The exchanges in various fields,like economics, science, culture, etc., have been enhanced unceasingly among different countries around the world in the twenty-first century, thus, the university graduate who masters one foreign language does not meet the need of the labor market in most countries.So, many universities began to develop new programs to cultivate students who can use more foreign languages to serve the intercultural communication. At the same time, there is more scientific research emerged which is related to the relationship between the second and third languages. This humble research seeks to explain the relevant concepts and analyze the real data collected from Shanghai International Studies University in China, to explore this relationship transparently in front of readers and provide recommendations for non-native speakers,especially Chinese learners. Additionally, as a sample study, it aims to serve other researchers and future studies as well.The research results will be produced according to the quantitative and qualitative analyses at the same timeto guarantee the objectivity and validity of the data. As for the part of the qualitative analysis, the paper will explain some related concepts generated in the western world, including their characteristics, benefits, and differences. As for the part of the quantitative analysis, it will refer to the statistics program SPSS. Then, it will produce relevant data with drawings and tables. Lastly, it will clarify the meanings of those data and the relationships among them.
تتميز اللغات باصواتها التي تميزها من غيرها, ولكل لغة اصواتها التي تختلف نوعا وكما , يبدو ان هناك اصواتا تتشابه في اغلب اللغات تلك هي الاصوات الصائتة او الصوائت (الالف والواو والياء) والاصوات المائعة او السائلة وما يطلق عليه (Liquids) وهي الاصوات المتوسطة بين الشدة والرخاوة , يضاف الى هاتين المجموعتين صوت اللغة , الصوت الشائع في اغلب اللغات , وقد علل سبب هذا الشيوع الى انه الصوت الاساس لصيحات الانفعال التلقائية عند ا
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Background: Repeated teenage pregnancy is a major burden on the healthcare system worldwide. Objective: We aimed to compare teenagers with their first and third pregnancies and to evaluate the likelihood of neonatal complications. Materials and Methods: This cross-sectional study was performed on female teenagers (aged ≤ 19 yr) with singleton pregnancies. The subjects (n = 298) were screened over 12 months. Ninety-six women were excluded, based on the exclusion criteria. The remaining subjects (n = 202) were divided into two groups: teenagers with first pregnancy (n = 96) and teenagers with third pregnancy (n = 47). The subjects were observed throughout pregnancy and delivery. The final sample size of the first and thi
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— To identify the effect of deep learning strategy on mathematics achievement and practical intelligence among secondary school students during the 2022/2023 academic year. In the research, the experimental research method with two groups (experimental and control) with a post-test were adopted. The research community is represented by the female students of the fifth scientific grade from the first Karkh Education Directorate. (61) female students were intentionally chosen, and they were divided into two groups: an experimental group (30) students who were taught according to the proposed strategy, and a control group (31) students who were taught according to the usual method. For the purpose of collecting data for the experimen
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t
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Abstract Background Deep learning (DL) has attracted increasing attention in orthodontics, with many studies reporting high diagnostic and predictive accuracy. However, despite these promising results, routine clinical adoption remains limited. Objectives This scoping review aimed to explore the main barriers that restrict the translation of DL systems from research environments into everyday orthodontic practice. Methodology The review was conducted in accordance with PRISMA-ScR guidelines. Electronic searches were performed in PubMed, Scopus, Web of Science, and IEEE Xplore for English-language studies published between 2015 and June 2025. Studies reporting quantitative performance of DL-based orthodontic applications were included. Dat
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