Xiaolu Xiong

Learn More
In contrast to typical laboratory experiments, the everyday use of online educational resources by large populations and the prevalence of software infrastructure for A/B testing leads us to consider how platforms can embed in vivo experiments that do not merely support research, but ensure practical improvements to their educational components. Examples(More)
BACKGROUND Rickettsia heilongjiangensis, the agent of Far-Eastern spotted fever (FESF), is an obligate intracellular bacterium. The surface-exposed proteins (SEPs) of rickettsiae are involved in rickettsial adherence to and invasion of host cells, intracellular bacterial growth, and/or interaction with immune cells. They are also potential molecular(More)
Coxiella burnetii is the etiological agent of Q fever. The clinical diagnosis of Q fever is mainly based on several serological tests. These tests all need Coxiella organisms which are difficult and hazardous to culture and purify. An immunoproteomic study of C. burnetii Xinqiao strain isolated in China was conducted with the sera from experimentally(More)
Researchers of Intelligent Tutoring Systems (ITS) and Educational Data Mining (EDM) have focused increasing attention on predicting students' long-term retention performance as well as attempting to find effective methods to help improve student knowledge retention. Wang and Beck proposed a system which allows ITS to strive for student long-term mastery(More)
Student modeling has been widely used in the prediction of student correctness behavior on the immediate next action. Some researchers have been working on student modeling to predict delayed performance, that is, retention. Prior work has found that the factors influencing retention differ from those that influence short-term performance. However, this(More)
Over the last couple of decades, there have been a large variety of approaches towards modeling student knowledge within intelligent tutoring systems. With the booming development of deep learning and large-scale artificial neural networks, there have been empirical successes in a number of machine learning and data mining applications, including student(More)
BACKGROUND Coxiella burnetii is an obligate intracellular bacterium and the etiologic agent of Q fever; both coxiella outer membrane protein 1 (Com1) and heat shock protein B (HspB) are its major immunodominant antigens. It is not clear whether Com1 and HspB have the ability to mount immune responses against C. burnetii infection. RESULTS The recombinant(More)
Coxiella burnetii is a Gram-negative bacterium that causes Q fever in humans. In the present study, 131 candidate peptides were selected from the major immunodominant proteins (MIPs) of C. burnetii due to their high-affinity binding capacity for the MHC class II molecule H2 I-A(b) based on bioinformatic analyses. Twenty-two of the candidate peptides with(More)