Considering the magnitude of its economic, social and political impact, unemployment represents a crucial challenge confronting the majority of the countries of the world. The problem of the study was the high rates of unemployment in Sudan and the inability of economic growth rates to keep pace with the steady increases in unemployment rates during the study period. This study aimed to identify the economic and social variables influencing unemployment rate in Sudan, in addition to measuring the impact of these variables over the period (1981-2015). Data were collected from databases of the World Bank and Atlas of the World's data .The study hypothesized the presence of statistically significant and direct relationship between u

يهدف هذا البحث الى عرض رؤيا تشخصيه لمجتمع المعرفة في ظل اقتصاد المعرفة من خلال استعراض العديد من المفاهيم النظرية والعلاقة بينهم كمفهوم البيانات والمعلومات والمعرفة ومجتمع المعلومات والمعرفة, ومصادر المعرفة, والمراحل التطورية للتحول الى مجتمع المعرفة, ومن ثم استعراض الأبعاد الأساسية لمجتمع المعرفة, إضافة إلى الملامح الأساسية لاقتصاد المعرفة وخصائص ذلك الاقتصاد, ثم تناول البحث المورد المعرفي وعلاقته

At the end of 2019, a new form of Coronavirus (later dubbed COVID-19) emerged in China and quickly spread to other regions of the globe. Despite the virus’s unique and unknown characteristics, it is a widely distributed infectious illness. Finding the geographical distribution of the virus transmission is therefore critical for epidemiologists and governments in order to respond to the illness epidemic rapidly and effectively. Understanding the dynamics of COVID-19’s spatial distribution can help to understand the pandemic’s scope and effects, as well as decision-making, planning, and community action aimed at preventing transmission. The main focus of this study is to investigate the geographic patterns of COVID-19 disseminat

By March 2020, a pandemic had been emerged Corona Virus Infection in 2019 (COVID-19), which was triggered through the sensitive pulmonary syndrome (SARS disease corona virus- 2 (SARS COV-2). Overall precise path physiology of SARS COV-2 still unknown, as does the involvement of every element of the acute or adaptable immunity systems. Additionally, evidence from additional corona virus groups, including SARS COV as well as the Middle East pulmonary disease, besides that, fresh discoveries might help researchers fully comprehend SARS CoV-2. Toll-like receptors (TLRs) serve a critical part in both detection of viral particles as well as the stimulation of the body's immune response. When TLR systems are activated, pro-inflammatory cy

BACKGROUND: Coronavirus current pandemic (COVID-19) is the striking subject worldwide hitting countries in an unexplained non-universal pattern. Bacillus Calmette–Guérin (BCG) vaccine was an adopted recent justification depending on its non-specific immune activation properties. Still the problem of post-vaccine short duration of protection needs to be solved. The same protective mechanism was identified in active or latent tuberculosis (TB). For each single patient of active TB, there are about nine cases of asymptomatic latent TB apparently normal individuals living within the community without restrictions carrying benefits of immune activation and involved in re-infection cycles in an excellent example of repeated immunity tr

This research aims to investigate the approaches adopted by Iraqi newspapers in addressing the COVID-19 pandemic crisis. Employing a descriptive methodology and survey technique, the study conducts content analysis on articles published in three prominent newspapers: Al-Sabah, Al-Mada, and Tareeq Al-Shaab. A multi-stage sampling method was employed, encompassing 260 issues of the aforementioned newspapers. Data collection involved the use of a content analysis questionnaire, with the "How it was said?" method utilized to determine analysis categories.
The results showed that Al-Sabah newspaper adopted a positive approach in addressing COVID-19-related topics, while Al-Mada newspaper remained neutral, and Tare

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

اشتمل هذا البحث على مقدمة البحث واهميته والاثر المهم للوسائل التدريبية اذ تجلت أهمية البحث في الوسائل المساعدة ودورها في تطوير أداء السلسلة الحركية على عارضة التوازن للطالبات مما يساعد في اختزال الوقت وتقليل الجهد المبذول وبناء قاعدة جيدة للمرحلة المقبلة وكذلك إيجاد انسب التمرينات وفق للوسيلة المساعدة المستخدمة وذلك لغرض تطوير المهارات الأساسية على عارضة التوازن في جمناستك الفني وحددت الباحثة مشكلة