Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

The problem of generated waste as a result of the implementation of construction projects, has  been aggravated recently because of construction activity experienced by the world, especially Iraq, which is going through a period of reconstruction, where construction waste represents (20-40%) of the total generated waste and has a negative effect on the environment and economic side of the project. In addition, the rate of consumpted  amounts of natural resources are estimated to be about 40% in the construction industry, so it became necessary to reduce waste and to be manage well. This study aims to identify the key factors affecting waste management through the various phases of the project, and this is accom

The melting duration in the photovoltaic/phase-change material (PV/PCM) system is a crucial parameter for thermal energy management such that its improvement can realize better energy management in respect to thermal storage capabilities, thermal conditions, and the lifespan of PV modules. An innovative and efficient technique for improving the melting duration is the inclusion of an exterior metal foam layer in the PV/PCM system. For detailed investigations of utilizing different metal foam configurations in terms of their convective heat transfer coefficients, the present paper proposes a newly developed mathematical model for the PV/PCM–metal foam assembly that can readily be implemented with a wide range of operating condition

Objectives: To assess the premenstrual syndrome among the working women in Baghdad City.
Methodology: A cross-sectional analytic study, using probability sampling cluster (multi-stage) sampling of
ft°e°*f:£m::?ehL:_ye;roerts:::Ciefdq::d:om|yNfro°v:£°::Cohth°:|o¥dto(3#:th°r3L:Sth2Doa;;WQe::s:j°o[£CateIT:t£T:ufth;::
designed and consisted of (4) parts, including demographic, reproductive, menstrual cycle characteristics, and
premeustmual syndrome symptoms. Content validity and reliability of the questionnaire were detemined by
conducting a pilot study. Descriptive and inferential statistical procedures were used to analyze the data.
Results: The results of the study revealed that the age of women ranged betwee

The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

A study carried out in quail’s field owned by the Department of Animal production/ Collage of Agriculture / Tikrit University. For the period 14/ 5/ 2016 to 4/ 6/ 2016 in order to study the effect of adding Curcuma longa - to the diet of quails - on some productive and physiological characteristics of the Japanese quail birds bred for meat production. Using (48) quail birds which are two weeks old provided by Department of Agricultural Research. The birds were divided randomly after weighing them into three treatments; four replicate treatments for (4 bird/ replicate). The treatments as follows: (T1) control group (fed diet without any supplement), second (T2) and third (T3) groups were fed diet supplemental 4.5 and 9g Curcuma powder /

In this study, the specimens of land snails Polygyra cereolus (Megerle v on Mühlfeld t , 181 8
(Gastropoda, Stylommatophora, are collected between March and April 2021
from gardens and nurseries in Baghdad province, this species was recorded as a new record to
Iraq molluscan fauna. Description of the most important characteristics, measurements of the
shell are presented with digital p photographs, subsequently, this study represents the first record
of the Polygyridae in Iraq.