Recently, Social Sustainability has gained significant value as it was considered by the late studies as a principal dimension along with the environmental and economic sustainability. And because of, on the other hand, the significant social role of the school for forming the student’s personality, this research is an appeal for rehabilitating and promoting Iraqi Schools according the issue of social sustainability.As there is no evaluation for the Iraqi Schools, the research is dedicated to this problem, aiming to carry out the stated evaluation and define the design treatments needed for the rehabilitation process. To achieve this goal, a theoretical background for the concept of social sustainability, its criteria, the school and its social functions was introduced. From reviewing previous architectural practices and theoretical studies, different design treatments were extracted and structured within the level of the building itself and the outside landscape. The design treatments were, then, applied to rehabilitate a selected standard school model used by the Directorate of Education in Nineveh Governorate. Evaluating the proposed model, the conclusions demonstrated the possibility of rehabilitating the existing Iraqi Schools to hold most indicators of social sustainability
After baking the flour, azodicarbonamide, an approved food additive, can be converted into carcinogenic semicarbazide hydrochloride (SEM) and biurea in flour products. Thus, determine SEM in commercial bread products is become mandatory and need to be performed. Therefore, two accurate, precision, simple and economics colorimetric methods have been developed for the visual detection and quantitative determination of SEM in commercial flour products. The 1st method is based on the formation of a blue-coloured product with λmax at 690 nm as a result of a reaction between the SEM and potassium ferrocyanide in an acidic medium (pH 6.0). In the 2nd method, a brownish-green colored product is formed due to the reaction between the SEM and phosph
... Show MoreThis research was aimed to study the exposure of Razzazah Lake to major hydrological changes in recent years as a result of natural climatic changes and drought, high evaporation in lake due to stop discharge from Habbaniyah Lake by Al- majera channel. During 2019, we collected surface water samples at three locations, and three samples from groundwater, in addition one samples from each location Imam Ali Drop and Sewage water of Karbala. The Results show that the heavy isotopes in lake and groundwater well are enriched during the warm period, and depleted during the cold period. Chemically, The dominant cations and anions in Al-Razzaza lake water are mainly of in Order Ca > Na > Mg and Cl>SO4 and the water
... Show MoreIn this study, thin film of pure zinc oxide (ZnO) and ZnO doped with Ga2O3 films with different concentrations (0, 0.03, 0.05, 0.07 and 0.09)wt% were prepared by pulsed laser deposition. The powder mixture was then sintered in a furnace at 1273 K for 5 h. The resulting powders were thoroughly ground and then pressed using a special press to form discs with a diameter of 1 cm and a thickness of 0.5 cm. The deposition was carried out under a vacuum of 2.5×10−2 mbar on various substrates, including glass for AFM measurements and n-type crystalline silicon wafers for the gas sensor. AFM results revealed a progressive increase in both grain size and roughness with moderate doping and irregularity at high doping levels. Gas-sensing meas
... Show MoreBackground/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to
... Show MoreWhile conservative access preparations could increase fracture resistance of endodontically treated teeth, it may influence the shape of the prepared root canal. The aim of this study was to compare the prepared canal transportation and centering ability after continuous rotation or reciprocation instrumentation in teeth accessed through traditional or conservative endodontic cavities by using cone-beam computed tomography (CBCT).
Forty extracted intact, matured, and 2-rooted human maxillary first premolars were selected for this
Metabolic syndrome has emerged as an important health concern globally, especially in developing countries where urbanization and lifestyle changes are rapidly increasing. No reliable epidemiological information regarding the prevalence and risk factors associated with metabolic syndrome is available among Iraqi adults in primary health care (PHC) clinics. This study was designed to determine the prevalence rate of metabolic syndrome and identify potential risk factors among adults attending PHC centers in Baghdad. Methods: An analytical cross-sectional study design was used, targeting 412 adult subjects selected randomly from multiple PHC centers in Baghdad. Sociodemographic, lifestyle, anthropometric, and biochemical data were col
... Show MoreThe research includes preparation of a new Schiff base from the condensation of sulfonic acid with 2-phthalaldehyde by dissolving (0.2 g, 0.346 mmole) of the ligand (L) in (10 ml) of absolute ethanol, then 0.06 g of potassium hydroxide (KOH) dissolved in 10 ml of distilled water added to it and reacting the product with some binary metal salts (Mn, Co, Ni, Cu, Cd, Zn, Pt, Hg). The biological study was conducted against two types of gram-positive and gram-negative bacteria, Staphylococcus. aureus and Escherichia coli, and the fungus Candida albicans was also used. All the prepared complexes showed higher activity against bacteria and fungi than the ligand for the free Schiff base. The total antioxidant content of the ligand and the c
... Show MoreThis 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
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