Counterfactual Monotonic Knowledge Tracing for Assessing Students' Dynamic Mastery of Knowledge Concepts

As the core of the Knowledge Tracking (KT) task, assessing students' dynamic mastery of knowledge concepts is crucial for both offline teaching and online educational applications. Since students' mastery of knowledge concepts is often unlabeled, existing KT methods rely on the implicit paradigm of historical practice to mastery of knowledge concepts to students' responses to practices to address the challenge of unlabeled concept mastery. However, purely predicting student responses without imposing specific constraints on hidden concept mastery values does not guarantee the accuracy of these intermediate values as concept mastery values. To address this issue, we propose a principled approach called Counterfactual Monotonic Knowledge Tracing (CMKT), which builds on the implicit paradigm described above by using a counterfactual assumption to constrain the evolution of students' mastery of knowledge concepts.Comment: Accepted by CIKM 2023, 10 pages, 5 figures, 4 table

No Length Left Behind: Enhancing Knowledge Tracing for Modeling Sequences of Excessive or Insufficient Lengths

Knowledge tracing (KT) aims to predict students' responses to practices based on their historical question-answering behaviors. However, most current KT methods focus on improving overall AUC, leaving ample room for optimization in modeling sequences of excessive or insufficient lengths. As sequences get longer, computational costs will increase exponentially. Therefore, KT methods usually truncate sequences to an acceptable length, which makes it difficult for models on online service systems to capture complete historical practice behaviors of students with too long sequences. Conversely, modeling students with short practice sequences using most KT methods may result in overfitting due to limited observation samples. To address the above limitations, we propose a model called Sequence-Flexible Knowledge Tracing (SFKT).Comment: Accepted by CIKM 2023, 10 pages, 8 figures, 5 table

Cognition-Mode Aware Variational Representation Learning Framework for Knowledge Tracing

The Knowledge Tracing (KT) task plays a crucial role in personalized learning, and its purpose is to predict student responses based on their historical practice behavior sequence. However, the KT task suffers from data sparsity, which makes it challenging to learn robust representations for students with few practice records and increases the risk of model overfitting. Therefore, in this paper, we propose a Cognition-Mode Aware Variational Representation Learning Framework (CMVF) that can be directly applied to existing KT methods. Our framework uses a probabilistic model to generate a distribution for each student, accounting for uncertainty in those with limited practice records, and estimate the student's distribution via variational inference (VI). In addition, we also introduce a cognition-mode aware multinomial distribution as prior knowledge that constrains the posterior student distributions learning, so as to ensure that students with similar cognition modes have similar distributions, avoiding overwhelming personalization for students with few practice records. At last, extensive experimental results confirm that CMVF can effectively aid existing KT methods in learning more robust student representations. Our code is available at https://github.com/zmy-9/CMVF.Comment: Accepted by ICDM 2023, 10 pages, 5 figures, 4 table

Characterization of a novel genus of jumbo phages and their application in wastewater treatment

Summary: Phages widely exist in numerous environments from wastewater to deep ocean, representing a huge virus diversity, yet remain poorly characterized. Among them, jumbo phages are of particular interests due to their large genome (>200 kb) and unusual biology. To date, only six strains of jumbo phages infecting Klebsiella pneumoniae have been described. Here, we report the isolation and characterization of two jumbo phages from hospital wastewater representing the sixth genus: φKp5130 and φKp9438. Both phages showed lytic activity against broad range of clinical antibiotic-resistant K. pneumoniae strains and distinct physiology including long latent period, small burst size, and high resistance to thermal and pH stress. The treatment of sewage water with the phages cocktail resulted in dramatic decline in K. pneumoniae population. Overall, this study provides detailed molecular and genomics characterization of two novel jumbo phages, expands viral diversity, and provides novel candidate phages to facilitate environmental wastewater treatment

DataSheet_2_Clinical features and outcomes of patients with follicular lymphoma: A real-world study of 926 patients in China.docx

BackgroundThe data about the clinical features and outcomes of Chinese patients with follicular lymphoma (FL) are limited. Here, we conducted a retrospective study to explore the initial treatment strategies and clinical outcomes of Chinese patients with FL in the real world.MethodThis study included FL patients who were newly diagnosed in Tianjin Medical University Cancer Institute and Hospital from March 2002 to August 2020.ResultsA total of 926 FL patients were enrolled. The median age was 54 years old, and the majority of the Chinese FL patients had advanced-stage disease and Eastern Cooperative Oncology Group(ECOG) ConclusionsWe revealed the clinical characteristics and outcomes of FL patients in the real world in China, which may provide novel data on prognostic factors and primary treatment of FL, applicable to routine clinical practice.</p

DataSheet_1_Clinical features and outcomes of patients with follicular lymphoma: A real-world study of 926 patients in China.doc

BackgroundThe data about the clinical features and outcomes of Chinese patients with follicular lymphoma (FL) are limited. Here, we conducted a retrospective study to explore the initial treatment strategies and clinical outcomes of Chinese patients with FL in the real world.MethodThis study included FL patients who were newly diagnosed in Tianjin Medical University Cancer Institute and Hospital from March 2002 to August 2020.ResultsA total of 926 FL patients were enrolled. The median age was 54 years old, and the majority of the Chinese FL patients had advanced-stage disease and Eastern Cooperative Oncology Group(ECOG) ConclusionsWe revealed the clinical characteristics and outcomes of FL patients in the real world in China, which may provide novel data on prognostic factors and primary treatment of FL, applicable to routine clinical practice.</p