The present study attempts to identify some of the differences between the skull bones of two species Cyprinus carpio and Carassius carassius, which belong to the Cyprinidae family. The study is a taxonomic diagnostic study between the two species which are considered local fish abundant in the Iraqi aquatic environment

This study was conducted to evaluate the efficacy of 6 isolates of Pseudomonas fluorescens and Trichoderma harzianum and there combination against Fusarium tomato wilt disease caused by Fusarium oxysporum F.sp. Lycopersisi under green house condition .The isolates of bacteria (B3) and Trichoderma (T1) were found to be highly effective in reducing the disease incidence to 13.3% , 21% respectively , compared to control treatment (40%).Furthermore, disease severity was reduced to 28 and 30% respectively in comparison to control (90%) .Colonization of the roots (cfu /g fresh root weight )by the two isolates whether alon or together was extremely high . The combination treatment had a high ability in reducing disease incidenece and sev

  

To evaluate and compare serum Leptin hormone level between Iraqi male & female and the relation between this hormone & BMI in these two groups.

A total of 44 normal male & female subjects were included in this study

{Group 1 : 22 female } , { Group 2 : 22 male}.

Serum Leptin hormone ,BMI &fasting blood glucose were measured for both groups.

   Serum Leptin level in group 1 was (8.82 + 2.9 μg/L) where as in group 2 it was (4.65 + 3.2 μg/L) . These changes were statistically significant. Fasting blood glucose levels were technically within the normal value (

  In  this  paper, we  introduced   some  fact  in   2-Banach  space. Also, we define  asymptotically  non-expansive  mappings  in  the  setting  of  2-normed  spaces analogous  to  asymptotically non-expansive mappings  in  usual  normed spaces. And then prove the existence of fixed points for this type of mappings in 2-Banach spaces.

Background: Patients with type 2 diabetes have an increased prevalence of lipid abnormalities, contributing to their high risk of cardiovascular diseases (CVD).Glycated hemoglobin (HbA1c) is a routinely used marker for long-term glycemic control. In accordance with its function as an indicator for the mean blood glucose level, HbA1c predicts the risk for the development of diabetic complications in diabetic patients[2].Apart from classical risk factors like dyslipidemia, HbA1c has now been regarded as an independent risk factor for (CVD) in subjects with or without diabetes.Objective The aim of this study was to find out association between glycaemic control (HbA1c as a marker) and serum lipid profile in type 2 diabetic patients.Methods

      The Internet of Things (IoT) is a network of devices used for interconnection and data transfer. There is a dramatic increase in IoT attacks due to the lack of security mechanisms. The security mechanisms can be enhanced through the analysis and classification of these attacks. The multi-class classification of IoT botnet attacks (IBA) applied here uses a high-dimensional data set. The high-dimensional data set is a challenge in the classification process due to the requirements of a high number of computational resources. Dimensionality reduction (DR) discards irrelevant information while retaining the imperative bits from this high-dimensional data set. The DR technique proposed here is a classifier-based fe

Nowad ays, with the development of internet communication that provides many facilities to the user leads in turn to growing unauthorized access. As a result, intrusion detection system (IDS) becomes necessary to provide a high level of security for huge amount of information transferred in the network to protect them from threats. One of the main challenges for IDS is the high dimensionality of the feature space and how the relevant features to distinguish the normal network traffic from attack network are selected. In this paper, multi-objective evolutionary algorithm with decomposition (MOEA/D) and MOEA/D with the injection of a proposed local search operator are adopted to solve the Multi-objective optimization (MOO) followed by Naï

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

     Analysis of image content is important in the classification of images, identification, retrieval, and recognition processes. The medical image datasets for content-based medical image retrieval (  are large datasets that are limited by high computational costs and poor performance. The aim of the proposed method is to enhance this image retrieval and classification by using a genetic algorithm (GA) to choose the reduced features and dimensionality. This process was created in three stages. In the first stage, two algorithms are applied to extract the important features; the first algorithm is the Contrast Enhancement method and the second is a Discrete Cosine Transform algorithm. In the next stage, we used datasets of the medi