IN SITU INTERFEROMETRIC STUDY ON THE GELATION PROCESS OF POLYACRYLIC ACID GELS

In situ interferometry was used to investigate the gelation process of polyacrylic acid (PAA) gels. The basic principle of the in situ interferometry technique is illustrated. It can give sufficient information for non-destructive and successful investigation of the whole gelation process. The effect of initiator concentration on the gelation process was studied. The polymerization rate of AA increases with increasing initiator concentration. The error arising from the thermal effect in the gelation process can be neglected.

Meeting deadlines for approximation processing in MapReduce environments

To provide timely results for big data analytics, it is crucial to satisfy deadline requirements for MapReduce jobs in today＇s production environments. Much effort has been devoted to the problem of meeting deadlines, and typically there exist two kinds of solutions. The first is to allocate appropriate resources to complete the entire job before the specified time limit, where missed deadlines result because of tight deadline constraints or lack of resources; the second is to run a pre-constructed sample based on deadline constraints, which can satisfy the time requirement but fail to maximize the volumes of processed data. In this paper, we propose a deadline-oriented task scheduling approach, named ＇Dart＇, to address the above problem. Given a specified deadline and restricted resources, Dart uses an iterative estimation method, which is based on both historical data and job running status to precisely estimate the real-time job completion time. Based on the estimated time, Dart uses an approach-revise algorithm to make dynamic scheduling decisions for meeting deadlines while maximizing the amount of processed data and mitigating stragglers. Dart also efficiently handles task failures and data skew, protecting its performance from being harmed. We have validated our approach using workloads from OpenCloud and Facebook on a cluster of 64 virtual machines. The results show that Dart can not only effectively meet the deadline but also process near-maximum volumes of data even with tight deadlines and limited resources.

Self-assembly Behavior of Copolymers with Super Segregated Structure Containing Fluorinated Segments

Copolymers with super segregated structure of hydrophilic methoxy poly（ethylene glycol） （mPEG） and fluorophilic poly（1H,1H,2H,2H-perfluorodecyl acrylate） （PFA） were prepared. And just because of this super segregated structure which was resulted from the extremely strong incompatibility between the two blocks, several interesting self- assembly behaviors of the copolymers were displayed and studied under different conditions. Transmission electron microscope （TEM） showed that with the increase of PFA in the polymerization system, the incompatibility in this super segregated structure became stronger, and the self-assembly behavior changed from ball-like or rod-like to vesicles, and finally collapsed to sheet-like. The self-assembly behavior changed likewise when the initial concentration increased. And the interesting formation of these barrel-like and spindle-like vesicles was finally studied with different cooling speeds. It＇s finally found that with this super segregation structure, these new self-assembly morphology might be formed due to the extremely strong incompatibility between mPEG and PFA segments.