BACKGROUND Candida parapsilosis (R)-carbonyl reductase (RCR) and (S)-carbonyl reductase (SCR) are involved in the stereoconversion of racemic (R,S)-1-phenyl-1,2-ethanediol (PED) to its (S)-isomer. RCR catalyzes (R)-PED to 2-hydroxyacetophenone (2-HAP), and SCR catalyzes 2-HAP to (S)-PED. However, the stereoconversion efficiency of racemic mixture to (S)-PED is not high because of an activity im...

In this paper, we assume that investors have the same information, but trade due to the evolution of their non-market wealth. Investors rebalance their portfolios in response to changes in their expected non-market wealth, and hence trade. Risky nonmarket wealth is non-hedgeable and independent of market risk, and thus represents an additive background risk. Investors who experience positive sh...

W e study the problem of rebalancing a replicated tree, while the tree is concurrently being updated in a P2P manner. Tree updates are asynchronous and commutative, as we aim at eventual consistency. However, rebalancing requires strong synchronisation, because only replicas that have performed the same rebalances can communicate with one another. In order to scale to large networks, we propose...

This paper concentrates on load management methods for multiprocessor systems with distributed memory. Most of the programs running on these machines do not create new processes during runtime and there is usually no sharing of nodes between multiple users. This causes load movement by process migration to be indispensable. We implemented a testbed to nd out which load parameters are signiicant...

Recent analyses of organizational change suggest a growing concern with the tempo of change, understood as the characteristic rate, rhythm, or pattern of work or activity. Episodic change is contrasted with continuous change on the basis of implied metaphors of organizing, analytic frameworks, ideal organizations, intervention theories, and roles for change agents. Episodic change follows the s...

In cases of extremely imbalanced dataset with high dimensions, standard machine learning techniques tend to be overwhelmed by the large classes. This paper rebalances skewed datasets by compressing the majority class. This approach combines Vector Quantization and Support Vector Machine and constructs a new approach, VQ-SVM, to rebalance datasets without significant information loss. Some issue...