Since cancer is becoming a leading cause of death worldwide, efforts should be concentrated on understanding its underlying biological alterations that would be utilized in disease management, especially prevention strategies. Within this context, multiple bodies of evidence have highlighted leptin’s practical and promising role, a peptide hormone extracted from adipose and fatty tissues with other adipokines, in promoting the proliferation, migration, and metastatic invasion of breast carcinoma cells. Excessive blood leptin levels and hyperleptinemia increase body fat content and stimulate appetite. Also, high leptin level is believed to be associated with several conditions, including overeating, emotional stress, inflammation, obesity,

ملخص البحث
تبحث الدراسھ عن تنفیذ افضل لمفھوم التعلم مدى الحیاة كھیكل موجھ للسیاسة التربویة في العراق بشكل عام وفي
التعلیم العالي بشكل خاص. تحدد الدراسة استراتجیات التعلم مدى الحیاة وتناقش اھمیتھ وسماتھ الرئیسیة لتسھیل
الوصول الى فرص تعلم متمیز و ملائم لحاجات الطلبة مدى الحیاة، كما تناقش دور الجامعة في تحقیق ھذا الھدف.

One of the most important challenges facing the designers of the sewerage system is the corrosion of sewers due to the influence of sewerage contaminates which lead to failure of the main lines of sewers. In this study, a reference mix of 1: 1.5: 3 was used and the 4% Flocrete PC200 by weight of cement was added to the same mixing ratio in the second mixture. Twenty-four samples were tested for each mixture, 12 of which were used to compression strength test in ages (7, 14 and 28) day and six samples were submerged after 28 days of wet treatment at (5 and 10) % concentrations of sulfuric acid. The other six samples were painted after 28 days of wet treatment with coating Polyurethane and after 24 hours were flooded with a concentrat

The research draws its importance from identifying the methods of profit management in misleading the financial statements, which in turn is reflected in the decisions of the authorities that relied on these reports, and then the models that help in detecting those methods used by the auditors. Risks. The index (margin of excess cash) was used to detect profit management practices on a group of banks listed in the Iraqi market for securities and the number of (23) banks, including (12) commercial bank and (11) Islamic bank and the results were compared to commercial banks with Islamic banks.((The research started from the hypothesis that the use of the (excess cash margin) model in the banking sector reveals the management

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.

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The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class