Smart Road Traffic Accidents Reduction Strategy Based on Intelligent Transportation Systems (TARS).

Traffic accidents have become an important problem for governments, researchers and vehicle manufacturers over the last few decades. However, accidents are unfortunate and frequently occur on the road and cause death, damage to infrastructure, and health injuries. Therefore, there is a need to develop a protocol to avoid or prevent traffic accidents at the extreme level in order to reduce human loss. The aim of this research is to develop a new protocol, named as the Traffic Accidents Reduction Strategy (TARS), for Vehicular Ad-hoc NETworks (VANETs) to minimize the number of road accidents, decrease the death rate caused by road accidents, and for the successful deployment of the Intelligent Transportation System (ITS). We have run multiple simulations and the results showed that our proposed scheme has outperformed DBSR and POVRP routing protocols in terms of the Message Delivery Ratio (MDR), Message Loss Ratio (MLR), Average Delay, and Basic Safety Message.

Association of Diabetic Neuropathy with Duration of Type 2 Diabetes and Glycemic Control.

INTRODUCTION: Diabetes mellitus is associated with severe microvascular and macrovascular complications with major implications for public health. Diabetic neuropathy is a very problematic complication of diabetes mellitus. It is associated with severe morbidity, mortality, and a huge economic burden. The present study was designed with two aims: 1) to analyze the association of diabetic neuropathy with the glycemic index (levels of fasting blood glucose, random blood glucose, and Hb1Ac) in patients with Type 2 diabetes, and 2) to analyze the association of diabetic neuropathy with time passed since the diagnosis of diabetes. METHODS: This case-control study was undertaken between June 2013 and February 2015 in the Armed Forces Institute of Rehabilitation Medicine (AFIRM), Rawalpindi, Pakistan. Type 2 diabetics with an age range of 30-60 years were recruited from outpatient departments of AFIRM, Rawalpindi. Data were collected and recorded on a form with four sections recording the following: 1) demographics of patients and number of years passed since diagnosis of diabetes; 2) clinical examination for touch, pressure, power, pain, vibration, and ankle reflex; 3) nerve conduction studies for motor components of the common peroneal nerve and tibial nerve and the sensory component of median nerve and sural nerve; 4) glycemic index, including fasting blood glucose levels (BSF), random blood glucose (BSR) levels, and HbA1c levels. Data were analyzed in SPSS v. 20. Chi-square and phi statistics and logistic regression analysis were run to analyze associations between diabetic neuropathy and time passed since diagnosis of diabetes and glycemic index. RESULTS: In total, 152 patients were recruited. One-half of those patients had neuropathy (76 patients) and the other half (76 patients) had normal nerve function. The mean (standard deviation [SD]) duration of diabetes was nine years (6.76), BSF levels 7.98 mmol/l (2.18), BSR 9.5 mmol/l (3.19), and HbA1c 6.5% (2.18). Logistic regression analysis predicted 87.5% of the model correctly. Duration since the diagnosis of diabetes and HbA1c levels were significantly associated with the diagnosis of neuropathy in diabetics. CONCLUSION: The presence of diabetic neuropathy was significantly associated with HbA1c levels and the duration of diabetes.