In recent years, non-oil primary balance indicator has been given considerable financial important in rentier state. It highly depends on this indicator to afford a clear and proper picture of public finance situation in term of appropriate and sustainability in these countries, due to it excludes the effect of oil- rental from compound of financial accounts which provide sufficient information to economic policy makers of how economy is able to create potential added value and then changes by eliminating one sided shades of economy. In Iraq, since, 2004, the deficit in value of this indicator has increased, due to almost complete dependence on the revenues of the oil to finance the budget and the obvious decline of the non-oil s

Electromyography (EMG) is being explored for evaluating muscle activity. For gait analysis, EMG needs to be small, lightweight, portable device, and with low power consumption. The proposed superficial EMG (sEMG) system is aimed to be used in rehabilitation centers and biomechanics laboratories for gait analysis in Iraq.

The system is built using MyoWare, which is controlled by using STM32F100 microcontroller. The sEMG signal is transferred via Bluetooth to the computer (about 30m range) for further processing. MATLAB is used for sEMG signal conditioning. The overall system cost (without computer) is about $80. The proposed system is validated using wired NORAXON EMG using the mean root mean squared metho

Praise be to God alone, and prayers and peace be upon the one after whom there is no prophet, and after:

This is a regular judicial search for the issuance, validity, and cancellation of regulations in the Saudi system. It came in an introduction and four demands and a conclusion of the most important results, then a list of the most important sources and references, in which I presented: A brief study on the issuance of regulations in the Kingdom of Saudi Arabia and the stages that they pass through, their validity and application, and the rules that govern this system in terms of people, places and times, then canceling and amending regulations And its rulings, I referred to it to the original sources approved in this section,

     The earth's surface comprises different kinds of land cover, water resources, and soil, which create environmental factors for varied animals, plants, and humans. Knowing the significant effects of land cover is crucial for long-term development, climate change modeling, and preserving ecosystems. In this research, the Google Earth Engine platform and freely available Landsat imagery were used to investigate the impact of the expansion and degradation in urbanized areas, watersheds, and vegetative cover on the land surface temperature in Baghdad from 2004 to 2021. Land cover indices such as the Normalized Difference Vegetation Index, Normalized Difference Water Index, and Normalized Difference Built-up Index (NDVI, NDWI, an

The problem of Multicollinearity is one of the most common problems, which deal to a large extent with the internal correlation between explanatory variables. This problem is especially Appear in economics and applied research, The problem of Multicollinearity has a negative effect on the regression model, such as oversized variance degree and estimation of parameters that are unstable when we use the Least Square Method ( OLS), Therefore, other methods were used to estimate the parameters of the negative binomial model, including the estimated Ridge Regression Method and the Liu type estimator, The negative binomial regression model is a nonline

Staphylococci are common commensals in human beings, yet certain species are pathogenic. Staphylococcus aureus, particularly, is a very virulent human pathogen. The capacity of staphylococci to sense the density of bacterial cell, i.e., quorum, and thereafter respond via genetic modifications is attributable to one primary mechanism known as accessory gene regulator (Agr). Agr's extracellular signal is a peptide that is posttranslationally modified with a thiolactone molecule. Agr is in charge of the upregulation of numerous exotoxins and hydrolyzing enzymes, as well as the downregulation of many colonization determinants, under circumstances of high cell density. This modulation is critical for the scheduling synthesis of virul

Cement-based adhesive (CBA) is used as a bonding agent in Carbon Fibre Reinforced Polymer (CFRP) applications as an alternative to epoxy-based adhesive due to the drawbacks of the epoxy system under severe service conditions which negatively affect the bond between the CFRP and strengthened elements. This paper reports the results of, an investigation carried out to develop two types of CBA using magnetized water (MW) for mixing and curing. Two magnetic devices (MD-I and MD-II), with different magnetic field strengths (9000 and 6000 Gauss) respectively, were employed for water magnetization. Different water flows with different water circulation times in the magnetizer were used for each device. Compressive and splitting tensile strength te

This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med