.