Alopecia areata is considered as a major health problem, its importance is attributed to its
recent increased incidence in our population. Till now, there is no exact cause for alopecia areata
although researchers thought it's an autoimmune disease.
This clinical study was designed to evaluate the role of trace elements (zinc and copper) in patients
with alopecia areata. Twenty patients were diagnosed as having alopecia areata with an age range
(10-40 years) were involved in this study. Normal subjects of the same age group were also
evaluated as control. The level of serum Zn and Cu were measured by flame atomic absorption
spectrophotometry in both control and patient group. And the ratio of Zn/Cu was also estimated.
The results of patients group revealed that serum Zn level was significantly lower than those of
control (p<0.001), while serum Cu was significantly higher than that of control group (p=0.002).
Furthermore, Zn/Cu ratio of patients group was significantly lower than that of control subjects
(p<0.001). These results suggest the possible role of Zn and Cu level in alopecia areata. In addition
to that the utility of measuring Zn/ Cu ratios for the diagnosis of the disease over that of
determining the serum level of Zn or Cu alone since this ratio clearly reflects the severity of the
progress.
Leading edge serration is now a well-established and effective passive control device for the reduction of turbulence–leading edge interaction noise, and for the suppression of boundary layer separation at high angle of attack. It is envisaged that leading edge blowing could produce the same mechanisms as those produced by a serrated leading edge to enhance the aeroacoustics and aerodynamic performances of aerofoil. Aeroacoustically, injection of mass airflow from the leading edge (against the incoming turbulent flow) can be an effective mechanism to decrease the turbulence intensity, and/or alter the stagnation point. According to classical theory on the aerofoil leading edge noise, there is a potential for the leading edge blowi
... Show MoreDeep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to
... Show MoreConstruction contractors usually undertake multiple construction projects simultaneously. Such a situation involves sharing different types of resources, including monetary, equipment, and manpower, which may become a major challenge in many cases. In this study, the financial aspects of working on multiple projects at a time are addressed and investigated. The study considers dealing with financial shortages by proposing a multi-project scheduling optimization model for profit maximization, while minimizing the total project duration. Optimization genetic algorithm and finance-based scheduling are used to produce feasible schedules that balance the finance of activities at any time w
Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th
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