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...

This research presents a new application of Data Envelopment Analysis (DEA) to empirically determine prices of multiple products. The DEA technique is now widely applied to performance analysis and efficiency measurement in economics, business and other areas in social science. This study does not explore such conventional DEA uses, rather directing towards a new DEA application to the determin...

ROBERT CAMPBELL, in honour of whose nmemory this lecture is held, was one of the great pioneers of aseptic surgery. He was the first surgeon to use rubber gloves in the British Isles, and he was responsible for many advances in our craft. He had a particular interest in the surgery of repair, and his appointment at the Children's Hospital gave him nmany opportunities to restore by means of repa...

Data envelopment analysis (DEA) is an effective method to evaluate the relative efficiency of decision-making units (DMUs). In one hand, the DEA models need accurate inputs and outputs data. On the other hand, in many situations, inputs and outputs are volatile and complex so that they are difficult to measure in an accurate way. The conflict leads to the researches of uncertain DEA models. Thi...

Two-stage data envelopment analysis (2-DEA) is commonly used in productive efficiency analysis to estimate the effects of operational conditions and practices on performance. In this method the DEA efficiency estimates are regressed on contextual variables representing the operational conditions. We reexamine the statistical properties of the 2-DEA estimator, and find that it is statistically c...

BACKGROUND The prevalence of dog erythrocyte antigen (DEA 1) in canine population is approximately 40-60%. Often data are limited to a small number of breeds and/or dogs. The aims of this study were to evaluate frequency of DEA 1 in a large population of purebred and mongrel dogs including Italian native breeds and to recognize a possible association between DEA 1 and breed, sex, and genetic an...

Quantifying cartilage contact stress is paramount to understanding hip osteoarthritis. Discrete element analysis (DEA) is a computationally efficient method to estimate cartilage contact stresses. Previous applications of DEA have underestimated cartilage stresses and yielded unrealistic contact patterns because they assumed constant cartilage thickness and/or concentric joint geometry. The stu...

This article computes the energy productivity changes of regions in Japan using total-factor frameworks based on data envelopment analysis (DEA). Since the traditional DEA-Malmquist index cannot analyze changes in single-factor productivity changes under the total-factor framework, we apply a new index proposed by Hu and Chang [2009. Total-factor energy productivity growth of regions in China. ...