Background: The immune system of the oral cavity suffers alterations due to fixed orthodontic treatment which act as potent stimulus for oral secretory immunity. The aims of this study are to estimate the effect of fixed orthodontic appliance on the level of salivary sIgA at different time intervals, and to verify the gender difference. Materials and method: The patient's history, clinical examination, and fixed orthodontic appliances were placed for 30 Iraqi orthodontic adult patients had class II division 1 and/ or class I malocclusion (15 males and 15 females) aged 18-25 years old. The unstimulated whole saliva was collected from each sample immediately before wearing fixed appliance (control group T0 as base line), and after 2 weeks (T1
... Show MoreIn Baghdad city, Iraq, the traffic volumes have rapidly grown during the last 15 years. Road networks need to reevaluate and decide if they are operating properly or not regarding the increase in the number of vehicles. Al-Jadriyah intersection (a four-leg signalized intersection) and Kamal Junblat Square (a multi-lane roundabout), which are two important intersections in Baghdad city with high traffic volumes, were selected to be reevaluated by the SIDRA package in this research. Traffic volume and vehicle movement data were abstracted from videotapes by the Smart Traffic Analyzer (STA) Software. The performance measures include delay and LOS. The analysis results by SIDRA Intersection 8.0.1 show that the performance of the roundab
... Show MoreIn this work, analytical study for simulating a Fabry-Perot bistable etalon (F-P cavity) filled with a dispersive optimized nonlinear optical material (Kerr type) such as semiconductors Indium Antimonide (InSb). Because of a trade off between the etalon finesse values and driving terms, an optimization procedures have been done on the InSb etalon/CO laser parameters, using critical switching irradiance (Ic) via simulation systems of optimization procedures of optical cavity. in order to achieve the minimum switching power and faster switching time, the optimization parameters of the finesse values and driving terms on optical bistability and switching dynamics must be studied.
... Show MoreIn this work, the spirurid nematode Hartertia gallinarum was reported in the intestine of the spotted sandgrouse, Pterocles senegallus, collected in three different locations: Ga'ara Depression, Iraqi Western Desert, Zurbatiyah and Al-Attariyah, Middle of Iraq. Description and measurements of the nematode were given. The role of termites in the infection of P. senegallus with H. gallinarum was discussed. Occurrence of H. gallinarum in P. senegallus represents a new host record.
This study is unique in this field. It represents a mix of three branches of technology: photometry, spectroscopy, and image processing. The work treats the image by treating each pixel in the image based on its color, where the color means a specific wavelength on the RGB line; therefore, any image will have many wavelengths from all its pixels. The results of the study are specific and identify the elements on the nucleus’s surface of a comet, not only the details but also their mapping on the nucleus. The work considered 12 elements in two comets (Temple 1 and 67P/Churyumoy-Gerasimenko). The elements have strong emission lines in the visible range, which were recognized by our MATLAB program in the treatment of the image. The percen
... Show MoreCancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei
... Show MoreBinary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin
... Show MoreThe virtual decomposition control (VDC) is an efficient tool suitable to deal with the full-dynamics-based control problem of complex robots. However, the regressor-based adaptive control used by VDC to control every subsystem and to estimate the unknown parameters demands specific knowledge about the system physics. Therefore, in this paper, we focus on reorganizing the equation of the VDC for a serial chain manipulator using the adaptive function approximation technique (FAT) without needing specific system physics. The dynamic matrices of the dynamic equation of every subsystem (e.g. link and joint) are approximated by orthogonal functions due to the minimum approximation errors produced. The contr
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
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