In our previous research , we study the method of women by ( al – sakhaawi " died 902
ah/1496a.c"book witch called ( al- dhau, al-lami) .
So in this paper , we will discuss the social life of women in the mamluk period through the
same book ,especially when the sakhaawi devoted a full part for women in the same book
called it (mhagam ,al –nessa)wich it translations a large number of women like wives
,daughters ,sisters ,and maids of mamluk sultans ,so that make my able to know a lot about
the social life of woman which we study it like a social aspects of women, here wealth,
business, professions ,and in the last we study the habits of them marriage .

This work investigates the use of hydrogenated amorphous silicon (a-Si:H) as a high-refractive-index material for quarter-wave distributed Bragg reflectors (DBRs) in photonic applications. In comparison to Si3N4, a-Si:H enables enhanced optical confinement, broader omnidirectional reflectance, and improved figures of merit, including higher Purcell and quality factors, while minimizing mirror complexity. To evaluate the practical impact of these advantages, a theoretical comparison is conducted between Fabry–Pérot cavities based on a-Si:H/SiO2 and Si3N4/SiO2 DBRs, examining resonance shifts as functions of cavity refractive index (1.0–3.0) and temperature (0–250 °C). The numerical results indicate that Si3N4/SiO2 planar Bragg caviti

AbstractOBJECTIVES: To evaluate the long-term remission efficacy and safety of isotretinoin in the treatment of Behcet's disease (BD). PATIENTS and METHODS: This single-blind, controlled therapeutic study was conducted in the Department of Dermatology and Venereology at Baghdad Teaching Hospital from February 2011 to January 2012. Thirty patients with BD were included in this work. Each patient received isotretinoin 20 mg orally once daily for 3 months. They were assessed at week 2 and then monthly depending on the Clinical Manifestation Index (CMI) and to record any side effects. At week 12, isotretinoin was stopped and patients were given placebo therapy in a form of glucose capsules for another 3 months. RESULTS: Thirty patients were tre

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

: Cervical malignancy positioned as the fourth most prevalent disease among women around the world. HPVs especially HPV16 are the causative agent of cervical cancer, responsible of about 5% of all human cancers worldwide. Some researchers found that the fibronectin is repressed by the papillomavirus (HPV) type 16 E7 oncoprotein in both HPV-positive nontumorigenic and tumorigenic cell lines, while others found that the HPV oncoprotein increase the levels of fibronectin. The aim is to study the effect of HPV infection on Fibronectin expression and their correlation onthe development of Cervicalcancinoma. The current retrospective study enrolled paraffinized blocks of two groups. The research included 30 cervical carcinomatous tissues as well

This study aims to investigate the features of stellar-gaseous kinematics and dynamics mass using scaling coefficient relationships (such as the Faber–Jackson relation (FJR)) of two samples of elliptical and lenticular galaxies. These two samples of 80 ellipticals and 97 lenticulars were selected from previous literature works. The Statistical Package for Social Sciences )SPSS( and Matrix Laboratory (MATLAB) program were used to find out the associations of multiple factors under investigation such as main kinematic properties of the gaseous-stellar (effective radius Re, surface density within the effective radius (Ʃeff) , stellar mass in the blue band (Mstar (B)), gas mass ( Mgas), dynamic (Mdyn) and baryonic (Mbar), supermassiv