Scaffolding online peer collaboration to enhance ill-structured problem solving with computer-based cognitive support.

The results reveal significant effects of procedure and metacognitive question prompts in ill-structured problem solving at both overall and univariate levels. However, there was no significant effect of online peer collaboration and no significant interaction. This study supported some previous research on using question prompts as a scaffolding strategy to support problem solving. Further, these findings support a redefined IDEAL problem solving model for solving ill-structured problems. The findings suggest many implications for instructional designers, educators in web-based learning environments, and educational researchers. These implications and the limitations of this study are discussed.The present study investigated the effects of question prompts and online peer collaborations on solving ill-structured problems. Sixty undergraduate students were randomly assigned to one of the four treatment groups: collaboration with question prompts, individual with question prompts, collaboration without question prompts, and individual without question prompts. Question prompts were designed to both facilitate problem solving procedure and promote students' metacognition. Students worked either individually or collaboratively with partners via MSN Messenger during the problem solving processes

The Cowen-Douglas operators with strongly flag structure

Denote $\mathcal{FB}_{n}(\Omega)$ as the collection of operators possessing a flag structure in the Cowen-Douglas class $\mathcal{B}_{n}(\Omega)$, and all the irreducible homogeneous operators in $\mathcal{B}_{n}(\Omega)$ belong to this class. G. Misra et al. pointed out in \cite{JJKM} that the unitary invariants of this class of operators include the curvature and the second fundamental form of the corresponding line bundle. In terms of the invariants, it is more tractable compared to general operators in $\mathcal{B}_{n}(\Omega)$. A subclass of $\mathcal{FB}_{n}(\Omega)$, denoted by $\mathcal{CFB}_{n}(\Omega)$, was proven to be norm dense in $\mathcal{B}_{n}(\Omega)$ in \cite{JJ}. In this paper, we introduce a smaller subclass of $\mathcal{FB}_{n}(\Omega)$ which possesses a strongly flag structure, and for which the curvature and the second fundamental form of the associated line bundle is a complete set of unitary invariants. And we notice that this class of operators is norm dense in $\mathcal{B}_{n}(\Omega)$ up to similarity. On this basis, we have completed the similar classification of a large class of operators with flag structure, which reduces the number of the similarity invariants in \cite{JKSX} from $\frac{n(n-1)}{2}+1$ to $n$. Furthermore, we also get a complete characterization of weakly homogeneous operators with high index and flag structure.Comment: 22page

Microwave Assisted Hydrolysis Of Holocellulose Catalyzed With Sulfonated Char Derived From Lignin-Rich Residue

A microwave assisted green process has been developed for production of sugars through liquefying holocellulose catalyzed with sulfonated char derived from the lignin-rich residue produced during pretreatment of lignocellulose. Various reaction parameters including the hydrolysis temperature, hydrolysis time, catalyst content, and the ratio of water to feedstock were evaluated. The maximum sugars yield of 82.6% (based on the dry mass of holocellulose) was obtained under the optimum reaction conditions. The sulfonated char showed superior catalytic performance to that of dilute sulfuric acid in converting holocellulose into sugars under microwave irradiation

PDID: Database of molecular-level putative protein-drug interactions in the structural human proteome

© 2015 The Author 2015. Published by Oxford University Press. All rights reserved. Motivation: Many drugs interact with numerous proteins besides their intended therapeutic targets and a substantial portion of these interactions is yet to be elucidated. Protein-Drug Interaction Database (PDID) addresses incompleteness of these data by providing access to putative protein-drug interactions that cover the entire structural human proteome. Results: PDID covers 9652 structures from 3746 proteins and houses 16 800 putative interactions generated from close to 1.1 million accurate, all-atom structure-based predictions for several dozens of popular drugs. The predictions were generated with three modern methods: ILbind, SMAP and eFindSite. They are accompanied by propensity scores that quantify likelihood of interactions and coordinates of the putative location of the binding drugs in the corresponding protein structures. PDID complements the current databases that focus on the curated interactions and the BioDrugScreen database that relies on docking to find putative interactions. Moreover, we also include experimentally curated interactions which are linked to their sources: DrugBank, BindingDB and Protein Data Bank. Our database can be used to facilitate studies related to polypharmacology of drugs including repurposing and explaining side effects of drugs. Availability and implementation: PDID database is freely available at http://biomine.ece.ualberta.ca/PDID/