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2,388 results on '"Guo, Sheng"'

2. DexGrasp-Diffusion: Diffusion-based Unified Functional Grasp Synthesis Pipeline for Multi-Dexterous Robotic Hands

Author

Zhang, Zhengshen, Zhou, Lei, Liu, Chenchen, Liu, Zhiyang, Yuan, Chengran, Guo, Sheng, Zhao, Ruiteng, Ang Jr., Marcelo H., and Tay, Francis EH

Subjects
Computer Science - Robotics
Abstract

The versatility and adaptability of human grasping catalyze advancing dexterous robotic manipulation. While significant strides have been made in dexterous grasp generation, current research endeavors pivot towards optimizing object manipulation while ensuring functional integrity, emphasizing the synthesis of functional grasps following desired affordance instructions. This paper addresses the challenge of synthesizing functional grasps tailored to diverse dexterous robotic hands by proposing DexGrasp-Diffusion, an end-to-end modularized diffusion-based pipeline. DexGrasp-Diffusion integrates MultiHandDiffuser, a novel unified data-driven diffusion model for multi-dexterous hands grasp estimation, with DexDiscriminator, which employs a Physics Discriminator and a Functional Discriminator with open-vocabulary setting to filter physically plausible functional grasps based on object affordances. The experimental evaluation conducted on the MultiDex dataset provides substantiating evidence supporting the superior performance of MultiHandDiffuser over the baseline model in terms of success rate, grasp diversity, and collision depth. Moreover, we demonstrate the capacity of DexGrasp-Diffusion to reliably generate functional grasps for household objects aligned with specific affordance instructions.

Published
2024

3. Edge Wasserstein Distance Loss for Oriented Object Detection

Author

Zhu, Yuke, Ruan, Yumeng, Xiong, Zihua, and Guo, Sheng

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Regression loss design is an essential topic for oriented object detection. Due to the periodicity of the angle and the ambiguity of width and height definition, traditional L1-distance loss and its variants have been suffered from the metric discontinuity and the square-like problem. As a solution, the distribution based methods show significant advantages by representing oriented boxes as distributions. Differing from exploited the Gaussian distribution to get analytical form of distance measure, we propose a novel oriented regression loss, Wasserstein Distance(EWD) loss, to alleviate the square-like problem. Specifically, for the oriented box(OBox) representation, we choose a specially-designed distribution whose probability density function is only nonzero over the edges. On this basis, we develop Wasserstein distance as the measure. Besides, based on the edge representation of OBox, the EWD loss can be generalized to quadrilateral and polynomial regression scenarios. Experiments on multiple popular datasets and different detectors show the effectiveness of the proposed method.

Published
2023

17. How fluctuation intensity flux drives SOL expansion

Author

Li, Nami, Xu, Xueqiao, Diamond, Patrick H, Zhang, Tao, Liu, Xiang, Wang, Yifeng, Yan, Ning, and Xu, Guo Sheng

Subjects
Atomic, Molecular, Nuclear, Particle and Plasma Physics, Fluids & Plasmas, Nuclear and plasma physics
Abstract

Abstract: Predictions of heat load widths λ_q based on particle orbits alone are very pessimistic. This paper shows that pedestal peeling-ballooning (P-B) MHD turbulence broadens the stable SOL by the transport, or spreading, of fluctuation energy from the pedestal. λ_q is seen to increase with Γ_ε, the fluctuation energy density flux. We elucidate the fundamental physics of the spreading process. Γ_ε increases with pressure fluctuation correlation length. P-B turbulence is seen to be especially effective at spreading, on account of its large effective mixing length. Spreading is shown to be a multiscale process, which is enhanced by the synergy of large and small-scale modes. Pressure fluctuation skewness correlates well with the spreading flux – with the zero crossing of skewness and Γ_ε spatially coincident – suggesting the role of coherent fluctuation structures and the presence of intermittency in λ_q broadening. λ_q~B_p^(-1) scaling persists for the broadened SOL. We show that the spreading flux increases for increasing pedestal pressure gradient ∇P_0 and for decreasing pedestal collisionality υ_ped^*. This trend is due to the dominance of peeling modes for large ∇P_0 and low υ_ped^*. Ultimately, we see that a state of weak MHD turbulence, as for small ELMs, is very attractive for heat load management. Our findings have transformative implications for future fusion reactor designs and call for experimental investigations to validate the observed trends.

Published
2023

18. Correlation between hemoglobin and the risk of common malignant tumors: a 1999–2020 retrospective analysis and causal association analysis

Author

Guo-Sheng Li, Tao Huang, Jing-Xiao Li, Jun Liu, Xiang Gao, Nuo Yang, and Hua-Fu Zhou

Subjects
Cancer, Risk factor, Biomarker, Mendelian randomization analysis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background The role of hemoglobin (HGB) in common malignant tumors remains unclear. Methods A retrospective analysis was conducted to identify the correlation between HGB levels and risk of 15 malignant tumors using 50,085 samples from the National Health and Nutrition Examination Survey. Mendelian Randomization analyses (MRAs) were performed based on genome-wide association study data to assess the causal relationship between HGB levels and these malignant tumors using more than 700,000 samples. The robustness of the MRA results was confirmed through various analytical methods. Fifty-six in-house samples were used to investigate the correlation between HGB levels and the prognosis in prostate cancer (PRCA) using the Kaplan-Meier curve. Results High HGB levels were associated with a higher risk for patients with cervix cancer, melanoma, and non-melanoma skin cancer (OR > 1.000, p 0.05), suggesting the robustness of the results. The results derived from the in-house data revealed a relationship between higher HGB values and a more favorable prognosis in PRCA (p

Published
2024
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19. Genome-wide identification and expression analysis of the KNOX family and its diverse roles in response to growth and abiotic tolerance in sweet potato and its two diploid relatives

Author

Li-Cong Jia, Zi-Tong Yang, Li-Li Shang, Shao-Zhen He, Huan Zhang, Xu Li, and Guo-Sheng Xin

Subjects
Sweet potato, I. trifida, I. triloba, KNOX, Tissue-specific expression, Hormone treatment, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract KNOXs, a type of homeobox genes that encode atypical homeobox proteins, play an essential role in the regulation of growth and development, hormonal response, and abiotic stress in plants. However, the KNOX gene family has not been explored in sweet potato. In this study, through sequence alignment, genomic structure analysis, and phylogenetic characterization, 17, 12 and 11 KNOXs in sweet potato (I. batatas, 2n = 6x = 90) and its two diploid relatives I. trifida (2n = 2x = 30) and I. triloba (2n = 2x = 30) were identified. The protein physicochemical properties, chromosome localization, phylogenetic relationships, gene structure, protein interaction network, cis-elements of promoters, tissue-specific expression and expression patterns under hormone treatment and abiotic stresses of these 40 KNOX genes were systematically studied. IbKNOX4, -5, and − 6 were highly expressed in the leaves of the high-yield varieties Longshu9 and Xushu18. IbKNOX3 and IbKNOX8 in Class I were upregulated in initial storage roots compared to fibrous roots. IbKNOXs in Class M were specifically expressed in the stem tip and hardly expressed in other tissues. Moreover, IbKNOX2 and − 6, and their homologous genes were induced by PEG/mannitol and NaCl treatments. The results showed that KNOXs were involved in regulating growth and development, hormone crosstalk and abiotic stress responses between sweet potato and its two diploid relatives. This study provides a comparison of these KNOX genes in sweet potato and its two diploid relatives and a theoretical basis for functional studies.

Published
2024
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20. StageInteractor: Query-based Object Detector with Cross-stage Interaction

Author

Teng, Yao, Liu, Haisong, Guo, Sheng, and Wang, Limin

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Previous object detectors make predictions based on dense grid points or numerous preset anchors. Most of these detectors are trained with one-to-many label assignment strategies. On the contrary, recent query-based object detectors depend on a sparse set of learnable queries and a series of decoder layers. The one-to-one label assignment is independently applied on each layer for the deep supervision during training. Despite the great success of query-based object detection, however, this one-to-one label assignment strategy demands the detectors to have strong fine-grained discrimination and modeling capacity. To solve the above problems, in this paper, we propose a new query-based object detector with cross-stage interaction, coined as StageInteractor. During the forward propagation, we come up with an efficient way to improve this modeling ability by reusing dynamic operators with lightweight adapters. As for the label assignment, a cross-stage label assigner is applied subsequent to the one-to-one label assignment. With this assigner, the training target class labels are gathered across stages and then reallocated to proper predictions at each decoder layer. On MS COCO benchmark, our model improves the baseline by 2.2 AP, and achieves 44.8 AP with ResNet-50 as backbone, 100 queries and 12 training epochs. With longer training time and 300 queries, StageInteractor achieves 51.1 AP and 52.2 AP with ResNeXt-101-DCN and Swin-S, respectively.

Published
2023

21. PDPP:Projected Diffusion for Procedure Planning in Instructional Videos

Author

Wang, Hanlin, Wu, Yilu, Guo, Sheng, and Wang, Limin

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In this paper, we study the problem of procedure planning in instructional videos, which aims to make goal-directed plans given the current visual observations in unstructured real-life videos. Previous works cast this problem as a sequence planning problem and leverage either heavy intermediate visual observations or natural language instructions as supervision, resulting in complex learning schemes and expensive annotation costs. In contrast, we treat this problem as a distribution fitting problem. In this sense, we model the whole intermediate action sequence distribution with a diffusion model (PDPP), and thus transform the planning problem to a sampling process from this distribution. In addition, we remove the expensive intermediate supervision, and simply use task labels from instructional videos as supervision instead. Our model is a U-Net based diffusion model, which directly samples action sequences from the learned distribution with the given start and end observations. Furthermore, we apply an efficient projection method to provide accurate conditional guides for our model during the learning and sampling process. Experiments on three datasets with different scales show that our PDPP model can achieve the state-of-the-art performance on multiple metrics, even without the task supervision. Code and trained models are available at https://github.com/MCG-NJU/PDPP., Comment: Accepted as a highlight paper at CVPR 2023

Published
2023

22. Efficient Training of Large-scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout

Author

Chen, Yuanyuan, Chen, Zichen, Guo, Sheng, Zhao, Yansong, Liu, Zelei, Wu, Pengcheng, Yang, Chengyi, Li, Zengxiang, and Yu, Han

Subjects
Computer Science - Machine Learning
Abstract

Artificial intelligence (AI)-empowered industrial fault diagnostics is important in ensuring the safe operation of industrial applications. Since complex industrial systems often involve multiple industrial plants (possibly belonging to different companies or subsidiaries) with sensitive data collected and stored in a distributed manner, collaborative fault diagnostic model training often needs to leverage federated learning (FL). As the scale of the industrial fault diagnostic models are often large and communication channels in such systems are often not exclusively used for FL model training, existing deployed FL model training frameworks cannot train such models efficiently across multiple institutions. In this paper, we report our experience developing and deploying the Federated Opportunistic Block Dropout (FEDOBD) approach for industrial fault diagnostic model training. By decomposing large-scale models into semantic blocks and enabling FL participants to opportunistically upload selected important blocks in a quantized manner, it significantly reduces the communication overhead while maintaining model performance. Since its deployment in ENN Group in February 2022, FEDOBD has served two coal chemical plants across two cities in China to build industrial fault prediction models. It helped the company reduce the training communication overhead by over 70% compared to its previous AI Engine, while maintaining model performance at over 85% test F1 score. To our knowledge, it is the first successfully deployed dropout-based FL approach.

Published
2023

23. CoMAE: Single Model Hybrid Pre-training on Small-Scale RGB-D Datasets

Author

Yang, Jiange, Guo, Sheng, Wu, Gangshan, and Wang, Limin

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Current RGB-D scene recognition approaches often train two standalone backbones for RGB and depth modalities with the same Places or ImageNet pre-training. However, the pre-trained depth network is still biased by RGB-based models which may result in a suboptimal solution. In this paper, we present a single-model self-supervised hybrid pre-training framework for RGB and depth modalities, termed as CoMAE. Our CoMAE presents a curriculum learning strategy to unify the two popular self-supervised representation learning algorithms: contrastive learning and masked image modeling. Specifically, we first build a patch-level alignment task to pre-train a single encoder shared by two modalities via cross-modal contrastive learning. Then, the pre-trained contrastive encoder is passed to a multi-modal masked autoencoder to capture the finer context features from a generative perspective. In addition, our single-model design without requirement of fusion module is very flexible and robust to generalize to unimodal scenario in both training and testing phases. Extensive experiments on SUN RGB-D and NYUDv2 datasets demonstrate the effectiveness of our CoMAE for RGB and depth representation learning. In addition, our experiment results reveal that CoMAE is a data-efficient representation learner. Although we only use the small-scale and unlabeled training set for pre-training, our CoMAE pre-trained models are still competitive to the state-of-the-art methods with extra large-scale and supervised RGB dataset pre-training. Code will be released at https://github.com/MCG-NJU/CoMAE., Comment: 10 pages(including references),5 figures, Accept by Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023)

Published
2023

27. PassDiff: A New Approach for Password Guessing Using Diffusion Model

Author

Guo, Sheng, Duan, Ming, Du, Yibin, Wang, Wei, Guo, Lulu, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Zhang, Yonghong, editor, Qi, Lianyong, editor, Liu, Qi, editor, Yin, Guangqiang, editor, and Liu, Xiaodong, editor

Published
2024
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28. Research on Aerial Target Recognition Method Based on PSO-BP Neural Network

Author

Li, Shuai, He, Xiao-Yuan, Xu, Xiao, Guo, Sheng-Ming, Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, and Li, Shaofan, editor

Published
2024
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34. Learning 3D-aware Image Synthesis with Unknown Pose Distribution

Author

Shi, Zifan, Shen, Yujun, Xu, Yinghao, Peng, Sida, Liao, Yiyi, Guo, Sheng, Chen, Qifeng, and Yeung, Dit-Yan

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Existing methods for 3D-aware image synthesis largely depend on the 3D pose distribution pre-estimated on the training set. An inaccurate estimation may mislead the model into learning faulty geometry. This work proposes PoF3D that frees generative radiance fields from the requirements of 3D pose priors. We first equip the generator with an efficient pose learner, which is able to infer a pose from a latent code, to approximate the underlying true pose distribution automatically. We then assign the discriminator a task to learn pose distribution under the supervision of the generator and to differentiate real and synthesized images with the predicted pose as the condition. The pose-free generator and the pose-aware discriminator are jointly trained in an adversarial manner. Extensive results on a couple of datasets confirm that the performance of our approach, regarding both image quality and geometry quality, is on par with state of the art. To our best knowledge, PoF3D demonstrates the feasibility of learning high-quality 3D-aware image synthesis without using 3D pose priors for the first time., Comment: CVPR 2023. Project page: https://vivianszf.github.io/pof3d/

Published
2023

35. Personalized Federated Learning for Multi-task Fault Diagnosis of Rotating Machinery

Author

Guo, Sheng, Li, Zengxiang, Liu, Hui, Zhao, Shubao, and Jin, Cheng Hao

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Intelligent fault diagnosis is essential to safe operation of machinery. However, due to scarce fault samples and data heterogeneity in field machinery, deep learning based diagnosis methods are prone to over-fitting with poor generalization ability. To solve the problem, this paper proposes a personalized federated learning framework, enabling multi-task fault diagnosis method across multiple factories in a privacypreserving manner. Firstly, rotating machines from different factories with similar vibration feature data are categorized into machine groups using a federated clustering method. Then, a multi-task deep learning model based on convolutional neural network is constructed to diagnose the multiple faults of machinery with heterogeneous information fusion. Finally, a personalized federated learning framework is proposed to solve data heterogeneity across different machines using adaptive hierarchical aggregation strategy. The case study on collected data from real machines verifies the effectiveness of the proposed framework. The result shows that the diagnosis accuracy could be improved significantly using the proposed personalized federated learning, especially for those machines with scarce fault samples.

Published
2022

36. CircHIPK3 regulates fatty acid metabolism through miR-637/FASN axis to promote esophageal squamous cell carcinoma

Author

Shi-qiang Cao, Song-tao Xue, Wen-juan Li, Guo-sheng Hu, Zhi-gang Wu, Jian-cong Zheng, Shu-liang Zhang, Xiao Lin, Chun Chen, Wen Liu, and Bin Zheng

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282, Cytology, QH573-671
Abstract

Abstract The oncogenic role of circRNA in cancers including esophageal cancer (EC) has been well studied. However, whether and how circRNAs are involved in cancer cell metabolic processes remains largely unknown. Here, we reported that circRNA, circHIPK3, is highly expressed in ESCC cell lines and tissues. Knockdown of circHIPK3 significantly restrained cell proliferation, colony formation, migration, and invasion in vitro and inhibited tumor growth in vivo. Mechanistically, circHIPK3 was found to act as a ceRNA by sponging miR-637 to regulate FASN expression and fatty acid metabolism in ESCC cells. Anti-sense oligonucleotide (ASO) targeting circHIPK3 substantially inhibited ESCC both in vitro and in vivo. Therefore, these results uncover a modulatory axis constituting of circHIPK3/miR-637/FASN may be a potential biomarker and therapeutic target for ESCC in the clinic.

Published
2024
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39. Viral shedding pattern of severe fever with thrombocytopenia syndrome virus in severely ill patients: A prospective, Multicenter cohort study

Author

Li-Fen Hu, Ting-Ting Bian, Qiang Chen, Meng-Yu Liu, Jia-Jia Li, Qin-Xiang Kong, Jian-Kang Zhang, Jin Wu, Jun Cheng, Rui Yu, Yan-Qin Qiu, Yu-Feng Gao, Guo-Sheng Chen, Ying Ye, Ting Wu, and Jia-Bin Li

Subjects
Severe fever with thrombocytopenia syndrome virus, Dabie bandavirus, Viral shedding, Precaution measures, Human-to-human transmission, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Background: Severe fever with thrombocytopenia syndrome (SFTS) is spreading rapidly in Asia. The pathway of SFTS virus shedding from patient and specific use of personal protective equipments (PPEs) against viral transmission have rarely been reported. The study was to determine SFTS virus (SFTSV) shedding pattern from the respiratory, digestive and urinary tract to outside in patients. Methods: Patients were divided into mild and severe groups in three sentinel hospitals for SFTS in Anhui province from April 2020 to October 2022. SFTSV level from blood, throat swabs, fecal/anal swabs, urine and bedside environment swabs of SFTS patients were detected by qRT-PCR. Specific PPEs were applied in healthcare workers contacting with the patients who had oropharyngeal virus shedding and hemorrhagic signs. Results: A total of 189 SFTSV-confirmed patients were included in the study, 54 patients died (case fatality rate, 28.57 %). Positive SFTSV in throat swabs (T-SFTSV), fecal/anal swabs (F-SFTSV) and urine (U-SFTSV) were detected in 121 (64.02 %), 91 (48.15 %) and 65 (34.4 %) severely ill patients, respectively. The levels of T-SFTSV, F-SFTSV and U-SFTSV were positively correlated with the load of SFTSV in blood. We firstly revealed that SFTSV positive rate of throat swabs were correlated with occurrence of pneumonia and case fatality rate of patients (P

Published
2024
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40. Advances and challenges of exosome-derived noncoding RNAs for hepatocellular carcinoma diagnosis and treatment

Author

Min Shi, Jun-Su Jia, Guo-Sheng Gao, and Xin Hua

Subjects
Exosome, Hepatocellular carcinoma, ncRNA, Diagnostic and therapeutic biomarkers, Biology (General), QH301-705.5, Biochemistry, QD415-436
Abstract

Exosomes, also termed extracellular vesicles (EVs), are an important component of the tumor microenvironment (TME) and exert versatile effects on the molecular communications in the TME of hepatocellular carcinoma (HCC). Exosome-mediated intercellular communication is closely associated with the tumorigenesis and development of HCC. Exosomes can be extracted through ultracentrifugation and size exclusion, followed by molecular analysis through sequencing. Increasing studies have confirmed the important roles of exosome-derived ncRNAs in HCC, including tumorigenesis, progression, immune escape, and treatment resistance. Due to the protective membrane structure of exosomes, the ncRNAs carried by exosomes can evade degradation by enzymes in body fluids and maintain good expression stability. Thus, exosome-derived ncRNAs are highly suitable as biomarkers for the diagnosis and prognostic prediction of HCC, such as exosomal miR-21-5p, miR-221-3p and lncRNA-ATB. In addition, substantial studies revealed that the up-or down-regulation of exosome-derived ncRNAs had an important impact on HCC progression and response to treatment. Exosomal biomarkers, such as miR-23a, lncRNA DLX6-AS1, miR-21-5p, lncRNA TUC339, lncRNA HMMR-AS1 and hsa_circ_0004658, can reshape immune microenvironment by regulating M2-type macrophage polarization and then promote HCC development. Therefore, by controlling exosome biogenesis and modulating exosomal ncRNA levels, HCC may be inhibited or eliminated. In this current review, we summarized the recent findings on the role of exosomes in HCC progression and analyzed the relationship between exosome-derived ncRNAs and HCC diagnosis and treatment.

Published
2024
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41. UV‐Triggered Hydrogel Coating of the Double Network Polyelectrolytes for Enhanced Endothelialization

Author

Xing‐wang Wang, Yi‐jing Yin, Jing Wang, Hong‐mei Yu, Qian Tang, Zhao‐yang Chen, Guo‐sheng Fu, Ke‐feng Ren, Jian Ji, and Lu Yu

Subjects
device‐related thrombus, double network polyelectrolyte hydrogel coating, endothelialization, left atrial appendage occluder, UV‐triggered polymerization, Science
Abstract

Abstract The left atrial appendage (LAA) occluder is an important medical device for closing the LAA and preventing stroke. The device‐related thrombus (DRT) prevents the implantation of the occluder in exerting the desired therapeutic effect, which is primarily caused by the delayed endothelialization of the occluder. Functional coatings are an effective strategy for accelerating the endothelialization of occluders. However, the occluder surface area is particularly large and structurally complex, and the device is subjected to a large shear friction in the sheath during implantation, which poses a significant challenge to the coating. Herein, a hydrogel coating by the in situ UV‐triggered polymerization of double‐network polyelectrolytes is reported. The findings reveal that the double network and electrostatic interactions between the networks resulted in excellent mechanical properties of the hydrogel coating. The sulfonate and Arg‐Gly‐Asp (RGD) groups in the coating promoted hemocompatibility and endothelial growth of the occluder, respectively. The coating significantly accelerated the endothelialization of the LAA occluder in a canine model is further demonstrated. This study has potential clinical benefits in reducing both the incidence of DRT and the postoperative anticoagulant course for LAA closure.

Published
2024
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42. The fusiform skin paddle in fibula free flap: a fusiform-designed skin paddle for maxillofacial soft defect reconstruction and reducing leg wound tension

Author

Shuai Li, Xin Zheng, Guo-Sheng Cheng, Hua-Ming Mai, Qian-Ting He, and An-Xun Wang

Subjects
fibula free flap, fusiform, skin graft, closure, complication, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

ObjectiveTo investigate the feasibility of leg wound closure and reconstruction of maxillofacial soft defect by a fusiform-designed skin paddle in fibula free flap (FFF).MethodsFifty patients who underwent FFF for reconstruction of maxillofacial soft defect were divided into two groups. The fusiform group (20 patients) was treated using a fusiform-designed skin paddle in FFF (skin paddle width less than 2 cm), and leg wound was closed using primary suturing. Reconstruction of the maxillofacial soft defect or filling of dead space was achieved by folding the fusiform skin paddle. The conventional group (30 patients) was treated using the conventional-designed skin paddle (skin paddle width no less than 2.5 cm). The leg wound was closed using mattress suturing or skin graft, while reconstruction of the maxillofacial soft defect or filling of dead space by conventional way. The average postoperative length of hospital stay, healing time of leg wound, and post-surgical complications were recorded at least 6 months after the surgery.ResultsCompared with traditional method, the fusiform-designed skin paddle reduced the average healing time of the leg wound (fusiform group: 11.05 days, conventional group: 14.77 days, P < 0.05). The average length-to-width ratio in fusiform group was significantly greater than that of in conventional group (fusiform group: 5.85, conventional group: 2.93, P < 0.05), and no difference was observed on the graft size of skin paddle between two groups (fusiform group: 23.13, conventional group: 27.13, P > 0.05). The post-surgical early complications of the leg wound in the conventional group were higher than that of in the fusiform group (fusiform group: 0%, conventional group: 6.67%), while the post-surgical late complication of the donor site between the two groups showed no case. Healing disorders of maxillofacial soft reconstruction in the conventional group were higher than that of in the fusiform group (fusiform group: 5.26%, conventional group: 20.69%).ConclusionsFusiform-designed skin paddle for closure of the leg wound and maxillofacial soft defect is a feasible alternative to the conventional- designed skin paddle. The fusiform- designed skin paddle resulted in the less postoperative length of hospital stay, shorter healing time of leg wound and less complication.

Published
2024
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43. Integrated mRNA–miRNA transcriptome profiling of blood immune responses potentially related to pulmonary fibrosis in forest musk deer

Author

Wen-Hua Qi, Li-Fan Hu, Yu-Jiawei Gu, Xiao-Yan Zhang, Xue-Mei Jiang, Wu-Jiao Li, Jun-Sheng Qi, Guo-Sheng Xiao, and Hang Jie

Subjects
blood transcriptome, immune response, miRNA-mRNA network, signal pathway analysis, RT-qPCR, forest musk deer, Immunologic diseases. Allergy, RC581-607
Abstract

BackgroundForest musk deer (FMD, Moschus Berezovskii) is a critically endangered species world-widely, the death of which can be caused by pulmonary disease in the farm. Pulmonary fibrosis (PF) was a huge threat to the health and survival of captive FMD. MicroRNAs (miRNAs) and messenger RNAs (mRNAs) have been involved in the regulation of immune genes and disease development. However, the regulatory profiles of mRNAs and miRNAs involved in immune regulation of FMD are unclear.MethodsIn this study, mRNA-seq and miRNA-seq in blood were performed to constructed coexpression regulatory networks between PF and healthy groups of FMD. The hub immune- and apoptosis-related genes in the PF blood of FMD were explored through Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Further, protein–protein interaction (PPI) network of immune-associated and apoptosis-associated key signaling pathways were constructed based on mRNA-miRNA in the PF blood of the FMD. Immune hub DEGs and immune hub DEmiRNAs were selected for experimental verification using RT-qPCR.ResultsA total of 2744 differentially expressed genes (DEGs) and 356 differentially expressed miRNAs (DEmiRNAs) were identified in the PF blood group compared to the healthy blood group. Among them, 42 DEmiRNAs were negatively correlated with 20 immune DEGs from a total of 57 correlations. The DEGs were significantly associated with pathways related to CD molecules, immune disease, immune system, cytokine receptors, T cell receptor signaling pathway, Th1 and Th2 cell differentiation, cytokine-cytokine receptor interaction, intestinal immune network for IgA production, and NOD-like receptor signaling pathway. There were 240 immune-related DEGs, in which 186 immune-related DEGs were up-regulated and 54 immune-related DEGs were down-regulated. In the protein-protein interaction (PPI) analysis of immune-related signaling pathway, TYK2, TLR2, TLR4, IL18, CSF1, CXCL13, LCK, ITGB2, PIK3CB, HCK, CD40, CD86, CCL3, CCR7, IL2RA, TLR3, and IL4R were identified as the hub immune genes. The mRNA-miRNA coregulation analysis showed that let-7d, miR-324-3p, miR-760, miR-185, miR-149, miR-149-5p, and miR-1842-5p are key miRNAs that target DEGs involved in immune disease, immune system and immunoregulation.ConclusionThe development and occurrence of PF were significantly influenced by the immune-related and apoptosis-related genes present in PF blood. mRNAs and miRNAs associated with the development and occurrence of PF in the FMD.

Published
2024
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44. Real2Sim or Sim2Real: Robotics Visual Insertion using Deep Reinforcement Learning and Real2Sim Policy Adaptation

Author

Chen, Yiwen, Li, Xue, Guo, Sheng, Ng, Xian Yao, and Ang, Marcelo

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence
Abstract

Reinforcement learning has shown a wide usage in robotics tasks, such as insertion and grasping. However, without a practical sim2real strategy, the policy trained in simulation could fail on the real task. There are also wide researches in the sim2real strategies, but most of those methods rely on heavy image rendering, domain randomization training, or tuning. In this work, we solve the insertion task using a pure visual reinforcement learning solution with minimum infrastructure requirement. We also propose a novel sim2real strategy, Real2Sim, which provides a novel and easier solution in policy adaptation. We discuss the advantage of Real2Sim compared with Sim2Real.

Published
2022

45. Cross-Architecture Self-supervised Video Representation Learning

Author

Guo, Sheng, Xiong, Zihua, Zhong, Yujie, Wang, Limin, Guo, Xiaobo, Han, Bing, and Huang, Weilin

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In this paper, we present a new cross-architecture contrastive learning (CACL) framework for self-supervised video representation learning. CACL consists of a 3D CNN and a video transformer which are used in parallel to generate diverse positive pairs for contrastive learning. This allows the model to learn strong representations from such diverse yet meaningful pairs. Furthermore, we introduce a temporal self-supervised learning module able to predict an Edit distance explicitly between two video sequences in the temporal order. This enables the model to learn a rich temporal representation that compensates strongly to the video-level representation learned by the CACL. We evaluate our method on the tasks of video retrieval and action recognition on UCF101 and HMDB51 datasets, where our method achieves excellent performance, surpassing the state-of-the-art methods such as VideoMoCo and MoCo+BE by a large margin. The code is made available at https://github.com/guoshengcv/CACL., Comment: Accepted to CVPR2022

Published
2022

46. Economical Precise Manipulation and Auto Eye-Hand Coordination with Binocular Visual Reinforcement Learning

Author

Chen, Yiwen, Guo, Sheng, Zhang, Zedong, Zhou, Lei, Ng, Xian Yao, and Ang Jr, Marcelo H.

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

Precision robotic manipulation tasks (insertion, screwing, precisely pick, precisely place) are required in many scenarios. Previous methods achieved good performance on such manipulation tasks. However, such methods typically require tedious calibration or expensive sensors. 3D/RGB-D cameras and torque/force sensors add to the cost of the robotic application and may not always be economical. In this work, we aim to solve these but using only weak-calibrated and low-cost webcams. We propose Binocular Alignment Learning (BAL), which could automatically learn the eye-hand coordination and points alignment capabilities to solve the four tasks. Our work focuses on working with unknown eye-hand coordination and proposes different ways of performing eye-in-hand camera calibration automatically. The algorithm was trained in simulation and used a practical pipeline to achieve sim2real and test it on the real robot. Our method achieves a competitively good result with minimal cost on the four tasks., Comment: 12 pages, 16 figures

Published
2022

49. NMDARs activation regulates endothelial ferroptosis via the PP2A-AMPK-HMGB1 axis

Author

Wei-Min Han, Yi-Xiang Hong, Guo-Sheng Xiao, Rui-Ying Wang, and Gang Li

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282, Cytology, QH573-671
Abstract

Abstract N-methyl-D-aspartate receptors (NMDARs) are ligand-gated, voltage-dependent channels of the ionotropic glutamate receptor family. The present study explored whether NMDAR activation induced ferroptosis in vascular endothelial cells and its complicated mechanisms in vivo and in vitro. Various detection approaches were used to determine the ferroptosis-related cellular iron content, lipid reactive oxygen species (LOS), siRNA molecules, RNA-sequence, MDA, GSH, and western blotting. The AMPK activator Acadesine (AICAR), HMGB1 inhibitor glycyrrhizin (GLY), PP2A inhibitor LB-100, and NMDAR inhibitor MK801 were used to investigate the involved in vivo and in vitro pathways. The activation of NMDAR with L-glutamic acid (GLU) or NMDA significantly promoted cellular ferroptosis, iron content, MDA, and the PTGS2 expression, while decreasing GPX4 expression and GSH concentration in human umbilical vein endothelial cells (HUVECs), which was reversed by ferroptosis inhibitors Ferrostatin-1(Fer-1), Liproxstatin-1 (Lip-1), or Deferoxamine (DFO). RNA-seq revealed that ferroptosis and SLC7A11 participate in NMDA or GLU-mediated NMDAR activation. The PP2A-AMPK-HMGB1 pathway was majorly associated with NMDAR activation-induced ferroptosis, validated using the PP2A inhibitor LB-100, AMPK activator AICAR, or HMGB1 siRNA. The role of NMDAR in ferroptosis was validated in HUVECs induced with the ferroptosis activator errasin or RSL3 and counteracted by the NMDAR inhibitor MK-801. The in vivo results showed that NMDA- or GLU-induced ferroptosis and LOS production was reversed by MK-801, LB-100, AICAR, MK-801, and GLY, confirming that the PP2A-AMPK-HMGB1 pathway is involved in NMDAR activation-induced vascular endothelium ferroptosis. In conclusion, the present study demonstrated a novel role of NMDAR in endothelial cell injury by regulating ferroptosis via the PP2A-AMPK-HMGB1 pathway.

Published
2024
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50. Weak beat frequency extraction method for photon Doppler signal with low signal-to-noise ratio

Author

Sun Ya-Nan, Wu Shen-Jiang, Qin Guo-Sheng, Wang Ke-Xuan, Wang Jia, Li Dang-Juan, and Du Yu-Qi

Subjects
photon doppler signal, low signal-to-noise ratio, spectrum refinement and filter, weak beat frequency extraction, Physics, QC1-999
Abstract

In the window function spectrum of the low signal-to-noise ratio photon Doppler signal after the short-time Fourier transform, the weak beat frequency cannot be obtained by extracting the maximum amplitude spectrum frequency of each window because the amplitude of the noise spectrum exceeds the weak beat frequency. In this article, the value of the beat frequency is first estimated by the Kalman filter. Then, a multiple analytical bandpass filter is constructed to refine the spectrum of the high noise signal with the value of the beat frequency estimate as the spectrum band center. This technique extracts only the beat frequencies from the narrowband refinement spectrum by removing the interference spectrum band range. We use this technique to process the photon Doppler signals from the tiny high-speed flying fragments explosion experiment. After data processing, the beat frequency value heavily affected by high-frequency noise can reduce the error by up to 64.9%. The beat frequency value of the low noise signal can be accurate to 106 Hz, equivalent to 0.775 m/s after velocity demodulation. This method fully considers the positioning and protection of the beat frequency characteristics. It makes weak beat frequencies more obvious in the refined narrowband spectrum without changing the signal amplitude. This article describes a method for extracting the weak beat frequency of the photon Doppler signal or a signal optimization algorithm for needing high-precision beat frequencies in a test environment.

Published
2023
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