This study aimed to determine the nickel (Ni), and chromium (Cr) ions amounts and investigate their potential effects on thyroid hormones in patients' saliva who were receiving treatment with fixed orthodontic appliances (FOA). In this study, 42 FOA volunteers participated, and all samples were obtained from a specialized center for manufacturing and orthodontics in Bab Al-Moadham, Baghdad, Iraq. According to the findings, individuals with fixed orthodontics have significantly higher levels of the thyroid hormones (P<0.05) FT3 and FT4 than those who did not have orthodontic treatment, whereas there were no significant changes in TSH (P=0.599). Additionally, the amounts of Ni+2 and Cr+3 were considerably higher in the individuals receiving metallic orthodontic treatment (P <0.0001). The findings of this investigation support the hypothesis that corrosion metals from the FOA have a meaningful impact on the concentration of Ni and Cr ions and, consequently, on the thyroid and salivary functioning of the patient group.
Urban agriculture is one of the important urban uses of land in cities since the inception of cities and civilizations, but the great expansion of cities in the world during the twentieth century and the beginning of the twentieth century and the increase in the number of urban residents compared to the rural population has led to a decline in this use in favor of other uses.
This decline in agricultural and green land areas in cities has negatively affected the environment, natural life and biological diversity in cities in addition to the great impact on the climate and the increase in temperatures and the negative impact on the economic side, since urban agriculture is an important pillar of the economy, especially
... Show MoreSeventy exudative lymphocytic pleural fluid specimens of patients with suspected tuberculous pleural effusion submitted to the National Reference Laboratory of tuberculosis/Baghdad from October 2012 to February 2013. These effusions were due to tuberculosis pleuritis (n=12) and non-tuberculosis pleuritis (n=58). The following parameters were analyzed: protein concentration, glucose concentration, lactate dehydrogenase (LDH) concentration and adenosine deaminase activity (ADA). As a result, the protein concentration was higher in TPE patients (8.80 ± 0.89 g/dl) than it's concentration in non-TPE patients (7.61 ± 0.54 g/dl), as well as LDH concentration was (3366.58 ± 284.28 U/L) in TPE patients and (3024.12 ± 116.84 U/L) in non-TPE pa
... Show MoreData security is a significant requirement in our time. As a result of the rapid development of unsecured computer networks, the personal data should be protected from unauthorized persons and as a result of exposure AES algorithm is subjected to theoretical attacks such as linear attacks, differential attacks, and practical attacks such as brute force attack these types of attacks are mainly directed at the S-BOX and since the S-BOX table in the algorithm is static and no dynamic so this is a major weakness for the S-BOX table, the algorithm should be improved to be impervious to future dialects that attempt to analyse and break the algorithm in order to remove these weakness points, Will be generated dynamic substitution box (S-B
... Show MoreOffline Arabic handwritten recognition lies in a major field of challenge due to the changing styles of writing from one individual to another. It is difficult to recognize the Arabic handwritten because of the same appearance of the different characters. In this paper a proposed method for Offline Arabic handwritten recognition. The proposed method for recognition hand-written Arabic word without segmentation to sub letters based on feature extraction scale invariant feature transform (SIFT) and support vector machines (SVMs) to enhance the recognition accuracy. The proposed method experimented using (AHDB) database. The experiment result show (99.08) recognition rate.
Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq
... Show MoreIn computer vision, visual object tracking is a significant task for monitoring
applications. Tracking of object type is a matching trouble. In object tracking, one
main difficulty is to select features and build models which are convenient for
distinguishing and tracing the target. The suggested system for continuous features
descriptor and matching in video has three steps. Firstly, apply wavelet transform on
image using Haar filter. Secondly interest points were detected from wavelet image
using features from accelerated segment test (FAST) corner detection. Thirdly those
points were descripted using Speeded Up Robust Features (SURF). The algorithm
of Speeded Up Robust Features (SURF) has been employed and impl
A proposed feature extraction algorithm for handwriting Arabic words. The proposed method uses a 4 levels discrete wavelet transform (DWT) on binary image. sliding window on wavelet space and computes the stander derivation for each window. The extracted features were classified with multiple Support Vector Machine (SVM) classifiers. The proposed method simulated with a proposed data set from different writers. The experimental results of the simulation show 94.44% recognition rate.
This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength. This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.
Moreover, the proposed controller i
... Show MoreThis paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to
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