This study aimed to determine the urodynamic characteristics of refractory enuresis and explore whether they can be managed through differential endoscopic injection with botulinum toxin. Methods: A total of 27 patients with nonmonosymptomatic enuresis who showed no response after conservative treatment for more than 12 months were included herein. Patients then underwent videourodynamic study and received a differential endoscopic injection of botulinum toxin within the same day. Reduced capacity, detrusor overactivity, and bladder neck widening were the three major abnormal findings assessed during the filling phase, while sphincter hyperactivity was the only abnormality assessed during the emptying phase. Intravesical or intrasphincteric injection of botulinum toxin was attempted according to videourodynamic study findings. Follow-up was conducted 1, 3, 6, and 12 months after treatment. Results: The median age was 10 (7-31) years. Although 19 and 8 patients had preoperative diagnosis of overactive bladder or dysfunctional voiding, respectively, urodynamic diagnosis was different in more than half of them. Those showing detrusor overactivity benefited from intravesical botulinum toxin injection, whereas those with only sphincter hyperactivity benefited from both intravesical and intrasphincteric injections. Treatment resistance to botulinum toxin seemed to have been attributed to bladder neck widening. Time had no apparent effect on efficacy, which remained 6 months after the injection. More than 80% of the patients retained the benefits of injection after 1 year. Conclusions: Videourodynamic study was useful in identifying reasons of refractory nonmonosymptomatic enuresis and helpful in determining appropriate sites of botulinum toxin A c c e p t e d A r t i c l e 2 injection.
As the number of social networking services (SNS) and their users grow, so does the complexity of individual networks as well as the amount of information to be consumed by the users. Users of SNS exchange short and instantaneous messages interactively, which can be seen as conversations. We explore this conversational aspect of SNS and show how refined topic-based semantic social networks can be formed in order to reduce the complexity and information overload. Among other possibilities, we use the notion of topic diversity and topic purity of SNS conversations between two users and show different types of social relationships can be identified in that they break down a huge “syntactic” social network into topic-based ones based on different interaction types. Resulting semantic social networks can be useful in designing various targeted services on online social networks.
An ability to predict people’s interests in different regions would be valuable to many applications including marketing and policymaking. We posit that social media plays an important role in capturing collective user interests in different regions and their dynamics over time and across regions. Event mentions in microblogs of social media like Twitter not only reflect the people’s interests in different regions but also affect the posting of future messages as the content of microblogs propagates to others through an online social network. Differentiating from the various network analysis techniques that have been developed to capture people’s interests and their propagation patterns, we propose an event mention prediction method that utilises an analysis of inter-region relationships. We first obtain regional user interests for each topic by applying Latent Dirichlet Allocation (LDA) to region-specific collections of tweets and then compute pairwise similarities among regions. The resulting similarity-based region network becomes the basis for constructing region groups through Markov Cluster Algorithm, which helps removing noise relationships among regions. We then propose a relatively simple regression technique to predict future event mentions in different regions. We demonstrate that the proposed method outperforms the state-of-the-art event prediction method, confirming that the novel method of constructing groups from region-based sub-topic interests indeed contributes to the increase in the prediction accuracy.
As the Web has become a commodity, it is used for a variety of purposes and tasks that may require a great deal of cognitive efforts. However, most search engines developed for the Web provide users with only searching and browsing capabilities, leaving all the burdens of manipulating information objects to the users. In this thesis, we focus on an exploratory search task and propose an underlying framework for human-Web interactions. Based on the framework, we designed and implemented a new information seeking interface that helps users reduce cognitive burden. The new human-Web interface provides a personal workspace that can be created and manipulated cooperatively with the system, which helps the user conceptualize his information seeking tasks and record their trails for future uses. This interaction tool has been tested for its efficacy as an aid for exploratory search.
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