Pub Date : 2025-12-19DOI: 10.1109/MEI.2026.11306288
Tony Lujia Chen
This issue includes three articles, the first titled “New Categories for Phase-Resolved Partial Discharge Pattern Classification,” by Contin, Piccolo, and Cavallini. It presents a refined framework for analyzing phase-resolved partial discharge (PRPD) patterns in insulation diagnostics. The study questions the traditional one-to-one link between PRPD shapes and defect types, proposing three new categories: voltage-dependent, multiple, and ambiguous patterns. This is to better represent the changing nature of discharge phenomena. By testing insulation systems rated between 4 and 18 kV, including porous tape insulation and four-layer mica tapes, the authors show how PRPD patterns develop under different voltage levels, aging conditions, and stress factors. Examples include distributed micro-void discharges that change from “rabbit-ear” to rounded shapes, symmetric in polarity and phase. The article emphasizes the limitations of relying only on pattern shape for diagnosis and recommends additional localization techniques such as antenna probes and ultrasound detectors. This work is especially valuable for those seeking to improve the reliability of insulation evaluation and develop more advanced pattern-recognition systems for rotating electrical machines.
{"title":"From the Editor","authors":"Tony Lujia Chen","doi":"10.1109/MEI.2026.11306288","DOIUrl":"https://doi.org/10.1109/MEI.2026.11306288","url":null,"abstract":"This issue includes three articles, the first titled “New Categories for Phase-Resolved Partial Discharge Pattern Classification,” by Contin, Piccolo, and Cavallini. It presents a refined framework for analyzing phase-resolved partial discharge (PRPD) patterns in insulation diagnostics. The study questions the traditional one-to-one link between PRPD shapes and defect types, proposing three new categories: voltage-dependent, multiple, and ambiguous patterns. This is to better represent the changing nature of discharge phenomena. By testing insulation systems rated between 4 and 18 kV, including porous tape insulation and four-layer mica tapes, the authors show how PRPD patterns develop under different voltage levels, aging conditions, and stress factors. Examples include distributed micro-void discharges that change from “rabbit-ear” to rounded shapes, symmetric in polarity and phase. The article emphasizes the limitations of relying only on pattern shape for diagnosis and recommends additional localization techniques such as antenna probes and ultrasound detectors. This work is especially valuable for those seeking to improve the reliability of insulation evaluation and develop more advanced pattern-recognition systems for rotating electrical machines.","PeriodicalId":444,"journal":{"name":"IEEE Electrical Insulation Magazine","volume":"42 1","pages":"4-5"},"PeriodicalIF":1.3,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11306288","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To address the synergistic challenges of energy efficiency and security in wireless sensor networks (WSNs) under complex attack environments, this article proposes a collaborative energy efficiency and security enhancement (CEESE) routing algorithm. During the clustering phase, an enhanced particle swarm optimization (PSO) method is introduced, which integrates the golden sine algorithm (Gold- SA) and Levy flight (LF) to balance the global exploration and local exploitation through sine perturbations and random long-hop mechanisms. A multiobjective fitness function is constructed, considering node residual energy, comprehensive trust values, and communication distance, thereby achieving the energy-balanced cluster head (CH) election. In the routing phase, a hybrid trust model combining direct and indirect trust is designed, which collaborates with deep Q (DQ)-learning to enable real-time path state awareness and dynamic maintenance. Simulation results demonstrate that CEESE achieves the superior performance across varying network scales and attack scenarios. Specifically, in a 100-node, 100 × 100 m monitoring area, the first node death round of CEESE improved by 37.8%, 36.9%, 14.7%, 10.4%, and 7.1% compared with TAOSC-MHR, MRCH, EEHCHR, DST-WOA, and CTRF algorithms, respectively. Its advantages persist in a large-scale network with 500 nodes within a 200 × 200 m area. Regarding security, under a black-hole attack involving 50% malicious nodes, CEESE achieves a packet delivery rate (PDR) 19.2%–59.3% higher, a malicious node detection rate (DR) 5.7%–28.1% higher, and an average delay 14.3%–46.5% lower than the compared algorithms. This study provides an efficient routing solution for energy-constrained WSN applications with stringent security requirements.
{"title":"Collaborative Energy Efficiency and Security Enhancement Routing Algorithm Based on Enhanced PSO and DQ-Learning for WSNs","authors":"Liubao Zhang;Cuiran Li;Jiahui Xu;Li Liu;Jianli Xie","doi":"10.1109/JSEN.2025.3643463","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3643463","url":null,"abstract":"To address the synergistic challenges of energy efficiency and security in wireless sensor networks (WSNs) under complex attack environments, this article proposes a collaborative energy efficiency and security enhancement (CEESE) routing algorithm. During the clustering phase, an enhanced particle swarm optimization (PSO) method is introduced, which integrates the golden sine algorithm (Gold- SA) and Levy flight (LF) to balance the global exploration and local exploitation through sine perturbations and random long-hop mechanisms. A multiobjective fitness function is constructed, considering node residual energy, comprehensive trust values, and communication distance, thereby achieving the energy-balanced cluster head (CH) election. In the routing phase, a hybrid trust model combining direct and indirect trust is designed, which collaborates with deep Q (DQ)-learning to enable real-time path state awareness and dynamic maintenance. Simulation results demonstrate that CEESE achieves the superior performance across varying network scales and attack scenarios. Specifically, in a 100-node, 100 × 100 m monitoring area, the first node death round of CEESE improved by 37.8%, 36.9%, 14.7%, 10.4%, and 7.1% compared with TAOSC-MHR, MRCH, EEHCHR, DST-WOA, and CTRF algorithms, respectively. Its advantages persist in a large-scale network with 500 nodes within a 200 × 200 m area. Regarding security, under a black-hole attack involving 50% malicious nodes, CEESE achieves a packet delivery rate (PDR) 19.2%–59.3% higher, a malicious node detection rate (DR) 5.7%–28.1% higher, and an average delay 14.3%–46.5% lower than the compared algorithms. This study provides an efficient routing solution for energy-constrained WSN applications with stringent security requirements.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 3","pages":"5165-5180"},"PeriodicalIF":4.3,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-19DOI: 10.1109/MEI.2026.11306287
The Conference on Electrical Insulation and Dielectric Phenomena (CEIDP) 2025, held from September 14 to 17 at the University of Manchester (UK), marked a landmark moment in its history. With 342 delegates from 33 countries, CEIDP 2025 marked its centennial edition by fostering technical excellence, shared expertise, and a strong sense of community.
{"title":"Bulletin Board: IEEE CEIDP 2025—A Celebration of Dielectric Science in Manchester","authors":"","doi":"10.1109/MEI.2026.11306287","DOIUrl":"https://doi.org/10.1109/MEI.2026.11306287","url":null,"abstract":"The Conference on Electrical Insulation and Dielectric Phenomena (CEIDP) 2025, held from September 14 to 17 at the University of Manchester (UK), marked a landmark moment in its history. With 342 delegates from 33 countries, CEIDP 2025 marked its centennial edition by fostering technical excellence, shared expertise, and a strong sense of community.","PeriodicalId":444,"journal":{"name":"IEEE Electrical Insulation Magazine","volume":"42 1","pages":"55-57"},"PeriodicalIF":1.3,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11306287","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-19DOI: 10.1109/MEI.2026.11306293
Mattewos Tefferi
When I was appointed as chair of the DEIS Young Professionals (YP) Committee in early 2023, I outlined several priorities in my editorial in IEEE Electrical Insulation Magazine [1]. Looking back now, as my term comes to an end, I am proud of what the YP Committee has accomplished over the past three years.
{"title":"Young Professionals: Retiring from the Young Professionals Committee","authors":"Mattewos Tefferi","doi":"10.1109/MEI.2026.11306293","DOIUrl":"https://doi.org/10.1109/MEI.2026.11306293","url":null,"abstract":"When I was appointed as chair of the DEIS Young Professionals (YP) Committee in early 2023, I outlined several priorities in my editorial in IEEE Electrical Insulation Magazine [1]. Looking back now, as my term comes to an end, I am proud of what the YP Committee has accomplished over the past three years.","PeriodicalId":444,"journal":{"name":"IEEE Electrical Insulation Magazine","volume":"42 1","pages":"45-47"},"PeriodicalIF":1.3,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11306293","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-19DOI: 10.1109/MEI.2026.11306291
Rui Wang;Haoyu Gao
My name is Rui Wang, and I am happy to share the progress I have made as a DEIS Graduate Student Fellow. This fellowship has provided invaluable support to improve my PhD research. I am deeply grateful to the DEIS Education Committee for the opportunity and to my advisor for continuous guidance.
{"title":"Young Professionals: DEIS Graduate Student Fellowship","authors":"Rui Wang;Haoyu Gao","doi":"10.1109/MEI.2026.11306291","DOIUrl":"https://doi.org/10.1109/MEI.2026.11306291","url":null,"abstract":"My name is Rui Wang, and I am happy to share the progress I have made as a DEIS Graduate Student Fellow. This fellowship has provided invaluable support to improve my PhD research. I am deeply grateful to the DEIS Education Committee for the opportunity and to my advisor for continuous guidance.","PeriodicalId":444,"journal":{"name":"IEEE Electrical Insulation Magazine","volume":"42 1","pages":"48-49"},"PeriodicalIF":1.3,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11306291","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-19DOI: 10.1109/MEI.2026.11306328
Bálint Németh;Richárd Cselkó
This article offers readers a glimpse into the daily operations of the High Voltage Laboratory at the Budapest University of Technology and Economics. This article, part of the “A Day in the Life of a ____ Laboratory” series, highlights the laboratory's unique role in live-line maintenance, encompassing the education of future professionals and development of innovative technologies.
{"title":"A Day in the Life of a High-Voltage Laboratory in Budapest","authors":"Bálint Németh;Richárd Cselkó","doi":"10.1109/MEI.2026.11306328","DOIUrl":"https://doi.org/10.1109/MEI.2026.11306328","url":null,"abstract":"This article offers readers a glimpse into the daily operations of the High Voltage Laboratory at the Budapest University of Technology and Economics. This article, part of the “A Day in the Life of a ____ Laboratory” series, highlights the laboratory's unique role in live-line maintenance, encompassing the education of future professionals and development of innovative technologies.","PeriodicalId":444,"journal":{"name":"IEEE Electrical Insulation Magazine","volume":"42 1","pages":"30-36"},"PeriodicalIF":1.3,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11306328","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-18DOI: 10.1109/TPS.2025.3638710
Rajesh Yadav;V. S. Pandey;Manoranjan Kumar;Anand Kumar Singh;Antony Judice
This article investigates the role of plasma support electromagnetic (EM) interactions and surface plasmon polariton (SPP) in enhancing the performance of terahertz (THz) wireless body area networks (WBANs) for consumer health applications. A bending log-periodic graphene-based antenna is proposed, comprising multiple log-periodic graphene elements excited through a silver nanostrip feedline to support plasmonic wave confinement. The antenna demonstrates dual-band operation at 5.95 and 6.31 THz, where the excitation of SPP modes leads to strong field localization and reduced propagation losses. The antenna exhibits impressive return loss values of −47.71 and −24.27 dB at 5.95 and 6.31 THz, respectively, ensuring minimal signal reflection. The front-to-back ratio (FBR) is 11.12, with an efficiency of 81% and 50.7% the antenna achieves a directivity of 10.14 dBi. It is ensuring reliable performance in plasma-mediated THz propagation. Bending analysis validates structural robustness under realistic WBAN conditions, while a three-layered human body model is employed to assess the specific absorption rate (SAR), confirming low exposure levels suitable for long-term wearable and implantable applications. Further, computer simulation technology (CST), HSS, and ADS results have been verified and validated using mathematical modeling. The integration of plasma-driven SPP mechanisms with graphene antenna technology highlights a pathway toward high-performance THz WBANs, enabling safe and continuous health monitoring through smart textiles and advanced biomedical platforms.
{"title":"Plasma-Coupled Graphene Antennas With Surface Plasmon Polariton Modes for Performance Optimization in Terahertz Wireless Body Area Networks","authors":"Rajesh Yadav;V. S. Pandey;Manoranjan Kumar;Anand Kumar Singh;Antony Judice","doi":"10.1109/TPS.2025.3638710","DOIUrl":"https://doi.org/10.1109/TPS.2025.3638710","url":null,"abstract":"This article investigates the role of plasma support electromagnetic (EM) interactions and surface plasmon polariton (SPP) in enhancing the performance of terahertz (THz) wireless body area networks (WBANs) for consumer health applications. A bending log-periodic graphene-based antenna is proposed, comprising multiple log-periodic graphene elements excited through a silver nanostrip feedline to support plasmonic wave confinement. The antenna demonstrates dual-band operation at 5.95 and 6.31 THz, where the excitation of SPP modes leads to strong field localization and reduced propagation losses. The antenna exhibits impressive return loss values of −47.71 and −24.27 dB at 5.95 and 6.31 THz, respectively, ensuring minimal signal reflection. The front-to-back ratio (FBR) is 11.12, with an efficiency of 81% and 50.7% the antenna achieves a directivity of 10.14 dBi. It is ensuring reliable performance in plasma-mediated THz propagation. Bending analysis validates structural robustness under realistic WBAN conditions, while a three-layered human body model is employed to assess the specific absorption rate (SAR), confirming low exposure levels suitable for long-term wearable and implantable applications. Further, computer simulation technology (CST), HSS, and ADS results have been verified and validated using mathematical modeling. The integration of plasma-driven SPP mechanisms with graphene antenna technology highlights a pathway toward high-performance THz WBANs, enabling safe and continuous health monitoring through smart textiles and advanced biomedical platforms.","PeriodicalId":450,"journal":{"name":"IEEE Transactions on Plasma Science","volume":"54 1","pages":"327-344"},"PeriodicalIF":1.5,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article presents a digital demodulation technique for use in galvanic-coupling intrabody communication (GC IBC) with binary phase shift keying (BPSK)-modulated signals at low frequencies (below megahertz). The technique relies on a direct oversampled acquisition of the BPSK-modulated signal with an analog-to-digital converter (ADC) associated with an original digital processing algorithm to extract the demodulated data from the acquired samples. The originality of the solution resides in the digital processing algorithm, which combines several mechanisms to fully exploit the redundancy present in the collected samples in order to provide a high degree of robustness, while maintaining a low level of complexity compatible with efficient implementation in a microcontroller. Simulation and measurement results are presented, confirming the robustness of the proposed solution. In particular, hardware measurements carried out under controlled conditions demonstrate very good performance, with a bit error rate (BER) below 3 × 10−5 for a signal with a signal-to-noise ratio (SNR) of −5 dB. The proposed solution is also validated under real conditions with a galvanic-coupling (GC) communication realized through the back muscle of a fish, resulting in a BER < 2.5 × 10−6.
{"title":"Implementation and Performance Analysis of a Digital BPSK Demodulation Technique for Galvanic-Coupling Communication","authors":"Stephane Pitou;Vincent Kerzerho;Serge Bernard;Tristan Rouyer;Fabien Soulier;David McKenzie;Florence Azais","doi":"10.1109/JSEN.2025.3641296","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3641296","url":null,"abstract":"This article presents a digital demodulation technique for use in galvanic-coupling intrabody communication (GC IBC) with binary phase shift keying (BPSK)-modulated signals at low frequencies (below megahertz). The technique relies on a direct oversampled acquisition of the BPSK-modulated signal with an analog-to-digital converter (ADC) associated with an original digital processing algorithm to extract the demodulated data from the acquired samples. The originality of the solution resides in the digital processing algorithm, which combines several mechanisms to fully exploit the redundancy present in the collected samples in order to provide a high degree of robustness, while maintaining a low level of complexity compatible with efficient implementation in a microcontroller. Simulation and measurement results are presented, confirming the robustness of the proposed solution. In particular, hardware measurements carried out under controlled conditions demonstrate very good performance, with a bit error rate (BER) below 3 × 10−5 for a signal with a signal-to-noise ratio (SNR) of −5 dB. The proposed solution is also validated under real conditions with a galvanic-coupling (GC) communication realized through the back muscle of a fish, resulting in a BER < 2.5 × 10−6.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 3","pages":"5141-5150"},"PeriodicalIF":4.3,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-17DOI: 10.1109/JSEN.2025.3642263
Xinghua Liu;Jiaxuan Du;Xiang Gao;Shiping Wen;Badong Chen;Peng Wang
We conducted an in-depth investigation into the impact of conditional variational autoencoders (CVAEs) and Bayesian neural networks (BNNs) on high dynamic range (HDR) image reconstruction. A parallel multiattention module (PMAM) is introduced in the improved YOLOv10 framework to enhance computational efficiency and detection performance. To reconstruct HDR images, we enhance the asynchronous Kalman filter (AKF) algorithm to improve image detail quality. We introduce BNN and CVAE into the AKF algorithm to reduce noise effects and improve the logarithmic intensity of the reconstructed image. The BNN estimates noise covariance, thereby reducing its impact during the reconstruction process. Simultaneously, the CVAE leverages polarity as a conditional input, and uses spatial and temporal information through a CVAE to generate more accurate logarithmic image intensities. In the object detection stage, we integrate a parallel module combining the self-attention mechanism and the ECA module to improve training efficiency without increasing the number of parameters. This PMAM module, based on improved YOLOv10, strengthens the model’s ability to capture global and channel-specific features. Finally, the proposed method’s accuracy and robustness are validated through extensive simulations and comparative experiments. Comprehensive experiments on public datasets show that our model achieves 81.32% mAP@0.5 and 59.67% mAP@[0.5:0.95], demonstrating significant improvements in detection accuracy and image reconstruction quality.
{"title":"Event Camera Object Detection Using Bayesian Neural Network-Conditional Variational Autoencoders and Improved YOLOv10","authors":"Xinghua Liu;Jiaxuan Du;Xiang Gao;Shiping Wen;Badong Chen;Peng Wang","doi":"10.1109/JSEN.2025.3642263","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3642263","url":null,"abstract":"We conducted an in-depth investigation into the impact of conditional variational autoencoders (CVAEs) and Bayesian neural networks (BNNs) on high dynamic range (HDR) image reconstruction. A parallel multiattention module (PMAM) is introduced in the improved YOLOv10 framework to enhance computational efficiency and detection performance. To reconstruct HDR images, we enhance the asynchronous Kalman filter (AKF) algorithm to improve image detail quality. We introduce BNN and CVAE into the AKF algorithm to reduce noise effects and improve the logarithmic intensity of the reconstructed image. The BNN estimates noise covariance, thereby reducing its impact during the reconstruction process. Simultaneously, the CVAE leverages polarity as a conditional input, and uses spatial and temporal information through a CVAE to generate more accurate logarithmic image intensities. In the object detection stage, we integrate a parallel module combining the self-attention mechanism and the ECA module to improve training efficiency without increasing the number of parameters. This PMAM module, based on improved YOLOv10, strengthens the model’s ability to capture global and channel-specific features. Finally, the proposed method’s accuracy and robustness are validated through extensive simulations and comparative experiments. Comprehensive experiments on public datasets show that our model achieves 81.32% mAP@0.5 and 59.67% mAP@[0.5:0.95], demonstrating significant improvements in detection accuracy and image reconstruction quality.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 3","pages":"5151-5164"},"PeriodicalIF":4.3,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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