Preparation of Iminodiacetic Acid-Polyethylene Glycol for Immobilized Metal Ion Affinity Partitioning

The synthesis route was investigated and optimized for the preparation of iminodiacetic acid-polyethylene glycol (IDA-PEG) for immobilized metal ion affinity partitioning in aqueous two-phase systems. IDA-PEG was synthesized from PEG in two steps by the reaction of iminodiacetic acid with a monosubstituted derivative of epichlorohydrin-activated PEG. The Cu2+ content combined with IDA-PEG was determined by atomic absorption spectrometry as 0.5 mol·mol^-1 (PEG). Furthermore, the affinity partitioning behavior of lactate dehydrogenase in polyethylene glycol/hydroxypropyl starch aqueous two-phase systems was studied to clarify the affinity effect of the Cu(Ⅱ)-IDA-PEG.

Local and global approaches of affinity propagation clustering for large scale data

Recently a new clustering algorithm called 'affinity propagation' (AP) has been proposed, which efficiently clustered sparsely related data by passing messages between data points. However, we want to cluster large scale data where the similarities are not sparse in many cases. This paper presents two variants of AP for grouping large scale data with a dense similarity matrix. The local approach is partition affinity propagation (PAP) and the global method is landmark affinity propagation (LAP). PAP passes messages in the subsets of data first and then merges them as the number of initial step of iterations; it can effectively reduce the number of iterations of clustering. LAP passes messages between the landmark data points first and then clusters non-landmark data points; it is a large global approximation method to speed up clustering. Experiments are conducted on many datasets, such as random data points, manifold subspaces, images of faces and Chinese calligraphy, and the results demonstrate that the two ap-proaches are feasible and practicable.