מחקר זה עוסק בנושא (העיירה היהודית) שטטל ביצירותיהם של שני סופרים עבריים שהתמקדו בביקורת בשטטל. וזה נחשב להגבלה או למכשול לפיתוחם של היהודים, אז זה התרחש ביצירותיהם והם נתנו תשומת לב רבה לזה –לפי דעתם- גם זה נחשב להיבט בהיסטוריה והחיים של היהודים באירופה.

 סופרים עבריים רבים התעסקו בנושא השטטל שנהיתה לחומר ביצירותיהם. גם כן נהיתה אצל כמה מהם לשאלה חשובה, כי אם  אנו מוצאים שיצירותיהם לא נטשו את האזכור

Carbonate reservoirs are an essential source of hydrocarbons worldwide, and their petrophysical properties play a crucial role in hydrocarbon production. Carbonate reservoirs' most critical petrophysical properties are porosity, permeability, and water saturation. A tight reservoir refers to a reservoir with low porosity and permeability, which means it is difficult for fluids to move from one side to another. This study's primary goal is to evaluate reservoir properties and lithological identification of the SADI Formation in the Halfaya oil field. It is considered one of Iraq's most significant oilfields, 35 km south of Amarah. The Sadi formation consists of four units: A, B1, B2, and B3. Sadi A was excluded as it was not filled with h

Introduction: Surgical removal of impacted lower wisdom teeth is one of the most commonly performed proce- dures in oral and maxillofacial surgery. Objectives: This study aimed to compare the operative and post-operative outcomes of 2 flap designs (limited vs. extended 2-sided flap) in surgical extractions of lower third molars (M3) regarding fully impacted teeth. Material and methods: A prospective, randomized, controlled split-mouth trial was designed, and included 27 patients with bilateral (symmetrically positioned) impacted M3. Limited 2-sided flap was performed on one side (group 1) and extended 2-sided flap on the other side (group 2). The effect of flap design on intra-operative (visibility, accessibility, and duration of surgery) a

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

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

Impairment of financial assets defined according to IFRS 9 as the difference between all contractual cash flows that are due to an entity in accordance with the contract and all the cash flows that the entity expects to receive, the entity should estimates all the cash flows through looking to the contract terms during the life time period of the assets or for shorter period if possible, the cash flow should include the amounts of selling any collateral taken or any other enhancement. On the other hand, the Central bank of Iraq guidelines regards impairment differ from the IFRS 9 that’s does not consider the collateral value on calculating the impairment that’s effects on the net profit through recognizing exaggerated loss an