30,166 results on '"Xiao, Jing"'
Search Results
52. Selective CO2 electroreduction to formate over oxide-derived In nanosheets under industrial-current-density
- Author
-
Zhu, Shan, Zhao, Yue, Zhu, Tai-Yun, Sun, Zhi-Xin, Zhu, Feng, Cao, Jun, Ma, Feng-Xiang, Li, Xiao-dong, Zhang, Xiao-Jing, and Sun, Yong-Fu
- Published
- 2024
- Full Text
- View/download PDF
53. Bio-inspired barnacle cement coating of biodegradable magnesium alloy for cerebrovascular application
- Author
-
Li, Hang, Wang, Fei, Sun, Xiao-Jing, Qi, Liu-Jie, Li, Jing-An, Iqbal, Mujahid, and Guan, Shao-Kang
- Published
- 2024
- Full Text
- View/download PDF
54. Study on hydroforming of aluminum alloy thin-wall curved parts based on upper layer sheet and numerical simulation
- Author
-
Liu, Xiao Jing, Zou, Zhao Long, Zhou, Ying Ying, and Li, Chao
- Published
- 2024
- Full Text
- View/download PDF
55. Two-dimensional bifunctional electrocatalyst (Mo–NiFe-LDH) with multilevel structure for highly efficient overall water splitting
- Author
-
Zhang, Bao-Jie, Chang, Bin, Qiu, Shi-Peng, Zhao, Gang, Wang, Xiao, Xu, Xi-Jin, Mu, Lan, Liao, Wen-Bo, and Dong, Xiao-Jing
- Published
- 2024
- Full Text
- View/download PDF
56. Value of radiofrequency ablation for treating locally recurrent thyroid cancer: a systematic review and meta-analysis for 2-year follow-up
- Author
-
Yang, Zhen, Zhang, Mingbo, Yan, Lin, Xiao, Jing, Li, Yingying, Li, Xinyang, and Luo, Yukun
- Published
- 2024
- Full Text
- View/download PDF
57. Differentiating mixed epithelial and stromal tumor family from predominantly cystic renal cell carcinoma using magnetic resonance imaging-based Bosniak classification system version 2019
- Author
-
Guo, Hui-Ping, Xu, Wei, Hao, Yu-Wei, Kang, Huan-Huan, Zhang, Xiao-Jing, Ding, Xiao-Hui, Zhao, Jian, Bai, Xu, Zhou, Shao-Peng, Ye, Hui-Yi, and Wang, Hai-Yi
- Published
- 2024
- Full Text
- View/download PDF
58. Cerastecins inhibit membrane lipooligosaccharide transport in drug-resistant Acinetobacter baumannii
- Author
-
Wang, Hao, Ishchenko, Andrii, Skudlarek, Jason, Shen, Pamela, Dzhekieva, Liudmila, Painter, Ronald E., Chen, Yun-Ting, Bukhtiyarova, Marina, Leithead, Andrew, Tracy, Rodger, Babaoglu, Kerim, Bahnck-Teets, Carolyn, Buevich, Alexei, Cabalu, Tamara D., Labroli, Marc, Lange, Henry, Lei, Ying, Li, Wei, Liu, Jian, Mann, Paul A., Meng, Tao, Mitchell, Helen J., Mulhearn, James, Scapin, Giovanna, Sha, Deyou, Shaw, Anthony W., Si, Qian, Tong, Ling, Wu, Chengwei, Wu, Zhe, Xiao, Jing Chen, Xu, Min, Zhang, Li-Kang, McKenney, David, Miller, Randy R., Black, Todd A., Cooke, Andrew, Balibar, Carl J., Klein, Daniel J., Raheem, Izzat, and Walker, Scott S.
- Published
- 2024
- Full Text
- View/download PDF
59. Multi-status mating mechanism and incomplete bifurcation of an internal gear system with time-variant parameters and temperature
- Author
-
Ma, Xiao-jing, Shi, Jian-fei, and Zhang, Li
- Published
- 2024
- Full Text
- View/download PDF
60. Potential of neuroimaging as a biomarker in amyotrophic lateral sclerosis: from structure to metabolism
- Author
-
Sun, Wei, Liu, Si-Han, Wei, Xiao-Jing, Sun, Hui, Ma, Zhen-Wei, and Yu, Xue-Fan
- Published
- 2024
- Full Text
- View/download PDF
61. Nuclear Factor Erythroid 2-Related Factor 2 is Essential for Low-Normobaric Oxygen Treatment-Mediated Blood-Brain Barrier Protection Following Ischemic Stroke
- Author
-
Ma, Xiao-Xiao, Xie, Hai-Yi, Hou, Pin-Pin, Wang, Xiao-Jing, Zhou, Wei, and Wang, Zhen-Hong
- Published
- 2024
- Full Text
- View/download PDF
62. Consumer Financial Capability and Financial Wellbeing; Multi-Year Analyses
- Author
-
Xiao, Jing Jian, Kim, Kyoung Tae, and Lee, Sunwoo
- Published
- 2024
- Full Text
- View/download PDF
63. Microstructure and Mechanical Properties of a Highly Alloyed Al–Zn–Mg–Cu–Zr Alloy Under T6I4 and T6R6I4 Agings
- Author
-
Li, Chen, Wei, Hong-Bo, Xu, Xiao-Jing, Zhou, Qingshan, Han, Meng-Nan, and Sha, Shao-Hui
- Published
- 2024
- Full Text
- View/download PDF
64. Financial capability and financial anxiety: comparison before and during the COVID-19 pandemic
- Author
-
Xiao, Jing Jian and Meng, Kexin
- Published
- 2024
- Full Text
- View/download PDF
65. Prior Bilinear Based Models for Knowledge Graph Completion
- Author
-
Li, Jiayi, Luo, Ruilin, Sun, Jiaqi, Xiao, Jing, and Yang, Yujiu
- Subjects
Computer Science - Artificial Intelligence - Abstract
Bilinear based models are powerful and widely used approaches for Knowledge Graphs Completion (KGC). Although bilinear based models have achieved significant advances, these studies mainly concentrate on posterior properties (based on evidence, e.g. symmetry pattern) while neglecting the prior properties. In this paper, we find a prior property named "the law of identity" that cannot be captured by bilinear based models, which hinders them from comprehensively modeling the characteristics of KGs. To address this issue, we introduce a solution called Unit Ball Bilinear Model (UniBi). This model not only achieves theoretical superiority but also offers enhanced interpretability and performance by minimizing ineffective learning through minimal constraints. Experiments demonstrate that UniBi models the prior property and verify its interpretability and performance.
- Published
- 2023
66. Active perception network for non-myopic online exploration and visual surface coverage
- Author
-
Vutetakis, David and Xiao, Jing
- Subjects
Computer Science - Robotics - Abstract
This work addresses the problem of online exploration and visual sensor coverage of unknown environments. We introduce a novel perception roadmap we refer to as the Active Perception Network (APN) that serves as a hierarchical topological graph describing how to traverse and perceive an incrementally built spatial map of the environment. The APN state is incrementally updated to expand a connected configuration space that extends throughout as much of the known space as possible, using efficient difference-awareness techniques that track the discrete changes of the spatial map to inform the updates. A frontier-guided approach is presented for efficient evaluation of information gain and covisible information, which guides view sampling and refinement to ensure maximum coverage of the unmapped space is maintained within the APN. The updated roadmap is hierarchically decomposed into subgraph regions which we use to facilitate a non-myopic global view sequence planner. A comparative analysis to several state-of-the-art approaches was conducted, showing significant performance improvements in terms of total exploration time and surface coverage, and demonstrating high computational efficiency that is scalable to large and complex environments., Comment: 19 pages, 10 figures
- Published
- 2023
67. Contrastive Latent Space Reconstruction Learning for Audio-Text Retrieval
- Author
-
Luo, Kaiyi, Zhang, Xulong, Wang, Jianzong, Li, Huaxiong, Cheng, Ning, and Xiao, Jing
- Subjects
Computer Science - Sound ,Computer Science - Multimedia ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
Cross-modal retrieval (CMR) has been extensively applied in various domains, such as multimedia search engines and recommendation systems. Most existing CMR methods focus on image-to-text retrieval, whereas audio-to-text retrieval, a less explored domain, has posed a great challenge due to the difficulty to uncover discriminative features from audio clips and texts. Existing studies are restricted in the following two ways: 1) Most researchers utilize contrastive learning to construct a common subspace where similarities among data can be measured. However, they considers only cross-modal transformation, neglecting the intra-modal separability. Besides, the temperature parameter is not adaptively adjusted along with semantic guidance, which degrades the performance. 2) These methods do not take latent representation reconstruction into account, which is essential for semantic alignment. This paper introduces a novel audio-text oriented CMR approach, termed Contrastive Latent Space Reconstruction Learning (CLSR). CLSR improves contrastive representation learning by taking intra-modal separability into account and adopting an adaptive temperature control strategy. Moreover, the latent representation reconstruction modules are embedded into the CMR framework, which improves modal interaction. Experiments in comparison with some state-of-the-art methods on two audio-text datasets have validated the superiority of CLSR., Comment: Accepted by The 35th IEEE International Conference on Tools with Artificial Intelligence. (ICTAI 2023)
- Published
- 2023
68. FastGraphTTS: An Ultrafast Syntax-Aware Speech Synthesis Framework
- Author
-
Wang, Jianzong, Zhang, Xulong, Sun, Aolan, Cheng, Ning, and Xiao, Jing
- Subjects
Computer Science - Sound ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
This paper integrates graph-to-sequence into an end-to-end text-to-speech framework for syntax-aware modelling with syntactic information of input text. Specifically, the input text is parsed by a dependency parsing module to form a syntactic graph. The syntactic graph is then encoded by a graph encoder to extract the syntactic hidden information, which is concatenated with phoneme embedding and input to the alignment and flow-based decoding modules to generate the raw audio waveform. The model is experimented on two languages, English and Mandarin, using single-speaker, few samples of target speakers, and multi-speaker datasets, respectively. Experimental results show better prosodic consistency performance between input text and generated audio, and also get higher scores in the subjective prosodic evaluation, and show the ability of voice conversion. Besides, the efficiency of the model is largely boosted through the design of the AI chip operator with 5x acceleration., Comment: Accepted by The 35th IEEE International Conference on Tools with Artificial Intelligence. (ICTAI 2023)
- Published
- 2023
69. AOSR-Net: All-in-One Sandstorm Removal Network
- Author
-
Si, Yazhong, Zhang, Xulong, Yang, Fan, Wang, Jianzong, Cheng, Ning, and Xiao, Jing
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Most existing sandstorm image enhancement methods are based on traditional theory and prior knowledge, which often restrict their applicability in real-world scenarios. In addition, these approaches often adopt a strategy of color correction followed by dust removal, which makes the algorithm structure too complex. To solve the issue, we introduce a novel image restoration model, named all-in-one sandstorm removal network (AOSR-Net). This model is developed based on a re-formulated sandstorm scattering model, which directly establishes the image mapping relationship by integrating intermediate parameters. Such integration scheme effectively addresses the problems of over-enhancement and weak generalization in the field of sand dust image enhancement. Experimental results on synthetic and real-world sandstorm images demonstrate the superiority of the proposed AOSR-Net over state-of-the-art (SOTA) algorithms., Comment: Accepted by The 35th IEEE International Conference on Tools with Artificial Intelligence. (ICTAI 2023)
- Published
- 2023
70. DiffTalker: Co-driven audio-image diffusion for talking faces via intermediate landmarks
- Author
-
Qi, Zipeng, Zhang, Xulong, Cheng, Ning, Xiao, Jing, and Wang, Jianzong
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
Generating realistic talking faces is a complex and widely discussed task with numerous applications. In this paper, we present DiffTalker, a novel model designed to generate lifelike talking faces through audio and landmark co-driving. DiffTalker addresses the challenges associated with directly applying diffusion models to audio control, which are traditionally trained on text-image pairs. DiffTalker consists of two agent networks: a transformer-based landmarks completion network for geometric accuracy and a diffusion-based face generation network for texture details. Landmarks play a pivotal role in establishing a seamless connection between the audio and image domains, facilitating the incorporation of knowledge from pre-trained diffusion models. This innovative approach efficiently produces articulate-speaking faces. Experimental results showcase DiffTalker's superior performance in producing clear and geometrically accurate talking faces, all without the need for additional alignment between audio and image features., Comment: submmit to ICASSP 2024
- Published
- 2023
71. Voice Conversion with Denoising Diffusion Probabilistic GAN Models
- Author
-
Zhang, Xulong, Wang, Jianzong, Cheng, Ning, and Xiao, Jing
- Subjects
Computer Science - Sound ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
Voice conversion is a method that allows for the transformation of speaking style while maintaining the integrity of linguistic information. There are many researchers using deep generative models for voice conversion tasks. Generative Adversarial Networks (GANs) can quickly generate high-quality samples, but the generated samples lack diversity. The samples generated by the Denoising Diffusion Probabilistic Models (DDPMs) are better than GANs in terms of mode coverage and sample diversity. But the DDPMs have high computational costs and the inference speed is slower than GANs. In order to make GANs and DDPMs more practical we proposes DiffGAN-VC, a variant of GANs and DDPMS, to achieve non-parallel many-to-many voice conversion (VC). We use large steps to achieve denoising, and also introduce a multimodal conditional GANs to model the denoising diffusion generative adversarial network. According to both objective and subjective evaluation experiments, DiffGAN-VC has been shown to achieve high voice quality on non-parallel data sets. Compared with the CycleGAN-VC method, DiffGAN-VC achieves speaker similarity, naturalness and higher sound quality., Comment: Accepted by 19th International Conference on Advanced Data Mining and Applications. (ADMA 2023)
- Published
- 2023
72. Machine Unlearning Methodology base on Stochastic Teacher Network
- Author
-
Zhang, Xulong, Wang, Jianzong, Cheng, Ning, Sun, Yifu, Zhang, Chuanyao, and Xiao, Jing
- Subjects
Computer Science - Machine Learning ,Computer Science - Computer Vision and Pattern Recognition - Abstract
The rise of the phenomenon of the "right to be forgotten" has prompted research on machine unlearning, which grants data owners the right to actively withdraw data that has been used for model training, and requires the elimination of the contribution of that data to the model. A simple method to achieve this is to use the remaining data to retrain the model, but this is not acceptable for other data owners who continue to participate in training. Existing machine unlearning methods have been found to be ineffective in quickly removing knowledge from deep learning models. This paper proposes using a stochastic network as a teacher to expedite the mitigation of the influence caused by forgotten data on the model. We performed experiments on three datasets, and the findings demonstrate that our approach can efficiently mitigate the influence of target data on the model within a single epoch. This allows for one-time erasure and reconstruction of the model, and the reconstruction model achieves the same performance as the retrained model., Comment: Accepted by 19th International Conference on Advanced Data Mining and Applications. (ADMA 2023)
- Published
- 2023
73. Symbolic & Acoustic: Multi-domain Music Emotion Modeling for Instrumental Music
- Author
-
Zhu, Kexin, Zhang, Xulong, Wang, Jianzong, Cheng, Ning, and Xiao, Jing
- Subjects
Computer Science - Sound ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
Music Emotion Recognition involves the automatic identification of emotional elements within music tracks, and it has garnered significant attention due to its broad applicability in the field of Music Information Retrieval. It can also be used as the upstream task of many other human-related tasks such as emotional music generation and music recommendation. Due to existing psychology research, music emotion is determined by multiple factors such as the Timbre, Velocity, and Structure of the music. Incorporating multiple factors in MER helps achieve more interpretable and finer-grained methods. However, most prior works were uni-domain and showed weak consistency between arousal modeling performance and valence modeling performance. Based on this background, we designed a multi-domain emotion modeling method for instrumental music that combines symbolic analysis and acoustic analysis. At the same time, because of the rarity of music data and the difficulty of labeling, our multi-domain approach can make full use of limited data. Our approach was implemented and assessed using the publicly available piano dataset EMOPIA, resulting in a notable improvement over our baseline model with a 2.4% increase in overall accuracy, establishing its state-of-the-art performance., Comment: Accepted by 19th International Conference on Advanced Data Mining and Applications. (ADMA 2023)
- Published
- 2023
74. From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning
- Author
-
Li, Ming, Zhang, Yong, Li, Zhitao, Chen, Jiuhai, Chen, Lichang, Cheng, Ning, Wang, Jianzong, Zhou, Tianyi, and Xiao, Jing
- Subjects
Computer Science - Computation and Language - Abstract
In the realm of Large Language Models (LLMs), the balance between instruction data quality and quantity is a focal point. Recognizing this, we introduce a self-guided methodology for LLMs to autonomously discern and select cherry samples from open-source datasets, effectively minimizing manual curation and potential cost for instruction tuning an LLM. Our key innovation, the Instruction-Following Difficulty (IFD) metric, emerges as a pivotal metric to identify discrepancies between a model's expected responses and its intrinsic generation capability. Through the application of IFD, cherry samples can be pinpointed, leading to a marked uptick in model training efficiency. Empirical validations on datasets like Alpaca and WizardLM underpin our findings; with a mere $10\%$ of original data input, our strategy showcases improved results. This synthesis of self-guided cherry-picking and the IFD metric signifies a transformative leap in the instruction tuning of LLMs, promising both efficiency and resource-conscious advancements. Codes, data, and models are available: https://github.com/tianyi-lab/Cherry_LLM, Comment: NAACL, Camera-ready
- Published
- 2023
75. Local Distortion Aware Efficient Transformer Adaptation for Image Quality Assessment
- Author
-
Xu, Kangmin, Liao, Liang, Xiao, Jing, Chen, Chaofeng, Wu, Haoning, Yan, Qiong, and Lin, Weisi
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
Image Quality Assessment (IQA) constitutes a fundamental task within the field of computer vision, yet it remains an unresolved challenge, owing to the intricate distortion conditions, diverse image contents, and limited availability of data. Recently, the community has witnessed the emergence of numerous large-scale pretrained foundation models, which greatly benefit from dramatically increased data and parameter capacities. However, it remains an open problem whether the scaling law in high-level tasks is also applicable to IQA task which is closely related to low-level clues. In this paper, we demonstrate that with proper injection of local distortion features, a larger pretrained and fixed foundation model performs better in IQA tasks. Specifically, for the lack of local distortion structure and inductive bias of vision transformer (ViT), alongside the large-scale pretrained ViT, we use another pretrained convolution neural network (CNN), which is well known for capturing the local structure, to extract multi-scale image features. Further, we propose a local distortion extractor to obtain local distortion features from the pretrained CNN and a local distortion injector to inject the local distortion features into ViT. By only training the extractor and injector, our method can benefit from the rich knowledge in the powerful foundation models and achieve state-of-the-art performance on popular IQA datasets, indicating that IQA is not only a low-level problem but also benefits from stronger high-level features drawn from large-scale pretrained models.
- Published
- 2023
76. Calibration of the Timing Performance of GECAM-C
- Author
-
Xiao, Shuo, Liu, Ya-Qing, Gong, Ke, An, Zheng-Hua, Xiong, Shao-Lin, Li, Xin-Qiao, Wen, Xiang-Yang, Peng, Wen-Xi, Zhang, Da-Li, Tuo, You-Li, Zheng, Shi-Jie, Song, Li-Ming, Wang, Ping, Zhao, Xiao-Yun, Huang, Yue, Ma, Xiang, Liu, Xiao-Jing, Qiao, Rui, Xu, Yan-Bing, Yang, Sheng, Zhang, Fan, Wang, Yue, Zhang, Yan-Qiu, Xue, Wang-Chen, Liu, Jia-Cong, Zheng, Chao, Wang, Chen-Wei, Tan, Wen-Jun, Cai, Ce, Yi, Qi-Bin, Zhang, Peng, Luo, Xi-Hong, Yang, Jiao-Jiao, Zhi, Qi-Jun, Dong, Ai-Jun, Dang, Shi-Jun, Shang, Lun-Hua, and Zhang, Shuang-Nan
- Subjects
Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - High Energy Astrophysical Phenomena - Abstract
As a new member of the Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) after GECAM-A and GECAM-B, GECAM-C (originally called HEBS), which was launched on board the SATech-01 satellite on July 27, 2022, aims to monitor and localize X-ray and gamma-ray transients from $\sim$ 6 keV to 6 MeV. GECAM-C utilizes a similar design to GECAM but operates in a more complex orbital environment. In this work, we utilize the secondary particles simultaneously produced by the cosmic-ray events on orbit and recorded by multiple detectors, to calibrate the relative timing accuracy between all detectors of GECAM-C. We find the result is 0.1 $\mu \rm s$, which is the highest time resolution among all GRB detectors ever flown and very helpful in timing analyses such as minimum variable timescale and spectral lags, as well as in time delay localization. Besides, we calibrate the absolute time accuracy using the one-year Crab pulsar data observed by GECAM-C and Fermi/GBM, as well as GECAM-C and GECAM-B. The results are $2.02\pm 2.26\ \mu \rm s$ and $5.82\pm 3.59\ \mu \rm s$, respectively. Finally, we investigate the spectral lag between the different energy bands of Crab pulsar observed by GECAM and GBM, which is $\sim -0.2\ {\rm \mu s\ keV^{-1}}$., Comment: submitted
- Published
- 2023
77. PMVC: Data Augmentation-Based Prosody Modeling for Expressive Voice Conversion
- Author
-
Deng, Yimin, Tang, Huaizhen, Zhang, Xulong, Wang, Jianzong, Cheng, Ning, and Xiao, Jing
- Subjects
Computer Science - Sound ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
Voice conversion as the style transfer task applied to speech, refers to converting one person's speech into a new speech that sounds like another person's. Up to now, there has been a lot of research devoted to better implementation of VC tasks. However, a good voice conversion model should not only match the timbre information of the target speaker, but also expressive information such as prosody, pace, pause, etc. In this context, prosody modeling is crucial for achieving expressive voice conversion that sounds natural and convincing. Unfortunately, prosody modeling is important but challenging, especially without text transcriptions. In this paper, we firstly propose a novel voice conversion framework named 'PMVC', which effectively separates and models the content, timbre, and prosodic information from the speech without text transcriptions. Specially, we introduce a new speech augmentation algorithm for robust prosody extraction. And building upon this, mask and predict mechanism is applied in the disentanglement of prosody and content information. The experimental results on the AIShell-3 corpus supports our improvement of naturalness and similarity of converted speech., Comment: Accepted by the 31st ACM International Conference on Multimedia (MM2023)
- Published
- 2023
- Full Text
- View/download PDF
78. EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices
- Author
-
Wang, Liang, Zhang, Nan, Qu, Xiaoyang, Wang, Jianzong, Wan, Jiguang, Li, Guokuan, Hu, Kaiyu, Jiang, Guilin, and Xiao, Jing
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence - Abstract
Real-time video analytics on edge devices for changing scenes remains a difficult task. As edge devices are usually resource-constrained, edge deep neural networks (DNNs) have fewer weights and shallower architectures than general DNNs. As a result, they only perform well in limited scenarios and are sensitive to data drift. In this paper, we introduce EdgeMA, a practical and efficient video analytics system designed to adapt models to shifts in real-world video streams over time, addressing the data drift problem. EdgeMA extracts the gray level co-occurrence matrix based statistical texture feature and uses the Random Forest classifier to detect the domain shift. Moreover, we have incorporated a method of model adaptation based on importance weighting, specifically designed to update models to cope with the label distribution shift. Through rigorous evaluation of EdgeMA on a real-world dataset, our results illustrate that EdgeMA significantly improves inference accuracy., Comment: Accepted by 30th International Conference on Neural Information Processing (ICONIP 2023)
- Published
- 2023
79. Boosting Chinese ASR Error Correction with Dynamic Error Scaling Mechanism
- Author
-
Fan, Jiaxin, Zhang, Yong, Li, Hanzhang, Wang, Jianzong, Li, Zhitao, Ouyang, Sheng, Cheng, Ning, and Xiao, Jing
- Subjects
Computer Science - Computation and Language ,Computer Science - Artificial Intelligence - Abstract
Chinese Automatic Speech Recognition (ASR) error correction presents significant challenges due to the Chinese language's unique features, including a large character set and borderless, morpheme-based structure. Current mainstream models often struggle with effectively utilizing word-level features and phonetic information. This paper introduces a novel approach that incorporates a dynamic error scaling mechanism to detect and correct phonetically erroneous text generated by ASR output. This mechanism operates by dynamically fusing word-level features and phonetic information, thereby enriching the model with additional semantic data. Furthermore, our method implements unique error reduction and amplification strategies to address the issues of matching wrong words caused by incorrect characters. Experimental results indicate substantial improvements in ASR error correction, demonstrating the effectiveness of our proposed method and yielding promising results on established datasets., Comment: Accepted by 24th Annual Conference of the International Speech Communication Association (INTERSPEECH 2023)
- Published
- 2023
80. Prompt Guided Copy Mechanism for Conversational Question Answering
- Author
-
Zhang, Yong, Li, Zhitao, Wang, Jianzong, Gao, Yiming, Cheng, Ning, Yu, Fengying, and Xiao, Jing
- Subjects
Computer Science - Computation and Language ,Computer Science - Artificial Intelligence - Abstract
Conversational Question Answering (CQA) is a challenging task that aims to generate natural answers for conversational flow questions. In this paper, we propose a pluggable approach for extractive methods that introduces a novel prompt-guided copy mechanism to improve the fluency and appropriateness of the extracted answers. Our approach uses prompts to link questions to answers and employs attention to guide the copy mechanism to verify the naturalness of extracted answers, making necessary edits to ensure that the answers are fluent and appropriate. The three prompts, including a question-rationale relationship prompt, a question description prompt, and a conversation history prompt, enhance the copy mechanism's performance. Our experiments demonstrate that this approach effectively promotes the generation of natural answers and achieves good results in the CoQA challenge., Comment: Accepted by 24th Annual Conference of the International Speech Communication Association (INTERSPEECH 2023)
- Published
- 2023
81. Establishing Virtual Bioequivalence and Clinically Relevant Specifications for Omeprazole Enteric-Coated Capsules by Incorporating Dissolution Data in PBPK Modeling
- Author
-
Yang, Ruwei, Lin, Yaqi, Chen, Kaifeng, Huang, Jie, Yang, Shuang, Yao, An, Yang, Xiaoyan, Lei, Deqing, Xiao, Jing, Yang, Guoping, and Pei, Qi
- Published
- 2024
- Full Text
- View/download PDF
82. The programmed death ligand 1 interactome demonstrates bidirectional signaling coordinating immune suppression and cancer progression in head and neck squamous cell carcinoma.
- Author
-
Nieto, Cera, Miller, Bettina, Alzofon, Nathaniel, Chimed, Tugy, Himes, Jack, Joshi, Molishree, Gomez, Karina, Chowdhury, Farshad, Le, Phuong, Weaver, Alice, Somerset, Hilary, Morton, J, Wang, Jing, Wang, Xiao-Jing, Gao, Dexiang, Hansen, Kirk, Keysar, Stephen, and Jimeno, Antonio
- Subjects
Animals ,Humans ,Mice ,B7-H1 Antigen ,Head and Neck Neoplasms ,Mice ,Inbred NOD ,Programmed Cell Death 1 Receptor ,Squamous Cell Carcinoma of Head and Neck - Abstract
BACKGROUND: The programmed cell death protein 1 (PD-1) and programmed death ligand 1 (PD-L1) are validated cancer targets; however, emerging mechanisms and impact of PD-L1 intracellular signaling on cancer behavior are poorly understood. METHODS: We investigated the cancer cell intrinsic role of PD-L1 in multiple patient-derived models in vitro and in vivo. PD-L1 overexpression, knockdown, and PD-L1 intracellular domain (PD-L1-ICD) deletion (Δ260-290PD-L1) models were assessed for key cancer properties: clonogenicity, motility, invasion, and immune evasion. To determine how PD-L1 transduces signals intracellularly, we used the BioID2 platform to identify the PD-L1 intracellular interactome. Both human papillomavirus-positive and negative patient-derived xenografts were implanted in NOD-scid-gamma and humanized mouse models to investigate the effects of recombinant PD-1, anti-PD-L1, and anti-signal transducer and activator of transcription 3 (STAT3) in vivo. RESULTS: PD-L1 intracellular signaling increased clonogenicity, motility, and invasiveness in multiple head and neck squamous cell carcinoma (HNSCC) models, and PD-1 binding enhanced these effects. Protein proximity labeling revealed the PD-L1 interactome, distinct for unbound and bound PD-1, which initiated cancer cell-intrinsic signaling. PD-L1 binding partners interleukin enhancer binding factors 2 and 3 (ILF2-ILF3) transduced their effect through STAT3. Δ260-290PD-L1 disrupted signaling and reversed pro-growth properties. In humanized HNSCC in vivo models bearing T-cells, PD-1 binding triggered PD-L1 signaling, and dual PD-L1 and STAT3 inhibition were required to achieve tumor control. CONCLUSIONS: Upon PD-1 binding, the PD-L1 extracellular and intracellular domains exert a synchronized effect to promote immune evasion by inhibiting T-cell function while simultaneously enhancing cancer cell-invasive properties.
- Published
- 2023
83. IL-22RA2 Is a SMAD7 Target Mediating the Alleviation of Dermatitis and Psoriatic Phenotypes in Mice.
- Author
-
Ke, Yao, Li, Ben-Zheng, Nguyen, Khoa, Wang, Donna, Wang, Suyan, Young, Christian, and Wang, Xiao-Jing
- Subjects
Mice ,Humans ,Animals ,Imiquimod ,Smad7 Protein ,Skin ,Psoriasis ,Dermatitis ,Keratinocytes ,Inflammation ,Phenotype ,Disease Models ,Animal ,Mice ,Inbred BALB C ,Receptors ,Interleukin - Abstract
Long-term management of inflammatory skin diseases is challenging because of side effects from repeated use of systemic treatments or topical corticosteroids. This study sought to identify the mechanisms and developmental therapeutics for these diseases using genetic models and pharmacological approaches. We found that mice overexpressing SMAD7 in keratinocytes but not mice overexpressing the N-terminal domain of SMAD7 (i.e., N-SMAD7) were resistant to imiquimod-induced T helper 1/17- and T helper 2-type inflammation. We generated a Tat-PYC-SMAD7 (truncated SMAD7 protein encompassing C-terminal SMAD7 and PY motif fused with cell-penetrating Tat peptide). Topically applied Tat-PYC-SMAD7 to inflamed skin entered cells upon contact and attenuated imiquimod-, 2,4-dinitrofluorobenzene-, and tape-stripping-induced inflammation. RNA-sequencing analyses of mouse skin exposed to these insults showed that in addition to inhibiting TGFβ/NF-κB, SMAD7 blunted IL-22/signal transducer and activator of transcription 3 activation and associated pathogenesis, which is due to SMAD7 transcriptionally upregulating IL-22 antagonist IL-22RA2. Mechanistically, SMAD7 facilitated nuclear translocation and DNA binding of C/EBPβ to IL22RA2 promoter for IL22RA2 transactivation. Consistent with the observations in mice mentioned earlier, transcript levels of IL22RA2 were increased in human atopic dermatitis and psoriasis lesions with clinical remission. Our study identified the anti-inflammation functional domain of SMAD7 and suggests the mechanism and feasibility for developing SMAD7-based biologics as a topical therapy for skin inflammatory disorders.
- Published
- 2023
84. Corneal nerve changes by anti-glaucoma medications examined by in vivo confocal microscopy
- Author
-
Xin-Yuan Zhu, Qing-Shu Ge, Zong-Yi Li, Long-Fang Zhou, Qian-Wen Bu, Ying Su, Xin-Jie Wang, Qing-Jun Zhou, Xiao-Jing Pan, and Die Hu
- Subjects
glaucoma therapy ,corneal nerve fibers ,in vivo confocal microscopy ,accmetrics ,Ophthalmology ,RE1-994 - Abstract
AIM: To evaluate the effects of antiglaucoma eye drops on corneal nerves by in vivo confocal microscopy (IVCM). METHODS: This study comprised 79 patients diagnosed with glaucoma and 16 healthy control individuals. Among the glaucoma patients, 54 were treated with medication, while 25 remained untreated. Central corneal images were evaluated by IVCM, and then ACCMetrics was used to calculate the following parameters: corneal nerve fiber density (CNFD), branch density (CNBD), fiber length (CNFL), total branch density (CTBD), fiber area (CNFA), fiber width (CNFW), and fractal dimension (CNFrD). The correlation between IVCM parameters and drugs was evaluated using non-parametric measurements of Spearman's rank correlation coefficient. RESULTS: The CNFD was reduced in glaucoma groups compared to healthy subjects (P
- Published
- 2024
- Full Text
- View/download PDF
85. DiffRank: Enhancing efficiency in discontinuous frame rate analysis for urban surveillance systems
- Author
-
Ziying Cheng, Zhe Li, Tianfan Zhang, Xiaochao Zhao, and Xiao Jing
- Subjects
Video image processing ,Portrait detection ,Public security management ,Two-stage algorithm ,Change detection ,Engineering (General). Civil engineering (General) ,TA1-2040 - Abstract
Urban public safety management relies heavily on video surveillance systems, which provide crucial visual data for resolving a wide range of incidents and controlling unlawful activities. Traditional methods for target detection predominantly employ a two-stage approach, focusing on precision in identifying objects such as pedestrians and vehicles. These objects, typically sparse in large-scale, lower-quality surveillance footage, induce considerable redundant computation during the initial processing stage. This redundancy constrains real-time detection capabilities and escalates processing costs. Furthermore, transmitting raw images and videos laden with superfluous information to centralized back-end systems significantly burdens network communications and fails to capitalize on the computational resources available at diverse surveillance nodes. This study introduces DiffRank, a novel preprocessing method for fixed-angle video imagery in urban surveillance. The method strategically generates candidate regions during preprocessing, thereby reducing redundant object detection and improving the efficiency of the detection algorithm. Drawing upon change detection principles, a background feature learning approach utilizing shallow features has been developed. This approach prioritizes learning the characteristics of fixed-area backgrounds over direct background identification. As a result, alterations in ROI are efficiently discerned using computationally efficient shallow features, markedly accelerating the generation of proposed Regions of Interest (ROIs) and diminishing the computational demands for subsequent object detection and classification. Comparative analysis on various public and private datasets illustrates that DiffRank, while maintaining high accuracy, substantially outperforms existing baselines in terms of speed, particularly with larger image sizes (e.g., an improvement exceeding 300 % at 1920×1080 resolution). Moreover, the method demonstrates enhanced robustness compared to baseline methods, efficiently disregarding static targets like mannequins in display windows. The advancements in candidate area preprocessing enable a balanced approach between detection accuracy and overall detection speed, making the algorithm highly applicable for real-time on-site analysis in edge computing scenarios and cloud-edge collaborative computing environments.
- Published
- 2024
- Full Text
- View/download PDF
86. Accuracy of cell-free Mycobacterium tuberculosis DNA testing in pleural effusion for diagnosing tuberculous pleurisy: a multicenter cross-sectional study
- Author
-
Wei-Li Du, Jian-Qin Liang, Xin-Ting Yang, Cheng-Jun Li, Qing-Feng Wang, Wen-Ge Han, Ye Li, Zhi-Hui Li, Dong-Mei Zhao, Fu-Dong Xu, Yan-Xiao Rong, Xiao-Jing Cui, Hui-Min Li, Feng Wang, Peng-Chong Liu, Dong-Lin Guo, Hai-Bin Wang, Xu-Ya Xing, Jia-Lu Che, Zi-Chen Liu, Na-Na Zhang, Kun Li, Yi Liu, Li Wang, Hai-Bo Wang, and Nan-Ying Che
- Subjects
Cell-free Mycobacterium tuberculosis DNA (cf-TB) ,Pleural effusion (PE) ,Tuberculous pleurisy (TP) ,Diagnosis ,Medicine (General) ,R5-920 ,Military Science - Abstract
Abstract Background The diagnosis of tuberculous pleurisy (TP) presents a significant challenge due to the low bacterial load in pleural effusion (PE) samples. Cell-free Mycobacterium tuberculosis DNA (cf-TB) in PE samples is considered an optimal biomarker for diagnosing TP. This study aimed to evaluate the applicability of cf-TB testing across diverse research sites with a relatively large sample size. Methods Patients suspected of TP and presenting with clinical symptoms and radiological evidence of PE were consecutively enrolled by treating physicians from 11 research sites across 6 provinces in China between April 2020 and August 2022. Following centrifugation, sediments obtained from PE were used for Xpert MTB/RIF (Xpert) and mycobacterial culture, while the supernatants were subjected to cf-TB testing. This study employed a composite reference standard to definite TP, which was characterized by any positive result for Mycobacterium tuberculosis (MTB) through either PE culture, PE Xpert, or pleural biopsy. Results A total of 1412 participants underwent screening, and 1344 (95.2%) were subsequently enrolled in this study. Data from 1241 (92.3%) participants were included, comprising 284 with definite TP, 677 with clinically diagnosed TP, and 280 without TP. The sensitivity of cf-TB testing in definite TP was 73.6% (95% CI 68.2–78.4), significantly higher than both Xpert (40.8%, 95% CI 35.3–46.7, P
- Published
- 2024
- Full Text
- View/download PDF
87. Basis-independent quantum coherence and its distribution under relativistic motion
- Author
-
Ming-Ming Du, Hong-Wei Li, Zhen Tao, Shu-Ting Shen, Xiao-Jing Yan, Xi-Yun Li, Wei Zhong, Yu-Bo Sheng, and Lan Zhou
- Subjects
Astrophysics ,QB460-466 ,Nuclear and particle physics. Atomic energy. Radioactivity ,QC770-798 - Abstract
Abstract Recent studies have increasingly focused on the effect of relativistic motion on quantum coherence. Prior research predominantly examined the influence of relative motion on basis-dependent quantum coherence, underscoring its susceptibility to decoherence under accelerated conditions. Yet, the effect of relativistic motion on basis-independent quantum coherence, which is critical for understanding the intrinsic quantum features of a system, remains an interesting open question. This paper addresses this question by examining how total, collective, and localized coherence are affected by acceleration and coupling strength. Our analysis reveals that both total and collective coherence significantly decrease with increasing acceleration and coupling strength, ultimately vanishing at high levels of acceleration. This underscores the profound impact of Unruh thermal noise. Conversely, localized coherence exhibits relative stability, decreasing to zero only under the extreme condition of infinite acceleration. Moreover, we demonstrate that collective, localized, and basis-independent coherence collectively satisfy the triangle inequality. These findings are crucial for enhancing our understanding of quantum information dynamics in environments subjected to high acceleration and offer valuable insights on the behavior of quantum coherence under relativistic conditions.
- Published
- 2024
- Full Text
- View/download PDF
88. Flexible gating between subspaces in a neural network model of internally guided task switching
- Author
-
Yue Liu and Xiao-Jing Wang
- Subjects
Science - Abstract
Abstract Behavioral flexibility relies on the brain’s ability to switch rapidly between multiple tasks, even when the task rule is not explicitly cued but must be inferred through trial and error. The underlying neural circuit mechanism remains poorly understood. We investigated recurrent neural networks (RNNs) trained to perform an analog of the classic Wisconsin Card Sorting Test. The networks consist of two modules responsible for rule representation and sensorimotor mapping, respectively, where each module is comprised of a circuit with excitatory neurons and three major types of inhibitory neurons. We found that rule representation by self-sustained persistent activity across trials, error monitoring and gated sensorimotor mapping emerged from training. Systematic dissection of trained RNNs revealed a detailed circuit mechanism that is consistent across networks trained with different hyperparameters. The networks’ dynamical trajectories for different rules resided in separate subspaces of population activity; the subspaces collapsed and performance was reduced to chance level when dendrite-targeting somatostatin-expressing interneurons were silenced, illustrating how a phenomenological description of representational subspaces is explained by a specific circuit mechanism.
- Published
- 2024
- Full Text
- View/download PDF
89. Systematic druggable genome‐wide Mendelian randomization identifies therapeutic targets for sarcopenia
- Author
-
Kang‐Fu Yin, Ting Chen, Xiao‐Jing Gu, Wei‐Ming Su, Zheng Jiang, Si‐Jia Lu, Bei Cao, Li‐Yi Chi, Xia Gao, and Yong‐Ping Chen
- Subjects
Colocalization ,Druggable genes ,Mendelian randomization ,Sarcopenia ,Diseases of the musculoskeletal system ,RC925-935 ,Human anatomy ,QM1-695 - Abstract
Abstract Background There are no effective pharmacological treatments for sarcopenia. We aim to identify potential therapeutic targets for sarcopenia by integrating various publicly available datasets. Methods We integrated druggable genome data, cis‐eQTL/cis‐pQTL from human blood and skeletal muscle tissue, and GWAS summary data of sarcopenia‐related traits to analyse the potential causal relationships between drug target genes and sarcopenia using the Mendelian Randomization (MR) method. Sensitivity analyses and Bayesian colocalization were employed to validate the causal relationships. We also assessed the side effects or additional indications of the identified drug targets using a phenome‐wide MR (Phe‐MR) approach and investigated actionable drugs for target genes using available databases. Results MR analysis identified 17 druggable genes with potential causation to sarcopenia in human blood or skeletal muscle tissue. Six of them (HP, HLA‐DRA, MAP 3K3, MFGE8, COL15A1, and AURKA) were further confirmed by Bayesian colocalization (PPH4 > 90%). The up‐regulation of HP [higher ALM (beta: 0.012, 95% CI: 0.007–0.018, P = 1.2*10−5) and higher grip strength (OR: 0.96, 95% CI: 0.94–0.98, P = 4.2*10−5)], MAP 3K3 [higher ALM (beta: 0.24, 95% CI: 0.21–0.26, P = 1.8*10−94), higher grip strength (OR: 0.82, 95% CI: 0.75–0.90, P = 2.1*10−5), and faster walking pace (beta: 0.03, 95% CI: 0.02–0.05, P = 8.5*10−6)], and MFGE8 [higher ALM (muscle eQTL, beta: 0.09, 95% CI: 0.06–0.11, P = 6.1*10−13; blood pQTL, beta: 0.05, 95% CI: 0.03–0.07, P = 3.8*10−09)], as well as the down‐regulation of HLA‐DRA [lower ALM (beta: ‐0.09, 95% CI: −0.11 to −0.08, P = 5.4*10−36) and lower grip strength (OR: 1.13, 95% CI: 1.07–1.20, P = 1.8*10−5)] and COL15A1 [higher ALM (muscle eQTL, beta: ‐0.07, 95% CI: −0.10 to −0.04, P = 3.4*10−07; blood pQTL, beta: ‐0.05, 95% CI: −0.06 to −0.03, P = 1.6*10−07)], decreased the risk of sarcopenia. AURKA in blood (beta: ‐0.16, 95% CI: −0.22 to −0.09, P = 2.1*10−06) and skeletal muscle (beta: 0.03, 95% CI: 0.02 to 0.05, P = 5.3*10−05) tissues showed an inverse relationship with sarcopenia risk. The Phe‐MR indicated that the six potential therapeutic targets for sarcopenia had no significant adverse effects. Drug repurposing analysis supported zinc supplementation and collagenase clostridium histolyticum might be potential therapeutics for sarcopenia by activating HP and inhibiting COL15A1, respectively. Conclusions Our research indicated MAP 3K3, MFGE8, COL15A1, HP, and HLA‐DRA may serve as promising targets for sarcopenia, while the effectiveness of zinc supplementation and collagenase clostridium histolyticum for sarcopenia requires further validation.
- Published
- 2024
- Full Text
- View/download PDF
90. Knockdown of fibrillin-1 suppresses retina-blood barrier dysfunction by inhibiting vascular endothelial apoptosis under diabetic conditions
- Author
-
Yue Zhang, Xiao-Jing Liu, Xin-Ran Zhai, Yao Yao, Bin Shao, Yu-Han Zhen, Xin Zhang, Zhe Xiao, Li-Fang Wang, Ming-Lian Zhang, and Zhi-Min Chen
- Subjects
diabetic retinopathy ,fibrillin-1 ,retina-blood barrier ,vascular leakage ,vascular permeability ,apoptosis ,retinal vascular endothelial cells ,Ophthalmology ,RE1-994 - Abstract
AIM: To investigate the effects of fibrillin-1 (FBN1) deletion on the integrity of retina-blood barrier function and the apoptosis of vascular endothelial cells under diabetic conditions. METHODS: Streptozotocin (STZ)-induced diabetic mice were used to simulate the diabetic conditions of diabetic retinopathy (DR) patients, and FBN1 expression was detected in retinas from STZ-diabetic mice and controls. In the Gene Expression Omnibus (GEO) database, the GSE60436 dataset was selected to analyze FBN1 expressions in fibrovascular membranes from DR patients. Using lentivirus to knock down FBN1 levels, vascular leakage and endothelial barrier integrity were detected by Evans blue vascular permeability assay, fluorescein fundus angiography (FFA) and immunofluorescence labeled with tight junction marker in vivo. High glucose-induced monkey retinal vascular endothelial cells (RF/6A) were used to investigate effects of FBN1 on the cells in vitro. The vascular endothelial barrier integrity and apoptosis were detected by trans-endothelial electrical resistance (TEER) assay and flow cytometry, respectively. RESULTS: FBN1 mRNA expression was increased in retinas of STZ-induced diabetic mice and fibrovascular membranes of DR patients (GSE60436 datasets) using RNA-seq approach. Besides, knocking down of FBN1 by lentivirus intravitreal injection significantly inhibited the vascular leakage compared to STZ-DR group by Evans blue vascular permeability assay and FFA detection. Expressions of tight junction markers in STZ-DR mouse retinas were lower than those in the control group, and knocking down of FBN1 increased the tight junction levels. In vitro, 30 mmol/L glucose could significantly inhibit viability of RF/6A cells, and FBN1 mRNA expression was increased under 30 mmol/L glucose stimulation. Down-regulation of FBN1 reduced high glucose (HG)-stimulated retinal microvascular endothelial cell permeability, increased TEER, and inhibited RF/6A cell apoptosis in vitro. CONCLUSION: The expression level of FBN1 increases in retinas and vascular endothelial cells under diabetic conditions. Down-regulation of FBN1 protects the retina of early diabetic rats from retina-blood barrier damage, reduce vascular leakage, cell apoptosis, and maintain vascular endothelial cell barrier function.
- Published
- 2024
- Full Text
- View/download PDF
91. Research Progress on the Development and Testing Techniques of Novel Food Raw Materials at Home and Abroad
- Author
-
XIAO Cenjun, WANG Dong, XIU Fanchao, WU Junjie, XIAO Jing, WU Yuan, XU Dunming, PANG Jie
- Subjects
novel food raw materials ,laws and regulations ,definition ,management ,standard ,analysis and detection ,Food processing and manufacture ,TP368-456 - Abstract
This study systematically reviewed the Chinese and international laws, regulations and scientific guidelines regarding novel food raw materials. It clarified the basic definition of “novel food raw materials” and related concepts at home and abroad, and elaborated on the changes in the nomenclature and types of novel food raw materials in China. It also gave a brief overview of the categories and scope of novel food raw materials abroad, a general explanation of declaration information and approval management of novel food raw materials, a brief summary of China’s standards for testing novel food raw materials, and a detailed review of various analytical methods for non-microbial novel food raw materials such as liquid chromatography, gas chromatography and mass spectrometry in order to provide reference for the standardization and uniform detection of novel food raw materials in China.
- Published
- 2024
- Full Text
- View/download PDF
92. Association of caesarean scar defect with risk of abnormal uterine bleeding: results from meta-analysis
- Author
-
Xiao-Jing Xu, Jing-Xing Jia, Zi-Qiong Sang, and Li Li
- Subjects
Caesarean scar defects ,Abnormal uterine bleeding ,Meta-analysis ,Gynecology and obstetrics ,RG1-991 ,Public aspects of medicine ,RA1-1270 - Abstract
Abstract Objective To investigate the association between caesarean scar defects and abnormal uterine bleeding through systematic literature review. Methods PubMed, Web of Science, Cochrane Library and Embase databases were searched based on PRISMA 2020 to include studies exploring abnormal uterine bleeding in women with caesarean scar defects. The combined relative risk (RR) of uterine bleeding, combined prevalence of abnormal uterine bleeding and combined RR of intermenstrual uterine bleeding were calculated using a fixed- or random-effects model. Results Ten studies involving 1,183 women with caesarean scar defects met the inclusion criteria for this study. Compared with women without caesarean scar defects, those with caesarean scar defects had a higher risk of abnormal uterine bleeding (RR: 3.22, 95% CI: 1.83–5.66) and intermenstrual bleeding (RR: 2.93, 95% CI: 1.91–4.50). The prevalence of abnormal uterine bleeding was approximately 0.46 (95% CI: 0.27–0.64), and across populations, women with a previous caesarean section who had undergone imaging specifically for gynaecological disease had a significantly higher prevalence of abnormal uterine bleeding (0.77, 95% CI: 0.65–0.89) than those with at least one caesarean Sect. (0.25, 95% CI: 0.10–0.39). Conclusion A significant association was observed between caesarean scar defects and abnormal uterine bleeding, with the former being a risk factor for the latter. However, previous studies have differed in the definition of caesarean scar defects and abnormal uterine bleeding, and more high-quality studies are needed to further investigate the relevant definitions and study results in the future.
- Published
- 2024
- Full Text
- View/download PDF
93. Artificial sweeteners and risk of incident cardiovascular disease and mortality: evidence from UK Biobank
- Author
-
Tao Sun, Juan Yang, Fang Lei, Xuewei Huang, Weifang Liu, Xingyuan Zhang, Lijin Lin, Linsu Sun, Xinlan Xie, Xiao-Jing Zhang, Jingjing Cai, Zhi-Gang She, Chengsheng Xu, and Hongliang Li
- Subjects
Diseases of the circulatory (Cardiovascular) system ,RC666-701 - Abstract
Abstract Background Artificial sweeteners are widely popular worldwide as substitutes for sugar or caloric sweeteners, but there are still several important unknowns and controversies regarding their associations with cardiovascular disease (CVD). We aimed to extensively assess the association and subgroup variability between artificial sweeteners and CVD and CVD mortality in the UK Biobank cohort, and further investigate the modification effects of genetic susceptibility and the mediation role of type 2 diabetes mellitus (T2DM). Methods This study included 133,285 participants in the UK Biobank who were free of CVD and diabetes at recruitment. Artificial sweetener intake was obtained from repeated 24-hour diet recalls. Cox proportional hazard models were used to estimate HRs. Genetic predisposition was estimated using the polygenic risk score (PRS). Furthermore, time-dependent mediation was performed. Results In our study, artificial sweetener intake (each teaspoon increase) was significantly associated with an increased risk of incident overall CVD (HR1.012, 95%CI: 1.008,1.017), coronary artery disease (CAD) (HR: 1.018, 95%CI: 1.001,1.035), peripheral arterial disease (PAD) (HR: 1.035, 95%CI: 1.010,1.061), and marginally significantly associated with heart failure (HF) risk (HR: 1.018, 95%CI: 0.999,1.038). In stratified analyses, non-whites were at greater risk of incident overall CVD from artificial sweetener. People with no obesity (BMI
- Published
- 2024
- Full Text
- View/download PDF
94. Financial Adaptation Among College Students: Helping Students Cope with Financial Strain
- Author
-
Serido, Joyce, Shim, Soyeon, Xiao, Jing Jian, Tang, Chuanyi, and Card, Noel A.
- Published
- 2014
- Full Text
- View/download PDF
95. FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer
- Author
-
Liu, Chenghao, Qu, Xiaoyang, Wang, Jianzong, and Xiao, Jing
- Subjects
Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
Federated Learning (FL) has been widely concerned for it enables decentralized learning while ensuring data privacy. However, most existing methods unrealistically assume that the classes encountered by local clients are fixed over time. After learning new classes, this assumption will make the model's catastrophic forgetting of old classes significantly severe. Moreover, due to the limitation of communication cost, it is challenging to use large-scale models in FL, which will affect the prediction accuracy. To address these challenges, we propose a novel framework, Federated Enhanced Transformer (FedET), which simultaneously achieves high accuracy and low communication cost. Specifically, FedET uses Enhancer, a tiny module, to absorb and communicate new knowledge, and applies pre-trained Transformers combined with different Enhancers to ensure high precision on various tasks. To address local forgetting caused by new classes of new tasks and global forgetting brought by non-i.i.d (non-independent and identically distributed) class imbalance across different local clients, we proposed an Enhancer distillation method to modify the imbalance between old and new knowledge and repair the non-i.i.d. problem. Experimental results demonstrate that FedET's average accuracy on representative benchmark datasets is 14.1% higher than the state-of-the-art method, while FedET saves 90% of the communication cost compared to the previous method., Comment: Accepted by 2023 International Joint Conference on Artificial Intelligence (IJCAI2023)
- Published
- 2023
96. Shoggoth: Towards Efficient Edge-Cloud Collaborative Real-Time Video Inference via Adaptive Online Learning
- Author
-
Wang, Liang, Lu, Kai, Zhang, Nan, Qu, Xiaoyang, Wang, Jianzong, Wan, Jiguang, Li, Guokuan, and Xiao, Jing
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence - Abstract
This paper proposes Shoggoth, an efficient edge-cloud collaborative architecture, for boosting inference performance on real-time video of changing scenes. Shoggoth uses online knowledge distillation to improve the accuracy of models suffering from data drift and offloads the labeling process to the cloud, alleviating constrained resources of edge devices. At the edge, we design adaptive training using small batches to adapt models under limited computing power, and adaptive sampling of training frames for robustness and reducing bandwidth. The evaluations on the realistic dataset show 15%-20% model accuracy improvement compared to the edge-only strategy and fewer network costs than the cloud-only strategy., Comment: Accepted by 60th ACM/IEEE Design Automation Conference (DAC2023)
- Published
- 2023
97. TransRef: Multi-Scale Reference Embedding Transformer for Reference-Guided Image Inpainting
- Author
-
Liao, Liang, Liu, Taorong, Chen, Delin, Xiao, Jing, Wang, Zheng, Lin, Chia-Wen, and Satoh, Shin'ichi
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
Image inpainting for completing complicated semantic environments and diverse hole patterns of corrupted images is challenging even for state-of-the-art learning-based inpainting methods trained on large-scale data. A reference image capturing the same scene of a corrupted image offers informative guidance for completing the corrupted image as it shares similar texture and structure priors to that of the holes of the corrupted image. In this work, we propose a transformer-based encoder-decoder network, named TransRef, for reference-guided image inpainting. Specifically, the guidance is conducted progressively through a reference embedding procedure, in which the referencing features are subsequently aligned and fused with the features of the corrupted image. For precise utilization of the reference features for guidance, a reference-patch alignment (Ref-PA) module is proposed to align the patch features of the reference and corrupted images and harmonize their style differences, while a reference-patch transformer (Ref-PT) module is proposed to refine the embedded reference feature. Moreover, to facilitate the research of reference-guided image restoration tasks, we construct a publicly accessible benchmark dataset containing 50K pairs of input and reference images. Both quantitative and qualitative evaluations demonstrate the efficacy of the reference information and the proposed method over the state-of-the-art methods in completing complex holes. Code and dataset can be accessed at https://github.com/Cameltr/TransRef., Comment: Under review
- Published
- 2023
98. EmoMix: Emotion Mixing via Diffusion Models for Emotional Speech Synthesis
- Author
-
Tang, Haobin, Zhang, Xulong, Wang, Jianzong, Cheng, Ning, and Xiao, Jing
- Subjects
Computer Science - Sound ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
There has been significant progress in emotional Text-To-Speech (TTS) synthesis technology in recent years. However, existing methods primarily focus on the synthesis of a limited number of emotion types and have achieved unsatisfactory performance in intensity control. To address these limitations, we propose EmoMix, which can generate emotional speech with specified intensity or a mixture of emotions. Specifically, EmoMix is a controllable emotional TTS model based on a diffusion probabilistic model and a pre-trained speech emotion recognition (SER) model used to extract emotion embedding. Mixed emotion synthesis is achieved by combining the noises predicted by diffusion model conditioned on different emotions during only one sampling process at the run-time. We further apply the Neutral and specific primary emotion mixed in varying degrees to control intensity. Experimental results validate the effectiveness of EmoMix for synthesizing mixed emotion and intensity control., Comment: Accepted by 24th Annual Conference of the International Speech Communication Association (INTERSPEECH 2023)
- Published
- 2023
99. SVVAD: Personal Voice Activity Detection for Speaker Verification
- Author
-
Kang, Zuheng, Wang, Jianzong, Peng, Junqing, and Xiao, Jing
- Subjects
Computer Science - Sound ,Computer Science - Artificial Intelligence ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
Voice activity detection (VAD) improves the performance of speaker verification (SV) by preserving speech segments and attenuating the effects of non-speech. However, this scheme is not ideal: (1) it fails in noisy environments or multi-speaker conversations; (2) it is trained based on inaccurate non-SV sensitive labels. To address this, we propose a speaker verification-based voice activity detection (SVVAD) framework that can adapt the speech features according to which are most informative for SV. To achieve this, we introduce a label-free training method with triplet-like losses that completely avoids the performance degradation of SV due to incorrect labeling. Extensive experiments show that SVVAD significantly outperforms the baseline in terms of equal error rate (EER) under conditions where other speakers are mixed at different ratios. Moreover, the decision boundaries reveal the importance of the different parts of speech, which are largely consistent with human judgments., Comment: Accepted by INTERSPEECH 2023
- Published
- 2023
100. P-vectors: A Parallel-Coupled TDNN/Transformer Network for Speaker Verification
- Author
-
Wang, Xiyuan, Wang, Fangyuan, Xu, Bo, Xu, Liang, and Xiao, Jing
- Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing ,Computer Science - Sound - Abstract
Typically, the Time-Delay Neural Network (TDNN) and Transformer can serve as a backbone for Speaker Verification (SV). Both of them have advantages and disadvantages from the perspective of global and local feature modeling. How to effectively integrate these two style features is still an open issue. In this paper, we explore a Parallel-coupled TDNN/Transformer Network (p-vectors) to replace the serial hybrid networks. The p-vectors allows TDNN and Transformer to learn the complementary information from each other through Soft Feature Alignment Interaction (SFAI) under the premise of preserving local and global features. Also, p-vectors uses the Spatial Frequency-channel Attention (SFA) to enhance the spatial interdependence modeling for input features. Finally, the outputs of dual branches of p-vectors are combined by Embedding Aggregation Layer (EAL). Experiments show that p-vectors outperforms MACCIF-TDNN and MFA-Conformer with relative improvements of 11.5% and 13.9% in EER on VoxCeleb1-O., Comment: Accepted by INTERSPEECH 2023
- Published
- 2023
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.