This study aimed to discuss concerning the link between savings and investment, and highlight on most of the past studies concerning this relationship are cross-sectional in nature. The obvious difficulty with such studies is the homogeneity assumption that is usually made across the countries under investigation. In light of this, the study tried to fill this gap in some ways by attempting to investigate the causal relationship between savings and investment in Jordan using relevant econometric techniques, like Augmented Dickey-Fuller (ADF) test in a regression & Johansen co integration test. The evidence arising from the study suggests that, savings and investment are co-integrated. In other words, there is no reason to suspect either a long-run or equilibrium relationship between these two variables. This could also be interpreted to imply the existence of high capital mobility. Furthermore, a unidirectional causal relationship between savings and investment in Jordan running from savings to investment was observed, and the main findings in this study were: Johansen co-integration test result shows evidence of co-integration implying that there is a long run relationship between GDP and savings, investment and FDI in Jordan. Savings and domestic investment have long run positive and significant impact on the Jordanian economy while FDI has negative but insignificant impact on the economy

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Journal: Journal of Economics and Sustainable Development www.iiste.org ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online) Vol.6, No.10, 2015

This study aims to determine the effect of EVA and ROI and which is better able to explain the change in Stock market’s value in the companies listed in (ASE) (2006-2015), the researcher addresses a random sample consisting of (46) Company, and uses regression model, which connects the dependent and independent variables. The results of the study shows that the return on investment (ROI) is better than (EVA) to interpret the changes in Stock market’s value, where the coefficient of determination (R2) for the ROI is (22.5%), while the R2 for EVA Only 1.3%. This study also recommends the need to look for additional factors that would explain the changes in stock market's value such as: the degree of leverage, systemic risks, and macroeconomic indicators such as: (interest rates and inflation).

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Journal: International Journal of Business and Management; Vol. 12, No. 10; 2017 ISSN 1833-3850 E-ISSN 1833-8119

This study discussed the Capital Assets Pricing model (CAPM) and its ability to measure the required return, the researcher tested this model on Amazon Company listed in S&P 500 during the period (2009-2016), to measure the impact of beta stock and market index return on the required return. Multiple regression model was used to test the effect of independent variables (Beta stock, Market Index Return) on the dependent variable (Required return), it should be noted that there is a statistically significant impact of the US stock market Return (S&P500) and Amazon stock Beta factor on Amazon stock required return, and the study model explanatory was 20% , this means that 20% of the changes in the required return are due to beta and market return, and 80% of the changes due to other factors, also find that CAPM can be applied on efficiency markets and huge companies. The researcher recommends applying the variables of the study on a group of large companies in the S&P 500 index, and looking for other factors that may affect the required return

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Journal: International Journal of Business and Management; Vol. 12, No. 8; 2017 ISSN 1833-3850 E-ISSN 1833-8119

Journal: Journal of law and political sciences VOL.2 ISSUE 1

The artificial intelligence methods in the Patch Antenna Multiple Wireless Applications, Recently indicate great prospects in the application of various areas of microengineering. This use of ANN for sizing patch patches of rectangular microstrip antennas with microstrip feed lines is presented in this article. Neural network in communication systems of wireless applications with antenna switching requires that antenna researchers design broadband antennas; Communication systems with high radiation efficiency should also be developed using the artificial neural network (ANN) simulation method; antenna size is a major limitation especially in mobile and wireless applications. In this paper, the problems of analysis and synthesis for the design of microstrip antennas using the artificial neural network method are considered. The task of the analysis is to calculate the resonant frequency of the microstrip patch antenna, while the artificial intelligence and the radial basis function RBF-ANN were used to implement the network model. Results obtained from an artificial neural network when compared with simulation results. The rapid development of wireless communication systems requires antenna researchers to develop miniature broadband antennas with high radiation efficiency. Communication systems require both the size and performance of the antennas, since there is a huge need for ultra-wideband, compact and efficient antenna structures that can operate in all desired subbands, from LTE (780 MHz) to WiMAX (5.5 GHz) Applications. ) with a good level of radiation efficiency and dimensions not exceeding 130 mm * 100 mm * 10 mm. All these functions are difficult to implement at the same time.

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Journal:

Information security risk analysis has increased the number of complex issues of information security, requiring the participation of specialists in different areas of knowledge. This leads to inability of such systems to evaluate the security state of computer system thoroughly. Present paper on the intellectual to risk analysis and vulnerability of information systems. The aim of the study is to eliminate subjectivity in the assessment of risks and reduction of time for the process of risk analysis and vulnerability of the computer system. The mathematical tools of artificial neural network and probabilistic attack tree were used in the research. In order to evaluate the efficiency of the developed system, the security assessment for the Windows systems was performed. As the result the conformity between the real security of the information system and the assigned evaluations was proved.

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Journal: Journal of Advanced Sciences and Engineering Technologies Vol. 2, No.1 (2019)

Silver nanoparticles (Ag NPs) are widely used in nanomedicine, pharmaceutical products, industry and other consumer products owing to their unique physiochemical properties with probable potential risk to human health and the ecosystems. The aim of this work was to investigate the in-life morphological effects, biochemical, histological and histochemical alterations that might be induced by variable sizes of Ag NPs in hepatic, renal and testicular tissues with the hypothesis that variable sizes of nano-Ag could induce variable effects in the vital organs. Five groups of adult healthy male mice (BALB/C) were exposed to 35 intraperitoneal injections of Ag NPs (1 mg/kg bw) using five different particle sizes (10, 20, 40, 60 and 100 nm). All mice were subjected to in-life morphometric, biochemical, histological and histochemical analysis. The findings demonstrated that Ag NPs could induce alterations in the average body weight gain, food consumption, water intake and organ indices. In addition, these NPs significantly altered hepatic and renal biomarkers. Moreover, Ag NPs produced ground glass hepatocyte cytoplasm, with mitotic activity, nuclear alterations, degeneration, glycogen depletion and inflammatory cells infiltration in the liver. The kidneys of treated mice exhibited proximal renal tubules degeneration, distal renal tubules regeneration, glomerular shrinkage, Bowman’s capsule thickening and interstitial inflammation. The testicular tissues demonstrated spermatocyte sloughing and spermatid giant cell formation. The findings together indicated that Ag NPs could interact with the anatomical structures of the liver, kidney and testis in ways that could induce injury. In addition, the results indicated that smaller Ag NPs posed a greater potential risk than the larger ones, which might be associated with their behaviour, dissolution rate, bioavailability and their probable variable toxicokinetics.

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Journal:

Metallic nanoparticles (NPs) are widely used in medical preparations. The present study aims to find out the influence of widely used five metallic NPs on the expression of major hepatic drug-metabolizing enzyme (DME) genes. Six groups of BALB/C mice, 7 mice each, were exposed to: Gold NPs, silver NPs, copper oxide NPs, silicon dioxide NPs and zinc oxide NPs, for 21 days. Liver biopsies from all mice were subjected to mouse cyp3a11, cyp2c29, ugt2b1 and interleukin-6 (il6) gene expression quantification using real-time polymerase chain reaction, in addition to inflammatory cell infiltration examination. All tested NPs caused a sharp and significant (ANOVA, p value <0.05) downregulation in the expression of DME genes, with the highest influence was observed in mice exposed to copper oxide NPs. Additionally, all NPs induced hepatic inflammation and upregulated the expression of il6 gene, which were inversely correlated with the expression of DMEs. It is concluded that all tested NPs downregulated the expression of DME genes, with the highest influence exhibited by copper oxide NPs, in correlation with inflammation and il6 gene induction in the liver. Further studies are needed to find out the effect of anti-inflammatory compounds against the alterations induced by metallic NPs exposure on hepatic DMEs

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Journal: Environmental Toxicology and Pharmacology, Volume 80, November 2020, 103449