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1. 3rd Workshop on Maritime Computer Vision (MaCVi) 2025: Challenge Results

Author

Kiefer, Benjamin, Žust, Lojze, Muhovič, Jon, Kristan, Matej, Perš, Janez, Teršek, Matija, Desai, Uma Mudenagudi Chaitra, Wiliem, Arnold, Kreis, Marten, Akalwadi, Nikhil, Quan, Yitong, Zhong, Zhiqiang, Zhang, Zhe, Liu, Sujie, Chen, Xuran, Yang, Yang, Fabijanić, Matej, Ferreira, Fausto, Lee, Seongju, Lee, Junseok, Lee, Kyoobin, Yao, Shanliang, Guan, Runwei, Huang, Xiaoyu, Ni, Yi, Kumar, Himanshu, Feng, Yuan, Cheng, Yi-Ching, Lin, Tzu-Yu, Lee, Chia-Ming, Hsu, Chih-Chung, Sheikh, Jannik, Michel, Andreas, Gross, Wolfgang, Weinmann, Martin, Šarić, Josip, Lin, Yipeng, Yang, Xiang, Jiang, Nan, Lu, Yutang, Feng, Fei, Awad, Ali, Lucas, Evan, Saleem, Ashraf, Cheng, Ching-Heng, and Lin, Yu-Fan

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

The 3rd Workshop on Maritime Computer Vision (MaCVi) 2025 addresses maritime computer vision for Unmanned Surface Vehicles (USV) and underwater. This report offers a comprehensive overview of the findings from the challenges. We provide both statistical and qualitative analyses, evaluating trends from over 700 submissions. All datasets, evaluation code, and the leaderboard are available to the public at https://macvi.org/workshop/macvi25., Comment: Part of the MaCVi 2025 workshop

Published
2025

4. Research and Implementation of Switching Mechanism for Cold Backup Converter

Author

Li, Zihe, Zhao, Zhenyu, Gao, Dong, Teng, Guofei, Dong, Kai, Feng, Fei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Yang, Qingxin, editor, and Li, Jian, editor

Published
2025
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5. Design of Quasi-Resonant Forward-Flyback DC/DC Converter Based on SiC MOSFET

Author

Li, Zihe, Zhao, Zhenyu, Dong, Kai, Gao, Dong, Feng, Fei, Teng, Guofei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Yang, Qingxin, editor, and Li, Jian, editor

Published
2025
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6. A Research Strategy Based on Chaotic Nonlinear Circuit Working State

Author

Zhao, Zhenyu, Li, Zihe, Dong, Kai, Guo, Chen, Feng, Fei, Teng, Guofei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Yang, Qingxin, editor, and Li, Jian, editor

Published
2025
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7. A Design of Low Voltage Switching Power Supply for Distributed Unit

Author

Zhao, Zhenyu, Li, Zihe, Guo, Chen, Feng, Fei, Dong, Kai, Teng, Guofei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Yang, Qingxin, editor, and Li, Jian, editor

Published
2025
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8. Boosting Large-scale Parallel Training Efficiency with C4: A Communication-Driven Approach

Author

Dong, Jianbo, Luo, Bin, Zhang, Jun, Zhang, Pengcheng, Feng, Fei, Zhu, Yikai, Liu, Ang, Chen, Zian, Shi, Yi, Jiao, Hairong, Lu, Gang, Guan, Yu, Zhai, Ennan, Xiao, Wencong, Zhao, Hanyu, Yuan, Man, Yang, Siran, Li, Xiang, Wang, Jiamang, Men, Rui, Zhang, Jianwei, Zhong, Huang, Cai, Dennis, Xie, Yuan, and Fu, Binzhang

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

The emergence of Large Language Models (LLMs) has necessitated the adoption of parallel training techniques, involving the deployment of thousands of GPUs to train a single model. Unfortunately, we have found that the efficiency of current parallel training is often suboptimal, largely due to the following two main issues. Firstly, hardware failures are inevitable, leading to interruptions in the training tasks. The inability to quickly identify the faulty components results in a substantial waste of GPU resources. Secondly, since GPUs must wait for parameter synchronization to complete before proceeding to the next round of computation, network congestions can greatly increase the waiting time for GPUs. To address these challenges, this paper introduces a communication-driven solution, namely the C4. The key insights of C4 are two folds. First, in parallel training, collective communication exhibits periodic and homogeneous characteristics, so any anomalies are certainly due to some form of hardware malfunction. By leveraging this feature, C4 can rapidly identify the faulty components, swiftly isolate the anomaly, and restart the task, thereby avoiding resource wastage caused by delays in anomaly detection. Second, the predictable communication model of collective communication, involving few large flows, allows C4 to efficiently execute traffic planning, substantially reducing network congestion. C4 has been extensively implemented across our production systems, cutting error-induced overhead by roughly 30% and enhancing runtime performance by about 15% for certain applications with moderate communication costs.

Published
2024

11. Pelvic floor MRI segmentation based on semi-supervised deep learning

Author

Zuo, Jianwei, Feng, Fei, Wang, Zhuhui, Ashton-Miller, James A., Delancey, John O. L., and Luo, Jiajia

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

The semantic segmentation of pelvic organs via MRI has important clinical significance. Recently, deep learning-enabled semantic segmentation has facilitated the three-dimensional geometric reconstruction of pelvic floor organs, providing clinicians with accurate and intuitive diagnostic results. However, the task of labeling pelvic floor MRI segmentation, typically performed by clinicians, is labor-intensive and costly, leading to a scarcity of labels. Insufficient segmentation labels limit the precise segmentation and reconstruction of pelvic floor organs. To address these issues, we propose a semi-supervised framework for pelvic organ segmentation. The implementation of this framework comprises two stages. In the first stage, it performs self-supervised pre-training using image restoration tasks. Subsequently, fine-tuning of the self-supervised model is performed, using labeled data to train the segmentation model. In the second stage, the self-supervised segmentation model is used to generate pseudo labels for unlabeled data. Ultimately, both labeled and unlabeled data are utilized in semi-supervised training. Upon evaluation, our method significantly enhances the performance in the semantic segmentation and geometric reconstruction of pelvic organs, Dice coefficient can increase by 2.65% averagely. Especially for organs that are difficult to segment, such as the uterus, the accuracy of semantic segmentation can be improved by up to 3.70%.

Published
2023

13. Conventional and drug‑eluting bead transarterial chemoembolization in patients with inoperable intrahepatic cholangiocarcinoma: a meta‑analysis

Author

Su-Rong Pan, Xue-Wen Wo, Hong-Fang Zhu, and Feng-Fei Xia

Subjects
conventional, drug-eluting beads, intrahepatic cholangiocarcinoma, transarterial chemoembolization, Medicine
Abstract

Introduction: In patients with inoperable intrahepatic cholangiocarcinoma (ICC), both conventional transarterial chemoembolization (cTACE) and drug-eluting bead TACE (DEB-TACE) can be employed as therapeutic interventions. However, the relative advantages of these strategies remain to be clarified. Aim: This meta-analysis was performed to compare the safety and efficacy of DEB-TACE and cTACE in the treatment of ICC. Materials and methods: A comprehensive search of the Cochrane Library, PubMed, and Wanfang databases was conducted to identify publications that were pertinent to the present meta-analysis. The primary outcome of interest was the overall survival (OS) rate. Secondary outcomes were progression-free survival (PFS), disease control rate (DCR), objective response rate (ORR), and adverse event (AE) rate. Heterogeneity was evaluated using the I2 statistic, while publication bias was assessed with the Egger test. Results: A total of 6 articles involving 283 and 178 patients who received cTACE and DEB-TACE treatment, respectively, were included in this study. DEB-TACE was superior to cTACE in terms of DCR (P = 0.004), PFS (P

Published
2024
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14. Cytosine base editors with increased PAM and deaminase motif flexibility for gene editing in zebrafish

Author

Yu Zhang, Yang Liu, Wei Qin, Shaohui Zheng, Jiawang Xiao, Xinxin Xia, Xuanyao Yuan, Jingjing Zeng, Yu Shi, Yan Zhang, Hui Ma, Gaurav K. Varshney, Ji-Feng Fei, and Yanmei Liu

Subjects
Science
Abstract

Abstract Cytosine base editing is a powerful tool for making precise single nucleotide changes in cells and model organisms like zebrafish, which are valuable for studying human diseases. However, current base editors struggle to edit cytosines in certain DNA contexts, particularly those with GC and CC pairs, limiting their use in modelling disease-related mutations. Here we show the development of zevoCDA1, an optimized cytosine base editor for zebrafish that improves editing efficiency across various DNA contexts and reduces restrictions imposed by the protospacer adjacent motif. We also create zevoCDA1-198, a more precise editor with a narrower editing window of five nucleotides, minimizing off-target effects. Using these advanced tools, we successfully generate zebrafish models of diseases that were previously challenging to create due to sequence limitations. This work enhances the ability to introduce human pathogenic mutations in zebrafish, broadening the scope for genomic research with improved precision and efficiency.

Published
2024
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17. Noise-Resilient Quantum Power Flow

Author

Feng, Fei, Zhou, Yifan, and Zhang, Peng

Subjects
Quantum Physics, Electrical Engineering and Systems Science - Systems and Control
Abstract

Quantum power flow (QPF) provides inspiring directions for tackling power flow's computational burdens leveraging quantum computing. However, existing QPF methods are mainly based on noise-sensitive quantum algorithms, whose practical utilization is significantly hindered by the limited capability of today's noisy-intermediate-scale quantum (NISQ) devices. This paper devises a NISQ-QPF algorithm, which enables power flow calculation on noisy quantum computers. The main contributions include: (1) a variational quantum circuit (VQC)-based AC power flow formulation, which enables QPF using short-depth quantum circuits; (2) noise-resilient QPF solvers based on the variational quantum linear solver (VQLS) and modified fast decoupled power flow; (3) a practical NISQ-QPF framework for implementable and reliable power flow analysis on noisy quantum machines. Promising case studies validate the effectiveness and accuracy of NISQ-QPF on IBM's real, noisy quantum devices., Comment: 6 pages, 6 figures

Published
2022

18. Design of Wind Turbine Speed Control System Based on Permanent Magnet Synchronous Motor

Author

He, Zhifei, Li, Xinyao, Dong, Kai, Feng, Fei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Cai, Chunwei, editor, Qu, Xiaohui, editor, Mai, Ruikun, editor, Zhang, Pengcheng, editor, Chai, Wenping, editor, and Wu, Shuai, editor

Published
2024
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19. Research on Current Measurement Technology Based on Ring Point Hall Sensor

Author

Zhao, Zhenyu, Gao, Xinyu, Li, Zihe, Feng, Fei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Cai, Chunwei, editor, Qu, Xiaohui, editor, Mai, Ruikun, editor, Zhang, Pengcheng, editor, Chai, Wenping, editor, and Wu, Shuai, editor

Published
2024
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20. Design of DC Surge Suppression for Airborne Computer

Author

Wang, Xuejian, Dong, Kai, Wang, Ruoxuan, Feng, Fei, Li, Zihe, Yan, Wen, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Yang, Qingxin, editor, Li, Zewen, editor, and Luo, An, editor

Published
2024
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21. Statistical Analysis of Electrothermal Damage Characteristics of Nanoelectrode Under High Electric Fields

Author

Gao, Xinyu, Feng, Fei, Teng, Guofei, Zhao, Jun, Xiao, Bing, Cheng, Yonghong, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Dong, Xuzhu, editor, and Cai, Li, editor

Published
2024
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28. Neuro-Dynamic State Estimation for Networked Microgrids

Author

Feng, Fei, Zhou, Yifan, and Zhang, Peng

Subjects
Electrical Engineering and Systems Science - Systems and Control, Computer Science - Machine Learning
Abstract

We devise neuro-dynamic state estimation (Neuro-DSE), a learning-based dynamic state estimation (DSE) algorithm for networked microgrids (NMs) under unknown subsystems. Our contributions include: 1) a data-driven Neuro-DSE algorithm for NMs DSE with partially unidentified dynamic models, which incorporates the neural-ordinary-differential-equations (ODE-Net) into Kalman filters; 2) a self-refining Neuro-DSE algorithm (Neuro-DSE+) which enables data-driven DSE under limited and noisy measurements by establishing an automatic filtering, augmenting and correcting framework; 3) a Neuro-KalmanNet-DSE algorithm which further integrates KalmanNet with Neuro-DSE to relieve the model mismatch of both neural- and physics-based dynamic models; and 4) an augmented Neuro-DSE for joint estimation of NMs states and unknown parameters (e.g., inertia). Extensive case studies demonstrate the efficacy of Neuro-DSE and its variants under different noise levels, control modes, power sources, observabilities and model knowledge, respectively., Comment: This paper needs to be withdrawn by the author. In Section II, Part C, there is lack of procedure to achieve parameter estimation using the proposed model. In Section V, Part E, experiment parameter setting is missed. Noise for estimating inertia case needs to be reset for simulation. Additional tests need to be added. These two parts need to be rewritten

Published
2022

32. Salamanders aid research into mechanisms of non‐canonical organ regeneration for clinical applications

Author

Binxu Yin, Xiao Cui, Yanmei Liu, and Ji‐Feng Fei

Subjects
kidney, liver, lung, pancreas, regeneration, salamander, Medicine
Abstract

Abstract Salamanders possess remarkable regenerative capacities for organ regeneration among tetrapod vertebrates. Previous research has primarily focused on studying the regeneration of canonical tissues or organs such as limbs, tail, brain, spinal cord, heart, and lens. The advancements made in these areas have broader implications for understanding regeneration and developing therapeutic approaches for these organs, not only in salamanders but also in other vertebrates. In recent years, there has been an increasing interest in studying the regeneration of non‐canonical organs in salamanders, such as the liver, lungs, kidneys, and pancreas. This diversification of research has opened up new avenues and provided potential solutions to challenging clinical problems. This review aims to summarize the progress made in the field of non‐canonical organ regeneration in salamanders and provides an outlook on future research directions.

Published
2024
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37. Image enhancement in acoustic-resolution photoacoustic microscopy enabled by a novel directional algorithm

Author

Feng, Fei, Liang, Siqi, and Chen, Sung-Liang

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Physics - Medical Physics, Physics - Optics
Abstract

Acoustic-resolution photoacoustic microscopy (AR-PAM) is a promising tool for microvascular imaging. In the focal region, resolution of AR-PAM is determined by the ultrasound transducer and ultimately limited by acoustic diffraction. In the out-of-focus region, resolution deteriorates with increasing distance from the focal plane, which restricts depth of focus (DOF). Besides, a trade-off exists between resolution and DOF. Previously, synthetic aperture focusing technique (SAFT) and/or deconvolution methods have been demonstrated to enhance AR-PAM images. However, they suffer from issues in low resolution, low signal-to-noise ratio (SNR), and/or poor image fidelity. Here, we propose a novel algorithm for AR-PAM to enhance image resolution, SNR, and fidelity. The algorithm consists of a Fourier accumulation SAFT (FA-SAFT) and a directional model-based (D-MB) deconvolution method. Inspired from Fourier denoising technique and directional SAFT, FA-SAFT mainly compensates for the defocusing effect. Besides, D-MB deconvolution enhances the resolution as well as preserves the image fidelity, especially for the objects with line patterns such as microvasculature. Full width at half maximum of 26-31 um over DOF of 1.8 mm and minimum resolvable distance of 46-49 um are experimentally achieved by imaging tungsten wire phantom. Moreover, imaging of leaf skeleton phantom and in vivo imaging of mouse blood vessels also prove that our algorithm is capable of providing high-resolution, high-SNR, and good-fidelity results for complex structures and for in vivo applications., Comment: 34 pages (including 16 pages of supplementary materials)

Published
2021

38. Dynamic fecal microenvironment properties enable predictions and understanding of peripartum blood oxidative status and nonesterified fatty acids in dairy cows

Author

Sen-Lin Zhu, Feng-Fei Gu, Yi-Fan Tang, Xiao-Han Liu, Ming-Hui Jia, Teresa G. Valencak, Jian-Xin Liu, and Hui-Zeng Sun

Subjects
host microbiota interaction, machine learning, peripartum oxidative status diagnosis, predictive warning, series analysis, Dairy processing. Dairy products, SF250.5-275, Dairying, SF221-250
Abstract

ABSTRACT: The transition period in dairy cows is a critical stage and peripartum oxidative status, negative energy balance (NEB), and inflammation are highly prevalent. Fecal microbial metabolism is closely associated with blood oxidative status and nonesterified fatty acids (NEFA) levels. Here, we investigated dynamic changes in total oxidative status markers and NEFA in blood, fecal microbiome, and metabolome of 30 dairy cows during transition (−21, −7, +7, +21 d relative to calving). Then the Bayesian network and 9 machine-learning algorithms were applied to dismantle their relationship. Our results show that the oxidative status indicator (OSI) of −21, −7, +7 d was higher than +21 d. The plasma concentration of NEFA peaked on +7 d. For fecal microenvironment, a decline in bacterial α diversity was observed at postpartum and in bacterial interactions at +7 d. Conversely, microbial metabolites involved in carbohydrate, lipid, and energy metabolism increased on +7 d. A correlation analysis revealed that 11 and 10 microbial metabolites contributed to OSI and NEFA variations, respectively (arc strength >0.5). The support vector machine (SVM) radial model showed the highest average predictive accuracy (100% and 88.9% in the test and external data sets) for OSI using 1 metabolite and 3 microbiota. The SVM radial model also showed the highest average diagnostic accuracy (100% and 91% in the test and external data sets) for NEFA with 2 metabolites and 3 microbiota. Our results reveal a relationship between variation in the fecal microenvironment and indicators of oxidative status, NEB, and inflammation, which provide a theoretical basis for the prevention and precise regulation of peripartum oxidative status and NEB.

Published
2024
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44. Quantum Power Flow

Author

Feng, Fei, Zhou, Yifan, and Zhang, Peng

Subjects
Quantum Physics, Electrical Engineering and Systems Science - Systems and Control
Abstract

This letter is a proof of concept for quantum power flow (QPF) algorithms which underpin various unprecedentedly efficient power system analytics exploiting quantum computing. Our contributions are three-fold: 1) Establish a quantum-state-based fast decoupled model empowered by Hermitian and constant Jacobian matrices; 2) Devise an enhanced Harrow-Hassidim-Lloyd (HHL) algorithm to solve the fast decoupled QPF; 3) Further improve the HHL efficiency by parameterizing quantum phase estimation and reciprocal rotation only at the beginning stage. Promising test results validate the accuracy and efficacy of QPF and demonstrate QPF's enormous potential in the era of quantum computing.

Published
2021

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