Abstract
        The research has discussed the public relations as dependent variable of its branch dimensions( confidence , commitment, control and satisfaction ) and the governmental service quality as independent variable of its branch dimensions (response, dependency, emphasis, tangibility and sympathy), and the research problem has represented by weakness of service quality presented to the customers dealing with company, which is observed via  field co-existence of the researcher, where he observe that the quality presented in the company services, are inappropriate with the customers expectations level, also there is weakness of attention and recognition by the

Kinetic and mechanism studies of the oxidation of oxalic acid by Cerium sulphate have been carried out in acid medium sulphuric acid. The uv- vis. Spectrophotometric technique was used to follow up the reaction and the selected wavelength to be followed was 320 nm. The kinetic study showed that the order of reaction is first order in Ce(IV) and fractional in oxalic acid. The effect of using different concentration of sulphuric acid on the rate of the reaction has been studied a and it was found that the rate decreased with increasing the acid concentration. Classical organic tests was used to identify the product of the oxidation reaction, the product was just bubbles of CO2.

The current research aims to identify "the impact of the round table strategies and the question of self-achievement and self-efficacy among students of the Faculty of Education in research methodology course.” The research sample consisted of (75) male and female-third stage students in the department of Life Sciences / College of Education for Pure Sciences / University of Dhi Qar for the academic year (2018-2019. The researcher adopted the experimental approach to achieving the study objectives. The researcher prepared two tools: the achievement test and the self-efficacy scale were applied to the collected sample to obtain the needed data. The result showed that there was a statistically significant difference at the level (0.05) b

thirty adult NewZealand rabbits used in this study, they were divided in to two groups (control and treaded with Helium — Neon laser). A square skin flap done on the medial aspect of the auricle of both sides, a square piece of cartilage incised, pealed out from each auricle and fixed in the site of the other, then the flaps sutured .The site of the operation in the rabbits of the treated group were irradiated using a Helium —Neon laser with (5mw) power for (10 days) began after the operation directly, (3 rabbits) from each group used for collection of specimens for histopathological examination at the weeks (1,2,3,4, & 6) weeks post the operation .The results revealed Early invasion of the matrix with elastic fibers which continue to t

Due to the easily access to the satellite images, Google Earth (GE) images have become more popular than other online virtual globes. However, the popularity of GE is not an indication of its accuracy. A considerable amount of literature has been published on evaluating the positional accuracy of GE data; however there are few studies which have investigated the subject of improving the GE accuracy. In this paper, a practical method for enhancing the horizontal positional accuracy of GE is suggested by establishing ten reference points, in University of Baghdad main campus, using different Global Navigation Satellite System (GNSS) observation techniques: Rapid Static, Post-Processing Kinematic, and Network. Then, the GE image for the study

This paper introduces an innovative method for image encryption called "Two-Fold Cryptography," which leverages the Henon map in a dual-layer encryption framework. By applying two distinct encryption processes, this approach offers enhanced security for images. Key parameters generated by the Henon map dynamically shape both stages of encryption, creating a sophisticated and robust security system. The findings reveal that Two-Fold Cryptography provides a notable improvement in image protection, outperforming traditional single-layer encryption techniques.

Antimicrobial resistance is one of the most significant threats to public health worldwide. As opposed to using traditional antibiotics, which are effective against diseases that are multidrug-resistant, it is vital to concentrate on the most innovative antibacterial compounds. These innate bacterial arsenals under the term «bacteriocins» refer to low-molecularweight, heat-stable, membrane-active, proteolytically degradable, and pore-forming cationic peptides. Due to their ability to attack bacteria, viruses, fungi, and biofilm, bacteriocins appear to be the most promising, currently accessible alternative for addressing the antimicrobial resistance (AMR) problem and minimizing the negative effects of antibiotics on the host’s m

The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

Ifosfamide (IFO), an alkylating chemotherapy agent, is known for its association with neurotoxicity and encephalopathy. This trial was designed to evaluate the protective action of daidzein (DZN) against IFO-induced neurotoxicity in male rats by determining the difference in certain inflammatory and apoptotic markers in the brain tissue of rats. Twenty-eight Wistar rats, weighing 120-150 g, were divided into four groups of seven rats: Group 1 (Control) received no treatment; Group 2 was orally administered DZN (100 mg/kg/day) for seven days; Group 3 received a single intraperitoneal (IP) dose of IFO (500 mg/kg); Group 4 received oral DZN (100 mg/kg/day) for one week prior to a single IP dose of IFO on the seventh day. Twenty-four hours post