This study presents a comprehensive list of the freshwater and marine bivalves distributed in Iraq. A total of 51 species were recorded, and distributed as: 14 freshwater species, and 37 marine species, these species belonging to 25 families, all available remarks on the distribution, taxonomy, and nomenclature of these species were given. This study included the recently collected specimens along with those previously studied and recorded in Iraq.

Objective: To examined the common frequency of cervical cancer in Iraqi women. Study Design: Descriptive study Place and Duration of Study: This study was conducted at the Iraqi Cancer Agency and the Cancer Registry data from the Iraqi Ministry of Health provided assistance in data gathering from 1st April 2020 to 31st December 2021. Methods: The study examined 504 women diagnosed with cervical cancer. Their ages ranged from 20 to over 80 years. The data analysis employed descriptive statistics to determine the frequency, proportion, and incidence of cervical cancer. Results: The cervical cancer was predominantly caused by human papillomavirus in women in 2020 (1.29%) and 2021 (2.1%). In 2020, the number of cases of cervical can

During the syrvey on natural enemies of whiteflies in Iraq, the following. predators were recorded.

ABSTRACT Background: Dental anomalies of teeth are major issue that contributes to dental problems encountered in general practice. The aim of this study is to measure the prevalence of dental anomalies and the associated etiological factors among 15 years old students in Basrah city –Iraq. Materials and methods: The total sample composed of 1000 students (435 males and 565 females) from urban area selected randomly from different high schools in the city. Diagnosis of dental anomalies were recorded by present or absent, diagnosis and recording of enamel defects were done according to the criteria of WHO (1997). Results: The prevalence of hypodontia was 4.6%, Females have higher prevalence than males (5.8% females and 3.0% males), ta

I noticed a researcher while working in the kindergarten that there is a group of
parameters resort to the use of different methods may be some undesirable and some
undesirable So felt researcher detection methods used parameters Riyadh in the face of the
pressures of life, being engaged in kindergarten eligibility, governmental or being married or
unmarried, as well as educational attainment for this parameter.
To achieve the objectives of the research: -
The researcher prepare a scale methods face the pressures of life of the parameters
have been confirmed the veracity of the paragraphs of the scale of the presentation to a group
of experts in this area, and extracted power discriminatory clauses scale and extra

0

I started writing the research because of the linguistic and rhetorical methods in the Holy Quran.
This Sura included in all its verses the plural form such as the word planets graves and seas except the word sky was singular as the name of a genus, and this Sura showed the horrors of the Day of Judgment at the world level Included another science is the science of the interview and also came in the repetition and deletion and other linguistic and rhetorical things and concluded this Sura that the goal of breaking the sky and scattering planets and scatter graves is the human himself.
The Koran is a miracle immortal and science is still drawn from him each according to his specialty.

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi