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ROLE OF SERUM ZINC AND COPPER AND ZINC/ COPPER RATIO IN ALOPECIA AREATA
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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.

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Publication Date
Wed May 26 2021
Journal Name
Energies
Rotational Piezoelectric Energy Harvesting: A Comprehensive Review on Excitation Elements, Designs, and Performances
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Rotational Piezoelectric Energy Harvesting (RPZTEH) is widely used due to mechanical rotational input power availability in industrial and natural environments. This paper reviews the recent studies and research in RPZTEH based on its excitation elements and design and their influence on performance. It presents different groups for comparison according to their mechanical inputs and applications, such as fluid (air or water) movement, human motion, rotational vehicle tires, and other rotational operational principal including gears. The work emphasises the discussion of different types of excitations elements, such as mass weight, magnetic force, gravity force, centrifugal force, gears teeth, and impact force, to show their effect

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Publication Date
Wed May 18 2016
Journal Name
Al-academy
Stereotactic and its association with cognitive performance career: صلاح نوري محمود - ظبية محمد
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The importance of this study of the growing importance of perception of touch and its association with the job performance of industrial product since the perception stereotactic means he means practiced by the individual through job performance and has assets of knowledge in the mind of the user and require him to mind the capabilities and knowledge cognitive following their individual focus Zhennea.oanfalh following their enthusiasm when using Sense of touch. The study in the first chapter of the research problem to reveal the role played by the process of cognition and its relationship with the touch function of the industrial product and the associated defect in performance and harder to use. The study also pointed to the research ob

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Industrial And Engineering Chemistry
Petroleum refinery wastewater treatment using a novel combined electro-Fenton and photocatalytic process
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Publication Date
Sat Jul 06 2024
Journal Name
Multimedia Tools And Applications
Text classification based on optimization feature selection methods: a review and future directions
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A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

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Publication Date
Wed Aug 28 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

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Publication Date
Wed Aug 28 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

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Publication Date
Tue May 04 2021
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
Tactical thinking and its relationship with solving mathematical problems among mathematics department students
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This research aims to know the essence of the correlative relationship between tactical thinking and solving mathematical problems. The researchers followed the descriptive research method to analyze relations, as all students from the mathematics department in the morning study were part of the research group. The research sample of (100) male and female students has been chosen based on the arbitrators' views. The tools for studying the sample of research composed of (12) items of the multiple-choice test in its final form to measure tactical thinking and require establish-ing a test of (6) test-type paragraphs to solve mathematical problems. The findings showed that sample students' tactical thinking and their capacity to overcome mathem

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Publication Date
Sun Aug 08 2021
Journal Name
Proceedings Of International Conference On Emerging Technologies And Intelligent Systems
Drone Altitude Control Using Proportional Integral Derivative Technique and Recycled Carbon Fiber Structure
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Publication Date
Thu Jun 01 2023
Journal Name
2023 Ieee 36th International Symposium On Computer-based Medical Systems (cbms)
Toward a Minimal sEMG Setup for Knee and Ankle Kinematic Estimation during Gait
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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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