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Research Progress and Future Development of Nonferrous Biomedical Materials
Guan Shaokang, Zhu Shijie, ZhengYufeng, Wang Yunbing, Zhang Xingdong
Strategic Study of Chinese Academy of Engineering doi: 10.15302/J-SSCAE-2023.01.008
Nonferrous biomedical materials have developed rapidly in recent years. A variety of new nonferrous biomedical materials and devices that adapt to different in vivo environments and tissues have been developed. It is of both theoretical and practical values to make research plans to improve the clinical application level of new nonferrous biomedical materials and devices. This study clarifies the key performance requirements of the nonferrous biomedical materials, regarding corrosion resistance, wear resistance, fatigue strength and toughness, and biocompatibility. The research progress, development trend, and scientific issues of nonferrous medical materials for permanent implants, biodegradable nonferrous medical materials, porous nonferrous medical materials, and surface modification of nonferrous medical materials are reviewed. After summarizing the future research directions of various nonferrous biomedical materials, this study proposes the following development suggestions: (1) strengthening basic research and the development of key core technologies, (2) establishing a collaborative innovation community that integrates industry, education, research, medicine, and supervision, (3) formulating relevant standards and evaluation norms, and (4) developing a highly skilled professional training system, thereby providing a guiding reference for developing the new material industry and relevant cutting-edge technologies.
Keywords: nonferrous biomedical materials nonferrous materials for permanent implants biodegradable nonferrous medical materials porous nonferrous medical materials surface modification of nonferrous medical materials
Sodium Nitrate Passivation as a Novel Insulation Technology for Soft Magnetic Composites Article
Mi Yan, Qiming Chen, Dong Liu, Chen Wu, Jian Wang
Engineering 2023, Volume 20, Issue 1, Pages 134-142 doi: 10.1016/j.eng.2022.01.016
Sodium nitrate passivation has been developed as a new insulation technology for the production of FeSiAl soft magnetic composites (SMCs). In this work, the evolution of coating layers grown at different pH values is investigated involving analyses on their composition and microstructure. An insulation coating obtained using an acidic NaNO3 solution is found to contain Fe2O3, SiO2, Al2O3, and AlO(OH). The Fe2O3 transforms into Fe3O4 with weakened oxidizability of the NO3– at an elevated pH, whereas an alkaline NaNO3 solution leads to the production of Al2O3, AlO(OH), and SiO2. Such growth is explained from both thermodynamic and kinetic perspectives and is correlated to the soft magnetic properties of the FeSiAl SMCs. Under tuned passivation conditions, optimal performance with an effective permeability of 97.2 and a core loss of 296.4 mW∙cm−3 is achieved at 50 kHz and 100 mT.
Keywords: Soft magnetic composites Surface passivation Insulation technology Growth mechanism Magnetic performance
A Thermo-Tunable Metamaterial as an Actively Controlled Broadband Absorber Article
Xiao-Chang Xing, Yang Cao, Xiao-Yong Tian, Lingling Wu
Engineering 2023, Volume 20, Issue 1, Pages 143-152 doi: 10.1016/j.eng.2022.04.028
Metamaterials have attracted increasing attention in recent years due to their powerful abilities in manipulating electromagnetic (EM) waves. However, most previously reported metamaterials are unable to actively control full-band EM waves. In this paper, we propose a thermo-tunable broadband metamaterial (T-TBM) using paraffin-based composites (PD-Cs) with different phase transition temperatures. Active control of the T-TBM reflection loss peaks from low to high frequency is realized by manipulating the solid–liquid state of the PD-Cs at different phase transition temperatures. The absorption peak bandwidth (where the reflection loss value is less than −30 dB) can be changed, while the broad bandwidth absorption (where the reflection loss value is less than −10 dB) is satisfied by adjusting the temperature of the T-TBM. It is shown that the stagnation of the phase transition temperature of the PD-Cs in the T-TBM provides a time window for actively controlling the EM wave absorption response under different thermal conditions. The device has a broad application prospect in the fields of EM absorption, intelligent metamaterials, multifunctional structural devices, and more.
Keywords: Metamaterials Active control Thermally tunable Broadband absorption
Development Strategy for Recovery Resilience of Urban Underground Space
Lu Dechun, Liao Yingze, Zeng Jiao, Jiang Yuan, Wang Guosheng, Qin Boyu, Du Xiuli
Strategic Study of Chinese Academy of Engineering doi: 10.15302/J-SSCAE-2023.01.013
The concept of disaster prevention and mitigation is vital for the safe development of urban underground space. Considering the coexistence of natural and engineering safety risks, the concept needs to be improved for further development of the urban underground space, and it is imperative to follow a disaster-adaptation-oriented concept that emphasizes post-disaster recovery resilience of the urban underground space. This study analyzes the implications and influencing factors of recovery resilience and summarizes the research on recovery resilience from the engineering and non-engineering perspectives. Moreover, the development status of recovery resilience research is analyzed from the aspects of structural system, evaluation method, management mechanism, space planning, and emergency plan. On this basis, a strategy that consists of three stages and an evaluation system is proposed; it categorizes post-disaster recovery into three stages—emergency rescue, recovery, and plan adaptation—and proposes recovery goals for each stage, providing a basis for the establishment of a recovery resilience evaluation system for the urban underground space.Furthermore, we suggest that the management regulations and emergency plans of the urban underground space should be optimized, the resilience planning improved, and intelligent management promoted, thereby realizing the orderliness and high efficiency of urban underground space recovery.
Keywords: urban underground space disaster prevention and mitigation disaster adaptation recovery resilience
Technology trends in large-scale high-efficiency network computing Review
Jinshu SU, Baokang ZHAO, Yi DAI, Jijun CAO, Ziling WEI, Na ZHAO, Congxi SONG, Yujing LIU, Yusheng XIA
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12, Pages 1733-1746 doi: 10.1631/FITEE.2200217
Keywords: Supercomputing Cloud computing Network technology Development trends
FinBrain 2.0: when finance meets trustworthy AI Review
Jun ZHOU, Chaochao CHEN, Longfei LI, Zhiqiang ZHANG, Xiaolin ZHENG
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12, Pages 1747-1764 doi: 10.1631/FITEE.2200039
Keywords: Artificial intelligence in finance Trustworthy artificial intelligence Risk management Fraud detection Wealth management
Parallel cognition: hybrid intelligence for human-machine interaction and management Research Article
Peijun YE, Xiao WANG, Wenbo ZHENG, Qinglai WEI, Fei-Yue WANG
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12, Pages 1765-1779 doi: 10.1631/FITEE.2100335
Keywords: Cognitive learning Artificial intelligence Behavioral prescription
Dual collaboration for decentralized multi-source domain adaptation Research Article
Yikang WEI, Yahong HAN
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12, Pages 1780-1794 doi: 10.1631/FITEE.2200284
Keywords: Multi-source domain adaptation Data decentralization Domain shift Negative transfer
Image-based traffic signal control via world models Research Article
Xingyuan DAI, Chen ZHAO, Xiao WANG, Yisheng LV, Yilun LIN, Fei-Yue WANG
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12, Pages 1795-1813 doi: 10.1631/FITEE.2200323
Keywords: Traffic signal control Traffic prediction Traffic world model Reinforcement learning
MSSSA: a multi-strategy enhanced sparrow search algorithm for global optimization Research Article
Kai MENG, Chen CHEN, Bin XIN
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12, Pages 1828-1847 doi: 10.1631/FITEE.2200237
Keywords: Swarm intelligence Sparrow search algorithm Adaptive parameter control strategy Hybrid disturbance mechanism Optimization problems
Interpreting the vulnerability of power systems in cascading failures using multi-graph convolutional networks Research Article
Supaporn LONAPALAWONG, Changsheng CHEN, Can WANG, Wei CHEN
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12, Pages 1848-1861 doi: 10.1631/FITEE.2200035
Keywords: Power systems Vulnerability Cascading failures Multi-graph convolutional networks Weighted line graph
Observer-based control for fractional-order singular systems with order Research Article
Bingxin LI, Xiangfei ZHAO, Xuefeng ZHANG, Xin ZHAO
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12, Pages 1862-1870 doi: 10.1631/FITEE.2200294
Keywords: Observer-based control Singular systems Fractional order Input delay Linear matrix inequality
Generalized labeled multi-Bernoulli filter with signal features of unknown emitters Research Article
Qiang GUO, Long TENG, Xinliang WU, Wenming SONG, Dayu HUANG
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12, Pages 1871-1880 doi: 10.1631/FITEE.2200286
A novel algorithm that combines the (GLMB) filter with signal features of the unknown emitter is proposed in this paper. In complex electromagnetic environments, emitter features (EFs) are often unknown and time-varying. Aiming at the unknown feature problem, we propose a method for identifying EFs based on of data fields. Because EFs are time-varying and the probability distribution is unknown, an improved algorithm is proposed to calculate the correlation coefficients between the target and measurements, to approximate the EF likelihood function. On this basis, the EF likelihood function is integrated into the recursive GLMB filter process to obtain the new prediction and update equations. Simulation results show that the proposed method can improve the tracking performance of multiple targets, especially in heavy clutter environments.
Keywords: Multi-target tracking Generalized labeled multi-Bernoulli Signal features of emitter Fuzzy C-means Dynamic clustering
Ensemble enhanced active learning mixture discriminant analysis model and its application for semi-supervised fault classification Research Article
Weijun WANG, Yun WANG, Jun WANG, Xinyun FANG, Yuchen HE
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12, Pages 1814-1827 doi: 10.1631/FITEE.2200053
Keywords: Semi-supervised Active learning Ensemble learning Mixture discriminant analysis Fault classification
Frontiers of Agricultural Science and Engineering doi: 10.15302/J-FASE-2022472
● Investigate the actual situation of food waste at university canteens in Beijing, China.
Keywords: university students food waste behavior theory of planned behavior university canteen
Title Author Date Type Operation
Research Progress and Future Development of Nonferrous Biomedical Materials
Guan Shaokang, Zhu Shijie, ZhengYufeng, Wang Yunbing, Zhang Xingdong
Journal Article
Sodium Nitrate Passivation as a Novel Insulation Technology for Soft Magnetic Composites
Mi Yan, Qiming Chen, Dong Liu, Chen Wu, Jian Wang
Journal Article
A Thermo-Tunable Metamaterial as an Actively Controlled Broadband Absorber
Xiao-Chang Xing, Yang Cao, Xiao-Yong Tian, Lingling Wu
Journal Article
Development Strategy for Recovery Resilience of Urban Underground Space
Lu Dechun, Liao Yingze, Zeng Jiao, Jiang Yuan, Wang Guosheng, Qin Boyu, Du Xiuli
Journal Article
Technology trends in large-scale high-efficiency network computing
Jinshu SU, Baokang ZHAO, Yi DAI, Jijun CAO, Ziling WEI, Na ZHAO, Congxi SONG, Yujing LIU, Yusheng XIA
Journal Article
FinBrain 2.0: when finance meets trustworthy AI
Jun ZHOU, Chaochao CHEN, Longfei LI, Zhiqiang ZHANG, Xiaolin ZHENG
Journal Article
Parallel cognition: hybrid intelligence for human-machine interaction and management
Peijun YE, Xiao WANG, Wenbo ZHENG, Qinglai WEI, Fei-Yue WANG
Journal Article
Dual collaboration for decentralized multi-source domain adaptation
Yikang WEI, Yahong HAN
Journal Article
Image-based traffic signal control via world models
Xingyuan DAI, Chen ZHAO, Xiao WANG, Yisheng LV, Yilun LIN, Fei-Yue WANG
Journal Article
MSSSA: a multi-strategy enhanced sparrow search algorithm for global optimization
Kai MENG, Chen CHEN, Bin XIN
Journal Article
Interpreting the vulnerability of power systems in cascading failures using multi-graph convolutional networks
Supaporn LONAPALAWONG, Changsheng CHEN, Can WANG, Wei CHEN
Journal Article
Observer-based control for fractional-order singular systems with order
Bingxin LI, Xiangfei ZHAO, Xuefeng ZHANG, Xin ZHAO
Journal Article
Generalized labeled multi-Bernoulli filter with signal features of unknown emitters
Qiang GUO, Long TENG, Xinliang WU, Wenming SONG, Dayu HUANG
Journal Article
Ensemble enhanced active learning mixture discriminant analysis model and its application for semi-supervised fault classification
Weijun WANG, Yun WANG, Jun WANG, Xinyun FANG, Yuchen HE
Journal Article