In this study, iron, steel and chromium waste heavyweight particles were replaced by calcerous sand with different percentages in volume and the radiation shielding properties of resulting mortar samples were investigated. ...

improving their operations with a view to human health and environmental awareness. Many methods with different rationales have been existed in the literature to prioritize hazards according to their risk levels and to ...

A linear non-resonant kinetic energy harvester for implantable devices is presented. The design contains a metal platform with permanent magnets, two stators with three-dimensional helical coils for increased power generation, ...

Location selection for offshore wind farms is a major challenge for renewable energy policy, marine spatial planning, and environmental conservation. This selection constitutes a multi-criteria decision-making problem, ...

The biological impact of nanomaterials (NMs) is determined by several factors such as size and shape, which need to be taken into consideration in any type of analysis. While investigators often prefer to conduct in vitro ...

Intense competition drives e-tailers to search for radically new ways to maintain and increase their market share. Drawing on Bagozzi’s (1992) appraisal → affective response → behavior framework, this study highlights the ...

We demonstrate that micro-scale rolling bearings exhibit friction and wear properties markedly different from their macro-scale counterparts. A microfabricated testing platform uses variable rolling element diameters or ...

Long non-coding RNAs (lncRNAs) can act as molecular sponge or decoys for an RNA-binding protein (RBP) through their RBP-binding sites, thereby modulating the expression of all target genes of the corresponding RBP of ...

Using regionally downscaled and adjusted outputs of three global climate models (GCMs), meteorological drought analysis was accomplished across Ankara, the capital city of Turkey. To this end, standardized precipitation ...

Genetic programming (GP) is recognized as a robust machine learning method for rainfall-runoff modelling. However, it may produce lagged forecasts if autocorrelation feature of runoff series is not taken carefully into ...