In this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcin

Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak

        New derivatives of thiosemicarbazide were synthesized by reaction of different aromatic aldehydes and ketones with thiosemicarbazide to give schiff-bases 1(a-d) . schiff-bases have been used for synthesized the thioimidazolidine 2(a-d)  by reaction of schiff-bases with ethyl chloroacetatein in presence of anhydrous sodium acetate that transformed part of it in to Beta-lactam 3(a-b) compounds with phenyl acetic acid and thionyl chloride , The compounds 4(a-b) came from the reactor of 4-bromobenzaldehyde with compounds 2(a-b) , as well as reaction of compounds 2(b-d) with methyl iodide and anhydrous potassium carbonate to give 5 (b-d) , then added  hydrazine hydrate formed 6(b-d) , then

    The aim of study was to  assess water stress for 2,8,14 days and spraying selenium at 0,10,20 mg/L-1 and brassinolide 0,1,2 mg/L-1 on vegetative growth and macro elements content (NPK) for Coriander (Coriandrum astivum L.) plant, The experiment was performed with Factorial Randomized Block Design (R.B.C.D) with three replicates .The results were summarized as follows: 1- The period of sever water stress for 14 days was passive effect on growth parameters. 2-  The means of elements content  NPK content  was increased at moderate stress for 8 days. 3- The effect of selenium and brassinolide was positively to increase studied parameters. 4- Selenium and Brassinolide decreased water stress also the triple in

This article includes designed and synthesized for bent-shaped liquid crystal molecules starting from 5,5-diethylpyrimidine-2,4,6(1H,3H,5H)-trione and two moles of chloroacetylchloride in N, N-dimethyl formamide (DMF) and triethylamine (TEA) to product compound [I] ,then reacted the later compound with two moles of 4-hydroxybenzonitrile to yield nitrile compound [II]. Likewise, reaction 5,5-diethylpyrimidine-2,4,6(1H,3H,5H)-trione and two moles of ethylchloroacetate with fused sodium acetate in ethanol to create an ester compound [III], and then the later compound was reacted with two moles of hydrazine hydrate in ethanol to obtained hydrazide acid compound [IV]. After that, the compound [IV] reacted with two moles of ethyl acetoacetate in

     The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written