Beta thalassaemia major (TM), a potentially fatal haemoglobinopathy, has transformed from a fatal to a chronic disease in the last 30 years following the introduction of effective, personalised iron chelation protocols, in particular the use of oral deferiprone, which is most effective in the removal of excess iron from the heart. This transition in TM has been achieved by the accessibility to combination therapy with the other chelating drugs deferoxamine and deferasirox but also therapeutic advances in the treatment of related co-morbidities. The transition and design of effective personalised chelation protocols was facilitated by the development of new non-invasive diagnostic techniques for monitoring iron removal such as MRI T2*. Despite this progress, the transition in TM is mainly observed in developed countries, but not globally. Similarly, potential cures of TM with haemopoietic stem cell transplantation and gene therapy are available to selected TM patients but potentially carry high risk of toxicity. A global strategy is required for the transition efforts to become available for all TM patients worldwide. The same strategy could also benefit many other categories of transfusional iron loaded patients including other thalassaemias, sickle cell anaemia, myelodysplasia and leukaemia patients.
Driving simulators emerged as a promising technology for the analysis of driving conditions and road users' behaviour in an attempt to tackle the problem of road accidents. The work presented herein demonstrates the design and development of a driving simulator that aims to contribute towards evaluating black spots in road networks by promoting rapid design of realistic models and facilitating the specification of test scenarios. A reliable driving simulator should be able to reproduce the driver's behaviour in a realistic way. In this study the authors examine different setups of the simulator to define the one that achieves highest levels of reliability. The chosen setup is then used to evaluate the impact of distractors (e.g. billboards) on driving behaviour of local road users for a chosen black spot in Limassol, Cyprus. Data collected from the experiments are analysed, and the main findings are presented and discussed.
The explosive growth of Internet-connected devices will soon result in a flood of generated data, which will increase the demand for network bandwidth as well as compute power to process the generated data. Consequently, there is a need for more energy efficient servers to empower traditional centralized Cloud data-centers as well as emerging decentralized data-centers at the Edges of the Cloud. In this paper, we present our approach, which aims at developing a new class of micro-servers-the UniServer-that exceed the conservative energy and performance scaling boundaries by introducing novel mechanisms at all layers of the design stack. The main idea lies on the realization of the intrinsic hardware heterogeneity and the development of mechanisms that will automatically expose the unique varying capabilities of each hardware component within commercial microservers and allow their operation at new extended operating points. Low overhead schemes are employed to monitor and predict the hardware behavior and report it to the system software. The system software including a virtualization and resource management layer is responsible for optimizing the system operation in terms of energy or performance, while guaranteeing non-disruptive operation under the extended operating points. Our characterization results on a 64-bit ARMv8 micro-server in 28nm process reveal large voltage margins in terms of Vmin variation among the 8 cores of the CPU chip, among 3 different sigma chips, and among different benchmarks with the potential to obtain up-to 38.8% energy savings. Similarly, DRAM characterizations show that refresh rate and voltage can be relaxed by 43x and 5%, respectively, leading to 23.2% power savings on average.
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