The Effect of Ownership Structure on Firm’s Financial Performance: An Empirical Study on the Most Active Firms in the Egyptian Stock Exchange

This paper seeks to examine the effect of ownership structure on firm financial performance in Egypt. Using a sample of 50 more active Egyptian companies listed on the Egyptian Stock Exchange of the non-financial sector covering the period of three financial years from 2007 to 2009. Ownership Structure is represented by Managerial Ownership, Institutional Ownership, Block holder Ownership and Free Float Ownership. Return on Assets (ROA) and Return on Equity (ROE) are used as a proxy for Firm financial Performance. Using multiple linear regressions as method of estimation, the results provide evidences that there is no significant relationship between ownership structure variables and firm financial performance measures by (ROA and ROE). This study provides many recommendations to the regulatory authorities in Egypt regarding ways to strengthen and reinforce the internal governance structure of companies especially ownership structure. Keywords: Corporate governance, Ownership structure, Firm Financial Performance, Egyp

Machine learning models for traffic classification in electromagnetic nano-networks

The number of nano-sensors connected to wireless electromagnetic nano-network generates different traffic volumes that have increased dramatically, enabling various applications of the Internet of nano-things. Nano-network traffic classification is more challenging nowadays to analyze different types of flows and study the overall performance of a nano-network that connects to the Internet through micro/nanogateways. There are traditional techniques to classify traffic, such as port-based technique and load-based technique, however the most promising technique used recently is machine learning. As machine learning models have a great impact on traffic classification and network performance evaluation in general, it is difficult to declare which is the best or the most suitable model to address the analysis of large volumes of traffic collected in operational nano-networks. In this paper, we study the classification problem of nano-network traffic captured by micro/nano-gateway, and then five supervised machine learning algorithms are used to analyze and classify the nano-network traffic from traditional traffic. Experimental analysis of the proposed models is evaluated and compared to show the most adequate classifier for nano-network traffic that gives very good accuracy and performance score to other classifiers.This work was supported in part by the ‘‘Agencia Estatal de Investigación’’ of ‘‘Ministerio de Ciencia e Innovación’’ of Spain under Project PID2019-108713RB-C51/MCIN/AEI/10.13039/501100011033, and in part by the ‘‘Agència de Gestió d’Ajuts Universitaris i de Recerca’’ (AGAUR) of the ‘‘Generalitat de Catalunya’’ under Grant 2021FI_B2 00091.Postprint (published version

CXC ligand 13 in rheumatoid arthritis and its relation to secondary Sjögren’s syndrome

AbstractAim of the workThe aim of the present study was to measure the level of the chemokine CXC ligand 13 protein (CXCL13) in the plasma and unstimulated saliva of rheumatoid arthritis (RA) patients in order to find out its role in the disease activity and its relation to secondary Sjögren’s syndrome (sSS).Patients and methodsThe study was conducted on thirty rheumatoid arthritis patients attending the Outpatient Clinic of Rheumatology and Rehabilitation department of Ain shams University Hospitals. The patients’ group had been classified into group (1) which included fifteen RA patients associated with sSS diagnosed according to the American–European Consensus Group Classification Criteria and group (2) which included fifteen RA patients not associated with sSS. Ten healthy subjects were included as a control group. Patients were subjected to full history taking, clinical examination, and laboratory detection of CXCL13 level in the plasma and saliva of patients as well as the control groups using ELISA technique. Assessment of disease activity in RA patients was done using the disease activity score (DAS28).ResultsPlasma levels of CXCL13 were significantly higher in RA patients than control group (p<0.001). Plasma levels of CXCL13 were significantly correlated with the RA disease activity (r=0.677, p<0.001) and disease duration (r=0.406, p<0.05), while the salivary levels were higher in those with sSS and correlated with sSS disease duration (r=0.536, p<0.05). A highly significant correlation was found between salivary CXCL13 and severity of sSS (r=0.816, p<0.001). Salivary levels of CXCL13 above 110pg/ml may diagnose sSS with sensitivity 80% and specificity 84%.ConclusionThe results of this preliminary study point out the importance of CXCL13 as a marker for RA disease activity, its role in diagnosing sSS, and estimation of sSS severity

The role of MR diffusion in differentiation of malignant and benign hepatic focal lesions

AbstractAimTo determine if focal liver masses could be differentiated as benign or malignant by DWI and ADC maps.Methods and materialsSixty focal liver lesions were scanned using 1.5T MRI. DWI was performed with b 0, b 500 and b 1000 gradients with ADC measurements. Comparison of mean ADC values between each benign and malignant lesion was done. Reference standard of diagnosis was obtained by correlating DWI with histopathologic findings and imaging follow-up. The accuracies of DWI and ADC values were assessed with the Student’s t test, and cut-off values were determined with receiver operating characteristic curve analysis.ResultsWhen ADC value of 1.0×10−3mm2/s was used as a threshold value for differentiation of malignant tumors from benign lesions, sensitivity was 90.3%, specificity 78.57% and accuracy 86.7%. The best result was obtained with the use of ADC cut off value (at b 500) of 1.5×10−3mm2/s and ADC cut off value (at b 1000) of 1.0×10−3mm2/s, with 90.3% sensitivity, 92.86% specificity, 91.1% accuracy, 96.6% positive predictive value and 81.3% negative predictive value.ConclusionDWI and ADC map is a useful tool in differential diagnosis of malignant from benign liver lesions

The outcomes of Skeletonized and Pedicled Internal Thoracic Artery in Patients undergoing coronary artery bypass grafting: a randomized clinical study

Background: Internal thoracic artery became the cornerstone graft in coronary artery bypass grafting. This study aimed to investigate sternal healing and wound infection in patients undergoing coronary artery bypass graft (CABG) surgery using skeletonized versus pedicled internal thoracic artery. Methods: 100 patients who underwent isolated CABG were divided into two groups; skeletonized internal thoracic artery (ITA) (50 patients) and pedicled internal thoracic artery (50 patients). The postoperative assessment was performed three months after surgery. Physical and radiological examinations were performed after surgery to assess sternal healing. Results: There was no significant difference in patients’ demographics between groups. Skeletonized group had more diabetic patients (65% vs 44%; p= 0.016). There was no significant difference between the two groups regarding the number of grafts (2.72 ± 0.89 vs. 2.68 ± 0.90; skeletonized vs pedicled group; p= 0.84). Harvesting time was longer in the skeletonized group (55.69 ± 8.80 vs. 44.28 ± 6.95 minutes; p=0.09). Superficial wound infection occurred more frequently in the pedicled group (24% vs. 8%; p=0.03). Conclusion: Skeletonization of the internal thoracic artery conduits lowers the risk of superficial and deep sternal wound infection in patients undergoing CABG compared to the pedicled technique. However, skeletonization of internal thoracic artery conduits prolongs the operation time and requires more surgical skills