In study carried out in the cold storage in college of Agric./Univ. of Baghdad at 8 ? C. shows that Alternaria , Pencillium , Rhizoctonia , Mucor , are the fungi that causes tomato fruits decay. This is the first record of Rhizoctonia and Mucor as a Tomato fruits rot under 8º c in Iraq. There is no fungal infection on cucumber fruits under 8 ? C. . Waxing tomato fruits reduced the severity of the fungi infection and gave shelflife (19 days) under 8 ? C. There is an infection with Mucor was found in tomato fruits kept in perforated polyethylene bages with 16 bores prevent the infection and the lowest severity and frequency of infection was found in waxed tomato fruits. Part of M.Sc thesis of the Second author.

A  biological   experirne.rit   was  CQhducted ·ll1  the   (Ibn-  Al­

Haitham).  University        of   Baghdad  for   growing   seasens   on   of

2004/2005 (by using gypsum soil taken from Al- Doar area I Salah Al­ Dean provinc)  to stucl·- the effect three levels of phosphorus (0, 400,

SOO)rng ! pot and four  levels of zinc (0, 10,.. J 5, 2.0) tngf I pot on some

features of two  varieties -Qf    wheat, (triticum aestivurn var. rateh)and

(Triticum aestiv1lm Var. Ipa 99)..

R't

Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

The research was conducted in the Department of Horticulture College of Agriculture, University of Baghdad for two seasons 1999-2000 on cultivars pomegranate Salimi and narrators seedless to study the effect of growth regulators in the amount of winning and some qualities included experience 9 transactions and three replicates per treatment used experience global Dhant design sectors full randomization carried out transactions in the two datesfirst at the onset of flowering and the second after 70 m results showed superior product Salimi Rawa