Zora Neale Hurston's (1891-1960) is an outstanding African American
novelist, playwright, autobiographer and essayists. Her work is considered as an
important part of the African American and Harlem Literature.**** It represents a
milestone and a keystone in the African-American literary canon because it breaks
from the style of the previous works and makes a beginning of a new style. Hurston
shifts from the black works that stick to racial themes and sheds the light on new
aspects and themes in blacks' life especially on feminist themes. Her exceptional fame
culminates in her novel Their Eyes Were Watching God (1937). 1
Their Eyes Were Watching God examines with a great deal of artistry
the struggle of a black

Background: Nickel-titanium (NiTi) archwires have become increasingly popular because of their ability to release constant light forces, which are especially useful during initial alignment and leveling phase. The aim of the present study was to investigate and compare the load–deflection characteristics of four commercially available NiTi archwires. Materials and methods: 200 NiTi 0.014, 0.016, 0.018, 0.016x0.022 and 0.019x0.025-inch nickel–titanium archwires from four different manufacturers (3M, Ortho Technology, Jiscop and Astar) were tested. The load-deflection properties of these archwires were evaluated by a full arch bending test in both palatal and gingival directionsat 37°C temperature using a universal material t

The research aims to shed light on the possibility of measuring the intellectual capital in the Iraqi insurance company using accounting models, as well as disclosing it in the financial statements of the company, where human capital was measured using the present value factor model for discounted future revenues and the intellectual value-added factor model for measuring structural capital It was also disclosed in the financial statements based on the theory of stakeholders. The research problem lies in the fact that the Iraqi insurance company does not carry out the process of measuring and disclosing the intellectual capital while it is considered an important source for the company’s progress in the labor market recently. T

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

SUMMARY. – Nanocrystalline thin fi lms of CdS are deposited on glass substrate by chemical bath deposited technique using polyvinyl alcohol (PVA) matrix solution. Crystallite size of the nanocrystalline films are determining from broading of X-ray diffraction lines and are found to vary from 0.33-0.52 nm, an increase of molarity the grain size decreases which turns increases the band gap. The band gap of nanocrystalline material is determined from the UV spectrograph. The absorption edge and absorption coefficient increases when the molarity increases and shifted towards the lower wavelength.

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve