What is the level of evidence for the use of currently available technologies in facilitating the self-management of difficulties associated with ADHD in children and young people? A systematic review

A number of technologies to help self-manage Attention Deficit Hyperactivity Disorder (ADHD) in children and young people (YP) have been developed. This review will assess the level of evidence for the use of such technologies. The review was undertaken in accordance with the general principles recommended in the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. 7545 studies were screened. Fourteen studies of technology that aim to manage difficulties associated with ADHD in children and YP were included. Primary outcome measures were measures that assessed difficulties related to ADHD. Databases searched were MEDLINE, Web of Science (Core collection), CINAHL, the Cochrane Library, ProQuest ASSIA, PsycINFO and Scopus. The methodological quality of the studies was assessed. This review highlights the potential for the use of technology in paediatric ADHD self-management. However, it also demonstrates that current research lacks robustness; using small sample sizes, non-validated outcome measures and little psychoeducation component. Future research is required to investigate the value of technology in supporting children and YP with ADHD and a focus psychoeducation is needed

Big data applications in engineering and science

Research to solve engineering and science problems commonly require the collection and complex analysis of a vast amount of data. This makes them a natural exemplar of big data applications. For example, data from weather stations, high resolution images from CT scans, or data captured by astronomical instruments all easily showcase one or more big data characteristics, i.e., volume, velocity, variety and veracity. These big data characteristics present computational and analytical challenges that need to be overcame in order to deliver engineering solutions or make scientific discoveries. In this chapter, we catalogued engineering and science problems that carry a big data angle. We will also discuss the research advances for these problems and present a list of tools available to the practitioner. A number of big data application exemplars from the past works of the authors are discussed with further depth, highlighting the association of the specific problem and its big data characteristics. The overview from these various perspectives will provide the reader an up-to-date audit of big data developments in engineering and science

High Dose Flamsa, CLAG or FLAG-Based Sequential Conditioning Regimen Followed By Allogeneic Hematopoietic Transplantation Results in Favorable Outcome for High Risk Acute Myeloid Leukemia, Myelodysplastic Syndrome, Myeloproliferative Neoplasia Patients : A Multicenter Study in Singapore

10.1182/blood-2020-141518American society of hematology136Supplement 117-1

Interactions of multiple spark-generated bubbles with phase differences

10.1007/s00348-008-0603-4Experiments in Fluids464705-724EXFL