Background: This study aimed to assess the effect of tooth shape ratio on mandibular incisor arrangement. Materials and methods: The sample included dental casts of some dental students and orthodontic patients having Class I dental and skeletal patterns with normal occlusion and severe crowding. The sample was divided into two groups according to the severity of crowding into: group I had Class I normal occlusion with mild or no crowded mandibular dentition and group II had Class I malocclusion with severe crowded mandibular dentition. Each group comprising of 40 subjects (20 males and 20 females). The mesio-distal and facio-lingual crown diameters were measured manually for each cast using modified vernier caliper gauge. Descriptive statistics were obtained for the measurements for both genders; independent samples t-test was performed to evaluate the gender difference in each group and to evaluate the groups' difference in total sample. Results and Conclusions: The results showed that there is non-significant genders difference in both groups. Generally, the mesio-distal and facio-lingual dimensions were higher in severely crowded mandibular incisor group. Neither facio-lingual dimension nor the tooth shape ratio has significant influence of the mandibular incisor arrangement and the mesio-distal dimension is the most important factor.
III-V zinc-blende AlP, AlAs semiconductors and their alloy Aluminum Arsenide phosphide Al AsxP1-x ternary nanocrystals have been investigated using Ab- initio density functional theory (Ab-initio-DFT) at the generalized-gradient approximation (GGA) level with STO-3G basis set coupled with large unit cell method (LUC). The dimension of crystal is found around (1.56 – 2.24) nm at a function of increasing the sizes (8, 16, 54, 64) with different concentration of arsenide (x=0, 0.25, 0.5, 0.75 and 1) respectively. Gaussian 03 code program has been used throughout this study to calculate some of the physical properties such as the electronic properties energy gap, lattice constant, valence and conduction band as well as density of state. Re
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This study was aimed to investigat integrated system for in vitro growth of paulownia plants by assessing the efficacy of chlorine dioxide (ClO2) as an alternative to autoclave in sterilizing culture medium. Therefore, this study was devised to compare autoclave sterilization at three different times (5, 10, and 15) minutes and three different concentrations of ClO2 (0, 0.4, 0,8, 1) mg/L. The results showed that, compared with (0.4) mg/L concentration, concentrations of (0.8 and 1) mg/L are more effective at sterilizing the culture medium. ClO2 sterilization improved individual single node growth more than autoclave sterilization. Since ClO2 is non-toxic, it could be used as a safe alternative to autoclave when propagating paulown
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Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio
In the present work advanced oxidation process, photo-Fenton (UV/H2O2/Fe+2) system, for the treatment of wastewater contaminated with oil was investigated. The reaction was influenced by the input concentration of hydrogen peroxide H2O2, the initial amount of the iron catalyst Fe+2, pH, temperature and the concentration of oil in the wastewater. The removal efficiency for the system UV/ H2O2/Fe+2 at the optimal conditions and dosage (H2O2 = 400mg/L, Fe+2 = 40mg/L, pH=3, temperature =30o C) for 1000mg/L load was found to be 72%.
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration
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This case series aims to evaluate patients affected with post COVID‐19 mucormycosis from clinical presentation to surgical and pharmacological treatment to improve the disease prognosis.
This case series was conducted at a specialized surgery hospital in Baghdad Medical City for over 10 months. Fifteen cases who had mild to severe COVID‐19 infections followed by symptoms similar to aggressive periodontitis, such as mobility and bone resorption around the multiple maxillary teeth, were included in this case series.
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