أن إحدى اكبر مشاكل الصحة العالمية هي ظهور مقاومة الميكروبية للأدوية الشائعة لذلك هناك حاجة ملحة لمضادات جرثومية جديدة ذات نشاط أحيائي معزز .في هذا الدراسة, تم تحضير خمسة مشتقات جديدة من الكينولين  A,B,C,D  وEكمضادات جرثومية. تم فحص بنية المركبات المحضرة باستخدام  UV light , FTIR NMR  . تم استخدام طريقة الانتشار بالحفر في الطبق لاختبار الخصائص المضادة للبكتريا للمركبات المحضرة في المختبر ضد نوعين من البكتريا الموجبة

  This research aims to harmonize contemporary and traditional clothes, also expenses and savings. It is done by recycling evening clothes into Clothes with traditional features. The study followed descriptive explanatory approach. The sample consisted of seven dresses, as well as 208 female participants from Makkah Al-Mukarramah province, the age range was between 21 and 65 years old. An electronic questionnaire was distributed and the stability and reliability of the internal consistency were measured.
The research resulted in the ability to recycle evening dresses into modern clothes with traditional characteristics. It also confirmed that the reason of wearing traditional clothes is spirituality of the month of Ramadan. Addi

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage