have suffered from deteriorating residential neighborhoods, poor economic, social and urban living conditions of the population and deteriorating the infrastructural and superior services. These problems were the secretions of these cities' rapid urbanization. Based on the principles of sustainable urban planning and in order to achieve adequate opportunities for the lives of the population and provide them with sustainable livelihoods, policies have emerged to upgrade along the lines of community participation and programmes to reform and develop those neighbourhoods, raise their efficiency and make them livable. Thus, the problem of research was identified "The absence of a comprehensive cognitive perception of the most prominent factors influencing community participation and its role in upgrading degraded neighborhoods". Accordingly, the research objective was set to activate community participation mechanisms to identify the most important factors influencing community participation and their impact on the development of degraded residential areas. While the main research hypothesis is (There are a range of factors influencing the activation of community participation to upgrade degraded residential areas). On one hand, the research included a theoretical aspect addressing the concept of community participation, the factors affecting it, the importance, objectives, benefits and patterns of community participation, and the concept, types and characteristics of degraded residential areas. On the other hand, the practical aspect included studying Imam district in Nasiriyah, where a questionnaire was conducted for a sample of residents in the neighborhood. The practical aspect included the study of Imam neighbourhood area of Nasiriyah, where a questionnaire was conducted for a sample of residents in the neighbourhood. The research, using the logistical regression model, found that stimulating the desire to participate through advisory and consultation has a moral and positive effect in activating community participation. In addition, empowering the community through their participation in workshops and training contributes to job creation, reducing unemployment and enabling participation in the upgrading of the residential area.The research also found that there were other influential factors but that their impact was not moral such as sex, age, length of stay, property and trust in the local authority. The research concluded that upgrading degraded residential areas can be done by engaging individuals and increasing their desire to develop their neighborhoods. Also, by social development and social inclusion through workshops, consultation and training in order to enhance their skills and enhance their participation in achieving the goal of improving urban and living standards.
The study aimed to assess the level of ANG‑2 in MM patients at diagnosis and in remission state and elaborate on its correlation with interleukin‑6 (IL‑6) and beta‑2 microglobulin (B2M) levels. Sixty MM patients; 20 newly diagnosed (ND), and 40 patients in remission were included. Twenty healthy individuals were included as a control group. Plasma levels of ANG‑2, B2M, and IL‑6 were tested by enzyme‑lin ked immunosorbent assay. There are significant statistical differences between ND patients and those in remission in hemoglobin, neutrophil count, blood urea, serum creatinine, glomerular filtration rate, B2M, IL6, and ANG‑2 (P = 0.001, 0.033, 0.005, 0.001, 0.001, 0.001, 0.004, and 0.001, respectively). ANG‑2 showed signifi
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The study aimed to analyze the effect of meteorological factors (rainfall rate and temperature) on the change in land use in the marshes of the Al‐Majar Al‐Kabir region in southern Iraq. Satellite images from Landsat 7 for 2012 and Landsat 8 for 2022 were used to monitor changes in the land coverings, the images taken from the Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) sensors of the Landsat satellite. Geometric correction was used to convert images into a format with precise geographic coordinates using ArcMap 10.5. The maximum likelihood classification method was used to examine satellite image data using a supervised approach, and the data were analyzed statistically. We obtained clear images of the area,
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Diabetic neuropathy is a form of nerve damage that can occur in people who have diabetes. High blood sugar (glucose) induced nerve damage in every part of the body. The nerves in the legs and feet were the most frequently affected. The extent to which a diabetic patient's body is impaired is calculated by the degree of nervosa harm.The purpose of this present study is estimation BMI,IL-10 , nesfatin-1 and HS-CRP in Iraqi DN patients before and after treatment via tegretol as well as it is the first study sheds light on the relationship between Nesfatin -1 and other parameters ( BMI,IL-10 and HS-CRP) also predication of Nesfatin-1 as a newly biomarker in patients with diabetic neuropathy. The present study consist of from 30 cohort G1 as hea
... Show MoreBackground: Oral squamous cell carcinoma is the most prevalent malignant neoplasm of the oral cavity which results from accumulated genetic and epigenetic alterations. It is not always inexorable and may be reversible if early intervention in the process can occur to prevent further genetic mutation and disease progression. The FHIT gene is a tumor suppressor gene located in FRA3B region which is the most active common fragile site, where DNA damage leading to aberrant transcripts and translocations frequently occur. The WWOX is a tumor suppressor gene that plays a central role in tumor suppression through transcriptional repression and apoptosis, with its apoptotic function the more prominent of the two. This study aimed to evaluate and co
... Show MoreAn essential issue in obstetrics is the prevalence of maternal and fetal complications in pregnant women with polycystic ovary syndrome (PCOS). The purpose of the present study was to investigate the prevalence of pregnancy complications among various phenotypes of pregnant women with PCOS.
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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Background: Pulpotomy is an accepted treatment for the management of cariously exposed pulps in symptom free primary molars to achieve one of the most important goals for Pedodontists, which is the retention of the pulpally involved deciduous teeth healthy until the time of normal exfoliation. The purpose of this study was to evaluate the relative success of pulpotec, formocresol and Mineral Trioxide Aggregate (MTA) in cariously exposed primary molar teeth, using clinical and radiographical examinations. Materials and methods: Thirty nine children with 45 primary molars requiring pulpotomy were selected in this study, 15 teeth treated by each type of pulpotomy medicament. Clinical and radiographical follow up for the patients was performed
... Show MoreIn this investigation, the mechanical properties and microstructure of Metal Matrix Composites (MMCs) of Al.6061 alloy reinforced by ceramic materials SiC and Al2O3 with different additive percentages 2.5, 5, 7.5, and 10 wt.% for the particle size of 53 µm are studied. Metal matrix composites were prepared by stir casting using vortex technique and then treated thermally by solution heat treatment at 530 0C for 1 hr. and followed by aging at 175 0C with different periods. Mechanical tests were done for the samples before and after heat treatment, such as impact test, hardness test, and tensile test. Also, the microstructure of the metal matrix composites was examine
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr
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