Disentangled Variational Auto-Encoder for Semi-supervised Learning

Semi-supervised learning is attracting increasing attention due to the fact that datasets of many domains lack enough labeled data. Variational Auto-Encoder (VAE), in particular, has demonstrated the benefits of semi-supervised learning. The majority of existing semi-supervised VAEs utilize a classifier to exploit label information, where the parameters of the classifier are introduced to the VAE. Given the limited labeled data, learning the parameters for the classifiers may not be an optimal solution for exploiting label information. Therefore, in this paper, we develop a novel approach for semi-supervised VAE without classifier. Specifically, we propose a new model called Semi-supervised Disentangled VAE (SDVAE), which encodes the input data into disentangled representation and non-interpretable representation, then the category information is directly utilized to regularize the disentangled representation via the equality constraint. To further enhance the feature learning ability of the proposed VAE, we incorporate reinforcement learning to relieve the lack of data. The dynamic framework is capable of dealing with both image and text data with its corresponding encoder and decoder networks. Extensive experiments on image and text datasets demonstrate the effectiveness of the proposed framework.Comment: 6 figures, 10 pages, Information Sciences 201

Human Theatre

Human Theatre III's photography series of juxtaposition of space is a confluence of ideas and a group of loose practices. It does not have a single point of origin, a clear meaning, or a linear narrative: Instead, it uses a series of fragmented metaphors and metonymy phrases to solve the problem of the passage of time, explore the philosophy of life, express desire, absence, complex, and the thought of Self, and try to find the combination of sensibility and reason with poetic narration methods, completing the transmutation of time to the juxtaposition of space

Spectral Computed Tomography for the Diagnosis of Secondary Skeletal Muscle Follicular Lymphoma: A Case Analysis

Follicular lymphoma (FL) is one of the frequent varieties of non-Hodgkin's lymphoma (NHL). Secondary skeletal muscle FL is an uncommon extra-nodal lymphoma that is more challenging to identify. Spectral CT imaging can aid in the diagnosis of it. A 52-year-old man who had a bulge in his left inguinal area for two months in 2021. Following a mass aspiration biopsy, cervical lymph node dissection and a bone marrow aspiration biopsy, the patient was diagnosed as follicular lymphoma grade I with bone marrow involvement. Later, the patient had progressive worsening of low back pain for 2 month and underwent a lumbar spectral enhanced-CT scan, which demonstrated the right psoas major muscle and the retroperitoneal swollen lymph nodes were discovered to be homologous lesions, indicating the lymphoma infiltration of the right psoas major muscle. Spectral enhanced-CT is a non-invasive, practical, and reliable alternative technique. By reconstructing and comparing the energy spectrum curves of different tissues to shed light on the nature of the mass, it can aid in the diagnosis of extra-nodal lymphoma, which is of great value in determining the extent of the lesion and guiding the clinical treatment plan

A Community Detection and Graph Neural Network Based Link Prediction Approach for Scientific Literature

This study presents a novel approach that synergizes community detection algorithms with various Graph Neural Network (GNN) models to bolster link prediction in scientific literature networks. By integrating the Louvain community detection algorithm into our GNN frameworks, we consistently enhance performance across all models tested. For example, integrating Louvain with the GAT model resulted in an AUC score increase from 0.777 to 0.823, exemplifying the typical improvements observed. Similar gains are noted when Louvain is paired with other GNN architectures, confirming the robustness and effectiveness of incorporating community-level insights. This consistent uplift in performance reflected in our extensive experimentation on bipartite graphs of scientific collaborations and citations highlights the synergistic potential of combining community detection with GNNs to overcome common link prediction challenges such as scalability and resolution limits. Our findings advocate for the integration of community structures as a significant step forward in the predictive accuracy of network science models, offering a comprehensive understanding of scientific collaboration patterns through the lens of advanced machine learning techniques

Behavioral and Neurobiological Changes in C57BL/6 Mouse Exposed to Cuprizone: Effects of Antipsychotics

Recent human studies suggest a role for altered oligodendrocytes in the pathophysiology of schizophrenia. Our recent animal study has reported some schizophrenia-like behaviors in mice exposed to cuprizone (Xu et al., 2009), a copper chelator that has been shown to selectively damage the white matter. This study was to explore mechanisms underlying the behavioral changes in cuprizone-exposed mice and to examine effects of the antipsychotics haloperidol, clozapine and quetiapine on the changes in the mice. Mice given cuprizone for 14 days showed a deficit in the prepulse inhibition of acoustic startle response and higher dopamine in the prefrontal cortex (PFC), which changes were not seen in mice given cuprizone plus antipsychotics. Mice given cuprizone for 21 days showed lower spontaneous alternations in Y-maze, which was not seen in mice treated with cuprizone plus the antipsychotics. Mice given cuprizone for 28 days displayed less social interactions, which was not seen in mice given cuprizone plus clozapine/quetiapine, but was seen in mice given cuprizone plus haloperidol. Mice given cuprizone for 42 days showed myelin sheath loss and lower myelin basic protein in PFC, caudate putamen, and hippocampus. The white matter damage in PFC was attenuated in mice given cuprizone plus clozapine/haloperidol. But the white matter damage in caudate putamen and hippocampus was only attenuated by clozapine and quetiapine, not by haloperidol. These results help us to understand the behavioral changes and provide experimental evidence for the protective effects of antipsychotics on white matter damage in cuprizone-exposed mice