101 research outputs found

    Examining scholars' activity on a Chinese blogging and academic social network site

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    This study analyzes scholars' activity on a popular academic blogging and social network site (SNS) in China, ScienceNet. We collected blogs, comments, recommendations, likes, and user profile information and analyzed how different groups of users differ in their patterns of activity with others in different disciplines, professional ranks, and universities. Results indicate that: 1) scholars in management and mathematics are active in recommending and commenting other users; 2) scholars from well-known universities and research institutes often receive more comments and recommendations than those from other universities; 3) scholars with higher professional ranks are more active, and are more likely to receive comments and recommendations from others. These findings suggest different usage of academic SNS among scholars of different disciplines, ranks, and universities

    Deconfounding Causal Inference for Zero-shot Action Recognition

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    Zero-shot action recognition (ZSAR) aims to recognize unseen action categories in the test set without corresponding training examples. Most existing zero-shot methods follow the feature generation framework to transfer knowledge from seen action categories to model the feature distribution of unseen categories. However, due to the complexity and diversity of actions, it remains challenging to generate unseen feature distribution, especially for the cross-dataset scenario when there is potentially larger domain shift. This paper proposes a De confounding Ca usa l GAN (DeCalGAN) for generating unseen action video features with the following technical contributions: 1) Our model unifies compositional ZSAR with traditional visual-semantic models to incorporate local object information with global semantic information for feature generation. 2) A GAN-based architecture is proposed for causal inference and unseen distribution discovery. 3) A deconfounding module is proposed to refine representations of local object and global semantic information confounder in the training data. Action descriptions and random object feature after causal inference are then used to discover unseen distributions of novel actions in different datasets. Our extensive experiments on C ross- D ataset Z ero- S hot A ction R ecognition (CD-ZSAR) demonstrate substantial improvement over the UCF101 and HMDB51 standard benchmarks for this problem

    Q-Diffusion: Quantizing Diffusion Models

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    Diffusion models have achieved great success in image synthesis through iterative noise estimation using deep neural networks. However, the slow inference, high memory consumption, and computation intensity of the noise estimation model hinder the efficient adoption of diffusion models. Although post-training quantization (PTQ) is considered a go-to compression method for other tasks, it does not work out-of-the-box on diffusion models. We propose a novel PTQ method specifically tailored towards the unique multi-timestep pipeline and model architecture of the diffusion models, which compresses the noise estimation network to accelerate the generation process. We identify the key difficulty of diffusion model quantization as the changing output distributions of noise estimation networks over multiple time steps and the bimodal activation distribution of the shortcut layers within the noise estimation network. We tackle these challenges with timestep-aware calibration and split shortcut quantization in this work. Experimental results show that our proposed method is able to quantize full-precision unconditional diffusion models into 4-bit while maintaining comparable performance (small FID change of at most 2.34 compared to >100 for traditional PTQ) in a training-free manner. Our approach can also be applied to text-guided image generation, where we can run stable diffusion in 4-bit weights with high generation quality for the first time.Comment: The code is available at https://github.com/Xiuyu-Li/q-diffusio

    TorchSparse++: Efficient Training and Inference Framework for Sparse Convolution on GPUs

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    Sparse convolution plays a pivotal role in emerging workloads, including point cloud processing in AR/VR, autonomous driving, and graph understanding in recommendation systems. Since the computation pattern is sparse and irregular, specialized high-performance kernels are required. Existing GPU libraries offer two dataflow types for sparse convolution. The gather-GEMM-scatter dataflow is easy to implement but not optimal in performance, while the dataflows with overlapped computation and memory access (e.g.implicit GEMM) are highly performant but have very high engineering costs. In this paper, we introduce TorchSparse++, a new GPU library that achieves the best of both worlds. We create a highly efficient Sparse Kernel Generator that generates performant sparse convolution kernels at less than one-tenth of the engineering cost of the current state-of-the-art system. On top of this, we design the Sparse Autotuner, which extends the design space of existing sparse convolution libraries and searches for the best dataflow configurations for training and inference workloads. Consequently, TorchSparse++ achieves 2.9x, 3.3x, 2.2x and 1.7x measured end-to-end speedup on an NVIDIA A100 GPU over state-of-the-art MinkowskiEngine, SpConv 1.2, TorchSparse and SpConv v2 in inference; and is 1.2-1.3x faster than SpConv v2 in mixed precision training across seven representative autonomous driving benchmarks. It also seamlessly supports graph convolutions, achieving 2.6-7.6x faster inference speed compared with state-of-the-art graph deep learning libraries.Comment: MICRO 2023; Haotian Tang and Shang Yang contributed equally to this projec

    Adaptive inverse control of a vibrating coupled vessel-riser system with input backlash

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    This article involves the adaptive inverse control of a coupled vessel-riser system with input backlash and system uncertainties. By introducing an adaptive inverse dynamics of backlash, the backlash control input is divided into a mismatch error and an expected control command, and then a novel adaptive inverse control strategy is established to eliminate vibration, tackle backlash, and compensate for system uncertainties. The bounded stability of the controlled system is analyzed and demonstrated by exploiting the Lyapunov’s criterion. The simulation comparison experiments are finally presented to verify the feasibility and effectiveness of the control algorithm

    Hydrogen Sulfide Protects against Chemical Hypoxia-Induced Injury by Inhibiting ROS-Activated ERK1/2 and p38MAPK Signaling Pathways in PC12 Cells

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    Hydrogen sulfide (H2S) has been proposed as a novel neuromodulator and neuroprotective agent. Cobalt chloride (CoCl2) is a well-known hypoxia mimetic agent. We have demonstrated that H2S protects against CoCl2-induced injuries in PC12 cells. However, whether the members of mitogen-activated protein kinases (MAPK), in particular, extracellular signal-regulated kinase1/2(ERK1/2) and p38MAPK are involved in the neuroprotection of H2S against chemical hypoxia-induced injuries of PC12 cells is not understood. We observed that CoCl2 induced expression of transcriptional factor hypoxia-inducible factor-1 alpha (HIF-1α), decreased cystathionine-β synthase (CBS, a synthase of H2S) expression, and increased generation of reactive oxygen species (ROS), leading to injuries of the cells, evidenced by decrease in cell viability, dissipation of mitochondrial membrane potential (MMP) , caspase-3 activation and apoptosis, which were attenuated by pretreatment with NaHS (a donor of H2S) or N-acetyl-L cystein (NAC), a ROS scavenger. CoCl2 rapidly activated ERK1/2, p38MAPK and C-Jun N-terminal kinase (JNK). Inhibition of ERK1/2 or p38MAPK or JNK with kinase inhibitors (U0126 or SB203580 or SP600125, respectively) or genetic silencing of ERK1/2 or p38MAPK by RNAi (Si-ERK1/2 or Si-p38MAPK) significantly prevented CoCl2-induced injuries. Pretreatment with NaHS or NAC inhibited not only CoCl2-induced ROS production, but also phosphorylation of ERK1/2 and p38MAPK. Thus, we demonstrated that a concurrent activation of ERK1/2, p38MAPK and JNK participates in CoCl2-induced injuries and that H2S protects PC12 cells against chemical hypoxia-induced injuries by inhibition of ROS-activated ERK1/2 and p38MAPK pathways. Our results suggest that inhibitors of ERK1/2, p38MAPK and JNK or antioxidants may be useful for preventing and treating hypoxia-induced neuronal injury

    Safety and efficacy of plasma exchange treatment in children with AQP4-IgG positive neuromyelitis optica spectrum disorder

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    Neuromyelitis optica spectrum disorder (NMOSD), a severe demyelinating disease, is rare among children. Plasma exchange (PE) is widely used as a salvage therapy for severe and corticosteroid-unresponsive patients with NMOSD. Presently, there are limited studies on the safety and efficacy of PE in children with NMOSD. Herein, we report the case of six children with NMOSD who received PE along with the outcomes and adverse events. All six children (female, age at onset 4 years 9 months–13 years 2 months) were AQP4-IgG positive and received standard PE using the COM.TEC Cell Separator. The interval between NMOSD onset and PE was 29 days (range 10–98). Only one patient (P3) who received PE 10 days after acute exacerbations exhibited clinical improvement. Her left visual acuity increased from 0.06 to 0.6 (spectacle-corrected visual acuity was 1.0) and her EDSS score decreased from 4 to 3 points. The other five patients had no clinical improvement and no EDSS scores changes after PE. Adverse events included rashes (P1, P3), acute non-occlusive thrombosis of the internal jugular vein (P1), and thrombocytopenia (P2). In conclusion, the timing of PE initiation as a rescue therapy for severe and corticosteroid-unresponsive pediatric AQP4-IgG positive NMOSD may be crucial to treatment efficacy, and early initiation of PE may be associated with a better outcome. Furthermore, PE has the potential risk for clinically significant adverse effects that should be considered before initiating the therapy and should be weighed against potential benefits

    Catalytic promiscuity of O-methyltransferases from Corydalis yanhusuo leading to the structural diversity of benzylisoquinoline alkaloids

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    O-methyltransferases play essential roles in producing structural diversity and improving the biological properties of benzylisoquinoline alkaloids (BIAs) in plants. In this study, Corydalis yanhusuo, a plant used in traditional Chinese medicine due to the analgesic effects of its BIA-active compounds, was employed to analyze the catalytic characteristics of O-methyltransferases in the formation of BIA diversity. Seven genes encoding O-methyltransferases were cloned, and functionally characterized using seven potential BIA substrates. Specifically, an O-methyltransferase (CyOMT2) with highly efficient catalytic activity of both 4′- and 6-O-methylations of 1-BIAs was found. CyOMT6 was found to perform two sequential methylations at both 9- and 2-positions of the essential intermediate of tetrahydroprotoberberines, (S)-scoulerine. Two O-methyltransferases (CyOMT5 and CyOMT7) with wide substrate promiscuity were found, with the 2-position of tetrahydroprotoberberines as the preferential catalytic site for CyOMT5 (named scoulerine 2-O-methyltransferase) and the 6-position of 1-BIAs as the preferential site for CyOMT7. In addition, results of integrated phylogenetic molecular docking analysis and site-directed mutation suggested that residues at sites 172, 306, 313, and 314 in CyOMT5 are important for enzyme promiscuity related to O-methylations at the 6- and 7-positions of isoquinoline. Cys at site 253 in CyOMT2 was proved to promote the methylation activity of the 6-position and to expand substrate scopes. This work provides insight into O-methyltransferases in producing BIA diversity in C. yanhusuo and genetic elements for producing BIAs by metabolic engineering and synthetic biology

    The 21st Century Maritime Silk Road: Sino-Sri Lanka Bilateral Maritime Cooperation

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    张仁平,教授,中国大连海事大学国际海事公约研究中心主任。 姜州阳,助理,中国大连海事大学国际海事公约研究中心。 任袖语,助理,中国大连海事大学国际海事公约研究中心。 杨迎,助理,中国大连海事大学国际海事公约研究中心。【中文摘要】丝绸之路经济带和21世纪海上丝绸之路是促进中国与古丝路沿线各国相互投资与合作的战略构想。2013年10月,中国国家主席习近平在出访东南亚国家期间,提出共建海上丝绸之路的重大倡议,他回顾了中国古代海上丝绸之路的历史,并勾勒出一条新的海上丝绸之路。中国重振海上丝绸之路,就是要弘扬古丝路和平、友好与合作的精神,与沿线各国实现共同发展,打造命运共同体,助推海上安全建设。本文将从3方面论述海上丝绸之路的建设:亚洲基础设施投资银行、基础设施建设和自由贸易区。最后,本文提出从政策、能力建设和培训等方面增强中斯双边海上合作。斯里兰卡是第一个正式支持中国“一带一路”战略的国家。中斯均希望两国的双边合作会成为新时期海上合作的样板,同时也让斯里兰卡成为镶嵌在21世纪海上丝绸之路上的一颗璀璨明珠。 【Abstract】 The Silk Road Economic Belt and the 21st Century Maritime Silk Road are Chinese strategic initiatives to increase investments and foster collaboration along the historic Silk Road. Chinese President Xi Jinping first raised the Maritime Silk Road initiative when he visited Southeast Asia in October 2013.During his visit, he memorialized the ancient Maritime Silk Road and outlined a new Maritime Silk Road, in order to revive the Maritime Silk Road to carry forward the spirit of peace, friendship, and cooperation of the ancient Silk Road.China hopes to realize common development with all countries along the road to improve maritime security, and develop a community of common destiny. This paper examines the building of the new Maritime Silk Road from three aspects: the Asian Infrastructure Investment Bank, infrastructure construction, and free trade areas. Finally, this paper proposes to better bilateral cooperation between China and Sri Lanka in the areas of policy, capacity building and training. Sri Lanka is the first country to officially support China’s initiatives and both countries hope that their bilateral collaboration will become a model for maritime cooperation in the new era, resulting in Sri Lanka becoming a dazzling pearl along the 21st Century Maritime Silk Road
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