The significance of the research conducted in northern Iraq comes despite the expansion of afforestation projects; yet, the suffering of the forests has increased due to their lack of scientific study, unpredictability of the climate, and adverse effects on the spread and growth of plant species Therefore, the goal of the study is to understand the effects of afforestation through a statistical analysis of plant diversity in northern Iraq and its distinctivenessThe analysis revealed that natural groupings had improved qualitatively more than other groups, particularly some dwindling species that are able to compete and occupy new areas. drought-prone vegetation, vegetation, and climat
Cadmium element is one of the group IIB and classified as heavy metal and effects on human health and environment. The present work concerns with the biosorption of Cd(II) ions from aqueous solution using the outer layer of onions. Adsorption of the used ions was found to be pH dependent and maximum removal of the ions by outer layer of onions and was found to be 99.7%.
Tomato (Solanum lycopersicum) is acknowledged worldwide as one of the major vegetable crops, as is the case in Iraq. This research in 2024 was designed to recognize the species of Root-Knot Nematode (RKN) in central Iraq, assess its distribution, and study the level of susceptibility of 5 tomato varieties (SPEEDY, GS-12, SUPER LUX, TALA, and JUDIVIS). Since there is a threat of chemical nematicides, a greenhouse study was performed to evaluate other control methods, such as the use of organic fertilizers and the extract of nettles (Urtica dioica). Root-knot nematode (RKN) species consisting of Meloidogyne incognita, M. arenaria, and M. javanica were found in Baghdad, while only M. incognita was found in Babil. Molecular identificati
... Show MoreDetection 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
... Show MoreAutism 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
... Show MoreIn recent years, the evolution of the community structure in social networks has gained significant attention. Due to the rapid and continuous evolution of real-world networks over time. This makes the process of identifying communities and tracking their topology changes challenging. To tackle these challenges, it is necessary to find efficient methodologies for analyzing the behavior patterns of dynamic communities. Several previous reviews have introduced algorithms and models for community detection. However, these methods have not been very accurate in identifying communities. Moreover, none of the reviewed papers made an apparent effort to link algorithms that can accurately detect dynamic communities. This review aims to present a ta
... Show MoreBackground: Fixed orthodontic appliances impede the maintenance of oral hygiene and result in plaque accumulation leads to enamel demineralization caused by acids produced by bacteria. Studies on plaque control strategies in orthodontic populations are limited. This might be caused by difficulties in the quantitative evaluation of dental plaque because the teeth have various levels of bracket coverage, and different tooth sizes and malocclusions, making the traditional categorical indices complex. The present study aims to evaluate the effect of different hygiene protocols on plaque quantity on bands with different attachments. Materials and method: Twenty patients had four bands within the orthodontic appliance. Then randomly divided into
... Show MoreTwo field experiments were conducted during the spring seasons of 2000,2001.The aim was to study the effect of hardening to drought tolerance on moisture percentage in root and stem of sunflower plant during growth stages . Asplit-split plots design was used with three replications.The main plots included irrigation treatments:irrigation to100%(full irrigation),75and50%of available soil water.The sub plots were the cultivars Euroflor and Flame.The sub-sub plots represented four seed soaking treatments :Control(unsoaked),soaking in water ,Paclobutrazol solution(250ppm),and Pix solution(500ppm). The soaking continued for 24 hours then seeds were dried at room temperature until they regained their original weight. Amount of water
... Show More