Vehicular Ad Hoc Networks

(First paragraph) Vehicular ad hoc networks (VANETs) have recently been proposed as one of the promising ad hoc networking techniques that can provide both drivers and passengers with a safe and enjoyable driving experience. VANETs can be used for many applications with vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. In the United States, motor vehicle traffic crashes are the leading cause of death for all motorists between two and thirty-four years of age. In 2009, the National Highway Traffic Safety Administration (NHTSA) reported that 33,808 people were killed in motor vehicle traffic crashes. The US Department of Transportation (US-DOT) estimates that over half of all congestion events are caused by highway incidents rather than by rush-hour traffic in big cities. The US-DOT also notes that in a single year, congested highways due to traffic incidents cost over $75 billion in lost worker productivity and over 8.4 billion gallons of fuel. Some of the significant applications of VANETs are road safety applications including collision and other safety warning systems, driver convenience and information systems, and, in the future, intelligent traffic management systems

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

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I want to seize this opportunity to thank every one who directly or indirectly helped me in completing this work. It is not possible to state all names nevertheless I feel indebted to all my teachers, friends, family members, university staff, neighbors and colleagues for their contributions in my work and my life. However, some names should be necessarily mentioned without those this work was not possible. First of all, I would like to express my heartiest gratitude to Dr. Brian Mark for his guidance, supervision and efforts during the last three years. His critique and assessment always helped me in improving my work and his consolation and support kept me from being frustrated and disappointed. Working with him was certainly a pleasure and a great rewarding opportunity. I am thankful to my committee members for their comments and analysis, though kept me awake for several nights, were surely vital to my work. I also want to thank Electrical Engineering faculty in general for their involvement in my graduate studies. I specially want to mention Dr. S. C. Chang and thank him for his continuous support, encouragement, and guidance during my studies at George Mason. I wan

Mobility Estimation Based on an Autoregressive Model

We propose an integrated scheme for estimating the mobility state and model parameters of a user based on a first-order autoregressive model of mobility that accurately captures the characteristics of realistic user movements in wireless networks. Estimation of the mobility parameters is performed by applying the Yule-Walker equations to the training data. Estimation of the mobility state, which consists of the position, velocity, and acceleration of the mobile station is accomplished via an extended Kalman filter using measurements from the wireless network. The integration of mobility state and model parameter estimation results in an efficient and accurate real-time mobility tracking scheme that can be applied in a variety of wireless networking applications. The mobility estimation scheme can also be used to generate realistic mobility patterns to drive computer simulations of mobile networks. We validate the proposed mobility estimation scheme using mobile trajectories collected from drive-test data obtained from a live cellular network

A Distributed Mobility Tracking Scheme for Ad Hoc Networks Based on an Autoregressive Model

In an ad hoc wireless network, node mobility causes the network topology to change dynamically over time, which complicates important tasks such as routing, flow control, and location management. We propose a distributed scheme for accurately and efficiently tracking the mobility of nodes in an ad hoc network. A first-order autoregressive (AR-1) model is used to represent the evolution of mobility state of each node which consists of position, velocity, and acceleration. Each node uses an extended Kalman filter to estimate its own mobility state by incorporating network-based signal measurements, such as received signal strength indicators (RSSI) and time-of-arrival (TOA), and the position estimates of the neighbor nodes. Neighbor nodes exchange their position estimates periodically by means of HELLO packets. Using the mobility state estimates, each node re-estimates the mobility model parameters. Simulation results validate the performance of the proposed tracking scheme. The proposed distributed tracking scheme can adapt to changing mobility characteristics and incurs relatively low communication overhead