No abstract

Recently, the advances in communication technologies have made music retrieval easier. Without downloading the music, the users can listen to music through online music websites. This incurs a challenging issue of how to provide the users with an effective online listening service. Although a number of past studies paid attention to this issue, the problems of new user, new item and rating sparsity are not easy to solve. To deal with these problems, in this paper, we propose a novel music recommender system that fuses user contents, music contents and preference ratings to enhance the music recommendation. For dealing with problem of new user, the user similarities are calculated by user profiles instead of traditional ratings. By the user similarities, the unknown ratings can be predicted using user-based Collaborative Filtering (CF). For dealing with problems of rating sparsity and new items, the unknown ratings are initialized by acoustic features and music genre ratings. Because the unknown ratings are initially imputed, the rating data will be enriched. Thereupon, the user preference can be predicted effectively by item-based CF. The evaluation results show that our proposed music recommender system performs better than the state-of-the-arts methods in terms of Root Mean Squared Error.

No abstract

Hepatitis B virus (HBV) is one of the most common DNA viruses that can cause aggressive hepatitis, cirrhosis and hepatocellular carcinoma. Although many people are persistently infected with HBV, the kinetics in serum levels of viral loads and the host immune responses vary from person to person. HBV precore/core open reading frame (ORF) encoding proteins, hepatitis B e antigen (HBeAg) and core antigen (HBcAg), are two indicators of active viral replication. The aim of this study was to discover a variety of amino acid covariances in responses to viral kinetics, seroconversion and genotypes during the course of HBV infection. A one year follow-up study was conducted with a total number of 1,694 clones from 23 HBeAg-positive chronic hepatitis B patients. Serum alanine aminotransferase, HBV DNA and HBeAg levels were measured monthly as criteria for clustering patients into several different subgroups. Monthly derived multiple precore/core ORFs were directly sequenced and translated into amino acid sequences. For each subgroup, time-dependent covariances were identified from their time-varying sequences over the entire follow-up period. The fluctuating, wavering, HBeAg-nonseroconversion and genotype C subgroups showed greater degrees of covariances than the stationary, declining, HBeAg-seroconversion and genotype B. Referring to literature, mutation hotspots within our identified covariances were associated with the infection process. Remarkably, hotspots were predominant in genotype C. Moreover, covariances were also identified at early stage (spanning from baseline to a peak of serum HBV DNA) in order to determine the intersections with aforementioned time-dependent covariances. Preserved covariances, namely representative covariances, of each subgroup are visually presented using a tree-based structure. Our results suggested that identified covariances were strongly associated with viral kinetics, seroconversion and genotypes. Moreover, representative covariances may benefit clinicians to prescribe a suitable treatment for patients even if they have no obvious symptoms at the early stage of HBV infection.