This research for university students dialectic unemployment and work, focusing on
serious discussion, accurate and provide opinions between specialists and those interested in
the university youth issues and identify them in the light of the dialectical relationship
between unemployment and work for the purpose interpreted accurate and access to reality
without coverage and linked to the movement of the changing society now and the situation
that is happening in Iraq, where the loss of the safety and the weakness of the determinants of
economic well-being and the decline of public and social health and the unemployment rate
security in the heart of - programs - and blocs parties that Tgtill public opinion in any
electoral campaign, where is the unemployment of assessing countries standards whether
advanced or well-developed or undeveloped or developing, and in We discussed that we
address this problem faced by university students after graduation and that adversely affect
their lives and their futures and their families and to hide the one that the unemployment rate
had reached dangerous levels exceed Sometimes the expectation levels and perception,
especially after the recent security events that swept the Iraqi society, but we must mention in
this area that young people are slide adopted in the progress and development of society
through endurance construction responsibility, reconstruction and development as they Imadsociety and that delaying work will deprive society of manpower could evolution, to develop
a society that is in dire need of these youth forces for development and advancement in the
areas of social and economic life and cultural all, particularly in a society exposed to the
problems of many pressures such as the Iraqi society, based on the foregoing has included
search several sections we are embarking upon head-ends findings and recommendations,
which included the first part, the methodological framework of the research, which consists of
the research problem and its importance, objectives and determine the concepts of scientific
and social terms, either topic the second may be from previous studies, and the third section to
ensure the causes of youth unemployment and the effects resulting from it. As for the fourth
topic Vttrq to economic and social problems of unemployment and where the dialectic of
work and its impact economically then touched on the problem of leisure and how exploited
by the students (young people).
As for the fifth topic it dealt with the field study in terms of the application of
appropriate curriculum and identify the areas of research, and finally the sixth section
contains the most important proposals and recommendations and the results of which provide
the necessary solutions to the problem of reducing unemployment.
This study presents, for the first time, an innovative Jet Plasma-assisted technique for the green synthesis of TiO₂@Ag core–shell nanoparticles using chard leaf extract as a natural reducing and stabilizing agent. The Jet Plasma provides a highly energetic environment that accelerates nucleation and core–shell formation at low temperatures without toxic precursors. The synthesized nanoparticles exhibited uniform and stable structures, as confirmed by comprehensive characterization techniques including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), ultraviolet–visible (UV–Vis) spectroscopy, transmission electron microscopy (TEM), and zeta potential analysis. XRD patterns confirmed the crystalline anatase
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The purpose of this study was to measure serum levels of insulin-like growth factor-binding protein (IGFBP7), Insulin-like Growth Factor 1 (IGF-1), Growth Hormone (GH), Interleukin 6 (IL-6) and insulin in acromegaly patients and healthy controls. The acromegaly group had 60 patients, while the population group had 30 people who had never had acromegaly before. The concentration of IGFBP7, IGF-1, GH, IL-6, and insulin were determined. The results of the present study indicate that IGFBP7 level in the acromegaly group was significantly lower (1.690.07 ng/mL vs. 2.740.12 ng/mL, respectively, p = 0.001). IGF-1, GH, IL-6, and insulin concentrations were also significantly higher in acromegaly patients. The diagnostic accuracy (2.194) was exce
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Release of industrial effluents comprising dyes in water bodies is one of the foremost causes of water pollution. Therefore, the proper and proficient treatment of these dyes contaminated left-over material before their release is crucial. Herein, an eco-friendly biological macromolecule Gum-Acacia (GA) integrated Fe3O4 nanoparticles composite hydrogel was manufactured via co-precipitation technique for effective adsorption of Congo red (CR) dye existing in water bodies. The as-prepared magnetic GA/Fe3O4 composite hydrogel was characterized by FTIR, XRD, EDX, VSM, SEM, and BET techniques. These studies discovered the fruitful fabrication of biodegradable magnetic GA/Fe3O4 composite hydrogel possessing porous structure with large surface are
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This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining
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Background/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to
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KE Sharquie, HR Al-Hamamy, AA Noaimi, AF Tahir, Journal of Cosmetics, Dermatological Sciences and Applications, 2012 - Cited by 2