A data science approach for quantifying spatio-temporal effects to graft failures in organ transplantation

This is the author accepted manuscript. The final version is available from IEEE via the DOI in tis recordThe transplantation of solid organs is one of the most important accomplishments of modern medicine. Yet, organ shortage is a major public health issue; 8,000 people died while waiting for an organ in 2014. Meanwhile, the allocation system currently implemented can lead to organs being discarded and the medical community still investigates factors that affects early graft failure such as distance and ischemic time. In this paper, we investigate early graft failure under a spatio-temporal perspective using a data science unified approach for all six organs that is based on complementary cumulative analysis of both distance and ischemic time. Interestingly, although distance seems to highly affect some organs (e.g. liver), it appears to have no effect on others (e.g. kidney). Similarly, the results on ischemic time confirm it affects early graft failure with higher influence for some organs such as (e.g. heart) and lower influence for others such as (e.g. kidney). This poses the question whether the allocation policies should be individually designed for each organ in order to account for their particularities as shown in this work

Risks and Challenges of Adopting Electric Vehicles in Smart Cities

Oil prices and increased carbon emissions are two of the key issues affecting mainstream transportation globally. Hence, EVs (Electric VehiclesElectric Vehicles) are becoming popular as they do not depend on oil, and the GHG (Greenhouse Gases) do not contribute to GHG emissions. In fact, their integration with smart grids makes them even more attractive. Although EVEV adoption is becoming widespread, three groups of challenges need to be addressed. These challenges are associated with EV technology adoption, integration of EVs and smart grids, and the supply chain of EV raw materials. Regarding the EV technology adoption, the risks and challenges include EV battery capacity, drivers’ range anxiety, the impact of auxiliary loads, EV drivers’ behavior, EV owners’ unwillingness to participate in the V2GV2G (Vehicle-to-Grid) program, economic barriers to adopting EVs, difficult EV maintenance, EV performance mismatch between the lab and the real world, need for government regulation, lack of charging infrastructure such as not enough charging stations, and expensive batteries. There are additional challenges concerning the integration with the smart grids such as system overload, high-cost investment in V2G technology, load mismatchLoad mismatch, and unmanaged recharging of EV batteries. Finally, there are challenges regarding the consistent supply of the raw materials needed for EVs. This chapter examines these risks and challenges, suggests solutions and provides recommendations for future research