Data envelopment analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs). Recently network DEA models been developed to examine the efficiency of DMUs with internal structures. The internal network structures range from a simple two-stage process to a complex system where multiple divisions are linked together with intermediate measures. In general, there ar...

Amiodarone (AMD)-induced pulmonary toxicity (AIPT) is the most life-threatening side-effect of AMD treatment. N-Monodesethylamiodarone (DEA), an active metabolite of AMD, also exhibits cytotoxicity and tends to accumulate in the lung more intensively than AMD. In this study, we characterized the mechanism of DEA accumulation using A549 cells as a model of the alveolar epithelium. Typical ATP-de...

In this paper, we discuss the relationship between multi-attribute utility theory and DEA models without explicit inputs (DEA-WEI), including dual models and some theoretical analysis of DEA-WEI models. We then propose generic DEA-WEI models with quadratic utility terms. Finally, we provide illustrative examples to show that DEA-WEI with suitable quadratic utility terms are able to reflect some...

Diethanolamine (DEA) is a common ingredient of personal care products. Dermal administration of DEA diminishes hepatic stores of the essential nutrient choline and alters brain development. We previously reported that 80 mg/kg/day of DEA during pregnancy in mice reduced neurogenesis and increased apoptosis in the fetal hippocampus. This study was designed to establish the dose-response relation...

D-eritadenine (DEA) is a potent inhibitor (IC(50) = 7 nm) of S-adenosyl-l-homocysteine hydrolase (AdoHcyase). Unlike cyclic sugar Ado analogue inhibitors, including mechanism-based inhibitors, DEA is an acyclic sugar Ado analogue, and the C2' and C3' have opposite chirality to those of the cyclic sugar Ado inhibitors. Crystal structures of DEA alone and in complex with AdoHcyase have been deter...

DEA models treat the DMU as a “black box.” Inputs enter and outputs exit, with no consideration of the intervening steps. Consequently, it is di(cult, if not impossible, to provide individual DMU managers with speci;c information regarding the sources of ine(ciency within their DMUs. We show how to use DEA to look inside the DMU, allowing greater insight as to the sources of organizational ine(...

In this study, the data envelopment analysis (DEA), three-stage DEA (3SDEA) and artificial neural network (ANN) are employed to measure the technical efficiency of 29 semi-conductor firms in Taiwan. Estimated results show that there are significant differences in efficiency scores among DEA, 3SDEA and ANN analysis. The advanced setting of the three stages mechanism of DEA does show some changes...