Data is an integral part of modern scientific work. Good research data management (RDM) and the communication related information extremely important matter. It not only crucial for ongoing its claims but also future uses data. In recent years some guiding principles, e.g. FAIR principles initiatives at national international level, NFDI, NFDI4Ing have been founded to improve RDM. The metadata ...

BACKGROUND The outcome of patients with bacteraemia is influenced by the initial selection of adequate antimicrobial therapy. The objective of our study was to clarify the influence of different crude data correction methods on a) microbial spectrum and ranking of pathogens, and b) cumulative antimicrobial susceptibility pattern of blood culture isolates obtained from patients from intensive ca...

The purpose of this study is to develop portfolio optimization and assets allocation using our proposed models. The study is based on a non-parametric efficiency analysis tool, namely Data Envelopment Analysis (DEA). Conventional DEA models assume non-negative data for inputs and outputs. However, many of these data take the negative value, therefore we propose the MeanSharp-βRisk (MShβR) model...


 Modern life sciences studies depend on the collection, management and analysis of comprehensive datasets in what has become data-intensive research. Life science research is also characterised by having relatively small groups researchers. This combination performed a few people led to an increasing bottleneck data (RDM). Parallel this, there been urgent call initiatives like FAIR Open S...

in data envelopment analyze (dea) the scale efficiency in the input-oriented ccr model is less than or equal to the scale efficiency in dea based on the fractional analysis (dea-r). also, the scale efficiency in case of multiple inputs and one output and vice versa the scale efficiencies are equal in dea and dea-r. in this paper, first, dea-r model with weight restrictions when there is relativ...