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1. Exploring Mathematical Extrapolation of Large Language Models with Synthetic Data

Author

Li, Haolong, Ma, Yu, Zhang, Yinqi, Ye, Chen, and Chen, Jie

Subjects
Computer Science - Computation and Language
Abstract

Large Language Models (LLMs) have shown excellent performance in language understanding, text generation, code synthesis, and many other tasks, while they still struggle in complex multi-step reasoning problems, such as mathematical reasoning. In this paper, through a newly proposed arithmetical puzzle problem, we show that the model can perform well on multi-step reasoning tasks via fine-tuning on high-quality synthetic data. Experimental results with the open-llama-3B model on three different test datasets show that not only the model can reach a zero-shot pass@1 at 0.44 on the in-domain dataset, it also demonstrates certain generalization capabilities on the out-of-domain datasets. Specifically, this paper has designed two out-of-domain datasets in the form of extending the numerical range and the composing components of the arithmetical puzzle problem separately. The fine-tuned models have shown encouraging performance on these two far more difficult tasks with the zero-shot pass@1 at 0.33 and 0.35, respectively., Comment: Accept by Findings of ACL 2024

Published
2024

2. POWQMIX: Weighted Value Factorization with Potentially Optimal Joint Actions Recognition for Cooperative Multi-Agent Reinforcement Learning

Author

Huang, Chang, Zhao, Junqiao, Zhu, Shatong, Zhou, Hongtu, Ye, Chen, Feng, Tiantian, and Jiang, Changjun

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

Value function factorization methods are commonly used in cooperative multi-agent reinforcement learning, with QMIX receiving significant attention. Many QMIX-based methods introduce monotonicity constraints between the joint action value and individual action values to achieve decentralized execution. However, such constraints limit the representation capacity of value factorization, restricting the joint action values it can represent and hindering the learning of the optimal policy. To address this challenge, we propose the Potentially Optimal joint actions Weighted QMIX (POWQMIX) algorithm, which recognizes the potentially optimal joint actions and assigns higher weights to the corresponding losses of these joint actions during training. We theoretically prove that with such a weighted training approach the optimal policy is guaranteed to be recovered. Experiments in matrix games, predator-prey, and StarCraft II Multi-Agent Challenge environments demonstrate that our algorithm outperforms the state-of-the-art value-based multi-agent reinforcement learning methods., Comment: change reference format

Published
2024

3. LOG-LIO2: A LiDAR-Inertial Odometry with Efficient Uncertainty Analysis

Author

Huang, Kai, Zhao, Junqiao, Lin, Jiaye, Zhu, Zhongyang, Song, Shuangfu, Ye, Chen, and Feng, Tiantian

Subjects
Computer Science - Robotics
Abstract

Uncertainty in LiDAR measurements, stemming from factors such as range sensing, is crucial for LIO (LiDAR-Inertial Odometry) systems as it affects the accurate weighting in the loss function. While recent LIO systems address uncertainty related to range sensing, the impact of incident angle on uncertainty is often overlooked by the community. Moreover, the existing uncertainty propagation methods suffer from computational inefficiency. This paper proposes a comprehensive point uncertainty model that accounts for both the uncertainties from LiDAR measurements and surface characteristics, along with an efficient local uncertainty analytical method for LiDAR-based state estimation problem. We employ a projection operator that separates the uncertainty into the ray direction and its orthogonal plane. Then, we derive incremental Jacobian matrices of eigenvalues and eigenvectors w.r.t. points, which enables a fast approximation of uncertainty propagation. This approach eliminates the requirement for redundant traversal of points, significantly reducing the time complexity of uncertainty propagation from $\mathcal{O} (n)$ to $\mathcal{O} (1)$ when a new point is added. Simulations and experiments on public datasets are conducted to validate the accuracy and efficiency of our formulations. The proposed methods have been integrated into a LIO system, which is available at https://github.com/tiev-tongji/LOG-LIO2.

Published
2024

4. Student Fatigue and Its Impact on Teaching Effectiveness Based on Online Teaching

Author

Ye Chen and Xiaoqun Qin

Abstract

Since the outbreak of COVID-19 in 2019, many countries have taken measures such as controlling the flow of people, logistics and reducing crowds. Educational institutions have shifted from traditional face-to-face teaching to online teaching. In order to understand the fatigue caused by long-term online teaching and its influence on teaching quality, this paper puts forward the concept of "student fatigue" according to the learning characteristics of students in our education system, and applies statistical principles to compile the student Fatigue Scale-18. In the four seasons of spring, summer, autumn and winter, 1236 times of 319 college students in grade 2021 were tested for fatigue, and the average incidence of fatigue was 64.97%. The incidence of fatigue in boys is higher than that in girls. There was a slight difference in the incidence of fatigue in different seasons, but no statistical significance was there. The effect of fatigue on online teaching is empirically analyzed. The degree of fatigue is negatively correlated with test scores. Students with better learning foundations are less affected by fatigue, while girls' scores are less affected by fatigue. This paper analyzes the common causes of students' fatigue, combined with the current research status of students' fatigue at home and abroad, and puts forward that college education should pay attention to students' fatigue, regularly or irregularly monitor students' fatigue, so that the incidence of fatigue is controlled below 30%. The analysis revealed that the degree of fatigue and gender significantly influenced academic performance. A negative correlation was found between fatigue degree and academic performance, indicating that more severe fatigue led to poorer academic results. Boys were more affected by fatigue than girls. The relationship between academic performance and seasons showed no significant impact. Try to avoid severe fatigue. In order to reduce the impact of fatigue on students' study and health, preventive measures should be taken. It provides theoretical and empirical basis for preventing students' fatigue, improving teaching quality and ensuring students' health.

Published
2024
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5. N$^{3}$-Mapping: Normal Guided Neural Non-Projective Signed Distance Fields for Large-scale 3D Mapping

Author

Song, Shuangfu, Zhao, Junqiao, Huang, Kai, Lin, Jiaye, Ye, Chen, and Feng, Tiantian

Subjects
Computer Science - Robotics
Abstract

Accurate and dense mapping in large-scale environments is essential for various robot applications. Recently, implicit neural signed distance fields (SDFs) have shown promising advances in this task. However, most existing approaches employ projective distances from range data as SDF supervision, introducing approximation errors and thus degrading the mapping quality. To address this problem, we introduce N$^{3}$-Mapping, an implicit neural mapping system featuring normal-guided neural non-projective signed distance fields. Specifically, we directly sample points along the surface normal, instead of the ray, to obtain more accurate non-projective distance values from range data. Then these distance values are used as supervision to train the implicit map. For large-scale mapping, we apply a voxel-oriented sliding window mechanism to alleviate the forgetting issue with a bounded memory footprint. Besides, considering the uneven distribution of measured point clouds, a hierarchical sampling strategy is designed to improve training efficiency. Experiments demonstrate that our method effectively mitigates SDF approximation errors and achieves state-of-the-art mapping quality compared to existing approaches., Comment: 8 pages, 10 figures. Accepted by RAL2024

Published
2024

6. Global marine microbial diversity and its potential in bioprospecting

Author

Chen, Jianwei, Jia, Yangyang, Sun, Ying, Liu, Kun, Zhou, Changhao, Liu, Chuan, Li, Denghui, Liu, Guilin, Zhang, Chengsong, Yang, Tao, Huang, Lei, Zhuang, Yunyun, Wang, Dazhi, Xu, Dayou, Zhong, Qiaoling, Guo, Yang, Li, Anduo, Seim, Inge, Jiang, Ling, Wang, Lushan, Lee, Simon Ming Yuen, Liu, Yujing, Wang, Dantong, Zhang, Guoqiang, Liu, Shanshan, Wei, Xiaofeng, Yue, Zhen, Zheng, Shanmin, Shen, Xuechun, Wang, Sen, Qi, Chen, Chen, Jing, Ye, Chen, Zhao, Fang, Wang, Jun, Fan, Jie, Li, Baitao, Sun, Jiahui, Jia, Xiaodong, Xia, Zhangyong, Zhang, He, Liu, Junnian, Zheng, Yue, Liu, Xin, Wang, Jian, Yang, Huanming, Kristiansen, Karsten, Xu, Xun, Mock, Thomas, Li, Shengying, Zhang, Wenwei, and Fan, Guangyi

Published
2024
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9. Progressive Dual Priori Network for Generalized Breast Tumor Segmentation

Author

Wang, Li, Wang, Lihui, Kuai, Zixiang, Tang, Lei, Ou, Yingfeng, Ye, Chen, and Zhu, Yuemin

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

To promote the generalization ability of breast tumor segmentation models, as well as to improve the segmentation performance for breast tumors with smaller size, low-contrast and irregular shape, we propose a progressive dual priori network (PDPNet) to segment breast tumors from dynamic enhanced magnetic resonance images (DCE-MRI) acquired at different centers. The PDPNet first cropped tumor regions with a coarse-segmentation based localization module, then the breast tumor mask was progressively refined by using the weak semantic priori and cross-scale correlation prior knowledge. To validate the effectiveness of PDPNet, we compared it with several state-of-the-art methods on multi-center datasets. The results showed that, comparing against the suboptimal method, the DSC and HD95 of PDPNet were improved at least by 5.13% and 7.58% respectively on multi-center test sets. In addition, through ablations, we demonstrated that the proposed localization module can decrease the influence of normal tissues and therefore improve the generalization ability of the model. The weak semantic priors allow focusing on tumor regions to avoid missing small tumors and low-contrast tumors. The cross-scale correlation priors are beneficial for promoting the shape-aware ability for irregular tumors. Thus integrating them in a unified framework improved the multi-center breast tumor segmentation performance. The source code and open data can be accessed at https://github.com/wangli100209/PDPNet., Comment: 14 pages, 12 figures

Published
2023
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10. Competition of electronic correlation and reconstruction in La1-xSrxTiO3/SrTiO3 heterostructures

Author

Wang, Xueyan, Sun, Lin, Ye, Chen, Huang, Zhen, Han, Kun, Huang, Ke, Yang, Allen Jian, Zeng, Shengwei, Loh, Xian Jun, Zhu, Qiang, Venkatesan, T., Ariando, Ariando, and Wang, X. Renshaw

Subjects
Condensed Matter - Strongly Correlated Electrons
Abstract

Electronic correlation and reconstruction are two important factors that play a critical role in shaping the magnetic and electronic properties of correlated low-dimensional systems. Here, we report a competition between the electronic correlation and structural reconstruction in La1-xSrxTiO3/SrTiO3 heterostructures by modulating material polarity and interfacial strain, respectively. The heterostructures exhibit a critical thickness (tc) at which a metal-to-insulator transition (MIT) abruptly occurs at certain thickness, accompanied by the coexistence of two- and three-dimensional (2D and 3D) carriers. Intriguingly, the tc exhibits a V-shaped dependence on the doping concentration of Sr, with the smallest tc value at x = 0.5. We attribute this V-shaped dependence to the competition between the electronic reconstruction (modulated by the polarity) and the electronic correlation (modulated by strain), which are borne out by the experimental results, including strain-dependent electronic properties and the evolution of 2D and 3D carriers. Our findings underscore the significance of the interplay between electronic reconstruction and correlation in the realization and utilization of emergent electronic functionalities in low-dimensional correlated systems.

Published
2023

11. Do Years of Teaching Experience Matter in Maker Teacher Professional Development? K-12 Teachers' Knowledge, Attitudes, and Design of Maker Lessons

Author

Ye Chen and Li Cao

Abstract

With the advance of the Maker movement, teacher professional development is needed to prepare K-12 teachers for maker-centered instruction. This study examined the influence of teaching experience in learning maker-centered instruction. Data included surveys, 3D models, and maker lesson plans created by 162 in-service K-12 teachers. Results show that, overall, years of teaching experience did not make a difference in knowledge, attitudes, and design of maker lessons between veteran and novice teachers. Both teacher groups held positive attitudes, yet were concerned with limited maker knowledge and skills. After the initial training, both groups were able to integrate maker technology and design maker lessons in creative ways. Research and practical implications are discussed for the maker-teacher professional development of K-12 teachers.

Published
2024
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13. How to Fine-tune the Model: Unified Model Shift and Model Bias Policy Optimization

Author

Zhang, Hai, Yu, Hang, Zhao, Junqiao, Zhang, Di, Huang, Chang, Zhou, Hongtu, Zhang, Xiao, and Ye, Chen

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

Designing and deriving effective model-based reinforcement learning (MBRL) algorithms with a performance improvement guarantee is challenging, mainly attributed to the high coupling between model learning and policy optimization. Many prior methods that rely on return discrepancy to guide model learning ignore the impacts of model shift, which can lead to performance deterioration due to excessive model updates. Other methods use performance difference bound to explicitly consider model shift. However, these methods rely on a fixed threshold to constrain model shift, resulting in a heavy dependence on the threshold and a lack of adaptability during the training process. In this paper, we theoretically derive an optimization objective that can unify model shift and model bias and then formulate a fine-tuning process. This process adaptively adjusts the model updates to get a performance improvement guarantee while avoiding model overfitting. Based on these, we develop a straightforward algorithm USB-PO (Unified model Shift and model Bias Policy Optimization). Empirical results show that USB-PO achieves state-of-the-art performance on several challenging benchmark tasks.

Published
2023

14. VNI-Net: Vector Neurons-based Rotation-Invariant Descriptor for LiDAR Place Recognition

Author

Tian, Gengxuan, Zhao, Junqiao, Cai, Yingfeng, Zhang, Fenglin, Mu, Wenjie, and Ye, Chen

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

LiDAR-based place recognition plays a crucial role in Simultaneous Localization and Mapping (SLAM) and LiDAR localization. Despite the emergence of various deep learning-based and hand-crafting-based methods, rotation-induced place recognition failure remains a critical challenge. Existing studies address this limitation through specific training strategies or network structures. However, the former does not produce satisfactory results, while the latter focuses mainly on the reduced problem of SO(2) rotation invariance. Methods targeting SO(3) rotation invariance suffer from limitations in discrimination capability. In this paper, we propose a new method that employs Vector Neurons Network (VNN) to achieve SO(3) rotation invariance. We first extract rotation-equivariant features from neighboring points and map low-dimensional features to a high-dimensional space through VNN. Afterwards, we calculate the Euclidean and Cosine distance in the rotation-equivariant feature space as rotation-invariant feature descriptors. Finally, we aggregate the features using GeM pooling to obtain global descriptors. To address the significant information loss when formulating rotation-invariant descriptors, we propose computing distances between features at different layers within the Euclidean space neighborhood. This greatly improves the discriminability of the point cloud descriptors while ensuring computational efficiency. Experimental results on public datasets show that our approach significantly outperforms other baseline methods implementing rotation invariance, while achieving comparable results with current state-of-the-art place recognition methods that do not consider rotation issues.

Published
2023

15. LOG-LIO: A LiDAR-Inertial Odometry with Efficient Local Geometric Information Estimation

Author

Huang, Kai, Zhao, Junqiao, Zhu, Zhongyang, Ye, Chen, and Feng, Tiantian

Subjects
Computer Science - Robotics
Abstract

Local geometric information, i.e. normal and distribution of points, is crucial for LiDAR-based simultaneous localization and mapping (SLAM) because it provides constraints for data association, which further determines the direction of optimization and ultimately affects the accuracy of localization. However, estimating normal and distribution of points are time-consuming tasks even with the assistance of kdtree or volumetric maps. To achieve fast normal estimation, we look into the structure of LiDAR scan and propose a ring-based fast approximate least squares (Ring FALS) method. With the Ring structural information, estimating the normal requires only the range information of the points when a new scan arrives. To efficiently estimate the distribution of points, we extend the ikd-tree to manage the map in voxels and update the distribution of points in each voxel incrementally while maintaining its consistency with the normal estimation. We further fix the distribution after its convergence to balance the time consumption and the correctness of representation. Based on the extracted and maintained local geometric information, we devise a robust and accurate hierarchical data association scheme where point-to-surfel association is prioritized over point-to-plane. Extensive experiments on diverse public datasets demonstrate the advantages of our system compared to other state-of-the-art methods. Our open source implementation is available at https://github.com/tiev-tongji/LOG-LIO., Comment: 8 pages, 4 figures

Published
2023

16. Bioinformatics analysis of HBV s gene mutation in blood donor

Author

Jiacheng FAN, Qing LI, Xiuli CHEN, Shixiang LIU, and Ye CHEN

Subjects
hbv, obi, s gene, blood donor, bioinformatics, Diseases of the blood and blood-forming organs, RC633-647.5, Medicine
Abstract

Objective To analyze the infectious indicators, HBV s gene mutations and changes in bioinformatics characteristics of HBV DNA+ /HBsAg- blood donor. Methods A sample of HBV DNA+ /HBsAg- was screened by PCR method, and HBsAg/HBsAb/HBeAg/HBeAb/HBcAb of HBV in the sample were detected by ELISA and chemiluminescence methods. The mutation of the HBVs gene fragment in the sample was sequenced and analyzed, and the bioinformatics analysis was performed using analysis software. Results The sample showed HBV DNA+, HBsAg-, HBsAb+, HBeAg+, HBeAb- and HBcAb+, with an amino acid unit point mutation (P151L) occurred in the HBV s gene, and the spatial structure changed. Conclusion The spatial structural changes in the gene sequence of HBVs may be the reason for the appearance of serological HBsAg-/HBsAb+ /HBV DNA+ in the test results.

Published
2024
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17. Seeing at a distance with multicore fibers

Author

Haogong Feng, Xi Chen, Runze Zhu, Yifeng Xiong, Ye Chen, Yanqing Lu, and Fei Xu

Subjects
long-distance fiber imaging, image transmission, parallel transmission, all-optical encoding, multicore fiber, Optics. Light, QC350-467
Abstract

Images and videos provide a wealth of information for people in production and life. Although most digital information is transmitted via optical fiber, the image acquisition and transmission processes still rely heavily on electronic circuits. The development of all-optical transmission networks and optical computing frameworks has pointed to the direction for the next generation of data transmission and information processing. Here, we propose a high-speed, low-cost, multiplexed parallel and one-piece all-fiber architecture for image acquisition, encoding, and transmission, called the Multicore Fiber Acquisition and Transmission Image System (MFAT). Based on different spatial and modal channels of the multicore fiber, fiber-coupled self-encoding, and digital aperture decoding technology, scenes can be observed directly from up to 1 km away. The expansion of capacity provides the possibility of parallel coded transmission of multimodal high-quality data. MFAT requires no additional signal transmitting and receiving equipment. The all-fiber processing saves the time traditionally spent on signal conversion and image pre-processing (compression, encoding, and modulation). Additionally, it provides an effective solution for 2D information acquisition and transmission tasks in extreme environments such as high temperatures and electromagnetic interference.

Published
2024
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18. Association between serum vitamin C and body mass index in adolescents aged 12–19 years

Author

Xiaoqi Su, Nishant Patel, Jun Chen, Ye Chen, Xin Zhou, Xuming Mo, and Shanliang Zhu

Subjects
Obesity, Body mass index, Serum vitamin C, Adolescents, NHANES, Public aspects of medicine, RA1-1270
Abstract

Abstract Background Evidence on the association between serum vitamin C (sVC) levels and obesity is limited. This study aimed to explore the relationship between sVC and body mass index (BMI) in adolescents aged 12 to 19 years. Methods We analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2003–2006, with 3952 participants. sVC and BMI were independent variables and dependent variables, respectively. The associations of sVC with BMI were examined using multivariable linear regression models. Age, sex, and race/ethnicity were analyzed as subgroups. Then, we devised smooth curve fittings and saturation threshold analysis to address the nonlinear relationship. Results sVC had a negative correlation with BMI after adjusting for all covariates (β: -1.020, 95% CI: -1.359, -0.680). In the subgroup analysis by age, sex, and race/ethnicity, there was still a negative correlation between sVC and BMI (p

Published
2024
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19. Evaluation of FluSight influenza forecasting in the 2021–22 and 2022–23 seasons with a new target laboratory-confirmed influenza hospitalizations

Author

Sarabeth M. Mathis, Alexander E. Webber, Tomás M. León, Erin L. Murray, Monica Sun, Lauren A. White, Logan C. Brooks, Alden Green, Addison J. Hu, Roni Rosenfeld, Dmitry Shemetov, Ryan J. Tibshirani, Daniel J. McDonald, Sasikiran Kandula, Sen Pei, Rami Yaari, Teresa K. Yamana, Jeffrey Shaman, Pulak Agarwal, Srikar Balusu, Gautham Gururajan, Harshavardhan Kamarthi, B. Aditya Prakash, Rishi Raman, Zhiyuan Zhao, Alexander Rodríguez, Akilan Meiyappan, Shalina Omar, Prasith Baccam, Heidi L. Gurung, Brad T. Suchoski, Steve A. Stage, Marco Ajelli, Allisandra G. Kummer, Maria Litvinova, Paulo C. Ventura, Spencer Wadsworth, Jarad Niemi, Erica Carcelen, Alison L. Hill, Sara L. Loo, Clifton D. McKee, Koji Sato, Claire Smith, Shaun Truelove, Sung-mok Jung, Joseph C. Lemaitre, Justin Lessler, Thomas McAndrew, Wenxuan Ye, Nikos Bosse, William S. Hlavacek, Yen Ting Lin, Abhishek Mallela, Graham C. Gibson, Ye Chen, Shelby M. Lamm, Jaechoul Lee, Richard G. Posner, Amanda C. Perofsky, Cécile Viboud, Leonardo Clemente, Fred Lu, Austin G. Meyer, Mauricio Santillana, Matteo Chinazzi, Jessica T. Davis, Kunpeng Mu, Ana Pastore y Piontti, Alessandro Vespignani, Xinyue Xiong, Michal Ben-Nun, Pete Riley, James Turtle, Chis Hulme-Lowe, Shakeel Jessa, V. P. Nagraj, Stephen D. Turner, Desiree Williams, Avranil Basu, John M. Drake, Spencer J. Fox, Ehsan Suez, Monica G. Cojocaru, Edward W. Thommes, Estee Y. Cramer, Aaron Gerding, Ariane Stark, Evan L. Ray, Nicholas G. Reich, Li Shandross, Nutcha Wattanachit, Yijin Wang, Martha W. Zorn, Majd Al Aawar, Ajitesh Srivastava, Lauren A. Meyers, Aniruddha Adiga, Benjamin Hurt, Gursharn Kaur, Bryan L. Lewis, Madhav Marathe, Srinivasan Venkatramanan, Patrick Butler, Andrew Farabow, Naren Ramakrishnan, Nikhil Muralidhar, Carrie Reed, Matthew Biggerstaff, and Rebecca K. Borchering

Subjects
Science
Abstract

Abstract Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021–22 and 2022–23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021–22 and 12 out of 18 models in 2022–23. Averaging across all forecast targets, the FluSight ensemble is the 2nd most accurate model measured by WIS in 2021–22 and the 5th most accurate in the 2022–23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

Published
2024
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20. Dynamic nanomechanical characterization of cells in exosome therapy

Author

Ye Chen, Zihan Zhang, Ziwei Li, Wenjie Wu, Shihai Lan, Tianhao Yan, Kainan Mei, Zihan Qiao, Chen Wang, Chuanbiao Bai, Ziyan Li, Shangquan Wu, Jianye Wang, and Qingchuan Zhang

Subjects
Technology, Engineering (General). Civil engineering (General), TA1-2040
Abstract

Abstract Exosomes derived from mesenchymal stem cells (MSCs) have been confirmed to enhance cell proliferation and improve tissue repair. Exosomes release their contents into the cytoplasmic solution of the recipient cell to mediate cell expression, which is the main pathway through which exosomes exert therapeutic effects. The corresponding process of exosome internalization mainly occurs in the early stage of treatment. However, the therapeutic effect of exosomes in the early stage remains to be further studied. We report that the three-dimensional cell traction force can intuitively reflect the ability of exosomes to enhance the cytoskeleton and cell contractility of recipient cells, serving as an effective method to characterize the therapeutic effect of exosomes. Compared with traditional biochemical methods, we can visualize the early therapeutic effect of exosomes in real time without damage by quantifying the cell traction force. Through quantitative analysis of traction forces, we found that endometrial stromal cells exhibit short-term cell roundness accompanied by greater traction force during the early stage of exosome therapy. Further experiments revealed that exosomes enhance the traction force and cytoskeleton by regulating the Rac1/RhoA signaling pathway, thereby promoting cell proliferation. This work provides an effective method for rapidly quantifying the therapeutic effects of exosomes and studying the underlying mechanisms involved.

Published
2024
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21. Safe Reinforcement Learning with Dead-Ends Avoidance and Recovery

Author

Zhang, Xiao, Zhang, Hai, Zhou, Hongtu, Huang, Chang, Zhang, Di, Ye, Chen, and Zhao, Junqiao

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

Safety is one of the main challenges in applying reinforcement learning to realistic environmental tasks. To ensure safety during and after training process, existing methods tend to adopt overly conservative policy to avoid unsafe situations. However, overly conservative policy severely hinders the exploration, and makes the algorithms substantially less rewarding. In this paper, we propose a method to construct a boundary that discriminates safe and unsafe states. The boundary we construct is equivalent to distinguishing dead-end states, indicating the maximum extent to which safe exploration is guaranteed, and thus has minimum limitation on exploration. Similar to Recovery Reinforcement Learning, we utilize a decoupled RL framework to learn two policies, (1) a task policy that only considers improving the task performance, and (2) a recovery policy that maximizes safety. The recovery policy and a corresponding safety critic are pretrained on an offline dataset, in which the safety critic evaluates upper bound of safety in each state as awareness of environmental safety for the agent. During online training, a behavior correction mechanism is adopted, ensuring the agent to interact with the environment using safe actions only. Finally, experiments of continuous control tasks demonstrate that our approach has better task performance with less safety violations than state-of-the-art algorithms., Comment: 8 pages, 5 figures

Published
2023

22. Learning Sequence Descriptor based on Spatio-Temporal Attention for Visual Place Recognition

Author

Zhao, Junqiao, Zhang, Fenglin, Cai, Yingfeng, Tian, Gengxuan, Mu, Wenjie, Ye, Chen, and Feng, Tiantian

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Visual Place Recognition (VPR) aims to retrieve frames from a geotagged database that are located at the same place as the query frame. To improve the robustness of VPR in perceptually aliasing scenarios, sequence-based VPR methods are proposed. These methods are either based on matching between frame sequences or extracting sequence descriptors for direct retrieval. However, the former is usually based on the assumption of constant velocity, which is difficult to hold in practice, and is computationally expensive and subject to sequence length. Although the latter overcomes these problems, existing sequence descriptors are constructed by aggregating features of multiple frames only, without interaction on temporal information, and thus cannot obtain descriptors with spatio-temporal discrimination.In this paper, we propose a sequence descriptor that effectively incorporates spatio-temporal information. Specifically, spatial attention within the same frame is utilized to learn spatial feature patterns, while attention in corresponding local regions of different frames is utilized to learn the persistence or change of features over time. We use a sliding window to control the temporal range of attention and use relative positional encoding to construct sequential relationships between different features. This allows our descriptors to capture the intrinsic dynamics in a sequence of frames.Comprehensive experiments on challenging benchmark datasets show that the proposed approach outperforms recent state-of-the-art methods.The code is available at https://github.com/tiev-tongji/Spatio-Temporal-SeqVPR., Comment: 8 pages, 6 figures, published to RA-L

Published
2023
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23. LIMOT: A Tightly-Coupled System for LiDAR-Inertial Odometry and Multi-Object Tracking

Author

Zhu, Zhongyang, Zhao, Junqiao, Huang, Kai, Tian, Xuebo, Lin, Jiaye, and Ye, Chen

Subjects
Computer Science - Robotics
Abstract

Simultaneous localization and mapping (SLAM) is critical to the implementation of autonomous driving. Most LiDAR-inertial SLAM algorithms assume a static environment, leading to unreliable localization in dynamic environments. Moreover, the accurate tracking of moving objects is of great significance for the control and planning of autonomous vehicles. This study proposes LIMOT, a tightly-coupled multi-object tracking and LiDAR-inertial odometry system that is capable of accurately estimating the poses of both ego-vehicle and objects. We propose a trajectory-based dynamic feature filtering method, which filters out features belonging to moving objects by leveraging tracking results before scan-matching. Factor graph-based optimization is then conducted to optimize the bias of the IMU and the poses of both the ego-vehicle and surrounding objects in a sliding window. Experiments conducted on the KITTI tracking dataset and self-collected dataset show that our method achieves better pose and tracking accuracy than our previous work DL-SLOT and other baseline methods. Our open-source implementation is available at https://github.com/tiev-tongji/LIMOT., Comment: 7 pages, 5 figures. This updated version mainly refines the experiments. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

Published
2023

24. 'Application of halogen moisture meter in volatile content measurement of nitrile rubber'

Author

XU Bin, YUAN Ji-yao, XIAO Ye, CHEN Dong-ping, YING Chan-juan, GUAN Yan

Subjects
halogen moisture meter, nitrile rubber, volatile content, rapid measurement, measurement condition, Organic chemistry, QD241-441, Chemical engineering, TP155-156, Chemicals: Manufacture, use, etc., TP200-248
Abstract

The volatile content in nitrile rubber was measured by halogen moisture meter and compared with the results obtained by the hot-roll method. The influence of different measurement conditions on the measured results of the halogen moisture meter was investigated. The results showed that using the halogen moisture meter, the volatile content in nitrile rubber raw rubber could be measured by both the preset drying time method and preset mass loss method. Under suitable conditions such as sample mass of 3 g, drying temperature of 110 ℃, preset heating time of 8 min, or preset mass loss of 1/140 mg/s, the measured results were consistent with the hot-roll method. This method reduced measure time, was easy to operate, and could be used to guide quickly actual production.

Published
2024
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25. Evaluation and salivary biochemistry associations of sour-salty taste interaction

Author

Hongnan Jiang, Ye Chen, Jianshe Chen, Louise Dye, and Xinmiao Wang

Subjects
Taste interaction evaluation, sensory analysis, salty taste perception, salivary biochemical components, Food processing and manufacture, TP368-456
Abstract

ABSTRACT: Taste interaction is a well-known phenomenon in sensory studies, but how to quantify the magnitude of the effect of one tastant on other taste attribute(s) is still largely unsolved, let alone further explorations from a salivary biochemistry perspective. Upon acquiring the individual taste threshold and evaluating the just noticeable difference (JND), this study firstly established a quantitative method to assess the magnitude of taste interaction in a binary taste mixture by evaluating the concentration difference upon psychologically-comparable stimulation. The change of salty taste intensity (CSI) was therefore defined as the subtraction of JND using sour-salty taste stimulant from JND using pure salty taste stimulant, with a dimension of concentration in mmol/L. CSI was then used to demonstrate how citric acid affected salty taste perception in a salty - sour binary taste mixture in 16 young and healthy participants. Concentrations of citric acid used in the binary taste mixture were 0.05, 0.09, 0.14, 0.24 and 0.40 mmol/L, respectively, and results showed that salty taste perception was enhanced (average CSI of 0.93 mmol/L) when the citric acid concentration was low (at 0.05 and 0.09 mmol/L), but with an increasing concentration of citric acid ranging from 0.14 to 0.40 mmol/L, this effect gradually turned from enhancement to suppression of salty taste perception (correspondingly a continuously decreasing CSI all the way down to an average of –2.94 mmol/L). It was also found that cystatin SN concentration in participants’ unstimulated saliva samples was significantly negatively correlated with salty taste threshold (with and without the presence of citric acid), and it was one of the most significant factors affecting CSI, as shown in multiple regression analysis. Carbonic anhydrase VI concentration in participants’ unstimulated saliva samples was also found to be significantly negatively correlated with salty taste recognition (with and without presence of citric acid), but it did not pose significant effect on CSI. From these results, this study had not only demonstrated a citric acid concentration-dependent salty taste perception phenomenon based on a proposed methodology to quantitively assess the taste interaction in binary taste mixtures, but also showed how salivary biochemical properties (cystatin SN and carbonic anhydrase VI) might have been associated with salty taste perception during food oral processing.

Published
2024
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31. Optimizing 3D UAV Path Planning: A Multi-strategy Enhanced Beluga Whale Optimizer

Author

Ye, Chen, Wang, Wentao, Zhang, Shaoping, Shao, Peng, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Luo, Biao, editor, Cheng, Long, editor, Wu, Zheng-Guang, editor, Li, Hongyi, editor, and Li, Chaojie, editor

Published
2024
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35. Patterns of neurogenic lower urinary tract dysfunction management and associated factors among Chinese community-dwelling individuals with spinal cord injury

Author

Mengyang Zhang, Ye Chen, Jiawei Liu, Can Luo, Zhong Chen, and Tao Xu

Subjects
Spinal cord injury, Neurogenic lower urinary tract dysfunction, Latent class analysis, Intermittent catheterization, Community-dwelling, Medicine, Science
Abstract

Abstract To identify different patterns of neurogenic lower urinary tract dysfunction management among Chinese community-dwelling individuals with spinal cord injury and explore the factors associated with latent classes. This was a cross-sectional study conducted in communities throughout China Mainland. Participants were recruited through the China Association of Persons with Physical Disability and a total of 2582 participants was included in the analysis. The data were collected by a questionnaire consisting of socio-demographic factors, disease-related factors, and a list of 8 bladder management methods. Latent class analysis was used to identify different latent classes of neurogenic lower urinary tract dysfunction management. Then the multinomial logistic regression was applied to analyze the relationship between neurogenic lower urinary tract dysfunction management patterns and socio-demographic and disease-related factors. Neurogenic lower urinary tract dysfunction management pattern among community-dwelling individuals with spinal cord injury was divided into four latent classes: “urinal collecting apparatus dominated pattern” (40.3%), “bladder compression dominated pattern” (30.7%), “intermittent catheterization dominated pattern” (19.3%) and “urethral indwelling catheterization dominated pattern” (9.6%). Multinomial logistic regression analysis found that the employment status, residential region, nursing need, payment method for catheterization products, hand function, time since spinal cord injury, urinary incontinence and concerns about social interaction affected by urination problems were significantly associated with latent classes. Only 19.3% of people used the intermittent catheterization as their main neurogenic lower urinary tract dysfunction management method. More attention needs to be paid to the promotion of the standardization process of intermittent catheterization in community-dwelling individuals with spinal cord injury. The associated factors of the four classes can be used for tailored and targeted interventions to increase the use of intermittent catheterization.

Published
2024
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36. Saccharomyces boulardii combined with triple therapy alter the microbiota in the eradication of Helicobacter pylori infection

Author

Yan Zhang, Bingyun Lu, Yu Dong, Yifeng Zhang, Qianming Du, Ye Chen, and Zhenyu Zhang

Subjects
Saccharomyces boulardii, Helicobacter pylori eradication, Intestinal flora, Medicine, Science
Abstract

Abstract To assess the effectiveness and safety of combining Saccharomyces boulardii powder with triple therapy as a primary approach for eradicating H. pylori infection, a total of 144 patients who tested positive for H. pylori and diagnosed with non-ulcer dyspepsia underwent endoscopy at two national centers between June 2017 and March 2019 were included. The patients were categorized into three groups using a subsection randomization method and received initial H. pylori eradication treatments. Microbial composition, eradication rates, symptom alleviation, and adverse reactions were monitored on the 14th and 44th days post-treatment. According to PP analysis showed the eradication rates for the SRAC group was 75%, BRAC was 93.18% and RAC was 65.2%. Group BRAC exhibited a marginally higher eradication rate compared to other groups. However, patients receiving Saccharomyces boulardii treatment exhibited an overall reduction in initial dyspepsia symptoms by the end of the treatment period. When employed as a primary strategy, the combination of Saccharomyces boulardii powder with triple therapy displayed notable efficacy and smaller gastrointestinal side effects in eradicating initial H. pylori infections among non-ulcer dyspepsia patients. Moreover, this approach demonstrated advantages in alleviating symptoms, exhibited favorable tolerance, and maintained a high level of clinical safety.

Published
2024
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37. Altered static and dynamic functional network connectivity in primary angle-closure glaucoma patients

Author

Yuanyuan Wang, Yongqiang Shu, Guoqian Cai, Yu Guo, Junwei Gao, Ye Chen, Lianjiang Lv, and Xianjun Zeng

Subjects
Primary angle-closure glaucoma, Magnetic resonance imaging, Static functional network connectivity, Dynamic functional network connectivity, Brain functional network, Medicine, Science
Abstract

Abstract To explore altered patterns of static and dynamic functional brain network connectivity (sFNC and dFNC) in Primary angle-closure glaucoma (PACG) patients. Clinically confirmed 34 PACG patients and 33 age- and gender-matched healthy controls (HCs) underwent evaluation using T1 anatomical and functional MRI on a 3 T scanner. Independent component analysis, sliding window, and the K-means clustering method were employed to investigate the functional network connectivity (FNC) and temporal metrics based on eight resting-state networks. Differences in FNC and temporal metrics were identified and subsequently correlated with clinical variables. For sFNC, compared with HCs, PACG patients showed three decreased interactions, including SMN-AN, SMN-VN and VN-AN pairs. For dFNC, we derived four highly structured states of FC that occurred repeatedly between individual scans and subjects, and the results are highly congruent with sFNC. In addition, PACG patients had a decreased fraction of time in state 3 and negatively correlated with IOP (p

Published
2024
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38. Origin of the light-induced spin currents in heavy metal/magnetic insulator bilayers

Author

Hongru Wang, Jing Meng, Jianjun Lin, Bin Xu, Hai Ma, Yucheng Kan, Rui Chen, Lujun Huang, Ye Chen, Fangyu Yue, Chun-Gang Duan, Junhao Chu, and Lin Sun

Subjects
Science
Abstract

Abstract Light-induced spin currents with the faster response is essential for the more efficient information transmission and processing. Herein, we systematically explore the effect of light illumination energy and direction on the light-induced spin currents in the W/Y3Fe5O12 heterojunction. Light-induced spin currents can be clearly categorized into two types. One is excited by the low light intensity, which mainly involves the photo-generated spin current from spin photovoltaic effect. The other is caused by the high light intensity, which is the light-thermally induced spin current and mainly excited by spin Seebeck effect. Under low light-intensity illumination, light-thermally induced temperature gradient is very small so that spin Seebeck effect can be neglected. Furthermore, the mechanism on spin photovoltaic effect is fully elucidated, where the photo-generated spin current in Y3Fe5O12 mainly originates from the process of spin precession induced by photons. These findings provide some deep insights into the origin of light-induced spin current.

Published
2024
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39. Association between serum vitamin A and body mass index in adolescents from NHANES 1999 to 2006

Author

Xiaoqi Su, Nishant Patel, Shanliang Zhu, Xin Zhou, Ye Chen, Jun Chen, and Xuming Mo

Subjects
Serum vitamin A, Obesity, Body mass index, NHANES, Adolescents, Medicine, Science
Abstract

Abstract Vitamin A plays a pivotal role in health, particularly in regulating fat metabolism. Despite its significance, research into the direct relationship between vitamin A levels and obesity, especially among adolescents, is sparse. This study aims to explore this association within the adolescent population in the United States. This cross-sectional study analyzed the National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2006, with 8218 participants. The levels of vitamin A in the serum were determined based on utilizing high-performance liquid chromatography with photodiode array detection. The relationship between serum vitamin A concentrations and body mass index (BMI) was evaluated using weighted multiple linear regression models, incorporating subgroup analyses by sex and race/ethnicity to provide nuanced insights. A positive correlation was observed between serum vitamin A levels and BMI, with BMI increasing progressively across vitamin A quartiles (P

Published
2024
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40. Sequential glycosylations at the multibasic cleavage site of SARS-CoV-2 spike protein regulate viral activity

Author

Shengjun Wang, Wei Ran, Lingyu Sun, Qingchi Fan, Yuanqi Zhao, Bowen Wang, Jinghong Yang, Yuqi He, Ying Wu, Yuanyuan Wang, Luoyi Chen, Arpaporn Chuchuay, Yuyu You, Xinhai Zhu, Xiaojuan Wang, Ye Chen, Yanqun Wang, Yao-Qing Chen, Yanqiu Yuan, Jincun Zhao, and Yang Mao

Subjects
Science
Abstract

Abstract The multibasic furin cleavage site at the S1/S2 boundary of the spike protein is a hallmark of SARS-CoV-2 and plays a crucial role in viral infection. However, the mechanism underlying furin activation and its regulation remain poorly understood. Here, we show that GalNAc-T3 and T7 jointly initiate clustered O-glycosylations in the furin cleavage site of the SARS-CoV-2 spike protein, which inhibit furin processing, suppress the incorporation of the spike protein into virus-like-particles and affect viral infection. Mechanistic analysis reveals that the assembly of the spike protein into virus-like particles relies on interactions between the furin-cleaved spike protein and the membrane protein of SARS-CoV-2, suggesting a possible mechanism for furin activation. Interestingly, mutations in the spike protein of the alpha and delta variants of the virus confer resistance against glycosylation by GalNAc-T3 and T7. In the omicron variant, additional mutations reverse this resistance, making the spike protein susceptible to glycosylation in vitro and sensitive to GalNAc-T3 and T7 expression in human lung cells. Our findings highlight the role of glycosylation as a defense mechanism employed by host cells against SARS-CoV-2 and shed light on the evolutionary interplay between the host and the virus.

Published
2024
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41. Predictors of Corporal Punishment during the COVID-19 Pandemic

Author

Robert D. Sege, Eliza Loren Purdue, Dina Burstein, Phyllis Holditch Niolon, Lori Lyn Price, Ye Chen, Elizabeth A. Swedo, Tammy Piazza Hurley, Kavita Prasad, and Bart Klika

Subjects
corporal punishment, spanking, intimate partner violence, COVID-19, Medicine, Pediatrics, RJ1-570
Abstract

Although current policies discourage the use of corporal punishment (CP), its use is still widespread in the US. The objective of this study was to assess the proportion of parents who used CP during the pandemic and identify related risk and protective factors. We analyzed results of a nationwide cross-sectional internet panel survey of 9000 US caregivers who responded in three waves from November 2020 to July 2021. One in six respondents reported having spanked their child in the past week. Spanking was associated with intimate partner violence and the use of multiple discipline strategies and not significantly associated with region or racial self-identification. Parents who spanked sought out more kinds of support, suggesting an opportunity to reduce spanking through more effective parenting resources. Additionally, these results suggest that parents who report using CP may be at risk for concurrent domestic violence.

Published
2024
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42. Comparison of outcomes and characteristics of patients admitted to the ICU with COVID-19 and other community-acquired pneumonia based on propensity score matching

Author

Hongli Zhao, Xiulin Yan, Ziru Guo, Kaiyu Li, Zhaopeng Wang, Jun Wang, Dong Lv, Jianling Zhu, and Ye Chen

Subjects
COVID-19, Community-acquired pneumonia, Propensity score matching, Infectious and parasitic diseases, RC109-216
Abstract

Abstract Objective To compare the similarities and differences between patients with Coronavirus Disease 2019 (COVID-19) and those with other community-acquired pneumonia (CAP) admitted to the intensive care unit (ICU), utilizing propensity score matching (PSM), regarding hospitalization expenses, treatment options, and prognostic outcomes, aiming to inform the diagnosis and treatment of COVID-19. Methods Patients admitted to the ICU of the Third People’s Hospital of Datong City, diagnosed with COVID-19 from December 2022 to February 2023, constituted the observation group, while those with other CAP admitted from January to November 2022 formed the control group. Basic information, clinical data at admission, and time from symptom onset to admission were matched using PSM. Results A total of 70 patients were included in the COVID-19 group and 119 in the CAP group. The patients were matched by the propensity matching method, and 37 patients were included in each of the last two groups. After matching, COVID-19 had a higher failure rate than CAP, but the difference was not statistically significant (73% vs. 51%, p = 0.055). The utilization rate of antiviral drugs (40% vs. 11%, p = 0.003), γ-globulin (19% vs. 0%, p = 0.011) and prone position ventilation (PPV) (27% vs. 0%, p

Published
2024
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43. The influence of hot isostatic pressing on precipitates, mechanical properties of Mg-12Gd-0.8Zn-0.4Zr (wt.%) alloy manufactured by sand casting

Author

Dan Wang, Chao Ma, Ye Chen, Li Gu, and Yangyang Yu

Subjects
Mg alloy, Hot isostatic pressing, Precipitates, Mechanical properties, Strengthening mechanism, Medicine, Science
Abstract

Abstract Microstructures and mechanical properties of Mg-12Gd-0.8Zn-0.4Zr (GZ1208K, wt.%) alloy under different treatments (as-cast: signed as nonHIP-GZ1208K, hot isostatic pressing (HIP): signed as HIP-GZ1208K) were characterized. Based on microstructure characterization, two prismatic precipitates, β′ and β1 precipitates, and one basal precipitate, γ′ precipitate, formed in both of nonHIP-GZ1208K and HIP-GZ1208K alloy. According to analysis, the area number density and the size of β′ precipitate could be adjusted through HIP treatment. The area number density of β′ precipitate increased after HIP treatment when aged at 32 h, and the size of β′ precipitate refined in both of the HIP-GZ1208K alloy aged at 8 h and 32 h. Except the influence of HIP treatment on microstructures, the ultimate tensile strength (UTS) and elongation of nonHIP-GZ1208K alloy also improved after HIP treatment. The UTS of the GZ1208K alloy aged at 8 h increased from 348 MPa (nonHIP-) to 371 MPa (HIP-) and the elongation increased from 2.6% to 4.7%. The density of the nonHIP-GZ1208K alloy increased after HIP treatment, that is to say the casting defects could be eliminated and the compactness of microstructures could be increased under the high pressure of HIP treatment.

Published
2024
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44. Frequency-encoded eye tracking smart contact lens for human–machine interaction

Author

Hengtian Zhu, Huan Yang, Siqi Xu, Yuanyuan Ma, Shugeng Zhu, Zhengyi Mao, Weiwei Chen, Zizhong Hu, Rongrong Pan, Yurui Xu, Yifeng Xiong, Ye Chen, Yanqing Lu, Xinghai Ning, Dechen Jiang, Songtao Yuan, and Fei Xu

Subjects
Science
Abstract

Abstract Eye tracking techniques enable high-efficient, natural, and effortless human-machine interaction by detecting users’ eye movements and decoding their attention and intentions. Here, a miniature, imperceptible, and biocompatible smart contact lens is proposed for in situ eye tracking and wireless eye-machine interaction. Employing the frequency encoding strategy, the chip-free and battery-free lens successes in detecting eye movement and closure. Using a time-sequential eye tracking algorithm, the lens has a great angular accuracy of

Published
2024
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45. Infusion of GMSCs relieves autoimmune arthritis by suppressing the externalization of neutrophil extracellular traps via PGE2-PKA-ERK axis

Author

Jun Zhao, Yan Liu, Xiaoyi Shi, Junlong Dang, Yu Liu, Siwen Li, Wei Cai, Yuluan Hou, Donglan Zeng, Ye Chen, Jia Yuan, Yiding Xiong, Wenbin Wu, Peihong Cai, Jingrong Chen, Jianbo Sun, Yiming Shao, David D. Brand, and Song Guo Zheng

Subjects
Rheumatoid arthritis, Gingival-derived mesenchymal stem cells, Neutrophil extracellular traps, PGE2-PKA-ERK axis, Medicine (General), R5-920, Science (General), Q1-390
Abstract

Introduction: Rheumatoid arthritis (RA) is a systemic autoimmune disease with limited treatment success, characterized by chronic inflammation and progressive cartilage and bone destruction. Accumulating evidence has shown that neutrophil extracellular traps (NETs) released by activated neutrophils are important for initiating and perpetuating synovial inflammation and thereby could be a promising therapeutic target for RA. K/B × N serum transfer-induced arthritis (STIA) is a rapidly developed joint inflammatory model that somehow mimics the inflammatory response in patients with RA. Human gingival-derived mesenchymal stem cells (GMSCs) have been previously shown to possess immunosuppressive effects in arthritis and humanized animal models. However, it is unknown whether GMSCs can manage neutrophils in autoimmune arthritis. Objectives: To evaluate whether infusion of GMSCs can alleviate RA by regulating neutrophils and NETs formation. If this is so, we will explore the underlying mechanism(s) in an animal model of inflammatory arthritis. Methods: The effects of GMSCs on RA were assessed by comparing the symptoms of the K/B × N serum transfer-induced arthritis (STIA) model administered either with GMSCs or with control cells. Phenotypes examined included clinical scores, rear ankle thickness, paw swelling, inflammation, synovial cell proliferation, and immune cell frequency. The regulation of GMSCs on NETs was examined through immunofluorescence and immunoblotting in GMSCs-infused STIA mice and in an in vitro co-culture system of neutrophils with GMSCs. The molecular mechanism(s) by which GMSCs regulate NETs was explored both in vitro and in vivo by silencing experiments. Results: We found in this study that adoptive transfer of GMSCs into STIA mice significantly ameliorated experimental arthritis and reduced neutrophil infiltration and NET formation. In vitro studies also showed that GMSCs inhibited the generation of NETs in neutrophils. Subsequent investigations revealed that GMSCs secreted prostaglandin E2 (PGE2) to activate protein kinase A (PKA), which ultimately inhibited the downstream extracellular signal-regulated kinase (ERK) pathway that is essential for NET formation. Conclusion: Our results demonstrate that infusion of GMSCs can ameliorate inflammatory arthritis mainly by suppressing NET formation via the PGE2-PKA-ERK signaling pathway. These findings further support the notion that the manipulation of GMSCs is a promising stem cell-based therapy for patients with RA and other autoimmune and inflammatory diseases.

Published
2024
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46. DL-SLOT: Dynamic LiDAR SLAM and object tracking based on collaborative graph optimization

Author

Tian, Xuebo, Zhu, Zhongyang, Zhao, Junqiao, Tian, Gengxuan, and Ye, Chen

Subjects
Computer Science - Robotics
Abstract

Ego-pose estimation and dynamic object tracking are two critical problems for autonomous driving systems. The solutions to these problems are generally based on their respective assumptions, \ie{the static world assumption for simultaneous localization and mapping (SLAM) and the accurate ego-pose assumption for object tracking}. However, these assumptions are challenging to hold in dynamic road scenarios, where SLAM and object tracking become closely correlated. Therefore, we propose DL-SLOT, a dynamic LiDAR SLAM and object tracking method, to simultaneously address these two coupled problems. This method integrates the state estimations of both the autonomous vehicle and the stationary and dynamic objects in the environment into a unified optimization framework. First, we used object detection to identify all points belonging to potentially dynamic objects. Subsequently, a LiDAR odometry was conducted using the filtered point cloud. Simultaneously, we proposed a sliding window-based object association method that accurately associates objects according to the historical trajectories of tracked objects. The ego-states and those of the stationary and dynamic objects are integrated into the sliding window-based collaborative graph optimization. The stationary objects are subsequently restored from the potentially dynamic object set. Finally, a global pose-graph is implemented to eliminate the accumulated error. Experiments on KITTI datasets demonstrate that our method achieves better accuracy than SLAM and object tracking baseline methods. This confirms that solving SLAM and object tracking simultaneously is mutually advantageous, dramatically improving the robustness and accuracy of SLAM and object tracking in dynamic road scenarios., Comment: 10 pages, 10 figures, this work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

Published
2022

47. Phase diagram of superconducting vortex ratchet motion in a superlattice with noncentrosymmetry

Author

Li, Shengyao, Zhang, Lijuan, Huang, Ke, Ye, Chen, Xing, Tingjing, Yang, Liu, Yang, Zherui, Zhu, Qiang, Sun, Bo, Wang, Xueyan, and Wang, X. Renshaw

Subjects
Condensed Matter - Superconductivity
Abstract

Ratchet motion of superconducting vortices, which is a directional flow of vortices in superconductors, is highly useful for exploring quantum phenomena and developing superconducting devices, such as superconducting diode and microwave antenna. However, because of the challenges in the quantitative characterization of the dynamic motion of vortices, a phase diagram of the vortex ratchet motion is still missing, especially in the superconductors with low dimensional structures. Here we establish a quantitative phase diagram of the vortex ratchet motion in a highly anisotropic superlattice superconductor, (SnS)1.17NbS2, using nonreciprocal magnetotransport. The (SnS)1.17NbS2, which possesses a layered atomic structure and noncentrosymmetry, exhibits nonreciprocal magnetotransport in a magnetic field perpendicular and parallel to the plane, which is considered a manifest of ratchet motion of superconducting vortices. We demonstrated that the ratchet motion is responsive to current excitation, magnetic field and thermal perturbation. Furthermore, we extrapolated a giant nonreciprocal coefficient ({\gamma}), which quantitatively describes the magnitude of the vortex ratchet motion, and eventually established phase diagrams of the ratchet motion of the vortices with a quantitative description. Last, we propose that the ratchet motion originates from the coexistence of pancake vortices (PVs) and Josephson vortices (JVs). The phase diagrams are desirable for controlling the vortex motion in superlattice superconductors and developing next-generation energy-efficient superconducting devices.

Published
2022
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48. Room temperature charge-to-spin conversion from q-2DEG at SrTiO3-based interfaces

Author

Shashank, Utkarsh, Deka, Angshuman, Ye, Chen, Gupta, Surbhi, Medwal, Rohit, Rawat, Rajdeep Singh, Asada, Hironori, Wang, X. Renshaw, and Fukuma, Yasuhiro

Subjects
Condensed Matter - Materials Science
Abstract

Interfacial two-dimensional electron gas (2DEG), especially the SrTiO3-based ones at the unexpected interface of insulators, have emerged to be a promising candidate for efficient charge-spin current interconversion. In this article, to gain insight into the mechanism of the charge-spin current interconversion at the oxide-based 2DEG, we focused on conducting interfaces between insulating SrTiO3 and two types of aluminium-based amorphous insulators, namely SrTiO3/AlN and SrTiO3/Al2O3, and estimated their charge-spin conversion efficiency, {\theta}_cs. The two types of amorphous insulators were selected to explicitly probe the overlooked contribution of oxygen vacancy to the {\theta}_cs. We proposed a mechanism to explain results of spin-torque ferromagnetic resonance (ST-FMR) measurements and developed an analysis protocol to reliably estimate the {\theta}_cs of the oxide based 2DEG. The resultant {\theta}_cs/t, where t is the thickness of the 2DEG, were estimated to be 0.244 nm-1 and 0.101 nm-1 for the SrTiO3/AlN and SrTiO3/Al2O3, respectively, and they are strikingly comparable to their crystalline counterparts. Furthermore, we also observe a large direct current modulation of resonance linewidth in SrTiO3/AlN samples, confirming its high {\theta}_cs and attesting an oxygen-vacancy-enabled charge-spin conversion. Our findings emphasize the defects' contribution to the charge-spin interconversion, especially in the oxide-based low dimensional systems, and provide a way to create and enhance charge-spin interconversion via defect engineering.

Published
2022
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49. Molecular basis of CX-5461-induced DNA damage response in primary vascular smooth muscle cells

Author

Tengfei Liu, Guopin Pan, Jing Zhang, Jianli Wang, Xiaosun Guo, Ye Chen, Xiaoyun Wang, Xiaopei Cui, Huiqing Liu, and Fan Jiang

Subjects
CX-5461, DNA damage response, Replication stress, Nucleolus, ATM/ATR, p53, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Our previous studies have shown that the novel selective RNA polymerase I inhibitor CX-5461 suppresses proliferation of vascular smooth muscle cells, mainly by inducing DNA damage response (DDR), including activations of ataxia telangiectasia mutated (ATM)/ATM and Rad3-related (ATR) and p53. Currently, there is no information about the molecular mechanism(s) underlying CX-5461-induced DDR in vascular cells, while the results obtained in cancer cells and immortalized cell lines are controversial. In this study, we examined the responses of various DDR pathways to CX-5461 treatment in primary aortic smooth muscle cells isolated from normal adult Sprague Dawley rats. We demonstrated that CX-5461-induced DDR was not associated with activations of the nucleotide excision repair, DNA mismatch repair, or the non-homologous end joining pathways, while the homologous recombination pathway was activated. However, the alkaline comet assay did not show massive DNA double strand breaks in CX-5461-treated cells. Instead, CX-5461-induced DDR appeared to be related to induction of DNA replication stress, which was not attributable to increased formation of G-quadruplex or R-loop structures, but might be explained by the increased replication-transcription conflict. CX-5461-induced DDR was not exclusively confined to rDNA within the nucleolar compartment; the extra-nucleolar DDR might represent a distinct secondary response related to the downregulated Rad51 expression in CX-5461-treated cells. In summary, we suggest that DNA replication stress may be the primary molecular event leading to downstream ATM/ATR and p53 activations in CX-5461-treated vascular smooth muscle cells. Our results provide further insights into the molecular basis of the beneficial effects of CX-5461 in proliferative vascular diseases.

Published
2024
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50. Development and evaluation of a rapid visual loop-mediated isothermal amplification assay for the tcdA gene in Clostridioides difficile detection

Author

Minyi Lin, Pu Wang, Bingyun Lu, Ming Jin, Jiasheng Tan, Wei Liu, Jing Yuan, Xiaomou Peng, and Ye Chen

Subjects
tcdA gene, Clostridioides difficile, Loop-mediated isothermal amplification, Visual detection, Medicine, Biology (General), QH301-705.5
Abstract

Background The tcdA gene codes for an important toxin produced by Clostridioides difficile (C. difficile), but there is currently no simple and cost-effective method of detecting it. This article establishes and validates a rapid and visual loop-mediated isothermal amplification (LAMP) assay for the detection of the tcdA gene. Methods Three sets of primers were designed and optimized to amplify the tcdA gene in C. difficile using a LAMP assay. To evaluate the specificity of the LAMP assay, C. difficile VPI10463 was used as a positive control, while 26 pathogenic bacterial strains lacking the tcdA gene and distilled water were utilized as negative controls. For sensitivity analysis, the LAMP assay was compared to PCR using ten-fold serial dilutions of DNA from C. difficile VPI10463, ranging from 207 ng/µl to 0.000207 pg/µl. The tcdA gene of C.difficile was detected in 164 stool specimens using both LAMP and polymerase chain reaction (PCR). Positive and negative results were distinguished using real-time monitoring of turbidity and chromogenic reaction. Results At a temperature of 66 °C, the target DNA was successfully amplified with a set of primers designated, and visualized within 60 min. Under the same conditions, the target DNA was not amplified with the tcdA12 primers for 26 pathogenic bacterial strains that do not carry the tcdA gene. The detection limit of LAMP was 20.700 pg/µl, which was 10 times more sensitive than that of conventional PCR. The detection rate of tcdA in 164 stool specimens using the LAMP method was 17% (28/164), significantly higher than the 10% (16/164) detection rate of the PCR method (X2 = 47, p < 0.01). Conclusion LAMP method is an effective technique for the rapid and visual detection of the tcdA gene of C. difficile, and shows potential advantages over PCR in terms of speed, simplicity, and sensitivity. The tcdA-LAMP assay is particularly suitable for medical diagnostic environments with limited resources and is a promising diagnostic strategy for the screening and detection of C. difficile infection in populations at high risk.

Published
2024
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