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1. Case-based reasoning approach for diagnostic screening of children with developmental delays

Author

Song, Zichen, Li, Jiakang, Lai, Songning, and Huang, Sitan

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

According to the World Health Organization, the population of children with developmental delays constitutes approximately 6% to 9% of the total population. Based on the number of newborns in Huaibei, Anhui Province, China, in 2023 (94,420), it is estimated that there are about 7,500 cases (suspected cases of developmental delays) of suspicious cases annually. Early identification and appropriate early intervention for these children can significantly reduce the wastage of medical resources and societal costs. International research indicates that the optimal period for intervention in children with developmental delays is before the age of six, with the golden treatment period being before three and a half years of age. Studies have shown that children with developmental delays who receive early intervention exhibit significant improvement in symptoms; some may even fully recover. This research adopts a hybrid model combining a CNN-Transformer model with Case-Based Reasoning (CBR) to enhance the screening efficiency for children with developmental delays. The CNN-Transformer model is an excellent model for image feature extraction and recognition, effectively identifying features in bone age images to determine bone age. CBR is a technique for solving problems based on similar cases; it solves current problems based on past experiences, similar to how humans solve problems through learning from experience. Given CBR's memory capability to judge and compare new cases based on previously stored old cases, it is suitable for application in support systems with latent and variable characteristics. Therefore, this study utilizes the CNN-Transformer-CBR to establish a screening system for children with developmental delays, aiming to improve screening efficiency.

Published
2024

2. CCSRP: Robust Pruning of Spiking Neural Networks through Cooperative Coevolution

Author

Song, Zichen, Li, Jiakang, Lai, Songning, and Huang, Sitan

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

Spiking neural networks (SNNs) have shown promise in various dynamic visual tasks, yet those ready for practical deployment often lack the compactness and robustness essential in resource-limited and safety-critical settings. Prior research has predominantly concentrated on enhancing the compactness or robustness of artificial neural networks through strategies like network pruning and adversarial training, with little exploration into similar methodologies for SNNs. Robust pruning of SNNs aims to reduce computational overhead while preserving both accuracy and robustness. Current robust pruning approaches generally necessitate expert knowledge and iterative experimentation to establish suitable pruning criteria or auxiliary modules, thus constraining their broader application. Concurrently, evolutionary algorithms (EAs) have been employed to automate the pruning of artificial neural networks, delivering remarkable outcomes yet overlooking the aspect of robustness. In this work, we propose CCSRP, an innovative robust pruning method for SNNs, underpinned by cooperative co-evolution. Robust pruning is articulated as a tri-objective optimization challenge, striving to balance accuracy, robustness, and compactness concurrently, resolved through a cooperative co-evolutionary pruning framework that independently prunes filters across layers using EAs. Our experiments on CIFAR-10 and SVHN demonstrate that CCSRP can match or exceed the performance of the latest methodologies.

Published
2024

3. A Comprehensive Review of Community Detection in Graphs

Author

Li, Jiakang, Lai, Songning, Shuai, Zhihao, Tan, Yuan, Jia, Yifan, Yu, Mianyang, Song, Zichen, Peng, Xiaokang, Xu, Ziyang, Ni, Yongxin, Qiu, Haifeng, Yang, Jiayu, Liu, Yutong, and Lu, Yonggang

Subjects
Computer Science - Social and Information Networks, Computer Science - Machine Learning
Abstract

The study of complex networks has significantly advanced our understanding of community structures which serves as a crucial feature of real-world graphs. Detecting communities in graphs is a challenging problem with applications in sociology, biology, and computer science. Despite the efforts of an interdisciplinary community of scientists, a satisfactory solution to this problem has not yet been achieved. This review article delves into the topic of community detection in graphs, which serves as a thorough exposition of various community detection methods from perspectives of modularity-based method, spectral clustering, probabilistic modelling, and deep learning. Along with the methods, a new community detection method designed by us is also presented. Additionally, the performance of these methods on the datasets with and without ground truth is compared. In conclusion, this comprehensive review provides a deep understanding of community detection in graphs.

Published
2023

7. Shared and Private Information Learning in Multimodal Sentiment Analysis with Deep Modal Alignment and Self-supervised Multi-Task Learning

Author

Lai, Songning, Li, Jiakang, Guo, Guinan, Hu, Xifeng, Li, Yulong, Tan, Yuan, Song, Zichen, Liu, Yutong, Ren, Zhaoxia, Wan, Chun, Miao, Danmin, and Liu, Zhi

Subjects
Computer Science - Computation and Language, Computer Science - Computer Vision and Pattern Recognition
Abstract

Designing an effective representation learning method for multimodal sentiment analysis tasks is a crucial research direction. The challenge lies in learning both shared and private information in a complete modal representation, which is difficult with uniform multimodal labels and a raw feature fusion approach. In this work, we propose a deep modal shared information learning module based on the covariance matrix to capture the shared information between modalities. Additionally, we use a label generation module based on a self-supervised learning strategy to capture the private information of the modalities. Our module is plug-and-play in multimodal tasks, and by changing the parameterization, it can adjust the information exchange relationship between the modes and learn the private or shared information between the specified modes. We also employ a multi-task learning strategy to help the model focus its attention on the modal differentiation training data. We provide a detailed formulation derivation and feasibility proof for the design of the deep modal shared information learning module. We conduct extensive experiments on three common multimodal sentiment analysis baseline datasets, and the experimental results validate the reliability of our model. Furthermore, we explore more combinatorial techniques for the use of the module. Our approach outperforms current state-of-the-art methods on most of the metrics of the three public datasets.

Published
2023

8. Community Detection Using Revised Medoid-Shift Based on KNN

Author

Hou, Jie, Li, Jiakang, Peng, Xiaokang, Ke, Wei, and Lu, Yonggang

Subjects
Computer Science - Social and Information Networks, Computer Science - Machine Learning
Abstract

Community detection becomes an important problem with the booming of social networks. The Medoid-Shift algorithm preserves the benefits of Mean-Shift and can be applied to problems based on distance matrix, such as community detection. One drawback of the Medoid-Shift algorithm is that there may be no data points within the neighborhood region defined by a distance parameter. To deal with the community detection problem better, a new algorithm called Revised Medoid-Shift (RMS) in this work is thus proposed. During the process of finding the next medoid, the RMS algorithm is based on a neighborhood defined by KNN, while the original Medoid-Shift is based on a neighborhood defined by a distance parameter. Since the neighborhood defined by KNN is more stable than the one defined by the distance parameter in terms of the number of data points within the neighborhood, the RMS algorithm may converge more smoothly. In the RMS method, each of the data points is shifted towards a medoid within the neighborhood defined by KNN. After the iterative process of shifting, each of the data point converges into a cluster center, and the data points converging into the same center are grouped into the same cluster. The RMS algorithm is tested on two kinds of datasets including community datasets with known ground truth partition and community datasets without ground truth partition respectively. The experiment results show sthat the proposed RMS algorithm generally produces betster results than Medoid-Shift and some state-of-the-art together with most classic community detection algorithms on different kinds of community detection datasets.

Published
2023
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11. When Automatic Voice Disguise Meets Automatic Speaker Verification

Author

Zheng, Linlin, Li, Jiakang, Sun, Meng, Zhang, Xiongwei, and Zheng, Thomas Fang

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Cryptography and Security, Computer Science - Sound
Abstract

The technique of transforming voices in order to hide the real identity of a speaker is called voice disguise, among which automatic voice disguise (AVD) by modifying the spectral and temporal characteristics of voices with miscellaneous algorithms are easily conducted with softwares accessible to the public. AVD has posed great threat to both human listening and automatic speaker verification (ASV). In this paper, we have found that ASV is not only a victim of AVD but could be a tool to beat some simple types of AVD. Firstly, three types of AVD, pitch scaling, vocal tract length normalization (VTLN) and voice conversion (VC), are introduced as representative methods. State-of-the-art ASV methods are subsequently utilized to objectively evaluate the impact of AVD on ASV by equal error rates (EER). Moreover, an approach to restore disguised voice to its original version is proposed by minimizing a function of ASV scores w.r.t. restoration parameters. Experiments are then conducted on disguised voices from Voxceleb, a dataset recorded in real-world noisy scenario. The results have shown that, for the voice disguise by pitch scaling, the proposed approach obtains an EER around 7% comparing to the 30% EER of a recently proposed baseline using the ratio of fundamental frequencies. The proposed approach generalizes well to restore the disguise with nonlinear frequency warping in VTLN by reducing its EER from 34.3% to 18.5%. However, it is difficult to restore the source speakers in VC by our approach, where more complex forms of restoration functions or other paralinguistic cues might be necessary to restore the nonlinear transform in VC. Finally, contrastive visualization on ASV features with and without restoration illustrate the role of the proposed approach in an intuitive way., Comment: accepted for publication

Published
2020

12. Adptive Heading Control of Underactuated Unmanned Surface Vehicle Based on Improved Backpropagation Neural Network

Author

Dong Zaopeng, Li Jiakang, Liu Wei, Zhang Haisheng, Qi Shijie, and Zhang Zhengqi

Subjects
underactuated unmanned surface vehicle, backpropagation neural network controller, heading control, hyperbolic tangent function, Naval architecture. Shipbuilding. Marine engineering, VM1-989
Abstract

Aiming at the challenges to the accurate and stable heading control of underactuated unmanned surface vehicles arising from the nonlinear interference caused by the overlay and the interaction of multi interference, and also the uncertainties of model parameters, a heading control algorithm for an underactuated unmanned surface vehicle based on an improved backpropagation neural network is proposed. Based on applying optimization theory to realize that the underactuated unmanned surface vehicle tracks the desired yaw angle and maintains it, the improved momentum of weight is combined with an improved tracking differentiator to improve the robustness of the system and the dynamic property of the control. A hyperbolic tangent function is used to establish the nonlinear mappings an approximate method is adopted to summarize the general mathematical expressions, and the gradient descent method is applied to ensure the convergence. The simulation results show that the proposed algorithm has the advantages of strong robustness, strong anti-interference and high control accuracy. Compared with two commonly used heading control algorithms, the accuracy of the heading control in the complex environment of the proposed algorithm is improved by more than 50%.

Published
2023
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13. An Improved Dynamic Surface Sliding Mode Method for Autonomous Cooperative Formation Control of Underactuated USVS with Complex Marine Environment Disturbances

Author

Dong Zaopeng, Qi Shijie, Yu Min, Zhang Zhengqi, Zhang Haisheng, Li Jiakang, and Liu Yang

Subjects
underactuated usv, dynamic surface sliding mode control, lateral velocity tracking differentiator, nonlinear disturbance observer, Naval architecture. Shipbuilding. Marine engineering, VM1-989
Abstract

In this paper, a novel dynamic surface sliding mode control (DSSMC) method, combined with a lateral velocity tracking differentiator (LVTD), is proposed for the cooperative formation control of underactuated unmanned surface vehicles (USVs) exposed to complex marine environment disturbances. Firstly, in view of the kinematic and dynamic models of USVs and the design idea of a virtual control law in a backstepping approach, the trajectory tracking control problem of USVs’ cooperative formation is transformed into a stabilisation problem of the virtual control law of longitudinal and lateral velocities. Then, aiming at the problem of differential explosion caused by repeated derivation in the process of backstepping design, the first-order low-pass filter about the virtual longitudinal velocity and intermediate state quantity of position is constructed to replace differential calculations during the design of the control law, respectively. In order to reduce the steady-state error when stabilising the virtual lateral velocity control law, the integral term is introduced into the design of the sliding mode surface with a lateral velocity error, and then the second-order sliding mode surface with an integral is structured. In addition, due to the problem of controller oscillation and the role of the tracking differentiator (TD) in active disturbance rejection control (ADRC), the LVTD is designed to smooth the state quantity of lateral velocity. Subsequently, based on the dynamic model of USV under complex marine environment disturbances, the nonlinear disturbance observer is designed to observe the disturbances and compensate the control law. Finally, the whole cooperative formation system is proved to be uniformly and ultimately bounded, according to the Lyapunov stability theory, and the stability and validity of the method is also verified by the simulation results.

Published
2022
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18. Research on Measuring the Bodies of Underwater Fish with Inclined Positions Using the YOLOv8 Model and a Line-Laser System.

Author

Li, Jiakang, Zhang, Shengmao, Li, Penglong, Dai, Yang, and Wu, Zuli

Subjects
*FISH farming, *IDENTIFICATION of fishes, *SUBMERGED structures, *LENGTH measurement, *FISHING techniques, *AQUACULTURE
Abstract

Fish body measurement is essential for monitoring fish farming and evaluating growth. Non-destructive underwater measurements play a significant role in aquaculture management. This study involved annotating images of fish in aquaculture settings and utilized a line laser for underwater distance calibration and fish body inclined-angle calculation. The YOLOv8 model was employed for fish identification and key-point detection, enabling the determination of actual body dimensions through a mathematical model. The results show a root-mean-square error of 6.8 pixels for underwater distance calibration using the line laser. The pre-training YOLOv8-n, with its lower parameter counts and higher MAP values, proved more effective for fish identification and key-point detection, considering speed and accuracy. Average body length measurements within 1.5 m of the camera showed a minor deviation of 2.46% compared to manual measurements. The average relative errors for body length and width were 2.46% and 5.11%, respectively, with corresponding average absolute errors. This study introduces innovative techniques for fish body measurement in aquaculture, promoting the digitization and informatization of aquaculture processes. [ABSTRACT FROM AUTHOR]

Published
2024
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20. Research on SOFC Properties of Low Concentration Gas Fuel and SFM-GDC Reforming

Author

Han Chao, Dong Xinyue, He Leiyi, Xu Jin, Li Pengxiang, and Li Jiakang

Subjects
Environmental sciences, GE1-350
Abstract

When gas fuel is used in solid oxide fuel cells, methane cracking occurs at high temperature in the Ni-based anode, forming granular carbon deposition in the active site of the anode, and finally completely wrapped Ni metal, greatly losing the electrochemical performance. Therefore, it is very necessary to add a reforming catalytic layer in the anode of the battery. The methane is reformed into CO and H2 fuel before entering the anode, and the place where methane cracking occurs is mostly transferred to the reforming layer, which reduces the catalytic reforming burden of the Ni-based anode, so as to effectively improve the battery performance. In this paper, Sr2Fe1.5Mo0.5O6 with double perovskite structure was synthesized and prepared, which maintained very good stability in high temperature REDOX atmosphere and had high electrical conductivity. The combination of GDC and SFM can increase the reaction site of the three-phase interface of the reforming layer, and also help to improve the thermal expansion matching between the reforming layer and anode. In this paper, the electrochemical performance of straight cell coated with SSFM-GDC reforming layer has been studied. Low concentration gas in coal mine contains methane, oxygen, nitrogen, and water hydrogen sulfide, etc., and its reaction process in solid oxide fuel cells is complicated. Therefore, studying the reaction mechanism of low concentration gas in solid oxide fuel cells has important practical significance for promoting its application.

Published
2023
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25. Biological Characteristics of Feline Calicivirus Epidemic Strains in China and Screening of Broad-Spectrum Protective Vaccine Strains.

Author

Cao, Longlong, Liu, Jian, Li, Yongfan, Xie, Denglong, Yan, Quanhui, Li, Qiuyan, Cao, Yiran, Du, Wenxin, Li, Jiakang, Ye, Zijun, Zhou, Dengyuan, Kang, Chao, and Cao, Shengbo

Subjects
CAT diseases, CALICIVIRUSES, ANTIBODY titer, VACCINES, VACCINE effectiveness, RESPIRATORY diseases
Abstract

Feline calicivirus (FCV) is one of the most important pathogens causing upper respiratory tract diseases in cats, posing a serious health threat to these animals. At present, FCV is mainly prevented through vaccination, but the protective efficacy of vaccines in China is limited. In this study, based on the differences in capsid proteins of isolates from different regions in China, as reported in our previous studies, seven representative FCV epidemic strains were selected and tested for their viral titers, virulence, immunogenicity, and extensive cross-protection. Subsequently, vaccine strains were selected to prepare inactivated vaccines. The whole-genome sequencing and analysis results showed that these seven representative FCV strains and 144 reference strains fell into five groups (A, B, C, D, and E). The strains isolated in China mainly fall into groups C and D, exhibiting regional characteristics. These Chinese isolates had a distant evolutionary relationship and low homology with the current FCV-255 vaccine strain. The screened FCV-HB7 and FCV-HB10 strains displayed desirable in vitro culture characteristics, with the highest virus proliferation titers (109.5 TCID50/mL) at 36 h post inoculation at a dose of 0.01 MOI. All five cats infected intranasally with FCV-HB7 or FCV-HB10 strains showed obvious clinical symptoms of FCV. The symptoms of cats infected with the FCV-HB7 strain were more severe than those infected with the FCV-HB10 strain. Both the single-strain inactivated immunization and combined bivalent inactivated vaccine immunization of FCV-HB7 and FCV-HB10 induced high neutralizing antibody titers in five cats immunized. Moreover, bivalent inactivated vaccine immunization protected cats from FCV-HB7 and FCV-HB10 strains. The cross-neutralizing antibody titer against seven representative FCV epidemic strains achieved by combined bivalent inactivated vaccine immunization was higher than that achieved by single-strain immunization, which was much higher than that achieved by commercial vaccine FCV-255 strain immunization. The above results suggest that the FCV-HB7 and FCV-HB10 strains screened in this study have great potential to become vaccine strains with broad-spectrum protective efficacy. However, their immune protective efficacy needs to be further verified by multiple methods before clinical application. [ABSTRACT FROM AUTHOR]

Published
2023
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35. Molecular characterization of antimicrobial resistance and virulence factors of Enterococcus faecalis from ducks at slaughterhouses

Author

Li, Jiakang, primary, Yang, Lei, additional, Huang, Xuelin, additional, Wen, Yiping, additional, Zhao, Qin, additional, Huang, Xiaobo, additional, Xia, Jing, additional, Huang, Yong, additional, Cao, Sanjie, additional, Du, Senyan, additional, Wu, Rui, additional, Zou, Likou, additional, Yan, Qigui, additional, and Han, Xinfeng, additional

Published
2022
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36. Additional file 1 of Characterization of a novel chitinolytic Serratia marcescens strain TC-1 with broad insecticidal spectrum

Author

Tao, Aili, Wang, Tan, Pang, Fahu, Zheng, Xueling, Ayra-Pardo, Camilo, Huang, Siliang, Xu, Ruxin, Liu, Fengqin, Li, Jiakang, Wei, Yibin, Wang, Zhiqing, Niu, Qiuhong, and Li, Dandan

Abstract

Additional file 1: Table S1. Effects of two levels (A and B) of chitinase-containing culture supernatants (CCS) of strain TC -1 on death rates of Spodoptera exigua larvae. Table S2. A broad-spectrum screening assay of primary chitinase with the highest chitinolytic activity in the culture supernatant of the strain TC-1 by isoelectric precipitation. Table S3. A narrow-spectrum screening assay of primary chitinase with the highest chitinolytic activity in the culture supernatant of the strain TC-1 by isoelectric precipitation. Table S4. Toxicity of the pH 6.7-precipitated crude chitinase from the culture supernatant of strain TC-1 against the second- and third-instar larvae of Spodoptera exigua1. Table S5. Factors and levels of response surface design for optimization of chitinase production conditions of strain TC-1. Table S6. Credibility analysis of the regression model. Figure S1. The standard curve of N-acetylglucosamine.

Published
2022
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39. Hyperspectral Real-Time Online Processing Local Anomaly Detection via Multiline Multiband Progressing

Author

Liu, Shihui, Song, Meiping, Li, Hui, Yang, Tingting, Cui, Bolun, Li, Xin, Li, Jiakang, and Xu, Dayong

Abstract

Anomaly detection, as one of the most critical tasks in hyperspectral image (HSI) processing, has been paid extensive attention in the past decades. The classical work of hyperspectral anomaly detection, sample correlation matrix R-based anomaly detection (R-AD), can achieve desirable detection accuracy, but its processing complexity remains a challenging problem. Real-time anomaly detection methods speed up the procedure through processing the data acquired by grating splitting or acousto-optic tunable filter (AOTF)-based imaging systems in the manner of pixel-by-pixel, line-by-line, or band-by-band. However, in practical industrial scenarios, the multiarray filter spectral imaging system is generally leveraged to avoid high construction and maintenance costs, which acquires multiline multiband (MLMB) data lacking a real-time processing version. In addition, the background of industrial assembly lines is chaotic, and the changes between batches are rapid, both increasing the difficulty of accurate anomaly detection online. To cope with these challenges, a real-time online processing version [real-time multiline multiband R anomaly detection (RTMLMB-RAD)] of R-AD based on MLMB data is proposed here for the first time. Specifically, a multiline multiband correlation matrix (MLMBCM) is designed to update the detector of R-AD recursively with MLMB data acquisition. Since MLMBCM relies only on the previous result and the current data, a large amount of data storage and complex matrix inversion calculation are avoided. At the same time, local anomaly detection mode is adopted to improve the sensitivity of anomalies in different batches and different types of products. The experimental results on six public hyperspectral datasets demonstrate that the proposed RTMLMB-RAD algorithm outperforms other state-of-the-art methods in terms of time cost and detection accuracy. Particularly, the proposed algorithm was tested on the tobacco primary processing line with a detection rate of 87% and a false alarm rate of 10% at a speed of 3 m/s, further verifying the algorithm’s feasibility and effectiveness in practical industrial scenarios.

Published
2023
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44. Molecular characterization of antimicrobial resistance and virulence factors of Enterococcus faecalisfrom ducks at slaughterhouses

Author

Li, Jiakang, Yang, Lei, Huang, Xuelin, Wen, Yiping, Zhao, Qin, Huang, Xiaobo, Xia, Jing, Huang, Yong, Cao, Sanjie, Du, Senyan, Wu, Rui, Zou, Likou, Yan, Qigui, and Han, Xinfeng

Abstract

This study investigated the prevalence of antimicrobial resistant Enterococcus faecalis(E. faecalis) from ducks at slaughterhouses, analyzed antimicrobial resistance genes and virulence-associated genes of the isolates. Multilocus sequence typing (MLST) was performed to characterize their molecular characteristics. A total of 227 E. faecalisisolates (67.8%) were obtained from cecum (n = 114), cloaca (n = 50), skin (n = 59), and rinsed water (n = 4). These E. faecalisexhibited high level of resistance against tetracycline (95.6%), doxycycline (94.3%), linezolid (75.8%), erythromycin (72.2%), followed by norfloxacin (56.8%), vancomycin (38.3%), penicillin (36.1%), teicoplanin (30.8%). Lower level of resistance was found to high-level streptomycin (19.8%), imipenem (15.9%) and high-level gentamicin (5.7%). The vast majority of isolates (90.3%) were multidrug resistant (MDR). Moreover, the commonly observed resistance genes were optrA(90.7%) and ermB(90.3%), followed by aph(3’)-Ⅲ(86.8%), tetM(84.6%), acc(6’)-aph(2)(77.5%), blaZ(76.7%) and aac(6’)-Ie-aph(2”)-Ia(75.8%). The less frequently observed genes were vanC(19.8%), blaTEM(4.8%), vanM(2.6%), and vanA(0.4%). None of the strains carried aph(2”)-Icand vanBgenes. Furthermore, a high prevalence of ten virulence determinants was identified, and efaA(99.1%) was predominant, followed by eep(97.4%), srtA(96.9%), asa1(95.6%), fsrB(92.1%), sprE(89.9%), aggA(63.9%), gelE(56.4%), esp(33.9%), and cylL(15.4%). Eleven isolates (4.9%) co-carried all of the tested virulence-associated genes. MLST analysis demonstrated that, E. faecalisisolates consisted of 12 known STs and 5 new STs, among which 6 of the identified STs were associated with nosocomial infection. Our data indicated that retail ducks serve as an important source of MDR E. faecaliswith high pathogenicity potential, and suggested that transmission to humans could not be excluded.

Published
2021
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45. Ultra-flat multicarrier light source based on recirculating frequency shift loop driven by a parity-time symmetric optoelectronic oscillator.

Author

Zhou J, Ban X, Zhang J, Li J, Yang J, Jia D, Ge C, and Wang Z

Abstract

A multicarrier light source based on a recirculating frequency shift loop (RFSL) driven by a parity-time (PT)-symmetric optoelectronic oscillator (OEO) is proposed and experimentally demonstrated. The impact of the side-mode suppression ratio (SMSR) of the radio frequency (RF) signal on the multicarrier is studied for the first time, to our knowledge. The RFSL driven by PT-symmetric OEO significantly optimizes the phase noise and flatness of the multicarrier, facilitating the system miniaturization. In the experiment, a 10.019 GHz RF signal with a SMSR of 42 dB is generated with -98.63 d B c / H z measured phase noise at 10 kHz offset frequency (actual phase noise should be lower than -122.87 d B c / H z ). Up to 120 subcarriers with 2.32 dB flatness are obtained successfully, covering the overall bandwidth of approximately 1.2 THz.

Published
2023
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