Abstract

The problem with the search at the reduction of adoption of new products, as there are three hypotheses of research have been formulated , the first one is no significant correlation between the religious and differences to customers and adopt new products, and This Study Aimed To Investigate The Relationship Between Religious differences for customers And New Products Adoption, Applied On Arab Mall Commercial Customers/ Egypt, an Analytical Model Is Developed As Guideline To Test The The Relationship Between Religious differences for customers And New Products Adoption, Aquantative Method With Deductive Approach Were Chosen In This Research . In Order To Collect Primary Data, A questionnaire Is

The necessary optimality conditions with Lagrange multipliers  are studied and derived for a new class that includes the system of Caputo–Katugampola fractional derivatives to the optimal control problems with considering the end time free. The formula for the integral by parts has been proven for the left Caputo–Katugampola fractional derivative that contributes to the finding and deriving the necessary optimality conditions. Also, three special cases are obtained, including the study of the necessary optimality conditions when both the final time  and the final state  are fixed. According to convexity assumptions prove that necessary optimality conditions are sufficient optimality conditions.

 In this work, the preparation of some new oxazolidine and thiazolidine derivatives has been conducted. This was done over two steps; the first step included the synthesis of Schiff bases A1-A5 in 72-88% yields by the condensation of isonicotinic acid hydrazide and aldehydes. The second step includes the cyclization of derivatives A1-A5 with glycolic acid and thioglycolic acid to obtain the desired products, oxazolidine derivatives B1-B5 (44-60% yields) and thiazolidine derivatives C1-C5 (41-61% yields), respectively. The structure of the prepared compounds was characterized using FT-IR, 1H NMR, and 13C NMR spectroscopy. Some of the produced compounds were tested for antioxidant properties.  

This study has been conducted to examin the effect of sodium propionate at different level of 0.03,0.06,0.10% on the number of bacteria and mold and to extend the storage life of laboratory processed biscuit. The results indicated that the use of 0.10% sodium propionate prolonged the storage peroid until the third month, while the use of 0.20% sodium propionate showed no growth of bacteria up to six month of storage, three types of bacteria has been isolated from processed biscuit, namely, Staphylococcus aureus, Bacillus cereus, Esherichia coli. using 0.10% sodium propionate showed no growth of mold up to three month of storage ,while using of 0.15 % and 0.20% sodium propionate prevent the growth

    Two different approaches, univariate and multivariate (simplex method), have been used to obtain the optimum conditions for the quantitative Spectrophotometric determination of Eu3+ using Solochrome violet RS (3-Hydroxy-4-(2-hydroxy phenyl azo) naphthalene -1sulfonic acid) (SVRS) as a chromogenic reagent. The investigation shows that Eu3+ ion forms a wine-red complex with SVRS in alkaline buffer solution having a maximum absorbance at 464 nm against reagent blank.       Calibration graphs obtained under univariate and simplex were found to be linear in the range of (0.30-8.0) µg/ml with detection limit 0.061µg/ml and molar absorptivity of 9877.66 L/mol.cm and (0.40-10.0)µg/ml with

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina