This literature review was conducted systematically to identify the gap in knowledge and practice related to the provision of sexual health to adolescents worldwide. The search was limited to peer-reviewed articles published between 2002 and 2018. Thirty-two relevant articles were identified and reviewed for quality assessment by using the Hawker critical appraisal tool. The studies were conducted in Africa, Europe, Asia, Oceania, and the United States of America (USA). The review findings suggested that potential tensions exist between the desire to prevent unwanted pregnancies and the provision of adolescent-friendly sexual health services in societies which disapprove of adolescents' premarital sexual activity, contraception use and abortion services. Healthcare professionals should be aware of comprehensive sexual and reproductive health services as their professional responsibility and the need to manage their own conflicts with regard to fulfilling their role.
•IoT within infectious disease epidemiology is an emerging field of research, however the ubiquitous availability of smart technologies, as well as increased risks of infectious disease spread through the globalization and interconnectedness of the world necessitates its use for predicting, preventing and controlling emerging infectious diseases.•Considering the present situation in China, IoT based smart disease surveillance systems have the potential to be a major breakthrough in efforts to control the current pandemic. With much of the infrastructure itself in place already (i.e. smartphones, wearable technologies, internet access) the role this technology can have in limiting the spread of the pandemic involves only the collection and analysis of data already gathered.•More research must be carried out for the development of automated and effective alert systems to provide early and timely detection of outbreaks of such diseases in order to reduce morbidity mortality and prevent global spread.
Hadoop MapReduce reactively detects and recovers faults after they occur based on the static heartbeat detection and the re-execution from scratch techniques. However, these techniques lead to excessive response time penalties and inefficient resource consumption during detection and recovery. Existing fault-tolerance solutions intend to mitigate the limitations without considering critical conditions such as fail-slow faults, the impact of faults at various infrastructure levels and the relationship between the detection and recovery stages. This paper analyses the response time under two main conditions: fail-stop and fail-slow, when they manifest with node, service, and the task at runtime. In addition, we focus on the relationship between the time for detecting and recovering faults. The experimental analysis is conducted on a real Hadoop cluster comprising MapReduce, YARN and HDFS frameworks. Our analysis shows that the recovery of a single fault leads to an average of 67.6% response time penalty. Even though the detection and recovery times are well-turned, data locality and resource availability must also be considered to obtain the optimum tolerance time and the lowest penalties.