Mining Object Parts from CNNs via Active Question-Answering

Given a convolutional neural network (CNN) that is pre-trained for object classification, this paper proposes to use active question-answering to semanticize neural patterns in conv-layers of the CNN and mine part concepts. For each part concept, we mine neural patterns in the pre-trained CNN, which are related to the target part, and use these patterns to construct an And-Or graph (AOG) to represent a four-layer semantic hierarchy of the part. As an interpretable model, the AOG associates different CNN units with different explicit object parts. We use an active human-computer communication to incrementally grow such an AOG on the pre-trained CNN as follows. We allow the computer to actively identify objects, whose neural patterns cannot be explained by the current AOG. Then, the computer asks human about the unexplained objects, and uses the answers to automatically discover certain CNN patterns corresponding to the missing knowledge. We incrementally grow the AOG to encode new knowledge discovered during the active-learning process. In experiments, our method exhibits high learning efficiency. Our method uses about 1/6-1/3 of the part annotations for training, but achieves similar or better part-localization performance than fast-RCNN methods.Comment: Published in CVPR 201

Interpreting CNN Knowledge via an Explanatory Graph

This paper learns a graphical model, namely an explanatory graph, which reveals the knowledge hierarchy hidden inside a pre-trained CNN. Considering that each filter in a conv-layer of a pre-trained CNN usually represents a mixture of object parts, we propose a simple yet efficient method to automatically disentangles different part patterns from each filter, and construct an explanatory graph. In the explanatory graph, each node represents a part pattern, and each edge encodes co-activation relationships and spatial relationships between patterns. More importantly, we learn the explanatory graph for a pre-trained CNN in an unsupervised manner, i.e., without a need of annotating object parts. Experiments show that each graph node consistently represents the same object part through different images. We transfer part patterns in the explanatory graph to the task of part localization, and our method significantly outperforms other approaches.Comment: in AAAI 201

CustomNet: Zero-shot Object Customization with Variable-Viewpoints in Text-to-Image Diffusion Models

Incorporating a customized object into image generation presents an attractive feature in text-to-image generation. However, existing optimization-based and encoder-based methods are hindered by drawbacks such as time-consuming optimization, insufficient identity preservation, and a prevalent copy-pasting effect. To overcome these limitations, we introduce CustomNet, a novel object customization approach that explicitly incorporates 3D novel view synthesis capabilities into the object customization process. This integration facilitates the adjustment of spatial position relationships and viewpoints, yielding diverse outputs while effectively preserving object identity. Moreover, we introduce delicate designs to enable location control and flexible background control through textual descriptions or specific user-defined images, overcoming the limitations of existing 3D novel view synthesis methods. We further leverage a dataset construction pipeline that can better handle real-world objects and complex backgrounds. Equipped with these designs, our method facilitates zero-shot object customization without test-time optimization, offering simultaneous control over the viewpoints, location, and background. As a result, our CustomNet ensures enhanced identity preservation and generates diverse, harmonious outputs.Comment: Project webpage available at https://jiangyzy.github.io/CustomNet

Puerarin Relieves Paclitaxel-Induced Neuropathic Pain: The Role of Nav1.8 β1 Subunit of Sensory Neurons

Currently there is no effective treatment available for clinical patients suffering from neuropathic pain induced by chemotherapy paclitaxel. Puerarin is a major isoflavonoid extracted from the Chinese medical herb kudzu root, which has been used for treatment of cardiovascular disorders and brain injury. Here, we found that puerarin dose-dependently alleviated paclitaxel-induced neuropathic pain. At the same time, puerarin preferentially reduced the excitability and blocked the voltage-gated sodium (Nav) channels of dorsal root ganglion (DRG) neurons from paclitaxel-induced neuropathic pain rats. Furthermore, puerarin was a more potent blocker of tetrodotoxin-resistant (TTX-R) Nav channels than of tetrodotoxin-sensitive (TTX-S) Nav channels in chronic pain rats’ DRG neurons. In addition, puerarin had a stronger blocking effect on Nav1.8 channels in DRG neurons of neuropathic pain rats and β1 subunit siRNA can abolish this selective blocking effect on Nav1.8. Together, these results suggested that puerarin may preferentially block β1 subunit of Nav1.8 in sensory neurons contributed to its anti-paclitaxel induced neuropathic pain effect

Severe fever with thrombocytopenia syndrome in children: a case report

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by a novel bunyavirus (SFTSV) in China. Humans of all ages living in endemic areas have high risk of acquiring SFTS. Most clinical data so far have been from adults and no clinical study was available from children yet. The present study identified four SFTSV infected children through hospital based surveillance. A prospective observational study was performed to obtain their clinical and laboratory characteristics. CASE PRESENTATION: The patients’ age ranged from 4–15 years old and two were male. On hospitalization, fever, malaise and gastrointestinal syndromes were the most commonly presenting symptoms. Hemorrhagic symptoms or neurological manifestation was not recorded in any of the four pediatric patients. Hematological abnormalities at admission into hospital included leucopenia (4 cases), thrombocytopenia (1 case) and bicytopenia (1 case). The abnormal parameters included elevated aminotransferase (1 case), alanine transaminase (2 case), and lactate dehydrogenase (3 case). Laboratory parameters indicative of renal damage was not observed during the hospitalization. All the patients recovered well without sequelae being observed. CONCLUSION: Compared with adults, pediatric patients with SFTSV infection seem to have less vague subjective complaints and less aggressive clinical course. Thrombocytopenia is suggested to be used less rigorously in recognizing SFTSV infection in pediatric patients, especially at early phase of disease