Riboswitches are cis-acting genetic regulatory elements within a specific mRNA that can regulate both transcription and translation by interacting with their corresponding metabolites. Recently, an increasing number of riboswitches have been identified in different species and investigated for their roles in regulatory functions. Both the sequence contexts and structural conformations are important characteristics of riboswitches. None of the previously developed tools, such as covariance models (CMs), Riboswitch finder, and RibEx, provide a web server for efficiently searching homologous instances of known riboswitches or considers two crucial characteristics of each riboswitch, such as the structural conformations and sequence contexts of functional regions. Therefore, we developed a systematic method for identifying 12 kinds of riboswitches. The method is implemented and provided as a web server, RiboSW, to efficiently and conveniently identify riboswitches within messenger RNA sequences. The predictive accuracy of the proposed method is comparable with other previous tools. The efficiency of the proposed method for identifying riboswitches was improved in order to achieve a reasonable computational time required for the prediction, which makes it possible to have an accurate and convenient web server for biologists to obtain the results of their analysis of a given mRNA sequence. RiboSW is now available on the web at http://RiboSW.mbc.nctu.edu.tw/.

In conventional classrooms, teachers attempt to enhance instruction by monitoring students' learning processes and analyzing their performances by paper records and observation. Similarly, distance learning systems on the Web should be designed to record students' behaviors to assist teachers in assessing performance and making decisions related to curriculum. Recent developments in Web server systems can record the students' access to the learning systems in Web logs. Information processing analysis on the historical classroom processes can help teachers to develop knowledge for applying proper teaching strategies according to available information in Web logs. However, teachers cannot easily infer the pedagogical meaning of Web logs and discover the pedagogical rules of students' behavior patterns in the Web logs to refine teaching strategies. Therefore, to use Web logs for pedagogical purposes, this article adopts decision tree and data cube information processing methodologies to observe students' behaviors and discover the pedagogical rules on students' learning performance from Web logs. The architecture and

The accurate identification of potential poly(A) sites has contributed to all many studies with regard to alternative polyadenylation. The aim of this study was the development of a machine-learning methodology that will help to discriminate real polyadenylation signals from randomly occurring signals in genomic sequence. Since previous studies have revealed that RNA secondary structure in certain genes has significant impact, the authors tried to computationally pinpoint common structural patterns around the poly(A) sites and to investigate how RNA secondary structure may influence polyadenylation. This involved an initial study on the impact of RNA structure and it was found using motif search tools that hairpin structures might be important. Thus, it was propose that, in addition to the sequence pattern around poly(A) sites, there exists a widespread structural pattern that is also employed during human mRNA polyadenylation. In this study, the authors present a computational model that uses support vector machines to predict human poly(A) sites. The results show that this predictive model has a comparable performance to the current prediction tool. In addition, it was identified common structural patterns associated with polyadenylation using several motif finding programs and this provides new insight into the role of RNA secondary structure plays in polyadenylation.

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Hard of hearing students usually face more difficulties at school than other students. A classroom environment with wireless technology was implemented to explore whether wireless technology could enhance mathematics learning and teaching activities for a hearing teacher and her 7 hard of hearing students in a Taiwan junior high school. Experiments showed that the highly interactive communication through the wireless network increased student participation in learning activities. Students demonstrated more responses to the teacher and fewer distraction behaviors. Fewer mistakes were made in in-class course work because Tablet PCs provided students scaffolds. Students stated that the environment with wireless technology was desirable and said that they hoped to continue using the environment to learn mathematics.