Countries have faced the challenges of high levels of public debt and seek to define the optimum limits to reduce risks to which the financial system can be exposed and its impact on the economy as a whole. Hence the importance of research in studying the impact of internal and external public debt components on indicators of stability of the financial system for the period 2005-2017 for the purpose of knowing the extent of the financial stability indicators response to the high level of the public debt from its optimum ratio, as the aim of the research is to estimate and analyze the dynamic relationship of short and long term between the components of public debt and indicators of financial stability using the (ARDL) model that

As the process of  estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying  model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .

One of the main causes for concern is the widespread presence of pharmaceuticals in the environment, which may be harmful to living things. They are often referred to as emerging chemical pollutants in water bodies because they are either still unregulated or undergoing regulation. Pharmaceutical pollution of the environment may have detrimental effects on ecosystem viability, human health, and water quality. In this study, the amount of remaining pharmaceutical compounds in environmental waters was determined using a straightforward review. Pharmaceutical production and consumption have increased due to medical advancements, leading to concerns about their environmental impact and potential harm to living things due to their increa

The present study investigates the use of intensifiers as linguisticdevices employed by Charles Dickens in Hard Times. For ease of analysis, the data are obtained by a rigorous observation of spontaneously occurring intensifiers in the text. The study aims at exploring the pragmatic functions and aesthetic impact of using intensifiers in Hard Times.The current study is mainly descriptive analytical and is based on analyzing and interpreting the use of intensifiers in terms ofHolmes (1984) andCacchiani’smodel (2009). From the findings, the novelist overuses intensifiers to the extent that 280 intensifiers are used in the text. These intensifiers(218) are undistinguished

A comparative investigation of the anatomical characters through a microscopical examination of the prepared transverse sections of the stem was carried out. Six plates with 32 photomicrographs were provided to convincingly show the considerable variations of anatomical characters within the nine examined species. The matrix of 18 anatomical characters which included nine quantitative and nine qualitative was applied for the clustering analysis (CA) followed by the principal component analysis (PCA) using the Multivariate Analysis of Ecological Data, PC-ORD.
The results exhibited significant variations among the species resulting in the construction of an artificial key; this key accurately represents a sufficient tool to display the

The accurate identification of internal and external pressures in thick-walled hyperelastic vessels is a challenging inverse problem with significant implications for structural health monitoring, biomedical devices, and soft robotics. Conventional analytical and numerical approaches address the forward problem effectively but offer limited means for recovering unknown load conditions from observable deformations. In this study, we introduce a Graph-FEM/ML framework that couples high-fidelity finite element simulations with machine learning models to infer normalized internal and external pressures from measurable boundary deformations. A dataset of 1386 valid samples was generated through Latin Hypercube Sampling of geometric and l