This study examines how Sahar Mustafah's book The Beauty of Your Face (2020) examines the intersectional aspects of Arab American identity. The novel traces the life of the Palestinian Arab American woman, Afaf Rahman who is a school principal. She negotiates the intricacies of gendered, religious, and cultural identities in America after 9/11. The analysis uses an intersectional lens to look at how Afaf's experiences as a woman, a Muslim, and an immigrant combine to influence how she sees herself and how she interacts with society at large. The book explores racial prejudice, misogyny, and Islamophobia, bringing to light the many difficulties Arab American women experience. Additionally, it shows the protagonist's autonomy and tenacity as

Inherent fluctuations in the availability of energy from renewables, particularly solar, remain a substantial impediment to their widespread deployment worldwide. Employing phase-change materials (PCMs) as media, saving energy for later consumption, offers a promising solution for overcoming the problem. However, the heat conductivities of most PCMs are limited, which severely limits the energy storage potential of these materials. This study suggests employing circular fins with staggered distribution to achieve improved thermal response rates of PCM in a vertical triple-tube heat exchanger involving two opposite flow streams of the heat-transfer fluid (HTF). Since heat diffusion is not the same at various portions of the PCM unit,

Abstract: The aim of the current research is to identify (the relationship between deep understanding skills and mathematical modeling among fifth grade students) the research sample consisted of (411) male and female students of the fifth grade of biology distributed over the General Directorates of Education in Baghdad / Al-Rusafa / 2 / and Al-Karkh / 1 /, and two research tools were built: 1- A test of deep understanding skills, consisting of (20) test items and a scale for two skills. 2- The second test consists of (24) test items distributed among (18) essay items and (6) objective items. The psychometric properties of validity, stability, discriminatory strength, and effectiveness of alternatives were verified for the two tests fo

This paper deals with the Kufis and basris agreements in Abo Al _ Barakat Al _ anbary’s
work “ Al- Insaf Fi Masael Al - Khilaf.It attempts to settle the disputes and find out the right
views.
The book presents the issnes that the two schools of Kufa and Basra dispute upon and try to
evaluate them so as to support the correct ones .The present researcher has noticed that the
author of the above work was not always right or accurate in picturing a number of issues as
disputable whereas they implicitly shared the same views .Accordingly ,this papor sheds light
on such cases and drew acadernic researchers, attention to the invalidity of Al –anbary’s
misjudged views.

ArcHydro is a model developed for building hydrologic information systems to synthesize geospatial and temporal water resources data that support hydrologic modeling and analysis. Raster-based digital elevation models (DEMs) play an important role in distributed hydrologic modeling supported by geographic information systems (GIS). Digital Elevation Model (DEM) data have been used to derive hydrological features, which serve as inputs to various models. Currently, elevation data are available from several major sources and at different spatial resolutions. Detailed delineation of drainage networks is the first step for many natural resource management studies. Compared with interpretation from aerial photographs or topographic maps, auto

Intrusion Detection Systems (IDS) is the main defense mechanism deployed by the current networks to prevent cyber threats. Recurrent Neural Network (RNN) are also a novel IDS structure that replaces the conventional training and testing mechanism. The strategy encodes network traffic data as biological sequences using amino acid codons in such a fashion that the RNN is capable of effectively analyzing temporal and sequence data patterns. RNN architecture design adopts embedding layers to handle codon representations and Long Short-Term Memory (LSTM) layers to perform sequential data learning, which is followed by a fully connected network to perform classification functions, which preserve high feature extraction and classification