Frequency of Renal Diseases in Diabetic Patients Renal diseases in diabetic patients

Diabetic nephropathy, also known as diabetic kidney disease is the chronic loss of kidney function occurring in those with diabetes mellitus. Diabetic nephropathy is one of the leading causes of chronic kidney disease (CKD) and end-stage renal disease (ESRD) globally. Protein loss in the urine due to damage to the glomeruli may become massive, and cause a low serum albumin with resulting generalized body swelling (edema) and result in the nephrotic syndrome. Objective: The aim of this study was to determine the frequency of renal disease in diabetic patients and its complications in Pakistan. Methods: A cross sectional study was conducted at Renal and Diabetic Departments of the Sir Ganga Ram Hospital, Lahore, over a period of 3 months, after obtaining the ethical approval from the The University of Lahore. A total number of 100 Diabetic patients were selected through non probability convenient sampling technique. Patients of both sexes and all age groups were included. Results: In this study 60% were male and 40% were female. About 41% diabetic patients were 1-6 month of age, 42% were 1-5 years old and 1% of 18-23 years old who had renal diseases while 9% patients were without any renal disease. Whereas the prevalence of diabetes is more in infants than others which is 35%. But there was not significant association between onset of renal diseases with the onset of diabetes mellitus with p-value 0.24. Conclusions: Results of current study showed that diabetes mellitus effecting individuals of all ages equally but there was not significant association between diabetes and renal diseases. 

Resource Aware Process Migration in Wireless Sensor Networks

This thesis presents a novel architecture for native process migration (PM) in wireless sensors networks (WSN) without the use of virtual execution environment. Resources in WSN are scarce, therefore creating a virtual execution environment for processes so that they can be migrated, put an extra burden on already constrained resources. The proposed architecture for process migration allows live native processes to be migrated during execution. The process migration architecture takes migration decisions by continuously monitoring resources including remaining battery life and free memory space on a node. The architecture is suitable for networks with fewer expensive sensor nodes as it allows for better utilization of network resources. Transferring a live executing process helps in meeting processing demands dynamically, improves fault tolerance and resource utilization, and allows easier network management in WSN. The proposed architecture supports resourcing monitoring, request broadcasting and response collection, target node selection, process code and state transfer, and restoration of native process at the target node. Implementation of proposed architecture has been successfully tested on COOJA simulator and a test-bed of TelosB motes. The final implementation has been compared to agent based systems and virtual machine architectures. It shows a remarkable improvement in runtime energy efficiency and executable code size.